Computational methods for genomics-guided immunotherapy

Sahar Al Seesi and Ion MăndoiuComputer Science & Engineering Department

University of Connecticut

Class I endogenous antigen presentation

Somatic rearrangement of T-cell receptor genes

Potential TCR repertoire diversity: 1015

T-cell selection in thymus

Estimated TCR repertoire diversity after selection: ~2x107

T-cell activation and proliferation

T-cell activation and proliferation

T-cell activation and proliferation

The immune system and cancer

Cutting the brakes: PD1 and CTLA-4 blockade

Stepping on the gas: vaccination with neoepitopes

Combined approach

Ton N. Schumacher, and Robert D. Schreiber Science 2015;348:69-74

Sequencing QC and Mapping

Calling SNVs

EpitopePrediction

Clonality Analysis

Vaccine Design

TCR Sequencing

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

Clonality Analysis

Vaccine Design

TCR Sequencing

Ion Proton

Tumor DNA

Sequencing

Exome AmpliSeq

Normal DNA Tumor RNA

Ion PGM

Sequencing

Whole TranscriptomeLibrary prep

Whole GenomeLibrary prep

or

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

Clonality Analysis

Vaccine Design

TCR Sequencing

# of reads # of bases Mean of reads lengths std of reads lengths

Melanoma Patient

PB 25,031,340 3,272,787,408 130.74 66.88

1T 19,252,932 2,589,624,915 134.5 68.67

2T 28,400,728 4,147,914,801 146.04 66.91

3T 26,039,006 3,800,446,471 145.95 67.02

Synthetic Tumor

Normal 20,726,352 3,353,732,704 161.81 63.35

TumorAF10 20,726,352 3,360,840,809 162.15 63.14

TumorAF20 20,726,352 3,367,827,877 162.49 62.92

ION-Torrent Proton Runs: read statistics

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

Clonality Analysis

Vaccine Design

TCR Sequencing

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

Clonality Analysis

Vaccine Design

TCR Sequencing

Normal Exome Reads

Tumor Exome Reads

Tumor RNA-Seq Reads

Human reference

Human reference

• fastq QC Tools Tools to analyze and preprocess fastq files

– FASTX (http://hannonlab.cshl.edu/fastx_toolkit/)• Charts quality statistics• Filters sequences based on quality• Trims sequences based on quality• Collapses identical sequences into a

single sequence

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

Clonality Analysis

Vaccine Design

TCR Sequencing

• fastq QC Tools Tools to analyze and preprocess fastq files

– PRINSEQ (http://prinseq.sourceforge.net/)• Generates read length and quality statistics• Filters reads based on length, quality, GC

content and other criteria• Trims reads based on length/position or quality

scores

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

Clonality Analysis

Vaccine Design

TCR Sequencing

• Mapping decisions– What is the best mapper for your data?

– End-to-end unspliced alignments vs. spliced or local alignments

– Unique vs. non-unique alignments

Normal Exome Reads

Tumor Exome Reads

Tumor RNA-Seq Reads

Human reference

Human reference

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

Clonality Analysis

Vaccine Design

TCR Sequencing

    Bowtie2 TMAP Segemehl

 

% of aligned bases Aligned reads length mean

% of aligned bases Aligned reads length mean

% of aligned bases 2

Aligned reads length mean2

Melanoma Patient

PB 89% 138.8 100% 130.7 99% 135.4

1T 90% 143.3 100% 134.5 99% 140.4

2T 90% 153.3 100% 146 99% 150.3

3T 91% 153.4 100% 146 99% 150.4

Synthetic Tumor

Normal 89% 172.89 100% 161.81 98% 167.66

Tumor_AF10 89% 173.03 100% 162.15 99% 167.87

Tumor_AF20 89% 173.17 100% 162.49 99% 168.08

ION-Torrent Proton read mapping comparison

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

Clonality Analysis

Vaccine Design

TCR Sequencing

Normal Exome Reads

Human reference

*

***

***

*

*

*

Tumor Exome Reads

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

Clonality Analysis

Vaccine Design

TCR Sequencing

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

Normal Exome Reads

Human reference

*

***

***

*

*

*

Tumor Exome Reads

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

Clonality Analysis

Vaccine Design

TCR Sequencing

Coverage distribution of exome vs. SNV calls

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

Clonality Analysis

Vaccine Design

TCR Sequencing

0 20 40 60 80 100 120 140 160 180 2000%

5%

10%

15%

20%

25%

30%

35%

40%

CCDS HCC1954BLCCDS HCC1954MutectSNVQSniperStrelkaVarscan2

Read depth

% o

f var

iant

s cal

led

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 NA19240 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.

