Medulloblastoma is the neuroepithelial tumor with the highest degree of malignancy in the central nervous system, accounting for about 8% to 10% of children’s brain tumors. It has a high degree of malignancy and is easily transmitted through cerebrospinal fluid, with a relatively poor prognosis. Although medulloblastoma has been widely studied and treated, its molecular mechanism remains unclear. To determine which gene plays a crucial role in medulloblastoma development and progression, we analyzed three microarray datasets from Gene Expression Omnibus. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were used to detect and evaluate differentially expressed genes. Protein interaction network was established, and the hub genes were determined in cytoHubba through various assessment methods, while the target genes were screened out using survival analysis. Ultimately, human medulloblastoma samples were utilized to confirm target gene expression. In conclusion, This study found that aurora kinase A (AURKA) and kinesin family member 20A (KIF20A) may be involved in the initiation and development of medulloblastoma, have a close association with prognosis, and may become a potential therapeutic target and prognostic marker of MED.

/pdf/integrated-analysis-of-transcriptome-data-revealed-aurka-and-1jhdic3y.pdf

Integrated Analysis of Transcriptome Data Revealed AURKA and KIF20A as Critical Genes in Medulloblastoma Progression

Colon adenocarcinoma (COAD) is among the most common digestive system malignancies worldwide, and its pathogenesis and gene signatures remain unclear. This study explored the genetic characteristics and molecular mechanisms underlying colon cancer development. Three gene expression data sets were obtained from the Gene Expression Omnibus (GEO) database. GEO2R was used to determine differentially expressed genes (DEGs) between COAD and normal tissues. Then, the intersection of the data sets was obtained. Metascape was used to perform the functional enrichment analyses. Next, STRING was used to build protein-protein interaction (PPI) networks. Hub genes were identified and analysed using Cytoscape. Next, survival analysis and expression analysis of the hub genes were performed. ROC curve analysis was performed for further test of the diagnostic efficacy. Finally, alterations in the hub genes were predicted and analysed by cBioPortal. Altogether, 436 DEGs were detected. The DEGs were mainly enriched in cell cycle phase transition, nuclear division, meiotic nuclear division, and cytokinesis. Based on PPI networks, 20 hub genes were selected. Among them, 6 hub genes (CCNB1, CCNA2, AURKA, NCAPG, DLGAP5, and CENPE) showed significant prognostic value in colon cancer (P < 0.05), while 5 hub genes (CDK1, CCNB1, CCNA2, MAD2L1, and DLGAP5) were associated with early colon cancer diagnosis and ROC curve analysis showed good diagnostic accuracy. In conclusion, integrated bioinformatics analysis was used to identify hub genes that reveal the potential mechanism of carcinogenesis and progression of colon cancer. The hub genes might be novel biomarkers for early diagnosis, treatment, and prognosis of colon cancer.

/pdf/identification-of-hub-genes-for-early-diagnosis-and-1ritgvd0.pdf

Identification of Hub Genes for Early Diagnosis and Predicting Prognosis in Colon Adenocarcinoma

Cancer stem cells (CSC) play one of the crucial roles in the pathogenesis of various cancers, including colorectal cancer (CRC). Although great efforts have been made regarding our understanding of the cancerogenesis of CRC, CSC involvement in CRC development is still poorly understood. Using bioinformatics and RNA-seq data of normal mucosa, colorectal adenoma, and carcinoma (n = 106) from GEO and TCGA, we identified candidate CSC genes and analyzed pathway enrichment analysis (PEI) and protein–protein interaction analysis (PPI). Identified CSC-related genes were validated using qPCR and tissue samples from 47 patients with adenoma, adenoma with early carcinoma, and carcinoma without and with lymph node metastasis and were compared to normal mucosa. Six CSC-related genes were identified: ANLN, CDK1, ECT2, PDGFD, TNC, and TNXB. ANLN, CDK1, ECT2, and TNC were differentially expressed between adenoma and adenoma with early carcinoma. TNC was differentially expressed in CRC without lymph node metastases whereas ANLN, CDK1, and PDGFD were differentially expressed in CRC with lymph node metastases compared to normal mucosa. ANLN and PDGFD were differentially expressed between carcinoma without and with lymph node metastasis. Our study identified and validated CSC-related genes that might be involved in early stages of CRC development (ANLN, CDK1, ECT2, TNC) and in development of metastasis (ANLN, PDGFD).

