The Therapeutic Application of Hydrogen in Cancer: The Potential and Challenges

Hydrogen therapy has emerged as a possible approach for both preventing and treating cancer. Cancers are often associated with oxidative stress and chronic inflammation. Hydrogen, with its unique physiological functions and characteristics, exhibits antioxidant, anti-inflammatory, and anti-apoptotic properties, making it an attractive candidate for cancer treatment. Through its ability to mitigate oxidative damage, modulate inflammatory responses, and sustain cellular viability, hydrogen demonstrates significant potential in preventing cancer recurrence and improving treatment outcomes. Preclinical studies have shown the efficacy of hydrogen therapy in several cancer types, highlighting its ability to enhance the effectiveness of conventional treatments while reducing associated side effects. Furthermore, hydrogen therapy has been found to be safe and well-tolerated in clinical settings. Nonetheless, additional investigations are necessary to improve a comprehensive understanding of the mechanisms underlying hydrogen's therapeutic potential and refine the administration and dosage protocols. However, further clinical trials are still needed to explore its safety profile and capacity. In aggregate, hydrogen therapy represents an innovative and promising treatment for several malignancies.

Genetic Determinants of Response to Statins in Cardiovascular Diseases

Despite extensive efforts to identify patients with cardiovascular disease (CVD) who could most benefit from the treatment approach, patients vary in their benefit from therapy and propensity for adverse drug events. Genetic variability in individual responses to drugs (pharmacogenetics) is considered an essential determinant in responding to a drug. Thus, understanding these pharmacogenomic relationships has led to a substantial focus on mechanisms of disease and drug response. In turn, understanding the genomic and molecular bases of variables that might be involved in drug response is the main step in personalized medicine. There is a growing body of data evaluating drug-gene interactions in recent years, some of which have led to FDA recommendations and detection of markers to predict drug responses (e.g., genetic variant in VKORC1 and CYP2C9 genes for prediction of drug response in warfarin treatment). Also, statins are widely prescribed drugs for the prevention of CVD. Atorvastatin, fluvastatin, rosuvastatin, simvastatin, and lovastatin are the most common statins used to manage dyslipidemia. This review provides an overview of the current knowledge on the pharmacogenetics of statins, which are being used to treat cardiovascular diseases.

Colorectal Cancer Stem Cell Biomarkers: Biological Traits and Prognostic Insights

Due to self-renewal, differentiation, and limitless proliferation properties, Cancer Stem Cells (CSCs) increase the probability of tumor development. These cells are identified by using CSC markers, which are highly expressed proteins on the cell surface of CSCs. Recently, the therapeutic application of CSCs as novel biomarkers improved both the prognosis and diagnosis outcome of colorectal Cancer. In the present review, we focused on a specific panel of colorectal CSC markers, including LGR5, ALDH, CD166, CD133, and CD44, which offers a targeted and comprehensive analysis of their functions. The selection criteria for these markers cancer were based on their established significance in Colorectal Cancer (CRC) pathogenesis and clinical outcomes, providing novel insights into the CSC biology of CRC. Through this approach, we aim to elevate understanding and stimulate further research for developing effective diagnostic and therapeutic strategies in CRC.

The Potential Therapeutic Applications of CRISPR/Cas9 in Colorectal Cancer

The application of the CRISPR-associated nuclease 9 (Cas9) system in tumor studies has led to the discovery of several new treatment strategies for colorectal cancer (CRC), including the recognition of novel target genes, the construction of animal mass models, and the identification of genes related to chemotherapy resistance. CRISPR/Cas9 can be applied to genome therapy for CRC, particularly regarding molecular-targeted medicines and suppressors. This review summarizes some aspects of using CRISPR/- Cas9 in treating CRC. Further in-depth and systematic research is required to fully realize the potential of CRISPR/Cas9 in CRC treatment and integrate it into clinical practice.

The Application of Nanotechnological Therapeutic Platforms against Gynecological Cancers

Gynecological cancers (GCs), ovarian, cervical, and endometrial/uterine cancers, are often associated with poor outcomes. Despite the development of several therapeutic modalities against GCs, the effectiveness of the current therapeutic approaches is limited due to their side effects, low therapeutic index, short halflife, and resistance to therapy. To overcome these limitations, nano delivery-based approaches have been introduced with the potential of targeted delivery, reduced toxicity, controlled release, and improved bioavailability of various cargos. This review summarizes the application of different nanoplatforms, such as lipid-based, metal- based, and polymeric nanoparticles, to improve the chemo/radio treatments of GC. In the following work, the use of nanoformulated agents to fight GCs has been mentioned in various clinical trials. Although nanosystems have their own challenges, the knowledge highlighted in this article could provide deep insight into translations of NPs approaches to overcome GCs.

