Secretome Proteomic Approaches for Biomarker Discovery: An Update on Colorectal Cancer

High-Throughput Mass Spectrometry Analysis of N-Glycans and Protein Markers after FUT8 Knockdown in the Syngeneic SW480/SW620 Colorectal Cancer Cell Model

Disruption of the glycosylation machinery is a common feature in many types of cancer, and colorectal cancer (CRC) is no exception. Core fucosylation is mediated by the enzyme fucosyltransferase 8 (FucT-8), which catalyzes the addition of α1,6-l-fucose to the innermost GlcNAc residue of N-glycans. We and others have documented the involvement of FucT-8 and core-fucosylated proteins in CRC progression, in which we addressed core fucosylation in the syngeneic CRC model formed by SW480 and SW620 tumor cell lines from the perspective of alterations in their N-glycosylation profile and protein expression as an effect of the knockdown of the FUT8 gene that encodes FucT-8. Using label-free, semiquantitative mass spectrometry (MS) analysis, we found noticeable differences in N-glycosylation patterns in FUT8-knockdown cells, affecting core fucosylation and sialylation, the Hex/HexNAc ratio, and antennarity. Furthermore, stable isotopic labeling of amino acids in cell culture (SILAC)-based proteomic screening detected the alteration of species involved in protein folding, endoplasmic reticulum (ER) and Golgi post-translational stabilization, epithelial polarity, and cellular response to damage and therapy. This data is available via ProteomeXchange with identifier PXD050012. Overall, the results obtained merit further investigation to validate their feasibility as biomarkers of progression and malignization in CRC, as well as their potential usefulness in clinical practice.

A Subset of Colon Cancer Cell Lines Displays a Cytokine Profile Linked to Angiogenesis, EMT and Invasion Which Is Modulated by the Culture Conditions In Vitro

Colorectal cancer (CRC) is one of the deadliest cancers worldwide. The dysregulation of secretory pathways is a crucial driver of CRC progression, since it modulates cell proliferation, angiogenesis and survival. This study explores the changes in the CRC cytokine profile depending on the culture conditions and the presence of fibroblasts and macrophages as cellular components of the tumor microenvironment in 2D and in 3D formed spheroids. Upon analysis of 45 different cytokines, chemokines and growth factors, 20 CRC cell lines were categorized into high and low secretors. In the high secretor group cytokines related to angiogenesis, EMT and invasion were significantly upregulated. LIF and HFG were identified as the best discriminator between both groups. Independent of this grouping, the addition of normal as well as cancer-associated fibroblasts had a similar impact on the cytokine profile by increasing the total amount of secreted cytokines in most of the investigated cell lines. In contrast, the differentiation and polarization of macrophages was modulated differently by normal vs. cancer-associated fibroblasts. In summary, we identified two groups of CRC cell lines that differ in their cytokine profile. The dependance of this profile was analyzed in detail-not only from the tumor cell line but as well from the culture condition in vitro. Key cytokines that discriminate the two groups were identified and their importance as promising biomarker candidates for CRC discussed.

Cancer secretome: finding out hidden messages in extracellular secretions

Secretome analysis has gained popularity recently as a very well-designed proteomic approach that is being used to study various interactions and their effects on cellular activity. This analysis is especially helpful while studying the effects of the cells on their microenvironment, paracrine and autocrine processes, their therapeutic purposes, and as a new diagnostic perspective. Cancer is a condition rather than a specific type of disease and is still yet to be fully understood. Cancer secretome is a fairly new concept that is being implemented to examine the interactions taking place in the tumor microenvironment and can help to understand the phenomena like induction of tumorigenesis, stimulation of immune cells, etc. The secretome analysis helps to gain a different perspective on the existing knowledge on cancer and its effects. The recent advances in secretome studies are directed toward secreted components as drug targets, biomarkers, and companion tools for diagnostic and prognostic purposes in cancer. This review aims to find the interactors in different types of cancer and understand the existing unstructured secretome data and its application in prognosis, diagnosis, and in biomarker study.

Differential plasma proteomes of the patients with Opisthorchiasis viverrini and cholangiocarcinoma identify a polymeric immunoglobulin receptor as a potential biomarker

