Identification of key genes affecting disease free survival time of pediatric acute lymphoblastic leukemia based on bioinformatic analysis

Synthesis, anti-leukemia activity, and molecular docking of novel 3,16-androstenedione derivatives

In this study, we synthesized androsta-4,14-diene-3,16-dione, 12β-hydroxyandrosta-4,14-diene-3,16-dione, and other 3,16-androstenedione derivatives from commercially available dehydroepiandrosterone as a starting material in 9-13 steps with high yields. The bioactivity of the obtained compounds was evaluated. Compounds 14a and 23a were shown to have high antitumor activity against acute lymphoblastic leukemia cell lines Nalm-6 and BALL-1, respectively. Network pharmacology analysis showed that the anti-leukemia activity of compounds 14a and 23a might be related to the JAK2, ABL1 protein, and PI3K/Akt signaling pathways. The molecular docking of compounds 14a and 23a identified possible active sites, with the lowest docking scores for PTGS2 and MAPK14, respectively. In addition, the absorption, distribution, metabolism, and excretion prediction results revealed the drug-likeness of the two compounds. Therefore, compounds 14a and 23a should be considered anti-leukemia candidates in future studies.

Kynureninase knockdown inhibits cisplatin resistance in vivo and in vitro and impacts the prognosis of cervical adenocarcinoma

BACKGROUND

Chemotherapy resistance is a leading cause of treatment failure in cases of cervical adenocarcinoma (ADC), and no effective treatment approach has yet been found. We previously identified the differentially expressed kynureninase (KYNU) mRNA in cervical adenocarcinoma cells (HeLa) and cervical adenocarcinoma cisplatin resistance cells (HeLa/DDP) using gene chips. However, the role and potential mechanism of KYNU in the cisplatin resistance of cervical adenocarcinoma remain unclear.

METHODS

We verified the expression of KYNU in the cells and tissues of ADC patients and analyzed its correlation with patient prognosis. A stable HeLa/DDP cell line with KYNU mRNA knockdown was constructed. We then used a CCK8 assay to detect cell survival, a transwell assay to evaluate cell migration and proliferation and flow cytometry to measure apoptosis. The effect of KYNU silence on cisplatin sensitivity was evaluated in an orthotopic model of metastatic ADC. Immunohistochemistry was performed to determine the changes in relevant drug resistance-associated protein expression, aiming to explore the underlying mechanism of KYNU-mediated drug resistance.

RESULTS

KYNU is overexpressed in HeLa/DDP cells and tissues and is associated with the poor prognoses of patients with ADC. After KYNU mRNA knockdown, the invasion, migration, and proliferation of HeLa/DDP cells in the cisplatin environment significantly reduced, while the apoptosis rate of HeLa/DDP cells significantly increased. Meanwhile, KYNU knockdown improved the DDP sensitivity of ADC in vivo. Furthermore, silencing KYNU decreased the expressions of CD34 and the drug-resistance related proteins P-gp, MRP1, and GST-π and increased the level of the proapoptotic regulatory protein Bax.

CONCLUSION

KYNU deficiency enhanced DDP sensitivity by suppressing cell proliferation, migration, and invasion and promoting apoptosis in DDP-resistant ADC cells in vitro. Furthermore, KYNU knockdown improved the drug sensitivity of ADC in vivo. The results showed that KYNU is involved in the chemotherapy resistance of cervical adenocarcinoma.

Aiding Cancer's "Sweet Tooth": Role of Hexokinases in Metabolic Reprogramming

Hexokinases (HKs) convert hexose sugars to hexose-6-phosphate, thus trapping them inside cells to meet the synthetic and energetic demands. HKs participate in various standard and altered physiological processes, including cancer, primarily through the reprogramming of cellular metabolism. Four canonical HKs have been identified with different expression patterns across tissues. HKs 1-3 play a role in glucose utilization, whereas HK 4 (glucokinase, GCK) also acts as a glucose sensor. Recently, a novel fifth HK, hexokinase domain containing 1 (HKDC1), has been identified, which plays a role in whole-body glucose utilization and insulin sensitivity. Beyond the metabolic functions, HKDC1 is differentially expressed in many forms of human cancer. This review focuses on the role of HKs, particularly HKDC1, in metabolic reprogramming and cancer progression.

