Single-cell transcriptional atlas of human breast cancers and model systems

Abstract

	•Patient-derived xenografts models more closely resemble patient samples in tumour heterogeneity and cell cycle characteristics when compared with cell lines.
	•3D organoid models exhibit differences in metabolic profiles compared to their in vivo counterparts.
	•A valuable multimodel reference dataset that can be useful in elucidating model differences and novel targetable pathways.

Keywords

breast cancer / cellular heterogeneity / model limitations / preclinical research / single-cell RNA sequencing / single-cell transcriptomics / subtype-specific insights / targetable pathways / therapeutic drug efficacy

References

[1] SiegelRL, MillerKD, WagleNS, Jemal A. Cancer statistics, 2023. Cancer J Clin. 2023; 73: 17-48.

[2] DesantisCE, MaJ, GaudetMM. Breast cancer statistics, 2019. Cancer J Clin. 2019; 69: 438-451.

[3] MaJ, JemalA. Breast Cancer Metastasis and Drug Resistance: Progress and Prospects. Springer; 2013: 1-18. Breast Cancer Statistics. ed. Ahmad, A..

[4] The Cancer Genome Atlas Network. Comprehensive molecular portraits of human breast tumours. Nature. 2012; 490: 61-70.

[5] KandothC, Mclellan MD, VandinF, et al. Mutational landscape and significance across 12 major cancer types. Nature. 2013; 502: 333-339.

[6] CurtisC, ShahSP, ChinS-F, et al. The genomic and transcriptomic architecture of 2, 000 breast tumours reveals novel subgroups. Nature. 2012; 486: 346-352.

[7] HuberKE, CareyLA, WazerDE. Breast cancer molecular subtypes in patients with locally advanced disease: impact on prognosis, patterns of recurrence, and response to therapy. Semin Radiat Oncol. 2009; 19(4): 204-210.

[8] PerouCM, Sørlie T, EisenMB, et al. Molecular portraits of human breast tumours. Nature. 2000; 406: 747-752.

[9] SørlieT, PerouCM, TibshiraniR, et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci. 2001; 98: 10869-10874.

[10] WuSZ, Al-Eryani G, RodenDL, et al. A single-cell and spatially resolved atlas of human breast cancers. Nat Genet. 2021; 53: 1334-1347.

[11] SørlieT, Tibshirani R, ParkerJ, et al. Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc Natl Acad Sci. 2003; 100: 8418-8423.

[12] TestaU, Castelli G, PelosiE. Breast cancer: a molecularly heterogenous disease needing subtype-specific treatments. Med Sci. 2020; 8: 18.

[13] MyersMB. Targeted therapies with companion diagnostics in the management of breast cancer: current perspectives. Pharmacogenomics Pers Med. 2016: 7-16.

[14] EssadiI, Benbrahim Z, KaakouaM, ReverdyT, Corbaux P, FreyerG. HER2-positive metastatic breast cancer: available treatments and current developments. Cancers. 2023; 15: 1738.

[15] LehmannBD, BauerJA, ChenXi, et al. Identification of human triple-negative breast cancer subtypes and preclinical models for selection of targeted therapies. J Clin Invest. 2011; 121: 2750-2767.

[16] LehmannBD, Jovanović B, ChenXi, et al. Refinement of triple-negative breast cancer molecular subtypes: implications for neoadjuvant chemotherapy selection. PLOS ONE. 2016; 11: e0157368.

[17] Ismail-KhanR, BuiMM. A review of triple-negative breast cancer. Cancer Control. 2010; 17: 173-176.

[18] DentR, Trudeau M, PritchardKI, et al. Triple-negative breast cancer: clinical features and patterns of recurrence. Clin Cancer Res. 2007; 13: 4429-4434.

[19] QiuJ, XueX, HuC, et al. Comparison of clinicopathological features and prognosis in triple-negative and non-triple negative breast cancer. J Cancer. 2016; 7: 167.

[20] YuanZY, et al. Clinical characteristics and prognosis of triple-negative breast cancer: a report of 305 cases. Ai Zheng Aizheng Chin J Cancer. 2008; 27: 561-565.

[21] ShapiroE, Biezuner T, LinnarssonS. Single-cell sequencing-based technologies will revolutionize whole-organism science. Nat Rev Genet. 2013; 14: 618-630.

[22] SharmaSV, LeeDY, LiB, et al. A chromatin-mediated reversible drug-tolerant state in cancer cell subpopulations. Cell. 2010; 141: 69-80.

