Transurethral Vapor Ablation in Patients with Intermediate-Risk Localized Prostate Cancer.

Purpose: We report results of a prospective, multicenter single-arm study of transurethral vapor ablation (TUVA) of prostate tissue in patients with unilateral, intermediate-risk, localized prostate cancer (PCa). Materials and Methods: Men ≥45 years of age with biopsy-confirmed unilateral Gleason grade group 2 (GGG2) adenocarcinoma of the prostate, prostate volume of 20-80 cc, and prostate-specific antigen (PSA) ≤15 ng/mL were enrolled. Cystoscopy and transrectal ultrasound (TRUS) guidance were used to deliver ∼103°C water vapor to prostate zones for unilateral hemigland ablation, including destruction of cancers detected by multiparametric MRI (mpMRI) and confirmed by biopsy. The primary outcomes were device-related serious adverse events (SAEs). At 7 days and 6 months postprocedure, the ablation extent was assessed by mpMRI; MRI/TRUS fusion biopsies were completed at 6 months. Quality of life (QOL) was assessed with validated questionnaires. Results: All subjects underwent a single hemigland TUVA procedure. No SAEs occurred. Grade 2 procedure-related AEs included transient urinary retention (n = 4) and erectile (n = 1) or ejaculatory dysfunction (n = 1). At 7 days, mpMRI revealed complete ablation of 14/17 (82%) visible lesions. At 6 months, biopsies showed no Gleason pattern ≥4 or ≥GGG2 cancer on the treated side of prostates in 13/15 (87%) subjects. Ten of 15 (67%) subjects were biopsy negative. Of the 5 biopsy-negative subjects, 2 had one core each of 3 + 4 disease and 3 had one core each of 3 + 3 disease with ≤5% involvement. Median prostate volume was reduced by 40.7% and PSA by 58%. Extensive QOL assessments showed, on average, no appreciable negative effects of treatment. Conclusions: Initial evidence suggests that TUVA is safe in men with intermediate-risk PCa. Preliminary results demonstrate the absence of ≥GGG2 disease on the treated side in 87% of men and a favorable QOL profile.

Snail acetylation by autophagy-derived acetyl-coenzyme A promotes invasion and metastasis of KRAS-LKB1 co-mutated lung cancer cells.

BACKGROUND: Autophagy is elevated in metastatic tumors and is often associated with active epithelial-to-mesenchymal transition (EMT). However, the extent to which EMT is dependent on autophagy is largely unknown. This study aimed to identify the mechanisms by which autophagy facilitates EMT. METHODS: We employed a liquid chromatography-based metabolomic approach with kirsten rat sarcoma viral oncogene (KRAS) and liver kinase B1 (LKB1) gene co-mutated (KL) cells that represent an autophagy/EMT-coactivated invasive lung cancer subtype for the identification of metabolites linked to autophagy-driven EMT activation. Molecular mechanisms of autophagy-driven EMT activation were further investigated by quantitative real-time polymerase chain reaction (qRT-PCR), Western blotting analysis, immunoprecipitation, immunofluorescence staining, and metabolite assays. The effects of chemical and genetic perturbations on autophagic flux were assessed by two orthogonal approaches: microtubule-associated protein 1A/1B-light chain 3 (LC3) turnover analysis by Western blotting and monomeric red fluorescent protein-green fluorescent protein (mRFP-GFP)-LC3 tandem fluorescent protein quenching assay. Transcription factor EB (TFEB) activity was measured by coordinated lysosomal expression and regulation (CLEAR) motif-driven luciferase reporter assay. Experimental metastasis (tail vein injection) mouse models were used to evaluate the impact of calcium/calmodulin-dependent protein kinase kinase 2 (CAMKK2) or ATP citrate lyase (ACLY) inhibitors on lung metastasis using IVIS luciferase imaging system. RESULTS: We found that autophagy in KL cancer cells increased acetyl-coenzyme A (acetyl-CoA), which facilitated the acetylation and stabilization of the EMT-inducing transcription factor Snail. The autophagy/acetyl-CoA/acetyl-Snail axis was further validated in tumor tissues and in autophagy-activated pancreatic cancer cells. TFEB acetylation in KL cancer cells sustained pro-metastatic autophagy in a mammalian target of rapamycin complex 1 (mTORC1)-independent manner. Pharmacological inhibition of this axis via CAMKK2 inhibitors or ACLY inhibitors consistently reduced the metastatic capacity of KL cancer cells in vivo. CONCLUSIONS: This study demonstrates that autophagy-derived acetyl-CoA promotes Snail acetylation and thereby facilitates invasion and metastasis of KRAS-LKB1 co-mutated lung cancer cells and that inhibition of the autophagy/acetyl-CoA/acetyl-Snail axis using CAMKK2 or ACLY inhibitors could be a potential therapeutic strategy to suppress metastasis of KL lung cancer.

