scholarly journals PCCR: Pancreatic Cancer Collaborative Registry

2011 ◽  
Vol 10 ◽  
pp. CIN.S6919 ◽  
Author(s):  
Simon Sherman ◽  
Oleg Shats ◽  
Marsha A. Ketcham ◽  
Michelle A. Anderson ◽  
David C. Whitcomb ◽  
...  

The Pancreatic Cancer Collaborative Registry (PCCR) is a multi-institutional web-based system aimed to collect a variety of data on pancreatic cancer patients and high-risk subjects in a standard and efficient way. The PCCR was initiated by a group of experts in medical oncology, gastroenterology, genetics, pathology, epidemiology, nutrition, and computer science with the goal of facilitating rapid and uniform collection of critical information and biological samples to be used in developing diagnostic, prevention and treatment strategies against pancreatic cancer. The PCCR is a multi-tier web application that utilizes Java/JSP technology and has Oracle 10 g database as a back-end. The PCCR uses a “confederation model” that encourages participation of any interested center, irrespective of its size or location. The PCCR utilizes a standardized approach to data collection and reporting, and uses extensive validation procedures to prevent entering erroneous data. The PCCR controlled vocabulary is harmonized with the NCI Thesaurus (NCIt) or Systematized Nomenclature of Medicine-Clinical Terms (SNOMED-CT). The PCCR questionnaire has accommodated standards accepted in cancer research and healthcare. Currently, seven cancer centers in the USA, as well as one center in Italy are participating in the PCCR. At present, the PCCR database contains data on more than 2,700 subjects (PC patients and individuals at high risk of getting this disease). The PCCR has been certified by the NCI Center for Biomedical Informatics and Information Technology as a cancer Biomedical Informatics Grid (caBIG®) Bronze Compatible product. The PCCR provides a foundation for collaborative PC research. It has all the necessary prerequisites for subsequent evolution of the developed infrastructure from simply gathering PC-related data into a biomedical computing platform vital for successful PC studies, care and treatment. Studies utilizing data collected in the PCCR may engender new approaches to disease prognosis, risk factor assessment, and therapeutic interventions.

2011 ◽  
Vol 10 ◽  
pp. CIN.S7845 ◽  
Author(s):  
Simon Sherman ◽  
Oleg Shats ◽  
Elizabeth Fleissner ◽  
George Bascom ◽  
Kevin Yiee ◽  
...  

The Breast Cancer Collaborative Registry (BCCR) is a multicenter web-based system that efficiently collects and manages a variety of data on breast cancer (BC) patients and BC survivors. This registry is designed as a multi-tier web application that utilizes Java Servlet/JSP technology and has an Oracle 11g database as a back-end. The BCCR questionnaire has accommodated standards accepted in breast cancer research and healthcare. By harmonizing the controlled vocabulary with the NCI Thesaurus (NCIt) or Systematized Nomenclature of Medicine-Clinical Terms (SNOMED-CT), the BCCR provides a standardized approach to data collection and reporting. The BCCR has been recently certified by the National Cancer Institute's Center for Biomedical Informatics and Information Technology (NCI CBIIT) as a cancer Biomedical Informatics Grid (caBIG®) Bronze Compatible product. The BCCR is aimed at facilitating rapid and uniform collection of critical information and biological samples to be used in developing diagnostic, prevention, treatment, and survivorship strategies against breast cancer. Currently, seven cancer institutions are participating in the BCCR that contains data on almost 900 subjects (BC patients and survivors, as well as individuals at high risk of getting BC).


2021 ◽  
Vol 135 (10) ◽  
pp. 1289-1293
Author(s):  
Gregor Werba ◽  
Tamas A. Gonda

Abstract Pancreatic ductal adenocarcinoma (PDAC) features a hostile tumor microenvironment (TME) that renders it remarkably resistant to most therapeutic interventions. Consequently, survival remains among the poorest compared with other gastrointestinal cancers. Concerted efforts are underway to decipher the complex PDAC TME, break down barriers to efficacious therapies and identify novel treatment strategies. In the recent Clinical Science, Li and colleagues identify the long noncoding RNA KLHDC7B-DT as a crucial epigenetic regulator of IL-6 transcription in PDAC and illustrate its potent influences on the pancreatic TME. In this commentary, we introduce epigenetics in pancreatic cancer and put the findings by Li et al. in context with current knowledge.


