Integrating machine learning and multi-omics analysis to develop an immune-derived multiple programmed cell death signature for predicting clinical outcomes in gastric cancer DOI Creative Commons
Chunhong Li,

Jiahua Hu,

Mengqin Li

et al.

ONCOLOGIE, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 2, 2024

Abstract Objectives Metastasis of tumor cells is the leading reason for mortality among patients diagnosed with gastric cancer (GC). Emerging evidence indicated a strong correlation between programmed cell death (PCD) and invasion metastasis cells. Therefore, we aimed to develop signature assess prognosis therapeutic efficacy in GC patients. Methods Here, collected 1911 PCD-related genes from 19 different PCD patterns, developed an immune-derived multiple index (MPCDI) using integrating machine learning multi-omics analysis, systematically dissected heterogeneity Subsequently, divided into two categories, namely high-MPCDI group low-MPCDI group, median MPCDI as threshold. We performed comprehensive analysis clinical characteristics, somatic mutations, immune infiltration, drug sensitivity, immunotherapeutic groups. Results Survival immunotherapy response analyses that experienced poorer overall survival (p=0.018) were more resistant commonly used chemotherapeutic drugs but benefited compared In addition, was confirmed standalone risk factor survival, nomograms can provide precise tool diagnosis Conclusions Taken together, serve robust diagnostic classifier guide medication administration improve outcomes

Language: Английский

Harnessing ferroptosis for precision oncology: challenges and prospects DOI Creative Commons
Roberto Fernández-Acosta,

Iuliana Vintea,

Ine Koeken

et al.

BMC Biology, Journal Year: 2025, Volume and Issue: 23(1)

Published: Feb. 24, 2025

Language: Английский

Citations

3
Biological characteristics, immune infiltration and drug prediction of PANoptosis related genes and possible regulatory mechanisms in inflammatory bowel disease DOI Creative Commons
Minglin Zhang, Tong Liu, Lijun Luo

et al.

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

Published: Jan. 15, 2025

PANoptosis is one of several modes programmed cell death (PCD) and plays an important role in many inflammatory immune diseases. The bowel disease (IBD) currently unknown. Differentially expressed PANoptosis-related genes (DE-PRGs) were identified, pathway enrichment analyses performed. LASSO regression model construction, a nomogram model, calibration curves, ROC DCA curves used to evaluate the predictive value model. Predicts transcription factors (TFs) small-molecule drugs DE-PRGs analysed. Model immuno-infiltration features IBD include 12 genes: OGT, TLR2, GZMB, TLR4, PPIF, YBX3, CASP5, BCL2L1, CASP6, MEFV, GSDMB BAX. analysis suggested that these related TNF signalling, NF-κB, pyroptosis necroptosis. Machine learning identified three GZMB CASP5. have strong value. Immuno-infiltration revealed infiltration was increased patients with IBD, closely various cells. TFs associated RELA, NFKB1, HIF1A, TP53 SP1. In addition, Connectivity Map (CMap) database top 10 compounds, including buspirone, chloroquine, spectinomycin chlortetracycline. This study indicate good ability for IBD. Moreover, may mediate process through pyroptosis, necroptosis mechanisms. These results present new horizon research treatment

Language: Английский

Citations

1
Machine learning and molecular subtyping reveal the impact of diverse patterns of cell death on the prognosis and treatment of hepatocellular carcinoma DOI

Xinyue Yan,

Meng Wang,

L. Min Ji

et al.

Computational Biology and Chemistry, Journal Year: 2025, Volume and Issue: 115, P. 108360 - 108360

Published: Jan. 27, 2025

Language: Английский

Citations

1
A Machine Learning Computational Framework Develops a Multiple Programmed Cell Death Index for Improving Clinical Outcomes in Bladder Cancer DOI
Chunhong Li,

Wangshang Qin,

Jiahua Hu

et al.

Biochemical Genetics, Journal Year: 2024, Volume and Issue: 62(6), P. 4710 - 4737

Published: Feb. 14, 2024

Language: Английский

Citations

5
Investigating lung cancer microenvironment from cell segmentation of pathological image and its application in prognostic stratification DOI Creative Commons
Xu Zhang,

Zi-Han Zhang,

Yongmin Liu

et al.

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

Published: Jan. 11, 2025

Lung cancer, particularly adenocarcinoma, ranks high in morbidity and mortality rates worldwide, with a relatively low five-year survival rate. To achieve precise prognostic assessment clinical intervention for patients, thereby enhancing their prospects, there is an urgent need more accurate stratification schemes. Currently, the TNM staging system predominantly used practice evaluation, but its accuracy constrained by reliance on physician experience. Although biomarker discovery based molecular pathology offers new perspective assessment, dependence expensive gene panel testing limits widespread application. Pathological images contain abundant diagnostic information, providing avenue evaluation. In this study, we employed advanced Hover-Net technology to accurately quantify abundance of epithelial cells, lymphocytes, macrophages, neutrophils from pathological images, delved into biological significance these cellular abundances. Our research findings reveal that, contrast patients classified as N0 stage, those belonging N1 stage demonstrated marked elevation infiltration neutrophils. Notably, patterns lymphocytes exhibited inverse relationship activation status numerous pivotal pathways, including HALLMARK_HEME_METABOLISM pathway. Furthermore, our analysis distinguished FABP7 biomarker, exhibiting pronounced differential expression between levels neutrophil infiltration, indicate that can provide cost-effective offering strategies management lung adenocarcinoma.

