Clinical management of typical and atypical carcinoids/neuroendocrine tumors in ENETS centres of excellence (CoE): Survey from the ENETS lung NET task force.

Lung carcinoid tumours are neuroendocrine neoplasms originating from the bronchopulmonary tract's neuroendocrine cells, accounting for only 1%-3% of all lung cancers but 30% of all neuroendocrine tumours. The incidence of lung carcinoids, both typical and atypical, has been increasing over the years due to improved diagnostic methods and increased awareness among clinicians and pathologists. The most recent WHO classification includes a subgroup of lung carcinoids with atypical morphology and higher mitotic count and/or Ki67 labelling index. Despite appropriate surgery, the 5-year survival rate for atypical carcinoids barely exceeds 50%-70%. The role of adjuvant therapy in lung carcinoids is not well-defined, and clinical decisions are generally based on the presence of high-risk features. Long-term follow-up is essential to monitor for recurrence, although the optimal follow-up protocol remains unclear. To address the lack of consensus in clinical management decisions, the European Neuroendocrine Tumor Society (ENETS) initiated a survey among 20 expert centres. The survey identified varied opinions on approaches to imaging, surgery, use of adjuvant therapy, and follow-up protocols. Notably, the absence of dedicated multidisciplinary lung neuroendocrine tumour boards in some centres was evident. Experts agreed on the need for a prospective adjuvant trial in high-risk patients, emphasizing the feasibility of such a study. In conclusion, the study highlights the need for a more uniform adoption of existing guidelines in the management of lung carcinoid tumours and emphasizes the importance of international collaboration to advance research and patient care. Close collaboration between healthcare providers and patients is vital for effective long-term surveillance and management of these rare tumours.

Multi-omic dataset of patient-derived tumor organoids of neuroendocrine neoplasms.

BACKGROUND: Organoids are 3-dimensional experimental models that summarize the anatomical and functional structure of an organ. Although a promising experimental model for precision medicine, patient-derived tumor organoids (PDTOs) have currently been developed only for a fraction of tumor types. RESULTS: We have generated the first multi-omic dataset (whole-genome sequencing [WGS] and RNA-sequencing [RNA-seq]) of PDTOs from the rare and understudied pulmonary neuroendocrine tumors (n = 12; 6 grade 1, 6 grade 2) and provide data from other rare neuroendocrine neoplasms: small intestine (ileal) neuroendocrine tumors (n = 6; 2 grade 1 and 4 grade 2) and large-cell neuroendocrine carcinoma (n = 5; 1 pancreatic and 4 pulmonary). This dataset includes a matched sample from the parental sample (primary tumor or metastasis) for a majority of samples (21/23) and longitudinal sampling of the PDTOs (1 to 2 time points), for a total of n = 47 RNA-seq and n = 33 WGS. We here provide quality control for each technique and the raw and processed data as well as all scripts for genomic analyses to ensure an optimal reuse of the data. In addition, we report gene expression data and somatic small variant calls and describe how they were generated, in particular how we used WGS somatic calls to train a random forest classifier to detect variants in tumor-only RNA-seq. We also report all histopathological images used for medical diagnosis: hematoxylin and eosin-stained slides, brightfield images, and immunohistochemistry images of protein markers of clinical relevance. CONCLUSIONS: This dataset will be critical to future studies relying on this PDTO biobank, such as drug screens for novel therapies and experiments investigating the mechanisms of carcinogenesis in these understudied diseases.

Altered splicing machinery in lung carcinoids unveils NOVA1, PRPF8 and SRSF10 as novel candidates to understand tumor biology and expand biomarker discovery.

