Translational cancer research最新文献

{"title":"Microbial community profiles in breast cancer and normal adjacent tissues: associations with clinicopathological characteristics.","authors":"Dengfeng Xue, Chunhui Wu, Ruihong Hou, Huijuan Xu, Xinzheng Li","doi":"10.21037/tcr-2025-1570","DOIUrl":"10.21037/tcr-2025-1570","url":null,"abstract":"<p><strong>Background: </strong>The microorganisms in breast tissue and its surrounding environment play a critical role in the development and progression of breast cancer (BC). This study aims to characterize BC-associated microbiota via 16S ribosomal RNA (rRNA) sequencing to explore potential pathogenic mechanisms and support early diagnosis and personalized treatment.</p><p><strong>Methods: </strong>Tumor and normal adjacent tissue (NAT) samples from 31 BC patients were analyzed by 16S rRNA sequencing targeting five variable regions. Microbial composition was analyzed via the Short MUltiple Regions Framework (SMURF) pipeline. Alpha and beta diversity analyses were conducted to compare the microbial communities between the BC and NAT groups, and among different BC subgroups stratified by the molecular subtype, clinical stage, histological grade, and proliferation index (Ki-67). Differential microbial taxa were identified using the Wilcoxon signed-rank test and linear discriminant analysis effect size (LEfSe). Functional pathways were predicted using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database.</p><p><strong>Results: </strong>No significant differences in alpha or beta diversity were observed between the BC and NAT groups (P>0.05). The LEfSe revealed that <i>Flavobacteriales</i>, <i>Comamonas</i>, and <i>Delftia</i> were enriched in BC. The KEGG pathway predictions showed that the ascorbate and aldarate metabolism, lysosome, and other glycan degradation pathways were upregulated in BC. <i>Brevundimonas</i> was the dominant genus in the high Ki-67 (H-Ki-67) group, in which, the glycolysis/gluconeogenesis, bacterial toxins, and isoflavonoid biosynthesis pathways were also shown to be upregulated (P<0.05).</p><p><strong>Conclusions: </strong>Overall, microbial diversity was similar between the BC and NAT groups; however, distinct microbial profiles were identified in the BC tissue group and among the clinicopathological subgroups. Brevundimonas was the predominant genus in the H-Ki-67 group. This study provides novel insights and potential targets that may extend our understanding of BC-related microbial mechanisms and advance microbiota-based therapies.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 8","pages":"5093-5108"},"PeriodicalIF":1.7,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12432769/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145065641","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":"Exploration of the mechanism of curcumin in the regulation of apoptosis for the treatment of colorectal cancer.","authors":"Yu Wu, Da-Zhi Gao, Ning-Ning Zhao, Yu Han, Xue-Feng Zhao","doi":"10.21037/tcr-2025-359","DOIUrl":"10.21037/tcr-2025-359","url":null,"abstract":"<p><strong>Background: </strong>The incidence of colorectal cancer (CRC) is steadily increasing, and its standard treatment regimen improves the survival rate of tumor patients, but metastatic CRC is the main cause of death in CRC patients. As a low-toxicity natural compound, curcumin, a traditional Chinese medicine, can effectively inhibit the growth of tumor cells by mediating various biological processes. This study aimed to investigate the molecular mechanism underlying curcumin in the treatment of CRC using a combination of network pharmacology analysis and experimental validation.</p><p><strong>Methods: </strong>The GeneCards database was used to identify potential targets associated with CRC and apoptosis. Target concentrations for curcumin and apoptosis were identified from the Search Tool for Interacting Chemicals (STITCH) and GeneCards databases, respectively. Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were conducted using the 'clusterprofile' package in R software. Furthermore, to examine the impact of curcumin on the viability and apoptosis of colon cancer cell lines, Cell Counting Kit-8 (CCK-8) assays and flow cytometry analyses were performed. Lastly, Western blot analysis was conducted to validate curcumin's effects on proapoptotic protein.</p><p><strong>Results: </strong>A total of 25 essential genes were identified for protein-protein interaction (PPI) network construction and enrichment analysis. The results of the CCK-8 assay indicated that curcumin exerted inhibitory effects on <i>in vitro</i> proliferation. Moreover, the results of flow cytometry demonstrated that curcumin triggered apoptosis in SW480 cells and HCT116 cells. Finally, western blot analysis revealed that curcumin down-regulated the expression of MDM2 and COX-2.