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Clonal populations of a human TNBC model display significant functional heterogeneity and divergent growth dynamics in distinct contexts

Oncogene volume 41, pages 112–124 (2022)Cite this article

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Abstract

Intratumoral heterogeneity has been described for various tumor types and models of human cancer, and can have profound effects on tumor progression and drug resistance. This study describes an in-depth analysis of molecular and functional heterogeneity among subclonal populations (SCPs) derived from a single triple-negative breast cancer cell line, including copy number analysis, whole-exome and RNA sequencing, proteome analysis, and barcode analysis of clonal dynamics, as well as functional assays. The SCPs were found to have multiple unique genetic alterations and displayed significant variation in anchorage independent growth and tumor forming ability. Analyses of clonal dynamics in SCP mixtures using DNA barcode technology revealed selection for distinct clonal populations in different in vitro and in vivo environmental contexts, demonstrating that in vitro propagation of cancer cell lines using different culture conditions can contribute to the establishment of unique strains. These analyses also revealed strong enrichment of a single SCP during the development of xenograft tumors in immune-compromised mice. This SCP displayed attenuated interferon signaling in vivo and reduced sensitivity to the antiproliferative effects of type I interferons. Reduction in interferon signaling was found to provide a selective advantage within the xenograft microenvironment specifically. In concordance with the previously described role of interferon signaling as tumor suppressor, these findings suggest that similar selective pressures may be operative in human cancer and patient-derived xenograft models.

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Fig. 1: Genomic and transcriptional heterogeneity among SCPs derived from a single TNBC cell line.
Fig. 2: SCPs display minimal variation in morphology and proliferation rate, but are markedly different with regard to their ability to form colonies in soft agar.
Fig. 3: Barcode analysis of tumors derived from SCP mixtures reveal divergent growth dynamics of SCP mixtures during tumor development and in vitro culture.
Fig. 4: SCP tumors are characterized by induction of IFN target genes with SCP32 showing the lowest activity.
Fig. 5: SCP32 cells display attenuated IFN signaling following IFN treatment.
Fig. 6: IFN signaling acts as a tumor suppressor in SCP tumors.
Fig. 7: PDX tumors display changes in IFN signaling during serial passaging in immune-compromised mice.

Data availability

Bulk and single-cell RNA sequencing data have been deposited to the Gene Expression Omnibus (GEO, series GSE184543). The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with dataset identifier PXD022325 (TMT1: experiment 1, TMT2: experiment 2). All other data supporting the findings of this study are available within the article, its supplementary information files, or from the corresponding author upon reasonable request.

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Acknowledgements

We are grateful to Angie Martinez-Gakidis for scientific editing, the ICCB-Longwood Screening Facility at Harvard Medical School for providing support and access to instruments, and the BioPolymers Facility at Harvard Medical School and Bauer Core Facility at Harvard University for providing support with next-generation sequencing. This work was supported by grants from the NIH (PPG P01CA080111), the Breast Cancer Research Foundation (BCRF-19-021), and the Ludwig Center at Harvard.

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Author notes

  1. Hendrik J. Kuiken

    Present address: Division of Molecular Carcinogenesis, The Netherlands Cancer Institute, Amsterdam, 1066 CX, the Netherlands

  2. Sabin Dhakal

    Present address: Inzen Therapeutics, Cambridge, MA, 02142, USA

  3. Ron C. J. Schackmann

    Present address: Merus, Utrecht, 3584 CM, the Netherlands

  4. Jett Crowdis

    Present address: Broad Institute, Cambridge, MA, 02142, USA

  5. Hyo-eun C. Bhang

    Present address: Civetta Therapeutics, Cambridge, MA, 02142, USA

  6. Frank Stegmeier

    Present address: KSQ Therapeutics, Inc., Cambridge, MA, 02139, USA

  7. These authors contributed equally: Hendrik J. Kuiken, Sabin Dhakal.

Authors and Affiliations

  1. Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA

    Hendrik J. Kuiken, Sabin Dhakal, Laura M. Selfors, Chandler M. Friend, Tian Zhang, Ron C. J. Schackmann, G. Kenneth Gray, Jett Crowdis, Steven P. Gygi & Joan S. Brugge

  2. Ludwig Center at Harvard, Boston, MA, 02115, USA

    Hendrik J. Kuiken, Sabin Dhakal, Laura M. Selfors, Chandler M. Friend, Ron C. J. Schackmann, G. Kenneth Gray, Jett Crowdis & Joan S. Brugge

  3. Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK

    Maurizio Callari & Carlos Caldas

  4. Department of Oncology, Novartis Institutes for Biomedical Research, Cambridge, MA, 02139, USA

    Hyo-eun C. Bhang & Frank Stegmeier

  5. Cancer Biology and Genetics Program, Memorial Sloan-Kettering Cancer Center, New York, NY, 10065, USA

    Timour Baslan

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Contributions

HJK and SD performed all experiments with help from CMF and JC. LMS performed all of the bioinformatics, with exception of the gene expression analysis of PDX tumors, which was performed by MC in the laboratory of CC, and the copy number analysis, which was performed in the laboratory of TB. The mass spectrometry analyses were performed by TZ in the laboratory of SPG. The CyTOF analysis was performed by RCJS and GKG. HCB and FS provided the ClonTracer constructs and protocols for the analysis of the DNA barcode experiments. HJK and JSB generated the first draft of the manuscript and all authors contributed to the revisions.

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Correspondence to Joan S. Brugge.

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JSB is a consultant for Agios Pharmaceuticals, eFFECTOR Therapeutics, and Frontier Medicines. The other authors declare no conflict of interest.

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Kuiken, H.J., Dhakal, S., Selfors, L.M. et al. Clonal populations of a human TNBC model display significant functional heterogeneity and divergent growth dynamics in distinct contexts. Oncogene 41, 112–124 (2022). https://doi.org/10.1038/s41388-021-02075-y

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