Variants del número de còpia al càncer colorectal: predisposició germinal i perfils genòmics tumorals

[cat] El càncer de còlon i recte, o càncer colorectal (CCR), és el tercer tipus de càncer amb més incidència mundial quan ambdós sexes es tenen en compte. El CCR sorgeix per l’acumulació de mutacions genètiques en gens claus que provoquen la progressió del teixit normal i fins al desenvolupament final del càncer. El CCR és d’entre les neoplàsies comuns la que presenta més proporció de casos amb agregació familiar. Estudis de parents i de bessons han estimat que un 30-35% dels casos de CCR presenten alguna forma d’herència familiar de la malaltia, o CCR germinal. Aproximadament un quart dels casos que presenten agregació familiar per CCR s’identifiquen entre les anomenades formes hereditàries, associades a mutacions d’alta penetrància en gens coneguts i que aporten alt risc a desenvolupar la malaltia. Les variants de número de còpia (CNVs, copy number variants) formen part del conjunt de les variants estructurals i representen variacions genòmiques “no balancejades” (duplicacions o delecions), alterant el caràcter diploide del genoma i aportant diversitat a la població genètica humana. Gràcies al desenvolupament de mètodes estadístics aplicats a l’anàlisi de dades de seqüenciació massiva, aquestes formes de variants genòmiques estructurals també poden ésser detectades mitjançant la seva inferència en dades de seqüenciació de l’exoma o del genoma. La predisposició genètica de molts casos amb forta agregació familiar per CCR i que no presenten mutacions als gens de les formes hereditàries encara és desconeguda. El primer estudi d’aquesta tesi presenta la identificació de CNVs potencialment implicades en la predisposició al CCR en famílies amb forta agregació per aquesta patologia, mitjançant la seva inferència en les dades de seqüenciació de l’exoma del DNA germinal de membres d’aquestes famílies. S’ha identificat, validat i caracteritzat una duplicació de 392 Kb del cromosoma 1 (chr1:117591257-117982865) en una de les famílies estudiades. En la regió genòmica de la duplicació s’hi localitzen quatre gens (TTF2, TRIM45, VTCN1 i MAN1A2) i un miRNA (MIR942), localitzat en l’intró 18 del gen TTF2. Per tal de caracteritzar els possibles efectes moleculars de la variant a sobre d’aquests gens, s’han estudiat els nivells d’expressió gènica i proteica d’aquests. D’altra banda, el concepte d’alteracions del número de còpia (CNAs, copy number alterations) va molt lligat al context tumoral somàtic. L’aneuploïdia, o adquisició d’alteracions numèriques i estructurals dels cromosomes, es considera un dels processos més importants a l’hora de facilitar la progressió tumoral, diferenciant-se entre les alteracions àmplies (broad): guanys i pèrdues de cromosomes o braços cromosòmics; i les alteracions focals, que afecten regions puntuals del genoma. Diversos estudis han demostrat la presència de patrons recurrents de CNAs específiques entre els distints tipus de càncer. La caracterització i integració d’aquest tipus d’esdeveniments genòmics amb anotacions moleculars o clíniques pot ajudar a la identificació de CNAs com a potencials bio-marcadors. Al segon estudi d’aquesta tesi s’ha desenvolupat l’eina bioinformàtica CNApp, amb l’objectiu d’analitzar i integrar la detecció de CNAs amb les anotacions molecular i/o clíniques disponibles en les mostres estudiades. CNApp genera perfils complets del genoma utilitzant segments genòmics, calcula la càrrega de CNAs diferenciant entre alteracions broad i focals, i utilitza sistemes d’aprenentatge automàtic per a la re-classificació de mostres. Aplicant aquesta eina a les 10.635 mostres del consorci TCGA, s’ha aconseguit diferenciar els distints tipus tumorals d’acord al seu perfil genòmic i segons el seu teixit d’origen. A més, CNApp ha estat capaç de re-classificar els distints subtipus moleculars de CCR depenent dels nivells de càrrega d’alteracions broad o focals, a més d’identificar certes regions genòmiques específiques entre els mateixos subtipus. CNApp facilita l’anàlisi de dades genòmiques amb un maneig senzill i òptim, i és accessible a https://tools.idibaps.org/CNApp/.[eng] Colorectal cancer (CRC) is the third most common cancer worldwide. A considerable number of cases with strong familial CRC aggregation and early disease onset remain unresolved at the genetic level. The first work analyzes germline whole- exome sequencing data from 38 families with strong CRC aggregation without alterations in known hereditary genes to infer rare candidate copy number variants involved in the predisposition to this disease. A duplication in chromosome 1 in one family stood out as interesting. TTF2, TRIM45, VTCN1 and MIR942 genes were found to be included in the duplication. Expression studies pointed to TTF2 and MIR942 overexpression in duplication carriers, and tumor immunohistochemistry showed TTF2 protein overexpression and under-expression of the TMEM158 protein, a predicted target of MIR942. The identified duplication may correspond to the mutational event involved in colorectal cancer predisposition in this family. On the other hand, somatic copy number alterations (CNAs) are a hallmark of cancer, but their role in tumorigenesis and clinical relevance remain largely unclear. In the second study, we developed CNApp, a web- based tool that allows a comprehensive exploration of CNAs by using genomic segmented data. CNApp generates genome-wide profiles, computes CNA scores for broad, focal and global CNA burdens, and uses machine learning-based predictions to classify samples. We applied CNApp to the TCGA pan-cancer dataset of 10,635 genomes showing that CNAs classify cancer types according to their tissue-of-origin, and that each cancer type shows specific ranges of broad and focal CNA scores. Moreover, CNApp reproduces recurrent CNAs in hepatocellular carcinoma and predicts colon cancer molecular subtypes and microsatellite instability based on broad CNA scores and discrete genomic imbalances. In summary, CNApp facilitates CNA-driven research by providing a unique framework to identify relevant clinical implications. CNApp is hosted at https://tools.idibaps.org/CNApp/

