Single-Cell RNA-Sequencing Atlas Reveals the Tumor Microenvironment of Metastatic High-Grade Serous Ovarian Carcinoma

Mechanism insights and therapeutic intervention of tumor metastasis: latest developments and perspectives

Metastasis remains a pivotal characteristic of cancer and is the primary contributor to cancer-associated mortality. Despite its significance, the mechanisms governing metastasis are not fully elucidated. Contemporary findings in the domain of cancer biology have shed light on the molecular aspects of this intricate process. Tumor cells undergoing invasion engage with other cellular entities and proteins en route to their destination. Insights into these engagements have enhanced our comprehension of the principles directing the movement and adaptability of metastatic cells. The tumor microenvironment plays a pivotal role in facilitating the invasion and proliferation of cancer cells by enabling tumor cells to navigate through stromal barriers. Such attributes are influenced by genetic and epigenetic changes occurring in the tumor cells and their surrounding milieu. A profound understanding of the metastatic process's biological mechanisms is indispensable for devising efficacious therapeutic strategies. This review delves into recent developments concerning metastasis-associated genes, important signaling pathways, tumor microenvironment, metabolic processes, peripheral immunity, and mechanical forces and cancer metastasis. In addition, we combine recent advances with a particular emphasis on the prospect of developing effective interventions including the most popular cancer immunotherapies and nanotechnology to combat metastasis. We have also identified the limitations of current research on tumor metastasis, encompassing drug resistance, restricted animal models, inadequate biomarkers and early detection methods, as well as heterogeneity among others. It is anticipated that this comprehensive review will significantly contribute to the advancement of cancer metastasis research.

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 RNA sequencing in ovarian cancer: revealing new perspectives in the tumor microenvironment

Single-cell sequencing technology has emerged as a pivotal tool for unraveling the complexities of the ovarian tumor microenvironment (TME), which is characterized by its cellular heterogeneity and intricate cell-to-cell interactions. Ovarian cancer (OC), known for its high lethality among gynecologic malignancies, presents significant challenges in treatment and diagnosis, partly due to the complexity of its TME. The application of single-cell sequencing in ovarian cancer research has enabled the detailed characterization of gene expression profiles at the single-cell level, shedding light on the diverse cell populations within the TME, including cancer cells, stromal cells, and immune cells. This high-resolution mapping has been instrumental in understanding the roles of these cells in tumor progression, invasion, metastasis, and drug resistance. By providing insight into the signaling pathways and cell-to-cell communication mechanisms, single-cell sequencing facilitates the identification of novel therapeutic targets and the development of personalized medicine approaches. This review summarizes the advancement and application of single-cell sequencing in studying the stromal components and the broader TME in OC, highlighting its implications for improving diagnosis, treatment strategies, and understanding of the disease's underlying biology.

The β-arrestin1/endothelin axis bolsters ovarian fibroblast-dependent invadosome activity and cancer cell metastatic potential

Recruitment of fibroblasts to tumors and their activation into cancer-associated fibroblasts (CAFs) is a strategy used by tumor cells to direct extracellular matrix (ECM) remodeling, invasion, and metastasis, highlighting the need to investigate the molecular mechanisms driving CAF function. Endothelin-1 (ET-1) regulates the communication between cancer and stroma and facilitates the progression of serous ovarian cancer (SOC). By binding to Endothelin A (ETA) and B (ETB) receptors, ET-1 enables the recruitment of β-arrestin1 (β-arr1) and the formation of signaling complexes that coordinate tumor progression. However, how ET-1 receptors might "educate" human ovarian fibroblasts (HOFs) to produce altered ECM and promote metastasis remains to be elucidated. This study identifies ET-1 as a pivotal factor in the activation of CAFs capable of proteolytic ECM remodeling and the generation of heterotypic spheroids containing cancer cells with a propensity to metastasize. An autocrine/paracrine ET-1/ETA/BR/β-arr1 loop enhances HOF proliferation, upregulates CAF marker expression, secretes pro-inflammatory cytokines, and increases collagen contractility, and cell motility. Furthermore, ET-1 facilitates ECM remodeling by promoting the lytic activity of invadosome and activation of integrin β1. In addition, ET-1 signaling supports the formation of heterotypic HOF/SOC spheroids with enhanced ability to migrate through the mesothelial monolayer, and invade, representing metastatic units. The blockade of ETA/BR or β-arr1 silencing prevents CAF activation, invadosome function, mesothelial clearance, and the invasive ability of heterotypic spheroids. In vivo, therapeutic inhibition of ETA/BR using bosentan (BOS) significantly reduces the metastatic potential of combined HOFs/SOC cells, associated with enhanced apoptotic effects on tumor cells and stromal components. These findings support a model in which ET-1/β-arr1 reinforces tumor/stroma interaction through CAF activation and fosters the survival and metastatic properties of SOC cells, which could be counteracted by ETA/BR antagonists.