HNMT Upregulation Induces Cancer Stem Cell Formation and Confers Protection against Oxidative Stress through Interaction with HER2 in Non-Small-Cell Lung Cancer

Background: The treatment of non-small-cell lung cancer (NSCLC) involves platinum-based chemotherapy. It is typically accompanied by chemoresistance resulting from antioxidant properties conferred by cancer stem cells (CSCs). Human epidermal growth factor receptor 2 (HER2) enhances CSCs and antioxidant properties in cancers, including NSCLC. Methods: Here, we elucidated the role of histamine N-methyltransferase (HNMT), a histamine metabolism enzyme significantly upregulated in NSCLC and coexpressed with HER2. HNMT expression in lung cancer tissues was determined using quantitative reverse transcription PCR (RT-qPCR). A publicly available dataset was used to determine HNMT’s potential as an NSCLC target molecule. Immunohistochemistry and coimmunoprecipitation were used to determine HNMT–HER2 correlations and interactions, respectively. HNMT shRNA and overexpression plasmids were used to explore HNMT functions in vitro and in vivo. We also examined miRNAs that may target HNMT and investigated HNMT/HER2’s role on NSCLC cells’ antioxidant properties. Finally, how HNMT loss affects NSCLC cells’ sensitivity to cisplatin was investigated. Results: HNMT was significantly upregulated in human NSCLC tissues, conferred a worse prognosis, and was coexpressed with HER2. HNMT depletion and overexpression respectively decreased and increased cell proliferation, colony formation, tumorsphere formation, and CSCs marker expression. Coimmunoprecipitation analysis indicated that HNMT directly interacts with HER2. TARGETSCAN analysis revealed that HNMT is a miR-223 and miR-3065-5p target. TBHp treatment increased HER2 expression, whereas shHNMT disrupted the Nuclear factor erythroid 2-related factor 2 (Nrf2)/ hemeoxygenase-1 (HO-1)/HER2 axis and increased reactive oxygen species accumulation in NSCLC cells. Finally, shHNMT sensitized H441 cells to cisplatin treatment in vitro and in vivo. Conclusions: Therefore, HNMT upregulation in NSCLC cells may upregulate HER2 expression, increasing tumorigenicity and chemoresistance through CSCs maintenance and antioxidant properties. This newly discovered regulatory axis may aid in retarding NSCLC progression and chemoresistance.

Glycolysis-Related Genes Serve as Potential Prognostic Biomarkers in Clear Cell Renal Cell Carcinoma

Metabolic rearrangement is a marker of cancer that has been widely studied in recent years. One of the major metabolic characteristics of tumor cells is the high levels of glycolysis, even under aerobic conditions, a phenomenon that is called the "Warburg effect." We investigated the expression and copy number variation (CNV) frequency of all glycolysis-related genes in multiple cancer types and found many differentially expressed genes, particularly in clear cell renal cell carcinoma (ccRCC). Single nucleotide variants (SNVs) showed that the overall average mutation frequency for all genes was low. The purpose of this study was to establish a predictive model by studying glycolysis-related genes in ccRCC. We compared the expression of glycolysis-related genes in 539 ccRCC tissues and 72 normal renal tissues from The Cancer Genome Atlas dataset and identified 17 upregulated and 26 downregulated genes. Pathway analysis revealed that PSAT1 and SDHB could activate the cell cycle, RPIA could activate the DNA damage response, and HK3 could activate apoptosis and EMT signaling, while PDK2 could inhibit apoptosis. The results of the drug sensitivity analysis suggested that some of these differentially expressed genes were positively correlated with drug sensitivity. Thirteen genes were selected from the gene coexpression network and the LASSO regression analysis. The Kaplan-Meier overall survival curves showed that the expression of upregulated genes in ccRCC patients was associated with lower overall survival. We established a predictive model consisting of 13 genes (RPIA, G6PD, PSAT1, ENO2, HK3, IDH1, PDK4, PGM2, PGK1, FBP1, OGDH, SUCLA2, and SUCLG2). This predictive model correlated well with the development and progression of ccRCC. Thus, it is of great value in the diagnosis and prognostic evaluation of ccRCC and may aid the identification of potential prognostic biomarkers and drug targets.

