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. 2019 Nov 12;14(11):e0225096. doi: 10.1371/journal.pone.0225096

Diagnostic accuracy of SOX11 immunohistochemistry in mantle cell lymphoma: A meta-analysis

Woojoo Lee 1,#, Eun Shin 2,#, Bo-Hyung Kim 3,4, Hyunchul Kim 2,*
Editor: Riccardo Dolcetti5
PMCID: PMC6850764  PMID: 31714947

Abstract

SOX11 is a transcription factor that is normally expressed in the fetal brain and has also been detected in some malignant tumors, including mantle cell lymphoma (MCL). MCL is a mature B-cell lymphoma that characteristically expresses cyclin D1, which has been used as a diagnostic tumor marker. SOX11 has also recently emerged as a tumor marker for MCL, particularly in cyclin D1-negative MCLs and to distinguish between MCLs and other cyclin D1-positive lymphomas. In this study, we evaluated the diagnostic accuracy of SOX11 immunohistochemistry for the diagnosis of MCL using a meta-analysis. A comprehensive literature search was performed using the PubMED, EMBASE, and Cochrane library through May 9, 2018. In total, 14 studies were included in our meta-analysis. The sensitivity, specificity, and area under the curve calculated from the summary receiver operator characteristic were 0.9, 0.95, and 0.934, respectively. Effect sizes of log positive likelihood ratios, log negative likelihood ratios, and log diagnostic odds ratios were 2.67, -2.12, and 5.27, respectively. Statistically significant substantial heterogeneity was observed for specificity (I2 = 95%), but not for sensitivity. Subgroup analysis and meta-regression were performed to explain the heterogeneity in specificity and showed that the proportions of Burkitt’s lymphoma, lymphoblastic lymphoma, and hairy cell leukemia were significant covariates among studies using rabbit polyclonal antibodies. Overall, this meta-analysis showed that SOX11 was a useful diagnostic marker for MCL, with the clone MRQ-58 mouse monoclonal antibody showing particularly robust performance.

Introduction

SOX11 is a transcription factor that is normally expressed in the fetal brain and is thought to play a role in nervous system development.[1] SOX11 is also expressed in several neoplastic conditions, including ovarian carcinomas, pancreatic solid pseudo-papillary tumor, brain tumors, and lymphomas.[2–5] Among lymphomas, mantle cell lymphoma (MCL) shows higher expression of SOX11 than other types of lymphoproliferative disorders (LPDs).[6]

MCL is a mature B-cell lymphoma characterized by expression of CD5 and cyclin D1.[7] Cyclin D1 expression is a result of t(11;14)(q13:q32) translocation between the IGH gene and the CCND1 gene.[8, 9] However, the diagnosis of MCLs can be complicated in some cases. For example, cyclin D1-negative MCLs[10] can overexpress cyclin D2 or cyclin D3,[11] and aggressive MCLs must be distinguished from cyclin D1-positive diffuse large B cells.[12] In such cases, SOX11 has emerged as a potential novel diagnostic marker of MCL.[6, 13]

As a diagnostic marker of MCL, the overall diagnostic accuracy of SOX11 in MCL has not yet been evaluated. Additionally, a comprehensive analysis of its reliability issues, including its low specificity[5] and high false-positive rates in Burkitt’s lymphoma (BL), lymphoblastic lymphoma (LBL), and hairy cell leukemia (HCL),[5, 14, 15] has not been performed.

Accordingly, in this meta-analysis, we evaluated the diagnostic accuracy of SOX11 immunohistochemistry for MCL. Additionally, we assessed the cause of the inconsistent specificity by comparing the specificities of different antibody clonalities and different monoclonal antibodies using subgroup analysis. Finally, meta-regression was carried out to determine the proportions of BL, LBL, and HCL, which could affect the specificity of SOX11 across different antibodies.

Materials and methods

Published studies and selection criteria

We searched PubMed, EMBASE, and Cochrane library through May 9, 2018 with the following key words: “SOX11” and (“lymphoma” or “lymphomas”). Reference lists of review articles were also searched. Duplicate data and articles were excluded considering the authors and their affiliations. Original articles were included if SOX11 immunohistochemistry was performed in human MCL and other LPD cases. When multiple articles from an author or institution were found, the most informative article was selected for the current study. Non-English articles, article or conference abstracts without sufficient information for meta-analysis, review articles, case reports, comments, errata, articles on cell lines or animals, articles with SOX11 immunohistochemistry on MCL only without other LPD, and those concerning SOX11 studies with methods other than IHC were excluded. The selection process is shown in Fig 1.

