Unraveling molecular similarities between colorectal polyps and colorectal cancer: a systems biology approach.

BACKGROUND/AIMS: Colorectal cancer (CRC) and colorectal polyps are intimately linked, with polyps acting as precursors to CRC. Understanding the molecular mechanisms governing their development is crucial for advancing diagnosis and treatment. Employing a systems biology approach, we investigated the molecular similarities between polyp and CRC. METHODS: We analyzed gene expression profiles, protein-protein interactions, transcription factors, and gene ontology to identify common differentially expressed genes (DEGs) and unravel shared molecular pathways. RESULTS: Our analysis revealed 520 commonly dysregulated genes in polyps and CRC, serving as potential biomarkers and pivotal contributors to disease progression. Gene ontology analysis elucidated distinct biological processes associated with upregulated and downregulated DEGs in both conditions, highlighting common pathways, including signal transduction, cell adhesion, and positive regulation of cell proliferation. Moreover, protein-protein interaction networks shed light on subnetworks involved in rRNA processing, positive regulation of cell proliferation, mRNA splicing, and cell division. Transcription factor analysis identified major regulators and differentially expressed transcription factors in polyp and CRC. Notably, we identified common differentially expressed transcription factors, including ZNF217, NR3C1, KLF5, GATA6, and STAT3, with STAT3 and NR3C1 exhibiting increased expression. CONCLUSIONS: This comprehensive analysis enriches our understanding of the molecular mechanisms underlying polyp formation and CRC development, providing potential targets for further investigation and therapeutic intervention. Our findings contribute substantively to crafting personalized strategies for refining the diagnosis and treatment of polyps and CRC.

Cell-cell communication in stem cells and cancer: Alone but in touch.

BACKGROUND: Cellular communication and signaling pathways are fundamental regulators of stem cell and cancer cell behaviors. This review explores the intricate interplay of these pathways in governing cellular behaviors, focusing on their implications for diseases, particularly cancer. OBJECTIVES: This comprehensive review aims to elucidate the significance of cellular signaling pathways in regulating the behavior of stem cells and cancer cells. It delves into the alterations in these pathways, their impact on cell fate, and their implications for developing diseases, notably cancer. The objective is to underscore the importance of understanding these signaling pathways for developing targeted therapeutic strategies. METHODS: The review critically analyzes existing literature and research findings concerning the roles of signaling pathways in stem cell behavior regulation, emphasizing their parallels and disparities in cancer cells. It synthesizes information on both direct and indirect modes of cell communication to delineate the complexity of signaling networks. RESULTS: Direct and indirect modes of cell communication intricately regulate the complex signaling pathways governing stem cell behaviors, influencing differentiation potential and tissue regeneration. Alterations in these pathways significantly impact stem cell fate, contributing to disease pathogenesis, including cancer. Understanding these signaling cascades offers insights into developing targeted therapies, particularly cancer treatment. CONCLUSION: Understanding the regulation of signaling pathways in stem cells and the specialized subset of cancer stem cells holds promise for innovative therapeutic approaches. By targeting aberrant signaling pathways, tailored interventions may improve treatment outcomes. This review underscores the critical role of signaling pathways in cellular behaviors, offering a pathway toward developing novel, more effective therapies for diverse diseases and disorders.

Identification of common factors among fibrosarcoma, rhabdomyosarcoma, and osteosarcoma by network analysis.

