Identification of proteomic and metabolic signatures associated with chemoresistance of human epithelial ovarian cancer

Identification of chemoresistance associated key genes-miRNAs-TFs in docetaxel resistant breast cancer by bioinformatics analysis

The present study aimed to identify the differentially expressed genes (DEGs) and enriched pathways in docetaxel (DTX) resistant breast cancer cell lines by bioinformatics analysis. The microarray dataset GSE28784 was obtained from gene expression omnibus (GEO) database. The differentially expressed genes (DEGs), gene ontology (GO), and Kyoto Encyclopedia of gene and genome (KEGG) pathway analyses were performed with the help of GEO2R and DAVID tools. Furthermore, the protein-protein interaction (PPI) and hub-gene network of DEGs were constructed using STRING and Cytohubba tools. The prognostic values of hub genes were calculated with the help of the Kaplan-Meier plotter database. From the GEO2R analysis, 222 DEGs were identified of which 120 are upregulated and 102 are downregulated genes. In the PPIs network, five up-regulated genes including CCL2, SPARC, CYR61, F3, and MFGE8 were identified as hub genes. It was observed that low expression of six hub genes CXCL8, CYR61, F3, ICAM1, PLAT, and THBD were significantly correlated with poor overall survival of BC patients in survival analysis. miRNA analysis identified that hsa-mir-16-5p, hsa-mir-335-5p, hsa-mir-124-3p, hsa-mir-20a-5p, and hsa-mir-155-5p are the top 5 interactive miRNAs that are commonly interacting with more hub genes with degree score of greater than five. Additionally, drug-gene interaction analysis was performed to identify drugs which are could potentially elevate/lower the expression levels of hub genes. In summary, the gene-miRNAs-TFs network and subsequent correlation of candidate drugs with hub genes may improve individualized diagnosis and help select appropriate combination therapy for DTX-resistant BC in the future.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-024-03971-2.

Orosomucoid 1 promotes colorectal cancer progression and liver metastasis by affecting PI3K/AKT pathway and inducing macrophage M2 polarization

Approximately 25-30% of those affected by colorectal cancer (CRC), the most prevalent gastrointestinal malignancy, develop metastases. The survival rate of patients with liver metastasis of CRC (CRLM) remains low owing to its unpredictability and a lack of biomarkers that can be applied to distinguish groups at higher risk for CRLM among patients with CRC. Therefore, our study aimed to find biomarkers that can predict the risk of CRLM. Screening of the Gene Expression Omnibus database, supported by an analysis of clinically obtained tissue and serum data using qPCR and ELISA, in an attempt to identify relevant biomarkers, enabled us to determine that orosomucoid 1 (ORM1) was differentially expressed in liver metastases and primary tumors of patients with CRC. Functionally, overexpression of ORM1 promoted the epithelial-mesenchymal transition and the proliferative, migratory, and invasive activities of MC38 cells and activated the PI3K/AKT signaling pathway. Moreover, MC38 cells overexpressing ORM1 enhanced the tumor immune microenvironment by promoting macrophage M2 polarization and elevating interleukin-10 (IL-10) expression. In vivo experiments further confirmed in vitro results, indicating that liver metastases elevated by ORM1 were partially attenuated by the depletion of macrophages or IL-10. Considered together, ORM1 promotes CRC progression and liver metastasis by regulating tumor cell growth and inducing macrophage M2 polarization, which mediates tumor immune tolerance, and thus acts as a potential predictive marker and therapeutic target in CRLM.

Identification of metabolic biomarkers for diagnosis of epithelial ovarian cancer using internal extraction electrospray ionization mass spectrometry (iEESI-MS)

BACKGROUND

Epithelial ovarian cancer (EOC) is the leading cause of death from gynecologic malignancies. The poor prognosis of EOC is mainly due to its asymptomatic early stage, lack of effective screening methods, and a late diagnosis in the advanced stages of the disease.

OBJECTIVE

This study investigated metabolomic abnormalities in epithelial ovarian cancers.

METHODS

Our study developed a novel strategy to rapidly identify the metabolic biomarkers in the plasma of the EOC patients using Internal Extraction Electrospray Ionization Mass Spectrometry (IEESI-MS) and Liquid Chromatography-mass Spectrometry (HPLC-MS), which could distinguish the differential metabolites in between plasma samples collected from 98 patients with epithelial ovarian cancer, including 78 cases with original (P), and 20 cases with self-configuration (ZP), as well as 60 healthy subjects, including 30 cases in the original sample (H), 30 cases in self-configuration (ZH), and 6 cases in a blind sample (B).

RESULTS

Our study detected 880 metabolites based on criteria variable importance in projection (VIP) > 1, among which 26 metabolites were selected for further identification. They are mainly metabolism-related lipids, amino acids, nucleic acids, and others. The metabolic pathways associated with the differential metabolites were explored by the KEGG analysis, a comprehensive database that integrates genome, chemistry, and system function information. The abnormal metabolites of EOC patients identified by IEESI-MS and HPLC-MS included Lysophosphatidylcholine (16:0) [Lyso PC (16:0)], L-Phenylalanine, L-Leucine, Phenylpyruvic acid, L-Tryptophan, and L-Histidine.

CONCLUSIONS

Identifying the abnormal metabolites of EOC patients through metabolomics analyses could provide a new strategy to identify valuable potential biomarkers for the screening and early diagnosis of EOC.

Transcriptome analysis of newly established carboplatin-resistant ovarian cancer cell model reveals genes shared by drug resistance and drug-induced EMT

BACKGROUND

In ovarian cancer (OC) therapy, even initially responsive patients develop drug resistance.