Exploring the diversity of cancer-associated fibroblasts: insights into mechanisms of drug resistance

Introduction: Among the various stromal cell types within the tumor microenvironment, cancer-associated fibroblasts (CAFs) emerge as the predominant constituent, exhibiting a diverse array of oncogenic functions not intrinsic to normal fibroblasts. Their involvement spans across all stages of tumorigenesis, encompassing initiation, progression, and metastasis. Current understanding posits the coexistence of distinct subpopulations of CAFs within the tumor microenvironment across a spectrum of solid tumors, showcasing both pro- and antitumor activities. Recent advancements in single-cell transcriptomics have revolutionized our ability to meticulously dissect the heterogeneity inherent to CAF populations. Furthermore, accumulating evidence underscores the pivotal role of CAFs in conferring therapeutic resistance to tumors against various drug modalities. Consequently, efforts are underway to develop pharmacological agents specifically targeting CAFs. Methods: This review embarks on a comprehensive analysis, consolidating data from 36 independent single-cell RNA sequencing investigations spanning 17 distinct human malignant tumor types. Results: Our exploration centers on elucidating CAF population markers, discerning their prognostic relevance, delineating their functional contributions, and elucidating the underlying mechanisms orchestrating chemoresistance. Discussion: Finally, we deliberate on the therapeutic potential of harnessing CAFs as promising targets for intervention strategies in clinical oncology.

Novel T cell exhaustion gene signature to predict prognosis and immunotherapy response in thyroid carcinoma from integrated RNA-sequencing analysis

Exhausted CD8+ T lymphocytes and tumor-associated macrophages play critical roles in determining cancer prognosis and the efficacy of immunotherapy. Our study revealed a negative correlation between exhausted CD8+ T lymphocytes and prognosis in thyroid carcinoma (THCA). Consensus clustering divided patients into two subgroups of exhaustion with different prognoses, as defined by marker genes of exhausted CD8+ T cells. Subsequently, we constructed an eight-gene prognostic signature, and developed a risk score named the exhaustion-related gene score (ERGS) to forecast both prognosis and immunotherapy response in THCA. Bulk RNA sequencing analysis revealed a higher prevalence of M2 macrophages, indicative of an immunosuppressive tumor microenvironment (TME), in the high-ERGS group. Single-cell RNA sequencing showed that SPP1+ macrophages and CD14+ monocytes infiltrations were positively associated with higher ERGS. Functionally, it was determined that SPP1+ macrophages exert an immunosuppressive role, while CD14+ monocytes were implicated in promoting tumor progression and angiogenesis. Analysis of cell-cell interactions between SPP1+ macrophages and T cells highlighted the activation of the SPP1-CD44 and MIF-CD74 axes, both of which could foster an immunosuppressive TME. Therapeutic strategies that target SPP1+ macrophages, CD14+ monocytes, and the SPP1-CD44 and MIF-CD74 axes may potentially improve the prognosis and amplify the immunotherapy response in THCA patients.

Constructing a Prognostic Model of Uterine Corpus Endometrial Carcinoma and Predicting Drug-Sensitivity Responses Using Programmed Cell Death-Related Pathways

Background: Uterine Corpus Endometrial Carcinoma (UCEC) is the most common type of cancer that develops in the uterus, specifically originating from the endometrium, the inner lining of the uterus. Programmed cell death (PCD) is a highly regulated process that eliminates damaged, aged, or unwanted cells in the body. Dysregulation of PCD pathways can contribute to the formation and progression of various cancers, including UCEC. Methods: Fourteen PCD pathways (autophagy-dependent cell death, alkaliptosis, apoptosis, cuproptosis, entotic cell death, ferroptosis, immunogenic cell death, lysosome-dependent cell death, MPT-driven necrosis, necroptosis, netotic cell death, oxeiptosis, parthanatos, and pyroptosis) were involved in building a prognostic signature. The model was trained and tested using data from the TCGA-UCEC and validated with the GSE119041 dataset. Results: A 12-gene PCD signature (DRAM1, ELAPOR1, MAPT, TRIM58, UCHL1, CDKN2A, CYFIP2, AKT2, LINC00618, TTPA, TRIM46, and NOS2) was established and validated in an independent dataset. UCEC patients with a high PCD score (PCDS) exhibited worse prognosis. Furthermore, PCDS was found to be associated with immune related cells and key tumor microenvironment components through multiple methods. It was observed that UCEC patients with a high PCD score may not benefit from immunotherapy, but some chemo drugs like Bortezomib may be useful. Conclusion: In conclusion, a novel PCD model was established by comprehensively analyzing diverse cell death patterns. This model accurately predicts the clinical prognosis and drug sensitivity of UCEC. The findings suggest that the PCD signature can serve as a valuable tool in assessing prognosis and guiding treatment decisions for UCEC patients.

