Novel immune gene expression signature risk-stratifies Mantle Cell Lymphoma outcomes independent of TP53 status

Abstract Background: The prognostic impact of specific genomic changes in mantle cell lymphoma (MCL) is not well characterized beyond altered TP53, which is recognized as a high-risk marker and commonly assessed at diagnosis, and the “proliferation signature” developed using gene expression in fresh frozen tissues (Rosenwald et al, Cancer Cell 2003). To bridge this knowledge gap, we applied comprehensive tumor sequencing to investigate how genomic abnormalities affect prognosis in patients (pts) with MCL with and without TP53 alterations. Methods: The Atlas of Blood Cancer Genomes project is an international collaborative effort including 25 sites for collecting and sequencing all blood cancers (Love et al, ASH 2021). We recruited MCL pts with detailed clinical data and subjected their tumors to whole exome, whole transcriptome, and targeted sequencing. TP53-aberrant cases (i.e., mutation or deletion) were identified from sequencing and clinical pathology reports. Progression-free survival (PFS) and overall survival (OS) were measured using the Kaplan-Meier method, with statistical comparisons by the log-rank test. Risk for a gene signature was defined as the coefficient from the respective Cox proportional hazard model. Results: RNA and DNA sequencing were performed successfully for 252 pts with MCL. Clinical features and treatment regimens were consistent with prior disease descriptions and have been reported previously (Koff et al, ASH 2022). In the entire cohort, median PFS was 38 months, and median OS was not reached. As expected, TP53 abnormalities were associated with inferior OS compared to TP53-wildtype (WT; 5-year OS 48% and 79%, respectively, p<0.001). A novel gene expression signature (“immune signature”) was determined by identifying genes that displayed prognostic ability independent of the previously described MCL proliferation signature (Rosenwald et al, Cancer Cell 2003; Scott et al, J Clinical Oncology 2017). This signature was distinct from the proliferation signature both in terms of included genes and ability to discriminate between risk groups; the correlation plot between the immune and proliferation signature scores showed a low R2 value of 0.01. The immune signature appears to derive from differences in tumor microenvironment (TME) CD8+ T and T follicular helper cells: pts designated as high-risk by the immune signature demonstrated lower proportions of these TME subsets as assessed by CIBERSORT (p=0.001). For the cohort with tumors sequenced prior to treatment (n=208), 5-year OS was 45% for pts with a high-risk immune score (bottom quartile), 80% for pts with intermediate-risk immune score (middle 2 quartiles), and 91% for low-risk immune score (top quartile, p <0.001), with improved discrimination compared to the proliferation signature (56%, 79%, and 80% for high-, intermediate-, and low-risk proliferation scores, respectively; p=0.03). The immune signature also risk-stratified outcomes in MCL subgroups with and without TP53 alteration. For pts with TP53-WT (n=74), low-risk immune score predicted 5-year OS of 86%, while high-risk immune score was associated with 5-year OS of 38% (p<0.001), compared to 72% vs 82% for low-risk and high-risk proliferation scores (p=0.16). For pts with aberrant TP53 (n=43), low-risk immune score had 5-year OS of 77%, and high-risk immune score had 5-year OS of 9% (p<0.001), compared to 35% vs 52% for low-risk and high-risk proliferation scores (p=0.28). Application of the immune signature also further stratified pts deemed high-risk by the proliferation score (n=52): within this group, low-risk immune score associated with 5-year OS of 76%, and high-risk immune score predicted 5-year OS of 29% (p<0.001). Similar stratification was also observed when the immune signature was applied to pts with low- and intermediate-risk proliferation scores (n=156; 5-year OS of 88% vs 57% for low-risk vs high-risk immune score respectively, p<0.001). Conclusions: In this largest-ever study of MCL's genomic landscape, we identify a novel gene expression signature that stratifies risk within and across existing prognostic groups, including TP53-altered cases. Our findings support development of the immune signature as a tool that can be used in routine clinical practice to improve risk stratification of all MCL patients at diagnosis. Additional study is warranted to define therapeutic implications of differential TME T cell subset composition in MCL.

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Journal
Blood
Published
2025-11-03
DOI
https://doi.org/10.1182/blood-2025-352
Primary Topic
Lymphoma Diagnosis and Treatment
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article
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article

Novel immune gene expression signature risk-stratifies Mantle Cell Lymphoma outcomes independent of TP53 status

Katelin Baird, Jonathon Brett Cohen, Anne Ortved Gang, Devang Thakkar et al.
Blood
Lymphoma Diagnosis and Treatment
article

Novel immune gene expression signature risk-stratifies Mantle Cell Lymphoma outcomes independent of TP53 status

Katelin Baird, Jonathon Brett Cohen, Anne Ortved Gang, Devang Thakkar, Michael C. Churnetski, Abner Louissaint, Kikkeri N. Naresh, Yuri D. Fedoriw, Colin B. O’Leary, Magdalena Czader, Sarah Lynn Ondrejka, Izidore S. Lossos, Sirpa Leppä, Rex K.H. Au-Yeung, Eric Tse, Andrew M. Evens, Amy Chadburn, Veronica S. Russell, David L. Jaye, Clayton Parker, Emily Ferguson Mason, Choon Kiat Ong, Cassandra Love, Christopher R. Flowers, Jean Louise Koff, Mette Ølgod Pedersen, Jennifer Rose Chapman, Rachel Kositsky, Sandeep S. Davé, Dina Sameh Soliman, Yan Jiong, Shaoying Li, Jessie Xu, Andrew Evans
article en

