Motivation: Pairing between the target sequence and the 6–8 nt long seed sequence of the miRNA presents the most important feature for miRNA target site prediction. Novel high-throughput technologies such as Argonaute HITS-CLIP afford meanwhile a detailed study of miRNA:mRNA duplices. These interaction maps enable a first discrimination between functional and non-functional target sites in a bulky fashion. Prediction algorithms apply different seed paradigms to identify miRNA target sites. Therefore, a quantitative assessment of miRNA target site prediction is of major interest.Results: We identified a set of canonical seed types based on a transcriptome wide analysis of experimentally verified functional target sites. We confirmed the specificity of long seeds but we found that the majority of functional target sites are formed by less specific seeds of only 6 nt indicating a crucial role of this type. A substantial fraction of genuine target sites arenon-conserved. Moreover, the majority of functional sites remain uncovered by common prediction methods.Contact: florian.buettner@helmholtz-muenchen.de v.stuempflen@helmholtz-muenchen.deSupplementary Information: Supplementary data are available at Bioinformatics online.

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Metabolite profiling of tissue samples is a promising approach for the characterization of cancer pathways and tumor classification based on metabolic features. Here, we present an analytical method for nontargeted metabolomics of kidney tissue. Capitalizing on different chemical properties of metabolites allowed us to extract a broad range of molecules covering small polar molecules and less polar lipid classes that were analyzed by LC-QTOF-MS after HILIC and RP chromatographic separation, respectively. More than 1000 features could be reproducibly extracted and analyzed (CV < 30%) in porcine and human kidney tissue, which were used as surrogate matrices for method development. To further assess assay performance, cross-validation of the nontargeted metabolomics platform to a targeted metabolomics approach was carried out. Strikingly, from 102 metabolites that could be detected on both platforms, the majority (>90%) revealed Spearman's correlation coefficients ≥0.3, indicating that quantitative results from the nontargeted assay are largely comparable to data derived from classical targeted assays. Finally, as proof of concept, the method was applied to human kidney tissue where a clear differentiation between kidney cancer and nontumorous material could be demonstrated on the basis of unsupervised statistical analysis.

Current therapies for metastatic clear cell renal cell carcinoma (ccRCC) show limited efficacy. Drug efficacy, typically investigated in preclinical cell line models during drug development, is influenced by pharmacogenes involved in targeting and disposition of drugs. Here we show through genome-wide DNA methylation profiling, that methylation patterns are concordant between primary ccRCC and macro-metastases irrespective of metastatic sites (rs ≥ 0.92). However, 195,038 (41%) of all investigated CpG sites, including sites within pharmacogenes, were differentially methylated (adjusted P < 0.05) in five established RCC cell lines compared to primary tumors, resulting in altered transcriptional expression. Exemplarily, gene-specific analyses of DNA methylation, mRNA and protein expression demonstrate lack of expression of the clinically important drug transporter OCT2 (encoded by SLC22A2) in cell lines due to hypermethylation compared to tumors or metastases. Our findings provide evidence that RCC cell lines are of limited benefit for prediction of drug effects due to epigenetic alterations. Similar epigenetic landscape of ccRCC-metastases and tumors opens new avenue for future therapeutic strategies.

Several subtypes of renal cell carcinoma (RCC) with different metastatic potentials and prognoses exist. In the present study, we provide novel insight into the metabolism of these different subtypes, which improves classification of subtypes and helps identify novel targets for RCC therapy.

The efflux transporter breast cancer resistance protein BCRP/ABCG2 is well-known for its contribution to multi-drug resistance in cancer. Its relevance in cancer biology independent from drug efflux remains largely elusive. Our study aimed at elucidating the biological relevance and regulatory mechanisms of BCRP/ABCG2 in clear cell renal cell carcinoma (ccRCC) and disease progression. Two independent ccRCC-cohorts [Cohort 1 (KIRC/TCGA): n = 453, Cohort 2: n = 64] were investigated to elucidate BCRP/ABCG2 mRNA and protein expression and their association with survival. The impact of BCRP/ABCG2 on response to sunitinib treatment was investigated in two independent sunitinib-treated ccRCC-cohorts based on mRNA levels. Moreover, underlying regulatory mechanisms for interindividual variability of BCRP/ABCG2 expression were systematically assessed. Owing to redundant functional properties, mRNA and protein expression of the multidrug resistance protein MDR1/ABCB1 were additionally evaluated in these cohorts. In independent ccRCC-cohorts, low BCRP/ABCG2 and MDR1/ABCB1 mRNA and protein expression were associated with severity (e.g., tumor stage) of ccRCC and poor cancer-specific survival. BCRP/ABCG2 and MDR1/ABCB1 mRNA expression were linked to decreased progression-free survival after sunitinib treatment. Germline and somatic variants influenced interindividual variability of BCRP/ABCG2 expression only moderately. miR-212-3p and miR-132-3p were identified to regulate BCRP/ABCG2 posttranscriptionally by interaction with the ABCG2 3'UTR as confirmed through reporter gene assays in RCC cell lines. In summary, BCRP/ABCG2 expression in ccRCC underlies considerable interindividual variability with impact on patient survival and response to sunitinib treatment. While germline or somatic genetic variants and DNA methylation cannot explain aberrant BCRP/ABCG2 expression, miR-212-3p and miR-132-3p were identified to contribute to posttranscriptional regulation of BCRP/ABCG2.

