Predicting TCR sequences for unseen antigen epitopes using structural and sequence features.

T-cell receptor (TCR) recognition of antigens is fundamental to the adaptive immune response. With the expansion of experimental techniques, a substantial database of matched TCR-antigen pairs has emerged, presenting opportunities for computational prediction models. However, accurately forecasting the binding affinities of unseen antigen-TCR pairs remains a major challenge. Here, we present convolutional-self-attention TCR (CATCR), a novel framework tailored to enhance the prediction of epitope and TCR interactions. Our approach utilizes convolutional neural networks to extract peptide features from residue contact matrices, as generated by OpenFold, and a transformer to encode segment-based coded sequences. We introduce CATCR-D, a discriminator that can assess binding by analyzing the structural and sequence features of epitopes and CDR3-ß regions. Additionally, the framework comprises CATCR-G, a generative module designed for CDR3-ß sequences, which applies the pretrained encoder to deduce epitope characteristics and a transformer decoder for predicting matching CDR3-ß sequences. CATCR-D achieved an AUROC of 0.89 on previously unseen epitope-TCR pairs and outperformed four benchmark models by a margin of 17.4%. CATCR-G has demonstrated high precision, recall and F1 scores, surpassing 95% in bidirectional encoder representations from transformers score assessments. Our results indicate that CATCR is an effective tool for predicting unseen epitope-TCR interactions. Incorporating structural insights enhances our understanding of the general rules governing TCR-epitope recognition significantly. The ability to predict TCRs for novel epitopes using structural and sequence information is promising, and broadening the repository of experimental TCR-epitope data could further improve the precision of epitope-TCR binding predictions.

Acrylamide-Aggravated Liver Injury by Activating Endoplasmic Reticulum Stress in Female Mice with Diabetes.

Acrylamide (ACR) is a common industrial contaminant with endocrine-disrupting toxicity. Numerous studies have indicated that females and diabetics are more sensitive to environmental contaminants. However, it remains unknown whether female diabetics are susceptible to ACR-induced toxicity and its potential mechanisms. Thus, the female ACR-exposure diabetic Balb/c mice model was established to address these issues. Results showed that ACR could induce liver injury in normal mice and cause more serious inflammatory cell infiltration, hepatocyte volume increase, and fusion in diabetic mice liver. Meanwhile, ACR could lead to exacerbation of diabetic symptoms in diabetic mice by disturbing the glucose and lipid metabolism in the liver, which mainly manifests as the accumulation of liver glycogen and liver lipids, the reduction of the activity/content of glycolytic and metabolizing enzyme as well as pentose phosphatase, upregulation of the gene expression in fatty acid transporter and gluconeogenesis, and downregulation of the gene expression in fatty acid synthesis and metabolism. Moreover, ACR exposure could induce oxidative stress, inflammation, and endoplasmic reticulum stress in the liver by a decrease in hepatic antioxidant enzyme activity and antioxidant content, an increase in inflammatory factor levels, and a change in the related protein expression of endoplasmic reticulum stress (ERS) and apoptosis-related pathways in diabetic mice. Statistical analysis results revealed that ACR-induced liver injury was highly correlated with inflammation and oxidative stress, and ERS and diabetic mice had a higher risk of liver injury than normal mice. Overall results suggested that female diabetic mice easily suffer from ACR-induced toxicity, and the reason was that ACR could induce further damage to the liver by worsening the condition of inflammation, oxidative stress, and ERS in the liver.

Fundamental Determinants of the Accuracy of Equilibrium Constants for Affinity Complexes.

The equilibrium constant of a chemical reaction is arguably the key thermodynamic parameter in chemistry; we naturally expect that equilibrium constants are determined accurately. The majority of equilibrium constants determined today are those of binding reactions that form affinity complexes, such as protein-protein, protein-DNA, and protein-small molecule. There is growing awareness that the determination of equilibrium constants for highly stable affinity complexes may be very inaccurate. However, fundamental (i.e., method-independent) determinants of accuracy are poorly understood. Here, we present a study that explicitly shows what the accuracy of equilibrium constants of affinity complexes depends on. This study reveals the critical importance of the choice of concentration of interacting components and creates a theoretical foundation for improving the accuracy of the equilibrium constants. The predicted influence of concentrations on accuracy was confirmed experimentally. The results of this fundamental study provide instructive guidance for experimentalists independently on the method they use.

Cytokine profiles in Tibetan macaques following α-1,3-galactosyltransferase-knockout pig liver xenotransplantation.

