Histological assessment of paxgene tissue fixation and stabilization reagents

Within SPIDIA, an EC FP7 project aimed to improve pre analytic procedures, the PAXgene Tissue System (PAXgene), was designed to improve tissue quality for parallel molecular and morphological analysis. Within the SPIDIA project promising results were found in both genomic and proteomic experiments with PAXgene-fixed and paraffin embedded tissue derived biomolecules. But, for this technology to be accepted for use in both clinical and basic research, it is essential that its adequacy for preserving morphology and antigenicity is validated relative to formalin fixation. It is our aim to assess the suitability of PAXgene tissue fixation for (immuno)histological methods. Normal human tissue specimens (n = 70) were collected and divided into equal parts for fixation either with formalin or PAXgene. Sections of the obtained paraffin-embedded tissue were cut and stained. Morphological aspects of PAXgene-fixed tissue were described and also scored relative to formalin-fixed tissue. Performance of PAXgene-fixed tissue in immunohistochemical and in situ hybridization assays was also assessed relative to the corresponding formalin-fixed tissues. Morphology of PAXgene-fixed paraffin embedded tissue was well preserved and deemed adequate for diagnostics in most cases. Some antigens in PAXgene-fixed and paraffin embedded sections were detectable without the need for antigen retrieval, while others were detected using standard, formalin fixation based, immunohistochemistry protocols. Comparable results were obtained with in situ hybridization and histochemical stains. Basically all assessed histological techniques were found to be applicable to PAXgene-fixed and paraffin embedded tissue. In general results obtained with PAXgene-fixed tissue are comparable to those of formalin-fixed tissue. Compromises made in morphology can be called minor compared to the advantages in the molecular pathology possibilities

Bcl3 Couples Cancer Stem Cell Enrichment With Pancreatic Cancer Molecular Subtypes

[Background & Aims]: The existence of different subtypes of pancreatic ductal adenocarcinoma (PDAC) and their correlation with patient outcome have shifted the emphasis on patient classification for better decision-making algorithms and personalized therapy. The contribution of mechanisms regulating the cancer stem cell (CSC) population in different subtypes remains unknown. [Methods]: Using RNA-seq, we identified B-cell CLL/lymphoma 3 (BCL3), an atypical nf-κb signaling member, as differing in pancreatic CSCs. To determine the biological consequences of BCL3 silencing in vivo and in vitro, we generated bcl3-deficient preclinical mouse models as well as murine cell lines and correlated our findings with human cell lines, PDX models, and 2 independent patient cohorts. We assessed the correlation of bcl3 expression pattern with clinical parameters and subtypes. [Results]: Bcl3 was significantly down-regulated in human CSCs. Recapitulating this phenotype in preclinical mouse models of PDAC via BCL3 genetic knockout enhanced tumor burden, metastasis, epithelial to mesenchymal transition, and reduced overall survival. Fluorescence-activated cell sorting analyses, together with oxygen consumption, sphere formation, and tumorigenicity assays, all indicated that BCL3 loss resulted in CSC compartment expansion promoting cellular dedifferentiation. Overexpression of BCL3 in human PDXs diminished tumor growth by significantly reducing the CSC population and promoting differentiation. Human PDACs with low BCL3 expression correlated with increased metastasis, and BCL3-negative tumors correlated with lower survival and nonclassical subtypes. [Conclusions]: We demonstrate that bcl3 impacts pancreatic carcinogenesis by restraining CSC expansion and by curtailing an aggressive and metastatic tumor burden in PDAC across species. Levels of BCL3 expression are a useful stratification marker for predicting subtype characterization in PDAC, thereby allowing for personalized therapeutic approaches.This work was supported by the Deutsche Forschungsgemeinschaft (grants AL 1174/4-1, AL1174/4-2, and Collaborative Research Center 1321 “Modeling and Targeting Pancreatic Cancer” to Hana Algül; SFB824 Z2 to Katja Steiger), the Deutsche Krebshilfe (grant 111646 to Hana Algül), a Ramon y Cajal Merit Award from the Ministerio de Economía y Competitividad, Spain (to Bruno Sainz Jr), a Coordinated Grant from Fundación Asociación Española Contra el Cáncer (GC16173694BARB to Bruno Sainz Jr), funding from The Fero Foundation (to Bruno Sainz Jr), and a Proyecto de Investigacion de Salud, ISCIII, Spain (no. PI18/00757 to Bruno Sainz Jr). Jiaoyu Ai is supported by the “China Scholarship Council” grant program

Discovery of New Molecular Subtypes in Oesophageal Adenocarcinoma

A large number of patients suffering from oesophageal adenocarcinomas do not respond to conventional chemotherapy; therefore, it is necessary to identify new predictive biomarkers and patient signatures to improve patient outcomes and therapy selections. We analysed 87 formalin-fixed and paraffin-embedded (FFPE) oesophageal adenocarcinoma tissue samples with a reverse phase protein array (RPPA) to examine the expression of 17 cancer-related signalling molecules. Protein expression levels were analysed by unsupervised hierarchical clustering and correlated with clinicopathological parameters and overall patient survival. Proteomic analyses revealed a new, very promising molecular subtype of oesophageal adenocarcinoma patients characterised by low levels of the HSP27 family proteins and high expression of those of the HER family with positive lymph nodes, distant metastases and short overall survival. After confirmation in other independent studies, our results could be the foundation for the development of a Her2-targeted treatment option for this new patient subgroup of oesophageal adenocarcinoma

Genetic alterations of the SUMO isopeptidase SENP6 drive lymphomagenesis and genetic instability in diffuse large B-cell lymphoma

SUMOylation is a post-translational modification of proteins that regulates these proteins' localization, turnover or function. Aberrant SUMOylation is frequently found in cancers but its origin remains elusive. Using a genome-wide transposon mutagenesis screen in a MYC-driven B-cell lymphoma model, we here identify the SUMO isopeptidase (or deconjugase) SENP6 as a tumor suppressor that links unrestricted SUMOylation to tumor development and progression. Notably, SENP6 is recurrently deleted in human lymphomas and SENP6 deficiency results in unrestricted SUMOylation. Mechanistically, SENP6 loss triggers release of DNA repair- and genome maintenance-associated protein complexes from chromatin thereby impairing DNA repair in response to DNA damages and ultimately promoting genomic instability. In line with this hypothesis, SENP6 deficiency drives synthetic lethality to Poly-ADP-Ribose-Polymerase (PARP) inhibition. Together, our results link SENP6 loss to defective genome maintenance and reveal the potential therapeutic application of PARP inhibitors in B-cell lymphoma

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

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

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

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

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