ANLN and UBE2T are prognostic biomarkers associated with immune regulation in breast cancer: a bioinformatics analysis

Differential whole-genome doubling based signatures for improvement on clinical outcomes and drug response in patients with breast cancer

Whole genome doublings (WGD), a hallmark of human cancer, is pervasive in breast cancer patients. However, the molecular mechanism of the complete impact of WGD on survival and treatment response in breast cancer remains unclear. To address this, we performed a comprehensive and systematic analysis of WGD, aiming to identify distinct genetic alterations linked to WGD and highlight its improvement on clinical outcomes and treatment response for breast cancer. A linear regression model along with weighted gene co-expression network analysis (WGCNA) was applied on The Cancer Genome Atlas (TCGA) dataset to identify critical genes related to WGD. Further Cox regression models with random selection were used to optimize the most useful prognostic markers in the TCGA dataset. The clinical implication of the risk model was further assessed through prognostic impact evaluation, tumor stratification, functional analysis, genomic feature difference analysis, drug response analysis, and multiple independent datasets for validation. Our findings revealed a high aneuploidy burden, chromosomal instability (CIN), copy number variation (CNV), and mutation burden in breast tumors exhibiting WGD events. Moreover, 247 key genes associated with WGD were identified from the distinct genomic patterns in the TCGA dataset. A risk model consisting of 22 genes was optimized from the key genes. High-risk breast cancer patients were more prone to WGD and exhibited greater genomic diversity compared to low-risk patients. Some oncogenic signaling pathways were enriched in the high-risk group, while primary immune deficiency pathways were enriched in the low-risk group. We also identified a risk gene, ANLN (anillin), which displayed a strong positive correlation with two crucial WGD genes, KIF18A and CCNE2. Tumors with high expression of ANLN were more prone to WGD events and displayed worse clinical survival outcomes. Furthermore, the expression levels of these risk genes were significantly associated with the sensitivities of BRCA cell lines to multiple drugs, providing valuable insights for targeted therapies. These findings will be helpful for further improvement on clinical outcomes and contribution to drug development in breast cancer.

Knockdown of Ubiquitin-Conjugating Enzyme E2 T Abolishes the Progression of Head and Neck Squamous Cell Carcinoma by Inhibiting NF-Κb Signaling and inducing Ferroptosis

BACKGROUND

Ubiquitin-conjugating enzyme 2T (UBE2T) has been reported to be associated with uncontrolled cell growth and tumorigenesis in multiple cancer types. However, the understanding of its regulatory role in the carcinogenesis of Head And Neck Squamous Cell Carcinoma (HNSC) is limited.

METHODS

UBE2T expression in HNSC patient samples and the correlation between its expression and patients' survival rates were evaluated using The Cancer Genome Atlas (TCGA) database. Cell survival and proliferation were investigated in UM-SCC1 and UM-SCC15 cells infected with control and shUBE2T lentivirus. The xenograft mouse model was established using UM-SCC15 cells to examine HNSC tumorigenesis with or without UBE2T. Western blot, qRT-PCR, and ferroptosis assays were carried out to disclose the interaction between UBE2T and NF-κB signaling and ferroptosis.

RESULTS

The increased expression of UBE2T was noted in tumor tissues of patients with HNSC, correlating with a significantly reduced overall survival time in this patient cohort. Knockdown of UBE2T inhibited HNSC tumorigenesis and tumor growth. Mechanistically, inhibition of UBE2T suppressed NF-κB signaling and induced ferroptosis in HNSC.

CONCLUSION

Our study underscores the multifaceted role of UBE2T in HNSC, illuminating its potential as a biomarker and therapeutic target.

Weighted Gene Co-Expression Network Analysis Based on Stimulation by Lipopolysaccharides and Polyinosinic:polycytidylic Acid Provides a Core Set of Genes for Understanding Hemolymph Immune Response Mechanisms of Amphioctopus fangsiao

The primary influencer of aquaculture quality in Amphioctopus fangsiao is pathogen infection. Both lipopolysaccharides (LPS) and polyinosinic:polycytidylic acid (Poly I:C) are recognized by the pattern recognition receptor (PRR) within immune cells, a system that frequently serves to emulate pathogen invasion. Hemolymph, which functions as a transport mechanism for immune cells, offers vital transcriptome information when A. fangsiao is exposed to pathogens, thereby contributing to our comprehension of the species' immune biological mechanisms. In this study, we conducted analyses of transcript profiles under the influence of LPS and Poly I:C within a 24 h period. Concurrently, we developed a Weighted Gene Co-expression Network Analysis (WGCNA) to identify key modules and genes. Further, we carried out Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses to investigate the primary modular functions. Co-expression network analyses unveiled a series of immune response processes following pathogen stress, identifying several key modules and hub genes, including PKMYT1 and NAMPT. The invaluable genetic resources provided by our results aid our understanding of the immune response in A. fangsiao hemolymph and will further our exploration of the molecular mechanisms of pathogen infection in mollusks.

