BACKGROUND Lymph node metastasis and tumor progression depend on lymphovascular invasion (LVI). This study aimed to investigate the prognostic role of LVI in patients with stage III colorectal cancer (CRC) and to develop a prognostic nomogram. MATERIAL AND METHODS A retrospective study included 437 patients with stage III CRC. The impact of LVI on overall survival (OS) was analyzed with the Kaplan-Meier method and Cox regression model. A nomogram was constructed, and its predictive accuracy was evaluated using the concordance index (C-index) and the calibration plot. RESULTS LVI was found in 19.7% of cases of stage III CRCs and was significantly correlated with high tumor grade (poor differentiation) and advanced tumor stage (all P<0.05). Patients age, a family history of cancer in a first-degree relative, pre-treatment levels of carcinoembryonic antigen (CEA), prognostic nutritional index (PNI), histological tumor grade, tumor-node-metastasis (TNM) stage, and LVI were independent prognostic indicators (all P<0.05). Compared with the LVI(-) group, patients in the LVI(+) group showed a 1.748-fold increased risk of death (P=0.004) and a significantly reduced OS rate (P<0.001). In the prognostic nomogram, the C-index was significantly increased with LVI compared with the TNM stage alone (0.742 vs. 0.593; P<0.001). Calibration plots showed good fitness of the nomogram for prediction of survival. Comparison of the nomograms with and without LVI showed that inclusion of LVI improved the C-index from 0.715 to 0.742. CONCLUSIONS LVI was an indicator of more aggressive biological behavior and poor prognosis in patients with stage III CRC.

N6-methyladenosine (m6A) methyltransferase has been shown to be an oncogene in a variety of cancers. Nevertheless, the relationship between the long non-coding RNAs (lncRNAs) and hepatocellular carcinoma (HCC) remains elusive. We integrated the gene expression data of 371 HCC and 50 normal tissues from The Cancer Genome Atlas (TCGA) database. Differentially expressed protein-coding genes (DE-PCGs)/lncRNAs (DE-lncRs) analysis and univariate regression and Kaplan–Meier (K–M) analysis were performed to identify m6A methyltransferase-related lncRNAs. Three prognostic lncRNAs were selected by univariate and LASSO Cox regression analyses to construct the m6A methyltransferase-related lncRNA signature. Multivariate Cox regression analyses illustrated that this signature was an independent prognostic factor for overall survival (OS) prediction. The Gene Set Enrichment Analysis (GSEA) suggested that the m6A methyltransferase-related lncRNAs were involved in the immune-related biological processes (BPs) and pathways. Besides, we discovered that the lncRNAs signature was correlated with the tumor microenvironment (TME) and the expression of critical immune checkpoints. Tumor Immune Dysfunction and Exclusion (TIDE) analysis revealed that the lncRNAs could predict the clinical response to immunotherapy. Our study had originated a prognostic signature for HCC based on the potential prognostic m6A methyltransferase-related lncRNAs. The present study had deepened the understanding of the TME status of HCC patients and laid a theoretical foundation for the choice of immunotherapy.

Introduction: The objective of our study was to develop a nomogram to predict overall survival (OS) and cancer-specific survival (CSS) in patients with gastric signet ring cell carcinoma (GSRCC). Methods: A total of 3,408 GSRCC patients between 1975 and 2017 were screened from the Surveillance, Epidemiology, and End Results (SEER) database and randomly divided into training and validation cohorts. Univariate and multivariate Cox analyses were conducted to identify independent prognostic factors for the construction of a nomogram. The performance of the model was then assessed by the concordance index (C-index), calibration plot, and area under the receiver operating characteristic curve (AUC). Then, the novel nomogram was further assessed by 64 GSRCC patients from our hospital as the external cohort. Results: We identified age, tumor lymph node metastasis (TNM) staging system, surgery, and chemotherapy as significant independent elements of prognosis. On this basis, a nomogram was constructed, with a C-index of OS in the training and validation cohorts of 0.763 (95% CI: 0.751–0.774) and 0.766 (95% CI: 0.748–0.784) and a C-index of CSS of 0.765 (95% CI: 0.753–0.777) and 0.773 (95% CI: 0.755–0.791), respectively. The AUCs of the nomogram for predicting 2- and 5-year OS were 0.848 and 0.885, respectively, and those for predicting CSS were 0.854 and 0.899, respectively, demonstrating the excellent predictive value of the constructed nomogram compared to the traditional AJCC staging system. Similar results were also observed in both the internal and external validation sets. Conclusion: The nomogram provided an accurate tool to predict OS and CSS in patients with GSRCC, which can assist clinicians in making predictions about individual patient survival.

