Machine learning-based integration develops a disulfidptosis-related lncRNA signature for improving outcomes in gastric cancer DOI Creative Commons
Tianze Zhang, Yuqing Chen, Zhiping Xiang

et al.

Artificial Cells Nanomedicine and Biotechnology, Journal Year: 2024, Volume and Issue: 53(1), P. 1 - 13

Published: Dec. 19, 2024

Gastric cancer remains one of the deadliest cancers globally due to delayed detection and limited treatment options, underscoring critical need for innovative prognostic methods. Disulfidptosis, a recently discovered programmed cell death triggered by disulphide stress, presents fresh avenue therapeutic exploration. This research examines disulfidptosis-related long noncoding RNAs (DRLs) in gastric cancer, with goal leveraging these lncRNAs as potential markers enhance patient outcomes approaches. Comprehensive genomic clinical data from stomach adenocarcinoma (STAD) were obtained The Cancer Genome Atlas (TCGA). Employing least absolute shrinkage selection operator (LASSO) regression analysis, model was devised incorporating five key DRLs forecast survival rates. effectiveness this validated using Kaplan-Meier plots, receiver operating characteristic (ROC) curves, extensive functional enrichment studies. importance select expression variability genes tied disulfidptosis via quantitative real-time PCR (qRT-PCR) Western blot tests, establishing solid foundation their utility. Analyses tumour mutation burden highlighted biological DRLs, connecting them pathways immune responses. These discoveries broaden our comprehension molecular framework bolster development tailored plans, highlighting substantial role prognosis intervention.

Language: Английский

Development of a novel risk signature revealing prognostic and tumor microenvironmental features in breast cancer DOI Creative Commons
Yong Shen,

Binbin Jiang,

Yingbo Luo

et al.

Medicine, Journal Year: 2025, Volume and Issue: 104(5), P. e41369 - e41369

Published: Jan. 31, 2025

This study aimed to devise a breast cancer (BC) risk signature for based on pyrimidine metabolism-related genes (PMRGs) evaluate its prognostic value and association with drug sensitivity. Transcriptomic clinical data were retrieved from The Cancer Genome Atlas database Gene Expression Omnibus repository. Pyrimidine metabolism-associated identified the Molecular Signatures Database collection. A was constructed through Cox regression Lasso methods. Further, relationship between PMRG-derived feature clinicopathological characteristics, gene expression patterns, somatic mutations, susceptibility, tumor immune microenvironment thoroughly investigated, culminating in development of nomogram. PMRGs displayed differential diverse mutations BC. Univariate analysis 36 significantly associated BC prognosis, leading categorization 2 molecular subtypes discernible differences prognosis. Using regression, composed 16 established, wherein high-risk scores indicative poor also related chemotherapy regimens showed significant correlations sensitivity multiple drugs. Furthermore, distinct properties, profiles, mutation patterns evident across varying scores. Ultimately, nomogram incorporating PMRGs-based alongside stage, status, demonstrating excellent performance prognosis prediction. We successfully developed PMRG-based that effectively combines attributes accurate assessment

Language: Английский

Citations

0
Comprehensive analysis of CLEC family genes in gastric cancer prognosis immune response and treatment DOI Creative Commons
Weijian Zhu,

Qiang Yi,

Jiaqi Wang

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Feb. 18, 2025

Language: Английский

Citations

0
A novel telomere-associated genes signature for the prediction of prognosis and treatment responsiveness of hepatocellular carcinoma DOI Creative Commons

Kuo Kang,

Hui Nie, Weilu Kuang

et al.

Biological Procedures Online, Journal Year: 2025, Volume and Issue: 27(1)

