Journal of Cancer最新文献

Background: Carcinoembryonic antigen related cell adhesion molecule-1 (CEACAM1) is a very important intercellular adhesion molecule, and its prognostic relevance to breast cancer (BC), especially basal-like breast cancer (BLBC), remains poorly understood. Methods: CEACAM1 mRNA expression data for BC were sourced from the Cancer Genome Atlas (TCGA) database. Kaplan-Meier survival analysis and Cox regression analysis were used to evaluate the prognostic relationship between CEACAM1 expression and BC. Signaling pathways associated with CEACAM1 were analysed using Gene Set Enrichment Analysis (GSEA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Moreover, cell counting kit-8 (CCK-8), flow cytometry, transwell and wound-healing assays were employed to identify the biological functions of CEACAM1 in BLBC. Results: CEACAM1 was correlated with overall survival (OS) of BLBC patients. Compared with the subgroup with better prognosis, the levels of CEACAM1 mRNA expression were significantly lower in the subgroup of BLBC with poorer prognosis. Both univariate and multivariate Cox regression analysis suggested that down-regulation of CEACAM1 expression may be an independent factor for poor prognosis in BLBC patients. GSEA and KEGG analysis revealed that CEACAM1 was negatively related with signaling pathways including extracellular matrix (ECM) receptor interaction, focal adhesion, and cell adhesion. The results of in vitro experiments indicated that CEACAM1 not only induced apoptosis of BLBC cells, but also inhibited the invasive and metastatic ability of cancer cells. Conclusions: CEACAM1 may contribute to improving the OS of BLBC patients due to its ability to inhibit the proliferation and metastasis of cancer cells. Therefore, CEACAM1 could be used as a potential prognostic biomarker and therapeutic target in BLBC.

Introduction: Despite the generally favorable prognosis of PTC (Papillary Thyroid Carcinoma), it can still exhibit aggressive behavior and lead to patient mortality. IPCEF1 (interaction protein for cytohesin exchange factors 1) has emerged as a critical player in cell signaling related to proliferation and migration in cancer progression. Objective: Our research aimed to determine whether IPCEF1 is a key gene in PTC, elucidate its possible molecular mechanisms and ultimately search for new targets. Methods: This research utilized four gene expression array datasets and TCGA database to examine the role of IPCEF1 in PTC. Differential gene expression analysis, survival analysis, KEGG and GO enrichment and immune cell infiltration correlations were realized by bioinformatic methods. The expressions of IPCEF1 in PTC tissues were examined by IHC and the proliferation, migration, cell cycles of PTC cells were examined by CCK8, transwell and flow cytometry. Results: IPCEF1 had lower expression in PTC tumor tissues and its lower expression might lead to worse T/N stage and DFS/ PFS, which is perhaps related to its regulation of the JAK/STAT signaling pathway and immune microenvironment (macrophage and Tregs). IPCEF1 reduced the proliferation and migration ability of PTC cells, which is consistent with our clinical observations. Besides, we also found that high expression level of IPCEF1 lead to cell cycle arrest in the S or G2 phase, which ultimately reduced cell growth and proliferation. Conclusion: IPCEF1 is a cancer suppressor gene in the progression of PTC, influencing patient survival and prognosis through modulation of immune infiltration and signaling pathways.

IDH-wildtype glioblastoma (GBM) is the most common and malignant primary brain tumor. The purpose of this study is to establish a prognostic gene signature for IDH-wildtype GBM. RNA sequencing data of normal brain tissue and GBM patients were obtained from TCGA, CGGA, GEO and the GTEx databases. Identification of prognostic differentially expressed genes (DEGs) with | log2 fold change | > 0.5 and adjust p < 0.05 in TCGA and CGGA databases by "limma" method. By LASSO regression analysis and multivariate Cox analysis, a 3-gene prognostic signature composed of FMOD, MXRA5 and RAB36 was established. The 3-gene prognostic risk model is validated by TCGA and GSE43378 datasets. The expression of FMOD, MXRA5 and RAB36 in GBM patients was significantly higher than that in normal brain tissues in CCGA, TCGA and GSE29796 data sets. In order to further verify this result, total RNA was extracted from tumors and paracancerous tissues of 9 GBM patients. RT-PCR results showed that the expression of FMOD, MXRA5 and RAB36 in tumor tissues of most patients was higher than that in paracancerous tissues. The results of GSEA showed that the pathway enrichment of the 3-gene signature was mainly related to tumor immunity. Immune cell infiltration analyzed by ssGSEA showed that there were significant differences in macrophages between high- and low-risk groups. Immune checkpoint genes correlation analysis showed that PD-L1 gene expression is closely related to risk score. Our study identifies a prognostic-associated risk model and provides a potential effective immunotherapy target for IDH-wildtype GBM patients.

