Shared Nearest Neighbors Approach and Interactive Browser for Network Analysis of a Comprehensive Non-Small-Cell Lung Cancer Data Set

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LC–MS/MS determination of D-mannose in human serum as a potential cancer biomarker

Several metabolites in human serum have been identified as potential cancer biomarkers for early detection. This study focuses on the LC–MS/MS method development and validation of D-mannose in human serum. Surrogate blank serum, coupled with stable isotope D-mannose-13C6, as internal standard, was used for generating standard curves ranging from 1 to 50 μg/mL. Separation was achieved by an Agilent 1200 series HPLC equipped with a SUPELCOGELTM Pb, 6% Crosslinked column with HPLC water as a mobile phase at flow rate of 0.5 mL/min at 80 °C. Mass detection was performed under negative ionization electrospray. Inter- and intra-day accuracy and precision were \u3c2%. The extraction recovery and matrix effect were 104.1%–105.5% and 97.0%–100.0%, respectively. This method was successfully applied for the quantification of D-mannose in the serum samples of 320 esophageal cancer patients and 323 healthy volunteers. We report a simple, specific and reproducible LC–MS/MS method for the quantification of D-mannose in human serum as a potential cancer biomarker

Detection of ABCC1 expression in classical Hodgkin lymphoma is associated with increased risk of treatment failure using standard chemotherapy protocols

BACKGROUND: The mechanisms responsible for chemoresistance in patients with refractory classical Hodgkin lymphoma (CHL) are unknown. ATP-binding cassette (ABC) transporters confer multidrug resistance in various cancers and ABCC1 overexpression has been shown to contribute to drug resistance in the CHL cell line, KMH2. FINDINGS: We analyzed for expression of five ABC transporters ABCB1, ABCC1, ABCC2, ABCC3 and ABCG2 using immunohistochemistry in 103 pre-treatment tumor specimens obtained from patients with CHL. All patients received first-line standard chemotherapy with doxorubicin (Adriamycin®), bleomycin, vinblastine, and dacarbazine (ABVD) or equivalent regimens. ABCC1 was expressed in Hodgkin and Reed-Sternberg (HRS) cells in 16 of 82 cases (19.5%) and ABCG2 was expressed by HRS cells in 25 of 77 cases (32.5%). All tumors were negative for ABCB1, ABCC2 and ABCC3. ABCC1 expression was associated with refractory disease (p = 0.01) and was marginally associated with poorer failure-free survival (p = 0.06). Multivariate analysis after adjusting for hemoglobin and albumin levels and age showed that patients with CHL with HRS cells positive for ABCC1 had a higher risk of not responding to treatment (HR = 2.84, 95%, CI: 1.12-7.19 p = 0.028). CONCLUSIONS: Expression of ABCC1 by HRS cells in CHL patients predicts a higher risk of treatment failure and is marginally associated with poorer failure-free survival using standard frontline chemotherapy regimens

Global and targeted serum metabolic profiling of colorectal cancer progression

BACKGROUND: Patients with colorectal adenoma polyps (PLPs) are at higher risk for developing colorectal cancer (CRC). However, the development of improved and robust biomarkers to enable the screening, surveillance, and early detection of PLPs and CRC continues to be a challenge. The aim of this study was to identify biomarkers of progression to CRC through metabolomic profiling of human serum samples with a multistage approach. METHODS: Metabolomic profiling was conducted with the Metabolon platform for 30 CRC patients, 30 PLP patients, and 30 control subjects, and this was followed by the targeted validation of the top metabolites in an additional set of 50 CRC patients, 50 PLP patients, and 50 controls with liquid chromatography–tandem mass spectrometry. Unconditional multivariate logistic regression models, adjusted for covariates, were used to evaluate associations with PLP and CRC risk. RESULTS: For the discovery phase, 404 serum metabolites were detected, with 50 metabolites showing differential levels between CRC patients, PLP patients, and controls (P for trend \u3c.05). After validation, the 3 top metabolites (xanthine, hypoxanthine, and d-mannose) were validated: lower levels of xanthine and hypoxanthine and higher levels of d-mannose were found in PLP and CRC cases versus controls. A further exploratory analysis of metabolic pathways revealed key roles for the urea cycle and caffeine metabolism associated with PLP and CRC risk. In addition, a joint effect of the top metabolites with smoking and a significant interaction with the body mass index were observed. An analysis of the ratio of hypoxanthine levels to xanthine levels indicated an association with CRC progression. CONCLUSIONS: These results suggest the potential utility of circulating metabolites as novel biomarkers for the early detection of CRC. Cancer 2017;123:4066-74. © 2017 American Cancer Society

Multiplex Tissue Imaging Harmonization: A Multicenter Experience from CIMAC-CIDC Immuno-Oncology Biomarkers Network

PurposeThe Cancer Immune Monitoring and Analysis Centers - Cancer Immunologic Data Commons (CIMAC-CIDC) network supported by the NCI Cancer Moonshot initiative was established to provide correlative analyses for clinical trials in cancer immunotherapy, using state-of-the-art technology. Fundamental to this initiative is implementation of multiplex IHC assays to define the composition and distribution of immune infiltrates within tumors in the context of their potential role as biomarkers. A critical unanswered question involves the relative fidelity of such assays to reliably quantify tumor-associated immune cells across different platforms.Experimental designThree CIMAC sites compared across their laboratories: (i) image analysis algorithms, (ii) image acquisition platforms, (iii) multiplex staining protocols. Two distinct high-dimensional approaches were employed: multiplexed IHC consecutive staining on single slide (MICSSS) and multiplexed immunofluorescence (mIF). To eliminate variables potentially impacting assay performance, we completed a multistep harmonization process, first comparing assay performance using independent protocols followed by the integration of laboratory-specific protocols and finally, validating this harmonized approach in an independent set of tissues.ResultsData generated at the final validation step showed an intersite Spearman correlation coefficient (r) of ≥0.85 for each marker within and across tissue types, with an overall low average coefficient of variation ≤0.1.ConclusionsOur results support interchangeability of protocols and platforms to deliver robust, and comparable data using similar tissue specimens and confirm that CIMAC-CIDC analyses may therefore be used with confidence for statistical associations with clinical outcomes largely independent of site, antibody selection, protocol, and platform across different sites