Correlation of CCL8 expression with immune cell infiltration of skin cutaneous melanoma: potential as a prognostic indicator and therapeutic pathway

Narrow band imaging-based radiogenomics for predicting radiosensitivity in nasopharyngeal carcinoma

Objectives

This study aims to assess the efficacy of narrow band imaging (NBI) endoscopy in utilizing radiomics for predicting radiosensitivity in nasopharyngeal carcinoma (NPC), and to explore the associated molecular mechanisms.

Materials

The study included 57 NPC patients who were pathologically diagnosed and underwent RNA sequencing. They were categorized into complete response (CR) and partial response (PR) groups after receiving radical concurrent chemoradiotherapy. We analyzed 267 NBI images using ResNet50 for feature extraction, obtaining 2048 radiomic features per image. Using Python for deep learning and least absolute shrinkage and selection operator for feature selection, we identified differentially expressed genes associated with radiomic features. Subsequently, we conducted enrichment analysis on these genes and validated their roles in the tumor immune microenvironment through single-cell RNA sequencing.

Results

After feature selection, 54 radiomic features were obtained. The machine learning algorithm constructed from these features showed that the random forest algorithm had the highest average accuracy rate of 0.909 and an area under the curve of 0.961. Correlation analysis identified 30 differential genes most closely associated with the radiomic features. Enrichment and immune infiltration analysis indicated that tumor-associated macrophages are closely related to treatment responses. Three key NBI differentially expressed immune genes (NBI-DEIGs), namely CCL8, SLC11A1, and PTGS2, were identified as regulators influencing treatment responses through macrophages.

Conclusion

NBI-based radiomics models introduce a novel and effective method for predicting radiosensitivity in NPC. The molecular mechanisms may involve the functional states of macrophages, as reflected by key regulatory genes.

Personalized identification and characterization of genome-wide gene expression differences between patient-matched intracranial and extracranial melanoma metastasis pairs

Melanoma is the most serious type of skin cancer that frequently spreads to other organs of the human body. Especially melanoma metastases to the brain (intracranial metastases) are hard to treat and a major cause of death of melanoma patients. Little is known about molecular alterations and altered mechanisms that distinguish intra- from extracranial melanoma metastases. So far, almost all existing studies compared intracranial metastases from one set of patients to extracranial metastases of an another set of melanoma patients. This neglects the important facts that each melanoma is highly individual and that intra- and extracranial melanoma metastases from the same patient are more similar to each other than to melanoma metastases from other patients in the same organ. To overcome this, we compared the gene expression profiles of 16 intracranial metastases to their corresponding 21 patient-matched extracranial metastases in a personalized way using a three-state Hidden Markov Model (HMM) to identify altered genes for each individual metastasis pair. This enabled three major findings by considering the predicted gene expression alterations across all patients: (i) most frequently altered pathways include cytokine-receptor interaction, calcium signaling, ECM-receptor interaction, cAMP signaling, Jak-STAT and PI3K/Akt signaling, (ii) immune-relevant signaling pathway genes were downregulated in intracranial metastases, and (iii) intracranial metastases were associated with a brain-like phenotype gene expression program. Further, the integration of all differentially expressed genes across the patient-matched melanoma metastasis pairs led to a set of 103 genes that were consistently down- or up-regulated in at least 11 of the 16 of the patients. This set of genes contained many genes involved in the regulation of immune responses, cell growth, cellular signaling and transport processes. An analysis of these genes in the TCGA melanoma cohort showed that the expression behavior of 11 genes was significantly associated with survival. Moreover, a comparison of the 103 genes to three closely related melanoma metastasis studies revealed a core set of eight genes that were consistently down- or upregulated in intra- compared to extracranial metastases in at least two of the three related studies (down: CILP, DPT, FGF7, LAMP3, MEOX2, TMEM119; up: GLDN, PMP2) including FGF7 that was also significantly associated with survival. Our findings contribute to a better characterization of genes and pathways that distinguish intra- from extracranial melanoma metastasis and provide important hints for future experimental studies to identify potential targets for new therapeutic approaches.

Chemokine profiling of melanoma-macrophage crosstalk identifies CCL8 and CCL15 as prognostic factors in cutaneous melanoma

