Postoperative recurrence of epithelial ovarian cancer patients and chemoresistance related protein analyses

HIST1H2BK predicts neoadjuvant-chemotherapy response and mediates 5-fluorouracil resistance of gastric cancer cells

BACKGROUND

Neoadjuvant chemotherapy (NACT) is routinely used to treat patients with advanced gastric cancer (AGC). However, the identification of reliable markers to determine which AGC patients would benefit from NACT remains challenging.

METHODS

A systematic screening of plasma proteins between NACT-sensitive and NACT-resistant AGC patients was performed by a mass spectrometer (n = 6). The effect of the most differential plasma protein was validated in two independent cohorts with AGC patients undergoing NACT (ELISA cohort: n = 155; Validated cohort: n = 203). The expression of this candidate was examined in a cohort of AGC tissues using immunohistochemistry (n = 34). The mechanism of this candidate on 5-Fluorouracil (5-FU) resistance was explored by cell-biology experiments in vitro and vivo.

RESULTS

A series of differential plasma proteins between NACT-sensitive and NACT-resistant AGC patients was identified. Among them, plasma HIST1H2BK was validated as a significant biomarker for predicting NACT response and prognosis. Moreover, HIST1H2BK was over-expression in NACT-resistant tissues compared to NACT-sensitive tissues in AGC. Mechanistically, HIST1H2BK inhibited 5-FU-induced apoptosis by upregulating A2M transcription and then activating LRP/PI3K/Akt pathway, thereby promoting 5-FU resistance in GC cells. Intriguingly, HIST1H2BK-overexpressing 5-FU-resistant GC cells propagated resistance to 5-FU-sensitive GC cells through the secretion of HIST1H2BK.

CONCLUSION

This study highlights significant differences in plasma protein profiles between NACT-resistant and NACT-sensitive AGC patients. Plasma HIST1H2BK emerged as an effective biomarker for achieving more accurate NACT in AGC. The mechanism of intracellular and secreted HIST1H2BK on 5-FU resistance provided a novel insight into chemoresistance in AGC.

Scientific and clinical relevance of non-cellular tumor microenvironment components in ovarian cancer chemotherapy resistance

The tumor microenvironment (TME) components play a crucial role in cancer cells' resistance to chemotherapeutic agents. This phenomenon is exceptionally fundamental in patients with ovarian cancer (OvCa), whose outcome depends mainly on their response to chemotherapy. Until now, most reports have focused on the role of cellular components of the TME, while less attention has been paid to the stroma and other non-cellular elements of the TME, which may play an essential role in the therapy resistance. Inhibiting these components could help define new therapeutic targets and potentially restore chemosensitivity. The aim of the present article is both to summarize the knowledge about non-cellular components of the TME in the development of OvCa chemoresistance and to suggest targeting of non-cellular elements of the TME as a valuable strategy to overcome chemoresistance and to develop new therapeutic strategies in OvCA patients.

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

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

Clusterin and Its Isoforms in Oral Squamous Cell Carcinoma and Their Potential as Biomarkers: A Comprehensive Review

Oral squamous cell carcinoma (OSCC) is a prevalent type of head and neck cancer, ranked as the sixth most common cancer worldwide, accounting for approximately 300,000 new cases and 145,000 deaths annually. Early detection using biomarkers significantly increases the 5-year survival rate of OSCC by up to 80-90%. Clusterin (CLU), also known as apolipoprotein J, is a sulfated chaperonic glycoprotein expressed in all tissues and human fluids and has been reported to be a potential biomarker of OSCC. CLU has been implicated as playing a vital role in many biological processes such as apoptosis, cell cycle, etc. Abnormal CLU expression has been linked with the development and progression of cancers. Despite the fact that there are many studies that have reported the involvement of CLU and its isoforms in OSCC, the exact roles of CLU and its isoforms in OSCC carcinogenesis have not been fully explored. This article aims to provide a comprehensive review of the current understanding of CLU structure and genetics and its correlation with OSCC tumorigenesis to better understand potential diagnostic and prognostic biomarker development. The relationship between CLU and chemotherapy resistance in cancer will also be discussed to explore the therapeutic application of CLU and its isoforms in OSCC.

