Risk of colon cancer in hereditary non-polyposis colorectal cancer patients as predicted by fuzzy modeling: Influence of smoking

AIM: To investigate whether a fuzzy logic model could predict colorectal cancer (CRC) risk engendered by smoking in hereditary non-polyposis colorectal cancer (HNPCC) patients. METHODS: Three hundred and forty HNPCC mismatch repair (MMR) mutation carriers from the Creighton University Hereditary Cancer Institute Registry were selected for modeling. Age-dependent curves were generated to elucidate the joint effects between gene mutation (hMLH1 or hMSH2), gender, and smoking status on the probability of developing CRC. RESULTS: Smoking significantly increased CRC risk in male hMSH2 mutation carriers (P \u3c 0.05). hMLH1 mutations augmented CRC risk relative to hMSH2 mutation carriers for males (P \u3c 0.05). Males had a significantly higher risk of CRC than females for hMLH1 non smokers (P \u3c 0.05), hMLH1 smokers (P \u3c 0.1) and hMSH2 smokers (P \u3c 0.1). Smoking promoted CRC in a dose-dependent manner in hMSH2 in males (P \u3c 0.05). Females with hMSH2 mutations and both sexes with the hMLH1 groups only demonstrated a smoking effect after an extensive smoking history (P \u3c 0.05). CONCLUSION: CRC promotion by smoking in HNPCC patients is dependent on gene mutation, gender and age. These data demonstrate that fuzzy modeling may enable formulation of clinical risk scores, thereby allowing individualization of CRC prevention strategies

Nonparametric versus Parametric Statistical Approaches for Genetic Anticipation: The Pancreatic Cancer Case

2000 Mathematics Subject Classi cation: 62N01, 62N05, 62P10, 92D10, 92D30.Genetic anticipation for a particular disease can involve an earlier age of onset, greater severity, and/or a higher number of affected individuals in successive generations within a family. Comparison between nonparametric and semiparametric tests is studied for matched data, and is one of the main focuses of this study. This comparison is investigated for the variable age of diagnosis among different birth cohorts, before and after adjustment for time under observation. The comparison is illustrated on an example of familial pancreatic cancer, which example is the second main focus of this study. The nonparametric test performed on our example better than the two semi-parametric tests, and was less sensitive to right censoring. After adjusting for follow up time, all methods detected genetic anticipation.This work was supported in part by a grant from the National Cancer Institute (1 R33 CA10595-01A2) to S. A. Sherman. G. R. Haynatzki thanks Mr. Oleg Shats and Mrs. Marsha Ketcham for their help with the PCCR

Immune microenvironment profiling of normal appearing colorectal mucosa biopsied over repeat patient visits reproducibly separates lynch syndrome patients based on their history of colon cancer

IntroductionLynch syndrome (LS) is the most common hereditary cause of colorectal cancer (CRC), increasing lifetime risk of CRC by up to 70%. Despite this higher lifetime risk, disease penetrance in LS patients is highly variable and most LS patients undergoing CRC surveillance will not develop CRC. Therefore, biomarkers that can correctly and consistently predict CRC risk in LS patients are needed to both optimize LS patient surveillance and help identify better prevention strategies that reduce risk of CRC development in the subset of high-risk LS patients.MethodsNormal-appearing colorectal tissue biopsies were obtained during repeat surveillance colonoscopies of LS patients with and without a history of CRC, healthy controls (HC), and patients with a history of sporadic CRC. Biopsies were cultured in an ex-vivo explant system and their supernatants were assayed via multiplexed ELISA to profile the local immune signaling microenvironment. High quality cytokines were identified using the rxCOV fidelity metric. These cytokines were used to perform elastic-net penalized logistic regression-based biomarker selection by computing a new measure – overall selection probability – that quantifies the ability of each marker to discriminate between patient cohorts being compared.ResultsOur study demonstrated that cytokine based local immune microenvironment profiling was reproducible over repeat visits and sensitive to patient LS-status and CRC history. Furthermore, we identified sets of cytokines whose differential expression was predictive of LS-status in patients when compared to sporadic CRC patients and in identifying those LS patients with or without a history of CRC. Enrichment analysis based on these biomarkers revealed an LS and CRC status dependent constitutive inflammatory state of the normal appearing colonic mucosa.DiscussionThis prospective pilot study demonstrated that immune profiling of normal appearing colonic mucosa discriminates LS patients with a prior history of CRC from those without it, as well as patients with a history of sporadic CRC from HC. Importantly, it suggests the existence of immune signatures specific to LS-status and CRC history. We anticipate that our findings have the potential to assess CRC risk in individuals with LS and help in preemptively mitigating it by optimizing surveillance and identifying candidate prevention targets. Further studies are required to validate our findings in an independent cohort of LS patients over multiple visits

