A Novel Necroptosis-Related miRNA Signature for Predicting the Prognosis of Breast Cancer Metastasis

Organotypic 3D Cell-Architecture Impacts the Expression Pattern of miRNAs-mRNAs Network in Breast Cancer SKBR3 Cells

BACKGROUND

Currently, most of the research on breast cancer has been carried out in conventional two-dimensional (2D) cell cultures due to its practical benefits, however, the three-dimensional (3D) cell culture is becoming the model of choice in cancer research because it allows cell-cell and cell-extracellular matrix (ECM) interactions, mimicking the native microenvironment of tumors in vivo.

METHODS

In this work, we evaluated the effect of 3D cell organization on the expression pattern of miRNAs (by Small-RNAseq) and mRNAs (by microarrays) in the breast cancer SKBR3 cell line and analyzed the biological processes and signaling pathways regulated by the differentially expressed protein-coding genes (DE-mRNAs) and miRNAs (DE-microRNAs) found in the organoids.

RESULTS

We obtained well-defined cell-aggregated organoids with a grape cluster-like morphology with a size up to 9.2 × 105 μm3. The transcriptomic assays showed that cell growth in organoids significantly affected (all p < 0.01) the gene expression patterns of both miRNAs, and mRNAs, finding 20 upregulated and 19 downregulated DE-microRNAs, as well as 49 upregulated and 123 downregulated DE-mRNAs. In silico analysis showed that a subset of 11 upregulated DE-microRNAs target 70 downregulated DE-mRNAs. These genes are involved in 150 gene ontology (GO) biological processes such as regulation of cell morphogenesis, regulation of cell shape, regulation of canonical Wnt signaling pathway, morphogenesis of epithelium, regulation of cytoskeleton organization, as well as in the MAPK and AGE-RAGE signaling KEGG-pathways. Interestingly, hsa-mir-122-5p (Fold Change (FC) = 15.4), hsa-mir-369-3p (FC = 11.4), and hsa-mir-10b-5p (FC = 20.1) regulated up to 81% of the 70 downregulated DE-mRNAs.

CONCLUSION

The organotypic 3D cell-organization architecture of breast cancer SKBR3 cells impacts the expression pattern of the miRNAs-mRNAs network mainly through overexpression of hsa-mir-122-5p, hsa-mir-369-3p, and hsa-mir-10b-5p. All these findings suggest that the interaction between cell-cell and cell-ECM as well as the change in the culture architecture impacts gene expression, and, therefore, support the pertinence of migrating breast cancer research from conventional cultures to 3D models.

A novel prognostic signature for clear cell renal cell carcinoma constructed using necroptosis-related miRNAs

Background

This work aims to analyze the relationship between necroptosis-related microRNAs (miRNAs) and the prognosis of clear cell renal cell carcinoma (ccRCC).

Methods

The miRNAs expression profiles of ccRCC and normal renal tissues from The Cancer Genome Atlas (TCGA) database were used to construct a matrix of the 13 necroptosis-related miRNAs. Cox regression analysis was used to construct a signature to predict the overall survival of ccRCC patients. The genes targeted by the necroptosis-related miRNAs in the prognostic signature were predicted using miRNA databases. Gene Ontology (Go) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to investigate the genes targeted by the necroptosis-related miRNAs. The expression levels of selected miRNAs in 15 paired samples (of ccRCC tissues and adjacent normal renal tissues) were investigated using reverse transcriptase quantitative polymerase chain reaction (RT-qPCR).

Results

Six necroptosis-related miRNAs were found to differentially expressed between ccRCC and normal renal tissues. A prognostic signature consisting of miR-223-3p, miR-200a-5p, and miR-500a-3p was constructed using Cox regression analysis and risk scores were calculated. Multivariate Cox regression analysis showed that the hazard ratio was 2.0315 (1.2627–3.2685, P = 0.0035), indicating that the risk score of the signature was an independent risk factor. The receiver operating characteristic (ROC) curve showed that the signature has a favorable predictive capacity and the Kaplan-Meier survival analysis indicated that ccRCC patients with higher risk scores had worse prognoses (P < 0.001). The results of the RT-qPCR verified that all three miRNAs used in the signature were differentially expressed between ccRCC and normal tissues (P < 0.05).

