Sanjib Basu

PTEN, RASSF1 and DAPK site-specific hypermethylation and outcome in surgically treated stage I and II nonsmall cell lung cancer patients.

The primary objective of this study is to identify prognostic site‐specific epigenetic changes in surgically treated Stage I and II nonsmall cell lung cancer (NSCLC) patients by quantifying methylation levels at multiple CpG sites within each gene promoter. Paraffin‐embedded tumors from stage Ib, IIa and IIb in training and validation groups of 75 and 57 surgically treated NSCLC patients, respectively, were analyzed for p16, MGMT, RASSF1, RASSF5, CDH1, LET7, DAPK and PTEN promoter hypermethylation. Hypermethylation status was quantified individually at multiple CpG sites within each promoter by pyrosequencing. Molecular and clinical characteristics with time to recurrence (TTR) and overall survival (OS) were evaluated. Overall average promoter methylation levels of MGMT and RASSF1 were significantly higher in smokers than in nonsmokers (p = 0.006 and p = 0.029, respectively). Methylation levels of the p16 promoter were significantly higher in squamous cell carcinoma than in adenocarcinoma (p = 0.020). In univariate analysis, hypermethylation of RASSF1 at CpG sites −53 and −48 and PTEN at CpG site −1310 were the significantly associated with shorter TTR (p = 0.002 and p < 0.000, respectively). Hypermethylation of PTEN at −1310 and DAPK at −1482 were most significantly associated with outcome in multivariate analysis. These results show that methylation of specific promoter CpG sites in PTEN, RASSF1 and DAPK is associated with outcome in early stage surgically treated NSCLC.

Development of a Multiplexed Tumor-Associated Autoantibody-Based Blood Test for the Detection of Non–Small Cell Lung Cancer

Purpose: Non–small cell lung cancer (NSCLC) has an overall 5-year survival of <15%; however, the 5-year survival for stage I disease is over 50%. Unfortunately, 75% of NSCLC is diagnosed at an advanced stage not amenable to surgery. A convenient serum assay capable of unambiguously identifying patients with NSCLC may provide an ideal diagnostic measure to complement computed tomography–based screening protocols. Experimental Design: Standard immunoproteomic method was used to assess differences in circulating autoantibodies among lung adenocarcinoma patients relative to cancer-free controls. Candidate autoantibodies identified by these discovery phase studies were translated into Luminex-based “direct-capture” immunobead assays along with 10 autoantigens with previously reported diagnostic value. These assays were then used to evaluate a second patient cohort composed of four discrete populations, including: 117 NSCLC (81 T1-2N0M0 and 36 T1-2N1-2M0), 30 chronic obstructive pulmonary disorder (COPD)/asthma, 13 nonmalignant lung nodule, and 31 “normal” controls. Multivariate statistical methods were then used to identify the optimal combination of biomarkers for classifying patient disease status and develop a convenient algorithm for this purpose. Results: Our immunoproteomic-based biomarker discovery efforts yielded 16 autoantibodies differentially expressed in NSCLC versus control serum. Thirteen of the 25 analytes tested showed statistical significance (Mann-Whitney P < 0.05 and a receiver operator characteristic “area under the curve” over 0.65) when evaluated against a second patient cohort. Multivariate statistical analyses identified a six-biomarker panel with only a 7% misclassification rate. Conclusions: We developed a six-autoantibody algorithm for detecting cases of NSCLC among several high-risk populations. Population-based validation studies are now required to assign the true value of this tool for identifying early-stage NSCLC. Clin Cancer Res; 16(13); 3452–62. ©2010 AACR.

