On a retrospective cohort of 1,082 FFPE breast tumors, we demonstrated the analytical validity of a test using multiplexed RNA-FISH-guided laser capture microdissection (LCM) coupled with RNA-sequencing (mFISHseq), which showed 93% accuracy compared to immunohistochemistry. The combination of these technologies makes strides in i) precisely assessing tumor heterogeneity, ii) obtaining pure tumor samples using LCM to ensure accurate biomarker expression and multigene testing, and iii) providing thorough and granular data from whole transcriptome profiling. We also constructed a 293-gene intrinsic subtype classifier that performed equivalent to the research based PAM50 and AIMS classifiers. By combining three molecular classifiers for consensus subtyping, mFISHseq alleviated single sample discordance, provided near perfect concordance with other classifiers (κ > 0.85), and reclassified 30% of samples into different subtypes with prognostic implications. We also use a consensus approach to combine information from 4 multigene prognostic classifiers and clinical risk to characterize high, low, and ultra-low risk patients that relapse early (< 5 years), late (> 10 years), and rarely, respectively. Lastly, to identify potential patient subpopulations that may be responsive to treatments like antibody drug-conjugates (ADC), we curated a list of 92 genes and 110 gene signatures to interrogate their association with molecular subtype and overall survival. Many genes and gene signatures related to ADC processing (e.g., antigen/payload targets, endocytosis, and lysosome activity) were independent predictors of overall survival in multivariate Cox regression models, thus highlighting potential ADC treatment-responsive subgroups. To test this hypothesis, we constructed a unique 19-feature classifier using multivariate logistic regression with elastic net that predicted response to trastuzumab emtansine (T-DM1; AUC = 0.96) better than either ERBB2 mRNA or Her2 IHC alone in the T-DM1 arm of the I-SPY2 trial. This test was deployed in a research-use only format on 26 patients and revealed clinical insights into patient selection for novel therapies like ADCs and immunotherapies and de-escalation of adjuvant chemotherapy.

Department of Pathology and Laboratory Medicine Memorial Sloan Kettering Cancer Center New York NY USA

Department of Radiotherapy and Oncology East Slovakia Institute of Oncology Košice Slovakia

Institute of Clinical Biochemistry and Diagnostics University Hospital Faculty of Medicine in Hradec Kralove Charles University Hradec Kralove Czech Republic

Laboratory for RNA Molecular Biology The Rockefeller University New York NY USA

MultiplexDX Inc Rockville MD USA

MultiplexDX s r o Comenius University Science Park Bratislava Slovakia

Unidad de Gestión Clínica Intercentros de Oncología Medica Hospitales Universitarios Regional y Virgen de la Victoria The Biomedical Research Institute of Málaga Málaga Spain

Wellcome Centre for Cell Biology School of Biological Sciences University of Edinburgh Edinburgh Scotland UK

Nat Commun. 2025 Jan 2;16(1):226. doi: 10.1038/s41467-024-55583-2. PubMed

Zobrazit více v PubMed

Yersal O. & Barutca S. Biological subtypes of breast cancer: Prognostic and therapeutic implications. World J Clin Oncol 5, 412–424 (2014). PubMed PMC

Sorlie T. et al. Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc Natl Acad Sci U S A 100, 8418–8423 (2003). PubMed PMC

Sørlie T. et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proceedings of the National Academy of Sciences 98, 10869–10874 (2001). PubMed PMC

Perou C. M. et al. Molecular portraits of human breast tumours. Nature 406, 747–752 (2000). PubMed

Litton J., Burstein H. & Turner N. Molecular testing in breast cancer. vol. 39 (2019). PubMed

Kittaneh M., Montero A. J. & Glück S. Molecular profiling for breast cancer: a comprehensive review. Biomark Cancer 5, 61–70 (2013). PubMed PMC

Mackay A. et al. Microarray-Based Class Discovery for Molecular Classification of Breast Cancer: Analysis of Interobserver Agreement. JNCI: Journal of the National Cancer Institute 103, 662–673 (2011). PubMed PMC

