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9:20AM 11/12/2014 – Panel Discussion – Genomic Technologies @10th Annual Personalized Medicine Conference at the Harvard Medical School, Boston

Posted in Academic Publishing, Conference Coverage with Social Media, Personalized and Precision Medicine & Genomic Research, Scientific & Biotech Conferences: Press Coverage, tagged #endcancer, #healtcare, #pharmaIT, #pharmanews, Agilent Technologies, Bioinformatics, Brigham and Women's, Cancer Genomics, Chip-Sequencing, clinical omics, DNA nanotechnology, emerging technologies, epigenomics, Framingham Heart Study, Full genome sequencing, genomic technology, Harvard MedicalSchool, healthcare, Illumina, MD Anderson Cancer center, personalised medicine on November 12, 2014| Leave a Comment »

9:20AM 11/12/2014 – 10th Annual Personalized Medicine Conference at the Harvard Medical School, Boston

Reporter: Aviva Lev-Ari, PhD, RN

REAL TIME Coverage of this Conference by Dr. Aviva Lev-Ari, PhD, RN – Director and Founder of LEADERS in PHARMACEUTICAL BUSINESS INTELLIGENCE, Boston http://pharmaceuticalintelligence.com

9:20 a.m. Panel Discussion – Genomic Technologies

Genomic Technologies

The greatest impetus for personalized medicine is the initial sequencing of the human genome at the beginning of this Century. As we began to recognize the importance of genetic factors in human health and disease, efforts to understand genetic variation and its impact on health have accelerated. It was estimated that it cost more than two billion dollars to sequence the first human genome and reduction in the cost of sequence became an imperative to apply this technology to many facets of risk assessment, diagnosis, prognosis and therapeutic intervention. This panel will take a brief historical look back at how the technologies have evolved over the last 15 years and what the future holds and how these technologies are being applied to patient care.

Genomic Technologies

Opening Speaker and Moderator:

George Church, Ph.D.
Professor of Genetics, Harvard Medical School; Director, Personal Genomics

Genomic Technologies and Sequencing

highly predictive, preventative
non predictive

Shareable Human Genomes Omics Standards

$800 Human Genome Sequence – Moore’s Law does not account for the rapid decrease in cost of Genome Sequencing

Genome Technologies and Applications

Genia nanopore – battery operated device
RNA & protein traffic
Molecular Stratification Methods – more than one read, sequence ties
Brain Atlas – transcriptome of mouse brains
Multigenics – 700 genes: hGH therapies

Therapies

vaccine
hygiene
age

~1970 Gene Therapy in Clinical Trials

Is Omic technologies — a Commodity?

Some practices will have protocols
other will never become a commodity

Panelists:

Sam Hanash, M.D., Ph.D. @MDAndersonNews

Director, Red & Charline McCombs Institute for Early Detection & Treatment of Cancer MD Anderson Cancer Center

Heterogeneity among Cancer cells. Data analysis and interpretation is very difficult, back up technology

Proteins and Peptides before analysis with spectrometry:

PM – Immunotherapy approaches need be combined with other techniques
How modification in protein type affects disease
amplification of an aberrant protein – when that happens cancer developed. Modeling on a CHip of peptide synthesizer

Mark Stevenson @servingscience

Executive Vice President and President, Life Sciences Solutions
Thermo Fisher Scientific

Issues of a Diagnostics Developer:

FDA regulation, need to test on several tissues
computational environment
PCR, qPCR – cost effective
BGI – competitiveness

Robert Green, MD @BrighamWomens

Partners, Health Care Personalized Medicine — >>Disclosure: Illumina and three Pharmas

Innovative Clinical Trial: Alzheimer’s Disease, integration of sequencing with drug development

Population based screening with diagnosis
Cancer predisposition: Cost, Value, BRCA
epigenomics technologies to be integrated
Real-time diagnostics
Screening makes assumption on Predisposition
Public Health view: Phenotypes in the Framingham Studies: 64% pathogenic genes were prevalent – complication based in sequencing.

