Hodgkin lymphoma and liquid biopsy: a story to be told

Abstract

Hodgkin lymphoma (HL) represents a neoplasm primarily affecting adolescents and young adults, necessitating the development of precise diagnostic and monitoring tools. Specifically, classical Hodgkin lymphoma (cHL), comprising 90% of cases, necessitating tailored treatments to minimize late toxicities. Although positron emission tomography/computed tomography (PET/CT) has enhanced response assessment, its limitations underscore the urgency for more reliable progression predictive tools. Genomic characterisation of rare Hodgkin Reed-Sternberg (HRS) cells is challenging but essential. Recent studies employ single-cell molecular analyses, mass cytometry, and Next-Generation Sequencing (NGS) to unveil mutational landscapes. The integration of liquid biopsies, particularly circulating tumor DNA (ctDNA), extracellular vesicles (EVs), miRNAs and cytokines, emerge as groundbreaking approaches. Recent studies demonstrate ctDNA's potential in assessing therapy responses and predicting relapses in HL. Despite cHL-specific ctDNA applications being relatively unexplored, studies emphasize its value in monitoring treatment outcomes. Overall, this review underscores the imperative role of liquid biopsies in advancing HL diagnosis and monitoring.

Background

Hodgkin lymphoma in clinic

Hodgkin lymphoma (HL) is a neoplasm with an annual incidence of three cases per 100,000 individuals, primarily affecting adolescents and young adults in Western society [1, 2]. There are two principal types of Hodgkin lymphoma: nodular lymphocyte-predominant Hodgkin lymphoma (NLPHL) and classical Hodgkin lymphoma (cHL). On one hand, 5–10% of cases are NLPHL, characterised by the proliferation of small lymphocytes with scattered large neoplastic cells known as lymphocyte-predominant (LP) cells [1]. On the other hand, more than 90% of cases are cHL, which is divided into four subtypes based on their morphology and immunohistochemistry: nodular sclerosis cHL (NSCHL), mixed cellularity cHL (MCCHL), lymphocyte-depleted cHL (LDCHL), and lymphocyte-rich cHL (LRCHL) [1, 3, 4]. While it is not always possible to distinguish between these subtypes, it is essential to differentiate cHL from NLPHL [3].

cHL is characterised by the presence of markedly rare malignant cells known as Hodgkin and Reed-Sternberg (HRS) cells. These cells have a B lymphocyte origin and are characterised by an increase in size and number of nuclei. The HRS cell microenvironment is composed of a variety of non-malignant immune effector cells such as T cells, B cells, eosinophils, macrophages, and fibroblasts [4,5,6]. In tissues, HRS cells constitute approximately 1% of the tumor complicating their molecular characterisation due to their scarcity [1, 4, 7]. Specifically, HRS cells form rosettes and interact with surrounding lymphocytes [8]. The origin of this disease has no definitive evidence, but it is believed to result from a combination of genetic, environmental, and immune system factors. It has also been suggested that in some cases, the Epstein-Barr Virus (EBV) [4, 7, 9] or human immunodeficiency virus [10] could be involved.

The initial treatment for cHL typically involves chemotherapy, with or without radiotherapy; however, other treatments such as monoclonal antibodies (BV) and immunotherapy could be also indicated. This therapy has proven effective, achieving remission in over 90% of cases and curing at least 80% of patients when considering all disease stages[11]. However, the treatment's effectiveness and aggressiveness, combined with poorly understood factors[12], mean that cHL is directly responsible for less than half of patient deaths[13]. This is particularly notable in patients with early-stage disease, where lymphoma progression accounts for less than one-third of fatalities[14].

The primary cause of death in cHL is the late toxic effects of treatment [15], which typically manifest after the fifth year of follow-up and steadily increase, even beyond 30 years from the initial treatment. Common late effects include secondary malignancies (such as solid tumors and acute leukaemia) and severe cardiovascular events (such as ischemic heart disease, stroke, and heart failure), primarily induced by the treatment, particularly radiotherapy [16].

Since the late twentieth century, a key focus of clinical research in cHL has been tailoring each patient's treatment based on their risk of lymphoma-related death. This approach aims to provide more aggressive treatments to patients with a poorer prognosis and less intensive treatments to those with a more favourable outlook, with the goal of reducing severe late side effects [17].

