The circadian clock as a potential biomarker and therapeutic target in pancreatic cancer.

Pancreatic cancer (PC) has a very high mortality rate globally. Despite ongoing efforts, its prognosis has not improved significantly over the last two decades. Thus, further approaches for optimizing treatment are required. Various biological processes oscillate in a circadian rhythm and are regulated by an endogenous clock. The machinery controlling the circadian cycle is tightly coupled with the cell cycle and can interact with tumor suppressor genes/oncogenes; and can therefore potentially influence cancer progression. Understanding the detailed interactions may lead to the discovery of prognostic and diagnostic biomarkers and new potential targets for treatment. Here, we explain how the circadian system relates to the cell cycle, cancer, and tumor suppressor genes/oncogenes. Furthermore, we propose that circadian clock genes may be potential biomarkers for some cancers and review the current advances in the treatment of PC by targeting the circadian clock. Despite efforts to diagnose pancreatic cancer early, it still remains a cancer with poor prognosis and high mortality rates. While studies have shown the role of molecular clock disruption in tumor initiation, development, and therapy resistance, the role of circadian genes in pancreatic cancer pathogenesis is not yet fully understood and further studies are required to better understand the potential of circadian genes as biomarkers and therapeutic targets.

A novel strategy for engineering of a smart generation of immune ribonucleases against EGFR+ cells.

The overexpression of epidermal growth factor receptor (EGFR) could result in the development of solid tumors of prostate, breast, gastric, colorectal, ovarian, and head and neck, leading to carcinoma. Antibody therapies are ideal methods to overcome malignant diseases. However, immunoribonucleases are a new generation of antibodies in which an RNase binds to a specific antibody and shows a stronger ability to terminate cancer cells. In this study, we engineered Rana pipiens RNase to bind to the scFv of human antiepidermal growth factor receptor antibody. The molecular dynamic simulations confirmed protein stability and the ability of scFv-ranpirnase (rantoxin) to bind to epidermal growth factor receptor protein. Then, the rantoxin construct was synthesized in a pCDNA 3.1 Neo vector. CHO-K1 cells were used as expression hosts and the construct was transfected. Cells were selected by antibiotic therapies using neomycin, 120 mg/ml, and the high-yield colony was screened by real-time polymerase chain reaction (PCR) methods. Then, the recombinant protein production was confirmed using the sodium dodecyl sulfate polyacrylamide gel electrophoresis and western blot analyses. The molecular dynamic simulation (MDS) confirmed that the I467, S468, Q408, and H409 amino acids of EGFR bonded well to rantoxin. As revealed by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) and western blot analyses, the rantoxin production and PCR analysis showed that the T3 colony can produce rantoxin messenger RNA fourfold higher than the GAPDH gene. The immunotoxin function was assessed in A431 cancer cells and EGFR-negative HEK293 cells, and IC50  values were estimated to be 22.4 ± 3 and >620.4 ± 5 nM, respectively. The results indicated that the immunotoxins produced in this study had the potential for use as anticancer drugs.

Production and introduction of a novel immunotoxin based on engineered RNase A for inducing death to Her1-positive cell lines.

The present study was performed to design an immunotoxin consisting of engineered RNase A and scFv of Cetuximab. To accomplish this study goal, at first to evade RNase A from its inhibitors in the cytoplasm, six amino acids of RNase A were substituted, then the physicochemical features of engineered RNase A were assessed. To investigate the interaction between the engineered RNase A and the ribonuclease inhibitor, protein-protein docking was performed. After engineering the RNase A, it was theoretically conjugated with scFv of Cetuximab using a cleavable linker to produce scFv-engineered RNase A. Then, wild-RNase A (14 kD), engineered RNase A (14 kD) and scFv-engineered RNase A (42 kDa) were expressed in the BL21 (DE3) strain of Escherichia coli and purified by Ni-NTA columns. To confirm the expressed proteins, western blot analysis was performed. The functioning of wild-RNase A and engineered RNase A were investigated by RNA fragmentation assay. Finally, to evaluate the cytotoxicity of scFv-engineered RNase A, a dose-response cytotoxicity assay was performed on Her1-positive and Her1-negative cell lines. The results showed that engineered RNase A could maintain its structure and disulfide bonds and evade its inhibitor. Expression and purification were successfully conducted and both enzymes could degrade yeast RNA. The result of cytotoxicity showed that the engineered immunotoxin could induce cell death to Her1-positive cell lines with an IC50 of 50 nM. It appears that scFv-engineered RNase A can be a promising molecule for use.

