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Vol. 26, Art. 4 (pp. 68-95)    |    2025       

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Features of the molecular landscape of multiple myeloma

Chebykin D.A.1, Motorin D.V.1, Semenova N.U.1, Motyko E.V.1, Kirienko A.N.1, Kustova D.V.1, Garifullin A.D.1, Bessmeltsev S.S.1,2, Sidorkevich S.V.1, Martynkevich I.S.1

1Russian Research Institute of Hematology and Transfusiology, Federal Medical and Bilogical Agency, 16 2-ya Sovetskaya str., Saint Petersburg, Russian Federation, 191024, Tel.: +7 (812) 309-79-81; e-mail: bloodscience@mail.ru
2Federal State Budgetary Institution of Higher Education "North-Western State Medical University named after I.I. Mechnikov" of the Ministry of Health of the Russian Federation
email:bessmeltsev@yandex.ru

Brief summary

Significant advances in the diagnosis and treatment of multiple myeloma (MM) have appreciably improved survival rates, but it has not been possible to exclude MM from the list of incurable diseases yet. The results of sequencing a panel of genes by means of the NGS make it possible not only to determine the prognosis, but also, thanks to the accumulation and systematization of data, the detection of new mutations, contribute to a deeper understanding of the pathogenesis of MM and the development of new targeted drugs. The aim of the work. Studying the prognostic significance of gene mutations in patients with MM using NGS analysis. Materials and methods. All patients underwent mutation screening using an NGS panel of probes for 118 genes. The patient's DNA was analyzed on the NextSeq Illumina platform by means of paired-end reading. To determine the prognostic significance of all mutations found in each patient, the tumor mutational burden (TMB) was calculated, which was defined as the number of mutations per 1 megabase (Mb) of the coding sequence. The median TMB was 5.0 mutations/Mb. Results. The study was conducted in 44 patients aged from 38 to 81 years old (median age 60 years old). The median follow-up was 32.8 months with a maximum follow-up period of 13 years. Among all the identified mutations, mutations in the NRAS, FAT 1 and ATM genes had an adverse effect on the course of MM. Three-year OS in the group with high TMB (≥ 6,63) was 42.8% (95% CI: 22.6-81.0), in patients with low ТМВ (< 6.63) -76,7% (95% ДИ: 22.6-81.0), р = 0,041 Conclusion. Mutations in the NRAS, FAT 1 and ATM genes had an adverse effect. It has been established that a high tumor mutational burden is a significant negative prognostic factor in patients with MM. The presence of at least one pathogenic mutation worsens the prognosis of patients with MM


Key words

multiple myeloma; chromosome rearrangements; mSMART; new generation sequencing

Reference list

1. Treon S., Xu L., Yang G. et al. MYD88 L265P somatic mutation in Waldenstrom’s macroglobulinemia. N Engl J Med. 2012; 367(9): 826-833. https://doi.org/ 10.1056/ NEJMoa1200710.


2. Bolli N., Biancon G., Moarii M. et al. Analysis of the genomic landscape of multiple myeloma highlights novel prognostic markers and disease subgroups. Leukemia. 2018; 32(12): 2604-2616. https://doi.org/10.1038/s41375-018-0037-9.


3. Raab M., Lehners N., Xu J. et al. Spatially divergent clonal evolution in multiple myeloma: overcoming resistance to BRAF inhibition. Blood. 2016; 127(17): 2155-2157. https://doi.org/10.1182/blood-2015-12-686782.


4. Paiva B., Vidriales M., Almeida H. i dr. Ocenka effekta lecheniya pri mnojestvennoi mielome: klinicheskoe znachenie monitoringa MOZ. Immynologiya gemopoeza. 2012; 10(1): 34-77.


5. Semenova N.U., Bessmelcev S.S., Rygal V.I.  Biologiya nishi gemopoeticheskih stvolovih kletok. Klinicheskaya onkogematologiya. Fyndamentalnie issledovaniya i klinicheskaya praktika. 2014; 7(4): 501-510.


6. Perroud C., Thurian D., Andres M. et al. Effect of MAPK activation via mutations in NRAS, KRAS and BRAF on clinical outcome in newly diagnosed multiple myeloma. Hematol Oncol. 2023; 41(5): 912-921. https://doi.org/10.1002/hon.3208.


7. Jelinek T., Zihala D., Sevcikova T. et al. Beyond the marrow: insights from comprehensive next-generation sequencing of extramedullary multiple myeloma tumors. Leukemia. 2024; 38(6): 1323-1333. https://doi.org/10.1038/s41375-024-02206-w.


8. Morawska M., Kiełbus M., Paziewska M. et al. Mutations of ARID1B, PIK3C2B, KMT2B, and FAT1 genes influence clinical outcome in newly diagnosed myeloma. Cancer Genet. 2024; 118(125): 288-289. https://doi.org/10.1016/j.cancergen.


9. Rizvi N., Hellmann M., Snyder A. et al. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer. Science. 2015; 348(6230):124-128. https://doi.org/10.1126/science.aaa1348.


10. Solovev M.V., Mendeleeva L.P., Alekseeva A.N. i dr. Effektivnost terapii mnojestvennoi mielomi v Rossii (rezyltati mnogocentrovogo prospektivnogo issledovaniya). Gematologiya i transfyziologiya. 2020; 65(1): 103-104.


11. Jimenez-Zepeda V. H., Neme-Yunes Y., Braggio E. Chromosome abnormalities defined by conventional cytogenetics in plasma cell leukemia: What have we learned about its biology? Eur. J. Haematol. 2011; 87(1): 20-27.


12. Chesi M., Nardini E., LimR. S. et al. The t(4;14) translocation in myeloma dysregulates both FGFR3 and a novel gene, MMSET, resulting in IgH/MMSET hybrid transcripts. Blood. 1998; 92(9): 3025-3034.


13. Bergsagel P., Kuehl W., Zhan F. et al. Cyclin D dysregulation: an early and unifying pathogenic event in multiple myeloma. Blood. 2005; 106(1): 296-303.


14. Brito J., Walker B., Jenner M. et al. MMSET deregulation affects cell cycle progression and adhesion regulons in t(4;14) myeloma plasma cells. Haematologica. 2009; 94(1): 78-86.


15. Shaughnessy J., Zhan F., B. Burington B. et al. A validated gene expression model of high-risk multiple myeloma is defined by deregulated expression of genes mapping to chromosome 1. Blood. 2007; 15: 2276-2284.


16. Denicourt C., Saenz C., B. Datnow B. et al. Relocalized p27Kip1 Tumor Suppressor Functions as a Cytoplasmic Metastatic Oncogene in Melanoma. Cancer Res. 2007; 67(19): 9238-9243.


17. Zhang Y. CKS1B (CDC28 protein kinase regulatory subunit 1B). Atlas Genet Cytogenet Oncol. Haematol. 2011; 14(7): 676-678.


18. Chang H., Jiang N., Jiang H. et al. CKS1B nuclear expression is inversely correlated with p27Kip1 expression and is predictive of an adverse survival in patients with multiple myeloma. Hematologica. 2010; 95(9): 1542-1547.


19. Kargin V.D., Soldatenkov V.E., Kapystin S.I. i dr. Geneticheskie markeri i biohimicheskaya harakteristika komorbidnosti y bolnih gemofiliei, associirovannie s oksidativnim stressom. Medline.ru. 2017: 18(22): 362-381.

Журнал основан 16 ноября 2000г.
Выдано Министерством РФ по делам печати, телерадиовещания и средств массовых коммуникаций

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