Gender Difference in sidE eFfects of ImmuNotherapy: a possible clue to optimize cancEr tReatment (G-DEFINER): study protocol of an observational prospective multicenter study.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have significantly improved outcomes in various cancers. ICI treatment is associated with the incidence of immune-related adverse events (irAEs) which can affect any organ. Data on irAEs occurrence in relation to sex- differentiation and their association with gender-specific factors are limited. AIMS: The primary objective of the G-DEFINER study is to compare the irAEs incidence in female and male patients who undergo ICI treatment. Secondary objectives are: to compare the irAEs incidence in pre- and postmenopausal female patients; to compare the irAEs incidence in female and male patients according to different clinical and gender-related factors (lifestyle, psychosocial, and behavioral factors). Exploratory objectives of the study are to compare and contrast hormonal, gene-expression, SNPs, cytokines, and gut microbiota profiles in relation to irAEs incidence in female and male patients. METHODS AND RESULTS: The patients are recruited from Fondazione IRCCS Istituto Nazionale dei Tumori, Italy, St Vincent's University Hospital, Ireland, Oslo University Hospital, Norway, and Karolinska Insitutet/Karolinska University Hospital, Sweden. The inclusion of patients was delayed due to the Covid pandemic, leading to a total of 250 patients recruited versus a planned number of 400 patients. Clinical and translational data will be analyzed. INTERPRETATION: The expected outcomes are to improve the management of cancer patients treated with ICIs, leading to more personalized clinical approaches that consider potential toxicity profiles. The real world nature of the trial makes it highly applicable for timely irAEs diagnosis.

UV1 telomerase vaccine with ipilimumab and nivolumab as second line treatment for pleural mesothelioma - A phase II randomised trial.

PURPOSE: The NIPU-trial investigates the effect of adding the telomerase vaccine UV1 to treatment with ipilimumab and nivolumab for patients with pleural mesothelioma (PM). METHODS: In this phase 2 open-label trial, patients with PM progressing after first-line chemotherapy were randomised to receive ipilimumab and nivolumab alone (arm B) or combined with UV1 (arm A). The primary endpoint was progression-free survival (PFS) as determined by BICR. It was estimated that 69 PFS events were needed to detect a hazard ratio (HR) of 0.60 with 80% power and a one-sided alpha level of 0.10. RESULTS: 118 patients were randomised. The median PFS determined by blinded independent central review (BICR) was 4.2 months (95%CI 2.9-9.8) in arm A and 4.7 months (95%CI 3.9-7.0) in arm B (HR 1.01, 80%CI 0.75-1.36 P = 0.979), after a median follow-up of 12.5 months (95%CI 9.7-15.6). The investigator-determined median PFS was 4.3 months (95%CI 3.0-6.8) in arm A and 2.9 months (95%CI 2.4-5.5) in arm B (HR 0.60, 80%CI 0.45-0.81 P = 0.025). Confirmed objective response rate (ORR) by BICR was 31% in arm A and 16% in arm B (odds ratio 2.44 80%CI 1.35-4.49 P = 0.056). After a median follow-up time of 17.3 months (95%CI 15.8-22.9), the OS was 15.4 months (95%CI 11.1-22.6) in arm A and 11.1 months (95%CI 8.8-18.1) in arm B, (HR 0.73, 80%CI 0.53-1.0, P = 0.197). CONCLUSION: The primary endpoint was not met. Predefined analyses of response rates are in favour of adding the vaccine.

A trans-omics assessment of gene-gene interaction in early-stage NSCLC.

