Serial single cell genomics reveals convergent subclonal evolution of resistance as patients with early stage breast cancer progress on endocrine plus CDK4 6 therapy nature cancer

16/6/2021 Serial single-cell genomics reveals convergent subclonal evolution of resistance as patients with early-stage breast cancer progress on e… View all journals content Journal info Article Publish Search My Account Sign up for alerts RSS feed Published: 03 June 2021 Serial single-cell genomics reveals convergent subclonal evolution of resistance as patients with early-stage breast cancer progress on endocrine plus CDK4/6 therapy Jason I Griffiths, Jinfeng Chen, Patrick A Cosgrove, Anne O’Dea, Priyanka Sharma, Cynthia Ma, Meghna Trivedi, Kevin Kalinsky, Kari B Wisinski, Ruth O’Regan, Issam Makhoul, Laura M Spring, Aditya Bardia, Frederick R Adler, Adam L Cohen, Jeffrey T Chang, Qamar J Khan Bild  & Andrea H   Nature Cancer (2021) 864 Accesses 29 Altmetric Metrics Abstract Combining cyclin-dependent kinase (CDK) inhibitors with endocrine therapy improves outcomes for patients with metastatic estrogen receptor-positive breast cancer but its value in earlier-stage patients is unclear We examined evolutionary trajectories of early-stage breast cancer tumors, using single-cell RNA sequencing of serial biopsies from the FELINE clinical trial of endocrine therapy (letrozole) alone or combined with the CDK inhibitor ribociclib Despite differences in subclonal diversity evolution across patients and treatments, common resistance phenotypes emerged Resistant tumors treated with combination therapy showed accelerated loss of estrogen signaling with convergent upregulation of JNK signaling through growth factor receptors In contrast, cancer cells maintaining estrogen signaling during mono- or combination therapy showed potentiation of CDK4/6 activation and ERK upregulation through ERBB4 signaling These results indicate that combination therapy in early-stage estrogen receptor-positive breast https://elksslnature.casb.nju.edu.cn:4443/articles/s43018-021-00215-7 1/23 16/6/2021 Serial single-cell genomics reveals convergent subclonal evolution of resistance as patients with early-stage breast cancer progress on e… cancer leads to emergence of resistance through a shift from estrogen to alternative growth signalmediated proliferation Access options Rent or Buy article Subscribe to Journal Get time limited or full article access on ReadCube Get full journal access for year from $8.99 92,52 €  only 7,71 € per issue Subscribe Rent or Buy All prices are NET prices All prices are NET prices VAT will be added later in the checkout Tax calculation will be finalised during checkout Additional access options: Log in Access through your institution Learn about institutional subscriptions Data availability Raw single-cell RNA-seq data are available through Gene Expression Omnibus under accession code GSE158724 DNA-seq data are available from dbGaP at phs002287.v1.p1 Source data are provided with this manuscript as individual Excel files (one per figure) and listed in the Inventory Code for Figs 1–6 is available on our GitHub repository at https://elkssl99cd2175108d157588c04758296d1cfcelksslnature.casb.nju.edu.cn:4443/U54Bioinfo rmatics/FELINE_project All other data supporting the findings of this study are available from the corresponding author on reasonable request Source data are provided with this paper https://elksslnature.casb.nju.edu.cn:4443/articles/s43018-021-00215-7 2/23 16/6/2021 Serial single-cell genomics reveals convergent subclonal evolution of resistance as patients with early-stage breast cancer progress on e… Code availability Custom code used in analyses are available on GitHub