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GenVisR: Genomic Visualizations in R [article]

Zachary L Skidmore, Alex H Wagner, Robert Lesurf, Katie M Campbell, Jason Kunisaki, Obi L Griffith, Malachi Griffith
2016 bioRxiv   pre-print
(Griffith, et al., 2015) , HCC38 and HCC1143 (Daemen, et al., 2013 ) breast cancer cell lines shows LOH events, across all chromosomes, shaded as dark blue.  ...  A variety of options exist to achieve this, however tools that offer both automation and flexibility to perform this task are lacking (Table S1 ) (Griffith, et al., 2015; Leiserson, et al., 2015; Nilsen  ... 
doi:10.1101/043604 fatcat:br3fofg43bg6fefjkglcyfnqke

GenVisR: Genomic Visualizations in R

Zachary L. Skidmore, Alex H. Wagner, Robert Lesurf, Katie M. Campbell, Jason Kunisaki, Obi L. Griffith, Malachi Griffith
2016 Bioinformatics  
(D) Output from lohSpec for HCC1395 (Griffith et al., 2015) , HCC38 and HCC1143 (Daemen et al., 2013) breast cancer cell lines shows LOH events, across all chromosomes, shaded as dark blue.  ...  A variety of options exist to achieve this; however tools that offer both automation and flexibility to perform this task are lacking (Supplementary Table S1 ) (Griffith et al., 2015; Leiserson et al  ... 
doi:10.1093/bioinformatics/btw325 pmid:27288499 pmcid:PMC5039916 fatcat:l5a5mgp63zhxjod2b2zd5gs4qq

Clinical implications of neoepitope landscapes for adult and pediatric cancers

Yang-Yang Feng, Obi L. Griffith, Malachi Griffith
2017 Genome Medicine  
Many immunotherapies rely on the presence of neoepitopes derived from somatic mutations that lead to altered peptide sequences. Several studies have now analyzed the neoepitope landscape of different cancer subtypes, predominantly for adult samples, which tend to feature significantly higher mutational burden. However, a new report publishing the first comprehensive analysis of the pediatric neoepitope landscape suggests that immunotherapies could also hold promise for pediatric cancers.
doi:10.1186/s13073-017-0470-9 pmid:28854952 pmcid:PMC5577778 fatcat:bvjn5aiokngdxn2ns4mpyblz6y

Single Cell T Cell Receptor Repertoire Profiling for Dogs [article]

Zachary L Skidmore, Hans Rindt, Shirley Chu, Bryan Fisk, Catrina Fronick, Robert Fulton, Mingyi Zhou, Nathan J Bivens, Carol N Reinero, Malachi Griffith, Jeffrey N Bryan, Obi L Griffith
2021 bioRxiv   pre-print
Primer design Primer design and application (Figure 1 ) was modeled from the Chromium Single Cell V(D)J Reagent Kits User Guide (CG000086 Rev L). This protocol uses a nested PCR design.  ...  cDNA generation cDNA generation was performed according to the Chromium Single Cell V(D)J Reagent Kits User Guide (CG000086 Rev L), with the exception of the TCR amplification (described below).  ... 
doi:10.1101/2021.06.29.450365 fatcat:ze73occhu5h5xl4scgghqian4m

Best practices for bioinformatic characterization of neoantigens for clinical utility

