MYC Deregulation and PTEN Loss Model Tumor and Stromal Heterogeneity of Aggressive Triple-Negative Breast Cancer.

Triple-negative breast cancer (TNBC) patients have a poor prognosis and few treatment options. Mouse models of TNBC are important for development of new therapies, however, few mouse models represent the complexity of TNBC. Here, we develop a female TNBC murine model by mimicking two common TNBC mutations with high co-occurrence: amplification of the oncogene MYC and deletion of the tumor suppressor PTEN. This Myc;Ptenfl model develops heterogeneous triple-negative mammary tumors that display histological and molecular features commonly found in human TNBC. Our research involves deep molecular and spatial analyses on Myc;Ptenfl tumors including bulk and single-cell RNA-sequencing, and multiplex tissue-imaging. Through comparison with human TNBC, we demonstrate that this genetic mouse model develops mammary tumors with differential survival and therapeutic responses that closely resemble the inter- and intra-tumoral and microenvironmental heterogeneity of human TNBC, providing a pre-clinical tool for assessing the spectrum of patient TNBC biology and drug response.

Panobinostat Induced Spatial In Situ Biomarkers Predictive of Anti-PD-1 Efficacy in Mouse Mammary Carcinoma.

Immunotherapies, including anti-PD-1 immune checkpoint blocking (ICB) antibodies, have revolutionized the treatment of many solid malignancies. However, their efficacy in breast cancer has been limited to a subset of patients with triple-negative breast cancer, where ICBs are routinely combined with a range of cytotoxic and targeted agents. Reliable biomarkers predictive of the therapeutic response to ICB in breast cancer are critically missing, though a combination response has been associated with immunogenic cell death (ICD). Here, we utilized a recently developed integrated analytical platform, the multiplex implantable microdevice assay (MIMA), to evaluate the presence and spatial cell relations of literature-based candidate markers predictive of ICB efficacy in luminal mouse mammary carcinoma. MIMA integrates (i) an implantable microdevice for the localized delivery of small amounts of drugs inside the tumor bed with (ii) sequential multiplex immunohistochemistry (mIHC) and spatial cell analysis pipelines to rapidly (within days) describe drug mechanisms of action and find predictive biomarkers in complex tumor tissue. We show that the expression of cleaved caspase-3, ICAM-1, neuropilin-1, myeloperoxidase, calreticulin, galectin-3, and PD-L1 were spatially associated with the efficacy of panobinostat, a pan-HDAC inhibitor that was previously shown to induce immunogenic cell death and synergize with anti-PD-1 in breast cancer. PD-L1 by itself, however, was not a reliable predictor. Instead, ICB efficacy was robustly identified through the in situ hotspot detection of galectin-3-positive non-proliferating tumor zones enriched in cell death and infiltrated by anti-tumor cytotoxic neutrophils positive for ICAM-1 and neuropilin-1. Such hotspots can be specifically detected using distance-based cluster analyses. Single-cell measurements of the functional states in the tumor microenvironment suggest that both qualitative and quantitative effects might drive effective therapy responses. Overall, the presented study provides (i) complementary biological knowledge about the earliest cell events of induced anti-tumor immunity in breast cancer, including the emergence of resistant cancer stem cells, and (ii) newly identified biomarkers in form of specific spatial cell associations. The approach used standard cell-type-, IHC-, and FFPE-based techniques, and therefore the identified spatial clustering of in situ biomarkers can be readily integrated into existing clinical or research workflows, including in luminal breast cancer. Since early drug responses were detected, the biomarkers could be especially applicable to window-of-opportunity clinical trials to rapidly discriminate between responding and resistant patients, thus limiting unnecessary treatment-associated toxicities.

A multiplex implantable microdevice assay identifies synergistic combinations of cancer immunotherapies and conventional drugs.

Systematically identifying synergistic combinations of targeted agents and immunotherapies for cancer treatments remains difficult. In this study, we integrated high-throughput and high-content techniques-an implantable microdevice to administer multiple drugs into different sites in tumors at nanodoses and multiplexed imaging of tumor microenvironmental states-to investigate the tumor cell and immunological response signatures to different treatment regimens. Using a mouse model of breast cancer, we identified effective combinations from among numerous agents within days. In vivo studies in three immunocompetent mammary carcinoma models demonstrated that the predicted combinations synergistically increased therapeutic efficacy. We identified at least five promising treatment strategies, of which the panobinostat, venetoclax and anti-CD40 triple therapy was the most effective in inducing complete tumor remission across models. Successful drug combinations increased spatial association of cancer stem cells with dendritic cells during immunogenic cell death, suggesting this as an important mechanism of action in long-term breast cancer control.