BACKGROUND: Lung neuroendocrine neoplasms (LungNENs) comprise a heterogeneous group of tumors ranging from indolent lesions with good prognosis to highly aggressive cancers. Carcinoids are the rarest LungNENs, display low to intermediate malignancy and may be surgically managed, but show resistance to radiotherapy/chemotherapy in case of metastasis. Molecular profiling is providing new information to understand lung carcinoids, but its clinical value is still limited. Altered alternative splicing is emerging as a novel cancer hallmark unveiling a highly informative layer. METHODS: We primarily examined the status of the splicing machinery in lung carcinoids, by assessing the expression profile of the core spliceosome components and selected splicing factors in a cohort of 25 carcinoids using a microfluidic array. Results were validated in an external set of 51 samples. Dysregulation of splicing variants was further explored in silico in a separate set of 18 atypical carcinoids. Selected altered factors were tested by immunohistochemistry, their associations with clinical features were assessed and their putative functional roles were evaluated in vitro in two lung carcinoid-derived cell lines. RESULTS: The expression profile of the splicing machinery was profoundly dysregulated. Clustering and classification analyses highlighted five splicing factors: NOVA1, SRSF1, SRSF10, SRSF9 and PRPF8. Anatomopathological analysis showed protein differences in the presence of NOVA1, PRPF8 and SRSF10 in tumor versus non-tumor tissue. Expression levels of each of these factors were differentially related to distinct number and profiles of splicing events, and were associated to both common and disparate functional pathways. Accordingly, modulating the expression of NOVA1, PRPF8 and SRSF10 in vitro predictably influenced cell proliferation and colony formation, supporting their functional relevance and potential as actionable targets. CONCLUSIONS: These results provide primary evidence for dysregulation of the splicing machinery in lung carcinoids and suggest a plausible functional role and therapeutic targetability of NOVA1, PRPF8 and SRSF10.

Druggable growth dependencies and tumor evolution analysis in patient-derived organoids of neuroendocrine neoplasms from multiple body sites.

Neuroendocrine neoplasms (NENs) comprise well-differentiated neuroendocrine tumors (NETs) and poorly differentiated neuroendocrine carcinomas (NECs). Treatment options for patients with NENs are limited, in part due to lack of accurate models. We establish patient-derived tumor organoids (PDTOs) from pulmonary NETs and derive PDTOs from an understudied subtype of NEC, large cell neuroendocrine carcinoma (LCNEC), arising from multiple body sites. PDTOs maintain the gene expression patterns, intra-tumoral heterogeneity, and evolutionary processes of parental tumors. Through hypothesis-driven drug sensitivity analyses, we identify ASCL1 as a potential biomarker for response of LCNEC to treatment with BCL-2 inhibitors. Additionally, we discover a dependency on EGF in pulmonary NET PDTOs. Consistent with these findings, we find that, in an independent cohort, approximately 50% of pulmonary NETs express EGFR. This study identifies an actionable vulnerability for a subset of pulmonary NETs, emphasizing the utility of these PDTO models.

Spotlight on Small-Cell Lung Cancer and Other Lung Neuroendocrine Neoplasms.

Lung neuroendocrine neoplasms (NENs) encompass a spectrum of neoplasms that are subdivided into the well-differentiated neuroendocrine tumors comprising the low- and intermediate-grade typical and atypical carcinoids, respectively, and the poorly differentiated, high-grade neuroendocrine carcinomas including large-cell neuroendocrine carcinomas and small-cell lung carcinoma (SCLC). Here, we review the current morphological and molecular classifications of the NENs on the basis of the updated WHO Classification of Thoracic Tumors and discuss the emerging subclassifications on the basis of molecular profiling and the potential therapeutic implications. We focus on the efforts in subtyping SCLC, a particularly aggressive tumor with few treatment options, and the recent advances in therapy with the adoption of immune checkpoint inhibitors in the frontline setting for patients with extensive-stage SCLC. We further highlight the promising immunotherapy strategies in SCLC that are currently under investigation.

Genetic Analysis of Lung Cancer and the Germline Impact on Somatic Mutation Burden.

