We investigated the contribution of age, coexisting medical conditions, sex, and vaccination to incidence of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection and of severe, critical, or fatal COVID‐19 in older adults since pandemic onset.A national retrospective cohort study was conducted in the population of Qatar aged ≥50 years between February 5, 2020 and June 15, 2023. Adjusted hazard ratios (AHRs) for infection and for severe coronavirus disease 2019 (COVID‐19) outcomes were estimated through Cox regression models.Cumulative incidence was 25.01%  for infection and 1.59% (95% CI: 1.55–1.64%) for severe, critical, or fatal COVID‐19 after a follow‐up duration of 40.9 months. Risk of infection varied minimally by age and sex but increased significantly with coexisting conditions. Risk of infection was reduced with primary‐series vaccination  and further with first booster vaccination . Risk of severe, critical, or fatal COVID‐19 increased exponentially with age and linearly with coexisting conditions. AHRs for severe, critical, or fatal COVID‐19 were 0.86 (95% CI: 0.7–0.97) for one dose, 0.15 (95% CI: 0.13–0.17) for primary‐series vaccination, and 0.11 (95% CI: 0.08–0.14) for first booster vaccination. Sensitivity analysis restricted to only Qataris yielded similar results.Incidence of severe COVID‐19 in older adults followed a dynamic pattern shaped by infection incidence, variant severity, and population immunity. Age, sex, and coexisting conditions were strong determinants of infection severity. Vaccine protection against severe outcomes showed a dose–response relationship, highlighting the importance of booster vaccination for older adults. Leveraging the national, federated platforms for SARS‐CoV‐2 infection and COVID‐19 vaccination in Qatar, this study aimed to investigate the role of age, coexisting conditions, sex, and vaccination in the incidence of SARS‐CoV‐2 infection and associated severe,While the vulnerability of older individuals to this infection and its more severe forms is well‐established, there remains an inadequate understanding of the interplay 22.1This study investigated the risk of SARS‐CoV‐2 infection and of severe, critical, or fatal COVID‐19 in the population of Qatar ≥50 years of age between February 5, 2020, the earliest record for a SARS‐CoV‐2 test in the country, and June 15, 2023. It analyzed the national, federated databases for COVID‐19 laboratory testing, vaccination, hospitalization, and death, retrieved from the integrated, nationwide, digital‐health information platform  tests regardless of location or facility and, from January 5, 2022, all medically supervised rapid antigen tests Section . SARS‐CoThe national mortality database was used to obtain data on all‐cause mortality, including deaths occurring at healthcare facilities and elsewhere.2.2We conducted a retrospective cohort study to investigate incidence and risk factors for SARS‐CoV‐2 primary infection and associated severe, critical, or fatal COVID‐19 in the national cohort of individuals ≥50 years of age. All individuals ≥50 years of age at the start of the study on February 5, 2020 were eligible for inclusion. Individuals were followed until their first documented SARS‐CoV‐2 infection (regardless of symptoms), or death, or administrative end of follow‐up .Incidence of documented infection was defined as the first documented PCR‐positive or rapid‐antigen‐positive test after the start of follow‐up, regardless of symptoms. Infection severity was classified following World Health Organization guidelines for COVID‐19 case severity ,2.3The institutional review boards at Hamad Medical Corporation and Weill Cornell Medicine–Qatar approved this retrospective study with a waiver of informed consent. The study was reported according to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines Table .2.4stptime command.The cohort was described using frequency distributions and measures of central tendency. Cumulative incidence of documented infection, defined as the proportion of individuals at risk, whose primary endpoint during follow‐up was a documented infection , was estimated using the Kaplan–Meier estimator method. Incidence rate of infection (and of severe COVID‐19 outcomes), defined as the number of identified infections (or severe COVID‐19 outcomes) divided by the number of person‐years contributed by all individuals in the cohort, was estimated, with the corresponding 95% confidence interval (CI), using a Poisson log‐likelihood regression model with the Stata 18.0 Hazard ratios (HRs), comparing incidence of infection across 5‐year age groups, number of coexisting conditions , sex, and vaccination dose status, along with the corresponding 95% CIs, were calculated using multivariable Cox regression models. HRs were further adjusted for 10 nationality groups and testing rate. Low, intermediate, and high testers were defined as individuals with <1, 1–3, and ≥4 tests per person‐year, respectively, during follow‐up. To account for changes in vaccination status over time, vaccination was included in all models as a time‐varying covariate. Standard errors were adjusted for clustering effects. Interactions were not investigated.The study analyzed infections and severe COVID‐19 outcomes that occurred in Qatar. However, certain outcomes might have occurred outside Qatar when expatriates were traveling abroad or permanently left the country after the follow‐up started. Consequently, an additional complete set of study results was generated through a sensitivity analysis restricted only to Qataris, thereby excluding all expatriates. The objective was to assess whether the travel or departure of expatriates from the country could have introduced bias that influenced the study's findings. Statistical analyses were performed using Stata/SE version 18.0 .33.1Figure 3.2The majority of the cohort was followed until the conclusion of the study, covering a median follow‐up duration of 40.9 months, with an interquartile range (IQR) of 35.2–40.9 months  by the end of the study at the 40.9‐month mark since the start of follow‐up Figure . In addiThe onset of the omicron wave led to a very rapid increase in the cumulative incidence of infection, reaching 19.93% (95% CI: 19.80–20.07%) within only one month (at the 24‐month mark). Cumulative incidence continued to increase thereafter, but at a slower pace. The incidence rate of infection throughout the duration of follow‐up was estimated at 86.14 (95% CI: 85.57–86.72) per 1000 person‐years. Similar results were found in the sensitivity analysis restricted only to Qataris Figure .3.4The cumulative incidence of severe, critical, or fatal COVID‐19 reached 1.59% (95% CI: 1.55–1.64%) by the end of the study at the 40.9‐month mark since the start of follow‐up Figure . Before Despite the onset of the omicron wave leading to a very large surge in the incidence of infection Figure , the ris3.5Figure 3.6Figure Notably, women had a substantially lower incidence of severe, critical, or fatal COVID‐19 compared with men. Number of vaccine doses showed a significant association with a reduced incidence of severe, critical, or fatal COVID‐19. In comparison with the unvaccinated group, the AHR was 0.86 (95% CI: 0.7–0.97) for individuals who received only one dose, 0.15 (95% CI: 0.13–0.17) for those who received primary‐series vaccination, and 0.11 (95% CI: 0.08–0.14) for those who received a first booster vaccination. The sensitivity analysis restricted only to Qataris demonstrated largely similar findings Figure .4Incidence of severe COVID‐19 among older adults varied throughout the pandemic reflecting differences in infection incidence Figure , severitSevere forms of COVID‐19 were strongly associated with age and number of coexisting conditions among older individuals. Even minor differences in age led to an exponential increase in the risk of severe COVID‐19. Severe COVID‐19 increased proportionally with the number of existing conditions. These findings align with the widely observed global patterns, highlighting the roles of age and underlying health conditions in infection progression to severe COVID‐19 among older individuals.Women were considerably less likely to progress to severe COVID‐19 than men, even after adjustment for the effects of age and coexisting conditions. This is consistent with global evidence and may reflect biological differences between men and women that extend beyond underlying health conditions.As expected, vaccination provided strong protection against severe COVID‐19 in older adults, retaining its effectiveness over a span of approximately three years of follow‐up. The observed pattern indicated a dose–response relationship where a higher number of vaccine doses elicited greater protection. While affirming the protective effects of vaccination within this populationAlthough some disparities in infection risk based on age, sex, and the number of coexisting conditions were observed, most of these differences were modest and could pose challenges for interpretation. These differences could stem from various factors, including variations in social networks, which might differ significantly with age among older adults because of retirement or reduced mobility and functionality, as well as frailty. These differences may also reflect variations in health‐seeking behaviors, beyond the controlled factor of testing frequency considered in this analysis.Despite a protective effect for vaccination against infection, the magnitude of protection was notably much smaller (over the entire time of follow‐up) compared with that against severe COVID‐19. This divergence can be attributed to the rapid waning of vaccine protection against infection, which lasts for only a few months after the last dose,This study has limitations. The study analyzed infection and COVID‐19 outcomes that occurred in Qatar, but some outcomes may have occurred outside Qatar, while expatriates were traveling abroad, or if they have left Qatar permanently because of end of employment or other reasons after initiation of follow‐up. Travel data were not available to factor in our analysis. With the restrictions on travel and international recruitment during the pandemic, such movements in and out of the country were probably limited in scale in the early phases of the pandemic but increased with time as restrictions were gradually lifted. Mid to end of 2022 in particular, was a time during which such migration movements have increased substantially as some expatriates may have left Qatar with the end of World Cup 2022 projects. Such migration movements could potentially introduce bias that affect the results because of differential loss of follow‐up for expatriates compared with Qataris. To investigate effect of this bias, we generated a complete set of study results for only Qataris, and these confirmed similar findings, suggesting that this bias may not have appreciably affected the findings. There were only small differences, and these affected only the effect sizes and not direction of effects between the results with and without inclusion of expatriates.As an observational study, unmeasured or uncontrolled confounding cannot be excluded. While we adjusted for several factors in our analyses, other factors were not available to adjust for. The study approach was to investigate broad effects over the entire duration of follow‐up, but the effect of confounding factors may have varied with calendar time, thereby potentially introducing bias. For example, having one dose of vaccination was associated with slightly higher risk of infection than no vaccination. However, this effect is likely to reflect uncontrolled bias arising from the temporal effect of most individuals receiving their first dose during a time of high infection incidence, specifically during the alpha and beta waves.The study analyzed documented infections, but some infections may have gone undocumented, particularly after the major reduction in testing that occurred starting from November 1, 2022.COVID‐19 severity in Qatar's population was relatively low, but this finding may not be generalizable to other countries. Qatar, with