Bioinformatics analysis based on immune-autophagy-related lncRNAs combined with immune infiltration in bladder cancer

An extensive overview of the role of lncRNAs generated from immune cells in the etiology of cancer

Long non-coding RNAs (lncRNAs) are involved in the control of critical tumor-suppressor and oncogenic pathways in cancer. These types of non-coding RNAs could affect both immune and cancer cells. The thorough analysis of lncRNAs derived from immune cells and the incorporation of new findings significantly advance our understanding of the complex role of lncRNAs in the context of cancer. This work highlights the promise of lncRNAs for translational therapeutic approaches while also establishing a solid foundation for comprehending the complex link between lncRNAs and cancer through a coherent narrative. The main findings of this article are that types of lncRNAs derived from immune cells, such as MM2P and MALAT1, can affect the behaviors of cancer cells, like invasion, angiogenesis, and proliferation. As research in this area grows, the therapeutic potential of targeting these lncRNAs offers promising opportunities for expanding our understanding of cancer biology and developing cutting-edge, precision-based therapies for cancer therapy.

Identification of glycogene signature as a tool to predict the clinical outcome and immunotherapy response in breast cancer

Background

Breast cancer is one of the most important diseases in women around the world. Glycosylation modification correlates with carcinogenesis and roles of glycogenes in the clinical outcome and immune microenvironment of breast cancer are unclear.

Methods

A total of 1297 breast cancer and normal cases in the TCGA and GTEx databases were enrolled and the transcriptional and survival information were extracted to identify prognostic glycogenes using Univariate Cox, LASSO regression, Multivariate Cox analyses and Kaplan-Meier method. The immune infiltration pattern was explored by the single sample gene set enrichment method. The HLA and immune checkpoint genes expression were also compared in different risk groups. The expressions of a glycogene MGAT5 as well as its products were validated by immunohistochemistry and western blotting in breast cancer tissues and cells.

Results

A 19-glycogene signature was identified to separate breast cancer patients into high- and low-risk groups with distinct overall survival rates (P < 0.001). Compared with the high-risk group, proportion of naive B cells, plasma cells and CD8⁺ T cells increased in the low-risk group (P < 0.001). Besides, expressions of HLA and checkpoint genes, such as CD274, CTLA4, LAG3 and TIGIT3, were upregulated in low-risk group. Additionally, highly expressed MGAT5 was validated in breast cancer tissues and cells. Downstream glycosylation products of MGAT5 were all increased in breast cancer.

Conclusions

We identified a 19-glycogene signature for risk prediction of breast cancer patients. Patients in the low-risk group demonstrated a higher immune infiltration and better immunotherapy response. The validation of MGAT5 protein suggests a probable pathway and target for the development and treatment of breast cancer.

Ferroptosis-Related Long Noncoding RNAs Have Excellent Predictive Ability for Multiomic Characteristics of Bladder Cancer

Background

The role of ferroptosis-related long non-coding RNAs (lncRNAs) in bladder cancer remains elusive. This study is aimed at examining the prognostic role of ferroptosis-related lncRNAs in bladder cancer.

Materials and Methods

The transcriptomic matrix and clinical information of patients with bladder cancer were obtained from The Cancer Genome Atlas (TCGA) database. A ferroptosis-related lncRNA signature was developed via the least absolute shrinkage and selection operator (LASSO) analysis using data from the training cohort, and the signature was further validated using data from the test cohort. The role of AC006160.1, the most significant lncRNA in the risk signature, was examined in various cell lines including SV-HUC-1, BIU-87, HT-1376, T24, RT4, RT-112, 5637, and UMUC3. The pcDNA3.1-AC006160.1 plasmid was constructed and transfected into the bladder cancer cell lines T24 and BIU-87. In addition, cell proliferation, colony formation, transwell, and wound healing assays were performed to examine the biological function of AC006160.1 in T24 and BIU-87 cell lines.

Results

Two clusters were identified through consensus clustering based on prognostic ferroptosis-related lncRNAs. A 5-lncRNA risk signature was successfully constructed using data from the training cohort and validated using data from the test cohort. The risk signature had excellent ability to predict survival outcomes, clinical stages, pathological grades, expression of immune checkpoints, and immunotherapeutic responses in bladder cancer samples. Furthermore, AC006160.1 expression was found to be lower in the cancer cell lines BIU-87, T24, RT4, RT-112, and 5637 than in the normal control cell line SV-HUC-1. Cell proliferation, colony formation, transwell migration, and wound healing assays validated that overexpression of AC006160.1 significantly inhibited the proliferation and invasion abilities of both T24 and BIU-87 cells. Drug sensitivity analysis revealed that patients with high expression of AC006160.1 were sensitive to metformin and methotrexate, and the results were further validated via in vitro drug experiments.

Conclusions

Ferroptosis-related lncRNAs play a vital role in predicting the multiomic characteristics of bladder cancer. The lncRNA AC006160.1 serves as a protective factor for the development of bladder cancer.

