FAM198B promotes colorectal cancer progression by regulating the polarization of tumor-associated macrophages via the SMAD2 signaling pathway

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ABSTRACT

Colorectal cancer (CRC) is one of the most common malignant tumors. Tumor-associated macrophages (TAMs) promote the progression of CRC, but the mechanism is not completely clear. The present study aimed to reveal the expression and function of FAM198B in TAMs, and the role of FAM198B in mediating macrophage polarization in CRC. The role of FAM198B in macrophage activity, cell cycle, and angiogenesis was evaluated by CCK-8 assay, flow cytometry, and vasculogenic mimicry assay. The effects of FAM198B on macrophage polarization were determined by flow cytometry. The function of FAM198B-mediated macrophage polarization on CRC progression was evaluated by transwell assays. Bioinformatic analyses and rescue assays were performed to identify biological functions and signaling pathways involved in FAM198B regulation of macrophage polarization. Increased FAM198B expression in TAMs is negatively associated with poor CRC prognosis. Functional assays showed that FAM198B promotes M2 macrophage polarization, which leads to CRC cell proliferation, migration, and invasion. Mechanistically, FAM198B regulates the M2 polarization of macrophages by targeting SMAD2, identifying the SMAD2 pathway as a mechanism by which FAM198B promotes CRC progression through regulating macrophage polarization. These findings provide a possible molecular mechanism for FAM198B in TAMs in CRC and suggest that FAM198B may be a novel therapeutic target in CRC.

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Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

Hyuna Sung, Jacques Ferlay, Rebecca Siegel … (2021)

This article provides an update on the global cancer burden using the GLOBOCAN 2020 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer. Worldwide, an estimated 19.3 million new cancer cases (18.1 million excluding nonmelanoma skin cancer) and almost 10.0 million cancer deaths (9.9 million excluding nonmelanoma skin cancer) occurred in 2020. Female breast cancer has surpassed lung cancer as the most commonly diagnosed cancer, with an estimated 2.3 million new cases (11.7%), followed by lung (11.4%), colorectal (10.0 %), prostate (7.3%), and stomach (5.6%) cancers. Lung cancer remained the leading cause of cancer death, with an estimated 1.8 million deaths (18%), followed by colorectal (9.4%), liver (8.3%), stomach (7.7%), and female breast (6.9%) cancers. Overall incidence was from 2-fold to 3-fold higher in transitioned versus transitioning countries for both sexes, whereas mortality varied <2-fold for men and little for women. Death rates for female breast and cervical cancers, however, were considerably higher in transitioning versus transitioned countries (15.0 vs 12.8 per 100,000 and 12.4 vs 5.2 per 100,000, respectively). The global cancer burden is expected to be 28.4 million cases in 2040, a 47% rise from 2020, with a larger increase in transitioning (64% to 95%) versus transitioned (32% to 56%) countries due to demographic changes, although this may be further exacerbated by increasing risk factors associated with globalization and a growing economy. Efforts to build a sustainable infrastructure for the dissemination of cancer prevention measures and provision of cancer care in transitioning countries is critical for global cancer control.

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STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets

Damian Szklarczyk, Annika L Gable, David Lyon … (2018)

Abstract Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biological phenomena, but the available information on protein–protein associations is incomplete and exhibits varying levels of annotation granularity and reliability. The STRING database aims to collect, score and integrate all publicly available sources of protein–protein interaction information, and to complement these with computational predictions. Its goal is to achieve a comprehensive and objective global network, including direct (physical) as well as indirect (functional) interactions. The latest version of STRING (11.0) more than doubles the number of organisms it covers, to 5090. The most important new feature is an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input. For the enrichment analysis, STRING implements well-known classification systems such as Gene Ontology and KEGG, but also offers additional, new classification systems based on high-throughput text-mining as well as on a hierarchical clustering of the association network itself. The STRING resource is available online at https://string-db.org/.

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GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses

Zefang Tang, Chenwei Li, Boxi Kang … (2017)

Abstract Tremendous amount of RNA sequencing data have been produced by large consortium projects such as TCGA and GTEx, creating new opportunities for data mining and deeper understanding of gene functions. While certain existing web servers are valuable and widely used, many expression analysis functions needed by experimental biologists are still not adequately addressed by these tools. We introduce GEPIA (Gene Expression Profiling Interactive Analysis), a web-based tool to deliver fast and customizable functionalities based on TCGA and GTEx data. GEPIA provides key interactive and customizable functions including differential expression analysis, profiling plotting, correlation analysis, patient survival analysis, similar gene detection and dimensionality reduction analysis. The comprehensive expression analyses with simple clicking through GEPIA greatly facilitate data mining in wide research areas, scientific discussion and the therapeutic discovery process. GEPIA fills in the gap between cancer genomics big data and the delivery of integrated information to end users, thus helping unleash the value of the current data resources. GEPIA is available at http://gepia.cancer-pku.cn/.

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Author and article information

Journal

Journal ID (nlm-ta): Bioengineered

Journal ID (iso-abbrev): Bioengineered

Title: Bioengineered

Publisher: Taylor & Francis

ISSN (Print): 2165-5979

ISSN (Electronic): 2165-5987

Publication date (Electronic, pub): 19 May 2022

Publication date (Electronic, collection): 2022

Publication date PMC-release: 19 May 2022

Volume: 13

Issue: 5

Pages: 12435-12445

Affiliations

[a ]College of Life Sciences, Zhejiang Chinese Medical University; , Hangzhou, Zhejiang, China

[b ]Cancer Institute of Integrated Traditional Chinese and Western Medicine, Key Laboratory of Cancer Prevention and Therapy Combining Traditional Chinese and Western Medicine, Zhejiang Academy of Traditional Chinese Medicine; , Hangzhou, Zhejiang, China

[c ]Academy of Chinese Medical Sciences, Zhejiang Chinese Medical University; , Hangzhou, Zhejiang, China

Author notes

CONTACT Wei Chen viogro@ 123456163.com Cancer Institute of Integrated Traditional Chinese and Western Medicine, Key Laboratory of Cancer Prevention and Therapy Combining Traditional Chinese and Western Medicine of Zhejiang Province; , Zhejiang Academy of Traditional Chinese Medicine, Tongde Hospital of Zhejiang Province, NO.234, Gu Cui Road, Hangzhou, 310012, Zhejiang, China

Hao Liu coioler@ 123456163.com

Ying Cai yingcai1112@ 123456163.com Cancer Institute of Integrated Traditional Chinese and Western Medicine, Key Laboratory of Cancer Prevention and Therapy Combining Traditional Chinese and Western Medicine Zhejiang Academy of Traditional Chinese Medicine; , Hangzhou, China

[*]

These authors contributed to this work equally and should be regarded as co-first authors.

Article

Publisher ID: 2075300

DOI: 10.1080/21655979.2022.2075300

PMC ID: 9276016

PubMed ID: 35587159

SO-VID: cb8c728f-fc25-4c2d-ad56-881e4da5fd0d

License:

This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

FAM198B promotes colorectal cancer progression by regulating the polarization of tumor-associated macrophages via the SMAD2 signaling pathway

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Online interactive cancer simulations and demos

Most cited references 38

Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets

GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses

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