2020 ◽  
Vol 40 (7) ◽  
pp. 629-643 ◽  
Author(s):  
Arielle G. Bensimon ◽  
Zheng-Yi Zhou ◽  
Madeline Jenkins ◽  
Yan Song ◽  
Wei Gao ◽  
...  

Pharmaceutics ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 1987
Author(s):  
Nagabhishek Sirpu Natesh ◽  
Brianna M. White ◽  
Maia M. C. Bennett ◽  
Metin Uz ◽  
Rakhee Rathnam Kalari Kandy ◽  
...  

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy with high mortality, poor prognosis, and palliative treatments, due to the rapid upregulation of alternative compensatory pathways and desmoplastic reaction. miRNAs, small non-coding RNAs, have been recently identified as key players regulating cancer pathogenesis. Dysregulated miRNAs are associated with molecular pathways involved in tumor development, metastasis, and chemoresistance in PDAC, as well as other cancers. Targeted treatment strategies that alter miRNA levels in cancers have promising potential as therapeutic interventions. miRNA-345 (miR-345) plays a critical role in tumor suppression and is differentially expressed in various cancers, including pancreatic cancer (PC). The underlying mechanism(s) and delivery strategies of miR-345 have been investigated by us previously. Here, we summarize the potential therapeutic roles of miR-345 in different cancers, with emphasis on PDAC, for miRNA drug discovery, development, status, and implications. Further, we focus on miRNA nanodelivery system(s), based on different materials and nanoformulations, specifically for the delivery of miR-345.


Author(s):  
Yang Gao ◽  
Enchong Zhang ◽  
Xiang Fei ◽  
Lingming Kong ◽  
Peng Liu ◽  
...  

Pancreatic cancer (PanC) is an intractable malignancy with a high mortality. Metabolic processes contribute to cancer progression and therapeutic responses, and histopathological subtypes are insufficient for determining prognosis and treatment strategies. In this study, PanC subtypes based on metabolism-related genes were identified and further utilized to construct a prognostic model. Using a cohort of 171 patients from The Cancer Genome Atlas (TCGA) database, transcriptome data, simple nucleotide variants (SNV), and clinical information were analyzed. We divided patients with PanC into metabolic gene-enriched and metabolic gene-desert subtypes. The metabolic gene-enriched subgroup is a high-risk subtype with worse outcomes and a higher frequency of SNVs, especially in KRAS. After further characterizing the subtypes, we constructed a risk score algorithm involving multiple genes (i.e., NEU2, GMPS, PRIM2, PNPT1, LDHA, INPP4B, DPYD, PYGL, CA12, DHRS9, SULT1E1, ENPP2, PDE1C, TPH1, CHST12, POLR3GL, DNMT3A, and PGS1). We verified the reproducibility and reliability of the risk score using three validation cohorts (i.e., independent datasets from TCGA, Gene Expression Omnibus, and Ensemble databases). Finally, drug prediction was completed using a ridge regression model, yielding nine candidate drugs for high-risk patients. These findings support the classification of PanC into two metabolic subtypes and further suggest that the metabolic gene-enriched subgroup is associated with worse outcomes. The newly established risk model for prognosis and therapeutic responses may improve outcomes in patients with PanC.


