Conventional and semi-automatic histopathological analysis of tumor cell content for multigene sequencing of lung adenocarcinoma.

BACKGROUND: Targeted genetic profiling of tissue samples is paramount to detect druggable genetic aberrations in patients with non-squamous non-small cell lung cancer (NSCLC). Accurate upfront estimation of tumor cell content (TCC) is a crucial pre-analytical step for reliable testing and to avoid false-negative results. As of now, TCC is usually estimated on hematoxylin-eosin (H&E) stained tissue sections by a pathologist, a methodology that may be prone to substantial intra- and interobserver variability. Here we the investigate suitability of digital pathology for TCC estimation in a clinical setting by evaluating the concordance between semi-automatic and conventional TCC quantification. METHODS: TCC was analyzed in 120 H&E and thyroid transcription factor 1 (TTF-1) stained high-resolution images by 19 participants with different levels of pathological expertise as well as by applying two semi-automatic digital pathology image analysis tools (HALO and QuPath). RESULTS: Agreement of TCC estimations [intra-class correlation coefficients (ICC)] between the two software tools (H&E: 0.87; TTF-1: 0.93) was higher compared to that between conventional observers (0.48; 0.47). Digital TCC estimations were in good agreement with the average of human TCC estimations (0.78; 0.96). Conventional TCC estimators tended to overestimate TCC, especially in H&E stainings, in tumors with solid patterns and in tumors with an actual TCC close to 50%. CONCLUSIONS: Our results determine factors that influence TCC estimation. Computer-assisted analysis can improve the accuracy of TCC estimates prior to molecular diagnostic workflows. In addition, we provide a free web application to support self-training and quality improvement initiatives at other institutions.

Targeting rare and non-canonical driver variants in NSCLC - An uncharted clinical field.

OBJECTIVES: Implementation of tyrosine kinase inhibitors (TKI) and other targeted therapies was a main advance in thoracic oncology with survival gains ranging from several months to years for non-small-cell lung cancer (NSCLC) patients. High-throughput comprehensive molecular profiling is of key importance to identify patients that can potentially benefit from these novel treatments. MATERIAL AND METHODS: Next-generation sequencing (NGS) was performed on 4500 consecutive formalin-fixed, paraffin-embedded specimens of advanced NSCLC (n = 4172 patients) after automated extraction of DNA and RNA for parallel detection of mutations and gene fusions, respectively. RESULTS AND CONCLUSION: Besides the 24.9 % (n = 1040) of cases eligible for approved targeted therapies based on the presence of canonical alterations in EGFR exons 18-21, BRAF, ROS1, ALK, NTRK, and RET, an additional n = 1260 patients (30.2 %) displayed rare or non-canonical mutations in EGFR (n = 748), BRAF (n = 135), ERBB2 (n = 30), KIT (n = 32), PIK3CA (n = 221), and CTNNB1 (n = 94), for which targeted therapies could also be potentially effective. A systematic literature search in conjunction with in silico evaluation identified n = 232 (5.5 %) patients, for which a trial of targeted treatment would be warranted according to available evidence (NCT level 1, i.e. published data showing efficacy in the same tumor entity). In conclusion, a sizeable fraction of NSCLC patients harbors rare or non-canonical alterations that may be associated with clinical benefit from currently available targeted drugs. Systematic identification and individualized management of these cases can expand applicability of precision oncology in NSCLC and extend clinical gain from established molecular targets. These results can also inform clinical trials.

Subtype specific expression and survival prediction of pivotal lncRNAs in muscle invasive bladder cancer.

