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Imaging is increasingly used to detect and monitor bacterial infection. Both anatomic (X-rays, computed tomography, ultrasound, and MRI) and nuclear medicine ([111In]-WBC SPECT, [18F]FDG PET) techniques are used in clinical practice but lack specificity for the causative microorganisms themselves. To meet this challenge, many groups have developed imaging methods that target pathogen-specific metabolism, including PET tracers integrated into the bacterial cell wall. We have previously reported the d-amino acid derived PET radiotracers d-methyl-[11C]-methionine, d-[3-11C]-alanine, and d-[3-11C]-alanine-d-alanine, which showed robust bacterial accumulation in vitro and in vivo. Given the clinical importance of radionuclide half-life, in the current study, we developed [18F]3,3,3-trifluoro-d-alanine (d-[18F]-CF3-ala), a fluorine-18 labeled tracer. We tested the hypothesis that d-[18F]-CF3-ala would be incorporated into bacterial peptidoglycan given its structural similarity to d-alanine itself. NMR analysis showed that the fluorine-19 parent amino acid d-[19F]-CF3-ala was stable in human and mouse serum. d-[19F]-CF3-ala was also a poor substrate for d-amino acid oxidase, the enzyme largely responsible for mammalian d-amino acid metabolism and a likely contributor to background signals using d-amino acid derived PET tracers. In addition, d-[19F]-CF3-ala showed robust incorporation into Escherichia coli peptidoglycan, as detected by HPLC/mass spectrometry. Based on these promising results, we developed a radiosynthesis of d-[18F]-CF3-ala via displacement of a bromo-precursor with [18F]fluoride followed by chiral stationary phase HPLC. Unexpectedly, the accumulation of d-[18F]-CF3-ala by bacteria in vitro was highest for Gram-negative pathogens in particular E. coli. In a murine model of acute bacterial infection, d-[18F]-CF3-ala could distinguish live from heat-killed E. coli, with low background signals. These results indicate the viability of [18F]-modified d-amino acids for infection imaging and indicate that improved specificity for bacterial metabolism can improve tracer performance.

Crucial transitions in cancer-including tumor initiation, local expansion, metastasis, and therapeutic resistance-involve complex interactions between cells within the dynamic tumor ecosystem. Transformative single-cell genomics technologies and spatial multiplex in situ methods now provide an opportunity to interrogate this complexity at unprecedented resolution. The Human Tumor Atlas Network (HTAN), part of the National Cancer Institute (NCI) Cancer Moonshot Initiative, will establish a clinical, experimental, computational, and organizational framework to generate informative and accessible three-dimensional atlases of cancer transitions for a diverse set of tumor types. This effort complements both ongoing efforts to map healthy organs and previous large-scale cancer genomics approaches focused on bulk sequencing at a single point in time. Generating single-cell, multiparametric, longitudinal atlases and integrating them with clinical outcomes should help identify novel predictive biomarkers and features as well as therapeutically relevant cell types, cell states, and cellular interactions across transitions. The resulting tumor atlases should have a profound impact on our understanding of cancer biology and have the potential to improve cancer detection, prevention, and therapeutic discovery for better precision-medicine treatments of cancer patients and those at risk for cancer.

Intratumoral heterogeneity in cancers arises from genomic instability and epigenomic plasticity and is associated with resistance to cytotoxic and targeted therapies. We show here that cell-state heterogeneity, defined by differentiation-state marker expression, is high in triple-negative and basal-like breast cancer subtypes, and that drug tolerant persister (DTP) cell populations with altered marker expression emerge during treatment with a wide range of pathway-targeted therapeutic compounds. We show that MEK and PI3K/mTOR inhibitor-driven DTP states arise through distinct cell-state transitions rather than by Darwinian selection of preexisting subpopulations, and that these transitions involve dynamic remodeling of open chromatin architecture. Increased activity of many chromatin modifier enzymes, including BRD4, is observed in DTP cells. Co-treatment with the PI3K/mTOR inhibitor BEZ235 and the BET inhibitor JQ1 prevents changes to the open chromatin architecture, inhibits the acquisition of a DTP state, and results in robust cell death in vitro and xenograft regression in vivo.

