CCL20 promotes lung adenocarcinoma progression by driving epithelial-mesenchymal transition

Senescence-associated secretory phenotype (SASP) and uterine fibroids: Association with PD-L1 activation and collagen deposition

Uterine fibroids (or uterine leiomyoma, UFs) are one of the most prevalent benign uterine tumors with high proliferation and collagen synthesis capabilities. UFs are a significant worldwide health issue for women, affecting their physical and financial well-being. Risk factors for UFs include age, racial disparities, obesity, uterine infections, hormonal variation, and lifestyle (i.e., diet, exercise, stress, and smoking). Senescence and its associated secretory phenotypes (SASPs) are among the most salient changes accompanying the aging process. As a result, SASPs are suggested to be one of the major contributors to developing UFs. Interleukin 6 (IL-6), IL-8, IL-1, chemokine ligand 20 (CCL-20), and transforming growth factor-beta (TGF-β) are the most prominent SASPs associated with aging. In addition, different processes contribute to UFs such as collagen deposition and the changes in the immune microenvironment. Programmed death ligand 1 is a major player in the tumor immune microenvironment, which helps tumor cells evade immune attacks. This review focuses on the correlation of SASPs on two axes of tumor progression: immune suppression and collagen deposition. This review opens the door towards more investigations regarding changes in the UF immune microenvironment and age-UFs correlation and thus, a novel targeting approach for UF treatment.

SFXN1-mediated immune cell infiltration and tumorigenesis in lung adenocarcinoma: A potential therapeutic target

BACKGROUND

Sideroflexin 1 (SFXN1), a mitochondrial serine transporter implicated in one-carbon metabolism, is a prognostic biomarker in lung adenocarcinoma (LUAD). However, its role in LUAD progression remains elusive. This study aimed to investigate the functional significance of SFXN1 in LUAD and evaluate its potential as a therapeutic target.

METHODS

We analyzed SFXN1 expression and its diagnostic and prognostic value in LUAD using the Pan-cancer TCGA dataset. In vitro assays (CCK-8, cell cycle, EDU, wound-healing, and transwell) were employed to assess the role of SFXN1, complemented by in vivo experiments. RNA sequencing elucidated SFXN1-mediated cellular functions and potential mechanisms. Bulk RNA-seq and scRNA-seq data from TCGA and GEO were used to investigate the correlation between SFXN1 and the tumor immune microenvironment. RT-qPCR, Western blot, and IHC assays validated SFXN1 expression and its impact on the immune microenvironment in LUAD.

RESULTS

SFXN1 was upregulated in LUAD tissues and associated with poor prognosis. RNA-seq and scRNA-seq analyses revealed increased SFXN1 expression in tumor cells, accompanied by decreased infiltration of NK and cytotoxic T cells. SFXN1 knockdown significantly reduced cell proliferation and migration, and the inhibition of ERK phosphorylation and CCL20 expression may be the molecular mechanism involved. In vivo, targeting SFXN1 decreased Tregs infiltration and inhibited tumor growth.

CONCLUSIONS

Our findings suggest that SFXN1 may be a potential therapeutic target for LUAD treatment.

Patient-derived tumoroids and proteomic signatures: tools for early drug discovery

Onco-virotherapy is an emergent treatment for cancer based on viral vectors. The therapeutic activity is based on two different mechanisms including tumor-specific oncolysis and immunostimulatory properties. In this study, we evaluated onco-virotherapy in vitro responses on immunocompetent non-small cell lung cancer (NSCLC) patient-derived tumoroids (PDTs) and healthy organoids. PDTs are accurate tools to predict patient's clinical responses at the in vitro stage. We showed that onco-virotherapy could exert specific antitumoral effects by producing a higher number of viral particles in PDTs than in healthy organoids. In the present work, we used multiplex protein screening, based on proximity extension assay to highlight different response profiles. Our results pointed to the increase of proteins implied in T cell activation, such as IFN-γ following onco-virotherapy treatment. Based on our observation, oncolytic viruses-based therapy responders are dependent on several factors: a high PD-L1 expression, which is a biomarker of greater immune response under immunotherapies, and the number of viral particles present in tumor tissue, which is dependent to the metabolic state of tumoral cells. Herein, we highlight the use of PDTs as an alternative in vitro model to assess patient-specific responses to onco-virotherapy at the early stage of the preclinical phases.