Since 2007, PET/CT (positron emission tomography/computed tomography) has emerged as the preferred tool for assessing the response in classical Hodgkin lymphoma (cHL). Interim PET/CT (iPET, PET performed after the first two cycles of chemotherapy) has gained acceptance as a valuable tool for adjusting treatment intensity based on the observed response [18].

iPET exhibits a robust negative predictive value (NPV) when evaluating the response of cHL, allowing for treatment de-escalation while maintaining a high cure rate [19, 20]. However, the positive predictive value (PPV) of iPET falls short of clinical utility, primarily due to its limited accuracy (approximately 40–50% after ABVD treatment)[21,22,23], resulting in relapse rates ranging from 15 to 60% [20, 22, 23].

Approximately 50% of patients with positive iPET results will remain free from progression, while 20–25% of patients with negative iPET will experience disease progression [24]. Given the substantial rate of false positives and the association between more intensive treatment regimens and both improved cure rates and heightened acute and long-term toxicity, there is an imperative need for a more dependable predictive tool for disease progression.

While FDG-PET (18-Fluoro-deoxyglucose positron emission tomography) is recognized as a valuable tool for detecting and monitoring responses to treatment in cHL and other lymphomas, some authors argue that it does not offer significant advantages over physical examination-based methods for detecting relapses [25,26,27]. Nonetheless, this procedure raises several issues for patients, including radiation exposure and the potential for false-positive results [28]. Importantly, this approach may not reliably detect relapses and may increase the risk of second malignancies, especially in pediatric and young adult patients. To underscore the radiation exposure concern, Pingali et al. determined that the cumulative exposure from additional scans is equivalent to 27 years of background radiation [25]. Furthermore, considering the issue of false-positives, two studies found a high proportion of patients with these erroneous scan results, often due to infectious and inflammatory processes, leading to unnecessary treatment changes for patients who were actually free of disease [29, 30].

In light of these considerations, there is an urgent and pressing need to develop innovative and non-invasive tools that can sensitively monitor the presence and progression of the disease during and after treatments (Fig. 1).

Fig. 1

Potential applications and limitations of different methodologies for the therapeutic management of Hodgkin lymphoma. A Comparison of tumor biopsy, liquid biopsy, and Imaging/PET-CT. B Potential uses of liquid biopsy to diagnose the disease, stratify patients, decipher tumor heterogeneity, monitor disease response, and predict relapse. C Circos plot illustrating the genes with mutations found in solid biopsy (teal), circulating free DNA (yellow), and both (purple) that are linked to any therapy. The recommended therapies for each mutated gene are depicted from T1 to T18. For the genes, the width of the lines corresponds to the total number of citations linking the gene with a given therapy. Conversely, the width of the lines for the treatments corresponds to the number of citations for each therapy (https://www.oncokb.org/). LOD: Limit of detection; MRD: Minimal Residual Disease; NPV: Negative predictive value; PPV: Positive predictive value

Molecular profile of HRS cells and tumor microenvironment

The diagnosis of cHL is made by a tissue biopsy as it is essential to identify the presence of HRS cells. Not only the diagnosis based on HRS but also the tumor microenvironment (TME) characterization is essential to differentiate between subtypes. The TME contributes to refractoriness to therapy, relapse or even poor survival rates in cHL [31]. Considering the above-mentioned caveat on tumor cells rarity in the tissue, the molecular characterization of HRS cells and TME, it is essential to identify valuable targets for precision therapy of patients with cHL. Some of the latest studies are based on single-cell molecular analysis, employing technologies such as mass cytometry (CyTOF), single-cell RNA sequencing (scRNA-seq), and multiplexed imaging. They also permit the study of the TME, paving the way for a better understanding of this disease [32]. However, there is currently no evidence of using the molecular characterization of these cells to implement and improve the clinical management of patients with cHL.

In this context, Next-Generation Sequencing (NGS) is a powerful tool, not only for diagnosis but also for monitoring treatment responses and stratifying patients based on their risk of relapse [33]. NGS has begun to shed light on the dynamic nature of this disease and has been used to characterize the mutational landscape of HRS cells. For instance, in a study conducted by Reichel et al., HRS cells were sequenced, revealing alterations in genes related to the immune system, genomic stability, and transcriptional regulation. The authors identified that inactivating mutations in the B2M gene resulted in major histocompatibility complex I (MHC-I) downregulation. Notably, they found that B2M inactivating mutations and alterations in the NF-κB pathway were more prevalent in the nodular sclerosis cHL (NSCHL) subtype, whereas certain cases classified as mixed cellularity cHL (MCCHL) did not exhibit a characteristic mutational landscape, suggesting molecular heterogeneity within this subtype [33].

