Caris Life Sciences and ECOG-ACRIN Partner to Enhance Breast Cancer Research Using AI
核心洞察
Caris Life Sciences (搜索) and ECOG-ACRIN (搜索) are collaborating to analyze data from the TAILORx breast cancer (搜索) trial using advanced AI and molecular profiling.
The project aims to identify biomarkers for recurrence risk, predict outcomes, and understand racial disparities in early-stage breast cancer (搜索) patients.
Caris will perform comprehensive molecular characterization on tumor tissues from nearly 10,000 TAILORx trial participants with long-term follow-up.
Caris Life Sciences (搜索) and ECOG-ACRIN (搜索) Cancer Research Group have initiated a multi-year research collaboration to further investigate early-stage breast cancer (搜索) using advanced artificial intelligence (AI) and comprehensive molecular profiling. The collaboration will leverage tumor tissue samples from the landmark Trial Assigning Individualized Options for Treatment (TAILORx) breast cancer clinical trial.
Utilizing AI to Interrogate TAILORx Data
Caris Life Sciences (搜索) will apply its genomic, transcriptomic, and proteomic profiling capabilities, coupled with advanced AI and machine learning algorithms, to analyze samples from the TAILORx trial. This trial, one of the largest breast cancer (搜索) research resources, was designed and led by ECOG-ACRIN (搜索) with support from the National Cancer Institute (NCI).
"Given the innovative capabilities offered by Caris, analysis of TAILORx biospecimens with cutting-edge AI approaches provides a great opportunity to discover superior biomarkers for risk stratification, prediction of recurrence and better understanding of racial disparities," said Mitchell D. Schnall, MD, PhD, group co-chair of ECOG-ARIN.
Focus on Early-Stage Breast Cancer and Recurrence Risk
The TAILORx project will focus on early-stage breast cancer (搜索), where the risk of recurrence remains a significant concern. According to the American Cancer Society, approximately 310,720 new cases of breast cancer are diagnosed annually in the United States, with about 60% being early-stage cases. While breast cancer deaths have declined by 42% over the past 30 years, a mortality gap persists between minority and white patients. A prior TAILORx analysis in JAMA Surgery highlighted racial and ethnic differences in locoregional breast cancer recurrence patterns, even within a clinical trial setting with similar access to care.
Comprehensive Molecular Characterization and Long-Term Follow-Up
As part of the project, Caris will perform whole exome and transcriptome sequencing on tumor tissues from nearly 10,000 patients with early-stage breast cancer (搜索) who participated in the TAILORx trial. These participants have been followed for 11 years or more, with planned follow-up extending to 20 years. The resulting data will be integrated with Caris' AI and machine learning algorithms. After a designated period, the data will be made publicly available in an appropriate NCI database.
ECOG-ACRIN Joins Caris Precision Oncology Alliance
In addition to the research collaboration, ECOG-ACRIN (搜索) has joined the Caris Precision Oncology Alliance (POA), a global network of cancer centers and research consortia. This alliance aims to advance precision oncology and biomarker-driven research, working collaboratively to establish and optimize standards of care for molecular testing to improve clinical outcomes for cancer patients.
"Our collaboration with Caris has deep roots, aligned interests, and a commitment to develop the best science in the service of early detection and treatment of cancer," said Peter J. O’Dwyer, MD, group co-chair of ECOG-ACRIN (搜索). "The promise of the joint effort is to provide broad availability of cutting-edge options for cancer patients in their communities."
The TAILORx trial previously demonstrated that chemotherapy could be avoided in certain patients with estrogen receptor-positive (ER (搜索)+), human epidermal growth factor receptor 2-negative (HER2 (搜索)-) early-stage breast cancer (搜索) with low recurrence scores (0-25) on the Oncotype DX Breast Recurrence Score test. The current collaboration seeks to build upon these findings by identifying additional biomarkers for risk stratification and prediction of recurrence.