Expanding control of the tumor cell cycle with a CDK2/4/6 inhibitor.

The CDK4/6 inhibitor, palbociclib (PAL), significantly improves progression-free survival in HR+/HER2- breast cancer when combined with anti-hormonals. We sought to discover PAL resistance mechanisms in preclinical models and through analysis of clinical transcriptome specimens, which coalesced on induction of MYC oncogene and Cyclin E/CDK2 activity. We propose that targeting the G1 kinases CDK2, CDK4, and CDK6 with a small-molecule overcomes resistance to CDK4/6 inhibition. We describe the pharmacodynamics and efficacy of PF-06873600 (PF3600), a pyridopyrimidine with potent inhibition of CDK2/4/6 activity and efficacy in multiple in vivo tumor models. Together with the clinical analysis, MYC activity predicts (PF3600) efficacy across multiple cell lineages. Finally, we find that CDK2/4/6 inhibition does not compromise tumor-specific immune checkpoint blockade responses in syngeneic models. We anticipate that (PF3600), currently in phase 1 clinical trials, offers a therapeutic option to cancer patients in whom CDK4/6 inhibition is insufficient to alter disease progression.

Exocyst protein subnetworks integrate Hippo and mTOR signaling to promote virus detection and cancer.

The exocyst is an evolutionarily conserved protein complex that regulates vesicular trafficking and scaffolds signal transduction. Key upstream components of the exocyst include monomeric RAL GTPases, which help mount cell-autonomous responses to trophic and immunogenic signals. Here, we present a quantitative proteomics-based characterization of dynamic and signal-dependent exocyst protein interactomes. Under viral infection, an Exo84 exocyst subcomplex assembles the immune kinase Protein Kinase R (PKR) together with the Hippo kinase Macrophage Stimulating 1 (MST1). PKR phosphorylates MST1 to activate Hippo signaling and inactivate Yes Associated Protein 1 (YAP1). By contrast, a Sec5 exocyst subcomplex recruits another immune kinase, TANK binding kinase 1 (TBK1), which interacted with and activated mammalian target of rapamycin (mTOR). RALB was necessary and sufficient for induction of Hippo and mTOR signaling through parallel exocyst subcomplex engagement, supporting the cellular response to virus infection and oncogenic signaling. This study highlights RALB-exocyst signaling subcomplexes as mechanisms for the integrated engagement of Hippo and mTOR signaling in cells challenged by viral pathogens or oncogenic signaling.

A Gene Expression High-Throughput Screen (GE-HTS) for Coordinated Detection of Functionally Similar Effectors in Cancer.

Genome-wide, loss-of-function screening can be used to identify novel vulnerabilities upon which specific tumor cells depend for survival. Functional Signature Ontology (FUSION) is a gene expression-based high-throughput screening (GE-HTS) method that allows researchers to identify functionally similar proteins, small molecules, and microRNA mimics, revealing novel therapeutic targets. FUSION uses cell-based high-throughput screening and computational analysis to match gene expression signatures produced by natural products to those produced by small interfering RNA (siRNA) and synthetic microRNA libraries to identify putative protein targets and mechanisms of action (MoA) for several previously undescribed natural products. We have used FUSION to screen for functional analogues to Kinase suppressor of Ras 1 (KSR1), a scaffold protein downstream of Ras in the Raf-MEK-ERK kinase cascade, and biologically validated several proteins with functional similarity to KSR1. FUSION incorporates bioinformatics analysis that may offer higher resolution of the endpoint readout than other screens which utilize Boolean outputs regarding a single pathway activation (i.e., synthetic lethal and cell proliferation). Challenges associated with FUSION and other high-content genome-wide screens include variation, batch effects, and controlling for potential off-target effects. In this review, we discuss the efficacy of FUSION to identify novel inhibitors and oncogene-induced changes that may be cancer cell-specific as well as several potential pitfalls within FUSION and best practices to avoid them.

An in vivo functional genomics screen of nuclear receptors and their co-regulators identifies FOXA1 as an essential gene in lung tumorigenesis.