Sarcoma cancers are uncommon malignant tumors, and there are many subgroups, including fibrosarcoma (FS), which mainly affects middle-aged and older adults in deep soft tissues. Rhabdomyosarcoma (RMS), on the other hand, is the most common soft-tissue sarcoma in children and is located in the head and neck area. Osteosarcomas (OS) is the predominant form of primary bone cancer among young adults, primarily resulting from sporadically random mutations. This frequently results in the dissemination of cancer cells to the lungs, commonly known as metastasis. Mesodermal cells are the origin of sarcoma cancers. In this study, a rather radical approach has been applied. Instead of comparing homogenous cancer types, we focus on three main subtypes of sarcoma: fibrosarcoma, rhabdomyosarcoma, and osteosarcoma, and compare their gene expression with normal cell groups to identify the differentially expressed genes (DEGs). Next, by applying protein-protein interaction (PPI) network analysis, we determine the hub genes and crucial factors, such as transcription factors (TFs), affected by these types of cancer. Our findings indicate a modification in a range of pathways associated with cell cycle, extracellular matrix, and DNA repair in these three malignancies. Results showed that fibrosarcoma (FS), rhabdomyosarcoma (RMS), and osteosarcoma (OS) had 653, 1270, and 2823 differentially expressed genes (DEGs), respectively. Interestingly, there were 24 DEGs common to all three types. Network analysis showed that the fibrosarcoma network had two sub-networks identified in FS that contributed to the catabolic process of collagen via the G-protein coupled receptor signaling pathway. The rhabdomyosarcoma network included nine sub-networks associated with cell division, extracellular matrix organization, mRNA splicing via spliceosome, and others. The osteosarcoma network has 13 sub-networks, including mRNA splicing, sister chromatid cohesion, DNA repair, etc. In conclusion, the common DEGs identified in this study have been shown to play significant and multiple roles in various other cancers based on the literature review, indicating their significance.

The Epigenetic Regulation of Quiescent in Stem Cells.

This review article discusses the epigenetic regulation of quiescent stem cells. Quiescent stem cells are a rare population of stem cells that remain in a state of cell cycle arrest until activated to proliferate and differentiate. The molecular signature of quiescent stem cells is characterized by unique epigenetic modifications, including histone modifications and deoxyribonucleic acid (DNA) methylation. These modifications play critical roles in regulating stem cell behavior, including maintenance of quiescence, proliferation, and differentiation. The article specifically focuses on the role of histone modifications and DNA methylation in quiescent stem cells, and how these modifications can be dynamically regulated by environmental cues. The future perspectives of quiescent stem cell research are also discussed, including their potential for tissue repair and regeneration, their role in aging and age-related diseases, and their implications for cancer research. Overall, this review provides a comprehensive overview of the epigenetic regulation of quiescent stem cells and highlights the potential of this research for the development of new therapies in regenerative medicine, aging research, and cancer biology.

Machine learning and deep learning techniques for breast cancer diagnosis and classification: a comprehensive review of medical imaging studies.

BACKGROUND: Breast cancer is a major public health concern, and early diagnosis and classification are critical for effective treatment. Machine learning and deep learning techniques have shown great promise in the classification and diagnosis of breast cancer. PURPOSE: In this review, we examine studies that have used these techniques for breast cancer classification and diagnosis, focusing on five groups of medical images: mammography, ultrasound, MRI, histology, and thermography. We discuss the use of five popular machine learning techniques, including Nearest Neighbor, SVM, Naive Bayesian Network, DT, and ANN, as well as deep learning architectures and convolutional neural networks. CONCLUSION: Our review finds that machine learning and deep learning techniques have achieved high accuracy rates in breast cancer classification and diagnosis across various medical imaging modalities. Furthermore, these techniques have the potential to improve clinical decision-making and ultimately lead to better patient outcomes.

A comprehensive analysis of transcriptomic data for comparison of plants with different photosynthetic pathways in response to drought stress.

The main factor leading to a decrease in crop productivity is abiotic stresses, particularly drought. Plants with C4 and CAM photosynthesis are better adapted to drought-prone areas than C3 plants. Therefore, it is beneficial to compare the stress response of plants with different photosynthetic pathways. Since most crops are C3 and C4 plants, this study focused on conducting an RNA-seq meta-analysis to investigate and compare how C3 and C4 plants respond to drought stress at the gene expression level in their leaves. Additionally, the accuracy of the meta-analysis results was confirmed with RT-qPCR. Based on the functional enrichment and network analysis, hub genes related to ribosomal proteins and photosynthesis were found to play a potential role in stress response. Moreover, our findings suggest that the low abundant amino acid degradation pathway, possibly through providing ATP source for the TCA cycle, in both groups of plants and the activation of the OPPP pathway in C4 plants, through providing the electron source required by this plant, can help to improve drought stress tolerance.