its high human development index,While these limitations may affect some of the results relating to infection, they are less likely to affect the results relating to severe COVID‐19, as severe COVID‐19 cases are not likely to be undocumented and COVID‐19 severity was assessed using the standardized WHO classification of COVID‐19 severity,In conclusion, incidence of severe COVID‐19 among older adults in Qatar displayed a dynamic pattern throughout the pandemic, influenced by infection rates, variant severity, and population immunity. The vast majority of severe cases occurred prior to the conclusion of the first omicron wave, with a major subsequent decline in incidence because of the rapid accumulation of natural immunity during the first omicron wave, as well as gradual improvements in vaccine coverage and case management. Age and number of coexisting conditions were identified as strong determinants of severe COVID‐19 risk among older adults, with even minor differences having a significant impact on progression from infection to severe COVID‐19. Despite the rapid waning of vaccine protection against infection, vaccination emerged as a critical protective measure against severe outcomes, maintaining its effectiveness over three years and demonstrating a clear dose–response relationship with the number of doses administered. These findings emphasize the importance of booster vaccination in mitigating the impact of predisposing factors for severe COVID‐19 in older adults.Mai A. Mahmoud: Conceptualization; data curation; methodology; writing—original draft; writing—review and editing. Houssein H. Ayoub: Data curation; writing—review and editing. Peter Coyle: Data curation; investigation; writing—review and editing. Patrick Tang: Data curation; investigation; writing—review and editing. Mohammad R. Hasan: Data curation; investigation; writing—review and editing. Hadi M. Yassine: Data curation; investigation; writing—review and editing. Asmaa A. Al Thani: Data curation; investigation; writing—review and editing. Zaina Al‐Kanaani: Data curation; writing—review and editing. Einas Al‐Kuwari: Data curation; writing—review and editing. Andrew Jeremijenko: Data curation; writing—review and editing. Anvar Hassan Kaleeckal: Data curation; writing—review and editing. Ali Nizar Latif: Data curation; writing—review and editing. Riyazuddin Mohammad Shaik: Data curation; writing—review and editing. Hanan F. Abdul‐Rahim: Data curation; writing—review and editing. Gheyath K. Nasrallah: Data curation; writing—review and editing. Mohamed Ghaith Al‐Kuwari: Data curation; writing—review and editing. Adeel A. Butt: Data curation; writing—review and editing. Hamad Eid Al‐Romaihi: Data curation; writing—review and editing. Mohamed H. Al‐Thani: Data curation; writing—review and editing. Abdullatif Al‐Khal: Data curation; writing—review and editing. Roberto Bertollini: Data curation; writing—review and editing. Laith J. Abu‐Raddad: Conceptualization; data curation; methodology; project administration; supervision; writing—original draft; writing—review and editing. Hiam Chemaitelly: Conceptualization; data curation; formal analysis; methodology; writing—original draft; writing—review and editing.Dr. Butt has received institutional grant funding from Gilead Sciences unrelated to the work presented in this paper. Otherwise, we declare no conflict of interest.https://www.webofscience.com/api/gateway/wos/peer-review/10.1111/irv.13224.The peer review history for this article is available at Hamad Medical Corporation and Weill Cornell Medicine‐Qatar Institutional Review Boards approved this retrospective study with a waiver of informed consent.TABLE S1. STROBE checklist for cohort studies.Table S2. Baseline characteristics of Qatari participants.Figure S1. Daily count of newly diagnosed SARS‐CoV‐2 infections between February 5, 2020 and June 15, 2023.Figure S2. Cumulative incidence of A) SARS‐CoV‐2 infection and B) severe, critical, or fatal COVID‐19 disease among Qataris over the duration of the study.Figure S3. Adjusted hazard ratios against SARS‐CoV‐2 infection among Qataris across A) age, B) number of coexisting conditions, C) sex, and D) vaccination dose status.Table S3. Adjusted hazard ratios against SARS‐CoV‐2 infection and against severe, critical, or fatal COVID‐19 disease among Qataris across age, number of coexisting conditions, sex, and vaccination status.Figure S4. Adjusted hazard ratios against severe, critical, or fatal COVID‐19 disease among Qataris across A) age, B) number of coexisting conditions, C) sex, and D) vaccination dose status.SECTION S1. Study population and data sources.SECTION S2. Laboratory methods and variant ascertainmentReal‐time reverse‐transcription polymerase chain reaction testing.Rapid antigen testingClassification of infections by variant typeSECTION S3. COVID‐19 severity, criticality, and fatality classificationSevere COVID‐19Critical COVID‐19Fatal COVID‐19SECTION S4. Phases of the COVID‐19 pandemicSECTION S5. Comorbidity classificationClick here for additional data file.


MET is a notable driver gene in the diversity of aberrations with clinical relevance, including exon 14 skipping, copy number gain, point mutations, and gene fusions. Compared with the former two, MET fusions are severely under‐reported, leaving a series of unanswered questions. In this study, we addressed this gap by characterizing MET fusions in a large, real‐world Chinese cancer population.MET fusion‐positive (MET+) patients were subsequently selected for clinical and molecular characterization.We retrospectively included patients with solid tumors who had DNA‐based genome profiles acquired through targeted sequencing from August 2015 to May 2021. MET fusions from 122 patients, resulting in an overall prevalence of 0.15%. Lung cancer comprised the majority of MET+ patients . Prevalence was markedly higher in liver cancer, biliary tract cancer, and renal cancer (range 0.52%–0.60%). It was lower in ovarian cancer (0.06%). A substantial proportion  of unique partners were reported for the first time. High heterogeneity was observed for partners, with ST7, HLA‐DRB1, and KIF5B as the three most common partners. Mutational landscape analysis of lung adenocarcinoma (n = 32) revealed a high prevalence of TP53 in MET+ alterations, EGFR L858R, EGFR L861Q, and MET amplification.We screened 79,803 patients across 27 tumor types and detected 155 putative MET fusions. Our findings warrant that further clinical validation and mechanistic study may translate into therapeutic avenues for MET+ cancer patients.To our knowledge, this is currently the largest study in characterizing  MET fusions are clinically relevant in that it results in constitutive MET activation, thereby promoting oncogenesis or therapeutic resistance.MET fusions is mostly derived from three studies, which identified 2  MET fusions in lung adenocarcinoma,MET fusions.MET fusions, which involved 58 unique partners, 48 of which reported for the first time. Subsequent characterization revealed the genomic landscape of these fusions and MET fusion‐positive lung adenocarcinoma cases. We also highlight the therapeutic relevance of MET fusions for targeted therapy with select LC cases.Herein, we report a retrospective study that screened 79,803 patients and identified 155 putative 22.1MET fusions and analyzed the clinical and molecular characteristics of the MET fusion‐positive patients. The study was approved by the institutional review board of Tianjin Medical University Cancer Hospital and Institute. Patients with solid tumors who had available genome profiles acquired through targeted sequencing from August 2015 to May 2021 were retrospectively included. There was no preselection based on tumor type, histologic subtype, age, sex, clinical stage, or sample type. A total of 79,803 patients were screened, corresponding to 41,404 tumor tissue samples, 35,770 plasma, 2,242 pleural effusion, and 387 cerebrospinal fluid. In this work, only one sample of each patient was included. After we reviewed the sample records, several patients had two or more types of samples or had more than two specimens with the same sample type . For those who had two or more types of samples, only the tissue sample was included. For those who had more than two specimens with the same sample type, only the sample detected the first time was included. Genomic profiling was performed with hybrid capture‐based next‐generation sequencing (NGS) using panels targeting 8, 41, 68, 108, 168, or 520 cancer‐related genes (Burning Rock Biotech). These panels were designed and validated for the identification of base substitutions, insertions, deletions, copy number variations (CNV), and gene fusions.This study screened the genomic profiles of patients with solid tumors for 2.2All wet‐lab procedures were performed at a College of American Pathologists (CAP)‐ and Clinical Laboratory Improvement Amendments (CLIA)‐certified clinical diagnostic laboratory (Burning Rock Biotech). Briefly, DNA from tumor tissues was extracted with a QIAamp DNA tissue kit, and cell‐free DNA from liquid biopsies was extracted with a QIAamp Circulating Nucleic Acid kit (Qiagen). DNA library construction and targeted sequencing with a commercial panel of 8, 41, 68, 108, 168, or 520 genes (Burning Rock Biotech) were performed as previously described.2.3MET fusions were investigated in 27 MET fusion‐positive lung adenocarcinoma (LUAD) patients who underwent targeted sequencing using a 168‐ or 520‐gene panel. In addition, the concurrent lung cancer driver alterations with MET fusions were also investigated in 32 MET+ LUAD patients who underwent targeted sequencing using panels targeting 8, 41, 68, 108, 168, or 520 cancer‐related genes. These panels included eight identical genes, also known as classic lung cancer oncogenes, including EGFR, KRAS, BRAF, ALK, ROS1, MET, RET, and ERBB2.All the reads were mapped to the human genome (hg19) with Burrows–Wheeler Aligner (BWA).2.4MET fusion‐positive patients. Wilcoxon signed‐rank test was used to compare the central tendency of a continuous variable, such as TMB, between two groups. All tests were two‐sided with a significance level set at p < 0.05.All statistical analyses were performed using the R programming language. Chi‐square or Fisher's exact test was used to compare between two groups in the proportions of values of a nominal variable, such as percentage of 33.1MET fusions events were identified in 122 patients (151 samples), resulting in an overall prevalence of 0.15% (122/79803).In this study, we retrospectively screened 79,803 patients with solid tumors who had DNA‐based genomic profiles acquired with panel‐based targeted sequencing. A total of 155 putative MET fusions (hereafter referred to as MET+) across cancer types. LC represents the largest subset , followed by colorectal cancer . These two cancer types showed similar prevalence rates of MET fusions (0.16% and 0.19%), which were comparable with overall prevalence. Although liver cancer (n = 3), biliary tract cancer , and renal cancer (n = 2) patients showed higher prevalence ranging from 0.52% to 0.60%, ovarian cancer  showed a markedly lower rate at 0.06%, these results may be artifacts due to the small number of MET+ patients. Pairwise comparison between different tumor types revealed no significant difference in prevalence levels  were women. Gender information was not documented for the remaining six cases (n = 1.2%). Median age was 58 years with a range of 27–87 years. More than half had stage III disease , followed by stage IV disease .Figure s Figure . Other cCRC, n = 1, 9.0%. 