Acetylation of KLF5 maintains EMT and tumorigenicity to cause chemoresistant bone metastasis in prostate cancer.

Advanced prostate cancer (PCa) often develops bone metastasis, for which therapies are very limited and the underlying mechanisms are poorly understood. We report that bone-borne TGF-ß induces the acetylation of transcription factor KLF5 in PCa bone metastases, and acetylated KLF5 (Ac-KLF5) causes osteoclastogenesis and bone metastatic lesions by activating CXCR4, which leads to IL-11 secretion, and stimulating SHH/IL-6 paracrine signaling. While essential for maintaining the mesenchymal phenotype and tumorigenicity, Ac-KLF5 also causes resistance to docetaxel in tumors and bone metastases, which is overcome by targeting CXCR4 with FDA-approved plerixafor. Establishing a mechanism for bone metastasis and chemoresistance in PCa, these findings provide a rationale for treating chemoresistant bone metastasis of PCa with inhibitors of Ac-KLF5/CXCR4 signaling.

Immunological Fingerprints of Controllers Developing Neutralizing HIV-1 Antibodies.

The induction of broadly neutralizing antibodies (bnAbs) is highly desired for an effective vaccine against HIV-1. Typically, bnAbs develop in patients with high viremia, but they can also evolve in some untreated HIV-1 controllers with low viral loads. Here, we identify a subgroup of neutralizer-controllers characterized by myeloid DCs (mDCs) with a distinct inflammatory signature and a superior ability to prime T follicular helper (Tfh)-like cells in an STAT4-dependent fashion. This distinct immune profile is associated with a higher frequency of Tfh-like cells in peripheral blood (pTfh) and an enrichment for Tfh-defining genes in circulating CD4+ T cells. Correspondingly, monocytes from this neutralizer controller subgroup upregulate genes encoding for chemotaxis and inflammation, and they secrete high levels of IL-12 in response to TLR stimulation. Our results suggest the existence of multi-compartment immune networks between mDCs, Tfh, and monocytes that may facilitate the development of bnAbs in a subgroup of HIV-1 controllers.

Immunologic alterations in the pancreatic cancer microenvironment of patients treated with neoadjuvant chemotherapy and radiotherapy.

Pancreatic ductal adenocarcinoma (PDAC) has dismal 5-year survival (<9%). We hypothesize that exposure of tumors to conventional therapies may preferentially modulate immune biomarkers in the tumor microenvironment in PDAC. PDAC patients who underwent upfront surgical resection or who received neoadjuvant FOLFIRINOX with or without neoadjuvant radiotherapy followed by surgical resection were selected for study. Total expression of immunologically relevant transcripts and spatially resolved expression of immunologically relevant proteins was quantitated using multiplexed methods (NanoString nCounter and GeoMX platforms). This analysis identified numerous differentially expressed transcripts associated with the type of neoadjuvant therapy received. Moreover, we identified significant alterations in the expression and/or spatial distribution of immunologically relevant proteins in different regions (tumor cell rich, immune cell rich, stromal cell rich) of the tumor microenvironment. These data provide insight into the immunological effects of clinically relevant neoadjuvant therapy for resectable/borderline-resectable PDAC by describing significant differences in the expression of key immunologic biomarkers within the PDAC microenvironment that were associated with the type of treatment patients received prior to surgical resection. This represents a comprehensive analysis of numerous biomarkers conducted on the PDAC microenvironment. This work may guide strategic new combination therapies for pancreatic cancer.

Gliosarcoma: distinct molecular pathways and genomic alterations identified by DNA copy number/SNP microarray analysis.

