. 2021 Aug;596(7870):126-132.

doi: 10.1038/s41586-021-03752-4. Epub 2021 Jul 21.

Transcriptional programs of neoantigen-specific TIL in anti-PD-1-treated lung cancers

Justina X Caushi^#^{1

2

3}, Jiajia Zhang^#^{1

2

3}, Zhicheng Ji^{4

5}, Ajay Vaghasia³, Boyang Zhang⁴, Emily Han-Chung Hsiue^{3

6

7}, Brian J Mog^{3

6

7}, Wenpin Hou⁴, Sune Justesen⁸, Richard Blosser^{1

3}, Ada Tam^{1

3}, Valsamo Anagnostou^{1

3}, Tricia R Cottrell^{1

2

3

9}, Haidan Guo^{1

2

3}, Hok Yee Chan^{1

2

3}, Dipika Singh^{1

2

3}, Sampriti Thapa^{1

2

3}, Arbor G Dykema^{1

2

3}, Poromendro Burman^{1

2

3}, Begum Choudhury^{1

2

3}, Luis Aparicio^{1

2

3}, Laurene S Cheung^{1

2

3}, Mara Lanis^{1

3}, Zineb Belcaid^{1

3}, Margueritta El Asmar^{1

3}, Peter B Illei³, Rulin Wang³, Jennifer Meyers³, Kornel Schuebel³, Anuj Gupta³, Alyza Skaist³, Sarah Wheelan³, Jarushka Naidoo^{1

3

10}, Kristen A Marrone^{1

3}, Malcolm Brock³, Jinny Ha³, Errol L Bush³, Bernard J Park¹¹, Matthew Bott¹¹, David R Jones¹¹, Joshua E Reuss^{3

12}, Victor E Velculescu^{1

3}, Jamie E Chaft¹¹, Kenneth W Kinzler^{3

6

7}, Shibin Zhou^{3

6

7}, Bert Vogelstein^{3

6

7}, Janis M Taube^{1

2

3}, Matthew D Hellmann¹¹, Julie R Brahmer^{1

3}, Taha Merghoub^{11

13

14}, Patrick M Forde^{1

3}, Srinivasan Yegnasubramanian^{15

16

17}, Hongkai Ji¹⁸, Drew M Pardoll^{19

20

21}, Kellie N Smith^{22

23

24}

Affiliations

¹ Bloomberg~Kimmel Institute for Cancer Immunotherapy at Johns Hopkins, Baltimore, MD, USA.
² The Mark Center for Advanced Genomics and Imaging at Johns Hopkins, Baltimore, MD, USA.
³ Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD, USA.
⁴ Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
⁵ Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC, USA.
⁶ Ludwig Center and Howard Hughes Medical Institute at Johns Hopkins, Baltimore, MD, USA.
⁷ Lustgarten Pancreatic Cancer Research Laboratory, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA.
⁸ Immunitrack, Copenhagen, Denmark.
⁹ Ontario Institute for Cancer Research, Queens University, Kingston, Ontario, Canada.
¹⁰ Beaumont Hospital Dublin, RCSI University of Medicine and Health Science, Dublin, Ireland.
¹¹ Department of Medicine, Memorial Sloan Kettering Cancer Center and Weill Cornell Medicine, New York, NY, USA.
¹² Georgetown Lombardi Comprehensive Cancer Center at Georgetown University, Washington, DC, USA.
¹³ The Swim Across America and Ludwig Collaborative Laboratory, Immunology Program, Parker Institute for Cancer Immunotherapy at Memorial Sloan Kettering Cancer Center, New York, NY, USA.
¹⁴ Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
¹⁵ Bloomberg~Kimmel Institute for Cancer Immunotherapy at Johns Hopkins, Baltimore, MD, USA. syegnasu@jhmi.edu.
¹⁶ The Mark Center for Advanced Genomics and Imaging at Johns Hopkins, Baltimore, MD, USA. syegnasu@jhmi.edu.
¹⁷ Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD, USA. syegnasu@jhmi.edu.
¹⁸ Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA. hji@jhu.edu.
¹⁹ Bloomberg~Kimmel Institute for Cancer Immunotherapy at Johns Hopkins, Baltimore, MD, USA. dpardol1@jhmi.edu.
²⁰ The Mark Center for Advanced Genomics and Imaging at Johns Hopkins, Baltimore, MD, USA. dpardol1@jhmi.edu.
²¹ Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD, USA. dpardol1@jhmi.edu.
²² Bloomberg~Kimmel Institute for Cancer Immunotherapy at Johns Hopkins, Baltimore, MD, USA. kellie@jhmi.edu.
²³ The Mark Center for Advanced Genomics and Imaging at Johns Hopkins, Baltimore, MD, USA. kellie@jhmi.edu.
²⁴ Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD, USA. kellie@jhmi.edu.

^# Contributed equally.

PMID: 34290408
PMCID: PMC8338555
DOI: 10.1038/s41586-021-03752-4

Transcriptional programs of neoantigen-specific TIL in anti-PD-1-treated lung cancers

Justina X Caushi et al. Nature. 2021 Aug.

. 2021 Aug;596(7870):126-132.

doi: 10.1038/s41586-021-03752-4. Epub 2021 Jul 21.

