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. 2023 Nov 18;14(1):7496.
doi: 10.1038/s41467-023-43324-w.

Comprehensive genomic characterization of HER2-low and HER2-0 breast cancer

Paolo Tarantino #  1   2   3   4 , Hersh Gupta #  5   6 , Melissa E Hughes  5 , Janet Files  5 , Sarah Strauss  5 , Gregory Kirkner  5 , Anne-Marie Feeney  5 , Yvonne Li  5 , Ana C Garrido-Castro  5   7   8 , Romualdo Barroso-Sousa  9   10 , Brittany L Bychkovsky  7   8   11 , Simona DiLascio  5 , Lynette Sholl  5 , Laura MacConaill  5 , Neal Lindeman  5   12 , Bruce E Johnson  5 , Matthew Meyerson  5   8   6 , Rinath Jeselsohn  5   7   8 , Xintao Qiu  5 , Rong Li  5 , Henry Long  5 , Eric P Winer  13 , Deborah Dillon  8   14 , Giuseppe Curigliano  15 , Andrew D Cherniack  5   8   6 , Sara M Tolaney  5   7   8 , Nancy U Lin  5   7   8
Affiliations

Comprehensive genomic characterization of HER2-low and HER2-0 breast cancer

Paolo Tarantino et al. Nat Commun. .

Erratum in

  • Author Correction: Comprehensive genomic characterization of HER2-low and HER2-0 breast cancer.
    Tarantino P, Gupta H, Hughes ME, Files J, Strauss S, Kirkner G, Feeney AM, Li Y, Garrido-Castro AC, Barroso-Sousa R, Bychkovsky BL, DiLascio S, Sholl L, MacConaill L, Lindeman N, Johnson BE, Meyerson M, Jeselsohn R, Qiu X, Li R, Long H, Winer EP, Dillon D, Curigliano G, Cherniack AD, Tolaney SM, Lin NU. Tarantino P, et al. Nat Commun. 2023 Dec 14;14(1):8321. doi: 10.1038/s41467-023-44124-y. Nat Commun. 2023. PMID: 38097580 Free PMC article. No abstract available.

Abstract

The molecular underpinnings of HER2-low and HER2-0 (IHC 0) breast tumors remain poorly defined. Using genomic findings from 1039 patients with HER2-negative metastatic breast cancer undergoing next-generation sequencing from 7/2013-12/2020, we compare results between HER2-low (n = 487, 47%) and HER2-0 tumors (n = 552, 53%). A significantly higher number of ERBB2 alleles (median copy count: 2.05) are observed among HER2-low tumors compared to HER2-0 (median copy count: 1.79; P = 2.36e-6), with HER2-0 tumors harboring a higher rate of ERBB2 hemideletions (31.1% vs. 14.5%). No other genomic alteration reaches significance after accounting for multiple hypothesis testing, and no significant differences in tumor mutational burden are observed between HER2-low and HER2-0 tumors (median: 7.26 mutations/megabase vs. 7.60 mutations/megabase, p = 0.24). Here, we show that the genomic landscape of HER2-low and HER2-0 tumors does not differ significantly, apart from a higher ERBB2 copy count among HER2-low tumors, and a higher rate of ERBB2 hemideletions in HER2-0 tumors.

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Conflict of interest statement