at https://elkssl99cd2175108d157588c04758296d1cfcelksslnature.casb.nju.edu.cn:4443/U54Bioinfo rmatics/FELINE_project References Harbeck, N & Gnant, M Breast cancer Lancet 389, 1134–1150 (2017) Rani, A., Stebbing, J., Giamas, G & Murphy, J Endocrine resistance in hormone receptor-positive breast cancer: from mechanism to therapy Front Endocrinol 10, 245  (2019) Zhao, H., Zhou, L., Shangguan, A J & Bulun, S E Aromatase expression and regulation in breast and endometrial cancer J Mol Endocrinol 57, R19–R33 (2016) Osborne, C K Tamoxifen in the treatment of breast cancer N Engl J Med 339, 1609– 1618 (1998) Early Breast Cancer Trialists’ Collaborative Group (EBCTCG) Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomised trials Lancet https://elkssl0a75e822c6f3334851117f8769a30e1celksslnature.casb.nju.edu.cn:4443/10.101 6/s0140-6736(05)66544-0 (2005) Pfizer PENELOPE-B trial of ibrance (palbociclib) in early breast cancer did not meet primary endpoint https://elkssl5deb59252c4fb1a716c7adaa2d8ccbf4elksslnature.casb.nju.edu.cn:4443/news/p ress-release/press-release-detail/penelope-b-trial-ibrancer-palbociclib-early-breast-cancer (2020) https://elksslnature.casb.nju.edu.cn:4443/articles/s43018-021-00215-7 3/23 16/6/2021 Serial single-cell genomics reveals convergent subclonal evolution of resistance as patients with early-stage breast cancer progress on e… 7 Weintraub, S J et al Mechanism of active transcriptional repression by the retinoblastoma protein Nature 375, 812–815 (1995) Finn, R S., Aleshin, A & Slamon, D J Targeting the cyclin-dependent kinases (CDK) 4/6 in estrogen receptor-positive breast cancers Breast Cancer Res 18, 17 (2016) Portman, N et al Overcoming CDK4/6 inhibitor resistance in ER-positive breast cancer Endocr Relat Cancer 26, R15–R30 (2019) 10 Sabbah, M., Courilleau, D., Mester, J & Redeuilh, G Estrogen induction of the cyclin D1 promoter: Involvement of a cAMP response-like element Proc Natl Acad Sci USA 96, 11217–11222 (1999)  11 Razavi, P et al The genomic landscape of endocrine-resistant advanced breast cancers Cancer Cell 34, 427–438 (2018) 12 Formisano, L et al Aberrant FGFR signaling mediates resistance to CDK4/6 inhibitors in ER+ breast cancer Nat Commun 10, 1373 (2019) 13 Kato, S et al Activation of the estrogen receptor through phosphorylation by mitogenactivated protein kinase Science 270, 1491–1494 (1995) 14 Filardo, E J., Quinn, J A., Bland, K I & Frackelton, A R Jr Estrogen-induced activation of Erk-1 and Erk-2 requires the G protein-coupled receptor homolog, GPR30, and occurs via trans-activation of the epidermal growth factor receptor through release of HBEGF Mol Endocrinol 14, 1649–1660 (2000) 15 Bi, R., Foy, M R., Vouimba, R.-M., Thompson, R F & Baudry, M Cyclic changes in estradiol regulate synaptic plasticity through the MAP kinase pathway Proc Natl Acad Sci USA 98, 13391–13395 (2001) 16 https://elksslnature.casb.nju.edu.cn:4443/articles/s43018-021-00215-7 4/23 16/6/2021 Serial single-cell genomics reveals convergent subclonal evolution of resistance as patients with early-stage breast cancer progress on e… Griffiths, 16 J I et al Reconstructing tumor trajectories during therapy through integration of multiple measurement modalities Preprint at bioRxiv https://elkssl0a75e822c6f3334851117f8769a30e1celksslnature.casb.nju.edu.cn:4443/10.110 1/2021.01.14.426737 (2021) 17 Berg, W A et al Combined screening with ultrasound and mammography vs mammography alone in women at elevated risk of breast cancer JAMA 299, 2151–2163 (2008) 18 Marinovich, M L et al Meta-analysis of magnetic resonance imaging in detecting residual breast cancer after neoadjuvant therapy J Natl Cancer Inst 105, 321–333 (2013)  19 Risso, D., Perraudeau, F., Gribkova, S., Dudoit, S & Vert, J P A general and flexible method for signal extraction from single-cell RNA-seq data Nat Commun 9, 284 (2018) 20 Stuart, T et al Comprehensive integration of single-cell data Cell 177, 1888–902 (2019) 21 Tickle, T I G C., Brown, M & Haas, B inferCNV of the Trinity CTAT Project 2019 https://elkssl99cd2175108d157588c04758296d1cfcelksslnature.casb.nju.edu.cn:4443/broadi nstitute/inferCNV (2019) 22 van der Maaten, L & Hinton, G Visualizing Data using t-SNE J Mach Learn Res 9, 2579–2605 (2008) 23 Aran, D et al Reference-based analysis of lung single-cell sequencing reveals a transitional profibrotic macrophage Nat Immunol 20, 163–172 (2019) 24 Roth, A et al PyClone: statistical inference of clonal population structure in cancer Nat Methods 11, 396–398 (2014) 25 https://elksslnature.casb.nju.edu.cn:4443/articles/s43018-021-00215-7 5/23 16/6/2021 Serial single-cell genomics reveals convergent subclonal evolution of resistance as patients with early-stage breast cancer progress on e… Brady, 25 S W et al Combating subclonal evolution of resistant cancer phenotypes Nat Commun 8, 1231 (2017) 26 Kim, C et al Chemoresistance evolution in triple-negative breast cancer delineated by single-cell sequencing Cell 173, 879–93 (2018) 27 Iwase, H et al Loss of heterozygosity of the oestrogen receptor gene in breast cancer Br J Cancer 71, 448–450 (1995) 28 Barbie, D A et al Systematic RNA interference reveals that oncogenic KRAS-driven cancers require TBK1 Nature 462, 108–112 (2009)  29 Liberzon, A et al Molecular signatures database (MSigDB) 3.0 Bioinformatics 27, 1739–1740 (2011) 30 Chen, S Y., Feng, Z & Yi, X A general introduction to adjustment for multiple comparisons J Thorac Dis 9, 1725–1729 (2017) 31 Herynk, M H & Fuqua, S A Estrogen receptor mutations in human disease Endocr Rev 25, 869–898 (2004) 32 Arpino, G., Wiechmann, L., Osborne, C K & Schiff, R Crosstalk between the estrogen receptor and the HER tyrosine kinase receptor family: molecular mechanism and clinical implications for endocrine therapy resistance Endocr Rev 29, 217–233 (2008) 33 Thomas, L W., Lam, C & Edwards, S W Mcl-1; the molecular regulation of protein function FEBS Lett 584, 2981–2989 (2010) 34 Hirata, Y., Sugie, A., Matsuda, A., Matsuda, S & Koyasu, S TAK1–JNK axis mediates survival signal through Mcl1 stabilization in activated T cells J Immunol 190, 4621–4626 (2013) https://elksslnature.casb.nju.edu.cn:4443/articles/s43018-021-00215-7 6/23 16/6/2021 Serial single-cell genomics reveals convergent subclonal evolution of resistance as patients with early-stage breast cancer progress on e… 35 35 Bausch-Fluck, D et al A mass spectrometric-derived cell surface protein atlas PLoS ONE 10, e0121314 (2015) 36 Zhu, Y et al Coregulation of estrogen receptor by ERBB4/HER4 establishes a growthpromoting autocrine signal in breast tumor cells Cancer Res 66, 7991–7998 (2006) 37 Tiong, K H., Mah, L Y & Leong, C O Functional roles of fibroblast growth factor receptors (FGFRs) signaling in human cancers Apoptosis 18, 1447–1468 (2013) 38 Brewer, J R., Mazot, P & Soriano, P Genetic insights into the mechanisms of Fgf signaling Genes Dev 30, 751–771 (2016)  39 Odawara, H et al Activation of aromatase expression by retinoic acid receptor-related orphan receptor (ROR) α in breast cancer cells: identification of a novel ROR response element J Biol Chem 284, 17711–17719 (2009) 40 Liu, Z et al Reconstructing cell cycle pseudo time-series via single-cell transcriptome data Nat Commun 8, 22 (2017) 41 Hortobagyi, G N et al Updated results from MONALEESA-2, a phase III trial of firstline ribociclib plus letrozole versus placebo plus letrozole in hormone receptor-positive, HER2-negative advanced