A pyroptosis‐related lncRNA signature in bladder cancer

Wang, Peng; Wang, Zhiqiang; Zhu, Liping; Sun, Yongchang; Castellano, Leandro; Stebbing, Justin; Yu, Zhentao; Peng, Ling

doi:10.1002/cam4.5344

Cited by 8 publications

(7 citation statements)

References 47 publications

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“…Wang et al. developed a novel signature based on pyroptosis-related lncRNAs in BC, playing vital roles in cancer immunology and serving as potential therapeutic targets [ 32 ]. MAN1B1 was also revealed as a new biomarker for BC and strongly linked with immune cells infiltration degree [ 33 ].…”

Section: Discussionmentioning

confidence: 99%

A novel 17 apoptosis-related genes signature could predict overall survival for bladder cancer and its associations with immune infiltration

Wang¹,

Cheng²,

Zeng³

et al. 2022

Heliyon

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Section: Discussionmentioning

confidence: 99%

A novel 17 apoptosis-related genes signature could predict overall survival for bladder cancer and its associations with immune infiltration

Wang¹,

Cheng²,

Zeng³

et al. 2022

Heliyon

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“…According to the previous studies, we selected 52 pyroptosis-related genes (PRGs) [ 16 , 17 ]. We compared the differential expression of PRGs in both normal and tumor tissues.…”

Section: Methodsmentioning

confidence: 99%

Risk factors analysis and survival prediction model establishment of patients with lung adenocarcinoma based on different pyroptosis-related gene subtypes

Wen,

Pei,

Dai

et al. 2023

Eur J Med Res

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Background Lung adenocarcinoma (LUAD) is a common cancer with a poor prognosis. Pyroptosis is an important process in the development and progression of LUAD. We analyzed the risk factors affecting the prognosis of patients and constructed a nomogram to predict the overall survival of patients based on different pyroptosis-related genes (PRGs) subtypes. Methods The genomic data of LUAD were downloaded from the TCGA and GEO databases, and all data were filtered and divided into TCGA and GEO cohorts. The process of data analysis and visualization was performed via R software. The data were classified based on different PRGs subtypes using the K-means clustering method. Then, the differentially expressed genes were identified between two different subtypes, and risk factors analysis, survival analysis, functional enrichment analysis, and immune cells infiltration landscape analysis were conducted. The COX regression analysis was used to construct the prediction model. Results Based on the PRGs of LUAD, the patients were divided into two subtypes. We found the survival probability of patients in subtype 1 is higher than that in subtype 2. The results of the logistics analysis showed that gene risk score was closely associated with the prognosis of LUAD patients. The results of GO analysis and KEGG analysis revealed important biological processes and signaling pathways involved in the differentially expressed proteins between the two subtypes. Then we constructed a prediction model of patients’ prognosis based on 13 genes, including IL-1A, P2RX1, GSTM2, ESYT3, ZNF682, KCNF1, STK32A, HHIPL2, GDF10, NDC80, GSTA1, BCL2L10, and CCR2. This model was strongly related to the overall survival (OS) and also reflects the immune status in patients with LUAD. Conclusion In our study, we examined LUAD heterogeneity with reference to pyroptosis and found different prognoses between the two subtypes. And a novel prediction model was constructed to predict the OS of LUAD patients based on different PRGs signatures. The model has shown excellent predictive efficiency through validation.

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“…Irregular levels of lncRNA expression can play a pivotal role in the development of various types of cancer, serving as a significant regulatory factor in their onset with a predictive potential (8). lncRNAs can perform diverse biological functions in different types of cancers, such as regulating gene expression, metabolism, immunity, influencing cell proliferation, controlling apoptosis and affecting tumor metastasis (13)(14)(15)(16). These versatile molecules can act as oncogenes, promoting cancer growth, or tumor suppressors, inhibiting tumor progression, or both depending on the specific context and type of cancer.…”

Section: Decoding Long Non-coding Rnas: Friends and Foes In Cancer De...mentioning

confidence: 99%

Decoding long non‑coding RNAs: Friends and foes in cancer development (Review)

Song,

Adu‑Amankwaah,

Zhao

et al. 2024

Int J Oncol

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Cancer remains a formidable adversary, challenging medical advancements with its dismal prognosis, low cure rates and high mortality rates. Within this intricate landscape, long non-coding RNAs (lncRNAs) emerge as pivotal players, orchestrating proliferation and migration of cancer cells. Harnessing the potential of lncRNAs as therapeutic targets and prognostic markers holds immense promise. The present comprehensive review delved into the molecular mechanisms underlying the involvement of lncRNAs in the onset and progression of the top five types of cancer. By meticulously examining lncRNAs across diverse types of cancer, it also uncovered their distinctive roles, highlighting their exclusive oncogenic effects or tumor suppressor properties. Notably, certain lncRNAs demonstrate diverse functions across different cancers, confounding the conventional understanding of their roles. Furthermore, the present study identified lncRNAs exhibiting aberrant expression patterns in numerous types of cancer, presenting them as potential indicators for cancer screening and diagnosis. Conversely, a subset of lncRNAs manifests tissue-specific expression, hinting at their specialized nature and untapped significance in diagnosing and treating specific types of cancer. The present comprehensive review not only shed light on the intricate network of lncRNAs but also paved the way for further research and clinical applications. The unraveled molecular mechanisms offer a promising avenue for targeted therapeutics and personalized medicine, combating cancer proliferation, invasion and metastasis.

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A pyroptosis‐related lncRNA signature in bladder cancer

Abstract: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 8 publications

References 47 publications

A novel 17 apoptosis-related genes signature could predict overall survival for bladder cancer and its associations with immune infiltration

A novel 17 apoptosis-related genes signature could predict overall survival for bladder cancer and its associations with immune infiltration

Risk factors analysis and survival prediction model establishment of patients with lung adenocarcinoma based on different pyroptosis-related gene subtypes

Decoding long non‑coding RNAs: Friends and foes in cancer development (Review)

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