Ovarian cancer circulating extracelluar vesicles promote coagulation and have a potential in diagnosis: an iTRAQ based proteomic analysis

Unlocking the intricacies: Exploring the complex interplay between platelets and ovarian cancer

Ovarian cancer, an aggressive malignancy of the female reproductive tract, is frequently linked to an elevated risk of thrombotic events. This association is manifested by a pronounced rise in platelet counts and activation levels. Current research firmly supports the pivotal role of platelets in the oncogenic processes of ovarian cancer, influencing tumor cell proliferation and metastasis. Platelets influence these processes through direct interactions with tumor cells or by secreting cytokines and growth factors that enhance tumor growth, angiogenesis, and metastasis. This review aims to thoroughly dissect the interactions between platelets and ovarian cancer cells, emphasizing their combined role in tumor progression and associated thrombotic events. Additionally, it summarizes therapeutic strategies targeting platelet-cancer interface which show significant promise. Such approaches could not only be effective in managing the primary ovarian tumor but also play a pivotal role in preventing metastasis and attenuating thrombotic complications associated with ovarian cancer.

Proteomic landscape of epithelial ovarian cancer

Epithelial ovarian cancer (EOC) is a deadly disease with limited diagnostic biomarkers and therapeutic targets. Here we conduct a comprehensive proteomic profiling of ovarian tissue and plasma samples from 813 patients with different histotypes and therapeutic regimens, covering the expression of 10,715 proteins. We identify eight proteins associated with tumor malignancy in the tissue specimens, which are further validated as potential circulating biomarkers in plasma. Targeted proteomics assays are developed for 12 tissue proteins and 7 blood proteins, and machine learning models are constructed to predict one-year recurrence, which are validated in an independent cohort. These findings contribute to the understanding of EOC pathogenesis and provide potential biomarkers for early detection and monitoring of the disease. Additionally, by integrating mutation analysis with proteomic data, we identify multiple proteins related to DNA damage in recurrent resistant tumors, shedding light on the molecular mechanisms underlying treatment resistance. This study provides a multi-histotype proteomic landscape of EOC, advancing our knowledge for improved diagnosis and treatment strategies.

Higher EpCAM-Positive Extracellular Vesicle Concentration in Ascites Is Associated with Shorter Progression-Free Survival of Patients with Advanced High-Grade Serous Carcinoma

Platinum-resistant high-grade serous carcinoma (HGSC) is an incurable disease, so biomarkers that could help with timely treatment adjustments and personalized approach are extensively being sought. Tumor-derived extracellular vesicles (EVs) that can be isolated from ascites and blood of HGSC patients are such promising biomarkers. Epithelial cell adhesion molecule (EpCAM) expression is upregulated in most epithelium-derived tumors; however, studies on prognostic value of EpCAM overexpression in ovarian carcinoma have shown contradictory results. The aim of our study was to evaluate the potential of total and EpCAM-positive EVs as prognostic and predictive biomarkers for advanced HGSC. Flow cytometry was used to determine the concentration of total and EpCAM-positive EVs in paired pretreatment ascites and plasma samples of 37 patients with advanced HGSC who underwent different first-line therapy. We found that higher EpCAM-positive EVs concentration in ascites is associated with shorter progression-free survival (PFS) regardless of treatment strategy. We also found a strong correlation of EpCAM-positive EVs concentration between ascites and plasma. Our findings indicate that EpCAM-positive EVs in ascites of patients with advanced HGSC have the potential to serve as prognostic biomarkers for predicting early recurrence and thereby likelihood of more aggressive tumor biology and development of chemoresistance.

Exploration and prognostic analysis of two types of high-risk ovarian cancers: clear cell vs. serous carcinoma: a population-based study

BACKGROUND

Ovarian clear cell carcinoma (OCCC) is a rare pathological histotype in ovarian cancer, while the survival rate of advanced OCCC (Stage III-IV) is substantially lower than that of the advanced serous ovarian cancer (OSC), which is the most common histotype. The goal of this study was to identify high-risk OCCC by comparing OSC and OCCC, with investigating potential risk and prognosis markers.

