Each year millions of pulmonary nodules are discovered by computed tomography and subsequently biopsied. As the majority of these nodules are benign, many patients undergo unnecessary and costly invasive procedures. We present a 13-protein blood-based classifier that differentiates malignant and benign nodules with high confidence, thereby providing a diagnostic tool to avoid invasive biopsy on benign nodules. Using a systems biology strategy, 371 protein candidates were identified and a multiple reaction monitoring (MRM) assay was developed for each. The MRM assays were applied in a three-site discovery study (n = 143) on plasma samples from patients with benign and Stage IA cancer matched on nodule size, age, gender and clinical site, producing a 13-protein classifier. The classifier was validated on an independent set of plasma samples (n = 104), exhibiting a high negative predictive value (NPV) of 90%. Validation performance on samples from a non-discovery clinical site showed NPV of 94%, indicating the general effectiveness of the classifier. A pathway analysis demonstrated that the classifier proteins are likely modulated by a few transcription regulators (NF2L2, AHR, MYC, FOS) that are associated with lung cancer, lung inflammation and oxidative stress networks. The classifier score was independent of patient nodule size, smoking history and age, which are risk factors used for clinical management of pulmonary nodules. Thus this molecular test can provide a powerful complementary tool for physicians in lung cancer diagnosis.

Purpose Indeterminate pulmonary nodules (IPNs) lack clinical or radiographic features of benign etiologies and often undergo invasive procedures unnecessarily, suggesting potential roles for diagnostic adjuncts using molecular biomarkers. The primary objective was to validate a multivariate classifier that identifies likely benign lung nodules by assaying plasma protein expression levels, yielding a range of probability estimates based on high negative predictive values (NPVs) for patients with 8 to 30 mm IPNs. Methods A retrospective, multi-center, case-control study was performed using multiple reaction monitoring mass spectrometry, a classifier comprising 5 diagnostic and 6 normalization proteins, and blinded analysis of an independent validation set of plasma samples. Results The classifier achieved validation on 141 lung nodule-associated plasma samples based on predefined statistical goals to optimize sensitivity. Using a population based NSCLC prevalence estimate of 23% for 8 to 30 mm IPNs, the classifier identified likely benign lung nodules with 90% NPV and 26% PPV, as shown in our prior work, at 92% sensitivity and 20% specificity, with the lower bound of the classifier’s performance at 70% sensitivity and 48% specificity. Classifier scores for the overall cohort were statistically independent of patient age, tobacco use, nodule size and COPD diagnosis. The classifier also demonstrated incremental diagnostic performance in combination with a four-parameter clinical model. Conclusions This proteomic classifier provides a range of probability estimates for the likelihood of a benign etiology that may serve as a non-invasive, diagnostic adjunct for clinical assessments of patients with IPNs.

Chromosome 3p was reported by previous studies as one of the regions showing strong evidence of linkage with schizophrenia. We performed a fine-mapping association study of a 6-Mb high-LD and gene-rich region on 3p in a Southern Chinese sample of 489 schizophrenia patients and 519 controls to search for susceptibility genes. In the initial screen, 4 SNPs out of the 144 tag SNPs genotyped were nominally significant (P < 0.05). One of the most significant SNPs (rs3732530, P = 0.0048) was a non-synonymous SNP in the neuroglycan C (NGC, also known as CSPG5) gene, which belongs to the neuregulin family. The gene prioritization program Endeavor ranked NGC 8th out of the 129 genes in the 6-Mb region and the highest among the genes within the same LD block. Further genotyping of NGC revealed 3 more SNPs to be nominally associated with schizophrenia. Three other genes (NRG1, ErbB3, ErbB4) involved in the neuregulin pathways were subsequently genotyped. Interaction analysis by multifactor dimensionality reduction (MDR) revealed a significant two-SNP interaction between NGC and NRG1 (P = 0.015) and three-SNP interactions between NRG1 and ErbB4 (P = 0.009). The gene NGC is exclusively expressed in the brain. It is implicated in neurodevelopment in rats and was previously shown to promote neurite outgrowth. Methamphetamine, a drug that may induce psychotic symptoms, was reported to alter the expression of NGC. Taken together, these results suggest that NGC may be a novel candidate gene, and neuregulin signaling pathways may play an important role in schizophrenia.

