Role of Long Non-Coding RNA Polymorphisms in Cancer Chemotherapeutic Response

Research Progress of Long Non-Coding RNA in Tumor Drug Resistance: A New Paradigm

In the past few decades, chemotherapy has been one of the most effective cancer treatment options. Drug resistance is currently one of the greatest obstacles to effective cancer treatment. Even though drug resistance mechanisms have been extensively investigated, they have not been fully elucidated. Recent genome-wide investigations have revealed the existence of a substantial quantity of long non-coding RNAs (lncRNAs) transcribed from the human genome, which actively participate in numerous biological processes, such as transcription, splicing, epigenetics, the cell cycle, cell differentiation, development, pluripotency, immune microenvironment. The abnormal expression of lncRNA is considered a contributing factor to the drug resistance. Furthermore, drug resistance may be influenced by genetic and epigenetic variations, as well as individual differences in patient treatment response, attributable to polymorphisms in metabolic enzyme genes. This review focuses on the mechanism of lncRNAs resistance to target drugs in the study of tumors with high mortality, aiming to establish a theoretical foundation for targeted therapy.

LncRNA polymorphisms and lung cancer risk

Lung cancer (LC) imposes a significant burden, and is associated with high mortality and morbidity among malignant tumors. Aberrant expression of particular lncRNAs is closely linked to LC. LncRNA polymorphisms cause abnormal expression levels and/or structural dysfunction. They can affect the progression of cancer, survival, response to chemotherapy and recurrence rates in cancer patients. The present article provides a comprehensive overview of the effect of lncRNA genetic polymorphisms on LC. It is proposed that lncRNA-related variants can be used to predict cancer risk and therapeutic outcomes. More large-scale trials on diverse ethnic groups are required to validate the results, thus personalizing LC therapy based on lncRNA genotypes.

The crosstalk between non-coding RNA polymorphisms and resistance to lung cancer therapies

Lung cancer (LC) is one of the most common cancer-related mortality in the world. Even with intensive multimodality therapies, lung cancer has a poor prognosis and a high morbidity rate. This review focused on the role of non-coding RNA polymorphisms such as lncRNAs and miRNAs in the resistance to LC therapies, which could open promising avenue for better therapeutic response. Of note, there is currently no valid biomarker to predict lung cancer sensitivity in patients during treatment. Since genetic variations cause many challenges in treating patients, genotyping of known polymorphisms must be thoroughly explored to find desirable treatment platforms. With this knowledge, individualized treatments could become more possible in management of LC.

LncRNA-Associated Genetic Etiologies Are Shared between Type 2 Diabetes and Cancers in the UAE Population

Numerous epidemiological studies place patients with T2D at a higher risk for cancer. Many risk factors, such as obesity, ageing, poor diet and low physical activity, are shared between T2D and cancer; however, the biological mechanisms linking the two diseases remain largely unknown. The advent of genome wide association studies (GWAS) revealed large numbers of genetic variants associated with both T2D and cancer. Most significant disease-associated variants reside in non-coding regions of the genome. Several studies show that single nucleotide polymorphisms (SNPs) at or near long non-coding RNA (lncRNA) genes may impact the susceptibility to T2D and cancer. Therefore, the identification of genetic variants predisposing individuals to both T2D and cancer may help explain the increased risk of cancer in T2D patients. We aim to investigate whether lncRNA genetic variants with significant diabetes and cancer associations overlap in the UAE population. We first performed an annotation-based analysis of UAE T2D GWAS, confirming the high prevalence of variants at or near non-coding RNA genes. We then explored whether these T2D SNPs in lncRNAs were relevant to cancer. We highlighted six non-coding genetic variants, jointly reaching statistical significance in T2D and cancer, implicating a shared genetic architecture between the two diseases in the UAE population.

Comprehensive bioinformatic analyses of lncRNA-mediated ceRNA network for uterine corpus endometrial carcinoma

Background

Given that long non-coding RNAs (lncRNAs) involved in the tumor initiation or progression of the endometrium and that competing endogenous RNA (ceRNA) plays an important role in increasingly more biological processes, lncRNA-mediated ceRNA is likely to function in the pathogenesis of uterine corpus endometrial carcinoma (UCEC). Our present study aimed to explore the potential molecular mechanisms for the prognosis of UCEC through a lncRNA-mediated ceRNA network.

Methods

The transcriptome profiles and corresponding clinical profiles of UCEC dataset were retrieved from Clinical Proteomic Tumor Analysis Consortium (CPTAC) and The Cancer Genome Atlas (TCGA) databases respectively. Differentially expressed genes (DEGs) in UCEC samples were identified via "Edge R" package. Then, an integrated bioinformatics analysis including functional enrichment analysis, tumor infiltrating immune cell (TIIC) analysis, Kaplan-Meier curve, Cox regression analysis were conducted to analyze the prognostic biomarkers.

Results

In the CPTAC dataset of UCEC, a ceRNA network comprised of 36 miRNAs, 123 lncRNAs and 124 targeted mRNAs was established, and 8 of 123 prognostic-related Differentially Expressed long noncoding RNAs (DElncRNAs) were identified. While in the TCGA dataset, a ceRNA network comprised of 38 miRNAs, 83 lncRNAs and 110 targeted mRNAs was established, and 2 of 83 prognostic-related DElncRNAs were identified. After filtered by risk grouping and Cox regression analysis, 10 prognostic-related lncRNAs including LINC00443, LINC00483, C2orf48, TRBV11-2, MEG-8 were identified. In addition, 33 survival-related Differentially Expressed messenger RNA (DEmRNAs) in two ceRNA networks were further validated in the Human Protein Atlas Portal (HPA) database. Finally, six lncRNA/miRNA/mRNA axes were established to elucidate prognostic regulatory roles in UCEC.

Conclusions

Several prognostic lncRNAs are identified and prognostic model of lncRNA-mediated ceRNA network is constructed, which promotes the understanding of UCEC development mechanisms and potential therapeutic targets.

Non-Coding Variants in Cancer: Mechanistic Insights and Clinical Potential for Personalized Medicine

The cancer genome is characterized by extensive variability, in the form of Single Nucleotide Polymorphisms (SNPs) or structural variations such as Copy Number Alterations (CNAs) across wider genomic areas. At the molecular level, most SNPs and/or CNAs reside in non-coding sequences, ultimately affecting the regulation of oncogenes and/or tumor-suppressors in a cancer-specific manner. Notably, inherited non-coding variants can predispose for cancer decades prior to disease onset. Furthermore, accumulation of additional non-coding driver mutations during progression of the disease, gives rise to genomic instability, acting as the driving force of neoplastic development and malignant evolution. Therefore, detection and characterization of such mutations can improve risk assessment for healthy carriers and expand the diagnostic and therapeutic toolbox for the patient. This review focuses on functional variants that reside in transcribed or not transcribed non-coding regions of the cancer genome and presents a collection of appropriate state-of-the-art methodologies to study them.