Genomic sequencing in cancer.
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ABSTRACT:
SUBMITTER: Tuna M
PROVIDER: S-EPMC3622788 | biostudies-literature | 2013 Nov
REPOSITORIES: biostudies-literature
Publications
Genomic sequencing has provided critical insights into the etiology of both simple and complex diseases. The enormous reductions in cost for whole genome sequencing have allowed this technology to gain increasing use. Whole genome analysis has impacted research of complex diseases including cancer by allowing the systematic analysis of entire genomes in a single experiment, thereby facilitating the discovery of somatic and germline mutations, and identification of the insertions, deletions, and ...[more]
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Project description:BackgroundDespite the rapid uptake of genomic technologies within cancer care, few studies provide detailed information on the costs of sequencing across different applications. The objective of the study was to examine and categorise the complete costs involved in genomic sequencing for a range of applications within cancer settings.MethodsWe performed a cost-analysis using gross and micro-costing approaches for genomic sequencing performed during 2017/2018 across different settings in Brisbane, Australia. Sequencing was undertaken for patients with lung, breast, oesophageal cancers, melanoma or mesothelioma. Aggregated resource data were captured for a total of 1433 patients and point estimates of per patient costs were generated. Deterministic sensitivity analyses addressed the uncertainty in the estimates. Estimated costs to the public health system for resources were categorised into seven distinct activities in the sequencing process: sampling, extraction, library preparation, sequencing, analysis, data storage and clinical reporting. Costs were also aggregated according to labour, consumables, testing, equipment and 'other' categories.ResultsThe per person costs were AU$347-429 (2018 US$240-297) for targeted panels, AU$871-$2788 (2018 US$604-1932) for exome sequencing, and AU$2895-4830 (2018 US$2006-3347) for whole genome sequencing. Cost proportions were highest for library preparation/sequencing materials (average 76.8% of total costs), sample extraction (8.1%), data analysis (9.2%) and data storage (2.6%). Capital costs for the sequencers were an additional AU$34-197 (2018 US$24-67) per person.ConclusionsTotal costs were most sensitive to consumables and sequencing activities driven by commercial prices. Per person sequencing costs for cancer are high when tumour/blood pairs require testing. Using the natural steps involved in sequencing and categorising resources accordingly, future evaluations of costs or cost-effectiveness of clinical genomics across cancer projects could be more standardised and facilitate easier comparison of cost drivers.
| S-EPMC7268398 | biostudies-literature
Project description:Pancreatic cancer is a multiple genetic disorder with many mutations identified during the progression. Two mouse pancreatic cancer cell lines were established which showed different phenotype in vivo: a non-metastatic cell line, Panc02, and a highly metastatic cell line, Panc02-H7, a derivative of Panc02. In order to investigate whether the genetic mutations of key genes in pancreatic cancer such as KRAS, TP53 (p53), CDKN2A (p16), SMAD4, ZIP4, and PDX-1 contribute to the phenotypic difference of these two mouse pancreatic cancer cells, we sequenced the exonic regions of these key genes in both cell lines and in the normal syngeneic mouse pancreas and compared them with the reference mouse genome sequence. The exons of KRAS, SMAD4, CDKN2A (p16), TP53 (p53), ZIP4, and PDX-1 genes were amplified and the genotype of these genes was determined by Sanger sequencing. The sequences were analyzed with Sequencher software. A mutation in SMAD4 was identified in both cell lines. This homozygote G to T mutation in the first position of codon 174 (GAA) generated a stop codon resulting in the translation of a truncated protein. Further functional analysis indicates that different TGF-?/SMAD signaling pathways were involved in those two mouse cell lines, which may explain the phonotypic difference between the two cells. A single nucleotide polymorphism (SNP) in KRAS gene (TAT to TAC at codon 32) was also identified in the normal pancreas DNA of the syngenic mouse and in both derived tumoral Panc02 and Panc02-H7 cells. No mutation or SNP was found in CDKN2A (p16), TP53 (p53), ZIP4, and PDX-1 genes in these two cell lines. The absence of mutations in genes such as KRAS, TP53, and CDKN2A, which are considered as key genes in the development of human pancreatic cancer suggests that SMAD4 might play a central and decisive role in mouse pancreatic cancer. These results also suggest that other mechanisms are involved in the substantial phenotypic difference between these two mouse pancreatic cancer cell lines. Further studies are warranted to elucidate the molecular pathways that lead to the aggressive metastatic potential of Panc02-H7.
| S-EPMC3799885 | biostudies-literature
Project description:Metastatic colorectal cancers (mCRCs) are clinically heterogeneous, but the genomic basis of this variability remains poorly understood. We performed prospective targeted sequencing of 1,134 CRCs. We identified splice alterations in intronic regions of APC and large in-frame deletions in CTNNB1, increasing oncogenic WNT pathway alterations to 96% of CRCs. Right-sided primary site in microsatellite stable mCRC was associated with shorter survival, older age at diagnosis, increased mutations, and enrichment of oncogenic alterations in KRAS, BRAF, PIK3CA, AKT1, RNF43, and SMAD4 compared with left-sided primaries. Left-sided tumors frequently had no identifiable genetic alteration in mitogenic signaling, but exhibited higher mitogenic ligand expression. Our results suggest different pathways to tumorigenesis in right- and left-sided microsatellite stable CRC that may underlie clinical differences.
