Nasopharyngeal Carcinoma Protein Interaction Mapping Analysis via Proteomic Approaches

Combination of bulk RNA sequencing and scRNA sequencing uncover the molecular characteristics of MAPK signaling in kidney renal clear cell carcinoma

The MAPK signaling pathway significantly impacts cancer progression and resistance; however, its functions remain incompletely assessed across various cancers, particularly in kidney renal clear cell carcinoma (KIRC). Therefore, there is an urgent need for comprehensive pan-cancer investigations of MAPK signaling, particularly within the context of KIRC. In this research, we obtained TCGA pan-cancer multi-omics data and conducted a comprehensive analysis of the genomic and transcriptomic characteristics of the MAPK signaling pathway. For in-depth investigation in KIRC, status of MAPK pathway was quantitatively estimated by ssGSEA and Ward algorithm was utilized for cluster analysis. Molecular characteristics and clinical prognoses of KIRC patients with distinct MAPK activities were comprehensively explored using a series of bioinformatics algorithms. Subsequently, a combination of LASSO and COX regression analyses were utilized sequentially to construct a MAPK-related signature to help identify the risk level of each sample. Patients in the C1 subtype exhibited relatively higher levels of MAPK signaling activity, which were associated with abundant immune cell infiltration and favorable clinical outcomes. Single-cell RNA sequencing (scRNA-seq) analysis of KIRC samples identified seven distinct cell types, and endothelial cells in tumor tissues had obviously higher MAPK scores than normal tissues. The immunohistochemistry results indicated the reduced expression levels of PAPSS1, MAP3K11, and SPRED1 in KIRC samples. In conclusion, our study represents the first integration of bulk RNA sequencing and single-cell RNA sequencing to elucidate the molecular characteristics of MAPK signaling in KIRC, providing a solid foundation for precision oncology.

Integrated analysis of single-cell and bulk RNA-sequencing reveals tumor heterogeneity and a signature based on NK cell marker genes for predicting prognosis in hepatocellular carcinoma

Background: Natural killer (NK) cells are a type of innate immune cell that recognize and eliminate tumor cells and infected cells, without prior sensitization or activation. Herein, we aimed to construct a predictive model based on NK cell-related genes for hepatocellular carcinoma (HCC) patients and assess the feasibility of utilizing this model for prognosis prediction. Methods: Single-cell RNA-seq data were obtained from the Gene Expression Omnibus (GEO) database to identify marker genes of NK cells. Univariate Cox and lasso regression were performed to further establish a signature in the TCGA dataset. Subsequently, qPCR and immunohistochemistry (IHC) staining were employed to validate the expression levels of prognosis signature genes in HCC. The effectiveness of the model was further validated using two external cohorts from the GEO and ICGC datasets. Clinical characteristics, prognosis, tumor mutation burden, immune microenvironments, and biological function were compared for different genetic subtypes and risk groups. Finally, molecular docking was performed to evaluate the binding affinity between the hub gene and chemotherapeutic drugs. Results: A total of 161 HCC-related NK cell marker genes (NKMGs) were identified, 28 of which were significantly associated with overall survival in HCC patients. Based on differences in gene expression characteristics, HCC patients were classified into three subtypes. Ten prognosis genes (KLRB1, CD7, LDB2, FCER1G, PFN1, FYN, ACTG1, PABPC1, CALM1, and RPS8) were screened to develop a prognosis model. The model not only demonstrated excellent predictive performance on the training dataset, but also were successfully validated on two independent external datasets. The risk scores derived from the model were shown to be an independent prognosis factor for HCC and were correlated with pathological severity. Moreover, qPCR and IHC staining confirmed that the expression of the prognosis genes was generally consistent with the results of the bioinformatic analysis. Finally, molecular docking revealed favorable binding energies between the hub gene ACTG1 and chemotherapeutic drugs. Conclusion: In this study, we developed a model for predicting the prognosis of HCC based on NK cells. The utilization of NKMGs as innovative biomarkers showed promise in the prognosis assessment of HCC.

