A single-cell landscape of high-grade serous ovarian cancer

Development of a prognostic immune cell-based model for ovarian cancer using multiplex immunofluorescence

BACKGROUND

Ovarian cancer is the most lethal gynecological malignancy, often diagnosed at advanced stages with poor prognosis. The tumor microenvironment (TME) plays a critical role in disease progression and treatment response. This study aimed to construct a prognostic model for ovarian cancer patients by evaluating the tumor immune landscape using multiplex immunofluorescence (mIF) staining, which focused on the spatial distribution and interactions of immune cells within the TME.

METHODS

Formalin-fixed paraffin-embedded (FFPE) tissues from 129 ovarian cancer patients were analyzed using mIF to assess the expression of PD-L1(Programmed death-ligand 1, PD-L1), CD8(Cluster of Differentiation 8, CD8), TOX (Thymocyte Selection-Associated HMG Box, TOX), CD68(Cluster of Differentiation 68, CD68), and CK (Cytokeratin, CK). The Vectra Polaris quantitative pathology imaging system and Inform software were employed for image and spatial analysis. The LASSO Cox regression model was used for feature selection, and Kaplan-Meier survival analysis was performed to evaluate the prognostic significance of immune cell markers. A nomogram was developed to predict overall survival (OS) based on clinical parameters and the Immune Cell Related Prognostic Index (ICRPI).

RESULTS

High percentages of CD8 + T cells, CD68 + macrophages, and CD68 + PD-L1 + macrophages were significantly associated with poor OS. Moreover, a high percentage of CD8 + T cells, CD68 + macrophages was significantly associated with poor disease-free survival (DFS). Spatial analysis revealed that a higher average count of CD68 + PD-L1 + macrophages within 30 μm of CD8 + T cells correlated with worse prognosis. The ICRPI model, incorporating CD68+, CD68 + PD-L1+, and spatial variables, effectively stratified patients into high- and low-risk groups, with high-risk patients showing significantly poorer OS.

CONCLUSION

This study highlights the prognostic value of immune cell spatial distribution in ovarian cancer. The ICRPI model, integrating immune cell markers and spatial analysis, provides a novel framework for predicting patient outcomes. Further validation in prospective studies is warranted to confirm the clinical utility of this model.

The fibroinflammatory response in cancer

Fibroinflammation refers to the highly integrated fibrogenic and inflammatory responses mediated by the concerted function of fibroblasts and innate immune cells in response to tissue perturbation. This process underlies the desmoplastic remodelling of the tumour microenvironment and thus plays an important role in tumour initiation, growth and metastasis. More specifically, fibroinflammation alters the biochemical and biomechanical signalling in malignant cells to promote their proliferation and survival and further supports an immunosuppressive microenvironment by polarizing the immune status of tumours. Additionally, the presence of fibroinflammation is often associated with therapeutic resistance. As such, there is increasing interest in targeting this process to normalize the tumour microenvironment and thus enhance the treatment of solid tumours. Herein, we review advances made in unravelling the complexity of cancer-associated fibroinflammation that can inform the rational design of therapies targeting this.

Role of tumor microenvironment in ovarian cancer metastasis and clinical advancements

Ovarian cancer (OC) is the most lethal gynecological malignancy worldwide, characterized by heterogeneity at the molecular, cellular and anatomical levels. Most patients are diagnosed at an advanced stage, characterized by widespread peritoneal metastasis. Despite optimal cytoreductive surgery and platinum-based chemotherapy, peritoneal spread and recurrence of OC are common, resulting in poor prognoses. The overall survival of patients with OC has not substantially improved over the past few decades, highlighting the urgent necessity of new treatment options. Unlike the classical lymphatic and hematogenous metastasis observed in other malignancies, OC primarily metastasizes through widespread peritoneal seeding. Tumor cells (the "seeds") exhibit specific affinities for certain organ microenvironments (the "soil"), and metastatic foci can only form when there is compatibility between the "seeds" and "soil." Recent studies have highlighted the tumor microenvironment (TME) as a critical factor influencing the interactions between the "seeds" and "soil," with ascites and the local peritoneal microenvironment playing pivotal roles in the initiation and progression of OC. Prior to metastasis, the interplay among tumor cells, immunosuppressive cells, and stromal cells leads to the formation of an immunosuppressive pre-metastatic niche in specific sites. This includes characteristic alterations in tumor cells, recruitment and functional anomalies of immune cells, and dysregulation of stromal cell distribution and function. TME-mediated crosstalk between cancer and stromal cells drives tumor progression, therapy resistance, and metastasis. In this review, we summarize the current knowledge on the onset and metastatic progression of OC. We provide a comprehensive discussion of the characteristics and functions of TME related to OC metastasis, as well as its association with peritoneal spread. We also outline ongoing relevant clinical trials, aiming to offer new insights for identifying potential effective biomarkers and therapeutic targets in future clinical practice.

Uncovering key regulatory pathways and prognostic biomarkers in the tumor microenvironment of high-grade serous ovarian cancer through single-cell RNA sequencing and experimental validation

Background

High-grade serous ovarian cancer (HGSOC) is a leading cause of cancer-related deaths among women globally. This study aims to identify novel regulatory targets and signaling pathways that modulate the tumor microenvironment (TME) in HGSOC, focusing on the pleiotrophin (PTN) signaling pathway and syndecan 4 (SDC4) expression as potential biomarkers for prognosis.

Methods

Bioinformatics analysis was conducted on single-cell RNA sequencing (scRNA-seq) data (GSE146026) of HGSOC to investigate the TME. The data were subjected to unsupervised clustering to classify cell types within the TME, revealing eight distinct clusters representing various cell types. Cell-cell interactions were analyzed using the CellChat tool. Additionally, TCGA datasets were used to validate the expression of SDC4 and its association with clinical outcomes. The functional enrichment of differentially expressed genes (DEGs) between high and low SDC4 expression groups was performed to uncover associated pathways. Experimental validation was carried out using quantitative real-time PCR (qRT-PCR) and Western blotting on ovarian cancer cell lines (OVCAR3 and SKOV3).

Results

The unsupervised clustering analysis revealed eight major cell types: macrophages, fibroblasts, ovarian cancer cells, B cells, T cells, dendritic cells, and erythrocytes. CellChat analysis highlighted significant interactions between these cell types, suggesting a complex TME. Further exploration identified PTN signaling as a key regulator within the HGSOC TME. Validation using TCGA datasets revealed upregulation of SDC4 in ovarian cancer tissues, with high SDC4 expression correlating with shorter overall survival. DEGs between high and low SDC4 expression groups were linked to the PI3K-Akt and MAPK signaling pathways, cell junction organization, and focal adhesion. qRT-PCR validation confirmed a significant upregulation of SDC4 in OVCAR3 and SKOV3 ovarian cancer cell lines, with expression levels 3.8- to 4.2-fold higher than control cells (p<0.01), supporting the computational predictions.

Conclusion

This study highlights the PTN signaling pathway as a potential therapeutic target in HGSOC and identifies SDC4 as a prognostic biomarker for poor patient outcomes. Our findings offer new insights into the molecular mechanisms governing the TME of HGSOC, although further investigation is needed to fully elucidate the functional role of SDC4 in ovarian cancer progression.

Emerging clinical applications of single-cell RNA sequencing in oncology

Single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of complex tissues both in health and in disease. Over the past decade, scRNA-seq has been applied to tumour samples obtained from patients with cancer in hundreds of studies, thereby advancing the view that each tumour is a complex ecosystem and uncovering the diverse states of both cancer cells and the tumour microenvironment. Such studies have primarily investigated and provided insights into the basic biology of cancer, although considerable research interest exists in leveraging these findings towards clinical applications. In this Review, we summarize the available data from scRNA-seq studies investigating samples from patients with cancer with a particular focus on findings that are of potential clinical relevance. We highlight four main research objectives of scRNA-seq studies and describe some of the most relevant findings towards such goals. We also describe the limitations of scRNA-seq, as well as future approaches in this field that are anticipated to further advance clinical applicability.

Mesothelial and immune cells interplay in the tumor microenvironment

Mesothelial cells (MCs) constitute a dynamic mesothelium in which their numerous crucial functions synergistically interact with other cells to maintain serosal integrity and homeostasis. Previous studies have confirmed the crucial role of interactions between MCs and tumor cells in tumorigenesis and progression in the tumor microenvironment (TME). However, recent research has found that MCs can induce an immunosuppressive microenvironment by secreting various cytokines, chemokines, and exosomes which recruit immunosuppressive cells or interact with immune cells, thus contributing to tumor progression. This review primarily examines the immunoregulatory role of MCs in the TME of mesothelioma and metastatic pleural and peritoneal carcinomas. It also explores the potential mechanisms by which these interactions induce immunosuppression and their impact on tumor growth and therapy.

