A large percentage of metastatic colorectal cancer (mCRC) patients presents metastasis at the time of diagnosis. In the last years, great efforts have been made in the treatment of these patients with the identification of different phenotypes playing a key role in the definition of new systemic therapies. Unsupervised hierarchical clustering analysis (HCA) was performed considering the clinicopathological characteristics of 51 mCRCs. Using immunohistochemistry on tissue microarrays, we assessed the expression of β-catenin, NHERF1, RASSF1A, TWIST1, HIF-1α proteins in tumors and paired liver metastases. We also analyzed RASSF1A methylation status on the samples of the same patients. HCA distinguished Group 1 and Group 2 characterized by different clinicopathological features. Group 1 was characterized by higher number of positive lymph nodes (=0.0139), poorly differentiated grade (<0.0001) and high extent of tumor spread (=0.0053) showing a more aggressive phenotype compared to Group 2. In both Groups, we found a common "basal" condition with a higher level of nuclear TWIST1 (<0.0001 and cytoplasmic β-catenin (<0.0001) in tumors than in paired liver metastases. Furthermore, the Group 1 was also characterized by RASSF1A hypermethylation (<0.0001) and nuclear HIF-1α overexpression (0.0354) in paired liver metastases than in tumors. In conclusion, HCA identifies mCRC patients with a more aggressive phenotype. Moroever, our results support the important contribution to the progression of the disease of RASSF1A methylation and the oncogenic role of HIF-1α in these patients. These evidences, should provide relevant information concerning the biology of this tumor and, as a consequence, potential new systemic therapeutic approaches.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5675672PMC
http://dx.doi.org/10.18632/oncotarget.21213DOI Listing

Publication Analysis

Top Keywords

hierarchical clustering
8
clustering analysis
8
metastatic colorectal
8
group characterized
8
analysis identifies
4
identifies metastatic
4
colorectal cancers
4
patients
4
cancers patients
4
patients aggressive
4

Similar Publications

Introduction: Gastric cancer (GC) is among the deadliest malignancies globally, characterized by hypoxia-driven pathways that promote cancer progression, including stemness mechanisms facilitating invasion and metastasis. This study aimed to develop a prognostic decision tree using genes implicated in hypoxia and stemness pathways to predict outcomes in GC patients.

Materials And Methods: GC RNA-seq data from The Cancer Genome Atlas (TCGA) were analyzed to compute hypoxia and stemness scores using Gene Set Variation Analysis (GSVA) and the mRNA expression-based stemness index (mRNAsi).

View Article and Find Full Text PDF

Background: To explore the symptom clusters of patients undergoing maintenance hemodialysis and construct a symptom network to identify the core symptoms and core symptom clusters, to provide reference for precise symptom management.

Methods: Conveniently selected 354 patients with maintenance hemodialysis were surveyed cross-sectionally using the general information questionnaire, the Dialysis Symptom Index and the Kidney Disease Questionnaire. Symptom clusters were extracted using exploratory factor analysis, and core symptom clusters were identified using hierarchical regression and network analysis.

View Article and Find Full Text PDF

Prognostic signature of multimorbidity, geriatric syndromes and resources cluster in older in- and outpatients: a pooled secondary analysis with a 6-month follow-up.

BMJ Open

December 2024

Department II of Internal Medicine and Center for Molecular Medicine Cologne, University of Cologne, Faculty of Medicine and University Hospital Cologne, University Hospital Cologne, Cologne, Nordrhein-Westfalen, Germany

Objective: The prognosis of older adults is strongly influenced by the relation of multifactorial geriatric syndromes (GS) and their health-maintaining counterparts, geriatric resources (GR). The present analysis aimed to identify clusters of comorbidities, GS and GR, and to measure their multidimensional prognostic signature in older patients admitted to different healthcare settings.

Design: Pooled secondary analysis of three longitudinal interventional studies with the 3- and 6-month follow-up data collection on mortality and rehospitalisation.

View Article and Find Full Text PDF

[Establishment of a quality grading standard of Isatidis Radix decoction pieces based on appearance traits and internal quality indexes].

Zhongguo Zhong Yao Za Zhi

December 2024

Institute of International Standardization for Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine Shanghai 201203, China Shanghai Academy of International Standardization for Traditional Chinese Medicine Shanghai 201203, China.

This study aims to establish a quality grading standard that combines the conventional quality evaluation based on morphological characteristics of traditional Chinese medicine with the modern quality evaluation. Based on the existing standards and market circulation of Isatidis Radix, the diameter and color of Isatidis Radix decoction pieces were selected as the appearance traits for preliminary grading. The effects of internal quality indexes such as moisture, total ash, acid-insoluble ash, ethanol-soluble extractives, and 9 water-soluble components on different grades of decoction pieces were comprehensively compared, and the key grading indexes were determined by t-test.

View Article and Find Full Text PDF

Nudiviruses (family ) are double-stranded DNA viruses that infect various insects and crustaceans. Among them, Heliothis zea nudivirus 1 (HzNV-1) represents the rare case of a lepidopteran nudivirus inducing a sexual pathology. Studies about molecular pathological dynamics of HzNV-1 or other nudiviruses are scarce.

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!