Characterizing the tumor microenvironment of metastatic ovarian cancer by single-cell transcriptomics

Single-cell resolution characterization of myeloid-derived cell states with implication in cancer outcome

Tumor-associated myeloid-derived cells (MDCs) significantly impact cancer prognosis and treatment responses due to their remarkable plasticity and tumorigenic behaviors. Here, we integrate single-cell RNA-sequencing data from different cancer types, identifying 29 MDC subpopulations within the tumor microenvironment. Our analysis reveals abnormally expanded MDC subpopulations across various tumors and distinguishes cell states that have often been grouped together, such as TREM2+ and FOLR2+ subpopulations. Using deconvolution approaches, we identify five subpopulations as independent prognostic markers, including states co-expressing TREM2 and PD-1, and FOLR2 and PDL-2. Additionally, TREM2 alone does not reliably predict cancer prognosis, as other TREM2+ macrophages show varied associations with prognosis depending on local cues. Validation in independent cohorts confirms that FOLR2-expressing macrophages correlate with poor clinical outcomes in ovarian and triple-negative breast cancers. This comprehensive MDC atlas offers valuable insights and a foundation for futher analyses, advancing strategies for treating solid cancers.

TCF1-positive and TCF1-negative TRM CD8 T cell subsets and cDC1s orchestrate melanoma protection and immunotherapy response

BACKGROUND

Melanoma, the most lethal form of skin cancer, has undergone a transformative treatment shift with the advent of checkpoint blockade immunotherapy (CBI). Understanding the intricate network of immune cells infiltrating the tumor and orchestrating the control of melanoma cells and the response to CBI is currently of utmost importance. There is evidence underscoring the significance of tissue-resident memory (TRM) CD8 T cells and classic dendritic cell type 1 (cDC1) in cancer protection. Transcriptomic studies also support the existence of a TCF7+ (encoding TCF1) T cell as the most important for immunotherapy response, although uncertainty exists about whether there is a TCF1+TRM T cell due to evidence indicating TCF1 downregulation for tissue residency activation.

METHODS

We used multiplexed immunofluorescence and spectral flow cytometry to evaluate TRM CD8 T cells and cDC1 in two melanoma patient cohorts: one immunotherapy-naive and the other receiving immunotherapy. The first cohort was divided between patients free of disease or with metastasis 2 years postdiagnosis while the second between CBI responders and non-responders.

RESULTS

Our study identifies two CD8+TRM subsets, TCF1+ and TCF1-, correlating with melanoma protection. TCF1+TRM cells show heightened expression of IFN-γ and Ki67 while TCF1- TRM cells exhibit increased expression of cytotoxic molecules. In metastatic patients, TRM subsets undergo a shift in marker expression, with the TCF1- subset displaying increased expression of exhaustion markers. We observed a close spatial correlation between cDC1s and TRMs, with TCF1+TRM/cDC1 pairs enriched in the stroma and TCF1- TRM/cDC1 pairs in tumor areas. Notably, these TCF1- TRMs express cytotoxic molecules and are associated with apoptotic melanoma cells. Both TCF1+ and TCF1- TRM subsets, alongside cDC1, prove relevant to CBI response.

CONCLUSIONS

Our study supports the importance of TRM CD8 T cells and cDC1 in melanoma protection while also highlighting the existence of functionally distinctive TCF1+ and TCF1- TRM subsets, both crucial for melanoma control and CBI response.

From monocyte-derived macrophages to resident macrophages-how metabolism leads their way in cancer

Macrophages are innate immune cells that play key roles during both homeostasis and disease. Depending on the microenvironmental cues sensed in different tissues, macrophages are known to acquire specific phenotypes and exhibit unique features that, ultimately, orchestrate tissue homeostasis, defense, and repair. Within the tumor microenvironment, macrophages are referred to as tumor-associated macrophages (TAMs) and constitute a heterogeneous population. Like their tissue resident counterpart, TAMs are plastic and can switch function and phenotype according to the niche-derived stimuli sensed. While changes in TAM phenotype are known to be accompanied by adaptive alterations in their cell metabolism, it is reported that metabolic reprogramming of macrophages can dictate their activation state and function. In line with these observations, recent research efforts have been focused on defining the metabolic traits of TAM subsets in different tumor malignancies and understanding their role in cancer progression and metastasis formation. This knowledge will pave the way to novel therapeutic strategies tailored to cancer subtype-specific metabolic landscapes. This review outlines the metabolic characteristics of distinct TAM subsets and their implications in tumorigenesis across multiple cancer types.

A developmental constraint model of cancer cell states and tumor heterogeneity

Cancer is a disease that stems from a fundamental liability inherent to multicellular life forms in which an individual cell is capable of reneging on the interests of the collective organism. Although cancer is commonly described as an evolutionary process, a less appreciated aspect of tumorigenesis may be the constraints imposed by the organism's developmental programs. Recent work from single-cell transcriptomic analyses across a range of cancer types has revealed the recurrence, plasticity, and co-option of distinct cellular states among cancer cell populations. Here, we note that across diverse cancer types, the observed cell states are proximate within the developmental hierarchy of the cell of origin. We thus posit a model by which cancer cell states are directly constrained by the organism's "developmental map." According to this model, a population of cancer cells traverses the developmental map, thereby generating a heterogeneous set of states whose interactions underpin emergent tumor behavior.

DC-derived CXCL10 promotes CTL activation to suppress ovarian cancer

This study investigates the role of dendritic cells (DCs), with a focus on their CXCL10 marker gene, in the activation of cytotoxic T lymphocytes (CTLs) within the ovarian cancer microenvironment and its impact on disease progression. Utilizing scRNA-seq data and immune infiltration analysis, we identified a diminished DC presence in ovarian cancer. Gene analysis pinpointed CXCL10 as a key regulator in OV progression via its influence on DCs and CTLs. Prognostic analysis and in vitro experiments substantiated this role. Our findings reveal that DC-derived CXCL10 significantly affects CTL activation and proliferation. Reduced CXCL10 levels hinder CTL cytotoxicity, promoting ovarian cancer cell migration and invasion. Experimental studies using animal models have provided further evidence that the capacity of CTLs to suppress tumor development is significantly diminished when treated with DCs that have low expression of CXCL10. Dendritic cell-derived CXCL10 emerges as a pivotal factor in restraining ovarian cancer growth and metastasis through the activation of cytotoxic T lymphocytes. This study sheds light on the crucial interplay within the ovarian cancer microenvironment, offering potential therapeutic targets for ovarian cancer treatment.

Unlocking ovarian cancer heterogeneity: advancing immunotherapy through single-cell transcriptomics

Ovarian cancer, a highly fatal gynecological cancer, warrants the need for understanding its heterogeneity. The disease's prevalence and impact are underscored with statistics on mortality rates. Ovarian cancer is categorized into distinct morphological groups, each with its characteristics and prognosis. Despite standard treatments, survival rates remain low due to relapses and chemoresistance. Immune system involvement is evident in ovarian cancer's progression, although the tumor employs immune evasion mechanisms. Immunotherapy, particularly immune checkpoint blockade therapy, is promising, but ovarian cancer's heterogeneity limits its efficacy. Single-cell sequencing technology could be explored as a solution to dissect the heterogeneity within tumor-associated immune cell populations and tumor microenvironments. This cutting-edge technology has the potential to enhance diagnosis, prognosis, and personalized immunotherapy in ovarian cancer, reflecting its broader application in cancer research. The present review focuses on recent advancements and the challenges in applying single-cell transcriptomics to ovarian cancer.

STING inhibitors sensitize platinum chemotherapy in ovarian cancer by inhibiting the CGAS-STING pathway in cancer-associated fibroblasts (CAFs)

Chemotherapy resistance in ovarian cancer hampers cure rates, with cancer-associated fibroblasts (CAFs) playing a pivotal role. Despite their known impact on cancer progression and chemotherapy resistance, the specific mechanism by which CAFs regulate the tumor inflammatory environment remains unclear. This study reveals that cisplatin facilitates DNA transfer from ovarian cancer cells to CAFs, activating the CGAS-STING-IFNB1 pathway in CAFs and promoting IFNB1 release. Consequently, this reinforces cancer cell resistance to platinum drugs. High STING expression in the tumor stroma was associated with a poor prognosis, while inhibiting STING expression enhanced ovarian cancer sensitivity. Understanding the relevance of the CGAS-STING pathway in CAFs for platinum resistance suggests targeting STING as a promising combination therapy for ovarian cancer, providing potential avenues for improved treatment outcomes.

