Identification of genes related to ribosomal proteins in colorectal cancer: exploring their potential as biomarkers, prognostic indicators, and therapeutic targets.

BACKGROUND: Colorectal cancer (CRC) ranks as the third most commonly diagnosed cancer in both females and males, underscoring the need for the identification of effective biomarkers. METHODS AND RESULTS: We assessed the expression levels of ribosomal proteins (RPs) at both mRNA and protein levels. Subsequently, leveraging the STRING database, we constructed a protein-protein interaction network and identified hub genes. The co-expression network of differentially expressed genes associated with CRC and their target hub RPs was constructed using the weighted gene co-expression network analysis algorithm. Gene ontology and molecular signatures database were conducted to gain insights into the biological roles of genes associated with the identified module. To confirm the results, the expression level of the candidate genes in the CRC samples compared to the adjacent healthy was evaluated by the RT-qPCR method. Our findings indicated that the genes related to RPs were predominantly enriched in biological processes associated with Myc Targets, Oxidative Phosphorylation, and cell proliferation. Also, results demonstrated that elevated levels of GRWD1, MCM5, IMP4, and RABEPK that related to RPs were associated with poor prognostic outcomes for CRC patients. Notably, IMP4 and RABEPK exhibited higher diagnostic value. Moreover, the expression of IMP4 and RABEPK showed a significant association with drug resistance using cancer cell line encyclopedia and genomics of drug sensitivity in cancer databases. Also, the results showed that the expression level of IMP4 and RABEPK in cancerous samples was significantly higher compared to the adjacent healthy ones. CONCLUSION: The general results of this study have shown that many genes related to RPs are increased in cancer and could be associated with the death rate of patients. We also highlighted the therapeutic and prognostic potentials of RPs genes in CRC.

Digital Screen Time and the Risk of Female Breast Cancer: A Retrospective Matched Case-Control Study.

Background: As the use of electronic devices such as mobile phones, tablets, and computers continues to rise globally, concerns have been raised about their potential impact on human health. Exposure to high energy visible (HEV) blue light, emitted from digital screens, particularly the so-called artificial light at night (ALAN), has been associated with adverse health effects, ranging from disruption of circadian rhythms to cancer. Breast cancer incidence rates are also increasing worldwide. Objective: This study aimed at finding a correlation between breast cancer and exposure to blue light from mobile phone. Material and Methods: In this retrospective matched case-control study, we aimed to investigate whether exposure to blue light from mobile phone screens is associated with an increased risk of female breast cancer. We interviewed 301 breast cancer patients (cases) and 294 controls using a standard questionnaire and performed multivariate analysis, chi-square, and Fisher's exact tests for data analysis. Results: Although heavy users in the case group of our study had a statistically significant higher mean 10-year cumulative exposure to digital screens compared to the control group (7089±14985 vs 4052±12515 hours, respectively, P=0.038), our study did not find a strong relationship between exposure to HEV and development of breast cancer. Conclusion: Our findings suggest that heavy exposure to HEV blue light emitted from mobile phone screens at night might constitute a risk factor for promoting the development of breast cancer, but further large-scale cohort studies are warranted.

The Association of miRNA-146a Gene Variation and Multiple Sclerosis in The Iranian Population.

Background: Multiple sclerosis (MS) is a complex human autoimmune-type inflammatory disease of the central nervous system (CNS). MicroRNA-146a (miR-146a) belongs to an endogenous and non-coding RNA family with 18-22 nucleotides long, which modulates the innate and adaptive immune response. Methods: Our study aimed to investigate a possible association between rs2910164 and rs2431697 polymorphisms of the miR-146a gene and multiple sclerosis in the Iranian population. A total of 60 MS cases and 100 controls were recruited. Single nucleotide polymorphism (SNP) rs2431697 was genotyped by utilizing polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP), and SNP rs2910164 was genotyped by using Tetra-primer ARMS-PCR. Statistical Analysis conducted by the chi-squared test utilizing SPSS version 21.0 Software. The Hardy-Weinberg equilibrium assumption was evaluated. Results: The results of the present study suggest the miR-146a gene rs2431697 polymorphism is not associated with multiple sclerosis. However, there is a significant relationship between polymorphism rs2910164 of the miR-146a gene and multiple sclerosis in the population studied (P = 0.012). Conclusion: Our data provide evidence that the miR-146a gene may be involved in creating the susceptibility to MS in the Iranian population.

TYK2 single-nucleotide variants associated with the severity of COVID-19 disease.