Apolipoproteins: New players in cancers

Apolipoproteins (APOs), the primary protein moiety of lipoproteins, are known for their crucial role in lipid traffic and metabolism. Despite extensive exploration of APOs in cardiovascular diseases, their roles in cancers did not attract enough attention. Recently, research focusing on the roles of APOs in cancers has flourished. Multiple studies demonstrate the interaction of APOs with classical pathways of tumorigenesis. Besides, the dysregulation of APOs may indicate cancer occurrence and progression, thus serving as potential biomarkers for cancer patients. Herein, we summarize the mechanisms of APOs involved in the development of various cancers, their applications as cancer biomarkers and their genetic polymorphism associated with cancer risk. Additionally, we also discuss the potential anti-cancer therapies by virtue of APOs. The comprehensive review of APOs in cancers may advance the understanding of the roles of APOs in cancers and their potential mechanisms. We hope that it will provide novel clues and new therapeutic strategies for cancers.

Prognostic utility of the ovarian cancer secretome: a systematic investigation

BACKGROUND

Ovarian cancer is usually detected at an advanced stage with frequent recurrence. The recurrence-free survival and overall survival is influenced by the age at diagnosis, tumor stage and histological subtype. Nonetheless, quantifiable prognostic biomarkers are needed for early identification of the high-risk patients and for personalized medicine. Several studies link tumor-specific dysregulated expression of certain proteins with ovarian cancer prognosis. However, careful investigation of presence of these prognostically relevant proteins in ovarian cancer secretome is lacking.

OBJECTIVE

To critically analyze the recent published data on prognostically relevant proteins for ovarian cancer and to carefully search how many of them are reported in the published ovarian cancer secretome datasets.

DESIGN

A search for relevant studies in the past 2 years was conducted in PubMed and a comprehensive list of proteins associated with the ovarian cancer prognosis was prepared. These were cross-referred to the published ovarian cancer secretome profiles. The proteins identified in the secretome were further shortlisted based on a scoring strategy employing stringent criteria.

RESULTS

A panel of seven promising secretory biomarkers associated with ovarian cancer prognosis is proposed.

CONCLUSION

Scanning the ovarian cancer secretome datasets provides the opportunity to identify if tumor-specific biomarkers could be tested as secretory biomarkers. Detecting their levels in the body fluid would be more advantageous than evaluating the expression in the tissue, since it could be monitored multiple times over the course of the disease to have a better judgment of the prognosis and response to therapy.

Applications of Multi-omics Approaches for Exploring the Molecular Mechanism of Ovarian Carcinogenesis

Ovarian cancer ranks as the fifth most common cause of cancer-related death in females. The molecular mechanisms of ovarian carcinogenesis need to be explored in order to identify effective clinical therapies for ovarian cancer. Recently, multi-omics approaches have been applied to determine the mechanisms of ovarian oncogenesis at genomics (DNA), transcriptomics (RNA), proteomics (proteins), and metabolomics (metabolites) levels. Multi-omics approaches can identify some diagnostic and prognostic biomarkers and therapeutic targets for ovarian cancer, and these molecular signatures are beneficial for clarifying the development and progression of ovarian cancer. Moreover, the discovery of molecular signatures and targeted therapy strategies could noticeably improve the prognosis of ovarian cancer patients.

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.

