Functional Precision Medicine Provides Clinical Benefit in Advanced Aggressive Hematologic Cancers and Identifies Exceptional Responders

Christoph Kornauth, Tea Pemovska, Gregory I Vladimer, Günther Bayer, Michael Bergmann, Sandra Eder, Ruth Eichner, Martin Erl, Harald Esterbauer, Ruth Exner, Verena Felsleitner-Hauer, Maurizio Forte, Alexander Gaiger, Klaus Geissler, Hildegard T Greinix, Wolfgang Gstöttner, Marcus Hacker, Bernd Lorenz Hartmann, Alexander W Hauswirth, Tim Heinemann, Daniel Heintel, Mir Alireza Hoda, Georg Hopfinger, Ulrich Jaeger, Lukas Kazianka, Lukas Kenner, Barbara Kiesewetter, Nikolaus Krall, Gerhard Krajnik, Stefan Kubicek, Trang Le, Simone Lubowitzki, Marius E Mayerhoefer, Elisabeth Menschel, Olaf Merkel, Katsuhiro Miura, Leonhard Müllauer, Peter Neumeister, Thomas Noesslinger, Katharina Ocko, Leopold Öhler, Michael Panny, Alexander Pichler, Edit Porpaczy, Gerald W Prager, Markus Raderer, Robin Ristl, Reinhard Ruckser, Julius Salamon, Ana-Iris Schiefer, Ann-Sofie Schmolke, Ilse Schwarzinger, Edgar Selzer, Christian Sillaber, Cathrin Skrabs, Wolfgang R Sperr, Ismet Srndic, Renate Thalhammer, Peter Valent, Emiel van der Kouwe, Katrina Vanura, Stefan Vogt, Cora Waldstein, Dominik Wolf, Christoph C Zielinski, Niklas Zojer, Ingrid Simonitsch-Klupp, Giulio Superti-Furga, Berend Snijder, Philipp B Staber, Christoph Kornauth, Tea Pemovska, Gregory I Vladimer, Günther Bayer, Michael Bergmann, Sandra Eder, Ruth Eichner, Martin Erl, Harald Esterbauer, Ruth Exner, Verena Felsleitner-Hauer, Maurizio Forte, Alexander Gaiger, Klaus Geissler, Hildegard T Greinix, Wolfgang Gstöttner, Marcus Hacker, Bernd Lorenz Hartmann, Alexander W Hauswirth, Tim Heinemann, Daniel Heintel, Mir Alireza Hoda, Georg Hopfinger, Ulrich Jaeger, Lukas Kazianka, Lukas Kenner, Barbara Kiesewetter, Nikolaus Krall, Gerhard Krajnik, Stefan Kubicek, Trang Le, Simone Lubowitzki, Marius E Mayerhoefer, Elisabeth Menschel, Olaf Merkel, Katsuhiro Miura, Leonhard Müllauer, Peter Neumeister, Thomas Noesslinger, Katharina Ocko, Leopold Öhler, Michael Panny, Alexander Pichler, Edit Porpaczy, Gerald W Prager, Markus Raderer, Robin Ristl, Reinhard Ruckser, Julius Salamon, Ana-Iris Schiefer, Ann-Sofie Schmolke, Ilse Schwarzinger, Edgar Selzer, Christian Sillaber, Cathrin Skrabs, Wolfgang R Sperr, Ismet Srndic, Renate Thalhammer, Peter Valent, Emiel van der Kouwe, Katrina Vanura, Stefan Vogt, Cora Waldstein, Dominik Wolf, Christoph C Zielinski, Niklas Zojer, Ingrid Simonitsch-Klupp, Giulio Superti-Furga, Berend Snijder, Philipp B Staber

