Distant metastasis (DM) and neoadjuvant treatment response prediction remain critical challenges in the management of locally advanced rectal cancer (LARC). The aim of this study was to investigate the clinical relevance of viable circulating tumor cells (CTCs) for DM or response in patients with LARC in a neoadjuvant setting.The detection of viable CTCs at different stages of treatment was planned for consecutive patients from a prospective trial. The Kaplan–Meier method, Cox proportional hazards model, and logistic regression model were utilized to analyze factors associated with DM or pathological complete response (pCR) and clinical complete response (cCR).p = 0.018, log‐rank test). When all the important variables were entered into the Cox model, the CTC risk group remained the only significant independent factor for DM (hazard ratio (HR), 2.74; 95% CI, 1.17–6.45, p = 0.021). The pCR and continuous cCR rates were higher in patients with a decreased number of CTCs of more than one after radiotherapy .Between December 2016 and July 2018, peripheral blood samples from 83 patients were collected before any treatment . CTCs were present in 76 of 83 patients (91.6%) at baseline, and more than three CTCs detected in the blood sample was considered high risk. Only the CTC risk group was significantly associated with 3‐year metastasis‐free survival (MFS)  vs. 78.3% , The dynamic detection of viable CTCs may strengthen pretreatment risk assessment and postradiotherapy decision making for LARC. This observation requires further validation in a prospective study. The core of the approach we used in this study is the positive labeling of TERT‐positive cells. In our previous study, high sensitivity and accuracy for CTC detection were achieved with tumor‐selective replication herpes simplex virus‐based technology rather than CellSearch,22.1Patients from a single principal center in a multicenter, open‐label, prospective phase II/III randomized trial who agreed to attend a translational study session were included in this analysis. In brief, the patients were randomized to receive short‐course preoperative radiotherapy  with neoadjuvant chemotherapy (NCT) (4 cycles of the XELOX regimen)  or preoperative long‐course chemoradiotherapy (2 Gy × 25 with capecitabine) (control group) for middle‐lower LARC. The inclusion criteria, treatment, and follow‐up details were described in our previous report.The exploratory study with respect to CTCs was prospectively designed with the hypothesis that if the hazard ratio (HR) for metastasis‐free survival (MFS) of the high‐risk patients defined by CTC counts was more than 2.5 compared to that of the low‐risk patients, a two‐sided log‐rank test with an overall sample size of 78 subjects (39 each in the high‐risk and low‐risk groups) would achieve 80.1% power at a 0.050 significance level. The detection of CTCs at different stages of treatment was also planned . A total of 599 patients have been examined to date, and among the 289 patients treated at the principal center, 83 willing to participate in this translational part of the study were consecutively included between December 2016 and June 2018   at room temperature for 5 min. After centrifugation, the supernatant was discarded, and the cell pellets were washed 2× with PBS. The oHSV1‐hTERT‐GFP virus used in this study, in which the endogenous ICP4 promoter is replaced with the hTERT promoter, has been described in our previous work.2 for another 24 h. Thereafter, the cells were collected, and 200 μL of PE‐Cy5 mouse anti‐human CD45  was added, followed by incubation in the dark at room temperature for 30 min. After one wash with PBS, the cells were resuspended in 1 mL of PBS. The detection of CD45‐/GFP+ cells from blood samples was performed via flow cytometry (Merck Millipore or BD). CD45‐/GFP+ cells were recorded as positive results.Peripheral blood samples (4 mL) were prepared in heparinized tubes and incubated with lysis buffer  and APC‐EpCAM antibody . Then, CTCs were detected by the ImageStreamX® Mark II system (Amnis). CD45‐/GFP+/EpCAM+ cells in blood samples were considered CTC‐positive cells.2.4p < 0.05 in two‐tailed tests. All authors had access to the study data and reviewed and approved the final manuscript.IBM SPSS Statistics 17.0 software (SPSS Inc.) was used to manage the data. OS, MFS, and locoregional recurrence (LR) were defined as previously reported.33.1Between December 2016 and July 2018, peripheral blood samples from 83 patients were collected before any treatment, with a median follow‐up time of 49.3 months as of December 2021 . There were 55 male (66.3%) and 28 female (33.7%) patients, with a median age of 55 years . The numbers of patients with tumors staged IIA, IIC, IIIB and IIIC were 13 (15.7%), 1 (1.2%), 56 (67.5%), and 13 (15.7%), respectively. In total, 57 (68.7%) and 43 (51.8%) patients had tumors with a positive mesorectal fascia status and a positive extramural vascular invasion (EMVI) status, respectively. CTCs were present at baseline in 76 of 83 patients (91.6%), ranging from 1 to 18 cells (median = 3 cells).To verify the CTCs, FlowSight imaging was performed. As shown in Figure 3.2n = 7), refusal (n = 6), and DM before surgery (n = 9)  received SCPRT plus chemotherapy and 41 (48.2%) received conventional preoperative concurrent chemoradiotherapy. Finally, 61 patients underwent surgery; the reasons the 22 patients did not undergo surgery were cCR (3.3p = 0.015) for patients who did not undergo surgery, and the 3‐year PFS rates were 63.4%  and 45.5%  (p = 0.071), respectively.The 3‐year OS rates were 86.9%  for patients who underwent surgery and 68.2%   and a specificity of 60.7%  Figure . The sigp = 0.659, Figure p = 0.675, Figure Ten and nine deaths were observed in the high‐risk and low‐risk groups, respectively, while four and six patients presented with LR or progression, respectively. No significant differences in OS . Upon analyzing various relevant clinical factors .Although no other relevant factors were found through the univariate analysis, we incorporated some previously reported significant factors that may affect DM into the multivariate Cox model analysis. When the age group (above 60 years vs. below 60 years), sex, tumor location (middle vs. lower segment), MRI lymph node stage (N2 vs. N0‐1), mesorectal fascia (MRF), EMVI status, neoadjuvant treatment modality, and CTC risk group were included, the CTC risk group remained the only independent prognostic factor for DM, with a nearly threefold higher risk of DM in the high‐risk group than in the low‐risk group  .3.5.1p = 0.096, Mann–Whitney test, Figure p = 0.041), while the common important clinical factors were balanced between these two groups, and no significant difference was found in survival outcomes (Table p < 0.1), ΔCTCs <−1 remained significantly associated with pCR and cCR  and a specificity of 71.4%   Table , PFS (Fi5) Table , MFS (Fi5) Table , and LRF5) Table , or in t Table , 4With the application of TME and preoperative CRT, the local control of LARC is relatively satisfactory, while DM remains the main problem at present.Several previous studies showed an association between the change in CTC count and the treatment response in LARC patients treated with neoadjuvant therapy,However, the majority of previous studies failed to show or did not report a relationship with long‐term prognosis, which may be related to the sensitivity of the methods used. CTCs were detected in 90% of the patients in the current study, while the detection rate in other studies that used the size‐based method was relatively low (19%).The novel finding that baseline CTCs have a prognostic effect on DM in LARC patients receiving neoadjuvant therapy in the current study is consistent with the findings from one study on advanced CRCThe optimal strategy that can be used to control DM in LARC is still not ideal, although a decline of 6.8% in the cumulative probability of DM could be achieved in LARC patients with unfavorable clinical features through short‐course radiotherapy with total neoadjuvant chemotherapy,Notably, the difference in OS was nonsignificant between the two risk groups. Although this does not seem very plausible based on the difference in MFS, it could be attributed to the early detection of metastasis in prospective trials, favorable outcome in treatment for metachronous metastases of CRC and relatively short follow‐up time. In a population‐based study, CRC patients with metachronous liver‐only or lung‐only metastases could achieve 3‐year OS rates of 50.2% and 61.5%, respectively.Moreover, although the state of MRI‐detected extramural vascular invasion (mrEMVI) has been reported in previous studies to be clearly related to DM,To the best of our knowledge, although the clinical relevance of CTC detection has been broadly reported in CRC, this investigation is one of the very few to uncover the prognostic effect on metastasis of the baseline CTC count for LARC in the neoadjuvant setting. The strengths of our study included the analysis of a subset of data from a randomized trial and the inclusion of a new neoadjuvant treatment modality.This translational study was limited by the low fraction of patients enrolled among all trial subjects with a limited sample size, the lack of independent validation, and the short follow‐up time for LARC.In conclusion, for patients with LARC in a neoadjuvant setting, the values of baseline viable CTCs for DM risk stratification and the dynamic change in CTCs for neoadjuvant treatment response prediction were identified in this study. This tool may strengthen the pretreatment risk assessment and postradiotherapy decision making for LARC, which deserves further validation.Wen‐Yang Liu: Conceptualization (lead); formal analysis (lead); funding acquisition (lead); investigation (lead); methodology ; project administration (lead); resources ; software ; supervision (lead); validation ; visualization ; writing – original draft (lead); writing – review and editing . Wen Zhang: Conceptualization ; data curation ; formal analysis ; investigation ; methodology ; resources ; software ; supervision ; validation ; visualization ; writing – original draft ; writing – review and editing . Yuan Tang: Data curation ; investigation ; resources (lead); supervision (lead); writing – original draft (supporting); writing – review and editing . Si‐Lin Chen: Data curation ; writing – original draft (supporting). Ning Li: Data curation ; writing – original draft (supporting). Jun‐Qin Lei: Data curation ; writing – original draft . Jin‐Ming Shi: Data curation ; resources (supporting); writing – original draft (supporting). Shulian Wang: Resources (supporting); writing – original draft (supporting); writing – review and editing (supporting). Ye‐Xiong Li: Resources (supporting); writing – original draft (supporting); writing – review and editing (supporting). Kai‐Tai Zhang: Conceptualization ; data curation ; formal analysis ; investigation ; methodology (lead); project administration ; resources ; supervision (lead); writing – original draft ; writing – review and editing . Jing Jin: Data curation ; formal analysis ; funding acquisition (lead); investigation (lead); methodology ; project administration (lead); resources ; supervision (lead); validation ; visualization ; writing – original draft (lead); writing – review and editing (lead).This study was funded by the Beijing Municipal Science & Technology Commission (no. Z181100001718136), the National Natural Science Foundation of China (no. 82073352), and the Beijing Hope Run Special Fund of Cancer Foundation of China .The authors have no conflict of interest to declare.The software used during this study is mentioned in the article.The study was approved by the Ethics Committee of Cancer Hospital, Chinese Academy of Medical Sciences (NO. CH‐GI‐090).Written informed consent was obtained from each patient before enrollment in this study.Written informed consent for publication was not applicable for this study.Table S1.Click here for additional data file.