BACKGROUND: Pig-to-nonhuman primate orthotopic liver xenotransplantation is often accompanied by thrombocytopenia and coagulation disorders. Furthermore, the release of cytokines can trigger cascade reactions of coagulation and immune attacks within transplant recipients. To better elucidate the process of inflammation in liver xenograft recipients, we utilized a modified heterotopic auxiliary liver xenotransplantation model for xeno-immunological research. We studied the cytokine profiles and the relationship between cytokine levels and xenograft function after liver xenotransplantation. METHODS: Appropriate donor and recipient matches were screened using complement-dependent cytotoxicity assays. Donor liver grafts from α1,3-galactosyltransferase gene-knockout (GTKO) pigs or GTKO pigs additionally transgenic for human CD47 (GTKO/CD47) were transplanted into Tibetan macaques via two different heterotrophic auxiliary liver xenotransplantation procedures. The cytokine profiles, hepatic function, and coagulation parameters were monitored during the clinical course of xenotransplantation. RESULTS: Xenograft blood flow was stable in recipients after heterotopic auxiliary transplantation. A Doppler examination indicated that the blood flow speed was faster in the hepatic artery (HA) and hepatic vein (HV) of xenografts subjected to the modified Sur II (HA-abdominal aorta+HV-inferior vena cava) procedure than in those subjected to our previously reported Sur I (HA-splenic artery+HV-left renal vein) procedure. Tibetan macaques receiving liver xenografts did not exhibit severe coagulation disorders or immune rejection. Although the recipients did suffer from a rapid loss of platelets, this loss was mild. In blood samples dynamically collected after xenotransplantation (post-Tx), dramatic increases in the levels of monocyte chemoattractant protein 1, interleukin (IL)-8, granulocyte-macrophage colony-stimulating factor, IL-6, and interferon gamma-induced protein 10 were observed at 1 hour post-Tx, even under immunosuppression. We further confirmed that the elevation in individual cytokine levels was correlated with the onset of graft damage. Finally, the release of cytokines might contribute to leukocyte infiltration in the xenografts. CONCLUSION: Here, we established a modified auxiliary liver xenotransplantation model resulting in near-normal hepatic function. Inflammatory cytokines might contribute to early damage in liver xenografts. Controlling the systemic inflammatory response of recipients might prevent early post-Tx graft dysfunction.

Pig BMSCs Transfected with Human TFPI Combat Species Incompatibility and Regulate the Human TF Pathway in Vitro and in a Rodent Model.

BACKGROUND: The activation of tissue factor (TF) is one of the major reasons for coagulation dysregulation after pig-to-primate xenotransplantation. Tissue factor pathway inhibitor (TFPI) is the most important inhibitor of TF. Studies have demonstrated species incompatibility between pig TFPI and human TF. METHODS: A pig-to-macaque heterotopic auxiliary liver transplantation model was established to determine the origin of activated TF. Chimeric proteins of human and pig TFPI were constructed to assess the role of Kunitz domains in species incompatibility. Immortalised pig bone marrow mesenchymal stem cells transfected with human TFPI were tested for their ability to inhibit clotting in vitro. RESULTS: TF from recipient was activated early after liver xenotransplantation. Pig TFPI Kunitz domain 2 bound human FXa, but Kunitz domain 1 did not effectively inhibit human TF/FVIIa. Immortalised pig bone marrow mesenchymal cells (BMSCs) transfected with human TFPI showed a prolonged recalcification time in vitro and in a rodent model. CONCLUSION: Recipient TF is relevant to dysregulated coagulation after xenotransplantation. Kunitz domain 1 plays the most important role in species incompatibility between pig TFPI and human TF, and clotting can be inhibited by human TFPI-transfected pig BMSCs. Our study shows a possible way to resolve the incompatibility of pig TFPI.

The efficacy and safety of PD-1 inhibitor combined with TACE in the first-line treatment of unresectable hepatocellular carcinoma.