Fig 1. Flow diagram of study selection.

Fig 1

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Data extraction

The following data from all eligible studies were extracted[5, 6, 12–23]: the first author’s name, year of publication, species and clonality of the anti-SOX11 antibody, clone or catalog number of the anti-SOX11 antibody, number of SOX11-positive MCLs (true positive [TP]), number of total MCLs (number of cases), number of SOX11-positive other LPDs (false positives), number of total other LPDs (number of controls), sensitivity, specificity, and numbers of SOX11-positive and total BL, LBL, and HCL (BL+LBL+HCL positive/total).

The Quality Assessment of Diagnostic Accuracy Studies (QUADAS) tool was applied for quality assessment of each study.[24] QUADAS consists of 14 questions, which are scored yes (score = 1), no (score = 0), or unclear (score = 0).

Statistical analyses

All data were analyzed using R version 3.4.3, with the “meta” and “mada” packages.[25–27] We calculated the sensitivity and specificity, and the results were visualized on Forest plots with 95% confidence intervals (CIs). Based on random effect models, statistical heterogeneity was evaluated using Higgins’ I2 statistics. In our meta-analysis, studies with I2 values of greater than 50% were considered substantially heterogeneous. The sensitivity and specificity of each study were used to plot the summary receiver operating characteristic (SROC) curve and calculate the area under the SROC curve (AUC). Publication bias was examined by the test for funnel plot asymmetry based on a linear regression model.[28] Subgroup analysis was performed for specificity by setting the species and clonality of the antibodies and clone of the monoclonal antibodies as moderators. Meta-regression analyses were performed for specificity with proportions of BL, LBL, and HCL among other LPDs (control) as covariates in all studies for mouse monoclonal antibodies and rabbit polyclonal antibodies. Residual heterogeneity, which could not be explained by the covariate used in the meta-regression, was also considered present when I2 values were greater than 50%. Results with P values of less than 0.05 were considered as statistically significant.

Results

Characteristics of the studies

Three hundred eighty-three reports were identified in the database search. In total, 14 studies fulfilled the inclusion criteria[5, 6, 12–23]; all were case-control studies. Two studies used more than one antibody [19, 21]. Rabbit polyclonal antibodies were used for seven study populations[5, 6, 14–17, 22]; mouse monoclonal antibodies were used for eight study populations [12, 18–21, 23]. A goat polyclonal antibody was used for one study population.[21] One study did not specify the species of antibody used.[13] Among the studies with mouse monoclonal antibodies, clone MRQ-58 was used in five study populations.[12, 18, 19, 21, 23] BL, LBL, and HCL were included in 12 study populations.[5, 6, 14, 15, 17, 19–21, 23] The proportions of LB, LBL, and HCL among other LPD cases ranged from 0.06 to 37 (Table 1). For all studies, meta-analysis was performed using random effect models. Quality assessment based on QUADAS guidelines was conducted for the included studies (S1 Table). The QUADAS scores of the studies ranged from 6 to 11 (Table 1).

Table 1. Characteristics of studies reporting SOX11 immunohistochemistry in mantle cell lymphoma and other lymphoproliferative diseases.

Study Ab species
and clonality		 Clone
(Cat. Number)		 Case/Controls TP FP FN TN BL+LBL+HCL
positive/total		 Proportion of
BL+LBL+HCL total/controls		 QUADAS
2008 Wang rabbit poly (HPA000536)* 53/12 48 0 5 12 None 0 8
2009 Dictor rabbit poly self-made 23/149 18 31 5 118 31/45 0.3 11
2009 Mozos rabbit poly (HPA000536)* 66/209 62 11 4 198 8/14 0.07 9
2010 Chen rabbit poly (HPA000536)* 57/154 54 5 3 149 5/10 0.06 8
2012 Cao rabbit poly (sc-20096) 4/11 3 0 1 11 None 0 7
2012 Hsiao N/A N/A 19/98 17 0 2 98 None 0 7
2012 Nordstrom mouse mono self-made 16/46 15 2 1 44 2/17 0.37 6
2012 Zeng rabbit poly N/A 35/110 35 5 0 105 5/10 0.09 9
2013 Zhang rabbit poly N/A 58/291 54 81 4 210 16/63 0.22 9
2014 Nakashima MRQ58 mouse mono MRQ-58 80/134 77 5 3 129 3/14 0.1 9
2014 Nakashima CL0142 mouse mono CL0142 41/95 41 26 0 69 7/10 0.11 9
2014 Soldini MRQ58 mouse mono MRQ-58 32/173 29 0 3 173 0/40 0.23 10
2014 Soldini CL0143 mouse mono CL0143 36/173 29 31 7 142 28/40 0.23 10
2014 Soldini sc-17347 Goat poly (sc-17347) 32/145 27 10 5 135 7/39 0.27 10
2014 Zhang mouse mono MRQ-58 13/46 13 0 0 46 0/9 0.2 7
2016 Hsi mouse mono MRQ-58* 8/63 7 0 1 63 None 0 8
2017 Chuang mouse mono MRQ-58 10/490 9 1 1 489 None 0 8
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Ab: antibody; Rabbit Poly: rabbit polyclonal; Mouse Mono: mouse monoclonal; Goat poly: goat polyclonal; N/A: not available; Cat. number: catalog number; TP: true positive; FP: false positive; FN: false negative; TN: true negative; BL: Burkitt's lymphoma, LBL: Lymphoblastic lymphoma, HCL: Hairy cell leukemia