Identification of Prognostic and Immune Characteristics of Two Lung Adenocarcinoma Subtypes Based on TRPV Channel Family Genes

Lung adenocarcinoma (LUAD) is one of the deadliest malignant tumors worldwide. Transient receptor potential vanilloid (TRPV) channels take pivotal parts in many cancers, but their impact on LUAD remains unexplored. In this study, LUAD samples were classified into two subtypes according to the expression characteristics of TRPV1-6 genes, with LUAD subtype cluster2 exhibiting significantly higher survival rates than cluster1. Subsequently, analysis of differentially expressed genes (DEGs) was performed between cluster1 and cluster2, revealing enrichment of DEGs in channel activity and Ca2+ signaling pathways. We established a protein-protein interaction network based on DEGs and constructed a LUAD prognostic model by using Cox regression analysis based on genes corresponding to 170 protein nodes. The prognostic model demonstrated good predictive ability for patient prognosis, with higher survival rates observed in the low-risk (LR) group. The risk score was validated as an independent prognostic indicator, according to Cox regression analysis. A clinically applicable nomogram was plotted. Immunological analysis indicated that the LR and high-risk (HR) groups had varied proportions of immune cell infiltration. The immunotherapy prediction indicated that LUAD patients in LR group had a greater likelihood to benefit from immune checkpoint blockade therapy. Furthermore, we hypothesized that the expression patterns of feature genes in the LUAD model were related to the sensitivity to lung cancer therapeutic drugs TAS-6417 and Erlotinib. To sum up, our LUAD prognostic model possessed clinical applicability for prognosis and immunotherapy response prediction.

Identifying a survival-associated cell type based on multi-level transcriptome analysis in idiopathic pulmonary fibrosis

BACKGROUND

Idiopathic pulmonary fibrosis (IPF) is a progressive disease with a five-year survival rate of less than 40%. There is significant variability in survival time among IPF patients, but the underlying mechanisms for this are not clear yet.

METHODS AND RESULTS

We collected single-cell RNA sequence data of 13,223 epithelial cells taken from 32 IPF patients and bulk RNA sequence data from 456 IPF patients in GEO. Based on unsupervised clustering analysis at the single-cell level and deconvolution algorithm at bulk RNA sequence data, we discovered a special alveolar type 2 cell subtype characterized by high expression of CCL20 (referred to as ATII-CCL20), and found that IPF patients with a higher proportion of ATII-CCL20 had worse prognoses. Furthermore, we uncovered the upregulation of immune cell infiltration and metabolic functions in IPF patients with a higher proportion of ATII-CCL20. Finally, the comprehensive decision tree and nomogram were constructed to optimize the risk stratification of IPF patients and provide a reference for accurate prognosis evaluation.

CONCLUSIONS

Our study by integrating single-cell and bulk RNA sequence data from IPF patients identified a special subtype of ATII cells, ATII-CCL20, which was found to be a risk cell subtype associated with poor prognosis in IPF patients. More importantly, the ATII-CCL20 cell subtype was linked with metabolic functions and immune infiltration.

The chemokine CCL20 can assist AFP in serological diagnosis of hepatocellular carcinoma

The chemokine 20 (CCL20) is a member of the CC chemokine family and plays a role in tumor immunity and autoimmune disease. This work investigated the value of CCL20 as a serum diagnostic marker for primary hepatocellular carcinoma (HCC). Based on the data of hepatocellular carcinoma patients in the TCGA database, the up-regulated genes encoding secretory proteins were analyzed in each pathological stage, and the candidate marker CCL20 gene was selected. Serum concentrations of CCL20 in patients with primary HCC, benign liver disease, and healthy subjects were analyzed by enzyme-linked immunosorbent assay (ELISA). The ROC curve evaluated the efficacy of CCL20 alone or in combination with AFP in the diagnosis of HCC. It was found the expression of CCL20 in HCC patients was significantly higher than that in the benign liver disease group and healthy controls (P < 0.05); The AUC of ROC curve to distinguish HCC patients from healthy controls was 0.859, the sensitivity was 73.42%, and the specificity was 86.84%. After combination with AFP, the AUC increased to 0.968, the sensitivity was 88.16%, and the specificity was 97.37%. Although CCL20 was increased in the serum of patients with benign liver diseases, combined with AFP, the AUC to distinguish HCC patients from non-HCC cohorts (benign liver disease group and healthy control group) was 0.902, with a sensitivity of 91.67% and a specificity of 75.26%. Collectively, serum CCL20 is closely related to the occurrence of HCC, and detection of serum CCL20 can assist AFP in improving the diagnostic sensitivity of HCC.

