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RAB37 Exerts a Context-Dependent Role in Cutaneous Melanoma Progression by Promoting Tumor Cell Proliferation and Being Associated with Favorable Immune Characteristics.
BACKGROUND: Rab proteins and small GTPase-mediated vesicle trafficking pathways play important roles in tumor progression and the tumor microenvironment. However, the biological function and clinical significance of RAB37 in cutaneous melanoma (CM) remain unclear. This study investigated the expression pattern, prognostic value, biological function, and immune-related characteristics of RAB37 in CM. METHODS: RAB37 expression and prognostic significance were analyzed using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. Kaplan-Meier and Cox regression analyses were performed to evaluate prognostic value. Spearman correlation analysis assessed associations between RAB37 expression and immune cell infiltration, immune checkpoint blockade (ICB)-related signatures, and inflammatory cytokines. Functional roles of RAB37 were validated using loss- and gain-of-function experiments in A375 and WM-115 melanoma cells. CCK-8, EdU, and Transwell assays evaluated cell proliferation and migration. Single-cell functional analysis was performed using CancerSEA. RESULTS: RAB37 expression was significantly higher in metastatic than in primary CM tissues. Elevated RAB37 expression and hypermethylation of the cg26263675 CpG site were associated with favorable survival outcomes. A prognostic nomogram integrating clinicopathological characteristics and RAB37 methylation was established. Functional experiments demonstrated that RAB37 knockdown significantly inhibited, whereas RAB37 overexpression promoted, melanoma cell proliferation and migration in both A375 and WM-115 cells. RAB37 expression was significantly associated with immune cell infiltration, ICB-related signatures, inflammatory cytokines, and immune-related pathways, including T-cell receptor signaling, PD-1 checkpoint signaling, IL-2/STAT5 signaling, and inflammatory responses. Single-cell analysis further revealed a positive association between RAB37 expression and inflammation-related functional states. CONCLUSION: RAB37 exhibits a context-dependent role in CM by promoting malignant cellular behaviors while being associated with immune-related characteristics and favorable clinical outcomes. These findings suggest that RAB37 may serve as a potential prognostic biomarker and provide new insights into the interplay between CM progression and the tumor immune microenvironment.
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Loss of OBSCN expression promotes bladder cancer progression but enhances the efficacy of PD-L1 inhibitors.
BACKGROUND: As the objective overall response rate to immune checkpoint inhibitors (ICIs) is less than 30% in late stage or metastatic bladder cancer (BLCA), elucidating the intrinsic mechanisms of immune evasion is of great importance for the discovery of predictive and prognostic biomarkers and the exploration of novel targets for intervention. Recent studies have shown that OBSCN and the cytoskeletal protein it encodes, obscurin, play an important role in tumour progression. However, no studies have reported the role of OBSCN in BLCA. METHODS: RNA sequencing and clinical data were downloaded from multiple public databases including The Cancer Genome Atlas and the Gene Expression Omnibus. Immunohistochemistry (IHC) was performed on tissue microarrays including 80 BLCA patients from Shuguang Hospital. Kaplan-Meier curves with log-rank test, univariate and multivariate COX regression were performed to evaluate the prognostic efficacy of OBSCN expression. In vitro experiments were conducted to determine the role of OBSCN deficiency in promoting BLCA progression. Pan-cancer tumour immune microenvironment (TIME) analysis was performed to explore the potential correlation between OBSCN deficiency and immune evasion. RESULTS: Pan-cancers and single-cell sequencing analysis revealed that the expression level and proportion of OBSCN was significantly decreased in BLCA cells compared to normal urothelium. Survival curves showed that BLCA patients with low OBSCN expression had a worse prognosis, yet a better clinical response to PD-L1 ICIs. Gene set variation analysis and Gene set enrichment analysis revealed that epithelial-mesenchymal transition (EMT) and immune-related processes were significantly enriched in BLCA samples with low OBSCN expression. In vitro experiments identified that OBSCN-deficient BLCA cells enhanced invasion, migration and EMT. Pan-cancer analysis of TIME revealed that neoantigen, tumor mutation burden, CD8+T cells and immune checkpoints were significantly negatively associated with OBSCN expression. IHC and Western blot assay identified that BLCA samples with low OBSCN expression had more CD8+ T-cell infiltration and higher PD-L1 expression. CONCLUSIONS: This study confirmed that BLCA patients with low OBSCN expression had a worse prognosis but a superior response to ICIs, providing a reference for individualised treatment of BLCA patients.
