Clinical trial · Observational
Liquid Biopsy-informed Precision Oncology Study to Evaluate Utility of Plasma Genomic Profiling for Therapy Selection
Liquid Biopsy-informed Precision Oncology Study to Evaluate the Clinical Utility of Non-invasive Comprehensive Genomic Profiling for Cancer Treatment Selection
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
Overall, this project has three main goals: first, to ascertain the feasibility of the approach and identify whether liquid biopsies can detect actionable mutations that can be utilized to generate precision oncology treatment recommendations. Second, the investigators will investigate whether enacting upon MTB recommendations would improve outcomes in terms of progression-free and overall survival. Third, the investigators aim to determine if molecular profiling via serial plasma tests after initiation of chemotherapy or other targeted treatment is sufficient to determine whether or not a patient is responding to therapy.
Conditions
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Solid Tumor | Solid Neoplasm | CURATED_BROADER | 0.80 |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| Non-invasive Comprehensive Genomic Profiling for Cancer Treatment Selection | Other | — | UNRESOLVED |
Design
Arms and outcomes
Arms (1)
- label
- Oncology Patients
- description
- All participants in the study.
- interventionNames
- Other: Non-invasive Comprehensive Genomic Profiling for Cancer Treatment Selection
Primary outcomes (5)
- measure
- Prevalence of variants in ctDNA with clinical significance across different levels of evidence
- timeFrame
- Up to 2 years after enrollment
- description
- To determine the prevalence of variants in ctDNA with clinical significance across different levels of evidence (stratified by gene and alteration type). In cases where tumor next-generation sequencing has been performed, tumor mutational profiles will be evaluated in conjunction with the liquid biopsy results.
- measure
- Percentage of patients with a molecular tumor board (MTB) treatment recommendation
- timeFrame
- Up to 2 years after enrollment
- description
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
Show eligibility criteria text
Inclusion Criteria: * ECOG performance status of 0-1. * Patients with solid tumors, including esophageal cancer, non-adenocarcinoma NSCLC, small-cell lung cancer, head \& neck cancer, mesothelioma, breast cancer and lung neuroendocrine cancer. * Patients who can provide whole blood collection to meet minimum of 20-30ml of blood at baseline, within 1-3 weeks from treatment initiation, at first radiographic imaging and at progression. Acquisition of an archival or time-matched tumor tissue specimen which meets the minimum sample input requirements (at least 20% tumor content and 100 ng) is preferred but not required. * Patients with metastatic disease will have progressed on the most recent treatment prior to enrollment. Patient can also be enrolled if their oncologist believes progression is imminent and test results would be used to inform next line of therapy. Patients considered for first-line SOC therapeutic options may be enrolled if the clinical efficacy of these therapies is not encouraging. * Patients must have disease evaluable for progression assessment; measurable disease is not required to participate in the study. * Able to voluntarily provide informed consent. Exclusion Criteria: * Women who are known to be pregnant * History of another primary malignancy in the last 5 years prior to registration unless approved by the Protocol Chair/designee. Patients with prior history of in situ cancer or basal or localized squamous cell skin cancer are eligible.
References
Publications (1)
- DERIVEDCanzoniero JV, Rabizadeh D, Ziakas I, Wehr J, Balan A, Jamali A, Landon BV, Sivapalan L, Scott S, Pereira G, Lam VK, Hann CL, Lovly CM, Tao J, Forde PM, Murray JC, Sausen M, Meijer GA, Vink GR, Fijneman RJA; MEDOCC Group; Velculescu VE, Phallen J, Scharpf RB, Anagnostou V. plasmaCHORD: A Machine Learning Approach to Distinguish Clonal Hematopoiesis-Derived Variants in Liquid Biopsies from Patients with Solid Tumors. Clin Cancer Res. 2026 May 1;32(9):1729-1744. doi: 10.1158/1078-0432.CCR-25-0976. PMID 42001480