Multiomics analysis of serial PARP inhibitor treated metastatic TNBC inform on rational combination therapies

C5aR1 inhibition reprograms tumor associated macrophages and reverses PARP inhibitor resistance in breast cancer

Although Poly (ADP-ribose) polymerase (PARP) inhibitors (PARPi) have been approved in multiple diseases, including BRCA1/2 mutant breast cancer, responses are usually transient requiring the deployment of combination therapies for optimal efficacy. Here we thus explore mechanisms underlying sensitivity and resistance to PARPi using two intrinsically PARPi sensitive (T22) and resistant (T127) syngeneic murine breast cancer models in female mice. We demonstrate that tumor associated macrophages (TAM) potentially contribute to the differential sensitivity to PARPi. By single-cell RNA-sequencing, we identify a TAM_C3 cluster, expressing genes implicated in anti-inflammatory activity, that is enriched in PARPi resistant T127 tumors and markedly decreased by PARPi in T22 tumors. Rps19/C5aR1 signaling is selectively elevated in TAM_C3. C5aR1 inhibition or transferring C5aR1hi cells increases and decreases PARPi sensitivity, respectively. High C5aR1 levels in human breast cancers are associated with poor responses to immune checkpoint blockade. Thus, targeting C5aR1 may selectively deplete pro-tumoral macrophages and engender sensitivity to PARPi and potentially other therapies.

In situ single-cell therapeutic response imaging facilitated by the TRIPODD fluorescence imaging platform

Purpose: Small molecule drugs such as tyrosine kinase inhibitors (TKIs) targeting tumoral molecular dependencies have become standard of care for numerous cancer types. Notably, epidermal growth factor receptor (EGFR) TKIs (e.g., erlotinib, afatinib, osimertinib) are the current first-line treatment for non-small cell lung cancer (NSCLC) due to their improved therapeutic outcomes for EGFR mutated and overexpressing disease over traditional platinum-based chemotherapy. However, many NSCLC tumors develop resistance to EGFR TKI therapy causing disease progression. Currently, the relationship between in situ drug target availability (DTA), local protein expression and therapeutic response cannot be accurately assessed using existing analytical tools despite being crucial to understanding the mechanism of therapeutic efficacy. Procedure: We have previously reported development of our fluorescence imaging platform termed TRIPODD (Therapeutic Response Imaging through Proteomic and Optical Drug Distribution) that is capable of simultaneous quantification of single-cell DTA and protein expression with preserved spatial context within a tumor. TRIPODD combines two complementary fluorescence imaging techniques: intracellular paired agent imaging (iPAI) to measure DTA and cyclic immunofluorescence (cyCIF), which utilizes oligonucleotide conjugated antibodies (Ab-oligos) for spatial proteomic expression profiling on tissue samples. Herein, TRIPODD was modified and optimized to provide a downstream analysis of therapeutic response through single-cell DTA and proteomic response imaging. Results: We successfully performed sequential imaging of iPAI and cyCIF resulting in high dimensional imaging and biomarker assessment to quantify single-cell DTA and local protein expression on erlotinib treated NSCLC models. Pharmacodynamic and pharmacokinetic studies of the erlotinib iPAI probes revealed that administration of 2.5 mg/kg each of the targeted and untargeted probe 4 h prior to tumor collection enabled calculation of DTA values with high Pearson correlation to EGFR, the erlotinib molecular target, expression in the tumors. Analysis of single-cell biomarker expression revealed that a single erlotinib dose was insufficient to enact a measurable decrease in the EGFR signaling cascade protein expression, where only the DTA metric detected the presence of bound erlotinib. Conclusion: We demonstrated the capability of TRIPODD to evaluate therapeutic response imaging to erlotinib treatment as it relates to signaling inhibition, DTA, proliferation, and apoptosis with preserved spatial context.

The Breast Cancer Proteome and Precision Oncology

The goal of precision oncology is to translate the molecular features of cancer into predictive and prognostic tests that can be used to individualize treatment leading to improved outcomes and decreased toxicity. Success for this strategy in breast cancer is exemplified by efficacy of trastuzumab in tumors overexpressing ERBB2 and endocrine therapy for tumors that are estrogen receptor positive. However, other effective treatments, including chemotherapy, immune checkpoint inhibitors, and CDK4/6 inhibitors are not associated with strong predictive biomarkers. Proteomics promises another tier of information that, when added to genomic and transcriptomic features (proteogenomics), may create new opportunities to improve both treatment precision and therapeutic hypotheses. Here, we review both mass spectrometry-based and antibody-dependent proteomics as complementary approaches. We highlight how these methods have contributed toward a more complete understanding of breast cancer and describe the potential to guide diagnosis and treatment more accurately.