Ascomycota and Basidiomycota is higher in COVID‐19, and the opportunistic pathogens, including the genera Candida, Saccharomyces, and Simplicillium, are increased in COVID‐19. The classifier based on two fungal biomarkers is constructed and can distinguish COVID‐19 patients from controls in the training, testing, and independent cohorts. Importantly, the classifier successfully diagnoses SCs with positive specific severe acute respiratory syndrome coronavirus 2 immunoglobulin G antibodies as COVID‐19 patients. The correlation between distinct fungi and bacteria in COVID‐19 and control groups is depicted. These data suggest that the oral mycobiome may play a role in COVID‐19.The oral bacteriome, gut bacteriome, and gut mycobiome are associated with coronavirus disease 2019 (COVID‐19). However, the oral fungal microbiota in COVID‐19 remains unclear. This article aims to characterize the oral mycobiome in COVID‐19 and recovered patients. Tongue coating specimens of 71 COVID‐19 patients, 36 suspected cases (SCs), 22 recovered COVID‐19 patients, 36 SCs who recovered, and 132 controls from Henan are collected and analyzed using internal transcribed spacer sequencing. The richness of oral fungi is increased in COVID‐19 versus controls, and beta diversity analysis reveals separate fungal communities for COVID‐19 and control. The ratio of  This research characterizes oral mycobiome in coronavirus disease 2019 (COVID‐19) patients and recovered COVID‐19 patients, constructs and validates the diagnostic model for COVID‐19, successfully diagnoses suspected cases with positive immunoglobulin G antibody as confirmed patients, and depicts the correlations between the oral microbiome and mycobiome. SARS‐CoV‐2 enters human cells by binding to angiotensin‐converting enzyme 2 (ACE2) and transmembrane protease serine 2 (TMPRSS2) receptors, which are highly expressed in intestinal epithelial cells, salivary gland cells, and lungs. This suggests that the virus may affect disease progression by disrupting the resident bacterial community of the oral cavity and gut, as recently reported with altered oral and gut microbiomes in patients with COVID‐19.The coronavirus disease 2019 (COVID‐19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) continues to pose a public health threat. To date, COVID‐19 has infected 700 million people and killed 6 million.1 The  However, the mycobiota plays a key role in human health and disease states. It maintains the structure and metabolism of the microbial community, interacts with the bacteriome, and participates in the host immune response, thereby regulating the degree of the inflammatory response and affecting human health and disease states, such as human immunodeficiency virus, inflammatory bowel disease, and asthma. Existing research elucidates the oral bacterial profile of patients with COVID‐19 and links oral bacteria to the severity of COVID‐19. However, oral fungal alterations in COVID‐19 patients and those who have recovered from COVID‐19 remain unclear.The oral cavity has the second largest microbial community in the human body after the gut, including bacteria, fungi, and viruses, and is closely related to human health. Much research has focused on the human bacteriome in health and diseases, with little attention given to the human mycobiome. This may be due to the small proportion of fungi (less than 1%) in the human microbiome.6 Howe liver cirrhosis, and type 2 diabetes. At present, the gold standard for the diagnosis of COVID‐19 is reverse transcription‐polymerase chain reaction (RT‐PCR), but due to irregular sampling, improper collection sites, experimental operation error, low virus volume, and other reasons, there are false‐negative cases, which lead to the spread of COVID‐19. At the same time, a small number of people have typical clinical manifestations of COVID‐19 and positive serum antibodies, but the nucleic acid test continues to be negative, which is undoubtedly a challenge to epidemic prevention and control. Therefore, there is an urgent need for a novel auxiliary diagnostic tool that can compensate for the deficiencies of RT‐PCR. Recently, it has been found that oral, pharyngeal, and intestinal microbial markers can effectively distinguish COVID‐19 from healthy people, with good diagnostic efficacy. However, the possibility of using oral fungal markers to diagnose COVID‐19 has not yet been explored.Analysis of the microbiome as a diagnostic tool for diseases has become a hot research topic including in colon cancer,9 liveGiven the emerging association between the human oral microbiome and COVID‐19 and the possibility of false‐negative cases by RT‐PCR, we sought to explore whether oral fungal dysregulation is associated with the progression of COVID‐19 and the possibility of oral fungal markers for the diagnosis of COVID‐19. Therefore, we recruited a cohort of COVID‐19 patients (who tested positive for SARS‐CoV‐2 by PCR) and suspected cases (SCs) from Henan Province, China, and collected tongue coating swabs during early admission and at discharge. The composition of oral fungi was analyzed by internal transcribed spacer (ITS) sequencing. Our findings uniquely describe how oral fungal dysbiosis is involved in the disease progression of COVID‐19 while establishing a diagnostic model that enables cross‐regional validation.22.1We prospectively collected 484 tongue‐coating samples from Central and East China. After rigorous screening, a total of 372 samples were sequenced including 71 COVID‐19 patients (COVID‐19) from Henan, 36 SCs with positive specific SARS‐CoV‐2 antibodies from Henan, 22 matched recovered COVID‐19 (Post‐COVID‐19), 36 matched recovered SCs (SCRs), 132 healthy individuals (controls) from Henan, and 75 COVID‐19 patients from Hangzhou (COVID‐19‐HZ)  were randomly divided into two groups . We characterized the oral mycobiome and construct COVID‐19 diagnostic model in the train phase and verified the efficacy of the model in the test phase and independent cohort (75 COVID‐19‐HZ and 36 SCs).Table p > 0.05). The comorbidities in the COVID‐19 group were mainly hypertension (n = 6), diabetes mellitus (n = 5), and coronary artery disease (n = 4) (Table p < 0.01), while alanine aminotransferase, aspartate aminotransferase, total bilirubin, and the neutrophil‐to‐lymphocyte ratio were increased in the COVID‐19 patients in both groups (p <0.05).The clinical characterization of the subjects in the train and test phase is described in 2.2Figure The train phase comprised 48 patients with COVID‐19 and 88 controls. Through ITS sequencing, 2341 operational taxonomy units (OTUs) were identified including 303 OTUs unique to COVID‐19 patients, and 839 OTUs unique to controls  and COVID‐19 patients with comorbidities . Then we analyzed the oral fungal characteristics of COVID‐19‐N, COVID‐19‐C, and control (n = 132) groups. The Shannon index was not significantly different between COVID‐19‐N and controls  and OTU925 (C. longus), were identified as the optimal marker set  in the train phase   in the independent cohort (Hangzhou Group)  index was markedly higher in the COVID‐19 patients than in the controls, with an area under the curve (AUC) of 99.79%  Figure  (Table S) Figure  (Table Sp < 0.0001) between SCs and controls  but negative nucleic acid for SARS‐CoV‐2   and positively correlated with one genus (Candida). LYMPH was negatively correlated with three genera  and positively correlated with one genus (Cryptococcus). N/L was negatively related to one genus (Cryptococcus) and positively correlated with two genera (Gibberella and Hydnobolites). This explains the interaction of oral fungi, liver and kidney function, and routine blood tests, pathways that may be involved in affecting disease progression.The correlation between oral fungi and clinical indicators was identified in COVID‐19 patients and controls through Spearman correlation analysis  and lymphocytes (rho = −0.233), suggesting that the interaction between Candida and human immune cells may be involved in the progression of COVID‐19. CD4+ T cells and innate lymphoid cells play a protective role in invasive candidiasis, and the reduction in lymphocytes in patients with COVID‐19 may induce Candida invasion and colonization, while Candida can destroy immune cells, induce inflammatory responses, and aggravate COVID‐19 progression. However, the results of the correlation analysis between clinical indicators and fungi can only suggest that there may be a relationship between the two and provide potential possible directions for subsequent studies. Whether there is a causal relationship and its specific mechanism, needs to be verified experimentally.The correlations between oral fungi and clinical indicators are reported in this article. For example, didiasis,24 and schizophrenia, colorectal cancer, Crohn's disease, Type I diabetes, and Clostridium difficile infection. For example, Jun Yu et al. found that fungal fecal markers have the potential for CRC diagnosis with an AUC of 0.93 and successful cross‐national validation. Ningning Liu established CRC cohorts from eight countries/regions and found that intestinal fungi were used for CRC diagnosis and were best combined with bacteria and archaea. However, there has never been a study using oral fungi to diagnose COVID‐19 or even other diseases. Herein, we are the first to find that oral fungi can effectively distinguish COVID‐19 patients from healthy people, and the diagnostic performance is better than that of oral, pharyngeal, and intestinal bacterial markers. Moreover, the classifier was validated in the test phase, that is, Hangzhou independent cohort, suggesting that fungal markers have the potential to detect COVID‐19. More importantly, we found that the fungal classifier could diagnose suspected patients with negative nucleic acid but positive IgG antibody as COVID‐19, suggesting that fungal markers may be used as an auxiliary diagnostic tool for RT‐PCR, and the combination of the two will be able to identify potential COVID‐19 patients in the population. In addition, we found that the oral fungal diversity and composition of suspected patients and COVID‐19 patients were similar, confirming that suspected patients were undiagnosed patients with COVID‐19, which again demonstrated the feasibility of using this model to diagnose suspected patients with COVID‐19.Dysbiosis of the human mycobiome has been associated with a variety of diseases, and fecal fungi, plasma fungi, intratumoral fungi, vaginal fungi, gastric mucosal fungi, and other fungi from several parts of the body have been found to be useful in the diagnosis of various diseases such as gastric cancer,25 schPseudomonas aeruginosa can affect the respiration of C. albicans by secreting phenazine compounds, thereby inhibiting its morphological transition and biofilm formation.Bacteroides polymorpha can activate host immune effector molecules, such as hypoxia‐inducible factor 1α and antimicrobial peptide LL‐37, conferring resistance to C. albicans colonization in the intestine. Compounds derived from lactic acid bacteria can inhibit the toxicology of Candida parapsilosis; reduce the proliferation, viability, and metabolic activity of the fungus; and increase the resistance of epithelial cells to the fungus. The interaction between bacteria and fungi can influence the development and progression of infection. Peptidoglycan fragments of bacterial cell walls activate adenylyl cyclase by binding to leucine‐rich repeat domains to promote the growth of C. albicans and increase susceptibility to Candida infection. Our findings revealed that alterations in some key oral fungi in COVID‐19 patients and recovered patients were closely related to changes in oral bacteria, suggesting that oral fungi and bacteria may interact to influence the disease progression of COVID‐19. For example, gram‐negative bacilli that produce the proinflammatory factor lipopolysaccharide, such as Veillonella and Halomonas, are enriched in COVID‐19 patients and are positively associated with Candida. Prevotella and Alloprevotella, which helps breakdown protein and carbohydrate foods, were reduced in COVID‐19 patients and increased gradually in recovered patients and were inversely associated with the opportunistic pathogen Simplicillium. The above results provide potential clues for exploring the pathogenesis of COVID‐19 and can be verified by experiments such as coculture.Bacteria and fungi have complex interactions, such as competition and symbiosis, and biofilms provide a venue for these interactions. Bacteria and fungi secrete signaling molecules and chemicals to inhibit or promote the survival and growth of each other, thereby affecting the immune function and health of the host. For example, ormation.33BacWe tried our best to elucidate the changes and potential contributions of oral fungi in COVID‐19, but there are still some deficiencies in this work. First, the SARS‐CoV‐2 we studied was the original strain, which did not include Delta, Omicron, and other mutant strains. Follow‐up work will collect specimens from patients infected with mutant strains for further research. Second, our sample size is relatively small, and we still need to validate the model with a larger, cross‐regional multi‐center population cohort to enhance the generalizability of the model in the future. Third, ITS sequencing results focus on reflecting the composition and evolutionary relationship of community species, but the information on the functional composition and metabolic pathways of community species is not accurate enough. Metagenome sequencing can solve this problem. Fourth, due to insufficient data in the existing fungal database, some unclassified fungi were not annotated by ITS sequencing; finally, omics studies can only describe the correlation between fungi