Single-cell RNA-seq recognized the initiator of epithelial ovarian cancer recurrence

PARK2 suppresses the proliferation of high-grade serous ovarian carcinoma via inducing the proteasomal degradation of ZNF703

High-grade serous ovarian cancer (HGSC) is an aggressive disease with poor prognosis. The oncoprotein ZNF703 is implicated in driving HGSC pathogenesis, but factors regulating its abundance remain unclear. In this study, we aim to investigate the potential connection between ZNF703 dysregulation and ubiquitin-mediated protein degradation in HGSC. Bioinformatics prediction was performed using BioGRID database. HGSC representative cell lines were utilized for in vitro and in vivo studies. Results showed that ZNF703 protein was stabilized upon proteasome inhibition, suggesting a regulation via ubiquitination. The ubiquitin E3 ligase PARK2 was found to interact with ZNF703 in a dose-dependent manner, promoting its polyubiquitination and subsequent proteasomal degradation. Re-expression of PARK2 in HGSC cells led to reduced ZNF703 levels together with decreased Cyclin D1/E1 abundance and G1 cell cycle arrest. ZNF703 overexpression alone increased S phase cells, Cyclin D1/E1 levels, and xenograft tumor growth, while co-expression with PARK2 mitigated these oncogenic effects. Collectively, our findings identify ZNF703 as a bona fide substrate of PARK2, reveal a tumor suppressive function for PARK2 in attenuating ZNF703-mediated G1/S transition and HGSC growth through instigating its degradation. This study elucidates a pivotal PARK2-ZNF703 axis with therapeutic implications for targeted intervention in HGSC.

Single-cell RNA-seq reveals the transcriptional program underlying tumor progression and metastasis in neuroblastoma

Neuroblastoma (NB) is one of the most common childhood malignancies. Sixty percent of patients present with widely disseminated clinical signs at diagnosis and exhibit poor outcomes. However, the molecular mechanisms triggering NB metastasis remain largely uncharacterized. In this study, we generated a transcriptomic atlas of 15 447 NB cells from eight NB samples, including paired samples of primary tumors and bone marrow metastases. We used time-resolved analysis to chart the evolutionary trajectory of NB cells from the primary tumor to the metastases in the same patient and identified a common 'starter' subpopulation that initiates tumor development and metastasis. The 'starter' population exhibited high expression levels of multiple cell cycle-related genes, indicating the important role of cell cycle upregulation in NB tumor progression. In addition, our evolutionary trajectory analysis demonstrated the involvement of partial epithelial-to-mesenchymal transition (p-EMT) along the metastatic route from the primary site to the bone marrow. Our study provides insights into the program driving NB metastasis and presents a signature of metastasis-initiating cells as an independent prognostic indicator and potential therapeutic target to inhibit the initiation of NB metastasis.

Integrated analysis of single-cell and bulk RNA-sequencing identifies a signature based on drug response genes to predict prognosis and therapeutic response in ovarian cancer

Ovarian cancer represents a severe gynecological malignancy with a dire prognosis, underscoring the imperative need for dependable biomarkers that can accurately predict drug response and guide therapeutic choices. In this study, we harnessed online single-cell RNA sequencing (scRNAseq) and bulk RNA sequencing (RNAseq) datasets, applying the Scissor algorithm to identify cells responsive to paclitaxel. From these cells, we derived a gene signature, subsequently used to construct a prognostic model that demonstrated high sensitivity and specificity in predicting patient outcomes. Moreover, we conducted pathway and functional enrichment analyses to uncover potential molecular mechanisms driving the prognostic gene signature. This study illustrates the critical role of scRNAseq and bulk RNAseq in developing precise prognostic models for ovarian cancer, potentially transforming clinical decision-making.

Establishment of an ovarian cancer exhausted CD8+T cells-related genes model by integrated analysis of scRNA-seq and bulk RNA-seq

Ovarian cancer (OC) was the fifth leading cause of cancer death and the deadliest gynecological cancer in women. This was largely attributed to its late diagnosis, high therapeutic resistance, and a dearth of effective treatments. Clinical and preclinical studies have revealed that tumor-infiltrating CD8+T cells often lost their effector function, the dysfunctional state of CD8+T cells was known as exhaustion. Our objective was to identify genes associated with exhausted CD8+T cells (CD8TEXGs) and their prognostic significance in OC. We downloaded the RNA-seq and clinical data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. CD8TEXGs were initially identified from single-cell RNA-seq (scRNA-seq) datasets, then univariate Cox regression, the least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression were utilized to calculate risk score and to develop the CD8TEXGs risk signature. Kaplan-Meier analysis, univariate Cox regression, multivariate Cox regression, time-dependent receiver operating characteristics (ROC), nomogram, and calibration were conducted to verify and evaluate the risk signature. Gene set enrichment analyses (GSEA) in the risk groups were used to figure out the closely correlated pathways with the risk group. The role of risk score has been further explored in the homologous recombination repair deficiency (HRD), BRAC1/2 gene mutations and tumor mutation burden (TMB). A risk signature with 4 CD8TEXGs in OC was finally built in the TCGA database and further validated in large GEO cohorts. The signature also demonstrated broad applicability across various types of cancer in the pan-cancer analysis. The high-risk score was significantly associated with a worse prognosis and the risk score was proven to be an independent prognostic biomarker. The 1-, 3-, and 5-years ROC values, nomogram, calibration, and comparison with the previously published models confirmed the excellent prediction power of this model. The low-risk group patients tended to exhibit a higher HRD score, BRCA1/2 gene mutation ratio and TMB. The low-risk group patients were more sensitive to Poly-ADP-ribose polymerase inhibitors (PARPi). Our findings of the prognostic value of CD8TEXGs in prognosis and drug response provided valuable insights into the molecular mechanisms and clinical management of OC.

