The prognosis of patients with small cell lung cancer (SCLC) and brain metastases (BM) was poor. This study aimed to explore the efficacy and safety of anlotinib as third‐line or above treatment in SCLC with BM.This was a subgroup analysis of the ALTER1202 trial, which was a randomized, placebo‐controlled trial aimed to evaluate the role of anlotinib as third‐line treatment or above in patients with SCLC. This study included patients with BM at baseline. The efficacy and safety outcomes included progression‐free survival (PFS), overall survival (OS), central nervous system (CNS), objective response rate (ORR), CNS disease control rate (DCR), time to CNS progression, and adverse events (AEs).p = 0.0005) and OS  than placebo. Anlotinib significantly prolonged the time to CNS progression (p < 0.0001). The anlotinib group had a higher CNS DCR than placebo . The most common grade 3 or higher AEs were increased lipase (19.0%), hypertension (14.3%), and hyponatremia (14.3%) in the anlotinib group.Twenty‐one and nine patients with BM were included in the anlotinib and placebo groups, respectively. The median PFS and OS were 3.8 months  and 6.1 months (95% CI: 4.1–8.0) in the anlotinib group. Anlotinib was associated with a significant improvement in PFS  and median OS  in SCLC patients with BM.In this post hoc analysis of a multicenter, randomized, double‐blind, placebo‐controlled trial, anlotinib demonstrated a potential survival benefit in small cell lung cancer (SCLC) with brain metastases (BM) compared with placebo, with manageable toxicity. Anlotinib significantly prolonged median progression‐free survival (PFS) (hazard ratio [HR] = 0.15, 95% CI: 0.04–0.51;  AEsadverse eventsBMbrain metastasesCIconfidence intervalCIRcumulative incidence ratesCNScentral nervous systemCRcomplete responseCTcomputed tomographyDCRdisease control rateECOGEastern Cooperative Oncology GroupFGFRfibroblast growth factor receptorHRhazard ratioMRImagnetic resonance imagingNCI‐CTCAENational Cancer Institute Common Terminology Criteria for Adverse EventsNCR/NPDnon‐CR/non‐PDNEnot evaluableNSCLCnon‐small cell lung cancerNTLsnon‐targeted lesionsORRobjective response rateOSoverall survivalPDprogressive diseasePDGFRplatelet‐derived growth factor receptorsPFSprogression‐free survivalPRpartial responseRECIST 1.1Response Evaluation Criteria In Solid Tumors version 1.1SCLCsmall cell lung cancerSDstable diseaseSRTstereotactic radiotherapyTKItyrosine kinase inhibitorTLstarget lesionsTTBPtime to brain progressionVEGFRvascular endothelial growth factor receptorWBRTwhole‐brain radiotherapy1Small cell lung cancer (SCLC) is regarded as one of the most malignant pulmonary neuroendocrine neoplasms due to its increased recurrence and metastatic rates, which accounts for approximately 15% of lung cancer and causes about 250,000 deaths globally each year . ApproxiAs a result of immunotherapy, treatment has revolutionized a wide range of malignancies in recent years. Survival outcomes of immunotherapy in metastatic SCLC have been investigated through several large trials. The phase 1/2, open‐label CheckMate‐032 trial revealed a promising outcome of a combination of nivolumab and ipilimumab in patients with extensive‐stage SCLC, but BM patients were not included in the study . BesidesAnlotinib is an oral tyrosine kinase inhibitor (TKI) targeting vascular endothelial growth factor receptor (VEGFR), platelet‐derived growth factor receptors (PDGFR), fibroblast growth factor receptor (FGFR), and c‐kit . In a prThis post hoc analysis included patients with BM at baseline in the ALTER1202 study, and aimed to evaluate the effectiveness and safety of anlotinib in patients with SCLC accompanied by BM to provide insights into clinical treatment.22.1This was a subgroup analysis of ALTER1202 , which was a multicenter, randomized, double‐blind, placebo‐controlled phase 2 study aimed to evaluate the efficacy and safety of anlotinib as a third‐line treatment or above in patients with SCLC. The ALTER1202 study followed the Declaration of Helsinki and Good Clinical Practice Guidelines and was approved by the institutional review board of each participating center . All patients provided signed informed consent before any procedure. Eligible patients were randomly assigned at a 2:1 ratio to receive oral anlotinib 12 mg or placebo daily for 14 days every 3 weeks. A detailed study design has been published before .The inclusion criteria of this study were as follows: (a) SCLC patients who have progressed after two or more lines of chemotherapy; (b) with BM at baseline; (c) without symptoms associated with BM; or (d) were stable after treatment for BM, not showing new or enlarged brain lesions 2 weeks after treatment (new or enlarged lesions appeared within 2 weeks after treatment indicating that they developed rapidly and were prone to present symptoms of BM), and stopped steroid or anticonvulsant therapy for at least 14 days before treatment initiation (the metabolism of anlotinib will be affected by anticonvulsant drugs such as phenytoin and carbamazepine).2.2Computed tomography (CT) brain scans and enhanced magnetic resonance imaging (MRI) were performed on all patients during the screening period. The extracranial and intracranial lesions were evaluated based on Response Evaluation Criteria In Solid Tumors version 1.1 (RECIST 1.1) at baseline and during the treatment . Adverse2.3Baseline characteristics of patients were reviewed, including age, sex, Eastern Cooperative Oncology Group performance status, smoking history, previous treatment, and relapse pattern to chemotherapy.Outcomes in this study included PFS, OS, time to central nervous system (CNS) progression, CNS objective response rate (ORR), CNS disease control rate (DCR), and safety profiles. The CNS response in target lesions (TLs) was classified as complete response (CR), partial response (PR), stable disease (SD), progressive disease (PD), or not evaluable (NE), while the CNS response in nontargeted lesions (NTLs) was categorized as CR, non‐CR/non‐PD (NCR/NPD), PD, or NE. Time to CNS progression was defined as the time from randomization to the first radiographic confirmation of CNS progression. The CNS ORR is determined by the numbers and percentage of patients with CNS response of CR or PR. CNS DCR was assessed by the numbers and percentages of patients with a therapeutic effect evaluation of CR, non‐CR, non‐PD, PR, or SD. PFS was defined as the time from randomization to disease progression or death from any cause, whichever came first. OS was defined as the time from randomization to death from any cause.2.4p < 0.05) in the univariable analysis and clinical significance were included in the multivariable model. A competing risk methodology with a few modifications was used for assessing the cumulative incidence rates (CIR) of CNS progression and time to CNS progression. The possibility of CNS progression (with or without systemic progression), non‐CNS progression, or death was considered, and only the first event was included. The Pearson's χ2 test or Fisher's exact test was utilized to compare CNS ORR and CNS DCR of two groups as appropriate. Two‐sided p < 0.05 indicated statistical significance.SAS v9.4 (SAS Institute) was utilized for all statistical analysis. Wilcoxon rank‐sum tests were used to compare the age of two groups, and Fisher's exact test was conducted for other categorical variables comparison. The Kaplan–Meier method was used for describing PFS and OS, and the log‐rank test was used to compare the two groups. To estimate the association between anlotinib and PFS, a multivariable Cox regression model (enter method) was used. Variables with statistical significance (33.1p = 0.0732). In the anlotinib and placebo groups, 17 cases (80.9%) and 6 cases (66.7%) had previously undergone brain radiotherapy (p = 0.0816). There are more current smokers in the placebo group than in the anlotinib group (p = 0.0159). Detailed information is presented in the Table From March 30, 2017, to June 8, 2018, 120 patients were enrolled in the ALTER1202 study, including 30 patients with BM at baseline . There are 13 and 9 males in the anlotinib group and in the placebo group, respectively. The median ages were 51 (43–68) years old and 61 (50–69) years old in the anlotinib group and placebo group, respectively (3.2p = 0.0005) and median OS  in SCLC patients with BM  months. A total of 15 and 6 patients administered anlotinib or placebo‐developed disease progression or died, respectively. The median PFS was 3.8 months  in the anlotinib group, and 0.8 months (95% CI: 0.5–2.1) in the placebo group, respectively. The anlotinib group had a median OS of 6.1 months (95% CI: 4.1–8.0), and the placebo group had a median OS of 2.6 months (95% CI: 0.5–5.2). Anlotinib significantly prolonged median PFS  after adjusting for smoking history and previous brain radiotherapy .The median time to CNS progression was not reached in the anlotinib group, and 0.8 months (95% CI: 0.7–2.1) in the placebo group, respectively . In patients with TLs, the CNS ORR was higher in the anlotinib group than in the placebo group . Among patients with NTLs, the CNS DCR was 93.8% in the anlotinib group and 33.3% in the placebo group (p = 0.0506) , while the CNS DCR was significantly higher  in the placebo group and all patients (100%) treated with anlotinib experienced AEs. SAE occurred in eight patients (38.1% [95% CI: 18.1–61.6]) in the anlotinib group and two  in the placebo group. In patients treated with anlotinib, the most common AEs were loss of appetite 47.6%), weight loss (42.9%), hypertriglyceridemia (38.1%), and leukopenia (38.1%), while the most common grade 3 or higher AEs were increased lipase (19.0%), hypertension (14.3%), and hyponatremia (14.3%)  and OS  for SCLC patients with BM, with similar results in the overall population in the ALTER1202 study  [p < 0.0001) and enhanced the CNS response , which may contribute to the extension of the PFS and OS after anlotinib administration. Based on a previous subgroup analysis, anlotinib prolongs PFS , and increases time to brain progression (TTBP)  in NSCLC patients with BM, which was consistent with our findings [According to the present subgroup analysis, anlotinib improved PFS  was adjusted in the multivariable model. Furthermore, the statistical power of this study was likely insufficient due to the limited sample size.This study had some limitations. First, this was a post hoc analysis of a randomized controlled trial. A completely balanced baseline characteristic was not achieved as a result of the randomization effect not being maintained. In this post hoc study, most baseline characteristics did not differ significantly between the two groups, while the significant difference in smoking history .All patients provided signed informed consent.


