Humberto Choi

Histologic and molecular characterization of lung cancer with tissue obtained by electromagnetic navigation bronchoscopy.

Background:Electromagnetic navigation bronchoscopy (ENB) is a catheter-based adjunct to standard bronchoscopic techniques for the sampling of lung lesions. We sought to evaluate the adequacy of ENB-obtained samples for histologic subtyping of lung cancer, epidermal growth factor receptor (EGFR) mutations, and echinoderm microtubule-associated protein-like 4-anaplastic lymphoma kinase (EML4-ALK) translocations. Methods:We retrospectively analyzed consecutive patients who underwent ENB for the diagnosis of lung lesions between 2008 and 2011. In those proven to be a primary lung cancer by ENB, tissue adequacy for histologic subtyping was recorded. Accuracy was determined by comparison with resected specimens when available. Tissue adequacy for EGFR mutation and/or EML4-ALK analyses was also reviewed. Results:Sixty-five ENB cases resulted in a diagnosis of lung cancer. Tissues obtained were adequate for histologic subtyping in all 65 cases. Forty-three (66.2%) were diagnosed with adenocarcinoma, 19 (29.2%) with squamous cell carcinoma, 3 (4.6%) with small cell carcinoma. In 51 cases (78.5%), subtyping was performed by morphology alone, whereas 11 (21.5%) required immunohistochemical staining. Sixteen of 65 tumors underwent surgical resection. Concordance of histologic subtyping between ENB and surgical specimens was 87.5% (14 tumors). ENB-obtained samples from 15 patients with adenocarcinoma were sent for EGFR mutation analysis, of which 14 (93.3%) were adequate. Samples from 2 patients were evaluated for EML4-ALK gene rearrangements, both of which were adequate for analysis. Conclusions:ENB is effective at obtaining tissue samples adequate for histologic subtyping, EGFR mutation, and EML4-ALK translocation analysis.

Frequency of Incidental Findings and Subsequent Evaluation in Low-Dose Computed Tomographic Scans for Lung Cancer Screening

Rationale: The U.S. Preventive Services Task Force recommends lung cancer screening with low‐dose chest computed tomographic scans (LDCT) for a well‐defined high‐risk population. Data on the frequency and impact of incidental findings (IFs) based on LDCT scans performed within a centralized lung cancer screening program have not been reported. Objectives: Researchers in previous studies have reported IFs in the setting of clinical trials. We present our findings in a real clinical setting where the decision to manage these findings may depend on factors that are not captured in a research trial such as disclosing IFs, patient preferences, severity of comorbidities, and physician expertise. Methods: We conducted a retrospective chart review of participants in the Cleveland Clinic Lung Cancer Screening Program from April 1, 2015, to February 17, 2016. Lung Imaging Reporting and Data System categories and all reported findings were extracted from the structured radiology report. Downstream investigations that occurred as a result of the imaging findings were recorded. Medicare reimbursement rates were documented for all screening‐related testing and treatment. Results: A total of 320 LDCT‐screened patients’ records were reviewed. The most commonly reported IFs were pulmonary (69.6%), cardiovascular (67.5%), and gastrointestinal (25.9%). Fifteen percent of the scans had an IF that resulted in further evaluation. The majority of patients who underwent further testing had cardiovascular findings (10.3%); less frequently, they had thyroid or adrenal nodules (2.1%), hepatic lesions (0.9%), renal masses (0.6%), or pulmonary disease (0.6%). The most frequently ordered investigations were echocardiography (n = 9), cardiac stress test (n = 9), and CT angiography (n = 6). Reimbursement for the screening process, evaluation, and treatment of screening‐detected findings averaged

Preoperative evaluation of the patient with lung cancer being considered for lung resection.

817 per screened patient. Conclusions: Clinically significant IFs on LDCT scans for lung cancer screening are common, and their potential impact should be included in the shared decision‐making process. Screening program staff should develop a standard approach for the evaluation of these findings and consider the financial impact when seeking infrastructure support for screening program implementation.