Epigenome-wide gene-gene (G × G) interactions associated with non-small-cell lung cancer (NSCLC) survival may provide insights into molecular mechanisms and therapeutic targets. Hence, we proposed a three-step analytic strategy to identify significant and robust G × G interactions that are relevant to NSCLC survival. In the first step, among 49 billion pairs of DNA methylation probes, we identified 175 775 G × G interactions with PBonferroni ≤ 0.05 in the discovery phase of epigenomic analysis; among them, 15 534 were confirmed with P ≤ 0.05 in the validation phase. In the second step, we further performed a functional validation for these G × G interactions at the gene expression level by way of a two-phase (discovery and validation) transcriptomic analysis, and confirmed 25 significant G × G interactions enriched in the 6p21.33 and 6p22.1 regions. In the third step, we identified two G × G interactions using the trans-omics analysis, which had significant (P ≤ 0.05) epigenetic cis-regulation of transcription and robust G × G interactions at both the epigenetic and transcriptional levels. These interactions were cg14391855 × cg23937960 (ßinteraction  = 0.018, P = 1.87 × 10-12 ), which mapped to RELA × HLA-G (ßinteraction  = 0.218, P = 8.82 × 10-11 ) and cg08872738 × cg27077312 (ßinteraction  = -0.010, P = 1.16 × 10-11 ), which mapped to TUBA1B × TOMM40 (ßinteraction =-0.250, P = 3.83 × 10-10 ). A trans-omics mediation analysis revealed that 20.3% of epigenetic effects on NSCLC survival were significantly (P = 0.034) mediated through transcriptional expression. These statistically significant trans-omics G × G interactions can also discriminate patients with high risk of mortality. In summary, we identified two G × G interactions at both the epigenetic and transcriptional levels, and our findings may provide potential clues for precision treatment of NSCLC.

Atezolizumab and stereotactic body radiotherapy in patients with advanced non-small cell lung cancer: safety, clinical activity and ctDNA responses-the ComIT-1 trial.

The introduction of immune checkpoint inhibitors has transformed the treatment landscape of metastatic non-small cell lung cancer. However, challenges remain to increase the fraction of patients achieving durable clinical responses to these drugs and to help monitor the treatment effect. In this phase II trial, we investigated the toxicity, systemic responses and circulating tumour DNA responses in patients (n = 21) with advanced non-small-cell lung cancer treated with atezolizumab and stereotactic body radiotherapy in the second or later line. We found the combined treatment to be safe with grade 3 toxicity reported in three patients. As the best overall response, four patients had a partial response, eight had stable disease and five had progressive disease. Median overall survival time was still not reached after a median follow-up of 26.5 months and 10/15 patients with programmed death-ligand 1 negative tumours were alive >18 months after the start of the study treatment. ctDNA was detectable at baseline in 11 patients. A rapid decline in ctDNA to <30% of baseline levels was seen in three patients, two of which were radiographic responders and one was considered clinically benefiting from therapy for almost 1 year.

Epigenome-wide three-way interaction study identifies a complex pattern between TRIM27, KIAA0226, and smoking associated with overall survival of early-stage NSCLC.

The interaction between DNA methylation of tripartite motif containing 27 (cg05293407TRIM27 ) and smoking has previously been identified to reveal histologically heterogeneous effects of TRIM27 DNA methylation on early-stage non-small-cell lung cancer (NSCLC) survival. However, to understand the complex mechanisms underlying NSCLC progression, we searched three-way interactions. A two-phase study was adopted to identify three-way interactions in the form of pack-year of smoking (number of cigarettes smoked per day × number of years smoked) × cg05293407TRIM27 × epigenome-wide DNA methylation CpG probe. Two CpG probes were identified with FDR-q ≤ 0.05 in the discovery phase and P ≤ 0.05 in the validation phase: cg00060500KIAA0226 and cg17479956EXT2 . Compared to a prediction model with only clinical information, the model added 42 significant three-way interactions using a looser criterion (discovery: FDR-q ≤ 0.10, validation: P ≤ 0.05) had substantially improved the area under the receiver operating characteristic curve (AUC) of the prognostic prediction model for both 3-year and 5-year survival. Our research identified the complex interaction effects among multiple environment and epigenetic factors, and provided therapeutic target for NSCLC patients.