Megan M. Richters, Huiming Xia, Katie M. Campbell, William E. Gillanders, Obi L. Griffith, Malachi Griffith
2019 Genome Medicine  
Neoantigens are newly formed peptides created from somatic mutations that are capable of inducing tumor-specific T cell recognition. Recently, researchers and clinicians have leveraged next generation sequencing technologies to identify neoantigens and to create personalized immunotherapies for cancer treatment. To create a personalized cancer vaccine, neoantigens must be computationally predicted from matched tumor-normal sequencing data, and then ranked according to their predicted capability
more » ... in stimulating a T cell response. This candidate neoantigen prediction process involves multiple steps, including somatic mutation identification, HLA typing, peptide processing, and peptide-MHC binding prediction. The general workflow has been utilized for many preclinical and clinical trials, but there is no current consensus approach and few established best practices. In this article, we review recent discoveries, summarize the available computational tools, and provide analysis considerations for each step, including neoantigen prediction, prioritization, delivery, and validation methods. In addition to reviewing the current state of neoantigen analysis, we provide practical guidance, specific recommendations, and extensive discussion of critical concepts and points of confusion in the practice of neoantigen characterization for clinical use. Finally, we outline necessary areas of development, including the need to improve HLA class II typing accuracy, to expand software support for diverse neoantigen sources, and to incorporate clinical response data to improve neoantigen prediction algorithms. The ultimate goal of neoantigen characterization workflows is to create personalized vaccines that improve patient outcomes in diverse cancer types.
doi:10.1186/s13073-019-0666-2 pmid:31462330 pmcid:PMC6714459 fatcat:gk5n5kfisrhmxca4b62bvtgjg4

p53 mutations exhibit sex specific gain-of-function activity in gliomagenesis [article]

Nathan C Rockwell, Wei Yang, Nicole Warrington, Malachi Griffith, Obi L Griffith, Christina Gurnett, Barak Cohen, Dustin Baldridge, Joshua B Rubin
2021 bioRxiv   pre-print
Immunocytochemistry/Immunofluorescence Astrocytes were plated on poly-L-lysine (ScienCell) coated coverslips and fixed with 3.2% paraformaldehyde for 10 minutes at room temperature.  ...  Dilution 2524 Mouse p53 Mouse Cell Signaling Technology Western Blot 1:1000 ChIP 5 µg antibody/25 µg DNA ICC 1:2000 SC-365062 GAPDH Mouse Santa Cruz Western Blot 1:200 P53-CM5P-L  ... 
doi:10.1101/2021.06.11.448124 fatcat:f36orrh3dfdgdmuq4swrghte3q

Spontaneous aggressive ERα+ mammary tumor model is driven by Kras activation [article]

Katie M. Campbell, Kathleen A. O'Leary, Debra E. Rugowski, William A. Mulligan, Erica K. Barnell, Zachary L. Skidmore, Kilannin Krysiak, Malachi Griffith, Linda A. Schuler, Obi L. Griffith
2018 biorxiv/medrxiv   pre-print
Skidmore, Z.L., Wagner, A.H., Lesurf, R., Campbell, K.M., Kunisaki, J., Griffith, O.L., and Griffith, M. (2016 . GenVisR: Genomic Visualizations in R.  ...  ., 2012; Griffith et al., 2018; Lefebvre et al., 2016; Stephens et al., 2012) .  ...  LEAD CONTACT AND MATERIALS AVAILABILITY Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Obi Griffith (obigriffith@wustl.edu)  ... 
doi:10.1101/442624 fatcat:qsdp4tebnfhazbcatjtlkj7jny

'Omic approaches to preventing or managing metastatic breast cancer

Obi L Griffith, Joe W Gray
2011 Breast Cancer Research  
Early detection of metastasis-prone breast cancers and characterization of residual metastatic cancers are important in eff orts to improve management of breast cancer. Applications of genome-scale molecular analysis technologies are making these complementary approaches possible by revealing molecular features uniquely associated with metastatic disease. Assays that reveal these molecular features will facilitate development of anatomic, histological and blood-based strategies that may enable
more » ... etection prior to metastatic spread. Knowledge of these features also will guide development of therapeutic strategies that can be applied when metastatic disease burden is low, thereby increasing the probability of a curative response.
doi:10.1186/bcr2923 pmid:22216753 pmcid:PMC3326544 fatcat:65uwtxtkinfalnqshkhsfsb43e

Stool-derived eukaryotic RNA biomarkers for detection of high-risk adenomas [article]