Vactosertib potently improves anti-tumor properties of 5-FU for colon cancer

BACKGROUND

Several studies have shown that the TGF-β signaling pathway plays a critical role in colorectal cancer (CRC) pathogenesis. The aim of the current study is to investigate the therapeutic potential of Vactosertib (EW-7197), a selective inhibitor of TGF-β receptor type I, either alone or in combination with the standard first-line chemotherapeutic treatment, 5-Fluorouracil (5-FU), in CRC progression in both cellular and animal models.

METHODS

Real-Time PCR, Zymography, enzyme-linked immunosorbent assay (ELISA), Hematoxylin and Eosin (H&E) tissue staining, and Flow cytometry techniques were applied to determine the anti-tumor properties of this novel TGF-β inhibitor in in vitro (CT-26 cell line) and in vivo (inbred BALB/C mice) samples.

RESULTS

Our findings showed that Vactosertib decreased cell proliferation and induced spheroid shrinkage. Moreover, this inhibitor suppressed the cell cycle and its administration either alone or in combination with 5-FU induced apoptosis by regulating the expression of p53 and BAX proteins. It also improved 5-FU anti-cancer effects by decreasing the tumor volume and weight, increasing tumor necrosis, and regulating tumor fibrosis and inflammation in an animal model. Vactosertib also enhanced the inhibitory effect of 5-FU on invasive behavior of CRC cells by upregulating the expression of E-cadherin and inhibiting MMP-9 enzymatic activity.

CONCLUSION

This study demonstrating the potent anti-tumor effects of Vactosertib against CRC progression. Our results clearly suggest that this inhibitor could be a promising agent reducing CRC tumor progression when administered either alone or in combination with standard treatment in CRC patients.

Breast cancer prediction using different machine learning methods applying multi factors

OBJECTIVE

Breast cancer (BC) is a multifactorial disease and is one of the most common cancers globally. This study aimed to compare different machine learning (ML) techniques to develop a comprehensive breast cancer risk prediction model based on features of various factors.

METHODS

The population sample contained 810 records (115 cancer patients and 695 healthy individuals). 45 attributes out of 85 were selected based on the opinion of experts. These selected attributes are in genetic, biochemical, biomarker, gender, demographic and pathological factors. 13 Machine learning models were trained with proposed attributes and coefficient of attributes and internal relationships were calculated.

RESULT

Compared to other methods random forest (RF) has higher performance (accuracy 99.26%, precision 99%, and area under the curve (AUC) 99%). The results of assessing the impact and correlation of variables using the RF method based on PCA indicated that pathology, biomarker, biochemistry, gene, and demographic factors with a coefficient of 0.35, 0.23, 0.15, 0.14, and 0.13 respectively, affected the risk of BC (r2 = 0.54).

CONCLUSION

Breast cancer has several risk factors. Medical experts use these risk factors for early diagnosis. Therefore, identifying related risk factors and their effect can increase the accuracy of diagnosis. Considering the broad features for predicting breast cancer leads to the development of a comprehensive prediction model. In this study, using RF technique a breast cancer prediction model with 99.3% accuracy was developed based on multifactorial features.

Prognostic value of primary tumor location in colorectal cancer: an updated meta-analysis

The clinical, histological, and molecular differences between right-sided colon cancer (RCC) and left-sided colon cancer (RCC) have received considerable attention. Over the past decade, many articles have been published concerning the association between primary tumor location (PTL) of colorectal cancer and survival outcomes. Therefore, there is a growing need for an updated meta-analysis integrating the outcomes of recent studies to determine the prognostic role of right vs left-sidedness of PTL in patients with colorectal cancer. We conducted a comprehensive database review using PubMed, SCOPUS, and Cochrane library databases from February 2016 to March 2023 for prospective or retrospective studies reporting data on overall survival (OS) and cancer-specific survival (CSS) of RCC compared with LCC. A total of 60 cohort studies comprising 1,494,445 patients were included in the meta-analysis. We demonstrated that RCC is associated with a significantly increased risk of death compared with LCC by 25% (hazard ratio (HR), 1.25; 95% confidence interval (CI), 1.19-1.31; I2 = 78.4%; Z = 43.68). Results showed that patients with RCC have a worse OS compared with LCC only in advanced stages (Stage III: HR, 1.275; 95% CI 1.16-1.4; P = 0.0002; I2 = 85.8%; Stage IV: HR, 1.34; 95% CI 1.25-1.44; P < 0.0001; I2 = 69.2%) but not in primary stages (Stage I/II: HR, 1.275; 95% CI 1.16-1.4; P = 0.0002; I2 = 85.8%). Moreover, a meta-analysis of 13 studies including 812,644 patients revealed that there is no significant difference in CSS between RCC and LCC (HR, 1.121; 95% CI 0.97-1.3; P = 0.112). Findings from the present meta-analysis highlight the importance of PTL in clinical decision-making for patients with CRC, especially in advanced stages. We provide further evidence supporting the hypothesis that RCC and LCC are distinct disease entities that should be managed differently.