During cancer evolution, tumor cells attract and dynamically interact with monocytes/macrophages. To find biomarkers of disease progression in human melanoma, we used unbiased RNA sequencing and secretome analyses of tumor-macrophage co-cultures. Pathway analysis of genes differentially modulated in human macrophages exposed to melanoma cells revealed a general upregulation of inflammatory hallmark gene sets, particularly chemokines. A selective group of chemokines, including CCL8, CCL15, and CCL20, was actively secreted upon melanoma-macrophage co-culture. Because we previously described the role of CCL20 in melanoma, we focused our study on CCL8 and CCL15 and confirmed that in vitro both chemokines contributed to melanoma survival, proliferation, and 3D invasion through CCR1 signaling. In vivo, both chemokines enhanced primary tumor growth, spontaneous lung metastasis, and circulating tumor cell survival and lung colonization in mouse xenograft models. Finally, we explored the clinical significance of CCL8 and CCL15 expression in human skin melanoma, screening a collection of 67 primary melanoma samples, using multicolor fluorescence and quantitative image analysis of chemokine-chemokine receptor content at the single-cell level. Primary skin melanomas displayed high CCR1 expression, but there was no difference in its level of expression between metastatic and nonmetastatic cases. By contrast, comparative analysis of these two clinically divergent groups showed a highly significant difference in the cancer cell content of CCL8 (p = 0.025) and CCL15 (p < 0.0001). Kaplan-Meier curves showed that a high content of CCL8 or CCL15 in cancer cells correlated with shorter disease-free and overall survival (log-rank test, p < 0.001). Our results highlight the role of CCL8 and CCL15, which are highly induced by melanoma-macrophage interactions in biologically aggressive primary melanomas and could be clinically applicable biomarkers for patient profiling. © 2024 The Pathological Society of Great Britain and Ireland.

CC Chemokine Family Members' Modulation as a Novel Approach for Treating Central Nervous System and Peripheral Nervous System Injury-A Review of Clinical and Experimental Findings

Despite significant progress in modern medicine and pharmacology, damage to the nervous system with various etiologies still poses a challenge to doctors and scientists. Injuries lead to neuroimmunological changes in the central nervous system (CNS), which may result in both secondary damage and the development of tactile and thermal hypersensitivity. In our review, based on the analysis of many experimental and clinical studies, we indicate that the mechanisms occurring both at the level of the brain after direct damage and at the level of the spinal cord after peripheral nerve damage have a common immunological basis. This suggests that there are opportunities for similar pharmacological therapeutic interventions in the damage of various etiologies. Experimental data indicate that after CNS/PNS damage, the levels of 16 among the 28 CC-family chemokines, i.e., CCL1, CCL2, CCL3, CCL4, CCL5, CCL6, CCL7, CCL8, CCL9, CCL11, CCL12, CCL17, CCL19, CCL20, CCL21, and CCL22, increase in the brain and/or spinal cord and have strong proinflammatory and/or pronociceptive effects. According to the available literature data, further investigation is still needed for understanding the role of the remaining chemokines, especially six of them which were found in humans but not in mice/rats, i.e., CCL13, CCL14, CCL15, CCL16, CCL18, and CCL23. Over the past several years, the results of studies in which available pharmacological tools were used indicated that blocking individual receptors, e.g., CCR1 (J113863 and BX513), CCR2 (RS504393, CCX872, INCB3344, and AZ889), CCR3 (SB328437), CCR4 (C021 and AZD-2098), and CCR5 (maraviroc, AZD-5672, and TAK-220), has beneficial effects after damage to both the CNS and PNS. Recently, experimental data have proved that blockades exerted by double antagonists CCR1/3 (UCB 35625) and CCR2/5 (cenicriviroc) have very good anti-inflammatory and antinociceptive effects. In addition, both single (J113863, RS504393, SB328437, C021, and maraviroc) and dual (cenicriviroc) chemokine receptor antagonists enhanced the analgesic effect of opioid drugs. This review will display the evidence that a multidirectional strategy based on the modulation of neuronal-glial-immune interactions can significantly improve the health of patients after CNS and PNS damage by changing the activity of chemokines belonging to the CC family. Moreover, in the case of pain, the combined administration of such antagonists with opioid drugs could reduce therapeutic doses and minimize the risk of complications.

Identifying a Novel Eight-NK Cell-related Gene Signature for Ovarian Cancer Prognosis Prediction

BACKGROUND

Ovarian cancer (OVC) is the most common and costly tumor in the world with unfavorable overall survival and prognosis. This study is aimed to explore the prognostic value of natural killer cells related genes for OVC treatment.

METHODS

RNA-seq and clinical information were acquired from the TCGA-OVC dataset (training dataset) and the GSE51800 dataset (validation dataset). Genes linked to NK cells were obtained from the immPort dataset. Moreover, ConsensusClusterPlus facilitated the screening of molecular subtypes. Following this, the risk model was established by LASSO analysis, and immune infiltration and immunotherapy were then detected by CIBERSORT, ssGSEA, ESTIMATE, and TIDE algorithms.

RESULTS

Based on 23 NK cell-related genes with prognosis, TCGA-OVC samples were classified into two clusters, namely C1 and C2. Of these, C1 had better survival outcomes as well as enhanced immune infiltration and tumor stem cells. Additionally, it was more suitable for immunotherapy and was also sensitive to traditional chemotherapy drugs. The eight-gene prognosis model was constructed and verified via the GSE51800 dataset. Additionally, a high infiltration level of immune cells was observed in low-risk patients. Low-risk samples also benefited from immunotherapy and chemotherapy drugs. Finally, a nomogram and ROC curves were applied to validate model accuracy.

