BASECAMP-1: An approach to improve patient screening efficiency and to provide large datasets for precision medicine clinical trials.

K Kristen Renee Spencer (Laura & Isaac Perlmutter Cancer Center at NYU Langone Health, New York, NY) M Matthew Ulrickson (28Banner MD Anderson Cancer Center, Gilbert, AZ) P Patrick Grierson (Washington University School of Medicine, Division of Medical Oncology, St. Louis, MO) S Sandip Pravin Patel J Jennifer M. Specht (University of Washington, Seattle, WA) J Jong Chul Park H Hemant S. Murthy (Mayo Clinic Florida, Jacksonville, FL) D Diane M. Simeone M Maria Pia Morelli (Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX) D David G. Maloney (Fred Hutchinson Cancer Center, Seattle, Washington, United States) M Marcela Valderrama Maus (Massachusetts General Hospital, Boston, MA) W Wen-Kai Weng (10Department of Medicine, Stanford University, Stanford, CA) C Cathy Eng (Vanderbilt-Ingram Cancer Center, Nashville) K Kai He B Brittany Waschke (A2 Biotherapeutics, Inc., Agoura Hills, CA) E Eric Wai-Choi Ng (A2 Biotherapeutics, Inc., Agoura Hills, CA) J Jessica Tebbets (A2 Biotherapeutics, Inc., Agoura Hills, CA) K Kedar Kirtane J Joel R. Hecht (David Geffen School of Medicine at University of California, Los Angeles, Los Angeles, CA) J Julian R. Molina (Mayo Clinic Rochester, Rochester, MN)

Abstract

e23020 Background: Precision medicine studies must overcome the challenges of identifying patients with uncommon molecular targets and small cohort sizes for correlative studies. BASECAMP-1 (NCT04981119) is a prescreening study that uses a single assay to address both problems by: 1) efficiently screening potentially eligible patients for subsequent clinical trials of Tmod logic-gated chimeric antigen receptor T-cell (CAR T) therapies; and 2) providing a large dataset available for translational studies. Methods: Initially, patients were identified for BASECAMP-1 by consenting and genotyping all potentially eligible patients for human leukocyte antigen (HLA)-A*02 heterozygosity. To improve screening efficiency, we co-developed a patient-matching program with Tempus AI, Inc (Tempus), in which Tempus informs the principal investigators of next-generation sequenced (NGS) patients with HLA-A*02 heterozygosity within their health system who may be eligible for BASECAMP-1. Patients are screened using the Tempus xT platform, which uses genomic and RNA sequencing (RNAseq) analyses to determine gene mutations and expression. Enrolled patients with colorectal (CRC), non-small cell lung, ovarian (OVCA), and pancreatic cancers (PANC) were analyzed for tumor purity, mutation distribution, HLA-A*02 loss of heterozygosity (LOH) status, and RNAseq to validate the data available for future clinical analyses. Results: As of January 3, 2025, 80 participants have been enrolled in BASECAMP-1. Through individual screening methods, 1684 patients were screened at 13 study sites, of which 30 patients had tumor-specific HLA-A*02 LOH and were enrolled (~1 eligible patient identified per 56 screened). The patient-matching program identified 282 patients with HLA-A*02 LOH at 12 sites; of these, 50 consented to the BASECAMP-1 study (~1 patient enrolled per 6 identified), demonstrating higher efficiency than the individual patient screening method. Correlative data from xT were available for 360 patients with germline HLA-A*02 and provided insights into mutational distribution and target expression. LOH status was not associated with tumor-specific differences in missense mutational distribution. RNAseq data demonstrated higher CEACAM5 expression in CRC and higher MSLN in PANC and OVCA vs other tumor types, while EGFR was consistently expressed with reduced variance across tumor types, confirming these as potential target antigens for Tmod CAR T interventional trials EVEREST-1, EVEREST-2, and DENALI-1. Conclusions: Identification and enrollment of HLA-A*02 LOH patients into BASECAMP-1 for logic-gated CAR T therapeutic studies were accelerated by the patient matching program. Concurrent xT analysis provides opportunities to augment analyses from robust propensity-matched comparisons, response correlation studies, and other translational discovery. Clinical trial information: NCT04981119 .

Article Details

Volume / Issue Vol. 43, Issue 16_suppl
Published June 01, 2025
ISSN 0732-183X
Publisher Lippincott Williams & Wilkins

Journal Info

Journal of Clinical Oncology

Lippincott Williams & Wilkins

ISSN: 0732-183X Health Sciences

Authors (20)

K

Kristen Renee Spencer

Laura & Isaac Perlmutter Cancer Center at NYU Langone Health, New York, NY

M

Matthew Ulrickson

28Banner MD Anderson Cancer Center, Gilbert, AZ

P

Patrick Grierson

Washington University School of Medicine, Division of Medical Oncology, St. Louis, MO

S

Sandip Pravin Patel

J

Jennifer M. Specht

University of Washington, Seattle, WA

J

Jong Chul Park

H

Hemant S. Murthy

Mayo Clinic Florida, Jacksonville, FL

D

Diane M. Simeone

M

Maria Pia Morelli

Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX

D

David G. Maloney

Fred Hutchinson Cancer Center, Seattle, Washington, United States

M

Marcela Valderrama Maus

Massachusetts General Hospital, Boston, MA

W

Wen-Kai Weng

10Department of Medicine, Stanford University, Stanford, CA

C

Cathy Eng

Vanderbilt-Ingram Cancer Center, Nashville

K

Kai He

B

Brittany Waschke

A2 Biotherapeutics, Inc., Agoura Hills, CA

E

Eric Wai-Choi Ng

A2 Biotherapeutics, Inc., Agoura Hills, CA

J

Jessica Tebbets

A2 Biotherapeutics, Inc., Agoura Hills, CA

K

Kedar Kirtane

J

Joel R. Hecht

David Geffen School of Medicine at University of California, Los Angeles, Los Angeles, CA

J

Julian R. Molina

Mayo Clinic Rochester, Rochester, MN