Landscape of immunoglobulin heavy chain γ gene class switch recombination in patients with adult T-cell leukemia–lymphoma

We are currently conducting the multicenter prospective study “Monitoring of immune responses following mogamulizumab-containing treatment in patients with adult T-cell leukemia–lymphoma (ATL)” (MIMOGA), (Trial registration number: UMIN000008696).^1-4 We previously reported the importance of humoral immune measures, such as the proportion of CD2-CD19+ B cells in peripheral blood mononuclear cells (PBMC), for the outcome of ATL patients.⁵ Subsequently, we demonstrated that lower immunoglobulin G (IgG) B-cell diversity in PBMC was a significant unfavorable prognostic factor for overall survival (OS) in patients.⁶ In that study, we had focused on the diversity-generating mechanism for the IgG variable regions. Therefore, here we focused on the diversity-generating mechanism in the IgG constant region, namely class switch recombination (CSR),^{7- 9} and explored its detailed status in ATL patients. The present investigation was affiliated with the MIMOGA study, and 81 ATL patients were enrolled according to the criteria used in that previous study.^5,6 Unbiased amplification and high-throughput sequencing of the immunoglobulin heavy chain γ (IGHG) genes was conducted using PBMC at enrollment in the MI-MOGA study.^6,10 The sequence reads whose immunoglobulin heavy chain constant (IGHC) region was determined to be assigned to immunoglobulin heavy constant γ P were excluded from the analysis. IGHG unique reads, with identical IGHV (variable), IGHD (diversity) and IGHJ (joining) gene usage and identical deduced amino acid sequences of the CDR3 complementarity determining region 3 (CDR3), were designated “VDJ/CDR3 identical unique reads”. Among IGHG unique reads in PBMC, the percentage of VDJ/CDR3 identical reads which were shared between two or more different subclass genes was designated “the percentage of CSR of IGHG unique reads in PBMC”, abbreviated to “%CSR of IGHG”. In practice, the %CSR of IGHG was calculated as follows: the total number of VDJ/CDR3 identical unique reads which were shared between two subclass genes (IGHG3-IGHG1, IGHG3-IGHG2, IGHG3-IGHG4, IGHG1-IGHG2, IGHG1-IGHG4, or IGHG2-IGHG4), or three subclass genes (IGHG3-IGHG1-IGHG2, IGHG3-IGHG1-IGHG4, IGHG3-IGHG2-IGHG4, or IGHG1-IGHG2-IGHG4), or four subclass genes (IGHG3-IGHG1-IGHG2-IGHG4) was divided by the total number of IGHG unique reads.

We first analyzed VDJ/CDR3 identical unique reads according to the type of subclass genes in PBMC of ATL patients, compared to those of 12 healthy individuals, who had also participated in our previous study.^6,10 The percentage of IGHG unique reads which had a single subclass gene of IGHG1 tended to be higher in ATL patients than in healthy individuals. Among IGHG unique reads, the percentages of VDJ/CDR3 identical reads which were shared between two different functional subclass genes, namely, IGHG3-IGHG1, IGHG3-IGHG2, IGHG3-IGHG4, or IGHG1-IGHG2 were significantly lower in ATL patients. The remaining two pairs consisting of two different subclasses, such as IGHG1-IGHG4 and IGHG2-IGHG4, tended to be lower in ATL patients. Additionally, those shared between three different functional subclass genes, in all four available pairs, i.e., IGHG3-IGHG1-IGHG2, IGHG3-IGHG1-IGHG4, IGHG3-IGHG2-IGHG4, or IGHG1-IGHG2-IGHG4, were significantly lower in ATL patients. Accordingly, the %CSR of IGHG was significantly lower in ATL patients than in healthy controls (Table 1). These data indicate that the CSR of IGHG unique reads occurs significantly less frequently in ATL patients. These differences in the frequency of CSR among IGHG are likely to reflect the degree of impairment of the humoral immune system.

Second, we sought correlations between the %CSR of IGHG, and the Shannon–Weaver diversity index (SWDI) for the IGHG repertoire in PBMC.^6,10 We found a significant positive correlation of the %CSR of IGHG with the SWDI (Spearman rank correlation coefficients [Rs]=0.860; P<0.001) in ATL patients. This was also the case in healthy controls (Rs=0.846; P=0.001), likely because both CSR and somatic hypermutation (SHM) leading to the diversification of antibody variable regions are mediated by activation-induced cytidine deaminase (AID).^12-14