ATF3 characterizes aggressive drug-tolerant persister cells in HGSOC

High-grade serous ovarian cancer (HGSOC) represents the most common and lethal subtype of ovarian cancer. Despite initial response to platinum-based standard therapy, patients commonly suffer from relapse that likely originates from drug-tolerant persister (DTP) cells. We generated isogenic clones of treatment-naïve and cisplatin-tolerant persister HGSOC cells. In addition, single-cell RNA sequencing of barcoded cells was performed in a xenograft model with HGSOC cell lines after platinum-based therapy. Published single-cell RNA-sequencing data from neo-adjuvant and non-treated HGSOC patients and patient data from TCGA were analyzed. DTP-derived cells exhibited morphological alterations and upregulation of epithelial-mesenchymal transition (EMT) markers. An aggressive subpopulation of DTP-derived cells showed high expression of the stress marker ATF3. Knockdown of ATF3 enhanced the sensitivity of aggressive DTP-derived cells to cisplatin-induced cell death, implying a role for ATF3 stress response in promoting a drug tolerant persister cell state. Furthermore, single cell lineage tracing to detect transcriptional changes in a HGSOC cell line-derived xenograft relapse model showed that cells derived from relapsed solid tumors express increased levels of EMT and multiple endoplasmic reticulum (ER) stress markers, including ATF3. Single cell RNA sequencing of epithelial cells from four HGSOC patients also identified a small cell population resembling DTP cells in all samples. Moreover, analysis of TCGA data from 259 HGSOC patients revealed a significant progression-free survival advantage for patients with low expression of the ATF3-associated partial EMT genes. These findings suggest that increased ATF3 expression together with partial EMT promote the development of aggressive DTP, and thereby relapse in HGSOC patients.

Unravelling immune microenvironment features underlying tumor progression in the single-cell era

The relationship between the immune cell and tumor occurrence and progression remains unclear. Profiling alterations in the tumor immune microenvironment (TIME) at high resolution is crucial to identify factors influencing cancer progression and enhance the effectiveness of immunotherapy. However, traditional sequencing methods, including bulk RNA sequencing, exhibit varying degrees of masking the cellular heterogeneity and immunophenotypic changes observed in early and late-stage tumors. Single-cell RNA sequencing (scRNA-seq) has provided significant and precise TIME landscapes. Consequently, this review has highlighted TIME cellular and molecular changes in tumorigenesis and progression elucidated through recent scRNA-seq studies. Specifically, we have summarized the cellular heterogeneity of TIME at different stages, including early, late, and metastatic stages. Moreover, we have outlined the related variations that may promote tumor occurrence and metastasis in the single-cell era. The widespread applications of scRNA-seq in TIME will comprehensively redefine the understanding of tumor biology and furnish more effective immunotherapy strategies.

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.

Omental preadipocytes stimulate matrix remodeling and IGF signaling to support ovarian cancer metastasis

Ovarian cancer can metastasize to the omentum, which is associated with a complex tumor microenvironment. Omental stromal cells facilitate ovarian cancer colonization by secreting cytokines and growth factors. Improved understanding of the tumor supportive functions of specific cell populations in the omentum could identify strategies to prevent and treat ovarian cancer metastasis. Here, we showed that omental preadipocytes enhance the tumor initiation capacity of ovarian cancer cells. Secreted factors from preadipocytes supported cancer cell viability during nutrient and isolation stress and enabled prolonged proliferation. Co-culturing with pre-adipocytes led to upregulation of genes involved in extracellular matrix (ECM) organization, cellular response to stress, and regulation of insulin-like growth factor (IGF) signaling in ovarian cancer cells. IGF-1 induced ECM genes and increased alternative NF-κB signaling by activating RelB. Inhibiting the IGF-1 receptor (IGF1R) initially increased tumor omental adhesion but decreased growth of established preadipocyte-induced subcutaneous tumors as well as established intraperitoneal tumors. Together, this study shows that omental preadipocytes support ovarian cancer progression, which has implications for targeting metastasis.

Spatial transcriptomics reveals discrete tumour microenvironments and autocrine loops within ovarian cancer subclones

High-grade serous ovarian carcinoma (HGSOC) is genetically unstable and characterised by the presence of subclones with distinct genotypes. Intratumoural heterogeneity is linked to recurrence, chemotherapy resistance, and poor prognosis. Here, we use spatial transcriptomics to identify HGSOC subclones and study their association with infiltrating cell populations. Visium spatial transcriptomics reveals multiple tumour subclones with different copy number alterations present within individual tumour sections. These subclones differentially express various ligands and receptors and are predicted to differentially associate with different stromal and immune cell populations. In one sample, CosMx single molecule imaging reveals subclones differentially associating with immune cell populations, fibroblasts, and endothelial cells. Cell-to-cell communication analysis identifies subclone-specific signalling to stromal and immune cells and multiple subclone-specific autocrine loops. Our study highlights the high degree of subclonal heterogeneity in HGSOC and suggests that subclone-specific ligand and receptor expression patterns likely modulate how HGSOC cells interact with their local microenvironment.

Identification of estrogen response-associated STRA6+ granulosa cells within high-grade serous ovarian carcinoma by single-cell sequencing

Background

High-grade serous ovarian carcinoma (HGSOC) is a pathologic subtype of ovarian cancer (OC) with a more lethal prognosis. Extensive heterogeneity results in HGSOC being more susceptible to treatment resistance and adverse treatment effects. Revealing the heterogeneity involved is crucial.

Methods

We downloaded the single-cell RNA-seq (scRNA) data from GEO database and performed a scRNA analysis for cell landscape of HGSOC by using the Seurat package. The highly expressed genes were uploaded into the DAVID and KEGG database for enrichment analysis, and the AUCell package was used to calculate cancer-associated hallmark score. The SCENIC analysis was used for key regulons, the estrogen response enrichment scores in TCGA-OV RNA-seq dataset were calculated by using the GSVA package. Besides, the expression of STRA6 and IRF1 and the cell invasion and migration in si-STRA6 OC cells were detected by using the quantitative reverse transcription (qRT)-PCR method and Transwell assay respectively.

Results

We successfully constructed a single-cell atlas of HGSOC and delineated the heterogeneity of epithelial cells therein. There were five epithelial cell subpopulations, GLDC + Epithelial cells, PEG3+ leydig cells, STRA6+ granulosa cells, POLE2+ Epithelial cells, and AURKA + Epithelial cells. STRA6+ granulosa cells have the potential to promote tumor growth as well as the highest estrogen response early activity through the biological pathways analysis of highly expressed genes and estrogen response score of ssGSEA. We found that IRF1 and STRA6 expression was remarkably upregulated in the OC cancer cell line HEY. Silencing of STRA6 markedly decreased the invasion and migration ability of the OC cancer cell line HEY.

Conclusion

There is extreme heterogeneity of epithelial cells in HGSOC, and STRA6+ granulosa cells may be able to promote cancer progression. Our findings are benefit to the heterogeneity identification of HGSOC and develop targeted therapy strategy for HGSOC patients.

APOC1 is a prognostic biomarker associated with M2 macrophages in ovarian cancer

BACKGROUND

Recent studies have demonstrated that APOC1 is associated with cancer progression, exerting cancer-promoting and immune infiltration-promoting effects. Nevertheless, there is currently no report on the presence of APOC1 in ovarian cancer (OV).

METHOD

In this study, we conducted data analysis using the GEO and TCGA databases. We conducted a thorough bioinformatics analysis to investigate the function of APOC1 in OV, utilizing various platforms including cBioPortal, STRING, GeneMANIA, LinkedOmics, GSCALite, TIMER, and CellMarker. Additionally, we performed immunohistochemical staining on tissue microarrays and conducted in vitro cellular assays to validate our findings.

