scholarly journals RNA Sequencing Data for FFPE Tumor Blocks Can Be Used for Robust Estimation of Tumor Mutation Burden in Individual Biosamples

2021 ◽  
Vol 11 ◽  
Author(s):  
Maxim Sorokin ◽  
Alexander Gorelyshev ◽  
Victor Efimov ◽  
Evgenia Zotova ◽  
Marianna Zolotovskaia ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Clinical Decision Making ◽  
Area Under The Curve ◽  
Single Sample ◽  
Spearman Correlation ◽  
Sequencing Data ◽  
High Quality ◽  
Tissue Samples ◽  
Tumor Mutation Burden ◽  
Mutation Burden

Tumor mutation burden (TMB) is a well-known efficacy predictor for checkpoint inhibitor immunotherapies. Currently, TMB assessment relies on DNA sequencing data. Gene expression profiling by RNA sequencing (RNAseq) is another type of analysis that can inform clinical decision-making and including TMB estimation may strongly benefit this approach, especially for the formalin-fixed, paraffin-embedded (FFPE) tissue samples. Here, we for the first time compared TMB levels deduced from whole exome sequencing (WES) and RNAseq profiles of the same FFPE biosamples in single-sample mode. We took TCGA project data with mean sequencing depth 23 million gene-mapped reads (MGMRs) and found 0.46 (Pearson)–0.59 (Spearman) correlation with standard mutation calling pipelines. This was converted into low (<10) and high (>10) TMB per megabase classifier with area under the curve (AUC) 0.757, and application of machine learning increased AUC till 0.854. We then compared 73 experimental pairs of WES and RNAseq profiles with lower (mean 11 MGMRs) and higher (mean 68 MGMRs) RNA sequencing depths. For higher depth, we observed ~1 AUC for the high/low TMB classifier and 0.85 (Pearson)–0.95 (Spearman) correlation with standard mutation calling pipelines. For the lower depth, the AUC was below the high-quality threshold of 0.7. Thus, we conclude that using RNA sequencing of tumor materials from FFPE blocks with enough coverage can afford for high-quality discrimination of tumors with high and low TMB levels in a single-sample mode.

scholarly journals Software Benchmark—Classification Tree Algorithms for Cell Atlases Annotation Using Single-Cell RNA-Sequencing Data

2021 ◽  
Vol 12 (2) ◽  
pp. 317-334
Author(s):  
Omar Alaqeeli ◽  
Li Xing ◽  
Xuekui Zhang
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Classification Tree ◽  
Area Under The Curve ◽  
Data Sets ◽  
Sequencing Data ◽  
Single Cell Rna Sequencing ◽  
Tree Algorithms ◽  
R Packages

Classification tree is a widely used machine learning method. It has multiple implementations as R packages; rpart, ctree, evtree, tree and C5.0. The details of these implementations are not the same, and hence their performances differ from one application to another. We are interested in their performance in the classification of cells using the single-cell RNA-Sequencing data. In this paper, we conducted a benchmark study using 22 Single-Cell RNA-sequencing data sets. Using cross-validation, we compare packages’ prediction performances based on their Precision, Recall, F1-score, Area Under the Curve (AUC). We also compared the Complexity and Run-time of these R packages. Our study shows that rpart and evtree have the best Precision; evtree is the best in Recall, F1-score and AUC; C5.0 prefers more complex trees; tree is consistently much faster than others, although its complexity is often higher than others.

scholarly journals Assessment of tumor mutation burden calculation from gene panel sequencing data

2019 ◽  
Vol Volume 12 ◽  
pp. 3401-3409 ◽  
Author(s):  
Zhenwu Xu ◽  
Jiawei Dai ◽  
Dandan Wang ◽  
Hui Lu ◽  
Heng Dai ◽  
...  
Keyword(s):  
Gene Panel ◽  
Sequencing Data ◽  
Tumor Mutation Burden ◽  
Mutation Burden ◽  
Gene Panel Sequencing ◽  
Panel Sequencing

scholarly journals ctDNA monitoring using patient-specific sequencing and integration of variant reads