Comprehensive transcriptome expression analyses of bladder cancer revealed distinct lncRNA clusters with differential molecular and clinical characteristics. In this study, pivotal lncRNAs were assessed for their impact on survival and their differential expression between the molecular bladder cancer subtypes. FFPE samples from chemotherapy-naïve patients with muscle invasive bladder cancer (MIBC) were analyzed on the Nanostring nCounter platform for absolute quantification. An established 36-gene panel was used for molecular subtype classification into basal, luminal and infiltrated MIBC. In a second step, 14 pivotal lncRNAs were assessed for their molecular subtype attribution, and their predictive value in disease-specific survival. In silico validation was performed on a total of 487 MIBC patients (MDA, TGCA and Chungbuk cohort). Several pivotal lncRNAs showed a distinct molecular subtype attribution: e.g. MALAT1 showed a downregulation in the basal subtype (p = 0.009), TUG1 and CBR3AS1 showed an upregulation in the luminal subtype (p ≤ 0.001). High transcript levels of SNHG16, CBR3AS1 and H19 appeared to be predictive for a shorter disease-specific survival. Patients overexpressing putative oncogenes MALAT1 and TUG1 in MIBC tissue presented prolonged survival, suggesting tumor suppressive effects of both lncRNAs. The Nanostring nCounter proved to be a valid platform for the quantification of low-abundance transcripts including lncRNAs.

YAP Orchestrates Heterotypic Endothelial Cell Communication via HGF/c-MET Signaling in Liver Tumorigenesis.

The oncogene yes-associated protein (YAP) controls liver tumor initiation and progression via cell extrinsic functions by creating a tumor-supporting environment in conjunction with cell autonomous mechanisms. However, how YAP controls organization of the microenvironment and in particular the vascular niche, which contributes to liver disease and hepatocarcinogenesis, is poorly understood. To investigate heterotypic cell communication, we dissected murine and human liver endothelial cell (EC) populations into liver sinusoidal endothelial cells (LSEC) and continuous endothelial cells (CEC) through histomorphological and molecular characterization. In YAPS127A-induced tumorigenesis, a gradual replacement of LSECs by CECs was associated with dynamic changes in the expression of genes involved in paracrine communication. The formation of new communication hubs connecting CECs and LSECs included the hepatocyte growth factor (Hgf)/c-Met signaling pathway. In hepatocytes and tumor cells, YAP/TEA domain transcription factor 4 (TEAD4)-dependent transcriptional induction of osteopontin (Opn) stimulated c-Met expression in EC with CEC phenotype, which sensitized these cells to the promigratory effects of LSEC-derived Hgf. In human hepatocellular carcinoma, the presence of a migration-associated tip-cell signature correlated with poor clinical outcome and the loss of LSEC marker gene expression. The occurrence of c-MET-expressing CECs in human liver cancer samples was confirmed at the single-cell level. In summary, YAP-dependent changes of the liver vascular niche comprise the formation of heterologous communication hubs in which tumor cell-derived factors modify the cross-talk between LSECs and CECs via the HGF/c-MET axis. SIGNIFICANCE: YAP-dependent changes of the liver vascular niche comprise the formation of heterologous communication hubs in which tumor cell-derived factors modify the cross-talk between EC subpopulations. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/80/24/5502/F1.large.jpg.

Quantifying potential confounders of panel-based tumor mutational burden (TMB) measurement.

OBJECTIVES: Retrospective data including subgroup analyses in clinical studies have sparked strong interest in developing tumor mutational burden (TMB) as a predictive biomarker for immune checkpoint blockade. While individual factors influencing panel sequencing based measurement of TMB (psTMB) have been discussed in the recent literature, an integrative study quantifying, comparing and combining all potential confounders is still missing. MATERIAL AND METHODS: We separated different potential confounders of psTMB measurement including "panel size", "germline mutation filtering", "biological variance" and "technical variance" and developed a specific error model for each of these factors. Published experimental psTMB data were fitted to the error models to quantify the contribution of each of the confounders. The total psTMB variance was obtained as sum over the variance contributions of each of the confounders. RESULTS: Using a typical large panel (size 1-1.5 Mbp) total errors of 57 %, 42 %, 34 % and 28 % were observed for tumors with psTMB of 5, 10, 20 and 40 muts/Mbp. Even for large panels, the stochastic error connected to the panel size represented the largest of all contributions to the total psTMB variance, especially for tumors with TMB up to 20 muts/Mbp. Other sources of psTMB variability could be kept under control, but rigorous quality control, best practice laboratory workflows and optimized bioinformatics pipelines are essential. CONCLUSION: A statistical framework for the analysis of complex, genomic biomarkers was developed and applied to the analysis of psTMB variability. The methods developed here can support the analysis of other quantitative biomarkers and their implementation in clinical practice.

