Evidence map›Paper›PMID 38463784›Full record

ArticleHeliyon2024

Single-cell RNA sequencing reveals distinct transcriptomic profiles and evolutionary patterns in lung cancer brain metastasis.

Xiaoyuan Wang, Hao Liang, Xiaoli Tang, Xiaodong Ling, Yingnan Yang

Abstract read
In one paragraph

Article in Heliyon, 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. Article
  3. Single-cell transcriptomic analyses provide insights into SPP1Cancer immunology, immunotherapy : CII · 2025
    Article
  4. Review
  5. Review
  6. Review
  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

5 authors.

Xiaoyuan WangDepartment of Thoracic Surgery, Harbin Medical University Cancer Hospital, Harbin, China.
Hao LiangDepartment of Thoracic Surgery, Harbin Medical University Cancer Hospital, Harbin, China.
Xiaoli TangDepartment of Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Xiaodong LingDepartment of Thoracic Surgery, Harbin Medical University Cancer Hospital, Harbin, China.
Yingnan YangDepartment of Thoracic Surgery, Harbin Medical University Cancer Hospital, Harbin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Lung cancer metastasis to the brain presents significant clinical challenges. Therefore, elucidating its underlying mechanisms and characterizing its transcriptomic landscape is essential for developing therapeutic interventions. Methods: We analyzed two distinct single-cell RNA sequencing datasets of lung cancer metastasis to analyze the evolutionary trajectory of brain metastatic tumors. In addition, a systematic comparison of cell-cell interaction between tumor cells and lymphocytes was conducted within primary and brain metastatic tumors. Results: The brain metastatic tumors showed greater transcriptomic changes (reflected by a higher pseudotime) than tumors in the lymph nodes and primary tumors. Furthermore, our investigation has not only revealed specific shared ligand-receptor pairs in both mLN and mBrain, exemplified by the interaction between SPP1 and CD99 in T cells, but has also unveiled a diverse array of ligand-receptor pairs exclusive to the mBrain. Notably, this includes distinctive pairs such as APP and IL1 observed specifically in myeloid cells. Conclusion: The distinct microenvironment in the brain may influence the observed transcriptomic changes in tumors, emphasizing the significance of the specific environment in determining tumor behavior and therapeutic response.

Indexed as

Lung cancer brain metastasisSingle-cell RNA sequencingTherapeutic responseTumor microenvironment

Identifiers

PMID38463784
PMCPMC10920378

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.