High-throughput approaches for precision medicine in high-grade serous ovarian cancer

Global Incidence of Ovarian Cancer According to Histologic Subtype: A Population-Based Cancer Registry Study

PURPOSE

Ovarian cancer can be categorized into distinct histologic subtypes with varying identifiable risk factors, molecular composition, clinical features, and treatment. The global incidence of ovarian cancer subtypes remains limited, especially in low- and middle-income countries (LMICs) without high-quality cancer registry systems.

MATERIALS AND METHODS

We used data from population-based cancer registries of the Cancer Incidence in Five Continents project to calculate the proportions of serous, mucinous, endometrioid, clear cell, and other histologic subtypes of ovarian cancer. Proportions were applied to the estimated numbers of patients with ovarian cancer from Global Cancer Observatory 2020. Age-standardized incidence rates were calculated.

RESULTS

Globally, an estimated 133,818 new patients of serous cancer, 35,712 new patients of mucinous cancer, 29,319 new patients of endometrioid cancer, and 17,894 new patients of clear cell cancer were identified in 2020. The distribution of ovarian cancer histologic subtypes exhibited regional variation. Eastern Europe had the highest rate of serous and mucinous carcinomas, whereas Northern Africa and Eastern Asia had the highest burden of endometrioid and clear cell carcinomas, respectively.

CONCLUSION

This study provides a global incidence landscape of histologic subtypes of ovarian cancer, particularly in LMICs lacking comprehensive registry systems. Our analysis offers valuable insights into disease burden and guidance for tailored strategies for prevention of ovarian cancer.

The development of a novel zeolite-based assay for efficient and deep plasma proteomic profiling

Plasma proteins are considered the most informative source of biomarkers for disease diagnosis and monitoring. Mass spectrometry (MS)-based proteomics has been applied to identify biomarkers in plasma, but the complexity of the plasma proteome and the extremely large dynamic range of protein abundances in plasma make the clinical application of plasma proteomics highly challenging. We designed and synthesized zeolite-based nanoparticles to deplete high-abundance plasma proteins. The resulting novel plasma proteomic assay can measure approximately 3000 plasma proteins in a 45 min chromatographic gradient. Compared to those in neat and depleted plasma, the plasma proteins identified by our assay exhibited distinct biological profiles, as validated in several public datasets. A pilot investigation of the proteomic profile of a hepatocellular carcinoma (HCC) cohort identified 15 promising protein features, highlighting the diagnostic value of the plasma proteome in distinguishing individuals with and without HCC. Furthermore, this assay can be easily integrated with all current downstream protein profiling methods and potentially extended to other biofluids. In conclusion, we established a robust and efficient plasma proteomic assay with unprecedented identification depth, paving the way for the translation of plasma proteomics into clinical applications.

Macrophage Checkpoint Nanoimmunotherapy Has the Potential to Reduce Malignant Progression in Bioengineered In Vitro Models of Ovarian Cancer

Most ovarian carcinoma (OvCa) patients present with advanced disease at the time of diagnosis. Malignant, metastatic OvCa is invasive and has poor prognosis, exposing the need for improved therapeutic targeting. High CD47 (OvCa) and SIRPα (macrophage) expression has been linked to decreased survival, making this interaction a significant target for therapeutic discovery. Even so, previous attempts have fallen short, limited by CD47 antibody specificity and efficacy. Macrophages are an important component of the OvCa tumor microenvironment and are manipulated to aid in cancer progression via CD47-SIRPα signaling. Thus, we have leveraged lipid-based nanoparticles (LNPs) to design a therapy uniquely situated to home to phagocytic macrophages expressing the SIRPα protein in metastatic OvCa. CD47-SIRPα presence was evaluated in patient histological sections using immunohistochemistry. 3D tumor spheroids generated on a hanging drop array with OVCAR3 high-grade serous OvCa and THP-1-derived macrophages created a representative model of cellular interactions involved in metastatic OvCa. Microfluidic techniques were employed to generate LNPs encapsulating SIRPα siRNA (siSIRPα) to affect the CD47-SIRPα signaling between the OvCa and macrophages. siSIRPα LNPs were characterized for optimal size, charge, and encapsulation efficiency. Uptake of the siSIRPα LNPs by macrophages was assessed by Incucyte. Following 48 h of 25 nM siSIRPα treatment, OvCa/macrophage heterospheroids were evaluated for SIRPα knockdown, platinum chemoresistance, and invasiveness. OvCa patient tumors and in vitro heterospheroids expressed CD47 and SIRPα. Macrophages in OvCa spheroids increased carboplatin resistance and invasion, indicating a more malignant phenotype. We observed successful LNP uptake by macrophages causing significant reduction in SIRPα gene and protein expressions and subsequent reversal of pro-tumoral alternative activation. Disrupting CD47-SIRPα interactions resulted in sensitizing OvCa/macrophage heterospheroids to platinum chemotherapy and reversal of cellular invasion outside of heterospheroids. Ultimately, our results strongly indicate the potential of using LNP-based nanoimmunotherapy to reduce malignant progression of ovarian cancer.

The CDK4/6 Inhibitor Palbociclib Induces Cell Senescence of High-grade Serous Ovarian Cancer Through Acetylation of p53

Cell senescence is an anti-cancer strategy following DNA repair and apoptosis, which is associated with the initiation, progression, and treatment of ovarian cancer. The CDK4/6 inhibitor alters cell cycle and induces cell senescence dependent on retinoblastoma (RB) family proteins. Objective Herein, we aimed to explore the effects of Palbociclib (a CDK4/6 inhibitor) on cellular senescence of high-grade serous ovarian cancer (HGSOC). Cell viability and cell cycle were evaluated by cell counting kit-8 and flow cytometry. Cell senescence was analyzed using the SA-β-gal staining assay. The senescence-associated secretory phenotype was assessed using quantitative PCR (qPCR). Senescence-related markers were tested using western blot. The role of Palbociclib in vivo was clarified using xenograft tumor. Acetylation of p53 was evaluated by qPCR and western blot. The results showed that Palbociclib inhibited cell viability, blocked cell cycle at G0/G1 phase, and induced cell senescence. A rescue study indicated that knockdown of p53 reversed the effects on cell cycle and senescence induced by Palbociclib. Moreover, we found that Palbociclib promotes P300-mediated p53 acetylation, thus increasing p53 stability and transcription activity. Moreover, Palbociclib suppressed tumor growth in vivo with increased p53 and acetylated p53 levels. In conclusion, Palbociclib induced cell senescence of HGSOC through P300-mediated p53 acetylation, suggesting that Palbociclib may have the effect of treating HGSOC.

