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      A novel enterocyte-related 4-gene signature for predicting prognosis in colon adenocarcinoma

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          Abstract

          Background

          Colon adenocarcinoma (COAD) is a fatal disease, and its cases are constantly increasing worldwide. Further, the therapeutic and management strategies for patients with COAD are still unsatisfactory due to the lack of accurate patient classification and prognostic models. Therefore, our study aims to identify prognostic markers in patients with COAD and construct a cell subtype-specific prognostic model with high accuracy and robustness.

          Methods

          Single-cell transcriptomic data of six samples were retrieved from the Gene expression omnibus (GEO) database. The cluster annotation and cell-cell communication analysis identified enterocytes as a key player mediating signal communication networks. A four-gene signature prognostic model was constructed based on the enterocyte-related differentially expressed genes (ERDEGs) in patients with COAD of the Cancer Genome Atlas cohort. The prognostic model was validated on three external validation cohorts from the GEO database. The correlation between immune cell infiltration, immunotherapy response, drug sensitivity, and the four-gene signature prognostic model was investigated. Finally, immunohistochemistry (IHC) was performed to determine the expression of the four genes.

          Results

          We found that the proportion of epithelial cells was obviously large in COAD samples. Further analysis of epithelial cells showed that the activity of the enterocytes was highest in the cell-cell communication network. Based on enterocyte data, 30 ERDEGs were identified and a 4-gene prognostic model including CPM, CLCA4, ELOVL6, and ATP2A3 was developed and validated. The risk score derived from this model was considered as an independent variable factor to predict overall survival. The patients were divided into high- and low-risk groups based on the median riskscore value. The correlation between immune cell infiltration, immunotherapy response, immune status, clinical characteristics, drug sensitivity, and risk score was analyzed. IHC confirmed the expression of signature genes in tissues from normal individuals, patients with polyps, and COAD.

          Conclusion

          In this study, we constructed and validated a novel four-gene signature prognostic model, which could effectively predict the response to immunotherapy and overall survival in patients with COAD. More importantly, this model provides useful insight into the management of colon cancer patients and aids in designing personalized therapy.

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          Most cited references37

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          Inference and analysis of cell-cell communication using CellChat

          Understanding global communications among cells requires accurate representation of cell-cell signaling links and effective systems-level analyses of those links. We construct a database of interactions among ligands, receptors and their cofactors that accurately represent known heteromeric molecular complexes. We then develop CellChat, a tool that is able to quantitatively infer and analyze intercellular communication networks from single-cell RNA-sequencing (scRNA-seq) data. CellChat predicts major signaling inputs and outputs for cells and how those cells and signals coordinate for functions using network analysis and pattern recognition approaches. Through manifold learning and quantitative contrasts, CellChat classifies signaling pathways and delineates conserved and context-specific pathways across different datasets. Applying CellChat to mouse and human skin datasets shows its ability to extract complex signaling patterns. Our versatile and easy-to-use toolkit CellChat and a web-based Explorer (http://www.cellchat.org/) will help discover novel intercellular communications and build cell-cell communication atlases in diverse tissues.
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            Immunotherapy in colorectal cancer: rationale, challenges and potential

            Following initial successes in melanoma treatment, immunotherapy has rapidly become established as a major treatment modality for multiple types of solid cancers, including a subset of colorectal cancers (CRCs). Two programmed cell death 1 (PD1)-blocking antibodies, pembrolizumab and nivolumab, have shown efficacy in patients with metastatic CRC that is mismatch-repair-deficient and microsatellite instability-high (dMMR-MSI-H), and have been granted accelerated FDA approval. In contrast to most other treatments for metastatic cancer, immunotherapy achieves long-term durable remission in a subset of patients, highlighting the tremendous promise of immunotherapy in treating dMMR-MSI-H metastatic CRC. Here, we review the clinical development of immune checkpoint inhibition in CRC leading to regulatory approvals for the treatment of dMMR-MSI-H CRC. We focus on new advances in expanding the efficacy of immunotherapy to early-stage CRC and CRC that is mismatch-repair-proficient and has low microsatellite instability (pMMR-MSI-L) and discuss emerging approaches for targeting the immune microenvironment, which might complement immune checkpoint inhibition.
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              Cancer treatment and survivorship statistics, 2022