Erica K. Barnell, Yiming Kang, Andrew R. Barnell, Katie M. Campbell, Kimberly R. Kruse, Elizabeth M. Wurtzler, Malachi Griffith, Aadel A. Chaudhuri, Obi L. Griffith
2019 bioRxiv   pre-print
and aims: Colorectal cancer (CRC) is the second leading cause of cancer related deaths in the United States. Mortality is largely attributable to low patient compliance with screening and a subsequent high frequency of late-stage diagnoses. Noninvasive methods, such as stool- or blood-based diagnostics could improve patient compliance, however, existing techniques cannot adequately detect high-risk adenomas (HRAs) and early-stage CRC. Methods: Here we apply cancer profiling using amplicon
more » ... cing of stool-derived eukaryotic RNA for 275 patients undergoing prospective CRC screening. A training set of 154 samples was used to build a random forest model that included 4 feature types (differentially expressed amplicons, total RNA expression, demographic information, and fecal immunochemical test results). An independent hold out test set of 121 patients was used to assess model performance. Results: When applied to the 121-patient hold out test set, the model attained a receiver operating characteristic (ROC) area under the curve (AUC) of 0.94 for CRC and a ROC AUC of 0.87 for CRC and HRAs. In aggregate, the model achieved a 91% sensitivity for CRC and a 73% sensitivity for HRAs at an 89% specificity for all other findings (medium-risk adenomas, low-risk adenomas, benign polyps, and no findings on a colonoscopy). Conclusion: Collectively, these results indicate that in addition to early CRC detection, stool-derived biomarkers can accurately and noninvasively identify HRAs, which could be harnessed to prevent CRC development for asymptomatic, average-risk patients.
doi:10.1101/534412 fatcat:uia7fynzdrfg7jqauiyzo35dxq

Text-mining clinically relevant cancer biomarkers for curation into the CIViC database [article]

Jake Lever, Martin R Jones, Arpad M Danos, Kilannin Krysiak, Melika Bonakdar, Jasleen Grewal, Luka Culibrk, Obi L Griffith, Malachi Griffith, Steven JM Jones
2018 bioRxiv   pre-print
Precision oncology involves analysis of individual cancer samples to understand the genes and pathways involved in the development and progression of a cancer. To improve patient care, knowledge of diagnostic, prognostic, predisposing and drug response markers is essential. Several knowledgebases have been created by different groups to collate evidence for these associations. These include the open-access Clinical Interpretation of Variants in Cancer (CIViC) knowledgebase. These databases rely
more » ... on time-consuming manual curation from skilled experts who read and interpret the relevant biomedical literature. To aid in this curation and provide the greatest coverage for these databases, particularly CIViC, we propose the use of text mining approaches to extract these clinically relevant biomarkers from all available published literature. To this end, a group of cancer genomics experts annotated biomarkers and their clinical associations discussed in 800 sentences and achieved good inter-annotator agreement. We then used a supervised learning approach to construct the CIViCmine knowledgebase (http://bionlp.bcgsc.ca/civicmine/) extracting 128,857 relevant sentences from PubMed abstracts and Pubmed Central Open Access full text papers. CIViCmine contains over 90,992 biomarkers associated with 7,866 genes, 402 drugs and 557 cancer types, representing 29,153 abstracts and 40,551 full-text publications. Through integration with CIVIC, we provide a prioritised list of curatable biomarkers as well as a resource that is valuable to other knowledgebases and precision cancer analysts in general.
doi:10.1101/500686 fatcat:bdcusa3qjvdvtcqft77yzqcay4

KiWi: A Scalable Subspace Clustering Algorithm for Gene Expression Analysis [article]

Obi L. Griffith, Byron J. Gao, Mikhail Bilenky, Yuliya Prichyna, Martin Ester, Steven J.M. Jones
2009 arXiv   pre-print
., , , n i i i i l l l L = to be a set of annotation labels for n conserved motifs predicted in the promoter of a gene "i".  ...  Figure 9 . cisRED analysis. ) 1 ( | | 2 , − = ∑ N N L L S j j i i ∩ The mean promoter similarity score (see methods) for each cluster size is shown.  ... 
arXiv:0904.1931v1 fatcat:6twh54lpfbhlxl3qq4lijclb6a

