Computational and bioinformatics frameworks for next-generation whole exome and genome sequencing.

It has become increasingly apparent that one of the major hurdles in the genomic age will be the bioinformatics challenges of next-generation sequencing. We provide an overview of a general framework of bioinformatics analysis. For each of the three stages of (1) alignment, (2) variant calling, and (3) filtering and annotation, we describe the analysis required and survey the different software packages that are used. Furthermore, we discuss possible future developments as data sources grow and highlight opportunities for new bioinformatics tools to be developed.

Personalizing rare disease research: how genomics is revolutionizing the diagnosis and treatment of rare disease.

A decade after the complete sequencing of the human genome, combined with recent advances in throughput and sequencing costs, the genetics of rare diseases has entered a new era. There has now been an explosion in the identification and mapping of rare diseases, with over 10,000 exomes having been sequenced to date. This article surveys the progress and development of technologies to understand rare disease; it provides a historical overview of traditional techniques such as karyotyping and homozygosity mapping, reviews current methods of whole-exome and -genome sequencing, and provides a future perspective on upcoming developments such as targeted drugs and gene therapy. This article will discuss the implications of these methods for rare disease research, along with a discussion of the success stories that provide great hope and optimism for patients and scientists alike.

The genetic landscape of the childhood cancer medulloblastoma.

Medulloblastoma (MB) is the most common malignant brain tumor of children. To identify the genetic alterations in this tumor type, we searched for copy number alterations using high-density microarrays and sequenced all known protein-coding genes and microRNA genes using Sanger sequencing in a set of 22 MBs. We found that, on average, each tumor had 11 gene alterations, fewer by a factor of 5 to 10 than in the adult solid tumors that have been sequenced to date. In addition to alterations in the Hedgehog and Wnt pathways, our analysis led to the discovery of genes not previously known to be altered in MBs. Most notably, inactivating mutations of the histone-lysine N-methyltransferase genes MLL2 or MLL3 were identified in 16% of MB patients. These results demonstrate key differences between the genetic landscapes of adult and childhood cancers, highlight dysregulation of developmental pathways as an important mechanism underlying MBs, and identify a role for a specific type of histone methylation in human tumorigenesis.

Protein microarrays for cancer diagnostics and therapy.

In this postgenomic age, cancer will be understood in intricate detail beyond the genomic level. New technologies are emerging that allow global proteomic level characterization, profiling and understanding. One of the most exciting emerging technologies of cancer proteomics is protein microarray. In this review, the different types of protein microarrays are discussed, including the methods, challenges and techniques of each type. Subsequently, the application of these specific methods to cancer diagnosis, prognosis and therapy will be overviewed, providing a general review of current methods, and proposing how protein arrays will help shape the future of oncoproteomics.

SMAD4 gene mutations are associated with poor prognosis in pancreatic cancer.

PURPOSE: Recently, the majority of protein coding genes were sequenced in a collection of pancreatic cancers, providing an unprecedented opportunity to identify genetic markers of prognosis for patients with adenocarcinoma of the pancreas. EXPERIMENTAL DESIGN: We previously sequenced more than 750 million base pairs of DNA from 23,219 transcripts in a series of 24 adenocarcinomas of the pancreas. In addition, 39 genes that were mutated in more than one of these 24 cancers were sequenced in a separate panel of 90 well-characterized adenocarcinomas of the pancreas. Of these 114 patients, 89 underwent pancreaticoduodenectomy, and the somatic mutations in these cancers were correlated with patient outcome. RESULTS: When adjusted for age, lymph node status, margin status, and tumor size, SMAD4 gene inactivation was significantly associated with shorter overall survival (hazard ratio, 1.92; 95% confidence interval, 1.20-3.05; P = 0.006). Patients with SMAD4 gene inactivation survived a median of 11.5 months, compared with 14.2 months for patients without SMAD4 inactivation. By contrast, mutations in CDKN2A or TP53 or the presence of multiple (> or =4) mutations or homozygous deletions among the 39 most frequently mutated genes were not associated with survival. CONCLUSIONS: SMAD4 gene inactivation is associated with poorer prognosis in patients with surgically resected adenocarcinoma of the pancreas.

Identification of microbial DNA in human cancer.

BACKGROUND: Microorganisms have been associated with many types of human diseases; however, a significant number of clinically important microbial pathogens remain to be discovered. METHODS: We have developed a genome-wide approach, called Digital Karyotyping Microbe Identification (DK-MICROBE), to identify genomic DNA of bacteria and viruses in human disease tissues. This method involves the generation of an experimental DNA tag library through Digital Karyotyping (DK) followed by analysis of the tag sequences for the presence of microbial DNA content using a compiled microbial DNA virtual tag library. RESULTS: To validate this technology and to identify pathogens that may be associated with human cancer pathogenesis, we used DK-MICROBE to determine the presence of microbial DNA in 58 human tumor samples, including brain, ovarian, and colorectal cancers. We detected DNA from Human herpesvirus 6 (HHV-6) in a DK library of a colorectal cancer liver metastasis and in normal tissue from the same patient. CONCLUSION: DK-MICROBE can identify previously unknown infectious agents in human tumors, and is now available for further applications for the identification of pathogen DNA in human cancer and other diseases.