BACKGROUND: Germline genetic variation contributes to lung cancer (LC) susceptibility. Previous genome-wide association studies (GWAS) have implicated susceptibility loci involved in smoking behaviors and DNA repair genes, but further work is required to identify susceptibility variants. METHODS: To identify LC susceptibility loci, a family history-based genome-wide association by proxy (GWAx) of LC (48 843 European proxy LC patients, 195 387 controls) was combined with a previous LC GWAS (29 266 patients, 56 450 controls) by meta-analysis. Colocalization was used to explore candidate genes and overlap with existing traits at discovered susceptibility loci. Polygenic risk scores (PRS) were tested within an independent validation cohort (1 666 LC patients vs 6 664 controls) using variants selected from the LC susceptibility loci and a novel selection approach using published GWAS summary statistics. Finally, the effects of the LC PRS on somatic mutational burden were explored in patients whose tumor resections have been profiled by exome (n = 685) and genome sequencing (n = 61). Statistical tests were 2-sided. RESULTS: The GWAx-GWAS meta-analysis identified 8 novel LC loci. Colocalization implicated DNA repair genes (CHEK1), metabolic genes (CYP1A1), and smoking propensity genes (CHRNA4 and CHRNB2). PRS analysis demonstrated that these variants, as well as subgenome-wide significant variants related to expression quantitative trait loci and/or smoking propensity, assisted in LC genetic risk prediction (odds ratio = 1.37, 95% confidence interval = 1.29 to 1.45; P < .001). Patients with higher genetic PRS loads of smoking-related variants tended to have higher mutation burdens in their lung tumors. CONCLUSIONS: This study has expanded the number of LC susceptibility loci and provided insights into the molecular mechanisms by which these susceptibility variants contribute to LC development.

Detection of acquired TERT amplification in addition to predisposing p53 and Rb pathways alterations in EGFR-mutant lung adenocarcinomas transformed into small-cell lung cancers.

INTRODUCTION: Among the different mechanisms of acquired resistance to EGFR tyrosine kinase inhibitors (TKIs) reported in EGFR-mutated lung adenocarcinoma (EGFR-LUAD) patients, histological transformation into small cell carcinoma (SCLC) occurs in 3-14% of resistant cases, regardless of the generation of EGFR-TKI. In recent studies, bi-allelic inactivation of TP53 and RB1 has been identified in a vast majority of transformed SCLCs. However, the molecular mechanisms driving this histologic transformation remain largely unknown, mainly due to the rarity of samples. PATIENTS AND METHODS: Out of an initial cohort of 64 patients, tumor tissues of adequate quality and quantity for whole exome sequencing (WES) analysis were available for nine tumors for six patients: paired pre- and post-SCLC transformation samples for three Patients and post-SCLC transformation samples for three other patients. RESULTS: Mutational analyses showed concurrent TP53 mutations and Rb pathway alterations in five of the six patients analyzed, confirming their suggested role as predisposing genetic alterations to SCLC transformation. In addition, TERT amplification was detected in four of the six patients and found to be an event acquired during SCLC transformation. Clonal history evolution analyses from the paired LUAD/SCLC samples showed different evolution patterns. In two patients, a large proportion of mutations were present in the most recent common ancestor cell of the initial LUAD and the transformed SCLC clones, whereas in the third patient, few clonal mutations were common between the LUAD and SCLC samples and the ancestor clone that lead to SCLC was present at low frequency in the initial LUAD. CONCLUSION: Despite varied clinical presentations and clonal history evolution patterns, in addition to p53 and Rb pathways alterations, TERT amplification emerged as another common genetic mechanism of EGFR-LUAD to SCLC transformation in our cohort, and could represent a candidate therapeutic target in this subset of SCLC tumors.

Differential Orthopedia Homeobox expression in pulmonary carcinoids is associated with changes in DNA methylation.

