CancerGenes: a gene selection resource for cancer genome projects

The genome sequence framework provided by the human genome project allows us to precisely map human genetic variations in order to study their association with disease and their direct effects on gene function. Since the description of tumor suppressor genes and oncogenes several decades ago, both germ-line variations and somatic mutations have been established to be important in cancer—in terms of risk, oncogenesis, prognosis and response to therapy. The Cancer Genome Atlas initiative proposed by the NIH is poised to elucidate the contribution of somatic mutations to cancer development and progression through the re-sequencing of a substantial fraction of the total collection of human genes—in hundreds of individual tumors and spanning several tumor types. We have developed the CancerGenes resource to simplify the process of gene selection and prioritization in large collaborative projects. CancerGenes combines gene lists annotated by experts with information from key public databases. Each gene is annotated with gene name(s), functional description, organism, chromosome number, location, Entrez Gene ID, GO terms, InterPro descriptions, gene structure, protein length, transcript count, and experimentally determined transcript control regions, as well as links to Entrez Gene, COSMIC, and iHOP gene pages and the UCSC and Ensembl genome browsers. The user-friendly interface provides for searching, sorting and intersection of gene lists. Users may view tabulated results through a web browser or may dynamically download them as a spreadsheet table. CancerGenes is available at

NCBI GEO: mining millions of expression profiles—database and tools

The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) is the largest fully public repository for high-throughput molecular abundance data, primarily gene expression data. The database has a flexible and open design that allows the submission, storage and retrieval of many data types. These data include microarray-based experiments measuring the abundance of mRNA, genomic DNA and protein molecules, as well as non-array-based technologies such as serial analysis of gene expression (SAGE) and mass spectrometry proteomic technology. GEO currently holds over 30 000 submissions representing approximately half a billion individual molecular abundance measurements, for over 100 organisms. Here, we describe recent database developments that facilitate effective mining and visualization of these data. Features are provided to examine data from both experiment- and gene-centric perspectives using user-friendly Web-based interfaces accessible to those without computational or microarray-related analytical expertise. The GEO database is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo

Phase II Study of a Non-Platinum–Containing Doublet of Paclitaxel and Pemetrexed with Bevacizumab as Initial Therapy for Patients with Advanced Lung Adenocarcinomas

Many patients with lung cancers cannot receive platinum-containing regimens due to co-morbid medical conditions. We designed the PPB regimen of paclitaxel, pemetrexed, and bevacizumab to maintain or improve outcomes while averting the unique toxicities of platinum-based chemotherapies

Conversion of Urine Protein-Creatinine Ratio or Urine Dipstick Protein to Urine Albumin-Creatinine Ratio for Use in Chronic Kidney Disease Screening and Prognosis : An Individual Participant–Based Meta-analysis

Financial Support: The CKD-PC Data Coordinating Center is funded in part by a program grant from the U.S. National Kidney Foundation and the National Institute of Diabetes and Digestive and Kidney Diseases (R01DK100446). Various sources have supported enrollment and data collection, including laboratory measurements and follow-up, in the collaborating cohorts of the CKD-PC. These funding sources include government agencies, such as national institutes of health and medical research councils, as well as the foundations and industry sponsors listed in Supplemental Appendix 3 (available at Annals.org).Peer reviewedPostprin

Mutational Analysis of EGFR and Related Signaling Pathway Genes in Lung Adenocarcinomas Identifies a Novel Somatic Kinase Domain Mutation in FGFR4

BACKGROUND: Fifty percent of lung adenocarcinomas harbor somatic mutations in six genes that encode proteins in the EGFR signaling pathway, i.e., EGFR, HER2/ERBB2, HER4/ERBB4, PIK3CA, BRAF, and KRAS. We performed mutational profiling of a large cohort of lung adenocarcinomas to uncover other potential somatic mutations in genes of this signaling pathway that could contribute to lung tumorigenesis. METHODOLOGY/PRINCIPAL FINDINGS: We analyzed genomic DNA from a total of 261 resected, clinically annotated non-small cell lung cancer (NSCLC) specimens. The coding sequences of 39 genes were screened for somatic mutations via high-throughput dideoxynucleotide sequencing of PCR-amplified gene products. Mutations were considered to be somatic only if they were found in an independent tumor-derived PCR product but not in matched normal tissue. Sequencing of 9MB of tumor sequence identified 239 putative genetic variants. We further examined 22 variants found in RAS family genes and 135 variants localized to exons encoding the kinase domain of respective proteins. We identified a total of 37 non-synonymous somatic mutations; 36 were found collectively in EGFR, KRAS, BRAF, and PIK3CA. One somatic mutation was a previously unreported mutation in the kinase domain (exon 16) of FGFR4 (Glu681Lys), identified in 1 of 158 tumors. The FGFR4 mutation is analogous to a reported tumor-specific somatic mutation in ERBB2 and is located in the same exon as a previously reported kinase domain mutation in FGFR4 (Pro712Thr) in a lung adenocarcinoma cell line. CONCLUSIONS/SIGNIFICANCE: This study is one of the first comprehensive mutational analyses of major genes in a specific signaling pathway in a sizeable cohort of lung adenocarcinomas. Our results suggest the majority of gain-of-function mutations within kinase genes in the EGFR signaling pathway have already been identified. Our findings also implicate FGFR4 in the pathogenesis of a subset of lung adenocarcinomas

Characterizing the cancer genome in lung adenocarcinoma

Somatic alterations in cellular DNA underlie almost all human cancers(1). The prospect of targeted therapies(2) and the development of high-resolution, genome-wide approaches(3-8) are now spurring systematic efforts to characterize cancer genomes. Here we report a large-scale project to characterize copy-number alterations in primary lung adenocarcinomas. By analysis of a large collection of tumours ( n = 371) using dense single nucleotide polymorphism arrays, we identify a total of 57 significantly recurrent events. We find that 26 of 39 autosomal chromosome arms show consistent large-scale copy-number gain or loss, of which only a handful have been linked to a specific gene. We also identify 31 recurrent focal events, including 24 amplifications and 7 homozygous deletions. Only six of these focal events are currently associated with known mutations in lung carcinomas. The most common event, amplification of chromosome 14q13.3, is found in similar to 12% of samples. On the basis of genomic and functional analyses, we identify NKX2-1 ( NK2 homeobox 1, also called TITF1), which lies in the minimal 14q13.3 amplification interval and encodes a lineage-specific transcription factor, as a novel candidate proto-oncogene involved in a significant fraction of lung adenocarcinomas. More generally, our results indicate that many of the genes that are involved in lung adenocarcinoma remain to be discovered.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62944/1/nature06358.pd

The Somatic Genomic Landscape of Glioblastoma

We describe the landscape of somatic genomic alterations based on multi-dimensional and comprehensive characterization of more than 500 glioblastoma tumors (GBMs). We identify several novel mutated genes as well as complex rearrangements of signature receptors including EGFR and PDGFRA. TERT promoter mutations are shown to correlate with elevated mRNA expression, supporting a role in telomerase reactivation. Correlative analyses confirm that the survival advantage of the proneural subtype is conferred by the G-CIMP phenotype, and MGMT DNA methylation may be a predictive biomarker for treatment response only in classical subtype GBM. Integrative analysis of genomic and proteomic profiles challenges the notion of therapeutic inhibition of a pathway as an alternative to inhibition of the target itself. These data will facilitate the discovery of therapeutic and diagnostic target candidates, the validation of research and clinical observations and the generation of unanticipated hypotheses that can advance our molecular understanding of this lethal cancer