The tumor-promoting role of methionyl-tRNA synthetase 1 in ovarian cancer and its potential mechanisms

Methionyl-tRNA synthetase 1 (MARS) is an enzyme that belongs to the family of aminoacyl-tRNA synthetases. High levels of MARS have been shown to correlate with a poorer prognosis in a variety of tumor types. However, its specific role and the underlying mechanism in cancer, especially in ovarian cancer, are not well understood. This study aims to investigate the roles and potential mechanisms of MARS in ovarian cancer. Our findings reveal that MARS protein levels are elevated in ovarian cancer tissues, and that high MARS expression is associated with reduced overall survival and progression-free survival. Silencing of MARS significantly inhibited the proliferation, colony formation, migration, and invasion of ovarian cancer cells in vitro and mildly suppressed ovarian tumor growth in vivo. MARS silencing contributes to the upregulation of p53 protein. Moreover, RNA sequencing and subsequent in vitro and in vivo validation showed that the TP53-regulated cell cycle genes and immune-related cell surface receptor and cytokine-encoding genes were downregulated following MARS knockdown, suggesting a potential mechanism for the observed attenuation of tumor progression. Our results suggest MARS as a potential biomarker and therapeutic target in ovarian cancer, highlighting the need for further investigation into its multifaceted role in tumor biology and immune cell function.

Direct cell interactions potentially regulate transcriptional programmes that control the responses of high grade serous ovarian cancer patients to therapy

The tumour microenvironment is composed of a complex cellular network involving cancer, stromal and immune cells in dynamic interactions. A large proportion of this network relies on direct physical interactions between cells, which may impact patient responses to clinical therapy. Doublets in scRNA-seq are usually excluded from analysis. However, they may represent directly interacting cells. To decipher the physical interaction landscape in relation to clinical prognosis, we inferred a physical cell-cell interaction (PCI) network from 'biological' doublets in a scRNA-seq dataset of approximately 18,000 cells, obtained from 7 treatment-naive ovarian cancer patients. Focusing on cancer-stromal PCIs, we uncovered molecular interaction networks and transcriptional landscapes that stratified patients in respect to their clinical responses to standard therapy. Good responders featured PCIs involving immune cells interacting with other cell types including cancer cells. Poor responders lacked immune cell interactions, but showed a high enrichment of cancer-stromal PCIs. To explore the molecular differences between cancer-stromal PCIs between responders and non-responders, we identified correlating gene signatures. We constructed ligand-receptor interaction networks and identified associated downstream pathways. The reconstruction of gene regulatory networks and trajectory analysis revealed distinct transcription factor (TF) clusters and gene modules that separated doublet cells by clinical outcomes. Our results indicate (i) that transcriptional changes resulting from PCIs predict the response of ovarian cancer patients to standard therapy, (ii) that immune reactivity of the host against the tumour enhances the efficacy of therapy, and (iii) that cancer-stromal cell interaction can have a dual effect either supporting or inhibiting therapy responses.

The dynamic immune behavior of primary and metastatic ovarian carcinoma

Patients with high-grade serous ovarian carcinoma (HGSC) are usually diagnosed with advanced-stage disease, and the tumors often have immunosuppressive characteristics. Together, these factors are important for disease progression, drug resistance, and mortality. In this study, we used a combination of single-cell sequencing and spatial transcriptomics to identify the molecular mechanisms that lead to immunosuppression in HGSC. Primary tumors consistently showed a more active immune microenvironment than did omental tumors. In addition, we found that untreated primary tumors were mostly populated by dysfunctional CD4 and CD8 T cells in later stages of differentiation; this, in turn, was correlated with expression changes in the interferon α and γ pathways in epithelial cells, showing that cross-communication between the epithelial and immune compartments is important for immune suppression in HGSC. These findings could have implications for the design of clinical trials with immune-modulating drugs.

Mechanisms of the JNK/p38 MAPK signaling pathway in drug resistance in ovarian cancer

Ovarian cancer (OC) is the most lethal malignancy in the female reproductive system, and chemotherapy drug resistance is the main cause of treatment failure. The Mitogen-Activated Protein Kinases (MAPK) pathway plays a pivotal role in regulating cell proliferation, migration, and invasive capacity in response to extracellular stimuli. This review focuses on the mechanisms and therapeutic strategies related to the JNK/p38 MAPK signaling pathway in OC resistance. The JNK/p38 MAPK pathway plays a dual role in OC chemoresistance. This review examines its role in mediating OC treatment resistance by exploring the mechanisms of action of the JNK/p38 MAPK signaling pathway, particularly its involvement in several key biological processes, including apoptosis, autophagy, DNA damage response, the tumor microenvironment (TME), and drug efflux. Additionally, the review investigates the timing of activation of this pathway and its crosstalk with other signaling pathways such as PI3K/AKT and NF-κB. Targeting JNK/p38 MAPK signaling has shown promise in reversing chemoresistance, with several inhibitors and natural compounds demonstrating potential in preclinical studies. Regulating JNK/p38 MAPK may transform what was once a terminal obstacle into a manageable challenge for OC patients with chemotherapy resistance, ultimately improving survival and quality of life.

Cracking the Code: Predicting Tumor Microenvironment Enabled Chemoresistance with Machine Learning in the Human Tumoroid Models

High-grade serous tubo-ovarian cancer (HGSC) is marked by substantial inter- and intra-tumor heterogeneity. The tumor microenvironments (TME) of HGSC show pronounced variability in cellular make-up across metastatic sites, which is linked to poorer patient outcomes. The influence of cellular composition on therapy sensitivity, including chemotherapy and targeted treatments, has not been thoroughly investigated. In this study, we examined the premise that the variations in cellular composition can forecast drug efficacy. Using a high-throughput 3D in vitro tumoroid model, we assessed the drug responses of twenty-three distinct cellular configurations to an assortment of five therapeutic agents, including carboplatin and paclitaxel. By amalgamating our experimental findings with random forest machine learning algorithms, we assessed the influence of TME cellular composition on treatment reactions. Our findings reveal notable disparities in drug responses correlated with tumoroid composition, underscoring the significance of cellular diversity within the TME as a predictor of therapeutic outcomes. However, our work also emphasizes the complex nature of cell composition's influence on drug response. This research establishes a foundation for employing human tumoroids with varied cellular composition as a method to delve into the roles of stromal, immune, and other TME cell types in enhancing cancer cell susceptibility to various treatments. Additionally, these tumoroids can serve as a platform to explore pivotal cellular interactions within the TME that contribute to chemoresistance and cancer recurrence.

Single-cell omics technologies - Fundamentals on how to create single-cell looking glasses for reproductive health

Over the last decade, in line with the goals of precision medicine to offer individualized patient care, various single-cell technologies measuring gene and proteomic expression in various tissues have rapidly advanced to study health and disease at the single cell level. Precisely understanding cell composition, position within tissues, signaling pathways, and communication can reveal insights into disease mechanisms and systemic changes during development, pregnancy, and gynecologic disorders across the lifespan. Single-cell technologies dissect the complex cellular compositions of reproductive tract tissues, providing insights into mechanisms behind reproductive tract dysfunction which impact wellness and quality of life. These technologies aim to understand basic tissue and organ functions and, clinically, to develop novel diagnostics, early disease biomarkers, and cell-targeted therapies for currently suboptimally-treated disorders. Increasingly, they are applied to pregnancy and pregnancy disorders, gynecologic malignancies, and uterine and ovarian physiology and aging, which are discussed in more detail in manuscripts in this special issue of AJOG. Here, we review recent applications of single-cell technologies to the study of gynecologic disorders and systemic biological adaptations during fetal development, pregnancy, and across a woman's lifespan. We discuss sequencing- and proteomic-based single-cell methods, as well as spatial transcriptomics and high-dimensional proteomic imaging, describing each technology's mechanism, workflow, quality control, and highlighting specific benefits, drawbacks, and utility in the context of reproductive medicine. We consider analytical methods for the high-dimensional single-cell data generated, highlighting statistical constraints and recent computational techniques for downstream clinical translation. Overall, current and evolving single-cell "looking glasses", or perspectives, have the potential to transform fundamental understanding of women's health and reproductive disorders and alter the trajectory of clinical practice and patient outcomes in the future.

Single-cell RNA sequencing and spatial transcriptomics reveal the heterogeneity and intercellular communication of cancer-associated fibroblasts in gastric cancer

BACKGROUND

Gastric cancer is a highly aggressive malignancy characterized by a complex tumor microenvironment (TME). Cancer-associated fibroblasts (CAFs), which are a key component of the TME, exhibit significant heterogeneity and play crucial roles in tumor progression. Therefore, a comprehensive understanding of CAFs is essential for developing novel therapeutic strategies for gastric cancer.

METHODS

This study investigates the characteristics and functional information of CAF subtypes and explores the intercellular communication between CAFs and malignant epithelial cells (ECs) in gastric cancer by analyzing single-cell sequencing data from 24 gastric cancer samples. CellChat was employed to map intercellular communication, and Seurat was used to integrate single-cell sequencing data with spatial transcriptome data to reconstruct a comprehensive single-cell spatial map. The spatial relationship between apCAFs and cancer cells was analyzed using multicolor immunohistochemistry.

