Diagnostic role of circulating extracellular matrix-related proteins in non-small cell lung cancer.

BACKGROUND: Interactions between cancer cells and the surrounding microenvironment are crucial determinants of cancer progression. During this process, bi-directional communication among tumor cells and cancer associated fibroblasts (CAF) regulate extracellular matrix (ECM) deposition and remodeling. As a result of this dynamic process, soluble ECM proteins can be released into the bloodstream and may represent novel circulating biomarkers useful for cancer diagnosis. The aim of the present study was to measure the levels of three circulating ECM related proteins (COL11A1, COL10A1 and SPARC) in plasma samples of lung cancer patients and in healthy heavy-smokers controls and test whether such measurements have diagnostic or prognostic value. METHODS: Gene expression profiling of lung fibroblasts isolated from paired normal and cancer tissue of NSCLC patients was performed by gene expression microarrays. The prioritization of the candidates for the study of circulating proteins in plasma was based on the most differentially expressed genes in cancer associated fibroblasts. Soluble ECM proteins were assessed by western blot in the conditioned medium of lung fibroblasts and by ELISA assays in plasma samples. RESULTS: Plasma samples from lung cancer patients and healthy heavy-smokers controls were tested for levels of COL11A1 and COL10A1 (n = 57 each) and SPARC (n = 90 each). Higher plasma levels of COL10A1 were detected in patients (p ≤ 0.001), a difference that was driven specifically by females (p < 0.001). No difference in COL11A1 levels between patients and controls was found. SPARC levels were also higher in plasma patients than controls (p < 0.001) with good performance in discriminating the two groups (AUC = 0.744). No significant association was observed between plasma proteins levels and clinicopathological features or survival. CONCLUSION: Soluble factors related to proficient tumor-stroma cross-talk are detectable in plasma of primary lung cancer patients and may represent a valuable complementary diagnostic tool to discriminate lung cancer patients from healthy heavy-smokers individuals as shown for the SPARC protein.

MiR-16 regulates the pro-tumorigenic potential of lung fibroblasts through the inhibition of HGF production in an FGFR-1- and MEK1-dependent manner.

BACKGROUND: Fibroblasts are crucial mediators of tumor-stroma cross-talk through synthesis and remodeling of the extracellular matrix and production of multiple soluble factors. Nonetheless, little is still known about specific determinants of fibroblast pro-tumorigenic activity in lung cancer. Here, we aimed at understanding the role of miRNAs, which are often altered in stromal cells, in reprogramming fibroblasts towards a tumor-supporting phenotype. METHODS: We employed a co-culture-based high-throughput screening to identify specific miRNAs modulating the pro-tumorigenic potential of lung fibroblasts. Multiplex assays and ELISA were instrumental to study the effect of miRNAs on the secretome of both primary and immortalized lung fibroblasts from lung cancer patients and to evaluate plasmatic levels of HGF in heavy smokers. Direct mRNA targeting by miRNAs was investigated through dual-luciferase reporter assay and western blot. Finally, the pro-tumorigenic activity of fibroblasts and their conditioned media was tested by employing in vitro migration experiments and mouse xenografts. RESULTS: We identified miR-16 as a master regulator of fibroblast secretome and showed that its upregulation reduces HGF secretion by fibroblasts, impairing their capacity to promote cancer cell migration. This effect is due to a pleiotropic activity of miR-16 which prevents HGF expression through direct inhibition of FGFR-1 signaling and targeting of HGF mRNA. Mechanistically, miR-16 targets FGFR-1 downstream mediator MEK1, thus reducing ERK1/2 activation. Consistently, chemical or genetic inhibition of FGFR-1 mimics miR-16 activity and prevents HGF production. Of note, we report that primary fibroblast cell lines derived from lungs of heavy smokers express reduced miR-16 levels compared to those from lungs not exposed to smoke and that HGF concentration in heavy smokers' plasma correlates with levels of tobacco exposure. Finally, in vivo experiments confirmed that restoration of miR-16 expression in fibroblasts reduced their ability to promote tumor growth and that HGF plays a central role in the pro-tumorigenic activity of fibroblasts. CONCLUSIONS: Overall, these results uncover a central role for miR-16 in regulating HGF production by lung fibroblasts, thus affecting their pro-tumorigenic potential. Correlation between smoking exposure and miR-16 levels could provide novel clues regarding the formation of a tumor-proficient milieu during the early phases of lung cancer development.

Extracellular matrix proteins as diagnostic markers of breast carcinoma.

Changes in amount and composition of extracellular matrix (ECM) are considered a hallmark of tumor development. We tested the hypothesis that abnormal production of ECM components leads to blood-released ECM molecules representing tumor circulating biomarkers. Candidate genes were selected through class comparison in two publicly available datasets and confirmed in paired normal and tumor associated fibroblasts from breast carcinoma (BC) specimens. Production and release of ECM molecules were evaluated in normal human dermal fibroblasts (NHDFs) treated with conditioned media from three BC cell lines. Plasma samples from healthy donors and from patients with malignant or benign breast disease were tested by ELISA for the presence of collagen 11a1 (COL11A1), collagen oligomeric matrix protein (COMP), and collagen 10a1 (COL10A1). Selected ECM molecules were investigated by IHC in malignant and benign specimens. In silico analysis of gene expression profiles identified 11 ECM genes significantly up-regulated in tumor versus normal tissue. Western blot analyses revealed increased levels of molecules encoded by three of these genes, COL11A1, COMP, and COL10A1, in cell lysates and supernatants of conditioned NHDFs. Class comparison and class prediction analyses of two independent series of human plasma samples identified the combination of COL11A1, COMP, and COL10A1 as potentially informative in discriminating BC patients from those with benign disease. The three molecules resulted expressed in the stroma of BC tissue samples. Our results indicate that circulating COL11A1, COMP, and COL10A1 may be useful in diagnostic assessment of suspicious breast nodules and ECM molecules could represent an avenue to biomarker identification.

