Cilengitide sensitivity is predicted by overall integrin expression in breast cancer.

Background: Treatment options for triple-negative breast cancer (TNBC) are limited and patients face a poor prognosis. Here, we sought to identify drugs that target TNBC vulnerabilities and understand the biology underlying these responses. We analyzed the Broad Institute DepMap to identify recurrent TNBC vulnerabilities and performed a 45-compound screen on vulnerability-related pathways on a set of up to 8 TNBC cell lines.

Cancer-cell derived S100A11 promotes macrophage recruitment in ER+ breast cancer.

Macrophages are pivotal in driving breast tumor development, progression, and resistance to treatment, particularly in estrogen receptor-positive (ER+) tumors, where they infiltrate the tumor microenvironment (TME) influenced by cancer cell-secreted factors. By analyzing single-cell RNA sequencing data from 25 ER+ tumors, we elucidated interactions between cancer cells and macrophages, correlating macrophage density with epithelial cancer cell density. We identified that S100A11, a previously unexplored factor in macrophage-cancer crosstalk, predicts high macrophage density and poor outcomes in ER+ tumors.

Rational Design of HER2-Targeted Combination Therapies to Reverse Drug Resistance in Fibroblast-Protected HER2+ Breast Cancer Cells.

Introduction: Fibroblasts, an abundant cell type in the breast tumor microenvironment, interact with cancer cells and orchestrate tumor progression and drug resistance. However, the mechanisms by which fibroblast-derived factors impact drug sensitivity remain poorly understood. Here, we develop rational combination therapies that are informed by proteomic profiling to overcome fibroblast-mediated therapeutic resistance in HER2+ breast cancer cells.

Systemic and local chronic inflammation and hormone disposition promote a tumor-permissive environment for breast cancer in older women.

Unlabelled: Estrogen receptor positive (ER+) breast cancer is the most common subtype of breast cancer and is an age-related disease. The peak incidence of diagnosis occurs around age 70, even though these post-menopausal patients have low circulating levels of estradiol (E2). Despite the hormone sensitivity of age-related tumors, we have a limited understanding of the interplay between systemic and local hormones, chronic inflammation, and immune changes that contribute to the growth and development of these tumors.

CAR T cell infiltration and cytotoxic killing within the core of 3D breast cancer spheroids under the control of antigen sensing in microwell arrays.

The success of chimeric antigen receptor (CAR) T cells in blood cancers has intensified efforts to develop CAR T therapies for solid cancers. In the solid tumor microenvironment, CAR T cell trafficking and suppression of cytotoxic killing represent limiting factors for therapeutic efficacy. Here, we present a microwell platform to study CAR T cell interactions with 3D breast tumor spheroids and determine predictors of anti-tumor CAR T cell function.

Enhancing PKA-dependent mesothelial barrier integrity reduces ovarian cancer transmesothelial migration via inhibition of contractility.

Cancer-mesothelial cell interactions are critical for multiple solid tumors to colonize the surface of peritoneal organs. Understanding mechanisms of mesothelial barrier dysfunction that impair its protective function is critical for discovering mesothelial-targeted therapies to combat metastatic spread. Here, we utilized a live cell imaging-based assay to elucidate the dynamics of ovarian cancer spheroid transmesothelial migration and mesothelial-generated mechanical forces.

Paracrine Ovarian Cancer Cell-Derived CSF1 Signaling Regulates Macrophage Migration Dynamics in a 3D Microfluidic Model that Recapitulates In Vivo Infiltration Patterns in Patient-Derived Xenografts.

A high density of macrophages in the ovarian cancer microenvironment is associated with disease progression and poor outcomes. Understanding cancer-macrophage interaction mechanisms that establish this pro-tumorigenic microenvironment is critical for developing macrophage-targeted therapies. Here, 3D microfluidic assays and patient-derived xenografts are utilized to define the role of cancer-derived colony stimulating factor 1 (CSF1) on macrophage infiltration dynamics toward ovarian cancer cells.

Rational design of HER2-targeted combination therapies to reverse drug resistance in fibroblast-protected HER2+ breast cancer cells.

Introduction: Fibroblasts, an abundant cell type in the breast tumor microenvironment, interact with cancer cells and orchestrate tumor progression and drug resistance. However, the mechanisms by which fibroblast-derived factors impact drug sensitivity remain poorly understood. Here, we develop rational combination therapies that are informed by proteomic profiling to overcome fibroblast-mediated therapeutic resistance in HER2+ breast cancer cells.

