Reversal of Lactate and PD-1-mediated Macrophage Immunosuppression Controls Growth of PTEN/p53-deficient Prostate Cancer.

PURPOSE: Phosphatase and tensin homolog (PTEN) loss of function occurs in approximately 50% of patients with metastatic castrate-resistant prostate cancer (mCRPC), and is associated with poor prognosis and responsiveness to standard-of-care therapies and immune checkpoint inhibitors. While PTEN loss of function hyperactivates PI3K signaling, combinatorial PI3K/AKT pathway and androgen deprivation therapy (ADT) has demonstrated limited anticancer efficacy in clinical trials. Here, we aimed to elucidate mechanism(s) of resistance to ADT/PI3K-AKT axis blockade, and to develop rational combinatorial strategies to effectively treat this molecular subset of mCRPC. EXPERIMENTAL DESIGN: Prostate-specific PTEN/p53-deficient genetically engineered mice (GEM) with established 150-200 mm3 tumors, as assessed by ultrasound, were treated with either ADT (degarelix), PI3K inhibitor (copanlisib), or anti-PD-1 antibody (aPD-1), as single agents or their combinations, and tumors were monitored by MRI and harvested for immune, transcriptomic, and proteomic profiling, or ex vivo co-culture studies. Single-cell RNA sequencing on human mCRPC samples was performed using 10X Genomics platform. RESULTS: Coclinical trials in PTEN/p53-deficient GEM revealed that recruitment of PD-1-expressing tumor-associated macrophages (TAM) thwarts ADT/PI3Ki combination-induced tumor control. The addition of aPD-1 to ADT/PI3Ki combination led to TAM-dependent approximately 3-fold increase in anticancer responses. Mechanistically, decreased lactate production from PI3Ki-treated tumor cells suppressed histone lactylation within TAM, resulting in their anticancer phagocytic activation, which was augmented by ADT/aPD-1 treatment and abrogated by feedback activation of Wnt/ß-catenin pathway. Single-cell RNA-sequencing analysis in mCRPC patient biopsy samples revealed a direct correlation between high glycolytic activity and TAM phagocytosis suppression. CONCLUSIONS: Immunometabolic strategies that reverse lactate and PD-1-mediated TAM immunosuppression, in combination with ADT, warrant further investigation in patients with PTEN-deficient mCRPC.

A novel strategy for combination of clofarabine and pictilisib is synergistic in gastric cancer.

Gastric cancer (GC) is frequently characterized by resistance to standard chemotherapeutic regimens and poor clinical outcomes. We aimed to identify a novel therapeutic approach using drug sensitivity testing (DST) and our computational SynerySeq pipeline. DST of GC cell lines was performed with a library of 215 Federal Drug Administration (FDA) approved compounds and identified clofarabine as a potential therapeutic agent. RNA-sequencing (RNAseq) of clofarabine treated GC cells was analyzed according to our SynergySeq pipeline and identified pictilisib as a potential synergistic agent. Clonogenic survival and Annexin V assays demonstrated increased cell death with clofarabine and pictilisib combination treatment (P<0.01). The combination induced double strand breaks (DSB) as indicated by phosphorylated H2A histone family member X (γH2AX) immunofluorescence and western blot analysis (P<0.01). Pictilisib treatment inhibited the protein kinase B (AKT) cell survival pathway and promoted a pro-apoptotic phenotype as evidenced by quantitative real time polymerase chain reaction (qRT-PCR) analysis of the B-cell lymphoma 2 (BCL2) protein family members (P<0.01). Patient derived xenograft (PDX) data confirmed that the combination is more effective in abrogating tumor growth with prolonged survival than single-agent treatment (P<0.01). The novel combination of clofarabine and pictilisib in GC promotes DNA damage and inhibits key cell survival pathways to induce cell death beyond single-agent treatment.

The Clinical Kinase Index: A Method to Prioritize Understudied Kinases as Drug Targets for the Treatment of Cancer.