Bioinformatics analysis and machine learning approach applied to the identification of novel key genes involved in non-alcoholic fatty liver disease

Non-alcoholic fatty liver disease (NAFLD) comprises a range of chronic liver diseases that result from the accumulation of excess triglycerides in the liver, and which, in its early phases, is categorized NAFLD, or hepato-steatosis with pure fatty liver. The mortality rate of non-alcoholic steatohepatitis (NASH) is more than NAFLD; therefore, diagnosing the disease in its early stages may decrease liver damage and increase the survival rate. In the current study, we screened the gene expression data of NAFLD patients and control samples from the public dataset GEO to detect DEGs. Then, the correlation betweenbetween the top selected DEGs and clinical data was evaluated. In the present study, two GEO datasets (GSE48452, GSE126848) were downloaded. The dysregulated expressed genes (DEGs) were identified by machine learning methods (Penalize regression models). Then, the shared DEGs between the two training datasets were validated using validation datasets. ROC-curve analysis was used to identify diagnostic markers. R software analyzed the interactions between DEGs, clinical data, and fatty liver. Ten novel genes, including ABCF1, SART3, APC5, NONO, KAT7, ZPR1, RABGAP1, SLC7A8, SPAG9, and KAT6A were found to have a differential expression between NAFLD and healthy individuals. Based on validation results and ROC analysis, NR4A2 and IGFBP1b were identified as diagnostic markers. These key genes may be predictive markers for the development of fatty liver. It is recommended that these key genes are assessed further as possible predictive markers during the development of fatty liver.

Natriuretic Peptides in Gastrointestinal Cancer: Biomarkers and Potential Therapeutic Targets

Gastrointestinal (GI) cancers are an important health problem globally. Natriuretic peptides are hormones that have a crucial role in human physiology. There are a variety of treatments for GI cancer, but conventional therapies have side effects and low efficacy. Studies have demonstrated that natriuretic peptides are therapeutic in different cancer types. Natriuretic peptides are best known for their involvement in regulating blood pressure and blood volume. The anti-tumor effect exerted by natriuretic peptides is via their inhibitory effects on DNA synthesis and by their effects on apoptosis. The anti-proliferative role of natriuretic peptides has been shown in human breast cancer, prostate, colon, pancreatic, lung, ovarian, and other tumors. The roles of natriuretic peptides in these cancers are diverse and not well understood. Therefore, we have reviewed the recent literature on natriuretic peptides in GI cancers as a common malignancy in adults to assess the pathways that NPs are involved in the progression of GI cancers and its effect on the prevention or treatment of GI cancers.

Therapeutic Potential of Hydrogen-Rich Water on Muscle Atrophy Caused by Immobilization in a Mouse Model

Skeletal muscle atrophy is associated with poor quality of life and disability. Thus, finding a new strategy for the prevention and treatment of skeletal muscle atrophy is very crucial. This study aimed to investigate the therapeutic potential of hydrogen-rich water (HRW) on muscle atrophy in a unilateral hind limb immobilization model. Thirty-six male Balb/C mice were divided into control (without immobilization), atrophy, and atrophy + hydrogen-rich water (HRW). Unilateral hind limb immobilization was induced using a splint for 7 days (atrophy) and removed for 10 days (recovery). At the end of each phase, gastrocnemius and soleus muscle weight, limb grip strength, skeletal muscle histopathology, muscle fiber size, cross-section area (CSA), serum troponin I and skeletal muscle IL-6, TNF-α and Malondialdehyde (MDA), and mRNA expression of NF-κB, BAX and Beclin-1 were evaluated. Muscle weight and limb grip strength in the H2-treated group were significantly improved during the atrophy phase, and this improvement continued during the recovery period. Treatment by HRW increased CSA and muscle fiber size and reduced muscle fibrosis, serum troponin I, IL-6, TNF-α and MDA which was more prominent in the atrophy phase. These data suggest that HRW could improve muscle atrophy in an immobilized condition and could be considered a new strategy during rehabilitation.