3.2MET+ patient is provided in Table MET was the 3' partner, among whom 21 (17.2%) carried multiple MET fusions, including 12 (9.8%) cases in which MET was also found as a 5' partner, and the remaining 9 patients had >1 (range 2–5) fusions, all of which with MET as the 3' partners. In terms of fusion events, MET was the 3' partner in 99 (63.9%) events and the 5' partner in the remaining 56 , these novel fusions were also identified in CRC (n = 7), BTC (n = 2), liver cancer (n = 2), gastroesophageal cancer , breast cancer (n = 1), pancreatic cancer (1 event), and other cancers (n = 1). A considerable proportion of MET fusions were intergenic . Precise 59 partners were found in nonintergenic fusions, with 76.3% of partners (n = 45) identified only once and 86.4% of partners (n = 51) identified ≤2 times. ST7 stood out as the most common partner occurring in 7 events, followed by HLA‐DRB1 and KIF5B (5 events each), and CAPZA2 and CFTR (4 events each). Notably, all nonintergenic fusions with HLA‐DRB or CAPZA2 had MET at the 3' end and occurred in LC. Fusions with KIF5B were also all detected in LC and had MET as the 3' partner except for one occasion. Besides LC (4 events), ST7‐MET was also present in CRC, OC, and other cancer types (1 event for each). Interestingly, apart from LC (2 events), fusions with CFTR were detected in 1 GEC and 1 breast cancer case in the forms of MET‐CFTR and CFTR‐MET, respectively. Analysis of breakpoint distribution indicated exon 15 as the most common exon  harbored MET exon 14 while most  had intact encoding sequences for MET KD. In addition, we found that 41.7% (50/122) of MET+ patients harbored concurrent MET amplification. The details are summarized in Table The majority  of the n Figure . Figure 3.3MET fusions, we then focused on the 32 MET+ LUAD cases for further characterization  had stage III or IV disease.LUAD was the predominant histologic subtype with n Figure . These pn Figure . SimilarKIF5B, CAPZA2, DOCK4, KCND2, LINC01392, and ST7  harbored MET KD or lacked exon 14  fusions. Excluding 25 intergenic ones, the remaining corresponded to 22 partners, including 15 novel ones. Most partners occurred only once except for 7 Figure . Figure TP53 (74%) and EGFR (63%) had high frequencies, while other drivers, such as ERBB2 (11%), RET (11%), and BRAF (7%), had relatively lower alteration rates. The most common concurrent MET alteration was MET amplification . TP53 aberrations were predominantly point mutations, including 13 (48.1%) missense, 3 (11.1%) nonsense, and 2 (7.4%) frameshift mutations. EGFR alterations included equal numbers of missense mutations and amplification (7 for each) as well as 3 indels and 1 fusion. The alteration frequencies of 8 LC‐associated driver genes were investigated in 32 MET+ LUAD patients who underwent a panel of 8, 41, 68, 108, 168, or 520 genes. KRAS (3%), ALK (3%), and ROS1 (0%) presented with low alteration frequencies  and achieved rapid partial response (PR) but developed brain metastasis 1 year later. Afterward, cabozantinib was started but the patient manifested intracranial progression within 1 month. She then received alectinib and crizotinib plus anlotinib. The patient achieved respective progression‐free survival (PFS) of 3 and 7 months. Genomic profiling 5 months later identified acquired MET Y1230C and Y1230H mutations in addition to HLA–DRB1–MET fusion, suggesting one or both point mutations as a potential mechanism of acquired resistance to crizotinib plus anlotinib.Next, we describe three cases that highlight the diverse therapeutic implications of different y Figure . She begEGFR L858R mutation (abundance: 1.9%). Plasma‐based genome profiling also identified low‐grade MET amplification (copy number: 2.4) and LINC01392‐MET (L2:M15) when the patient was on fourth‐line treatment with osimertinib plus anlotinib  and newly emerged IMMP2L‐MET (I4:M3) at low abundance. The patient progressed another 3 months later with the best response of PR. Whether one or both of the fusions were resistant to crizotinib and contribute to disease progression was unclear.The second patient was a 49‐year‐old woman (P13) with stage III LUAD positive for b Figure . She recKIF5B‐MET (K24:M15)‐positive LUAD resistant to second‐line crizotinib, as indicated by rapid progression within 2 months, which contrasted with previous report of durable response (10 months) to crizotinib in a patient with stage IV LUAD harboring KIF5B‐MET (K24:M14). Together, these cases demonstrated heterogeneity in the response to multi‐kinase and selective MET‐TKIs among carriers of different MET fusions.In the third highlighted case, a 62‐year‐old woman (P107) had a 4MET was first identified as part of an oncogenic gene arrangement with TRP,MET fusions and their therapeutic implications have been largely ignored. In this study, we addressed this challenge with a large‐scale screening of 79,803 patients across 27 tumor types, which led to the detection of 155 putative MET fusions from DNA‐based genomic profiles of 122 patients. Subsequent analyses answered fundamental questions such as prevalence rates in different tumor types, whether the fusions were enriched in any of these tumors, percentage of MET as the 3' partner and carriers of multiple fusions, location of the MET sequence, and breakpoints and partners. Notably, this study also identified 48 novel partners, which provided candidates for preclinical research into their biology and potential as drug targets. In terms of cancer types, LC patients represented the largest MET+ population  and LUAD as the largest histologic subtype . Analysis of the mutational landscape of MET+ LUAD revealed a prevalence of altered TP53 or EGFR much higher than those of other genes and found MET amplification, EGFR L858R, and EGFR L861Q as frequently concurrent aberrations.Although MET amplification and exon 14 skipping alterations are well‐known oncogenic drivers in multiple cancer types. A number of previous studies on the prevalence and clinicopathological characteristics of MET amplification/exon 14 skipping alterations in solid cancers across countries have been documented.MET fusions are poorly defined. To our knowledge, studies on MET fusions in large cohorts of tumors are scarce. Pekova et al. have reported EML4‐MET occuring in a pediatric papillary thyroid carcinoma patient  from a large cohort.EML4‐MET was detected in a stage IV CRC patient . A recent study by Yang et al. has revealed MET fusions in solid tumors from a multicenter study in China, indicating its incidence with 0.34% (37/10882) across cancer types and 0.07% (4/5835) in LC,MET fusions, including COMETT (LINC01510)‐MET, PRKAR1A‐MET, and SEMA3D‐MET, detected in LC and validated by RNA‐sequencing in Yang's work,MET fusions (COMETT (LINC01510)‐MET and PRKAR1A‐MET) were also detected in LC in the present work.MET fusions in various cancer types. Prevalence was 0.15% overall and ranged from 0.06% to 1.38% across tumor types. LC, CRC, breast cancer, and GEC each had more than 2,000 screened patients and showed similar, relatively low rates. In contrast, BTC, liver cancer, and renal cancer, all with <500 screened patients, showed markedly higher rates, which may or may not be an artifact due to the small sample size and warrants further investigation. Pairwise Fisher's exact test showed no significant difference among the tumor‐specific prevalence rates  events. In stark contrast, in a study of NSCLC patients confirmed to be ALK‐positive via immunohistochemistry and fluorescence in situ hybridization, those carrying fusions with one of the three most common partners  constituted 86.1% of (136/158) cases.RET‐positive cancer patients showed that 74% of fusions involved KIF5B, CCDC6, or NCOA4.MET was similar to NTRK in that both fusions were rare  and demonstrated no marked partner preference. In a similar study of NTRK fusions in cancer patients, those harboring fusions with any of the 3 most frequent partners ETV6, TPM3, and LMNA comprised 22.3% (198/889) of all NTRK‐positive cases, a percentage closer to our observation with MET .Our analysis revealed substantial heterogeneity in TP53 alterations in MET+ LUAD, which amounted to 74.1% (20/27). In comparison, TP53 has altered in 52.3% of (296/566) LUAD cases in The Cancer Genome Atlas databaseMET+ LUAD cases. This finding warrants further validation and may provide alternative therapeutic targets for MET+ LUAD patients. MET fusions are prohibitively rare for clinical trials of a MET‐altered cohort and as a result, no such trial has been reported to date.One interesting observation was the high frequency of MET as the 3' partner, involving 5' partners actionable targets such as protein kinase A (PRKAR1A),TLK2),LRIGDOCK4,DIXDC1YEATS2 .MET+ cancers. Also noteworthy were the fusions with MET as the 5' partner. The putative protein products may not undergo dimerization and subsequent MET transactivation and yet still be clinically relevant, as suggested by an interesting case report of MET‐UBE2H as a mechanism of acquired EGFR resistance in LC.Our findings also provided candidates for a mechanistic study that may translate into therapeutic inventions. Of the 58 unique fusion partners identified in our study, 48 were novel. Importantly, among the corresponding fusions, 13 were in‐frame with KD‐intact MET exon 14 may result in elevated oncogenic activity of the chimeric protein. For instance, our third highlighted case and a previously reported oneKIF5B), and regimen, although the former lacked MET exon 14. Nonetheless, the two cases showed vastly different responses to crizotinib as the former had a PFS of 2 months with best response of stable disease, while the response lasted for 10 months for the patient whose KIF5B‐MET included exon 14. This contrast was consistent with the observation that the prognosis for patients with MET exon 14 skipping was generally worse compared with MET‐amplified NSCLC.In addition to partners, breakpoints that result in the inclusion of MET fusions and heterogeneity of partners and breakpoint require large cohort sizes for high‐confidence characterization. Second, although this study is to date the largest effort in this field, MET+ patients were still scarce except in LC, which limited the depth of insights gained from the remaining tumor types. Third, MET fusions were identified from DNA‐based genomic profiles and were not validated on the mRNA or protein level. Therefore, the putative fused genes reported in our study will need further validation on the RNA and/or protein level. Fourth, the therapeutic data of most enrolled patients were not available. Therefore, it is challenging to determine whether the MET fusion is a primary or acquired event. The study could benefit from more detailed clinical information, especially those regarding treatment and response/progression, which could have led to the characterization of drug efficacy for different MET fusions and potential resistance mechanisms of MET+ patients.This study was limited by several factors. First, the low prevalence of 5MET fusions. Our findings provide insights into the structure, partner distribution, and concurrent genomic alterations of MET fusions. This study warrants further clinical validation and mechanistic investigations that may translate into therapeutic avenues for MET+ cancer patients.To our knowledge, this study is currently the largest in characterizing Hui Xia: Conceptualization ; data curation ; formal analysis ; writing – original draft ; writing – review and editing . Junhua Zhang: Conceptualization ; data curation ; formal analysis ; writing – original draft ; writing – review and editing . Tong Chen: Data curation . Mingzhao Wang: Data curation . Dongna Chen: Data curation . Tongguo si: Data curation ; project administration ; writing – review and editing . Yutao Liu: Data curation ; project administration ; writing – review and editing .This study was supported by the Translational research project of the Medical Oncology Key Foundation of Cancer Hospital Chinese Academy of Medical Sciences (CICAMS‐MOTRP2022002) and the Beijing Medical Award Foundation (YXJL‐2020‐0785‐1174).The authors have no conflict of interest to declare.All procedures performed in studies involving human participants were in accordance with the ethical standards of the Institutional Review Board of Tianjin Medical University Cancer Hospital and Institute and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.All patients had provided written informed consent for participating in the study.Figure S1.Click here for additional data file.Table S1.Click here for additional data file.Table S2.Click here for additional data file.Data S1.Click here for additional data file.