and COVID‐19, as well as fungi and bacteria. A causal relationship cannot be established, and the molecular mechanism cannot be elucidated. Microbial‐related experiments are needed to validate our findings.Taken together, our study elucidates the alterations in the oral mycobiome in COVID‐19 and recovered patients and demonstrates the potential usefulness of oral fungal markers in diagnosing COVID‐19 patients. Moreover, the classifiers could diagnose SCs as COVID‐19, making up for the deficiency of RT‐PCR, and may be used as an auxiliary diagnostic tool for RT‐PCR. Importantly, we reveal the ecological network in COVID‐19 and recovered patients, indicating that the synergistic and antagonistic interaction between bacteria and fungi may contribute to the progression of COVID‐19. These findings provide a new perspective on the pathology, diagnosis, and treatment of COVID‐19. Of course, more research and trials are needed in the future before they can be applied to the clinic.4 After admission, blood samples were collected from all patients for liver and kidney function and routine blood tests, and tongue coating samples were collected for subsequent ITS sequencing. Among them, 22 COVID‐19 patients and 36 SCs were followed up 2 weeks after discharge, and tongue‐coating samples were collected  issued by the National Health Commission of the People's Republic of China.37 AftA total of 132 age‐ and sex‐matched healthy individuals (controls) who were negative for SARS‐CoV‐2 by RT‐PCR were recruited from the First Affiliated Hospital of Zhengzhou University from January 2021 to March 2021. Controls had not taken antibiotics or probiotics in the past 8 weeks and had no underlying disease.The detailed inclusion and exclusion criteria of participants are described in the Experimental Section, Supporting Information. Patient data, such as demographic data, epidemiological characteristics, clinical symptoms and signs, and laboratory test results, were obtained from electronic medical records  and recovered SCs (SCR) were used to detect specific SARS‐CoV‐2 IgG antibody levels through chemiluminescence immunoassays . The positive cutoff value was defined as 10 U mLAll samples were inactivated at 56 °C for at least 30 min. The collection, transportation, storage, and testing of all COVID‐19‐related samples were strictly implemented in accordance with the “COVID‐19 Prevention and Control Plan (Fifth Edition).”38m guanidine thiocyanate; 10% N‐lauroyl sarcosine; 5% N‐lauroyl sarcosine‐0.1 m phosphate buffer (pH 8.0)) was added, followed by vigorous vortexing and incubation at 70 °C for 1 h. After incubation, 750 µL of glass beads (0.1 mm) was added to mix and beat for 10 min (25 HZ/S). Subsequent extraction was performed according to the instructions of the extraction kit (E.Z.N.A. Stool DNA Kit) .Each sample was placed in a 2‐mL centrifuge tube, and 790 µL of lysis buffer , 0.5 µL of Phanta Max Super‐Fidelity DNA Polymerase, 5 µL of template DNA, and 5.5 µL of ddH2O. Samples were subjected to four reactions using a PCR machine (ABI GeneAmp 9700): 95 °C for 3 min; 35 cycles of 94 °C for 30 s, 55 °C for 30 s, and 72 °C for 30 s; and finally 72 °C for 5 min. Agarose gel  was used to separate, extract, and purify the PCR products, and a fluorescence assay kit  to quantify the products.The universal primers ITS3F (5′‐GCATCGATGAAGAACGCAGC‐3′) and ITS4R (5′‐ TCCTCCGCTTATTGATATGC‐3′) were used for amplification of the ITS2 region of the fungal ITS gene. The PCR system included 12.5 µL of 2× Phanta Max Buffer, 0.5 µL of 10 mThe amplified products were purified by the magnetic bead method, and the purified products were used to construct DNA libraries according to the official operating instructions. The library products of different samples were mixed in an equimolar ratio, and then single‐end sequencing analysis was performed using the Illumina MiSeq platform . Raw Illumina read data of all specimens were deposited in the European Bioinformatics Institute European Nucleotide Archive database (PRJNA850097).http://drive5.com/uparse/) and annotated using unite v8.3 (https://unite.ut.ee/repository.php). Those annotated as unclassified fungi were further subjected to BLAST against ITS_RefSeq_Fungi version 1.1 (ftp://ftp.ncbi.nlm.nih.gov/blast/db/ITS_RefSeq_Fungi.tar.gz).Clean single‐read data were extracted from raw data using USEARCH (version 11.0.667), and reads with >1 expected error per base were discarded. Quality‐filtered sequences were clustered into unique sequences and sorted in order of decreasing abundance to identify representative sequences using UPARSE according to the UPARSE OTU analysis pipeline, and singletons were omitted in this step. OTUs were classified based on 98.5% similarity after chimeric sequences were removed using UPARSE (version 7.1 https://github.com/SegataLab/lefse). PICRUSt2 v2.4.1 (https://github.com/picrust/picrust2/wiki) was used to predict functional abundances based on ITS rRNA gene sequences.Alpha diversity metrics  were assessed by using Mothur v1.42.1. Both Bray–Curtis and weighted and unweighted UniFrac dissimilarity were calculated in QIIME. PCoA, NMDS plots, and PERMANOVA, which were used to test for statistical significance between the groups using 10 000 permutations, were generated in the R (version 3.6.0) package vegan 2.5‐7. The linear discriminant analysis (LDA) effect size (LEfSe) was used to detect taxa with differential abundance among groups  was used to complete the statistical analysis.Data are presented as the mean values ± standard deviations (SDs) for continuous variables and the number (percentage) for categorical variables. The nonparametric Mann–Whitney U test was used to compare significant differences between two groups for nonnormally distributed continuous variables. Student's This study was approved by the Institutional Review Board from the First Affiliated Hospital of Zhengzhou University (2020‐KY‐055). The study was performed in accordance with the Helsinki Declaration and Rules of Good Clinical Practice. All participants signed written informed consent after the study protocol was fully explained.Patients or the public were not involved in the design, conduct, reporting, or dissemination plans of our research.The authors declare no conflict of interest.X.H., H.W., B.Y., and J.Y. contributed equally to this work. Z.R., Y.J. and Z.W. designed the study. Z.R., Y.J., X.H., H.L., and Z.Z. treated the patients. H.W., B.Y., X.H., J.Y., J.S., Y.S., Y.Z., H.L., Z.Z., and S.L. collected clinical samples and clinical data. Z.W., Y.J., and HF.L. extracted bacterial DNA and completed MiSeq sequencing. H.W., B.Y., and J.Y. analyzed the data. H.W. and Z.R. wrote the manuscript. All authors reviewed and approved the manuscript.Supporting InformationClick here for additional data file.


A number of studies have claimed that carbonic anhydrase VI (CA VI) is associated with dental caries. The aim of this systematic review and meta‐analysis was to systematically review and analyze the literature on the association of CA VI (in terms of concentration and activity) with dental caries.A systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) guidelines. Relevant search terms were employed to search the following databases: PubMed, Web of Science, Scopus, China National Knowledge Infrastructure (CNKI), and Cochrane Library databases. Eligible publications from inception to August 2022 were included. The relevant records were assessed independently by two reviewers, and a meta‐analysis was performed using RevMan 5.3.95%): 0.386 and 1.392; p < 0.001), whereas the CA VI concentration was significantly lower among participants with caries than their caries‐free counterparts .Out of 237 relevant records from the initial search, 9 met the criteria for this review. The 9 papers, including 477 participants, were qualitatively analyzed. Seven studies with 411 participants (203 caries‐free) were included in the meta‐analysis on CA VI activity, and 2 studies with 141 participants (71 caries‐free) were included in the meta‐analysis on CA VI concentration. The results showed that CA VI activity was significantly higher among participants with caries than their caries‐free counterparts (standardized mean difference (SMD) = 0.894, 95% confidence interval (CIThis meta‐analysis of a relatively small number of studies suggests that the CA VI concentration is lower and CA VI activity is higher in patients with dental caries than in caries‐free individuals; however, further studies are needed to determine the exact role of CA VI in dental caries. The aetiology of dental caries includes physical, biological, environmental, behavioral, and lifestyle‐related factors such as high numbers of cariogenic bacteria, inadequate salivary flow, insufficient fluoride exposure, and poor oral hygiene , either in saliva or in biofilms  guidelines were rigorously followed in the present meta‐analysis Moher . The pro2.2The following databases were searched from inception to August 2022: PubMed, Scopus, Web of Science, China National Knowledge Infrastructure (CNKI), and Cochrane Library databases. The following keywords (or their Chinese translations) were searched:  AND .2.3All cross‐sectional and observational studies that investigated the possible associations of the concentration and/or activity of CA VI with the susceptibility of dental caries and met the following criteria were included in this systematic review: (1) included patients with dental caries and healthy controls (caries‐free), (2) had quantitative primary outcome measures , and (3) published in English or Chinese. The exclusion criteria were as follows: (1) studies that lacked a control group, (2) studies that lacked necessary quantitative data (mean and SD), (3) studies published in other languages, (4) case series, (5) case reports, (6) in vitro studies, or (7) review articles.2.4Two authors (R. A. M. and H. A. S) independently extracted the following relevant information from the included studies: authors and year of publication, country, research design, number of cases and controls, participant sex and age, diagnostic criteria/tools for identifying dental caries, calibration of caries detection/diagnosis, evaluation techniques, assay method and unit of measurement for CA VI and the main outcomes (activity and concentration of CA VI).2.5The Newcastle–Ottawa Scale (NOS) Stang,  was used2.6χ2 test and I2 statistics. The random‐effects model was used in cases of significant heterogeneity (I2 > 50%), and the fixed‐effects model was used in cases of nonsignificant heterogeneity (I2 ≤ 50%). A p value less than 0.05 was considered statistically significant.Comprehensive Meta‐Analysis software version 2.2.046 (Biostat) was used for the meta‐analysis. The standardized mean difference (SMD) along with the 95% confidence interval (CI) was calculated. To identify potential variability among studies, heterogeneity was identified according to the 2.7Funnel plots and Egger's test were used to investigate publication bias. Review Manager 5.3 software  was used to generate the funnel plots, while Stata for Windows was used to conduct Egger's test .33.1As illustrated in Figure 3.2n = 209), who ranged in age from 18 to 24 years  or were caries‐free . Caries status was identified using the dmft/DMFT score (either for teeth or for surfaces) in eight of the included studies; Cardoso et al. did not report using the dmft/DMFT score . As shown in Figure 95%: −1.011 and −0.332, Z score = −3.878 p < .001; τ2 = 0.00; Q value = 0.227; df = 1; p = .634; I2 = 0%).As shown in Figure 3.4p value was .04964.The funnel plot , respectively. Third, the main outcomes were homogenous among the included studies. However, many limitations should be noted. First, few studies were included; additional, more robust, and methodologically sound primary studies are needed. Second, seven out of the nine studies included were conducted in Brazil, with many of the studies having overlapping authors, a matter that impacts the external validity  of the results. Third, the measuring units were not standardized among studies, although this was accounted for in the meta‐analysis using the SMD. Fourth, and as indicated above, only two studies measured both the concentration and activity of CA VI in the same subjects (Picco et al., Given the results of this systematic review and meta‐analysis, and in light of the limitations indicated, we propose conducting studies to assess the clinical utility of CA VI as a predictor of the development and/or activity of dental caries and conducting studies on the clinical efficacy of adding CA VI into toothpaste formulas to prevent dental caries.5In conclusion, this meta‐analysis is one of the first to critically assess the role of the CA VI protein concentration and its activity in relation to dental caries. In light of the limitations of this systematic review, and according to our findings, we suggest that CA VI has lower concentrations and higher activity in patients with dental caries than in caries‐free individuals. Further studies are needed to determine the exact role of CA VI in dental caries.Rania Al‐Mahdi and Esam Halboub design the study. Rania Al‐Mahdi and Hesham Al‐Sharani searched and gathered the relevant articles. Hesham Al‐Sharani registered the project in the PROSPERO database. Rania Al‐Mahdi, Mohammed Al‐Haroni, and Esam Halboub drafted the manuscript. Rania Al‐Mahdi, Hesham Al‐Sharani, Mohammed Al‐Haroni, and Esam Halboub analyzed the data. The final manuscript is approved by all authors.The authors declare no conflict of interest.An ethics statement was not required for this study type, and no human or animal subjects or materials were used.Supporting information.Click here for additional data file.Supporting information.Click here for additional data file.