*: the data was not specified on the study and retrieved from vender's homepage

Diagnostic accuracy of SOX11 for MCL

The Forest plots of sensitivity, specificity, log positive likely hood ratio (PLR), log negative likelihood ratio (NLR), and log diagnostic odds ratio (DOR) are shown in Fig 2. The sensitivity of SOX11 for the diagnosis of MCL ranged from 78% to 100%, and the specificity ranged from 72% to 100%. The I2 values of sensitivity and specificity were 49% (p = 0.01) and 95% (p < 0.01), respectively, indicating that substantial heterogeneity existed in specificity among the eligible studies. The sensitivity and specificity of the studies were plotted in a SROC curve (Fig 3). The sensitivity and specificity (1-False positive rate) calculated from the hierarchical SROC were 0.9 (95% CI, 0.86–0.92) and 0.95 (95% CI, 0.9–0.97). The AUC of SROC was 0.934, indicating that SOX11 may be able to differentiate MCLs from other LPDs with relatively high accuracy. The Spearman correlation coefficient between the logit of sensitivity and 1-speicificty was 0.099 (p = 0.7048), suggesting that there was no significant threshold effect. The effect sizes of log PLR, log NLR, and log DOR were 2.67 (95% CI, 2.18–3.17), -2.12 (95% CI, -2.45–-1.78), and 5.27 (95% CI, 4.40–6.14), respectively. A good diagnostic test should have large log PLR, small log NLR, and large DOR. The overall effect sizes of log PLR and log NLR, which are significantly different from 0 (p<0.05), imply that SOX11 immunohistochemistry has diagnostic value for MCL. Following McGee,[29] the overall effect size of DOR also showed clear evidence of SOX11 immunohistochemistry as a diagnostic test for MCL.

Fig 2. Forest plot for measures of diagnostic accuracy of SOX11 immunohistochemistry as a diagnostic marker for mantle cell lymphoma.

Fig 2

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(A) sensitivity, (B) specificity, (C) log PLR, (D) log NLR, and (E) log DOR.

Fig 3. Summary receiver operating characteristics curve from the hierarchical summary receiver operating characteristic model generated from the eligible studies.

Fig 3

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Smaller circle: summary point of sensitivity and false positive rate; sensitivity 0.90 [0.86, 0.92], false positive rate (1-specificity) 0.05 [0.03, 0.1]. Larger circle: 95% confidence region. Dotted circle: 95% prediction region.

Publication bias

We used Thompson and Sharp’s test for funnel plot asymmetry to check whether there was evidence of publication bias in our collection of studies.[28] The funnel plot and test did not show significant results at the 0.05 level (p = 0.136 for sensitivity and p = 0.420 for specificity; Fig 4A and 4B).

Fig 4. Funnel plot of meta-analysis.

Fig 4

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(A) sensitivity and (B) specificity. FE = fixed effect and RE = random effect.

Subgroup analysis

Because substantial heterogeneity was present in the overall analysis of specificity, subgroup analysis was performed to explore heterogeneity further. Due to the limited number of studies, a univariate approach was employed.

The first categorical variable was the antibody clonality. All studies, except one without specified antibody species and clonality, were grouped according to their clonality, i.e., goat polyclonal, rabbit polyclonal, and mouse monoclonal[5, 6, 12, 14–23]; subgroup analysis was performed in an attempt to explain the source of heterogeneity. High levels of within group and between group heterogeneity were present (Fig 5A). The results indicated that the specific clonality of the antibody could not explain the inconsistency in specificity.

Fig 5. Forest plot of subgroup analysis.

Fig 5

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(A) Subgroup analysis by antibody clonality and (B) clone of monoclonal antibodies.

