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

Ipilimumab; Mesotelioma pleural maligne; Vacuna telomerasaIpilimumab; Mesotelioma pleural maligno; Vacuna de telomerasaIpilimumab; Malignant pleural mesothelioma; Telomerase vaccineBackground 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.Ultimovacs provides UV1 vaccine and sargramostin for patients treated in arm A and some funding for the clinical trial. BMS provides ipilimumab and nivolumab for all patients. The South-Eastern Norway regional health authority has provided support for the clinical trial, PhD students and research analyses (Grant nos. 2021083 and 2020077)

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 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

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 above 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

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.</p

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

This study was supported by the National Natural Science Foundation of China (82220108002 to FC, 82273737 to RZ, 81820108028 to HS, 81973142 to YW and 82103946 to SS), Natural Science Foundation of the Jiangsu Higher Education Institutions of China (21KJB330004 to SS), the US National Institutes of Health (CA209414, CA249096, CA092824 and ES000002 to DCC, CA209414 and CA249096 to YL), Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD). RZ was partially supported by the Qing Lan Project of the Higher Education Institutions of Jiangsu Province and the Outstanding Young Level Academic Leadership Training Program of Nanjing Medical University.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 P ≤ 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 (β = 0.018, P = 1.87 × 10), which mapped to RELA × HLA-G (β = 0.218, P = 8.82 × 10) and cg08872738 × cg27077312 (β = −0.010, P = 1.16 × 10), which mapped to TUBA1B × TOMM40 (β =−0.250, P = 3.83 × 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

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

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