Meniscal Allograft Size Can Be Predicted by Height, Weight, and Gender

PURPOSE Our purpose was to determine if height, weight, and gender can be used to accurately predict proper meniscal allograft dimensions. METHODS Data were obtained from the Joint Restoration Foundation (AlloSource, Centennial, CO) regarding meniscal size and patient characteristics from meniscal donors. Donor height, weight, sex, age, and anatomic meniscal dimensions were recorded for 930 donor menisci in 664 patients. Multivariate regressions were completed using gender, height, and weight as independent variables and lateral meniscus length, lateral meniscus width, medial meniscus length, and medial meniscus width as dependent variables. The regression formulas were then reapplied to the data in order to produce estimated meniscus dimensions based on donor height, weight, and gender. A 90:10 split of the data was used to validate the regression models. Predicted meniscal size was then compared to actual meniscal size and the results compared to current measurement techniques. RESULTS Regression formulas showed the ability to predict meniscal size based on gender, height, and weight with standard deviations (SDs) equal to or less than current radiographic techniques (SD, 6.4% to 8.2%). Average differences between predicted size and actual size ranged from 5.2% to 6.5% for length and 5.2% to 6.0% for width. Patient height was found to be a much more powerful predictor of meniscal size than patient weight. Data from the 90:10 split of data validated the model on an independent sample. These validated outputs were then compared to contemporary techniques and found to have lower SDs and average error rates in the majority of cases. CONCLUSIONS We have proposed a validated regression model that uses height, weight, and gender variables to accurately predict required allograft meniscal size. We compared it against previously published data for radiographic and magnetic resonance imaging sizing techniques and found it to produce results that were, overall, slightly more accurate. CLINICAL RELEVANCE This model provides a novel method for sizing meniscal allografts.

The Potential Predictive Value of Cyclooxygenase-2 Expression and Increased Risk of Gastrointestinal Hemorrhage in Advanced Non-Small Cell Lung Cancer Patients Treated with Erlotinib and Celecoxib

Purpose: Celecoxib, a cyclooxygenase-2 (COX-2) inhibitor, potentiates antitumor effects of erlotinib in preclinical studies, and COX-2 is frequently expressed in non–small cell lung cancer (NSCLC). With these observations, we designed a phase II trial to evaluate the efficacy and safety of erlotinib plus celecoxib in advanced NSCLC. Experimental Design: Previously treated stage IIIB/IV NSCLC patients were given celecoxib at 400 mg orally twice daily and erlotinib at 150 mg orally daily until disease progression. Planned accrual was 40 patients. Tissue was collected for epidermal growth factor receptor (EGFR) analysis and COX-2 immunohistochemistry. Results: Twenty-six patients were enrolled (17 men, 9 women; median age, 66 years). Eighteen and 21 patients had tissue available for EGFR analysis and COX-2 immunohistochemistry, respectively. The median progression-free survival (PFS) and overall survival were 2.0 and 9.2 months, respectively. Eleven of 21 patients tested had increased tumor COX-2 expression, which was strongly associated with prolonged PFS (P = 0.048). Four patients on anticoagulation or with a history of peptic ulcer disease had grade 3/grade 4 upper gastrointestinal bleeding (GIB), prompting early study closure. Three patients with GIB had endoscopy that found peptic ulcers. Conclusions: The combination of erlotinib and celecoxib does not seem superior to erlotinib alone in unselected patients. However, longer PFS with high-tumor COX-2 expression suggests that trials of EGFR and COX-2 inhibitors may be warranted in this patient subset. GIB observed in our trial supports excluding patients with a history of peptic ulcer disease or those requiring therapeutic anticoagulation from future EGFR and COX-2 inhibitor studies.

Bayesian analysis for masked system failure data using non-identical Weibull models

In ideal circumstances, failure time data for a K component series system contain the time to failure along with information on the exact component responsible for the system failure. These data then can be used to estimate system and component reliabilities. In many cases, however, due to cost and time constraints, the exact component causing the system failure is not identified, but the cause of failure is only narrowed down to a subsystem or a smaller set of components. A Bayesian analysis is developed in this article for such masked data from a general K component system. The theoretical failure times for the K components are assumed to have independent Weibull distributions. These K Weibulls can have different scale and shape parameters, thus allowing wide flexibility into the model. Further flexibility is introduced in the choice of the prior. Three different prior models are proposed. They can model different prior beliefs and can further provide a vehicle to check for robustness with respect to the prior. A Gibbs sampling based method is described to perform the relevant Bayesian computations. The proposed model is applied to data on a system unit of a particular type of IBM PS/2 models.