Chimeric antigen receptor (CAR) T cells have been successfully used in adoptive cell therapy for malignancies. However, some obstacles, including side effects such as graft‐versus‐host disease and cytokine release syndrome, therapy resistance, limited sources, as well as high cost, limited the application of CAR T cells. Recently, CAR natural killer (NK) cells have been pursued as the effector cells for adoptive immunotherapy for their attractive merits of strong intrinsic antitumor activity and relatively mild side effects. Additionally, CAR NK cells can be available from various sources and do not require strict human leukocyte antigen matching, which suggests them as promising “off‐the‐shelf” products for clinical application. Although the use of CAR NK cells is restrained by the limited proliferation and impaired efficiency within the immunosuppressive tumor microenvironment, further investigation in optimizing CAR structure and combination therapies will overcome these challenges. This review will summarize the advancement of CAR NK cells, CAR NK cell manufacture, the clinical outcomes of CAR NK therapy, the challenges in the field, and prospective solutions. Besides, we will discuss the emerging application of other immune cells for CAR engineering. Collectively, this comprehensive review will provide a valuable and informative summary of current progress and evaluate challenges and future opportunities of CAR NK cells in tumor treatment. NK cells for CAR NK generation can be derived from several sources, including PBMC, iPSC, UCB, and NK‐92 cells. NK cells are transduced with CAR structure by viral or nonviral vectors after isolation or differentiation from a variety of sources, then CAR‐NK cells can be sorted. CAR NK cells are then cocultured with cytokines or feeder cells expressing IL‐15 and mb‐IL‐21 to allow further expansion of NK cells. This review will discuss the advances of CAR NK cells, the design improvement of CAR, CAR NK cell manufacture, the challenges, and the clinical outcomes in CAR NK cell therapy. Instead of targeting the tumor cells directly, immunotherapy focuses on modifying immune effector cells or overcoming immunosuppression induced by tumor cells and the local microenvironment, endowing the immune cells with enhanced effect to target and eradicate malignant cells. Immunotherapies, including adoptive cell transfer (ACT) of genetically modified immune cells and inhibitors of immune checkpoints such as cytotoxic T Lymphocyte antigen 4 (CTLA‐4) and programmed death‐1 (PD‐1), have been applied in oncological clinical practice and obtained durable clinical responses.Earlier ACT, which directly infused activated autologous or allogeneic immune cells into cancer patients to eliminate tumor cells, had only achieved modest benefits in clinical trials.NK cells are lymphocytes of the innate immune system, which eliminate cancer cells and infected cells through secretion of perforin and granzyme or death receptor‐mediated cytotoxicity with no need for prior activation.In this review, we described the detailed structure and manufacturing process of CAR NK cells, and how CAR NK cells are activated. We also discussed current challenges and evolving strategies to promote persistence and killing capacity against tumor cells. Finally, we provided a comprehensive overview of the application of CAR NK cells for the treatment of solid tumors and hematologic malignancies.2Hitherto, barriers such as severe side effects, unsustainability, and high time and financial consumption still limit the broad adoption of CAR T cell therapy. On the contrary, the NK cell has the potential to become an outstanding option for CAR therapy because of its intrinsic cytotoxicity, high efficacy and controllable adverse effects. The comparison of CAR T and CAR NK therapy is summarized in Table Activation and expansion of CAR T cells lead to massive serum cytokines accumulation, which contributes to the potential risks of CRS and neurotoxicity.Although impressive clinical efficacy against malignant diseases has been achieved, relapse still occurs commonly in patients after CAR T therapy.T cells for CAR T cell generation are collected and separated from the patient's blood cells, which require complicated manufacturing processes, making CAR T therapy an expensive and time–cost treatment,3The CARs expressed in NK cells and T cells share similar structures, which usually consist of an extracellular portion, a transmembrane (TM) domain, and an intracellular domain Figure . The ext3.1The order of Fv, length of linker, and type of linker of the scFV did not noticeably affect the expression level of CAR on T cells. However, the surface expression of CAR can be improved by grafting complementarity‐determining region to the murine‐derived stable framework region in Fv, demonstrating that CAR expression efficiency and stability could be affected by the Fv structure.3.2The hinge region is the extracellular structural region of the CAR connecting the scFv units to the TM domain.3.3The first‐generation CARs contain only one activating signal, CD3ζ, while the second‐ and third‐generation CARs contain one and two costimulatory domains, respectively.Although extensive activation signals are necessary to induce a strong antitumor response, the effector cells could also be committed to a rapid exhaustion state. Therefore, the combination of costimulatory domains is important to regulate the response of adaptive immune cells. Compared with CD28/CD3ζ‐based CAR structure, 4‐1 BB/CD3ζ‐signaling induced slower and reduced downstream protein phosphorylation. However, the CD28/CD3ζ CAR T cells with more quick and intense phosphorylation signaling exhibited a less potent antitumor effect in mice models despite higher levels of immune cytokine production early after CAR ligation. In contrast, the weaker CD3ζ immunoreceptor tyrosine‐based activation motif (ITAM)‐signals in 4‐1 BB‐based CAR T cells exhibited better antitumor effect and longer persistence.In almost all the CAR NK cells, the CD3ζ transmits signals based on the interaction between CAR and target antigens.3.4Activation of CAR NK cells can be initiated through the recognition of specific target antigens on tumor cells by CAR expressed on NK cells, which transduce the activating signaling to the intracellular domains of the CAR, such as CD3ζ, DAP10, DAP12, and costimulatory domains, resulting in the downstream processes.3.4.12+ flux and cytoskeletal reorganization, enabling NK cells to lysis target cells.Activation of CAR NK cells depends on the integration signaling of intrinsic activating receptors, inhibitory receptors, and cytokine receptors, most of which share the common adaptor molecules and signaling pathways.2+ flux and synapse formation, and finally inhibits NK cell activation.Inhibitory receptors of NK cells, including KIRs, CD94–NKG2A heterodimer, LAG‐3, and TIM‐3, avoid unrestrained cytotoxicity and protect healthy cells from being attacked via engaging MHC‐I molecules.3.4.2CAR expression endows the NK cells with the capacity to capture specific target cells through antibody–antigen interactions. The most of costimulatory and signaling domains of CAR molecules applied for NK cells are similar to those for T cells. The latest CAR structures depend on the CD3ζ chain signaling domain, which contains three ITAMs, facilitating recruitment and activation of Syk or ZAP70 tyrosine kinases, or PI3K signaling to mediate NK cell activation.3.4.3Once NK cells are activated, a synapse linking the NK cell with the target cell is formed, and cytotoxic granules such as perforin and granzymes transport toward the synapse, which will fuse with the plasma membrane and finally relased.Apart from direct cytotoxicity, activated NK cells could trigger and recruit other immune effector cells, including dendritic cells and macrophages, into tumor tissue via secreting various cytokines and growth factors, including CC‐chemokine ligand 5, IFN‐γ, TNF and IL‐13.44.1NK cells can be isolated and obtained from multiple sources Figure . While a4.1.1NK cells for CAR‐NK cell manufacture can be directly enriched from the PBMC.4.1.2CB NK cells can be available from large global CB banks and expanded further in the absence of cytokines.4.1.3iPSCs can be obtained easily from various sources such as skin and PB.4.1.4NK‐92 is an IL‐2‐dependent cell line derived from a patient with non‐Hodgkin's lymphoma and is widely used to generate CAR NK cells.4.24.2.1+ cells suffered leukemia due to insertional mutagenesis.Lentiviral and retroviral vectors are commonly used to deliver CAR genes into NK cells based on their ability to integrate CAR genes into the host genome, resulting in highly efficient and stable expression of the CAR genes.4.2.2The transposon system transfers genes through a bi‐component vector system that consists of a transposon containing a gene flanked by inverted terminal repeats and a gene‐coding transposase. Transposase protein binds to the transposon ends of the cargo vector specifically, excising the CAR gene and integrating it into the genome of NK cells.4.2.3Unlike the two methods introduced above, electroporation transduces the CAR gene into NK cells transiently and cannot integrate it into the genome DNA of NK cells, which may therefore avoid severe cytokine storm resulting from the permanent CAR expression.55.1Expanding NK cells, especially PB NK cells, to satisfy clinical use in vitro is challenging.5.2Another major limitation of the clinical application of CAR‐NK cells is the short persistence of CAR‐NK cells after infusion.A phase I clinical trial was conducted using FT596 as a monotherapy or in combination with rituximab to treat patients with diffuse large B‐cell lymphoma. Results showed that seven out of 14 patients (50%) achieved complete remission, and 10 out of 14 patients (71%) achieved an objective response. Furthermore, the patient showed no neurotoxicity, GVHD, or other adverse effects related to FT596 treatment except for CRS, which was resolved later.Another approach to prevent the exhaustion of NK cells is to generate memory‐like phenotype immune cells, which exhibit improved persistence as well as a rapid and effective response to tumor antigens.5.3Generally, tumor‐associated antigens (TAAs) for CARs designing are highly expressed on the surface of tumor cells. However, most TAAs are expressed in tumors and normal cells, which makes it possible that normal cells will be attacked by CAR NK cells.5.45.4.12O2 in NK cells and therefore benefit the persistence and tolerance of NK cells to oxidative stress. Based on that, PD‐L1 CAR NK cells overexpressing PRDX1 was generated and proved to improve the survival of mice transplanted with human breast tumor, which exhibited high H2O2 concentration in the local TME.Generally, oxidative stress is caused by the increased production of reactive oxygen species (ROS) and impaired removal by antioxidants.5.4.2CD16a is an IgG Fc receptor on the surface of NK cells, which initiates NK ADCC by binding to IgG on target cells Figure . A disin5.4.3Adenosine, a critical immunosuppressive metabolite that binds to the A2A adenosine receptor (A2AR) on NK cells, was found to inhibit infiltration, maturation, and immune responses of NK cells Figure .137, In addition, TGF‐β is abundantly present in the TME and is secreted by various cell types, such as the tumor cells, regulatory T cells, and M2 macrophages, which induce inhibitory gene expression profile and suppress the cytotoxic function of NK cells.5.4.4Immune checkpoints, including PD‐1, CTLA‐4, CIS, and TIM‐3, are a series of molecules that prevent the activation of immune cells and inhibit immune response.Cytokine‐inducible SH2‐containing protein (CIS), a member of the suppressor of cytokine signaling family proteins, is a potent immune