case_images: PMC11441378_01
case_images: Treatment and molecular characteristics of CLL patient #491. a Treatment history of patient #491 from CLL diagnosis to Richter transformation and ibrutinib resistance. b Results from BCR Seq of blood samples at T1/2 obtained by amplicon sequencing and of BM1/2 samples extracted from RNA Seq data. Sequences correspond to CDR3 region of the Immune globulin g heavy chain (IGH). c Heat map of all somatic mutations of biopsies from peripheral blood (T1 and T2) and bone marrow (BM1 and BM2). Color spectrum corresponds to allelic frequencies of mutations. Genes marked with X were not covered by sequencing reads in BM samples. d Schematic representation of exonic mutations in genes potentially involved in ibrutinib resistance mechanism. Pins represent mutated amino acid positions at the individual genes. Colored sections represent Pfam protein domains. Created with R package G3viz. e Evaluation of effected pathways by individual blood tumor mutations via the QIAGEN Ingenuity Pathway Analyzer (IPA). All mutated genes that were mapped to pathways by IPA are depicted. Alem, alemtuzumab; Ofa, ofatumumab; Len, lenalidomide; Dex, dexamethasone; Idel, idelalisib; anti-CD19, antibody targeting CD19.
case_images: aha-2024-0147-0005-537791_F01.jpg
case_images: PMC11441378_02_aha-2024-0147-0005-537791_F01.jpg
case_images: F1
case_images: DNA mutation and copy number variation (CNV) analysis of peripheral blood samples (T1) and BM biopsies (BM1) prior ibrutinib resistance and at time of CLL progression during ibrutinib treatment (ibrutinib resistance [T2]) and at time of Richter transformation diagnosis (BM2) revealed significant clonal evolution during therapy (Fig. 1c; online suppl. FLNC, and KHDC3L accumulated upon ibrutinib resistance, as well as a UTR3 variant in the gene SEPT9 and a splicing mutation in EHMT2 showing an increased allelic frequency after ibrutinib resistance. Further, we observed two bone-marrow restricted mutations only detected after ibrutinib resistance and Richter transformation: a stop gain mutation in ASXL1 and a non-synonymous lesion in DIAPH3 e (Fig. 1c; online suppl. All non-synonymously mutated genes are listed in Figure 1c from which all mutations enriched at time of ibrutinib resistance are schematically depicted in Figure 1d. S581I conversion in the translated protein within the HEAT domain and is located relatively close to an already known mutational hotspot (T600I) (Fig. 1d). All individual mutations detected in blood samples were evaluated via the QIAGEN Ingenuity pathway analyzer for potential pathway alterations, revealing that mutations in MTOR, RPS15, and LIFR can potentially influence the MTOR signaling pathway (Fig. 1e). We decided to investigate BM samples instead of blood derived tumor cells since all tumor cells migrated from the blood into lymphatic tissue soon after the ibrutinib resistance was diagnosed most likely due to the Richter transformation of the CLL cells (Fig. 1a).
case_images: PMC11441378_02
case_images: Treatment and molecular characteristics of CLL patient #491. a Treatment history of patient #491 from CLL diagnosis to Richter transformation and ibrutinib resistance. b Results from BCR Seq of blood samples at T1/2 obtained by amplicon sequencing and of BM1/2 samples extracted from RNA Seq data. Sequences correspond to CDR3 region of the Immune globulin g heavy chain (IGH). c Heat map of all somatic mutations of biopsies from peripheral blood (T1 and T2) and bone marrow (BM1 and BM2). Color spectrum corresponds to allelic frequencies of mutations. Genes marked with X were not covered by sequencing reads in BM samples. d Schematic representation of exonic mutations in genes potentially involved in ibrutinib resistance mechanism. Pins represent mutated amino acid positions at the individual genes. Colored sections represent Pfam protein domains. Created with R package G3viz. e Evaluation of effected pathways by individual blood tumor mutations via the QIAGEN Ingenuity Pathway Analyzer (IPA). All mutated genes that were mapped to pathways by IPA are depicted. Alem, alemtuzumab; Ofa, ofatumumab; Len, lenalidomide; Dex, dexamethasone; Idel, idelalisib; anti-CD19, antibody targeting CD19.