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.

It's all about the base: stromal cells are central orchestrators of metastasis

The tumor microenvironment (TME) is an integral part of tumors and plays a central role in all stages of carcinogenesis and progression. Each organ has a unique and heterogeneous microenvironment, which affects the ability of disseminated cells to grow in the new and sometimes hostile metastatic niche. Resident stromal cells, such as fibroblasts, osteoblasts, and astrocytes, are essential culprits in the modulation of metastatic progression: they transition from being sentinels of tissue integrity to being dysfunctional perpetrators that support metastatic outgrowth. Therefore, better understanding of the complexity of their reciprocal interactions with cancer cells and with other components of the TME is essential to enable the design of novel therapeutic approaches to prevent metastatic relapse.

Residual ANTXR1+ myofibroblasts after chemotherapy inhibit anti-tumor immunity via YAP1 signaling pathway

Although cancer-associated fibroblast (CAF) heterogeneity is well-established, the impact of chemotherapy on CAF populations remains poorly understood. Here we address this question in high-grade serous ovarian cancer (HGSOC), in which we previously identified 4 CAF populations. While the global content in stroma increases in HGSOC after chemotherapy, the proportion of FAP+ CAF (also called CAF-S1) decreases. Still, maintenance of high residual CAF-S1 content after chemotherapy is associated with reduced CD8+ T lymphocyte density and poor patient prognosis, emphasizing the importance of CAF-S1 reduction upon treatment. Single cell analysis, spatial transcriptomics and immunohistochemistry reveal that the content in the ECM-producing ANTXR1+ CAF-S1 cluster (ECM-myCAF) is the most affected by chemotherapy. Moreover, functional assays demonstrate that ECM-myCAF isolated from HGSOC reduce CD8+ T-cell cytotoxicity through a Yes Associated Protein 1 (YAP1)-dependent mechanism. Thus, efficient inhibition after treatment of YAP1-signaling pathway in the ECM-myCAF cluster could enhance CD8+ T-cell cytotoxicity. Altogether, these data pave the way for therapy targeting YAP1 in ECM-myCAF in HGSOC.

Serine/threonine kinase 36 induced epithelial-mesenchymal transition promotes docetaxel resistance in prostate cancer

To investigate the role and potential mechanism of serine/threonine kinase 36 (STK36) in docetaxel resistance-prostate cancer (PCa). The expression of STK36 in PCa and the correlation with clinicopathological characteristics of PCa patients were analyzed using the data from different databases and tissue microarrays. To investigate the role of STK36 on cell proliferation, invasion, and migration, STK36 was overexpressed and silenced in DU-145 and PC-3 cell lines. Cell counting kit-8 (CCK8) was used to test cell proliferation. Cell invasion and migration were detected by cell wound scratch assay and trans well, respectively. The expression profile of STK36, E-Cadherin, and Vimentin was analyzed by Western blot. Cell apoptosis was detected by the TUNEL assay. STK36 expression was upregulated in PCa tissue compared with adjacent benign PCa tissue; it was higher in patients with advanced stages compared with lower stages and was significantly correlated with decreased overall survival. Up-regulation of STK36 significantly promoted the proliferation, invasion, and migration of DU-145 and PC-3 cells and compensated for the suppression caused by docetaxel treatment in vitro. A striking apoptosis inhibition could be observed when dealing with docetaxel, although the apoptosis of DU-145 and PC-3 cells was not affected by the STK36 exclusive overexpression. Besides, E-Cadherin expression was restrained while the expression levels of vimentin were all enhanced. The knockdown of STK36 reversed the above process. STK36 up-regulation could accelerate the biological behavior and docetaxel resistance of PCa by epithelial-mesenchymal transition (EMT) activation. STK36 may be potentially used as a target in PCa resolvent with docetaxel.

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.

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.

Afatinib combined with anti-PD1 enhances immunotherapy of hepatocellular carcinoma via ERBB2/STAT3/PD-L1 signaling

Background

Afatinib is mainly used to treat advanced non-small cell lung cancer, but its therapeutic effect on hepatocellular carcinoma is still unclear.

