Performance of a Shotgun Prediction Model for Colorectal Cancer When Using 16S rRNA Sequencing Data
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| Název: | Performance of a Shotgun Prediction Model for Colorectal Cancer When Using 16S rRNA Sequencing Data |
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| Autoři: | Ramon, Elies, Obón Santacana, Mireia, Khannous Lleiffe, Olfat, Saus, Ester, Gabaldon, Toni |
| Přispěvatelé: | Barcelona Supercomputing Center |
| Zdroj: | UPCommons. Portal del coneixement obert de la UPC Universitat Politècnica de Catalunya (UPC) |
| Informace o vydavateli: | MDPI AG, 2024. |
| Rok vydání: | 2024 |
| Témata: | 16S, Predictive model, Simulació per ordinador, Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica, Gut microbiota, Metagenomics, Microbial signatur, Shotgun, Genomics and bioinformatics, Colon cancer |
| Popis: | This research was funded by Instituto de Salud Carlos III, co-funded by FEDER funds–a way to build Europe–grants PI17-00092 and PI20-01439; Spanish Association Against Cancer (AECC) Scientific Foundation—grant GCTRA18022MORE; Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP) action Genrisk. E.R. has funding from Fundació Marató TV3—grant 875/C/2021. D.B-C. is supported by Instituto de Salud Carlos III Sara Borrell—grant CD21/00094. O.K-L is supported by the Formación de profesorado universitario (FPU) program from the Spanish Ministerio de Universidades—grant FPU2020-02907. T.G. group acknowledges support from the Spanish Ministry of Science and Innovation for grants PID2021-126067NB-I00, CPP2021-008552, PCI2022-135066-2, and PDC2022-133266-I00, cofounded by ERDF “A way of making Europe”; from the Catalan Research Agency (AGAUR) SGR01551; from the European Union’s Horizon 2020 research and innovation programme (ERC-2016-724173); from the Gordon and Betty Moore Foundation (Grant GBMF9742); from the “La Caixa” foundation (Grant LCF/PR/HR21/00737), and from the Instituto de Salud Carlos III (IMPACT Grant IMP/00019 and CIBERINFEC CB21/13/00061—ISCIII-SGEFI/ERDF). Sample collection of this work was supported by the Plataforma Biobancos (PT17/0015/0024) and ICOBIOBANC, sponsored by the Catalan Institute of Oncology. Colorectal cancer (CRC), the third most common cancer globally, has shown links to disturbed gut microbiota. While significant efforts have been made to establish a microbial signature indicative of CRC using shotgun metagenomic sequencing, the challenge lies in validating this signature with 16S ribosomal RNA (16S) gene sequencing. The primary obstacle is reconciling the differing outputs of these two methodologies, which often lead to divergent statistical models and conclusions. In this study, we introduce an algorithm designed to bridge this gap by mapping shotgun-derived taxa to their 16S counterparts. This mapping enables us to assess the predictive performance of a shotgun-based microbiome signature using 16S data. Our results demonstrate a reduction in performance when applying the 16S-mapped taxa in the shotgun prediction model, though it retains statistical significance. This suggests that while an exact match between shotgun and 16S data may not yet be feasible, our approach provides a viable method for comparative analysis and validation in the context of CRC-associated microbiome research "Article signat per 12 autors/es: Elies Ramon, Mireia Obón-Santacana, Olfat Khannous-Lleiffe, Ester Saus,Toni Gabaldón, Elisabet Guinó, David Bars-Cortina, Gemma Ibáñez-Sanz, Lorena Rodríguez-Alonso, Alfredo Mata, Ana García-Rodrígue and Victor Moreno " |
| Druh dokumentu: | Article |
| Popis souboru: | application/pdf |
| Jazyk: | English |
| Přístupová URL adresa: | https://hdl.handle.net/2117/409365 |
| Rights: | CC BY |
| Přístupové číslo: | edsair.dedup.wf.002..93f3275b4abf0f7ad0de7c7ce143e46c |
| Databáze: | OpenAIRE |
Nájsť tento článok vo Web of Science | Abstrakt: | This research was funded by Instituto de Salud Carlos III, co-funded by FEDER funds–a way to build Europe–grants PI17-00092 and PI20-01439; Spanish Association Against Cancer (AECC) Scientific Foundation—grant GCTRA18022MORE; Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP) action Genrisk. E.R. has funding from Fundació Marató TV3—grant 875/C/2021. D.B-C. is supported by Instituto de Salud Carlos III Sara Borrell—grant CD21/00094. O.K-L is supported by the Formación de profesorado universitario (FPU) program from the Spanish Ministerio de Universidades—grant FPU2020-02907. T.G. group acknowledges support from the Spanish Ministry of Science and Innovation for grants PID2021-126067NB-I00, CPP2021-008552, PCI2022-135066-2, and PDC2022-133266-I00, cofounded by ERDF “A way of making Europe”; from the Catalan Research Agency (AGAUR) SGR01551; from the European Union’s Horizon 2020 research and innovation programme (ERC-2016-724173); from the Gordon and Betty Moore Foundation (Grant GBMF9742); from the “La Caixa” foundation (Grant LCF/PR/HR21/00737), and from the Instituto de Salud Carlos III (IMPACT Grant IMP/00019 and CIBERINFEC CB21/13/00061—ISCIII-SGEFI/ERDF). Sample collection of this work was supported by the Plataforma Biobancos (PT17/0015/0024) and ICOBIOBANC, sponsored by the Catalan Institute of Oncology.<br />Colorectal cancer (CRC), the third most common cancer globally, has shown links to disturbed gut microbiota. While significant efforts have been made to establish a microbial signature indicative of CRC using shotgun metagenomic sequencing, the challenge lies in validating this signature with 16S ribosomal RNA (16S) gene sequencing. The primary obstacle is reconciling the differing outputs of these two methodologies, which often lead to divergent statistical models and conclusions. In this study, we introduce an algorithm designed to bridge this gap by mapping shotgun-derived taxa to their 16S counterparts. This mapping enables us to assess the predictive performance of a shotgun-based microbiome signature using 16S data. Our results demonstrate a reduction in performance when applying the 16S-mapped taxa in the shotgun prediction model, though it retains statistical significance. This suggests that while an exact match between shotgun and 16S data may not yet be feasible, our approach provides a viable method for comparative analysis and validation in the context of CRC-associated microbiome research<br />"Article signat per 12 autors/es: Elies Ramon, Mireia Obón-Santacana, Olfat Khannous-Lleiffe, Ester Saus,Toni Gabaldón, Elisabet Guinó, David Bars-Cortina, Gemma Ibáñez-Sanz, Lorena Rodríguez-Alonso, Alfredo Mata, Ana García-Rodrígue and Victor Moreno " |
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