Novel secretome-to-transcriptome integrated or secreto-transcriptomic approach to reveal liquid biopsy biomarkers for predicting individualized prognosis of breast cancer patients

Metabolic Functions of Biliverdin IXβ Reductase in Redox-Regulated Hematopoietic Cell Fate

Cytoprotective heme oxygenases derivatize heme to generate carbon monoxide, ferrous iron, and isomeric biliverdins, followed by rapid NAD(P)H-dependent biliverdin reduction to the antioxidant bilirubin. Recent studies have implicated biliverdin IXβ reductase (BLVRB) in a redox-regulated mechanism of hematopoietic lineage fate restricted to megakaryocyte and erythroid development, a function distinct and non-overlapping from the BLVRA (biliverdin IXα reductase) homologue. In this review, we focus on recent progress in BLVRB biochemistry and genetics, highlighting human, murine, and cell-based studies that position BLVRB-regulated redox function (or ROS accumulation) as a developmentally tuned trigger that governs megakaryocyte/erythroid lineage fate arising from hematopoietic stem cells. BLVRB crystallographic and thermodynamic studies have elucidated critical determinants of substrate utilization, redox coupling and cytoprotection, and have established that inhibitors and substrates bind within the single-Rossmann fold. These advances provide unique opportunities for the development of BLVRB-selective redox inhibitors as novel cellular targets that retain potential for therapeutic applicability in hematopoietic (and other) disorders.

Secretome of Stromal Cancer-Associated Fibroblasts (CAFs): Relevance in Cancer

The cancer secretome reflects the assortment of proteins released by cancer cells. Investigating cell secretomes not only provides a deeper knowledge of the healthy and transformed state but also helps in the discovery of novel biomarkers. Secretomes of cancer cells have been studied in the past, however, the secretome contribution of stromal cells needs to be studied. Cancer-associated fibroblasts (CAFs) are one of the predominantly present cell populations in the tumor microenvironment (TME). CAFs play key role in functions associated with matrix deposition and remodeling, reciprocal exchange of nutrients, and molecular interactions and signaling with neighboring cells in the TME. Investigating CAFs secretomes or CAFs-secreted factors would help in identifying novel CAF-specific biomarkers, unique druggable targets, and an improved understanding for personalized cancer diagnosis and prognosis. In this review, we have tried to include all studies available in PubMed with the keywords "CAFs Secretome". We aim to provide a comprehensive summary of the studies investigating role of the CAF secretome on cancer development, progression, and therapeutic outcome. However, challenges associated with this process have also been addressed in the later sections. We have highlighted the functions and clinical relevance of secretome analysis in stromal CAF-rich cancer types. This review specifically discusses the secretome of stromal CAFs in cancers. A deeper understanding of the components of the CAF secretome and their interactions with cancer cells will help in the identification of personalized biomarkers and a more precise treatment plan.

Integrative, In Silico and Comparative Analysis of Breast Cancer Secretome Highlights Invasive-Ductal-Carcinoma-Grade Progression Biomarkers

Globally, BC is the most frequently diagnosed cancer in women. The aim of this study was to identify novel secreted biomarkers that may indicate progression to high-grade BC malignancies and therefore predict metastatic potential. A total of 33 studies of breast cancer and 78 of other malignancies were screened via a systematic review for eligibility, yielding 26 datasets, 8 breast cancer secretome datasets, and 18 of other cancers that were included in the comparative secretome analysis. Sequential bioinformatic analysis using online resources enabled the identification of enriched GO_terms, overlapping clusters, and pathway reconstruction. This study identified putative predictors of IDC grade progression and their association with breast cancer patient mortality outcomes, namely, HSPG2, ACTG1, and LAMA5 as biomarkers of in silico pathway prediction, offering a putative approach by which the abovementioned proteins may mediate their effects, enabling disease progression. This study also identified ITGB1, FBN1, and THBS1 as putative pan-cancer detection biomarkers. The present study highlights novel, putative secretome biomarkers that may provide insight into the tumor biology and could inform clinical decision making in the context of IDC management in a non-invasive manner.

Nano-omics: nanotechnology-based multidimensional harvesting of the blood-circulating cancerome

Over the past decade, the development of 'simple' blood tests that enable cancer screening, diagnosis or monitoring and facilitate the design of personalized therapies without the need for invasive tumour biopsy sampling has been a core ambition in cancer research. Data emerging from ongoing biomarker development efforts indicate that multiple markers, used individually or as part of a multimodal panel, are required to enhance the sensitivity and specificity of assays for early stage cancer detection. The discovery of cancer-associated molecular alterations that are reflected in blood at multiple dimensions (genome, epigenome, transcriptome, proteome and metabolome) and integration of the resultant multi-omics data have the potential to uncover novel biomarkers as well as to further elucidate the underlying molecular pathways. Herein, we review key advances in multi-omics liquid biopsy approaches and introduce the 'nano-omics' paradigm: the development and utilization of nanotechnology tools for the enrichment and subsequent omics analysis of the blood-circulating cancerome.