Authors

Affiliations

¹ Bloomberg~Kimmel Institute for Cancer Immunotherapy at Johns Hopkins, Baltimore, MD, USA.
² The Mark Center for Advanced Genomics and Imaging at Johns Hopkins, Baltimore, MD, USA.
³ Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD, USA.
⁴ Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
⁵ Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC, USA.
⁶ Ludwig Center and Howard Hughes Medical Institute at Johns Hopkins, Baltimore, MD, USA.
⁷ Lustgarten Pancreatic Cancer Research Laboratory, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA.
⁸ Immunitrack, Copenhagen, Denmark.
⁹ Ontario Institute for Cancer Research, Queens University, Kingston, Ontario, Canada.
¹⁰ Beaumont Hospital Dublin, RCSI University of Medicine and Health Science, Dublin, Ireland.
¹¹ Department of Medicine, Memorial Sloan Kettering Cancer Center and Weill Cornell Medicine, New York, NY, USA.
¹² Georgetown Lombardi Comprehensive Cancer Center at Georgetown University, Washington, DC, USA.
¹³ The Swim Across America and Ludwig Collaborative Laboratory, Immunology Program, Parker Institute for Cancer Immunotherapy at Memorial Sloan Kettering Cancer Center, New York, NY, USA.
¹⁴ Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
¹⁵ Bloomberg~Kimmel Institute for Cancer Immunotherapy at Johns Hopkins, Baltimore, MD, USA. syegnasu@jhmi.edu.
¹⁶ The Mark Center for Advanced Genomics and Imaging at Johns Hopkins, Baltimore, MD, USA. syegnasu@jhmi.edu.
¹⁷ Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD, USA. syegnasu@jhmi.edu.
¹⁸ Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA. hji@jhu.edu.
¹⁹ Bloomberg~Kimmel Institute for Cancer Immunotherapy at Johns Hopkins, Baltimore, MD, USA. dpardol1@jhmi.edu.
²⁰ The Mark Center for Advanced Genomics and Imaging at Johns Hopkins, Baltimore, MD, USA. dpardol1@jhmi.edu.
²¹ Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD, USA. dpardol1@jhmi.edu.
²² Bloomberg~Kimmel Institute for Cancer Immunotherapy at Johns Hopkins, Baltimore, MD, USA. kellie@jhmi.edu.
²³ The Mark Center for Advanced Genomics and Imaging at Johns Hopkins, Baltimore, MD, USA. kellie@jhmi.edu.
²⁴ Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD, USA. kellie@jhmi.edu.

^# Contributed equally.

PMID: 34290408
PMCID: PMC8338555
DOI: 10.1038/s41586-021-03752-4

Erratum in

Author Correction: Transcriptional programs of neoantigen-specific TIL in anti-PD-1-treated lung cancers.
Caushi JX, Zhang J, Ji Z, Vaghasia A, Zhang B, Hsiue EH, Mog BJ, Hou W, Justesen S, Blosser R, Tam A, Anagnostou V, Cottrell TR, Guo H, Chan HY, Singh D, Thapa S, Dykema AG, Burman P, Choudhury B, Aparicio L, Cheung LS, Lanis M, Belcaid Z, El Asmar M, Illei PB, Wang R, Meyers J, Schuebel K, Gupta A, Skaist A, Wheelan S, Naidoo J, Marrone KA, Brock M, Ha J, Bush EL, Park BJ, Bott M, Jones DR, Reuss JE, Velculescu VE, Chaft JE, Kinzler KW, Zhou S, Vogelstein B, Taube JM, Hellmann MD, Brahmer JR, Merghoub T, Forde PM, Yegnasubramanian S, Ji H, Pardoll DM, Smith KN. Caushi JX, et al. Nature. 2021 Oct;598(7881):E1. doi: 10.1038/s41586-021-03893-6. Nature. 2021. PMID: 34608287 Free PMC article. No abstract available.

Abstract

PD-1 blockade unleashes CD8 T cells¹, including those specific for mutation-associated neoantigens (MANA), but factors in the tumour microenvironment can inhibit these T cell responses. Single-cell transcriptomics have revealed global T cell dysfunction programs in tumour-infiltrating lymphocytes (TIL). However, the majority of TIL do not recognize tumour antigens², and little is known about transcriptional programs of MANA-specific TIL. Here, we identify MANA-specific T cell clones using the MANA functional expansion of specific T cells assay³ in neoadjuvant anti-PD-1-treated non-small cell lung cancers (NSCLC). We use their T cell receptors as a 'barcode' to track and analyse their transcriptional programs in the tumour microenvironment using coupled single-cell RNA sequencing and T cell receptor sequencing. We find both MANA- and virus-specific clones in TIL, regardless of response, and MANA-, influenza- and Epstein-Barr virus-specific TIL each have unique transcriptional programs. Despite exposure to cognate antigen, MANA-specific TIL express an incompletely activated cytolytic program. MANA-specific CD8 T cells have hallmark transcriptional programs of tissue-resident memory (TRM) cells, but low levels of interleukin-7 receptor (IL-7R) and are functionally less responsive to interleukin-7 (IL-7) compared with influenza-specific TRM cells. Compared with those from responding tumours, MANA-specific clones from non-responding tumours express T cell receptors with markedly lower ligand-dependent signalling, are largely confined to HOBIT^high TRM subsets, and coordinately upregulate checkpoints, killer inhibitory receptors and inhibitors of T cell activation. These findings provide important insights for overcoming resistance to PD-1 blockade.