Coronavirus disease 2019 (COVID-19) is a lethal disease caused by the coronavirus SARS-CoV-2, which can result in a broad clinical spectrum of respiratory symptoms. While many clinical risk factors such as concomitant chronic diseases play roles in the pathophysiology of COVID-19, genetic predisposition factors have not been widely studied. The aim of this study was, therefore, to evaluate the relationship between some singlenucleotide polymorphisms (SNPs) of the human genes TYK2 and ACE2 and the severity of SARS-CoV-2 infection. Genomic DNA was isolated from 200 SARS-CoV-2-infected individuals with severe (n = 100) or mild (n = 100) disease. Owing to the importance of ACE2 and TYK2 genes in regulating the immune response to SARS-CoV-2 infection, TYK2 gene SNPs, i.e. rs2304255, rs2304256, rs12720270, and rs12720354 and ACE2 rs382746 variants, were genotyped in the samples. To confirm the results, the expression of different TYK2 genotypes was investigated using real-time PCR. The presence of the nucleotide T at the locus rs2304255 was shown to be a risk factor linked to disease severity (OR [95% CI] = 3.2485 [2.1554-4.8961]). Similarly, the presence of A at the locus rs12720354 increased the risk of severity (OR [95% CI]) = 3.9721 [2.6075-6.0509]). In contrast, the presence of A at the loci rs2304256 and rs12720270 was observed to reduce the severity risk (OR [95% CI] = 0.2495 [0.1642-0.3793] and 0.1668 [0.1083-0.2569], respectively). Real-time PCR results also demonstrated that the expression level of TYK2 in samples with the TT genotype of rs2304255 and the AA genotype of rs12720354 and in samples with the GG genotype of rs12720207 was significantly lower than in those with other genotypes. The results of this study suggest that TYK2 SNPs might be utilized to identify individuals who are at risk for severe COVID-19, in order to better manage their health care. It is predicted that the presence of some alleles (T in rs2304255, A in rs12720354, and G in rs12720207) of TYK2 can affect COVID-19 severity by reducing TYK2 expression and thereby affecting the regulatory role of TYK2 in the immune response.

MIMT1 and LINC01550 are uncharted lncRNAs down-regulated in colorectal cancer.

Incomplete knowledge of the molecular basis of colorectal cancer, with subsequent limitations in early diagnosis and effective treatment, has contributed to this form of malignancy becoming the second most common cause of cancer-related death worldwide. With the advances in high-throughput profiling techniques and the availability of public data sets such as The Cancer Genome Atlas Program (TCGA), a broad range of coding transcripts have been profiled and their underlying modes of action have been mapped. However, there is still a huge gap in our understanding of noncoding RNA dysregulation. To this end, we used a bioinformatics approach to shortlist and evaluate yet-to be-profiled long noncoding RNAs (lncRNAs) in colorectal cancer. We analysed the TCGA RNA-seq data and followed this by validating the expression patterns using a qPCR technique. Analysing in-house clinical samples, the real-time PCR method revealed that the shortlisted lncRNAs, that is MER1 Repeat Containing Imprinted Transcript 1 (MIMT1) and Non-Protein Coding RNA 1550 (LINC01550), were down-regulated in colorectal cancer tumours compared with the paired adjacent normal tissues. Mechanistically, the in silico results suggest that LINC01550 could form a complex competitive endogenous RNA (ceRNA) network leading to the subsequent regulation of colorectal cancer-related genes, such as CUGBP Elav-Like Family Member (CELF2), Polypyrimidine Tract Binding Protein 1 (PTBP1) and ELAV Like RNA Binding Protein 1 (ELAV1). The findings of this work indicate that MIMT1 and LINC01550 could be novel tumour suppressor genes that can be studied further to assess their roles in regulating the cancer signalling pathway(s).

Machine Learning Models for Predicting Breast Cancer Risk in Women Exposed to Blue Light from Digital Screens.

Background: Nowadays, there is a growing global concern over rapidly increasing screen time (smartphones, tablets, and computers). An accumulating body of evidence indicates that prolonged exposure to short-wavelength visible light (blue component) emitted from digital screens may cause cancer. The application of machine learning (ML) methods has significantly improved the accuracy of predictions in fields such as cancer susceptibility, recurrence, and survival. Objective: To develop an ML model for predicting the risk of breast cancer in women via several parameters related to exposure to ionizing and non-ionizing radiation. Material and Methods: In this analytical study, three ML models Random Forest (RF), Support Vector Machine (SVM), and Multi-Layer Perceptron Neural Network (MLPNN) were used to analyze data collected from 603 cases, including 309 breast cancer cases and 294 gender and age-matched controls. Standard face-to-face interviews were performed using a standard questionnaire for data collection. Results: The examined models RF, SVM, and MLPNN performed well for correctly classifying cases with breast cancer and the healthy ones (mean sensitivity> 97.2%, mean specificity >96.4%, and average accuracy >97.1%). Conclusion: Machine learning models can be used to effectively predict the risk of breast cancer via the history of exposure to ionizing and non-ionizing radiation (including blue light and screen time issues) parameters. The performance of the developed methods is encouraging; nevertheless, further investigation is required to confirm that machine learning techniques can diagnose breast cancer with relatively high accuracies automatically.

