Folks, everyone in the world who can get their hands on an illumina sequencer is developing these "30 gene", "400 gene", "N gene" tests, liquid biopsies, blah, blah, blah. Even the fact that they got a VC to shell out $45M is something happen pretty regularly now. Source: senior pathology resident in San Diego, driving past illumina and the Craig Venter Institute every day. Developing these tests is literally all molecular pathologists do. All day long.
The game is to actually get a lot of patients. Memorial Sloan Kettering, Foundation One, Broad Institute, Venter are the biggest data-gatherers I'm aware of right now, with the DoD starting to get in the game. But who really wins will be the platforms that do the bioinformatics analysis: Google Genomics, illumina (basespace), etc.
And the ethics questions and "we don't know about the environment" questions aren't going to get answered until the data is collected. Wait till the EMRs are tied into the big data pipelines. Oh, nellie.
Yep. Academic molecular biolgist here. 100% agree. For as much as this community knows about software it knows shockingly little about the rules of health care.
Hate to break it to everyone breathless over yet another press clipping, but this startup is dead in the water. Another $45M down the tubes.
As someone in the field, this is a refreshingly accurate viewpoint. What do you think are some of the needs in the genomics space that aren't being tackled?
This is border line academic imperialism. The founders seem to think that software engineering and data science applied to biological data will provide insight that traditional biology has not found. Unneccessary screening from a single dimension (genome) is only going to misguide patients into oppurtunistic drug companies and non-FDA approved remedies.
We are still unsure of the nature/nuture problem. What if the environment is more attributable to cancer development?
Hi, I am one of the founders of Color and have a Ph.D. from MIT working on cancer genetics before later working at Google and other places. Another founder is an MD and clinical pathologist from UCSF, and then two others have backgrounds in software.
Color is focused on testing for characterized genes (e.g. BRCA1, BRCA2, PTEN, etc.) which have an impact to an individuals risk of developing cancer. Environmental and other factors of course play a role, and most cancers are not caused by these genes. However, knowing that you are at high risk of developing cancer is something a patient can work on with their physician to develop a personalized screening and prevention plan. For example, national guidelines from NCCN suggest that women with a BRCA1 mutation get more frequent mammograms. See also cancer.gov risks for having a BRCA1 or BRCA2 mutation: https://www.cancer.gov/about-cancer/causes-prevention/geneti...
Color was developed working closely with some of the leading cancer researchers including Dr. Mary-Claire King, who is credited with discovering BCRA1, and Dr. Laura Esserman and Dr. Laura v'ant Veer at UCSF. Our team includes people with backgrounds in genetics, medicine, and clinical pathology as well as machine learning, big data, and systems engineering.
This unique combination of skills is really crucial to pushing this area forward. For example, the Komen Foundation (one of the world's biggest breast cancer foundation) held a conference I was part of the planning committee for at Rockefeller University last year on big data for breast cancer. http://ww5.komen.org/BD4BC.html
Marrying data science to medicine is a way to drive cancer research forward.
As an aside, one of Color's founders is a BRCA carriers whose mother had breast cancer twice, and whose grandmother died of the disease. So, it is a bit sad to me that the default assumption is we are "academic imperialists" versus people trying to do something good for the world.
Agree. This was my initial reaction as well. While I can appreciate the founders background in Cancer research and drive to do something about the problem, the solution is unfortunately not a "just apply computer science!" one.
We don't know what we don't know. Yes, we know that certain genes can contribute towards cancer. However, that doesn't mean you will develop it. You could have a torrent of SNPs underneath BRCA1 but never develop breast cancer.
The last comment I'll make (not to be a naysayer) but it's naive to approach the solution as if it's black and white. Biology is super messy. The data is often not clean. Sequencers do get it wrong (albeit not often) and the bioinformatics is not a perfect science. People looking at the field from the outside should approach it with healthy caution.
It's somewhat the equivalent of saying that, in theory it's easy to launch a rocket into orbit. You have a concentration of reaction mass, you ignite it, it propels you to space. In reality, it's obviously infinitely more complex, much like genetics.
Elad started his career with a PhD in cancer biology prior to starting the mobile team at Google, so I don't think "academic imperialism" is an accurate descriptor.
I think you'll see more people with these hybrid skills over time. They take years to develop, though.
If we want advancement in medicine, can we really do it without deep collaboration between biology and computer science? If so, isn't Color Genomics a model of particularly deep cross-disciplinary work, not academic imperialism?
Cancer has genetic predisposition, environmental causes, and random chance all in enough quantity that none of these influences can be ignored.
That said, I'm extremely skeptical that this is a useful consumer-driven test. Far better to be driven by your physician who can decide if there's enough of a familial cancer history to drive the test, to potentially drive other precautions.
Germline genetic testing is useful for entertainment, or for when you have some phenotype that you're interested in investigating, or perhaps for deciding about having children.
