Establishment and Evaluation of a Risk Prediction Model for Pathological Escalation of Gastric Low-Grade Intraepithelial Neoplasia.

The study aims to explore the risk factors for pathological escalation after endoscopic surgery for gastric low-grade intraepithelial neoplasia (LGIN) and to establish and evaluate a risk prediction model for LGIN. A total of 120 patients diagnosed with gastric LGIN by biopsy and endoscopic submucosal dissection (ESD) between November 2020 and June 2022 were retrospectively analyzed. Gender, age, Helicobacter pylori (HP) infection, lesion size, lesion location, morphology, gastric mucosal congestion, nodules status, surface ulceration and erosion, and ME-observation of all patients were collected and divided into upgraded and non-upgraded groups according to the biopsy and ESD postoperative pathological diagnosis results. Independent risk factors for pathological escalation after ESD surgical treatment were screened by logistic regression analysis, and a risk prediction model was established. Among the 120 patients with gastric LGIN, 49 patients developed postoperative pathological upgrading; the rate of pathological upgrading was 40.83%. Among them, 42 patients were upgraded to high-grade intraepithelial neoplasia (HGIN), 1 case was upgraded to advanced gastric cancer, and 6 cases were upgraded to early gastric carcinoma (EGC). Univariate analysis showed that age, lesion size, gastric mucosal congestion, surface ulcers, and erosion were significantly different between the groups (p < 0.05). Multivariate Logistic regression analysis revealed that age ≥60 years, focal length ≥2 cm, gastric mucosal congestion, and surface ulceration and erosion were independent risk factors for postoperative pathological escalation in patients with gastric LGIN. Final joint probability forecasting model for P = 1/[1 + e(26.515-0.161 x ß1-0.357 x ß2+0.039 x ß3-0.269 x ß4)]. Age, lesion size ≥2 cm, gastric mucosal congestion, and lesion surface ulceration and erosion are risk factors for postoperative pathological upgrading in patients with gastric LGIN. The risk prediction model established in this study based on risk factors has predictive value and can provide a scientific reference for the clinical treatment of patients with gastric LGIN.

CDK4 as a Prognostic Marker of Hepatocellular Carcinoma and CDK4 Inhibitors as Potential Therapeutics.

BACKGROUND: The proteins CDK4 and CDK6, which are extremely homologous, control cell cycle entry. For the treatment of breast tumors that include hormone receptors, CDK4 and CDK6 inhibitors have been authorized. The link between CDK4 and liver hepatocellular carcinoma (LIHC), however, has not yet been established. OBJECTIVE: The study aimed to explore the link between CDK4 and LIHC and the effect of CDK4 inhibitors on LIHC. METHOD: In this study, we have evaluated CDK4's prognostic relevance in LIHC using data from The Cancer Genome Atlas (TCGA). The relationship between clinical-pathologic features and CDK4 expression has been evaluated using the Kruskal-Wallis test, the Wilcoxon signed-rank test, and logistic regression. We have analyzed CDK4 and factors related to the prognosis of HCC using the Kaplan-Meier technique and multivariate Cox regression. Gene set enrichment analysis (GSEA) identified CDK4-related critical pathways. To investigate the connections between CDK4 and cancer immune infiltrates, TCGA data were employed in single-sample gene set enrichment analysis (ssGSEA). For functional validation, CDK4 was chosen since it can be inhibited by recognized CDK4/ 6-inhibitors (e.g., abemaciclib). RESULTS: Poorer overall and disease-specific outcomes were linked to high CDK4 expression in HCC patients. GSEA suggested that CDK4 and immune response are closely connected. The amount of Th2 cells infiltrating was positively correlated with CDK4 expression, while the amount of cytotoxic cells infiltrating was negatively correlated, according to ssGSEA. Both in vitro and in vivo, the anti-tumor efficacy of CDK4 inhibitor has been found to be superior to that of sorafenib. CONCLUSION: This study suggests a relationship between CDK4 and immune infiltration and prognosis in HCC. Additionally, a CDK4 inhibitor may have anti-tumor properties against hepatocellular cancer.

Development and validation of a novel lysosome-related LncRNA signature for predicting prognosis and the immune landscape features in colon cancer.

