1. Sahar Al Seesi University of Connecticut CANGS 2017
GeNeo: Bioinformatics toolbox for Genomics guided Neo-epitope prediction
Sahar Al Seesi
University of Connecticut
CANGS 2017

2. Class I endogenous antigen presentation

3. T-cell activation and proliferation

4. T-cell activation and proliferation

5. T-cell activation and proliferation

6. April, 2017

11. Read filtering

12. Normal Exome Reads
Human reference *
Tumor Exome Reads

13. Comparing Somatic Variant Callers
Synthetic Tumors
ION Torrent Proton exome sequencing of two 1K Genomes individual (mutations known)
Downloaded from the public Torrent server
Both exomes were sequenced on the same Proton chip
Subset of the NA19240 sample was used as the normal sample
Mixtures of NA and NA12878 samples were used as the tumor samples
Reads were mixed in different proportions to simulate allelic fractions, 0.1, 0.2, 0.3, 0.4 and 0.5.

14. Comparing Somatic Variant Callers

17. Results ATCC cell lines HCC1954: stage IIA, grade 3, ductal carcinoma
Proton Exome Sequencing
Illumina Exome Sequencing
Proton RNA-Seq
Illumina RNA-Seq
HCC1954BL: matched blood

18. What will we assess?
Sensitivity, specificity and PPV of the following filters (ways to select from CCCP call)
1 call
SNVQ Illumina
SNVQ Proton
Strelka Illumina
Strelka Proton
2 Calls
Illumina SNVQ and Strelka
Proton SNVQ and Strelka
SNVQ Illumina and Proton (cross platform)
Strelka Illumina and Proton (cross platform)
2CP : any 2 calls cross platform with relaxed condition for lack of coverage
Any 3 calls

20. We need ground truth to assess accuracy of the calls
1) AccessArray/ Ion Torrent amplicon sequencing
SNVs amplified using AccessArray and sequenced on PGM
81 called by CCCP
35 from Cancer Cell Line Encyclopedia (CCLE)
3 from an older CCCP run
Total: 111
Output analyzed using AccessArray demultiplexing tool

21. AccessArray demultiplexing tool

23. Access Array Validation
111 SNVs tested – 85 validated – 26 not validated

24. We need ground truth to assess accuracy of the calls
AccessArray/ Ion Torrent amplicon sequencing -108 SNVs
Validation by single cell sequencing (Fluidigm) – 84 SNVs

25. We need ground truth to assess accuracy of the calls
AccessArray/ Ion Torrent amplicon sequencing -108 SNVs
Validation by single cell sequencing (Fluidigm) – 84 SNVs
SNVs supported by RNA-Seq

26. Fluidigm Validation
84 validated

27. RNA Support as a proxy for PPV

28. Criteria for selecting candidate epitopes
Mutated epitope is expressed in the cell:
RNA Support filter

29. Criteria for selecting candidate epitopes
Mutated epitope is expressed in the cell:
RNA Support filter
Peptide will bind to an MHC molecule that will chaperone it to the cell surface
- EpitopeFinder/NetMHC

30. Criteria for selecting candidate epitopes
Mutated epitope is expressed in the cell:
RNA Support filter
Peptide will bind to an MHC molecule that will chaperone it to the cell surface
- EpitopeFinder/NetMHC
- Compute Differential Agretopic Index (DAI)

31. Duan et. al., JEM 2014

32. Criteria for selecting candidate epitopes
Mutated epitope is expressed in the cell:
RNA Support filter
Peptide will bind to an MHC molecule that will chaperone it to the cell surface
- EpitopeFinder/NetMHC
- Compute Differential Agretopic Index (DAI)
Mutated epitope is presented on significant number of tumor cells
- Amplicon sequencing of selected mutations at the single cell level

33. SNV Support Matrix Cells SNVs
Low High
Cells with less than 500 mapped reads filtered out
Mouse data (CM5 tumor cell line)

34. Summary CCCP: Consensus Caller Cross Platform somatic variant callers
Can be used with one technology or two
Set of filters to allow user to select variants at the desired stringency level
RNA support filter and dbSNP filter
Validation
Primer design tools ( Sanger sequencing and AccessArray)
AmpliSeq ION Torrent demultiplexing tool
Genome visualization tool
EpitopeFinder

35. Future Work 1000 Epitope project Pipeline enhancements
Build and train a predictive model for tumor rejection based on the peptide attributes
Pipeline enhancements
Incorporate indels in CCCP and AmpliSeq demultiplexing tool
Add flanking sequences to predicted epitopes

36. Acknowledgments Ion Mandoiu Pramod Srivastava Availability:
Anas Alokaily
Tatiana Shcheglova
Adam Hagymasi
Anu Kaur