RESULT

Our findings reveal that APOC1 expression is significantly upregulated in OV compared to normal tissues. Importantly, patients with high APOC1 levels show a significantly poorer prognosis. Furthermore, our study demonstrated that APOC1 exerted a crucial function in promoting the capacity of ovarian cancer cells to proliferate, migrate, and invade. Additionally, we have identified that genes co-expressed with APOC1 are primarily associated with adaptive immune responses. Notably, the levels of APOC1 in OV exhibit a correlation with the presence of M2 Tumor-associated Macrophages (TAMs).

CONCLUSION

APOC1 emerges as a promising prognostic biomarker for OV and exhibits a significant association with M2 TAMs in OV.

Fallopian tube single cell analysis reveals myeloid cell alterations in high-grade serous ovarian cancer

Most high-grade serous ovarian cancers (HGSCs) likely initiate from fallopian tube (FT) epithelia. While epithelial subtypes have been characterized using single-cell RNA-sequencing (scRNA-Seq), heterogeneity of other compartments and their involvement in tumor progression are poorly defined. Integrated analysis of human FT scRNA-Seq and HGSC-related tissues, including tumors, revealed greater immune and stromal transcriptional diversity than previously reported. We identified abundant monocytes in FTs across two independent cohorts. The ratio of macrophages to monocytes is similar between benign FTs, ovaries, and adjacent normal tissues but significantly greater in tumors. FT-defined monocyte and macrophage signatures, cell-cell communication, and gene set enrichment analyses identified monocyte- and macrophage-specific interactions and functional pathways in paired tumors and adjacent normal tissues. Further reanalysis of HGSC scRNA-Seq identified monocyte and macrophage subsets associated with neoadjuvant chemotherapy. Taken together, our work provides data that an altered FT myeloid cell composition could inform the discovery of early detection markers for HGSC.

Fibroblast heterogeneity and functions: insights from single-cell sequencing in wound healing, breast cancer, ovarian cancer and melanoma

Cancer has been described as the wound that does not heal, in large part due to fibroblast involvement. Activation of cancer-associated fibroblasts (CAFs) contributes to critical features of the tumor microenvironment, including upregulation of key marker proteins, recruitment of immune cells, and deposition of extracellular matrix (ECM)-similar to fibroblast activation in injury-induced wound healing. Prior to the widespread availability of single-cell RNA sequencing (scRNA seq), studies of CAFs or fibroblasts in wound healing largely relied on models guided by individual fibroblast markers, or methods with less resolution to unravel the heterogeneous nature of CAFs and wound healing fibroblasts (especially regarding scarring outcome). Here, insights from the enhanced resolution provided by scRNA sequencing of fibroblasts in normal wound healing, breast cancer, ovarian cancer, and melanoma are discussed. These data have revealed differences in expression of established canonical activation marker genes, epigenetic modifications, fibroblast lineages, new gene and proteins of clinical interest for further experimentation, and novel signaling interactions with other cell types that include spatial information.

ITGA7 loss drives the differentiation of adipose-derived mesenchymal stem cells to cancer-associated fibroblasts

Cancer-associated fibroblasts (CAFs) represent a major cellular component of the tumor (pre-)metastatic niche and play an essential role in omental dissemination of ovarian cancer. The omentum is rich in adipose, and adipose-derived mesenchymal stem cells (ADSCs) have been identified as a source of CAFs. However, the molecular events driving the phenotype shift of ADSCs remain largely unexplored. In this research, we focus on integrins, transmembrane receptors that have been widely involved in cellular plasticity. We found that integrin α7 (ITGA7) was the only member of the integrin family that positively correlated with both overall survival and progression-free survival in ovarian cancer through GEPIA2. The immunohistochemistry signal of ITGA7 was apparent in the tumor stroma, and a lower omental ITGA7 level was associated with metastasis. Primary ADSCs were isolated from the omentum of patients with ovarian cancer and identified by cellular morphology, biomarkers, and multilineage differentiation. The conditional medium of ovarian cancer cells induced ITGA7 expression decrease and phenotypic changes in ADSCs. Downregulation of ITGA7 in primary omental ADSCs led to decrease in stemness properties and emerge of characteristic morphology and biomarkers of CAFs. Moreover, the conditioned medium of ADSCs with ITGA7 depletion exhibited enhanced abilities to improve the migration and invasion of ovarian cancer cells in vitro. Overall, these findings indicate that loss of ITGA7 may induce the differentiation of ADSCs to CAFs that contribute to a tumor-supportive niche.

The Prognosis and Immunotherapy Prediction Model of Ovarian Serous Cystadenocarcinoma Patient was Constructed Based on Cuproptosis-Related LncRNA

Cuproptosis can serve as potential prognostic predictors in patients with cancer. However, the role of this relationship in ovarian serous cystadenocarcinoma (OV) remains unclear. 376 OV tumor samples were obtained from the Cancer Genome Atlas (TCGA) database, and long non-coding RNAs (lncRNAs) related to cuproptosis were obtained through correlation analysis. The risk assessment model was further constructed by univariate Cox regression analysis and LASSO Cox regression. Bioinformatics was used to analyze the regulatory effect of relevant risk assessment models on tumor mutational burden (TMB) and immune microenvironment. We obtained 5 lncRNAs (AC025287.2, AC092718.4, AC112721.2, LINC00996, and LINC01639) and incorporated them into the Cox proportional hazards model. Kaplan-Meier (KM) curve analysis of the prognosis found that the high-risk group was associated with a poorer prognosis. The receiver operating characteristic (ROC) curve showed stronger predictive power compared to other clinicopathological features. Immune infiltration analysis showed that high-risk scores were inversely correlated with CD8+ T cells, CD4+ T cells, macrophages, NK cells, and B cells. Functional enrichment analysis found that they may act via the extracellular matrix (ECM)-interacting proteins and other pathways. We successfully constructed a reliable cuproptosis-related lncRNA model for the prognosis of OV.

T-cell infiltration and its regulatory mechanisms in cancers: insights at single-cell resolution

Tumor-infiltrating T cells recognize, attack, and clear tumor cells, playing a central role in antitumor immune response. However, certain immune cells can impair this response and help tumor immune escape. Therefore, exploring the factors that influence T-cell infiltration is crucial to understand tumor immunity and improve therapeutic effect of cancer immunotherapy. The use of single-cell RNA sequencing (scRNA-seq) allows the high-resolution analysis of the precise composition of immune cells with different phenotypes and other microenvironmental factors, including non-immune stromal cells and the related molecules in the tumor microenvironment of various cancer types. In this review, we summarized the research progress on T-cell infiltration and the crosstalk of other stromal cells and cytokines during T-cell infiltration using scRNA-seq to provide insights into the mechanisms regulating T-cell infiltration and contribute new perspectives on tumor immunotherapy.

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.

Single-cell and transcriptomic analyses reveal the influence of diabetes on ovarian cancer

BACKGROUND

There has been a significant surge in the global prevalence of diabetes mellitus (DM), which increases the susceptibility of individuals to ovarian cancer (OC). However, the relationship between DM and OC remains largely unexplored. The objective of this study is to provide preliminary insights into the shared molecular regulatory mechanisms and potential biomarkers between DM and OC.

METHODS

Multiple datasets from the GEO database were utilized for bioinformatics analysis. Single cell datasets from the GEO database were analysed. Subsequently, immune cell infiltration analysis was performed on mRNA expression data. The intersection of these datasets yielded a set of common genes associated with both OC and DM. Using these overlapping genes and Cytoscape, a protein‒protein interaction (PPI) network was constructed, and 10 core targets were selected. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were then conducted on these core targets. Additionally, advanced bioinformatics analyses were conducted to construct a TF-mRNA-miRNA coregulatory network based on identified core targets. Furthermore, immunohistochemistry staining (IHC) and real-time quantitative PCR (RT-qPCR) were employed for the validation of the expression and biological functions of core proteins, including HSPAA1, HSPA8, SOD1, and transcription factors SREBF2 and GTAT2, in ovarian tumors.

