A unifying paradigm for transcriptional heterogeneity and squamous features in pancreatic ductal adenocarcinoma

Hayashi, Akimasa; Fan, Jun; Chen, Ruoyao; Ho, Yu-Jui; Makohon-Moore, Alvin; Lecomte, Nicolas; Zhong, Yi; Hong, Jae‐Hee; Ji, Huang; Sakamoto, Hitomi; Attiyeh, Marc A.; Kohutek, Zachary A.; Zhang, Lance; Boumiza, Aida; Kappagantula, Rajya; Baez, Priscilla; Bai, Jessica Jingyi; Lisi, Marta; Chadalavada, Kalyani; Melchor, Jerry P.; Wong, W. Douglas; Nanjangud, Gouri J.; Baştürk, Olca; O'Reilly, Eileen Mary; Klimstra, David S.; Hruban, Ralph H.; Wood, Laura D.; Overholtzer, Michael; Iacobuzio‐Donahue, Christine A.

doi:10.1038/s43018-019-0010-1

Cited by 154 publications

(198 citation statements)

References 62 publications

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“…, all tumor samples were composed of more than one subtype at single-cell level regardless of the classifier(Figures 3A-C; Supplementary Figures S3H-S3J), consistent with recent reports that Moffitt classical and basal-like subtypes coexist in a single tumor(22,23).…”

supporting

confidence: 90%

Elucidation of tumor-stromal heterogeneity and the ligand-receptor interactome by single cell transcriptomics in real-world pancreatic cancer biopsies

Lee

Bernard

Semaan

et al. 2020

Preprint

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Precision medicine approaches in pancreatic ductal adenocarcinoma (PDAC) are imperative for improving disease outcomes. However, the long-term fidelity of recently deployed ex vivo preclinical platforms, such as patient-derived organoids (PDOs), remains unknown. Through single-cell RNA sequencing (scRNA-seq), we identify substantial transcriptomic evolution of PDOs propagated from the parental tumor, which may alter predicted drug sensitivity. In contrast, scRNA-seq is readily applicable to limited biopsies from human primary and metastatic PDAC and identifies most cancers as being an admixture of previously described epithelial transcriptomic subtypes. Integrative analyses of our data provide an in-depth characterization of the heterogeneity within the tumor microenvironment, including cancer-associated fibroblast (CAF) subclasses, and predict a multitude of ligand-receptor interactions, revealing potential targets for immunotherapy approaches. While PDOs continue to enable prospective therapeutic prediction, our analysis also demonstrates the complementarity of using orthogonal de novo biopsies from PDAC patients paired with scRNA-seq to inform clinical decision-making.

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supporting

confidence: 90%

Elucidation of tumor-stromal heterogeneity and the ligand-receptor interactome by single cell transcriptomics in real-world pancreatic cancer biopsies

Lee

Bernard

Semaan

et al. 2020

Preprint

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“…Single cell RNA sequencing [15] and immunohistochemistry [18] of PDAC revealed intra-tumor heterogeneity where both types of cells (basal-like and classical) frequently co-exist. RNA profiling of multiple regions or multiple lesions from the same patient also demonstrated intra-tumor heterogeneity of the transformed epithelial compartment [4]. Using single cell RNA-seq, Chan-Seng-Yue et al in 2020 [15] confirmed the presence of several subpopulations with differential proliferative and migratory potentials in PDAC.…”

Section: Discussionmentioning

confidence: 98%

“…Recent reports indicate PDAC can be classified into distinct, biologically relevant categories based on histological and molecular analysis [4,5]. However, relatively few patients (15%) undergo resection that allows this analysis, and high intra-tumor heterogeneity and the limited amount of material obtained from EUS-FNA diagnostic biopsies prevent a precise classification of all PDAC tumors.…”

Section: Using Pdx To Define the Molecular Diversity Of Pdacmentioning

confidence: 99%

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

Nicolle

Blum

Duconseil

et al. 2020

Preprint

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BACKGROUND: A 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 PATIENTS: Tumors 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. RESULTS: 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 tumors (e.g. 308 consecutive resected PDAC, HR=0.321 95% CI [0.207;0.5] and 60 locallyadvanced 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). CONCLUSION: We 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.

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“…Three subsequent studies of distinct PASC cohorts, however, did not report somatic mutations in UPF1 [4][5][6] . This absence of UPF1 mutations is significantly different than the high rate reported by Liu et al (0 of 34 total PASC samples from three cohorts [4][5][6] vs. 18 of 23 PASC samples from Liu et al; p < 10 -8 by the two-sided binomial proportion test). Although these other studies relied on whole-exome and/or genome sequencing instead of targeted UPF1 gene sequencing, those technologies yield good coverage of the relevant UPF1 gene regions because the affected introns are very short.…”

Section: Main Textmentioning

confidence: 99%

“…We chose mouse pancreatic cancer cells (KPC cells: Kras G12D ; p53 R172H/null ; Pdx1-Cre) as a model system. KPC cells are defined by the Kras and Tp53 mutations that also occur in the vast majority of PASC cases 5,6,8 , making them a genetically appropriate system. We delivered Upf1-targeting paired guide RNAs to KPC cells using recombinant adenoviral vectors and confirmed that guide delivery resulted in production of UPF1 mRNA lacking exons 10 and 11 and a corresponding reduction in full-length UPF1 protein levels ( Fig.…”

Section: Main Textmentioning

confidence: 99%

The origins and consequences ofUPF1variants in pancreatic adenosquamous carcinoma

Polaski

Udy

Escobar‐Hoyos

et al. 2020

Preprint

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Pancreatic adenosquamous carcinoma (PASC) is a rare and aggressive subtype of pancreatic cancer whose mutational origins are poorly understood. An early study reported somatic mutations in UPF1, which encodes a core component of the nonsense-mediated mRNA decay (NMD) pathway, as a common signature of PASC, but subsequent studies did not observe these lesions in other PASC cohorts. The corresponding controversy about whether UPF1 mutations are important contributors to PASC has been exacerbated by a paucity of functional studies of these lesions. Here, we systematically assessed the potential roles of UPF1 mutations in PASC. We modeled two reported UPF1 mutations to find no consistent effects on pancreatic cancer growth, acquisition of adenosquamous features, UPF1 splicing, UPF1 protein levels, or NMD efficiency. We subsequently discovered that ~40% of UPF1 mutations reportedly present in PASCs are identical to standing genetic variation in the human population, suggesting that they are likely non-pathogenic inherited variation rather than pathogenic mutations. Our data suggest that UPF1 is not a common functional driver of PASC and motivate further attempts to identify unique genetic features defining these malignancies.

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A unifying paradigm for transcriptional heterogeneity and squamous features in pancreatic ductal adenocarcinoma

Cited by 154 publications

References 62 publications

Elucidation of tumor-stromal heterogeneity and the ligand-receptor interactome by single cell transcriptomics in real-world pancreatic cancer biopsies

Elucidation of tumor-stromal heterogeneity and the ligand-receptor interactome by single cell transcriptomics in real-world pancreatic cancer biopsies

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

The origins and consequences ofUPF1variants in pancreatic adenosquamous carcinoma

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