Epigenetics evaluation of the oncogenic mechanisms of two closely related bovine and human deltaretroviruses: A system biology study.

Human T-cell lymphotropic virus (HTLV-1) and bovine leukemia virus (BLV) are oncogenic deltaretroviruses, which are the cause of adult T cell leukemia/lymphoma (ATLL) and enzootic bovine leukosis (EBL), respectively. In this study, to evaluate the virus-host interactions in the manifestation of the associated malignancy, four pooled RNA samples of each host (three RNAs in each sample) were applied to RNA-seq. Differential expression analyses were conducted separately between ATLL and EBL groups, in comparison with the healthy group, to identify functional Gene Ontology (GO) terms and hub genes, using DAVID database and MCODE plugin in Cytoscape software, respectively. A broad range of effective genes, involved in the ATLL and EBL, was up- and downregulated. In the virus side, in both malignancy, Tax was expressed very low, but the HTLV-1-HBZ and BVL-As2 transcripts were highly expressed. Some upregulated hub genes, IL2, TOP2A, MKI67, TP73, MYC, and downregulated FOS gene family (FOS, FOSB, and FOSL2), are similarly activated in both human and bovine hosts, in related cell cycle and growth factors. Taken together, it seems that in preventing the infections and cell transformations, Tax must be targeted as a viral factor, and shared peptide in virological and immunological synapses as host factors. Therefore, in the malignant stages, HBZ and As2 transcripts along with growth factors, particularly IL-2R-γ and T-bet or TOP2A, and MKI67 should be targeted in both hosts. Additional studies at the protein level are necessary to elucidate the more useful targets for the therapy of these life-threatening diseases.

Hereditary breast cancer; Genetic penetrance and current status with BRCA.

The most important cause of developing hereditary breast cancer is germline mutations occurring in breast cancer (BCs) susceptibility genes, for example, BRCA1, BRCA2, TP53, CHEK2, PTEN, ATM, and PPM1D. Many BC susceptibility genes can be grouped into two classes, high- and low-penetrance genes, each of which interact with multiple genes and environmental factors. However, the penetrance of genes can also be represented by a spectrum, which ranges between high and low. Two of the most common susceptibility genes are BRCA1 and BRCA2, which perform vital cellular functions for repair of homologous DNA. Loss of heterozygosity accompanied by hereditary mutations in BRCA1 or BRCA2 increases chromosomal instability and the likelihood of cancer, as well as playing a key role in stimulating malignant transformation. With regard to pathological features, familial breast cancers caused by BRCA1 mutations usually differ from those caused by BRCA2 mutations and nonfamilial BCs. It is essential to acquire an understanding of these pathological features along with the genetic history of the patient to offer an individualized treatment. Germline mutations in BRCA1 and BRCA2 genes are the main genetic and inherited factors for breast and ovarian cancer. In fact, these mutations are very important in developing early onset and increasing the risk of familial breast and ovarian cancer and responsible for 90% of hereditary BC cases. Therefore, according to the conducted studies, screening of BRCA1 and BRCA2 genes is recommended as an important marker for early detection of all patients with breast or ovarian cancer risk with family history of the disease. In this review, we summarize the role of hereditary genes, mainly BRCA1 and BRCA2, in BC.

Immunogenic evaluation of FMD virus immuno-dominant epitopes coupled with IL-2/FcIgG in BALB/c mice.