RESULTS

The immune cell infiltration analysis based on mRNA expression data for both DM and OC, as well as analysis using single-cell datasets, reveals significant differences in mononuclear cell levels. By intersecting the single-cell datasets, a total of 119 targets related to mononuclear cells in both OC and DM were identified. PPI network analysis further identified 10 hub genesincludingHSP90AA1, HSPA8, SNRPD2, UBA52, SOD1, RPL13A, RPSA, ITGAM, PPP1CC, and PSMA5, as potential targets of OC and DM. Enrichment analysis indicated that these genes are primarily associated with neutrophil degranulation, GDP-dissociation inhibitor activity, and the IL-17 signaling pathway, suggesting their involvement in the regulation of the tumor microenvironment. Furthermore, the TF-gene and miRNA-gene regulatory networks were validated using NetworkAnalyst. The identified TFs included SREBF2, GATA2, and SRF, while the miRNAs included miR-320a, miR-378a-3p, and miR-26a-5p. Simultaneously, IHC and RT-qPCR reveal differential expression of core targets in ovarian tumors after the onset of diabetes. RT-qPCR further revealed that SREBF2 and GATA2 may influence the expression of core proteins, including HSP90AA1, HSPA8, and SOD1.

CONCLUSION

This study revealed the shared gene interaction network between OC and DM and predicted the TFs and miRNAs associated with core genes in monocytes. Our research findings contribute to identifying potential biological mechanisms underlying the relationship between OC and DM.

SINGLE-CELL TRANSCRIPTOME ANALYSIS IN HEALTH AND DISEASE

ABSTRACT

The analysis of the single-cell transcriptome has emerged as a powerful tool to gain insights on the basic mechanisms of health and disease. It is widely used to reveal the cellular diversity and complexity of tissues at cellular resolution by RNA sequencing of the whole transcriptome from a single cell. Equally, it is applied to discover an unknown, rare population of cells in the tissue. The prime advantage of single-cell transcriptome analysis is the detection of stochastic nature of gene expression of the cell in tissue. Moreover, the availability of multiple platforms for the single-cell transcriptome has broadened its approaches to using cells of different sizes and shapes, including the capture of short or full-length transcripts, which is helpful in the analysis of challenging biological samples. And with the development of numerous packages in R and Python, new directions in the computational analysis of single-cell transcriptomes can be taken to characterize healthy versus diseased tissues to obtain novel pathological insights. Downstream analysis such as differential gene expression analysis, gene ontology term analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis, cell-cell interaction analysis, and trajectory analysis has become standard practice in the workflow of single-cell transcriptome analysis to further examine the biology of different cell types. Here, we provide a broad overview of single-cell transcriptome analysis in health and disease conditions currently applied in various studies.

Defining the Role of Metastasis-Initiating Cells in Promoting Carcinogenesis in Ovarian Cancer

Ovarian cancer is the deadliest gynecological malignancy with a high prevalence of transcoelomic metastasis. Metastasis is a multi-step process and only a small percentage of cancer cells, metastasis-initiating cells (MICs), have the capacity to finally establish metastatic lesions. These MICs maintain a certain level of stemness that allows them to differentiate into other cell types with distinct transcriptomic profiles and swiftly adapt to external stresses. Furthermore, they can coordinate with the microenvironment, through reciprocal interactions, to invade and establish metastases. Therefore, identifying, characterizing, and targeting MICs is a promising strategy to counter the spread of ovarian cancer. In this review, we provided an overview of OC MICs in the context of characterization, identification through cell surface markers, and their interactions with the metastatic niche to promote metastatic colonization.

The Evolving Landscape of B Cells in Cancer Metastasis

Metastasis is the leading cause of cancer mortality. Functional and clinical studies have documented diverse B-cell and antibody responses in cancer metastasis. The presence of B cells in tumor microenvironments and metastatic sites has been associated with diverse effects that can promote or inhibit metastasis. Specifically, B cells can contribute to the spread of cancer cells by enhancing tumor cell motility, invasion, angiogenesis, lymphangiogenesis, and extracellular matrix remodeling. Moreover, they can promote metastatic colonization by triggering pathogenic immunoglobulin responses and recruiting immune suppressive cells. Contrastingly, B cells can also exhibit antimetastatic effects. For example, they aid in enhanced antigen presentation, which helps activate immune responses against cancer cells. In addition, B cells play a crucial role in preventing the dissemination of metastatic cells from the primary tumor and secrete antibodies that can aid in tumor recognition. Here, we review the complex roles of B cells in metastasis, delineating the heterogeneity of B-cell activity and subtypes by metastatic site, antibody class, antigen (if known), and molecular phenotype. These important attributes of B cells emphasize the need for a deeper understanding and characterization of B-cell phenotypes to define their effects in metastasis.

Prognostic features of the tumor microenvironment in high-grade serous ovarian cancer and dietary immunomodulation

High-grade serous ovarian cancer (HGSOC) is a particularly lethal malignancy that is prognostically influenced by the immune profile of the tumor microenvironment (TME). TME immune profiles have been sub-categorized according to features associated with both survival outcomes as well as response to systemic therapies. Five suggested immune phenotypes have been described and correlated with overall survival outcomes. Phenotypes associated with shorter overall survival rates appear to have prominent immunosuppressive features within their TME. The opportunity to triage patients according to their prognostic TME profile might allow selection of individual patients with poor prognostic features who could most benefit from innovative immunomodulatory treatment strategies. Two potential strategies to indirectly manipulate the TME (and oncologic outcomes) are alteration of the gut microbiome composition and alteration of TME metabolism through dietary interventions. Experimental dietary modifications in humans designed for influencing cancer outcomes are only beginning to be studied in a prospective fashion. Herein we summarize prognostic TME features in HGSOC and potential opportunities for immunomodulation via dietary and gut microbial interventions.

The effect of cuproptosis-relevant genes on the immune infiltration and metabolism of gynecological oncology by multiply analysis and experiments validation

Gynecological cancers are a leading cause of mortality for women, including ovarian cancer (OC), cervical squamous cell carcinoma (CESC), and uterine corpus endometrial carcinoma (UCEC). Nevertheless, these gynecological cancer types have not elucidated the role of cuproptosis and the correlated tumor microenvironment (TME) infiltration features. CRGs had important potential molecular functions and prognostic significance in gynecological cancers, especially in UCEC. Hub CRG, FDX1, was correlated with the CD8+ T cell immune infiltration in UCEC and CESC. FDX1 OE could significantly repress the proliferation ability in UCEC cells by MTT, EdU, and clone formation. High levels of FDX1 could repress ATP and lactic acid but enhance ROS and glucose levels by metabolism assay. The xenograft tumor model indicated that FDX1 OE significantly inhibited the growth of UCEC and attenuated the PCNA, HK2, PKM2, and Ki-67 expression. These CRGs are significant roles that could be potential markers and treatment targets to optimize the TME immune cell infiltration features for gynecological cancer types. FDX1 is a hub CRGs in UCEC to promote immune infiltration and attenuate proliferation and metabolism.

Ovarian cancer: Novel mechanisms and therapeutic targets regarding the microenvironment in the abdominal cavity

Ovarian cancer is an intractable disease that is mostly diagnosed at an advanced stage and has a high recurrence rate. The early development of characteristic peritoneal dissemination via ascites contributes to a poor prognosis. Based on the "seed and soil" theory, ovarian cancer is considered to form a disseminated tumor that interacts with the peritoneum; superficial mesothelial cells are structurally important. Thus far, we have reported that peritoneal mesothelial cells, which originally are ecological defenses, transform into ovarian cancer-associated mesothelial cells, which are allies of cancer. They are found to be actively involved in the formation of a friendly "soil" that promotes the survival of "seeds" of ovarian cancer cells. We also demonstrated that the progression of ovarian cancer and the induction of its refractory nature are partially mediated through competition and cooperation between ovarian cancer and mesothelial cells. We believe that it is necessary to shift the aim of treatment strategies from solely targeting cancer cells to focusing on the crosstalk between the surrounding environment and ovarian cancer, an approach that ultimately aims to achieve "coexistence" with cancer through disease control.

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.

