Radiotherapy (RT) is a primary treatment modality for a number of cancers, offering potentially curative outcomes. Despite its success, tumour can become resistant to RT, leading to disease recurrence. Components of the tumour microenvironment (TME) likely play an integral role in managing RT success or failure including infiltrating immune , the tumour vasculature and stroma. Furthermore, genomic profiling of the TME could identify predictive biomarkers or gene signatures indicative of RT response. In this review, we will discuss proposed mechanisms of radioresistance within the TME, biomarkers that may predict RT outcomes, and future perspectives on radiation treatment in the era of personalised medicine.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7830490 | PMC |
| http://dx.doi.org/10.3390/jpm11010053 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Highly multiplexed imaging reveals prognostic immune and stromal spatial biomarkers in breast cancer.
JCI Insight
January 2025
Department of Biomedical Engineering, Oregon Health and Science University, Portland, United States of America.
Spatial profiling of tissues promises to elucidate tumor-microenvironment interactions and generate prognostic and predictive biomarkers. We analyzed single-cell, spatial data from three multiplex imaging technologies: cyclic immunofluorescence (CycIF) data we generated from 102 breast cancer patients with clinical follow-up, and publicly available imaging mass cytometry and multiplex ion-beam imaging datasets. Similar single-cell phenotyping results across imaging platforms enabled combined analysis of epithelial phenotypes to delineate prognostic subtypes among estrogen-receptor positive (ER+) patients.
View Article and Find Full Text PDFPromising Nanoparticles-Based Oral Therapy for Effective Inhibition of Hepatocellular Carcinoma with Portal Vein Tumor Thrombus.
Nano Lett
January 2025
Faculty of Hepato-Pancreato-Biliary Surgery, The First Medical Center of Chinese People's Liberation Army (PLA) General Hospital, Beijing 100853, P. R. China.
Portal vein tumor thrombus (PVTT) is a poor prognostic factor for hepatocellular carcinoma (HCC) patients, highlighting the need for an oral drug delivery system that combines convenience, simplicity, biosafety, and improved patient compliance. Leveraging the unique anatomy of the portal vein and insights from single-cell RNA sequencing of the PVTT tumor microenvironment, we developed oral pellets using CaCO@PDA nanoparticles (NPs) encapsulating both doxorubicin hydrochloride and low molecular weight heparin. These NPs target the tumor thrombus microenvironment, aiming to break down the thrombus barrier and turn the challenge of portal vein blockage into an advantage by enhancing drug delivery efficiency through oral administration.
View Article and Find Full Text PDFAxonFinder: Automated segmentation of tumor innervating neuronal fibers.
Heliyon
January 2025
Cancer Early Detection Advanced Research Center (CEDAR), Knight Cancer Institute, Oregon Health and Science University, Portland, OR, USA.
Neurosignaling is increasingly recognized as a critical factor in cancer progression, where neuronal innervation of primary tumors contributes to the disease's advancement. This study focuses on segmenting individual axons within the prostate tumor microenvironment, which have been challenging to detect and analyze due to their irregular morphologies. We present a novel deep learning-based approach for the automated segmentation of axons, AxonFinder, leveraging a U-Net model with a ResNet-101 encoder, based on a multiplexed imaging approach.
View Article and Find Full Text PDFBackground And Aim: The high rate of tumor growth results in an increased need for amino acids. As solute carriers (SLC) transporters are capable of transporting different amino acids, cancer may develop as a result of these transporters' over-expression due to their complex formation with other biological molecules. Therefore, this review investigated the role of SLC transporters in the progression of cancer.
View Article and Find Full Text PDFIdentify characteristics of Vietnamese oral squamous cell carcinoma patients by machine learning on transcriptome and clinical-histopathological analysis.
J Dent Sci
December 2024
Blood Transfusion Haematology Hospital No. 2, Ho Chi Minh City, Viet Nam.
Background/purpose: Oral squamous cell carcinoma (OSCC) is notorious for its low survival rates, due to the advanced stage at which it is commonly diagnosed. To enhance early detection and improve prognostic assessments, our study harnesses the power of machine learning (ML) to dissect and interpret complex patterns within mRNA-sequencing (RNA-seq) data and clinical-histopathological features.
Materials And Methods: 206 retrospective Vietnamese OSCC formalin-fixed paraffin-embedded (FFPE) tumor samples, of which 101 were subjected to RNA-seq for classification based on gene expression.
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!