Deconstruction of a Metastatic Tumor Microenvironment Reveals a Common Matrix Response in Human Cancers

High levels of hypusinated eIF5A in leiomyoma and leiomyosarcoma pathologies: a possible novel therapeutic target

RESEARCH QUESTION

Is the hypusinated form of the eukaryotic translation initiation factor 5A (EIF5A) present in human myometrium, leiomyoma and leiomyosarcoma, and does it regulate cell proliferation and fibrosis?

DESIGN

The hypusination status of eIF5A in myometrial and leiomyoma patient-matched tissues was evaluated by immunohistochemistry and Western blotting as well as in leiomyosarcoma tissues by immunohistochemistry. Myometrial, leiomyoma and leiomyosarcoma cell lines were treated with N1-guanyl-1,7-diaminoheptane (GC-7), responsible for the inhibition of the first step of eIF5A hypunization, and the proliferation rate was determined by MTT assay; fibronectin expression was analysed by Western blotting. Finally, expression of fibronectin in leiomyosarcoma tissues was detected by immunohistochemistry.

RESULTS

The hypusinated form of eIF5A was present in all tissues examined, with an increasing trend of hypusinated eIF5A levels from normal myometrium to neoplastic benign leiomyoma up to neoplastic malignant leiomyosarcoma. The higher levels in leiomyoma compared with myometrium were confirmed by Western blotting (P = 0.0046). The inhibition of eIF5A hypusination, with GC-7 treatment at 100 nM, reduced the cell proliferation in myometrium (P = 0.0429), leiomyoma (P = 0.0030) and leiomyosarcoma (P = 0.0044) cell lines and reduced the expression of fibronectin in leiomyoma (P = 0.0077) and leiomyosarcoma (P = 0.0280) cells. The immunohistochemical staining of leiomyosarcoma tissue revealed that fibronectin was highly expressed in the malignant aggressive (central) part of the leiomyosarcoma lesion, where hypusinated eIF5A was also highly represented.

CONCLUSIONS

These data support the hypothesis that eIF5A may be involved in the pathogenesis of myometrial benign and malignant pathologies.

MMDAE-HGSOC: A novel method for high-grade serous ovarian cancer molecular subtypes classification based on multi-modal deep autoencoder

High-grade serous ovarian cancer (HGSOC) is a type of ovarian cancer developed from serous tubal intraepithelial carcinoma. The intrinsic differences among molecular subtypes are closely associated with prognosis and pathological characteristics. At present, multi-omics data integration methods include early integration and late integration. Most existing HGSOC molecular subtypes classification methods are based on the early integration of multi-omics data. The mutual interference among multi-omics data is ignored, which affects the effectiveness of feature learning. High-dimensional multi-omics data contains genes unassociated with HGSOC molecular subtypes, resulting in redundant information, which is not conducive to model training. In this paper, we propose a multi-modal deep autoencoder learning method, MMDAE-HGSOC. MiRNA expression, DNA methylation, and copy number variation (CNV) are integrated with mRNA expression data to construct a multi-omics feature space. The multi-modal deep autoencoder network is used to learn the high-level feature representation of multi-omics data. The superposition LASSO (S-LASSO) regression algorithm is proposed to fully obtain the associated genes of HGSOC molecular subtypes. The experimental results show that MMDAE-HGSOC is superior to the existing classification methods. Finally, we analyze the enrichment gene ontology (GO) terms and biological pathways of these significant genes, which are discovered during the gene selection process.

Biofabrication of Modular Spheroids as Tumor-Scale Microenvironments for Drug Screening

To streamline the drug discovery pipeline, there is a pressing need for preclinical models which replicate the complexity and scale of native tumors. While there have been advancements in the formation of microscale tumor units, these models are cell-line dependent, time-consuming and have not improved clinical trial success rates. In this study, two methods for generating 3D tumor microenvironments are compared, rapidly fabricated hydrogel microspheres and traditional cell-dense spheroids. These modules are then bioassembled into 3D printed thermoplastic scaffolds, using an automated biofabrication process, to form tumor-scale models. Modules are formed with SKOV3 and HFF cells as monocultures and cocultures, and the fabrication efficiency, cell architecture, and drug response profiles are characterized, both as single modules and as multimodular constructs. Cell-encapsulated Gel-MA microspheres are fabricated with high-reproducibility and dimensions necessary for automated tumor-scale bioassembly regardless of cell type, however, only cocultured spheroids form compact modules suitable for bioassembly. Chemosensitivity assays demonstrate the reduced potency of doxorubicin in coculture bioassembled constructs and a ≈five-fold increase in drug resistance of cocultured cells in 3D modules compared with 2D monolayers. This bioassembly system is efficient and tailorable so that a variety of relevant-sized tumor constructs could be developed to study tumorigenesis and modernize drug discovery.

Next Generation CD44v6-Specific CAR-NK Cells Effective against Triple Negative Breast Cancer

There is a medical need to develop new and effective therapies against triple-negative breast cancer (TNBC). Chimeric antigen receptor (CAR) natural killer (NK) cells are a promising alternative to CAR-T cell therapy for cancer. A search for a suitable target in TNBC identified CD44v6, an adhesion molecule expressed in lymphomas, leukemias and solid tumors that is implicated in tumorigenesis and metastases. We have developed a next-generation CAR targeting CD44v6 that incorporates IL-15 superagonist and checkpoint inhibitor molecules. We could show that CD44v6 CAR-NK cells demonstrated effective cytotoxicity against TNBC in 3D spheroid models. The IL-15 superagonist was specifically released upon recognition of CD44v6 on TNBC and contributed to the cytotoxic attack. PD1 ligands are upregulated in TNBC and contribute to the immunosuppressive tumor microenvironment (TME). Competitive inhibition of PD1 neutralized inhibition by PD1 ligands expressed on TNBC. In total, CD44v6 CAR-NK cells are resistant to TME immunosuppression and offer a new therapeutic option for the treatment of BC, including TNBC.

Extracellular matrix educates an immunoregulatory tumor macrophage phenotype found in ovarian cancer metastasis

Recent studies have shown that the tumor extracellular matrix (ECM) associates with immunosuppression, and that targeting the ECM can improve immune infiltration and responsiveness to immunotherapy. A question that remains unresolved is whether the ECM directly educates the immune phenotypes seen in tumors. Here, we identify a tumor-associated macrophage (TAM) population associated with poor prognosis, interruption of the cancer immunity cycle, and tumor ECM composition. To investigate whether the ECM was capable of generating this TAM phenotype, we developed a decellularized tissue model that retains the native ECM architecture and composition. Macrophages cultured on decellularized ovarian metastasis shared transcriptional profiles with the TAMs found in human tissue. ECM-educated macrophages have a tissue-remodeling and immunoregulatory phenotype, inducing altered T cell marker expression and proliferation. We conclude that the tumor ECM directly educates this macrophage population found in cancer tissues. Therefore, current and emerging cancer therapies that target the tumor ECM may be tailored to improve macrophage phenotype and their downstream regulation of immunity.

Semi-supervised analysis of myeloid and T cell behavior in ex vivo ovarian tumor slices reveals changes in cell motility after treatments

Studies of the high-grade serous ovarian cancer (HGSOC) tumor microenvironment, the most lethal gynecological cancer, aim to enhance the efficiency of established therapies. Cell motility is an important process of anti-tumor response. Using ex vivo human and mouse HGSOC tumor slices combined with time-lapse imaging, we assessed the motility of CD8+ T and myeloid cells. We developed a semi-supervised analysis of cell movements, identifying four cell behaviors: migrating, long migrating, static, and wobbling. Tumor slices were maintained 24h ex vivo, retaining viability and cell movements. Ex vivo treatments with lipopolysaccharide altered CD8+ T and myeloid cell behavior. In vivo chemotherapy reduced ex vivo cell movements in human and mouse tumors and differentially affected CD8+ T and myeloid cells in chemo-sensitive and chemo-resistant mouse models. Ex vivo tumor slices can extend in vivo mouse studies to human, providing a stepping stone to translate mouse cancer studies to clinical trials.

