BatchFLEX: feature-level equalization of X-batch.

MOTIVATION: Integrative analysis of heterogeneous expression data remains challenging due to variations in platform, RNA quality, sample processing, and other unknown technical effects. Selecting the approach for removing unwanted batch effects can be a time-consuming and tedious process, especially for more biologically focused investigators. RESULTS: Here, we present BatchFLEX, a Shiny app that can facilitate visualization and correction of batch effects using several established methods. BatchFLEX can visualize the variance contribution of a factor before and after correction. As an example, we have analyzed ImmGen microarray data and enhanced its expression signals that distinguishes each immune cell type. Moreover, our analysis revealed the impact of the batch correction in altering the gene expression rank and single-sample GSEA pathway scores in immune cell types, highlighting the importance of real-time assessment of the batch correction for optimal downstream analysis. AVAILABILITY AND IMPLEMENTATION: Our tool is available through Github https://github.com/shawlab-moffitt/BATCH-FLEX-ShinyApp with an online example on Shiny.io https://shawlab-moffitt.shinyapps.io/batch_flex/.

Jagged2 targeting in lung cancer activates anti-tumor immunity via Notch-induced functional reprogramming of tumor-associated macrophages.

Signaling through Notch receptors intrinsically regulates tumor cell development and growth. Here, we studied the role of the Notch ligand Jagged2 on immune evasion in non-small cell lung cancer (NSCLC). Higher expression of JAG2 in NSCLC negatively correlated with survival. In NSCLC pre-clinical models, deletion of Jag2, but not Jag1, in cancer cells attenuated tumor growth and activated protective anti-tumor T cell responses. Jag2-/- lung tumors exhibited higher frequencies of macrophages that expressed immunostimulatory mediators and triggered T cell-dependent anti-tumor immunity. Mechanistically, Jag2 ablation promoted Nr4a-mediated induction of Notch ligands DLL1/4 on cancer cells. DLL1/4-initiated Notch1/2 signaling in macrophages induced the expression of transcription factor IRF4 and macrophage immunostimulatory functionality. IRF4 expression was required for the anti-tumor effects of Jag2 deletion in lung tumors. Antibody targeting of Jagged2 inhibited tumor growth and activated IRF4-driven macrophage-mediated anti-tumor immunity. Thus, Jagged2 orchestrates immunosuppressive systems in NSCLC that can be overcome to incite macrophage-mediated anti-tumor immunity.

Comprehensive genomic analysis reveals molecular heterogeneity in pediatric ALK-positive anaplastic large cell lymphoma.

Anaplastic large cell lymphoma (ALCL) is a mature T-cell lymphoma that accounts for for 10-15% of childhood lymphomas. Despite the observation that more than 90% of pediatric cases harbor the anaplastic lymphoma kinase (ALK) rearrangement resulting in aberrant ALK kinase expression, there is significant clinical, morphologic, and biological heterogeneity. To gain insights into the genomic aberrations and molecular heterogeneity within ALK-positive ALCL(ALK+ ALCL), we analyzed 46 pediatric ALK+ ALCLs by whole-exome sequencing, RNA-sequencing, and DNA methylation profiling. Whole-exome sequencing found on average 25 SNV/Indel events per sample with recurring genetic events in regulators of DNA damage (TP53, MDM4), transcription (JUNB), and epigenetic regulators (TET1, KMT2B, KMT2A, KMT2C, KMT2E). Gene expression and methylation profiling consistently subclassified ALK+ ALCLs into two groups characterized by diferential ALK expression levels. The ALK-low group showed enrichment of pathways associated with immune response, cytokine signaling, and a hypermethylated predominant pattern compared to the ALK- high group, which had more frequent copy number changes, and was enriched with pathways associated with cell growth, proliferation, metabolic pathways, and. Taken together, these findings suggest that there is molecular heterogeneity within pediatric ALK+ALCL, predicting distinct biological mechanisms that may provide novel insights into disease pathogenesis and represent prognostic markers.

Pathogenic Roles for RNASET2 in Clear Cell Renal Cell Carcinoma.