RESULTS

Cells were categorized into nine distinct categories, revealing a positive correlation between the proportions of epithelial cells (ECs) and fibroblasts. Furthermore, six fibroblast subpopulations were identified: inflammatory (iCAFs), pericytes, matrix (mCAFs), antigen-presenting (apCAFs), smooth muscle cells (SMCs), and proliferative CAFs (pCAFs). Each of these subpopulations was linked to various biological processes and immune responses. Malignant ECs exhibited heightened intercellular communication, particularly with CAF subpopulations, through specific ligand-receptor interactions. High-density regions of CAF subpopulations displayed spatial exclusivity, with pericytes serving as a source for iCAFs, mCAFs, and apCAFs. Notably, malignant ECs and apCAFs showed increased interactions, with certain ligand-receptor pairs potentially impacting the prognosis of gastric cancer. Multiplex immunohistochemistry (mIHC) confirmed the close spatial proximity of apCAFs to cancer cells in gastric cancer.

CONCLUSION

Our study provided a comprehensive characterization of CAF heterogeneity in gastric cancer and revealed the intricate intercellular networks within the TME. The identified CAF subpopulations and their interactions with malignant cells could serve as potential therapeutic targets.

Combination therapy with Chicoric acid and PD-1/PD-L1 blockade improves the immunotherapy response in patient-derived ovarian cancer xenograft model

PURPOSE

Limited treatment options exist for refractory ovarian cancer (OC) due to its poor response to immune therapies. Therefore, there is an urgent need to develop new effective treatment strategies. Chicoric acid (CA) is reported to have immune-enhancing properties, but its efficacy in cancer treatment is not well understood. We hypothesize that CA might improve the efficacy of PD-1/PD-L1 blockade immunotherapy in refractory OC patients.

METHODS

Patient-derived xenograft (PDX) models were constructed from chemoresistant advanced high-grade serous ovarian cancer patients. These models were treated with CA, aPD-1/aPD-L1 antibodies, or a combination of both. Single-cell RNA sequencing was performed to analyze the cellular composition of the tumor microenvironment (TME), evaluate treatment efficacy, and explore therapeutic mechanisms. Variations in peripheral blood lymphocytes were analyzed via fluorescence-activated cell sorting. Immunohistochemistry confirmed the variations in tumor-infiltrating lymphocytes and tumor cells.

RESULTS

Immunocompetent peripheral blood mononuclear cell (PBMC)-PDX models were successfully constructed using malignant ascites fluid and PBMCs. After treatment, 158,734 cells from 15 samples were categorized into epithelial cells, T lymphocytes, myeloid cells, fibroblasts, and endothelial cells. CA enhanced the antitumor ability of immune cells against OC cells. Notably, CA stimulated the proliferation of CD45 + and CD3 + cells and promoted the migration of CD8 + and CD4 + T cells from peripheral blood to infiltrate the TME. Additionally, CA enhanced the response of OCs to aPD-L1/aPD-1 treatment, strengthened the interaction between tumor and nontumor cells, and identified APP/CD74 as a critical ligand‒receptor pair. CHI3L1 was also found to be a potential marker for predicting immunotherapy efficacy in OC.

CONCLUSION

This study demonstrated that combination therapy with CA and aPD-1/aPD-L1 might be a promising strategy for treating OC effectively.

Cross-Talk Between Cancer and Its Cellular Environment-A Role in Cancer Progression

The tumor microenvironment is a dynamic and complex three-dimensional network comprising the extracellular matrix and diverse non-cancerous cells, including fibroblasts, adipocytes, endothelial cells and various immune cells (lymphocytes T and B, NK cells, dendritic cells, monocytes/macrophages, myeloid-derived suppressor cells, and innate lymphoid cells). A constantly and rapidly growing number of studies highlight the critical role of these cells in shaping cancer survival, metastatic potential and therapy resistance. This review provides a synthesis of current knowledge on the modulating role of the cellular microenvironment in cancer progression and response to treatment.

A Peptide Derived from Nectin-4 Increases Cisplatin Cytotoxicity in Cell Lines and Cells from Ovarian Cancer Patients' Ascites

BACKGROUND/OBJECTIVES

New approaches to the treatment of women with ovarian cancer are desperately needed, since most women develop resistance to chemotherapy and the 5-year survival rate remains low. The hypothesis guiding this study was that the inhibition of cell adhesion could be used as a novel strategy to increase the chemosensitivity of ovarian cancer cells.

METHODS

The Nectin-4 peptide N4-P10 was used to inhibit the formation of cell-cell aggregates (spheroids) using cell lines and cells isolated from ovarian cancer patients' ascites. Cell lines were pre-treated with peptide N4-P10 or control scrambled peptides and monitored for spheroid formation with live-cell imaging by digital time-lapse photography. Cells were then tested for the cytotoxicity of the chemotherapeutic agent, cisplatin.

RESULTS

Peptide N4-P10 blocked aggregation in cell lines with different levels of Nectin-4 expression and different spheroid morphologies. The cytotoxicity of cisplatin increased in cells pre-treated with peptide N4-P10. Similarly, when single cells were isolated from the ascites of ovarian cancer patients, peptide N4-P10 blocked cell aggregation and increased the cytotoxicity of cisplatin.

CONCLUSIONS

These results suggest that targeting the cell-cell adhesive property of cancer cells could serve as a new approach to augment the cytotoxic effect of chemotherapy and potentially reduce disease recurrence in ovarian cancer patients.

Deciphering ovarian cancer heterogeneity through spatial transcriptomics, single-cell profiling, and copy number variations

High-grade serous ovarian carcinoma (HGSOC) poses a formidable clinical challenge due to multidrug resistance (MDR) caused by tumor heterogeneity. To elucidate the intricate mechanisms underlying HGSOC heterogeneity, we conducted a comprehensive analysis of five single-cell transcriptomes and eight spatial transcriptomes derived from eight HGSOC patients. This study provides a comprehensive view of tumor heterogeneity across the spectrum of gene expression, copy number variation (CNV), and single-cell profiles. Our CNV analysis revealed intratumor heterogeneity by identifying distinct tumor clones, illuminating their evolutionary trajectories and spatial relationships. We further explored the homogeneity and heterogeneity of CNV across tumors to pinpoint the origin of heterogeneity. At the cellular level, single-cell RNA sequencing (scRNA seq) analysis identified three meta-programs that delineate the functional profile of tumor cells. The communication networks between tumor cell clusters exhibited unique patterns associated with the meta-programs governing these clusters. Notably, the ligand-receptor pair MDK - NCL emerged as a highly enriched interaction in tumor cell communication. To probe the functional significance of this interaction, we induced NCL overexpression in the SOVK3 cell line and observed enhanced tumor cell proliferation. These findings indicate that the MDK - NCL interaction plays a crucial role in promoting HGSOC tumor growth and may represent a promising therapeutic target. In conclusion, this study comprehensively unravels the multifaceted nature of HGSOC heterogeneity, providing potential therapeutic strategies for this challenging malignancy.

Evaluating the specific STAT3 inhibitor YHO-1701 in ovarian cancer cell lines and patient-derived cell models: efficacy, mechanisms, and therapeutic potential

OBJECTIVE

Signal transducer and activator of transcription 3 (STAT3) plays key roles in regulating cancer cell proliferation, survival, and metastasis. We aimed to determine the effects of YHO-1701, an oral STAT3 inhibitor, in ovarian cancer (OC).

METHODS

We evaluated the impact of YHO-1701 on cell growth in patient-derived cells (PDCs) and OC cell lines using standard cell proliferation assays. Spheroid models derived from PDCs were assessed using three-dimensional (3D) cell viability assays. Antitumor activity was performed in SKOV3 xenograft mice treated orally administrated YHO-1701 with 20 mg/kg. Changes in STAT3 signaling were analyzed by western blotting. The molecular mechanisms of STAT3 inhibition were investigated by sequencing RNA and analyzing pathways in the SKOV3 using a small interfering RNA targeting STAT3 (STAT3 siRNA) and YHO-1701.

RESULTS

YHO-1701 inhibited the growth of OC cell lines by preventing STAT3 dimerization and decreasing the expression of its downstream signaling molecule, survivin. The growth of PDCs and spheroids obtained from patients with primary and recurrent OCs was significantly inhibited. Antitumor effect was observed in the SKOV3 xenograft mice with YHO-1701. YHO-1701 induced apoptosis in OC cells. Additionally, p53 and/or MAPK signaling pathways were upregulated in SKOV3 cells incubated with YHO-1701 and in those with STAT3 siRNA.

CONCLUSION

Our results showed that YHO-1701 suppressed cell growth in PDCs of OC, accompanied by survivin inhibition, and a decrease in the number of peritoneal metastasis in the mice by YHO-1701, compared with those treated with control. Therefore, YHO-1701 could be a promising candidate agent for treating OC.

