A cuproptosis-related gene expression signature predicting clinical prognosis and immune responses in intrahepatic cholangiocarcinoma detected by single-cell RNA sequence analysis.

BACKGROUND: Cholangiocarcinoma represents a malignant neoplasm originating from the hepatobiliary tree, with a subset of tumors developing inside the liver. Intrahepatic cholangiocarcinomas (ICC) commonly exhibit an asymptomatic presentation, rendering both diagnosis and treatment challenging. Cuproptosis, an emerging regulated cell death pathway induced by copper ions, has garnered attention recently. As cancer cells show altered copper metabolism and comparatively higher copper needs, cuproptosis may play a role in the development of ICC. However, studies investigating this possibility are currently lacking. METHODS: Single-cell and bulk RNA sequence data were analyzed, and correlations were established between the expression of cuproptosis-related molecules and ICC patient survival. Genes with predicting survival were used to create a CUPT score using Cox and LASSO regression and tumor mutation burden (TMB) analysis. The CIBERSORT software was employed to characterize immune cell infiltration within the tumors. Furthermore, immune infiltration prediction, biological function enrichment, and drug sensitivity analyses were conducted to explore the potential implications of the cuproptosis-related signature. The effects of silencing solute carrier family 39 member 4 gene (SLC39A4) expression using siRNA were investigated using assays measuring cell proliferation, colony formation, and cell migration. Key genes of cuproptosis were detected by western blotting. RESULTS: The developed CUPT score divided patients into high and low CUPT score groups. Those with a low score had significantly better prognosis and longer survival. In contrast, high CUPT scores were associated with worse clinical outcomes and significantly higher TMB. Comparisons of the two groups also indicated differences in the immune infiltrate present in the tumors. Finally, we were able to identify 95 drugs potentially affecting the cuproptosis pathway. Some of these might be effective in the treatment of ICC. The in vitro experiments revealed that suppressing the expression of SLC39A4 in ICC cell lines resulted in reduced cell proliferation, colony formation, and cell migration. It also led to an increase in cell death and the upregulation of key genes associated with cuproptosis, namely ferredoxin 1 (FDX1) and dihydrolipoyl transacetylase (DLAT). These findings strongly suggest that this cuproptosis-associated molecule may play a pivotal role in the development and metastasis of ICC. CONCLUSIONS: Changes in the expression of a cuproptosis-related gene signature can predict the clinical prognosis of ICC with considerable accuracy. This supports the notion that cuproptosis influences the diversity and complexity of the immune microenvironment, mutational landscape, and biological behavior of ICC. Understanding this pathway better may hold promise for the development of innovative strategies in the management of this disease.

Unraveling the molecular crosstalk and immune landscape between COVID-19 infections and ischemic heart failure comorbidity: New insights into diagnostic biomarkers and therapeutic approaches.

BACKGROUND: Coronavirus disease 2019 (COVID-19), resulting from severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), remains a persistent global health concern. Evidence has highlighted a significant association between COVID-19 and ischemic heart failure (IHF), contributing to disease progression and increased mortality. This study identified diagnostic biomarkers for these comorbidities and elucidated disease progression's molecular mechanisms. METHODS: We retrieved differentially expressed gene (DEG) data for COVID-19 and IHF from publicly available microarray and RNA-Seq datasets to investigate the underlying mechanisms and potential pathways associated with the co-occurrence of COVID-19 and IHF. By intersecting the results from the two diseases, we obtained diagnostic biomarkers using SVM-RFE and LASSO algorithms. Animal experiments and immunological analyses were conducted to help understand the association between SARS-CoV-2 and IHF in patients, enabling early diagnosis of disease progression. Finally, we analyzed the regulatory network of critical genes and identified potential drug compounds that could target the genetic links identified in our study. RESULTS: 1974 common DEGs were identified between COVID-19 and IHF, contributing to disease progression and potential cancer risk by participating in immune and cancer-related pathways. In addition, we identified six hub genes (VDAC3, EIF2AK2, CHMP5, FTL, VPS4A, and CHMP4B) associated with the co-morbidity, and their diagnostic potential was confirmed through validation using relevant datasets and a mouse model. Functional enrichment analysis and examination of immune cell infiltration revealed immune dysregulation after disease progression. The comorbid hub genes exhibited outstanding immunomodulatory capacities. We also constructed regulatory networks tightly linked to both disorders, including transcription factors (TFs), miRNAs, and genes at both transcriptional and post-transcriptional levels. Finally, we identified 92 potential drug candidates to enhance the precision of anti-comorbidity treatment strategies. CONCLUSION: Our study reveals a shared pathogenesis between COVID-19 and IHF, demonstrating that their coexistence exacerbates disease severity. By identifying and consolidating hub genes as pivotal diagnostic biomarkers for COVID-19 and IHF comorbidity, we have made significant advancements in understanding the underlying mechanisms of these conditions. Moreover, our study highlights dysregulated immunity and increased cancer risk in the advanced stages of disease progression. These findings offer novel perspectives for diagnosing and treating IHF progression during SARS-CoV-2 infection.

