ArticleBMC cancer2022
An integrative transcriptome analysis reveals potential predictive, prognostic biomarkers and therapeutic targets in colorectal cancer.
Article in BMC cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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23 citing papers in PubMed, 35 citations in OpenAlex.
- Integrated Bioinformatics Identification and Multi-Dimensional Characterization of Diagnostic Hub Genes in Colorectal Cancer.Current issues in molecular biology · 2026Article
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- Extending differential gene expression testing to handle genome aneuploidy in cancer.PLoS computational biology · 2026Article
- Multimodal deep learning for survival prediction and biomarker discovery in non-small cell lung cancer.BioData mining · 2026Article
- Integrated transcriptomic profiling reveals immune and molecular stage-specific signatures of colorectal cancer in hispanics living in Puerto Rico.Frontiers in immunology · 2026Article
- Identification of differentially expressed genes and associated immune cell types in South African gallbladder cancer patients.Scientific reports · 2025Article
- MUC1-Driven Guanylin Gene Delivery via Succinylated PEI-9 Nanocarrier for Colorectal Cancer Treatment: An in Silico and In vitro Study.Advanced pharmaceutical bulletin · 2025Article
- Machine learning-driven multi-targeted drug discovery in colon cancer using biomarker signatures.NPJ precision oncology · 2025Article
- Screening and validation of long non-coding RNAs associated with colorectal cancer based on random forest and LASSO regression algorithm.Discover oncology · 2025Article
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- Artificial Intelligence and Its Revolutionary Role in Physical and Mental Rehabilitation: A Review of Recent Advancements.BioMed research international · 2024Review
- A pan-cancer analysis indicates long noncoding RNA HAND2-AS1 as a potential prognostic, immunomodulatory and therapeutic biomarker in various cancers including colorectal adenocarcinoma.Cancer cell international · 2023Article
- Using machine learning approach for screening metastatic biomarkers in colorectal cancer and predictive modeling with experimental validation.Scientific reports · 2023Article
- Identification of GUCA2A and COL3A1 as prognostic biomarkers in colorectal cancer by integrating analysis of RNA-Seq data and qRT-PCR validation.Scientific reports · 2023Article
- A novel prognostic model based on immunogenic cell death-related genes for improved risk stratification in hepatocellular carcinoma patients.Journal of cancer research and clinical oncology · 2023Article
- MicroRNA-nanoparticles against cancer: Opportunities and challenges for personalized medicine.Molecular therapy. Nucleic acids · 2023Review
- A Systems Biology Approach to Identify Novel Biomarkers in Progression from Crohn's Disease to Colorectal Cancer.Asian Pacific journal of cancer prevention : APJCP · 2023Article
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundA deep understanding of potential molecular biomarkers and therapeutic targets related to the progression of colorectal cancer (CRC) from early stages to metastasis remain mostly undone. Moreover, the regulation and crosstalk among different cancer-driving molecules including messenger RNAs (mRNAs), long non-coding RNAs (lncRNAs) and micro-RNAs (miRNAs) in the transition from stage I to stage IV remain to be clarified, which is the aim of this study.
methodsWe carried out two separate differential expression analyses for two different sets of samples (stage-specific samples and tumor/normal samples). Then, by the means of robust dataset analysis we identified distinct lists of differently expressed genes (DEGs) for Robust Rank Aggregation (RRA) and weighted gene co-expression network analysis (WGCNA). Then, comprehensive computational systems biology analyses including mRNA-miRNA-lncRNA regulatory network, survival analysis and machine learning algorithms were also employed to achieve the aim of this study. Finally, we used clinical samples to carry out validation of a potential and novel target in CRC.
resultsWe have identified the most significant stage-specific DEGs by combining distinct results from RRA and WGCNA. After finding stage-specific DEGs, a total number of 37 DEGs were identified to be conserved across all stages of CRC (conserved DEGs). We also found DE-miRNAs and DE-lncRNAs highly associated to these conserved DEGs. Our systems biology approach led to the identification of several potential therapeutic targets, predictive and prognostic biomarkers, of which lncRNA LINC00974 shown as an important and novel biomarker.
conclusionsFindings of the present study provide new insight into CRC pathogenesis across all stages, and suggests future assessment of the functional role of lncRNA LINC00974 in the development of CRC.
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