Whole genome copy number analyses reveal a highly aberrant genome in TP53 mutant lung adenocarcinoma tumors.

BACKGROUND: Genetic alterations are common in non-small cell lung cancer (NSCLC), and DNA mutations and translocations are targets for therapy. Copy number aberrations occur frequently in NSCLC tumors and may influence gene expression and further alter signaling pathways. In this study we aimed to characterize the genomic architecture of NSCLC tumors and to identify genomic differences between tumors stratified by histology and mutation status. Furthermore, we sought to integrate DNA copy number data with mRNA expression to find genes with expression putatively regulated by copy number aberrations and the oncogenic pathways associated with these affected genes. METHODS: Copy number data were obtained from 190 resected early-stage NSCLC tumors and gene expression data were available from 113 of the adenocarcinomas. Clinical and histopathological data were known, and EGFR-, KRAS- and TP53 mutation status was determined. Allele-specific copy number profiles were calculated using ASCAT, and regional copy number aberration were subsequently obtained and analyzed jointly with the gene expression data. RESULTS: The NSCLC tumors tissue displayed overall complex DNA copy number profiles with numerous recurrent aberrations. Despite histological differences, tissue samples from squamous cell carcinomas and adenocarcinomas had remarkably similar copy number patterns. The TP53-mutated lung adenocarcinomas displayed a highly aberrant genome, with significantly altered copy number profiles including gains, losses and focal complex events. The EGFR-mutant lung adenocarcinomas had specific arm-wise aberrations particularly at chromosome7p and 9q. A large number of genes displayed correlation between copy number and expression level, and the PI(3)K-mTOR pathway was highly enriched for such genes. CONCLUSIONS: The genomic architecture in NSCLC tumors is complex, and particularly TP53-mutated lung adenocarcinomas displayed highly aberrant copy number profiles. We suggest to always include TP53-mutation status when studying copy number aberrations in NSCLC tumors. Copy number may further impact gene expression and alter cellular signaling pathways.

Improved adaptive radiotherapy to adjust for anatomical alterations during curative treatment for locally advanced lung cancer.

Anatomical changes during chemoradiation for lung cancer may decrease dose to the target or increase dose to organs at risk. To assess our ability to identify clinically significant anatomical alterations, we followed 67 lung cancer patients by daily cone-beam CT scans to ensure correct patient positioning and observe anatomical alterations. We also re-calculated the original dose distribution on a planned control CT scan obtained halfway during the treatment course to identify anatomical changes that potentially affected doses to the target or organs at risk. Of 66 patients who completed the treatment, 12 patients needed adaptation, two patients were adapted twice. We conclude that daily cone-beam CT and routines at the treatment machine discover relevant anatomical changes during curative radiotherapy for patients with lung cancer without additional imaging.

NIPU: a randomised, open-label, phase II study evaluating nivolumab and ipilimumab combined with UV1 vaccination as second line treatment in patients with malignant mesothelioma.

