Determination of neuron-specific enolase in patients with midgut-type tumour treated with somatostatin analogues

Circulating Neuroendocrine Tumor Biomarkers: Past, Present and Future

Neuroendocrine tumors are a heterogeneous group of neoplasms originating from the diffuse endocrine system. Depending on primary location and hormonal status, they range in terms of clinical presentation, prognosis and treatment. Functional tumors often develop symptoms indicating an excess of hormones produced by the neoplasm (exempli gratia insulinoma, glucagonoma and VIPoma) and can be diagnosed using monoanalytes. For non-functional tumors (inactive or producing insignificant amounts of hormones), universal biomarkers have not been established. The matter remains an important unmet need in the field of neuroendocrine tumors. Substances researched over the years, such as chromogranin A and neuron-specific enolase, lack the desired sensitivity and specificity. In recent years, the potential use of Circulating Tumor Cells or multianalytes such as a circulating microRNA and NETest have been widely discussed. They offer superior diagnostic parameters in comparison to traditional biomarkers and depict disease status in a more comprehensive way. Despite a lot of promise, no international standards have yet been developed regarding their routine use and clinical application. In this literature review, we describe the analytes used over the years and cover novel biomarkers that could find a use in the future. We discuss their pros and cons while showcasing recent advances in the field of neuroendocrine tumor biomarkers.

Serum levels of neuron-specific enolase as a prognostic factor for disease progression in patients with GET/NEN in the pancreas and the small intestine

The aim of this study was to assess the usefulness of neuron-specific enolase (NSE) concentrations as a prognostic factor in patients with neuroendocrine neoplasms and to determine the relationship between NSE and clinicopathological features. Serum NSE levels were measured in 179 NEN patients before treatment. It was found that NSE levels in patients with a primary pancreatic location were higher compared to patients with a small intestine lesion (P = 0.015). NSE levels were significantly higher in patients with primary pancreatic location with histological grade G2 compared with the group with low-grade G1 (P = 0.047). Patients with initial liver involvement showed significantly higher NSE levels compared to patients with tumour location in the pancreas (P = 0.009). Statistical analysis confirmed that higher NSE levels were associated with disease progression (P = 0.001) in both the overall study group and in patients with tumours in the pancreas and small intestine. During treatment monitoring, an increase in median NSE concentrations was observed in patients with persistent progression with subsequent blood draws, and a decrease in NSE concentrations was observed in patients with disease stabilisation. We showed that NSE concentrations have prognostic value for progression-free survival in addition to primary liver involvement. In conclusion, the most important results of the study include the demonstration of an association between NSE concentrations and clinical status, which confirms its usefulness in patient monitoring and as a potential predictive indicator for progression-free survival in patients with NENs.

Analysis of Influencing Factors of Serum Stress Index and Prognosis of HICH Patients by Different Anesthesia Methods Combined with Small Bone Window Microsurgery

In order to investigate the effects of sevoflurane on the serum stress index level and prognosis of patients with hypertensive cerebral hemorrhage (HICH) during small bone window microsurgery, a total of 102 HICH patients are selected for analysis. MAP values in both groups decreased significantly at T1 and T2 (P < 0.05), and the changes in MAP and HR indexes in the sevoflurane combined group were more stable than those in the control group. The time of postoperative awakening in the sevoflurane combined group decreases significantly than the control group (P < 0.001). The levels of T-AOC and GSH-Px in both groups increase significantly after operation, and those in the sevoflurane combined group increase significantly than the control group (P < 0.001). The levels of MDA and 8-OHDG in the sevoflurane combined group decrease significantly than the control group after operation (P < 0.05). Spearman correlation coefficient analysis shows that the levels of T-AOC and GSH-Px are negatively correlated with the prognosis of HICH patients, while MDA and 8-OHDG are positively correlated with the prognosis of HICH patients (P < 0.001). Sevoflurane interventional anesthesia has a high anesthetic effect in small bone window microsurgery, which has positive effects on controlling blood pressure of HICH patients, shortening postoperative recovery time and improving patients' stress response and neurological function. This paper conducts an in-depth analysis of the prognosis of HICH patients, indicating that the prognosis of HICH patients is closely related to their serum stress indicators T-AOC, GSH-Px, MDA, and 8-OHDG, providing a new direction for follow-up clinical diagnosis and treatment of HICH patients and accurate prognosis assessment.

Nomogram for preoperative estimation of histologic grade in gastrointestinal neuroendocrine tumors

BACKGROUND

The treatment strategies and prognosis for gastroenteropancreatic neuroendocrine tumors were associated with tumor grade. Preoperative predictive grading could be of great benefit in the selection of treatment options for patients. However, there is still a lack of effective non-invasive strategies to detect gastrointestinal neuroendocrine tumors (GI-NETs) grading preoperatively.

METHODS

The data on 147 consecutive GI-NETs patients was retrospectively collected from January 1, 2012, to December 31, 2019. Logistic regression was used to construct a predictive model of gastrointestinal neuroendocrine tumor grading using preoperative laboratory and imaging parameters.The validity of the model was assessed by area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA).

RESULTS

The factors associated with GI-NETs grading were age, tumor size, lymph nodes, neuron-specific enolase (NSE), hemoglobin (HGB) and sex, and two models were constructed by logistic regression for prediction. Combining these 6 factors, the nomogram was constructed for model 1 to distinguish between G3 and G1/2, achieving a good AUC of 0.921 (95% CI: 0.884-0.965), and the sensitivity, specificity, accuracy were 0.9167, 0.8256, 0.8630, respectively. The model 2 was to distinguish between G1 and G2/3, and the variables were age, tumor size, lymph nodes, NSE, with an AUC of 0.847 (95% CI: 0.799-0.915), and the sensitivity, specificity, accuracy were 0.7882, 0.8710, 0.8231, respectively. Two online web servers were established on the basis of the proposed nomogram to facilitate clinical use. Both models showed an excellent calibration curve through 1000 times bootstrapped dataset and the clinical usefulness were confirmed using decision curve analysis.

CONCLUSION

The model served as a valuable non-invasive tool for differentiating between different grades of GI-NETs, personalizing the calculation which can lead to a rational treatment choice.