The second categorical variable was the clone of monoclonal antibodies. Studies with monoclonal antibodies were divided into two groups: those with clone MRQ-58 and others,[12, 18–21, 23] and subgroup analysis was performed to determine whether the source of heterogeneity could be explained by the monoclonal antibody clone. Both groups showed high heterogeneity. The clone MRQ-58, which was expected to show a more homogeneous result, actually showed less heterogeneity (I2 = 62%, p = 0.03) than the other antibodies (I2 = 85%, p < 0.01; Fig 5B). However, the specificity of the studies in the MRQ-58 group was 1 or near 1, indicating that although the specificity of the MRQ-58 group was statistically heterogeneous, this antibody could be clinically regarded as highly specific.

Meta-regression

Because false-positive cases were frequent among BL, LBL, and HCL in the included studies, meta-regression was performed to further explore the effects of the proportions of BL, LBL, and HCL in controls to heterogeneity among studies. Meta-regression was performed for three different study groups: all studies, studies using mouse monoclonal antibodies, and studies using rabbit polyclonal antibodies with proportions of BL, LBL, and HCL in controls as a covariate. Due to the limited number of studies, a univariate approach was employed (Table 2).

Table 2. Meta-regression results.

Studies included in meta-regression Coefficient Intercept I2 (%)
estimate P value 95% CI estimate P value 95% CI
All studies -0.23 0.68 -1.33 to 0.86 1.32 <0.001 1.09 to 1.55 94.8
Mouse monoclonal antibody studies 0.56 0.6 -1.56 to 2.64 1.2 <0.0001 0.73 to 1.67 95.7
Rabbit polyclonal antibody studies -1.43 0.001 -2.3 to -0.56 1.44 <0.0001 1.29 to 1.6 83.8
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First, meta-regression was performed for all studies with specified cases of BL, LBL, and HCL.[5, 6, 14, 15, 17, 19–21, 23] The results showed that the proportions of BL, LBL, and HCL were not statistically significant covariates among all studies (intercept = 1.32, 95% CI, 1.09–1.55, p < 0.0001; slope = -0.23, 95% CI, -1.33–-0.86, p = 0.68). The meta-regression showed substantial residual heterogeneity (I2 = 94.8%), indicating that the proportions of BL, LBL, and HCL did not influence the specificity of all studies and that substantial residual heterogeneity was present in specificity after considering the effects of BL, LBL, and HCL.

Second, meta-regression was performed on studies using mouse monoclonal antibodies with specified cases of BL, LBL, and HCL.[19–21, 23] The results showed that the proportions of BL, LBL, and HCL were not significant covariates among studies using mouse monoclonal antibodies (intercept = 1.2, 95% CI, 0.73–1.67, p < 0.0001; slope = 0.56, 95% CI, -1.56–2.64, p = 0.6). Moreover, the meta-regression showed substantial residual heterogeneity (I2 = 95.7%), indicating that the proportions of BL, LBL, and HCL did not influence the specificity in studies using mouse monoclonal antibodies and that substantial residual heterogeneity in specificity was present after considering the effects of BL, LBL, and HCL.

Third, meta-regression was carried out for studies using rabbit polyclonal antibodies with specified cases of BL, LBL, and HCL.[5, 6, 14, 15, 17] The results showed that the proportions of BL, LBL, and HCL were significant covariates among studies using rabbit polyclonal antibodies (intercept = 1.44, 95% CI, 1.29–1.6, p < 0.0001; slope = -1.43, 95% CI, -2.3–0.56, p = 0.001). Additionally, meta-regression showed substantial residual heterogeneity (I2 = 83.8%). However, the residual heterogeneity was relatively lower than the previous two meta-regressions. These results indicated that there was an inverse relationship between the proportions of BL, LBL, and HCL and specificity in studies using rabbit polyclonal antibodies but substantial residual heterogeneity was present in specificity after considering the effects of BL, LBL, and HCL.

Discussion

In the current meta-analysis, we evaluated the diagnostic accuracy of SOX11 immunohistochemistry for diagnosis of MCL among LPDs. The results demonstrated that SOX11 was a potential diagnostic marker for MCL with a pooled sensitivity and specificity of 0.9 and 0.95, respectively. Heterogeneity of specificity was further explored with subgroup analysis and meta-regression, and meta-regression revealed a significant inverse relationship between specificity and proportions of BL, LBL, and HCL.

The pooled sensitivity was 0.9, and there was no substantial heterogeneity (I2 = 49%). Potential sources of false-negative results are leukemic non-nodal MCL, small cell variant MCL, and aggressive MCL, which tend to show low SOX11 expression.[7, 17, 30, 31] Meta-regression with proportions of such cases could have explained the heterogeneity observed in the sensitivity; however, the regression could not be performed because the included studies did not specify the number of such cases.

