Unravel Inter-Tumor and Intra-Tumor Heterogeneity of Digitally Sorted Single Hodgkin and Reed Sternberg Cells Using Genome-Wide Copy Number Profiling
2018
Introduction Immune-checkpoint blockade has emerged as an effective therapeutic strategy in solid tumor and in hematologic malignancies, including classical Hodgkin Lymphoma (cHL). cHL represents about 11% of all malignant lymphoma and it is generally highly curable with standard frontline therapies, although about 20% of the patients will relapse or become refractory after initial treatment. The hallmark of cHL is the presence of malignant Hodgkin and Reed-Sternberg Cells (HRS) that represent only a small fraction (about 1%) of the surrounding heterogeneous immune infiltrate. Despite this extensive inflammatory microenvironment, HRS are able to escape immune surveillance using several mechanisms, including the overexpression of PD-1 ligands (PD-Ls) that bind PD-1 on reactive T-cells, inhibiting their activity and proliferation and causing ultimately T-cell exhaustion. The PD-Ls expression is upregulated in a dose-dependent manner by copy number alterations of chromosome 9p24.1, a locus encoding for PD-L1/PD-L2 as well as JAK2, which further enhances PD-Ls expression through JAK2/STAT pathway. Here we present a method for the isolation and the genetic characterization of single purified HRS, which overcomes the limitations posed by the low tumor cellularity of cHL biopsies and gives an estimation of inter-tumor and intra-tumor heterogeneity which may be useful to guide immune treatment selection. Methods FFPE tissue sections from 4 cHL patients were dissociated down to single-cell suspension and stained using anti-CD30 and anti-PD-L1 antibodies. Since CD30 is not expressed exclusively by malignant cells, beyond the positivity to CD30 and PD-L1 HRS were selected according to morphological criteria, such as cell size and the presence of nuclei with ploidy higher than the surrounding lymphocytes. DEPArray™ NxT system (Menarini Silicon Biosystems) was used to isolate single target cells. After recovery, single cells were whole genome amplified ( Ampli 1™ WGA, Menarini Silicon Biosystems), and genome-wide copy-number alterations (CNAs) profiles were obtained using Ampli 1™ LowPass kits (Menarini Silicon Biosystems) on Illumina® and Ion Torrent™ platforms. Results For each patient, at least 8 HRS cells and infiltrating lymphocytes were identified and isolated from lymphoid tissue using DEPArray™ NxT system. Copy-number analyses of recovered cells allowed us to precisely discriminate HRS, characterized by extensive gains and losses, from non-tumor cells, showing flat profiles as expected ( Fig.1 ). Ploidy of HRS was automatically determined, based on best-fitting of profiles with underlying copy number levels. Hierarchical clustering showed that some alterations are highly conserved among patients, e.g. the region containing PD-L1/PD-L2/JAK2 has several copy gains in the majority of malignant cells. Interestingly, these alterations show high variable copy-number levels between different HRS even in the same patient, ranging from few copy-gains to amplifications, suggesting some level of heterogeneity. Different CNAs are also detected in regions containing genes belonging to pathways already known to be altered in cHL, like REL/NFKB and JAK/STAT pathways, which may be involved in the constitutive activation of proliferative and antiapoptotic phenotype of HRS. Conclusion Single HRS sorting combined with low-pass whole genome sequencing offer a valuable tool to uncover genetic alterations hidden by the massive cHL immune infiltrate and to estimate inter-tumor and intra-tumor heterogeneity in cHL patients. Considering that PD-Ls locus amplifications are associated with advanced stages of the disease and with a shorter progression free survival, the analysis of purified HRS could be helpful for patient stratification for the adoption of immune therapy. Disclosures Mangano: Menarini Silicon Biosystems: Employment. Edoardo: Menarini Silicon Biosystems: Employment. Garonzi: Menarini Silicon Biosystems: Employment. Lanzellotto: Menarini Silicon Biosystems: Employment. Papadopulos: Menarini Silicon Biosystems: Employment. Bolognesi: Menarini Silicon Biosystems: Employment. Buson: Menarini Silicon Biosystems: Employment. Ferrarini: Menarini Silicon Biosystems: Employment. Forcato: Menarini Silicon Biosystems: Employment. Fontana: Menarini Silicon Biosystems: Employment. Ceccolini: Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS: Employment. Fabbri: Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS: Employment. Fici: Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS: Employment. Gallerani: Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS: Employment. Simonelli: Menarini Silicon Biosystems: Employment. Medoro: Menarini Silicon Biosystems: Employment. Manaresi: Menarini Silicon Biosystems: Employment.
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