Multimodal analysis of cell-free DNA whole-genome sequencing for pediatric cancers with low mutational burden.
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ABSTRACT:
SUBMITTER: Peneder P
PROVIDER: S-EPMC8163828 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Mutational signatures accumulate in somatic cells as an admixture of endogenous and exogenous processes that occur during an individual's lifetime. Since dividing cells release cell-free DNA (cfDNA) fragments into the circulation, we hypothesize that plasma cfDNA might reflect mutational signatures. Point mutations in plasma whole genome sequencing (WGS) are challenging to identify through conventional mutation calling due to low sequencing coverage and low mutant allele fractions. In this proof of concept study of plasma WGS at 0.3-1.5x coverage from 215 patients and 227 healthy individuals, we show that both pathological and physiological mutational signatures may be identified in plasma. By applying machine learning to mutation profiles, patients with stage I-IV cancer can be distinguished from healthy individuals with an Area Under the Curve of 0.96. Interrogating mutational processes in plasma may enable earlier cancer detection, and might enable the assessment of cancer risk and etiology.
| S-EPMC9399180 | biostudies-literature
Project description:Telomeres are the protective arrays of tandem TTAGGG sequence and associated proteins at the termini of chromosomes. Telomeres shorten at each cell division due to the end-replication problem and are maintained above a critical threshold in malignant cancer cells to prevent cellular senescence or apoptosis. With the recent advances in massive parallel sequencing, assessing telomere content in the context of other cancer genomic aberrations becomes an attractive possibility. We present the first comprehensive analysis of telomeric DNA content change in tumors using whole-genome sequencing data from 235 pediatric cancers.To measure telomeric DNA content, we counted telomeric reads containing TTAGGGx4 or CCCTAAx4 and normalized to the average genomic coverage. Changes in telomeric DNA content in tumor genomes were clustered using a Bayesian Information Criterion to determine loss, no change, or gain. Using this approach, we found that the pattern of telomeric DNA alteration varies dramatically across the landscape of pediatric malignancies: telomere gain was found in 32% of solid tumors, 4% of brain tumors and 0% of hematopoietic malignancies. The results were validated by three independent experimental approaches and reveal significant association of telomere gain with the frequency of somatic sequence mutations and structural variations.Telomere DNA content measurement using whole-genome sequencing data is a reliable approach that can generate useful insights into the landscape of the cancer genome. Measuring the change in telomeric DNA during malignant progression is likely to be a useful metric when considering telomeres in the context of the whole genome.
| S-EPMC3580411 | biostudies-literature
Project description:BackgroundTumor mutational burden (TMB) is a promising biomarker for stratifying patient subpopulation who would benefit from immune checkpoint blockade (ICB) therapies. Although great efforts have been made for standardizing TMB measurement, mutation calling and TMB quantification can be challenging in samples with low tumor content including liquid biopsies. The effect of varying tumor content on TMB estimation by different assay methods has never been systematically investigated.MethodWe established a series of reference standard DNA samples derived from 11 pairs of tumor-normal matched human cell lines across different cancer types. Each tumor cell line was mixed with its matched normal at 0% (control), 1%, 2%, 5%, and 10% mass-to-mass ratio to mimic the clinical samples with low tumor content. TMB of these reference standards was evaluated by both ∼1000× whole-exome sequencing (wesTMB) and targeted panel sequencing (psTMB) at four different vendors. Both regression and classification analyses of TMB were performed for theoretical investigation and clinical practice purposes.ResultsLinear regression model was established that demonstrated in silico psTMB determined by regions of interest (ROI) as a great representative of wesTMB based on TCGA dataset. It was also true in our reference standard samples as the predicted psTMB interval based on the observed wesTMB captured the intended 90% of the in silico psTMB values. Although ∼1000× deep WES was applied, reference standard samples with less than 5% of tumor proportions are below the assay limit of detection (LoD) of wesTMB quantification. However, predicted wesTMB based on observed psTMB accurately classify (>0.97 AUC) for TMB high and low patient stratification even in samples with 2% of tumor content, which is more clinically relevant, as TMB determination should be a qualitative assay for TMB high and low patient classification. One targeted panel sequencing vendor using an optimized blood psTMB pipeline can further classify TMB status accurately (>0.82 AUC) in samples with only 1% of tumor content.ConclusionsWe developed a linear model to establish the quantitative correlation between wesTMB and psTMB. A set of DNA reference standards was produced in aid to standardize TMB measurements in samples with low tumor content across different targeted sequencing panels. This study is a significant contribution aiming to harmonize TMB estimation and extend its future application in clinical samples with low tumor content including liquid biopsy.