Previous studies on vaccine development against foot-and-mouth disease (FMD) virus reported that application of the inactivated vaccines for FMD virus is not completely effective. Novel vaccinations based on immune-dominant epitopes showed they induced immune responses. In addition, for better and safer immunization, access to of efficient adjuvants against FMD virus seems to be critical. In this study, we produced epitope recombinant vaccines from the VP1 protein of the FMD virus for serotype O of Iran that conjugated with Fc Immunoglobulin (FcIgG) and Interleukin-2 (IL-2). Multiple-epitope constructs included Polytope, Polytope-IL2-FcIgG, Polytope-IL2, Polytope-FcIgG that cloned and expressed in E. coli BL21 (DE3). To evaluate whether these epitope recombinant vaccines induce immune responses, BALB/c mice were injected with the epitope recombinant vaccines and their immune responses were compared with a negative control group. The humoral and cellular immune responses were measured by ELISA. The results showed there were significant differences between the negative control group and other immunized mice with recombinant epitope proteins (p < 0.05). The results of total IgG, IgG1, IgG2a levels and secretion of IFN-γ, IL-4 and IL-10 revealed that immune responses were enhanced when the epitope recombinant vaccine of FMD virus coupled with IL-2 and FcIgG. Observations indicated that the epitope recombinant plasmid of the VP1 protein co-expressed with IL-2 and FcIgG was effective in inducing an enhanced immune response. Therefore, IL-2 and FcIgG could be recommended as a potential adjuvant for epitope recombinant vaccine of the VP1 protein from FMD virus.

The comparative analysis of phenotypic and whole transcriptome gene expression data of ascites susceptible versus ascites resistant chickens.

Ascites syndrome (AS) is a metabolic disorder that mainly occurs at later ages of meat-type chickens. Despite many research, there is no consensus about the origin of this syndrome. Our main purpose were to investigate the syndrome using both phenotypic and RNA-Seq data to elucidate the most causative factors predisposing the birds to AS. Phenotypic data analysis showed that AS indicator traits (AITs) were moderate to high heritable. Inexistence of consistent direct genetic correlation between AITs and growth related traits, indicated that neither faster growth rate nor heavier body weight is the most causative factor affecting the susceptibility of broilers to AS. However, respiratory capacity was revealed to be the most probable factor predisposing the birds to AS, as both lung weight and lung percentage were negatively correlated with AITs. Transcriptomic data analysis revealed 125 differentially expressed genes (DEGs) between the ascitic and healthy groups. Up-regulated genes in ascitic group enriched mainly in gas transport biological process, while down-regulated genes involved in defense response to bacteria, biological adhesion, cell adhesion, killing of cells of another organism and cell division. Genetic association of the DEGs with human cardiovascular diseases suggested excessive heart problems of the ascitic chicks. Heart is, probably, the first tissue suffering from the incompetence of small respiratory system of the AS-susceptible chickens. In other word, tissue hypoxia, that causes free radicals to concentrate in heart cells, may be the commencement of events that finally result to heart failure, suffocation and death of chicks due to the AS.

Engineering Human Pancreatic RNase 1 as an Immunotherapeutic Agent for Cancer Therapy Through Computational and Experimental Studies.

Most plant and bacterial toxins are highly immunogenic with non-specific toxic effects. Human ribonucleases are thought to provide a promising basis for reducing the toxic agent's immunogenic properties, which are candidates for cancer therapy. In the cell, the ribonuclease inhibitor (RI) protein binds to the ribonuclease enzyme and forms a tight complex. This study aimed to engineer and provide a gene construct encoding an improved version of Human Pancreatic RNase 1 (HP-RNase 1) to reduce connection to RI and modulate the immunogenic effects of immunotoxins. To further characterize the interaction complex of HP-RNase 1 and RI, we established various in silico and in vitro approaches. These methods allowed us to specifically monitor interactions within native and engineered HP-RNase 1/RI complexes. In silico research involved molecular dynamics (MD) simulations of native and mutant HP-RNase 1 in their free form and when bound to RI. For HP-RNase 1 engineering, we designed five mutations (K8A/N72A/N89A/R92D/E112/A) based on literature studies, as this combination proved effective for the intended investigation. Then, the cDNA encoding HP-RNase 1 was generated by RT-PCR from blood and cloned into the pSYN2 expression vector. Consequently, wild-type and the engineered HP-RNase 1 were over-expressed in E. coli TG1 and purified using an IMAC column directed against a poly-his tag. The protein products were detected by SDS-PAGE and Western blot analysis. HP-RNase 1 catalytic activity, in the presence of various concentrations of RI, demonstrated that the mutated version of the protein is able to escape the ribonuclease inhibitor and target the RNA substrate 2.5 folds more than that of the wild type. From these data, we tend to suggest the engineered recombinant HP-RNase 1 potentially as a new immunotherapeutic agent for application in human cancer therapy.

