Preclinical 3D model screening reveals digoxin as an effective therapy for a rare and aggressive type of endometrial cancer.

OBJECTIVE: Dedifferentiated endometrial carcinoma (DDEC) characterized by SWItch/Sucrose Non-Fermentable (SWI/SNF) complex inactivation is a highly aggressive type of endometrial cancer without effective systemic therapy options. Its uncommon nature and aggressive disease trajectory pose significant challenges for therapeutic progress. To address this obstacle, we focused on developing preclinical models tailored to this tumor type and established patient tumor-derived three-dimensional (3D) spheroid models of DDEC. METHODS: High-throughput drug repurposing screens were performed on in vitro 3D spheroid models of DDEC cell lines (SMARCA4-inactivated DDEC-1 and ARID1A/ARID1B co-inactivated DDEC-2). The dose-response relationships of the identified candidate drugs were evaluated in vitro, followed by in vivo evaluation using xenograft models of DDEC-1 and DDEC-2. RESULTS: Drug screen in 3D models identified multiple cardiac glycosides including digoxin and digitoxin as candidate drugs in both DDEC-1 and DDEC-2. Subsequent in vitro dose-response analyses confirmed the inhibitory activity of digoxin and digitoxin with both drugs showing lower IC50 in DDEC cells compared to non-DDEC endometrial cancer cells. In in vivo xenograft models, digoxin significantly suppressed the growth of DDEC tumors at clinically relevant serum concentrations. CONCLUSION: Using biologically precise preclinical models of DDEC derived from patient tumor samples, our study identified digoxin as an effective drug in suppressing DDEC tumor growth. These findings provide compelling preclinical evidence for the use of digoxin as systemic therapy for SWI/SNF-inactivated DDEC, which may also be applicable to other SWI/SNF-inactivated tumor types.

Survey of NF1 inactivation by surrogate immunohistochemistry in ovarian carcinomas.

OBJECTIVE: Inhibition of the MAPK pathway by MEK inhibitors (MEKi) is currently a therapeutic standard in several cancer types, including ovarian low-grade serous carcinoma (LGSC). A common MAPK pathway alteration in tubo-ovarian high-grade serous carcinoma (HGSC) is the genomic inactivation of neurofibromin 1 (NF1). The primary objectives of our study were to survey the prevalence of NF1 inactivation in the principal ovarian carcinoma histotype as well as to evaluate its associations with clinico-pathological parameters and key biomarkers including BRCA1/2 status in HGSC. METHODS: A recently commercialized NF1 antibody (clone NFC) was orthogonally validated on an automated immunohistochemistry (IHC) platform and IHC was performed on tissue microarrays containing 2140 ovarian carcinoma cases. Expression was interpreted as loss/inactivated (complete or subclonal) versus normal/retained. RESULTS: Loss of NF1 expression was detected in 250/1429 (17.4%) HGSC including 11% with subclonal loss. Survival of NF1-inactivated HGSC patients was intermediate between favorable BRCA1/2 mutated HGSC and unfavorable CCNE1 high-level amplified HGSC. NF1 inactivation was mutually exclusive with CCNE1 high-level amplifications, co-occurred with RB1 loss and occurred at similar frequencies in BRCA1/2 mutated versus wild-type HGSC. NF1 loss was found in 21/286 (7.3%) endometrioid carcinomas with a favorable prognostic association (p = 0.048), and in 4/64 (5.9%) LGSC, mutually exclusive with other driver events. CONCLUSIONS: NF1 inactivation occurs in a significant subset of BRCA1/2 wild-type HGSC and a subset of LGSC. While the functional effects of NF1 inactivation need to be further characterized, this signifies a potential therapeutic opportunity to explore targeting NF1 inactivation in these tumors.

APOBEC1 cytosine deaminase activity on single-stranded DNA is suppressed by replication protein A.

Many APOBEC cytidine deaminase members are known to induce 'off-target' cytidine deaminations in 5'TC motifs in genomic DNA that contribute to cancer evolution. In this report, we characterized APOBEC1, which is a possible cancer related APOBEC since APOBEC1 mRNA is highly expressed in certain types of tumors, such as lung adenocarcinoma. We found a low level of APOBEC1-induced DNA damage, as measured by γH2AX foci, in genomic DNA of a lung cancer cell line that correlated to its inability to compete in vitro with replication protein A (RPA) for ssDNA. This suggests that RPA can act as a defense against off-target deamination for some APOBEC enzymes. Overall, the data support the model that the ability of an APOBEC to compete with RPA can better predict genomic damage than combined analysis of mRNA expression levels in tumors and analysis of mutation signatures.

