Systems Biology Approaches to Pancreatic Cancer Detection, Prevention and Treatment

2014 ◽  
Vol 20 (1) ◽  
pp. 73-80 ◽  
Author(s):  
Osama Alian ◽  
Philip Philip ◽  
Fazlul Sarkar ◽  
Asfar Azmi
Keyword(s):  
Pancreatic Cancer ◽  
Systems Biology ◽  
Cancer Detection ◽  
Prevention And Treatment

Development of extracellular vesicles-based classifier for detection of early-stage bladder, ovarian, and pancreatic cancer.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 3048-3048
Author(s):  
Juan Pablo Hinestrosa ◽  
Razelle Kurzrock ◽  
Jean Lewis ◽  
Nick Schork ◽  
Ashish M. Kamat ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Confidence Interval ◽  
Extracellular Vesicles ◽  
Metastatic Disease ◽  
Cancer Detection ◽  
Early Stage ◽  
Expression Patterns ◽  
Stepwise Logistic Regression ◽  
Liquid Biopsies ◽  
Cancer Early Detection

3048 Background: Many cancers are lethal because they present with metastatic disease. Because localized/resectable tumors produce vague symptoms, diagnosis is delayed. In pancreatic cancer, only ̃10% of patients survive five years, and it will soon become the second leading cause of cancer-related deaths in the USA. For patients with metastatic disease, the 2- and 5-year survival is < 10% and ̃3%, respectively. For the few patients with local disease, 5-year survival is ̃40%. Many other cancers have comparable differences between early- and late-stage disease. It is apparent a diagnostic assay for early-stage cancers would transform the field by minimizing the need for aggressive surgeries and other harsh interventions, and by its potential to increase survival. Identifying cancer-specific aberrations in blood-based “liquid” biopsies offers a prospect for a non-invasive cancer detection tool. In the bloodstream, there are extracellular vesicles (EVs) with cargoes including membrane and cytosolic proteins, as well as RNA and lipids derived from their parent cells. Methods: We used an alternating current electrokinetics (ACE) microarray to isolate EVs from the plasma of stage I and II bladder (N = 48), ovarian (N = 42), and pancreatic cancer patients (N = 44), and healthy volunteers (N = 110). EVs were analyzed using multiplex protein immunoassays for 54 cancer-related proteins. EV protein expression patterns were analyzed using stepwise logistic regression followed by a split between training and test sets (67%/33% respectively). This process enabled biomarker selection and generation of a classifier to discriminate between cancer and healthy donors. Results: The EV protein-based classifier had an overall area under curve (AUC) of 0.95 with a sensitivity of 71.2% (69.4% – 73.0%, at 95% confidence interval) at > 99% specificity. The classifier’s performance for the pancreatic cancer cohort was very strong, with overall sensitivity of 95.7% (94.6% – 96.9%, at 95% confidence interval) at > 99% specificity. Conclusions: EV-associated proteins may enable early cancer detection where surgical resection is most likely to improve outcomes. The classifier’s performance for the initial three cancers studied showed encouraging results. Future efforts will include examining additional cancer types and evaluating the classifier performance using samples from donors with related benign conditions with the aim of a pan-cancer early detection assay.

scholarly journals Artificial intelligence for pancreatic cancer detection: Recent development and future direction

2021 ◽  
Vol 2 (2) ◽  
pp. 56-68
Author(s):  
Passisd Laoveeravat ◽  
Priya R Abhyankar ◽  
Aaron R Brenner ◽  
Moamen M Gabr ◽  
Fadlallah G Habr ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Pancreatic Cancer ◽  
Cancer Detection ◽  
Future Direction

265 Rac1 is a therapeutic target for pancreatic cancer prevention and treatment

2010 ◽  
Vol 8 (7) ◽  
pp. 86
Author(s):  
C. Lubeseder-Martellato ◽  
I. Heid ◽  
B. Sipos ◽  
S. Rieder ◽  
R.M. Schmid ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Cancer Prevention ◽  
Therapeutic Target ◽  
Prevention And Treatment

Salivary Metabolomic Profiles for Oral, Breastand Pancreatic Cancer Detection

2010 ◽  
Vol 01 (01) ◽  
Author(s):  
Masahiro Sugimoto ◽  
Tomoyoshi Soga ◽  
Masaru Tomita
Keyword(s):  
Pancreatic Cancer ◽  
Cancer Detection

scholarly journals Omics Approaches in Pancreatic Adenocarcinoma

Cancers ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 1052
Author(s):  
Iranzu González-Boja ◽  
Antonio Viúdez ◽  
Saioa Goñi ◽  
Enrique Santamaria ◽  
Estefania Carrasco-García ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Survival Rate ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Ductal Adenocarcinoma ◽  
Curative Intent ◽  
Pancreatic Cancers ◽  
Wide Range ◽  
Prevention And Treatment ◽  
Shed Light

Pancreatic ductal adenocarcinoma, which represents 80% of pancreatic cancers, is mainly diagnosed when treatment with curative intent is not possible. Consequently, the overall five-year survival rate is extremely dismal—around 5% to 7%. In addition, pancreatic cancer is expected to become the second leading cause of cancer-related death by 2030. Therefore, advances in screening, prevention and treatment are urgently needed. Fortunately, a wide range of approaches could help shed light in this area. Beyond the use of cytological or histological samples focusing in diagnosis, a plethora of new approaches are currently being used for a deeper characterization of pancreatic ductal adenocarcinoma, including genetic, epigenetic, and/or proteo-transcriptomic techniques. Accordingly, the development of new analytical technologies using body fluids (blood, bile, urine, etc.) to analyze tumor derived molecules has become a priority in pancreatic ductal adenocarcinoma due to the hard accessibility to tumor samples. These types of technologies will lead us to improve the outcome of pancreatic ductal adenocarcinoma patients.

scholarly journals Mo1370 – Pancreatic Cancer Detection by Plasma Assay of Novel Methylated Dna Markers: A Case-Control Study

2019 ◽  
Vol 156 (6) ◽  
pp. S-754-S-755
Author(s):  
Shounak Majumder ◽  
William R. Taylor ◽  
Patrick H. Foote ◽  
Calise K. Berger ◽  
Chung Wah Wu ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Cancer Detection ◽  
Dna Markers ◽  
Case Control Study ◽  
Case Control ◽  
Methylated Dna ◽  
Control Study ◽  
Plasma Assay

964 Multiple Salivary Biomarkers for Pancreatic Cancer Detection

2009 ◽  
Vol 136 (5) ◽  
pp. A-147 ◽  
Author(s):  
James J. Farrell ◽  
Lei Zhang ◽  
M. Sugimoto ◽  
A. Hirayama ◽  
T. Soga ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Cancer Detection ◽  
Salivary Biomarkers
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