Genomes aren't blueprints for an entire life, they're just the parts book. So germline genetic testing is not some sort of Gattaca-like predictor of a person, even if we knew what most of the genome does.
This is just my clueless opinion so pardon me if I say something that makes no sense, but what if they get somewhere?
I don't think that it's a good idea if we end up in the scenario you just described, but what if they find something useful? I think that putting money into cancer research, no matter on what approach, is usually a good idea.
A lot of breakthroughs in history of science came from unrelated areas of research such as this where computer people are working in (at first) non-computer field.
Yes. This is going to be another clean tech debacle, a whole lot of companies raising money on a wave of buzzword (in this example, genomics, big data AND machine learning, what could possibly go wrong) hype, offering at best incremental improvements or at worst, inferior products (eg Theranos).
I don't see how their approach contradicts "traditional biology".
Sure, they are concentrating on one of the many aspects of human biology but as long as their findings are mere recommendations to get tested more often etc based on the potential genetic predisposition I don't see anything wrong with that.
As far as the article is concerned - I'd be very cautious going into the "share your dna report with your employer" (or anyone else for that matter) territory for a variety of reasons.
As a layperson the only genetic testing I am familiar with is the BRCA gene for breast cancer. Other than false positives and the risk of unnecessary treatment, is there a reason not to test all women for it and similar genes?
Additionally, is this company performing research or just doing testing on known factors? If it's the latter then I am not clear about why this is so objectionable. How is this company different from the others that provide genetic testing through your healthcare provider?
"Color has developed a next-generation sequencing based test for hereditary cancer. This test analyzes 30 genes associated with increased risk to develop breast, ovarian, colorectal, melanoma, pancreatic, prostate, stomach, and uterine cancers... The assay has a high degree of analytical validity for the detection of single nucleotide variants, small insertions and deletions (indels), and larger deletions and duplications (copy number variants, or CNVs)."
So not micro-arrays like 23andMe that test for SNPs ($99?), but not full genome sequencing either (~$1,000?); but specific sequencing for the sites of these genomic regions of those 30 genes.
Wet Lab sequencing method: "Specifically, it includes target enrichment by Agilent’s
SureSelect method (v1.7) and sequencing by Illumina’s NextSeq 500 (paired-end 150bp, High Output kit)"; Unanswered question, are they doing the sequencing in-house or using a facility somewhere else?
Computational method: "The bioinformatics pipeline was built using well-established algorithms
such as BWA-MEM, SAMtools, Picard and GATK. CNVs are detected using dedicated internally developed
algorithms for read depth analysis and split-read alignment detection."
So basically perform the standard genome assembly, alignment with human reference genome of your partial assembly, and then identify what variant of these 30 genes the patient sample has; plus a special sauce for counting the number of specific bp repeats, due to in-del events, this is not something I am not too familiar, but presumably the number of a specific k-mer repeats you have in these genes of interest might correlate to a specific type of cancer? (would love to hear someone who is an expert in this field their opinion).
"These [30] genes are APC, ATM, BAP1, BARD1, BMPR1A, BRCA1,BRCA2, BRIP1, CDH1, CDK4, CDKN2A (p14ARF and
p16INK4a), CHEK2, EPCAM, GREM1, MITF, MLH1, MSH2, MSH6, MUTYH, NBN, PALB2, PMS2, POLD1, POLE, PTEN,
RAD51C, RAD51D, SMAD4, STK11, and TP53". (You can follow up by searching them here, e.g., http://www.genecards.org/cgi-bin/carddisp.pl?gene=BRCA2&keyw...).
Also interesting to note, since it's clinical, each of their test has to be verified by a certified "genetics counselor" and also meet lots of clinical standards.
plus a special sauce for counting the number of specific bp repeats, due to in-del events, this is not something I am not too familiar, but presumably the number of a specific k-mer repeats you have in these genes of interest might correlate to a specific type of cancer? (would love to hear someone who is an expert in this field their opinion).
"Copy number variant" refers to larger deletions and duplications that can occur in the genome. There isn't some specific cutoff for size, but some examples in these kinds of genes would be an entire exon or gene. There are countless studies that find correlations between specific variants or CNVs and risk of cancers.
Standard variant detection is pretty straightforward. CNVs are harder because they are longer (several hundred to several thousand base pairs) than the raw data (150 to 250 bp for Illumina)- you don't get single reads that span the entire variant. You have to normalize then look for differences in coverage, or look for split reads (where the read is aligned on the border of one of these CNVs).
This kind of funding baffles me because they don't seem to be proposing anything new at all (maybe slightly better CNV detection?) and there are already lots of labs/companies doing this kind of testing. Maybe they are working on being very efficient to offer a better price.