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Immune landscape in liver of neonatal mice with phlebotomy-induced anemia.
BACKGROUND: Severe anemia is a common comorbidity in preterm infants in the neonatal intensive care unit, which is caused by phlebotomy, low erythropoietin levels, low red blood cell (RBC) lifespan, and exacerbated by the underlying erythropoietic immaturity. Anemia causes tissue hypoxia, which may alter the hematopoiesis niche in the liver. This study utilized our preclinical mouse model of phlebotomy-induced anemia (PIA) to investigate the immune cell atlas in the liver. METHODS: C57BL/6 mice were subjected to timed phlebotomy between postnatal days 2-10 to induce severe anemia. Immune cells in anemic liver were characterized by Single-cell (sc) RNA-sequencing and a flow cytometry approach. RESULTS: The scRNA-seq analysis revealed that PIA is associated with an altered immune landscape of the neonatal murine liver. We identified increased numbers of Ly6C2+monocytes and Gypa+erythroid cells and decreased numbers of lymphocytes (CD20+ [MS4a1]-B cells and Tcells) in the anemic liver. Further analysis of monocytes revealed a pro-inflammatory and highly chemotactic phenotype, while erythroid cells displayed a downregulation of inflammatory markers and maturational deficits. Lymphocytes (B and T cells) exhibited suppressed lipid metabolism processes, including those of steroids and hormones. CONCLUSION: PIA in neonatal mouse pups is associated with myelopoiesis (specifically monopoiesis) and erythropoiesis while suppressing lymphopoiesis in the liver. IMPACT: Anemia is nearly universal in preterm infants and is associated with increased morbidity and mortality worldwide, investigation of immune cell response in settings of preclinical anemia may be an index of therapeutic targets to modulate the response in anemia-related comorbidity. Our findings showed that phlebotomy-induced anemia in murine pup alters liver hematopoiesis including myelopoiesis and stressed erythropoiesis with suppressed lymphopoiesis. This study sheds light on emergency myelopoiesis, stressed erythropoiesis, and deficiency of lymphocytes in anemic liver, which may provide novel insight into the development of therapeutics to treat anemia in preterm infants and neonates.
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Construction of a human epidermal growth factor receptor 2-related gene risk model for predicting breast cancer prognosis.
The present study aimed to construct a human epidermal growth factor receptor 2 (HER2)-related gene risk model to predict breast cancer prognosis. Gene expression and clinical follow-up data were extracted from The Cancer Genome Atlas database, while the GSE7390 dataset was obtained from the Gene Expression Omnibus database. Prognostic and clinical feature analyses were performed. In addition, differentially expressed genes (DEGs) between HER2-negative and -positive groups were screened, followed by enrichment analysis. Subsequently, a prognostic model was established, and prognosis was predicted using a nomogram. In addition, the association of risk score with immunity was analyzed, and single-cell analysis was performed. Next, key genes were identified by reverse transcription-quantitive PCR (RT-qPCR) analysis. The results revealed that HER2 was significantly associated with estrogen receptor status, progesterone receptor status, N stage, American Joint Committee on Cancer stage, mutation count and tumor mutation burden of breast cancer. AS601245, AP.24534 and roscovitine were the top three chemotherapeutic agents showing the highest sensitivity differences between the risk groups. A total of 251 DEGs between HER2-negative and -positive groups were screened, which were found to be significantly involved in the Kyoto Encyclopedia of Genes and Genomes pathway of estrogen signaling, PI3K-AKT signaling pathway and chemical carcinogenesis-receptor activation. Eight prognostic gene models were constructed, and it was found that patients in the high-risk group had significantly shorter survival times than those in the low-risk group. A nomogram, incorporating risk groups and clinicopathological features, demonstrated strong predictive ability and high accuracy. The RT-qPCR results indicated that the expression of electron transfer flavoprotein subunit α, rap guanine nucleotide exchange factor-like 1, keratin 7, cluster of differentiation 24, proline rich 15-like, arachidonate 15-lipoxygenase type B, ELOVL fatty acid elongase 2 and C-X-C motif chemokine ligand 9 was consistent with the results of bioinformatic analysis. In conclusion, the HER2-related risk model and nomogram developed in the present study demonstrated high accuracy in predicting patient survival.