CAR T cell infiltration and cytotoxic killing within the core of 3D breast cancer spheroids under control of antigen sensing in microwell arrays.

The success of chimeric antigen receptor (CAR) T cells in blood cancers has intensified efforts to develop CAR T therapies for solid cancers. In the solid tumor microenvironment, CAR T cell trafficking and suppression of cytotoxic killing represent limiting factors for therapeutic efficacy. Here, we present a microwell platform to study CAR T cell interactions with 3D tumor spheroids and determine predictors of anti-tumor CAR T cell function.

Cancer-cell derived S100A11 promotes macrophage recruitment in ER+ breast cancer.

Macrophages are pivotal in driving breast tumor development, progression, and resistance to treatment, particularly in estrogen receptor-positive (ER+) tumors, where they infiltrate the tumor microenvironment (TME) influenced by cancer cell-secreted factors. By analyzing single-cell RNA-sequencing data from 25 ER+ tumors, we elucidated interactions between cancer cells and macrophages, correlating macrophage density with epithelial cancer cell density. We identified that S100A11, a previously unexplored factor in macrophage-cancer crosstalk, predicts high macrophage density and poor outcomes in ER+ tumors.

Fabrication of 3D-printed molds for polydimethylsiloxane-based microfluidic devices using a liquid crystal display-based vat photopolymerization process: printing quality, drug response and 3D invasion cell culture assays.

Microfluidic platforms enable more precise control of biological stimuli and environment dimensionality than conventional macroscale cell-based assays; however, long fabrication times and high-cost specialized equipment limit the widespread adoption of microfluidic technologies. Recent improvements in vat photopolymerization three-dimensional (3D) printing technologies such as liquid crystal display (LCD) printing offer rapid prototyping and a cost-effective solution to microfluidic fabrication. Limited information is available about how 3D printing parameters and resin cytocompatibility impact the performance of 3D-printed molds for the fabrication of polydimethylsiloxane (PDMS)-based microfluidic platforms for cellular studies.

Beyond matrix stiffness: targeting force-induced cancer drug resistance.

During tumor progression, mechanical abnormalities in the tumor microenvironment (TME) trigger signaling pathways in cells that activate cellular programs, resulting in tumor growth and drug resistance. In this review, we describe mechanisms of action for anti-cancer therapies and mechanotransduction programs that regulate cellular processes, including cell proliferation, apoptosis, survival and phenotype switching. We discuss how the therapeutic response is impacted by the three main mechanical TME abnormalities: high extracellular matrix (ECM) composition and stiffness; interstitial fluid pressure (IFP); and elevated mechanical forces.

Cancer-mesothelial and cancer-macrophage interactions in the ovarian cancer microenvironment.

The metastatic ovarian cancer microenvironment is characterized by an intricate interaction network between cancer cells and host cells. This complex heterotypic cancer-host cell crosstalk results in an environment that promotes cancer cell metastasis and treatment resistance, leading to poor patient prognosis and survival. In this review, we focus on two host cell types found in the ovarian cancer microenvironment: mesothelial cells and tumor-associated macrophages.

Modeling collective cell behavior in cancer: Perspectives from an interdisciplinary conversation.

Collective cell behavior contributes to all stages of cancer progression. Understanding how collective behavior emerges through cell-cell interactions and decision-making will advance our understanding of cancer biology and provide new therapeutic approaches. Here, we summarize an interdisciplinary discussion on multicellular behavior in cancer, draw lessons from other scientific disciplines, and identify future directions.

Synergistic combination therapy delivered via layer-by-layer nanoparticles induces solid tumor regression of ovarian cancer.

The majority of patients with high grade serous ovarian cancer (HGSOC) develop recurrent disease and chemotherapy resistance. To identify drug combinations that would be effective in treatment of chemotherapy resistant disease, we examined the efficacy of drug combinations that target the three antiapoptotic proteins most commonly expressed in HGSOC-BCL2, BCL-XL, and MCL1. Co-inhibition of BCL2 and BCL-XL (ABT-263) with inhibition of MCL1 (S63845) induces potent synergistic cytotoxicity in multiple HGSOC models.

Exploring approaches for predictive cancer patient digital twins: Opportunities for collaboration and innovation.