To build a catalog of peptides presented by breast cancer cells, we undertook systematic MHC class I immunoprecipitation followed by elution of MHC class I-loaded peptides in breast cancer cells. We determined the sequence of 3196 MHC class I ligands representing 1921 proteins from a panel of 20 breast cancer cell lines. After removing duplicate peptides, i.e., the same peptide eluted from more than one cell line, the total number of unique peptides was 2740. Of the unique peptides eluted, more than 1750 had been previously identified, and of these, sixteen have been shown to be immunogenic. Importantly, half of these immunogenic peptides were shared between different breast cancer cell lines. MHC class I binding probability was used to plot the distribution of the eluted peptides in accordance with the binding score for each breast cancer cell line. We also determined that the tested breast cancer cells presented 89 mutation-containing peptides and peptides derived from aberrantly translated genes, 7 of which were shared between four or two different cell lines. Overall, the high throughput identification of MHC class I-loaded peptides is an effective strategy for systematic characterization of cancer peptides, and could be employed for design of multi-peptide anticancer vaccines.SignificanceBy employing proteomic analyses of eluted peptides from breast cancer cells, the current study has built an initial HLA-I-typed antigen collection for breast cancer research. It was also determined that immunogenic epitopes can be identified using established cell lines and that shared immunogenic peptides can be found in different cancer types such as breast cancer and leukemia. Importantly, out of 3196 eluted peptides that included duplicate peptides in different cells 89 peptides either contained mutation in their sequence or were derived from aberrant translation suggesting that mutation-containing epitopes are on the order of 2-3% in breast cancer cells. Finally, our results suggest that interfering with MHC class I function is one of the mechanisms of how tumor cells escape immune system attack.

The Library of Integrated Network-Based Cellular Signatures (LINCS) is an NIH Common Fund program that catalogs how human cells globally respond to chemical, genetic, and disease perturbations. Resources generated by LINCS include experimental and computational methods, visualization tools, molecular and imaging data, and signatures. By assembling an integrated picture of the range of responses of human cells exposed to many perturbations, the LINCS program aims to better understand human disease and to advance the development of new therapies. Perturbations under study include drugs, genetic perturbations, tissue micro-environments, antibodies, and disease-causing mutations. Responses to perturbations are measured by transcript profiling, mass spectrometry, cell imaging, and biochemical methods, among other assays. The LINCS program focuses on cellular physiology shared among tissues and cell types relevant to an array of diseases, including cancer, heart disease, and neurodegenerative disorders. This Perspective describes LINCS technologies, datasets, tools, and approaches to data accessibility and reusability.

In the version of this article that was published on PubMed [1] the author's name "Mark A. Dane" was formatted incorrectly in the XML mark up and therefore appeared incorrectly on PubMed. In the XML mark up, the middle initial "A" was added as a Particle when it should have been included as a Given Name. Due to this error, the author's name was incorrectly formatted in PubMed as "A Dane M" and not as "Dane MA". The author's name is correct on the BioMed Central website. The author's name in the XML of the original article [1] has been updated accordingly.

Molecular networks governing responses to targeted therapies in cancer cells are complex dynamic systems that demonstrate nonintuitive behaviors. We applied a novel computational strategy to infer probabilistic causal relationships between network components based on gene expression. We constructed a model comprised of an ensemble of networks using multidimensional data from cell line models of cell-cycle arrest caused by inhibition of MEK1/2. Through simulation of a reverse-engineered Bayesian network model, we generated predictions of G1-S transition. The model identified known components of the cell-cycle machinery, such as CCND1, CCNE2, and CDC25A, as well as revealed novel regulators of G1-S transition, IER2, TRIB1, TRIM27. Experimental validation of model predictions confirmed 10 of 12 predicted genes to have a role in G1-S progression. Further analysis showed that TRIB1 regulated the cyclin D1 promoter via NFκB and AP-1 sites and sensitized cells to TRAIL-induced apoptosis. In clinical specimens of breast cancer, TRIB1 levels correlated with expression of NFκB and its target genes (IL8, CSF2), and TRIB1 copy number and expression were predictive of clinical outcome. Together, our results establish a critical role of TRIB1 in cell cycle and survival that is mediated via the modulation of NFκB signaling. Cancer Res; 77(7); 1575-85. ©2017 AACR.