Lysosomes are essential components for managing tumor microenvironment and regulating tumor growth. Moreover, recent studies have also demonstrated that long non-coding RNAs could be used as a clinical biomarker for diagnosis and treatment of colorectal cancer. However, the influence of lysosome-related lncRNA (LRLs) on the progression of colon cancer is still unclear. This study aimed to identify a prognostic LRL signature in colon cancer and elucidated potential biological function. Herein, 10 differential expressed lysosome-related genes were obtained by the TCGA database and ultimately 4 prognostic LRLs for conducting a risk model were identified by the co-expression, univariate cox, least absolute shrinkage and selection operator analyses. Kaplan-Meier analysis, principal-component analysis, functional enrichment annotation, and nomogram were used to verify the risk model. Besides, the association between the prognostic model and immune infiltration, chemotherapeutic drugs sensitivity were also discussed in this study. This risk model based on the LRLs may be promising for potential clinical prognosis and immunotherapeutic responses related indicator in colon cancer patients.

Immune depletion of the methylated phenotype of colon cancer is closely related to resistance to immune checkpoint inhibitors.

Background: Molecular typing based on single omics data has its limitations and requires effective integration of multiple omics data for tumor typing of colorectal cancer (CRC). Methods: Transcriptome expression, DNA methylation, somatic mutation, clinicopathological information, and copy number variation were retrieved from TCGA, UCSC Xena, cBioPortal, FireBrowse, or GEO. After pre-processing and calculating the clustering prediction index (CPI) with gap statistics, integrative clustering analysis was conducted via MOVICS. The tumor microenvironment (TME) was deconvolved using several algorithms such as GSVA, MCPcounter, ESTIMATE, and PCA. The metabolism-relevant pathways were extracted through ssGSEA. Differential analysis was based on limma and enrichment analysis was carried out by Enrichr. DNA methylation and transcriptome expression were integrated via ELMER. Finally, nearest template or hemotherapeutic sensitivity prediction was conducted using NTP or pRRophetic. Results: Three molecular subtypes (CS1, CS2, and CS3) were recognized by integrating transcriptome, DNA methylation, and driver mutations. CRC patients in CS3 had the most favorable prognosis. A total of 90 differentially mutated genes among the three CSs were obtained, and CS3 displayed the highest tumor mutation burden (TMB), while significant instability across the entire chromosome was observed in the CS2 group. A total of 30 upregulated mRNAs served as classifiers were identified and the similar diversity in clinical outcomes of CS3 was validated in four external datasets. The heterogeneity in the TME and metabolism-related pathways were also observed in the three CSs. Furthermore, we found CS2 tended to loss methylations while CS3 tended to gain methylations. Univariate and multivariate Cox regression revealed that the subtypes were independent prognostic factors. For the drug sensitivity analysis, we found patients in CS2 were more sensitive to ABT.263, NSC.87877, BIRB.0796, and PAC.1. By Integrating with the DNA mutation and RNA expression in CS3, we identified that SOX9, a specific marker of CS3, was higher in the tumor than tumor adjacent by IHC in the in-house cohort and public cohort. Conclusion: The molecular subtypes based on integrated multi-omics uncovered new insights into the prognosis, mechanisms, and clinical therapeutic targets for CRC.

FABP4 suppresses proliferation and invasion of hepatocellular carcinoma cells and predicts a poor prognosis for hepatocellular carcinoma.

Adipocyte fatty acid-binding protein (FABP4) is abundant in macrophage and adipocyte. It is known to be involved in lipid metabolism. The role of FABP4 has been reported in various cancers, such as non-small cell lung cancer, breast cancer, ovarian cancer, and prostatic cancer. However, its role remains unclear in hepatocellular carcinoma (HCC). In our study, we investigated the expression of FABP4 at both mRNA and protein levels, and by examining 175 cases of patients with cancer of the liver tissue microarray, the significance between the expression of FABP4 and clinical characteristics had been discussed. We found that FABP4 was lowly expressed in HCC tissues compared to the corresponding tissue adjacent, and the expression of FABP4 was significantly associated with the tumor size, PVTT, recurrence-free survival and overall survival. Moreover, multivariate Cox regression analysis indicated that the expression of FABP4, Alb, AFP, HBsAg, and PVTT were independent risk factors for overall survival, and the expression of FABP4, AFP, GGT, tumor size, and encapsulation were independent risk factors for HCC recurrence. In addition, we revealed that FABP4 suppressed HCC cell proliferation and invasion in vitro. Moreover, overexpression of FABP4 led to inhibit tumor growth and decreased tumor volume in vivo. These phenotypes were associated with altered expression of Snail and p-STAT3. Our studies thus suggest that FABP4 could be a potential target for HCC chemotherapy.