Current Pharmacogenomics and Personalized Medicine (Formerly Current Pharmacogenomics) - Volume 19, Issue 1, 2022

Background: Prostate Cancer (PCa) is a non-cutaneous malignancy in men, and Decipher being a genomic test, has gained increasing attention in estimating the risk of developing a recurrence or metastatic PCa disease in patients. Therefore, this study is focused on evaluating the association of Decipher score risk with recurrence of prostate cancer patients based on their medical, genetic predictors, and demographics (e.g., races) by conducting a systematic review. Moreover, the study has also assessed whether Decipher score risk can be a good predictor for prostate patients’ metastasis and prostate cancer-specific mortality in men and clinical decision-making regarding patient treatment recommendations. Methods: The research study has reviewed 74 research articles, and the systematic review results have been presented in the form of themes. The studies' review indicated that Decipher acts as a genomic metastasis signature to predict metastatic disease among patients and make better decisions about treating the disease. Moreover, this genomic test can also be used in conjunction with Magnetic Resonance Imaging (MRI) for identifying the lesions that may carry the biological potential for early metastases. Furthermore, this review also identified that treatment options for PCa might range from Adjuvant Radiation Treatment (ART) and Salvage Radiation Therapy (SRT) to Radical Prostatectomy (RP); however, the selection of treatment methodology depends upon the GC score and risk stratification. Results: The results further suggested that the occurrence of PCa is two folds greater among African-Americans (AA) men as compared to non-AA men. Thus, the increasing incidence of PCa among AA and discrimination within AA's health and socio-economic conditions plays a significant role in treating AA. In this scenario, the Decipher test score plays an essential role in making treatment decisions. Conclusion: To conclude, further trials are still required for validating the Decipher biomarkers, and scientists should enhance the decipher test ability to be run on a patient's blood samples instead of tumor tissue, which will help patients use decipher as a screening test at the asymptomatic level.

Background: To reduce the side effects of conventional chemotherapy drugs, new herbal remedies, such as alantolactone, can be used. Objective: We evaluated the association between stemness and EMT (Epithelial- Mesenchymal Transition) process in triple-negative breast cancer cells treated with alantolactone that targets STAT3. Methods: The MDA-MB-231 cell line was used as one of the triple-negative breast cancer cell lines. MTT assay was used to evaluate cell viability and alantolactone dose at threetime points of 24, 48, and 72 hours, and three doses, i.e., 1, 0.1, and 0.01 μM of alantolactone were used to evaluate cellular behavior in proliferative and invasion pathways, respectively. A scratch test was also performed to evaluate the invasive power of cancer cells. Real- time PCR was used to evaluate the expression of regular genes by cancerous cell proliferation, STAT3 NANOG, SOX-2, and E-cadherin metastasis. Results: It was observed that increasing the dose of alantolactone decreased proliferation and metastasis rate. The three doses selected for the cell culture study did not differ significantly from the control group regarding apoptosis-inducing abilities at desired time intervals. Expression of SOX-2, STAT3, and NANOG in the treated cells decreased with increasing dose of the alantolactone, whereas expression of E-cadherin was found to be increased. Conclusion: Alantolactone through the STAT3 signaling pathway affects the expression of E-cadherin, NANOG, and SOX2 genes, inhibiting the EMT process and subsequent stemness, and may potentially be used in therapeutics for cancer patients.

Background: After completing the human genome, the project has created opportunities to improve the diagnosis, prevention, and treatment of disease. However, the limitations in Health Professionals (HPs), genetic knowledge, technological resources, and a lack of scientific research prevent global genetic screening from being addressed. Objectives: The objective is to evaluate HPs’ knowledge, attitude, and future outlook toward neonatal genetic screening. Methods: The study was carried out in a cross-sectional survey. A simple random sampling technique was used to select health centers and healthcare professionals. Questionnaires were used to assess HPs knowledge, attitude, and future perspectives towards genetic disease screening. Results: Among the total of 384 HPs, 79.7% and 20.3% had good and poor knowledge on the basic idea of genetic screening, respectively. Similarly, 92.4% and 7.6% of HPs had good and poor knowledge, respectively, on the parental history of genetic disease. Besides, 68.8% and 31.3% of HPs had good and poor knowledge on the possibility of treating genetic diseases. Lastly, 81.3% and 18.5% of HPs had a positive and negative attitude towards genetic screening. Conclusion: The majority of HPs had good genetic knowledge and a positive attitude on the basic idea of genetic screening, parental history, and the possibility of treating genetic disease, respectively. However, the practice of genetic screening is not yet addressed in Ethiopia. Genetic HPs and non-genetic HPs have to encourage the concerned bodies, including the governmental system, to implement genetic screening in Ethiopia.

