Academic literature on the topic 'Limited Cell Sequencing'

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Journal articles on the topic "Limited Cell Sequencing"

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Mosier, Charles T., and Farzad Mahmoodi. "Work sequencing in a manufacturing cell with limited labour constraints." International Journal of Production Research 40, no. 12 (2002): 2883–99. http://dx.doi.org/10.1080/00207540210136577.

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Zhao, Xin, Shouguo Gao, Sachiko Kajigaya, et al. "Single-Cell RNA Sequencing of Healthy Human Marrow Hematopoietic Cells." Blood 134, Supplement_1 (2019): 4997. http://dx.doi.org/10.1182/blood-2019-123249.

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Hematopoiesis, especially the early events of blood cell formation, has been mainly studied in bulk populations of cells and using progenitor colony formation assays; the familiar hierarchy of cell lineage differentiation and maturation, and associated regulatory factors have been inferred from these methods. However, these techniques often require extensive manipulation of cells, the exposure of cells to unphysiological conditions, aggregation of heterogeneous populations, and prior assumptions concerning cell function and gene expression. New single cell methodology avoids many of these potential experimental deficiencies. Here we have applied single-cell RNA-sequencing(scRNA-seq)to fresh human bone marrow CD34+cells: we profiled 391 single hematopoietic stem/progenitor cells (HSPCs) from four healthy donors by deep sequencing of individual cell transcriptomes. An average of 4560 protein-coding genes were detected per cell. Cells clustered into six distinct groups, which could be assigned to known HSPC subpopulations (Fig 1A), based on expression of lineage-specific genes. Lin-CD34+CD38+cells emerged as locally clustered cell populations (Clusters 2-6, including MEP, GMP, ETP and ProB), while Lin-CD34+CD38-cells formed a single cluster (HSC/MLP). Reconstruction of differentiation trajectories by transcription in single cells revealed four committed lineages derived from stem cell compartment. The earliest fate split separates MEPs from MLPs, which partition further into lymphoid, and granulocyte-monocyte progenitors (Fig 1B). The overall pattern differs from the classical hematopoietic model describing a single binary split between myeloid and lymphoid differentiation immediately downstream of multipotent cells. However, our data align well to recently published scRNA-seq data showing sequential commitment of stem cells to the lymphoid, erythroid/megakaryocytic, and finally myeloid lineages (Setty M, Nat Biotechnol2019; Pellin D, Nat Commun2019). We further examined trends in gene expression in each of the branches and found dynamic expression changes underlying cell fate during early lineage differentiation (Fig 1C). As confirmation, PCA plot of published single-cell assay for transposase-accessible chromatin (scATAC-seq) shows similar differentiation pattern. After projecting scATAC-seq data to our transcriptomic clusters' specific genes, MEP-dependent and myeloid/lymphoid-dependent genes were located on opposing sides of the PC1 with same direction (Fig 1D), indicating transcriptome and epigenome work on differentiation in concerted effort. scRNA-seq provides opportunities for discovery and characterization at the molecular levels of early HSC differentiation and developmental intermediates, retrospectively, without the need to isolate purified populations. However, information inferred from scRNA-seq may be obscured due to missing reads and limited cell numbers. More cells would provide greater detail and higher resolution mapping.Given the low frequency of megakaryocyte progenitors within the CD34+cells as well as the neglected Lin-CD34-BM compartment, we could not fully resolve the separation and maturation of all lineages. Nonetheless, we found good coverage of cell types and a similar HSPC Atlas as other published studies (Velten L, Nat Cell Biol2017; Pellin D, Nat Commun2019)despite our limited numbers of starting cells. Our data accurately reflect the pattern of normal hematopoiesis, which may help to revise and refine characterization of hematopoiesis and provide a general reference framework to investigate the complexities of blood cell production at single-cell resolution - especially when cell numbers are limited, as from patient samples and in marrow failure syndromes. Fig. 1scRNA-seq of human hematopoietic stem and progenitor cells. (A) Unsupervised hierarchical clustering of gene expression data for all cells. C1, HSC/MLP; C2, MEP; C3, GMP; C4, ProB; C5-C6, ETP. (B)Visualization of the HSPC continuum. Each ball represents one cell.(C) Large-scale shifts in gene expression during development of hematopoietic cells.Bars on top indicate locations of individual cells, colored by stages of development, along this developmental trajectory. (D) Projections of five transcriptomic gene modules onto PCA of scATAC-seq data (Buenrostro JD,Cell 2018). Each dot represents a transcriptional factor. Figure 1 Disclosures No relevant conflicts of interest to declare.
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Sahoo, Malaya K., Susanna K. Tan, Sharon F. Chen, et al. "Limited Variation in BK Virus T-Cell Epitopes Revealed by Next-Generation Sequencing." Journal of Clinical Microbiology 53, no. 10 (2015): 3226–33. http://dx.doi.org/10.1128/jcm.01385-15.