Progress in the Development of Volatile Exhaled Breath Signatures of Lung Cancer

Purpose of review This review summarizes the general approach to evaluating the cardiopulmonary fitness of a patient with lung cancer being considered for lung resection. Many patients have a high risk for morbidity and mortality from lung resection owing to severe comorbidities or low cardiopulmonary reserve. A comprehensive and individualized assessment is essential to identify the factors that may impact operative outcome. Recent findings Identification of comorbid conditions related to cigarette smoking, particularly cardiovascular diseases, is essential because they need to be managed in advance. In those with low predicted postoperative forced expiratory volume during first second (FEV1) or carbon monoxide diffusing capacity (DLCO), or impaired performance on a low-technology exercise test, cardiopulmonary exercise testing should be considered. Summary Preoperative assessment requires an understanding of the relative benefits and harms of available treatment options and consideration of patients’ values. A balance between the potential to cure ones cancer and the short-term and long-term risks of the selected treatment needs to be reached. All patients should have a baseline FEV1 and DLCO measured, and predicted postoperative FEV1 and DLCO calculated to assist with risk prediction. Measures of exercise performance can help to further risk stratify patients. Means of modifying the risks should be considered for all patients. Video abstract http://links.lww.com/COAN/A37

S100B and S100B autoantibody as biomarkers for early detection of brain metastases in lung cancer

RATIONALE Volatile organic compounds present in the exhaled breath have shown promise as biomarkers of lung cancer. Advances in colorimetric sensor array technology, breath collection methods, and clinical phenotyping may lead to the development of a more accurate breath biomarker. OBJECTIVES Perform a discovery-level assessment of the accuracy of a colorimetric sensor array-based volatile breath biomarker. METHODS Subjects with biopsy-confirmed untreated lung cancer, and others at risk for developing lung cancer, performed tidal breathing into a breath collection instrument designed to expose a colorimetric sensor array to the alveolar portion of the breath. Random forest models were built from the sensor output of 70% of the study subjects and were tested against the remaining 30%. Models were developed to separate cancer and subgroups from control, and to characterize the cancer. Additional models were developed after matching the clinical phenotypes of cancer and control subjects. MEASUREMENTS AND MAIN RESULTS Ninety-seven subjects with lung cancer and 182 control subjects participated. The accuracies, reported as C-statistics, for models of cancer and subgroups versus control ranged from 0.794 to 0.861. The accuracy was improved by developing models for cancer and control groups selected through propensity matching for clinical variables. A model built using only subjects from the largest available clinical subgroup (49 subjects) had a C-statistic of 0.982. Models developed and tested to characterize cancer histology, and to compare early- with late-stage cancer, had C-statistics of 0.881-0.960. CONCLUSIONS The colorimetric sensor array signature of exhaled breath volatile organic compounds was capable of distinguishing patients with lung cancer from clinically relevant control subjects in a discovery level trial. The incorporation of clinical phenotypes into the further development of this biomarker may optimize its accuracy.

Survival in patients with metachronous second primary lung cancer.

BACKGROUND S100B is an astrocytic protein that enters the blood stream when there is disruption of the blood-brain barrier (BBB). Over time, antibodies against S100B develop in the sera of patients who experience persistent or repeated BBB disruptions. We explored the use of serum S100B protein and S100B autoantibodies for the detection of brain metastasis in patients with lung cancer. METHODS One hundred and twenty eight untreated patients with lung cancer who had brain imaging performed as part of their routine evaluation, participated. Serum S100B protein levels were measured by direct ELISA and S100B autoantibody levels by reverse ELISA. These levels in patients with brain metastases were compared alone and in combination to those without brain metastases. RESULTS Eighteen (14%) patients had brain metastasis at the time of lung cancer diagnosis. An S100B cutoff of 0.058 ng/mL had a sensitivity of 89% and specificity of 43% for brain metastasis. When an autoantibody threshold of <2.00 absorbance units was used in conjunction with S100B, the sensitivity remained at 89%, and the specificity increased to 58%. The overall accuracy was 51% with S100B alone, improving to 62.5% when combined with autoantibodies. CONCLUSIONS Serum S100B and S100B autoantibody levels may help to identify which lung cancer patients have brain metastases.

Radon and lung cancer: assessing and mitigating the risk.