Transcriptional Profiling of Peripheral Blood Mononuclear Cells in Pancreatic Cancer Patients Identifies Novel Genes with Potential Diagnostic Utility

Background: It is well known that many malignancies, including pancreatic cancer (PC), possess the ability to evade the immune system by indirectly downregulating the mononuclear cell machinery necessary to launch an effective immune response. This knowledge, in conjunction with the fact that the trancriptome of peripheral blood mononuclear cells has been shown to be altered in the context of many diseases, including renal cell carcinoma, lead us to study if any such alteration in gene expression exists in PC as it may have diagnostic utility. Methods and Findings: PBMC samples from 26 PC patients and 33 matched healthy controls were analyzed by whole genome cDNA microarray. Three hundred eighty-three genes were found to be significantly different between PC and healthy controls, with 65 having at least a 1.5 fold change in expression. Pathway analysis revealed that many of these genes fell into pathways responsible for hematopoietic differentiation, cytokine signaling, and natural killer (NK) cell and CD8+ T-cell cytotoxic response. Unsupervised hierarchical clustering analysis identified an eight-gene predictor set, consisting of SSBP2, Ube2b-rs1, CA5B, F5, TBC1D8, ANXA3, ARG1, and ADAMTS20, that could distinguish PC patients from healthy controls with an accuracy of 79% in a blinded subset of samples from treatment naïve patients, giving a sensitivity of 83% and a specificity of 75%. Conclusions: In summary, we report the first in-depth comparison of global gene expression profiles of PBMCs between PC patients and healthy controls. We have also identified a gene predictor set that can potentially be developed further for use in diagnostic algorithms in PC. Future directions of this research should include analysis of PBMC expression profiles in patients with chronic pancreatitis as well as increasing the number of early-stage patients to assess the utility of PBMCs in the early diagnosis of PC. © 2011 Baine et al

The 5S ribosomal RNA gene clusters in Tetrahymena thermophila : strain differences, chromosomal localization, and loss during micronuclear ageing

The organization of the 5S genes in the genome of Tetrahymena thermophila was examined in various strains, with germinal ageing, and the 5S gene clusters were mapped to the MIC chromosomes. When MIC or MAC DNA is cut with the restriction enzyme Eco RI, electrophoresed, blotted, and probed with a 5S rDNA probe, the banding patterns represent the clusters of the 5S rRNA genes as well as flanking regions. The use of long gels and 60 h of electrophoresis at 10 mA permitted resolution of some 30–35 5S gene clusters on fragments ranging in size from 30-2 kb (bottom of gel). The majority of the 5S gene clusters were found in both MIC and MAC genomes, a few being MIC limited and a few MAC limited. The relative copy number of 5S genes in each cluster was determined by integrating densitometric tracings made from autoradiograms. The total number of copies in the MAC was found to be 33% greater than in the MIC. When different inbred strains were examined, the majority of the 5S gene clusters were found to be conserved, with a few strain-specific clusters observed. Nine nullisomic strains missing both copies of one or more MIC chromosomes were used to map the 5S gene clusters. The clusters were distributed non-randomly to four of the five MIC chromosomes, with 17 of them localized to chromosome 1. A deletion map of chromosome 1 was constructed using various deletion strains. Some of these deletion strains included B strain clones which had been in continuous culture for 15 years. Losses of 5S gene clusters in these ageing MIC could be attributed to deletions of particular chromosomes. The chromosomal distribution of the 5S gene clusters in Tetrahymena is unlike that found for the well-studied eukaryotes, Drosophila and Xenopus .Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47556/1/438_2004_Article_BF00330970.pd

Prediagnostic serum biomarkers as early detection tools for pancreatic cancer in a large prospective cohort study