Weigelt B. et al. Breast cancer molecular profiling with single sample predictors: a retrospective analysis. Lancet Oncol 11, 339–349 (2010). PubMed

Bartlett J. M. S. et al. Comparing Breast Cancer Multiparameter Tests in the OPTIMA Prelim Trial: No Test Is More Equal Than the Others. J Natl Cancer Inst 108, djw050 (2016). PubMed PMC

Haibe-Kains B. et al. A three-gene model to robustly identify breast cancer molecular subtypes. J Natl Cancer Inst 104, 311–325 (2012). PubMed PMC

Vieira A. F. & Schmitt F. An Update on Breast Cancer Multigene Prognostic Tests-Emergent Clinical Biomarkers. Front Med (Lausanne) 5, 248 (2018). PubMed PMC

Liao J., Lu X., Shao X., Zhu L. & Fan X. Uncovering an Organ’s Molecular Architecture at Single-Cell Resolution by Spatially Resolved Transcriptomics. Trends Biotechnol 39, 43–58 (2021). PubMed

Turashvili G. & Brogi E. Tumor Heterogeneity in Breast Cancer. Front Med (Lausanne) 4, 227 (2017). PubMed PMC

Asp M., Bergenstråhle J. & Lundeberg J. Spatially Resolved Transcriptomes-Next Generation Tools for Tissue Exploration. Bioessays 42, e1900221 (2020). PubMed

Brueffer C. et al. Clinical Value of RNA Sequencing–Based Classifiers for Prediction of the Five Conventional Breast Cancer Biomarkers: A Report From the Population-Based Multicenter Sweden Cancerome Analysis Network—Breast Initiative. JCO Precision Oncology 1–18 (2018) doi:10.1200/PO.17.00135. PubMed DOI PMC

Atout S., Shurrab S. & Loveridge C. Evaluation of the Suitability of RNAscope as a Technique to Measure Gene Expression in Clinical Diagnostics: A Systematic Review. Mol Diagn Ther 26, 19–37 (2022). PubMed PMC

Li Y., Ge X., Peng F., Li W. & Li J. J. Exaggerated false positives by popular differential expression methods when analyzing human population samples. Genome Biology 23, 79 (2022). PubMed PMC

Gendoo D. M. A. et al. Genefu: an R/Bioconductor package for computation of gene expression-based signatures in breast cancer. Bioinformatics 32, 1097–1099 (2016). PubMed PMC

Chen X. et al. TNBCtype: A Subtyping Tool for Triple-Negative Breast Cancer. Cancer Inform 11, 147–156 (2012). PubMed PMC

Lehmann B. D. et al. Refinement of Triple-Negative Breast Cancer Molecular Subtypes: Implications for Neoadjuvant Chemotherapy Selection. PLoS One 11, e0157368 (2016). PubMed PMC

Lehmann B. D. et al. Identification of human triple-negative breast cancer subtypes and preclinical models for selection of targeted therapies. J Clin Invest 121, 2750–2767 (2011). PubMed PMC

Modi S. et al. Trastuzumab Deruxtecan in Previously Treated HER2-Low Advanced Breast Cancer. N Engl J Med 387, 9–20 (2022). PubMed PMC

Fernandez A. I. et al. Examination of Low ERBB2 Protein Expression in Breast Cancer Tissue. JAMA Oncol 8, 1–4 (2022). PubMed PMC

Corti C. et al. HER2-Low Breast Cancer: a New Subtype? Curr Treat Options Oncol (2023) doi:10.1007/s11864-023-01068-1. PubMed DOI

Nicol E., Boscolo Bielo L., Curigliano G. & Tarantino P. The HER2-low revolution in breast oncology: steps forward and emerging challenges. Ther Adv Med Oncol 15, 17588359231152842 (2023). PubMed PMC

Baez-Navarro X. et al. Selecting patients with HER2-low breast cancer: Getting out of the tangle. European Journal of Cancer 175, 187–192 (2022). PubMed

Rantalainen M. et al. Sequencing-based breast cancer diagnostics as an alternative to routine biomarkers. Sci Rep 6, 38037 (2016). PubMed PMC

