Immune Characteristics Research Articles

MA09.10 Spatial Transcriptomics and Next-Generation Sequencing Reveals the Gene Expression Andmolecular Immune Characteristics in LUAD

MA09.10 Spatial Transcriptomics and Next-Generation Sequencing Reveals the Gene Expression Andmolecular Immune Characteristics in LUAD

Immunoproteomics Reveal Different Characteristics for the Prognostic Markers of Intratumoral-Infiltrating CD3+ T Lymphocytes and Immunoscore in Colorectal Cancer

Tumor-infiltrating lymphocytes (TILs) and immunoscoring based on densities of CD3+ and CD8+ TILs are both favorable prognostic markers in colorectal cancer (CRC). However, determination of the molecular features of TILs, particularly their immunoproteomic signatures would require the development of large scale in situ spatiotemporal technologies. Recently, a multiplex in situ digital spatial proteomic profiling (DSP) tool GeoMx DSP has been applied to identify biomarkers predictive of therapeutic responses and to understand disease mechanisms and progression. Taking advantage of this tool, we simultaneously characterized the spatial distribution and interactions of 42 immune proteins in tumor cells (TCs), CD3+ T stromal TILs (sTILs), and CD20+ B sTILs using tissue microarrays, and further studied their associations with CD3+ T TILs and immunoscores in CRC. First, our data showed that well-known immune checkpoints, such as PD-L1, PD-L2, and LAG3, were expressed at low levels, whereas some other immune proteins, such as CD11c, CD68, STING, and CD44, were highly expressed. Second, 8 spatial interactions were identified, including 5 interactions between TC and CD20+ B sTILs, 2 interactions between CD3+ T sTILs and CD20+ B sTILs, and 1 interaction among TC, CD3+ T sTILs, and CD20+ B sTILs. Third, the differential immune microlandscape in the spatial compartments was identified in tissues with positive CD3+ T intratumoral TILs and high immunoscores. Collectively, to our knowledge, our study is the first to provide in situ spatial immune characteristics at the proteomic level. Moreover, our findings provide direct evidence supporting the infiltration of CD3+ T sTILs from stoma to TC and shed important insights into better understanding and treating CRC patients related to different immune prognostic markers.

Identification of immune feature genes and intercellular profiles in diabetic cardiomyopathy

BACKGROUND Diabetic cardiomyopathy (DCM) is a multifaceted cardiovascular disorder in which immune dysregulation plays a pivotal role. The immunological molecular mechanisms underlying DCM are poorly understood. AIM To examine the immunological molecular mechanisms of DCM and construct diagnostic and prognostic models of DCM based on immune feature genes (IFGs). METHODS Weighted gene co-expression network analysis along with machine learning methods were employed to pinpoint IFGs within bulk RNA sequencing (RNA-seq) datasets. Single-sample gene set enrichment analysis (ssGSEA) facilitated the analysis of immune cell infiltration. Diagnostic and prognostic models for these IFGs were developed and assessed in a validation cohort. Gene expression in the DCM cell model was confirmed through real time-quantitative polymerase chain reaction and western blotting techniques. Additionally, single-cell RNA-seq data provided deeper insights into cellular profiles and interactions. RESULTS The overlap between 69 differentially expressed genes in the DCM-associated module and 2483 immune genes yielded 7 differentially expressed immune-related genes. Four IFGs showed good diagnostic and prognostic values in the validation cohort: Proenkephalin (Penk) and retinol binding protein 7 (Rbp7), which were highly expressed, and glucagon receptor and inhibin subunit alpha, which were expressed at low levels in DCM patients (all area under the curves > 0.9). SsGSEA revealed that IFG-related immune cell infiltration primarily involved type 2 T helper cells. High expression of Penk (P < 0.0001) and Rbp7 (P = 0.001) was detected in cardiomyocytes and interstitial cells and further confirmed in a DCM cell model in vitro . Intercellular events and communication analysis revealed abnormal cellular phenotype transformation and signaling communication in DCM, especially between mesenchymal cells and macrophages. CONCLUSION The present study identified Penk and Rbp7 as potential DCM biomarkers, and aberrant mesenchymal-immune cell phenotype communication may be an important aspect of DCM pathogenesis.