The landscape of genomic copy number alterations in colorectal cancer and their consequences on gene expression levels and disease outcome

This work has been supported by the Instituto de Salud Carlos III and co-funded by the European Regional Development Fund (ERDF) [CP13/00160, PI14/00783, PI17/01304 to JC]; the Agència de Gestió d'Ajuts Universitaris i de Recerca, Generalitat de Catalunya [2017 SGR 1035]; PERIS Generalitat de Catalunya [SLT002/16/00398 to JC]; Fundación Científica de la Asociación Española Contra el Cáncer [GCB13131592CAST]; the intramural program of the National Institutes of Health. CIBEREHD is funded by the Instituto de Salud Carlos III. This article is based upon work from COST Action [CA17118], supported by COST (European Cooperation in Science and Technology). RB is supported by a REACH HIGH Scholars Programme-PostDoctoral Grants. The grant is part-financed by the EU, Operational Programme II-Cohesion Policy 2014–2020 investing in human capital to create more opportunities and promote the wellbeing of society-European Social Fund.Aneuploidy, the unbalanced state of the chromosome content, represents a hallmark of most solid tumors, including colorectal cancer. Such aneuploidies result in tumor specific genomic imbalances, which emerge in premalignant precursor lesions. Moreover, increasing levels of chromosomal instability have been observed in adenocarcinomas and are maintained in distant metastases. A number of studies have systematically integrated copy number alterations with gene expression changes in primary carcinomas, cell lines, and experimental models of aneuploidy. In fact, chromosomal aneuploidies target a number of genes conferring a selective advantage for the metabolism of the cancer cell. Copy number alterations not only have a positive correlation with expression changes of the majority of genes on the altered genomic segment, but also have effects on the transcriptional levels of genes genome-wide. Finally, copy number alterations have been associated with disease outcome; nevertheless, the translational applicability in clinical practice requires further studies. Here, we (i) review the spectrum of genetic alterations that lead to colorectal cancer, (ii) describe the most frequent copy number alterations at different stages of colorectal carcinogenesis, (iii) exemplify their positive correlation with gene expression levels, and (iv) discuss copy number alterations that are potentially involved in disease outcome of individual patients.Publisher PDFPeer reviewe

Approaches to functionally validate candidate genetic variants involved in colorectal cancer predisposition

Most next generation sequencing (NGS) studies identified candidate genetic variants predisposing to colorectal cancer (CRC) but do not tackle its functional interpretation to unequivocally recognize a new hereditary CRC gene. Besides, germline variants in already established hereditary CRC-predisposing genes or somatic variants share the same need when trying to categorize those with relevant significance. Functional genomics approaches have an important role in identifying the causal links between genetic architecture and phenotypes, in order to decipher cellular function in health and disease. Therefore, functional interpretation of identified genetic var iants by NGS platforms is now essential. Available approaches nowadays include bioinformatics, cell and mo lecular biology and animal models. Recent advances, such as the CRISPR-Cas9, ZFN and TALEN systems, have been already used as a powerful tool with this objective. However, the use of cell lines is of limited value due to the CRC heterogeneity and its close interaction with microenvironment. Access to tridimensional cultures or organoids and xenograft models that mimic the in vivo tissue architecture could revolutionize functional ana lysis. This review will focus on the application of state-of-the-art functional studies to better tackle new genes involved in germline predisposition to this neoplasm

CNApp, a tool for the quantification of copy number alterations and integrative analysis revealing clinical implications.

