Genomic landscape and tumor mutation burden analysis of Chinese patients with sarcomatoid carcinoma of the head and neck

Oral Oncology ◽  
2021 ◽  
Vol 121 ◽  
pp. 105436
Author(s):  
Hai-bing Chen ◽  
Xiao-yang Gong ◽  
Wang Li ◽  
Dong-sheng Chen ◽  
Le-le Zhao ◽  
...  
Keyword(s):  
Head And Neck ◽  
Sarcomatoid Carcinoma ◽  
Chinese Patients ◽  
Tumor Mutation Burden ◽  
Genomic Landscape ◽  
Mutation Burden

PD-L1 expression landscape and its relationship with tumor mutation burden in Chinese cancer patients.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e15267-e15267
Author(s):  
Haihua Yang ◽  
Longgang Cui ◽  
Yuzi Zhang ◽  
Zhengyi Zhao ◽  
Yuezong Bai ◽  
...  
Keyword(s):  
Cancer Patients ◽  
Expression Profiles ◽  
Chinese Patients ◽  
Cancer Type ◽  
Tissue Samples ◽  
Tumor Mutation Burden ◽  
Mutational Burden ◽  
Mutation Burden ◽  
Tumor Mutational Burden ◽  
Chinese Cancer Patients

e15267 Background: Little is known about the pan-cancer PD-L1 expression landscape in Chinese patients although PD-L1 expression has been approved by FDA as a diagnosis for anti-PD-(L)1 therapy in several types of cancer. We did a cross-sectional analysis to assess the PD-L1 expression landscape in Chinese patients and its relationship with Tumor mutation burden (TMB). Methods: Tissue samples were collected from more than 8,000 consecutive cases in China between January, 2017, and August, 2019 and were analyzed by 3D Medicines, a College of American Pathologists (CAP)-accredited and Clinical Laboratory Improvement Amendments (CLIA)-certified laboratory. The method for NGS sequencing and tumor mutational burden (TMB) measurement were described previously. Clinical data and PD-L1 expression profiles were obtained from 8,063 patients whose tissue samples assed quality control. IHC staining for PD-L1 expression was performed using PD-L1 IHC 22C3 pharmDx assay (Dako North America, Carpentaria, CA, U.S.) or Ventana PD-L1 SP263 assay (Ventana Medical Systems, Tucson, AZ, U.S.). PD-L1 expression was determined using Tumor Proportion Score (TPS), the percentage of viable tumor cells stained. Results: PD-L1 expression was examined for 8,063 tissue samples collected from more than 18 different types of solid tumors. There were 4,866 (60%) male and 3,197 (40%) female patients. Their median age was 59 (IQR range, 50-66) years. Given the significance of different cut-points of PD-L1 expression in predicting clinical outcomes, expression levels of PD-L1 were arranged into the following intervals: < 1%, 1%-5%, 5%-50% and ≥50% for each cancer type. Small cell lung cancer (SCLC) had the lowest and Squamous Carcinoma of Head and Neck (HNSC) had the highest levels of PD-L1 expression. Spearman correlation analysis indicated no correlation between PD-L1 and tumor mutational burden (TMB) for Chinese cancer patients (R = 0.1, P < 0.01), which is in line with the previous reports that PD-L1 and TMB were two independent predictors in immunotherapy. Conclusions: The landscape of PD-L1 expression among Chinese cancer population in this study will further assist the utilization of PD-L1 as a predictive biomarker in clinical practice.

scholarly journals Clinicopathological features of tumor mutation burden, Epstein-Barr virus infection, microsatellite instability and PD-L1 status in Chinese patients with gastric cancer

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Li Zhang ◽  
Yinkui Wang ◽  
Zhongwu Li ◽  
Dongmei Lin ◽  
Yiqiang Liu ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Microsatellite Instability ◽  
Epstein Barr Virus ◽  
Genetic Alterations ◽  
Chinese Patients ◽  
Epstein Barr Virus Infection ◽  
Tumor Mutation Burden ◽  
Barr Virus ◽  
Mutation Burden ◽  
Epstein Barr

Abstract Objectives Gastric cancer (GC) is the 4th most common type of cancer worldwide. Different GC subtypes have unique molecular features that may have different therapeutic methods. The aim of the present study was to investigate Epstein-Barr virus (EBV) infection, microsatellite instability (MSI) status, the expression of programmed death-ligand 1 (PD-L1) and gene mutations in GC patients. Methods The data of 2504 GC patients, who underwent curative gastrectomy with lymphadenectomy at Peking University Cancer Hospital between 2013 and 2018, were reviewed. We analyzed the clinicopathological factors associated with the immunohistochemistry (IHC) profiles of these patients, and genetic alterations were analyzed using next generation sequencing (NGS). Results Mismatch repair-deficient (d-MMR) GC patients were found to have a higher probability of expressing PD-L1 (p = 0.000, PD-L1 cutoff value = 1%). In addition, 4 and 6.9% of the 2504 gastric cancer patients were EBV-positive and d-MMR, respectively. The number of MLH1/PMS2-negative cases was 126 (6%), and the number of MSH2/MSH6-negative cases was 14 (0.9%). d-MMR status was associated with a intestinal group (p = 0.012), but not with tumor differentiation. Furthermore, MSI and d-MMR GC status (detected by NGS and IHC, respectively) were consistently high, and the rate of MSI was higher in patients with d-MMR GC. A number of genes associated with DNA damage repair were detected in GC patients with MSI, including POLE, ETV6, BRCA and RNF43. In patients with a high tumor mutation burden, the most significantly mutated genes were LRP1B (79.07%), ARID1A (74.42%), RNF43 (69.77%), ZFHX3 (65.12%), TP53 (58.14%), GANS (51.16%), BRCA2 (51.16%), PIK3CA (51.16%), NOTCH1 (51.16%), SMARCA4 (48.84%), ATR (46.51%), POLE (41.86%) and ATM (39.53%). Conclusions Using IHC and NGS, MSI status, protein expression, tumor mutation burden (TMB) and genetic alterations were identified in patients with GC, which provides a theoretical basis for the future clinical treatment of GC.

