Dataset Information

Exploring the Neandertal legacy of pancreatic ductal adenocarcinoma risk in Eurasians.

ABSTRACT:

Background

The genomes of present-day non-Africans are composed of 1-3% of Neandertal-derived DNA as a consequence of admixture events between Neandertals and anatomically modern humans about 50-60 thousand years ago. Neandertal-introgressed single nucleotide polymorphisms (aSNPs) have been associated with modern human disease-related traits, which are risk factors for pancreatic ductal adenocarcinoma (PDAC), such as obesity, type 2 diabetes, and inflammation. In this study, we aimed at investigating the role of aSNPs in PDAC in three Eurasian populations.

Results

The high-coverage Vindija Neandertal genome was used to select aSNPs in non-African populations from 1000 Genomes project phase 3 data. Then, the association between aSNPs and PDAC risk was tested independently in Europeans and East Asians, using existing GWAS data on more than 200 000 individuals. We did not find any significant associations between aSNPs and PDAC in samples of European descent, whereas, in East Asians, we observed that the Chr10p12.1-rs117585753-T allele (MAF = 10%) increased the risk to develop PDAC (OR = 1.35, 95%CI 1.19-1.54, P = 3.59 × 10^-6), with a P-value close to a threshold that takes into account multiple testing.

Conclusions

Our results show only a minimal contribution of Neandertal SNPs to PDAC risk.

SUBMITTER: Piccardi M

PROVIDER: S-EPMC10424372 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature

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Publications

Exploring the Neandertal legacy of pancreatic ductal adenocarcinoma risk in Eurasians.

Piccardi Margherita M Gentiluomo Manuel M Bertoncini Stefania S Pezzilli Raffaele R Erőss Bálint B Bunduc Stefania S Uzunoglu Faik G FG Talar-Wojnarowska Renata R Vanagas Tomas T Sperti Cosimo C Oliverius Martin M Aoki Mateus Nóbrega MN Ermini Stefano S Hussein Tamás T Boggi Ugo U Jamroziak Krzysztof K Maiello Evaristo E Morelli Luca L Vodickova Ludmila L Di Franco Gregorio G Landi Stefano S Szentesi Andrea A Lovecek Martin M Puzzono Marta M Tavano Francesca F van Laarhoven Hanneke W M HWM Zerbi Alessandro A Mohelnikova-Duchonova Beatrice B Stocker Hannah H Costello Eithne E Capurso Gabriele G Ginocchi Laura L Lawlor Rita T RT Vanella Giuseppe G Bazzocchi Francesca F Izbicki Jakob R JR Latiano Anna A Bueno-de-Mesquita Bas B Ponz de Leon Pisani Ruggero R Schöttker Ben B Soucek Pavel P Hegyi Péter P Gazouli Maria M Hackert Thilo T Kupcinskas Juozas J Poskiene Lina L Tacelli Matteo M Roth Susanne S Carrara Silvia S Perri Francesco F Hlavac Viktor V Theodoropoulos George E GE Busch Olivier R OR Mambrini Andrea A van Eijck Casper H J CHJ Arcidiacono Paolo P Scarpa Aldo A Pasquali Claudio C Basso Daniela D Lucchesi Maurizio M Milanetto Anna Caterina AC Neoptolemos John P JP Cavestro Giulia Martina GM Janciauskas Dainius D Chen Xuechen X Chammas Roger R Goetz Mara M Brenner Hermann H Archibugi Livia L Dannemann Michael M Canzian Federico F Tofanelli Sergio S Campa Daniele D

Biological research 20230813 1

<h4>Background</h4>The genomes of present-day non-Africans are composed of 1-3% of Neandertal-derived DNA as a consequence of admixture events between Neandertals and anatomically modern humans about 50-60 thousand years ago. Neandertal-introgressed single nucleotide polymorphisms (aSNPs) have been associated with modern human disease-related traits, which are risk factors for pancreatic ductal adenocarcinoma (PDAC), such as obesity, type 2 diabetes, and inflammation. In this study, we aimed at ...[more]

