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. 2023 Dec 26;7(24):7459-7470.
doi: 10.1182/bloodadvances.2023010402.

Distribution and clinical impact of molecular subtypes with dark zone signature of DLBCL in a Japanese real-world study

Tomohiro Urata  1   2   3 , Yusuke Naoi  1   2   3 , Aixiang Jiang  4 , Merrill Boyle  4 , Kazutaka Sunami  5 , Toshi Imai  6 , Yuichiro Nawa  7 , Yasushi Hiramatsu  8 , Kazuhiko Yamamoto  9 , Soichiro Fujii  10 , Isao Yoshida  11 , Tomofumi Yano  12 , Ryota Chijimatsu  3 , Hiroyuki Murakami  1   2   3 , Kazuhiro Ikeuchi  1   2   3 , Hiroki Kobayashi  1   2   3 , Katsuma Tani  1   2   3 , Hideki Ujiie  3 , Hirofumi Inoue  13 , Shuta Tomida  3 , Akira Yamamoto  2 , Takumi Kondo  2 , Hideaki Fujiwara  2 , Noboru Asada  2 , Hisakazu Nishimori  2 , Keiko Fujii  2 , Nobuharu Fujii  2 , Ken-Ichi Matsuoka  2 , Keisuke Sawada  14 , Shuji Momose  14 , Jun-Ichi Tamaru  14 , Asami Nishikori  15 , Yasuharu Sato  15 , Tadashi Yoshino  16 , Yoshinobu Maeda  1   2 , David W Scott  4 , Daisuke Ennishi  2   3
Affiliations

Distribution and clinical impact of molecular subtypes with dark zone signature of DLBCL in a Japanese real-world study

Tomohiro Urata et al. Blood Adv. .

Abstract

The distribution and clinical impact of cell-of-origin (COO) subtypes of diffuse large B-cell lymphoma (DLBCL) outside Western countries remain unknown. Recent literature also suggests that there is an additional COO subtype associated with the germinal center dark zone (DZ) that warrants wider validation to generalize clinical relevance. Here, we assembled a cohort of Japanese patients with untreated DLBCL and determined the refined COO subtypes, which include the DZ signature (DZsig), using the NanoString DLBCL90 assay. To compare the distribution and clinical characteristics of the molecular subtypes, we used a data set from the cohort of British Columbia Cancer (BCC) (n = 804). Through the 1050 patient samples on which DLBCL90 assay was successfully performed in our cohort, 35%, 45%, and 6% of patients were identified to have germinal center B-cell-like (GCB) DLBCL, activated B-cell-like (ABC) DLBCL, and DZsig-positive (DZsigpos) DLBCL, respectively, with the highest prevalence of ABC-DLBCL, differing significantly from the BCC result (P < .001). GCB-DLBCL, ABC-DLBCL, and DZsigpos-DLBCL were associated with 2-year overall survival rates of 88%, 75%, and 66%, respectively (P < .0001), with patients with DZsigpos-DLBCL having the poorest prognosis. In contrast, GCB-DLBCL without DZsig showed excellent outcomes after rituximab-containing immunochemotherapy. DZsigpos-DLBCL was associated with the significant enrichment of tumors with CD10 expression, concurrent MYC/BCL2 expression, and depletion of microenvironmental components (all, P < .05). These results provide evidence of the distinct distribution of clinically relevant molecular subtypes in Japanese DLBCL and that refined COO, as measured by the DLBCL90 assay, is a robust prognostic biomarker that is consistent across geographical areas.