Elevated CDK5R1 expression associated with poor prognosis, proliferation, and drug resistance in colorectal and breast malignancies: CDK5R1 as an oncogene in cancers.

BACKGROUND: Studies have shown that the CDK5R1 gene could have a part in some types of cancer. This study sought to examine the relationship between CDK5R1 expression and prognosis and medication resistance in 13 commonly occurring cancers. METHOD: The cancer genome atlas data and clinical data were utilized to assess the role of CDK5R1 in malignancies. The expression data of 13 cancers were also integrated and used for the co-expression network. The relationship between CDK5R1 expression and drug resistance and sensitivity was evaluated using pharmacogenomics data. The colorectal cancer (CRC) and breast cancer (BC) were used to confirm the results through the RT-qPCR method. RESULTS: With the exception of gastric cancer, all common malignancies showed an increase in CDK5R1 expression. Also, outcomes of sensitivity and specificity showed that CDK5R1 level could be a really good potential biomarker. Additionally, CDK5R1 expression was higher in CRC and BC samples compared to adjacent normal, according to RT-qPCR data. In six types of tumors and combined data, a poor prognosis was associated with increased CDK5R1 expression. The CDK5R1-associated genes were connected to the primary oncogenic pathways in cancer cells, according to the co-expression network. Also, CDK5R1 level was significantly linked to the resistance and sensitivity of several chemotherapy drugs and caused the highest resistance to cyclophosphamide. CONCLUSION: CDK5R1 expression is upregulated in 12 prevalent cancers and can play an oncogenic role. Also, this gene's expression could be used as a biomarker to predict patient survival and medication resistance.

ESRG, LINC00518 and PWRN1 are newly-identified deregulated lncRNAs in colorectal cancer.

Colorectal cancer is the 2nd leading cause of death in humans because of cancer. This rank of death could be due to the high rate of incidence from one hand, and the lack of sufficient diagnostic and therapeutic approaches from the other hand. Thus, molecular tools have been emerging as the potential biomarker to improve the early diagnosis and therapeutic management that subsequently could lead to the heightened survival rate of colorectal cancer patients. Long non-coding RNA (lncRNAs) have shown promising capabilities to be used in clinics. The profiling methods could identify novel aberrantly expressed lncRNAs in colorectal cancer. We, thus, performed a comprehensive and unbiased approach to shortlist the dysregulated lncRNAs based on the colon adenocarcinoma TCGA data. An unbiased in silico method was used to rank the yet to profiled lncRNAs in colorectal cancer. qPCR was used to measure the expression level of selected lncRNAs. Our results nominated ESRG, LINC00518, PWRN1, and TTTY14 lncRNAs as the top-hit novel lncRNAs with aberrant expression in colon cancer. The qPCR method was used to profile these lncRNAs that showed the up-regulation of ESRG and LINC00518, and down-regulation of TTTY14 in thirty paired colorectal cancer specimens. The statistical analyses demonstrated that ESRG, LINC00518 and PWRN1 could distinguish the tumor from normal samples. Moreover, ESRG showed a negative correlation with the overall survival of patients. These diagnostic and prognostic results suggest that profiling ESRG, LINC00518 and PWRN1 s may have implications in clinics.

The role of cell surface proteins gene expression in diagnosis, prognosis, and drug resistance of colorectal cancer: In silico analysis and validation.

Cell surface proteins (CSPs) are an important type of protein in different essential cell functions. This study aimed to distinguish overexpressed CSPs in colorectal cancer to investigate their biomarker, prognosis, and drug resistance potential. Raw data of three datasets including 1187 samples was downloaded then normalization and differential expression were performed. By the combination of the cancer genome atlas (TCGA) clinical data, survival analysis was carried out. Information of all CSPs was collected from cell surface protein atlas. The role of each candidate gene expression was investigated in drug resistance by CCEL and GDSC data from PharmacoGX. CRC samples including 30 tumor samples and adjacent normal were used to confirm data by RT-qPCR. Outcomes showed that 66 CSPs overexpressed in three datasets, and 146 CSPs expression associated with poor prognosis features in TCGA data that TIMP1 and QSOX2 can associate with poor patient survival independently. High-risk patients illustrated more fatality than low-risk patients based on the risk score calculated by the expression level of these genes. Receiver operating characteristic curve analysis showed that 39 CSPs as perfect biomarkers for diagnosis in CRC. Furthermore, QSOX2 and TIMP1 expression levels increased in tumor samples compared to adjacent normal samples. The Drug resistance analysis demonstrated ADAM12 and COL1A2 up-regulation among 66 overexpressed CSPs caused resistance to Venetoclax and Cyclophosphamide with a high estimate, respectively. Many CSPs are deregulated in CRC, and can be valuable candidates as biomarkers for diagnosis, prognosis, and drug resistance.