breast cancer Ann Oncol 29, 1541–1547 (2018) 42 Finn, R S et al Palbociclib and letrozole in advanced breast cancer N Engl J Med 375, 1925–1936 (2016) 43 Goetz, M P et al MONARCH 3: abemaciclib as initial therapy for advanced breast cancer J Clin Oncol 35, 3638–3646 (2017) 44 Ichijo, H et al Induction of apoptosis by ASK1, a mammalian MAPKKK that activates SAPK/JNK and p38 signaling pathways Science 275, 90–94 (1997) https://elksslnature.casb.nju.edu.cn:4443/articles/s43018-021-00215-7 7/23 16/6/2021 Serial single-cell genomics reveals convergent subclonal evolution of resistance as patients with early-stage breast cancer progress on e… 45 45 Tobiume, K et al ASK1 is required for sustained activations of JNK/p38 MAP kinases and apoptosis EMBO Rep 2, 222–228 (2001) 46 Piccart-Gebhart, M et al Adjuvant lapatinib and trastuzumab for early human epidermal growth factor receptor 2-positive breast cancer: results from the randomized phase III adjuvant lapatinib and/or trastuzumab treatment optimization trial J Clin Oncol 34, 1034–1042 (2016) 47 von Minckwitz, G et al Adjuvant pertuzumab and trastuzumab in early HER2-positive breast cancer N Engl J Med 377, 122–131 (2017) 48 Ruíz-Borrego, M et al Phase III evaluating the addition of fulvestrant (F) to anastrozole (A) as adjuvant therapy in postmenopausal women with hormone receptor-positive HER2negative (HR+/HER2−) early breast cancer (EBC): results from the GEICAM/2006-10 study Breast Cancer Res Treat 177, 115–125 (2019) 49 Johnston, S et al Randomized phase ii study evaluating palbociclib in addition to letrozole as neoadjuvant therapy in estrogen receptor-positive early breast cancer: PALLET trial J Clin Oncol 37, 178–189 (2019) 50 La Marca, J E & Richardson, H E Two-faced: roles of JNK signalling during tumourigenesis in the drosophila model Front Cell Dev Biol https://elkssl0a75e822c6f3334851117f8769a30e1celksslnature.casb.nju.edu.cn:4443/10.338 9/fcell.2020.00042 (2020) 51 Pinal, N., Calleja, M & Morata, G Pro-apoptotic and pro-proliferation functions of the JNK pathway of drosophila: roles in cell competition, tumorigenesis and regeneration Open Biol 9, 180256 (2019) 52 Colleoni, B et al JNKs function as CDK4-activating kinases by phosphorylating CDK4 and p21 Oncogene 36, 4349–4361 (2017) https://elksslnature.casb.nju.edu.cn:4443/articles/s43018-021-00215-7 8/23 16/6/2021 Serial single-cell genomics reveals convergent subclonal evolution of resistance as patients with early-stage breast cancer progress on e… 53 53 Zhang, J Y., Tao, S., Kimmel, R & Khavari, P A CDK4 regulation by TNFR1 and JNK is required for NF-κB-mediated epidermal growth control J Cell Biol 168, 561–566 (2005) 54 Hafner, M et al Multiomics profiling establishes the polypharmacology of FDAapproved CDK4/6 inhibitors and the potential for differential clinical activity Cell Chem Biol 26, 1067–1080 (2019) 55 Dowsett, M et al Short-term changes in Ki-67 during neoadjuvant treatment of primary breast cancer with anastrozole or tamoxifen alone or combined correlate with recurrencefree survival Clin Cancer Res 11, 951s–958ss (2005)  56 Chen, X & Chang, J T Planning bioinformatics workflows using an expert system Bioinformatics 33, 1210–1215 (2017) 57 Bolger, A M., Lohse, M & Usadel, B Trimmomatic: a flexible trimmer for Illumina sequence data Bioinformatics 30, 2114–2120 (2014) 58 Li, H & Durbin, R Fast and accurate short read alignment with Burrows–Wheeler transform Bioinformatics 25, 1754–1760 (2009) 59 Li, H & Durbin, R Fast and accurate long-read alignment with Burrows–Wheeler transform Bioinformatics 26, 589–595 (2010) 60 Li H Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM Preprint at