PubMed Disclaimer

Conflict of interest statement

V.A. receives research funding from Bristol-Myers Squibb and Astra Zeneca. J.M.T. receives research funding from Bristol-Myers Squibb and serves a consulting/advisory role for Bristol-Myers Squibb, Merck, and Astra Zeneca. P.B.I. receives research funding from Bristol-Myers Squibb and Erbe Elektromedizin GmbH and serves a consulting/advisory role for AstraZeneca and Veran Medical Technologies. J.N. receives research funding from AstraZeneca, Bristol-Myers Squibb, and Merck, and serves a consulting/advisory role for AstraZeneca, Daiichi Sankyo, Bristol-Myers Squibb, Merck, and Roche/Genentech. K.A.M. is a consultant for Amgen and Astra Zeneca. D.R.J. is a consultant for More Health and AstraZeneca and a Steering Committee Member for Merck. B.J.P. is a consultant for AstraZeneca and Regeneron and has received honoraria from Intuitive Surgical. J.E.C. is a consultant for AstraZeneca, Genentech, Merck, Flame Bioscience, and Novartis. V.E.V. is a founder of Delfi Diagnostics and Personal Genome Diagnostics, serves on the Board of Directors and as a consultant for both organizations, and owns Delfi Diagnostics and Personal Genome Diagnostics stock, which are subject to certain restrictions under university policy. Additionally, Johns Hopkins University owns equity in Delfi Diagnostics and Personal Genome Diagnostics. V.E.V. is an advisor to Bristol-Myers Squibb, Genentech, Merck, and Takeda Pharmaceuticals. Within the last five years, V.E.V. has been an advisor to Daiichi Sankyo, Janssen Diagnostics, and Ignyta. M.D.H. receives research support from Bristol-Myers Squibb; has been a compensated consultant for Merck, Bristol-Myers Squibb, AstraZeneca, Genentech/Roche, Nektar, Syndax, Mirati, Shattuck Labs, Immunai, Blueprint Medicines, Achilles, Arcus, and Natera; received travel support/honoraria from AstraZeneca, Eli Lilly, and Bristol-Myers Squibb; has options from Shattuck Labs, Immunai, and Arcus; and has a patent filed by his institution related to the use of tumor mutation burden to predict response to immunotherapy (PCT/US2015/062208), which has received licensing fees from PGDx. The Johns Hopkins University is in the process of filing patent applications related to technologies described in this paper on which E.H.-C.H., B.V., K.W.K. and S.Z. are listed as inventors. B.V. and K.W.K. are founders of Thrive Earlier Detection. K.W.K. is a consultant to and was on the Board of Directors of Thrive Earlier Detection. B.V., K.W.K. and S.Z. own equity in Exact Sciences. B.V., K.W.K. and S.Z. are founders of, hold or may hold equity in, and serve or may serve as consultants to manaT Bio, and hold or may hold equity in manaT Holdings, LLC. B.V., K.W.K., and S.Z. are founders of, hold equity in, and serve as consultants to Personal Genome Diagnostics. S.Z. has a research agreement with BioMed Valley Discoveries. K.W.K. and B.V. are consultants to Sysmex, Eisai, and CAGE Pharma and hold equity in CAGE Pharma. B.V. is a consultant to and holds equity in Catalio. K.W.K., B.V. and S.Z. are consultants to and hold equity in NeoPhore. The companies named above, as well as other companies, have licensed previously described technologies related to the work from this lab at Johns Hopkins University. Licenses to these technologies are or will be associated with equity or royalty payments to the inventors as well as to Johns Hopkins University. T.M. is a cofounder and holds equity in IMVAQ Therapeutics, is a consultant for Immunos Therapeutics, ImmunoGenesis, and Pfizer, receives research funding from Bristol-Myers Squibb, Surface Oncology, Kyn Therapeutics, Infinity Pharmaceuticals, Inc., Peregrine Pharmaceuticals, Inc., Adaptive Biotechnologies, Leap Therapeutics, Inc., and Aprea, and holds patents on applications related to work on oncolytic viral therapy, alpha virus-based vaccines, neoantigen modeling, CD40, GITR, OX40, PD-1, and CTLA-4. J.R.B. serves an advisory/consulting role for Amgen, AstraZeneca, Bristol-Myers Squibb, Genentech/Roche, Eli Lilly, GlaxoSmithKline, Merck, Sanofi, and Regeneron, receives research funding from AstraZeneca, Bristol-Myers Squibb, Genentech/Roche, Merck, RAPT Therapeutics, Inc., and Revolution Medicines, and is on the Data and Safety Monitoring Board of GlaxoSmithKline, Janssen, and Sanofi. P.M.F. receives research support from AstraZeneca, Bristol-Myers Squibb, Novartis, and Kyowa, and has been a consultant for AstraZeneca, Amgen, Bristol-Myers Squibb, Daichii Sankyo, and Janssen and serves on a data safety and monitoring board for Polaris. S.Y. receives research funding from Bristol-Myers Squibb/Celgene, Janssen, and Cepheid, has served as a consultant for Cepheid, and owns founder’s equity in Astra Therapeutics and Digital Harmonic. K.N.S., D.M.P., B.V. and K.W.K. have filed for patent protection on the MANAFEST technology described herein (serial no. 16/341,862). K.N.S., D.M.P., J.E.C., B.V., E.H.-C.H. D.M.P., K.W.K. and S.Z. have filed for patent protection on the p53 R248L mutation-specific TCR described herein (serial no. 63/168,878). D.M.P. is a consultant for Compugen, Shattuck Labs, WindMIL, Tempest, Immunai, Bristol-Myers Squibb, Amgen, Janssen, Astellas, Rockspring Capital, Immunomic, Dracen and owns founder’s equity in manaT Holdings, LLC, WindMIL, Trex, Jounce, Anara, Tizona, Tieza, RAPT and receives research funding from Compugen, Bristol-Myers Squibb, and Anara. K.N.S. has received travel support/honoraria from Illumina, Inc., receives research funding from Bristol-Myers Squibb, Anara, and Astra Zeneca, and owns founder’s equity in manaT Holdings, LLC. The terms of all these arrangements are being managed by the respective institutions in accordance with their conflict-of-interest policies.

Figures

**Fig. 1. Profiling single T cells in NSCLC treated with neoadjuvant PD-1 blockade.**
Twenty patients with resectable NSCLC were treated with two doses of PD-1 blockade before surgical resection. a, An overall schematic of the clinical trial, biospecimen collection (top) and study design (bottom). scRNA-seq–TCR-seq was performed on T cells isolated from resected tumour (n = 15), adjacent normal lung (NL; n = 12), TDLN (n = 3), and a resected brain metastasis (n = 1) from patients with NSCLC treated with two doses of neoadjuvant anti-PD-1 (bottom). The MANAFEST and ViraFEST assays were used to identify MANA- and viral (EBV and influenza)-specific TCRs, respectively. WES, whole-exome sequencing. b, UMAP projection of the expression profiles of the 560,916 T cells that passed quality control. Immune cell subsets, defined by 15 unique clusters, are annotated and marked by colour code. c, Relative expression of the top-3 most differentially expressed genes. Five-thousand cells (or all cells in the cluster if the cluster size was fewer than 5,000 cells) were randomly sampled from each cluster for visualization. MAIT, mucosal-associated invariant T cells; T_FH, T follicular helper cells; T_reg, regulatory T cells. d, Expression of T cell subset-defining genes, T cell subset-selective genes and major T cell checkpoint genes. *CD39* is also known as *ENTPD1*. e, PCA of cell-cluster-level pseudobulk gene expression for individual samples for tumour (yellow, n = 15) and adjacent normal lung (dark blue, n = 12). One-sided permutation test. f, PCA of cell-cluster-level pseudobulk gene expression for non-MPR (red, n = 9) and MPR (light blue, n = 6) tumours. One-sided permutation test.

