A novel cuproptosis-related prognostic 2-lncRNAs signature in breast cancer

Xu, Qitong; Wang, Ziwen; Cai, Mengyuan; Wei, Ji‐Fu; Ding, Qiang

doi:10.3389/fphar.2022.1115608

Cited by 4 publications

(1 citation statement)

References 61 publications

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“…Long noncoding RNAs (lncRNAs), which are functional RNA molecules exceeding 200 nucleotides in length, play critical roles in gene transcription and post-transcriptional modification despite their lack of protein-coding potential. Recently, lncRNAs have been identified as promising biomarkers for diagnosing and prognosing various diseases 9 . Aberrant expression of specific lncRNAs promotes tumor development and is linked to poor clinical outcomes.…”

Section: Introductionmentioning

confidence: 99%

Identification and validation of a copper homeostasis-related gene signature for the predicting prognosis of breast cancer patients via integrated bioinformatics analysis

Li,

Wei,

Wang

et al. 2024

Sci Rep

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The prognostic value of copper homeostasis-related genes in breast cancer (BC) remains largely unexplored. We analyzed copper homeostasis-related gene profiles within The Cancer Genome Atlas Program breast cancer cohorts and performed correlation analysis to explore the relationship between copper homeostasis-related mRNAs (chrmRNA) and lncRNAs. Based on these results, we developed a gene signature-based risk assessment model to predict BC patient outcomes using Cox regression analysis and a nomogram, which was further validated in a cohort of 72 BC patients. Using the gene set enrichment analysis, we identified 139 chrmRNAs and 16 core mRNAs via the Protein–Protein Interaction network. Additionally, our copper homeostasis-related lncRNAs (chrlncRNAs) (PINK1.AS, OIP5.AS1, HID.AS1, and MAPT.AS1) were evaluated as gene signatures of the predictive model. Kaplan–Meier survival analysis revealed that patients with a high-risk gene signature had significantly poorer clinical outcomes. Receiver operating characteristic curves showed that the prognostic value of the chrlncRNAs model reached 0.795 after ten years. Principal component analysis demonstrated the capability of the model to distinguish between low- and high-risk BC patients based on the gene signature. Using the pRRophetic package, we screened out 24 anticancer drugs that exhibited a significant relationship with the predictive model. Notably, we observed higher expression levels of the four chrlncRNAs in tumor tissues than in the adjacent normal tissues. The correlation between our model and the clinical characteristics of patients with BC highlights the potential of chrlncRNAs for predicting tumor progression. This novel gene signature not only predicts the prognosis of patients with BC but also suggests that targeting copper homeostasis may be a viable treatment strategy.

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Section: Introductionmentioning

confidence: 99%

Identification and validation of a copper homeostasis-related gene signature for the predicting prognosis of breast cancer patients via integrated bioinformatics analysis

Li,

Wei,

Wang

et al. 2024

Sci Rep

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Development of a novel disulfidptosis-related lncRNA signature for prognostic and immune response prediction in clear cell renal cell carcinoma