Scomberomorus guttatus and a single species pair was not captured by delimitation methods. Intraspecific K2P genetic distances averaged 0.36% among sequences within species, whereas K2P genetic distances among species within genera averaged 6.96%. The most speciose families in open water trawling differ from those at fish market, and discrepancies with historical data are discussed in the light of recently documented stock collapses.The Beibu Gulf in China is situated in the tropics, in the western Pacific Ocean. It is an emblematic region combining proximity to a marine biodiversity hotspot and a major seafood hub. Intensification of marine fishing and ocean warming led to a drastic decline in fish populations in the Beibu Gulf during the last decades. This situation urges the development of molecular resources of the Beibu Gulf fish fauna in order to enable automated molecular identifications at the species level for next‐generation monitoring. With this objective, we present the results of a large‐scale campaign to DNA barcode fishes of the Beibu Gulf. We successfully generated 789 new DNA barcodes corresponding to 263 species which, together with 291 sequences mined from Genbank and BOLD, resulted in a reference library of 1080 sequences from 285 species. Based on the use of four DNA‐based species delimitation methods , a total of 285 Molecular Operational Taxonomical Units (MOTUs). A single case of cryptic diversity was detected in  The fish fauna of the beibu gulf, one of the largest sea food hubs in Southeast Asia, is characterized here by DNA barcoding. The 1080 DNA barcodes analyzed show concordance between morphological identifications and DNA‐based species delimitation. Lower level of diversity detected here compared to historical observations is concordant with the stock collapses previously described in the literature for the area. This study opens new perspectives by enabling next‐generation monitoring of the 285 species DNA barcoded here. Prelimi2.21/FishR1 and FishF2/FishR2 , 3.5 μL of buffer, 1 μL of forward and reverse primers, 12.5 μL of Taq polymerase and 5 μL of genomic DNA. Amplifications employed the following thermocycling regime: initial denaturation at 92°C for 5 min followed by 33 cycles including denaturation at 92°C for 45 s, annealing at 50°C for 60 s and extension at 72°C for 60 s, followed by a final extension step at 72°C for 10 min. Sanger sequencing was conducted at Sangon Biotech company, and reads were assembled and edited using Sequencher 5.4.5. The primer pairs FishF1/FishR1 and FishF2/FishR2 resulted in sequences of 655 and 652 bp, respectively. Sequences analyzed in the present study were deposited in Genbank .DNA was extracted using the FastPure® Cell/Tissue DNA Isolation Mini Kit methodology using the manufacturer's specification. A fragment of 652 bp of the mitochondrial COI gene was amplified using the universal primers FishF2.3Sequences were aligned using MAFFT .Both Refined Single Linkage (RESL) and ASAP use DNA alignments as input, and sequences were submitted to the webserver of BOLD and ASAP for delimitation analysis respectively. For PTP analyses, a Maximum Likelihood (ML) tree was generated using the R package Phangorn 2.8.1 Schliep,  with a GFinally, we checked the sampling coverage of the present survey at the species and MOTUs level by computing the sequence accumulation curve with by R package vegan , it appears that among the 285 species detected here, one species is considered as critically‐endangered (CR), Sphyrna lewini , two species are indicated as endangered (EN), Evynnis cardinalis , and Argyrosomus japonicus , three species are indicated as vulnerable (VU), Albula glossodonta , Carcharhinus limbatus , Nemipterus virgatus , seven are considered as near‐threatened (NT) Scomberomorus commerson , Trachurus japonicus , Scoliodon macrorhynchos , Choerodon schoenleinii , Acanthopagrus chinshira Kume & Yoshino, 2008, Harpadon nehereus , Chiloscyllium plagiosum , and 171 are indicated as least‐concern  was also observed during the present survey and is indicated as threatened by the IUCN, however, O. mossambicus is considered as threatened only in its native range in Africa and is considered as invasive elsewhere.According to the last assessment of the International Union for Conservation of Nature (IUCN: https://fishdb.sinica.edu.tw/), 196 species are of commercial interest and 89 species are of low economic value. These 285 species display a great diversity of habitat preferences including for instance reef‐associated , demersal , and benthopelagic  families  with an average of 0.0036, whereas the nearest neighbor K2P distance ranged between 0.0077 and 0.2641 , however, reciprocal monophyly was observed.K2P genetic distances between congeneric species averaged 0.0696, ranging from 0.00 to 0.283 (Champsodontidae). K2P distances within the family averaged 0.15, ranging from 0.00 to 0.3398 (Ophidiiformes) , whose species delimitation method failed to separate and group in a single MOTU due to their close genetic affinity, despite several diagnostic morphological characters distinguishing them including caudal and dorsal fin coloration patterns. However, this trend is common among Apogonidae species  is strikingly similar to previous assessments at regional scale in the South China Sea where 1.7% of the species contained cryptic and highly divergent lineages  as the dominant species in deep waters of the Beibu Gulf , Terapon theraps Cuvier, 1829, Gerres filamentosus Cuvier, 1829, Carcharhinus menisorrah  and Gymnocranius griseus  have experienced serious declines  by medium and low commercial value species such as A. japonicum and several species of the family Leiognathidae ; data curation ; formal analysis ; methodology ; writing – original draft . Murong Yi: Data curation ; formal analysis ; methodology ; writing – original draft . Zhisen Luo: Formal analysis (supporting); investigation (supporting); validation (supporting); writing – review and editing (supporting). Xiongbo He: Formal analysis (supporting); investigation (supporting); validation (supporting); writing – review and editing (supporting). Hung‐Du Lin: Formal analysis (supporting); investigation (supporting); validation (supporting); writing – review and editing (supporting). Nicolas Hubert: Formal analysis (supporting); investigation (supporting); methodology (supporting); supervision (supporting); validation (supporting); writing – original draft (supporting); writing – review and editing . Yunrong Yan: Conceptualization (lead); formal analysis (supporting); funding acquisition (lead); investigation (lead); project administration (lead); validation (lead); writing – original draft ; writing – review and editing .The authors declare no competing interests.Figure S1.Click here for additional data file.Figure S2.Click here for additional data file.Figure S3.Click here for additional data file.Table S1.Click here for additional data file.Table S2.Click here for additional data file.Table S3.Click here for additional data file.Table S4.Click here for additional data file.


To evaluate the feasibility and safety of total neoadjuvant therapy (TNT) in patients with locally advanced rectal cancer (LARC) in Japan.This prospective, multicenter, open‐label, single‐arm phase II trial was conducted at five institutions. The key eligibility criteria were age ≥ 20 years, LARC within 12 cm from the anal verge, and cT3‐4N0M0 or TanyN+M0 at the time of diagnosis that enabled curative resection. Preoperative short‐course radiation therapy (SCRT) 5 Gy × 5 days  + CAPOX (six courses) followed by total mesorectum excision (TME) was the treatment protocol. Non‐operative management (NOM) was allowed if clinical complete response (cCR) was obtained in the preoperative evaluation. The primary endpoint was the pathological complete response (pCR) rate.n = 26; female, n = 4; median age, 62.5 [44–74] years; cT ; cN ) were enrolled. The final analysis included 30 patients in total. The completion rates were 100% for SCRT and 83% for CAPOX. TME and NOM were performed in 20 and seven patients, respectively. pCR was observed in six patients (30% [95% CI 14.0%–50.8%]). The primary endpoint was met. pCR+cCR was observed in 13 (43.3%) patients. There were no treatment‐related deaths. Grade ≥3 (CTCAE ver. 5.0) adverse events (≥20%), including diarrhea (23.3%) and neutropenia (23.3%). The median follow‐up period was 15.6 (10.5–22.8) months, with no recurrence or regrowth in NOM.Thirty patients  for patients with locally advanced rectal cancer (LARC) in Japan. Pathological complete response (pCR) and pCR + cCR were observed in 30% and 43.3% of patients, respectively. In 2021, 732 210 newly diagnosed cases of rectal cancer and 339 022 related deaths were reported worldwide.The outcomes of locally advanced rectal cancer (LARC) have been improved using multimodal treatment strategies. For local control of LARC, preoperative chemoradiotherapy (CRT) for LARC has been developed in Europe and the United States,In recent years, total neoadjuvant therapy (TNT), in which preoperative chemotherapy and (chemo)radiotherapy are administered sequentially to patients with LARC, has been developed in Europe, the United States, and Asia to improve the long‐term prognosis of LARC. In contrast, the standard treatment for LARC in the Japanese guidelines is upfront surgery and adjuvant chemotherapy (ACT) with LLND as an option.Therefore, we conducted a prospective multicenter single‐arm ENSEMBLE‐1 trial to evaluate the feasibility and safety of TNT in Japanese patients with LARC.22.1The ENSEMBLE‐1 study was a prospective, multicenter, open‐label, single‐arm, phase II trial conducted at five institutions  written informed consent obtained; (2) a histological diagnosis of primary rectal adenocarcinoma; (3) no distant metastases on computed tomography (CT) or positron emission tomography (PET), and radical resection was clinically possible; (4) age ≥ 20 years; (5) Eastern Cooperative Oncology Group Performance status (ECOG‐PS) of 0 or 1 (ECOG‐PS 0 for age ≥ 71 years); (6) no prior treatment for rectal cancer; (7) lower margin of the tumor was within 12 cm from the anal verge (AV); (8) clinically diagnosed as Union for International Cancer Control (UICC) TNM classification (8th edition),2.22 orally twice daily on days 1–14, oxaliplatin 130 mg/m2 intravenously on day 1, every 3 weeks), followed by total mesorectal excision (TME) or tumor‐specific mesorectal excision (TSME). The protocol stipulated that CAPOX should be initiated 14 ± 3 days after completion of SCRT. If treatment could not be started due to an adverse event, it could be delayed for up to 35 days. Surgery should be performed 3–8 weeks after the last dose of CAPOX (the last day of capecitabine administration) or the date of discontinuation. The following procedures were acceptable: low anterior resection (LAR), intersphincteric resection (ISR), abdominoperineal resection (APR), and Hartmann operation. In cases where invasion of adjacent organs is suspected, combined resection of adjacent organs was also acceptable to achieve radical resection. Additional LLND was acceptable at the discretion of the surgeon. The surgical approach  was not specified.After registration, the patient received short‐course radiation therapy (SCRT) , using three‐dimensional conformal radiation therapy or intensity‐modulated radiation therapy [IMRT], six cycles of CAPOX , near CR (nCR), and incomplete CR (iCR), based on colonoscopy, pelvic magnetic resonance imaging (MRI), and digital findings according to Memorial Sloan Kettering Cancer Center (MSKCC) Regression Schema2.3Standard pathological analyses were performed on all resected specimens at each participating institution. The pathological primary tumor response to TNT was evaluated using the grading scale according to the Japanese Classification of Colorectal, Appendiceal, and Anal Carcinoma.2.4Follow‐up was performed every 3 months for the first 3 years and every 6 months thereafter for up to 5 years. Tumor markers carcinoembryonic antigen (CEA) and carbohydrate antigen 19–9 (CA19‐9) were assessed at each follow‐up examination. Chest‐abdominal‐pelvic computed tomography (CT) was performed every 6 months. Total colonoscopies were performed annually. For patients with NOM, tumor markers, colonoscopy, rectal examination, pelvic MRI, and chest‐abdominal‐pelvic CT every 4 months were recommended in the first 2 years and every 6 months thereafter for up to 5 years.2.5The primary endpoint was the pCR rate. The secondary endpoints were R0 resection rate and safety in terms of adverse events, relapse‐free survival, overall survival, and recurrence pattern .The pCR rate of previous phase III trials in which SCRT was followed by surgical treatment was 0.5%–1%. With reference to these results and the fact that TNT will be added in this trial, we decided to examine whether 5% can be rejected in this trial. The expected pCR rate was set to 28% for patients treated with TNT followed by surgery as the expected value of the study treatment. With a pCR rate threshold of 5%, expected value of 28%, one‐sided significance level of 5%, and power