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An unbounded number of events exist beneath the intricacy of each particular hematologic malignancy, prompting the tumor cells into an unrestrained proliferation and invasion. Aberrant expression of cyclin-dependent kinases (CDKs) is one of these events which disrupts the regulation of cell cycle and subsequently, results in cancer progression. In this study, we surveyed the repressive impact of multi-CDK inhibitor AT7519 on a panel of leukemia-derived cell lines. Our data underlined that AT7519 abated the survival of all tested cells; however, in an overview, the response rate of leukemic cells to the inhibitor was varied irrespective of p53 status. Notably, the less sensitivity of leukemia cells to AT7519 was found to be mediated partly by the compensatory activation of c-Myc oncogene which was confirmed by the induction of a superior cytotoxicity upon its suppression in less sensitive cell. The blockage of cell cycle, as announced by induction of sub-G1 arrest as well as reduced S phase, resulted in a significant decrease in survival of acute promyelocytic leukemia (APL)-derived NB4 cells, as the most sensitive cell line, either as monotherapy or in combination with arsenic trioxide. Anti-leukemic effects of the inhibitor were further verified by apoptosis analysis, where we discovered that AT7519 induced apoptosis via alteration of pro- and anti-apoptotic genes in NB4. All in all, this study proposed that AT7519 is a rewarding agent opposed to APL; however, additional examinations should be performed to determine the advantages of this inhibitor in clinical setting.

Aim: The present study aims to evaluate the prognostic value of liver-related laboratory parameters in COVID-19. Background: This is not the first nor will it be the last time that a member of the β-coronaviruses wages a full-scale war against human health. Notwithstanding atypical pneumonia being the primary symptom, the emergence of severe disease mainly resulting from the injury of non-pulmonary organs leaves no alternative, in some cases, other than a dreadful death. Methods: To provide a well-conceptualized viewpoint representing the prognostic values of liver-related laboratory parameters in COVID-19, a meta-analysis was performed with the calculation of mean difference and 95% confidence intervals of alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin (Bili), and albumin (Alb) in severe and non-severe COVID-19 patients. Results: While severe COVID-19 cases displayed higher values of ALT, AST, and Bili compared to non-severe patients (mean differences of 7.48, 12.07, and 3.07, respectively), the value of Alb was significantly lower in severe cases (mean differences of -6.15). There was also a correlation between alterations in all of the parameters; however, only correlations between ALT and Bili (R=0.98, p=0.0031), and Bili and Alb (R=-1, p=0.0012) were significant. Conclusion: Abnormal values of liver-related examinations outwardly contribute to reflect the progression of the disease toward an unfavorable outcome. Therefore, careful scrutiny of these parameters will provide clinicians with invaluable information regarding SARS-CoV-2 infection, at least in terms of liver injury.

Due to the frequent contribution in the pathogenesis of different human malignancies, c-Myc is among those transcription factors that are believed to be pharmacologically targeted for cancer therapeutic approaches. In the present study, we examined the anti-leukemic effect of a well-known c-Myc inhibitor 10058-F4 on a panel of hematologic malignant cells harboring either mutant or wild-type p53. Notably, we found that the suppression of c-Myc was coupled with the reduction in the survival of all the tested leukemic cells; however, as far as we are aware, this study suggests for the first time that the cytotoxic effect of 10058-F4 was not significantly affected by the molecular status of p53. Delving into the molecular mechanisms of the inhibitor in the most sensitive cell line revealed that 10058-F4 could induce apoptotic cell death in mutant p53-expressing NB4 cells through the suppression of NF-κB pathway coupled with a significant induction of intracellular reactive oxygen species (ROS). In addition, we found that the anti-leukemic effect of 10058-F4 was overshadowed, at least partially, through the compensatory activation of the PI3K signaling pathway; highlighting a plausible attenuating role of this axis on 10058-F4 cytotoxicity. In conclusion, the results of the present study shed light on the favorable anti-leukemic effect of 10058-F4, especially in combination with PI3K inhibitors in acute promyelocytic leukemia; however, further investigations should be accomplished to determine the efficacy of the inhibitor, either as a single agent or in a combined-modal strategy, in leukemia treatment.

Introduction. The early detection and diagnosis of leukemia, i.e., the precise differentiation of malignant leukocytes with minimum costs in the early stages of the disease, is a major problem in the domain of disease diagnosis. Despite the high prevalence of leukemia, there is a shortage of flow cytometry equipment, and the methods available at laboratory diagnostic centers are time-consuming. Motivated by the capabilities of machine learning (machine learning (ML)) in disease diagnosis, the present systematic review was conducted to review the studies aiming to discover and classify leukemia by using machine learning. Methods. A systematic search in four databases (PubMed, Scopus, Web of Science, and ScienceDirect) and Google Scholar was performed via a search strategy using Machine Learning (ML), leukemia, peripheral blood smear (PBS) image, detection, diagnosis, and classification as the keywords. Initially, 116 articles were retrieved. After applying the inclusion and exclusion criteria, 16 articles remained as the population of the study. Results. This review study presents a comprehensive and systematic view of the status of all published ML-based leukemia detection and classification models that process PBS images. The average accuracy of the ML methods applied in PBS image analysis to detect leukemia was >97%, indicating that the use of ML could lead to extraordinary outcomes in leukemia detection from PBS images. Among all ML techniques, deep learning (DL) achieved higher precision and sensitivity in detecting different cases of leukemia, compared to its precedents. ML has many applications in analyzing different types of leukemia images, but the use of ML algorithms to detect acute lymphoblastic leukemia (ALL) has attracted the greatest attention in the fields of hematology and artificial intelligence. Conclusion. Using the ML method to process leukemia smear images can improve accuracy, reduce diagnosis time, and provide faster, cheaper, and safer diagnostic services. In addition to the current diagnostic methods, clinical and laboratory experts can also adopt ML methods in laboratory applications and tools.