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

Clonality Analysis

Vaccine Design

TCR Sequencing

Bowtie2 TMAP Semegehl Bowtie2 TMAP Semegehl Bowtie2 TMAP Semegehl Bowtie2 TMAP Semegehl Bowtie2 TMAP SemegehlTP 464 476 470 1,573 1,738 - 402 440 360 22 10 17 92 91 7 FP 1,232 341 295 331 218 - 85 80 80 3,050 1,469 1,344 1,971 1,056 20 FN 11,823 11,811 11,817 10,714 10,549 - 11,885 11,847 11,927 12,265 12,277 12,270 12,195 12,196 12,280 TP 2,506 2,605 2,668 4,220 4,475 - 1,094 1,183 994 35 15 20 797 836 837 FP 1,224 341 286 302 191 - 55 54 54 3,178 1,548 1,422 1,978 1,015 447 FN 9,781 9,682 9,619 8,067 7,812 - 11,193 11,104 11,293 12,252 12,272 12,267 11,490 11,451 11,450 TP 4,608 4,842 4,910 5,776 6,089 - 1,526 1,637 1,379 61 31 29 1,922 1,994 1,994 FP 1,219 364 307 317 199 - 43 39 46 3,235 1,618 1,471 1,952 1,013 476 FN 7,679 7,445 7,377 6,511 6,198 - 10,761 10,650 10,908 12,226 12,256 12,258 10,365 10,293 10,293 TP 6,138 6,404 6,465 6,660 7,005 - 1,797 1,907 1,614 89 48 44 3,198 3,298 3,312 FP 1,259 378 333 362 241 - 40 40 46 3,338 1,661 1,528 2,018 1,071 505 FN 6,149 5,883 5,822 5,627 5,282 - 10,490 10,380 10,673 12,198 12,239 12,243 9,089 8,989 8,975 TP 7,018 7,309 7,359 7,232 7,592 - 1,937 2,037 1,732 163 104 41 4,284 4,466 4,489 FP 1,322 394 357 388 286 - 41 49 49 3,375 1,763 558 2,162 1,161 590 FN 5,269 4,978 4,928 5,055 4,695 - 10,350 10,250 10,555 12,124 12,183 12,246 8,003 7,821 7,798

mixture_AF_20

mixture_AF_30

mixture_AF_40

mixture_AF_50

SNVQ Strelka Mutect Sniper Varscan2

mixture_AF_10

Comparing Somatic Variant Callers

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

Clonality Analysis

Vaccine Design

TCR Sequencing

0 10 20 30 40 50 60 700

20

40

60

80

100

120

StrelkaSNVQMutectSniperVarscan2

Sensitivity

PPV

Comparing Somatic Variant Callers

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

Clonality Analysis

Vaccine Design

TCR Sequencing

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 an IonTorrent

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

Clonality Analysis

Vaccine Design

TCR Sequencing

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

estimation)• IsoEM (Nicolae et. al., Algorithms for Molecular Biology, 2011) http://dna.engr.uconn.edu/?page_id=105

• RSEM (Li et. al., BMC Bioinformatics, 2011) http://deweylab.biostat.wisc.edu/rsem/

Not Expressed X

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

Clonality Analysis

Vaccine Design

TCR Sequencing

• 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

Clonality Analysis

Vaccine Design

TCR Sequencing

Candidate neo-epitopes statistics for two mouse cell lines

Duan et. al., JEM 2014

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

Clonality Analysis

Vaccine Design

TCR Sequencing

Epi-Seq pipeline for neo-epitope prediction on local Galaxy server

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

Clonality Analysis

Vaccine Design

TCR Sequencing

• Rational vaccine design requires info on the clonal structure of the tumor– Not all cells harbor all candidate epitopes

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

Clonality Analysis

Vaccine Design

TCR Sequencing

• Approaches to clonality analysis1) Computational inference from sequencing depth

