Quantitative proteomics reveals proteins involved in the progression from non-cancerous lesions to gastric cancer

Fernández-Coto, Diana Lashidua; Gil, Jeovanis; Hernández, A.; Herrera‐Goepfert, Roberto; Castro-Romero, Ivone; Hernández-Márquez, Eva; Arenas-Linares, Ana Silvia; Calderon-Sosa, Valia Tletzalli; Sánchez-Alemán, Miguel Ángel; Méndez‐Tenorio, Alfonso; Encarnación‐Guevara, Sergio; Ayala, Guadalupe

doi:10.1016/j.jprot.2018.07.013

Cited by 26 publications

(15 citation statements)

References 44 publications

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“…This enzyme is involved in the first step of gluconeogenesis and upregulation contributes to the accumulation of glycolysis intermediates that are required to support rapid cell proliferation. When compared to premalignant lesions, similar results in gastric adenocarcinoma biopsies have been found (Fernández-Coto et al 2018). The activation of glycolysis is also aided by the upregulation of proteins involved in the insulin signalling pathway.…”

Section: Understanding Melanoma By Mapping Proteomic Data On Biologicsupporting

confidence: 65%

Clinical protein science in translational medicine targeting malignant melanoma

et al. 2019

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Melanoma of the skin is the sixth most common type of cancer in Europe and accounts for 3.4% of all diagnosed cancers. More alarming is the degree of recurrence that occurs with approximately 20% of patients lethally relapsing following treatment. Malignant melanoma is a highly aggressive skin cancer and metastases rapidly extend to the regional lymph nodes (stage 3) and to distal organs (stage 4). Targeted oncotherapy is one of the standard treatment for progressive stage 4 melanoma, and BRAF inhibitors (e.g. vemurafenib, dabrafenib) combined with MEK inhibitor (e.g. trametinib) can effectively counter BRAFV600E-mutated melanomas. Compared to conventional chemotherapy, targeted BRAFV600E inhibition achieves a significantly higher response rate. After a period of cancer control, however, most responsive patients develop resistance to the therapy and lethal progression. The many underlying factors potentially causing resistance to BRAF inhibitors have been extensively studied. Nevertheless, the remaining unsolved clinical questions necessitate alternative research approaches to address the molecular mechanisms underlying metastatic and treatment-resistant melanoma. In broader terms, proteomics can address clinical questions far beyond the reach of genomics, by measuring, i.e. the relative abundance of protein products, post-translational modifications (PTMs), protein localisation, turnover, protein interactions and protein function. More specifically, proteomic analysis of body fluids and tissues in a given medical and clinical setting can aid in the identification of cancer biomarkers and novel therapeutic targets. Achieving this goal requires the development of a robust and reproducible clinical proteomic platform that encompasses automated biobanking of patient samples, tissue sectioning and histological examination, efficient protein extraction, enzymatic digestion, mass spectrometry-based quantitative protein analysis by label-free or labelling technologies and/or enrichment of peptides with specific PTMs. By combining data from, e.g. phosphoproteomics and acetylomics, the protein expression profiles of different melanoma stages can provide a solid framework for understanding the biology and progression of the disease. When complemented by proteogenomics, customised protein sequence databases generated from patient-specific genomic and transcriptomic data aid in interpreting clinical proteomic biomarker data to provide a deeper and more comprehensive molecular characterisation of cellular

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Section: Understanding Melanoma By Mapping Proteomic Data On Biologicsupporting

confidence: 65%

Clinical protein science in translational medicine targeting malignant melanoma

et al. 2019

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“…The most inhibited pathways in GC were oxidative phosphorylation and the TCA cycle. This is consistent with another report on GC [14]. Recent studies have shown that cancer cells exhibit significant metabolic changes in mitochondrial dynamics and function [35].…”

Section: Discussionsupporting

confidence: 93%

“…Several recent studies have investigated proteomic aspects of GC. Using the Isobaric Tags for Relative and Absolute Quantitation (iTRAQ) approach combined with high-resolution MS analysis, a previous study identified 3914 different proteins in six biopsies from different disease stages ranging from chronic gastritis and intestinal metaplasia to gastric adenocarcinoma [14]. Another study examined four GC tissues and four adjacent normal tissues and identified 431 differentially expressed protein (DEPs) using iTRAQ-based quantitative proteomic analysis [15].…”