Serum folate is considered a biomarker of chronic enteropathy (CE) in dogs, but few studies have examined associations with markers of CE.To evaluate serum folate concentrations in dogs with and without CE and associations with sample hemolysis and selected markers of CE. We hypothesized that hypofolatemia would be more common in dogs with CE and associated with hypocobalaminemia, higher CIBDAI, and hypoalbuminemia.Six hundred seventy‐three dogs with available serum folate measurements performed at an academic veterinary hospital between January 2016 and December 2019.Medical records were retrospectively reviewed to categorize cases as CE or non‐CE and record clinical details and laboratory markers. Relationships between serum folate, cobalamin, and CE variables were assessed using chi‐square, Kruskal‐Wallis, or Spearman's correlation tests.P = .75). In the CE subset, serum folate and cobalamin concentrations were positively associated . However, serum folate concentrations  were higher , non‐CE: 10.4 ; P = .04) and cobalamin concentrations were lower , non‐CE: 550 ; P = .001) in the CE vs non‐CE group. Serum folate was not associated with markers of CE, but serum cobalamin was associated with albumin (P = .04) and cholesterol (P = .03).Of the 673 dogs, 99 CE were compared to 95 non‐CE. In the overall cohort, serum folate concentration did not correlate with sample hemolysis (Hypofolatemia is an inferior biomarker of CE compared to hypocobalaminemia. AREantibiotic‐responsive enteropathyCEchronic enteropathyCIBDAICanine Inflammatory Bowel Disease Activity IndexFDRfalse discovery rateFREfood‐responsive enteropathyIREimmunosuppressant‐responsive enteropathynon‐CEnon‐chronic enteropathyNREnonresponsive enteropathyPLEprotein‐losing enteropathy1Chronic enteropathy (CE) is an umbrella term used for chronic gastrointestinal diseases in dogs that have clinical signs for ≥3 weeks of hyporexia, vomiting, diarrhea, or weight loss. Chronic enteropathy is diagnosed by excluding extragastrointestinal diseases and infectious, endocrine, or neoplastic causes of gastrointestinal disease.Hypocobalaminemia occurs in 19% to 54% dogs with CE,We hypothesized that hypofolatemia would be significantly associated with hypocobalaminemia, high CIBDAI scores, and hypoalbuminemia.22.1A retrospective review of medical records from the University of California, Davis, Veterinary Medical Teaching Hospital between 1 January 2016 to 31 December 2019 was performed to include client‐owned dogs whose serum folate concentrations had been measured. Serum cobalamin measurements and hemolysis indices associated with the samples were recorded when available. Serum folate and cobalamin measurements were performed using a chemiluminescence assay . At the diagnostic laboratory utilized in this study, the average interassay coefficient of variation for serum folate measurements was 6.1% at the low level of the reference interval and 5.2% at the high level. Intraassay coefficients of variation were 3.0% at the low level and 2.7% at the high level. For serum cobalamin measurements, the average interassay coefficient of variation was 5.5% at the low level of the reference interval and 6.8% at the high level. Intraassay coefficients of variation were 7.4% at the low level and 5.6% at the high level. If dogs were receiving cyanocobalamin or folic acid supplementation at the time of presentation to the University of California, Davis, Veterinary Medical Teaching Hospital, those cases were excluded. Dogs were also excluded from study entry if they were receiving medications such as sulfasalazine or methotrexate that could inhibit folate metabolism or absorption. If dogs had multiple serum folate measurements performed between 2016 and 2019, data from the earliest visit was analyzed. Remaining cases were classified as CE cases, non‐chronic enteropathy cases (non‐CE), or indeterminate using the following definitions. A CE case had to meet 1 of the following 2 criteria: 1. Clinical signs of gastrointestinal disease such as inappetence, weight loss, vomiting, or diarrhea for ≥3 weeks, or 2. Biochemical evidence of panhypoproteinemia  or hypoalbuminemia <3.4 g/dL with serum globulin <2.0 g/dL or serum cholesterol <200 mg/dL using University of California, Davis, Veterinary Diagnostic Laboratory reference intervals . Selected cut‐offs for serum globulin and serum cholesterol were decided by the authors based on clinical experience and reports of dogs with PLE having serum globulin and cholesterol concentrations on the lower end of the established reference interval.Chronic enteropathy dogs were subcategorized as FRE, IRE, both food and immunosuppressant responsive (FRE + IRE), ARE, or NRE. When CE cases could not be categorized because of an incomplete diagnostic work‐up, inappropriate treatment protocol , or lack of follow‐up, these uncategorized CE cases were excluded.An FRE was defined as considerable improvement or resolution of clinical signs associated with gastrointestinal disease in response to ≥2 weeks of a new diet . An IRE was defined as a failed diet trial and considerable improvement or resolution of clinical signs associated with gastrointestinal disease with ≥4 weeks of immunosuppressant therapy . A combination FRE + IRE was defined as considerable improvement or resolution of clinical signs associated with gastrointestinal disease with combination diet trials and immunosuppressant therapies. An ARE was defined as considerable improvement or resolution of clinical signs associated with gastrointestinal disease with ≥7 days of tylosin or metronidazole after failure to improve with dietary or immunosuppressant therapy. Granulomatous colitis cases were not classified as ARE. Cases with clinical improvement in response to tylosin or metronidazole administration for ≥7 days were not classified as ARE if dietary trials or immunosuppressant trials were not attempted because FRE and IRE were not appropriately excluded per antimicrobial guidelines for chronic diarrhea.Dogs were categorized non‐CE if a non‐CE disease was suspected to be the cause of clinical signs or labwork abnormalities associated with gastrointestinal disease. Examples of non‐CE diseases included renal (chronic kidney disease > Stage 2 or acute kidney injury) and hepatic disease (uncontrolled chronic hepatitis), neoplasia, pancreatitis, exocrine pancreatic insufficiency, gastrointestinal foreign body, or immune‐mediated diseases .Features collected from each medical record at the visit where serum folate was measured were age (in months), sex , breed, body weight (kilograms), and body condition score . For CE cases, the following clinical data were also obtained: CIBDAI score, duration of clinical signs associated with gastrointestinal disease (months), diarrhea type , presence or absence of PLE, and whether serum cobalamin or folate concentration was being checked for the first time or rechecked as a follow‐up test or visit. Hematologic and biochemical data obtained within 1 month of serum folate measurements were recorded. This data included hematocrit (Hct), hemoglobin (Hgb), mean corpuscular volume (MCV), mean corpuscular hemoglobin concentration (MCHC), reticulocyte count, neutrophil count, eosinophil count, albumin, globulin, cholesterol, glucose, blood urea nitrogen (BUN), creatinine, total magnesium (Mg), and total calcium (Ca).The CIBDAI score was calculated as described2.2Statistical analysis was performed using R Statistical Computing Software Version 4.0.3. Quantitative variables were summarized as means (SD) or median  and categorical variable as counts and percentages. All statistical tests were 2‐sided and evaluated at a significance level of 0.05 except as noted.2.2.1Values of serum folate and cobalamin concentrations beyond laboratory detection limits  were reported as above or below these thresholds. Analysis of these data were conducted in 2 ways. First, the values were categorized as low (<6.5 ng/mL), normal (6.5‐18.6 ng/mL), or high (>18.6 ng/mL) concentrations. Serum cobalamin readings were categorized into subgroups of markedly low (<150 ng/L), low (150‐399 ng/L), normal (400‐1000), or high (>1000 ng/L) concentrations. Second, we imputed concentrations below or above the limits of the assay  as the numerical assay limits. For example, serum cobalamin concentrations <150 were imputed as 150 ng/L. Pearson's chi‐square test was used to test for differences in observed and expected frequencies between serum folate and cobalamin categories. Then, to identify which cells were contributing to a significant result, adjusted standardized residuals were calculated. Spearman rank correlation tests were performed to evaluate the linear relationships between numeric values of serum folate with serum cobalamin concentrations and hemolysis index.2.2.2t‐tests  or Wilcoxon rank sum tests  were used for quantitative variables and Pearson's chi‐square test for sex and folate, cobalamin categories.To compare characteristics between CE and non‐CE groups, 2‐sample 2.2.3P‐values to adjust for multiple testing separately for serum folate and cobalamin evaluations. False discovery rate (FDR) values <0.1 were considered significant.Within the CE group, to evaluate relationships between serum folate concentration, serum cobalamin concentration, and numerous clinical and clinicopathologic variables, Spearman's correlation tests were used to assess relationships between serum folate and cobalamin concentrations with quantitative variables and Kruskal‐Wallis tests were used to test for median differences in serum folate and cobalamin concentrations for categorical variables. The CE variables evaluated comprised of 4 demographic variables: age, weight, BCS, and sex; 7 disease‐related variables: CIBDAI score, duration of clinical signs associated with gastrointestinal disease, diarrhea type, CE type (FRE dogs were compared to dogs requiring immunosuppressants: IRE and FRE + IRE dogs), presence or absence of PLE, response to antibiotic trials of tylosin or metronidazole, new or recheck serum cobalamin and folate; and 15 laboratory‐derived variables: Hct (%), Hgb (g/dL), MCV (fL), MCHC (g/dL), reticulocyte count (cells/μL), neutrophil count (/μL), eosinophil count (/μL), albumin (g/dL), globulin (g/dL), cholesterol (mg/dL), glucose (mg/dL), BUN (mg/dL), Cr (mg/dL), total Mg (mg/dL), and total Ca (mg/dL). Because of the large numbers of statistical tests, false discovery rates (FDR) were calculated from raw 33.1Six hundred seventy‐three dogs had serum folate readings available for analysis during the study period of which 666 had available serum cobalamin readings. Cases receiving vitamin B12 supplementation (n = 34) were excluded leaving a remainder of 632 dogs to evaluate associations between serum folate, serum cobalamin, and hemolysis index  in the study cohort. .Serum folate concentrations were low (<6.5 ng/mL) in 81/673 12.0%) dogs, normal (6.5‐18.6 ng/mL) in 456/673 (67.8%) dogs, and high (>18.6 ng/mL) in 136/673 (20.2%) dogs. Serum folate concentrations were >24 ng/mL in 77/673 dogs (11.4%). Of 673 dogs with serum folate measurements, 632 (93.9%) had available serum cobalamin readings and were not receiving cyanocobalamin supplementation. Of 632 dogs with available serum cobalamin readings, 31 dogs (4.9%) had markedly low (<150 ng/L), 231 dogs (36.6%) had low (150‐399 ng/L), 349 dogs (55.2%) had normal (400‐1000 ng/L) and 21 dogs (3.3%) had high concentrations (>1000 ng/L). Pearson's chi‐square test revealed significant differences in the observed and expected values indicating that serum cobalamin and folate subgroups were significantly associated . BCS was significantly higher in the CE group compared to the non‐CE group (P = .04). Variables of body weight and sex did not significantly differ between CE and non‐CE groups  and a body weight