Systematic analysis of circRNA biomarkers for diagnosis, prognosis and therapy in colorectal cancer

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Abstract

As the third most common cancer and the second leading cause of cancer death worldwide, colorectal cancer (CRC) poses a serious threat to people’s health. In recent years, circRNA has been widely reported as a new biomarker in CRC, but a comprehensive summary and analysis is lacking. This study aims to evaluate the diagnostic, therapeutic and prognostic significance of circRNAs in CRC by systematically analysing their expression patterns, biological functions and clinical significance in CRC. The literature on circRNA in CRC was searched in the PubMed database and included for analysis after screening according to strict inclusion and exclusion criteria. The UALCAN online tool was used to obtain host gene expression data. The miRTargetLink 2.0 was used to predict target genes for miRNAs action in CRC patients. Cytoscape was used to construct circRNA-miRNA-mRNA interaction networks. From the 236 included papers, we identified 217 circRNAs and their associated 108 host genes and 145 miRNAs. Among the 145 miRNAs, 27 miRNAs had no corresponding target genes. After prediction of target genes and differential analysis, a total of 25 target genes were obtained and a circRNA-miRNA-mRNA interaction network was constructed. Among the 217 circRNAs, 74 were associated with diagnosis, 160 with treatment and 51 with prognosis. And 154 of them function as oncogenes while 58 as tumour suppressor genes. In addition, these circRNAs include 32 exosomal circRNAs, which have unique advantages as biomarkers. In total, we summarize and analyze the expression patterns, biological functions and clinical significance of circRNAs in CRC. In addition, we constructed some new circRNA-miRNA-mRNA regulatory axes based on the miRNAs sponged by circRNAs.

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Cytoscape: a software environment for integrated models of biomolecular interaction networks.

Paul Shannon, Andrew Markiel, Owen Ozier … (2003)

Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.

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Cancer Statistics, 2021

Rebecca Siegel, Kimberly D Miller, Hannah Fuchs … (2021)

Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths in the United States and compiles the most recent data on population-based cancer occurrence. Incidence data (through 2017) were collected by the Surveillance, Epidemiology, and End Results Program; the National Program of Cancer Registries; and the North American Association of Central Cancer Registries. Mortality data (through 2018) were collected by the National Center for Health Statistics. In 2021, 1,898,160 new cancer cases and 608,570 cancer deaths are projected to occur in the United States. After increasing for most of the 20th century, the cancer death rate has fallen continuously from its peak in 1991 through 2018, for a total decline of 31%, because of reductions in smoking and improvements in early detection and treatment. This translates to 3.2 million fewer cancer deaths than would have occurred if peak rates had persisted. Long-term declines in mortality for the 4 leading cancers have halted for prostate cancer and slowed for breast and colorectal cancers, but accelerated for lung cancer, which accounted for almost one-half of the total mortality decline from 2014 to 2018. The pace of the annual decline in lung cancer mortality doubled from 3.1% during 2009 through 2013 to 5.5% during 2014 through 2018 in men, from 1.8% to 4.4% in women, and from 2.4% to 5% overall. This trend coincides with steady declines in incidence (2.2%-2.3%) but rapid gains in survival specifically for nonsmall cell lung cancer (NSCLC). For example, NSCLC 2-year relative survival increased from 34% for persons diagnosed during 2009 through 2010 to 42% during 2015 through 2016, including absolute increases of 5% to 6% for every stage of diagnosis; survival for small cell lung cancer remained at 14% to 15%. Improved treatment accelerated progress against lung cancer and drove a record drop in overall cancer mortality, despite slowing momentum for other common cancers.