PURPOSE: Gliosarcoma is a histologic variant of glioblastoma (GBM), and like GBM carries a poor prognosis. Median survival is less than one (1) year with less than 5% of patients alive after 5 years. Although there is no cure, standard treatment includes surgery, radiation and chemotherapy. While very similar to GBM, gliosarcoma exhibits several distinct differences, morphologically and molecularly. Therefore, we report a comprehensive analysis of DNA copy number changes in gliosarcoma using a cytogenomic DNA copy number (CN) microarray (OncoScan®). METHODS: Cytogenomic DNA copy number microarray (OncoScan®) was performed on 18 cases of gliosarcoma. MetaCore™ enrichment was applied to the array results to detect associated molecular pathways. RESULTS: The most frequent alteration was copy number loss, comprising 57% of total copy number changes. The number of losses far exceeded the number of amplifications (***, < 0.001) and loss of heterozygosity events (***, < 0.001). Amplifications were infrequent (4.6%), particularly for EGFR. Chromosomes 9 and 10 had the highest number of losses; a large portion of which correlated to CDKN2A/B loss. Copy number gains were the second most common alteration (26.2%), with the majority occurring on chromosome 7. MetaCore™ enrichment detected notable pathways for copy number gains including: HOXA, Rho family of GTPases, and EGFR; copy number loss including: WNT, NF-kß, and CDKN2A; and copy number loss of heterozygosity including: WNT and p53. CONCLUSIONS: The pathways and copy number alterations detected in this study may represent key drivers in gliosarcoma oncogenesis and may provide a starting point toward targeted oncologic analysis with therapeutic potential.

Anti-apoptotic Protein BIRC5 Maintains Survival of HIV-1-Infected CD4+ T Cells.

HIV-1 infection of CD4+ T cells leads to cytopathic effects and cell demise, which is counter to the observation that certain HIV-1-infected cells possess a remarkable long-term stability and can persist lifelong in infected individuals treated with suppressive antiretroviral therapy (ART). Using quantitative mass spectrometry-based proteomics, we showed that HIV-1 infection activated cellular survival programs that were governed by BIRC5, a molecular inhibitor of cell apoptosis that is frequently overexpressed in malignant cells. BIRC5 and its upstream regulator OX40 were upregulated in productively and latently infected CD4+ T cells and were functionally involved in maintaining their viability. Moreover, OX40-expressing CD4+ T cells from ART-treated patients were enriched for clonally expanded HIV-1 sequences, and pharmacological inhibition of BIRC5 resulted in a selective decrease of HIV-1-infected cells in vitro. Together, these findings suggest that BIRC5 supports long-term survival of HIV-1-infected cells and may lead to clinical strategies to reduce persisting viral reservoirs.

Transcriptional Changes during Naturally Acquired Zika Virus Infection Render Dendritic Cells Highly Conducive to Viral Replication.

Although dendritic cells are among the human cell population best equipped for cell-intrinsic antiviral immune defense, they seem highly susceptible to infection with the Zika virus (ZIKV). Using highly purified myeloid dendritic cells isolated from individuals with naturally acquired acute infection, we here show that ZIKV induces profound perturbations of transcriptional signatures relative to healthy donors. Interestingly, we noted a remarkable downregulation of antiviral interferon-stimulated genes and innate immune sensors, suggesting that ZIKV can actively suppress interferon-dependent immune responses. In contrast, several host factors known to support ZIKV infection were strongly upregulated during natural ZIKV infection; these transcripts included AXL, the main entry receptor for ZIKV; SOCS3, a negative regulator of ISG expression; and IDO-1, a recognized inducer of regulatory T cell responses. Thus, during in vivo infection, ZIKV can transform the transcriptome of dendritic cells in favor of the virus to render these cells highly conducive to ZIKV infection.

Clonal expansion of genome-intact HIV-1 in functionally polarized Th1 CD4+ T cells.

HIV-1 causes a chronic, incurable disease due to its persistence in CD4+ T cells that contain replication-competent provirus, but exhibit little or no active viral gene expression and effectively resist combination antiretroviral therapy (cART). These latently infected T cells represent an extremely small proportion of all circulating CD4+ T cells but possess a remarkable long-term stability and typically persist throughout life, for reasons that are not fully understood. Here we performed massive single-genome, near-full-length next-generation sequencing of HIV-1 DNA derived from unfractionated peripheral blood mononuclear cells, ex vivo-isolated CD4+ T cells, and subsets of functionally polarized memory CD4+ T cells. This approach identified multiple sets of independent, near-full-length proviral sequences from cART-treated individuals that were completely identical, consistent with clonal expansion of CD4+ T cells harboring intact HIV-1. Intact, near-full-genome HIV-1 DNA sequences that were derived from such clonally expanded CD4+ T cells constituted 62% of all analyzed genome-intact sequences in memory CD4 T cells, were preferentially observed in Th1-polarized cells, were longitudinally detected over a duration of up to 5 years, and were fully replication- and infection-competent. Together, these data suggest that clonal proliferation of Th1-polarized CD4+ T cells encoding for intact HIV-1 represents a driving force for stabilizing the pool of latently infected CD4+ T cells.