The approval of the first kinase inhibitor, Gleevec, ushered in a paradigm shift for oncological treatment-the use of genomic data for targeted, efficacious therapies. Since then, over 48 additional small-molecule kinase inhibitors have been approved, solidifying the case for kinases as a highly druggable and attractive target class. Despite the role deregulated kinase activity plays in cancer, only 8% of the kinome has been effectively "drugged." Moreover, 24% of the 634 human kinases are understudied. We have developed a comprehensive scoring system that utilizes differential gene expression, pathological parameters, overall survival, and mutational hotspot analysis to rank and prioritize clinically relevant kinases across 17 solid tumor cancers from The Cancer Genome Atlas. We have developed the clinical kinase index (CKI) app (http://cki.ccs.miami.edu) to facilitate interactive analysis of all kinases in each cancer. Collectively, we report that understudied kinases have potential clinical value as biomarkers or drug targets that warrant further study.

Network assessment of demethylation treatment in melanoma: Differential transcriptome-methylome and antigen profile signatures.

BACKGROUND: In melanoma, like in other cancers, both genetic alterations and epigenetic underlie the metastatic process. These effects are usually measured by changes in both methylome and transcriptome profiles, whose cross-correlation remains uncertain. We aimed to assess at systems scale the significance of epigenetic treatment in melanoma cells with different metastatic potential. METHODS AND FINDINGS: Treatment by DAC demethylation with 5-Aza-2'-deoxycytidine of two melanoma cell lines endowed with different metastatic potential, SKMEL-2 and HS294T, was performed and high-throughput coupled RNA-Seq and RRBS-Seq experiments delivered differential profiles (DiP) of both transcriptomes and methylomes. Methylation levels measured at both TSS and gene body were studied to inspect correlated patterns with wide-spectrum transcript abundance levels quantified in both protein coding and non-coding RNA (ncRNA) regions. The DiP were then mapped onto standard bio-annotation sources (pathways, biological processes) and network configurations were obtained. The prioritized associations for target identification purposes were expected to elucidate the reprogramming dynamics induced by the epigenetic therapy. The interactomic connectivity maps of each cell line were formed to support the analysis of epigenetically re-activated genes. i.e. those supposedly silenced by melanoma. In particular, modular protein interaction networks (PIN) were used, evidencing a limited number of shared annotations, with an example being MAPK13 (cascade of cellular responses evoked by extracellular stimuli). This gene is also a target associated to the PANDAR ncRNA, therapeutically relevant because of its aberrant expression observed in various cancers. Overall, the non-metastatic SKMEL-2 map reveals post-treatment re-activation of a richer pathway landscape, involving cadherins and integrins as signatures of cell adhesion and proliferation. Relatively more lncRNAs were also annotated, indicating more complex regulation patterns in view of target identification. Finally, the antigen maps matched to DiP display other differential signatures with respect to the metastatic potential of the cell lines. In particular, as demethylated melanomas show connected targets that grow with the increased metastatic potential, also the potential target actionability seems to depend to some degree on the metastatic state. However, caution is required when assessing the direct influence of re-activated genes over the identified targets. In light of the stronger treatment effects observed in non-metastatic conditions, some limitations likely refer to in silico data integration tools and resources available for the analysis of tumor antigens. CONCLUSION: Demethylation treatment strongly affects early melanoma progression by re-activating many genes. This evidence suggests that the efficacy of this type of therapeutic intervention is potentially high at the pre-metastatic stages. The biomarkers that can be assessed through antigens seem informative depending on the metastatic conditions, and networks help to elucidate the assessment of possible targets actionability.

Identification of urinary exosomal noncoding RNAs as novel biomarkers in chronic kidney disease.

