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Cited by 134Cancer Immunotherapy and BiomarkersT-cell and B-cell ImmunologyImmunotherapy and Immune Responses

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Global analysis of shared T cell specificities in human non-small cell lung cancer enables HLA inference and antigen discovery

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Chiou, Shin-Heng, Tseng, Diane, Reuben, Alexandre, Mallajosyula, Vamsee, Molina, Irene S., Conley, Stephanie, Wilhelmy, Julie, McSween, Alana M., Yang, Xinbo, Nishimiya, Daisuke, Sinha, Rahul, Nabet, Barzin Y., Wang, Chunlin, Shrager, Joseph B., Berry, Mark F., Backhus, Leah, Lui, Natalie S., Wakelee, Heather A., Neal, Joel W., Padda, Sukhmani K., Berry, Gerald J., Delaidelli, Alberto, Sorensen, Poul H., Sotillo, Elena, Tran, Patrick, Benson, Jalen A., Richards, Rebecca, Labanieh, Louai, Klysz, Dorota D., Louis, David M., Feldman, Steven A., Diehn, Maximilian, Weissman, Irving L., Zhang, Jianjun, Wistuba, Ignacio I., Futreal, P. Andrew, Heymach, John V., Garcia, K. Christopher, Mackall, Crystal L., Davis, Mark M.·2021·Immunity
DOI 10.1016/j.immuni.2021.02.014PMC PMC7960510
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Abstract

To identify disease-relevant T cell receptors (TCRs) with shared antigen specificity, we analyzed 778,938 TCRβ chain sequences from 178 non-small cell lung cancer patients using the GLIPH2 (grouping of lymphocyte interactions with paratope hotspots 2) algorithm. We identified over 66,000 shared specificity groups, of which 435 were clonally expanded and enriched in tumors compared to adjacent lung. The antigenic epitopes of one such tumor-enriched specificity group were identified using a yeast peptide-HLA A ∗ 02:01 display library. These included a peptide from the epithelial protein TMEM161A, which is overexpressed in tumors and cross-reactive epitopes from Epstein-Barr virus and E. coli . Our findings suggest that this cross-reactivity may underlie the presence of virus-specific T cells in tumor infiltrates and that pathogen cross-reactivity may be a feature of multiple cancers. The approach and analytical pipelines generated in this work, as well as the specificity groups defined here, present a resource for understanding the T cell response in cancer.

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Graphical abstract CC BY-NC-ND · PubMed Central
Figure 1 Establishing specificity groups with CDR3β sequences from lung cancer patients (A) Analysis of shared T cell specificities with the GLIPH2 algorithm. Step 1: 778,938 CDR3β sequences from the MDACC cohort as input for GLIPH2 analysis. Step 2: establish 66,094 specificity groups with multiple criteria (Figure S1A). Step 3: establish 4,226 clonally expanded specificity groups. Step 4: establish 435 clonally expanded, tumor-enriched specificity groups. (B) Clinical relevance of tumor-enriched specificity groups in lung cancer. The most clonally expanded CDR3β sequences from tumors belonged to the 435 tumor-enriched specificity groups, whereas those from lung tissues of healthy donors and COPD patients did not. The trend was validated with tumors from a second NSCLC cohort (the TRACERx consortium, n = 202, validation). ∗∗∗p < 0.001; ∗p < 0.05 by paired t test. NS, not significantly different. (C) Network analysis of 396 specificity groups annotated with CDR3β sequences from HLA tetramers with flu (red), EBV (green), and CMV (blue) antigens. Each dot is a specificity group, edges indicate the presence of identical CDR3β sequence(s) shared across two specificity groups. (D) Percentage (%) of HLA-A∗02 or HLA-B∗08 tetramer-annotated specificity groups with significantly enriched the A∗02 (purple, left plot) or B∗08 (blue, right plot) supertype alleles, respectively. Specificity groups annotated with tetramers of other HLA alleles (other tetramer) were included for comparisons. (E) Percentage of shared specificity between any two given MDACC NSCLC patients (% shared between any 2 patients, total n = 178) based on CDR3β membership in total specificity groups regardless of clonal expansion (n = 66,094), membership in clonally expanded specificity groups (n = 4,226), or comparison of identical CDR3β sequences. Boxes represent medians with the first (25th) and third (75th) quartiles. (F and G) Bootstrapping of specificity group numbers (y axis, specificity group #) with varying sampling sizes (individuals sampled) for either HLA-A∗02+ or HLA-A∗02− NSCLC patients (F) or healthy donors (G, Emerson study). Data represent means with 3× standard errors from repeated sampling.