Opportunities and challenges to engineer 3D models of tumor-adaptive immune interactions

Augmenting adaptive immunity is a critical goal for developing next-generation cancer therapies. T and B cells infiltrating the tumor dramatically influence cancer progression through complex interactions with the local microenvironment. Cancer cells evade and limit these immune responses by hijacking normal immunologic pathways. Current experimental models using conventional primary cells, cell lines, or animals have limitations for studying cancer-immune interactions directly relevant to human biology and clinical translation. Therefore, engineering methods to emulate such interplay at local and systemic levels are crucial to expedite the development of better therapies and diagnostic tools. In this review, we discuss the challenges, recent advances, and future directions toward engineering the tumor-immune microenvironment (TME), including key elements of adaptive immunity. We first offer an overview of the recent research that has advanced our understanding of the role of the adaptive immune system in the tumor microenvironment. Next, we discuss recent developments in 3D in-vitro models and engineering approaches that have been used to study the interaction of cancer and stromal cells with B and T lymphocytes. We summarize recent advancement in 3D bioengineering and discuss the need for 3D tumor models that better incorporate elements of the complex interplay of adaptive immunity and the tumor microenvironment. Finally, we provide a perspective on current challenges and future directions for modeling cancer-immune interactions aimed at identifying new biological targets for diagnostics and therapeutics.

Combining PARP Inhibition and Immunotherapy in BRCA-Associated Cancers

Poly (ADP-ribose) polymerase (PARP) inhibitors have significantly improved treatment outcomes of homologous recombination (HR) repair-deficient cancers. While the activity of these agents is largely linked to multiple mechanisms underlying the synthetic lethality of PARP inhibition and HR deficiency, emerging data suggest that their efficacy is also tied to their effects on the immune microenvironment and dependent upon cytotoxic T-cell activation. Effects observed in preclinical models are currently being validated in on-treatment biopsy samples procured from patients enrolled in clinical trials. Although this work has stimulated the development of combinations of PARP inhibitors with immunomodulatory agents, results to date have not demonstrated the superiority of combined PARP inhibition and immune checkpoint blockade compared with PARP inhibition alone. These results have stimulated a more comprehensive assessment of the immunosuppressive components of the tumor microenvironment that must be addressed so that the efficacy of PARP inhibitor agents can be maximized.

Contracting triple-negative breast cancer with immunotherapeutic armamentarium: recent advances and clinical prospects

Triple negative breast cancer (TNBC) portraying deficient expression of estrogen receptor (ER), progesterone receptor (PR) and Human epidermal growth factor receptor 2 (HER2) is known to be the most aggressive subtype associated with poor prognosis and interventional strategies limited to chemotherapy and breast conserving surgery. Some TNBC incidences have also been reported with positive circ-HER2 expression thus rendering circ-HER2 a potential immunotherapy target to direct drug development. Resistance and recurrence reported with traditional approaches has led us towards the application of immunotherapeutic interventions owing to their anti-tumor efficacy. This review provides an elaborative insight on potential molecular biomarkers to be targeted by immunotherapy. Additionally, clinical trials proposing the application of immunotherapy in neoadjuvant, adjuvant and metastatic TNBC setting have also been included. The gathered evidence indicates a positive application of immunotherapy in TNBC with therapeutic limitation available only owing to the possibility of adverse events which can be dealt considering risk-to-benefit ratio. Furthermore, potential targets to aim for therapeutic vaccines along with evidence from clinical trials have also been mentioned.

Mechanisms and Strategies to Overcome PD-1/PD-L1 Blockade Resistance in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is characterized by a high rate of systemic metastasis, insensitivity to conventional treatment and susceptibility to drug resistance, resulting in a poor patient prognosis. The immune checkpoint inhibitors (ICIs) represented by antibodies of programmed death receptor 1 (PD-1) and programmed death receptor ligand 1 (PD-L1) have provided new therapeutic options for TNBC. However, the efficacy of PD-1/PD-L1 blockade monotherapy is suboptimal immune response, which may be caused by reduced antigen presentation, immunosuppressive tumor microenvironment, interplay with other immune checkpoints and aberrant activation of oncological signaling in tumor cells. Therefore, to improve the sensitivity of TNBC to ICIs, suitable patients are selected based on reliable predictive markers and treated with a combination of ICIs with other therapies such as chemotherapy, radiotherapy, targeted therapy, oncologic virus and neoantigen-based therapies. This review discusses the current mechanisms underlying the resistance of TNBC to PD-1/PD-L1 inhibitors, the potential biomarkers for predicting the efficacy of anti-PD-1/PD-L1 immunotherapy and recent advances in the combination therapies to increase response rates, the depth of remission and the durability of the benefit of TNBC to ICIs.

