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March 29, 2026BMJ Oncology0 citationsOpen Access

BASECAMP-1 screening study: a model for efficient enrolment in precision oncology clinical trials

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JHJ Randolph HechtJMJulian R MolinaKLKirstin B. Liechty

Key Points

  • The aim is to identify efficient methods for enrolling eligible patients in precision oncology clinical trials, particularly those with rare molecular characteristics.
  • Developed a master screening study, BASECAMP-1, to identify eligible patients.
  • Used two screening methods: traditional patient consent and screening, and a bioinformatic program called Aware from Tempus AI.
  • Analyzed linked genomic and clinical data to identify patients with specific HLA-A loss.
  • Traditional screening enrolled 30 patients with tumour-associated HLA-A*02 loss over 42 months (~0.7 participants/month).
  • Tempus Aware screening enrolled 55 patients with the same criteria in 30 months (~1.8 participants/month).
  • Bioinformatic screening identified more eligible patients and reduced resource use compared to traditional methods.

Abstract

Objective Identifying eligible patients for precision oncology clinical trials is challenging, particularly for rare molecular subpopulations. To address this challenge, A2 Biotherapeutics developed BASECAMP-1 ( NCT04981119 ), a non-interventional master screening study to identify patients eligible for interventional studies of logic-gated Tmod chimeric antigen receptor T-cell therapies. Eligible patients for these interventional trials have an advanced solid malignancy and are germline human leucocyte antigen (HLA)-A*02 heterozygous, with tumour-associated HLA-A loss of heterozygosity (LOH). HLA-A LOH occurs in ~16% of advanced solid malignancies; therefore, an efficient screening strategy is required. This report describes BASECAMP-1; compares the efficiency of two screening methods; and discusses the broader advantages of BASECAMP-1 beyond efficient enrolment. Methods and analysis Patients are identified for BASECAMP-1 using two approaches. In the traditional approach, common for clinical trials, investigators consent and screen all patients who might be good candidates for cell therapy trials, with no prior knowledge of patient HLA-A type or LOH status. To further optimise our approach, we co-developed with Tempus AI (Tempus) the bioinformatic programme Aware, which identifies potentially eligible patients with tumour-associated HLA-A*02 LOH within a clinico-genomic database that includes linked genomic and transcriptomic sequencing and clinical data collected during routine care. Results Over 42 months of using a traditional approach to identify eligible patients, 1918 patients at 13 study sites were consented and screened for BASECAMP-1; of these, 30 patients with tumour-associated HLA-A*02 LOH were enrolled (~0.7 participants per month). Over the last 30 months of that same period, Tempus Aware screening was implemented and 55 patients with tumour-associated HLA-A*02 LOH were enrolled (~1.8 participants per month). The bioinformatic approach identified more patients than the traditional approach and used sequencing results produced as part of the standard clinical tumour sequencing workflow, reducing resource use and study staff burden. Additional advantages of using a screening study, such as BASECAMP-1, include manufacturing efficiencies and collection of a large dataset of molecular and clinical parameters that can be used to supplement trial analyses. Conclusions The BASECAMP-1 study demonstrates a clinico-genomic screening approach can more efficiently identify patients for precision oncology trials. Furthermore, precision oncology can be enhanced through collaborative data-sharing. Trial registration number NCT04981119 .

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Hecht et al. (2026) studied this question.

synapsesocial.com/papers/69c8c3cede0f0f753b39ed20https://doi.org/10.1136/bmjonc-2025-001033
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