Immuno-oncology gene expression profiling of formalin-fixed and paraffin-embedded clear cell renal cell carcinoma: Performance comparison of the NanoString nCounter technology with targeted RNA sequencing.

Inflammatory gene signatures are currently being explored as predictive biomarkers for immune checkpoint blockade, and particularly for the treatment of renal cell cancers. From a diagnostic point of view, the nCounter analysis platform and targeted RNA sequencing are emerging alternatives to microarrays and comprehensive transcriptome sequencing in assessing formalin-fixed and paraffin-embedded (FFPE) cancer samples. So far, no systematic study has analyzed and compared the technical performance metrics of these two approaches. Filling this gap, we performed a head-to-head comparison of two commercially available immune gene expression assays, using clear cell renal cell cancer FFPE specimens. We compared the nCounter system that utilizes a direct hybridization technology without amplification with an NGS assay that is based on targeted RNA-sequencing with preamplification. We found that both platforms displayed high technical reproducibility and accuracy (Pearson coefficient: ≥0.96, concordance correlation coefficient [CCC]: ≥0.93). A density plot for normalized expression of shared genes on both platforms showed a comparable bi-modal distribution and dynamic range. RNA-Seq demonstrated relatively larger signaling intensity whereas the nCounter system displayed higher inter-sample variability. Estimated fold changes for all shared genes showed high correlation (Spearman coefficient: 0.73). This agreement is even better when only significantly differentially expressed genes were compared. Composite gene expression profiles, such as an interferon gamma (IFNg) signature, can be reliably inferred by both assays. In summary, our study demonstrates that focused transcript read-outs can reliably be achieved by both technologies and that both approaches achieve comparable results despite their intrinsic technical differences.

Harmonization and Standardization of Panel-Based Tumor Mutational Burden Measurement: Real-World Results and Recommendations of the Quality in Pathology Study.

INTRODUCTION: Tumor mutational burden (TMB) is a quantitative assessment of the number of somatic mutations within a tumor genome. Immunotherapy benefit has been associated with TMB assessed by whole-exome sequencing (wesTMB) and gene panel sequencing (psTMB). The initiatives of Quality in Pathology (QuIP) and Friends of Cancer Research have jointly addressed the need for harmonization among TMB testing options in tissues. This QuIP study identifies critical sources of variation in psTMB assessment. METHODS: A total of 20 samples from three tumor types (lung adenocarcinoma, head and neck squamous cell carcinoma, and colon adenocarcinoma) with available WES data were analyzed for psTMB using six panels across 15 testing centers. Interlaboratory and interplatform variation, including agreement on variant calling and TMB classification, were investigated. Bridging factors to transform psTMB to wesTMB values were empirically derived. The impact of germline filtering was evaluated. RESULTS: Sixteen samples had low interlaboratory and interpanel psTMB variation, with 87.7% of pairwise comparisons revealing a Spearman's ρ greater than 0.6. A wesTMB cut point of 199 missense mutations projected to psTMB cut points between 7.8 and 12.6 mutations per megabase pair; the corresponding psTMB and wesTMB classifications agreed in 74.9% of cases. For three-tier classification with cut points of 100 and 300 mutations, agreement was observed in 76.7%, weak misclassification in 21.8%, and strong misclassification in 1.5% of cases. Confounders of psTMB estimation included fixation artifacts, DNA input, sequencing depth, genome coverage, and variant allele frequency cut points. CONCLUSIONS: This study provides real-world evidence that all evaluated panels can be used to estimate TMB in a routine diagnostic setting and identifies important parameters for reliable tissue TMB assessment that require careful control. As complex or composite biomarkers beyond TMB are likely playing an increasing role in therapy prediction, the efforts by QuIP and Friends of Cancer Research also delineate a general framework and blueprint for the evaluation of such assays.