BACKGROUND: Malignant pleural mesothelioma (MPM) is a rare and aggressive tumour. For patients with inoperable disease, few treatment options are available after first line chemotherapy. The combination of ipilimumab and nivolumab has recently shown increased survival compared to standard chemotherapy, but most patients do not respond and improvements are called for. Telomerase is expressed in mesothelioma cells, but only sparsely in normal tissues and is therefore an attractive target for therapeutic vaccination. Vaccination against telomerase is tolerable and has shown to induce immune responses associated with increased survival in other cancer types. There is a well-founded scientific rationale for the combination of a telomerase vaccine and checkpoint inhibition to improve treatment response in MPM patients. METHODS: NIPU is a randomized, multi-centre, open-label, phase II study comparing the efficacy and safety of nivolumab and ipilimumab with or without telomerase vaccine in patients with inoperable malignant pleural mesothelioma after first-line platinum-based chemotherapy. Participants (n = 118) are randomized 1:1 into two treatment arms. All participants receive treatment with nivolumab (240 mg every 2 weeks) and ipilimumab (1 mg/kg every 6 weeks) until disease progression, unacceptable toxicity or for a maximum of 2 years. Patients randomised to the experimental arm receive 8 intradermal injections of UV1 vaccine during the first three months of treatment. Tumour tissue, blood, urine, faeces and imaging will be collected for biomarker analyses and exploration of mechanisms for response and resistance to therapy. DISCUSSION: Checkpoint inhibition is used for treatment of mesothelioma, but many patients still do not respond. Increasing therapy response to immunotherapy is an important goal. Possible approaches include combination with chemotherapy, radiotherapy, targeted therapy and other immunotherapeutic agents. Predictive biomarkers are necessary to ensure optimal treatment for each patient and to prevent unnecessary side effects. This trial seeks to improve treatment response by combining checkpoint inhibition with a telomerase vaccine and also to explore mechanisms for treatment response and resistance. Knowledge gained in the NIPU study may be transferred to the first line setting and to other cancers with limited benefit from immunotherapy. TRIAL REGISTRATION: ClinicalTrials.gov: NCT04300244, registered March 8th, 2020, https://clinicaltrials.gov/ct2/show/NCT04300244?term=NIPU&draw=2&rank=1 .

Epigenome-wide gene-age interaction analysis reveals reversed effects of PRODH DNA methylation on survival between young and elderly early-stage NSCLC patients.

DNA methylation changes during aging, but it remains unclear whether the effect of DNA methylation on lung cancer survival varies with age. Such an effect could decrease prediction accuracy and treatment efficacy. We performed a methylation-age interaction analysis using 1,230 early-stage lung adenocarcinoma patients from five cohorts. A Cox proportional hazards model was used to investigate lung adenocarcinoma and squamous cell carcinoma patients for methylation-age interactions, which were further confirmed in a validation phase. We identified one adenocarcinoma-specific CpG probe, cg14326354PRODH, with effects significantly modified by age (HRinteraction = 0.989; 95% CI: 0.986-0.994; P = 9.18×10-7). The effect of low methylation was reversed for young and elderly patients categorized by the boundary of 95% CI standard (HRyoung = 2.44; 95% CI: 1.26-4.72; P = 8.34×10-3; HRelderly = 0.58; 95% CI: 0.42-0.82; P = 1.67×10-3). Moreover, there was an antagonistic interaction between low cg14326354PRODH methylation and elderly age (HRinteraction = 0.21; 95% CI: 0.11-0.40; P = 2.20×10-6). In summary, low methylation of cg14326354PRODH might benefit survival of elderly lung adenocarcinoma patients, providing new insight to age-specific prediction and potential drug targeting.

Independent Validation of Early-Stage Non-Small Cell Lung Cancer Prognostic Scores Incorporating Epigenetic and Transcriptional Biomarkers With Gene-Gene Interactions and Main Effects.

