World Journal of Gastrointestinal Oncology最新文献

Survival rates following radical surgery for gastric neuroendocrine neoplasms (g-NENs) are low, with high recurrence rates. This fact impacts patient prognosis and complicates postoperative management. Traditional prognostic models, including the Cox proportional hazards (CoxPH) model, have shown limited predictive power for postoperative survival in gastrointestinal neuroectodermal tumor patients. Machine learning methods offer a unique opportunity to analyze complex relationships within datasets, providing tools and methodologies to assess large volumes of high-dimensional, multimodal data generated by biological sciences. These methods show promise in predicting outcomes across various medical disciplines. In the context of g-NENs, utilizing machine learning to predict survival outcomes holds potential for personalized postoperative management strategies. This editorial reviews a study exploring the advantages and effectiveness of the random survival forest (RSF) model, using the lymph node ratio (LNR), in predicting disease-specific survival (DSS) in postoperative g-NEN patients stratified into low-risk and high-risk groups. The findings demonstrate that the RSF model, incorporating LNR, outperformed the CoxPH model in predicting DSS and constitutes an important step towards precision medicine.

Background: The prognostic impact of preoperative gamma-glutamyl transpeptidase to platelet ratio (GPR) levels in patients with solitary hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) following radical resection has not been established.

Aim: To examine the clinical utility of GPR for prognosis prediction in solitary HBV-related HCC patients.

Methods: A total of 1167 solitary HBV-related HCC patients were retrospectively analyzed. GPR levels were compared with 908 non-HCC individuals. Overall survival (OS) and recurrence-free survival (RFS) were evaluated, and cox proportional hazard model analyses were performed to identify independent risk factors. Differences in characteristics were adjusted by propensity score matching (PSM). Subgroup and stratified survival analyses for HCC risks were performed, and a linear trend of the hazard ratio (HR) according to GPR levels was constructed.

Results: GPR levels of patients with solitary HBV-related HCC were higher than those with hepatic hemangiomas, chronic hepatitis B and healthy control (adjusted P < 0.05). Variable bias was diminished after the PSM balance test. The low GPR group had improved OS (P < 0.001) and RFS (P < 0.001) in the PSM analysis and when combined with other variables. Multivariate cox analyses suggested that low GPR levels were associated with a better OS (HR = 0.5, 95%CI: 0.36-0.7, P < 0.001) and RFS (HR = 0.57, 95%CI: 0.44-0.73, P < 0.001). This same trend was confirmed in subgroup analyses. Prognostic nomograms were constructed and the calibration curves showed that GPR had good survival prediction. Moreover, stratified survival analyses found that GPR > 0.6 was associated with a worse OS and higher recurrence rate (P for trend < 0.001).

Conclusion: Preoperative GPR can serve as a noninvasive indicator to predict the prognosis of patients with solitary HBV-related HCC.

Newer systemic therapies for hepatocellular carcinoma (HCC) have led to growing interest in combining hepatic arterial infusion chemotherapy (HAIC) with systemic treatments. To evaluate the effectiveness and safety of HAIC and combination therapies in treating advanced HCC, a network meta-analysis was conducted by Zhou et al. The study included data from 44 articles. HAIC was superior in overall survival (OS), progression-free survival (PFS), and response rates compared to transarterial chemoembolization and sorafenib. Moreover, combinations of HAIC with other treatments and single agents (e.g., lenvatinib, ablation, anti-programmed cell death 1 therapy, radiotherapy) provided better OS and PFS outcomes than HAIC alone. In this editorial, we will discuss the study findings, the strengths and weaknesses of the metanalysis, and future advances in the field of HAIC for advanced HCC.

Hepatocellular carcinoma (HCC) is a lethal disease and unfortunately, most patients will be diagnosed with unresectable/advanced stages and the overall prognosis is poor. For patients with initially unresectable HCC (uHCC), transarterial chemoembolization (TACE) was the mainstream treatment. Lately, the incorporation of immune checkpoint inhibitors and antiangiogenics for the treatment of metastatic disease has paved the way for significant improvements in the treatment of initially uHCC. In this editorial we will discuss an article that evaluated ICI combinations with lenvatinib and TACE for the treatment of uHCC patients, and highlight future advances in the field.

