Long non-coding RNAs (lncRs), by virtue of their versatility and multilevel gene regulation, have emerged as attractive pharmacological targets for treating heterogenous and complex malignancies like triple-negative breast cancer (TNBC). Despite multiple studies on lncRNA functions in tumor pathology, systemic targeting of these "undruggable" macromolecules with conventional approaches remains a challenge. Here, we demonstrate effective TNBC therapy by nanoparticlemediated RNAi of the oncogenic lncRNA DANCR, which is significantly overexpressed in TNBC. Tumor-targeting RGD-PEG-ECO/siDANCR nanoparticles were formulated via selfassembly of multifunctional amino lipid ECO, cyclic RGD peptide-PEG, and siDANCR for systemic delivery. MDA-MB-231 and BT549 cells treated with the therapeutic RGD-PEG-ECO/ siDANCR nanoparticles exhibited 80-90% knockdown in the expression of DANCR for up to 7 days, indicating efficient intracellular siRNA delivery and sustained target silencing. The RGD-PEG-ECO/siDANCR nanoparticles mediated excellent in vitro therapeutic efficacy, reflected by the significant reduction in the invasion, migration, survival, tumor spheroid formation, and proliferation of the TNBC cell lines. At the molecular level, functional ablation of DANCR

We identified specific genetic and mutation features of HCCs associated with aflatoxin exposure, including mutations in ADGRB1, compared to HCCs from general populations. We associated these mutations with increased vascularization and expression of PD-L1 in HCC tissues. These findings might be used to identify patients with HCC due to aflatoxin exposure, and select therapies.

Single cell RNA sequencing (scRNA-seq) methods can profile the transcriptomes of single cells but cannot preserve spatial information. Conversely, spatial transcriptomics (ST) assays can profile spatial regions in tissue sections, but do not have single cell genomic resolution. Here, we developed a computational approach called CellTrek that combines these two datasets to achieve single cell spatial mapping. We benchmarked CellTrek using a simulation study and two in situ datasets. We then applied CellTrek to reconstruct cellular spatial structures in existing datasets from normal mouse brain and kidney tissues. We also performed scRNA-seq and ST experiments on two ductal carcinoma in situ (DCIS) tissues and applied CellTrek to identify tumor subclones that were restricted to different ducts, and specific T cell states adjacent to the tumor areas. Our data shows that CellTrek can accurately map single cells in diverse tissue types to resolve their spatial organization.

Cancer stem cells (CSCs) are characterized by self‐renewal and ‐differential potential as compared to common cancer cells and play an important role in the development and therapeutic resistance of liver hepatocellular carcinoma (LIHC). However, the specific pathogenesis of LIHC stem cells is still unclear, and the genes involved in the stemness of LIHC stem cells are currently unknown. In this study, we investigated novel biomarkers associated with LIHC and explored the expression characteristics of stem cell‐related genes in LIHC. We found that mRNA expression‐based stemness index (mRNAsi) was significantly overexpressed in liver cancer tissues. Further, mRNAsi expression in LIHC increased with the tumor pathological grade, with grade 4 tumors harboring the greatest stem cell features. Upon establishing mRNAsi scores based on mRNA expression of every gene, we found an association with poor overall survival in LIHC. Moreover, modules of interest were determined based on weighted gene co‐expression network analysis (WGCNA) inclusion criteria, and three significant modules (red, green, and brown) and 21 key genes (DCN, ECM1, HAND2, PTGIS, SFRP1, SRPX, COLEC10, GRP182, ADAMTS7, CD200, CDH11, COL8A1, FAP, LZTS1, MAP1B, NAV1, NOTCH3, OLFML2A, PRR16, TMEM119, and VCAN) were identified. Functional analysis of these 21 genes demonstrated their enrichment in pathways involved in angiogenesis, negative regulation of DNA‐binding transcription factor activity, apoptosis, and autophagy. Causal relationship with proteins indicated that the Wnt, Notch, and Hypoxia pathways are closely related to LIHC tumorigenesis. To our knowledge, this is the first report of a novel CSC biomarker, mRNAsi, to predict the prognosis of LIHC. Further, we identified 21 key genes through mRNA expression network analysis, which could be potential therapeutic targets to inhibit the stemness of cancer cells in LIHC.

Multiple sclerosis (MS) is a chronic inflammatory demyelinating disorder of the central nervous system characterized by episodic and progressive neurologic dysfunction resulting from inflammatory and autoimmune reactions. The underlying pathogenesis of MS remains largely unclear. However, it is currently accepted as a T cell-mediated autoimmune disease. Among other clinical manifestations, sexual dysfunction (SD) is a painful but still underreported and underdiagnosed symptom of the disorder. SD in MS patients may result from a complex set of conditions and may be associated with multiple anatomic, physiologic, biologic, medical and psychological factors. SD arises primarily from lesions affecting the neural pathways involved in physiologic function. In addition, psychological factors, the side effects of medications and physical symptoms such as fatigue, muscular weakness, menstrual changes, pain and concerns about bladder and bowel incontinence may also be involved. Since MS primarily affects young people, SD secondary to MS may have a great impact on quality of life. Thus, maintaining a healthy sexual life with MS is an important priority. The treatment of SD requires multidisciplinary teamwork and cooperation among specialists, individual patients, partners and the society.

ObjectivePrognosis of patients with advanced oesophagogastric adenocarcinoma (mEGAC) is poor and molecular determinants of shorter or longer overall survivors are lacking. Our objective was to identify molecular features and develop a prognostic model by profiling the genomic features of patients with mEGAC with widely varying outcomes.DesignWe profiled 40 untreated mEGACs (20 shorter survivors <13 months and 20 longer survivors >36 months) with whole-exome sequencing (WES) and RNA sequencing and performed an integrated analysis of exome, transcriptome, immune profile and pathological phenotypes to identify the molecular determinants, developing an integrated model for prognosis and comparison with The Cancer Genome Atlas (TCGA) cohorts.ResultsKMT2C alterations were exclusively observed in shorter survivors together with high level of intratumour heterogeneity and complex clonal architectures, whereas the APOBEC mutational signatures were significantly enriched in longer survivors. Notably, the loss of heterozygosity in chromosome 4 (Chr4) was associated with shorter survival and ‘cold’ immune phenotype characterised by decreased B, CD8, natural killer cells and interferon-gamma responses. Unsupervised transcriptomic clustering revealed a shorter survivor subtype with distinct expression features (eg, upregulated druggable targets JAK2, MAP3K13 and MECOM). An integrated model was then built based on clinical variables and the identified molecular determinants, which significantly segregated shorter and longer survivors. All the above features and the integrated model have been validated independently in multiple TCGA cohorts.ConclusionThis study discovered novel molecular features prognosticating overall survival in patients with mEGAC and identified potential novel targets in shorter survivors.

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