KRT19 is a Promising Prognostic Biomarker and Associates with Immune Infiltrates in Serous Ovarian Cystadenocarcinoma

Background

Ovarian cancer (OV) is the highest prevalent gynecologic tumor with complicated pathogenesis; high-grade serous ovarian cystadenocarcinoma (HGSOC) is the most epidemiological and malignant subtype of OV. Keratin type I cytoskeleton 19 (KRT19) is an intermediate filament protein which plays essential roles in the maintenance of epithelial cells. However, its role in OV remains largely unknown.

Methods

Bioinformatic analysis with various databases was conducted in this study. In details, KRT19 expression was assessed using databases including The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), Gene Expression Omnibus (GEO) and Human Protein Atlas (HPA). GO-KEGG and GSEA analysis were performed by R packages. The biological function of KRT19 was analyzed based on the single-cell sequencing information from CancerSEA database. The association of KRT19 expression with immunomodulator and chemokine was predicted via the TISIDB database.

Results

The expression of KRT19 was significantly upregulated in ovarian samples compared with normal controls. KRT19 expression was negatively associated with prognosis in OV, and further analysis revealed that KRT19 had promising diagnostic significance in distinguishing OV cancer from normal samples. GO-KEGG and GSEA analysis indicated that KRT19 was associated with multiple biological functions and pathways including epidermis development, apical junction, inflammatory response, and epithelial mesenchymal transition. By using different GEO series, we found that KRT19 was differentially expressed in OV-associated tissues. Furthermore, the increased KRT19 expression was positively correlated with the immune infiltration levels of the most immune cells in OV.

Conclusion

This study demonstrated that KRT19 is a promising prognosis and diagnosis biomarker that determines cancer progression and is correlated with tumor immune cells infiltration in OV, suggesting being a molecular target for immunotherapies.

A single-cell landscape of pre- and post-menopausal high-grade serous ovarian cancer ascites

High-grade serous ovarian cancer (HGSOC) is a hormone-related cancer with high mortality and poor prognosis. Based on the transcriptome of 57,444 cells in ascites from 10 patients with HGSOC (including 5 pre-menopausal and 5 post-menopausal patients), we identified 14 cell clusters which were further classified into 6 cell types, including T cells, B cells, NK cells, myeloid cells, epithelial cells, and stromal cells. We discovered an increased proportion of epithelial cells and a decreased proportion of T cells in pre-menopausal ascites compared with post-menopausal ascites. GO analysis revealed the pre-menopausal tumor microenvironments (TME) are closely associated with viral infection, while the post-menopausal TME are mostly related to the IL-17 immune pathway. SPP1/CD44-mediated crosstalk between myeloid cells and B cells, NK cells, and stromal cells mainly present in the pre-menopausal group, while SPP1/PTGER4 -mediated crosstalk between myeloid cells and epithelial cells mostly present in the post-menopausal group.

Characterization of tumour microenvironment reprogramming reveals invasion in epithelial ovarian carcinoma

BACKGROUND

Patients with epithelial ovarian carcinoma (EOC) are usually diagnosed at an advanced stage with tumour cell invasion. However, identifying the underlying molecular mechanisms and biomarkers of EOC proliferation and invasion remains challenging.

RESULTS

Herein, we explored the relationship between tumour microenvironment (TME) reprogramming and tissue invasion based on single-cell RNA sequencing (scRNA-seq) datasets. Interestingly, hypoxia, oxidative phosphorylation (OXPHOS) and glycolysis, which have biologically active trajectories during epithelial mesenchymal transition (EMT), were positively correlated. Moreover, energy metabolism and anti-apoptotic activity were found to be critical contributors to intratumor heterogeneity. In addition, HMGA1, EGR1 and RUNX1 were found to be critical drivers of the EMT process in EOC. Experimental validation revealed that suppressing EGR1 expression inhibited tumour cell invasion, significantly upregulated the expression of E-cadherin and decreased the expression of N-cadherin. In cell components analysis, cancer-associated fibroblasts (CAFs) were found to significantly contribute to immune infiltration and tumour invasion, and the accumulation of CAFs was associated with poorer patient survival.

CONCLUSION

We revealed the molecular mechanism and biomarkers of tumour invasion and TME reprogramming in EOC, which provides effective targets for the suppression of tumour invasion.

Increased expression of IDO1 is associated with improved survival and increased number of TILs in patients with high-grade serous ovarian cancer

BACKGROUND

The enzyme indoleamine 2,3-dioxygenase 1 (IDO1) plays a crucial role in regulating the immune system's response to tumors, but its exact role in cancer, especially in high-grade serous ovarian cancer (HGSOC), remains controversial. We aimed to investigate the prognostic impact of IDO1 expression and its correlation with tumor-infiltrating lymphocytes (TILs) in HGSOC.

METHODS

Immunohistochemical (IHC) staining and bioimage analysis using the QuPath software were employed to assess IDO1 protein expression in a well-characterized cohort of 507 patients with primary HGSOC. Statistical evaluation was performed using SPSS, and in silico validation considering IDO1 mRNA expression in bulk and single-cell gene expression datasets was conducted. Additionally, IDO1 expression in interferon-gamma (IFNG) stimulated HGSOC cell lines was analyzed.

RESULTS

Our findings revealed that IDO1 protein and mRNA expression serve as positive prognostic markers for overall survival (OS) and progression-free survival (PFS) in HGSOC. High IDO1 expression was associated with a significant improvement in OS by 21 months (p < 0.001) and PFS by 6 months (p = 0.016). Notably, elevated IDO1 expression correlated with an increased number of CD3+ (p < 0.001), CD4+ (p < 0.001), and CD8+ TILs (p < 0.001). Furthermore, high IDO1 mRNA expression and protein level were found to be associated with enhanced responsiveness to pro-inflammatory cytokines, particularly IFNG.

CONCLUSIONS

Our study provides evidence that IDO1 expression serves as a positive prognostic marker in HGSOC and is associated with an increased number of CD3+, CD4+ and CD8+ TILs. Understanding the intricate relationship between IDO1, TILs, and the tumor microenvironment may hold the key to improving outcomes in HGSOC.

Single-cell RNA sequencing reveals the cellular and molecular characteristics of high-grade and metastatic bladder cancer

PURPOSE

Metastatic bladder cancer (BC) has the highest somatic mutation frequency and recurrence rate of all tumors. However, the cellular and molecular characteristics of BC remain unclear.

METHODS

We performed single-cell RNA sequencing (scRNA-seq) on the samples of paracancerous normal tissue (PNT), primary tumor (PT) and lymph node metastasis (LNM). The proportions and gene expression profiles of different cell types in the tumor microenvironment (TME) were investigated.

RESULTS

In total, 50,158 cells were classified into six populations. Malignant cells of PT and LNM exhibited large mutant DNA fragments, while the cell phenotypes and gene expression profiles differed during differentiation. Metastasis was associated with a poorer prognosis than PT. Tumor-associated stromal cells and inhibitory immune cells were the main cell populations in PT and LNM. Cell-cell communication analysis revealed the roles of signaling pathways of inflammatory cancer-associated fibroblast (iCAF) and tumor-associated macrophage (TAM) in exhaustion of T cells. In addition, iCAF may recruit TAM to promote formation of the TME earlier than the differentiation of tumor cells.

CONCLUSION

This study through scRNA-seq enhanced our understanding of new features about the cellular and molecular similarities and differences of high-grade and metastatic bladder cancer, which might provide potential therapeutic targets in future treatment.

Advances in single-cell RNA sequencing and its applications in cancer research

Cancers are a group of heterogeneous diseases characterized by the acquisition of functional capabilities during the transition from a normal to a neoplastic state. Powerful experimental and computational tools can be applied to elucidate the mechanisms of occurrence, progression, metastasis, and drug resistance; however, challenges remain. Bulk RNA sequencing techniques only reflect the average gene expression in a sample, making it difficult to understand tumor heterogeneity and the tumor microenvironment. The emergence and development of single-cell RNA sequencing (scRNA-seq) technologies have provided opportunities to understand subtle changes in tumor biology by identifying distinct cell subpopulations, dissecting the tumor microenvironment, and characterizing cellular genomic mutations. Recently, scRNA-seq technology has been increasingly used in cancer studies to explore tumor heterogeneity and the tumor microenvironment, which has increased the understanding of tumorigenesis and evolution. This review summarizes the basic processes and development of scRNA-seq technologies and their increasing applications in cancer research and clinical practice.

