The holistic perspective of the INCISIVE Project: artificial intelligence in screening mammography

Finding new ways to cost-effectively facilitate population screening and improve cancer diagnoses at an early stage supported by data-driven AI models provides unprecedented opportunities to reduce cancer related mortality. This work presents the INCISIVE project initiative towards enhancing AI solutions for health imaging by unifying, harmonizing, and securely sharing scattered cancer-related data to ensure large datasets which are critically needed to develop and evaluate trustworthy AI models. The adopted solutions of the INCISIVE project have been outlined in terms of data collection, harmonization, data sharing, and federated data storage in compliance with legal, ethical, and FAIR principles. Experiences and examples feature breast cancer data integration and mammography collection, indicating the current progress, challenges, and future directions.This research received funding mainly from the European Union’s Horizon 2020 research and innovation program under grant agreement no 952179. It was also partially funded by the Ministry of Economy, Industry, and Competitiveness of Spain under contracts PID2019-107255GB and 2017-SGR-1414.Peer ReviewedArticle signat per 30 autors/es: Ivan Lazic (1), Ferran Agullo (2), Susanna Ausso (3), Bruno Alves (4), Caroline Barelle (4), Josep Ll. Berral (2), Paschalis Bizopoulos (5), Oana Bunduc (6), Ioanna Chouvarda (7), Didier Dominguez (3), Dimitrios Filos (7), Alberto Gutierrez-Torre (2), Iman Hesso (8), Nikša Jakovljević (1), Reem Kayyali (8), Magdalena Kogut-Czarkowska (9), Alexandra Kosvyra (7), Antonios Lalas (5) , Maria Lavdaniti (10,11), Tatjana Loncar-Turukalo (1),Sara Martinez-Alabart (3), Nassos Michas (4,12), Shereen Nabhani-Gebara (8), Andreas Raptopoulos (6), Yiannis Roussakis (13), Evangelia Stalika (7,11), Chrysostomos Symvoulidis (6,14), Olga Tsave (7), Konstantinos Votis (5) Andreas Charalambous (15) / (1) Faculty of Technical Sciences, University of Novi Sad, 21000 Novi Sad, Serbia; (2) Barcelona Supercomputing Center, 08034 Barcelona, Spain; (3) Fundació TIC Salut Social, Ministry of Health of Catalonia, 08005 Barcelona, Spain; (4) European Dynamics, 1466 Luxembourg, Luxembourg; (5) Centre for Research and Technology Hellas, 57001 Thessaloniki, Greece; (6) Telesto IoT Solutions, London N7 7PX, UK: (7) School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece; (8) Department of Pharmacy, Kingston University London, London KT1 2EE, UK; (9) Timelex BV/SRL, 1000 Brussels, Belgium; (10) Nursing Department, International Hellenic University, 57400 Thessaloniki, Greece; (11) Hellenic Cancer Society, 11521 Athens, Greece; (12) European Dynamics, 15124 Athens, Greece; (13) German Oncology Center, Department of Medical Physics, Limassol 4108, Cyprus; (14) Department of Digital Systems, University of Piraeus, 18534 Piraeus, Greece; (15) Department of Nursing, Cyprus University of Technology, Limassol 3036, CyprusPostprint (published version

Epigenetics override pro-inflammatory PTGS transcriptomic signature towards selective hyperactivation of PGE 2 in colorectal cancer

This is an Open Access article distributed under the terms of the Creative Commons Attribution License.-- et al.[Background]: Misregulation of the PTGS (prostaglandin endoperoxide synthase, also known as cyclooxygenase or COX) pathway may lead to the accumulation of pro-inflammatory signals, which constitutes a hallmark of cancer. To get insight into the role of this signaling pathway in colorectal cancer (CRC), we have characterized the transcriptional and epigenetic landscapes of the PTGS pathway genes in normal and cancer cells. [Results]: Data from four independent series of CRC patients (502 tumors including adenomas and carcinomas and 222 adjacent normal tissues) and two series of colon mucosae from 69 healthy donors have been included in the study. Gene expression was analyzed by real-time PCR and Affymetrix U219 arrays. DNA methylation was analyzed by bisulfite sequencing, dissociation curves, and HumanMethylation450K arrays. Most CRC patients show selective transcriptional deregulation of the enzymes involved in the synthesis of prostanoids and their receptors in both tumor and its adjacent mucosa. DNA methylation alterations exclusively affect the tumor tissue (both adenomas and carcinomas), redirecting the transcriptional deregulation to activation of prostaglandin E 2 (PGE 2 ) function and blockade of other biologically active prostaglandins. In particular, PTGIS, PTGER3, PTGFR, and AKR1B1 were hypermethylated in more than 40 % of all analyzed tumors. [Conclusions]: The transcriptional and epigenetic profiling of the PTGS pathway provides important clues on the biology of the tumor and its microenvironment. This analysis renders candidate markers with potential clinical applicability in risk assessment and early diagnosis and for the design of new therapeutic strategies.IC was funded by Fundação para a Ciência e a Tecnologia (SFRH/BD/28464/2006); JC was funded by a FPI fellowship. ADV was supported in part by a contract from the Ministerio de Economía y Competitividad (MINECO) (PTC2011-1091). This work was supported by the MINECO(SAF2011/23638, SAF2014/52492), the Catalan Institute of Oncology and the Instituto de Salud Carlos III (grant PI11-01439, RD12/0042/0019 and CIBERESP CB06/02/2005), the Generalitat de Catalunya (grant 2014SGR647), and the Asociación Española Contra el Cáncer (AECC).Peer Reviewe