CONCLUSION

The present study identified a RiskScore signature, which could stratify patients with different infiltration levels, immunotherapy, and chemotherapy drugs. Our study provided a basis for precisely evaluating OVC therapy and prognosis.

Comprehensive scRNA-seq Analysis and Identification of CD8_+T Cell Related Gene Markers for Predicting Prognosis and Drug Resistance of Hepatocellular Carcinoma

BACKGROUND

Tumor heterogeneity of immune infiltration of cells plays a decisive role in hepatocellular carcinoma (HCC) therapy response and prognosis. This study investigated the effect of different subtypes of CD8+T cells on the HCC tumor microenvironment about its prognosis.

METHODS

Single-cell RNA sequencing, transcriptome, and single-nucleotide variant data from LUAD patients were obtained based on the GEO, TCGA, and HCCD18 databases. CD8+ T cells-associated subtypes were identified by consensus clustering analysis, and genes with the highest correlation with prognostic CD8+ T cell subtypes were identified using WGCNA. The ssGSEA and ESTIMATE algorithms were used to calculate pathway enrichment scores and immune cell infiltration levels between different subtypes. Finally, the TIDE algorithm, CYT score, and tumor responsiveness score were utilized to predict patient response to immunotherapy.

RESULTS

We defined 3 CD8+T cell clusters (CD8_0, CD8_1, CD8_2) based on the scRNA- seq dataset (GSE149614). Among, CD8_2 was prognosis-related risk factor with HCC. We screened 30 prognosis genes from CD8_2, and identified 3 molecular subtypes (clust1, clust2, clust3). Clust1 had better survival outcomes, higher gene mutation, and enhanced immune infiltration. Furthermore, we identified a 12 genes signature (including CYP7A1, SPP1, MSC, CXCL8, CXCL1, GCNT3, TMEM45A, SPP2, ME1, TSPAN13, S100A9, and NQO1) with excellent prediction performance for HCC prognosis. In addition, High-score patients with higher immune infiltration benefited less from immunotherapy. The sensitivity of low-score patients to multiple drugs including Parthenolide and Shikonin was significantly higher than that of high-score patients. Moreover, high-score patients had increased oxidative stress pathways scores, and the RiskScore was closely associated with oxidative stress pathways scores. And the nomogram had good clinical utility.

CONCLUSION

To predict the survival outcome and immunotherapy response for HCC, we developed a 12-gene signature based on the heterogeneity of the CD8+ T cells.

The molecular subtypes and clinical prognosis characteristic of tertiary lymphoid structures-related gene of cutaneous melanoma

Despite the remarkable efficacy of PD-1-associated immune checkpoint inhibitors in treating cutaneous melanoma (CM), the inconsistency in the expression of PD-1 and its ligand PD-L1, and resulting variability in the effectiveness of immunotherapy, present significant challenges for clinical application. Therefore, further research is necessary to identify tumor-related biomarkers that can predict the prognosis of immunotherapy. Tertiary lymphoid structures (TLSs) have been recognized as a crucial factor in predicting the response of immune checkpoint inhibitors in solid tumors, including CM. However, the study of TLSs in CM is not yet comprehensive. Gene expression profiles have been shown to correlate with CM risk stratification and patient outcomes. In this study, we identified TLS-related genes that can be used for prognostic purposes and developed a corresponding risk model. The impact of TLS-related genes on clinicopathological characteristics, immune infiltration and drug susceptibility was also explored. Our biological function enrichment analysis provided preliminary evidence of related signaling pathways. Our findings provide a new perspective on risk stratification and individualized precision therapy for CM.

Development of a 5-mRNAsi-related gene signature to predict the prognosis of colon adenocarcinoma

Aim

To create a prognosis model based on mRNA-based stem index (mRNAsi) for evaluating the prognostic outcomes of colon adenocarcinoma (COAD).

Background

Generation of heterogeneous COAD cells could be promoted by the self-renewal and differentiation potential of cancer stem cells (CSCs). Biomarkers contributing to the development of COAD stem cells remained to be discovered.

Objective

To develop and validate an mRNAsi-based risk model for estimating the prognostic outcomes of patients suffering from COAD.

Methods

Samples were collected from Rectal Adenocarcinoma (TCGA-READ) PanCancer Atlas datasets, The Cancer Genome Atlas Colon Adenocarcinoma (TCGA-COAD), and the GSE87211 dataset. MRNAsi was calculated by one-class logistic regression (OCLR) algorithm. Under the criterion of correlation greater than 0.4, genes related to mRNAsi were screened and clustered. Meanwhile, differentially expressed genes (DEGs) between molecular subtypes were identified to establish a risk model. According to the median risk score value for immunotherapy and results from immune cell infiltration and clinicopathological analyses, clusters and patients were divided into high-RiskScore and low-RiskScore groups. Cell apoptosis and viability were detected by flow cytometer and Cell Counting Kit-8 (CCK-8) assay, respectively.

