Background: Tumor mutational burden (TMB) is an emerging biomarker used to identify patients who are more likely to benefit from immuno-oncology therapy. Aside from various unsettled technical aspects, biological variables such as tumor cell content and intratumor heterogeneity may play an important role in determining TMB.

Methods: TMB estimates were determined applying the TruSight Oncology 500 targeted sequencing panel. Spatial and temporal heterogeneity was analyzed by multiregion sequencing (two to six samples) of 24 pulmonary adenocarcinomas and by sequencing a set of matched primary tumors, locoregional lymph node metastases, and distant metastases in five patients.

Results: On average, a coding region of 1.28 Mbp was covered with a mean read depth of 609x. Manual validation of the mutation-calls confirmed a good performance, but revealed noticeable misclassification during germline filtering. Different regions within a tumor showed considerable spatial TMB variance in 30% (7 of 24) of the cases (maximum difference, 14.13 mut/Mbp). Lymph node-derived TMB was significantly lower (p = 0.016). In 13 cases, distinct mutational profiles were exclusive to different regions of a tumor, leading to higher values for simulated aggregated TMB. Combined, intratumor heterogeneity and the aggregated TMB could result in divergent TMB designation in 17% of the analyzed patients. TMB variation between primary tumor and distant metastases existed but was not profound.

Conclusions: Our data show that, in addition to technical aspects such as germline filtering, the tumor content and spatially divergent mutational profiles within a tumor are relevant factors influencing TMB estimation, revealing limitations of single-sample-based TMB estimations in a clinical context.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.jtho.2019.07.006DOI Listing

Publication Analysis

Top Keywords

tmb
10
spatial temporal
8
temporal heterogeneity
8
tumor
8
tumor mutational
8
mutational burden
8
technical aspects
8
intratumor heterogeneity
8
distant metastases
8
germline filtering
8

Similar Publications

The abnormal expression of acetylcholinesterase (AChE) is linked to the development of various diseases. Accurate determination of AChE activity as well as screening AChE inhibitors (AChEIs) holds paramount importance for early diagnosis and treatment of AChE-related diseases. Herein, a fluorescent and colorimetric dual-channel probe based on gold nanoclusters (AuNCs) and manganese dioxide nanosheets (MnO NSs) was developed.

View Article and Find Full Text PDF

To evaluate the predictive utility of N6-methyladenosine (m6A)-associated long non-coding RNAs (lncRNAs) for the prognosis and immunotherapy response in papillary renal cell carcinoma (pRCC). Transcriptomic data of pRCC samples were extracted from the TCGA database. The m6A-related lncRNAs were identified by Pearson correlation analysis.

View Article and Find Full Text PDF

TiCT MXene nanoribbons@MnO: A novel multifunctional probe for colorimetric and fluorescence dual-response sensing of trichlorfon.

Talanta

December 2024

Key Laboratory of Modern Agricultural Equipment and Technology, Ministry of Education, School of Agricultural Engineering, Jiangsu University, Zhenjiang, Jiangsu, 212013, China; College of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang, 471003, China. Electronic address:

Manganese dioxide nanosheets (MnO NSs) have garnered significant attention in analytical sensing, while the majority of the previous reports suffer from a complex preparation process involving reducing agents, template or high-temperature. In this work, a novel MnO NSs decorated TiCT MXene nanoribbons (TiCTNR@MnO) composite was firstly assemblied via a facile one-step strategy and applied as a bi-signal generator to enable colorimetric and fluorescence (FL) dual-response sensing. During the assembly process, TiCTNR innovatively acted as both reductant and carrier to prevent the aggregation of MnO NSs.

View Article and Find Full Text PDF

Multiomics integration and machine learning reveal prognostic programmed cell death signatures in gastric cancer.

Sci Rep

December 2024

Clinical Teaching Hospital of Medical School, Nanjing Children's Hospital, Nanjing University, Nanjing, 210008, China.

Gastric cancer (GC) is characterized by notable heterogeneity and the impact of molecular subtypes on treatment and prognosis. The role of programmed cell death (PCD) in cellular processes is critical, yet its specific function in GC is underexplored. This study applied multiomics approaches, integrating transcriptomic, epigenetic, and somatic mutation data, with consensus clustering algorithms to classify GC molecular subtypes and assess their biological and immunological features.

View Article and Find Full Text PDF

A dual-signal aptamer-based assay utilizing colorimetric and fluorescence techniques was developed for the determination of zearalenone (ZEN). The CdTe quantum dots, serving as the fluorescent signal source, were surface-modified onto FeO@SiO and subsequently functionalized with the aptamer. The COF-Au was modified with complementary chain, which possessed peroxide (POD)-like enzyme properties, and could catalyze the peroxidation of 3,3',5,5'-tetramethylbenzidine (TMB) to ox TMB, resulting in the generation of colorimetric signals.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!