Background: Kidney renal clear cell carcinoma (KIRC) is the most prevalent subtype of malignant renal cell carcinoma and is well known as a common genitourinary cancer. Stratifying tumors based on heterogeneity is essential for better treatment options. Methods: In this study, consensus clusters were constructed based on gene expression, DNA methylation, and gene mutation data, which were combined with multiple clustering algorithms. After identifying two heterogeneous subtypes, we analyzed the molecular characteristics, immunotherapy response, and drug sensitivity differences of each subtype. And we further integrated bulk data and single-cell RNA sequencing (scRNA-Seq) data to infer the immune cell composition and malignant tumor cell proportion of subtype-related cell subpopulations. Results: Among the two identified consensus subtypes (CS1 and CS2), CS1 was enriched in more inflammation-related and oncogenic pathways than CS2. Simultaneously, CS1 showed a worse prognosis and we found more copy number variations and BAP1 mutations in CS1. Although CS1 had a high immune infiltration score, it exhibited high expression of suppressive immune features. Based on the prediction of immunotherapy and drug sensitivity, we inferred that CS1 may respond poorly to immunotherapy and be less sensitive to targeted drugs. The analysis of bulk data integrated with single-cell data further reflected the high expression of inhibitory immune features in CS1 and the high proportion of malignant tumor cells. And CS2 contained a large number of plasmacytoid B cells, presenting an activated immune microenvironment. Finally, the robustness of our subtypes was successfully validated in four external datasets. Conclusion: In summary, we conducted a comprehensive analysis of multi-omics data with 10 clustering algorithms to reveal the molecular characteristics of KIRC patients and validated the relevant conclusions by single-cell analysis and external data. Our findings discovered new KIRC subtypes and may further guide personalized and precision treatments.

[This corrects the article DOI: 10.7150/jca.37932.].

Pancreatic cancer (PC) is a common and highly malignant tumor. Basement membrane (BM) is formed by the crosslinking of extracellular matrix macromolecules and acts as a barrier against tumor cell metastasis. However, the role of BM in PC prognosis, immune infiltration, and treatment remains unclear. This study collected transcriptome and clinical survival data of PC via TCGA, GEO, and ICGC databases. PC patients (PCs) from the First Affiliated Hospital of Dalian Medical University were obtained as the clinical validation cohort. BM-related genes (BMRGs) were acquired from GeneCards and basement membraneBASE databases. A total of 46 differential-expressed BMRGs were identified. Then the BM-related prognostic model (including DSG3, MET, and PLAU) was built and validated. PCs with a low BM-related score had a better outcome and were more likely to benefit from oxaliplatin, irinotecan, and KRAS(G12C) inhibitor-12, and immunotherapy. Immune analysis revealed that BM-related score was positively correlated with neutrophils, cancer-associated fibroblasts, and macrophages infiltration, but negatively correlated with CD8+ T cells, NK cells, and B cells infiltration. PCs from the clinical cohort further verified that BM-related model could accurately predict PCs' outcomes. DSG3, MET, and PLAU were notably up-regulated within PC tissues and linked to a poor prognosis. In vitro experiments showed that DSG3 knockdown markedly suppressed the proliferation, migration, and invasion of PC cells. Molecular docking indicated that epigallocatechin gallate had a strong binding activity with DSG3, MET, and PLAU and may be used as a potential therapeutic agent for PC. In conclusion, this study developed a BM-related model associated with PC prognosis, immune infiltration, and treatment, which provided new insights into PC stratification and drug intervention.

