Translational offsetting as a mode of estrogen receptor α-dependent regulation of gene expression.

Estrogen receptor alpha (ERα) activity is associated with increased cancer cell proliferation. Studies aiming to understand the impact of ERα on cancer-associated phenotypes have largely been limited to its transcriptional activity. Herein, we demonstrate that ERα coordinates its transcriptional output with selective modulation of mRNA translation. Importantly, translational perturbations caused by depletion of ERα largely manifest as "translational offsetting" of the transcriptome, whereby amounts of translated mRNAs and corresponding protein levels are maintained constant despite changes in mRNA abundance. Transcripts whose levels, but not polysome association, are reduced following ERα depletion lack features which limit translation efficiency including structured 5'UTRs and miRNA target sites. In contrast, mRNAs induced upon ERα depletion whose polysome association remains unaltered are enriched in codons requiring U34-modified tRNAs for efficient decoding. Consistently, ERα regulates levels of U34-modifying enzymes and thereby controls levels of U34-modified tRNAs. These findings unravel a hitherto unprecedented mechanism of ERα-dependent orchestration of transcriptional and translational programs that may be a pervasive mechanism of proteome maintenance in hormone-dependent cancers.

Translational profiling of macrophages infected with Leishmania donovani identifies mTOR- and eIF4A-sensitive immune-related transcripts.

The protozoan parasite Leishmania donovani (L. donovani) causes visceral leishmaniasis, a chronic infection which is fatal when untreated. Herein, we investigated whether in addition to altering transcription, L. donovani modulates host mRNA translation to establish a successful infection. Polysome-profiling revealed that one third of protein-coding mRNAs expressed in primary mouse macrophages are differentially translated upon infection with L. donovani promastigotes or amastigotes. Gene ontology analysis identified key biological processes enriched for translationally regulated mRNAs and were predicted to be either activated (e.g. chromatin remodeling and RNA metabolism) or inhibited (e.g. intracellular trafficking and antigen presentation) upon infection. Mechanistic in silico and biochemical analyses showed selective activation mTOR- and eIF4A-dependent mRNA translation, including transcripts encoding central regulators of mRNA turnover and inflammation (i.e. PABPC1, EIF2AK2, and TGF-ß). L. donovani survival within macrophages was favored under mTOR inhibition but was dampened by pharmacological blockade of eIF4A. Overall, this study uncovers a vast yet selective reprogramming of the host cell translational landscape early during L. donovani infection, and suggests that some of these changes are involved in host defense mechanisms while others are part of parasite-driven survival strategies. Further in vitro and in vivo investigation will shed light on the contribution of mTOR- and eIF4A-dependent translational programs to the outcome of visceral leishmaniasis.

Generally applicable transcriptome-wide analysis of translation using anota2seq.

mRNA translation plays an evolutionarily conserved role in homeostasis and when dysregulated contributes to various disorders including metabolic and neurological diseases and cancer. Notwithstanding that optimal and universally applicable methods are critical for understanding the complex role of translational control under physiological and pathological conditions, approaches to analyze translatomes are largely underdeveloped. To address this, we developed the anota2seq algorithm which outperforms current methods for statistical identification of changes in translation. Notably, in contrast to available analytical methods, anota2seq also allows specific identification of an underappreciated mode of gene expression regulation whereby translation acts as a buffering mechanism which maintains protein levels despite fluctuations in corresponding mRNA abundance ('translational buffering'). Thus, the universal anota2seq algorithm allows efficient and hitherto unprecedented interrogation of translatomes which is anticipated to advance knowledge regarding the role of translation in homeostasis and disease.

Cancer as an ecomolecular disease and a neoplastic consortium.

