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Employing proteomics to understand the effects of nutritional intervention in cancer treatment

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Abstract

Lifestyle optimizations are implementable changes that can have an impact on health and disease. Nutrition is a lifestyle optimization that has been shown to be of great importance in cancer initiation, progression, and metastasis. Dozens of clinical trials are currently in progress that focus on the nutritional modifications that cancer patients can make prior to and during medical care that increase the efficacy of treatment. In this review, we discuss various nutritional inventions for cancer patients and the analytical approaches to characterize the downstream molecular effects. We first begin by briefly explaining the many different forms of nutritional intervention currently being used in cancer treatment as well as their motivating biology. The forms of nutrient modulation described in this review include calorie restriction, the different practices of fasting, and carbohydrate restriction. The review then shifts to explain how proteomics is used to determine biomarkers of cancer and how it can be utilized in the future to determine the metabolic phenotype of a tumor, and inform physicians if nutritional intervention should be recommended for a cancer patient. Nutrigenomics aims to understand the relationship of nutrients and gene expression and can be used to understand the downstream molecular effects of nutrition restriction, partially through proteomic analysis. Proteomics is just beginning to be used as cancer diagnostic and predictive tools. However, these approaches have not been used to their full potential to understand nutritional intervention in cancer.

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Abbreviations

3D:

Three-dimensional

ASAP2 :

A scalable automated proteomic pipeline

CORE:

Cellular consumption and release

CR:

Calorie restriction

CRP:

c-Reactive protein

CRS:

Caloric Restriction Society

DSR:

Differential stress resistance

ELISA:

Enzyme-linked immunosorbent assays

ESI-MS/MS:

Electrospray-ionization tandem mass spectrometry

FT-ICR:

Fourier transform-ion cyclotron resonance

GH:

Growth hormone

Hba1c:

Hemoglobin A1C

IF:

Intermittent fasting

IGF-1:

Insulin growth factor-1

JAK/STAT:

Janus kinase and signal transducer activator of transcription

KD:

Ketogenic diet

LC:

Liquid chromatography

MRM:

Multiple reaction monitoring

MS:

Mass spectrometry

NF-κB:

Nuclear factor-κB

NIA:

National Institute of Aging

PASEF:

Parallel accumulation serial fragmentation

SDS:

Sodium dodecyl sulfate

S-Traps:

Suspension trapping

TOF:

Time-of-flight

TRF:

Time-restricted feeding

UW:

University of Wisconsin, Madison

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Acknowledgments

MMS was supported by the National Institutes of Health Training Grant–Chemistry Biochemistry Biology Interface Program (T32GM075762). ABH was supported by the National Institutes of Health (R01GM110406), and the National Science Foundation (CAREER Award, CHE-1351595). MMS researched available literature and was the major contributing author. All authors read and approved the final manuscript. We gratefully acknowledge the assistance of Dr. Susan Skube, Katelyn Ludwig, and Emily Herring for their edits.

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Authors and Affiliations

  1. Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN, 46556, USA

    Monica M. Schroll

  2. Harper Cancer Research Institute, University of Notre Dame, Notre Dame, IN, 46556, USA

    Monica M. Schroll

  3. Department of Chemistry and Biochemistry, Comprehensive Cancer Center, The Ohio State University, Columbus, OH, 43210, USA

    Amanda B. Hummon

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  1. Monica M. Schroll
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  2. Amanda B. Hummon
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Correspondence to Amanda B. Hummon.

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Schroll, M.M., Hummon, A.B. Employing proteomics to understand the effects of nutritional intervention in cancer treatment. Anal Bioanal Chem 410, 6371–6386 (2018). https://doi.org/10.1007/s00216-018-1219-z

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  • DOI: https://doi.org/10.1007/s00216-018-1219-z

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