Drug Resistance via Feedback Activation of Stat3 in Oncogene-Addicted Cancer Cells

SummaryPathway-targeted cancer drugs can produce dramatic responses that are invariably limited by the emergence of drug-resistant cells. We found that many drug-treated “oncogene-addicted” cancer cells engage a positive feedback loop leading to Stat3 activation, consequently promoting cell survival and limiting overall drug response. This was observed in cancer cells driven by diverse activated kinases, including EGFR, HER2, ALK, and MET, as well as mutant KRAS. Specifically, MEK inhibition led to autocrine activation of Stat3 via the FGF receptor and JAK kinases, and pharmacological inhibition of MEK together with JAK and FGFR enhanced tumor regression. These findings suggest that inhibition of a Stat3 feedback loop may augment the response to a broad spectrum of drugs that target pathways of oncogene addiction

Decreased DBC1 Expression Is Associated With Poor Prognosis in Patients With Non-Muscle-Invasive Bladder Cancer

Purpose The deleted in bladder cancer 1 (DBC1) gene is located within chromosome 9 (9q32-33), a chromosomal region that frequently shows loss of heterozygosity in bladder cancer (BC). It is suspected that it acts as a tumor suppressor gene, but its prognostic value remains unclear. The aim of the present study was to investigate the value of DBC1 as a prognostic marker in BC. Materials and Methods The expression of DBC1 was determined by real-time polymerase chain reaction analysis in 344 patients with BC (220 non-muscle-invasive BC [NMIBC] and 124 muscle-invasive BC [MIBC]) and in 34 patients with normal bladder mucosa. The results were compared with clinicopathologic parameters, and the prognostic value of DBC1 was evaluated by Kaplan-Meier analysis and a multivariate Cox regression model. Results: DBC1 expression was significantly decreased in patients with MIBC compared with those diagnosed with NMIBC (p=0.010). Patients with aggressive tumor characteristics had lower DBC1 expression levels in NMIBC (each, p<0.05). By multivariate Cox regression analysis, low DBC1 expression was a predictor of progression to MIBC (hazard ratio, 7.104; p=0.013). Kaplan-Meier estimates revealed a significant difference in tumor recurrence, progression to MIBC, and cancer-specific survival depending on the level of DBC1 expression in NMIBC (log-rank test, each, p<0.05). Conclusions: The expression of DBC1 was associated with tumor aggressiveness, progression to MIBC, and survival in NMIBC. Our results suggest that DBC1 expression can be a useful prognostic marker for patients with NMIBC

Single-cell transcriptome of bronchoalveolar lavage fluid reveals sequential change of macrophages during SARS-CoV-2 infection in ferrets

Few studies have used a longitudinal approach to describe the immune response to SARS-CoV-2 infection. Here, we perform single-cell RNA sequencing of bronchoalveolar lavage fluid cells longitudinally obtained from SARS-CoV-2-infected ferrets. Landscape analysis of the lung immune microenvironment shows distinct changes in cell proportions and characteristics compared to uninfected control, at 2 and 5 days post-infection (dpi). Macrophages are classified into 10 distinct subpopulations with transcriptome changes among monocyte-derived infiltrating macrophages and differentiated M1/M2 macrophages, notably at 2 dpi. Moreover, trajectory analysis reveals gene expression changes from monocyte-derived infiltrating macrophages toward M1 or M2 macrophages and identifies a macrophage subpopulation that has rapidly undergone SARS-CoV-2-mediated activation of inflammatory responses. Finally, we find that M1 or M2 macrophages show distinct patterns of gene modules downregulated by immune-modulatory drugs. Overall, these results elucidate fundamental aspects of the immune response dynamics provoked by SARS-CoV-2 infection. A longitudinal analysis of SARS-CoV-2 infection in humans is challenging. Here the authors show a single cell RNA-sequencing analysis of BAL fluid cells from ferrets and characterise the time dependent recruitment of macrophage subsets to the lungs in response to SARS-CoV-2 infection

Valproic Acid Induces Hair Regeneration in Murine Model and Activates Alkaline Phosphatase Activity in Human Dermal Papilla Cells

Alopecia is the common hair loss problem that can affect many people. However, current therapies for treatment of alopecia are limited by low efficacy and potentially undesirable side effects. We have identified a new function for valproic acid (VPA), a GSK3β inhibitor that activates the Wnt/β-catenin pathway, to promote hair re-growth in vitro and in vivo.Topical application of VPA to male C3H mice critically stimulated hair re-growth and induced terminally differentiated epidermal markers such as filaggrin and loricrin, and the dermal papilla marker alkaline phosphatase (ALP). VPA induced ALP in human dermal papilla cells by up-regulating the Wnt/β-catenin pathway, whereas minoxidil (MNX), a drug commonly used to treat alopecia, did not significantly affect the Wnt/β-catenin pathway. VPA analogs and other GSK3β inhibitors that activate the Wnt/β-catenin pathway such as 4-phenyl butyric acid, LiCl, and BeCl(2) also exhibited hair growth-promoting activities in vivo. Importantly, VPA, but not MNX, successfully stimulate hair growth in the wounds of C3H mice.Our findings indicate that small molecules that activate the Wnt/β-catenin pathway, such as VPA, can potentially be developed as drugs to stimulate hair re-growth

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data