Current anticancer paradigms largely target driver mutations considered integral for cancer cell survival and tumor progression. Although initially successful, many of these strategies are unable to overcome the tremendous heterogeneity that characterizes advanced tumors, resulting in the emergence of resistant disease. Cancer is a rapidly evolving, multifactorial disease that accumulates numerous genetic and epigenetic alterations. This results in wide phenotypic and molecular heterogeneity within the tumor, the complexity of which is further amplified through specific interactions between cancer cells and the tumor microenvironment. In this context, cancer may be perceived as an "ecomolecular" disease that involves cooperation between several neoplastic clones and their interactions with immune cells, stromal fibroblasts, and other cell types present in the microenvironment. This collaboration is mediated by a variety of secreted factors. Cancer is therefore analogous to complex ecosystems such as microbial consortia. In the present article, we comment on the current paradigms and perspectives guiding the development of cancer diagnostics and therapeutics and the potential application of systems biology to untangle the complexity of neoplasia. In our opinion, conceptualization of neoplasia as an ecomolecular disease is warranted. Advances in knowledge pertinent to the complexity and dynamics of interactions within the cancer ecosystem are likely to improve understanding of tumor etiology, pathogenesis, and progression. This knowledge is anticipated to facilitate the design of new and more effective therapeutic approaches that target the tumor ecosystem in its entirety.

eIF4E-Binding Proteins 1 and 2 Limit Macrophage Anti-Inflammatory Responses through Translational Repression of IL-10 and Cyclooxygenase-2.

Macrophages represent one of the first lines of defense during infections and are essential for resolution of inflammation following pathogen clearance. Rapid activation or suppression of protein synthesis via changes in translational efficiency allows cells of the immune system, including macrophages, to quickly respond to external triggers or cues without de novo mRNA synthesis. The translational repressors eIF4E-binding proteins 4E-BP1 and 4E-BP2 (4E-BP1/2) are central regulators of proinflammatory cytokine synthesis during viral and parasitic infections. However, it remains to be established whether 4E-BP1/2 play a role in translational control of anti-inflammatory responses. By comparing translational efficiencies of immune-related transcripts in macrophages from wild-type and 4E-BP1/2 double-knockout mice, we found that translation of mRNAs encoding two major regulators of inflammation, IL-10 and PG-endoperoxide synthase 2/cyclooxygenase-2, is controlled by 4E-BP1/2. Genetic deletion of 4E-BP1/2 in macrophages increased endogenous IL-10 and PGE2 protein synthesis in response to TLR4 stimulation and reduced their bactericidal capacity. The molecular mechanism involves enhanced anti-inflammatory gene expression (sIl1ra, Nfil3, Arg1, Serpinb2) owing to upregulation of IL-10-STAT3 and PGE2-C/EBPß signaling. These data provide evidence that 4E-BP1/2 limit anti-inflammatory responses in macrophages and suggest that dysregulated activity of 4E-BP1/2 might be involved in reprogramming of the translational and downstream transcriptional landscape of macrophages during pathological conditions, such as infections and cancer.

Polysome-profiling in small tissue samples.

Polysome-profiling is commonly used to study translatomes and applies laborious extraction of efficiently translated mRNA (associated with >3 ribosomes) from a large volume across many fractions. This property makes polysome-profiling inconvenient for larger experimental designs or samples with low RNA amounts. To address this, we optimized a non-linear sucrose gradient which reproducibly enriches for efficiently translated mRNA in only one or two fractions, thereby reducing sample handling 5-10-fold. The technique generates polysome-associated RNA with a quality reflecting the starting material and, when coupled with smart-seq2 single-cell RNA sequencing, translatomes in small tissues from biobanks can be obtained. Translatomes acquired using optimized non-linear gradients resemble those obtained with the standard approach employing linear gradients. Polysome-profiling using optimized non-linear gradients in serum starved HCT-116 cells with or without p53 showed that p53 status associates with changes in mRNA abundance and translational efficiency leading to changes in protein levels. Moreover, p53 status also induced translational buffering whereby changes in mRNA levels are buffered at the level of mRNA translation. Thus, here we present a polysome-profiling technique applicable to large study designs, primary cells and frozen tissue samples such as those collected in biobanks.

