Intratumoral drug-releasing microdevices allow in situ high-throughput pharmaco phenotyping in patients with gliomas - PubMed (original) (raw)

. 2023 Sep 6;15(712):eadi0069.

doi: 10.1126/scitranslmed.adi0069. Epub 2023 Sep 6.

Christine Dominas 2, Geoffrey Fell 3, Joshua D Bernstock 1, Sarah Blitz 4, Debora Mazzetti 1, Mykola Zdioruk 1, Hassan Y Dawood 1, Daniel V Triggs 1, Sebastian W Ahn 2, Sharath K Bhagavatula 2, Shawn M Davidson 5, Zuzana Tatarova 2, Michael Pannell 1, Kyla Truman 1, Anna Ball 1, Maxwell P Gold 6, Veronika Pister 6, Ernest Fraenkel 6 7, E Antonio Chiocca 1, Keith L Ligon 8, Patrick Y Wen 9, Oliver Jonas 2

Affiliations

Intratumoral drug-releasing microdevices allow in situ high-throughput pharmaco phenotyping in patients with gliomas

Pierpaolo Peruzzi et al. Sci Transl Med. 2023.

Abstract

The lack of reliable predictive biomarkers to guide effective therapy is a major obstacle to the advancement of therapy for high-grade gliomas, particularly glioblastoma (GBM), one of the few cancers whose prognosis has not improved over the past several decades. With this pilot clinical trial (number NCT04135807), we provide first-in-human evidence that drug-releasing intratumoral microdevices (IMDs) can be safely and effectively used to obtain patient-specific, high-throughput molecular and histopathological drug response profiling. These data can complement other strategies to inform the selection of drugs based on their observed antitumor effect in situ. IMDs are integrated into surgical practice during tumor resection and remain in situ only for the duration of the otherwise standard operation (2 to 3 hours). None of the six enrolled patients experienced adverse events related to the IMD, and the exposed tissue was usable for downstream analysis for 11 out of 12 retrieved specimens. Analysis of the specimens provided preliminary evidence of the robustness of the readout, compatibility with a wide array of techniques for molecular tissue interrogation, and promising similarities with the available observed clinical-radiological responses to temozolomide. From an investigational aspect, the amount of information obtained with IMDs allows characterization of tissue effects of any drugs of interest, within the physiological context of the intact tumor, and without affecting the standard surgical workflow.

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Conflict of interest statement

P.P. is a cofounder and is on the Board of Directors of Ternalys Therapeutics. He is a named inventor on microRNA-related patent PCT/US2019/029988. J.D.B. has an equity position in Treovir Inc., an oHSV clinical-stage company, and is a member of the UpFront Diagnostics, Centile Bioscience, and NeuroX1 Boards of Scientific Advisors. E.A.C. is currently (within the last year) an adviser to Amacathera, Bionaut Labs, Candel Therapeutics Inc., Genenta Inc., Insightec Inc., DNAtrix Inc., Seneca Therapeutics, and Theriva. He has equity options in Bionaut Laboratories, DNAtrix, Immunomic Therapeutics, Seneca Therapeutics, and Ternalys Therapeutics. He is a cofounder and is on the Board of Directors of Ternalys Therapeutics. In the past (over 12 months ago), he has also advised Alcyone, Amasa, Bexion, Biogen, GSK Oncorus, Merck, Tocagen, Ziopharm, Stemgen, NanoTx., Ziopharm Oncology, Cerebral Therapeutics, Ceregene, GSK, Merck, Janssen, Karcinolysis, Shanghai Biotech, Sangamo Therapeutics, and Voyager Therapeutics. He has received research support from NIH, U.S. Department of Defense, American Brain Tumor Association, National Brain Tumor Society, Alliance for Cancer Gene Therapy, Neurosurgical Research Education Foundation, Advantagene, NewLink Genetics, and Amgen. He also is a named inventor on patents related to oncolytic HSV1 (U.S. patent nos. US10,806,761B2, US10,232,002B1, and US2017/0015757A1) and noncoding RNAs (PCT/US2019/029988). K.L.L. is a founder of Travera. He is a consultant for Travera, Bristol Meyers Squibb, Blaze Bioscience, and Integragen and has received research funding from Bristol Meyers Squibb and Eli Lily. P.Y.W. received research support from Astra Zeneca, Black Diamond, Bristol Meyers Squibb, Celgene, Chimerix, Eli Lily, Erasca, Genentech/Roche, Kazia, MediciNova, Merck, Novartis, Nuvation Bio, Servier, Vascular Biogenics, and VBI Vaccines, and he is an advisory board/consultant for Astra Zeneca, Black Diamond, Celularity, Chimerix, Day One Bio, Genenta, Glaxo Smith Kline, Merck, Mundipharma, Novartis, Novocure, Nuvation Bio, Prelude Therapeutics, Sapience, Servier, Sagimet, Vascular Biogenics, and VBI Vaccines. O.J. is a coinventor of the IMD technology (U.S. patent no. US10390702B2) and is a consultant with compensation (non-equity) to Kibur Medical. The other authors declare that they have no competing interests.

