Identification of 14-3-3zeta associated protein networks in oral cancer.

Advancements in genomics, proteomics, and bioinformatics have improved our understanding of gene/protein networks involved in intra- and intercellular communication and tumor-host interactions. Using proteomics integrated with bioinformatics, previously we reported overexpression of 14-3-3ζ in premalignant oral lesions and oral squamous cell carcinoma tissues in comparison with normal oral epithelium. 14-3-3ζ emerged as a novel molecular target for therapeutics and a potential prognostic marker in oral squamous cell carcinoma patients. However, the role of 14-3-3ζ in development and progression of oral cancer is not known yet. This study aimed to identify the 14-3-3ζ associated protein networks in oral cancer cell lines using IP-MS/MS and bioinformatics. A total of 287 binding partners of 14-3-3ζ were identified in metastatic (MDA1986) and nonmetastatic (SCC4) oral cancer cell lines including other 14-3-3 isoforms (2%), proteins involved in apoptosis (2%), cytoskeleton (9%), metabolism (16%), and maintenance of redox potential (2%). Our bioinformatics analysis revealed involvement of 14-3-3ζ in protein networks regulating cell cycle, proliferation, apoptosis, cellular trafficking, and endocytosis in oral cancer. In conclusion, our data revealed several novel protein interaction networks involving 14-3-3ζ in oral cancer progression and metastasis.

Nuclear heterogeneous nuclear ribonucleoprotein D is associated with poor prognosis and interactome analysis reveals its novel binding partners in oral cancer.

BACKGROUND: Post-transcriptional regulation by heterogeneous ribonucleoproteins (hnRNPs) is an important regulatory paradigm in cancer development. Our proteomic analysis revealed hnRNPD overexpression in oral dysplasia as compared with normal mucosa; its role in oral carcinogenesis remains unknown. Here in we determined the hnRNPD associated protein networks and its clinical significance in oral squamous cell carcinoma (OSCC). METHODS: Immunoprecipitation (IP) followed by tandem mass spectrometry was used to identify the binding partners of hnRNPD in oral cancer cell lines. Ingenuity pathway analysis (IPA) was carried out to unravel the protein interaction networks associated with hnRNPD and key interactions were confirmed by co-IP-western blotting. hnRNPD expression was analyzed in 183 OSCCs, 44 oral dysplasia and 106 normal tissues using immunohistochemistry (IHC) and correlated with clinico-pathological parameters and follow up data over a period of 91 months. Kaplan-Meier survival and Cox-multivariate-regression analyses were used to evaluate the prognostic significance of hnRNPD in OSCC. RESULTS: We identified 345 binding partners of hnRNPD in oral cancer cells. IPA unraveled novel protein-protein interaction networks associated with hnRNPD and suggested its involvement in multiple cellular processes: DNA repair, replication, chromatin remodeling, cellular proliferation, RNA splicing and stability, thereby directing the fate of oral cancer cells. Protein-protein interactions of hnRNPD with 14-3-3ζ, hnRNPK and S100A9 were confirmed using co-IP-western blotting. IHC analysis showed significant overexpression of nuclear hnRNPD in oral dysplasia [p = 0.001, Odds ratio (OR) = 5.1, 95% CI = 2.1-11.1) and OSCCs (p = 0.001, OR = 8.1, 95% CI = 4.5-14.4) in comparison with normal mucosa. OSCC patients showing nuclear hnRNPD overexpression had significantly reduced recurrence free survival [p = 0.026, Hazard ratio = 1.95, 95% CI = 1.0-3.5] by Kaplan-Meier survival and Cox-multivariate-regression analyses and has potential to define a high-risk subgroup among OSCC patients with nodal negative disease. CONCLUSIONS: Our findings suggest novel functions of hnRNPD in cellular proliferation and survival, besides RNA splicing and stability in oral cancer. Association of nuclear hnRNPD with poor prognosis in OSCC patients taken together with its associated protein networks in oral cancer warrant future studies designed to explore its potential as a plausible novel target for molecular therapeutics.