[23] RosatiD, Giordano A. Single-cell RNA sequencing and bioinformatics as tools to decipher cancer heterogenicity and mechanisms of drug resistance. Biochem Pharmacol. 2022; 195: 114811.

[24] LeeHW, et al. Single-cell RNA sequencing reveals the tumor microenvironment and facilitates strategic choices to circumvent treatment failure in a chemorefractory bladder cancer patient. Genome Med. 2022; 12: 1-21.

[25] KanT, ZhangS, ZhouS, et al. Single-cell RNA-seq recognized the initiator of epithelial ovarian cancer recurrence. Oncogene. 2022; 41: 895-906.

[26] BP, et al. A single-cell RNA expression atlas of normal, preneoplastic and tumorigenic states in the human breast. EMBO J. 2021; 40.

[27] RakhaEA, El-Sayed ME, GreenAR, LeeAHS, Robertson JF, EllisIO. Prognostic markers in triple-negative breast cancer. Cancer. 2007; 109: 25-32.

[28] ImrichS, Hachmeister M, GiresO. EpCAM and its potential role in tumor-initiating cells. Cell Adhes Migr. 2012; 6: 30-38.

[29] RingA, Mineyev N, ZhuW, et al. EpCAM based capture detects and recovers circulating tumor cells from all subtypes of breast cancer except claudin-low. Oncotarget. 2015; 6: 44623.

[30] LimE, WuDi, PalB, et al. Transcriptome analyses of mouse and human mammary cell subpopulations reveal multiple conserved genes and pathways. Breast Cancer Res. 2010; 12: 1-14.

[31] SebastianA, HumNR, MartinKA, et al. Single-cell transcriptomic analysis of tumor-derived fibroblasts and normal tissue-resident fibroblasts reveals fibroblast heterogeneity in breast cancer. Cancers. 2020; 12: 1307.

[32] García-TeijidoP, Cabal ML, FernándezIP, PérezYF. Tumor-infiltrating lymphocytes in triple negative breast cancer: the future of immune targeting. Clin Med Insights Oncol. 2016; 10s1:CMO.S34540.

[33] VonderheideRH, Domchek SM, ClarkAS. Immunotherapy for breast cancer: what are we missing. Clin Cancer Res Off J Am Assoc Cancer Res. 2017; 23: 2640-2646.

[34] GoldbergJ, Pastorello RG, ValliusT, et al. The immunology of hormone receptor positive breast cancer. Front Immunol. 2021; 12: 674192.

[35] GoRS, AdjeiAA. Review of the comparative pharmacology and clinical activity of cisplatin and carboplatin. J Clin Oncol. 1999; 17: 409-409.

[36] GuillenKP, FujitaM, ButterfieldAJ, et al. A human breast cancer-derived xenograft and organoid platform for drug discovery and precision oncology. Nat Cancer. 2022; 3: 232-250.

[37] KangYP, Mockabee-Macias A, JiangC, et al. Non-canonical glutamate-cysteine ligase activity protects against ferroptosis. Cell Metab. 2021; 33: 174-189.

[38] ParkerJS, Mullins M, CheangMCU, et al. Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol. 2009; 27: 1160.

[39] GendooDMA, Ratanasirigulchai N, SchroederMS, et al. genefu: Computation of Gene Expression-Based Signatures in Breast Cancer. [Internet].2020. Available from: https://bioconductor.org/packages/genefu

[40] BeltjensF, MollyD, BertautA, et al. ER–/PR+ breast cancer: a distinct entity, which is morphologically and molecularly close to triple-negative breast cancer. Int J Cancer. 2021; 149: 200-213.

[41] GroenendijkFH, TreeceT, YoderE, et al. Estrogen receptor variants in ER-positive basal-type breast cancers responding to therapy like ER-negative breast cancers. Npj Breast Cancer. 2019; 5: 1-8.

[42] IwamotoT, BooserD, ValeroV, et al. Estrogen receptor (ER) mRNA and ER-related gene expression in breast cancers that are 1% to 10% ER-positive by immunohistochemistry. J Clin Oncol. 2012; 30: 729-734.

[43] DeyarminB, KaneJL, ValenteAL, et al. Effect of ASCO/CAP guidelines for determining ER status on molecular subtype. Ann Surg Oncol. 2013; 20: 87-93.