Comprehensive analysis of a necroptosis-associated diagnostic signature for myelodysplastic syndromes based on single-cell RNA-seq and bulk RNA-seq

BackgroundMyelodysplastic syndromes (MDS) are heterogeneous and clonal hematological disorders. The role and mechanism of necroptosis in MDS remain poorly understood.MethodsmRNA expression profiles and single-cell RNA-sequencing (scRNA-seq) data were sourced from the GEO database. ScRNA-seq data were processed using the “Seurat” package. After cell annotation, necroptosis-related scores (NRscores) for each cell were calculated using the “UCell” package. Differentially expressed genes (DEGs) and their associated biological functions in NRscore-related cell populations were identified. Additionally, DEGs and necroptosis-related genes (DE-NRGs) between MDS patients and healthy controls were identified. Consensus clustering was employed to classify MDS patients into distinct subclusters based on DE-NRGs. The biological functions and immune characteristics of these classifications were analyzed. Prognostic gene signatures were determined using LASSO and SVM-RFE analyses, and a nomogram was constructed based on the prognostic gene signature.ResultsA total of 12 cell types were identified in MDS and healthy controls. NRscore was found to be elevated in monocytes and common lymphoid precursors (CLPs). Enrichment analysis revealed that monocytes and CLPs with high NRscore were associated with mitochondria-related and immune-related pathways. Eleven DEGs in monocytes and CLPs between MDS patients and healthy controls were identified. Additionally, 13 DE-NRGs were identified from 951 DEGs between MDS and healthy controls. MDS patients were classified into two distinct subclusters based on these 13 DE-NRGs, revealing several immune-related processes and signaling pathways. Differences in immune subpopulations between the two subclusters were observed. A necroptosis-related diagnostic gene signature (IRF9, PLA2G4A, MLKL, BAX, JAK2, and STAT3) was identified as predictive of MDS prevalence.ConclusionNecroptosis plays a role in MDS progression by inducing inflammation. A novel necroptotic gene signature has been developed to distinguish and diagnose MDS at early stages of the disease.

Integrated machine learning and Mendelian randomization reveal PALMD as a prognostic biomarker for nonspecific orbital inflammation

Background: Nonspecific Orbital Inflammation (NSOI) remains a perplexing enigma among proliferative inflammatory disorders. Its etiology is idiopathic, characterized by distinctive and polymorphous lymphoid infiltration within the orbital region. Preliminary investigations suggest that PALMD localizes within the cytosol, potentially playing a crucial role in cellular processes, including plasma membrane dynamics and myogenic differentiation. The potential of PALMD as a biomarker for NSOI warrants meticulous exploration. Methods: PALMD was identified through the intersection analysis of common DEGs from datasets GSE58331 and GSE105149 from the GEO database, alongside immune-related gene lists from the ImmPort database, using Lasso regression and SVM-RFE analysis. GSEA and GSVA were conducted with gene sets co-expressed with PALMD. To further investigate the correlation between PALMD and immune-related biological processes, the CIBERSORT algorithm and ESTIMATE method were employed to evaluate immune microenvironment characteristics of each sample. The expression levels of PALMD were subsequently validated using GSE105149. Results: Among the 314 DEGs identified, several showed significant differences. Lasso and SVM-RFE algorithms pinpointed 15 hub genes. Functional analysis of PALMD emphasized its involvement in cell-cell adhesion, leukocyte migration, and leukocyte-mediated immunity. Enrichment analysis revealed that gene sets positively correlated with PALMD were enriched in immune-related pathways. Immune infiltration analysis indicated that resting dendritic cells, resting mast cells, activated NK cells, and plasma cells positively associate with PALMD expression. Conversely, naive B cells, activated dendritic cells, M0 and M1 macrophages, activated mast cells, activated CD4 memory T cells, and naive CD4 T cells showed a negative correlation with PALMD expression. PALMD demonstrated significant diagnostic potential in differentiating NSOI. Conclusions: This study identifies PALMD as a potential biomarker linked to NSOI, providing insights into its pathogenesis and offering new avenues for tracking disease progression.