A distinct subset of urothelial cells with enhanced EMT features promotes chemotherapy resistance and cancer recurrence by increasing COL4A1-ITGB1 mediated angiogenesis

Drug resistance and tumor recurrence remain clinical challenges in the treatment of urothelial carcinoma (UC). However, the underlying mechanism is not fully understood. Here, we performed single-cell RNA sequencing and identified a subset of urothelial cells with epithelial-mesenchymal transition (EMT) features (EMT-UC), which is significantly correlated with chemotherapy resistance and cancer recurrence. To validate the clinical significance of EMT-UC, we constructed EMT-UC like cells by introducing overexpression of two markers, Zinc Finger E-Box Binding Homeobox 1 (ZEB1) and Desmin (DES), and examined their histological distribution characteristics and malignant phenotypes. EMT-UC like cells were mainly enriched in UC tissues from patients with adverse prognosis and exhibited significantly elevated EMT, migration and gemcitabine tolerance in vitro. However, EMT-UC was not specifically identified from tumorous tissues, certain proportion of them were also identified in adjacent normal tissues. Tumorous EMT-UC highly expressed genes involved in malignant behaviors and exhibited adverse prognosis. Additionally, tumorous EMT-UC was associated with remodeled tumor microenvironment (TME), which exhibited high angiogenic and immunosuppressive potentials compared with the normal counterparts. Furthermore, a specific interaction of COL4A1 and ITGB1 was identified to be highly enriched in tumorous EMT-UC, and in the endothelial component. Targeting the interaction of COL4A1 and ITGB1 with specific antibodies significantly suppressed tumorous angiogenesis and alleviated gemcitabine resistance of UC. Overall, our findings demonstrated that the driven force of chemotherapy resistance and recurrence of UC was EMT-UC mediated COL4A1-ITGB1 interaction, providing a potential target for future UC treatment.

Therapy-induced secretion of spliceosomal components mediates pro-survival crosstalk between ovarian cancer cells

Ovarian cancer often develops resistance to conventional therapies, hampering their effectiveness. Here, using ex vivo paired ovarian cancer ascites obtained before and after chemotherapy and in vitro therapy-induced secretomes, we show that molecules secreted by ovarian cancer cells upon therapy promote cisplatin resistance and enhance DNA damage repair in recipient cancer cells. Even a short-term incubation of chemonaive ovarian cancer cells with therapy-induced secretomes induces changes resembling those that are observed in chemoresistant patient-derived tumor cells after long-term therapy. Using integrative omics techniques, we find that both ex vivo and in vitro therapy-induced secretomes are enriched with spliceosomal components, which relocalize from the nucleus to the cytoplasm and subsequently into the extracellular vesicles upon treatment. We demonstrate that these molecules substantially contribute to the phenotypic effects of therapy-induced secretomes. Thus, SNU13 and SYNCRIP spliceosomal proteins promote therapy resistance, while the exogenous U12 and U6atac snRNAs stimulate tumor growth. These findings demonstrate the significance of spliceosomal network perturbation during therapy and further highlight that extracellular signaling might be a key factor contributing to the emergence of ovarian cancer therapy resistance.

DCRELM: dual correlation reduction network-based extreme learning machine for single-cell RNA-seq data clustering

Single-cell ribonucleic acid sequencing (scRNA-seq) is a high-throughput genomic technique that is utilized to investigate single-cell transcriptomes. Cluster analysis can effectively reveal the heterogeneity and diversity of cells in scRNA-seq data, but existing clustering algorithms struggle with the inherent high dimensionality, noise, and sparsity of scRNA-seq data. To overcome these limitations, we propose a clustering algorithm: the Dual Correlation Reduction network-based Extreme Learning Machine (DCRELM). First, DCRELM obtains the low-dimensional and dense result features of scRNA-seq data in an extreme learning machine (ELM) random mapping space. Second, the ELM graph distortion module is employed to obtain a dual view of the resulting features, effectively enhancing their robustness. Third, the autoencoder fusion module is employed to learn the attributes and structural information of the resulting features, and merge these two types of information to generate consistent latent representations of these features. Fourth, the dual information reduction network is used to filter the redundant information and noise in the dual consistent latent representations. Last, a triplet self-supervised learning mechanism is utilized to further improve the clustering performance. Extensive experiments show that the DCRELM performs well in terms of clustering performance and robustness. The code is available at https://github.com/gaoqingyun-lucky/awesome-DCRELM .