METHODS

Here, we present an OC cell model composed of variants with differing degrees of acquired resistance to carboplatin (CBP), cross-resistance to paclitaxel, and CBP-induced metastatic properties (migration and invasion). Transcriptome data were analysed by two approaches identifying differentially expressed genes and CBP sensitivity-correlating genes. The impact of selected genes and signalling pathways on drug resistance and metastatic potential, along with their clinical relevance, was examined by in vitro and in silico approaches.

RESULTS

TMEM200A and PRKAR1B were recognised as potentially involved in both phenomena, also having high predictive and prognostic values for OC patients. CBP-resistant MES-OV CBP8 cells were more sensitive to PI3K/Akt/mTOR pathway inhibitors Rapamycin, Wortmannin, SB216763, and transcription inhibitor Triptolide compared with parental MES-OV cells. When combined with CBP, Rapamycin decreased the sensitivity of parental cells while Triptolide sensitised drug-resistant cells to CBP. Four PI3K/Akt/mTOR inhibitors reduced migration in both cell lines.

CONCLUSIONS

A newly established research model and two distinct transcriptome analysis approaches identified novel candidate genes enrolled in CBP resistance development and/or CBP-induced EMT and implied that one-gene targeting could be a better approach than signalling pathway inhibition for influencing both phenomena.

Alpha-1 antitrypsin expression is upregulated in multidrug-resistant cancer cells

Identification of the signature molecular profiles involved in therapy resistance is of vital importance in developing new strategies for treatments and disease monitoring. Protein alpha-1 antitrypsin (AAT, encoded by SERPINA1 gene) is an acute-phase protein, and its high expression has been linked with unfavorable clinical outcome in different types of cancer; however, data on its involvement in therapy resistance are still insufficient. We analyzed SERPINA1 mRNA expression in three different multidrug-resistant (MDR) cell lines-U87-TxR, NCI-H460/R, and DLD1-TxR-and in U87 cells grown in alginate microfibers as a 3D cellular model of glioblastoma. Expression of IL-6 as a major modulator of SERPINA1 was also analyzed. Additionally, AAT protein expression in MDR cells was analyzed by immunofluorescence. SERPINA1 gene expression and AAT protein expression were significantly upregulated in all the tested MDR cell lines compared with their sensitive counterparts. Moreover, SERPINA1 was significantly upregulated in 3D models of glioblastoma, previously found to have upregulated drug-resistance-related gene expression compared with 2D cells. With the exception of NCI-H460/R, in all cell lines as well as in a 3D model of U87 cells, increase in SERPINA1 expression correlated with the increase in IL-6 expression. Our results indicate that AAT could be utilized as a biomarker of therapy resistance in cancer; however, further studies are needed to elucidate the mechanisms driving AAT upregulation in therapy resistance and its biological significance in this process.

The Plasma DIA-Based Quantitative Proteomics Reveals the Pathogenic Pathways and New Biomarkers in Cervical Cancer and High Grade Squamous Intraepithelial Lesion

OBJECTIVE

The process of normal cervix changing into high grade squamous intraepithelial lesion (HSIL) and invasive cervical cancer is long and the mechanisms are still not completely clear. This study aimed to reveal the protein profiles related to HSIL and cervical cancer and find the diagnostic and prognostic molecular changes.

METHODS

Data-independent acquisition (DIA) analysis was performed to identify 20 healthy female volunteers, 20 HSIL and 20 cervical patients in a cohort to screen differentially expressed proteins (DEPs) for the HSIL and cervical cancer. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used for functional annotation of DEPs; the protein-protein interaction (PPI) and weighted gene co-expression network analysis (WGCNA) were performed for detection of key molecular modules and hub proteins. They were validated using the Enzyme-Linked Immunosorbent Assay (ELISA).

RESULTS

A total of 243 DEPs were identified in the study groups. GO and KEGG analysis showed that DEPs were mainly enriched in the complement and coagulation pathway, cholesterol metabolism pathway, the IL-17 signaling pathway as well as the viral protein interaction with cytokine and cytokine receptor pathway. Subsequently, the WGCNA analysis showed that the green module was highly correlated with the cervical cancer stage. Additionally, six interesting core DEPs were verified by ELISA, APOF and ORM1, showing nearly the same expression pattern with DIA. The area under the curve (AUC) of 0.978 was obtained by using ORM1 combined with APOF to predict CK and HSIL+CC, and in the diagnosis of HSIL and CC, the AUC can reach to 0.982. The high expression of ORM1 is related to lymph node metastasis and the clinical stage of cervical cancer patients as well as the poor prognosis.

CONCLUSION

DIA-ELSIA combined analysis screened and validated two previously unexplored but potentially useful biomarkers for early diagnosis of HSIL and cervical cancer, as well as possible new pathogenic pathways and therapeutic targets.

Single-cell sequencing reveals effects of chemotherapy on the immune landscape and TCR/BCR clonal expansion in a relapsed ovarian cancer patient

Cancer recurrence and chemoresistance are the leading causes of death in high-grade serous ovarian cancer (HGSOC) patients. However, the unique role of the immune environment in tumor progression for relapsed chemo-resistant patients remains elusive. In single-cell resolution, we characterized a comprehensive multi-dimensional cellular and immunological atlas from tumor, ascites, and peripheral blood of a chemo-resistant patient at different stages of treatment. Our results highlight a role in recurrence and chemoresistance of the immunosuppressive microenvironment in ascites, including MDSC-like myeloid and hypo-metabolic γδT cells, and of peripheral CD8⁺ effector T cells with chemotherapy-induced senescent/exhaustive. Importantly, paired TCR/BCR sequencing demonstrated relative conservation of TCR clonal expansion in hyper-expanded CD8⁺ T cells and extensive BCR clonal expansion without usage bias of V(D)J genes after chemotherapy. Thus, our study suggests strategies for ameliorating chemotherapy-induced immune impairment to improve the clinical outcome of HGSOC.