The pooled specificity was 0.95, and there was substantial heterogeneity (I2 = 95%). We suspected that the source of the heterogeneity may be the use of less specific polyclonal antibodies. However, the subgroup analysis result between antibody clonality showed statistically significant within- and between-group heterogeneity. Because the specificity of a MRQ-58 clone was thought to be superior to that of other mouse monoclonal antibodies,[12, 21] we performed subgroup analysis between the MRQ-58 clone and the remaining mouse monoclonal antibodies. Although the specificity of four of five studies in this group was 1, the subgroup analysis showed statistically significant substantial heterogeneity in the MRQ-58 group. This result could be explained by the observation that specificities close to 1 have very small standard errors, implying very short confidence intervals. Therefore, when the number of studies in the meta-analysis was low, the specificity of MRQ-58 was considered consistently high in the clinical setting, despite the statistically significant heterogeneity. With meta-regression, we found a statistically significant inverse relationship between specificity and proportions of BL, LBL, and HCL in studies using rabbit polyclonal antibodies. In other words, the specificity of rabbit polyclonal antibodies decreased as the proportions of BL, LBL, and HCL increased. In addition, rabbit polyclonal antibodies showed higher false-positive rates for diffuse large B cell lymphoma (DLBCL) as compared with mouse monoclonal antibodies, particularly for the MRQ-58 clone.[5, 19, 21]

With sensitivity and specificity from eligible studies, we plotted SROC curves and obtained an AUC of 0.934, indicating that SOX11 had good accuracy in the diagnosis of MCL from other LPDs. SOX11 is a good diagnostic marker for MCL, particularly in the diagnosis of cyclin D1-negative MCL and to distinguish between aggressive MCL and CD5-positive DLBCL.[7] However, because a small subset of MCL is SOX11-negative, the diagnostic applications of SOX11 should be incorporated in an immunohistochemistry panel approach rather than used alone.

This meta-analysis was limited by the relatively small number of studies included. In particular, a meta-regression of sensitivity, using possible factors causing false positives as covariates, could not be performed because the articles did not record such data. Additionally, residual heterogeneity of meta-regression in specificity could not be explored further because of a lack of additional data. Thus, we speculate that the possible source of residual heterogeneity could be different staining protocols, varying specimen conditions, and different cut-off thresholds for immunohistochemistry interpretation.

A previous study showed that differences in cut-off values used for the interpretation of SOX11 immunohistochemistry data between studies was an important source of inconsistency in results.[32] For the definition of negative SOX11 staining, 8 among the 14 studies included in this analysis specified a cut-off for SOX11 immunohistochemistry. 5 of these studies used 10% as the cut-off value, two used 20%, and one used 1%. We also think differences in cut-off values could affect study results, but additional detailed analysis in this direction is beyond the scope of this paper.

In conclusion, the current evidence suggested that SOX11 may be a useful diagnostic immunohistochemical marker for MCL. In particular, clone MRQ-58 mouse monoclonal antibody showed robust performance. Future studies using MRQ-58 are needed to improve our understanding of the diagnostic accuracy of SOX11 immunohistochemistry for MCL.

Supporting information

S1 Table. QUADAS evaluation.

QUADAS questions and answers are listed.

(XLSX)

Click here for additional data file. (11.6KB, xlsx)
S2 Table. PRISMA 2009 checklist.

(DOC)

Click here for additional data file. (63KB, doc)

Data Availability

All relevant data are within the manuscript and its Supporting Information files.

Funding Statement

This work was supported by a Grant from the Next-Generation BioGreen 21 program (Project No. PJ01337701), Rural Development Administration, Republic of Korea to WL. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Decision Letter 0

Riccardo Dolcetti

5 Sep 2019

PONE-D-19-19834

Diagnostic accuracy of SOX11 immunohistochemistry in mantle cell lymphoma: a meta-analysis

PLOS ONE

Dear Dr. Kim,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

In particular, the study need a more careful statistical assessment as pointed out by reviewers. The definition of SOX11 negativity should be clarified as well as the criteria used to identify SOX11-negative cases. Differences among different antigen retrievals I methods in the various studies should be also considered. In addition, the Authors should provide a more convincing description of the novelty and significance of the data obtained in the light of their potential relevance in the diagnosis of MCL.

