Similarity and diversity of the tumor microenvironment in multiple metastases: critical implications for overall and progression-free survival of high-grade serous ovarian cancer

The endothelin-1-driven tumor-stroma feed-forward loops in high-grade serous ovarian cancer

The high-grade serous ovarian cancer (HG-SOC) tumor microenvironment (TME) is constellated by cellular elements and a network of soluble constituents that contribute to tumor progression. In the multitude of the secreted molecules, the endothelin-1 (ET-1) has emerged to be implicated in the tumor/TME interplay; however, the molecular mechanisms induced by the ET-1-driven feed-forward loops (FFL) and associated with the HG-SOC metastatic potential need to be further investigated. The tracking of the patient-derived (PD) HG-SOC cell transcriptome by RNA-seq identified the vascular endothelial growth factor (VEGF) gene and its associated signature among those mostly up-regulated by ET-1 and down-modulated by the dual ET-1R antagonist macitentan. Within the ligand-receptor pairs concurrently expressed in PD-HG-SOC cells, endothelial cells and activated fibroblasts, we discovered two intertwined FFL, the ET-1/ET-1R and VEGF/VEGF receptors, concurrently activated by ET-1 and shutting-down by macitentan, or by the anti-VEGF antibody bevacizumab. In parallel, we observed that ET-1 fine-tuned the tumoral and stromal secretome toward a pro-invasive pattern. Into the fray of the HG-SOC/TME double and triple co-cultures, the secretion of ET-1 and VEGF, that share a common co-regulation, was inhibited upon the administration of macitentan. Functionally, macitentan, mimicking the effect of bevacizumab, interfered with the HG-SOC/TME FFL-driven communication that fuels the HG-SOC invasive behavior. The identification of ET-1 and VEGF FFL as tumor and TME actionable vulnerabilities, reveals how ET-1R blockade, targeting the HG-SOC cells and the TME simultaneously, may represent an effective therapeutic option for HG-SOC patients.

Molecular, Metabolic, and Subcellular Mapping of the Tumor Immune Microenvironment via 3D Targeted and Non-Targeted Multiplex Multi-Omics Analyses

Most platforms used for the molecular reconstruction of the tumor-immune microenvironment (TIME) of a solid tumor fail to explore the spatial context of the three-dimensional (3D) space of the tumor at a single-cell resolution, and thus lack information about cell-cell or cell-extracellular matrix (ECM) interactions. To address this issue, a pipeline which integrated multiplex spatially resolved multi-omics platforms was developed to identify crosstalk signaling networks among various cell types and the ECM in the 3D TIME of two FFPE (formalin-fixed paraffin embedded) gynecologic tumor samples. These platforms include non-targeted mass spectrometry imaging (glycans, metabolites, and peptides) and Stereo-seq (spatial transcriptomics) and targeted seqIF (IHC proteomics). The spatially resolved imaging data in a two- and three-dimensional space demonstrated various cellular neighborhoods in both samples. The collection of spatially resolved analytes in a voxel (3D pixel) across serial sections of the tissue was also demonstrated. Data collected from this analytical pipeline were used to construct spatial 3D maps with single-cell resolution, which revealed cell identity, activation, and energized status. These maps will provide not only insights into the molecular basis of spatial cell heterogeneity in the TIME, but also novel predictive biomarkers and therapeutic targets, which can improve patient survival rates.

A Microfluidics Approach for Ovarian Cancer Immune Monitoring in an Outpatient Setting

Among cancer diagnoses in women, ovarian cancer has the fifth-highest mortality rate. Current treatments are unsatisfactory, and new therapies are highly needed. Immunotherapies show great promise but have not reached their full potential in ovarian cancer patients. Implementation of an immune readout could offer better guidance and development of immunotherapies. However, immune profiling is often performed using a flow cytometer, which is bulky, complex, and expensive. This equipment is centralized and operated by highly trained personnel, making it cumbersome and time-consuming. We aim to develop a disposable microfluidic chip capable of performing an immune readout with the sensitivity needed to guide diagnostic decision making as close as possible to the patient. As a proof of concept of the fluidics module of this concept, acquisition of a limited immune panel based on CD45, CD8, programmed cell death protein 1 (PD1), and a live/dead marker was compared to a conventional flow cytometer (BD FACSymphony). Based on a dataset of peripheral blood mononuclear cells of 15 patients with ovarian cancer across different stages of treatment, we obtained a 99% correlation coefficient for the detection of CD8+PD1+ T cells relative to the total amount of CD45+ white blood cells. Upon further system development comprising further miniaturization of optics, this microfluidics chip could enable immune monitoring in an outpatient setting, facilitating rapid acquisition of data without the need for highly trained staff.