The prognostic, diagnostic, and therapeutic impact of Long noncoding RNAs in gastric cancer.

Gastric cancer (GC), ranking as the third deadliest cancer globally, faces challenges of late diagnosis and limited treatment efficacy. Long non-coding RNAs (lncRNAs) emerge as valuable treasured targets for cancer prognosis, diagnosis, and therapy, given their high specificity, convenient non-invasive detection in body fluids, and crucial roles in diverse physiological and pathological processes. Research indicates the significant involvement of lncRNAs in various aspects of GC pathogenesis, including initiation, metastasis, and recurrence, underscoring their potential as novel diagnostic and prognostic biomarkers, as well as therapeutic targets for GC. Despite existing challenges in the clinical application of lncRNAs in GC, the evolving landscape of lncRNA molecular biology holds promise for advancing the survival and treatment outcomes of gastric cancer patients. This review provides insights into recent studies on lncRNAs in gastric cancer, elucidating their molecular mechanisms and exploring the potential clinical applications in GC.

RNA-Seq Profiling between Commercial and Indigenous Iranian Chickens Highlights Differences in Innate Immune Gene Expression.

The purpose of the current study was to examine transcriptomic-based profiling of differentially expressed innate immune genes between indigenous and commercial chickens. In order to compare the transcriptome profiles of the different chicken breeds, we extracted RNA from blood samples of the Isfahan indigenous chicken (as indigenous) and Ross broiler chicken (as commercial) breeds. RNA-Seq yielded totals of 36,763,939 and 31,545,002 reads for the indigenous and commercial breeds, respectively, with clean reads then aligned to the chicken reference genome (Galgal5). Overall, 1327 genes were significantly differentially expressed, of which 1013 genes were upregulated in the commercial versus the indigenous breed, while 314 were more highly expressed in the indigenous birds. Furthermore, our results demonstrated that the SPARC, ATP6V0D2, IL4I1, SMPDL3A, ADAM7, TMCC3, ULK2, MYO6, THG1L and IRG1 genes were the most significantly expressed genes in the commercial birds and the PAPPA, DUSP1, PSMD12, LHX8, IL8, TRPM2, GDAP1L1, FAM161A, ABCC2 and ASAH2 genes were the most significant in the indigenous chickens. Of notable finding in this study was that the high-level gene expressions of heat-shock proteins (HSPs) in the indigenous breeds could serve as a guideline for future genetic improvement. This study identified genes with breed-specific expression, and comparative transcriptome analysis helped understanding of the differences in underlying genetic mechanisms between commercial and local breeds. Therefore, the current results can be used to identify candidate genes for further breed improvement.

Circulating Tumor Cells and Cell-free Nucleic Acids as Biomarkers in Colorectal Cancer.

Colorectal cancer (CRC) is currently the second most prevalent cancer diagnosed in women and the third most common kind of cancer in men. Despite tremendous efforts and advancements in diagnostic approaches and treatment options, the mortality rate of CRC accounts for around one million each year globally. The five-year survival rate of CRC is reported to be approximately 14 percent for patients diagnosed at an advanced stage. Due to its significant associated mortality and morbidity, diagnostic tools to identify the disease at its early stages are urgently required. Early diagnosis may lead to better outcomes. The gold standard approach for CRC diagnosis is colonoscopy with biopsy. However, it is an invasive process with a risk of complications and discomfort for the patient. Moreover, it is usually performed in symptomatic or high-risk individuals and therefore, asymptomatic patients might be missed. Thus, alternative non-invasive diagnostic techniques are required to improve CRC outcomes. The new era of personalized medicine is identifying novel biomarkers associated with overall survival and clinical outcomes. Recently, liquid biopsy, a minimally invasive analysis of body fluid biomarkers, has gained attention for diagnosis, evaluation of prognosis, and follow-up of patients with CRC. Several previous studies have demonstrated that this novel approach allows for better understanding of CRC tumor biology and leads to an improvement in clinical outcomes. Here, we explain the enrichment and detection methods of circulating biomarkers, including CTCs, ctDNA, miRNA, lncRNA, and circRNA. Furthermore, we provide an overview on their clinical potential as diagnostic, prognostic, and predictive biomarkers for CRC.