Conclusion

The three necroptosis-related-miRNAs used in this study could be a valuable signature for the prognosis of ccRCC patients. Necroptosis-related miRNAs should be further explored as prognostic indicators for ccRCC.

Comprehensive characterization of RNA cargo of extracellular vesicles in breast cancer patients undergoing neoadjuvant chemotherapy

Extracellular vesicles (EVs) are g7aining increased attention as carriers of cancer-derived molecules for liquid biopsies. Here, we studied the dynamics of EV levels in the plasma of breast cancer (BC) patients undergoing neoadjuvant chemotherapy (NAC) and explored the relevance of their RNA cargo for the prediction of patients' response to the therapy. EVs were isolated from serial blood samples collected at the time of diagnosis, at the end of NAC, and 7 days, 6, and 12 months after the surgery from 32 patients with locally advanced BC, and 30 cancer-free healthy controls (HCs) and quantified by nanoparticle tracking analysis. The pre-treatment levels of EVs in BC patients were higher than in HCs, significantly increased during the NAC and surgery, and decreased to the levels found in HCs 6 months after surgery, thus showing that a substantial fraction of plasma EVs in BC patients are produced due to the disease processes and treatment. RNA sequencing analysis revealed that the changes in the EV levels were associated with the alterations in the proportions of various RNA biotypes in EVs. To search for RNA biomarkers that predict response to the NAC, patients were dichotomized as responders and non-responders based on Miller-Payne grades and differential expression analyses were carried out between responders and non-responders, and HCs. This resulted in the identification of 6 miRNAs, 4 lncRNAs, and 1 snoRNA that had significantly higher levels in EVs from non-responders than responders at the time of diagnosis and throughout the NAC, and significantly lower levels in HCs, thus representing biomarkers for the prediction of response to NAC at the time of diagnosis. In addition, we found 14 RNAs representing piRNA, miRNA, lncRNA, snoRNA, and snRNA biotypes that were induced by NAC in non-responders and 2 snoRNAs and 1 piRNA that were induced by NAC in patients with early disease progression, thus warranting further functional studies on their role in chemoresistance and metastasis.

Identification of a novel necroptosis-associated miRNA signature for predicting the prognosis in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) is one of the most aggressive malignancies that have a poor prognosis. Necroptosis has been demonstrated in recent years to be a form of inflammatory cell death occurring in multicellular organism, which plays complex roles in cancer. However, the expression of necroptosis-related miRNAs and genes in HNSCC and their correlations with prognosis remain unclear. In this study, R software was used to screen differentially expressed miRNAs downloaded from The Cancer Genome Atlas. A prognostic model containing six necroptosis-related miRNAs (miR-141-3p, miR-148a-3p, miR-331-3p, miR-543, miR-425-5p, and miR-7-5p) was generated, whose risk score was validated as an independent prognostic factor for HNSCC. Target genes of the key miRNAs were obtained from TargetScan, miRDB, and miRTarBase, and 193 genes in the intersection of the three databases were defined as consensus genes. Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analyses indicated that the composition of the tumor microenvironment as well as specific pathways may be closely related to necroptosis in HNSCC. Nine key genes were also obtained by the MCODE and cytoHubba plug-ins of Cytoscape: PIK3CD, NRAS, PTK2, IRS2, IRS1, PARP1, KLF4, SMAD2, and DNMT1. A prognostic model formed by the key gene was also established, which can efficiently predict the overall survival of HNSCC patients. In conclusion, necroptosis-related miRNAs and genes play important roles in tumor development and metastasis and can be used to predict the prognosis of HNSCC.

Bibliometric analysis of publications on necroptosis from 2001 to 2021

Background: Necroptosis plays an important role in inflammation, cancer, and neurodegenerative diseases. In recent years, the number of studies related to necroptosis has increased and research has become increasingly in-depth. This study aimed to summarize the research conducted since 2001 to discover hotspots and trends in the field of necroptosis.

Methods: The Web of Science Core database was used to identify global publications on necroptosis from 2001 to 2021. Bibliometric analysis was performed using Rstudio, VOSviewer, and CiteSpace.

