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PDF file - 94K, Activation of ectopic E2F1 upregulates RBM38 expression in a p53-independent manner

The E2F family of transcription factors plays a pivotal role in the regulation of cell proliferation in higher eukaryotes and is a critical downstream target of the tumor suppressor pRB. The pRB/E2F pathway is defective in most human tumors, resulting in deregulated E2F activity that induces uncontrolled cell proliferation, a hallmark of tumor cells.The RNA-binding protein RBM38, also named RNPC1, induces cell-cycle arrest in G1, at least in part, via binding to and stabilizing the mRNA of the cyclin-dependent kinase inhibitor p21. RBM38 levels are altered in human cancer. Generally, RBM38 is overexpressed in various tumors; however, RBM38 mRNA levels are reduced in some breast tumors due to increased methylation of its promoter region.We show here that expression of RBM38 is regulated by E2F1. Specifically, RBM38 mRNA and protein levels are elevated upon activation of either exogenous E2F1 or endogenous E2Fs. Moreover, endogenous E2F1 binds the human RBM38 promoter and E2F1 knockdown reduces RBM38 levels. Our data raise the possibility that E2F1 together with E2F1-regulated RBM38 constitute a negative feedback loop that modulates E2F1 activity. In support of this, inhibition of RBM38 expression increases E2F1-mediated cell-cycle progression. Moreover, in human ovarian cancer, high correlation between expression of E2F1 and RBM38 is associated with increased survival.Overall, our data identify RBM38 as novel transcriptional target of E2F1 that restricts E2F1-induced proliferation. Furthermore, this negative feedback loop seems to restrict tumor aggressiveness, thereby promoting survival of patients with cancer. Mol Cancer Res; 10(9); 1169–77. ©2012 AACR.

PDF file - 171K, Activation of ectopic E2F1or endogenous E2F1 silencing regulates RBM38 levels

PDF file - 118K, Correlated expression of E2F1 and RBM38 is associated with increased survival in glioblastoma patients

PDF file - 125K, Correlated expression of E2F1 and RBM38 is associated with increased survival in breast cancer patients

PDF file - 132K, RBM38 restricts E2F1- induced G1-exit

Head and neck squamous cell carcinoma (HNSCC) is a global health problem. Successful immunotherapy in HNSCC is currently based on the ability to block the interaction of PD1 and PDL1 and abolish the inhibition of CD8+ T cells, thus enhancing the antitumor activity. T cells recognize peptide antigens in the context of MHC molecules through the clonally distributed T Cell receptor (TCR), which offers the means to detect and track specific T cells. We characterized TCR signatures in unique HNSCC paired samples (including L = Lymphocyte, S = Saliva, T = Tumor) to profile TCR repertoire diversity and clonality in different compartments. A total of 48 HNSCC samples corresponding to 14 patients (2 assayed 2X) were obtained from Johns Hopkins University. DNA samples were submitted for TCR sequencing (TCR-seq) via enrichment of the human TCRB locus using Human-TCRB-PD4bx. CDR3 sequences were downloaded from Adaptive ImmuneAnalyzer. For each sequence, V, D and J regions were extracted and translation to amino acid done on the CDR3 region. 8 paired (T, L, S) samples were submitted for shallow sequencing survey depth and 8 for deep assay depth. In order to better understand the TCR repertoire, we assessed the number of unique immune receptor clonotypes, their relative abundance, repertoire overlap, clonotype tracking and sequence length distribution. As expected, the deep assay revealed more clones than the survey. Using the TCR-seq deep assay, 9 out of 10 S samples harbored at least 10% of the number of clonotypes found in their paired T. As expected, L harbored a greater number and more diverse clones than T and S samples and showed partial overlap with T and S samples. Comparing the overlap between T, L and S based on a shared CDR3.aa repertoire: by shallow survey, 3/5 S samples had at least 1 overlap with the primary T. Using the deep assay, 9 out of 10 patients (90%) showed overlap between the S and paired T. We found top public clonotypes occupying the larger part in HPV negative samples, and surprisingly no known CDR3.aa sequences annotated to HPV in HPV positive samples but annotated to other common viruses (CMV, EBV). Our study demonstrates a robust TCR repertoire in S that corresponds at least partially to the clones observed in T and circulating L. The presence of HPV did not yet yield CDR3.aa specific sequences. Future single-cell transcriptomes may identify signatures of CD8+ and CD4+ neoantigen-reactive tumor-infiltrating L in the paired S samples in addition to the viral or tumor-associated antigens present in bulk assays. Our data need to be further validated in larger well characterized cohorts that include S from cancer-free subjects. These early results support the use of saliva as a potential surrogate for diagnostic immune-profiling of tumors, for early detection and follow-up. We further envision creating a personalized TCR repertoire for individual patients from an initial tumor sample biopsy to monitor their tumor immune dynamics using saliva. Citation Format: Dieila Giomo De Lima, Mariana Brait, Laura Palmieri, Fernando T. Zamuner, Esther Broner, Kellie N. Smith, Timothy Westlake, Or Malca, Sol Efroni, Ido Sloma, David Sidransky. Saliva TCR repertoire as a tool for head and neck cancer immunophenotype monitoring [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2121.