Figure 1 Establishing specificity groups with CDR3β sequences from lung cancer patients (A) Analysis of shared T cell specificities with the GLIPH2 algorithm. Step 1: 778,938 CDR3β sequences from the MDACC cohort as input for GLIPH2 analysis. Step 2: establish 66,094 specificity groups with multiple criteria (Figure S1A). Step 3: establish 4,226 clonally expanded specificity groups. Step 4: establish 435 clonally expanded, tumor-enriched specificity groups. (B) Clinical relevance of tumor-enriched specificity groups in lung cancer. The most clonally expanded CDR3β sequences from tumors belonged to the 435 tumor-enriched specificity groups, whereas those from lung tissues of healthy donors and COPD patients did not. The trend was validated with tumors from a second NSCLC cohort (the TRACERx consortium, n = 202, validation). ∗∗∗p < 0.001; ∗p < 0.05 by paired t test. NS, not significantly different. (C) Network analysis of 396 specificity groups annotated with CDR3β sequences from HLA tetramers with flu (red), EBV (green), and CMV (blue) antigens. Each dot is a specificity group, edges indicate the presence of identical CDR3β sequence(s) shared across two specificity groups. (D) Percentage (%) of HLA-A∗02 or HLA-B∗08 tetramer-annotated specificity groups with significantly enriched the A∗02 (purple, left plot) or B∗08 (blue, right plot) supertype alleles, respectively. Specificity groups annotated with tetramers of other HLA alleles (other tetramer) were included for comparisons. (E) Percentage of shared specificity between any two given MDACC NSCLC patients (% shared between any 2 patients, total n = 178) based on CDR3β membership in total specificity groups regardless of clonal expansion (n = 66,094), membership in clonally expanded specificity groups (n = 4,226), or comparison of identical CDR3β sequences. Boxes represent medians with the first (25th) and third (75th) quartiles. (F and G) Bootstrapping of specificity group numbers (y axis, specificity group #) with varying sampling sizes (individuals sampled) for either HLA-A∗02+ or HLA-A∗02− NSCLC patients (F) or healthy donors (G, Emerson study). Data represent means with 3× standard errors from repeated sampling.CC BY-NC-ND · PubMed Central
Figure 2 The TCR members of the tumor-enriched specificity group with the motif “S%DGMNTE” are inferred to recognize tumor antigen in the context of HLA-A∗02 (A) Left: volcano plot showing the comparison of the 4,226 clonally expanded specificity groups between tumor (T) and the adjacent lung (N) by Poisson test. The y axis represents the negative log10 converted p values of the Poisson test, and the x axis represents the log2 converted fold difference between tumor and adjacent lung (T/N). Dot size represents levels of clonal expansion. Tumor-enriched specificity groups (n = 435) are highlighted in red. Right: volcano plot of T/N comparison for CDR3β clonotypes. CDR3β clones of the 435 tumor-enriched specificity groups (left) are highlighted in red. (B) Pearson correlations and the corresponding p values between the signature scores for the hallmark GSEA gene sets (n = 50) and the percentages of CDR3β clones belonging to the 435 tumor-enriched specificity groups. Significant comparisons are highlighted in red (p < 0.05). (C) Heatmap showing the −log10 p values of top-enriched HLA allele(s) of the 435 tumor-enriched specificity groups. Top, number of MDACC patients carrying each indicated HLA alleles. (D) Number of top-enriched HLA allele(s) found in each of the 435 tumor-enriched specificity groups. (E) Volcano plot for the 4,226 NSCLC specificity groups as in (A, left). The tumor-enriched specificity groups significantly enriched with HLA-A∗02 alleles (p < 0.05 by Fisher’s exact test) are colored in green. The specificity group “S%DGMNTE” is highlighted. (F) The distinct CDR3β sequence members of the “S%DGMNTE” specificity group. For each CDR3β sequence, the Vβ gene usage (Vβ), number of patients with each sequence (patient counts), number of HLA-A∗02+ patients (counts of HLA-A∗02+ cases/total), and the average clonal frequencies (% by patient) found in the adjacent lung, tumor, and peripheral blood are shown. ND, not detected. Bottom: p values for the enrichment of Vβ gene usage, HLA-A∗02 alleles, and the level of clonal expansion are shown.