Targeted Mass Spectrometry of Longitudinal Patient Sera Reveals LTBP1 as a Potential Surveillance Biomarker for High-Grade Serous Ovarian Carcinoma

High-grade serous ovarian carcinoma (HGSC) is the most prevalent subtype of epithelial ovarian cancer. The combination of a high rate of recurrence and novel therapies in HGSC necessitates an accurate assessment of the disease. Currently, HGSC response to treatment and recurrence are monitored via immunoassay of serum levels of the glycoprotein CA125. CA125 levels predictably rise at HGSC recurrence; however, it is likely that the disease is progressing even before it is detectable through CA125. This may explain why treating solely based on CA125 increase has not been associated with improved outcomes. Thus, additional biomarkers that monitor HGSC progression and cancer recurrence are needed. For this purpose, we developed a scheduled parallel reaction monitoring mass spectrometry (PRM-MS) assay for the quantification of four previously identified HGSC-derived glycopeptides (from proteins FGL2, LGALS3BP, LTBP1, and TIMP1). We applied the assay to quantify their longitudinal expression profiles in 212 serum samples taken from 34 HGSC patients during disease progression. Analyses revealed that LTBP1 best-mirrored tumor load, dropping as a result of cancer treatment in 31 out of 34 patients and rising at HGSC recurrence in 28 patients. Additionally, LTBP1 rose earlier during remission than CA125 in 11 out of 25 platinum-sensitive patients with an average lead time of 116.4 days, making LTBP1 a promising candidate for monitoring of HGSC recurrence.

Silver nitroprusside as an efficient chemodynamic therapeutic agent and a peroxynitrite nanogenerator for targeted cancer therapies

INTRODUCTION

Chemodynamic therapy (CDT) holds great promise in achieving cancer therapy through Fenton and Fenton-like reactions, which generate highly toxic reactive species. However, CDT is limited by the lower amount of catalyst ions that can decompose already existing intracellular H2O2 and produce reactive oxygen species (ROS) to attain a therapeutic outcome.

OBJECTIVES

To overcome these limitations, a tailored approach, which utilizes dual metals cations (Ag+, Fe2+) based silver pentacyanonitrosylferrate or silver nitroprusside (AgNP) were developed for Fenton like reactions that can specifically kill cancer cells by taking advantage of tumor acidic environment without used of any external stimuli.

METHODS

A simple solution mixing procedure was used to synthesize AgNP as CDT agent. AgNP were structurally and morphologically characterized, and it was observed that a minimal dose of AgNP is required to destroy cancer cells with limited effects on normal cells. Moreover, comprehensive in vitro studies were conducted to evaluate antitumoral mechanism.

RESULTS

AgNP have an effective ability to decompose endogenous H2O2 in cells. The decomposed endogenous H2O2 generates several different types of reactive species (•OH, O2•-) including peroxynitrite (ONOO-) species as apoptotic inducers that kill cancer cells, specifically. Cellular internalization data demonstrated that in short time, AgNP enters in lysosomes, avoid degradation and due to the acidic pH of lysosomes significantly generate high ROS levels. These data are further confirmed by the activation of different oxidative genes. Additionally, we demonstrated the biocompatibility of AgNP on mouse liver and ovarian organoids as an ex vivo model while AgNP showed the therapeutic efficacy on patient derived tumor organoids (PDTO).

CONCLUSION

This work demonstrates the therapeutic application of silver nitroprusside as a multiple ROS generator utilizing Fenton like reaction. Thereby, our study exhibits a potential application of CDT against HGSOC (High Grade Serous Ovarian Cancer), a deadly cancer through altering the redox homeostasis.

Current Applications and Challenges of Next-Generation Sequencing in Plasma Circulating Tumour DNA of Ovarian Cancer

Circulating tumour DNA (ctDNA) facilitates longitudinal study of the tumour genome, which, unlike tumour tissue biopsies, globally reflects intratumor and intermetastatis heterogeneity. Despite its costs, next-generation sequencing (NGS) has revolutionised the study of ctDNA, ensuring a more comprehensive and multimodal approach, increasing data collection, and introducing new variables that can be correlated with clinical outcomes. Current NGS strategies can comprise a tumour-informed set of genes or the entire genome and detect a tumour fraction as low as 10-5. Despite some conflicting studies, there is evidence that ctDNA levels can predict the worse outcomes of ovarian cancer (OC) in both early and advanced disease. Changes in those levels can also be informative regarding treatment efficacy and tumour recurrence, capable of outperforming CA-125, currently the only universally utilised plasma biomarker in high-grade serous OC (HGSOC). Qualitative evaluation of sequencing shows that increasing copy number alterations and gene variants during treatment may correlate with a worse prognosis in HGSOC. However, following tumour clonality and emerging variants during treatment poses a more unique opportunity to define treatment response, select patients based on their emerging resistance mechanisms, like BRCA secondary mutations, and discover potential targetable variants. Sequencing of tumour biopsies and ctDNA is not always concordant, likely as a result of clonal heterogeneity, which is better captured in the plasma samples than it is in a large number of biopsies. These incoherences may reflect tumour clonality and reveal the acquired alterations that cause treatment resistance. Cell-free DNA methylation profiles can be used to distinguish OC from healthy individuals, and NGS methylation panels have been shown to have excellent diagnostic capabilities. Also, methylation signatures showed promise in explaining treatment responses, including BRCA dysfunction. ctDNA is evolving as a promising new biomarker to track tumour evolution and clonality through the treatment of early and advanced ovarian cancer, with potential applicability in prognostic prediction and treatment selection. While its role in HGSOC paves the way to clinical applicability, its potential interest in other histological subtypes of OC remains unknown.