Metastasis-associated fibroblasts in peritoneal surface malignancies

Over decades, peritoneal surface malignancies (PSMs) have been associated with limited treatment options and poor prognosis. However, advancements in perioperative systemic chemotherapy, cytoreductive surgery (CRS), and hyperthermic intraperitoneal chemotherapy (HIPEC) have significantly improved clinical outcomes. PSMs predominantly result from the spread of intra-abdominal neoplasia, which then form secondary peritoneal metastases. Colorectal, ovarian, and gastric cancers are the most common contributors. Despite diverse primary origins, the uniqueness of the peritoneum microenvironment shapes the common features of PSMs. Peritoneal metastization involves complex interactions between tumour cells and the peritoneal microenvironment. Fibroblasts play a crucial role, contributing to tumour development, progression, and therapy resistance. Peritoneal metastasis-associated fibroblasts (MAFs) in PSMs exhibit high heterogeneity. Single-cell RNA sequencing technology has revealed that immune-regulatory cancer-associated fibroblasts (iCAFs) seem to be the most prevalent subtype in PSMs. In addition, other major subtypes as myofibroblastic CAFs (myCAFs) and matrix CAFs (mCAFs) were frequently observed across PSMs studies. Peritoneal MAFs are suggested to originate from mesothelial cells, submesothelial fibroblasts, pericytes, endothelial cells, and omental-resident cells. This plasticity and heterogeneity of CAFs contribute to the complex microenvironment in PSMs, impacting treatment responses. Understanding these interactions is crucial for developing targeted and local therapies to improve PSMs patient outcomes.

Single-cell transcriptome analysis of macrophage subpopulations contributing to chemotherapy resistance in ovarian cancer

BACKGROUND

Ovarian cancer, a fatal gynecological malignancy, is primarily managed through surgery and chemotherapy. However, a significant challenge arises as patients frequently experience relapse due to chemotherapy resistance. This study delves into the complex functions and underlying mechanisms of macrophages in chemotherapy resistance in ovarian cancer.

METHOD

The single-cell transcriptome sequencing data of ovarian cancer with or without chemotherapy were analyzed. Then, corresponding cell types were identified, and macrophages were extracted from all cells. Following the standardized single-cell analysis using the Seurat package, 15 distinct macrophage clusters were found and differentially expressed genes among them were analyzed. Moreover, their association with chemotherapy resistance was explored through cell proportions and gene expression.

RESULT

In the single-cell transcriptomic analysis of ovarian cancer tissues before and after chemotherapy, the cellular proportion of CXCL5+ macrophages, THBS1+ macrophages, and MMP9+ macrophages were significantly increased following chemotherapy. Further investigation revealed that these macrophage subpopulations upregulated the expression of multiple pro-tumorigenic angiogenic or invasive factors, in addition to CXCL5, THBS1, and MMP9, including CTSL, CXCL1, and CCL18. Finally, pathway enrichment analysis revealed the significant activation of signaling pathways, such as NOD-like receptor, MAPK, and TNF in these macrophage subpopulations, which provides direction for studying the mechanism of these subpopulations.

CONCLUSION

CXCL5+, THBS1+, and MMP9+ macrophage subpopulations exhibit an increased cellular prevalence post-chemotherapy and pro-tumorigenic molecular expression profiles, suggesting a close association with chemoresistance in ovarian cancer. These findings contribute to our understanding of the roles and mechanisms of macrophages in ovarian cancer chemoresistance, providing a theoretical basis and direction for the development of therapies targeting macrophages in overcoming ovarian cancer chemoresistance.

Spatiotemporal architecture of immune cells and cancer-associated fibroblasts in high-grade serous ovarian carcinoma

High-grade serous ovarian carcinoma (HGSOC), the deadliest form of ovarian cancer, is typically diagnosed after it has metastasized and often relapses after standard-of-care platinum-based chemotherapy, likely due to advanced tumor stage, heterogeneity, and immune evasion and tumor-promoting signaling from the tumor microenvironment. To understand how spatial heterogeneity contributes to HGSOC progression and early relapse, we profiled an HGSOC tissue microarray of patient-matched longitudinal samples from 42 patients. We found spatial patterns associated with early relapse, including changes in T cell localization, malformed tertiary lymphoid structure (TLS)-like aggregates, and increased podoplanin-positive cancer-associated fibroblasts (CAFs). Using spatial features to compartmentalize the tissue, we found that plasma cells distribute in two different compartments associated with TLS-like aggregates and CAFs, and these distinct microenvironments may account for the conflicting reports about the role of plasma cells in HGSOC prognosis.