2020 ◽  
Vol 12 (548) ◽  
pp. eaaz8084 ◽  
Author(s):  
Jonathan C. M. Wan ◽  
Katrin Heider ◽  
Davina Gale ◽  
Suzanne Murphy ◽  
Eyal Fisher ◽  
...  
Keyword(s):  
Residual Disease ◽  
Early Stage ◽  
Area Under The Curve ◽  
Patient Specific ◽  
Sequencing Data ◽  
Liquid Biopsies ◽  
Whole Exome ◽  
Mutation Burden ◽  
Median Area ◽  
Personalized Cancer

Circulating tumor-derived DNA (ctDNA) can be used to monitor cancer dynamics noninvasively. Detection of ctDNA can be challenging in patients with low-volume or residual disease, where plasma contains very few tumor-derived DNA fragments. We show that sensitivity for ctDNA detection in plasma can be improved by analyzing hundreds to thousands of mutations that are first identified by tumor genotyping. We describe the INtegration of VAriant Reads (INVAR) pipeline, which combines custom error-suppression methods and signal-enrichment approaches based on biological features of ctDNA. With this approach, the detection limit in each sample can be estimated independently based on the number of informative reads sequenced across multiple patient-specific loci. We applied INVAR to custom hybrid-capture sequencing data from 176 plasma samples from 105 patients with melanoma, lung, renal, glioma, and breast cancer across both early and advanced disease. By integrating signal across a median of >105 informative reads, ctDNA was routinely quantified to 1 mutant molecule per 100,000, and in some cases with high tumor mutation burden and/or plasma input material, to parts per million. This resulted in median area under the curve (AUC) values of 0.98 in advanced cancers and 0.80 in early-stage and challenging settings for ctDNA detection. We generalized this method to whole-exome and whole-genome sequencing, showing that INVAR may be applied without requiring personalized sequencing panels so long as a tumor mutation list is available. As tumor sequencing becomes increasingly performed, such methods for personalized cancer monitoring may enhance the sensitivity of cancer liquid biopsies.

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.

Mutational landscape and tumor mutation burden (TMB) feature of biliary cancer.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e16670-e16670
Author(s):  
Bin Yi ◽  
Lianke Liu ◽  
Jinghai Song ◽  
Yingying Huang ◽  
Min Zhang ◽  
...  
Keyword(s):  
Gene Mutation ◽  
Target Therapy ◽  
Biliary Cancer ◽  
Plasma Samples ◽  
Extrahepatic Cholangiocarcinoma ◽  
Tissue Samples ◽  
Tumor Mutation Burden ◽  
Mutation Burden ◽  
Tumor Tissues ◽  
Next Generation Sequencing Ngs