Proposal of supervised data analysis strategy of plasma miRNAs from hybridisation array data with an application to assess hemolysis-related deregulation.

BACKGROUND: Plasma miRNAs have the potential as cancer biomarkers but no consolidated guidelines for data mining in this field are available. The purpose of the study was to apply a supervised data analysis strategy in a context where prior knowledge is available, i.e., that of hemolysis-related miRNAs deregulation, so as to compare our results with existing evidence. RESULTS: We developed a structured strategy with innovative applications of existing bioinformatics methods for supervised analyses including: 1) the combination of two statistical (t- and Anderson-Darling) test results to detect miRNAs with significant fold change or general distributional differences in class comparison, which could reveal hidden differential biological processes worth to be considered for building predictive tools; 2) a bootstrap selection procedure together with machine learning techniques in class prediction to guarantee the transferability of results and explore the interconnections among the selected miRNAs, which is important for highlighting their inherent biological dependences. The strategy was applied to develop a classifier for discriminating between hemolyzed and not hemolyzed plasma samples, defined according to a recently published hemolysis score. We identified five miRNAs with increased expression in hemolyzed plasma samples (miR-486-5p, miR-92a, miR-451, miR-16, miR-22). CONCLUSIONS: We identified four miRNAs previously reported in the literature as hemolysis related together with a new one (miR-22).which needs further investigations. Our findings confirm the validity of the proposed strategy and, in parallel, the hemolysis score capability to be used as pre-analytic hemolysis detector. R codes for implementing the approaches are provided.

Secondary electrospray ionization-mass spectrometry and a novel statistical bioinformatic approach identifies a cancer-related profile in exhaled breath of breast cancer patients: a pilot study.

Breath analysis represents a new frontier in medical diagnosis and a powerful tool for cancer biomarker discovery due to the recent development of analytical platforms for the detection and identification of human exhaled volatile compounds. Statistical and bioinformatic tools may represent an effective complement to the technical and instrumental enhancements needed to fully exploit clinical applications of breath analysis. Our exploratory study in a cohort of 14 breast cancer patients and 11 healthy volunteers used secondary electrospray ionization-mass spectrometry (SESI-MS) to detect a cancer-related volatile profile. SESI-MS full-scan spectra were acquired in a range of 40-350 mass-to-charge ratio (m/z), converted to matrix data and analyzed using a procedure integrating data pre-processing for quality control, and a two-step class prediction based on machine-learning techniques, including a robust feature selection, and a classifier development with internal validation. MS spectra from exhaled breath showed an individual-specific breath profile and high reciprocal homogeneity among samples, with strong agreement among technical replicates, suggesting a robust responsiveness of SESI-MS. Supervised analysis of breath data identified a support vector machine (SVM) model including 8 features corresponding to m/z 106, 126, 147, 78, 148, 52, 128, 315 and able to discriminate exhaled breath from breast cancer patients from that of healthy individuals, with sensitivity and specificity above 0.9.Our data highlight the significance of SESI-MS as an analytical technique for clinical studies of breath analysis and provide evidence that our noninvasive strategy detects volatile signatures that may support existing technologies to diagnose breast cancer.

Microenvironment-Modulated Metastatic CD133+/CXCR4+/EpCAM- Lung Cancer-Initiating Cells Sustain Tumor Dissemination and Correlate with Poor Prognosis.

Metastasis is the main reason for lung cancer-related mortality, but little is known about specific determinants of successful dissemination from primary tumors and metastasis initiation. Here, we show that CD133(+)/CXCR4(+) cancer-initiating cells (CIC) directly isolated from patient-derived xenografts (PDX) of non-small cell lung cancer are endowed with superior ability to seed and initiate metastasis at distant organs. We additionally report that CXCR4 inhibition successfully prevents the increase of cisplatin-resistant CD133(+)/CXCR4(+) cells in residual tumors and their metastatization. Immunophenotypic analysis of lung tumor cells intravenously injected or spontaneously disseminated to murine lungs demonstrated the survival advantage and increased colonization ability of a specific subset of CD133(+)/CXCR4(+) with reduced expression of epithelial cell adhesion molecule (EpCAM(-)), which also shows the greatest in vitro invasive potential. We next prove that recovered disseminated cells from lungs of PDX-bearing mice enriched for CD133(+)/CXCR4(+)/EpCAM(-) CICs are highly tumorigenic and metastatic. Importantly, microenvironment stimuli eliciting epithelial-to-mesenchymal transition, including signals from cancer-associated fibroblasts, are able to increase the dissemination potential of lung cancer cells through the generation of the CD133(+)/CXCR4(+)/EpCAM(-) subset. These findings also have correlates in patient samples where disseminating CICs are enriched in metastatic lymph nodes (20-fold, P = 0.006) and their detection in primary tumors is correlated with poor clinical outcome (disease-free survival: P = 0.03; overall survival: P = 0.05). Overall, these results highlight the importance of specific cellular subsets in the metastatic process, the need for in-depth characterization of disseminating tumor cells, and the potential of therapeutic strategies targeting both primary tumor and tumor-microenvironment interactions.