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Cotler MJ, Ramadi KB, Hou X, Christodoulopoulos E, Ahn S, Bashyam A, Ding H, Larson M, Oberg AL, Whittaker C, Jonas O, Kaufmann SH, Weroha SJ, Cima MJ. Machine-learning aided in situ drug sensitivity screening predicts treatment outcomes in ovarian PDX tumors. Transl Oncol 2022; 21:101427. [PMID: 35472731 PMCID: PMC9136609 DOI: 10.1016/j.tranon.2022.101427] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 02/28/2022] [Accepted: 04/10/2022] [Indexed: 12/14/2022] Open
Abstract
Long-term treatment outcomes for patients with high grade ovarian cancers have not changed despite innovations in therapies. There is no recommended assay for predicting patient response to second-line therapy, thus clinicians must make treatment decisions based on each individual patient. Patient-derived xenograft (PDX) tumors have been shown to predict drug sensitivity in ovarian cancer patients, but the time frame for intraperitoneal (IP) tumor generation, expansion, and drug screening is beyond that for tumor recurrence and platinum resistance to occur, thus results do not have clinical utility. We describe a drug sensitivity screening assay using a drug delivery microdevice implanted for 24 h in subcutaneous (SQ) ovarian PDX tumors to predict treatment outcomes in matched IP PDX tumors in a clinically relevant time frame. The SQ tumor response to local microdose drug exposure was found to be predictive of the growth of matched IP tumors after multi-week systemic therapy using significantly fewer animals (10 SQ vs 206 IP). Multiplexed immunofluorescence image analysis of phenotypic tumor response combined with a machine learning classifier could predict IP treatment outcomes against three second-line cytotoxic therapies with an average AUC of 0.91.
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Affiliation(s)
- Max J. Cotler
- The David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA,Harvard-MIT Program in Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Khalil B. Ramadi
- The David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA,Harvard-MIT Program in Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Xiaonan Hou
- Department of Oncology, Mayo Clinic, Rochester, MN 55905, USA
| | - Elena Christodoulopoulos
- The David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Sebastian Ahn
- Department of Radiology, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Ashvin Bashyam
- The David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA,Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Huiming Ding
- The David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Melissa Larson
- Division of Computational Biology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | - Ann L. Oberg
- Division of Computational Biology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | - Charles Whittaker
- The David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Oliver Jonas
- The David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA,Department of Radiology, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Scott H. Kaufmann
- Department of Oncology, Mayo Clinic, Rochester, MN 55905, USA,Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN 55905, USA
| | - S. John Weroha
- Department of Oncology, Mayo Clinic, Rochester, MN 55905, USA,Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN 55905, USA
| | - Michael J. Cima
- The David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA,Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA,Corresponding author at: The David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
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Raman R, Rousseau EB, Wade M, Tong A, Cotler MJ, Kuang J, Lugo AA, Zhang E, Graybiel AM, White FM, Langer R, Cima MJ. Platform for micro-invasive membrane-free biochemical sampling of brain interstitial fluid. Sci Adv 2020; 6:eabb0657. [PMID: 32978160 PMCID: PMC7518871 DOI: 10.1126/sciadv.abb0657] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Accepted: 08/11/2020] [Indexed: 05/11/2023]
Abstract
Neurochemical dysregulation underlies many pathologies and can be monitored by measuring the composition of brain interstitial fluid (ISF). Existing in vivo tools for sampling ISF do not enable measuring large rare molecules, such as proteins and neuropeptides, and thus cannot generate a complete picture of the neurochemical connectome. Our micro-invasive platform, composed of a nanofluidic pump coupled to a membrane-free probe, enables sampling multiple neural biomarkers in parallel. This platform outperforms the state of the art in low-flow pumps by offering low volume control (single stroke volumes, <3 nl) and bidirectional fluid flow (<100 nl/min) with negligible dead volume (<30 nl) and has been validated in vitro, ex vivo, and in vivo in rodents. ISF samples (<1.5 μL) can be processed via liquid chromatography-tandem mass spectrometry. These label-free liquid biopsies of the brain could yield a deeper understanding of the onset, mechanism, and progression of diverse neural pathologies.