Somatic copy number alterations (CNAs) are a hallmark of cancer, but their role in tumorigenesis and clinical relevance remain largely unclear. Here, we developed CNApp, a web-based tool that allows a comprehensive exploration of CNAs by using purity-corrected segmented data from multiple genomic platforms. CNApp generates genome-wide profiles, computes CNA scores for broad, focal and global CNA burdens, and uses machine learning-based predictions to classify samples. We applied CNApp to the TCGA pan-cancer dataset of 10,635 genomes showing that CNAs classify cancer types according to their tissue-of-origin, and that each cancer type shows specific ranges of broad and focal CNA scores. Moreover, CNApp reproduces recurrent CNAs in hepatocellular carcinoma and predicts colon cancer molecular subtypes and microsatellite instability based on broad CNA scores and discrete genomic imbalances. In summary, CNApp facilitates CNA-driven research by providing a unique framework to identify relevant clinical implications. CNApp is hosted at https://tools.idibaps.org/CNApp/

Using linkage studies combined with whole-exome sequencing to identify novel candidate genes for familial colorectal cancer

Colorectal cancer (CRC) is a complex disorder for which the majority of the underlying germline predisposition factors remain still unidentified. Here, we combined whole‐exome sequencing (WES) and linkage analysis in families with multiple relatives affected by CRC to identify candidate genes harboring rare variants with potential high‐penetrance effects. Forty‐seven affected subjects from 18 extended CRC families underwent WES. Genome‐wide linkage analysis was performed under linear and exponential models. Suggestive linkage peaks were identified on chromosomes 1q22-q24.2 (maxSNP = rs2134095; LODlinear = 2.38, LODexp = 2.196), 7q31.2-q34 (maxSNP = rs6953296; LODlinear = 2.197, LODexp = 2.149) and 10q21.2-q23.1 (maxSNP = rs1904589; LODlinear = 1.445, LODexp = 2.195). These linkage signals were replicated in 10 independent sets of random markers from each of these regions. To assess the contribution of rare variants predicted to be pathogenic, we performed a family‐based segregation test with 89 rare variants predicted to be deleterious from 78 genes under the linkage intervals. This analysis showed significant segregation of rare variants with CRC in 18 genes (weighted p‐value > 0.0028). Protein network analysis and functional evaluation were used to suggest a plausible candidate gene for germline CRC predisposition. Etiologic rare variants implicated in cancer germline predisposition may be identified by combining traditional linkage with WES data. This approach can be used with already available NGS data from families with several sequenced members to further identify candidate genes involved germline predisposition to disease. This approach resulted in one candidate gene associated with increased risk of CRC but needs evidence from further studies

Identification of a Novel Candidate Gene for Serrated Polyposis Syndrome Germline Predisposition by Performing Linkage Analysis Combined With Whole-Exome Sequencing