| S-EPMC8102856 | biostudies-literature
Project description:Purpose:To understand the clinical context of tumor mutational burden (TMB) when comparing a pan-cancer threshold and a cancer-specific threshold. Materials and Methods:Using whole exome sequencing (WES) data from primary tumors in The Cancer Genome Atlas (TCGA) (n=3,534) and advanced/metastatic tumors from Weill Cornell Medicine (WCM Advanced) (n=696), TMB status was determined using a pan-cancer and cancer-specific threshold. Survival curves, number of samples classified as TMB high, and predicted neoantigens were used to evaluate the differences between thresholds. Results:The distribution of TMB varied dramatically between cancer types. A cancer-specific threshold was able to adjust for the different TMB distributions, while the pan-cancer threshold was often too stringent. The dynamic nature of the cancer-specific threshold resulted in more tumors being classified as TMB high compared to the static pan-cancer threshold. Additionally, no significant difference in survival outcomes was found with the cancer-specific threshold compared to the pan-cancer one. Further, the cancer-specific threshold maintains higher predicted neoantigen load for the TMB high samples compared to the TMB low samples, even when the threshold is lower than the pan-cancer threshold. Conclusion:TMB is relative to the context of cancer type, metastatic state, and disease stage. Compared to a pan-cancer threshold, a cancer-specific threshold classifies more patients as TMB high while maintaining clinical outcomes that were not significantly different. Furthermore, the cancer-specific threshold identifies patients with a high number of predicted neoantigens. Due to the potential impact in cancer patient care, TMB status should be determined in a cancer-specific manner.
| S-EPMC6716608 | biostudies-other
Project description:Extraskeletal myxoid chondrosarcoma (EMC) is an ultra-rare cancer that makes up less than 3% of all soft tissue sarcomas. It most often arises in the soft tissues of the proximal limbs and has a higher incidence in males. Though EMC has a good prognosis, it has an indolent course with high rates of local recurrence as well as metastasis to the lungs. EMC is characterized in 70% of cases by an EWS1-NR4A3 translocation, leading to constitutive expression of NR4A3. Structural variants (SVs) in EMC, especially large-scale genomic alterations, have not been well studied and studies are severely limited by sample size. In this study, we describe Whole Genome Sequencing (WGS) of a rare case of matched EMC primary tumor, lung metastasis, and pelvic metastasis to identify genomic alterations. We examined somatic variants, copy number variants (CNVs), and larger scale SVs such as translocations and breakend points. While the primary tumor and lung metastasis had similar somatic variations and CNVs, the pelvic metastasis had more unique SVs with especially increased mutational burden of SVs in chromosome 2. This suggests that different molecular drivers appear in more advanced, relapsing EMC compared with the primary tumor and early lung metastasis. Genomic studies such as ours may identify novel molecular complexities in rare cancers that may be leveraged for therapeutic strategies and precision medicine.
| S-EPMC11285543 | biostudies-literature
Project description:BackgroundTumor mutational burden (TMB) is emerging as a promising biomarker in immune checkpoint inhibitor (ICI) therapy. Despite whole-exome sequencing (WES) being the gold standard for quantifying TMB, TMB is determined by selected targeted panels in most cases, and WES-derived TMB data are lacking due to the greater cost and complexity. Determining TMB thresholds is another issue that needs attention.MethodsA total of 309 patients who had received ICI therapy, representing five cancers (listed in "Results"), were recruited. Among them, 269 patients were evaluable for survival analysis. Tumor and matched blood samples from the patients were analyzed using WES and somatic mutations were determined. TMB is defined as the total number of somatic nonsynonymous mutations in the tumor exome in our study. The patients were divided into different TMB subgroups according to a common fixed number (10 mutations/Mb) or the top tertile within each tumor type.ResultsThe distribution of WES-derived median TMBs was highly variable across different tumor types, ranging from 2.71 (cholangiocarcinoma) to 2.97 (nervous system tumor), 3.69 (gastric cancer), 4.31 (hepatocellular carcinoma), and 4.64 [colorectal cancer (CRC)] mutations/Mb. In CRC, the survival benefit of TMB-high patients was significant using both the top tertile and the 10 mutations/Mb threshold. In hepatocellular carcinoma, the 10 mutations/Mb threshold showed an advantage over the top tertile threshold. Among patients with nervous system tumors, cholangiocarcinoma, and gastric cancer, no obvious survival differences were observed between the TMB-high and TMB-low groups with either TMB stratification approach.ConclusionsThe TMB threshold criterion may vary for different cancers. Our data suggest that TMB is unable to predict ICI benefit across all cancer types in Chinese patients. However, it may be an effective biomarker for predicting the clinical benefit of ICI therapy for patients with CRC.
