A Composite Decision Rule of CD8+ T-cell Density in Tumor Biopsies Predicts Efficacy in Early-stage, Immunotherapy Trials.

PURPOSE: To examine whether CD8+ T-cell numbers in paired tumor biopsies in early-stage clinical trials can be used as an early indicator of clinical benefit for cancer immunotherapies. EXPERIMENTAL DESIGN: Paraffin sections of tumor biopsies were stained immunohistochemically for CD8+ T cells, which were digitally enumerated. The tumor biopsies were from cancer patients in early-phase trials testing novel immunotherapeutic agents. Paired biopsies taken before the start of treatment and on-treatment were compared. A total of 155 patients were used as the training set and an additional 221 patients were used as the validation set. RESULTS: Using the Cox proportional hazard model, a ≥0.9- increase in fold change (FC) on a ln scale in CD8+ T cells (corresponding to a 2.5-fold increase on the linear scale), from baseline, demonstrated a greater association with prolonged progression-free survival and allowed improved differentiation between groups above and below the threshold. Similarly, a ≥6.2 threshold in geometric mean of the on-treatment density (OTD) of T cells, which approximately corresponds to 500 cells/mm2, correlated with longer PFS. The combination of both criteria (FC and OTD) provided the best discrimination between clinically nonactive and active compounds. CONCLUSIONS: We propose that a composite score of CD8+ T-cell density in paired biopsies taken before and on-treatment may be a new biomarker to inform on clinical outcomes in early immunotherapy clinical trials.

Zika virus infection of mature neurons from immunocompetent mice generates a disease-associated microglia and a tauopathy-like phenotype in link with a delayed interferon beta response.

BACKGROUND: Zika virus (ZIKV) infection at postnatal or adult age can lead to neurological disorders associated with cognitive defects. Yet, how mature neurons respond to ZIKV remains substantially unexplored. METHODS: The impact of ZIKV infection on mature neurons and microglia was analyzed at the molecular and cellular levels, in vitro using immunocompetent primary cultured neurons and microglia, and in vivo in the brain of adult immunocompetent mice following intracranial ZIKV inoculation. We have used C57BL/6 and the genetically diverse Collaborative Cross mouse strains, displaying a broad range of susceptibility to ZIKV infection, to question the correlation between the effects induced by ZIKV infection on neurons and microglia and the in vivo susceptibility to ZIKV. RESULTS: As a result of a delayed induction of interferon beta (IFNB) expression and response, infected neurons displayed an inability to stop ZIKV replication, a trait that was further increased in neurons from susceptible mice. Alongside with an enhanced expression of ZIKV RNA, we observed in vivo, in the brain of susceptible mice, an increased level of active Iba1-expressing microglial cells occasionally engulfing neurons and displaying a gene expression profile close to the molecular signature of disease-associated microglia (DAM). In vivo as well as in vitro, only neurons and not microglial cells were identified as infected, raising the question of the mechanisms underlying microglia activation following brain ZIKV infection. Treatment of primary cultured microglia with conditioned media from ZIKV-infected neurons demonstrated that type-I interferons (IFNs-I) secreted by neurons late after infection activate non-infected microglial cells. In addition, ZIKV infection induced pathological phosphorylation of Tau (pTau) protein, a hallmark of neurodegenerative tauopathies, in vitro and in vivo with clusters of neurons displaying pTau surrounded by active microglial cells. CONCLUSIONS: We show that ZIKV-infected mature neurons display an inability to stop viral replication in link with a delayed IFNB expression and response, while signaling microglia for activation through IFNs-I secreted at late times post-infection. In the brain of ZIKV-infected susceptible mice, uninfected microglial cells adopt an active morphology and a DAM expression profile, surrounding and sometimes engulfing neurons while ZIKV-infected neurons accumulate pTau, overall reflecting a tauopathy-like phenotype.

Effect of Monoclonal Antibody Blockade of Long Fragment Neurotensin on Weight Loss, Behavior, and Metabolic Traits After High-Fat Diet Induced Obesity.

