Validation of the RHL30 digital gene expression assay as a prognostic biomarker for relapsed Hodgkin lymphoma

Calvente, Lourdes; Tremblay-Lemay, Rosemarie; Xu, Wei; Chan, Fong Chun; Hong, Michael; Zhang, Tong; Yhim, Ho‐Young; Kuruvilla, John; Crump, Michael; Kukreti, Vishal; Prica, Anca; Regier, Dean A.; Marra, Marco A.; Karsan, Aly; Scott, David W.; Sabatini, Peter; Kridel, Robert

doi:10.1111/bjh.16777

Cited by 7 publications

(6 citation statements)

References 14 publications

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“…Outcome prediction models in relapsed CHL and pediatric patients await further validation. [242][243][244] Although the mutational landscape of CHL is established, [245][246][247] mutational testing for clinical purposes is hampered by the scarcity of the malignant Hodgkin Reed-Sternberg cells. Recent studies suggest the clinical utility of FISH-determined 9p24.1 amplification (harboring CD274, PDCD1LG2, and JAK2) as a favorable predictive biomarker in patients with relapsed/refractory CHL treated with PD1 inhibitors.…”

Section: Pediatric B-cell Lymphomasmentioning

confidence: 99%

Genomic profiling for clinical decision making in lymphoid neoplasms

Leval

Alizadeh

Bergsagel

et al. 2022

Blood

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With the introduction of large-scale molecular profiling methods and high-throughput sequencing technologies, the genomic features of most lymphoid neoplasms have been characterized at an unprecedented scale. While the principles for the classification and diagnosis of these disorders, founded on a multidimensional definition of disease entities, have been consolidated over the past 25 years, novel genomic data have markedly enhanced our understanding of lymphomagenesis and enriched the description of disease entities at the molecular level. Yet the current diagnosis of lymphoid tumors is largely based on morphological assessment and immunophenotyping, with only few entities being defined by genomic criteria. This paper, which accompanies the International Consensus Classification of mature lymphoid neoplasms, will address how established assays and newly developed technologies for molecular testing already complement clinical diagnoses and provide a novel lens on disease classification. More specifically, their contributions to diagnosis refinement, risk stratification and therapy prediction will be considered for the main categories of lymphoid neoplasms. The potential of whole-genome sequencing, circulating tumor DNA analyses, single-cell analyses and epigenetic profiling will be discussed, as these will likely become important future tools for implementing precision medicine approaches in clinical decision-making for patients with lymphoid malignancies.

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Section: Pediatric B-cell Lymphomasmentioning

confidence: 99%

Genomic profiling for clinical decision making in lymphoid neoplasms

Leval

Alizadeh

Bergsagel

et al. 2022

Blood

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“…In part, the latest results were different from those presented in the first work. The RHL30 risk score was associated with FFS post-ASCT, but the same cohort of patients didn't present an association with OS [125].…”

Section: Gep Signature and Tmementioning

confidence: 79%

Hodgkin Lymphoma: A Special Microenvironment

Opinto

Agostinelli

Ciavarella

et al. 2021

JCM

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Classical Hodgkn’s lymphoma (cHL) is one of the most particular lymphomas for the few tumor cells surrounded by an inflammatory microenvironment. Reed-Sternberg (RS) and Hodgkin (H) cells reprogram and evade antitumor mechanisms of the normal cells present in the microenvironment. The cells of microenvironment are essential for growth and survival of the RS/H cells and are recruited through the effect of cytokines/chemokines. We summarize recent advances in gene expression profiling (GEP) analysis applied to study microenvironment component in cHL. We also describe the main therapies that target not only the neoplastic cells but also the cellular components of the background.

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“…Furthermore, most classic models rely on microarray technologies 24 or digital GE pro ling, 56 which are largely based on cell scores derived from GE data and have only been validated for some clinical subsets. 57,58 Our series are too short to allow us to propose a de nitive model, since the number of variable combinations is very high. Similar pipelines in larger and more homogeneous series would be worthwhile, probably based on prospective and longitudinal samples from clinical trials.…”

Section: Discussionmentioning

confidence: 99%

Immune and stromal transcriptional patterns that influence the outcome of classic Hodgkin Lymphoma

Garcı́a

Menéndez²,

Solórzano

et al. 2023

Preprint

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Classic Hodgkin lymphoma (cHL) is characterized by a rich immune microenvironment as the main tumor component. It involves a broad range of cell populations, which are largely unexplored, even though they are known to be essential for growth and survival of Hodgkin and Reed–Sternberg cells. We profiled the gene expression of 25 FFPE cHL samples using NanoString technology and resolved their microenvironment compositions using cell-deconvolution tools, thereby generating patient-specific signatures. The results confirm individual immune fingerprints and recognize multiple clusters enriched in refractory patients, highlighting the relevance of: 1) the composition of immune cells and their functional status, including myeloid cell populations (M1-like, M2-like, plasmacytoid dendritic cells, myeloid-derived suppressor cells, etc.), CD4-positive T cells (exhausted, regulatory, Th17, etc.), cytotoxic CD8 T and natural killer cells; 2) the balance between inflammatory signatures (such as IL6, TNF, IFN-γ/TGF-β) and MHC-I/MHC-II molecules; and 3) several cells, pathways and genes related to the stroma and extracellular matrix remodeling. A validation model combining relevant immune and stromal signatures identifies patients with unfavorable outcomes, producing the same results in an independent cHL series. Our results reveal the heterogeneity of immune responses among patients, confirm previous findings, and identify new functional phenotypes of prognostic and predictive utility.

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Validation of the RHL30 digital gene expression assay as a prognostic biomarker for relapsed Hodgkin lymphoma

Cited by 7 publications

References 14 publications

Genomic profiling for clinical decision making in lymphoid neoplasms

Genomic profiling for clinical decision making in lymphoid neoplasms

Hodgkin Lymphoma: A Special Microenvironment

Immune and stromal transcriptional patterns that influence the outcome of classic Hodgkin Lymphoma

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