In Southeast Asian countries, nitrosamine compounds and the liver fluke Opisthorchis viverrini have long been identified as carcinogens for cholangiocarcinoma (CHCA). In order to effectively treat O. viverrini infections and prevent the development of CHCA, methods for disease detection are needed. This study aims to identify biomarkers for O. viverrini infection and CHCA. In the discovery phase, technical triplicates of five pooled plasma pools (10 plasma each) of healthy control subjects (noOVCCA), O. viverrini subjects (OV), and cholangiocarcinoma subjects (CCA), underwent solution-based digestion, with the label-free method, using a Thermo Scientific™ Q Exactive™ HF hybrid quadrupole-Orbitrap mass spectrometer and UltiMate 300 LC systems. The noOVCCA, OV, and CCA groups demonstrated different profiles and were clustered, as illustrated by PCA and heat map analysis. The STRING and reactome analysis showed that both OV and CCA groups up-regulated proteins targeting immune system-related proteins. Differential proteomic profiles, S100A9, and polymeric immunoglobulin receptor (PIGR) were specifically expressed in the CCA group. During the validation phase, another 50 plasma samples were validated via the PIGR sandwich ELISA. Using PIGR >1.559 ng/ml as a cut-off point, 78.00% sensitivity, 71.00% specificity, and AUC = 0.8216, were obtained. It is sufficient to differentially diagnose cholangiocarcinoma patients from healthy patients and those with Opisthorchiasis viverrini. Hence, in this study, PIGR was identified and validated as a potential biomarker for CHCA. Plasma PIGR is suggested for screening CHCA, especially in an endemic region of O. viverrini infection.

A comprehensive and comparative proteomic analysis of horse serum proteins in colitis

BACKGROUND

Equine colitis is a diarrhoeal disease caused by inflammation of the large bowel and can potentially be life-threatening due to its rapid progression. Pathogenesis is multifactorial and pathophysiology is highly complicated, therefore, reliable diagnostic biomarkers are needed in the veterinary field.

OBJECTIVE

Serum is one of the most commonly used diagnostic tools in equine clinical investigation. To discover diagnostic or prognostic protein markers for colitis in horse serum, comprehensive and comparative proteomic analysis was conducted using liquid chromatography-tandem mass spectrometry (LC-MS/MS).

STUDY DESIGN

Case-control study.

METHODS

Serum samples were collected from 36 healthy Thoroughbreds and 12 Thoroughbreds with colitis. Serum from each horse suffering from colitis was collected daily until death or recovery. Collected sera were digested with trypsin. Peptides obtained from serum proteins were measured by Q-Exactive HF Orbitrap mass spectrometer. The identification and quantification of peptides were performed using Proteome Discoverer version 2.2.

RESULTS

On day 1 of treatment, eight proteins in the colitis group were upregulated (P < .05, more than a twofold change) compared with the healthy group. Among the eight proteins, biliverdin reductase B was significantly upregulated (P < .05) in the non-survivor group (n = 5) compared with the survivor group (n = 7). On the last day of the treatment, haemoglobin subunit alpha, clusterin, glyceraldehyde-3-phosphate dehydrogenase, lipopolysaccharide-binding protein, and biliverdin reductase B showed significant increases (P < .05) in the non-survivor group.

MAIN LIMITATIONS

The number of the identified proteins is limited due to the existence of abundant proteins.

CONCLUSIONS

Measuring the changes of these proteins together may enable a potential prognosis or early diagnosis of horses suffering from colitis.

Analysis of ovarian cancer cell secretome during epithelial to mesenchymal transition reveals a protein signature associated with advanced stages of ovarian tumors

Ovarian cancer (OvCA) is the most lethal neoplasia among gynecologic malignancies and faces high rates of new cases particularly in South America. In special, the High Grade Serous Ovarian Carcinoma (HGSC) presents very poor prognosis with deaths caused mainly by metastasis. Among several mechanisms involved in metastasis, the Epithelial to Mesenchymal Transition (EMT) molecular reprogramming represents a model for latest stages of cancer progression. EMT promotes important cellular changes in cellular adhesion and cell-cell communication, which particularly depends on the paracrine signaling from neighbor cells. Considering the importance of cellular communication during EMT and metastasis, here we analyzed the changes in the secretome of the ovarian cancer cell line Caov-3 induced to EMT by Epidermal Growth Factor (EGF). Using a combination of GEL-LC-MS/MS and stable isotopic metabolic labelling (SILAC), we identified up-regulated candidates during EMT as a starting point to identify relevant proteins for HGSC. Based on public databases, our candidate proteins were validated and prioritized for further analysis. Importantly, several of the protein candidates were associated with cellular vesicles, which are important to the cell-cell communication and metastasis. Furthermore, the association of candidate proteins with gene expression data uncovered a subset of proteins correlated with the mesenchymal subtype of ovarian cancer. Based on this relevant molecular signature for aggressive ovarian cancer, supported by protein and gene expression data, we developed a targeted proteomic method to evaluate individual OvCA clinical samples. The quantitative information obtained for 33 peptides, representative of 18 proteins, was able to segregate HGSC from other tumor types. Our study highlighted the richness of the secretome and EMT to reveal relevant proteins for HGSC, which could be used in further studies and larger patient cohorts as a potential stratification signature for ovarian cancer tumor that could guide clinical conduct for patient treatment.