Comparative Proteomic Analysis of Advanced Serous Epithelial Ovarian Carcinoma: Possible Predictors of Chemoresistant Disease

The role of tumor-educated platelets in ovarian cancer: A comprehensive review and update

Platelets have recently surfaced as critical players in cancer metastasis and the local and systemic responses to tumor growth. The emerging concept of "Tumor-educated platelets (TEPs)" comprises the exchange of biomolecules between tumor cells and platelets, thereby leading to the "education" of platelets. Increased platelet numbers have long been associated with cancer patients' tumor metastasis and poor clinical prognosis. However, it is very recently that researchers have delved deeper into the tumor-microenvironment and probed the mechanism of interactions between tumor cells and platelets. Designing strategies to target the TEPs and the communications between platelets and tumor cells can prove to be a promising breakthrough in cancer therapy. Through this review, we aim to analyze the recent developments in this field and discuss the characteristics of TEPs, focusing on ovarian cancer-associated TEPs and their characteristics, the interplay between ovarian cancer-associated TEPs and cancer cells, and the purview of TEP-targeted cancer diagnosis and therapy, including platelet biomarkers and inhibitors.

N-Glycome changes reflecting resistance to platinum-based chemotherapy in ovarian cancer

A number of studies have reported aberrant glycosylation in connection with malignancy. Our investigation further expands on this topic through the examination of N-glycans, which could be associated with the resistance of advanced stage, high-grade non-mucinous ovarian cancer to platinum/taxane based chemotherapy. We used tissue samples of 83 ovarian cancer patients, randomly divided into two independent cohorts (basic and validation). Both groups involved either cases with/without postoperative tumor residue or the cases determined either resistant or sensitive to this chemotherapy. In the validation cohort, preoperative serum samples were also available. N-glycans released from tumors and sera were permethylated and analyzed by matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). The MS analysis yielded a consecutive detection of 68 (tissue) and 63 (serum) N-glycan spectral signals. Eight of these were found to be differentially abundant in tissues of both independent cohorts including the cases with a postoperative cancer residue. One of these glycans was detected as differentially abundant in sera of the validation cohort. No statistically significant differences in intensities due to the same N-glycans were found in the cases without postoperative macroscopic residues in either the basic or validation cohort. From the biochemical point of view, the statistically significant N-glycans correspond to the structures carrying bisecting (terminal) GlcNAc residue and tetra-antennary structures with sialic acid and/or fucose residues. Among them, six tissue N-glycans could be considered potential markers connected with a resistance to chemotherapy in ovarian cancer patients. The prediction of primary resistance to standard chemotherapy may identify the group of patients suitable for alternative treatment strategies. SIGNIFICANCE: Drug resistance has become a major impediment to a successful treatment of patients with advanced ovarian cancer. The glycomic measurements related to cancer are becoming increasingly popular in identification of the key molecules as potential diagnostic and prognostic indicators. Our report deals with identification of differences in N-glycosylation of proteins in tissue and serum samples from the individuals showing sensitivity or resistance to platinum/taxane-based chemotherapy. The detection sensitivity to chemotherapy is vitally important for these patients.

Proteome profiling of low grade serous ovarian cancer

Background

Serous carcinoma, the subtype of ovarian cancer has the highest occurrence and mortality in women. Proteomic profiling using mass spectrometry (MS) has been used to detect biomarkers in tissue s obtained from patients with ovarian cancer.

Thus, this study aimed at analyzing the interactome (protein-protein interaction (PPI)) and (MS) data to inspect PPI networks in patients with Low grade serous ovarian cancer.

Methods

For proteome profiling in Low grade serous ovarian cancer, 2DE and mass spectrometry were used. Differentially expressed proteins which had been determined in Low grade serous ovarian cancer and experimental group separately were integrated with PPI data to construct the (QQPPI) networks.

Results

Six Hub-bottlenecks proteins with significant centrality values, based on centrality parameters of the network (Degree and between), were found including Transgelin (TAGLN), Keratin (KRT14), Single peptide match to actin, cytoplasmic 1(ACTB), apolipoprotein A-I (APOA1), Peroxiredoxin-2 (PRDX2), and Haptoglobin (HP).

Discussion

This study showed these six proteins were introduced as hub-bottleneck protein. It can be concluded that regulation of gene expression can have a critical role in the pathology of Low-grade serous ovarian cancer.

