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hepatocellular_carcinoma [2019/05/20 04:16] – [Project 1:] adminhepatocellular_carcinoma [2019/10/07 15:45] – [Objectives] admin
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 ====== Hepatocellular carcinoma ====== ====== Hepatocellular carcinoma ======
 ===== Objectives ===== ===== Objectives =====
-\\ Hepatocellular carcinoma (HCC) is a the most common type of liver cancer and the third leading cause of cancer deaths in the world. The goal of project one is to identify the genes that are associated with regressing tumors (regardless of type of treatment) vs. those that are growing from the C3HeB/FeJ mouse model. Normal liver is used as a control. The results will be useful in identifying new therapeutic targets and potential drug combinations which could lead to more efficient treatments. Project two is related to knockdown of a specific protein that results in HCC in a different mouse model. The goal in the second project is to identify the genes and pathways that correlate with this protein.\\ \\ + 
 +\\ 
 +Hepatocellular carcinoma (HCC) is a the most common type of liver cancer and the third leading cause of cancer deaths in the world. [[https://www.merckmanuals.com/home/liver-and-gallbladder-disorders/fibrosis-and-cirrhosis-of-the-liver/cirrhosis-of-the-liver#v28485447|Cirrhosis]] of the liver is a major risk and contributing factor for HCC. The goal of project one is to identify the genes that are associated with regressing tumors (regardless of type of treatment) vs. those that are growing from the C3HeB/FeJ mouse model. Normal liver is used as a control. The results will be useful in identifying new therapeutic targets and potential drug combinations which could lead to more efficient treatments. Project two is related to knockdown of a specific protein that results in HCC in a different mouse model. The goal in the second project is to identify the genes and pathways that correlate with this protein. 
 + 
 ===== Data ===== ===== Data =====
  
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 ==== Publication: ==== ==== Publication: ====
-Jessica Zavadil, Maryanne Herzig, Kim Hildreth, Amir Foroushani, William Boswell, Ronald Walter, Robert Reddick, Hugh White, Habil Zare. C3HeB/FeJ Mice Mimic Gene Expression and Pathobiological Features of Human Hepatocellular Carcinoma,  //Molecular Carcinogenesis//, In press. + 
-{{:wiki:public:jessica_compare.png?direct&400|}}+Jessica Zavadil, Maryanne Herzig, Kim Hildreth, Amir Foroushani, William Boswell, Ronald Walter, Robert Reddick, Hugh White, Habil Zare. "C3HeB/FeJ Mice mimic many aspects of gene expression and pathobiological features of human hepatocellular carcinoma." [[https://onlinelibrary.wiley.com/doi/abs/10.1002/mc.22929|Molecular carcinogenesis ]]58.3 (2019): 309-320. 
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 +{{:wiki:public:jessica_compare.png?direct&400}} 
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 ==== Project 2: ==== ==== Project 2: ====
  
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 ===== Related work ===== ===== Related work =====
  
-  - Hoenerhoff, Mark J., et al. "Global Gene Profiling of Spontaneous Hepatocellular Carcinoma in B6C3F1 Mice Similarities in the Molecular Landscape with Human Liver Cancer." //[[http://www.ncbi.nlm.nih.gov/pubmed/21571946|Toxicologic]] pathology// 39.4 (2011): 678-699. \\  Microarray analysis of tumors from B6C3F1 mice (first generation of C57B/L6J and C3HeB/FeJ strains) +  - Hoenerhoff, Mark J., et al. "Global Gene Profiling of Spontaneous Hepatocellular Carcinoma in B6C3F1 Mice Similarities in the Molecular Landscape with Human Liver Cancer." //[[http://www.ncbi.nlm.nih.gov/pubmed/21571946|Toxicologic]] pathology//39.4 (2011): 678-699. \\ Microarray analysis of tumors from B6C3F1 mice (first generation of C57B/L6J and C3HeB/FeJ strains) 
-  - Keane, Thomas M., et al. "Mouse genomic variation and its effect on phenotypes and gene regulation." [[http://www.nature.com/nature/journal/v477/n7364/full/nature10413.html|Nature]] 477.7364 (2011): 289-294.\\  Compared the standard reference genomes of mouse (C57BL/6J) with other strains. +  - Keane, Thomas M., et al. "Mouse genomic variation and its effect on phenotypes and gene regulation." [[http://www.nature.com/nature/journal/v477/n7364/full/nature10413.html|Nature]] 477.7364 (2011): 289-294. \\  Compared the standard reference genomes of mouse (C57BL/6J) with other strains. 