In another study, a whole-exome sequencing (WES) analysis of HRS cells isolated by microdissection identified increased copy number alterations (CNAs) affecting the JAK2 gene, an enrichment of mutations in the STAT6 gene, and activating mutations in genes such as JAK1 and other transcription factors from the JAK-STAT signaling pathway, including STAT3 and STAT5B, in approximately 90% of cases. In this study, the most prevalent mutations were found in the GNA13 (24%), XPO1 (18%), ITPKB (16%), and STAT6 (32%) genes [34]. Additionally, Wienand et al. conducted WES on HRS cells isolated by flow cytometry. The authors observed frequent mutations in the B2M (39%), NFKBIE (26%), TNFAIP3 (26%), and NFKBIA (17%) genes. Consistent with previous reports, they also identified mutations in the JAK/STAT pathway, including mutations in the SOCS1 (70%) and STAT6 (35%) genes. Furthermore, somatic CNAs were observed, with frequencies ranging from 9 to 52%. One of the most frequent CNAs involved arm-level 9 gain and focal amplification of the 9p24.1/PD-L1/PD-L2/JAK2 region [35].

Collectively, these studies have illuminated the intricate genomic landscape of HRS cells. In this context, Mangano et al. introduced an innovative methodology utilizing single-cell isolation of these rare and scarce HRS cells through the use of DEPArray™, an image-based cell-sorting technology. This approach allowed for the isolation of individual cells from cHL tissues, enabling the study of their CNAs. Their investigation revealed common altered regions on chromosomes 2p, 8q, and 9q. Notably, these regions encompass genes known to be frequently altered in cHL, including those associated with the REL/ NF-κB and JAK/STAT pathways [36]. Elevated levels of genetic imbalances were also identified in oncogenes previously recognized as being altered in cHL, including MDM4 and U2AF1. This serves as an illustrative example of how innovative, high-precision single-cell isolation technologies can contribute to the comprehensive characterization of HRS cells. Such advancements not only enhance our understanding of cHL but also pave the way for the development of personalized therapeutic and disease-monitoring strategies (Fig. 1).

The challenges in characterizing HRS cells and translating this knowledge into clinical practice for the benefit of patient management are evident. In some recent significant study, investigators have demonstrated the feasibility of characterizing this disease through liquid biopsy, analyzing circulating tumor DNA to monitor therapy responses, establishing risk-of-relapse stratification and detecting minimal residual disease. Further discussion of this article will follow in the subsequent Sect. [37].

Liquid biopsy in lymphomas as an emerging diagnostic and monitoring tool

Liquid biopsy has emerged as a promising diagnostic and monitoring approach for the detection and characterization of cancers using bodily biofluids, such as blood. In the context of solid tumors, this methodology enables a more comprehensive characterization of the tumor’s genetic heterogeneity [38]. Furthermore, it offers the advantage of improved accessibility for serial monitoring of cancer progression (Fig. 1).

The translation of liquid biopsy into the concept of precision medicine and routine clinical practice holds significant potential, particularly in the context of detecting minimal residual disease (MRD) with the goal of identifying relapses before they manifest clinically [38, 39]. Specifically, the analysis of circulating tumor DNA (ctDNA) has emerged as a promising tool for cancer characterization, patient stratification, and the early detection of disease relapse [40,41,42] (Fig. 1).

In lymphoma research, a notable study has showcased the utility of ctDNA detection as an effective tool for disease monitoring in diffuse large B-cell lymphoma (DLBCL). This study provided compelling evidence that ctDNA during treatment and surveillance is a useful biomarker to predict therapy failure and risk of future relapse before clinically evident exhibiting enhanced sensitivity when compared to FDG-PET imaging [43]. In this context, one of the most recent research endeavors was conducted by Jimenez-Ubieto et al. Their study involved sequencing patients with follicular lymphoma (FL) to identify somatic mutations that could serve as personalized MRD assays in plasma. Following the design of a specific panel, they conducted sequencing at an ultra-high depth, achieving a remarkable sensitivity of 2 × 10^–4. The results were notable; their MRD assay, when coupled with PET/CT imaging analysis, effectively detected patients who experienced relapses in less than two years with an impressive sensitivity of 88% and a specificity of 100%. This serves as a compelling example of how liquid biopsy, personalized NGS assays for ctDNA detection, and current imaging tools can collectively enable the stratification of lymphoma patients based on their risk of relapse [44].