P.T. served as advisor/consultant for AstraZeneca, Daiichi-Sankyo, Gilead and Lilly. N.U.L. reports institutional research support from Genentech, Pfizer, Merck, Seattle Genetics, Zion Pharmaceuticals, Olema Pharmaceuticals, and AstraZeneca; consulting honoraria from Puma, Seattle Genetics, Daiichi-Sankyo, AstraZeneca, Denali Therapeutics, Prelude Therapeutics, Olema Pharmaceuticals, Aleta BioPharma, Affinia Therapeutics, Voyager Therapeutics, Janssen, Blueprint Medicines, Stemline/Menarini, and Artera Inc. and Reverie Labs;.; and royalties from UptoDate (book). S.M.T. reports consulting or advisory roles for Novartis, Pfizer, Merck, Eli Lilly, AstraZeneca, Genentech/Roche, Eisai, Sanofi, Bristol Myers Squibb, Seattle Genetics, CytomX Therapeutics, Daiichi-Sankyo, Gilead, Ellipses Pharma, 4D Pharma, OncoSec Medical Inc., BeyondSpring Pharmaceuticals, OncXerna, Zymeworks, Zentalis, Blueprint Medicines, Reveal Genomics, ARC Therapeutics, Infinity Therapeutics, Myovant, Zetagen, Umoja Biopharma, Artios Pharma, Menarini/Stemline, Aadi Biopharma, Bayer, Incyte Corp, and Jazz Pharmaceuticals; and research funding from Genentech/Roche, Merck, Exelixis, Pfizer, Lilly, Novartis, Bristol Myers Squibb, Eisai, AstraZeneca, Gilead, NanoString Technologies, Seattle Genetics, and OncoPep. G.C. reports honoraria for speaker’s engagement from Roche, Seattle Genetics, Novartis, Lilly, Pfizer, Foundation Medicine, NanoString, Samsung, Celltrion, BMS, MSD; honoraria for providing consultancy from Roche, Seattle Genetics, NanoString; honoraria for participating on the advisory boards of Roche, Lilly, Pfizer, Foundation Medicine, Samsung, Celltrion, Mylan; honoraria for writing engagement from Novartis and BMS; honoraria for participation in the Ellipsis Scientific Affairs Group; institutional research funding for conducting phase I and II clinical trials from Pfizer, Roche, Novartis, Sanofi, Celgene, Servier, Orion, AstraZeneca, Seattle Genetics, AbbVie, Tesaro, BMS, Merck Serono, Merck Sharp Dome, Janssen-Cilag, Philogen, Bayer, Medivation, and Medimmune. A.C.G.-C. reports research funding (to Institution) from AstraZeneca, Daiichi-Sankyo, Merck, Gilead Sciences, Zenith Epigenetics; and travel accommodations from Roche/Genentech. R.B.-S. reports receiving speaker bureau fees from Agilant, AstraZeneca, Daiichi-Sankyo, Eli Lilly, Pfizer, Novartis, Merck, and Roche. He has also served as a consultant/advisor for AstraZeneca, Eli Lilly, Libbs, Roche, Merck and has received support for attending medical conferences from AstraZeneca, Roche, Eli Lilly, Daiichi-Sankyo, and Merck. D.D. has served as a consultant for Novartis, on the Advisory Board for Oncology Analytics and receives research funding from Canon Inc. B.E.J. reports that he has served as a paid consultant to Novartis, Checkpoint Therapeutics, Hummingbird Diagnostics, Daiichi- Sankyo, AstraZeneca, G1 Therapeutics, BlueDotBio, GSK, Hengrui Therapeutics, Simcere Pharmaceutical, Jazz Pharmaceuticals, and Merus N.V. He is also an unpaid member of a Steering Committee for Pfizer. He receives research support from Cannon Medical Imaging. A.D.C. receives research support from Bayer AG. M.M. reports research support from Bayer AG and Janssen; consulting for Bayer, Delve, Interline, and Isabl; and royalties from Bayer and LabCorp. R.J. reports research support from Pfizer and Lilly and serves as an advisor to GE Health and Carrick Therapeutics. The remaining authors declare no competing interests.

Figures

Fig. 1
Fig. 1. Frequency of most common genomic alterations by HER2 status.
a The frequency of copy number variations (CNV); b the frequency of gene mutations. Shading represents the percentage of oncogenic events. An annotation of “(A)” beside a gene represents high amplification and “(D)” represents a deep or 2-copy deletion as the oncogenic event. Unshaded bars represent any other copy number event. HER2 human epidermal growth factor receptor 2, ER estrogen receptor.
Fig. 2
Fig. 2. OncoPrint view of the genomic landscape of HER2-0 (n = 552) and HER2-low (n = 487) metastatic breast cancer.
a The OncoPrint of ER-negative tumors, divided by HER2 status; b the OncoPrint of ER-positive tumors, divided by HER2 status. Genes are ordered by frequency of variants in the overall study population. Percentages listed show the frequency of alterations in HER2-0 and HER2-low, respectively. All variants represent oncogenic mutations or deep deletions/high amplifications. TMB (mut/mb) is recorded on the top of the plot. HER2 human epidermal growth factor receptor 2, MBC metastatic breast cancer, ER estrogen receptor, TMB tumor mutational burden.
Fig. 3
Fig. 3. Enrichment analysis of genomic alterations between HER2-low (n = 482) and HER2-0 (n = 551).
a The enrichment analysis for mutations; b the enrichment analysis for copy number variations (CNV). Modeling was done using multivariate logistic regression accounting for ER status and background rate of either mutation or copy number events, using the statsmodel package in Python. ER-low cases were included in the ER-positive group. Only models that reached a significant value for rejecting the log-likelihood null were included after multiple hypothesis correction using BH-FDR, as well as those that converged after 500 iterations. Only mutations that appeared in over 4% of either all HER2-0 or HER2-low samples were included. On the left, lines labeled “_ONC” represent only oncogenic mutations, while the CNVs were done on 2DELs or high amplifications for tumor suppressor genes and oncogenes, respectively (labeled in the figure). Error bars are reported as the 95% confidence interval. P-values are determined as the likelihood of the model’s calculated coefficients under the assumption that the true coefficients are 0 and are reported as two-tailed. Multiple hypothesis correction was done using BH-FDR. Exact p-values are reported in the source data of this figure. These are the same statistical tests used in the Supplementary Data File, Supplementary Figs. 3 and 6. CNV copy number variations, ER estrogen receptor, HER2 human epidermal growth receptor factor.
Fig. 4
Fig. 4. Comparison of ERBB2 copy counts between HER2-low (n = 369) and HER2-0 tumors (n = 417).
Panel a depicts the estimated copy count of ERBB2 by ER status and HER2 status. The blue line depicts the point at which HER2 would be called a 1-copy loss and the red line depicts the point at which it would be called a gain. Panel b shows a similar plot, except colored by IHC staining for HER2. Samples with a recorded IHC of unspecified value were excluded (HER2-low = 369 and HER2-0 = 417). Box plots are constructed with the central line as the median, the outer lines of the box as the lower and upper quartile, and whiskers are equal to 1.5x the closest quartile. HER2 human epidermal growth factor receptor 2, ER estrogen receptor, IHC immunohistochemistry.
See this image and copyright information in PMC

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