METHODS

Patients diagnosed with ovarian cancer from 2009 to 2018 were identified from the Surveillance, Epidemiology, and End Results (SEER) Program. Logistic and Cox regression models were used to identify risk and prognostic factors in high-risk OCCC patients. Cancer-specific survival (CSS) and overall survival (OS) were assessed using Kaplan-Meier curves. Furthermore, Cox analysis was employed to build a nomogram model. The performance evaluation results were displayed using the C-index, calibration plots, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA). Immunohistochemically approach was used to identify the expression of the novel target (GPC3).

RESULTS

In the Cox analysis for advanced OCCC, age (45-65 years), tumor numbers (total number of in situ/malignant tumors for patient), T3-stage, bilateral tumors, and liver metastases could be defined as prognostic variables. Nomogram showed good predictive power and clinical practicality. Compared with OSC, liver metastases had a stronger impact on the prognosis of patients with OCCC. T3-stage, positive distant lymph nodes metastases, and lung metastases were risk factors for developing liver metastases. Chemotherapy was an independent prognostic factor for patient with advanced OCCC, but had no effect on CSS in patients with liver metastases (p = 0.0656), while surgery was significantly related with better CSS in these patients (p < 0.0001) (p = 0.0041). GPC3 expression was detected in all tissue sections, and GPC3 staining was predominantly found in the cytoplasm and membranes.

CONCLUSION

Advanced OCCC and OCCC with liver metastases are two types of high-risk OCCC. The constructed nomogram exhibited a satisfactory survival prediction for patients with advanced OCCC. GPC3 immunohistochemistry is expected to accumulate preclinical evidence to support the inclusion of GPC3 in OCCC targeted therapy.

Boosting edgeR (Robust) by dealing with missing observations and gene-specific outliers in RNA-Seq profiles and its application to explore biomarker genes for diagnosis and therapies of ovarian cancer

The edgeR (Robust) is a popular approach for identifying differentially expressed genes (DEGs) from RNA-Seq profiles. However, it shows weak performance against gene-specific outliers and is unable to handle missing observations. To address these issues, we proposed a pre-processing approach of RNA-Seq count data by combining the iLOO-based outlier detection and random forest-based missing imputation approach for boosting the performance of edgeR (Robust). Both simulation and real RNA-Seq count data analysis results showed that the proposed edgeR (Robust) outperformed than the conventional edgeR (Robust). To investigate the effectiveness of identified DEGs for diagnosis, and therapies of ovarian cancer (OC), we selected top-ranked 12 DEGs (IL6, XCL1, CXCL8, C1QC, C1QB, SNAI2, TYROBP, COL1A2, SNAP25, NTS, CXCL2, and AGT) and suggested hub-DEGs guided top-ranked 10 candidate drug-molecules for the treatment against OC. Hence, our proposed procedure might be an effective computational tool for exploring potential DEGs from RNA-Seq profiles for diagnosis and therapies of any disease.

Extracellular vesicles as a potential delivery platform for CRISPR-Cas based therapy in epithelial ovarian cancer

Ovarian Cancer (OC) is the most common gynecological malignancy and the eighth most diagnosed cancer in females worldwide. Presently, it ranks as the fifth leading cause of cancer-related mortality among patients globally. Major factors contributing to the lethality of OC worldwide include delayed diagnosis, chemotherapy resistance, high metastatic rates, and the heterogeneity of subtypes. Despite continuous efforts to develop novel targeted therapies and chemotherapeutic agents, challenges persist in the form of OC resistance and recurrence. In the last decade, CRISPR-Cas-based genome editing has emerged as a powerful tool for modifying genetic and epigenetic mechanisms, holding potential for treating numerous diseases. However, a significant challenge for therapeutic applications of CRISPR-Cas technology is the absence of an optimal vehicle for delivering CRISPR molecular machinery into targeted cells or tissues. Recently, extracellular vesicles (EVs) have gained traction as potential delivery vehicles for various therapeutic agents. These heterogeneous, membrane-derived vesicles are released by nearly all cells into extracellular spaces. They carry a molecular cargo of proteins and nucleic acids within their intraluminal space, encased by a cholesterol-rich phospholipid bilayer membrane. EVs actively engage in cell-to-cell communication by delivering cargo to both neighboring and distant cells. Their inherent ability to shield molecular cargo from degradation and cross biological barriers positions them ideally for delivering CRISPR-Cas ribonucleoproteins (RNP) to target cells. Furthermore, they exhibit higher biocompatibility, lower immunogenicity, and reduced toxicity compared to classical delivery platforms such as adeno-associated virus, lentiviruses, and synthetic nanoparticles. This review explores the potential of employing different CRISPR-Cas systems to target specific genes in OC, while also discussing various methods for engineering EVs to load CRISPR components and enhance their targeting capabilities.

