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      Senescence-related signatures predict prognosis and response to immunotherapy in colon cancer

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          Abstract

          Background

          Colorectal cancer (CRC) is one of the most common cancers. Cellular senescence plays a vital role in carcinogenesis by activating many pathways. In this study, we aimed to identify biomarkers for predicting the survival and recurrence of CRC through cellular senescence-related genes.

          Methods

          Utilizing The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, RNA-sequencing data and clinical information for CRC were collected. A risk model for predicting overall survival was established based on five differentially expressed genes using least absolute shrinkage and selection operator-Cox regression (LASSO-Cox regression), receiver operating characteristic (ROC), and Kaplan-Meier analyses. The study also delved into both the tumor microenvironment and the response to immunotherapy. Moreover, we gathered clinical sample data from our center in order to confirm the findings of public database analysis.

          Results

          Through ROC and Kaplan-Meier analyses, a risk model was developed using five cellular senescence-related genes [i.e., CDKN2A, SERPINE1, SNAI1, CXCL1, and ETS2] to categorize patients into high- and low-risk groups. In the TCGA-colon adenocarcinoma (COAD) and GEO-COAD cohorts, the high-risk group was associated with a bleaker forecast (P<0.05), immune cell inactivation, and insensitivity to immunotherapy in IMvigor210 database ( http://research-pub.gene.com/IMvigor210CoreBiologies/). Clinical samples were then used to confirm that ETS2 and CDKN2A could serve as independent prognostic biomarkers in CRC.

          Conclusions

          Gene signatures related to cellular senescence, specifically involving CDKN2A and ETS2, are emerging as promising biomarkers for predicting CRC prognosis and guiding immunotherapy.

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          Most cited references50

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          limma powers differential expression analyses for RNA-sequencing and microarray studies

          limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.
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            Regularization Paths for Generalized Linear Models via Coordinate Descent

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              Gene Expression Omnibus: NCBI gene expression and hybridization array data repository.

              R. Edgar (2002)
              The Gene Expression Omnibus (GEO) project was initiated in response to the growing demand for a public repository for high-throughput gene expression data. GEO provides a flexible and open design that facilitates submission, storage and retrieval of heterogeneous data sets from high-throughput gene expression and genomic hybridization experiments. GEO is not intended to replace in house gene expression databases that benefit from coherent data sets, and which are constructed to facilitate a particular analytic method, but rather complement these by acting as a tertiary, central data distribution hub. The three central data entities of GEO are platforms, samples and series, and were designed with gene expression and genomic hybridization experiments in mind. A platform is, essentially, a list of probes that define what set of molecules may be detected. A sample describes the set of molecules that are being probed and references a single platform used to generate its molecular abundance data. A series organizes samples into the meaningful data sets which make up an experiment. The GEO repository is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo.
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                Author and article information

                Journal
                J Gastrointest Oncol
                J Gastrointest Oncol
                JGO
                Journal of Gastrointestinal Oncology
                AME Publishing Company
                2078-6891
                2219-679X
                27 June 2024
                30 June 2024
                : 15
                : 3
                : 1020-1034
                Affiliations
                [1 ]deptDepartment of Medical Oncology , Affiliated Cancer Hospital and Institute of Guangzhou Medical University , Guangzhou, China;
                [2 ]Guangzhou Youdi Bio-technology Co., Ltd. , Guangzhou, China;
                [3 ]deptDepartment of Oncology and Hematology , Tashkent State Pediatric Institute , Tashkent, Uzbekistan;
                [4 ]deptDepartment of Health Sciences , University of Piemonte Orientale , Novara, Italy;
                [5 ]deptDepartment of Surgery , University Maggiore Hospital della Carità , Novara, Italy;
                [6 ]Republican Specialized Scientific and Practical Medical Center of Oncology and Radiology (National Cancer Center of Uzbekistan) , Tashkent, Uzbekistan
                Author notes

                Contributions: (I) Conception and design: Y Zheng, AA Yusupbekov, X Hu; (II) Administrative support: X Zhu, L Li; (III) Provision of study materials or patients: Y Zheng, X Hu, X Zhu; (IV) Collection and assembly of data: W Zhang, Y Chen; (V) Data analysis and interpretation: H Liang, BB Usmanov, W Zhang, Y Chen; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.

                [#]

                These authors contributed equally to this work.

                Correspondence to: Yanfang Zheng, MD. Department of Medical Oncology, Affiliated Cancer Hospital and Institute of Guangzhou Medical University, 78 Hengzhigang Road, Guangzhou 510095, China. Email: zheng2020@ 123456gzhmu.edu.cn ; Abrorjon A. Yusupbekov, MD. Republican Specialized Scientific and Practical Medical Center of Oncology and Radiology (National Cancer Center of Uzbekistan), 383 Farobi Street, Tashkent, Uzbekistan. Email: dr.abr_info@ 123456mail.ru .
                Article
                jgo-15-03-1020
                10.21037/jgo-24-339
                11231866
                8895ea2f-ed9e-4c56-b4a0-aaaa87ae164b
                2024 Journal of Gastrointestinal Oncology. All rights reserved.

                Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0.

                History
                : 07 May 2024
                : 21 June 2024
                Funding
                Funded by: the Scientific Project Foundation of Guangzhou City
                Award ID: No. SL2022A04J00640
                Funded by: the Plan for Enhancing Scientific Research in GMU
                Funded by: the Science and Technology Foundation of Guangdong Province
                Award ID: No. 2021A1515010793
                Funded by: the Science and Technology Program of Guangzhou City
                Award ID: No. 202201020097
                Funded by: the Affiliated Cancer Hospital & Institute of Guangzhou Medical University
                Award ID: No. 2020-YZ-01
                Funded by: Wu Jieping Medical Foundation
                Award ID: No. 320.6750.2023.19-9
                Categories
                Original Article

                colorectal cancer (crc),cell senescence,tumor microenvironment (tme),immunotherapy

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