Active screening for lung cancer increases smoking abstinence in Australia.

BACKGROUND: Smoking cessation is an important screening component, but the evidence base to inform implementation is lacking. We report longitudinal smoking behavior in an Australian screening cohort and examine predictor variables associated with continued smoking. METHODS: Healthy current or former smokers (quit less than 15 years and ≥30-pack year smoking history) aged 60-74 years underwent CT screening at baseline, year 1 and year 2. Participants received brief smoking cessation advice and generic Quitline materials. Smoking status was self-reported every 6 months for 5 years. Mediators of smoking behavior, adjusted for sociodemographic, health and scan variables were explored using logistic regression modeling. RESULTS: Two hundred thirty-five participants were analyzed. One hundred eight (46%) were current smokers at enrolment. At baseline, current smokers' mean Fagerström Test for Nicotine Dependence was 4.9, and they had higher levels of lung cancer-specific distress and passive smoke exposure than former smokers. At 36 months, 33% of baseline smokers achieved sustained (≥6 months) smoking abstinence. Five (4%) former smokers relapsed at any point during the study. Continued smoking was positively associated with greater nicotine dependence and smoking pack-years, and negatively associated with cardiovascular disease, stroke, and lung cancer family history. CONCLUSIONS: This study provides the first data on smoking cessation rates in Australian lung cancer screenees and supports screening as a teachable moment. We identify several factors that identify smokers who may require more intensive smoking cessation interventions and could be used to develop effective smoking cessation as part of lung cancer screening, tailored to individual risk profiles.

USPSTF2013 versus PLCOm2012 lung cancer screening eligibility criteria (International Lung Screening Trial): interim analysis of a prospective cohort study.

BACKGROUND: Lung cancer is a major health problem. CT lung screening can reduce lung cancer mortality through early diagnosis by at least 20%. Screening high-risk individuals is most effective. Retrospective analyses suggest that identifying individuals for screening by accurate prediction models is more efficient than using categorical age-smoking criteria, such as the US Preventive Services Task Force (USPSTF) criteria. This study prospectively compared the effectiveness of the USPSTF2013 and PLCOm2012 model eligibility criteria. METHODS: In this prospective cohort study, participants from the International Lung Screening Trial (ILST), aged 55-80 years, who were current or former smokers (ie, had ≥30 pack-years smoking history or ≤15 quit-years since last permanently quitting), and who met USPSTF2013 criteria or a PLCOm2012 risk threshold of at least 1·51% within 6 years of screening, were recruited from nine screening sites in Canada, Australia, Hong Kong, and the UK. After enrolment, patients were assessed with the USPSTF2013 criteria and the PLCOm2012 risk model with a threshold of at least 1·70% at 6 years. Data were collected locally and centralised. Main outcomes were the comparison of lung cancer detection rates and cumulative life expectancies in patients with lung cancer between USPSTF2013 criteria and the PLCOm2012 model. In this Article, we present data from an interim analysis. To estimate the incidence of lung cancers in individuals who were USPSTF2013-negative and had PLCOm2012 of less than 1·51% at 6 years, ever-smokers in the Prostate Lung Colorectal and Ovarian Cancer Screening Trial (PLCO) who met these criteria and their lung cancer incidence were applied to the ILST sample size for the mean follow-up occurring in the ILST. This trial is registered at ClinicalTrials.gov, NCT02871856. Study enrolment is almost complete. FINDINGS: Between June 17, 2015, and Dec 29, 2020, 5819 participants from the International Lung Screening Trial (ILST) were enrolled on the basis of meeting USPSTF2013 criteria or the PLCOm2012 risk threshold of at least 1·51% at 6 years. The same number of individuals was selected for the PLCOm2012 model as for the USPSTF2013 criteria (4540 [78%] of 5819). After a mean follow-up of 2·3 years (SD 1·0), 135 lung cancers occurred in 4540 USPSTF2013-positive participants and 162 in 4540 participants included in the PLCOm2012 of at least 1·70% at 6 years group (cancer sensitivity difference 15·8%, 95% CI 10·7-22·1%; absolute odds ratio 4·00, 95% CI 1·89-9·44; p<0·0001). Compared to USPSTF2013-positive individuals, PLCOm2012-selected participants were older (mean age 65·7 years [SD 5·9] vs 63·3 years [5·7]; p<0·0001), had more comorbidities (median 2 [IQR 1-3] vs 1 [1-2]; p<0·0001), and shorter life expectancy (13·9 years [95% CI 12·8-14·9] vs 14·8 [13·6-16·0] years). Model-based difference in cumulative life expectancies for those diagnosed with lung cancer were higher in those who had PLCOm2012 risk of at least 1·70% at 6 years than individuals who were USPSTF2013-positive (2248·6 years [95% CI 2089·6-2425·9] vs 2000·7 years [1841·2-2160·3]; difference 247·9 years, p=0·015). INTERPRETATION: PLCOm2012 appears to be more efficient than the USPSTF2013 criteria for selecting individuals to enrol into lung cancer screening programmes and should be used for identifying high-risk individuals who benefit from the inclusion in these programmes. FUNDING: Terry Fox Research Institute, The UBC-VGH Hospital Foundation and the BC Cancer Foundation, the Alberta Cancer Foundation, the Australian National Health and Medical Research Council, Cancer Research UK and a consortium of funders, and the Roy Castle Lung Cancer Foundation for the UK Lung Screen Uptake Trial.