Down regulation of Cathepsin W is associated with poor prognosis in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is associated with a very poor prognosis. Therefore, there has been a focus on identifying new biomarkers for its early diagnosis and the prediction of patient survival. Genome-wide RNA and microRNA sequencing, bioinformatics and Machine Learning approaches to identify differentially expressed genes (DEGs), followed by validation in an additional cohort of PDAC patients has been undertaken. To identify DEGs, genome RNA sequencing and clinical data from pancreatic cancer patients were extracted from The Cancer Genome Atlas Database (TCGA). We used Kaplan-Meier analysis of survival curves was used to assess prognostic biomarkers. Ensemble learning, Random Forest (RF), Max Voting, Adaboost, Gradient boosting machines (GBM), and Extreme Gradient Boosting (XGB) techniques were used, and Gradient boosting machines (GBM) were selected with 100% accuracy for analysis. Moreover, protein-protein interaction (PPI), molecular pathways, concomitant expression of DEGs, and correlations between DEGs and clinical data were analyzed. We have evaluated candidate genes, miRNAs, and a combination of these obtained from machine learning algorithms and survival analysis. The results of Machine learning identified 23 genes with negative regulation, five genes with positive regulation, seven microRNAs with negative regulation, and 20 microRNAs with positive regulation in PDAC. Key genes BMF, FRMD4A, ADAP2, PPP1R17, and CACNG3 had the highest coefficient in the advanced stages of the disease. In addition, the survival analysis showed decreased expression of hsa.miR.642a, hsa.mir.363, CD22, BTNL9, and CTSW and overexpression of hsa.miR.153.1, hsa.miR.539, hsa.miR.412 reduced survival rate. CTSW was identified as a novel genetic marker and this was validated using RT-PCR. Machine learning algorithms may be used to Identify key dysregulated genes/miRNAs involved in the disease pathogenesis can be used to detect patients in earlier stages. Our data also demonstrated the prognostic and diagnostic value of CTSW in PDAC.

Extracellular vesicles: Emerging mediators of cell communication in gastrointestinal cancers exhibiting metabolic abnormalities

There is a complex interaction between pro-tumoural and anti-tumoural networks in the tumour microenvironment (TME). Throughout tumourigenesis, communication between malignant cells and various cells of the TME contributes to metabolic reprogramming. Tumour Dysregulation of metabolic pathways offer an evolutional advantage in the TME and enhance the tumour progression, invasiveness, and metastasis. Therefore, understanding these interactions within the TME is crucial for the development of innovative cancer treatments. Extracellular vesicles (EVs) serve as carriers of various materials that include microRNAs, proteins, and lipids that play a vital role in the communication between tumour cells and non-tumour cells. EVs are actively involved in the metabolic reprogramming process. This review summarized recent findings regarding the involvement of EVs in the metabolic reprogramming of various cells in the TME of gastrointestinal cancers. Additionally, we highlight identified microRNAs involved in the reprogramming process in this group of cancers and explained the abnormal tumour metabolism targeted by exosomal cargos as well as the novel potential therapeutic approaches.

Recent Advances in MXene Quantum Dots: A Platform with Unique Properties for General-Purpose Functional Materials with Novel Biomedical Applications

Developing new, high-performance materials is a prerequisite for technological advancement. In comparison to bulk materials, quantum dots have a number of good advantages due to their small size, high surface area, and quantum dimensions. Quantum dots, two-dimensional materials with lateral dimensions less than 100 nm, can be generated by the quantum confinement effect. Mxene quantum dots (MQDs) retain some of their two-dimensional characteristics. They also exhibit novel physicochemical properties, including enhanced dispersibility in aqueous and nonaqueous phases, modification or doping capabilities, and photoluminescence. MQDs, due to their unique and diverse properties, have been receiving a great deal of attention as new members of the Mxene group and wide use for biotechnology, bioimaging, optoelectronics, catalysis, cancer therapy, etc. This review aims to provide an overview of the synthesis of MQDs, their optical properties, and their cancer therapy applications. MQDs exhibit remarkable photothermal and photodynamic features and can be suitable for bioimaging. In addition to obtaining bioimaging, photothermal therapy (PTT) and photodynamic therapy (PDT) effects simultaneously, MQDs have high biocompatibility in vitro and in vivo, providing evidence of their potential clinical utility. Herein, recent developments and future prospects concerning MQDs biomedical applications are discussed.

