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In recent years, the incidence of breast cancer has gradually increased, and the research on it has become a hot spot in the scientific community. Central neurons play an important role in breast cancer. This study aims to explore the application of gene expression profile data mining in the study of shared function between central neurons and breast cancer, and focuses on the expression of EMID1 protein antibody. The study collected biomedical images and gene expression profile data of breast cancer patients. Then, we use image processing and analysis technology to extract and analyze features of biomedical images to obtain quantitative features of breast cancer. Gene expression profile data were preprocessed and analyzed to obtain information about breast cancer related genes. Integrating and fusing biomedical images and gene expression profile data, and exploring the sharing function between central neurons and breast cancer through data mining algorithms and statistical analysis methods. The results showed that the expression of EMID1 protein was high in breast cancer tissues, and the expression pattern was similar to that of central neurons. Further functional studies have shown that EMID1 protein is involved in the regulation of proliferation and invasion of breast cancer cells. By regulating the expression level of EMID1 protein, we observed that the proliferation and invasion ability of breast cancer cells were significantly affected. The research results show that through the comprehensive analysis of biomedical images and gene expression profile data, we found the sharing function between central neurons and breast cancer. The central neuronal cell marker genes EMID1 and GREB1L may be used as key biomarkers to regulate the pathogenesis of breast cancer and affect the occurrence and development of breast cancer.
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Background: Tumor tissue origin detection is of great importance in determining the appropriate course of treatment for cancer patients. Classifiers based on gene expression and DNA methylation profiles have been confirmed to be feasible and reliable to predict the tumor primary. However, few works have been performed to compare the performance of these classifiers based on different profiles. Methods: Using gene expression and DNA methylation profiles from The Cancer Genome Atlas (TCGA) project, eight machine learning methods were employed for the tumor tissue origin detection. We then evaluated the predictive performance using DNA methylation, mRNA, microRNA (miRNA) and long non-coding RNA (lncRNA) expression profiles in a comparative manner. A statistical method was introduced to select the most informative CpG sites. Results: We found that LASSO is the most predictive models based on various profiles. Further analyses indicated that the results derived from DNA methylation (overall accuracy: 97.77%) are better than those derived from mRNA expression (overall accuracy: 88.01%), microRNA expression (overall accuracy: 91.03%) and lncRNA expression (overall accuracy: 95.7%). It has been suggested that we can achieve an overall accuracy >90% using only 1,000 methylated CpG sites for prediction. Conclusion: In this work, we comprehensively evaluated the performance of classifiers based on different profiles for the tumor origin detection. Our findings demonstrated the effectiveness of DNA methylation as biomarker for tracing tumor tissue origin using LASSO and neural network.
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Non-neoplastic bone marrow disorders are main causes of non-regenerative anemia in dogs. Despite the high incidence of the diseases, their molecular pathophysiology has not been elucidated. We previously reported that Miniature Dachshund (MD) was a predisposed breed to be diagnosed with non-neoplastic bone marrow disorders in Japan, and immunosuppressive treatment-resistant MDs showed higher number of platelets and morphological abnormalities in peripheral blood cells. These data implied that treatment-resistant MDs might possess distinct pathophysiological features from treatment-responsive MDs. Therefore, we conducted transcriptomic analysis of bone marrow specimens to investigate the pathophysiology of treatment-resistant MDs. Transcriptomic analysis comparing treatment-resistant MDs and healthy control dogs identified 179 differentially expressed genes (DEGs). Pathway analysis using these DEGs showed that "Wnt signaling pathway" was a significantly enriched pathway. We further examined the expression levels of DEGs associated with Wnt signaling pathway and confirmed the upregulation of AXIN2 and CCND2 and the downregulation of SFRP2 in treatment-resistant MDs compared with treatment-responsive MDs and healthy control dogs. This alteration implied the activation of Wnt signaling pathway in treatment-resistant MDs. The activation of Wnt signaling pathway has been reported in human patients with myelodysplastic syndrome (MDS), which is characterized by dysplastic features of blood cells. Therefore, the results of this study implied that treatment-resistant MDs have distinct molecular pathological features from treatment-responsive MDs and the pathophysiology of treatment-resistant MDs might be similar to that of human MDS patients.