**Fig. 2. Characterization of antigen-specific T cells in NSCLC treated with neoadjuvant PD-1 blockade.**
The MANAFEST assay was performed on four patients with MPR and five patients without MPR. Results are shown in Extended Data Fig. 2 and Supplementary Data 5. a, Four TCRs recognizing p53(R248L)-derived MD01-004-MANA12 were identified in patient without MPR MD01-004. Their frequency was tracked in serial peripheral blood. Mut, mutant. b, Refined clustering was performed on 235,851 CD8⁺ T cells from tumour (n = 15), adjacent normal lung (n = 12), TDLN (n = 3) and one resected brain metastasis (MD043-011). Fourteen unique clusters were visualized and were using T cell gene programs described in previous studies. Cluster-defining genes are shown in Extended Data Fig. 5a. c, MANA-specific (red), influenza-specific (blue) and EBV-specific (purple) clonotypes were visualized on the CD8 UMAP. d, Antigen-specific gene programs in the TIL were visualized as a heat map. Comparisons were performed at the individual cell level using a two-sided Wilcoxon rank-sum test with P-value adjustment using Bonferroni correction. e, Expression levels of key markers are shown. *TBET* is also known as *TBX21*; *4-1BB* is also known as *TNFRSF9*. f, Transcriptional programs of influenza-specific and MANA-specific TIL were compared. The top-15 significantly upregulated genes in influenza -specific T cells (blue) and in MANA-specific T cells (yellow) are shown. g, TIL from MD01-004 were cultured with MD01-004-MANA-12 or influenza peptide and titrating concentrations of IL-7, followed by scRNA-seq–TCR-seq. In total, 814 influenza-specific TIL (410 co-cultured with influenza peptide and 404 co-cultured with MANA peptide) and 581 MANA-specific TIL (366 co-cultured with influenza peptide and 215 co-cultured with MANA peptide) were detected from a single experiment and were analysed. Composite expression of an IL-7 gene set by influenza-specific and MANA-specific TIL (as determined by their TCRVβ CDR3) was analysed. Dose–response curve of the IL-7-upregulated gene set-score is shown (mean ± s.e.m.). h, TCRs corresponding to seven MANA-specific clonotypes from two patients without MPR (red lines), three MANA-specific clonotypes from a patient with MPR (yellow lines), two influenza-specific TCRs, and one EBV-specific TCR (orange lines) were tested for ligand-dependent TCR-signalling capacity. Ctrl, control; RLU, relative luminescence units.

**Fig. 3. Differential gene expression programs of MANA-specific CD8 T cells in MPR versus non-MPR tumours.**
Seven unique MANA-specific clonotypes, representing 45 total transcriptomes, were identified in MPR TIL: 39 from MD01-005, 2 from MD043-003 and 4 from NY016-025. In non-MPR TIL, 16 unique clonotypes, representing 885 total transcriptomes, were identified: 782 from MD043-011, 62 from MD01-004 and 22 from NY016-014 (Supplementary Table 8). Differential gene expression analysis was performed on the MANA-specific T cells detected in MPR (n = 3) and non-MPR (n = 3) tumours. a, The top differential genes and selective immune markers of tumour-infiltrating MANA-specific T cells from MPR and non-MPR tumours. Comparisons were performed at the individual cell level using two-sided Wilcoxon rank sum test. P-value adjustment was performed using Bonferroni correction. Side bar shows the adjusted P value (green scale) and response status (red, TIL from MPR; light blue, TIL from non-MPR). b, Histograms show the expression of key genes among MANA-specific T cells from MPR (light blue) and non-MPR (red) tumours. c, A violin plot shows IL-7R expression by each MANA-specific CD8 T cell in MPR (red) and non-MPR (light blue) tumours. Comparisons were performed at the individual cell level using two-sided Wilcoxon rank-sum test. d, A T cell immune checkpoint score was calculated for each MANA-specific CD8 T cell detected in MPR (red) and non-MPR (light blue) tumours. This checkpoint score was compared between MPR and non-MPR using two-sided Wilcoxon rank-sum test. e, The relative correlation coefficient (MPR MANA-specific TIL versus non-MPR MANA-specific TIL) with the immune checkpoint score is shown for genes more highly correlated in non-MPR (yellow) and MPR (blue) TIL.

**Fig. 4. Neoadjuvant PD-1 blockade promotes systemic transcriptional reprogramming in MANA-specific T cells from a patient with complete pathologic response.**
a, Longitudinal peripheral blood mononuclear cells were collected from complete pathologic responder MD01-005 (0% residual tumour) during treatment and in post-surgery follow up. Peripheral blood CD8⁺ T cells were sorted using FACS on the basis of expression of TCRVβ2, which corresponds to the MANA-specific CDR3 CASNKLGYQPQHF, as identified by the MANAFEST assay (Extended Data Fig. 2a). scRNA-seq–TCR-seq was performed on the sorted population from each time point. b, UMAP projection of expression profiles of 4,409 peripheral blood CD8⁺TCRVβ2⁺ T cells. c, Heat map of the top-5 differential genes, ranked by average fold change, for each T cell cluster. d, UMAP projection of MANA-specific T cells, identified via the CASNKLGYQPQHF or CASSLLENQPQHF TCRVβ CDR3, is shown for each time point. Clusters were coloured using the same colour scheme as in b. MANA-specific T cells are highlighted as triangles. e, The proportions of cells in each T cell cluster among all MANA-specific cells identified at week 2 and week 4 were compared (two-sided Fisher’s exact test and a two-sided test accounting for background cell proportion, both smaller than 0.021; Methods). f, Diffusion plot with RNA velocity for clusters in which MANA-specific T cells were detected. Cells were randomly downsampled to 100 cells (or all cells in the cluster if cluster size was smaller than 100 cells) for each cluster for visualization. g, Heat map of the top differential genes along the pseudotime trajectory from T_mem(3) to T_eff(3). h, Pseudotemporal expression of genes that significantly change along the pseudotime from T_mem(3) to T_eff(3). Red curves represent the mean temporal function estimates of the three samples from this individual (Methods). Cells with gene expression levels above the top one percentile were removed as outliers.