Neoantigens in immunotherapy and personalized vaccines: Implications for head and neck squamous cell carcinoma

Paul Zolkind, Gavin P. Dunn, Tianxiang Lin, Malachi Griffith, Obi L. Griffith, Ravindra Uppaluri
2017 Oral Oncology  
The recent success of immunotherapies has demonstrated the potency of tumor-specific immune cells in mediating tumor rejection and generating durable tumor immunity. Our understanding of the scientific basis of these responses results from the confluence of a better comprehension of the cancer immunoediting process and the revolution in next generation sequencing of cancer genomes. Recent evidence suggests that T cell specificity for cancer cell expressed mutant proteins -termed neoantigens -is
more » ... an important component of immune mediated tumor rejection. Improved neoantigen prediction algorithms have made it possible to predict and monitor immune responses to checkpoint inhibitors and adoptively transferred autologous lymphocytes and have enabled the development of tumor-specific therapeutic vaccines. Herein, we review the current research on cancer neoantigens in immunotherapies and its implications for the future of head and neck cancer management.
doi:10.1016/j.oraloncology.2016.09.010 pmid:27751760 pmcid:PMC5423853 fatcat:itpatgu4fbbgfou42finra6lcq

pVAC-Seq: A genome-guided in silico approach to identifying tumor neoantigens

Jasreet Hundal, Beatriz M. Carreno, Allegra A. Petti, Gerald P. Linette, Obi L. Griffith, Elaine R. Mardis, Malachi Griffith
2016 Genome Medicine  
Acknowledgements We are grateful for creative and computational input from Zachary L. Skidmore, Susanna Siebert, Todd N. Wylie, Jason R. Walker, and Chris A. Miller. We thank Dr. Robert D.  ... 
doi:10.1186/s13073-016-0264-5 pmid:26825632 pmcid:PMC4733280 fatcat:t76uisfbh5ci5fmduetjpifsa4

Informatics for RNA Sequencing: A Web Resource for Analysis on the Cloud

Malachi Griffith, Jason R. Walker, Nicholas C. Spies, Benjamin J. Ainscough, Obi L. Griffith, Francis Ouellette
2015 PLoS Computational Biology  
Massively parallel RNA sequencing (RNA-seq) has rapidly become the assay of choice for interrogating RNA transcript abundance and diversity. This article provides a detailed introduction to fundamental RNA-seq molecular biology and informatics concepts. We make available open-access RNA-seq tutorials that cover cloud computing, tool installation, relevant file formats, reference genomes, transcriptome annotations, quality-control strategies, expression, differential expression, and alternative
more » ... plicing analysis methods. These tutorials and additional training resources are accompanied by complete analysis pipelines and test datasets made available without encumbrance at www.rnaseq.wiki. This is part of the PLOS Computational Biology Education collection. | Fig 2. RNA-seq data generation. A typical RNA-seq experimental workflow involves the isolation of RNA from samples of interest, generation of sequencing libraries, use of a high-throughput sequencer to produce hundreds of millions of short paired-end reads, alignment of reads against a reference genome or transcriptome, and downstream analysis for expression estimation, differential expression, transcript isoform discovery, and other applications. PLOS Computational Biology
doi:10.1371/journal.pcbi.1004393 pmid:26248053 pmcid:PMC4527835 fatcat:acf3mqrel5c7botm6u26npvknq

RegTools: Integrated analysis of genomic and transcriptomic data for discovery of splicing variants in cancer [article]

Yang-Yang Feng, Avinash Ramu, Kelsy C. Cotto, Zachary L. Skidmore, Jason Kunisaki, Donald F. Conrad, Yiing Lin, William C. Chapman, Ravindra Uppaluri, Ramaswamy Govindan, Obi L. Griffith, Malachi Griffith
2018 bioRxiv   pre-print
DNA and RNA alignment and variant calling were performed as previously described using the Genome Modeling System (GMS) Griffith, Miller, et al. , 2015 ; Supplementary Methods) .  ... 
doi:10.1101/436634 fatcat:godhohetzjfvjmhojdzwvxgsje
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