AI Outperforms Traditional Biomarkers in Predicting Breast Cancer Immunotherapy Success
New study in Nature Communications highlights AI's role in transforming immunotherapy decisions and precision oncology
Irving, Texas, August 6, 2025 /PRNewswire/ — Caris Life Sciences® (NASDAQ: CAI), a leading, patient-centric, next-generation AI TechBio company and precision medicine pioneer, has published a new study in the journal Communications Medicine, demonstrating that Caris's AI-based image analysis model has the potential to more accurately predict cancer biomarkers and patient survival than the conventional companion diagnostic (CDx) methods.
By analyzing hematoxylin and eosin (H&E) images, the study demonstrated that Caris's AI model can improve the assessment of critical cancer biomarkers and impact patient survival outcomes in breast and colorectal cancers.
For this study, Caris's AI model analyzed data from over 35,000 patients in the Caris clinico-genomic database.
In breast cancer, the AI model scored PD-L1 positive phenotype status using an H&E image alone and assessed overall survival of patients treated with pembrolizumab, achieving a hazard ratio (HR) for overall survival of 0.511 (p<0.001), compared to an HR of 0.882 (p>0.1) for traditionally scored PD-L1 IHCs, a result consistent with an almost doubling of overall survival for patients treated with pembrolizumab. In colorectal cancer, AI predicted mismatch repair deficiency (MMRd) and microsatellite instability (MSI) equivalent to traditional scoring.
"Traditional PD-L1 testing can undercall positive cases, especially near the 1 percent threshold," said Matthew Oberley, MD, PhD, SVP, chief clinical officer and pathologist-in-chief at Caris. "Caris's AI model enhances predictive accuracy, integrating features from both staining methods, and exhibits superior prognostic precision compared to current biomarker assessments. Clinical adoption of this tool could improve the precision and efficiency of cancer patient evaluation and aid clinical decision making."
"This study highlights how AI can significantly improve the accuracy and efficiency of tissue sample evaluation, and down the line, this has the potential to guide immunotherapy decisions and enhance patient outcomes," said George W. Sledge, Jr., MD, Caris EVP and chief medical officer.
- This press release was originally published by Caris Life Sciences