| S-EPMC5765991 | biostudies-literature
Project description:AIMS: Small cell lung cancer (SCLC) carries a poor prognosis, and the systemic therapies currently used as treatments are only modestly effective, as demonstrated by a low 5-year survival at only ?5%. In this retrospective collected from March 2013 to study, we performed comprehensive genomic profiling of 98 small cell undifferentiated lung cancer (SCLC) samples to identify potential targets of therapy not currently searched for in routine clinical practice. METHODS: DNA from 98 SCLC was sequenced to high, uniform coverage (Illumina HiSeq 2500) and analysed for all classes of genomic alterations. RESULTS: A total of 386 alterations were identified for an average of 3.9 alterations per tumour (range 1–10). Fifty-two (53%) of cases harboured at least 1 actionable alteration with the potential to personalise therapy including base substitutions, amplifications or homozygous deletions in RICTOR (10%), KIT (7%), PIK3CA (6%), EGFR (5%), PTEN (5%), KRAS (5%), MCL1 (4%), FGFR1 (4%), BRCA2, (4%), TSC1 (3%), NF1 (3%), EPHA3 (3%) and CCND1. The most common non-actionable genomic alterations were alterations in TP53 (86% of SCLC cases), RB1 (54%) and MLL2 (17%). CONCLUSIONS: Greater than 50% of the SCLC cases harboured at least one actionable alteration. Given the limited treatment options and poor prognosis of patients with SCLC, comprehensive genomic profiling has the potential to identify new treatment paradigms and meet an unmet clinical need for this disease.
| S-EPMC4145440 | biostudies-other
Project description:It is well established that genomic alterations play an essential role in oncogenesis, disease progression, and response of tumors to therapeutic intervention. The advances of next-generation sequencing technologies (NGS) provide unprecedented capabilities to scan genomes for changes such as mutations, deletions, and alterations of chromosomal copy number. However, the cost of full-genome sequencing still prevents the routine application of NGS in many areas. Capturing and sequencing the coding exons of genes (the "exome") can be a cost-effective approach for identifying changes that result in alteration of protein sequences. We applied an exome-sequencing technology (Roche Nimblegen capture paired with 454 sequencing) to identify sequence variation and mutations in eight commonly used cancer cell lines from a variety of tissue origins (A2780, A549, Colo205, GTL16, NCI-H661, MDA-MB468, PC3, and RD). We showed that this technology can accurately identify sequence variation, providing ?95% concordance with Affymetrix SNP Array 6.0 performed on the same cell lines. Furthermore, we detected 19 of the 21 mutations reported in Sanger COSMIC database for these cell lines. We identified an average of 2,779 potential novel sequence variations/mutations per cell line, of which 1,904 were non-synonymous. Many non-synonymous changes were identified in kinases and known cancer-related genes. In addition we confirmed that the read-depth of exome sequence data can be used to estimate high-level gene amplifications and identify homologous deletions. In summary, we demonstrate that exome sequencing can be a reliable and cost-effective way for identifying alterations in cancer genomes, and we have generated a comprehensive catalogue of genomic alterations in coding regions of eight cancer cell lines. These findings could provide important insights into cancer pathways and mechanisms of resistance to anti-cancer therapies.
| S-EPMC3118809 | biostudies-literature
Project description:BACKGROUND:Genome rearrangements are critical oncogenic driver events in many malignancies. However, the identification and resolution of the structure of cancer genomic rearrangements remain challenging even with whole genome sequencing. METHODS:To identify oncogenic genomic rearrangements and resolve their structure, we analyzed linked read sequencing. This approach relies on a microfluidic droplet technology to produce libraries derived from single, high molecular weight DNA molecules, 50 kb in size or greater. After sequencing, the barcoded sequence reads provide long range genomic information, identify individual high molecular weight DNA molecules, determine the haplotype context of genetic variants that occur across contiguous megabase-length segments of the genome and delineate the structure of complex rearrangements. We applied linked read sequencing of whole genomes to the analysis of a set of synchronous metastatic diffuse gastric cancers that occurred in the same individual. RESULTS:When comparing metastatic sites, our analysis implicated a complex somatic rearrangement that was present in the metastatic tumor. The oncogenic event associated with the identified complex rearrangement resulted in an amplification of the known cancer driver gene FGFR2. With further investigation using these linked read data, the FGFR2 copy number alteration was determined to be a deletion-inversion motif that underwent tandem duplication, with unique breakpoints in each metastasis. Using a three-dimensional organoid tissue model, we functionally validated the metastatic potential of an FGFR2 amplification in gastric cancer. CONCLUSIONS:Our study demonstrates that linked read sequencing is useful in characterizing oncogenic rearrangements in cancer metastasis.
