Background: The risk of liver metastasis (LM) may be estimated using predictive nomograms. While the nomogram has recently been applied in oncology, there are relatively few studies concentrating on predicting LM in patients with early-onset colon cancer. We aimed to identify independent risk factors for LM in patients with early-onset colon cancer and develop a nomogram for predicting the probability of LM in these patients.
Methods: Our study encompassed 4,890 early-onset colon cancer patients with LM who were registered in the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2015. These patients were randomly allocated into training and validation cohorts at a ratio of 7:3. Univariate and multivariate logistic regression analyses were conducted to identify the independent risk factors for LM, and a nomogram was developed using these factors. The model's discriminatory power, accuracy, and clinical utility were evaluated using receiver operating characteristics (ROC), calibration, and decision curve analyses.
Results: Overall, 4,890 patients with early-onset colon cancer and LM were selected from the SEER database. LM incidence in these patients was 18.4%. Univariate and multivariate analyses revealed histological type, T stage, N stage, and carcinoembryonic antigen (CEA) level as independent risk factors. ROC curve analysis revealed that the predictive nomogram for LM risk had an area under the curve of 0.812 [95% confidence interval (CI): 0.795-0.829] and 0.809 (95% CI: 0.784-0.834) in the training and validation sets, respectively, demonstrating good discriminatory ability of the model. Calibration curve analysis showed good agreement between predicted values from the nomogram and actual observations, and the decision curve analysis (DCA) demonstrated the high clinical utility of the nomogram.
Conclusions: LM incidence was higher in patients with early-onset colon cancer. Our nomogram demonstrates a high level of efficacy in predicting the risk of LM in patients with early-onset colon cancer, thereby assisting clinicians in making well-informed treatment decisions prior to further intervention.
Background: The significance of programmed cell death (PCD) in the context of cancer development and progression is widely acknowledged, yet its specific impact on cancer-associated fibroblasts (CAFs) remains a topic of ongoing investigation. Therefore, the study aims to explore the role of PCD in regulating CAFs and its potential implications for CRC progression.
Methods: CAFs from single-cell data of 23 colorectal cancer (CRC) patients were clustered by non-negative matrix factorization (NMF) and the impact of these subpopulations on the prognosis of CRC patients was predicted using public database cohorts.
Results: In total, we screened eight PCDs that are associated with significant prognostic impacts for CRC patients, and based on PCD regulators, we defined multiple subpopulations of CAFs associated with PCDs. Additionally, we found that the PCD key regulators may be closely related to the clinical and biological characteristics of CRC and the pseudotime trajectory of major CAFs subpopulations. Bulk RNA sequencing analyses revealed that subpopulations of CAFs mediated by PCD hold prognostic value for CRC patients. CellChat analysis further illustrated the extensive interactions between PCD-associated CAFs subpopulations and tumor epithelial cells. Following Cox regression and survival analyses, it was determined that the paraptosis-mediated CAFs subpopulation had the most pronounced impact on CRC patient prognosis, with DDIT3 identified as a marker protein influencing patient outcomes.
Conclusions: Our study reveals for the first time how PCD-mediated communication between CAFs regulates tumor growth in CRC patients and influences their prognosis, and has identified that DDIT3+ CAFs associated with paraptosis exhibit the most pronounced influence on the prognosis of individuals with CRC.
Background: The current literature lacks reports on the roles of proliferative cells in tumorigenesis and causal relationship between proliferative cells and cervical cancer. This study aims to investigate the role and mechanism of proliferative cells in cervical cancer.
Methods: Single-cell transcriptomics of cervical cancer were utilized to identify proliferative cells. Mendelian randomization (MR) and meta-analysis were employed to study the causal relationship between proliferative cells and cervical cancer. Additional assays such as 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), flow cytometry, gene set enrichment analysis (GSEA), and weighted gene co-expression network analysis (WGCNA) were exploited to study function of EPB41L4A-AS1 in the regulation of cell proliferation. Both complementary DNA (cDNA) microarray and GSEA were performed to elucidate the underlying mechanisms by which EPB41L4A-AS1 influenced proliferative cells.
Results: Cervical cancer exhibited a higher proportion of proliferative cells in tumor tissue compared to healthy tissue, as evidenced by single-cell transcriptomics. Genes specifically expressed in proliferative cells were found to be predictive of the prognosis of cervical cancer patients [P=0.009; hazard ratio (high groups) =1.893; 95% confidence interval: 1.169-3.064]. Proliferative cells, rather than squamous or columnar epithelial cells, were causally associated with cervical cancer. Mechanistically, EPB41L4A-AS1 was found to regulate proliferative cells (P<0.005), described as EPB41L4A-AS1-regulated genes which were predominantly enriched in proliferative cells. The mapping of pathways associated with EPB41L4A-AS1-regulated genes to proliferative cells revealed a significant enrichment of mitosis-related pathways (normalized enrichment score >1). Furthermore, knockdown of EPB41L4A-AS1 resulted in an increased number of cells during the M phase (Sh-NC: 2N: 74.5%, S: 11.7%, 4N: 10.0%; Sh-EPB41L4A-AS1: 2N: 66.0%, S: 11.2%, 4N: 18.7%), thereby promoting cell proliferation.
Conclusions: This study offered a novel perspective on the role of EPB41L4A-AS1 in regulating cervical cancer through its impact on proliferative cells.