Discovery and validation of serum glycoprotein biomarkers for high grade serous ovarian cancer

PURPOSE

This study aimed to identify serum glycoprotein biomarkers for early detection of high-grade serous ovarian cancer (HGSOC), the most common and aggressive histotype of ovarian cancer.

EXPERIMENTAL DESIGN

The glycoproteomics pipeline lectin magnetic bead array (LeMBA)-mass spectrometry (MS) was used in age-matched case-control serum samples. Clinical samples collected at diagnosis were divided into discovery (n = 30) and validation (n = 98) sets. We also analysed a set of preclinical sera (n = 30) collected prior to HGSOC diagnosis in the UK Collaborative Trial of Ovarian Cancer Screening.

RESULTS

A 7-lectin LeMBA-MS/MS discovery screen shortlisted 59 candidate proteins and three lectins. Validation analysis using 3-lectin LeMBA-multiple reaction monitoring (MRM) confirmed elevated A1AT, AACT, CO9, HPT and ITIH3 and reduced A2MG, ALS, IBP3 and PON1 glycoforms in HGSOC. The best performing multimarker signature had 87.7% area under the receiver operating curve, 90.7% specificity and 70.4% sensitivity for distinguishing HGSOC from benign and healthy groups. In the preclinical set, CO9, ITIH3 and A2MG glycoforms were altered in samples collected 11.1 ± 5.1 months prior to HGSOC diagnosis, suggesting potential for early detection.

CONCLUSIONS AND CLINICAL RELEVANCE

Our findings provide evidence of candidate early HGSOC serum glycoprotein biomarkers, laying the foundation for further study in larger cohorts.

Mass Spectrometry-based Proteomics of Epithelial Ovarian Cancers: a Clinical Perspective

Increasing proteomic studies focused on epithelial ovarian cancer (EOC) have attempted to identify early disease biomarkers, establish molecular stratification, and discover novel druggable targets. Here we review these recent studies from a clinical perspective. Multiple blood proteins have been used clinically as diagnostic markers. The ROMA test integrates CA125 and HE4, while the OVA1 and OVA2 tests analyze multiple proteins identified by proteomics. Targeted proteomics has been widely used to identify and validate potential diagnostic biomarkers in EOCs, but none has yet been approved for clinical adoption. Discovery proteomic characterization of bulk EOC tissue specimens has uncovered a large number of dysregulated proteins, proposed new stratification schemes, and revealed novel targets of therapeutic potential. A major hurdle facing clinical translation of these stratification schemes based on bulk proteomic profiling is intra-tumor heterogeneity, namely that single tumor specimens may harbor molecular features of multiple subtypes. We reviewed over 2500 interventional clinical trials of ovarian cancers since 1990, and cataloged 22 types of interventions adopted in these trials. Among 1418 clinical trials which have been completed or are not recruiting new patients, about 50% investigated chemotherapies. Thirty-seven clinical trials are at phase 3 or 4, of which 12 focus on PARP, 10 on VEGFR, 9 on conventional anti-cancer agents, and the remaining on sex hormones, MEK1/2, PD-L1, ERBB, and FRα. Although none of the foregoing therapeutic targets were discovered by proteomics, newer targets discovered by proteomics, including HSP90 and cancer/testis antigens, are being tested also in clinical trials. To accelerate the translation of proteomic findings to clinical practice, future studies need to be designed and executed to the stringent standards of practice-changing clinical trials. We anticipate that the rapidly evolving technology of spatial and single-cell proteomics will deconvolute the intra-tumor heterogeneity of EOCs, further facilitating their precise stratification and superior treatment outcomes.