FunSpace: A functional and spatial analytic approach to cell imaging data using entropy measures

Spatial heterogeneity in the tumor microenvironment (TME) plays a critical role in gaining insights into tumor development and progression. Conventional metrics typically capture the spatial differential between TME cellular patterns by either exploring the cell distributions in a pairwise fashion or aggregating the heterogeneity across multiple cell distributions without considering the spatial contribution. As such, none of the existing approaches has fully accounted for the simultaneous heterogeneity caused by both cellular diversity and spatial configurations of multiple cell categories. In this article, we propose an approach to leverage spatial entropy measures at multiple distance ranges to account for the spatial heterogeneity across different cellular organizations. Functional principal component analysis (FPCA) is applied to estimate FPC scores which are then served as predictors in a Cox regression model to investigate the impact of spatial heterogeneity in the TME on survival outcome, potentially adjusting for other confounders. Using a non-small cell lung cancer dataset (n = 153) as a case study, we found that the spatial heterogeneity in the TME cellular composition of CD14+ cells, CD19+ B cells, CD4+ and CD8+ T cells, and CK+ tumor cells, had a significant non-zero effect on the overall survival (p = 0.027). Furthermore, using a publicly available multiplexed ion beam imaging (MIBI) triple-negative breast cancer dataset (n = 33), our proposed method identified a significant impact of cellular interactions between tumor and immune cells on the overall survival (p = 0.046). In simulation studies under different spatial configurations, the proposed method demonstrated a high predictive power by accounting for both clinical effect and the impact of spatial heterogeneity.

Spatial Transcriptomics Depict Ligand-Receptor Cross-talk Heterogeneity at the Tumor-Stroma Interface in Long-Term Ovarian Cancer Survivors

Advanced high-grade serous ovarian cancer (HGSC) is an aggressive disease that accounts for 70% of all ovarian cancer deaths. Nevertheless, 15% of patients diagnosed with advanced HGSC survive more than 10 years. The elucidation of predictive markers of these long-term survivors (LTS) could help identify therapeutic targets for the disease, and thus improve patient survival rates. To investigate the stromal heterogeneity of the tumor microenvironment (TME) in ovarian cancer, we used spatial transcriptomics to generate spatially resolved transcript profiles in treatment-naïve advanced HGSC from LTS and short-term survivors (STS) and determined the association between cancer-associated fibroblasts (CAF) heterogeneity and survival in patients with advanced HGSC. Spatial transcriptomics and single-cell RNA-sequencing data were integrated to distinguish tumor and stroma regions, and a computational method was developed to investigate spatially resolved ligand-receptor interactions between various tumor and CAF subtypes in the TME. A specific subtype of CAFs and its spatial location relative to a particular ovarian cancer cell subtype in the TME correlated with long-term survival in patients with advanced HGSC. Also, increased APOE-LRP5 cross-talk occurred at the stroma-tumor interface in tumor tissues from STS compared with LTS. These findings were validated using multiplex IHC. Overall, this spatial transcriptomics analysis revealed spatially resolved CAF-tumor cross-talk signaling networks in the ovarian TME that are associated with long-term survival of patients with HGSC. Further studies to confirm whether such cross-talk plays a role in modulating the malignant phenotype of HGSC and could serve as a predictive biomarker of patient survival are warranted.

SIGNIFICANCE

Generation of spatially resolved gene expression patterns in tumors from patients with ovarian cancer surviving more than 10 years allows the identification of novel predictive biomarkers and therapeutic targets for better patient management. See related commentary by Kelliher and Lengyel, p. 1383.

