A Timely Shift from Shotgun to Targeted Proteomics and How It Can Be Groundbreaking for Cancer Research

Abstract

The fact that cancer is a leading cause of death all around the world has naturally sparked major efforts in the pursuit of novel and more efficient biomarkers that could better serve as diagnostic tools, prognostic predictors, or therapeutical targets in the battle against this type of disease. Mass spectrometry-based proteomics has proven itself as a robust and logical alternative to the immuno-based methods that once dominated the field. Nevertheless, intrinsic limitations of classic proteomic approaches such as the natural gap between shotgun discovery-based methods and clinically applicable results have called for the implementation of more direct, hypothesis-based studies such as those made available through targeted approaches, that might be able to streamline biomarker discovery and validation as a means to increase survivability of affected patients. In fact, the paradigm shifting potential of modern targeted proteomics applied to cancer research can be demonstrated by the large number of advancements and increasing examples of new and more useful biomarkers found during the course of this review in different aspects of cancer research. Out of the many studies dedicated to cancer biomarker discovery, we were able to devise some clear trends, such as the fact that breast cancer is the most common type of tumor studied and that most of the research for any given type of cancer is focused on the discovery diagnostic biomarkers, with the exception of those that rely on samples other than plasma and serum, which are generally aimed toward prognostic markers. Interestingly, the most common type of targeted approach is based on stable isotope dilution-selected reaction monitoring protocols for quantification of the target molecules. Overall, this reinforces that notion that targeted proteomics has already started to fulfill its role as a groundbreaking strategy that may enable researchers to catapult the number of viable, effective, and validated biomarkers in cancer clinical practice.

Interleukin 9 alterations linked to alzheimer disease in african americans

“…Finally, we sought to replicate our findings in a separate clinicopathologic cohort of NC, MCI, and AD cases . Proteomic analysis in the Mount Sinai cohort (26 African Americans, 180 Caucasians) did not detect IL‐9 or any of the proteins in its network, consistent with our and others’ experience that only abundant proteins are reproducibly detected using an untargeted approach . Brain transcriptomic analysis on 7 genes previously implicated in the IL‐9 network showed SPI1 (encoding PU.1, p = 0.030) to positively correlate with plaque burden independent of race, consistent with the brain IHC results from Emory for PU.1.…”

“…24 Proteomic analysis in the Mount Sinai cohort (26 African Americans, 180 Caucasians) did not detect IL-9 or any of the proteins in its network, consistent with our and others' experience that only abundant proteins are reproducibly detected using an untargeted approach. 28 Brain transcriptomic analysis on 7 genes previously implicated in the IL-9 network showed SPI1 (encoding PU.1, p = 0.030) to positively correlate with plaque burden independent of race, consistent with the brain IHC results from Emory for FIGURE 3: Immunohistochemistry of protein markers related to Th9 in postmortem brain tissue. (A-C) In Alzheimer disease (AD), there was intense staining of interleukin (IL)-9 in perivascular cells (A), which are also immunoreactive to T-cell marker CD3 (B) in adjacent slides, suggesting these to be IL-9-containing T cells (higher magnification in C).…”

Modeling cell line-specific recruitment of signaling proteins to the insulin-like growth factor 1 receptor

“…The models here were parameterized with shotgun proteomics data, which are evidently not well-suited for this purpose. Issues with shotgun proteomics data could emerge from biases introduced during sample preparation, inadequate coverage, or a limited ability to accurately quantify lower-abundance peptides [95][96][97]. Our approach here unintentionally serves as an example of how batch effects in proteomics data can be identified.…”

Assessing biological and technological variability in protein levels measured in pre-diagnostic plasma samples of women with breast cancer

“…Absolute measurements require the use of internal standards, which is not feasible in an untargeted study of hundreds of proteins. In recent years, emerging mass spectrometry-based technologies [ 16 ] have started to build quantitative assays for larger numbers of proteins; however, these technologies require either a priori knowledge of analytes of interest, or peptide spectral libraries that still rely on data dependent acquisition methods as exhibited in this study. The LC-MS/MS approach is also more sensitive towards higher abundance proteins, thus impacted by a relatively large amount of missing data compared to the antibody-based approaches due to the inherent under-sampling of the mass spectrometer.…”

“…However, technical advancements in mass spectrometry now allow for shotgun proteomics that provide unbiased relative protein measurements with higher coverage. Emerging reaction monitoring [ 16 ], and sequential window acquisition of all theoretical mass spectra [ 17 ] mass spectrometry-based technologies have also started to build quantitative assays for larger numbers of proteins. Each type of platform comes with advantages, disadvantages, and varying ability to detect true analytical signals beyond the biological noise.…”