Unveiling the link between chronic inflammation and cancer

The highly nuanced transition from an inflammatory process to tumorigenesis is of great scientific interest. While it is well known that environmental stimuli can cause inflammation, less is known about the oncogenic modifications that chronic inflammation in the tissue microenvironment can bring about, as well as how these modifications can set off pro-tumorigenic processes. It is clear that no matter where the environmental factors come from, maintaining an inflammatory microenvironment encourages carcinogenesis. In addition to encouraging angiogenesis and metastatic processes, sustaining the survival and proliferation of malignant transformed cells, and possibly altering the efficacy of therapeutic agents, inflammation can negatively regulate the antitumoral adaptive and innate immune responses. Because chronic inflammation has multiple pathways involved in tumorigenesis and metastasis, it has gained recognition as a marker of cancer and a desirable target for cancer therapy. Recent advances in our knowledge of the molecular mechanisms that drive cancer's progression demonstrate that inflammation promotes tumorigenesis and metastasis while suppressing anti-tumor immunity. In many solid tumor types, including breast, lung, and liver cancer, inflammation stimulates the activation of oncogenes and impairs the body's defenses against the tumor. Additionally, it alters the microenvironment of the tumor. As a tactical approach to cancer treatment, these findings have underscored the importance of targeting inflammatory pathways. This review highlights the role of inflammation in cancer development and metastasis, focusing on its impact on tumor progression, immune suppression, and therapy resistance. It examines current anti-inflammatory strategies, including NSAIDs, cytokine modulators, and STAT3 inhibitors, while addressing their potential and limitations. The review emphasizes the need for further research to unravel the complex mechanisms linking inflammation to cancer progression and identify molecular targets for specific cancer subtypes.

Single-cell RNA sequencing in ovarian cancer: Current progress and future prospects

Ovarian cancer is one of the most prevalent gynaecological malignancies. The rapid development of single-cell RNA sequencing (scRNA-seq) has allowed scientists to use this technique to study ovarian cancer development, heterogeneity, and tumour environment. Although multiple original research articles have reported the use of scRNA-seq in understanding ovarian cancer and how therapy resistance occurs, there is a lack of a comprehensive review that could summarize the findings from multiple studies. Therefore, this review aimed to fill this gap by comparing and summarizing the results from different studies that have used scRNA-seq in understanding ovarian cancer development, heterogeneity, tumour microenvironment, and treatment resistance. This review will begin with an overview of scRNA-seq workflow, followed by a discussion of various applications of scRNA-seq in studying ovarian cancer. Next, the limitations and future directions of scRNA-seq in ovarian cancer research will be presented.

PLIN2 Promotes Lipid Accumulation in Ascites-Associated Macrophages and Ovarian Cancer Progression by HIF1α/SPP1 Signaling

A major characteristic of ovarian cancer (OC) is its unique route of metastasis via ascites. The immune microenvironment in ascites remains understudied, leaving the mechanism of ascites-mediated abdominal metastasis obscure. Here, a single-cell transcriptomic landscape of CD45+ immune cells across multiple anatomical sites is depicted, including primary tumors, metastatic lesions, and ascites, from patients diagnosed with high-grade serous ovarian carcinoma (HGSOC). A novel subset of perilipin 2 high (PLIN2hi) macrophages are identified that are enriched in ascites and positively correlated with OC progression, hence being designated as "ascites-associated macrophages (AAMs)". AAMs are lipid-loaded with overexpression of the lipid droplet protein PLIN2. Overexpression or suppression of PLIN2 can enhance or inhibit tumor cell migration, invasion, and vascular permeability in vitro, which is also confirmed in vivo. Mechanistically, it is demonstrated that PLIN2 boosts HIF1α/SPP1 signaling in macrophages, thereby exerting pro-tumor functions. Finally, a PLIN2-targeting liposome is designed to efficiently suppress ascites production and tumor metastasis. Taken together, this work provides a comprehensive characterization of the cancer-promoting function and lipid-rich property of ascites-enriched PLIN2hi macrophages, establishes a link between lipid metabolism and hypoxia within the context of the ascites microenvironment, and elucidates the pivotal role of ascites in trans-coelomic metastasis of OC.

Single-cell transcriptomes reveal cell-type-specific and sample-specific gene function in human cancer

Accurate annotation of gene function in individual samples and even in each cell type is essential for understanding the pathogenesis of cancers. Single-cell RNA-sequencing (scRNA-seq) provides unprecedented resolution to decipher gene function. In order to explore how scRNA-seq contributes to the understanding of gene function in cancers, we constructed an assessment framework based on co-expression network and neighbor-voting method using 116,814 cells. Compared with bulk transcriptome, scRNA-seq recalled more experimentally verified gene functions. Surprisingly, scRNA-seq revealed cell-type-specific functions, especially in immune cells, whose expression profile recalled immune-related functions that were not discovered in cancer cells. Furthermore, scRNA-seq discovered sample-specific functions, highlighting that it provided sample-specific information. We also explored factors affecting the performance of gene function prediction. We found that 500 or more cells should be considered in the prediction with scRNA-seq, and that scRNA-seq datasets generated from 10x Genomics platform had a better performance than those from Smart-seq2. Collectively, we compared the prediction performance of bulk data and scRNA-seq data from multiple perspectives, revealing the irreplaceable role of single-cell sequencing in decoding the biological progresses in which the gene involved.

Defining the regulatory logic of breast cancer using single-cell epigenetic and transcriptome profiling

Annotation of cis-regulatory elements that drive transcriptional dysregulation in cancer cells is critical to understanding tumor biology. Herein, we present matched chromatin accessibility (single-cell assay for transposase-accessible chromatin by sequencing [scATAC-seq]) and transcriptome (single-cell RNA sequencing [scRNA-seq]) profiles at single-cell resolution from human breast tumors and healthy mammary tissues processed immediately following surgical resection. We identify the most likely cell of origin for subtype-specific breast tumors and implement linear mixed-effects modeling to quantify associations between regulatory elements and gene expression in malignant versus normal cells. These data unveil cancer-specific regulatory elements and putative silencer-to-enhancer switching events in cells that lead to the upregulation of clinically relevant oncogenes. In addition, we generate matched scATAC-seq and scRNA-seq profiles for breast cancer cell lines, revealing a conserved oncogenic gene expression program between in vitro and in vivo cells. This work highlights the importance of non-coding regulatory mechanisms that underlie oncogenic processes and the ability of single-cell multi-omics to define the regulatory logic of cancer cells.

Advances in biomaterials-based tissue engineering for regeneration of female reproductive tissues

The anatomical components of the female reproductive system-comprising the ovaries, uterus, cervix, vagina, and fallopian tubes-interact intricately to provide the structural and hormonal support essential for reproduction. However, this system is susceptible to various detrimental factors, both congenital and acquired, that can impair fertility and adversely affect quality of life. Recent advances in bioengineering have led to the development of sophisticated three-dimensional models that mimic the complex architecture and functionality of reproductive organs. These models, incorporating diverse cell types and tissue layers, are crucial for understanding physiological processes within the reproductive tract. They offer insights into decidualization, ovulation, folliculogenesis, and the progression of reproductive cancers, thereby enhancing personalized medical treatments and addressing female infertility. This review highlights the pivotal role of tissue engineering in diagnosing and treating female infertility, emphasizing the importance of considering factors like biocompatibility, biomaterial selection, and mechanical properties in the design of bioengineered systems. The challenge of replicating the functionally specialized and structurally complex organs, such as the uterus and ovary, underscores the need for reliable techniques that improve morphological and functional restoration. Despite substantial progress, the goal of creating a fully artificial female reproductive system is still a challenge. Nonetheless, the recent fabrication of artificial ovaries, uteruses, cervixes, and vaginas marks significant advancements toward this aim. Looking forward, the challenges in bioengineering are expected to spur further innovations in both basic and applied sciences, potentially hastening the clinical adoption of these technologies.

Expression of PRAME in high-grade serous carcinoma is associated with higher residual disease volume and Occludin expression

BACKGROUND

Patients with high-grade serous carcinoma (HGSC) are commonly diagnosed at late disease stages and after primary tumors have disseminated in the peritoneum. The overexpression of tight junction proteins has been associated with poor prognosis in this setting, potentially reflecting the tumor´s adaptive changes in the disease cascade.

METHODS

By performing immunohistochemistry in a large single-center cohort of a total of 705 HGSC, we test the hypothesis that the protein expression of PReferentially expressed Antigen of MElanoma (PRAME) contains prognostic, predictive or clinically translatable information. We further examine its co-expression with tight junction proteins.

RESULTS

We confirmed the nuclear expression of PRAME in 442 (63 %) of specimens with comparable expression levels in peritoneal and pleural effusions (p = 0.72), and in effusions versus surgical specimens (p = 0.339). In effusions, any degree of expression of PRAME was significantly associated with suboptimal debulking surgery during primary treatment (p = 0.034). In surgical specimens, higher expression of PRAME was significantly linked to more advanced FIGO stage (p = 0.021). PRAME expression was not associated with other clinico-pathologic factors as age, CA125 levels, chemoresistance or survival, but correlated with PRAME mRNA levels. Significant correlation was found between expression levels of PRAME and the tight junction protein Occludin (p = 0.002).

CONCLUSION

Taken together, our study confirms PRAME to be expressed in the majority of HGSC effusions and surgical samples. The association of high levels of PRAME expression with incomplete surgical resection status and advanced stage disease may suggest PRAME expression as adaptative mechanism during disease dissemination. This finding warrants confirmation in independent series.

