10 ms·

Color Genomics raises $45M to provide genetic tests that detect cancer risk

78 points by sandeepc 10y ago

mcarlise 10y ago
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?
- tucaz 10y ago
  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.
  - epistasis 10y ago
    This is a highly computer driven field, with tons of computer scientists working in genomics. This aspect is not something where they're any more likely to have interesting results than any of the academic labs around the country that are driving machine learning methods and working closely with those that are developing machine learning methods. Far more interesting is the data the Color will collect if they grow a customer base, which is not something that many researchers have access to. However, if they're only collecting features and not the labels (cancer incidence) then it's pretty boring data.
  - cowsandmilk 10y ago
    A huge thing in health care is currently the fact that many diagnostic tests turn up either (i) more false positives than true positives and (ii) diagnose things that turn out not to be true threats. For (ii), see the debates about PSA tests. You may diagnose potential for cancer, but if the treatment causes more health problems than the disease; you've just created useless worry and costs with your test. The optimists see two things (1) better tests that could tell whether the prostate cancer is problematic and (2) as lifespans increase, the likelihood of you living long enough for the cancer to be a problem increases, so if we are trying to live forever, then the PSA test results will matter eventually. Back to (i), the false positives. As a disease becomes more rare, the more your false positive rate matters. If a disease affects 1 in 10k people, your 0.1% FPR will diagnose 10 times as many people wrongly as it does correctly. This is pretty damn common with genetic tests. I think you can get somewhere data mining whole genome sequences, particularly if you sequence from healthy and diseased tissues in individuals and do exome sequencing as well, but that doesn't appear to be what Color Genomics actually does.
- epistasis 10y ago
  I agree with this assessment. 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.
- Gatsky 10y ago
  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).
- in_cahoots 10y ago
  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?
  - astazangasta 10y ago
    BRCA1/2 germline mutations occur at about 1/400 in the population at large. In breast cancer patients they occur at about 1/50; in breast cancer patients under 40 they occur at about 1/10. I.e., 98% of breast cancer patients and 90% of breast cancer patients under 40 do not have cancer because of this genetic susceptibility. This is by far the most common germline cancer mutation, and it is a severe, DNA damage repair mutation. There are few comparable mutations that will indicate such a severe risk. If you're NF1 mutant or have Li-Fraumeni (other germline cancer-causing mutations) you will have other disease syndromes before you develop cancer. In the vast majority of cases, testing cancer susceptibility genetically will either (1) miss the largest non-genetic component of cancer susceptibility and (2) incorrectly indicate risk (i.e., a positive test does not mean as much).
- brandonb 10y ago
  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?
  - jahewson 10y ago
    > If we want advancement in medicine, can we really do it without deep collaboration between biology and computer science? There's an entire field for that already, it's called bioinformatics.
  - sytse 10y ago
    I agree that Color Genomics is doing the right thing here. Of course any testing has the risk of misunderstandings and overtreatment. But they are aware of this and have counselors available to reduce the risk https://getcolor.com/learn/how-it-works https://getcolor.com/learn/how-it-works I think that medicine tends to treats us as patients instead of partners. Making testing much more affordable historically has done more good than bad. I think reducing the price of this testing by one or two orders of magnitude is a wonderful thing.
- rfc 10y ago
