Innexin hemichannel activation by Microplitis bicoloratus ecSOD monopolymer reduces ROS.

The extracellular superoxide dismutases (ecSODs) secreted by Microplitis bicoloratus reduce the reactive oxygen species (ROS) stimulated by the Microplitis bicoloratus bracovirus. Here, we demonstrate that the bacterial transferase hexapeptide (hexapep) motif and bacterial-immunoglobulin-like (BIg-like) domain of ecSODs bind to the cell membrane and transiently open hemichannels, facilitating ROS reductions. RNAi-mediated ecSOD silencing in vivo elevated ROS in host hemocytes, impairing parasitoid larva development. In vitro, the ecSOD-monopolymer needed to be membrane bound to open hemichannels. Furthermore, the hexapep motif in the beta-sandwich of ecSOD49 and ecSOD58, and BIg-like domain in the signal peptides of ecSOD67 were required for cell membrane binding. Hexapep motif and BIg-like domain deletions induced ecSODs loss of adhesion and ROS reduction failure. The hexapep motif and BIg-like domain mediated ecSOD binding via upregulating innexins and stabilizing the opened hemichannels. Our findings reveal a mechanism through which ecSOD reduces ROS, which may aid in developing anti-redox therapy.

A comprehensive investigation on the receptor BSG expression reveals the potential risk of healthy individuals and cancer patients to 2019-nCoV infection.

BACKGROUND: Coronavirus disease-2019 (COVID-19) pandemic is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a newly emerging coronavirus. BSG (basigin) is involved in the tumorigenesis of multiple tumors and recently emerged as a novel viral entry receptor for SARS-CoV-2. However, its expression profile in normal individuals and cancer patients are still unclear. METHODS: We performed a comprehensive analysis of the expression and distribution of BSG in normal tissues, tumor tissues, and cell lines via bioinformatics analysis and experimental verification. In addition, we investigated the expression of BSG and its isoforms in multiple malignancies and adjacent normal tissues, and explored the prognostic values across pan-cancers. Finally, we conducted function analysis for co-expressed genes with BSG. RESULTS: We found BSG was highly conserved in different species, and was ubiquitously expressed in almost all normal tissues and significantly increased in some types of cancer tissues. Moreover, BSG at mRNA expression level was higher than ACE2 in normal lung tissues, and lung cancer tissues. High expression of BSG indicated shorter overall survival (OS) in multiple tumors. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses indicated that BSG is mostly enriched in genes for mitochondria electron transport, oxidoreduction-driven active transmembrane transporter activity, mitochondrial inner membrane, oxidative phosphorylation, and genes involving COVID-19. CONCLUSIONS: Our present work emphasized the value of targeting BSG in the treatment of COVID-19 and cancer, and also provided several novel insights for understanding the SARS-CoV-2 pandemic.

Carbon-Iodine Polydiacetylene Nanofibers for Image-Guided Radiotherapy and Tumor-Microenvironment-Enhanced Radiosensitization.

Radiotherapy is a mainstay treatment used in clinics for locoregional therapy, although it still represents a great challenge to improve the sensitivity and accuracy of radiotherapy for tumors. Here, we report the conjugated polymer, polydiiododiacetylene (PIDA), with an iodine content of 84 wt %, as a highly effective computed tomography (CT) contrast agent and tumor microenvironment-responsive radiosensitizer. PIDA exhibited several key properties that contribute to the improvement of precision radiotherapy. The integrated PIDA nanofibers confined within the tumor envelope demonstrated amplified CT intensity and prolonged retention, providing an accurate calculation of dose distribution and precise radiation delivery for CT image-guided radiotherapy. Therefore, our strategy pioneers PIDA nanofibers as a bridge to cleverly connect a fiducial marker to guide accurate radiotherapy and a radiosensitizer to improve tumor sensitivity, thereby minimizing potential damage to surrounding tissues and facilitating on-demand therapeutic intervention in tumors.

Simulating immunosuppressive mechanism of Microplitis bicoloratus bracovirus coordinately fights Spodoptera frugiperda.