</p><p><strong>Conclusions: </strong>This study suggests a possible therapeutic approach for CRC by modulating key genes associated with apoptosis, such as MDM2 and COX-2, offering a novel therapeutic strategy for CRC.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 8","pages":"4507-4519"},"PeriodicalIF":1.7,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12432617/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145065449","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 novel risk score model incorporating six co-stimulatory molecules for accurate prognosis prediction of laryngeal cancer.","authors":"Tianyi Liu, Shan Gao, Jie Jiang, Yan Shi","doi":"10.21037/tcr-2024-2447","DOIUrl":"10.21037/tcr-2024-2447","url":null,"abstract":"<p><strong>Background: </strong>Laryngeal cancer (LC) is a common respiratory tract malignancy. Although early-stage LC often responds well to treatment, advanced cases typically have poor outcomes and prognosis, resulting in a low overall survival (OS) rate. This study aimed to explore the correlation between co-stimulatory molecules and immune infiltration in LC and to construct a risk score (RS) model for predicting patient prognosis.</p><p><strong>Methods: </strong>The RNA sequencing (RNA-seq) data of LC samples were downloaded from The Cancer Genome Atlas (TCGA) and used as the training dataset. The GSE27020 dataset served as the validation dataset. Univariate Cox regression analysis was performed to identify immune-related co-stimulatory molecules, based on which the samples were classified into three subtypes. Kaplan-Meier (KM) survival analysis was conducted to predict the survival prognosis in different subtypes. A prognostic RS model was constructed using the co-stimulatory molecules, which were obtained from the least absolute shrinkage and selection operator (LASSO) algorithm and validated using the GSE27020 dataset.</p><p><strong>Results: </strong>Eighteen immune-co-stimulatory molecules were identified, allowing classification of the samples into three subtypes, among which subtype 2 exhibited the most favorable prognosis. Eight immune cell types were found to be associated with the subtypes, and ten immune checkpoint genes showed differential expression across them. Six optimized co-stimulatory molecules were selected to construct the RS model, which was capable of predicting LC prognosis with an area under the curve (AUC) value of 0.870 for 1-year survival in the TCGA dataset. Validation using GSE27020 yielded an AUC of 0.736.</p><p><strong>Conclusions: </strong>An RS model incorporating six optimized co-stimulatory molecules was constructed and validated, demonstrating strong predictive power for the prognosis of patients with LC.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 8","pages":"4691-4702"},"PeriodicalIF":1.7,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12432682/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145065505","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":"Advancing <i>RET</i>-targeted therapy in thyroid cancer: insights and implications from the LIBRETTO-001 study.","authors":"Han-Sang Baek, Dong-Jun Lim","doi":"10.21037/tcr-2025-370","DOIUrl":"10.21037/tcr-2025-370","url":null,"abstract":"","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 8","pages":"4486-4490"},"PeriodicalIF":1.7,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12432614/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145065516","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":"Acute radiation-induced brain injury in patients with glioma and the construction of a clinical prediction model: a cohort study.","authors":"Liang Liang, Qiangfeng Pi, Shuo Jiang, Jie Zhou, Lauren Singer, Li Cao","doi":"10.21037/tcr-2025-800","DOIUrl":"10.21037/tcr-2025-800","url":null,"abstract":"<p><strong>Background: </strong>Glioma, which has a high degree of malignancy and mortality, is mainly treated by radiotherapy. Acute radiation-induced brain injury is one of the common complications of radiotherapy and can lead to brain herniation. Identifying risk of acute radiation-induced brain injury can facilitate the improvement of diagnostic and treatment strategies to ultimately improve patient outcomes. The purpose this study was to construct and validate a prediction model for acute radiation-induced brain injury in patients with glioma.