Original contribution
Identification of MUM1 as a prognostic immunohistochemical marker in follicular lymphoma using computerized
image analysis ☆ , ☆☆
Luc Xerri MD, PhD
a,⁎ , Emmanuel Bachy MD, PhD
b, Bettina Fabiani MD
c, Danielle Canioni MD
d, Catherine Chassagne-Clément MD
e,
Peggy Dartigues-Cuilléres MD
f, Frédéric Charlotte MD
g, Nicole Brousse MD, PhD
d, Marie-Christine Rousselet MD, PhD
h, Charles Foussard MD, PhD
h,
Pauline Brice MD, PhD
i, Pierre Feugier MD, PhD
j, Frank Morschhauser MD, PhD
k, Anne Sonet MD, PhD
l, Daniel Olive MD, PhD
a, Gilles Salles MD, PhD
ba LYSA study
aDepartments of Bio-Pathology, Molecular Oncology, Hematology, and Tumor Immunology, Institut Paoli-Calmettes and Aix-Marseille Université, 13009 Marseille, France
bHospices Civils de Lyon; CHU Lyon-sud, Department of Hematology, 69310 Pierre-Bénite, France
cDepartment of Pathology, Centre Hospitalier Saint Antoine, 75012 Paris, France
dDepartment of Pathology, Centre Hospitalier Necker, 75015 Paris, France
eDepartment of Pathology, Centre Léon Bérard, 69008 Lyon, France
fDepartment of Pathology, Institut Gustave Roussy, 94805 France
gDepartment of Pathology, Centre Hospitalier Pitié-Salpêtriére, 75013 Paris, France
hDepartment of Pathology, Centre Hospitalier, 49100 Angers, France
iDepartment of Hematology, Centre Hospitalier Saint Louis, 75010 Paris, France
jDepartment of Hematology, Centre Hospitalier, 54035 Nancy, France
kDepartment of Hematology and EA 4481 GRIIOT, CHU, 59000 Lille, France
lDepartment of Hematology, Centre Hospitalier de Louvain, 1348 Louvain-la-Neuve, Belgium
Received 14 March 2014; revised 17 June 2014; accepted 25 June 2014
Keywords:
Follicular lymphoma;
Prognosis;
Immunohistochemistry;
MUM1;
Ki-67;
Image analysis
☆ Competing interests: The authors declare no conflict of interest.
☆☆ Funding/Support: This work was supported by the Institut Paoli-Calmettes and LYSA.
⁎ Corresponding author at: Department of Bio-Pathology, Institut Paoli-Calmettes, 232 Bd Sainte-Marguerite, 13009 Marseille, France.
E-mail address:xerril@ipc.unicancer.fr(L. Xerri).
www.elsevier.com/locate/humpath
http://dx.doi.org/10.1016/j.humpath.2014.06.019 0046-8177/© 2014 Elsevier Inc. All rights reserved.
SummaryDetection of MUM1+ cells in follicular lymphoma (FL) tissues was previously found to be associated with poor prognosis in a single report, whereas the usefulness of Ki-67 immunostaining remains debated. Our goal was to establish whether these markers have predictive value for patients with FL. We analyzed MUM1 and Ki-67 expression using immunohistochemistry in biopsy samples from 434 patients from the PRIMA randomized trial. The MUM1 prognostic value was then validated in a cohort of 138 patients from the FL2000 randomized trial, using the optimal cutoff value obtained from the PRIMA cohort. The surface of positive staining was quantified using computerized image analysis. In the PRIMA cohort, both high levels of MUM1 positivity (cutoff value of 0.80%) and high levels of Ki-67 positivity (cutoff value of 10.25%) were significantly associated with a shorter progression-free survival (PFS) (P= .004 andP= .007 for MUM1 and Ki-67, respectively). In a multivariate Cox proportional hazards regression model, only MUM1 retained a statistical significance (hazards ratio 1.56; 95% confidence interval, 1.02-2.37;P= .038) after adjustment for the maintenance arm of treatment and the follicular lymphoma international prognostic index score. In the FL2000 cohort, high levels of MUM1 positivity were significantly associated to a shorter PFS (P = .004) and to a trend toward a shorter overall survival (P= .043). This remained significant using a multivariate Cox regression model after adjustment for the follicular lymphoma international prognostic index and the treatment arm for PFS (P = .016). These results show that MUM1 is a strong and robust predictive immunohistochemical marker in patients with FL.