Limited number of tumor types have been examined for Orthopedia Homeobox (OTP) expression. In pulmonary carcinoids, loss of expression is a strong indicator of poor prognosis. Here, we investigated OTP expression in 37 different tumor types, and the association between OTP expression and DNA methylation levels in lung neuroendocrine neoplasms. We analyzed publicly available multi-omics data (whole-exome-, whole-genome-, RNA sequencing and Epic 850K-methylation array) of 58 typical carcinoids, 27 atypical carcinoids, 69 large cell neuroendocrine carcinoma and 51 small cell lung cancer patients and TCGA (The Cancer Genome Atlas) data of 33 tumor types. 850K-methylation analysis was cross-validated using targeted pyrosequencing on 35 carcinoids. We report bimodality of OTP expression in carcinoids (OTPhigh vs OTPlow group, likelihood-ratio test P = 1.5 × 10-2 ), with the OTPhigh group specific to pulmonary carcinoids while absent from all other cohorts analyzed. Significantly different DNA methylation levels were observed between OTPhigh and OTPlow carcinoids in 12/34 OTP infinium probes (FDR < 0.05 and ß-value effect size > .2). OTPlow carcinoids harbor high DNA methylation levels as compared to OTPhigh carcinoids. OTPlow carcinoids showed a significantly worse overall survival (log-rank test P = .0052). Gene set enrichment analysis for somatically mutated genes associated with hallmarks of cancer showed robust enrichment of three hallmarks in the OTPlow group, that is, sustaining proliferative signaling, evading growth suppressor and genome instability and mutation. Together our data suggest that high OTP expression is a unique feature of pulmonary carcinoids with a favorable prognosis and that in poor prognostic patients, OTP expression is lost, most likely due to changes in DNA methylation levels.

A molecular phenotypic map of malignant pleural mesothelioma.

BACKGROUND: Malignant pleural mesothelioma (MPM) is a rare understudied cancer associated with exposure to asbestos. So far, MPM patients have benefited marginally from the genomics medicine revolution due to the limited size or breadth of existing molecular studies. In the context of the MESOMICS project, we have performed the most comprehensive molecular characterization of MPM to date, with the underlying dataset made of the largest whole-genome sequencing series yet reported, together with transcriptome sequencing and methylation arrays for 120 MPM patients. RESULTS: We first provide comprehensive quality controls for all samples, of both raw and processed data. Due to the difficulty in collecting specimens from such rare tumors, a part of the cohort does not include matched normal material. We provide a detailed analysis of data processing of these tumor-only samples, showing that all somatic alteration calls match very stringent criteria of precision and recall. Finally, integrating our data with previously published multiomic MPM datasets (n = 374 in total), we provide an extensive molecular phenotype map of MPM based on the multitask theory. The generated map can be interactively explored and interrogated on the UCSC TumorMap portal (https://tumormap.ucsc.edu/?p=RCG_MESOMICS/MPM_Archetypes ). CONCLUSIONS: This new high-quality MPM multiomics dataset, together with the state-of-art bioinformatics and interactive visualization tools we provide, will support the development of precision medicine in MPM that is particularly challenging to implement in rare cancers due to limited molecular studies.

TP53 Targeted Deep Sequencing of Cell-Free DNA in Esophageal Squamous Cell Carcinoma Using Low-Quality Serum: Concordance with Tumor Mutation.

Circulating cell-free DNA (cfDNA) is emerging as a potential tumor biomarker. CfDNA-based biomarkers may be applicable in tumors without an available non-invasive screening method among at-risk populations. Esophageal squamous cell carcinoma (ESCC) and residents of the Asian cancer belt are examples of those malignancies and populations. Previous epidemiological studies using cfDNA have pointed to the need for high volumes of good quality plasma (i.e., >1 mL plasma with 0 or 1 cycles of freeze-thaw) rather than archival serum, which is often the main available source of cfDNA in retrospective studies. Here, we have investigated the concordance of TP53 mutations in tumor tissue and cfDNA extracted from archival serum left-over from 42 cases and 39 matched controls (age, gender, residence) in a high-risk area of Northern Iran (Golestan). Deep sequencing of TP53 coding regions was complemented with a specialized variant caller (Needlestack). Overall, 23% to 31% of mutations were concordantly detected in tumor and serum cfDNA (based on two false discovery rate thresholds). Concordance was positively correlated with high cfDNA concentration, smoking history (p-value = 0.02) and mutations with a high potential of neoantigen formation (OR; 95%CI = 1.9 (1.11-3.29)), suggesting that tumor DNA release in the bloodstream might reflect the effects of immune and inflammatory context on tumor cell turnover. We identified TP53 mutations in five controls, one of whom was subsequently diagnosed with ESCC. Overall, the results showed that cfDNA mutations can be reliably identified by deep sequencing of archival serum, with a rate of success comparable to plasma. Nonetheless, 70% non-identifiable mutations among cancer patients and 12% mutation detection in controls are the main challenges in applying cfDNA to detect tumor-related variants when blindly targeting whole coding regions of the TP53 gene in ESCC.

