{"doi":"10.1002/hon.70094_192","title":"192 | FOLLICULAR LYMPHOMA DISPLAYS DISTINCT GENE EXPRESSION PROFILES ACCORDING TO HISTOLOGICAL GRADE","abstract":"E. A. Hawkes, D. Lee, J. Nguyen W. Lin, S. Agrawal, and K. Wong equally contributing author. Introduction: Follicular lymphoma (FL) is a heterogenous disease divided into histological grades; grades (G) 1–2 have similar outcomes and are grouped together, while G3 is divided into G3A and G3B. Histologically G3A and G3B are difficult to distinguish, with grading concordance of 60%–70%. Despite this, differentiation of G3A from G3B is important with major treatment implications. Improved differentiation of FL grades via molecular characterisation has been attempted in small studies with conflicting results. We assessed FL molecular characteristics via modern RNA sequencing and correlated with grade and outcomes. Methods: Tumour samples from patients with nodal FL diagnosed between 2014 and 2020 were selected from tissue banks of 2 Australian sites. Diagnosis and grading were done by an expert lymphoma haematopathologist. Patients were divided into early progressors (progression within 24 mo of diagnosis) versus late/non-progressors (progression after 24 mo or no progression). RNA was extracted using the Qiagen RNeasyA FFPE Kit and quantified by Qubit RNA High Sensitivity Assay Kit. Libraries for sequencing were prepared using the NEBNext Ultra II RNA Library Prep Kit and sequenced on the Nextseq 500 or Novaseq 6000 with 50 or 75bp paired-end reads. Sequenced reads were aligned to the human hg19 genome with HISAT2 and mapped to genes using HTSeq. The resulting gene count data were analysed using the edgeR package in R. Results: 49 samples were analysed: 13 G1/2FL, 24 G3AFL, 12 G3BFL. Median age was 67 years (range: 39–86) with a median follow-up of 39 months (range: 8–87). Early progressors accounted for 17 patients; 2 were G1/2FL, 10 were G3AFL, and 5 were G3BFL. Differential gene expression analysis comparing G1/2FL and G3BFL samples showed that genes involved in DNA replication and mitosis were significantly up-regulated in G3BFL compared with G1/2FL. Unsupervised hierarchical clustering of samples using G1/2FL and G3BFL differentially expressed genes delineated 2 distinct groups of G3AFL—those clustering with G1/2FL and those clustering with G3BFL. Further analysis demonstrated odds of early progression were 6.3 times higher (95% CI: 0.56–344, p = 0.17) in G3AFL clustering with G3BFL compared to those clustering with G1/2FL. Of the 7 G3AFL patients with a gene expression program clustering with G1/2FL, only 1 had early progression, whereas 9 out of 17 patients with a gene expression program clustering with G3BFL had early progression. Conclusions: In the largest study to date, gene expression analysis identified that compared to G1-3AFL, G3BFL upregulates genes involved in cell proliferation, reflecting a more aggressive disease phenotype. G1/2FL and G3BFL display distinct gene expression profiles, while G3AFL overlaps both entities; with early G3AFL progressors clustering with G3BFL and late/non-progressors clustering with G1/2FL. This may enable future clinical trial eligibility of G3AFL to reflect disease biology rather than grade. Research funding declaration: This study was supported by the Austin Health Lymphoma MDT grant fund Keywords: genomics, epigenomics, and other -omics; tumor biology and heterogeneity; indolent non-Hodgkin lymphoma Potential sources of conflict of interest: A. Barraclough Consultant or advisory role: Gilead, Roche, Novartis, Beigene Educational grants: AstraZeneca E. A. Hawkes Consultant or advisory role: Roche*, Merck Sharpe & Dohme*, Astra Zeneca*, Gilead, Antengene*, Novartis*, Regeneron, Janssen*, Specialised Therapeutics*, Sobi* (*paid to institution) Educational grants: Astra Zeneca Other remuneration: Research funding (paid to institution): Roche, Bristol Myers Squibb, Merck KgA, Astra Zeneca, TG therapeutics and Merck","journal":"Hematological Oncology","year":2025,"id":568581,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9618,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":270232,"name":"Eliza A. Hawkes","orcid":"0000-0002-0376-2559","position":1,"is_corresponding":false},{"id":1236760,"name":"Denise Lee","orcid":"0009-0000-9203-925X","position":2,"is_corresponding":false},{"id":1001287,"name":"Jill Nguyen","orcid":"0000-0002-1956-9665","position":3,"is_corresponding":false},{"id":1472861,"name":"Patrick Hosking","orcid":"0009-0007-9425-7841","position":4,"is_corresponding":false},{"id":434471,"name":"W. Lin","orcid":"0000-0002-9335-5702","position":5,"is_corresponding":false},{"id":1473427,"name":"Shivam Agrawal","orcid":null,"position":6,"is_corresponding":false},{"id":730600,"name":"Kimberly Wong","orcid":null,"position":7,"is_corresponding":false},{"id":1473428,"name":"Geoff Chong","orcid":null,"position":8,"is_corresponding":false},{"id":1455798,"name":"Enid Y.N. Lam","orcid":"0000-0001-5843-7836","position":9,"is_corresponding":false},{"id":1472860,"name":"Allison Barraclough","orcid":"0000-0003-1615-0540","position":0,"is_corresponding":true}],"reference_count":0,"raw_metadata":null,"created_at":"2026-07-19T02:56:52.212268Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}