8q24.21 Locus: A Paradigm to Link Non-Coding RNAs, Genome Polymorphisms and Cancer

Wilson, Claire; Kanhere, Aditi

doi:10.3390/ijms22031094

Cited by 21 publications

(22 citation statements)

References 173 publications

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“…These cells could promote PCa progression by promoting immunosuppressive responses ( 48 , 49 ). Through CNV analysis, we found that 8q24.21, strongly associated with risk of tumors ( 50 , 51 ), was amplificated in subgroup 1. Some long non-coding RNAs, such as CCAT1 ( 52 , 53 ), PVT1 ( 54 ), PRNCR1 ( 55 ), and PCAT1 ( 56 ), in 8q24.21 have an influence in oncogenesis of PCa.…”

Section: Discussionmentioning

confidence: 92%

Identification of Metabolism-Related Gene-Based Subgroup in Prostate Cancer

Liang

Yin

et al. 2022

Front. Oncol.

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Prostate cancer is still the main male health problem in the world. The role of metabolism in the occurrence and development of prostate cancer is becoming more and more obvious, but it is not clear. Here we firstly identified a metabolism-related gene-based subgroup in prostate cancer. We used metabolism-related genes to divide prostate cancer patients from The Cancer Genome Atlas into different clinical benefit populations, which was verified in the International Cancer Genome Consortium. After that, we analyzed the metabolic and immunological mechanisms of clinical beneficiaries from the aspects of functional analysis of differentially expressed genes, gene set variation analysis, tumor purity, tumor microenvironment, copy number variations, single-nucleotide polymorphism, and tumor-specific neoantigens. We identified 56 significant genes for non-negative matrix factorization after survival-related univariate regression analysis and identified three subgroups. Patients in subgroup 2 had better overall survival, disease-free interval, progression-free interval, and disease-specific survival. Functional analysis indicated that differentially expressed genes in subgroup 2 were enriched in the xenobiotic metabolic process and regulation of cell development. Moreover, the metabolism and tumor purity of subgroup 2 were higher than those of subgroup 1 and subgroup 3, whereas the composition of immune cells of subgroup 2 was lower than that of subgroup 1 and subgroup 3. The expression of major immune genes, such as CCL2, CD274, CD276, CD4, CTLA4, CXCR4, IL1A, IL6, LAG3, TGFB1, TNFRSF4, TNFRSF9, and PDCD1LG2, in subgroup 2 was almost significantly lower than that in subgroup 1 and subgroup 3, which is consistent with the results of tumor purity analysis. Finally, we identified that subgroup 2 had lower copy number variations, single-nucleotide polymorphism, and neoantigen mutation. Our systematic study established a metabolism-related gene-based subgroup to predict outcomes of prostate cancer patients, which may contribute to individual prevention and treatment.

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Section: Discussionmentioning

confidence: 92%

Identification of Metabolism-Related Gene-Based Subgroup in Prostate Cancer

Liang

Yin

et al. 2022

Front. Oncol.

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“…Significant non-coding RNAs such as PCAT1 which were found to be highly altered in chromosome 8 led us to believe that a high number of genes were altered in the chromosome 8 region (21) . It has been earlier reported in numerous articles about gains and losses in chromosome 8 (22,23) among various other cancers like breast, colorectal, and prostate cancer.…”

Section: Resultsmentioning

confidence: 80%

A Transcriptomic Analysis to Identify Prevalent lncRNAs in Gingivobuccal Oral Cancer

