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Letters to the Editor
Heterogenous mutation spectrum and deregulated cellular pathways in aberrant plasma cells underline molecular pathology of light-chain amyloidosis
Light-chain (AL) amyloidosis (ALA) is a rare but fatal monoclonal gammopathy (MG) causing organ and tissue damage resulting from the deposition of misfolded immunoglobulin free light chains in the form of amyloid fibrils.1 In some cases, ALA coexists with multiple myelo- ma (MM) (ALA+MM), which is the second most com- mon blood cancer and is caused by the proliferation of clonal plasma cells (PC).2 Due to insufficient knowledge of ALA and ALA+MM biology, therapeutic options have mirrored treatment regimens of MM, which focus on the elimination of clonal PC.3,4 We investigated the mutation and gene expression profiles in clonal aberrant PC (aPC) in order to better understand ALA and ALA+MM etiolo- gy and to clarify the molecular differences between indi- vidual MG diagnoses.
In order to address this, we analyzed 14 newly diag- nosed (untreated) histologically proven ALA samples, 11 ALA+MM samples and 37 MM samples. All ALA+MM and MM samples manifested at least one myeloma-defin- ing event. We isolated DNA and/or RNA from clonal bone marrow PC sorted using CD45-PB, CD38-FITC, CD19-PECy7 and CD56-PE fluorescent antibodies. Samples of frozen aPC from 12 ALA, 10 ALA+MM and 29 MM were subjected to whole genome amplification (WGA) using REPLI-g Mini Kit (Qiagen) employing mul- tiple displacement amplification. Amplified DNA and DNA from peripheral blood (for exclusion of germline variants) served for exome library preparation and sequencing (median coverage 56x, Online Supplementary Table S3). RNA was transcribed from six ALA, four ALA+MM and eight MM newly diagnosed patients and hybridized on GeneChip Human Gene 1.0 ST Array. Detailed methods and patient’s characteristics are pre- sented in the Online Supplementary Appendix and the Online Supplementary Tables S1, S8. Four ALA and three ALA+MM samples were used for both the exome and the transcriptome analysis in parallel.
We evaluated only single-nucleotide variants (SNV) due to the potential bias in indels and copy number vari- ations (CNV) introduced by the WGA method.5 Median numbers of non-synonymous exonic SNV that passed “effect” filters for ALA, ALA+MM, MM cohorts were 16.5, 20.5 and 23, respectively, and the mutation burden was similar across all three cohorts, median 1.36 SNV per megabase (Mb) (range: 0.28-5.86) (Figure 1A, Online Supplementary Table S2). The mutation burden did not significantly correlate with age in ALA or MM. For ALA+MM the test was not performed due to the lack of age information of some patients. The intra-sample analysis of clonality was performed in samples exceeding 30 unfiltred non-synonymous SNV and coverage ≥10X in copy number neutral regions. The results were available for 10 ALA, nine ALA+MM and 29 MM patients. Of those, only one clone was observed in one ALA, two ALA+MM, and three MM samples (Online Supplementary Table S1). MM samples in our analysis were composed of a higher number of subclones when compared to ALA and ALA+MM, though the difference was not statistical- ly significant (Figure 1B). The median number of sublones for ALA and ALA+MM remained four sub- clones per sample, while the median for MM was five subclones per sample.
The total pool of mutated genes consisted of 209 genes for ALA, 191 for ALA+MM and 682 for MM (Online
Supplementary Tables S4-S6). An overlap of gene sets among diagnoses is provided in Figure 1C. Heterogeneity of mutated gene profiles could be observed among all studied cohorts. Pairwise comparisons showed that only six mutated genes (FAT3, MUC3A, MUC6, PABPC3, RYR3, ZDHHC11) were present in at least one sample in all three diagnoses. These genes code for large proteins and possess a medium or high gene damage according to the gene damage index score, which points to their poly- morphic nature in the normal population. Thus, variants in those genes are unlikely to cause disease,6 however, the role of some those genes in MM, e.g., FAT3, is still debated.7
We identified more genes shared between ALA+MM versus MM (25) than in ALA versus MM (14) or ALA versus ALA+MM.6 This suggests a slightly more similar muta- tion profile between ALA+MM and MM. From the list of all 209 ALA mutated genes, only 26 genes were shared with a previous sequencing project of Boyle et al. 20188 and four mutated genes were in common with the origi- nal study by Paiva et al. 20169 (Online Supplementary Table S7). Such low gene set overlaps are in line with the assumed mutational heterogeneity in ALA.
Our datasets were not large enough to perform analy- sis of significantly mutated genes. Within the ALA, ALA+MM and MM cohort, genes mutated in more than one patient represented only 2, 6 and 47 genes (1%, 3% and 6.9%), respectively (Figure 1C). Such a marked het- erogeneity was also detected in previous ALA exome studies.8,9 However, Boyle’s work reported that 16% of the genes in ALA were mutated more than once.8 The observed difference can be explained by the different approach for the separation of target populations of cells and by different variant calling algorithms.
We performed comparison of all mutated genes with the 63 known MM drivers obtained from Walker et al. 2018.10 The results revealed that the average number of drivers per patient was lower in ALA and ALA+MM ver- sus MM, even though the differences were not significant (Figure 1D). The total number of drivers present in the entire set of samples (ALA, ALA+MM and MM) was 28 (Figure 1E, Online Supplementary Table S2). The only shared mutated drivers among the diagnoses were NRAS found in ALA+MM and MM, and DIS3 present in ALA and MM. Interestingly, ALA and ALA+MM did not pos- sess any SNV in the same driver gene (Figure 1E). Previously identified ALA drivers DIS3 and EP300 over- lap with our ALA dataset and NRAS and TRAF3 overlap with our ALA+MM dataset8 (Online Supplementary Table S7). The most frequent functional driver categories were epigenetic regulators in ALA, NF-κB pathway in ALA+MM and MEK/ERK pathway in MM (Figure 1E). Interestingly, the NF-κB pathway was previously suggest- ed to be one of the main affected pathways for ALA.8
Surprisingly, the differences at the mutational level did not manifest at the gene expression level. Our analysis did not reveal any differentially expressed genes between ALA and ALA+MM despite using several thresholds of significance. The expression analysis yielded 783 deregu- lated genes (837 probe sets) on the level of 0.05 P-value and fold change above 2 or below 0.5 in ALA or ALA+MM compared to MM (Online Supplementary Table S9-S10).
Genes uniquely upregulated in ALA fall into the regu- lation of B-cell activation, phagocytosis or regulation of protein localization pathway gene ontology (GO) terms (Figure 2A, Online Supplementary Table S11), while genes that were exclusively downregulated in ALA belonged to the mitochondrial translation and ribosome biogenesis
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