**Extended Data Fig. 1. Defining CD3⁺ T cell subsets in patients with non-small cell cancer treated with anti-PD-1.**
a, FACS gating strategy for sorting CD3+ T cells. The gating strategy is shown for sorting live CD3⁺ T cells from tumour, normal lung, lymph node, or metastasis, when available, on a BD FACSAria. b, Patient and tissue compartment variability across clusters on UMAP. scRNA-seq–TCR-seq was performed on available resected biospecimens (tumour, adjacent NL, TDLN, and a brain metastasis) from 16 patients treated with neoadjuvant PD-1 blockade. CD3⁺ T cells stratified by patient are visualized using UMAP. Each cluster is annotated and marked by colour code. c, Barplots show the proportion of each T cell cluster in the TDLN, brain metastasis, tumour, and adjacent NL of each patient. Each cluster as shown on the UMAP is denoted by colour code. No clusters were driven by a particular patient based. d, A density plot of all CD3⁺ T cells on the UMAP, stratified by tissue compartment, is shown. Cells were obtained from 15 tumours, 12 adjacent NL specimens, and 3 TDLN. Because a metastasis was sequenced in only one patient, this specimen is not included in this analysis. e, The proportion (%) of total CD3⁺ T cells made up by each T cell cluster was compared between tumour (n = 15 biologically independent samples), adjacent NL (n = 12 biologically independent samples), and TDLN (n = 3 biologically independent samples). P values were obtained using Kruskal–Wallis Test and were adjusted for multiple comparisons using Benjamini-Hochberg method. Each dot represents a patient and all data points are shown. Individual data points are superimposed over a Box and Whiskers plot summarizing the data. The middle bar shows the median, with the lower and upper hinges corresponding to the 25^th and 75^th percentiles, respectively (interquartile range, IQR). The upper whisker extends from the hinge to the largest value no further than 1.5 * IQR from the hinge. The lower whisker extends from the hinge to the smallest value at most 1.5 * IQR of the hinge. f, Tissue-resident defining genes and core TRM gene set signature on different T cell cluster. The top and middle violin plots show the expression of TRM-defining genes (ITGAE, ZNF683) by each cell in each cluster. The dashed line indicates the mean expression of the respective gene among all CD3⁺ T cells. Expression values were log₁₀ transformed for visualization. The bottom violin plot shows the TRM gene-set score for each cluster. This gene-set is comprised of TRM-associated genes as published previously (Supplementary Data 2.1). The dashed line shows the mean TRM gene-set score among all T cells. Because the proliferating cluster is driven by proliferation-associated genes and is comprised of mixed cell types, this cluster was not shown in the violin plots.

**Extended Data Fig. 2. MANA-specific TCRs detected in patient without MPR MD01-004 using MANAFEST and ViraFEST assays.**
Antigen-specific responses identified using the MANAFEST assay are shown for patient without MPR MD01-004. MANAFEST assays for all other patients are shown in Supplementary Data 5. Each antigen-specific clonotypic expansion is colour coded to indicate if the clone was not detected in the single-cell data (blue), detected in the single-cell data but not tested via TCR cloning (green), or detected in the single-cell data and validated with TCR cloning (red). Data are shown as the percent of MANAFEST+ clonotypes among CD8+ T cells after 10 day culture.

**Extended Data Fig. 3. Peripheral dynamics and cross-compartment representation of antigen-specific T cells.**
Bulk TCRseq was performed on pre- and post-treatment tissue (left panels) and peripheral blood (right panels) for each patient in whom antigen-specific TCRs were identified by ViraFEST/MANAFEST (as shown in Extended Data Fig. 2 and Supplementary Data 5). Data are shown as the frequency of each influenza-, CEF-, and MANA-specific TCR clonotype among all TCRs detected by bulk TCR sequencing of the indicated tissue or peripheral blood time point. Antigen-specific clonotypes were not detected by bulk TCRseq of any available tissue/peripheral blood time point in patient NY016-025. TDLN, tumour draining lymph node; DLN, draining lymph node.