[44] ThompsonKJ, Leon-Ferre RA, SinnwellJP, et al. Luminal androgen receptor breast cancer subtype and investigation of the microenvironment and neoadjuvant chemotherapy response. NAR Cancer. 2022; 4: zcac018.

[45] LehmannBD, BauerJA, SchaferJM, et al. PIK3CA mutations in androgen receptor-positive triple negative breast cancer confer sensitivity to the combination of PI3K and androgen receptor inhibitors. Breast Cancer Res. 2014; 16: 1-14.

[46] VoutsadakisIA. Comparison of clinical subtypes of breast cancer within the claudin-low molecular cluster reveals distinct phenotypes. Cancers. 2023; 15: 2689.

[47] PratA, ParkerJS, KarginovaO, et al. Phenotypic and molecular characterization of the claudin-low intrinsic subtype of breast cancer. Breast Cancer Res. 2010; 12: R68.

[48] PratA, Karginova O, ParkerJS, et al. Characterization of cell lines derived from breast cancers and normal mammary tissues for the study of the intrinsic molecular subtypes. Breast Cancer Res Treat. 2013; 142: 237-255.

[49] ThennavanA. Adapting bulk and single cell RNA sequencing for molecular analysis of breast pathology. The University of North Carolina at Chapel Hill, United States – North Carolina; 2022.

[50] ZborilEK, GribleJM, BoydDC, et al. Stratification of tamoxifen synergistic combinations for the treatment of ER+ breast cancer. Cancers. 2023; 15: 3179.

[51] TzukermanM, et al. The human estrogen receptor has transcriptional activator and repressor functions in the absence of ligand. New Biol. 1990; 2: 613-620.

[52] ShangY, HuX, DiRenzoJ, Lazar MA, BrownM. Cofactor dynamics and sufficiency in estrogen receptor–regulated transcription. Cell. 2000; 103: 843-852.

[53] KimMY,. A role for coactivators and histone acetylation in estrogen receptor α-mediated transcription initiation. EMBO J. 2001; 20: 6084-6094.

[54] ChoH, Katzenellenbogen BS. Synergistic activation of estrogen receptor-mediated transcription by estradiol and protein kinase activators. Mol Endocrinol. 1993; 7: 441-452.

[55] GronemeyerH. Transcription activation by estrogen and progesterone receptors. Annu Rev Genet. 1991; 25: 89-123.

[56] JonesPS, Parrott E, WhiteINH. Activation of transcription by estrogen receptor α and β is cell type-and promoter-dependent. J Biol Chem. 1999; 274: 32008-32014.

[57] HashimotoY, Masunaga N, KagaraN, et al. Detection of ultra-rare ESR1 mutations in primary breast cancer using LNA-Clamp ddPCR. Cancers. 2023; 15: 2632.

[58] JeselsohnR, Bergholz JS, PunM, et al. Allele-specific chromatin recruitment and therapeutic vulnerabilities of ESR1 activating mutations. Cancer Cell. 2018; 33: 173-186.

[59] VtorushinS, Dulesova A, KrakhmalN. Luminal androgen receptor (LAR) subtype of triple-negative breast cancer: molecular, morphological, and clinical features. J Zhejiang Univ Sci B. 2022; 23: 617-624.

[60] The NExT Screening Libraries (Pre-plated Copies Available) | Discovery | NExT Resources | NExT. Accessed January 4, 2024. https://next.cancer.gov/discoveryresources/resources_ndl.htm#oncology_interrogation_tools

[61] TurnerTH, AlzubiMA, HarrellJC. Identification of synergistic drug combinations using breast cancer patient-derived xenografts. Sci Rep. 2020; 10: 1493.

[62] BoydDC, ZborilEK, OlexAL, et al. Discovering synergistic compounds with BYL-719 in PI3K overactivated basal-like PDXs. Cancers. 2023; 15: 1582.

[63] BudimirI, Tomasović-Lončarić Č, KralikK, et al. Higher expressions of SHH and AR are associated with a positive receptor status and have impact on survival in a cohort of croatian breast cancer patients. Life. 2022; 12: 1559.

[64] UengS-H, et al. Phosphorylated mTOR expression correlates with poor outcome in early-stage triple negative breast carcinomas. Int J Clin Exp Pathol. 2013; 5: 806-813.

[65] WalshS, Flanagan L, QuinnC, et al. mTOR in breast cancer: differential expression in triple-negative and non-triple-negative tumors. Breast Edinb Scotl. 2012; 21: 178-182.

