ctGAN: combined transformation of gene expression and survival data with generative adversarial network.

Recent studies have extensively used deep learning algorithms to analyze gene expression to predict disease diagnosis, treatment effectiveness, and survival outcomes. Survival analysis studies on diseases with high mortality rates, such as cancer, are indispensable. However, deep learning models are plagued by overfitting owing to the limited sample size relative to the large number of genes. Consequently, the latest style-transfer deep generative models have been implemented to generate gene expression data. However, these models are limited in their applicability for clinical purposes because they generate only transcriptomic data. Therefore, this study proposes ctGAN, which enables the combined transformation of gene expression and survival data using a generative adversarial network (GAN). ctGAN improves survival analysis by augmenting data through style transformations between breast cancer and 11 other cancer types. We evaluated the concordance index (C-index) enhancements compared with previous models to demonstrate its superiority. Performance improvements were observed in nine of the 11 cancer types. Moreover, ctGAN outperformed previous models in seven out of the 11 cancer types, with colon adenocarcinoma (COAD) exhibiting the most significant improvement (median C-index increase of ~15.70%). Furthermore, integrating the generated COAD enhanced the log-rank p-value (0.041) compared with using only the real COAD (p-value = 0.797). Based on the data distribution, we demonstrated that the model generated highly plausible data. In clustering evaluation, ctGAN exhibited the highest performance in most cases (89.62%). These findings suggest that ctGAN can be meaningfully utilized to predict disease progression and select personalized treatments in the medical field.

DeepGRNCS: deep learning-based framework for jointly inferring gene regulatory networks across cell subpopulations.

Inferring gene regulatory networks (GRNs) allows us to obtain a deeper understanding of cellular function and disease pathogenesis. Recent advances in single-cell RNA sequencing (scRNA-seq) technology have improved the accuracy of GRN inference. However, many methods for inferring individual GRNs from scRNA-seq data are limited because they overlook intercellular heterogeneity and similarities between different cell subpopulations, which are often present in the data. Here, we propose a deep learning-based framework, DeepGRNCS, for jointly inferring GRNs across cell subpopulations. We follow the commonly accepted hypothesis that the expression of a target gene can be predicted based on the expression of transcription factors (TFs) due to underlying regulatory relationships. We initially processed scRNA-seq data by discretizing data scattering using the equal-width method. Then, we trained deep learning models to predict target gene expression from TFs. By individually removing each TF from the expression matrix, we used pre-trained deep model predictions to infer regulatory relationships between TFs and genes, thereby constructing the GRN. Our method outperforms existing GRN inference methods for various simulated and real scRNA-seq datasets. Finally, we applied DeepGRNCS to non-small cell lung cancer scRNA-seq data to identify key genes in each cell subpopulation and analyzed their biological relevance. In conclusion, DeepGRNCS effectively predicts cell subpopulation-specific GRNs. The source code is available at https://github.com/Nastume777/DeepGRNCS.

LDER-GE estimates phenotypic variance component of gene-environment interactions in human complex traits accurately with GE interaction summary statistics and full LD information.

Gene-environment (GE) interactions are essential in understanding human complex traits. Identifying these interactions is necessary for deciphering the biological basis of such traits. In this study, we review state-of-art methods for estimating the proportion of phenotypic variance explained by genome-wide GE interactions and introduce a novel statistical method Linkage-Disequilibrium Eigenvalue Regression for Gene-Environment interactions (LDER-GE). LDER-GE improves the accuracy of estimating the phenotypic variance component explained by genome-wide GE interactions using large-scale biobank association summary statistics. LDER-GE leverages the complete Linkage Disequilibrium (LD) matrix, as opposed to only the diagonal squared LD matrix utilized by LDSC (Linkage Disequilibrium Score)-based methods. Our extensive simulation studies demonstrate that LDER-GE performs better than LDSC-based approaches by enhancing statistical efficiency by ~23%. This improvement is equivalent to a sample size increase of around 51%. Additionally, LDER-GE effectively controls type-I error rate and produces unbiased results. We conducted an analysis using UK Biobank data, comprising 307 259 unrelated European-Ancestry subjects and 966 766 variants, across 217 environmental covariate-phenotype (E-Y) pairs. LDER-GE identified 34 significant E-Y pairs while LDSC-based method only identified 23 significant E-Y pairs with 22 overlapped with LDER-GE. Furthermore, we employed LDER-GE to estimate the aggregated variance component attributed to multiple GE interactions, leading to an increase in the explained phenotypic variance with GE interactions compared to considering main genetic effects only. Our results suggest the importance of impacts of GE interactions on human complex traits.