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Riccardo Dolcetti

Academic Editor

PLOS ONE

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**********

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Reviewer #1: The work reports the results of a meta-analysis focused on the diagnostic accuracy of the immunohistochemical analysis of SOX11 in mantle cell lymphoma.

SOX11 is a tumor marker particularly useful in the recognition of CydinD1 negative mantle cell lymphoma. Since SOX11 is "falsely" positive in cases of Burkitt lymphoma, lymphoblastic lymphoma and Hairy cell leukemia, the authors investigated the value of SOX11 against other lymphoproliferative disorders in which it is expressed.

The meta-analysis study was therefore limited to 14 of the 383 reports collected. From these 14 studies it was found that SOX 11, evaluated with the MRQ-58 mouse monoclonal antibody can be a useful diagnostic marker by immunohistochemistry, also in statistical comparison with the other examined lymphomas that showed false positivity for SOX11.

Reviewer #2: In this article, the authors performed extensive literature search to evaluate the accuracy of SOX11 immunostain in the diagnosis of mantle cell lymphoma using the meta-analysis on the published data. They concluded that SOX11 is a useful marker in diagnosing MCL, and the SOX11 mouse monoclonal antibody clone, MRQ-58, has robust performance in contrast to other antibodies. Overall, the paper is well-written, and the results are reliable. However, the findings are not novel or significant, and are of limited usage in the diagnosis of MCL.

Specific comments:

1). Was there any specific definition(s) of “negative SOX11 staining” in the literature?

2). During immunohistochemical staining, the antigen retrieval methods may significantly affect the quality of results. Therefore, it may be helpful for the authors to analyze the differences among different antigen retrievals of SOX11 immunostain.

3). For the SOX11-negative MCLs, how was the diagnosis established?

Reviewer #3: This manuscript reports the summarized results of using SOX11 in diagnostic test of MCL. I have below questions and comments.

Please add a table to show the results of quality evaluation of QUADAS.

Lines 114-117, threshold effect was mentioned. Were various thresholds used among cited studies? If yes, please report the cut-off value of each study. The Spearman r=0.99, very high, why no threshold effect was concluded? What are your interpretations for logPLR, logNLR and DOR in this meta-analysis results?

Fig 3. Line 124, please add “summary point of” before “sensitivity and false positive rate”. It indicates HSROC, but SROC is mentioned at lines 110-111.

For Figure 4, please provide legends for each line.

**********

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PLoS One. 2019 Nov 12;14(11):e0225096. doi: 10.1371/journal.pone.0225096.r002

Author response to Decision Letter 0

13 Oct 2019

Dear Dr. Dolcetti,

Thank you for giving us the opportunity to submit a revised draft of our manuscript titled “Diagnostic accuracy of SOX11 immunohistochemistry in mantle cell lymphoma: a meta-analysis” to PLOS ONE. We appreciate the time and effort that you and the reviewers have dedicated to providing your valuable feedback on our manuscript. We are grateful to the reviewers for their insightful comments on our paper. We have been able to incorporate changes to reflect many of the suggestions provided by the reviewers. We have highlighted the changes within the manuscript.

Here is a point-by-point response to the reviewers’ comments and concerns.

Academic Editor

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at http://www.journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and http://www.journals.plos.org/plosone/s/file? id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

Response: We have ensured that the revised manuscript conforms with the style requirements of PLOS ONE.

2. Please upload a new copy of Figures 2A, 2B, 5A and 5B as the detail is not clear. Please follow the link for more information: http://blogs.PLOS.org/everyone/2011/05/10/how-to-check-your-manuscript-image-quality-in-editorial-manager/

Response: Figures 2A, 2B, 5A and 5B are newly created to show the detail clearly.

3. Please provide any updates you might have since the original search was performed in May 2018, or please provide the rational for ending your search at that time.

Response: You have raised an important point here. And we also had considered renewal of searched articles, but we chose not to. There are several reasons for that.

First, this meta-analysis required several months to be completed. If search was renewed, the whole process would have to be done all over again and similar amount of time would have to be spent. So the search had to be stopped somewhere and it was May 2018.

Second, there was no additional article with available data searched until recently. Even after we decided to stop searching on May 2018, we searched databases regularly to see if there were new critical articles to be added. But until recently there was no new article with available data published. We searched database recently (September 6th, 2019), and found three new relevant articles below.

