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Article: A new immunostain algorithm classifies diffuse large B-cell lymphoma into molecular subtypes with high accuracy

TitleA new immunostain algorithm classifies diffuse large B-cell lymphoma into molecular subtypes with high accuracy
Authors
Issue Date2009
PublisherAmerican Association for Cancer Research.
Citation
Clinical Cancer Research, 2009, v. 15 n. 17, p. 5494-5502 How to Cite?
AbstractPurpose: Hans and coworkers previously developed an immunohistochemical algorithm with ∼80% concordance with the gene expression profiling (GEP) classification of diffuse large B-cell lymphoma (DLBCL) into the germinal center B-cell-like (GCB) and activated B-cell-like (ABC) subtypes. Since then, new antibodies specific to germinal center B-cells have been developed, which might improve the performance of an immunostain algorithm. Experimental Design: Westudied 84 cases of cyclophosphamide-doxorubicin-vincristine-prednisone (CHOP)-treated DLBCL (47 GCB, 37 ABC) with GCET1, CD10, BCL6, MUM1, FOXP1, BCL2,MTA3, and cyclin D2 immunostains, and compared different combinations of the immunostaining results with the GEP classification. A perturbation analysis was also applied to eliminate the possible effects of interobserver or intraobserver variations. A separate set of 63 DLBCL cases treatedwith rituximab plus CHOP (37 GCB, 26 ABC) was used to validate the new algorithm. Results: A new algorithm using GCET1, CD10, BCL6, MUM1, and FOXP1 was derived that closely approximated the GEP classification with 93% concordance. Perturbation analysis indicated that the algorithm was robust within the range of observer variance. The new algorithm predicted 3-year overall survival of the validation set [GCB (87%) versus ABC (44%); P < 0.001], simulating the predictive power of the GEP classification. For a group of seven primary mediastinal large B-cell lymphoma, the new algorithm is a better prognostic classifier (all GCB) than the Hans' algorithm (two GCB, five non-GCB). Conclusion: Our new algorithm is significantly more accurate than the Hans' algorithm and will facilitate risk stratification of DLBCL patients and future DLBCL research using archival materials. © 2009 American Association for Cancer Research.
DescriptionComment in: Clin Cancer Res. 2010 Jul 15;16(14):3805-3806 & Clin Cancer Res. 2009 Sep 1;15(17):5291-5293
Persistent Identifierhttp://hdl.handle.net/10722/139911
ISSN
2015 Impact Factor: 8.738
2015 SCImago Journal Rankings: 5.314
ISI Accession Number ID
Funding AgencyGrant Number
National Cancer InstituteU01CAl14778
CA36727
Leukaemia Research Fund of the United Kingdom
Funding Information:

National Cancer Institute Grants U01CAl14778 (W.C. Chan) and CA36727 (W.C. Chan, K. Fu, T.C. Greiner, J.M. Vose, and D.D. Weisenburger), and the Leukaemia Research Fund of the United Kingdom (A.H. Banham).

References

 