• SNV allelic fractions only

2) Targeted amplicon sequencing of selected mutations at single cell level

• More noisy data, potentially biased by capture protocols

Cell capture & pre-amp

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

Clonality Analysis

Vaccine Design

TCR Sequencing

PCR on Access Array

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

Clonality Analysis

Vaccine Design

TCR Sequencing

PCR on Access Array

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

Clonality Analysis

Vaccine Design

TCR Sequencing

Captured cells in pilot run

1 2 3 4 5 6 7 8 9 10 11 12

A 1_C03 1_C02 1_C01 1_C49 1_C50 1_C51 1_C06 3_C05 1_C04 1_C52 1_C53 1_C54

B 2_C09 1_C08 1_C07 1_C55 1_C56 1_C57 1_C12 1_C11 1_C10 1_C58 1_C59 1_C60

C 1_C15 2_C14 2_C13 1_C61 1_C62 1_C63 1_C18 2_C17 1_C16 1_C64 1_C65 1_C66

D 1_C21 2_C20 1_C19 1_C67 1_C68 1_C69 2_C24 2_C23 4_C22 1_C70 1_C71 1_C72

E bulk 2_C26 1_C27 1_C75 1_C74 1_C73 0_C28 0_C29 0_C30 1_C78 1_C77 2_C76

F 1_C31 0_C32 1_C33 1_C81 1_C80 1_C79 0_C34 1_C35 0_C36 1_C84 0_C83 1_C82

G 0_C37 1_C38 0_C39 1_C87 1_C86 1_C85 1_C40 1_C41 1_C42 1_C90 1_C89 1_C88

H 1_C43 1_C44 1_C45 1_C93 1_C92 1_C91 1_C46 1_C47 1_C48 1_C96 1_C95 1_C94

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

Clonality Analysis

Vaccine Design

TCR Sequencing

Analysis Pipeline96 fastq

files: one per well

pooled fastq file

Generate Referece

96x48 with total and fwd/rev

variant coverage for each well/SNV

Barcode list

List of SNV Locations

mm9 BALBc genome

fasta with +/- 300 bases

around each SNV

Fastx Barcode Splitter

tmap 96 sam files: one per well

compute coverage

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

Clonality Analysis

Vaccine Design

TCR Sequencing

Target Aligned Reads

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

Clonality Analysis

Vaccine Design

TCR Sequencing

- 20,000 40,000 60,000 80,000

100,000 120,000 140,000 160,000 180,000

Unaligned Reverse Forward

- 20,000 40,000 60,000 80,000

100,000

120,000 140,000 160,000 180,000

Unaligned Reverse Forward

Per SNV Coverage

chr1

0:20059582

chr1

1:101613424

chr1

1:6296832

chr1

:191675045

chr1

2:114383174

chr1

2:73884772

chr1

3:55554430

chr1

:57463849

chr1

5:85222168

chr1

7:27717774

chr1

7:53645675

chr1

9:24175196

chr2

:104271486

chr2

:166776842

chr3

:146082306

chr4

:62083556

chr6

:17257915

chr6

:71927367

chr7

:30151735

chr8

:268798280

50000

100000

150000

200000

250000

alt_revalt_fwdref_revref_fwd

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

Clonality Analysis

Vaccine Design

TCR Sequencing

Cells

SNV

s

SNV Support Matrix

Low High

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

Clonality Analysis

Vaccine Design

TCR Sequencing

