A DCS-related lncRNA signature predicts the prognosis and chemotherapeutic response of patients with gastric cancer

Zhang, Yang; Li, Leyan; Tu, Yi; Feng, Zongfeng; Li, Zhengrong; Cao, Yi; Li, Yong

doi:10.1042/bsr20220989

Cited by 5 publications

(4 citation statements)

References 54 publications

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“…These genes also play a significant role in DDR ( 53 – 55 ); nonetheless, the mechanism by which MAGI2-AS3 impacts DDR in GC has yet to be elucidated. Previous research revealed that LINC00106 expression was decreased in cisplatin-resistant GC cell lines and that knocking down LINC00106 enhanced the proliferation and migration of AGS cell lines ( 56 ). Given that cisplatin induces a DNA damage response by binding to DNA ( 57 ), it is possible that LINC00106 is involved in the DDR process and influences the phenotype of GC cells.…”

Section: Discussionmentioning

confidence: 99%

The DNA damage repair-related lncRNAs signature predicts the prognosis and immunotherapy response in gastric cancer

et al. 2023

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BackgroundGastric cancer (GC) is one of the most prevalent cancers, and it has unsatisfactory overall treatment outcomes. DNA damage repair (DDR) is a complicated process for signal transduction that causes cancer. lncRNAs can influence the formation and incidence of cancers by influencing DDR-related mRNAs/miRNAs. A DDR-related lncRNA prognostic model is urgently needed to improve treatment strategies.MethodsThe data of GC samples were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. A total of 588 mRNAs involved in DDR were selected from MSigDB, 62 differentially expressed mRNAs from TCGA-STAD were obtained, and 137 lncRNAs were correlated with these mRNAs. Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses were used to develop a DDR-related lncRNA prognostic model. Based on the risk model, the differentially expressed gene signature A/B in the low-risk and high-risk groups of TCGA-STAD was identified for further validation.ResultsThe prognosis model of 5 genes (AC145285.6, MAGI2-AS3, AL590705.3, AC007405.3, and LINC00106) was constructed and classified into two risk groups. We found that GC patients with a low-risk score had a better OS than those with a high-risk score. We found that the high-risk group tended to have higher TME scores. We also found that patients in the high-risk group had a higher proportion of resting CD4 T cells, monocytes, M2 macrophages, resting dendritic cells, and resting mast cells, whereas the low-risk subgroup had a greater abundance of activated CD4 T cells, follicular helper T cells, M0 macrophages, and M1 macrophages. We observed significant differences in the T-cell exclusion score, T-cell dysfunction, MSI, and TMB between the two risk groups. In addition, we found that patients treated with immunotherapy in the low-RS score group had a longer survival and a better prognosis than those in the high-RS score group.ConclusionThe prognostic model has a significant role in the TME, clinicopathological characteristics, prognosis, MSI, and drug sensitivity. We also discovered that patients treated with immunotherapy in the low-RS score group had a better prognosis. This work provides a foundation for improving the prognosis and response to immunotherapy among patients with GC.

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Section: Discussionmentioning

confidence: 99%

The DNA damage repair-related lncRNAs signature predicts the prognosis and immunotherapy response in gastric cancer

et al. 2023

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“…LncRNA AC104964.4 expression is associated with the sensitivity to docetaxel, cisplatin, and S-1 (DCS) treatment. Yang et al reported that the expression of the lncRNA AC104964.4 decreased in cisplatin-resistant gastric cancer (GC) cells, suggesting that lncRNA AC104964.4 is involved in the response to chemotherapeutic drugs 41 . It is also negatively related to immune infiltration (neutrophils, mast cells and Treg cells), indicating a relatively good prognosis in patients with GC 42 .…”

Section: Discussionmentioning

confidence: 99%

A Model to Predict Prognosis of Renal Cell Clear Cell Carcinoma Based on 3 Angiogenesis-related Long Non-coding RNAs

