The molecular characteristics of high-grade gastroenteropancreatic neuroendocrine neoplasms

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Abstract

High-grade (HG) gastroenteropancreatic (GEP) neuroendocrine neoplasms (NEN) are rare but have a very poor prognosis and represent a severely understudied class of tumours. Molecular data for HG GEP-NEN are limited, and treatment strategies for the carcinoma subgroup (HG GEP-NEC) are extrapolated from small-cell lung cancer (SCLC). After pathological re-evaluation, we analysed DNA from tumours and matched blood samples from 181 HG GEP-NEN patients; 152 neuroendocrine carcinomas (NEC) and 29 neuroendocrine tumours (NET G3). Based on the sequencing of 360 cancer-related genes, we assessed mutations and copy number alterations (CNA). For NEC, frequently mutated genes were TP53 (64%), APC (28%), KRAS (22%) and BRAF (20%). RB1 was only mutated in 14%, but CNAs affecting RB1 were seen in 34%. Other frequent copy number losses were ARID1A (35%), ESR1 (25%) and ATM (31%). Frequent amplifications/gains were found in MYC (51%) and KDM5A (45%). While these molecular features had limited similarities with SCLC, we found potentially targetable alterations in 66% of the NEC samples. Mutations and CNA varied according to primary tumour site with BRAF mutations mainly seen in colon (49%), and FBXW7 mutations mainly seen in rectal cancers (25%). Eight out of 152 (5.3%) NEC were microsatellite instable (MSI). NET G3 had frequent mutations in MEN1 (21%), ATRX (17%), DAXX, SETD2 and TP53 (each 14%). We show molecular differences in HG GEP-NEN, related to morphological differentiation and site of origin. Limited similarities to SCLC and a high fraction of targetable alterations indicate a high potential for better-personalized treatments.

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Fast and accurate short read alignment with Burrows–Wheeler transform

Heng Li, Richard Durbin (2009)

Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: rd@sanger.ac.uk

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Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden

Zachary Chalmers, Caitlin Connelly, David Fabrizio … (2017)

Background High tumor mutational burden (TMB) is an emerging biomarker of sensitivity to immune checkpoint inhibitors and has been shown to be more significantly associated with response to PD-1 and PD-L1 blockade immunotherapy than PD-1 or PD-L1 expression, as measured by immunohistochemistry (IHC). The distribution of TMB and the subset of patients with high TMB has not been well characterized in the majority of cancer types. Methods In this study, we compare TMB measured by a targeted comprehensive genomic profiling (CGP) assay to TMB measured by exome sequencing and simulate the expected variance in TMB when sequencing less than the whole exome. We then describe the distribution of TMB across a diverse cohort of 100,000 cancer cases and test for association between somatic alterations and TMB in over 100 tumor types. Results We demonstrate that measurements of TMB from comprehensive genomic profiling are strongly reflective of measurements from whole exome sequencing and model that below 0.5 Mb the variance in measurement increases significantly. We find that a subset of patients exhibits high TMB across almost all types of cancer, including many rare tumor types, and characterize the relationship between high TMB and microsatellite instability status. We find that TMB increases significantly with age, showing a 2.4-fold difference between age 10 and age 90 years. Finally, we investigate the molecular basis of TMB and identify genes and mutations associated with TMB level. We identify a cluster of somatic mutations in the promoter of the gene PMS2, which occur in 10% of skin cancers and are highly associated with increased TMB. Conclusions These results show that a CGP assay targeting ~1.1 Mb of coding genome can accurately assess TMB compared with sequencing the whole exome. Using this method, we find that many disease types have a substantial portion of patients with high TMB who might benefit from immunotherapy. Finally, we identify novel, recurrent promoter mutations in PMS2, which may be another example of regulatory mutations contributing to tumorigenesis. Electronic supplementary material The online version of this article (doi:10.1186/s13073-017-0424-2) contains supplementary material, which is available to authorized users.

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GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers

Craig H. Mermel, Steven Schumacher, Barbara Hill … (2011)

We describe methods with enhanced power and specificity to identify genes targeted by somatic copy-number alterations (SCNAs) that drive cancer growth. By separating SCNA profiles into underlying arm-level and focal alterations, we improve the estimation of background rates for each category. We additionally describe a probabilistic method for defining the boundaries of selected-for SCNA regions with user-defined confidence. Here we detail this revised computational approach, GISTIC2.0, and validate its performance in real and simulated datasets.

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Author and article information

Journal

Journal ID (nlm-ta): Endocr Relat Cancer

Journal ID (iso-abbrev): Endocr Relat Cancer

Journal ID (hwp): ERC

Title: Endocrine-Related Cancer

Publisher: Bioscientifica Ltd (Bristol )

ISSN (Print): 1351-0088

ISSN (Electronic): 1479-6821

Publication date (Electronic): 14 October 2021

Publication date Collection: 01 January 2022

Volume: 29

Issue: 1

Pages: 1-14

Affiliations

[1 ]K.G. Jebsen Center for Genome-Directed Cancer Therapy , Department of Clinical Science, University of Bergen, Bergen, Norway

[2 ]Department of Oncology , Haukeland University Hospital, Bergen, Norway

[3 ]Department of Oncology , Ålesund Hospital, Møre og Romsdal Hospital Trust, Ålesund, Norway

[4 ]Department of Clinical and Molecular Medicine , Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway

[5 ]Institute of Pathology , University of Bern, Bern, Switzerland

[6 ]Department of Pathology , Oslo University Hospital, Oslo, Norway

[7 ]Department of Pathology , Université de Paris, Bichat Hospital, AP-HP, Paris, France

[8 ]Department of Oncology , Oslo University Hospital, Oslo, Norway

[9 ]Departmentt of Oncology , Skåne University Hospital, Lund, Sweden

[10 ]Department of Medical Radiation Physics , Lund University, Lund, Sweden

[11 ]Department of Oncology , Sahlgrenska University Hospital, Gothenburg, Sweden

[12 ]Department of Oncology , Stavanger University Hospital, Stavanger, Norway

[13 ]Department of Research , Hospital of Southern Norway, Kristiansand, Norway

[14 ]Department of Oncology , St.Olavs Hospital, Trondheim, Norway

[15 ]Department of Pathology , Odense University Hospital, Odense, Denmark

[16 ]Department of Clinical Medicine , Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark

[17 ]Department of Oncology , Odense University Hospital, Odense, Denmark

[18 ]Department of Clinical Science , University of Bergen, Bergen, Norway

Author notes

Correspondence should be addressed to H Sorbye or S Knappskog: halfdan.sorbye@ 123456helse-bergen.no or stian.knappskog@ 123456uib.no

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Oleksii Nikolaienko http://orcid.org/0000-0002-5910-4934

Article

Publisher ID: ERC-21-0152

DOI: 10.1530/ERC-21-0152

PMC ID: 8630776

PubMed ID: 34647903

SO-VID: 0fe10328-9330-4e94-a928-9e5ec6ad32d5

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This work is licensed under a Creative Commons Attribution 4.0 International License.

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The molecular characteristics of high-grade gastroenteropancreatic neuroendocrine neoplasms

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Most cited references 54

Fast and accurate short read alignment with Burrows–Wheeler transform

Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden

GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers

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