Subject(s)
Dog Diseases , Gene Expression Profiling , Dogs , Animals , Dog Diseases/genetics , Dog Diseases/pathology , Gene Expression Profiling/veterinary , Bone Marrow/pathology , Myelodysplastic Syndromes/veterinary , Myelodysplastic Syndromes/genetics , Myelodysplastic Syndromes/pathology , Transcriptome , Male , Female , Wnt Signaling Pathway , Bone Marrow Diseases/veterinary , Bone Marrow Diseases/genetics , Bone Marrow Diseases/pathologyABSTRACT
Soybean production is significantly impacted by Phytophthora root rot (PRR), which is caused by Phytophthora sojae. The nucleotide-binding leucine-rich repeat (NLR) gene family plays a crucial role in plant disease resistance. However, current understanding of the function of soybean NLR genes in resistance to PRR is limited. To address this knowledge gap, transgenic soybean plants overexpressing the NLR gene (Glyma.18g283200) were generated to elucidate the molecular mechanism of resistance. Here, transcript changes and metabolic differences were investigated at three time points (12, 24, and 36 h) after P. sojae infection in hypocotyls of two soybean lines, Dongnong 50 (susceptible line, WT) and Glyma.18g283200 overexpression line (resistant line, OE). Based on the changes in differentially expressed genes (DEGs) in response to P. sojae infection in different lines and at different time points, it was speculated that HOPZ-ACTIVATED RESISTANCE 1 (ZAR1), valine, leucine, and isoleucine degradation, and phytohormone signaling may be involved in the defense response of soybean to P. sojae at the transcriptome level by GO term and KEGG pathway enrichment analysis. Differentially accumulated metabolites (DAMs) analysis revealed that a total of 223 and 210 differential metabolites were identified in the positive ion (POS) and negative ion (NEG) modes, respectively. An integrated pathway-level analysis of transcriptomics (obtained by RNA-seq) and metabolomics data revealed that isoflavone biosynthesis was associated with disease resistance. This work provides valuable insights that can be used in breeding programs aiming to enhance soybean resistance against PRR.
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The East Asian common octopus (Octopus sinensis) is an economically important species among cephalopods. This species exhibits a strict dioecious and allogamous reproductive strategy, along with a phenotypic sexual dimorphism, where the third right arm differentiates into hectocotylus in males. However, our understanding of the molecular mechanisms that underlie sex determination and differentiation in this species remains limited. In the present study, we surveyed gene-expression profiles in the immature male and female gonads of O. sinensis based on the RNA-seq, and a total of 47.83 Gb of high-quality data were generated. Compared with the testis, we identified 8302 differentially expressed genes (DEGs) in the ovary, of which 4459 genes were up-regulated and 3843 genes were down-regulated. Based on the GO enrichment, many GO terms related to sex differentiation were identified, such as sex differentiation (GO: 0007548), sexual reproduction (GO: 0019953) and male sex differentiation (GO: 0046661). A KEGG classification analysis identified three conserved signaling pathways that related to sex differentiation, including the Wnt signaling pathway, TGF-ß signaling pathway and Notch signaling pathway. Additionally, 21 sex-related DEGs were selected, of which 13 DEGs were male-biased, including Dmrt1, Foxn5, Foxj1, Sox30, etc., and 8 DEGs were female-biased, including Sox14, Nanos3, ß-tubulin, Suh, etc. Ten DEGs were used to verify the expression patterns in the testis and ovary using the RT-qPCR method, and the results showed that the expression level shown by RT-qPCR was consistent with that from the RNA-seq, which confirmed the reliability of the transcriptome data. The results presented in this study will not only contribute to our understanding of sex-formation mechanisms in O. sinensis but also provide the foundational information for further investigating the molecular mechanisms that underline its gonadal development and facilitate the sustainable development of octopus artificial breeding.