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BK virus (BKV) infection causing end-organ disease remains a formidable challenge to the hematopoietic cell transplant (HCT) and kidney transplant fields. As BKV-specific treatments are limited, immunologic-based therapies may be a promising and novel therapeutic option for transplant recipients with persistent BKV infection. Here, we describe a whole-genome, deep-sequencing methodology and bioinformatics pipeline that identify BKV variants across the genome and at BKV-specific HLA-A2-, HLA-B0702-, and HLA-B08-restricted CD8 T-cell epitopes. BKV whole genomes were amplified using long-range PCR with four inverse primer sets, and fragmentation libraries were sequenced on the Ion Torrent Personal Genome Machine (PGM). An error model and variant-calling algorithm were developed to accurately identify rare variants. A total of 65 samples from 18 pediatric HCT and kidney recipients with quantifiable BKV DNAemia underwent whole-genome sequencing. Limited genetic variation was observed. The median number of amino acid variants identified per sample was 8 (range, 2 to 37; interquartile range, 10), with the majority of variants (77%) detected at a frequency of <5%. When normalized for length, there was no statistical difference in the median number of variants across all genes. Similarly, the predominant virus population within samples harbored T-cell epitopes similar to the reference BKV strain that was matched for the BKV genotype. Despite the conservation of epitopes, low-level variants in T-cell epitopes were detected in 77.7% (14/18) of patients. Understanding epitope variation across the whole genome provides insight into the virus-immune interface and may help guide the development of protocols for novel immunologic-based therapies.
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Ma, Shi-Xun, and Su Bin Lim. "Single-Cell RNA Sequencing in Parkinson’s Disease." Biomedicines 9, no. 4 (2021): 368. http://dx.doi.org/10.3390/biomedicines9040368.

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Single-cell and single-nucleus RNA sequencing (sc/snRNA-seq) technologies have enhanced the understanding of the molecular pathogenesis of neurodegenerative disorders, including Parkinson’s disease (PD). Nonetheless, their application in PD has been limited due mainly to the technical challenges resulting from the scarcity of postmortem brain tissue and low quality associated with RNA degradation. Despite such challenges, recent advances in animals and human in vitro models that recapitulate features of PD along with sequencing assays have fueled studies aiming to obtain an unbiased and global view of cellular composition and phenotype of PD at the single-cell resolution. Here, we reviewed recent sc/snRNA-seq efforts that have successfully characterized diverse cell-type populations and identified cell type-specific disease associations in PD. We also examined how these studies have employed computational and analytical tools to analyze and interpret the rich information derived from sc/snRNA-seq. Finally, we highlighted important limitations and emerging technologies for addressing key technical challenges currently limiting the integration of new findings into clinical practice.
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Noé, Andrés, Tamsin N. Cargill, Carolyn M. Nielsen, Andrew J. C. Russell, and Eleanor Barnes. "The Application of Single-Cell RNA Sequencing in Vaccinology." Journal of Immunology Research 2020 (August 6, 2020): 1–19. http://dx.doi.org/10.1155/2020/8624963.

