A Tissue Microarray Classification in Multiple Myeloma (MM) Predicts Survival Post Autologous Stem Cell Transplant (ASCT).
Authors: Bahlis Nizar , Stewart Douglas , Shin Brian , Mansoor Adnan 
Published: October 2019

Background: The prognosis of MM patients undergoing ASCT is predicted BY the ISS in conjunction with cytogenetic studies. Along these parameters, GEP based molecular classification was proven to be a dominant and independent predictor of survival. However the wide implementation of the molecular classification is lacking due to the complexity of the methodology involved in the analysis of such approach.

Methods: After analysis of the GEP molecular classification we have constructed a four “biomarker” based decision tree for an immunohistochemical classification of MM. Immunoperoxidase results for cyclin B2, FGFR3, cyclin D2 and Integrin beta 7 were used to subclassify MM cases into a High risk (HR) and Low risk (LR) subgroups as shown below. Additional staining for PAX5 and PBX1 and cyclins D1, D3 and B1 were also performed. A tissue microarray containing diagnostic bone marrow biopsies of 52 newly diagnosed MM patients uniformly treated with a dexamethasone based regimen followed by ASCT was used as a training set to validate the proposed prognostic model. The clinical parameters, response criteria and survival outcomes (PFS and OS) of this testing cohort were defined according to the international uniform response criteria. FISH studies for del13 and t(4;14) were also performed. For immunohistochemical analysis (IHC) a pathologist who was blinded with regards to the clinical outcome of these patients scored these cases as positive or negative. The Kaplan-Meier method was used to estimate OS and TTP. Multivariate analysis was performed using the Cox regression method.

Results: 52 patients were included in this testing cohort: the median age was 59 yrs (39–72), 25.7% had ISS stage III, median beta2-microglobulin was 3.43 mg/L (1.16–21.81). Del13q, t(4;14) and del17p13 were detected in 38.9%, 26.1% and 11 25% of patients, respectively. Post ASCT, 31.1% achieved a CR or VGPR with a 4 yrs PFS and OS of 24.1% and 67.8% respectively. Expression of FGFR3 was seen 9.8% of the patients, cyclin B2 in 58.1%, cyclin D2 in 72.1% and integrin-beta7 in 33%. In univariate analysis expression of FGFR3 was associated with a significantly shorter PFS (P=0.003) but not OS (P=0.228). Similarly integrin-beta7 predicted for longer PFS (P=0.014) but not OS (P=0.745). Cyclin B2 predicted for worse PFS (P=0.002) and OS (P=0.032), whereas the expression of cyclin D2 did not predict for OS or PFS. Out of 43 evaluable cases, 24 (55.8%) were considered as High risk by TMA analysis and had a significantly shorter PFS (P=0.001) and OS (P=0.044) compared with the Low risk group. The 3 yrs PFS for the Low risk group was 62.3% compared to only 7.6% for the High risk group. The 5 yrs OS for the Low risk group was 83.9% compared to 60.7% for the High risk group. Multivariate analysis was performed using ISS, FGFR3, cylin B2 and the risk group classification as variables. The TMA classification and FGFR3 were the only independent predictors of PFS with the high risk group having 5.9 fold greater risk of relapse.

Conclusion: we found that expression of FGFR3, cyclinB2, cylinD2 and Integrin-beta7 in a tissue based array is powerful predictor of survival post ASCT in MM. A validation of the results in a larger cohort is underway.

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