Background: Obesity is a major public health problem of our time as a risk factor for cardiometabolic disease and the available pharmacological tools needed to tackle the obesity pandemic are insufficient. Neurotensin (NTS) is a 13 amino acid peptide, which is derived from a larger precursor hormone called proneurotensin or Long Form NTS (LF NTS). NTS modulates neuro-transmitter release in the central system nervous, and facilitates intestinal fat absorption in the gastrointestinal tract. Mice lacking LF NTS are protected from high fat diet (HFD) induced obesity, hepatic steatosis and glucose intolerance. In humans, increased levels of LF NTS strongly and independently predict the development of obesity, diabetes mellitus, cardiovascular disease and mortality. With the perspective to develop therapeutic tools to neutralize LF NTS, we developed a monoclonal antibody, specifically inhibiting the function of the LF NTS (LF NTS mAb). This antibody was tested for the effects on body weight, metabolic parameters and behavior in mice made obese by high-fat diet. Methods: C57bl/6j mice were subjected to high-fat diet (HFD) until they reached an obesity state, then food was switched to chow. Mice were treated with either PBS (control therapy) or LF NTS mAb at the dose of 5 mg/kg once a week (i.v.). Mice weight, plasma biochemical analysis, fat and muscle size and distribution and behavioral tests were performed during the losing weight period and the stabilization period. Results: Obese mice treated with the LF NTS mAb lost weight significantly faster than the control treated group. LF NTS mAb treatment also resulted in smaller fat depots, increased fecal cholesterol excretion, reduced liver fat and larger muscle fiber size. Moreover, mice on active therapy were also less stressed, more curious and more active, providing a possible explanation to their weight loss. Conclusion: Our results demonstrate that in mice subjected to HFD-induced obesity, a blockade of LF NTS with a monoclonal antibody results in reduced body weight, adipocyte volume and increased muscle fiber size, possibly explained by beneficial effects on behavior. The underlying mechanisms as well as any future role of LF NTS mAb as an anti-obesity agent warrants further studies.

Bayesian hierarchical meta-analytic methods for modeling surrogate relationships that vary across treatment classes using aggregate data.

Surrogate endpoints play an important role in drug development when they can be used to measure treatment effect early compared to the final clinical outcome and to predict clinical benefit or harm. Such endpoints are assessed for their predictive value of clinical benefit by investigating the surrogate relationship between treatment effects on the surrogate and final outcomes using meta-analytic methods. When surrogate relationships vary across treatment classes, such validation may fail due to limited data within each treatment class. In this paper, two alternative Bayesian meta-analytic methods are introduced which allow for borrowing of information from other treatment classes when exploring the surrogacy in a particular class. The first approach extends a standard model for the evaluation of surrogate endpoints to a hierarchical meta-analysis model assuming full exchangeability of surrogate relationships across all the treatment classes, thus facilitating borrowing of information across the classes. The second method is able to relax this assumption by allowing for partial exchangeability of surrogate relationships across treatment classes to avoid excessive borrowing of information from distinctly different classes. We carried out a simulation study to assess the proposed methods in nine data scenarios and compared them with subgroup analysis using the standard model within each treatment class. We also applied the methods to an illustrative example in colorectal cancer which led to obtaining the parameters describing the surrogate relationships with higher precision.

Cisplatin increases PD-L1 expression and optimizes immune check-point blockade in non-small cell lung cancer.

The number of clinical protocols testing combined therapies including immune check-point inhibitors and platinum salts is currently increasing in lung cancer treatment, however preclinical studies and rationale are often lacking. Here, we evaluated the impact of cisplatin treatment on PD-L1 expression analyzing the clinicopathological characteristics of patients who received cisplatin-based neoadjuvant chemotherapy followed by surgery and showed that cisplatin-based induction treatment significantly increased PD-L1 staining in both tumor and immune cells from the microenvironment. Twenty-two patients exhibited positive PD-L1 staining variation after neoadjuvant chemotherapy; including 9 (23.1%) patients switching from <50% to ≥50% of stained tumor-cells. We also confirmed the up-regulation of PD-L1 by cisplatin, at both RNA and protein levels, in nude and immunocompetent mice bearing tumors grafted with A549, LNM-R, or LLC1 lung cancer cell lines. The combined administration of anti-PD-L1 antibodies (3 mg/kg) and cisplatin (1 mg/kg) to mice harboring lung carcinoma significantly reduced tumor growth compared to single agent treatments and controls. Overall, these results suggest that cisplatin treatment could synergize with PD-1/PD-L1 blockade to increase the clinical response, in particular through early and sustainable enhancement of PD-L1 expression.

Bivariate network meta-analysis for surrogate endpoint evaluation.

Surrogate endpoints are very important in regulatory decision making in healthcare, in particular if they can be measured early compared to the long-term final clinical outcome and act as good predictors of clinical benefit. Bivariate meta-analysis methods can be used to evaluate surrogate endpoints and to predict the treatment effect on the final outcome from the treatment effect measured on a surrogate endpoint. However, candidate surrogate endpoints are often imperfect, and the level of association between the treatment effects on the surrogate and final outcomes may vary between treatments. This imposes a limitation on methods which do not differentiate between the treatments. We develop bivariate network meta-analysis (bvNMA) methods, which combine data on treatment effects on the surrogate and final outcomes, from trials investigating multiple treatment contrasts. The bvNMA methods estimate the effects on both outcomes for all treatment contrasts individually in a single analysis. At the same time, they allow us to model the trial-level surrogacy patterns within each treatment contrast and treatment-level surrogacy, thus enabling predictions of the treatment effect on the final outcome either for a new study in a new population or for a new treatment. Modelling assumptions about the between-studies heterogeneity and the network consistency, and their impact on predictions, are investigated using an illustrative example in advanced colorectal cancer and in a simulation study. When the strength of the surrogate relationships varies across treatment contrasts, bvNMA has the advantage of identifying treatment comparisons for which surrogacy holds, thus leading to better predictions.