Computational multiplex panel reduction to maximize information retention in breast cancer tissue microarrays

Recent state-of-the-art multiplex imaging techniques have expanded the depth of information that can be captured within a single tissue sample by allowing for panels with dozens of markers. Despite this increase in capacity, space on the panel is still limited due to technical artifacts, tissue loss, and long imaging acquisition time. As such, selecting which markers to include on a panel is important, since removing important markers will result in a loss of biologically relevant information, but identifying redundant markers will provide a room for other markers. To address this, we propose computational approaches to determine the amount of shared information between markers and select an optimally reduced panel that captures maximum amount of information with the fewest markers. Here we examine several panel selection approaches and evaluate them based on their ability to reconstruct the full panel images and information within breast cancer tissue microarray datasets using cyclic immunofluorescence as a proof of concept. We show that all methods perform adequately and can re-capture cell types using only 18 of 25 markers (72% of the original panel size). The correlation-based selection methods achieved the best single-cell marker mean intensity predictions with a Spearman correlation of 0.90 with the reduced panel. Using the proposed methods shown here, it is possible for researchers to design more efficient multiplex imaging panels that maximize the amount of information retained with the limited number of markers with respect to certain evaluation metrics and architecture biases.

PARP inhibition is a modulator of anti-tumor immune response in BRCA-deficient tumors

PARP inhibitors are synthetically lethal with BRCA1/2 mutations, and in this setting, accumulation of DNA damage leads to cell death. Because increased DNA damage and subsequent immune activation can prime an anti-tumor immune response, we studied the impact of olaparib ± immune checkpoint blockade (ICB) on anti-tumor activity and the immune microenvironment. Concurrent combination of olaparib, at clinically relevant exposures, with ICB gave durable and deeper anti-tumor activity in the Brca1m BR5 model vs. monotherapies. Olaparib and combination treatment modulated the immune microenvironment, including increases in CD8+ T cells and NK cells, and upregulation of immune pathways, including type I IFN and STING signaling. Olaparib also induced a dose-dependent upregulation of immune pathways, including JAK/STAT, STING and type I IFN, in the tumor cell compartment of a BRCA1m (HBCx-10) but not a BRCA WT (HBCx-9) breast PDX model. In vitro, olaparib induced BRCAm tumor cell–specific dendritic cell transactivation. Relevance to human disease was assessed using patient samples from the MEDIOLA (NCT02734004) trial, which showed increased type I IFN, STING, and JAK/STAT pathway expression following olaparib treatment, in line with preclinical findings. These data together provide evidence for a mechanism and schedule underpinning potential benefit of ICB combination with olaparib.

Single-Cell Proteomics Analysis of Recurrent Low-Grade Serous Ovarian Carcinoma and Associated Brain Metastases

Between 2% and 6% of epithelial ovarian cancer (EOC) patients develop brain metastases (brain mets), which are incurable and invariably result in death. This poor outcome is associated with a lack of established guidelines for the detection and treatment of brain mets in EOC patients. In this study, we characterize an unusual case of low-grade serous ovarian carcinoma (LGSOC) that metastasized to the brain. Using a spatially oriented single-cell proteomics platform, we compared sequential biopsies of a primary tumor with a peritoneal recurrence and brain mets. We identified several targetable oncogenic pathways and immunosuppressive mechanisms that are amplified in the brain mets and could be involved in the progression of LGSOC to the brain. Furthermore, we were able to identify cell populations that are shared between the primary tumor and the brain mets, suggesting that cells that have a propensity for metastasis to the brain could be identified early during the course of disease. Taken together, our findings further a path for personalized therapeutic decisions in LGSOC.

Therapy resistance: opportunities created by adaptive responses to targeted therapies in cancer

Normal cells explore multiple states to survive stresses encountered during development and self-renewal as well as environmental stresses such as starvation, DNA damage, toxins or infection. Cancer cells co-opt normal stress mitigation pathways to survive stresses that accompany tumour initiation, progression, metastasis and immune evasion. Cancer therapies accentuate cancer cell stresses and invoke rapid non-genomic stress mitigation processes that maintain cell viability and thus represent key targetable resistance mechanisms. In this Review, we describe mechanisms by which tumour ecosystems, including cancer cells, immune cells and stroma, adapt to therapeutic stresses and describe three different approaches to exploit stress mitigation processes: (1) interdict stress mitigation to induce cell death; (2) increase stress to induce cellular catastrophe; and (3) exploit emergent vulnerabilities in cancer cells and cells of the tumour microenvironment. We review challenges associated with tumour heterogeneity, prioritizing actionable adaptive responses for optimal therapeutic outcomes, and development of an integrative framework to identify and target vulnerabilities that arise from adaptive responses and engagement of stress mitigation pathways. Finally, we discuss the need to monitor adaptive responses across multiple scales and translation of combination therapies designed to take advantage of adaptive responses and stress mitigation pathways to the clinic.

The Human Tumor Atlas Network's beginning steps toward the future of collaborative multi-omic discovery

The Human Tumor Atlas Network is a multi-institutional effort to generate genomic and histologic datasets spanning thousands of patients. Johnson et al., in this issue of Cell Reports Medicine, illustrate how disparate data types from a single case can be combined to discover novel therapeutic directions.