Prognostic and Predictive Role of Body Composition in Metastatic Neuroendocrine Tumor Patients Treated with Everolimus: A Real-World Data Analysis

Identification of mitophagy-related hub genes during the progression of spinal cord injury by integrated multinomial bioinformatics analysis

Spinal cord injury (SCI) is a disturbance of peripheral and central nerve conduction that causes disability in sensory and motor function. Currently, there is no effective treatment for SCI. Mitophagy plays a vital role in mitochondrial quality control during various physiological and pathological processes. The study aimed to elucidate the role of mitophagy and identify potential mitophagy-related hub genes in SCI pathophysiology. Two datasets (GSE15878 and GSE138637) were analyzed. Firstly, the differentially expressed genes (DEGs) were identified and mitophagy-related genes were obtained from GeneCards, then the intersection between SCI and mitophagy-related genes was determined. Next, we performed gene set enrichment analysis (GSEA), weighted gene co-expression network analysis (WGCNA), protein-protein interaction network (PPI network), least absolute shrinkage and selection operator (LASSO), and cluster analysis to identify and define the hub genes in SCI. Finally, the link between hub genes and infiltrating immune cells was investigated and the potential transcriptional regulation/small molecular compounds to target hub genes were predicted. In total, SKP1 and BAP1 were identified as hub genes of mitophagy-related DEGs during SCI development and regulatory T cells (Tregs)/resting NK cells/activated mast cells may play an essential role in the progression of SCI. LINC00324 and SNHG16 may regulate SKP1 and BAP1, respectively, through miRNAs. Eleven and eight transcriptional factors (TFs) regulate SKP1 and BAP1, respectively, and six small molecular compounds target BAP1. Then, the mRNA expression levels of BAP1 and SKP1 were detected in the injured sites of spinal cord of SD rats at 6 h and 72 h after injury using RT-qPCR, and found that the level were decreased. Therefore, the pathways of mitophagy are downregulated during the pathophysiology of SCI, and SKP1 and BAP1 could be accessible targets for diagnosing and treating SCI.

The effect of hyperlipidemia on overall survival in patients with cancer was differentiated by BMI and hyperlipidemia type

BACKGROUND AND AIMS

The impact of lipids on the overall survival (OS) of patients with malignancy has not yet been clarified. This study aimed to evaluate the effect of hyperlipidemia on the OS among Chinese patients based on Body Mass Index (BMI) stratifications and hyperlipidemia types.

METHOD

The patients in this study were derived from the Investigation of the Nutrition Status and Clinical Outcome of Common Cancers (INSCOC) trial. Kaplan-Meier was used to draw the survival curve, and the log-rank test was used to estimate the survival rates between each group. Cox proportional hazards regression models were used to estimate the hazard ratios (HR) and 95% confidence intervals (CI).

RESULTS

A total of 9054 patients were included in the final study, with a median age of 59 years, and 55.3% (5004) of them were males. Regarding types of hyperlipidemia, only low high-density lipoprotein was an independent risk factor for the prognosis of all patients (HR = 1.35, 95% CI: 1.25-1.45, P < 0.001), while high total cholesterol (HR = 1.01, 95% CI: 0.90-1.15, P = 0.839) and high low-density lipoprotein (HR = 1.03, 95%CI: 0.91-1.16, P = 0.680) were not. In terms of BMI stratification, the effect of triglycerides on prognosis varied; high triglycerides were an independent risk factor for the prognosis of underweight patients (HR = 1.56, 95% CI:1.05-2.32, P = 0.027) and a protective factor for overweight patients (HR = 0.75, 95% CI: 0.63-0.89, P = 0.001). However, for normal-weight patients, there was no significant statistical difference (HR = 0.88, 95%CI: 0.75-1.03, P = 0.108).

CONCLUSIONS

The impact of hyperlipidemia on the OS among patients with cancer varied by different BMI and hyperlipidemia types. BMI and hyperlipidemia type ought to be considered in combination to estimate the prognosis of patients with malignancy.

Assessment of the Role of Leptin and Adiponectinas Biomarkers in Pancreatic Neuroendocrine Neoplasms

Data on the possible connection between circulating adipokines and PanNENs are limited. This novel study aimed to assess the serum levels of leptin and adiponectin and their ratio in patients with PanNENs and to evaluate the possible relationship between them and PanNEN's grade or stage, including the presence of metastases. The study group consisted of PanNENs (n = 83), and healthy controls (n = 39). Leptin and adiponectin measurement by an ELISA assay was undertaken in the entire cohort. The serum concentration of adiponectin was significantly higher in the control group compared to the study group (p < 0.001). The concentration of leptin and adiponectin was significantly higher in females than in males (p < 0.01). Anincreased leptin-adiponectin ratio was observed in well-differentiated PanNENs (G1) vs. moderatelydifferentiated PanNENs (G2) (p < 0.05). An increased leptin-adiponectin ratio was found in PanNENs with Ki-67 < 3% vs. Ki-67 ≥ 3% (p < 0.05). PanNENs with distal disease presented lower leptin levels (p < 0.001) and a decreased leptin-adiponectin ratio (p < 0.01) compared with the localized disease group. Leptin, adiponectin, and the leptin-adiponectin ratio may serve as potential diagnostic, prognostic, and predictive biomarkers for PanNENs. Leptin levels and the leptin-adiponectin ratio may play an important role as predictors of malignancy and metastasis in PanNENs.

