Faculty Bibliography

The objective of this study is to assess the impact on nodule detection and efficiency using a computer-aided detection (CAD) device seamlessly integrated into a commercially available picture archiving and communication system (PACS). Forty-eight consecutive low-dose thoracic computed tomography studies were retrospectively included from an ongoing multi-institutional screening study. CAD results were sent to PACS as a separate image series for each study. Five fellowship-trained thoracic radiologists interpreted each case first on contiguous 5 mm sections, then evaluated the CAD output series (with CAD marks on corresponding axial sections). The standard of reference was based on three-reader agreement with expert adjudication. The time to interpret CAD marking was automatically recorded. A total of 134 true-positive nodules, measuring 3 mm and larger were included in our study; with 85 >/= 4 and 50 >/= 5 mm in size. Readers detection improved significantly in each size category when using CAD, respectively, from 44 to 57 % for >/=3 mm, 48 to 61 % for >/=4 mm, and 44 to 60 % for >/=5 mm. CAD stand-alone sensitivity was 65, 68, and 66 % for nodules >/=3, >/=4, and >/=5 mm, respectively, with CAD significantly increasing the false positives for two readers only. The average time to interpret and annotate a CAD mark was 15.1 s, after localizing it in the original image series. The integration of CAD into PACS increases reader sensitivity with minimal impact on interpretation time and supports such implementation into daily clinical practice.

There is an unmet need for circulating biomarkers that can detect early-stage lung cancer. Here we show that a variant form of the nuclear matrix-associated DNA replication factor Ciz1 is present in 34/35 lung tumors but not in adjacent tissue, giving rise to stable protein quantifiable by Western blot in less than a microliter of plasma from lung cancer patients. In two independent sets, with 170 and 160 samples, respectively, variant Ciz1 correctly identified patients who had stage 1 lung cancer with clinically useful accuracy. For set 1, mean variant Ciz1 level in individuals without diagnosed tumors established a threshold that correctly classified 98% of small cell lung cancers (SCLC) and non-SCLC patients [receiver operator characteristic area under the curve (AUC) 0.958]. Within set 2, comparison of patients with stage 1 non-SCLC with asymptomatic age-matched smokers or individuals with benign lung nodules correctly classified 95% of patients (AUCs 0.913 and 0.905), with overall specificity of 76% and 71%, respectively. Moreover, using the mean of controls in set 1, we achieved 95% sensitivity among patients with stage 1 non-SCLC patients in set 2 with 74% specificity, demonstrating the robustness of the classification. RNAi-mediated selective depletion of variant Ciz1 is sufficient to restrain the growth of tumor cells that express it, identifying variant Ciz1 as a functionally relevant driver of cell proliferation in vitro and in vivo. The data show that variant Ciz1 is a strong candidate for a cancer-specific single marker capable of identifying early-stage lung cancer within at-risk groups without resort to invasive procedures.

It is currently not known whether most lung cancers detected by computerized tomography (CT) screening are aggressive and likely to be fatal if left untreated, or if a sizable fraction are indolent and unlikely to cause death during the natural lifetime of the individual. We developed a longitudinal biologically-based model of the relationship between individual smoking histories and the probability for lung cancer incidence, CT screen detection, lung cancer mortality, and other-cause mortality. The longitudinal model relates these different outcomes to an underlying lung cancer disease pathway and an effective other-cause mortality pathway, which are both influenced by the individual smoking history. The longitudinal analysis provides additional information over that available if these outcomes were analyzed separately, including testing if the number of CT detected and histologically-confirmed lung cancers is consistent with the expected number of lung cancers "in the pipeline". We assume indolent nodules undergo Gompertz growth and are detectable by CT, but do not grow large enough to contribute significantly to symptom-based lung cancer incidence or mortality. Likelihood-based model calibration was done jointly to data from 6878 heavy smokers without asbestos exposure in the control (placebo) arm of the Carotene and Retinol Efficacy Trial (CARET); and to 3,642 heavy smokers with comparable smoking histories in the Pittsburgh Lung Screening Study (PLuSS), a single-arm prospective trial of low-dose spiral CT screening for diagnosis of lung cancer. Model calibration was checked using data from two other single-arm prospective CT screening trials, the New York University Lung Cancer Biomarker Center (NYU) (n=1,021), and Moffitt Cancer Center (Moffitt) cohorts (n=677). In the PLuSS cohort, we estimate that at the end of year 2, after the baseline and first annual CT exam, that 33.0 (26.9, 36.9)% of diagnosed lung cancers among females and 7.0 (4.9,11.7)% among males were overdiagnosed due to being indolent cancers. At the end of the PLuSS study, with maximum follow-up of 5.8years, we estimate that due to early detection by CT and limited follow-up, an additional 2.2 (2.0,2.4)% of all diagnosed cancers among females and 7.1 (6.7,8.0)% among males would not have been diagnosed in the absence of CT screening. We also find a higher apparent cure rate for lung cancer among CARET females than males, consistent with the larger indolent fraction of CT detected and histologically confirmed lung cancers among PLuSS females. This suggests that there are significant gender differences in the aggressiveness of lung cancer. Females may have an inherently higher proportion of indolent lung cancers than males, or aggressive lung cancers may be brought into check by the immune system more frequently among females than males.