of 18.9 kg (SD = 13.8 kg). Most dogs were spayed or neutered . The majority were pure‐bred (74/99 [75%]) with 25/99 dogs (25%) being mixed breed. Of all dogs that presented to the academic hospital between January 2016 and December 2019, the 3 most common breeds were the Labrador retriever , chihuahua , and German shepherd . In the CE group, 8 dogs had subnormal serum folate (<6.5 ng/mL) concentrations and their breeds were Rhodesian ridgeback, greyhound, pitbull, Yorkshire terrier, hound mix, poodle mix, West Highland white terrier, and Shetland sheepdog. In the CE group, the 3 most common breeds with subnormal serum cobalamin concentrations (<400 ng/L) were the German shepherd , Labrador Retriever , and Yorkshire terrier .P = .06) between CE and non‐CE cases, but numerical serum folate concentrations were higher in CE compared to non‐CE cases (P = .04). Serum cobalamin subgroups (P = .01) and numerical serum cobalamin concentrations (P = .001) were significantly lower in CE compared to non‐CE cases (Table Serum folate concentrations were low in 8/99 (8.1%), normal in 73/99 (73.7%), and high in 18/99 (18.2%) in the CE group. In contrast, serum folate concentrations were low (<6.5 ng/mL) in 19/95 (20.0%), normal (6.5‐18.6 ng/mL) in 60/95 (63.2%), and high (>18.6 ng/mL) in 16/95 (16.8%) in the non‐CE group. In the CE group, 7/99 (7.1%) had markedly low (<150 ng/L) and 46/99 (46.5%) had low serum cobalamin (150‐399 ng/L) concentrations in comparison to the non‐CE group in which 4/95 (4.2%) had markedly low and 25/95 (26.3%) had low serum cobalamin concentrations. Serum folate subgroups did not significantly differ , serum glucose (P = .001), and BUN (P = .04) in raw P‐values, but only with serum glucose (FDR 0.01) after adjusting for false discoveries (Table SP = .04) and cholesterol  concentrations on raw P‐values, but not after adjusting for multiple testing (FDR = 0.34) . Serum folate concentration was significantly associated with eosinophil count  compared to a subnormal serum folate concentration <6.5 ng/mL (12.5%). Similarly, in the CE group, 54% of dogs had a subnormal serum cobalamin concentration and 8% had a subnormal serum folate concentration. This might have been because of the cut‐offs chosen to define subnormal serum concentrations. Subnormal serum folate was defined as concentrations below the lower limit of the reference interval (<6.5 ng/mL). Subnormal serum cobalamin was defined as concentrations <400 ng/L despite the laboratory reference interval of 271 to 875 ng/L. Ideally serum methylmalonic acid concentrations would have been measured to identify true cellular cobalamin deficiency, but these measurements could not be performed retrospectively. Therefore, a cut‐off of 400 ng/L was selected because increased methylmalonic acid concentrations indicative of cellular cobalamin deficiency tend to occur in dogs with serum cobalamin concentrations <400 ng/L.4folate trapping and subsequent folate depletion.To subvert limitations of selected cut‐offs, categories  as well as numerical concentrations of serum folate and cobalamin were analyzed to examine the relationship between serum folate and cobalamin status. Results showed a statistically significant positive correlation between serum folate and cobalamin concentrations in the overall study cohort and CE subset. This result was expected given findings in cross‐sectional humanThe findings that serum folate concentrations were higher in CE cases and hypofolatemia was more common in non‐CE vs CE cases suggest that hypofolatemia is an inferior marker relative to hypocobalaminemia in differentiating CE from non‐CE disease. The factors that impact cobalamin and folate concentrations could explain this finding as intestinal malabsorption and bacterial dysbiosis both decrease cobalamin concentrations, but opposingly affect folate concentrations. Malabsorption lowers folate concentrations, but dysbiosis increases bacterial synthesis of folate to elevate or normalize folate concentrations, which can mask folate deficiency.In this study, hyperfolatemia was more common than hypofolatemia in the overall study cohort and in the CE case group. In the overall study cohort, 19% of the dogs were hyperfolatemic and 12.5% hypofolatemic. In the CE group, 18% were hyperfolatemic and 8% hypofolatemic. Aside from hypotheses of small intestinal bacterial overgrowthAssociations of serum folate and cobalamin concentrations with clinical and clinicopathologic markers of CE were also evaluated in this study. Neither serum folate nor cobalamin concentration was associated with any of the clinical variables . This suggests that serum cobalamin and folate concentrations have limited ability to predict clinical features, disease severity, or therapeutic response to specific interventions. The inability of these B vitamins to distinguish between FRE, IRE, ARE, and other CE types is consistent with previous studies.P value form. This finding corroborated results from previous studies in dogs with CE, which have linked hypocobalaminemia, hypoalbuminemia, and poor clinical outcomes.Associations of serum folate and cobalamin concentrations with hematologic variables showed no relationship with Hct or erythrocyte indices in this study, consistent with a previous study in dogs.Main limitations of this study were because of its retrospective study design, which broached challenges in the categorization of CE cases. The diagnostic testing and treatment approach was not standardized for every dog with CE. To address this limitation, the authors used strict criteria to type CE cases by treatment response. However, assessing treatment response was a subjective process reliant upon the quality of the information provided in the medical record, reported by the pet owner and recorded by the clinician. As a result, many untyped cases were excluded, which reduced sample size and statistical power. Additionally, the inclusion of only typed CE cases might have biased the cohort to favor dogs with less severe, more treatment‐responsive disease and selected for pet owners more likely to pursue treatment and follow‐up. This was evidenced by the predominance of FRE dogs in the CE group, which is the CE type known to have the least severe and most treatable disease.Another potential limitation was that case selection was not restricted to treatment‐naïve cases. Therefore, serum folate and cobalamin concentrations might have been affected by previous or ongoing therapies. However, exclusion of treatment naive cases would have further reduced sample size because most dogs presenting to an academic referral hospital have already received 1 or more treatments before presentation. To overcome this potential limitation, dogs already partially or completely clinically controlled at the time of serum folate measurement were excluded.Finally, because of the large number of clinical and laboratory markers evaluated in this study, a multivariable linear regression analysis inclusive of all variables and accounting for interactions between confounding variables was not performed. Instead, exploratory univariate analyses were performed to test for associations between serum folate concentration, serum cobalamin concentration, and a number of clinical and laboratory markers individually followed by an adjustment for false discoveries. Statistical results might have differed if a multivariable linear regression approach was taken.Authors declare no conflict of interest.Authors declare no off‐label use of antimicrobials.Authors declare no IACUC or other approval was needed.Authors declare human ethics approval was not needed for this study.Table S1: Descriptive statistics for continuous variables related to signalment, clinical disease, and laboratory markers in dogs with chronic enteropathy.Table S2: Descriptive statistics for categorical variables related to signalment and clinical disease in dogs with chronic enteropathy.Table S3: Spearman's correlation assessment of serum cobalamin or folate concentrations vs continuous variables regarding signalment, clinical disease, and laboratory markers in dogs with chronic enteropathy.Table S4: Kruskal‐Wallis results evaluating associations between serum concentrations of cobalamin or folate and categorical clinical disease variables in dogs with chronic enteropathy.Click here for additional data file.


Streptococcus intermedius can cause aggressive infections. One such example as reported in this case is lung abscess which may be mistaken as malignancy on lung imaging. CT scan showing lingular mass abutting the mediastinal margin, mediastinal fat, and chest. Streptococcus intermedius (S. Intermedius). She was discharged on 4 weeks of amoxicillin/clavulanic acid and four liters of continuous oxygen. At follow‐up, she was clinically improved, with no oxygen requirements. Her repeat CT chest done after 4 weeks which showed significant reduction in size of the masses. She was continued on amoxicillin/clavulanic acid for another 4 weeks, after which repeat lung imaging showed near resolution of lingular mass and further reduction in size of left upper lobe mass. Antibiotics were discontinued after 8 weeks of total treatment.A 77‐year‐old female with Parkinson's disease and chronic obstructive pulmonary disease presented to the hospital due to worsening exertional shortness of breath and productive cough for several days. She had a 50 pack‐year history of smoking cigarettes. On presentation, she was hemodynamically stable and required four liters of oxygen, which was new for her. Initial laboratories included complete blood count and comprehensive metabolic profile which were within normal limits. Computerized tomography (CT) of chest with intravenous contrast showed a 3.0 cm × 2.7 cm mass within the lingula and a larger second mass with poorly defined margins in left upper lobe measuring 6.7 cm × 4.8 cm × 6.3 cm. This mass abuted the mediastinal margin, the anterior mediastinal fat, and anterior chest wall. Ipsilateral left mediastinal lymphadenopathy was noted Figure . MalignaStreptococcus anginosus group (SAG) consists of three different species: S. Anginosus, S. Intermedius, and S. Constellatus. SAG species have been considered opportunistic pathogens to some extent, and risk factors include but are not limited to periodontal disease, malignancy, type two diabetes mellitus, chronic kidney disease, chronic lung disease, tobacco smoking, liver disease, and central nervous system disease. S. intermedius has been reported in brain abscesses, orofacial abscesses, pleural empyema, pneumonia, pericarditis, endocarditis, and liver abscess.S. intermedius is particularly prone to causing abscesses and deep tissue infections.S. intermedius and cytology was negative. Her repeat imaging showed remarkable improvement with antibiotics. S. intermedius can cause invasive pulmonary infections mimicking malignancy and should always be considered in the differential for a lung mass. Excellent clinical recovery has been reported with appropriate antibiotics. To summarize this case presents an elderly female with significant smoking history and lung mass. Lung mass as per CT imaging appeared invading the surrounding tissue and mediastinum, which led to high concern for malignancy. The biopsy, however, ruled out malignancy and showed S. Intermedius. Repeat imaging revealed resolution of mass with antibiotics.Saliha Saleem: Writing – original draft; writing – review and editing. Taylor Nelson: Supervision; writing – review and editing.No funding was obtained for this article.The authors declare that there is no commercial or financial relationship to this article.Patient written consent was taken for the publication of images and patient related information. No patient identifiers were used.No ethical approval was required for this article.