</p><p><strong>Methods: </strong>The data from 420 patients with glioma admitted to the Nanxishan Hospital of Guangxi Zhuang Autonomous Region from January 2020 to December 2024 were retrospectively collected as the training set, while the data from 180 patients with glioma treated at the 940th Hospital of Joint Logistics Support Force of PLA during the same period were collected as the validation set. The differences in the clinical characteristics of patients with acute brain injury (n=112) and non-brain injury (n=308) in the training set were analyzed, as were the risk factors of acute radiation-induced brain injury. According to the relevant risk factors, a prediction model for acute radiation-induced brain injury was constructed and validated in the validation set.</p><p><strong>Results: </strong>Age, diabetes, size of gross tumor volume, radiation dose of gross tumor volume, and concurrent chemotherapy were independent risk factors for acute radiation-induced brain injury in patients with glioma, with the relative risks being 1.060 [95% confidence interval (CI): 1.030-1.091], 3.080 (95% CI: 1.384-6.852), 1.075 (95% CI: 1.049-1.100), 1.241 (95% CI: 1.176-1.310), and 3.951 (95% CI: 1.877-8.317), respectively. The area under the receiver operating characteristic (ROC) curve of the training set was 0.907 (95% CI: 0.875-0.939), and the area under curve of the validation set was 0.913 (95% CI: 0.861-0.965). The Hosmer-Lemeshow goodness-of-fit test was conducted on the model in the validation set, with a Chi-squared value of 5.135 and a P value of 0.743.</p><p><strong>Conclusions: </strong>Patients with glioma have a high incidence of acute radiation-induced brain injury during radiotherapy, which can lead to a poor prognosis. The model we developed demonstrated good efficacy and reliability for identifying risk of acute radiation-induced brain injury.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 8","pages":"5002-5011"},"PeriodicalIF":1.7,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12432773/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145065524","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":"Pulmonary metastasis risk and overall survival score in choriocarcinoma: a novel nomogram-based risk assessment system.","authors":"Wenqiang Li, Qian He, Qian Huang, Zhiping Deng","doi":"10.21037/tcr-2025-206","DOIUrl":"10.21037/tcr-2025-206","url":null,"abstract":"<p><strong>Background: </strong>At present, the risk of developing pulmonary metastasis and prognostic factors for choriocarcinoma (CC) remain unclear. This study aimed to investigate the independent risk factors and prognostic factors for pulmonary metastasis of CC and to construct a prognostic prediction model.</p><p><strong>Methods: </strong>We retrieved data on patients diagnosed with CC between 2010 and 2019 from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate logistic regressions were used to identify independent risk factors for developing pulmonary metastases in CC. Then, univariate and multivariate COX regression analyses were used to identify independent risk factors affecting the prognosis of patients with CC. Finally, we constructed a predictive nomogram and assessed the efficacy of the nomogram by receiver operating characteristic (ROC) curves, calibration curves, and decision analysis curves (DCAs).</p><p><strong>Results: </strong>Independent risk factors for developing pulmonary metastases in CC patients were gender and tissue type. Independent risk factors for the prognosis of CC patients were age, marriage, primary location, liver metastases, lung metastases, and surgical intervention. The results of ROC curves, calibration curves, and DCA in the training and validation groups confirmed that the nomogram could accurately predict the prognosis of CC patients.</p><p><strong>Conclusions: </strong>Patients with CC are more likely to be young, have a more primary male genital system, have a poor prognosis, and are most likely to be complicated by pulmonary metastasis at initial diagnosis. A novel prediction model to predict the prognosis of CC patients has been constructed to personalize and guide clinical decision-making.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 8","pages":"4867-4881"},"PeriodicalIF":1.7,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12432784/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145065578","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":"miR-378a-5p targets FGR to suppress proliferation, invasion and migration in lung adenocarcinoma cells.","authors":"Yali Zhang, Tingting Bian, Runfeng Yang, Qi Zheng, Jianguo Zhang, Yifei Liu, Lihua Gao","doi":"10.21037/tcr-2025-13","DOIUrl":"10.21037/tcr-2025-13","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Lung cancer (LC) remains the leading cause of cancer-related mortality worldwide. Emerging evidence demonstrates that microRNAs (miRNAs) serve as crucial post-transcriptional regulators in lung carcinogenesis. Previous studies have identified aberrant expression of miR-378a-5p in non-small cell lung cancer (NSCLC), although its precise regulatory mechanisms remain to be fully elucidated. This study aimed to investigate the mechanisms by which miR-378a-5p leads to the onset and progression of lung adenocarcinoma (LUAD).