Evidence map›Paper›PMID 35067161›Full record

ArticleBioengineered2022

Prognostic and therapeutic significance of a novel ferroptosis related signature in colorectal cancer patients.

Songtao Du, Furong Zeng, Huiyan Sun, Yanlong Liu, Peng Han, Bomiao Zhang, Weinan Xue, Guangtong Deng, Mingzhu Yin, Binbin Cui

Open access · goldAbstract readVideo-Audio Media
In one paragraph

Article in Bioengineered, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
7.9field-weighted citation impact, top 2% 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

33 citing papers in PubMed, 49 citations in OpenAlex.

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  17. Ferroptosis: the balance between death and survival in colorectal cancer.International journal of biological sciences · 2024
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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

10 authors at 4 institutions in 1 country.

Songtao DuDepartment of Colorectal Surgical Oncology, The Tumor Hospital of Harbin Medical University, Harbin, China.
Furong ZengDepartment of Dermatology, Hunan Engineering Research Center of Skin Health and Disease, Hunan Key Laboratory of Skin Cancer and Psoriasis, Xiangya Hospital, Central South University, Changsha, Hunan, China.
Huiyan SunDepartment of Dermatology, Hunan Engineering Research Center of Skin Health and Disease, Hunan Key Laboratory of Skin Cancer and Psoriasis, Xiangya Hospital, Central South University, Changsha, Hunan, China.
Yanlong LiuDepartment of Colorectal Surgical Oncology, The Tumor Hospital of Harbin Medical University, Harbin, China.
Peng HanDepartment of Colorectal Surgical Oncology, The Tumor Hospital of Harbin Medical University, Harbin, China.
Bomiao ZhangDepartment of Colorectal Surgical Oncology, The Tumor Hospital of Harbin Medical University, Harbin, China.
Weinan XueDepartment of Colorectal Surgical Oncology, The Tumor Hospital of Harbin Medical University, Harbin, China.
Guangtong DengDepartment of Dermatology, Hunan Engineering Research Center of Skin Health and Disease, Hunan Key Laboratory of Skin Cancer and Psoriasis, Xiangya Hospital, Central South University, Changsha, Hunan, China.
Mingzhu YinDepartment of Dermatology, Hunan Engineering Research Center of Skin Health and Disease, Hunan Key Laboratory of Skin Cancer and Psoriasis, Xiangya Hospital, Central South University, Changsha, Hunan, China.
Binbin CuiDepartment of Colorectal Surgical Oncology, The Tumor Hospital of Harbin Medical University, Harbin, China.
Harbin Medical University · CNHunan Cancer Hospital · CNCentral South University · CNXiangya Hospital Central South University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Increasing studies have highlighted the importance of ferroptosis in colorectal cancer (CRC). However, how to use ferroptosis-related genes (FRGs) to predict the prognosis and guide the treatment of CRC remains unknown. To build a prognostic prediction model using the GEO and TCGA databases and explored a therapeutic strategy for CRC patients based on FRGs. A total of 60 FRGs were identified and three of them including ACACA, GSS, and NFS1 were associated with the prognosis of CRC. Using Lasso regression analysis, an FRGs signature was constructed and validated as an independent prognostic predictor. Then we developed a nomogram based on the FRGs signature and clinical prognostic factors to predict the prognosis of CRC patients, which was better than the traditional TNM staging system. Single-sample gene set enrichment analysis (ssGSEA) was further performed for the functional analysis and suggested that JAK-STAT signaling, Ras signaling pathway, MAPK signaling pathway, and PI3K-Akt signaling pathway were significantly enriched in CRC patients with higher FRGs risk score. Interestingly, CRC cells with higher FRGs risk score were more sensitive to RSL3. Knocking down GSS and NFS1 increased the FRGs risk score and the sensitivity of CRC cells to RSL3. For the clinic use, we screened 75 FDA-approved cancer drugs and found that Fludarabine phosphate could decrease the expression of GSS and NFS1 most. Fludarabine phosphate, in combination with RSL3, showed a strong synergistic effect on CRC cells. Together, this study identified a potent prognostic model and provided an alternative individualized treatment for CRC patients.

Indexed as

Databases, GeneticFerroptosisGene Expression ProfilingGene Expression Regulation, NeoplasticModels, BiologicalAntineoplastic AgentsBiomarkers, TumorColorectal NeoplasmsHumansMAP Kinase Signaling SystemPrognosisAntineoplastic AgentsBiomarkers, Tumorcolorectal cancerFerroptosis-related genesfludarabine phosphatersl3signature

Identifiers

PMID35067161
PMCPMC8973628
OpenAlexW4206968097

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.