Exploiting Cancer Dormancy Signaling Mechanisms in Epithelial Ovarian Cancer Through Spheroid and Organoid Analysis

Epithelial ovarian cancer (EOC) exhibits a unique mode of metastasis, involving spheroid formation in the peritoneum. Our research on EOC spheroid cell biology has provided valuable insights into the signaling plasticity associated with metastasis. We speculate that EOC cells modify their biology between tumour and spheroid states during cancer dormancy, although the specific mechanisms underlying this transition remain unknown. Here, we present novel findings from direct comparisons between cultured EOC spheroids and organoids. Our results indicated that AMP-activated protein kinase (AMPK) activity was significantly upregulated and protein kinase B (Akt) was downregulated in EOC spheroids compared to organoids, suggesting a clear differential phenotype. Through RNA sequencing analysis, we further supported these phenotypic differences and highlighted the significance of cell cycle regulation in organoids. By inhibiting the G2/M checkpoint via kinase inhibitors, we confirmed that this pathway is essential for organoids. Interestingly, our results suggest that specifically targeting aurora kinase A (AURKA) may represent a promising therapeutic strategy since our cells were equally sensitive to Alisertib treatment as both spheroids and organoids. Our findings emphasize the importance of studying cellular adaptations of EOC cells, as there may be different therapeutic targets depending on the step of EOC disease progression.

Reversible downregulation of MYC in a spheroid model of metastatic epithelial ovarian cancer

Upon detachment from the primary tumour, epithelial ovarian cancer cells can form multicellular aggregates, also referred to as spheroids, that have the capacity to establish metastases at distant sites. These structures exhibit numerous adaptations that may facilitate metastatic transit and promote tumorigenic potential. One such adaptation is the acquisition of dormancy, characterized by decreased proliferation and molecular features of quiescence. One of the most frequently dysregulated genes in cancer is MYC, which encodes a transcription factor that promotes cell proliferation. In this study, we demonstrate that MYC protein abundance and associated gene expression is significantly decreased in EOC spheroids compared to adherent cells. This downregulation occurs rapidly upon cell detachment and is proteasome-dependent. Moreover, MYC protein abundance and associated gene expression is restored upon spheroid reattachment to an adherent culture surface. Overall, our findings suggest that suppression of MYC activity is a common feature of EOC spheroids and may contribute to the reversible acquisition of dormancy.

Integrated proteomics and scRNA-seq analyses of ovarian cancer reveal molecular subtype-associated cell landscapes and immunotherapy targets

BACKGROUND

Epithelial ovarian cancer (EOC) represents the most lethal gynaecological malignancy, yet understanding the connections between its molecular subtypes and their therapeutic implications remains incomplete.

METHODS

We conducted mass spectrometry-based proteomics analyses of 154 EOC tumour samples and 29 normal fallopian tubes, and single-cell RNA sequencing (scRNA-seq) analyses of an additional eight EOC tumours to classify proteomic subtypes and assess their cellular ecosystems and clinical significance. The efficacy of identified therapeutic targets was evaluated in patient-derived xenograft (PDX) and orthotopic mouse models.

RESULTS

We identified four proteomic subtypes with distinct clinical relevance: malignant proliferative (C1), immune infiltrating (C2), Fallopian-like (C3) and differentiated (C4) subtypes. C2 subtype was characterized by lymphocyte infiltration, notably an increased presence of GZMK CD8+ T cells and phagocytosis-like MRC+ macrophages. Additionally, we identified CD40 as a specific prognostic factor for C2 subtype. The interaction between CD40+ phagocytosis-like macrophages and CD40RL+ IL17R CD4+ T cells was correlated with a favourable prognosis. Finally, we established a druggable landscape for non-immune EOC patients and verified a TYMP inhibitor as a promising therapeutic strategy.

CONCLUSIONS

Our study refines the current immune subtype for EOC, highlighting CD40 agonists as promising therapies for C2 subtype patients and targeting TYMP for non-immune patients.

Patient-derived acellular ascites fluid affects drug responses in ovarian cancer cell lines through the activation of key signalling pathways

Malignant ascites is commonly produced in advanced epithelial ovarian cancer (EOC) and serves as unique microenvironment for tumour cells. Acellular ascites fluid (AAF) is rich in signalling molecules and has been proposed to play a role in the induction of chemoresistance. Through in vitro testing of drug sensitivity and by assessing intracellular phosphorylation status in response to mono- and combination treatment of five EOC cell lines after incubation with AAFs derived from 20 different patients, we investigated the chemoresistance-inducing potential of ascites. We show that the addition of AAFs to the culture media of EOC cell lines has the potential to induce resistance to standard-of-care drugs (SCDs). We also show that AAFs induce time- and concentration-dependent activation of downstream signalling to signal transducer and activator of transcription 3 (STAT3), and concomitantly altered phosphorylation of mitogen-activated protein kinase kinase (MEK), phosphoinositide 3-kinase (PI3K)-protein kinase B (AKT) and nuclear factor NF-kappa-B (NFκB). Antibodies targeting the interleukin-6 receptor (IL6R) effectively blocked phosphorylation of STAT3 and STAT1. Treatments with SCDs were effective in reducing cell viability in only a third of 30 clinically relevant conditions examined, defined as combinations of drugs, different cell lines and AAFs. Combinations of SCDs and novel therapeutics such as trametinib, fludarabine or rapamycin were superior in another third. Notably, we could nominate effective treatment combinations in almost all conditions except in 4 out of 30 conditions, in which trametinib or fludarabine showed higher efficacy alone. Taken together, our study underscores the importance of the molecular characterisation of individual patients' AAFs and the impact on treatment resistance as providing clinically meaningful information for future precision treatment approaches in EOC.

The present and future of the Cancer Dependency Map

Despite tremendous progress in the past decade, the complex and heterogeneous nature of cancer complicates efforts to identify new therapies and therapeutic combinations that achieve durable responses in most patients. Further advances in cancer therapy will rely, in part, on the development of targeted therapeutics matched with the genetic and molecular characteristics of cancer. The Cancer Dependency Map (DepMap) is a large-scale data repository and research platform, aiming to systematically reveal the landscape of cancer vulnerabilities in thousands of genetically and molecularly annotated cancer models. DepMap is used routinely by cancer researchers and translational scientists and has facilitated the identification of several novel and selective therapeutic strategies for multiple cancer types that are being tested in the clinic. However, it is also clear that the current version of DepMap is not yet comprehensive. In this Perspective, we review (1) the impact and current uses of DepMap, (2) the opportunities to enhance DepMap to overcome its current limitations, and (3) the ongoing efforts to further improve and expand DepMap.

Surface Molecular Markers for the Isolation of Viable Fibroblast Subpopulations in the Female Reproductive Tract: A Comprehensive Review

Advancements in single-cell analyzis technologies, particularly single-cell RNA sequencing (scRNA-seq) and Fluorescence-Activated Cell Sorting (FACS), have enabled the analyzis of cellular diversity by providing resolutions that were not available previously. These methods enable the simultaneous analyzis of thousands of individual transcriptomes, facilitating the classification of cells into distinct subpopulations, based on transcriptomic differences, adding a new level of complexity to biomolecular and medical research. Fibroblasts, despite being one of the most abundant cell types in the human body and forming the structural backbone of tissues and organs, remained poorly characterized for a long time. This is largely due to the high morphological similarity between different types of fibroblasts and the lack of specific markers to identify distinct subpopulations. Once thought to be cells responsible solely for the synthesis of extracellular matrix (ECM) components, fibroblasts are now recognized as active participants in diverse physiological processes, including inflammation and antimicrobial responses. However, defining the molecular profile of fibroblast subpopulations remains a significant challenge. In this comprehensive review, which is based on over two thousand research articles, we focus on the identification and characterization of fibroblast subpopulations and their specific surface markers, with an emphasis on their potential as molecular targets for selective cell isolation. By analyzing surface markers, alongside intra- and extracellular protein profiles, we identified multiple fibroblast subtypes within the female reproductive system. These subtypes exhibit distinct molecular signatures and functional attributes, shaped by their anatomical localization and the surrounding physiological or pathological conditions. Our findings underscore the heterogeneity of fibroblasts and their diverse roles in various biological contexts. This improved understanding of fibroblast subpopulations paves the way for innovative diagnostic and therapeutic strategies, offering the potential for precision targeting of specific fibroblast subsets in clinical applications.

Ovarian cancer-derived IL-4 promotes immunotherapy resistance

Ovarian cancer is resistant to immunotherapy, and this is influenced by the immunosuppressed tumor microenvironment (TME) dominated by macrophages. Resistance is also affected by intratumoral heterogeneity, whose development is poorly understood. To identify regulators of ovarian cancer immunity, we employed a spatial functional genomics screen (Perturb-map), focused on receptor/ligands hypothesized to be involved in tumor-macrophage communication. Perturb-map recapitulated tumor heterogeneity and revealed that interleukin-4 (IL-4) promotes resistance to anti-PD-1. We find ovarian cancer cells are the key source of IL-4, which directs the formation of an immunosuppressive TME via macrophage control. IL-4 loss was not compensated by nearby IL-4-expressing clones, revealing short-range regulation of TME composition dictating tumor evolution. Our studies show heterogeneous TMEs can emerge from localized altered expression of cancer-derived cytokines/chemokines that establish immune-rich and immune-excluded neighborhoods, which drive clone selection and immunotherapy resistance. They also demonstrate the potential of targeting IL-4 signaling to enhance ovarian cancer response to immunotherapy.

