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.

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.

Comprehensive genomic profiles of small cell lung cancer.

We have sequenced the genomes of 110 small cell lung cancers (SCLC), one of the deadliest human cancers. In nearly all the tumours analysed we found bi-allelic inactivation of TP53 and RB1, sometimes by complex genomic rearrangements. Two tumours with wild-type RB1 had evidence of chromothripsis leading to overexpression of cyclin D1 (encoded by the CCND1 gene), revealing an alternative mechanism of Rb1 deregulation. Thus, loss of the tumour suppressors TP53 and RB1 is obligatory in SCLC. We discovered somatic genomic rearrangements of TP73 that create an oncogenic version of this gene, TP73Δex2/3. In rare cases, SCLC tumours exhibited kinase gene mutations, providing a possible therapeutic opportunity for individual patients. Finally, we observed inactivating mutations in NOTCH family genes in 25% of human SCLC. Accordingly, activation of Notch signalling in a pre-clinical SCLC mouse model strikingly reduced the number of tumours and extended the survival of the mutant mice. Furthermore, neuroendocrine gene expression was abrogated by Notch activity in SCLC cells. This first comprehensive study of somatic genome alterations in SCLC uncovers several key biological processes and identifies candidate therapeutic targets in this highly lethal form of cancer.

A common classification framework for neuroendocrine neoplasms: an International Agency for Research on Cancer (IARC) and World Health Organization (WHO) expert consensus proposal.

The classification of neuroendocrine neoplasms (NENs) differs between organ systems and currently causes considerable confusion. A uniform classification framework for NENs at any anatomical location may reduce inconsistencies and contradictions among the various systems currently in use. The classification suggested here is intended to allow pathologists and clinicians to manage their patients with NENs consistently, while acknowledging organ-specific differences in classification criteria, tumor biology, and prognostic factors. The classification suggested is based on a consensus conference held at the International Agency for Research on Cancer (IARC) in November 2017 and subsequent discussion with additional experts. The key feature of the new classification is a distinction between differentiated neuroendocrine tumors (NETs), also designated carcinoid tumors in some systems, and poorly differentiated NECs, as they both share common expression of neuroendocrine markers. This dichotomous morphological subdivision into NETs and NECs is supported by genetic evidence at specific anatomic sites as well as clinical, epidemiologic, histologic, and prognostic differences. In many organ systems, NETs are graded as G1, G2, or G3 based on mitotic count and/or Ki-67 labeling index, and/or the presence of necrosis; NECs are considered high grade by definition. We believe this conceptual approach can form the basis for the next generation of NEN classifications and will allow more consistent taxonomy to understand how neoplasms from different organ systems inter-relate clinically and genetically.

Genomic architecture of lung cancers.

PURPOSE OF REVIEW: Lung cancer remains the most frequent cancer worldwide and the leading cause of cancer death in most countries. The molecular characteristics of lung tumors play an important role in clinical decisions, which ultimately affect patients' survival. This review aims to summarize the most recent genomic discoveries made on lung cancer. RECENT FINDINGS: A relatively comprehensive molecular characterization has been achieved for the three major types of lung cancer: adenocarcinoma, squamous-cell carcinoma, and small-cell carcinoma. Little is still known about large-cell neuroendocrine carcinoma and carcinoid tumors. A major finding has been the nonnegligible inter and intratumor heterogeneity of lung cancer and their impact in the clinical management of this disease. SUMMARY: The high load of mutations, the frequent inactivation of major tumor suppressor genes, and the huge heterogeneity of lung cancer tumors may complicate long-lasting therapeutic responses. The development of strategies for the early detection of lung cancer might translate into an increase of the number of surgical resectable tumors, and therefore contribute to improve the survival rate of these patients.

Lung cancers with acquired resistance to EGFR inhibitors occasionally harbor BRAF gene mutations but lack mutations in KRAS, NRAS, or MEK1.

