Tumor-stroma interactions differentially alter drug sensitivity based on the origin of stromal cells

Tumor-On-A-Chip Models for Predicting In Vivo Nanoparticle Behavior

Nanosized drug formulations are broadly explored for the improvement of cancer therapy. Prediction of in vivo nanoparticle (NP) behavior, however, is challenging, given the complexity of the tumor and its microenvironment. Microfluidic tumor-on-a-chip models are gaining popularity for the in vitro testing of nanoparticle targeting under conditions that simulate the 3D tumor (microenvironment). In this review, following a description of the tumor microenvironment (TME), the state of the art regarding tumor-on-a-chip models for investigating nanoparticle delivery to solid tumors is summarized. The models are classified based on the degree of compartmentalization (single/multi-compartment) and cell composition (tumor only/tumor microenvironment). The physiological relevance of the models is critically evaluated. Overall, microfluidic tumor-on-a-chip models greatly improve the simulation of the TME in comparison to 2D tissue cultures and static 3D spheroid models and contribute to the understanding of nanoparticle behavior. Interestingly, two interrelated aspects have received little attention so far which are the presence and potential impact of a protein corona as well as nanoparticle uptake through phagocytosing cells. A better understanding of their relevance for the predictive capacity of tumor-on-a-chip systems and development of best practices will be a next step for the further refinement of advanced in vitro tumor models.

Interaction of phenotypic sublines isolated from triple-negative breast cancer cell line MDA-MB-231 modulates their sensitivity to paclitaxel and doxorubicin in 2D and 3D assays

Breast cancer is a rapidly evolving, multifactorial disease that accumulates numerous genetic and epigenetic alterations. These result in molecular and phenotypic heterogeneity within the tumor, the complexity of which is further amplified through specific interactions between cancer cells. We aimed to analyze cell phenotypic sublines and the influence of their interaction on drug resistance, spheroid formation, and migration. Seven sublines were derived from the MDA-MB-231 breast cancer cell line using a multiple-cell suspension dilution. The growth rate, CD133 receptor expression, migration ability, and chemosensitivity of these sublines to anticancer drugs doxorubicin (DOX) and paclitaxel (PTX) were determined. Three sublines (F5, D8, H2) have been chosen to study their interaction in 2D and 3D assays. In the 2D model, the resistance of all sublines composition to DOX decreased, but in the 3D model, the resistance of all sublines except H2, increased to both PTX and DOX. In the 3D model, the combined sublines F5 and D8 had higher resistance to DOX and statistically significantly lower resistance for PTX compared to the control. The interaction between cancer stem-like cells (F5) and increased migration cells (D8) increased resistance to PTX in cell monolayer and increased resistance against both DOX and PTX in the spheroids. The interaction of DOX-resistant (H2) cells with other cell subpopulations (D8, F5, HF) decreased the resistance to DOX in cell monolayer and both DOX and PTX in spheroids.

Challenges and Opportunities Modeling the Dynamic Tumor Matrisome

We need novel strategies to target the complexity of cancer and, particularly, of metastatic disease. As an example of this complexity, certain tissues are particularly hospitable environments for metastases, whereas others do not contain fertile microenvironments to support cancer cell growth. Continuing evidence that the extracellular matrix (ECM) of tissues is one of a host of factors necessary to support cancer cell growth at both primary and secondary tissue sites is emerging. Research on cancer metastasis has largely been focused on the molecular adaptations of tumor cells in various cytokine and growth factor environments on 2-dimensional tissue culture polystyrene plates. Intravital imaging, conversely, has transformed our ability to watch, in real time, tumor cell invasion, intravasation, extravasation, and growth. Because the interstitial ECM that supports all cells in the tumor microenvironment changes over time scales outside the possible window of typical intravital imaging, bioengineers are continuously developing both simple and sophisticated in vitro controlled environments to study tumor (and other) cell interactions with this matrix. In this perspective, we focus on the cellular unit responsible for upholding the pathologic homeostasis of tumor-bearing organs, cancer-associated fibroblasts (CAFs), and their self-generated ECM. The latter, together with tumoral and other cell secreted factors, constitute the "tumor matrisome". We share the challenges and opportunities for modeling this dynamic CAF/ECM unit, the tools and techniques available, and how the tumor matrisome is remodeled (e.g., via ECM proteases). We posit that increasing information on tumor matrisome dynamics may lead the field to alternative strategies for personalized medicine outside genomics.

