Targeting TRIP13 in favorable histology Wilms tumor with nuclear export inhibitors synergizes with doxorubicin.

Wilms tumor (WT) is the most common renal malignancy of childhood. Despite improvements in the overall survival, relapse occurs in ~15% of patients with favorable histology WT (FHWT). Half of these patients will succumb to their disease. Identifying novel targeted therapies remains challenging in part due to the lack of faithful preclinical in vitro models. Here we establish twelve patient-derived WT cell lines and demonstrate that these models faithfully recapitulate WT biology using genomic and transcriptomic techniques. We then perform loss-of-function screens to identify the nuclear export gene, XPO1, as a vulnerability. We find that the FDA approved XPO1 inhibitor, KPT-330, suppresses TRIP13 expression, which is required for survival. We further identify synergy between KPT-330 and doxorubicin, a chemotherapy used in high-risk FHWT. Taken together, we identify XPO1 inhibition with KPT-330 as a potential therapeutic option to treat FHWTs and in combination with doxorubicin, leads to durable remissions in vivo.

Single-cell analysis reveals altered tumor microenvironments of relapse- and remission-associated pediatric acute myeloid leukemia.

Acute myeloid leukemia (AML) microenvironment exhibits cellular and molecular differences among various subtypes. Here, we utilize single-cell RNA sequencing (scRNA-seq) to analyze pediatric AML bone marrow (BM) samples from diagnosis (Dx), end of induction (EOI), and relapse timepoints. Analysis of Dx, EOI scRNA-seq, and TARGET AML RNA-seq datasets reveals an AML blasts-associated 7-gene signature (CLEC11A, PRAME, AZU1, NREP, ARMH1, C1QBP, TRH), which we validate on independent datasets. The analysis reveals distinct clusters of Dx relapse- and continuous complete remission (CCR)-associated AML-blasts with differential expression of genes associated with survival. At Dx, relapse-associated samples have more exhausted T cells while CCR-associated samples have more inflammatory M1 macrophages. Post-therapy EOI residual blasts overexpress fatty acid oxidation, tumor growth, and stemness genes. Also, a post-therapy T-cell cluster associated with relapse samples exhibits downregulation of MHC Class I and T-cell regulatory genes. Altogether, this study deeply characterizes pediatric AML relapse- and CCR-associated samples to provide insights into the BM microenvironment landscape.

Live-cell invasive phenotyping uncovers the ALK2/BMP6 iron homeostasis pathway as a therapeutic vulnerability in LKB1-mutant lung cancer.

The acquisition of invasive properties is a prerequisite for tumor progression and metastasis. Molecular subtypes of KRAS-driven lung cancer exhibit distinct modes of invasion that likely contribute to unique growth properties and therapeutic susceptibilities. Despite this, pre-clinical discovery strategies designed to exploit invasive phenotypes are lacking. To address this, we designed an experimental system to screen for targetable signaling pathways linked to active early invasion phenotypes in the two most prominent molecular subtypes, TP53 and LKB1, of KRAS-driven lung adenocarcinoma (LUAD). By combining live-cell imaging of human bronchial epithelial cells in a 3D invasion matrix with RNA transcriptome profiling, we identified the LKB1-specific upregulation of bone morphogenetic protein 6 (BMP6). Examination of early-stage lung cancer patients confirmed upregulation of BMP6 in LKB1-mutant lung tumors. At the molecular level, we find that the canonical iron regulatory hormone Hepcidin is induced via BMP6 signaling upon LKB1 loss, where intact LKB1 kinase activity is necessary to maintain signaling homeostasis. Furthermore, pre-clinical studies in a novel Kras/Lkb1-mutant syngeneic mouse model show that potent growth suppression was achieved by inhibiting the ALK2/BMP6 signaling axis with single agents that are currently in clinical trials. We show that alterations in the iron homeostasis pathway are accompanied by simultaneous upregulation of ferroptosis protection proteins. Thus, LKB1 is sufficient to regulate both the 'gas' and 'breaks' to finely tune iron-regulated tumor progression.

