Primer extension based quantitative polymerase chain reaction reveals consistent differences in the methylation status of the MGMT promoter in diffusely infiltrating gliomas (WHO grade II-IV) of adults

Diffusely infiltrating gliomas (WHO grade II-IV) are the most common primary brain tumours in adults. These tumours are not amenable to cure by surgery alone, so suitable biomarkers for adjuvant modalities are required to guide therapeutic decision-making. Epigenetic silencing of the O6-methylguanine-DNA methyltransferase (MGMT) gene by promoter methylation has been associated with longer survival of patients with high-grade gliomas who receive alkylating chemotherapy; and molecular testing for the methylation status of the MGMT promoter sequence is regarded as among the most relevant of such markers. We have developed a primer extension-based assay adapted to formalin-fixed paraffin-embedded tissues that enables quantitative assessment of the methylation status of the MGMT promoter. The assay is very sensitive, highly reproducible, and provides valid test results in nearly 100% of cases. Our results indicate that oligodendrogliomas, empirically known to have a relatively favourable prognosis, are also the most homogeneous entities in terms of MGMT promoter methylation. Conversely, astrocytomas, which are more prone to spontaneous progression to higher grade malignancy, are significantly more heterogeneous. In addition, we show that the degree of promoter methylation correlates with the prevalence of loss of heterozygosity on chromosome arm 1p in the oligodendroglioma group, but not the astrocytoma group. Our results may have potentially important implications for clinical molecular diagnosi

A Smart Parallel Gripper Industrial Automation System for Measurement of Gripped Work Piece Thickness

As part of the advanced programmable logic controllers (PLC) course at Michigan Tech, this class project is performed on a mechatronics system gifted by Donald Engineering, a Michigan-based supplier of industrial automation systems and components. This paper explores the functionality and ladder programming of the smart parallel gripper system to measure the width of components grasped with the gripper. In addition, details of the system’s components, operation, more advanced uses are discussed. On the automation line, this smart gripper can be used to measure the thickness of work pieces while handling them and classifying these as either acceptable, too large or too small. In addition, the pneumatic power supply and safety measures are discussed, along with the human machine interface (HMI)

Synergistic effects of FGFR1 and PLK1 inhibitors target a metabolic liability in KRAS-mutant cancer.

KRAS oncoprotein is commonly mutated in human cancer, but effective therapies specifically targeting KRAS-driven tumors remain elusive. Here, we show that combined treatment with fibroblast growth factor receptor 1 (FGFR1) and polo-like kinase 1 (PLK1) inhibitors evoke synergistic cytotoxicity in KRAS-mutant tumor models in vitro and in vivo. Pharmacological and genetic suppression of FGFR1 and PLK1 synergizes to enhance anti-proliferative effects and cell death in KRAS-mutant lung and pancreatic but not colon nor KRAS wild-type cancer cells. Mechanistically, co-targeting FGFR1 and PLK1 upregulates reactive oxygen species (ROS), leading to oxidative stress-activated c-Jun N-terminal kinase (JNK)/p38 pathway and E2F1-induced apoptosis. We further delineate that autophagy protects from PLK1/FGFR1 inhibitor cytotoxicity and that antagonizing the compensation mechanism by clinically approved chloroquine fully realizes the therapeutic potential of PLK1 and FGFR1 targeting therapy, producing potent and durable responses in KRAS-mutant patient-derived xenografts and a genetically engineered mouse model of Kras-induced lung adenocarcinoma. These results suggest a previously unappreciated role for FGFR1 and PLK1 in the surveillance of metabolic stress and demonstrate a synergistic drug combination for treating KRAS-mutant cancer

Success and failure rates of tumor genotyping techniques in routine pathological samples with non-small-cell lung cancer

Introduction—Identification of some somatic molecular alterations in non-small-cell lung cancer (NSCLC) has become evidence-based practice. The success and failure rate of using commercially-available tumor genotyping techniques in routine day-to-day NSCLC pathology samples is not well described. We sought to evaluate the success and failure rate of EGFR mutation, KRAS mutation, and ALK FISH in a cohort of lung cancers subjected to routine clinical tumor genotype. Methods—Clinicopathologic data, tumor genotype success and failure rates were retrospectively compiled and analyzed from 381 patient-tumor samples. Results—From these 381 patients with lung cancer, the mean age was 65 years, 61.2% were women, 75.9% were white, 27.8% were never smokers, 73.8% had advanced NSCLC and 86.1% had adenocarcinoma histology. The tumor tissue was obtained from surgical specimens in 48.8%, core needle biopsies in 17.9%, and as cell blocks from aspirates or fluid in 33.3% of cases. Anatomic sites for tissue collection included lung (49.3%), lymph nodes (22.3%), pleura (11.8%), bone (6.0%), brain (6.0%), among others. The overall success rate for EGFR mutation analysis was 94.2%, for KRAS mutation 91.6% and for ALK FISH 91.6%. The highest failure rates were observed when the tissue was obtained from image-guided percutaneous transthoracic core-needle biopsies (31.8%, 27.3%, and 35.3% for EGFR, KRAS, and ALK tests, respectively) and bone specimens (23.1%, 15.4%, and 23.1%, respectively). In specimens obtained from bone, the failure rates were significantly higher for biopsies than resection specimens (40% vs 0%, p=0.024 for EGFR) and for decalcified compared to non-decalcified samples (60% vs 5.5%, p=0.021 for EGFR). Conclusions—Tumor genotype techniques are feasible in most samples, outside small imageguided percutaneous transthoracic core-needle biopsies and bone samples from core biopsies with decalcification, and therefore expansion of routine tumor genotype into the care of patients with NSCLC may not require special tissue acquisition or manipulation

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

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