The Geometry of Normal Tissue and Cancer Gene Expression Manifolds.

A recent paper shows that in gene expression space the manifold spanned by normal tissues and the manifold spanned by the corresponding tumors are disjoint. The statement is based on a two-dimensional projection of gene expression data. In the present paper, we show that, for the multi-dimensional vectors defining the centers of cloud samples: 1. The closest tumor to a given normal tissue is the tumor developed in that tissue, 2. Two normal tissues define quasi-orthogonal directions, 3. A tumor may have a projection onto its corresponding normal tissue, but it is quasi-orthogonal to all other normal tissues, and 4. The cancer manifold is roughly obtained by translating the normal tissue manifold along an orthogonal direction defined by a global cancer progression axis. These geometrical properties add a new characterization of normal tissues and tumors and may have biological significance. Indeed, normal tissues at the vertices of a high-dimensional simplex could indicate genotype optimization for given tissue functions, and a way of avoiding errors in embryonary development. On the other hand, the cancer progression axis could define relevant pan-cancer genes and seems to be consistent with the atavistic theory of tumors.

Resistance to FOXM1 inhibitors in breast cancer is accompanied by impeding ferroptosis and apoptotic cell death.

PURPOSE: Cancer treatments often become ineffective because of acquired drug resistance. To characterize changes in breast cancer cells accompanying development of resistance to inhibitors of the oncogenic transcription factor, FOXM1, we investigated the suppression of cell death pathways, especially ferroptosis, in FOXM1 inhibitor-resistant cells. We also explored whether ferroptosis activators can synergize with FOXM1 inhibitors and can overcome FOXM1 inhibitor resistance. METHODS: In estrogen receptor-positive and triple-negative breast cancer cells treated with FOXM1 inhibitor NB73 and ferroptosis activators dihydroartemisinin and JKE1674, alone and in combination, we measured suppression of cell viability, motility, and colony formation, and monitored changes in gene and protein pathway expressions and mitochondrial integrity. RESULTS: Growth suppression of breast cancer cells by FOXM1 inhibitors is accompanied by increased cell death and alterations in mitochondrial morphology and metabolic activity. Low doses of FOXM1 inhibitor strongly synergize with ferroptosis inducers to reduce cell viability, migration, colony formation, and expression of proliferation-related genes, and increase intracellular Fe+2 and lipid peroxidation, markers of ferroptosis. Acquired resistance to FOXM1 inhibition is associated with increased expression of cancer stem-cell markers and proteins that repress ferroptosis, enabling cell survival and drug resistance. Notably, resistant cells are still sensitive to growth suppression by low doses of ferroptosis activators, effectively overcoming the acquired resistance. CONCLUSION: Delineating changes in viability and cell death pathways that can overcome drug resistance should be helpful in determining approaches that might best prevent or reverse resistance to therapeutic targeting of FOXM1 and ultimately improve patient clinical outcomes.

Intratumoral Delivery of Genetically Engineered Anti-IL-6 Trans-signaling Therapeutics.

