Evidence map›Paper›PMID 36419893›Full record

ArticleFrontiers in oncology2022

Development and validation of prognostic index based on immunogenic cell death-related genes with melanoma.

Yajun Han, Qinqin Cai, Xiaolin Xie, Shilong Gao, Xiwen Fan

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.6field-weighted citation impact, top 30% of its field
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

5 citing papers in PubMed, 6 citations in OpenAlex.

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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 at 1 institution in 1 country.

Yajun HanThird Clinical Medical College, Xinjiang Medical University, Urumqi, China.
Qinqin CaiThird Clinical Medical College, Xinjiang Medical University, Urumqi, China.
Xiaolin XieThird Clinical Medical College, Xinjiang Medical University, Urumqi, China.
Shilong GaoThird Clinical Medical College, Xinjiang Medical University, Urumqi, China.
Xiwen FanDepartment of Interventional Medicine, Affiliated Cancer Hospital, Xinjiang Medical University, Urumqi, China.
Xinjiang Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although immune checkpoint inhibitors have improved the overall survival rate of skin cutaneous melanoma (SKCM) patients, there is a wide variation and low response rate to these treatments in clinical immunotherapy for melanoma patients. These problems can be addressed through the induction of immunogenic cell death (ICD).We constructed an ICD-based prognostic model to predict the prognosis of SKCM patients and the efficacy of immunotherapy. Information on melanoma and normal samples obtained by TCGA and GTEx was stratified by ICD-related genes. The samples were divided into two subtypes according to high and low expression of ICD using an unsupervised clustering method (K-means). Patients with ICD-high subtype showed longer overall survival. We found that the ICD-related differential genes were associated with several cell death and immune-related pathways through GO, KEGG and GSEA. Immunoscore and tumor purity of ICD-associated genes was calculated using ESTIMATE, and ICD-high subtypes had higher immunoscore and lower tumor purity than ICD-low subtypes. Seven ICD-associated genes were obtained by one-way Cox regression and Lasso regression of ICD genes. Risk models were constructed to classify melanoma patients into high- risk and low-risk groups. The expression of ICD-related pivotal genes was lower in the high-risk group than in the low-risk group, and the survival time was significantly higher in the low-risk group than in the high-risk group. We then found that ICD risk characteristics had predictive value for the clinical efficacy of immunotherapy, with higher ICD risk scores in the immunotherapy non-responsive group. Combined with clinicopathological factors, a nomogram was established. the ROC and calibration curves assessed the ability of the nomogram to predict prognosis. We developed a new classification system for SKCM based on the characteristics of ICDs. This stratification has important clinical implications for estimating the prognosis and immunotherapy of SKCM patients.

Indexed as

immunogenic cell deathimmunotherapymelanomaprognosistumor microenvionment

Identifiers

PMID36419893
PMCPMC9677727
OpenAlexW4310330289

What OpenQuestion holds

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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.