© 2014 Elsevier Inc. All rights reserved.
1. Introduction
Previous attempts to identify prognostic factors using immunohistochemistry (IHC) in patients with follicular lymphoma (FL) have led to numerous discrepancies and appear not yet convincing (see review by de Jong and Fest[1]) when compared with usual clinicobiological parameters such as the follicular lymphoma international prognostic index (FLIPI) [2]. Possible explanations for these heterogeneous results include the limited number of patients in the different cohorts and the complexity of IHC manual scoring that is poorly reproducible between pathologists [3]. Assisted IHC scoring by computerized image analysis (CIA) has been recently shown to enable accurate and reproducible counting of huge numbers of events across numerous sections[3-8]and thus appears as a promising alternative method.
Most previous prognostic IHC studies using CIA in lymphomas have focused on the microenvironment[9-11]. A few reports have explored markers expressed in lymphoma cells such as Ki-67 and MUM1. High amounts of MUM1+ cells were found to be associated with poor outcome in a single unconfirmed report[12]. The predictive value of the proliferation marker Ki- 67, recognized by the MIB-1 monoclonal antibody, remains debated. The percentage of MIB-1–positive cells has been shown to be significantly higher in grade 3 FL as compared with grades 1 and 2[13,14], and patients with lower MIB-1 cell counts were associated with a significantly improved survival[14]. However, this has never been clearly confirmed, probably due to the heterogeneity of treatments and the lack of randomized trials.
Our group was able to collect a significant number of samples from patients with FL enrolled in the PRIMA[15]and the FL2000 [16] randomized trials. This prompted us to reappraise the prognostic value of MUM1 and Ki-67 in the light of CIA, using biopsy samples from the PRIMA and FL2000
trials, which were considered as a training set and a validation set, respectively.
2. Materials and methods
2.1. Design and characteristics of the PRIMA trial
The randomized, open-label PRIMA study was undertaken in 223 centers in 25 countries[15]. Patients (n = 1217) with previously untreated FL and needing systemic therapy received 1 of 3 nonrandomized immunochemotherapy induction regimens used in routine practice: R-CHOP (rituximab–cyclophosphamide doxorubicin, oncovin, pred- nisolone), R-CVP (rituximab–cyclophosphamide, vindesine, prednisolone), or R-FCM (rituximab–fludarabine, cyclophos- phamide, mitoxantrone). The 1019 patients who achieved a complete or partial response were then randomly assigned to receive 2 years of rituximab maintenance therapy or observa- tion. Treatment was assigned equally by centralized block randomization, stratified by induction regimen, response, region, and center. The primary end point was progression- free survival (PFS). Analysis was by intention to treat. This trial is registered with ClinicalTrials.gov, number NCT00140582. Patient response was assessed after the end of induction chemotherapy and was classified according to the International Workshop criteria[15,17].
2.2. Design and characteristics of the FL2000 trial
The design of the trial as well as the characteristics of the patients and long-term outcome have been already published [16,18]. Briefly, between May 2000 and May 2002, 358 patients entered onto the FL2000 prospective multicenter study. Patients were eligible if they were between ages 18 and
75 years and had untreated FL with high tumor burden.
Treatment consisted of rituximab–cyclophosphamide, vinde- sine, prednisolone (1 course a month for 6 courses; 1 course every 2 months for 6 additional courses) associated with interferonα2a (4.5 MU 3 times a week) for 18 months in the control arm. Treatment consisted of 6 courses (1 per month for 6 months) of rituximab–cyclophosphamide, vindesine, pred- nisolone associated with 18 months of interferon α2a combined with 6 infusions of 375 mg/m2of rituximab in the other arm. Both PRIMA and FL2000 trials as well as their respective ancillary IHC studies have been approved by the executive committee of the Lymphoma Study Association, which corresponds to the former Groupe d’Etude des Lymphomes de l’Adulte (GELA). Informed consent was obtained from all patients.
