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Disulfidptosis-Related lncRNA for the Establishment of Novel Prognostic Signature and Therapeutic Response Prediction to Endometrial Cancer

  • Gynecologic Oncology: Original Article
  • Published:
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Abstract

Disulfidptosis, a newly discovered cellular death mechanism initiated by disulfide stress, features elevated expression of SLC7A11 and restricted glucose availability, rendering it a possible therapeutic target for cancer. Endometrial cancer of the uterine corpus (ECUC) ranks among prevalent gynecological malignancies. Long non-coding RNAs (lncRNAs) have been implicated in ECUC’s metabolic pathways, invasive capabilities, and metastatic processes. Yet, the prognostic implications of Disulfidptosis-Linked lncRNAs (DLLs) in ECUC remain ambiguous. Transcriptome and clinical datasets related to ECUC were sourced from The Cancer Genome Atlas (TCGA), while genes linked with disulfidptosis were identified from existing literature. A panel of ten DLLs was discerned through least absolute shrinkage and selection operator (LASSO) coupled with Cox regression methods to formulate and validate risk prognostic models. We engineered a nomogram for ECUC patient prognosis forecasting and further examined the model via gene set enrichment analysis (GSEA), principal component analysis (PCA), gene set analysis (GSA), immune profiling, and sensitivity to antineoplastic agents. Prognostic models employing a set of ten DLLs (including AC005034.2, AC020765.2, AL158071.4, AL161663.2, AP000787.1, CR392039.3, EMSLR, SEC24B-AS1, Z69733.1, Z94721.3) were established. Based on median risk values, patient samples were stratified into high- and low-risk cohorts, revealing notable differences in survival across both training and validation datasets. The risk scores, when amalgamated with clinical variables, acted as standalone predictors of prognosis. GSEA findings indicated that the high-risk category predominantly aligned with pathways like extracellular matrix interactions and cell adhesion molecules, suggesting a likely association with metastatic potential. Concurrently, we scrutinized disparities in immune function and tumor mutational burden across risk categories and identified anticancer drugs with likely efficacy. In summary, a set of ten DLLs proved useful in forecasting patient outcomes and holds potential for informing targeted therapeutic approaches in ECUC.

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Data Availability

The data presented in this study are available on request from the corresponding author.

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Author notes

  1. Shanping Shi and Xiaojian Tang contributed equally to this work and shared the first authorship.

Authors and Affiliations

  1. Department of Obstetrics and Gynecology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, People’s Republic of China

    Shanping Shi, Xiaojian Tang & Hua Liu

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  1. Shanping Shi
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  2. Xiaojian Tang
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  3. Hua Liu
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Contributions

SS, HL, and XT initiated the study and designed the experiments. SS and HL performed data collection and analysis. XT helped with discussion and interpretation of results. SS wrote the manuscript.

Corresponding author

Correspondence to Hua Liu.

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Shi, S., Tang, X. & Liu, H. Disulfidptosis-Related lncRNA for the Establishment of Novel Prognostic Signature and Therapeutic Response Prediction to Endometrial Cancer. Reprod. Sci. 31, 811–822 (2024). https://doi.org/10.1007/s43032-023-01382-x

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