Chemotherapy

Development and validation of a highly accurate multigene gene expression biomarker to predict chemotherapy response in primary triple-negative breast cancer.

PURPOSE: Triple-negative breast cancer (TNBC) is an aggressive subtype lacking estrogen and progesterone receptors and HER2 amplification. Representing 10-15% of breast cancer cases, TNBC disproportionately affects Black and pre-menopausal women and is associated with poorer outcomes. With chemotherapy as the primary systemic treatment option, achieving a pathological complete response (pCR) to ne...

Systems-level integration of machine learning, SHAP explainability, PCA, and network topology reveals multitarget protective actions of tannic acid against doxorubicin toxicity in pentose phosphate pathway.

Doxorubicin (DOX) is an effective chemotherapeutic agent; however, its clinical use is limited due to dose-dependent toxicities. This study aimed to investigate the potential protective effect of tannic acid (TA), a natural polyphenol with antioxidant properties, against DOX-induced alterations in oxidative pentose phosphate pathway (PPP) enzymes in rat lung tissue. Male rats were treated with DOX...

Integrating Mechanistic Modeling and Machine Learning to Study CD4+/CD8+ CAR-T Cell Dynamics with Tumor Antigen Regulation.

Chimeric antigen receptor (CAR) T cell therapy has shown remarkable success in hematological malignancies, yet patient responses remain highly variabl...

AI-discovered cellular morphometric biomarkers in needle biopsy of prostate cancer predict neoadjuvant androgen deprivation therapy response and enable therapeutic targeting of mTOR in androgen deprivation therapy-resistant tumors.

It is imperative to identify patients with prostate cancer (PCa) who will not benefit from androgen receptor signaling inhibitors and to improve their...

Improving severity grading of chemotherapy-induced myelosuppression in AML via data-driven and model-based deep learning.

Chemotherapy-induced myelosuppression in acute myeloid leukemia (AML) frequently leads to life-threatening complications, yet current assessment stand...

Microneedle-based theranostics for melanoma: Advances and outlook.

Melanoma represents a highly aggressive malignancy that poses persistent challenges for clinical diagnosis and treatment. Although surgical interventi...

Mathematical Prediction Models for Sentinel Node Status in Early-Stage Breast Cancer: Protocol for a Systematic Review.

BACKGROUND: The status of the axilla remains a significant prognostic factor and influences adjuvant systemic and locoregional treatment choices in ea...

Precision oncology meets nanotechnology: AI-driven liposomal nanocarriers for enhanced cancer immunotherapy.

The integration of artificial intelligence (AI) with nanotechnology is redefining therapeutic strategies in cancer immunotherapy and chemotherapy. The...

A 13-gene prognostic model developed using machine learning to predict the response to neoadjuvant chemoradiotherapy in rectal carcinoma.

Diagnostic Accuracy of Artificial Intelligence for Predicting MGMT Promoter Methylation in Glioblastoma Using MR Imaging: A Systematic Review.

PURPOSE: Glioblastoma (GBM) is an aggressive brain tumor with poor prognosis. O6-methylguanine-DNA-methyltransferase (MGMT) promoter methylation is a ...

AI-assisted tumor board decision-making in pancreatic oncology.

BACKGROUND: Pancreatic cancer requires nuanced, multidisciplinary treatment planning typically conducted within tumor boards. While Large Language Mod...

Diagnostic accuracy of an AI-based pathologic response assessment in locally advanced non-small cell lung cancer after neoadjuvant chemo-immunotherapy.

Contrasting roles of PD-L1 expression in tumor and stroma: Biological and prognostic implications in esophageal squamous cell carcinoma.

Programmed death-ligand 1 (PD-L1) plays a central role in immune regulation in esophageal squamous cell carcinoma (ESCC) and has been widely used as a...

MRI-based AI framework for predicting lymph node metastasis and prognosis in rectal cancer after neoadjuvant chemoradiotherapy: a multicenter study.

BACKGROUND: Early prediction of lymph node metastasis (LNM) after neoadjuvant chemoradiotherapy (nCRT) is crucial for improving treatment planning and...

A programmable matrix-robust plasmonic MetaRing biosensor for rapid SERS-based chemotherapeutic response profiling.

Rapid assessment of chemotherapeutic response is essential for precision oncology but remains hindered by tumor heterogeneity and complex biological m...

Estimating major pathological response in non-small cell lung cancer patients with post-neoadjuvant therapy using MMT-net.

Neoadjuvant therapy (NAT) has demonstrated considerable effectiveness in treating locally advanced non-small cell lung cancer (NSCLC). Major pathologi...

Second-line chemotherapy after gemcitabine plus nab-paclitaxel in metastatic pancreatic cancer: comparative outcomes and AI-guided treatment selection.

BACKGROUND: International guidelines recommend 5FU/LV, Nal-IRI + 5FU/LV, FOLFIRI, FOLFOX, or (m)FOLFIRINOX as second-line (2 L) chemotherapy for patie...

Circulating MicroRNA Signatures in Severe Alopecia Areata: Diagnostic Discrimination, Pathway Analysis, and Therapeutic Implications.

INTRODUCTION: Alopecia areata (AA) is an autoimmune disorder characterized by non-scarring hair loss due to immune dysregulation. Despite advances, it...

Antibody-drug conjugate design and mechanisms of action for cancer treatment: state of the art and beyond.

Antibody-drug conjugates (ADCs) are a leading area of targeted cancer therapeutics, typically combining a tumour-associated antigen-specific antibody ...

Hypoxia-related and immune phenotype-related fusion model for non-invasive prognostication of hepatocellular carcinoma treated by TACE: a multicentre study.

BACKGROUND: Survival outcomes after transarterial chemoembolisation (TACE) vary in hepatocellular carcinoma (HCC) patients, and existing prognostic sc...