Exosomes as crucial emerging tools for intercellular communication with therapeutic potential in ovarian cancer

More than two-thirds of epithelial ovarian cancer (EOC) patients are diagnosed at advanced stages due to the lack of sensitive biomarkers. Currently, exosomes are intensively investigated as non-invasive cancer diagnostic markers. Exosomes are nanovesicles released in the extracellular milieu with the potential to modulate recipient cells' behavior. EOC cells release many altered exosomal cargoes that exhibit clinical relevance to tumor progression. Exosomes represent powerful therapeutic tools (drug carriers or vaccines), posing a promising option in clinical practice for curing EOC in the near future. In this review, we highlight the importance of exosomes in cell–cell communication, epithelial–mesenchymal transition (EMT), and their potential to serve as diagnostic and prognostic factors, particularly in EOC.

Exosomes: A potential tool for immunotherapy of ovarian cancer

Ovarian cancer is a malignant tumor of the female reproductive system, with a very poor prognosis and high mortality rates. Chemotherapy and radiotherapy are the most common treatments for ovarian cancer, with unsatisfactory results. Exosomes are a subpopulation of extracellular vesicles, which have a diameter of approximately 30-100 nm and are secreted by many different types of cells in various body fluids. Exosomes are highly stable and are effective carriers of immunotherapeutic drugs. Recent studies have shown that exosomes are involved in various cellular responses in the tumor microenvironment, influencing the development and therapeutic efficacy of ovarian cancer, and exhibiting dual roles in inhibiting and promoting tumor development. Exosomes also contain a variety of genes related to ovarian cancer immunotherapy that could be potential biomarkers for ovarian cancer diagnosis and prognosis. Undoubtedly, exosomes have great therapeutic potential in the field of ovarian cancer immunotherapy. However, translation of this idea to the clinic has not occurred. Therefore, it is important to understand how exosomes could be used in ovarian cancer immunotherapy to regulate tumor progression. In this review, we summarize the biomarkers of exosomes in different body fluids related to immunotherapy in ovarian cancer and the potential mechanisms by which exosomes influence immunotherapeutic response. We also discuss the prospects for clinical application of exosome-based immunotherapy in ovarian cancer.

Identification of TREM2-positive tumor-associated macrophages in esophageal squamous cell carcinoma: implication for poor prognosis and immunotherapy modulation

Background

It is now understood that the effectiveness of checkpoint immunotherapy can be impaired by immunosuppressive tumor-associated macrophages (TAMs). Nonetheless, the impact of different TAM subpopulations on the antitumor immune response remains unclear, mainly due to their heterogeneity. Herein, we identified a novel TAM subpopulation in esophageal squamous cell carcinoma (ESCC) that might contribute to poor clinical outcomes and immunotherapy modulation.

Methods and results

We analyzed two single-cell RNA sequencing (scRNA-seq) datasets (GSE145370 and GSE160269) of esophageal squamous cell carcinoma to identify a novel TREM2-positive TAM subpopulation characterized by upregulation of TREM2, C1QC, C1QB, C1QA, SPP1, and APOE. Quantitative real-time PCR (qRT-PCR) and enzyme-linked immunosorbent assay (ELISA) demonstrated that these genes were significantly overexpressed in ESCC. Multiplex immunofluorescence validated the infiltration of TREM2⁺ TAMs in ESCC tissues, which correlated with poorer overall survival (OS). The scRNA-seq analysis in dataset GSE120575 indicated significant enrichment of TREM2⁺ TAMs in melanoma patients (n=48) with poor immunotherapy response, which had an identical gene signature with TREM2⁺ TAMs from ESCC. Analysis of 29 bulk-RNA melanoma samples from dataset GSE78220 revealed that a gene signature of 40 genes associated with TREM2⁺ TAMs was upregulated in the transcriptome of melanomas that did not respond to anti-PD1 therapy. Validation in the TCGA ESCC cohort (n=80) showed that a high enrichment score of the TREM2⁺ TAM was associated with poor prognosis. In addition, 10 ESCC patients treated with anti-PD1 therapy suggested that patients who are not sensitive to immunotherapy have higher density of TREM2+TAMs infiltration.

