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TEDx Talks
Published: 2016-05-17
Source: https://www.youtube.com/watch?v=kyMzPwS88F8
today I hope to convince you in the last twenty years we've undergone three major revolutions in biomedical research which allow people like me in my students its cover potential drug targets to treat cancer dressed in RPGs so what are the three major natural sciences that we all take in high school biology chemistry physics cool %HESITATION among those which were mathematically intensive and chemistry you're giving my
talk of so twenty one years ago changed in nineteen ninety five genomes of to bacteria maaf loose influenza and mycoplasma genitalia were sequence meaning the letters of their DNA a see G. T. were read now analyzing these genomes number influenza genome is nearly two million letters or bases long so analyzing these genomes witcher finding jeans witcher like words embedded in a random sequence required people with
imputed programming that statistics backgrounds they required strong mathematical computational backgrounds as a result computer scientists statisticians mathematicians physicists chemists enter the field the biology given this new demand an opportunity to apply computational approaches to improving our understanding of biology and human health in nineteen ninety five biology became a mathematically intensive natural science this is the first revolution now I mentioned that influence the genome has nearly
two million DNA letters your genome contains over three billion the human genome project consisting of a consortium twenty top research institute started sequencing the human genome in nineteen ninety and ended in two thousand three what was the cost nearly three billion dollars and it took a consortium thirteen years day cost is one thousand dollars and we can do it a day mematikan driven by the development
of the new knowledge she thousand five high throughput sequence these are instruments sequence the letters of DNA really fast really cheap this is the second revolution I know many a view have may have heard of Moore's law right this effectively quantifies the rate at which computers are getting faster and cheaper that's the white line in this figure shown as cost reduction over time the Green Line
shows the cost reduction sequencing the human genome over the same time period plummeting much faster than computers it's our guild arguably been the fastest moving technology on the planet in recent years so the first revolution brought people with computational skills in nineteen ninety five into biology second revolution in two thousand five was development of instruments that could sequence the letters of DNA really fast for really
cheap what do you think it's happened since the amount of publicly available data skyrocketed here is the growth of one major genomic data archive that currently contains nearly three thousand trillion DNA letters and it's still rapidly growing these instruments have driven the success of big science genomics projects like the king genome atlas teams of scientists clinicians sequencing the genomes of patient tumors across a wide variety
of tumor types also driving the success of a number of other big science genomics projects each of which deposit massive data sets genomics data is also being generated by thousands of labs around the world as part of their research so what does this mean it means people like me can cover drug targets to treat cancer working from home re analyzing publicly available data dressed in my
PJS this is the third revolution now as an example I'm gonna collaborate collaboration with a colleague and friend doctor Marty mail broadly the goal of our research better understand how lung cancer spreads to other parts of the body see bone process known as metastasis and for many tumors task this is what kills a patient so we search for proteins that when blocked black spread of cancer
it could significantly extend patient lives so simulating the tumor environment Marty feeds the cells protein when the cells eat this protein the change start out held together by junctions I junctions retract they're degraded cells change shape and they become mobile they can actually become more like stem cells and revert to other cell types not it's long so when they travel to bone they can become bone
tumor cells thereby seating a new tumor in bone this is my task of there are about twenty thousand genes in the human genome which ultimately produce proteins we mapped eighteen factors that reduce the list to see hundred critical for metastasis he then compared this list of so it's hundred to a database of proteins that are secreted in these two our cells are spelled out and we
found one protein that the cells make themselves and eat thereby becoming self reliant maintaining the metastatic state Marty's lab tested this prediction the importance of these proteins but the cells make in metastases sperm mentally when you block this protein cells still make it but they can't eat it this holds the spread tumor to other tissues this could lead to a therapy Trent metastasis in lung cancer
so the first revolution brought people like me and my students into biology second revolution allowed us to map the gene control factors that took the list from twenty thousand genes to six hundred that could be important from third revolution allowed us to compare hundred G. publicly available data to write it in one protein that when blocked blocks metastasis I believe this will be the century of
the cell are increasing power it making and testing Zeiss predictions of cellular function will deliver precision medicine medicines tailored to your genome therapeutics specifically targeting individual patients mutations so if you're a good math cuter programming someone asks what do you want to do next a great answer would P. become a biologist you'll be able cover precise therapeutic targets revolutionize patient here working from home in your