  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.
  - colbyh 10y ago
    the solution isn't black and white and Color doesn't act like it should be. they provide licensed genetic counsellors (free of cost) to contextualize your results.
- ChemicalWarfare 10y ago
  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.
- steveplace 10y ago
  Because if people are getting cancer with no genetic markers, then we know it's environment... or at least not genetic.
  - barkbro 10y ago
    The human genome and body are extremely complex. Concluding that something is caused by environmental factors just because a few genetic markers can't be found, would be a massive over-simplification.
- eladgil 10y ago
  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/genetics/brca-fact-sheet#q2 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 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 10y ago
    Hi Elad, First off I want to say that I appreciate the drive to work on problems like this. I personally think it's a much better use of money than funding yet another marketing tool to 'revolutionize push notification blah blah'. I am wondering if you can answer a question (probably naive but curious nonetheless). Why not sequence the full genome on a 30x coverage? Why find just the mutations on these genes rather than across the board? The reason I'm asking is that it feels somewhat limiting to focus on only the currently known relationships of mutations rather than collecting the full data set. There's other initiatives, such as SB Genomics, that are doing very interesting work on the Cancer Cloud by utilizing new graphing techniques in data science to understand large scale pattern interactions, but they typically are utilizing the full data set.
daemonk 10y ago
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.
noname123 10y ago
Here's their white-paper on their testing methodology: https://s3.amazonaws.com/color-static-prod/pdfs/validationWhitePaper.pdf https://s3.amazonaws.com/color-static-prod/pdfs/validationWh... "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&keywords=BRCA2 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.
- daemonk 10y ago
  This seems very standard to me. The only thing that can't be reproduced immediately is the CNV algorithm?
zzguy 10y ago
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.
- deleted 10y ago
  [deleted]
niels_olson 10y ago
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.
- untilHellbanned 10y ago
  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.
  - dmix 10y ago
    Are you saying the lack of access to data will be the issue? Or following health laws? If they get some limited access to data, develop the machine learning software better than anyone, whats stopping one of the big pharma companies from shelling out $1B to acquire the company? Getting access to a tech team + IP could be very valuable. Pharma companies aren't known for their software teams either and this seems to be the core of their business offering here. Not the tests that everyone's already doing... I mean I just reread the article and they aren't claiming this is their core business proposition at all (as the OP seems to imply). Even Illumina makes $2B in revenue currently. There's lots of money in the pharma industry and they always converge on a few big firms. They don't need to be original to provide real technical value here. Unlike the pharma industry where you shield your IP with lawyers for 10 yrs, being first means nothing in the software world. It's about who can do it best. The founders comments here also clarifies that they aren't going after new interesting areas because they are focusing on commercializing something that works right now and advancing that data science aspect of it, instead of making a future play on some original R&D.
futuremeats 10y ago
Does anybody know the total number / exact list of SNPs covered in this panel? How about the read depth? I found this whitepaper on their website, which provides some level of detail... https://s3.amazonaws.com/color-static-prod/pdfs/validationWhitePaper.pdf 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/ http://myriadgenetics.eu/products/