In-Silico Multi-Omics Analysis of the Functional Significance of Calmodulin 1 in Multiple Cancers

Aberrant activation of calmodulin 1 (CALM1) has been reported in human cancers. However, comprehensive understanding of the role of CALM1 in most cancer types has remained unclear. We systematically analyzed the expression landscape, DNA methylation, gene alteration, immune infiltration, clinical relevance, and molecular pathway of CALM1 in multiple cancers using various online tools, including The Cancer Genome Atlas, cBioPortal and the Human Protein Atlas databases. Kaplan–Meier and receiver operating characteristic (ROC) curves were plotted to explore the prognostic and diagnostic potential of CALM1 expression. Multivariate analyses were used to evaluate whether the CALM1 expression could be an independent risk factor. A nomogram predicting the overall survival (OS) of patients was developed, evaluated, and compared with the traditional Tumor-Node-Metastasis (TNM) model using decision curve analysis. R language was employed as the main tool for analysis and visualization. Results revealed CALM1 to be highly expressed in most cancers, its expression being regulated by DNA methylation in multiple cancers. CALM1 had a low mutation frequency (within 3%) and was associated with immune infiltration. We observed a substantial positive correlation between CALM1 expression and macrophage and neutrophil infiltration levels in multiple cancers. Different mutational forms of CALM1 hampered immune cell infiltration. Additionally, CALM1 expression had high diagnostic and prognostic potential. Multivariate analyses revealed CALM1 expression to be an independent risk factor for OS. Therefore, our newly developed nomogram had a higher clinical value than the TNM model. The concordance index, calibration curve, and time-dependent ROC curves of the nomogram exhibited excellent performance in terms of predicting the survival rate of patients. Moreover, elevated CALM1 expression contributes to the activation of cancer-related pathways, such as the WNT and MAPK pathways. Overall, our findings improved our understanding of the function of CALM1 in human cancers.

Current Status and Future Perspectives about Molecular Biomarkers of Nasopharyngeal Carcinoma

Simple Summary

Nasopharyngeal carcinoma is a serious major public health problem in its endemic countries. Up to 80% of NPC patients with locally advanced disease or distant metastasis at diagnosis were associated with poor prognosis and with median survival less than 4 months. The mortality rate of NPC metastasis is up to 91%. To date, there is no available curative treatment or reliable early diagnosis or prognosis for NPC. Discovery and development of reliable early diagnosis and prognosis biomarkers for nasopharyngeal carcinoma are urgent needed. Hence, we have here listed the potential early diagnosis and prognosis biomarker candidates for nasopharyngeal carcinoma. This review will give an insight to readers on the progress of NPC biomarker discovery to date, as well as future prospective biomarker development and their translation to clinical use.

Abstract

Nasopharyngeal carcinoma (NPC) is an epithelial malignancy that shows a remarkable ethnic and geographical distribution. It is one of the major public health problems in some countries, especially Southern China and Southeast Asia, but rare in most Western countries. Multifactorial interactions such as Epstein–Barr virus infection, individual’s genetic susceptibility, as well as environmental and dietary factors may facilitate the pathogenesis of this malignancy. Late presentation and the complex nature of the disease have led it to become a major cause of mortality. Therefore, an effective, sensitive, and specific molecular biomarker is urgently needed for early disease diagnosis, prognosis, and prediction of metastasis and recurrence after treatment. In this review, we discuss the recent research status of potential biomarker discovery and the problems that need to be explored further for better NPC management. By studying the aberrant pattern of these candidate biomarkers that promote NPC development and progression, we are able to understand the complexity of this malignancy better, hence positing our stands better towards strategies that may provide a way forward to the discovery of more reliable and specific biomarkers for diagnosis and targeted therapeutic development.

