mitoBKCa is functionally expressed in murine and human breast cancer cells and potentially contributes to metabolic reprogramming.

Alterations in the function of K+ channels such as the voltage- and Ca2+-activated K+ channel of large conductance (BKCa) reportedly promote breast cancer (BC) development and progression. Underlying molecular mechanisms remain, however, elusive. Here, we provide electrophysiological evidence for a BKCa splice variant localized to the inner mitochondrial membrane of murine and human BC cells (mitoBKCa). Through a combination of genetic knockdown and knockout along with a cell permeable BKCa channel blocker, we show that mitoBKCa modulates overall cellular and mitochondrial energy production, and mediates the metabolic rewiring referred to as the 'Warburg effect', thereby promoting BC cell proliferation in the presence and absence of oxygen. Additionally, we detect mitoBKCa and BKCa transcripts in low or high abundance, respectively, in clinical BC specimens. Together, our results emphasize, that targeting mitoBKCa could represent a treatment strategy for selected BC patients in future.

Wnt/ß-catenin and NFκB signaling synergize to trigger growth factor-free regeneration of adult primary human hepatocytes.

BACKGROUND AND AIMS: The liver has a remarkable capacity to regenerate, which is sustained by the ability of hepatocytes to act as facultative stem cells that, while normally quiescent, re-enter the cell cycle after injury. Growth factor signaling is indispensable in rodents, whereas Wnt/ß-catenin is not required for effective tissue repair. However, the molecular networks that control human liver regeneration remain unclear. METHODS: Organotypic 3D spheroid cultures of primary human or murine hepatocytes were used to identify the signaling network underlying cell cycle re-entry. Furthermore, we performed chemogenomic screening of a library enriched for epigenetic regulators and modulators of immune function to determine the importance of epigenomic control for human hepatocyte regeneration. RESULTS: Our results showed that, unlike in rodents, activation of Wnt/ß-catenin signaling is the major mitogenic cue for adult primary human hepatocytes. Furthermore, we identified TGFß inhibition and inflammatory signaling through NF-κB as essential steps for the quiescent-to-regenerative switch that allows Wnt/ß-catenin-induced proliferation of human cells. In contrast, growth factors, but not Wnt/ß-catenin signaling, triggered hyperplasia in murine hepatocytes. High-throughput screening in a human model confirmed the relevance of NFκB and revealed the critical roles of polycomb repressive complex 2, as well as of the bromodomain families I, II, and IV. CONCLUSIONS: This study revealed a network of NFκB, TGFß, and Wnt/ß-catenin that controls human hepatocyte regeneration in the absence of exogenous growth factors, identified novel regulators of hepatocyte proliferation, and highlighted the potential of organotypic culture systems for chemogenomic interrogation of complex physiological processes.

Comparative analysis of YAP/TEAD inhibitors in 2D and 3D cultures of primary human hepatocytes reveals a novel non-canonical mechanism of CYP induction.

Induction of cytochrome P450 (CYP) genes constitutes an important cause of drug-drug interactions and preclinical evaluation of induction liability is mandatory for novel drug candidates. YAP/TEAD signaling has emerged as an attractive target for various oncological indications and multiple chemically distinct YAP/TEAD inhibitors are rapidly progressing towards clinical stages. Here, we tested the liability for CYP induction of a diverse set of YAP/TEAD inhibitors with different modes of action and TEAD isoform selectivity profiles in monolayers and 3D spheroids of primary human hepatocytes (PHH). We found that YAP/TEAD inhibition resulted in broad induction of CYPs in 2D monolayers, whereas, if at all, only marginal induction was seen in spheroid culture. Comprehensive RNA-Seq indicated that YAP/TEAD signaling was increased in 2D culture compared to spheroids, which was paralleled by elevated activities of the interacting transcription factors LXR and ESRRA, likely at least in part due to altered mechanosensing. Inhibition of this YAP/TEAD hyperactivation resulted in an overall reduction of hepatocyte dedifferentiation marked by increased hepatic functionality, including CYPs. These results thus demonstrate that the observed induction is due to on-target effects of the compounds rather than direct activation of xenobiotic sensing nuclear receptors. Combined, the presented data link hepatocyte dedifferentiation to YAP/TEAD dysregulation, reveal a novel non-canonical pathway of CYP induction and highlight the advantage of organotypic 3D cultures to predict clinically relevant pharmacokinetic properties, particularly for atypical induction mechanisms.

