Burning Rock Presents Latest Clinical Data from THUNDER Study at 2022 ASCO Annual Meeting

Rhea-AI Summary

Burning Rock (NASDAQ:BNR) presented final results from the THUNDER study at the 2022 ASCO Annual Meeting, evaluating their cfDNA methylation-based technology, ELSA-seq, for early cancer detection. The study showed that MCDBT-1 had a sensitivity of 69.1% at 98.9% specificity, while MCDBT-2 demonstrated a sensitivity of 75.1% with 95.1% specificity. The models predict the tissue origin of cancer accurately, achieving 83.2% accuracy in independent validation. The study suggests significant potential for reducing late-stage cancer incidence and improving survival rates, thereby enhancing public health outcomes.

Positive

• MCDBT-2 achieved a sensitivity of 75.1% with 95.1% specificity.
• MCDBT-1 decreased late-stage incidence by 38.7%-46.4%.
• The study indicated a potential increase in the 5-year survival rate by 33.1%-40.4%.
• The results enhance the application prospects for ELSA-seq in early cancer detection.

Negative

• None.

SHANGHAI, June 15, 2022 /PRNewswire/ -- Burning Rock (NASDAQ:BNR) presented the final results from the multi-center case-control THUNDER study (THe UNintrusive Detection of EaRly-stage cancer, NCT04820868) in a poster entitled "Unintrusive multi-cancer detection by circulating cell-free DNA methylation sequencing (THUNDER): development and independent validation studies" at the 2022 American Society of Clinical Oncology (ASCO) Annual Meeting. This is a comprehensive review of clinical performance after the four-year THUNDER study.

Through a rigorous "three-stage" design: marker discovery and panel validation, model training and validation (retrospective), and independent validation (prospective), the THUNDER study evaluated the performance of a previously described cfDNA methylation-based technology ELSA-seq in early detection and localization of six types of cancer in lung, colorectum, liver, esophagus, pancreas, and ovary.

In the study, a customized panel of 161,984 CpG sites was constructed and validated by public and in-house (cancer: n=249; non-cancer: n=288) methylome data, respectively. The study used the cancer-specific methylation regions for cancer detection as it can differentiate cancer signals from non-cancer signals, and identify the source (the tissue of origin) of the detected cancer signal.

In the model training and validation (retrospective) phase, the cfDNA samples from 1,693 participants (cancer: n=735; non-cancer: n=958) were collected and approximately three-quarter of the samples were used to establish two multi-cancer detection blood test (MCDBT-1/2) models with different cut-offs (cancer: n=399; non-cancer: n=626). About a quarter of the samples were used to build a validation set to test the two multi-cancer detection blood test models (cancer: n=301; non-cancer: n=123). In the independent validation ( prospective) phase, both models was blindly validated on a prospectively enrolled, independent validation set(cancer: n=473; non-cancer: n=473) to test the stability of high-dimensional modeling more rigorously.

The study showed that the sensitivity of MCDBT-1 was 69.1% at a specificity of 98.9% in the independent validation set. MCDBT-2 yielded a higher sensitivity (75.1%) and a slightly lower specificity (95.1%) compared to MCDBT-1.

The study also showed that ELSA-seq can accurately trace the tissue of origin (identify where the cancer is located in the body). For MCDBT-1, the accuracy of top prediction origin (TPO) was 89.7% in the training set, 82.8% in the validation set, 83.2% in the independent validation set, respectively. MCDBT-2 model also showed high TPO accuracy, with the TPO accuracy reaching 79.4% in the independent validation cohort.

Finally, an interception model was applied using such indicators as cancer incidence, distribution of cancer stage at diagnosis, five-year survival rate and tumor progression rate in China, to infer stage-shift and survival benefit and to demonstrate potential public health benefit of ELSA-seq in real-world application. Based on the interception model imputation, these two models achieved sensitivities of 70.6% and 77.5% in detecting the six cancers, respectively. MCDBT-1 decreased late-stage incidence by 38.7%-46.4% (shift from stage III-IV towards stage I-II), and increased 5-year survival rate by 33.1%-40.4%.

The THUNDER study has laid a foundation for extending non-invasive cfDNA methylation detection to more types of cancer in future and once again proved the excellent performance and broad application prospects of ELSA-seq in the early detection of multiple cancers. Burning Rock looks forward to collaborating with medical experts to take forward the clinical validation and development of the multi-cancer detection products, thus through detecting more cancers at the early stage to improve the survival rate of cancer patients, and reduce the social and economic burden stemming from cancer.

About Burning Rock

Burning Rock Biotech Limited (NASDAQ: BNR), whose mission is to guard life via science, focuses on the application of next generation sequencing (NGS) technology in the field of precision oncology. Its business consists of 1) NGS-based therapy selection testing for late-stage cancer patients, 2) Global pharmaceutical services on biomarker detection and companion diagnostics developing, and 3) NGS-based cancer early detection, which has moved beyond proof-of-concept R&D into the clinical validation stage.

For more information, please contact PR@brbiotech.com

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SOURCE Burning Rock

FAQ

What were the key findings of the THUNDER study presented by Burning Rock?

The THUNDER study highlighted that MCDBT-1 has a sensitivity of 69.1% at 98.9% specificity, while MCDBT-2 shows 75.1% sensitivity at 95.1% specificity for early cancer detection.

How does the ELSA-seq technology work in detecting cancer?

ELSA-seq uses cfDNA methylation patterns to distinguish cancer signals from non-cancer signals and identify the tissue of origin.

What is the implication of the THUNDER study results for public health?

The study suggests that the early detection models could significantly reduce late-stage cancer incidence and improve survival rates, benefiting public health.

What is the next step for Burning Rock following the THUNDER study?

Burning Rock aims to collaborate with medical experts for further clinical validation and development of multi-cancer detection products.