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Octopodiformes , Sex Differentiation , Transcriptome , Animals , Female , Male , Octopodiformes/genetics , Sex Differentiation/genetics , Transcriptome/genetics , Ovary/metabolism , Ovary/growth & development , Testis/metabolism , Testis/growth & development , Signal Transduction/genetics , Gene Expression Profiling/methods , Sex Determination Processes/genetics , East Asian PeopleABSTRACT
BACKGROUND: A subset of patients affected by cutaneous squamous cell carcinoma (cSCC) can exhibit locally invasive or metastatic tumors. Different staging classification systems are currently in use for cSCC. However, precise patient risk stratification has yet to be reached in clinical practice. The study aims to identify specific histological and molecular parameters characterizing metastatic cSCC. METHODS: Patients affected by metastatic and non-metastatic cSCC (controls) were included in the present study and matched for clinical and histological characteristics. Skin samples from primary tumors were revised for several histological parameters and also underwent gene expression profiling with a commercially available panel testing 770 different genes. RESULTS: In total, 48 subjects were enrolled in the study (24 cases, 24 controls); 67 genes were found to be differentially expressed between metastatic and non-metastatic cSCC. Most such genes were involved in immune regulation, skin integrity, angiogenesis, cell migration and proliferation. CONCLUSION: The combination of histological and molecular profiles of cSCCs allows the identification of features specific to metastatic cSCC, with potential implications for more precise patient risk stratification.
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Background: Allergic rhinitis (AR) is a widespread allergic airway disease that results from a complex interplay between genetic and environmental factors and affects approximately 10%-40% of the global population. Pollen is a common allergen, and exposure to pollen can cause epigenetic changes. However, the mechanism underlying pollen-induced DNA methylation changes and their potential effects on the allergic march are still unclear. The purpose of this study was to explore the methylation-driven mechanisms of AR during the pollen and non-pollen seasons using bioinformatics analysis and to investigate their relationship with asthma. Methods: We downloaded DNA methylation and gene expression data from the GEO database (GSE50387: GSE50222, GSE50101) and identified differentially methylated positions (DMPs) and differentially expressed genes (DEGs) during the pollen and non-pollen seasons using the CHAMP and limma packages. Through correlation analysis, we identified methylation-driven genes and performed pathway enrichment analysis to annotate their functions. We incorporated external data on AR combined with asthma (GSE101720) for analysis to identify key CpGs that promote the transformation of AR to asthma. We also utilized external data on olive pollen allergy (GSE54522) for analysis to validate the methylation-driven genes. Weighted correlation network analysis (WGCNA) was employed to identify gene modules significantly correlated with pollen allergy. We extracted genes related to the key methylation-driven gene ZNF667-AS1 from the significant module and performed pathway intelligent clustering using KOBAS-i. We also utilized gene set enrichment analysis to explore the potential function of ZNF667-AS1. Results: We identified 20 and 24 CpG-Gene pairings during the pollen and non-pollen seasons. After incorporating external data from GSE101720, we found that ZNF667-AS1 is a key gene that may facilitate the transformation of AR into asthma during the pollen season. This finding was further validated in another external dataset, GSE54522, which is associated with pollen allergy. WGCNA identified 17 modules, among which the blue module showed significant correlation with allergies. ZNF667-AS1 was located in the blue module. We performed pathway analysis on the genes correlated with ZNF667-AS1 extracted from the blue module and identified a prominent cluster of pathways in the KOBAS-i results, including Toll-like receptor (TLR) family, MyD88, MAPK, and oxidative stress. Gene set enrichment analysis around cg05508084 (paired with ZNF667-AS1) also indicated its potential involvement in initiating and modulating allergic inflammation from the perspective of TLR and MAPK signaling. Conclusion: We identified methylation-driven genes and their related pathways during the pollen and non-pollen seasons in patients with AR and identified key CpGs that promote the transformation of AR into asthma due to pollen exposure. This study provides new insights into the underlying molecular mechanisms of the transformation of AR to asthma.