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths worldwide. Major treatments include liver transplantation, resection, and chemotherapy, but the 5-year recurrence rate remains high. Late diagnosis often prevents surgical intervention, contributing to poor patient survival rates. Carcinogenesis in HCC involves genetic alterations that drive the transformation of normal cells into malignant ones. Enhancer of zeste homolog 2 (EZH2), a key regulator of cell cycle progression, is frequently upregulated in HCC and is associated with advanced stages and poor prognosis, making it a potential biomarker. Additionally, signal transducer and activator of transcription 3, which binds to EZH2, affects disease staging and outcomes. Targeting EZH2 presents a promising therapeutic strategy. On the other hand, abnormal lipid metabolism is a hallmark of HCC and impacts prognosis. Fatty acid binding protein 5 is highly expressed in HCC tissues and correlates with key oncogenes, suggesting its potential as a biomarker. Other genes such as guanine monophosphate synthase, cell division cycle associated 5, and epidermal growth factor receptor provide insights into the molecular mechanisms of HCC, offering potential as biomarkers and therapeutic targets.

Background: Signet-ring cell carcinoma (SRCC) is a rare subtype of colorectal cancer. The incidence of primary colonic SRCC is relatively rare in pediatric patients, with a limited number of reported cases currently available. The prognosis for this specific tumor type is unfavorable, and the preoperative diagnosis presents challenges, potentially leading to misdiagnosis. This case report describes the diagnosis of primary SRCC in the colon of a 10-year-old girl.

Case summary: The patient was admitted to the hospital due to abdominal pain and vomiting. A computed tomography scan revealed an irregular mass with soft tissue density in her transverse colon, showing uneven density and multiple calcifications. The patient underwent surgical resection of the affected bowel and lymph node dissection, which was confirmed by pathological examination to be SRCC infiltrating both nerves and the entire intestinal wall. Additionally, tumor thrombus formation was observed in blood vessels and lymphatic vessels, multiple cancerous nodules were found in the omentum, and metastasis to 18 of 26 mesenteric lymph nodes examined. Immunohistochemistry for mismatch repair gene protein demonstrated microsatellite stability. No mutations in KRAS, NRAS, BRAF, or PIK3CA genes were detected through molecular pathology analysis. After surgery, she received standard chemotherapy for 8 cycles without tumor progression or other abnormalities during a 12-month follow-up period.

Conclusion: Primary colonic SRCC is a rare malignant tumor with atypical clinical symptoms, and timely identification and intervention are crucial for improving the prognosis.

Background: Cirrhosis is a significant risk factor for the development of hepatocellular carcinoma (HCC). Variability in HCC risk among patients with cirrhosis is notable, particularly when considering the diverse etiologies of cirrhosis.

Aim: To identify specific risk factors contributing to HCC development in patients with cirrhosis.

Methods: This retrospective study analyzed data from cirrhotic patients at Beijing Youan Hospital from January 1, 2012 to September 30, 2022 with at least 6 mo of follow-up. Patient demographics, medical histories, etiologies, and clinical characteristics were examined. Cox regression analysis was used to analyze correlations of the above parameters with hepatocarcinogenesis, while competing risk regression was used to estimate their adjusted hazard ratios accounting for death. The cumulative incidence was plotted over time.

Results: Overall, 5417 patients with cirrhosis (median age: 54 years; 65.8% males) were analyzed. Hepatitis B virus (HBV) was the most common etiology (23.3%), with 25% (n = 1352) developing HCC over a 2.9-year follow-up period. Patients with multiple etiologies had the HCC highest incidence (30.3%), followed by those with HBV-related cirrhosis (29.5%). Significant risk factors included male sex, advanced age, hepatitis C virus (HCV) infection, elevated blood ammonia, and low platelet count. Men had a higher 5-year HCC risk than women (37.0% vs 31.5%). HBV, HCV, and HBV/HCV co-infected patients had 5-year risks of HCC of 45.8%, 42.9%, and 48.1%, respectively, compared to 29.5% in nonviral hepatitis cases, highlighting the significant HCC risk from viral hepatitis, especially HBV, and underscores the importance of monitoring these high-risk groups.