Alpha-enolase is a potential prognostic marker in clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is an aggressive disease with unpredictable behaviour. Clinical parameters are not always accurate for prognosis prediction. The integration of molecular markers to prognostic models can significantly improve prognostic assessment and consequently patient management. We assessed the expression of alpha-enolase (ENO1) protein by immunohistochemistry in 360 patients with primary ccRCC and correlated its expression with multiple clinicopathological parameters including stage, grade, tumor size, disease-free and overall survival. Cox proportional hazard regression models adjusted for clinicopathological factors were used to test for a link between ENO1 expression and both disease-free and overall survival. We correlated ENO1 mRNA expression with overall survival in an independent set of 428 ccRCC cases from The Cancer Genome Atlas. ENO1 showed cytoplasmic, membranous and nuclear staining patterns. There is a statistically significant negative correlation between ENO1 expression, tumor stage, and grade. ENO1 expression also shows a statistically significant direct correlation with disease-free survival (p = 0.011) and overall survival (p = 0.030) in ccRCC. Patients with higher ENO1 expression had lower hazard ratio of recurrence, although this was not statistically significant (HR = 0.330, p = 0.060). These findings were validated at the mRNA level in an independent set of 428 ccRCC cases which also showed that low ENO1 expression is associated with significantly shorter overall survival. Down-regulation of ENO1 can be a predictor of poor prognosis in ccRCC, and it can be a potential prognostic marker.

Lactate dehydrogenase A is a potential prognostic marker in clear cell renal cell carcinoma.

BACKGROUND: Over 90% of cancer-related deaths in clear cell renal cell carcinoma (RCC) are caused by tumor relapse and metastasis. Thus, there is an urgent need for new molecular markers that can potentiate the efficacy of the current clinical-based models of prognosis assessment. The objective of this study is to evaluate the potential significance of lactate dehydrogenase A (LDHA), assessed by immunohistochemical staining, as a prognostic marker in clear cell renal cell carcinoma in relation to clinicopathological features and clinical outcome. METHODS: We assessed the expression of LDHA at the protein level, by immunohistochemistry, and correlated its expression with multiple clinicopathological features including tumor size, clinical stage, histological grade, disease-free and overall survival in 385 patients with primary clear cell renal cell carcinoma. We also correlated the LDHA expression with overall survival, at mRNA level, in an independent data set of 170 clear cell renal cell carcinoma cases from The Cancer Genome Atlas databases. Cox proportional hazards models adjusted for the potential clinicopathological factors were used to test for associations between the LDHA expression and both disease-free survival and overall survival. RESULTS: There is statistically significant positive correlation between LDHA level of expression and tumor size, clinical stage and histological grade. Moreover, LDHA expression shows significantly inverse correlation with both disease-free survival and overall survival in patients with clear cell renal cell carcinoma. Our results are validated by examining LDHA expression, at the mRNA level, in the independent data set of clear cell renal cell carcinoma cases from The Cancer Genome Atlas databases which also shows that higher lactate dehydrogenase A expression is associated with significantly shorter overall survival. CONCLUSION: Our results indicate that LDHA up-regulation can be a predictor of poor prognosis in clear cell renal cell carcinoma. Thus, it represents a potential prognostic biomarker that can boost the accuracy of other prognostic models in patients with clear cell renal cell carcinoma.

Quantitative proteomic analysis reveals potential diagnostic markers and pathways involved in pathogenesis of renal cell carcinoma.

There are no serum biomarkers for the accurate diagnosis of clear cell renal cell carcinoma (ccRCC). Diagnosis and decision of nephrectomy rely on imaging which is not always accurate. Non-invasive diagnostic biomarkers are urgently required. In this study, we preformed quantitative proteomics analysis on a total of 199 patients including 30 matched pairs of normal kidney and ccRCC using isobaric tags for relative and absolute quantitation (iTRAQ) labeling and LC-MS/MS analysis to identify differentially expressed proteins. We found 55 proteins significantly dysregulated in ccRCC compared to normal kidney tissue. 54 were previously reported to play a role in carcinogenesis, and 39 are secreted proteins. Dysregulation of alpha-enolase (ENO1), L-lactate dehydrogenase A chain (LDHA), heat shock protein beta-1 (HSPB1/Hsp27), and 10 kDa heat shock protein, mitochondrial (HSPE1) was confirmed in two independent sets of patients by western blot and immunohistochemistry. Pathway analysis, validated by PCR, showed glucose metabolism is altered in ccRCC compared to normal kidney tissue. In addition, we examined the utility of Hsp27 as biomarker in serum and urine. In ccRCC patients, Hsp27 was elevated in the urine and serum and high serum Hsp27 was associated with high grade (Grade 3-4) tumors. These data together identify potential diagnostic biomarkers for ccRCC and shed new light on the molecular mechanisms that are dysregulated and contribute to the pathogenesis of ccRCC. Hsp27 is a promising diagnostic marker for ccRCC although further large-scale studies are required. Also, molecular profiling may help pave the road to the discovery of new therapies.

