Exploring Aerobic Energy Metabolism in Breast Cancer: A Mutational Profile of Glycolysis and Oxidative Phosphorylation

Abstract

Energy metabolism is a fundamental aspect of the aggressiveness and invasiveness of breast cancer (BC), the neoplasm that most affects women worldwide. Nonetheless, the impact of genetic somatic mutations on glycolysis and oxidative phosphorylation (OXPHOS) genes in BC remains unclear. To fill these gaps, the mutational profiles of 205 screened genes related to glycolysis and OXPHOS in 968 individuals with BC from The Cancer Genome Atlas (TCGA) project were performed. We carried out analyses to characterize the mutational profile of BC, assess the clonality of tumors, identify somatic mutation co-occurrence, and predict the pathogenicity of these alterations. In total, 408 mutations in 132 genes related to the glycolysis and OXPHOS pathways were detected. The PGK1, PC, PCK1, HK1, DONSON, GPD1, NDUFS1, and FOXRED1 genes are also associated with the tumorigenesis process in other types of cancer, as are the genes BRCA1, BRCA2, and HMCN1, which had been previously described as oncogenes in BC, with whom the target genes of this work were associated. Seven mutations were identified and highlighted due to the high pathogenicity, which are present in more than one of our results and are documented in the literature as being correlated with other diseases. These mutations are rs267606829 (FOXRED1), COSV53860306 (HK1), rs201634181 (NDUFS1), rs774052186 (DONSON), rs119103242 (PC), rs1436643226 (PC), and rs104894677 (ETFB). They could be further investigated as potential biomarkers for diagnosis, prognosis, and treatment of BC patients.

Keywords: biomarkers; glycolysis; mitochondria; oncogenes; oxidative phosphorylation.

Figure 1

Overview of the glycolysis and oxidative phosphorylation gene variant profile. (A) List of the number of variants per type of variant found in the genes targeted in this study. (B) Classification of the variants found in general groupings. (C) Genes with the highest number of alterations.

Figure 2

Mutational profile of glycolysis and oxidative phosphorylation genes. Samples affected by mutations in selected genes and the mutation rate per sample or tumor mutation burden (TMB). The nomenclature of the type of mutation and its respective color are indicated below.

Figure 3

Frequency ratio of the mutated allele. This graph represents the presence of the mutated allele within sequenced somatic tissue based on the number of copies found in the tumor sequencing compared to the reference sequencing. It also represents the sequenced tissue and clonality and subclonality ratio of the variants found in the genes with the highest number of alterations.

Figure 4

Somatic interaction of glycolysis and oxidative phosphorylation genes with the highest variants. The graph shows the genes and the number of variants found in them in brackets, as well as somatic mutation interaction of the highest number of variants of glycolysis and oxidative phosphorylation genes, looking for genes that have co-occurring variants or mutually exclusive variants. This step consisted mainly of indicating the target genes that are related between or within the two different pathways.

Figure 5

Somatic mutation interactions compared to genes with the highest number of variants. Somatic interactions between the genes with the highest number of variants in the TCGA database and genes associated with glycolysis and oxidative phosphorylation in search of genes with co-occurring variants or mutually exclusive variants. It is possible that these new relationships are maintained in relation to our selected target genes seen in the previous analysis, but here some of them interact with some genes such as BRCA1, BRCA2, MUC16, HMCN1, and TTN.