smoldering multiple myeloma
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Cells ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 130
Author(s):  
Tyler Lussier ◽  
Natalie Schoebe ◽  
Sabine Mai

Smoldering multiple myeloma is a heterogeneous asymptomatic precursor to multiple myeloma. Since its identification in 1980, risk stratification models have been developed using two main stratification methods: clinical measurement-based and genetics-based. Clinical measurement models can be subdivided in three types: baseline measurements (performed at diagnosis), evolving measurements (performed over time during follow-up appointments), and imaging (for example, magnetic resonance imaging). Genetic approaches include gene expression profiling, DNA/RNA sequencing, and cytogenetics. It is important to accurately distinguish patients with indolent disease from those with aggressive disease, as clinical trials have shown that patients designated as “high-risk of progression” have improved outcomes when treated early. The risk stratification models, and clinical trials are discussed in this review.


2021 ◽  
Author(s):  
Mark Bustoros ◽  
Shankara Anand ◽  
Romanos Sklavenitis-Pistofidis ◽  
Robert Redd ◽  
Eileen M. Boyle ◽  
...  

AbstractSmoldering multiple myeloma (SMM) is a precursor condition of multiple myeloma (MM) with significant heterogeneity in disease progression. Existing clinical models of progression risk do not fully capture this heterogeneity. Here we integrated 42 genetic alterations from 214 SMM patients using unsupervised binary matrix factorization (BMF) clustering and identified six distinct genetic subtypes. These subtypes were differentially associated with established MM-related RNA signatures, oncogenic and immune transcriptional profiles, and evolving clinical biomarkers. Three subtypes were associated with increased risk of progression to active MM in both the primary and validation cohorts, indicating they can be used to better predict high and low-risk patients within the currently used clinical risk stratification model.


Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 545-545
Author(s):  
Anil Aktas-Samur ◽  
Mariateresa Fulciniti ◽  
Sanika Derebail ◽  
Raphael Szalat ◽  
Giovanni Parmigiani ◽  
...  

Abstract On an average, 1% of monoclonal gammopathy of undermined significance (MGUS) and 10% of smoldering Multiple Myeloma (SMM) progress to symptomatic MM every year within the first five years of diagnosis. The probability of progression significantly decreases for SMM patients after first 5 years. However, a distinct subset of SMM patients progress within 2 years and are re-classified as high-risk patients based on risk markers such as 20/2/20 or certain genomic features. Although recent studies have evaluated the high-risk genomic features for SMM but genomic background of SMM patients who do not progress to MM after long-term follow-up (>= 5 years) has not been described. Here, we evaluated transcriptomic and genomic changes enriched in non-progressor (NP) (no progression after 5 years of follow-up) precursor conditions (N=31) with those progressed within short period of time (N=71) and compared them with changes observed in newly diagnosed MM (N=192). Additionally, using transcriptome, epigenome and whole genome profiling we also studied additional unique samples from 18 patients at their precursor stage as well as when progressed to MM. Overall, we have observed significantly lower mutational load for NP SMM from progressor SMM (median SNV 4900 vs. 7881 p < 3e-04) with high sensitivity (0.83) and specificity (0.65) to separate NP from progressors. We have further developed a deep learning model by using more than 4500 genome wide features using ten-fold cross validation. This model indicated that not only the load but also the patterns of mutations (type, location, frequency) are different between two conditions. We also found that NP samples have significantly lower heterogeneity (p < 0.05). However, progressed samples showed similar mutational load and heterogeneity at precursor stage and MM. Among CNA differences, absence of gain or deletion of chr8 (not involving MYC region) were strong predictor of NP (OR=7.2 95% CI 2.2-24). Focal genomic loss was also significantly lower for NP (p=0.004) which was also reflected by low genome scar score (GSS) (p=0.07). Structural variant and copy number signature analysis also showed that NPs were showing significantly low exposure to non-clustered variable size genomic deletions. We observed similar frequency of primary translocations [t(11;14), t(4;14), and t(14;16)] in both progressor and NP samples as well as newly diagnosed MM. MYC translocation with any partner was not observed in NP samples, whereas 37% of progressor samples had a MYC translocations (OR=12.8). Adding all these differences including chr8 CNAs, MYC translocations, mutation burden, GSS, focal deletions, all driver mutations as well as primary translocations into recursive partitioning model to predict non-progressor SMM, we have identified a simple genomic model only involving chr8 CN changes and overall mutational burden to achieve a high sensitivity (0.82) and specificity (74%). Our transcriptomic analysis measured the distance between progressor and NP SMM as well as MM and found that NP SMM has greater difference with MM which is closer to progressor SMM. We quantified transcriptomic heterogeneity by using molecular degree of perturbation. This analysis showed that consistent with DNA changes, DNA repair pathway and MYC target genes are expressed similarly in NP SMM as in normal plasma cells compared to progressor SMM. Epigenomic analysis yielded 75 SEs regions differentially utilized between precursor and symptomatic MM stage using paired samples. The targeted genes included BMP6, PRDM1, STAT1, SERTAD2 and RAB21 and possibly regulating genes related to oncogenic KRAS activities. In conclusion, we define genomic characterization of non-progressor SMM and our results now provide the basis to develop molecular definition of SMM as well as risk driving features. Disclosures Munshi: Janssen: Consultancy; Pfizer: Consultancy; Legend: Consultancy; Novartis: Consultancy; Adaptive Biotechnology: Consultancy; Oncopep: Consultancy, Current equity holder in publicly-traded company, Other: scientific founder, Patents & Royalties; Takeda: Consultancy; Abbvie: Consultancy; Karyopharm: Consultancy; Amgen: Consultancy; Celgene: Consultancy; Bristol-Myers Squibb: Consultancy.


