A clonal expression biomarker associates with lung cancer mortality

An aim of molecular biomarkers is to stratify patients with cancer into disease subtypes predictive of outcome, improving diagnostic precision beyond clinical descriptors such as tumor stage1. Transcriptomic intratumor heterogeneity (RNA-ITH) has been shown to confound existing expression-based biomarkers across multiple cancer types2,3,4,5,6. Here, we analyze multi-region whole-exome and RNA sequencing data for 156 tumor regions from 48 patients enrolled in the TRACERx study to explore and control for RNA-ITH in non-small cell lung cancer. We find that chromosomal instability is a major driver of RNA-ITH, and existing prognostic gene expression signatures are vulnerable to tumor sampling bias. To address this, we identify genes expressed homogeneously within individual tumors that encode expression modules of cancer cell proliferation and are often driven by DNA copy-number gains selected early in tumor evolution. Clonal transcriptomic biomarkers overcome tumor sampling bias, associate with survival independent of clinicopathological risk factors, and may provide a general strategy to refine biomarker design across cancer types

A systematic search strategy identifies cubilin as independent prognostic marker for renal cell carcinoma

$\textbf{Background:}$ There is an unmet clinical need for better prognostic and diagnostic tools for renal cell carcinoma (RCC). $\textbf{Methods:}$ Human Protein Atlas data resources, including the transcriptomes and proteomes of normal and malignant human tissues, were searched for RCC-specific proteins and cubilin (CUBN) identified as a candidate. Patient tissue representing various cancer types was constructed into a tissue microarray ($n$ = 940) and immunohistochemistry used to investigate the specificity of CUBN expression in RCC as compared to other cancers. Two independent RCC cohorts ($n$ = 181; $n$ = 114) were analyzed to further establish the sensitivity of CUBN as RCC-specific marker and to explore if the fraction of RCCs lacking CUBN expression could predict differences in patient survival. $\textbf{Results:}$ CUBN was identified as highly RCC-specific protein with 58% of all primary RCCs staining positive for CUBN using immunohistochemistry. In venous tumor thrombi and metastatic lesions, the frequency of CUBN expression was increasingly lost. Clear cell RCC (ccRCC) patients with CUBN positive tumors had a significantly better prognosis compared to patients with CUBN negative tumors, independent of T-stage, Fuhrman grade and nodal status (HR 0.382, CI 0.203–0.719, $P$ = 0.003). $\textbf{Conclusions:}$ CUBN expression is highly specific to RCC and loss of the protein is significantly and independently associated with poor prognosis. CUBN expression in ccRCC provides a promising positive prognostic indicator for patients with ccRCC. The high specificity of CUBN expression in RCC also suggests a role as a new diagnostic marker in clinical cancer differential diagnostics to confirm or rule out RCC.This work was supported by the Swedish Cancer Society and the Knut and Alice Wallenberg Foundation. The work of DJH and GDS was funded by the Chief Scientist Office (grant number ETM37), Renal Cancer Research Fund and Kidney Cancer Scotland

Linkage to chromosome 2q32.2-q33.3 in familial serrated neoplasia (Jass syndrome)

Causative genetic variants have to date been identified for only a small proportion of familial colorectal cancer (CRC). While conditions such as Familial Adenomatous Polyposis and Lynch syndrome have well defined genetic causes, the search for variants underlying the remainder of familial CRC is plagued by genetic heterogeneity. The recent identification of families with a heritable predisposition to malignancies arising through the serrated pathway (familial serrated neoplasia or Jass syndrome) provides an opportunity to study a subset of familial CRC in which heterogeneity may be greatly reduced. A genome-wide linkage screen was performed on a large family displaying a dominantly-inherited predisposition to serrated neoplasia genotyped using the Affymetrix GeneChip Human Mapping 10 K SNP Array. Parametric and nonparametric analyses were performed and resulting regions of interest, as well as previously reported CRC susceptibility loci at 3q22, 7q31 and 9q22, were followed up by finemapping in 10 serrated neoplasia families. Genome-wide linkage analysis revealed regions of interest at 2p25.2-p25.1, 2q24.3-q37.1 and 8p21.2-q12.1. Finemapping linkage and haplotype analyses identified 2q32.2-q33.3 as the region most likely to harbour linkage, with heterogeneity logarithm of the odds (HLOD) 2.09 and nonparametric linkage (NPL) score 2.36 (P = 0.004). Five primary candidate genes (CFLAR, CASP10, CASP8, FZD7 and BMPR2) were sequenced and no segregating variants identified. There was no evidence of linkage to previously reported loci on chromosomes 3, 7 and 9

A high resolution atlas of gene expression in the domestic sheep (Ovis aries)

Sheep are a key source of meat, milk and fibre for the global livestock sector, and an important biomedical model. Global analysis of gene expression across multiple tissues has aided genome annotation and supported functional annotation of mammalian genes. We present a large-scale RNA-Seq dataset representing all the major organ systems from adult sheep and from several juvenile, neonatal and prenatal developmental time points. The Ovis aries reference genome (Oar v3.1) includes 27,504 genes (20,921 protein coding), of which 25,350 (19,921 protein coding) had detectable expression in at least one tissue in the sheep gene expression atlas dataset. Network-based cluster analysis of this dataset grouped genes according to their expression pattern. The principle of 'guilt by association' was used to infer the function of uncharacterised genes from their co-expression with genes of known function. We describe the overall transcriptional signatures present in the sheep gene expression atlas and assign those signatures, where possible, to specific cell populations or pathways. The findings are related to innate immunity by focusing on clusters with an immune signature, and to the advantages of cross-breeding by examining the patterns of genes exhibiting the greatest expression differences between purebred and crossbred animals. This high-resolution gene expression atlas for sheep is, to our knowledge, the largest transcriptomic dataset from any livestock species to date. It provides a resource to improve the annotation of the current reference genome for sheep, presenting a model transcriptome for ruminants and insight into gene, cell and tissue function at multiple developmental stages