Molecular Regulation of Androgen Receptors in Major Female Reproductive System Cancers

There are three main types of cancer in the female reproductive system, specifically ovarian cancer (OVCA), endometrial cancer (EC), and cervical cancer (CC). They are common malignant tumors in women worldwide, with high morbidity and mortality. In recent years, androgen receptors (ARs) have been found to be closely related to the occurrence, progression, prognosis, and drug resistance of these three types of tumors. This paper summarizes current views on the role of AR in female reproductive system cancer, the associations between female reproductive system cancers and AR expression and polymorphisms. AR regulates the downstream target genes transcriptional activity and the expression via interacting with coactivators/corepressors and upstream/downstream regulators and through the gene transcription mechanism of “classical A/AR signaling” or “non-classical AR signaling”, involving a large number of regulatory factors and signaling pathways. ARs take part in the processes of cancer cell proliferation, migration/invasion, cancer cell stemness, and chemotherapeutic drug resistance. These findings suggest that the AR and related regulators could target the treatment of female reproductive system cancer.

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.

Platinum-resistant ovarian cancer: From drug resistance mechanisms to liquid biopsy-based biomarkers for disease management

Resistance to platinum-based chemotherapy is a major clinical challenge in ovarian cancer, contributing to the high mortality-to-incidence ratio. Management of the platinum-resistant disease has been difficult due to diverse underlying molecular mechanisms. Over the past several years, research has revealed several novel molecular targets that are being explored as biomarkers for treatment planning and monitoring of response. The therapeutic landscape of ovarian cancer is also rapidly evolving, and alternative therapies are becoming available for the recurrent platinum-resistant disease. This review provides a snapshot of platinum resistance mechanisms and discusses liquid-based biomarkers and their potential utility in effective management of platinum-resistant ovarian cancer.

Integrated Transcriptomic Analysis Revealed Hub Genes and Pathways Involved in Sorafenib Resistance in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC), a high mortality malignancy, has become a worldwide public health concern. Acquired resistance to the multikinase inhibitor sorafenib challenges its clinical efficacy and the survival benefits it provides to patients with advanced HCC. This study aimed to identify critical genes and pathways associated with sorafenib resistance in HCC using integrated bioinformatics analysis. Differentially expressed genes (DEGs) were identified using four HCC gene expression profiles (including 34 sorafenib-resistant and 29 sorafenib-sensitive samples) based on the robust rank aggregation method and R software. Gene ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID) online tool. A protein–protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes (STRING), and small molecules reversing sorafenib resistance were searched for using the connectivity map (CMAP) database. Pearson correlation and survival analyses of hub genes were performed using cBioPortal and Gene Expression Profiling and Interactive Analysis (GEPIA). Finally, the expression levels of hub genes in sorafenib-resistant HCC cells were verified using quantitative polymerase chain reaction (q-PCR). A total of 165 integrated DEGs (66 upregulated and 99 downregulated in sorafenib resistant samples compared sorafenib sensitive ones) primarily enriched in negative regulation of endopeptidase activity, extracellular exosome, and protease binding were identified. Some pathways were commonly shared between the integrated DEGs. Seven promising therapeutic agents and 13 hub genes were identified. These findings provide a strategy and theoretical basis for overcoming sorafenib resistance in HCC patients.

The Role of Omics Approaches to Characterize Molecular Mechanisms of Rare Ovarian Cancers: Recent Advances and Future Perspectives

Rare ovarian cancers are ovarian cancers with an annual incidence of less than 6 cases per 100,000 women. They generally have a poor prognosis due to being delayed diagnosis and treatment. Exploration of molecular mechanisms in these cancers has been challenging due to their rarity and research efforts being fragmented across the world. Omics approaches can provide detailed molecular snapshots of the underlying mechanisms of these cancers. Omics approaches, including genomics, transcriptomics, proteomics, and metabolomics, can identify potential candidate biomarkers for diagnosis, prognosis, and screening of rare gynecological cancers and can aid in identifying therapeutic targets. The integration of multiple omics techniques using approaches such as proteogenomics can provide a detailed understanding of the molecular mechanisms of carcinogenesis and cancer progression. Further, omics approaches can provide clues towards developing immunotherapies, cancer recurrence, and drug resistance in tumors; and form a platform for personalized medicine. The current review focuses on the application of omics approaches and integrative biology to gain a better understanding of rare ovarian cancers.

Long non-coding RNAs as the critical regulators of doxorubicin resistance in tumor cells

Resistance against conventional chemotherapeutic agents is one of the main reasons for tumor relapse and poor clinical outcomes in cancer patients. Various mechanisms are associated with drug resistance, including drug efflux, cell cycle, DNA repair and apoptosis. Doxorubicin (DOX) is a widely used first-line anti-cancer drug that functions as a DNA topoisomerase II inhibitor. However, DOX resistance has emerged as a large hurdle in efficient tumor therapy. Furthermore, despite its wide clinical application, DOX is a double-edged sword: it can damage normal tissues and affect the quality of patients’ lives during and after treatment. It is essential to clarify the molecular basis of DOX resistance to support the development of novel therapeutic modalities with fewer and/or lower-impact side effects in cancer patients. Long non-coding RNAs (lncRNAs) have critical roles in the drug resistance of various tumors. In this review, we summarize the state of knowledge on all the lncRNAs associated with DOX resistance. The majority are involved in promoting DOX resistance. This review paves the way to introducing an lncRNA panel marker for the prediction of the DOX response and clinical outcomes for cancer patients.