Section: Introductionmentioning

confidence: 99%

Screening of Potential Biomarkers for Gastric Cancer with Diagnostic Value Using Label-free Global Proteome Analysis

Song¹,

Wang²,

Sun³

et al. 2020

Preprint

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Gastric cancer (GC) is one of the most malignant tumors worldwide. Despite the recent decrease in mortality rates, the prognosis remains poor. Therefore, it is necessary to find novel biomarkers with early diagnostic value for GC. In this study, we present a large-scale proteomic analysis of 30 GC tissues and 30 matched healthy tissues using label-free global proteome profiling. Our results identified 537 differentially expressed proteins, including 280 upregulated and 257 downregulated proteins. The ingenuity pathway analysis (IPA) results indicated that the sirtuin signaling pathway was the most activated pathway in GC tissues whereas oxidative phosphorylation was the most inhibited. Moreover, the most activated molecular function was cellular movement, including tissue invasion by tumor cell lines. Based on IPA results, 15 hub proteins were screened. Using the receiver operating characteristic curve, most of hub proteins showed a high diagnostic power in distinguishing between tumors and healthy controls. A four-protein (ATP5B-ATP5O-NDUFB4-NDUFB8) diagnostic signature was built using a random forest model. The area under the curve (AUC) of this model was 0.996 and 0.886 for the training and testing set, respectively, suggesting that the four-protein signature has a high diagnostic power. This signature was further tested with independent datasets using plasma enzyme-linked immune sorbent assays, resulted in an AUC of 0.778 for distinguishing GC tissues from healthy controls, and using immunohistochemical tissue microarray analysis, resulting in an AUC of 0.805. In conclusion, this study identifies potential biomarkers and improves our understanding of the pathogenesis, providing novel therapeutic targets for GC.

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“…To analyze the complex protein mixtures with higher sensitivity, the main technology presently in use is mass spectrometry (MS) [69], combined with liquid chromatography or matrix-assisted laser desorption ionization (MALDI-TOF/TOF) [68,70,71]. However, new methods were recently developed for quantitative proteomic such as isotope-coded affinity tag (ICAT) labeling, stable isotope labeling with amino acids in cell culture (SILAC), and isobaric tag for relative and absolute quantitation (iTRAQ) [72,73,74]. X-ray crystallography and nuclear magnetic resonance (NMR) spectroscopy are two major high-throughput techniques that provide 3D structure of proteins [75].…”

Section: Omics Data Productionmentioning

confidence: 99%

“…The identification of these proteins shed light on the molecular signaling pathways that are associated with ovarian cancer development [84]. Similarly, by using an iTRAQ approach combined with high-resolution MS analysis, several proteins were found dysregulated during gastric cancer progression, demonstrating their potential use as specific biomarkers and/or therapeutic targets [73]. Moreover, by using MS-based proteomic analysis on 130 clinical breast cancer samples, Yanovich and colleagues demonstrated intertumor heterogeneity across three breast cancer subtypes and healthy tissues, identifying four proteomic clusters.…”

Section: Omics Data Productionmentioning

confidence: 99%

From Single Level Analysis to Multi-Omics Integrative Approaches: A Powerful Strategy towards the Precision Oncology

et al. 2018

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Integration of multi-omics data from different molecular levels with clinical data, as well as epidemiologic risk factors, represents an accurate and promising methodology to understand the complexity of biological systems of human diseases, including cancer. By the extensive use of novel technologic platforms, a large number of multidimensional data can be derived from analysis of health and disease systems. Comprehensive analysis of multi-omics data in an integrated framework, which includes cumulative effects in the context of biological pathways, is therefore eagerly awaited. This strategy could allow the identification of pathway-addiction of cancer cells that may be amenable to therapeutic intervention. However, translation into clinical settings requires an optimized integration of omics data with clinical vision to fully exploit precision cancer medicine. We will discuss the available technical approach and more recent developments in the specific field.

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Quantitative proteomics reveals proteins involved in the progression from non-cancerous lesions to gastric cancer

Cited by 26 publications

References 44 publications

Clinical protein science in translational medicine targeting malignant melanoma

Clinical protein science in translational medicine targeting malignant melanoma

Screening of Potential Biomarkers for Gastric Cancer with Diagnostic Value Using Label-free Global Proteome Analysis

From Single Level Analysis to Multi-Omics Integrative Approaches: A Powerful Strategy towards the Precision Oncology

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