Dendritic Cells or Macrophages? The Microenvironment of Human Clear Cell Renal Cell Carcinoma Imprints a Mosaic Myeloid Subtype Associated with Patient Survival.

Since their initial description by Elie Metchnikoff, phagocytes have sparked interest in a variety of biologic disciplines. These important cells perform central functions in tissue repair and immune activation as well as tolerance. Myeloid cells can be immunoinhibitory, particularly in the tumor microenvironment, where their presence is generally associated with poor patient prognosis. These cells are highly adaptable and plastic, and can be modulated to perform desired functions such as antitumor activity, if key programming molecules can be identified. Human clear cell renal cell carcinoma (ccRCC) is considered immunogenic; yet checkpoint blockades that target T cell dysfunction have shown limited clinical efficacy, suggesting additional layers of immunoinhibition. We previously described "enriched-in-renal cell carcinoma" (erc) DCs that were often found in tight contact with dysfunctional T cells. Using transcriptional profiling and flow cytometry, we describe here that ercDCs represent a mosaic cell type within the macrophage continuum co-expressing M1 and M2 markers. The polarization state reflects tissue-specific signals that are characteristic of RCC and renal tissue homeostasis. ErcDCs are tissue-resident with increasing prevalence related to tumor grade. Accordingly, a high ercDC score predicted poor patient survival. Within the profile, therapeutic targets (VSIG4, NRP1, GPNMB) were identified with promise to improve immunotherapy.

Bioengineered Pancreas-Liver Crosstalk in a Microfluidic Coculture Chip Identifies Human Metabolic Response Signatures in Prediabetic Hyperglycemia.

Aberrant glucose homeostasis is the most common metabolic disturbance affecting one in ten adults worldwide. Prediabetic hyperglycemia due to dysfunctional interactions between different human tissues, including pancreas and liver, constitutes the largest risk factor for the development of type 2 diabetes. However, this early stage of metabolic disease has received relatively little attention. Microphysiological tissue models that emulate tissue crosstalk offer emerging opportunities to study metabolic interactions. Here, a novel modular multitissue organ-on-a-chip device is presented that allows for integrated and reciprocal communication between different 3D primary human tissue cultures. Precisely controlled heterologous perfusion of each tissue chamber is achieved through a microfluidic single "synthetic heart" pneumatic actuation unit connected to multiple tissue chambers via specific configuration of microchannel resistances. On-chip coculture experiments of organotypic primary human liver spheroids and intact primary human islets demonstrate insulin secretion and hepatic insulin response dynamics at physiological timescales upon glucose challenge. Integration of transcriptomic analyses with promoter motif activity data of 503 transcription factors reveals tissue-specific interacting molecular networks that underlie ß-cell stress in prediabetic hyperglycemia. Interestingly, liver and islet cultures show surprising counter-regulation of transcriptional programs, emphasizing the power of microphysiological coculture to elucidate the systems biology of metabolic crosstalk.

A novel molecular signature identifies mixed subtypes in renal cell carcinoma with poor prognosis and independent response to immunotherapy.

