1. Statistical Learning of Next-Generation Sequencing T cell Repertoire Data
Li Zhang, Ph.D.
Associate Professor
Department of Medicine
Department of Epidemiology and Biostatistics
Helen Diller Family Comprehensive Cancer Center
University of California San Francisco

2. Acknowledgements Lawrence Fong, MD (PI), Immunologist and oncologist
Dave Oh, MD Ph.D. , Jason Cham and Alan Parcicok
San Francisco State University
Dr. Tao He, Assistant Professor

3. Combinatorial Diversity of Human β Locus
Freeman et. al Genome Research
TCRBeta locus at human chromosome 7q34
Recombination first occurs between TRBJ and TRBD genes, followed by recombination to a TRBV gene (Red lines).
After transcription, intervening sequences are spliced out so that a TRBC is adjacent to the recombined V-D-J sequence.
V(D)J recombination is not entirely random, and the prevalence of specific gene segments and combinations of gene segments shows marked variation in the repertoire.
T-cell repertoire is not static, but constantly molded by immune challenge
CDRs: Recognition specificity for diverse peptide-MHC (pMHC) complexes is provided by the three complementarity-determining regions (CDRs) of the TCR .
CDR1 and CDR2 are coded by germline sequences.
CDR3: the highly polymorphic principal recognition site, is created when TCR genomic loci undergo somatic recombination between gene segments during development of T lymphocytes in the thymus.
V(D)J recombination is not entirely random, and the prevalence of specific gene segments and combinations of gene segments shows marked variation in the repertoire.
T-cell repertoire is not static, but constantly molded by immune challenge.

4. T-cell Clonotype Tracking by TCRb SequencingV D J
~340bp
Consensus
primers
VH-FR1
~270bp JH
VH-FR2
~140bp
VH-FR3
Multiplexed PCR
Next generation sequence
CCCAGTAAC
T cells express T cell receptors (TCR) on the surface that determines the cell’s specificity. TCRs are formed by splicing together V, D, and J segments. The junctions between the V-D and D-J segments have insertions and deletions of random nucleotides, which add even more diversity. We sequenced the CDR3 region of the TCRβ region that spans these junctions by a next-generation sequencing-based method. We are able to identify unique T cell clones based on their TCRβ nucleotide sequence and determine frequency of the detected sequence. This allows us to track clonal expansion or contraction of the T cell repertoire in response to the Sip-T treatment.
Blue and purple TCR
Yellow and orange: NHC
Primer for each V,J segment
Primer uses library
Spike-in
a multiplex polymerase chain reaction (PCR) system was used to amplify the rearranged CDR3β sequences from sample DNA
We only look at beta chain (half of TCR)
ImmunoSEQ assay (Adaptive Biotechnologies, Seattle, WA)
Blue and purple represent the TCR, yellow is MHC, grey is the part MHC show to TCR, red arrows are primers
beta chain is generated by VDJ recombination (both involving a somewhat random joining of gene segments to generate the complete TCR chain
TCRb is TCR beta chain
GGGTCATTG
Count
1 AAAGCGACATTGGGATCTGTCAGTTGTCATTCGCG 1321
2 GCGGTTTTGTAGAAGGTTAGGGGAATAGGTTAGAT 1122
3 TGAGTGGCTTAAGAATGTAAAATCTGGGATTATAG 901
4 TGTAGTAATCTCTGATTAACGGTGACGGTTTTAAG 534
5 GAAGAATAATTAAGAAAAAAGCACCCCTCGTCGCC 421
6 TAGAATTACCTACCGCGGTCCACCATACCTTCGAT 132
7 TATCGCGCCCACTCTCCCATTAGTCGGCAGAGGTG 113
Independent Sequence Reads Per Run
(Adapted from Aaron Logan)

5. Typical TCR Sequencing Data
Clone_Sequence
Clone_Protein_Sequence
CDR3_Sense_Sequence
J_Segment_Major_
Gene
V_Segment_Major_
Count
Frequency
CAAGACAGAGAACCGATCACTGAGCAGCCTTGATTTTTCTAGTTGAGCTTCATTCTGGAAGTAAGTCAGAAACTCTGGGCCCTGCCCCAGGGTT
TLGQGPEFLTYFQNEAQLEKSRLLSDRFSVL
TGGGGCAGGGCCCAGAGTTTCTGACTTACTTCCAGAATGAAGCTCAACTAGAAAAATCAAGG
TRBJ1-4
TRBV7-9 3
-5.189
CAAGACAGAGAACTGTTGTGCGGAGAATCGTTCAAGAATGTTTCCTTTTGCTCTCTCTTCTCCATTATAATACTGAATGAGGAACTGGAGGCCC
GLQFLIQYYNGEERAKGNILERFSAQQFSVL
AGTATTATAATGGAGAAGAGAGAGCAAAAGGAAACATTCTTGAACGA
TRBV9 2
-5.365
CAAGACAGAGACACTGTACCCCTCAGGAATATCTCCTTTTTCTTTCATTTTAACATCATATGAGAAATAGATCAGCCGTAGCCCCAGACCTGGG
PGLGLRLIYFSYDVKMKEKGDIPEGYSVSVL
ATGAAAGAAAAAGGAGATATT
TRBV28
CAAGACAGAGAGCTGGGTTCCACTGCCAAAAAAACAGTTTTTCATTAGTTGTGGGACTGCTGGCACAGAAGTACATGGCTGAGTCCTCCAGCTT
SWRTQPCTSVPAVPQLMKNCFFGSGTQLSVL
TGTGCCAGCAGTCCCACAACTAATGAAAAACTGTTTTTTT
TRBV2
Should I explain what count frequency ?
One subject one file > 20 MB
Large number of unique nucleotides: 0.1M~1M
Uniqueness and dynamics: limited overlap nucleotides 10%-20%

6. Analysis Pipeline Clone-level VJ gene-level:
3D Analysis: Diversity, Dynamics & Differential Testing
VJ gene-level:
Feature selection by random forest: to select the important V and J gene
Hierarchical Clustering: to distinguish the subjects based on the selected important V and J genes
Pattern recognition by time-point change analysis: to recognize the gene abundance change across time

7. Study Design Ipi: once every 4 weeks
GM-CSF: everyday first 2 weeks for every 4 weeks
mCRPC and melanoma patients

8. VJ gene usage from baseline to post-treatment significantly different between mCRPC patients and melanoma patients
The first part of the genes show more changes in and the 2nd part of genes show more changes in
Jason, can you find some biological relevalnce.

9. At-most-one (AMO) change point detection for gene usage shows that more changes happened from C1 to C2 in melanoma patients, but more changes happened from C2 to C3 in mCRPC patients.