Insights into high-grade serous carcinoma pathobiology using three-dimensional culture model systems

Epithelial ovarian cancer (EOC) research has become more complex as researchers try to fully understand the metastatic process. Especially as we delve into the concept of tumour dormancy, where cells transition between proliferative and dormant states to survive during disease progression. Thus, the in vitro models used to conduct this research need to reflect this vast biological complexity. The innovation behind the many three-dimensional (3D) spheroid models has been refined to easily generate reproducible spheroids so that we may understand the various molecular signaling changes of cells during metastasis and determine therapeutic efficacy of treatments. This ingenuity was then used to develop the 3D ex vivo patient-derived organoid model, as well as multiple co-culture model systems for EOC research. Although, researchers need to continue to push the boundaries of these current models for in vitro and even in vivo work in the future. In this review, we describe the 3D models already in use, where these models can be developed further and how we can use these models to gain the most knowledge on EOC pathogenesis and discover new targeted therapies.

Macrophages and bone metastasis

In the prostate bone metastasis microenvironment, macrophages activate a cascade that involves Activin A, the extracellular matrix, and SRC kinase and drives resistance to anti-androgen therapy. These findings (Li et al., 2023. J. Exp. Med.https://doi.org/10.1084/jem.20221007) have broad implications, including metastasis diversity in different tissue milieus and the interplay between hormones and immunity.

Molecular landscape and emerging therapeutic strategies in breast cancer brain metastasis

Breast cancer (BC) is the most commonly diagnosed cancer worldwide. Advanced BC with brain metastasis (BM) is a major cause of mortality with no specific or effective treatment. Therefore, better knowledge of the cellular and molecular mechanisms underlying breast cancer brain metastasis (BCBM) is crucial for developing novel therapeutic strategies and improving clinical outcomes. In this review, we focused on the latest advances and discuss the contribution of the molecular subtype of BC, the brain microenvironment, exosomes, miRNAs/lncRNAs, and genetic background in BCBM. The blood–brain barrier and blood–tumor barrier create challenges to brain drug delivery, and we specifically review novel approaches to bypass these barriers. Furthermore, we discuss the potential application of immunotherapies and genetic editing techniques based on CRISPR/Cas9 technology in treating BCBM. Emerging techniques and research findings continuously shape our views of BCBM and contribute to improvements in precision therapies and clinical outcomes.

Novel microenvironment-based classification of intrahepatic cholangiocarcinoma with therapeutic implications

OBJECTIVE

The diversity of the tumour microenvironment (TME) of intrahepatic cholangiocarcinoma (iCCA) has not been comprehensively assessed. We aimed to generate a novel molecular iCCA classifier that incorporates elements of the stroma, tumour and immune microenvironment ('STIM' classification).

DESIGN

We applied virtual deconvolution to transcriptomic data from ~900 iCCAs, enabling us to devise a novel classification by selecting for the most relevant TME components. Murine models were generated through hydrodynamic tail vein injection and compared with the human disease.

RESULTS

iCCA is composed of five robust STIM classes encompassing both inflamed (35%) and non-inflamed profiles (65%). The inflamed classes, named immune classical (~10%) and inflammatory stroma (~25%), differ in oncogenic pathways and extent of desmoplasia, with the inflammatory stroma showing T cell exhaustion, abundant stroma and KRAS mutations (p<0.001). Analysis of cell-cell interactions highlights cancer-associated fibroblast subtypes as potential mediators of immune evasion. Among the non-inflamed classes, the desert-like class (~20%) harbours the lowest immune infiltration with abundant regulatory T cells (p<0.001), whereas the hepatic stem-like class (~35%) is enriched in 'M2-like' macrophages, mutations in IDH1/2 and BAP1, and FGFR2 fusions. The remaining class (tumour classical: ~10%) is defined by cell cycle pathways and poor prognosis. Comparative analysis unveils high similarity between a KRAS/p19 murine model and the inflammatory stroma class (p=0.02). The KRAS-SOS inhibitor, BI3406, sensitises a KRAS-mutant iCCA murine model to anti-PD1 therapy.

CONCLUSIONS

We describe a comprehensive TME-based stratification of iCCA. Cross-species analysis establishes murine models that align closely to human iCCA for the preclinical testing of combination strategies.

Cancer-Associated Fibroblasts in Inflammation and Antitumor Immunity

Tumor-associated inflammation (TAI) is a feature of essentially all cancers and can confer both tumor-promoting and -suppressive functions. Cancer-associated fibroblasts (CAF) comprise one very heterogeneous cellular component of the tumor microenvironment characterized by a high degree of plasticity. Recent single-cell sequencing analyses revealed distinct CAF populations in various human cancers and helped to define key CAF subtypes, such as myofibroblastic, inflammatory, and antigen-presenting CAFs, with the first two being present in virtually all tumors. Importantly, these three CAF populations are involved in and modulate the positive and negative consequences of TAI. The remarkable plasticity of CAFs allows them to shift phenotypically and functionally in response to environmental changes. In this review, we describe how CAFs nurture tumor-promoting inflammation and suppress adaptive immunity. We also summarize the recently emerging evidence pertaining to tumor-suppressive CAF functions in the context of TAI. Finally, we summarize therapeutic concepts that aim at modulating CAF functions or depleting immunosuppressive CAFs to synergize with immunotherapy.

Activated fibroblasts in cancer: Perspectives and challenges

Activated fibroblasts in tumors, or cancer-associated fibroblasts (CAFs), have become a popular research area over the past decade. As important players in many aspects of tumor biology, with functions ranging from collagen deposition to immunosuppression, CAFs have been the target of clinical and pre-clinical studies that have revealed their potential pro- and anti-tumorigenic dichotomy. In this review, we describe the important role of CAFs in the tumor microenvironment and the technological advances that made these discoveries possible, and we detail the models that are currently available for CAF investigation. Additionally, we present evidence to support the value of encompassing CAF investigation as a future therapeutic avenue alongside immune and cancer cells while highlighting the challenges that must be addressed for successful clinical translation of new findings.

Phase-specific signatures of wound fibroblasts and matrix patterns define cancer-associated fibroblast subtypes

Healing wounds and cancers present remarkable cellular and molecular parallels, but the specific roles of the healing phases are largely unknown. We developed a bioinformatics pipeline to identify genes and pathways that define distinct phases across the time-course of healing. Their comparison to cancer transcriptomes revealed that a resolution phase wound signature is associated with increased severity in skin cancer and enriches for extracellular matrix-related pathways. Comparisons of transcriptomes of early- and late-phase wound fibroblasts vs skin cancer-associated fibroblasts (CAFs) identified an "early wound" CAF subtype, which localizes to the inner tumor stroma and expresses collagen-related genes that are controlled by the RUNX2 transcription factor. A "late wound" CAF subtype localizes to the outer tumor stroma and expresses elastin-related genes. Matrix imaging of primary melanoma tissue microarrays validated these matrix signatures and identified collagen- vs elastin-rich niches within the tumor microenvironment, whose spatial organization predicts survival and recurrence. These results identify wound-regulated genes and matrix patterns with prognostic potential in skin cancer.

Model of collective detachment in high-grade serous ovarian cancer demonstrates that tumor spheroids produce ECM to support metastatic processes

High-grade serous ovarian cancer (HGSOC) metastasizes through transcoelomic spread, with both single cells and spheroids of tumor cells observed in patient ascites. These spheroids may form through single cells that detach and aggregate (Sph-SC) or through collective detachment (Sph-CD). We developed an in vitro model to generate and separate Sph-SC from Sph-CD to enable study of Sph-CD in disease progression. In vitro-generated Sph-CD and spheroids isolated from ascites were similar in size (mean diameter 51 vs 55 μm, p > 0.05) and incorporated multiple ECM proteins. Using the in vitro model, nascent protein labeling, and qRT-PCR, we determined that ECM was produced after detachment. As fibronectin plays a key role in many cell adhesion events, we confirmed that inhibiting RGD-based adhesion or fibronectin assembly reduced Sph-CD-mesothelial adhesion strength under shear stress. Our model will enable future studies to determine factors that favor formation of Sph-CD, as well as allow investigators to manipulate Sph-CD to better study their effects on HGSOC progression.