Parasitoid wasps control pests via a precise attack leading to the death of the pest. However, parasitoid larvae exhibit self-protection strategies against bracovirus-induced reactive oxygen species impairment. This has a detrimental effect on pest control. Here, we report a strategy for simulating Microplitis bicoloratus bracovirus using Mix-T dsRNA targeting 14 genes associated with transcription, translation, cell-cell communication, and humoral signaling pathways in the host, and from wasp extracellular superoxide dismutases. We implemented either one-time feeding to the younger instar larvae or spraying once on the corn leaves, to effectively control the invading pest Spodoptera frugiperda. This highlights the conserved principle of "biological pest control," as elucidated by the triple interaction of parasitoid-bracovirus-host in a cooperation strategy of bracovirus against its pest host.

The application and research progress of anti-angiogenesis therapy in tumor immunotherapy.

Tumor immunotherapy, as the focus of scientific research and clinical tumor treatment in recent years, has received extensive attention. Due to its remarkable curative effect and fewer side effects than traditional treatments, it has significant clinical benefits for the treatment of various advanced cancers and can improve cancer patient survival in the long term. Currently, most patients cannot benefit from immunotherapy, and some patients may experience tumor recurrence and drug resistance even if they achieve remission overcome. Numerous studies have shown that the abnormal angiogenesis state of tumors can lead to immunosuppressive tumor microenvironment, which affects the efficacy of immunotherapy. Actually, to improve the efficacy of immunotherapy, the application of anti-angiogenesis drugs to normalize abnormal tumor vessel has been widely confirmed in basic and clinical research. This review not only discusses the risk factors, mechanisms, and effects of abnormal and normalized tumor angiogenesis state on the immune environment, but summarizes the latest progress of immunotherapy combined with anti-angiogenic therapy. We hope this review provides an applied reference for anti-angiogenesis drugs and synergistic immunotherapy therapy.

Advances in nanomaterials for the diagnosis and treatment of head and neck cancers: A review.

Nanomaterials (NMs) have increasingly been used for the diagnosis and treatment of head and neck cancers (HNCs) over the past decade. HNCs can easily infiltrate surrounding tissues and form distant metastases, meaning that most patients with HNC are diagnosed at an advanced stage and often have a poor prognosis. Since NMs can be used to deliver various agents, including imaging agents, drugs, genes, vaccines, radiosensitisers, and photosensitisers, they play a crucial role in the development of novel technologies for the diagnosis and treatment of HNCs. Indeed, NMs have been reported to enhance delivery efficiency and improve the prognosis of patients with HNC by allowing targeted delivery, controlled release, responses to stimuli, and the delivery of multiple agents. In this review, we consider recent advances in NMs that could be used to improve the diagnosis, treatment, and prognosis of patients with HNC and the potential for future research.

Characterization of molecular subtypes based on chromatin regulators and identification of the role of NPAS2 in lung adenocarcinoma.

BACKGROUND: Chromatin regulators (CRs) are critical epigenetic modifiers and have been reported to play critical roles during the progression of various tumors, but their role in lung adenocarcinoma (LUAD) has not been comprehensively studied. METHODS: Differential expression and univariate Cox regression analyses were conducted to identify the prognostic CRs. Consensus clustering was applied to classify the subtypes of LUAD based on prognostic CRs. LASSO-multivariate Cox regression method was used for construction of a prognostic signature and development of chromatin regulator-related gene index (CRGI). The capacity of CRGI to distinguish survival was evaluated via Kaplan-Meier method in multiple datasets. Relationship between CRGI and tumor microenvironment (TME) was evaluated. Additionally, clinical variables and CRGI were incorporated to create a nomogram. The role of the prognostic gene NPAS2 in LUAD was elucidated via clinical samples validation and a series of in vitro and in vivo experiments. RESULTS: Two subtypes of LUAD were classified based on 46 prognostic CRs via consensus clustering which had significantly different survival and TME. A prognostic signature consisting of six CRs (MOCS, PBK, CBX3, A1CF, NPAS2, and CTCFL) was developed and proved to be an effective survival predictor in multiple independent datasets. The prognostic signature was also demonstrated to be an indicator of TME and sensitivity to immunotherapy and chemotherapy. The nomogram was suggested to be a simple tool that can predict survival accurately. Clinical samples show that NPAS2 is highly expressed in LUAD tissues, and in vitro and in vivo experiments demonstrated that inhibition of NPAS2 impeded malignant progression of LUAD cells. CONCLUSIONS: Our study comprehensively unveiled the functions of CRs in LUAD, developed a classifier to predict survival and response to treatments, and suggested that NPAS2 promoted LUAD progression for the first time.

