The Prognostic Power of Gene Expression Profiling with Cytogentics and Routinely Acquired Serum Markers: SKY92 Combined with Revised ISS
Authors: Kuiper Rowan , Duin Mark van , Van Vliet Martin H , Van Beers Erik H , Beverloo Berna Berna , Zweegman Sonja , Cupedo Tom , Broijl Annemiek , Sonneveld Pieter 
Published: February 2021

Background

Updating prognostic models for multiple myeloma is important in the context of changing treatment options. Previously we have described the value of the prognostic marker SKY92, which identifies high-risk multiple myeloma patients, as well as the value of the combined SKY92-ISS marker. With the introduction of revised ISS, it is of interest to evaluate the value of the updated combination of SKY92 with R-ISS. Within the HOVON87/NMSG18 trial, stratification into 3 groups was described: high-risk: 11% SKY92 high-risk (HR) + R-ISS II-III, low-risk: 15% SKY92 standard risk (SR) + R-ISS I and intermediate risk (74%, other). The 3-year PFS rates were 54% (95%CI: 38-77%), 27% (95%CI: 21-37%) and 7% (95%CI: 1-46%) for SKY-RISS I, II and III, respectively (p &lt; 0.001). The 3-yr OS rates for SKY-RISS I to III were 88%, 66% and 26% (p=6×10-7). Here we describe the validation of SKY92-RISS in the CoMMpass dataset.

Methods

SKY92 was determined using RNA-seq data available from the CoMMpass dataset. Briefly, the SKY92 score was obtained as a weighted summation of the expression given by the available Ensembl gene IDs, corresponding to the probe sets of the SKY92 classifier. Renormalization of the original SKY92 discovery data (HOVON65/GMMG-HD4) allowing a direct remodeling between the Affymetrix probe-set expressions (i.e. SKY92) and RNAseq Ensembl gene IDs. Only Ensembl gene IDs with an average log2 expression &gt;8 were used. Revised ISS status was determined as described. For optimal comparison to the discovery cohort of the HOVON87/NMSG18 trial, the analysis was limited to 93 patients older than 65 years in the CoMMpass data set, that did not receive transplant, and for whom RNA-Seq at diagnosis, R-ISS and follow-up data were available.

Results

The median follow-up is 41 months. SKY92 identified 24 high-risk patients (24/93: 26%). The 3-yr PFS and OS rates of standard-risk patients were 49% and 80% respectively, compared to 23% and 44% for high-risk, resulting in a significant log rank test (p &lt; 0.005). The R-ISS classified patients into the low-risk R-ISS I (24% of patients), intermediate-risk R-ISS II (63%) and high-risk R-ISS III (13%). The 3-yr PFS rates were 76% (RISS I), 33% (RISS II) and 33% (RISS III); for OS: 100% (RISS I), 68% (RISS II) and 33% (RISS III; PFS, p = 0.07; OS, p &lt; 0.001). SKY92 and R-ISS were independent prognostic factors in terms of OS and PFS. The SKY-RISS classification resulted in 20% low-, 61% intermediate- and 18% high-risk patients (Figure 1). The 3-yr PFS rates were 81% (95%CI: 64-100%), 42% (95%CI: 30-59%) and 12% (95%CI: 3-44%; p &lt; 0.001) and 3-yr OS rates were 100% (95%CI: 100-100%), 77% (95%CI: 66-89%) and 32% (95%CI: 16-61%; p &lt;0.001).

Out of 69 patients classed as standard risk using the SKY92 classifier (80% 3-yr OS rate), 17 and 52 were classified as SKY-RISS I and II, respectively, resulting in a 3-yr survival rate of 100% and 74%, respectively. In contrast, out of 24 SKY92 HR patients (44% 3 yr OS rate), 5 were classified as SKY-RISS II (100% alive at 3 years) with the remainder true high-risk patients (32% alive at 3 years). Out of 12 RISS III patients (3-yr OS, 33%), 5 were classified as SKY-RISS II (3-yr OS: 60%) and 7 as SKY-RISS III (3-yr OS: 14%).

Conclusion

This study demonstrates the value of gene expression profiling - SKY92 - alongside revised ISS. They form a solid combination, improving on either marker separately. Both models combined clearly identified more high-risk patients correctly, whilst also placing low risk patients into a more appropriate risk category. This was shown in the discovery set and was subsequently applied to an independent set, confirming the validity and usability of the SKY-RISS.

Disclosures

Kuiper: SkylineDx: Current Employment, Current equity holder in private company. Van Vliet:SkylineDx: Current Employment, Current equity holder in private company. Van Beers:SkylineDx: Ended employment in the past 24 months. Zweegman:Celgene: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding. Broijl:Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene/BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees. Sonneveld:Sanofi: Consultancy; Bristol-Myers Squibb: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Skyline Dx: Honoraria, Research Funding; Karyopharm: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria, Research Funding.