of at least 80%, the sample size required by the exact binomial distribution method would be ≥19 patients. Based on the above, the expected total number of patients was set to 22. Considering the few dropouts, ineligible cases, and patients in whom resection was not performed, the target sample size was set to 27. The statistical setting was designed by a clinical statistician. The primary analysis population was a full analysis set (FAS) in which at least one dose of protocol therapy was administered, all selection criteria were met, no exclusion criteria were violated, and some data were available.The pCR rate was estimated for the FAS, and 90% exact binomial confidence bounds were calculated. The overall frequencies and percentages were summarized for the demographic and clinicopathological characteristics. All statistical analyses were performed using SAS version 9.4 (SAS Institute Inc.) and GraphPad Prism version 6.01 for Windows (GraphPad Software).33.1Thirty patients with LARC managed at five institutions between January 2021 and January 2022 were enrolled in this study. A flow diagram showing patient enrollment and progression through the study protocol is shown in Figure The clinical characteristics of the 30 enrolled patients are summarized in Table 3.2All patients received and completed the SCRT. The median treatment duration was 5 days . There were no discontinuations due to adverse events. Twenty‐nine patients received CAPOX at a median of 14 days range: 7–27 days) after the completion of radiotherapy. Chemotherapy initiation was postponed due to adverse events associated with radiotherapy in four patients (diarrhea). One patient withdrew their consent before receiving neoadjuvant chemotherapy. Twenty‐five patients (83.3%) completed six cycles of CAPOX. TNT was completed in 25 patients (83.3%) (Table 7 days af3.3Twenty‐nine patients (96.7%) were re‐evaluated for efficacy using MRI, colonoscopy, and a digital examination. MRI was performed at a median of 12 days  after the last chemotherapy dose or the decision to discontinue chemotherapy, and a median of 154 days  after the start of radiation therapy. The clinical response rates were as follows: cCR 43.3% (13/30), nCR 43.3% (13/30), iCR 10.0% (3/30), and not evaluable (NE) 3.3% (1/30) (Table 3.4Seven of the 30 patients underwent NOM 23.3%), whereas 20 patients underwent TME (66.7%)  (30% [95% CI 14.0%–50.8%]), and the final classification was ypStage 0 in six patients (30%), ypStage I in five patients (25%), ypStage II in five patients (25%), and ypStage III in four patients (20%) .In conclusion, this trial provided evidence that SCRT followed by six cycles of CAPOX for patients with LARC was feasible and well‐tolerated in Japanese patients with LARC. The long‐term efficacy of DFS and OS requires further exploration in future randomized trials.Authors made substantial contributions to conception and design, acquisition of data, and/or analysis and interpretation of data: Yoshinori Kagawa, Jun Watanabe, Mamoru Uemura, Koji Ando, Akira Inoue, Ichiro Takemasa, Koji Oba, Eiji Oki. Authors participating in drafting the article or revising it critically for important intellectual content: Yoshinori Kagawa, Jun Watanabe, Mamoru Uemura, Koji Ando, Akira Inoue, Ichiro Takemasa, Koji Oba, Eiji Oki. Authors giving final approval of the version to be published: Yoshinori Kagawa, Jun Watanabe, Mamoru Uemura, Koji Ando, Akira Inoue, Ichiro Takemasa, Koji Oba, Eiji Oki.None.Annals of Gastroenterological Surgery.The authors declare no conflicts of interest related to this study, except for Eiji Oki's conflict of interest regarding Chugai Pharmaceutical. The authors Jun Watanabe, Ichiro Takemasa, and Eiji Oki are editorial members of the The ENSEMBLE‐1 trials were conducted in accordance with the Declaration of Helsinki, the Japanese Ethical Guidelines for Medical and Health Research Involving Human Subjects, and the Clinical Trial Acts in Japan. Each trial was approved by the Osaka General Medical Center Certified Review Board. Written informed consent was obtained from all patients before enrollment.Data S1:Click here for additional data file.


RNA modification includes four main types, N6‐methyladenosine, N1‐methyladenosine, alternative polyadenylation (APA), and adenosine‐to‐inosine (A‐to‐I) RNA editing, involving 41 enzymes that serve as “writers”, “readers” and “erasers”. By collecting RNA modifying enzyme information in 1759 hepatobiliary malignancy (HBM) samples from 11 datasets, an RNA modification HBM Score (RH_score) was established based on unsupervised cluster analysis of RNA modification‐associated differentially expressed genes (DEGs). We identified the imbalanced expression of 41 RNA modification enzymes in HBM, which was scientifically categorized into two groups: RH_Score high and RH_Score low. A high RH_Score was associated with a worse prognosis and more immature immune cells in the tumor microenvironment (TME), while a low RH_Score was associated with a better prognosis and more mature immune cells in the TME. Further analysis using single‐cell databases showed that the high RH_Score was immune exhaustion in the TME. RH_Score was involved in transcriptional regulation and post‐transcriptional events in HBM. Additionally, resistant and sensitive drugs were selected based on RNA modification, and anti‐PD‐L1 therapy responded better with low RH_Score. In conclusion, our study comprehensively analyzes RNA modification in HBM, which induces TME changes and transcriptional and posttranscriptional events, implying potential guiding significance in prognosis prediction and treatment options. Based on RNA modification‐associated differentially expressed genes from 1659 hepatobiliary malignancy (HBM) samples from 10 datasets, an RNA modification HBM Score (RH_score) is scientifically established and tested in 100 hepatocellular carcinoma clinical samples, which demonstrates excellent efficacy in terms of prognosis and targeted treatment. A high RH_Score means a worse prognosis and more immature immune cells, while a low RH_Score has the opposite result. Furthermore, we designed an RH score model to predict the clinical prognosis, response to molecular targeted drugs and immunotherapy, and transcriptional and posttranscriptional events based on RNA modification‐regulated DEGs, thereby providing a novel panel of next‐generation sequencing for clinical translation.22.1In this study, we selected 41 RNA modification regulators Table  to perfoFirst, the prevalence of nonsilent somatic mutations in 41 regulators was assessed in HBM. Consistent with a previous study,Next, genome ontology (GO) analysis, genome set variation analysis (GSVA), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed to compare the mutant and non‐mutant groups of regulatory genes in the TCGA cohort Figure . We defi2.2To comprehensively understand the expression patterns of RNA modification regulators in HBM, a total of 424 samples from TCGA with clinical data were chosen for further study Table . A univap < 0.001). Next, we performed a KEGG enrichment analysis to evaluate the biological significance of these two clusters . We used this model to calculate the scores of various classifications, finding that the score in cluster1 was higher than that in cluster2 , discovering that patients with high RH_Score had poorer survival Figure . The AUCIn this study, HBM included three pathological types of liver cancer: HCC, intrahepatic cholangiocarcinoma (ICC), and mixed type (HCC+ICC). Among the three types of liver cancer, ICC is reported to have the highest malignant degree and the worst prognosis. To understand the relationship between the RH score and HBM pathological subtypes, the RH score of different HBM subtypes in the TCGA cohort was analyzed. We found that different HBM subtypes showed a significant difference in RH_Score, the RH_Score of the ICC group was the highest Figure . Additio2.4To comprehensively elaborate the immune environment in RNA modification molecular signatures, we performed a global niche atlas with cell classification and marker gene identification using a single‐cell sequencing dataset (GSE125449) without anti‐PD‐L1 treatment from the NCBI Public Data Platform Tables  and 10. Unsupervised clustering of macrophages (an important component of myeloid cells) and T cells were then performed with 11 clusters found, including four clusters for macrophages  and seven clusters for T cells  Figure . Usually2.5To further evaluate the role of the RH score in interpreting transcriptional and posttranscriptional events, we focused on the processes associated with RNA modification, including APA and A‐I editing. It has been reported that RNA modification patterns are related to different miRNA signatures with the effect of APA modification.p < 0.001) and CES2  exhibited significant lengthening, which showed shorter survival in patients with HBM  and POLH  were related to poorer survival time in HBM patients , ML323 , dihydrorotenone , alisertib , erlotinib , Wnt‐C59 , AGI‐6780 , while the others showed resistance, including AZD8186 , AMG‐319 , MK‐2206 , dasatinib , and BDP < 0.001 . In addition, drug sensitivity to RNA modification regulators was closely related to specific signaling pathways  with the anti‐PD‐L1 treatment Table . Consist2.7Given that the RH_Score appears to correlate with the TME Figure , we expl36A, m1A, APA, and A‐I RNA editing, are the most common and the most studied types and they are primarily mediated by the “writer”, “reader” and “eraser” enzymes and constitute key mechanisms for epigenetic regulation of tumorigenesis.As a rising research hotspot, the function of RNA modifications in certain cancers has been revealed. More than 100 different types of modifications have been shown to be present in RNA. Among them, four RNA modifications, namely, m+ T cells, which regulates durable neoantigen‐specific immunity.RNA modification enzymes also influenced immune infiltration of the TME, which played a significant role in tumor progression and prognosis. Researchers found that KIAA1429 (an m6A methyltransferase) resulted in less TME dendritic cell (DC) infiltration and decreased expression of MHC molecules.6Sig score according to 23 m6A regulators, aiming to estimate prognosis and immunotherapy. The WM_score presented by Chen et al.More importantly, a reliable predictive RH_Score model was established based on RNA modification enzymes to provide a brighter and more precise landscape for targeted drugs and immunotherapy applications. Many researchers have concentrated on this field. Chong et al.From the perspective of RNA modification enzymes, TME analysis may be a ray of dawn for hepatobiliary tumor precision medicine. Although we enrolled 41 RNA‐modifying enzymes, other participants in the RNA modification process required inclusion. In addition, the predictive performance of the RH score still needs testing in other tumors and immunotherapy regimens, such as anti‐PD‐L1, anti‐cytotoxic T‐lymphocyte antigen‐4, therapeutic antibody, and adoptive T cell transfer.4In this study, we comprehensively analyzed RNA modifications in HBM that induce TME changes and transcriptional and posttranscriptional events, and the results may have potential guiding significance in prognosis prediction and treatment options.55.1https://gdc‐portal.nci.nih.gov/) and UCSC Xena data website (https://xenabrowser.net/datapages/). We acquired mRNA expression data of liver cancer samples from 5 GEO datasets . Since these five datasets were gathered from different chip platforms with unclear clinical information and various confounding factors, we analyzed each data set individually to avoid false positive results.The mRNA expression data, miRNA expression data, mutation data, CNV data, clinical information, and survival data of liver cancer and cholangiocarcinoma were collected from the TCGA database (https://10xgenomics.com) was used to retain cells with cell gene numbers and UMI numbers within the mean ± 2 SD and with a mitochondrial gene ratio of less than 10% as high‐quality cells and then ready for downstream analysis. Seurathttps://satijalab.org/seurat/) was used for cell filtration, standardization, clustering, cell subgroup classification, and marker gene screening.The single‐cell dataset (GSE125449) was obtained from the NCBI Public Data Platform, which is single‐cell transcriptome profiling of HBM biospecimens from nine hepatocellular carcinoma and ten intrahepatic cholangiocarcinoma patients. Cell Ranger . Based on this dataset, we determined the relationship between the RH score and various cancer immunotherapies.Detailed clinical immunotherapy data were downloaded from the IMvigor210 dataset5.2https://cibersort.stanford.edu/). For chip expression, data after quantile normalization were collected, and for RNA‐seq expression, nonnormalized data were selected. The number of permutation tests was set to 1000.The relative abundance of 22 immune cell types in cancer samples was computed by the CIBERSORT, RRID:SCR_016955 algorithm .Supporting InformationClick here for additional data file.Supporting InformationClick here for additional data file.


