Therapeutic implications of cancer stem cells in prostate cancer.

Prostate cancer, one of the most frequently occurring cancers in men, is a heterogeneous disease involving multiple cell types within tumors. This tumor heterogeneity at least partly results from genomic instability leading to sub-clonal cellular differentiation. The differentiated cell populations originate from a small subset of cells with tumor-initiating and stem-like properties. These cells, termed prostate cancer stem cells (PCSCs), play crucial roles in disease progression, drug resistance, and relapse. This review discusses the origin, hierarchy, and plasticity of PCSCs; methods for isolation and enrichment of PCSCs; and various cellular and metabolic signaling pathways involved in PCSC induction and maintenance, as well as therapeutic targeting.

Mining proteomics data to extract post-translational modifications associated with gastric cancer.

Gastric cancers are highly heterogeneous, deep-seated tumours associated with late diagnosis and poor prognosis. Post-translational modifications (PTMs) of proteins are known to be well-associated with oncogenesis and metastasis in most cancers. Several enzymes which drive PTMs have also been used as theranostics in cancers of the breast, ovary, prostate and bladder. However, there is limited data on PTMs in gastric cancers. Considering that experimental protocols for simultaneous analysis of multiple PTMs are being explored, a data-driven approach involving reanalysis of mass spectrometry-derived data is useful in cataloguing altered PTMs. We subjected publicly available mass spectrometry data on gastric cancer to an iterative searching strategy for fetching PTMs including phosphorylation, acetylation, citrullination, methylation and crotonylation. These PTMs were catalogued and further analyzed for their functional enrichment through motif analysis. This value-added approach delivered identification of 21,710 unique modification sites on 16,364 modified peptides. Interestingly, we observed 278 peptides corresponding to 184 proteins to be differentially abundant. Using bioinformatics approaches, we observed that majority of these altered PTMs/proteins belonged to cytoskeletal and extracellular matrix proteins, which are known to be perturbed in gastric cancer. The dataset derived by this mutiPTM investigation can provide leads to further investigate the potential role of altered PTMs in gastric cancer management.

Unveiling the arcanum of formalin-fixed paraffin-embedded archival tissue blocks: A valuable resource for genomic DNA extraction.

Background: Formalin-fixed paraffin-embedded (FFPE) tissue blocks are routinely preserved after pathological diagnosis and possess tremendous potential for biomarker discovery. These archival samples are prone to degradation on prolonged storage due to the formalin cross-linking. Aims: This study aimed to evaluate whether the storage period of the formalin-fixed paraffin-embedded tumor blocks had a significant impact on the yield and purity of the isolated DNA archived for 11 years. Settings and Design: A retrospective study was carried out in the Department of Oral Pathology and Microbiology in accordance with the Institutional Ethics Committee. Materials and Methods: Genomic DNA extraction was performed using TaKaRa DEXPAT Easy DNA kit from 40 FFPE tissue blocks of oral squamous cell carcinoma archived for 11 years (2006-2017). NanoDrop spectrophotometer was used to determine the DNA yield (A260) and purity (A260/A280 ratio). The quality of DNA fragments was validated using agarose gel electrophoresis. Statistical Analysis Used: Statistical analysis was obtained by SPSS 22, MS Excel and analyzed using the analysis of variance (ANOVA) test. P < 0.05 was set for statistical significance. Results: There was no statistically significant difference observed both in terms of DNA yield (P = 0.996) and purity (P = 0.997) of FFPE tumor blocks archived for 11 years among the study groups. Conclusions: It was concluded that, irrespective of years of storage of the FFPE, it is possible to extract genomic DNA and use it for molecular studies.

Omics Data Mining for multiPTMs in Oral Cancer: Cellular Proteome and Secretome of Chronic Tobacco-Treated Oral Keratinocytes.

Oral cancer is common worldwide but lacks robust diagnostics and therapeutics. Lifestyle factors, such as tobacco chewing and smoking, are significantly associated with oral cancers. Mapping the changes in the global proteome, secretome and post-translational modifications (PTMs) during tobacco exposure of oral keratinocytes hold great potential for understanding the mechanisms of oral carcinogenesis, not to mention for innovation toward clinical interventions in the future. On the other hand, although advances in mass spectrometry (MS)-based techniques have enabled the deep mining of complex proteomes, a large portion of the mass spectrometric data remains unassigned. These unassigned spectral data can be researched for multiple post-translational modifications (multiPTMs). Using data mining of publicly available proteomics data, we report, in this study, a multiPTM analysis of high-resolution MS-derived datasets on cellular proteome and secretome of chronic tobacco-treated oral keratinocytes. We identified 800 PTM sites in 496 proteins. Among them, 43 PTM sites in 37 proteins were found to be differentially expressed, accounting for their protein-level expression. Enrichment analysis of the proteins with altered phosphosite expression and the known kinases of these phosphosites discovered the overrepresentation of certain biological processes such as splicing and hemidesmosome assembly. These findings contribute to a deeper understanding of omics level changes in chronic tobacco-treated oral keratinocytes, and by extension, pathophysiology of oral cancers.

