AIMC Topic: Biomarkers, Tumor

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Classification of lung cancer using ensemble-based feature selection and machine learning methods.

Molecular bioSystems
Lung cancer is one of the leading causes of death worldwide. There are three major types of lung cancers, non-small cell lung cancer (NSCLC), small cell lung cancer (SCLC) and carcinoid. NSCLC is further classified into lung adenocarcinoma (LADC), sq...

Prediction of biochemical recurrence after robot-assisted radical prostatectomy: analysis of 784 Japanese patients.

International journal of urology : official journal of the Japanese Urological Association
OBJECTIVES: To examine biochemical recurrence after robot-assisted radical prostatectomy in Japanese patients, and to develop a risk stratification model for biochemical recurrence.

Multiomics Profiling of T-cell Leukemia and Lymphoma Enables Targeted Therapeutic Discovery.

Cancer research
UNLABELLED: T-cell leukemias and lymphomas (TCL) form a heterogeneous group of rare and often aggressive malignancies. Because of the rarity and heterogeneity of TCL subtypes, clinical trials are challenging to conduct, making pharmacogenomic studies...

Unraveling risk factors and transcriptomic signatures in liver cancer progression and mortality through machine learning and bioinformatics.

Briefings in functional genomics
Liver cancer (LC) is the second leading cause of cancer-related deaths globally, yet the molecular mechanisms linking its progression with associated risk factors (RFs) remain poorly understood. To address this, we developed an integrative multi-stag...

Path2Omics Enhances Transcriptomic and Methylation Prediction Accuracy from Tumor Histopathology.

Cancer research
UNLABELLED: Precision oncology is becoming increasingly integral to clinical practice, demonstrating notable improvements in treatment outcomes. Whereas molecular data provide comprehensive insights, obtaining such data remains costly and time-consum...

Deep learning predicts microsatellite instability status in colorectal carcinoma in an ethnically heterogeneous population in South Africa.

Journal of clinical pathology
BACKGROUND: Deep learning (DL) models are effective pre-screening tools for detecting mismatch repair deficiency (dMMR) in colorectal carcinoma (CRC). These models have been trained and validated on large cohorts from the Northern Hemisphere, without...

Precision Oncology: 2025 in Review.

Cancer discovery
This article discusses the specific advances made in precision oncology in 2025, in which we saw the approval of multiple new indications for known precision oncology agents and early promising data for novel agents that target either classical pathw...

Integrative machine learning and bioinformatics analysis unveil key genes for precise glioma classification and prognosis evaluation.

Computational biology and chemistry
Gliomas exhibit significant heterogeneity and diverse molecular subtypes, and there are marked differences in treatment strategies and prognoses for gliomas of different grades and molecular types. However, current glioma molecular subtyping systems ...

Improved analytical workflow towards machine learning supported N-glycomics-based biomarker discovery.

Talanta
The composition and function of glycans are very complex thus manual data interpretation of their structural elucidation is difficult. Capillary electrophoresis is one of the liquid phase separation techniques, which is most frequently used to addres...

Discovery of novel diagnostic biomarkers of hepatocellular carcinoma associated with immune infiltration.

Annals of medicine
OBJECTIVE: Diagnosis of hepatocellular carcinoma (HCC) remains challenging for clinicians. Machine learning approaches and big data analyses are viable strategies for identifying HCC diagnostic markers.