Validation of the Eighth Edition TNM Lung Cancer Staging System.

INTRODUCTION: We performed a validation study at our institution, the International Union Against Cancer (Union for International Cancer Control latest version of TNM Classification of Malignant Tumors Eighth Edition). METHODS: Data were collected from the Queensland Oncology Online registry of NSCLC or SCLC cases between 2000 and 2015 and validated against the Queensland Integrated Lung Cancer Outcomes Project registry using case identification number, first name, last name, and date of birth. Where data were available, cases were classified according to the Union for International Cancer Control TNM seventh edition stage groupings and then compared with the eighth edition groupings. Kaplan-Meier curves were plotted, and the log-rank test of survival differences was performed with SPSS version 25 (IBM Corp, Armonk, NY). RESULTS: Of the 3636 cases, 3352 and 1031 had complete clinical and pathologic staging, respectively. Median survival time was found to reduce with increasing clinical stage: seventh edition (IA: 88, IB: 44, IIA: 31, IIB: 18, IIIA: 15, IIIB: 8, and IV: 5 mo) versus eighth edition TNM stage (IA1: not reached, IA2: 88, IA3: 53, IB: 56, IIA: 36, IIB: 22, IIIA: 14, IIIB: 9, IIIC: 8, IVA: 6, and IVB: 3 mo). A similar overall pattern was reflected in the pathologic stage: seventh edition (IA: 124, IB: 110, IIA: 48, IIB: 42, IIIA: 26, IIIB: 31, and IV: 27 mo) versus eighth edition (IA1: not reached, IA2: 122, IA3: 125, IB: 144, IIA: 98, IIB: 57, IIIA: 31, IIIB: 24, and IVA: 7 mo). The log-rank test for survival curves was significant at p < 0.001. CONCLUSIONS: Our external validation study confirms the prognostic accuracy of the eighth edition TNM lung cancer classification. Our analyses also indicated that IIIB, IIIC, and IVA stage groups had similar survival outcomes and suggest further research for refinement.

Cost of screening for lung cancer in Australia.

BACKGROUND: Lung cancer screening can reduce lung cancer mortality. Australian cost estimates are important to inform policy but remain uncertain. AIM: To describe the first direct medical costs associated with lung cancer screening in Australia. METHODS: Single-centre prospective screening cohort. Healthy volunteers (age 60-74 years, current or former smokers quit <15 years prior to enrolment, ≥30 pack-years exposure) underwent baseline and two annual incidence computed tomography (CT) screening scans. Health status and healthcare usage data were collated for 5 years. The main outcome measures were: rates of lung cancer; individual healthcare resource use derived from multiple data sources adjusted to 2018 Australian Medicare Benefits Schedule values. RESULTS: A total of 256, 239, 233 participants was screened at each round respectively; 12 participants were diagnosed with lung cancer during screening and 2 during follow-up: 9 underwent surgery, 4 received concurrent chemoradiation, 1 received palliative chemotherapy. One surgical case died from lymphoma 1407 days after diagnosis, all other surgical cases survived >5 years. Non-surgical median survival post-diagnosis was 654 days. Gross trial cost was Australian dollar (AU$) 965 665 (AU$397 396 CT scans; AU$29 303 false-positive scan work-up; AU$96 340 true-positive scan workup; AU$336 914 lung cancer treatment; AU$104 712 lung cancer follow-up post-treatment). Average total direct medical cost per participant was AU$3 768. Average direct cost of surgery was AU$22 659; average non-surgical cost was AU$47 395 (radiotherapy, chemotherapy, palliative care). CONCLUSIONS: Advanced cancer cost more to treat and had worse survival than early cancer. Screening costs are similar to international studies and suggest that lung cancer early detection could limit treatment costs and improve outcomes.

