[Chromogranin A and neuroendocrine tumors].

Endocrinol Nutr

Servicio de Endocrinología y Nutrición, Hospital Clínico San Carlos, Madrid, España.

Published: July 2014

Chromogranin A (CgA) is the most abundant granin in gastroenteropancreatic neuroendocrine tumors (GEP-NETs). As a tumor marker is moderately sensitive and nonspecific. Despite the limitations of testing methods, which require careful interpretation, especially in the case of gastrinomas, patients treated with somatostatin analogues, and poorly differentiated tumors, it is the best tumor marker in GEP-NETs and may be of value in other tumors with neuroendocrine differentiation. CgA may be used as a marker in blood or tissue samples through immunohistochemical techniques. CgA levels correlate with tumor burden and extension and may be used for diagnosis and monitoring of GEP-NETs, especially midgut carcinoids and endocrine pancreatic tumors. It is also useful as a prognostic marker for detection of recurrence and monitoring of response to different treatments.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.endonu.2012.10.003DOI Listing

Publication Analysis

Top Keywords

tumor marker
8
[chromogranin neuroendocrine
4
neuroendocrine tumors]
4
tumors] chromogranin
4
chromogranin cga
4
cga abundant
4
abundant granin
4
granin gastroenteropancreatic
4
gastroenteropancreatic neuroendocrine
4
tumors
4

Similar Publications

Objective: Tuberous sclerosis complex (TSC) is a monogenetic disorder associated with sustained mechanistic target of rapamycin (mTOR) activation, leading to heterogeneous clinical manifestations. Epilepsy and renal angiomyolipoma are the most important causes of morbidity in adult people with TSC (pwTSC). mTOR is a key player in inflammation, which in turn could influence TSC-related clinical manifestations.

View Article and Find Full Text PDF

Next-generation cancer phenomics by deployment of multiple molecular endophenotypes coupled with high-throughput analyses of gene expression offer veritable opportunities for triangulation of discovery findings in non-small cell lung cancer (NSCLC) research. This study reports differentially expressed genes in NSCLC using publicly available datasets (GSE18842 and GSE229253), uncovering 130 common genes that may potentially represent crucial molecular signatures of NSCLC. Additionally, network analyses by GeneMANIA and STRING revealed significant coexpression and interaction patterns among these genes, with four notable hub genes-, , and -identified as pivotal in NSCLC progression.

View Article and Find Full Text PDF

Purpose: Patients with advanced non-small cell lung cancer (NSCLC) have varying responses to immunotherapy, but there are no reliable, accepted biomarkers to accurately predict its therapeutic efficacy. The present study aimed to construct individualized models through automatic machine learning (autoML) to predict the efficacy of immunotherapy in patients with inoperable advanced NSCLC.

Methods: A total of 63 eligible participants were included and randomized into training and validation groups.

View Article and Find Full Text PDF

Background: SET domain-containing protein 4 (SETD4) is a histone methyltransferase that has been shown to modulate cell proliferation, differentiation, and inflammatory responses by regulating histone H4 trimethylation (H4K20me3). Previous reports have demonstrated its function in the quiescence of cancer stem cells as well as drug resistance in several cancers. A limited number of systematic studies have examined SETD4's role in the tumor microenvironment, pathogenesis, prognosis, and therapeutic response.

View Article and Find Full Text PDF

Background: This study aims to elucidate the expression pattern of SERPINE1, assess its prognostic significance, and explore potential therapeutic drugs targeting this molecule.

Methods And Results: In this study, we delved into the variations in gene mutation, methylation patterns, and expression levels of SERPINE1 in head and neck squamous cell carcinoma (HNSCC) and normal tissues, leveraging comprehensive analyses of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. The connection between the biological function of the gene and prognosis was scrutinized through immune infiltration and enrichment analyses.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!