The prognostic and immune significance of Rab11A in pan-cancer and its function and mechanism underlying estrogen receptor targeting in breast cancer.

Rab11A is an important molecule for recycling endosomes and is closely related to the proliferation, invasion, and metastasis of tumors. This study investigated the prognostic and immune significance of Rab11A and validated its potential function and mechanism in breast cancer (BRCA). RNA sequencing data for 33 tumors were downloaded from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression databases. Correlation analysis was used to evaluate the relationship between Rab11A expression and immune characteristics. Potential pathways were identified using the Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analysis. Immunohistochemical analysis, colony formation assay, bromodeoxyuridine incorporation assay, immunofluorescence, and Western blot were used to explore potential function and mechanism. Analysis of the TCGA database showed significant upregulation of Rab11A expression in a variety of cancers. Rab11A was up-regulated in 82.4% of BRCA. High Rab11A expression is associated with poor survival in cancer patients and is a predictor of poor prognosis. CIBERSORT analysis showed that Rab11A was negatively associated with almost all immune cycle activity scores pan-cancer. The results of the TCGA-BRCA cohort were further confirmed by using pathological samples from clinical BRCA patients. The results showed that Rab11A expression was correlated with estrogen receptor (ER) and progesterone receptor expression in BRCA (p<0.05). Knockdown and overexpression of Rab11A affected the proliferation of BRCA cells. Further mechanistic studies revealed that down-regulation of ER alpha (ERα) and up-regulation of ER beta (ERβ) mediated Rab11A-induced inhibition of BRCA cell proliferation. Rab11A expression in pan-cancer is associated with poor prognosis and immune profile. In particular, in BRCA, Rab11A expression regulates cell proliferation by targeting ERα and ERβ. High Rab11A expression is tightly associated with immune characteristics, tumor microenvironment, and genetic mutations. These results provide a reference for exploring the role of Rab11A in pan-cancer and provide a new perspective for revealing potential therapeutic targets in BRCA.

Relation of CMV and brain atrophy to trajectories of immunosenescence in diverse populations.

Immunosenescence (ISC), the aging of the immune system, has largely been studied in populations of European descent. Here, circulating immune cell cytometric data from African-American, Hispanic, and non-Hispanic White participants were generated. Known and novel age effects were identified using either a meta-analysis approach or a parallel genetic approach. Most results are consistent across the three populations, but some cell populations display evidence of heterogeneity, such as a PD-L1 + CD56 + NK cell subset. The study estimated "Immunological Age" (IA) during physiologic aging. While we found no relation of IA to Multiple Sclerosis, IA is associated with entorhinal cortex atrophy, a presymptomatic feature of Alzheimer's disease, linking neurodegeneration and peripheral immunity. ISC trajectories were also inferred, highlighting age, CMV status, and genetic ancestry as key influences. Our assessment offers reference ISC trajectories for personalization of assessments of immune function over the life course in diverse populations.

Construction and validation of a histone-related gene signature for the diagnosis of endometriosis.