Cancer-associated fibroblasts: a versatile mediator in tumor progression, metastasis, and targeted therapy

Tumor microenvironment (TME) has been demonstrated to play a significant role in tumor initiation, progression, and metastasis. Cancer-associated fibroblasts (CAFs) are the major component of TME and exhibit heterogeneous properties in their communication with tumor cells. This heterogeneity of CAFs can be attributed to various origins, including quiescent fibroblasts, mesenchymal stem cells (MSCs), adipocytes, pericytes, endothelial cells, and mesothelial cells. Moreover, single-cell RNA sequencing has identified diverse phenotypes of CAFs, with myofibroblastic CAFs (myCAFs) and inflammatory CAFs (iCAFs) being the most acknowledged, alongside newly discovered subtypes like antigen-presenting CAFs (apCAFs). Due to these heterogeneities, CAFs exert multiple functions in tumorigenesis, cancer stemness, angiogenesis, immunosuppression, metabolism, and metastasis. As a result, targeted therapies aimed at the TME, particularly focusing on CAFs, are rapidly developing, fueling the promising future of advanced tumor-targeted therapy.

Altered tumor signature and T-cell profile after chemotherapy reveal new therapeutic opportunities in high-grade serous ovarian carcinoma

Chemotherapy combined with debulking surgery is the standard treatment protocol for high-grade serous ovarian carcinoma (HGSOC). Nonetheless, a significant number of patients encounter relapse due to the development of chemotherapy resistance. To better understand and address this resistance, we conducted a comprehensive study investigating the transcriptional alterations at the single-cell resolution in tissue samples from patients with HGSOC, using single-cell RNA sequencing and T-cell receptor sequencing techniques. Our analyses unveiled notable changes in the tumor signatures after chemotherapy, including those associated with epithelial-mesenchymal transition and cell cycle arrest. Within the immune compartment, we observed alterations in the T-cell profiles, characterized by naïve or pre-exhausted populations following chemotherapy. This phenotypic change was further supported by the examination of adjoining T-cell receptor clonotypes in paired longitudinal samples. These findings underscore the profound impact of chemotherapy on reshaping the tumor landscape and the immune microenvironment. This knowledge may provide clues for the development of future therapeutic strategies to combat treatment resistance in HGSOC.

Single-cell transcriptome analysis of epithelial, immune, and stromal signatures and interactions in human ovarian cancer

A comprehensive investigation of ovarian cancer (OC) progression at the single-cell level is crucial for enhancing our understanding of the disease, as well as for the development of better diagnoses and treatments. Here, over half a million single-cell transcriptome data were collected from 84 OC patients across all clinical stages. Through integrative analysis, we identified heterogeneous epithelial-immune-stromal cellular compartments and their interactions in the OC microenvironment. The epithelial cells displayed clinical subtype features with functional variance. A significant increase in distinct T cell subtypes was identified including Tregs and CD8+ exhausted T cells from stage IC2. Additionally, we discovered antigen-presenting cancer-associated fibroblasts (CAFs), with myofibroblastic CAFs (myCAFs) exhibiting enriched extracellular matrix (ECM) functionality linked to tumor progression at stage IC2. Furthermore, the NECTIN2-TIGIT ligand-receptor pair was identified to mediate T cells communicating with epithelial, fibroblast, endothelial, and other cell types. Knock-out of NECTIN2 using CRISPR/Cas9 inhibited ovarian cancer cell (SKOV3) proliferation, and increased T cell proliferation when co-cultured. These findings shed light on the cellular compartments and functional aspects of OC, providing insights into the molecular mechanisms underlying stage IC2 and potential therapeutic strategies for OC.

Exploring the tumor micro-environment in primary and metastatic tumors of different ovarian cancer histotypes

Ovarian cancer is a highly heterogeneous disease consisting of at least five different histological subtypes with varying clinical features, cells of origin, molecular composition, risk factors, and treatments. While most single-cell studies have focused on High grade serous ovarian cancer, a comprehensive landscape of the constituent cell types and their interactions within the tumor microenvironment are yet to be established in the different ovarian cancer histotypes. Further characterization of tumor progression, metastasis, and various histotypes are also needed to connect molecular signatures to pathological grading for personalized diagnosis and tailored treatment. In this study, we leveraged high-resolution single-cell RNA sequencing technology to elucidate the cellular compositions on 21 solid tumor samples collected from 12 patients with six ovarian cancer histotypes and both primary (ovaries) and metastatic (omentum, rectum) sites. The diverse collection allowed us to deconstruct the histotypes and tumor site-specific expression patterns of cells in the tumor, and identify key marker genes and ligand-receptor pairs that are active in the ovarian tumor microenvironment. Our findings can be used in improving precision disease stratification and optimizing treatment options.