[66] BryantC, Rawlinson R, MasseyAJ. Chk1 Inhibition as a novel therapeutic strategy for treating triple-negative breast and ovarian cancers. BMC Cancer. 2014; 14: 570.

[67] ZhouZ-R, YangZ-Z, WangS-J, et al. The Chk1 inhibitor MK-8776 increases the radiosensitivity of human triple-negative breast cancer by inhibiting autophagy. Acta Pharmacol Sin. 2017; 38: 513-523.

[68] KaiK, KondoK, WangX, et al. Antitumor activity of KW-2450 against triple-negative breast cancer by inhibiting Aurora A and B kinases. Mol Cancer Ther. 2015; 14: 2687-2699.

[69] SongC, LoweVJ, LeeS. Inhibition of Cdc20 suppresses the metastasis in triple negative breast cancer (TNBC). Breast Cancer. 2021; 28: 1073-1086.

[70] RomanelliA, ClarkA, AssayagF, et al. Inhibiting aurora kinases reduces tumor growth and suppresses tumor recurrence after chemotherapy in patient-derived triple-negative breast cancer xenografts. Mol Cancer Ther. 2012; 11: 2693-2703.

[71] MaCX, CaiS, LiS, et al. Targeting Chk1 in p53-deficient triple-negative breast cancer is therapeutically beneficial in human-in-mouse tumor models. J Clin Invest. 2012; 122: 1541-1552.

[72] HonmaN, HoriiR, ItoY, et al. Differences in clinical importance of Bcl-2 in breast cancer according to hormone receptors status or adjuvant endocrine therapy. BMC Cancer. 2015; 15: 698.

[73] MerinoD, LokSW, VisvaderJE, Lindeman GJ. Targeting BCL-2 to enhance vulnerability to therapy in estrogen receptor-positive breast cancer. Oncogene. 2016; 35: 1877-1887.

[74] Terranova-BarberioM, Thomas S, AliN, et al. HDAC inhibition potentiates immunotherapy in triple negative breast cancer. Oncotarget. 2017; 8: 114156.

[75] MaitiA, et al. Class I histone deacetylase inhibitor suppresses vasculogenic mimicry by enhancing the expression of tumor suppressor and anti-angiogenesis genes in aggressive human TNBC cells. Int J Oncol. 2019; 55: 116-130.

[76] GiltnaneJM, BalkoJM. Rationale for targeting the Ras/MAPK pathway in triple-negative breast cancer. Discov Med. 2014; 17: 275-283.

[77] JiangW, WangX, ZhangC, Xue L, YangL. Expression and clinical significance of MAPK and EGFR in triple negative breast cancer. Oncol Lett. 2020; 19: 1842-1848.

[78] BalkoJM, Schwarz LJ, BholaNE, et al. Activation of MAPK pathways due to DUSP4 loss promotes cancer stem cell-like phenotypes in basal-like breast cancer. Cancer Res. 2013; 73: 6346-6358.

[79] BartholomeuszC, XieX, PitnerMK, et al. MEK inhibitor selumetinib (AZD6244; ARRY-142886) prevents lung metastasis in a triple-negative breast cancer xenograft model. Mol Cancer Ther. 2015; 14: 2773-2781.

[80] MatossianMD, HoangVT, BurksHE, et al. Constitutive activation of MEK5 promotes a mesenchymal and migratory cell phenotype in triple negative breast cancer. Oncoscience. 2021; 8: 64.

[81] CoussyF, Lavigne M, De KoningL, et al. Response to mTOR and PI3K inhibitors in enzalutamide-resistant luminal androgen receptor triple-negative breast cancer patient-derived xenografts. Theranostics. 2020; 10: 1531.

[82] BashoRK, ZhaoLi, WhiteJB, et al. Comprehensive analysis identifies variability in PI3K pathway alterations in triple-negative breast cancer subtypes. JCO Precis Oncol. 2024; 8: e2300124.

[83] KumarS, BalA, DasA, et al. Spectrum of PIK3CA/AKT mutations across molecular subtypes of triple-negative breast cancer. Breast Cancer Res Treat. 2021; 187: 625-633.

[84] AziziE, CarrAJ, PlitasG, et al. Single-cell map of diverse immune phenotypes in the breast tumor microenvironment. Cell. 2018; 174: 1293-1308.