Interleukin-6 (IL-6) is a highly pro-inflammatory cytokine involved in the etiopathology of several inflammatory diseases and cancer. As so, the inhibition of IL-6 signaling pathways has emerged as an attractive therapeutic avenue for the treatment of several chronic diseases. Since IL-6 trans-signaling was described as the pathological branch of IL-6, selective inhibitors were developed. Next-generation variants with increased trans-signaling specificity and potency emerged as great candidates for the treatment of several diseases, with reduced off-target effects. The highly time-consuming and costly processes involving recombinant protein production, however, have hampered the progress of anti-cytokine pharmaceuticals in clinic so far. Herein, we developed gene therapeutic modalities of IL-6-trans-signaling inhibitors as alternatives for sustained recombinant protein secretion. By using an IL-6-dependent lymphoma cell line and xenograft tumor model, we demonstrated the superior inhibitory potential of second-generation anti-IL-6 trans-signaling therapeutic. We compared the efficiency of distinct gene delivery modalities using a bioluminescent biomarker probe and observed consistent protein production via cell-based delivery. When delivered intratumorally, genetically engineered sgp130FlyRFc-secreting cells significantly reduced tumor burden and increased animal survival, representing a promising therapeutic avenue to be explored in clinically relevant gene delivery applications.

Genetic factors of oocyte maturation arrest: an important cause for recurrent IVF/ICSI failures.

Oocyte maturation arrest (OMA) is a common phenotype observed in IVF/ICSI cycles, characterized by the production of immature oocytes which lead to infertility. Previous studies have demonstrated that genetic factors play an important role in OMA, but the genetic mechanisms underlying a group of patients remain to be elucidated. In the recent issue of Journal of Assisted Reproduction and Genetics, Hu et al. and Wan et al. identified novel PATL2 or ZFP36L2 variants in OMA patients, respectively. By conducting in vitro experiments, they demonstrated the destructive effect of the variants on protein function. These findings expand the mutational spectrum of PATL2 and ZFP36L2, and provide precise reference for genetic counseling of OMA patients.

F2c.*C20209T mutation in patients with a history of thrombosis: A case report, retrospective 2 site-results and review of the literature.

INTRODUCTION: G20210A (c.*97G>A) prothrombin gene variant, found in white population has been associated with an increased risk of venous thromboembolism (VTE). Other rare polymorphisms in F2 gene (C20209T) have been reported, more rare and touching black people, but its potential association with VTE remain uncertain. METHODS: About a 69 years-old Caucasian woman presenting an unprovoked deep venous thrombosis of the leg, we analyzed retrospectively 25.000 thrombophilia tests on a 11-year period of time (2007-2018), at Nice and Marseille University Hospitals, and performed extensive review of the literature. RESULTS: Genetic determination included a similar PCR protocol and sequencing. Twenty-one heterozygous cases out of 25.585 determinations (0.08%) was found. The C20209T mutation detected in our Caucasian patient is rare, with a frequency that differed from what was reported in the previous literature, mainly in non-Caucasian patients (Africans, Africans-Americans, and Caribbeans). One hundred and thirteen patients with this mutation have been described in the literature, of which only one homozygous. CONCLUSION: This study is the most important on C20209T mutation performed at present, allowing to precise its frequency and its potential role in venous thromboembolism.

Mobile-CRISPRi protocol optimization for Vibrionaceae.

Mobile clustered regularly interspaced palindromic repeats interference (Mobile-CRISPRi) is an established method for bacterial gene expression knockdown. The deactivated Cas9 protein and guide RNA are isopropyl ß-D-1-thiogalactopyranoside inducible, and all components are integrated into the chromosome via Tn7 transposition. Here, we optimized methods specific for applying Mobile-CRISPRi in multiple Vibrio species.

Immune response regulation by transduced mesenchymal stem cells with decorin gene on bleomycin-induced lung injury, fibrosis, and inflammation.