Questions from the Podium:

Variants analysis
Metastasis different than solid tumor itself – Genomics will not answer issues related to tumor in special tissues variability

– See more at: http://personalizedmedicine.partners.org/Education/Personalized-Medicine-Conference/Program.aspx#sthash.qGbGZXXf.dpuf

Aneuploidy and Carcinogenesis

Posted in Biological Networks, Gene Regulation and Evolution, CANCER BIOLOGY & Innovations in Cancer Therapy, Chemical Genetics, Genome Biology, Pharmacogenomics, Population Health Management, Genetics & Pharmaceutical, tagged aneuploidy, Brigham and Women's, Cancer - General, chromosomal deletions, driver mutation, Harvard Medical School, oncogene, potency, promoter gene, Stephen Elledge, tumor suppressor, Tumor suppressor gene on October 31, 2013| Leave a Comment »

Aneuploidy and Carcinogenesis

Curator and Reporter: Larry H. Berntein, MD, FCAP

and

Curator: Stephen J Williams, PhD

New Theory of Cancer Development

Researchers have been unable to explain why cancer cells contain abnormal numbers of chromosomes for over a century. The phenomenon known as aneuploidy is associated with all types of cancer. Harvard Medical School researchers have hypothesized why cancer cells contain many more chromosome abnormalities than healthy cells. They have devised a way to understand

patterns of aneuploidy in tumors and
predict which genes in the affected chromosomes are likely to be cancer suppressors or promoters, and
they propose that aneuploidy is a driver of cancer, rather than a result of it.

The study, to be published online in Cell, offers a new theory of cancer development and could lead to new treatment targets. This would be feasible if they could identify key cancers suppressors.

The cancer cell characteristically has many gene deletions and amplifications, chromosome gains and losses. Although it has the appearance of randomness, previous research has shown that there is a pattern to the alterations in chromosomes and chromosome arms, which suggests that we can decipher that pattern and perhaps learn how or if it drives the cancer, according to the senior author, Stephen Elledge, Gregor Mendel professor of Genetics and of Medicine at HMS and professor of medicine at Brigham and Women’s Hospital. Having proposed the theory about how these cellular genetic changes occur, the team set out to prove it using mathematical analysis.

See “Related Links” for full-size image. (Source: HMS/ University of Cambridge/Joanne Davidson, Mira Grigorova and Paul Edwards)

Mining for answers

Cancer research has focused on mutations for decades since the “oncogene revolution.” Changes in the DNA code that abnormally activate genes, called oncogenes, either promote cancer or deactivate genes that suppress cancer. The role of aneuploidy— in which entire chromosomes or chromosome arms are added or deleted— has remained largely unstudied.

Elledge and his team, including research fellow and first author Teresa Davoli, suspected that aneuploidy has a significant role to play in cancer because missing or extra chromosomes likely affect genes involved in tumor-related processes such as cell division and DNA repair.

To test their hypothesis, the researchers developed a computer program called TUSON (Tumor Suppressor and Oncogene) Explorer together with Wei Xu and Peter Park at HMS and Brigham and Women’s. The program analyzed genome sequence data from more than 8,200 pairs of cancerous and normal tissue samples in three preexisting databases.

They found many more potential cancer drivers than anticipated

after generating a list of suspected oncogenes and tumor suppressor genes based on their mutation patterns.

They ranked the suspects by how powerful an effect their deletion or duplication was likely to have on cancer development. The team then looked at where the suspects normally appear in chromosomes.

They discovered that

the number of tumor suppressor genes or oncogenes in a chromosome
correlated with how often the whole chromosome or part of the chromosome was deleted or duplicated in cancers.

Where there were concentrations of tumor suppressor genes alongside

fewer oncogenes and fewer genes essential to survival,
there was more chromosome deletion.

Conversely,

concentrations of oncogenes and fewer tumor suppressors coincided with
more chromosome duplication.

When the team factored in gene potency, the correlations got even stronger. A cluster of highly potent tumor suppressors was

more likely to mean chromosome deletion than a cluster of weak suppressors.

Number matters

Since 1971, the standard tumor suppressor model has held that

cancer is caused by a “two-hit” cascade in which first one copy and
then the second copy of a gene becomes mutated.

Elledge argues that simply losing or gaining one copy of a gene through aneuploidy can influence tumor growth as well. However, the loss or gain of multiple cancer driver genes that individually have low potency

can have big effects by accretion of potency

These novel algorithms that identify tumor suppressors and oncogenes give experimentally verifiable basis for how aneuploidies evolve in cancer cells, and

Indicate that subtle changes in the activity of many different genes at the same time can contribute to tumorigenesis

These findings also may have answered a long-standing question about whether aneuploidy is a cause or effect of cancer, leaving researchers free to pursue the question of how. “Aneuploidy is driving cancer, not simply a consequence of it,” said Elledge. “Other things also matter, such as gene mutations, rearrangements and changes in expression. We don’t know what the weighting is, but now we should be able to figure it out.” Elledge and Davoli plan to gather experimental evidence to support their mathematical findings. That will include validating some of the new predicted tumor suppressors and oncogenes as well as “making some deletions and amplifications and seeing if they have the properties we think they do”.

Source: Harvard Medical School