Challenges in lung and thoracic pathology: molecular advances in the classification of pleural mesotheliomas.

The diagnosis and classification of malignant pleural mesothelioma (MPM) is extremely challenging; obtaining an accurate histopathological diagnosis of the different types and subtypes requires expert assessment and suitable biopsies that are not always available, which can leave doctors uncertain about the patient's diagnosis, sometimes resulting in a delay in the start of treatment. In this review, we discuss recent major advances in the molecular characterisation of MPM and their implications for histological classification. We detail what is known of the molecular landscape of MPM at the genomic, transcriptomic, and epigenomic levels, describe the similarities and dissimilarities of the multiple molecular classifications that have been proposed, and provide an overview of the current state of knowledge regarding inter- and intra-tumour heterogeneity. We also highlight the current gaps in knowledge and how addressing them would benefit classification, as well as the patients in general.

Development of Sensitive Droplet Digital PCR Assays for Detecting Urinary TERT Promoter Mutations as Non-Invasive Biomarkers for Detection of Urothelial Cancer.

Somatic mutations in the telomerase reverse transcriptase (TERT) promoter regions are frequent events in urothelial cancer (UC) and their detection in urine (supernatant cell-free DNA or DNA from exfoliated cells) could serve as putative non-invasive biomarkers for UC detection and monitoring. However, detecting these tumor-borne mutations in urine requires highly sensitive methods, capable of measuring low-level mutations. In this study, we developed sensitive droplet digital PCR (ddPCR) assays for detecting TERT promoter mutations (C228T, C228A, CC242-243TT, and C250T). We tested the C228T and C250T ddPCR assays on all samples with sufficient quantity of urinary DNA (urine supernatant cell-free DNA (US cfDNA) or urine pellet cellular DNA (UP cellDNA)) from the DIAGURO (n = 89/93 cases and n = 92/94 controls) and from the IPO-PORTO (n = 49/50 cases and n = 50/50 controls) series that were previously screened with the UroMuTERT assay and compared the performance of the two approaches. In the DIAGURO series, the sensitivity and specificity of the ddPCR assays for detecting UC using either US cfDNA or UP cellDNA were 86.8% and 92.4%. The sensitivity was slightly higher than that of the UroMuTERT assay in the IPO-PORTO series (67.4% vs. 65.3%, respectively), but not in the DIAGURO series (86.8% vs. 90.7%). The specificity was 100% in the IPO-PORTO controls for both the UroMuTERT and ddPCR assays, whereas in the DIAGURO series, the specificity dropped for ddPCR (92.4% versus 95.6%). Overall, an almost perfect agreement between the two methods was observed for both US cfDNA (n = 164; kappa coefficient of 0.91) and UP cellDNA (n = 280; kappa coefficient of 0.94). In a large independent series of serial urine samples from DIAGURO follow-up BC cases (n = 394), the agreement between ddPCR and UroMuTERT was (i) strong (kappa coefficient of 0.87), regardless of urine DNA types (kappa coefficient 0.89 for US cfDNA and 0.85 for UP cellDNA), (ii) the highest for samples with mutant allelic fractions (MAFs) > 2% (kappa coefficient of 0.99) and (iii) only minimal for the samples with the lowest MAFs (< 0.5%; kappa coefficient 0.32). Altogether, our results indicate that the two methods (ddPCR and UroMuTERT) for detecting urinary TERT promoter mutations are comparable and that the discrepancies relate to the detection of low-allelic fraction mutations. The simplicity of the ddPCR assays makes them suitable for implementation in clinical settings.

Detecting Selection from Linked Sites Using an F-Model.