checkpoint in NK cells By interacting with the tyrosine kinase JAK1, CIS suppresses IL‐15 activating signaling in NK cells and inhibits the expansion and activation of NK cell.5.4.5Rare tumor infiltration of CAR NK cells caused by inhibitory KIRs, immunosuppressive cytokines, and anatomical barriers is related to the poor prognosis.Moreover, the application of TKI was found to inhibit the suppression effect of myeloid‐derived suppressor cells and regulatory T cells and increase the infiltration of lymphocytes in tumors.Other approaches such as intraperitoneal injection and ultrasound‐mediated injection have been developed to directly deliver immune effector cells into tumor sites and therefore overcome the anatomical barriers. For example, MRI‐guided focused ultrasound and microbubble ultrasound contrast agents, which increased the permeability of the cerebrovasculature in target regions, were used to deliver HER2 CAR NK‐92 cells to eradicate metastatic tumors in the brain. An appreciable effect was observed as evidenced by delayed tumor progression.6GD2 is a ganglioside highly expressed in neuroblastoma.GPC3 is a cell surface protein highly expressed in hepatocellular carcinoma (HCC) but barely expressed in normal liver tissue.The prostate‐specific membrane antigen (PSMA) has been a popular immunotherapy target for prostate cancer these past few years. Several clinical trials using PSMA monoclonal antibodies have been conducted in prostate cancer but the responses were observed in a minor fraction of patients.NKG2D is an activating receptor of NK cells, whose membrane‐anchored ligands such as MHC class I‐related molecules MICA and MICB are overexpressed in several tumor types.As a TM glycoprotein highly expressed in myeloma cells, B cell maturation antigen (BCMA) is the leading target for CAR NK therapy for multiple myeloma (MM).7In recent years, numerous preclinical studies demonstrated the therapeutic potential of CAR NK cells in treating hematological malignancies and solid tumors, and many CAR NK clinical trials are ongoing Table . Two triThe clinical success of CD19 CAR T cells in the treatment of malignant hematological diseases attracted more attention to applying CD19 CAR to NK cells.Based on the promising preclinical results NK cells expressing NKG2D CARs with the CD3zeta or DAP12 intracellular signaling domain showed significant immune responses, slower disease progression, and prolonged median survival time in mice with human colorectal cancer xenografts. Xiao et al.8Apart from NK cells and T cells, other immune cells, including invariant NK T (iNKT) cells, γδT cells, macrophages, dendritic cells, and neutrophils possessing specific advantages have been explored as candidates for CAR‐engineering cells, and some CAR‐based products using these cells are being tested in clinical trials.8.1iNKT cells are a small population of αβ T lymphocytes expressing a semi‐invariant T cell receptor, which recognizes lipids presented by CD1d, a nonpolymorphic MHC class I‐like molecule. Similar to innate immune cells such as NK cells, iNKT cells are stimulated by a variety of cytokines, such as IL‐12, IL‐18, and IL‐23 apart from TCR stimulation.CAR iNKT cells targeting tumor antigens such as CD19, CD38, BCMA, CSPG4, and GD2 have been generated, and the efficacy has been evaluated in preclinical models or clinical trials.8.2γδT cells account for 1−5% of all the circulating T cells but represent a major part (10–100%) of epithelial tissue. Epithelial γδT cells play a vital role in mediating a rapid immune defense response against invading pathogens while maintaining immune tolerance to microscopic organisms.γ9δ2T cells, a γδT cell subset, were found to be relatively abundant in the PB and can be expanded to a large number for clinical use ex vivo. Preclinical results showed that CAR γδT cells exhibited potent antitumor activity in vitro and in vivo. Expression of GD2 CAR γδT cells retained the functions of antigen cross‐presentation to αβT cells and migration toward tumor cells while exhibiting enhanced tumor‐killing capacity.9As an innovative and effective cellular immunotherapy, CAR NK cell owns several advantages compared with CAR T cell therapy. Owing to the independence of MHC‐matching and abundant sources, CAR NK cells can be available as off‐the‐shelf products, reducing the cost and waiting time for immediate clinical use. Relative shorter lifespan and alternative cytokine secretion spectrum of CAR NK cells reduce the risk of “on‐target, off‐tumor” toxicity, and CRS. Preclinical studies have shown the great promise of CAR NK cells in a wide range of tumor types. Besides, the safety as well as tolerance of CAR NK cell therapy have been shown in clinical trials.Although tremendous progress has been achieved, and CAR NK cell adoptive immunotherapy is being tested in multiple clinical trials and offers the possibility of a safer, off‐the‐shelf, antitumor therapy, the clinical translation of CAR NK cell therapy is still in the early stage compared with CAR T cell therapy. Some potential issues present in CAR NK treatment remain open, including tailor‐made CAR structure for NK cells, appropriate transduction system for CAR gene expression in NK cells, especially to naïve NK cells, and optimal source and expansion conditions for CAR NK cell manufacture. Besides, immunosuppressive TME that impairs NK cell activation, persistence, and infiltration is another obstacle to CAR NK therapy that needs to be solved.Reprogramming CAR‐NK cells via gene editing or including novel genes in CAR structure was proved to significantly improve the efficacy of CAR NK cells. Additionally, the combination therapy strategies, such as the integration of mAbs and small‐molecule inhibitors to block the checkpoint and deplete the immunosuppressive metabolites, provide a coordinated effect and increase the resistance of CAR NK cells to the TME.With the development of CAR NK cell therapy in clinical practice, a number of ethical issues have been raised and must be solved. Strict standards to monitor and evaluate the CAR NK cell manufacturers and medical institutions should be formulated to standardize the techniques of enriching NK cells and ensure their safety and effectiveness during treatment. Patients must be fully informed about the potential benefits and risks of CAR NK cell therapy. Additionally, NK cells for immunotherapy are obtained from autologous or allogeneic sources, allowing for the “off‐the‐shelf” availability of CAR NK cells, which can be immediately used for patients at lower cost. On the other hand, ensuring fair and equitable allocation of limited sources should be considered to avoid exacerbating existing health disparities.In conclusion, with the increasing evidence of safety and efficacy in clinical trials, and new strategies to address the remaining challenges, it is believed that immunotherapies based on CAR NK cells will continue to develop and represent a bright future for the treatment of hematological malignancies and solid tumors.Writing—original draft preparation: Y. W. Writing—review and editing: J. S., Y. W., S. J. J., Q. Q. Z., N. L., R. Y. C., and S. A. A. Visualization: Y. W. Supervision: J. J. and J. S. All authors have read and agreed to the published version of the manuscript.The authors declare no conflict of interest.Not applicable.


Primary cardiac sarcomas are rare and their clinicopathologic features are heterogeneous. Among them, particularly intimal sarcoma is a diagnostic challenge due to nonspecific histologic features. Recently, MDM2 amplification reported to be a characteristic genetic event in the intimal sarcoma. In this study, we aimed to identify the types and incidence of primary cardiac sarcomas that occurred over 25 years in tertiary medical institutions, and to find clinicopatholgical significance through reclassification of diagnoses using additional immunohistochemistry (IHC).We reviewed the primary cardiac sarcoma cases between January 1993 and June 2018 at Asan Medical Center, South Korea, with their clinicopathologic findings, and reclassified the subtypes, especially using IHC for MDM2 and then, analyzed the significance of prognosis.n = 25, 52.1%), and the most frequent tumor subtype was angiosarcoma . Seven cases (53.8%) were newly reclassified as an intimal sarcoma by IHC for MDM2. Twenty‐nine (60.4%) patients died of disease . Four patients underwent a heart transplantation and had a median survival of 26.8 months. This transplantation group tended to show good clinical outcomes in the earlier stages, but this was not statistically significant (p = 0.318). MDM2 positive intimal sarcoma showed the better overall survival (p = 0.003) than undifferentiated pleomorphic sarcoma. Adjuvant treatment is beneficial for patient survival (p < 0.001), particularly in angiosarcoma (p < 0.001), but not in intimal sarcoma (p = 0.154).Forty‐eight (6.8%) cases of a primary cardiac sarcoma were retrieved. The tumors most frequently involved the right atrium (Our study supports the use of adjuvant treatment in primary cardiac sarcoma, as it was associated with a significantly better overall survival rate. Further consideration of tumor histology may be important in determining the optimal use of adjuvant treatment for different types of sarcomas. Therefore, accurate diagnosis by MDM2 test is important condsidering patient's prognosis and treatment. MDM 2 expression is upregulated in numerous cancers, resulting in a loss of p53‐dependent activities, such as apoptosis and cell cycle arrest.MDM2 amplification was shown to associated with overexpression of both RNA and protein.MDM2Mouse double minute 2 Primary cardiac sarcomas show a dismal prognosis. Yin et al. reported a median survival of only 7 months for affected patients, and 1‐, 3‐, and 5‐year survival rates of 40.7%, 15.6%, and 9.8%.Much of the previously published data on cardiac tumors do not reflect the current updated disease classifications or entity description that have arisen from improved molecular and immunohistochemical diagnostic methods. Studies by clinicians based only on past medical records without a pathologist's review are also likely to produce erroneous data. Herein, we have reviewed the primary cardiac sarcoma patients at our hospital over a 25 year periods and classified the tumors in each cases in accordance with recent updates to these disease entities using additional immunohistochemistry (IHC). We also evaluated the clinicopathologic significance of these new evaluations.22.1We retrospectively reviewed 705 patients who underwent cardiac surgery for cardiac tumors between January 1993 and March 2018 at Asan Medical Center, Seoul, Korea. We identified 48 patients (6.8%) with a primary cardiac sarcoma. All of the study cases were histologically and radiologically reviewed by two bone and soft tissue pathologists (J.S.S and K.J.C) and two radiologists  along with their pathologic diagnosis, IHC, clinical data, and medical records. The Institutional Review Board of Asan Medical Center approved our study protocol.2.2IHC was newly performed to confirm the original diagnosis. Whole tissue was cut into 4‐μm thick sections. The IHC was performed using the Ventana NX automated immuno‐histochemistry system . The retrieved antibodies were as follows: SMA , MDM2 , Desmin , CD31, CD34 , CD99 , S‐100 protein , TLE‐1 , p53 , NKX2.2 , and myogenin . After incubation with primary antibodies, the sections were incubated with an UltraView universal DAB kit .2.3p‐value was <0.05. All statistical analyses were carried out using the SPSS software package, version 21.0 (SPSS).Survival analysis was performed using the Kaplan–Meier method and the resulting curves were compared using the log‐rank test. The results were considered statistically significant when the 33.1n = 22, 45.8%) and