Biomedical subjects

Ian Ellis

Publications and source records attributed to Ian Ellis.

4 recordsLinked to original sources

PubMed2003

BRCA2 germline mutations in familial pancreatic carcinoma.

BACKGROUND: Although as many as 10% of pancreatic cancer cases may have an inherited component, familial pancreatic cancer has not been linked to defects in any specific gene. Some studies have shown that families with germline mutations in the breast cancer susceptibility gene BRCA2 have an increased risk of breast and ovarian cancers, as well as a modestly increased risk of pancreatic cancer. To study these relationships in more detail, we examined whether BRCA2 germline mutations are associated with familial pancreatic cancer. METHODS: We identified 26 European families in which at least two first-degree relatives had a histologically confirmed diagnosis of pancreatic ductal adenocarcinoma. We sequenced genomic DNA isolated from peripheral blood lymphocytes obtained from participating family members to identify germline mutations in BRCA2. RESULTS: Three (12%, exact 95% confidence interval [CI] = 2% to 30%) families carried germline frameshift mutations in the BRCA2 gene that are predicted to result in a truncated BRCA2 protein. Two additional families harbored mutations previously designated as unclassified variants of BRCA2. Thus, 19% (exact 95% CI = 7% to 39%) of the families in our study had either a frameshift mutation or an unclassified variant of BRCA2. None of the families in our study met the criteria for familial breast or ovarian cancer. CONCLUSIONS: Our data support an important role for BRCA2 germline mutations in a subpopulation of families with familial pancreatic cancer. BRCA2 mutation analysis should be included in molecular genetic testing and counseling strategies in families with at least two first-degree relatives affected with ductal adenocarcinoma of the pancreas.

Adult↗

PubMed2003

A prototype methodology combining surface-enhanced laser desorption/ionization protein chip technology and artificial neural network algorithms to predict the chemoresponsiveness of breast cancer cell lines exposed to Paclitaxel and Doxorubicin under in vitro conditions.

An ability to predict the likelihood of cellular response towards particular chemotherapeutic agents based upon protein expression patterns could facilitate the identification of biological molecules with previously undefined roles in the process of chemoresistance/chemosensitivity, and if robust enough these patterns might also be exploited towards the development of novel predictive assays. To ascertain whether proteomic based molecular profiling in conjunction with artificial neural network (ANN) algorithms could be applied towards the specific recognition of phenotypic patterns between either control or drug treated and chemosensitive or chemoresistant cellular populations, a combined approach involving MALDI-TOF matrix-assisted laser desorption/ionization-time of flight mass spectrometry, Ciphergen protein chip technology and ANN algorithms have been applied to specifically identify proteomic 'fingerprints' indicative of treatment regimen for chemosensitive (MCF-7, T47D) and chemoresistant (MCF-7/ADR) breast cancer cell lines following exposure to Doxorubicin or Paclitaxel. The results indicate that proteomic patterns can be identified by ANN algorithms to correctly assign 'class' for treatment regimen (e.g. control/drug treated or chemosensitive/chemoresistant) with a high degree of accuracy using boot-strap statistical validation techniques and that biomarker ion patterns indicative of response/non-response phenotypes are associated with MCF-7 and MCF-7/ADR cells exposed to Doxorubicin. We have also examined the predictive capability of this approach towards MCF-7 and T47D cells to ascertain whether prediction could be made based upon treatment regimen irrespective of cell lineage. Models were identified that could correctly assign class (control or Paclitaxel treatment) for 35/38 samples of an independent dataset. A similar level of predictive capability was also found (> 92%; n = 28) when proteomic patterns derived from the drug resistant cell line MCF-7/ADR were compared against those derived from MCF-7 and T47D as a model system of drug resistant and drug sensitive phenotypes. This approach might offer a potential methodology for predicting the biological behaviour of cancer cells towards particular chemotherapeutics and through protein isolation and sequence identification could result in the identification of biological molecules associated with chemosensitive/chemoresistance tumour phenotypes.

Algorithms↗

PubMed2002

Severity of meningococcal disease in children and the angiotensin-converting enzyme insertion/deletion polymorphism.

Critical illness outcome may be causally related to inflammatory response severity. Given that tissue angiotensin-converting-enzyme (ACE) regulates such responses and that the deletion (D) [rather than insertion (I)] variant of the ACE gene is associated with higher tissue ACE levels, DD genotype might be associated with a poorer outcome in a uniform infectious disease state. Illness severity (Pediatric RIsk of Mortality score, the Glasgow Meningococcal Septicaemia Prognostic Score [GMSPS], and clinical course) was recorded for consecutive white patients with meningococcal disease (n = 110, 34 DD genotype, 61 male, aged 49.4 +/- 5.4 months) referred to the Royal Liverpool Children's Hospital, UK. Compared with children with > or = I allele, DD genotype was associated with 14% higher predicted risk of mortality (p = 0.038), higher GMSPS (DD 9.4 +/- 0.5, ID/II 7.7+/- 0.4 [mean +/- SEM], p = 0.013), greater prevalence of inotropic support (76% versus 55%, p = 0.03) and ventilation (82% versus 63%, p = 0.04), and longer Pediatric Intensive Care Unit (PICU) stay (5.8 versus 3.9, p = 0.02). DD genotype frequency was 6% (1 case) for the 18 children who did not require PICU care, 33% for the 84 PICU survivors, and 45% for those who died (p = 0.01). ACE DD is associated with increased illness severity in meningococcal disease.

Base Sequence↗

PubMed2002

Sacral appendage associated with a mutation in FGFR2.

We report a baby with craniosynostosis and a sacral appendage who has been found to have a Ser351Cys mutation in the fibroblast growth factor receptor 2 gene (FGFR2). This is the first report of sacral appendage associated with a confirmed mutation in one of the FGFR genes, and adds to the spectrum of abnormalities which can be seen in patients with FGFR mutations.

Craniosynostoses↗