A blood-based metabolomic signature predictive of risk for pancreatic cancer

Ehsan Irajizad; Ana Kenney; Tiffany Tang; Jody Vykoukal; Ranran Wu; Eunice Murage; Jennifer B Dennison; Marta Sans; James P Long; Maureen Loftus; John A Chabot; Michael D Kluger; Fay Kastrinos; Lauren Brais; Ana Babic; Kunal Jajoo; Linda S Lee; Thomas E Clancy; Kimmie Ng; Andrea Bullock; Jeanine M Genkinger; Anirban Maitra; Kim-Anh Do; Bin Yu; Brian M Wolpin; Sam Hanash; Johannes F Fahrmann

doi:10.1016/j.xcrm.2023.101194

A blood-based metabolomic signature predictive of risk for pancreatic cancer

Cell Rep Med. 2023 Sep 19;4(9):101194. doi: 10.1016/j.xcrm.2023.101194.

Authors

Ehsan Irajizad¹, Ana Kenney², Tiffany Tang², Jody Vykoukal³, Ranran Wu³, Eunice Murage³, Jennifer B Dennison³, Marta Sans⁴, James P Long⁵, Maureen Loftus⁶, John A Chabot⁷, Michael D Kluger⁷, Fay Kastrinos⁸, Lauren Brais⁶, Ana Babic⁶, Kunal Jajoo⁴, Linda S Lee⁴, Thomas E Clancy⁹, Kimmie Ng⁶, Andrea Bullock¹⁰, Jeanine M Genkinger¹¹, Anirban Maitra¹², Kim-Anh Do⁵, Bin Yu², Brian M Wolpin⁶, Sam Hanash¹³, Johannes F Fahrmann¹⁴

Affiliations

¹ Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
² Department of Statistics, University of California, Berkeley, Berkeley, CA, USA.
³ Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
⁴ Division of Gastroenterology, Hepatology and Endoscopy, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
⁵ Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
⁶ Dana-Farber Brigham and Women's Cancer Center, Division of Gastrointestinal Oncology, Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
⁷ Division of Digestive and Liver Diseases, Columbia University Irving Medical Cancer and the Vagelos College of Physicians and Surgeons, New York, NY, USA.
⁸ Division of Digestive and Liver Diseases, Columbia University Irving Medical Cancer and the Vagelos College of Physicians and Surgeons, New York, NY, USA; Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY, USA.
⁹ Dana-Farber Brigham and Women's Cancer Center, Division of Surgical Oncology, Department of Surgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA USA.
¹⁰ Division of Hematology/Oncology, Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
¹¹ Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY, USA; Department of Epidemiology, Columbia Mailman School of Public Health, New York, NY, USA.
¹² Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
¹³ Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. Electronic address: shanash@mdanderson.org.
¹⁴ Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. Electronic address: jffahrmann@mdanderson.org.

Abstract

Emerging evidence implicates microbiome involvement in the development of pancreatic cancer (PaCa). Here, we investigate whether increases in circulating microbial-related metabolites associate with PaCa risk by applying metabolomics profiling to 172 sera collected within 5 years prior to PaCa diagnosis and 863 matched non-subject sera from participants in the Prostate, Lung, Colorectal, and Ovarian (PLCO) cohort. We develop a three-marker microbial-related metabolite panel to assess 5-year risk of PaCa. The addition of five non-microbial metabolites further improves 5-year risk prediction of PaCa. The combined metabolite panel complements CA19-9, and individuals with a combined metabolite panel + CA19-9 score in the top 2.5th percentile have absolute 5-year risk estimates of >13%. The risk prediction model based on circulating microbial and non-microbial metabolites provides a potential tool to identify individuals at high risk of PaCa that would benefit from surveillance and/or from potential cancer interception strategies.

Keywords: biomarker; metabolites; microbiome; pancreatic cancer; risk assessment.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

CA-19-9 Antigen*
Humans
Male
Metabolomics
Pancreas
Pancreatic Neoplasms* / diagnosis

Substances

CA-19-9 Antigen

Abstract

Publication types

MeSH terms

Substances

Grants and funding