Triple-negative breast cancer (TNBC) shows considerable intratumoral heterogeneity, which contributes to therapeutic resistance. Recent studies show that targeted therapeutics can steer TNBC toward homogeneous, drug-resistant states, but little is understood about how the microenvironment modulates these responses. We report studies to determine how components of the microenvironment impact response to trametinib and cellular heterogeneity. We find that multiple microenvironmental factors, including HGF and neuregulin 1, can drive therapeutic resistance and that treatment with hepatocyte growth factor (HGF) inhibitors restores trametinib sensitivity. Interestingly, treatment with these ligands reverses trametinib-induced homogeneity, restoring heterogeneity to levels comparable to baseline both in vitro and in vivo. Analysis of patient data demonstrates that TNBC with high HGF expression levels has a poor outcome and increased expression of basal and mesenchymal state markers. Our data suggest that common growth factors drive therapeutic resistance and maintain tumor heterogeneity in TNBC, and that co-targeting these factors may improve therapeutic response.

Supplemental Figure Legends

Supplementary Table 2 from Immutable Functional Attributes of Histologic Grade Revealed by Context-Independent Gene Expression in Primary Breast Cancer Cells

Supplementary Figure 3 from Molecular Distinctions between Stasis and Telomere Attrition Senescence Barriers Shown by Long-term Culture of Normal Human Mammary Epithelial Cells

Supplementary Figure Legends 1-2 from Basal Subtype and MAPK/ERK Kinase (MEK)-Phosphoinositide 3-Kinase Feedback Signaling Determine Susceptibility of Breast Cancer Cells to MEK Inhibition

Legend Figure S1: Schematic of the experimental framework Legend Figure S2: Predicted phenotypic value and assessment of predictive power of the model. Legend Figure S3: Taget knock-down. Legend Figure S4: Treatment with individual siRNAs against TRIB1 leads to G1-S arrest. Legend Figure S5: RNA levels of cell cycle genes. Legend Figure S6: TRIB1 knockdown results in inhibition of NFκB-responsive promoter activity: comparison of individual siRNA duplexes. Legend Figure S7: TRIB1 resistant to siRNA (TRIB1-siR) rescues the phenotype induced by TRIB1-siRNA. Legend Figure S8: Downregulation of NFkB target genes after treatment with TRIB1 siRNA. Legend Figure S9: TRIB1 knock down leads to inhibition of NFκB pathway. Legend Figure S10: TRIB1 siRNA promotes TRAIL-induced apoptosis through activation of caspase-8 cleavage. Legend Figure S11: TRIB1 knockdown results in decrease of YY1gene expression. Legend Figure S12: Kaplan-Meier plots Legend Figure S13: Hazard Ratios for BCCS distribution. Legend Figure S14: Hazard Ratios for OS distribution.

Supplementary Tables 1-6 from Basal Subtype and MAPK/ERK Kinase (MEK)-Phosphoinositide 3-Kinase Feedback Signaling Determine Susceptibility of Breast Cancer Cells to MEK Inhibition

Supplementary Figure 1 from Molecular Distinctions between Stasis and Telomere Attrition Senescence Barriers Shown by Long-term Culture of Normal Human Mammary Epithelial Cells

Supplementary Figures S1-S2 and Supplementary Tables S2-S4.

Methods for Real-Time Quantitative RT-PCR, Assessment of medal accuracy, Gene expression, copy number and survival analysis,

Supplementary Figure 2 from Molecular Distinctions between Stasis and Telomere Attrition Senescence Barriers Shown by Long-term Culture of Normal Human Mammary Epithelial Cells

CDK4/6 inhibitors (CDK4/6i) have transformed the treatment of hormone receptor-positive (HR+), HER2-negative (HR+) breast cancers as they are effective across all clinicopathological, age, and ethnicity subgroups for metastatic HR+ breast cancer. In metastatic ER+ breast cancer, CDK4/6i lead to strong and consistent improvement in survival across different lines of therapy. To understand how metastatic HR+ breast cancers become refractory to CDK4/6i, we have created a multimodal and longitudinal tumor atlas to investigate therapeutic adaptations in malignant cells and in the tumor immune microenvironment. This atlas is part of the NCI Cancer Moonshot Human Tumor Atlas Network and includes seven pairs of pre- and on-progression biopsies from five metastatic HR+ breast cancer patients treated with CDK4/6i. Biopsies were profiled with bulk genomics, transcriptomics, and proteomics as well as single-cell ATAC-seq and multiplex tissue imaging for spatial, single-cell resolution. These molecular datasets were then linked with detailed clinical metadata to create an atlas for understanding tumor adaptations during therapy. Analysis of our atlas datasets revealed a diverse but tractable set of tumor adaptations to CDK4/6i therapy. Malignant cells adapted to therapy via mTORC1 activation, cell cycle bypass, and increased replication stress. The tumor immune microenvironment displayed evidence of both immune activation and immune suppression, including increased PD-1 expression, features of T cell dysfunction, and CD163 + macrophage infiltration. Together, our metastatic ER+ breast cancer atlas represents a rich multimodal resource to understand tumor therapeutic adaptations to CDK4/6i therapy.

