Background: In patients with early breast cancer, neoadjuvant therapy is widely performed as standard of care. While the molecular targeting strategy makes progress in HER2 positive breast cancer, the optimal regimens for ER+/HER2- breast cancer (BC) and triple negative breast cancer (TNBC) remain undecided. Furthermore, there are few strategies for patients who do not achieve complete pathological response (pCR) who have worse prognosis. To address these unmet clinical needs, there is urgent need to examine the genomic alterations and immune microenvironment of residual tumors after neoadjuvant therapy. Here, we conducted a comprehensive analysis integrating genomic, transcriptomic, and clinical data to investigate the difference between primary breast cancer and residual disease.

Materials and Methods: Using the large prospectively ascertained ethnically diverse Chicago Multi-Ethnic (ChiMEC) cohort of 562 participants with integrated genomic data, we identified 176 patients with breast cancer who underwent sequencing with Tempus xT next-generation sequencing panel including DNA- and whole-transcriptome RNA-sequencing. These included 131 primary breast tumors and 45 residual tumors after neoadjuvant therapy. We compared mutation rates between primary tumor and residual tumor in ER+/HER2- BC and TNBC. We also investigated homologous recombination deficiency (HRD) scores, tumor mutational burden (TMB), degree of immune infiltration, and microsatellite instability (MSI), and their association with survival.

Results: Out of the 176 patients, there were 72 ER+/HER2-BC, 42 TNBC, and 44 HER2 positive cases. Among patients with HR+/HER2- BC, residual tumors had higher mutation rates in PIK3CA (61% vs 33%), CDH1 (33% vs 17%), CCND1 (39% vs 7%), FGF3 (28% vs 0%), FGF4 (33% vs 2%), FGF19 (33% vs 2%), and GATA3 (44% vs 7%) than primary tumors, but lower rates in TP53 (28% vs 48%), MAP3K1 (6% vs 40%), KMT2D (0% vs 33%), MCL1 (0% vs 30%), SPEN (6% vs 20%), ZFHX3 (0% vs 20%), ARID1A (11% vs 16%), KMT2C (0% vs 19%), LZTR1 (0% vs 19%), BCORL1 (6% vs 17%), NOTCH3 (6% vs 17%), FAT1 (0% vs 17%) and LPR1B (0% vs 17%). Relative to primary TNBC tumors, residual TNBC tumors exhibited higher mutation rates in PTEN (10% vs 3%), CCNE1 (10% vs 3%), CIC (10% vs 0%), and KMT2D (10% vs 3%). Conversely, residual TNBC tumors had relatively lower rates of MCL1 (0% vs 21%), RB1 (0% vs 12%), CDH1 (0% vs 12%), KMT2C (11% vs 18%), and PIK3CA (0% vs 15%), CDKN1B (0% vs 12%) and ETV6 (0% vs 12%). There was a significant trend of higher TMB (>5.0 mutations/megabase, m/MB) associated with improved disease-free survival among the 176 patients (P=0.031). TMB was not significantly different between primary tumors and residual tumors, or across subtypes. Microsatellite instability (MSI) status was high in 3 patients (1.6%) and equivocal in 5 patients (2.7%). TMB in MSI-high or MSI-equivocal tumors was significantly higher than TMB in tumors with microsatellite stability (37.7m/MB vs 5.3m/MB, P<0.001). HRD scores were highest in TNBC, and lowest in ER+/HER2- breast cancers (P=0.022). There was no significant association between the HRD scores and survival. To date, tumors from 106 patients have undergone immune profiling, with estimation of immune cell infiltration, macrophages, B cells, CD4, CD8, and NK cells. Initial analysis showed no association between immune profiling and survival.

Conclusion: These comprehensive analyses demonstrated that mutation status in HR+/HER2- breast cancers and TNBC differs between primary and residual tumors after neoadjuvant therapy. We identified genomic alterations and pathways in residual tumors that could be further explored as potential targets in the adjuvant setting to improve long term outcomes for patients who do not achieve pCR.

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