BACKGROUND: DNA methylation and gene expression are promising biomarkers of various cancers, including non-small cell lung cancer (NSCLC). Besides the main effects of biomarkers, the progression of complex diseases is also influenced by gene-gene (G×G) interactions. RESEARCH QUESTION: Would screening the functional capacity of biomarkers on the basis of main effects or interactions, using multiomics data, improve the accuracy of cancer prognosis? STUDY DESIGN AND METHODS: Biomarker screening and model validation were used to construct and validate a prognostic prediction model. NSCLC prognosis-associated biomarkers were identified on the basis of either their main effects or interactions with two types of omics data. A prognostic score incorporating epigenetic and transcriptional biomarkers, as well as clinical information, was independently validated. RESULTS: Twenty-six pairs of biomarkers with G×G interactions and two biomarkers with main effects were significantly associated with NSCLC survival. Compared with a model using clinical information only, the accuracy of the epigenetic and transcriptional biomarker-based prognostic model, measured by area under the receiver operating characteristic curve (AUC), increased by 35.38% (95% CI, 27.09%-42.17%; P = 5.10 × 10-17) and 34.85% (95% CI, 26.33%-41.87%; P = 2.52 × 10-18) for 3- and 5-year survival, respectively, which exhibited a superior predictive ability for NSCLC survival (AUC3 year, 0.88 [95% CI, 0.83-0.93]; and AUC5 year, 0.89 [95% CI, 0.83-0.93]) in an independent Cancer Genome Atlas population. G×G interactions contributed a 65.2% and 91.3% increase in prediction accuracy for 3- and 5-year survival, respectively. INTERPRETATION: The integration of epigenetic and transcriptional biomarkers with main effects and G×G interactions significantly improves the accuracy of prognostic prediction of early-stage NSCLC survival.

Epigenetic-smoking interaction reveals histologically heterogeneous effects of TRIM27 DNA methylation on overall survival among early-stage NSCLC patients.

Tripartite motif containing 27 (TRIM27) is highly expressed in lung cancer, including non-small-cell lung cancer (NSCLC). Here, we profiled DNA methylation of lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) tumours from 613 early-stage NSCLC patients and evaluated associations between CpG methylation of TRIM27 and overall survival. Significant CpG probes were confirmed in 617 samples from The Cancer Genome Atlas. The methylation of the CpG probe cg05293407TRIM27 was significantly associated with overall survival in patients with LUSC (HR = 1.65, 95% CI: 1.30-2.09, P = 4.52 × 10-5), but not in patients with LUAD (HR = 1.08, 95% CI: 0.87-1.33, P = 0.493). As incidence of LUSC is associated with higher smoking intensity compared to LUAD, we investigated whether smoking intensity impacted on the prognostic effect of cg05293407TRIM27 methylation in NSCLC. LUSC patients had a higher average pack-year of smoking (37.49LUAD vs 54.79LUSC, P = 1.03 × 10-19) and included a higher proportion of current smokers than LUAD patients (28.24%LUAD vs 34.09%LUSC, P = 0.037). cg05293407TRIM27 was significantly associated with overall survival only in NSCLC patients with medium-high pack-year of smoking (HR = 1.58, 95% CI: 1.26-1.96, P = 5.25 × 10-5). We conclude that cg05293407TRIM27 methylation is a potential predictor of LUSC prognosis, and smoking intensity may impact on its prognostic value across the various types of NSCLC.

Trans-omics biomarker model improves prognostic prediction accuracy for early-stage lung adenocarcinoma.

Limited studies have focused on developing prognostic models with trans-omics biomarkers for early-stage lung adenocarcinoma (LUAD). We performed integrative analysis of clinical information, DNA methylation, and gene expression data using 825 early-stage LUAD patients from 5 cohorts. Ranger algorithm was used to screen prognosis-associated biomarkers, which were confirmed with a validation phase. Clinical and biomarker information was fused using an iCluster plus algorithm, which significantly distinguished patients into high- and low-mortality risk groups (Pdiscovery = 0.01 and Pvalidation = 2.71×10-3). Further, potential functional DNA methylation-gene expression-overall survival pathways were evaluated by causal mediation analysis. The effect of DNA methylation level on LUAD survival was significantly mediated through gene expression level. By adding DNA methylation and gene expression biomarkers to a model of only clinical data, the AUCs of the trans-omics model improved by 18.3% (to 87.2%) and 16.4% (to 85.3%) in discovery and validation phases, respectively. Further, concordance index of the nomogram was 0.81 and 0.77 in discovery and validation phases, respectively. Based on systematic review of published literatures, our model was superior to all existing models for early-stage LUAD. In summary, our trans-omics model may help physicians accurately identify patients with high mortality risk.