Using a mini-library of 1062 lentiviral shRNAs targeting 40 nuclear hormone receptors and 70 of their co-regulators, we searched for potential therapeutic targets that would be important during in vivo tumor growth using a parallel in vitro and in vivo shRNA screening strategy in the non-small cell lung cancer (NSCLC) line NCI-H1819. We identified 21 genes essential for in vitro growth, and nine genes specifically required for tumor survival in vivo, but not in vitro: NCOR2, FOXA1, HDAC1, RXRA, RORB, RARB, MTA2, ETV4, and NR1H2. We focused on FOXA1, since it lies within the most frequently amplified genomic region in lung adenocarcinomas. We found that 14q-amplification in NSCLC cell lines was a biomarker for FOXA1 dependency for both in vivo xenograft growth and colony formation, but not mass culture growth in vitro. FOXA1 knockdown identified genes involved in electron transport among the most differentially regulated, indicating FOXA1 loss may lead to a decrease in cellular respiration. In support of this, FOXA1 amplification was correlated with increased sensitivity to the complex I inhibitor phenformin. Integrative ChipSeq analyses reveal that FOXA1 functions in this genetic context may be at least partially independent of NKX2-1. Our findings are consistent with a neomorphic function for amplified FOXA1, driving an oncogenic transcriptional program. These data provide new insight into the functional consequences of FOXA1 amplification in lung adenocarcinomas, and identify new transcriptional networks for exploration of therapeutic vulnerabilities in this patient population.

High-throughput identification of protein functional similarities using a gene-expression-based siRNA screen.

A gene expression-based siRNA screen was used to evaluate functional similarity between genetic perturbations to identify functionally similar proteins. A siRNA library (siGenome library, Dharmacon) consisting of multiple siRNAs per gene that have been pooled in to one well per gene was arrayed in a 384-well format and used to individually target 14,335 proteins for depletion in HCT116 colon cancer cells. For each protein depletion, the gene expression of eight genes was quantified using the multiplexed Affymetrix Quantigene 2.0 assay in technical triplicate. As a proof of concept, six genes (BNIP3, NDRG1, ALDOC, LOXL2, ACSL5, BNIP3L) whose expression pattern reliably reflect the disruption of the molecular scaffold KSR1 were measured upon each protein depletion. The remaining two genes (PPIB and HPRT) are housekeeping genes used for normalization. The gene expression signatures from this screen can be used to estimate the functional similarity between any two proteins and successfully identified functional relationships for specific proteins such as KSR1 and more generalized processes, such as autophagy.

Metabolic Diversity in Human Non-Small Cell Lung Cancer Cells.

Intermediary metabolism in cancer cells is regulated by diverse cell-autonomous processes, including signal transduction and gene expression patterns, arising from specific oncogenotypes and cell lineages. Although it is well established that metabolic reprogramming is a hallmark of cancer, we lack a full view of the diversity of metabolic programs in cancer cells and an unbiased assessment of the associations between metabolic pathway preferences and other cell-autonomous processes. Here, we quantified metabolic features, mostly from the 13C enrichment of molecules from central carbon metabolism, in over 80 non-small cell lung cancer (NSCLC) cell lines cultured under identical conditions. Because these cell lines were extensively annotated for oncogenotype, gene expression, protein expression, and therapeutic sensitivity, the resulting database enables the user to uncover new relationships between metabolism and these orthogonal processes.

A Genome-wide Functional Signature Ontology Map and Applications to Natural Product Mechanism of Action Discovery.

Gene expression signature-based inference of functional connectivity within and between genetic perturbations, chemical perturbations, and disease status can lead to the development of actionable hypotheses for gene function, chemical modes of action, and disease treatment strategies. Here, we report a FuSiOn-based genome-wide integration of hypomorphic cellular phenotypes that enables functional annotation of gene network topology, assignment of mechanistic hypotheses to genes of unknown function, and detection of cooperativity among cell regulatory systems. Dovetailing genetic perturbation data with chemical perturbation phenotypes allowed simultaneous generation of mechanism of action hypotheses for thousands of uncharacterized natural products fractions (NPFs). The predicted mechanism of actions span a broad spectrum of cellular mechanisms, many of which are not currently recognized as "druggable." To enable use of FuSiOn as a hypothesis generation resource, all associations and analyses are available within an open source web-based GUI (http://fusion.yuhs.ac).