Cervical cancer (CC) is an important public health problem for women, gene expression patterns which were governed by epigenetic modifications can result in CC, CC-chemokine receptor 4 (CCR4) interacts with C-C-motif ligand 22 (CCL22) is associated with tumor progression or metastasis. A previous study by the present authors revealed the levels of chemokine CCL22 and its receptor CCR4 are increased in CC tissues, nevertheless, the regulatory mechanisms governing its expression remain poorly understood. The present study aimed to investigate the potential role of enhancer of zeste homolog 2 (EZH2)-induced epigenetic activation of CCL22/CCR4 and caused epithelial-to-mesenchymal transition (EMT) remodeling in CC. CCL22 and CCR4 were significantly up-regulated in CC samples compared with normal cervix tissues, and obvious induction of promoter DNA methylation levels of CCL22 and CCR4 was found in CC tissues. Demethylation reactivated the transcription of CCL22 and CCR4. DNA methyltransferase 3A (DNMT3A) was found to directly bind to the CCL22 and CCR4 promoter regions in vitro. Downregulation of the expression of EZH2 in CC cell lines altered DNMT3A expression and induced CCL22 and CCR4 promoters' methylation levels, while CCL22 and CCR4 mRNA expression decreased. An in vivo assay showed that EZH2 regulated the expression of CCL22/CCR4 components through DNMT3A, consistent with the in vitro results. In EZH2-silenced CC cells, migration was reduced, levels of EMT-related markers, including vimentin, slug, snail and β-catenin, were all reduced and zona occludens 1 (ZO-1) increased. In DNMT3A-silenced CC cells, migration was induced, vimentin, slug, snail and β-catenin were all induced and ZO-1 was reduced. Inhibition of CCL22 protein significantly decreased migration of CC cells and vimentin, slug, snail and β-catenin levels, while ZO-1 increased. In conclusion, EZH2 appears to regulate CCL22/CCR4 expression via epigenetic activation, causing EMT process remodeling in CC progression.

Purpose: Bladder cancer (BCa) is one of the most common malignant tumors in the urinary system. BCa with HER2 overexpression can benefit from more precise treatments, but HER2 testing is costly and subjective. This study aimed to detect HER2 expression using computed tomography urography (CTU) images. Method: We gathered CTU images from 97 patients with BCa during the excretion phase in Renmin Hospital of Wuhan University, manually delineated the BCa regions, extracted radiomic features using the Pyradiomics package, conducted data dimensionality reduction via principal component analysis (PCA), and trained three models (Logistic Regression [LR], Random Forest [RF] and Multilayer Perceptron [MLP]) to discern the HER2 expression status. Results: Pyradiomics package was used to extract 975 radiological features and the cumulative interpretation area under the variance curve was 90.964 by PCA. Using an MLP-based deep learning model for identifying HER2 overexpression, the area under the curve (AUC) reached 0.79 (95% confidence interval [CI] 0.74-0.86) in the training set and 0.73 (95% CI 0.66-0.77) in the validation set. LR and RF had AUC of 0.69 (95% CI 0.63-0.75) and 0.66 (95% CI 0.61-0.70) in the training set and 0.61 (95% CI 0.55-0.67) and 0.59 (95% CI 0.55-0.63) in the test set, respectively. Conclusion: The study firstly presents a non-invasive method for identifying and detecting HER2 expression in BCa CTU images. It might not only reduce the cost and subjectivity of traditional HER2 testing but also provide a new technical method for the precise treatment of BCa.

The eventually developed chemoresistance to proteasome inhibitors (PIs) is a major hurdle in curing patients with multiple myeloma (MM) and a key cause of poor prognosis, however the underlying molecular mechanisms of chemoresistance is still poorly understood. Herein, we provide evidences that N-acetyltransferase 10 (NAT10), a catalytic enzyme involving in the acetylation modification of RNA, is overexpressed in the BTZ-resistant (BR) MM cell lines and predicts poor outcomes in the clinic. Further manipulating of NAT10 gene expression in MM cells shows that enforced NAT10 expression decreases sensitivity to PI, however knockdown of NAT10 enhances anti-tumor efficacy of PIs in MM cells in vitro and in vivo. Acetylated RNA immunoprecipitation sequencing (acRIP-seq) combined with RIP-qPCR analysis identifies exportin 1 (XPO1) as an important downstream target of NAT10, with promotes N4-acetylcytidine (ac4C) modification of XPO1 mRNA. Importantly, expressions of XPO1 and NAT10 are meaningfully correlated in bone biopsies from the relapsed/refractory (R/R) MM patients, which were also highly associated with poor outcome. Translationally, dual pharmacological inhibition of NAT10 and XPO1 sensitizes MM cells to BTZ treatment in both cell lines and in a xenograft mouse model of MM. Thus, our study elucidates previously unrecognized role of ac4C modification of XPO1 mRNA in the chemoresistance of MM and provides a potential option for clinical management of R/R MM patients in the clinic.