Patient-derived tumor models in cancer research: Evaluation of the oncostatic effects of melatonin

The development of new anticancer therapies tends to be very slow. Although their impact on potential candidates is confirmed in preclinical studies, ∼95 % of these new therapies are not approved when tested in clinical trials. One of the main reasons for this is the lack of accurate preclinical models. In this context, there are different patient-derived models, which have emerged as a powerful oncological tool: patient-derived xenografts (PDXs), patient-derived organoids (PDOs), and patient-derived cells (PDCs). Although all these models are widely applied, PDXs, which are created by engraftment of patient tumor tissues into mice, is considered more reliable. In fundamental research, the PDX model is used to evaluate drug-sensitive markers and, in clinical practice, to select a personalized therapeutic strategy. Melatonin is of particular importance in the development of innovative cancer treatments due to its oncostatic impact and lack of adverse effects. However, the literature regarding the oncostatic effect of melatonin in patient-derived tumor models is scant. This review aims to describe the important role of patient-derived models in the development of anticancer treatments, focusing, in particular, on PDX models, as well as their use in cancer research. This review also summarizes the existing literature on the anti-tumoral effect of melatonin in patient-derived models in order to propose future anti-neoplastic clinical applications.

CCNB1 is a novel prognostic biomarker and promotes proliferation, migration and invasion in Wilms tumor

BACKGROUND

Wilms tumour (WT) is a mixed type of embryonal tumour that usually occurs in early childhood. However, our knowledge of the pathogenesis or progression mechanism of WT is inadequate, and there is a scarcity of beneficial therapeutic strategies.

METHODS

High-throughput RNA sequencing was employed in this study to identify differentially expressed genes (DEGs) in clinical tumor samples and matching normal tissues. The STRING database was utilized to build a protein-protein interaction (PPI) network, and the Cytohubba method was used to identify the top 10 highly related HUB genes. Then, the key genes were further screened by univariate COX survival analysis. Subsequently, the XCELL algorithm was used to evaluate the tumour immune infiltration. RT-PCR, WB, and IF were used to verify the expression level of key genes in clinical tissues and tumour cell lines. Finally, the function of the key gene was further verified by loss-of-function experiments.

RESULTS

We initially screened 1612 DEGs, of which 1030 were up-regulated and 582 were down-regulated. The GO and KEGG enrichment analysis suggested these genes were associated with 'cell cycle', 'DNA replication'. Subsequently, we identified 10 key HUB genes, among them CCNB1 was strongly related to WT patients' overall survival. Multiple survival analyses showed that CCNB1 was an independent indicator of WT prognosis. Thus, we constructed a nomogram of CCNB1 combined with other clinical indicators. Single gene GSEA and immune infiltration analysis revealed that CCNB1 was associated with the degree of infiltration or activation status of multiple immune cells. TIDE analysis indicated that this gene was correlated with multiple key immune checkpoint molecules and TIDE scores. Finally, we validated the differential expression level of CCNB1 in an external gene set, the pan-cancer, clinical samples, and cell lines. CCNB1 silencing significantly inhibited the proliferation, migration, and invasive capabilities of WIT-49 cells, also, promoted apoptosis, and in turn induced G2 phase cell cycle arrest in loss-of-function assays.

CONCLUSION

Our study suggests that CCNB1 is closely related to WT progression and prognosis, and serves as a potential target.

Gain-of-function p53R175H blocks apoptosis in a precursor model of ovarian high-grade serous carcinoma

Ovarian high-grade serous carcinoma (HGSC) is a highly lethal malignancy for which early detection is a challenge and treatment of late-stage disease is ineffective. HGSC initiation involves exfoliation of fallopian tube epithelial (FTE) cells which form multicellular clusters called spheroids that colonize and invade the ovary. HGSC contains universal mutation of the tumour suppressor gene TP53. However, not all TP53 mutations are the same, as specific p53 missense mutants contain gain-of-function (GOF) properties that drive tumour formation. Additionally, the role of GOF p53 in spheroid-mediated spread is poorly understood. In this study, we developed and characterized an in vitro model of HGSC based on mutation of TP53 in mouse oviductal epithelial cells (OVE). We discovered increased bulk spheroid survival and increased anchorage-independent growth in OVE cells expressing the missense mutant p53R175H compared to OVE parental and Trp53ko cells. Transcriptomic analysis on spheroids identified decreased apoptosis signaling due to p53R175H. Further assessment of the apoptosis pathway demonstrated decreased expression of intrinsic and extrinsic apoptosis signaling molecules due to Trp53 deletion and p53R175H, but Caspase-3 activation was only decreased in spheroids with p53R175H. These results highlight this model as a useful tool for discovering early HGSC transformation mechanisms and uncover a potential anti-apoptosis GOF mechanism of p53R175H.

Early warning and diagnosis of liver cancer based on dynamic network biomarker and deep learning

Background

Early detection of complex diseases like hepatocellular carcinoma remains challenging due to their network-driven pathology. Dynamic network biomarkers (DNB) based on monitoring changes in molecular correlations may enable earlier predictions. However, DNB analysis often overlooks disease heterogeneity.

Methods

We integrated DNB analysis with graph convolutional neural networks (GCN) to identify critical transitions during hepatocellular carcinoma development in a mouse model. A DNB-GCN model was constructed using transcriptomic data and gene expression levels as node features.

Results

DNB analysis identified a critical transition point at 7 weeks of age despite histological examinations being unable to detect cancerous changes at that time point. The DNB-GCN model achieved 100% accuracy in classifying healthy and cancerous mice, and was able to accurately predict the health status of newly introduced mice.

Conclusion

The integration of DNB analysis and GCN demonstrates potential for the early detection of complex diseases by capturing network structures and molecular features that conventional biomarker discovery methods overlook. The approach warrants further development and validation.

