CDKN2A was a cuproptosis-related gene in regulating chemotherapy resistance by the MAGE-A family in breast cancer: based on artificial intelligence (AI)-constructed pan-cancer risk model

Hong Wan; Xiaowei Yang; Guopeng Sang; Zhifan Ruan; Zichen Ling; Mingzhao Zhang; Chang Liu; Xiangyang Hu; Tao Guo; Juntong He; Defeng Liu; Jing Pei

doi:10.18632/aging.205125

CDKN2A was a cuproptosis-related gene in regulating chemotherapy resistance by the MAGE-A family in breast cancer: based on artificial intelligence (AI)-constructed pan-cancer risk model

Aging (Albany NY). 2023 Oct 19;15(20):11244-11267. doi: 10.18632/aging.205125. Epub 2023 Oct 19.

Authors

Hong Wan^{1

2}, Xiaowei Yang^{1

3}, Guopeng Sang^{1

3}, Zhifan Ruan^{1

3}, Zichen Ling^{1

3}, Mingzhao Zhang^{1

3}, Chang Liu^{1

3}, Xiangyang Hu⁴, Tao Guo^{1

2}, Juntong He^{1

2}, Defeng Liu^{1

2}, Jing Pei^{1

3}

Affiliations

¹ Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
² Anhui Public Health Clinical Center, Hefei, Anhui, China.
³ Department of Breast Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
⁴ Department of Pathology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.

Abstract

Background: Before the discovery of cuproptosis, copper-loaded nanoparticle is a wildly applied strategy for enhancing the tumor-cell-killing effect of chemotherapy. Although copper(ii)-related researches are wide, details of cuproptosis-related bioprocess in pan-cancer are not clear yet now, especially for prognosis and drug sensitivity prediction yet now.

Methods: In this study, VOSviewer is used for the literature review, and R4.2.0 is used for data analysis. Public data are collected from TCGA and GEO, local breast cancer cohort is collected to verify the expression level of CDKN2A.

Results: 7036 published articles exhibited a time-dependent linear relationship (R=0.9781, p<0.0001), and breast cancer (33.4%) is the most researched topic. Cuproptosis-related-genes (CRGs)-based unsupervised clustering divides pan-cancer subgroups into four groups (CRG subgroup) with differences in prognosis and tumor immunity. 44 tumor-driver-genes (TDGs)-based prediction model of drug sensitivity and prognosis is constructed by artificial intelligence (AI). Based on TDGs and clinical features, a nomogram is (C- index: 0.7, p= 6.958e- 12) constructed to predict the prognosis of breast cancer. Importance analysis identifies CDKN2A has a pivotal role in AI modeling, whose higher expression indicates worse prognosis in breast cancer. Furthermore, inhibition of CDKN2A down-regulates decreases Snail1, Twist1, Zeb1, vimentin and MMP9, while E-cadherin is increased. Besides, inhibition of CDKN2A also decreases the expression of MEGEA4, phosphorylated STAT3, PD-L1, and caspase3, while cleaved-caspase3 is increased. Finally, we find down-regulation of CDKN2A or MAGEA inhibits cell migration and wound healing, respectively.

Conclusions: AI identified CRG subgroups in pan-cancer based on CRGs-related TDGs, and 44-gene-based AI modeling is a novel tool to identify chemotherapy sensitivity in breast cancer, in which CDKN2A/MAGEA4 pathway played the most important role.

Keywords: CDKN2A; artificial intelligence (AI); breast cancer; cuproptosis; model.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Apoptosis
Artificial Intelligence
Breast Neoplasms* / drug therapy
Breast Neoplasms* / genetics
Copper
Cyclin-Dependent Kinase Inhibitor p16
Female
Genes, p16
Humans

Substances

CDKN2A protein, human
Copper
Cyclin-Dependent Kinase Inhibitor p16

Supplementary concepts

Breast Cancer, Familial