I am not sure there is really a large enough corpus of data out there that covers multiple facets of this system to really give us a strong predictive value. Just variant calls is probably not enough. There might be, if we can somehow consolidate and integrate disparate datasets from various publications and labs. But I don't think we are at that stage yet.
I am all for them trying though. I just don't think we are at a point where we can make a good diagnosis/conclusion yet.
However, there were a good many asterisks and caveats about not testing every position along these genes (some of which are quite large).
While I'm not aware of any other companies that are doing this type of direct to consumer testing, companies like Myriad have offered targeted panels on some of these gene targets for some time.
There are already companies that do this... Today they are called innovators, tomorrow they'll be called money-grubbing, unethical, anti-FDA maniacs for do the same thing.
[+] [-] niels_olson|9 years ago|reply
The game is to actually get a lot of patients. Memorial Sloan Kettering, Foundation One, Broad Institute, Venter are the biggest data-gatherers I'm aware of right now, with the DoD starting to get in the game. But who really wins will be the platforms that do the bioinformatics analysis: Google Genomics, illumina (basespace), etc.
And the ethics questions and "we don't know about the environment" questions aren't going to get answered until the data is collected. Wait till the EMRs are tied into the big data pipelines. Oh, nellie.
[+] [-] untilHellbanned|9 years ago|reply
Hate to break it to everyone breathless over yet another press clipping, but this startup is dead in the water. Another $45M down the tubes.
[+] [-] adenadel|9 years ago|reply
[+] [-] jghn|9 years ago|reply
[+] [-] mcarlise|9 years ago|reply
We are still unsure of the nature/nuture problem. What if the environment is more attributable to cancer development?
[+] [-] eladgil|9 years ago|reply
Color is focused on testing for characterized genes (e.g. BRCA1, BRCA2, PTEN, etc.) which have an impact to an individuals risk of developing cancer. Environmental and other factors of course play a role, and most cancers are not caused by these genes. However, knowing that you are at high risk of developing cancer is something a patient can work on with their physician to develop a personalized screening and prevention plan. For example, national guidelines from NCCN suggest that women with a BRCA1 mutation get more frequent mammograms. See also cancer.gov risks for having a BRCA1 or BRCA2 mutation: https://www.cancer.gov/about-cancer/causes-prevention/geneti...
Color was developed working closely with some of the leading cancer researchers including Dr. Mary-Claire King, who is credited with discovering BCRA1, and Dr. Laura Esserman and Dr. Laura v'ant Veer at UCSF. Our team includes people with backgrounds in genetics, medicine, and clinical pathology as well as machine learning, big data, and systems engineering.
This unique combination of skills is really crucial to pushing this area forward. For example, the Komen Foundation (one of the world's biggest breast cancer foundation) held a conference I was part of the planning committee for at Rockefeller University last year on big data for breast cancer. http://ww5.komen.org/BD4BC.html
Marrying data science to medicine is a way to drive cancer research forward.
As an aside, one of Color's founders is a BRCA carriers whose mother had breast cancer twice, and whose grandmother died of the disease. So, it is a bit sad to me that the default assumption is we are "academic imperialists" versus people trying to do something good for the world.
Thanks for reading :)
[+] [-] rfc|9 years ago|reply
We don't know what we don't know. Yes, we know that certain genes can contribute towards cancer. However, that doesn't mean you will develop it. You could have a torrent of SNPs underneath BRCA1 but never develop breast cancer.
The last comment I'll make (not to be a naysayer) but it's naive to approach the solution as if it's black and white. Biology is super messy. The data is often not clean. Sequencers do get it wrong (albeit not often) and the bioinformatics is not a perfect science. People looking at the field from the outside should approach it with healthy caution.
It's somewhat the equivalent of saying that, in theory it's easy to launch a rocket into orbit. You have a concentration of reaction mass, you ignite it, it propels you to space. In reality, it's obviously infinitely more complex, much like genetics.
[+] [-] brandonb|9 years ago|reply
I think you'll see more people with these hybrid skills over time. They take years to develop, though.
If we want advancement in medicine, can we really do it without deep collaboration between biology and computer science? If so, isn't Color Genomics a model of particularly deep cross-disciplinary work, not academic imperialism?
[+] [-] epistasis|9 years ago|reply
Cancer has genetic predisposition, environmental causes, and random chance all in enough quantity that none of these influences can be ignored.
That said, I'm extremely skeptical that this is a useful consumer-driven test. Far better to be driven by your physician who can decide if there's enough of a familial cancer history to drive the test, to potentially drive other precautions.
Germline genetic testing is useful for entertainment, or for when you have some phenotype that you're interested in investigating, or perhaps for deciding about having children.
Genomes aren't blueprints for an entire life, they're just the parts book. So germline genetic testing is not some sort of Gattaca-like predictor of a person, even if we knew what most of the genome does.