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Microarray experiments, a mainstay in gene expression analysis for nearly two decades, pose challenges due to their complexity. To address this, we introduce DExplore, a user-friendly web application enabling researchers to detect differentially expressed genes using data from NCBI's GEO. Developed with R, Shiny, and Bioconductor, DExplore integrates WebGestalt for functional enrichment analysis. It also provides visualization plots for enhanced result interpretation. With a Docker image for local execution, DExplore accommodates unpublished data. To illustrate its utility, we showcase two case studies on cancer cells treated with chemotherapeutic drugs. DExplore streamlines microarray data analysis, empowering molecular biologists to focus on genes of biological significance.
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Background: Empirical decisions to select therapies for psoriasis (PSO) and atopic dermatitis (AD) can lead to delays in disease control and increased health care costs. However, routine molecular testing for AD and PSO are lacking. Objective: To examine (1) how clinicians choose systemic therapies for patients with PSO and AD without molecular testing and (2) to determine how often the current approach leads to patients switching medications. Methods: A 20-question survey designed to assess clinician strategies for systemic treatment of AD and PSO was made available to attendees of a national dermatology conference in 2022. Results: Clinicians participating in the survey (265/414, 64% response rate) ranked "reported efficacy" as the most important factor governing treatment choice (P < .001). However, 62% (165/265) of clinicians estimated that 2 or more systemic medications were typically required to achieve efficacy. Over 90% (239/265) of respondents would or would likely find a molecular test to guide therapeutic selection useful. Limitations: To facilitate ease of recall, questions focused on systemic therapies as a whole and not individual therapies. Conclusion: Clinicians want a molecular test to help determine the most efficacious drug for individual patients.
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INTRODUCTION: Over the past decade, significant advancements in the field of melanoma have included the introduction of a new staging system and the development of immunotherapy and targeted therapies, leading to changes in substage classification and impacting patient prognosis. Despite these strides, early detection remains paramount. The quest for dependable prognostic biomarkers is ongoing, given melanoma's unpredictable nature, especially in identifying patients at risk of relapse. Reliable biomarkers are critical for informed treatment decisions. AREAS COVERED: This review offers a comprehensive review of prognostic biomarkers in the context of clinical trials for immunotherapy and targeted therapy. It explores different clinical scenarios, including adjuvant, metastatic, and neo-adjuvant settings. Key findings suggest that tumor mutational burden, PD-L1 expression, IFN-γ signature, and immune-related factors are promising biomarkers associated with improved treatment responses. EXPERT OPINION: Identifying practical prognostic factors for melanoma therapy is challenging due to the tumor's heterogeneity. Promising biomarkers include tumor mutational burden (TMB), circulating tumor DNA, and those characterizing the tumor microenvironment, especially the immune component. Future research should prioritize large-scale, prospective studies to validate and standardize these biomarkers, emphasizing clinical relevance and real-world applicability. Easily accessible biomarkers have the potential to enhance the precision and effectiveness of melanoma management.
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Biomarkers, Tumor , Immunotherapy , Melanoma , Humans , Melanoma/diagnosis , Melanoma/therapy , Melanoma/metabolism , Prognosis , Immunotherapy/methods , Clinical Trials as Topic , Tumor Microenvironment , Molecular Targeted Therapy/methods , MutationABSTRACT
Heavy-metal ATPases (HMAs) play a vital role in plants, helping to transport heavy metal ions across cell membranes.However, insufficient data exists concerning HMAs genes within the Arecaceae family.In this study, 12 AcHMA genes were identified within the genome of Areca catechu, grouped into two main clusters based on their phylogenetic relationships.Genomic distribution analysis reveals that the AcHMA genes were unevenly distributed across six chromosomes. We further analyzed their physicochemical properties, collinearity, and gene structure.Furthermore, RNA-seq data analysis exhibited varied expressions in different tissues of A. catechu and found that AcHMA1, AcHMA2, and AcHMA7 were highly expressed in roots, leaves, pericarp, and male/female flowers. A total of six AcHMA candidate genes were selected based on gene expression patterns, and their expression in the roots and leaves was determined using RT-qPCR under heavy metal stress. Results showed that the expression levels of AcHMA1 and AcHMA3 genes were significantly up-regulated under Cd2 + and Zn2 + stress. Similarly, in response to Cu2+, the AcHMA5 and AcHMA8 revealed the highest expression in roots and leaves, respectively. In conclusion, this study will offer a foundation for exploring the role of the HMAs gene family in dealing with heavy metal stress conditions in A. catechu.