Repurposing Drugs by In Silico Methods to Target BCR Kinase Domain in Chronic Myeloid Leukemia

BACKGROUND

Targeted therapy in the form of highly selective tyrosine kinase inhibitors (TKIs) has transformed the treatment of chronic myeloid leukemia (CML). However, mutations in the kinase domain contribute to drug resistance against TKIs which compromises the treatment response. Our aim is to explore regions outside the BCR-ABL oncoprotein to identify potential therapeutic targets to curb drug resistance by targeting growth factor receptor-bound protein-2 (Grb-2) which binds to BCR-ABL at the phosphorylated tyrosine (Y177) thereby activating the Ras and PI3K/AKT signaling pathway.

METHODS

We have used in silico methods to repurpose drugs for identifying their potential to inhibit the binding of Grb-2 with Y177 by occupying the active binding site of the BCR domain.

RESULTS

Differentially expressed genes from GEO dataset were found to be associated with hematopoietic cell lineage, NK cell-mediated cytotoxicity, NF-κB and chemokine signaling, cytokine-cytokine receptor interaction, histidine metabolism and transcriptional misregulation in cancer. The fold recognition method of SPARKS-X tool was used to model the BCR domain (Z-score = 8.21). Connectivity Map generated a drug list based on the gene expression profile, which were docked with BCR. Schrodinger XP glide docking identified Diphosphopyridine nucleotide, Hesperidin, Butirosin, Ovoflavin, and Nor-dihydroguaiaretic acid to show strong interaction in close proximity to the active binding pocket containing Y177 of the target protein and was further validated using iGEMDOCK and Parallelized Open Babel and AutoDock suite Pipeline (POAP).

CONCLUSION

Our study not only extends our current knowledge about repurposing drugs for newer indications but also provides a route towards combinatorial therapy with standard drugs used for CML treatment. However, the efficacy of these repurposed drugs needs to be further investigated using in vitro and in vivo studies.<br />.

Identifying new targets in leukemogenesis using computational approaches

There is a need to identify novel targets in Acute Lymphoblastic Leukemia (ALL), a hematopoietic cancer affecting children, to improve our understanding of disease biology and that can be used for developing new therapeutics. Hence, the aim of our study was to find new genes as targets using in silico studies; for this we retrieved the top 10% overexpressed genes from Oncomine public domain microarray expression database; 530 overexpressed genes were short-listed from Oncomine database. Then, using prioritization tools such as ENDEAVOUR, DIR and TOPPGene online tools, we found fifty-four genes common to the three prioritization tools which formed our candidate leukemogenic genes for this study. As per the protocol we selected thirty training genes from PubMed. The prioritized and training genes were then used to construct STRING functional association network, which was further analyzed using cytoHubba hub analysis tool to investigate new genes which could form drug targets in leukemia. Analysis of the STRING protein network built from these prioritized and training genes led to identification of two hub genes, SMAD2 and CDK9, which were not implicated in leukemogenesis earlier. Filtering out from several hundred genes in the network we also found MEN1, HDAC1 and LCK genes, which re-emphasized the important role of these genes in leukemogenesis. This is the first report on these five additional signature genes in leukemogenesis. We propose these as new targets for developing novel therapeutics and also as biomarkers in leukemogenesis, which could be important for prognosis and diagnosis.

Application of oncoproteomics to aberrant signalling networks in changing the treatment paradigm in acute lymphoblastic leukaemia

Oncoproteomics is an important innovation in the early diagnosis, management and development of personalized treatment of acute lymphoblastic leukaemia (ALL). As inherent factors are not completely known - e.g. age or family history, radiation exposure, benzene chemical exposure, certain viral exposures such as infection with the human T-cell lymphoma/leukaemia virus-1, as well as some inherited syndromes may raise the risk of ALL - each ALL patient may modify the susceptibility of therapy. Indeed, we consider these unknown inherent factors could be explained via coupling cytogenetics plus proteomics, especially when proteins are the ones which play function within cells. Innovative proteomics to ALL therapy may help to understand the mechanism of drug resistance and toxicities, which in turn will provide some leads to improve ALL management. Most important of these are shotgun proteomic strategies to unravel ALL aberrant signalling networks. Some shotgun proteomic innovations and bioinformatic tools for ALL therapies will be discussed. As network proteins are distinctive characteristics for ALL patients, unrevealed by cytogenetics, those network proteins are currently an important source of novel therapeutic targets that emerge from shotgun proteomics. Indeed, ALL evolution can be studied for each individual patient via oncoproteomics.