2019 ◽  
Author(s):  
Hidetoshi Ikeda ◽  
Takuma Ikeda ◽  
Hidetoshi Tahara
Keyword(s):  

Author(s):  
Amit Dang ◽  
Surendar Chidirala ◽  
Prashanth Veeranki ◽  
BN Vallish

Background: We performed a critical overview of published systematic reviews (SRs) of chemotherapy for advanced and locally advanced pancreatic cancer, and evaluated their quality using AMSTAR2 and ROBIS tools. Materials and Methods: PubMed and Cochrane Central Library were searched for SRs on 13th June 2020. SRs with metaanalysis which included only randomized controlled trials and that had assessed chemotherapy as one of the treatment arms were included. The outcome measures, which were looked into, were progression-free survival (PFS), overall survival (OS), and adverse events (AEs) of grade 3 or above. Two reviewers independently assessed all the SRs with both ROBIS and AMSTAR2. Results: Out of the 1,879 identified records, 26 SRs were included for the overview. Most SRs had concluded that gemcitabine-based combination regimes, prolonged OS and PFS, but increased the incidence of grade 3-4 toxicities, when compared to gemcitabine monotherapy, but survival benefits were not consistent when gemcitabine was combined with molecular targeted agents. As per ROBIS, 24/26 SRs had high risk of bias, with only 1/26 SR having low risk of bias. As per AMSTAR2, 25/26 SRs had critically low, and 1/26 SR had low, confidence in the results. The study which scored ‘low’ risk of bias in ROBIS scored ‘low confidence in results’ in AMSTAR2. The inter-rater reliability for scoring the overall confidence in the SRs with AMSTAR2 and the overall domain in ROBIS was substantial; ROBIS: kappa=0.785, SEM=0.207, p<0.001; AMSTAR2: kappa=0.649, SEM=0.323, p<0.001. Conclusion: Gemcitabine-based combination regimens can prolong OS and PFS but also worsen AEs when compared to gemcitabine monotherapy. The included SRs have an overall low methodological quality and high risk of bias as per AMSTAR2 and ROBIS respectively.


2020 ◽  
Vol 14 (11) ◽  
pp. 1009-1020
Author(s):  
Ryota Nakano ◽  
Shin Nishiumi ◽  
Takashi Kobayashi ◽  
Takuya Ikegawa ◽  
Yuzo Kodama ◽  
...  

Aim: The aim of this study was to identify whether metabolite biomarker candidates for pancreatic cancer (PC) could aid detection of intraductal papillary mucinous neoplasms (IPMN), recognized as high-risk factors for PC. Materials & methods: The 12 metabolite biomarker candidates, which were found to be useful to detect PC in our previous study, were evaluated for plasma samples from patients with PC (n = 44) or IPMN (n = 24) or healthy volunteers (n = 46). Results: Regarding the performance of individual biomarkers of PC and PC high-risk IPMN, lysine exhibited the best performance (sensitivity: 67.8%; specificity: 86.9%). The multiple logistic regression analysis-based detection model displayed high sensitivity and specificity values of 92.5 and 90.6%, respectively. Conclusion: Metabolite biomarker candidates for PC are useful for detecting high-risk IPMN, which can progress to PC.


2020 ◽  
Vol 29 (03) ◽  
pp. 143-148
Author(s):  
Ranjit Kumar Nath ◽  
Siva Subramaniyan ◽  
Neeraj Pandit ◽  
Deepankar Vatsa

AbstractTranspedal access is an evolving technique primarily used in patients after failed femoral antegrade approach to revascularize complex tibiopedal lesions. In patients who are at high risk for surgery the transpedal access may be the only option in failed antegrade femoral access to avoid amputation of the limbs. In recent years transpedal access is used routinely to revascularize supra-popliteal lesions due to more success and less complications over femoral artery approach. Retrograde approach parse will not give success in all cases and importantly success depends on techniques used. There are different techniques that need to be used depending on lesion characteristics, comorbidities, and hardware available to improve success with less complications. This review provides different strategies for successful treatment of iliac and femoral artery lesions by transpedal approach after failed antegrade femoral attempt.


Author(s):  
Umme Hani ◽  
Riyaz Ali M. Osmani ◽  
Ayesha Siddiqua ◽  
Shadma Wahab ◽  
Sadia Batool ◽  
...  

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