Figure 2 The TCR members of the tumor-enriched specificity group with the motif “S%DGMNTE” are inferred to recognize tumor antigen in the context of HLA-A∗02 (A) Left: volcano plot showing the comparison of the 4,226 clonally expanded specificity groups between tumor (T) and the adjacent lung (N) by Poisson test. The y axis represents the negative log10 converted p values of the Poisson test, and the x axis represents the log2 converted fold difference between tumor and adjacent lung (T/N). Dot size represents levels of clonal expansion. Tumor-enriched specificity groups (n = 435) are highlighted in red. Right: volcano plot of T/N comparison for CDR3β clonotypes. CDR3β clones of the 435 tumor-enriched specificity groups (left) are highlighted in red. (B) Pearson correlations and the corresponding p values between the signature scores for the hallmark GSEA gene sets (n = 50) and the percentages of CDR3β clones belonging to the 435 tumor-enriched specificity groups. Significant comparisons are highlighted in red (p < 0.05). (C) Heatmap showing the −log10 p values of top-enriched HLA allele(s) of the 435 tumor-enriched specificity groups. Top, number of MDACC patients carrying each indicated HLA alleles. (D) Number of top-enriched HLA allele(s) found in each of the 435 tumor-enriched specificity groups. (E) Volcano plot for the 4,226 NSCLC specificity groups as in (A, left). The tumor-enriched specificity groups significantly enriched with HLA-A∗02 alleles (p < 0.05 by Fisher’s exact test) are colored in green. The specificity group “S%DGMNTE” is highlighted. (F) The distinct CDR3β sequence members of the “S%DGMNTE” specificity group. For each CDR3β sequence, the Vβ gene usage (Vβ), number of patients with each sequence (patient counts), number of HLA-A∗02+ patients (counts of HLA-A∗02+ cases/total), and the average clonal frequencies (% by patient) found in the adjacent lung, tumor, and peripheral blood are shown. ND, not detected. Bottom: p values for the enrichment of Vβ gene usage, HLA-A∗02 alleles, and the level of clonal expansion are shown.CC BY-NC-ND · PubMed Central
Figure 3 Identification of tumor and pathogen-derived antigens recognized by a tumor-enriched TCR in human lung cancer (A) Top: top-20 mimotopes from the 4th round of selection on an 11-mer yeast library are used to stimulate Jurkat-TCR2 cells. CD69 fold change is shown compared to unstimulated control. Bottom: ranked raw counts (log10) of the enriched mimotopes from the selection. (B) Alignment of the top-two mimotopes with peptides from the human TMEM161A locus, EBV LMP-2A, and E. coli EntS. All peptides were 9-mers and predicted to bind HLA-A∗02 with high affinities. (C) Left: representative FACS plots showing the stimulation of the Jurkat-TCR2 cells with 9-mers from the human TMEM161A locus (TMEM9-mer), LMP-2A of EBV (LMP9-mer), and EntS from E. coli (EntS9-mer); right: results of Jurkat-TCR2 cell stimulation in triplicate. Control PP, control peptide (GILGFVFTL); No PP, no peptide. (D) Stimulation of primary T cells ectopically expressing TCR2 TCRα/β chains with either 9-mers (left) or full-length proteins (right). Stimulation of primary T cells expressing TCR14 by 293T-A∗02 cells expressing full-length FluM1 protein was shown as control. ∗p < 0.05; ∗∗p < 0.01; ∗∗∗p < 0.001 by t test. Control PP, control peptide (GILGFVFTL). (E) The binding of TCR2 to the indicated A∗02/9-mers was determined by biolayer interferometry. An overlay of binding traces over a concentration series of the indicated A∗02/9-mers from one representative experiment is shown. The data points are represented as open circles and the fits from a simple 1:1 Langmuir interaction model are indicated by solid lines. Each binding experiment was repeated three times. (F) The equilibrium association constants (KA) of the surface plasma resonance as in (E). The flu M1 peptide showed no detectable binding (n.b.) to TCR2. Significance was determined by t test after one-way ANOVA. The reported p values were corrected for multiple comparisons. ∗∗p < 0.01. ND, not different. All error bars represent standard deviation of the mean.