Comprehensive analysis of prognostic value, immune implication and biological function of CPNE1 in clear cell renal cell carcinoma.

Background: Elevated expression of Copine-1 (CPNE1) has been proved in various cancers; however, the underlying mechanisms by which it affects clear cell renal cell carcinoma (ccRCC) are unclear. Methods: In this study, we applied multiple bioinformatic databases to analyze the expression and clinical significance of CPNE1 in ccRCC. Co-expression analysis and functional enrichment analysis were investigated by LinkedOmics, cBioPortal and Metascape. The relationships between CPNE1 and tumor immunology were explored using ESTIMATE and CIBERSORT method. In vitro experiments, CCK-8, wound healing, transwell assays and western blotting were conducted to investigate the effects of gain- or loss-of-function of CPNE1 in ccRCC cells. Results: The expression of CPNE1 was notably elevated in ccRCC tissues and cells, and significantly correlated with grade, invasion range, stage and distant metastasis. Kaplan-Meier and Cox regression analysis displayed that CPNE1 expression was an independent prognostic factor for ccRCC patients. Functional enrichment analysis revealed that CPNE1 and its co-expressed genes mainly regulated cancer-related and immune-related pathways. Immune correlation analysis showed that CPNE1 expression was significantly related to immune and estimate scores. CPNE1 expression was positively related to higher infiltrations of immune cells, such as CD8+ T cells, plasma cells and regulatory T cells, exhibited lower infiltrations of neutrophils. Meanwhile, elevated expression of CPNE1 was characterized by high immune infiltration levels, increased expression levels of CD8+ T cell exhaustion markers (CTLA4, PDCD1 and LAG3) and worse response to immunotherapy. In vitro functional studies demonstrated that CPNE1 promoted proliferation, migration and invasion of ccRCC cells through EGFR/STAT3 pathway. Conclusion: CPNE1 is a reliable clinical predictor for the prognosis of ccRCC and promotes proliferation and migration by activating EGFR/STAT3 signaling. Moreover, CPNE1 significantly correlates with immune infiltration in ccRCC.

Genome-Wide Splicing Quantitative Expression Locus Analysis Identifies Causal Risk Variants for Non-Small Cell Lung Cancer.

Alternative RNA splicing is an essential mechanism linking genetic variation to human diseases. While the signals from genome-wide association studies (GWAS) have been linked to expression quantitative trait loci (eQTL) in previous studies, further work is needed to better elucidate the relationship to other genetic regulatory mechanisms, such as splicing QTLs (sQTL). Here, we performed a genome-wide sQTL analysis to identify variants that might affect RNA splicing in 1,010 non-small cell lung cancer (NSCLC) samples from The Cancer Genome Atlas. The identified sQTLs were largely independent of eQTLs and were predominantly enriched in exonic regions, genetic regulatory elements, RNA-binding protein (RBP) binding sites, and known NSCLC risk loci. In addition, target genes affected by sQTLs (sGenes) were involved in multiple processes in cancer, including cell growth, apoptosis, metabolism, immune infiltration, and drug responses, and sGenes were frequently altered genetically in NSCLC. Systematic screening of sQTLs associated with NSCLC risk using GWAS data from 15,474 cases and 12,375 controls identified an sQTL variant rs156697-G allele that was significantly associated with an increased risk of NSCLC. The association between the rs156697-G variant and NSCLC risk was further validated in two additional large population cohorts. The risk variant promoted inclusion of GSTO2 alternative exon 5 and led to higher expression of the GSTO2 full-length isoform (GSTO2-V1) and lower expression of the truncated GSTO2 isoform (GSTO2-V2), which was induced by RBP quaking (QKI). Mechanistically, compared with GSTO2-V1, GSTO2-V2 inhibited NSCLC cells proliferation by increasing S-glutathionylation of AKT1 and thereby functionally blocking AKT1 phosphorylation and activation. Overall, this study provides a comprehensive view of splicing variants linked to NSCLC risk and provides a set of genetic targets with therapeutic potential. SIGNIFICANCE: Analysis of sQTL reveals the role of genetically driven mRNA splicing alterations in NSCLC risk and elucidates that rs156697 variant impacts risk by altering GSTO2 splicing.