Zbp1 gene: a modulator of multiple aging hallmarks as potential therapeutic target for age-related diseases.

The Zbp1 gene has recently emerged as a potential therapeutic target for age-related diseases. Multiple studies have reported that Zbp1 plays a key role in regulating several aging hallmarks, including cellular senescence, chronic inflammation, DNA damage response, and mitochondrial dysfunction. Regarding cellular senescence, Zbp1 appears to regulate the onset and progression of senescence by controlling the expression of key markers such as p16INK4a and p21CIP1/WAF1. Similarly, evidence suggests that Zbp1 plays a role in regulating inflammation by promoting the production of pro-inflammatory cytokines, such as IL-6 and IL-1ß, through activation of the NLRP3 inflammasome. Furthermore, Zbp1 seems to be involved in the DNA damage response, coordinating the cellular response to DNA damage by regulating the expression of genes such as p53 and ATM. Additionally, Zbp1 appears to regulate mitochondrial function, which is crucial for energy production and cellular homeostasis. Given the involvement of Zbp1 in multiple aging hallmarks, targeting this gene represents a potential strategy to prevent or treat age-related diseases. For example, inhibiting Zbp1 activity could be a promising approach to reduce cellular senescence and chronic inflammation, two critical hallmarks of aging associated with various age-related diseases. Similarly, modulating Zbp1 expression or activity could also improve DNA damage response and mitochondrial function, thus delaying or preventing the development of age-related diseases. Overall, the Zbp1 gene appears to be a promising therapeutic target for age-related diseases. In the current review, we have discussed the molecular mechanisms underlying the involvement of Zbp1 in aging hallmarks and proposed to develop effective strategies to target this gene for therapeutic purposes.

Common factors among three types of cells aged in mice.

The greatest risk factor for the formation of numerous significant chronic disorders is aging. Understanding the core molecular underpinnings of aging can help to slow down the inevitable process. Systematic study of gene expression or DNA methylation data is possible at the transcriptomics and epigenetics levels. DNA methylation and gene expression are both affected by aging. Gene expression is an important element in the aging of Homo sapiens. In this work, we evaluated the expression of differentially expressed genes (DEGs), proteins, and transcription factors (TFs) in three different types of cells in mice: antibody-secreting cells, cardiac mesenchymal stromal cells, and skeletal muscle cells. The goal of this article is to uncover a common cause during aging among these cells in order to increase understanding about establishing complete techniques for preventing aging and improving people's quality of life. We conducted a comprehensive network-based investigation to establish which genes and proteins are shared by the three different types of aged cells. Our findings clearly indicated that aging induces gene dysregulation in immune, pharmacological, and apoptotic pathways. Furthermore, our research developed a list of hub genes with differential expression in aging responses that should be investigated further to discover viable anti-aging treatments.

The regulatory landscape of neurite development in Caenorhabditis elegans.

Neuronal communication requires precise connectivity of neurite projections (axons and dendrites). Developing neurites express cell-surface receptors that interpret extracellular cues to enable correct guidance toward, and connection with, target cells. Spatiotemporal regulation of neurite guidance molecule expression by transcription factors (TFs) is critical for nervous system development and function. Here, we review how neurite development is regulated by TFs in the Caenorhabditis elegans nervous system. By collecting publicly available transcriptome and ChIP-sequencing data, we reveal gene expression dynamics during neurite development, providing insight into transcriptional mechanisms governing construction of the nervous system architecture.

Identification of key genes and molecular mechanisms associated with temperature stress in lentil.