Identification and validation of dysregulated metabolic pathways in metastatic renal cell carcinoma.

Metastatic renal cell carcinoma (mRCC) is a devastating disease with a 5-year survival rate of approximately 9 % and low response to chemotherapy and radiotherapy. Targeted therapies have slightly improved patient survival, but are only effective in a small subset of patients, who eventually develop resistance. A better understanding of pathways contributing to tumor progression and metastasis will allow for the development of novel targeted therapies and accurate prognostic markers. We performed extensive bioinformatics coupled with experimental validation on proteins dysregulated in mRCC. Gene ontology analysis showed that many proteins are involved in oxidation reduction, metabolic processes, and signal transduction. Pathway analysis showed metabolic pathways are altered in mRCC including glycolysis and pyruvate metabolism, the citric acid cycle, and the pentose phosphate pathway. RT-qPCR analysis showed that genes involved in the citric acid cycle were downregulated in metastatic RCC while genes of the pentose phosphate pathway were overexpressed. Protein-protein interaction analysis showed that most of the 198 proteins altered in mRCC clustered together and many were involved in glycolysis and pyruvate metabolism. We identified 29 reported regions of chromosomal aberrations in metastatic disease that correlate with the direction of protein dysregulation in mRCC. Furthermore, 36 proteins dysregulated in mRCC are predicted to be targets of metastasis-related miRNAs. A more comprehensive understanding of the pathways dysregulated in metastasis can be useful for the development of new therapies and novel prognostic markers. Also, multileveled analyses provide a unique "snapshot" of the molecular "environment" in RCC with prognostic and therapeutic implications.

Quantitative proteomic analysis in metastatic renal cell carcinoma reveals a unique set of proteins with potential prognostic significance.

Metastatic renal cell carcinoma (RCC) is one of the most treatment-resistant malignancies, and patients have a dismal prognosis, with a <10% five-year survival rate. The identification of markers that can predict the potential for metastases will have a great effect in improving patient outcomes. In this study, we used differential proteomics with isobaric tags for relative and absolute quantitation (iTRAQ) labeling and LC-MS/MS analysis to identify proteins that are differentially expressed in metastatic and primary RCC. We identified 1256 non-redundant proteins, and 456 of these were quantified. Further analysis identified 29 proteins that were differentially expressed (12 overexpressed and 17 underexpressed) in metastatic and primary RCC. Dysregulated protein expressions of profilin-1 (Pfn1), 14-3-3 zeta/delta (14-3-3ζ), and galectin-1 (Gal-1) were verified on two independent sets of tissues by means of Western blot and immunohistochemical analysis. Hierarchical clustering analysis showed that the protein expression profile specific for metastatic RCC can distinguish between aggressive and non-aggressive RCC. Pathway analysis showed that dysregulated proteins are involved in cellular processes related to tumor progression and metastasis. Furthermore, preliminary analysis using a small set of tumors showed that increased expression of Pfn1 is associated with poor outcome and is a potential prognostic marker in RCC. In addition, 14-3-3ζ and Gal-1 also showed higher expression in tumors with poor prognosis than in those with good prognosis. Dysregulated proteins in metastatic RCC represent potential prognostic markers for kidney cancer patients, and a greater understanding of their involved biological pathways can serve as the foundation of the development of novel targeted therapies for metastatic RCC.

Identification of proteins secreted by head and neck cancer cell lines using LC-MS/MS: Strategy for discovery of candidate serological biomarkers.