What have we learnt from the past - would treatment decisions for GEP-NET patients differ between 2012 to 2016 by the new recommendations in 2022?

BACKGROUND

Gastroenteropancreatic neuroendocrine tumors (GEP-NETs) are a heterogeneous group of tumors with a broad range of local and systemic treatment options. Still a lack of data regarding treatment sequences exists. The aim of this study was to analyse outcomes in GEP-NETs depending on stage and treatment steps and compare our treatment decisions to the latest treatment recommendations of European Society of Medical Oncology (ESMO) 2020 for GEP-NETs.

METHODS

Patients were included in this retrospective single-center analysis from 2012-2016. All patients suffering from a GEP-NET, who were screened, treated or evaluated at ENETS Center in Zurich, Switzerland were included in analysis. Patients with any other diagnosis of NET were not included. We used Kaplan Meier estimator as well as Cox regression to compare survival rates between different sites of localization, grades or stages and treatment sequences.

RESULTS

Overall, we identified 256 GEP-NETs, most in advanced stage (62%) and located in small intestine tract or pancreatic gland. Survival depended on stage, grade, primary site and duration of response for the early systemic treatment. On average patients underwent 2.6 different treatment modalities, mostly depending on stage and higher tumor grade. Surgery was performed early but also in advanced stages, usually followed by Somatostatine-Agonist modalities. In distant disease (Stage IV), we investigated a positive effect of PFS after treatment with Somatostatine Analogues (SSA) (hazard ratio [HR], 0.45; 95% confidence interval [CI], 0.21 - 0.97; p = 0.04) and systemic treatment (HR, 0.51; 95% CI, 0.26 - 0.99; p = 0.047) if patients underwent prior surgery or endoscopic resection. Kaplan Meier distributions predict shorter OS in distant disease (Stage IV), (Figure. 1; HR, 2.06; 95% CI, 1.46 - 2.89; log-rank test, p < 0.001).

CONCLUSION

This retrospective analysis presents a great overview of all patients', disease and treatment characteristics of GEP-NETs at ENETS Center in Zurich, Switzerland. We illustrated survival (PFS) depending on implemented therapies. According to these findings, we formed a suggested treatment algorithm for advanced GEP-NETs, which does not differ from the latest treatment recommendation by ESMO guidelines for GEP-NETs. The results of this project may define GEP-NET patients' selection for upcoming clinical prospective studies.

Exploring the Relationship between Obesity, Metabolic Syndrome and Neuroendocrine Neoplasms

Obesity is a major burden for modern medicine, with many links to negative health outcomes, including the increased incidence of certain cancer types. Interestingly, some studies have supported the concept of an “Obesity Paradox”, where some cancer patients living with obesity have been shown to have a better prognosis than non-obese patients. Neuroendocrine neoplasms (NENs) are malignancies originating from neuroendocrine cells, in some cases retaining important functional properties with consequences for metabolism and nutritional status. In this review, we summarize the existing evidence demonstrating that obesity is both a risk factor for developing NENs as well as a good prognostic factor. We further identify the limitations of existing studies and further avenues of research that will be necessary to optimize the metabolic and nutritional status of patients living with NENs to ensure improved outcomes.

Impact of Change in Body Composition during Follow-Up on the Survival of GEP-NET

Background: Gastroenteropancreatic neuroendocrine tumors (GEP-NETs) are heterogeneous rare diseases causing malnutrition and cachexia in which the study of body composition may have an impact in prognosis. Aim: Evaluation of muscle and fat tissues by computed tomography (CT) at the level of the third lumbar (L3 level) at diagnosis and at the end of follow-up in GET-NET patients and their relationships with clinical and biochemical variables as predictors of survival. Methodology: Ninety-eight GEP-NET patients were included. Clinical and biochemical parameters were evaluated. Total body, subcutaneous, visceral and total fat areas and very low-density, low-density, normal density, high-density, very high-density and total muscle areas were obtained from CT images. Results: Body composition measures and overall mortality correlated with age, ECOG (Eastern Cooperative Oncology Group performance status) metastases, lactate dehydrogenase (LDH), albumin and urea levels. Although there was no relationship between body composition variables at diagnosis and overall and specific mortality, an increase in low-density muscle and a decrease in normal-density muscle during follow-up were independently correlated to overall (p <0.05) and tumor-cause mortality (p < 0.05). Conclusion: Although body composition measures obtained by CT at diagnosis did not impact survival of GEP-NET patients, a loss of good quality muscle during follow-up was associated with an increased overall and tumor-related mortality. Nutritional status should therefore be supervised by nutrition specialists and an increase in good quality muscle could improve prognosis.