              The number of cancer survivors continues to increase in the United States due to the growth and aging of the population as well as advances in early detection and treatment. To assist the public health community in better serving these individuals, the American Cancer Society and the National Cancer Institute collaborate triennially to estimate cancer prevalence in the United States using incidence and survival data from the Surveillance, Epidemiology, and End Results cancer registries, vital statistics from the Centers for Disease Control and Prevention's National Center for Health Statistics, and population projections from the US Census Bureau. Current treatment patterns based on information in the National Cancer Database are presented for the most prevalent cancer types by race, and cancer-related and treatment-related side-effects are also briefly described. More than 18 million Americans (8.3 million males and 9.7 million females) with a history of cancer were alive on January 1, 2022. The 3 most prevalent cancers are prostate (3,523,230), melanoma of the skin (760,640), and colon and rectum (726,450) among males and breast (4,055,770), uterine corpus (891,560), and thyroid (823,800) among females. More than one-half (53%) of survivors were diagnosed within the past 10 years, and two-thirds (67%) were aged 65 years or older. One of the largest racial disparities in treatment is for rectal cancer, for which 41% of Black patients with stage I disease receive proctectomy or proctocolectomy compared to 66% of White patients. Surgical receipt is also substantially lower among Black patients with non-small cell lung cancer, 49% for stages I-II and 16% for stage III versus 55% and 22% for White patients, respectively. These treatment disparities are exacerbated by the fact that Black patients continue to be less likely to be diagnosed with stage I disease than White patients for most cancers, with some of the largest disparities for female breast (53% vs 68%) and endometrial (59% vs 73%). Although there are a growing number of tools that can assist patients, caregivers, and clinicians in navigating the various phases of cancer survivorship, further evidence-based strategies and equitable access to available resources are needed to mitigate disparities for communities of color and optimize care for people with a history of cancer. CA Cancer J Clin. 2022;72:409-436.
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                Author and article information

                Contributors
                Journal
                Front Immunol
                Front Immunol
                Front. Immunol.
                Frontiers in Immunology
                Frontiers Media S.A.
                1664-3224
                02 December 2022
                2022
                : 13
                : 1052182
                Affiliations
                [1] 1 Department of Traditional Chinese Medicine (TCM) Geriatrics, Huadong Hospital Affiliated to Fudan University , Shanghai, China
                [2] 2 Translational Medicine Department, GeneScience Pharmaceuticals Co. Ltd. , Changchun, China
                [3] 3 Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine , Shanghai, China
                Author notes

                Edited by: Maria Rosaria Galdiero, University of Naples Federico II, Italy

                Reviewed by: Huiwu Ouyang, Cold Spring Harbor Laboratory, United States; Manoj Kumar Kashyap, Amity University Gurgaon, India

                *Correspondence: Li Han, tcmtoto@ 123456163.com ; Jiacheng Li, lijiacheng@ 123456shutcm.edu.cn

                This article was submitted to Cancer Immunity and Immunotherapy, a section of the journal Frontiers in Immunology

                Article
                10.3389/fimmu.2022.1052182
                9755665
                36532007
                83adc12b-1605-4184-aca6-ca48ac829257
                Copyright © 2022 Cheng, Wei, Fu, Li and Han

                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
                : 23 September 2022
                : 21 November 2022
                Page count
                Figures: 10, Tables: 0, Equations: 2, References: 37, Pages: 16, Words: 6729
                Categories
                Immunology
                Original Research

                Immunology
                colon adenocarcinoma,scrna-seq,immunotherapy,signature model,prognostic biomarkers
                Immunology
                colon adenocarcinoma, scrna-seq, immunotherapy, signature model, prognostic biomarkers

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