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;LUAD's miR-378a-5p expression levels were examined utilizing publicly accessible databases. Quantitative real-time fluorescence polymerase chain reaction (qRT-PCR) was used to measure the expression of miR-378a-5p in LUAD tissues and nearby normal tissues from the Affiliated Hospital of Nantong University. Additionally, A549 and H1299 cells were transfected with miR-378a-5p mimics and inhibitor, and the role of miR-378a-5p in cell proliferation, migration and invasion was evaluated by Cell Counting Kit-8 (CCK-8) assay, colony formation assay, wound healing assay and transwell assay. The downstream target genes of miR-378a-5p were predicted using the microCosm database. Subsequently, the differentially expressed genes between the high and low expression groups of miR-378a-5p were subjected to enrichment analysis. The related pathways were identified, and the corresponding pathway-related genes were retrieved from the MsigDB website. The intersection of these genes was analyzed, leading to the identification of FGR proto-oncogene, Src family tyrosine kinase (FGR) as a potential downstream target gene. The expression level of FGR in LUAD was analyzed using the UALCAN database, and the correlation between FGR expression and various clinicopathological parameters was assessed. Immune infiltration analysis was performed based on the gene expression profiles of LUAD from The Cancer Genome Atlas (TCGA).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;It was discovered that LUAD tissues had downregulated miR-378a-5p. The miR-378a-5p inhibitor facilitated the proliferation, invasion, and migration, but the overexpression of miR-378a-5p turned out to limit these processes in both cell lines. Bioinformatics analysis identified FGR as a gene that miR-378a-5p targeted, with a positive correlation between their expression levels. Individuals with LUAD with low FGR expression had a poor prognosis, based upon research results of an analysis of the TCGA database. Furthermore, multivariate Cox regression analysis demonstrated that FGR was an independent prognostic factor for LUAD. According to the UALCAN database, FGR was revealed to be under expressed in LUAD tissues and to be substantially correlated with T stage. Furthermore, there were notable variations in the quantity of different immune categories of cells between the groups with high and low FGR expression.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;By","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 8","pages":"4920-4938"},"PeriodicalIF":1.7,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12432781/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145065662","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":"An efficient epithelial-mesenchymal transition-related gene signature for predicting the survival of patients with lung adenocarcinoma.","authors":"Pengkai Han, Chittibabu Guda, Qiping Liu","doi":"10.21037/tcr-2025-1455","DOIUrl":"10.21037/tcr-2025-1455","url":null,"abstract":"<p><strong>Background: </strong>Epithelial-mesenchymal transition (EMT) plays an important role in the pathogenesis of lung adenocarcinoma (LUAD). In this study, we aimed to construct a prognostic signature based on EMT that could predict the prognosis of patients with LUAD.</p><p><strong>Methods: </strong>The messenger RNA (mRNA) expression profiles and the clinical data were downloaded from The Cancer Genome Atlas (TCGA) as the training set while data from the Gene Expression Omnibus (GEO) served as the validation set. Differentially expressed EMT-related genes (EMTGs) were identified from the training dataset. Univariate and multivariate Cox regression analyses were employed to develop a gene signature from the EMTGs to predict overall survival (OS) time. The prediction performance of the signature was tested using the time-dependent receiver operating characteristic (ROC) curve. The signature was verified in the TCGA dataset and the external dataset, GSE30219. A corresponding nomogram was also constructed to predict the prognosis of patients with LUAD. The expression of the prognostic genes at the protein level was investigated in the Clinical Proteomic Tumor Analysis Consortium (CPTAC) dataset. Gene set enrichment analysis was conducted to reveal the biological pathways associated with the high-risk group and the low-risk group.