FAK inhibitor PF-562271 inhibits the migration and proliferation of high-grade serous ovarian cancer cells through FAK and FAK mediated cell cycle arrest

Focal adhesion kinase (FAK) is a promising therapeutic target for various cancers and its inhibitor development is in full swing. PF-562271 is a classic FAK inhibitor that has shown promising preclinical data and has been found to exhibit an anti-migration effect on some cancer cells. However, its anticancer effect on high-grade serous ovarian cancer (HGSOC) has not been reported. In this study, we evaluated the anti-migration and anti-proliferation effects of PF-562271 against HGSOC SKOV3 and A2780 cells, as well as the underlying mechanism. The results demonstrated that FAK was overexpressed in clinical HGSOC tissues and was positively correlated with the pathological progression of HGSOC. Moreover, HGSOC patients with high FAK expression levels exhibited low survival rates. PF-562271 treatment significantly inhibited the cell adhesion and migration of SKOV3 and A2780 cells by inhibiting p-FAK expression and decreasing the FA surface area. Additionally, PF-562271 treatment inhibited colony formation and induced cell senescence through G1 phase cell cycle arrest mediated DNA replication inhibition. Taken together, the findings demonstrated that FAK inhibitor PF-562271 significantly inhibits HGSOC cell adhesion, migration, and proliferation process through FAK and/or FAK mediated cell cycle arrest, and suggested that PF-562271 could serve as a potential oncotherapeutic agent for HGSOC targeting treatment.

Iron nitroprusside as a chemodynamic agent and inducer of ferroptosis for ovarian cancer therapy

ChemoDynamic Therapy (CDT) is a powerful therapeutic modality using Fenton/Fenton-like reactions to produce oxidative stress for cancer treatment. However, the insufficient amount of catalyst ions and ROS scavenging activity of glutathione peroxidase (GPX4) limit the application of this approach. Therefore, a tailored strategy to regulate the Fenton reaction more efficiently (utilizing dual metal cations) and inhibit the GPX4 activity, is in great demand. Herein, a CDT system is based on dual (Fe²⁺ metals) iron pentacyanonitrosylferrate or iron nitroprusside (FeNP) having efficient ability to catalyze the reaction of endogenous H₂O₂ to form highly toxic ˙OH species in cells. Additionally, FeNP is involved in ferroptosis via GPX4 inhibition. In particular, FeNP was structurally characterized, and it is noted that a minimum dose of FeNP is required to kill cancer cells while a comparable dose shows negligible toxicity on normal cells. Detailed in vitro studies confirmed that FeNP participates in sustaining apoptosis, as determined using the annexin V marker. Cellular uptake results showed that in a short time period, FeNP enters lysosomes and, due to the acidic lysosomal pH, releases Fe²⁺ ions, which are involved in ROS generation (˙OH species). Western blot analyses confirmed the suppression of GPX4 activity over time. Importantly, FeNP has a therapeutic effect on ovarian cancer organoids derived from High-Grade Serous Ovarian Cancer (HGSOC). Furthermore, FeNP showed biocompatible nature towards normal mouse liver organoids and in vivo. This work presents the effective therapeutic application of FeNP as an efficient Fenton agent along with ferroptosis inducer activity to improve CDT, through disturbing redox homeostasis.

EVI2B Is a Prognostic Biomarker and Is Correlated with Monocyte and Macrophage Infiltration in Osteosarcoma Based on an Integrative Analysis

Osteosarcoma (OS) is the most common malignant bone tumor. However, treatment strategies have not changed over the past 30 years. The relationship between OS and the immune microenvironment may provide a basis for the establishment of novel therapeutic targets. In this study, a large-scale gene expression dataset (GSE42352) was used to identify key genes in OS. A Target-OS dataset from the Cancer Genome Atlas was used as a validation set. Ecotropic viral integration site 2B (EVI2B) was significantly upregulated in OS tumor samples. Differentially expressed genes (DEGs) were identified between samples with high and low EVI2B expression in both the test and validation cohorts. The top three functions of DEGs determined by a gene set enrichment analysis (GSEA) were chemokine signaling, cytokine-cytokine receptor interaction, and Human T-cell leukemia virus 1 infection. A prognostic prediction model including EVI2B, DOCK2, and CD33 was constructed by a Cox regression analysis. This model indicated that EVI2B is an independent protective prognostic marker in OS. An analysis of immune infiltration further showed that high EVI2B expression levels were correlated with high levels of macrophage infiltration. Protein expression data derived from the Human Protein Atlas suggested EVI2B to be highly expressed in monocytes. Finally, we validated the elevated expression of EVI2B in OS cell lines and OS tissue samples; these results were consistent with those of the analyses of the GSE42352 and Target-OS datasets. Our integrative bioinformatics analysis and experimental results provide clear evidence for the prognostic value of EVI2B in OS and its close relationship with monocyte and macrophage infiltration.

Computable structured aptamer for targeted treatment of ovarian cancer

Nucleolin protein expression is higher on the ovarian cancer cell surface. AS1411, a DNA aptamer, can bind with nucleolin protein specifically. In this study, we developed HA and ST DNA tiles to assemble six AS1411 aptamers to deliver doxorubicin. In addition, to superior serum stability and drug loading, HA-6AS and ST-6AS outperformed TDN-AS in cellular uptake. HA-6AS and ST-6AS exhibited satisfactory targeted cytotoxicity and achieved resounding lysosomal escape. Moreover, when injected into nude mice subcutaneous xenograft models, HA-6AS reached the peak in tumor more quickly than ST-6AS, and better expressed the active targeting ability of AS1411. Our study suggests that designing appropriate DNA tiles to assemble different aptamers to deliver different chemotherapeutic drugs is a promising treatment for ovarian cancer.

Differential Diagnosis of Hematologic and Solid Tumors Using Targeted Transcriptome and Artificial Intelligence

Diagnosis and classification of tumors is increasingly dependent on biomarkers. RNA expression profiling using next-generation sequencing provides reliable and reproducible information on the biology of cancer. This study investigated targeted transcriptome and artificial intelligence for differential diagnosis of hematologic and solid tumors. RNA samples from hematologic neoplasms (N = 2606), solid tumors (N = 2038), normal bone marrow (N = 782), and lymph node control (N = 24) were sequenced using next-generation sequencing using a targeted 1408-gene panel. Twenty subtypes of hematologic neoplasms and 24 subtypes of solid tumors were identified. Machine learning was used for diagnosis between two classes. Geometric mean naïve Bayesian classifier was used for differential diagnosis across 45 diagnostic entities with assigned rankings. Machine learning showed high accuracy in distinguishing between two diagnoses, with area under the curve varying between 1 and 0.841. Geometric mean naïve Bayesian algorithm was trained using 3045 samples and tested on 1415 samples, and showed correct first-choice diagnosis in 100%, 88%, 85%, 82%, 88%, 72%, and 72% of acute lymphoblastic leukemia, acute myeloid leukemia, diffuse large B-cell lymphoma, colorectal cancer, lung cancer, chronic lymphocytic leukemia, and follicular lymphoma cases, respectively. The data indicate that targeted transcriptome combined with artificial intelligence are highly useful for diagnosis and classification of various cancers. Mutation profiles and clinical information can improve these algorithms and minimize errors in diagnoses.