Endometriosis is a common chronic disease in childbearing women and a major cause of infertility. Our study aimed to identify and validate a novel gene signature for diagnosing endometriosis based on histone-related genes (HRGs), and to investigate their biological functions in endometriosis. RNA sequence data were downloaded from the Gene Expression Omnibus database, and HRGs were retrieved from the GeneCards database. We identified differentially expressed genes using the limma package, and constructed a diagnostic model using the rms package. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were performed for visualization, annotation, and integrated discovery. Subsequently, we validated the model using the recall and decision curve analysis (DCA). Additionally, we analyzed the immune microenvironment features using CIBERSORT. A total of 18 differentially expressed HRGs were identified in patients with endometriosis compared with controls. GO and KEGG enrichment was mainly in spindle organization, positive regulation of the cell cycle process, progesterone-mediated oocyte maturation, and cellular senescence and cell cycle. We obtained a signature of four HRGs (JUNB, FRY, LMNB1, and SPAG1). DCA revealed that the diagnostic model benefits patients with endometriosis, regardless of the incidence. CIBERSORT analysis showed that the number of plasma cells increased significantly in endometriosis samples from all four datasets. Our findings provide novel insights into the function of HRGs in the development of endometriosis and identify a new signature of four HRGs that may serve as valuable diagnostic markers and therapeutic targets for this disease.

A study on subcutaneous infection model of colibacillosis in broilers: Selected immunological and hematological aspects

Colibacillosis is still a major challenge to poultry industry. This study examined selected immune and hematological features of broilers experimentally infected with E. coli via subcutaneous (sc) route. Fifty-one 5-week-old chickens were randomly assigned to three groups: two controls (NC and SCC) and one experimental (SC) group. The SC group was inoculated by O2 E. coli suspension via sc route in the inguinal region. Three days after inoculation, blood sampling was performed. Bacterial count of liver was determined. Histopathological samples of liver, lung, spleen, thymus, and bursa were also collected. Serum total protein and globulin significantly increased in birds of SC group as compared to control birds (P < 0.05). Birds in SC group also showed decreased albumin/globulin ratio. Serum levels of IL-6, IL-10, and IFN-γ remained statistically the same among groups. Lymphocytosis, monocytosis, thrombocytosis and heterophilia were present in SC group. Heterophils/lymphocytes ratio increased in SC birds. Left shift was observed in SC group with cells showing vacuolated cytoplasm that contained toxic granules. Histologically, lung involvement was less severe than liver. Lymphoid depletion was present in all examined lymphoid organs. E. coli growth was observed in liver samples from SC group but not in control birds. In conclusion, using sc route for induction of colibacillosis was associated with a systemic inflammatory response in broilers and histopathological lesions of thymus, bursa, and spleen three days post-infection. It seems that detection of changes in serum cytokine levels (IL-6, IL-10, and IFN-γ) should be performed in earlier hours of the disease in this model.

Identification of prognostic biomarkers related to retinoic acid metabolism in gliomas and analysis of their impact on the immune microenvironment.

Glioma is a primary tumor of the central nervous system. Numerous investigations have demonstrated that retinoic acid (RA) signaling plays an important role in glioblastoma. This research aimed to develop a RA metabolism-related gene signature associated with glioma. The RA metabolism-related differentially expressed genes were obtained through differential analysis of RA metabolism-related genes in GSE4290. The univariate Cox and least absolute shrinkage and selection operator regression analysis were adopted to build a RA metabolism-related glioma prognostic signature. We further conducted immune feature estimation and functional enrichment analysis between 2 risk subgroups. Finally, the potential drug-targeting prognostic genes were predicted through the DrugBank database. A sum of 10 RA metabolism-related differentially expressed genes between normal and tumor groups were identified. Then, a RA metabolism-related prognostic signature was built based on the 7 prognostic genes (ADH4, DHRS3, DHRS9, LRAT, RDH10, RDH12, and RDH5). Glioma patients were separated into 2 risk subgroups (low-risk vs high-risk) based on the median value of the risk score. We found that monocytes were negatively correlated with DHRS9, while activated naive CD4+T cell was positively correlated with RDH10. These prognostic genes participated in some immune-related processes, such as "B cell-mediated immunity." Finally, 4 drugs targeting DHRS3, LRAT, and RDH12 were predicted, including vitamin A, nicotinamide adenine dinucleotide, ethanol, and cyclohexylformamide. The prognostic signature comprised of ADH4, DHRS3, DHRS9, LRAT, RDH10, RDH12, and RDH5 based on RA metabolism was established, which provided a theoretical basis and reference value for the research of glioma.