1. SOX11- negative Mantle Cell Lymphoma: Clinicopathologic and Prognostic Features of 75 Patients. Xu J, Am J Surg Pathol. 2019 May;43(5):710-716. doi: 10.1097/PAS.0000000000001233.,

2. CD23 expression in mantle cell lymphoma is associated with CD200 expression, leukemic non-nodal form, and a better prognosis. Saksena A, Hum Pathol. 2019 Jul;89:71-80. doi: 10.1016/j.humpath.2019.04.010. Epub 2019 May 2.,

3. Highly sensitive and specific in situ hybridization assay for quantification of SOX11 mRNA in mantle cell lymphoma reveals association of TP53 mutations with negative and low SOX11 expression. Federmann B, Haematologica. 2019 Jul 11. pii: haematol.2019.219543. doi: 10.3324/haematol.2019.219543. [Epub ahead of print])

As you can see, May 2019 is the earliest published date. The rest are published on July 2019. The published dates were too late for the data to be added. And we were unaware of the articles because by the time our manuscript was nearly completed and we could not renew the search.

4. Please include captions for your Supporting Information files at the end of your manuscript, and update any in-text citations to match accordingly. Please see our Supporting Information guidelines for more information: http://journals.plos.org/plosone/s/supporting-information.

Response: A supporting Information file is submitted and caption was newly inserted at the end of manuscript.

Reviewer #1: The work reports the results of a meta-analysis focused on the diagnostic accuracy of the immunohistochemical analysis of SOX11 in mantle cell lymphoma. SOX11 is a tumor marker particularly useful in the recognition of CydinD1 negative mantle cell lymphoma. Since SOX11 is "falsely" positive in cases of Burkitt lymphoma, lymphoblastic lymphoma and Hairy cell leukemia, the authors investigated the value of SOX11 against other lymphoproliferative disorders in which it is expressed. The meta-analysis study was therefore limited to 14 of the 383 reports collected. From these 14 studies it was found that SOX 11, evaluated with the MRQ-58 mouse monoclonal antibody can be a useful diagnostic marker by immunohistochemistry, also in statistical comparison with the other examined lymphomas that showed false positivity for SOX11.

Reviewer #2: In this article, the authors performed extensive literature search to evaluate the accuracy of SOX11 immunostain in the diagnosis of mantle cell lymphoma using the meta-analysis on the published data. They concluded that SOX11 is a useful marker in diagnosing MCL, and the SOX11 mouse monoclonal antibody clone, MRQ-58, has robust performance in contrast to other antibodies. Overall, the paper is well-written, and the results are reliable. However, the findings are not novel or significant, and are of limited usage in the diagnosis of MCL.

Specific comments:

1). Was there any specific definition(s) of “negative SOX11 staining” in the literature?

Response: Thank you for pointing this out. Some papers defined “negative SOX11 staining” with specific cut-off value. But others did not specify the definition. We revised the manuscript to add discussion on the issue. Regarding the interpretation of SOX11 immunohistochemistry, we briefly discussed the definition of “negative SOX11 staining” and cited a previous paper about effects of SOX11 staining interpretation on inconsistency between studies.

2). During immunohistochemical staining, the antigen retrieval methods may significantly affect the quality of results. Therefore, it may be helpful for the authors to analyze the differences among different antigen retrievals of SOX11 immunostain.

Response: We agree with your opinion on significance of antigen retrieval methods and wish we could perform subgroup analysis according to the antigen retrieval methods. But as you can see below, antigen retrieval methods used for each article are highly heterogeneous and such an analysis seems unavailable.

Detailed explanation is as follows. Most of the articles stated that they used heat-induced epitope retrieval. Two articles did not specify their antigen retrieval methods. Four studies used automated antigen retrieval methods (three with PT-LINK from Dako and two with BondMax from Leica). The rest are heat-induced epitope retrieval methods with varied equipment, reagents, and settings. To perform subgroup analysis, the studies needs to be divided into two or more groups. The best possible grouping seems to be automated group VS heat-induced group. But each group is highly heterogeneous; Automated group is composed of three PT-LINK used studies with different settings and two BondMax used studies with different settings. And heat-induced group is composed of all different combinations of equipment, reagents, and settings. Therefore subgroup analysis with simple two groups of automated group VS heat-induced group would be inappropriate. If, instead, studies are divided into subgroups according to individual combinations of equipments, reagents, the analysis would produce more than 10 subgroups with mostly one study per subgroup and the result would be meaningless.

In short, we agree with your opinion and we would much like to perform additional subgroup analysis. But because of the above mentioned limitations, proper analysis does not seem available.

