Transcriptome analysis reveal novel gene fusions in early onset sporadic rectal cancers
Ontology highlight
ABSTRACT: Gene fusions (GFs) represent a distinct class of structural variants identified consistently in cancer genomes across multiple cancer types. Several GFs exhibit gain of oncogenic function, and thus, have been the focus for development of efficient targeted therapies. Here, we present a comprehensive landscape of GFs in early-onset sporadic rectal cancer (EOSRC), a poorly studied colorectal cancer (CRC) subtype prevalent in developing countries from the transcriptome analysis of 37 EOSRC samples. Gene Ontology analysis revealed enrichment of unique biological process terms associated with 5’- and 3’- fusion partner genes. An extensive network analysis highlighted several promiscuous genes participating in GF formation. Further, an in-depth evaluation revealed significant association of these promiscuous genes with chromosome fragile sites.
Project description:Transcriptional profiling of early-onset sporadic rectal adenocarcinoma, comparing Wnt- and Wnt+ rectal tumor. Goal was to determine differentially expressed genes between them based on global gene expression.
Project description:Copy number profiling of early-onset sporadic rectal adenocarcinoma, comparing Wnt- and Wnt+ rectal tumor. Goal was to determine differentially altered genes between them based on global copy no.
Project description:Purpose: MicroRNAs play a prominent role in a variety of physiological and pathological biological processes, including cancer. For rectal cancers, only limited data are available on microRNA expression profiles, while the underlying genomic and transcriptomic aberrations have been firmly established. We therefore aimed to comprehensively map the microRNA expression patterns of this disease. Experimental design: Tumor biopsies and corresponding matched mucosa samples were prospectively collected from 72 patients (68 tumors and 70 normal mucosa) with locally advanced rectal cancers. Total RNA was extracted, and tumor and mucosa microRNA expression profiles were subsequently established for all patients. The expression of selected microRNAs was validated using semi-quantitative real-time PCR. Results: Forty-nine microRNAs were significantly differentially expressed (log2-fold difference >0.5 and P<0.001) between rectal cancer and normal rectal mucosa. The predicted targets for the identified microRNAs were enriched for the following KEGG pathways: Wnt, TGF-beta, mTOR, insulin, MAPK, and ErbB signaling. Between rectal tumor and normal tissue, miR-492, miR-542-5p, miR-584, miR-483-5p, miR-144, miR-2110, miR-652*, miR-375, miR-147b, miR-148a, miR-190, miR-26a/b, and miR-338-3p were found to be differentially expressed. Of clinical impact, miR-135b expression correlated significantly with overall survival that could be validated in a larger multicenter patient set (n=94). Conclusion: The comprehensive analysis of the rectal cancer microRNAome uncovered novel microRNAs and pathways associated with rectal cancer. This information contributes to a detailed view of rectal cancer. The identification and validation of miR-135b will help to identify novel molecular targets and pathways for therapeutic exploitation. Paired samples from rectal tumor and matched normal samples. Included are also 2 technical replicates.
Project description:Biopsy specimens were collected from rectal cancer before starting preoperative radiotherapy.The expression profiles were determined using Affymetrix Human Genome U95 version 2 arrays.Comparison between the sample groups allow to identify a set of discriminating genes that can be used for characterization of responders and nonresponders to preoperative radiotherapy in rectal cancer. Keywords: repeat
Project description:Purpose: MicroRNAs play a prominent role in a variety of physiological and pathological biological processes, including cancer. For rectal cancers, only limited data are available on microRNA expression profiles, while the underlying genomic and transcriptomic aberrations have been firmly established. We therefore aimed to comprehensively map the microRNA expression patterns of this disease. Experimental design: Tumor biopsies and corresponding matched mucosa samples were prospectively collected from 72 patients (68 tumors and 70 normal mucosa) with locally advanced rectal cancers. Total RNA was extracted, and tumor and mucosa microRNA expression profiles were subsequently established for all patients. The expression of selected microRNAs was validated using semi-quantitative real-time PCR. Results: Forty-nine microRNAs were significantly differentially expressed (log2-fold difference >0.5 and P<0.001) between rectal cancer and normal rectal mucosa. The predicted targets for the identified microRNAs were enriched for the following KEGG pathways: Wnt, TGF-beta, mTOR, insulin, MAPK, and ErbB signaling. Between rectal tumor and normal tissue, miR-492, miR-542-5p, miR-584, miR-483-5p, miR-144, miR-2110, miR-652*, miR-375, miR-147b, miR-148a, miR-190, miR-26a/b, and miR-338-3p were found to be differentially expressed. Of clinical impact, miR-135b expression correlated significantly with overall survival that could be validated in a larger multicenter patient set (n=94). Conclusion: The comprehensive analysis of the rectal cancer microRNAome uncovered novel microRNAs and pathways associated with rectal cancer. This information contributes to a detailed view of rectal cancer. The identification and validation of miR-135b will help to identify novel molecular targets and pathways for therapeutic exploitation.
Project description:Genomic profiling of human rectal adenoma and carcinoma by array-based comparative genomic hybridization Two group experiment, rectal adenoma vs. rectal carcinoma. Biological replicates: 8 adenomas vs. 8 carcinomas
Project description:Colorectal cancer (CRC) is the third most common lethal malignancy in Korea and worldwide. Rectal cancer patients occupy about 30% of CRC patients, and the majority of rectal cancer patients had locally advanced disease at diagnosis. The standard treatment of locally advanced rectal cancer (LARC) is neoadjuvant radiation therapy with concurrent chemotherapy (CCRT) followed by total mesorectal excision (TME). This multidisciplinary team approach improved local tumor control and overall survival of rectal cancer patients. High throughput proteomic analysis and machine learning algorithm identify DUOX2 (dual oxidase 2) as a novel biomarker for prediction of non-complete response after concurrent chemoradiation therapy for rectal cancer.High throughput proteomic analysis and machine learning algorithm identify DUOX2 (dual oxidase 2) as a novel biomarker for prediction of non-complete response after concurrent chemoradiation therapy for rectal cancer.