HLA-corrected tumor mutation burden and homologous recombination deficiency for the prediction of response to PD-(L)1 blockade in advanced non-small-cell lung cancer patients

Shim, Joon Ho; Kim, H.S.; Cha, Hongui; Kim, S.; Kim, T.M.; Anagnostou, Valsamo; Choi, Yoon‐La; Jung, Hyun Ae; Sun, Jong‐Mu; Ahn, Jin Seok; Ahn, Myung‐Ju; Park, K.; Park, W.-Y.; Lee, S.-H.

doi:10.1016/j.annonc.2020.04.004

Cited by 105 publications

(100 citation statements)

References 23 publications

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“…To sum up, the five gene markers are rarely discussed in the previous study of ovarian cancer and should be put more emphasis on. TMB is an important index to reflect the somatic mutation accumulation, and it was viewed as a biomarker to select patients who benefit from immune-checkpoint treatment [73]. In the checkmate 032 clinical trial, 401 patients with end stage lung cancer were divided into three groups according to the level of TMB, and the results showed that patients with high TMB patients are superior to other patients both in treatment efficiency and median survival [74].…”

Section: Discussionmentioning

confidence: 99%

Comprehensive analysis of prognostic gene signatures based on immune infiltration of ovarian cancer

et al. 2020

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Background Ovarian cancer (OV) is one of the most common malignant tumors of gynecology oncology. The lack of effective early diagnosis methods and treatment strategies result in a low five-year survival rate. Also, immunotherapy plays an important auxiliary role in the treatment of advanced OV patient, so it is of great significance to find out effective immune-related tumor markers for the diagnosis and treatment of OV. Methods Based on the consensus clustering analysis of single-sample gene set enrichment analysis (ssGSEA) score transformed via The Cancer Genome Atlas (TCGA) mRNA profile, we obtained two groups with high and low levels of immune infiltration. Multiple machine learning methods were conducted to explore prognostic genes associated with immune infiltration. Simultaneously, the correlation between the expression of mark genes and immune cells components was explored. Results A prognostic classifier including 5 genes (CXCL11, S1PR4, TNFRSF17, FPR1 and DHRS95) was established and its robust efficacy for predicting overall survival was validated via 1129 OV samples. Some significant variations of copy number on gene loci were found between two risk groups and it showed that patients with fine chemosensitivity has lower risk score than patient with poor chemosensitivity (P = 0.013). The high and low-risk groups showed significantly different distribution (P < 0.001) of five immune cells (Monocytes, Macrophages M1, Macrophages M2, T cells CD4 menory and T cells CD8). Conclusion The present study identified five prognostic genes associated with immune infiltration of OV, which may provide some potential clinical implications for OV treatment.

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Section: Discussionmentioning

confidence: 99%

Comprehensive analysis of prognostic gene signatures based on immune infiltration of ovarian cancer

et al. 2020

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“…31 32 However, the best predictive marker for response to immunotherapy is still to be defined. Of note, recently Shim et al 33 presented a human leucocyte antigen corrected TMB, that included loss of heterozygosity and enabled a better prediction of response to immune-checkpoint inhibitors. Moreover, the value of PD-L1 expression as a predictive biomarker for the treatment with PD-1/PD-L1 inhibitors in PDAC remains inconclusive.…”

Section: Discussionmentioning

confidence: 99%

Molecular characteristics of BRCA1/2 and PALB2 mutations in pancreatic ductal adenocarcinoma