Wang,

Hu,

Wang

et al. 2024

Sci Rep

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Disulfidptosis, a novel form of regulated cell death, occurs due to the aberrant accumulation of intracellular cystine and other disulfides. Moreover, targeting disulfidptosis could identify promising approaches for cancer treatment. Long non-coding RNAs (lncRNAs) are known to be critically implicated in clear cell renal cell carcinoma (ccRCC) development. Currently, the involvement of disulfidptosis-related lncRNAs in ccRCC is yet to be elucidated. This study primarily dealt with identifying and validating a disulfidptosis-related lncRNAs-based signature for predicting the prognosis and immune landscape of individuals with ccRCC. Clinical and RNA sequencing data of ccRCC samples were accessed from The Cancer Genome Atlas (TCGA) database. Pearson correlation analysis was conducted for the identification of the disulfidptosis-related lncRNAs. Additionally, univariate Cox regression analysis, Least Absolute Shrinkage and Selection Operator Cox regression, and stepwise multivariate Cox analysis were executed to develop a novel risk prognostic model. The prognosis-predictive capacity of the model was then assessed using an integrated method. Variation in biological function was noted using GO, KEGG, and GSEA. Additionally, immune cell infiltration, the tumor mutational burden (TMB), and tumor immune dysfunction and exclusion (TIDE) scores were calculated to investigate differences in the immune landscape. Finally, the expression of hub disulfidptosis-related lncRNAs was validated using qPCR. We established a novel signature comprised of eight lncRNAs that were associated with disulfidptosis (SPINT1-AS1, AL121944.1, AC131009.3, AC104088.3, AL035071.1, LINC00886, AL035587.2, and AC007743.1). Kaplan–Meier and receiver operating characteristic curves demonstrated the acceptable predictive potency of the model. The nomogram and C-index confirmed the strong correlation between the risk signature and clinical decision-making. Furthermore, immune cell infiltration analysis and ssGSEA revealed significantly different immune statuses among risk groups. TMB analysis revealed the link between the high-risk group and high TMB. It is worth noting that the cumulative effect of the patients belonging to the high-risk group and having elevated TMB led to decreased patient survival times. The high-risk group depicted greater TIDE scores in contrast with the low-risk group, indicating greater potential for immune escape. Finally, qPCR validated the hub disulfidptosis-related lncRNAs in cell lines. The established novel signature holds potential regarding the prognosis prediction of individuals with ccRCC as well as predicting their responses to immunotherapy.

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Determining new disulfidptosis-associated lncRNA signatures pertinent to breast cancer prognosis and immunological microenvironment

Zheng

Lin

Zhang

et al. 2023

Preprint

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Purpose: Disulfidptosis, a novel form of cell death triggered by disulfide stress, could have significant implications in breast cancer (BC) pathogenesis. Despite this, the identification of disulfidptosis-related lncRNAs in BC remains has not been reported. Therefore, this study aimed to examine the prognostic potential of disulfidptosis-associated lncRNAs in BC. Methods: RNA-seq data and clinical information of BC patients were obtained from the TCGA database. Co-expression analysis was performed to identify disulfidptosis-associated lncRNAs. Subsequently, a risk signature was developed through univariate Cox and LASSO analyses, and its predictive ability was validated. Additionally, the association between the risk signature and immune cell infiltration, immune function, tumor mutational burden (TMB）, and immune checkpoints was investigated. Finally, potential anticancer drugs associated with the risk signatures were predicted. Results: A 10-lncRNA signature was established to stratify BC patients into high-risk and low-risk groups, where the high-risk group showed an unfavorable prognosis. This signature served as an independent prognostic factor in BC patients. Notably, the two subgroups displayed distinct mutation gene profiles, and the risk score exhibited a significant correlation with TMB. Furthermore, ssGSEA and immune checkpoint analysis revealed a significant association between the predictive signature and the immune status of BC patients. Finally, 55 potential anticancer drugs associated with the signature were identified. CONCLUSIONS: We successfully established an independent prognostic signature of disulfidptosis-related lncRNAs in BC patients. This signature provides a solid basis for future investigations into the functional significance of disulfidptosis-associated lncRNAs in breast cancer.

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A novel cuproptosis-related prognostic 2-lncRNAs signature in breast cancer

Cited by 4 publications

References 61 publications

Identification and validation of a copper homeostasis-related gene signature for the predicting prognosis of breast cancer patients via integrated bioinformatics analysis

Identification and validation of a copper homeostasis-related gene signature for the predicting prognosis of breast cancer patients via integrated bioinformatics analysis

Development of a novel disulfidptosis-related lncRNA signature for prognostic and immune response prediction in clear cell renal cell carcinoma

Determining new disulfidptosis-associated lncRNA signatures pertinent to breast cancer prognosis and immunological microenvironment

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