Haldar¹,

Singh²

2023

IJST

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Objective: Gingivobuccal cancer is a subtype of oral cancer, prevalent in developing countries where the use of tobacco and Areca (betel) nut is rampant. This study aims to search through the publically available NCBI data to find comparisons between the normal and cancer-affected transcripts of RNA, which are molecules that copied the genetic information from DNA and that will be "read" as instructions to produce other molecules in the body. Using bioinformatic tools, we analyzed the variations in the transcripts and examined how they were correlated with other molecular processes in the body. We specifically investigated the role of "long noncoding RNAs (lncRNAs)" because it is speculated that they play an active role in the causality of cancer. Our analysis found a correlation of CTA-384D8.35 lncRNA with gingivobuccal cancer after analyzing the Hazard Ratio using the Cox Proportional-Hazard Model and is expected to pave the way for future studies. Methods: In this study, transcriptomic analysis was performed on a publicly available gingivobuccal cancer dataset obtained from NCBI. We developed a novel method for identification of annotated lncRNAs, which helped us select and correlate the lncRNA transcripts with the gingivobuccal cancer disease. Furthermore, the results were validated using the GEPIA2 tool for integrated analysis of co-lncRNA and GEPIA databases. Findings: From 24 RNA-Seq samples (12 normal samples and 12 tumor samples), a total of 16,065 potential lncRNA transcripts were recognized. From these 16,065 lncRNA transcripts, 1201 lncRNA transcripts were further filtered out based on a threshold adjusted p value of <0.01. We were able to for the first time identify these 1201 lncRNA transcripts, which were not annotated for gingivobuccal squamous cell carcinoma previously. Integrated analysis of co-lncRNA and GEPIA databases revealed that a total of 11 lncRNAs were upregulated, whereas 29 lncRNAs were downregulated. Furthermore, CTA-384D8.35 showed a significant correlation with disease-free survival time in HNSC. CTA-384D8.35 which is downregulated in gingivobuccal cancer has been correlated with tumor stage, metastasis, cancer status, clinical stage, and grade. Novelty: In this report we are for the first time correlating the CTA-384D8.35 lncRNA with the gingivobuccal cancer disease with the help of statistical and survival analysis. Furthermore, https://www.indjst.org/

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“…Cancer detection could benefit greatly from a better understanding of the co-expression network of lncRNAs and protein-coding genes. Cancer and other diseases can be caused by translocations and amplification of the 8q24 locus because it is susceptible to these events [30,31]. In addition, a number of critical regulatory elements can be found in this region, the absence of which can lead to the development of cancer.…”

Section: Discussionmentioning

confidence: 99%

Upregulation of the c-MYC oncogene and adjacent long noncoding RNAs PVT1 and CCAT1 in esophageal squamous cell carcinoma

Roohinejad¹,

Bahramian

Shamsabadi

et al. 2023

BMC Cancer

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Background All cell types express long non-coding RNAs (lncRNAs), which have the potential to play a role in carcinogenesis by altering the levels of their expression. Squamous cell carcinoma of the esophagus (ESCC) is a deadly disease with a poor prognosis and a high frequency of lymphatic metastases. Understanding the functional role and signaling pathways of two neighboring lncRNAs, CCAT1 and PVT1, in this oncogene’s pathogenesis may help us determine ESCC. Furthermore, it is still unclear whether these lncRNAs are linked to the clinicopathological characteristics of patients with ESCC. Methods For this study, we used biopsy from the Imam Khomeini Cancer Institute’s tumor bank in Tehran, Iran to obtain 40 ESCC tumor samples and their normal margin counterparts. The expression levels of the CCAT1, PVT1, and c-MYC genes were assessed using quantitative Real-Time RT-PCR. Additionally, demographic data and clinical-pathologic characteristics, such as tumor grade, tumor stage, lymph node, and metastasis, were taken into consideration. Graphpad prism version 8 was used for bioinformatics analyses. Results Comparing ESCC tissues to non-tumor tissues, we found significant upregulation of PVT1, CCAT1, and c-MYC. Patients with ESCC who had increased PVT1 expression also had higher rates of advanced stage and lymph node metastasis, whereas increased CCAT1 expression was only linked to advanced stage and wasn’t associated with lymph node metastasis. In predicting ESCC, CCAT1 (p < 0.05) was found to be an important factor. Overall survival was reduced by c-MYC and PVT1 overexpression (p < 0.001), according to Kaplan-Meier analysis. PVT1, CCAT1, and c-MYC were found to interact with 23 miRNAs with high and medium score classes, as shown in a bioinformatics study. We summarized the experimentally proven interactions between c-MYC, PVT1, and CCAT1 and other miRNAs, lncRNAs, and proteins. Conclusion This is the first report that CCAT1, PVT1 and c-MYC have been found to be up-regulated simultaneously in ESCC. It is possible that these genes may be involved in ESCC as a result of these findings. Therefore, as consequence, more research is needed to determine whether or not these lncRNAs play an oncogenic role in ESCC development and progression, as well as the regulatory mechanisms that control them.

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8q24.21 Locus: A Paradigm to Link Non-Coding RNAs, Genome Polymorphisms and Cancer

Cited by 21 publications

References 173 publications

Identification of Metabolism-Related Gene-Based Subgroup in Prostate Cancer

Identification of Metabolism-Related Gene-Based Subgroup in Prostate Cancer

A Transcriptomic Analysis to Identify Prevalent lncRNAs in Gingivobuccal Oral Cancer

Upregulation of the c-MYC oncogene and adjacent long noncoding RNAs PVT1 and CCAT1 in esophageal squamous cell carcinoma

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