Conclusion

Overall, TREM2⁺ TAM infiltration in ESCC is associated with poor prognosis and may serve as a biomarker for predicting outcomes and immunotherapy modulation in this patient population. modulation; single-cell RNA sequencing.

Synergistic effects of nab-PTX and anti-PD-1 antibody combination against lung cancer by regulating the Pi3K/AKT pathway through the Serpinc1 gene

Lung cancer is a type of cancer with higher morbidity and mortality. In spite of the impressive response rates of nab-paclitaxel (nab-PTX) or programmed cell death-1 (PD-1) and its ligand inhibitors, the effective treatment remains limited. Currently, alternative strategies aim at drug combination of nab-PTX and PD-1/PD-L1 inhibitors. Even as the clinical impact of the combined agents continues to increase, basic research studies are still limited and the mechanisms underlying this synergy are not well studied. In this study, we evaluated the antitumor efficacy and the molecular mechanisms of action of nab-PTX in combination with anti-PD-1 antibody, using Lewis lung carcinoma (LLC) cell and subcutaneously transplanted tumor models. The combination of nab-PTX and anti-PD-1 antibody displayed stronger antitumor effects, manifested at tumor volume, proliferation and apoptosis through Ki67 and TUNEL staining. In-vivo experiments showed significant increases in CD4+ T cells, CD8+ T cells, IFN-γ, TNF-α, IL-2, PF, and Gzms-B, exerting antitumor effects with reductions in MDSCs and IL-10 after the treatments. Furthermore, transcriptomic analysis indicated 20 overlapped differentially expressed genes, and Serpin peptidase inhibitor clade C Member 1 (Serpinc1) was downregulated during treatment in vivo, whose expression level was markedly related to metastasis and overall survival of lung cancer patients. Functional enrichment analysis of the target gene revealed primary GO terms related to tumor, which warrants further investigation. We also found that Serpinc1 overexpression promoted cell proliferation, migration, and invasion and inhibited cell apoptosis of LLC cells in vitro, possibly regulating the associated factors via the Pi3K/AKT pathway. In summary, our results reveal the synergistic antitumor responses of nab-PTX combined with anti-PD-1 antibody, in which Serpinc1 may play an important role, providing a target gene for combination treatment strategy.

The role of proteomics in the multiplexed analysis of gene alterations in human cancer

INTRODUCTION

Proteomics has played a pivotal role in identifying proteins perturbed in disease conditions when compared with healthy samples. Study of dysregulated proteins aids in identifying diagnostic markers and potential therapeutic targets. Cancer is an outcome of interplay of several such disarrayed proteins and molecular pathways which perturb cellular homeostasis, resulting in transformation. In this review, we discuss various facets of proteomic approaches, including tools and technological advancements, aiding in understanding differentially expressed molecules and signaling mechanisms.

AREAS COVERED

In this review, we have taken the approach of documenting the different methods of proteomic studies, ranging from labeling techniques, data analysis methods, and the nature of molecule detected. We summarize each technique and provide a glimpse of cancer research carried out using them, highlighting the advantages and drawbacks in comparison with others. Literature search using online resources, such as PubMed and Google Scholar were carried out for this approach.

EXPERT OPINION

Technological advancements in proteomics studies have come a long way from the study of two-dimensional mapping of proteins separated on gels in the early 1970s. Higher precision in molecular identification and quantification (high throughput), and greater number of samples analyzed have been the focus of researchers.

Extracellular Vesicles: New Tools for Early Diagnosis of Breast and Genitourinary Cancers

Breast cancers and cancers of the genitourinary tract are the most common malignancies among men and women and are still characterized by high mortality rates. In order to improve the outcomes, early diagnosis is crucial, ideally by applying non-invasive and specific biomarkers. A key role in this field is played by extracellular vesicles (EVs), lipid bilayer-delimited structures shed from the surface of almost all cell types, including cancer cells. Subcellular structures contained in EVs such as nucleic acids, proteins, and lipids can be isolated and exploited as biomarkers, since they directly stem from parental cells. Furthermore, it is becoming even more evident that different body fluids can also serve as sources of EVs for diagnostic purposes. In this review, EV isolation and characterization methods are described. Moreover, the potential contribution of EV cargo for diagnostic discovery purposes is described for each tumor.