Background: CXC chemokine ligand 13 (CXCL13) serves as the ligand for chemokine receptor 5 (CXCR5), The CXCL13/CXCR5 signaling axis plays a crucial role in the pathogenesis and progression of various malignancies. This study aimed to assess the expression and role of serum CXCL13 in patients with hepatocellular carcinoma (HCC) and explore its clinical significance in the diagnosis, treatment, and prognosis evaluation of HCC.
Methods: Serum samples and clinical data were collected from 74 HCC patients, 51 cirrhosis patients, and 53 healthy controls. The expression level of serum CXCL13 was measured using enzyme-linked immunosorbent assay (ELISA). Statistical software was employed to analyze the relationship between CXCL13 levels and clinicopathological features as well as laboratory indicators. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic value of CXCL13 and alpha-fetoprotein (AFP) for HCC.
Results: The level of serum CXCL13 in the HCC group (275.96±145.35 pg/mL) was significantly higher than that in the cirrhosis group (172.11±142.78 pg/mL) and healthy control group (58.83±41.29 pg/mL). The level of CXCL13 in HCC patients with tumor node metastasis (TNM) stage III-IV was significantly higher than that in those with TNM stage I-II, as well as positively correlated with γ-glutamyltransferase (GGT) and model for end-stage liver disease (MELD) values. The area under the ROC curve for CXCL13, AFP, and the combination of CXCL13 with AFP were 0.819, 0.813, and 0.885 respectively. The sensitivity and specificity of the combined CXCL13 with AFP were 88.9% and 77.9% respectively. Moreover, the diagnostic efficacy of combining CXCL13 with AFP was significantly superior to that of using either CXCL13 or AFP alone.
Conclusions: The expression of CXCL13 is upregulated in HCC patients and associated with tumor size, metastasis, GGT, and MELD score. Combining serum CXCL13 with AFP may hold clinical value to the diagnosis of HCC.
Background: Gastric signet ring cell carcinoma (GSRCC) is a highly lethal malignancy. Serpin family E member 2 (SERPINE2) is a pro-tumorigenic factor in cancer. Here, we sought to define the role of SERPINE2 in the pathogenesis of GSRCC.
Methods: Messenger RNA (mRNA) expression was analyzed by quantitative polymerase chain reaction (PCR). Protein expression was tested by immunohistochemistry (IHC) and immunoblot assays. Proliferation was assessed by 5-ethynyl-2'-deoxyuridine (EdU) assay, and invasion and migration were detected by transwell assay. Tube formation assay was used to test the influence on angiogenesis. Cell apoptosis and M2 macrophage polarization were evaluated by flow cytometry. The methyltransferase-like 3 (METTL3)-SERPINE2 relationship was analyzed by RNA immunoprecipitation (RIP), luciferase, and mRNA stabilization assays. Xenograft experiments were used for assessment of METTL3's influence on tumorigenicity of GSRCC cells.
Results: SERPINE2 and METTL3 levels were upregulated in human GSRCC. Functionally, SERPINE2 depletion enhanced apoptosis of GSRCC cells and diminished their proliferative, migratory and invasive capacities in vitro. Moreover, SERPINE2 depletion suppressed tube formation ability of human umbilical vein endothelial cells (HUVECs) and M2 polarization of THP-1-derived macrophages. Mechanistically, METTL3 induced SERPINE2 upregulation by enhancing SERPINE2 mRNA stabilization. Our rescue experiments indicated that the effects of METTL3 depletion on cell phenotypes were due to the reduction of SERPINE2 expression. Additionally, METTL3 deficiency inhibited GSRCC xenograft growth in vivo.
Conclusions: Our study defines the significant roles of the METTL3/SERPINE2 axis as an epigenetic mechanism in GSRCC progression. Our work may have diagnostic and/or therapeutic applications in GSRCC.
Background: Necroptosis, an alternative mode of programmed cell death (PCD) that overcomes apoptosis resistance, has been implicated in the progression and drug resistance of cancer. The aim of this study is to find the biological and prognostic significance of necroptosis in patients with head and neck squamous cell carcinoma (HNSCC).
Methods: Integrated clinical datasets from The Cancer Genome Atlas (TCGA) HNSCC cohort underwent analysis. R package "DESeq2" was used to conduct differential gene expression analysis between normal and tumor tissues in the cohort, resulting in the identification of 2,172 differentially expressed genes (DEGs). A total of 159 necroptosis-related genes (NRGs) were extracted and performed a Venn analysis to identify the optimal necroptosis-related DEGs, resulting in the selection of 25 genes specifically associated with necroptosis in HNSCC. Then prognostic analyze, Cox regression analysis and prognostic model were demonstrated the ability to predict the extent of immunological infiltration in HNSCC.
Results: Among these DEGs, five genes (FADD, H2AZ1, PYGL, JAK3, and ZBP1) were found to have prognostic value (P<0.05). Then, bioinformatic analyses were conducted, and the biological and clinical significance of these five genes were demonstrated. Furthermore, Cox regression analysis was performed to develop a prognostic gene model based on these genes, which effectively classified HNSCC patients into low- or high-risk groups. The prognostic model also demonstrated the ability to predict the extent of immunological infiltration in HNSCC. Additionally, a predictive nomogram based on the clinicopathological features of these five prognostic DEGs was constructed.
Conclusions: We performed a systematic bioinformatic analysis to identify necroptosis-related prognostic genes in HNSCC patients. These genes' prognostic value was synthesized into a predictive nomogram for forecasting HNSCC progression.
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