Robust in-silico identification of cancer cell lines based on next generation sequencing.
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ABSTRACT:
SUBMITTER: Otto R
PROVIDER: S-EPMC5470969 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Cancer cell lines (CCL) are an integral part of modern cancer research but are susceptible to misidentification. The increasing popularity of sequencing technologies motivates the in-silico identification of CCLs based on their mutational fingerprint, but care must be taken when identifying heterogeneous data. We recently developed the proof-of-concept Uniquorn 1 method which could reliably identify heterogeneous sequencing data from selected sequencing technologies. Here we present Uniquorn 2, a generic and robust in-silico identification method for CCLs with DNA/RNA-seq and panel-seq information. We benchmarked Uniquorn 2 by cross-identifying 1612?RNA and 3596 panel-sized NGS profiles derived from 1516 CCLs, five repositories, four technologies and three major cancer panel-designs. Our method achieves an accuracy of 96% for RNA-seq and 95% for mixed DNA-seq and RNA-seq identification. Even for a panel of only 94 cancer-related genes, accuracy remains at 82% but decreases when using smaller panels. Uniquorn 2 is freely available as R-Bioconductor-package 'Uniquorn'.
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Project description:Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has recently become a novel pandemic event following the swine flu that occurred in 2009, which was caused by the influenza A virus (H1N1 subtype). The accurate identification of the huge number of samples during a pandemic still remains a challenge. In this study, we integrate two technologies, next-generation sequencing and cloud computing, into an optimized workflow version that uses a specific identification algorithm on the designated cloud platform. We use 182 samples (92 for COVID-19 and 90 for swine flu) with short-read sequencing data from two open-access datasets to represent each pandemic and evaluate our workflow performance based on an index specifically created for SARS-CoV-2 or H1N1. Results show that our workflow could differentiate cases between the two pandemics with a higher accuracy depending on the index used, especially when the index that exclusively represented each dataset was used. Our workflow substantially outperforms the original complete identification workflow available on the same platform in terms of time and cost by preserving essential tools internally. Our workflow can serve as a powerful tool for the robust identification of cases and, thus, aid in controlling the current and future pandemics.
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Project description:Although targeted therapy has emerged as an effective treatment strategy for non-small cell lung cancer (NSCLC), some patients cannot benefit from such therapy due to the limited number of therapeutic targets. The present study aimed to identify mutated genes associated with clinicopathological characteristics and prognosis and to screen for mutations that are not concurrent with applicable drug target sites in patients with NSCLC. Tumor tissue and blood samples were obtained from 97 patients with NSCLC. A lung cancer-specific panel of 55 genes was established and analyzed using next-generation sequencing (NGS). The results obtained from the clinical cohort were compared with the NSCLC dataset from The Cancer Genome Atlas (TCGA). Subsequently, 25 driver genes were identified by taking the intersection of the 55 lung-cancer-specific genes with three databases, namely, the Catalog of Somatic Mutations in Cancer database, the Network of Cancer Genes database and Vogelstein's list. Functional annotation and protein-protein interaction analysis were conducted on these 25 driver genes. The χ2 test and logistic regression were used to evaluate the association between mutations in the 25 driver genes and the clinicopathological characteristics of 97 patients, and phosphatase and tensin homolog (PTEN) and kirsten rat sarcoma viral oncogene homolog (KRAS) were associated with stage at diagnosis and sex, respectively, while epidermal growth factor receptor (EGFR) was associated with sex, stage at diagnosis, metastasis, CEA and CYFRA21-1. Moreover, the association between the 25 driver gene mutations and overall survival were examined using Cox regression analysis. Age and Notch homolog 2 (NOTCH2) mutations were independent prognostic factors in TCGA dataset. The correlations between statistically significant mutations in EGFR, KRAS, PTEN and NOTCH2 were further examined, both in the clinical data and TCGA dataset. There was a negative correlation between EGFR and NOTCH2 mutations (correlation coefficient, -0.078; P=0.027). Thus, the present study highlights the importance of NOTCH2 mutations and might provide novel therapeutic options for patients with NSCLC who do not harbor EGFR mutations.