https://elkssla397d5726bfea6381bf48d983992cffcelksslnature.casb.nju.edu.cn:4443/abs/130 3.3997 (2013) 61 Picard T Broad Institute, GitHub Repository https://8271ceebc793cbd0902d1229733a5b52elksslnature.casb.nju.edu.cn:4443/picard/ (2019) https://elksslnature.casb.nju.edu.cn:4443/articles/s43018-021-00215-7 9/23 16/6/2021 Serial single-cell genomics reveals convergent subclonal evolution of resistance as patients with early-stage breast cancer progress on e… 62 McKenna, A et al The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data Genome Res 20, 1297–1303 (2010) 63 Kim, S et al Strelka2: fast and accurate calling of germline and somatic variants Nat Methods 15, 591–594 (2018) 64 Koboldt, D C et al VarScan 2: somatic mutation and copy number alteration discovery in cancer by exome sequencing Genome Res 22, 568–576 (2012) 65 Wang, K., Li, M & Hakonarson, H ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data Nucleic Acids Res 38, e164 (2010)  66 Shen, R & Seshan, V E FACETS: allele-specific copy number and clonal heterogeneity analysis tool for high-throughput DNA sequencing Nucleic Acids Res 44, e131 (2016) 67 Favero, F et al Sequenza: allele-specific copy number and mutation profiles from tumor sequencing data Ann Oncol 26, 64–70 (2015) 68 Dang, H X et al ClonEvol: clonal ordering and visualization in cancer sequencing Ann Oncol 28, 3076–3082 (2017) 69 Sei, E., Bai, S & Navin, N Dissociation of nuclear suspensions from human breast tissues protocols.io https://elkssl0a75e822c6f3334851117f8769a30e1celksslnature.casb.nju.edu.cn:4443/10.175 04/protocols.io.t3aeqie (2018) 70 Liao, Y., Smyth, G K & Shi, W featureCounts: an efficient general purpose program for assigning sequence reads to genomic features Bioinformatics 30, 923–930 (2014) 71 Müllner, D fastcluster: fast hierarchical, agglomerative clustering routines for R and Python J Stat Softw 53, 1–18 (2013) https://elksslnature.casb.nju.edu.cn:4443/articles/s43018-021-00215-7 10/23 16/6/2021 Serial single-cell genomics reveals convergent subclonal evolution of resistance as patients with early-stage breast cancer progress on e… 72 Hänzelmann, S., Castelo, R & Guinney, J GSVA: gene set variation analysis for microarray and RNA-seq data BMC Bioinf 14, (2013) 73 Bolker, B M et al Generalized linear mixed models: a practical guide for ecology and evolution Trends Ecol Evol 24, 127–135 (2009) 74 Kuznetsova, A., Brockhoff, P B & Christensen, R H B lmerTest Package: tests in linear mixed effects models J Stat Softw https://elkssl0a75e822c6f3334851117f8769a30e1celksslnature.casb.nju.edu.cn:4443/10.186 37/jss.v082.i13 (2017) 75 Pedersen, E J., Miller, D L., Simpson, G L & Ross, N Hierarchical generalized  additive models in ecology: an introduction with mgcv PeerJ 7, e6876 (2019) 76 Yates A D et al Ensembl 2020 Nucleic Acids Res https://elkssl0a75e822c6f3334851117f8769a30e1celksslnature.casb.nju.edu.cn:4443/10.109 3/nar/gkz966 (2020) 77 Hahsler, M & Hornik, K TSP: infrastructure for the traveling salesperson problem J Stat Softw https://elkssl0a75e822c6f3334851117f8769a30e1celksslnature.casb.nju.edu.cn:4443/10.186 37/jss.v023.i02 (2007) Acknowledgements We thank the anonymous patients from the trial that made this study possible A.H.B., J.G., J.C., J.T.C., P.C and F.A were supported by the National Cancer Institute of the National Institutes of Health (NIH) under award number U54CA209978 The content is solely the authors responsibility and does not necessarily represent the official views of the NIH The HighThroughput Genomics Shared Resource was supported by the NIH award number P30CA042014 The Integrative Genomics Core was supported by NIH award number P30CA33572 J.T.C was https://elksslnature.casb.nju.edu.cn:4443/articles/s43018-021-00215-7 