SIPA1L3 methylation modifies the benefit of smoking cessation on lung adenocarcinoma survival: an epigenomic-smoking interaction analysis.

Smoking cessation prolongs survival and decreases mortality of patients with non-small-cell lung cancer (NSCLC). In addition, epigenetic alterations of some genes are associated with survival. However, potential interactions between smoking cessation and epigenetics have not been assessed. Here, we conducted an epigenome-wide interaction analysis between DNA methylation and smoking cessation on NSCLC survival. We used a two-stage study design to identify DNA methylation-smoking cessation interactions that affect overall survival for early-stage NSCLC. The discovery phase contained NSCLC patients from Harvard, Spain, Norway, and Sweden. A histology-stratified Cox proportional hazards model adjusted for age, sex, clinical stage, and study center was used to test DNA methylation-smoking cessation interaction terms. Interactions with false discovery rate-q ≤ 0.05 were further confirmed in a validation phase using The Cancer Genome Atlas database. Histology-specific interactions were identified by stratification analysis in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) patients. We identified one CpG probe (cg02268510SIPA1L3 ) that significantly and exclusively modified the effect of smoking cessation on survival in LUAD patients [hazard ratio (HR)interaction  = 1.12; 95% confidence interval (CI): 1.07-1.16; P = 4.30 × 10-7 ]. Further, the effect of smoking cessation on early-stage LUAD survival varied across patients with different methylation levels of cg02268510SIPA1L3 . Smoking cessation only benefited LUAD patients with low methylation (HR = 0.53; 95% CI: 0.34-0.82; P = 4.61 × 10-3 ) rather than medium or high methylation (HR = 1.21; 95% CI: 0.86-1.70; P = 0.266) of cg02268510SIPA1L3 . Moreover, there was an antagonistic interaction between elevated methylation of cg02268510SIPA1L3 and smoking cessation (HRinteraction  = 2.1835; 95% CI: 1.27-3.74; P = 4.46 × 10-3 ). In summary, smoking cessation benefited survival of LUAD patients with low methylation at cg02268510SIPA1L3 . The results have implications for not only smoking cessation after diagnosis, but also possible methylation-specific drug targeting.

EMT network-based feature selection improves prognosis prediction in lung adenocarcinoma.

Various feature selection algorithms have been proposed to identify cancer prognostic biomarkers. In recent years, however, their reproducibility is criticized. The performance of feature selection algorithms is shown to be affected by the datasets, underlying networks and evaluation metrics. One of the causes is the curse of dimensionality, which makes it hard to select the features that generalize well on independent data. Even the integration of biological networks does not mitigate this issue because the networks are large and many of their components are not relevant for the phenotype of interest. With the availability of multi-omics data, integrative approaches are being developed to build more robust predictive models. In this scenario, the higher data dimensions create greater challenges. We proposed a phenotype relevant network-based feature selection (PRNFS) framework and demonstrated its advantages in lung cancer prognosis prediction. We constructed cancer prognosis relevant networks based on epithelial mesenchymal transition (EMT) and integrated them with different types of omics data for feature selection. With less than 2.5% of the total dimensionality, we obtained EMT prognostic signatures that achieved remarkable prediction performance (average AUC values >0.8), very significant sample stratifications, and meaningful biological interpretations. In addition to finding EMT signatures from different omics data levels, we combined these single-omics signatures into multi-omics signatures, which improved sample stratifications significantly. Both single- and multi-omics EMT signatures were tested on independent multi-omics lung cancer datasets and significant sample stratifications were obtained.

EGLN2 DNA methylation and expression interact with HIF1A to affect survival of early-stage NSCLC.

