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Patient-derived micro-organospheres enable clinical precision oncology.

ABSTRACT: Patient-derived xenografts (PDXs) and patient-derived organoids (PDOs) have been shown to model clinical response to cancer therapy. However, it remains challenging to use these models to guide timely clinical decisions for cancer patients. Here, we used droplet emulsion microfluidics with temperature control and dead-volume minimization to rapidly generate thousands of micro-organospheres (MOSs) from low-volume patient tissues, which serve as an ideal patient-derived model for clinical precision oncology. A clinical study of recently diagnosed metastatic colorectal cancer (CRC) patients using an MOS-based precision oncology pipeline reliably assessed tumor drug response within 14 days, a timeline suitable for guiding treatment decisions in the clinic. Furthermore, MOSs capture original stromal cells and allow T cell penetration, providing a clinical assay for testing immuno-oncology (IO) therapies such as PD-1 blockade, bispecific antibodies, and T cell therapies on patient tumors.

SUBMITTER: Ding S

PROVIDER: S-EPMC9177814 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Patient-derived micro-organospheres enable clinical precision oncology.

Ding Shengli S Hsu Carolyn C Wang Zhaohui Z Natesh Naveen R NR Millen Rosemary R Negrete Marcos M Giroux Nicholas N Rivera Grecia O GO Dohlman Anders A Bose Shree S Rotstein Tomer T Spiller Kassandra K Yeung Athena A Sun Zhiguo Z Jiang Chongming C Xi Rui R Wilkin Benjamin B Randon Peggy M PM Williamson Ian I Nelson Daniel A DA Delubac Daniel D Oh Sehwa S Rupprecht Gabrielle G Isaacs James J Jia Jingquan J Chen Chao C Shen John Paul JP Kopetz Scott S McCall Shannon S Smith Amber A Gjorevski Nikolche N Walz Antje-Christine AC Antonia Scott S Marrer-Berger Estelle E Clevers Hans H Hsu David D Shen Xiling X

Cell stem cell 20220503 6

Patient-derived xenografts (PDXs) and patient-derived organoids (PDOs) have been shown to model clinical response to cancer therapy. However, it remains challenging to use these models to guide timely clinical decisions for cancer patients. Here, we used droplet emulsion microfluidics with temperature control and dead-volume minimization to rapidly generate thousands of micro-organospheres (MOSs) from low-volume patient tissues, which serve as an ideal patient-derived model for clinical precisio ...[more]

PMID: 35508177

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Project description:PURPOSE:Precision oncology is hindered by the lack of decision support for determining the functional and therapeutic significance of genomic alterations in tumors and relevant clinically available options. To bridge this knowledge gap, we established a Precision Oncology Decision Support (PODS) team that provides annotations at the alteration-level and subsequently determined if clinical decision-making was influenced. METHODS:Genomic alterations were annotated to determine actionability based on a variant's known or potential functional and/or therapeutic significance. The medical records of a subset of patients annotated in 2015 were manually reviewed to assess trial enrollment. A web-based survey was implemented to capture the reasons why genotype-matched therapies were not pursued. RESULTS:PODS processed 1,669 requests for annotation of 4,084 alterations (2,254 unique) across 49 tumor types for 1,197 patients. 2,444 annotations for 669 patients included an actionable variant call: 32.5% actionable, 9.4% potentially, 29.7% unknown, 28.4% non-actionable. 66% of patients had at least one actionable/potentially actionable alteration. 20.6% (110/535) patients annotated enrolled on a genotype-matched trial. Trial enrolment was significantly higher for patients with actionable/potentially actionable alterations (92/333, 27.6%) than those with unknown (16/136, 11.8%) and non-actionable (2/66, 3%) alterations (p=0.00004). Actionable alterations in PTEN, PIK3CA, and ERBB2 most frequently led to enrollment on genotype-matched trials. Clinicians cited a variety of reasons why patients with actionable alterations did not enroll on trials. CONCLUSION:Over half of alterations annotated were of unknown significance or non-actionable. Physicians were more likely to enroll a patient on a genotype-matched trial when an annotation supported actionability. Future studies are needed to demonstrate the impact of decision support on trial enrollment and oncologic outcomes.

Dataset Information

Patient-derived micro-organospheres enable clinical precision oncology.

Publications

Patient-derived micro-organospheres enable clinical precision oncology.

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