bsrweb.burnham.org Stacy Xiayu Huang Roy Williams Alexey Eroshkin Gene-centric bioinformatics analysis to guide your cancer research

bsrweb.burnham.org Bioinformatics Shared Resource (BSR)/ Information and data management (IDM) Stacy Xiayu Huang, Biostatistician Roy Williams, Bioinformatics Specialist Alexey Eroshkin, Bioinformatics Specialist and Director

Guess what gene will we explore? bsrweb.burnham.org

CASP8 Caspase-8 bsrweb.burnham.org

Caspase-8 Cysteine proteases that plays a critical role in the regulation of programmed cell death (apoptosis). Present in the cytosol as inactive zymogen that become activated in response to specific death stimuli. Once activated, initiator caspases (caspase-8, -9, and -10) cleave and activate executioner caspases (caspases-3 and -7). Activity post-translationally regulated Two primary pathways to establish the cell death program: intrinsic mediates response to cellular stress, such as DNA damage, and extrinsic, triggered by extracellular signals such as Fas binding to its cognate receptor and leads to activation of initiator caspase-8. Highly conserved active sites and overlapping substrate specificities make it difficult to use inhibitors or activity-based probes to study the function, activation, localization and regulation of individual members of this family. bsrweb.burnham.org

Today: Assessing the potential impact of variations. Mutations in caspase-8 substrates. Cancer-related driver mutations vs passenger mutations Changes in a gene's expression during tumorigenesis. Including microarray, RNA-seq, chIP-seq and methylation data. Mutations and cancer stages, drug treatments and developing drug resistance * Most tools from web – public and proprietary Sometimes program install required We are NOT doing a review of casp8 publications We are NOT providing an expert opinion on casp8

Caspase-8 in pdb – very graphical bsrweb.burnham.org Death effector domains (DEDs) are protein-protein interaction structures that are found in proteins that regulate a variety of signal transduction pathways.

MetaCore - for every gene: bsrweb.burnham.org

Casp8 in Metacore (Thomson Reuters): pathways and processes bsrweb.burnham.org

MetaCore: Apoptosis and survival Caspase cascade bsrweb.burnham.org

MetaCore’s Process Network: Apoptosis_Apoptosis stimulation by external signals Interactions Hubs Divergence hubs Convergence hubs Nodes Transcription factors Membrane receptors Secreted proteins & peptides GO processes Diseases Tissues

You can edit Process Networks Change layout Add object Remove/move object Add relation/connection from your experiment Get more info for every –Relation –Object bsrweb.burnham.org

MetaCore: associated diseases (part)

Casp8: number of publications (associated diseases) 60 other associated diseases have just one reference: e.g., Adenocarcinoma, Bronchiolo-AlveolarAdenomaAdenomatous Polyposis ColiAIDS-Related ComplexAnoxia Arthritis, RheumatoidCarcinomaCarcinoma, Basal CellCarcinoma, Ductal, BreastCarcinoma, Lobular Carcinoma, Small CellClubfootDermatitis, Allergic ContactEndometrial Neoplasms Ependymoma Esophageal NeoplasmsGallbladder Neoplasms, etc

Drugs and biomarkers bsrweb.burnham.org

Summary on CASP8 in UniProt (well respected database) ( (

Sequence annotation in UniProt bsrweb.burnham.org

Switch between natural variants and isoforms can be related to cancer (UniProt) L (long): missing the catalytic site of caspase-8 but retains 2 N- terminal repeats of the death-effector domain – inhibitor of casp8

You can align isoforms sequences at UniProt and find that isoforms 5,6,7 and 8 lack catalytic sites.

bsrweb.burnham.org CASP8 in ENTREZ

CASP8 in Genome Browser from NextBio Not showing protein changes for SNPs but can show your study in context of others

bsrweb.burnham.org Protease association with cancer* Gene variants and isoforms Variation effects –in caspase-8 Inactivation, partial or complete altered signaling (different phosphorylation) Change in stability Change of specificity (e.g., new substrates) Change in Interactions localization –in caspase-8 targets Known targets may be not cleaved (not activated) or cleaved in a wrong place –new substrates can appear (cleavage sites in other proteins) Inactivating some protein functions Creating new activity Deregulation (epigenetics or transcriptional or posttranslational) –Up regulation - increase apoptosis, can cleave beyond targets –Down regulation - inhibits apoptosis (cells not dying … cancer?)

bsrweb.burnham.org How to test if there is a connection between CASP8 isoforms and cancer Do Next-gen sequencing (RNA-seq) Calculate transcription-level expression of gene’s isoforms (Partek, E/M) Expectation maximization (E/M) algorithm is used to quantitate gene alternative splicing in two sets of samples Assigns significance of the change in isoforms expression Here is the power of Next-Gen sequencing Cufflinks or SLIDE algorithms will do as well

bsrweb.burnham.org Mutations: Check first if there are somatic cancer- related mutations in your gene - List of ~500 genes associated with Cancers (Cancer Somatic Mutations) - Casp8 not in the “Catalog”