Multiparameter single-cell proteomic technologies give new insights into the biology of ovarian tumors

High-grade serous ovarian cancer (HGSOC) is the most lethal gynecological malignancy. Its diagnosis at advanced stage compounded with its excessive genomic and cellular heterogeneity make curative treatment challenging. Two critical therapeutic challenges to overcome are carboplatin resistance and lack of response to immunotherapy. Carboplatin resistance results from diverse cell autonomous mechanisms which operate in different combinations within and across tumors. The lack of response to immunotherapy is highly likely to be related to an immunosuppressive HGSOC tumor microenvironment which overrides any clinical benefit. Results from a number of studies, mainly using transcriptomics, indicate that the immune tumor microenvironment (iTME) plays a role in carboplatin response. However, in patients receiving treatment, the exact mechanistic details are unclear. During the past decade, multiplex single-cell proteomic technologies have come to the forefront of biomedical research. Mass cytometry or cytometry by time-of-flight, measures up to 60 parameters in single cells that are in suspension. Multiplex cellular imaging technologies allow simultaneous measurement of up to 60 proteins in single cells with spatial resolution and interrogation of cell-cell interactions. This review suggests that functional interplay between cell autonomous responses to carboplatin and the HGSOC immune tumor microenvironment could be clarified through the application of multiplex single-cell proteomic technologies. We conclude that for better clinical care, multiplex single-cell proteomic technologies could be an integral component of multimodal biomarker development that also includes genomics and radiomics. Collection of matched samples from patients before and on treatment will be critical to the success of these efforts.

Deep learning-based tumor microenvironment segmentation is predictive of tumor mutations and patient survival in non-small-cell lung cancer

BACKGROUND

Despite the fact that tumor microenvironment (TME) and gene mutations are the main determinants of progression of the deadliest cancer in the world - lung cancer, their interrelations are not well understood. Digital pathology data provides a unique insight into the spatial composition of the TME. Various spatial metrics and machine learning approaches were proposed for prediction of either patient survival or gene mutations from this data. Still, these approaches are limited in the scope of analyzed features and in their explainability, and as such fail to transfer to clinical practice.

METHODS

Here, we generated 23,199 image patches from 26 hematoxylin-and-eosin (H&E)-stained lung cancer tissue sections and annotated them into 9 different tissue classes. Using this dataset, we trained a deep neural network ARA-CNN. Next, we applied the trained network to segment 467 lung cancer H&E images from The Cancer Genome Atlas (TCGA) database. We used the segmented images to compute human-interpretable features reflecting the heterogeneous composition of the TME, and successfully utilized them to predict patient survival and cancer gene mutations.

RESULTS

We achieved per-class AUC ranging from 0.72 to 0.99 for classifying tissue types in lung cancer with ARA-CNN. Machine learning models trained on the proposed human-interpretable features achieved a c-index of 0.723 in the task of survival prediction and AUC up to 73.5% for PDGFRB in the task of mutation classification.

CONCLUSIONS

We presented a framework that accurately predicted survival and gene mutations in lung adenocarcinoma patients based on human-interpretable features extracted from H&E slides. Our approach can provide important insights for designing novel cancer treatments, by linking the spatial structure of the TME in lung adenocarcinoma to gene mutations and patient survival. It can also expand our understanding of the effects that the TME has on tumor evolutionary processes. Our approach can be generalized to different cancer types to inform precision medicine strategies.

Repertoire-scale measures of antigen binding

Antibodies and T cell receptors (TCRs) are the fundamental building blocks of adaptive immunity. Repertoire-scale functionality derives from their epitope-binding properties, just as macroscopic properties like temperature derive from microscopic molecular properties. However, most approaches to repertoire-scale measurement, including sequence diversity and entropy, are not based on antibody or TCR function in this way. Thus, they potentially overlook key features of immunological function. Here we present a framework that describes repertoires in terms of the epitope-binding properties of their constituent antibodies and TCRs, based on analysis of thousands of antibody-antigen and TCR-peptide-major-histocompatibility-complex binding interactions and over 400 high-throughput repertoires. We show that repertoires consist of loose overlapping classes of antibodies and TCRs with similar binding properties. We demonstrate the potential of this framework to distinguish specific responses vs. bystander activation in influenza vaccinees, stratify cytomegalovirus (CMV)-infected cohorts, and identify potential immunological "super-agers." Classes add a valuable dimension to the assessment of immune function.

Anti-Cancer Effects of YAP Inhibitor (CA3) in Combination with Sorafenib against Hepatocellular Carcinoma (HCC) in Patient-Derived Multicellular Tumor Spheroid Models (MCTS)

PURPOSE

To assess the expression levels of YAP and TAZ in patient-derived HCC tissue and identify the effects of YAP/TAZ inhibition depending on the baseline YAP/TAZ expression when combined with sorafenib using a patient-derived multicellular tumor spheroid (MCTS) model.