Subject(s)
Adenosine Triphosphatases , Metals, Heavy , Metals, Heavy/toxicity , Adenosine Triphosphatases/genetics , Adenosine Triphosphatases/metabolism , Phylogeny , Plant Proteins/genetics , Plant Proteins/metabolism , Genome, Plant , Gene Expression Regulation, Plant , Genes, Plant , Plant Leaves/genetics , Plant Roots/genetics , Plant Roots/metabolismABSTRACT
Aim: Cutaneous melanocytic neoplasms with diagnostic and/or clinical ambiguity pose patient management challenges. Methods: Six randomized case scenarios with diagnostic/clinical uncertainty were described with/without a benign or malignant diagnostic gene expression profile (GEP) result. Results: Clinical impact was assessed by reporting the mean increase/decrease of management changes normalized to baseline (n = 32 dermatologists). Benign GEP results prompted clinicians to decrease surgical margins (84.2%). Malignant GEP results escalated surgical excision recommendations (100%). A majority (72.2%) reduced and nearly all (98.9%) increased follow-up frequency for benign or malignant GEP results, respectively. There was an overall increase in management plan confidence with GEP results. Conclusion: Diagnostic GEP tests help guide clinical decision-making in a variety of diagnostically ambiguous or clinicopathologically discordant scenarios.
Dermatologists' use of diagnostic gene expression profiles for personalized patient care. When your doctor takes a piece of a mole, that mole is looked at under the microscope by a pathologist. The pathologist is responsible for figuring out if the mole is dangerous or not. Dangerous moles are removed with surgery to make sure all the dangerous tissue is gone. Moles without a health threat are left alone. Sometimes figuring out how dangerous a mole is is difficult. The pathologist may not provide the doctor with enough information for them to know how to treat your mole. There is a test that can provide information on whether your mole is unsafe. This test is called diagnostic gene expression profiling or GEP. In this study, GEP is used to help doctors figure out how to treat a mole and how often the patient should be seen in the office for skin checks. With GEP, important changes in patient treatment were identified. These include the need for an additional surgery, how much healthy tissue should be removed during surgery and how often the patient should be seen in the office. For suspicious moles where the pathology report is unclear, GEP can provide information that leads to more appropriate and personalized patient care.
Ancillary diagnostic gene expression profile testing for ambiguous cutaneous melanocytic lesions helps optimize dermatologist recommendations for excision margin and follow-up.
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Pediatric B-cell acute lymphoblastic leukemia (B-ALL) is a highly heterogeneous disease. According to large-scale RNA sequencing (RNA-seq) data, B-ALL patients can be divided into more than 10 subgroups. However, many genomic defects associated with resistance mechanisms have not yet been identified. As an individual clinical tool for molecular diagnostic risk classification, RNA-seq and gene expression pattern-based therapy could be potential upcoming strategies. In this study, we retrospectively analyzed the RNA-seq gene expression profiles of 45 children whose molecular diagnostic classifications were inconsistent with the response to chemotherapy. The relationship between the transcriptome and chemotherapy response was analyzed. Fusion gene identification was conducted for the included patients who did not have known high-risk associated fusion genes or gene mutations. The most frequently detected fusion gene pair in the high-risk group was the DHRSX duplication, which is a novel finding. Fusions involving ABL1, LMNB2, NFATC1, PAX5, and TTYH3 at onset were more frequently detected in the high-risk group, while fusions involving LFNG, TTYH3, and NFATC1 were frequently detected in the relapse group. According to the pathways involved, the underlying drug resistance mechanism is related to DNA methylation, autophagy, and protein metabolism. Overall, the implementation of an RNA-seq diagnostic system will identify activated markers associated with chemotherapy response, and guide future treatment adjustments.
Subject(s)
Precursor B-Cell Lymphoblastic Leukemia-Lymphoma , Humans , Child , Male , Female , Child, Preschool , Precursor B-Cell Lymphoblastic Leukemia-Lymphoma/genetics , Precursor B-Cell Lymphoblastic Leukemia-Lymphoma/drug therapy , Precursor B-Cell Lymphoblastic Leukemia-Lymphoma/diagnosis , Sequence Analysis, RNA , Adolescent , Drug Resistance, Neoplasm/genetics , Infant , Retrospective Studies , Oncogene Proteins, Fusion/geneticsABSTRACT
The GHRL, LEAP2, and GHSR system have recently been identified as important regulators of feed intake in mammals and chickens. However, the complete cloning of the quail GHRL (qGHRL) and quail LEAP2 (qLEAP2) genes, as well as their association with feed intake, remains unclear. This study cloned the entire qGHRL and qLEAP2 cDNA sequence in Chinese yellow quail (Coturnix japonica), including the 5' and 3' untranslated regions. Sanger sequencing analysis revealed no missense mutations in the coding region of qGHRL and qLEAP2. Subsequently, phylogenetic analysis and protein homology alignment were conducted on the qGHRL and qLEAP2 in major poultry species. The findings of this research indicated that the qGHRL and qLEAP2 sequences exhibit a high degree of similarity with those of chicken and turkey. Specifically, the N-terminal 6 amino acids of GHRL mature peptides and all the mature peptide sequence of LEAP2 exhibited consistent patterns across all species examined. The analysis of tissue gene expression profiles indicated that qGHRL was primarily expressed in the proventriculus and brain tissue, whereas qLEAP2 exhibited higher expression levels in the intestinal tissue, kidney, and liver tissue, differing slightly from previous studies conducted on chicken. It is necessary to investigate the significance of elevated expression of qGHRL in brain and qLEAP2 in kidney in the future. Further research has shown that the expression of qLEAP2 can quickly respond to changes in different energy states, whereas qGHRL does not exhibit the same capability. Overall, this study successfully cloned the complete cDNA sequences of qGHRL and qLEAP2, and conducted a comprehensive examination of their tissue expression profiles and gene expression levels in the main expressing organs across different energy states. Our current findings suggested that qLEAP2 is highly expressed in the liver, intestine, and kidney, and its expression level is regulated by feed intake.
Subject(s)
Cloning, Molecular , Phylogeny , Animals , Ghrelin/genetics , Ghrelin/metabolism , Avian Proteins/genetics , Avian Proteins/metabolism , Eating/genetics , Amino Acid Sequence , Gene Expression Profiling/methods , Coturnix/genetics , Coturnix/metabolism , Chickens/genetics , Chickens/metabolism , Quail/genetics , Polymorphism, GeneticABSTRACT
Smoking significantly elevates the risk of lung diseases such as chronic obstructive pulmonary disease (COPD) and lung cancer. This risk is attributed to the harmful chemicals in tobacco smoke that damage lung tissue and impair lung function. Current research on the impact of smoking on gene expression in specific lung cells is limited. This study addresses this gap by analyzing gene expression profiles at the single-cell level from 43,539 lung endothelial cells, 234,349 lung epithelial cells, 189,843 lung immune cells, and 16,031 lung stromal cells using advanced machine learning techniques. The data, categorized by different lung cell types, were classified into three smoking states: active smoker, former smoker, and never smoker. Each cell sample encompassed 28,024 feature genes. Employing an incremental feature selection method within a computational framework, several specific genes have been identified as potential markers of smoking status in different lung cell types. These include B2M, EEF1A1, and TPT1 in lung endothelial cells; FTL and MT-ATP8 in lung epithelial cells; HLA-B and HLA-C in lung immune cells; and HSP90B1 and LCN2 in lung stroma cells. Additionally, this study developed quantitative rules for representing the gene expression patterns related to smoking. This research highlights the potential of machine learning in oncology, enhancing our molecular understanding of smoking's harm and laying the groundwork for future mechanism-based studies.