BACKGROUND: Renal cell carcinoma (RCC) is a heterogeneous disease comprising histologically defined subtypes. For therapy selection, precise subtype identification and individualized prognosis are mandatory, but currently limited. Our aim was to refine subtyping and outcome prediction across main subtypes, assuming that a tumor is composed of molecular features present in distinct pathological subtypes. METHODS: Individual RCC samples were modeled as linear combination of the main subtypes (clear cell (ccRCC), papillary (pRCC), chromophobe (chRCC)) using computational gene expression deconvolution. The new molecular subtyping was compared with histological classification of RCC using the Cancer Genome Atlas (TCGA) cohort (n = 864; ccRCC: 512; pRCC: 287; chRCC: 65) as well as 92 independent histopathologically well-characterized RCC. Predicted continuous subtypes were correlated to cancer-specific survival (CSS) in the TCGA cohort and validated in 242 independent RCC. Association with treatment-related progression-free survival (PFS) was studied in the JAVELIN Renal 101 (n = 726) and IMmotion151 trials (n = 823). CSS and PFS were analyzed using the Kaplan-Meier and Cox regression analysis. RESULTS: One hundred seventy-four signature genes enabled reference-free molecular classification of individual RCC. We unambiguously assign tumors to either ccRCC, pRCC, or chRCC and uncover molecularly heterogeneous tumors (e.g., with ccRCC and pRCC features), which are at risk of worse outcome. Assigned proportions of molecular subtype-features significantly correlated with CSS (ccRCC (P = 4.1E - 10), pRCC (P = 6.5E - 10), chRCC (P = 8.6E - 06)) in TCGA. Translation into a numerical RCC-R(isk) score enabled prognosis in TCGA (P = 9.5E - 11). Survival modeling based on the RCC-R score compared to pathological categories was significantly improved (P = 3.6E - 11). The RCC-R score was validated in univariate (P = 3.2E - 05; HR = 3.02, 95% CI: 1.8-5.08) and multivariate analyses including clinicopathological factors (P = 0.018; HR = 2.14, 95% CI: 1.14-4.04). Heterogeneous PD-L1-positive RCC determined by molecular subtyping showed increased PFS with checkpoint inhibition versus sunitinib in the JAVELIN Renal 101 (P = 3.3E - 04; HR = 0.52, 95% CI: 0.36 - 0.75) and IMmotion151 trials (P = 0.047; HR = 0.69, 95% CI: 0.48 - 1). The prediction of PFS significantly benefits from classification into heterogeneous and unambiguous subtypes in both cohorts (P = 0.013 and P = 0.032). CONCLUSION: Switching from categorical to continuous subtype classification across most frequent RCC subtypes enables outcome prediction and fosters personalized treatment strategies.

Hepatic Expression of the Na+-Taurocholate Cotransporting Polypeptide Is Independent from Genetic Variation.

The hepatic Na+-taurocholate cotransporting polypeptide NTCP/SLC10A1 is important for the uptake of bile salts and selected drugs. Its inhibition results in increased systemic bile salt concentrations. NTCP is also the entry receptor for the hepatitis B/D virus. We investigated interindividual hepatic SLC10A1/NTCP expression using various omics technologies. SLC10A1/NTCP mRNA expression/protein abundance was quantified in well-characterized 143 human livers by real-time PCR and LC-MS/MS-based targeted proteomics. Genome-wide SNP arrays and SLC10A1 next-generation sequencing were used for genomic analyses. SLC10A1 DNA methylation was assessed through MALDI-TOF MS. Transcriptomics and untargeted metabolomics (UHPLC-Q-TOF-MS) were correlated to identify NTCP-related metabolic pathways. SLC10A1 mRNA and NTCP protein levels varied 44-fold and 10.4-fold, respectively. Non-genetic factors (e.g., smoking, alcohol consumption) influenced significantly NTCP expression. Genetic variants in SLC10A1 or other genes do not explain expression variability which was validated in livers (n = 50) from The Cancer Genome Atlas. The identified two missense SLC10A1 variants did not impair transport function in transfectants. Specific CpG sites in SLC10A1 as well as single metabolic alterations and pathways (e.g., peroxisomal and bile acid synthesis) were significantly associated with expression. Inter-individual variability of NTCP expression is multifactorial with the contribution of clinical factors, DNA methylation, transcriptional regulation as well as hepatic metabolism, but not genetic variation.

A Molecularly Characterized Preclinical Platform of Subcutaneous Renal Cell Carcinoma (RCC) Patient-Derived Xenograft Models to Evaluate Novel Treatment Strategies.