A novel iTreg-related signature for prognostic prediction in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer. Most patients are diagnosed at an advanced stage, therefore it is crucial to identify novel prognostic biomarkers for LUAD. As important regulatory cells, inducible regulatory T cells (iTregs) play a vital role in immune suppression and are important for the maintenance of immune homeostasis. This study explored the prognostic value and therapeutic effects of iTreg-related genes in LUAD. Data for LUAD patients, including immune infiltration data, RNA sequencing data, and clinical features, were acquired from The Cancer Genome Atlas, Gene Expression Omnibus, and Tumor Immune Single-cell Hub 2 databases. Immune-related subgroups with different infiltration patterns and iTreg-related genes were identified through univariate and multivariate Cox regression analyses and weighted correlation network analysis. Functional enrichment analyses were performed to explore the underlying mechanisms of iTreg-related genes. A prognostic risk signature was constructed using Cox regression analysis with the least absolute shrinkage and selection operator penalty. The ESTIMATE algorithm was applied to determine the immune status of LUAD patients. We applied the constructed signature to predict chemosensitivity and performed single-cell RNA sequencing analysis. The infiltration of iTregs was identified as an independent factor for predicting patient outcomes. We constructed a prognostic signature based on seven iTreg-related genes (GIMAP5, SLA, MS4A7, ZNF366, POU2AF1, MRPL12, and COL5A1), which was applied to subdivide patients into high- and low-risk subgroups. Our results revealed that patients in the iTreg-related low-risk subgroup had a better prognosis and possibly greater sensitivity to traditional chemotherapy. Our study provides a novel iTreg-related signature to elucidate the mechanisms underlying LUAD prognosis and promote individualized chemotherapy treatment.

PBK correlates with prognosis, immune escape and drug response in LUAD

PBK (PDZ-binding kinase) is a protein-coding gene that encodes a serine/threonine protein kinase associated with the dual-specific mitogen-activated protein kinase (MAPKK) family. Overexpression of this gene is closely linked to tumor development. In this study, we aimed to investigate the role of PBK in lung adenocarcinoma (LUAD) progression, prognosis, and immune evasion. We conducted a pan-cancer analysis of PBK to examine its expression and prognostic value. In the LUAD cohort, we analyzed PBK expression, prognosis, mutational features, and immune infiltration in groups with different PBK expression levels. We constructed a PBK-associated genomic model, integrated it into a nomogram, and compared high and low-risk subgroups. In our pan-cancer analysis, PBK was significantly upregulated, particularly in LUAD patients, and displayed poor prognosis. The high PBK expression group had many deletion mutations but still showed gene upregulation. Immune infiltration analysis indicated that PBK-triggered immune escape in the high expression group might relate to antigen presentation, dendritic cell, and CD8+ T cell infiltration. We constructed a 5-gene prognostic model and a nomogram to quantify individual survival probabilities. The PBK-associated gene prognostic model reliably predicted patient prognosis and drug response. Our findings offer new insights into PBK-induced immune escape and targeted therapy during LUAD development, providing valuable suggestions for clinical treatment approaches.

Heterogeneity of tumor immune microenvironment in malignant and metastatic change in LUAD is revealed by single-cell RNA sequencing

Lung adenocarcinoma (LUAD) is the most common type of non-small cell lung cancer and accounts for approximately 40% of all lung cancer cases. Multiple distant metastases are the major cause of mortality in lung cancer. In this study, single-cell sequencing datasets of LUAD were utilized to depict the transcriptome characteristic of LUAD based on the bioinformatic method. Firstly, the transcriptome landscape of heterogeneous cell types in LUAD was analyzed and memory T cells, NK cells, and helper T cells were revealed to be the common immune cells in tumor, normal, and metastasis tissue, respectively. Then, marker genes were calculated and 709 genes were identified to play a vital role in the microenvironment of LUAD. While macrophages were reported to act as one of the cells in LUAD, enrichment analysis of macrophage marker genes revealed the important role of macrophages in the activation of neutrophils. Next, the results of cell-cell communication analysis suggested that pericytes interact with broad immune cells via MDK-NCL pathways in metastasis samples, MIF-(CD74+CXCR4) and MIF-(CD74+CC44) interaction especially occurred between different cell types in tumor and normal samples. Finally, bulk RNA-seq was integrated to validate the prognosis effect of the marker gene and the maker gene of M2 macrophage, CCL20, showed the most related to LUAD prognosis. Besides, ZNF90 (Helper T cells), FKBP4 (memory T, helper T, Cytotoxic T, and B cells), CD79A (B cells), TPI1 (pericyte), and HOPX (epithelial cells, pericytes) were also pivotal in the pathology of LUAD, helping researchers understand the molecular insight of microenvironment in LUAD.