BACKGROUND: The WTC collapse exposed over 300,000 people to high concentrations of WTC-PM; particulates up to approximately 50 mm were recovered from rescue workers' lungs. Elevated MDC and GM-CSF independently predicted subsequent lung injury in WTC-PM-exposed workers. Our hypotheses are that components of WTC dust strongly induce GM-CSF and MDC in AM; and that these two risk factors are in separate inflammatory pathways. METHODOLOGY/PRINCIPAL FINDINGS: Normal adherent AM from 15 subjects without WTC-exposure were incubated in media alone, LPS 40 ng/mL, or suspensions of WTC-PM(10-53) or WTC-PM(2.5) at concentrations of 10, 50 or 100 microg/mL for 24 hours; supernatants assayed for 39 chemokines/cytokines. In addition, sera from WTC-exposed subjects who developed lung injury were assayed for the same cytokines. In the in vitro studies, cytokines formed two clusters with GM-CSF and MDC as a result of PM(10-53) and PM(2.5). GM-CSF clustered with IL-6 and IL-12(p70) at baseline, after exposure to WTC-PM(10-53) and in sera of WTC dust-exposed subjects (n = 70) with WTC lung injury. Similarly, MDC clustered with GRO and MCP-1. WTC-PM(10-53) consistently induced more cytokine release than WTC-PM(2.5) at 100 microg/mL. Individual baseline expression correlated with WTC-PM-induced GM-CSF and MDC. CONCLUSIONS: WTC-PM(10-53) induced a stronger inflammatory response by human AM than WTC-PM(2.5). This large particle exposure may have contributed to the high incidence of lung injury in those exposed to particles at the WTC site. GM-CSF and MDC consistently cluster separately, suggesting a role for differential cytokine release in WTC-PM injury. Subject-specific response to WTC-PM may underlie individual susceptibility to lung injury after irritant dust exposure.

OBJECTIVES/SPECIFIC AIMS: The lung is classically thought to be sterile although molecular techniques for microbial identification are now suggesting the existence of a human airway microbiota. The study of the microbiome has now opened an opportunity to characterize resident microbial flora without the need for bacterial culture although the lung microbiome in smokers has not been characterized. We therefore tested the hypothesis that in smokers, the upper and lower airways contain a distinct microbiota. METHODS/STUDY POPULATION: We obtained supraglotic and broncho-alveolar lavage (BAL) samples in 8 subjects. Bacterial quantification of supraglotic aspirate and BAL was determined by qPCR using universal primers for 16S rDNA. Dilution was corrected by urea. We defined bacteria OTU by 454 sequencing. We performed cluster analysis, principal coordinate analysis and weighted UniFrac to determine microbiome. RESULTS/ANTICIPATED RESULTS: Subjects were 55 +/- 13 yo, 4/8 female and 7/8 significant smokers (>10 pack/year). FEV1 was 94 +/- 11%, FVC 108 +/- 10% and FEV1/FVC was 71 +/- 8. Bacteria rDNA was higher in the supraglotic area than BAL (1.5e9 +/- 3.2e9 vs. 1e7 +/- 8.2e6 copies/mL of adjusted fluid, p < 0.001). Clustering of the bacterial community at the family level showed distinct microbiome in the upper airway and the lung (BAL). While Prevotellaceae, Veillonellaceae and Fusobacteriaceae predominated in the supraglotic sample, Micrococcaceae, Propionibacteriaceae and Staphylococcaceae among others predominated in BAL. UniFrac calculated distances showed no overlapping circle of inertia between supraglotic and BAL (p < 0.0001 for first principal axis). DISCUSSION/SIGNIFICANCE OF IMPACT: In the absence of signs or symptoms of infection, subjects had significant airway resident bacteria. Th is supports the existence of a bacterial reservoir in the lung, which might be influenced by smoking and/or innate immunity

BACKGROUND: Low-dose computed tomography (CT) for lung cancer screening can reduce lung cancer mortality. The National Lung Screening Trial reported a 20% reduction in lung cancer mortality in high-risk smokers. However, CT scanning is extremely sensitive and detects non-calcified nodules (NCNs) in 24-50% of subjects, suggesting an unacceptably high false-positive rate. We hypothesized that by reviewing demographic, clinical and nodule characteristics, we could identify risk factors associated with the presence of nodules on screening CT, and with the probability that a NCN was malignant. METHODS: We performed a longitudinal lung cancer biomarker discovery trial (NYU LCBC) that included low-dose CT-screening of high-risk individuals over 50 years of age, with more than 20 pack-year smoking histories, living in an urban setting, and with a potential for asbestos exposure. We used case-control studies to identify risk factors associated with the presence of nodules (n = 625) versus no nodules (n = 557), and lung cancer patients (n = 30) versus benign nodules (n = 128). RESULTS: The NYU LCBC followed 1182 study subjects prospectively over a 10-year period. We found 52% to have NCNs >4 mm on their baseline screen. Most of the nodules were stable, and 9.7% of solid and 26.2% of sub-solid nodules resolved. We diagnosed 30 lung cancers, 26 stage I. Three patients had synchronous primary lung cancers or multifocal disease. Thus, there were 33 lung cancers: 10 incident, and 23 prevalent. A sub-group of the prevalent group were stable for a prolonged period prior to diagnosis. These were all stage I at diagnosis and 12/13 were adenocarcinomas. CONCLUSIONS: NCNs are common among CT-screened high-risk subjects and can often be managed conservatively. Risk factors for malignancy included increasing age, size and number of nodules, reduced FEV1 and FVC, and increased pack-years smoking. A sub-group of screen-detected cancers are slow-growing and may contribute to over-diagnosis and lead-time biases.