Renal cell carcinoma (RCC) is a kidney cancer with an onset mainly during the sixth or seventh decade of the patient's life. Patients with advanced, metastasized RCC have a poor prognosis. The majority of patients develop treatment resistance towards Standard of Care (SoC) drugs within months. Tyrosine kinase inhibitors (TKIs) are the backbone of first-line therapy and have been partnered with an immune checkpoint inhibitor (ICI) recently. Despite the most recent progress, the development of novel therapies targeting acquired TKI resistance mechanisms in advanced and metastatic RCC remains a high medical need. Preclinical models with high translational relevance can significantly support the development of novel personalized therapies. It has been demonstrated that patient-derived xenograft (PDX) models represent an essential tool for the preclinical evaluation of novel targeted therapies and their combinations. In the present project, we established and molecularly characterized a comprehensive panel of subcutaneous RCC PDX models with well-conserved molecular and pathological features over multiple passages. Drug screening towards four SoC drugs targeting the vascular endothelial growth factor (VEGF) and PI3K/mTOR pathway revealed individual and heterogeneous response profiles in those models, very similar to observations in patients. As unique features, our cohort includes PDX models from metastatic disease and multi-tumor regions from one patient, allowing extended studies on intra-tumor heterogeneity (ITH). The PDX models are further used as basis for developing corresponding in vitro cell culture models enabling advanced high-throughput drug screening in a personalized context. PDX models were subjected to next-generation sequencing (NGS). Characterization of cancer-relevant features including driver mutations or cellular processes was performed using mutational and gene expression data in order to identify potential biomarker or treatment targets in RCC. In summary, we report a newly established and molecularly characterized panel of RCC PDX models with high relevance for translational preclinical research.

Nicotinamide-N-methyltransferase is a promising metabolic drug target for primary and metastatic clear cell renal cell carcinoma.

BACKGROUND: The metabolic enzyme nicotinamide-N-methyltransferase (NNMT) is highly expressed in various cancer entities, suggesting tumour-promoting functions. We systematically investigated NNMT expression and its metabolic interactions in clear cell renal cell carcinoma (ccRCC), a prominent RCC subtype with metabolic alterations, to elucidate its role as a drug target. METHODS: NNMT expression was assessed in primary ccRCC (n = 134), non-tumour tissue and ccRCC-derived metastases (n = 145) by microarray analysis and/or immunohistochemistry. Findings were validated in The Cancer Genome Atlas (kidney renal clear cell carcinoma [KIRC], n = 452) and by single-cell analysis. Expression was correlated with clinicopathological data and survival. Metabolic alterations in NNMT-depleted cells were assessed by nontargeted/targeted metabolomics and extracellular flux analysis. The NNMT inhibitor (NNMTi) alone and in combination with the inhibitor 2-deoxy-D-glucose for glycolysis and BPTES (bis-2-(5-phenylacetamido-1,3,4-thiadiazol-2-yl)ethyl-sulfide) for glutamine metabolism was investigated in RCC cell lines (786-O, A498) and in two 2D ccRCC-derived primary cultures and three 3D ccRCC air-liquid interface models. RESULTS: NNMT protein was overexpressed in primary ccRCC (p = 1.32 × 10-16 ) and ccRCC-derived metastases (p = 3.92 × 10-20 ), irrespective of metastatic location, versus non-tumour tissue. Single-cell data showed predominant NNMT expression in ccRCC and not in the tumour microenvironment. High NNMT expression in primary ccRCC correlated with worse survival in independent cohorts (primary RCC-hazard ratio [HR] = 4.3, 95% confidence interval [CI]: 1.5-12.4; KIRC-HR = 3.3, 95% CI: 2.0-5.4). NNMT depletion leads to intracellular glutamine accumulation, with negative effects on mitochondrial function and cell survival, while not affecting glycolysis or glutathione metabolism. At the gene level, NNMT-depleted cells upregulate glycolysis, oxidative phosphorylation and apoptosis pathways. NNMTi alone or in combination with 2-deoxy-D-glucose and BPTES resulted in inhibition of cell viability in ccRCC cell lines and primary tumour and metastasis-derived models. In two out of three patient-derived ccRCC air-liquid interface models, NNMTi treatment induced cytotoxicity. CONCLUSIONS: Since efficient glutamine utilisation, which is essential for ccRCC tumours, depends on NNMT, small-molecule NNMT inhibitors provide a novel therapeutic strategy for ccRCC and act as sensitizers for combination therapies.

Characterization of Genetic Heterogeneity in Recurrent Metastases of Renal Cell Carcinoma.

