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二硫化物诱导的细胞死亡和铁死亡相关基因定义了免疫微环境，而NUBPL作为预测膀胱癌预后和免疫治疗反应的潜在生物标志物。

Disulfidptosis and ferroptosis related genes define the immune microenvironment and NUBPL serves as a potential biomarker for predicting prognosis and immunotherapy response in bladder cancer.

作者信息

Zhang Xuezhou, Hong Baoan, Li Hongwei, Sun Zhipeng, Zhao Jiahui, Li Mingchuan, Wei Dechao, Wang Yongxing, Zhang Ning

机构信息

Department of Urology, Beijing Anzhen Hospital, Capital Medical University, Beijing, PR China.

Department of Pathology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, Beijing, PR China.

出版信息

Heliyon. 2024 Sep 7;10(17):e37638. doi: 10.1016/j.heliyon.2024.e37638. eCollection 2024 Sep 15.

DOI:10.1016/j.heliyon.2024.e37638
PMID:39290277
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11407088/
Abstract

BACKGROUND

Ferroptosis and disulfidptosis are regulatory forms of cell death that play an important role in tumorigenesis and progression. However, few biomarkers about disulfidptosis and ferroptosis related genes (DFRGs) have been developed to predict the prognosis of bladder cancer (BC).

METHODS

We conducted a bioinformatics analysis using public BC datasets to examine the prognostic significance of differentially expressed DFRGs. A Lasso regression was employed to create a prognostic prediction model from these DFRGs. Hub DFRGs that play a role in immunotherapy response and immunoregulation were pinpointed. Immunohistochemistry (IHC) experiment was performed to assess NUBPL and c-MYC expression in BC patients who underwent surgery or received immune checkpoint inhibitor (ICI) immunotherapy at Peking University Cancer Hospital.

RESULTS

We constructed a valid model to predict the prognosis of BC based on DFRGs and performed relevant validation, the results demonstrated that the model was an independent prognostic factor for BC. Further analysis indicated that the model score, combined with the expression of various immune factors and tumor mutation burden (TMB), could predict the prognosis for BC. In addition, we also found that NUBPL was strongly associated with prognosis and response to ICI treatment, and NUBPL may influence BC malignant progression through the c-MYC pathway.

CONCLUSIONS

Our research findings highlight the satisfactory predictive value of DFRGs in the immune microenvironment and suggest that NUBPL may be a highly promising biomarker for predicting the prognosis and efficacy of ICI treatment in BC patients.

摘要

背景

铁死亡和二硫化物依赖性细胞程序性死亡是细胞死亡的调控形式，在肿瘤发生和进展中起重要作用。然而，针对二硫化物依赖性细胞程序性死亡和铁死亡相关基因（DFRGs）的生物标志物却鲜有开发，用于预测膀胱癌（BC）的预后。

方法

我们使用公开的膀胱癌数据集进行了生物信息学分析，以检验差异表达的DFRGs的预后意义。采用套索回归从这些DFRGs中创建一个预后预测模型。确定了在免疫治疗反应和免疫调节中起作用的关键DFRGs。在北京肿瘤医院对接受手术或接受免疫检查点抑制剂（ICI）免疫治疗的膀胱癌患者进行免疫组织化学（IHC）实验，以评估NUBPL和c-MYC的表达。

结果

我们构建了一个基于DFRGs预测膀胱癌预后的有效模型并进行了相关验证，结果表明该模型是膀胱癌的独立预后因素。进一步分析表明，模型评分结合各种免疫因子的表达和肿瘤突变负荷（TMB），可以预测膀胱癌的预后。此外，我们还发现NUBPL与预后和ICI治疗反应密切相关，NUBPL可能通过c-MYC途径影响膀胱癌的恶性进展。

结论

我们的研究结果突出了DFRGs在免疫微环境中令人满意的预测价值，并表明NUBPL可能是预测膀胱癌患者ICI治疗预后和疗效的极具前景的生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b289/11407088/10154d189e81/mmcfigs5.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b289/11407088/a76c618513f7/mmcfigs1.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b289/11407088/10154d189e81/mmcfigs5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b289/11407088/f8944908b6a2/ga1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b289/11407088/fd20a70a1e29/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b289/11407088/4c222aa06bf1/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b289/11407088/65e0a933a431/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b289/11407088/9d99391aae87/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b289/11407088/2c1773846e91/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b289/11407088/14dda11f6cc8/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b289/11407088/4a04ee5f91bc/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b289/11407088/22766074dee9/gr8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b289/11407088/a76c618513f7/mmcfigs1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b289/11407088/dfde33141f2c/mmcfigs2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b289/11407088/c2b0b621e0b0/mmcfigs3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b289/11407088/c7056e6faf4c/mmcfigs4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b289/11407088/10154d189e81/mmcfigs5.jpg

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