Evidence map›Paper›PMID 33868792›Full record

ArticleOncoimmunology2021

Investigating Mechanisms of Response or Resistance to Immune Checkpoint Inhibitors by Analyzing Cell-Cell Communications in Tumors Before and After Programmed Cell Death-1 (PD-1) Targeted Therapy: An Integrative Analysis Using Single-cell RNA and Bulk-RNA Sequencing Data.

Yi-Quan Jiang, Zi-Xian Wang, Ming Zhong, Lu-Jun Shen, Xue Han, Xuxiazi Zou, Xin-Yi Liu, Yi-Nan Deng, Yang Yang, Gui-Hua Chen and 2 more

Open access · goldAbstract read
In one paragraph

Article in Oncoimmunology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
2.9field-weighted citation impact, top 7% 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

32 citing papers in PubMed, 36 citations in OpenAlex.

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  5. Cellular Landscape of Synovial Chondromatosis Synovium Revealed by Single-Cell RNA Sequencing.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 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

12 authors at 1 institution in 1 country.

Yi-Quan JiangDepartment of Minimally Invasive Interventional Therapy, Sun Yat-Sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou China.ORCID 0000-0002-9003-943X
Zi-Xian WangDepartment of Medical Oncology, Sun Yat-Sen University Cancer Center; State Key Laboratory of Oncology in South China; Artificial Intelligence Laboratory of Sun Yat-Sen University Cancer Center; Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
Ming ZhongDepartment of Medical Oncology, Sun Yat-Sen University Cancer Center; State Key Laboratory of Oncology in South China; Artificial Intelligence Laboratory of Sun Yat-Sen University Cancer Center; Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
Lu-Jun ShenDepartment of Minimally Invasive Interventional Therapy, Sun Yat-Sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou China.
Xue HanDepartment of Minimally Invasive Interventional Therapy, Sun Yat-Sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou China.
Xuxiazi ZouDepartment of Breast Surgery, Sun Yat-Sen University Cancer Center; State Key Laboratory of Oncology in South China; Artificial Intelligence Laboratory of Sun Yat-Sen University Cancer Center; Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
Xin-Yi LiuMOE Key Laboratory of Gene Function and Regulation, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, China.
Yi-Nan DengDepartment of Hepatic Surgery and Liver Transplantation Center of the Third Affiliated Hospital, Organ Transplantation Institute, Sun Yat-sen University, Guangzhou, China.
Yang YangDepartment of Hepatic Surgery and Liver Transplantation Center of the Third Affiliated Hospital, Organ Transplantation Institute, Sun Yat-sen University, Guangzhou, China.
Gui-Hua ChenDepartment of Hepatic Surgery and Liver Transplantation Center of the Third Affiliated Hospital, Organ Transplantation Institute, Sun Yat-sen University, Guangzhou, China.
Wuguo DengDepartment of Medical Oncology, Sun Yat-Sen University Cancer Center; State Key Laboratory of Oncology in South China; Artificial Intelligence Laboratory of Sun Yat-Sen University Cancer Center; Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
Jin-Hua HuangDepartment of Minimally Invasive Interventional Therapy, Sun Yat-Sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou China.
Sun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Currently, a significant proportion of cancer patients do not benefit from programmed cell death-1 (PD-1)-targeted therapy. Overcoming drug resistance remains a challenge. In this study, single-cell RNA sequencing and bulk RNA sequencing data from samples collected before and after anti-PD-1 therapy were analyzed. Cell-cell interaction analyses were performed to determine the differences between pretreatment responders and nonresponders and the relative differences in changes from pretreatment to posttreatment status between responders and nonresponders to ultimately investigate the specific mechanisms underlying response and resistance to anti-PD-1 therapy. Bulk-RNA sequencing data were used to validate our results. Furthermore, we analyzed the evolutionary trajectory of ligands/receptors in specific cell types in responders and nonresponders. Based on pretreatment data from responders and nonresponders, we identified several different cell-cell interactions, like WNT5A-PTPRK, EGFR-AREG, AXL-GAS6 and ACKR3-CXCL12. Furthermore, relative differences in the changes from pretreatment to posttreatment status between responders and nonresponders existed in SELE-PSGL-1, CXCR3-CCL19, CCL4-SLC7A1, CXCL12-CXCR3, EGFR-AREG, THBS1-a3b1 complex, TNF-TNFRSF1A, TNF-FAS and TNFSF10-TNFRSF10D interactions. In trajectory analyses of tumor-specific exhausted CD8 T cells using ligand/receptor genes, we identified a cluster of T cells that presented a distinct pattern of ligand/receptor expression. They highly expressed suppressive genes like HAVCR2 and KLRC1, cytotoxic genes like GZMB and FASLG and the tissue-residence-related gene CCL5. These cells had increased expression of survival-related and tissue-residence-related genes, like heat shock protein genes and the interleukin-7 receptor (IL-7R), CACYBP and IFITM3 genes, after anti-PD-1 therapy. These results reveal the mechanisms underlying anti-PD-1 therapy response and offer abundant clues for potential strategies to improve immunotherapy.

Indexed as

NeoplasmsProgrammed Cell Death 1 ReceptorApoptosisCalcium-Binding ProteinsCell CommunicationHumansImmune Checkpoint InhibitorsMembrane ProteinsRNARNA-Binding ProteinsSequence Analysis, RNACACYBP protein, humanCalcium-Binding ProteinsIFITM3 protein, humanImmune Checkpoint InhibitorsMembrane ProteinsProgrammed Cell Death 1 ReceptorRNARNA-Binding Proteinscell-cell interactionimmune checkpoint blockadeimmunotherapyprogrammed cell death-1Single-cell rna sequencing

Identifiers

PMID33868792
PMCPMC8023241
OpenAlexW3144797444

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.