We are rapidly approaching a future in which cancer patient digital twins will reach their potential to predict cancer prevention, diagnosis, and treatment in individual patients. This will be realized based on advances in high performance computing, computational modeling, and an expanding repertoire of observational data across multiple scales and modalities. In 2020, the US National Cancer Institute, and the US Department of Energy, through a trans-disciplinary research community at the intersection of advanced computing and cancer research, initiated team science collaborative projects to explore the development and implementation of predictive Cancer Patient Digital Twins.

A PDE Model of Breast Tumor Progression in MMTV-PyMT Mice.

The evolution of breast tumors greatly depends on the interaction network among different cell types, including immune cells and cancer cells in the tumor. This study takes advantage of newly collected rich spatio-temporal mouse data to develop a data-driven mathematical model of breast tumors that considers cells' location and key interactions in the tumor. The results show that cancer cells have a minor presence in the area with the most overall immune cells, and the number of activated immune cells in the tumor is depleted over time when there is no influx of immune cells.

Investigating key cell types and molecules dynamics in PyMT mice model of breast cancer through a mathematical model.

The most common kind of cancer among women is breast cancer. Understanding the tumor microenvironment and the interactions between individual cells and cytokines assists us in arriving at more effective treatments. Here, we develop a data-driven mathematical model to investigate the dynamics of key cell types and cytokines involved in breast cancer development.

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.

Mechanical Stress Signaling in Pancreatic Cancer Cells Triggers p38 MAPK- and JNK-Dependent Cytoskeleton Remodeling and Promotes Cell Migration via Rac1/cdc42/Myosin II.

Unlabelled: Advanced or metastatic pancreatic cancer is highly resistant to existing therapies, and new treatments are urgently needed to improve patient outcomes. Current studies focus on alternative treatment approaches that target the abnormal microenvironment of pancreatic tumors and the resulting elevated mechanical stress in the tumor interior. Nevertheless, the underlying mechanisms by which mechanical stress regulates pancreatic cancer metastatic potential remain elusive.

A Mathematical Model of Breast Tumor Progression Based on Immune Infiltration.

Breast cancer is the most prominent type of cancer among women. Understanding the microenvironment of breast cancer and the interactions between cells and cytokines will lead to better treatment approaches for patients. In this study, we developed a data-driven mathematical model to investigate the dynamics of key cells and cytokines involved in breast cancer development.

A SNAI2-PEAK1-INHBA stromal axis drives progression and lapatinib resistance in HER2-positive breast cancer by supporting subpopulations of tumor cells positive for antiapoptotic and stress signaling markers.

Intercellular mechanisms by which the stromal microenvironment contributes to solid tumor progression and targeted therapy resistance remain poorly understood, presenting significant clinical hurdles. PEAK1 (Pseudopodium-Enriched Atypical Kinase One) is an actin cytoskeleton- and focal adhesion-associated pseudokinase that promotes cell state plasticity and cancer metastasis by mediating growth factor-integrin signaling crosstalk. Here, we determined that stromal PEAK1 expression predicts poor outcomes in HER2-positive breast cancers high in SNAI2 expression and enriched for MSC content.

Large-Scale Characterization of Drug Responses of Clinically Relevant Proteins in Cancer Cell Lines.

Perturbation biology is a powerful approach to modeling quantitative cellular behaviors and understanding detailed disease mechanisms. However, large-scale protein response resources of cancer cell lines to perturbations are not available, resulting in a critical knowledge gap. Here we generated and compiled perturbed expression profiles of ∼210 clinically relevant proteins in >12,000 cancer cell line samples in response to ∼170 drug compounds using reverse-phase protein arrays.

Perturbation biology links temporal protein changes to drug responses in a melanoma cell line.

Cancer cells have genetic alterations that often directly affect intracellular protein signaling processes allowing them to bypass control mechanisms for cell death, growth and division. Cancer drugs targeting these alterations often work initially, but resistance is common. Combinations of targeted drugs may overcome or prevent resistance, but their selection requires context-specific knowledge of signaling pathways including complex interactions such as feedback loops and crosstalk.

Fibroblast-tumor cell signaling limits HER2 kinase therapy response via activation of MTOR and antiapoptotic pathways.

Despite the implementation of multiple HER2-targeted therapies, patients with advanced HER2 breast cancer ultimately develop drug resistance. Stromal fibroblasts represent an abundant cell type in the tumor microenvironment and have been linked to poor outcomes and drug resistance. Here, we show that fibroblasts counteract the cytotoxic effects of HER2 kinase-targeted therapy in a subset of HER2 breast cancer cell lines and allow cancer cells to proliferate in the presence of the HER2 kinase inhibitor lapatinib.