Gene rearrangements in hormone receptor negative breast cancers revealed by mate pair sequencing

Background: Chromosomal rearrangements in the form of deletions, insertions, inversions and translocations are frequently observed in breast cancer genomes, and a subset of these rearrangements may play a crucial role in tumorigenesis. To identify novel somatic chromosomal rearrangements, we determined the genome structures of 15 hormone-receptor negative breast tumors by long-insert mate pair massively parallel sequencing. Results: We identified and validated 40 somatic structural alterations, including the recurring fusion between genes DDX10 and SKA3 and translocations involving the EPHA5 gene. Other rearrangements were found to affect genes in pathways involved in epigenetic regulation, mitosis and signal transduction, underscoring their potential role in breast tumorigenesis. RNA interference-mediated suppression of five candidate genes (DDX10, SKA3, EPHA5, CLTC and TNIK) led to inhibition of breast cancer cell growth. Moreover, downregulation of DDX10 in breast cancer cells lead to an increased frequency of apoptotic nuclear morphology. Conclusions: Using whole genome mate pair sequencing and RNA interference assays, we have discovered a number of novel gene rearrangements in breast cancer genomes and identified DDX10, SKA3, EPHA5, CLTC and TNIK as potential cancer genes with impact on the growth and proliferation of breast cancer cells

Immune dysfunction revealed by digital spatial profiling of immuno-oncology markers in progressive stages of renal cell carcinoma and in brain metastases

Background The tumor microenvironment (TME) contributes to cancer progression and treatment response to therapy, including in renal cell carcinoma (RCC). Prior profiling studies, including single-cell transcriptomics, often involve limited sample sizes and lack spatial orientation. The TME of RCC brain metastases, a major cause of morbidity, also remains largely uncharacterized.Methods We performed digital spatial profiling on the NanoString GeoMx platform using 52 validated immuno-oncology markers on RCC tissue microarrays representing progressive stages of RCC, including brain metastases. We profiled 76 primary tumors, 27 adjacent histologically normal kidney samples, and 86 metastases, including 24 brain metastases.Results We observed lower immune checkpoint (TIM-3 and CTLA-4), cytolytic (GZMA and GZMB), and T cell activation (CD25) protein expression in metastases compared with primary tumors in two separate cohorts. We also identified changes in macrophages in metastases, with brain metastases-susceptible patients showing less M1-like, inflammatory macrophage markers (HLA-DR and CD127) in metastatic samples. A comparison of brain metastases to extracranial metastases revealed higher expression of the anti-apoptotic, BCL-2-family protein BCL-XL and lower expression of the innate immune activator STING in brain metastases. Lower TIM-3 and CD40 in the TME of brain metastases appear to be associated with longer survival, a finding that requires further validation.Conclusions Compared with primary tumors, RCC metastases, including brain metastases, express lower levels of numerous markers of immune activation and current or investigational therapeutic targets. Our findings may have important implications for designing future biomarker and treatment studies and may aid in development of brain metastases-specific therapies

A clonal expression biomarker associates with lung cancer mortality

An aim of molecular biomarkers is to stratify patients with cancer into disease subtypes predictive of outcome, improving diagnostic precision beyond clinical descriptors such as tumor stage. Transcriptomic intratumor heterogeneity (RNAITH) has been shown to confound existing expression-based biomarkers across multiple cancer types. Here, we analyze multi-region whole-exome and RNA sequencing data for 156 tumor regions from 48 patients enrolled in the TRACERx study to explore and control for RNA-ITH in non-small cell lung cancer. We find that chromosomal instability is a major driver of RNA-ITH, and existing prognostic gene expression signatures are vulnerable to tumor sampling bias. To address this, we identify genes expressed homogeneously within individual tumors that encode expression modules of cancer cell proliferation and are often driven by DNA copy-number gains selected early in tumor evolution. Clonal transcriptomic biomarkers overcome tumor sampling bias, associate with survival independent of clinicopathological risk factors, and may provide a general strategy to refine biomarker design across cancer types

Tissue-based map of the human proteome

Resolving the molecular details of proteome variation in the different tissues and organs of the human body will greatly increase our knowledge of human biology and disease. Here, we present a map of the human tissue proteome based on an integrated omics approach that involves quantitative transcriptomics at the tissue and organ level, combined with tissue microarray-based immunohistochemistry, to achieve spatial localization of proteins down to the single-cell level. Our tissue-based analysis detected more than 90% of the putative protein-coding genes.We used this approach to explore the human secretome, the membrane proteome, the druggable proteome, the cancer proteome, and the metabolic functions in 32 different tissues and organs. All the data are integrated in an interactive Web-based database that allows exploration of individual proteins, as well as navigation of global expression patterns, in all major tissues and organs in the human body