Peripheral T cell expansion predicts tumour infiltration and clinical response

Wu, Thomas D.; Madireddi, Shravan; Almeida, Patrícia E. de; Banchereau, Romain; Chen, Ying-Jiun J.; Chitre, Avantika S.; Chiang, Eugene Y.; Iftikhar, Hina; O’Gorman, William; Au-Yeung, Amelia; Takahashi, Chikara; Goldstein, Leonard D.; Poon, Chungkee; Keerthivasan, Shilpa; Nagata, Denise E. de Almeida; Du, Xiangnan; Lee, Hyang-Mi; Banta, Karl L.; Mariathasan, Sanjeev; Thakur, Meghna Das; Huseni, Mahrukh; Ballinger, Marcus; Estay, Ivette; Caplazi, Patrick; Modrušan, Zora; Delamarre, Lélia; Mellman, Ira; Bourgon, Richard; Grogan, Jane L.

doi:10.1038/s41586-020-2056-8

Cited by 520 publications

(534 citation statements)

References 55 publications

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“…We prespecified four categories of prior PD-1 blockade to characterize the temporal relationship between treatment exposure and diagnosis of COVID-19: ever received PD-1 blockade, most recent dose within 6 months, most recent dose within 6 weeks, and first dose within 3 months. These definitions were selected to examine how recent and more remote exposure to PD-1 blockade might influence COVID-19 severity, cognizant of both the prolonged receptor occupancy that can persist for months (28) as well as the distinct proliferative burst in response to initially starting this therapy (18)(19)(20)(21).…”

Section: Resultsmentioning

confidence: 99%

“…As another measurement of robustness, we examined different bio-plausible (19)(20)(21)28) definitions to define the proximity of prior PD-1 blockade exposure. This included those who received PD-1 blockade at any time previously, those in whom the most recent dose of PD-1 blockade was within 6 months of COVID-19 diagnosis, those in whom the most recent dose of PD-1 blockade was within 6 weeks of COVID-19 diagnosis, or who had initiated PD-1 blockade within 3 months of COVID-19 diagnosis.…”

Section: Discussionmentioning

confidence: 99%

“…Lastly, given the dissipating pharmacodynamic impact of PD-1 blockade following the initial proliferative burst associated with early doses (18)(19)(20)(21), it is possible that any interaction of PD-1 blockadefor better or worseon severity of COVID-19 would be limited to those who recently began therapy. Some (10,(22)(23)(24), but not all (11,(25)(26)(27), initial reports of COVID-19 described signals of increased severity associated with immune checkpoint inhibitors (ICIs).…”

Section: Introductionmentioning

confidence: 99%

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Impact of PD-1 Blockade on Severity of COVID-19 in Patients with Lung Cancers

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Impact of PD-1 Blockade on Severity of COVID-19 in Patients with Lung Cancers

et al. 2020

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“…However, observations of enhanced T cell infiltration and function in tumors after αPD-1 therapy do not formally prove the importance of intratumoral TIL reinvigoration in ICI therapy. Consistent with this idea, recent scRNA-seq studies in cancer patients have shown that the majority of tumor-specific TILs that expanded in response to PD-1 blockade was not initially detected in the tumor but rather had a peripheral origin and can be detected in the blood 33,34 . Although PD-1/PD-L1 engagement at the TIL-tumor interface still remains a critical barrier to overcome for the elicitation of protective CD8 + T cell responses, these studies raised the possibility that tumor-specific CD8 + T cells can respond peripherally, presumably through the help of PD-L1-expressing cells, and can be readily recruited into the tumor during αPD-1 treatment.…”

Section: Discussionmentioning

confidence: 73%

PD-1 blockade-driven anti-tumor CD8⁺T cell immunity requires XCR1⁺dendritic cells