Figures

Fig. 1.

Fig. 1.. Intratumoral microdevices.

(A) Photography of microdevice in real dimensions, compared with a pencil tip. The computer-aided design next to the picture shows an enlargement of the device to display the configuration of each independent drug reservoir outlet. (B) List of drugs contained in the IMD and their mechanism of action. (C) Cartoon representing the workflow of IMD use. (D) Trial schema.

Fig. 2.

Fig. 2.. Effects of IMD integration in the surgical care of patients with gliomas.

Comparison of common healthcare metrics between the group of patients receiving IMD implantation (red, n = 6) and a cohort of patients receiving standard surgery for HGG operated during the same period of time (gray, n = 9). (A) Surgical time (in minutes) from skin incision to skin closure during the surgical operation for tumor resection. (B) Duration of patient stays in the intensive care unit after surgery. (C) Duration of total hospital stays for each patient, from the day of surgery to the day of discharge from the hospital. (D) Cumulative expenses related to the surgical procedure. Reported are means and SD for each group. Comparisons use an unpaired t test, with two-tailed P values shown per each comparison.

Fig. 3.

Fig. 3.. Characterization of intratumoral drug diffusion.

(A) Drug release profiles from each patient for doxorubicin. (B) Drug release profiles from each patient for lapatinib. The inset shows the typical two-dimensional spatial profile of drug distribution. Inset scale bar, 200 μm. (C) Variation in maximum and average dose for doxorubicin between patients. (D) Variation in maximum and average dose for lapatinib between patients. Each dot on the graph represents the mean of triplicate measurements of drug release profile values (maximum or average dose) from biologically distinct regions of each patient’s tumor. Error bars represent SD.

Fig. 4.

Fig. 4.. Differential tumor response to temozolomide.

(A) Quantification of immunohistochemistry stains for pH2AX and CC3 in IMD tissue from each numbered patient. Each dot on the graph represents a unique biological replicate measurement from a tumor region within the area of the tumor exposed to TMZ for a given patient. Statistical comparisons were made using the repeated-measures ANOVA test, with P values shown for each comparison (in parentheses). *P < 0.05; ** P < 0.01. (B) Distance and concentration-dependent analysis of pH2AX and CC3 stains across the six patients. Graphs are shown as means (black) and SD (gray) where available. PAT, patient. ns, not significant.

Fig. 5.

Fig. 5.. Clinical-molecular comparisons.

(A) Quantification of specific in situ response to TMZ (by pH2AX immunostaining) for each patient in the study as determined by IMD analysis. Each point represents a measurement from a distinct tumor region comprising 800 mm by 400 mm exposed to the drug. Error bars display means and SD. Comparisons use a repeated-measures ANOVA test with P values shown per each comparison (in parentheses). **P < 0.01; ns, not significant. (B) Survival data for each patient in the study, including the type and timing of adjuvant therapy administered. Specific patients are color-coded to better visualize the alignment among radiologic data, IMD response, and survival. (C) Time-course MRIs of three representative patients who received systemic therapy after surgery and IMD analysis.

Fig. 6.

Fig. 6.. Personalized tumor responses to different drugs.

Comparison of tumor response to several agents by DNA damage (pH2AX). Values are expressed as a normalized marker index for all cells in drug-exposed tumor regions. Each dot on the graph represents a unique biological replicate measurement from a tumor region within the area of the tumor exposed to the listed drug, for a given patient. Mean and SE are shown. Patient 5 (cyan) and patient 6 (magenta) are highlighted. Comparisons use a one-way ANOVA test, with P values shown for each comparison between patients 5 and 6. *P < 0.05; **P < 0.01.

Fig. 7.

Fig. 7.. In situ phenotyping of targeted drug responses in patient 2.

(A) Biomarker discovery using metabolomics: MALDI images of metabolite changes in tumor in response to lapatinib exposure. (i) Tumor cross section shows three elevated metabolite concentrations in region of drug exposure. (ii) Glutathione concentrations are increased at lapatinib drug reservoir release zone. (iii) Lapatinib distribution measured by autofluorescence shows spatial overlap with elevated metabolite concentrations. Scale bar, 500 μm. (B) Volcano plots of spatial transcriptomics and pathway analysis from tumor specimens exposed to each targeted therapy. On-target, drug-specific effects are confirmed for four targeted agents used on IMD. The most down-regulated (blue) and up-regulated (red) pathways are shown for each drug. Control is tumor tissue adjacent to the microdevice but not exposed to any drugs. P values were generated from unpaired t tests based on four distinct regions of interest per condition. GPCR, G protein–coupled receptor; MAPK, mitogen-activated protein kinase.

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