PMID: 37574541

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Project description:Purpose: Compare pancreatic ductal adenocarcinoma (PDAC), preclinical models, by their transcriptome and drug response landscapes to evaluate their complementarity. Experimental Design: Three paired PDAC preclinical models-patient-derived xenografts (PDX), xenograft-derived pancreatic organoids (XDPO) and xenograft-derived primary cell cultures (XDPCC)-were derived from 20 patients and analyzed at the transcriptomic and chemosensitivity level. Transcriptomic characterization was performed using the basal-like/classical subtyping and the PDAC molecular gradient (PAMG). Chemosensitivity for gemcitabine, irinotecan, 5-fluorouracil and oxaliplatin was established and the associated biological pathways were determined using independent component analysis (ICA) on the transcriptome of each model. The selection criteria used to identify the different components was the chemosensitivity score (CSS) found for each drug in each model. Results: PDX was the most dispersed model whereas XDPO and XDPCC were mainly classical and basal-like, respectively. Chemosensitivity scoring determines that PDX and XDPO display a positive correlation for three out of four drugs tested, whereas PDX and XDPCC did not correlate. No match was observed for each tumor chemosensitivity in the different models. Finally, pathway analysis shows a significant association between PDX and XDPO for the chemosensitivity-associated pathways and PDX and XDPCC for the chemoresistance-associated pathways. Conclusions: Each PDAC preclinical model possesses a unique basal-like/classical transcriptomic phenotype that strongly influences their global chemosensitivity. Each preclinical model is imperfect but complementary, suggesting that a more representative approach of the clinical reality could be obtained by combining them. Translational Relevance: The identification of molecular signatures that underpin drug sensitivity to chemotherapy in PDAC remains clinically challenging. Importantly, the vast majority of studies using preclinical in vivo and in vitro models fail when transferred to patients in a clinical setting despite initially promising results. This study presents for the first time a comparison between three preclinical models directly derived from the same patients. We show that their applicability to preclinical studies should be considered with a complementary focus, avoiding tumor-based direct extrapolations, which might generate misleading conclusions and consequently the overlook of clinically relevant features.

Project description:IntroductionPancreatic ductal adenocarcinoma (PDAC) has the highest mortality rate among all solid tumors. Tumorigenesis is promoted by the oncogene KRAS, and KRAS mutations are prevalent in patients with PDAC. Therefore, a comprehensive understanding of the interactions between KRAS mutations and PDAC may expediate the development of therapeutic strategies for reversing the progression of malignant tumors. Our study aims at establishing and validating a prediction model of KRAS mutations in patients with PDAC based on survival analysis and mRNA expression.MethodsA total of 184 and 412 patients with PDAC from The Cancer Genome Atlas (TCGA) database and the International Cancer Genome Consortium (ICGC), respectively, were included in the study.ResultsAfter tumor mutation profile and copy number variation (CNV) analyses, we established and validated a prediction model of KRAS mutations, based on survival analysis and mRNA expression, that contained seven genes: CSTF2, FAF2, KIF20B, AKR1A1, APOM, KRT6C, and CD70. We confirmed that the model has a good predictive ability for the prognosis of overall survival (OS) in patients with KRAS-mutated PDAC. Then, we analyzed differential biological pathways, especially the ferroptosis pathway, through principal component analysis, pathway enrichment analysis, Gene Ontology (GO) enrichment analysis, and gene set enrichment analysis (GSEA), with which patients were classified into low- or high-risk groups. Pathway enrichment results revealed enrichment in the cytokine-cytokine receptor interaction, metabolism of xenobiotics by cytochrome P450, and viral protein interaction with cytokine and cytokine receptor pathways. Most of the enriched pathways are metabolic pathways predominantly enriched by downregulated genes, suggesting numerous downregulated metabolic pathways in the high-risk group. Subsequent tumor immune infiltration analysis indicated that neutrophil infiltration, resting CD4 memory T cells, and resting natural killer (NK) cells correlated with the risk score. After verifying that the seven gene expression levels in different KRAS-mutated pancreatic cancer cell lines were similar to that in the model, we screened potential drugs related to the risk score.DiscussionThis study established, analyzed, and validated a model for predicting the prognosis of PDAC based on risk stratification according to KRAS mutations, and identified differential pathways and highly effective drugs.

Dataset Information

Exploring the Neandertal legacy of pancreatic ductal adenocarcinoma risk in Eurasians.

Background

Results

Conclusions

Publications

Exploring the Neandertal legacy of pancreatic ductal adenocarcinoma risk in Eurasians.

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