Chen,

Zhang,

et al. 2024

J. Cancer

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Background: Tumor angiogenesis is closely related to the progression of clear cell renal cell carcinoma (ccRCC). Long non-coding RNAs (lncRNAs) regulating angiogenesis could be potential biomarkers for predicting ccRCC prognosis. With this study, we aimed to construct a prognostic model based on lncRNAs and explore its underlying mechanisms. Methods: RNA data and clinical information were obtained from The Cancer Genome Atlas (TCGA) database. Angiogenesis-related genes (ARGs) were extracted from the Molecular Signatures database. Pearson correlation and LASSO and COX regression analyses were performed to identify survival-related AR-lncRNAs (sAR-lncRNAs) and construct a prognostic model. The predictive power of the prognostic model was verified according to Kaplan-Meier curve, receiver operating characteristic (ROC) curve and nomogram analyses. The correlation between the prognostic model and clinicopathological characteristics was assessed via univariate and multivariate analyses. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was subsequently performed to elucidate the mechanisms of the sAR-lncRNAs. In vitro qPCR, immunohistochemistry, migration and invasion assays were conducted to confirm the angiogenic function of sAR-lncRNAs. Results: Three sAR-lncRNAs were used to construct a prognostic model. The model was moderately accurate in predicting 1-, 3-and 5-year ccRCC prognosis, and the risk score according to this model was closely related to clinicopathological characteristics such as T grade and T stage. A nomogram was constructed to precisely estimate the overall survival of ccRCC patients. KEGG enrichment analysis indicated that the MAPK and Notch pathways were highly enriched in high-risk patients. Additionally, we found that the expression of the lncRNAs AC005324.4 and AC104964.4 in the prognostic model was lower in ccRCC cell lines and cancer tissues than in the HK-2 cell line and paracancerous tissues, while the expression of the lncRNA AC087482.1 showed the opposite trend. In a coculture model, knockdown of lncRNA AC005324.4 and lncRNA AC104964.4 significantly promoted the migration and invasion of human umbilical vein endothelial cells (HUVECs), but siR-AC087482.1 transfection alleviated these effects. Conclusions:We constructed a prognostic model based on 3 sAR-lncRNAs and validated its value in clinicopathological characteristics and prognostic prediction of ccRCC patients, providing a new perspective for ccRCC treatment decision making.

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“…In this review, a total of 17 articles ( Table 3 ) used the differential expression of different functionally related lncRNAs to construct algorithms, so as to provide a basis for guiding clinical prognosis and predicting therapeutic effects. Four articles [ 191 , 192 , 193 , 194 ] used drug-resistant tissues or cells (PR, MDR, and DCSR) for differential lncRNA screening to construct a model. Four articles [ 193 , 194 , 195 , 196 ] constructed prediction models based on pyroptosis-related lncRNAs (PRlncRNAs).…”

Section: Clinical Application Of Drug Resistance-related Lncrnasmentioning

confidence: 99%

Long Non-Coding RNAs in Drug Resistance of Gastric Cancer: Complex Mechanisms and Potential Clinical Applications

Meng,

Bai,

et al. 2024

Biomolecules

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Gastric cancer (GC) ranks as the third most prevalent malignancy and a leading cause of cancer-related mortality worldwide. However, the majority of patients with GC are diagnosed at an advanced stage, highlighting the urgent need for effective perioperative and postoperative chemotherapy to prevent relapse and metastasis. The current treatment strategies have limited overall efficacy because of intrinsic or acquired drug resistance. Recent evidence suggests that dysregulated long non-coding RNAs (lncRNAs) play a significant role in mediating drug resistance in GC. Therefore, there is an imperative to explore novel molecular mechanisms underlying drug resistance in order to overcome this challenging issue. With advancements in deep transcriptome sequencing technology, lncRNAs—once considered transcriptional noise—have garnered widespread attention as potential regulators of carcinogenesis, including tumor cell proliferation, metastasis, and sensitivity to chemo- or radiotherapy through multiple regulatory mechanisms. In light of these findings, we aim to review the mechanisms by which lncRNAs contribute to drug therapy resistance in GC with the goal of providing new insights and breakthroughs toward overcoming this formidable obstacle.

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A DCS-related lncRNA signature predicts the prognosis and chemotherapeutic response of patients with gastric cancer

Cited by 5 publications

References 54 publications

The DNA damage repair-related lncRNAs signature predicts the prognosis and immunotherapy response in gastric cancer

The DNA damage repair-related lncRNAs signature predicts the prognosis and immunotherapy response in gastric cancer

A Model to Predict Prognosis of Renal Cell Clear Cell Carcinoma Based on 3 Angiogenesis-related Long Non-coding RNAs

Long Non-Coding RNAs in Drug Resistance of Gastric Cancer: Complex Mechanisms and Potential Clinical Applications

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