Overweight also had a significant negative causality with longevity expectancy . Moreover, the findings tend to favor causal links between body fat mass/body fat percentage on aging proxy indicators, but not body fat‐free mass. This study provides evidence of the causality between overweight and accelerated aging  and lower longevity expectancy. Accordingly, the potential significance of weight control and treatment of overweight in combating accelerated aging need to be emphasized.It is reported that overweight may lead to accelerated aging. However, there is still a lack of evidence on the causal effect of overweight and aging. We collected genetic variants associated with overweight, age proxy indicators , etc., from genome‐wide association studies datasets. Then we performed MR analyses to explore associations between overweight and age proxy indicators. MR analyses were primarily conducted using the inverse variance weighted method, followed by various sensitivity and validation analyses. MR analyses indicated that there were significant associations of overweight on telomere length, frailty index, and facial aging . Moreover, the findings support the association of overweight and decreased longevity expectancy . Accordingly, the potential significance of weight control and treatment of overweight in combating accelerated aging need to be emphasized. BFFMbody fat‐free massBFMbody fat massBFPbody fat percentageBMIbody mass indexBWbody weightCHDcoronary heart diseaseDBPdiastolic blood pressureFAfacial agingFIfrailty indexGIANTGenetic Investigation of ANthropometric TraitsGSCANGWAS and Sequencing Consortium of Alcohol and Nicotine useGWASesgenome‐wide association studiesHbA1cglycosylated hemoglobinHOMA‐IRhomeostasis model assessment of insulin resistanceISischemic strokeIVinstrumental variableIVW‐FEfixed effects inverse variance weightedIVW‐MREmultiplicative random effects inverse variance weightedMAGICthe Meta‐Analyses of Glucose and Insulin‐Related Traits ConsortiumMRMendelian randomizationMR‐PRESSOMendelian randomization pleiotropy residual sum and outlierORodd ratioPLparental lifespansqPCRquantitative polymerase chain reactionRCTsrandomized controlled trialsSBPsystolic blood pressureSCserum creatinineSNPsingle nucleotide polymorphismTLtelomere lengthWHOWorld Health Organization1Aging is the accumulation of aging cells in organisms, accompanied by the decline of biological functions and a series of prominent features, including genetic and epigenetic changes  standard, it is defined as body mass index (BMI) ≥ 25 kg/mLimited by the quality of evidence, possible potential reverse causality and residual confounding, observational studies have been almost unable to identify a causal association between overweight and aging  data of overweight, age proxy indicators such as TL, FI and FA, and other traits, etc.22.12, while for controls was 18.5 kg/m2 ≤ BMI < 25 kg/m2.Genetic variants significantly associated with overweight were extracted from a large GWAS of Genetic Investigation of ANthropometric Traits (GIANT) consortium, which comprised 93,105 cases and 65,840 controls . Using a mixed linear model analysis  and relatedness), FA can be identified as an ordered categorical variable. Then statistics on the linear scale were transformed into log odd ratio (OR) using a Taylor expansion series. OR >1 indicate greater odds of looking youthful  and 423,999 . At the UK Biobank, the mean leukocyte TL was measured in the mixed leukocyte population by using the multiplex quantitative polymerase chain reaction (qPCR) technique, which expressed the TL as the ratio of telomere repeats to single copy genes (T/S ratio)  with 37,037 subjects from Dupuis et al. ; body weAll the exposure and outcome datasets were of European ancestry or mainly composed of European ancestry. There was no large‐scale crossover and overlap between participants that included in GWAS of overweight and GWASes of aging proxy indicators and longevity.The present study only used publicly available summary‐level statistics. Ethical approval is therefore not required.2.2p < 5 × 10−8) were selected as IVs from the GWAS datasets, respectively. Then, we pruned the candidate IVs for linkage disequilibrium (r2 > 0.001) and discarded variants that were within 1‐Mb distance from other IVs with a stronger association. R2, the proportion of exposure explained by IVs, can be calculated by the formula: R2 = 2 × β2 × EAF × (1 − EAF), where β was the estimated effect size of the SNPs and EAF indicated effect allele frequency. F‐statistic is a common index to evaluate weak instrumental bias, can be calculated by the following formula: F = R2/(1 − R2) × (N–k − 1)/k, where N was the sample size and k was the number of included SNPs. When the F‐statistic <10, we consider the genetic variation used as a weak IV, which may produce a certain bias to the results, so SNPs with F‐statistic <10 will be excluded.SNPs significantly associated with exposures or outcome , we used base (version 4.2.1), TwoSampleMR (version 0.5.6), MRInstruments (version 0.3.2), MRPRESSO (version 1.0) MendelianRandomization (version 0.6.0), data table (version 1.14.2) and ggplot2 (version 3.3.6) R package and related functions.Q test, MR‐PRESSO global test), pleiotropy test , and leave‐one‐out test , the multiplicative random effects IVW (IVW‐MRE) method should be used for assessing the causal effect.For two‐sample MR analysis, we evaluated the causal links between exposures  and outcomes  by fixed effects inverse variance weighted (IVW‐FE) method. We also used the simple median, simple mode, weighted mode, weighted median, MR Egger and MR pleiotropy residual sum and outlier (MR‐PRESSO) methods for additional analysis. Sensitivity analyses were performed to verify and adjust the validity and stability of the results, which included heterogeneity test (Cochrane's http://www.phenoscanner.medschl.cam.ac.uk/) for a confounding analysis , then summarize and analyze the related information about the SNPs, GWASes and Diseases. This not only helps to identify potential confounders for adjustment in multivariate analysis, but also helps us to explore the mediation and potential mechanism of causality.Although a series of statistical methods have been carried out in the sensitivity analyses, we used Phenoscanner V2 .For multivariable MR analysis, pooled several factors  in the analysis for adjustment. The IVW method was used for the multivariable analysis. Bonferroni correction was used for multiple comparisons, and its critical We used a mediation MR analysis (two‐step MR) to verify and analyze the mediators that mediated the associations between overweight and aging proxy indicators. Candidate mediators were mainly HbA1C, CHD, and IS (it should be noted that they were included in the deficits of FI). The specific method includes two steps. Step (1): to find significant SNPs from the GWAS about exposure, remove SNPs with linkage disequilibrium, and then extract the remaining SNPs from the GWAS of the mediating variable. It is necessary to ensure that the remaining SNPs are not directly related to confounding factors and mediating variable. Finally, the causal effect of exposure on mediator (assume beta1) are calculated. Step (2): Use the same method to calculate the causal effect of mediator on outcome (assume it is beta2). Assume that the causal effect of exposure on outcome is beta0. The following conditions exist: (i) If beta0, beta1, and beta2 are all significant, this indicates that there is a causal association between exposure and outcome, and this association may be partially mediated by mediating variables. beta1*beta2 can be used as the mediating effect from exposure to outcome, and its mediating proportion can also be calculated ((beta1*beta2)/beta0). (ii) If beta0 is not significant, but beta1 and beta2 are both significant, the association from exposure to outcome can be considered to be completely mediated by this mediator. (iii) If beta0 is significant, but at least one of beta1 and beta2 is not significant, there is no mediating effect mediated by this mediating variable in the causal association of exposure on outcome  was excluded . Overweight was significantly associated with decreased telomere length, increased FI and FA . Leave‐one‐out tests suggested that the associations between overweight and TL, FI, and FA were effective and sensitive, while the association between overweight and TL was less robust  . Overweight was associated with decreased longevity expectancy  Figure .3.3β = −0.129, 95% CI = −0.173 to −0.084, p < 0.0001), but the reverse causality was not significant , but there was no causality of HOMA‐IR on aging proxy indicators . There were causal associations of BW on FI and FA , but not on TL. BFFM only significantly associated with FA . Although the IVW method showed a causal link between BFFM and FI, the MR‐Egger method showed an opposite direction, suggesting that the causality was invalid , while hip circumference, waist circumference and waist‐to‐hip ratio had significant positive causal effects on FA . After adjusted for BMI, only waist‐to‐hip ratio was significantly associated with FI, and waist circumference was significantly associated with FA  . After adjusted for all factors at once, the causal association of overweight and FA remained significant (p = 0.0001), while the association between overweight and FI was suggestive (p = 0.0245).To further estimate the associations between overweight and aging proxy indicators, we performed multivariate MR Analyses Figure . No sing3.9Based on the results of confounding analysis and multivariate analysis, we analyzed the mediating effects of HbA1c, CHD, and IS on the causality between overweight and aging proxy indicators Figure . The res4In this study, based on the large‐sample GWASes data, we mainly evaluated the associations between overweight and aging proxy indicators using MR analysis. We performed several MR analysis methods including two‐sample analysis, multivariate analysis and mediation analysis, which showed that (1) overweight is probably associated with a higher risk of decreased TL, increased FI, increased FA and decreased longevity expectancy ; (2) overweight seems to be causally associated with lower parental life expectancy, but the reverse causality was not valid; (3) there is significant causality between HOMA‐IR and overweight, but not with aging proxy indicators; (4) the findings tend to favor causal links between BFM/BFP on aging proxy indicators, but not BFFM; (5) regardless of overweight or not, waist‐to‐hip ratio is a risk factor for increased FI, and waist circumference is a risk factor for increased FA; (6) CHD and IS might mediate the association of overweight on both FI and FA.Aging is a complex biological process, mainly manifested as TL decrease at the molecular level  and decreased longevity expectancy. Accordingly, the potential significance of weight control and treatment of overweight in combating accelerated aging need to be emphasized. The findings additionally suggest the necessity of improving and treating insulin resistance against overweight and accelerated aging.Conceptualization: Xiaolei Jin; Investigation: Zong Chen, Zhiyou Chen; Writing, review, and editing: all authors.The authors have no conflicts of interest to declare.Figure. S1. The leave‐one‐out tests of overweight on aging proxy indicators Click here for additional data file.Figure. S2. SNPs' effect size of overweight on telomere lengthClick here for additional data file.Figure. S3. Mendelian randomization analysis of the effect of aging proxy indicators  on overweightClick here for additional data file.Figure. S4. The leave‐one‐out tests of overweight on longevity Click here for additional data file.Figure. S5. Bidirectional Mendelian randomization analysis of the effect between overweight and parental lifespansClick here for additional data file.Figure. S6. Mendelian randomization analysis of the effect of HOMA‐IR on overweight and aging proxy indicators Click here for additional data file.Figure. S7. Mendelian randomization analysis of the effect of obesity indices on aging proxy indicators Click here for additional data file.Table. S1.Click here for additional data file.


