Cancer Biomarkers最新文献

{"title":"Comprehensive analysis of thirteen-gene panel with prognosis value in Multiple Myeloma","authors":"Tingting Zheng, Panpan Chen, Yuanlin Xu, Peijun Jia, Yan Li, Yating Li, Jiaming Cao, Wanxin Li, Yazhe Zhen, Ying Zhang, Shijie Zhang, Jiangfeng Du, Jingxin Zhang","doi":"10.3233/cbm-230115","DOIUrl":"https://doi.org/10.3233/cbm-230115","url":null,"abstract":"BACKGROUND: Although there are many treatments for Multiple myeloma (MM), patients with MM still unable to escape the recurrence and aggravation of the disease. OBJECTIVE: We constructed a risk model based on genes closely associated with MM prognosis to predict its prognostic value. METHODS: Gene function enrichment and signal pathway enrichment analysis, Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis, univariate and multivariate Cox regression analysis, Kaplan-Meier (KM) survival analysis and Receiver Operating Characteristic (ROC) analysis were used to identify the prognostic gene signature for MM. Finally, the prognostic gene signature was validated using the Gene Expression Omnibus (GEO) database. RESULTS: Thirteen prognostic genes were screened by univariate Cox analysis and LASSO regression analysis. Multivariate Cox analysis revealed risk score to be an independent prognostic factor for patients with MM [Hazard Ratio (HR) = 2.564, 95% Confidence Interval (CI) = 2.223–2.958, P< 0.001]. The risk score had a high level of predictive value according to ROC analysis, with an area under the curve (AUC) of 0.744. CONCLUSIONS: The potential prognostic signature of thirteen genes were assessed and a risk model was constructed that significantly correlated with prognosis in MM patients.","PeriodicalId":56320,"journal":{"name":"Cancer Biomarkers","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135875116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Urinary VOCs as biomarkers of early stage lung tumour development in mice","authors":"Flora Gouzerh, Gwenaëlle Vigo, Laurent Dormont, Bruno Buatois, Maxime R. Hervé, Maicol Mancini, Antonio Maraver, Frédéric Thomas, Guila Ganem","doi":"10.3233/cbm-230070","DOIUrl":"https://doi.org/10.3233/cbm-230070","url":null,"abstract":"BACKGROUND: Lung cancer is the primary cause of cancer-induced death. In addition to prevention and improved treatment, it has increasingly been established that early detection is critical to successful remission. OBJECTIVE: The aim of this study was to identify volatile organic compounds (VOCs) in urine that could help diagnose mouse lung cancer at an early stage of its development. METHODS: We analysed the VOC composition of urine in a genetically engineered lung adenocarcinoma mouse model with oncogenic EGFR doxycycline-inducible lung-specific expression. We compared the urinary VOCs of 10 cancerous mice and 10 healthy mice (controls) before and after doxycycline induction, every two weeks for 12 weeks, until full-blown carcinomas appeared. We used SPME fibres and gas chromatography – mass spectrometry to detect variations in cancer-related urinary VOCs over time. RESULTS: This study allowed us to identify eight diagnostic biomarkers that help discriminate early stages of cancer tumour development (i.e., before MRI imaging techniques could identify it). CONCLUSION: The analysis of mice urinary VOCs have shown that cancer can induce changes in odour profiles at an early stage of cancer development, opening a promising avenue for early diagnosis of lung cancer in other models.","PeriodicalId":56320,"journal":{"name":"Cancer Biomarkers","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135875310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing the clinical utility of biomarkers using the intervention probability curve (IPC).","authors":"Rafael Paez, Dianna J Rowe, Stephen A Deppen, Eric L Grogan, Alexander Kaizer, Darryl J Bornhop, Amanda K Kussrow, Anna E Barón, Fabien Maldonado, Michael N Kammer","doi":"10.3233/CBM-230054","DOIUrl":"10.3233/CBM-230054","url":null,"abstract":"<p><strong>Background: </strong>Assessing the clinical utility of biomarkers is a critical step before clinical implementation. The reclassification of patients across clinically relevant subgroups is considered one of the best methods to estimate clinical utility. However, there are important limitations with this methodology. We recently proposed the intervention probability curve (IPC) which models the likelihood that a provider will choose an intervention as a continuous function of the probability, or risk, of disease.