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L. Raman et al.
Both HL and DLBCL typically display distinct morpho- logical, immunohistochemical and (epi)genetic features.2– 5 Their high cell turnover makes them excellent candi- dates for ‘liquid biopsy’-based research. Necrotic and apoptotic tumor cells have been shown to shed DNA6 into the peripheral circulation and this is informative with regard to diagnosis, prognosis and therapy.7 In theory, this would enable real-time (serial) sampling of the entire (often heterogeneous)8 genomic lymphoma architecture in a convenient and non-invasive manner through tradi- tional blood sampling.
Recent studies9–11 have focused on plasma cell-free DNA (cfDNA) analysis using ultra-deep targeted sequencing12 for single nucleotide variant (SNV) and translocation detection. Overall, these studies have provided two main insights: firstly, that variant allele frequencies often corre- late with disease status; and, secondly, that surveilling cir- culating tumor DNA (ctDNA) might outperform 18F-fluo- ro-2-deoxyglucose positron emission tomography/com- puted tomography (PET/CT) scans in terms of sensitivity. This latter finding holds a great deal of potential for relapse risk assessment by quantifying minimal residual disease.
Despite their potential, ultra-deep sequencing tech- niques are still expensive and require targeted panels. In contrast, shallow (coverage ~0.25x) whole-genome sequencing (sWGS) for primarily copy number detection is cheaper and fully operative in hospitals that offer non- invasive prenatal testing.13 One of the hallmarks of sWGS is its high specificity in identifying malignant cells: in comparison to SNV, large (i.e., >5 Mb) somatic copy num- ber alterations are rarely detected in unaffected subjects14 whereas SNV accumulate over time. Worth mentioning is that this also occurs in hematopoietic stem cells, a phe- nomenon referred to as clonal hematopoiesis,15 potential- ly resulting in incorrect driver identifications.
sWGS of cfDNA may therefore have clinical potential, especially for patients with lesions that are difficult to biopsy (e.g. those in brain; deep lymph nodes in the tho- racic cavity or abdomen); or when dealing with ambigu- ous PET/CT scans, as both imaging and clinical symp- toms of lymphoma are often non-specific. Nevertheless, this approach has only been superficially investigated.16 We, therefore, evaluated whether sWGS could serve as a molecular test in addition to established diagnostic meth- ods, using a diverse set of 123 prospectively recruited lymphoma patients, comprising baseline and longitudinal blood samples, supplemented with paired formalin-fixed paraffin-embedded (FFPE) biopsies.
Methods
Ethics statement
This study was approved by the institutional ethics commit- tee at Ghent University Hospital (EC/2016/0307). Written informed consent was obtained from all patients.
Study population
Between January 2016 and November 2019, 123 lymphoma patients were recruited at Ghent University Hospital and AZ Delta Roeselare. The subtypes studied include 38 HL (3 nodular lymphocyte predominant HL; 23 nodular sclerosis classical HL [cHL]; 5 mixed cellularity cHL; 5 lymphocyte-rich cHL; 1 lym-
phocyte-depleted cHL; and 1 not otherwise specified [NOS]); 81 DLBCL (61 NOS; 4 Epstein-Barr virus [EBV]-positive; 10 primary mediastinal large B-cell lymphomas [PMBCL]; 2 high-grade B- cell lymphomas; 2 T-cell/histiocyte-rich large B-cell lymphomas; 1 intravascular large B-cell lymphoma; and 1 plasmablastic lym- phoma) and four grey-zone lymphomas (GZL) (Online Supplementary File S2: Tables S1 and S2). Patients were included at the start, ‘baseline’, of a new line of therapy (i.e., baseline rep- resents initial diagnosis for 115 cases; after ineffective treatment in 6 other cases; and at relapse for the 2 remaining cases). Although patient recruitment was random, the final cohort was enriched for HL patients.
Sample series
Liquid biopsies were collected at baseline for all patients (n=123) and a random selection of paired FFPE tissue was made (n=33); this was obtained from 15 HL and 18 DLBCL patients. Longitudinal liquid biopsies were taken following milestones in treatment with 93 sequenced for 31 patients. These were inten- tionally enriched for refractory or relapsed disease: interim eval- uations after two and four cycles of ABVD in HL; interim evalu- ations after four cycles of R-CHOP in nHL; at restaging after ineffective treatment or relapse; following successful treatment; and every 6 months for patients in maintained complete remis- sion (CR). For HL (n=9), six patients had obtained CR within a year of inclusion whereas three were refractory. For nHL (n=22), 11 patients reached CR within a year; six were refractory; and five relapsed.
Negative liquid biopsies were included from non-invasive pre- natal assays (n=60), supplemented with benign FFPE tissue (n=9) as a control for the solid biopsies. In total, 318 samples were thus analyzed.
Clinical and pathological characteristics
Patient demographics and clinical variables were available through routine clinical practice. The total metabolic tumor vol- ume (MTV) was measured by PET/CT using AW workstation semi-automated segmentation software (GE medical systems, Waukesha, WI, USA), with a standard uptake value cutoff of 2.5.
Pathology diagnosis included standard histological examina- tion of FFPE biopsy material in combination with immunohisto- chemistry (IHC). Double/triple hit (MYC, BCL2 and/or BCL6) and double expressor (MYC and BCL2) samples were detected using fluorescence in situ hybridization and IHC, respectively. The germinal center B-cell (GCB) cell of origin (COO) status was assigned through the Hans algorithm.17
When using chromogenic in situ hybridization (CISH), the presence of EBV-encoded RNA (EBER) was evaluated via INFORM EBER probes (Ventana Medical Systems, Tucson, AZ, USA). Selected liquid biopsies were additionally tested using the quantitative EBV-polymerase chain reaction (PCR) method, as established by Bordon et al.18
Sequencing and bioinformatic analysis
Each laboratory step and subsequent computational analysis can be found in Online Supplementary File S1: Supplemental meth- ods. These include: copy number profiling;19 defining the tumor burden using the copy number profile abnormality (CPA) score20 and estimated tumor fraction;21 methods used to derive viral read fractions of HIV-1, HIV-2, EBV, JC polyomavirus, human T- lymphotropic virus 1, human herpesvirus 8 and hepatitis C virus; random forest modeling22 of copy number profiles to pre- dict tumor subtype; detection of copy number driver peaks;23 and general statistical testing.
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haematologica | 2022; 107(1)