The Protozoan Parasite Toxoplasma gondii Selectively Reprograms the Host Cell Translatome.

The intracellular parasite Toxoplasma gondii promotes infection by targeting multiple host cell processes; however, whether it modulates mRNA translation is currently unknown. Here, we show that infection of primary murine macrophages with type I or II T. gondii strains causes a profound perturbation of the host cell translatome. Notably, translation of transcripts encoding proteins involved in metabolic activity and components of the translation machinery was activated upon infection. In contrast, the translational efficiency of mRNAs related to immune cell activation and cytoskeleton/cytoplasm organization was largely suppressed. Mechanistically, T. gondii bolstered mechanistic target of rapamycin (mTOR) signaling to selectively activate the translation of mTOR-sensitive mRNAs, including those with a 5'-terminal oligopyrimidine (5' TOP) motif and those encoding mitochondrion-related proteins. Consistent with parasite modulation of host mTOR-sensitive translation to promote infection, inhibition of mTOR activity suppressed T. gondii replication. Thus, selective reprogramming of host mRNA translation represents an important subversion strategy during T. gondii infection.

Immune gene expression and response to chemotherapy in advanced breast cancer.

BACKGROUND: Transcriptomic profiles have shown promise as predictors of response to neoadjuvant chemotherapy in breast cancer (BC). This study aimed to explore their predictive value in the advanced BC (ABC) setting. METHODS: In a Phase 3 trial of first-line chemotherapy in ABC, a fine needle aspiration biopsy (FNAB) was obtained at baseline. Intrinsic molecular subtypes and gene modules related to immune response, proliferation, oestrogen receptor (ER) signalling and recurring genetic alterations were analysed for association with objective response to chemotherapy. Gene-set enrichment analysis (GSEA) of responders vs non-responders was performed independently. Lymphocytes were enumerated in FNAB smears and the absolute abundance of immune cell types was calculated using the Microenvironment Cell Populations counter method. RESULTS: Gene expression data were available for 109 patients. Objective response to chemotherapy was statistically significantly associated with an immune module score (odds ratio (OR)=1.62; 95% confidence interval (CI), 1.03-2.64; P=0.04). Subgroup analysis showed that this association was restricted to patients with ER-positive or luminal tumours (OR=3.54; 95%, 1.43-10.86; P=0.012 and P for interaction=0.04). Gene-set enrichment analysis confirmed that in these subgroups, immune-related gene sets were enriched in responders. CONCLUSIONS: Immune-related transcriptional signatures may predict response to chemotherapy in ER-positive and luminal ABC.

IL-15 activates mTOR and primes stress-activated gene expression leading to prolonged antitumor capacity of NK cells.

Treatment of hematological malignancies by adoptive transfer of activated natural killer (NK) cells is limited by poor postinfusion persistence. We compared the ability of interleukin-2 (IL-2) and IL-15 to sustain human NK-cell functions following cytokine withdrawal to model postinfusion performance. In contrast to IL-2, IL-15 mediated stronger signaling through the IL-2/15 receptor complex and provided cell function advantages. Genome-wide analysis of cytosolic and polysome-associated messenger RNA (mRNA) revealed not only cytokine-dependent differential mRNA levels and translation during cytokine activation but also that most gene expression differences were primed by IL-15 and only manifested after cytokine withdrawal. IL-15 augmented mammalian target of rapamycin (mTOR) signaling, which correlated with increased expression of genes related to cell metabolism and respiration. Consistently, mTOR inhibition abrogated IL-15-induced cell function advantages. Moreover, mTOR-independent STAT-5 signaling contributed to improved NK-cell function during cytokine activation but not following cytokine withdrawal. The superior performance of IL-15-stimulated NK cells was also observed using a clinically applicable protocol for NK-cell expansion in vitro and in vivo. Finally, expression of IL-15 correlated with cytolytic immune functions in patients with B-cell lymphoma and favorable clinical outcome. These findings highlight the importance of mTOR-regulated metabolic processes for immune cell functions and argue for implementation of IL-15 in adoptive NK-cell cancer therapy.