Abstract

Personalized medicine aims to match the right drug with the right patient by using specific features of the individual patient's tumor. However, current strategies of personalized therapy matching provide treatment opportunities for less than 10% of patients with cancer. A promising method may be drug profiling of patient biopsy specimens with single-cell resolution to directly quantify drug effects. We prospectively tested an image-based single-cell functional precision medicine (scFPM) approach to guide treatments in 143 patients with advanced aggressive hematologic cancers. Fifty-six patients (39%) were treated according to scFPM results. At a median follow-up of 23.9 months, 30 patients (54%) demonstrated a clinical benefit of more than 1.3-fold enhanced progression-free survival compared with their previous therapy. Twelve patients (40% of responders) experienced exceptional responses lasting three times longer than expected for their respective disease. We conclude that therapy matching by scFPM is clinically feasible and effective in advanced aggressive hematologic cancers. SIGNIFICANCE: This is the first precision medicine trial using a functional assay to instruct n-of-one therapies in oncology. It illustrates that for patients lacking standard therapies, high-content assay-based scFPM can have a significant value in clinical therapy guidance based on functional dependencies of each patient's cancer.See related commentary by Letai, p. 290.This article is highlighted in the In This Issue feature, p. 275.

©2021 The Authors; Published by the American Association for Cancer Research.

Figures

Figure 1.
Figure 1.
EXALT procedure and primary outcome measure. A, Viable cells from lymph node (LN), BM, or PB of patients with late-stage hematologic cancer were subjected to image-based scFPM. Target cells are identified by staining with fluorescent antibodies. Reports, automatically generated by the analysis pipeline, are discussed in a dedicated tumor board with patients treated accordingly. B, Our primary outcome measure was PFS ratio, defined as PFS(scFPM treatment)/PFS(previous treatment). A ratio of 1.3 is considered individually beneficial. DAPI, 4′,6-diamidino-2-phenylindole.
Figure 2.
Figure 2.
CONSORT diagram of study patients.
Figure 3.
Figure 3.
scFPM-guided treatment enhances PFS ratio in patients with advanced hematologic cancers and provides a survival benefit. A, Bar plot showing the PFS for all included, scFPM-guided patients: blue bars denote PFS in days for scFPM-guided treatment, red bars indicate last previous treatment, and asterisks denote ongoing response for scFPM treatment at the censoring date. PFS ratio is the following ratio: PFS(scFPM treatment)/PFS(previous treatment). Patient characteristics are color coded and stratified (leukemia vs. lymphoma, exceptional response vs. nonexceptional response, ECOG >1 vs. ECOG ≤1). B, Kaplan–Meier plot comparing PFS on scFPM-guided treatment with previous treatment in exceptional responders (n = 12). C, Bar plot showing PFS for all patients with an ECOG ≤1 (n = 39). Asterisks denote ongoing response for scFPM treatment at censoring date. D, Kaplan–Meier plot comparing PFS on scFPM treatment between patients with ECOG ≤1 (n = 39) versus ECOG>1 (n = 17). E, Bar plot showing PFS for all patients with OR on previous treatment. Asterisks denote ongoing response for scFPM treatment at censoring date. F, Kaplan–Meier plot comparing PFS on scFPM treatment stratified according to OR on last treatment (CR/PR: n = 27, SD/PD: n = 29). G, Scatter plot comparing PFS on last treatment to current treatment, for scFPM-guided versus physician's choice patients (paired Wilcoxon test). H, Kaplan–Meier plot comparing overall survival stratified according to scFPM-guided patients (n = 56) versus physician's choice patients (n = 20).
Figure 4.
Figure 4.
Post hoc analysis. A, Kaplan–Meier plot comparing scFPM-matched treatment with previous treatment. Dotted line denotes 1-year follow-up. B, Kaplan–Meier plot comparing non–scFPM-matched treatment with previous treatment. C, Paired scatter plot comparing nonmatched versus matched patients with regard to PFS ratio. Paired Wilcoxon test comparing PFS of previous treatment versus scFPM-matched/nonmatched treatment [H0: rank PFS(previous) = rank PFS(current)]. D, Kaplan–Meier plot of scFPM-matched treatment stratified according to ECOG <1 versus ECOG ≥1. E, Kaplan–Meier plot of scFPM-matched treatment stratified according to response on previous treatment. F, Kaplan–Meier plots comparing PFS for scFPM-matched patients stratified according to tumor cell content in the sample (high ≥50%, medium >10%, low ≥10%).

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Source: PubMed

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