IGF-binding proteins secreted by cancer-associated fibroblasts induce context-dependent drug sensitization of lung cancer cells

Cancer-associated fibroblasts (CAFs) in the tumor microenvironment are often linked to drug resistance. Here, we found that coculture with CAFs or culture in CAF-conditioned medium unexpectedly induced drug sensitivity in certain lung cancer cell lines. Gene expression and secretome analyses of CAFs and normal lung-associated fibroblasts (NAFs) revealed differential abundance of insulin-like growth factors (IGFs) and IGF-binding proteins (IGFBPs), which promoted or inhibited, respectively, signaling by the receptor IGF1R and the kinase FAK. Similar drug sensitization was seen in gefitinib-resistant, EGFR-mutant PC9GR lung cancer cells treated with recombinant IGFBPs. Conversely, drug sensitivity was decreased by recombinant IGFs or conditioned medium from CAFs in which IGFBP5 or IGFBP6 was silenced. Phosphoproteomics and receptor tyrosine kinase (RTK) array analyses indicated that exposure of PC9GR cells to CAF-conditioned medium also inhibited compensatory IGF1R and FAK signaling induced by the EGFR inhibitor osimertinib. Combined small-molecule inhibition of IGF1R and FAK phenocopied the CAF-mediated effects in culture and increased the antitumor effect of osimertinib in mice. Cells that were osimertinib resistant and had MET amplification or showed epithelial-to-mesenchymal transition also displayed residual sensitivity to IGFBPs. Thus, CAFs promote or reduce drug resistance in a context-dependent manner, and deciphering the relationship between the differential content of CAF secretomes and the signaling dependencies of the tumor may reveal effective combination treatment strategies.

Materials-driven approaches to understand extrinsic drug resistance in cancer

Metastatic cancer has a poor prognosis, because it is broadly disseminated and associated with both intrinsic and acquired drug resistance. Critical unmet needs in effectively killing drug resistant cancer cells include overcoming the drug desensitization characteristics of some metastatic cancers/lesions, and tailoring therapeutic regimens to both the tumor microenvironment and the genetic profiles of the resident cancer cells. Bioengineers and materials scientists are developing technologies to determine how metastatic sites exclude therapies, and how extracellular factors (including cells, proteins, metabolites, extracellular matrix, and abiotic factors) at metastatic sites significantly affect drug pharmacodynamics. Two looming challenges are determining which feature, or combination of features, from the tumor microenvironment drive drug resistance, and what the relative impact is of extracellular signals vs. intrinsic cell genetics in determining drug response. Sophisticated systems biology tools that can de-convolve a crowded network of signals and responses, as well as controllable microenvironments capable of providing discrete and tunable extracellular cues can help us begin to interrogate the high dimensional interactions governing drug resistance in patients.

3D Cell Culture Models as Recapitulators of the Tumor Microenvironment for the Screening of Anti-Cancer Drugs

Today, innovative three-dimensional (3D) cell culture models have been proposed as viable and biomimetic alternatives for initial drug screening, allowing the improvement of the efficiency of drug development. These models are gaining popularity, given their ability to reproduce key aspects of the tumor microenvironment, concerning the 3D tumor architecture as well as the interactions of tumor cells with the extracellular matrix and surrounding non-tumor cells. The development of accurate 3D models may become beneficial to decrease the use of laboratory animals in scientific research, in accordance with the European Union's regulation on the 3R rule (Replacement, Reduction, Refinement). This review focuses on the impact of 3D cell culture models on cancer research, discussing their advantages, limitations, and compatibility with high-throughput screenings and automated systems. An insight is also given on the adequacy of the available readouts for the interpretation of the data obtained from the 3D cell culture models. Importantly, we also emphasize the need for the incorporation of additional and complementary microenvironment elements on the design of 3D cell culture models, towards improved predictive value of drug efficacy.