Targeted and Untargeted Amine Metabolite Quantitation in Single Cells with Isobaric Multiplexing

We developed a single cell amine analysis approach utilizing isobarically multiplexed samples of 6 individual cells along with analyte abundant carrier. This methodology was applied for absolute quantitation of amino acids and untargeted relative quantitation of amines in a total of 108 individual cells using nanoflow LC with high-resolution mass spectrometry. Together with individually determined cell sizes, this provides accessible quantification of intracellular amino acid concentrations within individual cells. The targeted method was partially validated for 10 amino acids with limits of detection in low attomoles, linear calibration range covering analyte amounts typically from 30 amol to 120 fmol, and correlation coefficients (R) above 0.99. This was applied with cell sizes recorded during dispensing to determine millimolar intracellular amino acid concentrations. The untargeted approach yielded 249 features that were detected in at least 25 % of the single cells, providing modest cell type separation on principal component analysis. Using Greedy forward selection with regularized least squares, a sub-selection of 100 features explaining most of the difference was determined. These features were annotated using MS2 from analyte standards and accurate mass with library search. The approach provides accessible, sensitive, and high-throughput method with the potential to be expanded also to other forms of ultrasensitive analysis.

Water-Soluble Fluorescent Sensors for Quantification of Trace Cisplatin in Body Fluids from Clinical Cancer Patients

Accurate quantification of cisplatin (cDDP) in body fluids (blood, urine, and ascites) is crucial in monitoring therapeutic processes, assessing drug metabolism, and optimizing treatment schedules for cancer patients. Nonetheless, due to the inherent fluorescence and complexity of the body fluid matrix, along with the low cDDP concentrations in these fluids during treatment, using fluorescent sensors for fluid detection remains a subject of ongoing research. Herein, a series of water-soluble cDDP-activatable fluorescent sensors was rationally constructed by introducing thioether groups to the xanthene skeleton based on the chalcogenophilicity of platinum. These sensors exhibit excellent sensitivity and certain anti-interference capabilities for sensing cDDP in living cells, rat tissues, and zebrafish. Especially, with a simplified sample pretreatment procedure, for the first time, Rh3 and Rh4 have enabled quantitative detection of cDDP levels in diversiform body fluids from clinical ovarian and bladder cancer patients. These results are highly consistent with those obtained by ICP-MS detection. This work paves the way for utilizing fluorescent sensors in clinical body fluid analysis, thus potentially revolutionizing the monitoring methods of cDDP in clinic settings.

Myeloid activation clears ascites and reveals IL27-dependent regression of metastatic ovarian cancer

Patients with metastatic ovarian cancer (OvCa) have a 5-year survival rate of <30% due to the persisting dissemination of chemoresistant cells in the peritoneal fluid and the immunosuppressive microenvironment in the peritoneal cavity. Here, we report that intraperitoneal administration of β-glucan and IFNγ (BI) induced robust tumor regression in clinically relevant models of metastatic OvCa. BI induced tumor regression by controlling fluid tumor burden and activating localized antitumor immunity. β-glucan alone cleared ascites and eliminated fluid tumor cells by inducing intraperitoneal clotting in the fluid and Dectin-1-Syk-dependent NETosis in the omentum. In omentum tumors, BI expanded a novel subset of immunostimulatory IL27+ macrophages and neutralizing IL27 impaired BI efficacy in vivo. Moreover, BI directly induced IL27 secretion in macrophages where single agent treatment did not. Finally, BI extended mouse survival in a chemoresistant model and significantly improved chemotherapy response in a chemo-sensitive model. In summary, we propose a new therapeutic strategy for the treatment of metastatic OvCa.

The potential clinical utility of Whole Genome Sequencing for patients with cancer: evaluation of a regional implementation of the 100,000 Genomes Project

BACKGROUND

The 100,000 Genomes Project established infrastructure for Whole Genome Sequencing (WGS) in the United Kingdom.

METHODS

A retrospective study of cancer patients recruited to the 100,000 Genomes Project by the West Midlands Genomics Medicine Centre, evaluating clinical relevance of results.

RESULTS

After excluding samples with no sequencing data (1678/4851; 34.6%), 3166 sample sets (germline and somatic) from 3067 participants were sequenced. Results of 1256 participants (41.0%) were interpreted (excluding participants who died (308/3067; 10.0%) or were clinically excluded (1503/3067; 49.0%)). Of these, 323 (25.7%) had no variants in genes which may alter management (Domain 1 genes). Of the remaining 933 participants, 552 (59.2%) had clinical recommendations made (718 recommendations in total). These included therapeutic recommendations (377/933; 40.4%), such as clinical trial, unlicensed or licensed therapies or high TMB recommendations, and germline variants warranting clinical genetics review (85/933; 9.1%). At the last follow up, 20.2% of all recommendations were followed (145/718). However, only a small proportion of therapeutic recommendations were followed (5.1%, 25/491).

CONCLUSIONS

The 100,000 Genomes Project has established infrastructure and regional experience to support personalised cancer care. The majority of those with successful sequencing had actionable variants. Ensuring GTAB recommendations are followed will maximise benefits for patients.

Genetic and therapeutic heterogeneity shape the baseline and longitudinal immune ecosystem of ovarian clear cell carcinoma

BACKGROUND

Ovarian clear cell carcinoma (OCCC) is a rare and chemo-resistant subtype of ovarian cancer. While immunotherapy has demonstrated effectiveness in some OCCC cases, the mechanisms for heterogeneous immunoreactivity and potential combinatory strategies remain unclear.

METHODS

Tumor samples from 13 patients with OCCC underwent single-cell mRNA-seq and TCR-seq to generate 1 40 683 cells transcriptome, while additionally 31 formalin-fixed paraffin-embedded samples were used for immunohistochemistry. Spatial transcriptomics of two OCCC samples and bulk RNA-seq of 58 patients were incorporated for spatial and interpatient level explorations. Serum tumor markers and radiologic images of three patients with OCCC who received combinatory VEGF and PD-1 inhibition were retrospectively analyzed.

RESULTS

OCCC exhibited a dynamic immune architecture shaped by genetic and therapeutic pressure. ARID1A mutation linked to baseline immune activation, correlated with an enrichment of neoantigen-reactive CXCL13+ CTLA4+ CD8+ T cells (p<0.001) and enhanced FASLG-FAS interactions. Recurrent OCCC was fibrotic, angiogenic, and immunosuppressive, exhibiting metabolic reprogramming towards activated activity in fatty acid metabolism. High CD36 (log-rank p=0.012, HR: 4.515) and CD47 expression (log-rank p=0.037, HR: 3.246) indicated worse progression-free survival. Treatment with bevacizumab increased intratumoral T cell infiltration and activated T cell interferon-γ signaling. Retrospective analysis of clinical cases revealed that combination therapy with anti-VEGF (vascular endothelial growth factor) and anti-PD-1 agents exerted clinical benefits in patients with OCCC with persistent, recurrent, and metastatic disease.

CONCLUSIONS

ARID1A mutation correlated with OCCC baseline immune activation. Stromal reconstruction and tumor metabolic reprogramming functioned as key processes of OCCC dynamic progression. VEGF inhibition remodeled OCCC stroma, restored T cell function and potentiated immunotherapy. CD36 and CD47 might be potential therapeutic targets for recurrent OCCC.

ClassifieR 2.0: expanding interactive gene expression-based stratification to prostate and high-grade serous ovarian cancer

BACKGROUND

Advances in transcriptional profiling methods have enabled the discovery of molecular subtypes within and across traditional tissue-based cancer classifications. Such molecular subgroups hold potential for improving patient outcomes by guiding treatment decisions and revealing physiological distinctions and targetable pathways. Computational methods for stratifying transcriptomic data into molecular subgroups are increasingly abundant. However, assigning samples to these subtypes and other transcriptionally inferred predictions is time-consuming and requires significant bioinformatics expertise. To address this need, we recently reported "ClassifieR," a flexible, interactive cloud application for the functional annotation of colorectal and breast cancer transcriptomes. Here, we report "ClassifieR 2.0" which introduces additional modules for the molecular subtyping of prostate and high-grade serous ovarian cancer (HGSOC).

RESULTS

ClassifieR 2.0 introduces ClassifieRp and ClassifieRov, two specialised modules specifically designed to address the challenges of prostate and HGSOC molecular classification. ClassifieRp includes sigInfer, a method we developed to infer commercial prognostic prostate gene expression signatures from publicly available gene-lists or indeed any user-uploaded gene-list. ClassifieRov utilizes consensus molecular subtyping methods for HGSOC, including tools like consensusOV, for accurate ovarian cancer stratification. Both modules include functionalities present in the original ClassifieR framework for estimating cellular composition, predicting transcription factor (TF) activity and single sample gene set enrichment analysis (ssGSEA).