2.3. Pathologic reviewing
For both trials, formalin-fixed, paraffin-embedded biopsy specimens were obtained at the time of diagnosis, before any treatment. Patients were included onto either trial based on a histologically proven diagnosis of FL grade 1, 2, or 3A[19].
Patients with histologic grade 3B FL were excluded. The pathologic material was centrally reviewed by a panel of expert hematopathologists at the GELA pathology center (Paris, France) to confirm the diagnosis using appropriate staining and phenotyping.
2.4. Immunohistochemistry
Because of samples availability and technical limitation, biopsy samples from 138 FL2000 patients and 434 PRIMA patients were available for tissue microarray (TMA) construction. When compared with PRIMA patients, FL2000 patients exhibited slightly worse prognostic features as to the performance status and bone marrow involvement, whereas they were significantly older (Supplementary Tables 1 and 2). As regards the IHC scores, distribution of both markers showed lower values of staining in the FL2000 cohort. Archival paraffin blocks from the FL2000 trial were about 10 years older than the PRIMA blocks; this may account for a globally weaker staining intensity of the resulting slides (Supplementary Tables 1 and 2).
For both PRIMA and FL2000 cohorts, the characteristics of the corresponding patients did not differ significantly from those of the overall population in terms of baseline characteristics (not shown) except for a higher proportion of PRIMA patients with more than 4 nodal sites and bone marrow involvement (P= .003 for both).
Areas containing malignant follicles representative of the entire lymph node and avoiding fibrotic portions were marked on the paraffin blocks during pathologic reviewing of each case. Cylinders of 1-mm diameter from 3 different areas were then collected and included in TMA blocks. After dewaxing and pressure cooker antigen retrieval at pH 9, immunostaining was done in an automated immunostainer
(Dako, Glostrup, Denmark) using a standard avidin-biotin- peroxidase technique. Dilution was 1:50 for the anti-MUM1 monoclonal antibody (Dako, M7259), whereas the Ki-67 antibody (Dako, IR 62661) was ready to use. Dual-color immunostaining experiments using both CD20/MUM1 and CD138/MUM1 and CD3/MUM1 combinations were performed on 1 TMA PRIMA slide.
2.5. Computer-assisted image analysis
Automated scanning microscope and CIA system (Spot Browser; Excilone, Elancourt, France) were used under visual supervision for validation of staining specificity and exclusion of cores with artifacts (background staining, stretching). The CIA algorithm was also determined under visual supervision to optimize the threshold of automatic signal detection according to different degrees of staining intensity within a given TMA slide. For each TMA core, the areas of positive staining were automatically detected and measured. The resulting ratio of positively stained area to the total spot area was calculated. The total spot area included only cellular areas because the occasional fibrotic foci were manually selected and excluded.
The mean value calculated on at least 2 TMA cores from each patient was considered for subsequent statistical analysis. To evaluate the correspondence between manual and automatic MUM1 counting methods, manual analysis of a subset of 30 PRIMA samples (selected based on automatic analysis) was blindly performed by 3 different pathologists (L.X., B.F., D.C.). Intrafollicular MUM1-positive cells were counted according to a semiquantitative scoring as negative (0) if less than 10% of the cells were positive; +, if 10% to 30% of the cells were positive; and ++, if greater than 30% of the cells were positive.
2.6. Statistical analysis
Overall survival (OS) was calculated from the date of inclusion until the date of death from any cause or the date of last contact. PFS was measured from the date of inclusion to the date of death from any cause, relapse, progression, or the date of last contact. Survival curves were constructed with the Kaplan-Meier method and compared with the log-rank test. Both because cut-points are needed in routine practice to provide guidelines for medical decision-making and because it enables graphic representation, we sought to dichotomize MUM1 and Ki-67 positive staining areas.