The circadian rhythm key gene ARNTL2: a novel prognostic biomarker for immunosuppressive tumor microenvironment identification and immunotherapy outcome prediction in human cancers.

Background: Aryl hydrocarbon receptor nuclear translocator-like 2 (ARNTL2) belongs to the b HLH- PAS domain transcription factor family and is one of the key clock genes that control the circadian rhythm. ARNTL2 plays an important role in human biological functions. However, its role in various tumors, especially in the tumor immune microenvironment (TIME) and immunotherapy, remains unclear. Methods: We integrated data from cancer patients from multiple databases, including the Cancer Genome Atlas, Cancer Cell Lineage Encyclopedia, Genotype Tissue Expression, Human Protein Atlas, cBioPortal, TIMER, and ImmuCellAI, with data from a large clinical study, three immunotherapy cohorts, and in vitro experiments to investigate the involvement of ARNTL2 expression in cancer prognosis and immune response. Results: ARNTL2 displayed abnormal expression within most malignant tumors, and is significantly associated with poorer survival and pathologic staging. Through gene-set enrichment analysis (GSEA) and gene-set variation analysis (GSVA), we found that ARNTL2 not only regulates cell cycle-related functions to promote cell proliferation but also regulates autoimmunity-related functions of the innate and adaptive immune systems, and other immune-related signaling pathways. In addition, ARNTL2 overexpression contributes to an immunosuppressive tumor microenvironment that plays a key role in immunosuppression-related features, such as the expression of immunosuppression-related genes and pathways and the number of immunosuppressive-infiltrating cells, including regulatory T cells (Tregs), tumor-associated macrophages (TAMs), and cancer-associated fibroblasts (CAFs). The group of patients with low ARNTL2 expression who received immune checkpoint inhibitors (ICI) therapy had better response rates and longer survival when compared to those with high ARNTL2 expression. Conclusion: The findings of this study suggest that ARNTL2 is a potential human oncogene that plays an important role in tumorigenesis and cancer immunity. Elevated ARNTL2 expression indicates an immunosuppressive tumor microenvironment. Targeting ARNTL2 in combination with ICI therapy could bring more significant therapeutic benefits to patients with cancer. Our study sheds light on the remarkable potential of ARNTL2 in tumor immunity and provides a novel perspective for anti-tumor strategies.

Cuproptosis-related signature predicts prognosis, immunotherapy efficacy, and chemotherapy sensitivity in lung adenocarcinoma.

Background: Cuproptosis is a novel form of programmed cell death that disrupts the tricarboxylic acid (TCA) cycle and mitochondrial function. The mechanism of cuproptosis is quite different from that of common forms of cell death such as apoptosis, pyroptosis, necroptosis, and ferroptosis. However, the potential connection between cuproptosis and tumor immunity, especially in lung adenocarcinoma (LUAD), is poorly understood. Methods: We used machine learning algorithms to develop a cuproptosis-related scoring system. The immunological features of the scoring system were investigated by exploring its association with clinical outcomes, immune checkpoint expression, and prospective immunotherapy response in LUAD patients. The system predicted the sensitivity to chemotherapeutic agents. Unsupervised consensus clustering was performed to precisely identify the different cuproptosis-based molecular subtypes and to explore the underlying tumor immunity. Results: We determined the aberrant expression and prognostic relevance of cuproptosis-related genes (CRGs) in LUAD. There were significant differences in survival, biological function, and immune infiltration among the cuproptosis subtypes. In addition, the constructed cuproptosis scoring system could predict clinical outcomes, tumor microenvironment, and efficacy of targeted drugs and immunotherapy in patients with LUAD. After validating with large-scale data, we propose that combining the cuproptosis score and immune checkpoint blockade (ICB) therapy can significantly enhance the efficacy of immunotherapy and guide targeted drug application in patients with LUAD. Conclusion: The Cuproptosis score is a promising biomarker with high accuracy and specificity for determining LUAD prognosis, molecular subtypes, immune cell infiltration, and treatment options for immunotherapy and targeted therapies for patients with LUAD. It provides novel insights to guide personalized treatment strategies for patients with LUAD.