Extracellular Matrix in High-Grade Serous Ovarian Cancer: Advances in Understanding of Carcinogenesis and Cancer Biology

High-grade serous ovarian cancer (HGSOC) is notoriously known as the "silent killer" of post-menopausal women as it has an insidious progression and is the deadliest gynaecological cancer. Although a dual origin of HGSOC is now widely accepted, there is growing evidence that most cases of HGSOC originate from the fallopian tube epithelium. In this review, we will address the fallopian tube origin and involvement of the extracellular matrix (ECM) in HGSOC development. There is limited research on the role of ECM at the earliest stages of HGSOC carcinogenesis. Here we aim to synthesise current understanding on the contribution of ECM to each stage of HGSOC development and progression, beginning at serous tubal intraepithelial carcinoma (STIC) precursor lesions and proceeding across key events including dissemination of tumourigenic fallopian tube epithelial cells to the ovary, survival of these cells in peritoneal fluid as multicellular aggregates, and colonisation of the ovary. Likewise, as part of the metastatic series of events, serous ovarian cancer cells survive travel in peritoneal fluid, attach to, migrate across the mesothelium and invade into the sub-mesothelial matrix of secondary sites in the peritoneal cavity. Halting cancer at the pre-metastatic stage and finding ways to stop the dissemination of ovarian cancer cells from the primary site is critical for improving patient survival. The development of drug resistance also contributes to poor survival statistics in HGSOC. In this review, we provide an update on the involvement of the ECM in metastasis and drug resistance in HGSOC. Interplay between different cell-types, growth factor gradients as well as evolving ECM composition and organisation, creates microenvironment conditions that promote metastatic progression and drug resistance of ovarian cancer cells. By understanding ECM involvement in the carcinogenesis and chemoresistance of HGSOC, this may prompt ideas for further research for developing new early diagnostic tests and therapeutic strategies for HGSOC with the end goal of improving patient health outcomes.

Tumor microenvironment in ovarian cancer peritoneal metastasis

Ovarian cancer (OC) is one of the most common gynecological malignancies with high morbidity and mortality. The peritoneum is one of the most common metastatic sites in ovarian cancer, involving large amounts of ascites. However, its mechanism is unclear. The peritoneal microenvironment composed of peritoneal effusion and peritoneum creates favorable conditions for ovarian cancer progression and metastasis. Here, we reviewed the peritoneal metastasis patterns and molecular mechanisms of ovarian cancer, as well as major components of the peritoneal microenvironment, peritoneal effusion, and immune microenvironment, and investigated the relationship between the peritoneal microenvironment and ovarian cancer metastasis.

Targeting tumor-stroma communication by blocking endothelin-1 receptors sensitizes high-grade serous ovarian cancer to PARP inhibition

PARP inhibitors (PARPi) have changed the treatment paradigm of high-grade serous ovarian cancer (HG-SOC). However, the impact of this class of inhibitors in HG-SOC patients with a high rate of TP53 mutations is limited, highlighting the need to develop combinatorial therapeutic strategies to improve responses to PARPi. Here, we unveil how the endothelin-1/ET-1 receptor (ET-1/ET-1R) axis, which is overexpressed in human HG-SOC and associated with poor prognosis, instructs HG-SOC/tumor microenvironment (TME) communication via key pro-malignant factors and restricts the DNA damage response induced by the PARPi olaparib. Mechanistically, the ET-1 axis promotes the p53/YAP/hypoxia inducible factor-1α (HIF-1α) transcription hub connecting HG-SOC cells, endothelial cells and activated fibroblasts, hence fueling persistent DNA damage signal escape. The ET-1R antagonist macitentan, which dismantles the ET-1R-mediated p53/YAP/HIF-1α network, interferes with HG-SOC/stroma interactions that blunt PARPi efficacy. Pharmacological ET-1R inhibition by macitentan in orthotopic HG-SOC patient-derived xenografts synergizes with olaparib to suppress metastatic progression, enhancing PARPi survival benefit. These findings reveal ET-1R as a mechanistic determinant in the regulation of HG-SOC/TME crosstalk and DNA damage response, indicating the use of macitentan in combinatorial treatments with PARPi as a promising and emerging therapy.

Patient-Derived In Vitro Models of Ovarian Cancer: Powerful Tools to Explore the Biology of the Disease and Develop Personalized Treatments

Epithelial ovarian cancer (OC) is the most lethal gynecological malignancy worldwide due to a late diagnosis caused by the lack of specific symptoms and rapid dissemination into the peritoneal cavity. The standard of care for OC treatment is surgical cytoreduction followed by platinum-based chemotherapy. While a response to this frontline treatment is common, most patients undergo relapse within 2 years and frequently develop a chemoresistant disease that has become unresponsive to standard treatments. Moreover, also due to the lack of actionable mutations, very few alternative therapeutic strategies have been designed as yet for the treatment of recurrent OC. This dismal clinical perspective raises the need for pre-clinical models that faithfully recapitulate the original disease and therefore offer suitable tools to design novel therapeutic approaches. In this regard, patient-derived models are endowed with high translational relevance, as they can better capture specific aspects of OC such as (i) the high inter- and intra-tumor heterogeneity, (ii) the role of cancer stem cells (a small subset of tumor cells endowed with tumor-initiating ability, which can sustain tumor spreading, recurrence and chemoresistance), and (iii) the involvement of the tumor microenvironment, which interacts with tumor cells and modulates their behavior. This review describes the different in vitro patient-derived models that have been developed in recent years in the field of OC research, focusing on their ability to recapitulate specific features of this disease. We also discuss the possibilities of leveraging such models as personalized platforms to design new therapeutic approaches and guide clinical decisions.

Identifying M1-like macrophage related genes for prognosis prediction in lung adenocarcinoma based on a gene co-expression network

Macrophages are one of the most important players in the tumor microenvironment. But the contribution of macrophages to lung adenocarcinoma (LUAD) is still controversial. The current study aimed to display an immune landscape to clarify the function of macrophages and detect prognostic hub genes in LUAD. The transcriptome data were adopted to screen differently expressed genes (DEGs) in The Cancer Genome Atlas database (TCGA). The cell type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm was used to reveal the immune landscape. Weighted gene co-expression network analysis (WGCNA) analysis was performed to identify the hub module associated with macrophages. Function Enrichment analysis was conducted on hub module genes. Moreover, univariate and multivariate Cox regression analyses were performed to identify prognostic hub genes. Kaplan-Meier (KM) and Time-dependent receiver operating characteristic (ROC) curves were plotted to assess the prognostic capacity of the four prognostic hub genes. The GES1196959 dataset from the Gene Expression Omnibus (GEO) database was downloaded to verify the differential expression of the 4 prognostic hub genes.

In Vitro Models of Ovarian Cancer: Bridging the Gap between Pathophysiology and Mechanistic Models

Ovarian cancer (OC) is a disease of major concern with a survival rate of about 40% at five years. This is attributed to the lack of visible and reliable symptoms during the onset of the disease, which leads over 80% of patients to be diagnosed at advanced stages. This implies that metastatic activity has advanced to the peritoneal cavity. It is associated with both genetic and phenotypic heterogeneity, which considerably increase the risks of relapse and reduce the survival rate. To understand ovarian cancer pathophysiology and strengthen the ability for drug screening, further development of relevant in vitro models that recapitulate the complexity of OC microenvironment and dynamics of OC cell population is required. In this line, the recent advances of tridimensional (3D) cell culture and microfluidics have allowed the development of highly innovative models that could bridge the gap between pathophysiology and mechanistic models for clinical research. This review first describes the pathophysiology of OC before detailing the engineering strategies developed to recapitulate those main biological features.

Mitochondrial CPT1A: Insights into structure, function, and basis for drug development

Carnitine Palmitoyl-Transferase1A (CPT1A) is the rate-limiting enzyme in the fatty acid β-oxidation, and its deficiency or abnormal regulation can result in diseases like metabolic disorders and various cancers. Therefore, CPT1A is a desirable drug target for clinical therapy. The deep comprehension of human CPT1A is crucial for developing the therapeutic inhibitors like Etomoxir. CPT1A is an appealing druggable target for cancer therapies since it is essential for the survival, proliferation, and drug resistance of cancer cells. It will help to lower the risk of cancer recurrence and metastasis, reduce mortality, and offer prospective therapy options for clinical treatment if the effects of CPT1A on the lipid metabolism of cancer cells are inhibited. Targeted inhibition of CPT1A can be developed as an effective treatment strategy for cancers from a metabolic perspective. However, the pathogenic mechanism and recent progress of CPT1A in diseases have not been systematically summarized. Here we discuss the functions of CPT1A in health and diseases, and prospective therapies targeting CPT1A. This review summarizes the current knowledge of CPT1A, hoping to prompt further understanding of it, and provide foundation for CPT1A-targeting drug development.

