AIMC Topic: Biomarkers, Tumor

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Developing angiogenesis-related prognostic biomarkers and therapeutic strategies in bladder cancer using deep learning and machine learning.

Scientific reports
Bladder cancer (BLCA) is a prevalent urological malignancy that exhibits a high degree of tumor heterogeneity and morbidity. Tumor angiogenesis, a vital hallmark of cancer, greatly influences the tumor microenvironment (TME). The emergence of anti-an...

Immunodiagnostic plasma amino acid residue biomarkers detect cancer early and predict treatment response.

Nature communications
The immune response to tumour development is frequently targeted with therapeutics but remains largely unexplored in diagnostics, despite being stronger for early-stage tumours. We present an immunodiagnostic platform to detect this. We identify a pa...

Library-based virtual match-between-runs quantification in GlyPep-Quant improves site-specific glycan identification.

Nature communications
Glycosylation changes are closely related to various diseases, including cancer. The quantitative analysis of site-specific glycans at proteomics scale remains challenging due to low glycopeptide spectra interpretation. Here, we present GlyPep-Quant,...

A comprehensive analysis of transcription factors identified TCF3 as a prognostic target for glioma.

Scientific reports
Transcription factors (TFs) are pivotal in tumor initiation and progression, regulating downstream gene expression and modulating cellular processes. In this study, we conducted a comprehensive analysis of TF gene sets to define the molecular subtype...

Machine Learning-Assisted Multimodal Early Screening of Lung Cancer Based on a Multiplexed Laser-Induced Graphene Immunosensor.

ACS nano
Lung cancer remains the leading cause of cancer-related mortality worldwide, largely due to late-stage diagnosis. Early detection is critical for improving patient outcomes, yet current screening methods, such as low-dose computed tomography (CT), of...

Comprehensive multi-omics and machine learning framework for glioma subtyping and precision therapeutics.

Scientific reports
Glioma is a highly heterogeneous and aggressive brain tumour that demands an integrated understanding of its molecular and immunological landscape. We collected multi-omics data from 575 TCGA diffuse-glioma patients (156 IDH-wild-type WHO-grade 4 gli...

Exploration and validation of the prognostic value of mitophagy and mitochondrial dynamics-related genes in cervical cancer.

Scientific reports
The mechanisms underlying mitophagy and mitochondrial dynamics (MD) in cervical cancer (CC), a disease with a high mortality rate, remain poorly understood. This study aimed to assess the prognostic significance of these processes in CC. Mendelian ra...

OMT and tensor SVD-based deep learning model for segmentation and predicting genetic markers of glioma: A multicenter study.

Proceedings of the National Academy of Sciences of the United States of America
Glioma is the most common primary malignant brain tumor and preoperative genetic profiling is essential for the management of glioma patients. Our study focused on tumor regions segmentation and predicting the World Health Organization (WHO) grade, i...

Evaluating cell-free DNA integrity index as a non-invasive biomarker for neoadjuvant chemotherapy in colorectal cancer patients.

BMC cancer
BACKGROUND: Neoadjuvant chemotherapy (NAC) is gaining attention as a treatment for advanced colorectal cancer owing to its potential to improve surgical outcomes and prognosis. However, reliable biomarkers to predict the response to NAC are lacking. ...

Automated cell annotation and classification on histopathology for spatial biomarker discovery.

Nature communications
Histopathology with hematoxylin and eosin (H&E) staining is routinely employed for clinical diagnoses. Single-cell analysis of histopathology provides a powerful tool for understanding the intricate cellular interactions underlying disease progressio...