Background: The clinical management of pancreatic cancer is severely hampered by the absence of effective screening tools. Methods: Sixty-seven biomarkers were evaluated in prediagnostic sera obtained from cases of pancreatic cancer enrolled in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO). Results: The panel of CA 19-9, OPN, and OPG, identified in a prior retrospective study, was not effective. CA 19-9, CEA, NSE, bHCG, CEACAM1 and PRL were significantly altered in sera obtained from cases greater than 1 year prior to diagnosis. Levels of CA 19-9, CA 125, CEA, PRL, and IL-8 were negatively associated with time to diagnosis. A training/validation study using alternate halves of the PLCO set failed to identify a biomarker panel with significantly improved performance over CA 19-9 alone. When the entire PLCO set was used for training at a specificity (SP) of 95%, a panel of CA 19-9, CEA, and Cyfra 21-1 provided significantly elevated sensitivity (SN) levels of 32.4% and 29.7% in samples collected 1 year prior to diagnosis, respectively, compared to SN levels of 25.7% and 17.2% for CA 19-9 alone. Conclusions: Most biomarkers identified in previously conducted case/control studies are ineffective in prediagnostic samples, however several biomarkers were identified as significantly altered up to 35 months prior to diagnosis. Two newly derived biomarker combinations offered advantage over CA 19-9 alone in terms of SN, particularly in samples collected >1 year prior to diagnosis. However, the efficacy of biomarker-based tools remains limited at present. Several biomarkers demonstrated significant velocity related to time to diagnosis, an observation which may offer considerable potential for enhancements in early detection. © 2014 Nolen et al

Quality of Life in Chronic Pancreatitis is Determined by Constant Pain, Disability/Unemployment, Current Smoking, and Associated Co-Morbidities

OBJECTIVES: Chronic pancreatitis (CP) has a profound independent effect on quality of life (QOL). Our aim was to identify factors that impact the QOL in CP patients. METHODS: We used data on 1,024 CP patients enrolled in the three NAPS2 studies. Information on demographics, risk factors, co-morbidities, disease phenotype, and treatments was obtained from responses to structured questionnaires. Physical and mental component summary (PCS and MCS, respectively) scores generated using responses to the Short Form-12 (SF-12) survey were used to assess QOL at enrollment. Multivariable linear regression models determined independent predictors of QOL. RESULTS: Mean PCS and MCS scores were 36.7+/-11.7 and 42.4+/-12.2, respectively. Significant (P \u3c 0.05) negative impact on PCS scores in multivariable analyses was noted owing to constant mild-moderate pain with episodes of severe pain or constant severe pain (10 points), constant mild-moderate pain (5.2), pain-related disability/unemployment (5.1), current smoking (2.9 points), and medical co-morbidities. Significant (P \u3c 0.05) negative impact on MCS scores was related to constant pain irrespective of severity (6.8-6.9 points), current smoking (3.9 points), and pain-related disability/unemployment (2.4 points). In women, disability/unemployment resulted in an additional 3.7 point reduction in MCS score. Final multivariable models explained 27% and 18% of the variance in PCS and MCS scores, respectively. Etiology, disease duration, pancreatic morphology, diabetes, exocrine insufficiency, and prior endotherapy/pancreatic surgery had no significant independent effect on QOL. CONCLUSIONS: Constant pain, pain-related disability/unemployment, current smoking, and concurrent co-morbidities significantly affect the QOL in CP. Further research is needed to identify factors impacting QOL not explained by our analyses

Directive 02-14: Tax Obligations of Persons Purchasing Cigarettes in Interstate Commerce for which the Massachusetts Cigarette Excise Has Not Been Paid

The development of accurate clinical biomarkers has been challenging in part due to the diversity between patients and diseases. One approach to account for the diversity is to use multiple markers to classify patients, based on the concept that each individual marker contributes information from its respective subclass of patients. Here we present a new strategy for developing biomarker panels that accounts for completely distinct patient subclasses. Marker State Space (MSS) defines "marker states" based on all possible patterns of high and low values among a panel of markers. Each marker state is defined as either a case state or a control state, and a sample is classified as case or control based on the state it occupies. MSS was used to define multi-marker panels that were robust in cross validation and training-set/test-set analyses and that yielded similar classification accuracy to several other classification algorithms. A three-marker panel for discriminating pancreatic cancer patients from control subjects revealed subclasses of patients based on distinct marker states. MSS provides a straightforward approach for modeling highly divergent subclasses of patients, which may be adaptable for diverse applications.</p

Mechanisms of CFTR Functional Variants That Impair Regulated Bicarbonate Permeation and Increase Risk for Pancreatitis but Not for Cystic Fibrosis