Research status and prospects of biomarkers for nasopharyngeal carcinoma in the era of high‑throughput omics (Review)

As a malignant tumor type, nasopharyngeal carcinoma (NPC) is characterized by distinct geographical, ethnic and genetic differences; presenting a major threat to human health in many countries, especially in Southern China. At present, no accurate and effective methods are available for the early diagnosis, efficacious evaluation or prognosis prediction for NPC. As such, a large number of patients have locoregionally advanced NPC at the time of initial diagnosis. Many patients show toxic reactions to overtreatment and have risks of cancer recurrence and distant metastasis owing to insufficient treatment. To solve these clinical problems, high‑throughput '‑omics' technologies are being used to screen and identify specific molecular biomarkers for NPC. Because of the lack of comprehensive descriptions regarding NPC biomarkers, the present study summarized the research progress that has been made in recent years to discover NPC biomarkers, highlighting the existing problems that require exploration. In view of the lack of authoritative reports at present, study design factors that affect the screening of biomarkers are also discussed here and prospects for future research are proposed to provide references for follow‑up studies of NPC biomarkers.

Investigation of PRDM10 and PRDM13 Expression in Developing Mouse Embryos by an Optimized PACT-Based Embryo Clearing Method

Recent developments in tissue clearing methods have significantly advanced the three-dimensional analysis of biological structures in whole, intact tissue, providing a greater understanding of spatial relationships and biological circuits. Nonetheless, studies have reported issues with maintaining structural integrity and preventing tissue disintegration, limiting the wide application of these techniques to fragile tissues such as developing embryos. Here, we present an optimized passive tissue clearing technique (PACT)-based embryo clearing method, initial embedding PACT (IMPACT)-Basic, that improves tissue rigidity without compromising optical transparency. We also present IMPACT-Advance, which is specifically optimized for thin slices of mouse embryos past E13.5. We demonstrate proof-of-concept by investigating the expression of two relatively understudied PR domain (PRDM) proteins, PRDM10 and PRDM13, in intact cleared mouse embryos at various stages of development. We observed strong PRDM10 and PRDM13 expression in the developing nervous system and skeletal cartilage, suggesting a functional role for these proteins in these tissues throughout embryogenesis.

CALM1 promotes progression and dampens chemosensitivity to EGFR inhibitor in esophageal squamous cell carcinoma

Background

Calmodulin1 (CALM1) has been identified as one of the overexpression genes in a variety of cancers and EGFR inhibitor have been widely used in clinical treatment but it is unknown whether CALM1 and epidermal growth factor receptor (EGFR) have a synergistic effect in esophageal squamous cell carcinoma (ESCC). The aim of the present study was to explore the synergistic effects of knock-out CALM1 combined with EGFR inhibitor (Afatinib) and to elucidate the role of CALM1 in sensitizing the resistance to Afatinib in ESCC.

Method

Immunohistochemistry (IHC) and qRT-PCR were used to examine the expression of CALM1 and EGFR in ESCC tissues. Kaplan–Meier survival analysis was used to analyze the clinical and prognostic significance of CALM1 and EGFR expression in ESCC. Furthermore, to evaluate the biological function of CALM1 in ESCC, the latest gene editing technique CRISPR/Cas9(Clustered regularly interspaced short palindromic repeats)was applied to knockout CALM1 in ESCC cell lines KYSE150, Eca109 and TE-1. MTT, flow cytometry, Transwell migration, scratch wound-healing and colony formation assays were performed to assay the combined effect of knock-out CALM1 and EGFR inhibitor on ESCC cell proliferation and migration. In addition, nude mice xenograft model was used to observe the synergistic inhibition of knock-out CALM1 and Afatinib.

Results

Both CALM1 and EGFR were found to be significantly over-expressed in ESCC compared with paired normal control. Over-expressed CALM1 and EGFR were significantly associated with clinical stage, T classification and poor overall prognosis, respectively. In vitro, the combined effect of knock-out CALM1 mediated by the lentivirus and EGFR inhibitor was shown to be capable of inhibiting the proliferation, inducing cell cycle arrest at G1/S stage and increasing apoptosis of KYSE-150 and Eca109 cells; invasion and migration were also suppressed. In vivo, the results of tumor weight and total fluorescence were markedly reduced compared with the sgCtrl-infected group and sgCAML1 group.