In case of cHL, there are no experimental evidence of using advanced personalized NGS assays to monitor disease response and relapse monitoring. However, some studies have described the mutational landscape of ctDNA using NGS in this patient’s type. Certain mutations affecting genes such as SOCS1, STAT6, XPO1, TNFAIP3, NFKBIE, B2M, NOTCH and PI3K were observed in plasma from patients with cHL [45,46,47,48,49,50]. Indeed, it has been shown that ctDNA levels are correlated with metabolic tumor volumes and disease outcomes [46]. In this regard, Alcoceba et al., employed a targeted capture NGS panel for liquid biopsy including coding regions and splice sites of 37 genes, and hot-spots for an additional five genes involved in cHL. In detail, they detected ctDNA in 73.5% of samples at diagnosis and five variants per case with VAFs ranging from 0.84% to 28%. They observed mutations in most of the previously mentioned genes but also an association of higher ctDNA levels with poor prognosis clinical signatures [51].

In a groundbreaking study, Spina et al. conducted an in-depth investigation of ctDNA cHL through comprehensive sequencing. Their research aimed to establish the correlation between mutations found in tumor tissue and those in ctDNA, decipher the mutational landscape of ctDNA, and assess the potential of ctDNA for prognostic purposes in cHL. To achieve this, they utilized a non-specific targeted panel designed for mature B-cell tumors, complemented by ultra-deep sequencing techniques. The study revealed a robust correlation between genetic aberrations present in HRS cells and those found in ctDNA. Interestingly, their findings identified STAT6 as the most frequently altered gene in cHL, challenging previous research findings. This study proposes the measurement of ctDNA as a radiation-free tool for tracking residual disease, offering significant potential in cHL prognosis [52]. In detail, they observed a 100-fold drop in ctDNA as a marker to predict progression in their cohort that was also associated with complete response and cure. This observation was as also reported in previous investigations in other lymphoma types [53].

In another important study, Shi et al., employed a specific fixed target panel, including common genes affected in cHL and other common lymphomas and hematologic malignancies. Herein, they characterized the mutational landscape of cHL by ctDNA sequencing but also evaluated the capacity of ctDNA to predict immunotherapy treatment response and disease recurrence. In detail, they observed that: i) mutations affecting the gene CHD8 were significantly associated with longer progression-free survival (PFS), ii) baseline ctDNA was significantly higher in responders to therapy and iii) a decrease in ctDNA levels of ≥ 40% from baseline indicated better outcome. Furthermore, they propose that mutations in the B2M, TNFRSF14 and KDM2B genes are associated with acquired resistance to this particular treatment [47].

In another study conducted by Buedts et al., they analyzed CNAs in cell-free DNA (cfDNA) from cHL patients compared to healthy individuals. Approximately 90% of patients presented CNAs in cfDNA, with the detection of new recurrent CNAs such as gain of 15q21-q26 and the loss of 3p13-p26 and 12q21-q24. Interestingly, they discovered that CNAs and ctDNA levels decrease after treatment initiation, being present only in those patients with a higher probability of relapse [54]. Within the context of CNAs study in cfDNA, Raman et al. carried out a shallow-depth sequencing for tumor heterogeneity characterization, demonstrating that liquid biopsy-derived CNAs could differentiate between HL and DLBCL cases. Additionally, the results of the analysis of longitudinal samples suggest that CNAs patterns were similar across patients who were more likely to experience a relapse [55].

In a recent study, among other aspects, researchers investigated the clearance of ctDNA in previously untreated patients with cHL treated with the novel therapy involving pembrolizumab and chemotherapy. The study findings revealed that ctDNA clearance, observed after cycle two and at the end of treatment, was significantly associated with superior PFS. Furthermore, it's noteworthy that patients who exhibited imaging positivity but tested ctDNA-negative in plasma did not experience relapses by the time of the article's publication [56].

Finally, a recent investigation has explored the challenges associated with comprehensive genomic profiling of cHL through ctDNA characterization instead of tumor tissue. This study underscores the potential of liquid biopsies for molecular profiling of cHL. On one hand, the investigation revealed, through single-cell transcriptional profiles, that high ctDNA shedding in this tumor type is influenced by DNASE1L3 expression. Secondly, analysis of plasma samples from 366 patients identified two distinct genomic subtypes of cHL with clinical and prognostic implications, alongside novel IL4R mutations potentially targetable with IL-4Rα-blocking antibodies. The study also showcases the clinical value of pretreatment and on-treatment ctDNA levels for refining risk prediction and detecting minimal residual disease using an ultrasensitive technology called PhasED-seq. In this context, the researchers concluded that ctDNA levels have the potential to refine staging procedures, complement current risk stratification tools like iPET, and guide the selection of appropriate therapies [37].