BACKGROUND: Pulmonary fibrosis is a pathological hallmark of lung injury. It is an aggressive disease that replaces normal lung parenchyma by fibrotic tissue. The transforming growth factor-beta-mothers against decapentaplegic homolog 3 (TGF-ß1-Smad3) signaling pathway plays a key role in regulating lung fibrosis. Decorin (DCN), a small leucine-rich proteoglycan, has a modulatory effect on the immune system by reversibly binding with TGF-ß and reducing its bioavailability. Mesenchymal stem cell (MSC) therapy is a new strategy that has an immune-modulatory capacity. OBJECTIVE: The aim of this study was to introduce a new therapeutic approach to harness remodeling in injured lung. MATERIAL AND METHODS: Bone marrow MSCs were isolated and transduced by decorin gene. Lung injury was induced by bleomycin and mice were treated with MSCs, MSCs-decorin, and decorin. Then, oxidative stress biomarkers, remodeling biomarkers, bronchoalveolar lavage cells, and histopathology study were conducted. RESULTS: Reduced catalase and superoxide dismutase increased due to treatments. Elevated malondialdehyde, hydroxyproline, TGF-ß levels, and polymorphonuclear cells count decreased in the treated groups. Additionally, the histopathology of lung tissues showed controlled inflammation and fibrosis. CONCLUSION: Transfected decorin gene to MSCs and used cell therapy could control remodeling and bleomycin-induced lung injury.

Sex-specific survival gene mutations are discovered as clinical predictors of clear cell renal cell carcinoma.

Although sex differences have been reported in patients with clear cell renal cell carcinoma (ccRCC), biological sex has not received clinical attention and genetic differences between sexes are poorly understood. This study aims to identify sex-specific gene mutations and explore their clinical significance in ccRCC. We used data from The Cancer Genome Atlas-Kidney Renal Clear Cell Carcinoma (TCGA-KIRC), The Renal Cell Cancer-European Union (RECA-EU) and Korean-KIRC. A total of 68 sex-related genes were selected from TCGA-KIRC through machine learning, and 23 sex-specific genes were identified through verification using the three databases. Survival differences according to sex were identified in nine genes (ACSS3, ALG13, ASXL3, BAP1, JADE3, KDM5C, KDM6A, NCOR1P1, and ZNF449). Female-specific survival differences were found in BAP1 in overall survival (OS) (TCGA-KIRC, p = 0.004; RECA-EU, p = 0.002; and Korean-KIRC, p = 0.003) and disease-free survival (DFS) (TCGA-KIRC, p = 0.001 and Korean-KIRC, p = 0.000004), and NCOR1P1 in DFS (TCGA-KIRC, p = 0.046 and RECA-EU, p = 0.00003). Male-specific survival differences were found in ASXL3 (OS, p = 0.017 in TCGA-KIRC; and OS, p = 0.005 in RECA-EU) and KDM5C (OS, p = 0.009 in RECA-EU; and DFS, p = 0.016 in Korean-KIRC). These results suggest that biological sex may be an important predictor and sex-specific tailored treatment may improve patient care in ccRCC.

Combination of error-prone PCR (epPCR) and Circular Polymerase Extension Cloning (CPEC) for improving the coverage of random mutagenesis libraries.

Random mutagenesis, such as error-prone PCR (epPCR), is a technique capable of generating a wide variety of a single gene. However, epPCR can produce a large number of mutated gene variants, posing a challenge in ligating these mutated PCR products into plasmid vectors. Typically, the primers for mutagenic PCRs incorporate artificial restriction enzyme sites compatible with chosen plasmids. Products are cleaved and ligated to linearized plasmids, then recircularized by DNA ligase. However, this cut-and-paste method known as ligation-dependent process cloning (LDCP), has limited efficiency, as the loss of potential mutants is inevitable leading to a significant reduction in the library's breadth. An alternative to LDCP is the circular polymerase extension cloning (CPEC) method. This technique involves a reaction where a high-fidelity DNA polymerase extends the overlapping regions between the insert and vector, forming a circular molecule. In this study, our objective was to compare the traditional cut-and-paste enzymatic method with CPEC in producing a variant library from the gene encoding the red fluorescent protein (DsRed2) obtained by epPCR. Our findings suggest that CPEC can accelerate the cloning process in gene library generation, enabling the acquisition of a greater number of gene variants compared to methods reliant on restriction enzymes.