Proteomics of High-Grade Serous Ovarian Cancer Models Identifies Cancer-Associated Fibroblast Markers Associated with Clinical Outcomes

The tumor microenvironment has recently emerged as a critical component of high-grade serous ovarian cancer (HGSC) disease progression. Specifically, cancer-associated fibroblasts (CAFs) have been recognized as key players in various pro-oncogenic processes. Here, we use mass-spectrometry (MS) to characterize the proteomes of HGSC patient-derived CAFs and compare them to those of the epithelial component of HGSC to gain a deeper understanding into their tumor-promoting phenotype. We integrate our data with primary tissue data to define a proteomic signature of HGSC CAFs and uncover multiple novel CAF proteins that are prognostic in an independent HGSC patient cohort. Our data represent the first MS-based global proteomic characterization of CAFs in HGSC and further highlights the clinical significance of HGSC CAFs.

Combined Usage of MDK Inhibitor Augments Interferon-γ Anti-Tumor Activity in the SKOV3 Human Ovarian Cancer Cell Line

Ovarian cancer (OC) is a particularly lethal disease due to intratumoral heterogeneity, resistance to traditional chemotherapy, and poor response to targeted therapy and immunotherapy. Interferon-γ (IFN-γ) is an attractive therapeutic cytokine, with positive responses achieved in multiple OC clinical trials. However, clinical application of IFN-γ in OC is still hindered, due to the severe toxicity when used at higher levels, as well as the considerable pro-metastatic adverse effect when used at lower levels. Thus, an effective combined intervention is needed to enhance the anti-tumor efficacy of IFN-γ and to suppress the IFN-γ-induced metastasis. Here, we uncovered that OC cells develop an adaptive strategy by upregulating midkine (MDK) to counteract the IFN-γ-induced anti-tumor activity and to fuel IFN-γ-induced metastasis. We showed that MDK is a critical downstream target of IFN-γ in OC, and that this regulation acts in a dose-dependent manner and is mediated by STAT1. Gain-of-function studies showed that MDK overexpression promotes cell proliferation and metastasis in OC, indicating that IFN-γ-activated MDK may antagonize IFN-γ in inhibiting OC proliferation but synergize IFN-γ in promoting OC metastasis. Subsequently, we assessed the influence of MDK inhibition on IFN-γ-induced anti-proliferation and pro-metastasis effects using an MDK inhibitor (iMDK), and we found that MDK inhibition robustly enhanced IFN-γ-induced growth inhibition (all CIs < 0.1) and reversed IFN-γ-driven epithelial-to-mesenchymal transition (EMT) and metastasis in OC in vitro. Collectively, these data identify an IFN-γ responsive protein, MDK, in counteracting anti-proliferation while endowing the pro-metastatic role of IFN-γ in cancer treatment, and we therefore propose the combined utilization of the MDK inhibitor in IFN-γ-based therapies in future OC treatment.

The application of circulating tumor cell and cell-free DNA liquid biopsies in ovarian cancer

Ovarian cancer is the deadliest gynecological cancer. 70% of the cases are diagnosed at late stages with already developed metastases due to the absence of easily noticeable symptoms. Early-stage ovarian cancer has a good prognosis with a 5-year survival rate reaching 95%, hence the identification of effective biomarkers for early diagnosis is important. Advances in liquid biopsy-based methods can have a significant impact not just on the development of an efficient screening strategy, but also in clinical decision-making with additional molecular profiling and genetic alterations linked to therapy resistance. Despite the well-known advantages of liquid biopsy, there are still challenges that need to be addressed before its routine use in clinical practice. Various liquid biopsy-based biomarkers have been investigated in ovarian cancer; however, in this review, we are concentrating on the current use of cell-free DNA (cfDNA) and circulating tumor cells (CTCs) in disease management, focusing on their emerging importance in clinical practice. We also discuss the technical aspects of these workflows. The analysis of cfDNA is often chosen for the detection of mutations, copy number aberrations, and DNA methylation changes, whereas CTC analysis provides a unique opportunity to study whole cells, thus allowing DNA, RNA, and protein-based molecular profiling as well as in vivo studies. Combined solutions which merge the strengths of cfDNA and CTC approaches should be developed to maximize the potential of liquid biopsy technology.

Transcriptome Profiling of Eutopic and Ectopic Endometrial Stromal Cells in Women with Endometriosis Based on High-Throughput Sequencing

Endometriosis is a common gynecological disease that affects approximately 5–10% of reproductive-aged women. However, the etiology and pathophysiology of endometriosis are currently unclear. The objective of this study was to identify a potential pathogenic gene of endometriosis using RNA sequencing (RNA-seq) analysis. Human endometrial stromal cells were isolated from four patients receiving surgical treatment for endometriosis during laparoscopic surgery, and RNA-seq was used to examine differentially expressed genes (DEGs) in eutopic and ectopic endometrial stromal cells. The functional significance of the differentially expressed genes was analyzed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. A total of 1309 upregulated and 663 downregulated genes were identified through the analysis of the transcriptomes of eutopic and ectopic endometrial stromal cells. Furthermore, KEGG analysis indicated that these DEGs were mainly enriched in the PI3K-Akt signaling pathway, cytokine–cytokine receptor interaction, and MAPK signaling pathway. Our study identified differential gene expression in eutopic as compared to ectopic endometrial tissue stromal cells. We strongly believe that our findings can bring new insights into the underlying mechanisms of endometriosis. However, future research is necessary to clarify the roles of the identified genes.

