Cell-of-origin subtype classification and prognosis of diffuse large B-cell lymphoma based on variable importance analysis

HAO Ting; GAO Qian; XI Yanfeng; GUAN Hongwei; WANG Tong

doi:10.16462/j.cnki.zhjbkz.2024.02.011

Volume 28 Issue 2

Feb. 2024

Turn off MathJax

Article Contents

Article Navigation > CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION > 2024 > 28(2): 198-202

HAO Ting, GAO Qian, XI Yanfeng, GUAN Hongwei, WANG Tong. Cell-of-origin subtype classification and prognosis of diffuse large B-cell lymphoma based on variable importance analysis[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2024, 28(2): 198-202. doi: 10.16462/j.cnki.zhjbkz.2024.02.011

Citation:

HAO Ting, GAO Qian, XI Yanfeng, GUAN Hongwei, WANG Tong. Cell-of-origin subtype classification and prognosis of diffuse large B-cell lymphoma based on variable importance analysis[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2024, 28(2): 198-202. doi: 10.16462/j.cnki.zhjbkz.2024.02.011

Citation:

HAO Ting, GAO Qian, XI Yanfeng, GUAN Hongwei, WANG Tong. Cell-of-origin subtype classification and prognosis of diffuse large B-cell lymphoma based on variable importance analysis[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2024, 28(2): 198-202. doi: 10.16462/j.cnki.zhjbkz.2024.02.011

PDF( 7511 KB)

Cell-of-origin subtype classification and prognosis of diffuse large B-cell lymphoma based on variable importance analysis

doi: 10.16462/j.cnki.zhjbkz.2024.02.011

1.
Department of Health Statistics, School of Public Health, Shanxi Medical University, Key Laboratory of Coal Environmental Pathogenicity and Prevention, Ministry of Education, Taiyuan 030001, China
2.
Department of Pathology, Shanxi Provincial Cancer Hospital, Taiyuan 030013, China
3.
School of Health Sciences and Human Performance, Ithaca College, New York 14850, USA

Funds:

National Natural Science Foundation of China 82073674

National Natural Science Foundation of China 82204163

Shanxi Province Basic Research Programme 202203021212382

More Information

Corresponding author: WANG Tong, E-mail: tongwang@sxmu.edu.cn
Received Date: 2023-08-07
Rev Recd Date: 2023-10-20

Available Online: 2024-03-30

Publish Date: 2024-02-10

Abstract

Abstract

Objective Gene expression profiling (GEP) is the gold standard for cell-of-origin COO classification of diffuse large B-cell lymphoma (DLBCL). The aim of this study was to establish a GEP-based parsimony model to accurately predict the COO subtypes of DLBCL and provide a reference for its clinical application. Methods Genetic and clinical data from 6 DLBCL datasets in the GEO database were collected, and one dataset was used as the training set and the remaining five as the validation set. A variable importance analysis strategy based on penalized regression analysis was constructed to identify the optimal subset of variables, and a logistic regression analysis was performed to determine the six-gene model that was ultimately used for COO classification. Survival analysis was used to assess the relationship between the two COO subtypes predicted by the training and validation sets and clinical prognosis. Results The six-gene model predicted better in the training set [AUC(95% CI): 0.999 (0.997~1.000), discriminant slope and its 95% CI were 0.944 (0.920~0. 966)], and also showed better results in the validation set [AUC and its 95% CI fluctuated from 0.910 (0.820~0.999) to 1.000, and the discriminant slope and its 95% CI fluctuated from 0.506 (0.350~0. 966) to 0.927 (0.841~0.987)]. The prognostic modeling showed that the six genetically predicted subtypes were risk predictors in both the training and validation sets (all P < 0.05). Conclusions The six genes in the six-gene model have important clinical applications for the classification and prognosis of DLBCL. The gene ordering based on variable importance provides a reference basis for further-research on gene function and targeted drug research.
- Diffuse large B-cell lymphoma,
- Penalized regression,
- Prognosis,
- Subtype classification,
- Variable importance analysis

FullText(HTML)

References(20)