Upon the development of a therapeutic, a successful response to a global pandemic relies on efficient worldwide distribution, a process constrained by our global shipping network. Most existing strategies seek to maximize the outflow of the therapeutics, hence optimizing for rapid dissemination. Here we find that this intuitive approach is, in fact, counterproductive. The reason is that by focusing strictly on the quantity of disseminated therapeutics, these strategies disregard the way in which this quantity distributes across destinations. Most crucially—they overlook the interplay of the therapeutic spreading patterns with those of the pathogens. This results in a discrepancy between supply and demand, that prohibits efficient mitigation even under optimal conditions of superfluous flow. To solve this, we design a dissemination strategy that naturally follows the predicted spreading patterns of the pathogens, optimizing not just for supply volume, but also for its congruency with the anticipated demand. Specifically, we show that epidemics spread relatively uniformly across all destinations, prompting us to introduce an equality constraint into our dissemination that prioritizes supply homogeneity. This strategy may, at times, slow down the supply rate in certain locations, however, thanks to its egalitarian nature, which mimics the flow of the pathogens, it provides a dramatic leap in overall mitigation efficiency, potentially saving more lives with orders of magnitude less resources.

Identifying robust, patient-specific, and predictive biomarkers presents a major obstacle in precision oncology. To optimize patient-specific therapeutic strategies, here we couple pathway knowledge with large-scale drug sensitivity, RNAi, and CRISPR-Cas9 screening data from 460 cell lines. Pathway activity levels are found to be strong predictive biomarkers for the essentiality of 15 proteins, including the essentiality of MAD2L1 in breast cancer patients with high BRCA-pathway activity. We also find strong predictive biomarkers for the sensitivity to 31 compounds, including BCL2 and microtubule inhibitors (MTIs). Lastly, we show that Bcl-xL inhibition can modulate the activity of a predictive biomarker pathway and re-sensitize lung cancer cells and tumors to MTI therapy. Overall, our results support the use of pathways in helping to achieve the goal of precision medicine by uncovering dozens of predictive biomarkers., Predicting an individual's response to therapy is an important goal for precision medicine. Here, the authors use an algorithm that takes into account the interaction type and directionality of signalling pathways in protein–protein interactions and find that their pathway analysis can predict essential genes, which may be a target for therapy.

