Interpretable Multimodal Fusion Model for Bridged Histology and Genomics Survival Prediction in Pan-Cancer.

Understanding the prognosis of cancer patients is crucial for enabling precise diagnosis and treatment by clinical practitioners. Multimodal fusion models based on artificial intelligence (AI) offer a comprehensive depiction of the tumor heterogeneity landscape, facilitating more accurate predictions of cancer patient prognosis. However, in the real-world, the lack of complete multimodal data from patients often hinders the practical clinical utility of such models.

KRAS inhibitors may prevent colorectal cancer metachronous metastasis by suppressing TGF‑β mediated epithelial‑mesenchymal transition.

In colorectal cancer (CRC), KRAS mutations enhance metachronous metastasis, a condition without prognostic biomarkers or preventive measures. The present study demonstrated that KRAS mutation may be a risk factor for CRC metachronous metastasis through meta‑analysis of public databases. A risk scoring model was constructed using machine learning for predicting metachronous metastasis in KRAS‑mutant CRC.

Deciphering tertiary lymphoid structure heterogeneity reveals prognostic signature and therapeutic potentials for colorectal cancer: a multicenter retrospective cohort study.

Background: Tertiary lymphoid structures (TLSs) exert a crucial role in the tumor microenvironment (TME), impacting tumor development, immune escape, and drug resistance. Nonetheless, the heterogeneity of TLSs in colorectal cancer (CRC) and their impact on prognosis and treatment response remain unclear.

Methods: The authors collected genome, transcriptome, clinicopathological information, and digital pathology images from multiple sources.

Efficacy and Mechanism of a Biomimetic Nanosystem Carrying Doxorubicin and an IDO Inhibitor for Treatment of Advanced Triple-Negative Breast Cancer.

Introduction: Chemotherapy is still the treatment of choice for advanced triple-negative breast cancer. Chemotherapy combined with immunotherapy is being tried in patients with triple-negative breast cancer. As a kind of "cold tumor", triple-negative breast cancer has a bottleneck in immunotherapy.

Senescence-based colorectal cancer subtyping reveals distinct molecular characteristics and therapeutic strategies.

Cellular senescence has been listed as a hallmark of cancer, but its role in colorectal cancer (CRC) remains unclear. We comprehensively evaluated the transcriptome, genome, digital pathology, and clinical data from multiple datasets of CRC patients and proposed a novel senescence subtype for CRC. Multi-omics data was used to analyze the biological features, tumor microenvironment, and mutation landscape of senescence subtypes, as well as drug sensitivity and immunotherapy response.

An immune, stroma, and epithelial-mesenchymal transition-related signature for predicting recurrence and chemotherapy benefit in stage II-III colorectal cancer.

Background: Debates exist on the treatment decision of the stage II/III colorectal cancer (CRC) due to the insufficiency of the current TNM stage-based risk stratification system. Epithelial-mesenchymal transition (EMT) and tumor microenvironment (TME) have both been linked to CRC progression in recent studies. We propose to improve the prognosis prediction of CRC by integrating TME and EMT.

Deep learning based CT images automatic analysis model for active/non-active pulmonary tuberculosis differential diagnosis.

Active pulmonary tuberculosis (ATB), which is more infectious and has a higher mortality rate compared with non-active pulmonary tuberculosis (non-ATB), needs to be diagnosed accurately and timely to prevent the tuberculosis from spreading and causing deaths. However, traditional differential diagnosis methods of active pulmonary tuberculosis involve bacteriological testing, sputum culturing and radiological images reading, which is time consuming and labour intensive. Therefore, an artificial intelligence model for ATB differential diagnosis would offer great assistance in clinical practice.

Tumor Microenvironment Multiple Responsive Nanoparticles for Targeted Delivery of Doxorubicin and CpG Against Triple-Negative Breast Cancer.

Introduction: Currently, the main treatment for advanced breast cancer is still chemotherapy. Immunological and chemical combination therapy has a coordinated therapeutic effect and achieves some efficacy. However, the immunosuppressive tumor microenvironment is a major cause for the failure of immunotherapy in breast cancer.