The Origins of Phenotypic Heterogeneity in Cancer

Heterogeneity is a pervasive feature of cancer, and understanding the sources and regulatory mechanisms underlying heterogeneity could provide key insights to help improve the diagnosis and treatment of cancer. In this review, we discuss the origin of heterogeneity in the phenotype of individual cancer cells. Genotype-phenotype (G-P) maps are widely used in evolutionary biology to represent the complex interactions of genes and the environment that lead to phenotypes that impact fitness. Here, we present the rationale of an extended G-P (eG-P) map with a cone structure in cancer. The eG-P cone is formed by cells that are similar at the genome layer but gradually increase variability in the epigenome, transcriptome, proteome, metabolome and signalome layers to produce large variability at the phenome layer. Experimental evidence from single-cell -omics analyses supporting the cancer eG-P cone concept is presented, and the impact of epimutations and the interaction of cancer and tumor microenvironmental eG-P cones are integrated with the current understanding of cancer biology. The eG-P cone concept uncovers potential therapeutic strategies to reduce cancer evolution and improve cancer treatment. More methods to study phenotypes in single cells will be key to better understand cancer cell fitness in tumor biology and therapeutics.

Examining heterogeneity of stromal cells in tumor microenvironment based on pan-cancer single-cell RNA sequencing data

Tumor tissues contain both tumor and non-tumor cells, which include infiltrated immune cells and stromal cells, collectively called the tumor microenvironment (TME). Single-cell RNA sequencing (scRNAseq) enables the examination of heterogeneity of tumor cells and TME. In this review, we examined scRNAseq datasets for multiple cancer types and evaluated the heterogeneity of major cell type composition in different cancer types. We further showed that endothelial cells and fibroblasts/myofibroblasts in different cancer types can be classified into common subtypes, and the subtype composition is clearly associated with cancer characteristic and therapy response.

Crosstalk between Tumor-Infiltrating Immune Cells and Cancer-Associated Fibroblasts in Tumor Growth and Immunosuppression of Breast Cancer

Signals from the tumor microenvironment (TME) have a profound influence on the maintenance and progression of cancers. Chronic inflammation and the infiltration of immune cells in breast cancer (BC) have been strongly associated with early carcinogenic events and a switch to a more immunosuppressive response. Cancer-associated fibroblasts (CAFs) are the most abundant stromal component and can modulate tumor progression according to their secretomes. The immune cells including tumor-infiltrating lymphocytes (TILs) (cytotoxic T cells (CTLs), regulatory T cells (Tregs), and helper T cell (Th)), monocyte-infiltrating cells (MICs), myeloid-derived suppressor cells (MDSCs), mast cells (MCs), and natural killer cells (NKs) play an important part in the immunological balance, fluctuating TME between protumoral and antitumoral responses. In this review article, we have summarized the impact of these immunological players together with CAF secreted substances in driving BC progression. We explain the crosstalk of CAFs and tumor-infiltrating immune cells suppressing antitumor response in BC, proposing these cellular entities as predictive markers of poor prognosis. CAF-tumor-infiltrating immune cell interaction is suggested as an alternative therapeutic strategy to regulate the immunosuppressive microenvironment in BC.

