In the 1960-1970s two giants, Dr. Waldenström and Dr. Kyle debated the role of serum proteins in asymptomatic individuals, and whether they were linked to myeloma, or not (2/18)
After its first description by Dr Waldenström as “benign monoclonal gammopathy”, in 1978, Dr Kyle proposed the terminology MGUS, which allowed the field to move forward together and to acknowledge the risk of progression to myeloma was undetermined for individual patients (3/18)
Thanks to the advent of NGS our group and others (@Leif_Bergsagel@IreneGhobrial@MarkBustoros@DrGarethMorgan1) have shown that certain myeloma defining genomic events are associated with myeloma precursor progression. PMID: 31439946, 30135448, 32442065, 28550183 (4/18)
However, these studies were characterized by two main limitations: 1) they were mostly based on exome/targeted sequencing and hence not able to fully capture all myeloma defining genomic events; 2) they were focused mostly on smoldering myeloma (SMM) not MGUS. (5/18)
The reason why MGUS has not been included in previous WGS studies is the fact that standard WGS assays require >100,000s abnormal plasma cells to generate valid data (6/18)
To circumvent these limitations together with Peter Campbell and @BenedithOben
we leverage the low input WGS approach developed at the @sangerinstitute: rdcu.be/chslW (7/18)
Interestingly, we did not observe any significant quality difference between low input and standard WGS, suggesting that this new platform can be used in cancer genomic studies designed to characterize low levels of disease (8/18)
WGS allows the characterization of four main features: 1) mutational signatures; 2) driver mutations; 3) aneuploidies; and 4) structural variants/complex events. For each of these, we observed striking differences between stable and progressive myeloma precursor conditions (9/18)
Canonical APOBEC mutational activity (APOBEC3A:3B ~1) was not detected among stable precursors. In contrast, ~80% of multiple myeloma and progressive precursors condition had it. (10/18)
Driver mutations were rarely observed among stable precursors, confirming that the mutational landscape of stable myeloma precursor condition is significantly different in comparison to progressive myeloma precursor condition and multiple myeloma (11/18)
Stable myeloma precursor conditions have a lower prevalence of recurrent aneuploidies such as gain1q, del6q, del8p, gain8q24, and del16q. In contrast, progressive precursors did not show any difference compared to multiple myeloma (12/18)
Stable myeloma precursor conditions rarely have structural variants, chromothripsis, and templated insertions. On the contrary, progressive myeloma precursor conditions and multiple myeloma have the same prevalence (13/18)
Stable myeloma precursor conditions had a significantly different temporal pattern, in which multi-gain events occurred later in the patient’s life (median 53.5 y) compared to progressive myeloma precursor conditions (median 28 y) and multiple myeloma (median 20.5 y) (14/18)
In conclusion, we showed that using myeloma defining genomic events we can easily distinguish stable (or "benign") from progressive myeloma precursor conditions independently from the disease burden (15/18)
Using our novel approach, we are able to identify “myeloma-to-be cases” versus “stable cases” among groups of individuals with a current diagnosis of MGUS or smoldering myeloma (16/18)
The World Trade Center (WTC) attack of September 11, 2001 created an unprecedented environmental exposure to known and suspected carcinogens.
In 2019 @DrOlaLandgren together with @FDNY showed a high incidence of MM and precursors among first responders to the WTC disaster (2/10)
Using whole genome sequencing (WGS) it is possible to define which are the main mutational processes (i.e., mutational signatures) active in each patient. We recently identified 7 main mutational signatures in newly diagnosed MM rdcu.be/cemZN (3/10)
In 2020 with @DrOlaLandgren we revealed how Melphalan has strong mutagenic activity on myeloma cells. This can understandably create fear for patients who have undergone transplant, and we have received many questions from them. Here a thread on what we know so far #msmm 👇👇👇
Using whole-exome and genome sequencing data, we can capture the majority of mutations in cancer. Using bioinformatic algorithms we can identify and quantify which mutational processes are involved and responsible for this catalog of mutations (i.e. mutational signatures)
Can we define stable versus progressive myeloma precursor conditions (ie MGUS and smoldering multiple myeloma)? Check out our last preprint: biorxiv.org/content/10.110…#mmsm. Tweetorial 👇👇👇👇
Multiple myeloma (MM) is consistently preceded by the asymptomatic expansion of clonal plasma cells, (ie MGUS or SMM). These precursor conditions are found in 2-3% of the general population aged older than 40 years. Only a small fraction of these will ultimately progress to MM.
The differentiation between progressive and stable precursor condition (SMM and MGUS) represents one of the most important unmet clinical need in the multiple myeloma community. Recently important studies highlighted distinct genomic drivers associated with SMM progression