Raju Kandimalla1, Tadanobu Shimura1, Saurav Mallik2, Fuminori Sonohara3, Susan Tsai4, Douglas B Evans4, Song Cheol Kim5, Hideo Baba6, Yasuhiro Kodera3, Daniel Von Hoff7, Xi Chen2, Ajay Goel1,8. 1. Center for Gastrointestinal Research and Center for Translational Genomics and Oncology, Baylor Scott & White Research Institute and Charles A. Sammons Cancer Center, Baylor University Medical Center, Dallas, TX. 2. Division of Biostatistics and Bioinformatics, Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL. 3. Department of Gastroenterological Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan. 4. Department of Surgery, Division of Surgical Oncology, Medical College of Wisconsin, Milwaukee, WI. 5. Department of Hepatic and Pancreatobiliary Surgery, Asan Medical Center, Seoul, Korea. 6. Department of Gastroenterological Surgery, Graduate School of Medical Science, Kumamoto University, Kumamoto, Japan. 7. Translational Genomics Research Institute, Phoenix, AZ. 8. Department of Molecular Diagnostics and Experimental Therapeutics, Beckman Research Institute of City of Hope Comprehensive Cancer Center, Duarte, CA.
Abstract
OBJECTIVE: The aim of the study was to perform mRNA-miRNA regulatory network analyses to identify a miRNA panel for molecular subtype identification and stratification of high-risk patients with pancreatic ductal adenocarcinoma (PDAC). BACKGROUND: Recent transcriptional profiling effort in PDAC has led to the identification of molecular subtypes that associate with poor survival; however, their clinical significance for risk stratification in patients with PDAC has been challenging. METHODS: By performing a systematic analysis in The Cancer Genome Atlas and International Cancer Genome Consortium cohorts, we discovered a panel of miRNAs that associated with squamous and other poor molecular subtypes in PDAC. Subsequently, we used logistic regression analysis to develop models for risk stratification and Cox proportional hazard analysis to determine survival prediction probability of this signature in multiple cohorts of 433 patients with PDAC, including a tissue cohort (n = 199) and a preoperative serum cohort (n = 51). RESULTS: We identified a panel of 9 miRNAs that were significantly upregulated (miR-205-5p and -934) or downregulated (miR-192-5p, 194-5p, 194-3p, 215-5p, 375-3p, 552-3p, and 1251-5p) in PDAC molecular subtypes with poor survival [squamous, area under the receiver operating characteristic curve (AUC) = 0.90; basal, AUC = 0.89; and quasimesenchymal, AUC = 0.83]. The validation of this miRNA panel in a tissue clinical cohort was a significant predictor of overall survival (hazard ratio = 2.48, P < 0.0001), and this predictive accuracy improved further in a risk nomogram which included key clinicopathological factors. Finally, we were able to successfully translate this miRNA predictive signature into a liquid biopsy-based assay in preoperative serum specimens from PDAC patients (hazard ratio: 2.85, P = 0.02). CONCLUSION: We report a novel miRNA risk-stratification signature that can be used as a noninvasive assay for the identification of high-risk patients and potential disease monitoring in patients with PDAC.
OBJECTIVE: The aim of the study was to perform mRNA-miRNA regulatory network analyses to identify a miRNA panel for molecular subtype identification and stratification of high-risk patients with pancreatic ductal adenocarcinoma (PDAC). BACKGROUND: Recent transcriptional profiling effort in PDAC has led to the identification of molecular subtypes that associate with poor survival; however, their clinical significance for risk stratification in patients with PDAC has been challenging. METHODS: By performing a systematic analysis in The Cancer Genome Atlas and International Cancer Genome Consortium cohorts, we discovered a panel of miRNAs that associated with squamous and other poor molecular subtypes in PDAC. Subsequently, we used logistic regression analysis to develop models for risk stratification and Cox proportional hazard analysis to determine survival prediction probability of this signature in multiple cohorts of 433 patients with PDAC, including a tissue cohort (n = 199) and a preoperative serum cohort (n = 51). RESULTS: We identified a panel of 9 miRNAs that were significantly upregulated (miR-205-5p and -934) or downregulated (miR-192-5p, 194-5p, 194-3p, 215-5p, 375-3p, 552-3p, and 1251-5p) in PDAC molecular subtypes with poor survival [squamous, area under the receiver operating characteristic curve (AUC) = 0.90; basal, AUC = 0.89; and quasimesenchymal, AUC = 0.83]. The validation of this miRNA panel in a tissue clinical cohort was a significant predictor of overall survival (hazard ratio = 2.48, P < 0.0001), and this predictive accuracy improved further in a risk nomogram which included key clinicopathological factors. Finally, we were able to successfully translate this miRNA predictive signature into a liquid biopsy-based assay in preoperative serum specimens from PDAC patients (hazard ratio: 2.85, P = 0.02). CONCLUSION: We report a novel miRNA risk-stratification signature that can be used as a noninvasive assay for the identification of high-risk patients and potential disease monitoring in patients with PDAC.