SUPPLEMENTARY MATERIAL accompanies this paper athttp://links.lww.com/CTG/A114OBJECTIVES: Serrated polyposis syndrome (SPS) is a complex disorder with a high risk of colorectal cancer for which the germline factors remain largely unknown. Here, we combined whole-exome sequencing (WES) and linkage studies in families with multiple members affected by SPS to identify candidate genes harboring rare variants with higher penetrance effects. METHODS: Thirty-nine affected subjects from 16 extended SPS families underwent WES. Genome-wide linkage analysis was performed under linear and exponential models. The contribution of rare coding variants selected to be highly pathogenic was assessed using the gene-based segregation test. RESULTS: significant linkage peak was identified on chromosome 3p25.2-p22.3 (maxSNP = rs2293787; LODlinear = 2.311, LODexp = 2.11), which logarithm of the odds (LOD) score increased after fine mapping for the same marker (maxSNP = rs2293787; LODlinear = 2.4, LODexp = 2.25). This linkage signal was replicated in 10 independent sets of random markers from this locus. To assess the contribution of rare variants predicted to be pathogenic, we performed a family-based segregation test with 11 rare variants predicted to be deleterious from 10 genes under the linkage intervals. This analysis showed significant segregation of rare variants with SPS in CAPT7, TMEM43, NGLY1, and FBLN2 genes (weighted Pvalue > 0.007). DISCUSSION: Protein network analysis suggested FBLN2 as the most plausible candidate genes for germline SPS predisposition. Etiologic rare variants implicated in disease predisposition may be identified by combining traditional linkage with WES data. This powerful approach was effective for the identification of a new candidate gene for hereditary SPS.M.D.-G. was supported by a contract from Agencia de Gestio d'Ajuts Universitaris i de Recerca (AGAUR) (Generalitat de Catalunya, 2018FI_B1_00213). S.F.-E., C.A.-C. and J.M. were supported by a contract from CIBEREHD. Y.S.L. was supported by a fellowship (LCF/BQ/DI18/11660058) from "la Caixa" Foundation (ID 100010434) funded EU Horizon 2020 Programme (Marie Sklodowska-Curie grant agreement no. 713673). LB was supported by a Juan de la Cierva postdoctoral contract (FJCI-2017-32593). CIBEREHD and CIBERONC are funded by the Instituto de Salud Carlos III. CT, BJO, and JMF were supported by Australian National Health and Medical Research (NHMRC) Project Grants 1063960 and 1066177. This research was supported by grants from Fondo de Investigacion Sanitaria/FEDER (16/00766, 17/00878), Fundacion Cientifica de la Asociacion Espanola contra el Cancer (GCB13131592CAST), PERIS (SLT002/16/00398, Generalitat de Catalunya), CERCA Programme (Generalitat de Catalunya), and Agencia de Gestio d'Ajuts Universitaris i de Recerca (Generalitat de Catalunya, GRPRE 2017SGR21, GRC 2017SGR653). This article is based on work from COST Action CA17118, supported by COST (European Cooperation in Science and Technology). www.cost.eu.Potential competing interests: None to report

Germline Mutations in FAF1 Are Associated With Hereditary Colorectal Cancer

Background & aims: A significant proportion of colorectal cancer (CRC) cases have familial aggregation but little is known about the genetic factors that contribute to these cases. We performed an exhaustive functional characterization of genetic variants associated with familial CRC. Methods: We performed whole-exome sequencing analyses of 75 patients from 40 families with a history of CRC (including early-onset cases) of an unknown germline basis (discovery cohort). We also sequenced specific genes in DNA from an external replication cohort of 473 families, including 488 patients with colorectal tumors that had normal expression of mismatch repair proteins (validation cohort). We disrupted the Fas-associated factor 1 gene (FAF1) in DLD-1 CRC cells using CRISPR/Cas9 gene editing; some cells were transfected with plasmids that express FAF1 missense variants. Cells were analyzed by immunoblots, quantitative real-time polymerase chain reaction, and functional assays monitoring apoptosis, proliferation, and assays for Wnt signaling or nuclear factor (NF)-kappa-B activity. Results: We identified predicted pathogenic variant in the FAF1 gene (c.1111G>A; p.Asp371Asn) in the discovery cohort; it was present in 4 patients of the same family. We identified a second variant in FAF1 in the validation cohort (c.254G>C; p.Arg85Pro). Both variants encoded unstable FAF1 proteins. Expression of these variants in CRC cells caused them to become resistant to apoptosis, accumulate beta-catenin in the cytoplasm, and translocate NF-kappa-B to the nucleus. Conclusions: In whole-exome sequencing analyses of patients from families with a history of CRC, we identified variants in FAF1 that associate with development of CRC. These variants encode unstable forms of FAF1 that increase resistance of CRC cells to apoptosis and increase activity of beta-catenin and NF-kappa-B

Integrated Analysis of Germline and Tumor DNA Identifies New Candidate Genes Involved in Familial Colorectal Cancer

Colorectal cancer (CRC) shows aggregation in some families but no alterations in the known hereditary CRC genes. We aimed to identify new candidate genes which are potentially involved in germline predisposition to familial CRC. An integrated analysis of germline and tumor whole-exome sequencing data was performed in 18 unrelated CRC families. Deleterious single nucleotide variants (SNV), short insertions and deletions (indels), copy number variants (CNVs) and loss of heterozygosity (LOH) were assessed as candidates for first germline or second somatic hits. Candidate tumor suppressor genes were selected when alterations were detected in both germline and somatic DNA, fulfilling Knudson's two-hit hypothesis. Somatic mutational profiling and signature analysis were also performed. A series of germline-somatic variant pairs were detected. In all cases, the first hit was presented as a rare SNV/indel, whereas the second hit was either a different SNV (3 genes) or LOH affecting the same gene (141 genes). BRCA2, BLM, ERCC2, RECQL, REV3L and RIF1 were among the most promising candidate genes for germline CRC predisposition. The identification of new candidate genes involved in familial CRC could be achieved by our integrated analysis. Further functional studies and replication in additional cohorts are required to confirm the selected candidates