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A novel zinc finger protein gene signature for prognostic prediction, tumor microenvironment characterization, and therapeutic response in uterine corpus endometrial carcinoma.
Zinc finger protein (ZNF) family is the largest transcription factor family in the human genome. Studies have shown that the aberrant expression of ZNF had a potential role in tumorigenesis. However, the role of ZNF family genes in uterine corpus endometrial carcinoma (UCEC) is still not systematically understood. Transcriptomic profiles and clinical data of endometrial carcinoma were obtained from TCGA and GEO databases. Based on differentially expressed ZNF genes, unsupervised clustering was employed to stratify samples into distinct subtypes, followed by enrichment analysis to compare gene expression patterns and pathway alterations across subgroups. Patients were subsequently divided into training and test cohorts, through univariate COX regression, LASSO (least absolute shrinkage and selection operator) regression, and multivariate COX regression analyses, we identified prognostic ZNF genes in UCEC. A risk scoring model was established based on these prognostic ZNF genes, and its predictive performance was validated using extensive clinical data. The model was further evaluated for its associations with tumor microenvironment, immune infiltration, immunotherapy response, somatic mutations, and drug sensitivity. Additionally, single-cell RNA sequencing data and the human protein atlas (HPA) database were utilized to investigate the cellular-level functions and impacts of ZNF genes. We stratified UCEC patients into three subtypes based on differentially expressed ZNF genes, which exhibited distinct prognostic outcomes and pathway enrichment profiles. Eight prognostic ZNF genes were identified and incorporated into a ZNF scoring system named ZNF score to quantify patient risk. The ZNF score integrated with clinical characteristics demonstrated robust predictive performance in UCEC patients. Immune infiltration analysis demonstrated a significant increase in M1 Macrophages and M2 Macrophages abundance within the high-risk group. Drug sensitivity analysis identified potential therapeutic agents. Single-cell analysis, immunohistochemistry demonstrated and data-independent acquisition based quantitative proteomic analysis lower expression of most ZNF genes in tumor tissues compared to normal tissues, with predominant distribution in endothelial and epithelial cells. This study represents the first investigation utilizing ZNF genes to determine prognostic outcomes in UCEC patients. Our findings shed light on the potential of the ZNF score as a tool to evaluate ZNF expression patterns, immune cell infiltration, response to pharmacotherapy, clinicopathological features, and survival outcomes in UCEC. This may provide the more effective guide to select immunotherapeutic strategies of UCEC in the future.
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ANGPTL4 mediated mesothelial-mesenchymal transition in pulmonary fibrosis: a potential therapeutic target.