Results: The number of publications related to necroptosis gradually increased from 2001 to 2021. Vandenabeele P had the most publications at 45. Yuan JY had the most citations at 5,901. Necroptosis research has been dominated by China and Chinese institutions. Cell Death and Disease had the highest number of related publications among the examined journals. Seven of the top 10 most cited papers had more than 500 citations. Necroptosis, cell death, autophagy, injury, cancer, activated B cell nuclear factor kappa-light chain enhancer, and oxidative stress were important keywords in keyword analysis. Recent research has increasingly focused on breast cancer, receptor-interacting serine/threonine protein kinase 1, modulation, pseudokinase mixed lineage kinase domain-like protein, membrane, protection, and cycle.

Conclusion: Interest in necroptosis-related research continues to increase steadily, and there is close cooperation between countries and institutions in the field of necroptosis. The study of necroptosis-related molecules and mechanisms, and the relationship between necroptosis and cancer, may be hotspots and directions in future research.

Establishment of a Novel Prognostic Prediction Model for Gastric Cancer Based on Necroptosis-Related Genes

Background: Necroptosis plays a crucial role in the progression of multiple types of cancer. However, the role of necroptosis in gastric cancer (GC) remains unclear. The aim of this study is to establish a necroptosis-related prediction model, which could provide information for treatment monitoring.

Methods: The TCGA-STAD cohort was employed to establish a prognostic prediction signature and the GEO dataset was employed for external validation. The correlation between the risk score and the immune landscape, tumor mutational burden (TMB), microsatellite instability (MSI), as well as therapeutic responses of different therapies were analyzed.

Results: We constructed a prognostic model based on necroptosis-associated genes (NAGs), and its favorable predictive ability was confirmed in an external cohort. The risk score was confirmed as an independent determinant, and a nomogram was further established for prognosis. A high score implies higher tumor immune microenvironment (TIME) scores and more significant TIME cell infiltration. High-risk patients presented with lower TMB, and low-TMB patients had worse overall survival (OS). Meanwhile, Low-risk scores are characterized by MSI-high (MSI-H), lower Tumor Immune Dysfunction and Exclusion (TIDE) score, and higher immunogenicity in immunophenoscore (IPS) analysis.

Conclusion: The developed NAG score provides a novel and effective method for predicting the outcome of GC as well as potential targets for further research.

Identification of necroptosis-related subtypes and prognosis model in triple negative breast cancer

Background

Necroptosis is considered to be a new form of programmed necrotic cell death, which is associated with metastasis, progression and prognosis of various types of tumors. However, the potential role of necroptosis-related genes (NRGs) in the triple negative breast cancer (TNBC) is unclear.

Methods

We extracted the gene expression and relevant clinicopathological data of TNBC from The Cancer Genome Atlas (TCGA) databases and the Gene Expression Omnibus (GEO) databases. We analyzed the expression, somatic mutation, and copy number variation (CNV) of 67 NRGs in TNBC, and then observed their interaction, biological functions, and prognosis value. By performing Lasso and COX regression analysis, a NRGs-related risk model for predicting overall survival (OS) was constructed and its predictive capabilities were verified. Finally, the relationship between risk_score and immune cell infiltration, tumor microenvironment (TME), immune checkpoint, and tumor mutation burden (TMB), cancer stem cell (CSC) index, and drug sensitivity were analyzed.

Results

A total 67 NRGs were identified in our analysis. A small number of genes (23.81%) detected somatic mutation, most genes appeared to have a high frequency of CNV, and there was a close interaction between them. These genes were remarkably enriched in immune-related process. A seven-gene risk_score was generated, containing TPSG1, KRT6A, GPR19, EIF4EBP1, TLE1, SLC4A7, ESPN. The low-risk group has a better OS, higher immune score, TMB and CSC index, and lower IC50 value of common therapeutic agents in TNBC. To improve clinical practicability, we added age, stage_T and stage_N to the risk_score and construct a more comprehensive nomogram for predicting OS. It was verified that nomogram had good predictive capability, the AUC values for 1-, 3-, and 5-year OS were 0.847, 0.908, and 0.942.

Conclusion

Our research identified the significant impact of NRGs on immunity and prognosis in TNBC. These findings were expected to provide a new strategy for personalize the treatment of TNBC and improve its clinical benefit.