Application of heat above 43°C and up to 47°C, the so-called "thermal ablation" range, leads to tumor cell destruction either by apoptosis or by necrosis. However, tumor cells have developed mechanisms of defense that render them thermoresistant. Of importance, the application of heat for the treatment of localized solid tumors can also prime specific antitumor immunity. Herein, a bioinformatic approach was employed for the identification of molecular determinants implicated in thermoresistance and immunogenic cell death (ICD). To this end, both literature-derived (text mining) and microarray gene expression profile data were processed, followed by functional enrichment analysis. Two important functional gene modules were detected in hyperthermia resistance and ICD, the former including members of the heat shock protein (HSP) family of molecular chaperones and the latter including immune-related molecules, respectively. Of note, the molecules HSP90AA1 and HSPA4 were found common between thermoresistance and damage signaling molecules (damage-associated molecular patterns (DAMPs)) and ICD. In addition, the prognostic potential of and overexpression for cancer patients' overall survival was investigated. The results of this study could constitute the basis for the strategic development of more efficient and personalized therapeutic strategies against cancer by means of thermotherapy, by taking into consideration the genetic profile of each patient.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6878812PMC
http://dx.doi.org/10.1155/2019/4606219DOI Listing

Publication Analysis

Top Keywords

bioinformatic approach
8
identification molecular
8
molecular determinants
8
cancer thermotherapy
8
application heat
8
approach identification
4
molecular
4
determinants resistance/sensitivity
4
resistance/sensitivity cancer
4
thermotherapy application
4

Similar Publications

Integer Topological Defects Reveal Antisymmetric Forces in Active Nematics.

Phys Rev Lett

December 2024

Shanghai Jiao Tong University, School of Physics and Astronomy, Institute of Natural Sciences, Shanghai 200240, China.

Cell layers are often categorized as contractile or extensile active, nematics but recent experiments on neural progenitor cells with induced +1 topological defects challenge this classification. In a bottom-up approach, we first study a relevant particle-level model and then analyze a continuum theory derived from it. We show that both model and theory account qualitatively for the main experimental result, i.

View Article and Find Full Text PDF

Motivation: The accurate prediction of O-GlcNAcylation sites is crucial for understanding disease mechanisms and developing effective treatments. Previous machine learning models primarily relied on primary or secondary protein structural and related properties, which have limitations in capturing the spatial interactions of neighboring amino acids. This study introduces local environmental features as a novel approach that incorporates three-dimensional spatial information, significantly improving model performance by considering the spatial context around the target site.

View Article and Find Full Text PDF

Background: Lung adenocarcinoma is one of the most common malignant tumors worldwide. Its complex molecular mechanisms and high tumor heterogeneity pose significant challenges for clinical treatment. The manganese ion metabolism family plays a crucial role in various biological processes, and the abnormal expression of the NUDT3 gene in multiple cancers has drawn considerable attention.

View Article and Find Full Text PDF

SHP2 promotes the epithelial-mesenchymal transition in triple negative breast cancer cells by regulating β-catenin.

J Cancer Res Clin Oncol

January 2025

Key Laboratory of Laboratory Medicine, Ministry of Education of China, School of Laboratory Medicine and Life Sciences, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China.

Purpose: Growing evidence suggests that the tyrosine phosphatase SHP2 is pivotal for tumor progression. Triple-negative breast cancer (TNBC) is the most lethal subtype of breast cancer, characterized by its high recurrence rate, aggressive metastasis, and resistance to chemotherapy. Understanding the mechanisms of tumorigenesis and the underlying molecular pathways in TNBC could aid in identifying new therapeutic targets.

View Article and Find Full Text PDF

Average nucleotide identity (ANI) is a widely used metric to estimate genetic relatedness, especially in microbial species delineation. While ANI calculation has been well optimized for bacteria and closely related viral genomes, accurate estimation of ANI below 80%, particularly in large reference data sets, has been challenging due to a lack of accurate and scalable methods. To bridge this gap, we introduce MANIAC, an efficient computational pipeline optimized for estimating ANI and alignment fraction (AF) in viral genomes with divergence around ANI of 70%.

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!