Hypoxia occurs frequently in human cancers and promotes stabilization and activation of hypoxia inducible factor (HIF). HIF-1α is specific for the hypoxia response, and its degradation mediated by three enzymes EGLN1, EGLN2 and EGLN3. Although EGLNs expression has been found to be related to prognosis of many cancers, few studies examined DNA methylation in EGLNs and its relationship to prognosis of early-stage non-small cell lung cancer (NSCLC). We analyzed EGLNs DNA methylation data from tumor tissue samples of 1,230 early-stage NSCLC patients, as well as gene expression data from The Cancer Genome Atlas. The sliding windows sequential forward feature selection method and weighted random forest were used to screen out the candidate CpG probes in lung adenocarcinomas (LUAD) and lung squamous cell carcinomas patients, respectively, in both discovery and validation phases. Then Cox regression was performed to evaluate the association between DNA methylation and overall survival. Among the 34 CpG probes in EGLNs, DNA methylation at cg25923056EGLN2 was identified to be significantly associated with LUAD survival (HR = 1.02, 95% CI: 1.01-1.03, P = 9.90 × 10-5), and correlated with EGLN2 expression (r = - 0.36, P = 1.52 × 10-11). Meanwhile, EGLN2 expression was negatively correlated with HIF1A expression in tumor tissues (r = - 0.30, P = 4.78 × 10-8) and significantly (P = 0.037) interacted with HIF1A expression on overall survival. Therefore, DNA methylation of EGLN2- HIF1A is a potential marker for LUAD prognosis and these genes are potential treatment targets for further development of HIF-1α inhibitors in lung cancer therapy.

DNA Methylation of LRRC3B: A Biomarker for Survival of Early-Stage Non-Small Cell Lung Cancer Patients.

BACKGROUND: Previous studies support a tumor-suppressor role for LRRC3B across various types of cancers. We aimed to investigate the association between DNA methylation of LRRC3B and overall survival (OS) for patients with early-stage non-small cell lung cancer (NSCLC). METHODS: This study included 1,230 patients with early-stage NSCLC. DNA was extracted from lung tumor tissues and DNA methylation was measured using Illumina Infinium HumanMethylation450 BeadChips. The association between DNA methylation and OS was first tested using Cox regression on a discovery cohort and then validated in an independent cohort. Next, the association between DNA methylation and gene expression was investigated in two independent cohorts. Finally, the association between gene expression and OS was investigated in three independent groups of patients. RESULTS: Three novel DNA methylation sites in LRRC3B were significantly associated with OS in two groups of patients. Patients with hypermethylation in the DNA methylation sites had significantly longer survival than the others in both the discovery cohort (HR, 0.62; P = 2.02 × 10-05) and validation cohort (HR, 0.55; P = 4.44 × 10-04). The three DNA methylation sites were significantly associated with LRRC3B expression, which was also associated with OS. CONCLUSIONS: Using clinical data from a large population, we illustrated the association between DNA methylation of LRRC3B and OS of early-stage NSCLC. IMPACT: We provide evidence of plausibility for building biomarkers on DNA methylation of LRRC3B for OS of early-stage NSCLC, thus filling a gap between previous in vitro studies and clinical applications.

A multi-omic study reveals BTG2 as a reliable prognostic marker for early-stage non-small cell lung cancer.

B-cell translocation gene 2 (BTG2) is a tumour suppressor protein known to be downregulated in several types of cancer. In this study, we investigated a potential role for BTG2 in early-stage non-small cell lung cancer (NSCLC) survival. We analysed BTG2 methylation data from 1230 early-stage NSCLC patients from five international cohorts, as well as gene expression data from 3038 lung cancer cases from multiple cohorts. Three CpG probes (cg01798157, cg06373167, cg23371584) that detected BTG2 hypermethylation in tumour tissues were associated with lower overall survival. The prognostic model based on methylation could distinguish patient survival in the four cohorts [hazard ratio (HR) range, 1.51-2.21] and the independent validation set (HR = 1.85). In the expression analysis, BTG2 expression was positively correlated with survival in each cohort (HR range, 0.28-0.68), which we confirmed with meta-analysis (HR = 0.61, 95% CI 0.54-0.68). The three CpG probes were all negatively correlated with BTG2 expression. Importantly, an integrative model of BTG2 methylation, expression and clinical information showed better predictive ability in the training set and validation set. In conclusion, the methylation and integrated prognostic signatures based on BTG2 are stable and reliable biomarkers for early-stage NSCLC. They may have new applications for appropriate clinical adjuvant trials and personalized treatments in the future.