Figure 3 Identification of tumor and pathogen-derived antigens recognized by a tumor-enriched TCR in human lung cancer (A) Top: top-20 mimotopes from the 4th round of selection on an 11-mer yeast library are used to stimulate Jurkat-TCR2 cells. CD69 fold change is shown compared to unstimulated control. Bottom: ranked raw counts (log10) of the enriched mimotopes from the selection. (B) Alignment of the top-two mimotopes with peptides from the human TMEM161A locus, EBV LMP-2A, and E. coli EntS. All peptides were 9-mers and predicted to bind HLA-A∗02 with high affinities. (C) Left: representative FACS plots showing the stimulation of the Jurkat-TCR2 cells with 9-mers from the human TMEM161A locus (TMEM9-mer), LMP-2A of EBV (LMP9-mer), and EntS from E. coli (EntS9-mer); right: results of Jurkat-TCR2 cell stimulation in triplicate. Control PP, control peptide (GILGFVFTL); No PP, no peptide. (D) Stimulation of primary T cells ectopically expressing TCR2 TCRα/β chains with either 9-mers (left) or full-length proteins (right). Stimulation of primary T cells expressing TCR14 by 293T-A∗02 cells expressing full-length FluM1 protein was shown as control. ∗p < 0.05; ∗∗p < 0.01; ∗∗∗p < 0.001 by t test. Control PP, control peptide (GILGFVFTL). (E) The binding of TCR2 to the indicated A∗02/9-mers was determined by biolayer interferometry. An overlay of binding traces over a concentration series of the indicated A∗02/9-mers from one representative experiment is shown. The data points are represented as open circles and the fits from a simple 1:1 Langmuir interaction model are indicated by solid lines. Each binding experiment was repeated three times. (F) The equilibrium association constants (KA) of the surface plasma resonance as in (E). The flu M1 peptide showed no detectable binding (n.b.) to TCR2. Significance was determined by t test after one-way ANOVA. The reported p values were corrected for multiple comparisons. ∗∗p < 0.01. ND, not different. All error bars represent standard deviation of the mean.CC BY-NC-ND · PubMed Central
Figure 4 TMEM161A protein is highly expressed in human lung cancer (A) Representative images of TMEM161A immunohistochemistry on tumor (top) and the adjacent lung (bottom) sections from four patients. Scale bar, 100 μm. Rightmost panels: zoomed in images of patient A16 tumor with TMEM161A immunohistochemistry (top) and H&E staining on a serial section (bottom). Scale bar, 40 μm. (B) Quantification of TMEM161A immunohistochemistry on sections from the Stanford NSCLC cohort (n = 11). Boxplots show medians with the first (25th) and third (75th) quartiles with individual data points. ∗∗∗p < 0.001. (C) TMEM161A expression quantified by bulk RNA-seq of the indicated samples from TCGA (n = 958) is shown in boxplots. Adj-Ctrl, the adjacent lung control. TMEM161A expression normalized against Adj-Ctrl is shown. p values were calculated with the Wilcoxon Rank Sum test. ND, not significantly different. Boxplots represent medians with the first (25th) and third (75th) quartiles. (D) Gene set enrichment analysis of the ranked gene list based on Pearson correlation with TMEM161A abundance in the pan-lung cancer TCGA dataset (n = 958). Left: hallmark gene sets with highest (blue) and lowest (red) normalized enrichment scores are indicated, and their enrichment curves are shown (right). (E) Single-sample GSEA signature scores (Sig score) of two most and two least enriched hallmark signatures are plotted against TMEM161A expression. Pearson correlation coefficients are shown in plots (cor coef).
