Chemotherapy

Uncoupling Type I Interferon Benefits From Inflammatory Toxicity: Transformer-Prioritized Precision Agonists for Potent and Safer Cancer Immunotherapy.

Paclitaxel (PTX) chemotherapy is constrained by an "immunomodulatory paradox," where antitumor Type I Interferon (IFN-I) activation is coupled with detrimental pro-inflammatory cascades. To address this challenge, we developed Deep Learning for Innate Immunity Modulatory Potential (DLINP), a Transformer-based framework designed to identify precision immunomodulators that uncouple IFN-I induction f...

Radiologic, Pathologic, and Deep Learning Predictors of Response to Immune Checkpoint Blockade in Renal Cell Carcinoma Patients Undergoing Post-Treatment Nephrectomy.

Response assessment of primary kidney tumors in the consolidation cytoreductive and neoadjuvant settings offers a unique opportunity to inform postoperative adaptive treatment strategies. Yet, systematic analyses of nephrectomy specimens post immune checkpoint inhibition (ICI) therapies are lacking. We retrospectively identified consecutive renal cell carcinoma (RCC) patients with locoregionally a...

The Lymph Node Ratio as a Predictive Biomarker for Individualized Benefit from Adjuvant Chemotherapy in Gastric Cancer: A Retrospective Cohort and Causal Machine Learning Study.

BACKGROUND: Optimizing adjuvant chemotherapy (AC) for gastric cancer (GC) remains challenging due to patient heterogeneity. While the lymph node ratio...

Neoantigen in cancer immunotherapy: mechanism, therapeutic strategies and future perspectives.

Neoantigens are tumor-specific antigens resulting from genetic, transcriptomic, and proteomic changes, making them a promising avenue for personalized...

Integrative single-cell sequencing and machine learning analyses identify chronic inflammation and cancer-associated fibroblast subsets as drivers of adverse outcomes in ovarian cancer.

BACKGROUND: Ovarian cancer remains the deadliest gynecological malignancy, with neoadjuvant chemotherapy (NACT) often leaving residual fibroblast-enri...

Machine Learning-Guided Personalized Immunochemotherapy Strategies in Intrahepatic Cholangiocarcinoma.

BACKGROUND & AIMS: Immunochemotherapy (IO-chemo) has become standard care for patients with unresectable intrahepatic cholangiocarcinoma (iCCA), but b...

Artificial Intelligence-based 3D Assessment of Alopecia Areata Using Clinical Photographs.

Super-resolution MRI and 2.5D deep learning for intratumoral-peritumoral radiomics in preoperative prediction of rectal cancer perineural invasion.

OBJECTIVES: Preoperative prediction of perineural invasion (PNI) in rectal cancer (RC) is challenging due to limited MRI resolution and the neglect of...

Molecular active learning approaches for predicting skin cytotoxicity.

Skin cytotoxicity assessment of small molecules is vital for assessing their risk of cytotoxicity upon topical contact. However, identifying cytotoxic...

[Paeoniflorin alleviates cancer-related fatigue during chemotherapy for breast cancer by targeting EZH2/CCNE1 to regulate cell cycle and inflammatory microenvironment].

OBJECTIVES: To explore the molecular mechanisms and key pharmacodynamic basis of Baishao for alleviating cancer-related fatigue (CRF) during chemother...

[Reflections on surgical management strategies for locally advanced gastric cancer after neoadjuvant immunotherapy].

Neoadjuvant immunotherapy is reshaping the treatment landscape of locally advanced gastric cancer (GC). The central clinical challenge has expanded fr...

Artificial intelligence-driven prediction of neoadjuvant chemotherapy response in adult patients with gastric cancer: a systematic review and meta-analysis.

OBJECTIVES: A substantial proportion of adults with locally advanced gastric cancer derive limited benefit from neoadjuvant chemotherapy (NAC), with a...

[Endoscopic diagnostics and treatment of early neoplasia of the esophagus].

Endoscopic diagnostics and treatment of early esophageal neoplasia have achieved considerable progress in recent years. For Barrett's esophagus-associ...

Nanotechnology-based immunotherapy: integrating Artificial Intelligence (AI) with current strategies in combating brain cancer disease.

Brain cancer is one of the most challenging malignancies and a major contributor to worldwide morbidity and mortality. Glioblastoma, the most aggressi...

Alopecia Areata: Advances in Clinical Evaluation and Pathogenesis.

Alopecia areata (AA) is a common autoimmune condition that affects approximately 2% of the global population. Although it most commonly presents with ...

Integration of single-cell transcriptomics and genomic mutation analysis identifies an immunotherapy-resistant tumor subcluster and validates ARNTL2 as a malignant driver in lung adenocarcinoma.

BACKGROUND: Immunotherapy resistance in lung adenocarcinoma (LUAD) remains a critical clinical challenge, and the mechanisms underlying resistance-ass...

Transcriptomic Profiling of Mouse Mammary Tumors Enables Prognostic and Predictive Biomarker Discovery for Human Breast Cancer.

The development and validation of prognostic and predictive biomarkers in breast cancer is limited by the availability of well-annotated datasets link...

Evaluation of an AI-powered tool in improving lesion visualization on standard-dose contrast-enhanced brain MRI: a retrospective, multicenter study.

BACKGROUND AND PURPOSE: Artificial intelligence (AI) algorithms have been used to synthesize standard-dose images from low-dose images in brain MRI, b...

Radiomics-Based AI for Predicting Neoadjuvant Immunochemotherapy Pathological Response in Non-Small Cell Lung Cancer: Systematic Review and Meta-Analysis.

BACKGROUND: Non-small cell lung cancer (NSCLC) remains the leading cause of cancer-related mortality worldwide. Accurate early prediction of response ...

Building Machine Learning Models Based on Oxidative Stress Index Score to Predict Survival of Locally Advanced Rectal Cancer Receiving Different Neoadjuvant Therapy Patterns.

BACKGROUND: Liver enzyme biomarkers are known to contribute to the onset and progression of colorectal cancer. OBJECTIVE: To develop a novel oxidative...