Classical Hodgkin's Lymphoma (cHL) is a rare but highly treatable malignancy of the immune system, primarily affecting young adults. Despite significant therapeutic advancements, frontline treatment failure occurs in up to 30% of cases, with relapse or refractory disease affecting over 50% of these patients. The main therapeutic challenge in cHL remains achieving an optimal balance between disease control and reducing long-term adverse effects. Current prognostic tools only partially capture patient heterogeneity, and cHL continues to evolve spatially and temporally throughout the course of the disease. Personalized treatment strategies require novel integrated tools that better monitor tumor complexity and anticipate disease progression.
Fluorodeoxyglucose positron emission tomography (FDG-PET) has improved risk stratification in cHL, as metabolic response during or after chemotherapy strongly correlates with disease progression and survival. However, FDG-PET has limitations, including the absence of standardized criteria and the necessity to initiate treatment before response assessment. To overcome these limitations, molecular profiling and radiomic analysis of baseline FDG-PET data may provide deeper insights into tumor biology, improving prognostic accuracy.
This observational study aims to dissect the genetic and phenotypic heterogeneity of cHL at diagnosis and during disease evolution, with the goal of identifying novel prognostic biomarkers. These findings could lead to better treatment personalization, increasing cure rates while minimizing treatment-related toxicity. The study is based on the hypothesis that correlating DNA profiling at diagnosis, gene expression, and radiomic features may enable the identification of high-risk signatures, refining prognostic models in cHL. Additionally, liquid biopsy represents a non-invasive method for assessing tumor mutational complexity. The analysis of circulating DNA (cDNA) throughout disease progression could provide insights into genetic evolution and help predict overt progression before clinical manifestations occur.
The primary objective is to define the genetic mutational profile of cHL at disease progression. As secondary objectives, it will evaluate whether liquid biopsy can accurately recapitulate the genetic heterogeneity observed in tumor tissue, determine the predictive accuracy of liquid biopsy in anticipating disease progression, and correlate genomic and radiomic features with patient outcomes to refine risk stratification and therapeutic decision-making.
By integrating molecular and imaging-based biomarkers, this study aims to enhance personalized treatment strategies, improve risk-adapted therapeutic approaches, and ultimately optimize curability and quality of life for patients with cHL.
Age >18 anni
Written informed consent signed
Age >18 years
Histologically confirmed diagnosis of relapsed/refractory classical Hodgkin lymphoma identified during induction or follow-up
Patients with nodular lymphocyte predominant Hodgkin lymphoma are not eligible; all other subtypes including nodular sclerosis, lymphocyte-depleted, lymphocyte-rich, and mixed cellularity Hodgkin lymphoma may be enrolled.
Active HIV, HBV, HCV viral infection
Concomitant neoplasm not treated with a curative aim
The study will involve three patient cohorts, with participants recruited from multiple centers across Italy during routine follow-up visits. Cohort A will include 70 patients with classical Hodgkin lymphoma (cHL) who have a histological confirmation of relapse or progression. These patients will be enrolled at the time of disease relapse/progression, and plasma samples for ctDNA analysis will be collected concurrently. Cohort B will consist of 200 cHL patients who have completed active treatment and entered the follow-up phase. Plasma samples will be collected from these patients at the time of enrollment (P0) and again at a six-month follow-up (P6FU). This cohort will be followed for a minimum of two years from the time of enrollment. Cohort C is a retrospective cohort that will be divided into two subgroups: Training cohort: 235 consecutive cHL patients collected from the archives of the Hematology Unit of AUSL-IRCCS between 2004 and 2019. This cohort is representative of the ge
Cohort
Other
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Genetic Mutational Profiling of cHL at Progression
The mutational profile of Classical Hodgkin's Lymphoma patients enrolled in Cohort A will be generated using deep sequencing technologies, including Cancer Personalized Profiling by deep-sequencing (CAPP-seq), on biopsy samples collected at the time of initial diagnosis and at the time of progression to identify key alterations associated with disease progression and aggressiveness.
Liquid Biopsy Ability to Recapitulate Tissue Genetic Heterogeneity
Circulating tumor DNA (ctDNA) from plasma samples collected at baseline (Cohort B) and at the time of disease progression (Cohorts A and B) will be analyzed using CAPP-seq and compared with matched germline DNA (gDNA). Identified mutations will be compared to a background variant database to filter out technical sequencing errors and identify true positive alterations. Heatmaps and COSMIC database annotations will be used to assess the functional relevance of selected variants. The mutational profile in plasma will be compared with biopsy results obtained at progression to evaluate the ability of ctDNA to capture tumor heterogeneity and progression-related alterations.
Accuracy of Liquid Biopsy in Anticipating Disease Progression
Plasma samples of Cohort B patients will be collected at enrollement and at 6 months of follow-up, and the presence of mutations will be assessed using deep sequencing (CAPP-seq). The results will be compared with clinical outcomes over a follow-up period of at least 2 years to determine the specificity and sensitivity of liquid biopsy in predicting progression.
Correlation between Gene Expression Profiling and Progression-free survival (PFS)
Gene expression profiling conducted on tissue samples from subjects in Cohort C at diagnosis will be correlated with progression-free survival (PFS).
Correlation between Gene Expression Profiling and cnical events like relapse and refractoriness
Gene expression profiling conducted on tissue samples from subjects in Cohort C at diagnosis will be correlated with cnical events like relapse and refractoriness).
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