The COVID‐19 pandemic led to care disruptions across the cancer continuum. It is unknown if immunosuppressed patients with cancer, who may be at higher risk for complications of SARS‐CoV‐2 infection, are disproportionately impacted. Thus, we aimed to compare delays in cancer treatment initiation between people living with HIV (PLWH) and cancer, the general cancer population (GCP), and patients with cancer and a history of solid organ transplant (SOT). Comparisons were made across the period 2 years preceding the pandemic versus the first year of the pandemic.We used data from a real‐world electronic health record‐derived de‐identified database (2018–2021) comprised of US patients with cancer from 800 sites of care across the country. We included patients with 19 different cancer types. We calculated time to cancer treatment initiation (TTI) as the difference between the date of cancer diagnosis and the earliest date that cancer treatment was recorded.p = 0.007). The increase in TTI for PLWH was observed across treatment modalities, including surgery  and systemic therapy .The sample included 181 PLWH, 65,073 GCP patients, and 195 patients with a SOT. Difference‐in‐difference regression models adjusted for age, sex, and presence of metastatic disease at cancer diagnosis revealed a significant increase in delayed TTI among PLWH compared to the GCP during COVID‐19 versus prior to COVID‐19, with delays increasing by approximately 1 month during the pandemic (DID: 32.6 days [8.9–56.3]; PLWH experienced significant delays in cancer treatment initiation after diagnosis during the first year of COVID‐19, delays that may negatively impact cancer outcomes. These data warrant patient and provider attention as the pandemic continues to impact the US healthcare system. We aimed to determine whether already immunosuppressed populations, specifically people living with HIV and cancer and people living with a history of solid organ transplant and cancer, had more significant delays in cancer treatment initiation than the general cancer population during the COVID‐19 pandemic. To determine this, we used data from a real‐world electronic health record‐derived database with information from 800 sites of care around the United States. Utilization of cancer prevention services decreased significantly due to a variety of factors, including office closures during lockdown, patient fear of contracting COVID‐19 in the healthcare setting, or lack of transportation available to certain patients following widespread public transit closures.HIV care during COVID‐19 was also adversely impacted, with decreases in HIV testing and an increase in loss to follow‐up during HIV therapy.Despite published data documenting the impacts of COVID‐19 on cancer and HIV care separately, little is known about how COVID‐19 impacted cancer treatment among PLWH. Cancer treatment and outcomes disparities in PLWH are well‐documented in the pre‐pandemic era,22.1We used de‐identified electronic health record (EHR)‐derived data from the Flatiron Health Database, which is comprised of patients from approximately 280 cancer clinics (800 sites of cancer care) across the US. This longitudinal database includes both structured and unstructured patient‐level, de‐identified data obtained from technology‐enabled chart abstraction.2.2Three study groups were included in this analysis: people living with HIV (PLWH) and cancer, the general cancer population (GCP), defined as cancer patients without any underlying immunodeficiency, and cancer patients with a history of solid organ transplantation (SOT). We chose SOT patients as an additional, non‐HIV comparison group because these patients are administered immunosuppressive medications to prevent transplant rejection, allowing us to determine if any observed treatment delays were specific to PLWH or were generally present in immunosuppressed patients with cancer. The following International Classification of Diseases (ICD) codes were used to select PLWH: 42, 42.1, 42.2, 42.9, 43, 43.1, 43.2, 43.3, 43.9, 44, 44.9, 79.53, 795.8, B20, B97.35, O98.72, O98.71, O98.7. The following ICD codes were used to select patients with SOT: D89.81, Z94, Z94.0, Z94.1, Z94.2, Z94.3, Z94.4, Z94.5, Z94.6, Z94.7, Z94.8, Z94.82, Z94.83, Z94.89, Z94.9. Patients with hematopoietic transplantation were excluded from the SOT group. Patients with inherited immune disorders were excluded from the study. Our inclusion and exclusion criteria are displayed in Figure 2.3The primary endpoint was time to treatment initiation (TTI). TTI was calculated as the difference in days between the date of the first cancer diagnosis in the real‐world database and the earliest date listed for administration of any of the following cancer treatments: . We allowed a 14‐day window prior to diagnosis per oncologist‐defined, rule based Line of Therapy, such that if a patient was listed as both diagnosed and treated within 2 weeks in the EHR, the treatment lag was set to zero. All time to treatment analyses reported were conducted among patients with available treatment data; 16.4%, 19.9%, and 13.3% of the GCP, PLWH, and SOT groups, respectively, did not have treatment information in the database, either due to no treatment administration or to lack of treatment documentation.2.4t‐tests to compare median TTI between (1) the GCP and PLWH and cancer prior to COVID‐19, (2) the GCP and SOT recipients prior to COVID‐19, (3) the GCP and PLWH and cancer during COVID‐19, and (4) the GCP and SOT recipients during COVID‐19. A difference‐in‐differences analysis, which is a linear regression model that uses ordinary least squares to compare a change in the difference of an outcome between study groups over time, was performed to understand if differences in TTI between PLWH and the GCP changed across the pre‐ and during COVID‐19 time periods. This adjusted analysis included patient age, sex, and extent of disease (presence versus absence of metastatic disease at cancer diagnosis) in the regression model. Based on sample size, we were able to conduct DID analyses both overall and specific to two treatment types (surgery and systemic therapy). All data management was conducted using R,The TTI was compared between study groups prior to COVID‐19 and during COVID‐19. The time period prior to COVID‐19 was defined as a diagnosis date between January 1, 2018 and March 12, 2020. The time period during COVID‐19 was defined as a diagnosis date between March 13, 2020, the day COVID‐19 was declared a national emergency in the United States, and January 29, 2021. We used 3Sociodemographic and clinical characteristics of patients with cancer are outlined in Table p = 0.27), nor between the GCP and the SOT group . A lack of significant differences in median TTI between PLWH and the GCP was consistent across most demographic and clinical groups.Figure p = 0.0017). Females with HIV experienced pronounced cancer treatment delays, with a median TTI of 73.5 days, compared to 27.0 days for females in the GCP (p < 0.001). Statistically significant delays were also observed for smokers and obese PLWH, with median TTIs of 59.0 days and 65.0 days, respectively, compared to 30.0 and 31.0 days for smokers (p = 0.002) and obese patients from the GCP (p = 0.002). No difference was observed between the GCP and SOT recipients overall . However, statistically significant cancer treatment delays were observed for SOT males compared to male GCP patients . In addition, both PLWH (median TTI 40 days) and SOT recipients (median TTI 40 days) ages 45–64 were more likely to experience cancer treatment delays compared to the GCP population aged 45–64 years . This delay in treatment was not observed for patients age 65 and above.Figure p = 0.007) during COVID‐19, approximately a 1‐month increase in TTI between PLWH and the GCP. The increase in the treatment delay between PLWH and the GCP during COVID‐19 was consistent when stratifying by patients who underwent surgery  and patients who received a systemic cancer therapy as their first treatment . We did not observe similar changes in the relative TTI between the SOT group and the GCP during COVID‐19 . Limitations of the study include the overall low number of patients with HIV and history of SOT diagnosed with cancer in the examined 1‐year period after the emergence of COVID‐19. Additionally, heterogeneity of the cancer types included in the study population made granular comparisons challenging. Finally, 16.4%, 19.9%, and 13.3% of the GCP, PLWH, and SOT groups, respectively, did not have treatment information in the database and thus were excluded from analysis. This may have been due to no receipt of treatment or lack of data in the medical record due to receipt of treatment elsewhere. Nonetheless, the percentage of missing data was comparable among the three groups and so was unlikely to appreciably impact our key findings.5This is the first study to our knowledge that has examined delays in cancer treatment in PLWH during the COVID‐19 pandemic. We observed that during COVID‐19, delays in cancer treatment initiation for PLWH compared to the general cancer population were nearly 1 month greater. This delay was not observed among individuals with a history of SOT, suggesting a cancer treatment disparity specific to PLWH that warrants patient and provider attention.Ashley Khouri: Conceptualization ; data curation ; formal analysis ; investigation ; methodology ; project administration ; writing – original draft (lead); writing – review and editing (lead). Jessica Y Islam: Conceptualization ; data curation ; formal analysis ; methodology ; writing – review and editing . Nathan W. Van Bibber: Data curation ; formal analysis ; methodology (lead). Anna E. Coghill: Conceptualization ; data curation ; formal analysis ; investigation ; methodology ; supervision (lead); writing – review and editing . Gita Suneja: Conceptualization ; formal analysis ; investigation ; supervision (lead); writing – review and editing .None.The authors declare no conflict of interest.Table S1–S4.Click here for additional data file.


Objective To analyze if umbilical artery pH (pHua) ≤7.00 and umbilical artery blood deficit (BDua) ≥12.00 mmol/L are good predictors of adverse neonatal outcomes.Methods This was an observational, longitudinal and retrospective cohort study, conducted at the department of obstetrics and gynecology of Centro Hospitalar Tondela Viseu between September 2013 and September 2015. Total cohort and subgroup analysis were performed: group A—women with umbilical cord blood gas analysis (UCBGA) performed for non-reassuring fetal cardiotocographic patterns, placental abruption, or shoulder dystocia; and group B—all the others. Assays were made with the software SPSS for Windows, Versions 20.0 and 21.0 .Results A total of 428 UCBGAs met the inclusion criteria. The group analysis revealed an association between group A and pHua ≤7.00, as well as between BDua ≥12.00 mmol/L and 1st minute Apgar score ≤4 (p = 0.011). After the application of the logistic regression models in the total cohort analysis, pHua ≤7.00 had an impact in the occurrence of acute neonatal hypoxia ; multiparous women had a higher risk of delivering a newborn with first minute Apgar score ≤4 and acute neonatal hypoxia ; women who had urologic problems during pregnancy had a higher risk of delivering a newborn with 5th minute Apgar score ≤7 ; and shoulder dystocia represented a 15 times higher risk of acute neonatal hypoxia .Conclusion The pHua and the BDua are predictors of adverse neonatal outcome, and UCBGA is a useful tool for screening newborns at risk. Universal UCBGA should be considered for all deliveries, as it is an accurate screening test for neonatal hypoxia. The BDua is useful in distinguishing between respiratory and metabolic umbilical artery acidemia.ua ≤7.00 and BDua ≥12.00 mmol/L were good predictors of adverse neonatal outcomes. The secondary aim of the present study was to determine if there was any association between these outcomes and other potential risk factors that could act as confounders.Fetal and neonatal acidemia are associated with several adverse neonatal outcomes.This was an observational, longitudinal and retrospective cohort study conducted between September 2013 and September 2015, at the department of obstetrics and gynecology of Centro Hospitalar Tondela Viseu. All women who delivered in the labor ward and had a valid UCBGA according to the local protocol  were incua and umbilical vein pH.All cases of multiple pregnancies, fetal growth restrictions, preeclampsia, intrapartum fever, preterm delivery, pelvic vaginal