Artificial intelligence in clinical decision support systems for oncology.

Artificial intelligence (AI) has been widely used in various medical fields, such as image diagnosis, pathological classification, selection of treatment schemes, and prognosis analysis. Especially in the image-aided diagnosis of tumors, the cooperation of human-computer interactions has become mature. However, the ethics of the application of AI as an emerging technology in clinical decision-making have not been fully supported, so the clinical decision support system (CDSS) based on AI technology has not fully realized human-computer interactions in clinical practice as the image-aided diagnosis system. The CDSS was currently used and promoted worldwide including Watson for Oncology, Chinese society of clinical oncology-artificial intelligence (CSCO AI) and so on. This paper summarized the applications and clarified the principle of AI in CDSS, analyzed the difficulties of AI in oncology decisions, and provided a reference scheme for the application of AI in oncology decisions in the future.

Comprehensive Pan-Cancer Analyses of Immunogenic Cell Death as a Biomarker in Predicting Prognosis and Therapeutic Response.

Immunogenic cell death (ICD), a form of regulated cell death, is related to anticancer therapy. Due to the absence of widely accepted markers, characterizing ICD-related phenotypes across cancer types remained unexplored. Here, we defined the ICD score to delineate the ICD landscape across 33 cancerous types and 31 normal tissue types based on transcriptomic, proteomic and epigenetics data from multiple databases. We found that ICD score showed cancer type-specific association with genomic and immune features. Importantly, the ICD score had the potential to predict therapy response and patient prognosis in multiple cancer types. We also developed an ICD-related prognostic model by machine learning and cox regression analysis. Single-cell level analysis revealed intra-tumor ICD state heterogeneity and communication between ICD-based clusters of T cells and other immune cells in the tumor microenvironment in colon cancer. For the first time, we identified IGF2BP3 as a potential ICD regulator in colon cancer. In conclusion, our study provides a comprehensive framework for evaluating the relation between ICD and clinical relevance, gaining insights into identification of ICD as a potential cancer-related biomarker and therapeutic target.

Characterization of the SARS-CoV-2 co-receptor NRP1 expression profiles in healthy people and cancer patients: Implication for susceptibility to COVID-19 disease and potential therapeutic strategy.

Neuropilin-1 (NRP1) is a transmembrane protein involved in many physiological and pathological processes, and it functions as a co-receptor to facilitate the entry of SARS-CoV-2 into host cells. Therefore, it is critical to predict the susceptibility to SARS-CoV-2 and prognosis after infection among healthy people and cancer patients based on expression of NRP1. In the current study, we analyzed the conservation and isoform of NRP1 using public databases. NRP1 expression landscape in healthy people, COVID-19 patients, and cancer patients at both bulk and single-cell RNA-seq level was also depicted. We also analyzed the relationship between tissue-specific NRP1 expression and overall survival (OS), as well as tumor immune environment at a pan-cancer level, providing a comprehensive insight into the relationship between the vulnerability to SARS-CoV-2 infection and tumorigenesis. In conclusion, we identified NRP1 as a potential biomarker in predicting susceptibility to SARS-CoV-2 infection among healthy people and cancer patients.

Identifying potential pharmacological targets and mechanisms of vitamin D for hepatocellular carcinoma and COVID-19.