Epigenetics override pro-inflammatory PTGS transcriptomic signature towards selective hyperactivation of PGE2 in colorectal cancer.

BACKGROUND: Misregulation of the PTGS (prostaglandin endoperoxide synthase, also known as cyclooxygenase or COX) pathway may lead to the accumulation of pro-inflammatory signals, which constitutes a hallmark of cancer. To get insight into the role of this signaling pathway in colorectal cancer (CRC), we have characterized the transcriptional and epigenetic landscapes of the PTGS pathway genes in normal and cancer cells. RESULTS: Data from four independent series of CRC patients (502 tumors including adenomas and carcinomas and 222 adjacent normal tissues) and two series of colon mucosae from 69 healthy donors have been included in the study. Gene expression was analyzed by real-time PCR and Affymetrix U219 arrays. DNA methylation was analyzed by bisulfite sequencing, dissociation curves, and HumanMethylation450K arrays. Most CRC patients show selective transcriptional deregulation of the enzymes involved in the synthesis of prostanoids and their receptors in both tumor and its adjacent mucosa. DNA methylation alterations exclusively affect the tumor tissue (both adenomas and carcinomas), redirecting the transcriptional deregulation to activation of prostaglandin E2 (PGE2) function and blockade of other biologically active prostaglandins. In particular, PTGIS, PTGER3, PTGFR, and AKR1B1 were hypermethylated in more than 40 % of all analyzed tumors. CONCLUSIONS: The transcriptional and epigenetic profiling of the PTGS pathway provides important clues on the biology of the tumor and its microenvironment. This analysis renders candidate markers with potential clinical applicability in risk assessment and early diagnosis and for the design of new therapeutic strategies

Telomere length alterations in microsatellite stable colorectal cancer and association with the immune response

Telomeres are repetitive sequences (TTAGGG) located at the end of chromosomes. Telomeres progressively shorten with each cell replication cycle, ultimately leading to chromosomal instability and loss of cell viability. Telomere length anomaly appears to be one of the earliest and most prevalent genetic alterations in malignant transformation. Here we aim to estimate telomere length from whole-exome sequencing data in colon tumors and normal colonic mucosa, and to analyze the potential association of telomere length with clinical factors and gene expression in colon cancer. Reads containing at least five repetitions of the telomere sequence (TTAGGG) were extracted from the raw sequences of 42 adjacent normal-tumor paired samples. The number of reads from the tumor sample was normalized to build the Tumor Telomere Length Ratio (TTLR), considered an estimation of telomere length change in the tumor compared to the paired normal tissue. We evaluated the associations between TTLR and clinical factors, gene expression and copy number (CN) aberrations measured in the same tumor samples. Colon tumors showed significantly shorter telomeres than their paired normal samples. No significant association was observed between TTLR and gender, age, tumor location, prognosis, stromal infiltration or molecular subtypes. The functional gene set enrichment analysis showed pathways related to immune response significantly associated with TLLR. By extracting a relative measure of telomere length from whole-exome sequencing data, we have assessed that colon tumor cells predominantly shorten telomeres, and this alteration is associated with expression changes in genes related to immune response and inflammation in tumor cells

Mutanome and expression of immune response genes in microsatellite stable colon cancer

The aim of this study was to analyze the impact of the mutanome in the prognosis of microsatellite stable stage II CRC tumors. The exome of 42 stage II, microsatellite stable, colon tumors (21 of them relapse) and their paired mucosa were sequenced and analyzed. Although some pathways accumulated more mutations in patients exhibiting good or poor prognosis, no single somatic mutation was associated with prognosis. Exome sequencing data is also valuable to infer tumor neoantigens able to elicit a host immune response. Hence, putative neoantigens were identified by combining information about missense mutations in each tumor and HLAs genotypes of the patients. Under the hypothesis that neoantigens should be correctly presented in order to activate the immune response, expression levels of genes involved in the antigen presentation machinery were also assessed. In addition, CD8A level (as a marker of T-cell infiltration) was measured. We found that tumors with better prognosis showed a tendency to generate a higher number of immunogenic epitopes, and up-regulated genes involved in the antigen processing machinery. Moreover, tumors with higher T-cell infiltration also showed better prognosis. Stratifying by consensus molecular subtype, CMS4 tumors showed the highest association of expression levels of genes involved in the antigen presentation machinery with prognosis. Thus, we hypothesize that a subset of stage II microsatellite stable CRC tumors are able to generate an immune response in the host via MHC class I antigen presentation, directly related with a better prognosis