Other studies investigated the association of cfDNA/ctDNA with other biological or imaging tools involved in cHL. In the field of pediatric cHL, the amount of cfDNA and ctDNA in patients with cHL and healthy individuals was investigated. It was shown that the cfDNA levels were higher in patients with cHL but also were correlated with poor prognosis [57, 58]. In an additional study, the authors evaluated the capacity of EBV and/or cfDNA detection and quantification in blood to provide insights into prognosis and treatment response. In concordance with the previous studies, cfDNA was elevated in cHL compared to controls [59]. Recently, there has been an exploration of the associations between PET/CT parameters and ctDNA in HL. Studies have delved into parameters related to tumor burden, tumor location, and dispersion in conjunction with ctDNA measurements. The findings suggest that quantifying ctDNA could provide additional value to traditional PET/CT, leading to better stratification and enhanced clinical management for patients with cHL [60]. In another innovative study including iPET analysis involving patients with relapsed/refractory cHL, the authors focused on identifying reliable biomarkers for treatment failure in relapsed/refractory cHL. Analyzing 55 patients treated with the bendamustine, gemcitabine and vinorelbine (BEGEV) regimen, researchers found that baseline ctDNA genotyping mirrored gene mutations in newly diagnosed cHL. Baseline ctDNA quantification and serial monitoring proved prognostic in these patients undergoing salvage chemotherapy. Integrating ctDNA with iPET enhanced early identification of high-risk patients, suggesting potential benefits from an early switch to immunotherapeutic agents [61].

Currently, there are several significant studies assessing the potential of plasma DNA as a valuable tool for therapy response assessment and relapse monitoring. Nevertheless, a majority of these studies have employed non-specific approaches or utilized short gene panels, particularly in the context of cHL. In light of this, high-throughput methodologies, such as whole-genome sequencing (WGS), which also encompasses the analysis of CNAs, could greatly contribute to unraveling the complex genomic landscape of cHL. This, in turn, may facilitate the design of highly personalized gene panels for use in ctDNA monitoring. However, the detection and on-treatment monitoring of ctDNA demand the expertise of highly skilled personnel, cutting-edge technologies, and proficiency in bioinformatics. In contrast, the quantification of total cfDNA involves a more straightforward methodology, commonly utilizing fluorometric assays or PCR-based platforms for measurement. As previously mentioned, various studies have investigated total cfDNA levels in patients with cHL, particularly at pre-treatment stages, revealing associations with advanced disease stages, unfavorable outcomes, and treatment failures, among other factors [54, 57, 58]. Some investigations have delved into the correlation between fluctuations in total cfDNA levels during therapy and subsequent treatment responses [58, 59]. It is crucial to emphasize that further extensive studies, encompassing larger cohorts, are imperative to validate these findings. Consequently, the comprehensive measurement of cfDNA presents itself as a pragmatic and readily implementable approach in clinical settings over the short term.

It is worth noting that liquid biopsy, specifically the detection and characterization of ctDNA, has demonstrated substantial promise in elucidating the underlying genomic mechanisms of tumor pathology. It holds significant potential for aiding in the monitoring of treatment responses and the early detection of relapses. However, implementing liquid biopsy and ctDNA in clinical practice involves addressing significant challenges in the preanalytical, analytical, and postanalytical phases. In the preanalytical phase, standardized protocols for sample selection, handling, processing, and storage are crucial to minimize errors. Validating these protocols is essential for optimal mutation detection. Biological variability in biofluids poses additional challenges, and choosing the appropriate biofluid for biomarker discovery requires considering factors like tumor location and accessibility. Standardization in the preanalytical phase is key for ensuring the reproducibility and reliability of liquid biopsy studies [62].

In the analytical phase, critical factors must be addressed, including quantification and qualification of cfDNA. Methods such as fluorescence-based assays and PCR-based tools are vital for assessing sample suitability. The choice of ctDNA analysis method, whether tumor-informed or tumor-agnostic, adds complexity to homogenization efforts. Additionally, reference materials and the measure of analytical outcome, particularly in terms of quantitative potential and result presentation, further highlight the challenges in standardizing liquid biopsy procedures [63].