CONCLUSIONS

ClassifieR 2.0 combines molecular subtyping of prostate cancer and HGSOC with commonly used sample annotation tools in a single, user-friendly platform, allowing scientists without bioinformatics training to explore prostate and HGSOC transcriptional data without the need for extensive bioinformatics knowledge or manual data handling to operate various packages. Our sigInfer method within ClassifieRp enables the inference of commercially available gene signatures for prostate cancer, while ClassifieRov incorporates consensus molecular subtyping for HGSOC. Overall, ClassifieR 2.0 aims to make molecular subtyping more accessible to the wider research community. This is crucial for increased understanding of the molecular heterogeneity of these cancers and developing personalised treatment strategies.

The pivotal role of ZNF384: driving the malignant behavior of serous ovarian cancer cells via the LIN28B/UBD axis

Zinc finger protein 384 (ZNF384) is a highly conserved transcribed gene associated with the development of multiple tumors, however, its role and mechanism in serous ovarian cancer (SOC) are unknown. We first confirmed that ZNF384 was abnormally highly expressed in SOC tissues by bioinformatics analysis and immunohistochemistry. We further used lentivirus packaging and transfection techniques to construct ZNF384 overexpression or knockdown cell lines, and through a series of cell function experiments, gradually verified that ZNF384 promoted a series of malignant behaviors of SOC cell proliferation, migration, and invasion. By establishing a xenotransplantation model in nude mice, it was confirmed that ZNF384 promoted the progress of SOC in vivo. Mechanistically, Overexpression of ZNF384 enhanced the transcriptional activity of Lin-28 homolog B (LIN28B), which promoted the malignant behavior of SOC cells. In addition, LIN28B could regulate the expression of the downstream factor ubiquitin D (UBD) in SOC cells, further promoting the development of SOC. This study shows that ZNF384 aggravates the malignant behavior of SOC cells through the LIN28B/UBD axis, which may be used as a diagnostic biomarker for patients with SOC.

Loss of XIST lncRNA unlocks stemness and cellular plasticity in ovarian cancer

Plasticity, a key hallmark of cancer, enables cells to transition into different states, driving tumor heterogeneity. This cellular plasticity is associated with cancer progression, treatment resistance, and relapse. Cancer stem cells (CSCs) play a central role in this process, yet the molecular factors underlying cancer cell stemness remain poorly understood. In this study, we explored the role of XIST (X-inactive specific transcript) long noncoding RNA in ovarian cancer stemness and plasticity through in silico and in vitro analyses. We found that XIST is significantly down-regulated in ovarian tumors, with low XIST expression linked to a higher stemness index and lower overall survival. Knocking down XIST in ovarian cancer cells enhanced stemness, particularly increasing mesenchymal-like CSCs, and under hypoxic conditions, it promoted epithelial-like CSC markers. Our findings suggest that XIST loss leads to CSC enrichment and cellular plasticity in ovarian cancer, pointing to potential therapeutic targets for patients with low XIST expression.

DeSide: A unified deep learning approach for cellular deconvolution of tumor microenvironment

Cellular deconvolution via bulk RNA sequencing (RNA-seq) presents a cost-effective and efficient alternative to experimental methods such as flow cytometry and single-cell RNA-seq (scRNA-seq) for analyzing the complex cellular composition of tumor microenvironments. Despite challenges due to heterogeneity within and among tumors, our innovative deep learning-based approach, DeSide, shows exceptional accuracy in estimating the proportions of 16 distinct cell types and subtypes within solid tumors. DeSide integrates biological pathways and assesses noncancerous cell types first, effectively sidestepping the issue of highly variable gene expression profiles (GEPs) associated with cancer cells. By leveraging scRNA-seq data from six cancer types and 185 cancer cell lines across 22 cancer types as references, our method introduces distinctive sampling and filtering techniques to generate a high-quality training set that closely replicates real tumor GEPs, based on The Cancer Genome Atlas (TCGA) bulk RNA-seq data. With this model and high-quality training set, DeSide outperforms existing methods in estimating tumor purity and the proportions of noncancerous cells within solid tumors. Our model precisely predicts cellular compositions across 19 cancer types from TCGA and proves its effectiveness with multiple additional external datasets. Crucially, DeSide enables the identification and analysis of combinatorial cell type pairs, facilitating the stratification of cancer patients into prognostically significant groups. This approach not only provides deeper insights into the dynamics of tumor biology but also highlights potential therapeutic targets by underscoring the importance of specific cell type or subtype interactions.

The unveiled mosaic of intra-tumor heterogeneity in ovarian cancer through spatial transcriptomic technologies: A systematic review

Epithelial ovarian cancer is a significant global health issue among women. Diagnosis and treatment pose challenges due to difficulties in predicting patient responses to therapy, primarily stemming from gaps in understanding tumor chemoresistance mechanisms. Recent advancements in transcriptomic technologies like single-cell RNA sequencing and spatial transcriptomics have greatly improved our understanding of ovarian cancer intratumor heterogeneity and tumor microenvironment composition. Spatial transcriptomics, in particular, comprises a plethora of technologies that enable the detection of hundreds of transcriptomes and their spatial distribution within a histological section, facilitating the study of cell types, states, and interactions within the tumor and its microenvironment. Studies investigating the spatial distribution of gene expression in ovarian cancer masses have identified specific features that impact prognosis and therapy outcomes. Emerging evidence suggests that specific spatial patterns of tumor cells and their immune and non-immune microenvironment significantly influence therapy response, as well as the behavior and progression of primary tumors and metastatic sites. The importance of spatially contextualizing ovarian cancer transcriptomes is underscored by these findings, which will advance our understanding and therapeutic approaches for this complex disease.

Immunological and molecular features of the tumor microenvironment of long-term survivors of ovarian cancer

BACKGROUNDDespite an overall poor prognosis, about 15% of patients with advanced-stage tubo-ovarian high-grade serous carcinoma (HGSC) survive 10 or more years after standard treatment.METHODSWe evaluated the tumor microenvironment of this exceptional, understudied group using a large international cohort enriched for long-term survivors (LTS; 10+ years; n = 374) compared with mid-term (MTS; 5-7.99 years; n = 433) and short-term survivors (STS; 2-4.99 years; n = 416). Primary tumor samples were immunostained and scored for intraepithelial and intrastromal densities of 10 immune-cell subsets (including T cells, B cells, plasma cells, myeloid cells, PD-1+ cells, and PD-L1+ cells) and epithelial content.RESULTSPositive associations with LTS compared with STS were seen for 9 of 10 immune-cell subsets. In particular, the combination of intraepithelial CD8+ T cells and intrastromal B cells showed near 5-fold increased odds of LTS compared with STS. All of these associations were stronger in tumors with high epithelial content and/or the C4/Differentiated molecular subtype, despite immune-cell densities generally being higher in tumors with low epithelial content and/or the C2/Immunoreactive molecular subtype.CONCLUSIONThe tumor microenvironment of HGSC LTS is distinguished by the intersection of T and B cell coinfiltration, high epithelial content, and C4/differentiated molecular subtype, features which may inspire new approaches to immunotherapy.FUNDINGOvarian Cancer Research Program (OCRP) of the Congressionally Directed Medical Research Program (CDMRP), U.S. Department of Defense (DOD); American Cancer Society; BC Cancer Foundation; Canada's Networks of Centres of Excellence; Canadian Cancer Society; Canadian Institutes of Health Research; Cancer Councils of New South Wales, Victoria, Queensland, South Australia, and Tasmania, Cancer Foundation of Western Australia; Cancer Institute NSW; Cancer Research UK; Deutsche Forschungsgesellschaft; ELAN Funds of the University of Erlangen-Nuremberg; Fred C. and Katherine B. Andersen Foundation; Genome BC; German Cancer Research Center; German Federal Ministry of Education and Research, Programme of Clinical Biomedical Research; Instituto de Salud Carlos III; Mayo Foundation; Minnesota Ovarian Cancer Alliance; Ministerio de Economía y Competitividad; Medical Research Council (MRC); National Center for Advancing Translational Sciences; National Health and Medical Research Council of Australia (NHMRC); Ovarian Cancer Australia; Peter MacCallum Foundation; Sydney West Translational Cancer Research Centre; Terry Fox Research Institute; The Eve Appeal (The Oak Foundation); UK National Institute for Health Research Biomedical Research Centres at the University of Cambridge; University of Pittsburgh School of Medicine; U.S. National Cancer Institute of the National Institutes of Health; VGH & UBC Hospital Foundation; Victorian Cancer Agency.

CCR7/DUSP1 signaling Axis mediates iCAF to regulates head and neck squamous cell carcinoma growth

OBJECTIVE

C-C motif chemokine receptor 7 (CCR7) significantly influences tumors onset and progression, yet its impact on the tumor microenvironment (TME) and specific mechanisms remain elusive. Inflammatory Cancer-Associated Fibroblasts (iCAF), a vital subtype of Cancer-Associated Fibroblasts (CAF), play a critical role in regulating the TME and tumor growth, though the underlying molecular mechanisms are not fully understood. This study aims to determine whether CCR7 participates in tumor regulation by iCAF and to elucidate the specific mechanisms involved.