ERBB2)–positive breast cancer. We aimed to study tumor HER2 expression and its effects on T‐DM1 responses in patients with HER2‐positive urothelial bladder cancer (UBC) or pancreatic cancer (PC)/cholangiocarcinoma (CC). In the phase II KAMELEON study (NCT02999672), HER2 status was centrally assessed by immunohistochemistry, with positivity defined as non‐focal homogeneous or heterogeneous overexpression of HER2 in ≥30% of stained cells. We also performed exploratory biomarker analyses  on tissue samples collected from study participants and consenting patients who failed screening. Of the 284 patients successfully screened for HER2 status , 13 with UBC, four with PC, and three with CC fulfilled eligibility criteria. Due to recruitment difficulty, the sponsor terminated KAMELEON prematurely. Of the five responders in the UBC cohort , HER2 expression was heterogeneous in two and homogeneous in three. The one responder in the PC/CC cohort had PC, and the tumor displayed homogeneous expression. In the biomarker‐evaluable population, composed of screen‐failed and enrolled patients, 24.3% (9/37), 1.5% (1/66), and 8.2% (4/49) of those with UBC, PC, or CC, respectively, had HER2‐positive tumors. In a gene‐protein assay combining in situ hybridization with immunohistochemistry, greater HER2 homogeneity was associated with increased ERBB2 amplification ratio. In conclusion, KAMELEON showed that some patients with HER2‐positive UBC or PC can respond to T‐DM1 and provided insight into the prevalence of HER2 positivity and expression patterns in three non‐breast tumor types.The antibody‐drug conjugate trastuzumab emtansine (T‐DM1) is approved for human epidermal growth factor receptor 2 (HER2/ The phase II KAMELEON study investigated the efficacy of T‐DM1 in selected HER2‐positive non‐breast tumors. Although KAMELEON was terminated prematurely due to recruitment difficulty, the study demonstrated that patients with HER2‐positive urothelial bladder cancer or pancreatic cancer can respond to T‐DM1. This study provided insight into the prevalence of HER2 positivity and expression patterns in these tumor types and may inform the use of T‐DM1–based regimens in HER2‐positive non‐breast tumors. With equivocal ISH test results , the final decision is made based on the IHC result.By IHC, a breast tumor is considered HER2‐positive if scored as IHC 3+ based on circumferential membrane staining that is complete, intense, and in >10% of tumor cells. By ISH, a breast tumor is considered HER2‐positive if the ratio of ERBB2 gene levels. For example, the rate of HER2‐positivity in urothelial bladder cancer (UBC) ranges from 17% to 80% based on IHCERBB2 gene amplification in pancreatic cancer. In one study, only 64% of pancreatic tumors graded as IHC 3+ exhibited ERBB2 amplification.ERBB2 gene amplification rates were higher in extrahepatic biliary tract carcinomas than in intrahepatic cholangiocarcinoma (19.9% vs. 4.8%).HER2 testing guidelines exist only for tumor types with approved HER2‐targeted therapies ,ERBB2‐mutant/HER2‐overexpressing lung cancersERBB2‐mutant metastatic non‐small cell lung cancer and HER2‐positive recurrent or metastatic salivary gland tumors.In the United States and the European Union, T‐DM1 is approved for use in patients with previously treated HER2‐positive metastatic breast cancer and in patients with HER2‐positive early breast cancer who have residual invasive disease following neoadjuvant treatment. Previous clinical trials have demonstrated the efficacy of HER2‐targeted therapies in non‐breast solid tumors, including biliary tract, non‐small cell lung, colorectal, and bladder cancers,22.1ClinicalTrials.gov NCT02999672), pre‐trial biomarker analyses were undertaken to determine a HER2 threshold that would potentially lead to treatment responses in UBC or pancreatic cancer/cholangiocarcinoma. To this end, tumor samples were analyzed centrally using IHC at Targos Molecular Pathology GmbH for HER2 staining intensity  and pattern  via the PATHWAY anti‐HER‐2/neu (4B5) assay . The PATHWAY anti‐HER‐2/neu [4B5] IHC assay was performed in accordance with the manufacturer's instructions.Although the cutoffs for HER2‐positivity in breast and gastric cancers may be useful in defining similar values in other tumor types, the thresholds for treatment benefit may differ across indications. Thus, in preparation for KAMELEON . It was investigator‐initiated, but eventually received corporate sponsorship (Roche). KAMELEON, which was conducted at 10 sites across Italy, Spain, and the Netherlands, sought to determine the best tumor response following treatment with T‐DM1 in patients with HER2‐overexpressing solid tumors. Eligible adults (≥18 years) had HER2‐positive locally advanced (unresectable and not treatable with curative intent) or metastatic UBC or locally advanced or metastatic pancreatic cancer/cholangiocarcinoma measurable per Response Evaluation Criteria in Solid Tumors (RECIST), version 1.1.In the pre‐trial IHC analyses, 25.0% (11/44) of patients with UBC, 0% (0/62) with pancreatic cancer, and 7.1% (3/42) with cholangiocarcinoma had tumors exhibiting complete membrane staining in ≥30% of stained cells. Since HER2 heterogeneity is prevalent in UBCThis study was performed in compliance with the Declaration of Helsinki, the International Conference on Harmonization Guidelines for Good Clinical Practice, and applicable national and local regulatory requirements. The study protocol was approved by the Independent Ethics Committee or Institutional Review Board at each participating site. Written informed consent was obtained from patients for the clinical and exploratory biomarker analyses.2.3The primary efficacy objective was to evaluate the best overall response (BOR), with tumor responders defined as individuals with confirmed complete response (CR) or partial response (PR), as determined by the study investigator using RECIST 1.1. Secondary efficacy endpoints included PFS  and OS (time from the first day of study treatment until death due to any cause). Adverse events (AEs), which were recorded throughout the study, were coded to the Medical Dictionary for Regulatory Activities (version 21.0) and graded per National Cancer Institute Common Terminology Criteria for Adverse Events (version 4.03). A serious AE was defined as any AE that was fatal or life‐threatening, required or prolonged hospitalization, resulted in persistent or significant disability/incapacity, was a congenital anomaly/birth defect in a neonate/infant born to a mother exposed to study drug, or was a significant medical event (per investigator's opinion). The primary pharmacokinetic objective was to quantify serum/plasma concentrations of T‐DM1 to determine exposure. Additional details regarding assessments are available in the Data ERBB2 copy number by a novel gene‐protein assay combining ISH  with IHC  on a single slide. As described previously,ERBB2 probe and a digoxigenin (DIG)‐labeled CEN17 probe. ERBB2 and CEN17 were detected via the ultraView Silver ISH DNP and ultraView Red ISH DIG Detection Kits, respectively , with ERRB2 developed first. Slides were then counterstained with hematoxylin II  and visualized via light microscopy, with ERBB2 appearing as a black signal, CEN17 as a red signal, and HER2 as a brown stain. Tumors were evaluated in accordance with American Society of Clinical Oncology/College of American Pathologists guidelines for breast cancer.To explore the relationship between biomarkers and tumor response and to evaluate biomarkers that could increase our understanding of the underlying biology of these cancers, the following exploratory biomarker analyses were undertaken: determination of HER2 protein expression pattern in correlation to 2.4The sample size calculation was based on Simon's two‐stage design with early futility analysis to test the null hypothesis (BOR ≤ 5%) against the alternative hypothesis (BOR ≥ 20%). With a one‐sided alpha of 5%, 27 patients were required to reject the null hypothesis with 80% power. To allow for a dropout rate of 10%–15%, 32 patients per cohort were targeted for enrollment. Evidence of potential clinical activity would be concluded if at least four patients in a single cohort responded to study treatment.The number and percentage of responders , with the corresponding two‐sided Clopper–Pearson 90% confidence intervals (CIs), were provided for the primary efficacy endpoint. Time‐to‐event measures were analyzed using the method of Kaplan–Meier; medians and two‐sided 95% CIs were provided when applicable. AEs were summarized using standard frequency tables (number and percentages of patients with events). For patients receiving T‐DM1 2.4 mg/kg qw, blood samples for the pharmacokinetic assessments were drawn during cycle 1 , cycle 2 (pre‐dose on Day 1), and cycle 4 (pre‐dose and 15–30 min post‐dose on Day 1). For patients receiving T‐DM1 3.6 mg/kg q3w, blood samples were drawn during cycle 1 (pre‐dose and 15–30 min post‐dose on Day 1), cycle 2 (pre‐dose on day 1), and cycle 4 (pre‐dose and 15–30 min post‐dose on Day 1). All efficacy and safety analyses were based on the safety population (patients who received ≥1 dose of T‐DM1). Statistical analyses were performed using SAS version 9.2 or higher. The last patient's last visit occurred April 10, 2018, and the database was locked June 8, 2018.33.1n = 13; pancreatic cancer, n = 4; cholangiocarcinoma, n = 3) met all eligibility criteria . Of these, 25% (17/69), 4% (5/133), and 7% (6/82) were HER2‐positive, respectively, and 20 patients  and one displaying intermediate HER2 protein expression and an ERBB2 amplification ratio by gene‐protein assay of 1.65. The one responder in the pancreatic cancer/cholangiocarcinoma cohort had pancreatic cancer and received T‐DM1 2.4 mg/kg qw  of 38.5% (16.57–64.52%) and 14.3% (0.73–52.07%), respectively. No patient in either cohort had a CR Table . In termqw Table . This pan = 4) and 0%, respectively. Three patients (23.1%) experienced fatal AEs ; all fatal AEs occurred in patients who received T‐DM1 2.4 mg/kg qw  of patients in the UBC cohort experienced ≥1 AE, all considered treatment‐related  and trough concentration (Cmin), following administration of 2.4 mg/kg qw in patients with UBC (n = 6–13) were similar to historical data from patients with metastatic breast cancer (n = 15) , a trend of lower exposure was observed for these patients relative to those with either UBC or metastatic breast cancer , in whom a lower T‐DM1 exposure was found relative to patients with metastatic breast cancer.max across cycles was low (2.13–4.01 ng/mL) and largely comparable across indications .T‐DM1 exposures at cycle 1, as measured by maximum concentration (C) Figure . Althougr Figure . However3.4Of the 284 patients successfully screened for HER2 overexpression via IHC, 207 consented to the biomarker analyses. However, biomarker data were not available for 55 patients, owing to insufficient or poor‐quality tumor tissue or to assay‐related issues. Thus, the biomarker‐evaluable population was comprised of 152 patients.ERBB2 amplification ratio  , focal , heterogeneous , and homogeneous  HER2 protein expression by IHC, respectively. Among patients with UBC, pancreatic cancer, or cholangiocarcinoma in the biomarker‐evaluable population, only 24.3% (9/37), 1.5% (1/66), and 