DC FieldValueLanguage
dc.contributor.authorChoi, WWLen_HK
dc.contributor.authorWeisenburger, DDen_HK
dc.contributor.authorGreiner, TCen_HK
dc.contributor.authorPiris, MAen_HK
dc.contributor.authorBanham, AHen_HK
dc.contributor.authorDelabie, Jen_HK
dc.contributor.authorBraziel, RMen_HK
dc.contributor.authorGeng, Hen_HK
dc.contributor.authorIqbal, Jen_HK
dc.contributor.authorLenz, Gen_HK
dc.contributor.authorVose, JMen_HK
dc.contributor.authorHans, CPen_HK
dc.contributor.authorFu, Ken_HK
dc.contributor.authorSmith, LMen_HK
dc.contributor.authorLi, Men_HK
dc.contributor.authorLiu, Zen_HK
dc.contributor.authorGascoyne, RDen_HK
dc.contributor.authorRosenwald, Aen_HK
dc.contributor.authorOtt, Gen_HK
dc.contributor.authorRimsza, LMen_HK
dc.contributor.authorCampo, Een_HK
dc.contributor.authorJaffe, ESen_HK
dc.contributor.authorJaye, DLen_HK
dc.contributor.authorStaudt, LMen_HK
dc.contributor.authorChan, WCen_HK
dc.date.accessioned2011-09-23T06:00:28Z-
dc.date.available2011-09-23T06:00:28Z-
dc.date.issued2009en_HK
dc.identifier.citationClinical Cancer Research, 2009, v. 15 n. 17, p. 5494-5502en_HK
dc.identifier.issn1078-0432en_HK
dc.identifier.urihttp://hdl.handle.net/10722/139911-
dc.descriptionComment in: Clin Cancer Res. 2010 Jul 15;16(14):3805-3806 & Clin Cancer Res. 2009 Sep 1;15(17):5291-5293-
dc.description.abstractPurpose: Hans and coworkers previously developed an immunohistochemical algorithm with ∼80% concordance with the gene expression profiling (GEP) classification of diffuse large B-cell lymphoma (DLBCL) into the germinal center B-cell-like (GCB) and activated B-cell-like (ABC) subtypes. Since then, new antibodies specific to germinal center B-cells have been developed, which might improve the performance of an immunostain algorithm. Experimental Design: Westudied 84 cases of cyclophosphamide-doxorubicin-vincristine-prednisone (CHOP)-treated DLBCL (47 GCB, 37 ABC) with GCET1, CD10, BCL6, MUM1, FOXP1, BCL2,MTA3, and cyclin D2 immunostains, and compared different combinations of the immunostaining results with the GEP classification. A perturbation analysis was also applied to eliminate the possible effects of interobserver or intraobserver variations. A separate set of 63 DLBCL cases treatedwith rituximab plus CHOP (37 GCB, 26 ABC) was used to validate the new algorithm. Results: A new algorithm using GCET1, CD10, BCL6, MUM1, and FOXP1 was derived that closely approximated the GEP classification with 93% concordance. Perturbation analysis indicated that the algorithm was robust within the range of observer variance. The new algorithm predicted 3-year overall survival of the validation set [GCB (87%) versus ABC (44%); P < 0.001], simulating the predictive power of the GEP classification. For a group of seven primary mediastinal large B-cell lymphoma, the new algorithm is a better prognostic classifier (all GCB) than the Hans' algorithm (two GCB, five non-GCB). Conclusion: Our new algorithm is significantly more accurate than the Hans' algorithm and will facilitate risk stratification of DLBCL patients and future DLBCL research using archival materials. © 2009 American Association for Cancer Research.en_HK
dc.languageengen_US
dc.publisherAmerican Association for Cancer Research.en_US
dc.relation.ispartofClinical Cancer Researchen_HK
dc.subject.meshGene Expression Profiling-
dc.subject.meshImmunohistochemistry - methods-
dc.subject.meshLymphoma, Large B-Cell, Diffuse - classification - genetics - metabolism-
dc.subject.meshAlgorithms-
dc.subject.meshTumor Markers, Biological - genetics - metabolism-
dc.titleA new immunostain algorithm classifies diffuse large B-cell lymphoma into molecular subtypes with high accuracyen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1078-0432&volume=15&issue=17&spage=5494&epage=5502&date=2009&atitle=A+new+immunostain+algorithm+classifies+diffuse+large+B-cell+lymphoma+into+molecular+subtypes+with+high+accuracyen_US
dc.identifier.emailChoi, WWL:wlchoi@pathology.hku.hken_HK
dc.identifier.authorityChoi, WWL=rp00247en_HK
dc.description.naturelink_to_OA_fulltext-
dc.identifier.doi10.1158/1078-0432.CCR-09-0113en_HK
dc.identifier.pmid19706817-
dc.identifier.scopuseid_2-s2.0-68549124173en_HK
dc.identifier.hkuros168844en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-68549124173&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume15en_HK
dc.identifier.issue17en_HK
dc.identifier.spage5494en_HK
dc.identifier.epage5502en_HK
dc.identifier.eissn1557-3265-
dc.identifier.isiWOS:000269565800025-
dc.publisher.placeUnited Statesen_HK
dc.identifier.f10001164826-

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