Differential expression of HNF1A and HNF1A-AS1 in colon cancer cells.

The human hepatocyte nuclear factor 1 homeobox A (HNF1A) gene loci express the protein-coding HNF1A transcript and a long non-coding RNA in the anti-sense (HNF1A-AS1) direction. HNF1A-AS1 is expressed in numerous types of cancers and poor clinical outcomes such as higher mortality rates, greater metastatic capacity, and poor prognosis of the disease are the results of this expression. In this study, we determined the epigenetic features of the HNF1A gene loci, and expression and cellular localization of HNF1A-AS1 RNA, HNF1A RNA, and HNF1A protein in colorectal cancer (HT-29, HTC116, RKO, and SW480) and normal colon epithelial (CCD841) cells. The HT-29 HNF1A gene had active histone marks (H3K4me3, H3K27ac) and DNase 1 accessible sites at the promoter regions of the HNF1A and HNF1A-AS1 genes. These epigenetic marks were not observed in the other colorectal cancer cells or in the normal colon epithelial cells. Consistent with the active gene epigenetic signature of the HNF1A gene in HT-29 cells, HNF1A protein, and HNF1A/HNF1A-AS1 transcripts were detected in HT-29 cells but poorly, if at all observed, in the other cell types. In HT-29 cells, HNF1A-AS1 localized to the nucleus and was found to bind to the enhancer of zeste homolog 2 (EZH2, a member of PRC2 complex) and potentially form RNA-DNA triplexes with DNase 1 accessible sites in the HT-29 genome. These activities of HNF1A-AS1 may contribute to the oncogenic properties of this long non-coding RNA.

Identification of novel genes involved in apoptosis of HIV-infected macrophages using unbiased genome-wide screening.

BACKGROUND: Macrophages, besides resting latently infected CD4+ T cells, constitute the predominant stable, major non-T cell HIV reservoirs. Therefore, it is essential to eliminate both latently infected CD4+ T cells and tissue macrophages to completely eradicate HIV in patients. Until now, most of the research focus is directed towards eliminating latently infected CD4+ T cells. However, few approaches have been directed at killing of HIV-infected macrophages either in vitro or in vivo. HIV infection dysregulates the expression of many host genes essential for the survival of infected cells. We postulated that exploiting this alteration may yield novel targets for the selective killing of infected macrophages. METHODS: We applied a pooled shRNA-based genome-wide approach by employing a lentivirus-based library of shRNAs to screen novel gene targets whose inhibition should selectively induce apoptosis in HIV-infected macrophages. Primary human MDMs were infected with HIV-eGFP and HIV-HSA viruses. Infected MDMs were transfected with siRNAs specific for the promising genes followed by analysis of apoptosis by flow cytometry using labelled Annexin-V in HIV-infected, HIV-exposed but uninfected bystander MDMs and uninfected MDMs. The results were analyzed using student's t-test from at least four independent experiments. RESULTS: We validated 28 top hits in two independent HIV infection models. This culminated in the identification of four target genes, Cox7a2, Znf484, Cstf2t, and Cdk2, whose loss-of-function induced apoptosis preferentially in HIV-infected macrophages. Silencing these single genes killed significantly higher number of HIV-HSA-infected MDMs compared to the HIV-HSA-exposed, uninfected bystander macrophages, indicating the specificity in the killing of HIV-infected macrophages. The mechanism governing Cox7a2-mediated apoptosis of HIV-infected macrophages revealed that targeting respiratory chain complex II and IV genes also selectively induced apoptosis of HIV-infected macrophages possibly through enhanced ROS production. CONCLUSIONS: We have identified above-mentioned novel genes and specifically the respiratory chain complex II and IV genes whose silencing may cause selective elimination of HIV-infected macrophages and eventually the HIV-macrophage reservoirs. The results highlight the potential of the identified genes as targets for eliminating HIV-infected macrophages in physiological environment as part of an HIV cure strategy.