Genetic mutations associated with cigarette smoking in pancreatic cancer.

Cigarette smoking doubles the risk of pancreatic cancer, and smoking accounts for 20% to 25% of pancreatic cancers. The recent sequencing of the pancreatic cancer genome provides an unprecedented opportunity to identify mutational patterns associated with smoking. We previously sequenced >750 million bp DNA from 23,219 transcripts in 24 adenocarcinomas of the pancreas (discovery screen). In this previous study, the 39 genes that were mutated more than once in the discovery screen were sequenced in an additional 90 adenocarcinomas of the pancreas (validation screen). Here, we compared the somatic mutations in the cancers obtained from individuals who ever smoked cigarettes (n = 64) to the somatic mutations in the cancers obtained from individuals who never smoked cigarettes (n = 50). When adjusted for age and gender, analyses of the discovery screen revealed significantly more nonsynonymous mutations in the carcinomas obtained from ever smokers (mean, 53.1 mutations per tumor; SD, 27.9) than in the carcinomas obtained from never smokers (mean, 38.5; SD, 11.1; P = 0.04). The difference between smokers and nonsmokers was not driven by mutations in known driver genes in pancreatic cancer (KRAS, TP53, CDKN2A/p16, and SMAD4), but instead was predominantly observed in genes mutated at lower frequency. No differences were observed in mutations in carcinomas from the head versus tail of the gland. Pancreatic carcinomas from cigarette smokers harbor more mutations than do carcinomas from never smokers. The types and patterns of these mutations provide insight into the mechanisms by which cigarette smoking causes pancreatic cancer.

Exomic sequencing identifies PALB2 as a pancreatic cancer susceptibility gene.

Through complete sequencing of the protein-coding genes in a patient with familial pancreatic cancer, we identified a germline, truncating mutation in PALB2 that appeared responsible for this patient's predisposition to the disease. Analysis of 96 additional patients with familial pancreatic cancer revealed three distinct protein-truncating mutations, thereby validating the role of PALB2 as a susceptibility gene for pancreatic cancer. PALB2 mutations have been previously reported in patients with familial breast cancer, and the PALB2 protein is a binding partner for BRCA2. These results illustrate that complete, unbiased sequencing of protein-coding genes can lead to the identification of a gene responsible for a hereditary disease.

An integrated genomic analysis of human glioblastoma multiforme.

Glioblastoma multiforme (GBM) is the most common and lethal type of brain cancer. To identify the genetic alterations in GBMs, we sequenced 20,661 protein coding genes, determined the presence of amplifications and deletions using high-density oligonucleotide arrays, and performed gene expression analyses using next-generation sequencing technologies in 22 human tumor samples. This comprehensive analysis led to the discovery of a variety of genes that were not known to be altered in GBMs. Most notably, we found recurrent mutations in the active site of isocitrate dehydrogenase 1 (IDH1) in 12% of GBM patients. Mutations in IDH1 occurred in a large fraction of young patients and in most patients with secondary GBMs and were associated with an increase in overall survival. These studies demonstrate the value of unbiased genomic analyses in the characterization of human brain cancer and identify a potentially useful genetic alteration for the classification and targeted therapy of GBMs.

Core signaling pathways in human pancreatic cancers revealed by global genomic analyses.

There are currently few therapeutic options for patients with pancreatic cancer, and new insights into the pathogenesis of this lethal disease are urgently needed. Toward this end, we performed a comprehensive genetic analysis of 24 pancreatic cancers. We first determined the sequences of 23,219 transcripts, representing 20,661 protein-coding genes, in these samples. Then, we searched for homozygous deletions and amplifications in the tumor DNA by using microarrays containing probes for approximately 10(6) single-nucleotide polymorphisms. We found that pancreatic cancers contain an average of 63 genetic alterations, the majority of which are point mutations. These alterations defined a core set of 12 cellular signaling pathways and processes that were each genetically altered in 67 to 100% of the tumors. Analysis of these tumors' transcriptomes with next-generation sequencing-by-synthesis technologies provided independent evidence for the importance of these pathways and processes. Our data indicate that genetically altered core pathways and regulatory processes only become evident once the coding regions of the genome are analyzed in depth. Dysregulation of these core pathways and processes through mutation can explain the major features of pancreatic tumorigenesis.