AIMC Topic: Tumor Microenvironment

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Automated tumor stroma ratio assessment in colorectal cancer using hybrid deep learning approach.

Scientific reports
The Tumor-Stroma Ratio (TSR) is a critical prognostic factor in colorectal cancer (CRC), offering insights into tumor microenvironment interactions. However, traditional TSR assessment methods are subjective and labor-intensive. This study is among t...

Constructing a sixteen lactate-related gene risk signature for LUAD to predict the prognosis and TME by machine learning.

Scientific reports
Although it is the most common subtype of lung cancer in clinical practice, lung adenocarcinoma (LUAD) was proven to be associated with a poor prognosis. In recent years, lactate metabolism has been considered an important biological mechanism in lun...

Macrophage mitophagy-related genes predict prognosis and therapeutic response in lung adenocarcinoma.

Scientific reports
Mitochondrial autophagy (mitophagy) in macrophages is crucial yet poorly understood within the lung adenocarcinoma (LUAD) tumor microenvironment. This study aimed to identify key macrophage mitophagy-related genes and develop a robust prognostic mode...

Spatial profiling of HPV-stratified head and neck squamous cell carcinoma reveals distinct immune niches and microenvironmental architectures.

Journal of translational medicine
BACKGROUND: HPV status is a key determinant of prognosis and treatment response in head and neck squamous cell carcinoma (HNSCC). To investigate how HPV influences the tumor-immune-stromal landscape, we performed high-dimensional spatial profiling, i...

Multimodal AI and tumour microenvironment integration predicts metastasis in cutaneous melanoma.

Nature communications
Accurate prognostication is essential to guide clinical management in localised cutaneous melanoma (CM), the form of skin cancer with the highest mortality. While the tumour microenvironment (TME) plays a key role in disease progression, current stag...

Automatically quantifying spatial heterogeneity of immune and tumor hypoxia environment and predicting disease-free survival for patients with rectal cancer.

Cancer immunology, immunotherapy : CII
Immunohistochemistry (IHC) remains the gold standard for evaluating protein expression in tumor microenvironment analysis. This approach hinders robust correlation analyses between spatial heterogeneity in the tumor microenvironment and clinical outc...

SpatialFusion: A Unified Model for Integrating Spatial Transcriptomics to Unveil Cell-type Distribution, Interaction, and Functional Heterogeneity in Tissue Microenvironments.

Journal of molecular biology
Recent advances in spatial transcriptomics (ST) have significantly enhanced our understanding of tissue structure and intercellular interactions. However, existing methods for spatial domain identification and cell type deconvolution still face chall...

Drug resistance in cancer: molecular mechanisms and emerging treatment strategies.

Molecular biomedicine
Therapeutic resistance remains a defining challenge in oncology, limiting the durability of current therapies and contributing to disease relapse and poor patient outcomes. This review systematically integrates recent progress in understanding the mo...

Dual smart monitoring and predictive non-destructive evaluation: A review of advanced hydrogel and stem cell-based strategies for oral cancer theragnostic applications.

International journal of pharmaceutics
Oral cancer remains one of the most aggressive malignancies worldwide, with high recurrence and limited treatment outcomes due to late diagnosis and ineffective targeting of tumor microenvironments. Stem cell-based hydrogel therapies have emerged as ...

Selectivity Approaches in Therapeutic Antibody Design.

Journal of medicinal chemistry
Protein therapeutics, particularly antibody-based therapies, have emerged as a cornerstone in modern disease treatment, offering key advantages over small molecules, including superior target specificity, longer half-life, and expanded target accessi...