Rare germline copy number variants in colorectal cancer predisposition characterized by exome sequencing analysis

EPICOLON consortium: et al.Colorectal cancer (CRC) is one of the most common neoplasms and an important cause of mortality worldwide (http://globocan.iarc.fr/). Approximately 35% of the variation in CRC susceptibility is likely due to heritable factors (Lichtenstein et al., 2000). Genetic variations in the human genome include single nucleotide variants (SNVs), short insertions and deletions, and larger structural variants resulting in gain or loss of genomic DNA larger than 1 kb, such as copy number variants (CNVs). Leaving aside the importance of CNVs in sporadic tumor development, these variants can also be present in the germline DNA of healthy individuals from the general population and be considered polymorphic. Common germline CNVs can confer a small increase in the risk of predisposition to disease, whereas rare CNVs have been linked to hereditary cancer predisposition including CRC. Recent examples include alterations involving EPCAM, PTPRJ, CDH18, GREM1 and FOCAD (Ligtenberg et al., 2009; Venkatachalam et al., 2011; Jaeger et al., 2012; Weren et al., 2015).This work was supported by CIBEREHD (to SFE, CEJ and JM), CIBERER, Fondo de Investigación Sanitaria/FEDER (14/00173, 14/00230 and 17/00878), Ministerio de Economía y Competitividad (SAF2014-54453-R), Fundación Científica de la Asociación Española contra el Cáncer (GCB13131592CAST), PERIS (SLT002/16/00398, Generalitat de Catalunya), COST Action BM1206, Beca Grupo de Trabajo “Oncología” AEG (Asociación Española de Gastroenterología), CERCA Programme (Generalitat de Catalunya) and Agència de Gestió d'Ajuts Universitaris i de Recerca (Generalitat de Catalunya, FI 2017 B00619 to MDG, 2014SGR255, 2014SGR135).Peer Reviewe

CNApp, a tool for the quantification of copy number alterations and integrative analysis revealing clinical implications

Somatic copy number alterations (CNAs) are a hallmark of cancer, but their role in tumorigenesis and clinical relevance remain largely unclear. Here, we developed CNApp, a web-based tool that allows a comprehensive exploration of CNAs by using purity-corrected segmented data from multiple genomic platforms. CNApp generates genome-wide profiles, computes CNA scores for broad, focal and global CNA burdens, and uses machine learning-based predictions to classify samples. We applied CNApp to the TCGA pan-cancer dataset of 10,635 genomes showing that CNAs classify cancer types according to their tissue-of-origin, and that each cancer type shows specific ranges of broad and focal CNA scores. Moreover, CNApp reproduces recurrent CNAs in hepatocellular carcinoma and predicts colon cancer molecular subtypes and microsatellite instability based on broad CNA scores and discrete genomic imbalances. In summary, CNApp facilitates CNA-driven research by providing a unique framework to identify relevant clinical implications. CNApp is hosted at . In most cases, human cells contain two copies of each of their genes, yet sometimes this can change, an effect called copy number alteration (CNA). Cancer is a genetic disease and thus, studying the DNA from tumor samples is crucial to improving diagnosis and choosing the right treatment. Most tumors contain cells with CNAs; however, the impact of CNAs in cancer progression is poorly understood. CNAs can be studied by examining the genome of tumor cells and finding which regions display an unusual number of copies. It may also be possible to gather information about different cancer types by analyzing the CNAs in a tumor, but this approach requires the analysis of large amounts of data. To aid the analysis of CNAs in cancer cells, Franch-Expósito, Bassaganyas et al. have created an online tool called CNApp, which is able to identify and count CNAs in genomic data and link them to features associated with different cancers. The hope is that a better understanding of the effect of CNAs in cancer could help better diagnose cancers, and improve outcomes for patients. Potentially, this could also predict what type of treatment would work better for a specific tumor. Besides, by using a machine-learning approach, the tool can also make predictions about specific cancer subtypes in order to facilitate clinical decisions. Franch-Expósito, Bassaganyas et al. tested CNApp using previously existing cancer data from 33 different cancer types to show how CNApp can help the interpretation of CNAs in cancer. Moreover, CNApp can also use CNAs to identify different types of bowel (colorectal) cancer in a way that could help doctors to make decisions about treatment. Together these findings show that CNApp provides an adaptable and accessible research tool for the study of cancer genomics, which could provide opportunities to inform medical procedures