Bicarbonate and CO2 are essential substrates for carboxylation reactions in bacterial central metabolism. In Staphylococcus aureus, the bicarbonate transporter, MpsABC (membrane potential-generating system) is the only carbon concentrating system. An mpsABC deletion mutant can hardly grow in ambient air. In this study, we investigated the changes that occur in S. aureus when it suffers from CO2/bicarbonate deficiency. Electron microscopy revealed that ΔmpsABC has a twofold thicker cell wall thickness compared to the parent strain. The mutant was also substantially inert to cell lysis induced by lysostaphin and the non-ionic surfactant Triton X-100. Mass spectrometry analysis of muropeptides revealed the incorporation of alanine into the pentaglycine interpeptide bridge, which explains the mutant's lysostaphin resistance. Flow cytometry analysis of wall teichoic acid (WTA) glycosylation patterns revealed a significantly lower α-glycosylated and higher ß-glycosylated WTA, explaining the mutant's increased resistance towards Triton X-100. Comparative transcriptome analysis showed altered gene expression profiles. Autolysin-encoding genes such as sceD, a lytic transglycosylase encoding gene, were upregulated, like in vancomycin-intermediate S. aureus mutants (VISA). Genes related to cell wall-anchored proteins, secreted proteins, transporters, and toxins were downregulated. Overall, we demonstrate that bicarbonate deficiency is a stress response that causes changes in cell wall composition and global gene expression resulting in increased resilience to cell wall lytic enzymes and detergents. [ABSTRACT FROM AUTHOR]

Sample preparation is critical to biological electron microscopy (EM), and there have been continuous efforts on optimizing the procedures to best preserve structures of interest in the sample. However, a quantitative characterization of the morphological changes associated with each step in EM sample preparation is currently lacking. Using correlative EM and superresolution microscopy (SRM), we have examined the effects of different drying methods as well as osmium tetroxide (OsO4) post-fixation on cell morphology during scanning electron microscopy (SEM) sample preparation. Here, SRM images of the sample acquired under hydrated conditions were used as a baseline for evaluating morphological changes as the sample went through SEM sample processing. We found that both chemical drying and critical point drying lead to a mild cellular boundary retraction of ~60 nm. Post-fixation by OsO4 causes at least 40 nm additional boundary retraction. We also found that coating coverslips with adhesion molecules such as fibronectin prior to cell plating helps reduce cell distortion from OsO4 post-fixation. These quantitative measurements offer useful information for identifying causes of cell distortions in SEM sample preparation and improving current procedures.

PurposeThe recent increase in the incidence of ductal carcinoma in situ (DCIS) has sparked debate over the classification and treatment of this disease. Although DCIS is considered a precursor lesion to invasive breast cancer, some DCIS may have more or less risk than is realized. In this study, we characterized the immune microenvironment in DCIS to determine if immune infiltrates are predictive of recurrence.MethodsFifty-two cases of high-grade DCIS (HG-DCIS), enriched for large lesions and a history of recurrence, were age matched with 65 cases of non-high-grade DCIS (nHG-DCIS). Immune infiltrates were characterized by single- or dual-color staining of FFPE sections for the following antigens: CD4, CD8, CD20, FoxP3, CD68, CD115, Mac387, MRC1, HLA-DR, and PCNA. Nuance multispectral imaging software was used for image acquisition. Protocols for automated image analysis were developed using CellProfiler. Immune cell populations associated with risk of recurrence were identified using classification and regression tree analysis.ResultsHG-DCIS had significantly higher percentages of FoxP3+ cells, CD68+ and CD68+PCNA+ macrophages, HLA-DR+ cells, CD4+ T cells, CD20+ B cells, and total tumor infiltrating lymphocytes compared to nHG-DCIS. A classification tree, generated from 16 immune cell populations and 8 clinical parameters, identified three immune cell populations associated with risk of recurrence: CD8+HLADR+ T cells, CD8+HLADR- T cells, and CD115+ cells.ConclusionThese findings suggest that the tumor immune microenvironment is an important factor in identifying DCIS cases with the highest risk for recurrence and that manipulating the immune microenvironment may be an efficacious strategy to alter or prevent disease progression.