Mining TCGA database for gene expression in ovarian serous cystadenocarcinoma microenvironment

Background

Ovarian cancer is one of the leading causes of female deaths worldwide. Ovarian serous cystadenocarcinoma occupies about 90% of it. Effective and accurate biomarkers for diagnosis, outcome prediction and personalized treatment are needed urgently

Methods

Gene expression profile for OSC patients was obtained from the TCGA database. The ESTIMATE algorithm was used to calculate immune scores and stromal scores of expression data of ovarian serous cystadenocarcinoma samples. Survival results between high and low groups of immune and stromal score were compared and differentially expressed genes (DEGs) were screened out by limma package. The Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and the protein-protein interaction (PPI) network analysis were performed with the g:Profiler database, the Cytoscape and Search Tool for the Retrieval of Interacting Genes (STRING-DB). Survival results between high and low immune and stromal score groups were compared. Kaplan-Meier plots based on TCGA follow up information were generated to evaluate patients’ overall survival.

Results

Eighty-six upregulated DEGs and one downregulated DEG were identified. Three modules, which included 49 nodes were chosen as important networks. Seven DEGs (VSIG4, TGFBI, DCN, F13A1, ALOX5AP, GPX3, SFRP4) were considered to be correlated with poor overall survival.

Conclusion

Seven DEGs (VSIG4, TGFBI, DCN, F13A1, ALOX5AP, GPX3, SFRP4) were correlated with poor overall survival in our study. This new set of genes can become strong predictor of survival, individually or combined. Further investigation of these genes is needed to validate the conclusion to provide novel understanding of tumor microenvironment with ovarian serous cystadenocarcinoma prognosis and treatment.

Proteomic Studies on the Management of High-Grade Serous Ovarian Cancer Patients: A Mini-Review

High-grade serous ovarian cancer (HGSC) remains the most common and deadly subtype of ovarian cancer. It is characterized by its late diagnosis and frequent relapse despite standardized treatment with cytoreductive surgery and platinum-based chemotherapy. The past decade has seen significant advances in the clinical management and molecular understanding of HGSC following the publication of the Cancer Genome Atlas (TCGA) researchers and the introduction of targeted therapies with anti-angiogenic drugs and poly(ADP-ribose) polymerase inhibitors in specific subgroups of patients. We provide a comprehensive review of HGSC, focusing on the most important molecular advances aimed at providing a better understanding of the disease and its response to treatment. We emphasize the role that proteomic technologies are now playing in these two aspects of the disease, through the identification of proteins and their post-translational modifications in ovarian cancer tumors. Finally, we highlight how the integration of proteomics with genomics, exemplified by the work performed by the Clinical Proteomic Tumor Analysis Consortium (CPTAC), can guide the development of new biomarkers and therapeutic targets.

Complement C4-A and Plasminogen as Potential Biomarkers for Prediction of Papillary Thyroid Carcinoma

BACKGROUND

Early diagnosis and therapy of papillary thyroid carcinoma (PTC) is essential for reducing recurrence and improving the long-term survival. In this study, we aimed to investigate the proteome profile of plasma and screen unique proteins which could be used as a biomarker for predicting PTC.

METHODS

Serum samples were collected from 29 PTC patients and 29 nodular goiter (NG) patients. Five PTC serum samples and five NG serum samples were selected for proteome profiles by proteomics. Eight proteins in PTC and NG serum samples were selected for confirmation by enzyme-linked immunosorbent assay analysis. Receiver operating characteristic curves was used to evaluate the diagnostic value of potential biomarkers.

RESULTS

Complement C4-A (C4A) and plasminogen (PLG) were significantly lower in serum samples of PTC patients compared with NG patients. C4A was observed to have excellent diagnostic accuracy for PTC, with a sensitivity of 91.67% and specificity of 83.33%. The diagnostic value of PLG for PTC was demonstrated by a sensitivity at 87.50% and specificity at 75.00%. The AUC for C4A and PLG was 0.97 ± 0.02 and 0.89 ± 0.05.

CONCLUSION

C4A and PLG appeared to be excellent potential biomarkers for the prediction of PTC.