Holm J. et al. Concordance of Immunohistochemistry-Based and Gene Expression-Based Subtyping in Breast Cancer. JNCI Cancer Spectrum 5, pkaa087 (2021). PubMed PMC

Krishnan P. et al. Profiling of Small Nucleolar RNAs by Next Generation Sequencing: Potential New Players for Breast Cancer Prognosis. PLOS ONE 11, e0162622 (2016). PubMed PMC

Koduru S. V. et al. A Comprehensive NGS Data Analysis of Differentially Regulated miRNAs, piRNAs, lncRNAs and sn/snoRNAs in Triple Negative Breast Cancer. Journal of Cancer 8, 578–596 (2017). PubMed PMC

Huang Z., Du Y., Wen J., Lu B. & Zhao Y. snoRNAs: functions and mechanisms in biological processes, and roles in tumor pathophysiology. Cell Death Discov. 8, 1–10 (2022). PubMed PMC

Gong J. et al. A Pan-cancer Analysis of the Expression and Clinical Relevance of Small Nucleolar RNAs in Human Cancer. Cell Rep 21, 1968–1981 (2017). PubMed

Staaf J. et al. RNA sequencing-based single sample predictors of molecular subtype and risk of recurrence for clinical assessment of early-stage breast cancer. npj Breast Cancer 8, 1–17 (2022). PubMed PMC

Raj-Kumar P.-K. et al. PCA-PAM50 improves consistency between breast cancer intrinsic and clinical subtyping reclassifying a subset of luminal A tumors as luminal B. Sci Rep 9, 7956 (2019). PubMed PMC

Paquet E. R. & Hallett M. T. Absolute assignment of breast cancer intrinsic molecular subtype. J Natl Cancer Inst 107, 357 (2015). PubMed

Cascianelli S., Molineris I., Isella C., Masseroli M. & Medico E. Machine learning for RNA sequencing-based intrinsic subtyping of breast cancer. Sci Rep 10, 14071 (2020). PubMed PMC

MJ. Sontrop H., JT. Reinders M. & D. Moerland P. Breast cancer subtype predictors revisited: from consensus to concordance? BMC Medical Genomics 9, 26 (2016). PubMed PMC

Schettini F., Brasó-Maristany F., Kuderer N. M. & Prat A. A perspective on the development and lack of interchangeability of the breast cancer intrinsic subtypes. NPJ Breast Cancer 8, 85 (2022). PubMed PMC

Bastien R. R. et al. PAM50 Breast Cancer Subtyping by RT-qPCR and Concordance with Standard Clinical Molecular Markers. BMC Medical Genomics 5, 44 (2012). PubMed PMC

Elloumi F. et al. Systematic Bias in Genomic Classification Due to Contaminating Non-neoplastic Tissue in Breast Tumor Samples. BMC Medical Genomics 4, 54 (2011). PubMed PMC

Lien T. G. et al. Sample Preparation Approach Influences PAM50 Risk of Recurrence Score in Early Breast Cancer. Cancers 13, 6118 (2021). PubMed PMC

Nielsen T. et al. Analytical validation of the PAM50-based Prosigna Breast Cancer Prognostic Gene Signature Assay and nCounter Analysis System using formalin-fixed paraffin-embedded breast tumor specimens. BMC Cancer 14, 177 (2014). PubMed PMC

Nielsen T. O. et al. A comparison of PAM50 intrinsic subtyping with immunohistochemistry and clinical prognostic factors in tamoxifen-treated estrogen receptor positive breast cancer. Clin Cancer Res 16, 5222–5232 (2010). PubMed PMC

Bardia A. et al. Sacituzumab Govitecan in Metastatic Triple-Negative Breast Cancer. N Engl J Med 384, 1529–1541 (2021). PubMed

Bardia A. et al. Biomarker analyses in the phase III ASCENT study of sacituzumab govitecan versus chemotherapy in patients with metastatic triple-negative breast cancer☆. Annals of Oncology 32, 1148–1156 (2021). PubMed