Extreme temperature is one of the serious threats to crop production in present and future scenarios of global climate changes. Lentil (Lens culinaris) is an important crop, and there is a serious lack of genetic information regarding environmental and temperature stresses responses. This study is the first report of evaluation of key genes and molecular mechanisms related to temperature stresses in lentil using the RNA sequencing technique. De novo transcriptome assembly created 44,673 contigs and differential gene expression analysis revealed 7494 differentially expressed genes between the temperature stresses and control group. Basic annotation of generated transcriptome assembly in our study led to the identification of 2765 novel transcripts that have not been identified yet in lentil genome draft v1.2. In addition, several unigenes involved in mechanisms of temperature sensing, calcium and hormone signaling and DNA-binding transcription factor activity were identified. Also, common mechanisms in response to temperature stresses, including the proline biosynthesis, the photosynthetic light reactions balancing, chaperone activity and circadian rhythms, are determined by the hub genes through the protein-protein interaction networks analysis. Deciphering the mechanisms of extreme temperature tolerance would be a new way for developing crops with enhanced plasticity against climate change. In general, this study has identified set of mechanisms and various genes related to cold and heat stresses which will be useful in better understanding of the lentil's reaction to temperature stresses.

Identification and profiling of conserved microRNAs in different developmental stages of crown imperial (Fritillaria imperialis L.) using high-throughput sequencing.

BACKGROUND: Novel strategies for improvement of ornamental plants and their properties relay on miRNA control of differential plant gene expression modulation. Still, in response to the same abiotic stresses, some conserved miRNA families show different expression patterns in different plant species. In parallel, the use of deep sequencing technologies reveals new levels of complexity of regulatory networks in plants through identification of new miRNAs. METHODS AND RESULTS: Fritillaria imperialis plants were collected from their natural habitats in Koohrang, Chaharmahal va Bakhtiari, Iran. Several tissues including stamen, pistil, petal, sepal, leaf, stem, bulb and fruit were collected during three developmental stages (stem elongation, flower development and seed head stages). Using RNAseq and qRT-PCR approach, this research revealed 21 conserved miRNAs, matching 15 miRNA families, in Fritilaria imperialis. CONCLUSIONS: The expression of seven conserved miRNAs (Fim-miR156b, Fim-miR159, Fim-miR166a-5p, Fim-miR169d-5p, Fim-miR171c, Fim-miR393 and Fim-miR396e-3p) was further investigated in different tissues and three developmental stages, suggesting different roles for these miRNAs during growth and development of crown imperial. Gained knowledge from this research can open the door to find efficient ways to secure crown imperial survival, preservation and utilization and if proven useful may be applied in other plant species as well.

Dynamics of transcription regulatory network during mice-derived retina organoid development.

The retina is a complex system containing several neuron types arranged in distinct layers. Many aspects of the retina's development and the molecular events in the human light-sensing system have been previously unveiled. However, there is limited information about regulatory networks governing the transitional stages during retina development. To address this issue, we have studied the transcriptome dynamics of mice-derived retinal organoid development in 10 successive time-points, from stem cell to functional retina. For the first time, we have identified the main modules of genes related to different stages of development and predicted all possible transcription factors. A major shift in the transcriptome occurs during the transition of cells from D0 to D10 and again at the late stages of retina development. Transcription, nervous system development, cell cycle, neurotransmitter transport, glycosylation, and lipid metabolisms are the most important biological processes during retina development. Altogether, we have identified and reported 15 TFs, including Irx2, Irx3, Lmo2, Tead2, Tbx20, and Zeb1, which are potentially involved in the regulation of retinal organoid development. In conclusion, using several rigorous analyses, we have found main stage-specific biological processes in the retina development and predicted TFs with strong potency in controlling this structure.

Survival prognostic factors in patients with acute myeloid leukemia using machine learning techniques.

This paper identifies prognosis factors for survival in patients with acute myeloid leukemia (AML) using machine learning techniques. We have integrated machine learning with feature selection methods and have compared their performances to identify the most suitable factors in assessing the survival of AML patients. Here, six data mining algorithms including Decision Tree, Random Forrest, Logistic Regression, Naive Bayes, W-Bayes Net, and Gradient Boosted Tree (GBT) are employed for the detection model and implemented using the common data mining tool RapidMiner and open-source R package. To improve the predictive ability of our model, a set of features were selected by employing multiple feature selection methods. The accuracy of classification was obtained using 10-fold cross-validation for the various combinations of the feature selection methods and machine learning algorithms. The performance of the models was assessed by various measurement indexes including accuracy, kappa, sensitivity, specificity, positive predictive value, negative predictive value, and area under the ROC curve (AUC). Our results showed that GBT with an accuracy of 85.17%, AUC of 0.930, and the feature selection via the Relief algorithm has the best performance in predicting the survival rate of AML patients.