2021 ◽  
Vol 11 (11) ◽  
Author(s):  
Alissa Visram ◽  
S. Vincent Rajkumar ◽  
Prashant Kapoor ◽  
Angela Dispenzieri ◽  
Martha Q. Lacy ◽  
...  

AbstractThe Mayo-2018 smoldering multiple myeloma (SMM) risk score is used routinely in the clinical setting but has only been validated at diagnosis. In SMM patients, the progression risk decreases over time. However, the utility of applying risk stratification models after diagnosis is unknown. We retrospectively studied 704 SMM patients and applied the Mayo 2018 and IMWG-2020 risk stratification models at annual landmark timepoints up to 5 years post diagnosis. The Mayo-2018 and IMWG-2020 models reliably stratified patients based on progression risk when applied post diagnosis. The respective 2-year progression risk in Mayo-2018 high risk patients versus IMWG-2020 intermediate-high risk patients was 51% versus 62% at the 1-year landmark and 47% versus 45% at the 4-year landmark. We showed that patients categorized at Mayo-2018 high-risk at follow-up had a similar risk of progression if the baseline risk assessment was low-intermediate versus high-risk (HR 1.04, 95% CI 0.46–2.36, p = 0.931 at 5-year landmark). Patients migrating to a higher risk category during follow up had a higher progression risk compared to patients with stable/decreased risk categorization. Our findings support the use of these risk scores post-diagnosis and suggest that patients evolving to a high-risk category may benefit from early intervention therapeutic approaches.


Author(s):  
Rim Rakez ◽  
◽  
Areej Chefaii ◽  
Rym Hadhri ◽  
Mouna Bahrini Sassi ◽  
...  

Immune thrombocytopenic purpura is an autoimmune disorder retained after elimination of other causes of low platelets’ rate. It is mostly seen with B cell lymphoproliferative disorders. Immune thrombocytopenic purpura’s association with plasma cell neoplasms is possible but extremely rare. Although several pathophysiological mechanisms have been proposed, the causal link between these two conditions is not yet clearly understood. Therapeutic management is not standardized and depends mainly on the type of gammopathy and the chronology of onset of immune thrombocytopenic purpura compared to multiple myeloma. Our case is about an 81-year-old male diagnosed with concurrent smoldering multiple myeloma and immune thrombocytopenic purpura who was started on steroids without anti-neoplastic therapy for multiple myeloma with partial platelet response. We also review the few reported cases of simultanious immune thrombocytopenic purpura and smoldering multiple myelom or multiple myeloma. Keywords: ITP; thrombocytopenia; smoldering multiple myeloma; corticosteroids.


2021 ◽  
pp. 1-12
Author(s):  
Laly Nsiala ◽  
Arthur Bobin ◽  
Anthony Levy ◽  
Cécile Gruchet ◽  
Florence Sabirou ◽  
...  

2021 ◽  
pp. 1-14
Author(s):  
Brooke N Learned ◽  
Wazhma Nasiri-Ahad ◽  
James E Davis ◽  
Alpa G Desai ◽  
Alan Chang

2021 ◽  
Vol 21 ◽  
pp. S111
Author(s):  
Laura Notarfranchi ◽  
Rosanna Vescovini ◽  
Roberta Segreto ◽  
Sabrina Bonomini ◽  
Paola Storti ◽  
...  

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