Epigenetic modifications in KDM lysine demethylases associate with survival of early-stage NSCLC

BACKGROUND: KDM lysine demethylase family members are related to lung cancer clinical outcomes and are potential biomarkers for chemotherapeutics. However, little is known about epigenetic alterations in KDM genes and their roles in lung cancer survival. METHODS: Tumor tissue samples of 1230 early-stage non-small cell lung cancer (NSCLC) patients were collected from the five independent cohorts. The 393 methylation sites in KDM genes were extracted from epigenome-wide datasets and analyzed by weighted random forest (Ranger) in discovery phase and validation dataset, respectively. The variable importance scores (VIS) for the sites in top 5% of both discovery and validation sets were carried forward for Cox regression to further evaluate the association with patient's overall survival. TCGA transcriptomic data were used to evaluate the correlation with the corresponding DNA methylation. RESULTS: DNA methylation at sites cg11637544 in KDM2A and cg26662347 in KDM1A were in the top 5% of VIS in both discovery phase and validation for squamous cell carcinomas (SCC), which were also significantly associated with SCC survival (HRcg11637544 = 1.32, 95%CI, 1.16-1.50, P = 1.1 × 10-4; HRcg26662347 = 1.88, 95%CI, 1.37-2.60, P = 3.7 × 10-3), and correlated with corresponding gene expression (cg11637544 for KDM2A, P = 1.3 × 10-10; cg26662347 for KDM1A P = 1.5 × 10-5). In addition, by using flexible criteria for Ranger analysis followed by survival classification tree analysis, we identified four clusters for adenocarcinomas and five clusters for squamous cell carcinomas which showed a considerable difference of clinical outcomes with statistical significance. CONCLUSIONS: These findings highlight the association between somatic DNA methylation in KDM genes and early-stage NSCLC patient survival, which may reveal potential epigenetic therapeutic targets

An Atlas of Epithelial Cell States and Plasticity in Lung Adenocarcinoma

Understanding the cellular processes that underlie early lung adenocarcinoma (LUAD) development is needed to devise intervention strategies1. Here we studied 246,102 single epithelial cells from 16 early-stage LUADs and 47 matched normal lung samples. Epithelial cells comprised diverse normal and cancer cell states, and diversity among cancer cells was strongly linked to LUAD-specific oncogenic drivers. KRAS mutant cancer cells showed distinct transcriptional features, reduced differentiation and low levels of aneuploidy. Non-malignant areas surrounding human LUAD samples were enriched with alveolar intermediate cells that displayed elevated KRT8 expression (termed KRT8+ alveolar intermediate cells (KACs) here), reduced differentiation, increased plasticity and driver KRAS mutations. Expression profiles of KACs were enriched in lung precancer cells and in LUAD cells and signified poor survival. In mice exposed to tobacco carcinogen, KACs emerged before lung tumours and persisted for months after cessation of carcinogen exposure. Moreover, they acquired Kras mutations and conveyed sensitivity to targeted KRAS inhibition in KAC-enriched organoids derived from alveolar type 2 (AT2) cells. Last, lineage-labelling of AT2 cells or KRT8+ cells following carcinogen exposure showed that KACs are possible intermediates in AT2-to-tumour cell transformation. This study provides new insights into epithelial cell states at the root of LUAD development, and such states could harbour potential targets for prevention or intervention

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

Analysis of Area-Specific Expression Patterns of RORbeta, ER81 and Nurr1 mRNAs in Rat Neocortex by Double In Situ Hybridization and Cortical Box Method

BACKGROUND: The mammalian neocortex is subdivided into many areas, each of which exhibits distinctive lamina architecture. To investigate such area differences in detail, we chose three genes for comparative analyses, namely, RORbeta, ER81 and Nurr1, mRNAs of which have been reported to be mainly expressed in layers 4, 5 and 6, respectively. To analyze their qualitative and quantitative coexpression profiles in the rat neocortex, we used double in situ hybridization (ISH) histochemistry and cortical box method which we previously developed to integrate the data of different staining and individuals in a standard three-dimensional space. PRINCIPAL FINDINGS: Our new approach resulted in three main observations. First, the three genes showed unique area distribution patterns that are mostly complementary to one another. The patterns revealed by cortical box method matched well with the cytoarchitectonic areas defined by Nissl staining. Second, at single cell level, RORbeta and ER81 mRNAs were coexpressed in a subpopulation of layer 5 neurons, whereas Nurr1 and ER81 mRNAs were not colocalized. Third, principal component analysis showed that the order of hierarchical processing in the cortex correlates well with the expression profiles of these three genes. Based on this analysis, the dysgranular zone (DZ) in the somatosensory area was considered to exhibit a profile of a higher order area, which is consistent with previous proposal. CONCLUSIONS/SIGNIFICANCE: The tight relationship between the expression of the three layer specific genes and functional areas were revealed, demonstrating the usefulness of cortical box method in the study on the cerebral cortex. In particular, it allowed us to perform statistical evaluation and pattern matching, which would become important in interpreting the ever-increasing data of gene expression in the cortex

Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

Protein ubiquitination is a dynamic and reversibleprocess of adding single ubiquitin molecules orvarious ubiquitin chains to target proteins. Here,using multidimensional omic data of 9,125 tumorsamples across 33 cancer types from The CancerGenome Atlas, we perform comprehensive molecu-lar characterization of 929 ubiquitin-related genesand 95 deubiquitinase genes. Among them, we sys-tematically identify top somatic driver candidates,including mutatedFBXW7with cancer-type-specificpatterns and amplifiedMDM2showing a mutuallyexclusive pattern withBRAFmutations. Ubiquitinpathway genes tend to be upregulated in cancermediated by diverse mechanisms. By integratingpan-cancer multiomic data, we identify a group oftumor samples that exhibit worse prognosis. Thesesamples are consistently associated with the upre-gulation of cell-cycle and DNA repair pathways, char-acterized by mutatedTP53,MYC/TERTamplifica-tion, andAPC/PTENdeletion. Our analysishighlights the importance of the ubiquitin pathwayin cancer development and lays a foundation fordeveloping relevant therapeutic strategies