Improvement of patient care using cancer genomic profiling: SCRUM-/CIRCULATE-Japan experience.
Atsushi OhtsuKoichi GotoTakayuki YoshinoPublished in: Proceedings of the Japan Academy. Series B, Physical and biological sciences (2023)
Cancer comprehensive genomic profiling (CGP) is a fundamental tool for promoting precision oncology in advanced solid tumors. In 2015, we launched the SCRUM-Japan platform for CGP test screening followed by enrollment in genomically-matched clinical trials. More than 30,000 tissue-based and 10,000 liquid-based CGP tests have already been performed for enrollment in a total of 127 industry-/investigator-initiated registration trials. So far, 12 new agents with 14 indications have achieved regulatory approval for health care coverage in Japan. Using the clinical-genomic database of this project, a new driver gene was recently discovered with a dramatic response to a genomically-matched agent. Liquid biopsies are a potentially powerful tool for establishing precision oncology. Our comparative study with tissue-based CGPs revealed the utility of liquid biopsy in terms of being less invasive, shorter turn-round time, and higher enrollment rate for genotype-matched treatment than tissue-based CGP in gastrointestinal cancers. Another major multilayer multi-omics study (MONSTAR-SCREEN-2) including whole exome/transcriptome tissue- and liquid-based analyses and multiplex immunohistochemistry, with artificial intelligence/machine learning was launched in 2020 for the purpose of novel biomarker and new oncology agent discovery/development in collaboration with 18 pharmaceutical companies.For detecting minimal/molecular residual disease (MRD) after surgery, post-surgical monitoring with tumor-informed liquid biopsy assays in association with two randomized controlled trials also started in 2020 (CIRCULATE-Japan). More than 5,000 patients have already been enrolled and the observational cohort study showed the clear utility of MRD monitoring for predicting recurrence, leading to changes in clinical practice in patient selection regarding who should receive adjuvant therapy in the near future.
Keyphrases
- artificial intelligence
- machine learning
- single cell
- high throughput
- copy number
- ionic liquid
- healthcare
- clinical trial
- palliative care
- papillary thyroid
- affordable care act
- big data
- clinical practice
- health insurance
- randomized controlled trial
- genome wide
- deep learning
- ultrasound guided
- end stage renal disease
- squamous cell
- rna seq
- systematic review
- small molecule
- ejection fraction
- gene expression
- young adults
- transcription factor
- squamous cell carcinoma
- study protocol
- childhood cancer
- emergency department
- adverse drug
- current status
- open label
- case report