Language: Английский

Citations

0
A gene signature related to programmed cell death to predict immunotherapy response and prognosis in colon adenocarcinoma DOI Creative Commons
Lei Zheng, Lu Jia, Dalu Kong

et al.

PeerJ, Journal Year: 2025, Volume and Issue: 13, P. e18895 - e18895

Published: Feb. 10, 2025

Background Tumor development involves the critical role of programmed cell death (PCD), but correlation between colon adenocarcinoma (COAD) and PCD-related genes is not clear. Methods Subtyping analysis COAD was performed by consensus clustering based on The Cancer Genome Atlas (TCGA), with AC-ICAM queue from cBioportal database as a validation set. Immune infiltration samples evaluated using CIBERSORT Microenvironment Cell Populations (MCP)-counter algorithms. Patients’ immunotherapy response predicted TIDE aneuploidy scores. Pathway enrichment conducted gene set (GSEA). A RiskScore model established independent prognostic filtered Cox regression analysis. mafCompare function used to compare differences in mutation rates somatic genes. Wound healing, transwell assays Flow cytometer were applied measure migration, invasion apoptosis. Results patients grouped into S1 S2 subtypes total 21 PCD associated outcomes COAD. Specifically, subtype mainly related pathway activation tumor deterioration had worse prognosis. six genes, including two protective ( ATOH1 , ZG16 ) four risk HSPA1A SEMA4C CDKN2A ARHGAP4 ). Notably, silencing inhibited activity migration promoted apoptosis cells. Based model, high- low-risk groups. Independent factors, namely, Age, pathologic_M, pathologic_stage, RiskScore, integrated develop nomogram strong good prediction performance. High-risk group high-expressed immune checkpoint higher scores, showing escape ability less active response. Compared group, TP53 exhibited rate high-risk group. Conclusion We constructed for assessment COAD, providing valuable insight exploration new targets improvement

Language: Английский

Citations

0
Ferroptosis and noncoding RNAs: exploring mechanisms in lung cancer treatment DOI Creative Commons

Nadi Rostami Ravari,

Farzad Sadri,

Mohammad Ali Mahdiabadi

et al.

Frontiers in Cell and Developmental Biology, Journal Year: 2025, Volume and Issue: 13

Published: Feb. 26, 2025

Lung cancer (LC) is a highly prevalent and deadly type of characterized by intricate molecular pathways that drive tumor development, metastasis, resistance to conventional treatments. Recently, ferroptosis, controlled mechanism cell death instigated iron-dependent lipid peroxidation, has gained attention for its role in LC progression treatment. Noncoding RNAs (ncRNAs), such as microRNAs (miRNAs) long noncoding (lncRNAs), are emerging key modulators significantly influencing biology. This review explores how ncRNAs control ferroptotic affect growth, therapy LC. By understanding the dual functions both activating inhibiting we aim uncover new therapeutic targets strategies These insights provide promising direction development ncRNA-based treatments designed induce potentially improving outcomes patients with

Language: Английский

Citations

0
Development of an alkaliptosis-related lncRNA risk model and immunotherapy target analysis in lung adenocarcinoma DOI Creative Commons
Xiang Xiong, Wenzhao Liu, Chun‐Hsu Yao

et al.

Frontiers in Genetics, Journal Year: 2025, Volume and Issue: 16

Published: April 8, 2025

Lung cancer has the highest mortality rate among all cancers worldwide. Alkaliptosis is characterized by a pH-dependent form of regulated cell death. In this study, we constructed model related to alkaliptosis-associated long non-coding RNAs (lncRNAs) and developed prognosis-related framework, followed identification potential therapeutic drugs. The TCGA database was utilized obtain RNA-seq-based transcriptome profiling data, clinical information, mutation data. We conducted multivariate Cox regression analysis identify alkaliptosis-related lncRNAs. Subsequently, employed training group construct prognostic testing validate model's accuracy. Calibration curves were generated illustrate discrepancies between predicted observed outcomes. Principal Component Analysis (PCA) performed investigate distribution LUAD patients across high- low-risk groups. Additionally, Gene Ontology (GO) Set Enrichment (GSEA) conducted. Immune infiltration Tumor Mutational Burden (TMB) analyses carried out using CIBERSORT maftools algorithms. Finally, "oncoPredict" package predict immunotherapy sensitivity further forecast anti-tumor immune qPCR used for experimental verification. identified 155 lncRNAs determined that 5 these serve as independent factors. progression-free survival (PFS) overall (OS) rates significantly higher than those high-risk group. risk signature functions factor other variables. Different stages (I-II III-IV) effectively lung adenocarcinoma (LUAD) patients, can reliably signatures. GSEA revealed processes chromosome segregation response activation enriched in both exhibited lower fraction plasma cells proportion activated CD4 memory T cells. OS low TMB compared high Furthermore, drug greater These may biomarkers treating patients. summary, construction an lncRNA provides new insights into diagnosis treatment advanced

Language: Английский

Citations

0
Development of a machine learning-derived programmed cell death index for prognostic prediction and immune insights in colorectal cancer DOI Creative Commons
Jinping Li, Yan Jiang,

S H Nong

et al.

Discover Oncology, Journal Year: 2025, Volume and Issue: 16(1)

Published: April 24, 2025

Language: Английский

Citations

0
ZACN Associated with Poor Prognosis Promotes Proliferation of Kidney Renal Clear Cell Carcinoma Cells by Inhibiting JTC801-Induced Alkaliptosis DOI
Yifan Li, Can Li

Applied Biochemistry and Biotechnology, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 12, 2025

Language: Английский

Citations

0