Third, we analyzed the clinical characteristics of ATL patients according to the %CSR of IGHG. Clinically meaningful cut-off values of the %CSR of IGHG had not been determined. Hence, we divided the patients into two groups according to the %CSR. Subsequently, univariate analysis for survival was performed using a Cox proportional hazards regression model at each of the six cut-off points. In the present study, the cut-off point yielding the minimum P value was selected as the most meaningful cut-off value, as previously described.^5,11 As a result, the cut-off value of the %CSR of IGHG was set at 9.363% (Online Supplementary Table S1). In this context, the median age was 67 years (range, 41–86) and 70 years (range, 58– 83) in patients with a lower and higher %CSR, respectively (not significantly different; P=0.119). There were also no significant differences between patients with a lower or higher %CSR regarding previous systemic chemotherapy (yes or no; P=0.579), sex (P=1.000), or Eastern Cooperative Oncology Group Performance Status (ECOG PS) (0, 1 vs. 2, 3, 4; P=0.207). In addition, there were also no significant differences between patients with a lower or higher %CSR for clinical subtype (chronic, smoldering vs. acute, lymphoma; P=1.000), or in serum soluble interleukin-2 receptor (sIL-2R) (mean and median, 17,971, and 8,600, vs. 13,879 and 4,590; P= 0.127). Accordingly, this makes it hard to estimate the status of IGHG CSR based on clinical characteristics.

Table 1.VDJ/CDR3 identical unique reads according to the types of shared subclass genes in adult T-cell leukemia–lymphoma patients and healthy individuals.

Fourth, we analyzed the immunological characteristics of ATL patients according to the %CSR of IGHG. The percentages of CD2-CD19+ B cells were significantly higher in the patients with a higher %CSR of IGHG compared to those with a lower %CSR. This suggests that as more B cells, including IgG B cells, are present in PBMC, more CSR of IGHG can occur. On the other hand, there was no significant difference in the percentage of CD3+CD8+ or CD3+CD4+ T cells in the patients with a higher or lower %CSR. With respect to CD16+CD56+ natural killer (NK) cells, or CD11c+ monocytes, the former were significantly higher, and the latter tended to be higher in the patients with a higher %CSR. These NK cells or monocytes might assist CSR for IgG, but no responsible mechanisms have been clearly identified. Serum IgG and IgA titers were significantly higher in patients with a higher %CSR than in those with a lower %CSR, but the difference in serum IgM was not significant (Table 2). These results likely reflect the gene order in the IGHC locus on chromosome 14q32, such as IGHM (immunoglobulin heavy constant m)-IGHD (immunoglobulin heavy constant δ)-IGHG3-IGHG1-IGHA1 (immunoglobulin heavy constant α1)-IGHG2-IGHG4-IGHE (immunoglobulin heavy constant e)-IGHA2 (Online Supplementary Figure S1).⁸ That is to say, the IGHG gene region overlaps IGHA on chromosome 14q32. Therefore, the frequent CSR of IGHG would be likely associated with frequent CSR of IGHA, thus leading to higher serum IgG and IgA, but not IgM, titers. The significantly higher SWDI for the IGHG repertoire in patients with a higher %CSR of IGHG would be expected, due to AID,^12-14 and SHM and CSR might both reflect the degree of impairment of the humoral immune system.

Table 2.Immunological characteristics of T-cell leukemia–lymphoma patients according to the percentage of class switch recombination of IGHG unique reads of IGHG in peripheral blood mononuclear cells.

Finally, we analyzed the prognostic impact of %CSR of IGHG. The OS of patients with a higher %CSR of IGHG was significantly longer than of those with a lower %CSR (median OS, 30.9 vs. 13.2 months; P=0.043) (Online Supplementary Figure S2A). Multivariate analysis of OS in the 81 ATL patients was performed using the following six variables: sex, age, clinical subtype, ECOG PS, sIL-2R, and %CSR of IGHG. Of these, two variables significantly affected OS, namely a higher serum sIL-2R, and a higher %CSR of IGHG (HR, 0.439; 95% confidence interval [CI]: 0.229–0.839) (Table 3). CSR is a process resulting in improved ability of antibodies to eliminate pathogens.^8,9,14 Thus, a higher frequency of efficient CSR possibly implies better humoral immune status, leading to a more favorable prognosis. Considering the previously identified prognostic factor, the frequency of CD2-CD19+ B cells within lymphocytes,⁵ the OS of patients with both a lower %CSR and a lower CD2-CD19+ B cells was significantly worse than of the other patients (median OS 7.2 vs. 18.8 months; P=0.004) (Online Supplementary Figure S2B). Based on the present observations of host immune status of the patients, together with an assessment of somatic alterations in the tumor cells,¹⁵ the establishment of precision medicine for patients with ATL is imminent.

Table 3.Multivariate analysis including the percentage of class switch recombination of IGHG unique reads in peripheral blood mononuclear cells for overall survival of patients with T-cell leukemia–lymphoma.

The present investigation offers significant observations regarding associations of IGHG CSR with clinical outcomes in ATL patients. However, a limitation of the study should be recognized, namely, the possibility that the %CSR of IGHG was affected by the absolute B-cell count in the patients’ blood used for the IGHG sequencing, which cannot be completely excluded. Nonetheless, mitigating against this in the present patient cohort, there was no significant correlation between these two factors (Rs=0.214; P=0.056).

