About two years ago, @stephanie_mul tallied the whole exome data we had & mapped it against theoretical power calculations @gaddyg set forth for discovering significant cancer genes in any cancer type (see: ncbi.nlm.nih.gov/pubmed/24390350)
Turned out we had a lot! So we started wondering, "If you have enough tumor genomics in any one cancer type, can you find mutations in genes that invoke *all* Cancer Hallmarks, even those never seen in that cancer?" (see: cell.com/abstract/S0092…)
We took a first stab at this at our 2015 PCF/SU2C team meeting → @nikolausschultz approached me at snack table (The Great Chips & Dip Scientific Summit of 2015) → he was doing the same thing, and we both immediately agreed we should do this together because #squadgoals
After numerous analyses, realigning, re-re-aligning, re-analysis, etc, we had a refined set of 1,013 #prostatecancer exomes - in 2018, we also now have many cancer genomics & biology priors to apply with a statistical framework (h/t @MarkARubin1) and learn!
Main finding: A true “long tail” of significantly mutated genes in #prostatecancer, including genes/pathways we had no idea were involved & rare, but helped us cover the remaining territory of the Cancer Hallmarks (e.g. SF3B1/splicing, Ras signaling)
We also saw an entire subclass of prostate cancer with mutations exclusively in epigenetic genes, raising new therapeutic & tumor-immune hypotheses, plus new collabs with @kadochlab@CKadoch et al cc: @SKCCDirector
With a bigger cohort, we also could take a better swing at defining a genomic “signature” of metastatic vs. primary prostate cancer – we are still a long way from a clinical test, but the potential is vast, e.g. wsj.com/articles/prost…@LucetteLagnado
Of course, we hope to augment this cohort (exclusively from academic sites via traditional means) with the patient-driven Metastatic Prostate Cancer Project cohort → 3 months in & 100s of men have said “Count Me In!” mpcproject.org@PrCaProject@corrie_painter et al
Finally, this is yet another example of the power of #teamscience → just the latest product from a group effort that has yielded numerous findings for #prostatecancer, and we're excited/hopeful for where this will go in the future! @PCFnews@PCF_Science@SU2C [fin]
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We analyzed every tumor-normal exome from patients getting immune checkpoint blockade (ICB) we could get & integrated w/ clinical outcomes for biological and clinical exploration → lots of technical pain here + open questions re: defining clinical benefit
For context, lots of ongoing biology re: mutations/neoantigens driving response to immune checkpoint blockade by many groups (including ours).
In parallel, lots of buzz about tumor mutational burden (TMB) as a *clinical* biomarker for cancer ICB...
Lots of discussion whether broad cancer NGS testing is good/bad given @JAMAOnc article below. Tbh I'm far more interested in some general issues it exposes re: prospectively testing the precision oncology hypothesis:
1) NGS testing w/o companion (early phase?) clinical trial network & mid-trial adjustments for when new approvals arise creates a ‘last mile’ problem that reduces potential impact. Can a precision oncology trial have experimental Rx access and be changed in real time? [2/4]
2) Dropping a complicated test of any kind on providers who have no prior training or expertise in its interpretation (when also paired with often…err…curious interpretations from vendors) will confound outcomes.
Reflecting on the recent/heated “hype vs. hope” precision oncology debates: It’s not “vs.” → real hope it engenders & current limitations are simultaneously true. This tension mirrors so much of oncology, as @Bob_Wachter elegantly points out here: nytimes.com/2018/04/19/opi… [1/n]
Thankfully, @DHymanMD captured this critical point clearly, here:
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A recent 'back of the envelope' study noted only ~15% (~95k) metastatic cancer patients may get genome-informed Rx in 2018, & less achieve clinical benefit: jamanetwork.com/journals/jamao…
There’s an established heritability for colorectal cancer hovering around 30%, though only roughly 5-10% is explained by known syndromes involving genes like APC, MSH2, and PTEN, among others – the rest is so-called “missing heritability”
In addition, traditional clinical measures like family history have not thus far been closely related to the identification of bona fide pathogenic mutations, so new studies are needed looking at a broader patient population to understand the patterns of these mutations