XRCC1: A Potential Prognostic and Immunological Biomarker in Low-Grade Gliomas

01-30-2024

“We conducted a comprehensive investigation into the potential of XRCC1 as a valuable diagnostic and prognostic indicator in diverse cancer types."

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BUFFALO, NY- January 30, 2024 – A new research paper was published inAging (listed by MEDLINE/PubMed as "Aging (Albany NY)" and "Aging-US" by Web of Science) Volume 16, Issue 1, entitled, “XRCC1: a potential prognostic and immunological biomarker in LGG based on systematic pan-cancer analysis.”

X-ray repair cross-complementation group 1 (XRCC1) is a pivotal contributor to base excision repair, and its dysregulation has been implicated in the oncogenicity of various human malignancies. However, a comprehensive pan-cancer analysis investigating the prognostic value, immunological functions, and epigenetic associations of XRCC1 remains lacking.

In this new study, researchers Guobing Wang, Yunyue Li, Rui Pan, Xisheng Yin, Congchao Jia, Yuchen She, Luling Huang, Guanhu Yang, Hao Chi, and Gang Tian from Southwest Medical University, The Affiliated Hospital of Southwest Medical University, Yibin Hospital of T.C.M, Medical School of Nanchang University, Fourth Military Medical University, and Ohio University aimed to address this knowledge gap by conducting a systematic investigation employing bioinformatics techniques across 33 cancer types.

“Our analysis encompassed XRCC1 expression levels, prognostic and diagnostic implications, epigenetic profiles, immune and molecular subtypes, Tumor Mutation Burden (TMB), Microsatellite Instability (MSI), immune checkpoints, and immune infiltration, leveraging data from TCGA, GTEx, CELL, Human Protein Atlas, Ualcan, and cBioPortal databases.”

Notably, XRCC1 displayed both positive and negative correlations with prognosis across different tumors. Epigenetic analysis revealed associations between XRCC1 expression and DNA methylation patterns in 10 cancer types, as well as enhanced phosphorylation. Furthermore, XRCC1 expression demonstrated associations with TMB and MSI in the majority of tumors. 

Interestingly, XRCC1 gene expression exhibited a negative correlation with immune cell infiltration levels, except for a positive correlation with M1 and M2 macrophages and monocytes in most cancers. Additionally, the researchers observed significant correlations between XRCC1 and immune checkpoint gene expression levels. Lastly, their findings implicated XRCC1 in DNA replication and repair processes, shedding light on the precise mechanisms underlying its oncogenic effects. 

“Overall, our study highlights the potential of XRCC1 as a prognostic and immunological pan-cancer biomarker, thereby offering a novel target for tumor immunotherapy.”

Read the full paper: DOI:https://doi.org/10.18632/aging.205426

Corresponding Authors: Guanhu Yang, Hao Chi, Gang Tian

Corresponding Emails:guanhuyang@gmail.com, Chihao7511@163.com, tiangang@swmu.edu.cn

Keywords: X-ray repair cross-complementation group 1, pan-cancer, prognosis, immune infiltration, tumor microenvironment

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About Aging-US:

Aging publishes research papers in all fields of aging research including but not limited, aging from yeast to mammals, cellular senescence, age-related diseases such as cancer and Alzheimer’s diseases and their prevention and treatment, anti-aging strategies and drug development and especially the role of signal transduction pathways such as mTOR in aging and potential approaches to modulate these signaling pathways to extend lifespan. The journal aims to promote treatment of age-related diseases by slowing down aging, validation of anti-aging drugs by treating age-related diseases, prevention of cancer by inhibiting aging. Cancer and COVID-19 are age-related diseases.

Aging is indexed by PubMed/Medline (abbreviated as “Aging (Albany NY)”), PubMed CentralWeb of Science: Science Citation Index Expanded (abbreviated as “Aging‐US” and listed in the Cell Biology and Geriatrics & Gerontology categories), Scopus (abbreviated as “Aging” and listed in the Cell Biology and Aging categories), Biological Abstracts, BIOSIS Previews, EMBASE, META (Chan Zuckerberg Initiative) (2018-2022), and Dimensions (Digital Science).

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