When confronted with a globally spreading epidemic, we seek efficient strategies for drug dissemination, creating a competition between supply and demand at a global scale. Propagating along similar networks, e.g., air-transportation, the spreading dynamics of the supply vs. the demand are, however, fundamentally different, with the pathogens driven by contagion dynamics, and the drugs by commodity flow. We show that these different dynamics lead to intrinsically distinct spreading patterns: while viruses spread homogeneously across all destinations, creating a concurrent global demand, commodity flow unavoidably leads to a highly uneven spread, in which selected nodes are rapidly supplied, while the majority remains deprived. Consequently, even under ideal conditions of extreme production and shipping capacities, due to the inherent heterogeneity of network-based commodity flow, efficient mitigation becomes practically unattainable, as homogeneous demand is met by highly heterogeneous supply. Therefore, we propose here a decentralized mitigation strategy, based on local production and dissemination of therapeutics, that, in effect, bypasses the existing distribution networks. Such decentralization is enabled thanks to the recent development of digitizable therapeutics, based on, e.g., short DNA sequences or printable chemical compounds, that can be distributed as digital sequence files and synthesized on location via DNA/3D printing technology. We test our decentralized mitigation under extremely challenging conditions, such as suppressed local production rates or low therapeutic efficacy, and find that thanks to its homogeneous nature, it consistently outperforms the centralized alternative, saving many more lives with significantly less resources.

Neurotoxicology is hampered by the inability to predict regional and cellular targets of toxicant‐induced damage. Evaluating astrogliosis overcomes this problem because reactive astrocytes highlight the location of toxicant‐induced damage. While enhanced expression of glial fibrillary acidic protein is a hallmark of astrogliosis, few other biomarkers have been identified. However, bacterial artificial chromosome ‐ translating ribosome affinity purification (bacTRAP) technology allows for characterization of the actively translating transcriptome of a particular cell type; use of this technology in aldehyde dehydrogenase 1 family member L1 (ALDH1L1) bacTRAP mice can identify genes selectively expressed in astrocytes. The aim of this study was to characterize additional biomarkers of neurotoxicity‐induced astrogliosis using ALDH1L1 bacTRAP mice. The known dopaminergic neurotoxicant 1‐methyl‐4‐phenyl‐1,2,3,6‐tetrahydropyridine (MPTP; 12.5 mg/kg s.c.) was used to induce astrogliosis. Striatal tissue was obtained 12, 24, and 48 h following exposure for the isolation of actively translating RNA. Subsequently, MPTP‐induced changes in this RNA pool were analyzed by microarray and 184 statistically significant, differentially expressed genes were identified. The dataset was interrogated by gene ontology, pathway, and co‐expression network analyses, which identified novel genes, as well as those with known immune and inflammatory functions. Using these analyses, we were directed to several genes associated with reactive astrocytes. Of these, TIMP1 and miR‐147 were identified as candidate biomarkers because of their robust increased expression following both MPTP and trimethyl tin exposures. Thus, we have demonstrated that bacTRAP can be used to identify new biomarkers of astrogliosis and aid in the characterization of astrocyte phenotypes induced by toxicant exposures. Open Science Badges This article has received a badge for *Open Materials* because it provided all relevant information to reproduce the study in the manuscript. The complete Open Science Disclosure form for this article can be found at the end of the article. More information about the Open Practices badges can be found at https://cos.io/our-services/open-science-badges/. Cover Image for this issue: doi: 10.1111/jnc.14518.

The partial success of tumor immunotherapy induced by checkpoint blockade, which is not antigen-specific, suggests that the immune system of some patients contain antigen receptors able to specifically identify tumor cells. Here we focused on T-cell receptor (TCR) repertoires associated with spontaneous breast cancer. We studied the alpha and beta chain CDR3 domains of TCR repertoires of CD4 T cells using deep sequencing of cell populations in mice and applied the results to published TCR sequence data obtained from human patients. We screened peripheral blood T cells obtained monthly from individual mice spontaneously developing breast tumors by 5 months. We then looked at identical TCR sequences in published human studies; we used TCGA data from tumors and healthy tissues of 1,256 breast cancer resections and from 4 focused studies including sequences from tumors, lymph nodes, blood and healthy tissues, and from single cell dataset of 3 breast cancer subjects. We now report that mice spontaneously developing breast cancer manifest shared, Public CDR3 regions in both their alpha and beta and that a significant number of women with early breast cancer manifest identical CDR3 sequences. These findings suggest that the development of breast cancer is associated, across species, with biomarker, exclusive TCR repertoires., Author summary More than 1,100 cancer treatments are currently in clinical testing. Of these, 295 are immune-oncology medicines and vaccines. For Checkpoint Immunotherapy alone, 52,539 patients were enrolled in 2017. Of these treatments, 108 are for breast cancer, the leading cancer diagnosed in women. Although checkpoint immunotherapy has yet to be proven beneficial in most types of breast cancer, current observations of which specific T cell go into the tumor, and how these cells are connected to the response to treatment, have lead to a new understating of the role of the immune system. Yet, and in spite of this intense research into the role of T cells in tumors, very little is known about how clones of T cells behave during tumor formation. The paper we present here studies this clonal behavior over time. We study it during mammary tumor development in mice. We see that a set of T cell clones, which comes from a diversity of different nucleotide sequences, stands out in its behavior compared with other T cell clones. Importantly, we show that these mouse T cell clones have a strong connection to human breast cancer. The specific identification of a subset of T cell clones, together with the behavior of these clones over time, is critical to our understanding of the effect of modifications to the immune system, such as the modifications made by immunotherapy treatments, and to our understanding of how to better control the behavior of the immune system.