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. Fibroblasts from primary breast tumors, normal breast tissue, and lung tissue have similar protective effects on tumor cells via paracrine factors. This fibroblast-mediated reduction in drug sensitivity involves increased expression of antiapoptotic proteins and sustained activation of the PI3K/AKT/MTOR pathway, despite inhibition of the HER2 and the RAS-ERK pathways in tumor cells. HER2 therapy sensitivity is restored in the fibroblast cocultures by combination treatment with inhibitors of MTOR or the antiapoptotic proteins BCL-XL and MCL-1. Expression of activated AKT in tumor cells recapitulates the effects of fibroblasts resulting in sustained MTOR signaling and poor lapatinib response. Lapatinib sensitivity was not altered by fibroblasts in tumor cells that exhibited sustained MTOR signaling due to a strong gain-of-function PI3KCA mutation. These findings indicate that in addition to tumor cell-intrinsic mechanisms that cause constitutive PI3K/AKT/MTOR pathway activation, secreted factors from fibroblasts can maintain this pathway in the context of HER2 inhibition. Our integrated proteomic-phenotypic approach presents a strategy for the discovery of protective mechanisms in fibroblast-rich tumors and the design of rational combination therapies to restore drug sensitivity.

Drug antagonism and single-agent dominance result from differences in death kinetics

Cancer treatment generally involves drugs used in combinations. Most previous work has focused on identifying and understanding synergistic drug-drug interactions; however, understanding antagonistic interactions remains an important and understudied issue. To enrich for antagonism and reveal common features of these combinations, we screened all pairwise combinations of drugs characterized as activators of regulated cell death. This network is strongly enriched for antagonism, particularly a form of antagonism that we call 'single-agent dominance'. Single-agent dominance refers to antagonisms in which a two-drug combination phenocopies one of the two agents. Dominance results from differences in cell death onset time, with dominant drugs acting earlier than their suppressed counterparts. We explored mechanisms by which parthanatotic agents dominate apoptotic agents, finding that dominance in this scenario is caused by mutually exclusive and conflicting use of Poly(ADP-ribose) polymerase 1 (PARP1). Taken together, our study reveals death kinetics as a predictive feature of antagonism, due to inhibitory crosstalk between cell death pathways.

Modeling chemical effects on breast cancer: the importance of the microenvironment in vitro

Accumulating evidence suggests that our ability to predict chemical effects on breast cancer is limited by a lack of physiologically relevant in vitro models; the typical in vitro breast cancer model consists of the cancer cell and excludes the mammary microenvironment. As the effects of the microenvironment on cancer cell behavior becomes more understood, researchers have called for the integration of the microenvironment into in vitro chemical testing systems. However, given the complexity of the microenvironment and the variety of platforms to choose from, identifying the essential parameters to include in a chemical testing platform is challenging. This review discusses the need for more complex in vitro breast cancer models and outlines different approaches used to model breast cancer in vitro. We provide examples of the microenvironment modulating breast cancer cell responses to chemicals and discuss strategies to help pinpoint what components should be included in a model.

Applicability of drug response metrics for cancer studies using biomaterials

Bioengineers have built models of the tumour microenvironment (TME) in which to study cell-cell interactions, mechanisms of cancer growth and metastasis, and to test new therapies. These models allow researchers to culture cells in conditions that include features of the in vivo TME implicated in regulating cancer progression, such as extracellular matrix (ECM) stiffness, integrin binding to the ECM, immune and stromal cells, growth factor and cytokine depots, and a three-dimensional geometry more representative of the in vivo TME than tissue culture polystyrene (TCPS). These biomaterials could be particularly useful for drug screening applications to make better predictions of efficacy, offering better translation to preclinical models and clinical trials. However, it can be challenging to compare drug response reports across different biomaterial platforms in the current literature. This is, in part, a result of inconsistent reporting and improper use of drug response metrics, and vast differences in cell growth rates across a large variety of biomaterial designs. This study attempts to clarify the definitions of drug response measurements used in the field, and presents examples in which these measurements can and cannot be applied. We suggest as best practice to measure the growth rate of cells in the absence of drug, and follow our 'decision tree' when reporting drug response metrics. This article is part of a discussion meeting issue 'Forces in cancer: interdisciplinary approaches in tumour mechanobiology'.

