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This study aimed to evaluate the correlation between the proportion of flow-sorted CX3CR1+T cells in peripheral blood and the CX3CR1+T-specific gene signature and the efficacy of immunotherapy.
The status and abundance of T cells vary across tumor microenvironments (TMEs) may fundamentally influence response to immunotherapy in non-small cell lung cancer. CX3CR1+ CD8+ T cells showed high migration in and were enriched in the blood, whose amplification is strongly associated with response to anti-PD-1 therapy and better survival. However, the prediction performance of CX3CR1+ T features and characteristics has not been fully validated. This study intends to conduct a clinical trial based on CX3CR1+ CD8+T Cell in peripheral blood to verify the association of proportion and specific transcriptome signature of CX3CR1+T Cell in immunotherapy efficacy prediction. With the help of RECIST 1.1 criteria, the investigators evaluate the clinical response after prescribed cycles of treatment to explore the correlation between peripheral blood markers and immunotherapy efficacy. To develop a low cost, robust and accurate prototype prediction model for NSCLC patients who take anti-PD-1 drugs is investigators final translational purpose.
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| PD-1 inhibitor based immunotherapy | Drug | Patients received at least 4 cycles of PD-1 inhibitor-based immune monotherapy or chemoimmunotherapy. PD-1 drug selection should be limited in 4 types of PD-1 inhibitor approved by China FDA and launched in China and Opdivo or Keytruda. |
| Measure | Description | Time Frame |
|---|---|---|
| objective response rate(ORR) | Imaging findings of CR, PR, and stable disease (SD) in all subjects evaluated according to RECIST V1.1 after completing 4 cycles of immunotherapy. best overall response (BoR) was evaluated in participants achieving complete and partial response. | 4 weeks |
| Measure | Description | Time Frame |
|---|---|---|
| progression-free survival (PFS) | progression-free survival (PFS) defined as time from surgery until disease progression or death from any cause | 1 year |
| overall survival (OS) | Overall survival (OS) was defined as the time from surgery until death from any cause |
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Inclusion Criteria:
Exclusion Criteria:
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patients with advanced non-small cell lung cancer (stage IIIA-IVB) anticipate to receive primary/first-line immunotherapy
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| Name | Affiliation | Role |
|---|---|---|
| Chang Chen, MD, Ph.D. | Shanghai Pulmonary Hospital, Shanghai, China | Principal Investigator |
| Deping Zhao, MD, Ph.D. | Shanghai Pulmonary Hospital, Shanghai, China | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Hunan cancer hospital | Changsha | Hunan | China | |||
| Shanghai Pulmonary Hospital |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 34914499 | Background | Zheng L, Qin S, Si W, Wang A, Xing B, Gao R, Ren X, Wang L, Wu X, Zhang J, Wu N, Zhang N, Zheng H, Ouyang H, Chen K, Bu Z, Hu X, Ji J, Zhang Z. Pan-cancer single-cell landscape of tumor-infiltrating T cells. Science. 2021 Dec 17;374(6574):abe6474. doi: 10.1126/science.abe6474. Epub 2021 Dec 17. | |
| 33658501 | Background |
| Label | URL |
|---|---|
| Related Info | View source |
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| ID | Term |
|---|---|
| D002289 | Carcinoma, Non-Small-Cell Lung |
| ID | Term |
|---|---|
| D002283 | Carcinoma, Bronchogenic |
| D001984 | Bronchial Neoplasms |
| D008175 | Lung Neoplasms |
| D012142 | Respiratory Tract Neoplasms |
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| 1 year |
| Shanghai |
| Shanghai Municipality |
| China |
| Yamauchi T, Hoki T, Oba T, Jain V, Chen H, Attwood K, Battaglia S, George S, Chatta G, Puzanov I, Morrison C, Odunsi K, Segal BH, Dy GK, Ernstoff MS, Ito F. T-cell CX3CR1 expression as a dynamic blood-based biomarker of response to immune checkpoint inhibitors. Nat Commun. 2021 Mar 3;12(1):1402. doi: 10.1038/s41467-021-21619-0. |
| 41747737 | Derived | Dong Y, Xu X, Si H, Li Y, Yang D, Chen J, Wang Y, Zhang HM, Yang L, Xie H, Yang M, Shi B, Zhao D, Hu X, Wen J, Xu L, Wu J, Chen C. A machine learning model integrating circulating Temra cell transcriptional profiles to predict immunotherapy efficacy. Med. 2026 Apr 10;7(4):101027. doi: 10.1016/j.medj.2026.101027. Epub 2026 Feb 25. |
| Related Info | View source |
| D013899 |
| Thoracic Neoplasms |
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
| D008171 | Lung Diseases |
| D012140 | Respiratory Tract Diseases |