Therapeutic implications of mitochondrial stress-induced proteasome inhibitor resistance in multiple myeloma.

The connections between metabolic state and therapy resistance in multiple myeloma (MM) are poorly understood. We previously reported that electron transport chain (ETC) suppression promotes sensitivity to the BCL-2 antagonist venetoclax. Here, we show that ETC suppression promotes resistance to proteasome inhibitors (PIs). Interrogation of ETC-suppressed MM reveals integrated stress response-dependent suppression of protein translation and ubiquitination, leading to PI resistance. ETC and protein translation gene expression signatures from the CoMMpass trial are down-regulated in patients with poor outcome and relapse, corroborating our in vitro findings. ETC-suppressed MM exhibits up-regulation of the cystine-glutamate antiporter SLC7A11, and analysis of patient single-cell RNA-seq shows that clusters with low ETC gene expression correlate with higher SLC7A11 expression. Furthermore, erastin or venetoclax treatment diminishes mitochondrial stress-induced PI resistance. In sum, our work demonstrates that mitochondrial stress promotes PI resistance and underscores the need for implementing combinatorial regimens in MM cognizant of mitochondrial metabolic state.

Obesity-induced galectin-9 is a therapeutic target in B-cell acute lymphoblastic leukemia.

The incidence of obesity is rising with greater than 40% of the world's population expected to be overweight or suffering from obesity by 2030. This is alarming because obesity increases mortality rates in patients with various cancer subtypes including leukemia. The survival differences between lean patients and patients with obesity are largely attributed to altered drug pharmacokinetics in patients receiving chemotherapy; whereas, the direct impact of an adipocyte-enriched microenvironment on cancer cells is rarely considered. Here we show that the adipocyte secretome upregulates the surface expression of Galectin-9 (GAL-9) on human B-acute lymphoblastic leukemia cells (B-ALL) which promotes chemoresistance. Antibody-mediated targeting of GAL-9 on B-ALL cells induces DNA damage, alters cell cycle progression, and promotes apoptosis in vitro and significantly extends the survival of obese but not lean mice with aggressive B-ALL. Our studies reveal that adipocyte-mediated upregulation of GAL-9 on B-ALL cells can be targeted with antibody-based therapies to overcome obesity-induced chemoresistance.

Survival Genie, a web platform for survival analysis across pediatric and adult cancers.

The genomics data-driven identification of gene signatures and pathways has been routinely explored for predicting cancer survival and making decisions related to targeted treatments. A large number of packages and tools have been developed to correlate gene expression/mutations to the clinical outcome but lack the ability to perform such analysis based on pathways, gene sets, and gene ratios. Furthermore, in this single-cell omics era, the cluster markers from cancer single-cell transcriptomics studies remain an underutilized prognostic option. Additionally, no bioinformatics online tool evaluates the associations between the enrichment of canonical cell types and survival across cancers. Here we have developed Survival Genie, a web tool to perform survival analysis on single-cell RNA-seq (scRNA-seq) data and a variety of other molecular inputs such as gene sets, genes ratio, tumor-infiltrating immune cells proportion, gene expression profile scores, and tumor mutation burden. For a comprehensive analysis, Survival Genie contains 53 datasets of 27 distinct malignancies from 11 different cancer programs related to adult and pediatric cancers. Users can upload scRNA-seq data or gene sets and select a gene expression partitioning method (i.e., mean, median, quartile, cutp) to determine the effect of expression levels on survival outcomes. The tool provides comprehensive results including box plots of low and high-risk groups, Kaplan-Meier plots with univariate Cox proportional hazards model, and correlation of immune cell enrichment and molecular profile. The analytical options and comprehensive collection of cancer datasets make Survival Genie a unique resource to correlate gene sets, pathways, cellular enrichment, and single-cell signatures to clinical outcomes to assist in developing next-generation prognostic and therapeutic biomarkers. Survival Genie is open-source and available online at https://bbisr.shinyapps.winship.emory.edu/SurvivalGenie/ .