The application of immune checkpoint inhibitors (ICIs) has changed the treatment of advanced hepatocellular carcinoma. Transcatheter arterial chemoembolization (TACE) is a first-line treatment for intermediate hepatocellular carcinoma. Serving as a local treatment modality that can induce immunogenic cell death, the efficacy and safety of combined use with ICI have not been evaluated. Although there have been prospective studies aimed at evaluating the efficacy and safety of ICI combined with TACE in BCLC stage B HCC patients, there are few reports on the evaluation of BCLC stage C patients with distant metastasis or portal vein cancer thrombus. Data of unresectable hepatocellular carcinoma patients received PD-1 inhibitor and TACE were collected in Xijing Hospital from June 2019 to December 2022. The tumor response was evaluated according to the Solid Tumor Modified Response Evaluation Standard (mRECIST), including complete response (CR), partial response (PR), disease stability (SD), disease progression (PD), objective response rate (ORR), and disease control rate (DCR). The progression-free survival (PFS) and overall survival (OS) were used to estimate therapy efficacy. The treatment-related adverse events were evaluated based on National Cancer Institute Common Adverse Event Evaluation Criteria (CTCAE) version 5.0. A total of 42 patients with unresectable hepatocellular carcinoma were included in this study, including 34 males (80.5%) and 8 females (19.5%). The average age is 54.5 years, ranging from 34 to 72. The median follow-up time was 12.3 months, with an ORR of 42.9% and a DCR of 90.5% as of the follow-up time. The median PFS is 7.5 months (95% CI: 5.76-9.23), and the median OS has not yet been reached; 6-month PFS was 62.2%. Safety analysis showed that 41 (97.6%) patients experienced treatment-related adverse reactions, mainly including elevated AST and ALT, fever, elevated bilirubin, hypothyroidism, nausea, abdominal pain, and rash. 40 patients had grade 1/2 adverse reactions, and only one patient had grade 3 adverse reactions, manifested as intolerable rash, nausea, and vomiting. Treatment is terminated when symptomatic treatment and drug suspension cannot be alleviated. In this study, thre patients with unresectable hepatocellular carcinoma were treated with PD-1 inhibitor combined with TACE to achieve good tumor reduction effect and underwent liver cancer resection surgery. For patients with unresectable hepatocellular carcinoma, whether in BCLC stage B or stage C, effective systemic therapy (PD-1 inhibitor) combined with local therapy (TACE) can achieve a high rate of tumor regression and objective response. Some patients may even pursue surgical treatment opportunities, and the treatment-related adverse reactions are controllable, which is expected to provide new options for extending the survival of unresectable hepatocellular carcinoma patients.

Stratifying hepatocellular carcinoma based on immunophenotypes for immunotherapy response and prognosis.

Immunotherapy has transformed the management of hepatocellular carcinoma (HCC), but effectiveness varies among patients. This study aimed to identify biomarkers and HCC subtypes responsive to immunotherapy. Patients were classified into Immunity-High (Immunity-H) and Immunity-Low (Immunity-L) subtypes using ssGSEA scores. Prognostic genes were identified through Cox regression, and immune cell infiltration was quantified with TIMER 2.0. Brother of CDO (BOC) expression, analyzed via immunohistochemistry, correlated with immunotherapy responses. Flow cytometry assessed immune cell infiltration relative to BOC levels, while CCK-8 and transwell assays evaluated BOC overexpression's effects on cell proliferation and invasiveness. Clinically, immunity-H patients had better survival outcomes. Three hub genes-BOC, V-Set and Transmembrane Domain Containing 1 (VSTM1), and PRDM12-were identified as significantly associated with prognosis. Among these, BOC and VSTM1 demonstrated positive correlations with immune cell infiltration. Elevated expression of BOC was found to be predictive of favorable responses to immunotherapy and was associated with enhanced infiltration of T cells, dendritic cells, and B cells in the tumor microenvironment. Conversely, BOC overexpression in liver cancer cell lines led to decreased cell proliferation and invasiveness. This study underscores the prognostic significance of HCC subtypes defined by immunogenomic profiles and identifies BOC as a potential biomarker for immunotherapy selection and outcome prediction.

Identifying specific TLS-associated genes as potential biomarkers for predicting prognosis and evaluating the efficacy of immunotherapy in soft tissue sarcoma.

Background: The tertiary lymphatic structure (TLS) is an important component of the tumor immune microenvironment and has important significance in patient prognosis and response to immune therapy. However, the underlying mechanism of TLS in soft tissue sarcoma remains unclear. Methods: A total of 256 RNAseq and 7 single-cell sequencing samples were collected from TCGA-SARC and GSE212527 cohorts. Based on published TLS-related gene sets, four TLS scores were established by GSVA algorithm. The immune cell infiltration was calculated via TIMER2.0 and "MCPcounter" algorithms. In addition, the univariate, LASSO, and multivariate-Cox analyses were used to select TLS-related and prognosis-significant hub genes. Single-cell sequencing dataset, clinical immunohistochemical, and cell experiments were utilized to validate the hub genes. Results: In this study, four TLS-related scores were identified, and the total-gene TLS score more accurately reflected the infiltration level of TLS in STS. We further established two hub genes (DUSP9 and TNFSF14) prognosis markers and risk scores associated with soft tissue sarcoma prognosis and immune therapy response. Flow cytometry analysis showed that the amount of CD3, CD8, CD19, and CD11c positive immune cell infiltration in the tumor tissue dedifferentiated liposarcoma patients was significantly higher than that of liposarcoma patients. Cytological experiments showed that soft tissue sarcoma cell lines overexpressing TNFSF14 could inhibit the proliferation and migration of sarcoma cells. Conclusion: This study systematically explored the TLS and related genes from the perspectives of bioinformatics, clinical features and cytology experiments. The total-gene TLS score, risk score and TNFSF14 hub gene may be useful biomarkers for predicting the prognosis and immunotherapy efficacy of soft tissue sarcoma.