Exploring the cellular and molecular differences between ovarian clear cell carcinoma and high-grade serous carcinoma using single-cell RNA sequencing and GEO gene expression signatures

The two most prevalent subtypes of epithelial ovarian carcinoma (EOC) are ovarian clear cell carcinoma (OCCC) and high-grade serous ovarian carcinoma (HGSC). Patients with OCCC have a poor prognosis than those with HGSC due to chemoresistance, implying the need for novel treatment target. In this study, we applied single-cell RNA sequencing (scRNA-seq) together with bulk RNA-seq data from the GEO (Gene Expression Omnibus) database (the GSE189553 dataset) to characterize and compare tumor heterogeneity and cell-level evolution between OCCC and HGSC samples. To begin, we found that the smaller proportion of an epithelial OCCC cell subset in the G2/M phase might explain OCCC chemoresistance. Second, we identified a possible pathogenic OCCC epithelial cell subcluster that overexpresses LEFTY1. Third, novel biomarkers separating OCCC from HGSC were discovered and subsequently validated on a wide scale using immunohistochemistry. Amine oxidase copper containing 1 (AOC1) was preferentially expressed in OCCC over HGSC, while S100 calcium-binding protein A2 (S100A2) was detected less frequently in OCCC than in HGSC. In addition, we discovered that metabolic pathways were enriched in the epithelial compartment of the OCCC samples. In vitro experiments verified that inhibition of oxidative phosphorylation or glycolysis pathways exerted direct antitumor effects on both OCCC and HGSC cells, while targeting glutamine metabolism or ferroptosis greatly attenuated chemosensitivity only in OCCC cells. Finally, to determine whether there were any variations in immune cell subsets between OCCC and HGSC, data from scRNA-seq and mass cytometry were pooled for analysis. In summary, our work provides the first holistic insights into the cellular and molecular distinctions between OCCC and HGSC and is a valuable source for discovering new targets to leverage in clinical treatments to improve the poor prognosis of patients with OCCC.

High EVI1 and PARP1 expression as favourable prognostic markers in high-grade serous ovarian carcinoma

BACKGROUND

Mechanisms of development and progression of high-grade serous ovarian cancer (HGSOC) are poorly understood. EVI1 and PARP1, part of TGF-ß pathway, are upregulated in cancers with DNA repair deficiencies with DNA repair deficiencies and may influce disease progression and survival. Therefore we questioned the prognostic significance of protein expression of EVI1 alone and in combination with PARP1 and analyzed them in a cohort of patients with HGSOC.

METHODS

For 562 HGSOC patients, we evaluated EVI1 and PARP1 expression by immunohistochemical staining on tissue microarrays with QuPath digital semi-automatic positive cell detection.

RESULTS

High EVI1 expressing (> 30% positive tumor cells) HGSOC were associated with improved progression-free survival (PFS) (HR = 0.66, 95% CI: 0.504-0.852, p = 0.002) and overall survival (OS) (HR = 0.45, 95% CI: 0.352-0.563, p < 0.001), including multivariate analysis. Most interestingly, mutual high expression of both proteins identifies a group with particularly good prognosis. Our findings were proven technically and clinically using bioinformatical data sets for single-cell sequencing, copy number variation and gene as well as protein expression.

CONCLUSIONS

EVI1 and PARP1 are robust prognostic biomarkers for favorable prognosis in HGSOC and imply further research with respect to their reciprocity.

Tumor and local lymphoid tissue interaction determines prognosis in high-grade serous ovarian cancer

Tertiary lymphoid structure (TLS) is associated with prognosis in copy-number-driven tumors, including high-grade serous ovarian cancer (HGSOC), although the function of TLS and its interaction with copy-number alterations in HGSOC are not fully understood. In the current study, we confirm that TLS-high HGSOC patients show significantly better progression-free survival (PFS). We show that the presence of TLS in HGSOC tumors is associated with B cell maturation and cytotoxic tumor-specific T cell activation and proliferation. In addition, the copy-number loss of IL15 and CXCL10 may limit TLS formation in HGSOC; a list of genes that may dysregulate TLS function is also proposed. Last, a radiomics-based signature is developed to predict the presence of TLS, which independently predicts PFS in both HGSOC patients and immune checkpoint inhibitor (ICI)-treated non-small cell lung cancer (NSCLC) patients. Overall, we reveal that TLS coordinates intratumoral B cell and T cell response to HGSOC tumor, while the cancer genome evolves to counteract TLS formation and function.

Identification of novel candidate targets for suppressing ovarian cancer progression through IL-33/ST2 axis components using the system biology approach

Background: Cancer-associated fibroblasts (CAFs) of ovarian cancer (OvC) are the most prevalent element of the tumor microenvironment (TM). By promoting angiogenesis, immunological suppression, and invasion, CAFs speed up the growth of tumors by changing the extracellular matrix's structure and composition and/or initiating the epithelial cells (EPT). IL-33/ST2 signaling has drawn a lot of attention since it acts as a pro-tumor alarmin and encourages spread by altering TM. Methods: Differentially expressed genes (DEGs) of the OvC tumor microenvironment were found in the GEO database, qRT-PCR, western blotting, and immunohistochemistry, and their presence and changes in healthy and tumor tissue content were examined. Primary cultures of healthy fibroblasts and CAFs obtained from healthy and tumor tissues retrieved from OvC samples were used for in vitro and in vivo investigations. Cultured primary human CAFs were utilized to investigate the regulation and the IL-33/ST2 axis role in the inflammation reactions. Results: Although ST2 and IL-33 expression was detected in both epithelial (EPT) and fibroblast cells of ovarian cancer, they are more abundant in CAFs. Lipopolysaccharides, serum amyloid A1, and IL-1β, the inflammatory mediators, could all induce IL-33 expression through NF-κB activation in human CAFs. In turn, via the ST2 receptor, IL-33 affected the production of IL-6, IL-1β, and PTGS2 in human CAFs via the MAPKs-NF-κB pathway. Conclusion: Our findings suggest that IL-33/ST2 is affected by the interaction of CAFs and epithelial cells inside the tumor microenvironment. Activation of this axis leads to increased expression of inflammatory factors in tumor CAFs and EPT cells. Therefore, targeting the IL-33/ST2 axis could have potential value in the prevention of OvC progression.

Intraperitoneal metastasis of ovarian cancer: new insights on resident macrophages in the peritoneal cavity

Ovarian cancer metastasis occurs primarily in the peritoneal cavity. Orchestration of cancer cells with various cell types, particularly macrophages, in the peritoneal cavity creates a metastasis-favorable environment. In the past decade, macrophage heterogeneities in different organs as well as their diverse roles in tumor settings have been an emerging field. This review highlights the unique microenvironment of the peritoneal cavity, consisting of the peritoneal fluid, peritoneum, and omentum, as well as their own resident macrophage populations. Contributions of resident macrophages in ovarian cancer metastasis are summarized; potential therapeutic strategies by targeting such cells are discussed. A better understanding of the immunological microenvironment in the peritoneal cavity will provide a stepping-stone to new strategies for developing macrophage-based therapies and is a key step toward the unattainable eradication of intraperitoneal metastasis of ovarian cancer.

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.

B cells in the tumor microenvironment: Multi-faceted organizers, regulators, and effectors of anti-tumor immunity

Our understanding of tumor-infiltrating lymphocytes (TILs) is rapidly expanding beyond T cell-centric perspectives to include B cells and plasma cells, collectively referred to as TIL-Bs. In many cancers, TIL-Bs carry strong prognostic significance and are emerging as key predictors of response to immune checkpoint inhibitors. TIL-Bs can perform multiple functions, including antigen presentation and antibody production, which allow them to focus immune responses on cognate antigen to support both T cell responses and innate mechanisms involving complement, macrophages, and natural killer cells. In the stroma of the most immunologically "hot" tumors, TIL-Bs are prominent components of tertiary lymphoid structures, which resemble lymph nodes structurally and functionally. Additionally, TIL-Bs participate in a variety of other lympho-myeloid aggregates and engage in dynamic interactions with the tumor stroma. Here, we summarize our current understanding of TIL-Bs in human cancer, highlighting the compelling therapeutic opportunities offered by their unique tumor recognition and effector mechanisms.