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Background: The pathological damage mechanism of type 2 diabetes (T2D) and macroangiopathy is extremely complex, and T2D and arteriosclerosis obliterans have different biological behaviors and clinical features. To explore the mechanism of lower extremity arteriosclerosis occlusion (LEAOD) in T2D patients, we utilized RNA-seq to identify unique gene expression signatures of T2D and LEAOD through transcriptomic analysis. Methods: We obtained blood samples and performed RNA sequencing from four patients with T2D, five of whom had LEAOD. Another six age- and gender-matched blood samples from healthy volunteers were used for control. By exploring the general and specific differential expression analysis after transcriptome sequencing, specific gene expression patterns of T2D and LEAOD were verified. Results: Transcriptome analysis found differentially expressed genes in T2D, and T2D + LEAOD (vs normal) separately, of which 35/486 (T2D/T2D + LEAOD) were up-regulated and 1290/2970 (T2D/T2D + LEAOD) were down-regulated. A strong overlap of 571 genes across T2D, LEAOD, and coexisting conditions was mainly involved in extracellular exosomes and the transcription process. By exploring the sex difference gene expression features between T2D, T2D + LEAOD, and healthy controls, we noticed that sex chromosome-associated genes do not participate in the sexual dimorphism gene expression profiles of T2D and LEAOD. Protein-Protein Interaction Network analysis and drug target prediction provided the drug candidates to treat T2D and LEAOD. Conclusion: This study provides some evidence at the transcript level to uncover the association of T2D with LEAOD. The screened hub genes and predicted target drugs may be therapeutic targets.
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PURPOSE OF REVIEW: The role of Sentinel Lymph Node Biopsy (SLNB) is pivotal in the contemporary staging of cutaneous melanoma. In this review, we examine advanced molecular testing platforms like gene expression profiling (GEP) and immunohistochemistry (IHC) as tools for predicting the prognosis of sentinel lymph nodes. We compare these innovative approaches with traditional staging assessments. Additionally, we delve into the shared genetic and protein markers between GEP and IHC tests and their relevance to melanoma biology, exploring their prognostic and predictive characteristics. Finally, we assess alternative methods to potentially obviate the need for SLNB altogether. RECENT FINDINGS: Progress in adjuvant melanoma therapy has diminished the necessity of Sentinel Lymph Node Biopsy (SLNB) while underscoring the importance of accurately identifying high-risk stage I and II melanoma patients who may benefit from additional anti-tumor interventions. The clinical application of testing through gene expression profiling (GEP) or immunohistochemistry (IHC) is gaining traction, with platforms such as DecisionDx, Merlin Assay (CP-GEP), MelaGenix GEP, and Immunoprint coming into play. Currently, extensive validation studies are in progress to incorporate routine molecular testing into clinical practice. However, due to significant methodological limitations, widespread clinical adoption of tissue-based molecular testing remains elusive at present. SUMMARY: While various tissue-based molecular testing platforms have the potential to stratify the risk of sentinel lymph node positivity (SLNP), most suffer from significant methodological deficiencies, including limited sample size, lack of prospective validation, and limited correlation with established clinicopathological variables. Furthermore, the genes and proteins identified by individual gene expression profiling (GEP) or immunohistochemistry (IHC) tests exhibit minimal overlap, even when considering the most well-established melanoma mutations. However, there is hope that the ongoing prospective trial for the Merlin Assay may safely reduce the necessity for SLNB procedures if successful. Additionally, the MelaGenix GEP and Immunoprint tests could prove valuable in identifying high-risk stage I-II melanoma patients and potentially guiding their selection for adjuvant therapy, thus potentially reducing the need for SLNB. Due to the diverse study designs employed, effective comparisons between GEP or IHC tests are challenging, and to date, there is no study directly comparing the clinical utility of these respective GEP or IHC tests.
