Plasma protein biomarkers for the detection of pancreatic neuroendocrine tumors and differentiation from small intestinal neuroendocrine tumors

Plasma tryptophan pathway metabolites quantified by liquid chromatography-tandem mass spectrometry as biomarkers in neuroendocrine tumor patients

A good and accessible biomarker is of great clinical value in neuroendocrine tumor (NET) patients, especially considering its frequently indolent nature and long-term follow-up. Plasma chromogranin A (CgA) and 5-hydroxyindoleacetic acid (5-HIAA) are currently used as biomarkers in NET, but their sensitivity and specificity are restricted. 5-HIAA is the main metabolite of serotonin, an important neurotransmitter of the tryptophan pathway. The aim of this study is to estabish a sensitive and accurate method for the quantification of tryptophan pathway metabolites in plasma. We further aimed to evaluate its utility as a clinical tool in NET disease. We obtained plasma samples from NET patients and healthy controls recruited from the University Hospital of North Norway, Tromsø. Samples were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS), and eight metabolites of the tryptophan pathway were quantified. We included 130 NET patients (72/130 small intestinal [SI] NET, 35/130 pancreatic NET, 23/130 other origin) and 20 healthy controls. In the SI-NET group, 26/72 patients presented with symptoms of carcinoid syndrome (CS). We found that combining tryptophan metabolites into a serotonin/kynurenine pathway ratio improved diagnostic sensitivity (92.3%) and specificity (100%) in detecting CS patients from healthy controls compared with plasma 5-HIAA alone (sensitivity 84.6%/specificity 100%). Further, a clinical marker based on the combination of plasma serotonin, 5-HIAA, and 5OH-tryptophan, increased diagnostic capacity identifying NET patients with metastasized disease from healthy controls compared with singular plasma 5-HIAA, serotonin, or CgA. In addition, this marker was positive in 61% of curatively operated SI-NET patients compared with only 10% of healthy controls (p < .001). Our results indicate that simultaneous quantification of several tryptophan metabolites in plasma, using LC-MS/MS, may represent a clinically useful diagnostic tool in NET disease.

Prioritization of Fluorescence In Situ Hybridization (FISH) Probes for Differentiating Primary Sites of Neuroendocrine Tumors with Machine Learning

Determining neuroendocrine tumor (NET) primary sites is pivotal for patient care as pancreatic NETs (pNETs) and small bowel NETs (sbNETs) have distinct treatment approaches. The diagnostic power and prioritization of fluorescence in situ hybridization (FISH) assay biomarkers for establishing primary sites has not been thoroughly investigated using machine learning (ML) techniques. We trained ML models on FISH assay metrics from 85 sbNET and 59 pNET samples for primary site prediction. Exploring multiple methods for imputing missing data, the impute-by-median dataset coupled with a support vector machine model achieved the highest classification accuracy of 93.1% on a held-out test set, with the top importance variables originating from the ERBB2 FISH probe. Due to the greater interpretability of decision tree (DT) models, we fit DT models to ten dataset splits, achieving optimal performance with k-nearest neighbor (KNN) imputed data and a transformation to single categorical biomarker probe variables, with a mean accuracy of 81.4%, on held-out test sets. ERBB2 and MET variables ranked as top-performing features in 9 of 10 DT models and the full dataset model. These findings offer probabilistic guidance for FISH testing, emphasizing the prioritization of the ERBB2, SMAD4, and CDKN2A FISH probes in diagnosing NET primary sites.

Established and novel circulating neuroendocrine tumor biomarkers for diagnostic, predictive and prognostic use

The management of neuroendocrine tumors (NETs) represents a clinical challenge due to heterogeneity of their clinical behaviour, molecular biology and response to treatment. Over the years, several circulating biomarkers have been developed for the early diagnosis and follow-up of NETs. The specific secretory products of tumors associated with a secretory syndrome (functioning tumors) may be used as diagnostic and/or prognostic biomarkers while the most common non-specific circulating biomarkers, that may be increased in both functioning and non-functioning tumors, are chromogranin A and the neuron specific enolase. However, the diagnostic accuracy as well as the prognostic and predictive value of these biomarkers are limited and novel techniques of multianalyte analysis of regulators of tumor biology have been developed. The NETest has been most extensively studied and proved to be useful in NET diagnosis, early detection of post-operative recurrence and prediction of response to treatment but further investigation establishing higher level of evidence is required for implementation in clinical practice.