Spatiotemporally deciphering the mysterious mechanism of persistent HPV-induced malignant transition and immune remodelling from HPV-infected normal cervix, precancer to cervical cancer: Integrating single-cell RNA-sequencing and spatial transcriptome

BACKGROUND

The mechanism underlying cervical carcinogenesis that is mediated by persistent human papillomavirus (HPV) infection remains elusive.

AIMS

Here, for the first time, we deciphered both the temporal transition and spatial distribution of cellular subsets during disease progression from normal cervix tissues to precursor lesions to cervical cancer.

MATERIALS & METHODS

We generated scRNA-seq profiles and spatial transcriptomics data from nine patient samples, including two HPV-negative normal, two HPV-positive normal, two HPV-positive HSIL and three HPV-positive cancer samples.

RESULTS

We not only identified three 'HPV-related epithelial clusters' that are unique to normal, high-grade squamous intraepithelial lesions (HSIL) and cervical cancer tissues but also discovered node genes that potentially regulate disease progression. Moreover, we observed the gradual transition of multiple immune cells that exhibited positive immune responses, followed by dysregulation and exhaustion, and ultimately established an immune-suppressive microenvironment during the malignant program. In addition, analysis of cellular interactions further verified that a 'homeostasis-balance-malignancy' change occurred within the cervical microenvironment during disease progression.

DISCUSSION

We for the first time presented a spatiotemporal atlas that systematically described the cellular heterogeneity and spatial map along the four developmental steps of HPV-related cervical oncogenesis, including normal, HPV-positive normal, HSIL and cancer. We identified three unique HPV-related clusters, discovered critical node genes that determined the cell fate and uncovered the immune remodeling during disease escalation.

CONCLUSION

Together, these findings provided novel possibilities for accurate diagnosis, precise treatment and prognosis evaluation of patients with precancer and cervical cancer.

Single-cell RNA sequencing reveals tumor heterogeneity, microenvironment, and drug-resistance mechanisms of recurrent glioblastoma

Glioblastomas are highly heterogeneous brain tumors. Despite the availability of standard treatment for glioblastoma multiforme (GBM), i.e., Stupp protocol, which involves surgical resection followed by radiotherapy and chemotherapy, glioblastoma remains refractory to treatment and recurrence is inevitable. Moreover, the biology of recurrent glioblastoma remains unclear. Increasing evidence has shown that intratumoral heterogeneity and the tumor microenvironment contribute to therapeutic resistance. However, the interaction between intracellular heterogeneity and drug resistance in recurrent GBMs remains controversial. The aim of this study was to map the transcriptome landscape of cancer cells and the tumor heterogeneity and tumor microenvironment in recurrent and drug-resistant GBMs at a single-cell resolution and further explore the mechanism of drug resistance of GBMs. We analyzed six tumor tissue samples from three patients with primary GBM and three patients with recurrent GBM in which recurrence and drug resistance developed after treatment with the standard Stupp protocol using single-cell RNA sequencing. Using unbiased clustering, nine major cell clusters were identified. Upregulation of the expression of stemness-related and cell-cycle-related genes was observed in recurrent GBM cells. Compared with the initial GBM tissues, recurrent GBM tissues showed a decreased proportion of microglia, consistent with previous reports. Finally, vascular endothelial growth factor A expression and the blood-brain barrier permeability were high, and the O⁶ -methylguanine DNA methyltransferase-related signaling pathway was activated in recurrent GBM. Our results delineate the single-cell map of recurrent glioblastoma, tumor heterogeneity, tumor microenvironment, and drug-resistance mechanisms, providing new insights into treatment strategies for recurrent glioblastomas.

Reconstruction of the tumor spatial microenvironment along the malignant-boundary-nonmalignant axis

Although advances in spatial transcriptomics (ST) enlarge to unveil spatial landscape of tissues, it remains challenging to delineate pathology-relevant and cellular localizations, and interactions exclusive to a spatial niche (e.g., tumor boundary). Here, we develop Cottrazm, integrating ST with hematoxylin and eosin histological image, and single-cell transcriptomics to delineate the tumor boundary connecting malignant and non-malignant cell spots in tumor tissues, deconvolute cell-type composition at spatial location, and reconstruct cell type-specific gene expression profiles at sub-spot level. We validate the performance of Cottrazm along the malignant-boundary-nonmalignant spatial axis. We identify specific macrophage and fibroblast subtypes localized around tumor boundary that interacted with tumor cells to generate a structural boundary, which limits T cell infiltration and promotes immune exclusion in tumor microenvironment. In this work, Cottrazm provides an integrated tool framework to dissect the tumor spatial microenvironment and facilitates the discovery of functional biological insights, thereby identifying therapeutic targets in oncologic ST datasets.

Extracellular Vesicle-Packaged circATP2B4 Mediates M2 Macrophage Polarization via miR-532-3p/SREBF1 Axis to Promote Epithelial Ovarian Cancer Metastasis

Ovarian cancer is one of the most common gynecologic malignancies with a highly immunosuppressive tumor microenvironment (TME) and poor prognosis. Circular RNA (circRNA) is a type of noncoding RNA with high stability, which has been shown to play an important role in biological processes and TME reprogramming in a variety of tumors. The biological function of a novel circRNA, circATP2B4, in epithelial ovarian cancer (EOC) was detected and evaluated. Transmission electron microscopy, differential ultracentrifugation and qRT-PCR were used to verify the existence of extracellular vesicles (EV)-packaged circATP2B4. Macrophage uptake of circATP2B4 was determined by EVs tracing. Dual luciferase reporter, FISH, Western blotting, and flow cytometry assays were used to investigate the interactions between circATP2B4 and miR-532-3p as well as sterol regulatory element-binding factor 1 (SREBF1) expression in macrophages. CircATP2B4 was upregulated in EOC tissues and positively correlated with ovarian cancer progression. Functionally, circATP2B4 promoted carcinogenic progression and metastasis of EOC both in vitro and in vivo. Mechanistically, EV-packaged circATP2B4 in EOC could be transmitted to infiltrated macrophages and acted as competing endogenous RNA of miR-532-3p to relieve the repressive effect of miR-532-3p on its target SREBF1. Furthermore, circATP2B4 induced macrophage M2 polarization by regulating the miR-532-3p/SREBF1/PI3Kα/AKT axis, thereby leading to immunosuppression and ovarian cancer metastasis. Collectively, these data indicate that circATP2B4-containing EVs generated by EOC cells promoted M2 macrophages polarization and malignant behaviors of EOC cells. Thus, targeting EVs-packaged circATP2B4 may provide a potential diagnosis and treatment strategy for ovarian cancer.

CD4+ conventional T cells-related genes signature is a prognostic indicator for ovarian cancer

Introduction

It is believed that ovarian cancer (OC) is the most deadly form of gynecological cancer despite its infrequent occurrence, which makes it one of the most salient public health concerns. Clinical and preclinical studies have revealed that intratumoral CD4+ T cells possess cytotoxic capabilities and were capable of directly killing cancer cells. This study aimed to identify the CD4+ conventional T cells-related genes (CD4TGs) with respect to the prognosis in OC.

Methods

We obtained the transcriptome and clinical data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. CD4TGs were first identified from single-cell datasets, then univariate Cox regression was used to screen prognosis-related genes, LASSO was conducted to remove genes with coefficient zero, and multivariate Cox regression was used to calculate riskscore and to construct the CD4TGs risk signature. Kaplan-Meier analysis, univariate Cox regression, multivariate Cox regression, time-dependent receiver operating characteristics (ROC), decision curve analysis (DCA), nomogram, and calibration were made to verify and evaluate the risk signature. Gene set enrichment analyses (GSEA) in risk groups were conducted to explore the tightly correlated pathways with the risk group. The role of riskscore has been further explored in the tumor microenvironment (TME), immunotherapy, and chemotherapy. A risk signature with 11 CD4TGs in OC was finally established in the TCGA database and furtherly validated in several GEO cohorts.

