Machine learning in oncological pharmacogenomics: advancing personalized chemotherapy DOI
Çıgır Biray Avci, Bakiye Göker Bağca,

Behrouz Shademan

и другие.

Functional & Integrative Genomics, Год журнала: 2024, Номер 24(5)

Опубликована: Окт. 1, 2024

Язык: Английский

CD4+ T cells in antitumor immunity DOI Creative Commons
Elena Montauti, David Y. Oh, Lawrence Fong

и другие.

Trends in cancer, Год журнала: 2024, Номер unknown

Опубликована: Сен. 1, 2024

Язык: Английский

Процитировано

11

Artificial intelligence in gastrointestinal cancers: diagnostic, prognostic, and surgical strategies DOI
Ganji Purnachandra Nagaraju,

T A Sandhya,

Mundla Srilatha

и другие.

Cancer Letters, Год журнала: 2025, Номер 612, С. 217461 - 217461

Опубликована: Янв. 12, 2025

Язык: Английский

Процитировано

1

Pan-gastrointestinal adenocarcinoma analysis uncovers the prognostic and immune correlates of ferroptosis-related genes DOI Open Access

Xiaochuan Dong,

Yanyan Xie, Wenxi Chen

и другие.

Translational Gastroenterology and Hepatology, Год журнала: 2025, Номер 10, С. 7 - 7

Опубликована: Янв. 1, 2025

Gastrointestinal adenocarcinomas (GIACs) are common malignant tumors with poor prognosis in the world. Ferroptosis, characterized by accumulation of intracellular iron and lipid reactive oxygen species, emerges as a pivotal process tumorigenesis cancer advancement. However, implications ferroptosis-related genes GIAC remain to be elucidated. This study aimed at exploring potential role on treatment GIAC. In our study, comprehensive clinical, transcriptomic, and/or genomic data were acquired from The Cancer Genome Atlas (TCGA), Cell Line Encyclopedia (CCLE), Genomics Drug Sensitivity (GDSC), Gene Expression Omnibus (GEO). We formulated ferroptosis-score within TCGA cohort through gene set variation analysis (GSVA) subsequently validated 4 GEO datasets (GSE84437, GSE17536, GSE103479, GSE19417). sensitivity immunotherapy efficacy analyzed GDSC dataset PRJEB25780 cohort, respectively. was significantly associated favorable overall survival both training [TCGA: P=0.003; hazard ratio (HR), 0.67, 95% confidence interval (95% CI): 0.52-0.87] across four validation cohorts (GSE17536: P=0.03; HR, 0.57, CI: 0.34-0.96; GSE19417: P=0.047; 0.53, 0.28-1.01; GSE84437: P=0.004; 0.68, 0.51-0.90; GSE103479: 0.55, 0.32-0.96). Furthermore, correlated activation DNA damage repair pathway resistance cisplatin. Notably, GIACs low ferroptosis-scores exhibited heightened expression immune checkpoint molecules such programmed death-(ligand) 1 cytotoxic T lymphocyte antigen-4, elevated densities tumor-infiltrating CD8+ cells, response pembrolizumab monotherapy. Our findings delineated clinical relevance demonstrated utility predicting effectiveness.

Язык: Английский

Процитировано

0

Uridine-cytidine kinase 2 is correlated with immune, DNA damage repair and promotion of cancer stemness in pan-cancer DOI Creative Commons
Jinlong Tian, Yanlei Li,

Tong Yu

и другие.

Frontiers in Oncology, Год журнала: 2025, Номер 15

Опубликована: Янв. 27, 2025

Background UCK2 (Uridine-Cytidine Kinase 2) is a promising prognostic marker for malignant tumors, but its association with immune infiltration and cancer stemness in pan-cancer remains to be fully understood. we find that gene closed related RNA scores (RNAss) DNA (DNAss), which measured the tumor stemness. We also discover an between expression cells by CIBERSORT algorithm, ESTIMATE algorithm ssGSEA especially, T cell, monocytes, mast cells, macrophages. This study aims shed light on role possible mechanism of pan-cancer. Methods used R programming language bulk sequencing data analysis, were obtained from University California, Santa Cruz (UCSC) datasets. UCSC database very useful explore TCGA other genomics datasets, The explored at transcriptome level came database. differential normal samples. Immunohistochemistry (IHC) was utilized validate different types cancers using tissue chips. correlations prognosis, genetic instability, repair, stem cell characteristics, investigated. Furthermore, single-cell acquired Gene Expression Omnibus (GEO) database, relationship cells. GEO famous public supporting freely disseminates microarray data. Finally, analyzed correlation drug sensitivity. Results observed high most remarkably prognosis pan-cancers. found increased associated higher instability. Additionally, positive relationships mismatch repair genes, homologous recombination across types. There significant Moreover, as expected, checkpoint human leucocyte antigen (HLA) negatively UCK2. Similarly, have negative major histocompatibility complex (MHC) genes. noted had sensitivity various anti-cancer drug. Conclusion plays pivotal roles immunity, it exhibits strong checkpoints HLA. highlights potential impact

Язык: Английский

Процитировано

0

MAGEA6 Engages a YY1‐Dependent Transcription to Dictate Perineural Invasion in Colorectal Cancer DOI Creative Commons
Hao Wang,

Kexin He,

Ruixue Huo

и другие.

Advanced Science, Год журнала: 2025, Номер unknown

Опубликована: Март 27, 2025

Abstract Perineural invasion (PNI), characterized by tumor cells surrounding and invading nerves, is associated with poor prognosis in colorectal cancer (CRC). Understanding the mechanisms of PNI crucial for developing targeted therapies to impede progression. In this study, clinical information transcriptome data are obtained from TCGA database. Stable MAGEA6 knockdown CRC cell lines established investigate impact on malignancy. Immunohistochemical staining used assess significance MAGEA6. Rectal orthotopic sciatic nerve models employed verify role PNI. Schwann (SCs) infiltration recruitment assessed using ssGSEA co‐culture experiments. The results reveal that a key regulator PNI, its expression correlating prognosis. reduces migration, invasion, ability. Moreover, recruit SCs, CXCL1 promoting SCs migration. Mechanistically, inhibits YY1 ubiquitination, stabilizing enhancing SC via YY1‐mediated transcription. These findings suggest enhances invasiveness YY1, which upregulates secretion promotes recruitment. This interaction underscores critical highlights potential therapeutic target CRC.

Язык: Английский

Процитировано

0

Machine learning in oncological pharmacogenomics: advancing personalized chemotherapy DOI
Çıgır Biray Avci, Bakiye Göker Bağca,

Behrouz Shademan

и другие.

Functional & Integrative Genomics, Год журнала: 2024, Номер 24(5)

Опубликована: Окт. 1, 2024

Язык: Английский

Процитировано

0