RNA-Based Detection of Gene Fusions in Formalin-Fixed and Paraffin-Embedded Solid Cancer Samples.

Oncogenic gene fusions are important drivers in many cancer types, including carcinomas, with diagnostic and therapeutic implications. Hence, sensitive and rapid methods for parallel profiling in formalin-fixed and paraffin-embedded (FFPE) specimens are needed. In this study we analyzed gene fusions in a cohort of 517 cases where standard treatment options were exhausted. To this end the Archer® DX Solid tumor panel (AMP; 285 cases) and the Oncomine Comprehensive Assay v3 (OCA; 232 cases) were employed. Findings were validated by Sanger sequencing, fluorescence in situ hybridization (FISH) or immunohistochemistry. Both assays demonstrated minimal dropout rates (AMP: 2.4%; n = 7/292, OCA: 2.1%; n = 5/237) with turnaround times of 6-9 working days (median, OCA and AMP, respectively). Hands-on-time for library preparation was 6 h (AMP) and 2 h (OCA). We detected n = 40 fusion-positive cases (7.7%) with TMPRSS2::ERG in prostate cancer being most prevalent (n = 9/40; 22.5%), followed by other gene fusions identified in cancers of unknown primary (n = 6/40; 15.0%), adenoid cystic carcinoma (n = 7/40; 17.5%), and pancreatic cancer (n = 7/40; 17.5%). Our results demonstrate that targeted RNA-sequencing of FFPE samples is feasible, and a well-suited approach for the detection of gene fusions in a routine clinical setting.

Spatial and Temporal Heterogeneity of Panel-Based Tumor Mutational Burden in Pulmonary Adenocarcinoma: Separating Biology From Technical Artifacts.

BACKGROUND: Tumor mutational burden (TMB) is an emerging biomarker used to identify patients who are more likely to benefit from immuno-oncology therapy. Aside from various unsettled technical aspects, biological variables such as tumor cell content and intratumor heterogeneity may play an important role in determining TMB. METHODS: TMB estimates were determined applying the TruSight Oncology 500 targeted sequencing panel. Spatial and temporal heterogeneity was analyzed by multiregion sequencing (two to six samples) of 24 pulmonary adenocarcinomas and by sequencing a set of matched primary tumors, locoregional lymph node metastases, and distant metastases in five patients. RESULTS: On average, a coding region of 1.28 Mbp was covered with a mean read depth of 609x. Manual validation of the mutation-calls confirmed a good performance, but revealed noticeable misclassification during germline filtering. Different regions within a tumor showed considerable spatial TMB variance in 30% (7 of 24) of the cases (maximum difference, 14.13 mut/Mbp). Lymph node-derived TMB was significantly lower (p = 0.016). In 13 cases, distinct mutational profiles were exclusive to different regions of a tumor, leading to higher values for simulated aggregated TMB. Combined, intratumor heterogeneity and the aggregated TMB could result in divergent TMB designation in 17% of the analyzed patients. TMB variation between primary tumor and distant metastases existed but was not profound. CONCLUSIONS: Our data show that, in addition to technical aspects such as germline filtering, the tumor content and spatially divergent mutational profiles within a tumor are relevant factors influencing TMB estimation, revealing limitations of single-sample-based TMB estimations in a clinical context.

Variant classification in precision oncology.

Next-generation sequencing has become a cornerstone of therapy guidance in cancer precision medicine and an indispensable research tool in translational oncology. Its rapidly increasing use during the last decade has expanded the options for targeted tumor therapies, and molecular tumor boards have grown accordingly. However, with increasing detection of genetic alterations, their interpretation has become more complex and error-prone, potentially introducing biases and reducing benefits in clinical practice. To facilitate interdisciplinary discussions of genetic alterations for treatment stratification between pathologists, oncologists, bioinformaticians, genetic counselors and medical scientists in specialized molecular tumor boards, several systems for the classification of variants detected by large-scale sequencing have been proposed. We review three recent and commonly applied classifications and discuss their individual strengths and weaknesses. Comparison of the classifications underlines the need for a clinically useful and universally applicable variant reporting system, which will be instrumental for efficient decision making based on sequencing analysis in oncology. Integrating these data, we propose a generalizable classification concept featuring a conservative and a more progressive scheme, which can be readily applied in a clinical setting.