Coronavirus disease 2019 (COVID-19) is a severe pandemic that has posed an unprecedented challenge to public health worldwide. Hepatocellular carcinoma (HCC) is a common digestive system malignancy, with high aggressiveness and poor prognosis. HCC patients may be vulnerable to COVID-19. Since the anti-inflammatory, immunomodulatory and antiviral effects of vitamin D, we aimed to investigate the possible therapeutic effects and underlying action mechanisms of vitamin D in COVID-19 and HCC in this study. By using a range of bioinformatics and network pharmacology analyses, we identified many COVID-19/HCC target genes and analyzed their prognostic significance in HCC patients. Further, a risk score model with good predictive performance was developed to evaluate the prognosis of HCC patients with COVID-19 based on these target genes. Moreover, we identified seven possible pharmacological targets of vitamin D against COVID-19/HCC, including HMOX1, MB, TLR4, ALB, TTR, ACTA1 and RBP4. And we revealed the biological functions, signaling pathways and TF-miRNA coregulatory network of vitamin D in COVID-19/HCC. The enrichment analysis revealed that vitamin D could help in treating COVID-19/HCC effects through regulation of immune response, epithelial structure maintenance, regulation of chemokine and cytokine production involved in immune response and anti-inflammatory action. Finally, the molecular docking analyses were performed and showed that vitamin D possessed effective binding activity in COVID-19. Overall, we revealed the possible molecular mechanisms and pharmacological targets of vitamin D for treating COVID-19/HCC for the first time. But these findings need to be further validated in actual HCC patients with COVID-19 and need further investigation to confirm.

Identification of a prognostic classifier based on EMT-related lncRNAs and the function of LINC01138 in tumor progression for lung adenocarcinoma.

Purpose: This study aimed to develop a prognostic indicator based on epithelial-mesenchymal transition (EMT)-related long noncoding RNAs (lncRNAs) and explore the function of EMT-related lncRNAs in malignant progression in lung adenocarcinoma (LUAD). Materials and methods: A LUAD dataset was acquired from The Cancer Genome Atlas (TCGA) to identify prognostic EMT-related lncRNAs via differential expression analysis and univariate Cox regression analysis. Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis was utilized for variable selection and model construction. The EMT-related prognostic index (ERPI) was calculated according to the model and served as a classifier to divide LUAD individuals into high-ERPI and low-ERPI groups. A nomogram incorporating ERPI and clinicopathological variables was constructed. TCGA-LUAD, GSE50081, and GSE31210 were used to test the predictive capacity of the ERPI and nomogram. The characteristics of the tumor microenvironment (TME) were evaluated via the ESTIMATE, TIMER, and ssGSEA algorithms. Gene set variation analysis (GSVA) and ssGSEA were used to annotate the functions of the high-ERPI and low-ERPI groups. CCK8, transwell assay, wound-healing assay, and clone formation assay were conducted to clarify the biological functions of prognostic EMT-related lncRNAs. Results: Ninety-seven differentially expressed EMT-related lncRNAs were identified, 15 of which were related to overall survival (OS). A prognostic signature was constructed based on 14 prognostic EMT-related lncRNAs to calculate the ERPI of each patient, and the predictive ability of ERPI was verified in TCGA, GSE50081, and GSE31210. The low-ERPI group survived longer and had a lower percentage of patients in advanced stage than the high-ERPI group. The nomogram had the highest predictive accuracy, followed by ERPI and stage. Patients with low ERPI had higher infiltration degree of immune cells and stronger immune responses than those with high ERPI. A series of in vitro experiments demonstrated that knockdown of LINC01138 dampened variability, proliferation, and motility of A549 and H460 cells. Conclusion: Our study developed a prognostic classifier with robust prognostic performance and clarified the biological functions of LINC01138 in LUAD, aiding in making individual treatments for patients with LUAD and dissecting the mechanism of oncogenesis.

Establishment of a Necroptosis Related Genes Signature to Predict Prognosis and Therapeutic Response in Colon Cancer.

Necroptosis, as a form of programmed cell death, is involved in many physiological and pathological processes. However, its role in cancer progression and therapeutic response remains controversial. Colon cancer is one of the leading causes of cancer death and patients' response to immune checkpoint blockade vary to a large degree. In this study, we investigated necroptosis related genes (NRGs) alterations in colon cancer by bioinformatics analysis. Colon cancer patients were classified into two subtypes with distinct clinical and molecular features based on NRGs. After finding differentially expressed genes and lasso regression, a prognostic model based on four necroptosis signature genes was constructed. The necroptosis signature was also a good predictor in the field of chemotherapy and immunotherapy in colon cancer. Altogether, this study illustrates the relationship between necroptosis and colon cancer, and establishes a novel scoring method to predict prognosis and therapeutic response in colon cancer patients.