| S-EPMC8506705 | biostudies-literature
Project description:BackgroundData are scarce about tumor mutational burden (TMB) as a biomarker in never smokers with non-small cell lung cancer (NSCLC).MethodsTMB was assessed by whole-genome sequencing (WGS) and compared with in silico reduced whole-exome sequencing (WES) and targeted commercial next-generation sequencing (NGS) gene panels in 92 paired tumor-normal samples from never smokers who underwent NSCLC resection with curative intent. Analyses were performed to test for association with survival after surgery and to identify the optimal prognostic TMB cutoff.ResultsTumors of never smokers with NSCLC had low TMB scores (median 1.57 mutations/Mb; range, 0.13-17.94). A TMB cutoff of 1.70 mutations/Mb was associated with a 5-year overall survival of 58% in the high-TMB (42% of cases) compared with 86% in low-TMB patients (Wald P = 0.0029). TMB scores from WGS and WES were highly correlated (Spearman ρ = 0.93, P < 2.2e-16). TMB scores from NGS panels demonstrated high intraindividual fluctuations and identified high-TMB patients with 65% concordance in average compared with WGS.ConclusionsIn resected NSCLC of never smokers, high TMB was associated with worse prognosis. WES provided a good estimate of TMB while targeted NGS panels seem to lack adequate depth and resolution in the setting of low mutation burden.ImpactTMB is a prognostic indicator of survival in resected NSCLC from individuals who never smoked. In this setting of low mutation counts, TMB can be accurately measured by WGS or WES, but not NGS panels.
| S-EPMC9720425 | biostudies-literature
Project description:In order to identify novel somatic mutations associated with classic BCR/ABL1-negative myeloproliferative neoplasms, we performed high-coverage genome sequencing of DNA from peripheral blood granulocytes and cultured skin fibroblasts from a patient with MPL W515K-positive primary myelofibrosis. The primary myelofibrosis genome had a low somatic mutation rate, consistent with that observed in similar hematopoietic tumor genomes. Interfacing of whole-genome DNA sequence data with RNA expression data identified three somatic mutations of potential functional significance: i) a nonsense mutation in CARD6, implicated in modulation of NF-kappaB activation; ii) a 19-base pair deletion involving a potential regulatory region in the 5'-untranslated region of BRD2, implicated in transcriptional regulation and cell cycle control; and iii) a non-synonymous point mutation in KIAA0355, an uncharacterized protein. Additional mutations in three genes (CAP2, SOX30, and MFRP) were also evident, albeit with no support for expression at the RNA level. Re-sequencing of these six genes in 178 patients with polycythemia vera, essential thrombocythemia, and myelofibrosis did not identify recurrent somatic mutations in these genes. Finally, we describe methods for reducing false-positive variant calls in the analysis of hematologic malignancies with a low somatic mutation rate. This trial is registered with ClinicalTrials.gov (NCT01108159).
| S-EPMC3815168 | biostudies-literature
Project description:Genomic characterization of pediatric acute lymphoblastic leukemia (ALL) has identified distinct patterns of genes and pathways altered in patients with well-defined genetic aberrations. To extend the spectrum of known somatic variants in ALL, we performed whole genome and transcriptome sequencing of three B-cell precursor patients, of which one carried the t(12;21)ETV6-RUNX1 translocation and two lacked a known primary genetic aberration, and one T-ALL patient. We found that each patient had a unique genome, with a combination of well-known and previously undetected genomic aberrations. By targeted sequencing in 168 patients, we identified KMT2D and KIF1B as novel putative driver genes. We also identified a putative regulatory non-coding variant that coincided with overexpression of the growth factor MDK. Our results contribute to an increased understanding of the biological mechanisms that lead to ALL and suggest that regulatory variants may be more important for cancer development than recognized to date. The heterogeneity of the genetic aberrations in ALL renders whole genome sequencing particularly well suited for analysis of somatic variants in both research and diagnostic applications.
| S-EPMC4309499 | biostudies-literature
Project description:BackgroundCirculating cell-free DNA (cfDNA) in the plasma of cancer patients contains cell-free tumour DNA (ctDNA) derived from tumour cells and it has been widely recognized as a non-invasive source of tumour DNA for diagnosis and prognosis of cancer. Molecular profiling of ctDNA is often performed using targeted sequencing or low-coverage whole genome sequencing (WGS) to identify tumour specific somatic mutations or somatic copy number aberrations (sCNAs). However, these approaches cannot efficiently detect all tumour-derived genomic changes in ctDNA.MethodsWe performed WGS analysis of cfDNA from 4 breast cancer patients and 2 patients with benign tumours. We sequenced matched germline DNA for all 6 patients and tumour samples from the breast cancer patients. All samples were sequenced on Illumina HiSeqXTen sequencing platform and achieved approximately 30x, 60x and 100x coverage on germline, tumour and plasma DNA samples, respectively.ResultsThe mutational burden of the plasma samples (1.44 somatic mutations/Mb of genome) was higher than the matched tumour samples. However, 90% of high confidence somatic cfDNA variants were not detected in matched tumour samples and were found to comprise two background plasma mutational signatures. In contrast, cfDNA from the di-nucleosome fraction (300 bp-350 bp) had much higher proportion (30%) of variants shared with tumour. Despite high coverage sequencing we were unable to detect sCNAs in plasma samples.ConclusionsDeep sequencing analysis of plasma samples revealed higher fraction of unique somatic mutations in plasma samples, which were not detected in matched tumour samples. Sequencing of di-nucleosome bound cfDNA fragments may increase recovery of tumour mutations from plasma.
| S-EPMC8772083 | biostudies-literature