Prediction of Chemoresistance-How Preclinical Data Could Help to Modify Therapeutic Strategy in High-Grade Serous Ovarian Cancer

High-grade serous ovarian cancer (HGSOC) is one of the most lethal tumors generally and the most fatal cancer of the female genital tract. The approved standard therapy consists of surgical cytoreduction and platinum/taxane-based chemotherapy, and of targeted therapy in selected patients. The main therapeutic problem is chemoresistance of recurrent and metastatic HGSOC tumors which results in low survival in the group of FIGO III/IV. Therefore, the prediction and monitoring of chemoresistance seems to be of utmost importance for the improvement of HGSOC management. This type of cancer has genetic heterogeneity with several subtypes being characterized by diverse gene signatures and disturbed peculiar epigenetic regulation. HGSOC develops and metastasizes preferentially in the specific intraperitoneal environment composed mainly of fibroblasts, adipocytes, and immune cells. Different HGSOC subtypes could be sensitive to distinct sets of drugs. Moreover, primary, metastatic, and recurrent tumors are characterized by an individual biology, and thus diverse drug responsibility. Without a precise identification of the tumor and its microenvironment, effective treatment seems to be elusive. This paper reviews tumor-derived genomic, mutational, cellular, and epigenetic biomarkers of HGSOC drug resistance, as well as tumor microenvironment-derived biomarkers of chemoresistance, and discusses their possible use in the novel complex approach to ovarian cancer therapy and monitoring.

Unveiling the novel immune and molecular signatures of ovarian cancer: insights and innovations from single-cell sequencing

Ovarian cancer is a highly heterogeneous and lethal malignancy with limited treatment options. Over the past decade, single-cell sequencing has emerged as an advanced biological technology capable of decoding the landscape of ovarian cancer at the single-cell resolution. It operates at the level of genes, transcriptomes, proteins, epigenomes, and metabolisms, providing detailed information that is distinct from bulk sequencing methods, which only offer average data for specific lesions. Single-cell sequencing technology provides detailed insights into the immune and molecular mechanisms underlying tumor occurrence, development, drug resistance, and immune escape. These insights can guide the development of innovative diagnostic markers, therapeutic strategies, and prognostic indicators. Overall, this review provides a comprehensive summary of the diverse applications of single-cell sequencing in ovarian cancer. It encompasses the identification and characterization of novel cell subpopulations, the elucidation of tumor heterogeneity, the investigation of the tumor microenvironment, the analysis of mechanisms underlying metastasis, and the integration of innovative approaches such as organoid models and multi-omics analysis.

Single-cell RNA sequencing reveals a pro-metastatic subpopulation and the driver transcription factor NFE2L1 in ovarian cancer cells

BACKGROUND

Although cytoreductive surgery followed by adjuvant chemotherapy is effective as a standard treatment for early-stage ovarian cancer, the majority of ovarian cancer cases are diagnosed at the advanced stages with dissemination to the peritoneal cavity, leading to a poor prognosis. Therefore, it is crucial to understand the cellular and molecular mechanisms underlying metastasis and identify novel therapeutic targets.

OBJECTIVE

In this study, we aimed to elucidate the mechanisms underlying gene expression alterations during the acquisition of metastatic potential and characterize the metastatic subpopulations within ovarian cancer cells.

METHODS

We conducted single-cell RNA sequencing of two human ovarian cancer cell lines: SKOV-3 and SKOV-3-13, a highly metastatic subclone of SKOV-3. Suppression of NFE2L1 expression was performed through siRNA-mediated knockdown and CRISPR-Cas9-mediated knockout.

RESULTS

Clustering and pseudotime trajectory analysis revealed pro-metastatic subpopulation within these cells. Furthermore, gene set enrichment analysis and prognosis analysis indicated that NFE2L1 could be a key transcription factor in the acquisition of metastasis potential. Inhibition of NFE2L1 significantly reduced migration and viability of both cells. In addition, NFE2L1 knockout cells exhibited significantly reduced tumor growth in a mouse xenograft model, recapitulating in silico and in vitro results.

CONCLUSION

The results presented in this study deepen our understanding of the molecular pathogenesis of ovarian cancer metastasis with the ultimate goal of developing treatments targeting pro-metastatic subclones prior to metastasis.

Molecular typing and prognostic risk models for ovarian cancer: a study based on cell differentiation trajectory

Ovarian cancer is a heterogeneous disease with different molecular phenotypes. We performed molecular typing of ovarian cancer using cell differentiation trajectory analysis and proposed a prognostic risk scoring model. Using the copy number variation provided by inferCNV, we identified malignant tumor cells. Then, ovarian cancer samples were divided into four subtypes based on differentiation-related genes (DRGs). There were significant differences in survival rates, clinical features, tumor microenvironment scores, and the expression levels of ICGs among the subtypes. Based on nine DRGs, a prognostic risk score model was generated (AUC at 1 year: 0.749; 3 years: 0.651). Then we obtained a nomogram of the prognostic variable combination, including risk scores and clinicopathological characteristics, and predicted the 1-, 3- and 5-year overall survival. Finally, we explored some issues of immune escape using the established risk model. Our study demonstrates the significant influence of cell differentiation on predicting prognosis in OV patients and provides new insights for OV treatment and potential immunotherapeutic strategies.