PurposeGoblet cells may represent a potentially successful adaptive response to acid and bile by producing a thick mucous barrier that protects against cancer development in Barrett's esophagus (BE). The aim of this study was to determine the relationship between goblet cells (GC) and risk of progression to adenocarcinoma, and DNA content flow cytometric abnormalities, in BE patients.Experimental DesignBaseline mucosal biopsies (N=2988) from 213 patients, 32 of whom developed cancer during the follow up period, enrolled in a prospective dynamic cohort of BE patients were scored in a blinded fashion, for the total number (#) of GC, mean # of GC/crypt (GC density), # of crypts with ≥ 1 GC, and the proportion of crypts with ≥1 GC, in both dysplastic and non-dysplastic epithelium separately. The relationship between these four GC parameters and DNA content flow cytometric abnormalities and adenocarcinoma outcome was compared, after adjustment for age, gender, and BE segment length.ResultsHigh GC parameters were inversely associated with DNA content flow cytometric abnormalities, such as aneuploidy, ploidy >2.7N, and an elevated 4N fraction > 6%, and with risk of adenocarcinoma. However, a Kaplan-Meier analysis showed that the total # of GC and the total # crypts with ≥1 GC were the only significant GC parameters (p<0.001 and 0.003, respectively).ConclusionsThe results of this study show, for the first time, an inverse relationship between high GC counts and flow cytometric abnormalities and risk of adenocarcinoma in BE. Further studies are needed to determine if GC depleted foci within esophageal columnar mucosa are more prone to neoplastic progression or whether loss of GC occurs secondary to underlying genetic abnormalities.

Objective-The objective of this study was to test the association between calpain-10 (CAPN10), a diabetes susceptibility gene, with risk of pancreatic cancer (PC).Methods-DNA samples from 83 incident exocrine PC cases and 166 controls, all of whom were smokers, were genotyped for four markers of CAPN10 in a nested case-control study based on the Beta-Carotene and Retinol Efficacy Trial (CARET), a randomized chemoprevention trial of subjects at high risk of lung cancer. Controls were matched on sex, race, age, CARET intervention arm, duration of exposure to asbestos, and smoking history. Conditional logistic regression was used for statistical analyses.Results-The minor allele of SNP-43 (rs3792267) in intron 3 was associated with increased risk of PC with an odds ratio of 1.57 (95%CI 1.03-2.38, p = 0.035) per allele. The three markers of the highest risk haplotype had an odds ratio of 1.98 (95%CI 1.12-3.49, p=0.019) for risk of PC compared to the most common haplotype. There was no evidence of interaction between either of these associations by diabetes status.Conclusion-These results suggest that variation in CAPN10 may be associated with increased risk of PC among smokers. Thus, studies of genes associated with diabetes risk in PC are warranted in a larger population.

The purpose of this study was to evaluate evidence for linkage to interrelated quantitative features of the metabolic syndrome (MetS). Data on eight quantitative MetS traits (body weight, waist circumference, systolic and diastolic blood pressure, high-density lipoprotein (HDL) cholesterol, triglycerides (TGs), and fasting glucose and insulin measurements) and a 10 cM genome scan were available for 78 white families (n = 532 subjects). These data were used to conduct multipoint, multivariate linkage analyses, including tests for coincident linkage and complete pleiotropy. The strongest evidence for linkage from the bivariate analyses was observed on chromosome 1 (1p22.2) (HDL-TG; univariate lod score equivalent (lod eq = 3.99)) with stronger results from the trivariate analysis at the same location (HDL-TG-Insulin; lod eq = 4.32). Seven additional susceptibility regions (lod eq scores >1.9) were observed (1p36, 1q23, 2q21.2, 8q23.3, 14q23.2, 14q32.11, and 20p11.21). The results from this study indicate that several correlated traits of the MetS are influenced by the same gene(s) that account for some of the clustering of the MetS features.

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