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Single-cell RNA sequencing allows highly detailed profiling of cellular immune responses from limited-volume samples, advancing prospects of a new era of systems immunology. The power of single-cell RNA sequencing offers various opportunities to decipher the immune response to infectious diseases and vaccines. Here, we describe the potential uses of single-cell RNA sequencing methods in prophylactic vaccine development, concentrating on infectious diseases including COVID-19. Using examples from several diseases, we review how single-cell RNA sequencing has been used to evaluate the immunological response to different vaccine platforms and regimens. By highlighting published and unpublished single-cell RNA sequencing studies relevant to vaccinology, we discuss some general considerations how the field could be enriched with the widespread adoption of this technology.
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Paglino, Chiara, and Camillo Porta. "Sequencing or not sequencing multikinase inhibitors in kidney cancer: this is the dilemma." Oncology Reviews 4, no. 1 (2011): 1. http://dx.doi.org/10.4081/oncol.2010.1.

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With the recent development of targeted therapies (Sorafenib, Sunitinib, Temsirolimus, Bevacizumab plus Interferon-a, Everolimus and now also Pazopanib) patients with advanced renal cell carcinoma (RCC) now have a wide range of treatment options, all of which have shown both relevant clinical activity and manageable safety profile. This abundance of active treatments, coupled with relatively limited information, we have gathered from registrative phase III trials have raised the question of how to use these agents optimally...
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Vu, Trung Nghia, Ha-Nam Nguyen, Stefano Calza, Krishna R. Kalari, Liewei Wang, and Yudi Pawitan. "Cell-level somatic mutation detection from single-cell RNA sequencing." Bioinformatics 35, no. 22 (2019): 4679–87. http://dx.doi.org/10.1093/bioinformatics/btz288.

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Abstract Motivation Both single-cell RNA sequencing (scRNA-seq) and DNA sequencing (scDNA-seq) have been applied for cell-level genomic profiling. For mutation profiling, the latter seems more natural. However, the task is highly challenging due to the limited input materials from only two copies of DNA molecules, while whole-genome amplification generates biases and other technical noises. ScRNA-seq starts with a higher input amount, so generally has better data quality. There exists various methods for mutation detection from DNA sequencing, it is not clear whether these methods work for scRNA-seq data. Results Mutation detection methods developed for either bulk-cell sequencing data or scDNA-seq data do not work well for the scRNA-seq data, as they produce substantial numbers of false positives. We develop a novel and robust statistical method—called SCmut—to identify specific cells that harbor mutations discovered in bulk-cell data. Statistically SCmut controls the false positives using the 2D local false discovery rate method. We apply SCmut to several scRNA-seq datasets. In scRNA-seq breast cancer datasets SCmut identifies a number of highly confident cell-level mutations that are recurrent in many cells and consistent in different samples. In a scRNA-seq glioblastoma dataset, we discover a recurrent cell-level mutation in the PDGFRA gene that is highly correlated with a well-known in-frame deletion in the gene. To conclude, this study contributes a novel method to discover cell-level mutation information from scRNA-seq that can facilitate investigation of cell-to-cell heterogeneity. Availability and implementation The source codes and bioinformatics pipeline of SCmut are available at https://github.com/nghiavtr/SCmut. Supplementary information Supplementary data are available at Bioinformatics online.
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Diaz-Mejia, J. Javier, Elaine C. Meng, Alexander R. Pico, et al. "Evaluation of methods to assign cell type labels to cell clusters from single-cell RNA-sequencing data." F1000Research 8 (March 15, 2019): 296. http://dx.doi.org/10.12688/f1000research.18490.1.

