Intratumor heterogeneity (ITH) is defined as differences in molecular and phenotypic profiles between different tumor cells and immune cells within a tumor. ITH was involved in the cancer progression, aggressiveness, therapy resistance and cancer rec...
OBJECTIVE: Immunotherapy has dramatically altered the therapeutic landscape for oncology, but more research is needed to identify patients who are likely to achieve durable clinical benefit and those who may develop unacceptable side effects. We inve...
Glioblastoma presents characteristically with an exuberant, poorly functional vasculature that causes malperfusion, hypoxia and necrosis. Despite limited clinical efficacy, anti-angiogenesis resulting in vascular normalization remains a promising the...
International journal of molecular sciences
Jan 18, 2024
Cancer stands as the leading global cause of mortality, with rare cancer comprising 230 distinct subtypes characterized by infrequent incidence. Despite the inherent challenges in addressing the diagnosis and treatment of rare cancers due to their lo...
Using the particular nature of melanoma mutanomes to develop medicines that activate the immune system against specific mutations is a game changer in immunotherapy individualisation. It offers a viable solution to the recent rise in resistance to ac...
Expert review of molecular diagnostics
Dec 15, 2023
INTRODUCTION: Pancreatic cancer (PC) has an extremely poor prognosis, even with surgical resection and triplet chemotherapy treatment. Cancer immunotherapy has been recently approved for tumor-agnostic treatment with genome analysis, including in PC....
RATIONALE AND OBJECTIVES: This study aimed to develop and evaluate a radiomics-based model combined with clinical and qualitative radiological (semantic feature [SF]) features to predict immune checkpoint inhibitor-related pneumonitis (CIP) in patien...
This article expands on recent studies of machine learning or artificial intelligence (AI) algorithms that crucially depend on benchmark datasets, often called 'ground truths.' These ground-truth datasets gather input-data and output-targets, thereby...
Predicting protein stability change upon variation through a computational approach is a valuable tool to unveil the mechanisms of mutation-induced drug failure and develop immunotherapy strategies. Some previous machine learning-based techniques exh...