Acquired resistance to EGF receptor (EGFR) tyrosine kinase inhibitors (TKIs) is inevitable in metastatic EGFR-mutant lung cancers. Here, we modeled disease progression using EGFR-mutant human tumor cell lines. Although five of six models displayed alterations already found in humans, one harbored an unexpected secondary NRAS Q61K mutation; resistant cells were sensitive to concurrent EGFR and MEK inhibition but to neither alone. Prompted by this finding and because RAS/RAF/MEK mutations are known mediators of acquired resistance in other solid tumors (colon cancers, gastrointestinal stromal tumors, and melanomas) responsive to targeted therapies, we analyzed the frequency of secondary KRAS/NRAS/BRAF/MEK1 gene mutations in the largest collection to date of lung cancers with acquired resistance to EGFR TKIs. No recurrent NRAS, KRAS, or MEK1 mutations were found in 212, 195, or 146 patient samples, respectively, but 2 of 195 (1%) were found to have mutations in BRAF (G469A and V600E). Ectopic expression of mutant NRAS or BRAF in drug-sensitive EGFR-mutant cells conferred resistance to EGFR TKIs that was overcome by addition of a MEK inhibitor. Collectively, these positive and negative results provide deeper insight into mechanisms of acquired resistance to EGFR TKIs in lung cancer and inform ongoing clinical trials designed to overcome resistance. In the context of emerging knowledge about mechanisms of acquired resistance to targeted therapies in various cancers, our data highlight the notion that, even though solid tumors share common signaling cascades, mediators of acquired resistance must be elucidated for each disease separately in the context of treatment.

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.

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.

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.

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.

Prognostic and predictive value of TP53 mutations in node-positive breast cancer patients treated with anthracycline- or anthracycline/taxane-based adjuvant therapy: results from the BIG 02-98 phase III trial.

INTRODUCTION: Pre-clinical data suggest p53-dependent anthracycline-induced apoptosis and p53-independent taxane activity. However, dedicated clinical research has not defined a predictive role for TP53 gene mutations. The aim of the current study was to retrospectively explore the prognosis and predictive values of TP53 somatic mutations in the BIG 02-98 randomized phase III trial in which women with node-positive breast cancer were treated with adjuvant doxorubicin-based chemotherapy with or without docetaxel. METHODS: The prognostic and predictive values of TP53 were analyzed in tumor samples by gene sequencing within exons 5 to 8. Patients were classified according to p53 protein status predicted from TP53 gene sequence, as wild-type (no TP53 variation or TP53 variations which are predicted not to modify p53 protein sequence) or mutant (p53 nonsynonymous mutations). Mutations were subcategorized according to missense or truncating mutations. Survival analyses were performed using the Kaplan-Meier method and log-rank test. Cox-regression analysis was used to identify independent predictors of outcome. RESULTS: TP53 gene status was determined for 18% (520 of 2887) of the women enrolled in BIG 02-98. TP53 gene variations were found in 17% (90 of 520). Nonsynonymous p53 mutations, found in 16.3% (85 of 520), were associated with older age, ductal morphology, higher grade and hormone-receptor negativity. Of the nonsynonymous mutations, 12.3% (64 of 520) were missense and 3.6% were truncating (19 of 520). Only truncating mutations showed significant independent prognostic value, with an increased recurrence risk compared to patients with non-modified p53 protein (hazard ratio = 3.21, 95% confidence interval = 1.740 to 5.935, P = 0.0002). p53 status had no significant predictive value for response to docetaxel. CONCLUSIONS: p53 truncating mutations were uncommon but associated with poor prognosis. No significant predictive role for p53 status was detected. TRIAL REGISTRATION: ClinicalTrials.gov NCT00174655.

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.

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.

p53 status influences response to tamoxifen but not to fulvestrant in breast cancer cell lines.

Mutations in the tumor suppressor gene TP53 are associated with poor prognosis in breast cancer. This prognostic value may rely in part on the fact that p53 plays a role in the antiproliferative and apoptotic activities of chemotherapy regimens used to treat breast tumors. However, some studies suggested that p53 may also influence response to antihormone treatments. Here we investigate how p53 may affect response to antihormonal treatments, using estrogen-dependent breast cancer cell-lines with different p53 status. We show that p53 mutated cells were more resistant to cytotoxic effects of 4-hydroxy-tamoxifen (OHT) compared to p53 wild-type cells. In contrast, p53 status did not significantly impact on response to fulvestrant. p53 mutated cells were also hypersensitive to proliferative effects of estradiol. Interestingly, OHT at doses in the low range had proliferative activities in p53 mutated cells (120-150% proliferation rate under 1 µM OHT treatment in low estrogen conditions). Using gene silencing or specific tyrosine kinase inhibitors, we show that the proliferative effects of OHT were estrogen receptor dependent and could be abrogated by the inhibition of EGFR and/or HER2 kinases. These findings suggest that loss of p53 function may increase cross-talks between estrogen receptor and EGFR/HER2 pathways, contributing to a proliferative effect of OHT. These results bring new insights into the prognostic role of p53 in breast cancer and into possible mechanisms underlying tamoxifen resistance.

