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

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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.

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Data availability

The datasets used and/or analyzed during the present study are available from the corresponding author on reasonable request.

Abbreviations

TNBC:

Triple-negative breast cancer

ER:

Estrogen receptor

PR:

Progesterone receptor

HER2:

HER2/Neu gene

DNA:

Deoxyribonucleic acid

pCR:

Pathological complete response

IHC:

Immunohistochemistry

FISH:

Fluorescence in situ hybridization

WUSM:

Washington University School of Medicine

BCM:

Baylor College of Medicine

AUC:

Area under the curve

NCI CTCAE:

National Cancer Institute Common Terminology Criteria for Adverse Events

C1D3:

Cycle 1 day 3

RCB:

Residual cancer burden

TIL:

Tumor-infiltrating lymphocytes

WES:

Whole-exome sequencing

SNV:

Single-nucleotide variant

RNA:

Ribonucleic acid

FFPE:

Formalin-fixed paraffin-embedded

TIS:

Tumor inflammation signature

IUO:

Investigational use only

RUO:

Research use only

SKAT:

Sequence kernel-based association

SAE:

Serious adverse events

ALC:

Absolute lymphocyte count

OR:

Odds ratio

VAF:

Variant allele frequency

TME:

Tumor microenvironment

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Acknowledgements

Tracy Summa, Isabella Grigsby, Christina Robinson, and Kristen Otte for providing clinical research support.

Funding

FOA—Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under Award Number K12 CA167540. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. Research reported in this publication was supported by NeoImmuneTech, Inc. MJE—Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under Award Number U01 CA214125-03. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. Research reported in this publication was supported by the Cancer Prevention & Research Institute of Texas Established Investigator Award RR140033. The content is solely the responsibility of the authors and does not necessarily represent the official views of the CPRIT. OLG—Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under Award Number K22CA188163. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. MG—Research reported in this publication was supported by the National Human Genome Research Institute of the National Institutes of Health under Award Number R00HG007940. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

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Author notes

  1. Foluso O. Ademuyiwa and Ina Chen are Co-first authors.

Authors and Affiliations

  1. Division of Oncology, Department of Medicine, Washington University School of Medicine, 660 S. Euclid Ave., St Louis, MO, 63110, USA

    Foluso O. Ademuyiwa, Cynthia X. Ma, Katherine Weilbaecher, Jennifer Davis, Rama Suresh, Lindsay L. Peterson, Ron Bose, Nusayba Bagegni, Caron E. Rigden, Ashley Frith, Timothy P. Rearden, Leonel F. Hernandez-Aya, Anna Roshal, Katherine Clifton & Mateusz Opyrchal

  2. Department of Surgery, Washington University School of Medicine, St Louis, MO, 63110, USA

    Ina Chen, Jingqin Luo, Feng Gao & William Gillanders

  3. Lester & Sue Smith Breast Center and Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, 77030, USA

    Mothaffar F. Rimawi, Meenakshi Anurag & Matthew J. Ellis

  4. Department of Pathology and Immunology, Washington University School of Medicine, St Louis, MO, 63110, USA

    Ian S. Hagemann

  5. McDonnell Genome Institute, Washington University School of Medicine, Campus Box 8501, 4444 Forest Park Ave., St Louis, MO, 63108, USA

    Bryan Fisk, Gejae Jeffers, Zachary L. Skidmore, Anamika Basu, Megan Richters, Obi L. Griffith & Malachi Griffith

  6. Department of Pathology, Christian Hospital NE/NW, St. Louis, MO, 63136, USA

    Olaronke Akintola-Ogunremi

  7. NeoImmuneTech, Inc., 2400 Research Boulevard Suite 250, Rockville, MD, 20850, USA

    Byung Ha Lee & Sara Ferrando-Martinez

  8. NanoString Technologies, Inc., 530 Fairview Ave N, Seattle, WA, 98109, USA

    Sarah E. Church

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  1. Foluso O. Ademuyiwa
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Contributions