**Extended Data Fig. 4. TCR cloning validation of MANA-specific TCRs and MANA binding kinetics.**
Ten TCRs identified via the MANAFEST assay were selected for TCR cloning and transfer into our NFAT/luciferase Jurkat reporter system. Seven of these TCRs recognized the cognate MANA. a, In MD01-005, three TCR Vβ clonotypes recognizing the ARVCF H497L-derived EVIVPLSGW MANA were identified by MANAFEST. Single-cell analysis determined that the Vβ CDR3 s CASNKLGYQPQHF and CASSLLENQPQHF were consistently detected in the same cell and paired with the same Vα CDR3, CALSMGGNEKLTF, likely the result of incomplete allelic exclusive at the beta locus. To validated that these TCRs recognized MD01-005-MANA7, and to determine which Vβ CDR3 was responsible for recognition in the case of incomplete allelic exclusion, all three TCRs were cloned into the Jurkat NFAT luciferase reporter system and tested against autologous LCL loaded with titrating concentrations of MD01-005-MANA7. Data are shown as relative luminescence units (RLU) for MD01-005-MANA7 (solid red square), the cognate wild-type peptide (open red square), or MD01-005-MANA8, which was predicted to bind A*25:01, for each individual TCR. b, In patient without MPR MD01-004, four TCRs recognizing the p53 R248L-derived NSSCMGGMNLR MANA (MD01-004-MANA12) were identified by MANAFEST and were detected in the single-cell data. Each Vβ chain paired exclusively with a single Vα chain. These four TCRs were cloned into the Jurkat NFAT/luciferase reporter system and tested against autologous LCL loaded with titrating concentrations of MD01-004-MANA12. Data are shown as relatively luminescence units (RLU) in response to MD01-004-MANA12 (solid blue square) or the cognate wild-type peptide (open blue square). c, In patient without MPR MD043-011, a TCR recognizing the CARM1 R208W-derived FAAQAGAWKIY MANA (MD043-011-MANA36) was a candidate for positivity by MANAFEST and was detected in the single-cell data. This Vβ chain paired exclusively with a single Vα chain. This TCR was cloned into the Jurkat NFAT/luciferase reporter system and tested against autologous LCL loaded with titrating concentrations of MD043-011-MANA36. Data are shown as relatively luminescence units (RLU) in response to MD01-004-MANA12 (solid green square) or the cognate wild-type peptide (open green square). d, The affinity of MD01-005-MANA7 for HLA A*25:01 was assessed using a luminescent oxygen channeling immunoassay (LOCI, left). This is a proximity-based system using a “donor” and “acceptor” bead, each conjugated with an epitope tag. When the donor bead is excited with light at 650nm and can activate an acceptor bead, resulting in a signal at 520-620nm, which can be quantified per second as a surrogate of affinity. A higher number of counts per second indicates higher affinity of the peptide:HLA pair. Data are shown as the number of counts per second for titrating concentrations of MD01-005-MANA7 (solid blue square), the cognate wild-type (open blue square), MD01-005-MANA8, which is predicted to bind HLA A*68:01 (black circle), or no peptide (star). Stability of these same peptides in the HLA A*68:01 complex was also evaluated using a urea-based assay, whereby the stability of the peptide:HLA complex is measured at increasing concentrations of urea (right). Data are shown as the absorbance at 450nm. Data points represent the mean +/− s.d. of two independent experiments. e, Binding (top left) and stability (top right) assays were conducted as in (b) for the p53 R248L-derived MD01-004-MANA12 (solid green square), the cognate wild-type peptide (open green square), a positive control peptide for HLA A*68:01 (orange diamond), the YTAVPLVYV peptide which is predicted to bind A*68:01 (black circle), or no peptide (black star). Data points represent the mean +/− s.d. of two independent experiments. To determine if MD01-004-MANA12 is endogenously processed and presented by HLA A*68:01, COS-7 cells were transfected with HLA-A*68:01 plasmid and p53 R248L mutant plasmid or p53 wild type plasmid. HLA- and p53-transfected COS-7 cells, autologous APC loaded with MD01-004-MANA12, and HLA-A*68:01-transfected COS-7 were co-cultured with CD8+ Jurkat reporter cells expressing the MD01-004-MANA12-reactive TCR, Vβ: CATTGGQNTEAFF, V𝛼: CILSGANNLFF. Data are shown as relative luminescence units (RLU) for each condition (bottom).

**Extended Data Fig. 5. Refined clustering on CD8 T cells.**
a, A heat map shows the top differential genes, ranked by average fold change, for each refined CD8 T cell cluster. 5,000 cells (or all cells in the cluster if cluster size <5000 cells) were randomly sampled from each cluster for visualization (n = 16 patients). b, Violin plots show the log10 expression of the TRM-defining genes, ITGAE (top) and ZNF683 (HOBIT, middle), and a TRM gene-set score (bottom) for each CD8 T cell cluster. The dashed line indicates the mean expression of the respective gene or gene-set score among all CD8 T cells. Because the proliferating cluster is driven by proliferation-associated genes and represents mixed cell types, this cluster was not shown in the plot. c, 2D UMAP red-scale projection of canonical T cell subset marker genes, cell subset selective genes, and immune checkpoints on CD8 T cell subsets. d, A heat map shows the proportion of each refined CD8 T cell cluster (Fig. 2b) that is found within each global UMAP T cell cluster (Fig. 1b). This enables visualization of the “parent” cluster for the refined CD8 T cell clusters. e, A violin plot shows the exhaustion gene-set score, comprised of a published exhaustion gene list (Supplementary Data 2.2), for each refined CD8 T cell cluster. The dashed line shows the mean exhaustion gene-set score among all CD8 T cells. Because the proliferating cluster is driven by proliferation-associated genes and represents mixed cell types, this cluster was not shown in the plot. f, CD8⁺ T cell clonotypic cluster composition. The top 50 CD8⁺ TCR clonotypes in the tumour are shown for each patient, and the proportion of each clonotype that was found within each cluster is designated by the colour code.

**Extended Data Fig. 6. Distinct phenotype of antigen-specific T cells.**
a, Distribution of MANA-specific T cells on UMAP. Individual MANA-specific clonotypes are shown on the UMAP, stratified by tissue compartment and patient ID. Each colour represents a unique MANA-specific clonotype, and each symbol represents a patient. b, Distribution of EBV-specific T cells on UMAP. Individual EBV-specific clonotypes are shown on the UMAP, stratified by tissue compartment. Each colour represents a unique EBV-specific clonotype and each symbol represents a patient. c, Distribution of influenza-specific T cells on UMAP. Individual influenza-specific clonotypes are shown on the UMAP, stratified by tissue compartment and patient ID. Each colour represents a unique influenza-specific clonotype, and each symbol represents a patient. The CD8 T cell clusters are annotated according to the designation in Fig. 2b. d, The barplot (upper) shows the proportion of antigen-specific T cells among total CD8 T cells by tissue compartment (blue bar, adjacent NL; yellow bar, tumour). The dotplot (bottom) shows the proportion of antigen-specific T cells stratified by subset, with the size of the dot representing the proportion among total CD8 T cells (blue dot, adjacent NL; yellow dot, tumour). e, TIL and adjacent NL CD8 T cells were downsampled to equal numbers of cells on UMAP before visualization of antigen-specific clonotypes in tumour (left) and adjacent normal lung (right). f, The immune checkpoint score and exhaustion score of antigen-specific T cells. A violin plot shows a composite immune checkpoint score (left) and exhaustion score (right) for EBV(purple)-, influenza (blue)-, and MANA (red)-specific T cells.