Estrogen receptor signaling regulates the expression of the breast tumor kinase in breast cancer cells.

BACKGROUND: BRK is, a non-receptor tyrosine kinase, overexpressed in approximately 85% of human invasive ductal breast tumors. It is not clear whether BRK expression correlates with breast cancer subtypes, or the expression has prognostic or diagnostic significance. Herein, we investigated the correlation of BRK with any breast cancer subtypes and clinicopathological significance of BRK expression in breast cancer. METHODS: In this study, we examined BRK expression in 120 breast tumor samples and 29 breast cancer cell lines to explore the positive correlation between BRK and the expression of ERα. We used immunohistochemistry, RT-PCR, and immunoblotting to analyse our experimental samples. RESULT: We demonstrate that estrogen induces BRK gene and protein expression in ER+ breast cancer cells. Over-expression of ERα in the ER-negative breast cancer cell line increased BRK expression, and knock-down of ESR1 in MCF7 cells reduced BRK levels. Further, we provide evidence that BRK is regulated by ERα signaling and the presence of ER antagonists (tamoxifen and fulvestrant) reduce the expression of BRK in ER-positive breast cancer cells. Finally, we demonstrate that the overall survival of ER-positive breast cancer patients is poor when their cancers express high levels of BRK. CONCLUSION: Our data indicate that BRK is a prognostic marker for ER+ breast cancers and provide a strong rationale for targeting BRK to improve patients' survival.

Biochemical characterization of INTS3 and C9ORF80, two subunits of hNABP1/2 heterotrimeric complex in nucleic acid binding.

Human nucleic acid-binding protein 1 and 2 (hNABP1 and hNABP2, also known as hSSB2 and hSSB1 respectively) form two separate and independent complexes with two identical proteins, integrator complex subunit 3 (INTS3) and C9ORF80. We and other groups have demonstrated that hNABP1 and 2 are single-stranded (ss) DNA- and RNA-binding proteins, and function in DNA repair; however, the function of INTS3 and C9OFR80 remains elusive. In the present study, we purified recombinant proteins INTS3 and C9ORF80 to near homogeneity. Both proteins exist as a monomer in solution; however, C9ORF80 exhibits anomalous behavior on SDS-PAGE and gel filtration because of 48% random coil present in the protein. Using electrophoretic mobility shift assay (EMSA), INTS3 displays higher affinity toward ssRNA than ssDNA, and C9ORF80 binds ssDNA but not ssRNA. Neither of them binds dsDNA, dsRNA, or RNA : DNA hybrid. INTS3 requires minimum of 30 nucleotides, whereas C9OFR80 requires 20 nucleotides for its binding, which increased with the increasing length of ssDNA. Interestingly, our GST pulldown results suggest that the N-terminus of INTS3 is involved in protein-protein interaction, while EMSA implies that the C-terminus is required for nucleic acid binding. Furthermore, we purified the INTS3-hNABP1/2-C9ORF80 heterotrimeric complex. It exhibits weaker binding compared with the individual hNABP1/2; interestingly, the hNABP1 complex prefers ssDNA, whereas hNABP2 complex prefers ssRNA. Using reconstituted heterotrimeric complex from individual proteins, EMSA demonstrates that INTS3, but not C9ORF80, affects the nucleic acid-binding ability of hNABP1 and hNABP2, indicating that INTS3 might regulate hNABP1/2's biological function, while the role of C9ORF80 remains unknown.

An integrated computational and experimental study uncovers FUT9 as a metabolic driver of colorectal cancer.

Metabolic alterations play an important role in cancer and yet, few metabolic cancer driver genes are known. Here we perform a combined genomic and metabolic modeling analysis searching for metabolic drivers of colorectal cancer. Our analysis predicts FUT9, which catalyzes the biosynthesis of Ley glycolipids, as a driver of advanced-stage colon cancer. Experimental testing reveals FUT9's complex dual role; while its knockdown enhances proliferation and migration in monolayers, it suppresses colon cancer cells expansion in tumorspheres and inhibits tumor development in a mouse xenograft models. These results suggest that FUT9's inhibition may attenuate tumor-initiating cells (TICs) that are known to dominate tumorspheres and early tumor growth, but promote bulk tumor cells. In agreement, we find that FUT9 silencing decreases the expression of the colorectal cancer TIC marker CD44 and the level of the OCT4 transcription factor, which is known to support cancer stemness. Beyond its current application, this work presents a novel genomic and metabolic modeling computational approach that can facilitate the systematic discovery of metabolic driver genes in other types of cancer.