Bayesian analysis of competing risks with partially masked cause of failure

Summary. Bayesian analysis of system failure data from engineering applications under a competing risks framework is considered when the cause of failure may not have been exactly identified but has only been narrowed down to a subset of all potential risks. In statistical literature, such data are termed masked failure data. In addition to masking, failure times could be right censored owing to the removal of prototypes at a prespecified time or could be interval censored in the case of periodically acquired readings. In this setting, a general Bayesian formulation is investigated that includes most commonly used parametric lifetime distributions and that is sufficiently flexible to handle complex forms of censoring. The methodology is illustrated in two engineering applications with a special focus on model comparison issues.

Establishment of a multi-analyte serum biomarker panel to identify lymph node metastases in non-small cell lung cancer.

Introduction: In non-small cell lung cancer (NSCLC), the presence of locoregional lymph node metastases remains the most important prognostic factor and significantly guides treatment regimens. Unfortunately, currently-available noninvasive staging modalities have limited accuracy. The objective of this study was to create a multianalyte blood test capable of discriminating a patient’s true (pathologic) nodal status preoperatively. Methods: Pretreatment serum specimens collected from 107 NSCLC patients with localized disease were screened with 47 biomarkers implicated in disease presence or progression. Multivariate statistical algorithms were then used to identify the optimal combination of biomarkers for accurately discerning each patient’s nodal status. Results: We identified 15 candidate biomarkers that met our criteria for statistical relevance in discerning a patient’s preoperative nodal status. A ‘random forest’ classification algorithm was used with these parameters to define a 6-analyte panel, consisting of macrophage inflammatory protein-1α, carcinoembryonic antigen, stem cell factor, tumor necrosis factor-receptor I, interferon-γ, and tumor necrosis factor-α, that was the optimum combination of biomarkers for identifying a patient’s pathologic nodal status. A Classification and Regression Tree analysis was then created with this panel that was capable of correctly classifying 88% of the patients tested, relative to the pathologic assessments. This value is in contrast to our observed 85% classification rate using conventional clinical methods. Conclusions: This study establishes a serum biomarker panel with efficacy in discerning preoperative nodal status. With further validation, this blood test may be useful for assessing nodal status (including occult disease) in NSCLC patients facing tumor resection therapy.

Repeat pulmonary resection for metachronous colorectal carcinoma is beneficial

BACKGROUND Initial pulmonary metastatectomy for limited colorectal carcinoma metastases is associated with improved survival. The role of repeat thoracic interventions is less well defined. The purpose of this study is to clarify the role of repeat pulmonary resection for metastatic colorectal carcinoma. METHODS A retrospective study was performed using patients who underwent pulmonary metastatectomy for colorectal carcinoma at a single academic institution between January 1, 1985, and December 31, 2007. Sex, age at colorectal operation, colorectal TNM stage, and operative procedures for pulmonary metastases were recorded. Intervals between the original colorectal operation and thoracic operation and between the first pulmonary metastatectomy and repeat thoracic interventions were calculated. Log-rank comparison of Kaplan-Meier survival curves and covariate analysis were performed. RESULTS A total of 69 patients were identified as having undergone at least 1 pulmonary metastatectomy. There were 32 female and 37 male patients with a mean age of 57 +/- 11 years. The median disease-free interval from original colorectal operation to first pulmonary metastatectomy for all the patients was 27 months. A total of 125 pulmonary resections were performed: 64 wedge resections, 27 segmentectomies, 30 lobectomies, and 4 pneumonectomies. Of the 69 patients, 41 underwent a single thoracic metastatectomy, whereas 28 underwent at least 1 second thoracic metastatectomy (2nd, 17 patients; 3rd, 6; 4th, 4; 5th, 1). There were no perioperative mortalities. From the original colorectal resection, the 5-year survival was 59% (median, 52 months). From the initial pulmonary metastatectomy, the 5-year survival for all patients was 25% (median, 36 months). The 5-year survival for patients undergoing only 1 thoracic resection was 23% (median, 24 months), which was not significantly different compared to patients undergoing repeat thoracic resections, 29% (median: 42 months). In the covariate analysis, no parameters significantly impacted survival. CONCLUSIONS Patients undergoing multiple pulmonary resections have the same survival as patients undergoing a single pulmonary resection for metachronous colorectal carcinoma. These findings indicate pulmonary metastases may be favorably treated with repeat thoracic interventions.

