Initiation and maintenance of several cancers including glioblastoma (GBM) may be driven by a small subset of cells called cancer stem cells (CSCs). CSCs may provide a repository of cells in tumor cell populations that are refractory to chemotherapeutic agents developed for the treatment of tumors. STAT3 is a key transcription factor associated with regulation of multiple stem cell types. Recently, a novel autocrine loop (IL-6/STAT3/HIF1alpha) has been observed in multiple tumor types (pancreatic, prostate, lung, and colon). The objective of this study was to probe perturbations of this loop in a glioblastoma cancer stem cell line (GSC11) derived from a human tumor by use of a JAK2/STAT3 phosphorylation inhibitor (WP1193), IL-6 stimulation, and hypoxia. A quantitative phosphoproteomic approach that employed phosphoprotein enrichment, chemical tagging with isobaric tags, phosphopeptide enrichment, and tandem mass spectrometry in a high-resolution instrument was applied. A total of 3414 proteins were identified in this study. A rapid Western blotting technique (<1 h) was used to confirm alterations in key protein expression and phosphorylation levels observed in the mass spectrometric experiments. About 10% of the phosphoproteins were linked to the IL-6 pathway, and the majority of remaining proteins could be assigned to other interlinked networks. By multiple comparisons between the sample conditions, we observed expected changes and gained novel insights into the contribution of each factor to the IL6/STAT3/HIF1alpha autocrine loop and the CSC response to perturbations by hypoxia, inhibition of STAT3 phosphorylation, and IL-6 stimulation.

Background:Well-collected and well-documented sample repositories are necessary for disease biomarker development. The availability of significant numbers of samples with the associated patient information enables biomarker validation to proceed with maximum efficacy and minimum bias. The creation and utilization of such a resource is an important step in the development of blood-based biomarker tests for colorectal cancer. Methods: We have created a subject data and biological sample resource, Endoscopy II, which is based on 4698 individuals referred for diagnostic colonoscopy in Denmark between May 2010 and November 2012. Of the patients referred based on 1 or more clinical symptoms of colorectal neoplasia, 512 were confirmed by pathology to have colorectal cancer and 399 were confirmed to have advanced adenoma. Using subsets of these sample groups in case-control study designs (300 patients for colorectal cancer, 302 patients for advanced adenoma), 2 panels of plasma-based proteins for colorectal cancer and 1 panel for advanced adenoma were identified and validated based on ELISA data obtained for 28 proteins from the samples. Results: One of the validated colorectal cancer panels was comprised of 8 proteins (CATD, CEA, CO3, CO9, SEPR, AACT, MIF, and PSGL) and had a validation ROC curve area under the curve (AUC) of 0.82 (CI 0.75-0.88). There was no significant difference in the performance between early-and late-stage cancer. The advanced adenoma panel was comprised of 4 proteins (CATD, CLUS, GDF15, SAA1) and had a validation ROC curve AUC of 0.65 (CI 0.56 -0.74). Conclusions: These results suggest that the development of blood-based aids to colorectal cancer detection and diagnosis is feasible.

These results have demonstrated the ability of simultaneous assessment of candidate marker proteins using high-multiplex, targeted-mass spectrometry to identify a subset group of CRC markers with significant and meaningful performance.

BackgroundThe aim was to improve upon an existing blood-based colorectal cancer (CRC) test directed to high-risk symptomatic patients, by developing a new CRC classifier to be used with a new test embodiment. The new test uses a robust assay format—electrochemiluminescence immunoassays—to quantify protein concentrations. The aim was achieved by building and validating a CRC classifier using concentration measures from a large sample set representing a true intent-to-test (ITT) symptomatic population.Methods4435 patient samples were drawn from the Endoscopy II sample set. Samples were collected at seven hospitals across Denmark between 2010 and 2012 from subjects with symptoms of colorectal neoplasia. Colonoscopies revealed the presence or absence of CRC. 27 blood plasma proteins were selected as candidate biomarkers based on previous studies. Multiplexed electrochemiluminescence assays were used to measure the concentrations of these 27 proteins in all 4435 samples. 3066 patients were randomly assigned to the Discovery set, in which machine learning was used to build candidate classifiers. Some classifiers were refined by allowing up to a 25% indeterminate score range. The classifier with the best Discovery set performance was successfully validated in the separate Validation set, consisting of 1336 samples.ResultsThe final classifier was a logistic regression using ten predictors: eight proteins (A1AG, CEA, CO9, DPPIV, MIF, PKM2, SAA, TFRC), age, and gender. In validation, the indeterminate rate of the new panel was 23.2%, sensitivity/specificity was 0.80/0.83, PPV was 36.5%, and NPV was 97.1%.ConclusionsThe validated classifier serves as the basis of a new blood-based CRC test for symptomatic patients. The improved performance, resulting from robust concentration measures across a large sample set mirroring the ITT population, renders the new test the best available for this population. Results from a test using this classifier can help assess symptomatic patients’ CRC risk, increase their colonoscopy compliance, and manage next steps in their care.