In the postanalytical phase, factors crucially affect sensitivity and specificity. Processes like fragmentomic and bioinformatic pipelines enhance ctDNA detection accuracy. Meticulous evaluation of detected variants, including addressing artifacts and applying in silico size-selection, is essential. In addition, comprehensive diagnostic molecular reports, are necessary for accurate interpretation. Furthermore, standardization remains a significant challenge, requiring the development and validation of protocols through interlaboratory studies. In this regard, collaborative efforts involving international consortia are imperative for establishing universally applicable guidelines for clinical implementation [63].

The previously mentioned studies are summarized in Table 1 and depicted in Fig. 2.

Table 1 Liquid biopsy in lymphomas as an emerging diagnostic and monitoring tool

Fig. 2

Diagram illustrating the primary advantages of liquid biopsy in oncology and the main published studies. Previous selected investigations that utilized cytokines, proteins, miRNAs, and circulating DNAs are depicted along with a reference to the specific timepoint during the patient's clinical course when the blood samples were extracted and studied. Studies in dashed squares explore the role of extracellular vesicles in HL

Beyond circulating tumor DNA: extracellular vesicles and circulating RNAs

Extracellular vesicles (EVs) exhibit a wide range of sizes and biogenesis pathways. Apoptotic bodies (1–4 µm) and microvesicles (100–1000 nm) originate from plasma membrane budding. In this regard, exosomes, a subset of EVs, are small membrane microvesicles (40–150 nm) derived from endosomes within multivesicular bodies [64] playing a crucial role in intercellular communication. The formation of exosomes begins with the invagination of the plasma membrane, leading to the creation of intracellular multivesicular bodies containing intraluminal vesicles. Exosomes report tumor-derived information as they carry diverse types of biomolecules, including proteins, lipids, and nucleic acids which are essential for molecular interrogation. Their vital role in intercellular communication has been extensively documented [65, 66]. Importantly, exosomes have garnered significant attention due to their remarkable capacity to transport molecules of interest, which hold potential as disease biomarkers and tumor-derived information [67].

Furthermore, EVs have been found to influence neoplasia promotion. Studies have revealed that various molecules, such as nucleic acids and signaling proteins, can induce protumorigenic effects in tumor microenviroment [64]. Metastasis research has also highlighted the involvement of EV-mediated communication, for example in prostate cancer [68, 69]. In the field of biomedical research, EVs are being extensively investigated as potential biomarkers for predicting clinical outcomes. Their intriguing properties and ability to reflect disease-related changes make them promising candidates for future diagnostic and prognostic applications.

In HL, one of the earliest studies showed that these patients present a more prominent appearance of smaller EVs (< 0.3 µm) than the control group. Also, the concentration of plasmatic EVs was statistically higher in patients with HL than in the control group. Importantly, some tumor-related antigens significantly expressed in HL compared to controls were CD61 and CD30. In particular, CD30 was observed with higher levels in early disease stages [70].

Proteins are among the components present in EVs. In this regard, Repetto et al. carried out a proteomic study using two-dimensional difference gel electrophoresis followed by liquid chromatography-tandem mass spectrometry to identify proteins in EVs from patients with HL. They described differences in certain proteins between relapsed and no-relapsed pediatric patients with HL. Importantly, the proteins found exclusively in patients when comparing with healthy controls were described to participate in platelet degranulation and serine-type endopeptidase activities [66]. This study is summarized in Table 2 and included in Fig. 2.

Table 2 Protein profiles of exosomes

Other intriguing investigations have focused on developing novel biosensors to detect EVs released by HRS cells, with potential implications for the diagnosis and treatment-response monitoring of this disease. In this context, Slyusarenko et al. employed the HRS marker CD30 to capture EVs from HRS cells using gold nanoparticles (AuNPs) with peroxidase activity. They observed an increased number of CD30-positive particles in the plasma of patients with cHL compared to healthy individuals. Furthermore, they discovered a strong correlation with PET-CT scans and a significant decrease in the number of CD30-positive particles in patients with cHL after two cycles of chemotherapy [71].