[85] DeroseYS, WangG, LinYi-C, et al. Tumor grafts derived from women with breast cancer authentically reflect tumor pathology, growth, metastasis and disease outcomes. Nat Med. 2011; 17: 1514-1520.

[86] EirewP, SteifA, KhattraJ, et al. Dynamics of genomic clones in breast cancer patient xenografts at single-cell resolution. Nature. 2015; 518: 422-426.

[87] SachsN, De Ligt J, KopperO, et al. A living biobank of breast cancer organoids captures disease heterogeneity. Cell. 2018; 172: 373-386.

[88] DieciMV, Criscitiello C, GoubarA, et al. Prognostic value of tumor-infiltrating lymphocytes on residual disease after primary chemotherapy for triple-negative breast cancer: a retrospective multicenter study. Ann Oncol. 2014; 25: 611-618.

[89] DisisML, Stanton SE. Triple-negative breast cancer: immune modulation as the new treatment paradigm. Am Soc Clin Oncol Educ Book. 2015: e25-e30.

[90] DenkertC, Von Minckwitz G, Darb-EsfahaniS, et al. Tumour-infiltrating lymphocytes and prognosis in different subtypes of breast cancer: a pooled analysis of 3771 patients treated with neoadjuvant therapy. Lancet Oncol. 2018; 19: 40-50.

[91] BertucciF, Finetti P, GoncalvesA, BirnbaumD. The therapeutic response of ER+/HER2– breast cancers differs according to the molecular Basal or Luminal subtype. Npj Breast Cancer. 2020; 6: 1-7.

[92] KüngA, Strickmann DB, GalanskiMS, KepplerBK. Comparison of the binding behavior of oxaliplatin, cisplatin and analogues to 5′-GMP in the presence of sulfur-containing molecules by means of capillary electrophoresis and electrospray mass spectrometry. J Inorg Biochem. 2001; 86: 691-698.

[93] LiH, SunX, LiJ, et al. Hypoxia induces docetaxel resistance in triple-negative breast cancer via the HIF-1α/miR-494/Survivin signaling pathway. Neoplasia. 2022; 32: 100821.

[94] NedeljkovićM, Damjanović A. Mechanisms of chemotherapy resistance in triple-negative breast cancer – how we can rise to the challenge. Cells. 2019; 8: 957.

[95] KrawczykZ, Gogler-Pigłowska A, SojkaDR, ScieglinskaD. The role of heat shock proteins in cisplatin resistance. Anti-Cancer Agents Med Chem-Anti-Cancer Agents. 2018; 18: 2093-2109.

[96] ShenWH, Balajee AS, WangJ, et al. Essential role for nuclear PTEN in maintaining chromosomal integrity. Cell. 2007; 128: 157-170.

[97] GuptaA, YangQ, PanditaRK, et al. Cell cycle checkpoint defects contribute to genomic instability in PTEN deficient cells independent of DNA DSB repair. Cell Cycle. 2009; 8: 2198-2210.

[98] ZhaoJ-L, YangJ, LiKe, et al. Abrogation of ATR function preferentially augments cisplatin-induced cytotoxicity in PTEN-deficient breast cancer cells. Chem Biol Interact. 2023; 385: 110740.

[99] SolainiG, SgarbiG, BaraccaA. Oxidative phosphorylation in cancer cells. Biochim Biophys Acta BBA – Bioenerg. 2011; 1807: 534-542.

[100] SemenzaGL. Defining the role of hypoxia-inducible factor 1 in cancer biology and therapeutics. Oncogene. 2010; 29: 625-634.

[101] LiaoC, Glodowski CR, FanC, et al. Integrated metabolic profiling and transcriptional analysis reveals therapeutic modalities for targeting rapidly proliferating breast cancers. Cancer Res. 2022; 82: 665-680.

[102] BrettJO, SpringLM, BardiaA, Wander SA. ESR1 mutation as an emerging clinical biomarker in metastatic hormone receptor-positive breast cancer. Breast Cancer Res. 2021; 23: 85.

[103] HoySM. Elacestrant: first approval. Drugs. 2023; 83: 555-561.

[104] StellaS, Martorana F, MassiminoM, VitaleSR, Manzella L, VigneriP. Potential therapeutic targets for luminal androgen receptor breast cancer: what we know so far. OncoTargets Ther. 2023; 16: 235-247.

[105] GerratanaL, BasileD, BuonoG, et al. Androgen receptor in triple negative breast cancer: a potential target for the targetless subtype. Cancer Treat Rev; 68: 2018.