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Affiliation(s)
- Ritu Raman
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Erin B Rousseau
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
- Harvard-MIT Program in Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Michael Wade
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Allison Tong
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Max J Cotler
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
- Harvard-MIT Program in Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jenevieve Kuang
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
- Center for Precision Cancer Medicine, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Alejandro Aponte Lugo
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Elizabeth Zhang
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Ann M Graybiel
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Forest M White
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
- Center for Precision Cancer Medicine, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Robert Langer
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Michael J Cima
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
- Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
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Cotler MJ, Rousseau EB, Ramadi KB, Fang J, Graybiel AM, Langer R, Cima MJ. Steerable Microinvasive Probes for Localized Drug Delivery to Deep Tissue. Small 2019; 15:e1901459. [PMID: 31183933 DOI: 10.1002/smll.201901459] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2019] [Revised: 04/25/2019] [Indexed: 06/09/2023]
Abstract
Enhanced understanding of neuropathologies has created a need for more advanced tools. Current neural implants result in extensive glial scarring and are not able to highly localize drug delivery due to their size. Smaller implants reduce surgical trauma and improve spatial resolution, but such a reduction requires improvements in device design to enable accurate and chronic implantation in subcortical structures. Flexible needle steering techniques offer improved control over implant placement, but often require complex closed-loop control for accurate implantation. This study reports the development of steerable microinvasive neural implants (S-MINIs) constructed from borosilicate capillaries (OD = 60 µm, ID = 20 µm) that do not require closed-loop guidance or guide tubes. S-MINIs reduce glial scarring 3.5-fold compared to prior implants. Bevel steered needles are utilized for open-loop targeting of deep-brain structures. This study demonstrates a sinusoidal relationship between implant bevel angle and the trajectory radius of curvature both in vitro and ex vivo. This relationship allows for bevel-tipped capillaries to be steered to a target with an average error of 0.23 mm ± 0.19 without closed-loop control. Polished microcapillaries present a new microinvasive tool for chronic, predictable targeting of pathophysiological structures without the need for closed-loop feedback and complex imaging.
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Affiliation(s)
- Max J Cotler
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA, 02139, USA
- Harvard-MIT Program in Health Sciences and Technology, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA, 02139, USA
| | - Erin B Rousseau
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA, 02139, USA
- Harvard-MIT Program in Health Sciences and Technology, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA, 02139, USA
| | - Khalil B Ramadi
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA, 02139, USA
- Harvard-MIT Program in Health Sciences and Technology, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA, 02139, USA
| | - Joshua Fang
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA, 02139, USA
| | - Ann M Graybiel
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA, 02139, USA
| | - Robert Langer
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA, 02139, USA
- Harvard-MIT Program in Health Sciences and Technology, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA, 02139, USA
- Department of Chemical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA, 02139, USA
| | - Michael J Cima
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA, 02139, USA
- Department of Materials Science and Engineering, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA, 02139, USA
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Kozin ED, Black NL, Cheng JT, Cotler MJ, McKenna MJ, Lee DJ, Lewis JA, Rosowski JJ, Remenschneider AK. Design, fabrication, and in vitro testing of novel three-dimensionally printed tympanic membrane grafts. Hear Res 2016; 340:191-203. [PMID: 26994661 DOI: 10.1016/j.heares.2016.03.005] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2015] [Revised: 03/07/2016] [Accepted: 03/09/2016] [Indexed: 10/22/2022]