Single cell transcriptomic landscape of diabetic foot ulcers.

Diabetic foot ulceration (DFU) is a devastating complication of diabetes whose pathogenesis remains incompletely understood. Here, we profile 174,962 single cells from the foot, forearm, and peripheral blood mononuclear cells using single-cell RNA sequencing. Our analysis shows enrichment of a unique population of fibroblasts overexpressing MMP1, MMP3, MMP11, HIF1A, CHI3L1, and TNFAIP6 and increased M1 macrophage polarization in the DFU patients with healing wounds. Further, analysis of spatially separated samples from the same patient and spatial transcriptomics reveal preferential localization of these healing associated fibroblasts toward the wound bed as compared to the wound edge or unwounded skin. Spatial transcriptomics also validates our findings of higher abundance of M1 macrophages in healers and M2 macrophages in non-healers. Our analysis provides deep insights into the wound healing microenvironment, identifying cell types that could be critical in promoting DFU healing, and may inform novel therapeutic approaches for DFU treatment.

MTHFR single nucleotide polymorphism associated with working memory in pediatric medulloblastoma survivors.

Background: Associations have been found between single nucleotide polymorphisms (SNPs) in the MTHFR gene and cognitive outcomes in cancer survivors. Prior research has demonstrated that the presence of MTHFR SNPs (rs1801131 and rs1801133) in survivors of acute lymphoblastic leukemia (ALL) corresponds to impairments in attention and executive functioning. The current study examines the associations between rs1801131 and/or rs1801133 SNPs and cognitive performance in long-term survivors of medulloblastoma. Procedure: Eighteen pediatric medulloblastoma survivors, on average 12.42 years post-diagnosis, completed the Digit Span Forward, Digit Span Backward, California Verbal Learning Test Trial 1, and Auditory Consonant Trigrams tests. MTHFR SNPs were detected using whole genome sequencing data and custom scripts within R software. Results: Survivors with a rs1801131 SNP performed significantly worse on Digit Span Backward than survivors without this SNP exhibiting a large effect (p = 0.049; d = 0.95). Survivors with a rs1801131 SNP performed worse on Digit Span Forward (d = 0.478) and the CVLT Trial 1 (d = 0.417) with medium effect sizes. In contrast to rs1801131, relationships were not identified between a rs1801133 SNP and these performance measures. Conclusions: Our findings demonstrate the potential links between MTHFR SNPs and cognitive outcomes following treatment in brain tumor survivors. The current findings establish a novel relationship between rs1801131 and working memory in medulloblastoma. Increases in homocysteine levels and oxidative damage from radiation may lead to adverse long-term outcomes. This establishes the need to look beyond leukemia and methotrexate treatment to consider the risk of MTHFR SNPs for medulloblastoma survivors.

The level of oncogenic Ras determines the malignant transformation of Lkb1 mutant tissue in vivo.

The genetic and metabolic heterogeneity of RAS-driven cancers has confounded therapeutic strategies in the clinic. To address this, rapid and genetically tractable animal models are needed that recapitulate the heterogeneity of RAS-driven cancers in vivo. Here, we generate a Drosophila melanogaster model of Ras/Lkb1 mutant carcinoma. We show that low-level expression of oncogenic Ras (RasLow) promotes the survival of Lkb1 mutant tissue, but results in autonomous cell cycle arrest and non-autonomous overgrowth of wild-type tissue. In contrast, high-level expression of oncogenic Ras (RasHigh) transforms Lkb1 mutant tissue resulting in lethal malignant tumors. Using simultaneous multiview light-sheet microcopy, we have characterized invasion phenotypes of Ras/Lkb1 tumors in living larvae. Our molecular analysis reveals sustained activation of the AMPK pathway in malignant Ras/Lkb1 tumors, and demonstrate the genetic and pharmacologic dependence of these tumors on CaMK-activated Ampk. We further show that LKB1 mutant human lung adenocarcinoma patients with high levels of oncogenic KRAS exhibit worse overall survival and increased AMPK activation. Our results suggest that high levels of oncogenic KRAS is a driving event in the malignant transformation of LKB1 mutant tissue, and uncovers a vulnerability that may be used to target this aggressive genetic subset of RAS-driven tumors.