RSPO2 gene rearrangement: a powerful driver of ß-catenin activation in liver tumours.

OBJECTIVE: We aimed at the identification of genetic alterations that may functionally substitute for CTNNB1 mutation in ß-catenin-activated hepatocellular adenomas (HCAs) and hepatocellular carcinoma (HCC). DESIGN: Large cohorts of HCA (n=185) and HCC (n=468) were classified using immunohistochemistry. The mutational status of the CTNNB1 gene was determined in ß-catenin-activated HCA (b-HCA) and HCC with at least moderate nuclear CTNNB1 accumulation. Ultra-deep sequencing was used to characterise CTNNB1wild-type and ß-catenin-activated HCA and HCC. Expression profiling of HCA subtypes was performed. RESULTS: A roof plate-specific spondin 2 (RSPO2) gene rearrangement resulting from a 46.4 kb microdeletion on chromosome 8q23.1 was detected as a new morphomolecular driver of ß-catenin-activated HCA. RSPO2 fusion positive HCA displayed upregulation of RSPO2 protein, nuclear accumulation of ß-catenin and transcriptional activation of ß-catenin-target genes indicating activation of Wingless-Type MMTV Integration Site Family (WNT) signalling. Architectural and cytological atypia as well as interstitial invasion indicated malignant transformation in one of the RSPO2 rearranged b-HCAs. The RSPO2 gene rearrangement was also observed in three ß-catenin-activated HCCs developing in context of chronic liver disease. Mutations of the human telomerase reverse transcriptase promoter-known to drive malignant transformation of CTNNB1-mutated HCA-seem to be dispensable for RSPO2 rearranged HCA and HCC. CONCLUSION: The RSPO2 gene rearrangement leads to oncogenic activation of the WNT signalling pathway in HCA and HCC, represents an alternative mechanism for the development of b-HCA and may drive malignant transformation without additional TERT promoter mutation.

Combined targeted DNA and RNA sequencing of advanced NSCLC in routine molecular diagnostics: Analysis of the first 3,000 Heidelberg cases.

Tyrosine kinase inhibitors currently confer the greatest survival gain for nonsmall cell lung cancer (NSCLC) patients with actionable genetic alterations. Simultaneously, the increasing number of targets and compounds poses the challenge of reliable, broad and timely molecular assays for the identification of patients likely to benefit from novel treatments. Here, we demonstrate the feasibility and clinical utility of comprehensive, NGS-based genetic profiling for routine workup of advanced NSCLC based on the first 3,000 patients analyzed in our department. Following automated extraction of DNA and RNA from formalin-fixed, paraffin-embedded tissue samples, parallel sequencing of DNA and RNA for detection of mutations and gene fusions, respectively, was performed using PCR-based enrichment with an ion semiconductor sequencing platform. Overall, 807 patients (27%) were eligible for currently approved, EGFR-/BRAF-/ALK- and ROS1-directed therapies, while 218 additional cases (7%) with MET, ERBB2 (HER2) and RET alterations could potentially benefit from experimental targeted compounds. In addition, routine capturing of comutations, e.g. TP53 (55%), KEAP1 (11%) and STK11 (11%), as well as the precise typing of fusion partners and involved exons in case of actionable translocations including ALK and ROS1, are prognostic and predictive tools currently gaining importance for further refinement of therapeutic and surveillance strategies. The reliability, low dropout rates (<5%), minimal tissue requirements, fast turnaround times (6 days on average) and lower costs of the diagnostic approach presented here compared to sequential single-gene testing, highlight its practicability in order to support individualized decisions in routine patient care, enrollment in molecularly stratified clinical trials, as well as translational research.

Size matters: Dissecting key parameters for panel-based tumor mutational burden analysis.