Regulating, Measuring, and Modeling the Viscoelasticity of Bacterial Biofilms

Biofilms occur in a broad range of environments under heterogeneous physicochemical conditions, such as in bioremediation plants, on surfaces of biomedical implants, and in the lungs of cystic fibrosis patients. In these scenarios, biofilms are subjected to shear forces, but the mechanical integrity of these aggregates often prevents their disruption or dispersal. Biofilms' physical robustness is the result of the multiple biopolymers secreted by constituent microbial cells which are also responsible for numerous biological functions. A better understanding of the role of these biopolymers and their response to dynamic forces is therefore crucial for understanding the interplay between biofilm structure and function. In this paper, we review experimental techniques in rheology, which help quantify the viscoelasticity of biofilms, and modeling approaches from soft matter physics that can assist our understanding of the rheological properties. We describe how these methods could be combined with synthetic biology approaches to control and investigate the effects of secreted polymers on the physical properties of biofilms. We argue that without an integrated approach of the three disciplines, the links between genetics, composition, and interaction of matrix biopolymers and the viscoelastic properties of biofilms will be much harder to uncover.

Correction: Mitochondrial clearance by the STK38 kinase supports oncogenic Ras-induced cell transformation.

[This corrects the article DOI: 10.18632/oncotarget.9875.].

Selective Cytotoxicity of the NAMPT Inhibitor FK866 Toward Gastric Cancer Cells With Markers of the Epithelial-Mesenchymal Transition, Due to Loss of NAPRT.

BACKGROUND & AIMS: Markers of the epithelial-to-mesenchymal transition (EMT) in gastric tumor tissues are associated with poor patient outcomes. We performed a screen to identify pharmacologic compounds that kill gastric cancer cells with EMT-associated gene expression patterns and investigate their mechanisms. METHODS: We identified 29 gastric cancer cell lines with a gene expression signature previously associated with an EMT subtype, based on data from RNA sequence analyses, and confirmed the mesenchymal phenotypes of 7 lines (Hs746T, SNU1750, MKN1, SK4, SNU484, SNU668, and YCC11), based on invasive activity and protein markers. We screened 1,345 compounds for their ability to kill cells with the EMT signature compared with cell lines without this pattern. We tested the effects of identified compounds in BALB/c nude mice bearing GA077 tumors; mice were given intraperitoneal injections of the compound or vehicle (control) twice daily for 24 days and tumor growth was monitored. Proteins associated with the toxicity of the compounds were overexpressed in MKN1 and SNU484 cells or knocked down in MKN45 and SNU719 using small interfering RNAs. We performed immunohistochemical analyses of 942 gastric cancer tissues and investigated associations between EMT markers and protein expression patterns. RESULTS: The nicotinamide phosphoribosyltransferase inhibitor FK866 killed 6 of 7 gastric cancer cell lines with EMT-associated gene expression signatures but not gastric cancer cells without this signature. The 6 EMT-subtype gastric cell lines expressed significantly low levels of nicotinic acid phosphoribosyltransferase (NAPRT), which makes the cells hypersensitive to nicotinamide phosphoribosyltransferase inhibition. Gastric cell lines that expressed higher levels of NAPRT, regardless of EMT markers, were sensitized to FK866 after knockdown of NAPRT, whereas overexpression of NAPRT in deficient EMT cell lines protected them from FK866-mediated toxicity. Administration of FK866 to nude mice with tumors grown from GA077 cells (human gastric cancer tumors of the EMT subtype) led to tumor regression in 2 weeks; FK866 did not affect tumors grown from MKN45 cells without the EMT expression signature. Loss of NAPRT might promote the EMT, because it stabilizes ß-catenin. We correlated the EMT gene expression signature with lower levels of NAPRT in 942 gastric tumors from patients; we also found lower levels of NAPRT mRNA in colorectal, pancreatic, and lung adenocarcinoma tissues with the EMT gene expression signature. CONCLUSIONS: FK866 selectively kills gastric cancer cells with an EMT gene expression signature by inhibiting nicotinamide phosphoribosyltransferase in cells with NAPRT deficiency. Loss of NAPRT expression, frequently through promoter hypermethylation, is observed in many gastric tumors of the EMT subtype. FK866 might be used to treat patients with tumors of this subtype.

Chemistry-First Approach for Nomination of Personalized Treatment in Lung Cancer.