Developing a Prognostic Gene Panel of Epithelial Ovarian Cancer Patients by a Machine Learning Model

Epithelial ovarian cancer patients usually relapse after primary management. We utilized the support vector machine algorithm to develop a model for the chemo-response using the Cancer Cell Line Encyclopedia (CCLE) and validated the model in The Cancer Genome Atlas (TCGA) and the GSE9891 dataset. Finally, we evaluated the feasibility of the model using ovarian cancer patients from our institute. The 10-gene predictive model demonstrated that the high response group had a longer recurrence-free survival (RFS) (log-rank test, p = 0.015 for TCGA, p = 0.013 for GSE9891 and p = 0.039 for NTUH) and overall survival (OS) (log-rank test, p = 0.002 for TCGA and p = 0.016 for NTUH). In a multivariate Cox hazard regression model, the predictive model (HR: 0.644, 95% CI: 0.436⁻0.952, p = 0.027) and residual tumor size < 1 cm (HR: 0.312, 95% CI: 0.170⁻0.573, p < 0.001) were significant factors for recurrence. The predictive model (HR: 0.511, 95% CI: 0.334⁻0.783, p = 0.002) and residual tumor size < 1 cm (HR: 0.252, 95% CI: 0.128⁻0.496, p < 0.001) were still significant factors for death. In conclusion, the patients of high response group stratified by the model had good response and favourable prognosis, whereas for the patients of medium to low response groups, introduction of other drugs or clinical trials might be beneficial.

Platelet protein biomarker panel for ovarian cancer diagnosis

BACKGROUND

Platelets support cancer growth and spread making platelet proteins candidates in the search for biomarkers.

METHODS

Two-dimensional (2D) gel electrophoresis, Partial Least Squares Discriminant Analysis (PLS-DA), Western blot, DigiWest.

RESULTS

PLS-DA of platelet protein expression in 2D gels suggested differences between the International Federation of Gynaecology and Obstetrics (FIGO) stages III-IV of ovarian cancer, compared to benign adnexal lesions with a sensitivity of 96% and a specificity of 88%. A PLS-DA-based model correctly predicted 7 out of 8 cases of FIGO stages I-II of ovarian cancer after verification by western blot. Receiver-operator curve (ROC) analysis indicated a sensitivity of 83% and specificity of 76% at cut-off >0.5 (area under the curve (AUC) = 0.831, p < 0.0001) for detecting these cases. Validation on an independent set of samples by DigiWest with PLS-DA differentiated benign adnexal lesions and ovarian cancer, FIGO stages III-IV, with a sensitivity of 70% and a specificity of 83%.

CONCLUSION

We identified a group of platelet protein biomarker candidates that can quantify the differential expression between ovarian cancer cases as compared to benign adnexal lesions.

Identification of cisplatin-resistance associated genes through proteomic analysis of human ovarian cancer cells and a cisplatin-resistant subline

Chemoresistance to cancer therapy is a major obstacle to the effective treatment of human cancers with cisplatin (DDP), but the mechanisms of cisplatin-resistance are not clear. In this study, we established a cisplatin- resistant human ovarian cancer cell line (COC1/DDP) and identified differentially expressed proteins related to cisplatin resistance. The proteomic expression profiles in COC1 before and after DDP treatment were examined using 2-dimensional electrophoresis technology. Differentially expressed proteins were identified using matrix- assisted laser desorption/ ionization time-of-flight mass spectrometry (MALDI-TOF-MS) and high performance liquid chromatography-electrospray tandem MS (NanoUPLC-ESI-MS/MS). 5 protein spots, for cytokeratin 9, keratin 1, deoxyuridine triphosphatase (dUTPase), aarF domain containing kinase 4 (ADCK 4) and cofilin1, were identified to be significantly changed in COC1/DDP compared with its parental cells. The expression of these five proteins was further validated by quantitative PCR and Western blotting, confirming the results of proteomic analysis. Further research on these proteins may help to identify novel resistant biomarkers or reveal the mechanism of cisplatin-resistance in human ovarian cancers.

Proteomic Analysis of Matched Formalin-Fixed, Paraffin-Embedded Specimens in Patients with Advanced Serous Ovarian Carcinoma

OBJECTIVE

The biology of high grade serous ovarian carcinoma (HGSOC) is poorly understood. Little has been reported on intratumoral homogeneity or heterogeneity of primary HGSOC tumors and their metastases. We evaluated the global protein expression profiles of paired primary and metastatic HGSOC from formalin-fixed, paraffin-embedded (FFPE) tissue samples.

METHODS

After IRB approval, six patients with advanced HGSOC were identified with tumor in both ovaries at initial surgery. Laser capture microdissection (LCM) was used to extract tumor for protein digestion. Peptides were extracted and analyzed by reversed-phase liquid chromatography coupled to a linear ion trap mass spectrometer. Tandem mass spectra were searched against the UniProt human protein database. Differences in protein abundance between samples were assessed and analyzed by Ingenuity Pathway Analysis software. Immunohistochemistry (IHC) for select proteins from the original and an additional validation set of five patients was performed.

RESULTS

Unsupervised clustering of the abundance profiles placed the paired specimens adjacent to each other. IHC H-score analysis of the validation set revealed a strong correlation between paired samples for all proteins. For the similarly expressed proteins, the estimated correlation coefficients in two of three experimental samples and all validation samples were statistically significant (p < 0.05). The estimated correlation coefficients in the experimental sample proteins classified as differentially expressed were not statistically significant.

CONCLUSION

A global proteomic screen of primary HGSOC tumors and their metastatic lesions identifies tumoral homogeneity and heterogeneity and provides preliminary insight into these protein profiles and the cellular pathways they constitute.