Lisa A. Cannon-Albright

Bio: Lisa A. Cannon-Albright is an academic researcher from University of Utah. The author has contributed to research in topics: Population & Cancer. The author has an hindex of 62, co-authored 327 publications receiving 28945 citations. Previous affiliations of Lisa A. Cannon-Albright include University of Koblenz and Landau & United States Department of Veterans Affairs.

A strong candidate for the breast and ovarian cancer susceptibility gene BRCA1

Abstract: A strong candidate for the 17q-linked BRCA1 gene, which influences susceptibility to breast and ovarian cancer, has been identified by positional cloning methods. Probable predisposing mutations have been detected in five of eight kindreds presumed to segregate BRCA1 susceptibility alleles. The mutations include an 11-base pair deletion, a 1-base pair insertion, a stop codon, a missense substitution, and an inferred regulatory mutation. The BRCA1 gene is expressed in numerous tissues, including breast and ovary, and encodes a predicted protein of 1863 amino acids. This protein contains a zinc finger domain in its amino-terminal region, but is otherwise unrelated to previously described proteins. Identification of BRCA1 should facilitate early diagnosis of breast and ovarian cancer susceptibility in some individuals as well as a better understanding of breast cancer biology.

Genetic Heterogeneity and Penetrance Analysis of the BRCA1 and BRCA2 Genes in Breast Cancer Families

Abstract: The contribution of BRCA1 and BRCA2 to inherited breast cancer was assessed by linkage and mutation analysis in 237 families, each with at least four cases of breast cancer, collected by the Breast Cancer Linkage Consortium. Families were included without regard to the occurrence of ovarian or other cancers. Overall, disease was linked to BRCA1 in an estimated 52% of families, to BRCA2 in 32% of families, and to neither gene in 16% (95% confidence interval [CI] 6%-28%), suggesting other predisposition genes. The majority (81%) of the breast-ovarian cancer families were due to BRCA1, with most others (14%) due to BRCA2. Conversely, the majority of families with male and female breast cancer were due to BRCA2 (76%). The largest proportion (67%) of families due to other genes was found in families with four or five cases of female breast cancer only. These estimates were not substantially affected either by changing the assumed penetrance model for BRCA1 or by including or excluding BRCA1 mutation data. Among those families with disease due to BRCA1 that were tested by one of the standard screening methods, mutations were detected in the coding sequence or splice sites in an estimated 63% (95% CI 51%-77%). The estimated sensitivity was identical for direct sequencing and other techniques. The penetrance of BRCA2 was estimated by maximizing the LOD score in BRCA2-mutation families, over all possible penetrance functions. The estimated cumulative risk of breast cancer reached 28% (95% CI 9%-44%) by age 50 years and 84% (95% CI 43%-95%) by age 70 years. The corresponding ovarian cancer risks were 0.4% (95% CI 0%-1%) by age 50 years and 27% (95% CI 0%-47%) by age 70 years. The lifetime risk of breast cancer appears similar to the risk in BRCA1 carriers, but there was some suggestion of a lower risk in BRCA2 carriers <50 years of age.

Localization of a breast cancer susceptibility gene, BRCA2, to chromosome 13q12-13

Abstract: A small proportion of breast cancer, in particular those cases arising at a young age, is due to the inheritance of dominant susceptibility genes conferring a high risk of the disease. A genomic linkage search was performed with 15 high-risk breast cancer families that were unlinked to the BRCA1 locus on chromosome 17q21. This analysis localized a second breast cancer susceptibility locus, BRCA2, to a 6-centimorgan interval on chromosome 13q12-13. Preliminary evidence suggests that BRCA2 confers a high risk of breast cancer but, unlike BRCA1, does not confer a substantially elevated risk of ovarian cancer.

REVEL: An Ensemble Method for Predicting the Pathogenicity of Rare Missense Variants

Abstract: The vast majority of coding variants are rare, and assessment of the contribution of rare variants to complex traits is hampered by low statistical power and limited functional data. Improved methods for predicting the pathogenicity of rare coding variants are needed to facilitate the discovery of disease variants from exome sequencing studies. We developed REVEL (rare exome variant ensemble learner), an ensemble method for predicting the pathogenicity of missense variants on the basis of individual tools: MutPred, FATHMM, VEST, PolyPhen, SIFT, PROVEAN, MutationAssessor, MutationTaster, LRT, GERP, SiPhy, phyloP, and phastCons. REVEL was trained with recently discovered pathogenic and rare neutral missense variants, excluding those previously used to train its constituent tools. When applied to two independent test sets, REVEL had the best overall performance (p −12 ) as compared to any individual tool and seven ensemble methods: MetaSVM, MetaLR, KGGSeq, Condel, CADD, DANN, and Eigen. Importantly, REVEL also had the best performance for distinguishing pathogenic from rare neutral variants with allele frequencies

Systematic population-based assessment of cancer risk in first-degree relatives of cancer probands.