Diversity in the genetic lesions that cause cancer is extreme. In consequence, a pressing challenge is the development of drugs that target patient-specific disease mechanisms. To address this challenge, we employed a chemistry-first discovery paradigm for de novo identification of druggable targets linked to robust patient selection hypotheses. In particular, a 200,000 compound diversity-oriented chemical library was profiled across a heavily annotated test-bed of >100 cellular models representative of the diverse and characteristic somatic lesions for lung cancer. This approach led to the delineation of 171 chemical-genetic associations, shedding light on the targetability of mechanistic vulnerabilities corresponding to a range of oncogenotypes present in patient populations lacking effective therapy. Chemically addressable addictions to ciliogenesis in TTC21B mutants and GLUT8-dependent serine biosynthesis in KRAS/KEAP1 double mutants are prominent examples. These observations indicate a wealth of actionable opportunities within the complex molecular etiology of cancer.

A Functional Signature Ontology (FUSION) screen detects an AMPK inhibitor with selective toxicity toward human colon tumor cells.

AMPK is a serine threonine kinase composed of a heterotrimer of a catalytic, kinase-containing α and regulatory ß and γ subunits. Here we show that individual AMPK subunit expression and requirement for survival varies across colon cancer cell lines. While AMPKα1 expression is relatively consistent across colon cancer cell lines, AMPKα1 depletion does not induce cell death. Conversely, AMPKα2 is expressed at variable levels in colon cancer cells. In high expressing SW480 and moderate expressing HCT116 colon cancer cells, siRNA-mediated depletion induces cell death. These data suggest that AMPK kinase inhibition may be a useful component of future therapeutic strategies. We used Functional Signature Ontology (FUSION) to screen a natural product library to identify compounds that were inhibitors of AMPK to test its potential for detecting small molecules with preferential toxicity toward human colon tumor cells. FUSION identified 5'-hydroxy-staurosporine, which competitively inhibits AMPK. Human colon cancer cell lines are notably more sensitive to 5'-hydroxy-staurosporine than are non-transformed human colon epithelial cells. This study serves as proof-of-concept for unbiased FUSION-based detection of small molecule inhibitors of therapeutic targets and highlights its potential to identify novel compounds for cancer therapy development.

Inferring Genome-Wide Interaction Networks Using the Phi-Mixing Coefficient, and Applications to Lung and Breast Cancer (Invited Paper).

Constructing gene interaction networks (GINs) from high-throughput gene expression data is an important and challenging problem in systems biology. Existing algorithms produce networks that either have undirected and unweighted edges, or else are constrained to contain no cycles, both of which are biologically unrealistic. In the present paper we propose a new algorithm, based on a concept from probability theory known as the ϕ-mixing coefficient, that produces networks whose edges are weighted and directed, and are permitted to contain cycles. Specifically, we inferred networks for two subtypes of lung cancer small cell (SCLC) and non-small cell (NSCLC) as well as normal lung tissue. Then we compared with the outcomes of siRNA screening of 19,000+ genes on 11 NSCLC cell lines, and found that the higher the degree of a gene in the inferred network, the more essential it is to the survival of a cell. We also analyzed data from a ChIP-Seq experiment to determine putative downstream targets of ASCL1. The SCLC network was enriched for ChIP-seq neighbors of this oncogenic transcription factor, but not in the NSCLC network. We also reverse-engineered whole-genome interaction networks for two distinct subtypes of breast cancer, namely Luminal-A and Basal (also known as triple negative).

TBK1 Provides Context-Selective Support of the Activated AKT/mTOR Pathway in Lung Cancer.

Emerging observations link dysregulation of TANK-binding kinase 1 (TBK1) to developmental disorders, inflammatory disease, and cancer. Biochemical mechanisms accounting for direct participation of TBK1 in host defense signaling have been well described. However, the molecular underpinnings of the selective participation of TBK1 in a myriad of additional cell biological systems in normal and pathophysiologic contexts remain poorly understood. To elucidate the context-selective role of TBK1 in cancer cell survival, we employed a combination of broad-scale chemogenomic and interactome discovery strategies to generate data-driven mechanism-of-action hypotheses. This approach uncovered evidence that TBK1 supports AKT/mTORC1 pathway activation and function through direct modulation of multiple pathway components acting both upstream and downstream of the mTOR kinase itself. Furthermore, we identified distinct molecular features in which mesenchymal, Ras-mutant lung cancer is acutely dependent on TBK1-mediated support of AKT/mTORC1 pathway activation for survival. Cancer Res; 77(18); 5077-94. ©2017 AACR.

Therapeutic Targeting of Nuclear Export Inhibition in Lung Cancer.