Correlation of the treatment sensitivity of patient-derived organoids with treatment outcomes in patients with head and neck cancer (SOTO): protocol for a prospective observational study

IntroductionOrganoids have been successfully used in several areas of cancer research and large living biobanks of patient-derived organoids (PDOs) have been developed from various malignancies. The characteristics of the original...

Hypoxia-related lncRNA correlates with prognosis and immune microenvironment in uveal melanoma

BackgroundHypoxia-related genes are linked to the prognosis of various solid malignant tumors. However, the role of hypoxia-related long non-coding RNAs (HRLs) in uveal melanoma (UVM) remains unclear. This study aimed to identify HRLs associated with UVM prognosis and develop a novel risk signature to predict patient outcomes.MethodsData from 80 UVM samples were obtained from The Cancer Genome Atlas. Prognostic HRLs were screened using Cox univariate and Pearson correlation analyses. HRL signature were constructed using Lasso analysis, and gene enrichment analysis was performed to explore the association between HRLs and immune features. Cell Counting Kit-8 assay was used to measure the propagation of human uveal melanoma (MuM2B) cells, while tumor invasion and migration were evaluated using Transwell and wound-healing experiments. Inflammatory factors and macrophage polarization were evaluated using quantitative PCR.ResultsIn total, 621 prognostic HRLs were screened and constructed in 12 HRLs. The risk score showed a significant correlation with the survival time of patients with UVM. Additionally, HRL correlated with diverse key immune checkpoints, revealing possible targets for immunotherapy. Immune-related pathways were highly enriched in the high-risk group. LINC02367, a protective HRL, was associated with the tumor microenvironment and survival time of patients with UVM. In vitro, LINC02367 significantly influenced MuM2B proliferation and migration. It also modulated macrophage polarization by regulating inflammatory factor levels, thereby affecting the immune microenvironment.ConclusionsWe developed a novel HRL signature to predict prognosis in patients with UVM. HRLs are potential biomarkers and therapeutic targets for the treatment of UVM.

Molecular and Clinical Features of Pancreatic Acinar Cell Carcinoma: A Single-Institution Case Series

Objectives: Acinar cell carcinoma (ACC) accounts for about 1% of pancreatic cancers. The molecular and clinical features of ACC are less characterized than those of pancreatic ductal adenocarcinoma. Methods: We retrospectively evaluated the clinical and molecular features of ACC patients who underwent germline and/or somatic molecular testing at The University of Texas MD Anderson Cancer Center from 2008 to 2022 and two cases from 2023–2024 who underwent RNA and TME analysis by Boston Gene. Patient information was extracted from our institutional database with the approval of the Institutional Review Board. Results: We identified 16 patients with available molecular testing results. Fourteen patients had metastatic disease, one had borderline resectable disease, and one had localized resectable disease at diagnosis. Fifteen patients were wild type for KRAS (one patient had unknown KRAS status). Somatic/germline mutations of DNA damage repair genes (BRCA1/2, PALB2, and ATM) were present in 5 of 12 patients tested for these genes. One patient was found to have RET fusion and responded favorably to selpercatinib for over 42 months. The median overall survival (OS) was 24 months for patients with metastatic disease. One of the additional two cases who underwent BostonGene testing was found to have NTRK1 fusion. RNA and TME analysis by Boston Gene of the two cases reported immune desert features and relatively lower RNA levels of CEACAM5, CD47, CD74, and MMP1 and higher RNA levels of CDH6 compared with PDAC.

