Spatial Proximity of Immune Cell Pairs to Cancer Cells in the Tumor Microenvironment as Biomarkers for Patient Stratification.

Background/objectives: The tumor microenvironment (TME) plays a critical role in cancer progression by shaping immune responses and influencing patient outcomes. We hypothesized that the relative proximity of specific immune cell pairs to cancer cells within the TME could help predict their pro- or anti-tumor functions and reflect clinically relevant immune dynamics.

Methods: We analyzed imaging mass cytometry (IMC) data from lung adenocarcinoma (LUAD) and triple-negative breast cancer (TNBC) cohorts.

Lineage Tracing and Single-Cell RNA Sequencing Reveal a Common Transcriptional State in Breast Cancer Tumor-Initiating Cells Characterized by IFN/STAT1 Activity.

A tumor cell subpopulation of tumor-initiating cells (TIC) or "cancer stem cells" is associated with therapeutic resistance, as well as both local and distant recurrences. Signal transducer and activator of transcription (STAT) activity is elevated in TICs in claudin-low models of human triple-negative breast cancer, which enables enrichment of TICs using a STAT-responsive reporter. Lineage tracing of TICs as they undergo cell state changes could enable a better understanding of the molecular phenotypes of TIC and uncover strategies to selectively target TICs.

Influence of Endogenous Derivatives on the Chemical Sensing Performance of Carbonized Polymer Dots.

Endogenous derivatives, inevitably introduced during carbonized polymer dots (CPDs) synthesis, are considered to significantly influence their sensing performance. In this study, comparative studies on CPDs prepared via hydrothermal methods (CPDs-HO) and airflow-assisted melt polymerization (CPDs-AMP) reveal that CPDs-HO, containing abundant derivatives, exhibit superior stability and robustness in Fe sensing in both solution and cells compared to derivative-deficient CPDs-AMP. Mechanistic investigations highlight the crucial role of endogenous derivatives in enhancing the intrinsic stability of CPDs polymer frameworks, challenging conventional perceptions and providing valuable insights for designing robust CPDs-based sensors for practical applications.

The interferon/STAT1 signaling axis is a common feature of tumor-initiating cells in breast cancer.

Unlabelled: A tumor cell subpopulation of tumor-initiating cells (TIC), or "cancer stem cells", are associated with therapeutic resistance, as well as both local and distant recurrence. Enriched populations of TIC are identified by markers including aldehyde dehydrogenase (ALDH1) activity, the cell surface marker combination CD44 /CD24 , or fluorescent reporters for signaling pathways that regulate TIC function. We showed previously that S ignal T ransducer and A ctivator of T ranscription (STAT)-mediated transcription allows enrichment for TIC in claudin-low models of human triple-negative breast cancer using a STAT-responsive reporter.

The Development of Immunotherapy for the Treatment of Recurrent Glioblastoma.

Recurrent glioblastoma (rGBM) is a highly aggressive form of brain cancer that poses a significant challenge for treatment in neuro-oncology, and the survival status of patients after relapse usually means rapid deterioration, thus becoming the leading cause of death among patients. In recent years, immunotherapy has emerged as a promising strategy for the treatment of recurrent glioblastoma by stimulating the body's immune system to recognize and attack cancer cells, which could be used in combination with other treatments such as surgery, radiation, and chemotherapy to improve outcomes for patients with recurrent glioblastoma. This therapy combines several key methods such as the use of monoclonal antibodies, chimeric antigen receptor T cell (CAR-T) therapy, checkpoint inhibitors, oncolytic viral therapy cancer vaccines, and combination strategies.

Spatial imaging of glycoRNA in single cells with ARPLA.

Little is known about the biological roles of glycosylated RNAs (glycoRNAs), a recently discovered class of glycosylated molecules, because of a lack of visualization methods. We report sialic acid aptamer and RNA in situ hybridization-mediated proximity ligation assay (ARPLA) to visualize glycoRNAs in single cells with high sensitivity and selectivity. The signal output of ARPLA occurs only when dual recognition of a glycan and an RNA triggers in situ ligation, followed by rolling circle amplification of a complementary DNA, which generates a fluorescent signal by binding fluorophore-labeled oligonucleotides.

