SERPING1, a biomarker for colorectal liver metastasis, promotes colorectal cancer cell proliferation, migration, and invasion DOI
Wenhao Yu,

Boyuan Gu,

Zhiwei Huang

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 24, 2024

Abstract Colorectal liver metastasis (CRLM) is a major cause of mortality in colorectal cancer (CRC) patients, but its precise etiology remains unclear. Identifying genes associated with CRLM and understanding their molecular mechanisms crucial. Here, we identified SERPING1 as hub gene causing by WGCNA, differentially expressed analysis K-M survival analysis. In addition, confirmed the high expression using human samples. Furthermore, our vitro experiments showed that promotes proliferation, migration invasion cells activates EMT pathway cells. Finally, to explore role tumour microenvironment, performed single-cell sequencing found was enriched cancer-associated fibroblasts (CAFs) immune infiltration CAFs. Collectively, these studies promising target for control CRLM.

Language: Английский

Reinventing gene expression connectivity through regulatory and spatial structural empowerment via principal node aggregation graph neural network DOI Creative Commons

Fengyao Yan,

Limin Jiang, Dan‐Qian Chen

et al.

Nucleic Acids Research, Journal Year: 2024, Volume and Issue: 52(13), P. e60 - e60

Published: June 17, 2024

Abstract The intricacies of the human genome, manifested as a complex network genes, transcend conventional representations in text or numerical matrices. intricate gene-to-gene relationships inherent this complexity find more suitable depiction graph structures. In pursuit predicting gene expression, an endeavor shared by predecessors like L1000 and Enformer methods, we introduce novel spatial graph-neural (GNN) approach. This innovative strategy incorporates features, encompassing both regulatory structural elements. elements include pair-wise correlation, biological pathways, protein–protein interaction networks, transcription factor regulation. chromosomal distance, histone modification Hi-C inferred 3D genomic features. Principal Node Aggregation models, validated independently, emerge frontrunners, demonstrating superior performance compared to traditional regression other deep learning models. By embracing GNN paradigm, our method significantly advances description interactions, surpassing performance, predictable scope, initial requirements set previous methods.

Language: Английский

Citations

0
Co-expression and Data Fusion Analysis of Omics Data for Liver Related Metabolic Diseases DOI

P. Shobha,

N. Nalini

SN Computer Science, Journal Year: 2024, Volume and Issue: 5(6)

Published: June 25, 2024

Language: Английский

Citations

0
Deciphering the prognostic role of endoplasmic reticulum stress in lung adenocarcinoma: integrating prognostic prediction and immunotherapy strategies DOI Creative Commons
Bing Wen, Pengpeng Zhang,

Jiping Xie

et al.

Clinical and Experimental Medicine, Journal Year: 2024, Volume and Issue: 24(1)

Published: July 25, 2024

Endoplasmic reticulum stress (ERS) is a critical factor influencing lung adenocarcinoma (LUAD) progression and patient outcomes. In this study, we analyzed gene expression data from LUAD samples sourced The Cancer Genomic Atlas Gene Expression Omnibus databases. Utilizing advanced statistical methods including LASSO Cox regression, developed ERS-associated signature (ERAS) based on ten ERS-related genes. This model stratified patients into high- low-risk groups, with the high-risk group exhibiting decreased survival rates, elevated tumor mutational burden, heightened chemotherapy sensitivity. Additionally, observed lower immune ESTIMATE scores in high-ERAS group, indicating potentially compromised response. Experimental validation through quantitative real-time polymerase chain reaction confirmed utility of our model. Furthermore, constructed nomogram to predict 1-, 3-, 5-year providing clinicians valuable tool for personalized management. conclusion, study demonstrates efficacy ERAS identifying patients, offering promising implications improved prognostication treatment strategies.

Language: Английский

Citations

0
Tumor Heterogeneity in Gastrointestinal Cancer Based on Multimodal Data Analysis DOI Open Access
Dongmei Ai, Yang Du,

Hongyu Duan

et al.

Genes, Journal Year: 2024, Volume and Issue: 15(9), P. 1207 - 1207

Published: Sept. 13, 2024

Gastrointestinal cancer cells display both morphology and physiology diversity, thus posing a significant challenge for precise representation by single data model. We conducted an in-depth study of gastrointestinal heterogeneity integrating analyzing from multiple modalities.

Language: Английский

Citations

0
SERPING1, a biomarker for colorectal liver metastasis, promotes colorectal cancer cell proliferation, migration, and invasion DOI
Wenhao Yu,

Boyuan Gu,

Zhiwei Huang

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 24, 2024

Abstract Colorectal liver metastasis (CRLM) is a major cause of mortality in colorectal cancer (CRC) patients, but its precise etiology remains unclear. Identifying genes associated with CRLM and understanding their molecular mechanisms crucial. Here, we identified SERPING1 as hub gene causing by WGCNA, differentially expressed analysis K-M survival analysis. In addition, confirmed the high expression using human samples. Furthermore, our vitro experiments showed that promotes proliferation, migration invasion cells activates EMT pathway cells. Finally, to explore role tumour microenvironment, performed single-cell sequencing found was enriched cancer-associated fibroblasts (CAFs) immune infiltration CAFs. Collectively, these studies promising target for control CRLM.

Language: Английский

Citations

0