Comprehending the Proteomic Landscape of Ovarian Cancer: A Road to the Discovery of Disease Biomarkers

Despite recent technological advancements allowing the characterization of cancers at a molecular level along with biomarkers for cancer diagnosis, the management of ovarian cancers (OC) remains challenging. Proteins assume functions encoded by the genome and the complete set of proteins, termed the proteome, reflects the health state. Comprehending the circulatory proteomic profiles for OC subtypes, therefore, has the potential to reveal biomarkers with clinical utility concerning early diagnosis or to predict response to specific therapies. Furthermore, characterization of the proteomic landscape of tumor-derived tissue, cell lines, and PDX models has led to the molecular stratification of patient groups, with implications for personalized therapy and management of drug resistance. Here, we review single and multiple marker panels that have been identified through proteomic investigations of patient sera, effusions, and other biospecimens. We discuss their clinical utility and implementation into clinical practice.

Systematic prediction of drug resistance caused by transporter genes in cancer cells

To study the drug resistance problem caused by transporters, we leveraged multiple large-scale public data sets of drug sensitivity, cell line genetic and transcriptional profiles, and gene silencing experiments. Through systematic integration of these data sets, we built various machine learning models to predict the difference between cell viability upon drug treatment and the silencing of its target across the same cell lines. More than 50% of the models built with the same data set or with independent data sets successfully predicted the testing set with significant correlation to the ground truth data. Features selected by our models were also significantly enriched in known drug transporters annotated in DrugBank for more than 60% of the models. Novel drug-transporter interactions were discovered, such as lapatinib and gefitinib with ABCA1, olaparib and NVPADW742 with ABCC3, and gefitinib and AZ628 with SLC4A4. Furthermore, we identified ABCC3, SLC12A7, SLCO4A1, SERPINA1, and SLC22A3 as potential transporters for erlotinib, three of which are also significantly more highly expressed in patients who were resistant to therapy in a clinical trial.

The application of metabolomics in ovarian cancer management: a systematic review

Metabolomics, the global analysis of metabolites in a biological specimen, could potentially provide a fast method of biomarker identification for ovarian cancer. This systematic review aims to examine findings from studies that apply metabolomics to the diagnosis, prognosis, treatment, and recurrence of ovarian cancer. A systematic search of English language publications was conducted on PubMed, Science Direct, and SciFinder. It was augmented by a snowball strategy, whereby further relevant studies are identified from reference lists of included studies. Studies in humans with ovarian cancer which focus on metabolomics of biofluids and tumor tissue were included. No restriction was placed on the time of publication. A separate review of targeted metabolomic studies was conducted for completion. Qualitative data were summarized in a comprehensive table. The studies were assessed for quality and risk of bias using the ROBINS-I tool. 32 global studies were included in the main systematic review. Most studies applied metabolomics to diagnosing ovarian cancer, within which the most frequently reported metabolite changes were a down-regulation of phospholipids and amino acids: histidine, citrulline, alanine, and methionine. Dysregulated phospholipid metabolism was also reported in the separately reviewed 18 targeted studies. Generally, combinations of more than one significant metabolite as a panel, in different studies, achieved a higher sensitivity and specificity for diagnosis than a single metabolite; for example, combinations of different phospholipids. Widespread metabolite differences were observed in studies examining prognosis, treatment, and recurrence, and limited conclusions could be drawn. Cellular processes of proliferation and invasion may be reflected in metabolic changes present in poor prognosis and recurrence. For example, lower levels of lysine, with increased cell invasion as an underlying mechanism, or glutamine dependency of rapidly proliferating cancer cells. In conclusion, this review highlights potential metabolites and biochemical pathways which may aid the clinical care of ovarian cancer if further validated.

Metabolic Reprogramming of Chemoresistant Cancer Cells and the Potential Significance of Metabolic Regulation in the Reversal of Cancer Chemoresistance

Metabolic reprogramming is one of the hallmarks of tumors. Alterations of cellular metabolism not only contribute to tumor development, but also mediate the resistance of tumor cells to antitumor drugs. The metabolic response of tumor cells to various chemotherapy drugs can be analyzed by metabolomics. Although cancer cells have experienced metabolic reprogramming, the metabolism of drug resistant cancer cells has been further modified. Metabolic adaptations of drug resistant cells to chemotherapeutics involve redox, lipid metabolism, bioenergetics, glycolysis, polyamine synthesis and so on. The proposed metabolic mechanisms of drug resistance include the increase of glucose and glutamine demand, active pathways of glutaminolysis and glycolysis, promotion of NADPH from the pentose phosphate pathway, adaptive mitochondrial reprogramming, activation of fatty acid oxidation, and up-regulation of ornithine decarboxylase for polyamine production. Several genes are associated with metabolic reprogramming and drug resistance. Intervening regulatory points described above or targeting key genes in several important metabolic pathways may restore cell sensitivity to chemotherapy. This paper reviews the metabolic changes of tumor cells during the development of chemoresistance and discusses the potential of reversing chemoresistance by metabolic regulation.

The Role and Underlying Mechanism of Exosomal CA1 in Chemotherapy Resistance in Diffuse Large B Cell Lymphoma

Chemotherapy resistance plays a major role in treatment failure of diffuse large B cell lymphoma (DLBCL). Exosomes are closely related to tumor drug resistance. Herein, the expression of exosomal proteins in DLBCL and their roles in chemotherapy resistance of DLBCL are explored. Tandem mass tag labeling proteomics was used to perform proteomic profiling in exosomes from DLBCL patients’ serum. The expression of carbonic anhydrase 1 (CA1) in parental, chemo-resistant DLBCL cells and DLBCL patient exosomes was detected. Proliferation of DLBCL following CA1 knockdown was investigated both in vitro and in vivo, along with the effects on nuclear factor κB (NF-κB) and signal transducer and activator of transcription 3 (STAT3) pathways. We identified 54 differentially expressed proteins. We validated that the expression level of exosomal CA1 was higher in chemo-resistant DLBCL cells than in chemo-sensitive counterparts. Knockdown of CA1 inhibited the growth of DLBCL via inhibiting the activation of NF-κB and STAT3 signaling pathways both in vitro and in vivo. An increased expression level of exosomal CA1 was associated with poorer prognosis, and exosomal CA1 could be used as a biomarker to predict chemotherapeutic efficacy. Our study suggests that exosomal CA1 can promote chemotherapy resistance in DLBCL via the NF-κB and STAT3 pathways, and it can serve as a biomarker for DLBCL prognosis.