Potential Role of Zinc Finger 365 rs10822013 and rs10995190 in Mammographic Density, Sporadic Breast Cancer Risk, and Prognosis.

Background: Despite suggesting many genetic risk markers as the outcome of Genome-wide association studies (GWAS) for breast cancer, replicating the results in different populations has remained the main issue. In this regard, this study assessed the association of two variations in Zinc Finger 365 (ZNF365) in an Iranian population. Methods: In a case-control study conducted at Mashhad University of Medical Sciences, Mashhad, Iran, between 2017 and 2020, ZNF365-rs10822013 and rs10995190 were genotyped using Allele-Specific PCR (AS-PCR). Breast density was assessed using mammography images. PHASE software module version 2 and SPSS version 16.0 were used for haplotype and statistical analyses. Quantitative and qualitative variables were compared between groups using independent t tests and Chi square tests, respectively. Binary logistic regression analysis was performed to calculate odds ratios. Multivariate analysis was then undertaken for the baseline variables, with a P<0.05 in the univariate analysis. The survival analysis was performed using the Kaplan-Meier method and the log-rank test. Results: In this survey, 732 females, including 342 breast cancer patients and 390 healthy subjects, were enrolled. rs10822013-T allele (P=0.014), rs10995190-G allele (P=0.003), and TG haplotype (P=0.002) were significantly associated with the increased risk of breast cancer. Moreover, rs10995190-GG genotype (P=0.042) and C-G haplotype (P=0.019) revealed a significant association with better overall survival. However, considered polymorphisms and their haplotypes indicated no association with breast density and clinical features of breast cancer. Conclusion: ZNF365 variants might be a potential risk marker of breast cancer in the Iranian population. The interaction between alleles in haplotypes may modulate the amount of the risk conferred by these variants. Further studies on different ethnic groups can validate these results.

Genetic contribution of caspase-8 variants and haplotypes to breast cancer risk and prognosis: a case-control study in Iran.

PURPOSE: Multiple genome-wide and candidate-gene association studies have been conducted to search for common risk variants of breast cancer. Recent large meta-analyses and consolidating evidence have highlighted the role of the caspase-8 gene in breast cancer pathogenesis. Therefore, this study aimed to identify common variations and haplotypes associated with risk and overall survival of breast cancer with respect to underlying susceptibility variants in the CASP8 gene region in a group of the Iranian population. METHODS: In a case-control study with a total of 1008 samples (455 cases and 553 controls), genotyping of 12 candidate polymorphisms, consisting of rs3834129, rs2037815, rs7608692, rs12990906, rs3769821, rs6435074, rs3754934, rs3817578, rs10931936, rs1045485, rs1045487, and rs13113, were performed using PCR-based methods, including ARMS-PCR, AS-PCR, RFLP-PCR, HRM-PCR, and TaqMan-PCR. RESULTS: rs3834129, rs3754934, rs12990906, and rs10931936 were associated with the risk and overall survival of breast cancer. Several haplotypes were also identified an associated with a higher risk of breast cancer, including a three-SNP haplotype rs3817578-rs10931936-rs1045485 [p < 0.001, OR = 1.78(1.32-2.41)]. rs3754934-C allele showed an association with a lower risk of death in all patients [p = 0.022; HR = 0.46(0.23-0.89)] and in the hormone-receptor-positive group [p = 0.038; HR = 0.37(0.14-0.95)], as well as CC genotype in the hormone-receptor-positive group [p = 0.002; HR = 0.09(0.02-0.43)]. CONCLUSION: The present study suggests a diagnostic and prognostic role of CASP8 gene variations in breast cancer. The risky haplotypes are likely to have one or more underlying breast cancer susceptibility alleles. Understanding the mode of action of these alleles will aid individual-level risk prediction. It also may help identify at-risk patients to provide them with better surveillance.

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. RESULTS: 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.

Therapeutic Potential of Herbal Medicine against Non-alcoholic Fatty Liver Disease.