Targeting transforming growth factor beta (TGF-β) using Pirfenidone, a potential repurposing therapeutic strategy in colorectal cancer

The modulating factors within the tumor microenvironment, for example, transforming growth factor beta (TGF-β), may limit the response to chemo and immunotherapy protocols in colorectal cancer (CRC). In the current study, the therapeutic potential of targeting the TGF-β pathway using Pirfenidone (PFD), a TGF-β inhibitor, either alone or in combination with five fluorouracil (5-FU) has been explored in preclinical models of CRC. The anti-proliferative and migratory effects of PFD were assessed by MTT and wound-healing assays respectively. Xenograft models were used to study the anti-tumor activity, histopathological, and side effects analysis. Targeting of TGF-β resulted in suppression of cell proliferation and migration, associated with modulation of survivin and MMP9/E-cadherin. Moreover, the PFD inhibited TGF-β induced tumor progression, fibrosis, and inflammatory response through perturbation of collagen and E-cadherin. Targeting the TGF-β pathway using PFD may increase the anti-tumor effects of 5-FU and reduce tumor development, providing a new therapeutic approach to CRC treatment.

Preclinical tumor mouse models for studying esophageal cancer

Preclinical models are extensively employed in cancer research because they can be manipulated in terms of their environment, genome, molecular biology, organ systems, and physical activity to mimic human behavior and conditions. The progress made in in vivo cancer research has resulted in significant advancements, enabling the creation of spontaneous, metastatic, and humanized mouse models. Most recently, the remarkable and extensive developments in genetic engineering, particularly the utilization of CRISPR/Cas9, transposable elements, epigenome modifications, and liquid biopsies, have further facilitated the design and development of numerous mouse models for studying cancer. In this review, we have elucidated the production and usage of current mouse models, such as xenografts, chemical-induced models, and genetically engineered mouse models (GEMMs), for studying esophageal cancer. Additionally, we have briefly discussed various gene-editing tools that could potentially be employed in the future to create mouse models specifically for esophageal cancer research.

Dual targeting of TGF-β and PD-L1 inhibits tumor growth in TGF-β/PD-L1-driven colorectal carcinoma

Immunosuppressive factors within the tumor microenvironment (TME), such as Transforming growth factor beta (TGF-β), constitute a crucial hindrance to immunotherapeutic approaches in colorectal cancer (CRC). Furthermore, immune checkpoint factors (e.g., programmed death-ligand 1 [PD-L1]) inhibit T-cell proliferation and activation. To cope with the inhibitory effect of immune checkpoints, the therapeutic value of dual targeting PD-L1 and TGF-β pathways via M7824 plus 5-FU in CRC has been evaluated. Integrative-systems biology approaches and RNAseq were used to assess the differential level of genes associated with 88 metastatic-CRC patients. The level of PD-L1 and TGF-β was evaluated in a validation cohort. The anti-proliferative, migratory, and apoptotic effects of PD-L1/TGF-β inhibitor, M7824, were assessed by MTT, wound-healing assay, and flow cytometry. Anti-tumor activity was assessed in a xenograft model, followed by biochemical studies and histological staining, and gene/protein expression analyses by RT-PCR and ELISA/IHC. The result of differentially expressed genes (DEGs) analysis showed 1268 upregulated and 1074 downregulated genes in CRC patients. Among the highest scoring genes and dysregulated pathways associated with CRC, PD-L1, and TGF-β were identified and further validated in 92 CRC patients. Targeting of PD-L1-TGF-β inhibited cell growth and migration, associated with modulation of CyclinD1 and MMP9. Furthermore, M7824 inhibited tumor growth via targeting TGF-β and PD-L1 pathways, resulting in modulation of inflammatory response and fibrosis via TNF-α/IL6/CD4-8 and COL1A1/1A2, respectively. In conclusion, our data illustrated that co-targeting PD-L1 and TGF-β pathways increased the effect of Fluorouracil (5-FU) and reduced the tumor growth in PD-L1/TGF-β expressing tumors, providing a new therapeutic option in the treatment of CRC.