</p><p><strong>Objective: </strong>To assess the potential impact of a new biomarker for lung cancer using the IPC.</p><p><strong>Methods: </strong>The IPC derived from the National Lung Screening Trial was used to assess the potential clinical utility of a biomarker for suspected lung cancer. The summary statistics of the change in likelihood of intervention over the population can be interpreted as the expected clinical impact of the added biomarker.</p><p><strong>Results: </strong>The IPC analysis of the novel biomarker estimated that 8% of the benign nodules could avoid an invasive procedure while the cancer nodules would largely remain unchanged (0.1%). We showed the benefits of this approach compared to traditional reclassification methods based on thresholds.</p><p><strong>Conclusions: </strong>The IPC methodology can be a valuable tool for assessing biomarkers prior to clinical implementation.</p>","PeriodicalId":56320,"journal":{"name":"Cancer Biomarkers","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2023-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11055936/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138813944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A comprehensive analysis of mRNA expression profiles of Esophageal Squamous Cell Carcinoma reveals downregulation of Desmoglein 1 and crucial genomic targets","authors":"Amal Alotaibi, Veerendra P. Gadekar, Pranav Swaroop Gundla, Sumana Mandarthi, Subramanyeshwari Ravi, Dhyeya Mallya, Asna Tungekar, B.V. Lavanya, Ashok Kumar Bhagavath, MaryAnne Wong Cordero, Janne Pitkaniemi, Raviraja N. Seetharam, Asmatanzeem Bepari, Prashantha Hebbar","doi":"10.3233/cbm-230145","DOIUrl":"https://doi.org/10.3233/cbm-230145","url":null,"abstract":"AIM: Esophageal Squamous Cell Carcinoma (ESCC) is a histological subtype of esophageal cancer that begins in the squamous cells in the esophagus. In only 19% of the ESCC-diagnosed patients, a five-year survival rate has been seen. This necessitates the identification of high-confidence biomarkers for early diagnosis, prognosis, and potential therapeutic targets for the mitigation of ESCC. METHOD: We performed a meta-analysis of 10 mRNA datasets and identified consistently perturbed genes across the studies. Then, integrated with ESCC ATLAS to segregate ‘core’ genes to identify consequences of primary gene perturbation events leading to gene-gene interactions and dysregulated molecular signaling pathways. Further, by integrating with toxicogenomics data, inferences were drawn for gene interaction with environmental exposures, trace elements, chemical carcinogens, and drug chemicals. We also deduce the clinical outcomes of candidate genes based on survival analysis using the ESCC related dataset in The Cancer Genome Atlas. RESULT: We identified 237 known and 18 novel perturbed candidate genes. Desmoglein 1 (DSG1) is one such gene that we found significantly downregulated (Fold Change =-1.89, p-value = 8.2e-06) in ESCC across six different datasets. Further, we identified 31 ‘core’ genes (that either harbor genetic variants or are regulated by epigenetic modifications) and found regulating key biological pathways via adjoining genes in gene-gene interaction networks. Functional enrichment analysis showed dysregulated biological processes and pathways including “Extracellular matrix”, “Collagen trimmer” and “HPV infection” are significantly overrepresented in our candidate genes. Based on the toxicogenomic inferences from Comparative Toxicogenomics Database we report the key genes that interacted with risk factors such as tobacco smoking, zinc, nitroso benzylmethylamine, and drug chemicals such as cisplatin, Fluorouracil, and Mitomycin in relation to ESCC. We also point to the STC2 gene that shows a high risk for mortality in ESCC patients. CONCLUSION: We identified novel perturbed genes in relation to ESCC and explored their interaction network. DSG1 is one such gene, its association with microbiota and a clinical presentation seen commonly with ESCC hints that it is a good candidate for early diagnostic marker. Besides, in this study we highlight candidate genes and their molecular connections to risk factors, biological pathways, drug chemicals, and the survival probability of ESCC patients.","PeriodicalId":56320,"journal":{"name":"Cancer Biomarkers","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2023-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138554461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"STEAP3 