Metastatic renal cell carcinoma (RCC) exhibits poor prognosis. Better knowledge of distant metastases is crucial to foster personalized treatment strategies. Here, we aimed to investigate the genetic landscape of metastases, including synchronous and/or recurrent metastases to elucidate potential drug target genes and clinically relevant mutations in a real-world setting of patients. We assessed 81 metastases from 56 RCC patients, including synchronous and/or recurrent metastases of 19 patients. Samples were analysed through next-generation sequencing with a high coverage (~1000× mean coverage). We therefore established a novel sequencing panel comprising 32 genes with impact on RCC development. We observed a high frequency of mutations in known RCC driver genes (e.g., >40% carriers of VHL and PBRM1 mutations) in metastases irrespective of the metastatic site. The somatic mutational composition was significantly associated with cancer-specific survival (p(logrank) = 0.03). Moreover, we identified in 34 patients at least one drug target gene as well as clinically relevant mutations listed in the VICC Meta-Knowledgebase in 7%. In addition to significantly higher mutational burden in recurrent metastases compared to earlier ones, synchronous and/or recurrent metastases of individual patients, even after a time-period >2 yrs, shared a high proportion of somatic events. Our data demonstrate the importance of somatic profiling in metastases for precision medicine in RCC.

Gene Expression Signatures of BRCAness and Tumor Inflammation Define Subgroups of Early-Stage Hormone Receptor-Positive Breast Cancer Patients.

PURPOSE: Patients with estrogen receptor- and/or progesterone receptor-positive, early breast cancer benefit from hormonal treatment, yet high global death burdens due to high prevalence and long-term recurrence risk call for biomarkers to guide additional treatment approaches. EXPERIMENTAL DESIGN: From a prospective, observational study of postmenopausal early breast cancer patients treated with tamoxifen or aromatase inhibitors, gene expression analyses of 612 tumors was performed using the NanoString Breast Cancer 360 panel to interrogate 23 breast cancer pathways. Candidate signatures associated with disease subtype and event-free survival (EFS) were obtained by cluster analysis, Cox modeling, and conditional inference trees, and were independently tested in 613 patients from BreastMark. Tumor-infiltrating lymphocytes (TIL) were assessed on tissue sections, and mutational burden was assessed in 36 tumors by whole-exome sequencing. RESULTS: PAM50-derived classification distinguished lower-risk (Luminal A) from higher-risk subtypes (Luminal B, P = 0.04; HER2, P = 0.006; Basal, P = 0.008). In higher-risk patients, shorter EFS was associated with low androgen receptor [HR = 3.61; 95% confidence interval (CI), 1.72-7.56; P = 0.001] or high BRCAness signature expression (HR = 3.58; 95% CI, 1.19-10.7; P = 0.023). BRCAness was independently confirmed as a predictor of shorter EFS (HR = 2.64; 95% CI, 1.31-5.34; P = 0.007). About 13%-15% of patients, enriched for high-grade, higher-risk subtypes (P ≤ 0.0001), had strong expression of the Tumor Inflammation Signature (TIS) suggestive of an inhibited antitumor immune response. TIS scores were strongly associated with TIL numbers (P < 1e-30) but not with tumor mutation status. CONCLUSIONS: BRCA-related DNA repair deficiency and suppressed tumor immune responses may be clinically relevant predictors of endocrine therapy complementing treatment options in subgroups of hormone-sensitive early breast cancer.

Integrative -omics and HLA-ligandomics analysis to identify novel drug targets for ccRCC immunotherapy.

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 eighty-five 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 by immunogenicity analysis were able to activate naïve CD8+ T cells, including peptides derived from EGLN3. Functional analysis of EGLN3 revealed possible tumor-promoting functions. CONCLUSIONS: Integration of HLA ligandomics, transcriptomics, genetic, and epigenetic data leads to the identification of novel functionally relevant therapeutic targets for ccRCC immunotherapy. Validation of the identified targets is recommended to expand the treatment landscape of ccRCC.

Germline variant burden in multidrug resistance transporters is a therapy-specific predictor of survival in breast cancer patients.