The Prognostic Value of ASPHD1 and ZBTB12 in Colorectal Cancer: A Machine Learning-Based Integrated Bioinformatics Approach

Introduction: Colorectal cancer (CRC) is a common cancer associated with poor outcomes, underscoring a need for the identification of novel prognostic and therapeutic targets to improve outcomes. This study aimed to identify genetic variants and differentially expressed genes (DEGs) using genome-wide DNA and RNA sequencing followed by validation in a large cohort of patients with CRC. Methods: Whole genome and gene expression profiling were used to identify DEGs and genetic alterations in 146 patients with CRC. Gene Ontology, Reactom, GSEA, and Human Disease Ontology were employed to study the biological process and pathways involved in CRC. Survival analysis on dysregulated genes in patients with CRC was conducted using Cox regression and Kaplan-Meier analysis. The STRING database was used to construct a protein-protein interaction (PPI) network. Moreover, candidate genes were subjected to ML-based analysis and the Receiver operating characteristic (ROC) curve. Subsequently, the expression of the identified genes was evaluated by Real-time PCR (RT-PCR) in another cohort of 64 patients with CRC. Gene variants affecting the regulation of candidate gene expressions were further validated followed by Whole Exome Sequencing (WES) in 15 patients with CRC. Results: A total of 3576 DEGs in the early stages of CRC and 2985 DEGs in the advanced stages of CRC were identified. ASPHD1 and ZBTB12 genes were identified as potential prognostic markers. Moreover, the combination of ASPHD and ZBTB12 genes was sensitive, and the two were considered specific markers, with an area under the curve (AUC) of 0.934, 1.00, and 0.986, respectively. The expression levels of these two genes were higher in patients with CRC. Moreover, our data identified two novel genetic variants-the rs925939730 variant in ASPHD1 and the rs1428982750 variant in ZBTB1-as being potentially involved in the regulation of gene expression. Conclusions: Our findings provide a proof of concept for the prognostic values of two novel genes-ASPHD1 and ZBTB12-and their associated variants (rs925939730 and rs1428982750) in CRC, supporting further functional analyses to evaluate the value of emerging biomarkers in colorectal cancer.

Nanoliposomal oxaliplatin ameliorates chemotherapy-induced neuropathy

Chemotherapy-induced peripheral neuropathy (CIPN) is an important adverse effect of treatment with oxaliplatin (OXA). We have developed PEGylated nanoliposomal oxaliplatin (OXA-LIP) and tested its activity in an animal model of CIPN. OXA-LIPs were prepared using a combination of egg yolk lecithin, cholesterol, and DSPE-mPEG2000 (at ratios 400, 80, and 27 mg). These liposomes were characterized using several different methods (e.g., polydispersity index (PDI), and zeta potential, FESEM). The in vivo study was performed in 15 male rats comprising three groups: a negative control (normal saline) OXA, and OXA-LIP. These were injected intraperitoneally at a concentration of 4 mg/kg on two consecutive days every week, for 4 weeks. After that, CIPN was assessed using the hotplate and acetonedropmethods. Oxidative stress biomarkers such as SOD, catalase, MDA, and TTG were measured in the serum samples. The functional disturbances of the liver and kidney were assessed by measuring the serum levels of ALT, AST, creatinine, urea, and bilirubin. Furthermore, hematological parameters were determined in the three groups. The OXA-LIP had an average particle size, PDI, and zeta potential of 111.2 ± 1.35 nm, 0.15 ± 0.045, and -52.4 ± 17 mV, respectively. The encapsulation efficiency of OXA-LIP was 52% with low leakage rates at 25 °C.Thermal hyperalgesia changes showed OXA has significant effects in the induction of neuropathy on days 7, 14, and 21 compared to the control group. OXA had a significantly greater sensitivity than the OXA-LIP and control groups in the thermal allodynia test (P < 0.001). OXA-LIP administration did not show significant effects on the changes of oxidative stress, biochemical factors, and cell count. Our findings provide a proof of concept on the potential application of oxaliplatin encapsulated with PEGylated nanoliposome to ameliorate the severity of neuropathy, supporting further studies in clinical phases to explore the value of this agent for Chemotherapy-induced peripheral neuropathy.