/pdf/bioinformatics-analysis-of-rna-seq-data-reveals-genes-gvqaq0za.pdf

Bioinformatics Analysis of RNA-seq Data Reveals Genes Related to Cancer Stem Cells in Colorectal Cancerogenesis

Microsatellite instability states serve as predictive biomarkers for tumors chemotherapy sensitivity

The Aurora Kinase family (AKI) is composed of serine-threonine protein kinases involved in the modulation of the cell cycle and mitosis. These kinases are required for regulating the adherence of hereditary-related data. Members of this family can be categorized into aurora kinase A (Ark-A), aurora kinase B (Ark-B), and aurora kinase C (Ark-C), consisting of highly conserved threonine protein kinases. These kinases can modulate cell processes such as spindle assembly, checkpoint pathway, and cytokinesis during cell division. The main aim of this review is to explore recent updates on the oncogenic signaling of aurora kinases in chemosensitive/chemoresistant cancers and to explore the various medicinal chemistry approaches to target these kinases. We searched Pubmed, Scopus, NLM, Pubchem, and Relemed to obtain information pertinent to the updated signaling role of aurora kinases and medicinal chemistry approaches and discussed the recently updated roles of each aurora kinases and their downstream signaling cascades in the progression of several chemosensitive/chemoresistant cancers; subsequently, we discussed the natural products (scoulerine, Corynoline, Hesperidin Jadomycin-B, fisetin), and synthetic, medicinal chemistry molecules as aurora kinase inhibitors (AKIs). Several natural products' efficacy was explained as AKIs in chemosensitization and chemoresistant cancers. For instance, novel triazole molecules have been used against gastric cancer, whereas cyanopyridines are used against colorectal cancer and trifluoroacetate derivatives could be used for esophageal cancer. Furthermore, quinolone hydrazine derivatives can be used to target breast cancer and cervical cancer. In contrast, the indole derivatives can be preferred to target oral cancer whereas thiosemicarbazone-indole could be used against prostate cancer, as reported in an earlier investigation against cancerous cells. Moreover, these chemical derivatives can be examined as AKIs through preclinical studies. In addition, the synthesis of novel AKIs through these medicinal chemistry substrates in the laboratory using in silico and synthetic routes could be beneficial to develop prospective novel AKIs to target chemoresistant cancers. This study is beneficial to oncologists, chemists, and medicinal chemists to explore novel chemical moiety synthesis to target specifically the peptide sequences of aurora kinases in several chemoresistant cancer cell types.

Recent Updates on Oncogenic Signaling of Aurora Kinases in Chemosensitive, Chemoresistant Cancers: Novel Medicinal Chemistry Approaches for Targeting Aurora Kinases.

AURKA, a cell cycle-regulated kinase, is associated with malignant transformation and progression in many cancer types. We analyzed the expression change of AURKA in pan-cancer and its effect on the prognosis of cancer patients using the TCGA dataset. We revealed that AURKA was extensively elevated and predicted a poor prognosis in most of the detected cancer types, with an exception in colon cancer. AURKA was elevated in colon cancer, but the upregulation of AURKA indicated better outcomes of colon cancer patients. Then we revealed that undermethylation of the AURKA gene and several transcription factors contributed to the upregulation of AURKA in colon cancer. Moreover, we demonstrated that AURKA overexpression promoted the death of colon cancer cells induced by Oxaliplatin, whereas knockdown of AURKA significantly weakened the chemosensitivity of colon cancer cells to Oxaliplatin. Mechanistically, AURKA inhibited DNA damage response by suppressing the expression of various DNA damage repair genes in a TP53-dependent manner, which can partly explain that ARUKA is associated with a beneficial outcome of colon cancer. This study provided a possibility to use AURKA as a biomarker to predict the chemosensitivity of colon cancer to platinum in the clinic.

/pdf/aurka-increase-the-chemosensitivity-of-colon-cancer-cells-to-3mapepctpp.pdf

AURKA Increase the Chemosensitivity of Colon Cancer Cells to Oxaliplatin by Inhibiting the TP53-Mediated DNA Damage Response Genes.

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AURKA Increase the Chemosensitivity of Colon Cancer Cells to Oxaliplatin by Inhibiting the TP53-Mediated DNA Damage Response Genes.