M2-type macrophage signature genes and the immune microenvironment of colon cancer

doi:10.3877/cma.j.issn.2095-3224.2024.04.006

Abstract

Abstract:

Objective

We aimed to identify for macrophage-2 (M2) characteristic genes with hub prognostic value through machine learning combined with bioinformatics techniques, and to explore their relationship with the immune microenvironment and tumor immunotherapy.

Methods

This study collected the TCGA-COAD dataset and the dataset (GSE39582) from the GEO database. The CIBERSORT method was used to calculate the levels of M2-type macrophages in tumor samples, and characteristic genes were screened through correlation analysis, univariate and multivariate Cox regression analysis, and the random survival forest algorithm. The ESTIMATE algorithm was employed to calculate the immune microenvironment scores (stromal score and immune score) of tumor samples, and to study the characteristic genes and their relationships, finally validating in an immunotherapy cohort.

Results

This study identified PPM1M and MRAS as core prognostic genes determined by machine learning. In the TCGA data, populations with high expression levels of MRAS had shorter progression-free survival (P=0.0013). In the GEO data, high expression of PPM1M gene (P=0.031) and MRAS gene (P=0.002) were both associated with recurrence. Both PPM1M and MRAS genes were positively correlated with tumor immune score and stromal score, and positively correlated with the levels of suppressive regulatory T cells (Treg). Finally, in the evaluation of immunotherapy, patients with high expression of PPM1M and MRAS had better prognosis after receiving immunotherapy.

Conclusion

Characteristic genes of M2-type macrophages determined by machine learning are related to survival, recurrence, and progression. In the immune microenvironment, PPM1M and MRAS are both positively correlated with suppressive tumor immune components and stromal components. Furthermore, PPM1M and MRAS may serve as novel biomarkers for the efficacy of immunotherapy.

Key words: Colon neoplasms, M2 type macrophage, Random survival forest, Immune microenvironment, Survival analysis

Jun Zhu, Jiawei Song, Yihuan Qiao, Yajie Guo, Shuai Liu, Yu Jiang, Jipeng Li. M2-type macrophage signature genes and the immune microenvironment of colon cancer[J]. Chinese Journal of Colorectal Diseases(Electronic Edition), 2024, 13(04): 303-311.

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URL: https://zhjzcjbdzzz.cma-cmc.com.cn/EN/10.3877/cma.j.issn.2095-3224.2024.04.006

https://zhjzcjbdzzz.cma-cmc.com.cn/EN/Y2024/V13/I04/303

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References 35

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特征	TCGA-COAD数据集（n=435）	GSE39582数据集（n=585）
年龄（岁）	67.2±13.0	66.9±13.2
性别
女	208（47.82）	263（44.96）
男	227（52.18）	322（55.04）
T分期
T1	8（1.84）	12（2.05）
T2	74（17.01）	49（8.38）
T3	299（68.74）	379（64.79）
T4	54（12.41）	119（20.34）
NA	0（0）	26（4.44）
M分期
M0	330（75.86）	499（85.30）
M1	62（14.25）	61（10.43）
NA	43（9.89）	25（4.27）
N分期
N0	257（59.08）	314（53.68）
N1	101（23.22）	137（23.42）
N2	77（17.70）	100（17.09）
NA	0（0）	34（5.81）
MSI状态
MSI-H	76（17.47）	77（13.16）
MSI-L/MSS	323（74.25）	459（78.46）
NA	36（8.28）	49（8.38）

特征	TCGA-COAD数据集（n=435）	GSE39582数据集（n=585）
年龄（岁）	67.2±13.0	66.9±13.2
性别
女	208（47.82）	263（44.96）
男	227（52.18）	322（55.04）
T分期
T1	8（1.84）	12（2.05）
T2	74（17.01）	49（8.38）
T3	299（68.74）	379（64.79）
T4	54（12.41）	119（20.34）
NA	0（0）	26（4.44）
M分期
M0	330（75.86）	499（85.30）
M1	62（14.25）	61（10.43）
NA	43（9.89）	25（4.27）
N分期
N0	257（59.08）	314（53.68）
N1	101（23.22）	137（23.42）
N2	77（17.70）	100（17.09）
NA	0（0）	34（5.81）
MSI状态
MSI-H	76（17.47）	77（13.16）
MSI-L/MSS	323（74.25）	459（78.46）
NA	36（8.28）	49（8.38）

基因名称	评价指标	评价方法	相关系数	P值
PPM1M	M2型巨噬细胞	MCPCOUNTER	0.719	<0.001
PPM1M	M2型巨噬细胞	QUANTISEQ	0.544	<0.001
PPM1M	M2型巨噬细胞	XCELL	0.312	<0.001
PPM1M	调节性T淋巴细胞	QUANTISEQ	0.492	<0.001
PPM1M	免疫评分	ESTIMATE	0.660	0.066
PPM1M	间质评分	ESTIMATE	0.590	<0.001
PPM1M	肿瘤突变负荷	Varscan	0.144	0.009
PPM1M	PDCD1	Spearman	0.540	<0.001
PPM1M	CD274	Spearman	0.500	<0.001
MRAS	M2型巨噬细胞	MCPCOUNTER	0.815	<0.001
MRAS	M2型巨噬细胞	QUANTISEQ	0.533	<0.001
MRAS	M2型巨噬细胞	XCELL	0.348	<0.001
MRAS	调节性T淋巴细胞	QUANTISEQ	0.499	<0.001
MRAS	免疫评分	ESTIMATE	0.650	<0.001
MRAS	间质评分	ESTIMATE	0.940	<0.001
MRAS	肿瘤突变负荷	Varscan	0.073	0.191
MRAS	PDCD1	Spearman	0.550	<0.001
MRAS	CD274	Spearman	0.530	<0.001
MRAS	PPM1M	Spearman	0.770	<0.001

基因名称	评价指标	评价方法	相关系数	P值
PPM1M	M2型巨噬细胞	MCPCOUNTER	0.719	<0.001
PPM1M	M2型巨噬细胞	QUANTISEQ	0.544	<0.001
PPM1M	M2型巨噬细胞	XCELL	0.312	<0.001
PPM1M	调节性T淋巴细胞	QUANTISEQ	0.492	<0.001
PPM1M	免疫评分	ESTIMATE	0.660	0.066
PPM1M	间质评分	ESTIMATE	0.590	<0.001
PPM1M	肿瘤突变负荷	Varscan	0.144	0.009
PPM1M	PDCD1	Spearman	0.540	<0.001
PPM1M	CD274	Spearman	0.500	<0.001
MRAS	M2型巨噬细胞	MCPCOUNTER	0.815	<0.001
MRAS	M2型巨噬细胞	QUANTISEQ	0.533	<0.001
MRAS	M2型巨噬细胞	XCELL	0.348	<0.001
MRAS	调节性T淋巴细胞	QUANTISEQ	0.499	<0.001
MRAS	免疫评分	ESTIMATE	0.650	<0.001
MRAS	间质评分	ESTIMATE	0.940	<0.001
MRAS	肿瘤突变负荷	Varscan	0.073	0.191
MRAS	PDCD1	Spearman	0.550	<0.001
MRAS	CD274	Spearman	0.530	<0.001
MRAS	PPM1M	Spearman	0.770	<0.001

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