Urine metallomics signature as an indicator of pancreatic cancer† Original paper
Researched by:
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Karen Pendergrass
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Karen Pendergrass
Read MoreKaren Pendergrass is a microbiome researcher specializing in microbiome-targeted interventions (MBTIs). She systematically analyzes scientific literature to identify microbial patterns, develop hypotheses, and validate interventions. As the founder of the Microbiome Signatures Database, she bridges microbiome research with clinical practice. In 2012, based on her own investigative research, she became the first documented case of FMT for Celiac Disease—four years before the first published case study.
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Metals
Metals
OverviewHeavy metals play a significant and multifaceted role in the pathogenicity of microbial species. Their involvement can be viewed from two primary perspectives: the toxicity of heavy metals to microbes and the exploitation of heavy metals by microbial pathogens to establish infections and evade the host immune response. Understanding these aspects is critical for both […]
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Karen Pendergrass
Read More
Researched by:
-
Karen Pendergrass
ID
Karen Pendergrass
Read More
Microbiome Signatures identifies and validates condition-specific microbiome shifts and interventions to accelerate clinical translation. Our multidisciplinary team supports clinicians, researchers, and innovators in turning microbiome science into actionable medicine.
Karen Pendergrass
What was studied?
This study explored the utility of urinary metallomic profiling—specifically concentrations and isotopic composition of essential metals—as a non-invasive diagnostic tool for pancreatic ductal adenocarcinoma (PDAC). The researchers examined urine samples from PDAC patients and healthy controls to identify specific metal dyshomeostasis and isotopic shifts that could serve as biomarkers for PDAC detection.
Who was studied?
Urine samples from 21 patients diagnosed with PDAC and 46 healthy control subjects were analyzed. All samples were collected under ethical approval through the Barts Pancreas Tissue Bank.
Most important findings:
A distinct urinary metallomic signature was identified in pancreatic ductal adenocarcinoma (PDAC) patients, characterized by decreased calcium and magnesium and increased zinc and copper levels. The multivariate model integrating these four elements exhibited outstanding diagnostic accuracy, achieving an area under the curve (AUC) of 0.995 with 99.5% sensitivity. Moreover, stable zinc isotope analysis revealed a shift toward isotopically lighter zinc in PDAC patients (median δ⁶⁶Zn = −0.15‰) compared to healthy controls (median δ⁶⁶Zn = +0.02‰), likely due to oxidative stress-induced oxidation of cysteine-rich metallothioneins, which preferentially bind lighter isotopes. From a microbiome-metallomic perspective, such trace metal imbalances—particularly involving zinc and copper—may influence microbial community structure by selectively enriching pathogenic taxa and diminishing beneficial ones. Although the microbiome was not directly assessed in this study, the metallomic disturbances observed may serve as indirect indicators of host-microbe dysregulation, especially relevant in gastrointestinal malignancies such as PDAC.
| Element | Change in PDAC vs. Control |
|---|---|
| Calcium (Ca) | Decreased (***p <0.0001) |
| Magnesium (Mg) | Decreased (**p = 0.0002) |
| Zinc (Zn) | Increased (*p = 0.015) |
| Copper (Cu) | Increased (*p = 0.02) |
Greatest implications of the study:
This work provides strong preliminary evidence that urinary metallomic profiles—specifically Ca, Mg, Cu, Zn concentrations and zinc isotopic signatures—can serve as non-invasive biomarkers for PDAC detection. It is the first study to report isotopic zinc alterations in urine associated with PDAC and proposes a compelling mechanistic link to oxidative stress and metalloprotein dysregulation. If validated in larger cohorts, this approach could represent a breakthrough in early detection of pancreatic cancer, a malignancy notorious for its asymptomatic progression and poor prognosis. The authors propose that isotopic measurements, which offer significantly greater resolution than standard clinical assays, could even function as prognostic tools if longitudinally correlated with disease progression.