Haptoglobin: From hemoglobin scavenging to human health

Haptoglobin (Hp) belongs to the family of acute-phase plasma proteins and represents the most important plasma detoxifier of hemoglobin (Hb). The basic Hp molecule is a tetrameric protein built by two α/β dimers. Each Hp α/β dimer is encoded by a single gene and is synthesized as a single polypeptide. Following post-translational protease-dependent cleavage of the Hp polypeptide, the α and β chains are linked by disulfide bridge(s) to generate the mature Hp protein. As human Hp gene is characterized by two common Hp1 and Hp2 alleles, three major genotypes can result (i.e., Hp1-1, Hp2-1, and Hp2-2). Hp regulates Hb clearance from circulation by the macrophage-specific receptor CD163, thus preventing Hb-mediated severe consequences for health. Indeed, the antioxidant and Hb binding properties of Hp as well as its ability to stimulate cells of the monocyte/macrophage lineage and to modulate the helper T-cell type 1 and type 2 balance significantly associate with a variety of pathogenic disorders (e.g., infectious diseases, diabetes, cardiovascular diseases, and cancer). Alternative functions of the variants Hp1 and Hp2 have been reported, particularly in the susceptibility and protection against infectious (e.g., pulmonary tuberculosis, HIV, and malaria) and non-infectious (e.g., diabetes, cardiovascular diseases and obesity) diseases. Both high and low levels of Hp are indicative of clinical conditions: Hp plasma levels increase during infections, inflammation, and various malignant diseases, and decrease during malnutrition, hemolysis, hepatic disease, allergic reactions, and seizure disorders. Of note, the Hp:Hb complexes display heme-based reactivity; in fact, they bind several ferrous and ferric ligands, including O₂, CO, and NO, and display (pseudo-)enzymatic properties (e.g., NO and peroxynitrite detoxification). Here, genetic, biochemical, biomedical, and biotechnological aspects of Hp are reviewed.

Heat Shock Proteins and Ovarian Cancer: Important Roles and Therapeutic Opportunities

Ovarian cancer is a serious cause of death in gynecological oncology. Delayed diagnosis and poor survival rates associated with late stages of the disease are major obstacles against treatment efforts. Heat shock proteins (HSPs) are stress responsive molecules known to be crucial in many cancer types including ovarian cancer. Clusterin (CLU), a unique chaperone protein with analogous oncogenic criteria to HSPs, has also been proven to confer resistance to anti-cancer drugs. Indeed, these chaperone molecules have been implicated in diagnosis, prognosis, metastasis and aggressiveness of various cancers. However, relative to other cancers, there is limited body of knowledge about the molecular roles of these chaperones in ovarian cancer. In the current review, we shed light on the diverse roles of HSPs as well as related chaperone proteins like CLU in the pathogenesis of ovarian cancer and elucidate their potential as effective drug targets.

Label-Free Proteomics Revealed Oxidative Stress and Inflammation as Factors That Enhance Chemoresistance in Luminal Breast Cancer

Breast cancer is the leading cause of cancer-associated death among women worldwide. Its high mortality rate is related to resistance towards chemotherapies, which is one of the major challenges of breast cancer research. In this study, we used label-free mass spectrometry- (MS-) based proteomics to investigate the differences between circulating proteins in the plasma of patients with chemoresponsive and chemoresistant luminal A breast cancer. MS analysis revealed 205 differentially expressed proteins. Furthermore, we used in silico tools to build protein-protein interaction networks. Most of the upregulated proteins in the chemoresistant group were closely related and tightly linked. The predominant networks were related to oxidative stress, the inflammatory response, and the complement cascade. Through this analysis, we identified inflammation and oxidative stress as central processes of breast cancer chemoresistance. Furthermore, we confirmed our hypothesis by evaluating oxidative stress and performing cytokine profiling in our cohort. The connections among oxidative stress, inflammation, and the complement system described in our study seem to indicate a pivotal axis in breast cancer chemoresistance. Hence, these findings will have significant clinical implications for improving therapies to bypass breast cancer chemoresistance in the future.