Involvement of methylation of group of miRNA genes in regulation of expression of RAR-beta2 and NKIRAS1 target genes in lung cancer

Ходырев, Д. С.; Пронина, И. В.; Rykov, S. V.; Береснева, Е. В.; Freedman, Matt; Kazubskaya, T. P.; Логинов, В. И.; Брага, Э. А.

doi:10.1134/s002689331205007x

Cited by 13 publications

(3 citation statements)

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“…The results may provide a useful revelation to determine the machine learning model and to understand actual pathological conditions. Furthermore, our results are confirmed by the literatures, with 6 out of top 10 features associated with specific cancers including NKIRAS1 (Gerashchenko et al, 2010;Khodyrev et al, 2012), CDKN2B (Clavell et al, 2008), YTHDC2 (Wittliff et al, 2015;Yu et al, 2020), MECOM (Choi et al, 2017), RBFOX1 (Sengupta et al, 2013), and RAB6B (Kou et al, 2015). The corresponding molecular functions and related cancer of six genes are given in Table 4.…”

Section: Resultssupporting

confidence: 88%

A Novel XGBoost Method to Identify Cancer Tissue-of-Origin Based on Copy Number Variations

et al. 2020

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The discovery of cancer of unknown primary (CUP) is of great significance in designing more effective treatments and improving the diagnostic efficiency in cancer patients. In the study, we develop an appropriate machine learning model for tracing the tissue of origin of CUP with high accuracy after feature engineering and model evaluation. Based on a copy number variation data consisting of 4,566 training cases and 1,262 independent validation cases, an XGBoost classifier is applied to 10 types of cancer. Extremely randomized tree (Extra tree) is used for dimension reduction so that fewer variables replace the original high-dimensional variables. Features with top 300 weights are selected and principal component analysis is applied to eliminate noise. We find that XGBoost classifier achieves the highest overall accuracy of 0.8913 in the 10-fold cross-validation for training samples and 0.7421 on independent validation datasets for predicting tumor tissue of origin. Furthermore, by contrasting various performance indices, such as precision and recall rate, the experimental results show that XGBoost classifier significantly improves the classification performance of various tumors with less prediction error, as compared to other classifiers, such as K-nearest neighbors (KNN), Bayes, support vector machine (SVM), and Adaboost. Our method can infer tissue of origin for the 10 cancer types with acceptable accuracy in both cross-validation and independent validation data. It may be used as an auxiliary diagnostic method to determine the actual clinicopathological status of specific cancer.

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Section: Resultssupporting

confidence: 88%

A Novel XGBoost Method to Identify Cancer Tissue-of-Origin Based on Copy Number Variations

et al. 2020

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“…Retinoid acid receptors (RARs) are a class of receptor proteins that exist in the nucleus of tissue cells and function by regulating transcription factor-speci c target genes, which are not only involved in cell differentiation and growth and development, but also closely related to differentiation functions [5,6] .There are two known classes of retinoid intranuclear receptors, RARs and retinoid x receptors (RXRs), each with α, β, and γ subtypes, respectively [7,8] . It has been demonstrated that abnormal expression of retinoid acid receptor B (RAR-β) in cells is closely related to tumorigenesis.RARB is highly expressed in normal epithelial cells, and its expression is reduced or absent in a large number of tumor cells, such as breast, lung, esophageal, thyroid, prostate, bladder, endometrial, and cervical cancers [9][10][11][12][13][14][15][16] . Therefore, as a major inducible isoform in retinoic acid, RARB has become a hotspot of research, but the expression, biological function and in uence pathway of RARB in gastric cancer have not been studied in more depth.…”

Section: Discussionmentioning

confidence: 99%

RARB, a gene associated with MSI gastric cancer, affects progression and prognosis of gastric cancer

Cai,

Lin,

et al. 2023

Preprint

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MSI gastric cancer exhibits greater sensitivity to immunotherapy due to its own characteristics. Here, we firstly identified the RARB gene associated with MSI gastric cancer, which was positively correlated with mismatch repair proteins(MMR).Although relatively low in expression in MSI gastric cancer, RARB promotes gastric cancer progression and leads to poor prognosis. However, we found that in cellular experiments, lowering the expression of RARB accelerated the proliferation, invasion and migration of cancer cells and promoted the EMT. The contradictory reasons for these two results may be related to the tumor immune microenvironment. RARB may be a potential target for the treatment of gastric cancer.

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“…In primary lung tumors, methylation of CpG islands in genes for miR-9-1, miR-9-3, miR-34b/c, and miR-193a resulted in their downregulation with a concurrent increase in the expression of their target genes, RAR-β2 and NKIRAS1. 77 Other examples include hypermethylation of miR-91, miR-124a-3, miR-148, miR-152, and miR-663 in human breast cancer and aberrant DNA methylation and downregulation of miR-127 in prostate and bladder cancers. 98,148 In the latter example, chromatin-modifying drugs successfully restored miR-127 expression and downregulated its predicted target Bcl6, a proto-oncogene, thereby highlighting the therapeutic potential of chromatin-modifying drugs in modulating miRNA expression.…”

Section: Micrornas: Introduction and A Brief Historymentioning

confidence: 99%

MicroRNAs

2013

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The discovery of microRNAs (miRNAs) in 1993 followed by developments and discoveries in small RNA biology have redefined the biological landscape by significantly altering the longstanding dogmas that defined gene regulation. These small RNAs play a significant role in modulation of an array of physiological and pathological processes ranging from embryonic development to neoplastic progression. Unique miRNA signatures of various inherited, metabolic, infectious, and neoplastic diseases have added a new dimension to the studies that look at their pathogenesis and highlight their potential to be reliable biomarkers. Also, altering miRNA functionality and the development of novel in vivo delivery systems to achieve targeted modulation of specific miRNA function are being actively pursued as novel approaches for therapeutic intervention in many diseases. Here we review the current body of knowledge on the role of miRNAs in development and disease and discuss future implications.

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Involvement of methylation of group of miRNA genes in regulation of expression of RAR-beta2 and NKIRAS1 target genes in lung cancer

Cited by 13 publications

References 50 publications

A Novel XGBoost Method to Identify Cancer Tissue-of-Origin Based on Copy Number Variations

A Novel XGBoost Method to Identify Cancer Tissue-of-Origin Based on Copy Number Variations

RARB, a gene associated with MSI gastric cancer, affects progression and prognosis of gastric cancer

MicroRNAs

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