Published: Feb. 27, 2025

Hepatocellular carcinoma (HCC) is a prevalent malignancy worldwide, characterized by its high and poor prognosis. Telomeres, crucial components of eukaryotic chromosomes, have been increasingly recognized for their involvement in tumorigenesis, development, impact on the prognosis cancer patients. However, precise role telomere-associated genes HCC remains incompletely elucidated. The Cancer Genome Atlas (TCGA) database was utilized to download data from 374 50 normal liver tissue samples. Differential were screened intersected with 2093 telomere-related (TRGs) GeneCards, resulting identification 704 TRGs exhibiting survival differences. Through univariate Cox regression analysis, multivariate LASSO regression, prognostic model consisting 18 risk assessment developed. single-cell spatial transcriptomics analyze expression distribution HCC. Subsequently, Mendelian randomization (MR) analysis confirmed causal relationship between ASF1A alcoholic among identified TRGs. functional significance cell lines investigated through colony formation assays, Transwell migration wound healing experiments. We developed incorporating Kaplan–Meier demonstrated that overall (OS) rate high-risk group significantly inferior low-risk group. age (HR = 1.017, 95% CI: 1.002–1.032, P 0.03), stage 1.389, 1.111–1.737, 0.004), score 5.097, 3.273–7.936, < 0.001) as three independent factors five-year receiver operating characteristic curve (ROC) further validated accuracy our model. Time-dependent ROC results revealed 1-year, 3-year, 5-year AUC values 0.801, 0.734, 0.690, respectively. data. Additionally, immune subtype indicated lower proportion C3 C4 subtypes TRG compared Meanwhile, tumor dysfunction exclusion (TIDE) higher than Furthermore, we observed differences IC50 nine chemotherapeutic drugs across different which partially model's predictive efficacy immunotherapy. Amongst these eighteen analyzed MR found be associated pathogenesis. significant overexpression Western blotting. also explored it's carcinogenic via transwell, healing, clone In this study, novel comprising HCC, exhibited remarkable predicting patients' successfully established first time, provided new theoretical foundation management

Language: Английский

Citations

0
Integrated analysis of single-cell and bulk RNA-sequencing to predict prognosis and therapeutic response for colorectal cancer DOI Creative Commons

Liyang Cai,

Xin Guo, Yucheng Zhang

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 7, 2025

Colorectal cancer (CRC) is a prevalent malignant tumor characterized by high global incidence and mortality rates. Furthermore, it imperative to comprehend the molecular mechanisms underlying its development identify effective prognostic markers. These efforts are crucial for pinpointing potential therapeutic targets enhancing patient survival Therefore, we develop novel model aimed at providing new theoretical support clinical prognosis evaluation treatment. We downloaded data from Gene Expression Omnibus (GEO) The Cancer Genome Atlas (TCGA) databases. Subsequently, performed single-cell analysis developed associated with colorectal cancer. divided scRNA-seq dataset (GSE221575) into 19 cell clusters classified these 11 distinct types using marker genes. Using univariate Cox regression LASSO (Least Absolute Shrinkage Selection Operator) analyses, consisting of 9 Based on our 9-gene model, patients high-risk low-risk groups median risk score. group demonstrated significant positive correlations M0 macrophages, CD8+ T cells, M2 macrophages. enrichment analyses indicate immune-related pathways in group, including HEDGEHOG_SIGNALING, Wnt signaling pathway, adhesion molecules. Drug sensitivity revealed that was sensitive 5 chemotherapeutic drugs, while only 1. Additionally, highly reliable nomogram application. This suggests score derived modeling stratifying samples. study comprehensively applied bioinformatics methods construct model. showed good predictive performance, offering guidance individualized treatment patients. may provide valuable insights disease's pathogenesis further research.

Language: Английский

Citations

0
Disulfidptosis related immune genes drive prognostic model development and tumor microenvironment characterization in bladder urothelial carcinoma DOI Creative Commons

Shenchao Guo,

Guangjia Lv,

Hengyue Zhu

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 8, 2025

The intricate nature and varied forms of bladder urothelial carcinoma (BLCA) highlight the need for new indicators to define tumor prognosis. Disulfidptosis, a novel form cell death, is closely linked BLCA progression, prognosis, treatment outcomes. Our current goal develop disulfidptosis-related immune prognostic model enhance strategies. Utilizing RNA-seq data from Cancer Genome Atlas (TCGA) , which included 419 patients (19 normal, 400 tumor), we performed weighted gene co-expression network analysis (WGCNA) identify disulfidptosis-associated genes. Through multivariate Cox regression, least absolute shrinkage selection operator (LASSO) regularization, established risk scoring system. A nomogram combining score clinical features predicted Model performance was validated through survival curve independent validation cohort. Immune checkpoints, infiltration, mutation load were assessed. Differential enrichment conducted. Prognostic genes via in vitro experiments. Eight related disulfidptosis identified verified outperformed previous ones predicting overall (OS) high- low-risk groups. Patients with scores had higher OS rates burden (TMB) compared high-risk patients. CD4 memory T cells, CD8 M1 macrophages, resting NK cells found be group. checkpoint inhibitor (ICI) may more effective High-risk group exhibited stronger correlation cancer malignant pathways. Knocking out necrosis factor receptor superfamily member 12 (TNFRSF12A) inhibits proliferation invasion while overexpressing it has opposite effect. We constructed that combines genes, demonstrating good prediction performance. discovered TNFRSF12A an oncogene BLCA, help provide personalized guidance individualized immunotherapy certain extent.

Language: Английский

Citations

0
Machine learning-based identification of telomere-related gene signatures for prognosis and immunotherapy response in hepatocellular carcinoma DOI Creative Commons

Zhengmei Lu,

Xiaowei Chai,

Shibo Li

et al.

Molecular Cytogenetics, Journal Year: 2025, Volume and Issue: 18(1)

Published: March 18, 2025

Telomere in cancers shows a main impact on maintaining chromosomal stability and unlimited proliferative capacity of tumor cells to promote cancer development progression. So, we targeted detect telomere-related genes(TRGs) hepatocellular carcinoma (HCC) develop novel predictive maker response immunotherapy. We sourced clinical data gene expression datasets HCC patients from databases including TCGA GEO database. The TelNet database was utilized identify genes associated with telomeres. Genes altered GSE14520 were intersected TRGs, Cox regression analysis conducted pinpoint strongly linked survival prognosis. risk model developed using the Least Absolute Shrinkage Selection Operator (LASSO) technique. Subsequently, evaluation focused immune cell infiltration, checkpoint genes, drug responsiveness, immunotherapy outcomes across both high- low-risk patient groups. obtained 25 TRGs overlapping set 34 analysis. Finally, six (CDC20, TRIP13, EZH2, AKR1B10, ESR1, DNAJC6) identified formulate score (RS) model, which independently predicted prognosis for HCC. high-risk group demonstrated worse showed elevated levels infiltration by Macrophages M0 Tregs. Furthermore, notable correlation observed between genes. RS derived has been validated its value outcomes. In conclusion, this not only but also their responses, providing innovative strategies therapy.

Language: Английский

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Identification of key genes related to cancer associated fibroblasts in neuroblastoma: A comprehensive bioinformatics approach DOI

Zhao Qianyun,

Jianjun Wang,

Fan Kaisi

et al.

Cancer Biomarkers, Journal Year: 2025, Volume and Issue: 42(2)

Published: Feb. 1, 2025

Background Neuroblastoma (NB) is one of the most common and aggressive pediatric solid tumors, characterized by a highly complex pathogenesis. Within tumor microenvironment (TME), cancer-associated fibroblasts (CAFs) constitute major cell population play pivotal role in facilitating communication among various stromal cells. However, specific functions contributions CAFs NB remain incompletely understood. Objective To investigate impact CAFs-related genes on prognosis NB, we developed risk model to facilitate diagnosis prognostication patients. Methods In this study, gene prognostic for was established using single-cell analysis genomic sequencing data. The effectiveness subsequently evaluated through development nomogram, immune infiltration analysis, drug prediction, set enrichment analysis. Ultimately, expression levels identified key were experimentally validated tissues. Results A novel related transcriptome dataset high-risk group worse than that low-risk group. validity confirmed sensitivity methods. Finally, high STEAP2 tissues verified experiments. Conclusions study introduces new predictive uses CAF markers forecast NB. plays identifying neuroblastoma may become potential therapeutic target

Language: Английский

Citations

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Development and evaluation of an ovarian cancer prognostic model based on adaptive immune-related genes DOI Creative Commons

H. Shi,

Lijuan Li,

Linying Zhou

et al.

