Serial Tumor Molecular Profiling of Newly Diagnosed HER2-Negative Breast Cancers During Chemotherapy in Combination with Angiogenesis Inhibitors

Abstract

Background: Breast cancers are heterogeneous with variable clinical courses and treatment responses.

Objective: We sought to evaluate dynamic changes in the molecular landscape of HER2-negative tumors treated with chemotherapy and anti-angiogenic agents.

Patients and methods: Newly diagnosed HER2-negative breast cancer patients received low-dose sunitinib or bevacizumab prior to four 2-weekly cycles of dose-dense doxorubicin and cyclophosphamide. Tumor biopsies were obtained at baseline, after 2 weeks and after 8 weeks of chemotherapy. Next-generation sequencing was performed to assess for single nucleotide variants (SNVs) and copy number alterations (CNAs) of 440 cancer-related genes (ACTOnco®). Observed genomic changes were correlated with the Miller-Payne histological response to treatment.

Results: Thirty-four patients received sunitinib and 18 received bevacizumab. In total, 77% were hormone receptor positive (HER2-/HR+) and 23% were triple negative breast cancers (TNBC). New therapy-induced mutations were infrequent, occurring only in 13%, and appeared early after a single cycle of treatment. Seventy-two percent developed changes in the variant allele frequency (VAF) of pathogenic SNVs; the majority (51%) of these changes occurred early at 2 weeks and were sustained for 8 weeks. Changes in VAF of SNVs were most commonly seen in the PI3K/mTOR/AKT pathway; 13% developed changes in pathogenic mutations, which potentially confer sensitivity to PIK3CA inhibitors. Tumors with poor Miller-Payne response to treatment were less likely to experience changes in VAF of SNVs compared with those with good response (50% [7/14] vs 15% [4/24] had no changes observed at any timepoint, p = 0.029).

Conclusions: Serial molecular profiling identifies early therapy-induced genomic alterations, which may guide future selection of targeted therapies in breast cancer patients who progress after standard chemotherapy.

Clinical trial registration: ClinicalTrials.gov: NCT02790580 (first posted June 6, 2016).

Conflict of interest statement

Soo Chin Lee has received Honoraria and consulting fees from Astra Zeneca, Pfizer, Novartis, Eli Lilly, Roche, ACT Genomics, Eisai; research funding from Taiho, Eisai, Pfizer and ACT Genomics. Samuel GW Ow has received honoraria from AstraZeneca, Pfizer, Lilly, Roche and Novartis. Andrea Wong has received research funding from Otsuka Pharmaceuticals, and has advisory roles with Pfizer, Novartis and Eisai. Natalie Ngoi has received honoraria from AstraZeneca. Joline SJ Lim has consultancy with Pfizer, Novartis; research funding from Synthon. Goh Boon Cher has received honoraria from Novartis, Merck Serono, MSD; has consultancy with Adagene; research support and funding from Bayer, MSD, BMS, Adagene, and Taiho; stock interests in Gilead Sciences and Avantor. Yi-Hua Jan, Shu-Jen Chen and Kien Thiam Tan are under employment by ACT Genomics. Joan RE Choo, Matilda Xinwei Lee, Kritika Yadav, Siew Eng Lim, Ching Wan Chan, Mikael Hartman, Siau Wei Tang, Hon Lyn Tan, Wan Qin Chong, Ang Li En Yvonne, Gloria HJ Chan declared no conflicts of interest.

© 2022. The Author(s).

Figures

Fig. 1

Consort diagram of sample disposition

Fig. 2

Tumor SNV and CNA landscape at baseline. Commonly detected SNVs and CNAs by NGS are shown in decreasing order of prevalence. Pathogenic SNVs are labeled as driver mutations while SNVs of unknown significance are labeled as VUS. Copy number gain was defined as copy number between 4–7 while copy number amplification was defined as copy number ≥8. Copy number loss was defined as an observed copy number ≤1 where heterozygous loss (shallow deletion) was defined as observed copy number 1 while homozygous loss (deep deletion) was defined as observed copy number 0s. CNAs copy number alterations; NGS next-generation sequencing; SNV single nucleotide variants; VUS variants of uncertain significance

Fig. 3

Genomic alterations in signaling molecules that interact with the VEGF angiogenesis pathway at baseline. Percentages of HER2−/HR+ and TNBC tumors (represented on the left and right of each module diagram, respectively) with alterations in signaling molecules that interact with the angiogenesis pathway are shown. Blue highlights the presence of inactivating mutations while red highlights the presence of activating mutations within that gene. The arrows describe whether the interactions are activating or inhibitory upon downstream signaling molecules. Sunitinib and bevacizumab have direct inhibitory effects on certain targets within the signaling cascades which are marked by the symbols. HER2− human epidermal growth factor receptor 2 negative; HR+ hormone receptor positive; TNBC triple-negative breast cancer; VEGF vascular endothelial growth factor

Fig. 4

Timing of changes in CCF of SNVs. Patients with 3 serial tumor biopsies were analysed for timing of significant changes in VAF of SNVs [measured by the CCF slope (post-treatment CCF/baseline CCF)]. Patients were classified into 4 groups: no changes, early and sustained changes (those who experienced changes at 2 weeks which were persist at 8 weeks), transient changes (those who experienced changes at 2 weeks which subsequently normalized at 8 weeks) and those who experienced late changes alone. The blue bar highlights the patients with no changes, while orange bars highlight those with changes in VAF of SNVs. Of those who experienced changes in VAF of SNVs, majority had early and sustained changes. CCF cancer cell fraction; SNVs single nucleotide variants; VAF variant allele frequency

Fig. 5

Change in VAF measured by CCF slope (post-treatment CCF/baseline CCF) of pathogenic PIK3CA mutations by treatment cohort. The change in VAF measured by the CCF slope (post-treatment CCF/baseline CCF) of each patient with pathogenic PIK3CA mutations are represented here. A slope of ≤0.8 indicates a decrease in VAF and ≥1.25 indicates an increase in VAF. Of the 20 patients with pathogenic PIK3CA mutations at baseline, 35% had sustained increase in VAF of pathogenic PIK3CA alterations. Significant rise in VAF of pathogenic PI3K mutations only occurred in HER2−/HR+ tumors. CCF cancer cell fraction; VAF variant allele frequency