Linda B. Baughn

@theMMRF @MMRFTeam4Cures An incredible experience. 30 miles of hiking with new friends. The best part: the team raised $75K for MM research! So grateful for the opportunity @GD_251

Excited to have participated in the 2026 AACR cancer disparities progress report. A lot of progress has been made especially in narrowing the mortality gap, but more work is needed. @AACR @MayoCancerCare cancerprogressreport.aacr.org/wp-content/upl…

@VincentRK @FrancescoMaura4 @MayoClinic @MSKCancerCenter @nyulangone @SylvesterCancer I suspect it is an interaction effect between germline variants x environment x immune response x infection and possibly other factors.

Exactly. The reason for the disparity is that certain not all people of African ancestry seem to get it far more frequently than White people and at much younger ages. That has not been studied as to why it happens. Based on the studies we have done this genomic MGUG (clonal premalignancy) is most likely driven by some genetic factor rather than environmental. Once the MGUS is established, the driver for who and when and how genomic / and overt myeloma (malignancy) develops is not driven by ancestry. And that’s what your paper shows.

Our new study from the Polyethnic-1000 initiative is out! We investigated how genetic ancestry relates to multiple myeloma biology and outcomes. Several interesting and potentially provocative findings. Great collaboration @MayoClinic @MSKCancerCenter @nyulangone @SylvesterCancer

Great seeing all of you!

Super cool study. A good reason not to fast.

@Rfonsi1 @RahulBanerjeeMD This could help 😀pmc.ncbi.nlm.nih.gov/articles/insta…

I invite any smart and courageous MM doctor to interpret this FISH result. @RahulBanerjeeMD, your efforts will pay off one day!

Thrilled about this collaborative project evaluating venetoclax response in the myeloma subtype I’m so curious about-t(11;14). Grateful to all of the collaborators included here.

@mehndz @RahulBanerjeeMD @VincentRK @OncBrothers @BijoyTelivala @rajshekharucms @Myeloma_Doc 20% is the technical cutoff- determined by the lab. If result is < 20%, you can’t say a result is “positive”. <20% is within the “normal range” because by FISH you can random lost, gained, overlapped signals etc similar to other assays. Assay “noise.”

@RahulBanerjeeMD @VincentRK @OncBrothers @BijoyTelivala @rajshekharucms @Myeloma_Doc @lbaughn I was about to say the same thing, this is gain of 17. It is so difficult to Interpret these reports and then they have a cut of value towards it of 20%; what does that even imply? 😮

@VincentRK @OncBrothers @rajshekharucms 75 M-recurrent ITP with plt going down to10. Has needed Dex/R (last dose6 mths ago) Light chain ratio 10. Small M spike- stablish for 5-6 yrs BM Bx 5-10 % plasma cells FISH p53+ Pet neg I was going to observe , but i am worried about p53

@RahulBanerjeeMD @VincentRK @OncBrothers @BijoyTelivala @rajshekharucms @Myeloma_Doc Good call Rahul. Agree likely trisomy 17. Curious if case is hyperdiploid with a possible trisomy 11 and 17 since they found gain of TP53 and CCND1. NOT tp53 del.

@VincentRK @OncBrothers @BijoyTelivala @rajshekharucms @Myeloma_Doc Agreed with Vincent – I’ll also add that the FISH report is the phenomenon that @lbaughn and others have been working on fixing – clearly work left to be done. That report shows trisomy 17 instead of del(17p), and it’s so hard for anyone to notice unless you really look!

Standardizing FISH testing in myeloma is critical to reduce lab to lab variability and misinterpretation. We propose guidelines for FISH panel design and reporting to align with the new IMS/IMWG risk stratification. @CG_Consortium @MayoMyeloma

@RenoHemonc @AuclairDan Commercial labs like Mayo will be reporting mono and biallelic 1p. This information would also be in the cytogenetics nomenclature in commercial lab reports. Mono del=x1, biallelic del=x0

@AuclairDan Are commercial labs like Neo reporting mono vs biallelic?

