Improving Early Cancer Detection with Hotspot Mutations
Author Information
Author(s): Nguyen Thi Hue Hanh, Vu Giang Hoang, Nguyen Tu Thi, Nguyen Tuan Anh, Tran Vu Uyen, Vu Luyen Thi, Nguyen Giang Thi Huong, Nguyen Nhat Duy, Tran Trung Hieu, Nguyen Van Thien Chi, Nguyen Thanh Dat, Nguyen Trong Hieu, Vo Dac Ho, Van Thi Tuong Vi, Do Thanh Thi, Le Minh Phong, Huynh Le Anh Khoa, Nguyen Duy Sinh, Tang Hung Sang, Nguyen Hoai‐Nghia, Phan Minh‐Duy, Giang Hoa, Tu Lan N., Tran Le Son
Primary Institution: Medical Genetics Institute Ho Chi Minh Vietnam
Hypothesis
Can integrating hotspot mutations into the SPOT-MAS assay enhance early cancer detection rates?
Conclusion
Integrating genetic and epigenetic alterations into a multimodal assay significantly enhances the early detection of various cancers.
Supporting Evidence
- Hotspot mutations were detected in 51.4% of cancer patients.
- The highest detection rates were in liver cancer (96.5%).
- Combining hotspot mutations with SPOT-MAS improved early-stage cancer detection to 78.5%.
- SPOT-MAS showed higher sensitivity for early-stage cancers compared to hotspot mutations.
Takeaway
This study shows that combining different tests can help find cancer earlier, which is really important for treatment.
Methodology
A targeted amplicon sequencing approach was developed to profile 700 hotspot mutations in cell-free DNA and integrated into the SPOT-MAS assay, validated in a cohort of 255 cancer patients and 304 healthy individuals.
Potential Biases
Potential bias due to the retrospective nature and the absence of staging information for some patients.
Limitations
The study is retrospective and requires prospective validation in larger populations; also, the performance may be influenced by the amount and quality of cfDNA.
Participant Demographics
The study included 255 cancer patients (64 breast, 59 colorectal, 62 gastric, 29 liver, 41 lung) and 304 healthy individuals, with a median age of 50 years for controls.
Statistical Information
P-Value
p<0.0001
Confidence Interval
95% CI: 73.0–83.0
Statistical Significance
p<0.0001
Digital Object Identifier (DOI)
Want to read the original?
Access the complete publication on the publisher's website