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

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Kornauth, Christoph, Pemovska, Tea, Vladimer, Gregory I., Bayer, Günther, Bergmann, Michael, Eder, Sandra, Eichner, Ruth, Erl, Martin, Esterbauer, Harald, Exner, Ruth, Felsleitner-Hauer, Verena, Forte, Maurizio, Gaiger, Alexander, Geissler, Klaus, Greinix, Hildegard T., Gstöttner, Wolfgang, Hacker, Marcus, Hartmann, Bernd Lorenz, Hauswirth, Alexander W., Heinemann, Tim, Heintel, Daniel, Hoda, Mir Alireza, Hopfinger, Georg, Jaeger, Ulrich, Kazianka, Lukas, Kenner, Lukas, Kiesewetter, Barbara, Krall, Nikolaus, Krajnik, Gerhard, Kubicek, Stefan, Le, Trang, Lubowitzki, Simone, Mayerhoefer, Marius E., Menschel, Elisabeth, Merkel, Olaf, Miura, Katsuhiro, Müllauer, Leonhard, Neumeister, Peter, Noesslinger, Thomas, Ocko, Katharina, Öhler, Leopold, Panny, Michael, Pichler, Alexander, Porpaczy, Edit, Prager, Gerald W., Raderer, Markus, Ristl, Robin, Ruckser, Reinhard, Salamon, Julius, Schiefer, Ana-Iris, Schmolke, Ann-Sofie, Schwarzinger, Ilse, Selzer, Edgar, Sillaber, Christian, Skrabs, Cathrin, Sperr, Wolfgang R., Srndic, Ismet, Thalhammer, Renate, Valent, Peter, van der Kouwe, Emiel, Vanura, Katrina, Vogt, Stefan, Waldstein, Cora, Wolf, Dominik, Zielinski, Christoph C., Zojer, Niklas, Simonitsch-Klupp, Ingrid, Superti-Furga, Giulio, Snijder, Berend, Staber, Philipp B.·2022·Cancer Discovery
DOI 10.1158/2159-8290.cd-21-0538PMC PMC9762339

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Abstract

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

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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 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.CC BY-NC-ND · PubMed Central
Figure 2. CONSORT diagram of study patients.
Figure 2. CONSORT diagram of study patients.CC BY-NC-ND · PubMed Central
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 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).CC BY-NC-ND · PubMed Central
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%).
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%).CC BY-NC-ND · PubMed Central

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  1. Swerdlow, 2017, WHO classification of tumours of haematopoietic and lymphoid tissues. Rev. 4th ed

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Authors
Kornauth, C., Pemovska, T., Vladimer, G. I., Bayer, G., Bergmann, M., Eder, S., Eichner, R., Erl, M., Esterbauer, H., Exner, R., Felsleitner-Hauer, V., Forte, M., Gaiger, A., Geissler, K., Greinix, H. T., Gstöttner, W., Hacker, M., Hartmann, B. L., Hauswirth, A. W., Heinemann, T., Heintel, D., Hoda, M. A., Hopfinger, G., Jaeger, U., Kazianka, L., Kenner, L., Kiesewetter, B., Krall, N., Krajnik, G., Kubicek, S., Le, T., Lubowitzki, S., Mayerhoefer, M. E., Menschel, E., Merkel, O., Miura, K., Müllauer, L., Neumeister, P., Noesslinger, T., Ocko, K., Öhler, L., Panny, M., Pichler, A., Porpaczy, E., Prager, G. W., Raderer, M., Ristl, R., Ruckser, R., Salamon, J., Schiefer, A.-I., Schmolke, A.-S., Schwarzinger, I., Selzer, E., Sillaber, C., Skrabs, C., Sperr, W. R., Srndic, I., Thalhammer, R., Valent, P., van der Kouwe, E., Vanura, K., Vogt, S., Waldstein, C., Wolf, D., Zielinski, C. C., Zojer, N., Simonitsch-Klupp, I., Superti-Furga, G., Snijder, B., & Staber, P. B.
Affiliations
  • Vienna General Hospital (AT)
  • Austrian Academy of Sciences (AT)
  • Medical University of Vienna (AT)
  • Klinikum Klagenfurt (AT)
  • 8Abteilung für Innere Medizin, Krankenhaus der Barmherzigen Brüder Salzburg, Salzburg, Austria.
  • Universitätsklinikum Wiener Neustadt (AT)
  • Sigmund Freud Privatuniversität Wien (AT)
  • Medical University of Graz (AT)
  • Landeskrankenhaus Feldkirch (AT)
  • ETH Zurich (CH)
  • 17Division of Medicine I, Klinik Ottakring, Vienna, Austria.
  • 19Third Medical Department, Centre for Oncology and Haematology, Klinik Favoriten, Vienna, Austria.
  • Universitätsklinikum St. Pölten (AT)
  • Memorial Sloan Kettering Cancer Center (US)
  • Hanusch Hospital (AT)
  • Nihon University (JP)
  • St. Josef-Krankenhaus Wien (AT)
  • 29Second Medical Department, Klinik Donaustadt, Vienna, Austria.
  • 30Department of Medicine, Landesklinikum Waidhofen a.d. Ybbs, Waidhofen-Ybbs, Austria.
  • Ludwig Boltzmann Institute for Hematology and Oncology (AT)
  • 1Department of Medicine I, Division of Hematology and Hemostaseology, Medical University of Vienna, Vienna, Austria.
  • Innsbruck Medical University (AT)
  • 5Department of Pathology, Medical University of Vienna, Vienna, Austria.
  • 3CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.
Corresponding author
Staber, Philipp B.
ORCID
Venue
Cancer Discovery
Publisher
American Association for Cancer Research (AACR)
Published
2021-10-11
Volume
12
Issue
2
Pages
372-387
ISSN
  • 2159-8274 (ISSN-L)
  • 2159-8290
DOI
10.1158/2159-8290.cd-21-0538
PMC
PMC9762339
OpenAlex
W3205761999
Cited by
206
References
43
Citations by year
2026: 36 · 2025: 47 · 2024: 45 · 2023: 46 · 2022: 29 · 2021: 3
FWCI
20.21
Type
journal article
Language
en
Open access
Licence
Locations
  • Cancer Discovery (publishedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
Funders
  • Vienna Science and Technology Fund (LS16-034)
  • Austrian Science Fund (F4704-B20, F4711-B20, P27132-B20)
  • European Molecular Biology Organization (1543-2012, 733-2016)
  • Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (PP00P3_163961, PP00P3_194809, CRSII5_193832)
  • European Research Council
Topics
  • Health Sciences › Medicine › Hematology › Acute Myeloid Leukemia Research
  • Health Sciences › Medicine › Hematology › Chronic Lymphocytic Leukemia Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Degradation and Inhibitors
Keywords
functional precision medicine, hematologic malignancies, high-content imaging, drug response prediction, progression-free survival, exceptional responders
MeSH terms
Progression-Free Survival, Adult, Aged, Aged, 80 and over, Austria, Female, Humans, Male, Middle Aged, Cohort Studies, Hematologic Neoplasms, Young Adult, Precision Medicine, Molecular Targeted Therapy

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