Predicting prognosis and immunotherapy response among colorectal cancer patients based on a tumor immune microenvironment-related lncRNA signature.

Long non-coding RNAs (lncRNAs) remodel the tumor immune microenvironment (TIME) by regulating the functions of tumor-infiltrating immune cells. It remains uncertain the way that TIME-related lncRNAs (TRLs) influence the prognosis and immunotherapy response of colorectal cancer (CRC). Aiming at providing survival and immunotherapy response predictions, a CRC TIME-related lncRNA signature (TRLs signature) was developed and the related potential regulatory mechanisms were explored with a comprehensive analysis on gene expression profiles from 97 immune cell lines, 61 CRC cell lines and 1807 CRC patients.

Multi-Size Deep Learning Based Preoperative Computed Tomography Signature for Prognosis Prediction of Colorectal Cancer.

Preoperative and postoperative evaluation of colorectal cancer (CRC) patients is crucial for subsequent treatment guidance. Our study aims to provide a timely and rapid assessment of the prognosis of CRC patients with deep learning according to non-invasive preoperative computed tomography (CT) and explore the underlying biological explanations. A total of 808 CRC patients with preoperative CT (development cohort: = 426, validation cohort: = 382) were enrolled in our study.

DNA Repair-Related Gene Signature in Predicting Prognosis of Colorectal Cancer Patients.

Increasing evidence have depicted that DNA repair-related genes (DRGs) are associated with the prognosis of colorectal cancer (CRC) patients. Thus, the aim of this study was to evaluate the impact of DNA repair-related gene signature (DRGS) in predicting the prognosis of CRC patients. In this study, we retrospectively analyzed the gene expression profiles from six CRC cohorts.

Artificial Intelligence Assisting the Early Detection of Active Pulmonary Tuberculosis From Chest X-Rays: A Population-Based Study.

As a major infectious disease, (TB) still poses a threat to people's health in China. As a triage test for TB, reading chest radiography with traditional approach ends up with high inter-radiologist and intra-radiologist variability, moderate specificity and a waste of time and medical resources. Thus, this study established a deep convolutional neural network (DCNN) based artificial intelligence (AI) algorithm, aiming at diagnosing TB on posteroanterior chest X-ray photographs in an effective and accurate way.

Co-delivery of the autophagy inhibitor si-Beclin1 and the doxorubicin nano-delivery system for advanced prostate cancer treatment.

Resistance to apoptosis is a key mechanism underlying how cancer cells evade tumor therapy. Autophagy can prevent anticancer drug-induced apoptosis and promote tumor resistance. The purpose of this study was to improve the sensitivity and efficacy of chemotherapeutic drugs through the inhibition of autophagy.

Aptamer-conjugated multi-walled carbon nanotubes as a new targeted ultrasound contrast agent for the diagnosis of prostate cancer.

Early diagnosis is primarily important for the therapeutic and prognostic outcomes of malignancies including prostate cancer (PCa). However, the visuality and veracity of ultrasound imaging for the diagnosis and prognostic prediction of PCa remains poor at present. In this study, we developed a new nanoultrasound contrast agent by modifying multi-walled carbon nanotubes (MWCNTs) with polyethylene glycol (PEG) and anti-PSMA aptamer.

Codelivery of miR-4638-5p and Docetaxel Based on Redox-Sensitive Polypeptide Micelles as an Improved Strategy for the Treatment of Castration-Resistant Prostate Cancer.

In this work, we have developed a reducible, self-assembling disulfide cross-linked and peptide-based micelle system for codelivery of miR-4638-5p and DTX to improve the efficacy of castration-resistant prostate cancer (CRPC) therapy. The result showed that DTX in micelles (DTX-VPs) inhibited cell growth and induced apoptosis more effectively than free DTX both in vitro and in vivo. In addition, the DTX and miR-4638-5p loaded micelles (Co-VPs) achieved the most pronounced anticancer effect of all groups.

Functionalized Multi-Walled Carbon Nanotubes for Targeting Delivery of Immunostimulatory CpG Oligonucleotides Against Prostate Cancer.

