Inhibition of MET Signaling with Ficlatuzumab in Combination with Chemotherapy in Refractory AML: Clinical Outcomes and High-Dimensional Analysis - PubMed (original) (raw)

doi: 10.1158/2643-3230.BCD-21-0055. Epub 2021 Jul 16.

Bradley W Blaser # 3, Ravi K Patel 4, Gregory K Behbehani 3, Arjun A Rao 4, Blythe Durbin-Johnson 5, Tommy Jiang 1 2, Aaron C Logan 1 2, Matthew Settles 5, Gabriel N Mannis 1, Rebecca Olin 1 2, Lloyd E Damon 1 2, Thomas G Martin 1 2, Peter H Sayre 1 2, Karin M Gaensler 1 2, Emma McMahon 1 2, Michael Flanders 1 2, Vivian Weinberg 1, Chun J Ye 1, David P Carbone 3, Pamela N Munster 1 2, Gabriela K Fragiadakis 4 6 7, Frank McCormick 2, Charalambos Andreadis 8 2

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Inhibition of MET Signaling with Ficlatuzumab in Combination with Chemotherapy in Refractory AML: Clinical Outcomes and High-Dimensional Analysis

Victoria E Wang et al. Blood Cancer Discov. 2021 Sep.

Abstract

Acute myeloid leukemia patients refractory to induction therapy or relapsed within one year have poor outcomes. Autocrine production of hepatocyte growth factor by myeloid blasts drives leukemogenesis in pre-clinical models. A phase Ib trial evaluated ficlatuzumab, a first-in-class anti-HGF antibody, in combination with cytarabine in this high-risk population. Dose-limiting toxicities were not observed, and 20 mg/kg was established as the recommended phase II dose. The most frequent treatment-related adverse event was febrile neutropenia. Among 17 evaluable patients, the overall response rate was 53%, all complete remissions. Phospho-proteomic mass cytometry showed potent on-target suppression of p-MET after ficlatuzumab treatment and that attenuation of p-S6 was associated with clinical response. Multiplexed single cell RNA sequencing using prospectively acquired patient specimens identified interferon response genes as adverse predictive factors. The ficlatuzumab and cytarabine combination is well-tolerated with favorable efficacy. High-dimensional analyses at single-cell resolution represent promising approaches for identifying biomarkers of response and mechanisms of resistance in prospective clinical studies.

Keywords: CyTOF; MET; ficlatuzumab; refractory AML; single cell RNA sequencing.

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Conflict of interest statement

Conflict of Interests: The authors declare no potential conflicts of interest.

Figures

Figure 1

Figure 1. Trial schema and endpoints

A. Dose escalation scheme utilizing the traditional 3+3 design. Ficlatuzumab was started at the 10 mg/kg dose and escalated by increments of 5 mg/kg while keeping the dose of cytarabine fixed at 2,000 mg/m2. B. Timeline for drug administration and biospecimens acquisition. Bone marrow biopsies were collected at baseline, on day 14, at count recovery, and at disease relapse. Blood collection occurred at baseline, on days 1–3, prior to and 24 hours after each subsequent doses of ficalatuzumab, at count recovery, and at relapse. C. Kaplan-Meier curves for progression-free survival (PFS). D. Kaplan-Meier curves for overall survival (OS). E. Kaplan-Meier curves for overall survival censored at time of allogenic stem cell transplant. P values indicate comparison between responders and non-responders. All patients (green), responders (blue), and non-responders (red).

Figure 2

Figure 2. Ficlatuzumab treatment exerts on-target effect through attenuation of p-MET

A. UMAP representation of mass cytometry data according to cellular identity after filtering for debris. B. p-MET expression in the CD34+ early myeloid compartment between all patients, independent of pervandate stimulation, versus untreated control as assessed by UMAP and SPADE. C. p-MET expression in the CD33+ myeloid compartment between all patients, independent of pervandate stimulation, versus untreated control as assessed by UMAP and SPADE. D. T-MET expression in the CD34+ early myeloid compartment between all patients versus untreated control. E. T-MET expression in the CD33+ myeloid compartment between all patients versus untreated control as assessed by UMAP and SPADE. F. Differential p-S6 expression between non-responders (NR) and responders (CR) using both UMAP and SPADE analysis. P-values calculated using the Mann-Whitney test.

Figure 3

Figure 3. Cell type identification and HGF expression using freemuxlet

A. Batch-corrected UMAP representation of all cells according to patient identify after filtering for doublets and low-quality cells. B. Batch-corrected UMAP partitioned using top expressed markers according to Jensen-Shannon divergence (PC= plasma cells). C. Heatmap of top expressed genes by cluster. D. Dot plot denoting major immune subsets versus lineage specific markers. Size of the circles indicates proportion of cells expressing the particular marker. Color denotes mean expression in log scale. E. Dot plot quantifying temporal HGF expression across cell type and stratified by response and time. Circle size indicates proportion of cells expressing HGF. Color denotes mean HGF expression in log scale.

Figure 4

Figure 4. Gene module analysis identifies transcriptional signature as biomarkers of ficlatuzumab resistance

A. Unsupervised clustering of gene modules within the myelomonocytic lineage according to treatment day and clinical responses. B. Aggregated counts for module 3 genes in responders (CR) and non-responders (NR) for each treatment timepoint. C. Gene Ontology (GO) terms enriched in module 3. D. Aggregated counts for module 18 genes in CR and NR for each treatment timepoint. E. Gene Ontology (GO) terms enriched in module 18. F. Aggregated counts for module 1 genes in CR and NR for each treatment timepoint. G. Gene Ontology (GO) terms enriched in module 1. H. Aggregated counts for module 7 genes in CR and NR for each treatment timepoint. I. Gene Ontology (GO) terms enriched in module 7.

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