Multidrug resistance due to facilitated drug efflux mediated by ATP-binding cassette (ABC) transporters is a main cause for failure of cancer therapy. Genetic polymorphisms in ABC genes affect the disposition of chemotherapeutics and constitute important biomarkers for therapeutic response and toxicity. Here we correlated germline variability in ABC transporters with disease-specific survival (DSS) in 960 breast cancer (BRCA), 314 clear cell renal cell carcinoma and 325 hepatocellular carcinoma patients. We find that variant burden in ABCC1 is a strong predictor of DSS in BRCA patients, whereas candidate polymorphisms are not associated with DSS. This association is highly drug-specific for subgroups treated with the MRP1 substrates cyclophosphamide (log-rank p = 0.0011) and doxorubicin (log-rank p = 0.0088) independent of age and tumor stage, whereas no association was found in individuals treated with tamoxifen (log-rank p = 0.13). Structural mapping of significant variants revealed multiple variants at residues involved in protein stability, cofactor stabilization or substrate binding. Our results demonstrate that BRCA patients with high variant burden in ABCC1 are less prone to respond appropriately to pharmacological therapy with MRP1 substrates, thus incentivizing the consideration of genomic germline data for precision cancer medicine.

Metabolic and Lipidomic Reprogramming in Renal Cell Carcinoma Subtypes Reflects Regions of Tumor Origin.

BACKGROUND: Renal cell carcinoma (RCC) consists of prognostic distinct subtypes derived from different cells of origin (eg, clear cell RCC [ccRCC], papillary RCC [papRCC], and chromophobe RCC [chRCC]). ccRCC is characterized by lipid accumulation and metabolic alterations, whereas data on metabolic alterations in non-ccRCC are limited. OBJECTIVE: We assessed metabolic alterations and the lipid composition of RCC subtypes and ccRCC-derived metastases. Moreover, we elucidated the potential of metabolites/lipids for subtype classification and identification of therapeutic targets. DESIGN, SETTING, AND PARTICIPANTS: Metabolomic/lipidomic profiles were quantified in ccRCC (n=58), chRCC (n=19), papRCC (n=14), corresponding nontumor tissues, and metastases (n=9) through a targeted metabolomic approach. Transcriptome profiling was performed in corresponding samples and compared with expression data of The Cancer Genome Atlas cohorts (patients with ccRCC, n=452; patients with papRCC, n=260; and patients with chRCC, n=59). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: In addition to cluster analyses, metabolomic/transcriptomic data were analyzed to evaluate metabolic differences of ccRCC and chRCC using Welch's t test or paired t test as appropriate. Where indicated, p values were adjusted for multiple testing using Bonferroni or Benjamini-Hochberg correction. RESULTS AND LIMITATIONS: Based on their metabolic profiles, RCC subtypes clustered into two groups separating ccRCC and papRCC from chRCC, which mainly reflected the different cells of origin. ccRCC-derived metastases clustered with primary ccRCCs. In addition to differences in certain lipids (lysophosphatidylcholines and sphingomyelins), the coregulation network of lipids differed between ccRCC and chRCC. Consideration of metabolic gene expression indicated, for example, alterations of the polyamine pathway at metabolite and transcript levels. In vitro treatment of RCC cells with the ornithine-decarboxylase inhibitor difluoromethylornithine resulted in reduced cell viability and mitochondrial activity. Further evaluation of clinical utility was limited by the retrospective study design and cohort size. CONCLUSIONS: In summary, we provide novel insight into the metabolic profiles of ccRCC and non-ccRCC, thereby confirming the different ontogeny of RCC subtypes. Quantification of differentially regulated metabolites/lipids improves classification of RCC with an impact on the identification of novel therapeutic targets. PATIENT SUMMARY: 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.

Characterization of the breast cancer resistance protein (BCRP/ABCG2) in clear cell renal cell carcinoma.

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.

Clinical utility of the S3-score for molecular prediction of outcome in non-metastatic and metastatic clear cell renal cell carcinoma.

