AIMC Topic: Biomarkers, Tumor

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Electrochemical biosensing in oncology: a review advancements and prospects for cancer diagnosis.

Cancer biology & therapy
Early and precise diagnosis of cancer is pivotal for effective therapeutic intervention. Traditional diagnostic methods, despite their reliability, often face limitations such as invasiveness, high costs, labor-intensive procedures, extended processi...

Machine learning reveals glycolytic key gene in gastric cancer prognosis.

Scientific reports
Glycolysis is recognized as a central metabolic pathway in the neoplastic evolution of gastric cancer, exerting profound effects on the tumor microenvironment and the neoplastic growth trajectory. However, the identification of key glycolytic genes t...

An interpretable machine learning model based on computed tomography radiomics for predicting programmed death ligand 1 expression status in gastric cancer.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: Programmed death ligand 1 (PD-L1) expression status, closely related to immunotherapy outcomes, is a reliable biomarker for screening patients who may benefit from immunotherapy. Here, we developed and validated an interpretable machine l...

Multimodal deep learning for predicting PD-L1 biomarker and clinical immunotherapy outcomes of esophageal cancer.

Frontiers in immunology
Although the immune checkpoint inhibitors (ICIs) have demonstrated remarkable anti-tumor efficacy in solid tumors, the proportion of ESCC patients who benefit from ICIs remains limited. Current biomarkers have assisted in identifying potential respon...

Dual-Modality Virtual Biopsy System Integrating MRI and MG for Noninvasive Predicting HER2 Status in Breast Cancer.

Academic radiology
RATIONALE AND OBJECTIVES: Accurate determination of human epidermal growth factor receptor 2 (HER2) expression is critical for guiding targeted therapy in breast cancer. This study aimed to develop and validate a deep learning (DL)-based decision-mak...

Nano biosensor unlocks tumor derived immune signals for the early detection of ovarian cancer.

Biosensors & bioelectronics
Ovarian cancer is a critical health issue for women nowadays. Its impact is significant because of its high mortality rate (324,603 worldwide), late-stage diagnosis and poor survival rate. Lack of screening tests, vague symptoms, misdiagnosis, and ag...

Enhancing pancreatic cancer diagnostics: Ensemble-based model for automated urine biomarker classification.

Computers in biology and medicine
This research addresses the critical challenge of early detection in pancreatic ductal adenocarcinoma (PDAC) by exploring urinary biomarkers and integrating artificial intelligence (AI) models. The study emphasizes the significance of liquid biopsy, ...

Harnessing Artificial Intelligence for Precision Diagnosis and Treatment of Triple Negative Breast Cancer.

Clinical breast cancer
Triple-Negative Breast Cancer (TNBC) is a highly aggressive subtype of breast cancer (BC) characterized by the absence of estrogen, progesterone, and HER2 receptors, resulting in limited therapeutic options. This article critically examines the role ...

Artificial intelligence and whole slide imaging, a new tool for the microsatellite instability prediction in colorectal cancer: Friend or foe?

Critical reviews in oncology/hematology
Colorectal cancer (CRC) is the third most common and second most deadly cancer worldwide. Despite advances in screening and treatment, CRC is heterogeneous and the response to therapy varies significantly, limiting personalized treatment options. Cer...

Molecular testing in urinary cytology specimens: Current status and future directions.

Urologic oncology
Bladder cancer is a common type of urological cancer with high recurrence and mortality rates. Currently, it is diagnosed and monitored using minimal invasive cystoscopies and biopsies. Urinary cytology, the most widely accepted noninvasive and more ...