Intracellular compartmentalization and trafficking of molecules plays a critical role in complex and essential cellular processes. In lung cancer and other malignancies, aberrant nucleocytoplasmic transport of tumor suppressor proteins and cell cycle regulators results in tumorigenesis and inactivation of apoptosis. Pharmacologic agents targeting this process, termed selective inhibitors of nuclear export (SINE), have demonstrated antitumor efficacy in preclinical models and human clinical trials. Exportin-1 (XPO1), which serves as the sole exporter of several tumor suppressor proteins and cell cycle regulators, including retinoblastoma, adenomatous polyposis coli, p53, p73, p21, p27, forkhead box O, signal transducer and activator of transcription 3, inhibitor of κB, topoisomerase II, and protease activated receptor 4-is the principal focus of development of SINE. The most extensively studied of the SINE to date, the exportin-1 inhibitor selinexor (KPT-330 [Karyopharm Therapeutics, Inc., Newton Centre, MA]), has demonstrated single-agent anticancer activity and synergistic effects in combination regimens against multiple cancer types, with principal toxicities of low-grade cytopenias and gastrointestinal effects. SINE may have particular relevance in KRAS-driven tumors, for which this treatment strategy demonstrates significant synthetic lethality. A multicenter phase 1/2 clinical trial of selinexor in previously treated advanced KRAS-mutant NSCLC is under way.

Biomarker Accessible and Chemically Addressable Mechanistic Subtypes of BRAF Melanoma.

Genomic diversity among melanoma tumors limits durable control with conventional and targeted therapies. Nevertheless, pathologic activation of the ERK1/2 pathway is a linchpin tumorigenic mechanism associated with the majority of primary and recurrent disease. Therefore, we sought to identify therapeutic targets that are selectively required for tumorigenicity in the presence of pathologic ERK1/2 signaling. By integration of multigenome chemical and genetic screens, recurrent architectural variants in melanoma tumor genomes, and patient outcome data, we identified two mechanistic subtypes of BRAFV600 melanoma that inform new cancer cell biology and offer new therapeutic opportunities. Subtype membership defines sensitivity to clinical MEK inhibitors versus TBK1/IKBKε inhibitors. Importantly, subtype membership can be predicted using a robust quantitative five-feature genetic biomarker. This biomarker, and the mechanistic relationships linked to it, can identify a cohort of best responders to clinical MEK inhibitors and identify a cohort of TBK1/IKBKε inhibitor-sensitive disease among nonresponders to current targeted therapy.Significance: This study identified two mechanistic subtypes of melanoma: (1) the best responders to clinical BRAF/MEK inhibitors (25%) and (2) nonresponders due to primary resistance mechanisms (9.9%). We identified robust biomarkers that can detect these subtypes in patient samples and predict clinical outcome. TBK1/IKBKε inhibitors were selectively toxic to drug-resistant melanoma. Cancer Discov; 7(8); 832-51. ©2017 AACR.See related commentary by Jenkins and Barbie, p. 799This article is highlighted in the In This Issue feature, p. 783.

Sparse feature selection for classification and prediction of metastasis in endometrial cancer.

BACKGROUND: Metastasis via pelvic and/or para-aortic lymph nodes is a major risk factor for endometrial cancer. Lymph-node resection ameliorates risk but is associated with significant co-morbidities. Incidence in patients with stage I disease is 4-22% but no mechanism exists to accurately predict it. Therefore, national guidelines for primary staging surgery include pelvic and para-aortic lymph node dissection for all patients whose tumor exceeds 2cm in diameter. We sought to identify a robust molecular signature that can accurately classify risk of lymph node metastasis in endometrial cancer patients. 86 tumors matched for age and race, and evenly distributed between lymph node-positive and lymph node-negative cases, were selected as a training cohort. Genomic micro-RNA expression was profiled for each sample to serve as the predictive feature matrix. An independent set of 28 tumor samples was collected and similarly characterized to serve as a test cohort. RESULTS: A feature selection algorithm was designed for applications where the number of samples is far smaller than the number of measured features per sample. A predictive miRNA expression signature was developed using this algorithm, which was then used to predict the metastatic status of the independent test cohort. A weighted classifier, using 18 micro-RNAs, achieved 100% accuracy on the training cohort. When applied to the testing cohort, the classifier correctly predicted 90% of node-positive cases, and 80% of node-negative cases (FDR = 6.25%). CONCLUSION: Results indicate that the evaluation of the quantitative sparse-feature classifier proposed here in clinical trials may lead to significant improvement in the prediction of lymphatic metastases in endometrial cancer patients.