8.2% (4/49), respectively, exhibited heterogeneous or homogeneous expression of HER2  Figure . In the o Figure .4In this phase II study of non‐breast tumor types, HER2‐positivity was detected via gene‐protein assay in 24.3% of patients with UBC, 1.5% with pancreatic cancer, and 8.2% with cholangiocarcinoma. The relatively low prevalence of HER2‐positivity resulted in poor accrual and premature termination of the study. Although centralized HER2 testing may help identify these individuals, the recruitment of such patients is likely to be prohibitively slow if HER2‐positivity rates are as low as those encountered, especially in pancreatic cancer. For biomarker‐driven clinical studies to succeed, we recommend that HER2 testing become part of the standard diagnostic work‐up of non‐breast cancers. Moreover, novel antibody‐drug conjugates like trastuzumab deruxtecan and trastuzumab duocarmazine have resulted in clinically meaningful responses in patients with tumors expressing low HER2 levels,n = 5). HER2 heterogeneity (30%–79% of stained cells) has been reported in ~10% of advanced breast tumorsFor each of the three cancers studied in KAMELEON, no meaningful differences were observed regarding the proportion of patients with IHC 3+ tumors exhibiting heterogeneous vs. homogenous HER2 staining. Among patients with metastatic UBC, the HER2 staining pattern did not appear to influence the response to T‐DM1, but the number of responders was too small to make a reliable comparison . Only one patient with pancreatic cancer and two with cholangiocarcinoma had tumors categorized as strong. In patients with IHC 1–2+ tumors, a positive association with ERBB2 copy number was seen in UBC, but the relationship was less evident in pancreatic cancer and cholangiocarcinoma. Although intriguing, the results of the biomarker analyses should be interpreted with caution as they were exploratory. In advanced breast cancer, HER2 heterogeneity has been associated with the presence of certain mutations, such as in PIK3CA,The concordance between HER2 IHC score and the gene‐protein assay and between ISH and the gene‐protein assay has been estimated at 93% and 96%, respectively.ERBB2 copy number,ERBB2 copy number and HER2 overexpression in UBC, pancreatic cancer, or cholangiocarcinoma. In HER2‐positive breast cancer, the concordance between HER2 at the protein and genetic levels is high. For example, in an Australian study examining 53,402 ISH tests, 196 were identified as discordant to IHC performed at the local laboratory. Upon ISH re‐testing at a central laboratory, 12 (6.1%) remained discordant, with only one sample found to be a false‐positive (IHC 3+/ISH‐negative). The other 11 samples were considered either IHC 0 or 1+  and displayed low ERBB2 amplification; one also exhibited clonal heterogeneity.ERBB2 copy number predicts the response to trastuzumab plus chemotherapy,ERBB2 copy number affected the observed responses to T‐DM1. Furthermore, our study did not distinguish HER2 testing results from primary versus metastatic tumor tissue. Prior studies have noted discordance in HER2 status between the primary tumor and metastases in multiple cancer types, including breast, endometrial, and urothelial.In contrast to guidelines developed for breast and gastric cancers that also consider n = 7). Of note, the AEs observed in this study were generally consistent with the known safety profile of T‐DM1. Importantly, the three AEs leading to death were not judged by study investigators to be treatment‐related.Due to early termination, KAMELEON was unable to address its primary and secondary objectives fully. Per the original study design, an objective response (CR or PR) in at least four of 27 patients per cohort would have been regarded as evidence of promising efficacy. Five of 13 patients with previously treated HER2‐positive metastatic UBC‐administered single‐agent T‐DM1 exhibited a PR, resulting in an ORR of 38.5%. However, the treatment of metastatic UBC has evolved since KAMELEON was initially planned. PD‐1 or PD‐L1 checkpoint inhibitors (pembrolizumab or atezolizumab), enfortumab vedotin, and erdafitinib were granted accelerated approval by the United States Food and Drug Administration for this indication. For the pancreatic cancer/cholangiocarcinoma cohort, it was not possible to conclude the presence/absence of an efficacy signal due to the small number of enrolled patients  are currently recruiting. Results from these trials may ultimately help inform on the use of T‐DM1‐based regimens in HER2‐positive non‐breast tumors, such as those studied in KAMELEON.Several early‐phase studies exploring HER2‐targeted therapies in non‐breast tumors, as well as a T‐DM1 combination therapy in breast cancer, may have implications for the treatment of the tumor types studied in KAMELEON. In a phase I study, trastuzumab deruxtecan led to an almost 80% reduction in tumor size in a patient with cholangiocarcinoma.In conclusion, KAMELEON provided preliminary insight into the prevalence of HER2‐positivity, as well as the patterns of HER2 expression, in patients with locally advanced or metastatic non‐breast tumors. The efficacy of single‐agent T‐DM1 observed in patients with advanced UBC is encouraging and suggests that HER2 may represent a viable treatment target for these patients. This is supported by data from a phase I study of trastuzumab duocarmazine, where four of 16 patients with HER2‐expressing urothelial cancer achieved PR.Daniel Castellano: Formal analysis ; writing – review and editing . Derk Jan A. de Groot: Conceptualization ; methodology ; writing – review and editing . Elisabeth de Vries: Conceptualization ; formal analysis ; investigation ; methodology ; resources ; writing – original draft ; writing – review and editing . Emile E. Voest: Conceptualization ; investigation ; methodology ; resources ; writing – review and editing . Gilles Erb: Conceptualization ; resources ; writing – review and editing . Giuseppe Viale: Conceptualization ; formal analysis ; methodology ; validation ; writing – review and editing . Josep Tabernero: Conceptualization ; formal analysis ; methodology ; writing – review and editing . Julia Naab: Data curation ; resources ; writing – review and editing . Luca Gianni: Conceptualization ; investigation ; methodology ; resources ; writing – review and editing . Martijn Lolkema: Conceptualization ; investigation ; methodology ; resources ; writing – original draft ; writing – review and editing . Margarita Donica: Formal analysis ; writing – review and editing . M. S. van der Heijden: Investigation ; resources ; writing – review and editing . Regula Deurloo: Conceptualization ; formal analysis ; investigation ; methodology ; resources ; supervision ; writing – review and editing . Josef Rüschoff: Conceptualization ; formal analysis ; methodology ; validation ; writing – review and editing .EGEdV reports institutional financial support for serving as an advisor to Daiichi Sankyo, Merck, National Surgical Adjuvant Breast and Bowel Project, Pfizer, Sanofi, and Synthon, as well as institutional financial support for participating in clinical trials or undertaking contracted research for Amgen, AstraZeneca, Bayer, Chugai Pharma, CytomX Therapeutics, G1 Therapeutics, Genentech, Nordic Nanovector, Radius Health, Regeneron, Roche, Crescendo, Servier, and Synthon. JR reports institutional (Targos) financial support for biomarker testing, has served as advisor to Roche, Genentech, Merck Sharpe & Dohme, Daiichi Sankyo, AstraZeneca, GlaxoSmithKline, and Exact Sciences, and is co‐founder of Targos. ML has received research grants to the institute from Sanofi, JnJ, MSD, and Astellas, has served as advisor to Incyte, Amgen, Janssen Cilag B.V., Bayer, Servier, Roche, INCa, Pfizer, Sanofi Aventis Netherlands BV, Astellas, Astra Zeneca, Merck Sharp and Dome, Novartis, and Julius Clinical. JT reports personal financial interest in the form of scientific consultancy role for Array Biopharma, AstraZeneca, Avvinity, Bayer, Boehringer Ingelheim, Chugai, Daiichi Sankyo, F. Hoffmann‐La Roche Ltd, Genentech Inc, HalioDX SAS, Hutchison MediPharma International, Ikena Oncology, IQVIA, Lilly, Menarini, Merck Serono, Merus, MSD, Mirati, Neophore, Novartis, Orion Biotechnology, Peptomyc, Pfizer, Pierre Fabre, Samsung Bioepis, Sanofi, Seattle Genetics, Scandion Oncology, Servier, Taiho, Tessa Therapeutics, and TheraMyc.; reports educational collaboration with Imedex, Medscape Education, MJH Life Sciences, PeerView Institute for Medical Education, and Physicians Education Resource (PER); and declares institutional financial interest in the form of financial support for clinical trials or contracted research for Amgen Inc, Array Biopharma Inc, AstraZeneca Pharmaceuticals LP, BeiGene, Boehringer Ingelheim, Bristol‐Myers Squibb, Celgene, Debiopharm International SA, F. Hoffmann‐La Roche Ltd, Genentech Inc, HalioDX SAS, Hutchison MediPharma International, Janssen‐Cilag SA, MedImmune, Menarini, Merck Health KGAA, Merck Sharp & Dohme, Merus NV, Mirati, Novartis Farmacéutica SA, Pfizer, Pharma Mar, Sanofi Aventis Recherche & Développement, Servier, Taiho Pharma USA Inc, Spanish Association Against Cancer Scientific Foundation, and Cancer Research UK. LG has served on advisory boards for ADC Therapeutics, AstraZeneca, Celgene, Eli Lilly, G1 Therapeutics, Genentech, Genomic Health, Merck Sharp & Dohme, Oncolytics Biotech, Odonate Therapeutics, Onkaido Therapeutics, Roche, Pfizer, Taiho Pharmaceutical, Hexal Sandoz, Seattle Genetics, Synthon, Zymeworks, and Sanofi‐Aventis; has served as a consultant for selected programs of Forty Seven (CD47), GENENTA, METIS Precision Medicine, Novartis, Odonate Therapeutics, Revolution Medicines, Synaffix, Zymeworks, Menarini Ricerche, Amgen, and Biomedical Insights Inc; has received research support paid to his institution from Zymeworks and Revolution Medicines; and is co‐inventor of European Patent Application N. 12195182.6 and 12196177.5, titled “PDL‐1 expression in anti‐HER2 therapy”‐Roche (no compensation provided). EV has served as a consultant for Roche with an honorarium given to his institution, and his institution received research funding from Roche. DJAdG has no disclosures to report. DC has served as a consultant or advisor to Janssen Oncology, Roche/Genentech, Astellas Pharma, AstraZeneca, Pfizer, Novartis, Ipsen, Bristol‐Myers Squibb, MSD Oncology, Bayer, Lilly, Sanofi, Pierre Fabre, and Boehringer Ingelheim; has received research funding from Janssen Oncology; has received support for travel/accommodations from Pfizer, Roche, Bristol‐Myers Squibb, and AstraZeneca Spain. GE is a salaried employee of Roche. JN is an employee of Hays AG contracted by Roche for technical and operational support of tissue sample analysis and data management in the conduct of the study. MD was an employee at Roche at the time work was conducted. RD is a salaried employee of, and owns stock in, Roche. MSvdH has received research grants (paid to the institute) from BMS, AstraZeneca, Roche and 4SC and has served as an advisor (fees paid to the institute) to Roche, Pfizer, Astellas, Astra Zeneca, Merck Sharp and Dome, BMS, and Janssen. GV has served as a consultant to Novartis, Roche, Merck Sharpe & Dohme, Bayer, Menarini, Daiichi Sankyo, and AstraZeneca.Data S1.Click here for additional data file.