References

[1]	Tilly H, Gomes da Silva M, Vitolo U, et al. Diffuse large B-cell lymphoma (DLBCL): ESMO clinical practice guidelines for diagnosis, treatment and follow-up [J]. Ann Oncol, 2015, 26(Suppl 5): v116-v125. DOI: 10.1093/annonc/mdv304.
[2]	Alizadeh AA, Eisen MB, Davis RE, et al. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling [J]. Nature, 2000, 403(6769): 503-511. DOI: 10.1038/35000501.
[3]	Li SY, Young KH, Medeiros LJ. Diffuse large B-cell lymphoma [J]. Pathology, 2018, 50(1): 74-87. DOI: 10.1016/j.pathol.2017.09.006.
[4]	Zou H. The adaptive lasso and its oracle properties [J]. J Am Stat Assoc, 2006, 101(476): 1418-1429. DOI:10.1198/01621450600 735.
[5]	Zou H, Hastie T. Addendum: regularization and variable selection via the elastic net [J]. J Royal Stat Soc Ser B Stat Methodol, 2005, 67(5): 768. DOI: 10.1111/j.1467-9868.2005.00527.x.
[6]	Tibshirani R. Regression shrinkage and selection via the lasso [J]. J Royal Stat Soc Ser B Methodol, 1996, 58(1): 267-288. DOI: 10.1111/j.2517-6161.1996.tb02080.x.
[7]	Zhang CH. Nearly unbiased variable selection under minimax concave penalty [J]. Ann Statist, 2010, 38(2): 894-942. DOI: 10.1214/09-aos729.
[8]	Hoerl AE, Kennard RW. Ridge regression: biased estimation for nonorthogonal problems [J]. Technometrics, 1970, 12(1): 55-67. DOI: 10.1080/00401706.1970.10488634.
[9]	Pihur V, Datta S, Datta S. RankAggreg, an R package for weighted rank aggregation [J]. BMC Bioinformatics, 2009, 10: 62. DOI: 10.1186/1471-2105-10-62.
[10]	Lenz G, Wright G, Dave SS, et al. Stromal gene signatures in large-B-cell lymphomas[J]. N Engl J of Med, 2008, 359(22): 2313-2323. DOI: 10.1056/NEJMoa0802885.
[11]	Golay J, Broccoli V, Lamorte G, et al. The A-Myb transcription factor is a marker of centroblasts in vivo [J]. J Immunol, 1998, 160(6): 2786-2793.
[12]	Muppidi JR, Schmitz R, Green JA, et al. Loss of signalling via Gα13 in germinal centre B-cell-derived lymphoma [J]. Nature, 2014, 516(7530): 254-258. DOI: 10.1038/nature13765.
[13]	Flori M, Schmid CA, Sumrall ET, et al. The hematopoietic oncoprotein FOXP1 promotes tumor cell survival in diffuse large B-cell lymphoma by repressing S1PR2 signaling [J]. Blood, 2016, 127(11): 1438-1448. DOI: 10.1182/blood-2015-08-662635.
[14]	Onishi H, Yamasaki A, Kawamoto M, et al. Hypoxia but not normoxia promotes Smoothened transcription through upregulation of RBPJ and Mastermind-like 3 in pancreatic cancer [J]. Cancer Lett, 2016, 371(2): 143-150. DOI: 10.1016/j.canlet.2015.11.012.
[15]	Muppidi JR, Schmitz R, Green JA, et al. Loss of signalling via Gα13 in germinal centre B-cell-derived lymphoma [J]. Nature, 2014, 516(7530): 254-258. DOI: 10.1038/nature13765.
[16]	Devaney JM, Wang S, Funda S, et al. Identification of novel DNA-methylated genes that correlate with human prostate cancer and high-grade prostatic intraepithelial neoplasia [J]. Prostate Cancer Prostatic Dis, 2013, 16(4): 292-300. DOI: 10.1038/pcan.2013.21.
[17]	Lotem J, Sachs L. Epigenetics and the plasticity of differentiation in normal and cancer stem cells [J]. Oncogene, 2006, 25(59): 7663-7672. DOI: 10.1038/sj.onc.1209816.
[18]	Liu Q, Liu YX, Li WL, et al. Genetic, epigenetic, and molecular landscapes of multifocal and multicentric glioblastoma [J]. Acta Neuropathol, 2015, 130(4): 587-597. DOI: 10.1007/s00401-015-1470-8.
[19]	Care MA, Cocco M, Laye JP, et al. SPIB and BATF provide alternate determinants of IRF4 occupancy in diffuse large B-cell lymphoma linked to disease heterogeneity [J]. Nucleic Acids Res, 2014, 42(12): 7591-7610. DOI: 10.1093/nar/gku451.
[20]	Scott DW, Wright GW, Williams PM, et al. Determining cell-of-origin subtypes of diffuse large B-cell lymphoma using gene expression in formalin-fixed paraffin-embedded tissue [J]. Blood, 2014, 123(8): 1214-1217. DOI: 10.1182/blood-2013-11-536433.