Medicine, Journal Year: 2025, Volume and Issue: 104(14), P. e42030 - e42030

Published: April 4, 2025

The adaptive immune system plays a vital role in cancer prevention and control. However, research investigating the predictive value of immune-related genes (AIRGs) ovarian (OC) prognosis is limited. This study aims to explore functional roles AIRGs OC. Transcriptomic, clinical-pathological, prognostic data for OC were downloaded from public databases. Differential expression analysis, univariate, Lasso Cox regression analyses utilized construct risk signature. Kaplan–Meier survival enrichment somatic mutation infiltration drug sensitivity analysis performed characterize differences between high-risk low-risk groups. Independent factors identified through multivariate nomogram. Expression signature-related was validated using cells tissues. A total 109 significantly associated with overall (OS) identified, which 15 selected signature: AP1S2, AP2A1, ASB2, BTLA, BTN3A3, CALM1, CD3G, CD79A, EVL, FBXO4, FBXO9, HLA-DOB, LILRA2, MALT1, PIK3CD. signature stratified cohort into groups, exhibited significant prognosis, gene expression, profiles, immunotherapy response, sensitivity. Specifically, group showed better higher tumor mutational burden, greater response immunotherapy, increased M1 macrophage T follicular helper (Tfh) cell infiltration, cisplatin gemcitabine. nomogram, integrating AIRG-derived age clinical stage, demonstrated superior performance predicting compared other factors. Moreover, differential further confirmed tissue as normal or Our findings highlight association model developed demonstrates strong capabilities.

Language: Английский

Citations

0
Identification of a NEK7-related pyroptosis gene signature against pancreatic cancer and evaluation of its potential in tumor microenvironment remodeling via regulating inflammasome complex DOI Creative Commons
Jia‐Ren Liu, Zilong Yan,

Tongning Zhong

et al.

Functional & Integrative Genomics, Journal Year: 2025, Volume and Issue: 25(1)

Published: April 21, 2025

The treatment options for pancreatic ductal adenocarcinoma (PDAC) remain limited. It is therefore important to explore new therapeutic targets and strategies better prognosis patients with PDAC. NIMA-related kinase 7 (NEK7) a serine/threonine involved in PDAC development. Moreover, NEK7 was reported regulate NLRP3 inflammasome cell pyroptosis. To evaluate the role of PDAC, we performed RNA sequencing analysis cells, series bioinformatics analyses were employed determine biological function We identified NEK7-Specific Pyroptosis Gene Set (NEK7-SPGS) by high-throughput transcriptome combining Enrichment Analysis (GSEA). reveal that NEK7-SPGS highly associated T helper infiltration inflammatory response proposed might have potential tumor microenvironment remodeling via cells induced response. Using dataset from TCGA database, established NEK7-SPGS-related prognostic signature Subsequently, sensitivity estimation chemotherapeutic drugs revealed chemotherapy agents according signature, including gemcitabine paclitaxel, been used as conventional therapy. Meanwhile, showed expression SCAMP1, which member NEK7-SPGS, progression vivo vitro. NEK7-specific pyroptosis gene evaluated its microenvironment. could act biomarker serve guidance clinical application.

Language: Английский

Citations

0
Mechanisms of HRAS regulation of liver hepatocellular carcinoma for prognosis prediction DOI Creative Commons

Xingbao Fang,

Yan Cai, Zixiao Zhao

et al.

BMC Cancer, Journal Year: 2025, Volume and Issue: 25(1)

Published: April 28, 2025

Liver hepatocellular carcinoma (LIHC) often has a poor prognosis. Since the relationship between HRas proto-oncogene, GTPase (HRAS) and LIHC not been elucidated, aim of this study was to explore mechanisms by which HRAS is involved in regulating prognosis LIHC. We usedThe Cancer Genome Atlas (TCGA) database characterize differences gene expression patients healthy individuals. In addition, we analysed relationships levels clinicopathological characteristics patients. Next, used univariate multivariate Cox regression analyses identify prognostic factors. Differentially expressed genes were identified low- high-expression groups, KEGG GO GSEA performed underlying mechanisms. The effects high low on determined according CIBERSORT. subsequently assayed at cellular level, these data validated tumour xenograft model. established as signature features. Patients categorized into groups. that associated with carbon metabolism, PPAR signalling pathway, small molecule catabolism cancer. Furthermore, conclude results from elevated immune cell infiltration. LASSO + KNN build an AI classification model shows good performance distinguishing liver cancer tissues form normal tissues. Finally, verified highly cells promotes growth. role assess can be applied predict survival, for personalized treatment strategies, provide information development potential targeted therapies new ideas patient treatment.

Language: Английский

Citations

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