Low tumour cell content in a lung tumour bank: implications for molecular characterisation.

Lung cancer encompasses multiple malignant epithelial tumour types, each with specific targetable, potentially actionable mutations, such that precision management mandates accurate tumour typing. Molecular characterisation studies require high tumour cell content and low necrosis content, yet lung cancers are frequently a heterogeneous mixture of tumour and stromal cells. We hypothesised that there may be systematic differences in tumour cell content according to histological subtype, and that this may have implications for tumour banks as a resource for comprehensive molecular characterisation studies in lung cancer. To investigate this, we estimated tumour cell and necrosis content of 4267 samples resected from 752 primary lung tumour specimens contributed to a lung tissue bank. We found that banked lung cancer samples had low tumour cell content (33%) generally, although it was higher in carcinoids (77.5%) than other lung cancer subtypes. Tumour cells comprise a variable and often small component of banked resected tumour samples, and are accompanied by stromal reaction, inflammation, fibrosis, and normal structures. This has implications for the adequacy of unselected tumour bank samples for diagnostic and molecular investigations, and further research is needed to determine whether tumour cell content has a significant impact on analytical results in studies using tissue from tumour bank resources.

The effect of different radiological models on diagnostic accuracy and lung cancer screening performance.

High false-positive (FP) scan rates associated with low-dose computed tomography (LDCT) lung cancer screening result in unnecessary follow-up tests and exposure to harm. The definition of a 'positive' scan can impact FP rates and screening performance. We explored the effect of Lung Imaging Reporting and Data System (Lung-RADS) criteria, PanCan Nodule Malignancy Probability Model and varying nodule size thresholds (≥4 mm, ≥6 mm, ≥8 mm) on diagnostic accuracy and screening performance compared with original trial definitions (National Lung Screening Trial (NLST) criteria) in a secondary analysis of a lung cancer screening cohort. We found Lung-RADS criteria and the PanCan Nodule Malignancy Probability Model could substantially improve screening performance and reduce FP scan rates compared with NLST definitions of positivity but that this needs to be balanced against possible risk of false-negative results. TRIAL REGISTRATION NUMBER: Australian New Zealand Clinical Trials Registry, ACTRN12610000007033.

Screen-detected subsolid pulmonary nodules: long-term follow-up and application of the PanCan lung cancer risk prediction model.

OBJECTIVE: To report the long-term follow-up of subsolid nodules (SSNs) detected in participants of a prospective low-dose CT lung cancer screening cohort, and to investigate the utility of the PanCan model in stratifying risk in baseline SSNs. METHODS: Participants underwent a baseline scan, two annual incidence scans and further follow-up scans for the detected nodules. All SSNs underwent a minimum of 2 years of follow-up (unless resolved or resected). Risk of malignancy was estimated using the PanCan model; discrimination [area under the receiver-operating characteristic curve (AUC)] and calibration (Hosmer-Lemeshow goodness-of-fit test) were assessed. The Mann-Whitney U-Wilcoxon test was used to compare estimated risk between groups. RESULTS: 70 SSNs were detected in 41 (16.0%) out of 256 total participants. Median follow-up period was 25.5 months (range 2.0-74.0 months). 29 (41.4%) SSNs were transient. Five (7.1%) SSNs were resected, all found to be Stage I lung adenocarcinoma, including one SSN stable in size for 3.0 years before growth was detected. The PanCan model had good discrimination for the 52 baseline SSNs (AUC = 0.89; 95% confidence interval 0.76-1); the Hosmer-Lemeshow goodness-of-fit test was non-significant (p = 0.27). Estimated risk was significantly higher in the baseline SSNs found to be cancer vs those not found to be cancer after 2-6 years of follow-up (p < 0.01). CONCLUSION: Our findings support a long-term follow-up approach for screen-detected SSNs for 3 years or longer. The PanCan model appeared discriminatory and well calibrated in this cohort. ADVANCES IN KNOWLEDGE: The PanCan model may have utility in identifying low-risk SSNs which could be followed with less frequent CT scans.

Brief Tailored Smoking Cessation Counseling in a Lung Cancer Screening Population is Feasible: A Pilot Randomized Controlled Trial.