Identification of immune-related hub genes and miRNA-mRNA pairs involved in immune infiltration in human septic cardiomyopathy by bioinformatics analysis

Abstract

Septic cardiomyopathy (SCM) is a serious complication caused by sepsis that will further exacerbate the patient's prognosis. However, immune-related genes (IRGs) and their molecular mechanism during septic cardiomyopathy are largely unknown. Therefore, our study aims to explore the immune-related hub genes (IRHGs) and immune-related miRNA-mRNA pairs with potential biological regulation in SCM by means of bioinformatics analysis and experimental validation.

Method

Firstly, screen differentially expressed mRNAs (DE-mRNAs) from the dataset GSE79962, and construct a PPI network of DE-mRNAs. Secondly, the hub genes of SCM were identified from the PPI network and the hub genes were overlapped with immune cell marker genes (ICMGs) to further obtain IRHGs in SCM. In addition, receiver operating characteristic (ROC) curve analysis was also performed in this process to determine the disease diagnostic capability of IRHGs. Finally, the crucial miRNA-IRHG regulatory network of IRHGs was predicted and constructed by bioinformatic methods. Real-time quantitative reverse transcription-PCR (qRT-PCR) and dataset GSE72380 were used to validate the expression of the key miRNA-IRHG axis.

Result

The results of immune infiltration showed that neutrophils, Th17 cells, Tfh cells, and central memory cells in SCM had more infiltration than the control group; A total of 2 IRHGs were obtained by crossing the hub gene with the ICMGs, and the IRHGs were validated by dataset and qRT-PCR. Ultimately, we obtained the IRHG in SCM: THBS1. The ROC curve results of THBS1 showed that the area under the curve (AUC) was 0.909. Finally, the miR-222-3p/THBS1 axis regulatory network was constructed.

Conclusion

In summary, we propose that THBS1 may be a key IRHG, and can serve as a biomarker for the diagnosis of SCM; in addition, the immune-related regulatory network miR-222-3p/THBS1 may be involved in the regulation of the pathogenesis of SCM and may serve as a promising candidate for SCM therapy.

Decreased Levels of GSH Are Associated with Platinum Resistance in High-Grade Serous Ovarian Cancer

High-grade serous ovarian cancer (HGSOC) is the most common and aggressive OC histotype. Although initially sensitive to standard platinum-based chemotherapy, most HGSOC patients relapse and become chemoresistant. We have previously demonstrated that platinum resistance is driven by a metabolic shift toward oxidative phosphorylation via activation of an inflammatory response, accompanied by reduced cholesterol biosynthesis and increased uptake of exogenous cholesterol. To better understand metabolic remodeling in OC, herein we performed an untargeted metabolomic analysis, which surprisingly showed decreased reduced glutathione (GSH) levels in resistant cells. Accordingly, we found reduced levels of enzymes involved in GSH synthesis and recycling, and compensatory increased expression of thioredoxin reductase. Cisplatin treatment caused an increase of reduced GSH, possibly due to direct binding hindering its oxidation, and consequent accumulation of reactive oxygen species. Notably, expression of the cysteine-glutamate antiporter xCT, which is crucial for GSH synthesis, directly correlates with post-progression survival of HGSOC patients, and is significantly reduced in patients not responding to platinum-based therapy. Overall, our data suggest that cisplatin treatment could positively select cancer cells which are independent from GSH for the maintenance of redox balance, and thus less sensitive to cisplatin-induced oxidative stress, opening new scenarios for the GSH pathway as a therapeutic target in HGSOC.

N6-methyladenosine (m6A) modification in gynecological malignancies

N6-methyladenosine (m6A) modification is one of the most abundant modifications in eukaryotic mRNA, regulated by m6A methyltransferase and demethylase. m6A modified RNA is specifically recognized and bound by m6A recognition proteins, which mediate splicing, maturation, exonucleation, degradation, and translation. In gynecologic malignancies, m6A RNA modification-related molecules are expressed aberrantly, significantly altering the posttranscriptional methylation level of the target genes and their stability. The m6A modification also regulates related metabolic pathways, thereby controlling tumor development. This review analyzes the composition and mode of action of m6A modification-related proteins and their biological functions in the malignant progression of gynecologic malignancies, which provide new ideas for the early clinical diagnosis and targeted therapy of gynecologic malignancies.

The Roles of Drug Metabolism-Related ADH1B in Immune Regulation and Therapeutic Response of Ovarian Cancer

Background: The different pharmacological effects of drugs in different people can be explained by the polymorphisms of drug metabolism-related genes. Emerging studies have realized the importance of drug metabolism-related genes in the treatment and prognosis of cancers, including ovarian cancer (OV). In this study, using comprehensive bioinformatics and western blot, we identified that the drug metabolism-related gene, ADH1B, was significantly down-regulated in OV cells and tissues. The patients with a high level of ADH1B presented a good prognosis. We also found a negative correlation between ADH1B expression and the activity of chemotherapeutic agents, such as cyclophosphamide. In addition, positive correlations were observed between ADH1B expression and multiple immune checkpoints, including LAG3 and HAVCR2. The immune infiltration analysis further indicated that aberrantly expressed ADH1B might have important roles in regulating the infiltration of macrophages and neutrophils in OV tissues. Then, the co-expression analysis was conducted and the top three enriched KEGG pathways were spliceosome, RNA transport, and DNA replication. In conclusion, the drug metabolism-related gene ADH1B and its interactive network play an essential role in the immune regulation and therapeutic response and maybe identified as promising therapeutic targets for OV patients.

Evaluation of serum tRF-23-Q99P9P9NDD as a potential biomarker for the clinical diagnosis of gastric cancer

Background

Gastric cancer (GC) is one of the diseases that endanger human health with high morbidity and mortality. The positive rates of traditional biomarkers in the diagnosis of GC are low, so it is necessary to find biomarkers with high sensitivity to increase the detection rate. tRNA-derived small RNAs (tsRNAs) are novel small non-coding RNAs with specific biological functions and aberrant expression in cancer. In this study, we focused on the potential of tRNA-derived small RNAs as GC biomarkers.