Clinical efficacy and safety evaluation of camrelizumab plus lenvatinib in adjuvant therapy after hepatocellular carcinoma surgery.

Objective: To assess the efficacy and safety of camrelizumab plus different targeted drugs in adjuvant therapy after hepatocellular carcinoma (HCC) surgery. Patients and methods: This retrospective cohort study included HCC patients who, after undergoing failed postoperative adjuvant lenvatinib therapy, received intravenous camrelizumab 200 mg every 3 weeks (C group, n = 97), camrelizumab plus oral apatinib 250 mg daily (C+A group, n = 125), camrelizumab plus oral lenvatinib 12 mg daily (for bodyweight ≥60 kg)/lenvatinib 8 mg daily (for bodyweight <60 kg) (C+L group, n = 120), or camrelizumab plus oral sorafenib 400 mg bi-daily (C+S group, n = 114) between October 2020 and October 2021. The outcomes including the objective response rate (ORR) and disease control rate (DCR) were evaluated by RECIST 1.1 and iRECIST. The median progression-free survival (mPFS), median overall survival (mOS), 6-month OS rate, 12-month OS rate, and adverse events were evaluated. Results: As of 31 May 2022 with last follow-up time, the ORR was 17.2% for the C group, 44.6% for the C+A group, 47.9% for the C+L group, and 36.3% for the C+S group. The DCR was 72.0% for the C group, 81.8% for the C+A group, 85.5% for the C+L group, and 77.9% for the C+S group. The mPFS was 11.0 months (10.1-12.8) for the C group, 14.0 months (12.7-16.5) for the C+A group, 18.0 months (16.9-20.1) for the C+L group, and 12.0 months (9.7-14.4) for the C+S group. The mOS was 13.0 months (11.6-15.3) for the C group, 17.0 months (15.8-19.4) for the C+A group, 19.0 months (17.7-20.2) for the C+L group, and 15.0 months (14.1-17.3) for the C+S group. Grade 3 or 4 treatment-related adverse events occurred in 14 patients (14.4%) for the C group, 10 patients (8.0%) for the C+A group, 5 patients (4.2%) for the C+L group, and 11 patients (9.6%) for the C+S group. The most common adverse events were fatigue and transaminitis. Conclusion: Camrelizumab combined with lenvatinib as adjuvant therapy showed promising efficacy and manageable safety in HCC patients. It might be a potential adjuvant therapy or second-line treatment for these patients.

Redefining the Incidence and Profile of Fluoropyrimidine-Associated Cardiotoxicity in Cancer Patients: A Systematic Review and Meta-Analysis.

AIM: The cardiac toxicity that occurs during administration of anti-tumor agents has attracted increasing concern. Fluoropyrimidines have been used for more than half a century, but their cardiotoxicity has not been well clarified. In this study, we aimed to assess the incidence and profile of fluoropyrimidine-associated cardiotoxicity (FAC) comprehensively based on literature data. METHODS: A systematic literature search was performed using PubMed, Embase, Medline, Web of Science, and Cochrane library databases and clinical trials on studies investigating FAC. The main outcome was a pooled incidence of FAC, and the secondary outcome was specific treatment-related cardiac AEs. Random or fixed effects modeling was used for pooled meta-analyses according to the heterogeneity assessment. PROSPERO registration number: (CRD42021282155). RESULTS: A total of 211 studies involving 63,186 patients were included, covering 31 countries or regions in the world. The pooled incidence of FAC, by meta-analytic, was 5.04% for all grades and 1.5% for grade 3 or higher. A total of 0.29% of patients died due to severe cardiotoxicities. More than 38 cardiac AEs were identified, with cardiac ischemia (2.24%) and arrhythmia (1.85%) being the most frequent. We further performed the subgroup analyses and meta-regression to explore the source of heterogeneity, and compare the cardiotoxicity among different study-level characteristics, finding that the incidence of FAC varied significantly among different publication decades, country/regions, and genders. Patients with esophagus cancer had the highest risk of FAC (10.53%), while breast cancer patients had the lowest (3.66%). The treatment attribute, regimen, and dosage were significantly related to FAC. When compared with chemotherapeutic drugs or targeted agents, such a risk was remarkably increased (χ2 = 10.15, p < 0.01; χ2 = 10.77, p < 0.01). The continuous 5-FU infusion for 3-5 consecutive days with a high dosage produced the highest FAC incidence (7.3%) compared with other low-dose administration patterns. CONCLUSIONS: Our study provides comprehensive global data on the incidence and profile of FAC. Different cancer types and treatment appear to have varying cardiotoxicities. Combination therapy, high cumulative dose, addition of anthracyclines, and pre-existing heart disease potentially increase the risk of FAC.