Tumor mutational burden (TMB) represents a new determinant of clinical benefit from immune checkpoint blockade that identifies responders independent of PD-L1 expression levels and is currently being explored in clinical trials. Although TMB can be measured directly by comprehensive genomic approaches such as whole-genome and exome sequencing, broad availability, short turnaround times, costs and amenability to formalin-fixed and paraffin-embedded tissue support the use of gene panel sequencing for approximating TMB in routine diagnostics. However, data on the parameters influencing panel-based TMB estimation are limited. Here, we report an extensive in silico analysis of the TCGA data set that simulates various panel sizes and compositions. We demonstrate that panel size is a critical parameter that influences confidence intervals (CIs) and cutoff values as well as important test parameters including sensitivity, specificity, and positive predictive value. Moreover, we evaluate the Illumina TSO500 panel, which will be made available for TMB estimation, and propose dynamic, entity-specific cutoff values based on current clinical trial data. Optimizing the cost-benefit ratio, our data suggest that panels between 1.5 and 3 Mbp are ideally suited to estimate TMB with small CIs, whereas smaller panels tend to deliver imprecise TMB estimates for low to moderate TMB (0-30 muts/Mbp), connected with insufficient separation of hypermutated tumors from non-hypermutated tumors.

Measurement of tumor mutational burden (TMB) in routine molecular diagnostics: in silico and real-life analysis of three larger gene panels.

Assessment of Tumor Mutational Burden (TMB) for response stratification of cancer patients treated with immune checkpoint inhibitors is emerging as a new biomarker. Commonly defined as the total number of exonic somatic mutations, TMB approximates the amount of neoantigens that potentially are recognized by the immune system. While whole exome sequencing (WES) is an unbiased approach to quantify TMB, implementation in diagnostics is hampered by tissue availability as well as time and cost constrains. Conversely, panel-based targeted sequencing is nowadays widely used in routine molecular diagnostics, but only very limited data are available on its performance for TMB estimation. Here, we evaluated three commercially available larger gene panels with covered genomic regions of 0.39 Megabase pairs (Mbp), 0.53 Mbp and 1.7 Mbp using i) in silico analysis of TCGA (The Cancer Genome Atlas) data and ii) wet-lab sequencing of a total of 92 formalin-fixed and paraffin-embedded (FFPE) cancer samples grouped in three independent cohorts (non-small cell lung cancer, NSCLC; colorectal cancer, CRC; and mixed cancer types) for which matching WES data were available. We observed a strong correlation of the panel data with WES mutation counts especially for the gene panel >1Mbp. Sensitivity and specificity related to TMB cutpoints for checkpoint inhibitor response in NSCLC determined by wet-lab experiments well reflected the in silico data. Additionally, we highlight potential pitfalls in bioinformatics pipelines and provide recommendations for variant filtering. In summary, our study is a valuable data source for researchers working in the field of immuno-oncology as well as for diagnostic laboratories planning TMB testing.

Implementing tumor mutational burden (TMB) analysis in routine diagnostics-a primer for molecular pathologists and clinicians.

Tumor mutational burden (TMB) is a new biomarker for prediction of response to PD-(L)1 treatment. Comprehensive sequencing approaches (i.e., whole exome and whole genome sequencing) are ideally suited to measure TMB directly. However, as their applicability in routine diagnostics is currently limited by high costs, long turnaround times and poor availability of fresh tissue, targeted next-generation sequencing (NGS) of formalin-fixed and paraffin-embedded (FFPE) samples appears to be a more feasible and straight-forward approach for TMB approximation, which can be seamlessly integrated in already existing diagnostic workflows and pipelines. In this work, we provide an overview of the clinical implications of TMB testing and highlight key parameters including pre-analysis, analysis and post-analytical steps that influence and shape TMB approximation by panel sequencing. Collectively, the data will not only serve as a field guide and state of the art knowledge source for molecular pathologists who consider implementation of TMB measurement in their lab, but also enable clinicians in understanding the specific parameters influencing TMB test results and reporting.

WEADE: A workflow for enrichment analysis and data exploration.