Conclusion

Our data demonstrated that knock-out of CALM1 could sensitize ESCC cells to EGFR inhibitor, and it may exert oncogenic role via promotion of EMT. Taken together, CALM1 may be a tempting target to overcome Afatinib resistance.

Multifaceted Role of PRDM Proteins in Human Cancer

The PR/SET domain family (PRDM) comprise a family of genes whose protein products share a conserved N-terminal PR [PRDI-BF1 (positive regulatory domain I-binding factor 1) and RIZ1 (retinoblastoma protein-interacting zinc finger gene 1)] homologous domain structurally and functionally similar to the catalytic SET [Su(var)3-9, enhancer-of-zeste and trithorax] domain of histone methyltransferases (HMTs). These genes are involved in epigenetic regulation of gene expression through their intrinsic HMTase activity or via interactions with other chromatin modifying enzymes. In this way they control a broad spectrum of biological processes, including proliferation and differentiation control, cell cycle progression, and maintenance of immune cell homeostasis. In cancer, tumor-specific dysfunctions of PRDM genes alter their expression by genetic and/or epigenetic modifications. A common characteristic of most PRDM genes is to encode for two main molecular variants with or without the PR domain. They are generated by either alternative splicing or alternative use of different promoters and play opposite roles, particularly in cancer where their imbalance can be often observed. In this scenario, PRDM proteins are involved in cancer onset, invasion, and metastasis and their altered expression is related to poor prognosis and clinical outcome. These functions strongly suggest their potential use in cancer management as diagnostic or prognostic tools and as new targets of therapeutic intervention.

Identification of chemoresistance-associated miRNAs in breast cancer

Background

Neoadjuvant chemotherapy (NAC) is an effective therapeutic regimen for patients with breast cancer. However, some individuals cannot benefit from NAC because of drug resistance. To date, valid strategies about enhancing sensitivity of breast cancer to NAC are still scarce. miRNAs have been reported to proverbially be involved in the onset and development of malignancies including drug resistance.

Methods

GSE73736 was downloaded from the GEO database. Student's t-test was conducted to acquire differentially expressed-miRNAs (DE-miRNAs). Potential target genes of DE-miRNAs were predicted by miRTarBase. Gene Ontology annotation and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses for these target genes were performed by database for annotation, visualization, and integrated discovery. Protein-protein interaction network was constructed by STRING database and visualized through Cytoscape software. The hub target gene-miRNA network was also established by Cytoscape software. Next, the expression of potential functional miRNAs in breast cancer cell lines and tissues was determined. Finally, the roles of miR-3617-3p, miR-3136-3p, and miR-520b in modulating breast cancer chemoresistance were further examined.

Results

A total of 123 DE-miRNAs were identified, including 60 upregulated miRNAs and 63 downregulated miRNAs in the chemoresistant breast cancer group when compared with the chemosensitive group. Six hundred and seventeen and 1,146 potential target genes for the top 10 most upregulated and downregulated miRNAs were predicted, respectively. Enrichment analyses revealed that these target genes were enriched in some cancer-associated or chemo-resistance-associated pathways, such as MAPK signaling pathway, wnt signaling pathway, and p53 signaling pathway. MAPK1 and PRDM10 were identified as hub genes in the protein-protein interaction network. The top 25 hub genes were potentially regulated by 16 DE-miRNAs, among which miR-3617-3p and miR-3136-3p were commonly upregulated, whereas miR-520b was downregulated in two chemoresistant breast cancer cells compared with chemosensitive cell. By analyzing TCGA data, we found that expression of miR-3136-3p and miR-520b was increased and decreased in breast cancer tissues, respectively. Moreover, functional experiments demonstrated that miR-3136-3p and miR-3617-3p could reduce chemosensitivity of breast cancer, whereas miR-520b could reverse chemoresistance.

Conclusion

The present study, based on bioinformatics analysis and experimental validation, brings to light novel mechanisms of breast cancer NAC resistance.