Methods

Over 800 drugs were screened by CCK8 technology and afatinib was found to have a significant inhibitory effect on liver cancer cells. The expression of PDL1 in tumor cells treated with drugs were detected by qRT-PCR and Weston Blot experiments. The effects of afatinib on the growth, migration and invasion of HCC cells were evaluated using wound healing, Transwell, and cell cloning assays. The in vivo effects of afatinib in combination with anti-PD1 were evaluated in C57/BL6J mice with subcutaneous tumorigenesis. Bioinformatics analysis was performed to explore the specific mechanism of afatinib's inhibition of ERBB2 in improving the expression level of PD-L1, which was subsequently verified through experiments.

Results

Afatinib was found to have a significant inhibitory effect on liver cancer cells, as confirmed by in vitro experiments, which demonstrated that it could significantly suppress the growth, invasion and migration of HCC cells. qRT PCR and Weston Blot experiments also showed that Afatinib can enhance the expression of PD-L1 in tumor cells. In addition, in vitro experiments confirmed that afatinib can significantly enhance the immunotherapeutic effect of hepatocellular carcinoma. Afatinib's ability to increase PD-L1 expression is mediated by STAT3 activation following its action on HCC cells.

Conclusion

Afatinib enhances PD-L1 expression in tumor cells through the STAT3/PD-L1 pathway. The combination of afatinib and anti-PD1 treatment significantly increases the immunotherapeutic effect of HCC.

Prognostic value of autophagy-related genes based on single-cell RNA-sequencing in colorectal cancer

Background: Colorectal cancer (CRC) is the second most common cancer in China. Autophagy plays an important role in the initiation and development of CRC. Here, we assessed the prognostic value and potential functions of autophagy-related genes (ARGs) using integrated analysis using single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) and RNA sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA).

Methods: We analyzed GEO-scRNA-seq data from GEO using various single-cell technologies, including cell clustering, and identification of differentially expressed genes (DEGs) in different cell types. Additionally, we performed gene set variation analysis (GSVA). The differentially expressed ARGs among different cell types and those between CRC and normal tissues were identified using TCGA-RNA-seq data, and the hub ARGs were screened. Finally, a prognostic model based on the hub ARGs was constructed and validated, and patients with CRC in TCGA datasets were divided into high- and low-risk groups based on their risk-score, and immune cells infiltration and drug sensitivity analyses between the two groups were performed.

Results: We obtained single-cell expression profiles of 16,270 cells, and clustered them into seven types of cells. GSVA revealed that the DEGs among the seven types of cells were enriched in many signaling pathways associated with cancer development. We screened 55 differentially expressed ARGs, and identified 11 hub ARGs. Our prognostic model revealed that the 11 hub ARGs including CTSB, ITGA6, and S100A8, had a good predictive ability. Moreover, the immune cell infiltrations in CRC tissues were different between the two groups, and the hub ARGs were significantly correlated with the enrichment of immune cell infiltration. The drug sensitivity analysis revealed that the patients in the two risk groups had difference in their response to anti-cancer drugs.

Conclusion: We developed a novel prognostic 11-hub ARG risk model, and these hubs may act as potential therapeutic targets for CRC.

Artificial Intelligence-Assisted Transcriptomic Analysis to Advance Cancer Immunotherapy

The emergence of immunotherapy has dramatically changed the cancer treatment paradigm and generated tremendous promise in precision medicine. However, cancer immunotherapy is greatly limited by its low response rates and immune-related adverse events. Transcriptomics technology is a promising tool for deciphering the molecular underpinnings of immunotherapy response and therapeutic toxicity. In particular, applying single-cell RNA-seq (scRNA-seq) has deepened our understanding of tumor heterogeneity and the microenvironment, providing powerful help for developing new immunotherapy strategies. Artificial intelligence (AI) technology in transcriptome analysis meets the need for efficient handling and robust results. Specifically, it further extends the application scope of transcriptomic technologies in cancer research. AI-assisted transcriptomic analysis has performed well in exploring the underlying mechanisms of drug resistance and immunotherapy toxicity and predicting therapeutic response, with profound significance in cancer treatment. In this review, we summarized emerging AI-assisted transcriptomic technologies. We then highlighted new insights into cancer immunotherapy based on AI-assisted transcriptomic analysis, focusing on tumor heterogeneity, the tumor microenvironment, immune-related adverse event pathogenesis, drug resistance, and new target discovery. This review summarizes solid evidence for immunotherapy research, which might help the cancer research community overcome the challenges faced by immunotherapy.