Data analysis based on enrichment of Gene Ontology terms has become an important step in exploring large gene or protein expression datasets and several stand-alone or web tools exist for that purpose. However, a comprehensive and consistent analysis downstream of the enrichment calculation is missing so far. With WEADE we present a free web application that offers an integrated workflow for the exploration of genomic data combining enrichment analysis with a versatile set of tools to directly compare and intersect experiments or candidate gene lists of any size or origin including cross-species data. Lastly, WEADE supports the graphical representation of output data in the form of functional interaction networks based on prior knowledge, allowing users to go from plain expression data to functionally relevant candidate sub-lists in an interactive and consistent manner.

Decoding the Regulatory Logic of the Drosophila Male Stem Cell System.

The niche critically controls stem cell behavior, but its regulatory input at the whole-genome level is poorly understood. We elucidated transcriptional programs of the somatic and germline lineages in the Drosophila testis and genome-wide binding profiles of Zfh-1 and Abd-A expressed in somatic support cells and crucial for fate acquisition of both cell lineages. We identified key roles of nucleoporins and V-ATPase proton pumps and demonstrate their importance in controlling germline development from the support side. To make our dataset publicly available, we generated an interactive analysis tool, which uncovered conserved core genes of adult stem cells across species boundaries. We tested the functional relevance of these genes in the Drosophila testis and intestine and found a high frequency of stem cell defects. In summary, our dataset and interactive platform represent versatile tools for identifying gene networks active in diverse stem cell types.

Subclassification, survival prediction and drug target analyses of chemotherapy-naïve muscle-invasive bladder cancer with a molecular screening.

BACKGROUND: Transcriptome expression studies identified distinct muscle invasive bladder cancer (MIBC) subtypes closely related with breast cancer subclasses. Here we developed a sensitive quantification method for MIBC subclassification (luminal, basal, p53-like). In addition, the subtype specific expression of drug targets has been investigated. METHODS: Absolute quantification (nCounter) of a 64-gene panel was performed on MIBC patients (n=47) treated exclusively with radical cystectomy (RC). In conjunction of 170 MIBCs from 3 independent cohorts, a minimal set of consensus genes has been established. Survival of the consensus subtypes has been assessed by multivariate analysis. Relevant drug targets were tested for their subtype specificity in a clustering independent assessment. RESULTS: A reduced 36-gene panel stably clustered into 3 subtypes throughout the cohorts (luminal, basal, infiltrated). Patients treated by RC only, showed worst 8-year disease specific survival (DSS) for the luminal subtype in contrast to the infiltrated subtype (17% vs. 73%, p=0.011). In multivariate analyses, the risk stratification based on luminal versus not-luminal MIBC proved to be an independent predictor for DSS superior to the TNM system in patients with RC. Drug targets (e.g. ERBB2, FGFR, AR, PDGFRB) showed a distinct subtype attribution. The subtypes based on this nCounter screening could further be validated by the TCGA cohort. CONCLUSION: This MIBC subtype screening predicted survival and allowed an analysis of subtype specific drug targets, thus being a powerful tool for the translation of personalized MIBC treatment concepts.

The molecular signature of AML with increased ALDH activity suggests a stem cell origin.

Enrichment of leukemic blasts with a stem cell phenotype correlates with poor survival in acute myeloid leukemia (AML). In this context, measurement of the stem cell marker aldehyde-dehydrogenase (ALDH) activity can distinguish poor prognosis cases with increased fractions of ALDH-positive cells (ALDH-numerous AML) and favorable outcome cases with low percentages (ALDH-rare AML). It has been shown that ALDH-numerous AML favor leukemic engraftment in xenotransplantation assays which suggests increased leukemic stem cell (LSC) potential. To test if this reflects an immature cell of origin, comparative gene-expression studies of CD34+ leukemic blasts were performed. This analysis revealed increased expression of LSC and HSC signatures in ALDH-numerous AML, whereas ALDH-rare AML were enriched for a progenitor signature. The enrichment of stemness-associated transcriptional programs suggests that ALDH-numerous AML derive from immature hematopoietic progenitors and offers an explanation for the poor prognosis and therapy resistance of this subgroup which is likely caused by inherited stem cell properties.