Estrogen levels act as a rheostat on p53 levels and modulate p53-dependent responses in breast cancer cell lines.

A large proportion of breast cancers expresses the estrogen receptor alpha (ERα) and are dependent on estrogens for their proliferation and survival. The tumor suppressor TP53 encodes the p53 protein, an important mediator of the anti-proliferative and apoptotic effects of several treatments used for breast cancer. A significant proportions of breast tumors (20-30%) carry mutations in TP53 gene and these mutations are associated with poor survival and poor response to several types of chemotherapeutic treatments. While there is mounting evidence for functional interactions between p53 and ERα pathways in breast and other tissues, the impact of these interactions on response to chemotherapy and anti-hormone treatments remain largely unknown. Here, using estrogen-dependent breast cancer cell lines with different p53 status, we show that estrogens, through ERα, influence p53 protein levels and activities. Estrogen deprivation reduced, while estradiol increased p53 levels, in a time and dose-dependent manner. Both wild-type and endogenously expressed mutant p53 proteins were affected. This reduction in p53 protein levels resulted in reduced p53-dependent responses induced by DNA damage in p53 wild-type cells, lowering the capacity of doxorubicine to induce apoptosis. The p53 response appeared to be quantitatively but not qualitatively affected. These results suggest that ERα activity is required for a strong p53 response in estrogen-dependent breast cancer cells. These results are in line with previous observations that we made in a clinical series, where a larger effect of TP53 mutation status was found for patient survival in cases with progesterone receptor positive status, a marker of a functional ERα pathway. It would thus be important to further characterize the influence of ERα pathway on the predictive value of TP53 mutation status in specifically designed clinical trials, as it may open perspectives for improving breast cancer treatment.

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.

New molecular classification of large cell neuroendocrine carcinoma and small cell lung carcinoma with potential therapeutic impacts.

Large cell neuroendocrine carcinoma (LCNECs) and small cell lung carcinomas (SCLCs) are high-grade neuroendocrine carcinomas of the lung with very aggressive behavior and poor prognosis. Their histological classification as well as their therapeutic management has not changed much in recent years, but genomic and transcriptomic analyses have revealed different molecular subtypes raising hopes for more personalized treatment. Indeed, four subtypes of SCLCs have been recently described, SCLC-A driven by the master gene ASCL1, SCLC-N driven by NEUROD1, SCLC-Y by YAP1 and SCLC-P by POU2F3. Whereas SCLC standard of care is based on concurrent chemoradiation for limited stages and on chemotherapy alone or chemotherapy combined with anti-PD-L1 checkpoint inhibitors for extensive stage SCLC, SCLC-A variants could benefit from DLL3 or BCL2 inhibitors, and SCLC-N variants from Aurora kinase inhibitors combined with chemotherapy, or PI3K/mTOR or HSP90 inhibitors. In addition, a new SCLC variant (SCLC-IM) with high-expression of immune checkpoints has been also reported, which could benefit from immunotherapies. PARP inhibitors also gave promising results in combination with chemotherapy in a subset of SCLCs. Regarding LCNECs, they represent a heterogeneous group of tumors, some of them exhibiting mutations also found in SCLC but with a pattern of expression of NSCLC, while others harbor mutations also found in NSCLC but with a pattern of expression of SCLC, questioning their clinical management as NSCLCs or SCLCs. Overall, we are probably entering a new area, which, if personalized treatments are effective, will also lead to the implementation in practice of molecular testing or biomarkers detection for the selection of patients who can benefit from them.

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.

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.