LncRNAs as tumor cell intrinsic factors that affect cancer immunotherapy

Egranov, Sergey D.; Hu, Qingsong; Lin, Chunru; Yang, Liuqing

doi:10.1080/15476286.2020.1767455

Cited by 14 publications

(6 citation statements)

References 28 publications

(37 reference statements)

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“…This is quite different from the direct effects of regular lncRNAs on the biological functions of tumor cells [ 12 , 30 ]. Therefore, the expression levels of IRlncRs often correlate with clinical outcomes such as sensitivity to immunotherapy and prognosis [ 13 ], highlighting their advantage as tumor biomarkers.…”

Section: Discussionmentioning

confidence: 99%

“…Specifically, a subset of lncRNAs act as immune-related lncRNAs (IRlncRs) by regulating immune responses in the tumor microenvironment. This subset of lncRNAs has been shown to play a key role in modulating tumor immunosurveillance, immune cell infiltration into the tumor microenvironment, and sensitivity of cancer cells to immunotherapy treatment [ 12 , 13 ]. Cao et al identified an immune-related five-lncRNAs signature positively correlated with tumour immune cell infiltration and the poor prognosis in bladder cancer patients.…”

Section: Introductionmentioning

confidence: 99%

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Immune-related LncRNAs scores predicts chemotherapeutic responses and prognosis in cervical cancer patients

Tian,

Tan,

Wang

et al. 2024

Discov Onc

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Background Long non-coding RNAs (LncRNAs) regulating the immune microenvironment of cancer is a hot spot. But little is known about the influence of the immune-related lncRNA (IRlncRs) on the chemotherapeutic responses and prognosis of cervical cancer (CC) patients. The purpose of the study was to identify an immune-related lncRNAs (IRlncRs)-based model for the prospective prediction of clinical outcomes in CC patients. Methods CC patients’ relevant data was acquired from The Cancer Genome Atlas (TCGA). Correlation analysis and Cox regression analyses were applied. A risk score formula was formulated. Prognostic factors were combined into a nomogram, while sensitivity for chemotherapy drugs was analyzed using the OncoPredict algorithm. Results Eight optimal IRlncRs(ATP2A1-AS1, LINC01943, AL158166.1, LINC00963, AC009065.8, LIPE-AS1, AC105277.1, AC098613.1.) were incorporated in the IRlncRs model. The overall survival (OS) of the high-risk group of the model was inferior to those in the low-risk group. Further analysis demonstrated this eight-IRlncRs model as a useful prognostic marker. The Nomogram had a concordance index of survival prediction of 0.763(95% CI 0.746–0.780) and more robust predictive accuracy. Furthermore, patients in the low-risk group were found to be more sensitive to chemotherapy, including Paclitaxel, Rapamycin, Epirubicin, Vincristine, Docetaxel and Vinorelbine. Conclusions An eight-IRlncRs-based prediction model was identified that has the potential to be an important tool to predict chemotherapeutic responses and prognosis for CC patients.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Immune-related LncRNAs scores predicts chemotherapeutic responses and prognosis in cervical cancer patients

Tian,

Tan,

Wang

et al. 2024

Discov Onc

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“…It has been demonstrated that p53 induces the alternative transcript PVT1B during genotoxic stress, which helps p53-mediated tumor growth restriction in vivo by regulating the transcription of the nearby MYC genes. Alternatively, it has also been shown that the lncRNA LINC02525, which is upregulated in neuroblastomas and interacts with the ribosomal protein RPL35 to activate the translation of E2F1, maintains the stability of the NMYC protein, and causes ERK protein phosphorylation, plays an obvious oncogenic role [ 12 , 13 ].…”

Section: Introductionmentioning

confidence: 99%

“…Maternally expressed gene 3 (lncRNA MEG3) is one of these tumor suppressor lncRNAs that have received a lot of attention [ 13 ]. Researchers have demonstrated that the lncRNA MEG3 could control p53 expression to act as a tumor suppressor gene.…”

Section: Introductionmentioning

confidence: 99%

Decoding the regulatory landscape of lncRNAs as potential diagnostic and prognostic biomarkers for gastric and colorectal cancers