A systematic literature review assessing if genetic biomarkers are predictors for platinum-based chemotherapy response in ovarian cancer patients

BACKGROUND

Ovarian cancer is the deadliest of gynecologic malignancies with the 5-year overall survival rate remaining at approximately 30%, a rate that has not improved over the last three decades. Standard of care for epithelial ovarian cancer patients consists of a platinum compound with a taxane given intravenously following debulking surgery; however, 80% of cases relapse within 2 years of diagnosis. This review sought to identify key underlying biomarkers related to platinum resistance in ovarian cancer to establish possible prognostic biomarkers of chemoresponse.

METHODS

A systematic literature review was conducted across three databases PubMed, EMBASE and SCOPUS to summarise the evidence for prognostic biomarkers in platinum-resistant ovarian cancer patients.

RESULTS

Forty-eight human studies were used in the review encompassing 6719 participants in retrospective and prospective study designs. A total of 68 biomarkers were reported that were significantly correlated with chemoresponse and/or survival reporting a p value less than or equal to 0.05.

CONCLUSION

This review accentuates the pleiotropic phenotypic complexities related to the response to platinum therapy in ovarian cancer. A one-size-fits-all approach may be ineffective in a large portion of patients, emphasising the need for a whole system-based approach and personalised treatment strategies. Identifying key biomarkers to aid clinical decision-making is the first essential step in developing and appropriating therapies for at-risk patients, reducing toxicity and improving quality of life.

Proteomic Discovery of Biomarkers to Predict Prognosis of High-Grade Serous Ovarian Carcinoma

Initial identification of biomarkers predicting the exact prognosis of high-grade serous ovarian carcinoma (HGSOC) is important in precision cancer medicine. This study aimed to investigate prognostic biomarkers of HGSOC through proteomic analysis. We conducted label-free liquid chromatography-mass spectrometry using chemotherapy-naïve, fresh-frozen primary HGSOC specimens, and compared the results between a favorable prognosis group (progression-free survival (PFS) ≥ 18 months, n = 6) and a poor prognosis group (PFS < 18 months, n = 6). Among 658 differentially expressed proteins, 288 proteins were upregulated in the favorable prognosis group and 370 proteins were upregulated in the poor prognosis group. Using hierarchical clustering, we selected α1-antitrypsin (AAT), nuclear factor-κB (NFKB), phosphomevalonate kinase (PMVK), vascular adhesion protein 1 (VAP1), fatty acid-binding protein 4 (FABP4), platelet factor 4 (PF4), apolipoprotein A1 (APOA1), and α1-acid glycoprotein (AGP) for further validation via immunohistochemical (IHC) staining in an independent set of chemotherapy-naïve primary HGSOC samples (n = 107). Survival analyses revealed that high expression of AAT, NFKB, and PMVK were independent biomarkers for favorable PFS. Conversely, high expression of VAP1, FABP4, and PF4 were identified as independent biomarkers for poor PFS. Furthermore, we constructed models predicting the 18-month PFS by combining clinical variables and IHC results. Through leave-one-out cross-validation, the optimal model was based on initial serum CA-125, germline BRCA1/2 mutations, residual tumors after surgery, International Federation of Gynecology and Obstetrics (FIGO) stage, and expression levels of the six proteins. The present results elucidate the proteomic landscape of HGSOC and six protein biomarkers to predict the prognosis of HGSOC.

Functional and transcriptomic characterization of cisplatin-resistant AGS and MKN-28 gastric cancer cell lines

Gastric cancer (GC) is a significant cancer-related cause of death worldwide. The most used chemotherapeutic regimen in GC is based on platinum drugs such as cisplatin (CDDP). However, CDDP resistance reduces advanced GC survival. In vitro drug-resistant cell model would help in the understanding of molecular mechanisms underlying this drug-resistance phenomenon. The aim of this study was to characterize new models of CDDP-resistant GC cell lines (AGS R-CDDP and MKN-28 R-CDDP) obtained through a stepwise increasing drug doses method, in order to understand the molecular mechanisms underlying chemoresistance as well as identify new therapeutic targets for the treatment of GC. Cell viability assays, cell death assays and the expression of resistance molecular markers confirmed that AGS R-CDDP and MKN-28 R-CDDP are reliable CDDP-resistant models. RNA-seq and bioinformatics analyses identified a total of 189 DEGs, including 178 up-regulated genes and 11 down-regulated genes, associated mainly to molecular functions involved in CDDP-resistance. DEGs were enriched in 23 metabolic pathways, among which the most enriched was the inflammation mediated by chemokine and cytokine signaling pathway. Finally, the higher mRNA expression of SERPINA1, BTC and CCL5, three up-regulated DEGs associated to CDDP resistance found by RNA-seq analysis was confirmed. In summary, this study showed that AGS R-CDDP and MKN-28 R-CDDP are reliable models of CDDP resistance because resemble many of resistant phenotype in GC, being also useful to assess potential therapeutic targets for the treatment of gastric cancers resistant to CDDP. In addition, we identified several DEGs associated with molecular functions such as binding, catalytic activity, transcription regulator activity and transporter activity, as well as signaling pathways associated with inflammation process, which could be involved in the development of CDDP resistance in GC. Further studies are necessary to clarify the role of inflammatory processes in GC resistant to CDDP and these models could be useful for these purposes.