In search of blood-based biomarkers that would enhance the ability to diagnose head and neck/oral squamous cell carcinoma (HNOSCC) in early stages or predict its prognosis, we analyzed the HNOSCC secretome (ensemble of proteins secreted and/or shed from the tumor cells) for potential biomarkers using proteomic technologies. LC-MS/MS was used to identify proteins in the conditioned media of four HNOSCC cell lines (SCC4, HSC2, SCC38, and AMOSIII); 140 unique proteins were identified on the basis of 5% global false discovery rate, 122 of which were secretory proteins, with 29 being previously reported to be overexpressed in HNOSCC in comparison to normal head and neck tissues. Of these, five proteins including α-enolase, peptidyl prolyl isomerase A/cyclophilin A, 14-3-3 ζ, heterogeneous ribonucleoprotein K, and 14-3-3 σ were detected in the sera of HNOSCC patients by Western blot analysis. Our study provides the evidence that analysis of head and neck cancer cells' secretome is a viable strategy for identifying candidate serological biomarkers for HNOSCC. In future, these biomarkers may be useful in predicting the likelihood of transformation of oral pre-malignant lesions, prognosis of HNOSCC patients and evaluate response to therapy using minimally invasive tests.

Identification of differentially regulated secretome components during skeletal myogenesis.

Myogenesis is a well-characterized program of cellular differentiation that is exquisitely sensitive to the extracellular milieu. Systematic characterization of the myogenic secretome (i.e. the ensemble of secreted proteins) is, therefore, warranted for the identification of novel secretome components that regulate both the pluripotency of these progenitor mesenchymal cells, and also their commitment and passage through the differentiation program. Previously, we have successfully identified 26 secreted proteins in the mouse skeletal muscle cell line C2C12 (1). In an effort to attain a more comprehensive picture of the regulation of myogenesis by its extracellular milieu, quantitative profiling employing stable isotope labeling by amino acids in cell culture was implemented in conjunction with two parallel high throughput online reverse phase liquid chromatography-tandem mass spectrometry systems. In summary, 34 secreted proteins were quantified, 30 of which were shown to be differentially expressed during muscle development. Intriguingly, our analysis has revealed several novel up- and down-regulated secretome components that may have critical biological relevance for both the maintenance of pluripotency and the passage of cells through the differentiation program. In particular, the altered regulation of secretome components, including follistatin-like protein-1, osteoglycin, spondin-2, and cytokine-induced apoptosis inhibitor-1, along with constitutively expressed factors, such as fibulin-2, illustrate dynamic changes in the secretome that take place when differentiation to a specific lineage occurs.

Secretome-based identification and characterization of potential biomarkers in thyroid cancer.

In search of thyroid cancer biomarkers, proteins secreted by thyroid cancer cell lines, papillary-derived TPC-1 and anaplastic-derived CAL62, were analyzed using liquid chromatography-tandem mass spectrometry. Of 46 high-confidence identifications, 6 proteins were considered for verification in thyroid cancer patients' tissue and blood. The localization of two proteins, nucleolin and prothymosin-α (PTMA), was confirmed in TPC-1 and CAL62 cells by confocal microscopy and immunohistochemically in xenografts of TPC-1 cells in NOD/SCID/γ mice and human thyroid cancers (48 tissues). Increased nuclear and cytoplasmic expression of PTMA was observed in anaplastic compared to papillary and poorly differentiated carcinomas. Nuclear expression of nucleolin was observed in all subtypes of thyroid carcinomas, along with faint cytoplasmic expression in anaplastic cancers. Importantly, PTMA, nucleolin, clusterin, cysteine-rich angiogenic inducer 61, enolase 1, and biotinidase were detected in thyroid cancer patients' sera, warranting future analysis to confirm their potential as blood-based thyroid cancer markers. In conclusion, we demonstrated the potential of secretome analysis of thyroid cancer cell lines to identify novel proteins that can be independently verified in cell lines, xenografts, tumor tissues, and blood samples of thyroid cancer patients. These observations support their potential utility as minimally invasive biomarkers for thyroid carcinomas and their application in management of these diseases upon future validation.