Application of Nonlinear Models Combined with Conventional Laboratory Indicators for the Diagnosis and Differential Diagnosis of Ovarian Cancer.

Existing biomarkers for ovarian cancer lack sensitivity and specificity. We compared the diagnostic efficacy of nonlinear machine learning and linear statistical models for diagnosing ovarian cancer using a combination of conventional laboratory indicators. We divided 901 retrospective samples into an ovarian cancer group and a control group, comprising non-ovarian malignant gynecological tumor (NOMGT), benign gynecological disease (BGD), and healthy control subgroups. Cases were randomly assigned to training and internal validation sets. Two linear (logistic regression (LR) and Fisher's linear discriminant (FLD)) and three nonlinear models (support vector machine (SVM), random forest (RF), and artificial neural network (ANN)) were constructed using 22 conventional laboratory indicators and three demographic characteristics. Model performance was compared. In an independent prospectively recruited validation set, the order of diagnostic efficiency was RF, SVM, ANN, FLD, LR, and carbohydrate antigen 125 (CA125)-only (AUC, accuracy: 0.989, 95.6%; 0.985, 94.4%; 0.974, 93.4%; 0.915, 82.1%; 0.859, 80.1%; and 0.732, 73.0%, respectively). RF maintained satisfactory classification performance for identifying different ovarian cancer stages and for discriminating it from NOMGT-, BGD-, or CA125-positive control. Nonlinear models outperformed linear models, indicating that nonlinear machine learning models can efficiently use conventional laboratory indicators for ovarian cancer diagnosis.

Circular RNA in multiple myeloma: A new target for therapeutic intervention.

Circular RNAs (circRNAs) are RNA molecules with a stable closed-loop structure that are found in a variety of organisms. CircRNAs are highly stable and conserved, and they play important roles in transcriptional regulation and splicing. Multiple Myeloma (MM) is a malignant proliferative disease for which there are currently no effective and comprehensive treatments. Numerous circRNAs may contribute to the development and progression of MM by acting as oncogenes or regulators. Due to the unique function of circRNAs, they have a high potential for regulating the biological functions (including proliferation and apoptosis) of MM cells, and their expression levels and molecular mechanism are closely related to their diagnostic value, therapeutic sensitivity, and clinical prognosis of MM patients. In this review, we aim to provide a detailed overview of the structure and function of circRNAs and demonstrate the potential therapeutic value and potential mechanism of circRNAs in MM via experiments and clinical trials.

m5C Regulator-mediated methylation modification clusters contribute to the immune microenvironment regulation of multiple myeloma.

Background: Multiple myeloma (MM) is a hematological malignancy in which plasma cells proliferate abnormally. 5-methylcytosine (m5C) methylation modification is the primary epigenetic modification and is involved in regulating the occurrence, development, invasion, and metastasis of various tumors; however, its immunological functions have not been systematically described in MM. Thus, this study aimed to clarify the significance of m5C modifications and how the immune microenvironment is linked to m5C methylation in MM. Method: A total of 483 samples (60 healthy samples, 423 MM samples) from the Gene Expression Omnibus dataset were acquired to assess the expression of m5C regulators. A nomogram model was established to predict the occurrence of MM. We investigated the impact of m5C modification on immune microenvironment characteristics, such as the infiltration of immunocytes and immune response reactions. We then systematically evaluated three different m5C expression patterns to assess immune characteristics and metabolic functional pathways and established m5C-related differentially expressed genes (DEGs). In addition, biological process analysis was performed and an m5C score was constructed to identify potentially significant immunological functions in MM. Result: Differential expressions of m5C regulators were identified between healthy and MM samples. The nomogram revealed that m5C regulators could predict higher disease occurrence of MM. We identified three distinct m5C clusters with unique immunological and metabolic characteristics. Among the three different m5C clusters, cluster C had more immune characteristics and more metabolism-related pathways than clusters A and B. We analyzed 256 m5C-related DEGs and classified the samples into three different m5C gene clusters. Based on the m5C and m5C gene clusters, we calculated m5C scores and classified each patient into high- and low-m5C score groups. Conclusion: Our study demonstrated that m5C modification is involved in and contributes to the diversity and complexity of the immune microenvironment, which offers promise for the development of accurate therapeutic strategies.