Ki67 measured in metastatic tissue and prognosis in patients with advanced breast cancer.

The purpose of this study is to determine the prognostic role of Ki67 evaluated in relapse biopsies from patients with metastatic breast cancer (MBC). Two hundred and ten patients diagnosed with MBC in Stockholm, Sweden between 1998 and 2009 and with Ki67 assessed at time of first systemic relapse (mKi67) were retrospectively identified and divided into two groups according to mKi67 fraction (low ≤20 %, high >20 %). Post-relapse survival was compared between the groups using Kaplan-Meier and Cox regression methods. Death rate as function of continuous mKi67 was also evaluated. Furthermore, the prognostic role of intra-individual change in Ki67 between primary tumor and matched metastasis was explored by Kaplan-Meier plots. One hundred and twenty-five patients had low and 85 had high mKi67. Median survival was 25 and 17 months in low- and high-mKi67 group, respectively [hazard ratio (HR) 0.69, 95 % confidence intervals (CI) 0.51-0.92, P = 0.01]. In a multivariate model adjusted for prognostic confounders, low-mKi67 showed a non-significant trend toward better survival (HR 0.85, 95 %CI 0.62-1.16, P = 0.30). Nevertheless, mKi67 independently correlated with survival when compared with primary tumor proliferation (HR 0.56, 95 %CI 0.38-0.81, P = 0.002). The 2-year death rate steeply increased as mKi67 increased. Moreover, the change from high in primary tumor to low in metastasis significantly correlated with longer survival when compared with stable Ki67 levels (HR 0.48, 95 %CI 0.31-0.76, P = 0.002). In this cohort of MBC patients, mKi67 inversely but not independently correlated with survival. However, a significant association between mKi67 and survival was shown regardless of primary tumor proliferation.

Analysis of human lung mast cells by single cell RNA sequencing.

Mast cells are tissue-resident cells playing major roles in homeostasis and disease conditions. Lung mast cells are particularly important in airway inflammatory diseases such as asthma. Human mast cells are classically divided into the subsets MCT and MCTC, where MCT express the mast cell protease tryptase and MCTC in addition express chymase, carboxypeptidase A3 (CPA3) and cathepsin G. Apart from the disctintion of the MCT and MCTC subsets, little is known about the heterogeniety of human lung mast cells and a deep analysis of their heterogeniety has previously not been performed. We therefore performed single cell RNA sequencing on sorted human lung mast cells using SmartSeq2. The mast cells showed high expression of classical mast cell markers. The expression of several individual genes varied considerably among the cells, however, no subpopulations were detected by unbiased clustering. Variable genes included the protease-encoding transcripts CMA1 (chymase) and CTSG (cathepsin G). Human lung mast cells are predominantly of the MCT subset and consistent with this, the expression of CMA1 was only detectable in a small proportion of the cells, and correlated moderately to CTSG. However, in contrast to established data for the protein, CPA3 mRNA was high in all cells and the correlation of CPA3 to CMA1 was weak.

Exploratory analysis of multiple omics datasets using the adjusted RV coefficient.

The integration of multiple high-dimensional data sets (omics data) has been a very active but challenging area of bioinformatics research in recent years. Various adaptations of non-standard multivariate statistical tools have been suggested that allow to analyze and visualize such data sets simultaneously. However, these methods typically can deal with two data sets only, whereas systems biology experiments often generate larger numbers of high-dimensional data sets. For this reason, we suggest an explorative analysis of similarity between data sets as an initial analysis steps. This analysis is based on the RV coefficient, a matrix correlation, that can be interpreted as a generalization of the squared correlation from two single variables to two sets of variables. It has been shown before however that the high-dimensionality of the data introduces substantial bias to the RV. We therefore introduce an alternative version, the adjusted RV, which is unbiased in the case of independent data sets. We can also show that in many situations, particularly for very high-dimensional data sets, the adjusted RV is a better estimator than previously RV versions in terms of the mean square error and the power of the independence test based on it. We demonstrate the usefulness of the adjusted RV by applying it to data set of 19 different multivariate data sets from a systems biology experiment. The pairwise RV values between the data sets define a similarity matrix that we can use as an input to a hierarchical clustering or a multidimensional scaling. We show that this reveals biological meaningful subgroups of data sets in our study.