INTRODUCTION: Maximizing smoking abstinence in lung cancer screening participants is important to reduce individual risk of disease and improve screening cost-effectiveness; however, the optimal strategy remains undefined. We hypothesized that a single session of tailored face-to-face counseling on the day of screening CT scan, coupled with audio and printed cessation information would be feasible to deliver in a CT screening trial. METHODS: We randomized volunteer smokers in the Queensland Lung Cancer Screening Study to intervention (counseling session, audio quit materials, printed quit materials, Quitline contact details) or control group (printed quit materials, Quitline contact details). Participants self-reported point prevalence quit rates at 1 year. RESULTS: Fifty-five smokers were enrolled; 28 randomized to intervention and 27 controls. Median cigarette consumption was 25/day; 54/55 smoked at least 15 cigarettes per day. Median smoking duration was 46 years. Median Fagerström dependence score was 6. In total 58% did not report any quit attempt in the prior 12 months. Mean duration of counseling was 26.5 minutes. After 1 year, four participants (14.3%) in the intervention group and five participants (18.5%) in the control group had quit (P = .74). Combined annual point prevalence quit rate was 16.4%. CONCLUSIONS: Although feasible to deliver a single session of tailored counseling on the day of screening this intervention had no discernible impact on cessation over and above printed materials and Quitline access. As participants exhibited hardcore smoking characteristics, more intensive strategies, in larger cohorts, should be explored. IMPLICATIONS: The optimal smoking cessation strategy within a lung cancer screening program is not known. This study demonstrates that a single session of counseling can be feasibly delivered on the day of screening but may not have been intensive enough for long-term, hard-core smokers.

Phenotypes and karyotypes of human malignant mesothelioma cell lines.

BACKGROUND: Malignant mesothelioma is an aggressive tumour of serosal surfaces most commonly pleura. Characterised cell lines represent a valuable tool to study the biology of mesothelioma. The aim of this study was to develop and biologically characterise six malignant mesothelioma cell lines to evaluate their potential as models of human malignant mesothelioma. METHODS: Five lines were initiated from pleural biopsies, and one from pleural effusion of patients with histologically proven malignant mesothelioma. Mesothelial origin was assessed by standard morphology, Transmission Electron Microscopy (TEM) and immunocytochemistry. Growth characteristics were assayed using population doubling times. Spectral karyotyping was performed to assess chromosomal abnormalities. Authentication of donor specific derivation was undertaken by DNA fingerprinting using a panel of SNPs. RESULTS: Most of cell lines exhibited spindle cell shape, with some retaining stellate shapes. At passage 2 to 6 all lines stained positively for calretinin and cytokeratin 19, and demonstrated capacity for anchorage-independent growth. At passage 4 to 16, doubling times ranged from 30-72 hours, and on spectral karyotyping all lines exhibited numerical chromosomal abnormalities ranging from 41 to 113. Monosomy of chromosomes 8, 14, 22 or 17 was observed in three lines. One line displayed four different karyotypes at passage 8, but only one karyotype at passage 42, and another displayed polyploidy at passage 40 which was not present at early passages. At passages 5-17, TEM showed characteristic features of mesothelioma ultrastructure in all lines including microvilli and tight intercellular junctions. CONCLUSION: These six cell lines exhibit varying cell morphology, a range of doubling times, and show diverse passage-dependent structural chromosomal changes observed in malignant tumours. However they retain characteristic immunocytochemical protein expression profiles of mesothelioma during maintenance in artificial culture systems. These characteristics support their potential as in vitro model systems for studying cellular, molecular and genetic aspects of mesothelioma.

Pleural fluid cell-free DNA integrity index to identify cytologically negative malignant pleural effusions including mesotheliomas.

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.

Genetic influences on right ventricular systolic pressure (RVSP) in chronic obstructive pulmonary disease (COPD).

