Blood‐circulating EV‐miRNAs, serum TARC, and quantitative FDG‐PET features in classical Hodgkin lymphoma

Abstract Blood‐based biomarkers are gaining interest for response evaluation in classical Hodgkin lymphoma (cHL). However, it is unknown how blood‐based biomarkers relate to quantitative 18F‐FDG‐PET features. We correlated extracellular vesicle‐associated miRNAs (EV‐miRNA), serum TARC, and complete blood count (CBC) with PET features (e.g., metabolic tumor volume [MTV], dissemination and intensity features) in 30 cHL patients at baseline. EV‐miR127‐3p, EV‐miR24‐3p, sTARC, and several CBC parameters showed weak to strong correlations with MTV and dissemination features, but not with intensity features. Two other EV‐miRNAs only showed weak correlations with PET features. Therefore, blood‐based biomarkers may be complementary to PET features, which warrants further exploration of combining these biomarkers in prognostic models.


INTRODUCTION
Classical Hodgkin lymphoma (cHL) is a lymphoid malignancy characterized by a minority of large multinucleated Hodgkin and Reed-Sternberg (HRS) tumor cells, surrounded by a nonmalignant immune cell infiltrate [1]. Despite high survival rates in young patients, treatment of cHL relies on multidrug anthracycline-based chemotherapy, which causes considerable burden of acute and late toxicities, such as infertility and cardiovascular toxicity [2]. 18 F-fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) imaging is performed for staging and response evaluation to guide treatment in cHL, but the positive predictive-value for response evaluation with PET/CT is rather low [3]. Improving risk-stratification and response assessment could be helpful to early identify chemotherapy refractory patients and switch to novel therapies [4). Molecular-based blood-based biomarkers can be repeated on a regular basis during treatment, which is therefore an attractive strategy to improve response assessment.
HRS cells are unique in the pathogenesis of cHL and secrete several cytokines and chemokines that actively recruit immune cells to the tumor microenvironment, which may support tumor growth [5,6]. The CC chemokine CCL17 or thymus and activation-regulated chemokine (TARC) is present in lymph node biopsies in approximately 90%-95% of cHL cases and is secreted by HRS cells. Serum TARC (sTARC) can be used as an early response marker in cHL and has been shown to correlate with metabolic tumor volume (MTV) [7,8]. Noncoding microRNAs (miRNAs) in extracellular vesicles are actively secreted in the circulation by tumor cells and can potentially be used as diagnostic and prognostic cancer biomarkers [9]. In cHL patients, several miRNAs have been detected in the plasma that correlate with active disease [10]. In a previous study, we demonstrated that several miRNAs bound to small extracellular vesicles (EVs) are stably enriched in plasma of cHL patients and correlate with treatment response [11,12].
Quantitative analysis of PET scans also provides a way to improve risk-stratification and response assessment, complementary to the visual interpretation of the PET scan. Quantitative PET features include the assessment of MTV, which has already been shown to have prognostic value in newly diagnosed as well as relapsed/refractory (R/R) cHL patients [13][14][15]. Standard uptake value (SUV) features represent the intensity of glucose metabolism, and distance (dissemination) features can assess spread of disease.
The high potential of blood-based biomarkers to improve response assessment in cHL treatment urges us to investigate how blood-based biomarkers relate to quantitative PET features. Therefore, we aimed to assess the correlations between several experimental biomarkers (i.e. EV-miRNAs, sTARC) and PET features in newly diagnosed and R/R cHL patients.

METHODS
Thirty cHL patients (N = 17 newly diagnosed and 13 R/R patients) who have been treated at Amsterdam UMC, were included in this comparative analysis. Patient characteristics are summarized in Table S1.
PET/CT scans were performed, and blood samples were collected at baseline, that is, before start of first or salvage therapy. PET/CT scans were assessed according to the guidelines of the European Association of Nuclear Medicine [16]. MTV was calculated using semi-automatic segmentation with a fixed threshold of SUV ≥4.0 with ACCURATE software, which has been validated in a large cohort of cHL patients [17,18]. The following quantitative PET features were extracted from the original images: MTV, SUVmax, SUVpeak (i.e., the 1 ml with the highest SUV), SUVmean, and total lesion glycolysis (TLG; i.e. the MTV multiplied by SUVmean). Dissemination features (i.e., number of lesions, DmaxPatient, DmaxBulk, SpreadPatient, and SpreadBulk) were extracted using RaCat software [19]. The number of lesions is defined as the number of separate metabolically active lesions, DmaxPatient is the largest distance between two lesions, DmaxBulk is the largest distance between the largest lesion and one other lesion, SpreadPatient is the sum of the distances between all lesions, and SpreadBulk is the sum of the distances between the largest lesion and all other lesions ( Figure 1A).
Serum and plasma samples were collected at baseline and analyzed for sTARC and plasma EV-miRNA levels. ELISA-based detection of sTARC was performed on serum. EV-miRNAs were detected with qRT-PCR as previously described [11]. Additional protocols are described in the supplemental methods. Of note, miRNA and sTARC results of a part of the current patient cohort have been published previously [11].
Wilcoxon rank sum test for nonparametric data was used to com-

RESULTS
Baseline PET scans of both newly diagnosed and R/R patients were included in this analysis. As such, we first analyzed differences in baseline PET features between newly diagnosed and R/R patients. MTV, TLG, and SUVpeak were significantly higher in the newly diagnosed versus R/R patients ( Figure S1A). Assessing the blood-based biomarkers, sTARC was significantly higher in the newly diagnosed patients compared to R/R patients. EV-miRNAs were not significantly different between these groups, as previously described [11]. Further analyses were performed on the whole dataset without discriminating between newly diagnosed or R/R patients. We observed significant weak to moderate negative correlations between hemoglobin and MTV and weak to moderate positive correlations between thrombocyte, leucocyte, and neutrophil counts with MTV ( Figure 1). Thus, in patients with high tumor volumes (MTV), blood abnormalities like anemia, increased thrombocytes, increased white blood cell count, and high ESR are more prevalent.
Previously, we found that the five aforementioned EV-miRNAs are elevated in cHL when there is metabolically active disease present but are strongly reduced in complete metabolic responders [11,12].
Here, we found that EV-miRNAs miR21-5p and let7a-5p have no correlations with quantitative PET features. However miR127-3p and miR24-3p weakly to moderately correlated with the number of lesions and SpreadPatient, but not with MTV. Thus, even though miR21-5p,

F I G U R E 2 Correspondence of number of lesions and metabolic tumor volume (MTV) with levels of several blood-based biomarkers. (A-F)
Boxplots of several blood-based biomarker levels, stratified for high (≥94 ml), or low (<94 ml) MTV measured by positron emission tomography (PET)/computed tomography (CT). (G-L) Boxplots of several blood-based biomarker levels, stratified for a high (≥8) or low (<8) number of lesions on the PET/CT scan. Each individual dot represents a PET value of one patient, the boxplot represents the median and interquartile range, and the whiskers represent the minimum and maximum values miR155-5p, and let7a-5p are elevated in cHL, their levels in the blood do not correlate with the MTV. This suggests that these EV-miRNAs are probably more immune-response related than HRS-cell associated, while miR127-3p and miR24-3p levels may be actively released in the blood stream by HRS cells [10,20]. Likewise sTARC is HRScell associated [21] and strongly correlated with the size of the tumor lesions (MTV, Figures 1 and 2) as previously reported by others [22].

ETHICS STATMENT
Samples were collected in the BioLymph-study (VUmc METc registra-