Results

A negative correlation between mRNAsi and clinical stages was observed. Three clusters of patients (C1, C2, and C3) were defined based on a total of 165 survival-related mRNAsi genes. Specifically, C1 patients had greater immune cell infiltration and a poorer prognosis. A 5-mRNAsi-gene signature (HEYL, FSTL3, FABP4, ADAM8, and EBF4) served as a prediction index for COAD prognosis. High-RiskScore patients had a poorer prognosis and higher level of immune cell infiltration. In addition, the five genes in the signature all showed a high expression in COAD cells. Knocking down HEYL promoted COAD cell apoptosis and inhibited viability.

Conclusion

Our mRNAsi risk model could better predict the prognosis of COAD patients.

SLC31A1 Identifying a Novel Biomarker with Potential Prognostic and Immunotherapeutic Potential in Pan-Cancer

Solute carrier family 31 member 1 (SLC31A1) encodes a protein that functions as a homotrimer for the uptake of dietary copper. As a vital member of the cuproptosis gene family, it plays an essential role in both normal tissues and tumors. In this study, we analyzed SLC31A1 across human cancer types to gain a better understanding of SLC31A1's role in cancer development. We searched for information using online databases to analyze, systematically and comprehensively, the role of SLC31A1 in tumors. Amongst nine cancer types, the expression of SLC31A1 was significantly different between tumors and normal tissues. According to further analysis, pancreatic cancer had the highest mutation rate of the SLC31A1 gene, and the methylation levels of the gene were significantly reduced in seven tumors. The expression of SLC31A1 is also linked to the infiltration of tumors by immune cells, the expression of immune checkpoint genes, and immunotherapy markers (TMB and MSI), suggesting that SLC31A1 may be of particular relevance in immunotherapy. This thorough analysis of SLC31A1 across different types of cancer gives us a clear and comprehensive insight into its role in causing cancer on a systemic level.

Targeting Members of the Chemokine Family as a Novel Approach to Treating Neuropathic Pain

Neuropathic pain is a debilitating condition that affects millions of people worldwide. Numerous studies indicate that this type of pain is a chronic condition with a complex mechanism that tends to worsen over time, leading to a significant deterioration in patients' quality of life and issues like depression, disability, and disturbed sleep. Presently used analgesics are not effective enough in neuropathy treatment and may cause many side effects due to the high doses needed. In recent years, many researchers have pointed to the important role of chemokines not only in the development and maintenance of neuropathy but also in the effectiveness of analgesic drugs. Currently, approximately 50 chemokines are known to act through 20 different seven-transmembrane G-protein-coupled receptors located on the surface of neuronal, glial, and immune cells. Data from recent years clearly indicate that more chemokines than initially thought (CCL1/2/3/5/7/8/9/11, CXCL3/9/10/12/13/14/17; XCL1, CX3CL1) have pronociceptive properties; therefore, blocking their action by using neutralizing antibodies, inhibiting their synthesis, or blocking their receptors brings neuropathic pain relief. Several of them (CCL1/2/3/7/9/XCL1) have been shown to be able to reduce opioid drug effectiveness in neuropathy, and neutralizing antibodies against them can restore morphine and/or buprenorphine analgesia. The latest research provides irrefutable evidence that chemokine receptors are promising targets for pharmacotherapy; chemokine receptor antagonists can relieve pain of different etiologies, and most of them are able to enhance opioid analgesia, for example, the blockade of CCR1 (J113863), CCR2 (RS504393), CCR3 (SB328437), CCR4 (C021), CCR5 (maraviroc/AZD5672/TAK-220), CXCR2 (NVPCXCR220/SB225002), CXCR3 (NBI-74330/AMG487), CXCR4 (AMD3100/AMD3465), and XCR1 (vMIP-II). Recent research has shown that multitarget antagonists of chemokine receptors, such as CCR2/5 (cenicriviroc), CXCR1/2 (reparixin), and CCR2/CCR5/CCR8 (RAP-103), are also very effective painkillers. A multidirectional strategy based on the modulation of neuronal-glial-immune interactions by changing the activity of the chemokine family can significantly improve the quality of life of patients suffering from neuropathic pain. However, members of the chemokine family are still underestimated pharmacological targets for pain treatment. In this article, we review the literature and provide new insights into the role of chemokines and their receptors in neuropathic pain.

