Research Article

Roles of the Immune/Methylation/Autophagy Landscape on Single-Cell Genotypes and Stroke Risk in Breast Cancer Microenvironment

Figure 1

Identification and screening of different immune, methylation, and autophagy-related genes (IMAAGs). (a) The experimental design. RNA-seq and clinical data from 1109 BRCA samples were retrieved from TCGA database. A total of immune-related genes, 16 m6A methylation-related genes, and 222 autophagy-related genes were included in this study. Breast Cancer Recurrence Risk Score (BCRRS) and Breast Cancer Prognostic Risk Score (BCPRS) systems were constructed based on these genes. The BRCA nomogram prediction model, potential drug-ceRNA network, PPI network, and single-cell analysis were then constructed. (b) Data error rate of the classification tree function. (c) Important values of the genes in the random forest model. (d) A forest chart showing factors selected from the single-factor COX regression analysis (). (e) Interaction of the immune, methylation, and autophagy-related genes. The size of each cell represents the survival effect of each gene. The correlation coefficient estimated by Spearman’s correlation analysis is represented by the thickness of each line. Red represents a positive correlation whereas blue indicates a negative correlation. (f) Waterfall plot of tumor somatic mutations showed that genes related to the breast (IKBKB, ATG16L2, CLN3, MBTPS2, TSC2, and CAPN10) had a high frequency of mutations. (g) Breast cancer OS-associated genes (CLN3, TSC2, DAPK2, LAMP1, ATG16L2, FADD, IKBKB, RAB24, CAPN10, CFLAR, PEX14, MBTPS2, ST13, MAP2K7, and STK11) in the positions of CNV on 23 chromosomes based on TCGA-BRCA dataset. (h, i) Key genes selected using the LASSO regression model using the minimum criterion of 5-fold cross-validation. Generation of coefficient outline based on the log (lambda) sequence, where the optimal lambda acquires the characteristics of the 6 nonzero coefficients. (j) A forest chart showing the factors selected from the multivariate COX regression analysis ().
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