BACKGROUND: Pulmonary hypertension (PH) is a complication of chronic obstructive pulmonary disease (COPD). This study examined genetic variations in mediators of vascular remodelling and their association with PH in patients with COPD. In patients with COPD, we genotyped 7 SNPs in 6 candidate PH genes (NOS3, ACE, EDN1, PTGIS, SLC6A4, VEGFA). We tested for association with right ventricular systolic pressure (RVSP), spirometry and gas transfer, and hypoxemia. METHODS: In patients with COPD, we genotyped 7 SNPs in 6 candidate PH genes (NOS3, ACE, EDN1, PTGIS, SLC6A4, VEGFA). We tested for association with right ventricular systolic pressure (RVSP), spirometry and gas transfer, and hypoxemia. RESULTS: 580 COPD patients were recruited, 341 patients had a transthoracic echocardiogram, with RVSP measurable in 278 patients (mean age 69 years, mean FEV1 50% predicted, mean RVSP 44 mmHg, median history of 50 pack-years). Of the 7 tested SNPs, the NOS3-VNTR polymorphism was significantly associated with RVSP in a dose-dependent fashion for the risk allele: mean RVSP for a/a and a/b genotypes were 52.0 and 46.6 mmHg respectively, compared to 43.2 mmHg for b/b genotypes (P = 0.032). No associations were found between RVSP and other polymorphisms. ACE II or ID genotypes were associated with a lower FEV1% predicted than the ACE DD genotype (P = 0.028). The NOS3-298 TT genotype was associated with lower KCO % predicted than the NOS3-298 GG or GT genotype (P = 0.031). CONCLUSIONS: The NOS3-VNTR polymorphism was associated with RVSP in patients with COPD, supporting its involvement in the pathogenesis of PH in COPD. ACE and NOS3 genotypes were associated with COPD disease severity, but not with the presence of PH. Further study of these genes could lead to the development of prognostic and screening tools for PH in COPD.

MicroRNA-218 is deleted and downregulated in lung squamous cell carcinoma.

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.

ADAM28: a potential oncogene involved in asbestos-related lung adenocarcinomas.

Asbestos-related lung cancer accounts for 4-12% of all lung cancers worldwide. Since putative mechanisms of carcinogenesis differ between asbestos and tobacco induced lung cancers, tumors induced by the two agents may be genetically distinct. To identify gene expression biomarkers associated with asbestos-related lung tumorigenicity we performed gene expression array analysis on tumors of 36 patients with primary lung adenocarcinoma, comparing 12 patients with lung asbestos body counts above levels associated with urban dwelling (ARLC-AC: asbestos-related lung cancer-adenocarcinoma) with 24 patients with no asbestos bodies (NARLC-AC: non-asbestos related lung cancer-adenocarcinoma). Genes differentially expressed between ARLC-AC and NARLC-AC were identified on fold change and P value, and then prioritized using gene ontology. Candidates included ZNRF3, ADAM28, PPP1CA, IRF6, RAB3D, and PRDX1. Expression of these six genes was technically and biologically replicated by qRT-PCR in the training set and biologically validated in three independent test sets. ADAM28, encoding a disintegrin and metalloproteinase domain protein that interacts with integrins, was consistently upregulated in ARLC across all four datasets. Further studies are being designed to investigate the possible role of this gene in asbestos lung tumorigenicity, its potential utility as a marker of asbestos related lung cancer for purposes of causal attribution, and its potential as a treatment target for lung cancers arising in asbestos exposed persons.

Lung asbestos content in lungs resected for primary lung cancer.

INTRODUCTION: The majority of Australia's burden of lung cancer occurs in current or former tobacco smokers. To determine the possible contribution of asbestos exposure in Australians presenting with primary lung cancer, we measured lung asbestos content in cases resected consecutively at a single cardio-thoracic hospital. METHODS: Asbestos bodies were quantified by lung tissue digestion, filtration, and light microscopy, and were correlated with exposure questionnaires and clinicopathological features. RESULTS: We demonstrate high intrarater reproducibility and interrater reliability using these methods. In 463 patients with resected primary lung cancers, asbestos content ranged from 0 to 749 asbestos bodies per gram wet weight (AB/gww). Forty-eight percent of patients had no asbestos bodies identified. One-third had less than or equal to 20 AB/gww (a level previously found to be consistent with urban dwelling). Nineteen percent had lung content in excess of this level. Only 20 cases had AB >100/gww, approximately equivalent to the Helsinki threshold for attribution of lung cancer to asbestos. Median asbestos body counts were higher in patients who reported previous asbestos exposure than in those who reported no exposure. A subgroup of cases gave detailed exposure histories that did not predict presence or absence of asbestos bodies in men or women. In cases with cumulative tobacco exposure less than 20 pack-years, asbestos body counts exceeding 20 AB/gww were overrepresented. CONCLUSIONS: We found that the majority of patients with primary lung cancer at a single Australian center have detectable asbestos in resected lung tissue, but fiber burdens are generally low. The contributory role of this low-level asbestos exposure in causing lung cancer remains uncertain.

Gene expression signature predicts recurrence in lung adenocarcinoma.

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.

Expression profiling defines a recurrence signature in lung squamous cell carcinoma.

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.