Immuno-based oncotherapy has been successfully implemented for cancer treatment. In the present study, we developed a Oligodeoxynucleotides (ODNs) containing unmethylated CpG motifs (CpG ODNs) nano-delivery system based on Multi-walled carbon nanotubes (MWCNTs) conjugated with H3R6 polypeptide (MHR-CpG) for prostate cancer immunotherapy. The in vitro and in vivo toxicity data revealed that the prepared MHR showed high biocompatibility.

A33 antibody-functionalized exosomes for targeted delivery of doxorubicin against colorectal cancer.

Exosomes have emerged as a promising drug carrier with low immunogenicity, high biocompatibility and delivery efficiency. Here in, we isolated exosomes from A33-positive LIM1215 cells (A33-Exo) and loaded them with doxorubicin (Dox). Furthermore, we coated surface-carboxyl superparamagnetic iron oxide nanoparticles (US) with A33 antibodies (A33Ab-US), expecting that these A33 antibodies on the surface of the nanoparticles could bind to A33-positive exosomes and form a complex (A33Ab-US-Exo/Dox) to target A33-positive colon cancer cells.

Co-delivery of autophagy inhibitor ATG7 siRNA and docetaxel for breast cancer treatment.

The lysosomal degradation pathway of autophagy has a crucial role in protecting cancer cells from multiple endogenous and exogenous stresses, particularly during the pathogenesis of cancer. Accordingly, agents that inhibit autophagy may have broad therapeutic applications. We have developed a novel strategy based on co-delivery of an autophagy related 7 (ATG7) siRNA and docetaxel (DTX) in a crosslinked, reducible, peptide-based micellar system for breast cancer treatment.

Tumour microenvironment-responsive lipoic acid nanoparticles for targeted delivery of docetaxel to lung cancer.

In the present study, we developed a novel type of reduction-sensitive nanoparticles (NPs) for docetaxel (DTX) delivery based on cross-linked lipoic acid NPs (LANPs). The physicochemical properties, cellular uptake and in vitro cytotoxicity of DTX loaded LANPs (DTX-LANPs) on A549 cells were investigated. Furthermore, the in vivo distribution and in vivo efficacy of DTX-LANPs was evaluated.

Synergistic effect of reduced polypeptide micelle for co-delivery of doxorubicin and TRAIL against drug-resistance in breast cancer.

Cationic peptides as a non-viral gene vector have become a hotspot of research because of their high transfection efficcacy and safety. Based on our previous study, we synthesized a cationic reduction-responsive vector based on disulfide cross-linked L-arginine, L-histidine and lipoic acid (LHRss) as the co-carrier of both doxorubicin (DOX) and the necrosis factor-related apoptosis-inducing ligand (pTRAIL). The LHRss/DOX/TRAIL construct has reduction-sensitive behavior and an enhanced endosomal escape ability to increase the cytotoxicity of DOX and the transfection efficiency.

Aptamer-mediated delivery of docetaxel to prostate cancer through polymeric nanoparticles for enhancement of antitumor efficacy.

Treatment of aggressive prostate cancer remains a great challenge due to inadequate drug distribution into the cancerous lesions after administration. This study aimed to develop aptamer-anchored nanoparticles (apt-NPs) for systemic delivery of docetaxel (DTX) and to evaluate the tumoricidal activity against the prostate cancer in vitro and in vivo. DTX-loaded apt-NPs (DTX-apt-NPs) were prepared by a solvent diffusion technique using functional PLGA-b-PEG and sodium oleate.

Reducible self-assembling cationic polypeptide-based micelles mediate co-delivery of doxorubicin and microRNA-34a for androgen-independent prostate cancer therapy.

The co-delivery of chemotherapeutic drugs and microRNAs (miR) represents a promising strategy for tumor therapy due to the synergistic effect achieved. In the present study, hydrophobic doxorubicin (DOX) and negatively charged miR-34a were simultaneously delivered via a reducible self-assembling disulfide cross-linked stearyl-peptide-based micellar system (SHRss) using poly(l-arginine)-poly(l-histidine)-stearoyl as the copolymer building unit. The nanoscale SHRss micelles exhibited a low critical micelle concentration (CMC) with positive surface charge.