1. Accurate Classification of Germinal Center B-Cell–Like/Activated B-Cell–Like Diffuse Large B-Cell Lymphoma Using a Simple and Rapid Reverse Transcriptase–Multiplex Ligation-Dependent Probe Amplification Assay 
Sylvain Mareschal, Philippe Ruminy, Cristina Bagacean, Vinciane Marchand, Marie Cornic, Jean-Philippe Jais, Martin Figeac, Jean- Michel Picquenot, Thierry Jo Molina, Thierry Fest, Gilles Salles, Corinne Haioun, Karen Leroy, Hervé Tilly, Fabrice Jardin 
The Journal of Molecular Diagnostics 
Volume 17, Issue 3, Pages (May 2015)
DOI: /j.jmoldx
Copyright © 2015 American Society for Investigative Pathology and the Association for Molecular Pathology Terms and Conditions

2. Figure 1
Description of the analyzed cohorts. General structure and overlaps between the different cohorts are indicated, along with their main characteristics (sample count, material type, GEP standard when available). Cohorts from our institution (A) are separated from the external cohort (B) to highlight their independence. ABC, activated C-cell–like; CHB, Centre Henri Becquerel; DASL, cDNA-mediated Annealing, Selection, extension and Ligation method; FFPE, formalin-fixed, paraffin-embedded; GCB, germinal center B-cell–like; GEP, gene expression profiling; IHC, immunohistochemical; Lysa, Lymphoma Study Association.
The Journal of Molecular Diagnostics  , DOI: ( /j.jmoldx )
Copyright © 2015 American Society for Investigative Pathology and the Association for Molecular Pathology Terms and Conditions

3. Figure 2
Representative RT-MLPA profiles. RT-MLPA profiles generated by the dedicated software are presented for two representative samples (GCB and ABC). For each sample, a fragment-analysis profile (intensity of fluorescence as a function of the PCR fragment sizes) is provided in the left panel, with intervals scanned for gene-related peaks highlighted by various colors [blue for ABC-related genes, orange for GCB-related genes, green for the MS4A1 (encodes CD20) internal control, and gray for other diagnostically or prognostically relevant genes]. Size markers, as used for alignment of profiles and fragment size estimation (ROX channel), are displayed with dotted lines, indicating their theoretical size. The right panel illustrates the prediction made by the RT-MLPA predictor, showing the superposition of the score of the sample on the theoretic distributions of scores in the ABC and GCB subgroups. ABC, activated B-cell–like; GCB, germinal center B-cell–like; RT-MLPA, reverse transcriptase multiplex ligation-dependent probe amplification.
The Journal of Molecular Diagnostics  , DOI: ( /j.jmoldx )
Copyright © 2015 American Society for Investigative Pathology and the Association for Molecular Pathology Terms and Conditions

4. Figure 3
RT-MLPA predictor training and validation. A: The scores of the GCB and ABC samples of the training series are presented as vertical bars, beneath the estimated density functions used in the prediction model. B and C: The expression of the eight genes included in the GCB-ABC predictor in the training (B) and validation (C) series are presented as heat maps, along with the expected classes computed with the DASL technology (middle panel) and the predicted probability to belong to each of the groups (top panel). Samples (columns) are ordered by ascending RT-MLPA scores, whereas genes (rows) are ordered by their discriminating power (t statistics displayed on the right). Black vertical bars split samples according to the group prediction (GCB, unclassified, and ABC from left to right). ABC, activated B-cell–like; DASL, cDNA-mediated annealing, selection, extension, and ligation method; GCB, germinal center B-cell–like; RT-MLPA, reverse transcriptase multiplex ligation-dependent probe amplification.
The Journal of Molecular Diagnostics  , DOI: ( /j.jmoldx )
Copyright © 2015 American Society for Investigative Pathology and the Association for Molecular Pathology Terms and Conditions