Allele frequencies vary across populations and loci, even in the presence of migration. While most differences may be due to genetic drift, divergent selection will further increase differentiation at some loci. Identifying those is key in studying local adaptation, but remains statistically challenging. A particularly elegant way to describe allele frequency differences among populations connected by migration is the F-model, which measures differences in allele frequencies by population specific FST coefficients. This model readily accounts for multiple evolutionary forces by partitioning FST coefficients into locus- and population-specific components reflecting selection and drift, respectively. Here we present an extension of this model to linked loci by means of a hidden Markov model (HMM), which characterizes the effect of selection on linked markers through correlations in the locus specific component along the genome. Using extensive simulations, we show that the statistical power of our method is up to twofold higher than that of previous implementations that assume sites to be independent. We finally evidence selection in the human genome by applying our method to data from the Human Genome Diversity Project (HGDP).

A molecular map of lung neuroendocrine neoplasms.

BACKGROUND: Lung neuroendocrine neoplasms (LNENs) are rare solid cancers, with most genomic studies including a limited number of samples. Recently, generating the first multi-omic dataset for atypical pulmonary carcinoids and the first methylation dataset for large-cell neuroendocrine carcinomas led us to the discovery of clinically relevant molecular groups, as well as a new entity of pulmonary carcinoids (supra-carcinoids). RESULTS: To promote the integration of LNENs molecular data, we provide here detailed information on data generation and quality control for whole-genome/exome sequencing, RNA sequencing, and EPIC 850K methylation arrays for a total of 84 patients with LNENs. We integrate the transcriptomic data with other previously published data and generate the first comprehensive molecular map of LNENs using the Uniform Manifold Approximation and Projection (UMAP) dimension reduction technique. We show that this map captures the main biological findings of previous studies and can be used as reference to integrate datasets for which RNA sequencing is available. The generated map can be interactively explored and interrogated on the UCSC TumorMap portal (https://tumormap.ucsc.edu/?p=RCG_lungNENomics/LNEN). The data, source code, and compute environments used to generate and evaluate the map as well as the raw data are available, respectively, in a Nextjournal interactive notebook (https://nextjournal.com/rarecancersgenomics/a-molecular-map-of-lung-neuroendocrine-neoplasms/) and at the EMBL-EBI European Genome-phenome Archive and Gene Expression Omnibus data repositories. CONCLUSIONS: We provide data and all resources needed to integrate them with future LNENs transcriptomic studies, allowing meaningful conclusions to be drawn that will eventually lead to a better understanding of this rare understudied disease.

Needlestack: an ultra-sensitive variant caller for multi-sample next generation sequencing data.

The emergence of next-generation sequencing (NGS) has revolutionized the way of reaching a genome sequence, with the promise of potentially providing a comprehensive characterization of DNA variations. Nevertheless, detecting somatic mutations is still a difficult problem, in particular when trying to identify low abundance mutations, such as subclonal mutations, tumour-derived alterations in body fluids or somatic mutations from histological normal tissue. The main challenge is to precisely distinguish between sequencing artefacts and true mutations, particularly when the latter are so rare they reach similar abundance levels as artefacts. Here, we present needlestack, a highly sensitive variant caller, which directly learns from the data the level of systematic sequencing errors to accurately call mutations. Needlestack is based on the idea that the sequencing error rate can be dynamically estimated from analysing multiple samples together. We show that the sequencing error rate varies across alterations, illustrating the need to precisely estimate it. We evaluate the performance of needlestack for various types of variations, and we show that needlestack is robust among positions and outperforms existing state-of-the-art method for low abundance mutations. Needlestack, along with its source code is freely available on the GitHub platform: https://github.com/IARCbioinfo/needlestack.

Circulating tumour-derived KRAS mutations in pancreatic cancer cases are predominantly carried by very short fragments of cell-free DNA.