Adaptive translational reprogramming of metabolism limits the response to targeted therapy in BRAFV600 melanoma.

Despite the success of therapies targeting oncogenes in cancer, clinical outcomes are limited by residual disease that ultimately results in relapse. This residual disease is often characterized by non-genetic adaptive resistance, that in melanoma is characterised by altered metabolism. Here, we examine how targeted therapy reprograms metabolism in BRAF-mutant melanoma cells using a genome-wide RNA interference (RNAi) screen and global gene expression profiling. Using this systematic approach we demonstrate post-transcriptional regulation of metabolism following BRAF inhibition, involving selective mRNA transport and translation. As proof of concept we demonstrate the RNA processing kinase U2AF homology motif kinase 1 (UHMK1) associates with mRNAs encoding metabolism proteins and selectively controls their transport and translation during adaptation to BRAF-targeted therapy. UHMK1 inactivation induces cell death by disrupting therapy induced metabolic reprogramming, and importantly, delays resistance to BRAF and MEK combination therapy in multiple in vivo models. We propose selective mRNA processing and translation by UHMK1 constitutes a mechanism of non-genetic resistance to targeted therapy in melanoma by controlling metabolic plasticity induced by therapy.

PAK4 suppresses RELB to prevent senescence-like growth arrest in breast cancer.

Overcoming cellular growth restriction, including the evasion of cellular senescence, is a hallmark of cancer. We report that PAK4 is overexpressed in all human breast cancer subtypes and associated with poor patient outcome. In mice, MMTV-PAK4 overexpression promotes spontaneous mammary cancer, while PAK4 gene depletion delays MMTV-PyMT driven tumors. Importantly, PAK4 prevents senescence-like growth arrest in breast cancer cells in vitro, in vivo and ex vivo, but is not needed in non-immortalized cells, while PAK4 overexpression in untransformed human mammary epithelial cells abrogates H-RAS-V12-induced senescence. Mechanistically, a PAK4 - RELB - C/EBPß axis controls the senescence-like growth arrest and a PAK4 phosphorylation residue (RELB-Ser151) is critical for RELB-DNA interaction, transcriptional activity and expression of the senescence regulator C/EBPß. These findings establish PAK4 as a promoter of breast cancer that can overcome oncogene-induced senescence and reveal a selective vulnerability of cancer to PAK4 inhibition.

Intrinsic subtypes and genomic signatures of primary breast cancer and prognosis after systemic relapse.

Molecular subtypes and gene expression signatures are widely used in early breast cancer but their role in metastatic disease is less explored. Two hundred-twenty patients diagnosed with primary breast cancer and subsequent relapse in Stockholm, Sweden between 1997 and 2006 were identified and their primary tumor was assessed for immunohistochemistry (IHC)- and PAM50-based subtypes, risk of recurrence (ROR-S) score, 21-gene and 70-gene signatures using research-based microarray expression profiles. Clinical and pathological data were retrospectively collected. Post-relapse survival within intrinsic subtypes and genomic signatures was investigated by Kaplan-Meier and Cox regression methods. ROR weighted for proliferation index (ROR-P) was explored and the prognostic contribution provided when combined to a clinical model estimated as change in LR- χ(2). IHC classified 27%, 24%, 36% and 13% of the tumors as luminal A, luminal B, HER2+ and triple negative, respectively. PAM50 categorized 22%, 24%, 26%, 22%, 6% of the tumors as luminal A, luminal B, HER2-enriched, basal-like and normal-like. Triple negative and basal tumors had a significantly shorter median post-relapse survival in comparison with luminal. Overall, neither IHC nor PAM50 subtypes, 21- and 70- gene profiles were prognostic in multivariable models. Low and medium ROR-S had a longer survival compared with the high-risk group (23 vs 10 months; p = 0.04). ROR-P independently correlated with post-relapse survival (p = 0.002) and provided the most significant prognostic information when added to a clinical model. ROR score from primary tumor represents an independent prognostic factor of post-relapse survival beyond classical clinical and pathological variables.

