PCSK2 expression in neuroendocrine tumors points to a midgut, pulmonary, or pheochromocytoma-paraganglioma origin

Susceptibility of PCSK2 Polymorphism to Hirschsprung Disease in Southern Chinese Children

Introduction

Hirschsprung's disease (HSCR) is a developmental defect of the enteric nervous system (ENS), which is caused by abnormal development of enteric neural crest cells. Its occurrence is caused by genetic factors and environmental factors. It has been reported that single nucleotide polymorphisms (SNPs) of proprotein convertase subtilisin/kexin type 2 (PCSK2) gene are associated with HSCR. However, the correlation of HSCR in southern Chinese population is still unclear.

Methods

We assessed the association of rs16998727 with HSCR susceptibility in southern Chinese children using TaqMan SNP genotyping analysis of 2943 samples, including 1470 HSCR patients and 1473 controls. The association test between rs16998727 and phenotypes was performed using multivariable logistic regression analysis.

Results

We got an unexpected result, PCSK2 SNP rs16998727 was not significantly different from HSCR and its HSCR subtypes: S-HSCR (OR = 1.08, 95% IC: 0.93~1.27, P_adj = 0.3208), L-HSCR (OR = 1.07, 95% IC: 0.84~1.36, P_adj = 0.5958) and TCA (OR = 0.94, 95% IC: 0.61~1.47, P_adj = 0.8001).

Conclusion

In summary, we report that rs16998727 (PCSK2 and OTOR) is not associated with the risk of HSCR in southern Chinese population.

A more novel and robust gene signature predicts outcome in patients with esophageal squamous cell carcinoma

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) is a life-threatening thoracic tumor with a poor prognosis. The tumor microenvironment (TME) mainly comprises tumor cells and tumor-infiltrating immune cells mixed with stromal components. The latest research has displayed that tumor immune cell infiltration (ICI) is closely connected with the ESCC patients' clinical prognosis. This study was designed to construct a gene signature based on the ICI of ESCC to predict prognosis.

METHODS

Based on the selection criteria we set, the eligible ESCC cases from the GSE53625 and TCGA-ESCA datasets were chosen for the training cohort and the validation cohort, respectively. Unsupervised clustering detailed grouped ESCC cases of the training cohort based on the ICI profile. We determined the differential expression genes (DEGs) between the ICI clusters, and, subsequently, we adopted the univariate Cox analysis to recognize DEGs with prognostic potential. These screened DEGs underwent a Lasso regression, which then generated a gene signature. The harvested signature's predictive ability was further examined by the Kaplan-Meier analysis, Cox analysis, ROC, IAUC, and IBS. More importantly, we listed similar studies in the most recent year and compared theirs with ours. We performed the functional annotation, immune relevant signature correlation analysis, and immune infiltrating analysis to thoroughly understand the functional mechanism of the signature and the immune cells' roles in the gene signature's predicting capacity.

RESULTS

A sixteen-gene signature (ARSD, BCAT1, BIK, CLDN11, DLEU7-AS1, GGH, IGFBP2, LINC01037, LINC01446, LINC01497, M1AP, PCSK2, PCSK5, PPP2R2A, TIGD7, and TMSB4X) was generated from the Lasso model. We then confirmed the signature as having solid and stable prognostic capacity by several statistical methods. We revealed the superiority of our signature after comparing it to our predecessors, and the GSEA uncovered the specifically mechanism of action related to the gene signature. Two immune relevant signatures, including GZMA and LAG3 were identified associating with our signature. The immune-infiltrating analysis identified crucial roles of resting mast cells, which potentially support the sixteen-gene signature's prognosis ability.

CONCLUSIONS

We discovered a robust sixteen-gene signature that can accurately predict ESCC prognosis. The immune relevant signatures, GZMA and LAG3, and resting mast cells infiltrating were closely linked to the sixteen-gene signature's ability.

The Role of Lipid Metabolism in Gastric Cancer

Gastric cancer has been one of the most common cancers worldwide with extensive metastasis and high mortality. Chemotherapy has been found as a main treatment for metastatic gastric cancer, whereas drug resistance limits the effectiveness of chemotherapy and leads to treatment failure. Chemotherapy resistance in gastric cancer has a complex and multifactorial mechanism, among which lipid metabolism plays a vital role. Increased synthesis of new lipids or uptake of exogenous lipids can facilitate the rapid growth of cancer cells and tumor formation. Lipids form the structural basis of biofilms while serving as signal molecules and energy sources. It is noteworthy that lipid metabolism is capable of inducing drug resistance in gastric cancer cells by reshaping the tumor micro-environment. In this study, new mechanisms of lipid metabolism in gastric cancer and the metabolic pathways correlated with chemotherapy resistance are reviewed. In particular, we discuss the effects of lipid metabolism on autophagy, biomarkers treatment and drug resistance in gastric cancer from the perspective of lipid metabolism. In brief, new insights can be gained into the development of promising therapies through an in-depth investigation of the mechanism of lipid metabolism reprogramming and resensitization to chemotherapy in gastric cancer cells, and scientific treatment can be provided by applying lipid-key enzyme inhibitors as cancer chemical sensitizers in clinical settings.

PCSK2 expression in neuroendocrine tumors points to a midgut, pulmonary, or pheochromocytoma-paraganglioma origin

Neuroendocrine tumors (NETs) are often diagnosed from the metastases of an unknown primary tumor. Specific immunohistochemical (IHC) markers indicating the location of a primary tumor are needed. The proprotein convertase subtilisin/kexin type 2 (PCSK2) is found in normal neural and neuroendocrine cells, and known to express in NETs. We investigated the tissue microarray (TMA) of 86 primary tumors from 13 different organs and 9 metastatic NETs, including primary tumor‐metastasis pairs, for PCSK2 expression with polymer‐based IHC. PCSK2 was strongly positive in all small intestine and appendiceal NETs, the so‐called midgut NETs, in most pheochromocytomas and paragangliomas, and in some of the typical and atypical pulmonary carcinoid tumors. NETs showing strong positivity were re‐evaluated in larger tumor cohorts confirming the primary observation. In the metastases, the expression of PCSK2 mirrored that of the corresponding primary tumors. We found negative or weak staining in NETs from the thymus, gastric mucosa, pancreas, rectum, thyroid, and parathyroid. PCSK2 expression did not correlate with Ki‐67 in well‐differentiated NETs. Our data suggest that PCSK2 positivity can indicate the location of the primary tumor. Thus, PCSK2 could function in the IHC panel determined from screening metastatic NET biopsies of unknown primary origins.