A specific splicing isoform of RNASET2 is associated with worse oncologic outcomes in clear cell renal cell carcinoma (ccRCC). However, the interplay between wild-type RNASET2 and its splice variant and how this might contribute to the pathogenesis of ccRCC remains poorly understood. We sought to better understand the relationship of RNASET2 in the pathogenesis of ccRCC and the interplay with a pathogenic splicing isoform (RNASET2-SV) and the tumor immune microenvironment. Using data from The Cancer Genome Atlas and Clinical Proteomic Tumor Analysis Consortium, we correlated clinical variables to RNASET2 expression and the presence of a specific RNASET2-SV. Immunohistochemical staining with matched RNA sequencing of ccRCC patients was then utilized to understand the spatial relationships of RNASET2 with immune cells. Finally, in vitro studies were performed to demonstrate the oncogenic role of RNASET2 and highlight its potential mechanisms. RNASET2 gene expression is associated with higher grade tumors and worse overall survival in The Cancer Genome Atlas cohort. The presence of the RNASET2-SV was associated with increased expression of the wild-type RNASET2 protein and epigenetic modifications of the gene. Immunohistochemical staining revealed increased intracellular accumulation of RNASET2 in patients with increased RNA expression of RNASET2-SV. In vitro experiments reveal that this accumulation results in increased cell proliferation, potentially from altered metabolic pathways. RNASET2 exhibits a tumor-promoting role in the pathogenesis of ccRCC that is increased in the presence of a specific RNASET2-SV and associated with changes in the cellular localization of the protein.

CBFA2T3-GLIS2-dependent pediatric acute megakaryoblastic leukemia is driven by GLIS2 and sensitive to navitoclax.

Pediatric acute megakaryoblastic leukemia (AMKL) is an aggressive blood cancer associated with poor therapeutic response and high mortality. Here we describe the development of CBFA2T3-GLIS2-driven mouse models of AMKL that recapitulate the phenotypic and transcriptional signatures of the human disease. We show that an activating Ras mutation that occurs in human AMKL increases the penetrance and decreases the latency of CBF2AT3-GLIS2-driven AMKL. CBFA2T3-GLIS2 and GLIS2 modulate similar transcriptional networks. We identify the dominant oncogenic properties of GLIS2 that trigger AMKL in cooperation with oncogenic Ras. We find that both CBFA2T3-GLIS2 and GLIS2 alter the expression of a number of BH3-only proteins, causing AMKL cell sensitivity to the BCL2 inhibitor navitoclax both in vitro and in vivo, suggesting a potential therapeutic option for pediatric patients suffering from CBFA2T3-GLIS2-driven AMKL.

An Assessment of the Penile Squamous Cell Carcinoma Surfaceome for Biomarker and Therapeutic Target Discovery.

Penile squamous cell carcinoma (PSCC) is a rare malignancy in most parts of the world and the underlying mechanisms of this disease have not been fully investigated. About 30-50% of cases are associated with high-risk human papillomavirus (HPV) infection, which may have prognostic value. When PSCC becomes resistant to upfront therapies there are limited options, thus further research is needed in this venue. The extracellular domain-facing protein profile on the cell surface (i.e., the surfaceome) is a key area for biomarker and drug target discovery. This research employs computational methods combined with cell line translatomic (n = 5) and RNA-seq transcriptomic data from patient-derived tumors (n = 18) to characterize the PSCC surfaceome, evaluate the composition dependency on HPV infection, and explore the prognostic impact of identified surfaceome candidates. Immunohistochemistry (IHC) was used to validate the localization of select surfaceome markers. This analysis characterized a diverse surfaceome within patient tumors with 25% and 18% of the surfaceome represented by the functional classes of receptors and transporters, respectively. Significant differences in protein classes were noted by HPV status, with the most change being seen in transporter proteins (25%). IHC confirmed the robust surface expression of select surfaceome targets in the top 85% of expression and a superfamily immunoglobulin protein called BSG/CD147 was prognostic of survival. This study provides the first description of the PSCC surfaceome and its relation to HPV infection and sets a foundation for novel biomarker and drug target discovery in this rare cancer.