BACKGROUND: The DNA released into the bloodstream by malignant tumours· called circulating tumour DNA (ctDNA), is often a small fraction of total cell-free DNA shed predominantly by hematopoietic cells and is therefore challenging to detect. Understanding the biological properties of ctDNA is key to the investigation of its clinical relevance as a non-invasive marker for cancer detection and monitoring. METHODS: We selected 40 plasma DNA samples of pancreatic cancer cases previously reported to carry a KRAS mutation at the 'hotspot' codon 12 and re-screened the cell-free DNA using a 4-size amplicons strategy (57 bp, 79 bp, 167 bp and 218 bp) combined with ultra-deep sequencing in order to investigate whether amplicon lengths could impact on the capacity of detection of ctDNA, which in turn could provide inference of ctDNA and non-malignant cell-free DNA size distribution. FINDINGS: Higher KRAS amplicon size (167 bp and 218 bp) was associated with lower detectable cell-free DNA mutant allelic fractions (p < 0·0001), with up to 4·6-fold (95% CI: 2·6-8·1) difference on average when comparing the 218bp- and the 57bp-amplicons. The proportion of cases with detectable KRAS mutations was also hampered with increased amplicon lengths, with only half of the cases having detectable ctDNA using the 218 bp assay relative to those detected with amplicons less than 80 bp. INTERPRETATION: Tumour-derived mutations are carried by shorter cell-free DNA fragments than fragments of wild-type allele. Targeting short amplicons increases the sensitivity of cell-free DNA assays for pancreatic cancer and should be taken into account for optimized assay design and for evaluating their clinical performance. FUNDING: IARC; MH CZ - DRO; MH SK; exchange program between IARC and Sao Paulo medical Sciences; French Cancer League.

Urinary TERT promoter mutations are detectable up to 10 years prior to clinical diagnosis of bladder cancer: Evidence from the Golestan Cohort Study.

BACKGROUND: Detecting pre-clinical bladder cancer (BC) using urinary biomarkers may provide a valuable opportunity for screening and management. Telomerase reverse transcriptase (TERT) promoter mutations detectable in urine have emerged as promising BC biomarkers. METHODS: We performed a nested case-control study within the population-based prospective Golestan Cohort Study (50,045 participants, followed up to 14 years) and assessed TERT promoter mutations in baseline urine samples from 38 asymptomatic individuals who subsequently developed primary BC and 152 matched controls using a Next-Generation Sequencing-based single-plex assay (UroMuTERT) and droplet digital PCR assays. FINDINGS: Results were obtained for 30 cases and 101 controls. TERT promoter mutations were detected in 14 pre-clinical cases (sensitivity 46·67%) and none of the controls (specificity 100·00%). At an estimated BC cumulative incidence of 0·09% in the cohort, the positive and negative predictive values were 100·00% and 99·95% respectively. The mutant allelic fractions decreased with the time interval from urine collection until BC diagnosis (p = 0·033) but the mutations were detectable up to 10 years prior to clinical diagnosis. INTERPRETATION: Our results provide the first evidence from a population-based prospective cohort study of the potential of urinary TERT promoter mutations as promising non-invasive biomarkers for early detection of BC. Further studies should validate this finding and assess their clinical utility in other longitudinal cohorts. FUNDING: French Cancer League, World Cancer Research Fund International, Cancer Research UK, Tehran University of Medical Sciences, the International Agency for Research on Cancer, and the U.S. National Cancer Institute.

EURACAN/IASLC Proposals for Updating the Histologic Classification of Pleural Mesothelioma: Towards a More Multidisciplinary Approach.

INTRODUCTION: Molecular and immunologic breakthroughs are transforming the management of thoracic cancer, although advances have not been as marked for malignant pleural mesothelioma where pathologic diagnosis has been essentially limited to three histologic subtypes. METHODS: A multidisciplinary group (pathologists, molecular biologists, surgeons, radiologists, and oncologists), sponsored by European Network for Rare Adult Solid Cancers/International Association for the Study of Lung Cancer, met in 2018 to critically review the current classification. RESULTS: Recommendations include: (1) classification should be updated to include architectural patterns and stromal and cytologic features that refine prognostication; (2) subject to data accrual, malignant mesothelioma in situ could be an additional category; (3) grading of epithelioid malignant pleural mesotheliomas should be routinely undertaken; (4) favorable/unfavorable histologic characteristics should be routinely reported; (5) clinically relevant molecular data (programmed death ligand 1, BRCA 1 associated protein 1 [BAP1], and cyclin dependent kinase inhibitor 2A) should be incorporated into reports, if undertaken; (6) other molecular data should be accrued as part of future trials; (7) resection specimens (i.e., extended pleurectomy/decortication and extrapleural pneumonectomy) should be pathologically staged with smaller specimens being clinically staged; (8) ideally, at least three separate areas should be sampled from the pleural cavity, including areas of interest identified on pre-surgical imaging; (9) image-acquisition protocols/imaging terminology should be standardized to aid research/refine clinical staging; (10) multidisciplinary tumor boards should include pathologists to ensure appropriate treatment options are considered; (11) all histologic subtypes should be considered potential candidates for chemotherapy; (12) patients with sarcomatoid or biphasic mesothelioma should not be excluded from first-line clinical trials unless there is a compelling reason; (13) tumor subtyping should be further assessed in relation to duration of response to immunotherapy; and (14) systematic screening of all patients for germline mutations is not recommended, in the absence of a family history suspicious for BAP1 syndrome. CONCLUSIONS: These multidisciplinary recommendations for pathology classification and application will allow more informative pathologic reporting and potential risk stratification, to support clinical practice, research investigation and clinical trials.