Multiomics identification of ALDH9A1 as a crucial immunoregulatory molecule involved in calcific aortic valve disease

Mitochondrial dysfunction and immune cell infiltration play crucial yet incompletely understood roles in the pathogenesis of calcific aortic valve disease (CAVD). This study aimed to identify immune-related mitochondrial genes critical to the pathological process of CAVD using multiomics approaches. The CIBERSORT algorithm was employed to evaluate immune cell infiltration characteristics in CAVD patients. An integrative analysis combining weighted gene coexpression network analysis (WGCNA), machine learning, and summary data-based Mendelian randomization (SMR) was performed to identify key mitochondrial genes implicated in CAVD. Spearman’s rank correlation analysis was also performed to assess the relationships between key mitochondrial genes and infiltrating immune cells. Compared with those in normal aortic valve tissue, an increased proportion of M0 macrophages and resting memory CD4 T cells, along with a decreased proportion of plasma cells and activated dendritic cells, were observed in CAVD patients. Additionally, eight key mitochondrial genes associated with CAVD, including PDK4, LDHB, SLC25A36, ALDH9A1, ECHDC2, AUH, ALDH2, and BNIP3, were identified through the integration of WGCNA and machine learning methods. Subsequent SMR analysis, incorporating multiomics data, such as expression quantitative trait loci (eQTLs) and methylation quantitative trait loci (mQTLs), revealed a significant causal relationship between ALDH9A1 expression and a reduced risk of CAVD. Moreover, ALDH9A1 expression was inversely correlated with M0 macrophages and positively correlated with M2 macrophages. These findings suggest that increased ALDH9A1 expression is significantly associated with a reduced risk of CAVD and that it may exert its protective effects by modulating mitochondrial function and immune cell infiltration. Specifically, ALDH9A1 may contribute to the shift from M0 macrophages to anti-inflammatory M2 macrophages, potentially mitigating the pathological progression of CAVD. In conclusion, ALDH9A1 represents a promising molecular target for the diagnosis and treatment of CAVD. However, further validation through in vivo and n vitro studies is necessary to confirm its role in CAVD pathogenesis and therapeutic potential.

Exploring the diagnostic and immune infiltration roles of disulfidptosis related genes in pulmonary hypertension

BackgroundPulmonary hypertension (PH) is marked by elevated pulmonary artery pressures due to various causes, impacting right heart function and survival. Disulfidptosis, a newly recognized cell death mechanism, may play a role in PH, but its associated genes (DiGs) are not well understood in this context. This study aims to define the diagnostic relevance of DiGs in PH.MethodsUsing GSE11726 data, we analyzed DiGs and their immune characteristics to identify core genes influencing PH progression. Various machine learning models, including RF, SVM, GLM, and XGB, were compared to determine the most effective diagnostic model. Validation used datasets GSE57345 and GSE48166. Additionally, a CeRNA network was established, and a hypoxia-induced PH rat model was used for experimental validation with Western blot analysis.Results12 DiGs significantly associated with PH were identified. The XGB model excelled in diagnostic accuracy (AUC = 0.958), identifying core genes DSTN, NDUFS1, RPN1, TLN1, and MYH10. Validation datasets confirmed the model’s effectiveness. A CeRNA network involving these genes, 40 miRNAs, and 115 lncRNAs was constructed. Drug prediction suggested therapeutic potential for folic acid, supported by strong molecular docking results. Experimental validation in a rat model aligned with these findings.ConclusionWe uncovered the distinct expression patterns of DiGs in PH, identified core genes utilizing an XGB machine-learning model, and established a CeRNA network. Drugs targeting the core genes were predicted and subjected to molecular docking. Experimental validation was also conducted for these core genes.

Causal role of 731 immune cells in diabetic nephropathy: a bi-directional two-sample Mendelian randomization study.

