Observational Basket Trial to Collect Tissue to Develop and Train a Live Tumor Diagnostic Platform
The primary objective of this study is to develop and train the Elephas live tumor diagnostic platform and determine the ex-vivo accuracy of the Elephas Score using in-vivo RECIST 1.1 as the reference method
Inclusion Criteria
- Inclusion Criteria -- 1. Written informed consent and HIPAA authorization for release of personal health information prior to registration. NOTE: HIPAA authorization may be included in the informed consent or obtained separately. 2. Age ≥ 18 years at the time of consent. 3. Subjects must meet one of the following criteria: - Subjects suspected or diagnosed with recurrent, locally advanced or metastatic cancer: - Bladder: Urothelial Carcinoma (UC) - Kidney: Clear Cell Renal Cell Carcinoma (ccRCC) - Subjects suspected or diagnosed with recurrent or metastatic cancer: - Colon and Rectum: Microsatellite instability-high (MSI-H)/deficient mismatch repair (dMMR) Colorectal Cancer (CRC) - Head and Neck: Squamous Cell Carcinoma (HNSCC), excluding nasopharyngeal and salivary gland cancers - Liver: Hepatocellular Carcinoma - Lung: Non-small cell lung cancer (NSCLC) - Skin: Cutaneous Melanoma, excluding Uveal Melanoma - Uterus: endometrial cancer - Subjects suspected or diagnosed with one of the following cancer types eligible for pure ICI neoadjuvant therapy: o Skin: Cutaneous Melanoma, Stage III - Subjects suspected or diagnosed with: - Any solid tumor type that is eligible for pure ICI therapy in the neoadjuvant or advanced/metastatic setting - Any metastatic solid tumor with high TMB, MSI-High or dMMR and are being considered for treatment with ICI therapy. - Any recurrent or metastatic patient with a solid tumor that the clinician plans to treat with ICI therapy. 4. Subjects must be clinically able, at investigator discretion, to undergo a biopsy procedure 5. Subjects who are newly diagnosed or have suspected cancer must be treatment-naïve at the time of biopsy. All other subjects should have the biopsy performed before starting their next line of treatment. Exclusion Criteria -- 1. Subjects who are pregnant 2. Subjects with a known auto-immune disease that would render them ineligible for immune-oncology treatment 3. Immunocompromised subjects, and subjects known to be HIV positive and currently receiving antiretroviral therapy 4. Subjects who are enrolled or plan to be enrolled in a blinded oncology treatment trial
Study sponsor and potential other locations can be found on ClinicalTrials.gov for NCT05520099.
Locations matching your search criteria
United States
New York
Buffalo
North Carolina
Chapel Hill
Wisconsin
Madison
Cancer is a leading cause of death and despite many new drugs, a major diagnostic
challenge remains knowing which drug will work best for a patient. A new class of drugs
called checkpoint inhibitors (CPIs) have revolutionized cancer treatment. However,
current diagnostic methods (e.g. PDL1, MSI and TMB) do not accurately predict which
patients will respond.
Elephas is developing a diagnostic platform using small 3D Live Tumor Fragments (LTFs)
from participants for accurate prediction of drug response with a focus on CPIs such as
Pembrolizumab (Keytruda). These LTFs contain both tumor cells and infiltrating immune
cells, which are critical in determining response to CPIs and other immunotherapies.
In this observational clinical basket trial, participants will be recruited and their
actual clinical response (using RECIST 1.1) to CPIs across five solid tumors (lung,
head/neck, bladder, kidney, and skin) will be compared to the platform's predictive
Artificial Intelligence (AI) score that is based on RNA, clinical data, and 3D microscopy
images. The sensitivity and specificity of the platform's score will be determined and
compared to current diagnostic methods for CPIs like PDL1, MSI, and TMB.
Trial PhaseNo phase specified
Trial TypeNot provided by clinicaltrials.gov
Lead OrganizationElephas
Principal InvestigatorJon D. Oliner
- Primary IDELEPHAS-02
- Secondary IDsNCI-2023-10512, HCRN BSK22-562
- ClinicalTrials.gov IDNCT05520099