Conclusion: In conclusion, HBV-related cirrhosis strongly correlates with HCC, with male sex, older age, viral hepatitis, elevated blood ammonia, and lower albumin and platelet levels increasing the risk of HCC.

Background: Gastrointestinal stromal tumors (GIST) are prevalent neoplasm originating from the gastrointestinal mesenchyme. Approximately 50% of GIST patients experience tumor recurrence within 5 years. Thus, there is a pressing need to accurately evaluate risk stratification preoperatively.

Aim: To assess the application of a deep learning model (DLM) combined with computed tomography features for predicting risk stratification of GISTs.

Methods: Preoperative contrast-enhanced computed tomography (CECT) images of 551 GIST patients were retrospectively analyzed. All image features were independently analyzed by two radiologists. Quantitative parameters were statistically analyzed to identify significant predictors of high-risk malignancy. Patients were randomly assigned to the training (n = 386) and validation cohorts (n = 165). A DLM and a combined DLM were established for predicting the GIST risk stratification using convolutional neural network and subsequently evaluated in the validation cohort.

Results: Among the analyzed CECT image features, tumor size, ulceration, and enlarged feeding vessels were identified as significant risk predictors (P < 0.05). In DLM, the overall area under the receiver operating characteristic curve (AUROC) was 0.88, with the accuracy (ACC) and AUROCs for each stratification being 87% and 0.96 for low-risk, 79% and 0.74 for intermediate-risk, and 84% and 0.90 for high-risk, respectively. The overall ACC and AUROC were 84% and 0.94 in the combined model. The ACC and AUROCs for each risk stratification were 92% and 0.97 for low-risk, 87% and 0.83 for intermediate-risk, and 90% and 0.96 for high-risk, respectively. Differences in AUROCs for each risk stratification between the two models were significant (P < 0.05).

Conclusion: A combined DLM with satisfactory performance for preoperatively predicting GIST stratifications was developed using routine computed tomography data, demonstrating superiority compared to DLM.

Background: Colorectal cancer (CRC), the third most common cancer worldwide, has increasingly detrimental effects on human health. Radiotherapy resistance diminishes treatment efficacy. Studies suggest that spermine synthase (SMS) may serve as a potential target to enhance the radiosensitivity.

Aim: To investigate the association between SMS and radiosensitivity in CRC cells, along with a detailed elucidation of the underlying mechanisms.

Methods: Western blot was adopted to assess SMS expression in normal colonic epithelial cells and CRC cell lines. HCT116 cells were transfected with control/SMS-specific shRNA or control/pcDNA3.1-SMS plasmids. Assessments included cell viability, colony formation, and apoptosis via MTT assays, colony formation assays, and flow cytometry. Radiosensitivity was studied in SMS-specific shRNA-transfected HCT116 cells post-4 Gy radiation, evaluating cell viability, colony formation, apoptosis, DNA damage (comet assays), autophagy (immunofluorescence), and mammalian target of rapamycin (mTOR) pathway protein expression (western blot).

Results: Significant up-regulation of SMS expression levels was observed in the CRC cell lines. Upon down-regulation of SMS expression, cellular viability and colony-forming ability were markedly suppressed, concomitant with a notable increase in apoptotic indices. Furthermore, attenuation of SMS expression significantly augmented the sensitivity of HCT116 cells to radiation therapy, evidenced by a pronounced elevation in levels of cellular DNA damage and autophagy. Importantly, down-regulation of SMS corresponded with a marked reduction in the expression levels of proteins associated with the mTOR signaling pathway.

Conclusion: Knocking down SMS attenuates the mTOR signaling pathway, thereby promoting cellular autophagy and DNA damage to enhance the radiosensitivity of CRC cells.

In this editorial we comment on the interesting article by Liu et al. The topic of discussion is the need for a cost-effective and easy-to-use scoring system for predicting the prognosis of colorectal cancer patients. In this context, nutritional assessment plays a crucial role in the multimodal evaluation of patients. In particular, the controlling nutritional status score was found to be an effective tool in the clinical decision-making process, in order to customize treatment strategies and to improve patient outcomes.