Summary Biology of the response to anti-CTLA-4 involves the dynamics of specific T cell clones. Reasons for clinical success and failure of this treatment are still largely unknown. Here, we quantified the dynamics of the T cell receptor (TCR) repertoire, throughout 4 weeks involving treatment with anti-CTLA-4, in a syngeneic mouse model for colorectal cancer. These dynamics show an initial increase in clonality in tandem with a decrease in diversity, effects which gradually subside. Furthermore, response to treatment is tightly connected to the shared and public parts of the T cell repertoire. We were able to recognize time-dependent behaviors of specific TCR sequences and cell types and to show the response is dominated by specific motifs. We see that a single, specific time point might be useful to inform a physician of the true response to treatmentThe research further highlights the importance of temporal analyses of the immune response., Graphical Abstract, Highlights • Response to ICI is associated with pre-treatment TCR repertoire in mice • TCR repertoire goes through distinct, ICI-dependent changes with time • Tumor size and its response to ICI can be tracked by TCR repertoire metrics • A single time point is found to be a focal point of the immune response, Immunology; Cell Biology: Bioinformatics

We describe and provide an array of diverse methods to predict cellular positions in tissue from RNA-seq data selecting mapping genes according to their spatial/statistical properties and their effect on improving the cell positioning., Single-cell RNA-sequencing (scRNAseq) technologies are rapidly evolving. Although very informative, in standard scRNAseq experiments, the spatial organization of the cells in the tissue of origin is lost. Conversely, spatial RNA-seq technologies designed to maintain cell localization have limited throughput and gene coverage. Mapping scRNAseq to genes with spatial information increases coverage while providing spatial location. However, methods to perform such mapping have not yet been benchmarked. To fill this gap, we organized the DREAM Single-Cell Transcriptomics challenge focused on the spatial reconstruction of cells from the Drosophila embryo from scRNAseq data, leveraging as silver standard, genes with in situ hybridization data from the Berkeley Drosophila Transcription Network Project reference atlas. The 34 participating teams used diverse algorithms for gene selection and location prediction, while being able to correctly localize clusters of cells. Selection of predictor genes was essential for this task. Predictor genes showed a relatively high expression entropy, high spatial clustering and included prominent developmental genes such as gap and pair-rule genes and tissue markers. Application of the top 10 methods to a zebra fish embryo dataset yielded similar performance and statistical properties of the selected genes than in the Drosophila data. This suggests that methods developed in this challenge are able to extract generalizable properties of genes that are useful to accurately reconstruct the spatial arrangement of cells in tissues.