Figure 4 TMEM161A protein is highly expressed in human lung cancer (A) Representative images of TMEM161A immunohistochemistry on tumor (top) and the adjacent lung (bottom) sections from four patients. Scale bar, 100 μm. Rightmost panels: zoomed in images of patient A16 tumor with TMEM161A immunohistochemistry (top) and H&E staining on a serial section (bottom). Scale bar, 40 μm. (B) Quantification of TMEM161A immunohistochemistry on sections from the Stanford NSCLC cohort (n = 11). Boxplots show medians with the first (25th) and third (75th) quartiles with individual data points. ∗∗∗p < 0.001. (C) TMEM161A expression quantified by bulk RNA-seq of the indicated samples from TCGA (n = 958) is shown in boxplots. Adj-Ctrl, the adjacent lung control. TMEM161A expression normalized against Adj-Ctrl is shown. p values were calculated with the Wilcoxon Rank Sum test. ND, not significantly different. Boxplots represent medians with the first (25th) and third (75th) quartiles. (D) Gene set enrichment analysis of the ranked gene list based on Pearson correlation with TMEM161A abundance in the pan-lung cancer TCGA dataset (n = 958). Left: hallmark gene sets with highest (blue) and lowest (red) normalized enrichment scores are indicated, and their enrichment curves are shown (right). (E) Single-sample GSEA signature scores (Sig score) of two most and two least enriched hallmark signatures are plotted against TMEM161A expression. Pearson correlation coefficients are shown in plots (cor coef).CC BY-NC-ND · PubMed Central
Figure 5 Isolation and characterization of cross-reactive TMEM161A-specific T cells from peripheral blood of healthy donors and lung cancer patients (A) Schematic showing the procedure used to capture antigen-specific T cell clones from HLA-A∗02+ healthy donors and NSCLC patients. Cells were sorted by FACS directly into 96-well plates for scRNA-seq and scTCR-seq. (B) Representative FACS plots of T cells sorted with indicated tetramers from the PBMC of HLA-A∗02+ healthy donors (He65 and He66) or HLA-A∗02+ NSCLC patients (A6 and A17). (C) Percentage of tetramer+ T cells from healthy donors (n = 11) and NSCLC patients (n = 7). Boxes represent medians with the first (25th) and third (75th) quartiles. NS, not significantly different. (D) Percentage of distinct CDR3β sequences in tetramer-sorted T cells from healthy donors and NSCLC patient. Numbers in plots represent the cell counts. (E) Indicated TCR clonotypes identified with tetramers were expressed in Jurkat cells and co-cultured with T2 cells pulsed with indicated 9-mers. y axis (fold stimulated) shows activation by CD69 fold change compared to unstimulated control. ∗∗∗p < 0.001. Ctrl peptide, control peptide (GILGFVFTL). (F and G) Cell-mediated cytotoxicity of H1395 lung cancer cells. Primary T cells ectopically expressing TCR2α/β chains were co-cultured with the A∗02+ H1395 cancer cells and pulsed with either no peptide, TMEM9-mer, or LMP9-mer. Representative images (F) and results using cells from two different donors (G) are shown. ∗∗p < 0.01; ∗∗∗p < 0.001 by t test. Error bars represent standard deviation of the mean.
Figure 5 Isolation and characterization of cross-reactive TMEM161A-specific T cells from peripheral blood of healthy donors and lung cancer patients (A) Schematic showing the procedure used to capture antigen-specific T cell clones from HLA-A∗02+ healthy donors and NSCLC patients. Cells were sorted by FACS directly into 96-well plates for scRNA-seq and scTCR-seq. (B) Representative FACS plots of T cells sorted with indicated tetramers from the PBMC of HLA-A∗02+ healthy donors (He65 and He66) or HLA-A∗02+ NSCLC patients (A6 and A17). (C) Percentage of tetramer+ T cells from healthy donors (n = 11) and NSCLC patients (n = 7). Boxes represent medians with the first (25th) and third (75th) quartiles. NS, not significantly different. (D) Percentage of distinct CDR3β sequences in tetramer-sorted T cells from healthy donors and NSCLC patient. Numbers in plots represent the cell counts. (E) Indicated TCR clonotypes identified with tetramers were expressed in Jurkat cells and co-cultured with T2 cells pulsed with indicated 9-mers. y axis (fold stimulated) shows activation by CD69 fold change compared to unstimulated control. ∗∗∗p < 0.001. Ctrl peptide, control peptide (GILGFVFTL). (F and G) Cell-mediated cytotoxicity of H1395 lung cancer cells. Primary T cells ectopically expressing TCR2α/β chains were co-cultured with the A∗02+ H1395 cancer cells and pulsed with either no peptide, TMEM9-mer, or LMP9-mer. Representative images (F) and results using cells from two different donors (G) are shown. ∗∗p < 0.01; ∗∗∗p < 0.001 by t test. Error bars represent standard deviation of the mean.CC BY-NC-ND · PubMed Central