METHODS

Primary HCC cell lines were established from patient-derived tissue. Six patient-derived HCC cell lines were selected according to YAP/TAZ expression on Western blot: high, medium, low. Then, MCTS was generated by mixing patient-derived HCC cells and stroma cells (LX2, WI38, and HUVECs) and YAP/TAZ expression was assessed using Western blot. Cell viability of MCTS upon 48 h of drug treatment (sorafenib, sorafenib with CA3 0.1 µM, and CA3 (novel YAP1 inhibitor)) was analyzed.

RESULTS

Out of six patient-derived HCC cell lines, cell lines with high YAP/TAZ expression at the MCTS level responded more sensitively to the combination therapy (Sorafenib + CA3 0.1 μM) despite the potent cytotoxic effect of CA3 exhibited in all of the patient-derived HCCs.

CONCLUSION

Targeting YAP/TAZ inhibition using the novel YAP1 inhibitor CA3 could be a promising therapeutic strategy to enhance sensitivity to sorafenib especially in HCCs with high YAP/TAZ expression in MCTS.

Neo-Adjuvant Chemotherapy Reduces, and Surgery Increases Immunosuppression in First-Line Treatment for Ovarian Cancer

In monotherapy, immunotherapy has a poor success rate in ovarian cancer. Upgrading to a successful combinatorial immunotherapy treatment implies knowledge of the immune changes that are induced by chemotherapy and surgery.

METHODOLOGY

Patients with a new d ovarian cancer diagnosis underwent longitudinal blood samples at different time points during primary treatment.

RESULTS

Ninety patients were included in the study (33% primary debulking surgery (PDS) with adjuvant chemotherapy (ACT), 61% neo-adjuvant chemotherapy (NACT) with interval debulking surgery (IDS), and 6% debulking surgery only). Reductions in immunosuppression were observed after NACT, but surgery reverted this effect. The immune-related proteins showed a pronounced decrease in immune stimulation and immunosuppression when primary treatment was completed. NACT with IDS leads to a transient amelioration of the immune microenvironment compared to PDS with ACT.

CONCLUSION

The implementation of immunotherapy in the primary treatment schedule of ovarian cancer cannot be induced blindly. Carboplatin-paclitaxel seems to ameliorate the hostile immune microenvironment in ovarian cancer, which is less pronounced at the end of primary treatment. This prospective study during primary therapy for ovarian cancer that also looks at the evolution of immune-related proteins provides us with an insight into the temporary windows of opportunity in which to introduce immunotherapy during primary treatment.

Personalized models of heterogeneous 3D epithelial tumor microenvironments: Ovarian cancer as a model

Intractable human diseases such as cancers, are context dependent, unique to both the individual patient and to the specific tumor microenvironment. However, conventional cancer treatments are often nonspecific, targeting global similarities rather than unique drivers. This limits treatment efficacy across heterogeneous patient populations and even at different tumor locations within the same patient. Ultimately, this poor efficacy can lead to adverse clinical outcomes and the development of treatment-resistant relapse. To prevent this and improve outcomes, it is necessary to be selective when choosing a patient's optimal adjuvant treatment. In this review, we posit the use of personalized, tumor-specific models (TSM) as tools to achieve this remarkable feat. First, using ovarian cancer as a model disease, we outline the heterogeneity and complexity of both the cellular and extracellular components in the tumor microenvironment. Then we examine the advantages and disadvantages of contemporary cancer models and the rationale for personalized TSM. We discuss how to generate precision 3D models through careful and detailed analysis of patient biopsies. Finally, we provide clinically relevant applications of these versatile personalized cancer models to highlight their potential impact. These models are ideal for a myriad of fundamental cancer biology and translational studies. Importantly, these approaches can be extended to other carcinomas, facilitating the discovery of new therapeutics that more effectively target the unique aspects of each individual patient's TME. STATEMENT OF SIGNIFICANCE: In this article, we have presented the case for the application of biomaterials in developing personalized models of complex diseases such as cancers. TSM could bring about breakthroughs in the promise of precision medicine. The critical components of the diverse tumor microenvironments, that lead to treatment failures, include cellular- and extracellular matrix- heterogeneity, and biophysical signals to the cells. Therefore, we have described these dynamic components of the tumor microenvironments, and have highlighted how contemporary biomaterials can be utilized to create personalized in vitro models of cancers. We have also described the application of the TSM to predict the dynamic patterns of disease progression, and predict effective therapies that can produce durable responses, limit relapses, and treat any minimal residual disease.