Molecular alterations in oral cancer between tobacco chewers and smokers using serum proteomics.

BACKGROUND: Tobacco exposure (through smoking or chewing) is one of the predominant risk factors associated with the development of oral squamous cell carcinoma (OSCC). Despite the growing number of patients diagnosed with OSCC, there are few circulating biomarkers for identifying individuals at a higher risk of developing the disease. Successful identification of candidate molecular markers for risk assessment could aid in the early detection of oral lesions and potentially be used for community screening of high-risk populations. OBJECTIVE: Identification of differentially expressed proteins in the serum of oral cancer patients which can serve as biomarkers for the diagnosis of the onset of oral cancer among tobacco users. METHODS: We employed a tandem mass tag (TMT)-based quantitative proteomics approach to study alterations in the serum proteomes of OSCC patients based on their tobacco exposure habits (chewing and smoking) compared to healthy individuals with no history of using any form of tobacco or any symptoms of the disease. RESULTS: Mass spectrometry-based analysis resulted in the identification of distinct signatures in the serum of OSCC patients who either chewed or smoked tobacco. Pathway analysis revealed opposing effects of dysregulated proteins enriched in the complement-coagulation signaling cascades with a high expression of the Serpin family of proteins observed in OSCC patients who chewed tobacco compared to healthy individuals whereas these proteins showed decreased levels in OSCC patients who smoked. ELISA-based validation further confirmed our findings revealing higher expression of SERPINA6 and SERPINF1 across serum of OSCC patients who chewed tobacco compared to healthy individuals. CONCLUSIONS: This study serves as a benchmark for the identification of serum-based protein markers that may aid in the identification of high-risk patients who either chew tobacco or smoke tobacco.

Molecular alterations in oral cancer using high-throughput proteomic analysis of formalin-fixed paraffin-embedded tissue.

Loss of cell differentiation is a hallmark for the progression of oral squamous cell carcinoma (OSCC). Archival Formalin-Fixed Paraffin-Embedded (FFPE) tissues constitute a valuable resource for studying the differentiation of OSCC and can offer valuable insights into the process of tumor progression. In the current study, we performed LC-MS/MS-based quantitative proteomics of FFPE specimens from pathologically-confirmed well-differentiated, moderately-differentiated, and poorly-differentiated OSCC cases. The data were analyzed in four technical replicates, resulting in the identification of 2376 proteins. Of these, 141 and 109 were differentially expressed in moderately-differentiated and poorly differentiated OSCC cases, respectively, compared to well-differentiated OSCC. The data revealed significant metabolic reprogramming with respect to lipid metabolism and glycolysis with proteins belonging to both these processes downregulated in moderately-differentiated OSCC when compared to well-differentiated OSCC. Signaling pathway analysis indicated the alteration of extracellular matrix organization, muscle contraction, and glucose metabolism pathways across tumor grades. The extracellular matrix organization pathway was upregulated in moderately-differentiated OSCC and downregulated in poorly differentiated OSCC, compared to well-differentiated OSCC. PADI4, an epigenetic enzyme transcriptional regulator, and its transcriptional target HIST1H1B were both found to be upregulated in moderately differentiated and poorly differentiated OSCC, indicating epigenetic events underlying tumor differentiation. In conclusion, the findings support the advantage of using high-resolution mass spectrometry-based FFPE archival blocks for clinical and translational research. The candidate signaling pathways identified in the study could be used to develop potential therapeutic targets for OSCC.

CusVarDB: A tool for building customized sample-specific variant protein database from next-generation sequencing datasets.