</p><p><strong>Results: </strong>A set of 79 differentially expressed EMTGs were identified. An EMT-related signature was constructed which classified patients with LUAD into two subgroups based on the median risk score. In the ROC curve analysis, the prognostic signature had a moderate discrimination accuracy for the 1-, 3-, and 5-year survival rate with areas under the curve (AUCs) of 0.732, 0.675, 0.702 in TCGA training set, respectively and 0.813, 0.672, 0.706 in the GSE30219 validation set, respectively. The established nomogram effectively predicted the OS of patients with LUAD.</p><p><strong>Conclusions: </strong>The novel EMT-related signature established in this study is a robust and independent prognostic indicator for patients with LUAD. This signature is expected to improve the personalized management of patients with LUAD.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 8","pages":"4989-5001"},"PeriodicalIF":1.7,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12432770/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145065474","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 development and validation of predictive model based on novel immune-related gene-based subtypes for the risk assessment of cutaneous melanoma.","authors":"Fei Li, Xinji Li, Tianhui Niu, Xiaoxin Li, Ling Guan, Zhiyong Wang, Bin Liang, Yuanyuan Li, Zhiwei Hao, Chengyu Sui","doi":"10.21037/tcr-2025-954","DOIUrl":"10.21037/tcr-2025-954","url":null,"abstract":"<p><strong>Background: </strong>Cutaneous melanoma (CM) exhibits considerable heterogeneity, and the immune status of patients can serve as a prognostic indicator. The increasing significance of immune-related markers in cancer prognosis provides clinicians with valuable tools for risk stratification and management decisions. The objective of this study was to develop a predictive model for assessing the risk of CM based on novel subtypes delineated according to immune-related genes.</p><p><strong>Methods: </strong>This study included a cohort from The Cancer Genome Atlas (TCGA). Immune-related genes were carefully selected, and a comprehensive analysis was performed to characterize the molecular alterations and clinical implications linked to these genes. From this, an immune-related risk scoring system aimed at predicting the survival outcomes of patients diagnosed with CM was developed.</p><p><strong>Results: </strong>In this study, using an unsupervised consensus clustering algorithm, the study identified two subtypes-Cluster 1 (C1) and Cluster 2 (C2)-within the TCGA melanoma (MEL) cohort based on 1,959 immune-related genes. Survival analysis indicated that C1 was linked to poorer overall survival (OS) as compared to C2. We found significant correlations between these subtypes and clinical variables including tumor-node-metastasis (TNM) classification, new tumor events, and radiation therapy. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that 161 genes upregulated in C1 were associated with tyrosine metabolism, melanogenesis, and the p53 signaling pathway, while downregulated genes in C1 were linked to hematopoietic cell lineage, cytokine-cytokine receptor interactions, and cell adhesion molecules. Immune-related genes in CM were optimized and assessed using univariate Cox regression and a protein-protein interaction (PPI) network, with 20 genes being identified, including <i>CXCL10</i>, <i>CCL5</i>, <i>CXCR4</i>, <i>CXCR3</i>, <i>IL10</i>, <i>CCR5</i>, <i>CCR7</i>, <i>STAT1</i>, <i>TNF</i>, <i>CD4</i>, <i>CD8A</i>, <i>ITGB2</i>, <i>FCGR3A</i>, <i>ITGAM</i>, <i>PTPRC</i>, <i>CD19</i>, <i>LCK</i>, <i>B2M</i>, <i>TYROBP</i>, and IFNG. From these, four key prognostic markers (CXCL10, IL10, B2M, and IFNG) were selected via a least absolute shrinkage and selection operator (LASSO) regression penalty approach and multivariate Cox analyses. For the prediction of the 1-, 3-, and 5-year survival rates, the immune-related risk score yielded area under the curve (AUC) values of 0.671, 0.667, and 0.676, respectively.</p><p><strong>Conclusions: </strong>CM was divided into two subtypes based on immune gene expression, with the C1 subtype associated with poor prognosis. A prognostic risk model was developed using these classifications to predict patient outcomes.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 8","pages":"5155-5165"},"PeriodicalIF":1.7,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12432783/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145065515","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":"Balancing evidence and individualization in adjuvant CDK4/6 therapy.","authors":"Humaid O Al-Shamsi, Muharrem Oner, Kefah Mokbel","doi":"10.21037/tcr-2025-879","DOIUrl":"10.21037/tcr-2025-879","url":null,"abstract":"","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 8","pages":"4479-4481"},"PeriodicalIF":1.7,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12432663/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145065569","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}