**Extended Data Fig. 7. IL-7-induced gene signature between MANA-specific and influenza-specific TIL.**
TIL from patient MD01-004 were cultured with MD01-004-MANA-12 or influenza A peptide and titrating concentrations of recombinant human IL-7, followed by coupled scRNA-seq–TCR-seq. A total of 814 influenza-specific (410 co-cultured with influenza peptide, 404 co-cultured with MANA peptide) and 581 MANA-specific TIL (366 co-cultured with influenza peptide, 215 co-cultured with MANA peptide) were detected in the single-cell data from a single experiment and were analysed. a, Composite expression of an IL-7 gene set by influenza-specific and MANA-specific TIL (as determined by their TCR Vβ CDR3) stimulated with cognate or non-cognate antigen is shown. b, Dose–response curve showing the fold change of averaged expression of IL-7-induced genes (Supplementary Data 2.3) that significantly changed from baseline (no IL-7 vs 0.1 ng/ml) in influenza-specific (red) or MANA-specific (blue) T cells. Comparisons were performed using two-sided Wilcoxon rank sum test and adjusted for multiple comparisons using BH method.

**Extended Data Fig. 8. Cloning and dose response of antigen-specific T cells.**
a–c, Cloning and screening of TCRs corresponding to CD8 T cells with highly differential gene expression relative to influenza-specific T cells. Seven TCRs were selected from the refined CD8 sc data based on highly differential gene expression relative to influenza-specific T cells. These TCRs were cloned into the Jurkat/NFAT luciferase reporter system and first screened against autologous LCL pre-loaded with pools of putative MANA peptides (10μg/ml) based on the respective patient’s WES and MANA predictions. Three TCRs recognized a MANA peptide pool, one each from patients MD01-005 (a), MD01-004 (b), and MD043-011 (c). The reactive MANA was then mapped from the reactive peptide pool by stimulating the TCR-transfected Jurkat cell with autologous LCL pre-loaded with 10μg/ml of each individual MANA within the reactive pool (centre). Dose–response curves were then generated for each MANA-specific TCR (right). Data are shown as relative luminescence units. A (+) sign indicates the positive response. d, Functional characterization of MANAFEST-identified and screening-identified TCRs. 2D projection of clones identified from the MANAFEST assay (red) and clones identified via cloning of TCRs corresponding to T cells with differential gene expression relative to influenza-specific T cells (green) is shown for patients MD01-004, MD01-005, and MD043-011. CD8 T cell clusters are marked with the same colour code as Fig. 2b. e, Viral-specific TCRs and MANA-specific TCRs from one patient with MPR and two patients without MPR were cloned into the Jurkat reporter system and tested against titrating concentrations of relevant peptide. The average log₁₀ relative luminescence of viral-specific TCRs (blue, 3 clonotypes from 3 different patients), MANA-specific MPR TCRs (green, 3 clonotypes from 1 patient with MPR), and MANA-specific non-MPR TCRs (red, 7 clonotypes from 2 patients without MPR) was compared at each peptide titration. Data are shown as a Box and Whiskers plot. The middle bar shows the median, with the lower and upper hinges corresponding to the 25^th and 75^th percentiles, respectively (interquartile range, IQR). The upper whisker extends from the hinge to the largest value no further than 1.5 * IQR from the hinge. The lower whisker extends from the hinge to the smallest value at most 1.5 * IQR of the hinge. Comparisons of relative luminescence units for viral-specific vs MANA-specific T cell clonotypes at different titrations were performed using two-sided Wilcoxon rank sum test. ns: P > 0.05; *, 0.01 < P < 0.05.

**Extended Data Fig. 9. Patient representation of antigen-specific clonotypes.**
a, b, Barplots summarize the total number of unique tumour-infiltrating clonotypes (a) and cells (b), stratified by antigen specificity and method of detection (MANAFEST or based on the TRM gene signature and cloning/peptide screen). Different colours represent the patient identity. c, Visualization of clonotypes included in the MANA-specific analysis. The individual UMAP projections of clonotypes that were validated (left) and were not validated (right) by TCR cloning are shown. Of the cells that corresponded to a MANAFEST-identified, MANA-specific clonotype that was detected in the single-cell data, >94% were validated by the jurkat/luciferase TCR cloning system.

**Extended Data Fig. 10. Signatures of MANA-specific T cells according to response and tissue compartment.**
a, Exhaustion score and co-expression of immune checkpoints/effector/memory function gene on MANA-specific TIL. Violin plot shows the exhaustion gene-set score (Supplementary Data 2.2) of MANA-specific TIL of non-MPR (red, n = 3) and MPR (light blue, n = 3) tumours. Comparisons were performed at the individual cell level using two-sided Wilcoxon rank sum test without multiple comparison adjustment. b, Heat map shows co-expression of immune checkpoints and effector/memory genes on MANA-specific TIL. Each column represent a cell. The exhaustion score, response status, and patient IDs are designated by the relevant colour bar. For visualization, MANA-specific T cells were downsampled to the same number of cells from MPR (n = 3) and non-MPR (n = 3). c, Top ranked genes correlated with the immune checkpoint score in MANA-specific TIL. Barplots show the correlation coefficients of the top ranked genes highly correlated with the immune checkpoint score in MPR (left) and non-MPR (right) MANA-specific TIL. d, MANA-specific T cells found in the tumour (red triangles) and TDLN (blue triangles) of patients MD01-004, MD01-005, and MD043-011 were projected on the refined CD8 UMAP. e, Expression of selective genes is shown for MANA-specific T cells in the tumour and TDLN (n = 3). f, MANA-specific T cells found in the tumour (red triangle) and brain metastasis (purple triangle) are shown on the UMAP for patient MD043-011. g, The scatterplot shows the average expression of genes comparing all refined CD8 T cells from the primary tumour and metastatic brain resection in patient MD043-011. The top differential genes enriched in the brain metastasis are labelled in red. Comparisons were performed at the individual cell level using two-sided Wilcoxon rank sum test. P-value adjustment was performed using bonferroni correction. A complete list of differential genes comparing primary tumour at resection vs. the distant brain metastasis is shown in Supplementary Data 1.5. CD8 T cell clusters are marked by the same colour code as Fig. 2b.

