Precision Medicine will need to get out of the pharma silo that is based on symptoms


Welcome to the digital era of biology (and to this modest blog I started in early 2005).

To cure many diseases, like cancer or cystic fibrosis, we will need to target genes (mutations, for ex.), not organs! I am convinced that the future of replacement medicine (organ transplant) is genomics (the science of the human genome). In 10 years we will be replacing (modifying) genes; not organs!


Anticipating the $100 genome era and the P4™ medicine revolution. P4 Medicine (Predictive, Personalized, Preventive, & Participatory): Catalyzing a Revolution from Reactive to Proactive Medicine.


After low-cost airlines (Ryanair, Easyjet ...) comes "low-cost" participatory medicine. Some of my readers have recently christened this long-lasting, clumsy attempt at e-writing of mine "THE LOW-COSTE INNOVATION BLOG". I am an
early adopter of scientific MOOCs. My name's Catherine Coste. I've earned myself four MIT digital diplomas: 7.00x, 7.28x1, 7.28.x2 and 7QBWx. Instructor of 7.00x: Eric Lander PhD.

Upcoming books: Doomsdare, a medical thriller (action taking place in Beijing) Fall 2016; Jesus CRISPR Superstar, a sci-fi -- French title: La Passion du CRISPR (2017). Special thanks to Prof. Emmanuel Lincot, lawyer David Kilgour and Isabelle Provost for their help.

I love Genomics. Would you rather donate your data, or... your vital organs?

Audio files on this blog are Windows files ; if you have a Mac, you might want to use VLC (http://www.videolan.org) to read them.

Concernant les fichiers son ou audio (audio files) sur ce blog : ce sont des fichiers Windows ; pour les lire sur Mac, il faut les ouvrir avec VLC (http://www.videolan.org).


"Clinical Genomics Transcends Sequencing"

Martin Reese of Inc.: "Genomic analysis will switch from 80% research in 2013 to 80% clinical in 3-5 years" (source)

Fridge magnet found in Prague, Aug. 2013. Just added "I love Genomics"
"Clinical Genomics Transcends Sequencing"
April 1 issue. Article by Nicholas Miliaras, Ph.D.
GEN -- Genetic Engineering & Biotech News

"To establish a link between a specific disease and a genetic abnormality, researchers must first obtain tissue samples from affected patients. Nucleic acids are then isolated and sequenced. Then, the data obtained can be used to identify susceptibility loci in families where sequence variants such as single nucleotide polymorphisms (SNPs) or copy number variants (CNVs) are co-inherited with the disease. The data must then be validated by comparison with sequences from unrelated individuals who have the same disease, as well as reference genomes from different populations, before a relationship can be established. Although sequence variants are essential for understanding the genetic basis of diseases, they represent marker sequences, not actual mutations. Only about 1.5% of the human genome contains sequences that code for proteins. Thus, identifying actual mutations that affect protein function resulting in a pathogenic phenotype requires the sequencing and analysis of many genomes from unrelated individuals. Both whole-genome sequencing (WGS) and exome sequencing (sequencing the expressed regions of the genome) make it possible to identify mutations in a relatively short time through next-generation sequencing (NGS) technologies. In addition, data from genome-wide expression, in vitro, and in vivo studies provide a framework for assessing the relevance of mutations and developing panels for targeted genetic diagnostics. The rapid evolution of NGS technology has made it possible to sequence genomes from individual patients in the clinic and to use this information to both identify the genetic causes of disease and also determine the best course of treatment, based on how patients with a given genotype respond to drugs or surgery."


GEN

GEN
"Elizabeth Worthey, Ph.D., a director in the Genomic Medicine Clinic at the Medical College of Wisconsin and Children’s Hospital of Wisconsin, shares Dr. Jongbloed’s opinion that WGS is preferable to exome sequencing in general. 'If you focus on the exome, nongenic regions aren’t covered. Also, the first exon and some parts of other exons of a gene are often not covered very well.' She also sees challenges in sequencing regions with high GC content and in designing probes for regions that are homologous to other regions of the genome. 'If finances weren’t an issue, everyone would do WGS,' Dr. Worthey says. 'In some cases, clinics may resort to using WGS as a reflex test for exome sequencing. If the answer isn’t there, you go to WGS.' Regardless, Dr. Worthey remains optimistic that costs will come down as technology improves.

The Genomic Medicine clinic sees about 20 to 25 new patients each month and performs WGS for about one-third to one-half of them. The current cost is about $5,000 per patient for clinical exome sequencing and analysis, and it is about $17,000 per patient for WGS. 'The costs will definitely come down for WGS. For example, the recently released Illumina HiSeq X Ten systems will provide individual centers with two or three times the capacity of what the largest centers in the world can currently process combined.' Dr. Worthey sees the greatest challenge for clinical genomics in the interpretation phase. 'People say that while the sequencing costs $5,000, the analysis costs $1 million. But that needn’t be true—not if the lab has a suitable clinical analysis tool in place.' The area that needs improvement the most is clinical interpretation, explains Dr. Worthey: 'For example, how do you differentiate between all these errors, polymorphisms, causal mutations, etc.? One way is to determine whether a variant has been identified as deleterious previously, or whether it has been seen in many different individuals with different clinical presentations.' Dr. Worthey points out that there are lots of repositories where this type of data is maintained. 'If somebody else has found the same mutation in a patient elsewhere, then that’s what you are looking for, but you won’t know if you don’t have access to their data.' Ultimately, Dr. Worthey surmises, the problem is data sharing: 'If you have been working on breast cancer for many years, are you going to want to put your data in someone else’s database? Ideally, we would develop something where we could share data instantaneously, or there would be a central repository where we could access the data.' But such a repository, adds Dr. Worthey, 'would have to be updated frequently for the greatest impact.' WGS results cannot be interpreted effectively, Dr. Worthey suggests, unless they are compared with all clinical data available from affected patients as well as those who may have the same disease in an early or unusual presentation: 'Clinical presentation data can be one page or many hundreds of pages, and there will have to be efforts to better catalogue and curate the data for others to interpret it successfully.'"

Quality Issues

"A major challenge for any diagnostic laboratory is ensuring that the data is correctly matched with the original sample and patient. For clinical genomics, this is particularly important, since samples change hands several times. The tissue could be isolated in a hospital and sent to a separate core facility for nucleic acid isolation and sequencing, and the sequence could be analyzed and interpreted offsite by a bioinformatics team. Thus, a unique genetic label that can be assigned at the time of isolation and tracked at each stage of this process is highly desirable.  

Sarah Ennis, Ph.D., head of genomic informatics at the University of Southampton, U.K., has identified 117 unique SNPs for the approximately 180,000 exons in the human genome. The SNPs that Dr. Ennis and her colleagues have identified are sufficiently varied that there is little chance that two individuals in a population of 100,000 could have the same SNP fingerprint. Still, Dr. Ennis notes that there is a somewhat higher frequency of such duplicates in the Han Chinese population (1 in 85,000). While annotating the SNP data is challenging, perhaps the greatest obstacle in controlling data quality is communication. 'We need multidisciplinary teams working together and discussing things, rather than working in silos,' remarks Dr. Ennis. 'Also, we need to develop more and better wet lab functional models for genomic data. It’s very hard to just look at a histopathology report and pull out an answer.'"
GEN

Aucun commentaire: