Cross-platform gene expression profiling of breast cancer: Exploring the relationship between breast cancer grades and gene expression pattern.

Gene expression profiling is a powerful tool that has been extensively used to investigate the underlying biology and etiology of diseases, including cancer. Microarray gene expression analysis enables simultaneous measurement of thousands of mRNA levels. Sophisticated computational approaches have evolved in parallel with the rapid progress in bioassay technologies, enabling more effective analysis of the large and complex datasets that these technologies produce. In this study, we utilized systems biology approaches to examine gene expression profiles across different grades of breast cancer progression. We conducted a meta-analysis of publicly available microarray data to elucidate the molecular mechanisms underlying breast cancer grade classification. Our results suggest that while grade index is commonly used for evaluating cancer progression status in the clinic, the complexity of molecular mechanisms, histological characteristics, and other factors related to patient outcomes raises doubts about the utility of breast cancer grades as a foundation for formulating treatment protocols. Our study underscores the importance of advancing personalized strategies for breast cancer classification and management. More research is crucial to refine diagnostic tools and treatment modalities, aiming for greater precision and tailored care in patient outcomes.

The Reticulon-4 3-bp Deletion/Insertion Polymorphism Is Associated with Structural mRNA Changes and the Risk of Breast Cancer: A Population-Based Case-Control Study with Bioinformatics Analysis.

Breast cancer (BC) is a complex disease caused by molecular events that disrupt cellular survival and death. Discovering novel biomarkers is still required to better understand and treat BC. The reticulon-4 (RTN4) gene, encoding Nogo proteins, plays a critical role in apoptosis and cancer development, with genetic variations affecting its function. We investigated the rs34917480 in RTN4 and its association with BC risk in an Iranian population sample. We also predicted the rs34917480 effect on RTN4 mRNA structure and explored the RTN4's protein-protein interaction network (PPIN) and related pathways. In this case-control study, 437 women (212 BC and 225 healthy) were recruited. The rs34917480 was genotyped using AS-PCR, mRNA secondary structure was predicted with RNAfold, and PPIN was constructed using the STRING database. Our findings revealed that this variant was associated with a decreased risk of BC in heterozygous (p = 0.012), dominant (p = 0.015), over-dominant (p = 0.017), and allelic (p = 0.035) models. Our prediction model showed that this variant could modify RTN4's mRNA thermodynamics and potentially its translation. RTN4's PPIN also revealed a strong association with apoptosis regulation and key signaling pathways highly implicated in BC. Consequently, our findings, for the first time, demonstrate that rs34917480 could be a protective factor against BC in our cohort, probably via preceding mechanisms.

Omics Integration Analysis Unravel the Landscape of Driving Mechanisms of Colorectal Cancer.

Colorectal cancer (CRC) is one of the most malignant cancers and results in a substantial rate of morbidity and mortality. Diagnosis of this malignancy in early stages increases the chance of effective treatment. High-throughput data analyses reveal omics signatures and also provide the possibility of developing computational models for early detection of this disease. Such models would be able to use as complementary tools for early detection of different types of cancers including CRC. In this study, using gene expression data, the Flux balance analysis (FBA) applied to decode metabolic fluxes in cancer and normal cells. Moreover, transcriptome and genome analyses revealed driver agents of CRC in a biological network scheme. By applying comprehensive publicly available data from TCGA, different aspect of CRC regulome including the regulatory effect of gene expression, methylation, microRNA, copy number aberration and point mutation profile over protein levels investigated and the results provide a regulatory picture underlying CRC. Compiling omics profiles indicated snapshots of changes in different omics levels and flux rate of CRC. In conclusion, considering obtained CRC signatures and their role in biological operating systems of cells, the results suggest reliable driver regulatory modules that could potentially serve as biomarkers and therapeutic targets and furthermore expand our understanding of driving mechanisms of this disease.
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Omics Integration Analyses Reveal the Early Evolution of Malignancy in Breast Cancer.

The majority of cancer evolution studies involve individual-based approaches that neglect the population dynamics necessary to build a global picture of cancer evolution for each cancer type. Here, we conducted a population-based study in breast cancer to understand the timing of malignancy evolution and its correlation to the genetic evolution of pathological stages. In an omics integrative approach, we integrated gene expression and genomic aberration data for pre-invasive (ductal carcinoma in situ; DCIS, early-stage) and post-invasive (invasive ductal carcinoma; IDC, late-stage) samples and investigated the evolutionary role of further genetic changes in later stages compared to the early ones. We found that single gene alterations (SGAs) and copy-number alterations (CNAs) work together in forward and backward evolution manners to fine-tune the signaling pathways operating in tumors. Analyses of the integrated point mutation and gene expression data showed that (i) our proposed fine-tuning concept is also applicable to metastasis, and (ii) metastases sometimes diverge from the primary tumor at the DCIS stage. Our results indicated that the malignant potency of breast tumors is constant over the pre- and post-invasive pathological stages. Indeed, further genetic alterations in later stages do not establish de novo malignancy routes; however, they serve to fine-tune antecedent signaling pathways.

Selection of a fully human single domain antibody specific to Helicobacter pylori urease.