Short-term exposure to acrylamide exacerbated metabolic disorders and increased metabolic toxicity susceptibility on adult male mice with diabetes.

Diabetes mellitus is a common endocrine metabolic disorder, and previous studies have shown that diabetics are more sensitive to the toxic environmental contaminants. Acrylamide (ACR) is both an industrially multipurpose compound and a common endogenous food contaminant to which people are frequently exposed and at high risk. However, the toxicity of ACR on diabetes hasn't attracted much attention. In this study, both healthy mice and diabetic mice received ACR administration orally to investigate the ACR-induced metabolic toxicity, mechanism and susceptibility to ACR toxicity in adult diabetic male mice. The results showed that ACR significantly increased FBG level and decreased bodyweight, serum lipid and liver lipid biomarkers (TC, TG, LDL-C, HDL-C) levels as well as expression of lipid and glucose metabolism-related genes in diabetic mice, indicating that ACR can exacerbate metabolic disorders of glucose and lipid in diabetic male mice. Moreover, ACR exposure significantly increased levels of MDA and COX-2), decreased GSH level and antioxidant enzyme activity (SOD, GSH-PX and CAT) by downregulating expression of Nrf2 and Keap1 in diabetic mice. Factorial analysis showed ACR had a more significant disturbance in diabetic mice compared with healthy mice. Our results indicated that ACR exposure can cause oxidative stress and inflammatory damage, which can exacerbate abnormal glucose and lipid metabolism. This work helps to elucidate the effects and underlying mechanisms of ACR-induced metabolic toxicity in adults with diabetes.

Fear of Progression, Anxiety, and Depression in Patients With Advanced Melanoma in the COVID-19 and Post-COVID-19 Era.

Background: The novel coronavirus disease 2019 (COVID-19) pandemic causes great disruption to cancer care services, which might bring about psychological problems and further lower both physical and mental life quality in cancer patients. Until now, very few studies focused on the psychological distress of patients with advanced melanoma before or during the epidemic. This study aimed to elucidate the fear of progression (FoP), anxiety, depression, and related independent predictors in patients with advanced melanoma during the COVID-19 outbreak. Methods: Two hundred and seventy-three patients with unresectable stage III or metastatic melanoma were recruited from February 2020 to November 2021, and completed the Fear of Progression Questionnaire-Short Form (FoP-Q-SF), State Trait Anxiety Inventory (STAI-6), and Patient Health Questionnaire (PHQ-9). Results: One hundred and seventy-four (64.7%) patients experienced heighted FoP (FoP-Q-SF: 39.9 ± 11.0), 198 (72.5%) patients reported elevated anxiety (STAI-6: 13.1 ± 3.0), and 62 (22.7%) patients had increased depression (PHQ-9: 6.4 ± 6.1). In multivariate analysis, illness duration (OR = 0.987 for FoP; OR = 0.984 for depression), cancer stage (OR = 14.394 for anxiety) and disease progression (OR = 1.960 for FoP; OR = 23.235 for anxiety; OR = 1.930 for depression) were independent predictors for FoP, anxiety or depression. Additionally, the high levels of FoP, anxiety and depression were significantly positive correlated with each other (r = 0.466 for FoP and anxiety; r = 0.382 for FoP and depression; r = 0.309 for anxiety and depression). Conclusion: Our study indicates that FoP, anxiety and depression are persisting among patients with advanced melanoma in the COVID-19 and post-COVID-19 era. Effective psycho-oncological interventions are needed for melanoma patients with psychological distress during the ongoing COVID-19 pandemic.

Identification of stromal microenvironment characteristics and key molecular mining in pancreatic cancer.

