Proteomic test for anti-PD-1 checkpoint blockade treatment of metastatic melanoma with and without BRAF mutations

Abstract

The therapeutic landscape in metastatic melanoma has changed dramatically in the last decade, with the success of immune checkpoint inhibitors resulting in durable responses for a large number of patients. For patients with BRAF mutations, combinations of BRAF and MEK inhibitors demonstrated response rates and benefit comparable to those from immune checkpoint inhibitors, providing the rationale for sequential treatment with targeted and immunotherapies and raising the question of optimal treatment sequencing. Biomarkers for the selection of anti-PD-1 therapy in BRAF wild type ( BRAF WT) and in BRAF mutated ( BRAF MUT) patients help development of alternative treatments for patients unlikely to benefit, and might lead to better understanding of the interaction of checkpoint inhibition and targeted therapy. In this paper we evaluate the performance of a previously developed serum proteomic test, BDX008, in metastatic melanoma patients treated with anti-PD-1 agents and investigate the role of BRAF mutation status. BDX008, a pre-treatment proteomic test associated with acute phase reactants, wound healing and complement activation, stratifies patients into two groups, BDX008+ and BDX008-, with better and worse outcomes on immunotherapy. Serum samples were available from 71 patients treated with anti-PD1 inhibitors; 25 patients had BRAF mutations, 39 were wild type. Overall, BDX008+ patients had significantly better overall survival (OS) (HR = 0.50, P = 0.016) and a trend for better progression-free survival (PFS) (HR = 0.61, P = 0.060) than BDX008- patients. BDX008 classification was statistically significant in the analyses adjusted for mutation status, LDH, and line of treatment ( P = 0.009 for OS and 0.031 for PFS). BRAF WT BDX008+ patients had markedly long median OS of 32.5 months and 53% landmark 2 years survival, with statistically significantly superior OS as compared to BDX008- patients (HR = 0.41, P = 0.032). The difference between BDX008+ and BDX008- in PFS in BRAF WT patients and in OS and PFS in BRAF MUT patients did not reach statistical significance, though numerically was consistent with overall results. The test demonstrated significant interaction with neutrophil-to-lymphocyte ratio (NLR) (PFS P = 0.041, OS P = 0.004). BDX008 as a biomarker selecting for benefit from immune checkpoint blockade, especially in patients with wild type BRAF and in subgroups with low NLR , warrants further evaluation. Electronic supplementary material The online version of this article (10.1186/s40425-019-0569-1) contains supplementary material, which is availa...

Correlative Monitoring of Immune Activation and Tissue Damage in Malignant Melanoma—An Algorithm for Identification of Tolerance Breakage During Immune Checkpoint Inhibitor Therapy of Cancer

“…Enhanced programmed cell death ligand 1 (PD-L1) expression in the tumor melanoma, non-small cell lung cancer (NSCLC), renal-cell carcinoma, prostate cancer, colorectal cancer [5][6][7][8] Presence of CD8+tumor-infiltrating lymphocytes melanoma, NSCLC, renal-cell carcinoma, colorectal cancer [5][6][7]9,10] High tumor mutational burden or neoantigen burden melanoma, NSCLC, colorectal cancer, urothelial carcinoma [5,11,12] Presence of intratumoral major histocompatibility complex (MHC) class II expression melanoma [5,13] Presence of intratumoral interferon-γ-immune gene signature melanoma, head and neck cancer [5,14] Low interleukin (IL)-6 expression in the tumor colorectal cancer [15] Peripheral blood count: low absolute neutrophils, low absolute monocytes, low myeloid-derived suppressor cells, high FoxP3+ regulatory T cells, high lymphocytes, high eosinophils, high CD19−HLA-DR+ myeloid cells, high CD14+CD16b−HLA-DRhi monocytes melanoma, NSCLC [5,[16][17][18] Low level of c-reactive protein (CRP) in the serum, low relative eosinophil count uveal melanoma [19] Serum proteome analysis: BDX008 melanoma [20] An alternative approach to the search of predictive biomarkers sensu stricto is the identification of predictive biomarkers which are determined under checkpoint inhibitor therapy but before evidence by radiologic imaging of response to therapy [18,21,22]. Table 2 provides an overview of treatment response monitoring biomarkers.…”

Mass Spectrometry-Based Multivariate Proteomic Tests for Prediction of Outcomes on Immune Checkpoint Blockade Therapy: The Modern Analytical Approach

“…Tests classifications were found to be correlated with several prognostic factors: BDX008classification was significantly associated with higher levels of LDH (Fisher's test p = 0.006) and NLR > 5 (Fisher's test p = 0.003) in melanoma patients [46]; the ICB test correlated with LDH (p = 0.006) and with baseline tumor size (p < 0.001) [43]. However, all the tests retained their statistical significance for prediction of OS in multivariate analyses that included various prognostic factors and available biomarker measurements: the BDX008 test was an independent predictive factor (p = 0.009) when adjusted for BRAF mutation status, line of treatment, and LDH in an independent validation cohort of melanoma patients [46]; the ICB classification remained a significant predictor of survival (p = 0.002) when adjusted for gender, age, LDH, PD-L1 expression, prior treatment, and tumor size [43]. In the lung cancer setting, the PIR test (Resistant vs. Not Resistant) was a significant predictor of survival when adjusted for ECOG performance status, smoking history, histology, and PD-L1 expression (p = 0.030) [67].…”

“…Similar results are also observed for 3-year survival landmark, Table 2. Both tests have been validated in multiple independent cohorts of melanoma patients [43,46,53] treated with ICIs; the BDX008 test has also shown potential utility in NSCLC patients treated with nivolumab [50].…”

“…In the case of melanoma patients, we could evaluate the potential interaction between test classifications and NLR [23]-a biomarker of systemic inflammation that has previously shown association with outcomes on ICIs [24,25]. The Kaplan-Meier plots suggested that the difference in outcomes between BDX008 classifications may be qualitatively different in the subgroups defined by NLR: it appeared that patients with NLR <5 classified as BDX008+ had especially good outcomes on anti-PD-1 treatment; while at the same time patients classified as BDX008-had poor prognosis independently of NLR status [46] (Figure 2). A Cox proportional hazard analysis of the interaction between BDX008 classification and NLR resulted in an interaction p = 0.002, confirming the importance of both variables for prognosis [46].…”

“…The Kaplan-Meier plots suggested that the difference in outcomes between BDX008 classifications may be qualitatively different in the subgroups defined by NLR: it appeared that patients with NLR <5 classified as BDX008+ had especially good outcomes on anti-PD-1 treatment; while at the same time patients classified as BDX008-had poor prognosis independently of NLR status [46] (Figure 2). A Cox proportional hazard analysis of the interaction between BDX008 classification and NLR resulted in an interaction p = 0.002, confirming the importance of both variables for prognosis [46]. A significant interaction between BDX008 and NLR is notable, because it shows that information about host response that is associated with the BDX008 test is complementary to the measurements of systemic inflammation that are based on immune cell counts in blood.…”