| S-EPMC8200943 | biostudies-literature
Project description:Exosomes are nanosized (30-100 nm) membrane vesicles secreted by most cell types. Exosomes have been found to contain various RNA species including miRNA, mRNA and long non-protein coding RNAs. A number of cancer cells produce elevated levels of exosomes. Because exosomes have been isolated from most body fluids they may provide a source for non-invasive cancer diagnostics. Transcriptome profiling that uses deep-sequencing technologies (RNA-Seq) offers enormous amount of data that can be used for biomarkers discovery, however, in case of exosomes this approach was applied only for the analysis of small RNAs. In this study, we utilized RNA-Seq technology to analyze RNAs present in microvesicles secreted by human breast cancer cell lines. Exosomes were isolated from the media conditioned by two human breast cancer cell lines, MDA-MB-231 and MDA-MB-436. Exosomal RNA was profiled using the Ion Torrent semiconductor chip-based technology. Exosomes were found to contain various classes of RNA with the major class represented by fragmented ribosomal RNA (rRNA), in particular 28S and 18S rRNA subunits. Analysis of exosomal RNA content revealed that it reflects RNA content of the donor cells. Although exosomes produced by the two cancer cell lines shared most of the RNA species, there was a number of non-coding transcripts unique to MDA-MB-231 and MDA-MB-436 cells. This suggests that RNA analysis might distinguish exosomes produced by low metastatic breast cancer cell line (MDA-MB-436) from that produced by highly metastatic breast cancer cell line (MDA-MB-231). The analysis of gene ontologies (GOs) associated with the most abundant transcripts present in exosomes revealed significant enrichment in genes encoding proteins involved in translation and rRNA and ncRNA processing. These GO terms indicate most expressed genes for both, cellular and exosomal RNA. For the first time, using RNA-seq, we examined the transcriptomes of exosomes secreted by human breast cancer cells. We found that most abundant exosomal RNA species are the fragments of 28S and 18S rRNA subunits. This limits the number of reads from other RNAs. To increase the number of detectable transcripts and improve the accuracy of their expression level the protocols allowing depletion of fragmented rRNA should be utilized in the future RNA-seq analyses on exosomes. Present data revealed that exosomal transcripts are representative of their cells of origin and thus could form basis for detection of tumor specific markers.
| S-EPMC3828613 | biostudies-literature
Project description:Hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) remains a global health concern, and HBV proteins may be ideal targets for T cell-based immunotherapy for HCC. There is a need for fast and efficient identification of HBV-specific T cell receptors (TCRs) for the development of TCR-transduced T (TCR-T) cell-based immunotherapy. Two widely employed TCR identification approaches, T cell clonal expansion and single-cell sequencing, involve a TCR singularization process for the direct identification of Vα and Vβ pairs of TCR chains. Clonal expansion of T cells is well known to have tedious time and effort requirements due to the use of T cell cultures, whereas single-cell sequencing is limited by the requirements of cell sorting and the preparation of a single-cell immune-transcriptome library as well as the massive cost of the whole procedure. Here, we present a next-generation sequencing (NGS)-based HBV-specific TCR identification that does not require the TCR singularization process. Conclusion: Two pairing strategies, ranking-based strategy and α-β chain mixture-based strategy, have proved to be useful for NGS-based TCR identification, particularly for polyclonal T cells purified by a peptide-major histocompatibility complex (pMHC) multimer-based approach. Functional evaluation confirmed the specificity and avidity of two identified HBV-specific TCRs, which may potentially be used to produce TCR-T cells to treat patients with HBV-related HCC.
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Project description:NGPS is a method for de-novo, full-length protein sequencing in high throughput. The method is based on cleavage of the protein at semi-random sites by microwave-assisted acid hydrolysis (MAAH), enrichment of LC-MS/MS amenable peptides from the hydrolysate by solid-phase-extraction, LC-MS/MS analysis, de-novo long peptide tag sequencing of resulting peptides and assembly of peptide tags into consensus contigs.
2017-04-03 | PXD003804 | Pride
Project description:Improvements in cost and speed of next generation sequencing (NGS) have provided a new pathway for delivering disease diagnosis, molecular typing, and detection of antimicrobial resistance (AMR). Numerous published methods and protocols exist, but a lack of harmonisation has hampered meaningful comparisons between results produced by different methods/protocols vital for global genomic diagnostics and surveillance. As an exemplar, this study evaluated the sensitivity and specificity of five well-established in-silico AMR detection software where the genotype results produced from running a panel of 436 Escherichia coli were compared to their AMR phenotypes, with the latter used as gold-standard. The pipelines exploited previously known genotype-phenotype associations. No significant differences in software performance were observed. As a consequence, efforts to harmonise AMR predictions from sequence data should focus on: (1) establishing universal minimum to assess performance thresholds (e.g. a control isolate panel, minimum sensitivity/specificity thresholds); (2) standardising AMR gene identifiers in reference databases and gene nomenclature; (3) producing consistent genotype/phenotype correlations. The study also revealed limitations of in-silico technology on detecting resistance to certain antimicrobials due to lack of specific fine-tuning options in bioinformatics tool or a lack of representation of resistance mechanisms in reference databases. Lastly, we noted user friendliness of tools was also an important consideration. Therefore, our recommendations are timely for widespread standardisation of bioinformatics for genomic diagnostics and surveillance globally.