Abstract

Abstract Background: The prognostic impact of specific genomic changes in mantle cell lymphoma (MCL) is not well characterized beyond altered TP53, which is recognized as a high-risk marker and commonly assessed at diagnosis, and the “proliferation signature” developed using gene expression in fresh frozen tissues (Rosenwald et al, Cancer Cell 2003). To bridge this knowledge gap, we applied comprehensive tumor sequencing to investigate how genomic abnormalities affect prognosis in patients (pts) with MCL with and without TP53 alterations. Methods: The Atlas of Blood Cancer Genomes project is an international collaborative effort including 25 sites for collecting and sequencing all blood cancers (Love et al, ASH 2021). We recruited MCL pts with detailed clinical data and subjected their tumors to whole exome, whole transcriptome, and targeted sequencing. TP53-aberrant cases (i.e., mutation or deletion) were identified from sequencing and clinical pathology reports. Progression-free survival (PFS) and overall survival (OS) were measured using the Kaplan-Meier method, with statistical comparisons by the log-rank test. Risk for a gene signature was defined as the coefficient from the respective Cox proportional hazard model. Results: RNA and DNA sequencing were performed successfully for 252 pts with MCL. Clinical features and treatment regimens were consistent with prior disease descriptions and have been reported previously (Koff et al, ASH 2022). In the entire cohort, median PFS was 38 months, and median OS was not reached. As expected, TP53 abnormalities were associated with inferior OS compared to TP53-wildtype (WT; 5-year OS 48% and 79%, respectively, p<0.001). A novel gene expression signature (“immune signature”) was determined by identifying genes that displayed prognostic ability independent of the previously described MCL proliferation signature (Rosenwald et al, Cancer Cell 2003; Scott et al, J Clinical Oncology 2017). This signature was distinct from the proliferation signature both in terms of included genes and ability to discriminate between risk groups; the correlation plot between the immune and proliferation signature scores showed a low R2 value of 0.01. The immune signature appears to derive from differences in tumor microenvironment (TME) CD8+ T and T follicular helper cells: pts designated as high-risk by the immune signature demonstrated lower proportions of these TME subsets as assessed by CIBERSORT (p=0.001). For the cohort with tumors sequenced prior to treatment (n=208), 5-year OS was 45% for pts with a high-risk immune score (bottom quartile), 80% for pts with intermediate-risk immune score (middle 2 quartiles), and 91% for low-risk immune score (top quartile, p <0.001), with improved discrimination compared to the proliferation signature (56%, 79%, and 80% for high-, intermediate-, and low-risk proliferation scores, respectively; p=0.03). The immune signature also risk-stratified outcomes in MCL subgroups with and without TP53 alteration. For pts with TP53-WT (n=74), low-risk immune score predicted 5-year OS of 86%, while high-risk immune score was associated with 5-year OS of 38% (p<0.001), compared to 72% vs 82% for low-risk and high-risk proliferation scores (p=0.16). For pts with aberrant TP53 (n=43), low-risk immune score had 5-year OS of 77%, and high-risk immune score had 5-year OS of 9% (p<0.001), compared to 35% vs 52% for low-risk and high-risk proliferation scores (p=0.28). Application of the immune signature also further stratified pts deemed high-risk by the proliferation score (n=52): within this group, low-risk immune score associated with 5-year OS of 76%, and high-risk immune score predicted 5-year OS of 29% (p<0.001). Similar stratification was also observed when the immune signature was applied to pts with low- and intermediate-risk proliferation scores (n=156; 5-year OS of 88% vs 57% for low-risk vs high-risk immune score respectively, p<0.001). Conclusions: In this largest-ever study of MCL's genomic landscape, we identify a novel gene expression signature that stratifies risk within and across existing prognostic groups, including TP53-altered cases. Our findings support development of the immune signature as a tool that can be used in routine clinical practice to improve risk stratification of all MCL patients at diagnosis. Additional study is warranted to define therapeutic implications of differential TME T cell subset composition in MCL.

BloodVol. 146(Supplement 1)
University of North Carolina at Chapel Hill (US), University of Copenhagen (DK), Boston Medical Center (US), Cleveland Clinic (US), Cape Town HVTN Immunology Laboratory / Hutchinson Centre Research Institute of South Africa (ZA), University of Helsinki (FI), The University of Texas MD Anderson Cancer Center (US), University of Indianapolis (US), University of Miami (US), Emory University (US), Duke University (US), University of Toronto (CA), Durham University (GB), Cornell University (US), University of Rochester Medical Center (US), Massachusetts General Hospital (US), Fred Hutch Cancer Center (US), Argos Therapeutics (United States) (US), National Cancer Centre Singapore (SG), Electrophysiology Research Foundation (US), Hamad Medical Corporation (QA), Indiana University – Purdue University Indianapolis (US), Miami University (US), University of Hong Kong (HK), Vanderbilt University Medical Center (US)
Openalex Percentile: Top 46%
Lymphoma Diagnosis and Treatment
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