Low-Frequency Mutational Heterogeneity of Invasive Ductal Carcinoma Subtypes: Information to Direct Precision Oncology

Abstract

Information regarding the role of low-frequency hotspot cancer-driver mutations (CDMs) in breast carcinogenesis and therapeutic response is limited. Using the sensitive and quantitative Allele-specific Competitor Blocker PCR (ACB-PCR) approach, mutant fractions (MFs) of six CDMs (PIK3CA H1047R and E545K, KRAS G12D and G12V, HRAS G12D, and BRAF V600E) were quantified in invasive ductal carcinomas (IDCs; including ~20 samples per subtype). Measurable levels (i.e., ≥ 1 × 10^-5, the lowest ACB-PCR standard employed) of the PIK3CA H1047R, PIK3CA E545K, KRAS G12D, KRAS G12V, HRAS G12D, and BRAF V600E mutations were observed in 34/81 (42%), 29/81 (36%), 51/81 (63%), 9/81 (11%), 70/81 (86%), and 48/81 (59%) of IDCs, respectively. Correlation analysis using available clinicopathological information revealed that PIK3CA H1047R and BRAF V600E MFs correlate positively with maximum tumor dimension. Analysis of IDC subtypes revealed minor mutant subpopulations of critical genes in the MAP kinase pathway (KRAS, HRAS, and BRAF) were prevalent across IDC subtypes. Few triple-negative breast cancers (TNBCs) had appreciable levels of PIK3CA mutation, suggesting that individuals with TNBC may be less responsive to inhibitors of the PI3K/AKT/mTOR pathway. These results suggest that low-frequency hotspot CDMs contribute significantly to the intertumoral and intratumoral genetic heterogeneity of IDCs, which has the potential to impact precision oncology approaches.

Keywords: PIK3CA; TNBC; breast cancer; cancer-driver; heterogeneity; invasive ductal carcinoma; mutation; subclonal; triple-negative breast cancer.

Figure 1

Representative images of the fluorescein-labeled ACB-PCR products on a polyacrylamide gel are shown for PIK3CA codon 1047 CAT→CGT (H1047R) (a). The pixel intensities of the bands produced from the standards were quantified and used to construct a standard curve relating pixel intensity to MF (b). The standard curve was used to interpolate the MFs of the samples from their measured fluorescence.

Figure 2

Levels of somatic mutations were quantified in (a) HR+/HER2+, (b) HR+/HER2−, (c) HR−/HER2+, and (d) HR−/HER2− (TNBC) IDCs. Error bars indicate the SEM for the replicate ACB-PCR MF measurements of each sample. Measurements below the level of accurate ACB-PCR quantification (1 × 10⁻⁵) are not shown.

Figure 3

Percent of IDC samples with one, two, three, four, or five CDMs present at levels ≥ 1 × 10⁻⁵.

Figure 4

Dot plots and corresponding boxplots of (a) PIK3CA H1047R, (b) PIK3CA E545K, (c) KRAS G12D, (d) KRAS G12V, (e) HRAS G12D and (f) BRAF V600E MFs measured in normal breast [7,11] and four subtypes of IDC. Measurements in the shaded area are below the level of accurate ACB-PCR quantification (1 × 10⁻⁵). * Significant compared to normal breast. ^† Significant difference between IDC subtypes (Fisher’s exact test; p > 0.05).

Figure 5

PIK3CA H1047R (a) and BRAF V600E (b) MFs are correlated positively with maximum tumor dimension. KRAS G12V (c) MF is correlated negatively with maximum tumor dimension (non-significant). Correlation analyses were conducted using samples with MFs ≥ 1 × 10⁻⁵. The solid line denotes the linear regression line. Dashed lines denote the 95% confidence interval. p values ≤ 0.05 are in red.