Cancer genome sequencing studies have revealed a number of variants in coding regions of several genes. Some of these coding variants play an important role in activating specific pathways that drive proliferation. Coding variants present on cancer cell surfaces by the major histocompatibility complex serve as neo-antigens and result in immune activation. The success of immune therapy in patients is attributed to neo-antigen load on cancer cell surfaces. However, which coding variants are expressed at the protein level can't be predicted based on genomic data. Complementing genomic data with proteomic data can potentially reveal coding variants that are expressed at the protein level. However, identification of variant peptides using mass spectrometry data is still a challenging task due to the lack of an appropriate tool that integrates genomic and proteomic data analysis pipelines. To overcome this problem, and for the ease of the biologists, we have developed a graphical user interface (GUI)-based tool called CusVarDB. We integrated variant calling pipeline to generate sample-specific variant protein database from next-generation sequencing datasets. We validated the tool with triple negative breast cancer cell line datasets and identified 423, 408, 386 and 361 variant peptides from BT474, MDMAB157, MFM223 and HCC38 datasets, respectively.

The Proteomic Landscape of Resting and Activated CD4+ T Cells Reveal Insights into Cell Differentiation and Function.

CD4+ T cells (T helper cells) are cytokine-producing adaptive immune cells that activate or regulate the responses of various immune cells. The activation and functional status of CD4+ T cells is important for adequate responses to pathogen infections but has also been associated with auto-immune disorders and survival in several cancers. In the current study, we carried out a label-free high-resolution FTMS-based proteomic profiling of resting and T cell receptor-activated (72 h) primary human CD4+ T cells from peripheral blood of healthy donors as well as SUP-T1 cells. We identified 5237 proteins, of which significant alterations in the levels of 1119 proteins were observed between resting and activated CD4+ T cells. In addition to identifying several known T-cell activation-related processes altered expression of several stimulatory/inhibitory immune checkpoint markers between resting and activated CD4+ T cells were observed. Network analysis further revealed several known and novel regulatory hubs of CD4+ T cell activation, including IFNG, IRF1, FOXP3, AURKA, and RIOK2. Comparison of primary CD4+ T cell proteomic profiles with human lymphoblastic cell lines revealed a substantial overlap, while comparison with mouse CD+ T cell data suggested interspecies proteomic differences. The current dataset will serve as a valuable resource to the scientific community to compare and analyze the CD4+ proteome.

Proteomic Analysis of the Human Anterior Pituitary Gland.

The pituitary function is regulated by a complex system involving the hypothalamus and biological networks within the pituitary. Although the hormones secreted from the pituitary have been well studied, comprehensive analyses of the pituitary proteome are limited. Pituitary proteomics is a field of postgenomic research that is crucial to understand human health and pituitary diseases. In this context, we report here a systematic proteomic profiling of human anterior pituitary gland (adenohypophysis) using high-resolution Fourier transform mass spectrometry. A total of 2164 proteins were identified in this study, of which 105 proteins were identified for the first time compared with high-throughput proteomic-based studies from human pituitary glands. In addition, we identified 480 proteins with secretory potential and 187 N-terminally acetylated proteins. These are the first region-specific data that could serve as a vital resource for further investigations on the physiological role of the human anterior pituitary glands and the proteins secreted by them. We anticipate that the identification of previously unknown proteins in the present study will accelerate biomedical research to decipher their role in functioning of the human anterior pituitary gland and associated human diseases.

Clinicopathological analysis of oral squamous cell carcinoma among the younger age group in coastal Karnataka, India: A retrospective study.

AIMS: Oral squamous cell carcinoma (OSCC) primarily occurs in older age group. However, in the recent years, incidence of oral cancer in young people has been on rise worldwide. Towards this end, we sought to analyze the clinical and histopathological characteristics of OSCC in patients less than 45 years of age. MATERIALS AND METHODS: The clinical and histological features of patients diagnosed with squamous cell carcinoma of the oral cavity at two hospitals in the coastal Karnataka region of South India between 1996-2012 were reviewed. The tabulation and descriptive statistics of the study were carried out. RESULTS: A total of 420 patients were treated for OSCC in the 17-year period (1996-2012), of which 86 (20.5 %) patients were under 45 years of age. The most common site of involvement among the young was tongue (29.07%) and buccal mucosa (27.9%) respectively. A total of 47 (54.65%) patients were either habitual chewers, smokers, or alcoholics. Pathological grading of cases classified tumors into well differentiated (34.88%), moderately differentiated (46.51%) and poorly differentiated (4.65%). CONCLUSIONS: The data from this study reveals that a significant proportion of the OSCC cases are observed in patients of 45 years or younger. Additionally, our study also indicated an increase in the usage of tobacco and pan chewing in young adults in comparison to older individuals in the two hospitals of South India. The data obtained from this analysis emphasizes the need for screening programs that are tailor-made for individuals at high risk of developing oral cancer and warrants tobacco awareness programs in the community.