A1 A2 A3 A4 A5 A6 A7 A8_3 A9 A10 A11 A12 B1_2 B2 B3 B4 B5 B6 B7 B8 B9 B10 B11 B12 C1 C2_2 C3_2 C4 C5 C6 C7 C8_2 C9 C10 C11 C12 D1 D2_2 D3 D4 D5 D6 D7_2 D8_2 D9_4 D10 D11 D12 E1_bulk E2_2 E3 E4 E5 E6 E7_0 E8_0 E9_0 E10 E11 E12_2 F1 F2_0 F3 F4 F5 F6 F7_0 F8 F9_0 F10 F11_0 F12 G1_0 G2 G3_0 G4 G5 G6 G7 G8 G9 G10 G11 G12 H1 H2 H3 H4 H5 H6 H7 H8 H9 H10 H11 H12Alt in forward 0 - - 0 0 1892 - - 1 - 0 0 509 501 101 0 79 0 2 828 419 0 - - - - 913 1668 2 1218 - - - - - - 0 - 1112 0 0 - 0 - 516 - 0 351 349 - 0 - 0 0 0 - 0 1017 - 2 - 0 1332 2389 1 1 - 2 - 723 - - 0 - 0 393 2243 2948 - 1254 - - - 472 - - 0 0 - 0 - - 1089 825 395 -Alt in reverse 0 - - 7 1 1312 - - 0 - 0 0 429 471 132 2 98 1 0 1093 461 0 - - - - 1083 1992 0 1413 - - - - - - 2 - 1285 1 0 - 0 - 728 - 0 266 505 - 0 - 1 2 0 - 0 1231 - 0 - 1 1776 2727 4 0 - 0 - 667 - - 0 - 1 344 2794 2786 - 956 - - - 367 - - 2 0 - 1 - - 1291 869 412 -Alt in forward 0 - - 1 6 - 1 610 550 24 958 132 1282 1545 688 0 2 1345 529 618 547 - 1354 - - 0 1050 2172 - 456 - - - 0 248 - 9 - 1184 0 1 - 807 1762 598 - 935 1213 362 - 0 396 - 0 0 - - 483 - 743 - 0 997 1 0 1 - 0 0 1238 - 6 0 0 0 843 - 3 1 - 2 0 1339 6 - 2 - 0 - 8 - - - 253 285 1Alt in reverse 2 - - 0 5 - 2 759 596 21 759 117 1412 1132 832 1 0 604 668 826 548 - 1170 - - 1 1262 2345 - 428 - - - 0 224 - 5 - 1499 1 0 - 1104 2102 746 - 1101 919 623 - 1 418 - 1 1 - - 441 - 912 - 0 1117 3 0 0 - 0 1 1146 - 0 1 1 0 655 - 1 0 - 0 0 1322 2 - 1 - 0 - 1 - - - 262 232 1Alt in forward 0 0 1239 0 2651 1225 103 11 1 1 748 1345 634 - 351 0 3 2641 285 666 1472 - 2 - 0 - 299 0 0 1059 - 0 - - 1099 0 - 1 2209 0 0 14 157 2 780 - 1325 662 587 - 1171 2475 - 1784 4 0 0 1734 - 477 - 0 - 1068 1 2 4 2 0 1592 0 2 1 0 0 2 0 1 2 81 4 0 1112 1747 2751 1433 0 - - 1 0 0 0 0 2 1Alt in reverse 4 0 3189 5 4018 1229 144 12 2 1 942 1964 1012 - 681 2 1 1971 519 1967 1879 - 0 - 0 - 430 1 1 2553 - 0 - - 1436 0 - 1 3522 5 0 19 362 0 1240 - 2478 589 1157 - 1889 3913 - 3342 7 1 1 2872 - 731 - 0 - 1598 13 0 1 1 0 2209 0 0 13 1 0 4 1 0 2 126 0 0 1947 2932 3357 1999 0 - - 2 0 0 0 2 0 0Alt in forward 0 - 0 0 - 225 338 688 266 986 - 562 678 - 213 0 0 21 632 1 143 - - - - 1 432 0 - 553 - - - - - - 0 577 - 1 - - 362 0 234 - 0 811 318 1486 0 0 - - - - - 682 - 425 - 0 - 0 0 - - 0 0 - - 2 1 - - 0 - 0 0 - 0 - 2 5 - 0 - - - 0 - - 0 176 246 0Alt in reverse 1 - 3 6 - 238 545 1216 380 1245 - 629 942 - 333 2 2 16 1001 0 210 - - - - 0 673 3 - 777 - - - - - - 0 889 - 3 - - 633 0 362 - 0 730 624 2574 0 1 - - - - - 962 - 755 - 0 - 5 0 - - 0 1 - - 0 0 - - 3 - 0 1 - 0 - 0 0 - 0 - - - 0 - - 0 253 293 0Alt in forward - - - 462 291 47 262 258 37 520 52 0 261 0 83 - 3 0 180 34 39 1 282 - - - 143 0 - 41 415 0 - - 370 - - - - - - 0 83 - 133 - 371 279 258 - 199 0 - 0 0 - - - - 108 - 2 428 - 0 - - - - 571 - 2 0 - - 92 - 0 0 0 1 0 1 582 1221 