Identification of Novel Genes and Pathways of Ovarian Cancer Using a Comprehensive Bioinformatic Framework.

Ovarian cancer (OC) is a significant contributor to gynecological cancer-related deaths worldwide, with a high mortality rate. Despite several advances in understanding the pathogenesis of OC, the molecular mechanisms underlying its development and prognosis remain poorly understood. Therefore, the current research study aimed to identify hub genes involved in the pathogenesis of OC that could serve as selective diagnostic and therapeutic targets. To achieve this, the dataset GEO2R was used to retrieve differentially expressed genes. The study identified a total of five genes (CDKN1A, DKK1, CYP1B1, NTS, and GDF15) that were differentially expressed in OC. Subsequently, a network analysis was performed using the STRING database, followed by the construction of a network using Cytoscape. The network analyzer tool in Cytoscape predicted 276 upregulated and 269 downregulated genes. Furthermore, KEGG analysis was conducted to identify different pathways related to OC. Subsequently, survival analysis was performed to validate gene expression alterations and predict hub genes, using a p-value of 0.05 as a threshold. Four genes (CDKN1A, DKK1, CYP1B1, and NTS) were predicted as significant hub genes, while one gene (GDF15) was predicted as non-significant. The adjusted P values of said predicted genes are 2.85E - 07, 5.49E - 06, 4.28E - 07, 1.43E - 07, and 3.70E - 07 for CDKN1A, DKK1, NTS, GDF15, and CYP1B1 respectively; additionally 6.08, 5.76, 5.74, 5.01, and 4.9 LogFc values of the said genes were predicted in GEO data set. In a boxplot analysis, the expression of these genes was analyzed in normal and tumor cells. The study found that three genes were highly expressed in tumor cells, while two genes (CDKN1A and DKK1) were more elevated in normal cells. According to the boxplot analysis for CDKN1A, 50% of tumor cells ranged between approx 3.8 and 5, while 50% of normal cells ranged between approx 6.9 and 7.9, which is greater than tumor cells. This shows that in normal cells, the CYP1B1 has a high expression level according to the GEPIA boxplot; addtionally the boxplot for DKK1 indicated that 50% of tumor cells ranged between approx 0 and 0.5, which was less than that of normal cells which ranged between approx 0.3 and 0.9. It shows that DKK1 is highly expressed in normal genes. Overall, the current study provides novel insights into the molecular mechanisms underlying OC. The identified hub genes and drug candidate targets could potentially serve as alternative diagnostic and therapeutic options for OC patients. Further research is needed to investigate the clinical significance of these findings and develop effective interventions that can improve the prognosis of patients with OC.

Expression of CD22 in Triple-Negative Breast Cancer: A Novel Prognostic Biomarker and Potential Target for CAR Therapy.

Triple-negative breast cancer (TNBC) accounts for 15-20% of all breast cancer cases. Due to the lack of expression of well-known molecular targets [estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2)], there is a need for more alternative treatment approaches in TNBC. Chimeric antigen receptor (CAR)-T cell-based immunotherapy treatment is one of the latest treatment technologies with outstanding therapeutic advances in the past decade, especially in the treatment of hematologic malignancies, but the therapeutic effects of CAR-T cells against solid tumors have not yet shown significant clinical benefits. Identification of highly specific CAR-T targets in solid tumors is also crucial for its successful treatment. CD22 is reported to be a multifunctional receptor that is mainly expressed on the surface of mature B-cells (lymphocytes) and is also highly expressed in most B-cell malignancies. This study aimed to investigate the expression of CD22 in TNBC. Bioinformatic analysis was performed to evaluate the expression of CD22 in breast carcinoma and normal tissues. RNA-seq data of normal and breast carcinoma patients were downloaded from The Cancer Genome Atlas (TCGA), and differential gene expression was performed using R language. Additionally, online bioinformatics web tools (GEPIA and TNM plot) were used to evaluate the expression of CD22 in breast carcinoma and normal tissues. Western blot (WB) analysis and immunofluorescence (IF) were performed to characterize the expression of CD22 in TNBC cell lines. Immunohistochemical (IHC) staining was performed on tumor specimens from 97 TNBC patients for CD22 expression. Moreover, statistical analysis was performed to analyze the association of clinical pathological parameters with CD22 expression. Correlation analysis between overall survival data of TNBC patients and CD22 expression was also performed. Differential gene expression analysis of TCGA data revealed that CD22 is among the upregulated differentially expressed genes (DEGs) with high expression in breast cancer, as compared to normal breast tissues. WB and IF analysis revealed high expression of CD22 in TNBC cell lines. IHC results also showed that approximately 62.89% (61/97) of TNBC specimens were stained positive for CD22. Cell membrane expression of CD22 was evident in 23.71% (23/97) of TNBC specimens, and 39.18% (38/97) of TNBC specimens showed cytoplasmic/membrane expression, while 37.11% (36/97) specimens were negative for CD22. Furthermore, significant associations were found between the size of tumors in TNBC patients and CD22 expression, which unveils its potential as a prognostic biomarker. No significant correlation was found between the overall survival of TNBC patients and CD22 expression. In conclusion, we demonstrated for the first time that CD22 is highly expressed in TNBC. Based on our findings, we anticipated that CD22 could be used as a prognostic biomarker in TNBC, and it might be a potential CAR-T target in TNBC for whom few therapeutic options exist. However, more large-scale studies and clinical trials will ensure its potential usefulness as a CAR-T target in TNBC.

Recent Advances in Syndactyly: Basis, Current Status and Future Perspectives.

A comprehensive summary of recent knowledge in syndactyly (SD) is important for understanding the genetic etiology of SD and disease management. Thus, this review article provides background information on SD, as well as insights into phenotypic and genetic heterogeneity, newly identified gene mutations in various SD types, the role of HOXD13 in limb deformities, and recently introduced modern surgical techniques for SD. This article also proposes a procedure for genetic analysis to obtain a clearer genotype-phenotype correlation for SD in the future. We briefly describe the classification of non-syndromic SD based on variable phenotypes to explain different phenotypic features and mutations in the various genes responsible for the pathogenesis of different types of SD. We describe how different types of mutation in HOXD13 cause various types of SD, and how a mutation in HOXD13 could affect its interaction with other genes, which may be one of the reasons behind the differential phenotypes and incomplete penetrance. Furthermore, we also discuss some recently introduced modern surgical techniques, such as free skin grafting, improved flap techniques, and dermal fat grafting in combination with the Z-method incision, which have been successfully practiced clinically with no post-operative complications.