| Literature DB >> 31893993 |
Prashant Dogra1, Javier R Ramírez1, María J Peláez1,2, Zhihui Wang1, Vittorio Cristini1, Gulshan Parasher3, Manmeet Rawat3.
Abstract
Pancreatic Ductal Adenocarcinoma (PDAC) is regarded as one of the most lethal cancer types for its challenges associated with early diagnosis and resistance to standard chemotherapeutic agents, thereby leading to a poor five-year survival rate. The complexity of the disease calls for a multidisciplinary approach to better manage the disease and improve the status quo in PDAC diagnosis, prognosis, and treatment. To this end, the application of quantitative tools can help improve the understanding of disease mechanisms, develop biomarkers for early diagnosis, and design patient-specific treatment strategies to improve therapeutic outcomes. However, such approaches have only been minimally applied towards the investigation of PDAC, and we review the current status of mathematical modeling works in this field. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.Entities:
Keywords: Cancer; Carcinoembryoniczzm321990Antigen (CEA); Desmoplasia; Mathematical modeling; Numerical simulation; Pancreatic ductal adenocarcinoma.
Year: 2020 PMID: 31893993 PMCID: PMC7279939 DOI: 10.2174/1568026620666200101095641
Source DB: PubMed Journal: Curr Top Med Chem ISSN: 1568-0266 Impact factor: 3.295