Evidence map›Paper›PMID 39726591›Full record

ArticleFrontiers in immunology2024

TLS and immune cell profiling: immunomodulatory effects of immunochemotherapy on tumor microenvironment in resectable stage III NSCLC.

Chaopin Yang, Jinqi You, Yizhi Wang, Si Chen, Yan Tang, Hao Chen, Haoran Zhong, Ruyue Song, Hao Long, Tong Xiang and 2 more

Abstract read
In one paragraph

Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
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

7 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. Review
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.

Chaopin Yang *State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China.
Jinqi You *State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China.
Yizhi Wang *State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China.
Si ChenState Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China.
Yan TangState Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China.
Hao ChenState Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China.
Haoran ZhongState Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China.
Ruyue SongState Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China.
Hao LongState Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China.
Tong XiangState Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China.
Ze-Rui ZhaoState Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China.
Jianchuan XiaState Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The use of programmed death-1 (PD-1) inhibitors in the neoadjuvant setting for patients with resectable stage III NSCLC has revolutionized this field in recent years. However, there is still 40%-60% of patients do not benefit from this approach. The complex interactions between immune cell subtypes and tertiary lymphoid structures (TLSs) within the tumor microenvironment (TME) may influence prognosis and the response to immunochemotherapy. This study aims to assess the relationship between immune cells subtypes and TLSs to better understand their impact on immunotherapy response. Methods: This study initially compared the tertiary lymphoid structures (TLSs) density among patients who underwent immunochemotherapy, chemotherapy and upfront surgery using 123 tumor samples from stage-matched patients. Multiplex immunohistochemistry (mIHC) was employed to analyze the spatial distribution of PD-L1+CD11c+ cells and PD1+CD8+ T cells within TLSs. Cytometry by time-of-flight (CyTOF) was used to assess immune cell dynamics in paired biopsy and resection specimens from six patients who underwent immunochemotherapy. Key immune cells were validated in newly collected samples using flow cytometry, mIHC, and Results: Patients who underwent neoadjuvant chemotherapy or immunochemotherapy exhibited increased TLSs compared to those who opted for upfront surgery. The TLS area-to-tumor area ratio distinguished pCR+MPR and NR patients in the immunochemotherapy group. Spatial analysis revealed variations in the distance between PD-L1+CD11c+ cells and PD1+CD8+ T cells within TLSs in the immunochemotherapy group. CyTOF analysis revealed an increase in the frequency of key immune cells (CCR7+CD127+CD69+CD4+ and CD38+CD8+ cells) following combined therapy. Treatment responders exhibited an increase in CCR7+CD4+ T cells, whereas CD38+CD8+ T cells were associated with compromised treatment effectiveness. Conclusions: Immunochemotherapy and chemotherapy increase TLSs and granzyme B+ CD8+ T cells in tumors. The TLS area-to-tumor ratio distinguishes responders from non-responders, with PD-L1+ dendritic cells near CD8+PD-1+ T cells linked to efficacy, suggesting that PD-1 inhibitors disrupt harmful interactions. Post-immunochemotherapy, CD8+ T cells increase, but CD38+CD8+ T cells show reduced functionality. These findings highlight the complex immune dynamics and their implications for NSCLC treatment.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsTumor MicroenvironmentAgedCD8-Positive T-LymphocytesFemaleHumansImmune Checkpoint InhibitorsImmunotherapyLymphocytes, Tumor-InfiltratingMaleMiddle AgedNeoadjuvant TherapyNeoplasm StagingProgrammed Cell Death 1 ReceptorTertiary Lymphoid StructuresImmune Checkpoint InhibitorsProgrammed Cell Death 1 ReceptorCCR7+CD4+ T cellsCD38+CD8+ T cellsimmunochemotherapyNSCLCtertiary lymphoid structures (TLSs)the axis of PD-L1+CD11c+ cells and PD1+CD8+ T cells

Identifiers

PMID39726591
PMCPMC11670196

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.