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UALCAN: A Portal for Facilitating Tumor Subgroup Gene Expression and Survival Analyses1

Darshan S. Chandrashekar, Bhuwan Bashel, Sai Balasubramanya … (2017)

Genomics data from The Cancer Genome Atlas (TCGA) project has led to the comprehensive molecular characterization of multiple cancer types. The large sample numbers in TCGA offer an excellent opportunity to address questions associated with tumo heterogeneity. Exploration of the data by cancer researchers and clinicians is imperative to unearth novel therapeutic/diagnostic biomarkers. Various computational tools have been developed to aid researchers in carrying out specific TCGA data analyses; however there is need for resources to facilitate the study of gene expression variations and survival associations across tumors. Here, we report UALCAN, an easy to use, interactive web-portal to perform to in-depth analyses of TCGA gene expression data. UALCAN uses TCGA level 3 RNA-seq and clinical data from 31 cancer types. The portal's user-friendly features allow to perform: 1) analyze relative expression of a query gene(s) across tumor and normal samples, as well as in various tumor sub-groups based on individual cancer stages, tumor grade, race, body weight or other clinicopathologic features, 2) estimate the effect of gene expression level and clinicopathologic features on patient survival; and 3) identify the top over- and under-expressed (up and down-regulated) genes in individual cancer types. This resource serves as a platform for in silico validation of target genes and for identifying tumor sub-group specific candidate biomarkers. Thus, UALCAN web-portal could be extremely helpful in accelerating cancer research. UALCAN is publicly available at http://ualcan.path.uab.edu.

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Author and article information

Contributors

Yafei Xiao: URI : https://loop.frontiersin.org/people/1282936/overview

Mengmeng Li: URI : https://loop.frontiersin.org/people/1474966/overview

Journal

Journal ID (nlm-ta): Front Genet

Journal ID (iso-abbrev): Front Genet

Journal ID (publisher-id): Front. Genet.

Title: Frontiers in Genetics

Publisher: Frontiers Media S.A.

ISSN (Electronic): 1664-8021

Publication date (Electronic): 12 October 2022

Publication date Collection: 2022

Volume: 13

Electronic Location Identifier: 938672

Affiliations

[1] ¹ Department of General Surgery , Huaihe Hospital of Henan University , Kaifeng, China

[2] ² Department of Neurology , Peking University People’s Hospital , Peking University School of Medicine , Beijing, China

[3] ³ Institute of Biomedical Informatics , Cell Signal Transduction Laboratory , Bioinformatics Center , Henan Provincial Engineering Center for Tumor Molecular Medicine , School of Basic Medical Sciences , Henan University , Kaifeng, China

[4] ⁴ Department of Gynecology and Obstetrics , The First Affiliated Hospital , Zhejiang University School of Medicine , Hangzhou, China

[5] ⁵ Department of Pediatric Orthopaedics , The Third Affiliated Hospital of Zhengzhou University , Zhengzhou, China

[6] ⁶ Department of Thoracic Surgery , The First Affiliated Hospital of Henan University , Kaifeng, China

Author notes

Edited by: Parvin Mehdipour, Tehran University of Medical Sciences, Iran

Reviewed by: Pouria Samadi, Hamadan University of Medical Sciences, Iran

Saeid Afshar, Hamadan University of Medical Sciences, Iran

*Correspondence: Changjiang Qin, qincj888@ 123456163.com

This article was submitted to RNA, a section of the journal Frontiers in Genetics

^†These authors have contributed equally to this work and share first authorship

Article

Publisher ID: 938672

DOI: 10.3389/fgene.2022.938672

PMC ID: 9597305

PubMed ID: 36313458

SO-VID: 7fa33618-d0cc-4a35-a5b0-ffe958e3c380

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

History

Date received : 16 May 2022

Date accepted : 23 September 2022

Funding

Funded by: National Natural Science Foundation of China , doi 10.13039/501100001809;

Funded by: Natural Science Foundation of Henan Province , doi 10.13039/501100006407;

Systematic analysis of circRNA biomarkers for diagnosis, prognosis and therapy in colorectal cancer

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Journal of Circulating Biomarkers

Most cited references 89

Cytoscape: a software environment for integrated models of biomolecular interaction networks.

Cancer Statistics, 2021

UALCAN: A Portal for Facilitating Tumor Subgroup Gene Expression and Survival Analyses1

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