Understanding the responses of tillering to 2,4-D isooctyl ester in Setaria viridis L.

BACKGROUND: Green foxtail [Setaria viridis (L.)] is one of the most abundant and troublesome annual grass weeds in alfalfa fields in Northeast China. Synthetic auxin herbicide is widely used in agriculture, while how auxin herbicide affects tillering on perennial grass weeds is still unclear. A greenhouse experiment was conducted to examine the effects of auxin herbicide 2,4-D on green foxtail growth, especially on tillers. RESULTS: In the study, 2,4-D isooctyl ester was used. There was an inhibition of plant height and fresh weight on green foxtail after application. The photosynthetic rate of the leaves was dramatically reduced and there was an accumulation of malondialdehyde (MDA) content. Moreover, applying 2,4-D isooctyl ester significantly reduced the tillering buds at rates between 2100 and 8400 ga. i. /ha. Transcriptome results showed that applying 2,4-D isooctyl ester on leaves affected the phytohormone signal transduction pathways in plant tillers. Among them, there were significant effects on auxin, cytokinin, abscisic acid (ABA), gibberellin (GA), and brassinosteroid signaling. Indeed, external ABA and GA on leaves also limited tillering in green foxtail. CONCLUSIONS: These data will be helpful to further understand the responses of green foxtail to 2, 4-D isooctyl ester, which may provide a unique perspective for the development and identification of new target compounds that are effective against this weed species.

Enhancement of Green Production of Heme by Deleting Odor-Related Genes from Bacillus amyloliquefaciens Based on CRISPR/Cas9n.

Heme is a crucial component in endowing plant-based meat analogs with flavor and color. This study aimed to develop a green strategy for heme production by reducing fermentation off-odor and accelerating heme synthesis. First, an efficient CRISPR/Cas9n system was constructed in Bacillus amyloliquefaciens to construct the odor-reducing chassis cell HZC9nΔGPSU, and the odor substances including the branched-chain short fatty acids, putrescine, and ammonia were reduced by 62, 70, and 88%, respectively. Meanwhile, the hemA gene was confirmed to be the key gene for enhanced heme synthesis. Various hemA genes were compared to obtain the best gene dhemA, and the catalysis mechanism was explained by molecular docking simulation. After further expression of dhemA in HZC9nΔGPSU, the heme titer of HZC9nΔGPSU/pHY-dhemA reached 11.31 ± 0.51 mg/L, 1.70-fold higher than that of HZC9n/pHY-dhemA. The knockout of off-odor-related genes reduced the odor substances and enhanced the heme synthesis, which is promising for the green production of high-quality heme.

GLDADec: marker-gene guided LDA modeling for bulk gene expression deconvolution.

Inferring cell type proportions from bulk transcriptome data is crucial in immunology and oncology. Here, we introduce guided LDA deconvolution (GLDADec), a bulk deconvolution method that guides topics using cell type-specific marker gene names to estimate topic distributions for each sample. Through benchmarking using blood-derived datasets, we demonstrate its high estimation performance and robustness. Moreover, we apply GLDADec to heterogeneous tissue bulk data and perform comprehensive cell type analysis in a data-driven manner. We show that GLDADec outperforms existing methods in estimation performance and evaluate its biological interpretability by examining enrichment of biological processes for topics. Finally, we apply GLDADec to The Cancer Genome Atlas tumor samples, enabling subtype stratification and survival analysis based on estimated cell type proportions, thus proving its practical utility in clinical settings. This approach, utilizing marker gene names as partial prior information, can be applied to various scenarios for bulk data deconvolution. GLDADec is available as an open-source Python package at https://github.com/mizuno-group/GLDADec.

Exploring a Desirable Quadr-mRNAs Panel for Non-invasive and Ultrasensitive Bladder Cancer Diagnosis: In-silico and Clinical Studies.

