A Generalized Beta model for the age distribution of cancers: application to pancreatic and kidney cancer.

The relationships between cancer incidence rates and the age of patients at cancer diagnosis are a quantitative basis for modeling age distributions of cancer. The obtained model parameters are needed to build rigorous statistical and biological models of cancer development. In this work, a new mathematical model, called the Generalized Beta (GB) model is proposed. Confidence intervals for parameters of this model are derived from a regression analysis. The GB model was used to approximate the incidence rates of the first primary, microscopically confirmed cases of pancreatic cancer (PC) and kidney cancer (KC) that served as a test bed for the proposed approach. The use of the GB model allowed us to determine analytical functions that provide an excellent fit for the observed incidence rates for PC and KC in white males and females. We make the case that the cancer incidence rates can be characterized by a unique set of model parameters (such as an overall cancer rate, and the degree of increase and decrease of cancer incidence rates). Our results suggest that the proposed approach significantly expands possibilities and improves the performance of existing mathematical models and will be very useful for modeling carcinogenic processes characteristic of cancers. To better understand the biological plausibility behind the aforementioned model parameters, detailed molecular, cellular, and tissue-specific mechanisms underlying the development of each type of cancer require further investigation. The model parameters that can be assessed by the proposed approach will complement and challenge future biomedical and epidemiological studies

Extension of Cox Proportional Hazard Model for Estimation of Interrelated Age-Period-Cohort Effects on Cancer Survival

In the frame of the Cox proportional hazard (PH) model, a novel two-step procedure for estimating age-period-cohort (APC) effects on the hazard function of death from cancer was developed. In the first step, the procedure estimates the influence of joint APC effects on the hazard function, using Cox PH regression procedures from a standard software package. In the second step, the coefficients for age at diagnosis, time period and birth cohort effects are estimated. To solve the identifiability problem that arises in estimating these coefficients, an assumption that neighboring birth cohorts almost equally affect the hazard function was utilized. Using an anchoring technique, simple procedures for obtaining estimates of interrelated age at diagnosis, time period and birth cohort effect coefficients were developed

PCCR: Pancreatic Cancer Collaborative Registry

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

Multicenter Breast Cancer Collaborative Registry

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 role of the SEA (sea urchin sperm protein, enterokinase and agrin) module in cleavage of membrane-tethered mucins

The membrane-tethered mucins are cell surface-associated dimeric or multimeric molecules with extracellular, transmembrane and cytoplasmic portions, that arise from cleavage of the primary polypeptide chain. Following the first cleavage, which may be cotranslational, the subunits remain closely associated through undefined noncovalent interactions. These mucins all share a common structural motif, the SEA module that is found in many other membrane-associated proteins that are released from the cell surface and has been implicated in both the cleavage events and association of the subunits. Here we examine the SEA modules of three membrane-tethered mucins, MUC1, MUC3 and MUC12, which have significant sequence homology within the SEA domain. We previously identified the primary cleavage site within the MUC1 SEA domain as FRPG/SVVV a sequence that is highly conserved in MUC3 and MUC12. We now show by site-directed mutagenesis that the F, G and S residues are important for the efficiency of the cleavage reaction but not indispensable and that amino acids outside this motif are probably important. These data are consistent with a new model of the MUC1 SEA domain that is based on the solution structure of the MUC16 SEA module, derived by NMR spectroscopy. Further, we demonstrate that cleavage of human MUC3 and MUC12 occurs within the SEA domain. However, the SEA domains of MUC1, MUC3 and MUC12 are not interchangeable, suggesting that either these modules alone are insufficient to mediate efficient cleavage or that the 3D structure of the hybrid molecules does not adequately re-create an accessible cleavage site