The prognostic value of chromosome 7 polysomy in non-small cell lung cancer patients treated with gefitinib.

Introduction: Specific subpopulations of non-small cell lung cancer (NSCLC) patients defined by clinical features and molecular profiles seem to derive greater benefit from epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors, but no general consensus on molecular testing to optimize treatment has emerged. The objective of this study was to evaluate chromosome 7 polysomy and other potential indicators of gefitinib efficacy in advanced NSCLC patients. Methods: Paraffin-embedded tumors from 82 patients treated with gefitinib were analyzed by immunohistochemistry for expression of EGFR and other markers, and by fluorescence in situ hybridization for EGFR gene or chromosome copy number. Mutational status was assessed by single-strand conformational polymorphism, sequence-specific polymerase chain reaction, and direct sequencing. Molecular and clinical characteristics were evaluated in relation to objective response (OR), progression-free survival (PFS), and overall survival (OS). Results: EGFR mutational status (p = 0.002), never smoking (p = 0.052), and chromosome 7 polysomy (p = 0.029) were significant indicators of OR. EGFR mutation, pAKT or PTEN expression, and chromosome 7 polysomy were associated with longer OS. There was a significant difference in OS between the chromosome 7 polysomy groups (p = 0.015) and the groups with both chromosome 7 polysomy and pAkt+ (p = 0.002) and both chromosome7 polysomy and PTEN+ (p = 0.04). In a stepwise proportional hazards analysis, chromosome 7 polysomy and PTEN+ expression were both significantly associated with longer OS (p = 0.004 and 0.017 respectively). Conclusion: These results suggest that further study of chromosome 7 polysomy and of pAKT and PTEN expression in patients treated with EGFR tyrosine kinase inhibitors is warranted in developing a clinical test for selecting patients for gefitinib therapy.

Development and validation of a plasma biomarker panel for discerning clinical significance of indeterminate pulmonary nodules.

Introduction: The recent findings of the National Lung Screening Trial showed 24.2% of individuals at high risk for lung cancer having one or more indeterminate nodules detected by low-dose computed tomography–based screening, 96.4% of which were eventually confirmed as false positives. These positive scans necessitate additional diagnostic procedures to establish a definitive diagnosis that adds cost and risk to the paradigm. A plasma test able to assign benign versus malignant pathology in high-risk patients would be an invaluable tool to complement low-dose computed tomography–based screening and promote its rapid implementation. Methods: We evaluated 17 biomarkers, previously shown to have value in detecting lung cancer, against a discovery cohort, comprising benign (n = 67) cases and lung cancer (n = 69) cases. A Random Forest method based analysis was used to identify the optimal biomarker panel for assigning disease status, which was then validated against a cohort from the Mayo Clinic, comprising patients with benign (n = 61) or malignant (n = 20) indeterminate lung nodules. Results: Our discovery efforts produced a seven-analyte plasma biomarker panel consisting of interleukin 6 (IL-6), IL-10, IL-1ra, sIL-2R&agr;, stromal cell-derived factor-1&agr;+&bgr;, tumor necrosis factor &agr;, and macrophage inflammatory protein 1 &agr;. The sensitivity and specificity of our panel in our validation cohort is 95.0% and 23.3%, respectively. The validated negative predictive value of our panel was 93.8%. Conclusion: We developed a seven-analyte plasma biomarker panel able to identify benign nodules, otherwise deemed indeterminate, with a high degree of accuracy. This panel may have clinical utility in risk-stratifying screen-detected lung nodules, decrease unnecessary follow-up imaging or invasive procedures, and potentially avoid unnecessary morbidity, mortality, and health care costs.