Cancer-associated fibroblasts as key regulators of the breast cancer tumor microenvironment

Tumor cells exist in close proximity with non-malignant cells. Extensive and multilayered crosstalk between tumor cells and stromal cells tailors the tumor microenvironment (TME) to support survival, growth, and metastasis. Fibroblasts are one of the largest populations of non-malignant host cells that can be found within the TME of breast, pancreatic, and prostate tumors. Substantial scientific evidence has shown that these cancer-associated fibroblasts (CAFs) are not only associated with tumors by proximity but are also actively recruited to developing tumors where they can influence other cells of the TME as well as influencing tumor cell survival and metastasis. This review discusses the impact of CAFs on breast cancer biology and highlights their heterogeneity, origin and their role in tumor progression, ECM remodeling, therapy resistance, metastasis, and the challenges ahead of targeting CAFs to improve therapy response.

Upregulation of DLEU1 expression by epigenetic modification promotes tumorigenesis in human cancer

The function of DLEU1 in human cancer is largely unknown. The Cancer Genome Atlas data were applied to identify the landscape of differential genes between tumor tissues and normal tissues, which was further validated by our cohort data and pan-cancer data including 33 cancer types with 11,060 patients. Next, DLEU1 was selected to validate the novel finding and result showed that it promoted tumorigenesis in vitro and in vivo. Mechanistically, DLEU1 promotes SRP4 expression via increasing H3K27ac enrichment to SRP4 locus epigenetically. Moreover, epigenetic modification leads to upregulation of DLEU1 expression via decreased DNA methylation and increased H3K27ac and H3K4me3 histone modification in its locus. Finally, high expression of DLEU1 correlates with worse prognosis not only in specific cancer type patients but also in patients in the pan-cancer cohort. In summary, the work broadens the function landscape of known long noncoding RNAs in human cancer and provides novel insights into their roles in tumorigenesis.

Landscape of tumor suppressor long noncoding RNAs in breast cancer

BACKGROUND

The landscape and biological functions of tumor suppressor long noncoding RNAs in breast cancer are still unknown.

METHODS

Data from whole transcriptome sequencing of 33 breast specimens in the Harbin Medical University Cancer Center cohort and The Cancer Genome Atlas was applied to identify and validate the landscape of tumor suppressor long noncoding RNAs, which was further validated by The Cancer Genome Atlas pancancer data including 33 cancer types and 12,839 patients. Next, the expression model, prognostic roles, potential biological functions and epigenetic regulation of tumor suppressor long noncoding RNAs were investigated and validated in the breast cancer and pancancer cohorts. Finally, EPB41L4A-AS2 was selected to validate our novel finding, and the tumor suppressive roles of EPB41L4A-AS2 in breast cancer were examined.

RESULTS

We identified and validated the landscape of tumor suppressor long noncoding RNAs in breast cancer. The expression of the identified long noncoding RNAs was downregulated in cancer tissue samples compared with normal tissue samples, and these long noncoding RNAs correlated with a favorable prognosis in breast cancer patients and the patients in the pancancer cohort. Multiple carcinogenesis-associated biological functions were predicted to be regulated negatively by these long noncoding RNAs. Moreover, these long noncoding RNAs were transcriptionally regulated by epigenetic modification, including DNA methylation and histone methylation modification. Finally, EPB41L4A-AS2 inhibited breast cancer cell proliferation, migration and invasion and induced cell apoptosis in vitro. Mechanistically, EPB41L4A-AS2, acting at least in part as a tumor suppressor, upregulated tumor suppressor gene expression. Moreover, ZNF217 recruited EZH2 to the EPB41L4A-AS2 locus and suppressed the expression of EPB41L4A-AS2 by epigenetically increasing H3K27me3 enrichment.

CONCLUSIONS

This work enlarges the functional landscape of known long noncoding RNAs in human cancer and provides novel insights into the suppressive roles of these long noncoding RNAs.