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Project description:Combining single-cell methods and next-generation sequencing should provide a powerful means to understand single-cell biology and obviate the effects of sample heterogeneity. Here we report a single-cell identification method and seamless cancer gene profiling using semiconductor-based massively parallel sequencing. A549 cells (adenocarcinomic human alveolar basal epithelial cell line) were used as a model. Single-cell capture was performed using laser capture microdissection (LCM) with an Arcturus® XT system, and a captured single cell and a bulk population of A549 cells (≈ 10(6) cells) were subjected to whole genome amplification (WGA). For cell identification, a multiplex PCR method (AmpliSeq™ SNP HID panel) was used to enrich 136 highly discriminatory SNPs with a genotype concordance probability of 10(31-35). For cancer gene profiling, we used mutation profiling that was performed in parallel using a hotspot panel for 50 cancer-related genes. Sequencing was performed using a semiconductor-based bench top sequencer. The distribution of sequence reads for both HID and Cancer panel amplicons was consistent across these samples. For the bulk population of cells, the percentages of sequence covered at coverage of more than 100 × were 99.04% for the HID panel and 98.83% for the Cancer panel, while for the single cell percentages of sequence covered at coverage of more than 100 × were 55.93% for the HID panel and 65.96% for the Cancer panel. Partial amplification failure or randomly distributed non-amplified regions across samples from single cells during the WGA procedures or random allele drop out probably caused these differences. However, comparative analyses showed that this method successfully discriminated a single A549 cancer cell from a bulk population of A549 cells. Thus, our approach provides a powerful means to overcome tumor sample heterogeneity when searching for somatic mutations.
| S-EPMC4887956 | biostudies-literature
Project description:The taxonomical identification merely based on morphology is often difficult for ancient remains. Therefore, universal or specific PCR amplification followed by sequencing and BLAST (basic local alignment search tool) search has become the most frequently used genetic-based method for the species identification of biological samples, including ancient remains. However, it is challenging for these methods to process extremely ancient samples with severe DNA fragmentation and contamination. Here, we applied whole-genome sequencing data from 12 ancient samples with ages ranging from 2.7 to 700 kya to compare different mapping algorithms, and tested different reference databases, mapping similarities and query coverage to explore the best method and mapping parameters that can improve the accuracy of ancient mammal species identification. The selected method and parameters were tested using 152 ancient samples, and 150 of the samples were successfully identified. We further screened the BLAST-based mapping results according to the deamination characteristics of ancient DNA to improve the ability of ancient species identification. Our findings demonstrate a marked improvement to the normal procedures used for ancient species identification, which was achieved through defining the mapping and filtering guidelines to identify true ancient DNA sequences. The guidelines summarized in this study could be valuable in archaeology, paleontology, evolution, and forensic science. For the convenience of the scientific community, we wrote a software script with Perl, called AncSid, which is made available on GitHub.
| S-EPMC6679096 | biostudies-literature
Project description:Introduction Colorectal cancer (CRC) is one of the leading causes of death and illness in the general population. Although the incidence of CRC is steadily decreasing worldwide, it is being diagnosed more in individuals under 50 years of age. Multiple disease-causing variants have been reported to be involved in the development of CRC. This study aimed to investigate the molecular and clinical characteristics of Thai patients with CRC. Methods NGS-based multigene cancer panel testing was performed on 21 unrelated patients. Target enrichment was performed using a custom-designed Ion AmpliSeq on-demand panel. Thirty-six genes associated with CRC and other cancer were analyzed for variant detection. Results Sixteen variants (five nonsense, eight missense, two deletions, and one duplication) in nine genes were identified in 12 patients. Eight (66.7%) patients harboring disease-causing deleterious variants in genes APC, ATM, BRCA2, MSH2, and MUTYH. One of the eight patients also carried additional heterozygous variants in genes ATM, BMPR1A, and MUTYH. In addition, four patients carried variants of uncertain significance in genes APC, MLH1, MSH2, STK11, and TP53. Among all detected genes, APC was the most frequent causative gene observed in CRC patients, which is consistent with previous reports. Conclusion This study demonstrated the comprehensive molecular and clinical characterization of CRC patients. These findings showed the benefits of using multigene cancer panel sequencing for pathogenic gene detection and showed the prevalence of genetic aberrations in Thai patients with CRC.
| S-EPMC10267666 | biostudies-literature