Global phosphoproteomic analysis identifies SRMS-regulated secondary signaling intermediates.

BACKGROUND: The non-receptor tyrosine kinase, SRMS (Src-related kinase lacking C-terminal regulatory tyrosine and N-terminal myristoylation sites) is a member of the BRK family kinases (BFKs) which represents an evolutionarily conserved relative of the Src family kinases (SFKs). Tyrosine kinases are known to regulate a number of cellular processes and pathways via phosphorylating substrate proteins directly and/or by partaking in signaling cross-talks leading to the indirect modulation of various signaling intermediates. In a previous study, we profiled the tyrosine-phosphoproteome of SRMS and identified multiple candidate substrates of the kinase. The broader cellular signaling intermediates of SRMS are unknown. METHODS: In order to uncover the broader SRMS-regulated phosphoproteome and identify the SRMS-regulated indirect signaling intermediates, we performed label-free global phosphoproteomics analysis on cells expressing wild-type SRMS. Using computational database searching and bioinformatics analyses we characterized the dataset. RESULTS: Our analyses identified 60 hyperphosphorylated (phosphoserine/phosphothreonine) proteins mapped from 140 hyperphosphorylated peptides. Bioinfomatics analyses identified a number of significantly enriched biological and cellular processes among which DNA repair pathways were found to be upregulated while apoptotic pathways were found to be downregulated. Analyses of motifs derived from the upregulated phosphosites identified Casein kinase 2 alpha (CK2α) as one of the major potential kinases contributing to the SRMS-dependent indirect regulation of signaling intermediates. CONCLUSIONS: Overall, our phosphoproteomics analyses identified serine/threonine phosphorylation dynamics as important secondary events of the SRMS-regulated phosphoproteome with implications in the regulation of cellular and biological processes.

Interaction landscape of membrane-protein complexes in Saccharomyces cerevisiae.

Macromolecular assemblies involving membrane proteins (MPs) serve vital biological roles and are prime drug targets in a variety of diseases. Large-scale affinity purification studies of soluble-protein complexes have been accomplished for diverse model organisms, but no global characterization of MP-complex membership has been described so far. Here we report a complete survey of 1,590 putative integral, peripheral and lipid-anchored MPs from Saccharomyces cerevisiae, which were affinity purified in the presence of non-denaturing detergents. The identities of the co-purifying proteins were determined by tandem mass spectrometry and subsequently used to derive a high-confidence physical interaction map encompassing 1,726 membrane protein-protein interactions and 501 putative heteromeric complexes associated with the various cellular membrane systems. Our analysis reveals unexpected physical associations underlying the membrane biology of eukaryotes and delineates the global topological landscape of the membrane interactome.

Molecular characterization of breast cancer cell lines through multiple omic approaches.

BACKGROUND: Breast cancer cell lines are frequently used as model systems to study the cellular properties and biology of breast cancer. Our objective was to characterize a large, commonly employed panel of breast cancer cell lines obtained from the American Type Culture Collection (ATCC 30-4500 K) to enable researchers to make more informed decisions in selecting cell lines for specific studies. Information about these cell lines was obtained from a wide variety of sources. In addition, new information about cellular pathways that are activated within each cell line was generated. METHODS: We determined key protein expression data using immunoblot analyses. In addition, two analyses on serum-starved cells were carried out to identify cellular proteins and pathways that are activated in these cells. These analyses were performed using a commercial PathScan array and a novel and more extensive phosphopeptide-based kinome analysis that queries 1290 phosphorylation events in major signaling pathways. Data about this panel of breast cancer cell lines was also accessed from several online sources, compiled and summarized for the following areas: molecular classification, mRNA expression, mutational status of key proteins and other possible cancer-associated mutations, and the tumorigenic and metastatic capacity in mouse xenograft models of breast cancer. RESULTS: The cell lines that were characterized included 10 estrogen receptor (ER)-positive, 12 human epidermal growth factor receptor 2 (HER2)-amplified and 18 triple negative breast cancer cell lines, in addition to 4 non-tumorigenic breast cell lines. Within each subtype, there was significant genetic heterogeneity that could impact both the selection of model cell lines and the interpretation of the results obtained. To capture the net activation of key signaling pathways as a result of these mutational combinations, profiled pathway activation status was examined. This provided further clarity for which cell lines were particularly deregulated in common or unique ways. CONCLUSIONS: These two new kinase or "Kin-OMIC" analyses add another dimension of important data about these frequently used breast cancer cell lines. This will assist researchers in selecting the most appropriate cell lines to use for breast cancer studies and provide context for the interpretation of the emerging results.