p21-activated kinase group II small compound inhibitor GNE-2861 perturbs estrogen receptor alpha signaling and restores tamoxifen-sensitivity in breast cancer cells.

Estrogen receptor alpha (ERα) is highly expressed in most breast cancers. Consequently, ERα modulators, such as tamoxifen, are successful in breast cancer treatment, although tamoxifen resistance is commonly observed. While tamoxifen resistance may be caused by altered ERα signaling, the molecular mechanisms regulating ERα signaling and tamoxifen resistance are not entirely clear. Here, we found that PAK4 expression was consistently correlated to poor patient outcome in endocrine treated and tamoxifen-only treated breast cancer patients. Importantly, while PAK4 overexpression promoted tamoxifen resistance in MCF-7 human breast cancer cells, pharmacological treatment with a group II PAK (PAK4, 5, 6) inhibitor, GNE-2861, sensitized tamoxifen resistant MCF-7/LCC2 breast cancer cells to tamoxifen. Mechanistically, we identified a regulatory positive feedback loop, where ERα bound to the PAK4 gene, thereby promoting PAK4 expression, while PAK4 in turn stabilized the ERα protein, activated ERα transcriptional activity and ERα target gene expression. Further, PAK4 phosphorylated ERα-Ser305, a phosphorylation event needed for the PAK4 activation of ERα-dependent transcription. In conclusion, PAK4 may be a suitable target for perturbing ERα signaling and tamoxifen resistance in breast cancer patients.

Randomized phase II/III trial assessing gemcitabine/carboplatin and methotrexate/carboplatin/vinblastine in patients with advanced urothelial cancer who are unfit for cisplatin-based chemotherapy: EORTC study 30986.

PURPOSE: This is the first randomized phase II/III trial comparing two carboplatin-based chemotherapy regimens in patients with urothelial cancer who are ineligible ("unfit") for cisplatin chemotherapy. PATIENTS AND METHODS: The primary objective of the phase III part of this study was to compare the overall survival (OS) of chemotherapy-naive patients with measurable disease and an impaired renal function (glomerular filtration rate < 60 but > 30 mL/min) and/or performance score of 2 who were randomly assigned to receive either gemcitabine/carboplatin (GC) or methotrexate/carboplatin/vinblastine (M-CAVI). To detect an increase of 50% in median survival with GC compared with M-CAVI (13.5 v 9 months) based on a two-sided log-rank test at error rates α = .05 and ß = .20, 225 patients were required. Secondary end points were overall response rate (ORR), progression-free survival (PFS), toxicity, and quality of life. RESULTS: In all, 238 patients were randomly assigned by 29 institutions over a period of 7 years. The median follow-up was 4.5 years. Best ORRs were 41.2% (36.1% confirmed response) for patients receiving GC versus 30.3% (21.0% confirmed response) for patients receiving M-CAVI (P = .08). Median OS was 9.3 months in the GC arm and 8.1 months in the M-CAVI arm (P = .64). There was no difference in PFS (P = .78) between the two arms. Severe acute toxicity (death, grade 4 thrombocytopenia with bleeding, grade 3 or 4 renal toxicity, neutropenic fever, or mucositis) was observed in 9.3% of patients receiving GC and 21.2% of patients receiving M-CAVI. CONCLUSION: There were no significant differences in efficacy between the two treatment groups. The incidence of severe acute toxicities was higher for those receiving M-CAVI.