Identifying tumour microenvironment-related signature that correlates with prognosis and immunotherapy response in breast cancer.

Tumor microenvironment (TME) plays important roles in prognosis and immune evasion. However, the relationship between TME-related genes and clinical prognosis, immune cell infiltration, and immunotherapy response in breast cancer (BRCA) remains unclear. This study described the TME pattern to construct a TME-related prognosis signature, including risk factors PXDNL, LINC02038 and protective factors SLC27A2, KLRB1, IGHV1-12 and IGKV1OR2-108, as an independent prognostic factor for BRCA.

The dynamic dysregulated network identifies stage-specific markers during lung adenocarcinoma malignant progression and metastasis.

Brain metastasis occurs in approximately 30% of patients with lung adenocarcinoma (LUAD) and is closely associated with poor prognosis, recurrence, and death. However, dynamic gene regulation and molecular mechanism driving LUAD progression remain poorly understood. In this study, we performed a comprehensive single-cell transcriptome analysis using data from normal, early stage, advanced stage, and brain metastasis LUAD.

LncTarD 2.0: an updated comprehensive database for experimentally-supported functional lncRNA-target regulations in human diseases.

An updated LncTarD 2.0 database provides a comprehensive resource on key lncRNA-target regulations, their influenced functions and lncRNA-mediated regulatory mechanisms in human diseases. LncTarD 2.

Identifying enhancer-driven subtype-specific prognostic markers in breast cancer based on multi-omics data.

Breast cancer is a cancer of high complexity and heterogeneity, with differences in prognosis and survival among patients of different subtypes. Copy number variations (CNVs) within enhancers are crucial drivers of tumorigenesis by influencing expression of their targets. In this study, we performed an integrative approach to identify CNA-driven enhancers and their effect on expression of target genes in four breast cancer subtypes by integrating expression data, copy number data and H3K27ac data.

Comprehensive characterization of clonality of driver genes revealing their clinical relevance in colorectal cancer.

Background: Genomic studies of colorectal cancer have revealed the complex genomic heterogeneity of the tumor. The acquisition and selection of genomic alterations may be critical to understanding the initiation and progression of this disease.

Methods: In this study, we have systematically characterized the clonal architecture of 97 driver genes in 536 colorectal cancer patients from TCGA.

Functional regulations between genetic alteration-driven genes and drug target genes acting as prognostic biomarkers in breast cancer.

Differences in genetic molecular features including mutation, copy number alterations and DNA methylation, can explain interindividual variability in response to anti-cancer drugs in cancer patients. However, identifying genetic alteration-driven genes and characterizing their functional mechanisms in different cancer types are still major challenges for cancer studies. Here, we systematically identified functional regulations between genetic alteration-driven genes and drug target genes and their potential prognostic roles in breast cancer.