AIMC Topic: Biomarkers, Tumor

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Deployment of a Machine Learning Algorithm in a Real-World Cohort for Quality Control Monitoring of Human Epidermal Growth Factor-2-Stained Clinical Specimens in Breast Cancer.

Archives of pathology & laboratory medicine
CONTEXT.—: Precise determination of biomarker status is necessary for clinical trial enrollment and endpoint analyses, as well as for optimal treatment determination in real-world practice. However, variabilities may be introduced into this process d...

GBMPurity: A machine learning tool for estimating glioblastoma tumor purity from bulk RNA-sequencing data.

Neuro-oncology
BACKGROUND: Glioblastoma (GBM) presents a significant clinical challenge due to its aggressive nature and extensive heterogeneity. Tumor purity, the proportion of malignant cells within a tumor, is an important covariate for understanding the disease...

Exosomal Gene Biomarkers in Osteosarcoma: Mifepristone as a Targeted Therapeutic Revealed by Multi-Omics Analysis.

FASEB journal : official publication of the Federation of American Societies for Experimental Biology
Osteosarcoma (OS) is an aggressive bone cancer that mainly occurs in children and adolescents. OS patients are mainly treated with neoadjuvant chemotherapy and surgical resection. This treatment is effective for early osteosarcoma. However, the effec...

Metabolic pathway alterations in cerebrospinal fluid as diagnostic biomarkers for primary central nervous system lymphoma.

Clinica chimica acta; international journal of clinical chemistry
Primary Central Nervous System Lymphoma (PCNSL) is a rare and aggressive type of hematological malignancy that can pose diagnostic challenges. Early detection is critical for effective treatment and better patient outcomes. The goal of this study was...

Mid-level data fusion of pleural effusion SERS spectra and serum CEA levels using machine learning algorithms for precise lung cancer detection.

Nanoscale
Accurate identification of clinically malignant pleural effusions is critical for cancer diagnosis and subsequent treatment planning. Here, surface-enhanced Raman spectroscopy (SERS) data of pleural effusions and serum carcinoembryonic antigen (CEA) ...

Combining Spatial Transcriptomics, Pseudotime, and Machine Learning Enables Discovery of Biomarkers for Prostate Cancer.

Cancer research
UNLABELLED: Early cancer diagnosis is crucial but challenging owing to the lack of reliable biomarkers that can be measured using routine clinical methods. The identification of biomarkers for early detection is complicated by each tumor involving ch...

Global Thyroid Cancer Patterns and Predictive Analytics: Integrating Machine Learning for Advanced Diagnostic Modelling.

Journal of cellular and molecular medicine
BACKGROUND: The global increase in thyroid cancer prevalence, particularly among female populations, underscores critical gaps in our understanding of molecular pathogenesis and diagnostic capabilities. Our investigation addresses these knowledge def...

Leveraging deep learning to discover interpretable cellular spatial biomarkers for prognostic predictions based on hepatocellular carcinoma histology.

The journal of pathology. Clinical research
The spatial structure of various cell types in the tumour microenvironment (TME) can provide valuable insights into disease progression. However, identifying the spatial organization of diverse cell types that significantly correlates with patient pr...

Integrating multi-omics data with artificial intelligence to decipher the role of tumor-infiltrating lymphocytes in tumor immunotherapy.

Pathology, research and practice
Tumor-infiltrating lymphocytes (TILs) are capable of recognizing tumor antigens, impacting tumor prognosis, predicting the efficacy of neoadjuvant therapies, contributing to the development of new cell-based immunotherapies, studying the tumor immune...

Advances in pancreatic cancer diagnosis: from DNA methylation to AI-assisted imaging.

Expert review of molecular diagnostics
INTRODUCTION: Pancreatic Cancer (PC) is a highly aggressive tumor that is mainly diagnosed at later stages. Various imaging technologies, such as CT, MRI, and EUS, possess limitations in early PC diagnosis. Therefore, this review article explores the...