A single step and rapid protein extraction protocol developed for cell lines and tissues: Compatible for gel based and gel free proteomic approaches.

Proteins are crucial research molecules in modern biology. Almost every biological research area needs protein-based assays to answer the research questions. The study of the total protein content of a biological sample known as Proteomics, is one of the highly rated qualitative and quantitative approach to address numerous biological problems including clinical research. The key step to successfully generate high quality proteomics data is the efficient extraction of proteins from biological samples. Although different methods are in use for protein extraction from a wide variety of samples, however, because of their prolonged protocol and multiple steps involved, final protein yield is sacrificed. Here, we have shown the development of a simple single step method for extraction of proteins from mammalian cell lines as well as tissue samples in an effective and reproducible manner. This method is based on lysis of samples directly in a modified lysis buffer without CHAPS (7 M Urea, 2 M Thiourea, and 10 mM Tris-Cl; pH 8.5) that is compatible with gel based and gel free approaches. This developed protocol is reliable and should be useful for a wide range of proteomic studies involving various biological samples.

Urinary proteome alterations in HER2 enriched breast cancer revealed by multipronged quantitative proteomics.

Globally, breast cancer is the second most common cancer among women. Although biomarker discoveries through various proteomic approaches of tissue and serum samples have been studied in breast cancer, urinary proteome alterations in breast cancer are least studied. Urine being a noninvasive biofluid and a significant source of proteins, it has the potential in early diagnosis of breast cancer. This study used complementary quantitative gel-based and gel-free proteomic approaches to find a panel of urinary protein markers that could discriminate HER2 enriched (HE) subtype breast cancer from the healthy controls. A total of 183 differentially expressed proteins were identified using three complementary approaches, namely 2D-DIGE, iTRAQ, and sequential window acquisition of all theoretical mass spectra. The differentially expressed proteins were subjected to various bioinformatics analyses for deciphering the biological context of these proteins using protein analysis through evolutionary relationships, database for annotation, visualization and integrated discovery, and STRING. Multivariate statistical analysis was undertaken to identify the set of most significant proteins, which could discriminate HE breast cancer from healthy controls. Immunoblotting and MRM-based validation in a separate cohort testified a panel of 21 proteins such as zinc-alpha2-glycoprotein, A2GL, retinol-binding protein 4, annexin A1, SAP3, SRC8, gelsolin, kininogen 1, CO9, clusterin, ceruloplasmin, and α1-antitrypsin could be a panel of candidate markers that could discriminate HE breast cancer from healthy controls.

Multipronged quantitative proteomics reveals serum proteome alterations in breast cancer intrinsic subtypes.

Being molecularly heterogeneous, breast cancer tends to be a complicated oncological disease with high incidence rates throughout the world. The primary aim of this study was to identify the set of serum proteins with discriminatory capabilities towards the four major subtypes of breast cancer. We employed multipronged quantitative proteomic approaches like 2D-DIGE, iTRAQ and SWATH-MS and identified 307 differentially regulated proteins. Luminal A subtype consisted of 24, Luminal B subtype 38, HER2 Enriched subtype 17 and Triple negative breast cancer subtype 10 differentially regulated subtype specific proteins. These specific proteins were further subjected to bioinformatic tools which revealed the involvement in platelet degranulation, fibrinolysis, lipid metabolism, immune response, complement activation, blood coagulation, glycolysis and cancer signaling pathways in the subtypes of the breast cancer. The significant discrimination efficiency of the models generated through multivariate statistical analysis was decent to distinguish each of the four subtypes from controls. Further, some of the statistically significant differentially regulated proteins were verified and validated by immunoblotting and mass spectrometry based selected reaction monitoring (SRM) approach. Our Multipronged proteomics approaches revealed panel of serum proteins specifically altered for individual subtypes of breast cancer. The mass spectrometry data are available via ProteomeXchange with identifier PXD006441. BIOLOGICAL SIGNIFICANCE: Worldwide, breast cancer continues to be one of the leading causes of cancer related deaths in women and it encompasses four major molecular subtypes. As breast cancer treatment majorly depends on identification of specific subtype, it is important to diagnosis the disease at subtype level. Our results using multipronged quantitative proteomics identified 307 differentially regulated proteins in which 24 were specific for Luminal A, 38 for Luminal B, 17 for HER2 enriched and 10 proteins were specific for TN subtype. Bioinformatic analysis of these proteins revealed certain biological processes and pathways altered at subtype level and validation experiments of some of these proteins using immunoblotting and SRM assays are consistent with discovery data. This is the first comprehensive proteomic study on serum proteome alterations at subtype level which will not only help to distinguish subtype of breast cancer but also contribute to a better understanding of the molecular characteristic of breast cancer at individual subtype level.