ISGylation drives basal breast tumour progression by promoting EGFR recycling and Akt signalling

ISG15 is an ubiquitin-like modifier that is associated with reduced survival rates in breast cancer patients. The mechanism by which ISG15 achieves this however remains elusive. We demonstrate that modification of Rab GDP-Dissociation Inhibitor Beta (GDI2) by ISG15 (ISGylation) alters endocytic recycling of the EGF receptor (EGFR) in non-interferon stimulated cells using CRISPR-knock out models for ISGylation. By regulating EGFR trafficking, ISGylation enhances EGFR recycling and sustains Akt-signalling. We further show that Akt signalling positively correlates with levels of ISG15 and its E2-ligase in basal breast cancer cohorts, confirming the link between ISGylation and Akt signalling in human tumours. Persistent and enhanced Akt activation explains the more aggressive tumour behaviour observed in human breast cancers. We show that ISGylation can act as a driver of tumour progression rather than merely being a bystander.

Global mapping of cancers: The Cancer Genome Atlas and beyond

Cancer genomes have been explored from the early 2000s through massive exome sequencing efforts, leading to the publication of The Cancer Genome Atlas in 2013. Sequencing techniques have been developed alongside this project and have allowed scientists to bypass the limitation of costs for whole-genome sequencing (WGS) of single specimens by developing more accurate and extensive cancer sequencing projects, such as deep sequencing of whole genomes and transcriptomic analysis. The Pan-Cancer Analysis of Whole Genomes recently published WGS data from more than 2600 human cancers together with almost 1200 related transcriptomes. The application of WGS on a large database allowed, for the first time in history, a global analysis of features such as molecular signatures, large structural variations and noncoding regions of the genome, as well as the evaluation of RNA alterations in the absence of underlying DNA mutations. The vast amount of data generated still needs to be thoroughly deciphered, and the advent of machine-learning approaches will be the next step towards the generation of personalized approaches for cancer medicine. The present manuscript wants to give a broad perspective on some of the biological evidence derived from the largest sequencing attempts on human cancers so far, discussing advantages and limitations of this approach and its power in the era of machine learning.

Liquid biopsies and cancer omics

The development of the sequencing technologies allowed the generation of huge amounts of molecular data from a single cancer specimen, allowing the clinical oncology to enter the era of the precision medicine. This massive amount of data is highlighting new details on cancer pathogenesis but still relies on tissue biopsies, which are unable to capture the dynamic nature of cancer through its evolution. This assumption led to the exploration of non-tissue sources of tumoral material opening the field of liquid biopsies. Blood, together with body fluids such as urines, or stool, from cancer patients, are analyzed applying the techniques used for the generation of omics data. With blood, this approach would allow to take into account tumor heterogeneity (since the circulating components such as CTCs, ctDNA, or ECVs derive from each cancer clone) in a time dependent manner, resulting in a somehow "real-time" understanding of cancer evolution. Liquid biopsies are beginning nowdays to be applied in many cancer contexts and are at the basis of many clinical trials in oncology.

Microfluidic Immunoassays for Time-Resolved Measurement of Protein Secretion from Single Cells

Measurement of humoral factors secreted from cells has served as an indispensable method to monitor the states of a cell ensemble because humoral factors play crucial roles in cell-cell interaction and aptly reflect the states of individual cells. Although a cell ensemble consisting of a large number of cells has conventionally been the object of such measurements, recent advances in microfluidic technology together with highly sensitive immunoassays have enabled us to quantify secreted humoral factors even from individual cells in either a population or a temporal context. Many groups have reported various miniaturized platforms for immunoassays of proteins secreted from single cells. This review focuses on the current status of time-resolved assay platforms for protein secretion with single-cell resolution. We also discuss future perspectives of time-resolved immunoassays from the viewpoint of systems biology.

Personalized Approach to Determination of Histidine-Rich Glycoprotein and E-Cadherin in Supernatants of Immunocompetent Blood Cells and Breast Biopsy Specimens in Breast Malignant and Non-Malignant Disease

The material of patients with invasive carcinoma of no special type (ICNT) and nonmalignant diseases (ND) of the mammary gland was studied. When comparing the concentrations of histidine-rich glycoprotein (HRG) and E-cadherin (CDH1), statistically significant differences between ICNT and ND by HRG in the supernatant of blood cells and its spontaneous production by biopsies and by CDH1 at its induced production, as well as by influence indices of polyclonal activators on the production of CDH1 were found. When comparing the expression of immunohistochemical markers, no statistically significant differences between ICNT and ND were obtained.

Proteomic examination of the neuroglial secretome: lessons for the clinic

Introduction: Glial cells are closely associated with neurons located throughout the nervous system and regulate neuronal activity and function through various mechanisms including the secretion of proteins and other signaling molecules. Glia-secreted proteins play crucial roles in modulating neuronal function in physiological and pathological conditions. Aberrant activation of glial cells leading to neuroinflammation is a common phenomenon observed in various neurological disorders. Aberrantly activated glial cells secrete proteins in disease-specific manner and can be exploited as a repository for novel biomarker discovery.Areas covered: In this review, we describe the recent advances in proteomic techniques, highlighting the need for their application to the secretomic field. Studies regarding the secretome profile of glial cells published within the last 5 years are discussed in detail. The use of glia-based biomarkers in various neuroinflammatory and neurodegenerative diseases is also discussed.Expert opinion: Precise diagnosis and timely treatment of neurological disorders remains a challenge and glia-focused research to identify specific biomarkers appears to be a promising approach to combat these disorders. Recent technological advancement in proteomic research would open new frontiers for more rigorous analysis of glial secretome variations over time and the discovery/development of novel biomarkers for neurological disorders.