The cancer secretome and secreted biomarkers

The Role and Potential Mechanism of Complement Factor D in Fibromyalgia Development

Purpose

Fibromyalgia (FM) is a syndrome characterized by chronic musculoskeletal pain. Its clinical symptoms include both somatic and psychiatric symptoms, making the treatment of FM extremely challenging. The cause of FM is still unknown, and some patients do not improve their symptoms even after long-term active treatment. Thus, the development of new targeted therapies is important to reduce pain and improve quality of life for FM patients.

Methods

In this study, we screened genes and secreted factors that play key roles in FM through bioinformatics and big data analysis. Furthermore, we performed CCK-8, qRT-PCR, glucose, ATP and lactate content testing, dual luciferase reporter gene assay to investigate the potential mechanism of complement factor D in fibromyalgia development.

Results

In bioinformatics and big data analysis, we identified CFD was negatively correlated with the pro-inflammatory factor IL-6 and positively correlated with the anti-inflammatory factor IL-4, which suggested that CFD may be an anti-inflammatory factor. Through cellular assays, we verified that CFD reversed the decrease in IL-4 expression and the increase in IL-6 expression in BV2 cells caused by ATP.

Conclusion

In summary, based on bioinformatic methods and big data mining we obtained a new target CFD for FM, and further experiments verified that CFD has significant inhibition of ATP-induced neuropathic pain. These findings provide a new theoretical basis for the clinical translation of CFD.

Microenvironment Molecular Profile Combining Glycation Adducts and Cytokines Patterns on Secretome of Short-term Blood-derived Cultures during Tumour Progression

Cancer cells are known to secrete many bioactive factors acting both with paracrine and autocrine mechanisms by which they condition the surrounding microenvironment. At the same time, the intracytoplasmic metabolic activities microenvironment influences the profile of this secretion. It is well known that cancer cells exhibit prevalent glycolytic metabolism and a more oxidative atmosphere compared to their healthy counterparts; this metabolic phenotype promotes glycate adducts formation and secretion. Considering the exacerbation of metabolic changes during the cancer progression, it is suggestive to explore the potential correlation between the increasing rate of glycan adducts and the specific pattern of secreted cytokines in different phases of cancer disease. We analyzed the secretomes of blood-derived cancer cell cultures from cancer patients and healthy subjects. The relative glycate adducts content in cancer secretomes was higher in comparison to that of healthy samples. Moreover, the stratification based on different phases of cancer disease correlated with a specific cytokines panel. The results obtained open a new perspective of observation of the intricate relationship between metabolome and inflammation in cancer. By using the analysis of secretome combined with a standardized protocol of liquid biopsy, it would be possible to identify specific profiles of molecular markers useful to arrange alternative and personalized medicine strategies.

An Integrated Meta-Analysis of Secretome and Proteome Identify Potential Biomarkers of Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is extremely aggressive, has an unfavorable prognosis, and there are no biomarkers for early detection of the disease or identification of individuals at high risk for morbidity or mortality. The cellular and molecular complexity of PDAC leads to inconsistences in clinical validations of many proteins that have been evaluated as prognostic biomarkers of the disease. The tumor secretome, a potential source of biomarkers in PDAC, plays a crucial role in cell proliferation and metastasis, as well as in resistance to treatments, which together contribute to a worse clinical outcome. The massive amount of proteomic data from pancreatic cancer that has been generated from previous studies can be integrated and explored to uncover secreted proteins relevant to the diagnosis and prognosis of the disease. The present study aimed to perform an integrated meta-analysis of PDAC proteome and secretome public data to identify potential biomarkers of the disease. Our meta-analysis combined mass spectrometry data obtained from two systematic reviews of the pancreatic cancer literature, which independently selected 20 studies of the secretome and 35 of the proteome. Next, we predicted the secreted proteins using seven in silico tools or databases, which identified 39 secreted proteins shared between the secretome and proteome data. Notably, the expression of 31 genes of these secretome-related proteins was upregulated in PDAC samples from The Cancer Genome Atlas (TCGA) when compared to control samples from TCGA and The Genotype-Tissue Expression (GTEx). The prognostic value of these 39 secreted proteins in predicting survival outcome was confirmed using gene expression data from four PDAC datasets (validation set). The gene expression of these secreted proteins was able to distinguish high- and low-survival patients in nine additional tumor types from TCGA, demonstrating that deregulation of these secreted proteins may also contribute to the prognosis in multiple cancers types. Finally, we compared the prognostic value of the identified secreted proteins in PDAC biomarkers studies from the literature. This analysis revealed that our gene signature performed equally well or better than the signatures from these previous studies. In conclusion, our integrated meta-analysis of PDAC proteome and secretome identified 39 secreted proteins as potential biomarkers, and the tumor gene expression profile of these proteins in patients with PDAC is associated with worse overall survival.

Oncometabolites in cancer aggressiveness and tumour repopulation

Tumour repopulation is recognized as a crucial event in tumour relapse where therapy-sensitive dying cancer cells influence the tumour microenvironment to sustain therapy-resistant cancer cell growth. Recent studies highlight the role of the oncometabolites succinate, fumarate, and 2-hydroxyglutarate in the aggressiveness of cancer cells and in the worsening of the patient's clinical outcome. These oncometabolites can be produced and secreted by cancer and/or surrounding cells, modifying the tumour microenvironment and sustaining an invasive neoplastic phenotype. In this review, we report recent findings concerning the role in cancer development of succinate, fumarate, and 2-hydroxyglutarate and the regulation of their related enzymes succinate dehydrogenase, fumarate hydratase, and isocitrate dehydrogenase. We propose that oncometabolites are crucially involved in tumour repopulation. The study of the mechanisms underlying the relationship between oncometabolites and tumour repopulation is fundamental for identifying efficient anti-cancer therapeutic strategies and novel serum biomarkers in order to overcome cancer relapse.