The complex role of MEG3: An emerging long non-coding RNA in breast cancer

Hussain, Md Sadique; Majami, Abdullah A.; Ali, Haider; Gupta, Gaurav; Almalki, Waleed Hassan; Alzarea, Sami I.; Kazmi, Imran; Syed, Rahamat Unissa; Khalifa, Nasrin E.; Bin Break, Mohammed Khaled; Khan, Ruqaiyah; Altwaijry, Najla; Sharma, Rahul

doi:10.1016/j.prp.2023.154850

Cited by 27 publications

(1 citation statement)

References 96 publications

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“…Loss of RARRES3 is a key driver of lung metastasis in estrogen receptor-positive breast cancer, and the activation of RARRES3 is considered a useful therapeutic strategy for bladder cancer [ 50 , 51 ]. MEG3 serves as a tumor suppressor in breast cancer by influencing on the expression of miR-182 and miR-29 [ 52 ]. These genes displayed differential expression between patients with PACA and the control participants and were significantly correlated with the survival of patients with PACA.…”

Section: Discussionmentioning

confidence: 99%

Identification and Validation of T-Cell Exhaustion Signature for Predicting Prognosis and Immune Response in Pancreatic Cancer by Integrated Analysis of Single-Cell and Bulk RNA Sequencing Data

Zhu,

Tan,

Luo

et al. 2024

Diagnostics

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Purpose: Pancreatic cancer (PACA) is one of the most fatal malignancies worldwide. Immunotherapy is largely ineffective in patients with PACA. T-cell exhaustion contributes to immunotherapy resistance. We investigated the prognostic potential of T-cell exhaustion-related genes (TEXGs). Methods: A single-cell RNA (scRNA) sequencing dataset from Tumor Immune Single-Cell Hub (TISCH) and bulk sequencing datasets from the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) were used to screen differentially expressed TEXGs. Kaplan–Meier survival, LASSO regression, and univariate/multivariate Cox regression analyses were performed to construct a TEXG risk model. This model was used to predict the prognosis, tumor immune microenvironment, and immunotherapy response. The PACA cohorts from the ICGC and GSE71729 datasets were used to validate the risk model. Pan-cancer expression of SPOCK2 was determined using the TISCH database. Results: A six-gene (SPOCK2, MT1X, LIPH, RARRES3, EMP1, and MEG3) risk model was constructed. Patients with low risk had prolonged survival times in both the training (TCGA-PAAD, n = 178) and validation (ICGC-PACA-CA, ICGC-PAAD-US, and GSE71729, n = 412) datasets. Multivariate Cox regression analysis demonstrated that the risk score was an independent prognostic variable for PACA. High-risk patients correlated with their immunosuppressive status. Immunohistochemical staining confirmed the changes in TEXGs in clinical samples. Moreover, pan-cancer scRNA sequencing datasets from TISCH analysis indicated that SPOCK2 may be a novel marker of exhausted CD8+ T-cells. Conclusion: We established and validated a T-cell exhaustion-related prognostic signature for patients with PACA. Moreover, our study suggests that SPOCK2 is a novel marker of exhausted CD8+ T cells.

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Section: Discussionmentioning

confidence: 99%