Shahrzad Soleymani Fard,1 Mansour Yazdanbod,2 Masoud Sotoudeh,3 Davood Bashash,4 Habibollah Mahmoodzadeh,5 Kioomars Saliminejad,1 Seyed Asadollah Mousavi,1 Seyed H Ghaffari,1 Kamran Alimoghaddam1 1Hematology, Oncology and Stem Cell Transplantation Research Institute, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran; 2Department of Surgery, Madaen Hospital, Tehran, Iran; 3Digestive Oncology Research Center, Digestive Diseases Research Institute, Tehran University of Medical Sciences, Tehran, Iran; 4Department of Hematology and Blood Banking, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran; 5Department of Surgical Oncology, Cancer Institute, Imam Khomeini Hospital Complex, Tehran University of Medical Sciences, Tehran, IranCorrespondence: Kamran Alimoghaddam; Seyed H Ghaffari Hematology, Oncology and Stem Cell Transplantation Research Institute, Shariati Hospital, School of MedicineTehran University of Medical Sciences, North Kargar Avenue, Tehran, IranTel +982184902665Fax +982188004140Email alimgh@tums.ac.ir; shghaffari200@yahoo.comPurpose: The clinical studies carried out in the last few decades unequivocally introduced activated androgen receptor (AR) as a pathogenic feature of human malignancies which not only endows cancer cells with survival advantage, but also may be exploited for anticancer interventions.Patients and Methods: In this study, we have investigated the expression profile of AR and EMT-related genes in fresh gastric cancer (GC), adjacent nontumor and normal gastric tissues, as well as the effect and molecular mechanisms of AR inhibition in GC cell lines.Results: Amongst 60 GC patients, 66.7% overexpressed AR that was remarkably correlated with the overexpression of Snail, β-catenin, Twist1, and STAT3. AR overexpression was also remarkably associated with unfavorable outcome (HR=3.478, P=0.001); however, multivariate Cox regression analysis indicated that it was not an independent prognostic factor (HR=2.089, P=0.056). This study has investigated simultaneous assessment of AR and EMT-related genes expression and indicated that concurrent overexpression of AR and Snail is an independent unfavorable factor for GC overall survival after adjustment with other variables (HR=2.382, P=0.021). Interestingly, the inhibition of AR signaling by potent AR antagonist enzalutamide suppressed cell growth, migration and invasion of GC cells via regulation of apoptosis-, cell cycle-, and EMT-related gene expressions.Conclusion: Our findings have clinical importance proposing AR as an important prognostic factor involved in GC progression and metastasis, and submit AR inhibition as an appealing therapeutic approach for GC patients, either as a single agent or in a combined-modal strategy.Keywords: androgen receptor, gastric cancer, epithelial-mesenchymal transition, EMT, prognosis, targeted therapy, enzalutamide

Despite impressive advances in therapeutic approaches, long-term survival with acute myeloid leukemia (AML) is low as a result of treatment resistance and frequent relapse. Among multitude oncogenic proteins involved in the acquisition of a chemo-resistant phenotype, osteopontin (OPN) recently has attracted marked attention. In spite of the well-defined association between OPN expression and cure rate with solid tumors, there is a scarcity of information on any role of this protein in AML cases. Based on the critical role of OPN in cell survival, it seems reasonable to hypothesize that isoform expression levels may impact on the regulation of apoptosis in AML cells in response to conventional chemotherapeutic drugs and its relation to relapse. To investigate associations between induction of apoptosis and OPN isoform expression, two distinct AML cell lines (KG-1 as a leukemic stem cell model and U937) were treated with chemotherapy drugs, and cell viability and apoptosis were evaluated by MTT and Annexin/PI assay. After determination of appropriate drug doses, mRNA expression levels of OPN isoforms and OPN-related genes were investigated. Our results demonstrated for the first time that acquired up-regulation of OPN-b and c isoforms might prevent conventional chemotherapy regimen-induced apoptosis in AML cells. Moreover, upregulation of OPN-b and c in AML cells appears concurrent with upregulation of AKT/VEGF/CXCR4/STAT3/ IL-6 gene expression. To sum up, this study suggests that OPN-b and c isoforms could be considered as unique beneficial molecular biomarkers associated with leukemic stem cell chemoresistance. Hence, they have potential as molecular candidates for detection of minimal residual disease (MRD) and determination of remission in AML patients. Further evaluation with quantitative real time PCR on patient samples for confirmation appears warranted.