Tutt, Andrew

Importance Molecular analyses of biospecimens collected from study participants are essential for identifying biomarkers that can tailor treatments to specific subsets of patients who are most likely to benefit. Sharing of data and biospecimens from clinical trials enables personalized, patient-centric use of cancer therapies and accelerates the development of new treatments. Objective To describe obstacles to sharing data and biospecimens and to propose strategies to enhance access and collaboration. Evidence Review This is a Special Communication authored by 53 academic investigators and patient representatives from the breast cancer community with extensive experience in conducting clinical and translational research. The article also evaluates the impact of biomarker research on specifying responsive subpopulations in the 29 registrational clinical trials that have led to approval of a new drug for treatment of breast cancer between 2017 and 2024. Findings Clinical trial participants are increasingly asked to provide tissue and/or body fluid biospecimens for biomarker research that is typically controlled by the sponsoring pharmaceutical company, but published biomarker studies are rare. Among 29 breast cancer registrational studies reported in the past 8 years, none resulted in biomarker research that restricted a drug’s approved indication. Herein, strategies to maximize the value of clinical data and biospecimens contributed by participants are proposed, thereby supporting the shared goals of the pharmaceutical industry and academia to improve patient care. These strategies include (1) establishing coleadership structures involving academia and patients in clinical trial design and conduct, (2) ensuring that informed consent forms state that data and biospecimens will be shared with academia for future research, (3) requiring the sharing of clinical data as a condition for regulatory approval, and (4) enabling access to biospecimens and translational research data for independent studies on biomarkers that may indicate drug efficacy and toxicity. Conclusions and Relevance Data and biospecimen sharing from registrational trials has been suboptimal. Improving clinical data, biospecimens, and biospecimens’ related data sharing requires concrete actions and a multidimensional stakeholder approach to accelerate the impact of clinical cancer research on the quality of patient care.

10586 Background: Teschendorff et al. (Breast Cancer Res 2008) reported a 7-gene, immune response-enriched gene expression classifier using microarrays that was prognostic in women with ER-negative breast cancer. To facilitate further evaluation of the prognostic value of a classifier in archival fixed tumor tissue, we developed two multiplex TaqMan assays to quantify the expression levels of these genes, then trained and validated a 7-gene immune response score (IRS). Methods: RNA was extracted from FFPE sections of 185 ER-negative breast cancer patient samples from Mayo Clinic (n=81), Guy’s Hospital (n=50) and California Pacific Medical Center (CPMC) (n=27). Patients (N+ and N-) did not receive adjuvant therapy and were followed for a minimum of 5 years. Amplification of i) LY9, TNFRSF17, HLA-F, and IGLC2 and ii) XCL2, SPP1, C1QA and two reference genes NUP214 and PPIG were carried out in two multiplex RT-PCR TaqMan reactions and relative expression levels were determined using the DDCT method. The training set, comprised of the Mayo Clinic samples, was used to develop an IRS by using a summation of expression levels of the 7 genes. Association of the IRS with distant metastasis was assessed using a Cox proportional hazards model. The score was subsequently tested in a validation set (Guy’s + CPMC). Results: The amplification efficiency of each gene within the multiplex reactions was comparable to singleplex reactions. Duplicate amplifications showed excellent assay reproducibility and sensitivity (R2=0.98). The hazard ratio for a single standard deviation decrease in the IRS was 1.45 (95% CI 0.99-2.12, p=0.056) in the training set and 2.18 (1.32-3.61, p=0.002) in the validation set. ROC curves of continuous IRS to predict distant metastasis within 5 years had AUC of 0.74, 95% CI = 0.60-0.88. Conclusions: Robust multiplex TaqMan assays for FFPE tissue extracted RNA were developed for a 7-gene IRS. Increases in risk are associated with decreases in the IRS. Immune related gene expression clearly plays an important role in the spectrum of risk of ER-negative tumors. Additional signatures are in development that further support this conclusion.