the second was chest pain or chest discomfort . Other symptoms include chronic cough , syncope , pericardial effusion  and incidental findings during a regular medical check‐up .Forty‐eight patients (6.8%) with primary cardiac sarcoma out of 705 patients for cardiac tumor were retrieved. There were 21 men and 27 women with mean age of a 47.2 years . The most common presenting symptom was dyspnea with a New York Heart Association functional classification of greater than II , followed by the left atrium  and a specific tumor histology was associated with these different sites. The histologic types were angiosarcoma , intimal sarcoma , synovial sarcoma , undifferentiated pleomorphic sarcoma , myxofibrosarcoma , fibrosarcoma , malignant peripheral nerve sheath tumor  and Ewing sarcoma/primitive neuroectodermal tumor    Figure . The clirium n = 5, 31.2% We performed IHC for MDM2 and p53 to confirm the diagnosis in 14 cases which were initially diagnosed as angiosarcoma, MPNST, ES/PNET, and synovial sarcoma. Seven cases were reclassified as an intimal sarcoma in accordance with their MDM2 immunopositivity. Two of these cases had been initially diagnosed as myxosarcomas, four as a malignant fibrous histiocytoma and one as a leiomyosarcoma. Patient 47 was initially diagnosed with an embryonal rhabdomyosarcoma but was found in our current analyses to be immunonegative for all of the tested muscle markers including desmin, myogenin, myoglobin, and myoD1. Histologically, the tumor cells in this case were composed of short spindle cells with a short fascicular pattern and alternating cellularity. They did not show any specific lineage by IHC or ultrastructural examination, and the final diagnosis was revised to an undifferentiated spindle cell sarcoma.Representative pathologic features of sarcomas including angiosarcoma Figure , Ewing sThe intimal sarcomas in our present series showed variable histologic features including a spindle cell sarcoma with myxoid stroma, hemangiopericytoma‐like sarcoma, osteosarcomatous differentiation, a pleomorphic sarcoma with extensive inflammatory infiltrates, and a mixed epithelioid, spindle, myxoid, and pleomorphic sarcoma pattern Figure . All of Eleven of patients underwent a complete excision, 23 received an incomplete excision, 10 had a biopsy or pericardiotomy, and four received a heart transplantation. Radiologic and gross findings for the intimal sarcoma Figure  and angi3.2p = 0.001), which is consistent with the common occurrence of intimal sarcoma at that location.The testing for MDM2 expression is mainly done to distinguish intimal sarcoma from UPS. A total of 15 patients were included in the analysis, and all MDM2 positive patients were classified as intimal sarcoma. These were summarized in Table 3.3Follow‐up data were obtained in 34 of the study patients and the periods ranged from one day to 87.7 months (mean 15.9 months). Twenty‐nine (85.3%) patients died of disease  and five (14.7%) were alive with disease at the time of writing. Twenty‐seven patients (79.4%) underwent recurrence and/or metastasis, most commonly in the brain, lung, and liver.p = 0.045, log‐rank, Figure p = 0.315, log‐rank, Figure A complete excision, including heart transplantation, produced a better prognosis than an incomplete resection , but an UPS had the poorest prognosis  than MDM2 non‐amplified UPS (61 months). Conversely however, Guellec et alMDM2 amplification, conventional DDLPS, and UPS without MDM2 expression of 93.3%, 90.7%, and 73.9%, respectively, thus indicating that MDM2 amplified sarcomas showed a better prognosis. Our present study indicated that intimal sarcomas with an MDM2 amplification had a better prognosis than non‐amplified undifferentiated sarcomas. These findings are the first to be reported in primary cardiac sarcomas. It will therefore be important going forward, from a prognostic perspective, to distinguish intimal sarcomas with MDM2 amplifications from UPS, and this may serve as a basis for the application of MDM2 inhibitors as future therapies.The correlation between Our findings revealed that adjuvant treatment in primary cardiac sarcoma significantly improved overall survival, which is consistent with the recent study by Hendriksen et alMDM2 protein expression can be identified by IHC, not MDM2 gene amplification. However, in accordance with our previous study,MDM2 gene amplification revealed by FISH, with a sensitivity of 93% and specificity of 100% (p < 0.001). Hence, in diagnosing intimal sarcoma, screening by IHC will be a robust and accurate approach without the need to conduct FISH assays. A second limitation of our current analyses was that the detection of PDGFRA amplification among the intimal sarcomas could not be confirmed. However, it is not necessary to perform MDM2 gene amplification specifically for diagnosis or prognostic assessment of the patient. As mentioned earlier, there is a strong correlation between MDM2 gene amplification and MDM2 protein expression. Additionally, it is known that not only MDM2 gene amplification but also CDK4 and PDGFR gene amplification can occur together in intimal sarcoma.p = 0.13) compared to cases from earlier decades (1973–2005). As a final limitation, due to the rarity of primary cardiac sarcoma, the sample size included in this study was too small. To overcome this limitation, we hope that multicentric studies with a large cohort will support our research findings.One of the limitations of our present study was that only In conclusion, our study supports the use of adjuvant treatment in primary cardiac sarcoma, as it was associated with a significantly better overall survival rate. Further consideration of tumor histology may be important in determining the optimal use of adjuvant treatment for different types of sarcomas. The reason for emphasizing the MDM2 test is that if MDM2 overexpression is detected in high‐grade sarcoma, it should be classified as intimal sarcoma, which has a better prognosis compared to UPS, thus, accurate diagnosis by MDM2 test is important. In addition, when considering adjuvant treatment, histology should also be taken into consideration as there is no statistically proven survival benefit of adjuvant treatment.Haeyon Cho: Data curation ; formal analysis ; investigation ; writing – original draft . In Hye Song: Data curation ; investigation ; writing – original draft . Uiree Jo: Conceptualization ; data curation ; formal analysis ; investigation . Ji‐Seon Jeong: Data curation ; formal analysis ; methodology . Hyun Jung Koo: Data curation ; investigation . Dong Hyun Yang: Data curation ; investigation . Sung‐Ho Jung: Data curation ; investigation . Joon Seon Song: Conceptualization ; funding acquisition ; resources ; supervision ; writing – review and editing . Kyung‐Ja Cho: Conceptualization ; writing – review and editing .This study was supported by a grant (2018IL‐0664) from the Asan Institute for Life Sciences, Asan Medical Center, Seoul, Korea. (JSS).The authors declare no competing interest.This study was approved by the Institutional Review Board of Asan Medical Center, Seoul, Republic of Korea, (IRB no. 2016–0180). The requirement for written informed consent was waived by the institutional review board of the Asan Medical Center (IRB no. 2016–0180) due to the retrospective nature of this study. All procedures performed in this study involving human participants were in accordance with the ethical standards of the institutional research committee and the 1964 Declaration of Helsinki and its later amendments.Data S1. Supporting Information.Click here for additional data file.Supplement Table 1. Patient demographicsClick here for additional data file.


Oral submucous fibrosis (OSF) is a chronic progressive fibrosis disease that affects in oral mucosal tissues. Interleukin (IL)‐13 has been implicated in the development of fibrosis in multiple organs. Indeed, it contributes to diseases such as pulmonary fibrosis, liver cirrhosis among others. Currently, its expression in OSF and the specific mechanisms are not well understood. The aim of this study was to investigate the role of IL‐13 in OSF and further explore whether IL‐13 regulates—polarization of M2‐macrophages in OSF. Initially, in the tissues of patients with OSF, we observed a high expression of M2‐macrophages and IL‐13 protein. Additionally, we found a correlation between the expression of IL‐13 and the stage of OSF. Arecoline inhibited the proliferation of fibroblasts (FBs) and promoted IL‐13 production in vitro. Furthermore, our observations revealed that M2‐macrophages increased upon co‐culturing M0‐macrophages with supernatants containing the IL‐13 cytokine. In conclusion, our study demonstrated that arecoline stimulates FBs leading to increased secretion of IL‐13, which in turn IL‐13 leads to polarization of M2‐macrophages and promotes the occurrence of OSF. This suggests that IL‐13 may be a potential therapeutic target of OSF. This disease, which was first described by Paymaster to be potentially malignant,Studies have shown that the immune microenvironment of OSF significantly changes during OSF occurrence, including infiltration of immune cells of different subtypes and functions in the diseased tissue, as well as expression of immune‐related cytokines.Interleukins (ILs) are cytokines that play an important role in the activation, differentiation, proliferation, maturation and migration of immune cells.The Areca nut ranks fourth among the most commonly used addictive substances globally.In this study, we explored the possible mechanism underlying IL‐13's action as an ‘inducing factor’ during stimulation of polarization of M2‐type macrophages, and its role in pathogenesis of fibrosis. Further, we investigated the effect of arecoline, the main pathogenic factor of OSF, on the function of FBs.22.1The research protocol used in the current study was approved by the Institutional Review Board of Hunan Xiangya Stomatological Hospital, Central South University . FBs were extracted from normal tissue from patients who met the following conditions: had normal local mucosa; no inflammation; no history of chewing areca nut; no medication history in the past 3 months; and no family history of OSF disease. Patients were stratified into the following subgroup, based on presentations: restricted mouth opening, white mucosa, palpable striae, firm texture, and OSF diagnosed via biopsy, and this part of the OSF tissue was used for subsequent experiments. A total of 85 tissue specimens, including 75 OSF and 10 normal tissues, were collected from patients at Hunan Xiangya Stomatological Hospital Central South University between 2018 and December 2021. The specimens had been previously diagnosed via pathological biopsy, with OSF histopathology confirmed by an expert pathologist.2.2p (adj. p) <0.05, and log2 fold change (FC) >1.GSE64216, a dataset with mRNA expression profiles for OSF alongside normal samples, was downloaded from the Gene Expression Omnibus (GEO) database. Analysis of differentially expressed genes in the dataset was conducted at the following threshold: adjusted 2.3Paraffin‐embedded blocks were used to prepare OSF specimens, and 4‐μm sections were cut from them. These sections were then subjected to IHC by incubating them with specific primary antibodies at 4°C overnight: anti‐IL13 , anti‐CD163 , anti‐CD206 , anti‐CD209 , (CD163/206/209 are the markers of M2 macrophages). The sections were then incubated with secondary antibodies using the Immunohistochemistry detection system kit (Bioss), dehydrated and the slides sealed with neutral resin. The sections were visualized under a microscope, where positive particles were stained brown. Optical density sum (IOD SUM), and area were measured using ImagePro Plus, and the mean density was calculated as follows: mean