Quantitative analysis of proteins related to chemoresistance to paclitaxel and carboplatin in human SiHa cervical cancer cells via iTRAQ

Objective

This study aimed to identify proteins related to paclitaxel and carboplatin chemoresistance in cervical cancer.

Methods

Quantitative proteomic analysis was performed on normal SiHa cells and those treated with paclitaxel and carboplatin for 14 days, with isobaric tags for relative and absolute quantitation (iTRAQ) analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were used to identify related processes and differentially expressed proteins.

Results

A total of 67 and 96 differentially expressed proteins were identified in the paclitaxel- and carboplatin- treated groups, respectively. GO and KEGG enrichment analyses identified 53 (43 upregulated and 10 downregulated) and 85 differentially expressed proteins (70 upregulated and 15 downregulated) in the paclitaxel- and carboplatin-treated groups, respectively. The cell counting kit-8 results revealed that APOA1 was overexpressed in both the paclitaxel- and carboplatin- resistant SiHa cells compared with the control cells. Immunohistochemistry showed that APOA1 was highly expressed in the paclitaxel- and carboplatin- resistant squamous cell carcinoma of the cervix.

Conclusion

This study is the first to use iTRAQ to identify paclitaxel- and carboplatin- resistance proteins in cervical cells. We identified several proteins previously unassociated with paclitaxel and carboplatin resistance in cervical cancer, thereby expanding our understanding of paclitaxel and carboplatin resistance mechanisms. Moreover, these findings indicate that the APOA1 protein could serve as a potential marker for monitoring and predicting paclitaxel and carboplatin resistance levels.

Dietary Selenium Supplementation Ameliorates Female Reproductive Efficiency in Aging Mice

Female reproductive (ovarian) aging is distinctively characterized by a markedly reduced reproductive function due to a remarkable decline in quality and quantity of follicles and oocytes. Selenium (Se) has been implicated in playing many important biological roles in male fertility and reproduction; however, its potential roles in female reproduction, particularly in aging subjects, remain poorly elucidated. Therefore, in the current study we used a murine model of female reproductive aging and elucidated how different Se-levels might affect the reproductive efficiency in aging females. Our results showed that at the end of an 8-week dietary trial, whole-blood Se concentration and blood total antioxidant capacity (TAOC) were significantly reduced in Se-deficient (0.08 mg Se/kg; Se-D) mice, whereas both of these biomarkers were significantly higher in inorganic (0.33 mg/kg; ISe-S) and organic (0.33 mg/kg; OSe-S) Se-supplemented groups. Similarly, compared to the Se-D group, Se supplementation significantly ameliorated the maintenance of follicles and reduced the rate of apoptosis in ovaries. Meanwhile, the rate of in vitro-produced embryos resulting from germinal vesicle (GV) oocytes was also significantly improved in Se-supplemented (ISe-S and OSe-S) groups compared to the Se-D mice, in which none of the embryos developed to the hatched blastocyst stage. RT-qPCR results revealed that mRNA expression of Gpx1, Gpx3, Gpx4, Selenof, p21, and Bcl-2 genes in ovaries of aging mice was differentially modulated by dietary Se levels. A considerably higher mRNA expression of Gpx1, Gpx3, Gpx4, and Selenof was observed in Se-supplemented groups compared to the Se-D group. Similarly, mRNA expression of Bcl-2 and p21 was significantly lower in Se-supplemented groups. Immunohistochemical assay also revealed a significantly higher expression of GPX4 in Se-supplemented mice. Our results reasonably indicate that Se deficiency (or marginal levels) can negatively impact the fertility and reproduction in females, particularly those of an advancing age, and that the Se supplementation (inorganic and organic) can substantiate ovarian function and overall reproductive efficiency in aging females.

The epigenetic factor BORIS (CTCFL) controls the androgen receptor regulatory network in ovarian cancer

The identification of prognostic biomarkers is a priority for patients suffering from high-grade serous ovarian cancer (SOC), which accounts for >70% of ovarian cancer (OC) deaths. Meanwhile, borderline ovarian cancer (BOC) is a low malignancy tumor and usually patients undergo surgery with low probabilities of recurrence. However, SOC remains the most lethal neoplasm due to the lack of biomarkers for early diagnosis and prognosis. In this regard, BORIS (CTCFL), a CTCF paralog, is a promising cancer biomarker that is overexpressed and controls transcription in several cancer types, mainly in OC. Studies suggest that BORIS has an important function in OC by altering gene expression, but the effect and extent to which BORIS influences transcription in OC from a genome-wide perspective is unclear. Here, we sought to identify BORIS target genes in an OC cell line (OVCAR3) with potential biomarker use in OC tumor samples. To achieve this, we performed in vitro knockout and knockdown experiments of BORIS in OVCAR3 cell line followed by expression microarrays and bioinformatics network enrichment analysis to identify relevant BORIS target genes. In addition, ex vivo expression data analysis of 373 ovarian cancer patients were evaluated to identify the expression patterns of BORIS target genes. In vitro, we uncovered 130 differentially expressed genes and obtained the BORIS-associated regulatory network, in which the androgen receptor (AR) acts as a major transcription factor. Also, FN1, FAM129A, and CD97 genes, which are related to chemoresistance and metastases in OC, were identified. In SOC patients, we observed that malignancy is associated with high levels of BORIS expression while BOC patients show lower levels. Our study suggests that BORIS acts as a main regulator, and has the potential to be used as a prognostic biomarker and to yield novel drug targets among the genes BORIS controls in SOC patients.