Therapeutic Potential of Targeting the Cytochrome P450 Enzymes Using Lopinavir/Ritonavir in Colorectal Cancer: A Study in Monolayers, Spheroids and In Vivo Models

Cytochrome P450 (CYP450) enzyme has been shown to be expressed in colorectal cancer (CRC) and its dysregulation is linked to tumor progression and a poor prognosis. Here we investigated the therapeutic potential of targeting CYP450 using lopinavir/ritonavir in CRC. The integrative systems biology method and RNAseq were utilized to investigate the differential levels of genes associated with patients with colorectal cancer. The antiproliferative activity of lopinavir/ritonavir was evaluated in both monolayer and 3-dimensional (3D) models, followed by wound-healing assays. The effectiveness of targeting CYP450 was examined in a mouse model, followed by histopathological analysis, biochemical tests (MDA, SOD, thiol, and CAT), and RT-PCR. The data of dysregulation expressed genes (DEG) revealed 1268 upregulated and 1074 down-regulated genes in CRC. Among the top-score genes and dysregulated pathways, CYPs were detected and associated with poor prognosis of patients with CRC. Inhibition of CYP450 reduced cell proliferation via modulating survivin, Chop, CYP13a, and induction of cell death, as detected by AnnexinV/PI staining. This agent suppressed the migratory behaviors of cells by induction of E-cadherin. Moreover, lopinavir/ritonavir suppressed tumor growth and fibrosis, which correlated with a reduction in SOD/thiol levels and increased MDA levels. Our findings illustrated the therapeutic potential of targeting the CYP450 using lopinavir/ritonavir in colorectal cancer, supporting future investigations on this novel therapeutic approach for the treatment of CRC.

Identification of ZMYND19 as a novel biomarker of colorectal cancer: RNA-sequencing and machine learning analysis

Colorectal cancer (CRC) is the third most common cause of cancer-related deaths. The five-year relative survival rate for CRC is estimated to be approximately 90% for patients diagnosed with early stages and 14% for those diagnosed at an advanced stages of disease, respectively. Hence, the development of accurate prognostic markers is required. Bioinformatics enables the identification of dysregulated pathways and novel biomarkers. RNA expression profiling was performed in CRC patients from the TCGA database using a Machine Learning approach to identify differential expression genes (DEGs). Survival curves were assessed using Kaplan-Meier analysis to identify prognostic biomarkers. Furthermore, the molecular pathways, protein-protein interaction, the co-expression of DEGs, and the correlation between DEGs and clinical data have been evaluated. The diagnostic markers were then determined based on machine learning analysis. The results indicated that key upregulated genes are associated with the RNA processing and heterocycle metabolic process, including C10orf2, NOP2, DKC1, BYSL, RRP12, PUS7, MTHFD1L, and PPAT. Furthermore, the survival analysis identified NOP58, OSBPL3, DNAJC2, and ZMYND19 as prognostic markers. The combineROC curve analysis indicated that the combination of C10orf2 -PPAT- ZMYND19 can be considered as diagnostic markers with sensitivity, specificity, and AUC values of 0.98, 1.00, and 0.99, respectively. Eventually, ZMYND19 gene was validated in CRC patients. In conclusion, novel biomarkers of CRC have been identified that may be a promising strategy for early diagnosis, potential treatment, and better prognosis.

Association of dietary intake and cervical cancer: a prevention strategy

INTRODUCTION

Cervical cancer is one of lethal cancers in women. As a global concern, identifying important factors of cancer is a useful strategy for prevention. Due to the role of diet/nutrition factors for cancer, the purpose of our study was to determine the impact of 150 nutrition/vitamin factors and 50 non-nutritional factor in cervical cancer and phase.

METHODS

Population samples of 2088 healthy subjects and patients with cervical cancer were investigated. 200 factors such as vitamin E, B1, B6, fruits, HPV, and age were gathered. Deep learning, Decision tree, and correlation matrix were used for modeling and identifying important factors. SPSS 26, R4.0.3, and Rapid miner were utilized for implementation.

RESULTS

Our findings indicated that zinc, Iron, Niacin, Potassium, Phosphorous, and Cooper have a beneficial impact in reducing the risk of cervical cancer and progression of phase in Iranian women, as well as Salt, snacks and milk Were identified as high-risk food factors (P value < 0.05 and coefficient correlation > 0.6). Also, alcohol, and sex patient with two groups, HPV positive have an impact on cervical cancer incidence. Phosphorus and selenium in the Micronutrients category (R² = 0.85, AUC = 0.993) and polyunsaturated fatty acid and salt in the Macronutrients category and other categories of nutrients were identified as the most effective factors in cervical cancer using deep learning (R² = 0.93, AUC = 0.999).