Global map of SUMO function revealed by protein-protein interaction and genetic networks.

Systematic functional genomics approaches were used to map a network centered on the small ubiquitin-related modifier (SUMO) system. Over 250 physical interactions were identified using the SUMO protein as bait in affinity purification-mass spectrometry and yeast two-hybrid screens. More than 500 genes and 1400 synthetic genetic interactions were mapped by synthetic genetic array (SGA) analysis using eight different SUMO pathway query genes. The resultant global SUMO network highlights its role in 15 major biological processes and better defines functional relationships between the different components of the SUMO pathway. Using this information-rich resource, we have identified roles for the SUMO system in the function of the AAA ATPase Cdc48p, the regulation of lipid metabolism, localization of the ATP-dependent endonuclease Dna2p, and recovery from the DNA-damage checkpoint.

A High Through-put Platform for Recombinant Antibodies to Folded Proteins.

Antibodies are key reagents in biology and medicine, but commercial sources are rarely recombinant and thus do not provide a permanent and renewable resource. Here, we describe an industrialized platform to generate antigens and validated recombinant antibodies for 346 transcription factors (TFs) and 211 epigenetic antigens. We describe an optimized automated phage display and antigen expression pipeline that in aggregate produced about 3000 sequenced Fragment antigen-binding domain that had high affinity (typically EC50<20 nm), high stability (Tm∼80 °C), good expression in E. coli (∼5 mg/L), and ability to bind antigen in complex cell lysates. We evaluated a subset of Fabs generated to homologous SCAN domains for binding specificities. These Fragment antigen-binding domains were monospecific to their target SCAN antigen except in rare cases where they cross-reacted with a few highly related antigens. Remarkably, immunofluorescence experiments in six cell lines for 270 of the TF antigens, each having multiple antibodies, show that ∼70% stain predominantly in the cytosol and ∼20% stain in the nucleus which reinforces the dominant role that translocation plays in TF biology. These cloned antibody reagents are being made available to the academic community through our web site recombinant-antibodies.org to allow a more system-wide analysis of TF and chromatin biology. We believe these platforms, infrastructure, and automated approaches will facilitate the next generation of renewable antibody reagents to the human proteome in the coming decade.

Epigenetic silencing of CREB3L1 by DNA methylation is associated with high-grade metastatic breast cancers with poor prognosis and is prevalent in triple negative breast cancers.

BACKGROUND: CREB3L1 (cAMP-responsive element-binding protein 3-like protein 1), a member of the unfolded protein response, has recently been identified as a metastasis suppressor in both breast and bladder cancer. METHODS: Quantitative real time PCR (qPCR) and immunoblotting were used to determine the impact of histone deacetylation and DNA methylation inhibitors on CREB3L1 expression in breast cancer cell lines. Breast cancer cell lines and tumor samples were analyzed similarly, and CREB3L1 gene methylation was determined using sodium bisulfite conversion and DNA sequencing. Immunohistochemistry was used to determine nuclear versus cytoplasmic CREB3L1 protein. Large breast cancer database analyses were carried out to examine relationships between CREB3L1 gene methylation and mRNA expression in addition to CREB3L1 mRNA expression and prognosis. RESULTS: This study demonstrates that the low CREB3L1 expression previously seen in highly metastatic breast cancer cell lines is caused in part by epigenetic silencing. Treatment of several highly metastatic breast cancer cell lines that had low CREB3L1 expression with DNA methyltransferase and histone deacetylase inhibitors induced expression of CREB3L1, both mRNA and protein. In human breast tumors, CREB3L1 mRNA expression was upregulated in low and medium-grade tumors, most frequently of the luminal and HER2 amplified subtypes. In contrast, CREB3L1 expression was repressed in high-grade tumors, and its loss was most frequently associated with triple negative breast cancers (TNBCs). Importantly, bioinformatics analyses of tumor databases support these findings, with methylation of the CREB3L1 gene associated with TNBCs, and strongly negatively correlated with CREB3L1 mRNA expression. Decreased CREB3L1 mRNA expression was associated with increased tumor grade and reduced progression-free survival. An immunohistochemistry analysis revealed that low-grade breast tumors frequently had nuclear CREB3L1 protein, in contrast to the high-grade breast tumors in which CREB3L1 was cytoplasmic, suggesting that differential localization may also regulate CREB3L1 effectiveness in metastasis suppression. CONCLUSIONS: Our data further strengthens the role for CREB3L1 as a metastasis suppressor in breast cancer and demonstrates that epigenetic silencing is a major regulator of the loss of CREB3L1 expression. We also highlight that CREB3L1 expression is frequently altered in many cancer types suggesting that it could have a broader role in cancer progression and metastasis.