Figure 6 Phenotypic characterization of the TMEM161A-specific CD8+ T cells (A and B) Dimension reduction by Uniform Manifold Approximation and Projection (UMAP) of the scRNA-seq data from 2,950 sorted tumor-infiltrating T cells from 10 NSCLC patients (Stanford cohort). The identified cell clusters (n = 14) are labeled with distinct colors (A) and shown with varying dot sizes representing the level of clonal expansion (B). (C) Clonality of the 2,950 sorted T cells as in (B) quantified as 1 - Pielou’s evenness. (D) Breakdown of cell states for T cell clones of the 4,226 specificity groups defined in Figure S1A (top), viral-related specificity groups (second from top), the 435 tumor-enriched specificity groups (third from top), and TMEM9-mer/A∗02 tetramer-sorted CD8 T cells from tumor (bottom, patient A6). (E) Heatmap showing differentially expressed genes for each cell cluster defined in (A). Select differential genes for cluster c5, c6, and c7 are highlighted. (F) Stacked violin plot showing the expression of highlighted differential genes in (E) in all cell clusters. (G) Pseudotime trajectory of CD8+ single cells by Monocle (v2.10.1). (H) Exhaustion score versus activation score for CD8+ T cells sorted by the HLA-A∗02/TMEM9-mer tetramer (top right) and those that belong to tumor-enriched specificity groups (bottom right), colored by the cluster identity. Exhausted CD8+ T cells (c11) and activated CTL (c12) are shown for comparison.
Figure 6 Phenotypic characterization of the TMEM161A-specific CD8+ T cells (A and B) Dimension reduction by Uniform Manifold Approximation and Projection (UMAP) of the scRNA-seq data from 2,950 sorted tumor-infiltrating T cells from 10 NSCLC patients (Stanford cohort). The identified cell clusters (n = 14) are labeled with distinct colors (A) and shown with varying dot sizes representing the level of clonal expansion (B). (C) Clonality of the 2,950 sorted T cells as in (B) quantified as 1 - Pielou’s evenness. (D) Breakdown of cell states for T cell clones of the 4,226 specificity groups defined in Figure S1A (top), viral-related specificity groups (second from top), the 435 tumor-enriched specificity groups (third from top), and TMEM9-mer/A∗02 tetramer-sorted CD8 T cells from tumor (bottom, patient A6). (E) Heatmap showing differentially expressed genes for each cell cluster defined in (A). Select differential genes for cluster c5, c6, and c7 are highlighted. (F) Stacked violin plot showing the expression of highlighted differential genes in (E) in all cell clusters. (G) Pseudotime trajectory of CD8+ single cells by Monocle (v2.10.1). (H) Exhaustion score versus activation score for CD8+ T cells sorted by the HLA-A∗02/TMEM9-mer tetramer (top right) and those that belong to tumor-enriched specificity groups (bottom right), colored by the cluster identity. Exhausted CD8+ T cells (c11) and activated CTL (c12) are shown for comparison.CC BY-NC-ND · PubMed Central
Figure 7 Virus-specific CD8 T cell clones expanded in patients responding to anti-PD1 treatment (A) Comparisons of pre- and post-treatment CDR3β clonal frequencies (in log10 percent) in the peripheral blood of patient M1 (left) and M2 (right). CDR3β clones inferred to recognize viral antigens are highlighted. (B) Specificity groups containing expanded CDR3β clones post-treatment (column 5, CDR3β sequence) from patients M1 or M2 (column 6, Patient ID) that are annotated with viral tetramer CDR3β sequences (column 2–4, antigen and HLA alleles of the tetramers). Enrichment of the A∗02:01 or B∗35:01 allele is shown (last two columns, p values from the hypergeometric tests are shown). CDR3α/β sequences of the two EBV-related expanded clones from patient M2 are shown at the bottom. (C) TCR27- (CDR3β: CASSTGDSNQPQHF, top panels) and TCR28- (CDR3β: CASSARTGELFF, bottom panels) Jurkat cell lines were created and tested for their reactivities to the predicted EBV antigens in the context of B∗35 as shown in (B). TCR27- and TCR28-Jurkat cells were co-cultured with T2-B∗35 cells pulsed with indicated peptides (above each plot). Level of activation was quantified with CD69 expression. Control peptide: LPFDFTPGY.