Authors: Peter Bailey; David K Chang; Katia Nones; Amber L Johns; Ann-Marie Patch; Marie-Claude Gingras; David K Miller; Angelika N Christ; Tim J C Bruxner; Michael C Quinn; Craig Nourse; L Charles Murtaugh; Ivon Harliwong; Senel Idrisoglu; Suzanne Manning; Ehsan Nourbakhsh; Shivangi Wani; Lynn Fink; Oliver Holmes; Venessa Chin; Matthew J Anderson; Stephen Kazakoff; Conrad Leonard; Felicity Newell; Nick Waddell; Scott Wood; Qinying Xu; Peter J Wilson; Nicole Cloonan; Karin S Kassahn; Darrin Taylor; Kelly Quek; Alan Robertson; Lorena Pantano; Laura Mincarelli; Luis N Sanchez; Lisa Evers; Jianmin Wu; Mark Pinese; Mark J Cowley; Marc D Jones; Emily K Colvin; Adnan M Nagrial; Emily S Humphrey; Lorraine A Chantrill; Amanda Mawson; Jeremy Humphris; Angela Chou; Marina Pajic; Christopher J Scarlett; Andreia V Pinho; Marc Giry-Laterriere; Ilse Rooman; Jaswinder S Samra; James G Kench; Jessica A Lovell; Neil D Merrett; Christopher W Toon; Krishna Epari; Nam Q Nguyen; Andrew Barbour; Nikolajs Zeps; Kim Moran-Jones; Nigel B Jamieson; Janet S Graham; Fraser Duthie; Karin Oien; Jane Hair; Robert Grützmann; Anirban Maitra; Christine A Iacobuzio-Donahue; Christopher L Wolfgang; Richard A Morgan; Rita T Lawlor; Vincenzo Corbo; Claudio Bassi; Borislav Rusev; Paola Capelli; Roberto Salvia; Giampaolo Tortora; Debabrata Mukhopadhyay; Gloria M Petersen; Donna M Munzy; William E Fisher; Saadia A Karim; James R Eshleman; Ralph H Hruban; Christian Pilarsky; Jennifer P Morton; Owen J Sansom; Aldo Scarpa; Elizabeth A Musgrove; Ulla-Maja Hagbo Bailey; Oliver Hofmann; Robert L Sutherland; David A Wheeler; Anthony J Gill; Richard A Gibbs; John V Pearson; Nicola Waddell; Andrew V Biankin; Sean M Grimmond Journal: Nature Date: 2016-02-24 Impact factor: 49.962
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Authors: Nicola Waddell; Marina Pajic; Ann-Marie Patch; David K Chang; Karin S Kassahn; Peter Bailey; Amber L Johns; David Miller; Katia Nones; Kelly Quek; Michael C J Quinn; Alan J Robertson; Muhammad Z H Fadlullah; Tim J C Bruxner; Angelika N Christ; Ivon Harliwong; Senel Idrisoglu; Suzanne Manning; Craig Nourse; Ehsan Nourbakhsh; Shivangi Wani; Peter J Wilson; Emma Markham; Nicole Cloonan; Matthew J Anderson; J Lynn Fink; Oliver Holmes; Stephen H Kazakoff; Conrad Leonard; Felicity Newell; Barsha Poudel; Sarah Song; Darrin Taylor; Nick Waddell; Scott Wood; Qinying Xu; Jianmin Wu; Mark Pinese; Mark J Cowley; Hong C Lee; Marc D Jones; Adnan M Nagrial; Jeremy Humphris; Lorraine A Chantrill; Venessa Chin; Angela M Steinmann; Amanda Mawson; Emily S Humphrey; Emily K Colvin; Angela Chou; Christopher J Scarlett; Andreia V Pinho; Marc Giry-Laterriere; Ilse Rooman; Jaswinder S Samra; James G Kench; Jessica A Pettitt; Neil D Merrett; Christopher Toon; Krishna Epari; Nam Q Nguyen; Andrew Barbour; Nikolajs Zeps; Nigel B Jamieson; Janet S Graham; Simone P Niclou; Rolf Bjerkvig; Robert Grützmann; Daniela Aust; Ralph H Hruban; Anirban Maitra; Christine A Iacobuzio-Donahue; Christopher L Wolfgang; Richard A Morgan; Rita T Lawlor; Vincenzo Corbo; Claudio Bassi; Massimo Falconi; Giuseppe Zamboni; Giampaolo Tortora; Margaret A Tempero; Anthony J Gill; James R Eshleman; Christian Pilarsky; Aldo Scarpa; Elizabeth A Musgrove; John V Pearson; Andrew V Biankin; Sean M Grimmond Journal: Nature Date: 2015-02-26 Impact factor: 49.962
Authors: Maarouf A Saad; Selena Z Kuo; Elham Rahimy; Angela E Zou; Avinaash Korrapati; Mehran Rahimy; Elizabeth Kim; Hao Zheng; Michael Andrew Yu; Jessica Wang-Rodriguez; Weg M Ongkeko Journal: Mol Cancer Date: 2015-10-15 Impact factor: 27.401
Authors: Richard A Moffitt; Raoud Marayati; Elizabeth L Flate; Keith E Volmar; S Gabriela Herrera Loeza; Katherine A Hoadley; Naim U Rashid; Lindsay A Williams; Samuel C Eaton; Alexander H Chung; Jadwiga K Smyla; Judy M Anderson; Hong Jin Kim; David J Bentrem; Mark S Talamonti; Christine A Iacobuzio-Donahue; Michael A Hollingsworth; Jen Jen Yeh Journal: Nat Genet Date: 2015-09-07 Impact factor: 38.330