Panel of miR-150 and linc00673, regulators of CCR6/CCL20 may serve as non-invasive diagnostic marker of non-small cell lung cancer

The C-C motif ligand 20 (CCL20) is a chemokine that specifically binds to the chemokine receptor 6 (CCR6) and the CCL20/CCR6 axis has been implicated in the non-small lung cancer (NSCLC) development and progression. Its expression is regulated by mutual interactions of non-coding RNAs (ncRNAs). This goals of presented study was to evaluate the expression level of CCR6/CCL20 mRNA in NSCLC tissue comparative to selected ncRNAs: miR-150, linc00673. The expression level of the studied ncRNAs was also assessed in serum extracellular vesicles (EVs). Thirty patients (n = 30) were enrolled as the study cohort. Total RNA was isolated from tumor tissue, adjacent macroscopically unchanged tissue and serum EVs. The expression level of studied genes and ncRNAs were estimated based on the qPCR method. Higher expression level of CCL20 mRNA but lower expression level of CCR6 mRNA were observed in tumor in comparison to control tissue. Relative to the smoking status, higher CCL20 (p < 0.05) and CCR6 mRNA (p > 0.05) expression levels were observed in current smokers than in never smokers. In serum EVs the expression level of miR-150 has a negative correlation with AJCC tumor staging, whereas the expression level of linc00673 positively correlated (p > 0.05). The lower expression level of miR-150 and higher expression level of linc00673 in serum EVs were observed in NSCLC patients with lymph nodes metastases (p > 0.05). Regarding the histopathological type, significantly lower expression level of miR-150 and higher expression level of linc00673 were observed in the serum EVs of patients with AC compared to patient with SCC. Our findings revealed that smoking significantly changed the expression level of CCL20 mRNA in NSCLC tissue. Changes in expression levels of miR-150 and linc00673 in the serum EVs of NSCLC patients in relation to presence of lymph node metastases and the stage of cancer development may serve as a non-invasive molecular biomarkers of tumor progression. Furthermore, expression levels of miR-150 and linc00673 may serve as non-intrusive diagnostic biomarkers differentiating adenocarcinoma from squamous cell carcinoma.

A systematic and comprehensive analysis of T cell exhaustion related to therapy in lung adenocarcinoma tumor microenvironment

Background: T cell exhaustion (TEX) is an important immune escape mechanism, and an in-depth understanding of it can help improve cancer immunotherapy. However, the prognostic role of TEX in malignant lung adenocarcinoma (LUAD) remains unclear. Methods: Through TCGA and GEO datasets, we enrolled a total of 498 LUAD patients. The patients in TCGA-LUAD were unsupervised clustered into four clusters according to TEX signaling pathway. WGCNA analysis, survival random forest analysis and lasso regression analysis were used to select five differentially expressed genes among different clusters to construct a TEX risk model. The risk model was subsequently validated with GEO31210. By analyzing signaling pathways, immune cells and immune checkpoints using GSEA, GSVA and Cibersortx, the relationship between TEX risk score and these variables was evaluated. In addition, we further analyzed the expression of CCL20 at the level of single-cell RNA-seq and verified it in cell experiments. Results: According to TEX signaling pathway, people with better prognosis can be distinguished. The risk model constructed by CD109, CCL20, DKK1, TNS4, and TRIM29 genes could further accurately identify the population with poor prognosis. Subsequently, it was found that dendritic cells, CD44 and risk score were closely related. The final single-cell sequencing suggested that CCL2O is a potential therapeutic target of TEX, and the interaction between TEX and CD8 + T is closely related. Conclusion: The classification of T cell depletion plays a crucial role in the clinical decision-making of lung adenocarcinoma and needs to be further deepened.

Hepatitis B virus pathogenesis relevant immunosignals uncovering amino acids utilization related risk factors guide artificial intelligence-based precision medicine