"DEPHENCE" system-a novel regimen of therapy that is urgently needed in the high-grade serous ovarian cancer-a focus on anti-cancer stem cell and anti-tumor microenvironment targeted therapies

Ovarian cancer, especially high-grade serous type, is the most lethal gynecological malignancy. The lack of screening programs and the scarcity of symptomatology result in the late diagnosis in about 75% of affected women. Despite very demanding and aggressive surgical treatment, multiple-line chemotherapy regimens and both approved and clinically tested targeted therapies, the overall survival of patients is still unsatisfactory and disappointing. Research studies have recently brought some more understanding of the molecular diversity of the ovarian cancer, its unique intraperitoneal biology, the role of cancer stem cells, and the complexity of tumor microenvironment. There is a growing body of evidence that individualization of the treatment adjusted to the molecular and biochemical signature of the tumor as well as to the medical status of the patient should replace or supplement the foregoing therapy. In this review, we have proposed the principles of the novel regimen of the therapy that we called the "DEPHENCE" system, and we have extensively discussed the results of the studies focused on the ovarian cancer stem cells, other components of cancer metastatic niche, and, finally, clinical trials targeting these two environments. Through this, we have tried to present the evolving landscape of treatment options and put flesh on the experimental approach to attack the high-grade serous ovarian cancer multidirectionally, corresponding to the "DEPHENCE" system postulates.

Screening and Identification of a Prognostic Model of Ovarian Cancer by Combination of Transcriptomic and Proteomic Data

The integration of transcriptome and proteome analysis can lead to the discovery of a myriad of biological insights into ovarian cancer. Proteome, clinical, and transcriptome data about ovarian cancer were downloaded from TCGA's database. A LASSO-Cox regression was used to uncover prognostic-related proteins and develop a new protein prognostic signature for patients with ovarian cancer to predict their prognosis. Patients were brought together in subgroups using a consensus clustering analysis of prognostic-related proteins. To further investigate the role of proteins and protein-coding genes in ovarian cancer, additional analyses were performed using multiple online databases (HPA, Sangerbox, TIMER, cBioPortal, TISCH, and CancerSEA). The final resulting prognosis factors consisted of seven protective factors (P38MAPK, RAB11, FOXO3A, AR, BETACATENIN, Sox2, and IGFRb) and two risk factors (AKT_pS473 and ERCC5), which can be used to construct a prognosis-related protein model. A significant difference in overall survival (OS), disease-free interval (DFI), disease-specific survival (DSS), and progression-free interval (PFI) curves were found in the training, testing, and whole sets when analyzing the protein-based risk score (p < 0.05). We also illustrated a wide range of functions, immune checkpoints, and tumor-infiltrating immune cells in prognosis-related protein signatures. Additionally, the protein-coding genes were significantly correlated with each other. EMTAB8107 and GSE154600 single-cell data revealed that the genes were highly expressed. Furthermore, the genes were related to tumor functional states (angiogenesis, invasion, and quiescence). We reported and validated a survivability prediction model for ovarian cancer based on prognostic-related protein signatures. A strong correlation was found between the signatures, tumor-infiltrating immune cells, and immune checkpoints. The protein-coding genes were highly expressed in single-cell RNA and bulk RNA sequencing, correlating with both each other and tumor functional states.

Single-cell RNA sequencing reveals cell landscape following antimony exposure during spermatogenesis in Drosophila testes

Antimony (Sb), is thought to induce testicular toxicity, although this remains controversial. This study investigated the effects of Sb exposure during spermatogenesis in the Drosophila testis and the underlying transcriptional regulatory mechanism at single-cell resolution. Firstly, we found that flies exposed to Sb for 10 days led to dose-dependent reproductive toxicity during spermatogenesis. Protein expression and RNA levels were measured by immunofluorescence and quantitative real-time PCR (qRT-PCR). Single-cell RNA sequencing (scRNA-seq) was performed to characterize testicular cell composition and identify the transcriptional regulatory network after Sb exposure in Drosophila testes. scRNA-seq analysis revealed that Sb exposure influenced various testicular cell populations, especially in GSCs_to_Early_Spermatogonia and Spermatids clusters. Importantly, carbon metabolism was involved in GSCs/early spermatogonia maintenance and positively related with SCP-Containing Proteins, S-LAPs, and Mst84D signatures. Moreover, Seminal Fluid Proteins, Mst57D, and Serpin signatures were highly positively correlated with spermatid maturation. Pseudotime trajectory analysis revealed three novel states for the complexity of germ cell differentiation, and many novel genes (e.g., Dup98B) were found to be expressed in state-biased manners during spermatogenesis. Collectively, this study indicates that Sb exposure negatively impacts GSC maintenance and spermatid elongation, damaging spermatogenesis homeostasis via multiple signatures in Drosophila testes and therefore supporting Sb-mediated testicular toxicity.