Alternative splicing of modulates killer lymphocyte-triggered pyroptosis.

Granzyme A from killer lymphocytes cleaves gasdermin B (GSDMB) and triggers pyroptosis in targeted human tumor cells, eliciting antitumor immunity. However, GSDMB has a controversial role in pyroptosis and has been linked to both anti- and protumor functions. Here, we found that splicing variants are functionally distinct.

AD-Syn-Net: systematic identification of Alzheimer's disease-associated mutation and co-mutation vulnerabilities via deep learning.

Alzheimer's disease (AD) is one of the most challenging neurodegenerative diseases because of its complicated and progressive mechanisms, and multiple risk factors. Increasing research evidence demonstrates that genetics may be a key factor responsible for the occurrence of the disease. Although previous reports identified quite a few AD-associated genes, they were mostly limited owing to patient sample size and selection bias.

Circulating metabolites associated with tumor hypoxia and early response to treatment in bevacizumab-refractory glioblastoma after combined bevacizumab and evofosfamide.

Glioblastomas (GBM) are the most common and aggressive form of primary malignant brain tumor in the adult population, and, despite modern therapies, patients often develop recurrent disease, and the disease remains incurable with median survival below 2 years. Resistance to bevacizumab is driven by hypoxia in the tumor and evofosfamide is a hypoxia-activated prodrug, which we tested in a phase 2, dual center (University of Texas Health Science Center in San Antonio and Dana Farber Cancer Institute) clinical trial after bevacizumab failure. Tumor hypoxic volume was quantified by 18F-misonidazole PET.

i-Modern: Integrated multi-omics network model identifies potential therapeutic targets in glioma by deep learning with interpretability.

Effective and precise classification of glioma patients for their disease risks is critical to improving early diagnosis and patient survival. In the recent past, a significant amount of multi-omics data derived from cancer patients has emerged. However, a robust framework for integrating multi-omics data types to efficiently and precisely subgroup glioma patients and predict survival prognosis is still lacking.

Multi-omics to characterize the functional relationships of R-loops with epigenetic modifications, RNAPII transcription and gene expression.

Abnormal accumulation of R-loops results in replication stress, genome instability, chromatin alterations and gene silencing. Little research has been done to characterize functional relationships among R-loops, histone marks, RNA polymerase II (RNAPII) transcription and gene regulation. We built extremely randomized trees (ETs) models to predict the genome-wide R-loops using RNAPII and multiple histone modifications chromatin immunoprecipitation (ChIP)-seq, DNase-seq, Global Run-On sequencing (GRO-seq) and R-loop profiling data.

Vitexin ameliorates glycochenodeoxycholate-induced hepatocyte injury through SIRT6 and JAK2/STAT3 pathways.

Objectives: Vitexin, a natural flavonoid, is commonly found in many foods and traditional herbal medicines and has clear health benefits. However, the role of vitexin in cholestasis is presently unclear. This study investigated whether vitexin mitigated glycochenodeoxycholate (GCDC)-induced hepatocyte injury and further elucidated the underlying mechanisms.

D-GPM: A Deep Learning Method for Gene Promoter Methylation Inference.

Whole-genome bisulfite sequencing generates a comprehensive profiling of the gene methylation levels, but is limited by a high cost. Recent studies have partitioned the genes into landmark genes and target genes and suggested that the landmark gene expression levels capture adequate information to reconstruct the target gene expression levels. This inspired us to propose that the methylation level of the promoters in landmark genes might be adequate to reconstruct the promoter methylation level of target genes, which would eventually reduce the cost of promoter methylation profiling.

DNA Methylation Markers for Pan-Cancer Prediction by Deep Learning.

For cancer diagnosis, many DNA methylation markers have been identified. However, few studies have tried to identify DNA methylation markers to diagnose diverse cancer types simultaneously, i.e.