Background: The heterogeneity of some diseases, such as cancer, makes the decisions on therapeutic strategy very challenging. In this context, pathway analysis can support the identification of the best treatment and indeed prevent the issues arising from the trial and error process, in terms of best overall efficacy and lowest toxicity, ultimately saving time and resources. In a pathway, each gene is represented by a node and the pathway analysis can be performed using algorithms that interpolate data from different sources (i.e., sequencing, microarray, drug efficacy and interactions). Objective: The purpose of this study was to evaluate the effects of erbb2 amplification on HER2- positive breast cancer and to predict, with a pathway based computational approach, the efficacy of a therapy with Trastuzumab and Palbociclib, alone or in combination. Methods: One of the available and most integrated algorithms is PHENSIM that was used in this study to evaluate the gene dysregulations caused by the erbb2 amplification on its related pathways and the effects of Trastuzumab and Palbociclib on these deregulations. The effects have been estimated considering the drugs alone or in a combination therapy. Results: A reduction of the number of pro-proliferative signals has been observed for both drugs alone or in combination. Regarding genes involved in MAPK signaling pathway, a total of 69 nodes were activated by the erbb2 mutation. A simulated treatment with Palbociclib reduced the number of activated genes down to 60, while with Trastuzumab the activated nodes were only 53. The combined therapy revealed an intriguing result providing a significant and remarkable reduction of the activated genes from 69 to 33. Conclusion: These results let us hypothesize that there could be an increased efficacy giving the combination therapy to subjects with HER2 positive breast cancer. Finally, pathway analysis could be specifically used to design clinical trials predicting the efficacy of combination therapies or untested drugs on a specific disease.

Aim: This study aimed to discover the most effective anti-cancer medicine for cancer patients infected with SARS-CoV-2. Background: The correlation between TP53 and SARS-CoV-2 was examined using biomolecular networking analysis. Objective: Cancer patients with TP53 gene mutations are more likely to be infected with the SARS-CoV-2 virus since it is the most frequently mutated tumor suppressor gene in human cancer. The main goal of this study is to discover the most effective and efficient anti-cancer therapy for patients with SARS-CoV-2 infection. Materials and Methods: Topp gene analysis was used to prioritize candidate genes based on molecular function, biological process, and pathway analysis. Biomolecular networking was carried out using Cytoscape 2.8.2. The protein-protein interaction network was used to identify the functionally associated proteins. The protein-drug interaction network was used to observe the molecular therapeutic efficiency of drugs. The network was further analyzed using CytoHubba to find the hub nodes. The molecular docking was used to study the proteinligand interaction, and the protein-ligand complex was further evaluated through molecular dynamic simulation to determine its stability. Results: Functionally relevant genes were prioritized through Toppgene analysis. Using Cytohabba, it was found that the genes UBE2N, BRCA1, BARD1, TP53, and DPP4 had a high degree and centrality score. The drugs 5-fluorouracil, Methotrexate, Temozolomide, Favipiravir, and Levofloxacin have a substantial association with the hub protein, according to protein-drug interaction analysis. Finally, a docking study revealed that 5-fluorouracil has the highest connection value and stability compared to Methotrexate, Favipiravir, and Levofloxacin. Conclusion: The biomolecular networking study was used to discover the link between TP53 and SARS-CoV-2, and it was found that 5-fluorouracil had a higher affinity for binding to TP53 and its related genes, such as UBE2N, BRCA1, RARD1, and SARS-CoV-2 specific DPP4. For cancer patients with TP53 gene mutations and Covid-19 infection, this treatment is determined to be the most effective.