1/ 🧵Check out our new study in @NatureGenet, which examines how precancerous conditions (MGUS/SMM) evolve into Multiple Myeloma, and offers new computational methods to predict progression risk and model cancer evolution. https://t.co/IHnN87QKTk

Genomic Landscape of Multiple Myeloma and Its Precursor Conditions - Jean-Baptiste Alberge (@JbAlberge) @NatureGenet @CancerWorldmag https://t.co/ROZL6i4ZGP #OncoDaily #Oncology #Cancer #Health #Medicine #MedTwitter #MedEd #MedOnc #MedNews #MulripleMyeloma

12/ 📣 Huge thanks to the international team behind this work, led by @ghobrial_lab & @getz_lab. Fantastic collaboration with @ankitkdutta @andreapoletti19, and many others across institutions @DanaFarber @broadinstitute 🇫🇷🇦🇺🇮🇹🇳🇱🇨🇦🇩🇪🇬🇧🇬🇷🇺🇸 🔗 https://t.co/IHnN87QKTk 🧵/End

11/ 💡 Final takeaways: Our study: ✔ Builds a genomic timeline of MM development ✔ Provides a predictive MM-like score ✔ Reveals new driver mutations (and new computational methods to discover them) ✔ Supports genomic characterization and risk stratification using WGS

10/ 🧬 Clinical relevance: The "MM-like score" could inform who needs closer monitoring or even early treatment. In our opinion, WGS (and WGS-based risk tools) are also ready to replace FISH and could be assessed repeatedly using liquid biopsies

9/ 👾 We also used for the first time another new computational method, "SVelfie", to discover significant driver genes in structural variants @XLoinaz17004 https://t.co/2vLFbZ79mV

8/ 📌 Another key insight: The order of genetic events matters. Some events (e.g., MYC gains, del(12)) occur late and are stronger predictors of progression with our new implementation of the Bradley-Terry model "TiMMing" @andreapoletti19 @Unibo

7/ 🧪 We characterized *where* and *when* mutational processes emerge (clock-like and AID, normal biology in early stages versus APOBEC & ROS, cancer-like stress in later stages), including in regulatory and structural variant regions

6/ ⏳ We also estimated the tumor’s age (how long ago it began) and found that tumors in stable patients are "younger", while tumors in patients who later progressed are already ~30 years of age at diagnosis

5/ 📈 The MM-like score increases in patients who later progressed and was validated in 2 cohorts. Clinically, a higher score = higher risk of transformation

4/ 📊 We introduce the "MM-like score", a genomic risk score derived from WGS data. It reflects how far a patient's tumor has progressed along the path to MM; a stepwise model of evolution we name "ladder-climbing."

3/🔬 We identified >100 significant genetic drivers across cancer stages, including mutations in known MM players (FAM46C, DIS3, SP140), new candidates (IKZF3, IKBKB), non-coding elements (ILF2 promoter), and structural variants (TRAF3/AMN)

2/❗Multiple Myeloma is preceded by precursor asymptomatic stages like MGUS and smoldering MM (SMM). But predicting who will progress remains a challenge. In our study, we analyzed > 1,000 genomes to map the evolution of precancers —both genetically and over time.

Spread the word! Registration for the "Mutations in Time and Space" conference is open. The meeting is all about the origins, patterns, and consequences of mutations across cells, individuals, populations, species. Abstract submission deadline: Jan 17th https://t.co/KMEHdXnLMQ...

Check out our new article in @NatureRevCancer where we take a deep dive into early myeloma and discuss the potential of T cell-redirecting therapies! https://t.co/AXODimd1OQ @IrenemGhobrial @JbAlberge @LucaBertamini and Rosa Toenges @DanaFarberNews #mmsm

Fantastic news and congrats!!!

So thrilled to be a part of @NCIHTAN! Looking forward to exciting collaborations and projects in the spatial field!

One of many benefits being a researcher is making friends with highly talented people and visiting them around the world. Last weekend was a blast! Thanks and congrats to @LucaBertamini! With @JbAlberge

Check out our new study in @NatureMedicine looking at nonrelapse mortality after CAR-T cell treatment with Tobias Tix and @KRejeski https://t.co/36tDpkwg3S

Very excited to release Sequoia, our pipeline for phylogenetic tree reconstruction from mutations in normal cells. A detailed description is now published in @NatureProtocols!