Strategies in functional proteomics: Unveiling the pathways to precision oncology

Shifting Gears in Precision Oncology-Challenges and Opportunities of Integrative Data Analysis

For decades, research relating to modification of host immunity towards antitumor response activation has been ongoing, with the breakthrough discovery of immune-checkpoint blockers. Several biomarkers with potential predictive value have been reported in recent studies for these novel therapies. However, with the plethora of therapeutic options existing for a given cancer entity, modern oncology is now being confronted with multifactorial interpretation to devise “the best therapy” for the individual patient. Into the bargain come the multiverse guidelines for established and emerging diagnostic biomarkers, as well as the complex interplay between cancer cells and tumor microenvironment, provoking immense challenges in the therapy decision-making process. Through this review, we present various molecular diagnostic modalities and techniques, such as genomics, immunohistochemistry and quantitative image analysis, which have the potential of becoming powerful tools in the development of an optimal treatment regime when analogized with patient characteristics. We will summarize the underlying complexities of these methods and shed light upon the necessary considerations and requirements for data integration. It is our hope to provide compelling evidence to emphasize on the need for inclusion of integrative data analysis in modern cancer therapy, and thereupon paving a path towards precision medicine and better patient outcomes.

Pericardial fluid proteomic label-free quantification of differentially expressed proteins in ischemic heart disease patients with systolic dysfunction by nano-LC-ESI-MS/MS analysis

Left ventricular systolic dysfunction (LVSD) is common in patients with pre-existing ischemic heart disease (IHD) and myocardial infarction. An untargeted proteomic approach is used to improve the understanding of the molecular mechanisms associated with LVSD and to find out potential proteomic signatures in pericardial fluid. The pericardial fluid of IHD (n = 45) patients was grouped into two categories according to the left ventricular ejection fraction, LVEF ≥45 (n = 33) and LVEF <45 (n = 12), and analyzed by using nano-liquid chromatography-mass spectrometry (nano-LC-MS/MS) technique. The nano-LC-MS/MS analysis resulted in the identification of 709 pericardial fluid (PF) proteins in both normal and impaired systolic functional groups (LVEF ≥45 vs. LVEF <45). Sixteen proteins were found to be differentially expressed (p < 0.05, fold change >2) including 12 down-regulated and 4 up-regulated in the impaired systolic functional group (LVEF <45) compared to the normal group (LVEF ≥45). Among the differentially expressed proteins the inflammatory marker albumin, atherosclerosis marker apolipoprotein A-IV and hedgehog-interacting protein marker of angiogenesis were predominantly associated with the impaired LVEF <45 group. KEGG pathway analysis revealed that the hedgehog (Hh) signalling pathway is up-regulated in LVSD reflecting the underlying molecular and pathophysiological processes.

Existing and novel biomarkers for precision medicine in systemic sclerosis

The discovery and validation of biomarkers resulting from technological advances in the analysis of genomic, transcriptomic, lipidomic and metabolomic pathways involved in the pathogenesis of complex human diseases have led to the development of personalized and rationally designed approaches for the clinical management of such disorders. Although some of these approaches have been applied to systemic sclerosis (SSc), an unmet need remains for validated, non-invasive biomarkers to aid in the diagnosis of SSc, as well as in the assessment of disease progression and response to therapeutic interventions. Advances in global transcriptomic technology over the past 15 years have enabled the assessment of microRNAs that circulate in the blood of patients and the analysis of the macromolecular content of a diverse group of lipid bilayer membrane-enclosed extracellular vesicles, such as exosomes and other microvesicles, which are released by all cells into the extracellular space and circulation. Such advances have provided new opportunities for the discovery of biomarkers in SSc that could potentially be used to improve the design and evaluation of clinical trials and that will undoubtedly enable the development of personalized and individualized medicine for patients with SSc.

SuperQuant-assisted comparative proteome analysis of glioblastoma subpopulations allows for identification of potential novel therapeutic targets and cell markers

Glioblastoma (GBM) is a highly aggressive brain cancer with poor prognosis and low survival rate. Invasive cancer stem-like cells (CSCs) are responsible for tumor recurrence because they escape current treatments. Our main goal was to study the proteome of three GBM subpopulations to identify key molecules behind GBM cell phenotypes and potential cell markers for migrating cells. We used SuperQuant-an enhanced quantitative proteome approach-to increase proteome coverage. We found 148 proteins differentially regulated in migrating CSCs and 199 proteins differentially regulated in differentiated cells. We used Ingenuity Pathway Analysis (IPA) to predict upstream regulators, downstream effects and canonical pathways associated with regulated proteins. IPA analysis predicted activation of integrin-linked kinase (ILK) signaling, actin cytoskeleton signaling, and lysine demethylase 5B (KDM5B) in CSC migration. Moreover, our data suggested that microRNA-122 (miR-122) is a potential upstream regulator of GBM phenotypes as miR-122 activation was predicted for differentiated cells while its inhibition was predicted for migrating CSCs. Finally, we validated transferrin (TF) and procollagen-lysine 2-oxoglutarate 5-dioxygenase 2 (PLOD2) as potential markers for migrating cells.

Proteomic-Based Approaches for the Study of Cytokines in Lung Cancer

Proteomic techniques are currently used to understand the biology of different human diseases, including studies of the cell signaling pathways implicated in cancer progression, which is important in knowing the roles of different proteins in tumor development. Due to its poor prognosis, proteomic approaches are focused on the identification of new biomarkers for the early diagnosis, prognosis, and targeted treatment of lung cancer. Cytokines are proteins involved in inflammatory processes and have been proposed as lung cancer biomarkers and therapeutic targets because it has been reported that some cytokines play important roles in tumor development, invasion, and metastasis. In this review, we aim to summarize the different proteomic techniques used to discover new lung cancer biomarkers and therapeutic targets. Several cytokines have been identified as important players in lung cancer using these techniques. We underline the most important cytokines that are useful as biomarkers and therapeutic targets. We also summarize some of the therapeutic strategies targeted for these cytokines in lung cancer.