Linda Passmore

PURPOSE: Improving outcomes for early-stage lung cancer is a major research focus at present because a significant proportion of stage I patients develop recurrent disease within 5 years of curative-intent lung resection. Within tumor stage groups, conventional prognostic indicators currently fail to predict relapse accurately. EXPERIMENTAL DESIGN: To identify a gene signature predictive of recurrence in primary lung adenocarcinoma, we analyzed gene expression profiles in a training set of 48 node-negative tumors (stage I-II), comparing tumors from cases who remained disease-free for a minimum of 36 months with those from cases whose disease recurred within 18 months of complete resection. RESULTS: Cox proportional hazards modeling with leave-one-out cross-validation identified a 54-gene signature capable of predicting risk of recurrence in two independent validation cohorts of 55 adenocarcinomas [log-rank P=0.039; hazard ratio (HR), 2.2; 95% confidence interval (95% CI), 1.1-4.7] and 40 adenocarcinomas (log-rank P=0.044; HR, 3.3; 95% CI, 1.4-7.9). Kaplan-Meier log-rank analysis found that predicted poor-outcome groups had significantly shorter survival, and furthermore, the signature predicted outcome independently of conventional indicators of tumor stage and node stage. In a subset of earliest stage adenocarcinomas, generally expected to have good outcome, the signature predicted samples with significantly poorer survival. CONCLUSIONS: We describe a 54-gene signature that predicts the risk of recurrent disease independently of tumor stage and which therefore has potential to refine clinical prognosis for patients undergoing resection for primary adenocarcinoma of the lung.

Lung cancer remains the leading cause of cancer death worldwide. Overall 5-year survival is approximately 10-15% and despite curative intent surgery, treatment failure is primarily due to recurrent disease. Conventional prognostic markers are unable to determine which patients with completely resected disease within each stage group are likely to relapse. To identify a gene signature associated with recurrent squamous cell carcinoma (SCC) of lung, we analyzed primary tumor gene expression for a total of 51 SCCs (Stages I-III) on 22 323 element microarrays, comparing expression profiles for individuals who remained disease-free for a minimum of 36 months with those from individuals whose disease recurred within 18 months of complete resection. Cox proportional hazards modeling with leave-one-out cross-validation identified a 71-gene signature capable of predicting the likelihood of tumor recurrence and a 79-gene signature predictive for cancer-related death. These two signatures were pooled to generate a 111-gene signature which achieved an overall predictive accuracy for disease recurrence of 72% (77% sensitivity, 67% specificity) in an independent set of 58 (Stages I-III SCCs). This signature also predicted differences in survival [log-rank P=0.0008; hazard ratio (HR), 3.8; 95% confidence interval (CI), 1.6-8.7], and was superior to conventional prognostic markers such as TNM stage or N stage in predicting patient outcome. Genome-wide profiling has revealed a distinct gene-expression profile for recurrent lung SCC which may be clinically useful as a prognostic tool.

MicroRNAs (miRNAs) are a family of small, non-coding RNA species functioning as negative regulators of multiple target genes including tumour suppressor genes and oncogenes. Many miRNA gene loci are located within cancer-associated genomic regions. To identify potential new amplified oncogenic and/or deleted tumour suppressing miRNAs in lung cancer, we inferred miRNA gene dosage from high dimensional arrayCGH data. From miRBase v9.0 (http://microrna.sanger.ac.uk), 474 human miRNA genes were physically mapped to regions of chromosomal loss or gain identified from a high-resolution genome-wide arrayCGH study of 132 primary non-small cell lung cancers (NSCLCs) (a training set of 60 squamous cell carcinomas and 72 adenocarcinomas). MiRNAs were selected as candidates if their immediately flanking probes or host gene were deleted or amplified in at least 25% of primary tumours using both Analysis of Copy Errors algorithm and fold change (≥ ± 1.2) analyses. Using these criteria, 97 miRNAs mapped to regions of aberrant copy number. Analysis of three independent published lung cancer arrayCGH datasets confirmed that 22 of these miRNA loci showed directionally concordant copy number variation. MiR-218, encoded on 4p15.31 and 5q35.1 within two host genes (SLIT2 and SLIT3), in a region of copy number loss, was selected as a priority candidate for follow-up as it is reported as underexpressed in lung cancer. We confirmed decreased expression of mature miR-218 and its host genes by qRT-PCR in 39 NSCLCs relative to normal lung tissue. This downregulation of miR-218 was found to be associated with a history of cigarette smoking, but not human papilloma virus. Thus, we show for the first time that putative lung cancer-associated miRNAs can be identified from genome-wide arrayCGH datasets using a bioinformatics mapping approach, and report that miR-218 is a strong candidate tumour suppressing miRNA potentially involved in lung cancer.

BACKGROUND: The diagnosis of malignant pleural effusions (MPE) is often clinically challenging, especially if the cytology is negative for malignancy. DNA integrity index has been reported to be a marker of malignancy. The aim of this study was to evaluate the utility of pleural fluid DNA integrity index in the diagnosis of MPE. METHODS: We studied 75 pleural fluid and matched serum samples from consecutive subjects. Pleural fluid and serum ALU DNA repeats [115bp, 247bp and 247bp/115bp ratio (DNA integrity index)] were assessed by real-time quantitative PCR. Pleural fluid and serum mesothelin levels were quantified using ELISA. RESULTS: Based on clinico-pathological evaluation, 52 subjects had MPE (including 16 mesotheliomas) and 23 had benign effusions. Pleural fluid DNA integrity index was higher in MPE compared with benign effusions (1.2 vs. 0.8; p<0.001). Cytology had a sensitivity of 55% in diagnosing MPE. If cytology and pleural fluid DNA integrity index were considered together, they exhibited 81% sensitivity and 87% specificity in distinguishing benign and malignant effusions. In cytology-negative pleural effusions (35 MPE and 28 benign effusions), elevated pleural fluid DNA integrity index had an 81% positive predictive value in detecting MPEs. In the detection of mesothelioma, at a specificity of 90%, pleural fluid DNA integrity index had similar sensitivity to pleural fluid and serum mesothelin (75% each respectively). CONCLUSION: Pleural fluid DNA integrity index is a promising diagnostic biomarker for identification of MPEs, including mesothelioma. This biomarker may be particularly useful in cases of MPE where pleural aspirate cytology is negative, and could guide the decision to undertake more invasive definitive testing. A prospective validation study is being undertaken to validate our findings and test the clinical utility of this biomarker for altering clinical practice.