| S-EPMC5477353 | biostudies-literature
Project description:Critical cancer mutations are often regional and mosaic, confounding the efficacy of targeted therapeutics. Single cell mRNA sequencing (scRNA-seq) has enabled unprecedented studies of intra-tumor heterogeneity and its role in cancer progression, metastasis, and treatment resistance. When coupled with DNA sequencing, scRNA-seq allows one to infer the in vivo impact of genomic alterations on gene expression. This combination can be used to reliably distinguish neoplastic from non-neoplastic cells, to correlate paracrine-signaling pathways between neoplastic cells and stroma, and to map expression signatures to inferred clones and phylogenies. Here we review recent advances in scRNA-seq, with a special focus on cancer. We discuss the challenges and prospects of combining scRNA-seq with DNA sequencing to assess intra-tumor heterogeneity.
| S-EPMC5450061 | biostudies-literature
Project description:Cancer genome sequencing is being used at an increasing rate to identify actionable driver mutations that can inform therapeutic intervention strategies. A comparison of two of the most prominent cancer genome sequencing databases from different institutes (Cancer Cell Line Encyclopedia and Catalogue of Somatic Mutations in Cancer) revealed marked discrepancies in the detection of missense mutations in identical cell lines (57.38% conformity). The main reason for this discrepancy is inadequate sequencing of GC-rich areas of the exome. We have therefore mapped over 400 regions of consistent inadequate sequencing (cold-spots) in known cancer-causing genes and kinases, in 368 of which neither institute finds mutations. We demonstrate, using a newly identified PAK4 mutation as proof of principle, that specific targeting and sequencing of these GC-rich cold-spot regions can lead to the identification of novel driver mutations in known tumor suppressors and oncogenes. We highlight that cross-referencing between genomic databases is required to comprehensively assess genomic alterations in commonly used cell lines and that there are still significant opportunities to identify novel drivers of tumorigenesis in poorly sequenced areas of the exome. Finally, we assess other reasons for the observed discrepancy, such as variations in dbSNP filtering and the acquisition/loss of mutations, to give explanations as to why there is a discrepancy in pharmacogenomic studies, given recent concerns with poor reproducibility of data.
| S-EPMC4247168 | biostudies-literature
Project description:Our knowledge of Neanderthals is based on a limited number of remains and artifacts from which we must make inferences about their biology, behavior, and relationship to ourselves. Here, we describe the characterization of these extinct hominids from a new perspective, based on the development of a Neanderthal metagenomic library and its high-throughput sequencing and analysis. Several lines of evidence indicate that the 65,250 base pairs of hominid sequence so far identified in the library are of Neanderthal origin, the strongest being the ascertainment of sequence identities between Neanderthal and chimpanzee at sites where the human genomic sequence is different. These results enabled us to calculate the human-Neanderthal divergence time based on multiple randomly distributed autosomal loci. Our analyses suggest that on average the Neanderthal genomic sequence we obtained and the reference human genome sequence share a most recent common ancestor approximately 706,000 years ago, and that the human and Neanderthal ancestral populations split approximately 370,000 years ago, before the emergence of anatomically modern humans. Our finding that the Neanderthal and human genomes are at least 99.5% identical led us to develop and successfully implement a targeted method for recovering specific ancient DNA sequences from metagenomic libraries. This initial analysis of the Neanderthal genome advances our understanding of the evolutionary relationship of Homo sapiens and Homo neanderthalensis and signifies the dawn of Neanderthal genomics.
| S-EPMC2583069 | biostudies-other
Project description:BackgroundWhile next generation sequencing has enhanced our understanding of the biological basis of malignancy, current knowledge on global practices for sequencing cancer samples is limited. To address this deficiency, we developed a survey to provide a snapshot of current sequencing activities globally, identify barriers to data sharing and use this information to develop sustainable solutions for the cancer research community.MethodsA multi-item survey was conducted assessing demographics, clinical data collection, genomic platforms, privacy/ethics concerns, funding sources and data sharing barriers for sequencing initiatives globally. Additionally, respondents were asked as to provide the primary intent of their initiative (clinical diagnostic, research or combination).ResultsOf 107 initiatives invited to participate, 59 responded (response rate = 55%). Whole exome sequencing (P = 0.03) and whole genome sequencing (P = 0.01) were utilized less frequently in clinical diagnostic than in research initiatives. Procedures to identify cancer-specific variants were heterogeneous, with bioinformatics pipelines employing different mutation calling/variant annotation algorithms. Measurement of treatment efficacy varied amongst initiatives, with time on treatment (57%) and RECIST (53%) being the most common; however, other parameters were also employed. Whilst 72% of initiatives indicated data sharing, its scope varied, with a number of restrictions in place (e.g. transfer of raw data). The largest perceived barriers to data harmonization were the lack of financial support (P < 0.01) and bioinformatics concerns (e.g. lack of interoperability) (P = 0.02). Capturing clinical data was more likely to be perceived as a barrier to data sharing by larger initiatives than by smaller initiatives (P = 0.01).ConclusionsThese results identify the main barriers, as perceived by the cancer sequencing community, to effective sharing of cancer genomic and clinical data. They highlight the need for greater harmonization of technical, ethical and data capture processes in cancer sample sequencing worldwide, in order to support effective and responsible data sharing for the benefit of patients.
| S-EPMC5406763 | biostudies-literature