Jonathan Keats: 12 Days of CoMMpass – Day 1
Jonathan Keats, Assistant Professor at Translational Genomics Research Institute, posted on X:
“12 Days of CoMMpass – Day 1: Today is a major milestone for the Multiple Myeloma Research Foundation CoMMpass project with the network’s formal publication of the entire cohort in Nature Genetics. Like CoMMpass data the manuscript is open access to ensure community access.
This massive effort lead by Multiple Myeloma Research Foundation, Sagar Lonial and myself accrued 1143 patients from over 85 sites in the USA, Canada, Spain, and Italy. Bone marrow and blood samples (n=5112) were processed Van Andel Institute and 5377 sequencing results files were generated.
A study of this magnitude involves far more people than those that are listed as authors and CoMMpass Network members. None of this could have been possible without all the people consenting patients, collecting clinical data, and providing logistics support.
What should you take away from this manuscript from Sheri S today? Likely more than I can ever put in a long thread but for the average patient this study shows that average survival is more than the 8 year observation period.
It builds on existing work by Fenghuang Zhan, Ruben Carrasco, Giovanni Tonon, and Broijl Annemiek to define subtypes of multiple myeloma. When possible we have kept the subtype names defined by these efforts to minimize confusion in the field.
One of the most translatable observations today is the copy number subtypes that identifies 8 subtypes. Importantly hyperdiploid myeloma falls into 5 subtypes with one group HRD(+1q, diploid 11, -13) having poor outcome but HRD(++15) having the best outcome.
Question that intrigues me is why does hyperdiploid without trisomy 3 also lack trisomy 7. For our clinical colleagues, when you see a hyperdiploid FISH report watch for co-existence of del(13) and gain(1q), poor OS. Watch for tetraploidy of chromosome 15, favorable OS.
When looking at the RNA data, which has much more dynamic range, we identified 12 subtypes. One has significant impact on outcome, and matches the classic PR subtype, and even with IMID and PI based frontline therapy continues be associated with poor outcome.
Importantly, all of the current cell surface immunotherapy targets are equally expressed in this high risk population providing hope for this patient population. Also, BCMA expression is actually higher and the NFkB index is lower, which could have resistance risk implications.
We also show patients can progress into this PR subtype with time, explaining in part how some patients can switch to a more aggressive form of disease. Using integrated analysis we show the PR phenotype is associated complete loss of RB1, MAX, and CDKN2C.
Finally taking advantage of the comprehensive nature of the CoMMpass data set we integrated all the data types to assign genes functional states and identified gain of function and loss of function genes that likely contribute to myeloma pathogenesis.
Ben Derman, Assistant Professor at the University of Chicago, shared this post on X adding:
“Great thread below; so much interesting data that will take a while to truly comprehend. One takeaway is explanation for the heterogeneity in outcomes w/ 1q gain. I err on the side of calling it a high risk abnormality but upcoming hi risk definition will help to further clarify.”
Read Further.
Source: Jonathan Keats/X and Ben Derman/X
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