Evidence map›Paper›PMID 33900375›Full record

ArticleThe Journal of experimental medicine2021

STARTRAC analyses of scRNAseq data from tumor models reveal T cell dynamics and therapeutic targets.

Dev Bhatt, Boxi Kang, Deepali Sawant, Liangtao Zheng, Kristy Perez, Zhiyu Huang, Laura Sekirov, Dan Wolak, Julie Y Huang, Xian Liu and 6 more

Open access · greenAbstract read
In one paragraph

Article in The Journal of experimental medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
2.9field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

33 citing papers in PubMed, 46 citations in OpenAlex.

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  13. The immunosuppressive role of CCR8Journal of Cancer · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors at 2 institutions in 2 countries.

Dev Bhatt *Department of Inflammation and Oncology, Amgen Research, Amgen, South San Francisco, CA.
Boxi Kang *Beijing Advanced Innovation Centre for Genomics, Peking-Tsinghua Centre for Life Sciences, Peking University, Beijing, China.
Deepali Sawant *Department of Inflammation and Oncology, Amgen Research, Amgen, South San Francisco, CA.
Liangtao Zheng *Beijing Advanced Innovation Centre for Genomics, Peking-Tsinghua Centre for Life Sciences, Peking University, Beijing, China.
Kristy PerezDepartment of Inflammation and Oncology, Amgen Research, Amgen, South San Francisco, CA.
Zhiyu HuangDepartment of Inflammation and Oncology, Amgen Research, Amgen, South San Francisco, CA.
Laura SekirovDepartment of Inflammation and Oncology, Amgen Research, Amgen, South San Francisco, CA.
Dan WolakDepartment of Inflammation and Oncology, Amgen Research, Amgen, South San Francisco, CA.
Julie Y HuangDepartment of Inflammation and Oncology, Amgen Research, Amgen, South San Francisco, CA.
Xian LiuDepartment of Inflammation and Oncology, Amgen Research, Amgen, South San Francisco, CA.
Jason DeVossDepartment of Inflammation and Oncology, Amgen Research, Amgen, South San Francisco, CA.
Paolo S ManzanilloDepartment of Inflammation and Oncology, Amgen Research, Amgen, South San Francisco, CA.
Nathan PierceDepartment of Inflammation and Oncology, Amgen Research, Amgen, South San Francisco, CA.
Zemin ZhangBeijing Advanced Innovation Centre for Genomics, Peking-Tsinghua Centre for Life Sciences, Peking University, Beijing, China.
Antony SymonsDepartment of Inflammation and Oncology, Amgen Research, Amgen, South San Francisco, CA.
Wenjun OuyangDepartment of Inflammation and Oncology, Amgen Research, Amgen, South San Francisco, CA.
Amgen (United States) · USPeking University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single-cell RNA sequencing is a powerful tool to examine cellular heterogeneity, novel markers and target genes, and therapeutic mechanisms in human cancers and animal models. Here, we analyzed single-cell RNA sequencing data of T cells obtained from multiple mouse tumor models by PCA-based subclustering coupled with TCR tracking using the STARTRAC algorithm. This approach revealed various differentiated T cell subsets and activation states, and a correspondence of T cell subsets between human and mouse tumors. STARTRAC analyses demonstrated peripheral T cell subsets that were developmentally connected with tumor-infiltrating CD8+ cells, CD4+ Th1 cells, and T reg cells. In addition, large amounts of paired TCRα/β sequences enabled us to identify a specific enrichment of paired public TCR clones in tumor. Finally, we identified CCR8 as a tumor-associated T reg cell marker that could preferentially deplete tumor-associated T reg cells. We showed that CCR8-depleting antibody treatment provided therapeutic benefit in CT26 tumors and synergized with anti-PD-1 treatment in MC38 and B16F10 tumor models.

Indexed as

AnimalsCD4-Positive T-LymphocytesCD8-Positive T-LymphocytesCell Line, TumorDisease Models, AnimalFemaleLymphocytes, Tumor-InfiltratingMiceMice, Inbred BALB CMice, Inbred C57BLNeoplasmsProgrammed Cell Death 1 ReceptorTh1 CellsT-Lymphocytes, RegulatoryProgrammed Cell Death 1 Receptor

Identifiers

PMID33900375
PMCPMC8077174
OpenAlexW3158284947

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.