Multitrait genome association analysis identifies new susceptibility genes for human anthropometric variation in the GCAT cohort

Background Heritability estimates have revealed an important contribution of SNP variants for most common traits; however, SNP analysis by single-trait genome-wide association studies (GWAS) has failed to uncover their impact. In this study, we applied a multitrait GWAS approach to discover additional factor of the missing heritability of human anthropometric variation. Methods We analysed 205 traits, including diseases identified at baseline in the GCAT cohort (Genomes For Life- Cohort study of the Genomes of Catalonia) (n=4988), a Mediterranean adult population-based cohort study from the south of Europe. We estimated SNP heritability contribution and single-trait GWAS for all traits from 15 million SNP variants. Then, we applied a multitrait-related approach to study genome-wide association to anthropometric measures in a two-stage meta-analysis with the UK Biobank cohort (n=336 107). Results Heritability estimates (eg, skin colour, alcohol consumption, smoking habit, body mass index, educational level or height) revealed an important contribution of SNP variants, ranging from 18% to 77%. Single-trait analysis identified 1785 SNPs with genome-wide significance threshold. From these, several previously reported single-trait hits were confirmed in our sample with LINC01432 (p=1.9×10−9) variants associated with male baldness, LDLR variants with hyperlipidaemia (ICD-9:272) (p=9.4×10−10) and variants in IRF4 (p=2.8×10−57), SLC45A2 (p=2.2×10−130), HERC2 (p=2.8×10−176), OCA2 (p=2.4×10−121) and MC1R (p=7.7×10−22) associated with hair, eye and skin colour, freckling, tanning capacity and sun burning sensitivity and the Fitzpatrick phototype score, all highly correlated cross-phenotypes. Multitrait meta-analysis of anthropometric variation validated 27 loci in a two-stage meta-analysis with a large British ancestry cohort, six of which are newly reported here (p value threshold <5×10−9) at ZRANB2-AS2, PIK3R1, EPHA7, MAD1L1, CACUL1 and MAP3K9. Conclusion Considering multiple-related genetic phenotypes improve associated genome signal detection. These results indicate the potential value of data-driven multivariate phenotyping for genetic studies in large population-based cohorts to contribute to knowledge of complex traits.This work was supported in part by the Spanish Ministerio de Economía y Competitividad (MINECO) project ADE 10/00026, by the Catalan Departament de Salut and by the Departament d’Empresa i Coneixement de la Generalitat de Catalunya, the Agència de Gestió d’Estudis Universitaris i de Recerca (AGA UR) (SGR 1269, SGR 1589 and SGR 647). RdC is the recipient of a Ramon y Cajal grant (RYC-2011-07822). The Project GCAT is coordinated by the Germans Trias i Pujol Research Institute (IGTP), in collaboration with the Catalan Institute of Oncology (ICO), and in partnership with the Blood and Tissue Bank of Catalonia (BST). IGTP is part of the CERCA Programme/Generalitat de Catalunya.Peer ReviewedPostprint (published version

Scarce evidence of the causal role of germline mutations in UNC5C in hereditary colorectal cancer and polyposis

Germline mutations in UNC5C have been suggested to increase colorectal cancer (CRC) risk, thus causing hereditary CRC. However, the evidence gathered thus far is insufficient to include the study of the UNC5C gene in the routine genetic testing of familial CRC. Here we aim at providing a more conclusive answer about the contribution of germline UNC5C mutations to genetically unexplained hereditary CRC and/or polyposis cases. To achieve this goal we sequenced the coding region and exon-intron boundaries of UNC5C in 544 familial CRC or polyposis patients (529 families), using a technique that combines pooled DNA amplification and massively parallel sequencing. A total of eight novel or rare variants, all missense, were identified in eight families. Co-segregation data in the families and association results in case-control series are not consistent with a causal effect for 7 of the 8 identified variants, including c.1882_1883delinsAA (p.A628K), previously described as a disease-causing mutation. One variant, c.2210G > A (p.S737N), remained unclassified. In conclusion, our results suggest that the contribution of germline mutations in UNC5C to hereditary colorectal cancer and to polyposis cases is negligible

Multitrait genome association analysis identifies new susceptibility genes for human anthropometric variation in the GCAT cohort

