Evidence map›Paper›PMID 39026661›Full record

ReviewFrontiers in immunology2024

Advancing immunotherapy for melanoma: the critical role of single-cell analysis in identifying predictive biomarkers.

Ru He, Jiaan Lu, Jianglong Feng, Ziqing Lu, Kaixin Shen, Ke Xu, Huiyan Luo, Guanhu Yang, Hao Chi, Shangke Huang

Abstract readReview
In one paragraph

Review 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 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Review
  8. CD39Frontiers in oncology · 2025
    Review
  9. Article
  10. Therapeutic Significance of NLRP3 Inflammasome in Cancer: Friend or Foe?International journal of molecular sciences · 2024
    Review
  11. Article
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

10 authors.

Ru He *Clinical Medical College, Southwest Medical University, Luzhou, China.
Jiaan Lu *Clinical Medical College, Southwest Medical University, Luzhou, China.
Jianglong Feng *Department of Pathology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China.
Ziqing LuClinical Medical College, Southwest Medical University, Luzhou, China.
Kaixin ShenDepartment of Art and Design, Shanghai Institute of Technology, Shanghai, China.
Ke XuDepartment of Oncology, Chongqing General Hospital, Chongqing University, Chongqing, China.
Huiyan LuoDepartment of Oncology, Chongqing General Hospital, Chongqing University, Chongqing, China.
Guanhu YangDepartment of Specialty Medicine, Ohio University, Athens, OH, United States.
Hao ChiClinical Medical College, Southwest Medical University, Luzhou, China.
Shangke HuangDepartment of Oncology, The Affiliated Hospital, Southwest Medical University, Luzhou, Sichuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Melanoma, a malignant skin cancer arising from melanocytes, exhibits rapid metastasis and a high mortality rate, especially in advanced stages. Current treatment modalities, including surgery, radiation, and immunotherapy, offer limited success, with immunotherapy using immune checkpoint inhibitors (ICIs) being the most promising. However, the high mortality rate underscores the urgent need for robust, non-invasive biomarkers to predict patient response to adjuvant therapies. The immune microenvironment of melanoma comprises various immune cells, which influence tumor growth and immune response. Melanoma cells employ multiple mechanisms for immune escape, including defects in immune recognition and epithelial-mesenchymal transition (EMT), which collectively impact treatment efficacy. Single-cell analysis technologies, such as single-cell RNA sequencing (scRNA-seq), have revolutionized the understanding of tumor heterogeneity and immune microenvironment dynamics. These technologies facilitate the identification of rare cell populations, co-expression patterns, and regulatory networks, offering deep insights into tumor progression, immune response, and therapy resistance. In the realm of biomarker discovery for melanoma, single-cell analysis has demonstrated significant potential. It aids in uncovering cellular composition, gene profiles, and novel markers, thus advancing diagnosis, treatment, and prognosis. Additionally, tumor-associated antibodies and specific genetic and cellular markers identified through single-cell analysis hold promise as predictive biomarkers. Despite these advancements, challenges such as RNA-protein expression discrepancies and tumor heterogeneity persist, necessitating further research. Nonetheless, single-cell analysis remains a powerful tool in elucidating the mechanisms underlying therapy response and resistance, ultimately contributing to the development of personalized melanoma therapies and improved patient outcomes.

Indexed as

Biomarkers, TumorImmunotherapyMelanomaSingle-Cell AnalysisTumor MicroenvironmentAnimalsHumansImmune Checkpoint InhibitorsPrognosisSkin NeoplasmsBiomarkers, TumorImmune Checkpoint InhibitorsICIimmunotherapymelanomapredictive biomarkerssingle-cell analysisTME

Identifiers

PMID39026661
PMCPMC11254669

What OpenQuestion holds

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Registered trials

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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.