Results

High riskscore was significantly associated with a poorer prognosis and proven to be an independent prognostic biomarker by multivariate Cox regression. The 1-, 3-, and 5-year ROC values, DCA curve, nomogram, and calibration results confirmed the excellent prediction power of this model. Compared with the reported risk models, our model showed better performance. The patients were grouped into high-risk and low-risk subgroups according to the riskscore by the median value. The low-risk group patients tended to exhibit a higher immune infiltration, immune-related gene expression and were more sensitive to immunotherapy and chemotherapy.

Discussion

Collectively, our findings of the prognostic value of CD4TGs in prognosis and immune response, provided valuable insights into the molecular mechanisms and clinical management of OC.

Comparative analysis between high-grade serous ovarian cancer and healthy ovarian tissues using single-cell RNA sequencing

Introduction

High-grade serous ovarian cancer (HGSOC) is the most common histological subtype of ovarian cancer, and is associated with high mortality rates.

Methods

In this study, we analyzed specific cell subpopulations and compared different gene functions between healthy ovarian and ovarian cancer cells using single-cell RNA sequencing (ScRNA-seq). We delved deeper into the differences between healthy ovarian and ovarian cancer cells at different levels, and performed specific analysis on endothelial cells.

Results

We obtained scRNA-seq data of 6867 and 17056 cells from healthy ovarian samples and ovarian cancer samples, respectively. The transcriptional profiles of the groups differed at various stages of ovarian cell development. A detailed comparison of the cell cycle, and cell communication of different groups, revealed significant differences between healthy ovarian and ovarian cancer cells. We also found that apoptosis-related genes, URI1, PAK2, PARP1, CLU and TIMP3, were highly expressed, while immune-related genes, UBB, RPL11, CAV1, NUPR1 and Hsp90ab1, were lowly expressed in ovarian cancer cells. The results of the ScRNA-seq were verified using qPCR.

Discussion

Our findings revealed differences in function, gene expression and cell interaction patterns between ovarian cancer and healthy ovarian cell populations. These findings provide key insights on further research into the treatment of ovarian cancer.

Modulating the tumor immune microenvironment with nanoparticles: A sword for improving the efficiency of ovarian cancer immunotherapy

With encouraging antitumor effects, immunotherapy represented by immune checkpoint blockade has developed into a mainstream cancer therapeutic modality. However, only a minority of ovarian cancer (OC) patients could benefit from immunotherapy. The main reason is that most OC harbor a suppressive tumor immune microenvironment (TIME). Emerging studies suggest that M2 tumor-associated macrophages (TAMs), T regulatory cells (Tregs), myeloid-derived suppressor cells (MDSCs), and cancer-associated fibroblasts (CAFs) are enriched in OC. Thus, reversing the suppressive TIME is considered an ideal candidate for improving the efficiency of immunotherapy. Nanoparticles encapsulating immunoregulatory agents can regulate immunocytes and improve the TIME to boost the antitumor immune response. In addition, some nanoparticle-mediated photodynamic and photothermal therapy can directly kill tumor cells and induce tumor immunogenic cell death to activate antigen-presenting cells and promote T cell infiltration. These advantages make nanoparticles promising candidates for modulating the TIME and improving OC immunotherapy. In this review, we analyzed the composition and function of the TIME in OC and summarized the current clinical progress of OC immunotherapy. Then, we expounded on the promising advances in nanomaterial-mediated immunotherapy for modulating the TIME in OC. Finally, we discussed the obstacles and challenges in the clinical translation of this novel combination treatment regimen. We believe this resourceful strategy will open the door to effective immunotherapy of OC and benefit numerous patients.

Establishment of an ovarian cancer omentum metastasis-related prognostic model by integrated analysis of scRNA-seq and bulk RNA-seq

OBJECTIVE

Ovarian cancer has the highest mortality rate among gynecological malignant tumors, and it preferentially metastasizes to omental tissue, leading to intestinal obstruction and death. scRNA-seq is a powerful technique to reveal tumor heterogeneity. Analyzing omentum metastasis of ovarian cancer at the single-cell level may be more conducive to exploring and understanding omentum metastasis and prognosis of ovarian cancer at the cellular function and genetic levels.

METHODS

The omentum metastasis site scRNA-seq data of GSE147082 were acquired from the GEO (Gene Expression Omnibus) database, and single cells were clustered by the Seruat package and annotated by the SingleR package. Cell differentiation trajectories were reconstructed through the monocle package. The ovarian cancer microarray data of GSE132342 were downloaded from GEO and were clustered by using the ConsensusClusterPlus package into omentum metastasis-associated clusters according to the marker genes gained from single-cell differentiation trajectory analysis. The tumor microenvironment (TME) and immune infiltration differences between clusters were analyzed by the estimate and CIBERSORT packages. The expression matrix of genes used to cluster GSE132342 patients was extracted from bulk RNA-seq data of TCGA-OV (The Cancer Genome Atlas ovarian cancer), and least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression were performed to establish an omentum metastasis-associated gene (OMAG) signature. The signature was then tested by GSE132342 data. Finally, the clinicopathological characteristics of TCGA-OV were screened by univariate and multivariate Cox regression analysis to draw the nomogram.

RESULTS

A total of 9885 cells from 6 patients were clustered into 18 cell clusters and annotated into 14 cell types. Reconstruction of differentiation trajectories divided the cells into 5 branches, and a total of 781 cell trajectory-related characteristic genes were obtained. A total of 3769 patients in GSE132342 were subtyped into 3 clusters by 74 cell trajectory-related characteristic genes. Kaplan-Meier (K-M) survival analysis showed that the prognosis of cluster 2 was the worst, P < 0.001. The TME analysis showed that the ESTIMATE score and stromal score in cluster 2 were significantly higher than those in the other two clusters, P < 0.001. The immune infiltration analysis showed differences in the fraction of 8 immune cells among the 3 clusters, P < 0.05. The expression data of 74 genes used for GEO clustering were extracted from 379 patients in TCGA-OV, and combined with survival information, 10 candidates for OMAGs were filtered by LASSO. By using multivariate Cox regression, the 6-OMAGs signature was established as RiskScore = 0.307*TIMP3 + 3.516*FBN1-0.109*IGKC + 0.209*RPL21 + 0.870*UCHL1 + 0.365*RARRES1. Taking TCGA-OV as the training set and GSE132342 as the test set, receiver operating characteristic (ROC) curves were drawn to verify the prognostic value of 6-OMAGs. Screened by univariate and multivariate Cox regression analysis, 3 (age, cancer status, primary therapy outcome) of 5 clinicopathological characteristics were used to construct the nomogram combined with risk score.

CONCLUSION

We constructed an ovarian cancer prognostic model related to omentum metastasis composed of 6-OMAGs and 3 clinicopathological features and analyzed the potential mechanism of these 6-OMAGs in ovarian cancer omental metastasis.

Immunobiology of high-grade serous ovarian cancer: lessons for clinical translation

Treatment of high-grade serous ovarian cancer (HGSOC) remains challenging. Although HGSOC can potentially be responsive to immunotherapy owing to endogenous immunity at the molecular or T cell level, immunotherapy for this disease has fallen short of expectations to date. This Review proposes a working classification for HGSOC based on the presence or absence of intraepithelial T cells, and elaborates the putative mechanisms that give rise to such immunophenotypes. These differences might explain the failures of existing immunotherapies, and suggest that rational therapeutic approaches tailored to each immunophenotype might meet with improved success. In T cell-inflamed tumours, treatment could focus on mobilizing pre-existing immunity and strengthening the activation of T cells embedded in intraepithelial tumour myeloid niches. Conversely, in immune-excluded and immune-desert tumours, treatment could focus on restoring inflammation by reprogramming myeloid cells, stromal cells and vascular epithelial cells. Poly(ADP-ribose) polymerase (PARP) inhibitors, low-dose radiotherapy, epigenetic drugs and anti-angiogenesis therapy are among the tools available to restore T cell infiltration in HGSOC tumours and could be implemented in combination with vaccines and redirected T cells.