Immunogenomic profiling and pathological response results from a clinical trial of docetaxel and carboplatin in triple-negative breast cancer

Abstract

Purpose: Patients with triple-negative breast cancer (TNBC) who do not achieve pathological complete response (pCR) following neoadjuvant chemotherapy have a high risk of recurrence and death. Molecular characterization may identify patients unlikely to achieve pCR. This neoadjuvant trial was conducted to determine the pCR rate with docetaxel and carboplatin and to identify molecular alterations and/or immune gene signatures predicting pCR.

Experimental design: Patients with clinical stages II/III TNBC received 6 cycles of docetaxel and carboplatin. The primary objective was to determine if neoadjuvant docetaxel and carboplatin would increase the pCR rate in TNBC compared to historical expectations. We performed whole-exome sequencing (WES) and immune profiling on pre-treatment tumor samples to identify alterations that may predict pCR. Thirteen matching on-treatment samples were also analyzed to assess changes in molecular profiles.

Results: Fifty-eight of 127 (45.7%) patients achieved pCR. There was a non-significant trend toward higher mutation burden for patients with residual cancer burden (RCB) 0/I versus RCB II/III (median 80 versus 68 variants, p 0.88). TP53 was the most frequently mutated gene, observed in 85.7% of tumors. EGFR, RB1, RAD51AP2, SDK2, L1CAM, KPRP, PCDHA1, CACNA1S, CFAP58, COL22A1, and COL4A5 mutations were observed almost exclusively in pre-treatment samples from patients who achieved pCR. Seven mutations in PCDHA1 were observed in pre-treatment samples from patients who did not achieve pCR. Several immune gene signatures including IDO1, PD-L1, interferon gamma signaling, CTLA4, cytotoxicity, tumor inflammation signature, inflammatory chemokines, cytotoxic cells, lymphoid, PD-L2, exhausted CD8, Tregs, and immunoproteasome were upregulated in pre-treatment samples from patients who achieved pCR.

Conclusion: Neoadjuvant docetaxel and carboplatin resulted in a pCR of 45.7%. WES and immune profiling differentiated patients with and without pCR.

Trial registration: Clinical trial information: NCT02124902, Registered 24 April 2014 & NCT02547987, Registered 10 September 2015.

Keywords: Breast cancer; Clinical trials; Combination chemotherapy; Genomic biomarkers; Immune biomarkers.

Conflict of interest statement

Competing interests

FOA reports consulting for Eisai, Immunomedics, Astra Zeneca, Athenex, Cardinal Health, Pfizer, Abbvie, Best Doctors, and Advance Medical. FOA reports contracted research for Immunomedics, Pfizer, Seattle Genetics, NeoImmuneTech, RNA Diagnostics, and Astellas. MFR reports consulting for Genentech, MacroGenics, Daiichi, Seattle Genetics, and Novartis. MFR reports contracted research for Pfizer. RB consulting for Genentech. RB reports contracted research for Puma Biotechnology, Inc.

© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Figures

Figure 1.

Clinical trial schema. Diagram of clinical trial showing chemotherapy regimen and biospecimen collection time points.

Figure 2.

Differential expression of gene signatures’ forest plot based on pCR in baseline samples only (N = 66 patients). This shows the differential expression means and 95% confidence intervals between response variables, for each signature on an unadjusted scale. The vertical axis is shown at fold change equal to zero, indicating equivalent expression between pCR and no pCR (no). As the marker shifts from the center line there is an increase (shift to the right), or decrease (shift to the left), in the differential expression of that signature when compared to the no pCR group (represented as the vertical line at zero). The shape of the marker in each box indicates whether there is a significant difference in the signature as assessed by univariate analysis (note that this significance is not adjusted for multiple comparisons). A signature is considered significant if the 95% confidence interval (the horizontal line of the signature) does not cross the vertical axis representing the no response group.

Figure 3.

Differential expression of IO360 gene signatures before and on-treatment (N = 66 patients). A) Volcano plot showing differential expression of IO360 immune signatures from baseline or on treatment samples. Signatures in blue were significantly different using an adjusted p-value (p

Figure 4.

The mutation landscape waterfall plot of genes with a non-synonymous (frameshift, in-frame deletion, in-frame insertion, mature miRNA, missense, protein altering, splice acceptor, splice donor, splice region, start lost, stop gained, and stop lost) mutation frequency >5%. Top bar plot indicates mutation burden, left bar plot indicates mutation frequency, and lower panel provides clinical annotation.

Figure 5.

Overall mutation burden according to pathological response (N = 56 patients). Log scale of somatic mutation burden according to pathological response following neoadjuvant chemotherapy. Red bar indicates patients without pCR. Green bar indicates patients with pCR. pCR, pathological complete response.

Figure 6.

Comparison of variant detection in pre-treatment and on-treatment paired tumor samples. Of the 13 participants for which WES was performed at both baseline and C1D3, 12 matched samples are plotted. One paired sample set is not shown due to low variant counts. For the variants plotted, the minimum coverage was set to 30 reads. The clonal status of variants in each sample is indicated by color. Red represents subclonal depleted mutations, green represents subclonal selected mutations, and grey represents shared clonal mutations. TP53 variants were called in 11 of the participants’ samples and are highlighted in the plots by the triangle.