e16670 Background: Biliary cancer are relatively rare, highly aggressive and have poor prognoses. Most biliary cancers are diagnosed in the advanced and metastatic stages. Chemotherapy is the main treatment of advanced biliary cancer. We focus on gene mutation and tumor mutation burden (TMB) of biliary cancer. Methods: We retrospectively reviewed one hundred and fifty-six cases of biliary cancer. One hundred and fifty-six tumor tissues and 35 plasma samples were subjected to next-generation sequencing (NGS), which enables simultaneously assess snv, indel, rearrangements and cnv variations at least 59 genes (range 59-1021 genes). Results: Fifty-eight patients were intrahepatic cholangiocarcinoma (IHCC), 50 were extrahepatic cholangiocarcinoma (EHCC) and 48 were gall bladder cancer (GBC). From tissue samples, the commonly mutated genes were different in three groups. TP53 was the most frequently mutated gene among the three groups (IHCC 43%, EHCC 58%, GBC 79%). KRAS (33%), TERT (16%), LRP1B (16%), IDH1/2 (10%) were usual in IHCC. KRAS (28%), SMAD4 (20%), STK11 (18%), ARID1A (12%) were usual in EHCC. And ERBB2 (19%), LRP1B (17%), TERT (15%), MLL3 (15%) were usual in GBC. TP53, LRP1B and MLL3 had a higher frequency in GBC than cholangiocarcinoma (p < 0.05), and KRAS was more common in cholangiocarcinoma than GBC (p < 0.05). 72.4% IHCC, 76.0% EHCC and 60.4% GBC had gene mutation associated with target therapies, which involved in multiple signal pathway, such as IDH1/2, FGFR, ERBB1/2/3, MET, PIK3CA, PTEN, BRCA, etc. Thirty-five patients had paired tissue and plasma samples, 21 stage Ⅲ/Ⅳ, 11 stage Ⅱ and 3 unknown. The concordance between tissue and plasma was 53% in all patients and was higher in stage Ⅲ/Ⅳ than stage Ⅱ (p < 0.05). One hundred and thirty-three tissue samples assessed TMB, the mean TMB was highest in the GBC group, followed by EHCC and IHCC (7.1 vs 5.5 vs 3.9 muts/Mb, p < 0.05). The proportion of TMB-H (defined 9.0 muts/Mb as cutoff value) was higher in GBC than IHCC and EHCC. Conclusions: IHCC, EHCC, and GBC have distinctive mutational landscapes and TMB features. It maybe guide different target therapy and immunotherapy strategies in the clinic. ctDNA has promising potential in biliary cancer.

Co-mutations of KRAS/BRAF and TP53 or the high tumor mutation burden to predict survival in patients with biliary tract carcinoma.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e16650-e16650
Author(s):  
Lingling Guo ◽  
Xiaoxia Kou ◽  
Panpan Song ◽  
Xiaoyu Zhang ◽  
Hongjuan Zhang ◽  
...  
Keyword(s):  
Biliary Tract ◽  
Poor Prognosis ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Biliary Tract Carcinoma ◽  
Rank Test ◽  
Braf Mutations ◽  
Tumor Mutation Burden ◽  
Synonymous Mutations ◽  
Mutation Burden

e16650 Background: Biliary tract carcinoma (BTC), including cholangiocarcinoma and gallbladder carcinoma, is the second most common type of hepatobiliary cancer. Patients with BTC always show poor prognosis, here we revealed the molecular landscape of BTC in the Chinese population and evaluated the role of different mutations in informing prognosis. Methods: Formalin-Fixed Paraffin-Embedded (FFPE) or freshly-sampled tumor tissues from 59 BTC patients were conducted next-generation sequencing of 620 genes related to oncogenesis. Tumor mutation burden (TMB) value represents the number of non-synonymous mutations per mega base pairs in each sample. Kaplan-Meier survival curves were generated and compared using the log-rank test. Results: Altogether, 59 patients have mutations mainly in TP53, Ras/Raf, PI3K, CDK signaling pathways and SWI/SNF complex. The most frequently mutated gene was TP53(53%), followed by KRAS(23%), ARID1A(17%), ATM(12%), CDKN2A(10%), SMAD4(8%), BRCA2(8%), STK11(7%), BRAF(5%), IDH1(5%) and FGFR3 (3%). Noticeably, only one patient with FGFR2 fusion was detected. The Median TMB of these patients is 2.80 Muts/Mbp (0-36.52 Muts/Mbp). Existing data showed that KRAS/BRAF alterations were associated with a worse overall survival (OS) (median OS 166d vs. 294d, p= 0.063). Further analysis indicated that RAS/BRAF mutations were often co-current with TP53 alternations. And patients with coaltered RAS/BRAF and TP53 demonstrated the worst prognosis (media OS 123d vs. 294d, p= 0.087). In addition, a higher TMB ( > 2.80 Muts/Mb) was also associated with a worse survival (median OS 174d vs. 355d, p= 0.085). Conclusions: We identified KRAS/BRAF, or co-mutations with TP53 and high TMB could predict poor prognosis in BTC patients. These findings will be useful for clinical decision making in patients with refractory biliary tract cancer and for risk stratification of patients in future clinical studies.