Expression profiling of luminal B breast tumor in Indian women

PURPOSE

In this study, we aimed at profiling of luminal B breast cancer specific gene expression pattern in Indian women using mRNA-seq and validation based on TCGA expression data.

METHODS

RNA isolated from luminal B tumor and adjacent normal tissues was used for library construction and sequencing. Reference-based assemblies of these reads were used for differential gene expression analysis using DeSeq2. The DEGs were evaluated using TCGA expression data. Kaplan-Meier survival method was used to evaluate association between genes showing luminal B specific differential expression pattern and breast cancer prognosis and statistical significance was assessed using log-rank test. Alternate splicing analysis was done using rmats.

RESULTS

Differential expression analysis identified 2371 differentially expressed genes (DEGs) in luminal B breast tumors in comparison with adjacent normal tissues of Indian Women. Of them, 1692 DEGs were validated using TCGA luminal B paired samples. Integration of this data with the DEGs obtained by comparative analysis of unpaired luminal B with luminal A unpaired samples from TCGA resulted in 291 DEGs showing luminal B specific expression pattern. Further, 26 genes of prognostic value were identified. Differential splicing analysis between luminal B tumors and adjacent normal tissues in our cohort led to the identification of 687 genes showing significant differential alternate splicing events.

CONCLUSION

This study profiled gene expression pattern of luminal B tumors of Indian women and identified 26 key genes of prognostic value for luminal B breast cancer. This study also profiled differential alternate splicing and identified important alternate splicing events in luminal B breast cancer.

Identification of MIR600HG/hsa-miR-342-3p/ANLN network as a potential prognosis biomarker associated with lmmune infiltrates in pancreatic cancer

Pancreatic cancer is one of the tumors with the worst prognosis, causing serious harm to human health. The RNA network and immune response play an important role in tumor progression. While a systematic RNA network linked to the tumor immune response remains to be further explored in pancreatic cancer. Based on The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, the MIR600HG/hsa-miR-342-3p/ANLN network was determined. WB and IHC were used to confirm the high expression of ANLN in pancreatic cancer. The prognostic model based on the RNA network could effectively predict the survival prognosis of patients. The analysis of immune infiltration showed that the MIR600HG/hsa-miR-342-3p/ANLN network altered the level of infiltration of T helper 2 (Th2) and effector memory T (Tem) cells. Furthermore, we found that the chemokines chemokine ligand (CCL) 5 and CCL14 may play a key role in immune cell infiltration mediated by the RNA network. In conclusion, this study constructed a prognostic model based on the MIR600HG/hsa-miR-342-3p/ANLN network and found that it may function in tumor immunity.

Diverse roles of UBE2T in cancer (Review)

As a leading cause of mortalities worldwide, cancer results from accumulation of both genetic and epigenetic alterations. Disruption of epigenetic regulation in cancer, particularly aberrant ubiquitination, has drawn increasing interest in recent years. The present study aimed to review the roles of ubiquitin‑conjugating enzyme E2 T (UBE2T) and its associated pathways in the pathogenesis of pan‑cancer, and the development of small‑molecule modulators to regulate ubiquitination for treatment strategies. The current study comprehensively investigated the expression landscape and functional significance of UBE2T, as well as its correlation with cancer cell sensitivity to chemotherapy/radiotherapy. Multiple levels of evidence suggested that aberrant UBE2T played important roles in pan‑cancer. Information was collected from 16 clinical trials on ubiquitin enzymes, and it was found that these molecules had an important role in the ubiquitin‑proteasome system. Further studies are necessary to explore their feasibility and effectiveness as diagnostic and prognostic biomarkers, or as up/down‑stream and therapeutic targets for cancer treatment.

Development and Validation of Ferroptosis-Related lncRNAs as Prognosis and Diagnosis Biomarkers for Breast Cancer

Breast cancer (BC) is one of the most common malignancies affecting women. Ferroptosis is a novel cancer treatment option. The present study is aimed to identify suitable ferroptosis-related lncRNAs to predict and diagnose BC. Differential expression and Cox regression analyses were used to screen suitable prognostic biomarkers and construct a suitable risk model. We identified four ferroptosis-related differentially expressed lncRNAs (FR-DELs) (LINC01152, AC004585.1, MAPT-IT1, and AC026401.3), which were independently correlated with the overall survival of BC patients. The area under the curve value of the prognostic model using those four biomarkers was over 0.60 in all three groups. The sensitivity and specificity of the diagnostic model using those four biomarkers were 86.89% and 86.73%, respectively. Our present study indicated that these four FR-DELs (LINC01152, AC004585.1, MAPT-IT1, and AC026401.3) could be prognostic biomarkers for BC, although clinical validation studies are required.