A network based approach to drug repositioning identifies plausible candidates for breast cancer and prostate cancer.

BACKGROUND: The high cost and the long time required to bring drugs into commerce is driving efforts to repurpose FDA approved drugs-to find new uses for which they weren't intended, and to thereby reduce the overall cost of commercialization, and shorten the lag between drug discovery and availability. We report on the development, testing and application of a promising new approach to repositioning. METHODS: Our approach is based on mining a human functional linkage network for inversely correlated modules of drug and disease gene targets. The method takes account of multiple information sources, including gene mutation, gene expression, and functional connectivity and proximity of within module genes. RESULTS: The method was used to identify candidates for treating breast and prostate cancer. We found that (i) the recall rate for FDA approved drugs for breast (prostate) cancer is 20/20 (10/11), while the rates for drugs in clinical trials were 131/154 and 82/106; (ii) the ROC/AUC performance substantially exceeds that of comparable methods; (iii) preliminary in vitro studies indicate that 5/5 candidates have therapeutic indices superior to that of Doxorubicin in MCF7 and SUM149 cancer cell lines. We briefly discuss the biological plausibility of the candidates at a molecular level in the context of the biological processes that they mediate. CONCLUSIONS: Our method appears to offer promise for the identification of multi-targeted drug candidates that can correct aberrant cellular functions. In particular the computational performance exceeded that of other CMap-based methods, and in vitro experiments indicate that 5/5 candidates have therapeutic indices superior to that of Doxorubicin in MCF7 and SUM149 cancer cell lines. The approach has the potential to provide a more efficient drug discovery pipeline.

Method designed to respect molecular heterogeneity can profoundly correct present data interpretations for genome-wide expression analysis.

Although genome-wide expression analysis has become a routine tool for gaining insight into molecular mechanisms, extraction of information remains a major challenge. It has been unclear why standard statistical methods, such as the t-test and ANOVA, often lead to low levels of reproducibility, how likely applying fold-change cutoffs to enhance reproducibility is to miss key signals, and how adversely using such methods has affected data interpretations. We broadly examined expression data to investigate the reproducibility problem and discovered that molecular heterogeneity, a biological property of genetically different samples, has been improperly handled by the statistical methods. Here we give a mathematical description of the discovery and report the development of a statistical method, named HTA, for better handling molecular heterogeneity. We broadly demonstrate the improved sensitivity and specificity of HTA over the conventional methods and show that using fold-change cutoffs has lost much information. We illustrate the especial usefulness of HTA for heterogeneous diseases, by applying it to existing data sets of schizophrenia, bipolar disorder and Parkinson's disease, and show it can abundantly and reproducibly uncover disease signatures not previously detectable. Based on 156 biological data sets, we estimate that the methodological issue has affected over 96% of expression studies and that HTA can profoundly correct 86% of the affected data interpretations. The methodological advancement can better facilitate systems understandings of biological processes, render biological inferences that are more reliable than they have hitherto been and engender translational medical applications, such as identifying diagnostic biomarkers and drug prediction, which are more robust.

An all-statistics, high-speed algorithm for the analysis of copy number variation in genomes.

Detection of copy number variation (CNV) in DNA has recently become an important method for understanding the pathogenesis of cancer. While existing algorithms for extracting CNV from microarray data have worked reasonably well, the trend towards ever larger sample sizes and higher resolution microarrays has vastly increased the challenges they face. Here, we present Segmentation analysis of DNA (SAD), a clustering algorithm constructed with a strategy in which all operational decisions are based on simple and rigorous applications of statistical principles, measurement theory and precise mathematical relations. Compared with existing packages, SAD is simpler in formulation, more user friendly, much faster and less thirsty for memory, offers higher accuracy and supplies quantitative statistics for its predictions. Unique among such algorithms, SAD's running time scales linearly with array size; on a typical modern notebook, it completes high-quality CNV analyses for a 250 thousand-probe array in ∼1 s and a 1.8 million-probe array in ∼8 s.