Furthermore, EVs carry a wide array of cargo with significant biological relevance in cancer. Among these cargoes, microRNAs (miRNAs) are small, double-stranded RNA molecules comprising approximately 19–35 nucleotides. They play a crucial role in regulating gene expression, controlling differentiation, and modulating proliferation at the post-transcriptional level. Notably, miRNAs exhibit remarkable stability in the bloodstream [72]. Recent studies on exosome-derived miRNAs in various tumor types have indicated their potential use as biomarkers. These biomarkers, in combination with other circulating RNAs, can serve diagnostic purposes and also aid in predicting responses to treatments [73, 74].

In a groundbreaking analysis involving patients with cHL, Van Eijndhoven et al. investigated the association between EV-associated and free plasma miRNAs with metabolic disease. The authors observed a more extensive repertoire of EV-associated miRNAs and identified elevated levels of miR24-3p, miR127-3p, miR21-5p, let7a-5p, and miR155-5p in patients with cHL compared to healthy controls. Importantly, this study demonstrated the potential of miRNAs for disease monitoring. They observed that miRNA levels decreased in patients achieving complete metabolic response during long-term plasma follow-up, consistent with FDG-PET findings. Additionally, these levels increased in relapsed patients [75].

As previously mentioned, conventional imaging techniques for evaluating treatment response in Hodgkin lymphoma (HL) cannot be frequently repeated, highlighting the need for identifying novel biomarkers for monitoring therapy outcomes. In a recent study, Drees et al. conducted a comparison between the expression of specific EV-associated miRNAs and FDG-PET assessments in patients with cHL. Their findings revealed a significant increase in miR-127-3p, miR-155-5p, miR-21-5p, miR-24-3p, and let-7a-5p in pre-treatment patients with cHL compared to individuals who exhibited treatment response. Remarkably, these miRNA levels remained elevated in non-responsive patients. Furthermore, combining EV-miR-127-3p and/or EV-let-7a-5p with serum TARC (a validated protein biomarker in cHL) significantly enhanced the accuracy of predicting PET status, resulting in a specificity of 83.8% to 85.0% and a sensitivity of 93.5%, with a negative predictive value of 96% [76].

In this context, the same investigators also examined the relationship between blood-based biomarkers, including EV-miRNAs, and specific assessments using FDG-PET. Prior to treatment initiation, they observed correlations between EV-miR127-3p, EV-miR24-3p, serum TARC, and complete blood counts with the metabolic tumor volume and dissemination features, albeit not with intensities. Additionally, certain other EV-miRNAs exhibited weak correlations with other PET features [77]. In biofluids, miRNAs can circulate either in combination with EVs, as previously mentioned, or as free molecules, often associated with proteins. To our knowledge, there is only one significant publication that characterizes the presence of free miRNAs in cHL. In this study, conducted by Jones et al., over 1,000 miRNAs were profiled in a small cohort comprising 14 primary cHL tissues and eight healthy lymph nodes. The findings revealed an association between miR-494 and miR-1973 with the disease. Subsequently, the presence of these miRNAs was assessed in the plasma of a cohort of patients. Blood samples were analyzed at various time points, including pre-treatment, during treatment, and after remission. The results showed that miR-494, miR-1973, and miR-21 exhibited increased levels in patients with cHL compared to healthy controls, and these levels became undetectable after achieving remission. Notably, only miR-494 and miR-1973 correlated with interim therapy responses [78].

Another critical aspect to consider is the potential for therapy-related side effects, often associated with the toxicity mentioned earlier. In this context, a recent study delved into the impact of therapy on fertility, specifically examining the risk of temporary or permanent loss of fertility. In this study, conducted by Caponnetto et al., researchers utilized follicular fluid samples from women affected by HL. Their findings revealed the deregulation of 13 miRNAs in these women when compared to the control group. Several of these deregulated miRNAs were found to play roles in biological processes linked to follicle development and oocyte maturation [79].

All of the aforementioned studies have underscored the promising potential of liquid biopsy, extending beyond ctDNA, in the context of cHL. However, further investigations are warranted, particularly those incorporating high-throughput sequencing technologies, to provide a comprehensive overview of the circulating RNA landscape. Furthermore, future studies that integrate insights from various 'omics' disciplines have the potential to yield innovative non-invasive tools for monitoring treatment responses.

These studies are summarized in Table 3 and included in Fig. 2.