Methods

The differentially expressed tsRNAs in three pairs of GC tissues were screened with high-throughput sequencing and verified using the TCGA database and Quantitative real-time PCR. The methodological evaluation of tRF-23-Q99P9P9NDD was verified by agarose gel electrophoresis, RIN evaluation, and Sanger sequencing. The Chi-square test was used to evaluate the relationship between the tRF-23-Q99P9P9NDD expression and clinicopathological parameters. Kaplan–Meier survival analysis was used to evaluate the effect of the tRF-23-Q99P9P9NDD expression on survival. Additionally, the receiver operating characteristic curve (ROC) was used to evaluate the diagnostic efficacy of tRF-23-Q99P9P9NDD in GC.

Results

Differential expression of serum tRF-23-Q99P9P9NDD could distinguish GC patients from gastritis patients and healthy donors. Chi-square test showed that high expression of tRF-23-Q99P9P9NDD was significantly associated with T stage, lymph node metastasis, TNM stage, and nerve/vascular invasion. Kaplan–Meier curve showed that patients with high expression of tRF-23-Q99P9P9NDD had a lower survival rate than patients with low expression of this biomarker. ROC analysis showed that, compared with conventional biomarkers, the efficacy of tRF-23-Q99P9P9NDD was higher, which was improved by the combination of biomarkers, and even in the early stages. Finally, we preliminarily predicted the downstream of tRF-23-Q99P9P9NDD in GC cells.

Conclusions

The expression of tRF-23-Q99P9P9NDD in GC serum can identify GC patients, and it has higher efficacy than conventional biomarkers even in the early stages. Furthermore, tRF-23-Q99P9P9NDD can monitor the postoperative conditions of GC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s10020-022-00491-8.

PTH2R is related to cell proliferation and migration in ovarian cancer: a multi-omics analysis of bioinformatics and experiments

Background

Ovarian cancer is a common gynecological disease and seriously endangers women's health. Currently, there is still a lack of effective molecular markers for the diagnosis and treatment of ovarian cancer. The present study aimed to investigate the molecular markers associated with ovarian cancer.

Methods

The molecular and gene related to ovarian cancer were extracted from GEO database and TCGA database by bioinformatics, and the related genes and functions were further analyzed. The results were verified by qPCR, WB, CCK-8 and Transwell experiments.

Results

Data analysis showed that PTH2R gene was highly expressed in tumors, and 51 HUB genes were obtained. Finally, experimental verification showed that PTH2R gene was highly expressed in ovarian cancer, and PTH2R gene was involved in the proliferation, invasion and metastasis of ovarian cancer cells.

Conclusions

After experimental verification, we found that knocking down the expression of PTH2R can inhibit the proliferation, invasion and migration of tumor cells.PTH2R is expected to become a new molecular marker for ovarian cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-022-02566-2.

Patient-derived tumor models are attractive tools to repurpose drugs for ovarian cancer treatment: Pre-clinical updates

Despite advances in understanding of ovarian cancer biology, the progress in translation of research findings into new therapies is still slow. It is associated in part with limitations of commonly used cancer models such as cell lines and genetically engineered mouse models that lack proper representation of diversity and complexity of actual human tumors. In addition, the development of de novo anticancer drugs is a lengthy and expensive process. A promising alternative to new drug development is repurposing existing FDA-approved drugs without primary oncological purpose. These approved agents have known pharmacokinetics, pharmacodynamics, and toxicology and could be approved as anticancer drugs quicker and at lower cost. To successfully translate repurposed drugs to clinical application, an intermediate step of pre-clinical animal studies is required. To address challenges associated with reliability of tumor models for pre-clinical studies, there has been an increase in development of patient-derived xenografts (PDXs), which retain key characteristics of the original patient’s tumor, including histologic, biologic, and genetic features. The expansion and utilization of clinically and molecularly annotated PDX models derived from different ovarian cancer subtypes could substantially aid development of new therapies or rapid approval of repurposed drugs to improve treatment options for ovarian cancer patients.

Personalized models of heterogeneous 3D epithelial tumor microenvironments: Ovarian cancer as a model

Intractable human diseases such as cancers, are context dependent, unique to both the individual patient and to the specific tumor microenvironment. However, conventional cancer treatments are often nonspecific, targeting global similarities rather than unique drivers. This limits treatment efficacy across heterogeneous patient populations and even at different tumor locations within the same patient. Ultimately, this poor efficacy can lead to adverse clinical outcomes and the development of treatment-resistant relapse. To prevent this and improve outcomes, it is necessary to be selective when choosing a patient's optimal adjuvant treatment. In this review, we posit the use of personalized, tumor-specific models (TSM) as tools to achieve this remarkable feat. First, using ovarian cancer as a model disease, we outline the heterogeneity and complexity of both the cellular and extracellular components in the tumor microenvironment. Then we examine the advantages and disadvantages of contemporary cancer models and the rationale for personalized TSM. We discuss how to generate precision 3D models through careful and detailed analysis of patient biopsies. Finally, we provide clinically relevant applications of these versatile personalized cancer models to highlight their potential impact. These models are ideal for a myriad of fundamental cancer biology and translational studies. Importantly, these approaches can be extended to other carcinomas, facilitating the discovery of new therapeutics that more effectively target the unique aspects of each individual patient's TME. STATEMENT OF SIGNIFICANCE: In this article, we have presented the case for the application of biomaterials in developing personalized models of complex diseases such as cancers. TSM could bring about breakthroughs in the promise of precision medicine. The critical components of the diverse tumor microenvironments, that lead to treatment failures, include cellular- and extracellular matrix- heterogeneity, and biophysical signals to the cells. Therefore, we have described these dynamic components of the tumor microenvironments, and have highlighted how contemporary biomaterials can be utilized to create personalized in vitro models of cancers. We have also described the application of the TSM to predict the dynamic patterns of disease progression, and predict effective therapies that can produce durable responses, limit relapses, and treat any minimal residual disease.