Type of chemotherapy has substantial effects on the immune system in ovarian cancer

Chemotherapy induces a variety of immunological changes. Studying these effects can reveal opportunities for successful combining chemotherapy and immunotherapy. Immuno-chemotherapeutic combinations in ovarian cancer are currently not generating the anticipated positive effects. To date, only scattered and inconsistent information is available about the immune-induced changes by chemotherapy in ovarian cancer. In this study, we compared six common chemotherapeutics used in ovarian cancer patients (carboplatin, paclitaxel, pegylated liposomal doxorubicin, gemcitabine, carboplatin-paclitaxel and carboplatin-gemcitabine) and studied their effects on the immune system in an ovarian cancer mouse model. Mice received a single chemotherapy or vehicle injection 21 days after tumor inoculation with ID8-fluc cells. One week after therapy administration, we collected peritoneal washings for flow cytometry, serum for cytokine analysis with cytometric bead array and tumor biopsies for immunohistochemistry. Carboplatin-paclitaxel showed the most favorable profile with a decrease in immunosuppressive cells in the peritoneal cavity and an increase of interferon-gamma in serum. In contrast, carboplatin-gemcitabine seemed to promote a hostile immune environment with an increase in regulatory T-cells in tumor tissue and an increase of macrophage-inflammatory-protein-1-beta in the serum.

Predicting the results of competition between two breast cancer lines grown in 3-D spheroid culture

This study develops a novel model of a consumer-resource system with mobility included, in order to explain a novel experiment of competition between two breast cancer cell lines grown in 3D in vitro spheroid culture. The model reproduces observed differences in monoculture, such as overshoot phenomena and final size. It also explains both theoretically and through simulation the inevitable triumph of the same cell line in co-culture, independent of initial conditions. The mobility of one cell line (MDA-MB-231) is required to explain both the success and the rapidity with which that species dominates the population and drives the other species (MCF-7) to extinction. It is shown that mobility directly interferes with the other species and that the cost of that mobility is in resource usage rate.

Phenotypic Characterization by Mass Cytometry of the Microenvironment in Ovarian Cancer and Impact of Tumor Dissociation Methods

Simple Summary

High-grade serous ovarian cancer (HGSOC) is the deadliest gynecological malignancy. Despite increasing research on HGSOC, biomarkers for individualized selection of therapy are scarce. In this study, we develop a multiparametric mass cytometry antibody panel to identify differences in the cellular composition of the microenvironment of tumor tissues dissociated to single-cell suspensions. We also investigate how dissociation methods impact results. Application of our antibody panel to HGSOC tissues showed its ability to identify established main cell subsets and subpopulations of these cells. Comparisons between dissociation methods revealed differences in cell fractions for one immune, two stromal, and three tumor cell subpopulations, while functional marker expression was not affected by the dissociation method. The interpatient disparities identified in the tumor microenvironment were more significant than those identified between differently dissociated tissues from one patient, indicating that the panel facilitates the mapping of individual tumor microenvironments in HGSOC patients.

Abstract

Improved molecular dissection of the tumor microenvironment (TME) holds promise for treating high-grade serous ovarian cancer (HGSOC), a gynecological malignancy with high mortality. Reliable disease-related biomarkers are scarce, but single-cell mapping of the TME could identify patient-specific prognostic differences. To avoid technical variation effects, however, tissue dissociation effects on single cells must be considered. We present a novel Cytometry by Time-of-Flight antibody panel for single-cell suspensions to identify individual TME profiles of HGSOC patients and evaluate the effects of dissociation methods on results. The panel was developed utilizing cell lines, healthy donor blood, and stem cells and was applied to HGSOC tissues dissociated by six methods. Data were analyzed using Cytobank and X-shift and illustrated by t-distributed stochastic neighbor embedding plots, heatmaps, and stacked bar and error plots. The panel distinguishes the main cellular subsets and subpopulations, enabling characterization of individual TME profiles. The dissociation method affected some immune (n = 1), stromal (n = 2), and tumor (n = 3) subsets, while functional marker expressions remained comparable. In conclusion, the panel can identify subsets of the HGSOC TME and can be used for in-depth profiling. This panel represents a promising profiling tool for HGSOC when tissue handling is considered.