Furthermore, we demonstrate the use of flight-like instrumentation after exposure to space-like ionizing radiation. Our findings will inform the development of novel and improved biosensors and technologies for future missions to deep space.With the imminent human exploration of deep space, it is more important than ever to understand the biological risks of deep space radiation exposure. The BioSentinel mission will be the first biological payload to study the effects of radiation beyond low Earth orbit in 50 years. This study is the last in a collection of articles about the BioSentinel biological CubeSat mission, where budding yeast cells will be used to investigate the response of a biological organism to long-term, low-dose deep space radiation. In this study, we define the methodology for detecting the biological response to space-like radiation using simulated deep space radiation and a metabolic indicator dye reduction assay. We show that there is a dose-dependent decrease in yeast cell growth and metabolism in response to space-like radiation, and this effect is significantly more pronounced in a strain of yeast that is deficient in DNA damage repair ( As we venture deeper into space for longer durations, we need to understand the biological risks that long-term spaceflight exposure can impose on organisms, and how these risks can be prevented or mitigated. Such deep space missions are expected to require significant biomedical and technological countermeasures to protect humans from the chronic radiation exposure they will encounter. Chronic exposure to galactic cosmic rays (GCRs), high-energy solar protons, and the possibility of large solar particle events poses the most significant health risks to humans, potentially increasing the risk of astronauts developing cancer as well as degeneration of the central nervous system, which can result in cognitive and behavioral impairment or neurological disorders , yeast and humans share many mechanisms involved in the response to DNA damage and in DNA repair, including the response to space-like ionizing radiation (IR).Current missions beyond low Earth orbit (LEO) are limited in the types of organisms they can use for biological research. The extended prelaunch periods, where biology remains loaded in the payload for multiple months under ambient or uncontrolled conditions, and long mission durations currently limit such voyages to model organisms that can remain dormant for prolonged periods. The budding yeast et al., et al., Moreover, many genes involved in human diseases and carcinogenesis were first discovered and studied using budding yeast. The yeast intended for experiments during the BioSentinel mission will have been loaded on the launch vehicle for over 2 years by the time they have been rehydrated in space, further highlighting the value and suitability of this species to biological research in deep space. We previously optimized yeast survival for the BioSentinel mission by air drying cells in 10% trehalose, which acts as a defense against the stresses of desiccation  at Brookhaven National Laboratory. In BioSentinel, after exposure to space radiation at varying doses, the desiccated cells will be rehydrated and their subsequent metabolism measured during the growth phase using the alamarBlue (aB) metabolic indicator dye  strains used in this study. Both strains are diploid prototrophic derivatives of the W303 background (MATa/MATα ADE2 CAN1 HIS3 LEU2 TRP1 URA3).Standard genetic cross and tetrad dissection procedures were used to generate the WT (YBS71-1) and 2.2.et al., 7 cells in 1 mL of 10% trehalose . Ten microliter aliquots of the 1 × 107 cell suspension (containing ∼105 cells) were gently dispensed into the bottom edge of the wells of 96-well Stripwell™ microplates  or onto the sidewall of each microfluidic card well , and the cells were air dried in a 23°C incubator, 20–30% relative humidity, for 7 days. Yeast cells in fluidic cards were air dried inside sterile boxes at the same conditions before card sealing using a pneumatic press  growth medium containing 1 × aB metabolic indicator dye  before each exposure  for plate reading. All experiments were performed in triplicate.WT and 2.3.2.rad51Δ yeast cells in microwell plates in both a desiccated state and liquid suspension were placed in the beam line at NSRL and exposed to 0, 0.01, 0.1, 0.25, 0.5, 1, or 2.5 Gy of 300 MeV/n iron (Fe-56). WT cells were exposed to 0, 1, or 2.5 Gy of 300 MeV/n iron. After sample release, three wells of dried cells per condition were rehydrated with 100 μL 1 × aB+SC, incubated for 30 min, then gently pipette mixed. Cell suspensions were then transferred to clear 96-well microplates for plate reading.Desiccated cells in microfluidic cards were exposed to 1 GeV protons (H-1) at 0 and 25 cGy at NSRL. Once the card radioactivity reached background levels, the samples were released from NSRL, ∼4 h after the proton exposures. The fluidic cards were then mounted on custom-made fluidic manifolds and filled with 1 × aB+SC medium using a peristaltic pump. Optical measurements were performed as described below.2.3.3.et al., Simplified 5-ion GCR simulations were conducted at NSRL. Simulations consisted of six sequential beams, including two proton and one helium energies, in addition to three heavy ion species  (Simonsen 2.4.B] below) was calculated for each experimental well using the following formula, modified from the manufacturer's manual to account for optical differences related to cell density (750 nm):Following irradiation (and after rehydration for samples exposed in a desiccated state), microplate reader optical measurements of yeast cells in 1 × aB+SC were taken once per hour on Molecular Devices SpectraMax 250/340 plate readers at 570 nm (detects concentration of pink aB), 600 nm (detects concentration of blue aB), and 750 nm (detects cell density or turbidity) for at least 48 h. Percent reduction of aB  of the cells.R1 = constant (ratio of cell density observed at 600 to 750 nm).R2 = constant (ratio of cell density observed at 570 to 750 nm).P = constant (ratio of pink-form aB observed at 600 to 570 nm).B = constant (ratio of blue-form aB observed at 570 to 600 nm).B]0 = percent reduction of aB at time zero.[where:R1, R2, P, and B were changed accordingly. We were unable to use the same wavelengths due to constraints of the SpectraMax 250/340 plate readers. Preliminary tests confirmed that aB reduction curves were not significantly different at these wavelengths (data not shown).The data were plotted in Microsoft Excel. Note that percent reduction of aB in flight-like microfluidic cards was calculated using the same formula. However, the light emitting diode (LED) wavelengths measured in cards are 570, 630, and 850 nm. The values used for the constants 2.5.et al., et al., Once sealed, the cards containing the desiccated yeast cells were exposed to 1 GeV protons at NSRL. After filling with 100 μL 1 × aB+SC medium, optical measurements were performed by using flight-like LED emitter and detector boards (Padgen 2.6.t-test (Supplementary Methods). A p-value of <0.05 denotes radiation sensitivity in comparison with the 0 Gy (unexposed) dose or a significant difference in metabolic response to radiation between doses. Statistical analyses were completed in Microsoft Excel, and graphs were created using GraphPad Prism.To assess the metabolic effects of radiation, triplicate values of percent reduction of aB at each radiation dose were averaged and plotted over time with standard deviation error bars. To compare differences in aB reduction across samples, we used the threshold slope, which is the slope from 10% reduction in aB to 85% reduction, as a first parameter of interest (Supplementary Methods). A value of 10% was chosen because detectable cell growth does not typically occur until aB reaches ∼10% or 5–7 h. The 85% value is based on the point at which all samples within the experiment have reached a common maximum threshold of aB reduction. For the fluidic card analysis, a top threshold of 70% was used since there were many replicates that did not reach higher than 70% reduction in aB. Slope values were compared between each radiation dose condition using the Student 3.3.1.rad51Δ yeast were desiccated and rehydrated with SC medium containing aB, they were exposed in liquid suspension to increasing doses of gamma radiation (rad51Δ cells to gamma IR is shown in rad51Δ mutant strain was sensitive to gamma radiation doses as low as 1 Gy (p = 0.039), and that there is an increasing dose-dependent sensitivity at 2.5 Gy (p = 0.033), 5 Gy (p = 0.014), 10 Gy (p = 0.003), 20 Gy (p = 0.0006), 30 Gy (p = 0.0002), 40 Gy (p = 0.0001), 50 Gy (p = 0.00008), and 60 Gy (p = 0.00007)  .rad51Δ mutant, as this strain showed a dose-dependent sensitivity starting at 20 Gy (0.021) and at subsequent doses of 30 Gy (0.001), 40 Gy (p = 0.002), 50 Gy (p = 0.002), and 60 Gy (p = 0.001) (r = 0.9624 for WT and r = 0.9252 for rad51Δ) and no radiation (r = 0.968 for WT and r = 0.9453 for rad51Δ)  . Using a rad51Δ) .3.2.rad51Δ strains exhibited a dose-dependent response to high-energy protons in desiccated form , then further sensitivity at 0.25 Gy (p = 0.001), 0.5 Gy (p = 0.0002), 1 Gy (p = 0.02), and 2.5 Gy (p = 0.0001) (p = 0.01), 0.5 Gy (p = 0.03), 1 Gy (p = 0.033), and 2.5 Gy (p = 0.0001)   and in t 0.0001) .p = 0.036) and 2.5 Gy (p = 0.043) in liquid suspension (p = 0.025) and 2.5 Gy (p = 0.005) when cells were exposed, while in the desiccated state and rehydrated for aB measurements , 0.1 Gy (p = 0.009), 0.35 Gy (p = 0.0001), and 1 Gy (p = 0.0002) (rad51Δ cells were sensitive at 0.05 Gy (p = 0.009), 0.1 Gy (p = 0.004), 0.35 Gy (p = 0.002), 0.5 Gy (p = 0.0018), and 1 Gy (p = 0.001)  . Similar= 0.001) . These p3.4.rad51Δ strains in a more flight-like environment—exposed in desiccated state inside microfluidic cards using a flight optical detection system  of each of the three measured wavelengths directly. These measurements should follow a certain pattern over time as the yeast grow, metabolize, and reduce the aB after radiation exposure . The redFinally, the near-infrared LED readings at 850 nm should start to decrease as the cells grow, indicating that cell density and turbidity is increasing. As cell density gets higher toward the end of the growth cycle, all three wavelengths will start to decrease together, as the turbidity becomes so high that it starts to block all three wavelengths of light.rad51Δ strain is sensitive to 25 cGy protons compared with both the unirradiated WT (p = 0.0029) and rad51Δ (p = 0.0008) strains. The exposed WT strain, on the other hand, is not significantly different compared with its unirradiated control (p = 0.119). These results indicate that, in flight-like conditions where the yeast cells are exposed to radiation while in a desiccated state and rehydrated later for measurement of metabolic activity, we see significant changes in sensitivity to radiation in rad51Δ cells at a level that the BioSentinel free flyer hardware will be able to detect.For this experiment, we exposed desiccated yeast inside fluidic cards to 1 GeV protons at NSRL . Similar4.S. cerevisiae strains that will be employed in the BioSentinel deep space mission. We validated the assay itself by performing initial experiments using relatively high doses of gamma radiation and yeast in liquid suspension, and we further established that the strains preserve sensitivity to high-energy IR in both a desiccated form and liquid