BACKGROUND: Most patients with non-muscle invasive bladder cancer (NMIBC) have a high direction for recurrence and disease progression, which remains a significant unresolved challenge in bladder cancer patients. Therefore, a constant search is necessary for identifying appropriate and reliable biomarkers for early diagnosis of NMIBC. The current study has aimed to search for valuable diagnostic biomarkers in the tissue and urine specimens of NMIBC patients. METHODS: The changes of twelve candidate mRNAs in a screening phase (40 tissue samples of NMIBC patients and their corresponding 40 urine specimens) and a subsequent independent validation phase (40 urine specimens) were estimated using real-time polymerase chain reaction (RT-qPCR). The receiver operating characteristic (ROC) analysis was executed to determine the potential diagnostic values of mRNAs. RESULTS: The mRNA levels of seven candidate genes were markedly higher in tissue specimens relative to their neighboring tissues. Among them, four mRNAs, including ERBB2, CCND1, MKI67, and MAGEA6, were differentially expressed in urine samples of NMIBC patients relative to control subjects. Further, the expression of these four mRNAs was validated in the validation step. Combining these biomarkers showed better diagnostic performance than single biomarkers in the urine sample for non-invasive NMIBC detection. The combination of these mRNAs and cytology enhanced the sensitivity of cytology from 37% to 87%. CONCLUSION: Our findings suggested that a four-mRNA panel may be promising in the non-invasive diagnosis of NMIBC, which deserves further investigation.

Impact of homologous recombination repair/BReast CAncer (BRCA) gene alterations on survival in a real-world setting of metastatic prostate cancer.

OBJECTIVE: To investigate alterations of homologous recombination repair (HRR) and especially BReast CAncer 1/2 (BRCA1/2) gene on overall survival (OS). Moreover, to explore the effect of inhibition of poly(ADP-ribose)-polymerase (PARPi) as systemic therapy for metastatic castration-resistant prostate cancer (mCRPC). PATIENTS AND METHODS: Of all HRR-screened patients with metastatic prostate cancer, baseline characteristics were sampled. Kaplan-Meier estimates and multivariable Cox regression models predicted the effect of HRR/BRCA1/2 alterations on OS. RESULTS: Of 196 eligible patients, 61 (31%) harboured any HRR and 40 (20%) BRCA1/2 alterations. Of HRR alterations, 40 (66%) vs six (10%) vs five (8.2%) vs four (6.6%) vs two (3.3%) vs four (6.6%) were BRCA1/2 vs Ataxia-telangiectasia mutated kinase (ATM) vs checkpoint kinase 2 (CHEK2) vs cyclin-dependent kinase 12 (CDK12) vs Fanconi anaemia complementation Group A (FANCA) vs positive for other mutations. Of these, 30% received a PARPi. OS differed significantly between HRR-positive vs -negative patients. Specifically in hormone-sensitive prostate cancer, the median OS was 63 (HRR positive) vs 57 (BRCA1/2 positive) vs 113 months (HRR negative) (P ≤ 0.01). In mCRPC, OS was 42 (HRR positive) vs 41 (BRCA1/2 positive) vs 70 months (HRR negative) (P ≤ 0.01). HRR and BRCA1/2 alterations were associated with worse OS after multivariable adjustment. Finally, patients with mCRPC with BRCA1/2 mutation treated without PARPi harboured worse OS than patients with BRCA1/2 mutation and PARPi therapy (median OS: 33 vs 48 months, P < 0.03). CONCLUSION: Incidence of HRR alteration in a clinical real-world setting is high when using blood- and tissue-based tests. Patients with HRR/BRCA alterations have worse outcomes resulting in significant OS differences between HRR/BRCA-positive patients with mCRPC with and without PARPi usage vs HRR/BRCA-negative patients.

A novel amino acid metabolism-related gene signature to predict the overall survival of esophageal squamous cell carcinoma patients.

