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DOI 10.1016/j.ebiom.2020.102858

Медицинская библиотека · EBioMedicine · 2020

Establishment of a pancreatic adenocarcinoma molecular gradient (PAMG) that predicts the clinical outcome of pancreatic cancer.

Nicolle Rémy, Blum Yuna, Duconseil Pauline, Vanbrugghe Charles, Brandone Nicolas, Poizat Flora, Roques Julie, Bigonnet Martin, Gayet Odile, Rubis Marion, Elarouci Nabila, Armenoult Lucile, Ayadi Mira, de Reyniès Aurélien, Giovannini Marc, Grandval Philippe, Garcia Stephane, Canivet Cindy, Cros Jérôme, Bournet Barbara, Buscail Louis, BACAP Consortium, Moutardier Vincent, Gilabert Marine, Iovanna Juan, Dusetti Nelson

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Аннотация

BACKGROUND

A significant gap in pancreatic ductal adenocarcinoma (PDAC) patient's care is the lack of molecular parameters characterizing tumours and allowing a personalized treatment.

METHODS

Patient-derived xenografts (PDX) were obtained from 76 consecutive PDAC and classified according to their histology into five groups. A PDAC molecular gradient (PAMG) was constructed from PDX transcriptomes recapitulating the five histological groups along a continuous gradient. The prognostic and predictive value for PMAG was evaluated in: i/ two independent series (n = 598) of resected tumours; ii/ 60 advanced tumours obtained by diagnostic EUS-guided biopsy needle flushing and iii/ on 28 biopsies from mFOLFIRINOX treated metastatic tumours.

FINDINGS: A unique transcriptomic signature (PAGM) was generated with significant and independent prognostic value. PAMG significantly improves the characterization of PDAC heterogeneity compared to non-overlapping classifications as validated in 4 independent series of tumours (e.g. 308 consecutive resected PDAC, uHR=0.321 95% CI [0.207-0.5] and 60 locally-advanced or metastatic PDAC, uHR=0.308 95% CI [0.113-0.836]). The PAMG signature is also associated with progression under mFOLFIRINOX treatment (Pearson correlation to tumour response: -0.67, p-value < 0.001).

INTERPRETATION: PAMG unify all PDAC pre-existing classifications inducing a shift in the actual paradigm of binary classifications towards a better characterization in a gradient.

FUNDING: Project funding was provided by INCa (Grants number 2018-078 and 2018-079, BACAP BCB INCa_6294), Canceropole PACA, DGOS (labellisation SIRIC), Amidex Foundation, Fondation de France, INSERM and Ligue Contre le Cancer.

Для цитирования: Nicolle Rémy, Blum Yuna, Duconseil Pauline, Vanbrugghe Charles, Brandone Nicolas, Poizat Flora, Roques Julie, Bigonnet Martin, Gayet Odile, Rubis Marion, Elarouci Nabila, Armenoult Lucile, Ayadi Mira, de Reyniès Aurélien, Giovannini Marc, Grandval Philippe, Garcia Stephane, Canivet Cindy, Cros Jérôme, Bournet Barbara, Buscail Louis, BACAP Consortium, Moutardier Vincent, Gilabert Marine, Iovanna Juan, Dusetti Nelson. Establishment of a pancreatic adenocarcinoma molecular gradient (PAMG) that predicts the clinical outcome of pancreatic cancer.. EBioMedicine. 2020. DOI: 10.1016/j.ebiom.2020.102858.

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