PATH-SURVEYOR: pathway level survival enquiry for immuno-oncology and drug repurposing.

Pathway-level survival analysis offers the opportunity to examine molecular pathways and immune signatures that influence patient outcomes. However, available survival analysis algorithms are limited in pathway-level function and lack a streamlined analytical process. Here we present a comprehensive pathway-level survival analysis suite, PATH-SURVEYOR, which includes a Shiny user interface with extensive features for systematic exploration of pathways and covariates in a Cox proportional-hazard model. Moreover, our framework offers an integrative strategy for performing Hazard Ratio ranked Gene Set Enrichment Analysis and pathway clustering. As an example, we applied our tool in a combined cohort of melanoma patients treated with checkpoint inhibition (ICI) and identified several immune populations and biomarkers predictive of ICI efficacy. We also analyzed gene expression data of pediatric acute myeloid leukemia (AML) and performed an inverse association of drug targets with the patient's clinical endpoint. Our analysis derived several drug targets in high-risk KMT2A-fusion-positive patients, which were then validated in AML cell lines in the Genomics of Drug Sensitivity database. Altogether, the tool offers a comprehensive suite for pathway-level survival analysis and a user interface for exploring drug targets, molecular features, and immune populations at different resolutions.

Bcl11b sustains multipotency and restricts effector programs of intestinal-resident memory CD8+ T cells.

The networks of transcription factors (TFs) that control intestinal-resident memory CD8+ T (TRM) cells, including multipotency and effector programs, are poorly understood. In this work, we investigated the role of the TF Bcl11b in TRM cells during infection with Listeria monocytogenes using mice with post-activation, conditional deletion of Bcl11b in CD8+ T cells. Conditional deletion of Bcl11b resulted in increased numbers of intestinal TRM cells and their precursors as well as decreased splenic effector and circulating memory cells and precursors. Loss of circulating memory cells was in part due to increased intestinal homing of Bcl11b-/- circulating precursors, with no major alterations in their programs. Bcl11b-/- TRM cells had altered transcriptional programs, with diminished expression of multipotent/multifunctional (MP/MF) program genes, including Tcf7, and up-regulation of the effector program genes, including Prdm1. Bcl11b also limits the expression of Ahr, another TF with a role in intestinal CD8+ TRM cell differentiation. Deregulation of TRM programs translated into a poor recall response despite TRM cell accumulation in the intestine. Reduced expression of MP/MF program genes in Bcl11b-/- TRM cells was linked to decreased chromatin accessibility and a reduction in activating histone marks at these loci. In contrast, the effector program genes displayed increased activating epigenetic status. These findings demonstrate that Bcl11b is a frontrunner in the tissue residency program of intestinal memory cells upstream of Tcf1 and Blimp1, promoting multipotency and restricting the effector program.

DRPPM-PATH-SURVEIOR: Plug-and-Play Survival Analysis of Pathway-level Signatures and Immune Components.

Pathway-level survival analysis offers the opportunity to examine molecular pathways and immune signatures that influence patient outcomes. However, available survival analysis algorithms are limited in pathway-level function and lack a streamlined analytical process. Here we present a comprehensive pathway-level survival analysis suite, DRPPM-PATH-SURVEIOR, which includes a Shiny user interface with extensive features for systematic exploration of pathways and covariates in a Cox proportional-hazard model. Moreover, our framework offers an integrative strategy for performing Hazard Ratio ranked Gene Set Enrichment Analysis (GSEA) and pathway clustering. As an example, we applied our tool in a combined cohort of melanoma patients treated with checkpoint inhibition (ICI) and identified several immune populations and biomarkers predictive of ICI efficacy. We also analyzed gene expression data of pediatric acute myeloid leukemia (AML) and performed an inverse association of drug targets with the patient's clinical endpoint. Our analysis derived several drug targets in high-risk KMT2A-fusion-positive patients, which were then validated in AML cell lines in the Genomics of Drug Sensitivity database. Altogether, the tool offers a comprehensive suite for pathway-level survival analysis and a user interface for exploring drug targets, molecular features, and immune populations at different resolutions.