Highly expressed TLX1NB and NPSR1-AS1 lncRNAs could serve as diagnostic tools in colorectal cancer.

Colorectal cancer is the main cause of human death due to cancer. This fact could be due to the insufficiency of early diagnosis or poor therapeutic strategies. Various molecular tools have been utilized in studies to assess their potentials as diagnostic biomarkers or determining factors in precision medicine. Among these molecules, long non-coding RNAs (lncRNA) have been emerging as accurate and potent transcripts to improve the detection of cancer. The overexpressed lncRNAs could also be deeply studied as the molecules for the targeted therapy in different malignancies, in particular colorectal cancer. Thus, we utilized an unbiased approach to select the up-regulated lncRNAs in colon adenocarcinoma via analyzing the TCGA dataset. Then, we validated the overexpression of two first-ranked lncRNAs, i.e., NPSR1-AS1 and TLX1NB, in our in-house colorectal cancer samples as compared to the paired adjacent normal tissues. The analyses revealed that these lncRNAs could significantly distinguish the tumor against the normal samples. The results may have implications in the early diagnosis and targeted therapy of colorectal cancer.

miR-324-3p and miR-508-5p expression levels could serve as potential diagnostic and multidrug-resistant biomarkers in childhood acute lymphoblastic leukemia.

Acute lymphoblastic leukemia (ALL) is one of the most frequent hematological malignancies in children, representing approximately 25 % of all pediatric cancers. Despite striking advances in ALL treatments, a small population of patients does not still respond to chemotherapy, raising the number of deaths in children. ABC transporters are one of the major causes of multidrug resistance (MDR) in cancers and overexpression of ABCA3 is directly associated with increased chemo-resistance in pediatric ALL. Here, we aimed to identify the microRNAs (miRNAs) which may regulate the expression of ABCA3 in childhood ALL. Bone marrow samples from a total of 50 ALLs and 59 controls were collected and after in silico and literature search, miR-324-3p and miR-508-5p were nominated from a list of putative miRNAs targeting ABCA3. Our qPCR analysis showed a low expression profile of selected miRNAs in pediatric ALL patients compared with non-cancer controls. Furthermore, we found that both miR-324-3p and miR-508-5p were significantly differentially expressed between patients with positive and negative minimal residual disease (MRD + vs MRD-) after one year of chemotherapy while only miR-508-5p was underexpressed in relapsed ALL patients. Additionally, a negative correlation was identified between the expression of these two miRNAs and ABCA3, supporting the regulatory effect of them on drug resistance through interacting with ABCA3. Overall, we suggested miR-324-3p and miR-508-5p as potential diagnostic and drug-resistant biomarkers in pediatric ALL. Moreover, our findings presented miR-508-5p to behave as a promising relapsed indicator in childhood ALL which can be applied in the development of novel therapeutic strategies.

Relation between Body Iron Status and Cardiovascular Risk Factors in Patients with Cardiovascular Disease.

BACKGROUND: There is conflicting evidence regarding the relationship between iron stores and cardiovascular disease (CVD). The present study aimed to investigate the association between body iron indices and some cardiovascular risk factors. METHODS: In a case-control study conducted in the south of Shiraz, Iran, we determined ferritin, iron, total iron binding capacity (TIBC), metabolic risk factors, C-reactive protein (CRP), and anthropometric measurements in 100 men aged 45 years and higher with newly diagnosed CVD and 100 adjusted controls without evidence for CVD. RESULTS: The mean of low density lipoprotein (LDL-c), CRP, and ferritin concentrations were significantly higher in cases than controls, and high density lipoprotein (HDL-c) was significantly lower in cases than controls. Pearson correlation coefficient between CRP and the other risk factors in case group showed that only ferritin, serum iron, waist circumference, and LDL-c significantly correlated with CRP (r = 0.32 with P < 0.001, r = 0.29 with P < 0.05, r = 0.41 with P < 0.01, and r = 0.36 with P < 0.001, respectively). CONCLUSIONS: This study indicated an association between a positive balance of body iron and CVD. Hence, caution should be exercised in administration of iron supplements to patients with CVD and in consumption of food rich in iron by them.