Potential biomarkers for diagnosis and assessment of disease activity in systemic lupus erythematosus.

BACKGROUND: Systemic lupus erythematosus (SLE) is a chronic autoimmune disease involving multiple system functions. Our study aimed to screen out more effective new indicators that can assist clinical diagnosis and judge disease activity. METHODS: We first screened serum levels of 45 cytokines of SLE patients (n = 3) and healthy controls (n = 3). Subsequently, we selected five elevated cytokines for verification with an expanded sample size. Then, the relationship between cytokines and laboratory parameters was also investigated. Finally, we used receiver operating characteristic (ROC) curves to assess the clinical value of these cytokines. RESULTS: Through screening of 45 cytokines, 15 were found to be elevated in SLE patients. We chose five cytokines (IL-6, IL-10, IL-1RA, IP-10 and LIF) for further research and found elevated expression of all five cytokines in SLE patients. Serum levels of IL-10, IL-1RA and LIF were positively correlated with SLEDAI-2K score. Besides, the level of IL-10 was significantly positively correlated with serum IgG and erythrocyte sedimentation rate (ESR); IL-1RA was significantly negatively correlated with C3 and C4; and LIF was significantly positively correlated with serum IgG, C-reactive protein (CRP), and ESR. Furthermore, IL-1RA and LIF were strongly positively correlated with 24-hour urine protein levels. The ROC analysis showed that IL-1RA has good diagnostic value, and IL-10 and LIF levels can be utilized to discriminate between active and inactive SLE. CONCLUSION: IL-1RA can be used as a biomarker for diagnosing SLE, while IL-10 and LIF can be indicators to discriminate between active and inactive SLE.

AP3S1 is a Novel Prognostic Biomarker and Correlated With an Immunosuppressive Tumor Microenvironment in Pan-Cancer.

Background: Adaptor-related protein complex 3, sigma one subunit (AP3S1) is one of the encoding subunits of the adaptor complex AP-3. However, its role in various tumor types and relationship with the tumor immune microenvironment (TIME) remains unclear. Methods: AP3S1 expression was analyzed using datasets from The Cancer Genome Atlas, Genotype-Tissue Expression, UALCAN, and HPA databases. Then, we performed a systematic analysis of the genetic alterations, clinical features, and prognostic value of AP3S1 in pan-cancer. Gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were used to identify the signaling pathways associated with AP3S1. The correlation between immune cell infiltration and AP3S1 expression was analyzed using immune cell infiltration data from the ImmuCellAI, TIMER2, and a previous study. Finally, we analyzed the association of AP3S1 with tumor mutational burden (TMB), microsatellite instability (MSI), and immune-related genes. Results: We found AP3S1 overexpression in most tumors and a significant association with low survival rates. GSEA and GSVA results show that AP3S1 is involved in tumor progression and associated with immune pathways in different tumor types. We also found that AP3S1 expression was positively correlated with the level of infiltration of immunosuppressive cells (tumor-associated macrophages, cancer-associated fibroblasts, Tregs) and negatively correlated with immune killer cells, including NK cells and CD8+ T cells, in pan-cancer. The expression of AP3S1 could affect TMB and MSI in various cancers. In addition, AP3S1 was positively correlated with most immunosuppressive genes, including PD-1, PD-L1, CTLA4, LAG3 and TIGIT in most cancer types. Conclusion: Our study reveals that AP3S1 is a potential pan-cancer oncogene and plays an essential role in tumorigenesis and cancer immunity. Elevated expression of AP3S1 indicates an immunosuppressive microenvironment and can be used as a potential prognostic biomarker and a target for immunotherapy.

Research advances of N6-methyladenosine in diagnosis and therapy of pancreatic cancer.