Redefining malignant pleural mesothelioma types as a continuum uncovers immune-vascular interactions.

BACKGROUND: Malignant Pleural Mesothelioma (MPM) is an aggressive disease related to asbestos exposure, with no effective therapeutic options. METHODS: We undertook unsupervised analyses of RNA-sequencing data of 284 MPMs, with no assumption of discreteness. Using immunohistochemistry, we performed an orthogonal validation on a subset of 103 samples and a biological replication in an independent series of 77 samples. FINDINGS: A continuum of molecular profiles explained the prognosis of the disease better than any discrete model. The immune and vascular pathways were the major sources of molecular variation, with strong differences in the expression of immune checkpoints and pro-angiogenic genes; the extrema of this continuum had specific molecular profiles: a "hot" bad-prognosis profile, with high lymphocyte infiltration and high expression of immune checkpoints and pro-angiogenic genes; a "cold" bad-prognosis profile, with low lymphocyte infiltration and high expression of pro-angiogenic genes; and a "VEGFR2+/VISTA+" better-prognosis profile, with high expression of immune checkpoint VISTA and pro-angiogenic gene VEGFR2. We validated the gene expression levels at the protein level for a subset of five selected genes belonging to the immune and vascular pathways (CD8A, PDL1, VEGFR3, VEGFR2, and VISTA), in the validation series, and replicated the molecular profiles as well as their prognostic value in the replication series. INTERPRETATION: The prognosis of MPM is best explained by a continuous model, which extremes show specific expression patterns of genes involved in angiogenesis and immune response.

Sex specific associations in genome wide association analysis of renal cell carcinoma.

Renal cell carcinoma (RCC) has an undisputed genetic component and a stable 2:1 male to female sex ratio in its incidence across populations, suggesting possible sexual dimorphism in its genetic susceptibility. We conducted the first sex-specific genome-wide association analysis of RCC for men (3227 cases, 4916 controls) and women (1992 cases, 3095 controls) of European ancestry from two RCC genome-wide scans and replicated the top findings using an additional series of men (2261 cases, 5852 controls) and women (1399 cases, 1575 controls) from two independent cohorts of European origin. Our study confirmed sex-specific associations for two known RCC risk loci at 14q24.2 (DPF3) and 2p21(EPAS1). We also identified two additional suggestive male-specific loci at 6q24.3 (SAMD5, male odds ratio (ORmale) = 0.83 [95% CI = 0.78-0.89], Pmale = 1.71 × 10-8 compared with female odds ratio (ORfemale) = 0.98 [95% CI = 0.90-1.07], Pfemale = 0.68) and 12q23.3 (intergenic, ORmale = 0.75 [95% CI = 0.68-0.83], Pmale = 1.59 × 10-8 compared with ORfemale = 0.93 [95% CI = 0.82-1.06], Pfemale = 0.21) that attained genome-wide significance in the joint meta-analysis. Herein, we provide evidence of sex-specific associations in RCC genetic susceptibility and advocate the necessity of larger genetic and genomic studies to unravel the endogenous causes of sex bias in sexually dimorphic traits and diseases like RCC.