PAX8 modulates the tumor microenvironment of high grade serous ovarian cancer through changes in the secretome

High grade serous ovarian cancer (HGSC) arises from the fimbriated end of the fallopian tube epithelium (FTE), and in some cases, the ovarian surface epithelium (OSE). PAX8 is a commonly used biomarker for HGSC and is expressed in ∼90% of HGSC. Although the OSE does not express PAX8, murine models of HGSC derived from the OSE acquire PAX8, suggesting that it is not only a marker of Müllerian origin, but also an essential part of cancer progression, potentially from both the OSE and FTE. Previously, we have shown that PAX8 loss in HGSC cells causes tumor cell death and reduces cell migration and invasion. Herein, secretome analysis was performed in PAX8 deleted cells and we identified a reduction of the extracellular matrix (ECM) components, collagen and fibronectin. Immunoblotting and immunofluorescence in PAX8 deleted HGSC cells further validated the results from the secretome analysis. PAX8 loss reduced the amount of secreted TGFbeta, a cytokine that plays a crucial role in remodelling the tumor microenvironment. Furthermore, PAX8 loss reduced the integrity of 3D spheroids and caused a reduction of ECM proteins fibronectin and collagen in 3D cultures. Due to the ubiquitous nature of PAX8 in HGSC, regardless of cell origin, and the association of its reduced expression with decreasing tumor burden, a PAX8 inhibitor could be a promising drug target against various types of HGSC. To accomplish this, we generated a murine oviductal epithelial (MOE) cell line stably expressing PAX8 promoter-luciferase. Using this cell line, we performed a screening assay with a library of FDA-approved drugs (Prestwick Library) and quantitatively assessed these compounds for their inhibition of PAX8. We identified two hits: losartan and captropril, both inhibitors of the renin-angiotensin pathway that inhibit PAX8 expression and function. Overall, this study validates PAX8 as a regulator of ECM deposition in the tumor microenvironment.

Kinase Inhibitors in the Treatment of Ovarian Cancer: Current State and Future Promises

Ovarian cancer is the deadliest gynecological cancer, the high-grade serous ovarian carcinoma (HGSC) being its most common and most aggressive form. Despite the latest therapeutical advancements following the introduction of vascular endothelial growth factor receptor (VEGFR) targeting angiogenesis inhibitors and poly-ADP-ribose-polymerase (PARP) inhibitors to supplement the standard platinum- and taxane-based chemotherapy, the expected overall survival of HGSC patients has not improved significantly from the five-year rate of 42%. This calls for the development and testing of more efficient treatment options. Many oncogenic kinase-signaling pathways are dysregulated in HGSC. Since small-molecule kinase inhibitors have revolutionized the treatment of many solid cancers due to the generality of the increased activation of protein kinases in carcinomas, it is reasonable to evaluate their potential against HGSC. Here, we present the latest concluded and on-going clinical trials on kinase inhibitors in HGSC, as well as the recent work concerning ovarian cancer patient organoids and xenograft models. We discuss the potential of kinase inhibitors as personalized treatments, which would require comprehensive assessment of the biological mechanisms underlying tumor spread and chemoresistance in individual patients, and their connection to tumor genome and transcriptome to establish identifiable subgroups of patients who are most likely to benefit from a given therapy.

Laminins in tumor-derived exosomes upregulated by ETS1 reprogram omental macrophages to promote omental metastasis of ovarian cancer

Tumor-derived exosomes participate in omental metastatic colonization of ovarian cancer by inducing an adaptive response in the tumor microenvironment. However, cell-cell communication via exosomes between primary tumor cells and the microenvironment of distant omentum and the mechanism of pre-metastatic niche formation are poorly understood. Here, we demonstrated that ETS1-overexpressing ovarian cancer cells secreted larger exosomes with higher laminin levels. In addition, ovarian cancer exosomes could be taken up by omental macrophages through integrin and laminin interaction. Compared with control exosomes, exosomes derived from ETS1-overexpressing ovarian cancer cells (LV-ETS1 Exos) stimulated the polarization of more macrophages toward the M2 phenotype (CD163 marker), as well as the production of more CXCL5 and CCL2 in macrophages, via integrin αvβ5/AKT/Sp1 signaling. In vivo experiments showed that LV-ETS1 Exos promoted omental metastasis of ovarian cancer by mediating the tumor-promoting effect of macrophages, which could be neutralized by integrin ανβ5 inhibitor cilengitide. These results indicated that ETS1 could drive ovarian cancer cells to release exosomes with higher laminin levels, thereby accelerating the exosome-mediated pro-metastatic effects of omental macrophages via the integrin αvβ5/AKT/Sp1 signaling pathway, and the integrin ανβ5 inhibitor cilengitide could inhibit omental metastasis of ovarian cancer driven by tumor-derived exosomes.

Activation of innate-adaptive immune machinery by poly(I:C) exposes a therapeutic vulnerability to prevent relapse in stroma-rich colon cancer

OBJECTIVE

Stroma-rich tumours represent a poor prognostic subtype in stage II/III colon cancer (CC), with high relapse rates and limited response to standard adjuvant chemotherapy.

DESIGN

To address the lack of efficacious therapeutic options for patients with stroma-rich CC, we stratified our human tumour cohorts according to stromal content, enabling identification of the biology underpinning relapse and potential therapeutic vulnerabilities specifically within stroma-rich tumours that could be exploited clinically. Following human tumour-based discovery and independent clinical validation, we use a series of in vitro and stroma-rich in vivo models to test and validate the therapeutic potential of elevating the biology associated with reduced relapse in human tumours.

RESULTS

By performing our analyses specifically within the stroma-rich/high-fibroblast (HiFi) subtype of CC, we identify and validate the clinical value of a HiFi-specific prognostic signature (HPS), which stratifies tumours based on STAT1-related signalling (High-HPS v Low-HPS=HR 0.093, CI 0.019 to 0.466). Using in silico, in vitro and in vivo models, we demonstrate that the HPS is associated with antigen processing and presentation within discrete immune lineages in stroma-rich CC, downstream of double-stranded RNA and viral response signalling. Treatment with the TLR3 agonist poly(I:C) elevated the HPS signalling and antigen processing phenotype across in vitro and in vivo models. In an in vivo model of stroma-rich CC, poly(I:C) treatment significantly increased systemic cytotoxic T cell activity (p<0.05) and reduced liver metastases (p<0.0002).

CONCLUSION

This study reveals new biological insight that offers a novel therapeutic option to reduce relapse rates in patients with the worst prognosis CC.

Highlight: microfluidic devices for cancer metastasis studies

Whilst cancer is the single most researched disease by number of clinical trials, it remains a leading cause of death in middle- to high-income countries, with metastasis as the prime factor in cancer-associated mortality. The complex, multistep process of metastasis, in which cancer cells disseminate from the primary tumour and home to distant sites, is modulated by an extensive set of factors such as matrix properties, cancer cell plasticity, intercellular communication and oxygen tension. However, traditional treatment approaches have been focussed on the removal of the primary and secondary lesions, rather than interference with the metastatic cascade. Microfluidic platforms enable the deconvolution of the processes involved in metastasis by recapitulating key aspects of the tumour microenvironment in a controlled and reproducible fashion. Herein, we review recent developments in microfluidics for metastasis research and explain how these devices offer exceptional potential towards gaining a deeper understanding of this key aspect of malignancy.

Radiotherapy induced immunogenic cell death by remodeling tumor immune microenvironment

Emerging evidence indicates that the induction of radiotherapy(RT) on the immunogenic cell death (ICD) is not only dependent on its direct cytotoxic effect, changes in the tumor immune microenvironment also play an important role in it. Tumor immune microenvironment (TIME) refers to the immune microenvironment that tumor cells exist, including tumor cells, inflammatory cells, immune cells, various signaling molecules and extracellular matrix. TIME has a barrier effect on the anti-tumor function of immune cells, which can inhibit all stages of anti-tumor immune response. The remodeling of TIME caused by RT may affect the degree of immunogenicity, and make it change from immunosuppressive phenotype to immunostimulatory phenotype. It is of great significance to reveal the causes of immune escape of tumor cells, especially for the treatment of drug-resistant tumor. In this review, we focus on the effect of RT on the TIME, the mechanism of RT in reversing the TIME to suppress intrinsic immunity, and the sensitization effect of the remodeling of TIME caused by RT on the effectiveness of immunotherapy.