BackgroundRestoration of T-cell repertoire diversity after allogeneic bone marrow transplantation (allo-BMT) is crucial for immune recovery. T-cell diversity is produced by rearrangements of germline gene segments (V (D) and J) of the T-cell receptor (TCR) α and β chains, and selection induced by binding of TCRs to MHC-peptide complexes. This diversity can be measured by many measures. We here focus on the V gene usage and the CDR3 sequences of the beta chain. We compared multiple T-cell repertoires to follow T cell repertoire changes post allo-BMT in HLA-matched related donor and recipient pairs.ResultsOur analyses of the differences between donor and recipient complementarity determining region 3 (CDR3) beta composition and V-gene profile show that the CDR sequence composition does not change during restoration, implying its dependence on the HLA typing. In contrast, V gene usage followed a time-dependent pattern, got following the donor profile post transplant and then shifting back to the recipients’ profile. The final long-term repertoire was more similar to that of the recipient’s original one than the donor’s.; some recipients converged within months while others took multiple years.ConclusionBased on the results of our analyses, we propose that donor-recipient V-gene distribution differences may serve as clinical biomarkers for monitoring immune recovery.

The introduction of novel cancer drugs and innovative treatments brings great hope for cancer patients, but also an urgent need to match drugs to suitable patients, since certain drugs that benefit one patient may actually harm others. The newly developed poly-ADP ribose polymerase (PARP) inhibitors (PARPis) are a group of pharmacological enzyme inhibitors used clinically for multiple indications. Several forms of cancer tend to be PARP dependent, making PARP an attractive target for cancer therapy. Specifically, PARPis are commonly used in BRCA-associated breast cancers patients, since unrepaired single-strand breaks are converted into double-strand breaks and BRCA-associated tumors cannot repair them by homologous recombination so that PARPi leads to tumor cell death, by a mechanism called “Synthetic Lethality”. Unfortunately, not all patients respond to PARPi, and it is not currently possible to predict who will or will not respond. Here, we present a specific genomic marker, which reflects a single-nucleotide polymorphism of human PARP1 and correlates in vitro with response to PARPi, throughout all indications. In addition, we report that this SNP is associated with re-shaping mRNA, and mRNA levels, and influences the final protein structure to expose new binding sites while hiding others. The status of the SNP is therefore critical to patients’ care, as it relates responses to PARPi to the PARP1-SNP carried.

The wide variety of nest architectural designs exhibited by passerine birds allowed them to diversify into a wide variety of ecological niches and terrestrial habitats. At present, very little is known about the mechanics of building these structures. Digitizing natural biological structures such as bird nests provides the opportunity to explore their structural properties and behavior under specific conditions by means of computational manipulations, simulations, and analyses. This study describes a generic algorithm for the digitization and exploration of complex interlocked bird nests, and validates it on nests built by the Dead-Sea Sparrow (Passer moabiticus) in branches of trees using stiff dry branches. This algorithm takes as input computerized tomographic scans of the nest, identifies and isolates each branch entity within the three-dimensional data, and finally extracts the characteristics of each branch. The result is a reliable three-dimensional digital model of the nest that contains a complete geometric dataset per each of its components, e.g. dimensions and contact points with neighboring components, as well as global properties, e.g. density distribution and network structure. Based on these, we were able to simulate various models of the nest construction process. Altogether, the described algorithm and possible derivatives thereof could be a valuable tool in studying the structure-function relationships of similarly complex biological objects, and may provide further insights into the potential selective mechanisms underlying historical evolution of this distinct nest form.

Paclitaxel, the most commonly used form of chemotherapy, is utilized in curative protocols in different types of cancer. The response to treatment differs among patients. Biological interpretation of a mechanism to explain this personalized response is still unavailable. Since paclitaxel is known to target BCL2 and TUBB1, we used pan-cancer genomic data from hundreds of patients to show that a single-nucleotide variant in the BCL2 sequence can predict a patient’s response to paclitaxel. Here, we show a connection between this BCL2 genomic variant, its transcript structure, and protein abundance. We demonstrate these findings in silico, in vitro, in formalin-fixed paraffin-embedded (FFPE) tissue, and in patient lymphocytes. We show that tumors with the specific variant are more resistant to paclitaxel. We also show that tumor and normal cells with the variant express higher levels of BCL2 protein, a phenomenon that we validated in an independent cohort of patients. Our results indicate BCL2 sequence variations as determinants of chemotherapy resistance. The knowledge of individual BCL2 genomic sequences prior to the choice of chemotherapy may improve patient survival. The current work also demonstrates the benefit of community-wide, integrative omics data sources combined with in-lab experimentation and validation sets.