In conclusion, the present study demonstrated that IGHG CSR occurs less frequently in ATL patients than in healthy individuals. Additionally, the lower frequency of CSR of IGHG was a significant independent unfavorable prognostic factor in patients with ATL receiving mogamulizumab-containing treatment. These observations provide novel insights into the mechanism of impaired humoral immunity in ATL patients, the degree of dysfunction of which may be reflected in the status of IGHG CSR, which is associated with the clinical outcome. Further investigation of strategies to enhance the quality of humoral immunity is warranted.

Footnotes

• Received May 21, 2022
• Accepted November 15, 2022

Correspondence

T. ISHIDA - itakashi@med.nagoya-u.ac.jp

Disclosures

KN has received consultancy fees, research funding and honoraria from Kyowa Kirin, research funding from Chugai Pharmaceutical, and honoraria from Celgene, Eisai, Meiji Seika Pharma, Janssen Pharmaceutical and Bristol Myers Squibb. SK has received consultancy fees, research funding and honoraria from Chugai Pharmaceutical, research funding and honoraria from Kyowa Kirin, Daiichi Sankyo, Takeda Pharmaceutical, Janssen Pharmaceutical and honoraria from Otsuka Pharmaceutical and Eisai. NN has received consultancy fees from JIMRO and honoraria from Novartis, Takeda pharmaceutical, Chugai Pharmaceutical, Celgene, Otsuka Pharmaceutical, Nippon Shinyaku, Kyowa Kirin and Asahi Kasei Pharma. MY has received honoraria from Novartis International, Takeda Pharmaceutical and Sanofi. YI has received honoraria from Kyowa Kirin, Celgene, Eisai, Bristol Myers Squibb and Sanofi, Meiji Seika Pharma Co., Ltd., SymBio Pharmaceuticals Limited, Sumitomo Dainippon Pharma, and Nippon Shinyaku Co., Ltd. MH has received research funding from Chugai Pharmaceutical and honoraria from JCI Pharma. KY has received honoraria from Janssen, and Taiho Pharmaceutical. HT has received honoraria from Bristol Myers Squibb, Chugai Pharmaceutical, Eisai, Ono Pharmaceutical, SymBio Pharmaceuticals Limited and patents and royalties from Mesoblast. YS has received research funding and honoraria from Kyowa Kirin and honoraria from Celgene and Bristol Myers Squibb. KI has received honoraria from Abbvie, Astellas Pharma, Bristol Myers Squibb, Celgene, Chugai Pharmaceutical, CSL Behring, Daiichi Sankyo, Eizai, Janssen, Kyowa Kirin, Meiji Seika, Ono Pharmaceutical, Otsuka, Pfizer, Sanofi, Takeda, Yakult, and consultancy from Daiichi Sankyo, Meiji Seika, and Yakult, and research funding from Kyowa Kirin, and Ono Pharmaceutical. SI has received honoraria from Janssen, Sanofi, Bristol-Myers Squibb, Pfizer, Takeda, Ono, and Celgene, and research funding from Janssen, Sanofi, Bristol-Myers Squibb, Takeda, Ono, Pfizer, Amgen, Abbvie, Glaxo SmithKlein, and Daichi Sankyo, and donation of commercial property from Chugai, and Sanofi. TM is an employee and a stockholder and an employee of Repertoire Genesis Incorporation. HN has received research funding and honoraria from Ono, Bristol-Myers, MSD, Chugai, and research funding from Taiho, Daiichi-Sankyo, Kyowa Kirin, Zenyaku, Oncolys BioPharma, Debiopharma, Asahi-Kasei, Sysmex, Fujifilm, SRL, Astellas, Sumitomo Dainippon and BD Japan. AU has received honoraria from Bristol-Myers, and Meiji Seika Pharma, and has received consulting fees from JIMRO and Otsuka Medical Devices. RU has received research funding from Kyowa Kirin, Chugai Pharmaceutical and Ono Pharmaceutical. All other authors have no conflicts of interest to disclose.

Contributions

HH, RU and TI developed the concept and design of the study; KN, SK, NN, IC, MY, YI, MH, HS, JM, EO, TJ, MO, AI, KY, HT, TK, TK, YS, KI, SI, AU and TI aquired and analyzed data; HH, TM, HN, RU and TI interpreted data. All authors wrote and approved the final version of the manuscript.

Data-sharing statement

Original data can be made available in response to a reasonable, written request to the corresponding author.

Funding

Acknowledgments

We thank all nurses and clinical research coordinators who were involved in this study, for their patient care and schedule management. We also thank the Japan Institute of Statistical Technology (Saitama, Japan) for their critical review of the statistical analyses, and for providing a certificate attesting the validity of the statistical methods used for the data analyses in the present manuscript. We are grateful to Mr. Hiroshi Iwata (SRL Medisearch Inc., Tokyo, Japan) for his support in scheduling samples from patients, and for sample preservation. We are also grateful to Mr. Satoshi Shinohara (Repertoire Genesis Inc.) for his fruitful discussions with us.