Dissecting the molecular responses of lentil to individual and combined drought and heat stresses by comparative transcriptomic analysis.

Lentil cultivation could be challenged by combined heat and drought stress in semi-arid regions. We used RNA-seq approach to profile transcriptome changes of Lens culinaris exposed to individual and combined heat and drought stresses. It was determined that most of the differentially expressed genes observed in response to combined stress, could not be identified by analysis of transcriptome exposed to corresponding individual stresses. Interestingly, this study results revealed that the expression of ribosome generation and protein biosynthesis and starch degradation pathways related genes were uniquely up-regulated under the combined stress. Although multiple genes related to antioxidant activity were up-regulated in response to all stresses, variation in types and expression levels of these genes under the combined stress were higher than that of individual stresses. Using this comparative approach, for the first time, we reported up-regulation of several TF, CDPK, CYP, and antioxidant genes in response to combined stress in plants.

The clinical significance of circulating DSCAM-AS1 in patients with ER-positive breast cancer and construction of its competitive endogenous RNA network.

Long Non-Coding RNAs (lncRNAs), with diagnostic and therapeutic applications in malignancies, are newly described tumour-related molecules. Here, we reported the importance of circulating DSCAM-AS1 as the biomarker to detect Estrogen Receptor (ER)-positive breast cancer (BC) cases. Moreover, the expression of a BC-associated lncRNAs, namely DSCAM-AS1, was measured in tumoural and Paired Adjacent Non-Tumoral (PANT) tissue, as well as plasma, using Real-Time Polymerase Chain Reaction (RT-PCR). Besides, the correlations between gene expression and the clinicopathological features were analyzed. The diagnostic power of circulating DSCAM-AS1 in BC was estimated using the Area Under the Curve (AUC) value. Furthermore, we studied the DSCAM-AS1 associated with the network of competitive endogenous RNA (ceRNA) in BC using the literature review and in silico analysis. We found a significant increase in the expression levels of lncRNA in the tumour (P < 0.001) and in plasma (P < 0.001) of ER-positive BC patients. The sensitivity and specificity of DSCAM-AS1 in plasma for detection of BC from healthy controls were 100 and 97%, respectively (AUC = 0.98, P < 0.001). Accordingly, we suggest an elevated level of circulating DSCAM-AS1 as a candidate biomarker of ER-positive BC patients. Moreover, perturbation of DSCAM-AS1, as a ceRNA, acts in the tumor progression and drug resistance by affecting different cell signaling.

System-level responses to cisplatin in pro-apoptotic stages of breast cancer MCF-7 cell line.

Cisplatin ceases cell division and induces apoptosis in cancer cell lines. It is well established that cisplatin alters the expression of many genes involved in several cellular processes and pathways including transcription, p53 signaling pathway, and apoptosis. However, system-wide responses to cisplatin in breast cancer cell lines have not been studied. Therefore, we have used a network analysis approach to unveil such responses at early stages of drug treatment. To do this, we have first identified those genes that are responding to cisplatin treatment in MCF-7 cell line. Network and gene ontology analyses were then employed to uncover the molecular pathways affected by cisplatin treatment. Then the results obtained from cisplatin-treated MCF7 cell line were compared to those obtained from other cancer cell lines at comparable time points. In conclusion, we found that ADCY9, GSK3B, MAPK14, NCK1, NCOA2, PIK3CA, PIK3CB, PTK2, RHOB act as hub genes in the cisplatin-responsive regulatory network at the pro-apoptotic stages. The results could be useful in finding new drugs to target these genes in order to obtain similar responses.