Background: Although immune microenvironment-related chemokines, extracellular matrix (ECM), and intrahepatic immune cells are reported to be highly involved in hepatitis B virus (HBV)-related diseases, their roles in diagnosis, prognosis, and drug sensitivity evaluation remain unclear. Here, we aimed to study their clinical use to provide a basis for precision medicine in hepatocellular carcinoma (HCC) via the amalgamation of artificial intelligence. Methods: High-throughput liver transcriptomes from Gene Expression Omnibus (GEO), NODE (https://www.bio.sino.org/node), the Cancer Genome Atlas (TCGA), and our in-house hepatocellular carcinoma patients were collected in this study. Core immunosignals that participated in the entire diseases course of hepatitis B were explored using the "Gene set variation analysis" R package. Using ROC curve analysis, the impact of core immunosignals and amino acid utilization related gene on hepatocellular carcinoma patient's clinical outcome were calculated. The utility of core immunosignals as a classifier for hepatocellular carcinoma tumor tissue was evaluated using explainable machine-learning methods. A novel deep residual neural network model based on immunosignals was constructed for the long-term overall survival (LS) analysis. In vivo drug sensitivity was calculated by the "oncoPredict" R package. Results: We identified nine genes comprising chemokines and ECM related to hepatitis B virus-induced inflammation and fibrosis as CLST signals. Moreover, CLST was co-enriched with activated CD4+ T cells bearing harmful factors (aCD4) during all stages of hepatitis B virus pathogenesis, which was also verified by our hepatocellular carcinoma data. Unexpectedly, we found that hepatitis B virus-hepatocellular carcinoma patients in the CLST^highaCD4^high subgroup had the shortest overall survival (OS) and were characterized by a risk gene signature associated with amino acids utilization. Importantly, characteristic genes specific to CLST/aCD4 showed promising clinical relevance in identifying patients with early-stage hepatocellular carcinoma via explainable machine learning. In addition, the 5-year long-term overall survival of hepatocellular carcinoma patients can be effectively classified by CLST/aCD4 based GeneSet-ResNet model. Subgroups defined by CLST and aCD4 were significantly involved in the sensitivity of hepatitis B virus-hepatocellular carcinoma patients to chemotherapy treatments. Conclusion: CLST and aCD4 are hepatitis B virus pathogenesis-relevant immunosignals that are highly involved in hepatitis B virus-induced inflammation, fibrosis, and hepatocellular carcinoma. Gene set variation analysis derived immunogenomic signatures enabled efficient diagnostic and prognostic model construction. The clinical application of CLST and aCD4 as indicators would be beneficial for the precision management of hepatocellular carcinoma.

Plasma Olink Proteomics Identifies CCL20 as a Novel Predictive and Diagnostic Inflammatory Marker for Preeclampsia

Inflammation is generally thought to be involved in the occurrence and development of preeclampsia (PE), but its specific effect on PE remains unclear. In the present study, the expression levels of 92 inflammation-related proteins were measured in the late pregnancy maternal plasma from patients with PE (n = 15) and normal pregnant controls (n = 15) using the Olink inflammation panel based on the highly sensitive and specific proximity extension assay technology. A total of 28 inflammation-related markers differed between the PE and control groups. Among them, fibroblast growth factor 21 (FGF-21) and cysteine-cysteine motif chemokine ligand 20 (CCL20) had the largest fold changes. We further validated the levels of CCL20 in the late (43 with PE and 44 controls) and early (37 with PE and 37 controls) pregnancy maternal plasma using enzyme-linked immunosorbent assay (ELISA). To the best of our knowledge, for the first time, CCL20 was found to be upregulated in the late and early pregnancy plasma of patients with PE and had an area under the curve (AUC) of 0.753 and 0.668, respectively. In conclusion, patients with PE had increased levels of most inflammatory markers, and CCL20 might be a novel potential predictive and diagnostic biomarker for PE.

Tertiary lymphoid structure patterns aid in identification of tumor microenvironment infiltration and selection of therapeutic agents in bladder cancer

BACKGROUND

Tertiary lymphoid structures (TLSs) are emerging as a potential predictor of prognosis and response to immunotherapy in some solid tumors. However, the comprehensive role of TLSs in bladder cancer remains unclear.

METHODS

Eighteen bladder cancer (BCa) datasets were downloaded from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), ArratyExpress and IMvigor210. Based on 39 validated TLS signature genes (TSGs), we evaluated the TLS patterns in all patients, and correlated the TLS patterns with prognosis and tumor microenvironment (TME) cell-infiltrating characteristics. The cox regression model and principal component analysis (PCA) algorithms were used to construct the TLS score, which helps to quantify the TLS pattern in individuals.

RESULTS

The landscape of 39 validated TSGs in BCa was assessed first. Five distinct TLS patterns and four gene clusters were determined. TLS cluster C2 and gene cluster A were thought to be characterized by mature TLSs and showed better prognosis and higher immune cells infiltration than other clusters. The TLS score was discovered to be tightly correlated with the infiltration level of immune cells, and could predict the maturation status of TLSs to some extent. We found TLS score was an excellent predictor for prognosis in patients with BCa independent of tumor mutation burden (TMB), and low TLS score was related to better prognosis than high TLS score. Besides, low TLS score was correlated with a better response to immune checkpoint blockade (ICB) immunotherapy and commonly used chemotherapy drugs.

CONCLUSIONS

Our work demonstrated the characteristics of TLSs in BCa. By using the TLS score, we could evaluate the TLS pattern in individuals. Better understanding of TLS pattern and the usage of TLS score could help instruct clinical strategy and precision medicine for BCa.