Cystic precursors to invasive pancreatic cancer
Open accessAbstract
Improvements in the sensitivity and quality of cross-sectional imaging have led to increasing numbers of patients being diagnosed with cystic lesions of the pancreas. In parallel, clinical, radiological, pathological and molecular studies have improved the systems for classifying these cysts. Patients with asymptomatic serous cystic neoplasms can be managed conservatively with regular monitoring; however, the clinical management of patients with intraductal papillary mucinous neoplasms and mucinous cystic neoplasms is far more challenging, as it is difficult to determine whether these lesions will progress to malignancy. Fortunately, prospective studies have helped to establish that proposed clinical and radiological criteria (the Sendai guidelines) can be used to guide the care of patients with cystic lesions of the pancreas. Despite this progress in imaging and clinical guidelines, sensitive and specific tests have not yet been developed that can reliably predict the histology and biological properties of a cystic lesion. Such biomarkers are urgently needed, as noninvasive precursors of pancreatic cancer are curable, while the vast majority of invasive pancreatic adenocarcinomas are not.
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Intraductal papillary mucinous neoplasms (IPMNs) are the most common cystic mucinous precursors, are macroscopic, and can be followed by imaging.
“cystic mucinous neoplasms of the pancreas, of which intraductal papillary mucinous neoplasms (IPMNs) are the most common histological subtype, are macroscopic precursors that arise within the main pancreatic duct or one of its branches. These can be observed and followed for progression by imaging techniques25.”
From Pancreatic cancer: Advances and challenges (2023) · cites this paper as [25]
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Self-citationPANDA cyst-fluid analysis: eats, shoots and leaves?
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Pancreatic cancer: Advances and challenges
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Self-citationRecurrent GNAS Mutations Define an Unexpected Pathway for Pancreatic Cyst Development
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Self-citationMultidisciplinary standards of care and recent progress in pancreatic ductal adenocarcinoma
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Self-citationCancer overdiagnosis: a biological challenge and clinical dilemma
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Precursor Lesions for Sporadic Pancreatic Cancer: PanIN, IPMN, and MCN
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A multimodality test to guide the management of patients with a pancreatic cyst
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Self-citationThe pancreatic cancer genome revisited
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Preoperative<i>GNAS</i>and<i>KRAS</i>Testing in the Diagnosis of Pancreatic Mucinous Cysts
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RUNX3 Controls a Metastatic Switch in Pancreatic Ductal Adenocarcinoma
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Self-citationNeat1 is a p53-inducible lincRNA essential for transformation suppressionPreprint
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Plasticity and Dedifferentiation within the Pancreas: Development, Homeostasis, and Disease
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Pancreatic cancer in 2021: What you need to know to win
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A Plasma-Derived Protein-Metabolite Multiplexed Panel for Early-Stage Pancreatic Cancer
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Self-citationRadiomics in stratification of pancreatic cystic lesions: Machine learning in action
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Combating pancreatic cancer with PI3K pathway inhibitors in the era of personalised medicine
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Self-citationPancreatic cyst fluid harbors a unique microbiome
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The Impact of Biomarkers in Pancreatic Ductal Adenocarcinoma on Diagnosis, Surveillance and Therapy
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Neoplasms of the Exocrine Pancreas
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Self-citationFrom Machine Learning to Patient Outcomes: A Comprehensive Review of AI in Pancreatic Cancer
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A KRAS wild type mutational status confers a survival advantage in pancreatic ductal adenocarcinoma
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The BRG1/SOX9 axis is critical for acinar cell–derived pancreatic tumorigenesis
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Validation of Biomarkers for Early Detection of Pancreatic Cancer
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Non-coding RNA biomarkers in pancreatic ductal adenocarcinoma
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Quantitation of circulating satellite RNAs in pancreatic cancer patients
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Epithelial-Stromal Interactions in Pancreatic Cancer
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Is It Time to Expand the Role of Total Pancreatectomy for IPMN?
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Self-citationGlobal Protease Activity Profiling Provides Differential Diagnosis of Pancreatic Cysts
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Exosomal miRNA signatures of pancreatic lesions
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Case report: intraductal tubulopapillary neoplasm of the pancreas with unique clear cell phenotype
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DNA testing of pancreatic cyst fluid: is it ready for prime time?
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Molecular Diagnostics in the Evaluation of Pancreatic Cysts
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- Authors
- Matthaei, H., Schulick, R. D., Hruban, R. H., & Maitra, A.
- Affiliations
- Johns Hopkins University (US)
- Corresponding author
- Maitra, Anirban
- Venue
- Nature Reviews Gastroenterology & Hepatology
- Published
- 2011-03
- Volume
- 8
- Issue
- 3
- Pages
- 141-150
- ISSN
- 1759-5045 (ISSN-L)
- 1759-5053
- PMC
- PMC3236705
- OpenAlex
- W2063562637
- Cited by
- 193
- References
- 98
- Citations by year
- 2026: 6 · 2025: 6 · 2024: 8 · 2023: 12 · 2022: 9 · 2021: 13 · 2020: 17 · 2019: 10 · 2018: 25 · 2017: 16 · 2016: 15 · 2015: 13 · 2014: 16 · 2013: 13 · 2012: 10
- FWCI
- 1.26
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Nature Reviews Gastroenterology & Hepatology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Rolfe Pancreatic Cancer Foundation
- Deutsche Krebshilfe
- National Cancer Institute (R01CA113669, P50CA062924)
- Topics
- Health Sciences › Medicine › Oncology › Pancreatic and Hepatic Oncology Research
- Health Sciences › Medicine › Surgery › Pancreatitis Pathology and Treatment
- Health Sciences › Medicine › Epidemiology › Neuroendocrine Tumor Research Advances
- Keywords
- pancreatic cysts, precursor lesions, serous cystic neoplasm, intraductal papillary mucinous neoplasm, mucinous cystic neoplasm, cyst classification, biomarkers, pancreatic ductal adenocarcinoma, conservative treatment, radiological criteria
- MeSH terms
- Adenocarcinoma, Humans, Neoplasm Invasiveness, Pancreatic Cyst, Pancreatic Neoplasms, Precancerous Conditions, Disease Progression
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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