Skin microbiome differences in pancreatic adenocarcinoma, other cancers, and healthy controls: a pilot study
IntroductionMany studies have reported the importance of the human microbiome in relationship to the overall health of its host. While recent studies have explored the microbiome’s role in various types of cancer compared to healthy patients, this pilot study is the first to investigate differences...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-02-01
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| Series: | Frontiers in Oncology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2025.1495500/full |
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| author | Taylor Davis Katherine T. Decker Dana Hosseini Gayle Jameson Erkut Borazanci |
| author_facet | Taylor Davis Katherine T. Decker Dana Hosseini Gayle Jameson Erkut Borazanci |
| author_sort | Taylor Davis |
| collection | DOAJ |
| description | IntroductionMany studies have reported the importance of the human microbiome in relationship to the overall health of its host. While recent studies have explored the microbiome’s role in various types of cancer compared to healthy patients, this pilot study is the first to investigate differences in the skin microbiome composition among pancreatic adenocarcinoma patients, individuals with other cancers, and cancer-free controls.MethodsThe study characterizes the skin microbiome’s potential associations with cancer status by analyzing skin swabs from the forehead and cheek of 58 participants using Next Generation Sequencing (NGS), differential abundance analysis, and machine learning techniques.ResultsThe study results indicated that the cancer group displayed a significantly higher mean alpha diversity compared to the control group. Additionally, a machine learning classification model achieved a mean F1 Score of 0.943 in predicting cancer status, indicating measurable differentiation in the skin microbiome between the study groups. This differentiation is supported by differential abundance methods, including ANCOM-BC and MaAsLin2.DiscussionThis pilot study suggests that skin microbiome profiling could serve as a non-invasive biomarker for cancer detection and monitoring, which warrants a larger, longitudinal study to validate these results. |
| format | Article |
| id | doaj-art-0e623fd3dd6842b8ad36a47cba91989f |
| institution | Kabale University |
| issn | 2234-943X |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Oncology |
| spelling | doaj-art-0e623fd3dd6842b8ad36a47cba91989f2025-02-06T05:21:40ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2025-02-011510.3389/fonc.2025.14955001495500Skin microbiome differences in pancreatic adenocarcinoma, other cancers, and healthy controls: a pilot studyTaylor Davis0Katherine T. Decker1Dana Hosseini2Gayle Jameson3Erkut Borazanci4Department of Oncology, HonorHealth Research Institute, Scottsdale, AZ, United StatesProdermIQ, Inc., San Diego, CA, United StatesProdermIQ, Inc., San Diego, CA, United StatesDepartment of Oncology, HonorHealth Research Institute, Scottsdale, AZ, United StatesDepartment of Oncology, HonorHealth Research Institute, Scottsdale, AZ, United StatesIntroductionMany studies have reported the importance of the human microbiome in relationship to the overall health of its host. While recent studies have explored the microbiome’s role in various types of cancer compared to healthy patients, this pilot study is the first to investigate differences in the skin microbiome composition among pancreatic adenocarcinoma patients, individuals with other cancers, and cancer-free controls.MethodsThe study characterizes the skin microbiome’s potential associations with cancer status by analyzing skin swabs from the forehead and cheek of 58 participants using Next Generation Sequencing (NGS), differential abundance analysis, and machine learning techniques.ResultsThe study results indicated that the cancer group displayed a significantly higher mean alpha diversity compared to the control group. Additionally, a machine learning classification model achieved a mean F1 Score of 0.943 in predicting cancer status, indicating measurable differentiation in the skin microbiome between the study groups. This differentiation is supported by differential abundance methods, including ANCOM-BC and MaAsLin2.DiscussionThis pilot study suggests that skin microbiome profiling could serve as a non-invasive biomarker for cancer detection and monitoring, which warrants a larger, longitudinal study to validate these results.https://www.frontiersin.org/articles/10.3389/fonc.2025.1495500/fullskin microbiomepancreatic adenocarcinomadysbiosismachine learningalpha diversity |
| spellingShingle | Taylor Davis Katherine T. Decker Dana Hosseini Gayle Jameson Erkut Borazanci Skin microbiome differences in pancreatic adenocarcinoma, other cancers, and healthy controls: a pilot study Frontiers in Oncology skin microbiome pancreatic adenocarcinoma dysbiosis machine learning alpha diversity |
| title | Skin microbiome differences in pancreatic adenocarcinoma, other cancers, and healthy controls: a pilot study |
| title_full | Skin microbiome differences in pancreatic adenocarcinoma, other cancers, and healthy controls: a pilot study |
| title_fullStr | Skin microbiome differences in pancreatic adenocarcinoma, other cancers, and healthy controls: a pilot study |
| title_full_unstemmed | Skin microbiome differences in pancreatic adenocarcinoma, other cancers, and healthy controls: a pilot study |
| title_short | Skin microbiome differences in pancreatic adenocarcinoma, other cancers, and healthy controls: a pilot study |
| title_sort | skin microbiome differences in pancreatic adenocarcinoma other cancers and healthy controls a pilot study |
| topic | skin microbiome pancreatic adenocarcinoma dysbiosis machine learning alpha diversity |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2025.1495500/full |
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