Dynamic Changes in the Extracellular Matrix in Primary, Metastatic, and Recurrent Ovarian Cancers

Cancer-associated fibroblasts (CAFs) and their extracellular matrix are active participants in cancer progression. While it is known that functionally different subpopulations of CAFs co-exist in ovarian cancer, it is unclear whether certain CAF subsets are enriched during metastatic progression and/or chemotherapy. Using computational image analyses of patient-matched primary high-grade serous ovarian carcinomas, synchronous pre-chemotherapy metastases, and metachronous post-chemotherapy metastases from 42 patients, we documented the dynamic spatiotemporal changes in the extracellular matrix, fibroblasts, epithelial cells, immune cells, and CAF subsets expressing different extracellular matrix components. Among the different CAF subsets, COL11A1+ CAFs were associated with linearized collagen fibers and exhibited the greatest enrichment in pre- and post-chemotherapy metastases compared to matched primary tumors. Although pre- and post-chemotherapy metastases were associated with increased CD8+ T cell infiltration, the infiltrate was not always evenly distributed between the stroma and cancer cells, leading to an increased frequency of the immune-excluded phenotype where the majority of CD8+ T cells are present in the tumor stroma but absent from the tumor parenchyma. Overall, most of the differences in the tumor microenvironment were observed between primary tumors and metastases, while fewer differences were observed between pre- and post-treatment metastases. These data suggest that the tumor microenvironment is largely determined by the primary vs. metastatic location of the tumor while chemotherapy does not have a significant impact on the host microenvironment.

MatrisomeDB 2.0: 2023 updates to the ECM-protein knowledge database

The extracellular matrix (ECM) is a complex assembly of proteins that constitutes the scaffold organizing cells, tissues, and organs. Over the past decade, mass-spectrometry-based proteomics has become the method of choice to profile the composition of the ECM, or the matrisome, of tissues. To assist non-specialists with the reuse of ECM proteomic datasets, we released MatrisomeDB (https://matrisomedb.org) in 2020. Here, we report the expansion of the database to include 25 new curated studies on the ECM of 24 new tissues in addition to datasets on tissues previously included, more than doubling the size of the original database and achieving near-complete coverage of the in-silico predicted matrisome. We further enhanced data visualization by maps of peptides and post-translational-modifications detected onto domain-based representations and 3D structures of ECM proteins. We also referenced external resources to facilitate the design of targeted mass spectrometry assays. Last, we implemented an abstract-mining tool that generates an enrichment word cloud from abstracts of studies in which a queried protein is found with higher confidence and higher abundance relative to other studies in MatrisomeDB.

The Development of a Three-Dimensional Platform for Patient-Derived Ovarian Cancer Tissue Models: A Systematic Literature Review

There is an unmet biomedical need for ex vivo tumour models that would predict drug responses and in turn help determine treatment regimens and potentially predict resistance before clinical studies. Research has shown that three dimensional models of ovarian cancer (OvCa) are more realistic than two dimensional in vitro systems as they are able to capture patient in vivo conditions in more accurate manner. The vast majority of studies aiming to recapitulate the ovarian tumour morphology, behaviors, and study chemotherapy responses have been using ovarian cancer cell lines. However, despite the advantages of utilising cancer cell lines to set up a platform, they are not as informative as systems applying patient derived cells, as cell lines are not able to recapitulate differences between each individual patient characteristics. In this review we discussed the most recent advances in the creation of 3D ovarian cancer models that have used patient derived material, the challenges to overcome and future applications.

Molecular, cellular and systemic aspects of epithelial ovarian cancer and its tumor microenvironment

Ovarian cancer encompasses a heterogeneous group of malignancies that involve the ovaries, fallopian tubes and the peritoneal cavity. Despite major advances made within the field of cancer, the majority of patients with ovarian cancer are still being diagnosed at an advanced stage of the disease due to lack of effective screening tools. The overall survival of these patients has, therefore, not substantially improved over the past decades. Most patients undergo debulking surgery and treatment with chemotherapy, but often micrometastases remain and acquire resistance to the therapy, eventually leading to disease recurrence. Here, we summarize the current knowledge in epithelial ovarian cancer development and metastatic progression. For the most common subtypes, we focus further on the properties and functions of the immunosuppressive tumor microenvironment, including the extracellular matrix. Current and future treatment modalities are discussed and finally we provide an overview of the different experimental models used to develop novel therapies.

COL11A1 as an novel biomarker for breast cancer with machine learning and immunohistochemistry validation

Machine learning (ML) algorithms were used to identify a novel biological target for breast cancer and explored its relationship with the tumor microenvironment (TME) and patient prognosis. The edgR package identified hub genes associated with overall survival (OS) and prognosis, which were validated using public datasets. Of 149 up-regulated genes identified in tumor tissues, three ML algorithms identified COL11A1 as a hub gene. COL11A1was highly expressed in breast cancer samples and associated with a poor prognosis, and positively correlated with a stromal score (r=0.49, p<0.001) and the ESTIMATE score (r=0.29, p<0.001) in the TME. Furthermore, COL11A1 negatively correlated with B cells, CD4 and CD8 cells, but positively associated with cancer-associated fibroblasts. Forty-three related immune-regulation genes associated with COL11A1 were identified, and a five-gene immune regulation signature was built. Compared with clinical factors, this gene signature was an independent risk factor for prognosis (HR=2.591, 95%CI 1.831-3.668, p=7.7e-08). A nomogram combining the gene signature with clinical variables, showed better predictive performance (C-index=0.776). The model correction prediction curve showed little bias from the ideal curve. COL11A1 is a potential therapeutic target in breast cancer and may be involved in the tumor immune infiltration; its high expression is strongly associated with poor prognosis.

A novel cell line panel reveals non-genetic mediators of platinum resistance and phenotypic diversity in high grade serous ovarian cancer

OBJECTIVES

Resistance to cancer therapy is an enduring challenge and accurate and reliable preclinical models are lacking. We interrogated this unmet need using high grade serous ovarian cancer (HGSC) as a disease model.

METHODS

We created five in vitro and two in vivo platinum-resistant HGSC models and characterised the entire cell panel via whole genome sequencing, RNASeq and creation of intraperitoneal models.

RESULTS

Mutational signature analysis indicated that platinum-resistant cell lines evolved from a pre-existing ancestral clone but a unifying mutational cause for drug resistance was not identified. However, cisplatin-resistant and carboplatin-resistant cells evolved recurrent changes in gene expression that significantly overlapped with independent samples obtained from multiple patients with relapsed HGSC. Gene Ontology Biological Pathways (GOBP) related to the tumour microenvironment, particularly the extracellular matrix, were repeatedly enriched in cisplatin-resistant cells, carboplatin-resistant cells and also in human resistant/refractory samples. The majority of significantly over-represented GOBP however, evolved uniquely in either cisplatin- or carboplatin-resistant cell lines resulting in diverse intraperitoneal behaviours that reflect different clinical manifestations of relapsed human HGSC.

CONCLUSIONS

Our clinically relevant and usable models reveal a key role for non-genetic factors in the evolution of chemotherapy resistance. Biological pathways relevant to the extracellular matrix were repeatedly expressed by resistant cancer cells in multiple settings. This suggests that recurrent gene expression changes provide a fitness advantage during platinum therapy and also that cancer cell-intrinsic mechanisms influence the tumour microenvironment during the evolution of drug resistance. Candidate genes and pathways identified here could reveal therapeutic opportunities in platinum-resistant HGSC.

