Metadata Correction: Engaging a Community for Rare Genetic Disease: Best Practices and Education From Individual Crowdfunding Campaigns.

[This corrects the article DOI: 10.2196/ijmr.7176.

Engaging a Community for Rare Genetic Disease: Best Practices and Education From Individual Crowdfunding Campaigns.

Background: Genetic sequencing is critically important to diagnostic health care efforts in the United States today, yet it is still inaccessible to many. Meanwhile, the internet and social networking have made crowdfunding a realistic avenue for individuals and groups hoping to fund medical and research causes, including patients in need of whole exome genetic sequencing (WES).

Objective: Amplify Hope is an educational program designed to investigate what factors affect the success of medical crowdfunding campaigns.

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.

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.

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.

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.

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.

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.

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).

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.

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.

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.