02477nas a2200325   4500008004100000022001400041245009500055210006900150260005700219300001400276490000700290520142400297653001201721653002001733653001501753653001101768653002001779100002001799700002001819700001701839700002501856700002101881700002001902700002201922700001901944700002501963700002101988700002202009856012002031       2014                        eng d  a0175-759800aProteomics of arsenic stress in the gram-positive organism Exiguobacterium sp PS NCIM 54630 aProteomics of arsenic stress in the grampositive organism Exiguo  a233 SPRING ST, NEW YORK, NY 10013 USAbSPRINGERcAUG  a6761-67730 v983 a<p>The general responses of microorganisms to environmental onslaughts are modulated by altering the gene expression pattern to reduce damage in the cell and produce compensating stress responses. The present study attempts to unravel the response of the Gram-positive Exiguobacterium sp. PS NCIM 5463 in the presence of [As(III)] and arsenate [As(V)] using comparative proteomics via two-dimension gel electrophoresis (2-DE) coupled with identification of proteins using matrix-assisted laser desorption/ionisation (MALDI-TOF/MALDI-TOF/TOF). Out of 926 Coomassie-stained proteins, 45 were differentially expressed (p &lt; 0.05). Considering the resolution and abundance level, 24 spots (peptides) were subjected to MALDI analysis, identified and categorised into several functional categories, viz., nitrogen metabolism, energy and stress regulators, carbohydrate metabolism, protein synthesis components and others. A functional role of each protein is discussed in Exiguobacterium sp. PS 5463 under arsenic stress and validated at their transcript level using a quantitative real-time polymerase chain reaction. Unlike previous reports that unravel the responses toward arsenic stress in Gram-negative organisms, the present study identified new proteins under arsenic stress in a Gram-positive organism, Exiguobacterium sp. PS NCIM 5463, which could elucidate the physiology of organisms under arsenic stress.</p>
10aArsenic10aExiguobacterium10aproteomics10aStress10aTranscriptomics1 aSacheti, Poonam1 aPatil, Rajendra1 aDube, Ankita1 aBhonsle, Hemangi, S.1 aThombre, Dipalee1 aMarathe, Sayali1 aVidhate, Ravindra1 aWagh, Priyanka1 aKulkarni, Mahesh, J.1 aRapole, Srikanth1 aGade, Wasudeo, N.  uhttps://library.ncl.res.in/content/proteomics-arsenic-stress-gram-positive-organism-exiguobacterium-sp-ps-ncim-546302738nas a2200349   4500008004100000022001400041245011300055210006900168260000800237300001400245490000700259520163400266653001201900653001601912653001801928653001801946653001001964653002301974100002201997700001602019700002002035700002902055700002502084700001802109700002002127700001802147700002902165700002202194700002002216700002102236856013102257       2016                        eng d  a1615-985300aUrinary proteome alterations in HER2 enriched breast cancer revealed by multipronged quantitative proteomics0 aUrinary proteome alterations in HER2 enriched breast cancer reve  cSEP  a2403-24180 v163 a<p>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 alpha 1-antitrypsin could be a panel of candidate markers that could discriminate HE breast cancer from healthy controls.</p>10a2D-DIGE10aBiomedicine10aBreast cancer10aHER2 enriched10aSWATH10aUrinary biomarkers1 aGajbhiye, Akshada1 aDabhi, Raju1 aTaunk, Khushman1 aVannuruswamy, Garikapati1 aRoyChoudhury, Sourav1 aAdhav, Ragini1 aSeal, Shubhendu1 aMane, Anupama1 aBayatigeri, Santhakumari1 aSantra, Manas, K.1 aChaudhury, Koel1 aRapole, Srikanth  uhttps://library.ncl.res.in/content/urinary-proteome-alterations-her2-enriched-breast-cancer-revealed-multipronged-quantitative03488nas a2200241   4500008004100000245011200041210006900153260000800222300000900230490000800239520264200247100002202889700001602911700002002927700003902947700002502986700001803011700002903029700002003058700002203078700002103100856012503121       2017                        eng d00aMultipronged quantitative proteomics reveals serum proteome alterations in breast cancer intrinsic subtypes0 aMultipronged quantitative proteomics reveals serum proteome alte  cJUN  a1-130 v1633 aBeing 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. (C) 2017 Elsevier B.V. All rights reserved.1 aGajbhiye, Akshada1 aDabhi, Raju1 aTaunk, Khushman1 aJagadeeshaprasad, Mashanipalya, G.1 aRoyChoudhury, Sourav1 aMane, Anupama1 aBayatigeri, Santhakumari1 aChaudhury, Koel1 aSantra, Manas, K.1 aRapole, Srikanth  uhttps://library.ncl.res.in/content/multipronged-quantitative-proteomics-reveals-serum-proteome-alterations-breast-cancer