Caenorhabditis elegans hub genes that respond to amyloid beta are homologs of genes involved in human Alzheimer's disease.

The prominent characteristic of Alzheimer's disease (AD) is the accumulation of amyloid beta (Abeta) proteins in the form of plaques that cause molecular and cellular alterations in the brain. Due to the paucity of brain samples of early-stage Abeta aggregation, animal models have been developed to study early events in AD. Caenorhabditis elegans is a genetically tractable animal model for AD. Here, we used transcriptomic data, network-based protein-protein interactions and weighted gene co-expression network analysis (WGCNA), to detect modules and their gene ontology in response to Abeta aggregation in C. elegans. Additionally, hub genes and their orthologues in human and mouse were identified to study their relation to AD. We also found several transcription factors (TFs) responding to Abeta accumulation. Our results show that Abeta expression in C. elegans relates to general processes such as molting cycle, locomotion, and larval development plus AD-associated processes, including protein phosphorylation, and G-protein coupled receptor-regulated pathways. We reveal that many hub genes and TFs including ttbk-2, daf-16, and unc-49 have human and mouse orthologues that are directly or potentially associated with AD and neural development. In conclusion, using systems biology we identified important genes and biological processes in C. elegans that respond to Abeta aggregation, which could be used as potential diagnostic or therapeutic targets. In addition, because of evolutionary relationship to AD in human, we suggest that C. elegans is a useful model for studying early molecular events in AD.

Genome imprinting in stem cells: A mini-review.

Genomic imprinting is an epigenetic process result in silencing of one of the two alleles (maternal or paternal) based on the parent of origin. Dysregulation of imprinted genes results in detectable developmental and differential abnormalities. Epigenetics erasure is required for resetting the cell identity to a ground state during the production of induced pluripotent stem (iPS) cells from somatic cells. There are some contradictory reports regarding the status of the imprinting marks in the genome of iPS cells. Additionally, many studies highlighted the existence of subtle differences in the imprinting loci between different types of iPS cells and embryonic stem (ES) cells. These observations could ultimately undermine the use of patient-derived iPS cells for regenerative medicine.

Characterization of bovine (Bos taurus) imprinted genes from genomic to amino acid attributes by data mining approaches.

Genomic imprinting results in monoallelic expression of genes in mammals and flowering plants. Understanding the function of imprinted genes improves our knowledge of the regulatory processes in the genome. In this study, we have employed classification and clustering algorithms with attribute weighting to specify the unique attributes of both imprinted (monoallelic) and biallelic expressed genes. We have obtained characteristics of 22 known monoallelically expressed (imprinted) and 8 biallelic expressed genes that have been experimentally validated alongside 208 randomly selected genes in bovine (Bos taurus). Attribute weighting methods and various supervised and unsupervised algorithms in machine learning were applied. Unique characteristics were discovered and used to distinguish mono and biallelic expressed genes from each other in bovine. To obtain the accuracy of classification, 10-fold cross-validation with concerning each combination of attribute weighting (feature selection) and machine learning algorithms, was used. Our approach was able to accurately predict mono and biallelic genes using the genomics and proteomics attributes.

Regulatory networks upon neurogenesis induction in PC12 cell line by small molecules.

Alteration in the normal regulatory pathway of differentiation can lead to the induction of programmed cell death. Accordingly, some chemicals like staurosporine, nerve growth factor, pituitary adenylate cyclase activating peptide, and trimethyltin are shown to be able to induce differentiation in vitro, via different mechanisms in the PC12 cell line. Hence, understanding the details of the molecular mechanisms of differentiation induction by these small molecules are important for further application of these molecules in neurogenesis. Therefore, we sought to determine these signaling pathways, using gene regulatory networks analysis. Then, we have conducted a comparative analysis of the alterations in the gene expression pattern of the PC12 cell lines in response to these chemicals at the early stages. Based on the comparative analysis and previous knowledge, we have proposed the affected pathways during differentiation and apoptosis. Our findings could be useful in the development of protocols to reprogramming of neurons by such small molecules with high efficiency.