Dataset Information

G-quadruplexes formation in the 5'UTRs of mRNAs associated with colorectal cancer pathways.

ABSTRACT: RNA G-quadruplexes (rG4) are stable non-canonical secondary structures composed of G-rich sequences. Many rG4 structures located in the 5'UTRs of mRNAs act as translation repressors due to their high stability which is thought to impede ribosomal scanning. That said, it is not known if these are mRNA-specific examples, or if they are indicative of a global expression regulation mechanism of the mRNAs involved in a common pathway based on structure folding recognition. Gene-ontology analysis of mRNAs bearing a predicted rG4 motif in their 5'UTRs revealed an enrichment for mRNAs associated with the colorectal cancer pathway. Bioinformatic tools for rG4 prediction, and experimental in vitro validations were used to confirm and compare the folding of the predicted rG4s of the mRNAs associated with dysregulated pathways in colorectal cancer. The rG4 folding was confirmed for the first time for 9 mRNAs. A repressive effect of 3 rG4 candidates on the expression of a reporter gene was also measured in colorectal cancer cell lines. This work highlights the fact that rG4 prediction is not yet accurate, and that experimental characterization is still essential in order to identify the precise rG4 folding sequences and the possible common features shared between the rG4 overrepresented in important biological pathways.

SUBMITTER: Jodoin R

PROVIDER: S-EPMC6277105 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

G-quadruplexes formation in the 5'UTRs of mRNAs associated with colorectal cancer pathways.

Jodoin Rachel R Perreault Jean-Pierre JP

PloS one 20181203 12

RNA G-quadruplexes (rG4) are stable non-canonical secondary structures composed of G-rich sequences. Many rG4 structures located in the 5'UTRs of mRNAs act as translation repressors due to their high stability which is thought to impede ribosomal scanning. That said, it is not known if these are mRNA-specific examples, or if they are indicative of a global expression regulation mechanism of the mRNAs involved in a common pathway based on structure folding recognition. Gene-ontology analysis of m ...[more]

PMID: 30507959

Similar Datasets

Project description:ObjectivesColorectal cancer (CRC) is the second leading cause of cancer in Europe, with 1.931.590 people newly diagnosed in 2020. The purpose of this study is the investigation of treatment options and healthcare resource metastatic CRC (mCRC) in Greece.MethodsThis study is based on the information collected in November 2020 by an expert panel comprising of 6 medical oncologists from major public and private centers around Greece. A 3-round survey was undertaken, according to Delphi method. The treatment phases studied were: pre-progression; disease progression and terminal care. Pharmaceutical costs and resource utilization data were considered from the perspective of the Greek National Services Organization (EOPYY).ResultsExperts agreed that the anticipated prevalence of RAS mutation in mCRC is 47% (30% RAS/BRAF WT Left, 17% RAS/BRAF WT Right); 8% BRAF while, MSI-H/dMMR are found in 5% of mCRC tumors. Based on mutational status, 74.8% of patients receive biological targeted therapies in combination with fluoropyrimidine/based combination chemotherapy, as 1st line treatment, and 25.2% combination chemotherapy alone. At 2nd line, 58.6% of patients receive biological targeted therapies in combination with chemotherapy, 25.4% immunotherapy, 11% combination chemotherapy and 5% biological targeted therapies. At 3rd line 56% of patients receive combination chemotherapy, 28% biological targeted therapies, 10% biological targeted therapies in combination with chemotherapy and 6% immunotherapy. The weighted annual cost (pharmaceuticals and resource use cost) in 1st line per mCRC patient was calculated at €28,407, in 2nd line €33,568, in 3rd line €25,550. The annual cost beyond 3rd line per patient regardless mutation was €19,501 per mCRC patient.ConclusionsmCRC is a societal challenge for healthcare systems as the treatment is more prolonged but expand patients' survival. Thus, reimbursement decisions should be based not just on the cost of the treatment, but on the magnitude of the benefit of its treatment on patients' survival and quality of life.

Project description:BackgroundChromosomal rearrangements are the typical phenomena in cancer genomes causing gene disruptions and fusions, corruption of regulatory elements, damage to chromosome integrity. Among the factors contributing to genomic instability are non-B DNA structures with stem-loops and quadruplexes being the most prevalent. We aimed at investigating the impact of specifically these two classes of non-B DNA structures on cancer breakpoint hotspots using machine learning approach.MethodsWe developed procedure for machine learning model building and evaluation as the considered data are extremely imbalanced and it was required to get a reliable estimate of the prediction power. We built logistic regression models predicting cancer breakpoint hotspots based on the densities of stem-loops and quadruplexes, jointly and separately. We also tested Random Forest models varying different resampling schemes (leave-one-out cross validation, train-test split, 3-fold cross-validation) and class balancing techniques (oversampling, stratification, synthetic minority oversampling).ResultsWe performed analysis of 487,425 breakpoints from 2234 samples covering 10 cancer types available from the International Cancer Genome Consortium. We showed that distribution of breakpoint hotspots in different types of cancer are not correlated, confirming the heterogeneous nature of cancer. It appeared that stem-loop-based model best explains the blood, brain, liver, and prostate cancer breakpoint hotspot profiles while quadruplex-based model has higher performance for the bone, breast, ovary, pancreatic, and skin cancer. For the overall cancer profile and uterus cancer the joint model shows the highest performance. For particular datasets the constructed models reach high predictive power using just one predictor, and in the majority of the cases, the model built on both predictors does not increase the model performance.ConclusionDespite the heterogeneity in breakpoint hotspots' distribution across different cancer types, our results demonstrate an association between cancer breakpoint hotspots and stem-loops and quadruplexes. Approximately for half of the cancer types stem-loops are the most influential factors while for the others these are quadruplexes. This fact reflects the differences in regulatory potential of stem-loops and quadruplexes at the tissue-specific level, which yet to be discovered at the genome-wide scale. The performed analysis demonstrates that influence of stem-loops and quadruplexes on breakpoint hotspots formation is tissue-specific.

Dataset Information

G-quadruplexes formation in the 5'UTRs of mRNAs associated with colorectal cancer pathways.

Publications

G-quadruplexes formation in the 5'UTRs of mRNAs associated with colorectal cancer pathways.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets