Oncology/Hematology

SOHO State of the Art Updates and Next Questions | Management of Primary Central Nervous System Lymphoma.

Primary Central Nervous System Lymphoma (PCNSL) is a rare and aggressive form of extranodal non-Hodgkin lymphoma. Recent insights into the molecular characteristics of neoplastic B-cells are opening the era of precision diagnostics with the development of liquid biopsy based on biomarkers, such as interleukin-10 level and the presence of MYD88L265P mutation, in the cerebrospinal fluid. Moreover, a...

Advancing precision medicine in pancreatic cancer using novel biomarkers and clinical targets.

Precision-guided therapy is imperative in the battle against pancreatic ductal adenocarcinoma (PDAC), one of the most lethal solid malignancies with limited improvements in survival despite advances in molecular profiling and systemic therapy. While oncogenic drivers such as KRAS, TP53, CDKN2A, and SMAD4 are nearly ubiquitous, their translation into effective targeted therapies has been constraine...

plasmaCHORD: A Machine Learning Approach to Distinguish Clonal Hematopoiesis-Derived Variants in Liquid Biopsies from Patients with Solid Tumors.

PURPOSE: Targeted next-generation sequencing (NGS) of cell-free DNA (cfDNA) enables comprehensive molecular profiling and can guide the selection of g...

A Roadmap to Transform Lung Cancer Outcomes: Priorities in Biology, Therapeutic Innovation, Early Detection, Prevention and Interception.

Advances in targeted therapies, immunotherapy, and early detection have revolutionized lung cancer treatment and extended survival. Nonetheless, lung ...

Multimodal machine learning integrates clinical and comorbidity data to predict breast cancer prognosis and treatment outcomes.

Breast cancer prognosis and treatment outcomes are shaped by intricate interplay between tumor biology, systemic comorbidities, and patient-reported f...

Clinical Machine Learning Model for Predicting Pathological Complete Response in Patients with Esophageal and Gastroesophageal Junction Adenocarcinoma After Trimodality Therapy.

BACKGROUND: Accurate prediction of pathological complete response (pCR) after preoperative chemoradiation therapy, followed by surgery (trimodality th...

From Time-Limited Therapy to Treatment-Free Observation: The Evolving Role of MRD in CLL Management.

The integration of measurable residual disease (MRD) into the management of chronic lymphocytic leukemia (CLL) has emerged as a major advance in risk ...

A review of clinical trial radiotherapy quality assurance: value, evolution and lessons.

BACKGROUND AND PURPOSE: Deviations in radiotherapy quality can significantly affect clinical trial outcomes, including overall survival. Radiotherapy ...

Integrated multi-omics data and machine learning approaches to decipher the molecular network and gene signatures of renal cell carcinoma induced by aristolochic acid.

OBJECTIVE: This study aims to delineate the molecular mechanisms through which aristolochic acid (AA) exposure drives renal cell carcinoma (RCC) patho...

Integrated multi-omics and machine learning highlight PTM-related genes as potential biomarkers in endometrial cancer.

BACKGROUND: Endometrial cancer, the most common gynecological malignancy, represents about 5 % of all cancers in women, with rising incidence rates. E...

Ultrasound-MRI Fusion Deep Learning Radiomics Nomogram: Refining Prognostic Stratification for Triple-Negative Breast Cancer Treated With Neoadjuvant Chemotherapy.

Revealing Li Staging Process in Graphite via a Genetic Algorithm Coupled with a Machine-Learning Interatomic Potential.

Graphite remains the dominant anode material in Li-ion batteries, yet a complete understanding of its Li intercalation mechanism, commonly described a...

Mammography-based artificial intelligence model for predicting axillary lymph node status after neoadjuvant therapy in breast cancer.

OBJECTIVES: Our objective is to develop a deep learning-based artificial intelligence (AI) model capable of analyzing digital mammography (DM) images ...

Enabling AI to Drive Innovation and Precision across Oncology R&D.

The use of integrated large-scale, multidomain datasets with artificial intelligence (AI) is now essential in drug discovery and development. Organiza...

Predictive models for the occurrence and lymph node metastasis of papillary thyroid carcinoma with regional risk heterogeneity.

Papillary thyroid carcinoma (PTC) is the most common thyroid malignancy, and cervical lymph node metastasis significantly impacts patient prognosis. T...

A noninvasive urinary microRNA-based assay for early detection of lung cancer and its potential application to prognosis and recurrence monitoring: a case-control study.

Lung cancer remains the leading cause of cancer-related mortality worldwide, with recurrence or cancer-related death occurring even after curative-int...

Risk prediction model of survival in patients with low-grade serous ovarian cancer: a multicenter Cohort study.

PURPOSE: Accurate prognostic prediction remains a significant challenge in the management of low-grade serous ovarian cancer (LGSOC), a rare and molec...

The B7 family subgroup reflects tumor cell heterogeneity and patient post-operative prognosis in gallbladder cancer.

PURPOSE: To elucidate the biological heterogeneity of gallbladder cancer (GBC) cells and refine post-operative risk stratification by investigating th...

[Bottlenecks and breakthroughs in gastric cancer diagnosis and treatment: Towards a new era of precision and intelligent integration].

Gastric cancer constitutes a significant global health burden, and its clinical management is undergoing a critical transition from a traditional expe...

[Practice and reflection on sentinel lymph node navigation surgery for early gastric cancer].

With the continuous update and iteration of minimally invasive techniques, artificial intelligence and big data, the surgical treatment of early gastr...