Other Cancers

Fatty acid synthesis therapy-induced senescence (FASTIS) in cancer cells.

Therapy-induced senescence (TIS) in cancer cells can be triggered by radiotherapy, chemotherapy, and certain targeted therapeutics. Here, we demonstrate that a new form of TIS, termed fatty acid synthesis therapy-induced senescence (FASTIS), can be induced by pharmacologically targeting de novo lipogenesis. Cancer cells can evade the anti-proliferative effects of clinically relevant inhibitors of ...

A multimodal MRI radiomics model for distinguishing borderline from malignant ovarian epithelial tumors.

BACKGROUND: To develop and validate a multimodal MRI radiomics machine learning model for differentiating borderline epithelial ovarian tumors (BEOTs) from malignant epithelial ovarian tumors (MEOTs). METHODS: A total of 147 patients (72 with BEOTs and 75 with MEOTs) were retrospectively enrolled and randomly divided into training and test cohorts at a ratio of 7:3. Multivariate logistic regressio...

Radiomics using contrast-enhanced T1-weighted imaging and clinical features for predicting response to EGFR-TKIs in EGFR-mutated non-small cell lung cancer patients with brain metastases.

OBJECTIVES: To construct and validate a model based on clinical characteristics and magnetic resonance imaging (MRI) radiomics to predict 1-year effic...

Radiomics-based unsupervised clustering and deep learning nomogram for response prediction after neoadjuvant chemotherapy in locally advanced laryngeal cancer.

OBJECTIVES: To develop a nomogram model for individualized prediction of neoadjuvant chemotherapy (NAC) response in locally advanced laryngeal cancer ...

Single-cell multi-omics dissection of RevitalAge Markers uncovers age-dependent immunotherapy resistance and druggable targets in melanoma.

Aging-related molecular reprogramming profoundly influences melanoma progression and therapeutic sensitivity, yet underlying mechanisms remain poorly ...

Integrative spatiotemporal transcriptomics identifies a liver metastasis-related initial cell population associated with the SEMA3A-NRP1 axis in pancreatic ductal adenocarcinoma.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy in which liver metastasis represents the principal determinant of po...

The potential utility of in-silico approach in identifying phytochemicals against various targets for the management of lung cancer.

Research on novel treatment approaches is crucial for lung cancer, because it is one of the most common and aggressive malignancies with high mortalit...

CORR Insights®: Development and Internal Evaluation of EAST-BMS (East Asian Survival Tool for Bone Metastasis Surgery): A Multinational Machine-learning Survival Prediction Model for Patients Undergoing Surgery for Nonspinal Bone Metastasis in East Asia.

Deep-Learning Solution Providing Molecular Marker Subtyping of Breast Cancer Whole Slide Images: Protocol for a UK Clinical Service Evaluation Study.

BACKGROUND: As the histopathology workforce continues to struggle and service demand continues to increase, it has become prudent to consider viable a...

Cellular architecture and neighborhood-informed virtual spatial tumor profiling from histopathology.

The tumor microenvironment (TME) critically shapes disease progression and therapeutic resistance. However, a comprehensive understanding of its spati...

A preoperative Artificial Intelligence model to estimate cancer-specific mortality in nonmetastatic kidney cancer patients.

Surgical resection is the standard treatment for nonmetastatic renal cell carcinoma, yet survival outcomes vary significantly among patients. Current ...

Early and late mortality among patients with T1-T3 head and neck squamous cell carcinoma: a machine learning analysis using a SEER population-based cohort study.

Despite advances in the management of head and neck squamous cell carcinoma (HNSCC), mortality within 6 months of diagnosis remains a substantial clin...

Construction of a diagnostic model for nasopharyngeal carcinoma using a consensus machine learning approach and study of immune infiltration characteristics.

BACKGROUND: Nasopharyngeal carcinoma requires reliable diagnostic biomarkers due to its occult location and poor outcomes. METHODS: This study analyze...

A 5mC-related gene signature predicts prognosis and therapy response in hepatocellular carcinoma.

Increasing evidence has highlighted the biological significance of 5-methylcytosine (5mC) DNA modification in regulating tumorigenesis and cancer prog...

Real-time identification of malignant breast tissue during electrosurgical resection.

Achieving complete resection of breast cancer with clear margins remains a significant surgical challenge, particularly for infiltrating subtypes, whe...

Transcriptomic profiling identifies immunotherapy-responsive phenotypes in microsatellite-stable metastatic colorectal cancer.

Conventional immune checkpoint inhibitors (ICIs) remain largely ineffective in microsatellite-stable metastatic colorectal cancer (MSS mCRC), where lo...

Integrating machine learning and retrospective cohort to explore the effects of AEDs on the prognosis of LGG and identify related molecular targets.

Antiepileptic drugs (AEDs) were frequently employed in glioma patients, especially those with low-grade glioma (LGG), in which epilepsy manifested in ...

Metabolic SERS Profiling under Triple-Coupled Hotspots Aided by Machine Learning for Precise Identification of Gastrointestinal Malignancies.

Serum metabolic analysis based on label-free SERS fingerprints represents a highly promising technique for the detection of tumors. However, the insuf...

Dissecting PCD-driven molecular landscapes in AML: a multi-omic framework for prognostication and therapeutic targeting.

Acute myeloid leukemia (AML) remains a molecularly heterogeneous malignancy with poor prognosis, necessitating robust biomarkers for risk stratificati...

Multi-omics analysis identifies GINS1 as a prognostic biomarker in lung adenocarcinoma, linked to macrophage polarization and tumor cell survival.

This study aimed to identify essential genes driving lung adenocarcinoma (LUAD) progression by integrating CRISPR-Cas9 dependency data from the Cancer...