Materials and construction methods of nests vary between bird species and at present, very little is known about the relationships between architecture and function in these structures. This study combines computational and experimental techniques to study the structural biology of nests fabricated by the edible nest swiftlet Aerodramus fuciphagus on vertical rock walls using threaded saliva. Utilizing its own saliva as a construction material allows the swiftlets full control over the structural features at a very high resolution in a process similar to additive manufacturing. It was hypothesized that the mechanical properties would vary between the structural regions of the nest (i.e. anchoring to the wall, center of the cup, and rim) mainly by means of architecture to offer structural support and bear the natural loads of birds and eggs. We generated numerical models of swiftlet nests from μCT scans based on collected swiftlet nests, which we loaded with a force of birds and eggs. This was done in order to study and assess the stress distribution that characterizes the specific nest’s architecture, evaluate its strength and weak points if any, as well as to understand the rationale and benefits that underlie this natural structure. We show that macro- and micro-scale structural patterns are identical in all nests, suggesting that their construction is governed by specific design principles. The nests’ response to applied loads of birds and eggs in finite element simulations suggests a mechanical overdesign strategy, which ensures the stresses experienced by its components in any loading scenario are actively minimized to be significantly smaller than the tensile fracture strength of the nests’ material. These findings highlight mechanical overdesign as a biological strategy for resilient, single-material constructions designed to protect eggs and hatchlings.

Here, we outline an overview of the mammalian immune system that updates and extends the classical clonal selection paradigm. Rather than focusing on strict self-not-self discrimination, we propose that the system orchestrates variable inflammatory responses that maintain the body and its symbiosis with the microbiome while eliminating the threat from pathogenic infectious agents and from tumors. The paper makes four points: The immune system classifies healthy and pathologic states of the body-including both self and foreign elements-by deploying individual lymphocytes as cellular computing machines; immune cells transform input signals from the body into an output of specific immune reactions.Rather than independent clonal responses, groups of individually activated immune-system cells co-react in lymphoid organs to make collective decisions through a type of self-organizing swarm intelligence or crowd wisdom.Collective choices by swarms of immune cells, like those of schools of fish, are modified by relatively small numbers of individual regulators responding to shifting conditions-such collective inflammatory responses are dynamically responsive.Self-reactive autoantibody and T-cell receptor (TCR) repertoires shared by healthy individuals function in a biological version of experience-based supervised machine learning. Immune system decisions are primed by formative experience with training sets of self-antigens encountered during lymphocyte development; these initially trained T cell and B cell repertoires form a Wellness Profile that then guides immune responses to test sets of antigens encountered later. This experience-based machine learning strategy is analogous to that deployed by supervised machine-learning algorithms. We propose experiments to test these ideas. This overview of the immune system bears clinical implications for monitoring wellness and for treating autoimmune disease, cancer, and allograft reactions.