YAP1 Expression in SCLC Defines a Distinct Subtype With T-cell-Inflamed Phenotype.

INTRODUCTION: The clinical and biological significance of the newly described SCLC subtypes, SCLC-A, SCLC-N, SCLC-Y, and SCLC-P, defined by the dominant expression of transcription factors ASCL1, NeuroD1, YAP1, and POU2F3, respectively, remain to be established. METHODS: We generated new RNA sequencing expression data from a discovery set of 59 archival tumor samples of neuroendocrine tumors and new protein expression data by immunohistochemistry in 99 SCLC cases. We validated the findings from this discovery set in two independent validation sets consisting of RNA sequencing data generated from 51 SCLC cell lines and 81 primary human SCLC samples. RESULTS: We successfully classified 71.8% of SCLC and 18.5% of carcinoid cases in our discovery set into one of the four SCLC subtypes. Gene set enrichment analysis for differentially expressed genes between the SCLC survival outliers (top and bottom deciles) matched for clinically relevant prognostic factors revealed substantial up-regulation of interferon-γ response genes in long-term survivors. The SCLC-Y subtype was associated with high expression of interferon-γ response genes, highest weighted score on a validated 18-gene T-cell-inflamed gene expression profile score, and high expression of HLA and T-cell receptor genes. YAP1 protein expression was more prevalent and more intensely expressed in limited-stage versus extensive-stage SCLC (30.6% versus 8.5%; p = 0.0058) indicating good prognosis for the SCLC-Y subtype. We replicated the inflamed phenotype of SCLC-Y in the two independent validation data sets from the SCLC cell lines and tumor samples. CONCLUSIONS: SCLC subtyping using transcriptional signaling holds clinical relevance with the inflamed phenotype associated with the SCLC-Y subset.

Signatures of somatic mutations and gene expression from p16INK4A positive head and neck squamous cell carcinomas (HNSCC).

Human papilloma virus (HPV) causes a subset of head and neck squamous cell carcinomas (HNSCC) of the oropharynx. We combined targeted DNA- and genome-wide RNA-sequencing to identify genetic variants and gene expression signatures respectively from patients with HNSCC including oropharyngeal squamous cell carcinomas (OPSCC). DNA and RNA were purified from 35- formalin fixed and paraffin embedded (FFPE) HNSCC tumor samples. Immuno-histochemical evaluation of tumors was performed to determine the expression levels of p16INK4A and classified tumor samples either p16+ or p16-. Using ClearSeq Comprehensive Cancer panel, we examined the distribution of somatic mutations. Somatic single-nucleotide variants (SNV) were called using GATK-Mutect2 ("tumor-only" mode) approach. Using RNA-seq, we identified a catalog of 1,044 and 8 genes as significantly expressed between p16+ and p16-, respectively at FDR 0.05 (5%) and 0.1 (10%). The clinicopathological characteristics of the patients including anatomical site, smoking and survival were analyzed when comparing p16+ and p16- tumors. The majority of tumors (65%) were p16+. Population sequence variant databases, including gnomAD, ExAC, COSMIC and dbSNP, were used to identify the mutational landscape of somatic sequence variants within sequenced genes. Hierarchical clustering of The Cancer Genome Atlas (TCGA) samples based on HPV-status was observed using differentially expressed genes. Using RNA-seq in parallel with targeted DNA-seq, we identified mutational and gene expression signatures characteristic of p16+ and p16- HNSCC. Our gene signatures are consistent with previously published data including TCGA and support the need to further explore the biologic relevance of these alterations in HNSCC.

Epigenetically heterogeneous tumor cells direct collective invasion through filopodia-driven fibronectin micropatterning.