Opposite Macrophage Polarization in Different Subsets of Ovarian Cancer: Observation from a Pilot Study

The role of the innate immune system in ovarian cancer is gaining importance. The relevance of tumor-associated macrophages (TAM) is insufficiently understood. In this pilot project, comprising the immunofluorescent staining of 30 biopsies taken from 24 patients with ovarian cancer, we evaluated the presence of total TAM (cluster of differentiation (CD) 68 expression), M1 (major histocompatibility complex (MHC) II expression), and M2 (anti-mannose receptor C type 1 (MRC1) expression), and the blood vessel diameter. We observed a high M1/M2 ratio in low-grade ovarian cancer compared to high-grade tumors, more total TAM and M2 in metastatic biopsies, and a further increase in total TAM and M2 at interval debulking, without beneficial effects of bevacizumab. The blood vessel diameter was indicative for M2 tumor infiltration (Spearman correlation coefficient of 0.65). These data mainly reveal an immune beneficial environment in low-grade ovarian cancer in contrast to high-grade serous ovarian cancer, where immune suppression is not altered by neoadjuvant therapy.

Immune Heterogeneity Between Primary Tumors and Corresponding Metastatic Lesions and Response to Platinum Therapy in Primary Ovarian Cancer

CD3⁺ and CD8⁺ lymphocytes are well known prognostic markers in primary ovarian cancer. In contrast, the predictive value of the immune infiltrate concerning treatment response and the involvement of immune heterogeneity between primary and metastatic lesions are poorly understood. In this study, the immune infiltrate of 49 primary tumors and 38 corresponding lesions in the omentum (n = 23) and the peritoneum (n = 15) was immunohistochemically analyzed and correlated with clinicopathological factors and platinum-sensitivity. Immune heterogeneity was observed between paired primary and metastatic lesions for all immune cell phenotypes. The stromal immune infiltrate was higher in the omental lesions than in the primary tumors, which was reflected by CD45 (p=0.007), CD3 (p=0.005), CD8 (p=0.012), and PD-1 (programmed cell-death protein 1) (p=0.013). A higher stromal infiltrate of both CD45⁺ and CD3⁺ cells in the omental lesions was associated with the detection of lymph node metastasis (CD45, p=0.018; CD3, p=0.037). Platinum-sensitive ovarian cancers revealed a higher intratumoral CD8⁺ infiltrate in the peritoneal lesions compared to the primary tumors (p=0.045). In contrast, higher counts of stromal PD-1⁺ cells in the peritoneal lesions have been associated with reduced platinum-sensitivity (p=0.045). Immune heterogeneity was associated with platinum response and might represent a selection marker for personalized therapy.

Tumor-associated macrophages modulate resistance to oxaliplatin via inducing autophagy in hepatocellular carcinoma

Background

Oxaliplatin-based chemotherapy is widely used to treat hepatocellular carcinoma (HCC). Recent studies suggested that therapeutic resistance of tumors was affected by tumor microenvironment (TME). As a major component of TME, the role of tumor-associated macrophages (TAMs) on drug resistance in HCC is largely unknown.

Methods

26 HCC samples were obtained from patients who had underwent transarterial chemoembolization (TACE) within 3 months before receiving curative resections. Immunohistochemistry was applied to detect the density of TAMs in these tissues. SMMC-7721 and Huh-7 cell lines were used to co-culture with THP-1 derived macrophages. Under oxaliplatin treatment, cell death was measured using MTT and annexin V/propidium iodide assays. Autophagy activation was evaluated by GFP-LC3 redistribution and LC3 conversion in SMMC-7721 and Huh-7. Short-interfering RNA against ATG5 gene was applied to inhibit autophagy. In vivo validation was conducted in Huh-7 with or without macrophages using an HCC xenograft model in nude mice after oxaliplatin administration.