RATIONALE Four to 10% of patients with non-small cell lung cancer subsequently develop a metachronous second primary lung cancer. The decision to perform surveillance or screening imaging for patients with potentially cured lung cancer must take into account the outcomes expected when detecting metachronous second primaries. OBJECTIVES To assess potential survival differences between patients with metachronous second primary lung cancer compared to matched patients with first primary lung cancer. METHODS We retrospectively reviewed patients diagnosed with lung cancer at the Cleveland Clinic (2006-2010). Metachronous second primary lung cancer was defined as lung cancer diagnosed after a 4-year, disease-free interval from the first lung cancer, or if there were two different histologic subtypes diagnosed at different times. Patients with first primary lung cancer diagnosed in the same time period served as control subjects. Propensity score matching was performed using age, sex, smoking history, histologic subtype, and collaborative stage, with a 1:3 case-control ratio. Survival analyses were performed by Cox proportional hazards modeling and Kaplan-Meier estimates. MEASUREMENTS AND MAIN RESULTS Forty-four patients met criteria for having a metachronous second primary lung cancer. There were no statistically significant differences between case subjects and control subjects in prognostic variables. The median survival time and 2-year overall survival rate for the metachronous second primary group, compared with control subjects, were as follows: 11.8 versus 18.4 months (P = 0.18) and 31.0 versus 40.9% (P = 0.28). The survival difference was largest in those with stage I metachronous second primaries (median survival time, 26.8 vs. 60.4 mo, P = 0.09; 2-year overall survival, 56.3 vs. 71.2%, P = 0.28). CONCLUSIONS Patients with stage I metachronous second primary lung cancer may have worse survival than those who present with a first primary lung cancer. This could influence the benefit-risk balance of screening the high-risk cohort with a previously treated lung cancer.

Medical Diagnoses Associated with Substance Dependence among Inpatients at a Large Urban Hospital

Radon is a naturally occurring radioactive gas. Its progenies emit alpha particles capable of causing tissue damage. Radon exposure is estimated to be the second most common cause of lung cancer in the United States. Management of patients with a history of radon exposure should involve a lung cancer specialist. Radon exposure is the second most common cause of lung cancer, but the evidence so far does not support screening for lung cancer in people exposed to it.

Evaluation of a Serum Lung Cancer Biomarker Panel

Background There are limited data on reasons for hospital admission among patients dependent on substances other than alcohol. We compared primary discharge diagnoses for heroin- or cocaine-dependent patients to non-dependent patients. Material and Methods We evaluated a cohort of patients admitted to a general medicine service at a public teaching hospital during July 2005-June 2008. Through bedside interviews, we identified patients who had substance-use disorders. We categorized patients by substance used, route of administration, and dependent or non-dependent use. We grouped diagnostic codes (i.e., ICD-9) using Healthcare Utilization Project categories. We excluded HIV-infected patients. Results Of 11,397 patients, 341 (3.0%) were dependent on inhalational heroin, 260 (2.3%) on non-injection cocaine, and 106 (0.9%) on injection heroin. Compared to non-dependent patients, inhalational heroin-dependent patients were over three-fold more likely to have been admitted for respiratory diseases (28% vs. 8%, p<0.01); this association was strongest for asthma exacerbation (OR=7.0; 95% CI, 4.7 to 70.4, p<0.01). Of the 225 admissions for an asthma exacerbation, 44 (19.6%) had co-occurrent heroin-dependence. The most frequent diagnostic category among cocaine-dependent patients was circulatory, which was similar to non-dependent patients (22% vs. 21%, p=0.92). Discussion There is a strong association between heroin dependence and hospital admission for an asthma exacerbation. Provision of specialized substance-use treatment for inhalational heroin users will be necessary to reduce the frequency of exacerbations and repeat hospital admissions.

RaPtomics: Integrating radiomic and pathomic features for predicting recurrence in early stage lung cancer

Background: A panel of 3 serum proteins and 1 autoantibody has been developed to assist with the detection of lung cancer. We aimed to validate the accuracy of the biomarker panel in an independent test set and explore the impact of adding a fourth serum protein to the panel, as well as the impact of combining molecular and clinical variables. Methods: The training set of serum samples was purchased from commercially available biorepositories. The testing set was from a biorepository at the Cleveland Clinic. All lung cancer and control subjects were >50 years old and had smoked a minimum of 20 pack-years. A panel of biomarkers including CEA (carcinoembryonic antigen), CYFRA21-1 (cytokeratin-19 fragment 21-1), CA125 (carbohydrate antigen 125), HGF (hepatocyte growth factor), and NY-ESO-1 (New York esophageal cancer-1 antibody) was measured using immunoassay techniques. The multiple of the median method, multivariate logistic regression, and random forest modeling was used to analyze the results. Results: The training set consisted of 604 patient samples (268 with lung cancer and 336 controls) and the testing set of 400 patient samples (155 with lung cancer and 245 controls). With a threshold established from the training set, the sensitivity and specificity of both the 4- and 5-biomarker panels on the testing set was 49% and 96%, respectively. Models built on the testing set using only clinical variables had an area under the receiver operating characteristic curve of 0.68, using the biomarker panel 0.81 and by combining clinical and biomarker variables 0.86. Conclusions: This study validates the accuracy of a panel of proteins and an autoantibody in a population relevant to lung cancer detection and suggests a benefit to combining clinical features with the biomarker results.