Figure 7 Virus-specific CD8 T cell clones expanded in patients responding to anti-PD1 treatment (A) Comparisons of pre- and post-treatment CDR3β clonal frequencies (in log10 percent) in the peripheral blood of patient M1 (left) and M2 (right). CDR3β clones inferred to recognize viral antigens are highlighted. (B) Specificity groups containing expanded CDR3β clones post-treatment (column 5, CDR3β sequence) from patients M1 or M2 (column 6, Patient ID) that are annotated with viral tetramer CDR3β sequences (column 2–4, antigen and HLA alleles of the tetramers). Enrichment of the A∗02:01 or B∗35:01 allele is shown (last two columns, p values from the hypergeometric tests are shown). CDR3α/β sequences of the two EBV-related expanded clones from patient M2 are shown at the bottom. (C) TCR27- (CDR3β: CASSTGDSNQPQHF, top panels) and TCR28- (CDR3β: CASSARTGELFF, bottom panels) Jurkat cell lines were created and tested for their reactivities to the predicted EBV antigens in the context of B∗35 as shown in (B). TCR27- and TCR28-Jurkat cells were co-cultured with T2-B∗35 cells pulsed with indicated peptides (above each plot). Level of activation was quantified with CD69 expression. Control peptide: LPFDFTPGY.CC BY-NC-ND · PubMed Central

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Authors
Chiou, S.-H., Tseng, D., Reuben, A., Mallajosyula, V., Molina, I. S., Conley, S., Wilhelmy, J., McSween, A. M., Yang, X., Nishimiya, D., Sinha, R., Nabet, B. Y., Wang, C., Shrager, J. B., Berry, M. F., Backhus, L., Lui, N. S., Wakelee, H. A., Neal, J. W., Padda, S. K., Berry, G. J., Delaidelli, A., Sorensen, P. H., Sotillo, E., Tran, P., Benson, J. A., Richards, R., Labanieh, L., Klysz, D. D., Louis, D. M., Feldman, S. A., Diehn, M., Weissman, I. L., Zhang, J., Wistuba, I. I., Futreal, P. A., Heymach, J. V., Garcia, K. C., Mackall, C. L., & Davis, M. M.
Affiliations
  • Stanford University (US)
  • Stanford Medicine (US)
  • The University of Texas MD Anderson Cancer Center (US)
  • Rutgers, The State University of New Jersey (US)
  • Institute for Stem Cell Biology and Regenerative Medicine (US)
  • BC Cancer Agency (CA)
  • Stanford Cancer Institute (US)
  • Howard Hughes Medical Institute (US)
Corresponding author
Davis, Mark M.
ORCID
Venue
Immunity
Publisher
Elsevier BV
Published
2021-03
Volume
54
Issue
3
Pages
586-602.e8
ISSN
1074-7613 (ISSN-L)
DOI
10.1016/j.immuni.2021.02.014
PMC
PMC7960510
OpenAlex
W3134245065
Cited by
133
References
77
Citations by year
2026: 20 · 2025: 19 · 2024: 26 · 2023: 28 · 2022: 29 · 2021: 10
FWCI
8.56
Type
journal article
Language
en
Open access
Licence
Locations
  • Immunity (publishedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • Rutgers University Community Repository (Rutgers University) (submittedVersion)
Funders
  • NCI Cancer Moonshot
  • Stand up to Cancer
Topics
  • Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
  • Life Sciences › Immunology and Microbiology › Immunology › T-cell and B-cell Immunology
  • Life Sciences › Immunology and Microbiology › Immunology › Immunotherapy and Immune Responses
Keywords
non-small cell lung cancer, T cell clones, cross-reactive epitopes, Epstein-Barr virus, Escherichia coli, virus-specific T cells, tumor immunology
MeSH terms
Algorithms, Antigens, Neoplasm, Carcinoma, Non-Small-Cell Lung, Cells, Cultured, Cross Reactions, Humans, Lung Neoplasms, Protein Binding, T-Lymphocytes, HLA-A2 Antigen, Receptors, Antigen, T-Cell, alpha-beta, Antigen Presentation, Epitope Mapping, Epitopes, T-Lymphocyte, T-Cell Antigen Receptor Specificity

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