by Jonathan Reichel, Amy Chadburn, Paul G

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Flow sorting and exome sequencing reveal the oncogenome of primary Hodgkin and Reed-Sternberg cells by Jonathan Reichel, Amy Chadburn, Paul G. Rubinstein, Lisa Giulino-Roth, Wayne Tam, Yifang Liu, Rafael Gaiolla, Kenneth Eng, Joshua Brody, Giorgio Inghirami, Carmelo Carlo-Stella, Armando Santoro, Daoud Rahal, Jennifer Totonchy, Olivier Elemento, Ethel Cesarman, and Mikhail Roshal Blood Volume 125(7):1061-1072 February 12, 2015 ©2015 by American Society of Hematology

HRS cell flow sorting and ultralow-input sequence library validation. HRS cell flow sorting and ultralow-input sequence library validation. (A) Identification of HRS cells for flow cytometric sorting. HRS cells (red) show high forward and side scatter, are positive for CD30, bright for CD40 and CD95, and are typically positive for CD15. Many cases show various degrees of rosetting by T cells, resulting in composite CD5+/CD45+ immunophenotype. CD20+ (light blue) B cells and CD5+ (green) T cells with appropriate CD45 and side scatter parameters were sorted for experiment controls. (B) Sorted HRS cells could be visualized on a cytospin using Wright-Giemsa stain to confirm population identity and purity. Original magnification ×100. (C) Comparison of depth of sequence coverage per base between libraries generated with 1 ng (red), 10 ng (blue), and 100 ng (green) of starting genomic DNA from intratumoral T cells. Depth of coverage was comparable between 10 ng and 100 ng DNA input, resulting in 48× vs 52× median coverage, respectively. (D) Each of 2 panels depicts copy number variation analysis results comparing data between 2 sequenced libraries. Exonic probe segments (x-axis) vs copy number change on log2 scale (y-axis) are plotted for a single representative chromosome (chr 6). Comparing data from a 10-ng low-input library from intratumoral T cell DNA to a 100-ng normal-input library from intratumoral T cell DNA from the same case showed no significant false-positive results; that is, low-input and normal-input libraries are copy neutral (top). Numerous segmental copy number alterations could be seen when data from a 10-ng low-input library from HRS were compared against intratumoral T cells of the same case (bottom), indicating that this method reveals copy number gains and losses. FSC, forward scatter; SSC, side scatter. Jonathan Reichel et al. Blood 2015;125:1061-1072 ©2015 by American Society of Hematology

Copy number variation analysis of HRS cells. Copy number variation analysis of HRS cells. (A) Representative results for all chromosomes for case 2 (top) and case 3 (bottom) are shown. HRS cells vs T-cell exon copy number changes are plotted on log2 scale. Case 2 had a relatively high frequency of copy number alterations, whereas case 3 had relatively fewer. Focal losses of the immunoglobulin genes are seen in chromosomes 14, 2, and 22 (red arrows), and gains in the TCR genes on chromosomes 7 and 14 (blue arrows). (B) Circos plot showing the segments containing copy number variations in the 10 primary cases of cHL plus the 2 cell lines sequenced. The samples correspond to cases 1 through 10 beginning at the outermost ring and followed by cell lines L1236 and L428 in the inner circle. Important oncogenes, such as REL, can be seen recurrently amplified (blue), and tumor suppressors (eg, ATM) can be seen recurrently deleted (red). Jonathan Reichel et al. Blood 2015;125:1061-1072 ©2015 by American Society of Hematology

Recurrently mutated genes in cHL with potential pathogenic functions. Jonathan Reichel et al. Blood 2015;125:1061-1072 ©2015 by American Society of Hematology

SNP and indel analysis reveal recurrent alterations and subsets. SNP and indel analysis reveal recurrent alterations and subsets. Unsupervised clustering (asymmetric binary distance matrix and complete linkage hierarchical clustering) based on mutation status of the 104 genes that were mutated in at least 2 cases divides 10 sequenced cases of cHL into 2 molecular subgroups—one of which is exclusively wild-type for B2M; the other exclusively mutated for B2M. Jonathan Reichel et al. Blood 2015;125:1061-1072 ©2015 by American Society of Hematology

B2M-inactivating mutations result in lack of MHC-I expression. B2M-inactivating mutations result in lack of MHC-I expression. (A) Diagram showing the localization and type of mutations in B2M in 7 sequenced primary cases of cHL containing these mutations. (B) Sequence analysis of DNA (top) and RNA (bottom) of the B2M gene in case 8 shows a point mutation in the start site of one allele and an out-of-frame deletion in another allele. Sequences were visualized using Integrated Genome Viewer. (C) Schematic representation of B2M together with MHC-I on the cell surface. (D) The L428 cell line was nucleofected with a plasmid encoding the wild-type B2M and a green fluorescent protein (GFP)-expressing plasmid, and flow cytometry was performed to evaluate MHC-I and B2M expression gating in the GFP+ (red) and GFP− (blue) populations. Jonathan Reichel et al. Blood 2015;125:1061-1072 ©2015 by American Society of Hematology

B2M validation by immunohistochemistry and correlation with subtype and EBV status. B2M validation by immunohistochemistry and correlation with subtype and EBV status. (A) Hematoxylin and eosin (H&E) staining and immunohistochemical staining for B2M and for MHC-I are shown for 2 representative cases of cHL. Case 1 has wild-type B2M sequences, whereas case 7 is mutated for B2M, indicating that this genomic alteration can be determined by lack of B2M expression in HRS cells. Correspondingly, case 1 shows clear Golgi and membrane localization of MHC-I, whereas staining is diffuse in the cytoplasm in case 7, indicating mislocalization. Original magnifications ×20 (H&E) and ×60 (B2M and MHC-I). (B) There was a significant correlation between the lack of B2M expression and the NS subtype of cHL, and between the presence of B2M expression and the MC subtype of cHL. Cases classified as “Others” include 1 case of lymphocyte-rich cHL and cases with features of both NS and MC, making the distinction challenging. (C) A cohort of patients with HIV infection and cHL was evaluated for B2M expression; however, the relationship of histologic subtype and B2M expression did not reach statistical significance in this cohort. (D) The presence of EBV in the HRS cells was assessed by in situ hybridization for Epstein-Barr encoding region. EBV-negative cases were more frequently also negative for B2M; however, among the EBV-positive cases, both B2M-positive and B2M-negative cases were identified. IC, immunocompetent; neg, negative; pos, positive. Jonathan Reichel et al. Blood 2015;125:1061-1072 ©2015 by American Society of Hematology

Lack of expression of B2M is associated with a better clinical outcome in advanced disease. Lack of expression of B2M is associated with a better clinical outcome in advanced disease. Kaplan-Meier curves of cases with clinical information show that positivity for B2M by immunohistochemistry in the HRS cells associates with a poor progression-free survival (PFS) and overall survival (OS), as compared with cases that lack B2M expression in the entire cohort (top row). The middle row shows Kaplan-Meier curves for patients with stages I and II cHL; the bottom row shows Kaplan-Meier curves for patients with stages III and IV cHL. Among patients with advanced stage, but not in patients with early-stage cHL, positivity for B2M by immunohistochemistry in the HRS cells showed a trend for poor OS, as compared with cases that lack B2M expression. NS, not significant. Jonathan Reichel et al. Blood 2015;125:1061-1072 ©2015 by American Society of Hematology