Glycosylation modification patterns reveal distinct tumor metabolism and immune microenvironment landscape in lower-grade gliomas

Glycosylation alterations, a key driver throughout tumorigenesis and tumor progression, could regulate the microenvironment and immune response as well as lead to harmful metabolism and cell signaling. In this study, we first comprehensively evaluated the glycosylation modification patterns of LGGs based on glycosyltransferase family genes and systematically integrated these modification patterns with tumor metabolism and immune microenvironment characteristics. Glycosylation score was also developed to quantify glycosylation modification patterns of individuals. As a result, two glycosylation modification patterns were identified, with distinct prognosis, metabolism, and immune microenvironment features. The glycosylation subtype A and cluster A were characterized by higher carbohydrates and amino acid metabolism activity, higher levels of infiltrating cells, and poor prognosis, whereas an opposite modification pattern was observed in glycosylation subtype B and cluster B. In addition, a high glycosylation score is closer to a microenvironment characterized by chronic inflammation, immunosuppression, and tumor promotion. Following analysis and validation, the glycosylation score was a reliable and independent prognostic index. More importantly, the glycosylation score influenced the response to immunotherapy, chemotherapy, or targeted therapy, which provided a novel insight into promoting personalized therapy in the future and may contribute to developing novel therapeutic drugs or exploring promising drug combination therapy strategies.

An HDAC9-associated immune-related signature predicts bladder cancer prognosis

Background

The close relationship between histone deacetylase 9 (HDAC9) and immunity has attracted attention. We constructed an immune signature for HDAC9, a vital epigenetic modification, to predict the survival status and treatment benefits in bladder cancer (BC).

Methods

An exhaustive analysis of HDAC9 and immunology via the tumor and immune system interaction database (TISIDB) was performed, and an immune prognostic risk signature was developed based on genes enriched in the top five immune-related pathways under high HDAC9 status. Comprehensive analysis of survival curves and Cox regression were used to estimate the effectiveness of the risk signature. The relationship between immunological characteristics and the risk score was evaluated, and the mechanisms were also explored.

Results

In the TISIDB, HDAC9 was closely related to various immunological characteristics. The risk signature was obtained based on genes related to prognosis enriched in the top five immune-related pathways under high HDAC9 status. The survival rate of the high-risk BC patients was poor. The risk score was closely related to multiple immunological characteristics, drug sensitivity, immunotherapy benefits and biofunctions.

Conclusion

An immune-related prognostic signature established for HDAC9 expression status could independently predict the prognosis of BC patients. The use of this signature could help clinicians make personalized treatment decisions.

Identification of an Autophagy-Related Pair Signature for Predicting Prognoses and Immune Activity in Pancreatic Adenocarcinoma

BACKGROUND

Pancreatic adenocarcinoma (PAAD) spreads quickly and has a poor prognosis. Autophagy research on PAAD could reveal new biomarkers and targets for diagnosis and treatment.

METHODS

Autophagy-related genes were translated into autophagy-related gene pairs, and univariate Cox regression was performed to obtain overall survival (OS)-related IRGPs (P<0.001). LASSO Cox regression analyses were performed to construct an autophagy-related gene pair (ARGP) model for predicting OS. The Cancer Genome Atlas (TCGA)-PAAD cohort was set as the training group for model construction. The model predictive value was validated in multiple external datasets. Receiver operating characteristic (ROC) curves were used to evaluate model performance. Tumor microenvironments and immune infiltration were compared between low- and high-risk groups with ESTIMATE and CIBERSORT. Differentially expressed genes (DEGs) between the groups were further analyzed by Gene Ontology biological process (GO-BP) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses and used to identify potential small-molecule compounds in L1000FWD.

RESULTS

Risk scores were calculated as follows: ATG4B|CHMP4C×(-0.31) + CHMP2B|MAP1LC3B×(0.30) + CHMP6|RIPK2 ×(-0.33) + LRSAM1|TRIM5×(-0.26) + MAP1LC3A|PAFAH1B2×(-0.15) + MAP1LC3A|TRIM21×(-0.08) + MET|MFN2×(0.38) + MET|MTDH×(0.47) + RASIP1|TRIM5×(-0.23) + RB1CC1|TPCN1×(0.22). OS was significantly shorter in the high-risk group than the low-risk group in each PAAD cohort. The ESTIMATE analysis showed no difference in stromal scores but a significant difference in immune scores (p=0.0045) and ESTIMATE scores (p=0.014) between the groups. CIBERSORT analysis showed higher naive B cell, Treg cell, CD8 T cell, and plasma cell levels in the low-risk group and higher M1 and M2 macrophage levels in the high-risk group. In addition, the results showed that naive B cells (r=-0.32, p<0.001), Treg cells (r=-0.31, p<0.001), CD8 T cells (r=-0.24, p=0.0092), and plasma cells (r=-0.2, p<0.026) were statistically correlated with the ARGP risk score. The top 3 enriched GO-BPs were signal release, regulation of transsynaptic signaling, and modulation of chemical synaptic transmission, and the top 3 enriched KEGG pathways were the insulin secretion, dopaminergic synapse, and NF-kappa B signaling pathways. Several potential small-molecule compounds targeting ARGs were also identified.

CONCLUSION

Our results demonstrate that the ARGP-based model may be a promising prognostic indicator for identifying drug targets in patients with PAAD.