Audencel is a dendritic cell (DC)-based cellular cancer immunotherapy against glioblastoma multiforme (GBM). It is characterized by loading of DCs with autologous whole tumor lysate and in vitro maturation via “danger signals”. The recent phase II “GBM-Vax” trial showed no clinical efficacy for Audencel as assessed with progression-free and overall survival in all patients. Here we present immunological research accompanying the trial with a focus on immune system factors related to outcome and Audencel’s effect on the immune system. Methodologically, peripheral blood samples (from apheresis before Audencel or venipuncture during Audencel) were subjected to functional characterization via enzyme-linked immunospot (ELISPOT) assays connected with cytokine bead assays (CBAs) as well as phenotypical characterization via flow cytometry and mRNA quantification. GBM tissue samples (from surgery) were subjected to T cell receptor sequencing and immunohistochemistry. As results we found: Patients with favorable pre-existing anti-tumor characteristics lived longer under Audencel than Audencel patients without them. Pre-vaccination blood CD8+ T cell count and ELISPOT Granzyme B production capacity in vitro upon tumor antigen exposure were significantly correlated with overall survival. Despite Audencel’s general failure to induce a significant clinical response, it nevertheless seemed to have an effect on the immune system. For instance, Audencel led to a significant up-regulation of the Th1-related immunovariables ELISPOT IFNγ, the transcription factor T-bet in the blood and ELISPOT IL-2 in a dose-dependent manner upon vaccination. Post-vaccination levels of ELISPOT IFNγ and CD8+ cells in the blood were indicative of a significantly better survival. In summary, Audencel failed to reach an improvement of survival in the recent phase II clinical trial. No clinical efficacy was registered. Our concomitant immunological work presented here indicates that outcome under Audencel was influenced by the state of the immune system. On the other hand, Audencel also seemed to have stimulated the immune system. Overall, these immunological considerations suggest that DC immunotherapy against glioblastoma should be studied further – with the goal of translating an apparent immunological response into a clinical response. Future research should concentrate on investigating augmentation of immune reactions through combination therapies or on developing meaningful biomarkers. Electronic supplementary material The online version of this article (10.1186/s40478-018-0621-2) contains supplementary material, which is available to authorized users.

Immune tolerance toward “self” is critical in multiple immune disorders. While there are several mechanisms to describe the involvement of immune cells in the process, the role of peripheral tissue cells in that context is not yet clear. The theory of ecoimmunity postulates that interactions between immune and tissue cells represent a predator–prey relationship. A lifelong interaction, shaped mainly during early ontogeny, leads to selection of nonimmune cell phenotypes. Normally, therefore, nonimmune cells that evolve alongside an intact immune system would be phenotypically capable of evading immune responses, and cells whose phenotype falls short of satisfying this steady state would expire under hostile immune responses. This view was supported until recently by experimental evidence showing an inferior endurance of severe combined immunodeficiency (SCID)-derived pancreatic islets when engrafted into syngeneic immune-intact wild-type (WT) mice, relative to islets from WT. Here we extend the experimental exploration of ecoimmunity by searching for the presence of the phenotypic changes suggested by the theory. Immune-related phenotypes of islets, spleen, and bone marrow immune cells were determined, as well as SCID and WT nonlymphocytic cells. Islet submass grafting was performed to depict syngeneic graft functionality. Islet cultures were examined under both resting and inflamed conditions for expression of CD40 and major histocompatibility complex (MHC) class I/II and release of interleukin-1α (IL-1α), IL-1β, IL-6, tumor necrosis factor-α (TNF-α), IL-10, and insulin. Results depict multiple pathways that appear to be related to the sculpting of nonimmune cells by immune cells; 59 SCID islet genes displayed relative expression changes compared with WT islets. SCID cells expressed lower tolerability to inflammation and higher levels of immune-related molecules, including MHC class I. Accordingly, islets exhibited a marked increase in insulin release upon immunocyte depletion, in effect resuming endocrine function that was otherwise suppressed by resident immunocytes. This work provides further support of the ecoimmunity theory and encourages subsequent studies to identify its role in the emergence and treatment of autoimmune pathologies, transplant rejection, and cancer.

SummaryMice overexpressing the longevity protein SIRT6 or deficient for the liver’s most prevalent microRNA miR-122 display a similar set of phenotypes, including improved lipid profile and protection against damage linked to obesity. Here, we show that miR-122 and SIRT6 negatively regulate each other’s expression. SIRT6 downregulates miR-122 by deacetylating H3K56 in the promoter region. MiR-122 binds to three sites on the SIRT6 3′ UTR and reduces its levels. The interplay between SIRT6 and miR-122 is manifested in two physiologically relevant ways in the liver. First, they oppositely regulate a similar set of metabolic genes and fatty acid β-oxidation. Second, in hepatocellular carcinoma patients, loss of a negative correlation between SIRT6 and miR-122 expression is significantly associated with better prognosis. These findings show that SIRT6 and miR-122 negatively regulate each other to control various aspects of liver physiology and SIRT6-miR-122 correlation may serve as a biomarker for hepatocarcinoma prognosis.