Abstract
The tympanic membrane (TM) is an exquisite structure that captures and transmits sound from the environment to the ossicular chain of the middle ear. The creation of TM grafts by multi-material three-dimensional (3D) printing may overcome limitations of current graft materials, e.g. temporalis muscle fascia, used for surgical reconstruction of the TM. TM graft scaffolds with either 8 or 16 circumferential and radial filament arrangements were fabricated by 3D printing of polydimethylsiloxane (PDMS), flex-polyactic acid (PLA) and polycaprolactone (PCL) materials followed by uniform infilling with a fibrin-collagen composite hydrogel. Digital opto-electronic holography (DOEH) and laser Doppler vibrometry (LDV) were used to measure acoustic properties including surface motions and velocity of TM grafts in response to sound. Mechanical properties were determined using dynamic mechanical analysis (DMA). Results were compared to fresh cadaveric human TMs and cadaveric temporalis fascia. Similar to the human TM, TM grafts exhibit simple surface motion patterns at lower frequencies (400 Hz), with a limited number of displacement maxima. At higher frequencies (>1000 Hz), their displacement patterns are highly organized with multiple areas of maximal displacement separated by regions of minimal displacement. By contrast, temporalis fascia exhibited asymmetric and less regular holographic patterns. Velocity across frequency sweeps (0.2-10 kHz) measured by LDV demonstrated consistent results for 3D printed grafts, while velocity for human fascia varied greatly between specimens. TM composite grafts of different scaffold print materials and varied filament count (8 or 16) displayed minimal, but measurable differences in DOEH and LDV at tested frequencies. TM graft mechanical load increased with higher filament count and is resilient over time, which differs from temporalis fascia, which loses over 70% of its load bearing properties during mechanical testing. This study demonstrates the design, fabrication and preliminary in vitro acoustic and mechanical evaluation of 3D printed TM grafts. Data illustrate the feasibility of creating TM grafts with acoustic properties that reflect sound induced motion patterns of the human TM; furthermore, 3D printed grafts have mechanical properties that demonstrate increased resistance to deformation compared to temporalis fascia.
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Affiliation(s)
- Elliott D Kozin
- Department Otolaryngology, Massachusetts Eye and Ear Infirmary, Boston, MA, USA; Eaton Peabody Laboratories, Massachusetts Eye and Ear Infirmary, Boston, MA, USA; Department of Otology and Laryngology, Harvard Medical School, Boston, MA, USA
| | - Nicole L Black
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA; Wyss Institute for Biologically Inspired Engineering, Harvard University, Cambridge, MA, USA
| | - Jeffrey T Cheng
- Department Otolaryngology, Massachusetts Eye and Ear Infirmary, Boston, MA, USA; Eaton Peabody Laboratories, Massachusetts Eye and Ear Infirmary, Boston, MA, USA; Department of Otology and Laryngology, Harvard Medical School, Boston, MA, USA
| | - Max J Cotler
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA; Wyss Institute for Biologically Inspired Engineering, Harvard University, Cambridge, MA, USA
| | - Michael J McKenna
- Department Otolaryngology, Massachusetts Eye and Ear Infirmary, Boston, MA, USA; Eaton Peabody Laboratories, Massachusetts Eye and Ear Infirmary, Boston, MA, USA; Department of Otology and Laryngology, Harvard Medical School, Boston, MA, USA
| | - Daniel J Lee
- Department Otolaryngology, Massachusetts Eye and Ear Infirmary, Boston, MA, USA; Eaton Peabody Laboratories, Massachusetts Eye and Ear Infirmary, Boston, MA, USA; Department of Otology and Laryngology, Harvard Medical School, Boston, MA, USA
| | - Jennifer A Lewis
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA; Wyss Institute for Biologically Inspired Engineering, Harvard University, Cambridge, MA, USA
| | - John J Rosowski
- Department Otolaryngology, Massachusetts Eye and Ear Infirmary, Boston, MA, USA; Eaton Peabody Laboratories, Massachusetts Eye and Ear Infirmary, Boston, MA, USA; Department of Otology and Laryngology, Harvard Medical School, Boston, MA, USA
| | - Aaron K Remenschneider
- Department Otolaryngology, Massachusetts Eye and Ear Infirmary, Boston, MA, USA; Eaton Peabody Laboratories, Massachusetts Eye and Ear Infirmary, Boston, MA, USA; Department of Otology and Laryngology, Harvard Medical School, Boston, MA, USA.
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