Circulating immune markers and risks of non-Hodgkin lymphoma subtypes: A pooled analysis

Jongeun Rhee; Brenda M Birmann; Anneclaire J De Roos; Mara M Epstein; Otoniel Martinez-Maza; Elizabeth C Breen; Larry I Magpantay; Lynn I Levin; Kala Visvanathan; H Dean Hosgood 3rd; Thomas E Rohan; Sylvia W Smoller; Bryan A Bassig; Lihong Qi; Xiao-Ou Shu; Woon-Puay Koh; Wei Zheng; Jian-Min Yuan; Stephanie J Weinstein; Demetrius Albanes; Qing Lan; Nathaniel Rothman; Mark P Purdue

doi:10.1002/ijc.34299

Circulating immune markers and risks of non-Hodgkin lymphoma subtypes: A pooled analysis

Int J Cancer. 2023 Mar 1;152(5):865-878. doi: 10.1002/ijc.34299. Epub 2022 Oct 5.

Authors

Jongeun Rhee¹, Brenda M Birmann², Anneclaire J De Roos³, Mara M Epstein⁴, Otoniel Martinez-Maza^{5

6

7

8

9}, Elizabeth C Breen¹⁰, Larry I Magpantay^{8

9}, Lynn I Levin¹¹, Kala Visvanathan^{12

13}, H Dean Hosgood 3rd¹⁴, Thomas E Rohan¹⁴, Sylvia W Smoller¹⁴, Bryan A Bassig¹, Lihong Qi¹⁵, Xiao-Ou Shu¹⁶, Woon-Puay Koh^{17

18}, Wei Zheng¹⁶, Jian-Min Yuan^{19

20}, Stephanie J Weinstein¹, Demetrius Albanes¹, Qing Lan¹, Nathaniel Rothman¹, Mark P Purdue¹

Affiliations

¹ Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, USA.
² Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.
³ Department of Environmental and Occupational Health, Dornsife School of Public Health, Drexel University, Philadelphia, Pennsylvania, USA.
⁴ Department of Medicine and the Meyers Health Care Institute, University of Massachusetts Chan Medical School, Worcester, Massachusetts, USA.
⁵ Department of Microbiology, Immunology & Molecular Genetics, University of California, Los Angeles, Los Angeles, California, USA.
⁶ Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, California, USA.
⁷ Jonsson Comprehensive Cancer Center, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA.
⁸ UCLA AIDS Institute, Los Angeles, California, USA.
⁹ Department of Obstetrics & Gynecology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA.
¹⁰ Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA.
¹¹ Statistics and Epidemiology Branch, Walter Reed Army Institute of Research, Silver Spring, Maryland, USA.
¹² Johns Hopkins Sidney Kimmel Comprehensive Cancer Center, Baltimore, Maryland, USA.
¹³ Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
¹⁴ Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, New York, USA.
¹⁵ Department of Public Health Sciences, University of California Davis, Davis, California, USA.
¹⁶ Division of Epidemiology, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee, USA.
¹⁷ Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
¹⁸ Singapore Institute for Clinical Sciences, Agency for Science Technology and Research (A*STAR), Singapore, Singapore.
¹⁹ Division of Cancer Control and Population Sciences, University of Pittsburgh Medical Center (UPMC) Hillman Cancer Center, Pittsburgh, Pennsylvania, USA.
²⁰ Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.

Abstract

Although prediagnostic circulating concentrations of the immune activation markers soluble CD27 (sCD27), sCD30 and chemokine ligand-13 (CXCL13) have been associated with non-Hodgkin lymphoma (NHL) risk, studies have been limited by sample size in associations with NHL subtypes. We pooled data from eight nested case-control studies to investigate subtype-specific relationships for these analytes. Using polytomous regression, we calculated odds ratios (ORs) with 95% confidence intervals (CIs) relating study-specific analyte tertiles to selected subtypes vs controls (n = 3310): chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL; n = 623), diffuse large B cell lymphoma (DLBCL; n = 621), follicular lymphoma (FL; n = 398), marginal zone lymphoma (MZL; n = 138), mantle cell lymphoma (MCL; n = 82) and T cell lymphoma (TCL; n = 92). We observed associations with DLBCL for elevated sCD27 [OR for third vs first tertile (OR_T3 ) = 2.2, 95% CI = 1.6-3.1], sCD30 (OR_T3 = 2.0, 95% CI = 1.6-2.5) and CXCL13 (OR_T3 = 2.3, 95% CI = 1.8-3.0). We also observed associations with sCD27 for CLL/SLL (OR_T3 = 3.3, 95% CI = 2.4-4.6), MZL (OR_T3 = 7.7, 95% CI = 3.0-20.1) and TCL (OR_T3 = 3.4, 95% CI = 1.5-7.7), and between sCD30 and FL (OR_T3 = 2.7, 95% CI = 2.0-3.5). In analyses stratified by time from phlebotomy to case diagnosis, the sCD27-TCL and all three DLBCL associations were equivalent across both follow-up periods (<7.5, ≥7.5 years). For other analyte-subtype comparisons, associations were stronger for the follow-up period closer to phlebotomy, particularly for indolent subtypes. In conclusion, we found robust evidence of an association between these immune markers and DLBCL, consistent with hypotheses that mechanisms related to immune activation are important in its pathogenesis. Our other findings, particularly for the rarer subtypes MZL and TCL, require further investigation.

Keywords: CXCL13; immune markers; non-Hodgkin lymphoma; sCD27; sCD30.

Publication types

Research Support, N.I.H., Intramural

MeSH terms

Adult
Biomarkers
Case-Control Studies
Humans
Leukemia, Lymphocytic, Chronic, B-Cell* / complications
Lymphoma, Follicular*
Lymphoma, Large B-Cell, Diffuse*
Lymphoma, Mantle-Cell*
Lymphoma, Non-Hodgkin* / etiology

Substances

Biomarkers

Abstract

Publication types

MeSH terms

Substances

Grants and funding