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Background: Identification of cell type subpopulations from complex cell mixtures using single-cell RNA-sequencing (scRNA-seq) data includes automated computational steps like data normalization, dimensionality reduction and cell clustering. However, assigning cell type labels to cell clusters is still conducted manually by most researchers, resulting in limited documentation, low reproducibility and uncontrolled vocabularies. Two bottlenecks to automating this task are the scarcity of reference cell type gene expression signatures and the fact that some dedicated methods are available only as web servers with limited cell type gene expression signatures. Methods: In this study, we benchmarked four methods (CIBERSORT, GSEA, GSVA, and ORA) for the task of assigning cell type labels to cell clusters from scRNA-seq data. We used scRNA-seq datasets from liver, peripheral blood mononuclear cells and retinal neurons for which reference cell type gene expression signatures were available. Results: Our results show that, in general, all four methods show a high performance in the task as evaluated by receiver operating characteristic curve analysis (average area under the curve (AUC) = 0.94, sd = 0.036), whereas precision-recall curve analyses show a wide variation depending on the method and dataset (average AUC = 0.53, sd = 0.24). Conclusions: CIBERSORT and GSVA were the top two performers. Additionally, GSVA was the fastest of the four methods and was more robust in cell type gene expression signature subsampling simulations. We provide an extensible framework to evaluate other methods and datasets at https://github.com/jdime/scRNAseq_cell_cluster_labeling.
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Lim, Su Bin, Chwee Teck Lim, and Wan-Teck Lim. "Single-Cell Analysis of Circulating Tumor Cells: Why Heterogeneity Matters." Cancers 11, no. 10 (2019): 1595. http://dx.doi.org/10.3390/cancers11101595.

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Unlike bulk-cell analysis, single-cell approaches have the advantage of assessing cellular heterogeneity that governs key aspects of tumor biology. Yet, their applications to circulating tumor cells (CTCs) are relatively limited, due mainly to the technical challenges resulting from extreme rarity of CTCs. Nevertheless, recent advances in microfluidics and immunoaffinity enrichment technologies along with sequencing platforms have fueled studies aiming to enrich, isolate, and sequence whole genomes of CTCs with high fidelity across various malignancies. Here, we review recent single-cell CTC (scCTC) sequencing efforts, and the integrated workflows, that have successfully characterized patient-derived CTCs. We examine how these studies uncover DNA alterations occurring at multiple molecular levels ranging from point mutations to chromosomal rearrangements from a single CTC, and discuss their cellular heterogeneity and clinical consequences. Finally, we highlight emerging strategies to address key challenges currently limiting the translation of these findings to clinical practice.
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Contino, Gianmarco, Matthew D. Eldridge, Maria Secrier, et al. "Whole-genome sequencing of nine esophageal adenocarcinoma cell lines." F1000Research 5 (June 10, 2016): 1336. http://dx.doi.org/10.12688/f1000research.7033.1.

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Esophageal adenocarcinoma (EAC) is highly mutated and molecularly heterogeneous. The number of cell lines available for study is limited and their genome has been only partially characterized. The availability of an accurate annotation of their mutational landscape is crucial for accurate experimental design and correct interpretation of genotype-phenotype findings. We performed high coverage, paired end whole genome sequencing on eight EAC cell lines—ESO26, ESO51, FLO-1, JH-EsoAd1, OACM5.1 C, OACP4 C, OE33, SK-GT-4—all verified against original patient material, and one esophageal high grade dysplasia cell line, CP-D. We have made available the aligned sequence data and report single nucleotide variants (SNVs), small insertions and deletions (indels), and copy number alterations, identified by comparison with the human reference genome and known single nucleotide polymorphisms (SNPs). We compare these putative mutations to mutations found in primary tissue EAC samples, to inform the use of these cell lines as a model of EAC.
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Dissertations / Theses on the topic "Limited Cell Sequencing"

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Hu, Eileen Yifan. "Developing Methods and Targeted Therapeutics to Address Complications of Ibrutinib Treatment in Chronic Lymphocytic Leukemia." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1587494624201361.

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Gressel, Saskia. "Multi-omics analysis of transcription kinetics in human cells." Doctoral thesis, 2019. http://hdl.handle.net/21.11130/00-1735-0000-0003-C183-E.

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Book chapters on the topic "Limited Cell Sequencing"

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Sloan, Philip, and Max Robinson. "Promising Biomarkers for Early Diagnosis and Prognosis Prediction." In Critical Issues in Head and Neck Oncology. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-63234-2_1.