is a prognostic biomarker that promotes glioma progression by regulating immune microenvironment and PI3K-AKT pathway","authors":"Zihan Song, Zijun Zhao, Siyu Zhu, Qianxu Jin, Yunpeng Shi, Shiyang Zhang, Zairan Wang, Yizheng Wang, Zongmao Zhao","doi":"10.3233/cbm-230217","DOIUrl":"https://doi.org/10.3233/cbm-230217","url":null,"abstract":"BACKGROUND: STEAP3 is a metal reductase located on the plasma membrane close to the nucleus and vesicles. Despite numerous studies indicating the involvement of STEAP3 in tumor advancement, the prognostic value of STEAP3 in glioma and the related mechanisms have not been fully investigated. METHODS: Initially, we examined the correlation between STEAP3 expression and the survival rate in various glioma datasets. To assess the prognostic capability of STEAP3 for one-year, three-year, and five-year survival, we created receiver operating characteristic (ROC) curves and nomograms. Additionally, an investigation was carried out to examine the mechanisms that contribute to the involvement of STEAP3 in gliomas, including immune and enrichment analysis. To confirm the expression of STEAP3 in LGG and GBM, tumor tissue samples were gathered, and cell experiments were conducted to explore the impacts of STEAP3. The function of STEAP3 in the tumor immune microenvironment was assessed using the M2 macrophage infiltration assay. RESULTS: We found that STEAP3 expressed differently in group with different age, tumor grade IDH and 1p19q status. The analysis of survival illustrated that glioma patients with high level of STEAP3 experienced shorter survival durations, especially for IDH-mutant astrocytoma. Cox analysis demonstrated that STEAP3 had potential to act as an independent prognostic factor for glioma. The predictive value of STEAP3 for glioma prognosis was demonstrated by ROC curves and nomogram. Immune analysis showed that STEAP3 may lead to a suppressive immune microenvironment through the control of immunosuppressive cell infiltration and Cancer-Immunity Cycle. Combining enrichment analysis and cell experiments, we discovered that STEAP3 can promote glioma progression through regulation of PI3K-AKT pathway and M2 macrophage infiltration. CONCLUSION: STEAP3 plays significant roles in the advancement of glioma by regulating immune microenvironment and PI3K-AKT pathway. It has the potential to serve as a therapy target for glioma.","PeriodicalId":56320,"journal":{"name":"Cancer Biomarkers","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136376250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Albumin-bilirubin score predicts trastuzumab resistance in HER2-positive breast cancer","authors":"Wen-Juan Huang, Jia-Rui Yuan, Lei Zhang, Wen Wang, Shi-Di Miao, Xin Wang, Rui-Tao Wang","doi":"10.3233/cbm-230077","DOIUrl":"https://doi.org/10.3233/cbm-230077","url":null,"abstract":"BACKGROUND: The albumin-bilirubin (ALBI) score is a novel indicator of liver function. Some studies showed that the ALBI score was a predictive marker for the prognosis and efficacy of drug therapy in malignancies. We aimed to assess the predicted role of ALBI score in the sensitivity to therapy with trastuzumab in patients with human epidermal growth factor receptor 2 (HER2) positive breast cancer (BC). The clinical data of 226 HER2-positive BC patients at the Harbin Medical University Cancer Hospital from January 2017 and December 2018 were retrospectively collected. The ALBI score was calculated with serum albumin and bilirubin before diagnosis. The associations between ALBI score and trastuzumab resistance were analyzed by logistic regression analyses. The patients with trastuzumab resistance had higher ALBI scores compared with the patients without trastuzumab resistance. Moreover, there were weak correlations between the ALBI score and lymph node status (P= 0.093). In addition, multivariate analysis revealed that the ALBI score was an independent prognostic factor for trastuzumab resistance in HER2-positive BC. High ALBI score is associated with trastuzumab resistance in HER2-positive BC. Future studies are needed.","PeriodicalId":56320,"journal":{"name":"Cancer Biomarkers","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134971588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Subgroup identification of targeted therapy effects on biomarker for time to event data","authors":"Gajendra K. Vishwakarma, Atanu Bhattacharjee, Fatih Tank, Alexander F. Pashchenko","doi":"10.3233/cbm-230181","DOIUrl":"https://doi.org/10.3233/cbm-230181","url":null,"abstract":"BACKGROUND: The initiation biomarker-driven trials have revolutionized oncology drug development by challenging the traditional phased approach and introducing basket studies. Notable successes in non-small cell lung cancer (NSCLC) with ALK, ALK/ROS1, and EGFR inhibitors have prompted the need to expand this approach to other cancer sites. OBJECTIVES: This study explores the use of dose response modeling and time-to-event algorithms on the biomarker molecular targeted agent (MTA). By simulating subgroup identification in MTA-related time-to-event data, the study aims to develop statistical methodology supporting biomarker-driven trials in oncology. METHODS: A total of n patients are selected assigned for different doses. A dataset is prepared to mimic the situation on Subgroup Identification of MTA for time to event data analysis. The response is measured through MTA. The MTA value is also measured through ROC. The Markov Chain Monte Carlo (MCMC) techniques are prepared to perform the proposed algorithm. The analysis is carried out with a simulation study. The subset selection is performed through the Threshold Limit Value (TLV) by the Bayesian approach. RESULTS: The MTA is observed with range 12–16. It is expected that there is a marginal level shift of the MTA from pre to post-treatment. The Cox time-varying model can be adopted further as causal-effect relation to establishing the MTA on prolonging the survival duration. The proposed work in the statistical methodology to support the biomarker-driven trial for oncology research. CONCLUSION: This study extends the application of biomarker-driven trials beyond NSCLC, opening possibilities for implementation in other cancer sites. By demonstrating the feasibility and efficacy of utilizing MTA as a biomarker, the research lays the foundation for refining and validating biomarker use in clinical trials. These advancements aim to enhance the precision and effectiveness of cancer treatments, ultimately benefiting patients.","PeriodicalId":56320,"journal":{"name":"Cancer Biomarkers","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135944270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correlation between IL3 signaling pathway-related genes and immune checkpoint inhibitor efficacy in patients with renal cell carcinoma.","authors":"Shuang Hou, Tianqi Gu, Ying Shi, Yushan Huang, Jiarong Yao, Peng Luo, Manming Cao, Jian Zhang, Anqi Lin, Weiliang Zhu","doi":"10.3233/CBM-230226","DOIUrl":"10.3233/CBM-230226","url":null,"abstract":"<p><strong>Background: </strong>There is a lack of effective biomarkers that predict immunotherapy efficacy in clear cell renal cell carcinoma(KIRC).</p><p><strong>Objective: </strong>We aimed to identify biomarkers that would predict the efficacy of KIRC treatment with immune checkpoint inhibitors (ICIs).</p><p><strong>Methods: </strong>Cohort data of KIRC patients with somatic mutations, mRNA expression and survival data from The Cancer Genome Atlas (TCGA) database and immunotherapy cohort and Genomics of Drug Sensitivity in Cancer (GDSC) database were analyzed and divided into interleukin 3 (IL3) pathway-related genes high expression (IL3-High) and IL3 pathway-related genes low expression (IL3-Low) groups according to pathway expression status to assess the relationship between the IL3 pathway-related genes activation status and the prognosis of KIRC patients treated with ICIs. The data were validated by immunohistochemistry experiments, and possible mechanisms of action were explored at the level of gene mutation landscape, immune microenvironment characteristics, transcriptome and copy number variation(CNV) characteristicsRESULTS: The IL3 pathway-related genes was an independent predictor of the efficacy of ICIs in KIRC patients, and the IL3-High group had a longer overall survival (OS); KIRC patients in the IL3-High group had increased levels of chemokines, cytolysis, immune checkpoint gene expression and abundant immunity. The IL3-Low group had poor immune cell infiltration and significant downregulation of complement activation, cytophagy, B-cell activation, and humoral immune response pathways. The high group was more sensitive to targeted drugs of some signaling pathways, and its efficacy in combining these drugs with immunity has been predicted in the published literature.</p><p><strong>Conclusion: </strong>The IL3 pathway-related genes can be used as a predictor of the efficacy of ICIs in KIRC. The IL3 pathway-related genes may affect the therapeutic efficacy of ICIs by affecting the expression of immune-related molecules, immune cell infiltration, and the level of immune response pathways.