Development and Validation of a 7-Gene Inflammatory Signature Forecasts Prognosis and Diverse Immune Landscape in Lung Adenocarcinoma

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Abstract

Background: Inflammatory responses are strongly linked with tumorigenesis and cancer development. This research aimed to construct and validate a novel inflammation response–related risk predictive signature for forecasting the prognosis of patients with LUAD.

Methods: Differential expression analysis, univariate Cox, LASSO, and multivariate Cox regression analyses of 200 inflammatory response–related genes (IRRG) were performed to establish a risk predictive model in the TCGA training cohort. The performance of the IRRG model was verified in eight GEO datasets. GSEA analysis, ESTIMATE algorithms, and ssGSEA analysis were applied to elucidate the possible mechanisms. Furthermore, the relationship analysis between risk score, model genes, and chemosensitivity was performed. Last, we verified the protein expression of seven model genes by immunohistochemical staining or Western blotting.

Results: We constructed a novel inflammatory response–related 7-gene signature (MMP14, BTG2, LAMP3, CCL20, TLR2, IL7R, and PCDH7). Patients in the high-risk group presented markedly decreased survival time in the TCGA cohort and eight GEO cohorts than the low-risk group. Interestingly, multiple pathways related to immune response were suppressed in high-risk groups. The low infiltration levels of B cell, dendritic cell, natural killer cell, and eosinophil can significantly affect the unsatisfactory prognosis of the high-risk group in LUAD. Moreover, the tumor cells’ sensitivity to anticancer drugs was markedly related to risk scores and model genes. The protein expression of seven model genes was consistent with the mRNA expression.

Conclusion: Our IRRG prognostic model can effectively forecast LUAD prognosis and is tightly related to immune infiltration.

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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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Inflammation predisposes to the development of cancer and promotes all stages of tumorigenesis. Cancer cells as well as surrounding stromal and inflammatory cells engage in well-orchestrated reciprocal interactions to form an inflammatory tumor microenvironment (TME). Cells within the TME are highly plastic, continuously changing their phenotypic and functional characteristics. Here we review the origins of inflammation in tumors, and the mechanisms whereby inflammation drives tumor initiation, growth, progression and metastasis. We discuss how tumor promoting inflammation closely resembles inflammatory processes typically found during development, immunity, maintenance of tissue homeostasis or tissue repair, and illuminate the distinctions between tissue-protective and pro-tumorigenic inflammation, including spatio-temporal considerations. Defining the cornerstone rules of engagement governing molecular and cellular mechanisms of tumor-promoting inflammation will be essential for the further development of anti-cancer therapies. Grivennikov and Greten review the mechanisms underlying the initiation of pro-tumorigenic inflammatory responses, how these evolve throughout the different stages of tumor development and the plasticity of the cells within the tumor microenvironment.

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Cell cycle control in cancer

Helen K. Matthews, Cosetta Bertoli, Robertus A. M. de Bruin (2022)

Cancer is a group of diseases in which cells divide continuously and excessively. Cell division is tightly regulated by multiple evolutionarily conserved cell cycle control mechanisms, to ensure the production of two genetically identical cells. Cell cycle checkpoints operate as DNA surveillance mechanisms that prevent the accumulation and propagation of genetic errors during cell division. Checkpoints can delay cell cycle progression or, in response to irreparable DNA damage, induce cell cycle exit or cell death. Cancer-associated mutations that perturb cell cycle control allow continuous cell division chiefly by compromising the ability of cells to exit the cell cycle. Continuous rounds of division, however, create increased reliance on other cell cycle control mechanisms to prevent catastrophic levels of damage and maintain cell viability. New detailed insights into cell cycle control mechanisms and their role in cancer reveal how these dependencies can be best exploited in cancer treatment.

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Author and article information

Contributors

Aitao Nai: URI : https://loop.frontiersin.org/people/1445578/overview

Feng Ma: URI : https://loop.frontiersin.org/people/1377171/overview

Zirui He: URI : https://loop.frontiersin.org/people/1666046/overview

Journal

Journal ID (nlm-ta): Front Mol Biosci

Journal ID (iso-abbrev): Front Mol Biosci

Journal ID (publisher-id): Front. Mol. Biosci.

Title: Frontiers in Molecular Biosciences

Publisher: Frontiers Media S.A.

ISSN (Electronic): 2296-889X

Publication date (Electronic): 15 March 2022

Publication date Collection: 2022

Volume: 9

Electronic Location Identifier: 822739

Affiliations

[1] ¹ Department of Oncology , The First Affiliated Hospital of Jinan University , Guangzhou, China

[2] ² Department of Oncology , ZhongShan Torch Development Zone Hospital , Zhongshan, China

Author notes

Edited by: Imtaiyaz Hassan, Jamia Millia Islamia, India

Reviewed by: Yao Jiang, The Affiliated Hospital of Southwest Medical University, China

Chaoyuan Huang, Guangzhou University of Chinese Medicine, China

Jinhui Liu, Nanjing Medical University, China

*Correspondence: Meng Xu, 641704010@ 123456qq.com ; Jian Song, 1084805428@ 123456qq.com

This article was submitted to Molecular Diagnostics and Therapeutics, a section of the journal Frontiers in Molecular Biosciences

[ † ]

These authors have contributed equally to this work

Article

Publisher ID: 822739

DOI: 10.3389/fmolb.2022.822739

PMC ID: 8964604

PubMed ID: 35372503

SO-VID: c92706fa-a0b1-4415-8f5d-12d6852debb0

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 : 26 November 2021

Date accepted : 15 February 2022

Funding

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

Award ID: 81774376

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