[Identification of Candidate Biomarkers for EGFR-T790M Drug-resistant Gene Mutation in Advanced Lung Adenocarcinoma]

背景与目的

奥希替尼（Osimertinib）是美国食品和药物管理局（Food and Drug Administration, FDA）批准用于携带表皮生长因子受体（epidermal growth factor receptor, EGFR）-T790M突变的晚期非小细胞肺癌（non-small cell lung cancer, NSCLC）患者的药物，用药前需行EGFR-T790M检测。不少患者因进展病灶隐匿或体弱无法进行组织活检错过Osimertinib治疗，本研究希望能从血清中筛查出预测EGFR-T790M耐药突变相关蛋白，为临床用药提供帮助。本研究旨在探索EGFR-T790M耐药基因相关蛋白，为临床用药提供帮助。

方法

本研究纳入口服易瑞沙晚期肺腺癌患者36例，在疾病进展后行组织活检，使用ARMS方法检测出EGFR-T790M突变组患者18例，非EGFR-T790M突变组18例。收集耐药患者血清，采用同位素标记相对和绝对定量标记结合二维液相色谱串联质谱蛋白组学技术筛选与EGFR-T790M耐药相关蛋白。

结果

筛出17种差异性蛋白，与EGFR-T790M基因突变相关上调蛋白6种，下调蛋白11种，主要参与31种生物过程，7种细胞组分，26种分子功能；反应途径中共鉴定出12种富集途径，其中富集指数最高的是凝血级联途径。

结论

发现与EGFR-T790M耐药相关蛋白共17种，参与凝血级联途径蛋白有望成为预测EGFR-T790M耐药突变相关的生物标志物。

Recent Developments and Applications of Quantitative Proteomics Strategies for High-Throughput Biomolecular Analyses in Cancer Research

Innovations in medical technology and dedicated focus from the scientific community have inspired numerous treatment strategies for benign and invasive cancers. While these improvements often lend themselves to more positive prognoses and greater patient longevity, means for early detection and severity stratification have failed to keep pace. Detection and validation of cancer-specific biomarkers hinges on the ability to identify subtype-specific phenotypic and proteomic alterations and the systematic screening of diverse patient groups. For this reason, clinical and scientific research settings rely on high throughput and high sensitivity mass spectrometry methods to discover and quantify unique molecular perturbations in cancer patients. Discussed within is an overview of quantitative proteomics strategies and a summary of recent applications that enable revealing potential biomarkers and treatment targets in prostate, ovarian, breast, and pancreatic cancer in a high throughput manner.

The Complement System in Ovarian Cancer: An Underexplored Old Path

Ovarian cancer is one of the most lethal gynecological cancers. Current therapeutic strategies allow temporary control of the disease, but most patients develop resistance to treatment. Moreover, although successful in a range of solid tumors, immunotherapy has yielded only modest results in ovarian cancer. Emerging evidence underscores the relevance of the components of innate and adaptive immunity in ovarian cancer progression and response to treatment. Particularly, over the last decade, the complement system, a pillar of innate immunity, has emerged as a major regulator of the tumor microenvironment in cancer immunity. Tumor-associated complement activation may support chronic inflammation, promote an immunosuppressive microenvironment, induce angiogenesis, and activate cancer-related signaling pathways. Recent insights suggest an important role of complement effectors, such as C1q or anaphylatoxins C3a and C5a, and their receptors C3aR and C5aR1 in ovarian cancer progression. Nevertheless, the implication of these factors in different clinical contexts is still poorly understood. Detailed knowledge of the interplay between ovarian cancer cells and complement is required to develop new immunotherapy combinations and biomarkers. In this context, we discuss the possibility of targeting complement to overcome some of the hurdles encountered in the treatment of ovarian cancer.

