Orphan noncoding RNA (oncRNA) liquid biopsy assay is prognostic for survival in patients with triple-negative breast cancer (TNBC) and residual disease

Rachel Yoder¹, Jennifer Yen², Mehran Karimzadeh², Joshua M. Staley¹, India Fernandez³, Adam Heinrich³, Fereydoun Hormozdiari², Jeffrey Gregg², Andrew K. Godwin⁴, Irene Acerbi², Raaj Trivedi², Babak Alipanahi², Shane R. Stecklein⁴, Priyanka Sharma³

¹The University of Kansas Cancer Center, Westwood, KS; ²Exai Bio, Inc., Palo Alto, CA; ³University of Kansas Medical Center, Westwood, KS; ⁴University of Kansas Medical Center, Kansas City, KS

Background

Residual disease (RD) after neoadjuvant chemotherapy (NACT) is associated with high risk of recurrence in TNBC.¹
oncRNAs are a novel category of small RNAs that are largely absent in healthy tissue but enriched in tumors and can be detected using a blood-based assay.
An oncRNA-based artificial intelligence tumor-naïve blood assay has been developed to predict risk of recurrence in TNBC patients with RD.²

Aim

Investigate impact of an oncRNA recurrence risk model on outcomes in TNBC patients with RD.

Methods

Study population included stage I-III TNBC (ER/PR <10% and HER2-negative) patients with RD and available end-of-treatment (EOT) serum samples who were enrolled in an IRB-approved multisite prospective cohort study (P.R.O.G.E.C.T., NCT02302742).
EOT samples were collected 14-180 days after completion of all curative treatment (local/systemic).
Small RNAs isolated from EOT serum were sequenced at average depth of 76.5 ±12.5 million 50bp single-end reads and annotated using a bioinformatics pipeline to identify oncRNAs.
Cancer risk scores were generated using an oncRNA-based tumor detection model trained on 451 treatment-naïve breast cancer samples and 470 samples from individuals without known cancer diagnosis.
Study cohort was divided into training and testing sets of equal size. Score cutpoint for high vs low recurrence risk was determined in the testing set through ROC analysis.
Impact of EOT oncRNA risk category on event-free survival (EFS) and overall survival (OS) was estimated by Kaplan-Meier method and compared between groups by log-rank test, followed by Cox regression modeling.
Residual cancer burden (RCB) was determined according to the classification by Symmans et al.³

Results

oncRNA isolation/score generation was successful for 79 out of 80 TNBC patients with RD and available EOT serum sample. RCB class distribution was: RCB I=27%, RCB II=49%, RCB III=18%. Median age was 48 years and 39% had node-positive disease.
Training and testing sets were balanced for clinico-pathologic characteristics, treatment, and pathologic response. Training set (n=39) was used to define oncRNA recurrence risk score cutpoint, which was applied to the testing set (n=40).
38% (15/40) of patients in the testing set were classified as oncRNA high-risk. oncRNA high-risk status was associated with higher T stage (p=0.018) (Table 1). Rates of oncRNA high-risk status in RCB I, II, and III groups were 25%, 41%, and 57%, respectively.
In the testing set, at a median follow-up of 29 months, oncRNA high-risk status was associated with lower EFS and OS (Figure 1, Table 2).
In multivariable analysis including oncRNA risk status, T stage, nodal status, and RCB class, oncRNA high risk status and RCB class retained significant association with EFS (HR 7.70, 95% CI 1.33-44.64, p=0.023 and HR 40.33, 95% CI 2.67-608.99, p=0.008, respectively) and OS (HR 7.99, 95% CI 1.36-47.00, p=0.022 and HR 28.59, 95% CI 2.47-601.93, p=0.009, respectively).
Among patients with RCB classes I-II, oncRNA low-risk status was associated with better outcomes: 3y EFS 94% vs 66% (HR 6.31, 95% CI 0.65-60.88, p=0.068) and 3y OS 93% vs 76% (HR 7.30, 95% CI 0.75-70.81, p=0.045) for low vs high risk, respectively (Figure 2). Patients with RCB III had suboptimal outcomes regardless of oncRNA levels (7/7 of patients with RCB III in the testing cohort had an EFS event).

Table 1. Characteristics of patients in the testing set

(a) RCB class not available for n=3 patients

Table 2. Univariable analysis

P-values in red denote inclusion of the variable in multivariable model.

Figure 1: Survival by oncRNA risk group in all patients

Figure 2: Survival by oncRNA risk group in patients with RCB I-II

Conclusions

A novel tumor-naïve liquid biopsy assay, employing breast cancer-specific oncRNAs, effectively predicted recurrence risk in end-of-treatment samples from triple-negative breast cancer patients with residual disease.
oncRNA risk stratification has the potential to provide prognostic utility complementary to clinicopathologic characteristics in patients with TNBC.
In patients with RCB I-II, oncRNA risk stratification provided further prognostic utility, as patients with oncRNA low-risk status had excellent outcomes (3y EFS/OS >93%). These patients could potentially be spared further adjuvant therapy intensification.
If confirmed in other TNBC studies, these findings may provide insights for patient stratification/selection in RD adjuvant therapy intensification trials. Efforts are underway to evaluate oncRNA risk stratification in other breast cancer cohorts.

This presentation is the intellectual property of the author/presenter. Contact ryoder@kumc.edu for permission to reprint and/or distribute.

Funding:

The University of Kansas Cancer Center (KUCC), Cancer Center Support Grant to KUCC (P30 CA168524, Biospecimen Repository Core Facility).

References:

Liedtke et al, J Clin Oncol 2008.
Tbeileh et al, SABCS 2023.
Symmans et al, J Clin Oncol 2007.