In chronic kidney disease (CKD), the decline in the glomerular filtration rate is associated with increased morbidity and mortality and thus poses a major challenge for healthcare systems. While the contribution of tissue-derived miRNAs and mRNAs to CKD progression has been extensively studied, little is known about the role of urinary exosomes and their association with CKD. Exosomes are small, membrane-derived endocytic vesicles that contribute to cell-to-cell communication and are present in various body fluids, such as blood or urine. Next-generation sequencing approaches have revealed that exosomes are enriched in noncoding RNAs and thus exhibit great potential for sensitive nucleic acid biomarkers in various human diseases. Therefore, in this study we aimed to identify urinary exosomal ncRNAs as novel biomarkers for diagnosis of CKD. Since up to now most approaches have focused on the class of miRNAs, we extended our analysis to several other noncoding RNA classes, such as tRNAs, tRNA fragments (tRFs), mitochondrial tRNAs, or lincRNAs. For their computational identification from RNA-seq data, we developed a novel computational pipeline, designated as ncRNASeqScan. By these analyses, in CKD patients we identified 30 differentially expressed ncRNAs, derived from urinary exosomes, as suitable biomarkers for early diagnosis. Thereby, miRNA-181a appeared as the most robust and stable potential biomarker, being significantly decreased by about 200-fold in exosomes of CKD patients compared to healthy controls. Using a cell culture system for CKD indicated that urinary exosomes might indeed originate from renal proximal tubular epithelial cells.

Changes in the miRNA-mRNA Regulatory Network Precede Motor Symptoms in a Mouse Model of Multiple System Atrophy: Clinical Implications.

Multiple system atrophy (MSA) is a fatal rapidly progressive α-synucleinopathy, characterized by α-synuclein accumulation in oligodendrocytes. It is accepted that the pathological α-synuclein accumulation in the brain of MSA patients plays a leading role in the disease process, but little is known about the events in the early stages of the disease. In this study we aimed to define potential roles of the miRNA-mRNA regulatory network in the early pre-motor stages of the disease, i.e., downstream of α-synuclein accumulation in oligodendroglia, as assessed in a transgenic mouse model of MSA. We investigated the expression patterns of miRNAs and their mRNA targets in substantia nigra (SN) and striatum, two brain regions that undergo neurodegeneration at a later stage in the MSA model, by microarray and RNA-seq analysis, respectively. Analysis was performed at a time point when α-synuclein accumulation was already present in oligodendrocytes at neuropathological examination, but no neuronal loss nor deficits of motor function had yet occurred. Our data provide a first evidence for the leading role of gene dysregulation associated with deficits in immune and inflammatory responses in the very early, non-symptomatic disease stages of MSA. While dysfunctional homeostasis and oxidative stress were prominent in SN in the early stages of MSA, in striatum differential gene expression in the non-symptomatic phase was linked to oligodendroglial dysfunction, disturbed protein handling, lipid metabolism, transmembrane transport and altered cell death control, respectively. A large number of putative miRNA-mRNAs interaction partners were identified in relation to the control of these processes in the MSA model. Our results support the role of early changes in the miRNA-mRNA regulatory network in the pathogenesis of MSA preceding the clinical onset of the disease. The findings thus contribute to understanding the disease process and are likely to pave the way towards identifying disease biomarkers for early diagnosis of MSA.

OncomiRdbB: a comprehensive database of microRNAs and their targets in breast cancer.

BACKGROUND: Given the estimate that 30% of our genes are controlled by microRNAs, it is essential that we understand the precise relationship between microRNAs and their targets. OncomiRs are microRNAs (miRNAs) that have been frequently shown to be deregulated in cancer. However, although several oncomiRs have been identified and characterized, there is as yet no comprehensive compilation of this data which has rendered it underutilized by cancer biologists. There is therefore an unmet need in generating bioinformatic platforms to speed the identification of novel therapeutic targets. DESCRIPTION: We describe here OncomiRdbB, a comprehensive database of oncomiRs mined from different existing databases for mouse and humans along with novel oncomiRs that we have validated in human breast cancer samples. The database also lists their respective predicted targets, identified using miRanda, along with their IDs, sequences, chromosome location and detailed description. This database facilitates querying by search strings including microRNA name, sequence, accession number, target genes and organisms. The microRNA networks and their hubs with respective targets at 3'UTR, 5'UTR and exons of different pathway genes were also deciphered using the 'R' algorithm. CONCLUSION: OncomiRdbB is a comprehensive and integrated database of oncomiRs and their targets in breast cancer with multiple query options which will help enhance both understanding of the biology of breast cancer and the development of new and innovative microRNA based diagnostic tools and targets of therapeutic significance. OncomiRdbB is freely available for download through the URL link http://tdb.ccmb.res.in/OncomiRdbB/index.htm.