Recently, a paper titled “A Modified Algorithm Adjusting Both High and Minor Allele Frequency Mutation to Rede Fine Blood-Based Tumor Mutational Burden (bTMB) for Optimal Prediction of Clinical Benefits From Immune Checkpoint Inhibitor Therapy” on the study carried out by the team of Professor He Jianxing of the First Affiliated Hospital of Guangzhou Medical University and SKLRD was published online in the Journal of Thoracic Oncology =12.5.

Immunotherapy led by PD-1/PD-L1 blockade has relieved some patients with advanced disease for long term remission or even cured clinically. However, the proportion of effective superior population is not high (about 20%). It is very important to find the beneficiaries and accurately guide the treatment. A previous study published in Nature Medicine has verified that calculating tumor mutational burden from blood can predict the benefit of immunotherapy. In this study, the team of Professor He Jianxing further explored the potential influencing factors (maximum mutation frequency and ctDNA mutation abundance heterogeneity) of bTMB-guided immunotherapy efficacy and corrected it, redefined a more precise "optimization-bTMB", and proved that it is superior to the current international mainstream algorithm, and can predict the ORR, PFS and OS of immunotherapy more accurately. This study was co-directed by He Jianxing and Professor Liang Wenhua and completed by Liu Zhichao graduated from the Nanshan Class as the first author.