// Rotem Ben-Hamo 1 , Alona Zilberberg 1 , Helit Cohen 1 and Sol Efroni 1 1 The Mina and Everard Goodman Faculty of Life Science, Bar Ilan University, Ramat-Gan, Israel Correspondence to: Sol Efroni, email: // Keywords : MAPKAP signaling, cytoskeleton, pathways, glioblastoma, metastasis, hsa-miR9 Received : July 23, 2015 Accepted : December 05, 2015 Published : December 21, 2015 Abstract Background: Glioblastoma Multiforme (GBM) is the most common and lethal primary tumor of the brain. GBM is associated with one of the worst 5-year survival rates among all human cancers, despite much effort in different modes of treatment. Results: Here, we demonstrate specific GBM cancer phenotypes that are governed by modifications to the MAPAKAP network. We then demonstrate a novel regulation mode by which a set of five key factors of the MAPKAP pathway are regulated by the same microRNA, hsa-miR-9. We demonstrate that hsa-miR-9 overexpression leads to MAPKAP signaling inhibition, partially by interfering with the MAPK14/MAPKAP3 complex. Further, hsa-miR-9 overexpression initiates re-arrangement of actin filaments, which leads us to hypothesize a mechanism for the observed phenotypic shift. Conclusion: The work presented here exposes novel microRNA features and situates hsa-miR-9 as a therapeutic target, which governs metastasis and thus determines prognosis in GBM through MAPKAP signaling.

Cancer immunotherapy by checkpoint blockade proves that an effective immune response to a tumor can be induced clinically. However, little is known about the evolution of tumor-associated T-cell receptor (TCR) repertoires without intervention. Here we studied TCR repertoire evolution in mice spontaneously developing mammary tumors; we sequenced peripheral blood alpha and beta TCRs of CD4+CD62L+CD44− T cells monthly for 8 months in 10 FVB/NJ mice transgenic at the Erbb2 locus, all developing tumors; 5 FVB/NJ mice without the transgene were age-matched controls. Sequences were either private (restricted to one mouse) or public (shared among mice); public sequences were either exclusive to the tumor group or inclusive among different groups. We now report that 1), public AA sequences were each encoded by many different nucleotide sequences (NT) recombinations (convergent recombination; CR); 2) mice developing tumors evolved tumor-exclusive public sequences, derived initially from private or from inclusive public sequences; and 3) tumor-exclusive public sequences in mice were also present among published public TCR sequences from human breast cancer patients. These cross-species tumor-exclusive TCR sequences manifested high CR; but the AA sequences shared by mice and humans did not share NT sequences. Thus, tumor-exclusive TCR AA sequences across species are selected from different NT recombination events. The roles of tumor-exclusive TCR repertoires in advancing or inhibiting tumor development and the effects of tumor immunotherapy on these T cells remain to be seen.

Long noncoding RNAs (lncRNAs) are major regulators of many cellular processes including cell cycle progression and tumorigenesis. In this study, we identify a novel lncRNA, MA-linc1, and reveal its effects on cell cycle progression and cancer growth. Inhibition of MA-linc1 expression alters cell cycle distribution, leading to a decrease in the number of G1 cells and a concomitant increase in all other stages of the cell cycle, and in particular G2/M, suggesting its involvement in the regulation of M phase. Accordingly, knock down of MA-linc1 inhibits M phase exit upon release from a mitotic block. We further demonstrate that MA-linc1 predominantly functions in cis to repress expression of its neighboring gene, Purα, which is often deleted in human cancers and whose ectopic expression inhibits cell cycle progression. Knock down of Purα partially rescues the MA-linc1 dependent inhibition of M phase exit. In agreement with its suggested role in M phase, inhibition of MA-linc1 enhances apoptotic cell death induced by the antimitotic drug, Paclitaxel and this enhancement of apoptosis is rescued by Purα knockdown. Furthermore, high levels of MA-linc1 are associated with reduced survival in human breast and lung cancer patients. Taken together, our data identify MA-linc1 as a novel lncRNA regulator of cell cycle and demonstrate its potential role in cancer progression and treatment.