Elevating pancreatic cystic lesion stratification: Current and future pancreatic cancer biomarker(s)

Pancreatic cystic neoplasms (PCNs) are being detected increasingly frequently due to the widespread use of high-resolution abdominal imaging modalities. Some subtypes of PCNs have the potential for malignant transformation. Therefore, accurate diagnosis of PCNs is crucial to determine whether surgical resection or surveillance is the best management strategy. However, the current cross-section imaging modalities are not accurate enough to enable definite diagnoses. In the last decade, EUS-based techniques have emerged, aiming to overcome the limitations of standard cross-section imaging modalities. These novel EUS-based techniques were primarily designed to acquire distinct images to make radiological diagnoses, collect cyst fluid to undergo biochemical or molecular analyses, and obtain tissue to conclude the pathological diagnoses. In this article, we present a comprehensive and critical review of these emerging EUS techniques for the diagnosis of PCNs, with emphasis being placed on the advantages, feasibilities, diagnostic performances, and limitations of these novel techniques.

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“…However, due to high numbers and variability, the proteins tested display a lack of one definitive marker capable of accurate diagnoses. [ 89 ]…”

Section: Cyst Fluid Molecular Analysismentioning

confidence: 99%

Application of EUS-based techniques in the evaluation of pancreatic cystic neoplasms

2021

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“…This enzymatic process produces glycosidic linkages of saccharides to other saccharides, lipids, or proteins which can affect the activity and localization of proteins/transmembrane proteins involved in cellcell adhesion [48,61]. Recently, it has been noted that N-glycosylation profiles or the 'N-glycome' of the potential protein biomarkers or panels of biomarkers are emerging as potential therapeutic targets in the various types/subtypes of diabetes [62,63]. In light of this, we believe that more hyperglycemia induced levels of glycosylated protein biomarkers will be found and helpful to understand the association of subtype-diabetes with subtype-pancreatic cancer in future.…”

Section: Diabetes Mellitus and Pancreatic Cancer Association At The Cellular Levelmentioning

confidence: 99%

Review of Diabetes Mellitus in Relation to Pancreatic Cancer

2021

Clinical Medical Case Reports and Reviews

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Background Global Epidemiology of Pancreatic CancerToday's statistical studies implicate that PC is the fourth leading cause of death among all the cancers, and is even projected to become the second leading cause of death in the coming years [1]. For this highly aggressive and devastating malignancy it is known that pancreatic cancer's incidence and mortality patterns differ among populations. Overall clinical data show 93% pancreatic cancers are exocrine adenocarcinoma with the remainder (7%) being pancreatic neuroendocrine tumors. Pancreatic ductal adenocarcinoma (PDAC) remains highly lethal with a 5-year survival rate of 8.2% in United States and Europe [1,2] (American Cancer Society; https://www. cancer.org). ASCO guidelines for the management of locally advanced pancreatic (LAPC) with an expected 5-year overall survival rate of less than 5% are more limited than for a potentially curable disease, and much more so for metastatic pancreatic cancer whose patients have less than 1-year median life expectancy with the 5-year overall survival rate of only 2% [3].It is estimated that during 2020 in the United States, 57,600 adults (30,400 men and 27,200 women) will be diagnosed with PC, 3-7% of all cancers in the US population [4]. Whereas Europe and the European Union (40 total countries) comprise 9% of the world population, the region has a 25% share of the global cancer (burden) and thus provides key cancer planning programs (European Network of Cancer Registries, ENCR, www.encr.eu and United Nations, population division, World Population Prospects, https://esa.un.org/ unpd/wpp/). In 2018, estimated incidence of new PC cases and

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“…Whereas standard "semantic" radiologic features are typically subjectively and qualitatively measured, computer algorithmgenerated radiomic features such as tumor signal intensity, texture, shape, and volume have many advantages (15)(16)(17)(18)(19)(20)(21): they represent quantitative, objective measures; reflect tumor heterogeneity and subregional habitats; and are reproducible, stable, and strongly linked to clinical outcomes and underlying molecular data. Radiomic evaluations of pancreas CT scans have been conducted by our team (22)(23)(24) and others (15,(25)(26)(27)(28)(29)(30)(31)(32)(33)(34)(35)(36)(37)(38), but to date none of these studies have focused on evaluating radiomic features present in pancreatic tumors from AA compared to other ethnic populations. Furthermore, we are unaware of published investigations that specifically compare racial and ethnic differences in radiomic features of different types of non-pancreas tumors.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Radiomic Features in a Diverse Cohort of Patients With Pancreatic Ductal Adenocarcinomas

Permuth

Vyas

et al. 2021

Front. Oncol.

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BackgroundSignificant racial disparities in pancreatic cancer incidence and mortality rates exist, with the highest rates in African Americans compared to Non-Hispanic Whites and Hispanic/Latinx populations. Computer-derived quantitative imaging or “radiomic” features may serve as non-invasive surrogates for underlying biological factors and heterogeneity that characterize pancreatic tumors from African Americans, yet studies are lacking in this area. The objective of this pilot study was to determine if the radiomic tumor profile extracted from pretreatment computed tomography (CT) images differs between African Americans, Non-Hispanic Whites, and Hispanic/Latinx with pancreatic cancer.MethodsWe evaluated a retrospective cohort of 71 pancreatic cancer cases (23 African American, 33 Non-Hispanic White, and 15 Hispanic/Latinx) who underwent pretreatment CT imaging at Moffitt Cancer Center and Research Institute. Whole lesion semi-automated segmentation was performed on each slice of the lesion on all pretreatment venous phase CT exams using Healthmyne Software (Healthmyne, Madison, WI, USA) to generate a volume of interest. To reduce feature dimensionality, 135 highly relevant non-texture and texture features were extracted from each segmented lesion and analyzed for each volume of interest.ResultsThirty features were identified and significantly associated with race/ethnicity based on Kruskal-Wallis test. Ten of the radiomic features were highly associated with race/ethnicity independent of tumor grade, including sphericity, volumetric mean Hounsfield units (HU), minimum HU, coefficient of variation HU, four gray level texture features, and two wavelet texture features. A radiomic signature summarized by the first principal component partially differentiated African American from non-African American tumors (area underneath the curve = 0.80). Poorer survival among African Americans compared to Non-African Americans was observed for tumors with lower volumetric mean CT [HR: 3.90 (95% CI:1.19–12.78), p=0.024], lower GLCM Avg Column Mean [HR:4.75 (95% CI: 1.44,15.37), p=0.010], and higher GLCM Cluster Tendency [HR:3.36 (95% CI: 1.06–10.68), p=0.040], and associations persisted in volumetric mean CT and GLCM Avg Column after adjustment for key clinicopathologic factors.ConclusionsThis pilot study identified several textural radiomics features associated with poor overall survival among African Americans with PDAC, independent of other prognostic factors such as grade. Our findings suggest that CT radiomic features may serve as surrogates for underlying biological factors and add value in predicting clinical outcomes when integrated with other parameters in ongoing and future studies of cancer health disparities.

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Elevating pancreatic cystic lesion stratification: Current and future pancreatic cancer biomarker(s)

Cited by 31 publications

References 227 publications

Application of EUS-based techniques in the evaluation of pancreatic cystic neoplasms

Application of EUS-based techniques in the evaluation of pancreatic cystic neoplasms

Review of Diabetes Mellitus in Relation to Pancreatic Cancer

Comparison of Radiomic Features in a Diverse Cohort of Patients With Pancreatic Ductal Adenocarcinomas

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