Mao

Song

Iwasaki

2020

Preprint

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9CD8 + T cells are required for effective anti-PD-1 (αPD-1) cancer immunotherapy. Type 1 10 conventional dendritic cells (cDC1s) bearing XCR1 critically mediate the initiation of 11 protective anti-tumor CD8 + T cell responses in mice and humans. However, whether 12 cDC1s contribute to evoking the effector function of CD8 + T cells during αPD-1 antibody 13 therapy remains unclear. Here, by deleting cDC1s at the effector phase of αPD-1 therapy, 14we identify these cells as a crucial innate determinant for effective αPD-1 immunotherapy. 15 αPD-1 treatment unleashed cDC1s to promote anti-tumor CD8 + T cell immunity, through 16 the expansion of TCF1 + precursors and generation of TIM3 + terminally differentiated 17 effectors. Furthermore, tumor cDC1 abundance was predictive of enhanced CD8 + T cell 18 infiltration, higher survival, and improved clinical responses to αPD-1 therapy in human 19 cancer patients. Together, this study reveals the requirement for cDC1s in PD-1 blockade 20 therapy, through their ability to elicit CD8 + T cell effector responses that mediate tumor 21 control, and highlight cDC1s as an attractive cellular target to be harnessed for novel 22 immunotherapeutics. 23 3 effector axis mediates protective anti-tumor immune responses during αPD-1 46 immunotherapy. 47The initiation of anti-tumor CD8 + T cell responses requires BATF3-dependent 48 cDC1s, which are a subset of antigen presenting cells (APCs) that specializes in the 49 acquisition, processing, and presentation of tumor antigens 20 . Tumor-infiltrating cDC1s 50 traffic tumor antigens to the tumor draining lymph node (TDLN) in a CCR7-dependent 51 manner where they efficiently cross-prime tumor-specific naive CD8 + T cells 21,22,23 . In 52 addition to mediating the induction of endogenous anti-tumor immune responses, recent 53 studies have implicated an important role for cDC1s in the efficacy of checkpoint blockade 54 therapy 24,25,26,27 . In particular, it was shown that tumor-bearing mice that were 55 developmentally deficient in BATF3-dependent DCs failed to respond to αPD-1 or αPD-56 L1. The lack of an immune response to αPD-1, however, could be due to defective priming 57 of tumor-specific T cells by DCs during early stages of tumor development, and does not 58 reflect the requirement of cDC1s during immunotherapy. Therefore, the role of cDC1s 59 independent of early TDLN priming and their impact on activated, antigen-experienced 60 CD8 + T cells during αPD-1 therapy remain unclear. Here we probe the role of cDC1s 61 during the effector stage of αPD-1 cancer immunotherapy. 62 63Results 64 XCR1 + cDC1s are required for effective anti-PD-1 immunotherapy against 65 established murine melanoma 66We first examined the presence of tumor-infiltrating cDC1s using a melanoma 67 model B16.F10 expressing the lymphocytic choriomeningitis virus glycoprotein epitope 68 4 GP33-41 (B16.GP33). cDC1s were identified by their surface expression of I-A/I-E, 69CD11c, XCR1, and CD24, representing a distinct APC compartment in the tumor 70 ( Supplementary F...

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“…To demonstrate the applicability to a real-world scenario, we re-analyzed a recent single-cell dataset of ~140k T cells (Wu et al , 2020) . Single T cells were isolated from tumours, normal adjacent tissue, and peripheral blood of 14 patients with four different cancer types, and subjected to single-cell RNA and TCR sequencing with the 10x technology.…”

Section: Case Study: Re-analysis Of 140k Single T Cellsmentioning

confidence: 99%

Scirpy: A Scanpy extension for analyzing single-cell T-cell receptor sequencing data

Sturm

Szabó

Fotakis

et al. 2020

Preprint

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Advances in single-cell technologies have enabled the investigation of T cell phenotypes and repertoires at unprecedented resolution and scale. Bioinformatic methods for the efficient analysis of these large-scale datasets are instrumental for advancing our understanding of adaptive immune responses in cancer, but also in infectious diseases like COVID-19. However, while well-established solutions are accessible for the processing of single-cell transcriptomes, no streamlined pipelines are available for the comprehensive characterization of T cell receptors. Here we propose Scirpy , a scalable Python toolkit that provides simplified access to the analysis and visualization of immune repertoires from single cells and seamless integration with transcriptomic data. Availability and implementationScirpy source code and documentation are available at https://github.com/icbi-lab/scirpy .

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Peripheral T cell expansion predicts tumour infiltration and clinical response

Cited by 520 publications

References 55 publications

Impact of PD-1 Blockade on Severity of COVID-19 in Patients with Lung Cancers

Impact of PD-1 Blockade on Severity of COVID-19 in Patients with Lung Cancers

PD-1 blockade-driven anti-tumor CD8⁺T cell immunity requires XCR1⁺dendritic cells

Scirpy: A Scanpy extension for analyzing single-cell T-cell receptor sequencing data

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Peripheral T cell expansion predicts tumour infiltration and clinical response

Cited by 520 publications

References 55 publications

Impact of PD-1 Blockade on Severity of COVID-19 in Patients with Lung Cancers

Impact of PD-1 Blockade on Severity of COVID-19 in Patients with Lung Cancers

PD-1 blockade-driven anti-tumor CD8+T cell immunity requires XCR1+dendritic cells

Scirpy: A Scanpy extension for analyzing single-cell T-cell receptor sequencing data

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PD-1 blockade-driven anti-tumor CD8⁺T cell immunity requires XCR1⁺dendritic cells