scholarly journals Genomic Landscape of Angiosarcoma: A Targeted and Immunotherapy Biomarker Analysis

Cancers ◽  
2021 ◽  
Vol 13 (19) ◽  
pp. 4816
Author(s):  
Andrea P. Espejo-Freire ◽  
Andrew Elliott ◽  
Andrew Rosenberg ◽  
Philippos Apolinario Costa ◽  
Priscila Barreto-Coelho ◽  
...  
Keyword(s):  
Head And Neck ◽  
Genetic Alterations ◽  
Design And Optimization ◽  
Whole Exome ◽  
Genomic Landscape ◽  
Mutation Burden ◽  
Biomarker Analysis ◽  
Next Generation Sequencing Ngs ◽  
Response Biomarkers ◽  
Ngs Data

We performed a retrospective analysis of angiosarcoma (AS) genomic biomarkers and their associations with the site of origin in a cohort of 143 cases. Primary sites were head and neck (31%), breast (22%), extremity (11%), viscera (20%), skin at other locations (8%), and unknown (9%). All cases had Next Generation Sequencing (NGS) data with a 592 gene panel, and 53 cases had Whole Exome Sequencing (WES) data, which we used to study the microenvironment phenotype. The immunotherapy (IO) response biomarkers Tumor Mutation Burden (TMB), Microsatellite Instability (MSI), and PD-L1 status were the most frequently encountered alteration, present in 36.4% of the cohort and 65% of head and neck AS (H/N-AS) (p < 0.0001). In H/N-AS, TMB-High was seen in 63.4% of cases (p < 0.0001) and PDL-1 positivity in 33% of cases. The most common genetic alterations were TP53 (29%), MYC amplification (23%), ARID1A (17%), POT1 (16%), and ATRX (13%). H/N-AS cases had predominantly mutations in TP53 (50.0%, p = 0.0004), POT1 (40.5%, p < 0.0001), and ARID1A (33.3%, p = 0.5875). In breast AS, leading alterations were MYC amplification (63.3%, p < 0.0001), HRAS (16.1%, p = 0.0377), and PIK3CA (16.1%, p = 0.2352). At other sites, conclusions are difficult to generate due to the small number of cases. A microenvironment with a high immune signature, previously associated with IO response, was evenly distributed in 13% of the cases at different primary sites. Our findings can facilitate the design and optimization of therapeutic strategies for AS.

An effective and accurate algorithm for measuring the tumor mutation burden of cancer patients plasma.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e14177-e14177
Author(s):  
Bo Liu ◽  
Shuang Zhou ◽  
Yu Hang Cai ◽  
Ying Yang ◽  
Mingzhi Ye ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Pearson Correlation ◽  
Chinese Patients ◽  
Cancer Type ◽  
Plasma Samples ◽  
Single Nucleotide Variants ◽  
Tissue Samples ◽  
Tumor Mutation Burden ◽  
Synonymous Mutations ◽  
Mutation Burden

e14177 Background: Tumor Mutation Burden (TMB) is deemed to be one of the effective genomic biomarkers that are used to predict the response to PD-1/PD-L1 blockade immunotherapy. As an exciting biomarker for diagnose and an alternative assess method for tissue TMB (tTMB), blood TMB (bTMB) is measured to further distinguish the patients who may benefit from immunotherapy. However, there is no recognized rule to calculate bTMB so far. Methods: In this study, we developed an in-house algorithm called PTAB to calculate bTMB of plasma, all credible single nucleotide variants and insertion-deletions whose allele frequency is greater than 1% are selected in PTAB without synonymous mutations and drive mutations. We also constructed a 636 genes panel which region size is 1.95Mb to identify all the associated mutations, due to the high costs and long turnaround time of WES. Results: Meanwhile, we assessed a cohort of 50 lung cancer plasma samples and paired tissues to ensure the consistency of different algorithm used for tissue and plasma. The results show that Pearson correlation coefficient (R2) between bTMB and tTMB in 50 patients is 0.7128. In addition, we found that the consistency of lung squamous carcinomas obviously higher than that of lung adenocarcinoma (0.8932 vs. 0.5947). We also described the distribution of bTMB and tTMB value of Chinese patients, including 594 tissue samples and 561 plasma samples from 8 types of cancers, including lung cancer, colorectal cancer, breast cancer, et al. The overall comparative analysis of 1155 previous data suggested that the distribution modes of bTMB and tTMB were almost same in certain cancer type, though the level of bTMB was generally lower than that of tTMB. Conclusions: Preliminary data highlight that PTAB is an effective and accurate algorithm for measure the TMB of plasma. The applicability of bTMB testing on liquid biopsy needs further investigation and may be clarified within the ongoing clinical trials.

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