**Extended Data Fig. 11. Canonical correlations of CD8 T cell clusters with pathologic response.**
The canonical correlation between pathologic response status and CD8 T cell clusters vs. a MANA-specific T cell-enriched cluster was evaluated. a, Selection of MANA-specific T cell enriched clusters (Proliferating, TRM(IV), TRM (V) and TRM (II)) based on >2 fold change (red dotted line) of MANA-specific T cell frequency relative to random expectation. The above 4 clusters were combined as a ‘MANA-combined’ cluster. b, Combined MANA-specific T cell enriched clusters showed the highest canonical correlation with pathologic response. c, PCA of pseudobulk gene expression from all CD8 T cell clusters for individual tumour samples (n = 15, 6 MPRs and 9 non-MPRs), coloured by response status (MPR as blue blue dots, non-MPR as red dots). d, PCA of pseudobulk gene expression from combined MANA enriched T cell cluster for individual tumour samples (n = 15, 6 MPRs and 9 non-MPRs), coloured by response status (MPR as light blue dots, non-MPR as red dots). P values were obtained using a one-sided permutation test, without correction for multiple comparisons.

**Extended Data Fig. 12. Phenotypic characteristics of FACS-sorted peripheral blood CD8+/Vβ2+ T cells from MPR MD01-005.**
a, Selective gene expression of 2D UMAP red-scale projection is shown of canonical T cell subset marker genes, cell subset selective genes, and immune checkpoints on CD8 T cell subsets sorted from longitudinal peripheral blood of one patient (MD01-005) with complete pathologic response. **b-d**, Pseudotime reconstruction and pseudo-temporal dynamic gene identification in peripheral blood CD8 T cells from a complete pathologic responder. Longitudinal PBMC were collected from complete pathologic responder MD01-005 (0% residual tumour) during treatment and in post-surgery follow up. Peripheral blood CD8⁺ T cells were FACS sorted based on expression of TCR Vβ2, which corresponds to the MANA-specific CDR3 CASNKLGYQPQHF as identified previously via the MANAFEST assay (Extended Data Fig. 2a). scRNA-seq–TCR-seq was performed on the sorted population from each time point. b, Constructing the pseudotime axis on the diffusion map from T_mem(3) to T_eff(3) as trajectory 1. c, GO analysis for genes that significantly change along trajectory 1, ranked by FDR. d, Constructing the pseudotime axis on the diffusion map from T_mem(3) to T_mem(2) as trajectory 2. e, GO analysis for genes that significantly change along trajectory 2, ranked by FDR. f, Heat map showing genes that significantly change along trajectory 2 (FDR < 0.05).

See this image and copyright information in PMC

Comment in

Tumour antigen-induced T cell exhaustion - the archenemy of immune-hot malignancies.
Lopez de Rodas M, Schalper KA. Lopez de Rodas M, et al. Nat Rev Clin Oncol. 2021 Dec;18(12):749-750. doi: 10.1038/s41571-021-00562-5. Nat Rev Clin Oncol. 2021. PMID: 34556846 Free PMC article.

References

1. Tumeh PC, et al. PD-1 blockade induces responses by inhibiting adaptive immune resistance. Nature. 2014;515:568–571. - PMC - PubMed
1. Simoni Y, et al. Bystander CD8+ T cells are abundant and phenotypically distinct in human tumour infiltrates. Nature. 2018;557:575–579. - PubMed
1. Danilova L, et al. The mutation-associated neoantigen functional expansion of specific T Cells (MANAFEST) assay: a sensitive platform for monitoring antitumor immunity. Cancer Immunol. Res. 2018;6:888–899. - PMC - PubMed
1. Vogelstein B, et al. Cancer genome landscapes. Science. 2013;339:1546–1558. - PMC - PubMed
1. Yarchoan M, Hopkins A, Jaffee EM. Tumor mutational burden and response rate to PD-1 inhibition. N. Engl. J. Med. 2017;377:2500–2501. - PMC - PubMed

Publication types

Actions
Actions

MeSH terms

Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions

Substances

Actions
Actions
Actions
Actions
Actions

Grants and funding

LinkOut - more resources

Full Text Sources
Other Literature Sources
- The Lens - Patent Citations Database
Medical
- MedlinePlus Health Information
Molecular Biology Databases
- NIAID Data Ecosystem - Find datasets on Infectious and Immune-mediated Diseases
Research Materials
- NCI CPTC Antibody Characterization Program

Save citation to file

Email citation

Add to Collections

Add to My Bibliography

Your saved search

Create a file for external citation management software

Your RSS Feed

Transcriptional programs of neoantigen-specific TIL in anti-PD-1-treated lung cancers

Affiliations

Transcriptional programs of neoantigen-specific TIL in anti-PD-1-treated lung cancers

Authors

Affiliations

Erratum in

Abstract

Conflict of interest statement

Figures

Comment in

References

Publication types

MeSH terms

Substances

Grants and funding

LinkOut - more resources

Full Text Sources

Other Literature Sources

Medical

Molecular Biology Databases

Research Materials