Because it is statistically invalid to test multiple divisions and accept the bestPvalue, 2 study cohorts were considered. The PRIMA cohort was used as a training set to determine the optimal cutoff for both MUM1 and Ki-67 based on the highest of theχ2log-rank values. Optimal cutoff was then validated on the FL2000 cohort.
Optimal cutoff value was obtained with the use of the X-Tile statistical software package (Yale University, New Haven, CT) [20]. All tests were 2-sided, and P b .05 was considered as statistically significant. Statistical analyses were conducted with SAS software version 9.2 (SAS Institute, Cary, NC).
3. Results
3.1. Distribution of markers in the PRIMA cohort
The pattern of positivity was visually checked on each TMA slide. Positive cells were mainly intrafollicular for both markers.
Most MUM1+ cells within the follicles had irregular nuclei and were either scattered or had a tendency to cluster at the follicle periphery. The rare MUM1 perifollicular positive cells, including plasma cells, were also taken into account for image
analysis to standardize the procedure and make it available for
routine analysis (Fig. 1and Supplementary Fig. S3). Dual-color F1
immunostaining experiments showed that most intrafollicular MUM1+ cells appeared to coexpress CD20 and were CD138 negative. MUM1+ T cells detected by CD3/MUM1 dual staining were exceedingly rare when compared with the entire population of MUM1-expressing cells. For technical reasons, not all data were available for each case because the subsequent analysis was performed only if there were 2 or 3 high-quality cores representing a total of 2 to 3 mm2. From the
C
B D
A
Fig. 1 Histologic pattern and image analysis of MUM1 immunostaining. Left panel (original magnification ×50) shows a FL case from the PRIMA cohort with high numbers of MUM1-positive cells after immunostaining (A) and after CIA (B). The final result obtained from automatized analysis was 10.5%, corresponding to the ratio of positively stained area to the total spot area. Right panel (×50) shows a FL case from the PRIMA cohort with low numbers of MUM1-positive cells after immunostaining (C) and after CIA (D). The final result obtained from automatized analysis was 0.29%, corresponding to the ratio of positively stained area to the total spot area.
original cohort, MUM1 and Ki-67 data were then finally available for 423 and 323 patients, respectively. Among these patients, the median percentage area of MUM1 and Ki-67 was
1% and 6%, respectively. Distributions of markers for the PRIMA cohort of patients are depicted in Supplementary Fig.
S1A and B.
Fig. 2 Correlation between MUM1 expression or Ki-67 expression and PFS in the PRIMA study. A, A high level of MUM1 positivity (ie, above 0.80%) was significantly associated with a shorter PFS (P= .004). B, A high level of Ki-67 positivity (ie, above an optimal cutoff value of 10.25%) was significantly associated with a shorter PFS (P= .007).
3.2. Prognostic significance of histologic markers in the PRIMA cohort
As regards PFS, the optimal cutoff for both markers was determined by the highest of theχ2log-rank values, which was 0.80% for MUM1. A high level of MUM1positivity (ie, above 0.80%) was significantly associated with a shorter PFS. Four-year PFS was 53.1% for patients in the high MUM1 group instead of 68.7% in the low MUM1 group of patients (P= .004, log-rank test,Fig. 2A
F2 ). A high level
of Ki-67 positivity (ie, above an optimal cutoff value of 10.25%) was significantly associated with a shorter PFS.
Four-year PFS was 45.8% for patients in the high Ki-67 group instead of 64.3% in the low Ki-67 group of patients (P= .007, log-rank test,Fig. 2B).
In a multivariate Cox proportional hazards regression model, only MUM1 staining retained a statistical significance (hazards ratio 1.56; 95% confidence interval, 1.02-2.37;
P = .038) over Ki-67 staining after adjustment for the maintenance arm of treatment and the FLIPI score (Table 1
T1 ).
Neither MUM1 nor Ki-67 was significantly associated with outcome in terms of OS, but only few death events were observed within the short-term follow-up (data not shown).