Cancer Stem Cells and the Tumor Microenvironment: Targeting the Critical Crosstalk through Nanocarrier Systems

The physiological state of the tumor microenvironment (TME) plays a central role in cancer development due to multiple universal features that transcend heterogeneity and niche specifications, like promoting cancer progression and metastasis. As a result of their preponderant involvement in tumor growth and maintenance through several microsystemic alterations, including hypoxia, oxidative stress, and acidosis, TMEs make for ideal targets in both diagnostic and therapeutic ventures. Correspondingly, methodologies to target TMEs have been investigated this past decade as stratagems of significant potential in the genre of focused cancer treatment. Within targeted oncotherapy, nanomedical derivates-nanocarriers (NCs) especially-have emerged to present notable prospects in enhancing targeting specificity. Yet, one major issue in the application of NCs in microenvironmental directed therapy is that TMEs are too broad a spectrum of targeting possibilities for these carriers to be effectively employed. However, cancer stem cells (CSCs) might portend a solution to the above conundrum: aside from being quite heavily invested in tumorigenesis and therapeutic resistance, CSCs also show self-renewal and fluid clonogenic properties that often define specific TME niches. Further scrutiny of the relationship between CSCs and TMEs also points towards mechanisms that underly tumoral characteristics of metastasis, malignancy, and even resistance. This review summarizes recent advances in NC-enabled targeting of CSCs for more holistic strikes against TMEs and discusses both the current challenges that hinder the clinical application of these strategies as well as the avenues that can further CSC-targeting initiatives. Central role of CSCs in regulation of cellular components within the TME.

Mechanical Confinement and DDR1 Signaling Synergize to Regulate Collagen-Induced Apoptosis in Rhabdomyosarcoma Cells

Fibrillar collagens promote cell proliferation, migration, and survival in various epithelial cancers and are generally associated with tumor aggressiveness. However, the impact of fibrillar collagens on soft tissue sarcoma behavior remains poorly understood. Unexpectedly, this study finds that fibrillar collagen-related gene expression is associated with favorable patient prognosis in rhabdomyosarcoma. By developing and using collagen matrices with distinct stiffness and in vivo-like microarchitectures, this study uncovers that the activation of DDR1 has pro-apoptotic and of integrin β1 pro-survival function, specifically in 3D rhabdomyosarcoma cell cultures. It demonstrates that rhabdomyosarcoma cell-intrinsic or extrinsic matrix remodeling promotes cell survival. Mechanistically, the 3D-specific collagen-induced apoptosis results from a dual DDR1-independent and a synergistic DDR1-dependent TRPV4-mediated response to mechanical confinement. Altogether, these results indicate that dense microfibrillar collagen-rich microenvironments are detrimental to rhabdomyosarcoma cells through an apoptotic response orchestrated by the induction of DDR1 signaling and mechanical confinement. This mechanism helps to explain the preference of rhabdomyosarcoma cells to grow in and metastasize to low fibrillar collagen microenvironments such as the lung.

Matrix proteoglycans in tumor inflammation and immunity

Cancer immunoediting progresses through elimination, equilibrium, and escape. Each of these phases is characterized by breaching, remodeling, and rebuilding tissue planes and structural barriers that engage extracellular matrix (ECM) components, in particular matrix proteoglycans. Some of the signals emanating from matrix proteoglycan remodeling are readily co-opted by the growing tumor to sustain an environment of tumor-promoting and immune-suppressive inflammation. Yet other matrix-derived cues can be viewed as part of a homeostatic response by the host, aiming to eliminate the tumor and restore tissue integrity. These latter signals may be harnessed for therapeutic purposes to tip the polarity of the tumor immune milieu toward anticancer immunity. In this review, we attempt to showcase the importance and complexity of matrix proteoglycan signaling in both cancer-restraining and cancer-promoting inflammation. We propose that the era of matrix diagnostics and therapeutics for cancer is fast approaching the clinic.

Decellularized organ biomatrices facilitate quantifiable in vitro 3D cancer metastasis models

Metastatic cancers are chemoresistant, involving complex interplay between disseminated cancer cell aggregates and the distant organ microenvironment (extracellular matrix and stromal cells). Conventional metastasis surrogates (scratch/wound healing, Transwell migration assays) lack 3D architecture and ECM presence. Metastasis studies can therefore significantly benefit from biomimetic 3D in vitro models recapitulating the complex cascade of distant organ invasion and colonization by collective clusters of cells. We aimed to engineer reproducible and quantifiable 3D models of highly therapy-resistant cancer processes: (i) colorectal cancer liver metastasis; and (ii) breast cancer lung metastasis. Metastatic seeds are engineered using 3D tumor spheroids to recapitulate the 3D aggregation of cancer cells both in the tumor and in circulation throughout the metastatic cascade of many cancers. Metastatic soil was engineered by decellularizing porcine livers and lungs to generate biomatrix scaffolds, followed by extensive materials characterization. HCT116 colorectal and MDA-MB-231 breast cancer spheroids were generated on hanging drop arrays to initiate clustered metastatic seeding into liver and lung biomatrix scaffolds, respectively. Between days 3-7, biomatrix cellular colonization was apparent with increased metabolic activity and the presence of cellular nests evaluated via multiphoton microscopy. HCT116 and MDA-MB-231 cells colonized liver and lung biomatrices, and at least 15% of the cells invaded more than 20 μm from the surface. Engineered metastases also expressed increased signatures of genes associated with the metastatic epithelial to mesenchymal transition (EMT). Importantly, inhibition of matrix metalloproteinase-9 inhibited metastatic invasion into the biomatrix. Furthermore, metastatic nests were significantly more chemoresistant (>3 times) to the anti-cancer drug oxaliplatin, compared to 3D spheroids. Together, our data indicated that HCT116 and MDA-MB-231 spheroids invade, colonize, and proliferate in livers and lungs establishing metastatic nests in 3D settings in vitro. The metastatic nature of these cells was confirmed with functional readouts regarding EMT and chemoresistance. Modeling the dynamic metastatic cascade in vitro has potential to identify therapeutic targets to treat or prevent metastatic progression in chemoresistant metastatic cancers.

Downregulation of LEMD1-AS1 and Its Influences on the Diagnosis, Prognosis, and Immune Infiltrates of Epithelial Ovarian Cancer

Previous studies have confirmed long noncoding RNA LEMD1-AS1 (LEMD1-AS1) as a functional factor in several tumors. The present work is aimed at exploring the prognostic and diagnostic values of LEMD1-AS1 in patients with epithelial ovarian cancer (EOC). We examined the expressions of LEMD1-AS1 in pan-cancer from TCGA microarray datasets and GTEx Project. The expressions of LEMD1-AS1 were detected by qRT-PCR in EOC specimens and normal ovarian specimens from 30 EOC patients. The χ² test was applied to compare the clinicopathological characteristics of different groups. ROC curves were established to determine the diagnostic values of LEMD1-AS1 in screening EOC tissues. The association of LEMD1-AS1 expression with clinical outcome was determined by the Kaplan-Meier methods and COX assays. A decreased expression of LEMD1-AS1 was observed in EOC tissues compared to matched normal specimens (p < 0.01). Low LEMD1-AS1 expression could be used to distinguish EOC from adjacent normal specimens. A clinical study revealed that patients with low LEMD1-AS1 expression have a shorter overall survival (p = 0.035) and progress-free interval (p = 0.041) than those with high LEMD1-AS1 expression. The Spearman correlation test revealed that LEMD1-AS1 expressions were negatively associated with the expressions of neutrophil and myeloid dendritic cell. Overall, our finding suggested that LEMD1-AS1 may have potential roles as a potential biomarker and/or a therapeutic target in EOC.

Proceedings from the Blood and Marrow Transplant Clinical Trials Network Myeloma Intergroup Workshop on Immune and Cellular Therapy in Multiple Myeloma

The Blood and Marrow Transplant Clinical Trials Network (BMT CTN) Myeloma Intergroup conducted a workshop on Immune and Cellular Therapy in Multiple Myeloma on January 7, 2022. This workshop included presentations by basic, translational, and clinical researchers with expertise in plasma cell dyscrasias. Four main topics were discussed: platforms for myeloma disease evaluation, insights into pathophysiology, therapeutic target and resistance mechanisms, and cellular therapy for multiple myeloma. Here we provide a comprehensive summary of these workshop presentations.

CMTM6 and CMTM4 as two novel regulators of PD-L1 modulate the tumor microenvironment

The tumor microenvironment (TME) plays crucial roles in regulating tumor occurrence, progress, metastasis and drug resistance. However, it remains largely elusive how the components of TME are regulated to govern its functions in tumor biology. Here, we discussed how the two novel functional proteins, chemokine-like factor (CKLF)-like MARVEL transmembrane domain-containing 6 (CMTM6) and CMTM4, which involved in the post-translational regulation of PD-L1, modulate the TME functions. The roles of CMTM6 and CMTM4 in regulating TME components, including immune cells and tumor cells themselves were discussed in this review. The potential clinical applications of CMTM6 and CMTM4 as biomarkers to predict therapy efficacy and as new or combined immunotherapy targets are also highlighted. Finally, the current hot topics for the biological function of CMTM6/4 and several significant research directions for CMTM6/4 are also briefly summarized in the review.