Results

We found that the density of TAMs in HCC samples was associated with the efficacy of TACE. Macrophages inhibited cell death induced by oxaliplatin in HCC cells. Autophagy was functionally activated in HCC cells after co-culturing with macrophages. Suppression of autophagy using RNA interference of ATG5 in HCC cells promoted the oxaliplatin cytotoxicity in the co-culture system. Critically, co-implantation with macrophages in HCC xenografts weakens cytotoxic effect of oxaliplatin through inducing autophagy to avoid apoptosis.

Conclusions

Our results suggest that TAMs induce autophagy in HCC cells which might contribute to oxaliplatin resistance. Targeting TAMs is a promising therapeutic strategy to enhance the effects of chemotherapy oxaliplatin in HCC patients.

Intratumoral Heterogeneity in Ductal Carcinoma In Situ: Chaos and Consequence

Ductal carcinoma in situ (DCIS) is a non-invasive proliferative growth in the breast that serves as a non-obligate precursor to invasive ductal carcinoma. The widespread adoption of screening mammography has led to a steep increase in the detection of DCIS, which now comprises approximately 20% of new breast cancer diagnoses in the United States. Interestingly, the intratumoral heterogeneity (ITH) that has been observed in invasive breast cancers may have been established early in tumorigenesis, given the vast and varied ITH that has been detected in DCIS. This review will discuss the intratumoral heterogeneity of DCIS, focusing on the phenotypic and genomic heterogeneity of tumor cells, as well as the compositional heterogeneity of the tumor microenvironment. In addition, we will assess the spatial heterogeneity that is now being appreciated in these lesions, and summarize new approaches to evaluate heterogeneity of tumor and stromal cells in the context of their spatial organization. Importantly, we will discuss how a growing understanding of ITH has led to a more holistic appreciation of the complex biology of DCIS, specifically its evolution and natural history. Finally, we will consider ways in which our knowledge of DCIS ITH might be translated in the future to guide clinical care for DCIS patients.

Microenvironmental niche divergence shapes BRCA1-dysregulated ovarian cancer morphological plasticity

How tumor microenvironmental forces shape plasticity of cancer cell morphology is poorly understood. Here, we conduct automated histology image and spatial statistical analyses in 514 high grade serous ovarian samples to define cancer morphological diversification within the spatial context of the microenvironment. Tumor spatial zones, where cancer cell nuclei diversify in shape, are mapped in each tumor. Integration of this spatially explicit analysis with omics and clinical data reveals a relationship between morphological diversification and the dysregulation of DNA repair, loss of nuclear integrity, and increased disease mortality. Within the Immunoreactive subtype, spatial analysis further reveals significantly lower lymphocytic infiltration within diversified zones compared with other tumor zones, suggesting that even immune-hot tumors contain cells capable of immune escape. Our findings support a model whereby a subpopulation of morphologically plastic cancer cells with dysregulated DNA repair promotes ovarian cancer progression through positive selection by immune evasion.

Microenvironmental niche divergence shapes BRCA1-dysregulated ovarian cancer morphological plasticity

How tumor microenvironmental forces shape plasticity of cancer cell morphology is poorly understood. Here, we conduct automated histology image and spatial statistical analyses in 514 high grade serous ovarian samples to define cancer morphological diversification within the spatial context of the microenvironment. Tumor spatial zones, where cancer cell nuclei diversify in shape, are mapped in each tumor. Integration of this spatially explicit analysis with omics and clinical data reveals a relationship between morphological diversification and the dysregulation of DNA repair, loss of nuclear integrity, and increased disease mortality. Within the Immunoreactive subtype, spatial analysis further reveals significantly lower lymphocytic infiltration within diversified zones compared with other tumor zones, suggesting that even immune-hot tumors contain cells capable of immune escape. Our findings support a model whereby a subpopulation of morphologically plastic cancer cells with dysregulated DNA repair promotes ovarian cancer progression through positive selection by immune evasion.

Microenvironmental niche divergence shapes BRCA1-dysregulated ovarian cancer morphological plasticity

How tumor microenvironmental forces shape plasticity of cancer cell morphology is poorly understood. Here, we conduct automated histology image and spatial statistical analyses in 514 high grade serous ovarian samples to define cancer morphological diversification within the spatial context of the microenvironment. Tumor spatial zones, where cancer cell nuclei diversify in shape, are mapped in each tumor. Integration of this spatially explicit analysis with omics and clinical data reveals a relationship between morphological diversification and the dysregulation of DNA repair, loss of nuclear integrity, and increased disease mortality. Within the Immunoreactive subtype, spatial analysis further reveals significantly lower lymphocytic infiltration within diversified zones compared with other tumor zones, suggesting that even immune-hot tumors contain cells capable of immune escape. Our findings support a model whereby a subpopulation of morphologically plastic cancer cells with dysregulated DNA repair promotes ovarian cancer progression through positive selection by immune evasion.

