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Computational methods for genomics-guided immunotherapy Sahar Al Seesi Computer Science & Engineering Department, UCONN Immunology Department, UCONN Health

Computational methods for genomics-guided immunotherapy Sahar Al Seesi Computer Science & Engineering Department, UCONN Immunology Department, UCONN Health

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Page 1: Computational methods for genomics-guided immunotherapy Sahar Al Seesi Computer Science & Engineering Department, UCONN Immunology Department, UCONN Health

Computational methods for genomics-guided immunotherapy

Sahar Al Seesi Computer Science & Engineering Department, UCONNImmunology Department, UCONN Health

Page 2: Computational methods for genomics-guided immunotherapy Sahar Al Seesi Computer Science & Engineering Department, UCONN Immunology Department, UCONN Health

Sequencing QC and Mapping

Calling SNVs

EpitopePrediction

TCR Sequencin

g

Page 3: Computational methods for genomics-guided immunotherapy Sahar Al Seesi Computer Science & Engineering Department, UCONN Immunology Department, UCONN Health

Ion Proton

Tumor DNA

Exome AmpliSeq

Normal DNA Tumor RNA

Sequencing

Whole TranscriptomeLibrary prep

Whole GenomeLibrary prep

or

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

TCR Sequencing

Page 4: Computational methods for genomics-guided immunotherapy Sahar Al Seesi Computer Science & Engineering Department, UCONN Immunology Department, UCONN Health

Tumor DNA

Sequencing

Nextera Rapid Capture Exome

Normal DNA Tumor RNA

Whole TranscriptomeLibrary prep

Illumina HiSeq

Whole GenomeLibrary prep

or

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

TCR Sequencing

Page 5: Computational methods for genomics-guided immunotherapy Sahar Al Seesi Computer Science & Engineering Department, UCONN Immunology Department, UCONN Health

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

TCR Sequencing

C C G C G G T C A GT C T C G G A A T TT C C C G G T A A TT C C C G G T A A TT C C C G G T A A TA T C G G T T T A TC C T C T A A C A CT A A T G G A A T TC C G C G A A C A CA A C A C C C C G G

Read Quality Control

Low quality base

Page 6: Computational methods for genomics-guided immunotherapy Sahar Al Seesi Computer Science & Engineering Department, UCONN Immunology Department, UCONN Health

• Tools to analyze and preprocess fastq files– FASTX

http://hannonlab.cshl.edu/fastx_toolkit/

– PRINSEQ http://prinseq.sourceforge.net/)

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

TCR Sequencing

Page 7: Computational methods for genomics-guided immunotherapy Sahar Al Seesi Computer Science & Engineering Department, UCONN Immunology Department, UCONN Health

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

TCR Sequencing

Normal Exome Reads

Tumor Exome Reads

Tumor RNA-Seq Reads

Human reference

Human reference

Read Mapping

Page 8: Computational methods for genomics-guided immunotherapy Sahar Al Seesi Computer Science & Engineering Department, UCONN Immunology Department, UCONN Health
Page 9: Computational methods for genomics-guided immunotherapy Sahar Al Seesi Computer Science & Engineering Department, UCONN Immunology Department, UCONN Health

Normal Exome Reads

Human Reference

Tumor Exome Reads

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

TCR Sequencing

****

*

**

**

Page 10: Computational methods for genomics-guided immunotherapy Sahar Al Seesi Computer Science & Engineering Department, UCONN Immunology Department, UCONN Health

Somatic Variant Callers• Mutect (Broad Inst.)• VarScan2 (Wash. U.)• SomaticSniper (Wash. U)• Strelka (Illumina)• SNVQ w/ subtraction (UConn)

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

TCR Sequencing

Normal Exome Reads

Human Reference

Tumor Exome Reads

****

*

**

**

Page 11: Computational methods for genomics-guided immunotherapy Sahar Al Seesi Computer Science & Engineering Department, UCONN Immunology Department, UCONN Health

The ICGC-TCGA DREAM Somatic Mutation Calling Challenge• Initial Goal: Find the Best WGS Analysis Methods• Challenge 1 Data: 10 Real Tumor/Normal pairs

– 5 from pancreatic tumors and 5 from prostate tumors– Sequenced to ~50x/30x

• Up to 10K candidates will be validated• Re-sequencing to ~300x coverage using AmpliSeq

primers on IonTorrent

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

TCR Sequencing

Page 12: Computational methods for genomics-guided immunotherapy Sahar Al Seesi Computer Science & Engineering Department, UCONN Immunology Department, UCONN Health

• Criteria for selecting candidate epitopes1) Gene harboring the SNV must be expressed (FPKM

estimation)

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

TCR Sequencing

Tumor RNA-Seq Reads

* ***

Page 13: Computational methods for genomics-guided immunotherapy Sahar Al Seesi Computer Science & Engineering Department, UCONN Immunology Department, UCONN Health

• Criteria for selecting candidate epitopes1) Gene harboring the SNV must be expressed2) Peptide will be generated inside the cell upon protein being

cleaved by the proteasome3) Peptide will bind to an MHC molecule that will chaperon it to the

cell surface • NetChop

Predicts cleavage sites of the human proteasome http://www.cbs.dtu.dk/services/NetChop/• SYFPEITHI Predicts MHC I, MHC II binding http://www.syfpeithi.de/• NETMHC Predicts MHC I binding http://www.cbs.dtu.dk/services/NetMHC/• NetCTL

Combined cleavage and MHC biding predictions http://www.cbs.dtu.dk/services/NetCTL/

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

TCR Sequencing