Tumor heterogeneity drives disease progression, treatment resistance, and patient relapse, yet remains largely underexplored in invasion and metastasis. Here, we investigated heterogeneity within collective cancer invasion by integrating DNA methylation and gene expression analysis in rare purified lung cancer leader and follower cells. Our results showed global DNA methylation rewiring in leader cells and revealed the filopodial motor MYO10 as a critical gene at the intersection of epigenetic heterogeneity and three-dimensional (3D) collective invasion. We further identified JAG1 signaling as a previously unknown upstream activator of MYO10 expression in leader cells. Using live-cell imaging, we found that MYO10 drives filopodial persistence necessary for micropatterning extracellular fibronectin into linear tracks at the edge of 3D collective invasion exclusively in leaders. Our data fit a model where epigenetic heterogeneity and JAG1 signaling jointly drive collective cancer invasion through MYO10 up-regulation in epigenetically permissive leader cells, which induces filopodia dynamics necessary for linearized fibronectin micropatterning.

Prognostic significance of an invasive leader cell-derived mutation cluster on chromosome 16q.

BACKGROUND: Intratumoral heterogeneity is defined by subpopulations with varying genotypes and phenotypes. Specialized, highly invasive leader cells and less invasive follower cells are phenotypically distinct subpopulations that cooperate during collective cancer invasion. Because leader cells are a rare subpopulation that would be missed by bulk sequencing, a novel image-guided genomics platform was used to precisely select this subpopulation. This study identified a novel leader cell mutation signature and tested its ability to predict prognosis in non-small cell lung cancer (NSCLC) patient cohorts. METHODS: Spatiotemporal genomic and cellular analysis was used to isolate and perform RNA sequencing on leader and follower populations from the H1299 NSCLC cell line, and it revealed a leader-specific mutation cluster on chromosome 16q. Genomic data from patients with lung squamous cell carcinoma (LUSC; n = 475) and lung adenocarcinoma (LUAD; n = 501) from The Cancer Genome Atlas were stratified by 16q mutation cluster (16qMC) status (16qMC+ vs 16qMC-) and compared for overall survival (OS), progression-free survival (PFS), and gene set enrichment analysis (GSEA). RESULTS: Poorer OS, poorer PFS, or both were found across all stages and among early-stage patients with 16qMC+ tumors within the LUSC and LUAD cohorts. GSEA revealed 16qMC+ tumors to be enriched for the expression of metastasis- and survival-associated gene sets. CONCLUSIONS: This represents the first leader cell mutation signature identified in patients and has the potential to better stratify high-risk NSCLC and ultimately improve patient outcomes.

GSTP1 polymorphisms sex-specific association with verbal intelligence in survivors of pediatric medulloblastoma tumors.

Glutathione S-transferase (GST) single nucleotide polymorphisms (SNPs) have been associated with a lower intellectual quotient (IQ) in medulloblastoma survivors. We investigated the association of GSTP1 polymorphisms with intellectual, neurocognitive skills (e.g., attention span, working memory, and processing speed), and adaptive outcomes for long-term pediatric medulloblastoma survivors. We hypothesized that genetic risk and sex-specific risk would contribute to significantly lower performances across all measures. Eighteen long-term pediatric medulloblastoma survivors completed the Wechsler Abbreviated Scale Intelligence, California Verbal Learning Test-II, Auditory Consonant Trigrams, and Oral Symbol Digit Modality Test. Informants were interviewed with the Scales of Independent Behavior-Revised (SIB-R). After controlling for the false discovery rate, females with a polymorphism performed significantly worse than females without a polymorphism on verbal IQ (p = .005) and SIB-R (p = .012). There was a significant interaction between sex and polymorphism status for verbal IQ (b = -1.8, SE = 0.827, CI: -3.58, -.036). The main effect of this interaction was significant for females (p = .004) and not for males (p = .557). We found large effect sizes between males with the polymorphism and females with the polymorphism across measures of attention span (g = .877), working memory (g = 1.12), and processing speed (g = 1.53). Female medulloblastoma survivors with a GSTP1 polymorphism may have increased vulnerability to deficits in core cognitive skills, IQ, and everyday functional outcomes. Sex-specific genetic risk contributes to the variability in long-term verbal intelligence for medulloblastoma survivors.