Malignant Progression of an Ancestral Bone Marrow Clone Harboring a CIC-NUTM2A Fusion in Isolated Myeloid Sarcoma.

Myeloid sarcoma is a rare condition consisting of extramedullary myeloid blasts found in association with acute myeloid leukemia or, in the absence of bone marrow involvement. We identified an infant with isolated myeloid sarcoma whose bone marrow was negative for involvement by flow cytometry. Sequencing revealed the fusion oncogene CIC-NUTM2A and identified the sarcoma to be clonally evolved from the bone marrow, which carried the fusion despite the absence of pathology. Murine modeling confirmed the ability of the fusion to transform hematopoietic cells and identified receptor tyrosine kinase (RTK) signaling activation consistent with disruption of the CIC transcriptional repressor. These findings extend the definition of CIC-rearranged malignancies to include hematologic disease, provide insight into the mechanism of oncogenesis, and demonstrate the importance of molecular analysis and tracking of bone marrow involvement over the course of treatment in myeloid sarcoma, including patients that lack flow cytometric evidence of leukemia at diagnosis. IMPLICATIONS: This study illustrates molecular involvement of phenotypically normal bone marrow in myeloid sarcoma, which has significant implications in clinical care. Further, it extends the definition of CIC-rearrangements to include hematologic malignancies and shows evidence of RTK activation that may be exploited therapeutically in cancer(s) driven by these fusions.

Ablation of the endoplasmic reticulum stress kinase PERK induces paraptosis and type I interferon to promote anti-tumor T cell responses.

Activation of unfolded protein responses (UPRs) in cancer cells undergoing endoplasmic reticulum (ER) stress promotes survival. However, how UPR in tumor cells impacts anti-tumor immune responses remains poorly described. Here, we investigate the role of the UPR mediator pancreatic ER kinase (PKR)-like ER kinase (PERK) in cancer cells in the modulation of anti-tumor immunity. Deletion of PERK in cancer cells or pharmacological inhibition of PERK in melanoma-bearing mice incites robust activation of anti-tumor T cell immunity and attenuates tumor growth. PERK elimination in ER-stressed malignant cells triggers SEC61ß-induced paraptosis, thereby promoting immunogenic cell death (ICD) and systemic anti-tumor responses. ICD induction in PERK-ablated tumors stimulates type I interferon production in dendritic cells (DCs), which primes CCR2-dependent tumor trafficking of common-monocytic precursors and their intra-tumor commitment into monocytic-lineage inflammatory Ly6C+CD103+ DCs. These findings identify how tumor cell-derived PERK promotes immune evasion and highlight the potential of PERK-targeting therapies in cancer immunotherapy.

DRPPM-EASY: A Web-Based Framework for Integrative Analysis of Multi-Omics Cancer Datasets.

High-throughput transcriptomic and proteomic analyses are now routinely applied to study cancer biology. However, complex omics integration remains challenging and often time-consuming. Here, we developed DRPPM-EASY, an R Shiny framework for integrative multi-omics analysis. We applied our application to analyze RNA-seq data generated from a USP7 knockdown in T-cell acute lymphoblastic leukemia (T-ALL) cell line, which identified upregulated expression of a TAL1-associated proliferative signature in T-cell acute lymphoblastic leukemia cell lines. Next, we performed proteomic profiling of the USP7 knockdown samples. Through DRPPM-EASY-Integration, we performed a concurrent analysis of the transcriptome and proteome and identified consistent disruption of the protein degradation machinery and spliceosome in samples with USP7 silencing. To further illustrate the utility of the R Shiny framework, we developed DRPPM-EASY-CCLE, a Shiny extension preloaded with the Cancer Cell Line Encyclopedia (CCLE) data. The DRPPM-EASY-CCLE app facilitates the sample querying and phenotype assignment by incorporating meta information, such as genetic mutation, metastasis status, sex, and collection site. As proof of concept, we verified the expression of TP53 associated DNA damage signature in TP53 mutated ovary cancer cells. Altogether, our open-source application provides an easy-to-use framework for omics exploration and discovery.