Objective. Recent years, there has been a rapid increase in the incidence of esophageal adenocarcinoma (EAC), while the prognosis for patients diagnosed remains poor and has slightly improved. Methods. We extracted 6,466 cases with detailed demographical characteristics including age at diagnosis, sex, ethnicity, marital status, and clinical features, involving tumor grade and stage at diagnosis and treatment modalities (radiation therapy, chemotherapy, and surgery) from the Surveillance, Epidemiology, and End Results (SEER) (19752017) dataset. They were further randomly divided into the training and validating cohorts. Univariate and multivariate Cox analyses were conducted to determine significant variables for construction of nomogram. The predictive power of the model was then assessed by Harrell concordance index (C-index) and the area under the curve (AUC) of the receiver operating characteristic (ROC) curve. Results. Multivariate analysis revealed that age, marital status, insurance, tumor grade, TNM stage, surgery, and chemotherapy all showed a significant association with overall survival (OS) and cancer-specific survival (CSS). These characteristics were employed to build a nomogram. Particularly, the discrimination of nomogram for OS and CSS prediction in the training set were excellent (C-index=0.762, 95 CI: 0.7540.770 and C-index=0.774, 95 CI: 0.7660.782). The AUC of the nomogram for predicting 2- and 5-year OS was 0.834 and 0.853 and CSS was 0.844 and 0.866. Similar results were observed in the internal validation set. Conclusion. We have successfully established a novel nomogram for predicting OS and CSS in EAC patients with good accuracy, which can help clinicians predict the survival of individual patient survival and provide optimal treatment strategies.

We describe herein a 37-year-old woman with a 2-week history of melena who was eventually diagnosed with ileal haemolymphangioma, a rare benign tumour. Local mucosal congestion and swelling were found through single-balloon enteroscopy, which showed an irregular protuberance approximately 10 cm long, located 3.2 m from the Treitz ligament. We performed a laparoscopic-assisted partial resection of the small intestine combined with intestinal adhesiolysis. According to postoperative pathology, the final diagnosis was ileal haemolymphangioma with haemorrhage.

Objectives. Primary gastric diffuse large B-cell lymphoma (PG-DLBCL) is a common phenotype of extranodal non-Hodgkins lymphoma (NHL). This research aims to identify a model for predicting overall survival (OS) and cancer-specific survival (CSS) in PG-DLBCL. Methods. A total of 1716 patients diagnosed with PG-DLBCL between 1975 and 2017 were obtained from the SEER database and further randomly divided into the training and validating cohorts at a ratio of 7:3. Univariate and multivariate cox analyses were conducted to determine significant variables for the construction of nomogram. The performance of the model was then assessed by the concordance index (C-index), the calibration plot, and the area under the receiver operating characteristic (ROC) curve (AUC). Results. Multivariate analysis revealed that age, race, insurance status, Ann Arbor stage, marital status, chemotherapy, and radiation therapy all showed a significant association with OS and CSS. These characteristics were applied to build a nomogram. In the training cohort, the discrimination of nomogram for OS and CSS prediction was excellent (C-index=0.764, 95 CI, 0.7440.784 and C-index=0.756, 95 CI, 0.7320.780). The AUC of the nomogram for predicting 3- and 5-year OS was 0.779 and 0.784 and CSS was 0.765 and 0.772. Similar results were also observed in the internal validation set. Conclusions. We have successfully established a novel nomogram for predicting OS and CSS in PG-DLBCL patients with good accuracy, which can help physicians to quickly and accurately complete the evaluation of survival probability, risk stratification, and therapeutic strategy at diagnosis.