Dissemin is shutting down on January 1st, 2025

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MDPI, Cancers, 4(14), p. 1017, 2022

DOI: 10.3390/cancers14041017

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Molecular Profiling of Well-Differentiated Neuroendocrine Tumours: The Role of ctDNA in Real-World Practice

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Preprint: archiving allowed
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Postprint: archiving allowed
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Published version: archiving allowed
Data provided by SHERPA/RoMEO

Abstract

Background: The role of tumour genomic profiling in the clinical management of well-differentiated neuroendocrine tumours (WdNETs) is unclear. Circulating tumour DNA (ctDNA) may be a useful surrogate for tumour tissue when the latter is insufficient for analysis. Methods: Patients diagnosed with WdNETs underwent ctDNA genomic profiling (FoundationLiquid®); non-WdNETs (paraganglioma, goblet cell or poorly-differentiated neuroendocrine carcinoma) were used for comparison. The aim was to determine the rate of: test failure (primary end-point), “pathological alterations” (PAs) (secondary end-point) and patients for whom ctDNA analysis impacted management (secondary end-point). Results: Forty-five patients were included. A total of 15 patients with WdNETs (18 ctDNA samples) were eligible: 8 females (53.3%), median age 63.2 years (range 23.5–86.8). Primary: small bowel (8; 53.3%), pancreas (5; 33.3%), gastric (1; 6.7%) and unknown primary (1; 6.7%); grade (G)1 (n = 5; 33.3%), G2 (9; 60.0%) and G3 (1; 6.7%); median Ki-67: 5% (range 1–30). A total of 30 patients with non-WdNETs (34 ctDNA samples) were included. Five WdNETs samples (27.78%) failed analysis (vs. 17.65% in non-WdNETs; p-value 0.395). Of the 13 WdNET samples with successful ctDNA analyses, PAs were detected in 6 (46.15%) (vs. 82.14% in non-WdNETs; p-value 0.018). In WdNETs, the PA rate was independent of concomitant administration anti-cancer systemic therapies (2/7; 28.57% vs. 4/6; 66.67%; p-value 0.286) at the time of the ctDNA analysis: four, one and one samples had one, two and three PAs, respectively. These were: CDKN2A mutation (mut) (one sample), CHEK2mut (one), TP53mut (one), FGFR2 amplification (one), IDH2mut (one), CTNNB1mut (one), NF1mut (one) and PALB2mut (one). None were targetable (0%) or impacted clinical management (0%). There was a lower maximum mutant allele frequency (mMAF) in WdNETs (mean 0.33) vs. non-WdNETs (mean 26.99), even though differences did not reach statistical significance (p-value 0.0584). Conclusions: Although feasible, mutation-based ctDNA analysis was of limited clinical utility for patients with advanced WdNETs. The rates of PAs and mMAFs were higher in non-WdNETs. While patients with WdNETs could still be offered genomic profiling (if available and reimbursed), it is important to manage patients’ expectations regarding the likelihood of the results impacting their treatment.