BACKGROUND: N6-methyladenosine (m6A) is the addition of a methyl group on the N6 position of adenosine and is the most prevalent and abundant epigenetic modification in eukaryote mRNA. m6A marks are added to mRNA by the m6A methyltransferase complex ("writers"), removed by m6A demethylases ("erasers"), and recognized by m6A-binding proteins ("readers"). Recent evidence has shown that the m6A modification plays a crucial role in the pathogenic mechanism and malignant progression of pancreatic cancer, with roles in cell survival, proliferation, migration, invasion, tumor metastasis, and drug resistance. METHODS: Literature was searched in Pubmed and Web of Science for the following keywords: "N6-methyladenosine", "pancreatic cancer", "epigenetic modification", "immunotherapy". RESULTS: Among classical m6A regulators, while METTL3, METTL14, WTAP, FTO, YTHDF2, IGF2BP1-3, hnRNPC, and NKAP are upregulated in pancreatic cancer, METTL16 and ALKBH5 are downregulated in pancreatic cancer. m6A modification has been investigated in pancreatic cancer therapy. CONCLUSION: Dysregulated m6A and its related factors in pancreatic cancer cells and patients indicate their potential values as novel biomarkers in pancreatic cancer diagnosis and targeted therapy.

Pre-existing hypertension is associated with poor progression-free survival in newly diagnosed multiple myeloma patients.

Approximately 31% of patients diagnosed with multiple myeloma (MM) have pre-existing hypertension, but its effects on patient survival have not been investigated. We collected data from 228 newly diagnosed patients with MM and found that 71 (31.1%) had pre-existing hypertension. The impact of pre-existing hypertension on MM patients was determined by evaluating progression-free survival (PFS). Kaplan-Meier analyses revealed a significantly lower PFS in the pre-existing hypertension group than their non-hypertensive counterparts (median 22.6 vs 34.8 months, respectively). The multivariable Cox proportional hazards model showed that pre-existing hypertension was an independent risk factor for PFS reduction in MM patients. Moreover, the risk of disease progression in MM patients with pre-existing hypertension was higher than in non-hypertension comparator patients (hazard ratio 1.735, 95% confidence interval 1.261-2.387). In MM patients with pre-existing hypertension, Kaplan-Meier analyses found that those with a higher risk of hypertension had a significantly shorter PFS than those with lower risk (median 19.3 vs 25.4 months, respectively). However, multivariate Cox regression analysis showed that the risk stratification of hypertension was not an independent risk factor for poor PFS in MM patients with pre-existing hypertension. Our study demonstrates that pre-existing hypertension was significantly associated with a lower PFS in newly diagnosed MM patients.

Hypertonic saline maintains coagulofibrinolytic homeostasis following moderate­to­severe traumatic brain injury by regulating monocyte phenotype via expression of lncRNAs.

Traumatic brain injury (TBI) is the most common cause of death and permanent disability in people aged <45, and is associated with secondary brain injury and bleed progression, resulting in increased morbidity and mortality. TBI may also induce innate host defense responses characterized by activation of resident microglia and astrocytes, brain microvascular endothelial cells and peripheral blood monocytes. In the present study, 34 patients with moderate­to­severe traumatic brain injury were randomly divided into two groups, including a 7.5% hypertonic saline (HS) treatment group (4 ml/kg) and 3% HS treatment group (4 ml/kg). The results demonstrated that treatment with 7.5% HS decreased the intracranial pressure and improved coagulofibrinolytic homeostasis. Analysis of the monocyte subsets revealed significant reduction in the proportion of cluster of differentiation (CD)14++CD16+ circulating inflammatory monocytes in the 7.5% HS group. In addition, 7.5% HS treatment downregulated the expression of long non­coding (lnc) RNA2448­11 and lncRNA1403 in the peripheral blood mononuclear cells of patients with TBI. Using reverse transcription­quantitative polymerase chain reaction, it was determined that 7.5% HS regulated the expression of tumor necrosis factor­α, interleukin­1ß, transforming growth factor­ß and thrombomodulin, which are the target genes of lncRNA2448­11 and lncRNA1403. These results indicated that 7.5% HS improved the intracranial pressure and coagulofibrinolytic homeostasis by modulating the phenotype of monocytes through lncRNA2448­11 and lncRNA1403. These findings provided evidence that initial resuscitation with HS imparts functional changes to inflammatory cells following TBI, thereby reducing potential neuroinflammatory events associated with secondary brain injury.