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Proteomics Based Characterization of...

Rasam, Sailee Suryakant,

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Proteomics Based Characterization of Cancer and Cardiovascular Disease Models & Advancement of MHC-Peptidome Identification Strategies for High Fidelity Discovery /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Proteomics Based Characterization of Cancer and Cardiovascular Disease Models & Advancement of MHC-Peptidome Identification Strategies for High Fidelity Discovery // Sailee Suryakant Rasam.
Author:	Rasam, Sailee Suryakant,
Description:	1 electronic resource (139 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 85-12, Section: B.
Contained By:	Dissertations Abstracts International85-12B.
Subject:	Biochemistry. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31299481
ISBN:	9798382832869

Proteomics Based Characterization of Cancer and Cardiovascular Disease Models & Advancement of MHC-Peptidome Identification Strategies for High Fidelity Discovery /
Rasam, Sailee Suryakant,

Proteomics Based Characterization of Cancer and Cardiovascular Disease Models & Advancement of MHC-Peptidome Identification Strategies for High Fidelity Discovery /Sailee Suryakant Rasam. - 1 electronic resource (139 pages)

Source: Dissertations Abstracts International, Volume: 85-12, Section: B.

Quantitative and qualitative proteomics based on liquid chromatography - mass spectrometry (LC-MS) is a powerful tool to study complex biological matrices. LC-MS techniques can be utilized for confident identification of biologically relevant proteins and peptides. While it is a powerful technique, there are many challenges including sensitive identification of low abundance proteins. We have previously showed using the IonStar workflow that optimizing every step of the experimental pipeline can alleviate the challenges associated with sensitive and confident detection of low abundant peptides. In Chapter 2, I describe the application of IonStar to a pancreatic cancer model where a single LC-MS experiment enabled insight into a new combination drug therapy, thereby showing the power of an optimized and robust method development strategy. I was able to identify some key processes (metabolic remodelling, apoptosis, and antigen presentation via MHC-1) responsible for synergistic action of a combination drug treatment over single drug treatment. The data also provided inspiration for method development of MHC immunopeptidomics protocol which is described in Chapter 3. MHC immunopeptidomics has been an up-and-coming field of study in academic settings over the past decade and has recently transitioned to the pharmaceutical industry due to its potential application in identifying antigenic peptides for vaccines and cancer immunotherapy. In Chapter 4, I present application of the next version of IonStar (UHR-IonStar), which utilizes higher resolution, in a swine cardiac model. Along with proteomics, I also optimized the phosphoproteomics pipeline to study phosphorylation events in pathological states. We have applied this pipeline to numerous cancer projects and Chapter 4 describes the application in a cardiac pressure overload model in swine.

English

ISBN: 9798382832869Subjects--Topical Terms:

518028
Biochemistry.
Subjects--Index Terms:

Immunopeptidomics

Proteomics Based Characterization of Cancer and Cardiovascular Disease Models & Advancement of MHC-Peptidome Identification Strategies for High Fidelity Discovery /
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