-  - Munger, Steven C., et al. "RNA-Seq alignment to individualized genomes improves transcript abundance estimates in multiparent populations."//[[http://www.genetics.org/content/198/1/59.full#T2|Genetics]]// 198.1 (2014): 59-73.\\  Proposed a method for strain-specific alignment and compared with mapping RNAseq data from a strain to the reference genome. Observed >10% change in expression in about 2,000 genes. +  - Munger, Steven C., et al. "RNA-Seq alignment to individualized genomes improves transcript abundance estimates in multiparent populations."//[[http://www.genetics.org/content/198/1/59.full#T2|Genetics]]// 198.1 (2014): 59-73. \\ Proposed a method for strain-specific alignment and compared with mapping RNAseq data from a strain to the reference genome. Observed >10% change in expression in about 2,000 genes. 
-  - Huang, Shunping, et al. "Transforming genomes using **MOD** files with applications." //Proceedings of the International Conference on Bioinformatics, Computational Biology and Biomedical Informatics//. [[http://web.cs.ucla.edu/~weiwang/paper/ACMBCB13_1.pdf|ACM]], 2013.\\  Figure 4 shows that if we map to reference genome, we may loose not more than 7% of reads. +  - Huang, Shunping, et al. "Transforming genomes using **MOD**  files with applications." //Proceedings of the International Conference on Bioinformatics, Computational Biology and Biomedical Informatics//. [[http://web.cs.ucla.edu/~weiwang/paper/ACMBCB13_1.pdf|ACM]], 2013. \\  Figure 4 shows that if we map to reference genome, we may loose not more than 7% of reads. 
-  - Hart, Steven N., et al. "Calculating sample size estimates for RNA sequencing data." //Journal of Computational [[http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3842884/|Biology]]// 20.12 (2013): 970-978.Wu, Hao, Chi Wang, and Zhijin Wu. "PROPER: comprehensive power evaluation for differential expression using RNA-seq." //[[http://bioinformatics.oxfordjournals.org/content/31/2/233.short|Bioinformatics]]// 31.2 (2015): 233-241.From [[http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3842884/figure/f2/|Fig2]] and [[http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3842884/figure/f2/|Fig3]] of Huang et al. paper, and [[http://bioinformatics.oxfordjournals.org.libproxy.txstate.edu/content/31/2/233/F5.expansion.html|Fig5]] of Hart et al., it seems that at least 5-7 samples are needed for each condition. +  - Hart, Steven N., et al. "Calculating sample size estimates for RNA sequencing data." //Journal of Computational [[http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3842884/|Biology]]//20.12 (2013): 970-978.Wu, Hao, Chi Wang, and Zhijin Wu. "PROPER: comprehensive power evaluation for differential expression using RNA-seq." //[[http://bioinformatics.oxfordjournals.org/content/31/2/233.short|Bioinformatics]]//31.2 (2015): 233-241.From [[http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3842884/figure/f2/|Fig2]] and [[http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3842884/figure/f2/|Fig3]] of Huang et al. paper, and [[http://bioinformatics.oxfordjournals.org.libproxy.txstate.edu/content/31/2/233/F5.expansion.html|Fig5]] of Hart et al., it seems that at least 5-7 samples are needed for each condition. 
-  - Ching, Travers, Sijia Huang, and Lana X. Garmire. "Power analysis and sample size estimation for RNA-Seq differential expression." //[[http://rnajournal.cshlp.org/content/early/2014/09/22/rna.046011.114|rna]]// 20.11 (2014): 1684-1696. +  - Ching, Travers, Sijia Huang, and Lana X. Garmire. "Power analysis and sample size estimation for RNA-Seq differential expression." //[[http://rnajournal.cshlp.org/content/early/2014/09/22/rna.046011.114|rna]]//20.11 (2014): 1684-1696. 