A negative genetic interaction map in isogenic cancer cell lines reveals cancer cell vulnerabilities.

Improved efforts are necessary to define the functional product of cancer mutations currently being revealed through large-scale sequencing efforts. Using genome-scale pooled shRNA screening technology, we mapped negative genetic interactions across a set of isogenic cancer cell lines and confirmed hundreds of these interactions in orthogonal co-culture competition assays to generate a high-confidence genetic interaction network of differentially essential or differential essentiality (DiE) genes. The network uncovered examples of conserved genetic interactions, densely connected functional modules derived from comparative genomics with model systems data, functions for uncharacterized genes in the human genome and targetable vulnerabilities. Finally, we demonstrate a general applicability of DiE gene signatures in determining genetic dependencies of other non-isogenic cancer cell lines. For example, the PTEN(-/-) DiE genes reveal a signature that can preferentially classify PTEN-dependent genotypes across a series of non-isogenic cell lines derived from the breast, pancreas and ovarian cancers. Our reference network suggests that many cancer vulnerabilities remain to be discovered through systematic derivation of a network of differentially essential genes in an isogenic cancer cell model.

PhenoM: a database of morphological phenotypes caused by mutation of essential genes in Saccharomyces cerevisiae.

About one-fifth of the genes in the budding yeast are essential for haploid viability and cannot be functionally assessed using standard genetic approaches such as gene deletion. To facilitate genetic analysis of essential genes, we and others have assembled collections of yeast strains expressing temperature-sensitive (ts) alleles of essential genes. To explore the phenotypes caused by essential gene mutation we used a panel of genetically engineered fluorescent markers to explore the morphology of cells in the ts strain collection using high-throughput microscopy. Here, we describe the design and implementation of an online database, PhenoM (Phenomics of yeast Mutants), for storing, retrieving, visualizing and data mining the quantitative single-cell measurements extracted from micrographs of the ts mutant cells. PhenoM allows users to rapidly search and retrieve raw images and their quantified morphological data for genes of interest. The database also provides several data-mining tools, including a PhenoBlast module for phenotypic comparison between mutant strains and a Gene Ontology module for functional enrichment analysis of gene sets showing similar morphological alterations. The current PhenoM version 1.0 contains 78,194 morphological images and 1,909,914 cells covering six subcellular compartments or structures for 775 ts alleles spanning 491 essential genes. PhenoM is freely available at http://phenom.ccbr.utoronto.ca/.

MEMO1 binds iron and modulates iron homeostasis in cancer cells.