FOA, IC, MJE, WG were involved in the conception and design of the study. FOA, MFR, CXM, KW, RS, LLP, RB, NB, CER, AF, TPR, LFH, AR,KC, MO participated in the acquisition of data (acquired and managed patients, provided facilities, etc.). FOA, IC, JL, MFR, ISH, BF, GJ, ZLS, AB, MR, CXM, KW, JD, LLP, RB, MO, OA, BHL, SF, SC, MA, FG, WG, OLG, MG provided analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis). All authors were involved in writing, reviewing, and/or revision of the manuscript. FOA, BF, GJ, ZLS, AB, MR, SC, MA, OLG, MG provided administrative, technical, or material support (i.e., reporting or organizing data, constructing databases). The authors read and approved the final manuscript.

Corresponding authors

Correspondence to Foluso O. Ademuyiwa or Malachi Griffith.

Ethics declarations

Conflict of interest

FOA reports consulting for Eisai, Immunomedics, AstraZeneca, 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.

Ethical Approval

The protocol and informed consent documents were approved by WUSM and BCM. Upon approval, all participating institutions agreed to follow the Declaration of Helsinki, good clinical practice guidelines, and the applicable parts of the U.S. Code of Federal Regulations.

Informed consent

Written informed consent was required for enrollment.

Additional information

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Supplementary Information

Below is the link to the electronic supplementary material.

10549_2021_6307_MOESM1_ESM.docx

Supplementary file1 (DOCX 61 kb) Additional file 1. Study Consort Diagram. Flow diagram of clinical trial including all patients screened, registered, received intervention, and are evaluable for the primary endpoint. Also indicates number of patients from both sites. WUSM, Washington University School of Medicine and BCM, Baylor College of Medicine.

10549_2021_6307_MOESM2_ESM.docx

Supplementary file2 (DOCX 338 kb) Additional file 2. Complete linkage clustering of IO360 signatures and additional gene signatures (PIK3R2, PIK3R1, JAK1, JAK3, IL2RG, STAT3, FYN) and individual baseline samples z-scaled transformed and trimmed to plus or minus 3 (N = 66 patients).

10549_2021_6307_MOESM3_ESM.docx

Supplementary file3 (DOCX 13 kb) Additional file 3. Table of fold change and adjusted p values for immune gene signatures significantly higher at baseline versus on-treatment.

10549_2021_6307_MOESM4_ESM.docx

Supplementary file4 (DOCX 257 kb) Additional file 4. The TP53 mutation profile of patients in this study is shown in the top panel, and the TP53 mutation profile from the COSMIC database is shown in the bottom panel. Each distinct mutation is represented by a disc sized in proportion to number of affected samples and filled with the color representing its mutation class. The TP53 protein is displayed as a ruler with color-banding denoting the protein domains and numerical markings denoting the number of amino acid residues from N-terminus to C-terminus. Forty-one unique TP53 mutations were observed in 48 of 56 patients’ samples sequenced on this study.

10549_2021_6307_MOESM5_ESM.docx

Supplementary file5 (DOCX 214 kb) Additional file 5. The EGFR mutation profile of patients in our study is shown in the top panel, and the EGFR mutation profile from the COSMIC database is shown in the bottom panel. Each distinct mutation is represented by a disc sized in proportion to the number of affected samples and filled with the color representing its mutation class. The EGFR protein is displayed as a ruler with color-banding denoting the protein domains and numerical markings denoting the number of amino acid residues from N-terminus to C-terminus. Four unique EGFR mutations were observed in 3 patient samples on our study.

Supplementary file6 (DOCX 367 kb) Additional file 6. Table of MsigDB C7 set—Immune-signature related gene sets.

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Ademuyiwa, F.O., Chen, I., Luo, J. et al. Immunogenomic profiling and pathological response results from a clinical trial of docetaxel and carboplatin in triple-negative breast cancer. Breast Cancer Res Treat 189, 187–202 (2021). https://doi.org/10.1007/s10549-021-06307-3

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