Age-related hearing loss (ARHL), or presbycusis, is defined as the progressive and bilateral worsening of auditory function. According to the World Health Organization (2018), one-third of adults over 65 experience ARHL, which has a strong impact on their quality of life, and is associated with isolation, age-related cognitive deficit, and neurological disorders. The etiology of ARHL is complex with

Recent technological advances and the application of high-throughput mutation and transcriptome analyses have improved our understanding of cancer diseases, including non-small cell lung cancer. For instance, genomic profiling has allowed the identification of mutational events which can be treated with specific agents. However, detection of DNA alterations does not fully recapitulate the complexity of the disease and it does not allow selection of patients that benefit from chemo- or immunotherapy. In this context, transcriptional profiling has emerged as a promising tool for patient stratification and treatment guidance. For instance, transcriptional profiling has proven to be especially useful in the context of acquired resistance to targeted therapies and patients lacking targetable genomic alterations. Moreover, the comprehensive characterization of the expression level of the different pathways and genes involved in tumor progression is likely to better predict clinical benefit from different treatments than single biomarkers such as PD-L1 or tumor mutational burden in the case of immunotherapy. However, intrinsic technical and analytical limitations have hindered the use of these expression signatures in the clinical setting. In this review, we will focus on the data reported on molecular classification of non-small cell lung cancer and discuss the potential of transcriptional profiling as a predictor of survival and as a patient stratification tool to further personalize treatments.

BackgroundMalignant pleural mesothelioma (MPM) is a rare and aggressive neoplasia affecting the lung mesothelium. Immune checkpoint inhibitors (ICI) in MPM have not been extremely successful, likely due to poor identification of suitable candidate patients for the therapy. We aimed to identify cellular immune fractions associated with clinical outcome and classify patients with MPM based on their immune contexture. For each defined group, we sought for molecular specificities that could help further define our MPM classification at the genomic and transcriptomic level, as well as identify differential therapeutic strategies based on transcriptional signatures predictive of drug response.MethodsThe abundance of 20 immune cell fractions in 516 MPM samples from 7 gene expression datasets was inferred using gene set variation analysis. Identification of clinically relevant fractions was performed with Cox proportional-hazards models adjusted for age, stage, sex, and tumor histology. Immune-based groups were defined based on the identified fractions.ResultsT-helper 2 (TH2) and cytotoxic T (TC) cells were found to be consistently associated with overall survival. Three immune clusters (IG) were subsequently defined based on TH2 and TC immune infiltration levels: IG1 (54.5%) was characterized by high TH2 and low TC levels, IG2 (37%) had either low or high levels of both fractions, and IG3 (8.5%) was defined by low TH2 and high TC levels. IG1 and IG3 groups were associated with worse and better overall survival, respectively. While no differential genomic alterations were identified among immune groups, at the transcriptional level, IG1 samples showed upregulation of proliferation signatures, while IG3 samples presented upregulation of immune and inflammation-related pathways. Finally, the integration of gene expression with functional signatures of drug response showed that IG3 patients might be more likely to respond to ICI.ConclusionsThis study identifies a novel immune-based signature with potential clinical relevance based on TH2 and TC levels, unveiling a fraction of patients with MPM with better prognosis and who might benefit from immune-based therapies. Molecular specificities of the different groups might be used to tailor specific potential therapies in the future.

10630 Background: Patients with early onset lung cancer might be more likely to carry pathogenic (or likely-pathogenic) germline variants (PGV) in genes associated with cancer predisposition. However, germline testing is not recommended in this population. We designed this study to determine the prevalence of PGVs in patients with early onset lung cancer. Methods: This prospective, multicenter cohort study assessed PGV in patients younger than 51 years diagnosed with non-small cell lung cancer (NSCLC) in 3 sites at the Catalan Institute of Oncology between June 2018 to May 2022. Genomic DNA was sequenced using a custom-designed NGS panel covering 164 cancer-predisposing genes and results were discussed in a multidisciplinary tumor board. Results: 138 patients were included. Median age was 45.5 (28-50) years; 49% were females; 79% were ever-smokers with a median packs-year of 24 and median age of tobacco initiation of 16 years old. Most patients had non-squamous histology (88%) and had stage IV (62%) at diagnosis. Somatic oncogenic drivers were found in 74 patients (54%): EGFR 27 (20%); ALK 22 (16%); KRAS 20 (14%); RET 3 (2%); ROS1 1 (1%); BRAF V600E 1 (1%). Only 4% had past personal history of cancer and 50% had family history of cancer in a first-degree relative, being lung and breast cancer the most common tumors. Overall, 20 patients (14%) carried PGVs involving 12 genes associated with cancer predisposition: PARK2 (n=4); SBDS (n=3); NBN (n=2); ATM (n=2); TSC1 (n=2) and BLM, FANCA, MCPH1, PMS2, POLH, SDHA, RECQL4 (n=1, each). Four patients (3%) fulfilled criteria to be referred to genetic counseling clinic. There were no significant differences in clinical and molecular characteristics among patients with PGVs compared to their counterparts (Table). Conclusions: In this prospective cohort, 14% of patients with early onset NSCLC harbored germline PGVs. As clinicopathological and genomic features were not associated with PGVs, germline testing might be considered in addition to comprehensive genomic characterization of tumor tissue in young patients with NSCLC. However, only a minority of PGVs were deemed clinically actionable.[Table: see text]

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Background. Malignant pleural mesothelioma (MPM) is a rare and aggressive neoplasia affecting the lung mesothelium. Immune checkpoint inhibitors (ICI) in MPM have not been extremely successful, likely due to poor identification of suitable candidate patients for the therapy. We aimed to identify cellular immune fractions associated with clinical outcome and classify MPM patients based on their immune contexture. For each defined group, we sought for molecular specificities that could help further define our MPM classification at the genomic and transcriptomic level, as well as identify differential therapeutic strategies based on transcriptional signatures predictive of drug response. Methods. The abundance of 20 immune cell fractions in 516 MPM samples from 7 gene expression datasets was inferred using Gene Set Variation Analysis. Identification of clinically relevant fractions was performed with Cox Proportional-Hazards Models adjusted for age, stage, sex, and tumor histology. Immune-based groups were identified using unsupervised classification. Results. T-Helper 2 (TH2) and cytotoxic T (TC) cells were found to be consistently associated with overall survival. Three immune clusters (IG) were subsequently defined based on TH2 and TC immune infiltration levels: IG1 (54.5%) was characterized by high TH2 and low TC levels, IG2 (37%) had either low or high levels of both fractions, and IG3 (8.5%) was defined by low TH2and high TC levels. IG1 and IG3 groups were associated with worse and better overall survival, respectively. The three groups showed differential molecular profiles, with IG1 enriched for CDKN2A and IFN-related genes deletions. At the transcriptional level, IG1 samples showed upregulation of proliferation signatures, while IG3 samples presented upregulation of immune and inflammation-related pathways. Finally, the integration of gene expression with functional signatures of drug response showed that IG3 patients might be more likely to respond to ICI, while IG1 patients could be more sensitive to PARP inhibitors. Conclusions. This study identifies a novel immune-based signature with potential clinical relevance based on TH2 and TC levels, unveiling a fraction of MPM patients with better prognosis and who might benefit from immune-based therapies. Genomic and transcriptomic specificities of the different groups could be used to tailor potential therapies in the future.