Revisiting ovarian cancer microenvironment: a friend or a foe?

Development of ovarian cancer involves the co-evolution of neoplastic cells together with the adjacent microenvironment. Steps of malignant progression including primary tumor outgrowth, therapeutic resistance, and distant metastasis are not determined solely by genetic alterations in ovarian cancer cells, but considerably shaped by the fitness advantage conferred by benign components in the ovarian stroma. As the dynamic cancer topography varies drastically during disease progression, heterologous cell types within the tumor microenvironment (TME) can actively determine the pathological track of ovarian cancer. Resembling many other solid tumor types, ovarian malignancy is nurtured by a TME whose dark side may have been overlooked, rather than overestimated. Further, harnessing breakthrough and targeting cures in human ovarian cancer requires insightful understanding of the merits and drawbacks of current treatment modalities, which mainly target transformed cells. Thus, designing novel and precise strategies that both eliminate cancer cells and manipulate the TME is increasingly recognized as a rational avenue to improve therapeutic outcome and prevent disease deterioration of ovarian cancer patients.

Absence of PD-L1 on tumor cells is associated with reduced MHC I expression and PD-L1 expression increases in recurrent serous ovarian cancer

Immune-evasion and immune checkpoints are promising new therapeutic targets for several cancer entities. In ovarian cancer, the clinical role of programmed cell death receptor ligand 1 (PD-L1) expression as mechanism to escape immune recognition has not been clarified yet. We analyzed PD-L1 expression of primary ovarian and peritoneal tumor tissues together with several other parameters (whole transcriptomes of isolated tumor cells, local and systemic immune cells, systemic cytokines and metabolites) and compared PD-L1 expression between primary tumor and tumor recurrences. All expressed major histocompatibility complex (MHC) I genes were negatively correlated to PD-L1 abundances on tumor tissues, indicating two mutually exclusive immune-evasion mechanisms in ovarian cancer: either down-regulation of T-cell mediated immunity by PD-L1 expression or silencing of self-antigen presentation by down-regulation of the MHC I complex. In our cohort and in most of published evidences in ovarian cancer, low PD-L1 expression is associated with unfavorable outcome. Differences in immune cell populations, cytokines, and metabolites strengthen this picture and suggest the existence of concurrent pathways for progression of this disease. Furthermore, recurrences showed significantly increased PD-L1 expression compared to the primary tumors, supporting trials of checkpoint inhibition in the recurrent setting.

Activated hepatic stellate cells play pivotal roles in hepatocellular carcinoma cell chemoresistance and migration in multicellular tumor spheroids

Most Hepatocellular carcinoma (HCC) are resistant to conventional chemotherapeutic agents and remain an unmet medical need. Recently, multiple studies on the crosstalk between HCC and their tumor microenvironment have been conducted to overcome chemoresistance in HCC. In this study, we formed multicellular tumor spheroids (MCTS) to elucidate the mechanisms of environment-mediated chemoresistance in HCC. We observed that hepatic stellate cells (HSCs) in MCTS significantly increased the compactness of spheroids and exhibited strong resistance to sorafenib and cisplatin relative to other types of stromal cells. Increased collagen 1A1 (COL1A1) expression was apparent in activated HSCs but not in fibroblasts or vascular endothelial cells in MCTS. Additionally, COL1A1 deficiency, which was increased by co-culture with HSCs, decreased the cell-cell interactions and thereby increased the therapeutic efficacy of anticancer therapies in MCTS. Furthermore, losartan, which can inhibit collagen I synthesis, attenuated the compactness of spheroids and increased the therapeutic efficacy of anticancer therapies in MCTS. Meanwhile, activated HSCs facilitated HCC migration by upregulating matrix metallopeptidase 9 (MMP9) in MCTS. Collectively, crosstalk between HCC cells and HSCs promoted HCC chemoresistance and migration by increasing the expression of COL1A1 and MMP9 in MCTS. Hence, targeting HSCs might represent a promising therapeutic strategy for liver cancer therapy.