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

Autor: Nicolle, Rémy, Blum, Yuna, Duconseil, Pauline, Vanbrugghe, Charles, Brandone, Nicolas, Poizat, Flora, Roques, Julie, Bigonnet, Martin, Gayet, Odile, Rubis, Marion, Dou, Samir, Elarouci, Nabila, Armenoult, Lucile, Ayadi, Mira, de Reyniès, Aurélien, Giovannini, Marc, Grandval, Philippe, Garcia, Stephane, Canivet, Cindy, Cros, Jérôme, Bournet, Barbara, Buscail, Louis, Moutardier, Vincent, Gilabert, Marine, Iovanna, Juan, Dusetti, Nelson
Rok vydání: 2020
Předmět:
Oncology
Male
Research paper
endocrine system diseases
Personalized treatment
Leucovorin
lcsh:Medicine
Tumor response
Mice
Antineoplastic Combined Chemotherapy Protocols
Neoplasm Metastasis
Precision Medicine
lcsh:R5-920
Clinical Trials as Topic
medicine.diagnostic_test
Middle Aged
Prognosis
Predictive value
Well differentiated
Neoplasm Proteins
Gene Expression Regulation
Neoplastic
Oxaliplatin
Adenocarcinoma
Heterografts
Female
Translational medicine
Fluorouracil
lcsh:Medicine (General)
Adult
medicine.medical_specialty
Adolescent
Transcriptomic signature
Irinotecan
Prognostic
Disease-Free Survival
Young Adult
Chemosensitivity prediction
Internal medicine
Pancreatic cancer
Cell Line
Tumor
Biopsy
medicine
Biomarkers
Tumor
Animals
Humans
Endoscopic Ultrasound-Guided Fine Needle Aspiration
Aged
business.industry
lcsh:R
Histology
medicine.disease
Pancreatic Neoplasms
Drug Resistance
Neoplasm
business
Transcriptome
Zdroj: EBioMedicine
EBioMedicine, Vol 57, Iss, Pp 102858-(2020)
ISSN: 2352-3964
Popis: BACKGROUNDA significant gap in pancreatic ductal adenocarcinoma (PDAC) patient’s care is the lack of molecular parameters characterizing tumors and allowing a personalized treatment. The goal of this study was to examine whole PDAC transcriptomic profiles to define a signature that would predict aggressiveness and treatment responsiveness better than done until now.METHODS AND PATIENTSTumors were obtained from 76 consecutive resectable (n=40) or unresectable (n=36) tumors. PDAC were transplanted in mice to produce patient-drived xenografts (PDX). PDX were classified according to their histology into five groups, from highly undifferentiated to well differentiated. This classification resulted strongly associated with tumors aggressiveness. 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 tumors; ii/ 60 advanced tumors obtained by diagnostic EUS-guided biopsy needle flushing and iii/ on 28 biopsies from mFOLFIRINOX treated metastatic tumors.RESULTSA 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 tumors (e.g. 308 consecutive resected PDAC, HR=0.321 95% CI [0.207;0.5] and 60 locally-advanced or metastatic PDAC, HR=0.308 95% CI [0.113;0.836]). The PAMG signature is also associated with progression under mFOLFIRINOX treatment (Pearson correlation to tumor response: -0.67, p-value < 0.001).CONCLUSIONWe identified a transcriptomic signature (PAMG) that, unlike all other stratification schemas already proposed, classifies PDAC along a continuous gradient. It can be performed on formalin-fixed paraffin-embedded samples and EUS-guided biopsies showing a strong prognostic value and predicting mFOLFIRINOX responsiveness. We think that PAMG could unify all PDAC preexisting classifications inducing a shift in the actual paradigm of binary classifications towards a better characterization in a gradient.Trial RegistrationThe PaCaOmics study is registered atwww.clinicaltrials.govwith registration numberNCT01692873. The validation BACAP study is registered atwww.clinicaltrials.govwith registration numberNCT02818829.
Databáze: OpenAIRE
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