BackgroundHigh mitotic activity is associated with the genesis and progression of many cancers. Small molecule inhibitors of mitotic apparatus proteins are now being developed and evaluated clinically as anticancer agents. With clinical trials of several of these experimental compounds underway, it is important to understand the molecular mechanisms that determine high mitotic activity, identify tumor subtypes that carry molecular aberrations that confer high mitotic activity, and to develop molecular markers that distinguish which tumors will be most responsive to mitotic apparatus inhibitors.MethodsWe identified a coordinately regulated mitotic apparatus network by analyzing gene expression profiles for 53 malignant and non-malignant human breast cancer cell lines and two separate primary breast tumor datasets. We defined the mitotic network activity index (MNAI) as the sum of the transcriptional levels of the 54 coordinately regulated mitotic apparatus genes. The effect of those genes on cell growth was evaluated by small interfering RNA (siRNA).ResultsHigh MNAI was enriched in basal-like breast tumors and was associated with reduced survival duration and preferential sensitivity to inhibitors of the mitotic apparatus proteins, polo-like kinase, centromere associated protein E and aurora kinase designated GSK462364, GSK923295 and GSK1070916, respectively. Co-amplification of regions of chromosomes 8q24, 10p15-p12, 12p13, and 17q24-q25 was associated with the transcriptional upregulation of this network of 54 mitotic apparatus genes, and we identify transcription factors that localize to these regions and putatively regulate mitotic activity. Knockdown of the mitotic network by siRNA identified 22 genes that might be considered as additional therapeutic targets for this clinically relevant patient subgroup.ConclusionsWe define a molecular signature which may guide therapeutic approaches for tumors with high mitotic network activity.

The cellular heterogeneity and complex tissue architecture of most tumor samples is a major obstacle in image analysis on standard hematoxylin and eosin-stained (H&E) tissue sections. A mixture of cancer and normal cells complicates the interpretation of their cytological profiles. Furthermore, spatial arrangement and architectural organization of cells are generally not reflected in cellular characteristics analysis. To address these challenges, first we describe an automatic nuclei segmentation of H&E tissue sections. In the task of deconvoluting cellular heterogeneity, we adopt Landmark based Spectral Clustering (LSC) to group individual nuclei in such a way that nuclei in the same group are more similar. We next devise spatial statistics for analyzing spatial arrangement and organization, which are not detectable by individual cellular characteristics. Our quantitative, spatial statistics analysis could benefit H&E section analysis by refining and complementing cellular characteristics analysis.

It remains unclear whether causal, rather than merely correlational, relationships in molecular networks can be inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective, and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess inferred molecular networks in a causal sense.

Melanoma is difficult to treat once it becomes metastatic. However, the precise ancestral relationship between primary tumors and their metastases is not well understood. We performed whole-exome sequencing of primary melanomas and multiple matched metastases from eight patients to elucidate their phylogenetic relationships. In six of eight patients, we found that genetically distinct cell populations in the primary tumor metastasized in parallel to different anatomic sites, rather than sequentially from one site to the next. In five of these six patients, the metastasizing cells had themselves arisen from a common parental subpopulation in the primary, indicating that the ability to establish metastases is a late-evolving trait. Interestingly, we discovered that individual metastases were sometimes founded by multiple cell populations of the primary that were genetically distinct. Such establishment of metastases by multiple tumor subpopulations could help explain why identical resistance variants are identified in different sites after initial response to systemic therapy. One primary tumor harbored two subclones with different oncogenic mutations in CTNNB1, which were both propagated to the same metastasis, raising the possibility that activation of wingless-type mouse mammary tumor virus integration site (WNT) signaling may be involved, as has been suggested by experimental models.

Rat sarcoma (Ras) GTPases regulate cell proliferation and survival through effector pathways including Raf-MAPK, and are the most frequently mutated genes in human cancer. Although it is well established that Ras activity requires binding to both GTP and the membrane, details of how Ras operates on the cell membrane to activate its effectors remain elusive. Efforts to target mutant Ras in human cancers to therapeutic benefit have also been largely unsuccessful. Here we show that Ras-GTP forms dimers to activate MAPK. We used quantitative photoactivated localization microscopy (PALM) to analyze the nanoscale spatial organization of PAmCherry1-tagged KRas 4B (hereafter referred to KRas) on the cell membrane under various signaling conditions. We found that at endogenous expression levels KRas forms dimers, and KRas(G12D), a mutant that constitutively binds GTP, activates MAPK. Overexpression of KRas leads to formation of higher order Ras nanoclusters. Conversely, at lower expression levels, KRas(G12D) is monomeric and activates MAPK only when artificially dimerized. Moreover, dimerization and signaling of KRas are both dependent on an intact CAAX (C, cysteine; A, aliphatic; X, any amino acid) motif that is also known to mediate membrane localization. These results reveal a new, dimerization-dependent signaling mechanism of Ras, and suggest Ras dimers as a potential therapeutic target in mutant Ras-driven tumors.

During the type-setting of the final version of the article [1] some of the additional files were swapped. The correct files are republished in this Erratum.