The primary cause of end-stage renal disease (ESRD) is diabetic nephropathy (DN), and a growing body of research indicates that immunology plays a part in how DN develops into ESRD. Our objective is to identify causal relationships between various immune invading cells and DN to identify possible targets for immunotherapy. This study used a complete Mendelian randomization (MR) analysis with two samples to identify the underlying mechanism linking immune cell characteristics with DN. Using publicly available genetic data, we investigated the causal link between 731 immune cell profiles and DN risk. Included were four different types of immune systems: morphological parameters (MP), absolute cell (AC), relative cell (RC), and median fluorescence intensities (MFI). The results' robustness, heterogeneity, and horizontal pleiotropy were confirmed through extensive sensitivity analysis. Following FDR (False Discovery Rate correction method) correction, no statistically significant differences were observed; however, six immunophenotypes were shown to be significantly associated with DN risk at the 0.25 level. Only CD28+ CD4- CD8- T cells were identified as the protective immunophenotype (OR = 0.588, 95% CI 0.437-0.792, P = 4.71 × 10-4). Moreover, DN had no discernible impact on immunophenotyping after FDR correction. Surprisingly, three unadjusted phenotypes with low P values were discovered to be positively correlated with the risk of DN: CD20 on IgD- CD27- B cells (OR = 1.263, 95% CI 1.076-1.482, P = 4.22 × 10-3), CD8 on naive CD8 + T cells with Effector Memory (OR = 1.107, 95% CI 1.013-1.209, P = 2.40 × 10-2), and CD8 on Effector Memory CD8 + T cells (OR = 1.126, 95% CI 1.024-1.239, P = 1.46 × 10-2). Our findings provide a genetic basis for the association between immune cells and DN and should inform future clinical research.

Regulators of placental antibody transfer through a modeling lens.

Infants are vulnerable to infections owing to a limited ability to mount a humoral immune response and their tolerogenic immune phenotype, which has impeded the success of newborn vaccination. Transplacental transfer of IgG from mother to fetus provides crucial protection in the first weeks of life, and maternal immunization has recently been implemented as a public health strategy to protect newborns against serious infections. Despite their early success, current maternal vaccines do not provide comparable protection across pregnancies with varying gestational lengths and placental and maternal immune features, and they do not account for the dynamic interplay between the maternal immune response and placental transfer. Moreover, progress toward the rational design of maternal vaccines has been hindered by inadequacies of existing experimental models and safety challenges of investigating longitudinal dynamics of IgG transfer in pregnant humans. Alternatively, in silico mechanistic models are a logical framework to disentangle the processes regulating placental antibody transfer. This Review synthesizes current literature through a mechanistic modeling lens to identify placental and maternal regulators of antibody transfer, their clinical covariates, and knowledge gaps to guide future research. We also describe opportunities to use integrated modeling and experimental approaches toward the rational design of vaccines against existing and emerging neonatal pathogen threats.

Development and Validation of a Comprehensive Prognostic and Depression Risk Index for Gastric Adenocarcinoma

Depressive disorder contributes to the initiation and prognosis of patients with cancer, but the interaction between cancer and depressive disorder remains unclear. We generated a gastric adenocarcinoma patient-derived xenograft mice model, treated with chronic unpredictable mild stimulation. Based on the RNA-sequence from the mouse model, patient data from TCGA, and MDD-related (major depressive disorder) genes from the GEO database, 56 hub genes were identified by the intersection of differential expression genes from the three datasets. Molecular subtypes and a prognostic signature were generated based on the 56 genes. A depressive mouse model was constructed to test the key changes in the signatures. The signature was constructed based on the NDUFA4L2, ANKRD45, and AQP3 genes. Patients with high risk-score had a worse overall survival than the patients with low scores, consistent with the results from the two GEO cohorts. The comprehensive results showed that a higher risk-score was correlated with higher levels of tumor immune exclusion, higher infiltration of M0 macrophages, M2 macrophages, and neutrophils, higher angiogenetic activities, and more enriched epithelial–mesenchymal transition signaling pathways. A higher risk score was correlated to a higher MDD score, elevated MDD-related cytokines, and the dysfunction of neurogenesis-related genes, and parts of these changes showed similar trends in the animal model. With the Genomics of Drug Sensitivity in Cancer database, we found that the gastric adenocarcinoma patients with high risk-score may be sensitive to Pazopanib, XMD8.85, Midostaurin, HG.6.64.1, Elesclomol, Linifanib, AP.24534, Roscovitine, Cytarabine, and Axitinib. The gene signature consisting of the NDUFA4L2, ANKRD45, and AQP3 genes is a promising biomarker to distinguish the prognosis, the molecular and immune characteristics, the depressive risk, and the therapy candidates for gastric adenocarcinoma patients.