A Genetic Variant in CD274 Is Associated With Prognosis in Metastatic Colorectal Cancer Patients Treated With Bevacizumab-Based Chemotherapy.

Bevacizumab plus chemotherapy is a well-established first-line treatment for metastatic colorectal cancer (mCRC). We investigated whether polymorphisms of genes involved in immune regulation signaling are related to the clinical outcome of mCRC patients treated with bevacizumab-based chemotherapy. In this study, we genotyped 14 single-nucleotide polymorphisms (SNP) in IFN-γ/IFNGRs/JAKs/STATs/PD-L1 pathway by using DNA from blood samples of 141 mCRC patients treated with first-line bevacizumab-based chemotherapy. In the univariate and multivariate analysis, patients with AA genotype of CD274:rs2297136 had a significantly better PFS and OS than patients with AG or GG genotype (10.8 versus 9.8, log-rank P=0.0031; 31.4 versus 20.9, log-rank P=0.0233). Patients with AG/GG genotype of IFNGR1:rs2234711, CT/TT genotype of IFNGR1:rs9376267 also showed longer OS than patients with AA or CC genotype, however, the statistic did not reach significant after adjusted by clinical factors in the multivariate analysis. A nomogram based on the genetic variants and clinic characteristics was developed with a good accuracy to predict patients' survival. Our result indicates that CD274:rs2297136 is one of the most important predictors for the prognosis of mCRC patients treated with bevacizumab-based chemotherapy, if further validated in larger population.

Sitagliptin Alleviates Radiation-Induced Intestinal Injury by Activating NRF2-Antioxidant Axis, Mitigating NLRP3 Inf--lammasome Activation, and Reversing Gut Microbiota Disorder.

Radiation-induced intestinal injury is a common and critical complication of radiotherapy for pelvic or abdominal tumors, with limited therapeutic strategies and effectiveness. Sitagliptin, a dipeptidyl peptidase IV (DPP4) inhibitor, has previously been reported to alleviate total body irradiation- (TBI-) induced damage of hematopoietic system in mice, but its effect on radiation-induced intestinal injury remains unclear. In this study, we confirmed that Sitagliptin could not only protect mice from death and weight loss caused by whole abdominal irradiation (WAI) but also improve the morphological structure of intestine and the regeneration ability of enterocytes. In addition, Sitagliptin significantly inhibited the production of radiation-induced proinflammatory cytokines and reduced the number of apoptotic intestinal epithelial cells and γ-H2AX expression. In vitro, we demonstrated that Sitagliptin protected HIEC-6 cells from ionizing radiation, resulting in increased cell viability and reduced DNA damage. Mechanistically, the radiation protection of Sitagliptin might be related to the upregulation of NRF2 level and the decrease of NLRP3 inflammasome activity. Importantly, Sitagliptin significantly restored radiation-induced changes in bacterial composition. In conclusion, our results suggested that Sitagliptin could reduce WAI-induced intestinal injury in mice, which may provide novel therapeutic strategy for radiation-induced intestinal injury.

Integrative Analysis Constructs an Extracellular Matrix-Associated Gene Signature for the Prediction of Survival and Tumor Immunity in Lung Adenocarcinoma.