Helicobacter pylori bacteria are involved in gastroduodenal disorders, including gastric adenocarcinoma. Since the current therapies encounter with some significant shortcomings, much attention has been paid to the development of new alternative diagnostic and treatment modalities such as immunomedicines to target H. pylori. Having used phage display technology, we isolated fully humane small antibody (Ab) fragment (VL) against the Flap region of urease enzyme of H. pylori to suppress its enzymatic activity. Solution biopanning (SPB) and screening process against a customized biotinylated peptide corresponding to the enzyme Flap region resulted in the selection of VL single domain Abs confirmed by the enzyme-linked immunosorbent assay (ELISA), sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), and Western blotting. The selected Ab fragments showed a high affinity with a KD value of 97.8 × 10-9 and specificity to the enzyme with high inhibitory impact. For the first time, a VL single domain Ab was isolated by SPB process against a critical segment of H. pylori urease using a diverse semi-synthetic library. Based on our findings, the selected VL Ab fragments can be used for the diagnosis, imaging, targeting, and/or immunotherapy of H. pylori. Further, Flap region shows great potential for vaccine therapy.

Evaluation of 4-bp insertion/deletion polymorphism within the 3'UTR of SGSM3 in bladder cancer using mismatch PCR-RFLP method: A preliminary report.

The small G protein signaling modulator 3 (SGSM3) has been shown to be associated with small G-protein-coupled receptor signaling. There is little data regarding the impact of SGSM3 polymorphisms on cancer risk. In the present study, we aimed to evaluate the impact of 4-bp insertion/deletion (rs56228771) polymorphism in the 3'UTR of SGSM3 and susceptibility to bladder cancer in a sample of the Iranian population. This case-control study included 143 pathologically confirmed bladder cancer patients and 144 healthy subjects. The SGSM3 4-bp ins/del (rs56228771) variant was determined by mismatch PCR-RFLP. The findings showed that ins/del genotype and ins allele of SGSM3 4-bp ins/del polymorphism significantly increased the risk of bladder cancer (OR = 3.11, 95%CI = 1.70-5.71, P < 0.0001 and OR = 2.11, 95%CI = 1.27-3.52, P = 0.004, respectively). Our findings support an association between 4-bp ins/del polymorphism in the 3'UTR of SGSM3 and the risk of bladder cancer in an Iranian population. Additional studies with larger sample sizes and diverse ethnicities are warranted to establish if such an association exists in general.

4-bp insertion/deletion (rs3783553) polymorphism within the 3'UTR of IL1A contributes to the risk of prostate cancer in a sample of Iranian population.

Growing evidence demonstrated the presence of an association between IL1A rs3783553 polymorphism and the risk of various cancers. We aimed to evaluate whether the 4-bp insertion/deletion polymorphism (rs3783553) within the 3' untranslated region (3'UTRs) of IL1A was associated to the risk of prostate cancer (PCa) in a sample of Iranian population. A case-control study, including 150 prostate cancer patients and 155 healthy men, was done to examine the possible association between IL1A 4-bp ins/del polymorphism and PCa risk in a sample of southeast Iranian population. Mismatched polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) was designed for genotyping the studied variant. Our findings showed that 4-bp ins/del polymorphism significantly increased the risk of PCa in codominant, recessive and allelic inheritance model. We also evaluated the association between the IL1A 4-bp ins/del polymorphism and clinicopathological characteristics of the patients, and found a significant association between 4-bp ins/del variant and stage, perineural invasion and surgical margin of tumor samples. Bioinformatics analysis revealed that the ins/del variant affected the IL1A mRNA stability leading to a structural shift in IL1A mRNA and has-miR-125a-3p hybrid. In conclusion, our findings proposed an association between IL1A 4-bp ins/del polymorphism and PCa risk. Additional studies with enlarged sample size and diverse ethnicities are required to validate our finding.

A Systems Biology Approach Provides Deeper Insights into Differentially Expressed Genes in Taxane-Anthracycline Chemoresistant and Non-Resistant Breast Cancers

Objective: To date, numerous studies have been conducted to search for reasons for chemoresistance and differences in survival rates of patients receiving chemotherapy. We have sought to identify differentially expressed genes (DEGs) between predicted chemotherapy resistance and sensitive phenotypes by a network as well as gene enrichment approach. Methods: Functional modules were explored with network analysis of DEGs in predicted neoadjuvant taxane-anthracycline resistance versus sensitive cases in the GSE25066 dataset, including 508 samples. A linear model was created by limma package in R to establish DEGs. Results: A gene set related to phagocytic vesicle membrane was found to be up-regulated in chemoresistance samples. Also, we found GO_CYTOKINE_ACTIVITY and GO_GROWTH_FACTOR BINDING to be up-regulated gene sets with the chemoresistance phenotype. Growth factors and cytokines are two groups of agents that induce the immune system to recruit APCs and promote tolerogenic phagocytosis. Some hub nodes like S100A8 were found to be important in the chemoresistant tumor cell network with associated high rank genes in GSEA. Conclusions: Functional gene sets and hub nodes could be considered as potential treatment targets. Moreover, by screening and enrichment analysis of a chemoresistance network, ligands and chemical agents have been found that could modify significant gene sets like the phagocytic vesicle membrane functional gene set as a key to chemoresistance. They could also impact on down- or up-regulated hub nodes.