856 0 0 - 0 - - - 304 266 0Alt in reverse - - - 638 471 46 442 382 83 638 31 0 358 1 111 - 1 0 288 62 47 0 327 - - - 182 1 - 65 645 0 - - 518 - - - - - - 0 117 - 269 - 499 221 452 - 317 0 - 0 0 - - - - 182 - 0 711 - 1 - - - - 612 - 0 3 - - 111 - 1 0 0 1 0 0 684 1580 1079 2 0 - 1 - - - 363 277 2Alt in forward 0 - - 0 - - 338 1 558 719 27 972 0 - 0 0 773 1190 1 0 430 1 1 - - - 10 1799 5981 969 993 180 - - 56 - - - 57 0 - 4 1 1 296 - 885 229 263 - 466 1654 - 663 3 - 0 0 - 59 - - 1292 - 0 2 1 3 0 0 0 0 1 - - 1547 - 1 4 259 0 0 1216 0 2090 184 - 0 - 7 - - - 189 427 -Alt in reverse 0 - - 1 - - 394 0 580 678 11 657 0 - 1 0 725 482 0 0 336 0 0 - - - 9 1949 1942 980 980 159 - - 50 - - - 41 2 - 9 0 0 370 - 741 134 303 - 388 1726 - 769 2 - 0 0 - 85 - - 1417 - 5 0 0 0 0 0 0 0 6 - - 1288 - 0 0 155 0 1 842 1 2232 138 - 1 - 0 - - - 160 351 -Alt in forward - - - 351 0 25 164 173 325 - 26 16 11 - 104 50 424 0 227 98 79 - 94 - - - 14 0 - 0 354 - - - 163 - - 201 28 0 - 1 120 0 172 0 33 40 25 - 54 0 - 286 1 - 0 294 - 50 - - 0 0 0 1 - - 1 38 - 0 0 - - 339 - 1 0 83 - - 0 2 - - - 92 - - - - - 44 301 5Alt in reverse - - - 1284 0 50 539 1097 785 - 688 609 288 - 439 2309 1465 0 1142 672 194 - 490 - - - 564 5 - 0 892 - - - 870 - - 777 933 2 - 10 808 0 503 0 1227 507 1021 - 159 2 - 1145 1 - 1 1248 - 248 - - 1 1 2 0 - - 0 195 - 0 4 - - 1321 - 0 0 357 - - 14 20 - - - 405 - - - - - 152 1027 252Alt in forward 0 0 - 1 - 47 1 2 3 0 1376 - 234 1 0 0 1153 638 - 46 218 - 2 - 0 0 553 1397 0 0 - 1 - - 937 - 4 - - 0 - 3 0 4 172 1 460 43 383 - 238 1 - 796 1 0 1 1 - 469 - 2 - - 0 2 2 1 0 525 - 5 0 0 - 86 1 1 2 1 0 1 332 3 2147 - 0 0 - 2 - - 1260 30 312 -Alt in reverse 0 1 - 3 - 79 0 1 2 0 1303 - 313 0 1 0 1416 721 - 63 518 - 2 - 0 0 769 1731 1 1 - 0 - - 994 - 9 - - 0 - 11 0 2 423 0 725 52 745 - 528 2 - 1248 1 0 0 0 - 680 - 0 - - 9 0 0 1 0 517 - 0 9 0 - 113 0 0 0 2 0 0 457 0 2713 - 1 1 - 2 - - 1832 35 357 -Alt in forward 2 6 3 2 889 1367 170 1201 1 1115 2 850 1011 2450 888 7 6 2939 786 834 42 2 2 7 3 3 842 4 7 2 4 1588 0 1 2 - 0 710 83 4 5 6 1 6 706 1 86 1160 664 3 1188 1333 0 2 4 2 1 866 3 279 2 6 1 2 5 3 4 4 3 3 3 6 2 3 5 2542 2 4 6 1080 3 5 1842 7 1 1564 425 0 1 7 0 2 1323 1152 84 2Alt in reverse 3 0 5 5 1342 1183 238 1692 1 1377 1 1050 1471 2307 1430 12 6 1726 1138 1245 43 4 0 2 2 7 1197 12 4 1 7 2433 3 7 0 - 4 1004 133 6 3 3 4 6 1108 5 155 1155 1327 6 1414 1834 1 3 2 6 1 1385 3 467 2 8 3 9 9 3 3 3 2 1 3 0 8 4 4 2670 1 1 4 1063 4 2 2367 3 1 2024 499 2 0 3 4 0 1823 1310 96 3Alt in forward 0 - - 1852 0 1388 301 4 0 2 - 659 730 - 595 0 1739 0 3 689 126 1 1 0 - - 68 2130 - 982 - 555 - - 619 - 3044 1909 - 0 0 - 223 1 341 - 723 494 368 1 701 606 - 0 0 - 1 879 - 511 - 5 1395 0 1 2 - 1 - 1 1 7 1 0 - 920 0 1 4 1 2 - - 1244 1788 1532 1723 1543 - 1 0 - - 681 207 3Alt in reverse 1 - - 1974 