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AbstractSingle molecule biomarkers are used extensively in head and neck pathology for diagnosis and increasingly for prognosis. Companion markers for therapy such as PDL-1 and NTRK are now finding applications in head and neck cancer care. Immunohistochemistry is an attractive option because of its rapid turnaround time and convenience but molecular testing is often necessary for validation. This chapter will focus on some selected biomarkers being developed for translational purposes. Adoptive T cell therapies are being trialled for head and neck cancer and have limited efficacy currently. Identification of biomarkers as targets is an attractive option for development, and the use of molecular sequencing to identify individual neo-antigens is a promising way forward for precision medicine approaches including adoptive T cell therapies.
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Watson, Geoffrey Alan, Kirsty Taylor, and Lillian L. Siu. "Innovation and Advances in Precision Medicine in Head and Neck Cancer." In Critical Issues in Head and Neck Oncology. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-63234-2_24.

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AbstractThe clinical utility of precision medicine through molecular characterization of tumors has been demonstrated in some malignancies, especially in cases where oncogenic driver alterations are identified. Next generation sequencing data from thousands of patients with head and neck cancers have provided vast amounts of information about the genomic landscape of this disease. Thus far, only a limited number of genomic alterations have been druggable, such as NTRK gene rearrangements in salivary gland cancers (mainly mammary analogue secretory carcinoma), NOTCH mutations in adenoid cystic cancers, HRAS mutations in head and neck squamous cell cancers, and even a smaller number of these have reached regulatory approval status. In order to expand the scope of precision medicine in head and neck cancer, additional evaluation beyond genomics is necessary. For instance, there is increasing interest to perform transcriptomic profiling for target identification. Another advance is in the area of functional testing such as small interfering RNA and drug libraries on patient derived cell cultures. Liquid biopsies to detect specific tumor clones or subclones, or viral sequences such as HPV, are of great interest to enable non-invasive tracking of response or resistance to treatment. In addition, precision immuno-oncology is a tangible goal, with a growing body of knowledge on the interactions between the host immunity, the tumor and its microenvironment. Immuno-oncology combinations that are tailored to immunophenotypes of the host-tumor-microenvironment triad, personalized cancer vaccines, and adoptive cell therapies, among others, are in active development. Many therapeutic possibilities and opportunities lie ahead that ultimately will increase the reality of precision medicine in head and neck cancer.
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Golz, Julia Carolin, and Kerstin Stingl. "Natural Competence and Horizontal Gene Transfer in Campylobacter." In Current Topics in Microbiology and Immunology. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-65481-8_10.

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AbstractThermophilic Campylobacter, in particular Campylobacter jejuni, C. coli and C. lari are the main relevant Campylobacter species for human infections. Due to their high capacity of genetic exchange by horizontal gene transfer (HGT), rapid adaptation to changing environmental and host conditions contribute to successful spreading and persistence of these foodborne pathogens. However, extensive HGT can exert dangerous side effects for the bacterium, such as the incorporation of gene fragments leading to disturbed gene functions. Here we discuss mechanisms of HGT, notably natural transformation, conjugation and bacteriophage transduction and limiting regulatory strategies of gene transfer. In particular, we summarize the current knowledge on how the DNA macromolecule is exchanged between single cells. Mechanisms to stimulate and to limit HGT obviously coevolved and maintained an optimal balance. Chromosomal rearrangements and incorporation of harmful mutations are risk factors for survival and can result in drastic loss of fitness. In Campylobacter, the restricted recognition and preferential uptake of free DNA from relatives are mediated by a short methylated DNA pattern and not by a classical DNA uptake sequence as found in other bacteria. A class two CRISPR-Cas system is present but also other DNases and restriction–modification systems appear to be important for Campylobacter genome integrity. Several lytic and integrated bacteriophages have been identified, which contribute to genome diversity. Furthermore, we focus on the impact of gene transfer on the spread of antibiotic resistance genes (resistome) and persistence factors. We discuss remaining open questions in the HGT field, supposed to be answered in the future by current technologies like whole-genome sequencing and single-cell approaches.
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Nguyen, Trang, Trang Minh Tran, Yee Shen Choo, Maria Alexiadis, Peter J. Fuller, and Simon Chu. "Genetics and Mutational Landscape of Ovarian Sex Cord-Stromal Tumors." In Ovarian Cancer - Updates in Tumour Biology and Therapeutics [Working Title]. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.97540.