VSELs and OSCs together sustain oogenesis in adult ovaries and their dysfunction results in age-related senescence, PCOS, POI and cancer

Multiple studies using single-cell RNA sequencing (scRNAseq) have failed to detect stem cells in adult ovaries. We have maintained that two populations of ovarian stem cells including pluripotent, very small embryonic-like stem cells (VSELs) and tissue-committed 'progenitors' termed ovarian stem cells (OSCs) can easily be detected in Hematoxylin and Eosin-stained ovary surface epithelial (OSE) cells smears prepared from both mice and human ovaries. Most likely the stem cells never get subjected to scRNAseq since they pellet down only by centrifuging cells suspension at 1000 g while cells for scRNAseq were invariably prepared by centrifuging at 200-400 g. A recent article provided further explanation for the failure of scRNAseq to detect ovarian stem cells. Extensive reanalysis of data (generated by scRNAseq) using an advanced software successfully detected OSCs and meiotic markers supporting neo-oogenesis in adult human ovaries. But this article remained critical on the biological relevance of VSELs and their relationship with OSCs. By carefully studying the OSE cells smears (which hold VSELs, OSCs and germ cell nests GCNs), prepared by partial trypsin digestion of intact mice ovaries during different stages of estrus cycle, we have successfully delineated novel functions of VSELs/OSCs in vivo under physiological conditions. VSELs undergo asymmetrical divisions to self-renew and give rise to slightly bigger OSCs which in turn undergo symmetrical divisions and clonal expansion to form GCNs, regular neo-oogenesis and follicle assembly. GCNs have been earlier described in fetal ovaries and during OSE cells culture (from adult ovaries) in response to FSH treatment. Dysfunction of VSELs/OSCs (which express ERα, ERβ, FSHR) due to neonatal exposure to endocrine disruption results in ovarian insufficiency and polycystic ovaries. VSELs have also been implicated in ovarian cancer. Age-related ovarian senescence/menopause is also due to dysfunction and blocked differentiation of VSELs/OSCs. These novel findings in vivo along with abundant in vitro and lineage tracing studies data in published literature provides huge scope for further research, offers novel avenues to manage ovarian pathologies and calls for re-writing of textbooks.

Expression level of CD117 (KIT) on ovarian cancer extracellular vesicles correlates with tumor aggressiveness

Ovarian cancer is known to be the most lethal malignancy among all gynecological cancers affecting a large number of women worldwide. The treatment of ovarian cancer is challenging due to the high recurrence rate of the disease and is further complicated by acquired chemoresistance. Most ovarian cancer deaths are the result of the metastatic spread of drug-resistant cells. The theory of cancer stem cells (CSC) suggests that both tumor initiation and progression are driven by a population of undifferentiated capable of self-renewal, tumor initiation and development of chemoresistance. The CD117 mast/stem cell growth factor receptor (KIT) is the most commonly used marker for ovarian CSCs. Here, we analyze the correlation between CD117 expression and histological tumor type in ovarian cancer cell lines (SK-OV-3 and MES-OV) and in small/medium extracellular vesicles (EVs) isolated from the urine of ovarian cancer patients. We have demonstrated that the abundance of CD117 on cells and EVs is correlated with tumor grade and therapy resistance status. Moreover, using small EVs isolated from ovarian cancer ascites, it was shown that recurrent disease is characterized by a much higher abundance of CD117 on EVs than primary tumor.

Single-cell analysis reveals that Jinwu Gutong capsule attenuates the inflammatory activity of synovial cells in osteoarthritis by inhibiting AKR1C3

Jinwu Gutong capsule (JGC) is a traditional Chinese medicine formula for the treatment of osteoarthritis (OA). Synovitis is a typical pathological change in OA and promotes disease progression. Elucidating the therapeutic mechanism of JGC is crucial for the precise treatment of OA synovitis. In this study, we demonstrate that JGC effectively inhibits hyperproliferation, attenuates inflammation, and promotes apoptosis of synovial cells. Through scRNA-seq data analysis of OA synovitis, we dissected two distinct cell fates that influence disease progression (one fate led to recovery while the other fate resulted in deterioration), which illustrates the principles of fate determination. By intersecting JGC targets with synovitis hub genes and then mimicking picomolar affinity interactions between bioactive compounds and binding pockets, we found that the quercetin-AKR1C3 pair exhibited the best affinity, indicating that this pair constitutes the most promising molecular mechanism. In vitro experiments confirmed that the expression of AKR1C3 in synovial cells was reduced after JGC addition. Further overexpression of AKR1C3 significantly attenuated the therapeutic efficacy of JGC. Thus, we revealed that JGC effectively treats OA synovitis by inhibiting AKR1C3 expression.

Hexokinase 2 promoted cell motility and proliferation by activating Akt1/p-Akt1 in human ovarian cancer cells

Background

Recently, increasing evidence has indicated that elevation of Hexokinase 2 (HK2) plays an important role in several cancers on regulating cell motility and growth. However, its role on regulating cell EMT in human ovarian cancer still less to known.