case_images: aha-2024-0147-0005-537791_F01.jpg
case_images: PMC11441378_02_aha-2024-0147-0005-537791_F01.jpg
case_images: F1
case_images: DNA mutation and copy number variation (CNV) analysis of peripheral blood samples (T1) and BM biopsies (BM1) prior ibrutinib resistance and at time of CLL progression during ibrutinib treatment (ibrutinib resistance [T2]) and at time of Richter transformation diagnosis (BM2) revealed significant clonal evolution during therapy (Fig. 1c; online suppl. FLNC, and KHDC3L accumulated upon ibrutinib resistance, as well as a UTR3 variant in the gene SEPT9 and a splicing mutation in EHMT2 showing an increased allelic frequency after ibrutinib resistance. Further, we observed two bone-marrow restricted mutations only detected after ibrutinib resistance and Richter transformation: a stop gain mutation in ASXL1 and a non-synonymous lesion in DIAPH3 e (Fig. 1c; online suppl. All non-synonymously mutated genes are listed in Figure 1c from which all mutations enriched at time of ibrutinib resistance are schematically depicted in Figure 1d. S581I conversion in the translated protein within the HEAT domain and is located relatively close to an already known mutational hotspot (T600I) (Fig. 1d). All individual mutations detected in blood samples were evaluated via the QIAGEN Ingenuity pathway analyzer for potential pathway alterations, revealing that mutations in MTOR, RPS15, and LIFR can potentially influence the MTOR signaling pathway (Fig. 1e). We decided to investigate BM samples instead of blood derived tumor cells since all tumor cells migrated from the blood into lymphatic tissue soon after the ibrutinib resistance was diagnosed most likely due to the Richter transformation of the CLL cells (Fig. 1a).
case_images: Gene set enrichment analysis (GSEA) of transcriptomic analysis of BM samples. BM samples of Pat #491 before ibrutinib resistance (BM1) and after ibrutinib resistance and Richter transformation (BM2) were used for RNA-Seq analysis. a Results of GSEA using the MSigDB hallmark gene sets. All significantly enriched hallmark gene sets are displayed. b MTORC1 GSEA plot of the most significantly enriched hallmark gene set from the GSEA analysis shown in a. c Heatmap displaying the expression levels (log2 counts per million +2) of the leading edge genes from the MTORC1 GSEA analysis shown in b. NES, normalized enrichment score.
case_images: aha-2024-0147-0005-537791_F02.jpg
case_images: PMC11441378_02_aha-2024-0147-0005-537791_F02.jpg
case_images: F2
case_images: Notably, when performing a gene set enrichment analysis (GSEA) using the MSigDB Hallmark gene sets, the most significantly upregulated gene set turned out to be "Hallmark MTORC1 signaling" (normalized enrichment score [NES] = 1.44, padj = 2e-7) indicating an increased MTOR pathway activation post ibrutinib resistance/Richter transformation (Fig. 2a, b). Additionally, MSigDB Hallmark gene sets involved in cell cycle progression (G2M checkpoint, E2F targets, Myc targets, P53 pathway, and mitotic spindle), immune regulation (inflammatory response, interferon gamma response, allograft rejection), DNA damage (DNA repair, UV response down), and oxidative phosphorylation also showed a highly significant activation (Fig. 2a). Figure 2c displays expression levels of genes from the "Hallmark MTORC1 signaling" gene set that contribute most to the pathway upregulation. Notably, the key KEGG MTOR pathway target SGK1 that confers cell survival is significantly upregulated (+3.88, padj = 3.88e-8) post ibrutinib resistance (Fig. 2c, online suppl.