CONCLUSIONS

A diet and rich nutrition can be helpful for the prevention of cervix cancer and may reduce the risk of disease. Additional research is necessary for different countries.

Screening and introduction of key cell cycle microRNAs deregulated in colorectal cancer by integrated bioinformatics analysis

Colorectal cancer (CRC) is the second most common cancer in women and the third most common in men worldwide. Impaired cell cycle regulation leads to many cancers and is also approved in CRC. Therefore, cell cycle regulation is a critical therapeutic target for CRC. Furthermore, miRNAs have been discovered as regulators in a variety of cancer-related pathways. This study is designed to investigate how miRNAs and mRNAs interact to regulate the cell cycle in CRC patients. Utilizing the Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Expression Omnibus (GEO), and Therapeutic Target Database (TTD), cell cycle-associated genes were identified and evaluated. Seven of the 22 differentially expressed genes (DEGs) implicated in the cell cycle in three GSEs (GSE24514, GSE10950, and GSE74604) were identified as potential therapeutic targets. Then, using PyRx software, we performed docking proteins with selected drugs. The results demonstrated that these drugs are appropriate molecules for targeting cell cycle DEGs. Tarbase, miRTarbase, miRDIP, and miRCancer databases were used to find miRNAs that target the indicated genes. The ability of these six miRNAs to impact the cell cycle in colorectal cancer may be concluded. These miRNAs were found to be downregulated in SW480 cells when compared to the normal tissue. Our data imply that a precise selection of bioinformatics tools can facilitate the identification of miRNAs that impact mRNA translation at different stages of the cell cycle. The candidates can be investigated more as targets for cell cycle arrest in cancers.

Developing and validating a national set of standards for undergraduate medical education using the WFME framework: the experience of an accreditation system in Iran

BACKGROUND

Defining standards is the first step toward quality assurance and improvement of educational programs. This study aimed at developing and validating a set of national standards for the Undergraduate Medical Education (UME) program through an accreditation system in Iran using the World Federation for Medical Education (WFME) framework.

METHODS

The first draft of standards was prepared through consultative workshops with the participation of different UME program stakeholders. Subsequently, standards were sent to medical schools and UME directors were asked to complete a web-based survey. The content validity index at the item level (I-CVI) was computed using criteria including clarity, relevance, optimization and evaluability for each standard. Afterward, a full-day consultative workshop was held and a wide range of UME stakeholders across the country (n = 150) discussed the survey results and made corrections to standards.

RESULTS

Analysis of survey results showed that relevance criteria had the best CVI as only 15 (13%) standards demonstrated CVI < 0.78. More than two-thirds (71%) and a half (55%) of standards showed CVI < 0.78 for optimization and evaluability criteria. The final set of UME national standards was structured in 9 areas, 24 sub-areas, 82 basic and 40 quality development standards, and 84 annotations.

CONCLUSIONS

We developed and validated national standards as a framework to ensure the quality of UME training with input from UME stakeholders. We used WFME standards as a benchmark while addressing local requirements. The standards and participatory approach to developing standards may guide relevant institutions.

Mechanism-Based Pharmacological Management of Chemotherapy-Induced Neuropathic Pain from Preclinical Studies to Clinical Prospective: Platinum-based drugs, Taxanes, and Vinca Alkaloids

BACKGROUND

Chemotherapy-induced peripheral neuropathy (CIPN) is a painful condition, experienced by patients undergoing chemotherapy with some specific drugs, such as platinum-based agents, taxanes, and vinca alkaloids. Painful CIPN may lead to dose interruptions and discontinuation of chemotherapy and can negatively impact on the quality of life and clinical outcome of these patients. Due to a lack of a practical medical therapy for CIPN, it is necessary to further explore and identify novel therapeutic options.

METHODS

We have reviewed PubMed and EMBASE libraries to gather data on the mechanism-based pharmacological management of chemotherapy-induced neuropathic pain.

RESULT

This review has focused on the potential mechanisms by which these chemotherapeutic agents may be involved in the development of CIPN, and explains how this may be translated into clinical management. Additionally, we have presented an overview of emerging candidates for the prevention and treatment of CIPN in preclinical and clinical studies.

CONCLUSION

Taken together, due to the debilitating consequences of CIPN for the quality of life and clinical outcome of cancer survivors, future studies should focus on identifying underlying mechanisms contributing to CIPN as well as developing effective pharmacological interventions based on these mechanistic insights.