Non-alcoholic fatty liver disease (NAFLD) is a common metabolic disorder associated with obesity, diabetes mellitus, dyslipidemia, and cardiovascular disease. A "multiple hit" model has been a widely accepted explanation for the disease's complicated pathogenesis. Despite advances in our knowledge of the processes underlying NAFLD, no conventional pharmaceutical therapy exists. The only currently approved option is to make lifestyle modifications, such as dietary and physical activity changes. The use of medicinal plants in the treatment of NAFLD has recently gained interest. Thus, we review the current knowledge about these agents based on clinical and preclinical studies. Moreover, the association between NAFLD and colorectal cancer (CRC), one of the most common and lethal malignancies, has recently emerged as a new study area. We overview the shared dysregulated pathways and the potential therapeutic effect of herbal medicines for CRC prevention in patients with NAFLD.

Integrated analysis of multi-omics data for the discovery of biomarkers and therapeutic targets for colorectal cancer.

The considerable burden of colorectal cancer and the rising trend in young adults emphasize the necessity of understanding its underlying mechanisms, providing new diagnostic and prognostic markers, and improving therapeutic approaches. Precision medicine is a new trend all over the world and identification of novel biomarkers and therapeutic targets is a step forward towards this trend. In this context, multi-omics data and integrated analysis are being investigated to develop personalized medicine in the management of colorectal cancer. Given the large amount of data from multi-omics approach, data integration and analysis is a great challenge. In this Review, we summarize how statistical and machine learning techniques are applied to analyze multi-omics data and how it contributes to the discovery of useful diagnostic and prognostic biomarkers and therapeutic targets. Moreover, we discuss the importance of these biomarkers and therapeutic targets in the clinical management of colorectal cancer in the future. Taken together, integrated analysis of multi-omics data has great potential for finding novel diagnostic and prognostic biomarkers and therapeutic targets, however, there are still challenges to overcome in future studies.

The therapeutic potential value of Cancer-testis antigens in immunotherapy of gastric cancer.

Gastric cancer (GC) is the fourth most common cause of mortality and the fifth for incidence, globally. Diagnosis, early prognosis, and therapy remains challenging for this condition, and new tumor-associated antigens are required for its detection and immunotherapy. Cancer-testis antigens (CTAs) are a subfamily of tumor-associated antigens (TAAs) that have been identified as potential biomarkers and targets for cancer immunotherapy. The CTAs-restricted expression pattern in tumor cells and their potential immunogenicity identify them as attractive target candidates in CTA-based diagnosis or prognosis or immunotherapy. To date, numerous studies have reported the dysregulation of CTAs in GC. Several clinical trials have been done to assess CTA-based immunotherapeutic potential in the treatment of GC patients. NY-ESO-1, MAGE, and KK-LC-1 have been used in GC clinical trials. We review recent studies that have investigated the potential of the CTAs in GC regarding the expression, function, aggressive phenotype, prognosis, and immunological responses as well as their possible clinical significance as immunotherapeutic targets with a focus on challenges and future interventions.

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.

Machine learning algorithms reveal potential miRNAs biomarkers in gastric cancer.

Gastric cancer is the high mortality rate cancers globally, and the current survival rate is 30% even with the use of combination therapies. Recently, mounting evidence indicates the potential role of miRNAs in the diagnosis and assessing the prognosis of cancers. In the state-of-art research in cancer, machine-learning (ML) has gained increasing attention to find clinically useful biomarkers. The present study aimed to identify potential diagnostic and prognostic miRNAs in GC with the application of ML. Using the TCGA database and ML algorithms such as Support Vector Machine (SVM), Random Forest, k-NN, etc., a panel of 29 was obtained. Among the ML algorithms, SVM was chosen (AUC:88.5%, Accuracy:93% in GC). To find common molecular mechanisms of the miRNAs, their common gene targets were predicted using online databases such as miRWalk, miRDB, and Targetscan. Functional and enrichment analyzes were performed using Gene Ontology (GO) and Kyoto Database of Genes and Genomes (KEGG), as well as identification of protein-protein interactions (PPI) using the STRING database. Pathway analysis of the target genes revealed the involvement of several cancer-related pathways including miRNA mediated inhibition of translation, regulation of gene expression by genetic imprinting, and the Wnt signaling pathway. Survival and ROC curve analysis showed that the expression levels of hsa-miR-21, hsa-miR-133a, hsa-miR-146b, and hsa-miR-29c were associated with higher mortality and potentially earlier detection of GC patients. A panel of dysregulated miRNAs that may serve as reliable biomarkers for gastric cancer were identified using machine learning, which represents a powerful tool in biomarker identification.

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.