The catalog of cancer genes (part) bsrweb.burnham.org

Cosmic: 22 somatic mutation in casp8 bsrweb.burnham.org

But: very small % of tissues with mutated casp8 bsrweb.burnham.org

Known clinical variants at NCBI :

bsrweb.burnham.org Ways to assess the significance of the amino acid variation on protein function Most algorithms assume that important positions in a protein sequence have been conserved throughout evolution and therefore substitutions at these positions may affect protein function. SIFT, popular non-synonymous SNP annotation software that assigns a "functional importance" score to SNPs, PolyPhen, PolyPhen2: DIY: Align protein sequences and analyze the replacement on your own – use your best judgment, look for 3D structure –Use family sequence alignment –Assess variability of residues in particular position –Role of the position in structure/function –If mutation outside of known in mammalian species, likely destructive

Where to go: Merops and CutDB – source of data on proteases, protease known substrates

Assess mutation in coding region using CASP8 multiple sequence alignment

Cut and paste alignment into JalView and you can see the natural variations JalView can be installed or webstart can be used

bsrweb.burnham.org Can dig deep – to 3D structure

bsrweb.burnham.org To analyze ALL KNOWN mutations go to Exome Sequencing Project (NHLBI ESP)

bsrweb.burnham.org dbSNP database

bsrweb.burnham.org How to evaluate the effect of mutations in CASP8 substrates (cleavage sites in cancer sample) Motif: S4 S3 S2 S1 S1’ [DL][ES] X D* [GSA] Position weight matrix

Assess variations in cancer genome for new casp8 substrates Predict casp8 cleavage sites in cancer sample proteins (e.g., public/SitePrediction/, public/SitePrediction/ Predict casp8 cleavage sites in normal sample proteome Compare two predictions and analyze New cleavage sites in proteins from cancer samples Missing cleavage sites in proteins from cancer samples Prioritize cancer relevance of the difference (COSMIC gene set, cancer-related pathways etc.)

PMAP whole proteome substrate prediction (part) bsrweb.burnham.org

Casp8 cleaves phosphorylated sites and cleavage sites get phosphorylated caspase cleavage can expose new sites for phosphorylation, and, conversely, Phosphorylation at the +3 position of cleavage sites can directly promote substrate proteolysis by caspase-8 functional crosstalk between phosphorylation and caspase proteolytic pathways that lead to enhanced rates of protein cleavage and the unveiling of new sites for phosphorylation phosphorylation events are enriched on cleaved proteins and are clustered around sites of caspase cleavage Interesting to compare cleavage in phosphorylated and non phosphorylated proteins Melissa M Dix, Cell 150, 426–440, July 20, 2012 ª201

Human phospho-site knowledge database: casp8 ( bsrweb.burnham.org

You study some cancer and you want to find cancer driver genes Perform whole-exome sequencing –matched normal DNAs and –metastatic tumor DNAs Variant detection (next-gen sequencing) and validation (Sanger) Find genes that appeared to be somatically mutated at elevated frequency (statistical model) –Majority (many) of tumor samples have disruptive variations –Few or no normal sample have such variations bsrweb.burnham.org Wei X. Nat Genet May;43(5):442-6

Identification of likely driver mutations –Take all (or frequent) somatic mutations –Filter for the cancer genes from the Cancer Gene Census ( that are known to be mutated to contribute to cancer development –Take mutations that conformed to the known patterns of cancer- causing mutation for each cancer gene in COSMIC database Truncating mutations, missense mutations, essential splice site mutations and homozygous deletions for recessive cancer genes For dominant genes, include mutations that had been previously registered in COSMIC –CONS: this cover only 2% of human genes bsrweb.burnham.org Stephens, Nature, 486, p.400, 2012

Identify frequent somatic drivers Frequency of mutation (cancer vs normal samples) –Tumor tissue with mutation (T) –Normal and Tumor tissues with mutation (N+T) –T/(N+T) ratio –Consider T/(N+T) > cutoff (0.2?) –For this mutation find MAF - minor allele frequency in population (ESP6500 data) MAF 0.01 considered as common polymorphism) –Compare T/(N+T) ratio with MAF T/(N+T) >> MAF – potential driver mutation Example: T/(N+T) =0.2, MAF = bsrweb.burnham.org

CASP8: Driver mutations implicated in breast cancer development bsrweb.burnham.org Stephens, Nature, 486, p.400, 2012

The Human Protein Atlas protein expression profiles based on immunohistochemistry for a large number of human tissues, cancers and cell lines bsrweb.burnham.org

Casp8 antibody staining in breast cancer bsrweb.burnham.org

Thanks Questions? bsrweb.burnham.org