Integration of bulk RNA sequencing data and single-cell RNA sequencing analysis on the heterogeneity in patients with colorectal cancer

The cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) pathway has emerged as a critical innate immune pathway that could virtually impact nearly all aspects of tumorigenesis including colorectal cancer. This work aimed to develop and validate molecular subtypes related to cGAS-STING pathways for colorectal cancer using Bulk RNA-seq and single-cell RNA-seq (scRNA-seq) data. Bulk RNA-seq data were acquired from The Cancer Genome Atlas dataset (training dataset) and Gene Expression Omnibus dataset (validation dataset). Univariate COX survival analysis was utilized to identify prognostic differentially expressed genes (DEGs) from 6 immune pathways related to cGAS-STING. ConsensusClusterPlus package was used to classify different subtypes based on DEGs. scRNA-seq data were used to validate differences in immune status between different subtypes. Two clusters with distinct prognosis were identified based on 27 DEGs. The six cGAS-STING-related pathways had different levels of significance between the two clusters. Clust1 had most number of amplified CNVs and clust2 had the most number of loss CNVs. TP53 was the top mutated gene of which missense mutations contributed the most of single-nucleotide variants. Immune score of clust1 was higher than that in clust2, as reflected in macrophages, T cells, and natural killer cells. Three unfavorable genes and 31 protection factors were screened between the two clusters in three datasets. ScRNA-seq data analysis demonstrated that macrophages were more enriched in clust1, and tumor cells and immune cells had close interaction. We classified two distinct subtypes with different prognosis, mutation landscape, and immune characteristics.

Nicotine promotes e-cigarette vapour-induced lung inflammation and structural alterations

BACKGROUND

Electronic cigarette (e-cigarette) vapour is gaining popularity as an alternative to tobacco smoking and can induce acute lung injury. However, the specific role of nicotine in e-cigarette vapour and its long-term effects on the airways, lung parenchyma and vasculature remain unclear.

RESULTS

In vitro exposure to nicotine-containing e-cigarette vapour extract (ECVE) or to nicotine-free e-cigarette vapour extract (NF ECVE) induced changes in gene expression of epithelial cells and pulmonary arterial smooth muscle cells (PASMCs), but ECVE in particular caused functional alterations (e.g. a decrease in human and mouse PASMC proliferation by 29.3±5.3% and 44.3±8.4%, respectively). Additionally, acute inhalation of nicotine-containing e-cigarette vapour (ECV) but not nicotine-free e-cigarette vapour (NF ECV) increased pulmonary endothelial permeability in isolated lungs. Long-term in vivo exposure of mice to ECV for 8 months significantly increased the number of inflammatory cells, in particular lymphocytes, compared to control and NF ECV in the bronchoalveolar fluid (BALF) (ECV: 853.4±150.8 cells·mL-1; control: 37.0±21.1 cells·mL-1; NF ECV: 198.6±94.9 cells·mL-1) and in lung tissue (ECV: 25.7±3.3 cells·mm-3; control: 4.8±1.1 cells·mm-3; NF ECV: 14.1±2.2 cells·mm-3). BALF cytokines were predominantly increased by ECV. Moreover, ECV caused significant changes in lung structure and function (e.g. increase in airspace by 17.5±1.4% compared to control), similar to mild tobacco smoke-induced alterations, which also could be detected in the NF ECV group, albeit to a lesser degree. In contrast, the pulmonary vasculature was not significantly affected by ECV or NF ECV.

CONCLUSIONS

NF ECV components induce cell type-specific effects and mild pulmonary alterations, while inclusion of nicotine induces significant endothelial damage, inflammation and parenchymal alterations.

Identification and validation of TME-related signatures to predict prognosis and response to anti-tumor therapies in skin cutaneous melanoma

The tumor microenvironment (TME) dynamically regulates cancer progression and affects clinical outcomes. This study aimed to identify molecular subtypes and construct a prognostic risk model based on TME-related signatures in skin cutaneous melanoma (SKCM) patients. We categorized SKCM patients based on transcriptome data of SKCM from The Cancer Genome Atlas (TCGA) database and 29 TME-related gene signatures. Differentially expressed genes were identified using univariate Cox regression and Lasso regression analysis, which were used for risk model construction. The robustness of this model was validated in independent external cohorts. Genetic landscape alterations, immune characteristics, and responsiveness to immunotherapy/chemotherapy were evaluated. Three TME-related subtypes were identified, and subtype C3 exhibited the most favorable prognosis, had enriched immune-related pathways, and possessed more infiltration of T_cells_CD8, T_cells_CD4_memory_activated, and Macrophages_M1 but a lower TumorPurity, whereas Macrophages_M2 were increased in subtype C1 and subtype C2. Subtype C1 was more sensitive to Cisplatin, subtype C2 was more sensitive to Temozolomide, and subtype C3 was more sensitive to Paclitaxel; 8 TME-related genes (NOTCH3, HEYL, ZNF703, ABCC2, PAEP, CCL8, HAPLN3, and HPDL) were screened for risk model construction. High-risk patients had dismal prognosis with good prediction performance. Moreover, low-risk patients were more sensitive to Paclitaxel and Temozolomide, whereas high-risk patients were more sensitive to Cisplatin. This risk model had robustness in predicting prognosis in SKCM patients. The results facilitate the understanding of TME-related genes in SKCM and provide a TME-related genes-based predictive model in prognosis and direction of personalized options for SKCM patients.

