Myeloma Genomics and Microenvironment and immune profiling

Comparative Genomic Analysis of Active Multiple Myeloma and Monoclonal Gammopathy of Uncertain Significance Using Single Nucleotide Variants Microarray

P-213: Comparative Genomic Analysis of Active Multiple Myeloma and Monoclonal Gammopathy of Uncertain Significance Using Single Nucleotide Variants Microarray

Wednesday, September 25, 2024

David Garrido, MD

Hematology fellowship
Hospital de Clínicas Dr. Manuel Quintela
Montevideo, Montevideo, Uruguay

Introduction: Monoclonal gammopathy of uncertain significance (MGUS) is a premalignant condition that may progress to diverse neoplasms or monoclonal gammopathies, with active multiple myeloma (MM) being the most frequent

Aims: To analyze the differences of single nucleotide variants (SNVs) frequencies between MGUS and MM patients by microarray genomic analysis, and its discriminatory capability.

Methods: An analytic and retrospective study of 56 MM patients (median age 57 years, 43.8% females; subtypes IgG 59.3%, IgA 23.4%, others 17.3%; risk staging ISS-1 31.2%, ISS-2 37.5%, and ISS-3 31.3%) and 14 MGUS (71.4% females, median age 65.5 years; subtypes 64.3% IgG, 28.6% IgA, and 7.1% IgM) was performed. Genomic DNA was purified from peripheral blood or bone marrow cells by conventional methods. SNVs were analyzed using the Illumina Infinium GSA on the Illumina iScan Platform which contains 654,027 markers. Binary Discriminant Analysis (BDA), Random forest (RF), Principal Components Analysis (PCA), and k-means clustering were employed. Hg19 genome was used as reference

Results: Upon several filtering steps, 103,942 SNVs were obtained. Of those, 251 across 193 genes were significant using the BDA algorithm and satisfactorily clustered MM and MGUS through PCA (Dim1 16.9%, Dim2 4.5%). Among these SNVs, 52 were more prevalent in MM, involving genes related to various cellular components, molecular functions, and biological processes by Overrepresentation Analysis of GO pathways. More frequent MM-associated SNVs included CFAP74 rs2803337, FAF1 rs3827730, FSTL1 rs1147696, SORCS2 rs2285778, ARHGEF37 rs4409073, UST rs9390613, NUGGC rs7840091, MMRN2 rs746677, TRPC6 rs4326755, ATP10A rs6576456, UST rs10457838, SGF29 rs4788073, and PCP4 rs9983735. On the other hand, more frequent MGUS associated SNV included OR2W5 rs10925061, PADI2 rs11588995, ATP8B4 rs12915207, KCNN2 rs1487228, ECE1 rs213019, ATP8B4 rs28706888, PGAP6 rs763146, RC3H1 rs80205789. The top ten SNVs by the RF selection were: KIAA1614 rs17302207, ALPK2 rs9967112, TMEM132C rs117202260, NOTCH1 rs10870078, and MYO5B 17714688, MYOD1 rs71484784, ITGA9 rs76052815, ROS1 rs13201929, PLXNA2 rs72739456, and SHISA9 rs153096, with 80% of them being associated with cancer risk or tumoral progression

Conclusions: In summary, our study underscores the potential role of extensive SNV genotyping in distinguishing between MGUS and MM. We observed distinct SNV patterns indicating potential associations with prognostic biomarkers for susceptibility to MM progression, based on genes involved and their biological functions. These findings have implications for personalized therapeutic strategies in clinical practice. Further research is warranted to elucidate the underlying molecular mechanisms and validate the clinical utility of these SNVs in MM management.

Funding. IMS and The Paula and Rodger Riney Foundation