Pancreatic cancer
Credit: Science Photo Library - SCIEPRO/Getty Images

A simplified version of multi-omics testing that involves just one blood sample per year can detect the particularly difficult-to-diagnose condition of early pancreatic cancer, a case report has shown.

The researchers believe their longitudinal multi-omics monitoring (LMOM) system is more practical than existing approaches, deploying fewer measurements, annual sampling, and faster decision making.

“This case report illustrates the potentials of blood LMOM for precision/personalized medicine and rethinking medical diagnostic innovation for a potentially life-saving early diagnosis of pancreatic cancer,” they reported in the Mary Ann Liebert publication OMICS: A Journal of Integrative Biology.

The team added: “LMOM may potentially allow early identification and intervention in cases that could otherwise progress to late-stage incurable disease.”

Integrated, multi-omics approaches to precision medicine are impressive but have shortcomings, including the need for near-daily monitoring, extensive and varied measurements, and challenging data interpretation.

David Wishart, PhD, from the University of Alberta in Edmonton, Canada, and co-authors therefore set out to develop a simpler and cheaper alternative that could also detect less obvious medical conditions and early-stage diseases.

The researchers adopted only absolutely quantitative multi-omics methods to speed data comparison and integration, reducing omics measurements to just proteomics and metabolomics.

They then developed and tested two in-house quantitative assays: a metabolomics assay for 143 high-value serum metabolites and a proteomics assay for 140 high-value plasma proteins.

Patients were only sampled once a year to reduce burden and cost, and machine learning (ML) used to accelerate diagnosis.

ML-based literature mining tools and techniques created a large, in-house proprietary database of metabolite and protein biomarkers corresponding to the molecules measured by the assays.

The team has used LMOM to follow hundreds of people over the years, in whom it has diagnosed early cardiovascular disease and Type 2 diabetes.

It also led many others to instigate diet or lifestyle interventions to improve their cardiovascular, hormone, nutritional, and gut health.

In the current case report, the researchers describe how multiyear LMOM helped detect a precancerous pancreatic tumor in a postmenopausal woman living in Canada, resulting in successful surgery.

The researchers note that pancreatic cancer is one of the deadliest of all malignancies, with a five-year survival rate of less than nine percent.

The 62-year-old woman had undergone annual blood-based LMOM since 2018 and began suffering from persistent fatigue and night sweats for about two months after a bout of COVID-19.

Her 2021 and 2022 metabolomics and proteomics results showed dramatic changes that, although not detectable in standard laboratory tests, were indicative of a tumor-promoting microenvironment.

This prompted further clinical diagnostic testing for pancreatic cancer and an abdominal ultrasound confirmed the presence of a 2.6 cm lesion in the tail of the pancreas. Tumor fluid from an aspiration biopsy had 10,000 times that of normal carcinoembryonic antigen levels, the team notes.

The patient underwent surgical tumor resection, and subsequent testing revealed she was no longer at a high risk of cancer.

“As this case report illustrates, the early diagnosis of a pancreatic tumor was possible with guidance from quantitative proteomic and metabolomic tests, which was later confirmed using imaging and histopathological findings,” the researchers reported.

Editor-in-Chief at OMICS Vural Özdemir added: “Longitudinal multi-omics monitoring offers promise for systems medicine and warrants translational research for early detection and clinical management of pancreatic cancer.”

Also of Interest