suspension. We then showed that the aB assay detects changes in response to space-like GCR simulations. Lastly, we demonstrated that the yeast is sensitive to radiation exposure while loaded into flight-like hardware and exposed while desiccated, which is similar to spaceflight conditions.In the current study, we show that the aB assay is sensitive enough to measure metabolic changes in response to even small doses of space-relevant IR using the et al., unpublished data). This is to be expected, considering the reduced number of water molecules in desiccated samples and, thus, a reduction in the production and exposure to free radical species that can damage cell membranes, lipids, DNA, etc.  as our initial proof-of-concept statistical test, other parameters of the curve analysis can be compared, such as the lag time before exponential growth or metabolic activity start, maximum rate of reduction, total time to peak reduction, yeast duplication rates, and the less frequently studied change of aB from pink to colorless form. We are currently investigating and optimizing parameters for the analysis of flight cell growth and aB reduction in yeast; however, it is important to note that the optimal parameters may differ depending on the application, experiment, or biological organism.The methods described in this study are meant as a proof of concept for the analysis of metabolic activity and growth of yeast in the presence of the aB redox dye. While we have chosen to show only one of the data processing tools  mission, which will launch in 2026 and land on the lunar surface by way of a Commercial Lunar Payload Services lander. The LEIA mission will study the effect of the lunar radiation environment and partial gravity in These initial investigations have provided the following preliminary conclusions in preparation for our flight mission beyond LEO. First, the shift in the aB metabolic response is dependent on the degree of exposure to IR. The higher the radiation dose, the further the reduction profile is shifted or delayed. Second, the longer the yeast cells are desiccated, the further the metabolic curve is shifted to the right. In other words, the older the cells are, the longer the delay in the aB metabolic reduction profile.e.g., by signaling DNA damage response mechanisms or temporarily halting cell division) before the cells return to normal activity, or (3) exposure to radiation causing permanent changes to the cell line and changing the growth kinetics  entirely. As it stands, the aB assay alone is not sufficient to distinguish between these possibilities, and further testing is required to determine whether one or more are responsible. These preliminary observations have helped us gauge what to expect for an aB reduction timeline for flight and to fine-tune our science mission operations .As we see it, there are a few potential mechanisms driving this shift in aB reduction, including (1) potentially fewer surviving cells that could result in a lag in the growth and reduction of aB over time, (2) an additional damage-induced lag period as cells react to radiation exposure  have allowed us to define the aB assay for a biology mission beyond LEO. Future ground studies in support of new missions to deep space and the lunar surface will help to build upon the aB metabolic assay and attain deeper insight into those molecular mechanisms that are activated by space radiation. Finally, we hope that the scientific data we receive from the BioSentinel deep space CubeSat will help to inform and motivate the next generation of human explorers on the Moon and beyond and help train new generations of scientists and engineers.Our preliminary ground experiments with dormant


Androgen deprivation therapy (ADT), used increasingly in the treatment of prostate cancer (PCa), negatively influences glycemic control in diabetes and is associated with an increased risk of diabetes complications where hospitalization commonly ensues. Metformin could decrease the metabolic consequences of ADT and enhance its effect. This study examined the association of metformin use with healthcare resources utilization among diabetic, PCa patients receiving ADT.Diabetic adults with PCa on ADT in Hong Kong between December 1999 and March 2021 were identified. Patients with <6 months of concurrent metformin and ADT use were excluded. All included patients were followed up until September 2021. The outcomes were hospital attendances and related costs.p < 0.001), inpatient attendances , and days of hospitalization . Annual attendance costs were lower for metformin users than non‐users .In total, 1,284 metformin users and 687 non‐users were studied. Over 8,045 person‐years, 9,049 accident and emergency (A&E), and 21,262 inpatient attendances, with 11,2781 days of hospitalization were observed. Metformin users had significantly fewer A&E attendances (incidence rate ratio (IRR): 0.61 [95% confidence interval 0.54–0.69], Metformin use was associated with decreased hospital attendances, days of hospitalization, and associated costs, which could help reduce healthcare resource utilization following ADT in the treatment of PCa. Metformin users showed lower rates of Accident & Emergency and Inpatient attendances, shorter inpatient length‐of‐stay and lower attendance‐related costs compared to metformin non‐users. In prostate cancer (PCa) patients, androgen deprivation therapy (ADT) is the landmark treatment and is usually continued until evidence of treatment resistance in advanced and metastatic disease.In diabetic patients with PCa, metformin may reduce the metabolic side effects incurred by ADT as well as promote its efficacy.International Classification of Diseases, Ninth Revision (ICD‐9) codes  receiving ADT in Hong Kong between 1 December 1999 and 31 March 2021 were included. Diagnosis of PCa was identified by es Table , while tPatients with <6 months of chemical castration without subsequent BO, <6 months of concurrent metformin and ADT use, or missing baseline HbA1c value were excluded. Metformin users had ≥6 months of concurrent metformin and ADT usage, while non‐users had no concurrent usage of metformin and ADT or never used metformin.p values were two‐sided, and p < 0.05 was considered as statistically significant. The statistical analyses were done using Stata v16.1.Continuous variables were expressed as mean ± standard deviation. To balance covariates between metformin users and non‐users, inverse treatment probability weighting (IPTW) using demographics, comorbidities, medications use, type of ADT, and PCa treatment was performed with a generalized boosted model with a maximum of 10,000 regression trees, with an iteration stopping point that minimized the maximal absolute standardized mean difference in effect size between groups. Standardized mean difference (SMD) was used to reflect inter‐group balance of covariates, with SMD values ≤0.1 considered to reflect good balance. Negative binomial regression with IPTW using follow‐up duration as an exposure variable was applied to estimate incidence rates (IR) of each group and incidence rate ratios (IRR) between groups for accident and emergency (A&E) and inpatient attendances, with 95% confidence intervals (CI). The annualized length of hospitalization and its between‐group ratio was also estimated using negative binomial regression as detailed above. A&E and inpatient attendance costs were calculated by multiplying the number of attendances with the per‐attendance cost (€148.7), and the length of hospitalization with the daily hospitalization cost (€616.5) as published by the Hong Kong Hospital Authority in 2020.In total, 2,886 patients were identified as eligible for inclusion. After applying the exclusion criteria, 1,971 patients (age 76.2 ± 7.8 years and follow‐up duration 4.1 ± 3.2 years) were analyzed Figure , of whomp < 0.001), inpatient attendances , and days of hospitalization . These translated to lower annualized per‐patient A&E attendances‐related cost among metformin users  as well as lower annualized per‐patient inpatient attendances‐related cost . Overall, the estimated annualized per‐patient hospital attendances‐related cost was €12,111  for metformin users and €42,952  for non‐users, with a cost ratio of 0.28 [0.10–0.80] (p = 0.017), indicating that metformin users had lower hospital attendances‐related costs when compared to metformin non‐users. The sensitivity analysis using multivariable adjustments showed consistent results, where patients on metformin have significantly fewer hospital attendances and days of hospitalization compared to those not on metformin , with a cost ratio of 0.57 [0.50–0.66] (p < 0.001). These are summarized in Table Over a total of 8,045 person‐years, 9,049 A&E attendances, 21,262 inpatient attendances, and 112,781 days of hospitalization were observed. The IR and IRR for each group, with metformin non‐users as reference, were summarized in Table These associations may be related to metformin's protective effects such that metformin was shown to lessen the development of ADT‐associated metabolic syndrome by decreasing systolic blood pressure and body mass index.In addition to metformin's potential role in inhibiting the survival of PCa cells by androgen receptor signaling suppression,This study used a large, representative population‐based cohort with a long follow‐up period. Therefore, our results are likely widely applicable and reflect real‐world clinical practice. However, this study has a number of limitations, and should therefore be viewed as a hypothesis‐generating study which requires further, confirmatory work. Owing to its observational nature, unmeasured, or residual confounding may exist but was partly addressed by IPTW. Also, cancer staging is lacking; nonetheless, PCa treatments which may at least partially reflect disease severity were included as covariates in IPTW. In addition, patients whose diabetes is well controlled with metformin may have improved health maintenance and/or lower rates of diabetic comorbidities compared to non‐users; however, IPTW allowed for balancing and adjustment of these possible confounders. In addition, the data available could not be individually adjudicated; however, none of the authors had influence over data input.Concurrent metformin use and ADT in Asian, diabetic adults with PCa was associated with decreased hospital attendances and the associated costs, regardless of the type of attendance.Yan Hiu Athena Lee: Conceptualization (lead); data curation ; formal analysis ; investigation (lead); methodology (lead); project administration (lead); validation ; visualization ; writing – original draft . Jeremy Man Ho Hui: Conceptualization (lead); validation ; visualization ; writing – original draft (lead). Cheuk To Chung: Writing – original draft . Kang Liu: Data curation . Edward Christopher Dee: Writing – review and editing . Kenrick Ng: Writing – review and editing . Jeffrey Shi Kai Chan: Conceptualization ; formal analysis ; software ; validation ; writing – original draft . Chi Fai Ng: Conceptualization ; supervision ; writing – review and editing .The authors declare no conflict of interest.This study was approved by the Joint Chinese University of Hong Kong–New Territories East Cluster Clinical Research Ethics Committee.Not applicable due to the nature of the study.Not applicable due to the nature of the study.Not applicable due to the nature of the study.Figure S1.Click here for additional data file.Appendix S1.Click here for additional data file.