</p>","PeriodicalId":56320,"journal":{"name":"Cancer Biomarkers","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138479471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DNALI1 is a prognosis-related biomarker and correlates with immune infiltrates in low grade glioma.","authors":"Yapeng Lu, Panpan Chang, Jiangpei Bian, Li Zhu","doi":"10.3233/CBM-230139","DOIUrl":"10.3233/CBM-230139","url":null,"abstract":"<p><strong>Background: </strong>Dynein axonemal light intermediate chain 1 (DNALI1) is a component of axonemal dyneins and its role in cancer progression is not known.</p><p><strong>Objective: </strong>The influence of DNALI1 expression on the prognosis of low-grade gliomas (LGG) and the possible mechanisms of DNALI1 in promoting the progression of LGG was investigated by applying multiple bioinformatics analyses using datasets from TCGA, GTEx, CPTAC, and CGGA.</p><p><strong>Methods: </strong>The expression of DNALI1 in different tumor tissues including LGG was investigated. GO functional annotation, KEGG pathway analysis, and GSEA enrichment analysis were performed. The correlation between DNALI1 and prognosis, tumor microenvironment (TME) and immune checkpoints in LGG were assessed.</p><p><strong>Results: </strong>DNALI1 is mainly expressed in malignant cells in the TME of LGG and positively correlated with the development of LGG. DNALI1 expression is negatively correlated with isocitrate dehydrogenase (IDH) mutations and 1p/19q co-deletion. High DNALI1 expression is associated with poor prognosis in LGG. DNALI1 may promote LGG progression through multiple immune-related pathways. The expression of DNALI1 is positively correlated with the infiltration of certain types of immune cells and the expression of some immune checkpoints.</p><p><strong>Conclusions: </strong>DNALI1 is a potential prognostic marker for LGG, and high expression of DNALI1 may play an important role in maintaining the immunosuppressive microenvironment of LGG.</p>","PeriodicalId":56320,"journal":{"name":"Cancer Biomarkers","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89720826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A new immune-related gene signature predicts the prognosis and immune escape of bladder cancer.","authors":"Yang Liu, Yan-Song Han, Jin-Feng Wang, Zhong-Qi Pang, Jian-She Wang, Lu Zhang, Jia-Xin He, Lin-Kun Shen, Bo Ji, Bei-Chen Ding, Ming-Hua Ren","doi":"10.3233/CBM-230190","DOIUrl":"10.3233/CBM-230190","url":null,"abstract":"<p><strong>Background: </strong>The biological roles of immune-related genes (IRGs) in bladder cancer (BC) need to be further elucidated.</p><p><strong>Objective: </strong>To elucidate the predictive value of IRGs for prognosis and immune escape in BC.</p><p><strong>Methods: </strong>We comprehensively analyzed the transcriptomic and clinical information of 430 cases, including 19 normal and 411 BC patients from the TCGA database, and verified 165 BC cases in the GSE13507 dataset. The risk model was constructed based on IRGs by applying LASSO Cox regression and exploring the relationship between the risk score and prognosis, gene mutations, and immune escape in BC patients.</p><p><strong>Results: </strong>We identified 4 survival-related genes (PSMC1, RAC3, ROBO2 and ITGB3) among 6,196 IRGs in both the TCGA and GES13507 datasets,, which were used to establish a gene risk model by applying LASSO Cox regression. The results showed that the high-risk (HR) group was closely associated with poor survival or advanced pathological stage of BC. Furthermore, the risk score was found to be an independent risk factor for prognosis of BC patients. In addition, high-risk individuals showed a greater prevalence of TP53 mutations lower CD8+ T-cell and NK cell infiltration, higher Treg cell infiltration, higher expression of PD-L1, and higher immune exclusion scores than those in the low-risk (LR) group. Finally, the experimental verification shows that the model construction gene, especially PMSC1, plays an important role in the growth and metastasis of bladder cancer.</p><p><strong>Conclusions: </strong>These evidences revealed the vital role of IRGs in predicting prognosis, TP53 mutation and immune escape in BC patients.</p>","PeriodicalId":56320,"journal":{"name":"Cancer Biomarkers","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138813943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}