Distinct Immune Cell Populations Define Response to Anti-PD-1 Monotherapy and Anti-PD-1/Anti-CTLA-4 Combined Therapy

Gide, Tuba N.; Quek, Camelia; Menzies, Alexander M.; Tasker, Annie; Shang, Peng; Holst, Jeff; Madore, Jason; Lim, Su Yin; Velickovic, Rebecca; Wongchenko, Matthew J.; Yan, Yibing; Lo, Serigne; Carlino, Matteo S.; Guminski, Alexander; Saw, Robyn P.M.; Pang, Angel; McGuire, Helen M.; Palendira, Umaimainthan; Thompson, John F.; Rizos, Helen; Silva, Inês Pires da; Batten, Marcel; Scolyer, Richard A.; Long, Georgina V.; Wilmott, James S.

doi:10.1016/j.ccell.2019.01.003

Cited by 586 publications

(643 citation statements)

References 84 publications

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“…Multiple studies have established that PD-1 blockade increases T cell infiltrations in tumors leading to improved anti-tumor control (Curran et al, 2010;Wei et al, 2017;Gubin et al, 2018;Gide et al, 2019). Moreover, recent studies have shown that ICB promotes expansion of tumor-specific memory-like cells and their differentiation into (terminally) exhausted cells (Miller et al, 2019;Siddiqui et al, 2019).…”

Section: Discussionmentioning

confidence: 99%

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Deciphering the transcriptomic landscape of tumor-infiltrating CD8 lymphocytes in B16 melanoma tumors with single-cell RNA-Seq

Carmona

Siddiqui

Bilous

et al. 2019

Preprint

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Recent studies have proposed that tumor-specific tumor-infiltrating CD8 + T lymphocytes (CD8 TIL) can be classified into two main groups: "exhausted" TILs, characterized by high expression of the inhibitory receptors PD-1 and TIM-3 and lack of transcription factor 1 (Tcf1); and "memory-like" TILs, with self-renewal capacity and co-expressing Tcf1 and PD-1. However, a comprehensive definition of the heterogeneity existing within both tumor-specific and total CD8 TILs has yet to be clearly established.To investigate this heterogeneity at the transcriptomic level, we performed paired single-cell RNA and TCR sequencing of CD8 T cells infiltrating B16 murine melanoma tumors, including cells of known tumor specificity. Unsupervised clustering and gene signature analysis revealed four distinct CD8 TIL states -exhausted, memory-like, naïve and effector memory-like (EM-like) -and predicted novel markers, including Ly6C for the EM-like cells, that were validated by flow cytometry. Tumor-specific PMEL T cells were predominantly found within the exhausted and memory-like states but also within the EM-like state. Further, TCR repertoire sequencing revealed a large clonal expansion of exhausted, memory-like and EM-like cells with partial clonal relatedness between them. Finally, meta-analyses of public bulk and single-cell RNAseq data suggested that anti-PD-1 treatment induces expansion of EM-like cells.Our reference map of the transcriptomic landscape of murine CD8 TILs will help interpreting future bulk and single-cell transcriptomic studies and may guide the analysis of CD8 TIL subpopulations in response to therapeutic interventions.2

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Section: Discussionmentioning

confidence: 99%

“…Multiple studies have established that PD-1 blockade expands intratumoral T cells and improves tumor control (Curran et al, 2010;Wei et al, 2017;Gubin et al, 2018;Gide et al, 2019). However, it is less clear how different CD8 T cell states are affected by immune-checkpoint blockade (ICB).…”

Section: Pd-1 Checkpoint Blockade Expands Em-like Cellsmentioning

confidence: 99%

Deciphering the transcriptomic landscape of tumor-infiltrating CD8 lymphocytes in B16 melanoma tumors with single-cell RNA-Seq

Carmona

Siddiqui

Bilous

et al. 2019

Preprint

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“…Kaplan-Meier curves showing different overall survival and progression-free survival in melanoma patients after commencing treatment with ICB. Patients from (10) were stratified in three groups according to pre-treatment expression of FDCSP . C-D .…”

Section: Bulk Rnaseq: Discovery Cohortsmentioning

confidence: 99%

“…The methods described in this section were used to quantify gene expression in all datasets used in this study as discovery cohorts and for the first validation cohort, for which original FASTQ files were available. For the second and third validation cohort (10), we used the gene expression values provided in the original publications (11, 12).…”

Section: Bulk Rnaseq: Discovery Cohortsmentioning

confidence: 99%

“…The RNAseq datasets used in this study as validation cohorts were downloaded from the following published sources. First validation cohort : data for 91 melanoma samples collected before or during ICB treatment was downloaded from the European Nucleotide Archive (ENA; 9), study PRJEB23709 (10). Second validation cohort : data for 16 melanoma samples collected before ICB treatment was obtained from (11).…”

Section: Bulk Rnaseq: Discovery Cohortsmentioning

confidence: 99%

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Fibroblastic reticular cells predict response to immune checkpoint inhibitors