Identification of Pyroptosis-Relevant Signature in Tumor Immune Microenvironment and Prognosis in Skin Cutaneous Melanoma Using Network Analysis

Background

Pyroptosis is closely related to the programmed death of cancer cells as well as the tumor immune microenvironment (TIME) via the host-tumor crosstalk. However, the role of pyroptosis-related genes as prognosis and TIME-related biomarkers in skin cutaneous melanoma (SKCM) patients remains unknown.

Methods

We evaluated the expression profiles, copy number variations, and somatic mutations (CNVs) of 27 genes obtained from MSigDB database regulating pyroptosis among TCGA-SKCM patients. Thereafter, we conducted single-sample gene set enrichment analysis (ssGSEA) for evaluating pyroptosis-associated expression patterns among cases and for exploring the associations with clinicopathological factors and prognostic outcome. In addition, a prognostic pyroptosis-related signature (PPRS) model was constructed by performing Cox regression, weighted gene coexpression network analysis (WGCNA), and least absolute shrinkage and selection operator (LASSO) analysis to score SKCM patients. On the other hand, we plotted the ROC and survival curves for model evaluation and verified the robustness of the model through external test sets (GSE22153, GSE54467, and GSE65904). Meanwhile, we examined the relations of clinical characteristics, oncogene mutations, biological processes (BPs), tumor stemness, immune infiltration degrees, immune checkpoints (ICs), and treatment response with PPRS via multiple methods, including immunophenoscore (IPS) analysis, gene set variation analysis (GSVA), ESTIMATE, and CIBERSORT. Finally, we constructed a nomogram incorporating PPRS and clinical characteristics to improve risk evaluation of SKCM.

Results

Many pyroptosis-regulated genes showed abnormal expression within SKCM. TP53, TP63, IL1B, IL18, IRF2, CASP5, CHMP4C, CHMP7, CASP1, and GSDME were detected with somatic mutations, among which, a majority displayed CNVs at high frequencies. Pyroptosis-associated profiles established based on pyroptosis-regulated genes showed markedly negative relation to low stage and superior prognostic outcome. Blue module was found to be highly positively correlated with pyroptosis. Later, this study established PPRS based on the expression of 8 PAGs (namely, GBP2, HPDL, FCGR2A, IFITM1, HAPLN3, CCL8, TRIM34, and GRIPAP1), which was highly associated with OS, oncogene mutations, tumor stemness, immune infiltration degrees, IC levels, treatment responses, and multiple biological processes (including cell cycle and immunoinflammatory response) in training and test set samples.

Conclusions

Based on our observations, analyzing modification patterns associated with pyroptosis among diverse cancer samples via PPRS is important, which can provide more insights into TIME infiltration features and facilitate immunotherapeutic development as well as prognosis prediction.

Melanoma molecular subtyping and scoring model construction based on ligand-receptor pairs

Melanoma is a malignancy of melanocytes, responsible for a high percentage of skin cancer mortality. Ligand-Receptor pairs, a type of cellular communication, are essential for tumor genesis, growth, metastasis, and prognosis. Yet, the role of Ligand-Receptor pairs in melanoma has not been fully elucidated. Our research focused on the function of Ligand-Receptor pairs in melanoma prognosis. We screened 131 melanoma prognosis corresponded ligand-receptor pairs by analyzing the TCGA data of melanoma and the 2293 LR pairs retrieved from the connectomeDB2020 database. And further developed subtypes of melanoma according to the expression of these ligand-receptor pairs by Consensus Clustering. Then we using lasso cox regression and stepwise multivariate regression analysis established a ligand-receptor pairs-based scoring model for the evaluation of melanoma prognosis. Our study demonstrated that the ligand-receptor pairs are vital to the molecular heterogeneity of melanoma, and characterized three different melanoma ligand-receptor pairs subtypes. Among them, the C3 subtype showed a better prognosis, while the C1 subtype exhibited a low prognosis state. And our analysis then found out that this could be related to the differed activation and inhabitation of the cell cycle and immune-related pathways. Using lasso cox regression and stepwise multivariate regression analysis, we further identified 9 key ligand-receptor pairs and established a scoring model that effectively correlated with the prognosis, immune pathways, and therapy of melanoma, showing that the LR.score model was a trustworthy and independent biomarker for melanoma prognosis evaluation. In sum, we found that ligand-receptor pairs are significantly associated with the prognosis and therapy of melanoma. And our ligand-receptor-based scoring model showed potential for the evaluation of melanoma prognosis and immune therapy outcome prediction, which is crucial to the survival for the patients.

Pathogenic Th2 Cytokine Profile Skewing by IFN-γ-Responding Vitiligo Fibroblasts via CCL2/CCL8

PURPOSE

Vitiligo is a T cell-mediated skin depigmentation disease. Though treatments arresting disease progression and inducing repigmentation are available, the efficacy of these options is often limited and poorly sustained. How stromal signals contribute to the interferon-γ-dominant skin niches is unclear. This study aims to determine how fibroblasts participate in the IFN-γ-dominant vitiligo niche.

