Prognostic Nomogram for Postoperative Patients With Gastroesophageal Junction Cancer of No Distant Metastasis

Downregulation of DIP2B as a prognostic marker inhibited cancer proliferation and migration and was associated with immune infiltration in lung adenocarcinoma via CCND1 and MMP2

Background

DIP2B is related to cancer progression. This study investigated the roles and pathways of DIP2B in lung adenocarcinoma (LUAD).

Methods

DIP2B expression and the relationship between survival time of cancer patients and DIP2B expression were analyzed. The relationship between DIP2B expression and survival time in LUAD patients was evaluated by a meta-analysis. Cox and survival analyses were used to evaluate the prognostic factors and construct a prognostic nomogram. The mechanisms and effects of DIP2B and the relationship between DIP2B expression and the immune microenvironment were investigated using bioinformatics, CCK-8, western blotting, and transwell experiments.

Results

DIP2B was overexpressed in LUAD tissues. DIP2B overexpression was associated with shorter prognosis and was an unfavorable risk factor for prognosis in LUAD patients. DIP2B co-expressed genes were involved in cell division, DNA repair, cell cycle, and others. Inhibition of DIP2B expression could downregulate the proliferation, migration, and invasion of LUAD A549 and H1299 cells, which was related to the decrease in CCND1 and MMP2 protein expression. BRCA1 overexpression was associated with short prognosis, and the nomogram formed by DIP2B and BRCA1 was associated with a poor prognosis in LUAD patients. DIP2B expression correlated with immune cells (such as CD8 T cells, Tcm, and iDCs) and cell markers.

Conclusion

DIP2B is a potential biomarker of poor prognosis and the immune microenvironment in LUAD. Inhibition of DIP2B expression downregulated cancer cell proliferation, migration, and invasion, which might be related to the decrease in CCND1 and MMP2 protein expression. DIP2B-related nomograms might be useful tools for predicting the prognosis of LUAD patients.

The Long-Term Outcomes of Surgery Versus Endoscopic Treatment in Patients With Siewert Type II T1M0N0 Adenocarcinoma of the Esophagogastric Junction

OBJECTIVE

We compared the long-term prognosis of surgery and endoscopic treatment (ET) in patients diagnosed with Siewert Type II pT1N0M0 adenocarcinoma of the esophagogastric junction (AEG).

METHODS

Using the Surveillance, Epidemiology, and End Results (SEER) database, we performed a real-world retrospective cohort study and enrolled patients with Siewert Type II pT1N0M0 AEG who underwent surgery or endoscopic treatment (ET) from 2010 to 2018. Matched cohorts were generated using propensity score matching Competing-risk analysis was applied. The cumulative incidence function was used to calculate cancer-specific death and other causes of death (OCD) at different time points. Univariate and multivariate analyses were performed to identify significant prognostic factors by using the subdistribution hazard ratio.

RESULTS

We enrolled 725 patients: 462 underwent surgery and 263 received ET. The 5 year cumulative CSD incidence significantly differed between surgery and ET cohorts (16.87% vs 11.08%, P = .01). Following PSM, 2 balanced groups (n = 219 patients each) were analyzed. No significant difference in the 5 year cumulative incidences of CSD was noted between cohorts (17.61% vs. 12.16%, P = .14). In multivariable analysis, the CSD incidence was high among patients with aged ≥65 (SHR 2.29, 95%CI 0.99-5.33, P = .05) and T1b-stage (SHR 1.92, 95%CI 1.03-3.57, P = .04); treatment (surgery or ET) was not significantly associated with cancer survival (SHR 1.51, 95% CI 0.81-2.81, P = .20).

CONCLUSION

Long-term survival did not significantly differ among patients with Siewert Type II pT1N0M0 AEG adenocarcinoma undergoing surgery or ET. ET may be considered in patients >65 years old or those with submucosal (T1b-stage) cancer of AEG.