11/23 16/6/2021 Serial single-cell genomics reveals convergent subclonal evolution of resistance as patients with early-stage breast cancer progress on e… supported by a Cancer Prevention Research Institute of Texas Core Facility Support Award (RP170668) Author information Jinfeng Chen Present address: State Key Laboratory of Integrated Management of Pest Insects and Rodents, Institute of Zoology, Chinese Academy of Sciences, Beijing, China These authors contributed equally: Jason I Griffiths, Jinfeng Chen  These authors jointly supervised this work: Andrea H Bild, Qamar J Khan Affiliations Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, CA, USA Jason I Griffiths, Jinfeng Chen, Patrick A Cosgrove & Andrea H Bild Department of Mathematics, University of Utah, Salt Lake City, UT, USA Jason I Griffiths & Frederick R Adler Division of Medical Oncology, University of Kansas Medical Center, Westwood, KS, USA Anne O’Dea, Priyanka Sharma & Qamar J Khan Division of Oncology, Washington University School of Medicine, St Louis, MO, USA Cynthia Ma https://elksslnature.casb.nju.edu.cn:4443/articles/s43018-021-00215-7 12/23 16/6/2021 Serial single-cell genomics reveals convergent subclonal evolution of resistance as patients with early-stage breast cancer progress on e… Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA Meghna Trivedi & Kevin Kalinsky Department of Medicine, University of Wisconsin School of Medicine and Public Health, Carbone Cancer Center, Madison, WI, USA Kari B Wisinski & Ruth O’Regan Division of Internal Medical Oncology, University of Arkansas for Medical Sciences, Fayetteville, AR, USA  Issam Makhoul Department of Medicine, Massachusetts General Hospital Cancer Center and Harvard Medical School, Boston, MA, USA Laura M Spring & Aditya Bardia School of Biological Sciences, University of Utah, Salt Lake City, UT, USA Frederick R Adler 10 Department of Internal Medicine, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA Adam L Cohen 11 Department of Integrative Biology and Pharmacology, School of Medicine, School of Biomedical Informatics, UT Health Sciences Center at Houston, Houston, TX, USA Jeffrey T Chang https://elksslnature.casb.nju.edu.cn:4443/articles/s43018-021-00215-7 13/23 16/6/2021 Serial single-cell genomics reveals convergent subclonal evolution of resistance as patients with early-stage breast cancer progress on e… Contributions J.I.G contributed to study design and coordination, evaluated patient response to therapies, analyzed tumor heterogeneity, identified response-related phenotypes using scRNA-Seq ssGSEA pathway analysis, quantified resistance phenotypes using mathematical models, linked genetic copy-number alterations to phenotypes, reconstructed cancer cell cycle transition and gene expression and wrote the manuscript J.C conducted the bioinformatics pipelines to process DNA and scRNA-seq data, performed normalization and cell type classification, conducted structural variation analysis of whole-genome sequencing, determined subclonal tumor structure, analyzed WES data and contributed to writing the manuscript P.C performed scRNA and whole-genome sequencing experiment, and managed the project’s datasets A.O.D., P.S., C.M., M.T., K.K., K.B.W., R.O.R., I.M., L.M.S and A.B contributed patient samples and contributed to writing the manuscript F.R.A developed analyses and models and contributed to writing the manuscript J.T.C developed bioinformatics pipelines, performed data management and curation, conducted data analysis and wrote the manuscript A.L.C contributed to data analysis and study design, provided clinical insight and contributed to writing the manuscript Q.K conceived and coordinated the clinical