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.

A serum-based molecular predictor identifies asymptomatic pregnant women at risk of spontaneous preterm delivery, which may provide utility in identifying women at risk at an early stage of pregnancy to allow for clinical intervention. This early detection would guide enhanced levels of care and accelerate development of clinical strategies to prevent preterm delivery.

Brucella virulence is linked to components of the cell envelope and tightly connected to the function of the BvrR/BvrS sensory-regulatory system. To quantify the impact of BvrR/BvrS on cell envelope proteins, we performed a label-free mass spectrometry-based proteomic analysis of spontaneously released outer membrane fragments from four strains of Brucella abortus (wild type virulent, avirulent bvrR- and bvrS- mutants as well as reconstituted virulent bvrR+ (bvrR-/pbvrR+)). We identified 167 differentially expressed proteins, of which 25 were assigned to the outer membrane. Approximately half of the outer membrane proteins decreased in abundance, whereas half increased. Notably, expression of five Omp3 family proteins decreased whereas five lipoproteins increased in the mutant strains. In the periplasmic space, by contrast, approximately 80% of the 60 differentially expressed proteins were increased in at least one avirulent mutant. Periplasmic proteins are primarily involved in substrate uptake and transport, and a uniform increase in this class may indicate a nutritional stress response, possibly a consequence of defective outer membrane function. Virtually all proteins reverted to wild type levels in the reconstituted virulent bvrR+ strain. We propose that the wide changes in cell envelope protein expression relate to the markedly avirulent phenotype of bvrR- and bvrS- mutants and that Brucella virulence depends on regulatory networks involving cell envelope and metabolism rather than on discrete virulence factors. This model may be relevant to other alpha-Proteobacteria harboring BvrR/BvrS orthologous systems known to be essential for parasitism or endosymbiosis.

BACKGROUND:Pulmonary nodules (PNs) are a common reason for referral to pulmonologists. The majority of data for the evaluation and management of PNs is derived from studies performed in academic medical centers. Little is known about the prevalence and diagnosis of PNs, the use of diagnostic testing, or the management of PNs by community pulmonologists.METHODS:This multicenter observational record review evaluated 377 patients aged 40 to 89 years referred to 18 geographically diverse community pulmonary practices for intermediate PNs (8-20 mm). Study measures included the prevalence of malignancy, procedure/test use, and nodule pretest probability of malignancy as calculated by two previously validated models. The relationship between calculated pretest probability and management decisions was evaluated.RESULTS:The prevalence of malignancy was 25% (n = 94). Nearly one-half of the patients (46%, n = 175) had surveillance alone. Biopsy was performed on 125 patients (33.2%). A total of 77 patients (20.4%) underwent surgery, of whom 35% (n = 27) had benign disease. PET scan was used in 141 patients (37%). The false-positive rate for PET scan was 39% (95% CI, 27.1%-52.1%). Pretest probability of malignancy calculations showed that 9.5% (n = 36) were at a low risk, 79.6% (n = 300) were at a moderate risk, and 10.8% (n = 41) were at a high risk of malignancy. The rate of surgical resection was similar among the three groups (17%, 21%, 17%, respectively; P = .69).CONCLUSIONS:A substantial fraction of intermediate-sized nodules referred to pulmonologists ultimately prove to be lung cancer. Despite advances in imaging and nonsurgical biopsy techniques, invasive sampling of low-risk nodules and surgical resection of benign nodules remain common, suggesting a lack of adherence to guidelines for the management of PNs.

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ClinicalTrials.gov; No.: NCT01752114; URL: www.clinicaltrials.gov).

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Proteomics research programs typically comprise the identification of protein content of any given cell, their isoforms, splice variants, post-translational modifications, interacting partners and higher-order complexes under different conditions. These studies present significant analytical challenges owing to the high proteome complexity and the low abundance of the corresponding proteins, which often requires highly sensitive and resolving techniques. Mass spectrometry plays an important role in proteomics and has become an indispensable tool for molecular and cellular biology. However, the analysis of mass spectrometry data can be a daunting task in view of the complexity of the information to decipher, the accuracy and dynamic range of quantitative analysis, the availability of appropriate bioinformatics software and the overwhelming size of data files. The past ten years have witnessed significant technological advances in mass spectrometry-based proteomics and synergy with bioinformatics is vital to fulfill the expectations of biological discovery programs. We present here the technological capabilities of mass spectrometry and bioinformatics for mining the cellular proteome in the context of discovery programs aimed at trace-level protein identification and expression from microgram amounts of protein extracts from human tissues.