Collagen XI Alpha 1 Chain, a Novel Therapeutic Target for Cancer Treatment

The extracellular matrix (ECM) plays an important role in the progression of cancer. Collagen is the most abundant component in ECM, and is involved in the biological formation of cancer. Although type XI collagen is a minor fibrillar collagen, collagen XI alpha 1 chain (COL11A1) expression has been found to be upregulated in a variety of human cancers including colorectal, esophagus, glioma, gastric, head and neck, lung, ovarian, pancreatic, salivary gland, and renal cancers. High levels of COL11A1 usually predict poor prognosis, owing to its association with angiogenesis, invasion, and drug resistance in cancer. However, little is known about the specific mechanism through which COL11A1 regulates tumor progression. Here, we have organized and summarized recent developments regarding the interactions between COL11A1 and intracellular signaling pathways and selected therapeutic agents targeting COL11A1, as these indicate its potential as a target for treatment of cancers, especially epithelial ovarian cancer.

Injectable three-dimensional tumor microenvironments to study mechanobiology in ovarian cancer

Epithelial ovarian cancers are among the most aggressive forms of gynecological malignancies. Despite the advent of poly adenosine diphosphate-ribose polymerase (PARP) and checkpoint inhibitors, improvement to patient survival has been modest. Limited in part by clinical translation, beneficial therapeutic strategies remain elusive in ovarian cancers. Although elevated levels of extracellular proteins, including collagens, proteoglycans, and glycoproteins, have been linked to chemoresistance, they are often missing from the processes of drug- development and screening. Biophysical and biochemical signaling from the extracellular matrix (ECM) determine cellular phenotype and affect both tumor progression and therapeutic response. However, many state-of-the-art tumor models fail to mimic the complexities of the tumor microenvironment (TME) and omit key signaling components. In this article, two interpenetrating network (IPN) hydrogel scaffold platforms, comprising of alginate-collagen or agarose-collagen, have been characterized for use as 3D in vitro models of epithelial ovarian cancer ECM. These highly tunable, injection mold compatible, and inexpensive IPNs replicate the critical governing physical and chemical signaling present within the ovarian TME. Additionally, an effective and cell-friendly live-cell retrieval method has been established to recover cells post-encapsulation. Lastly, functional mechanotransduction in ovarian cancers was demonstrated by increasing scaffold stiffness within the 3D in vitro ECM models. With these features, the agarose-collagen and alginate-collagen hydrogels provide a robust TME for the study of mechanobiology in epithelial cancers. STATEMENT OF SIGNIFICANCE: Ovarian cancer is the most lethal gynecologic cancer afflicting women today. Here we present the development, characterization, and validation of 3D interpenetrating platforms to shift the paradigm in standard in vitro modeling. These models help elucidate the roles of biophysical and biochemical cues in ovarian cancer progression. The agarose-collagen and alginate-collagen interpenetrating network (IPN) hydrogels are simple to fabricate, inexpensive, and can be modified to create custom mechanical stiffnesses and concentrations of bio-adhesive motifs. Given that investigations into the roles of biophysical characteristics in ovarian cancers have provided incongruent results, we believe that the IPN platforms will be critically important to uncovering molecular drivers. We also expect these platforms to be broadly applicable to studies involving mechanobiology in solid tumors.

Physiologically Based Pharmacokinetic (PBPK) Modeling to Predict PET Image Quality of Three Generations EGFR TKI in Advanced-Stage NSCLC Patients

Introduction: Epidermal growth factor receptor (EGFR) mutated NSCLC is best treated using an EGFR tyrosine kinase inhibitor (TKI). The presence and accessibility of EGFR overexpression and mutation in NSCLC can be determined using radiolabeled EGFR TKI PET/CT. However, recent research has shown a significant difference between image qualities (i.e., tumor-to-lung contrast) in three generation EGFR TKIs: ¹¹C-erlotinib, ¹⁸F-afatinib and ¹¹C-osimertinib. In this research we aim to develop a physiological pharmacokinetic (PBPK)-model to predict tumor-to-lung contrast and as a secondary outcome the uptake of healthy tissue of the three tracers. Methods: Relevant physicochemical and drug specific properties (e.g., pKa, lipophilicity, target binding) for each TKI were collected and applied in established base PBPK models. Key hallmarks of NSCLC include: immune tumor deprivation, unaltered tumor perfusion and an acidic tumor environment. Model accuracy was demonstrated by calculating the prediction error (PE) between predicted tissue-to-blood ratios (TBR) and measured PET-image-derived TBR. Sensitivity analysis was performed by excluding each key component and comparing the PE with the final mechanistical PBPK model predictions. Results: The developed PBPK models were able to predict tumor-to-lung contrast for all EGFR-TKIs within threefold of observed PET image ratios (PE tumor-to-lung ratio of −90%, +44% and −6.3% for erlotinib, afatinib and osimertinib, respectively). Furthermore, the models depicted agreeable whole-body distribution, showing high tissue distribution for osimertinib and afatinib and low tissue distribution at high blood concentrations for erlotinib (mean PE, of −10.5%, range −158%–+190%, for all tissues). Conclusion: The developed PBPK models adequately predicted the image quality of afatinib and osimertinib and erlotinib. Some deviations in predicted whole-body TBR lead to new hypotheses, such as increased affinity for mutated EGFR and active influx transport (erlotinib into excreting tissues) or active efflux (afatinib from brain), which is currently unaccounted for. In the future, PBPK models may be used to predict the image quality of new tracers.

Another Wrinkle with Age: Aged Collagen and Intra-peritoneal Metastasis of Ovarian Cancer

Background

Age is the most significant risk factor for ovarian cancer (OvCa), the deadliest gynecologic malignancy. Metastasizing OvCa cells adhere to the omentum, a peritoneal structure rich in collagen, adipocytes, and immune cells. Ultrastructural changes in the omentum and the omental collagen matrix with aging have not been evaluated.

Aim

The aim of this study was to test the hypothesis that age-related changes in collagen in the ovarian tumor microenvironment promote OvCa metastatic success in the aged host.

Methods/Results

Young (3-6 months) and aged mice (20-23 months) were used to study the role of aging in metastatic success. Intra-peritoneal (IP) injection of ID8Trp53 ^-/- ovarian cancer cells showed enhanced IP dissemination in aged vs young mice. In vitro assays using purified collagen demonstrated reduced collagenolysis of aged fibers, as visualized using scanning electron microscopy (SEM) and quantified with a hydroxyproline release assay. Omental tumors in young and aged mice showed similar collagen deposition; however enhanced intra-tumoral collagen remodeling was seen in aged mice probed with a biotinylated collagen hybridizing peptide (CHP). In contrast, second harmonic generation (SHG) microscopy showed significant differences in collagen fiber structure and organization in omental tissue and SEM demonstrated enhanced omental fenestration in aged omenta. Combined SHG and Alexa Fluor-CHP microscopy in vivo demonstrated that peri-tumoral collagen was remodeled more extensively in young mice. This collagen population represents truly aged host collagen, in contrast to intra-tumoral collagen that is newly synthesized, likely by cancer associated fibroblasts (CAFs).

Conclusions

Our results demonstrate that tumors in an aged host can grow with minimal collagen remodeling, while tumors in the young host must remodel peri-tumoral collagen to enable effective proliferation, providing a mechanism whereby age-induced ultrastructural changes in collagen and collagen-rich omenta establish a permissive pre-metastatic niche contributing to enhanced OvCa metastatic success in the aged host.