PATIENTS AND METHODS

Mouse vitiligo models were established. Fibroblasts from control and vitiligo mice were extracted for RNA sequencing. In vitro IFN-γ stimulation was performed to verify the JAK-STAT pathway by qPCR and Western blot. T cell polarization with chemokines was measured by flow cytometry. Protein levels in tissues were also examined by IHC.

RESULTS

The vitiligo mouse model recapitulates the human CD8-IFN-γ pathway. RNA sequencing revealed elevated chemokine CCL2 and CCL8 in vitiligo fibroblast, which may be regulated by the JAK-STAT signaling. Such phenomenon is verified by JAK inhibitor peficitinib in vitro. Moreover, CCL2 addition into the naïve T polarization system promoted type 2 cytokines secretion, which represents a hallmark of vitiligo lesions.

CONCLUSION

Dermal fibroblasts, a principal constituent of skin structure, respond to IFN-γ by skewing T cells towards a type 2 cytokine profile via CCL2 and CCL8, which can be abrogated by JAK inhibitor peficitinib.

Identification of immune related gene signature for predicting prognosis of cholangiocarcinoma patients

Objective

To identify the gene subtypes related to immune cells of cholangiocarcinoma and construct an immune score model to predict the immunotherapy efficacy and prognosis for cholangiocarcinoma.

Methods

Based on principal component analysis (PCA) algorithm, The Cancer Genome Atlas (TCGA)-cholangiocarcinoma, GSE107943 and E-MTAB-6389 datasets were combined as Joint data. Immune genes were downloaded from ImmPort. Univariate Cox survival analysis filtered prognostically associated immune genes, which would identify immune-related subtypes of cholangiocarcinoma. Least absolute shrinkage and selection operator (LASSO) further screened immune genes with prognosis values, and tumor immune score was calculated for patients with cholangiocarcinoma after the combination of the three datasets. Kaplan-Meier curve analysis determined the optimal cut-off value, which was applied for dividing cholangiocarcinoma patients into low and high immune score group. To explore the differences in tumor microenvironment and immunotherapy between immune cell-related subtypes and immune score groups of cholangiocarcinoma.

Results

34 prognostic immune genes and three immunocell-related subtypes with statistically significant prognosis (IC1, IC2 and IC3) were identified. Among them, IC1 and IC3 showed higher immune cell infiltration, and IC3 may be more suitable for immunotherapy and chemotherapy. 10 immune genes with prognostic significance were screened by LASSO regression analysis, and a tumor immune score model was constructed. Kaplan-Meier (KM) and receiver operating characteristic (ROC) analysis showed that RiskScore had excellent prognostic prediction ability. Immunohistochemical analysis showed that 6 gene (NLRX1, AKT1, CSRP1, LEP, MUC4 and SEMA4B) of 10 genes were abnormal expressions between cancer and paracancer tissue. Immune cells infiltration in high immune score group was generally increased, and it was more suitable for chemotherapy. In GSE112366-Crohn's disease dataset, 6 of 10 immune genes had expression differences between Crohn's disease and healthy control. The area under ROC obtained 0.671 based on 10-immune gene signature. Moreover, the model had a sound performance in Crohn's disease.

Conclusion

The prediction of tumor immune score model in predicting immune microenvironment, immunotherapy and chemotherapy in patients with cholangiocarcinoma has shown its potential for indicating the effect of immunotherapy on patients with cholangiocarcinoma.

Pharmacological Evidence of the Important Roles of CCR1 and CCR3 and Their Endogenous Ligands CCL2/7/8 in Hypersensitivity Based on a Murine Model of Neuropathic Pain

Neuropathic pain treatment remains a challenging issue because the therapies currently used in the clinic are not sufficiently effective. Moreover, the mechanism of neuropathy is still not entirely understood; however, much evidence indicates that chemokines are important factors in the initial and late phases of neuropathic pain. To date, the roles of CCR1, CCR3 and their endogenous ligands have not been extensively studied; therefore, they have become the subject of our research. In the present comprehensive behavioral and biochemical study, we detected significant time-dependent and long-lasting increases in the mRNA levels of CCR1 and/or CCR3 ligands, such as CCL2/3/4/5/6/7/8/9, in the murine spinal cord after chronic constriction injury of the sciatic nerve, and these increases were accompanied by changes in the levels of microglial/macrophage, astrocyte and neutrophil cell markers. ELISA results suggested that endogenous ligands of CCR1 and CCR3 are involved in the development (CCL2/3/5/7/8/9) and persistence (CCL2/7/8) of neuropathic pain. Moreover, intrathecal injection of CCL2/3/5/7/8/9 confirmed their possible strong influence on mechanical and thermal hypersensitivity development. Importantly, inhibition of CCL2/7/8 production and CCR1 and CCR3 blockade by selective/dual antagonists effectively reduced neuropathic pain-like behavior. The obtained data suggest that CCL2/7/8/CCR1 and CCL7/8/CCR3 signaling are important in the modulation of neuropathic pain in mice and that these chemokines and their receptors may be interesting targets for future investigations.