BACKGROUND: Stratification of cancer patients to identify those with worse prognosis is increasingly important. Through in silico analyses, we recently developed a gene expression-based prognostic score (S3-score) for clear cell renal cell carcinoma (ccRCC), using the cell type-specific expression of 97 genes within the human nephron. Herein, we verified the score using whole-transcriptome data of independent cohorts and extend its application for patients with metastatic disease receiving tyrosine kinase inhibitor treatment. Finally, we sought to improve the signature for clinical application using qRT-PCR. METHODS: A 97 gene-based S3-score (S397) was evaluated in a set of 52 primary non-metastatic and metastatic ccRCC patients as well as in 53 primary metastatic tumors of sunitinib-treated patients. Gene expression data of The Cancer Genome Atlas (n = 463) was used for platform transfer and development of a simplified qRT-PCR-based 15-gene S3-score (S315). This S315-score was validated in 108 metastatic and non-metastatic ccRCC patients and ccRCC-derived metastases including in part several regions from one metastasis. Univariate and multivariate Cox regression stratified by T, N, M, and G were performed with cancer-specific and progression-free survival as primary endpoints. RESULTS: The S397-score was significantly associated with cancer-specific survival (CSS) in 52 ccRCC patients (HR 2.9, 95% Cl 1.0-8.0, PLog-rank = 3.3 × 10-2) as well as progression-free survival in sunitinib-treated patients (2.1, 1.1-4.2, PLog-rank = 2.2 × 10-2). The qRT-PCR based S315-score performed similarly to the S397-score, and was significantly associated with CSS in our extended cohort of 108 patients (5.0, 2.1-11.7, PLog-rank = 5.1 × 10-5) including metastatic (9.3, 1.8-50.0, PLog-rank = 2.3 × 10-3) and non-metastatic patients (4.4, 1.2-16.3, PLog-rank = 1.6 × 10-2), even in multivariate Cox regression, including clinicopathological parameters (7.3, 2.5-21.5, PWald = 3.3 × 10-4). Matched primary tumors and metastases revealed similar S315-scores, thus allowing prediction of outcome from metastatic tissue. The molecular-based qRT-PCR S315-score significantly improved prediction of CSS by the established clinicopathological-based SSIGN score (P = 1.6 × 10-3). CONCLUSION: The S3-score offers a new clinical avenue for ccRCC risk stratification in the non-metastatic, metastatic, and sunitinib-treated setting.

Comprehensive Metabolomic and Lipidomic Profiling of Human Kidney Tissue: A Platform Comparison.

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.

Profiles of miRNAs matched to biology in aromatase inhibitor resistant breast cancer.

Aromatase inhibitor (AI) resistance during breast cancer treatment is mimicked by MCF-7:5C (5C) and MCF-7:2A (2A) cell lines that grow spontaneously. Survival signaling is reconfigured but cells are vulnerable to estradiol (E2)-inducible apoptosis. These model systems have alterations of stress related pathways including the accumulation of endoplasmic reticulum, oxidative, and inflammatory stress that occur prior to E2-induced apoptosis. We investigated miRNA expression profiles of 5C and 2A to characterize their AI resistance phenotypes. Affymetrix GeneChip miRNA2.0 arrays identified 184 miRNAs differentially expressed in 2A and 5C compared to E2-free wild-type MCF-7:WS8. In 5C, 34 miRNAs of the DLK1-DIO3 locus and miR-31 were overexpressed, whereas miR-222 was low. TCGA data revealed poor and favorable overall survival for low miR-31 and miR-222 levels, respectively (HR=3.0, 95% CI:1.9-4.8; HR=0.3, 95% CI:0.1-0.6). Targets of deregulated miRNAs were identified using CLIP-confirmed TargetScan predictions. KEGG enrichment analyses for 5C- and 2A-specific target gene sets revealed pathways associated with cell proliferation including insulin, mTOR, and ErbB signaling as well as immune response and metabolism. Key genes overrepresented in 5C- and 2A-specific pathway interaction networks including EGFR, IGF1R and PIK3R1 had lower protein levels in 5C compared to 2A and were found to be differentially modulated by respective miRNA sets. Distinct up-regulated miRNAs from the DLK1-DIO3 locus may cause these attenuative effects as they are predicted to interact with corresponding 3' untranslated regions. These new miRNA profiles become an important regulatory database to explore E2-induced apoptotic mechanisms of clinical relevance for the treatment of resistant breast cancer.