density = IOD SUM/area.2.4OSF lesion tissues were collected from patients and subjected to RNA TRIzol Reagent according to the manufacturer's instructions. The RNA was quantified then converted to cDNA using the HiScriptIIQ RT SuperMix Kit . The cDNA was subjected to qRT‐ PCR, performed using the ChamQ Universal SYBR qPCR Master Mix (Vazyme), targeting IL13 gene .In this test, GAPDH  was included as the internal amplification control. Relative gene expression was calculated using the 22.5Experimental specimens were obtained from healthy mucosal tissues, resected during oral and maxillofacial surgery. The tissues were first washed with PBS supplemented with 20% penicillin and streptomycin, chopped into small pieces then centrifuged at 1000 rpm for 5 min. The tissue was digested with a mixture of Collagenase I (6 mg/mL) and Dispase (8 mg/mL) for 15 min, the cells counted, and transferred to a Petri dish. Culture medium was changed after every 3 days. FBs were cultured in Dulbecco‘s modified Eagle‘s medium , supplemented with 10% fetal bovine serum and 1% antibiotics, namely penicillin and streptomycin . Cells at the 3rd to 6th passage three were used in subsequent experiments.2.6Fourth‐generation FBs were seeded into 6‐well plates for immunocytochemical staining. Briefly, the cells were fixed with 4% paraformaldehyde, permeabilized with 0.3% Triton‐x‐100 at room temperature for 20 min, then blocked with 3% BSA at room temperature for 30 min. Next, they were incubated overnight with primary antibody  at 4 C, washed, then incubated for 1 h with diluted fluorescent secondary antibody  in a wet box. The sections were stained with DAPI for 5 min in the dark, and then incubated with the anti‐fluorescence quenching reagent. The sections were finally dried in the dark, then visualized under an inverted fluorescence microscope.2.74 cells per well), and treated with different arecoline concentrations  (Sorabio). Cell growth was monitored using a Microplate Reader System (Rayto RT‐6100) at 0, 1, 2, 3 and 4 day after treatment.Proliferative activity of the FBs was assessed using the Cell Counting Assay Kit (CCK)‐8 (Dojindo Molecular Technologies), according to the manufacturer's instructions. Briefly, fourth‐generation cells were seeded into a 96‐well plate (1 × 102.8Levels of IL‐13 were quantified in the supernatant from FBs treated with arecoline using the ELISA kit (Zci Bio), following the manufacturer's instructions. Absorbance was measured at 450 nm wavelength using a microplate reader.2.9Cubital venous blood was collected from normal people in an EDTA anticoagulation tube, and peripheral blood mononuclear cells (PBMC) obtained via density gradient centrifugation and cultured in Roswell Park Memorial Institute‐1640 (RPMI‐1640) medium (containing 10% FBS). The next day, the supernatant was discarded and anchorage‐dependent cells were collected. The resulting monocytes were incubated with M‐CSF (PeproTech) for 7 days to obtain differentiated mature macrophages (M0‐phenotype).2.107 cells/mL, then macrophages incubated with FITC anti‐human CD14, PE anti‐human CD68, APC anti‐human CD209, PE anti‐human CD163, Cy5 anti‐human CD206 (BioLegend). Finally, the cells were detected with flow cytometry (Cyto‐Flex Beckman).The supernatant of FBs stimulated by arecoline was used as the conditioned medium for the experimental group whereas the supernatant of FBs without arecoline stimulation was utilized as the conditioned medium for the control group. After 48 h of treatment, the samples were analysed by flow cytometry. Cell density was adjusted to 1 × 102.11t‐test, whereas those among multiple groups were performed using one‐way anova or two‐way anova, followed by Tukey's post hoc test for mean separations. p < 0.05 was considered statistically significant. Figures were generated using Origin version 8.0.All experiments were conducted in triplicates. All statistical analyses were performed using SPSS software (version 25.0), and data were presented as means ± SD. Comparisons between two groups were achieved using the 33.1Bioinformatics analysis results revealed ARG1 was significantly overexpressed in OSF tissues. Figure . ARG1 is3.2n = 10 cases) and OSF tissues at different stages , and found that IL‐13 was significantly upregulated in OSF relative to normal tissue across the stages . Next, we cultured the monocytes in M‐CSF‐containing medium for 7 days to obtain target cells (M0 macrophages). Mature M0‐macrophages were then polarized into M2‐macrophages by induction with conditioned medium Figure . Flow cy3.6To investigate whether IL‐13 secreted by FBs under arecoline treatment can induce changes in polarization of macrophages, we first stimulated FBs with arecoline for 3 days, centrifuged the cells to obtain a supernatant for use as a conditioned medium. Next, we co‐cultured this medium with M0‐macrophages, with supernatant without arecoline used as a control group. Results revealed a slightly higher proportion of CD163 cells in the experimental (52.00%) than in the control group (46.77%). Similarly, more CD206 cells were recorded in the experimental (52.38%) than control group (46.94%). A similar trend was also observed with regard to CD209 cells, 51.92% and 46.78% in the experimental and control groups, respectively Figure . These d4The Results of the present study revealed that M2‐macrophages and IL‐13 were overexpressed in human OSF specimens relative to normal tissues. Notably, arecoline causes FBs to produce IL‐13, which subsequently induces polarization of M0‐macrophages into M2‐macrophages, thereby affecting occurrence and development of OSF. Macrophages are immune cells with multiple functions. For example, they are not only important targets for studying cellular phagocytosis, cellular immunity and molecular immunology, but are also involved in tissue inflammation and post‐repair.The IL‐13 cytokine is an important factor in polarization of M2 macrophages. Based on our results, we speculate that the high expression of M2‐macrophages in OSF is due to upregulation of IL‐13 cytokines. Previous studies have reported that IL‐13 is highly expressed in lungs of patients with progressive fibrosing interstitial lung diseases.At present, most scholars believe that arecoline is the main cause of OSF. Arecoline stimulates the oral mucosa to induce secretion of numerous cytokines, ECM and collagen, thereby resulting in excessive collagen synthesis and reduced degradation. This imbalance is caused by fibrous key conditions for the transformation.Next, we investigated whether IL‐13 secreted by FBs would induce changes to polarization of macrophages under the arecoline. To this end, we stimulated FBs with arecoline, then co‐cultured the supernatant (at this time considered conditioned medium), with M0‐macrophages. Results revealed that CD163, CD206 and CD209 were all upregulated, which is consistent with previous studies and is in line with our conjecture at the time.In summary, we investigated the mechanism underlying the role of IL‐13 in M2‐macrophages and OSF progression. Our results demonstrated that arecoline can regulate IL‐13 cytokines produced by FBs and activates the transformation of polarized M0‐macrophages into M2‐macrophages. This result show that IL‐13 may be involved in the OSF pathogenesis.Junhui Huang: Conceptualization (lead); data curation (lead); investigation (lead); project administration (lead); resources (lead); validation (lead); writing – original draft (lead); writing – review and editing (lead). Liping Wang: Conceptualization (lead); data curation (lead); formal analysis (lead); funding acquisition ; investigation (lead); methodology (lead); resources (lead); software (lead); supervision (lead); validation ; writing – original draft (lead); writing – review and editing (lead). Zhangui Tang: Funding acquisition (lead); resources ; supervision (lead).The authors report no conflicts of interest.


Background: Potential novel strategies for adverse event (AE) management of osimertinib therapy, including therapeutic drug monitoring and the use of biomarkers, have not yet been fully investigated. This study aimed to evaluate (1) the relationship between exposure to osimertinib, especially its active metabolites (AZ5104 and AZ7550), and AEs, and (2) the relationship between germline polymorphisms and AEs. Methods: We conducted a prospective, longitudinal observational study of 53 patients with advanced non-small cell lung cancer receiving osimertinib therapy from February 2019 to April 2022. A population pharmacokinetic model was developed to estimate the area under the serum concentration–time curve from 0 to 24 h (AUC0–24) of osimertinib and its metabolites. Germline polymorphisms were analyzed using TaqMan® SNP genotyping and CycleavePCR® assays. Results: There was a significant association between the AUC0–24 of AZ7550 and grade ≥ 2 paronychia (p = 0.043) or anorexia (p = 0.011) and between that of osimertinib or AZ5104 and grade ≥ 2 diarrhea . Furthermore, the AUC0–24 of AZ5104 was significantly associated with any grade ≥ 2 AEs (p = 0.046). EGFR rs2293348 and rs4947492 were associated with severe AEs , and ABCG2 rs2231137 and ABCB1 rs1128503 were associated with grade ≥ 2 AEs . Conclusion: Higher exposures to osimertinib, AZ5104, and AZ7550 and polymorphisms in EGFR, ABCG2, and ABCB1 were related to higher severity of AEs; therefore, monitoring these may be beneficial for osimertinib AE management.The online version contains supplementary material available at 10.1007/s10637-023-01328-9. EGFR T790M mutation, but the indication was extended to include it as a first-line treatment and adjuvant therapy after tumor resection [Osimertinib, a third-generation epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitor (TKI), is a first-line treatment for patients with advanced EGFR-positive non-small cell lung cancer (NSCLC) . It has esection –6. ThereN-methyl, whereas AZ7550 is produced by demethylation of the osimertinib terminal amine [Therapeutic drug monitoring (TDM) and the use of biomarkers can be novel strategies for AE management. The potential benefits of TDM in TKI treatments have been suggested , and osial amine . Both acal amine , 10. ThuEGFR, breast cancer resistance protein (BCRP/ABCG2), drug transporter P-glycoprotein (MDR1/ABCB1), and metabolism-related genes  are associated with the occurrence of AEs or pharmacokinetics (PK) of the first- and second-generation EGFR-TKIs  [EGFR, is a substrate of ABCG2 and ABCB1, and is metabolized by cytochrome P450, which requires electron transfer via POR [Some germline polymorphisms in the target fatinib) –20. Thes via POR .EGFR, ABCG2, ABCB1, or POR have a significant impact on the AEs of first- and second-generation EGFR-TKIs [While there have been reports on the association between exposure to osimertinib parent compound and its efficacy/safety , 21, no GFR-TKIs –20, but This study aimed to evaluate (1) the exposure–toxicity relationship and (2) the association of germline polymorphisms with osimertinib AEs to provide evidence for safe treatment and quality-of-life improvement for patients with NSCLC treated with long-term administration of osimertinib.EGFR-mutation-positive NSCLC aged ≥ 20 years who were orally administered osimertinib (standard dose: 80 mg tablet/day) were included in this study. The inclusion criteria did not restrict the type of EGFR mutation, disease or treatment history, or line of treatment. Patients who were mentally or physically incapable of providing informed consent were excluded from the study. The protocol of this study was reviewed and approved by the ethics committees of Ageo Central General Hospital , Keio University School of Medicine , and Keio University Faculty of Pharmacy , and written informed consent was obtained from all participants. The study was conducted