Background: Esophageal squamous cell carcinoma (ESCC) has a poor early detection rate, prognosis, and survival rate. Effective prognostic markers are urgently needed to assist in the prediction of ESCC treatment outcomes. There is accumulating evidence of a strong relationship between cancer cell growth and amino acid metabolism. This study aims to determine the relationship between amino acid metabolism and ESCC prognosis. Methods: This study comprehensively evaluates the association between amino acid metabolism-related gene (AAMRG) expression profiles and the prognosis of ESCC patients based on data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Real-time quantitative polymerase chain reaction (RT-qPCR) was used to verify the expression of prognosis-related genes. Results: A univariate Cox regression analysis of TCGA data identified 18 prognosis-related AAMRGs. The gene expression profiles of 90 ESCC tumor and normal tissues were obtained from the GSE20347 and GSE67269 datasets. Two differently expressed genes (DEGs) were considered as ESCC prognosis-related genes; and they were branched-chain amino acid transaminase 1 (BCAT1) and methylmalonic aciduria and homocystinuria type C protein (MMACHC). These two AAMRGs were used to develop a novel AAMRG-related gene signature to predict 1- and 2-year prognostic risk in ESCC patients. Both BCAT1 and MMACHC expression were verified by RT-qPCR. A prognostic nomogram that incorporated clinical factors and BCAT1 and MMACHC gene expression was constructed, and the calibration plots showed that it had good prognostic performance. Conclusions: The AAMRG signature established in our study is efficient and could be used in clinical settings to predict the early prognosis of ESCC patients.

Complex heterozygous mutations in hereditary spherocytosis: A case report.

BACKGROUND: The aim of this study was to investigate the complex heterozygous mutations of ANK1 and SPTA1 in the same individual and improve our understanding of hereditary spherocytosis (HS) in children. We also hope to promote the application of gene detection technology in children with HS, with the goals of identifying more related gene mutations, supporting the acquisition of improved molecular genetic information to further reveal the pathogenesis of HS in children, and providing important guidance for the diagnosis, treatment, and prevention of HS in children. CASE SUMMARY: A 1-year and 5-month-old patient presented jaundice during the neonatal period, mild anemia 8 months later, splenic enlargement at 1 year and 5 months, and brittle red blood cell permeability. Genetic testing was performed on the patient, their parents, and sister. Swiss Model software was used to predict the protein structure of complex heterozygous mutations in ANK1 and SPTA1. Genetic testing revealed that the patient harbored a new mutation in the ANK1 gene from the father and a mutation in the SPTA1 gene from the mother. Combined with the clinical symptoms of the children, it is suggested that the newly discovered complex heterozygous mutations of ANK1 and SPTA1 may be the cause, providing important guidance for revealing the pathogenesis, diagnosis, treatment, and promotion of gene detection technology in children with HS. CONCLUSION: This case involves an unreported complex heterozygous mutation of ANK1 and SPTA1, which provides a reference for exploring HS.

Mycobacterium tuberculosis and host interactions in the manifestation of tuberculosis.

The final step of epigenetic processes is changing the gene expression in a new microenvironment in the body, such as neuroendocrine changes, active infections, oncogenes, or chemical agents. The case of tuberculosis (TB) is an outcome of Mycobacterium tuberculosis (M.tb) and host interaction in the manifestation of active and latent TB or clearance. This comprehensive review explains and interprets the epigenetics findings regarding gene expressions on the host-pathogen interactions in the development and progression of tuberculosis. This review introduces novel insights into the complicated host-pathogen interactions, discusses the challengeable results, and shows the gaps in the clear understanding of M.tb behavior. Focusing on the biological phenomena of host-pathogen interactions, the epigenetic changes, and their outcomes provides a promising future for developing effective TB immunotherapies when converting gene expression toward appropriate host immune responses gradually becomes attainable. Overall, this review may shed light on the dark sides of TB pathogenesis as a life-threatening disease. Therefore, it may support effective planning and implementation of epigenetics approaches for introducing proper therapies or effective vaccines.