Methods

The transwell and wound-healing assay were used to detect the effective of HK2 on regulating motility of ovarian cancer cells. Real Time PCR and Western Blotting were used to explore the changing of EMT-related proteins in HK2-modified cells. The clonogenic formation, cell growth curves and MTT assays were used to evaluate the effective of HK2 on regulating cell proliferation in HK2-modified cells. The flow cytometry was used to detect the differences in the distribution of cells in the cell cycle between the HK2-modified cells and their control cells. The correlation of HK2 and Akt1/p-Akt1 was explored by using Western Blotting, Akt1 inhibitor (MK2206) and transient transfection of an Akt1 recombinant plasmid. The potential correlation between HK2 and EMT-related proteins in human ovarian cancer tissues and OV (ovarian serous cystadenocarcinoma) was confirmed by using Pearson correlation analysis and TIMER 2.0.

Results

In ovarian cancer cells, overexpressing of HK2 enhanced cell motility by inducing of EMT-related proteins, such as CDH2, fibronectin, MMP9, ZEB1, ZEB2 and vimentin. Moreover, overexpressing of HK2 promoted cell growth by reducing p21 and p27 expression in ovarian cancer cells. Further studies demonstrated that this promotion of cell motility and growth by HK2 was probably a result of it activating of Akt1 (p-Akt1) in ovarian cancer cells. Additionally, the positive correlation between HK2 and p-Akt1, fibronectin, MMP9 expression in human ovarian cancer samples was verified by using Pearson correlation analysis. The positive correlation between HK2 and CDH2, fibronectin, MMP9, ZEB1, ZEB2 and vimentin in OV (ovarian serous cystadenocarcinoma) was confirmed by using TIMER 2.0.

Conclusion

This study demonstrated that HK2 could induce EMT-related proteins and reduce cell cycle inhibitor by activating Akt1 in human ovarian cancer cells, subsequently enhancing cell motility and growth, suggesting that HK2 participate in the malignant process of ovarian cancer by interacting with Akt1.

Single-cell analysis of a high-grade serous ovarian cancer cell line reveals transcriptomic changes and cell subpopulations sensitive to epigenetic combination treatment

Ovarian cancer (OC) is a lethal gynecological malignancy with a five-year survival rate of only 46%. Development of resistance to platinum-based chemotherapy is a common cause of high mortality rates among OC patients. Tumor and transcriptomic heterogeneity are drivers of platinum resistance in OC. Platinum-based chemotherapy enriches for ovarian cancer stem cells (OCSCs) that are chemoresistant and contribute to disease recurrence and relapse. Studies examining the effect of different treatments on subpopulations of HGSOC cell lines are limited. Having previously demonstrated that combined treatment with an enhancer of zeste homolog 2 inhibitor (EZH2i) and a RAC1 GTPase inhibitor (RAC1i) inhibited survival of OCSCs, we investigated EZH2i and RAC1i combination effects on HGSOC heterogeneity using single cell RNA sequencing. We demonstrated that RAC1i reduced expression of stemness and early secretory marker genes, increased expression of an intermediate secretory marker gene and induced inflammatory gene expression. Importantly, RAC1i alone and in combination with EZH2i significantly reduced oxidative phosphorylation and upregulated Sirtuin signaling pathways. Altogether, we demonstrated that combining a RAC1i with an EZH2i promoted differentiation of subpopulations of HGSOC cells, supporting the future development of epigenetic drug combinations as therapeutic approaches in OC.

Comparing the Secretomes of Chemorefractory and Chemoresistant Ovarian Cancer Cell Populations

High-grade serous ovarian cancer (HGSOC) constitutes the majority of all ovarian cancer cases and has staggering rates of both refractory and recurrent disease. While most patients respond to the initial treatment with paclitaxel and platinum-based drugs, up to 25% do not, and of the remaining that do, 75% experience disease recurrence within the subsequent two years. Intrinsic resistance in refractory cases is driven by environmental stressors like tumor hypoxia which alter the tumor microenvironment to promote cancer progression and resistance to anticancer drugs. Recurrent disease describes the acquisition of chemoresistance whereby cancer cells survive the initial exposure to chemotherapy and develop adaptations to enhance their chances of surviving subsequent treatments. Of the environmental stressors cancer cells endure, exposure to hypoxia has been identified as a potent trigger and priming agent for the development of chemoresistance. Both in the presence of the stress of hypoxia or the therapeutic stress of chemotherapy, cancer cells manage to cope and develop adaptations which prime populations to survive in future stress. One adaptation is the modification in the secretome. Chemoresistance is associated with translational reprogramming for increased protein synthesis, ribosome biogenesis, and vesicle trafficking. This leads to increased production of soluble proteins and extracellular vesicles (EVs) involved in autocrine and paracrine signaling processes. Numerous studies have demonstrated that these factors are largely altered between the secretomes of chemosensitive and chemoresistant patients. Such factors include cytokines, growth factors, EVs, and EV-encapsulated microRNAs (miRNAs), which serve to induce invasive molecular, biophysical, and chemoresistant phenotypes in neighboring normal and cancer cells. This review examines the modifications in the secretome of distinct chemoresistant ovarian cancer cell populations and specific secreted factors, which may serve as candidate biomarkers for aggressive and chemoresistant cancers.