A novel Anoikis and immune-related genes marked prognostic signature for colorectal cancer

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Abstract

Colorectal cancer (CRC) is second most commonly diagnosed cancer with high morbidity and mortality. The heterogeneity of CRC makes clinical treatment tremendously challenging. Here, we aimed to comprehensively analyze the prognosis of CRC patients based on ANOIKIS- and immune-related genes. ANOIKIS-related genes were identified by differentially analysis of high anoikis score group (ANOIKIS_high group) and low anoikis score group (ANOIKIS_low group) divided by the cutoff value of anoikis score. Immune-related genes were screened by differentially analysis of high immune score group (ImmuneScore_high group) and low immune score group (ImmuneScore_low group) classified by the cutoff value of ImmuneScore. Prognostic ANOIKIS- and immune-related genes were identified by univariate Cox regression analysis. Multivariate Cox regression analysis were used for prognostic model construction. Ferroptosis expression profiles, the infiltration of immune cells, and the somatic mutation status were analyzed and compared. Univariate and multivariate Cox-regression analyses were performed to identify independent prognostic factors for CRC patient. Nomogram that contained the independent prognostic factors was established to predict 1-, 3-, and 5-year OS probability of CRC patients. Three ANOIKIS- and immune-related signatures were applied to construct a prognostic model, which divided the CRC patients into high-risk and low-risk groups. The patients with high-risk scores had obviously shorter OSs than those with low-risk scores. The time dependent ROC curve indicated that the risk score model had a stable performance to predict survival rates. Notably, the age, pathologic T, and risk score could be used independent indicators for CRC prognosis prediction. A nomogram containing the independent prognostic factors showed that the nomogram accurately predicted 1-, 3-, and 5-year survival rates of CRC patients. In our research, a novel prognostic model was developed based on ANOIKIS- and immune-related genes in CRC, which could be used for prognostic prediction of CRC patients.

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Cancer statistics, 2020

Rebecca Siegel, Kimberly D Miller, Ahmedin Jemal (2020)

Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths that will occur in the United States and compiles the most recent data on population-based cancer occurrence. Incidence data (through 2016) 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 2017) were collected by the National Center for Health Statistics. In 2020, 1,806,590 new cancer cases and 606,520 cancer deaths are projected to occur in the United States. The cancer death rate rose until 1991, then fell continuously through 2017, resulting in an overall decline of 29% that translates into an estimated 2.9 million fewer cancer deaths than would have occurred if peak rates had persisted. This progress is driven by long-term declines in death rates for the 4 leading cancers (lung, colorectal, breast, prostate); however, over the past decade (2008-2017), reductions slowed for female breast and colorectal cancers, and halted for prostate cancer. In contrast, declines accelerated for lung cancer, from 3% annually during 2008 through 2013 to 5% during 2013 through 2017 in men and from 2% to almost 4% in women, spurring the largest ever single-year drop in overall cancer mortality of 2.2% from 2016 to 2017. Yet lung cancer still caused more deaths in 2017 than breast, prostate, colorectal, and brain cancers combined. Recent mortality declines were also dramatic for melanoma of the skin in the wake of US Food and Drug Administration approval of new therapies for metastatic disease, escalating to 7% annually during 2013 through 2017 from 1% during 2006 through 2010 in men and women aged 50 to 64 years and from 2% to 3% in those aged 20 to 49 years; annual declines of 5% to 6% in individuals aged 65 years and older are particularly striking because rates in this age group were increasing prior to 2013. It is also notable that long-term rapid increases in liver cancer mortality have attenuated in women and stabilized in men. In summary, slowing momentum for some cancers amenable to early detection is juxtaposed with notable gains for other common cancers.

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Colorectal cancer

Evelien Dekker, Pieter Tanis, Jasper Vleugels … (2019)

Several decades ago, colorectal cancer was infrequently diagnosed. Nowadays, it is the world's fourth most deadly cancer with almost 900 000 deaths annually. Besides an ageing population and dietary habits of high-income countries, unfavourable risk factors such as obesity, lack of physical exercise, and smoking increase the risk of colorectal cancer. Advancements in pathophysiological understanding have increased the array of treatment options for local and advanced disease leading to individual treatment plans. Treatments include endoscopic and surgical local excision, downstaging preoperative radiotherapy and systemic therapy, extensive surgery for locoregional and metastatic disease, local ablative therapies for metastases, and palliative chemotherapy, targeted therapy, and immunotherapy. Although these new treatment options have doubled overall survival for advanced disease to 3 years, survival is still best for those with non-metastasised disease. As the disease only becomes symptomatic at an advanced stage, worldwide organised screening programmes are being implemented, which aim to increase early detection and reduce morbidity and mortality from colorectal cancer.

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The Gene Expression Omnibus Database.

Emily Clough, Tanya Barrett (2016)

The Gene Expression Omnibus (GEO) database is an international public repository that archives and freely distributes high-throughput gene expression and other functional genomics data sets. Created in 2000 as a worldwide resource for gene expression studies, GEO has evolved with rapidly changing technologies and now accepts high-throughput data for many other data applications, including those that examine genome methylation, chromatin structure, and genome-protein interactions. GEO supports community-derived reporting standards that specify provision of several critical study elements including raw data, processed data, and descriptive metadata. The database not only provides access to data for tens of thousands of studies, but also offers various Web-based tools and strategies that enable users to locate data relevant to their specific interests, as well as to visualize and analyze the data. This chapter includes detailed descriptions of methods to query and download GEO data and use the analysis and visualization tools. The GEO homepage is at http://www.ncbi.nlm.nih.gov/geo/.

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Author and article information

Contributors

Zhiqiang Cai

Journal

Journal ID (nlm-ta): Medicine (Baltimore)

Journal ID (iso-abbrev): Medicine (Baltimore)

Journal ID (publisher-id): MD

Title: Medicine

Publisher: Lippincott Williams & Wilkins (Hagerstown, MD )

ISSN (Print): 0025-7974

ISSN (Electronic): 1536-5964

Publication date Collection: 18 November 2022

Publication date (Electronic): 18 November 2022

Volume: 101

Issue: 46

Electronic Location Identifier: e31127

Affiliations

[a ] Department of Radiation and Medical Oncology, Hubei Key Laboratory of Tumor Biological Behaviors, Hubei Clinical Cancer Study Center, Zhongnan Hospital of Wuhan University, Wuhan, China.

Author notes

* Correspondence: Fuxiang Zhou, Department of Radiation and Medical Oncology, Hubei Key Laboratory of Tumor Biological Behaviors, Hubei Clinical Cancer Study Center, Zhongnan Hospital of Wuhan University, No. 169 Donghu Road, Wuchang District, Wuhan 430071, China (e-mail: 153273617@ 123456qq.com ).

Article

Accession ID: 00024

DOI: 10.1097/MD.0000000000031127

PMC ID: 9678618

PubMed ID: 36401385

SO-VID: 7cd7ef58-167f-4ed4-8017-d69038e9642a

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal.

History

Date received : 17 August 2021

Date received : 9 September 2022

Date accepted : 13 September 2022

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Keywords: anoikis and immune-related genes,colorectal cancer,nomogram,prognostic model

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Keywords: anoikis and immune-related genes, colorectal cancer, nomogram, prognostic model

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A novel Anoikis and immune-related genes marked prognostic signature for colorectal cancer

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Karger: Oncology

Most cited references 35

Cancer statistics, 2020

Colorectal cancer

The Gene Expression Omnibus Database.

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