Chemotherapy-Induced Distal Enhancers Drive Transcriptional Programs to Maintain the Chemoresistant State in Ovarian Cancer

Chemoresistance is driven by unique regulatory networks in the genome that are distinct from those necessary for cancer development. Here, we investigate the contribution of enhancer elements to cisplatin resistance in ovarian cancers. Epigenome profiling of multiple cellular models of chemoresistance identified unique sets of distal enhancers, super-enhancers (SE), and their gene targets that coordinate and maintain the transcriptional program of the platinum-resistant state in ovarian cancer. Pharmacologic inhibition of distal enhancers through small-molecule epigenetic inhibitors suppressed the expression of their target genes and restored cisplatin sensitivity in vitro and in vivo. In addition to known drivers of chemoresistance, our findings identified SOX9 as a critical SE-regulated transcription factor that plays a critical role in acquiring and maintaining the chemoresistant state in ovarian cancer. The approach and findings presented here suggest that integrative analysis of epigenome and transcriptional programs could identify targetable key drivers of chemoresistance in cancers. SIGNIFICANCE: Integrative genome-wide epigenomic and transcriptomic analyses of platinum-sensitive and -resistant ovarian lines identify key distal regulatory regions and associated master regulator transcription factors that can be targeted by small-molecule epigenetic inhibitors.

Overcoming platinum-acquired resistance in ovarian cancer patient-derived xenografts

Background:

Epithelial ovarian cancer is the most lethal gynecological cancer and the high mortality is due to the frequent presentation at advanced stage, and to primary or acquired resistance to platinum-based therapy.

Methods:

We developed three new models of ovarian cancer patient-derived xenografts (ovarian PDXs) resistant to cisplatin (cDDP) after multiple in vivo drug treatments. By different and complementary approaches based on integrated metabolomics (both targeted and untargeted mass spectrometry-based techniques), gene expression, and functional assays (Seahorse technology) we analyzed and compared the tumor metabolic profile in each sensitive and their corresponding cDDP-resistant PDXs.

Results:

We found that cDDP-sensitive and -resistant PDXs have a different metabolic asset. In particular, we found, through metabolomic and gene expression approaches, that glycolysis, tricarboxylic acid cycle and urea cycle pathways were deregulated in resistant versus sensitive PDXs. In addition, we observed that oxygen consumption rate and mitochondrial respiration were higher in resistant PDXs than in sensitive PDXs under acute stress conditions. An increased oxidative phosphorylation in cDDP-resistant sublines led us to hypothesize that its interference could be of therapeutic value. Indeed, in vivo treatment of metformin and cDDP was able to partially reverse platinum resistance.

Conclusions:

Our data strongly reinforce the idea that the development of acquired cDDP resistance in ovarian cancer can bring about a rewiring of tumor metabolism, and that this might be exploited therapeutically.

Novel Approaches in Ovarian Cancer Research against Heterogeneity, Late Diagnosis, Drug Resistance, and Transcoelomic Metastases

The development of modern technologies has revolutionised science and has had a huge impact on biomedical studies. This review focuses on possible tools that scientists can use to face the challenges of fighting ovarian cancer. Ovarian cancer is the deadliest gynaecologic malignancy and, even after years of study, the mortality has not decreased significantly. In the era of sequencing and personalised and precision medicine, we are now closer than ever to helping patients and physicians in regard to treatment and diagnosis of this disease. This work summarises the newest findings in the development of ovarian cancer research.

Selenium, Selenoproteins, and Female Reproduction: A Review

Selenium (Se) is an essential micronutrient that has several important functions in animal and human health. The biological functions of Se are carried out by selenoproteins (encoded by twenty-five genes in human and twenty-four in mice), which are reportedly present in all three domains of life. As a component of selenoproteins, Se has structural and enzymatic functions; in the latter context it is best recognized for its catalytic and antioxidant activities. In this review, we highlight the biological functions of Se and selenoproteins followed by an elaborated review of the relationship between Se and female reproductive function. Data pertaining to Se status and female fertility and reproduction are sparse, with most such studies focusing on the role of Se in pregnancy. Only recently has some light been shed on its potential role in ovarian physiology. The exact underlying molecular and biochemical mechanisms through which Se or selenoproteins modulate female reproduction are largely unknown; their role in human pregnancy and related complications is not yet sufficiently understood. Properly powered, randomized, controlled trials (intervention vs. control) in populations of relatively low Se status will be essential to clarify their role. In the meantime, studies elucidating the potential effect of Se supplementation and selenoproteins (i.e., GPX1, SELENOP, and SELENOS) in ovarian function and overall female reproductive efficiency would be of great value.

Fibronectin-1 modulated by the long noncoding RNA OIP5-AS1/miR-200b-3p axis contributes to doxorubicin resistance of osteosarcoma cells

Chemoresistance has been an obstacle in the further improvement of 5-year survival rates of osteosarcoma (OS) patients, but the underlying mechanism of chemo-resistance remains unclear. A comprehensive analysis of mRNAs and noncoding RNAs related to OS chemo-resistance could help solve this problem. In the current study, we first identified that fibronectin-1 (FN1), screened by microarray analysis in three paired chemo-resistant and chemo-sensitive OS cell lines, was significantly upregulated in the chemo-resistant OS cell lines and tissues and was related to unfavourable prognosis. Further functional assays revealed that FN1 inhibition greatly increased the sensitivity of OS cells to doxorubicin in vitro and in vivo, whereas FN1 overexpression had the opposite effect. Moreover, mechanistic investigation demonstrated, by a series of assays that included luciferase reporter gene, RNA immunoprecipitation, RNA pull-down and rescue assays, that FN1 expression was regulated by the oncogenic long noncoding RNA (lncRNA) OIP5-AS1 through sponging miR-200b-3p. Thus, these results indicated the role and potential application of the lncRNA OIP5-AS1/miR-200b-3p/FN1 regulatory pathway as a promising target in treatment of OS chemo-resistance.

