Intratumoral heterogeneity contributes to the chemotherapy prognosis of breast cancer

J Cancer Res Ther. 2022 Sep;18(5):1268-1275. doi: 10.4103/jcrt.jcrt_1166_21.

Abstract

Context: Previous studies have shown that intratumoral heterogeneity (ITH) is associated with poor clinical outcomes and is thought to be a mechanism of resistance to chemotherapy and radiotherapy.

Aims: We aimed to determine how ITH affects the response to drug therapy in breast cancer (BC).

Settings and design: We assessed ITH using mutated allele tumor heterogeneity (MATH) data from BC patients in the TCGA database.

Methods and material: The study enrolled 515 patients with BC treated with chemotherapy from the TCGA database who had available data on survival, whole-exome sequencing, and genome-wide transcriptome sequencing. Additionally, 399 MSK-BRCA cohort patients were treated with chemotherapy.

Statistical analysis used: All statistical analyses were conducted using R. All comparisons were made using the two-sided Mann-Whitney test, Pearson's Chi-squared test, and the Kruskal-Wallis test. Statistical significance was defined as P values less than 0.05 (*P < 0.05). The survival package in R was used to conduct the analysis.

Results: Additional analysis was performed on 515 BC patients receiving adjuvant chemotherapy. MATH was associated with overall survival (OS) in multivariate analysis (hazard ratio (HR), 1.432; 95% confidence interval, 1.073-1.913; P = 0.015). Pathway enrichment and immune cell analysis revealed that the low MATH group had significantly higher infiltration of 24 different types of immune cells than the high MATH group.

Conclusions: Individuals with low MATH scores had a longer OS than those with high MATH scores. Immune responses were significantly enhanced in breast cancer patients with low MATH scores.

Keywords: Breast cancer; MATH; chemotherapy; intratumoral heterogeneity.

MeSH terms

  • Breast Neoplasms* / drug therapy
  • Breast Neoplasms* / genetics
  • Chemotherapy, Adjuvant
  • Cohort Studies
  • Female
  • Humans
  • Prognosis
  • Proportional Hazards Models