BACKGROUND: Heritability estimates have revealed an important contribution of SNP variants for most common traits; however, SNP analysis by single-trait genome-wide association studies (GWAS) has failed to uncover their impact. In this study, we applied a multitrait GWAS approach to discover additional factor of the missing heritability of human anthropometric variation. METHODS: We analysed 205 traits, including diseases identified at baseline in the GCAT cohort (Genomes For Life- Cohort study of the Genomes of Catalonia) (n=4988), a Mediterranean adult population-based cohort study from the south of Europe. We estimated SNP heritability contribution and single-trait GWAS for all traits from 15 million SNP variants. Then, we applied a multitrait-related approach to study genome-wide association to anthropometric measures in a two-stage meta-analysis with the UK Biobank cohort (n=336 107). RESULTS: Heritability estimates (eg, skin colour, alcohol consumption, smoking habit, body mass index, educational level or height) revealed an important contribution of SNP variants, ranging from 18% to 77%. Single-trait analysis identified 1785 SNPs with genome-wide significance threshold. From these, several previously reported single-trait hits were confirmed in our sample with LINC01432 (p=1.9×10-9) variants associated with male baldness, LDLR variants with hyperlipidaemia (ICD-9:272) (p=9.4×10-10) and variants in IRF4 (p=2.8×10-57), SLC45A2 (p=2.2×10-130), HERC2 (p=2.8×10-176), OCA2 (p=2.4×10-121) and MC1R (p=7.7×10-22) associated with hair, eye and skin colour, freckling, tanning capacity and sun burning sensitivity and the Fitzpatrick phototype score, all highly correlated cross-phenotypes. Multitrait meta-analysis of anthropometric variation validated 27 loci in a two-stage meta-analysis with a large British ancestry cohort, six of which are newly reported here (p value threshold <5×10-9) at ZRANB2-AS2, PIK3R1, EPHA7, MAD1L1, CACUL1 and MAP3K9. CONCLUSION: Considering multiple-related genetic phenotypes improve associated genome signal detection. These results indicate the potential value of data-driven multivariate phenotyping for genetic studies in large population-based cohorts to contribute to knowledge of complex traits

Comprehensive analysis of copy number aberrations in microsatellite stable colon cancer in view of stromal component

Background: Somatic copy number aberrations (CNA) are common acquired changes in cancer cells playing an important role in the progression of colon cancer (CRC). This study aimed to perform a characterization of CNA and their impact in gene expression.Methods: CNA were inferred from SNP array data in a series of 99 CRC. CNA events were calculated and used to assess the association between copy number dosage, clinical and molecular characteristics of the tumours, and gene expression changes. All analyses were adjusted for the quantity of stroma in each sample, that was inferred from gene expression data.Results: High heterogeneity among samples was observed, the proportion of altered genome ranged between 0.04 and 26.6%. Recurrent CNA regions with gains were frequent in chromosomes 7p, 8q, 13q, and 20 while 8p, 17p, and 18 cumulated loses. A significant positive correlation was observed between the number of somatic mutations and total CNA (Spearman r=0.42, P=0.006). Approximately 37% of genes located in CNA regions changed their level of expression, and the average partial correlation (adjusted for stromal content) with copy number was 0.54 (inter-quartile range 0.20 to 0.81). Altered genes showed enrichment in pathways relevant for colorectal cancer. Tumours classified as CMS2 and CMS4 by the consensus molecular subtyping showed higher frequency of CNA. Loses of one small region in 1p36.33, with gene CDK11B, were associated with poor prognosis. More than 66% of the recurrent CNA were validated in the TCGA data when analysed with the same procedure. Also 79% of the genes with altered expression in our data were validated in the TCGA.Conclusion: Though CNA are frequent events in MSS CRC, few focal recurrent regions were found. These aberrations have strong effects on gene expression and contribute to deregulate relevant cancer pathways. Due to the diploid nature of stromal cells, it is important to consider the purity of tumour samples to accurately calculate CNA events in CRC

COLONOMICS - integrative omics data of one hundred paired normal-tumoral samples from colon cancer patients

Colonomics is a multi-omics dataset that includes 250 samples: 50 samples from healthy colon mucosa donors and 100 paired samples from colon cancer patients (tumor/adjacent). From these samples, Colonomics project includes data from genotyping, DNA methylation, gene expression, whole exome sequencing and micro-RNAs (miRNAs) expression. It also includes data from copy number variation (CNV) from tumoral samples. In addition, clinical data from all these samples is available. The aims of the project were to explore and integrate these datasets to describe colon cancer at molecular level and to compare normal and tumoral tissues. Also, to improve screening by finding biomarkers for the diagnosis and prognosis of colon cancer. This project has its own website including four browsers allowing users to explore Colonomics datasets. Since generated data could be reuse for the scientific community for exploratory or validation purposes, here we describe omics datasets included in the Colonomics project as well as results from multi-omics layers integration