Role of Extracellular Vesicles in Epithelial Ovarian Cancer: A Systematic Review

Extracellular vesicles (EVs) are a heterogeneous group of cell-derived submicron vesicles released under physiological or pathological conditions. EVs mediate the cellular crosstalk, thus contributing to defining the tumor microenvironment, including in epithelial ovarian cancer (EOC). The available literature investigating the role of EVs in EOC has been reviewed following PRISMA guidelines, focusing on the role of EVs in early disease diagnosis, metastatic spread, and the development of chemoresistance in EOC. Data were identified from searches of Medline, Current Contents, PubMed, and from references in relevant articles from 2010 to 1 April 2020. The research yielded 194 results. Of these, a total of 36 papers, 9 reviews, and 27 original types of research were retained and analyzed. The literature findings demonstrate that a panel of EV-derived circulating miRNAs may be useful for early diagnosis of EOC. Furthermore, it appears clear that EVs are involved in mediating two crucial processes for metastatic and chemoresistance development: the epithelial–mesenchymal transition, and tumor escape from the immune system response. Further studies, more focused on in vivo evidence, are urgently needed to clarify the role of EV assessment in the clinical management of EOC patients.

Progressive and Prognostic Performance of an Extracellular Matrix-Receptor Interaction Signature in Gastric Cancer

The role of an extracellular matrix- (ECM-) receptor interaction signature has not been fully clarified in gastric cancer. This study performed comprehensive analyses on the differentially expressed ECM-related genes, clinicopathologic features, and prognostic application in gastric cancer. The differentially expressed genes between tumorous and matched normal tissues in The Cancer Genome Atlas (TCGA) and validation cohorts were identified by a paired t-test. Consensus clusters were built to find the correlation between clinicopathologic features and subclusters. Then, the least absolute shrinkage and selection operator (lasso) method was used to construct a risk score model. Correlation analyses were made to reveal the relation between risk score-stratified subgroups and clinicopathologic features or significant signatures. In TCGA (26 pairs) and validation cohort (134 pairs), 25 ECM-related genes were significantly highly expressed and 11 genes were downexpressed in gastric cancer. ECM-based subclusters were slightly related to clinicopathologic features. We constructed a risk score model = 0.081∗log₂ (CD36) + 0.043∗log₂ (COL5A2) + 0.001∗log₂ (ITGB5) + 0.039∗log₂ (SDC2) + 0.135∗log₂ (SV2B) + 0.012∗log₂ (THBS1) + 0.068∗log₂ (VTN) + 0.023∗log₂ (VWF). The risk score model could well predict the outcome of patients with gastric cancer in both training (n = 351, HR: 1.807, 95% CI: 1.292-2.528, P = 0.00046) and validation (n = 300, HR: 1.866, 95% CI: 1.347-2.584, P = 0.00014) cohorts. Besides, risk score-based subgroups were associated with angiogenesis, cell adhesion molecules, complement and coagulation cascades, TGF-beta signaling, and mismatch repair-relevant signatures (P < 0.0001). By univariate (1.845, 95% CI: 1.382-2.462, P < 0.001) and multivariate (1.756, 95% CI: 1.284-2.402, P < 0.001) analyses, we regarded the risk score as an independent risk factor in gastric cancer. Our findings revealed that ECM compositions became accomplices in the tumorigenesis, progression, and poor survival of gastric cancer.

Identification of key factors associated with early- and late-onset ovarian serous cystadenocarcinoma

Aim: To uncover the molecular mechanisms of early-onset ovarian serous cystadenocarcinoma (EOOSC; patients <50 years old) and late-onset ovarian serous cystadenocarcinoma (LOOSC; patients ≥50 years old). Materials & methods: Bioinformatics was utilized to identify the key factors. Results: 478 EOOSC and 899 LOOSC individual differentially expressed genes were identified and enriched in different pathways. The expression of key genes LAG3, LRRC63 and MT1B significantly influenced the overall survival of EOOSC patients. The expression of key genes RDH12, NTSR1, ZSCAN16, CT45A3 and EPPIN_WFDC6 significantly affected the overall survival of LOOSC patients. Conclusions: The molecular mechanisms of EOOSC and LOOSC appear to be different, so that patients might be treated individually in respect of age.