-  - Comprehensive and Integrative Genomic Characterization of Hepatocellular Carcinoma, [[http://www.cell.com/cell/abstract/S0092-8674(17)30639-6?innerTabgraphical_S0092867417306396|Cell]], 2017 [{{ :ally-copmprehensive_and_integrative_genomic_char_of_hcc-cell-2017.pdf|pdf}}]. TCGA's HCC data and subtyping using DNA copy number, DNA methylation, mRNA expression, miRNA expression and RPPA (protein expression). Links to the MDACC dataset with 100 HCC samples. +  - Comprehensive and Integrative Genomic Characterization of Hepatocellular Carcinoma, [[http://www.cell.com/cell/abstract/S0092-8674(17)30639-6?innerTabgraphical_S0092867417306396|Cell]], 2017 [{{:ally-copmprehensive_and_integrative_genomic_char_of_hcc-cell-2017.pdf|pdf}}  ]. TCGA's HCC data and subtyping using DNA copy number, DNA methylation, mRNA expression, miRNA expression and RPPA (protein expression). Links to the MDACC dataset with 100 HCC samples. 
-\\ **Related software**\\ +  - Subramaniam, Somasundaram, Robin K. Kelley, and Alan P. Venook. "A review of hepatocellular carcinoma (HCC) staging systems." [[http://cco.amegroups.com/article/view/2528/3943|Chinese clinical oncology]] 2.4 (2013). 
 + 
 +---- 
 + 
 + 
 +=====   Related software   =====
  
   - [[https://ccb.jhu.edu/software/tophat/index.shtml|TopHat]], useful for aligning RNAseq data to a genome.   - [[https://ccb.jhu.edu/software/tophat/index.shtml|TopHat]], useful for aligning RNAseq data to a genome.
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   - [[http://homer.salk.edu/homer/basicTutorial/mapping.html|Homer's]] quick tutorial on mapping NGS data using several tools including bowtie2, bwa, TopHAt, etc. with command line examples.   - [[http://homer.salk.edu/homer/basicTutorial/mapping.html|Homer's]] quick tutorial on mapping NGS data using several tools including bowtie2, bwa, TopHAt, etc. with command line examples.
   - [[http://gqinnovationcenter.com/documents/bioinformatics/RNAseq_Cuba_OMICS_2013.pdf|Lefebvre's]] quick tutorial on RNA-Seq data analysis.   - [[http://gqinnovationcenter.com/documents/bioinformatics/RNAseq_Cuba_OMICS_2013.pdf|Lefebvre's]] quick tutorial on RNA-Seq data analysis.
-  - Schiffthaler's ~1 hour video on RNA Seq data [[https://www.youtube.com/watch?v=1rNEkWSxB5s|preprocessing]] including FastQC, sortmerna to exclude rRNA, trimmomatic to trim the adaptors and low quality bps, STAR to map reads to the genome, samtools to index the bam file, IGV to visualize the reads on the genome, and HTSeq to count the number of reads mapped to each gene (coverage). These are all steps we need to do before differential analysis using, say DESeq2. [[http://www.epigenesys.eu/images/stories/protocols/pdf/20150303161357_p67.pdf|This]] is a textual version explaining the same steps.\\ \\  +  - Schiffthaler's ~1 hour video on RNA Seq data [[https://www.youtube.com/watch?v=1rNEkWSxB5s|preprocessing]] including FastQC, sortmerna to exclude rRNA, trimmomatic to trim the adaptors and low quality bps, STAR to map reads to the genome, samtools to index the bam file, IGV to visualize the reads on the genome, and HTSeq to count the number of reads mapped to each gene (coverage). These are all steps we need to do before differential analysis using, say DESeq2. [[http://www.epigenesys.eu/images/stories/protocols/pdf/20150303161357_p67.pdf|This]] is a textual version explaining the same steps. \\ 
-[[|Drafts]], [[|Next steps]]+ 
 +[[:hepatocellular_carcinoma|Drafts]], [[:hepatocellular_carcinoma|Next steps]] 
 +