Abstract 370P
Background
In this study, we examined the TMB landscape of 5,660 pan-cancer cases in Chinese population, using NGS panel. We established cancer-specific and histology-specific biological pathways associated with the TMB status. In addition, as a proof on concept, an unsupervised algorithm was conducted using stepwise logistic regression to generate TMB-predicting signatures from both lung adenocarcinoma and lung squamous cell carcinoma.
Methods
Patients: 5,660 Chinese cancer patients across 11 cancer types Panel: Targeted sequencing was performed on tissue samples using a panel consisting of 295 or 520 cancer-related genes, spanning 1.4 and 1.6Mb of human genome, respectively. An average sequencing depth of 1,000X and 10,000x were achieved for tissue and plasma samples, respectively. Tumor mutation burden: calculated as the ratio of mutation count to the size of coding region of the panel, excluding CNV, fusions, large genomic rearrangements and mutations occurring on the kinase domain of EGFR and ALK.
Results
Across the 11 cancer types included in the analysis, lung squamous cell carcinoma had the highest average TMB, whereas sarcoma has the lowest TMB. High microsatellite instability, DNA damage response deficiency, and homologous recombination repair deficiency indicated significantly higher TMB.The independent predictive power for TMB 26 biological pathways was tested in 11 cancer types. Mismatch repair, DNA damage response, homologous recombination repair, and PI3K-AKT signaling pathway were most commonly correlated with high-TMB. In contrast, ERBB signaling pathway, and adhesion-related pathways were most commonly correlated with low-TMB. Moreover, we developed a 23- and 16-gene signature for TMB prediction for LUAD and LUSC, respectively, with 12 genes shared by both signatures, indicating a histology- specific mechanism for driving high- TMB in lung cancer.
Conclusions
The findings extended the knowledge of the underlying biological mechanisms for high TMB and might be helpful for developing more precise and accessible TMB assessment panels and algorithms in more cancer types.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Burning Rock Biotech.
Disclosure
All authors have declared no conflicts of interest.
Resources from the same session
313P - Immunotherapy application for advanced cancers: One institution experiences since 2016 to 2019
Presenter: Jo Pai Chen
Session: Poster display session
Resources:
Abstract
314P - An EGF motif of Del1 inhibits efficient angiogenesis and suppresses tumour growth in vivo
Presenter: Hisataka Kitano
Session: Poster display session
Resources:
Abstract
315P - Inhibition of JAK1 sensitizes human head and neck cancer cells to cetuximab
Presenter: James Bonner
Session: Poster display session
Resources:
Abstract
316TiP - Neoadjuvant and adjuvant pembrolizumab (pembro) plus standard of care (SOC) in patients (pts) with resectable locally advanced (LA) head and neck squamous cell carcinoma (HNSCC): The phase III KEYNOTE-689 study
Presenter: Ezra Cohen
Session: Poster display session
Resources:
Abstract
322P - Three-year overall survival update from the PACIFIC trial
Presenter: Yi-Long Wu
Session: Poster display session
Resources:
Abstract
323P - Novel tumour mutation score versus tumour mutation burden in predicting survival after immunotherapy in pan-cancer from MSK-IMPACT cohort
Presenter: Yuan Li
Session: Poster display session
Resources:
Abstract
324P - A novel anti-PD-1 antibody HLX10 study led to the initiation of combination immunotherapy
Presenter: Tsu Yi Chao
Session: Poster display session
Resources:
Abstract
325P - Association between immune-related adverse events and efficacy of immune checkpoint inhibitors in patients with advanced hepatocellular carcinoma
Presenter: Lawrence Wong
Session: Poster display session
Resources:
Abstract
326P - Autologous V gamma 9 V delta 2 T cell therapy to target Epstein Barr Virus (EBV)-related malignancies
Presenter: Esdy Rozali
Session: Poster display session
Resources:
Abstract
327P - Neoantigen profile of hepatocellular carcinoma reveals its correlation with tumour progression and clonal evolution
Presenter: Xiaolong Liu
Session: Poster display session
Resources:
Abstract