The presence or absence of estrogen and progesterone steroid hormone receptor expression (ER, PR) is an essential feature of invasive breast cancer and determines prognosis and endocrine treatment decisions. Among the four ER/PR receptor phenotypes, the ER-/PR+ is infrequent, and its clinical relevance has been controversially discussed. Thus, we investigated its clinical significance and gene expression pattern in large datasets. In a retrospective clinical study of 15,747 breast cancer patients, we determined the ER/PR subtype survival probabilities using Kaplan-Meier and Cox regression analyses. From The Cancer Genome Atlas (TCGA) breast cancer dataset, PAM50 expression signature and pathway analyses were performed to test for distinct molecular features. In our cohort, the ER-/PR+ phenotype has been observed at a frequency of 4.1 % and was associated with an improved 10-year survival for stage I cancers compared to the ER+/PR+ reference subtype (median; 95 % CI 88.1 %; 83-93 vs. 84.3 %; 82-86 %, P = 0.024) as was confirmed by multivariate analysis over the entire follow-up (HR 0.59, 95 % CI 0.38-0.92, P = 0.021). This association lacked significance when including all stages. ER-/PR+ patients treated with antihormonal agents (34.5 %) had shorter survival compared to their non-treated counterparts (Log-rank P = 0.0001). PAM50 signatures suggest a distinct configuration for the ER-/PR+ phenotype. This specific phenotype has been further separated by a set of 59 uniquely expressed genes. Our study supports the notion of the existence of an ER-/PR+ phenotype with clinical and molecular features distinct from the large group of ER+/PR+ patients.

Background: Clear cell renal cell carcinoma (ccRCC) is the dominant subtype of renal cancer. With currently available therapies, cure of advanced and metastatic ccRCC is achieved only in rare cases. Here, we developed a workflow integrating different-omics technologies to identify ccRCC-specific HLA-presented peptides as potential drug targets for ccRCC immunotherapy. Methods: We analyzed HLA-presented peptides by MS-based ligandomics of 55 ccRCC tumors (cohort 1), paired non-tumor renal tissues, and 158 benign tissues from other organs. Pathways enriched in ccRCC compared to its cell type of origin were identified by transcriptome and gene set enrichment analyses in 51 tumor tissues of the same cohort. To retrieve a list of candidate targets with involvement in ccRCC pathogenesis, ccRCC-specific pathway genes were intersected with the source genes of tumor-exclusive peptides. The candidates were validated in an independent cohort from The Cancer Genome Atlas (TCGA KIRC, n = 452). DNA methylation (TCGA KIRC, n = 273), somatic mutations (TCGA KIRC, n = 392), and gene ontology (GO) and correlations with tumor metabolites (cohort 1, n = 30) and immune-oncological markers (cohort 1, n = 37) were analyzed to characterize regulatory and functional involvements. CD8 + T cell priming assays were used to identify immunogenic peptides. The candidate gene EGLN3 was functionally investigated in cell culture. Results: A total of 34,226 HLA class I-and 19,325 class II-presented peptides were identified in ccRCC tissue, of which 443 class I and 203 class II peptides were ccRCC-specific and presented in ≥ 3 tumors. One hundred eightyfive of the 499 corresponding source genes were involved in pathways activated by ccRCC tumors. After validation in the independent cohort from TCGA, 113 final candidate genes remained. Candidates were involved in extracellular matrix organization, hypoxic signaling, immune processes, and others. Nine of the 12 peptides assessed