Skin Cancer

Gut dysbiosis in oncology: a risk factor for immunoresistance.

The gut microbiome is recognized as a determinant of response to immune checkpoint inhibitor (ICI) therapies in cancer. However, the clinical translation of microbiome science has been hampered by inconsistent definitions of dysbiosis, inadequate biomarker frameworks, and limited mechanistic understanding. In this review, we synthesize the current state of knowledge on how gut microbial compositio...

A combinatorial transcription factor screening platform for immune cell reprogramming.

Direct reprogramming of immune cells holds promise for immunotherapy but is constrained by limited knowledge of transcription factor (TF) networks. Here, we developed REPROcode, a combinatorial single-cell screening platform to identify TF combinations for immune cell reprogramming. We first validated REPROcode by inducing type-1 conventional dendritic cells (cDC1s) with multiplexed sets of 9, 22,...

Cutting-Edge AI Technologies in Skin Cancer Applications.

The rapid development of multimodal large language models (LLMs) such as GPT and Med-PaLM is reshaping medical practice. Skin cancer, one of the most ...

Programmable Smart CAR-T design: A new paradigm in precision immunotherapy driven by logic gates, conditional activation, allogeneic strategies, and artificial intelligence.

Chimeric antigen receptor T-cell (CAR-T) therapy has achieved unprecedented success in hematological malignancies but faces formidable challenges in s...

Utilizing artificial intelligence for the diagnosis of ocular surface squamous neoplasia with ultrasound biomicroscopy images.

PURPOSE: This study aims to develop an artificial intelligence (AI) model to assist ophthalmologists in distinguishing ocular surface squamous neoplas...

Programmable lipid nanoparticles for RNA therapeutics: Design principles and clinical translation.

RNA therapeutics have come of age as clinically validated modalities including mRNA, siRNA, antisense oligonucleotides (ASOs), and in vivo genome edit...

Advances in melanoma immunotherapy: harnessing vaccination as a potential novel immunotherapeutic strategy.

Melanoma, an aggressive form of skin cancer, demands innovative immunotherapeutic strategies to improve patient outcomes. This review explores recent ...

Unraveling stress-adaptation pathways in cancer: Functional dissection through CRISPR-based genetic screens.

Cancer cells face a hostile microenvironment characterized by hypoxia, nutrient deprivation, endoplasmic reticulum (ER) stress, and oxidative imbalanc...

Integration of histopathological characteristics by machine learning improves the prediction of neoadjuvant immunochemotherapy response in triple-negative breast cancer.

Neoadjuvant immunochemotherapy (NAIC) is a standard treatment for triple-negative breast cancer (TNBC), but there is no reliable biomarker to identify...

Automated CT-derived body composition predicts pathologic response to neoadjuvant immunotherapy in non-small cell lung cancer.

Tumor-intrinsic biomarkers alone insufficiently predict pathological complete response (pCR) to neoadjuvant immunochemotherapy (NICT) in non-small cel...

[Chronic skin damage from UV radiation].

Ultraviolet (UV) radiation is the primary risk factor for the development of both melanocytic and nonmelanocytic skin cancer. In particular, UVA and U...

Single‑cell mapping of neutrophil extracellular trap signatures in lung adenocarcinoma reveals immune landscapes, prognostic potential, and therapeutic targets.

Neutrophil extracellular traps (NETs) have emerged as key modulators in the tumor microenvironment, yet their cellular heterogeneity, molecular mechan...

Identifying transcriptional signatures of leukocytes in tissue and blood for multicancer diagnosis by using machine learning methods.

Investigating the transcriptional signatures of immune cells in various cancer types is crucial for understanding their roles in the tumor microenviro...

Metabolic-immune interactions in gastric cancer T cells: A single-cell atlas for prognostic biomarker identification.

Metabolic alterations and immune dysfunction within the gastric tumor microenvironment critically drive gastric cancer (GC) progression and therapeuti...

Artificial Intelligence Applications in the Diagnosis, Treatment, and Prognosis of Hepatocellular Carcinoma.

The global burden of hepatocellular carcinoma (HCC) has shifted from viral to nonviral etiologies. However, successful antiviral therapy does not full...

AI Clinical Decision Tools in Multidisciplinary Team Discussions for Colorectal Cancer.

Multidisciplinary team (MDT) discussions have become a cornerstone of colorectal cancer (CRC) management, integrating the expertise of surgeons, oncol...

Machine learning-assisted prognosis of multiple myeloma side population cells via SRGs and OCLR stemness index.

BACKGROUND AND OBJECTIVE: Relapse in Multiple Myeloma, driven by therapy-resistant cancer stem cells, necessitates the development of more specific an...

Decoding Senescence-Driven Heterogeneity in Early-Onset Colorectal Cancer for Prognostic and Therapeutic Stratification.

Early-onset colorectal cancer (EOCRC), diagnosed in patients under 50, is particularly aggressive, yet lacks targeted therapeutic strategies. This stu...

Post-Translational Modification Mediated By Acylation Modification Related Genes Induces Immunosuppression and Immunotherapy Resistance in Head and Neck Squamous Cell Carcinoma.

Acylation modification plays a crucial role in modulating head and neck squamous cell carcinoma (HNSCC) progression, and their specific prognostic imp...

A multicenter multimodel habitat radiomics model for predicting immunotherapy response in advanced NSCLC.

A robust predictive biomarker is critical for identifying patients with NSCLC who may benefit from immunotherapy. This study developed a CT-based habi...