Table 3 Beyond circulating tumor DNA: Extracellular vesicles and circulating miRNAs

Beyond circulating tumor DNA: Cytokines

Cytokines, characterized by a relative molecular weight below 30,000 Da, are either polypeptides or glycoproteins. They play a crucial role in supplying signals for the growth, differentiation, inflammation, or anti-inflammatory responses of various cell types. Additionally, they have the capacity to activate immune cells against tumors or counteract immunosuppression, ultimately leading to the inhibition of tumor growth [80]. As mentioned above, HRS cells in cHL constitute a minor fraction of the tumor and are overshadowed by a predominant mixed inflammatory infiltrate. Patients with cHL often exhibit constitutional symptoms such as fever, weight loss, and night sweats, along with a discernible systemic deficiency in cell-mediated immune responses. These distinct clinical and histopathologic characteristics of cHL are indicative of an abnormal immune response, primarily attributed to a diverse array of cytokines produced by HRS cells and, to a lesser extent, by the surrounding reactive infiltrate [81].

Similar to ctDNA, cytokines can be identified in blood samples from cancer patients through minimally invasive approaches [82]. Their presence has been demonstrated to correlate with the risk of developing specific types of cancer [83,84,85] as well as being associated with the tumor stage [86] and prognosis [87] or influencing treatment efficacy [88]. Indeed, certain studies have conducted a combined analysis to detect both ctDNA and cytokines as potential non-invasive biomarkers [89, 90]. In cHL, one interesting study assessed the prognostic value of pretreatment serum cytokine levels in cHL. The authors observed elevated levels of twelve cytokines in patients with cHL compared to controls, with HGF, IL-6, IL-2R, IP-10, and MIG linked to poorer event-free survival (EFS). IL-2R and IL-6 were independently prognostic, associating with a higher risk of early relapse and death. Notably, this remained significant after adjusting for the International Prognostic Score (IPS). The study suggests that pretreatment cytokine profiling, particularly focusing on IL-6 and IL-2R, could effectively identify high-risk cHL patients prone to early-disease relapse and may serve as an additional prognostic tool beyond existing risk stratification methods [91]. In addition, other publications have also confirmed the role of IL-6 as biomarker for disease outcome in patients with cHL [92]. Furthermore, another study showed the involvement of other cytokines such as IL-10, TNF-α, IFN-γ, IL-8, and TNFSF10 associated with high-risk disease, as well as CCL13, IFN-λ1, and IL-8 with treatment response [93]. Additionally, a recent publication showed serum concentration kinetics of key cytokines in patients with cHL. They compared these levels with PET/CT scan results and treatment outcomes. Herein, they investigators observed the median concentration of IL-10, IL-6, TNF-α at end-of-treatment-PET (EOT-PET) decreased in comparison with the levels at initial PET (PET-0), while IFNγ and IPI10 showed an increase. Also, IL-8 levels were increased in HL compared to FL. Overall, they observed that only the levels of TARC showed variations during therapy, correlating well with the results of PET/CT and therefore also with the response to therapy, especially in cHL. These results should be taken with caution considering the small patient cohort included in this study [94]. However, TARC levels prove useful in assessing treatment failure or extrapulmonary spread, with decreased levels correlating with better treatment response and complete remission, while elevated levels are associated with positive PET scans in other studies [95, 96]. Finally, other investigations have linked viral infections as a crucial factor influencing local expression of chemokines rather than HL subtypes [97,98,99].

In cHL, cytokines may play a dual role—complementing ctDNA or other tumor components in disease diagnosis, treatment monitoring, or MRD detection, as observed in studies on other tumor types [89, 90] and contributing to the development of novel treatment strategies [80, 100,101,102]. Cytokines, with their pivotal signaling role in cHL, stand out as promising components in the quest for biomarkers through liquid biopsies.

The previously mentioned studies are summarized in Table 4 and included in Fig. 2.

Table 4 Beyond circulating tumor DNA: Cytokines

Conclusion

In the evolving landscape of liquid biopsy for HL, numerous crucial questions persist. The clinical integration of liquid biopsy demands thorough validation across diverse patient populations, necessitating exploration of optimal timing, frequency, and specific clinical contexts for its application. Integrative approaches spanning proteomics, genomics, and epigenomics hold the potential for innovative non-invasive tools, yet their exact contributions and clinical implications require further exploration. Robust validation through expanded patient cohorts is essential, considering potential variations in liquid biopsy performance across HL subtypes and stages. Moreover, understanding how liquid biopsy data can effectively inform treatment decisions and its economic implications compared to traditional imaging modalities is pivotal for its seamless integration into routine clinical practice, offering personalized strategies for managing this hematologic malignancy.