BACKGROUND: Glycolysis plays a major role in progression of idiopathic pulmonary fibrosis (IPF). Here, we aim to explore the predictive signature based on glycolysis-related genes for predicting the prognosis and identified a potential therapeutic target for IPF. METHODS: Gene expression data of bronchoalveolar lavage (BAL) cells and clinical information were downloaded from the Gene Expression Omnibus database. Bioinformatic analysis was then performed to identify differentially expressed genes (DEGs). Lasso multivariate cox analysis and multivariate Cox regression were used to establish a gene signature. The prediction model was evaluated using the time-dependent receiver operating characteristic (ROC) curve and validated using an external independent dataset. The expression of these key genes in cellular level analyzed from Single Cell Expression Atlas. Cell Counting Kit-8 assay, immunofluorescence, wound healing and plasmid transfection were performed. RESULTS: A total of 4 gene (ANGPTL4, ME2, TPBG and IER3), which were associated with the prognosis of IPF patients, were selected to establish our signature. The prediction model was an independent prognostic indicator for IPF patients. ANGPTL4 was significantly upregulated in pleural mesothelial cells (PMCs). In vitro assay showed that ANGPTL4 promoted PMCs proliferation and migration. Knockdown of ANGPTL4 can inhibit mesothelial-mesenchymal transition by suppressed glycolysis-associated gene, such as PGM1, GPI, PGK1, LDHA, ALDOA, ENO1 and TPI1. CONCLUSIONS: Our research established a glycolysis-associated gene signature that holds potential to assist clinicians in the personalized management of IPF. Furthermore, we identified that ANGPTL4 mediates mesothelial-mesenchymal transition, suggesting its viability as a therapeutic target for IPF treatment.
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Comprehensive immunoproteogenomic analyses of malignant pleural mesothelioma.
We generated a comprehensive atlas of the immunologic cellular networks within human malignant pleural mesothelioma (MPM) using mass cytometry. Data-driven analyses of these high-resolution single-cell data identified 2 distinct immunologic subtypes of MPM with vastly different cellular composition, activation states, and immunologic function; mass spectrometry demonstrated differential abundance of MHC-I and -II neopeptides directly identified between these subtypes. The clinical relevance of this immunologic subtyping was investigated with a discriminatory molecular signature derived through comparison of the proteomes and transcriptomes of these 2 immunologic MPM subtypes. This molecular signature, representative of a favorable intratumoral cell network, was independently associated with improved survival in MPM and predicted response to immune checkpoint inhibitors in patients with MPM and melanoma. These data additionally suggest a potentially novel mechanism of response to checkpoint blockade: requirement for high measured abundance of neopeptides in the presence of high expression of MHC proteins specific for these neopeptides.
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Analysis of the molecular nature associated with microsatellite status in colon cancer identifies clinical implications for immunotherapy.
BACKGROUND: Microsatellite instability in colon cancer implies favorable therapeutic outcomes after checkpoint blockade immunotherapy. However, the molecular nature of microsatellite instability is not well elucidated. METHODS: We examined the immune microenvironment of colon cancer using assessments of the bulk transcriptome and the single-cell transcriptome focusing on molecular nature of microsatellite stability (MSS) and microsatellite instability (MSI) in colorectal cancer from a public database. The association of the mutation pattern and microsatellite status was analyzed by a random forest algorithm in The Cancer Genome Atlas (TCGA) and validated by our in-house dataset (39 tumor mutational burden (TMB)-low MSS colon cancer, 10 TMB-high MSS colon cancer, 15 MSI colon cancer). A prognostic model was constructed to predict the survival potential and stratify microsatellite status by a neural network. RESULTS: Despite the hostile CD8+ cytotoxic T lymphocyte (CTL)/Th1 microenvironment in MSI colon cancer, a high percentage of exhausted CD8+ T cells and upregulated expression of immune checkpoints were identified in MSI colon cancer at the single-cell level, indicating the potential neutralizing effect of cytotoxic T-cell activity by exhausted T-cell status. A more homogeneous highly expressed pattern of PD1 was observed in CD8+ T cells from MSI colon cancer; however, a small subgroup of CD8+ T cells with high expression of checkpoint molecules was identified in MSS patients. A random forest algorithm predicted important mutations that were associated with MSI status in the TCGA colon cancer cohort, and our in-house cohort validated higher frequencies of BRAF, ARID1A, RNF43, and KM2B mutations in MSI colon cancer. A robust microsatellite status-related gene signature was built to predict the prognosis and differentiate between MSI and MSS tumors. A neural network using the expression profile of the microsatellite status-related gene signature was constructed. A receiver operating characteristic curve was used to evaluate the accuracy rate of neural network, reaching 100%. CONCLUSION: Our analysis unraveled the difference in the molecular nature and genomic variance in MSI and MSS colon cancer. The microsatellite status-related gene signature is better at predicting the prognosis of patients with colon cancer and response to the combination of immune checkpoint inhibitor-based immunotherapy and anti-VEGF therapy.