ETV2/ER71 regulates the generation of FLK1+ cells from mouse embryonic stem cells through miR-126-MAPK signaling.

Previous studies including ours have demonstrated a critical function of the transcription factor ETV2 (ets variant 2; also known as ER71) in determining the fate of cardiovascular lineage development. However, the underlying mechanisms of ETV2 function remain largely unknown. In this study, we demonstrated the novel function of the miR (micro RNA)-126-MAPK (mitogen-activated protein kinase) pathway in ETV2-mediated FLK1 (fetal liver kinase 1; also known as VEGFR2)+ cell generation from the mouse embryonic stem cells (mESCs). By performing a series of experiments including miRNA sequencing and ChIP (chromatin immunoprecipitation)-PCR, we found that miR-126 is directly induced by ETV2. Further, we identified that miR-126 can positively regulate the generation of FLK1+ cells by activating the MAPK pathway through targeting SPRED1 (sprouty-related EVH1 domain containing 1). Further, we showed evidence that JUN/FOS activate the enhancer region of FLK1 through AP1 (activator protein 1) binding sequences. Our findings provide insight into the novel molecular mechanisms of ETV2 function in regulating cardiovascular lineage development from mESCs.

Genetic heterogeneity within collective invasion packs drives leader and follower cell phenotypes.

Collective invasion, the coordinated movement of cohesive packs of cells, has become recognized as a major mode of metastasis for solid tumors. These packs are phenotypically heterogeneous and include specialized cells that lead the invasive pack and others that follow behind. To better understand how these unique cell types cooperate to facilitate collective invasion, we analyzed transcriptomic sequence variation between leader and follower populations isolated from the H1299 non-small cell lung cancer cell line using an image-guided selection technique. We now identify 14 expressed mutations that are selectively enriched in leader or follower cells, suggesting a novel link between genomic and phenotypic heterogeneity within a collectively invading tumor cell population. Functional characterization of two phenotype-specific candidate mutations showed that ARP3 enhances collective invasion by promoting the leader cell phenotype and that wild-type KDM5B suppresses chain-like cooperative behavior. These results demonstrate an important role for distinct genetic variants in establishing leader and follower phenotypes and highlight the necessity of maintaining a capacity for phenotypic plasticity during collective cancer invasion.

Host Genome Variation is Associated with Neurocognitive Outcome in Survivors of Pediatric Medulloblastoma.

Host genome analysis is a promising source of predictive information for long-term morbidity in cancer survivors. However, studies on genetic predictors of long-term outcome, particularly neurocognitive function following chemoradiation in pediatric oncology, are limited. Here, we evaluated variation in host genome of long-term survivors of medulloblastoma and its association with neurocognitive outcome. Whole-genome sequencing was conducted on peripheral blood of long-term survivors of pediatric medulloblastoma who also completed neuropsychological testing. Cognitively impaired and less impaired survivors did not differ in exposure to chemoradiation therapy or age at treatment. Unsupervised consensus clustering yielded two distinct variant clusters that were significantly associated with neurocognitive outcome. Interestingly, 34 of the 36 significant variants were found in noncoding DNA regions with unknown regulatory function. A separate unsupervised cluster analysis of variants within DNA repair genes identified discrete variant groups that were not associated with neurocognitive outcome, suggesting that variations in genes corresponding to a single functional group may be insufficient to predict long-term outcome alone. These findings are supportive of the presence of a genetic diathesis for treatment-related neurocognitive morbidity in medulloblastoma that may be driven by variation in noncoding regulatory elements.

IL12 Abrogates Calcineurin-Dependent Immune Evasion during Leukemia Progression.

