{"entity":{"id":"paper-hans-immunohistochemistry-cell-of-origin-dlbcl-blood-2004","kind":"paper","name":"Confirmation of the molecular classification of diffuse large B-cell lymphoma by immunohistochemistry using a tissue microarray","aka":["Hans algorithm","Hans 2004","CD10, BCL6 and MUM1 classifier"],"tldr":"Three ordinary laboratory stains, available in any hospital, were shown to sort lymphoma into the same two prognostic groups that an expensive gene-expression machine had found.","summary":"The cell-of-origin classification was a research technique: it needed fresh-frozen tissue and a microarray. Hans and colleagues asked whether routine immunohistochemistry on paraffin-embedded tissue could reproduce it. They built tissue microarray blocks from 152 cases of diffuse large B-cell lymphoma, 142 of which had already been classified by complementary DNA microarray (75 germinal-centre, 41 activated B-cell, 26 type 3), and stained for CD10, BCL6, MUM1, FOXP1, cyclin D2 and BCL2.\n\nBCL6 (p < 0.001) and CD10 (p = 0.019) expression went with better overall survival, MUM1 (p = 0.009) and cyclin D2 (p < 0.001) with worse. Using CD10, BCL6 and MUM1, 64 cases (42 per cent) were classed germinal-centre and 88 (58 per cent) non-germinal-centre. Five-year overall survival was 76 per cent for the germinal-centre group against 34 per cent for the non-germinal-centre group (p < 0.001), similar to what the microarray gave. On multivariate analysis an International Prognostic Index of 3 to 5 and the non-germinal-centre phenotype were independent adverse predictors (p < 0.0001).\n\nThe algorithm is the reason the classification exists outside research centres. It is also the reason the classification is noisier than it looks on paper.","asOf":"2026-10-01","links":[{"label":"Blood 2004","url":"https://doi.org/10.1182/blood-2003-05-1545"},{"label":"PubMed","url":"https://pubmed.ncbi.nlm.nih.gov/14504078/"},{"label":"Europe PMC","url":"https://europepmc.org/article/MED/14504078"}],"tags":["lymphoma-evidence"],"related":["paper-rosenwald-molecular-profiling-dlbcl-nejm-2002","paper-wright-lymphgen-genetic-subtypes-dlbcl-cancer-cell-2020","lymphoma-roadmap"],"cancers":["dlbcl","non-hodgkin-lymphoma"],"sections":["diagnostics"],"technologies":[],"targets":["bcl2","bcl6"],"drugs":[],"companies":[],"institutions":[],"pathways":[],"terms":["cell-of-origin","ipi-score"],"trials":[],"people":[],"bottlenecks":["b-biomarker-validation","b-global-access"],"keyPapers":[],"journals":["blood"],"dependsOn":[],"notes":[],"journal":"Blood","year":2004,"doi":"10.1182/blood-2003-05-1545","pmid":"14504078","authors":"Hans CP, Weisenburger DD, Greiner TC, et al.","paperType":"translational","findings":["A three-antibody algorithm using CD10, BCL6 and MUM1 classified 42 per cent of 152 cases as germinal-centre and 58 per cent as non-germinal-centre.","Five-year overall survival was 76 per cent in the germinal-centre group against 34 per cent in the non-germinal-centre group (p < 0.001), similar to the complementary DNA microarray classification.","BCL6 and CD10 expression were associated with better overall survival; MUM1 and cyclin D2 with worse.","BCL2 and cyclin D2 were adverse predictors within the non-germinal-centre group.","On multivariate analysis, an International Prognostic Index of 3 to 5 and the non-germinal-centre phenotype were independent adverse predictors."],"whatItMeans":"The practical form of cell-of-origin classification, used in pathology laboratories worldwide. When a report says germinal-centre or non-germinal-centre, this is almost always the algorithm behind it.","caveats":["Concordance with gene-expression profiling is imperfect, and estimates of the disagreement rate vary widely between series; the algorithm misclassifies a meaningful minority of cases.","Scoring thresholds for the three stains are not fully standardised between laboratories, so the same tumour can be called differently in two hospitals.","The 152 cases came from the same consortium as the profiling study, so this is a confirmation within a cohort rather than an independent validation.","Trials that selected patients by this algorithm for activated B-cell-directed drugs, such as PHOENIX and ROBUST, were negative, which is part of the evidence that it is too blunt an instrument."],"changedPractice":true,"participants":152},"route":"/key-papers/paper-hans-immunohistochemistry-cell-of-origin-dlbcl-blood-2004/","neighbours":{"paper":[{"id":"paper-wright-lymphgen-genetic-subtypes-dlbcl-cancer-cell-2020","kind":"paper","name":"A probabilistic classification tool for genetic subtypes of diffuse large B cell lymphoma with therapeutic implications","route":"/key-papers/paper-wright-lymphgen-genetic-subtypes-dlbcl-cancer-cell-2020/"},{"id":"paper-alizadeh-nature","kind":"paper","name":"Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling","route":"/key-papers/paper-alizadeh-nature/"},{"id":"paper-phoenix-ibrutinib-r-chop-non-gcb-dlbcl-jco-2019","kind":"paper","name":"Randomized phase III trial of ibrutinib and R-CHOP in non-germinal centre B-cell diffuse large B-cell lymphoma (PHOENIX)","route":"/key-papers/paper-phoenix-ibrutinib-r-chop-non-gcb-dlbcl-jco-2019/"},{"id":"paper-rosenwald-molecular-profiling-dlbcl-nejm-2002","kind":"paper","name":"The use of molecular profiling to predict survival after chemotherapy for diffuse large-B-cell lymphoma","route":"/key-papers/paper-rosenwald-molecular-profiling-dlbcl-nejm-2002/"}],"roadmap":[{"id":"lymphoma-roadmap","kind":"roadmap","name":"Lymphoma roadmap: from a jaw tumour in Uganda and the first human cancer virus to gene-expression subtypes, PET-adapted chemotherapy, CAR-T cells, bispecific antibodies and the genetics-directed trials now recruiting","route":"/roadmaps/lymphoma-roadmap/"}],"cancer":[{"id":"dlbcl","kind":"cancer","name":"Diffuse large B-cell lymphoma","route":"/cancers/dlbcl/"},{"id":"non-hodgkin-lymphoma","kind":"cancer","name":"Non-Hodgkin lymphoma (all types)","route":"/cancers/non-hodgkin-lymphoma/"}],"section":[{"id":"diagnostics","kind":"section","name":"Diagnostics & Biomarkers","route":"/fronts/diagnostics/"}],"target":[{"id":"bcl2","kind":"target","name":"BCL-2","route":"/targets/bcl2/"},{"id":"bcl6","kind":"target","name":"BCL6","route":"/targets/bcl6/"}],"term":[{"id":"cell-of-origin","kind":"term","name":"Cell of origin (GCB vs ABC)","route":"/terms/cell-of-origin/"},{"id":"ipi-score","kind":"term","name":"International Prognostic Index (IPI)","route":"/terms/ipi-score/"}],"bottleneck":[{"id":"b-biomarker-validation","kind":"bottleneck","name":"Biomarkers are not validated or standardised","route":"/bottlenecks/b-biomarker-validation/"},{"id":"b-global-access","kind":"bottleneck","name":"Most of the world has almost no cancer care","route":"/bottlenecks/b-global-access/"}],"journal":[{"id":"blood","kind":"journal","name":"Blood","route":"/journals/blood/"}]}}