Identification of cuproptosis-related gene signature to predict prognosis in lung adenocarcinoma

Background: Studies have reported that coppers are involved in the tumorigenesis and development of tumor. In herein, we aimed to construct a prognostic classification system for lung adenocarcinoma (LUAD) associated with cuproptosis.

Methods: Samples information of LUAD were acquired from The Cancer Genome Atlas (TCGA) and GSE31210 dataset. Cuproptosis-related genes were screened from previous research. ConsensusClusterPlus was applied to determine molecular subtypes, which evaluated by genome analysis, tumor immune microenvironment analysis, immunotherapy, functional enrichment analysis. Furthermore, univariate Cox analysis combined with Lasso analysis were employed to construct a cuproptosis-related risk model for LUAD.

Results: 14 genes related to cuproptosis phenotype were identified, and 2 clusters (C1 and C2) were determined. Among which, C1 had better survival outcome, less advanced stages, enhanced immune infiltration and enriched in TCA related pathways. A 7 cuproptosis-associated genes risk model was constructed, and the performance was verified in the GSE31210 dataset. A higher RiskScore was significantly correlated with worse overall survival, advanced stages. Cox survival analysis showed that RiskScore was an independent predictor. High-risk group patients had weakened immune infiltration, less likely to benefit from immunotherapy and was more sensitived to immunotherapy.

Conclusion: The cuproptosis-related gene signature could serve as potential prognostic predictors for LUAD patients and may provide clues for the intervention of cuproptosis induced harm and targeted anti-tumor application.

Analysis on heterogeneity of hepatocellular carcinoma immune cells and a molecular risk model by integration of scRNA-seq and bulk RNA-seq

Background

Studies have shown that hepatocellular carcinoma (HCC) heterogeneity is a main cause leading to failure of treatment. Technology of single-cell sequencing (scRNA) could more accurately reveal the essential characteristics of tumor genetics.

Methods

From the Gene Expression Omnibus (GEO) database, HCC scRNA-seq data were extracted. The FindCluster function was applied to analyze cell clusters. Autophagy-related genes were acquired from the MSigDB database. The ConsensusClusterPlus package was used to identify molecular subtypes. A prognostic risk model was built with the Least Absolute Shrinkage and Selection Operator (LASSO)–Cox algorithm. A nomogram including a prognostic risk model and multiple clinicopathological factors was constructed.

Results

Eleven cell clusters labeled as various cell types by immune cell markers were obtained from the combined scRNA-seq GSE149614 dataset. ssGSEA revealed that autophagy-related pathways were more enriched in malignant tumors. Two autophagy-related clusters (C1 and C2) were identified, in which C1 predicted a better survival, enhanced immune infiltration, and a higher immunotherapy response. LASSO–Cox regression established an eight-gene signature. Next, the HCCDB18, GSA14520, and GSE76427 datasets confirmed a strong risk prediction ability of the signature. Moreover, the low-risk group had enhanced immune infiltration and higher immunotherapy response. A nomogram which consisted of RiskScore and clinical features had better prediction ability.

Conclusion

To precisely assess the prognostic risk, an eight-gene prognostic stratification signature was developed based on the heterogeneity of HCC immune cells.

Identification of Diagnostic Genes and Effective Drugs Associated with Osteoporosis Treatment by Single-Cell RNA-Seq Analysis and Network Pharmacology

Background

Osteoporosis is a common bone metabolic disease with increased bone fragility and fracture rate. Effective diagnosis and treatment of osteoporosis still need to be explored due to the increasing incidence of disease.

Methods

Single-cell RNA-seq was acquired from GSE147287 dataset. Osteoporosis-related genes were obtained from chEMBL. Cell subpopulations were identified and characterized by scRNA-seq, t-SNE, clusterProfiler, and other computational methods. “limma” R packages were used to identify all differentially expressed genes. A diagnosis model was build using rms R packages. Key drugs were determined by proteins-proteins interaction and molecular docking.

Results

Firstly, 15,577 cells were obtained, and 12 cell subpopulations were identified by clustering, among which 6 cell subpopulations belong to CD45+ BM-MSCs and the other subpopulations were CD45-BM-MSCs. CD45- BM-MSCs_6 and CD45+ BM-MSCs_5 were consider as key subpopulations. Furthermore, we found 7 genes were correlated with above two subpopulations, and F9 gene had highest AUC. Finally, five compounds were identified, among which DB03742 bound well to F9 protein.

Conclusions

This work discovered that 7 genes were correlated with CD45-BM-MSCs_6 and CD45+ BM-MSCs_5 subpopulations in osteoporosis, among which F9 gene had better research value. Moreover, compound DB03742 was a potential inhibitor of F9 protein.