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Conflict of interest statement

Conflict-of-interest disclosure: K. Sunami declares research funding and honoraria from Celgene, Sanofi, Bristol Myers Squibb (BMS), Ono, and Janssen, and research funding from Takeda, AbbVie, GlaxoSmithKline, Chugai, Otsuka, Merck Sharp and Dohme, Novartis, Astellas Amgen, Pfizer, Parexel, Kyowa Kirin, Symbio, and Agios. I.Y. declares research funding and honoraria from Kyowa Kirin and Chugai, and honoraria from Eisai, Janssen, Nippon-Shinyaku, Otsuka, Symbio, Takeda, Sumitomo Pharma, and Meiji. N.A. received honoraria from AbbVie. N.F. received honoraria from Novartis, Daiichi Sankyo, Chugai, Astellas, Janssen, and BMS. J.-i.T. declares research funding, honoraria, and speakers’ bureau fees from Takeda; honoraria and speakers, bureau fees from Chugai and BMS; and research funding from Nichirei and Ridgelinez. Y.M. declares research funding and scholarship donations from Chugai; research funding from Nippon Shinyaku; and scholarship donations from Eisai, Otsuka, Kyowa Kirin, and Takeda. D.W.S. declares consultancy for AbbVie and Incyte; consultancy for and honoraria from AstraZeneca; consultancy for and research funding from Janssen; research funding from Roche; and patent with NanoString. D.E. declares research funding from Nippon Shinyaku; honoraria from Eisai and Kyowa Kirin; and research funding and honoraria from Chugai. The remaining authors declare no competing financial interests.

Figures

None
Graphical abstract
Figure 1.
Figure 1.
Distribution of refined COO in Japanese patients with DLBCL. (A) Gene expression profiling–based molecular classification algorithm using the DLBCL90 assay. (B) The number of patients with COO classification (inner circle) and with DZsig classification separated into a new class (outer circle). For the latter, the overall distribution between classes is shown in the bar graph. (C) Heat map shows the Lymph2Cx component of the DLBCL90 assay with the 15 informative genes shown as rows, and all 1050 DLBCLs shown as columns. Arrayed below the heat map are clinical characteristics of the tumors. (D) Comparison of the distribution of molecular subtypes according to age group. Multinomial logistic regression P value (GCB vs ABC) is shown above the bar plot. (E) The number of patients in the BCC cohort, with COO classification (inner circle) and DZsig classification (outer circle) separated into new classes. (F) Bar plot showing the distribution of refined COO in the 2 cohorts compared using Fisher exact test. Ind, indeterminate; mRNA, messenger RNA; Neg, negative; OHSG, Okayama Hematology Study Group; Pos, positive.
Figure 2.
Figure 2.
Distribution of molecular subtypes according to biopsy sites. Pie charts represent the frequency of molecular subtypes in each biopsy site.
Figure 3.
Figure 3.
Prognostic significance of molecular classification of DLBCL. (A,B) Kaplan-Meier curves represent PFS and OS, per the molecular subtypes. (C,D) Kaplan-Meier curves showing OS according to the molecular subtypes combined with 2 IPI risk groups: low/low-intermediate–risk IPI group (low) and high/high-intermediate–risk IPI group (high). (E,F) Forest plots show the results of multivariable analyses (PFS and OS). IPI scores were classified into 2 groups as described earlier. DPE, dual protein expressor; ns, not significant; PR, primary refractory. ∗P < .05; ∗∗P < .01; ∗∗∗P < .001; ∗∗∗∗P < .0001.
Figure 4.
Figure 4.
Phenotypic characterization of the DZsig. (A) Heat map represents the 30 informative DZsig genes shown as rows, and the 432 patients with GCB or DZsigpos-DLBCLs shown as columns. Arrayed below the heat map are immunohistochemical characteristics of the tumors. (B) Bar plots show the proportion of MYC/BCL2 DPEs, per molecular subtypes. (C) Box plots showing H-score (left) of c-MYC and BCL2, and messenger RNA expression (right) of MYC and BCL2 in DZsigpos tumors vs GCB tumors, compared using Wilcoxon rank-sum test. (D) Comparison of mean z scores of IHC-positive rate for each antibody per molecular subtypes. mRNA, messenger RNA.
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