Decreased APOC1 expression inhibited cancer progression and was associated with better prognosis and immune microenvironment in esophageal cancer

Several studies have demonstrated the involvement of apolipoprotein C1 (APOC1) in multiple cancers. However, the role of APOC1 in esophageal cancer (ESCA) has not been elucidated. Hence, we examined the expression of APOC1 in ESCA tissues acquired from The Cancer Genome Atlas (TCGA) database and clinical samples from our hospital. An investigation of the association of APOC1 with the clinicopathological characteristics, prognosis, and diagnosis of ESCA was carried out on the basis of survival, receiver operating characteristics, and correlation analyses. Gene ontology, KEGG analysis, and protein-protein interaction network showed that co-expressed APOC1 genes were involved in the functions, mechanisms, and action network. The effects of APOC1 expression on ESCA cells were explored using CCK-8, migration and invasion assays. The relationship between APOC1 expression and ESCA immune-infiltrating cells and cell markers were examined using correlation analysis. We found that APOC1 was overexpressed in TCGA ESCA tissues and the same was validated in clinical ESCA tissues, with the area under the curve for APOC1 being 0.887. Overexpression of APOC1 was associated with short overall survival, disease-specific survival, progression-free interval, T stage, pathological stage, body mass index, and histological grade. Inhibition of APOC1 expression significantly reduced the proliferation, migration, and invasion of ESCA cells. Furthermore, APOC1 expression positively correlated with the ESTIMATE, immune, and stromal scores in ESCA. Overexpression of APOC1 correlated with the tumor purity, B cells, T helper cells, natural killer cells, cytotoxic cells, and other immune cells. Moreover, APOC1 was involved in ESCA progression via T cell receptor, B cell receptor, and other immune signaling pathways. Thus, APOC1 overexpression is expected to be a biomarker for dismal prognosis and diagnosis of ESCA. Inhibition of APOC1 expression significantly reduced the proliferation, migration, and invasion of ESCA cells. Overexpression of APOC1 was associated with the immune microenvironment in ESCA. Thus, APOC1 may be an efficient biomarker for proper prognosis and diagnosis of ESCA.

A Risk Model Based on Sorafenib-Response Target Genes Predicts the Prognosis of Patients with HCC

Sorafenib is used to treat digestive system tumors in patients who do not respond to or cannot tolerate surgery. However, the roles and inhibitory mechanisms of sorafenib against hepatocellular carcinoma (HCC) are unclear. Differentially expressed genes in tissues from responders and nonresponders to sorafenib were investigated using the HCC GSE109211 data set. Biological functions and mechanisms were studied using the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases. The expression levels of differential expressed target genes were identified in HCC tissues, using The Cancer Genome Atlas database, and their prognostic and diagnostic values were explored using survival and receiver operating characteristic curve analysis. A nomogram and risk model of sorafenib-response target genes enabled the evaluation of the prognosis of patients with HCC. The relationship between risk scores and levels of infiltrating immune cells was visualized via correlation analysis. We identified 1620 sorafenib-response target genes involved in the PPAR signaling pathway, antigen processing and presentation, and ferroptosis. SLC41A3, SEC61A1, LRP4, PPM1G, and HSP90AA1 were independent risk factors for a poor prognosis for patients with HCC and had diagnostic value. A risk model based on SLC41A3, SEC61A1, LRP4, PPM1G, and HSP90AA1 expression showed that patients with HCC in the high-risk group had a worse prognosis. Consensus-clustering analysis (performed with K set to 2) distinguished two clusters (the cluster 1 and cluster 2 groups). Patients in cluster 1 survived significantly longer than those in cluster 2. The risk score correlated with the levels of T cells, cytotoxic lymphocytes, CD8+ T cells, macrophages, memory B cells, follicular helper T cells, and other immune cells. The high risk based on the sorafenib-response targets SLC41A3, SEC61A1, LRP4, PPM1G, and HSP90AA1 represented the poor prognosis for patients with HCC and significantly correlated with the levels of immune infiltrating cells in HCC.