PURPOSE: Pancreatic cancer is one of the deadliest cancers worldwide. The extracellular matrix (ECM) microenvironment affects the drug sensitivity and prognosis of pancreatic cancer patients. This study constructed an 8-genes pancreatic ECM scoring (PECMS) model, to classify the ECM features of pancreatic cancer, analyze the impact of ECM features on survival and drug sensitivity, and mine key molecules that influence ECM features in pancreatic cancer. METHODS: GSVA score calculation and clustering were performed in TCGA-PAAD patients. Lasso regression was used to construct the PECMS model. The association between PECMS and patient survival was analyzed and validated in the CPTAC-3 dataset of TCGA and our single-center retrospective cohort. The relationships between PECMS and features of the matrix microenvironment were analyzed. Finally, PECMS feature genes were screened and verified in pancreatic cancer specimens to select key genes associated with the ECM microenvironment. RESULT: The survival of the PECMS-high group was significantly worse. The PECMS-high group showed higher oxidative stress levels, lower levels of antigen presentation- and MHC-I molecule-related pathways, and less immune effector cell infiltration. Data from IMvigor-210 cohort suggested that PECMS-low group patients were more sensitive to immune checkpoint blockers. The PECMS score was negatively correlated with chemotherapy drug sensitivity. The negative association of PECMS with survival and drug sensitivity was validated in our retrospective cohort. KLHL32 expression predicted lower oxidative stress level and more immune cells infiltrate in pancreatic cancer. CONCLUSION: PECMS is an effective predictor of prognosis and drug sensitivity in pancreatic cancer patients. KLHL32 may play an important role in the construction of ECM, and the mechanism is worth further study.

Treatment-Related Coronary Disorders of Fluoropyrimidine Administration: A Systematic Review and Meta-Analysis.

Background: Coronary disorders are recognized as the most common manifestation of fluoropyrimidine-related cardiotoxicity in clinical practice. However, there are limited and conflicting data on the incidence and profiles of fluoropyrimidine-related coronary disorders. In this meta-analysis, we aimed to systematically assess the incidence of all-grade and grade 3 or higher fluoropyrimidine-related coronary disorders, and further explore the factors that influence its occurrence. Methods: Studies reporting the fluoropyrimidine-related coronary disorders were retrieved from a systematic search of English literature in the PubMed, Web of Science, Medline, and Cochrane database from 1 Jan 2001, to 1 Jan 2022. The NIH assessment tool was used to evaluate the quality of each study. The data of basic study characteristics, treatment details, and results of coronary toxicities were extracted. According to the results of the heterogeneity test (I2 and p-value statistic), a random-effect model or fixed-effect model was selected for the pooled analysis of the incidence of adverse coronary events. Subgroup analysis was conducted to further explore the risks influencing the occurrence of fluoropyrimidine-related coronary disorders. The stability and publication bias of our results were evaluated by sensitivity analysis and Egger test, respectively. Results: A total of 63 studies were finally included in our pooled analysis, involving 25,577 patients. The pooled cumulative incidence of all-grade and grade 3 or higher coronary disorders was 2.75% (95% CI 1.89%-3.76%) and 1.00% (95% CI 0.62%-1.47%), respectively. The coronary disorders were most reported as myocardial ischemia (1.28%, 95% CI 0.42%-2.49%) and angina/chest pain (1.1%, 95% CI 0.54%-1.81%). Subgroup analysis revealed that studies in the female-only population seemed to have a lower incidence of fluoropyrimidine-related coronary disorders. The occurrence of adverse coronary events varied among different tumor types. Patients with esophageal cancer have the highest coronary toxicity (6.32%), while those with breast cancer have a relatively lower incidence (0.5%). Coronary disorders induced by 5-FU monotherapy are more frequent than that induced by capecitabine (3.31% vs. 1.21%, p < 0.01). Fluoropyrimidine combination therapy, whether combined with other chemotherapy drugs, targeted therapy drugs, or radiotherapy, significantly increased the incidence of coronary complications (p < 0.01). Conclusion: This meta-analysis has defined the incidence of fluoropyrimidine-related coronary disorders and depicted its epidemiological profiles for the first time, which may provide a reference for clinical practice in cancer management.

Construction of m6A-based prognosis signature and prediction for immune and anti-angiogenic response.