78 points by sandeepc 10y ago

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?

tucaz 10y ago
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.
- epistasis 10y ago
  This is a highly computer driven field, with tons of computer scientists working in genomics. This aspect is not something where they're any more likely to have interesting results than any of the academic labs around the country that are driving machine learning methods and working closely with those that are developing machine learning methods. Far more interesting is the data the Color will collect if they grow a customer base, which is not something that many researchers have access to. However, if they're only collecting features and not the labels (cancer incidence) then it's pretty boring data.
- cowsandmilk 10y ago
  A huge thing in health care is currently the fact that many diagnostic tests turn up either (i) more false positives than true positives and (ii) diagnose things that turn out not to be true threats. For (ii), see the debates about PSA tests. You may diagnose potential for cancer, but if the treatment causes more health problems than the disease; you've just created useless worry and costs with your test. The optimists see two things (1) better tests that could tell whether the prostate cancer is problematic and (2) as lifespans increase, the likelihood of you living long enough for the cancer to be a problem increases, so if we are trying to live forever, then the PSA test results will matter eventually. Back to (i), the false positives. As a disease becomes more rare, the more your false positive rate matters. If a disease affects 1 in 10k people, your 0.1% FPR will diagnose 10 times as many people wrongly as it does correctly. This is pretty damn common with genetic tests. I think you can get somewhere data mining whole genome sequences, particularly if you sequence from healthy and diseased tissues in individuals and do exome sequencing as well, but that doesn't appear to be what Color Genomics actually does.
epistasis 10y ago
I agree with this assessment. 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.
Gatsky 10y ago
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).
in_cahoots 10y ago
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?
- astazangasta 10y ago
  BRCA1/2 germline mutations occur at about 1/400 in the population at large. In breast cancer patients they occur at about 1/50; in breast cancer patients under 40 they occur at about 1/10. I.e., 98% of breast cancer patients and 90% of breast cancer patients under 40 do not have cancer because of this genetic susceptibility. This is by far the most common germline cancer mutation, and it is a severe, DNA damage repair mutation. There are few comparable mutations that will indicate such a severe risk. If you're NF1 mutant or have Li-Fraumeni (other germline cancer-causing mutations) you will have other disease syndromes before you develop cancer. In the vast majority of cases, testing cancer susceptibility genetically will either (1) miss the largest non-genetic component of cancer susceptibility and (2) incorrectly indicate risk (i.e., a positive test does not mean as much).
brandonb 10y ago
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?
- jahewson 10y ago
  > If we want advancement in medicine, can we really do it without deep collaboration between biology and computer science? There's an entire field for that already, it's called bioinformatics.
- sytse 10y ago
  I agree that Color Genomics is doing the right thing here. Of course any testing has the risk of misunderstandings and overtreatment. But they are aware of this and have counselors available to reduce the risk https://getcolor.com/learn/how-it-works https://getcolor.com/learn/how-it-works I think that medicine tends to treats us as patients instead of partners. Making testing much more affordable historically has done more good than bad. I think reducing the price of this testing by one or two orders of magnitude is a wonderful thing.
rfc 10y ago
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.
- colbyh 10y ago
  the solution isn't black and white and Color doesn't act like it should be. they provide licensed genetic counsellors (free of cost) to contextualize your results.
ChemicalWarfare 10y ago
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.
steveplace 10y ago
Because if people are getting cancer with no genetic markers, then we know it's environment... or at least not genetic.
- barkbro 10y ago
  The human genome and body are extremely complex. Concluding that something is caused by environmental factors just because a few genetic markers can't be found, would be a massive over-simplification.
eladgil 10y ago
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/genetics/brca-fact-sheet#q2 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 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 10y ago
  Hi Elad, First off I want to say that I appreciate the drive to work on problems like this. I personally think it's a much better use of money than funding yet another marketing tool to 'revolutionize push notification blah blah'. I am wondering if you can answer a question (probably naive but curious nonetheless). Why not sequence the full genome on a 30x coverage? Why find just the mutations on these genes rather than across the board? The reason I'm asking is that it feels somewhat limiting to focus on only the currently known relationships of mutations rather than collecting the full data set. There's other initiatives, such as SB Genomics, that are doing very interesting work on the Cancer Cloud by utilizing new graphing techniques in data science to understand large scale pattern interactions, but they typically are utilizing the full data set.

daemonk 10y ago

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.

noname123 10y ago

Here's their white-paper on their testing methodology: https://s3.amazonaws.com/color-static-prod/pdfs/validationWhitePaper.pdf https://s3.amazonaws.com/color-static-prod/pdfs/validationWh... "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&keywords=BRCA2 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.

daemonk 10y ago
This seems very standard to me. The only thing that can't be reproduced immediately is the CNV algorithm?

zzguy 10y ago

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.

deleted 10y ago
[deleted]

niels_olson 10y ago

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.

untilHellbanned 10y ago
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.
- dmix 10y ago
  Are you saying the lack of access to data will be the issue? Or following health laws? If they get some limited access to data, develop the machine learning software better than anyone, whats stopping one of the big pharma companies from shelling out $1B to acquire the company? Getting access to a tech team + IP could be very valuable. Pharma companies aren't known for their software teams either and this seems to be the core of their business offering here. Not the tests that everyone's already doing... I mean I just reread the article and they aren't claiming this is their core business proposition at all (as the OP seems to imply). Even Illumina makes $2B in revenue currently. There's lots of money in the pharma industry and they always converge on a few big firms. They don't need to be original to provide real technical value here. Unlike the pharma industry where you shield your IP with lawyers for 10 yrs, being first means nothing in the software world. It's about who can do it best. The founders comments here also clarifies that they aren't going after new interesting areas because they are focusing on commercializing something that works right now and advancing that data science aspect of it, instead of making a future play on some original R&D.

futuremeats 10y ago

Does anybody know the total number / exact list of SNPs covered in this panel? How about the read depth? I found this whitepaper on their website, which provides some level of detail... https://s3.amazonaws.com/color-static-prod/pdfs/validationWhitePaper.pdf 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/ http://myriadgenetics.eu/products/