3.3. Validation of MUM1 prognostic value in the FL2000 cohort
Because MUM1 was the only significant marker for PFS in multivariate analysis based on the PRIMA cohort of patients, its prognostic value was further tested on the FL2000 cohort, in which MUM1 staining was available for 121 patients.
Distributions of markers for the FL2000 cohort of patients are depicted in Supplementary Fig. S2A and B. When the optimal cutoff value obtained from the PRIMA cohort was applied to the FL2000 cohort for dichotomization, a higher MUM1 expression (ie, positive staining N0.80%) was significantly associated to a shorter PFS (P= .004,Fig. 3A
F3 ).
Four-year PFS was therefore 39.5% for patients in the high MUM1 group instead of 58.9% in the low MUM1 group of patients. This correlation remained significant using a
multivariate Cox regression model after adjustment for the
FLIPI and the treatment arm (P = .016, Table 2) for PFS. T2
Importantly, a trend toward a worse outcome in terms of OS was also observed. Four-year OS was indeed 86.8% for patients in the MUM1-high group instead of 94.0% in the MUM1-low group (P = .043, log-rank test, Fig. 3B). The prognostic value of Ki-67 staining (using the optimal cutoff based on the PRIMA cohort) was further tested as an exploratory purpose in the FL2000 cohort (in which Ki-67 staining was available for 116 patients) and was not associated to outcome in terms of PFS or OS (data not shown).
3.4. Correspondence between manual and automatic counting methods
Results are summarized in Supplementary Table 3. The subset of 30 selected PRIMA samples manually analyzed included 10 samples with high MUM1 expression as assessed by CIA (N0.8% cutoff; range, 1.5%-12.2%), 10 samples with low MUM1 expression (b0.8% cutoff; range, 0.05%-0.4%), and 10 samples with MUM1 expression close to the significant CIA cutoff of 0.8% (range, 0.76%-0.89%). For the latter subgroup, manual counting was estimated as + (between 10%
and 30% of positive cells) in all 10 samples; whereas it was ++ (N30% of positive cells) in 9 of 10 samples of the high-expression group and 0 (less than 10% of positive cells) in 9 of 10 samples of the low-expression group.
4. Discussion
The interferon regulatory factor 4/multiple myeloma–
associated antigen 1 (IRF4/MUM1) has been initially characterized as an important transcription factor for differen- tiation of various subsets of T cells [21-24]. In the B-cell lineage, IRF4/MUM1 has a decisive role for the formation of germinal centers, differentiation of plasma cells, and isotype switching [25]. In normal lymph nodes, MUM1 is mainly expressed in plasma cells and in a small number of germinal center B cells[26]and is mutually exclusive with BCL6[27].
Expression of MUM1 in lymphoid neoplasms includes multiple myeloma, classic Hodgkin lymphoma, and a subset of diffuse large B-cell lymphoma[28].
As regards FL, although it was initially said to be absent, MUM1 is currently considered as expressed in 15% to 40% of FL cases[28-30]. Natkunam et al[28]and Naresh et al[29]
reported MUM1 positivity in 23% and 37% of their FL series, respectively. A significant proportion of grades 3A and 3B were observed among MUM1-positive FL cases [28-32].
Altogether, previous studies indicate that MUM1 expression tends to dichotomize FL into MUM1-negative/low-grade and MUM1-positive/high-grade subgroups.