Zabeti Touchaei,

Vahidi,

Samadani

2024

Clin Exp Med

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Colorectal cancer (CRC) and gastric cancer (GC) are major contributors to cancer-related mortality worldwide. Despite advancements in understanding molecular mechanisms and improved drug treatments, the overall survival rate for patients remains unsatisfactory. Metastasis and drug resistance are major challenges contributing to the high mortality rate in both CRC and GC. Recent research has shed light on the role of long noncoding RNAs (lncRNAs) in the development and progression of these cancers. LncRNAs regulate gene expression through various mechanisms, including epigenetic modifications and interactions with microRNAs (miRNAs) and proteins. They can serve as miRNA precursors or pseudogenes, modulating gene expression at transcriptional and post-transcriptional levels. Additionally, circulating lncRNAs have emerged as non-invasive biomarkers for the diagnosis, prognosis, and prediction of drug therapy response in CRC and GC. This review explores the intricate relationship between lncRNAs and CRC/GC, encompassing their roles in cancer development, progression, and chemoresistance. Furthermore, it discusses the potential of lncRNAs as therapeutic targets in these malignancies. The interplay between lncRNAs, miRNAs, and tumor microenvironment is also highlighted, emphasizing their impact on the complexity of cancer biology. Understanding the regulatory landscape and molecular mechanisms governed by lncRNAs in CRC and GC is crucial for the development of effective diagnostic and prognostic biomarkers, as well as novel therapeutic strategies. This review provides a comprehensive overview of the current knowledge and paves the way for further exploration of lncRNAs as key players in the management of CRC and GC. Graphical Abstract

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“…Over the past few decades, there has been increasing evidence that lncRNAs play a key role in regulating cancer proliferation, metastasis, cell cycle, and programmed death [10][11][12][13]. LncRNA is a class of RNA molecules with transcripts longer than 200 nucleotides.…”

Section: Introductionmentioning

confidence: 99%

Construction and validation of a prognostic risk model for cuproptosis-related lncrna in breast cancer

Chen

Zhong

Chen

et al. 2023

Preprint

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Background Long non-coding RNAs(LncRNAs) are vital in regulating programmed death in breast cancer. Cuproptosis is a newly type of regulatory cell death(RCD) in tumor pathogenesis, development, prognosis and potentially as a target for immunotherapy. Methods The expression profile data and clinical information data of breast cancer (BRCA) from the Cancer Genome Atlas (TCGA) were downloaded using the R package TCGA biolinks. The differential expression analysis was performed using R package ‘limma’. Univariate Cox analysis was performed on deregulated LncRNA related to cuproptosis to screen signature related to the prognosis of breast cancer. Using Cytoscape construct mRNA (cuproptosis-related factors) and co-expression of LncRNA networks. The network was verified in TCGA training set, global set and test set. Functional enrichment analysis was also performed for studied pathway. Results In this study, 1156 samples was screened from TCGA dataset for differential expression analysis, and finally a total of 284 dysregulated LncRNAs in breast cancer was identified. Then based on the expression of cuproptosis factors and dysregulated LncRNAs, a total of 140 cuproptosis-related dysregulated lncRNAs (CRDLs) were obtained by correlation analysis. Finally, eight model genes(LINC01235, MIR205HG, RP11-459E5.1, RP11-817J15.3, KLHDC7B-DT, LMNTD2-AS1, RP11-6O2.3, LINC00987) were obtained, one of which was a risk factor., we identified a prognostic risk model of dysregulated lncRNAs associated with cuproptosis by collecting RNA-seq data from TCGA. Subsequently, we verify this model, and the results showed that there were significant differences between the high and low-risk groups. Then, we took the test set and whole set, respectively, to perform model verification and prove that they have stable and favorable performance on survival prediction. And the Risk score we selected can be used as an independent prognostic factor. There were significant differences in the proportion of immune cell infiltration, genomic mutations, pathway enrichment scores, expression levels of immune checkpoints and chemoresistance between high and low-risk groups. Conclusion Ultimately, we conclude that the risk score can predict the benefit of immunotherapy in patients, and the model genes may be markers of immunotherapy response.

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LncRNAs as tumor cell intrinsic factors that affect cancer immunotherapy

Cited by 14 publications

References 28 publications

Immune-related LncRNAs scores predicts chemotherapeutic responses and prognosis in cervical cancer patients

Immune-related LncRNAs scores predicts chemotherapeutic responses and prognosis in cervical cancer patients

Decoding the regulatory landscape of lncRNAs as potential diagnostic and prognostic biomarkers for gastric and colorectal cancers

Construction and validation of a prognostic risk model for cuproptosis-related lncrna in breast cancer

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