with adherence to the Declaration of Helsinki.This prospective, longitudinal observational study was designed and conducted at the Ageo Central General Hospital from February 2019 to July 2020 and Keio University Hospital from June 2020 to April 2022. The primary endpoint was the association of exposures to osimertinib, AZ5104, AZ7550, or germline polymorphisms with AE severity. Patients with AEs were assessed during hospital stays for 3 months or at three outpatient visits, when blood was collected at 2 months or later after the initial osimertinib administration . TheSerum samples for PK analysis and whole peripheral blood samples for genotyping were opportunistically collected  once every 1–2 months after commencing osimertinib therapy. Patients were asked to determine the time of drug intake. The collected serum and whole peripheral blood samples were stored at − 80 °C until analysis.The serum concentrations of the osimertinib parent compound, AZ5104, and AZ7550 were analyzed as previously described . BrieflyEGFR, ABCG2, ABCB1, and POR  were analyzed using TaqMan® probe-based assays , whereas the ABCG2 polymorphism (rs2231137) was studied using the CycleavePCR® assay . The detailed genotyping method is provided in the Online Resource (Appendix A).Polymorphisms in 0–24) of the osimertinib parent compound, AZ5104, and AZ7550, applied as exposure measures. The detailed method for PopPK model development is provided in the Online Resource (Appendix B).A population pharmacokinetic (PopPK) model was developed using Phoenix® NLME™ 8.3 software  to estimate the area under the serum concentration–time curve from 0 to 24 h ; estimates of PopPK parameters are presented as mean . Exposure–toxicity and pharmacogenomics–exposure analyses (comparison of continuous variables) were performed using Mann–Whitney U test. Receiver operating characteristic (ROC) curve analysis was used to evaluate the discrimination potential of AUC0–24 for grade ≥ 2 AEs. Significance of deviation of allele and genotype frequencies from Hardy–Weinberg equilibrium was tested, and pharmacogenomics–toxicity analysis  was performed using Fisher’s exact test. For the pharmacogenomics association analysis, multiple statistical analyses were performed using additive, recessive, and dominant genetic models. All p-values were two-sided, and statistical significance was set at p < 0.05. IBM® SPSS® statistics version 28.0  was used for all the statistical analyses.The cut-off date for data collection was April 4, 2022. Continuous variables such as AUCp = 0.004). Other characteristics, including sex, age, ECOG PS, and somatic EGFR mutation, were not associated with any grade ≥ 2 or ≥ 3 AEs.Patient characteristics are summarized in Table p < 0.05). The PopPK parameters were estimated using models (1), (2), and (3) for osimertinib, AZ5104, and AZ7550, respectively. The estimated values were close to the mean values calculated from the bootstrap sampling of n = 974 , n = 1000 , and n = 1000 , respectively, and all fell within the 95% percentile confidence intervals , , and (3)0–24 at steady state  of the osimertinib parent compound, AZ5104, and AZ7550 were 4278 (3328–5589) ng/mL*h, 414 (309–584) ng/mL*h, and 367 (275–516) ng/mL*h, respectively, regardless of dosage.The median (IQR) values of AUC0–24 of the active metabolite AZ7550 and grade ≥ 2 paronychia or grade ≥ 2 anorexia; AUC0–24 of the osimertinib parent compound or active metabolite AZ5104 and grade ≥ 2 diarrhea; and AUC0–24 of the parent or either of the two active metabolites and grade ≥ 2 increased creatinine. Overall, the AUC0–24 of AZ5104 was significantly associated with any grade ≥ 2 AEs  were 0.680 (51% and 90%), 0.705 (42% and 100%), and 0.651 (49% and 90%), respectively . The frequency of the aforementioned AEs (grade ≥ 2) was higher in patients with ≥ 4938 ng/mL*h parent compound, ≥ 540 ng/mL*h AZ5104, or ≥ 462 ng/mL*h AZ7550 AUC0–24 .The cut-off AUCp > 0.050), except for EGFR rs4947492, EGFR rs2227983, ABCG2 rs2622604, and ABCB1 rs1045642 , but the allele frequency was similar to that reported by Togo Var [All analyzed genotypes were in Hardy–Weinberg equilibrium (EGFR and severe AEs or anorexia. EGFR rs2293348 C > T (C/T genotype) and EGFR rs4947492 G > A (A/A genotype) were both associated with any severe AEs . EGFR rs2293348 C > T (C/T genotype) was also significantly associated with grade ≥ 1 or ≥ 2 anorexia .There was a significant relationship between polymorphisms in germline ABCG2 rs2231137 G > A polymorphism (G/A and A/A genotypes) was significantly associated with both AEs and PK. A higher frequency of any grade ≥ 2 AEs (Table p = 0.008 in a dominant model) was observed in patients with ABCG2 rs2231137 G/A or A/A genotypes. Furthermore, patients with the G/A or A/A genotype had a significantly higher exposure (AUC0–24) to the osimertinib parent compound .The ABCB1 rs1128503 C > T polymorphism (C/T and T/T genotypes) and any grade ≥ 2 AEs (Table p = 0.038 in a dominant model). Additionally, the ABCB1 rs2032582 G > T/A polymorphism (A/T and G/T genotypes) was associated with any grade ≥ 2 skin disorders and grade ≥ 2 lymphocyte count decrease . Polymorphisms in the POR were not significantly associated with any AEs or PK of the drug.A significant association was observed between EGFR, ABCG2, ABCB1, and POR) and the severity of AEs.To the best of our knowledge, this is the first report to evaluate the association between exposures to the two active metabolites of osimertinib (AZ5104 and AZ7550) or germline polymorphisms  and AEs [0–24 of osimertinib at steady state was consistent or slightly lower than that in previous reports because some patients included in our study received a reduced dose [PopPK modeling was performed to estimate the AUC and AEs . The medced dose , 28. Albced dose . C-reactced dose . Decreasced dose –32. TherTo our knowledge, our study is the first to report a PopPK model and a significant covariate (BW) for AZ7550. The BW may have an impact on the clearance of AZ7550 because AZ7550 has a longer half-life than the parent compound and AZ5104 , and greater distribution and accumulation are expected [The exposure–toxicity relationships were different among the three compounds: osimertinib parent, AZ5104, and AZ7550. Exposure to AZ7550 was associated with grade ≥ 2 paronychia and anorexia, both of which are potentially related to direct epidermal or mucosal damage. The mechanisms underlying EGFR-TKI-induced skin disorders, such as paronychia, involve decreased keratinocyte proliferation and increased keratinocyte differentiation at the epidermis, resulting in impaired skin barrier function . HoweverOur results also indicated that exposures to the osimertinib parent compound and AZ5104 were associated with grade ≥ 2 diarrhea and increase in creatinine level. Similarly, a previous report suggested a linear relationship between the exposure to the parent compound and the occurrence of diarrhea , whereas0–24 of the parent compound, AZ5104, and AZ7550, showed low sensitivity but high specificity. Therefore, the AUC0–24 levels may not be an absolute index for any AE prediction, but it may become a useful index to decide whether a patient experiencing AEs needs dose reduction. Since several reports suggested that there is no relationship between exposure to osimertinib and efficacy, dose reduction up to 50% of mean exposure may be considered for patients experiencing AEs and high AUC0–24 levels; however, further validation is needed [Overall, exposure to AZ5104 was significantly associated with any grade ≥ 2 AEs; the exposure to AZ5104 showed a higher area under the curve in ROC analysis than that to osimertinib parent compound and AZ7550. Likewise, an earlier study suggested an absence of a relationship between the trough concentration of the osimertinib parent compound and any toxicity ; thus, ms needed , 40, 42.EGFR, rs2293348 C > T (C/T genotype) and rs4947492 G > A (A/A genotype), were associated with severe AEs. According to earlier studies, EGFR rs2293348 is related to erlotinib-induced rash, and rs4947492 is related to gefitinib-induced diarrhea [EGFR rs2293348 and rs4947492 may influence sensitivity to EGFR inhibition and severity of AEs.The two intron variants in diarrhea , 19. Thediarrhea . Thus, EABCG2 rs2231137 G > A (G/A and A/A genotypes) and ABCB1 rs1128503 C > T (C/T and T/T genotypes) were significantly associated with any grade ≥ 2 AEs, and ABCB1 rs2032582 G > T/A polymorphism (A/T and G/T genotypes) was significantly associated with any grade ≥ 2 skin disorders. Osimertinib is a substrate of ABCG2 and ABCB1; thus, polymorphisms in these genes may influence the distribution or PK of this drug [ABCG2 rs2231137 G > A (G/A and A/A genotypes) results in Val12Met substitution and is partly responsible for the functional impairment of ABCG2. The association of this variant with gefitinib-induced rash and the PK of gefitinib has been reported [ABCB1 polymorphisms (rs1128503 and rs2032582) were associated with grade ≥ 2 AEs but not with the serum concentration of osimertinib. We hypothesized that ABCB1 polymorphisms may influence the tissue distribution and accumulation of osimertinib and its active metabolites, as an in vivo study suggested the involvement of ABCB1 and ABCG2 in tissue accumulation of other TKIs [The germline polymorphisms in his drug . ABCG2 rreported , 45, whiher TKIs .EGFR, ABCG2, and ABCB1 are potential new approaches for AE management. AEs can be effectively managed without dose interruption by adjusting the dose and increasing awareness about the need for AE management. The AEs we focused on in this study, such as paronychia, anorexia, and diarrhea, are not fatal but need to be managed to improve quality of life and encourage patients to continue osimertinib therapy for a long period.Taken together, our results suggested that monitoring exposure to the parent compound, AZ5104, and AZ7550 and genotyping polymorphisms in max) for PopPK analysis. Additional blood sampling is required to improve the accuracy of the volume of distribution estimate, but this was not essential for the purpose of this study. The exposure–efficacy relationship was not analyzed in this study because progression-free survival was not reached for many of the participants at the time of data cut-off. Although many reports have suggested that there is no relationship between osimertinib exposure and efficacy, further studies are needed to identify the optimal therapeutic window for osimertinib treatment.This study has several limitations to consider when interpreting the results. Because of the small sample size, we were unable to perform a multivariable analysis to compare the impact of multiple risk factors or check for potential confounding variables. A larger sample size is also required to evaluate the relationship between fatal or severe AEs (grade ≥ 3) and exposure to osimertinib or its active metabolites. Opportunistic collection of serum samples reduced the burden on patients but led to there being fewer concentration data points around the time of peak serum concentration (TEGFR (rs2293348 and rs4947492), ABCG2 (rs2231137), and ABCB1 (rs1128503 and rs2032582) were identified as potential biomarkers for predicting the severity of AEs and may help increase awareness of the importance of AE management for patients at higher risk.Our findings demonstrated for the first time that exposures to the two active metabolites of osimertinib (AZ5104 and AZ7550) were associated with AEs and may have a different impact than exposure to the osimertinib parent compound. Therefore, monitoring not only the parent compound but also the active metabolites is a potential approach for osimertinib AE management. Germline polymorphisms in Below is the link to the electronic supplementary material.Supplementary Material 1