Background: Increasing evidence illustrated that m6A regulator-mediated modification plays a crucial role in regulating tumor immune and angiogenesis microenvironment. And the combination of immune checkpoint inhibitor and anti-angiogenic therapy has been approved as new first-line therapy for advanced HCC. This study constructed a novel prognosis signature base on m6A-mediated modification and explored the related mechanism in predicting immune and anti-angiogenic responses. Methods: Gene expression profiles and clinical information were collected from TCGA and GEO. The ssGSEA, MCPCOUNT, and TIMER 2.0 algorithm was used to Estimation of immune cell infiltration. The IC50 of anti-angiogenic drugs in GDSC was calculated by the "pRRophetic" package. IMvigor210 cohort and Liu et al. cohort were used to validate the capability of immunotherapy response. Hepatocellular carcinoma single immune cells sequencing datasets GSE140228 were collected to present the expression landscapes of 5 hub genes in different sites and immune cell subpopulations of HCC patients. Results: Three m6A clusters with distinct immune and angiogenesis microenvironments were identified by consistent cluster analysis based on the expression of m6A regulators. We further constructed a 5-gene prognosis signature (termed as m6Asig-Score) which could predict both immune and anti-angiogenic responses. We illustrated that high m6Asig-Score is associated with poor prognosis, advanced TNM stage, and high TP53 mutation frequency. Besides, the m6Asig-Score was negatively associated with immune checkpoint inhibitors and anti-angiogenic drug response. We further found that two of the five m6Asig-Score inner genes, B2M and SMOX, were associated with immune cell infiltration, immune response, and the sensitivity to sorafenib, which were validated in two independent immunotherapy cohorts and the Genomics of Drug Sensitivity in Cancer (GDSC) database. Conclusion: We constructed a novel prognosis signature and identified B2M and SMOX for predicting immune and anti-angiogenic efficacy in HCC, which may guide the combined treatment strategies of immunotherapy and anti-angiogenic therapy in HCC.

A novel cuproptosis-related prognostic signature and potential value in HCC immunotherapy.

Background: Copper metabolism plays an important role in the tumor microenvironment, and cuproptosis is the last discovered programmed cell death process. However, the potential mechanism of cuproptosis in regulating the immune microenvironment of HCC remains unclear. Methods: A total of 716 HCC patients with complete mRNA expression and survival information were collected from three public HCC cohorts (TCGA-LIHC cohort, n = 370; GSE76427 cohort, n = 115; ICGC-LIRI cohort, n = 231). The unsupervised clustering analysis (NMF) was performed to identify three different cuproptosis-related subtypes. The univariate-Cox, lasso-Cox and multivariate-Cox regression analyses were performed to screen the cuproptosis related and construct the cuproptosis-related prognosis signature (Cu-PS). The immune cell infiltration was estimated by both CIBERSORT and MCPcounter algorithms. Results: This study identified three distinct cuproptosis-related metabolic patterns, which presented different pathway enrichment and immune cell infiltration. The Cu-PS, a 5-genes (C7, MAGEA6, HK2, CYP26B1 and EPO) signature, was significantly associated with TNM stage, tumor mutational burden (TMB), drugs sensitivity, and immunotherapies response. Conclusion: This study performed a multi-genetic analysis of cuproptosis-related genes and further explored the regulatory mechanism of cuproptosis in HCC. The Cu-PS might be a useful biomarker for predicting immunotherapy response and enhancing the diagnosis and treatment of HCC.

Clinical feature-related single-base substitution sequence signatures identified with an unsupervised machine learning approach.

BACKGROUND: Mutation processes leave different signatures in genes. For single-base substitutions, previous studies have suggested that mutation signatures are not only reflected in mutation bases but also in neighboring bases. However, because of the lack of a method to identify features of long sequences next to mutation bases, the understanding of how flanking sequences influence mutation signatures is limited. METHODS: We constructed a long short-term memory-self organizing map (LSTM-SOM) unsupervised neural network. By extracting mutated sequence features via LSTM and clustering similar features with the SOM, single-base substitutions in The Cancer Genome Atlas database were clustered according to both their mutation site and flanking sequences. The relationship between mutation sequence signatures and clinical features was then analyzed. Finally, we clustered patients into different classes according to the composition of the mutation sequence signatures by the K-means method and then studied the differences in clinical features and survival between classes. RESULTS: Ten classes of mutant sequence signatures (mutation blots, MBs) were obtained from 2,141,527 single-base substitutions via LSTM-SOM machine learning approach. Different features in mutation bases and flanking sequences were revealed among MBs. MBs reflect both the site and pathological features of cancers. MBs were related to clinical features, including age, sex, and cancer stage. The class of an MB in a given gene was associated with survival. Finally, patients were clustered into 7 classes according to the MB composition. Significant differences in survival and clinical features were observed among different patient classes. CONCLUSIONS: We provided a method for analyzing the characteristics of mutant sequences. Result of this study showed that flanking sequences, together with mutation bases, shape the signatures of SBSs. MBs were shown related to clinical features and survival of cancer patients. Composition of MBs is a feasible predictive factor of clinical prognosis. Further study of the mechanism of MBs related to cancer characteristics is suggested.