Subject(s)
Lymphadenopathy , Melanoma , Sentinel Lymph Node , Skin Neoplasms , Humans , Melanoma/pathology , Skin Neoplasms/pathology , Sentinel Lymph Node Biopsy , Sentinel Lymph Node/pathology , Neurofibromin 2 , Neoplasm Staging , PrognosisABSTRACT
Resection of the left atrial appendage reportedly improves blood pressure in patients with hypertension. This study aimed to validate the transcriptional profiles of atrial genes responsible for blood pressure regulation in patients with hypertension as well as to identify the molecular mechanisms in rat biological systems. RNA sequencing data of left atrial appendages from patients with (n = 6) and without (n = 6) hypertension were subjected to unsupervised principal component analysis (PCA). Reduction of blood pressure was reflected by third and ninth principal components PC3 and PC9, and that eighteen transcripts, including endothelin-1, were revealed by PCA-based pathway analysis. Resection of the left atrial appendage in hypertensive rats improved their blood pressure accompanied by a decrease in serum endothelin-1 concentration. Expression of the endothelin-1 gene in the atrium and atrial appendectomy could play roles in blood pressure regulation in humans and rats.
Subject(s)
Atrial Appendage , Hypertension , Humans , Rats , Animals , Blood Pressure , Endothelin-1 , Hypertension/complications , Heart AtriaABSTRACT
BACKGROUND: Aspergillus fumigatus (Af) is one of the most ubiquitous fungi and its infection potency is suggested to be strongly controlled by the host genetic background. The aim of this study was to search for candidate genes associated with host susceptibility to Aspergillus fumigatus (Af) using an RNAseq approach in CC lines and hepatic gene expression. METHODS: We studied 31 male mice from 25 CC lines at 8 weeks old; the mice were infected with Af. Liver tissues were extracted from these mice 5 days post-infection, and next-generation RNA-sequencing (RNAseq) was performed. The GENE-E analysis platform was used to generate a clustered heat map matrix. RESULTS: Significant variation in body weight changes between CC lines was observed. Hepatic gene expression revealed 12 top prioritized candidate genes differentially expressed in resistant versus susceptible mice based on body weight changes. Interestingly, three candidate genes are located within genomic intervals of the previously mapped quantitative trait loci (QTL), including Gm16270 and Stox1 on chromosome 10 and Gm11033 on chromosome 8. CONCLUSIONS: Our findings emphasize the CC mouse model's power in fine mapping the genetic components underlying susceptibility towards Af. As a next step, eQTL analysis will be performed for our RNA-Seq data. Suggested candidate genes from our study will be further assessed with a human cohort with aspergillosis.
Subject(s)
Aspergillosis , Collaborative Cross Mice , Humans , Male , Mice , Animals , Collaborative Cross Mice/genetics , Chromosome Mapping , Aspergillus fumigatus/genetics , RNA-Seq , Genetic Predisposition to Disease/genetics , Quantitative Trait Loci/genetics , Aspergillosis/genetics , Body Weight/geneticsABSTRACT
BACKGROUND: Synovial hyperplasia caused by rheumatoid arthritis (RA), an autoimmune inflammatory disease, leads to the destruction of the articular cartilage and bone. A member of the tumor necrosis factor superfamily, Lymphotoxin-related inducible ligand that competes for glycoprotein D binding to herpes virus entry mediator on T cells (LIGHT) has been shown to correlate with the pathogenesis of RA. METHODS: We used cDNA microarray analysis to compare the expression of genes in rheumatoid fibroblast-like synoviocytes with and without LIGHT stimulation. RESULTS: Significant changes in gene expression (P-values < 0.05 and fold change ≥ 2.0) were associated mainly with biological function categories of glycoprotein, glycosylation site as N-linked, plasma membrane part, integral to plasma membrane, intrinsic to plasma membrane, signal, plasma membrane, signal peptide, alternative splicing, and topological domain as extracellular. CONCLUSIONS: Our results indicate that LIGHT may regulate the expression in RA-FLS of genes which are important in the differentiation of several cell types and in cellular functions.