[106] HicksSC, TownesFW, TengM, Irizarry RA. Missing data and technical variability in single-cell RNA-sequencing experiments. Biostatistics. 2018; 19: 562-578.

[107] RashidNS, HairrNS, MurrayG, et al. Identification of nuclear export inhibitor-based combination therapies in preclinical models of triple-negative breast cancer. Transl Oncol. 2021; 14: 10123.

[108] TurnerTH, AlzubiMA, SohalSS, Olex AL, DozmorovMG, HarrellJC. Characterizing the efficacy of cancer therapeutics in patient-derived xenograft models of metastatic breast cancer. Breast Cancer Res Treat. 2018; 170: 221-234.

[109] MillerTE, MackSC, RichJN. Mouse Cell Depletion. Miltenyi Biotec.

[110] ChenY, PalB, LindemanGJ, Visvader JE, SmythGK. R code and downstream analysis objects for the scRNA-seq atlas of normal and tumorigenic human breast tissue. Sci Data. 2022; 9: 96.

[111] AndrewsS. FastQC: a quality control tool for high throughput sequence data. 2018. Accessed October 9, 2024. Available online: https://www.bioinformatics.babraham.ac.uk/projects/fastqc/

[112] EwelsP, Magnusson M, LundinS, KällerM. MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics. 2016; 32(19): 3047-3048.

[113] Cell ranger secondary analysis outputs—official 10x Genomics Support. 10x Genomics. Accessed February 27, 2024. https://www.10xgenomics.com/support/software/cell-ranger/latest/analysis/outputs/cr-outputs-secondary-analysis

[114] HaoY, HaoS, Andersen-NissenE, et al. Integrated analysis of multimodal single-cell data. Cell. 2021; 184: 3573-3587.

[115] Common Considerations for Quality Control Filters for Single Cell RNA-seq Data. 10x Genomics. Accessed September 4, 2024. https://www.10xgenomics.com/analysis-guides/common-considerations-for-quality-control-filters-for-single-cell-rna-seq-data

[116] Ahlmann-EltzeC, HuberW. Comparison of transformations for single-cell RNA-seq data. Nat Methods. 2023; 20: 665-672.

[117] DaveA, Charytonowicz D, FrancoeurNJ, et al. The Breast Cancer Single-Cell Atlas: defining cellular heterogeneity within model cell lines and primary tumors to inform disease subtype, stemness, and treatment options. Cell Oncol. 2023; 46: 603-628.

[118] AntonssonSE, Melsted P. Batch correction methods used in single cell RNA-sequencing analyses are often poorly calibrated. bioRxiv. 2024; 2024.03.19.585562 Preprint at doi:10.1101/2024.03.19585562

[119] KrämerA, GreenJ, PollardJ, Tugendreich S. Causal analysis approaches in Ingenuity Pathway Analysis. Bioinforma Oxf Engl. 2014; 30: 523-530.

[120] ChoiJ-H, In KimH, WooHG. scTyper: a comprehensive pipeline for the cell typing analysis of single-cell RNA-seq data. BMC Bioinformatics. 2020; 21: 342.

[121] TickleT, TiroshI, GeorgescuC, Brown M, HaasB. inferCNV of the Trinity CTAT Project. Cambridge, MA, USA; Klarman Cell Observatory, Broad Institute of MIT and Harvard; 2019. https://github.com/broadinstitute/inferCNV

[122] omicsCore/scTyper. omicsCore 2024.

[123] WCCTR_RNASeq_Pipeline/SingleCell/cells2keep_convertMerged2Unmerged_050823.R at master · AmyOlex/WCCTR_RNASeq_Pipeline. GitHub. Accessed February 27, 2024. https://github.com/AmyOlex/WCCTR_RNASeq_Pipeline/blob/master/SingleCell/cells2keep_convertMerged2Unmerged_050823.R

[124] LoveMI, HuberW, AndersS. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014; 15: 550.

[125] BrCa_cell_atlas/scSubtype at main Swarbricklab-code/BrCa_cell_atlas. GitHub. Accessed February 27, 2024. https://github.com/Swarbricklab-code/BrCa_cell_atlas/tree/main/scSubtype

[126] ChenXi, LiJ, GrayWH, et al. TNBCtype: a subtyping tool for triple-negative breast cancer. Cancer Inform. 2012; 11: 147-156.

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