Evidence map›Paper›PMID 40317346›Full record

ArticleJournal of molecular medicine (Berlin, Germany)2025

CD24, NFIL3, FN1, and KLRK1 signature predicts melanoma immunotherapy response and survival.

Bruna Pereira Sorroche, Renan de Jesus Teixeira, Vinicius Gonçalves de Souza, Isabela Cristiane Tosi, Katiane Tostes, Ana Carolina Laus, Iara Viana Vidigal Santana, Vinicius de Lima Vazquez, Lidia Maria Rebolho Batista Arantes

Abstract read
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In one paragraph

Article in Journal of molecular medicine (Berlin, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

9 authors.

Bruna Pereira SorrocheMolecular Oncology Research Center, Barretos Cancer Hospital, Barretos, São Paulo, Brazil.ORCID http://orcid.org/0000-0001-9802-8236
Renan de Jesus TeixeiraMolecular Oncology Research Center, Barretos Cancer Hospital, Barretos, São Paulo, Brazil.ORCID http://orcid.org/0000-0001-9782-9306
Vinicius Gonçalves de SouzaMolecular Oncology Research Center, Barretos Cancer Hospital, Barretos, São Paulo, Brazil.ORCID http://orcid.org/0000-0002-1656-6928
Isabela Cristiane TosiMolecular Oncology Research Center, Barretos Cancer Hospital, Barretos, São Paulo, Brazil.ORCID http://orcid.org/0000-0003-0718-1396
Katiane TostesMolecular Oncology Research Center, Barretos Cancer Hospital, Barretos, São Paulo, Brazil.ORCID http://orcid.org/0000-0002-8312-9269
Ana Carolina LausMolecular Oncology Research Center, Barretos Cancer Hospital, Barretos, São Paulo, Brazil.ORCID http://orcid.org/0000-0003-4748-8819
Iara Viana Vidigal SantanaDepartment of Pathology, Barretos Cancer Hospital, Barretos, São Paulo, Brazil.
Vinicius de Lima VazquezMolecular Oncology Research Center, Barretos Cancer Hospital, Barretos, São Paulo, Brazil.ORCID http://orcid.org/0000-0002-0325-5514
Lidia Maria Rebolho Batista ArantesMolecular Oncology Research Center, Barretos Cancer Hospital, Barretos, São Paulo, Brazil. lirebolho@hotmail.com.ORCID http://orcid.org/0000-0001-8230-1218

Funding

Fundação de Amparo à Pesquisa do Estado de São Paulo 2019/07111-9
6 · The paper itself

Abstract

Melanoma poses a significant health concern due to its propensity to metastasize and its high mortality rate. Immunotherapy has emerged as a promising treatment strategy for harnessing the patient's immune system to fight tumor cells. However, not all patients respond equally to immunotherapy, highlighting the need for predictive biomarkers to identify potential responders and optimize treatment strategies. Using data from 579 immunology-related genes evaluated by the NanoString nCounter Human Immunology v2 Panel, we integrated transcriptomic data with the clinical characteristics of 35 individuals to develop a predictive signature for immunotherapy response in melanoma patients. Through comprehensive analysis, we identified 18 genes upregulated in non-responder patients and three upregulated in responder patients. In multivariate analysis, CD24, NFIL3, FN1, and KLRK1 were identified as key predictors with significant potential for forecasting treatment outcomes. We then calculated a score incorporating the expression levels of these genes. The score achieved high accuracy in discriminating responders from non-responders, with an area under the curve of 0.935 (p < 0.001). The signature was also significantly associated with progression-free survival, overall survival, and survival following immunotherapy (p < 0.001). The validation of the signature in two independent cohorts confirmed its robustness and applicability, with areas under the curve of 0.758 (p = 0.036) and 0.833 (p = 0.004), respectively. This study represents a significant advance in precision medicine for melanoma. By identifying patients unlikely to benefit from immunotherapy, our approach could help optimize treatment allocation and improve patient outcomes. KEY MESSAGES: Novel 4-gene signature predicts immunotherapy failure in melanoma. High accuracy for personalized treatment decisions. Signature associated with decreased survival for non-responders. Signature validated in independent cohorts, enhancing generalizability. Potential to tailor treatment strategies and avoid unnecessary burden to patients.

Indexed as

Biomarkers, TumorCD24 AntigenImmunotherapyMelanomaAdultAgedFemaleFibronectinsGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMaleMiddle AgedPrognosisTranscriptomeTreatment OutcomeBiomarkers, TumorCD24 AntigenCD24 protein, humanFibronectinsFN1 protein, humanGene expression profilingImmunotherapyMelanomaProgrammed cell death 1 receptorTreatment outcome

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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.