A single previous study based on 3 sequential non- randomized FL trials has suggested that expression of MUM1 may have prognostic significance [12]. However, Table 1 Predictive value of MUM1 and Ki-67 on PFS using
multivariate analysis after adjustment for FLIPI and randomization in the PRIMA cohort
Parameter Label HR 95% CI P
FLIPI Intvslow 1.774 0.936-3.362 .078 Highvslow 2.711 1.523-4.828 b.001 KI-67 area N10.3vs≤10.3 1.273 0.840-1.930 .255 MUM1 area N0.80vs≤0.80 1.558 1.025-2.369 .038 Randomization Rvsno R
maintenance
0.725 0.496-1.058 .095
Abbreviations: PFS, progression-free survival; HR, hazards ratio; CI, confidence interval; Int, intermediate; R, rituximab.
only 180 biopsy samples were available from these protocols, which were heterogeneous in terms of immuno- therapy[12]. Although MUM1 expression was associated with the risk of death in the entire data set, it was not correlated with survival within the main trial including most
patients [12]. The present study validates the adverse prognostic impact of MUM1 in 2 large cohorts of uniformly treated patients from independent randomized trials. To our knowledge, the corresponding pooled series represents the greatest collection of FL samples ever reported to date. The Fig. 3 Correlation between MUM1 expression and PFS or OS in the FL2000 study. A, A higher MUM1 expression (ie, positive staining N0.80%) was significantly associated to a shorter PFS (P= .004). B, A trend toward a worse outcome in terms of OS was also observed (P= .043).
use of CIA led to similar conclusions after both univariate analysis and adjustment on the FLIPI, thereby pointing to MUM1 expression as a robust predictor of worse outcome in FL.
The predictive value of MUM1 may be related to its implication in a functional mechanism favoring the growth of lymphoma cells. Recently, some FL subtypes distinguished by a high level of MUM1 expression were shown to carry MUM1/IRF4 breaks including IG-IRF4 fusion[33,34]. These FL cases, however, were characterized by a histologic grade 3B and a disease onset predominantly in childhood [33,34].
This does not seem relevant in our study because grade 3B and pediatric cases were criteria of exclusion for both FL2000 and PRIMA protocols. For the same reason, our series do not include cases of composite lymphoma harboring a MUM1+
diffuse large cell lymphoma component that could explain an adverse outcome. In this extent, our series also do not include highly unfavorable prognosis cases, which implies that the MUM1 value is relevant for patients pursuing a relatively indolent course, who represent most FL cases. A predictive marker in this FL population has less dramatic clinical impact but remains an essential tool to stratify these patients in clinical trials to improve FL therapies.
The adverse role of MUM1 in FL may result from a mechanism of activation similar to myeloma cells, in which expression of MUM1 not only drives the cell survival in cases withIG-IRF4fusion but is also essential in cases lacking this translocation[35]. Alternatively, the poor predictive value of MUM1 may be a surrogate marker for another aspect of tumor biology, not directly related to MUM1.
Because MUM1+ interfollicular plasma cells were taken into account in automatic counts to standardize the procedure, we cannot exclude that plasma cells could play a role in the adverse influence of MUM1 expression. This hypothesis seems, however, unlikely due to the small number and random distribution of plasma cells among FL samples. Similarly, MUM1+ T cells were hardly detectable using dual staining experiments, so their impact on MUM1 counting appears probably insignificant. The MUM1 predictive value was previously reported using manual counting with a cutoff of 20% of MUM1-positive intrafollicular cells [10]. In accor- dance with this previous study, our manual count of samples displaying automatic count values close to the cutoff of 0.8%
showed that all these samples contained 10% to 30% of MUM1-positive cells. Although this correspondence obtained in a small subgroup of cases has a limited value, it may help pathologists in routine practice to select cases for further image analysis.
Although CIA remains currently difficult to handle in routine practice, it appears as a promising tool, as it has been shown to reduce the poor reproducibility due to the visual assessment of IHC stainings[3,6-8]. The increasing access to digital slide scanners should allow most laboratories to perform automated measurements in the near future. Standardization and comparison across centers of automatically generated data are still needed before MUM1 can be used as a routine biomarker for the clinical management of patients with FL.
Supplementary data
Supplementary data to this article can be found online at http://dx.doi.org/10.1016/j.humpath.2014.06.019.
Acknowledgments
We thank Benedicte Gelas-Dore for precious help in statistical analyses, Nadine Vailhen and the Lymphoma Study Association pathology technicians for their assistance in pathologic reviewing, and Francine Azario-Cheillan for assistance in computer image analysis.
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