Targeting Akt in cancer for precision therapy

Biomarkers-guided precision therapeutics has revolutionized the clinical development and administration of molecular-targeted anticancer agents. Tailored precision cancer therapy exhibits better response rate compared to unselective treatment. Protein kinases have critical roles in cell signaling, metabolism, proliferation, survival and migration. Aberrant activation of protein kinases is critical for tumor growth and progression. Hence, protein kinases are key targets for molecular targeted cancer therapy. The serine/threonine kinase Akt is frequently activated in various types of cancer. Activation of Akt promotes tumor progression and drug resistance. Since the first Akt inhibitor was reported in 2000, many Akt inhibitors have been developed and evaluated in either early or late stage of clinical trials, which take advantage of liquid biopsy and genomic or molecular profiling to realize personalized cancer therapy. Two inhibitors, capivasertib and ipatasertib, are being tested in phase III clinical trials for cancer therapy. Here, we highlight recent progress of Akt signaling pathway, review the up-to-date data from clinical studies of Akt inhibitors and discuss the potential biomarkers that may help personalized treatment of cancer with Akt inhibitors. In addition, we also discuss how Akt may confer the vulnerability of cancer cells to some kinds of anticancer agents.

MKNK2 enhances chemoresistance of ovarian cancer by suppressing autophagy via miR-125b

Chemoresistance is a major cause for high mortality and poor survival in patients with ovarian cancer. Changes of cellular autophagy is associated with tumor cell chemoresistance. MAP kinase interacting serine/threonine kinase 2 (MKNK2) belongs to the protein kinase superfamily mediating cell cycle, apoptosis and angiogenesis. However, its effects on chemoresistance during ovarian cancer development remain unclear. In this study, we found that MKNK2 expression levels were markedly up-regulated in chemoresistant ovarian cancer cells compared with the sensitive cells. In addition, significantly increased expression of MKNK2 was detected in clinical ovarian cancer tissues, particularly in tumor samples from patients with drug resistance, and high MKNK2 expression is closely associated with poor prognosis. Our in vitro experiments subsequently showed that MKNK2 knockdown markedly reduced the proliferation of chemoresistant ovarian cancer cells, which was confirmed in SKOV3/DDP xenograft mouse models. Importantly, MKNK2 knockdown considerably induced autophagy in ovarian cancer cells with drug resistance, which was involved in the suppression of cell proliferation. Of note, we showed that miR-125b directly targeted MKNK2, and a negative correlation was observed between the expression of them in clinical tumor tissues. MKNK2 silence also increased miR-125b expression levels in drug-resistant ovarian cancer cells. Intriguingly, MKNK2 knockdown-suppressed cell proliferation and -induced autophagy were almost abrogated by miR-125b inhibition in chemoresistant ovarian cancer cells. Together, these findings demonstrated that MNKN2 is responsible for chemoresistance in ovarian cancer through modulating autophagy by targeting miR-125b, which may be a promising therapeutic target to develop strategies against ovarian cancer with drug resistance.

Genome-editing approaches and applications: a brief review on CRISPR technology and its role in cancer

The development of genome-editing technologies in 1970s has discerned a new beginning in the field of science. Out of different genome-editing approaches such as Zing-finger nucleases, TALENs, and meganucleases, clustered regularly interspaced short palindromic repeats-CRISPR-associated protein 9 (CRISPR/Cas9) is a recent and versatile technology that has the ability of making changes to the genome of different organisms with high specificity. Cancer is a complex process that is characterized by multiple genetic and epigenetic changes resulting in abnormal cell growth and proliferation. As cancer is one of the leading causes of deaths worldwide, a large number of studies are done to understand the molecular mechanisms underlying the development of cancer. Because of its high efficiency and specificity, CRISPR/Cas9 has emerged as a novel and powerful tool in the field of cancer research. CRISPR/Cas9 has the potential to accelerate cancer research by dissecting tumorigenesis process, generating animal and cellular models, and identify drug targets for chemotherapeutic approaches. However, despite having tremendous potential, there are certain challenges associated with CRISPR/Cas9 such as safe delivery to the target, potential off-target effects and its efficacy which needs to be addressed prior to its clinical application. In this review, we give a gist of different genome-editing technologies with a special focus on CRISPR/Cas9 development, its mechanism of action and its applications, especially in different type of cancers. We also highlight the importance of CRISPR/Cas9 in generating animal models of different cancers. Finally, we present an overview of the clinical trials and discuss the challenges associated with translating CRISPR/Cas9 in clinical use.

Possible Role of Metformin as an Immune Modulator in the Tumor Microenvironment of Ovarian Cancer

Growing evidence suggests that the immune component of the tumor microenvironment (TME) may be highly involved in the progression of high-grade serous ovarian cancer (HGSOC), as an immunosuppressive TME is associated with worse patient outcomes. Due to the poor prognosis of HGSOC, new therapeutic strategies targeting the TME may provide a potential path forward for preventing disease progression to improve patient survival. One such postulated approach is the repurposing of the type 2 diabetes medication, metformin, which has shown promise in reducing HGSOC tumor progression in retrospective epidemiological analyses and through numerous preclinical studies. Despite its potential utility in treating HGSOC, and that the immune TME is considered as a key factor in the disease’s progression, little data has definitively shown the ability of metformin to target this component of the TME. In this brief review, we provide a summary of the current understanding of the effects of metformin on leukocyte function in ovarian cancer and, coupled with data from other related disease states, posit the potential mechanisms by which the drug may enhance the anti-tumorigenic effects of immune cells to improve HGSOC patient survival.

RNA sequencing: new technologies and applications in cancer research

Over the past few decades, RNA sequencing has significantly progressed, becoming a paramount approach for transcriptome profiling. The revolution from bulk RNA sequencing to single-molecular, single-cell and spatial transcriptome approaches has enabled increasingly accurate, individual cell resolution incorporated with spatial information. Cancer, a major malignant and heterogeneous lethal disease, remains an enormous challenge in medical research and clinical treatment. As a vital tool, RNA sequencing has been utilized in many aspects of cancer research and therapy, including biomarker discovery and characterization of cancer heterogeneity and evolution, drug resistance, cancer immune microenvironment and immunotherapy, cancer neoantigens and so on. In this review, the latest studies on RNA sequencing technology and their applications in cancer are summarized, and future challenges and opportunities for RNA sequencing technology in cancer applications are discussed.