2 1110 394 6 1 2 - 953 977 - 758 2 1720 0 4 1023 166 0 3 0 - - 108 2245 - 1142 - 793 - - 652 - 3930 2092 - 9 0 - 330 0 471 - 994 486 698 0 624 616 - 0 1 - 0 939 - 840 - 0 1787 0 9 1 - 0 - 0 0 0 7 1 - 833 1 1 0 0 0 - - 1092 1864 1482 1668 1859 - 0 2 - - 687 227 6Alt in forward - - - 0 - 2340 0 1124 0 - 0 136 745 1 1 - 0 1166 0 717 505 - 1015 - 1809 - 512 0 2 0 - - - - 1 - 0 0 - 2 - - 400 0 394 - 206 766 448 0 82 0 - 0 - - - 856 0 1 - 0 - 0 0 0 - 0 - 1241 - 0 0 - - 1204 - - 0 1 0 - - 0 - 0 0 1266 - 0 - - 1555 851 372 0Alt in reverse - - - 0 - 1146 0 717 0 - 0 85 883 0 0 - 0 355 0 438 336 - 547 - 1341 - 384 1 0 0 - - - - 0 - 0 0 - 2 - - 320 0 287 - 140 309 486 0 55 0 - 1 - - - 620 0 0 - 2 - 0 3 0 - 0 - 761 - 0 0 - - 729 - - 0 1 1 - - 0 - 0 1 883 - 0 - - 1120 502 258 1Alt in forward - 0 1408 1361 0 332 906 142 966 1119 375 1066 812 293 859 0 744 1648 233 567 710 - 331 0 1 - 326 1996 1 200 302 - - 0 831 0 1563 1051 1005 1 - 0 501 1620 452 0 68 563 353 0 1134 733 - 1 0 - 0 1102 - 403 - 1 1135 2470 0 1 0 0 - 749 2 7 1 - - 989 1 2 1 0 1 - 1 2 - 226 2 556 - 5 - - 861 482 367 1175Alt in reverse - 0 2390 1440 0 207 1085 180 940 1135 354 1150 939 227 931 2 715 664 247 798 736 - 250 0 0 - 405 2160 0 233 271 - - 0 779 0 2184 1323 1321 10 - 0 725 2097 536 0 88 431 488 0 1206 841 - 2 0 - 0 1249 - 501 - 1 1375 2775 4 0 0 0 - 749 0 0 1 - - 912 0 1 0 0 0 - 2 1 - 234 1 626 - 0 - - 1128 509 344 1780Alt in forward - - - 0 708 - 680 510 0 0 12 697 2 - 0 - 0 134 303 489 574 - - - - - 586 - 0 0 44 - - - 1064 - - 0 - 0 - - 0 - 327 - 23 759 299 0 585 994 - 0 0 - - 270 - 73 - 0 824 - 0 - - 2 1 1007 - 1 2 - - 1027 0 0 0 0 0 1 355 0 547 0 1179 - - 0 - - - 230 0 0Alt in reverse - - - 2 1035 - 833 742 0 0 7 532 1 - 0 - 1 64 422 839 543 - - - - - 673 - 0 0 56 - - - 1180 - - 0 - 2 - - 0 - 467 - 28 514 463 0 640 1166 - 2 1 - - 407 - 98 - 0 1041 - 5 - - 0 0 1073 - 0 1 - - 1059 0 0 0 0 0 0 276 0 569 0 1494 - - 0 - - - 219 0 0Alt in forward - 1 - 0 0 0 521 0 974 - 1285 3 1002 1429 139 0 1944 0 1508 203 131 3381 1 - 3188 - 1785 0 - 2710 - - 8 - 1955 - - 2 1977 1 1 0 718 0 736 0 1 2068 749 0 1808 0 0 0 1 - 1 0 0 0 - 1 227 0 6779 - - 3 - 277 - 0 0 - - 1662 - 0 - 1 0 1 0 0 - 0 0 0 - - - 0 0 1034 94 -Alt in reverse - 0 - 0 0 0 757 0 1259 - 1101 0 1214 1152 139 2 2043 4 1979 315 135 3807 0 - 4677 - 2215 0 - 3487 - - 0 - 2033 - - 0 2623 0 0 0 1026 1 1005 0 0 1741 1389 1 2130 4 0 2 0 - 0 1 0 0 - 0 326 4 1154 - - 0 - 286 - 0 0 - - 1709 - 4 - 4 0 0 0 0 - 3 3 0 - - - 1 0 1020 76 -Alt in forward - - - 1 - - - 2 - 182 - 342 209 - 532 0 358 903 569 337 695 - - - 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- 0 277 3 - 663 - - - 0 6 - - 4 1863 1 - 0 0 0 355 - 246 186 424 - 481 2 - 2 0 - - 658 2 1 - - 484 - 1 0 0 1 1 1 - 0 0 1 - 0 - 0 0 3 0 - 768 1602 - 9 9 - - 0 - - - 341 319 1