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Ovarian sex cord-stromal tumors (SCST) are uncommon tumors accounting for approximately 8% of all ovarian malignancies. By far, the most common are granulosa cell tumors (GCT) which represent approximately 90% of SCST. SCST are also found in the hereditary syndromes: Peutz-Jeghers syndrome, Ollier disease and Maffucci syndrome, and DICER1 syndrome. Key genomic and genetic events contributing to their pathogenesis have been the focus of recent studies. Most of the genomic studies have been limited to GCT which have identified a number of recurring chromosomal abnormalities (monosomy and trisomy), although their contribution to pathogenesis remains unclear. Recurrent DICER1 mutations are reported in non-hereditary cases of Sertoli cell and Sertoli–Leydig cell tumors (SLCT), while recurrent somatic mutations in both the juvenile (jGCT) and adult forms of GCT (aGCT) have also been reported. Approximately 30% of jGCT contain a somatic mutation in the gsp oncogene, while a further 60% have activating mutations or duplications in the AKT gene. For aGCT, a well characterized mutation in the FOXL2 transcription factor (FOXL2 C134W) is found in the majority of tumors (primary and recurrent), arguably defining the disease. A further mutation in the human telomerase promoter appears to be an important driver for recurrent disease in aGCT. However, despite several studies involving next generation sequencing, the molecular events that determine the stage, behavior and prognosis of aGCT still remain to be determined. Further, there is a need for these studies to be expanded to other SCST in order to identify potential targets for personalized medicine.
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Wurst, Wolfgang, and Achim Gossler. "Gene trap strategies in ES cells." In Gene Targeting. Oxford University Press, 1999. http://dx.doi.org/10.1093/oso/9780199637928.003.0010.

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Gene trap (GT) strategies in mouse embryonic stem (ES) cells are increasingly being used for detecting patterns of gene expression (1-4, isolating and mutating endogenous genes (5-7), and identifying targets of signalling molecules and transcription factors (3, 8-10). The general term gene trap refers to the random integration of a reporter gene construct (called entrapment vector) (11, 12) into the genome such that ‘productive’ integration events bring the reporter gene under the transcriptional regulation of an endogenous gene. In some cases this also simultaneously generates an insertional mutation. Entrapment vectors were originally developed in bacteria (13), and applied in Drosophila to identify novel developmental genes and/or regulatory sequences (14-17). Subsequently, a modified strategy was developed for mouse in which the reporter gene mRNA becomes fused to an endogenous transcript. Such ‘gene trap’ vectors were initially used primarily as a tool to discover genes involved in development (1, 2,18). In the last five years there has been a significant shift of GT approaches in mouse to much broader, large scale applications in the context of the analysis of mammalian genomes and ‘functional genomics’. Sequencing and physical mapping of both the human and mouse genomes is expected to be completed within the next five years. Already, a large number of mouse and human genes have been identified as expressed sequence tags (ESTs), and very likely the majority of genes will be discovered as ESTs shortly. This vast sequence information contrasts with a rather limited understanding of the in vivo functions of these genes. Whereas DNA sequence can provide some indication of the potential functions of these genes and their products, their physiological roles in the organism have to be determined by mutational analysis. Thus, the sequencing effort of the human genome project has to be complemented by efficient functional analyses of the identified genes. One potentially powerful complementation to the efforts of the human genome project would be a strategy whereby large scale random mutagenesis in mouse is combined with the rapid identification of the mutated genes (6,7,19, and German gene trap consortium, W. W. unpublished data).
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Conference papers on the topic "Limited Cell Sequencing"

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Hamon, Morgan, Kirn Cramer, Sachin Jambovane, Jing Dai, Ali Khademhosseini, and Jong Wook Hong. "Wide Range Logarithmic Gradient Formation for Cell Response." In ASME 2011 Summer Bioengineering Conference. American Society of Mechanical Engineers, 2011. http://dx.doi.org/10.1115/sbc2011-53710.