This protocol outlines the NanoString GeoMx Digital Spatial Profiler Whole Transcriptome Atlas (DSP WTA) assay that was applied in the Human Tumor Atlas Network (HTAN) Tissue MicroArrary (TMA) -TransNetwork Project (TNP). The TMA-TNP evaluates various characterization and analytics methodologies on a large array of breast tumor samples representing a broad spectrum of disease state and subtype. A commercially available anonymized breast tumor TMA was purchased and serial sections were distributed. Participating HTAN Centers characterized the FFPE specimens using various imaging platforms and generated a spatially resolved cell type/state census using each center’s method of choice. Data was recorded in a common repository to enable joint analysis. The protocol that immediately precedes this one for TMA-TNP Phase 4 can be found at: dx.doi.org/10.17504/protocols.io.ewov1o7wolr2/v1. It describes FFPE block serial sectioning, slide processing and TMA sample distribution. Two compartments (Tumor and Stroma) in each TMA core were analyzed to determine cell-to-cell interactions in the tissues.

Supplementary Table 3 from Immutable Functional Attributes of Histologic Grade Revealed by Context-Independent Gene Expression in Primary Breast Cancer Cells

Supplementary Figure 2 from Basal Subtype and MAPK/ERK Kinase (MEK)-Phosphoinositide 3-Kinase Feedback Signaling Determine Susceptibility of Breast Cancer Cells to MEK Inhibition

Supplementary Table 1 from Immutable Functional Attributes of Histologic Grade Revealed by Context-Independent Gene Expression in Primary Breast Cancer Cells

Supplementary Figure 1 from Basal Subtype and MAPK/ERK Kinase (MEK)-Phosphoinositide 3-Kinase Feedback Signaling Determine Susceptibility of Breast Cancer Cells to MEK Inhibition

Supplementary Tables 1- 4 from Molecular Distinctions between Stasis and Telomere Attrition Senescence Barriers Shown by Long-term Culture of Normal Human Mammary Epithelial Cells

This protocol outlines the NanoString GeoMx DSP phase 4 protein assay that was applied in the Human Tumor Atlas Network (HTAN) Tissue MicroArrary (TMA)-TransNetwork Project (TNP). The TMA-TNP evaluates various characterization and analytics methodologies on a large array of breast tumor samples representing a broad spectrum of disease state and subtype. A commercially available anonymized breast tumor TMA was purchased and serial sections were distributed. Participating HTAN Centers characterized the FFPE specimens using various imaging platforms and generated a spatially resolved cell type/state census using each center’s method of choice. Data was recorded in a common repository to enable joint analysis. The protocol that immediately precedes this one for TMA-TNP Phase 4 can be found at: dx.doi.org/10.17504/protocols.io.ewov1o7wolr2/v1. It describes FFPE block serial sectioning, slide processing and TMA sample distribution. In this protocol, the DSP protein assay was performed with the following human marker panels: Immune cell profiling core, Immune activation status, Immune-Oncology (IO) Drug target, Cell death, Pan-tumor, MAPK and PI3K/AKT panels including OHSU custom panel (Cell cycle and DNA damage). A total of 85 protein targets were evaluated in the TMA samples. Two compartments (Tumor and Stroma) in each TMA core were analyzed to determine cell-to-cell interactions in the tissues.

The phenotype of a cell and its underlying molecular state is strongly influenced by extracellular signals, including growth factors, hormones, and extracellular matrix proteins. While these signals are normally tightly controlled, their dysregulation leads to phenotypic and molecular states associated with diverse diseases. To develop a detailed understanding of the linkage between molecular and phenotypic changes, we generated a comprehensive dataset that catalogs the transcriptional, proteomic, epigenomic and phenotypic responses of MCF10A mammary epithelial cells after exposure to the ligands EGF, HGF, OSM, IFNG, TGFB and BMP2. Systematic assessment of the molecular and cellular phenotypes induced by these ligands comprise the LINCS Microenvironment (ME) perturbation dataset, which has been curated and made publicly available for community-wide analysis and development of novel computational methods ( synapse.org/LINCS_MCF10A ). In illustrative analyses, we demonstrate how this dataset can be used to discover functionally related molecular features linked to specific cellular phenotypes. Beyond these analyses, this dataset will serve as a resource for the broader scientific community to mine for biological insights, to compare signals carried across distinct molecular modalities, and to develop new computational methods for integrative data analysis.