Mutually Exclusive Expression of COL11A1 by CAFs and Tumour Cells in a Large panCancer and a Salivary Gland Carcinoma Cohort

Procollagen 11A1 (COL11A1) is a central component of the extracellular matrix in many carcinomas, which is considered to be mainly produced by cancer associated fibroblasts (CAFs). As COL11A1 expression correlates with adverse prognosis and is implicated in chemoresistance, it is a promising putative target. For the first time, we used RNA in-situ hybridization to systematically identify the cells that produce COL11A1 in the ten most prevalent carcinoma types, lymphomas (n = 275) and corresponding normal tissue (n = 55; panCancer cohort). Moreover, as most salivary gland carcinomas (SGC) display distinct stromal architectures, we also analysed 110 SGC. The corresponding protein formation of COL11A1 was determined by MALDI-TOF-MS-Imaging. We report that colon, breast and salivary duct carcinomas are highly infiltrated by COL11A1 positive CAFs (CAFs_COL11A1) and might thus be promising candidates for antidesmoplastic or COL11A1-targeted therapies. The amount of CAFs_COL11A1 correlated significantly with tumour grade, tumour stage and nodal spread in the panCancer cohort. Significant associations between CAFs_COL11A1 and vascular invasion, perineural spread and nodal spread were observed in the SGC cohort. Also, we discovered that tumour cells of intercalated duct derived SGC and CAFs produce COL11A1 in a mutually exclusive manner. Our findings represent a novel mode of extracellular matrix production in carcinomas and could be highly relevant in the future. Our findings elucidate the mode of COL11A1 expression in very different carcinoma types and may aid to categorise tumours in the setting of possible future COL11A1-related therapies.

Biophysics Role and Biomimetic Culture Systems of ECM Stiffness in Cancer EMT

Oncological diseases have become the second leading cause of death from noncommunicable diseases worldwide and a major threat to human health. With the continuous progress in cancer research, the mechanical cues from the tumor microenvironment environment (TME) have been found to play an irreplaceable role in the progression of many cancers. As the main extracellular mechanical signal carrier, extracellular matrix (ECM) stiffness may influence cancer progression through biomechanical transduction to modify downstream gene expression, promote epithelial-mesenchymal transition (EMT), and regulate the stemness of cancer cells. EMT is an important mechanism that induces cancer cell metastasis and is closely influenced by ECM stiffness, either independently or in conjunction with other molecules. In this review, the unique role of ECM stiffness in EMT in different kinds of cancers is first summarized. By continually examining the significance of ECM stiffness in cancer progression, a biomimetic culture system based on 3D manufacturing and novel material technologies is developed to mimic ECM stiffness. The authors then look back on the novel development of the ECM stiffness biomimetic culture systems and finally provide new insights into ECM stiffness in cancer progression which can broaden the fields' horizons with a view toward developing new cancer diagnosis methods and therapies.

Immune Mechanisms of Resistance to Cediranib in Ovarian Cancer

This article investigates mechanisms of resistance to the VEGF receptor inhibitor cediranib in high-grade serous ovarian cancer (HGSOC), and defines rational combination therapies. We used three different syngeneic orthotopic mouse HGSOC models that replicated the human tumor microenvironment (TME). After 4 to 5 weeks treatment of established tumors, cediranib had antitumor activity with increased tumor T-cell infiltrates and alterations in myeloid cells. However, continued cediranib treatment did not change overall survival or the immune microenvironment in two of the three models. Moreover, treated mice developed additional peritoneal metastases not seen in controls. Cediranib-resistant tumors had intrinsically high levels of IL6 and JAK/STAT signaling and treatment increased endothelial STAT3 activation. Combination of cediranib with a murine anti-IL6 antibody was superior to monotherapy, increasing mouse survival, reducing blood vessel density, and pSTAT3, with increased T-cell infiltrates in both models. In a third HGSOC model, that had lower inherent IL6 JAK/STAT3 signaling in the TME but high programmed cell death protein 1 (PD-1) signaling, long-term cediranib treatment significantly increased overall survival. When the mice eventually relapsed, pSTAT3 was still reduced in the tumors but there were high levels of immune cell PD-1 and Programmed death-ligand 1. Combining cediranib with an anti-PD-1 antibody was superior to monotherapy in this model, increasing T cells and decreasing blood vessel densities. Bioinformatics analysis of two human HGSOC transcriptional datasets revealed distinct clusters of tumors with IL6 and PD-1 pathway expression patterns that replicated the mouse tumors. Combination of anti-IL6 or anti-PD-1 in these patients may increase activity of VEGFR inhibitors and prolong disease-free survival.

Cancer-associated fibroblasts require proline synthesis by PYCR1 for the deposition of pro-tumorigenic extracellular matrix

Elevated production of collagen-rich extracellular matrix is a hallmark of cancer-associated fibroblasts (CAFs) and a central driver of cancer aggressiveness. Here we find that proline, a highly abundant amino acid in collagen proteins, is newly synthesized from glutamine in CAFs to make tumour collagen in breast cancer xenografts. PYCR1 is a key enzyme for proline synthesis and highly expressed in the stroma of breast cancer patients and in CAFs. Reducing PYCR1 levels in CAFs is sufficient to reduce tumour collagen production, tumour growth and metastatic spread in vivo and cancer cell proliferation in vitro. Both collagen and glutamine-derived proline synthesis in CAFs are epigenetically upregulated by increased pyruvate dehydrogenase-derived acetyl-CoA levels. PYCR1 is a cancer cell vulnerability and potential target for therapy; therefore, our work provides evidence that targeting PYCR1 may have the additional benefit of halting the production of a pro-tumorigenic extracellular matrix. Our work unveils new roles for CAF metabolism to support pro-tumorigenic collagen production.

Deep learning identification of stiffness markers in breast cancer

While essential to our understanding of solid tumor progression, the study of cell and tissue mechanics has yet to find traction in the clinic. Determining tissue stiffness, a mechanical property known to promote a malignant phenotype in vitro and in vivo, is not part of the standard algorithm for the diagnosis and treatment of breast cancer. Instead, clinicians routinely use mammograms to identify malignant lesions and radiographically dense breast tissue is associated with an increased risk of developing cancer. Whether breast density is related to tumor tissue stiffness, and what cellular and non-cellular components of the tumor contribute the most to its stiffness are not well understood. Through training of a deep learning network and mechanical measurements of fresh patient tissue, we create a bridge in understanding between clinical and mechanical markers. The automatic identification of cellular and extracellular features from hematoxylin and eosin (H&E)-stained slides reveals that global and local breast tissue stiffness best correlate with the percentage of straight collagen. Importantly, the percentage of dense breast tissue does not directly correlate with tissue stiffness or straight collagen content.

The Aging-Related Prognostic Signature Reveals the Landscape of the Tumor Immune Microenvironment in Head and Neck Squamous Cell Carcinoma

Background

Numerous studies have shown that the aging microenvironment played a huge impact on tumor progression. However, the clinical prognostic value of aging-related risk signatures and their effects on the tumor immune microenvironment (TIME) in head and neck squamous cell carcinoma (HNSCC) remains largely unclear. This study aimed to identify novel prognostic signatures based on aging-related genes (AGs) and reveal the landscape of the TIME in HNSCC.

Methods

Differentially expressed AGs were identified using the gene set enrichment analysis (GSEA). The prognostic risk model of AGs was established by univariate and multivariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses. The independent prognostic value of the risk model and the correlations of the prognostic signature with immune score, tumor immune cell infiltration, and immune checkpoints were systematically analyzed.

Results

A prognostic risk model of four AGs (BAK1, DKK1, CDKN2A, and MIF) was constructed and validated in the training and testing datasets. Kaplan–Meier curves and time-dependent receiver operating characteristic (ROC) curve analysis confirmed that the four-AG risk signature possessed an accurate predictive value for the prognosis of patients with HNSCC. Correlation analysis revealed that the risk score was negatively associated with immune score and immune cell infiltration level while positively correlated with immune checkpoint blockade (ICB) response score. Patients of the high-risk subtype contained higher infiltration levels of resting natural killer (NK) cells, M0 macrophages, M2 macrophages, and resting mast cells while having lower infiltration levels of memory B cells, CD8+ T cells, follicular helper T cells, regulatory T cells (Tregs), and activated mast cells than did those of the low-risk subtype. The expressions of CTLA4, PDCD1, and TIGIT were downregulated while the PDCD1LG2 expression was upregulated in the high-risk subtype compared to those in the low-risk subtype. Furthermore, the four selected AGs in the risk model were demonstrated to possess important functions in immune cell infiltration and ICB response of HNSCC.

Conclusions

The aging-related risk signature is a reliable prognostic model for predicting the survival of HNSCC patients and provides potential targets for improving outcomes of immunotherapy.