Analysis of the plasma proteome using iTRAQ and TMT-based Isobaric labeling

Over the past decade, chemical labeling with isobaric tandem mass tags, such as isobaric tags for relative and absolute quantification reagents (iTRAQ) and tandem mass tag (TMT) reagents, has been employed in a wide range of different clinically orientated serum and plasma proteomics studies. In this review the scope of these works is presented with attention to the areas of research, methods employed and performance limitations. These applications have covered a wide range of diseases, disorders and infections, and have implemented a variety of different preparative and mass spectrometric approaches. In contrast to earlier works, which struggled to quantify more than a few hundred proteins, increasingly these studies have provided deeper insight into the plasma proteome extending the numbers of quantified proteins to over a thousand.

Exosome-mediated transfer of lncRNA RP11‑838N2.4 promotes erlotinib resistance in non-small cell lung cancer

Currently, resistance to tyrosine kinase inhibitors, such as erlotinib, has become a major obstacle for improving the clinical outcome of patients with metastatic and advanced-stage non-small cell lung cancer (NSCLC). While cell behavior can be modulated by long non-coding RNAs (lncRNAs), the roles of lncRNAs within extracellular vesicles (exosomes) are largely unknown. To this end, in this study, the involvement and regulatory functions of potential lncRNAs wrapped by exosomes during the development of chemoresistance in human NSCLC were investigated. Erlotinib-resistant cell lines were established by grafting HCC827 and HCC4006 cells into mice and which were treated with erlotinib. After one treatment course, xenografted NSCLC cells were isolated and transplanted into nude mice again followed by erlotinib treatment. This process was repeated until 4th generation xenografts were isolated and confirmed to be erlotinib-resistant NSCLC cells. lncRNA microarray assays followed by RT-qPCR were then performed which identified that lncRNA RP11-838N2.4 was upregulated in erlotinib-resistant cells when compared to normal NSCLC cells. Furthermore, bioinformatics analysis and chromatin immunoprecipitation revealed that forkhead box protein O1 (FOXO1) could bind to the promoter region of lncRNA RP11-838N2.4, resulting in its silencing through the recruitment of histone deacetylase. Functional experiments demonstrated that the knockdown of lncRNA RP11-838N2.4 potently promoted erlotinib-induced cytotoxicity. Furthermore, extracellular lncRNA RP11-838N2.4 could be incorporated into exosomes and transmitted to sensitive cells, thus disseminating erlotinib resistance. Treatment-sensitive cells with exosomes containing lncRNA RP11-838N2.4 induced erlotinib resistance, while the knockdown of lncRNA RP11-838N2.4 abrogated this effect. In addition, the serum expression levels of exosomal lncRNA RP11-838N2.4 were upregulated in patients exhibiting resistance to erlotinib treatment. On the whole, exosomal lncRNA RP11-838N2.4 may serve as a therapeutic target for patients with NSCLC.

The role of ROS and subsequent DNA-damage response in PUMA-induced apoptosis of ovarian cancer cells

PUMA is a member of the "BH3-only" branch of the BCL-2 family. Our previous study suggests a therapeutic potential of PUMA in treating ovarian cancer, however, the action mechanism of PUMA remains elusive. In this work, we found that in PUMA adenovirus-infected A2780s ovarian cancer cells, exogenous PUMA was partially accumulated in the cytosol and mainly located to the mitochondria. We further showed that PUMA induces mitochondrial dysfunction-mediated apoptosis and ROS generation through functional BAX in a ROS generating enzyme- and caspase-independent manner irrespective of their p53 status, and results in activation of Nrf2/HO-1 pathway. Furthermore, PUMA induces DNA breaks in γ-H2AX staining, and causes activation of DNA damage-related kinases including ATM, ATR, DNA-PKcs, Chk1 and Chk2, which are correlated with the apoptosis. PUMA also results in ROS-triggered JNK activation. Intriguingly, JNK plays a dual role in both DNA damage response and apoptosis, and has an additional contribution to apoptosis. Taken together, we have provided new insight into the action mechanism by which elevated PUMA first induces ROS generation then results in DNA damage response and JNK activation, ultimately contributing to apoptosis in ovarian cancer cells.

STROBE-compliant integrin through focal adhesion involve in cancer stem cell and multidrug resistance of ovarian cancer

Cancer stem cells (CSCs) are considered to be the root of carcinoma relapse and drug resistance in ovarian cancer. Hunting for the potential CSC genes and explain their functions would be a feasible strategy to meet the challenge of the drug resistance in ovarian cancer. In this study, we performed bioinformatic approaches such as biochip data extraction and pathway enrichment analyses to elucidate the mechanism of the CSC genes in regulation of drug resistance. Potential key genes, integrins, were identified to be related to CSC in addition to their associations with drug resistance and prognosis in ovarian cancer. A total of 36 ovarian CSC genes involved in regulation of drug resistance were summarized, and potential drug resistance-related CSC genes were identified based on 3 independent microarrays retrieved from the Gene Expression Omnibus (GEO) Profiles. Pathway enrichment of CSC genes associated with drug resistance in ovarian cancer indicated that focal adhesion signaling might play important roles in CSC genes-mediated drug resistance. Integrins are members of the adhesion molecules family, and integrin subunit alpha 1, integrin subunit alpha 5, and integrin subunit alpha 6 (ITGA6) were identified as central CSC genes and their expression in side population cells, cisplatin-resistant SKOV3 (SKOV3/DDP2) cells, and cisplatin-resistant A2780 (A2780/DDP) cells were dysregulated as measured by real-time quantitative polymerase chain reaction. The high expression of ITGA6 in 287 ovarian cancer patients of TCGA cohort was significantly associated with poorer progression-free survival. This study provide the basis for further understanding of CSC genes in regulation of drug resistance in ovarian cancer, and integrins could be a potential biomarker for prognosis of ovarian cancer.