The latest hot spot: the use of copper death related genes for tumor prognosis typing!

Introduction

Copper death is a new type of cell death , Highly correlated with mitochondrial metabolism . However , Copper death related genes （CRG） Its role in renal clear cell carcinoma is unclear .

Background introduction

Copper death is one of the most novel hot spots this year . The concept of copper death was introduced on March 18 this year science Published on . Today, I'd like to bring you a new article about the prognosis of tumor typing by copper death related genes . This article is published in genes On , stay science The document will be received within two months , titled A Novel Cuproptosis-Related Prognostic Gene Signature and Validation of Differential Expression in Clear Cell Renal Cell Carcinoma.

Data is introduced

come from TCGA and GEO Public data for .

Result analysis

01

Expression and mutation of copper death related genes

The author chooses from the literature 10 Copper death related genes （CDKN2A,FDX1,DLD,DLAT,LIAS,GLS,LIPT1,MTF1,PDHA1 and PDHB）. In comparison TCGA Clear cell carcinoma of the kidney （ccRCC） The differential expression of genes between the patient's tumor and normal tissue , Only CDKN2A The expression of , and DLAT、DLD、FDX1、GLS、PDHA1 and PDHB stay ccRCC The expression in tissues was significantly lower than that in normal tissues （ chart 1A）. The authors studied the correlation between the expression of different genes , Found a strong association between genes related to copper death ( chart 1B).

chart 1

Besides , The author explores ccRCC Mutation of copper death related genes in the sample , Including somatic mutations and CNV etc. （ chart 1C-E）. have CNV The missing genes are PDHB and CDKN2A. With the highest CNV The amplified genes are GLS .

According to the classification type of mutation , Missense mutation is the most common type of mutation （ chart 1D）.SNP Is the most common type of variation ,C > T In single nucleotide variation (SNV) Top of the category .DLD (1%) and MTF1 (1%) It shows a higher mutation frequency than other genes ( chart 1E).

02

Functional enrichment and PPI The Internet

The author passes GO and KEGG The database analyzed the related pathways of copper death gene in renal cell carcinoma . GO The main biological process of copper death involved in the analysis is acetyl coenzyme of pyruvate A The process of biosynthesis 、 Acetyl coenzyme A The process of biosynthesis 、 Tricarboxylic acid cycle 、 Acetyl coenzyme A The metabolic process 、 Thioester biosynthesis process 、 Mitochondrial matrix, etc （ chart 2A）. stay KEGG Pathway enrichment analysis CRGs And TCA loop 、 Pyruvate metabolism 、 Glycolysis / Gluconeogenesis 、 Carbon metabolism 、 Lipoic acid metabolism 、 Central carbon metabolism in cancer （ chart 2B）. protein - Protein interactions （PPI） The analysis shows that DLD、PDHB、DLAT and PDHA1 yes hub gene .

chart 2

03

To construct the prognosis model of copper death

The authors further evaluated the association between copper death gene expression and prognosis of renal clear cell carcinoma . Results show , In a single variable Cox In the risk regression model , except GLS All other copper death genes are associated with overall survival （OS） Highly correlated .CDKN2A Showing carcinogenic characteristics , Its overexpression is related to ccRCC Poor patient survival is associated with . other 9 A gene （FDX1、LIPT1、LIAS、DLD、DLAT、PDHA1、PDHB、MTF1 and GLS） High expression and ccRCC A significantly higher survival rate in , It shows the characteristics of tumor suppressor .

then , The author constructed ccRCC In patients OS and PFS Prognosis of copper death . about ccRCC Patient's OS result , Three genes were selected and their regression coefficients were used to construct the prognostic score ：Scoreos = -0.44 × FDX1-0.28 × DLAT + 0.23 × CDKN2A. Copper death signature A higher risk score and a lower risk score OS significant correlation （HR=2.72（2.01-3.68）,P=1.76E-07, chart 3A-B）. The author also applies the risk scoring model to estimate 1 year 、3 Years and 5 year OS（ chart 3C、F）. stay 1 year 、3 Years and 5 year ROC In the curve ,AUC The prediction accuracy of the evaluation is 0.652、0.633 and 0.658. At age 、 In different subgroups of gender and pathological stage , The risk score also has a good performance . All in all , The risk characteristics related to copper death show that ccRCC There was a significant correlation between the survival rate of .

chart 3

04

Development and verification of nomograph

In order to promote the clinical application of predictive models , The author integrates the data from TCGA Clinical information and genetic characteristics of patients , Implemented multivariable Cox Regression model to develop nomograms . Nomographs are applied to OS and PFS result （ chart 4）. Results show ,OS Of c Index is 0.77,PFS by 0.824, This reflects the relatively excellent prediction performance of nomograms . meanwhile , The calibration chart shows the results at 1、3 and 5 Predicted annual survival OS or PFS Compared with the observation OS or PFS Good consistency between （ chart 4C,F）.

chart 4

05

Verification of differential expression of copper death gene

Use two independent validations GEO Data sets （GSE40435 and GSE53757） Conduct a meta-analysis .CDKN2A stay ccRCC Significant high expression in tissues , and DLAT、FDX1 and LIAS stay ccRCC The expression level in tissues was significantly down regulated （ chart 5A、B）.

Due to the heterogeneity among the three data sets , Therefore, a random effect model was used for meta-analysis . Results show ,CDKN2A、DLAT and FDX1 stay ccRCC And normal tissues , Reveals FDX1 and DLAT As a tumor suppressor gene and CDKN2A As a proto oncogene .

chart 5

06

Correlation between copper death gene and immune infiltration level

The author examined CDKN2A、DLAT、FDX1 and LIAS And ccRCC The relationship between immune infiltration in .CDKN2A The expression level of CD8+ T There was a positive correlation between the level of cellular immune infiltration （P = 2.89E-02）, Negative correlation with macrophages （P = 2.89E-02）（ chart 6A）.DLAT The level of expression and B cells 、 Macrophages 、 There was a positive correlation between the level of immune infiltration of neutrophils and dendritic cells （ chart 6B）.FDX1 The level of expression and B The abundance of cells and macrophages was positively correlated （ chart 6C）.LIAS Expression and CD8+ T cells 、 Macrophages and neutrophils There is a positive correlation between abundance .

chart 6

07

Differential expression of copper death gene in different pathological stages and histological grades

Four genes （CDKN2A、DLAT、FDX1 and LIAS） The level of expression is ccRCC It is different in different pathological stages and histological grades （ chart 7）. To be specific , Regardless of tumor stage or histological grade ,FDX1 and LIAS The expression showed a downward trend , and CDKN2A The expression is on the rise . Sum up , The expression of copper death related genes may be related to disease grade and ccRCC The presence of necrosis .

chart 7

Editor's summary

This is a very traditional article about tumor classification and prognosis , But the biggest innovation is the use of copper death related genes as signature, So it took less than two months from submission to receipt . We may also try to analyze the role of copper death related genes in other cancer types along the idea of copper death .