Epigenetic modifications in KDM lysine demethylases associate with survival of early-stage NSCLC.

Background: KDM lysine demethylase family members are related to lung cancer clinical outcomes and are potential biomarkers for chemotherapeutics. However, little is known about epigenetic alterations in KDM genes and their roles in lung cancer survival. Methods: Tumor tissue samples of 1230 early-stage non-small cell lung cancer (NSCLC) patients were collected from the five independent cohorts. The 393 methylation sites in KDM genes were extracted from epigenome-wide datasets and analyzed by weighted random forest (Ranger) in discovery phase and validation dataset, respectively. The variable importance scores (VIS) for the sites in top 5% of both discovery and validation sets were carried forward for Cox regression to further evaluate the association with patient's overall survival. TCGA transcriptomic data were used to evaluate the correlation with the corresponding DNA methylation. Results: DNA methylation at sites cg11637544 in KDM2A and cg26662347 in KDM1A were in the top 5% of VIS in both discovery phase and validation for squamous cell carcinomas (SCC), which were also significantly associated with SCC survival (HRcg11637544 = 1.32, 95%CI, 1.16-1.50, P = 1.1 × 10-4; HRcg26662347 = 1.88, 95%CI, 1.37-2.60, P = 3.7 × 10-3), and correlated with corresponding gene expression (cg11637544 for KDM2A, P = 1.3 × 10-10; cg26662347 for KDM1A P = 1.5 × 10-5). In addition, by using flexible criteria for Ranger analysis followed by survival classification tree analysis, we identified four clusters for adenocarcinomas and five clusters for squamous cell carcinomas which showed a considerable difference of clinical outcomes with statistical significance. Conclusions: These findings highlight the association between somatic DNA methylation in KDM genes and early-stage NSCLC patient survival, which may reveal potential epigenetic therapeutic targets.

A unique set of 6 circulating microRNAs for early detection of non-small cell lung cancer.

INTRODUCTION: Circulating microRNAs are promising biomarkers for diagnosis, predication and prognostication of diseases. Lung cancer is the cancer disease accountable for most cancer deaths, largely due to being diagnosed at late stages. Therefore, diagnosing lung cancer patients at an early stage is crucial for improving the outcome. The purpose of this study was to identify circulating microRNAs for detection of early stage lung cancer, capable of discriminating lung cancer patients from those with chronic obstructive pulmonary disease (COPD) and healthy volunteers. RESULTS: We identified 7 microRNAs separating lung cancer patients from controls. By using RT-qPCR, we validated 6 microRNAs (miR-429, miR-205, miR-200b, miR-203, miR-125b and miR-34b) with a significantly higher abundance in serum from NSCLC patients. Furthermore, the 6 miRNAs were validated in a different dataset, revealing an area under the receiver operating characteristic curve of 0.89 for stage I-IV and 0.88 for stage I/II. MATERIALS AND METHODS: We profiled the expression of 754 unique microRNAs by TaqMan Low Density Arrays, and analyzed serum from 38 patients with NSCLC, 16 patients suffering from COPD and 16 healthy volunteers from Norway, to explore their potential as diagnostic biomarkers. For validation, we analyzed serum collected from high-risk individuals enrolled in the Valencia branch of the International Early Lung Cancer Action Program screening trial (n=107) in addition to 51 lung cancer patients. CONCLUSIONS: Considering the accessibility and stability of circulating miRNAs, these 6 microRNAs are promising biomarkers as a supplement in future screening studies.