The Risk Model Based on the Three Oxidative Stress-Related Genes Evaluates the Prognosis of LAC Patients

Background

Oxidative stress plays a role in carcinogenesis. This study explores the roles of oxidative stress-related genes (OSRGs) in lung adenocarcinoma (LAC). Besides, we construct a risk score model of OSRGs that evaluates the prognosis of LAC patients.

Methods

OSRGs were downloaded from the Gene Set Enrichment Analysis (GSEA) website. The expression levels of OSRGs were confirmed in LAC tissues of the TCGA database. GO and KEGG analyses were used to evaluate the roles and mechanisms of oxidative stress-related differentially expressed genes (DEGs). Survival, ROC, Cox analysis, and AIC method were used to screen the prognostic DEGs in LAC patients. Subsequently, we constructed a risk score model of OSRGs and a nomogram. Further, this work investigated the values of the risk score model in LAC progression and the relationship between the risk score model and immune infiltration.

Results

We discovered 163 oxidative stress-related DEGs in LAC, involving cellular response to oxidative stress and reactive oxygen species. Besides, the areas under the curve of CCNA2, CDC25C, ERO1A, CDK1, PLK1, ITGB4, and GJB2 were 0.970, 0.984, 0.984, 0.945, 0.984, 0.771, and 0.959, respectively. This indicates that these OSRGs have diagnosis values of LAC and are significantly related to the overall survival of LAC patients. ERO1A, CDC25C, and ITGB4 overexpressions were independent risk factors for the poor prognosis of LAC patients and were associated with risk scores in the risk model. High-risk score levels affected the poor prognosis of LAC patients. Notably, a high-risk score may be implicated in LAC progression via cell cycle, DNA replication, mismatch repair, and other mechanisms. Further, ERO1A, CDC25C, and ITGB4 expression levels were related to the immune infiltrating cells of LAC, including mast cells, NK cells, and CD8 T cells.

Conclusion

In summary, ERO1A, CDC25C, and ITGB4 of OSRGs are associated with poor prognosis of LAC patients. We confirmed that the risk model based on the ERO1A, CDC25C, and ITGB4 is expected to assess the prognosis of LAC patients.

A New Nomogram for Predicting the Postoperative Overall Survival in Patients with Middle-Aged and Elderly Rectal Cancer: A Single Center Retrospective Study in Chinese Population

Purpose

Patients with middle-aged and elderly rectal cancer (MERC) usually have poor prognosis after surgery. This study aimed to develop a nomogram to achieve individualized prediction of overall survival (OS) in patients with MERC and to guide follow-up and subsequent diagnosis and treatment plans.

Patients and Methods

A total of 349 patients were randomly assigned to the training and validation cohorts in a 7:3 ratio. Multivariate Cox regression analysis was performed using the results of univariate Cox regression analysis to confirm independent prognostic factors of OS. Thereafter, the nomogram was built using the “rms” package. Subsequently, discriminative ability and calibration of the nomogram were evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Integrated discrimination improvement (IDI), net reclassification improvement (NRI), and the area under the ROC curves (AUC) were compared between the nomogram and the tumor-node-metastasis (TNM) staging system (8th edition). Finally, we established a predictive model to assess the survival benefit of patients with MERC by calculating nomogram scores for each patient.

Results

Six variables were identified as independent prognostic factors and included in the nomogram: smoking history, family history, hematochezia, tumor size, N stage, and M stage. Based on these factors, we successfully constructed a nomogram and evaluated its discriminative and predictive abilities using ROC curves, calibration curves, and DCA. ROC curves, IDI, and NRI showed that the nomogram had outstanding clinical utility compared with the TNM staging system (8th edition) for OS prediction. The predictive model successfully distinguished between high-, medium-, and low-risk MERC patients.

Conclusion

Our nomogram provided a more satisfactory survival prediction ability than the TNM staging system (8th edition) for MERC patients. In addition, the nomogram was able to accurately categorize patients into different risk groups after surgery.