5. Figure 4
RT-MLPA predictor independent validation on Affymetrix samples. The expression of the eight genes included in the GCB-ABC predictor in an independent series of 64 frozen samples is presented as a heat map, along with the expected classes computed with Affymetrix U133+2 arrays and the predicted probability of belonging to each of the groups. Samples (columns) are ordered by ascending RT-MLPA scores, whereas genes (rows) are ordered by their discriminating power (t statistics displayed on the right). Black vertical bars split samples according to the group prediction (GCB, unclassified, and ABC from left to right). ABC, activated B-cell–like; DASL, cDNA-mediated annealing, selection, extension, and ligation method; GCB, germinal center B-cell–like; RT-MLPA, reverse transcriptase multiplex ligation-dependent probe amplification.
The Journal of Molecular Diagnostics  , DOI: ( /j.jmoldx )
Copyright © 2015 American Society for Investigative Pathology and the Association for Molecular Pathology Terms and Conditions

6. Figure 5
RT-MLPA predictor performances in FFPE samples. A: The expression of the eight genes included in the GCB-ABC predictor in a series of 28 FFPE samples is presented as a heat map, along with the expected classes computed with the DASL technology on matching frozen samples and the predicted probability of belonging to each of the groups. The samples (columns) are ordered by ascending RT-MLPA scores, whereas the genes (rows) are ordered by their discriminating power (t statistics displayed on the right). The black vertical bars split samples according to the group prediction (GCB, unclassified, and ABC from left to right). B: RT-MLPA scores measured in FFPE and frozen samples from the same 28 patients are presented as a scatter plot. Score thresholds to classify samples as GCB or ABC with a confidence of ≥95% are materialized by grey lines. Green circles are used for samples classified in the same subtype using both samples. Black circles are used for samples unclassified in one or the other sample. ABC, activated B-cell–like; DASL, cDNA-mediated annealing, selection, extension, and ligation method; FFPE, formalin-fixed paraffin-embedded; GCB, germinal center B-cell–like; RT-MLPA, reverse transcriptase multiplex ligation-dependent probe amplification.
The Journal of Molecular Diagnostics  , DOI: ( /j.jmoldx )
Copyright © 2015 American Society for Investigative Pathology and the Association for Molecular Pathology Terms and Conditions

7. Figure 6
RT-MLPA predictor performances compared with immunohistochemistry. The expression of the eight genes included in the GCB-ABC predictor in a series of 100 frozen samples is presented as a heat map, along with Hans IHC algorithm results, and the predicted probability of belonging to each of the groups. Samples (columns) are ordered by ascending RT-MLPA scores, whereas genes (rows) are ordered by their discriminating power (t statistics displayed on the right). Black vertical bars split samples according to the group prediction (GCB, unclassified, and ABC from left to right). ABC, activated B-cell–like; GCB, germinal center B-cell–like; IHC, immunohistochemical; RT-MLPA, reverse transcriptase multiplex ligation-dependent probe amplification.
The Journal of Molecular Diagnostics  , DOI: ( /j.jmoldx )
Copyright © 2015 American Society for Investigative Pathology and the Association for Molecular Pathology Terms and Conditions

8. Figure 7
Patient outcomes according to RT-MLPA–based grouping. Progression-free and overall survival of a series of 135 patients treated with a combination of rituximab and chemotherapy are presented according to various grouping factors: GCB-ABC subgroup, as predicted by RT-MLPA (A), LMO2 (B), BCL6 (C), and TNFRSF13B (D) expressions as measured by RT-MLPA according to their respective medians, MYC+ BCL2+ against the rest of the cohort (E), defined by an RT-MLPA expression higher than for MYC and for BCL2. Raw log-rank P values are displayed on the respective legend panels. ABC, activated B-cell–like; GCB, germinal center B-cell–like; RT-MLPA, reverse transcriptase multiplex ligation-dependent probe amplification.
The Journal of Molecular Diagnostics  , DOI: ( /j.jmoldx )
Copyright © 2015 American Society for Investigative Pathology and the Association for Molecular Pathology Terms and Conditions