scholarly journals Single-cell RNA sequencing of intramedullary canal tissue to improve methods for studying fracture repair biology

BioTechniques ◽  
2021 ◽  
Author(s):  
James M Dominguez ◽  
Sharon M Moe ◽  
Neal X Chen ◽  
Todd O McKinley ◽  
Krista M Brown ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Prospective Studies ◽  
Fracture Repair ◽  
Bone Microenvironment ◽  
Sequencing Data ◽  
Tissue Samples ◽  
Intramedullary Canal ◽  
Single Cell Rna Sequencing ◽  
Fracture Nonunion

The ability to study the bone microenvironment of failed fracture healing may lead to biomarkers for fracture nonunion. Herein the authors describe a technique for isolating individual cells suitable for single-cell RNA sequencing analyses from intramedullary canal tissue collected by reaming during surgery. The purpose was to detail challenges and solutions inherent to the collection and processing of intramedullary canal tissue samples. The authors then examined single-cell RNA sequencing data from fresh and reanimated samples to demonstrate the feasibility of this approach for prospective studies.

Comprehensive genomic profiling to merge precision medicine with immunotherapy.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e23108-e23108
Author(s):  
Stephen Lyle ◽  
Julie Y Tse ◽  
Ruobai Sun ◽  
Xiu Huang ◽  
Meaghan Russell ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Copy Number ◽  
Treatment Strategies ◽  
Gene Panel ◽  
Next Generation Sequencing Data ◽  
Patient Treatment ◽  
Clinical Samples ◽  
Sequencing Data ◽  
Tumor Mutation Burden ◽  
Mutation Burden

e23108 Background: Immunotherapy is rapidly emerging as one of the most promising therapeutic options in clinical oncology. However, not all patients will respond to immune-oncology drugs and diagnostic assays are urgently needed to identify biomarkers that predict response to these therapies. We developed an assay that utilizes next generation sequencing data to simultaneously determine different types of somatic changes in tumors. The assay was designed, in part, to facilitate identification of cancer patients most likely to respond to immunotherapies by detecting 1) CD274 (PD-L1) copy number alterations, 2) viral infections (HPV16/18 and EBV), 3) microsatellite instability (MSI), and 4) tumor mutation burden. Methods: We developed a 435-gene panel assay (CancerPlex) with the goal of identifying all the genomic changes that inform treatment decisions with the highest possible accuracy. We thoroughly evaluated the performance of the assay using reference samples that represent all classes of genetic variation, including SNPs, indels, copy number changes, rearrangements, HPV/EBV infection and MSI. FFPE clinical samples were also evaluated to assess the ability of the assay to detect genetic variation in complex, heterogeneous tumors. Results: The assay has excellent performance, with a mean sensitivity of 99.4% and specificity of 99.9% for detecting somatic mutations with an allele fraction as low as 10%. The assay identified the MSI status of colorectal tumors with the same sensitivity as immunohistochemistry but with greater sensitivity than PCR. We also showed that calculating tumor mutation burden using the 435-gene panel predicts response to pembrolizumab as effectively as using whole exome sequencing. Among 892 patients across all tumor types, 6.8% were identified as candidates for immunotherapy based upon high tumor mutation burden and/or MSI status. Conclusions: The capacity of the 435-gene panel to determine all of the critical genetic changes, tumor mutation burden, MSI status, CD274 (PD-L1) CNVs, and HPV/EBV status has important ramifications for patient treatment strategies, including identification of patients who are more likely to benefit from immune checkpoint inhibitor therapies.

Sign in / Sign up

Export Citation Format

Share Document