UV-induced reactive oxygen species and transcriptional control of 3-deoxyanthocyanidin biosynthesis in black sorghum pericarp.

Black pericarp sorghum has notable value due to the biosynthesis of 3-deoxyanthocyanidins (3-DOAs), a rare class of bioactive polyphenols valued as antioxidant food additives and as bioactive compounds with cytotoxicity to human cancer cells. A metabolic and transcriptomic study was conducted to ascertain the cellular events leading to the activation of 3-DOA biosynthesis in black sorghum pericarp. Prolonged exposure of pericarp during grain maturation to high-fluence ultraviolet (UV) light resulted in elevated levels of reactive oxygen species (ROS) and the activation of 3-DOA biosynthesis in pericarp tissues. In conjunction with 3-DOA biosynthesis was the transcriptional activation of specific family members of early and late flavonoid biosynthesis pathway genes as well as the downstream activation of defense-related pathways. Promoter analysis of genes highly correlated with 3-DOA biosynthesis in black pericarp were enriched in MYB and HHO5/ARR-B motifs. Light microscopy studies of black pericarp tissues suggest that 3-DOAs are predominantly localized in the epicarp and are associated with the cell wall. A working model of UV-induced 3-DOA biosynthesis in black pericarp is proposed that shares features of plant immunity associated with pathogen attack or mechanical wounding. The present model depicts ROS accumulation, the transcriptional activation of receptor kinases and transcription factors (TFs) including NAC, WRKY, bHLH, AP2, and C2H2 Zinc finger domain. This study identified key biosynthetic and regulatory genes of 3-DOA accumulation in black pericarp and provided a deeper understanding of the gene networks and cellular events controlling this tissue-and genotype-specific trait.

Immune-related glycosylation genes based classification predicts prognosis and therapy options of osteosarcoma

Osteosarcoma is the most common primary bone malignancy, with a very poor prognosis. Aberrant glycosylation is close involvement in osteosarcoma. Accordingly, this study aimed at investigating the role of glycosylation genes in the prognosis and therapy options of osteosarcoma. The microenvironment of osteosarcoma was assessed using estimate algorithm. A total of 20 immune-related glycosylation genes (IRGGs) was identified using Pearson correlation analysis. Accordingly, osteosarcoma patients were divided into C1 and C2 type using consensus clustering. Multiple algorithms (Xcell, MCP-counter, ssGSEA, epic, quantiseq), cancer immune cycle analysis, and GSVA were applied to estimate the immune, molecule and metabolism characteristics of osteosarcoma, indicating that C1 type was featured with high immune infiltration, high glycosylation, enriched MEK signaling, and good prognosis, while C2 type was characterized by more metastasis, enriched immunotherapy-positive gene signatures, high tumor mutation burden, and poor prognosis. Results from TIDE algorithm and immunotherapy datasets suggested the C2 type’s preference of immune checkpoint inhibitors (ICIs), while data of GDSC, CMap analysis and cell experiments indicated that C1 type was sensitivity to MEK inhibitor PD0325901. In addition, univariate Cox and Lasso analysis was combined to establish an IRGGs’ risk score containing 6 genes (B3GNT8, FUT7, GAL3ST4, GALNT14, HS3ST2, and MFNG). The data of DCA and ROC indicated its well prediction of prognosis in osteosarcoma. Finally, cellular location analysis showed that the 6 genes not only distributed in tumor cells but also in immune cells. In summary, the classification and risk score based on IRGGs effectively predicted the prognosis and therapy options of osteosarcoma. Further studies on IRGGs may contribute to the understanding of cancer immunity in osteosarcoma.