Background: Lung adenocarcinoma (LUAD) accounts for the majority of lung cancers, and the survival of patients with advanced LUAD is poor. The extracellular matrix (ECM) is a fundamental component of the tumor microenvironment (TME) that determines the oncogenesis and antitumor immunity of solid tumors. However, the prognostic value of extracellular matrix-related genes (ERGs) in LUAD remains unexplored. Therefore, this study is aimed to explore the prognostic value of ERGs in LUAD and establish a classification system to predict the survival of patients with LUAD. Methods: LUAD samples from The Cancer Genome Atlas (TCGA) and GSE37745 were used as discovery and validation cohorts, respectively. Prognostic ERGs were identified by univariate Cox analysis and used to construct a prognostic signature by Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis. The extracellular matrix-related score (ECMRS) of each patient was calculated according to the prognostic signature and used to classify patients into high- and low-risk groups. The prognostic performance of the signature was evaluated using Kaplan-Meier curves, Cox regression analyses, and ROC curves. The relationship between ECMRS and tumor immunity was determined using stepwise analyses. A nomogram based on the signature was established for the convenience of use in the clinical practice. The prognostic genes were validated in multiple databases and clinical specimens by qRT-PCR. Results: A prognostic signature based on eight ERGs (FERMT1, CTSV, CPS1, ENTPD2, SERPINB5, ITGA8, ADAMTS8, and LYPD3) was constructed. Patients with higher ECMRS had poorer survival, lower immune scores, and higher tumor purity in both the discovery and validation cohorts. The predictive power of the signature was independent of the clinicopathological parameters, and the nomogram could also predict survival precisely. Conclusions: We constructed an ECM-related gene signature which can be used to predict survival and tumor immunity in patients with LUAD. This signature can serve as a novel prognostic indicator and therapeutic target in LUAD.

Development of Tumor Mutation Burden-Related Prognostic Model and Novel Biomarker Identification in Stomach Adenocarcinoma.

Background: Stomach adenocarcinoma (STAD) is one of the most common tumors. Tumor mutation burden (TMB) has been linked to immunotherapy response. We wanted to see if there was any link between TMB and cancer prognosis. Methods: The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases were used to obtain mutation data, gene expression profiles, and clinical data. We looked at the differences in gene expression and immune markers between low and high TMB groups, built an immune prognostic model, and created a dynamic nomograph App that may be used in the clinic. Simultaneously, We ran the immunotherapy prediction and model comparison at the same time. Finally, model gene mutation and copy number variation (CNV) were displayed. The cellular functional experiments were used to investigate the potential role of GLP2R in gastric cancer. Results: Firstly, basic mutation information and differences in immune infiltration in STAD are revealed. Secondly, the prognostic model developed by us has good accuracy, and the corresponding dynamic nomograph Apps online and immunotherapy prediction facilitate clinical transformation. Furthermore, GLP2R knockdown significantly inhibited the proliferation, migration of gastric cancer cells in vitro. Conclusion: Our findings imply that TMB plays a significant role in the prognosis of STAD patients from a biological perspective. GLP2R may serve as a potential target for gastric cancer.

Construction of a Redox-Related Prognostic Model with Predictive Value in Survival and Therapeutic Response for Patients with Lung Adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) represents the most common histological subtype of lung cancer. Redox plays a significant role in oncogenesis and antitumor immunity. In this study, we aimed to investigate the prognostic redox-associated genes and construct a redox-based prognostic signature for LUAD. MATERIALS AND METHODS: A discovery cohort containing 479 LUAD samples from The Cancer Genome Atlas (TCGA) was analyzed. We identified prognostic redox-associated genes by weighted correlation network analysis (WGCNA) and univariate Cox regression analysis to construct a prognostic model via least absolute shrinkage and selection operator (LASSO)-multivariate Cox regression analyses. The performance of the redox-based model was validated in the TCGA cohort and an independent cohort of 456 samples by Cox regression analyses, log-rank test, and receiver operating characteristic (ROC) curves. Correlations of the model with clinicopathological variables and lymphocyte infiltration were assessed. Gene set enrichment analysis (GSEA) was used to clarify the underlying mechanism of the prognostic model. We constructed a nomogram based on the model and created calibration curves to show the accordance between actual survival and predicted survival of the nomogram. RESULTS: Stepwise analyses identified 6 prognostic redox-associated genes of LUAD and constructed a prognostic model that performed well in both the discovery and validation cohorts. The model was found to be associated with tumor stage, mutation of TP53 and EGFR, and lymphocyte infiltration. The model was mainly involved in the regulation of the cell cycle, DNA replication and repair, NADH metabolism, and the p53 signaling pathway. Calibration curves showed the high predictive accuracy of the nomogram. CONCLUSIONS: This study explored the role of redox-associated genes in LUAD and constructed a prognostic model of LUAD. The signature was also associated with tumor progression and therapeutic response to immunotherapy. These findings contributed to uncovering the underlying mechanism and discovering novel prognostic predictor of LUAD.