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Dissecting hematopoietic and renal cell heterogeneity in adult zebrafish at single-cell resolution using RNA sequencing.
Recent advances in single-cell, transcriptomic profiling have provided unprecedented access to investigate cell heterogeneity during tissue and organ development. In this study, we used massively parallel, single-cell RNA sequencing to define cell heterogeneity within the zebrafish kidney marrow, constructing a comprehensive molecular atlas of definitive hematopoiesis and functionally distinct renal cells found in adult zebrafish. Because our method analyzed blood and kidney cells in an unbiased manner, our approach was useful in characterizing immune-cell deficiencies within DNA-protein kinase catalytic subunit (prkdc), interleukin-2 receptor γ a (il2rga), and double-homozygous-mutant fish, identifying blood cell losses in T, B, and natural killer cells within specific genetic mutants. Our analysis also uncovered novel cell types, including two classes of natural killer immune cells, classically defined and erythroid-primed hematopoietic stem and progenitor cells, mucin-secreting kidney cells, and kidney stem/progenitor cells. In total, our work provides the first, comprehensive, single-cell, transcriptomic analysis of kidney and marrow cells in the adult zebrafish.
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Analysis of CDKN1C in fetal growth restriction and pregnancy loss.
Background: Cyclin-dependent kinase inhibitor 1C (CDKN1C) is a key negative regulator of cell growth encoded by a paternally imprinted/maternally expressed gene in humans. Loss-of-function variants in CDKN1C are associated with an overgrowth condition (Beckwith-Wiedemann Syndrome) whereas "gain-of-function" variants in CDKN1C that increase protein stability cause growth restriction as part of IMAGe syndrome ( Intrauterine growth restriction, Metaphyseal dysplasia, Adrenal hypoplasia and Genital anomalies). As three families have been reported with CDKN1C mutations who have fetal growth restriction (FGR)/Silver-Russell syndrome (SRS) without adrenal insufficiency, we investigated whether pathogenic variants in CDKN1C could be associated with isolated growth restriction or recurrent loss of pregnancy. Methods: Analysis of published literature was undertaken to review the localisation of variants in CDKN1C associated with IMAGe syndrome or fetal growth restriction. CDKN1C expression in different tissues was analysed in available RNA-Seq data (Human Protein Atlas). Targeted sequencing was used to investigate the critical region of CDKN1C for potential pathogenic variants in SRS (n=66), FGR (n=37), DNA from spontaneous loss of pregnancy (n= 22) and women with recurrent miscarriages (n=78) (total n=203). Results: All published single nucleotide variants associated with IMAGe syndrome are located in a highly-conserved "hot-spot" within the PCNA-binding domain of CDKN1C between codons 272-279. Variants associated with familial growth restriction but normal adrenal function currently affect codons 279 and 281. CDKN1C is highly expressed in the placenta compared to adult tissues, which may contribute to the FGR phenotype and supports a role in pregnancy maintenance. In the patient cohorts studied no pathogenic variants were identified in the PCNA-binding domain of CDKN1C. Conclusion: CDKN1C is a key negative regulator of growth. Variants in a very localised "hot-spot" cause growth restriction, with or without adrenal insufficiency. However, pathogenic variants in this region are not a common cause of isolated fetal growth restriction phenotypes or loss-of-pregnancy/recurrent miscarriages.