Structural characterization of a novel Schisandra polysaccharides and nutritional intervention in immunotoxicity to PCBs.

A new polysaccharide from fruits of Schisandra chinensis (SCPP22) with a molecular weight of 143 ± 0.13 KDa was mainly made up of glucose and galactose. The possible structure of SCPP22 was showed that its main chain was composed of 1,4-α-d-Glup and branch was stretched from O-6 position of 1,4-ß-d-Glup. Branches consisted of T-α-d-Galp. Further, SCPP22 could reverse PCB126-induced immunosuppression, significantly enhance body weight and immune organ indices. It also significantly ameliorated oxidative injury to immune organ induced by PCB126, as shown by evaluation of SOD activities, as well as MDA levels in spleen and thymus. SCPP22 strongly stimulated cytokines production by up-regulating mRNA expression of TNF-α, INF-γ and IL-2. Mechanism investigation revealed that recovery effects of SCPP22 in immunosuppression induced by PCB126 are mainly through regulating apoptosis-related proteins expression. Schisandra polysaccharides might be applied in functional food as nutritional intervention ingredient.

Leveraging machine learning techniques for predicting pancreatic neuroendocrine tumor grades using biochemical and tumor markers.

BACKGROUND: The incidence of pancreatic neuroendocrine tumors (PNETs) is now increasing rapidly. The tumor grade of PNETs significantly affects the treatment strategy and prognosis. However, there is still no effective way to non-invasively classify PNET grades. Machine learning (ML) algorithms have shown potential in improving the prediction accuracy using comprehensive data. AIM: To provide a ML approach to predict PNET tumor grade using clinical data. METHODS: The clinical data of histologically confirmed PNET cases between 2012 and 2018 were collected. A method of minimum P for the Chi-square test was used to divide the continuous variables into binary variables. The continuous variables were transformed into binary variables according to the cutoff value, while the P value was minimum. Four classical supervised ML models, including logistic regression, support vector machine (SVM), linear discriminant analysis (LDA) and multi-layer perceptron (MLP) were trained by clinical data, and the models were labeled with the pathological tumor grade of each PNET patient. The performance of each model, including the weight of the different parameters, were evaluated. RESULTS: In total, 91 PNET cases were included in this study, in which 32 were G1, 48 were G2 and 11 were G3. The results showed that there were significant differences among the clinical parameters of patients with different grades. Patients with higher grades tended to have higher values of total bilirubin, alpha fetoprotein, carcinoembryonic antigen, carbohydrate antigen 19-9 and carbohydrate antigen 72-4. Among the models we used, LDA performed best in predicting the PNET tumor grade. Meanwhile, MLP had the highest recall rate for G3 cases. All of the models stabilized when the sample size was over 70 percent of the total, except for SVM. Different parameters varied in affecting the outcomes of the models. Overall, alanine transaminase, total bilirubin, carcinoembryonic antigen, carbohydrate antigen 19-9 and carbohydrate antigen 72-4 affected the outcome greater than other parameters. CONCLUSION: ML could be a simple and effective method in non-invasively predicting PNET grades by using the routine data obtained from the results of biochemical and tumor markers.

Dioxin-like (DL-) polychlorinated biphenyls induced immunotoxicity through apoptosis in mice splenocytes via the AhR mediated mitochondria dependent signaling pathways.

Polychlorinated biphenyls (PCBs) would do serious damage to multiple systems, while coplanar polychlorinated biphenyls, the most toxic member of the family, has been widely taken into consideration. In this study, ICR mice were fed with different doses of PCB126 to explore the underlying molecular mechanisms on immunotoxicity. The results showed that PCB126 caused immunosuppression as evidenced by inhibiting the ratios of thymus and spleen weights, changing the organizational structure and decreasing levels and mRNA expression of TNF-α, IFN-γ and IL-2. PCB126 inhibited the SOD activity and spurred the accumulation of MDA in spleen and thymus. Meanwhile, it also disturbed the Nrf2 signaling pathway as evidenced by up-regulating the mRNA expression of Nrf2 and Keap1. Additionally, a remarkable reduction in the mRNA expression of AhR and enhancement in the mRNA expression of Cyp1 enzymes (Cyp1a1, Cyp1a2 and Cyp1b1) were observed, which increased the ROS levels. PCB126 could increase protein expression of Bax, Caspase-3, Caspase-8 and Caspase-9, while the protein expression of Bcl-2 was decreased. In summary, the results indicated that PCB126 modulated the AhR signaling pathway, which interacted with apoptosis and oxidative stress to induce immunotoxicity, enrich the immunotoxicological mechanisms of PCB126.