• Which Epitopes go into the vaccine?1) Diversify across HLA alleles2) Select mutations with balanced allele specific

expression3) Maximize (expected) clone coverage4) Include epitopes with high MHC binding affinity5) Include epitopes with high Differential Agretopic

Index (DAI): difference in MHC affinity between mutant epitope and its wild type counter part

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

Clonality Analysis

Vaccine Design

TCR Sequencing

Duan et. al., JEM 2014

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

Clonality Analysis

Vaccine Design

TCR Sequencing

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

Clonality Analysis

Vaccine Design

TCR Sequencing

• Expitope (Haase et. al., Bioinformatics 2014) – Checks for cross-reactivity based on ENCODE RNA-Seq from normal

tissues– http://webclu.bio.wzw.tum.de/expitope/

• OptiTope (Toussaint and Kohlbacher, Nucleic Acid Research 2009)– Optimizes allele coverage– http://etk.informatik.uni-tuebingen.de/optitope

Toussaint and Kohlbacher, Nucleic Acid Research 2009

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

Clonality Analysis

Vaccine Design

TCR Sequencing

• T Cell Receptor sequencing – Compare the TCR repertoire before and after

immunization to determine response against used epitope(s)

• Primary analysis of TCR sequencing data– IMSEQ (Kuchenbecker et. al., Bioinformatics 2015) http://www.imtools.org/

– HTJoinSolver (Russ et. al., BMC Bioinformatics 2015)

https://dcb.cit.nih.gov/HTJoinSolver/

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

Clonality Analysis

Vaccine Design

TCR Sequencing

• tcR (Nazarov et. al., BMC Bioinformatics, 2015)– R package for downstream analysis, including diversity

measures, shared T cell receptor sequences identification http://imminfo.github.io/tcr/

Sequencing QC and Mapping

Calling SNVs

Epitope Prediction

Clonality Analysis

Vaccine Design

TCR Sequencing

• QC• FASTX: http://hannonlab.cshl.edu/fastx_toolkit /)• PRINSEQ: http://prinseq.sourceforge.net/)

• Epitope prediction• NetChop: http://www.cbs.dtu.dk/services/NetChop/• SYFPEITHI: http://www.syfpeithi.de/• NETMHC: http://www.cbs.dtu.dk/services/NetMHC /• NetCTL: http://www.cbs.dtu.dk/services/NetCTL /

• Tumor Specific epitope predicton pipeline • Epi-Seq: http://dna.engr.uconn.edu/? page_id=470Also available on out galaxy server: http://mhc1.engr.uconn.edu:8080 /

• Vaccine design• Expitope: http://webclu.bio.wzw.tum.de/expitope/• OptiTope: http://etk.informatik.uni-tuebingen.de/optitope

• TCR sequencing analysis• Epi-Seq: http://imminfo.github.io/tcr/

THANK YOU!