Antigen Retrieval Methods of Articles

2008 Wang Heat-induced (Retriever 2100)

2009 Dictor Heat-induced (Microwave, Tris/EDTA, pH9, 8+7min)

2009 Mozos ER2, BondMax, Leica, 15min

2010 Chen Heat-induced (Decloaking Chamber, Biocare Medical, pH6.0)

2012 Cao Heat-induced (Decloaking Chamber, Biocare Medical, pH6.0)

2012 Hsiao N/A

2012 Nordstrom PT-LINK, Dako, pH9

2012 Zeng Heat-induced (Tris-based buffer, pH9.0)

2013 Zhang N/A

2014 Nakashima MRQ58 Heat-induced (EDTA, pH8.9-9.1, 20min)

2014 Nakashima CL0142 Heat-induced (EDTA, pH8.9-9.1, 20min)

2014 Soldini MRQ58 PT-LINK, low, Dako, 24 degree, 30 min

2014 Soldini CL0143 PT-LINK, high PH, Dako, 24 degree, 60 min

2014 Soldini sc-17347 ER1, high PH, BondMax, Leica, 30 degree, 60 min

2014 Zhang Heat-induced (citrate buffer, pH 6.0, 20min)

2016 Hsi Heat-induced (Ultra Cell Conditioning Solution, 95 degree for 65 min)

2017 Chuang Heat-induced (EDTA, 100 degree, 30 min)

3). For the SOX11-negative MCLs, how was the diagnosis established?

Response: We would like to answer the question in two parts.

First, we would like to answer first part of the question regarding SOX11-negative immunohistochemistry. As stated in answer for question No.1, some authors used specific cut-off value to interpret SOX11 immunohistochemistry. Others did not specify how they interpreted the immunohistochemistry.

The second part of the question seems to be about establishing diagnosis of MCL with SOX11 negative immunohistochemistry. The authors’ diagnoses were in accordance with well-known definition of MCL (such as small to intermediate cell size, and CD5 and Cyclin D1 co-expression).

Reviewer #3: This manuscript reports the summarized results of using SOX11 in diagnostic test of MCL. I have below questions and comments.

Please add a table to show the results of quality evaluation of QUADAS.

Response: The QUADAS questions and answers are provided as a Supplement Material (S1 Table). QUADAS scores are added in the far right column of Table.1.

Lines 114-117, threshold effect was mentioned. Were various thresholds used among cited studies? If yes, please report the cut-off value of each study. The Spearman r=0.99, very high, why no threshold effect was concluded? What are your interpretations for logPLR, logNLR and DOR in this meta-analysis results?

Response: Thank you for pointing out our mistake. The Spearman correlation was not 0.99, but 0.099. We corrected the number. A good diagnostic test should have large log PLR, small log NLR, and large DOR. The overall effect sizes of log PLR and log NLR, which are significantly away from 0, imply that SOX11 immunohistochemistry has diagnostic value for MCL. Following McGee[28], the overall effect size of DOR also shows clear evidence of SOX11 immunohistochemistry as a diagnostic test for MCL. This interpretation is added in Diagnostic accuracy of SOX11 for MCL.

Fig 3. Line 124, please add “summary point of” before “sensitivity and false positive rate”. It indicates HSROC, but SROC is mentioned at lines 110-111.

Response: The words and phrases are added at the positions.

For Figure 4, please provide legends for each line.

Response: We added legends for each line. See Figure 4. The vertical dashed line corresponds to the estimate of the fixed effect model, the diagonal dashed lines represent 95% confidence interval limits under the fixed effect model, and the vertical dotted line corresponds to the estimate of the random effect model.

We look forward to hearing from you in due time regarding our submission and to respond to any further questions and comments you may have.

Sincerely,

Hyunchul Kim

Attachment

Submitted filename: Rebuttal Letter.docx

Click here for additional data file. (24.8KB, docx)

Decision Letter 1

Riccardo Dolcetti

30 Oct 2019

Diagnostic accuracy of SOX11 immunohistochemistry in mantle cell lymphoma: a meta-analysis

PONE-D-19-19834R1

Dear Dr. Kim,

We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements.

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With kind regards,

Riccardo Dolcetti

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Acceptance letter

Riccardo Dolcetti

5 Nov 2019

PONE-D-19-19834R1

Diagnostic accuracy of SOX11 immunohistochemistry in mantle cell lymphoma: a meta-analysis

Dear Dr. Kim:

I am pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

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Associated Data

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    Supplementary Materials

    S1 Table. QUADAS evaluation.

    QUADAS questions and answers are listed.

    (XLSX)

    Click here for additional data file. (11.6KB, xlsx)
    S2 Table. PRISMA 2009 checklist.

    (DOC)

    Click here for additional data file. (63KB, doc)
    Attachment

    Submitted filename: Rebuttal Letter.docx

    Click here for additional data file. (24.8KB, docx)

    Data Availability Statement

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