Exploitation of the immune system has emerged as an important therapeutic strategy for acute lymphoblastic leukemia (ALL). However, the mechanisms of immune evasion during leukemia progression remain poorly understood. We sought to understand the role of calcineurin in ALL and observed that depletion of calcineurin B (CnB) in leukemia cells dramatically prolongs survival in immune-competent but not immune-deficient recipients. Immune-competent recipients were protected from challenge with leukemia if they were first immunized with CnB-deficient leukemia, suggesting robust adaptive immunity. In the bone marrow (BM), recipients of CnB-deficient leukemia harbored expanded T-cell populations as compared with controls. Gene expression analyses of leukemia cells extracted from the BM identified Cn-dependent significant changes in the expression of immunoregulatory genes. Increased secretion of IL12 from CnB-deficient leukemia cells was sufficient to induce T-cell activation ex vivo, an effect that was abolished when IL12 was neutralized. Strikingly, recombinant IL12 prolonged survival of mice challenged with highly aggressive B-ALL. Moreover, gene expression analyses from children with ALL showed that patients with higher expression of either IL12A or IL12B exhibited prolonged survival. These data suggest that leukemia cells are dependent upon calcineurin for immune evasion by restricting the regulation of proinflammatory genes, particularly IL12. SIGNIFICANCE: This report implicates calcineurin as an intracellular signaling molecule responsible for immune evasion during leukemia progression and raises the prospect of re-examining IL12 as a therapeutic in leukemia.

NOJAH: NOt Just Another Heatmap for genome-wide cluster analysis.

Since their inception, several tools have been developed for cluster analysis and heatmap construction. The application of such tools to the number and types of genome-wide data available from next generation sequencing (NGS) technologies requires the adaptation of statistical concepts, such as in defining a most variable gene set, and more intricate cluster analyses method to address multiple omic data types. Additionally, the growing number of publicly available datasets has created the desire to estimate the statistical significance of a gene signature derived from one dataset to similarly group samples based on another dataset. The currently available number of tools and their combined use for generating heatmaps, along with the several adaptations of statistical concepts for addressing the higher dimensionality of genome-wide NGS-derived data, has created a further challenge in the ability to replicate heatmap results. We introduce NOJAH (NOt Just Another Heatmap), an interactive tool that defines and implements a workflow for genome-wide cluster analysis and heatmap construction by creating and combining several tools into a single user interface. NOJAH includes several newly developed scripts for techniques that though frequently applied are not sufficiently documented to allow for replicability of results. These techniques include: defining a most variable gene set (a.k.a., 'core genes'), estimating the statistical significance of a gene signature to separate samples into clusters, and performing a result merging integrated cluster analysis. With only a user uploaded dataset, NOJAH provides as output, among other things, the minimum documentation required for replicating heatmap results. Additionally, NOJAH contains five different existing R packages that are connected in the interface by their functionality as part of a defined workflow for genome-wide cluster analysis. The NOJAH application tool is available at http://bbisr.shinyapps.winship.emory.edu/NOJAH/ http://shinygispa.winship.emory.edu/shinyGISPA/ with corresponding source code available at https://github.com/bbisr-shinyapps/NOJAH/.

shinySISPA: A web tool for defining sample groups using gene sets from multiple-omics data.

As opposed to genome-wide testing of several hundreds of thousands of genes on very few samples, gene panels target as few as tens of genes and enable the simultaneous testing of many samples.  For example, some cancer gene panels test for 50 genes that can affect tumor growth and potentially identify treatment options directed against the genetic mutation.  The increasing popularity of gene panel testing has spurred the technological development of panels that test for diverse data types such as expression and mutation.   Once samples are tested, there is the desire to examine clinical associations based on the panel and for this purpose, one would like to identify, among the samples tested, which show support for a molecular profile (e.g., presence of mutation with increased expression) versus those samples that do not among the genes tested.  With user-specified molecular profile of interest, and gene panel data matrices (e.g., gene expression, variants, etc.) that define the profile, shinySISPA (Sample Integrated Set Profile Analysis) is a web-based shiny tool to define two sample groups with and without profile support based on our previously published method from which clinical associations may be readily examined. The shinySISPA can be accessed from http://shinygispa.winship.emory.edu/shinySISPA/.