Mediator of ERBB2-driven cell motility 1 (MEMO1) is an evolutionary conserved protein implicated in many biological processes; however, its primary molecular function remains unknown. Importantly, MEMO1 is overexpressed in many types of cancer and was shown to modulate breast cancer metastasis through altered cell motility. To better understand the function of MEMO1 in cancer cells, we analyzed genetic interactions of MEMO1 using gene essentiality data from 1028 cancer cell lines and found multiple iron-related genes exhibiting genetic relationships with MEMO1. We experimentally confirmed several interactions between MEMO1 and iron-related proteins in living cells, most notably, transferrin receptor 2 (TFR2), mitoferrin-2 (SLC25A28), and the global iron response regulator IRP1 (ACO1). These interactions indicate that cells with high-MEMO1 expression levels are hypersensitive to the disruptions in iron distribution. Our data also indicate that MEMO1 is involved in ferroptosis and is linked to iron supply to mitochondria. We have found that purified MEMO1 binds iron with high affinity under redox conditions mimicking intracellular environment and solved MEMO1 structures in complex with iron and copper. Our work reveals that the iron coordination mode in MEMO1 is very similar to that of iron-containing extradiol dioxygenases, which also display a similar structural fold. We conclude that MEMO1 is an iron-binding protein that modulates iron homeostasis in cancer cells.

Breast Tumor Metastasis and Its Microenvironment: It Takes Both Seed and Soil to Grow a Tumor and Target It for Treatment.

Metastasis remains a major challenge in treating breast cancer. Breast tumors metastasize to organ-specific locations such as the brain, lungs, and bone, but why some organs are favored over others remains unclear. Breast tumors also show heterogeneity, plasticity, and distinct microenvironments. This contributes to treatment failure and relapse. The interaction of breast cancer cells with their metastatic microenvironment has led to the concept that primary breast cancer cells act as seeds, whereas the metastatic tissue microenvironment (TME) is the soil. Improving our understanding of this interaction could lead to better treatment strategies for metastatic breast cancer. Targeted treatments for different subtypes of breast cancers have improved overall patient survival, even with metastasis. However, these targeted treatments are based upon the biology of the primary tumor and often these patients' relapse, after therapy, with metastatic tumors. The advent of immunotherapy allowed the immune system to target metastatic tumors. Unfortunately, immunotherapy has not been as effective in metastatic breast cancer relative to other cancers with metastases, such as melanoma. This review will describe the heterogeneic nature of breast cancer cells and their microenvironments. The distinct properties of metastatic breast cancer cells and their microenvironments that allow interactions, especially in bone and brain metastasis, will also be described. Finally, we will review immunotherapy approaches to treat metastatic breast tumors and discuss future therapeutic approaches to improve treatments for metastatic breast cancer.

Exploiting the determinants of stochastic gene expression in Saccharomyces cerevisiae for genome-wide prediction of expression noise.

Gene regulation is a process with many steps allowing for stochastic biochemical reactions, which leads to expression noise-i.e., the cell-to-cell stochastic fluctuation in protein abundance. Such expression noise can give rise to drastically diverse phenotypes, even within isogenic cell populations. Although numerous biophysical approaches had been proposed to model the origin and propagation of expression noise in biological networks, these models essentially characterize the innate stochastic dynamics in gene regulation in a mechanistic way. In this work, by investigating expression noise in the context of yeast cellular networks, we place the biophysical formulism onto solid genetic ground. At the sequence level, we show that extremely noisy genes are highly conserved in their coding sequences. At the level of cellular networks where natural selection is manifested by the topological constraints, we show that genes with varying expression noise are modularly organized in the protein interaction network and are positioned orderly in the gene regulatory network. We demonstrate that these topological constraints are highly predictive of stochastic gene expression, with which we were able to confidently predict stochastic expression for more than 2,000 yeast genes whose expression noise was previously not known. We validated the predictions by high-content cell imaging. Our approach makes feasible genome-wide prediction of stochastic gene expression, and such predictability in turn suggests that expression noise is an evolvable genetic trait.

A CRISPR Platform for Targeted In Vivo Screens.

Large-scale genetic screens are becoming increasingly used as powerful tools to query the genome to identify therapeutic targets in cancer. The advent of the CRISPR technology has revolutionized the effectiveness of these screens and has made it possible to carry out loss-of-function screens to identify cancer-specific genetic interactions. Such loss-of-function screens can be performed in silico, in vitro, and in vivo, depending on the scale of the screen, as well as research questions to be answered. Performing screens in vivo has its challenges but also advantages, providing opportunities to study the tumor microenvironment and cancer immunity. In this chapter, we present a procedural framework and associated notes for conducting in vivo CRISPR knockout screens in cancer models to study cancer biology, anti-tumor immune responses, tumor microenvironment, and predicting treatment responses.