et al. 2020

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IntroductionPoly-(ADP)-ribose polymerase (PARP) inhibitors are successfully used for treatment of BRCA-mutated (mut) breast cancers and are under extensive evaluation for BRCA- and PALB2-mutated pancreatic ductal adenocarcinoma (PDAC). However, the optimal treatment regimen for BRCA/PALB2-mutated PDCA has yet to be established. Moreover, limited data are available on the association of BRCA/PALB2 gene alterations with other comutations and immunological biomarkers.Material and methodsTumour samples of 2818 patients with PDAC were analysed for BRCA1/2 PALB2 mutations and other genes by next-generation sequencing (NGS) (MiSeq on 47 genes, NextSeq on 592 genes). TMB was calculated based on somatic non-synonymous missense mutations. MSI-H/dMMR was evaluated by NGS, and PD-L1 expression was determined using immunohistochemistry.ResultsIn 4.2% (n=124) of all PDAC samples BRCA mutations have been detected. BRCA2 mutations were more commonly observed than BRCA1 mutations (3.1%(n=89) vs 1.1% [n=35], p<0.0001). BRCA2 mutation was associated with an older age (64 vs 61 years for wild-type (wt), p=0.002) and PALB2 mutation was observed more frequently in female than in male patients. BRCA and PALB2 mutations were associated with MSI-H/dMMR compared with wt (BRCA: 4.8% vs 1.2%, p=0.002; PALB2: 6.7% vs 1.3 %, p=0.18), PD-L1 expression of >1.0% (BRCA: 21.8% vs wt 11.2%, p<0.001, PALB2: 0.0% vs 12.4 %, p=0.38) and high TMB (BRCA: mean 8.7 vs 6.5 mut/MB, p<0.001; PALB2: 10.6 mut/Mb vs 6.6 mut/Mb, p=0.0007). Also, PD-L1 expression and TMB differed between BRCA and PALB2 mutation and wt samples in MSS tumours (p<0.05). BRCA-mutated and PALB2-mutated PDACs were characterised by a different mutational profile than was observed in wt tumours.ConclusionsBRCA and PALB2 mutations were found in a significant subgroup of PDACs. These mutations were associated with a distinct molecular profile potentially predictive for response to immune-checkpoint inhibitor therapy. Therefore, these data provide a rationale to evaluate PARP inhibitors in combination with immune-checkpoint inhibitors in patients with BRCA/PALB2-mutated PDAC.

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“…We have also demonstrated a link between YIF1B expression and TMB and MSI in some cancer types, and certain tumors also exhibit co-expression of YIF1B with the major MMR genes and methylation transferases. Previous studies have correlated TMB and MSI to patients' drug responses, especially for drugs that target immune checkpoint inhibitors, such as a TGF-β antagonist and PD-1 inhibitor [27][28][29][30][31][32]. We propose, therefore, that YIF1B could be deployed as an additional indicator for immune therapy evaluation of cancer patients after administration.…”

Section: Discussionmentioning

confidence: 98%

Prognostic and immune regulating roles of YIF1B in Pan-Cancer: a potential target for both survival and therapy response evaluation

et al. 2020

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The neurotransmitter serotonin has emerged as a tumor growth factor and immune response regulator through complex signaling pathways. Yip1 Interacting Factor Homolog B (YIF1B) is a membrane protein involved in serotonin receptor membrane trafficking and signal transmission in neuropathy. Participation of YIF1B in serotonin-induced tumor growth and immune regulation has not been previously investigated. Data for analysis of YIF1B mRNA expression were downloaded from the website portals TCGA, GTEx, CCLE and ICGC, including clinical and mutational information. Survival analysis included the Kaplan-Meier method for calculation of the cumulative incidence of the survival event and the log rank method for comparison of survival curves between groups. Infiltration levels of immune cells were calculated and correlated with YIF1B expression using the Spearman correlation test to evaluate significance. Further correlation analyses between YIF1B expression and mutation indicators such as tumor mutation burden (TMB), microsatellite instability (MSI), and mismatch repair (MMR) were also examined by the Spearman test. YIF1B expression was elevated in most cancer types and this high expression was indicative of poor overall survival and death specific survival. In BRCA and LIHC, high YIF1B expression correlated with a poor disease-free interval, indicating a role in malignancy progression. There was a positive relationship between YIF1B expression and immune cell infiltration in several cancer types, and YIF1B also positively correlated with TMB, MSI, and methylation in some cancer types, linking its expression to possible evaluation of therapy response. The bioinformatic analyses have, therefore, established YIF1B as a good biomarker for prognostic and therapeutic evaluation.

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HLA-corrected tumor mutation burden and homologous recombination deficiency for the prediction of response to PD-(L)1 blockade in advanced non-small-cell lung cancer patients

Cited by 105 publications

References 23 publications

Comprehensive analysis of prognostic gene signatures based on immune infiltration of ovarian cancer

Comprehensive analysis of prognostic gene signatures based on immune infiltration of ovarian cancer

Molecular characteristics of BRCA1/2 and PALB2 mutations in pancreatic ductal adenocarcinoma

Prognostic and immune regulating roles of YIF1B in Pan-Cancer: a potential target for both survival and therapy response evaluation

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