BMC Cancer (Dec 2020)

Immune-related protein signature in serum stratify relapsed mantle cell lymphoma patients based on risk

  • Lavanya Lokhande,
  • Venera Kuci Emruli,
  • Arne Kolstad,
  • Martin Hutchings,
  • Riikka Räty,
  • Mats Jerkeman,
  • Sara Ek

DOI
https://doi.org/10.1186/s12885-020-07678-4
Journal volume & issue
Vol. 20, no. 1
pp. 1 – 13

Abstract

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Abstract Background Response to modern treatment strategies, which combine cytotoxic compounds with immune stimulatory agents and targeted treatment is highly variable among MCL patients. Thus, providing prognostic and predictive markers for risk adapted therapy is warranted and molecular information that can help in patient stratification is a necessity. In relapsed MCL, biopsies are rarely available and molecular information from tumor tissue is often lacking. Today, the main tool to access risk is the MCL international prognostic index (MIPI), which does not include detailed biological information of relevance for different treatment options. To enable continuous monitoring of patients, non-invasive companion diagnostic tools are needed which can further reduce cost and patient distress and enable efficient measurements of biological markers. Methods We have assessed if serum-based protein profiling can identify immune related proteins that stratify relapsed MCL patients based on risk. Overall, 371 scFv targeting 158 proteins were assessed using an antibody microarray platform. We profiled patients (n = 44) who had been treated within the MCL6-Philemon trial combining targeted and immune-modulatory treatment. Results The downstream processing led to the identification of the relapsed immune signature (RIS) consisting of 11 proteins with potential to stratify patients with long and short overall survival (OS). Moreover, in this population, MIPI alone failed to separate high, intermediate and low risk patients, but a combined index based on MIPI together with RIS, MIPIris, showed improved performance and significantly stratified all three risk groups based on OS. Conclusions Our results show that addition of biological parameters to previous prognostic indices improves patient stratification among patients treated with BTK inhibitor triplet combination, particularly, in the identification of an extreme high risk group.

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