trial, contributed clinical support and infrastructure and provided clinical data and patient samples as well as contributed to writing the manuscript A.H.B designed the research project and analyses, performed scRNA experiments and data analysis, coordinated genomic and mathematical/statistical analyses and wrote the manuscript Corresponding authors Correspondence to Qamar J Khan or Andrea H Bild Ethics declarations Competing interests R.O.R participates on the advisory board for Cyclacel, PUMA, Biotheranostics, Lilly, Pfizer, Genentech and Novartis; and declares research funding from Pfizer, Novartis, Seattle Genetics and PUMA P.S declares research funding from Novartis, Merck and Bristol Myers Squibb; and https://elksslnature.casb.nju.edu.cn:4443/articles/s43018-021-00215-7 14/23 16/6/2021 Serial single-cell genomics reveals convergent subclonal evolution of resistance as patients with early-stage breast cancer progress on e… consulting for Seattle Genetics, Merck, Novartis, Astra Zeneca, Immunomedics and Exact Biosciences L.M.S participates on the advisory board for Novartis, Lumicell, Puma Biotechnology and Avrobio C.M declares research funding from Pfizer and Puma; and consulting for Eisai, Athenex, OncoSignal, Agendia, Biovica, Astra Zeneca and Seattle Genetics K.B.W declares research funding and clinical trial involvement with Novartis, Eli Lilly, Astra Zeneca, Sanofi and Pfizer He participated on an advisory board for Eisai, Pfizer and Astra Zeneca K.K is a medical advisor to Immunomedics, Pfizer, Novartis, Eisai, Eli Lilly, Amgen, Merck, Seattle Genetics and Astra Zeneca; receives institutional support from Immunomedics, Novartis, Incyte, Genentech/Roche, Eli Lilly, Pfizer, Calithera Biosciences, Acetylon, Seattle Genetics, Amgen, Zentalis Pharmaceuticals and CytomX Therapeutics; and his spouse is employed by Grail and previously by Array Biopharma and Pfizer A.O.D consults for Pfizer, PUMA Biotechnology, Astra Zeneca and Daiichi Sankyo Q.J.K declares research funding from  Novartis All other authors have no conflicts of interest to disclose Additional information Peer review information Nature Cancer thanks Paolo Tarantino and the other, anonymous, reviewer(s) for their contribution to the peer review of this work Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations Extended data Extended Data Fig Classification of patient tumors as sensitive or resistant to treatment, reflecting changes in tumor size observed at pathology relative to baseline Reconstructed trajectories of tumor burden are consistent with results of RECIST 1.1 MRI assessment at day 90 and allow sensitive and resistant tumors to be distinguished at end of treatment (day 180) a, Changes in tumor size during therapy for tumors classified as sensitive or resistant Tumor growth (y-axis) calculated directly from data as the proportion tumor remaining at end of trial (final observed tumor size at pathology/baseline MRI tumor measurement) Values https://elksslnature.casb.nju.edu.cn:4443/articles/s43018-021-00215-7 15/23 16/6/2021 Serial single-cell genomics reveals convergent subclonal evolution of resistance as patients with early-stage breast cancer progress on e… 1 indicate an increase in size (Dashed horizontal line = no change in size during trial) A detailed biological response classification was determined by classifying tumors with similar trajectories using a Gaussian mixture model (colors) Sustained or partial responses were grouped and defined as sensitive tumors, whilst those with stable, progressive or rebound disease were classified as resistant tumors The changes in tumor size are highly significantly different between resistance categories (two-sided ANOVA test: t=4.45, p