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Recently, the number of potential drug targets has dramatically increased because of the recent completion of the human genome sequencing and the progress in genomics and proteomics. In parallel, the number of new drugs for those targets has also been increased due to the use of combinatorial synthesis and the increased access to natural molecules [1]. However, this has not increased consequently the number of approved new drugs delivered to patients [2]. Indeed the drug discovery process is still limited by numbers of challenges; among them the need to analyze in more rapid and accurate manner precious sample of drug candidates.
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Zhao, Liang, Xiannian Zhang, Aaron M. Streets, Yuhong Pang, Fuchou Tang, and Yanyi Huang. "Microfluidics Facilitated Genome Sequencing for Limited Number of Cells." In CLEO: Science and Innovations. OSA, 2013. http://dx.doi.org/10.1364/cleo_si.2013.am3m.4.

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Zhao, Liang, Xiannian Zhang, Aaron M. Streets, Yuhong Pang, Fuchou Tang, and Yanyi Huang. "Microfluidics Facilitated Genome Sequencing for Limited Number of Cells." In CLEO: Applications and Technology. OSA, 2013. http://dx.doi.org/10.1364/cleo_at.2013.am3m.4.

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Rauthan, Amit, Poonam Patil, Rajashree Aswath, Nitin Yashas, and Gaurav Ningade. "Immunotherapy in Patients with Lung Cancer with Driver Mutations: A Single-Centre Experience." In Annual Conference of Indian Society of Medical and Paediatric Oncology (ISMPO). Thieme Medical and Scientific Publishers Pvt. Ltd., 2021. http://dx.doi.org/10.1055/s-0041-1735365.

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Abstract Introduction Immunotherapy has revolutionized treatment in metastatic nonsmall cell lung cancer (NSCLC) without driver mutations. Trial data shows that programmed death-1/PDL1 blockade in epidermal growth factor receptor (EGFR) and other driver mutation positive lung cancers is not beneficial; and instead maybe detrimental. Here, we evaluated the efficacy of immune check point inhibitors in a series of patients with EGFR and other driver mutation–positive advanced NSCLC. Objectives This study was aimed to evaluate the efficacy of immune check point inhibitors in a series of patients with EGFR and other driver mutation–positive advanced NSCLC. Materials and Methods We retrospectively analyzed 75 patients which received PD1/PDL1 inhibitors for advanced NSCL between January 2017 and January 2020. Ten patients were detected to have driver mutations on either tumor tissue or blood by next-generation sequencing (NGS). PDL1 status was assessed on SP263 ventana platform. Results Out of 10 patients, 7 were male and 3 were female. EGFR was detected in six patients (three on tumor and three in blood NGS), MET exon 14 skipping mutation in two patients, and RAS mutation in two patients on NGS in blood. Immunotherapy combined with chemotherapy was given in 5 (50%) patients, immunotherapy + bevacizumab + chemotherapy in two (20%) and immunotherapy alone in three patients (30%). Immunotherapy was started as first line in four patients as tumor tissue was negative for EGFR, ALK, and ROS1 by single gene testing. The remaining six patients received immunotherapy on progression in the second or subsequent lines. On NGS testing at progression, EGFR mutation was detected in one patient, MET exon 14 skip mutation was detected in two patients, and RAS mutation was detected in two patients. Immunotherapy alone was used in three patients in view of advanced age and multiple comorbidities. The median progression-free survival (PFS) was 5 months (range: 2–11 months). Two patients who received chemotherapy + bevacizumab + immunotherapy continue to do well without progression at 9 months. Conclusion PD1/PDL1 checkpoint inhibitors seem to have a limited impact in treatment in patients with driver mutations. Molecular testing by NGS is recommended either on tumor tissue or on blood by NGS if single gene testing for EGFR/ALK/ROS1 alterations is negative. We recommend not using single agent checkpoint inhibitors in molecular driven advanced NSCLC even with high PDL1 expression. We do see benefit in patients who received PD1/PDL1 inhibitors in combination with chemotherapy with bevacizumab. In conclusion, in patients with molecular-driven NSCLC who progress after standard therapy can be treated with PD1/PDL1 inhibitors, but this should always be given in combination with chemotherapy and bevacizumab.
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