Integrative Omic Profiling Reveals Unique Hypoxia Induced Signatures in Gastric Cancer Associated Myofibroblasts

Although hypoxia is known to contribute to several aspects of tumour progression, relatively little is known about the effects of hypoxia on cancer-associated myofibroblasts (CAMs), or the consequences that conditional changes in CAM function may have on tumour development and metastasis. To investigate this issue in the context of gastric cancer, a comparative multiomic analysis was performed on populations of patient-derived myofibroblasts, cultured under normoxic or hypoxic conditions. Data from this study reveal a novel set of CAM-specific hypoxia-induced changes in gene expression and secreted proteins. Significantly, these signatures are not observed in either patient matched adjacent tissue myofibroblasts (ATMs) or non-cancer associated normal tissue myofibroblasts (NTMs). Functional characterisation of different myofibroblast populations shows that hypoxia-induced changes in gene expression not only enhance the ability of CAMs to induce cancer cell migration, but also confer pro-tumorigenic (CAM-like) properties in NTMs. This study provides the first global mechanistic insight into the molecular changes that contribute to hypoxia-induced pro-tumorigenic changes in gastric stromal myofibroblasts

Analysis of intrinsic peptide detectability via integrated label-free and SRM-based absolute quantitative proteomics

Quantitative mass spectrometry-based proteomics of complex biological samples remains challenging in part due to the variability and charge competition arising during electrospray ionization (ESI) of peptides and the subsequent transfer and detection of ions. These issues preclude direct quantification from signal intensity alone in the absence of a standard. A deeper understanding of the governing principles of peptide ionization and exploitation of the inherent ionization and detection parameters of individual peptides is thus of great value. Here, using the yeast proteome as a model system, we establish the concept of peptide F-factor as a measure of detectability, closely related to ionization efficiency. F-factor is calculated by normalizing peptide precursor ion intensity by absolute abundance of the parent protein. We investigated F-factor characteristics in different shotgun proteomics experiments, including across multiple ESI-based LC–MS platforms. We show that F-factors mirror previously observed physicochemical predictors as peptide detectability but demonstrate a nonlinear relationship between hydrophobicity and peptide detectability. Similarly, we use F-factors to show how peptide ion coelution adversely affects detectability and ionization. We suggest that F-factors have great utility for understanding peptide detectability and gas-phase ion chemistry in complex peptide mixtures, selection of surrogate peptides in targeted MS studies, and for calibration of peptide ion signal in label-free workflows. Data are available via ProteomeXchange with identifier PXD003472

A quantitative and temporal map of proteostasis during heat shock in Saccharomyces cerevisiae

Temporal changes in the yeast proteome under heat stress are mapped and integrated to protein networks to reveal cognate groups of chaperones (orange and blue circles) acting on coherent groups of substrate proteins (red and green).</p

Analysis of Intrinsic Peptide Detectability via Integrated Label-Free and SRM-Based Absolute Quantitative Proteomics

Quantitative mass spectrometry-based proteomics of complex biological samples remains challenging in part due to the variability and charge competition arising during electrospray ionization (ESI) of peptides and the subsequent transfer and detection of ions. These issues preclude direct quantification from signal intensity alone in the absence of a standard. A deeper understanding of the governing principles of peptide ionization and exploitation of the inherent ionization and detection parameters of individual peptides is thus of great value. Here, using the yeast proteome as a model system, we establish the concept of peptide F-factor as a measure of detectability, closely related to ionization efficiency. F-factor is calculated by normalizing peptide precursor ion intensity by absolute abundance of the parent protein. We investigated F-factor characteristics in different shotgun proteomics experiments, including across multiple ESI-based LC–MS platforms. We show that F-factors mirror previously observed physicochemical predictors as peptide detectability but demonstrate a nonlinear relationship between hydrophobicity and peptide detectability. Similarly, we use F-factors to show how peptide ion coelution adversely affects detectability and ionization. We suggest that F-factors have great utility for understanding peptide detectability and gas-phase ion chemistry in complex peptide mixtures, selection of surrogate peptides in targeted MS studies, and for calibration of peptide ion signal in label-free workflows. Data are available via ProteomeXchange with identifier PXD003472