delivery, antenatal or postnatal diagnosis of cardiac malformations and low birthweight newborn were excluded . Valid sua ≤7.00 and BDua ≥12.00 mmol/L in group A and to find out if the predictive value of pHua ≤7.00 and BDua ≥12.00 mmol/L for adverse neonatal outcomes was stronger in group A than in group B. Data was collected through the review of electronic and manuscript clinical files.The total cohort data was analyzed. A subsequent group analysis was also done: group A, which included the UCBGA performed for non-reassuring fetal cardiotocography (CTG) patterns or placental abruption, and group B, which included all the remaining cases. The purpose of the group analysis was to check for a stronger association of pH®, Smiths medical ASD, Inc., Keene, New Hampshire, USA) were used. The samples were analyzed within a maximum of 30 minutes at the hospital central laboratory, and the results were made electronically available to the team immediately after.In the UCBGA technique used, the cord was triple-clamped immediately after delivery with an in-between length of ∼ 10 to 20 cm. The distal segment was then cut and placed over a table, where the blood samples were taken, first from the artery and then from the vein. Preheparinised syringes  ≤4;Fifth minute Apgar Score (5′AS)  ≤ 7;Acute neonatal hypoxia (ANH)—condition in which the newborn has been exposed to intrapartum reversible asphyxia, without documented HIE;ua ≤7.00 and/or BDua ≥12.00 mmol/L; (c) presence of multisystem organ failure consistent with HIE;Hypoxic-ischemic encephalopathy—disturbed neurologic function in the earliest days of life, manifested by a reduced level of consciousness or seizures, often accompanied by difficulty at initiating and maintaining respiration, and by depression of tone and reflexes, in a newborn with one or more of the following: (a) a sentinel hypoxic or ischemic event occurring immediately before or during labor and delivery; (b) pHNeonatal convulsion;Hyaline membrane disease or respiratory distress syndrome type I (RDS I);Transient tachypnea of the newborn or respiratory distress syndrome type II (RDS II);Meconium aspiration syndrome—respiratory distress at or shortly after birth in the presence of evidence of meconium-stained amniotic fluid on infant and characteristic radiographic features ;Neonatal bradycardia;Neonatal sepsis—a clinically ill newborn with isolation of pathogenic bacteria from blood culture or, in its absence, with laboratory test results consistent with infection ; and after exclusion of other infectious causes.p < 0.05).The Analysis was performed using the software SPSS for Windows, Versions 20.0 and 21.0 . Maternal and newborn demographic data and the incidence of outcomes were compared between the groups with the chi-squared test and the Fisher exact test. The association between each outcome and the predictors was made through univariate analysis, calculating the odds ratio (OR) with a 95% confidence interval (CI). The Wald test was applied to the outcomes with a statistically significantly association with one or both predictors to check if the ORs were different between the groups and to decide whether to analyze them separately for each group or in the total cohort. Independent predictors of three outcomes were obtained with two multivariate analyses with multiple logistic regressions. The multivariate analysis models were tested with the Hosmer and Lemeshow test and receiver operating characteristic curves. The possible confounders tested were: (a) maternal age (< 35 versus ≥35 years old); (b) parity (nulliparity versus multiparity); (c) gestational age (37–38 versus ≥39 weeks); (d) presence of insulin treated and non-insulin treated gestational diabetes; (e) urologic problems during pregnancy ; (e) presence of oligohydramnios; (f) mode of delivery; (g) shoulder dystocia at birth; (h) newborn gender; (i) newborn birthweight ; (j) presence of neonatal sepsis; and (k) presence of neonatal seizures. The significance level was 5% . In addition, there were no major differences in the distribution of maternal age between the age groups (p = 0.957). In both groups, the majority of women was nulliparous . Few women had a diagnosis of gestational diabetes, gestational hypertension, or urologic problems during pregnancy. Only two women in group A and six women in group B had oligohydramnios (p = 0.481).The mean maternal age did not differ significantly between the groups; it was 31.0 ± 5.1 and 30.8 ± 5.3 years old in groups A and B, respectively (p = 0.380), and most women delivered at 39 weeks or beyond . Vacuum assisted delivery was the most common birth type in both groups  and the caesarean rate was higher in group A . The most frequent reason to perform an UCBGA in group A was a non-reassuring fetal CTG pattern , while in group B it was instrumental delivery . The women in group A were more likely to have male newborns , although the male gender predominated in both groups. The mean birthweight was higher in group B  and the women in group B were more likely to have macrosomic newborns .The mean gestational age at delivery was similar between the groups  and the mean BDua was higher  than in group B. The newborns from group A were more likely to have pHua ≤7.00, but not BDua ≥12.00 mmol/L   .ua ≥12.00 mmol/L in group A also had pHua ≤7.00. Considering the total cohort, newborns with pHua ≤7.00 were more likely to have BDua ≥12.00 mmol/L (p = 0.000) and vice-versa (p = 0.000). There were no statistically significant differences between the groups pHua ≤7.00 and pHua > 7.00 and the groups BDua ≥12.00 mmol/L and BDua < 12.00 mmol/L regarding any of the potentially confounders analyzed. Among all newborns, 26 in group A and 23 in group B had at least one adverse neonatal outcome  (All eight cases of BD= 0.065) .p = 0.020) was 5′ AS ≤7. In the total cohort, there was only one case of HIE, which occurred in group B. It was a 40-week pregnancy, with the diagnosis of gestational hypertension and oligohydramnios, ending in a vacuum-assisted delivery due to a second stage arrest of labor. The 3,150 g male newborn had a 1′ AS = 3 and a 5′ AS = 7. The pHua was 6.85 and the BDua was 18.90. The results of the univariate regression analyses of association between neonatal outcomes and pHua ≤7.00 or BDua ≥12.00 mmol/L showed five significant associations ;pHua ≤7.00 and 5′ AS ≤7 ;pHua ≤7.00 and ANH ;pHua ≥12.00 mmol/L and 1′ AS ≤4 ;BDua ≥12.00 mmol/L and ANH .BDIn the total cohort, the univariate regression analysis of the association between these three neonatal outcomes and the possible confounding factors revealed that :p = 0.022; OR: 5.47; 95% CI: 1.05–28.58; p = 0.037; and OR: 2.74; 95% CI: 1.11–6.77; p = 0.024, respectively)There was a statistically significant association between maternal multiparity and 1′AS ≤4, 5′AS ≤7 and ANH .There was a statistically significant association between shoulder dystocia at birth and ANH ;Belonging to group A did not affect the occurrence of 1′ AS ≤4, 5′ AS ≤7, or ANH when compared with group B , but not in the occurrence of 1′ AS ≤4 or of 5′ AS ≤7 ;There was a statistically significant impact of pHp = 0.017; and OR: 2.66; 95% CI: 1.03–6.89; p = 0.043, respectively);Multiparous women had a statistically significant higher risk of delivering a newborn with 1′ AS ≤4 and ANH ;Women who had urologic problems during pregnancy had a statistically significantly higher risk of delivering a newborn with 5′ AS ≤7 .Shoulder dystocia represents a 15 times higher risk of ANH (OR: 14.82; 95% CI: 2.20–99.60; ua seems to be a reliable marker for acute peripartum problems and a good predictor of adverse neonatal outcomes, as has been widely documented in the literature.ua ≤7.00 had a 9.57 times higher risk of 1′ AS ≤4, a 10.83 times higher risk of 5′ AS ≤7, and a 7.6 times higher risk of ANH; and after the multivariate analysis, pHua ≤7.00 remained as an independent predictor of ANH, granting a 6.71 higher risk.The pHua as an adverse outcome predictor.ua ≥12.00 mmol/L, respectively; and after excluding the confounding factors, BDua ≥12.00 mmol/L remained an independent predictor of 1′AS ≤4, increasing its risk almost 52 times.There is no consensus about the importance of BDShoulder dystocia is a well-known risk factor of neonatal hypoxia. Therefore, it is not surprising that it significantly increases the risk of ANH. Performing an UCBGA seems warranted in these situations.ua ≤7.00 and 1′AS ≤4, as well as between pHua ≤7.00 and 5′AS ≤7, belonging to group A did not affect the occurrence of 1′AS ≤4 or of 5′AS ≤7. This fact can be explained by the findings of Sabol et al,Although there was an association between pHFinally, the present study has found two other things that neither were expected nor clear in the previous literature. The newborns from multiparous women had a 5.38 and a 2.66 times higher risk of having 1′AS ≤4 and ANH, respectively, when compared with newborns from nulliparous women. One study of Mgaya et alThe only independent predictor for 5′AS ≤7 in the present study was urologic problems during pregnancy, which granted a 15.17 times higher risk of this adverse outcome. This finding is difficult to understand in the light of the current knowledge.ua ≤7.00 and 1′AS ≤4; between 5′AS ≤7 and ANH; and between BDua ≥12.00 mmol/L and 1′AS ≤4 and ANH. Because only one newborn had HIE and there were no deaths, it became impossible to assess the relationship between these outcomes and neonatal pHua ≤7.00 or BDua ≥12.00mmol/L.The present study has the limitations of a retrospective cohort: not all of the confounding variables can be controlled, and the data collected relies on accurate patient files, except for the UCBGA. In the 56 cases excluded due to limited data, there were 2 cases of shoulder dystocia and 23 cases of non-reassuring fetal CTG patterns, which may have caused a bias. Another limitation of the present study is that the UCBGA was not performed in all deliveries, but this seems to be shared in the majority of UBCGA studies. Collecting umbilical cord blood samples in emergency situations, like placental abruption or non-reassuring CTG patterns is difficult. In this study 66 out of the 148 UCBGA that were excluded because of incomplete, non-valid or only one-vessel results ocurred in such emergency settings, which lead to an inevitable bias. The small cohort size can justify why the only significant associations found were between pHIn the light of new evidence, the umbilical artery lactate level seems as a reliable outcome predictor of low Apgar score and of neurologic morbidityua ≤7.10.ua threshold is changed from pHua ≤7.00 to pHua ≤7.10, the number of acidemic neonates increases from 17 to 79, so further studies can be designed to verify whether there is an association between pHua ≤7.10 and other neonatal outcomes besides 1′AS ≤4; 5′AS ≤7, and ANH.Some recent studies argue that the threshold for adverse neonatal outcomes is pHAdditional studies are necessary to understand if multiparity and urologic problems during pregnancy are true predictors of adverse neonatal outcome; and, if so, what are the responsible physiopathological mechanisms.ua and the BDua are predictors of adverse neonatal outcomes, and the UCBGA is a useful tool for screening newborns at risk. The meaning of low pHua and high BDua present in clinically healthy newborns with good Apgar scores remains to be determined, but the healthy acidemic newborns seem to have worse outcomes when compared with their non-acidemic counterparts. Therefore, universal UCBGA should be considered for all deliveries because it is an accurate screening test for neonatal hypoxia.The pH