Biasci

Tavaré

Thaventhiran

2020

Preprint

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While the role of CD8+ T cells in mediating response to cancer 1 immunotherapy is well established, the role of other cell types, 2 including B cells, remains more controversial. By conducting 3 the largest gene expression study of response to immune check-4 point blockade (ICB) to date, here we show that pre-treatment 5 expression of B cell genes is associated with ICB response inde-6 pendently of CD8+ T cells. Strikingly, we discovered that such 7 association is completely explained by a single gene expressed 8 in fibroblastic reticular cells (FRCs). We further validated this 9 finding in three independent cohorts of patients treated with 10 ICB, in both melanoma and renal cell carcinoma. 11The role of B cells in cancer immunotherapy is currently a 12 matter of debate (1-3). Recently, it has been reported that 13 expression of B cell specific genes inside tumours is asso-14 ciated with response to immune checkpoint blockade (ICB), 15 thus suggesting an unappreciated biological role for B cells in 16 promoting ICB response (4). However, association between 17 B cell gene expression and ICB response was not statisti-18 cally significant when other immune populations, including 19 CD8+ T cells, were taken into account (4). For this rea-20 son, it remains unclear whether B cells are associated with 21 ICB response independently of CD8+ T cells. Clarifying this 22 point is crucial for the biological interpretation of these re-23 sults. In fact, expression of B cell specific genes in the tu-24 mour microenvironment (TME) is often strongly correlated 25 with markers of CD8+ T cells (5), which express the ac-26 tual molecular targets of ICB treatment and are a validated 27 predictor of immunotherapy response (6-8). Two additional 28 recent studies on this topic did not address the issue, be-29 cause they described predictive signatures containing both B 30 cell and CD8+ T cell markers, as well as genes expressed 31 in other immune cell types (9, 10). In order to address this 32 problem, we analysed the entire transcriptome of a larger 33 number of melanoma samples compared to previous studies 34 (n = 366), and we then considered only samples collected 35 before commencing treatment with immune checkpoint in-36 82 nificant after FDCSP expression was included in the model 83 (Fig. 1D). Taken together, these results suggest that expres-84 sion of FDCSP might be an independent predictor of ICB 85 response. We tested this hypothesis in a completely inde-86 pendent cohort of melanoma patients treated with anti-PD1, 87 either alone or in combination with anti-CTLA4 (23). In this 88 validation cohort, patients with higher expression of FDCSP 89 at baseline experienced significantly longer overall survival 90 Biasci et al. | | 1-S22 (log-rank p < 0.0001) and progression-free survival (log-91 rank p < 0.0001) after commencing treatment with ICB (Fig-92 ures 1B and 1C). Moreover, we observed a significant asso-93 ciation between expression of FDCSP at baseline and subse-94 quent RECIST response (Cochran-Armitage test p < 0.0001; ...

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Analysis of DNA methylation patterns in the tumor immune microenvironment of metastatic melanoma

et al. 2020

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The presence of immune cells in the tumor microenvironment has been associated with response to immunotherapies across several cancer types, including melanoma. Despite its therapeutic relevance, characterization of the melanoma immune microenvironments remains insufficiently explored. To distinguish the immune microenvironment in a cohort of 180 metastatic melanoma clinical specimens, we developed a method using promoter CpG methylation of immune cell type-specific genes extracted from genome-wide methylation arrays. Unsupervised clustering identified three immune methylation clusters with varying levels of immune CpG methylation that are related to patient survival. Matching protein and gene expression data further corroborated the identified epigenetic characterization. Exploration of the possible immune exclusion mechanisms at play revealed likely dependency on MITF protein level and PTEN loss-of-function events for melanomas unresponsive to immunotherapies (immune-low). To understand whether melanoma tumors resemble other solid tumors in terms of immune methylation characteristics, we explored 15 different solid tumor cohorts from TCGA. Low-dimensional projection based on immune cell type-specific methylation revealed grouping of the solid tumors in line with melanoma immune methylation clusters rather than tumor types. Association of survival outcome with immune cell typespecific methylation differed across tumor and cell types. However, in melanomas immune cell type-specific methylation was associated with inferior patient survival. Exploration of the immune methylation patterns in a pan-cancer context suggested that specific immune microenvironments might occur across the cancer spectrum. Together, our findings underscore the existence of diverse immune microenvironments, which may be informative for future immunotherapeutic applications.

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Distinct Immune Cell Populations Define Response to Anti-PD-1 Monotherapy and Anti-PD-1/Anti-CTLA-4 Combined Therapy

Cited by 586 publications

References 84 publications

Deciphering the transcriptomic landscape of tumor-infiltrating CD8 lymphocytes in B16 melanoma tumors with single-cell RNA-Seq

Deciphering the transcriptomic landscape of tumor-infiltrating CD8 lymphocytes in B16 melanoma tumors with single-cell RNA-Seq

Fibroblastic reticular cells predict response to immune checkpoint inhibitors

Analysis of DNA methylation patterns in the tumor immune microenvironment of metastatic melanoma

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