Important paper. Note slight tweaks since it was first presented last year #mmsm

We will also be providing recommendations to other labs on how to perform and interpret to meet the IMS/IMWG definition with a publication led by @lbaughn in @BloodCancerJnl shortly. Stay tuned.

We’re hiring! Postdoc in Computational Genomics at @EdinUni_IGC Focus: myeloma genome, structural variants, heterochromatin, multiomics Deadline: 9 July 2025, 23:59 GMT Apply here: elxw.fa.em3.oraclecloud.com/hcmUI/Candidat… #myeloma #postdoc #genomics #bioinformatics #epigenetics #codeandkilts

Visualize genomic data with ease using gggenomes, an R package that extends ggplot2 to handle and display genomic information intuitively. Whether you’re comparing genomes, analyzing features, or showcasing synteny, gggenomes provides the tools you need to turn complex genomic data into clear, informative visualizations. Why use gggenomes? ✔️ Genomic-focused visualizations: Specifically designed for handling genomic data, including features, alignments, and comparative analysis. ✔️ Versatile and modular: Create detailed and layered plots for diverse genomic scenarios with flexibility for customization. ✔️ Built on ggplot2: Leverages ggplot2’s familiar framework, making it easy for users to adapt and enhance their visualizations. The example visualization shown here is taken directly from the gggenomes GitHub repository, demonstrating how it transforms genomic data into compelling plots: github.com/thackl/gggenom… Curious to learn more about creating data visualizations in R and using tools like ggplot2 and its extensions? Check out my online course, "Data Visualization in R Using ggplot2 & Friends!" Take a look here for more details: statisticsglobe.com/online-course-… #datascienceeducation #Statistical #datastructure #RStats

A recently published paper supports the reporting of these unbalanced MYC-R as positive. Nice to see additional support for unbalanced MYC-R as being real abnormalities sciencedirect.com/science/articl…

We propose interpreting unbalanced MYC-r by FISH in HGBCL as “likely positive”. I hope future testing will incorporate WGS and/or RNA seq.

FISH testing for MYC is part of routine clinical evaluation for high grade B-cell lymphomas. We showed a high false negative rate for the MYC break apart FISH probe (4%) or the MYC/IGH probe (22%). Thus, FISH will not detect all MYC rearrangements in B-cell lymphomas.

@RahulBanerjeeMD @bbehin Agree on del 17p. I would also suggest other high risk abnormalities like 1p del, 1q gain or amplification. If enough sample exists IGH break apart. If abnormal, t(4;14).

It’s an excellent question! I’ll defer to @lbaughn for a more nuanced answer, since I actually don’t know how carefully this has been addressed. I’d suggest del(17p) as the most important test to triage, but I’m not sure if a consensus exists here - if not, we should make one!

The future of FISH reporting in #MMsm is almost here thanks to great work by @lbaughn and the consensus panel she has assembled for this important topic!

The MMRF Immune Atlas team describes immune cells & clinical outcomes in myeloma. Emory, Beth Israel, WUSTL, MSSM, Mayo & MMRF profiled >1.1 million marrow cells from CoMMpass patients. Preprint at biorxiv.org/content/10.110… has details. #myeloma

@RahulBanerjeeMD @adamssperling @alex_epi_tria *interpret

@RahulBanerjeeMD @adamssperling @alex_epi_tria One question is how to intercept a “relative TP53 loss” (2 copies of TP53) in the context of a trisomy 17. Is this worse than 3 copies of TP53?

In contrast, shout out to Neogenomics for this EXCELLENT myeloma #MMsm FISH report 👏 3 copies of the probes on 17p and 17q? Throw in a “trisomy 17” into the report and clearly say that del(17p) was not detected. Hopefully this type of report will become the norm!

@MyelomaAmateur @RahulBanerjeeMD @alex_epi_tria Some trisomies can be present from birth like trisomy 21. In this context however, these trisomies are acquired in the MM clone. Great questions Kate.

@RahulBanerjeeMD @alex_epi_tria @lbaughn Are these trisomies acquired or present from birth?