A total of 6100 and 5710 differentially expressed genes (DEGs) were identified in RILpur–W22 and RILbro–W22 seedlings, respectively, under salt–stressed conditions when compared to the non–treated groups. Among these DEGs, 3160 were identified as being present in both RILpur–W22 and RILbro–W22, and these served as commonly stressed EDGs that were mainly enriched in the redox process, the monomer metabolic process, catalytic activity, the plasma membrane, and metabolic process regulation. Furthermore, we detected 1728 specific DEGs in the salt–tolerant RILpur–W22 line that were not detected in the salt–sensitive RILbro–W22 line, of which 887 were upregulated and 841 were downregulated. These DEGs are primarily associated with redox processes, biological regulation, and the plasma membrane. Notably, the anthocyanin synthesis related genes in RILpur–W22 were strongly induced under salt treatment conditions, which was consistented with the salt tolerance phenotype of its seedlings. In summary, the results of the transcriptome analysis not only expanded our understanding of the complex molecular mechanism of anthocyanin in improving the salt tolerance of maize seedlings, but also, the DEGs specifically expressed in the salt–tolerant line (RILpur–W22) provided candidate genes for further genetic analysis.Anthocyanin, a kind of flavonoid, plays a crucial role in plant resistance to abiotic stress. Salt stress is a kind of abiotic stress that can damage the growth and development of plant seedlings. However, limited research has been conducted on the involvement of maize seedlings in salt stress resistance via anthocyanin accumulation, and its potential molecular mechanism is still unclear. Therefore, it is of great significance for the normal growth and development of maize seedlings to explore the potential molecular mechanism of anthocyanin improving salt tolerance of seedlings via transcriptome analysis. In this study, we identified two W22 inbred lines (tolerant line pur–W22 and sensitive line bro–W22) exhibiting differential tolerance to salt stress during seedling growth and development but showing no significant differences in seedling characteristics under non–treatment conditions. In order to identify the specific genes involved in seedlings’ salt stress response, we generated two recombinant inbred lines (RIL Maize is the largest grain product in the world, renowned for its rich protein, starch, vitamin, and trace element content . Maize eO–glucosyltransferase (UFGT) are involved in the anthocyanin biosynthesis pathway [Anthocyanin is a natural water–soluble pigment and one of the flavonoid compounds widely found in nature . Enzymes pathway ,14,15,16 pathway ,18,19. F pathway ,22,23,24AtDFR expression in Brassica napus L. was upregulated, anthocyanidin accumulation was increased, and plant tolerance to salt stress was enhanced [The global area of saline–alkali land is about 950 million hectares. Saline soil will directly affect seed germination, seedling morphogenesis, and plant growth and development, thus affecting crop yield ,26,27. Uenhanced . Therefopur–W22 and RILbro–W22) for transcriptome analysis. Expected to explore the differentially expressed genes (DEGs) involved in the salt tolerance of maize seedlings via transcriptome analysis, so as to further understand the potential molecular mechanism of anthocyanin in improving the salt tolerance of maize seedlings.A transcriptome refers to the sum of all gene transcription products of a specific organism at specific development stage. Transcriptome analysis is a powerful tool for identifying genes that contribute to complex traits ,33,34,35The seeds of purple W22 (pur–W22) inbred lines were purple, while the seeds of bronze W22 (bro–W22) inbred lines were bronze. Upon comparing the seed traits of the two W22 inbred lines, it was observed that, apart from the color difference, the seed length, width, and thickness of the pur–W22 inbred lines were significantly larger than those of bro–W22 . Additio2 population through self–pollination. Subsequently, the F6 generation RILs (RILpur–W22 and RILbro–W22) were derived by self–pollinating the F2 generation plants over multiple generations. Comparing the seed traits of the two RIL populations, we observed no significant differences in seed length, width, thickness, or 100–grain weight between RILpur–W22 and RILbro–W22, except for the variations in color  that had germinated and grown for 14 days under non–treated and salt stress environments (pur–W22 seedlings (NT–RILpur–W22) and salt–treated RILpur–W22 seedlings . Similar distinctions were observed between non–treated RILbro–W22 seedlings (NT–RILbro–W22) and salt–treated RILbro–W22 seedlings   b. These pur–W22 and RILbro–W22, while the number of expressed genes in non–treated RILs was lower than that in salt–treated RILs, indicating that there was an induction of gene expression in the salt–stressed environment compared to the non–treated RILs. Notably, the highest number of expressed genes was observed in salt–treated RILpur–W22 seedlings , the number of reads and fragment length were calculated for 46,424 genes, which were then assigned FPKM (fragments per kilobase of transcript per million mapped reads) values. Genes with an FPKM value ≥ 1 were considered to be expressed genes. We observed a similar number of expressed genes in non–treated RILeedlings .p–value of ≤0.01, we screened the DEGs and compared them in various combinations. In the NT–RILpur–W22 vs. NT–RILbro–W22 group, which compares non–treated RILpur–W22 and RILbro–W22 seedlings based on their color difference, we identified 1606 DEGs, including 846 up– and 760 downregulated DEGs. The NT–RILpur–W22 vs. salt–RILpur–W22 group represents DEGs produced by RILpur–W22 seedlings under salt stress, which accounted for 6100 DEGs, with 3109 up– and 2991 downregulated DEGs. Similarly, in the NT–RILbro–W22 vs. salt–RILbro–W22 group, which compares RILbro–W22 seedlings under salt stress, we identified 5710 DEGs, with 2961 up– and 2749 downregulated DEGs. Lastly, the salt–RILpur–W22 vs. salt–RILbro–W22 group represents DEGs resulting from the combined effects of color difference and salt stress between RILpur–W22 and RILbro–W22 seedlings. We found 1040 DEGs, including 578 up– and 462 downregulated DEGs  that were exclusively expressed in non–treated RILpur–W22 seedlings and salt–treated RILpur–W22 seedlings  and were not observed in other groups  exclusively expressed in non–treated RILbro–W22 seedlings and salt–treated RILbro–W22 seedlings .In comparison to RILr groups . Therefopur–W22 and RILbro–W22 seedlings and observed that the specific DEGs in the NT–RILpur–W22 vs. salt–RILpur–W22 group exhibited significant expression changes in RILpur–W22 seedlings under salt stress compared to non–treated RILpur–W22 seedlings, while the expression levels in RILbro–W22 either remained unchanged or changed to a lesser extent , redox processes (GO: 0055114), oxidoreductase activity (GO: 0016491), and the plasma membrane (GO: 0005886)  a. On the0005886) b. Additimulation b. The upbro–W22 vs. salt–RILbro–W22 group revealed significant enrichment in functional pathways related to cell metabolism (GO: 0044237), nitrogen compound metabolism (GO: 0006807), chloroplast (GO: 0009507), photosynthesis (GO: 0009768), and quercetin 7–O–glucosyltransferase activity (GO: 0080044)  . On the 0080044) . Notablyuercetin ,41. Addiis point d.bro–W22 under salt–treated conditions, we conducted a GO enrichment analysis on 140 DEGs (65 upregulated DEGs and 75 downregulated DEGs) specifically responsive to salt stress in the salt–RILpur–W22 vs. salt–RILbro–W22 group , Zm00001d018181 (fls2), and Zm00001d047425 (F3′5′H) were upregulated in RILpur–W22 under salt stress  and can effectively neutralize excessive ROS under stress conditions, thereby contributing to salt tolerance in seedlings ,43. In teedlings . Therefopur–W22 and RILbro–W22 seedlings. Additionally, through KEGG pathway enrichment analysis, we observed the enrichment of precursor synthesis or metabolic pathways related to various plant hormones [pur–W22 and RILbro–W22 seedlings to salt stress.Hormones play a crucial role in regulating plant responses to abiotic stress. Numerous studies have demonstrated the involvement of hormones in mediating plant tolerance to stress conditions ,45,46,47hormones ,49,50,512O2 in chloroplasts, leading to stomatal closure and enhancing plant resistance to abiotic stress [OsIAA20 gene in rice reduces salt tolerance, affecting yield and seed viability [bro–W22 seedlings under salt stress conditions. As a result, RILbro–W22 seedlings may experience difficulty in efficiently removing excessive ROS accumulation, leading to reduced salt tolerance.Under abiotic stress conditions, plants exhibit the upregulation of genes related to ABA biosynthesis pathway. High levels of ABA can induce the accumulation of Hc stress . Additioc stress . IAA plaiability . In appliability . In thishttp://planttfdb.gao–lab.org/index.php, accessed on 26 June 2023). And we identified 472 and 420 DEGs encoding transcription factors in the NT–RILpur–W22 vs. salt–RILpur–W22 and NT–RILbro–W22 vs. salt–RILbro–W22 groups, respectively  of pur–W22/bro–W22 for generations in both Sanya (Hainan province) and Zhuozhou (Hei Bei province), in winter and summer, respectively.The purple W22 (pur–W22) inbred line was obtained from the laboratory of Professor Mingliang Xu, International Maize Improvement Center, China Agricultural University. The bronze W22 (bro–W22) inbred line was obtained from the mutant maize COOP stock center. The homozygous RILStandard germination: 90 seeds  were disinfected in 0.1% sodium hypochlorite for 5 min, rinsed with distilled water three times, and then sown in germination paper. The rolled germination paper was placed vertically in a sealed plastic bag and cultured in an incubator with a light/dark cycle of 16 h/8 h at 25 °C.Salt–treated paper germination: 90 seeds were disinfected using standard germination steps, seeded on germination paper containing 100 mM NaCl solution, and then cultured according to standard germination culture conditions.p value was calculated by one–way analysis of variance.Cultivation in sand: 90 seeds were sterilized in 0.1% sodium hypochlorite solution, washed three times with distilled water, and sowed in sandy soil containing 0 mM and 100 mM NaCl solutions. The germination box after sowing was placed in an incubator at 25 °C and cultured at a 16 h/8 h light–dark ratio for 14 days. Stem length and root length were measured with a ruler 14 days after sowing. The histogram of root length and seedling length was drawn using the Graphpad Prism 8 software package, and the p value.Fifty randomly selected seeds were scanned three times repeatedly using an EPSON J221A scanner , and then the data regarding seed length, seed width, and seed thickness were analyzed using the Seeds Identification and Photoshop software packages . Finallypur–W22 and RILbro–W22 seedlings  germinated for 14 days in 0 mM and 100 mM NaCl solution environments for RNA sequencing, with two replicates for each sample. Total RNA was extracted using the RNA extraction kit . RNA concentration and quality were measured using an ultra–micro spectrophotometer ND2000 . The prepared RNA was sent to Annoroad Gene Technology  for library construction, sequencing, and data filtering  [p–value of <0.01 and an absolute difference multiple fold change (FC) of ≥2. The FPKM value is calculated using the number of raw reads, and the formula is: FPKM = read count/(mapping reads (millions)) × exon length (KB). If FPKM ≥ 1 in at least one sample, the gene was considered to be an expressed gene. All of the expressed genes from different samples were applied to TBtools for PCA calculation, using the default settings [The filtered data were used to establish a genome index file using the Hisat2 program and were compared to the maize reference genome (B73_RefGen_v4) . The Samne 2023) . When ansettings .https://www.maizegdb.org/gene_center/gene, accessed on 26 June 2023), KOBAS  was used for Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis [The obtained differentially expressed genes were subjected to gene ontology (GO) enrichment analysis using agriGO v2.0  . After tanalysis .–ΔCT method for relative quantification. The GAPDH was used as an internal control. The primer sequences used are listed in First–strand cDNA was synthesized using a StarScript II RT Mix with gDNA Remover kit . qRT–PCR was performed using 2 × HQ SYBR qPCR Mix  in triplicate on an ABI Life Q6 real–time fluorescent quantitative PCR instrument  and using the obtained results and the 2pur–W22 seedlings was mainly related to the redox process, biological regulation, and the plasma membrane. Among them, anthocyanidin–synthesis–related genes were strongly induced under salt treatment, which was partially consistent with the physiological results regarding salt tolerance in seedlings. The results showed that improving the anthocyanidin–synthesis–related genes in maize could effectively compensate for seedling growth inhibition caused by salt stress. This study could lay a foundation for mining and cloning key genes affecting the salt tolerance of maize seedlings under salt stress conditions.We screened two maize W22 inbred lines  regarding the different salt tolerance levels of seedlings under a salt stress environment and performed transcriptome analysis of their RILs to identify the genes related to the salt stress tolerance of maize seedlings. We found that the specific expression of DEGs in the salt tolerance of RIL