METHODS

Differential gene analysis of CAF subtypes in CCR7 knockout and wild-type groups was conducted using single-cell data. Animal models facilitated the extraction of primary iCAF cells via flow cytometry sorting. Changes in DUSP1 expression and the efficiency of lentivirus-mediated knockdown and overexpression were examined through qPCR and Western Blot. MOC1 and MOC2 cells were co-cultured with iCAF, with subsequent validation of changes in tumor cell proliferation, migration, and invasion using CCK8, EdU, and wound healing assays. ELISA was employed to detect changes in TGF-β1 concentration in the iCAF supernatant.

RESULTS

CAF was categorized into three subtypes-myCAF, iCAF, and apCAF-based on single-cell data. Analysis revealed a significant increase in DUSP1 expression in iCAF from the CCR7 knockout group, confirmed by in vitro experiments. Co-culturing MOC1 and MOC2 cells with iCAF exhibiting lentivirus-mediated DUSP1 knockdown resulted in inhibited tumor cell proliferation, invasion, and migration. In contrast, co-culture with iCAF overexpressing DUSP1 enhanced these capabilities. Additionally, the TGF-β1 concentration in the supernatant increased in the DUSP1 knockdown iCAF group, whereas it decreased in the DUSP1 overexpression group.

CONCLUSION

The CCR7/DUSP1 signaling axis regulates tumor growth by modulating TGF-β1 secretion in iCAF.

Mapping spatial organization and genetic cell-state regulators to target immune evasion in ovarian cancer

The drivers of immune evasion are not entirely clear, limiting the success of cancer immunotherapies. Here we applied single-cell spatial and perturbational transcriptomics to delineate immune evasion in high-grade serous tubo-ovarian cancer. To this end, we first mapped the spatial organization of high-grade serous tubo-ovarian cancer by profiling more than 2.5 million cells in situ in 130 tumors from 94 patients. This revealed a malignant cell state that reflects tumor genetics and is predictive of T cell and natural killer cell infiltration levels and response to immune checkpoint blockade. We then performed Perturb-seq screens and identified genetic perturbations-including knockout of PTPN1 and ACTR8-that trigger this malignant cell state. Finally, we show that these perturbations, as well as a PTPN1/PTPN2 inhibitor, sensitize ovarian cancer cells to T cell and natural killer cell cytotoxicity, as predicted. This study thus identifies ways to study and target immune evasion by linking genetic variation, cell-state regulators and spatial biology.

Extracellular vesicles of Bacteroides uniformis induce M1 macrophage polarization and aggravate gut inflammation during weaning

Weaning process is commonly associated with gastrointestinal inflammation and dysbiosis of the intestinal microbes. In particular, the impact of gut bacteria and extracellular vesicles on the etiology of intestinal inflammation during weaning is not well understood. We have uncovered a potential link between gut inflammation and the corresponding variation of macrophage bacterial sensing and pro-inflammatory polarization during the weaning process of piglets through single-cell transcriptomic analyses. We conducted a comprehensive analysis of bacterial distribution across the gastrointestinal tract and pinpointed Bacteroides uniformis enriching in piglets undergoing weaning. Next, we found out that exposure to B. uniformis-derived extracellular vesicles (BEVs) exacerbated gut inflammation in a murine colitis model while recruiting and polarizing intestinal macrophages toward a pro-inflammatory phenotype. BEVs modulated the function of macrophages cultured in vitro by suppressing the granulocyte-macrophage colony-stimulating factor/signal transducer and activator of transcription 5/arginase 1 pathway, thereby affecting polarization toward an M1-like state. The effects of BEVs were verified both in the macrophage clearance murine model and by using an adoptive transfer assay. Our findings highlight the involvement of BEVs in facilitating the polarization of pro-inflammatory macrophages and promoting gut inflammation during weaning.

Anoikis in cell fate, physiopathology, and therapeutic interventions

The extracellular matrix (ECM) governs a wide spectrum of cellular fate processes, with a particular emphasis on anoikis, an integrin-dependent form of cell death. Currently, anoikis is defined as an intrinsic apoptosis. In contrast to traditional apoptosis and necroptosis, integrin correlates ECM signaling with intracellular signaling cascades, describing the full process of anoikis. However, anoikis is frequently overlooked in physiological and pathological processes as well as traditional in vitro research models. In this review, we summarized the role of anoikis in physiological and pathological processes, spanning embryonic development, organ development, tissue repair, inflammatory responses, cardiovascular diseases, tumor metastasis, and so on. Similarly, in the realm of stem cell research focused on the functional evolution of cells, anoikis offers a potential solution to various challenges, including in vitro cell culture models, stem cell therapy, cell transplantation, and engineering applications, which are largely based on the regulation of cell fate by anoikis. More importantly, the regulatory mechanisms of anoikis based on molecular processes and ECM signaling will provide new strategies for therapeutic interventions (drug therapy and cell-based therapy) in disease. In summary, this review provides a systematic elaboration of anoikis, thus shedding light on its future research.

CYP24A1 affected macrophage polarization through degradation of vitamin D as a candidate biomarker for ovarian cancer prognosis

Ovarian cancer (OC) is a fatal gynecological malignancy with a poor prognosis in which mitochondria-related genes are involved deeply. In this study, we aim to screen mitochondria-related genes that play a role in OC prognosis and investigate its effects. Through single-cell sequencing technology and bioinformatics analysis, including TCGA ovarian cancer data analysis, gene expression signature analysis (GES), immune infiltration analysis, Gene Ontology (GO) enrichment analysis, Gene Set Enrichment Analysis (GSEA), and Principal Component Analysis (PCA), our findings revealed that CYP24A1 regulated macrophage polarization through vitamin D (VD) degradation and served as a target gene for the second malignant subtype of OC through bioinformatics analyses. For further validation, the expression and function of CYP24A1 in OC cells was investigated. And the expression of CYP24A1 was much higher in carcinoma than in paracancerous tissue, whereas the VD content decreased in the OC cell lines with CYP24A1 overexpression. Moreover, macrophages were polarized towards M1 after the intervention of VD-treated OC cell lines and inhibited the malignant phenotypes of OC. However, the effect could be reversed by overexpressing CYP24A1, resulting in the polarization of M2 macrophages, thereby promoting tumor progression, as verified by constructing xenograft models in vitro. In conclusion, our findings suggested that CYP24A1 induced M2 macrophage polarization through interaction with VD, thus promoting the malignant progression of OC.

Cancer cell states: Lessons from ten years of single-cell RNA-sequencing of human tumors

Human tumors are intricate ecosystems composed of diverse genetic clones and malignant cell states that evolve in a complex tumor micro-environment. Single-cell RNA-sequencing (scRNA-seq) provides a compelling strategy to dissect this intricate biology and has enabled a revolution in our ability to understand tumor biology over the last ten years. Here we reflect on this first decade of scRNA-seq in human tumors and highlight some of the powerful insights gleaned from these studies. We first focus on computational approaches for robustly defining cancer cell states and their diversity and highlight some of the most common patterns of gene expression intra-tumor heterogeneity (eITH) observed across cancer types. We then discuss ambiguities in the field in defining and naming such eITH programs. Finally, we highlight critical developments that will facilitate future research and the broader implementation of these technologies in clinical settings.

Biological Functions and Therapeutic Potential of NAD+ Metabolism in Gynecological Cancers

Nicotinamide adenine dinucleotide (NAD+) is an important cofactor for both metabolic and signaling pathways, with the dysregulation of NAD+ levels acting as a driver for diseases such as neurodegeneration, cancers, and metabolic diseases. NAD+ plays an essential role in regulating the growth and progression of cancers by controlling important cellular processes including metabolism, transcription, and translation. NAD+ regulates several metabolic pathways such as glycolysis, the citric acid (TCA) cycle, oxidative phosphorylation, and fatty acid oxidation by acting as a cofactor for redox reactions. Additionally, NAD+ acts as a cofactor for ADP-ribosyl transferases and sirtuins, as well as regulating cellular ADP-ribosylation and deacetylation levels, respectively. The cleavage of NAD+ by CD38-an NAD+ hydrolase expressed on immune cells-produces the immunosuppressive metabolite adenosine. As a result, metabolizing and maintaining NAD+ levels remain crucial for the function of various cells found in the tumor microenvironment, hence its critical role in tissue homeostasis. The NAD+ levels in cells are maintained by a balance between NAD+ biosynthesis and consumption, with synthesis being controlled by the Preiss-Handler, de novo, and NAD+ salvage pathways. The primary source of NAD+ synthesis in a variety of cell types is directed by the expression of the enzymes central to the three biosynthesis pathways. In this review, we describe the role of NAD+ metabolism and its synthesizing and consuming enzymes' control of cancer cell growth and immune responses in gynecologic cancers. Additionally, we review the ongoing efforts to therapeutically target the enzymes critical for NAD+ homeostasis in gynecologic cancers.