[+] [-] tucaz|9 years ago|reply
I don't think that it's a good idea if we end up in the scenario you just described, but what if they find something useful? I think that putting money into cancer research, no matter on what approach, is usually a good idea.
A lot of breakthroughs in history of science came from unrelated areas of research such as this where computer people are working in (at first) non-computer field.
[+] [-] Gatsky|9 years ago|reply
[+] [-] ChemicalWarfare|9 years ago|reply
Sure, they are concentrating on one of the many aspects of human biology but as long as their findings are mere recommendations to get tested more often etc based on the potential genetic predisposition I don't see anything wrong with that.
As far as the article is concerned - I'd be very cautious going into the "share your dna report with your employer" (or anyone else for that matter) territory for a variety of reasons.
[+] [-] in_cahoots|9 years ago|reply
Additionally, is this company performing research or just doing testing on known factors? If it's the latter then I am not clear about why this is so objectionable. How is this company different from the others that provide genetic testing through your healthcare provider?
[+] [-] steveplace|9 years ago|reply
[+] [-] noname123|9 years ago|reply
"Color has developed a next-generation sequencing based test for hereditary cancer. This test analyzes 30 genes associated with increased risk to develop breast, ovarian, colorectal, melanoma, pancreatic, prostate, stomach, and uterine cancers... The assay has a high degree of analytical validity for the detection of single nucleotide variants, small insertions and deletions (indels), and larger deletions and duplications (copy number variants, or CNVs)."
So not micro-arrays like 23andMe that test for SNPs ($99?), but not full genome sequencing either (~$1,000?); but specific sequencing for the sites of these genomic regions of those 30 genes.
Wet Lab sequencing method: "Specifically, it includes target enrichment by Agilent’s SureSelect method (v1.7) and sequencing by Illumina’s NextSeq 500 (paired-end 150bp, High Output kit)"; Unanswered question, are they doing the sequencing in-house or using a facility somewhere else?
Computational method: "The bioinformatics pipeline was built using well-established algorithms such as BWA-MEM, SAMtools, Picard and GATK. CNVs are detected using dedicated internally developed algorithms for read depth analysis and split-read alignment detection."
So basically perform the standard genome assembly, alignment with human reference genome of your partial assembly, and then identify what variant of these 30 genes the patient sample has; plus a special sauce for counting the number of specific bp repeats, due to in-del events, this is not something I am not too familiar, but presumably the number of a specific k-mer repeats you have in these genes of interest might correlate to a specific type of cancer? (would love to hear someone who is an expert in this field their opinion).
"These [30] genes are APC, ATM, BAP1, BARD1, BMPR1A, BRCA1,BRCA2, BRIP1, CDH1, CDK4, CDKN2A (p14ARF and p16INK4a), CHEK2, EPCAM, GREM1, MITF, MLH1, MSH2, MSH6, MUTYH, NBN, PALB2, PMS2, POLD1, POLE, PTEN, RAD51C, RAD51D, SMAD4, STK11, and TP53". (You can follow up by searching them here, e.g., http://www.genecards.org/cgi-bin/carddisp.pl?gene=BRCA2&keyw...).
Also interesting to note, since it's clinical, each of their test has to be verified by a certified "genetics counselor" and also meet lots of clinical standards.
[+] [-] jrm5100|9 years ago|reply
"Copy number variant" refers to larger deletions and duplications that can occur in the genome. There isn't some specific cutoff for size, but some examples in these kinds of genes would be an entire exon or gene. There are countless studies that find correlations between specific variants or CNVs and risk of cancers.
Standard variant detection is pretty straightforward. CNVs are harder because they are longer (several hundred to several thousand base pairs) than the raw data (150 to 250 bp for Illumina)- you don't get single reads that span the entire variant. You have to normalize then look for differences in coverage, or look for split reads (where the read is aligned on the border of one of these CNVs).
This kind of funding baffles me because they don't seem to be proposing anything new at all (maybe slightly better CNV detection?) and there are already lots of labs/companies doing this kind of testing. Maybe they are working on being very efficient to offer a better price.
[+] [-] daemonk|9 years ago|reply
[+] [-] lunula|9 years ago|reply
Whole genome is not controlled enough to meet clinical standards.
[+] [-] daemonk|9 years ago|reply
I am all for them trying though. I just don't think we are at a point where we can make a good diagnosis/conclusion yet.
[+] [-] futuremeats|9 years ago|reply
I found this whitepaper on their website, which provides some level of detail...
https://s3.amazonaws.com/color-static-prod/pdfs/validationWh...
However, there were a good many asterisks and caveats about not testing every position along these genes (some of which are quite large).
While I'm not aware of any other companies that are doing this type of direct to consumer testing, companies like Myriad have offered targeted panels on some of these gene targets for some time.
http://myriadgenetics.eu/products/
[+] [-] zzguy|9 years ago|reply
[+] [-] unknown|9 years ago|reply
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