CFTR is a dynamically regulated anion channel. Intracellular WNK1-SPAK activation causes CFTR to change permeability and conductance characteristics from a chloride-preferring to bicarbonate-preferring channel through unknown mechanisms. Two severe CFTR mutations (CFTRsev) cause complete loss of CFTR function and result in cystic fibrosis (CF), a severe genetic disorder affecting sweat glands, nasal sinuses, lungs, pancreas, liver, intestines, and male reproductive system. We hypothesize that those CFTR mutations that disrupt the WNK1-SPAK activation mechanisms cause a selective, bicarbonate defect in channel function (CFTRBD) affecting organs that utilize CFTR for bicarbonate secretion (e.g. the pancreas, nasal sinus, vas deferens) but do not cause typical CF. To understand the structural and functional requirements of the CFTR bicarbonate-preferring channel, we (a) screened 984 well-phenotyped pancreatitis cases for candidate CFTRBD mutations from among 81 previously described CFTR variants; (b) conducted electrophysiology studies on clones of variants found in pancreatitis but not CF; (c) computationally constructed a new, complete structural model of CFTR for molecular dynamics simulation of wild-type and mutant variants; and (d) tested the newly defined CFTRBD variants for disease in non-pancreas organs utilizing CFTR for bicarbonate secretion. Nine variants (CFTR R74Q, R75Q, R117H, R170H, L967S, L997F, D1152H, S1235R, and D1270N) not associated with typical CF were associated with pancreatitis (OR 1.5, p = 0.002). Clones expressed in HEK 293T cells had normal chloride but not bicarbonate permeability and conductance with WNK1-SPAK activation. Molecular dynamics simulations suggest physical restriction of the CFTR channel and altered dynamic channel regulation. Comparing pancreatitis patients and controls, CFTRBD increased risk for rhinosinusitis (OR 2.3, p<0.005) and male infertility (OR 395, p<<0.0001). WNK1-SPAK pathway-activated increases in CFTR bicarbonate permeability are altered by CFTRBD variants through multiple mechanisms. CFTRBD variants are associated with clinically significant disorders of the pancreas, sinuses, and male reproductive system.Fil: LaRusch, Jessica. Univeristy of Pittsburgh. School of Medicine; Estados UnidosFil: Jung, Jinsei. Yonsei University College of Medicine; Corea del SurFil: General, Ignacio. University of Pittsburgh; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Lewis, Michele D.. Mayo Clinic. Division of Gastroenterology and Hepatology; Estados UnidosFil: Park, Hyun Woo. Yonsei University College of Medicine; Corea del SurFil: Brand, Randall E.. Univeristy of Pittsburgh. School of Medicine; Estados UnidosFil: Gelrud, Andres. Univeristy of Pittsburgh. School of Medicine; Estados UnidosFil: Anderson, Michelle A.. University of Michigan; Estados UnidosFil: Banks, Peter A.. Brigham and Women’s Hospital. Division of Gastroenterology; Estados UnidosFil: Conwell, Darwin. Brigham and Women’s Hospital. Division of Gastroenterology; Estados UnidosFil: Lawrence, Christopher. Medical University of South Carolina; Estados UnidosFil: Romagnuolo, Joseph. Medical University of South Carolina; Estados UnidosFil: Baillie, John. University of Duke; Estados UnidosFil: Alkaade, Samer. St. Louis University. School of Medicine; Estados UnidosFil: Cote, Gregory. Indiana University; Estados UnidosFil: Gardner, Timothy B.. Dartmouth-Hitchcock Medical Center; Estados UnidosFil: Amann, Stephen T.. North Mississippi Medical Center; Estados UnidosFil: Slivka, Adam. Univeristy of Pittsburgh. School of Medicine; Estados UnidosFil: Sandhu, Bimaljit. Virginia Commonwealth University Medical Center; Estados UnidosFil: Aloe, Amy. Univeristy of Pittsburgh. School of Medicine; Estados UnidosFil: Kienholz, Michelle L.. Univeristy of Pittsburgh. School of Medicine; Estados UnidosFil: Yadav, Dhiraj. Univeristy of Pittsburgh. School of Medicine; Estados UnidosFil: Barmada, M. Michael. Univeristy of Pittsburgh. School of Medicine; Estados UnidosFil: Bahar, Ivet. Univeristy of Pittsburgh. School of Medicine; Estados UnidosFil: Lee, Min Goo. Yonsei University College of Medicine; Corea del SurFil: Whitcomb, David C.. Univeristy of Pittsburgh. School of Medicine; Estados UnidosFil: North American Pancreatitis Study Group. No especifica