Abstract: BACKGROUND Cancer has long been recognized to have a familial component. Elevated risks for cancers at the same site for relatives of cancer probands have been reported for both common cancers and a number of the rarer cancer sites. For a particular cancer site, however, the estimated risks to relatives have varied considerably depending on criteria for selection of probands, how cancers were determined in relatives, and overall study design. Not surprisingly, the estimated risks of other cancers in relatives of probands with cancer at a given site have been subject to even more variation. PURPOSE The aim of this study was to use the Utah Population Database resource to systematically study familial clustering of 28 distinct cancer site definitions among first-degree relatives (parents, siblings, and off-spring) of cancer probands. METHODS We estimated familial relative risks from the Utah Population Database by identifying all cases of cancer in these first-degree relatives. These observed values were compared with those expected based on cohort-specific internal rates calculated from 399,786 relatives of all individuals in the Utah Population Database known to have died in Utah. RESULTS All sites showed an excess of cancers of the same site among relatives, with thyroid and colon cancers and lymphocytic leukemia showing the highest familial risks. When the analyses were restricted to cases with early ages at diagnosis, increased familial components for most cancer sites became evident. A significant difference in familial relative risk (FRR) between male (FRR = 4.04; 95% confidence interval [CI] = 3.13-5.07) and female (FRR = 2.24; 95% CI = 1.54-3.08) probands was found for colon cancer. Highly significant familial associations (one-sided; P < .001) were found among breast, colon, and prostate cancers and between breast and thyroid cancers. Statistically significant (one-sided, P < .01) associations were also found between tobacco-associated sites (lung, larynx, lip, and cervix). CONCLUSIONS This study represents a unique comprehensive population-based study of familial cancer. The familial associations reported here will be useful in generating hypotheses about specific genetic and environmental factors that can be tested in genetic linkage and case-control studies.

Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.

Abstract: The BLAST programs are widely used tools for searching protein and DNA databases for sequence similarities. For protein comparisons, a variety of definitional, algorithmic and statistical refinements described here permits the execution time of the BLAST programs to be decreased substantially while enhancing their sensitivity to weak similarities. A new criterion for triggering the extension of word hits, combined with a new heuristic for generating gapped alignments, yields a gapped BLAST program that runs at approximately three times the speed of the original. In addition, a method is introduced for automatically combining statistically significant alignments produced by BLAST into a position-specific score matrix, and searching the database using this matrix. The resulting Position-Specific Iterated BLAST (PSIBLAST) program runs at approximately the same speed per iteration as gapped BLAST, but in many cases is much more sensitive to weak but biologically relevant sequence similarities. PSI-BLAST is used to uncover several new and interesting members of the BRCT superfamily.

WHO Classification of Tumours of Haematopoietic and Lymphoid Tissues

Abstract: WHO CLASSIFICATION OF TUMOURS OF HAEMATOPOIETIC AND LYMPHOID TISSUES , WHO CLASSIFICATION OF TUMOURS OF HAEMATOPOIETIC AND LYMPHOID TISSUES , کتابخانه مرکزی دانشگاه علوم پزشکی تهران

Finding the missing heritability of complex diseases

Abstract: Genome-wide association studies have identified hundreds of genetic variants associated with complex human diseases and traits, and have provided valuable insights into their genetic architecture. Most variants identified so far confer relatively small increments in risk, and explain only a small proportion of familial clustering, leading many to question how the remaining, 'missing' heritability can be explained. Here we examine potential sources of missing heritability and propose research strategies, including and extending beyond current genome-wide association approaches, to illuminate the genetics of complex diseases and enhance its potential to enable effective disease prevention or treatment.

A strong candidate for the breast and ovarian cancer susceptibility gene BRCA1

Abstract: A strong candidate for the 17q-linked BRCA1 gene, which influences susceptibility to breast and ovarian cancer, has been identified by positional cloning methods. Probable predisposing mutations have been detected in five of eight kindreds presumed to segregate BRCA1 susceptibility alleles. The mutations include an 11-base pair deletion, a 1-base pair insertion, a stop codon, a missense substitution, and an inferred regulatory mutation. The BRCA1 gene is expressed in numerous tissues, including breast and ovary, and encodes a predicted protein of 1863 amino acids. This protein contains a zinc finger domain in its amino-terminal region, but is otherwise unrelated to previously described proteins. Identification of BRCA1 should facilitate early diagnosis of breast and ovarian cancer susceptibility in some individuals as well as a better understanding of breast cancer biology.