Modulation of lung cancer cell plasticity and heterogeneity with the restoration of cisplatin sensitivity by neurotensin antibody.

Overall survival of patients with metastatic non-small cell lung cancer (NSCLC) has significantly improved with platinum-based salt treatments and recently with targeted therapies and immunotherapies. However, treatment failure occurs due to acquired or emerging tumor resistance. We developed a monoclonal antibody against the proform of neurotensin (LF-NTS mAb) that alters the homeostasis of tumors overexpressing NTSR1. Neurotensin is frequently overexpressed along with its high affinity receptor (NTSR1) in tumors from epithelial origins. This ligand/receptor complex contributes to the progression of many tumor types by activation of the cellular effects involved in tumor progression (proliferation, survival, migration, and invasion). We demonstrate that LF-NTS mAb operates on the plasticity of tumor cells overexpressing NTSR1 and lowers their aggressiveness. The mAb enables the restoration of platinum-based therapies responsiveness, while also decreasing metastatic processes. Efficacy dosage with long-term treatment showed no obvious adverse events, while demonstrating improvement in the performance status. Our data suggests that LF-NTS mAb is an ideal candidate to be safely added to the conventional standard of care in order to improve its efficacy.

Molecular heterogeneity at the network level: high-dimensional testing, clustering and a TCGA case study.

MOTIVATION: Molecular pathways and networks play a key role in basic and disease biology. An emerging notion is that networks encoding patterns of molecular interplay may themselves differ between contexts, such as cell type, tissue or disease (sub)type. However, while statistical testing of differences in mean expression levels has been extensively studied, testing of network differences remains challenging. Furthermore, since network differences could provide important and biologically interpretable information to identify molecular subgroups, there is a need to consider the unsupervised task of learning subgroups and networks that define them. This is a nontrivial clustering problem, with neither subgroups nor subgroup-specific networks known at the outset. RESULTS: We leverage recent ideas from high-dimensional statistics for testing and clustering in the network biology setting. The methods we describe can be applied directly to most continuous molecular measurements and networks do not need to be specified beforehand. We illustrate the ideas and methods in a case study using protein data from The Cancer Genome Atlas (TCGA). This provides evidence that patterns of interplay between signalling proteins differ significantly between cancer types. Furthermore, we show how the proposed approaches can be used to learn subtypes and the molecular networks that define them. AVAILABILITY AND IMPLEMENTATION: As the Bioconductor package nethet. CONTACT: staedler.n@gmail.com or sach.mukherjee@dzne.de. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Neurotensin regulation induces overexpression and activation of EGFR in HCC and restores response to erlotinib and sorafenib.

Hepatocellular carcinoma (HCC) is the third leading cause of death from cancer due to the combination of late diagnosis and a lack of curative treatments. The identification of factors which promote tumor aggressiveness, and those that predict treatment responses, are a means to optimize the management of HCC patients. The complex of Neurotensin (NTS) and its high affinity receptor (NTSR1) has been shown to induce tumor growth and metastasis process in various cancers. In this paper, we propose that NTS and NTSR1 can assist in the management of HCC. Concomitant expression of NTS/NTSR1 was correlated with poor prognosis and found in 50% of HCC patients. We show that NTSR1 expression was positively correlated with the alteration of the Wnt/ß-catenin pathway. Its activation creates EGFR driver activation which consequently enhances tumor progression, and sensitizes HCC tumor cells to TKI, such as sorafenib. The NTS/NTSR1 complex is a potential drug target for HCC, because it is an upstream regulator in the chain of cellular events involved in HCC progression. It could also be used as a theranostic biomarker for sorafenib to improve the HCC patient management.

A Systematic Review and Network Meta-Analysis to Evaluate the Comparative Efficacy of Interventions for Unfit Patients with Chronic Lymphocytic Leukemia.

INTRODUCTION: Rituximab plus fludarabine and cyclophosphamide (RFC) is the standard of care for fit patients with untreated chronic lymphocytic leukemia (CLL); however, its use is limited in 'unfit' (co-morbid and/or full-dose F-ineligible) patients due to its toxicity profile. We conducted a systematic review and Bayesian network meta-analysis (NMA) to determine the relative efficacy of commercially available interventions for the first-line treatment of unfit CLL patients. METHODS: For inclusion in the NMA, studies had to be linked via common treatment comparators, report progression-free survival (PFS), and/or overall survival (OS), and meet at least one of the five inclusion criteria: median cumulative illness score >6, median creatinine clearance ≤70 mL/min, existing co-morbidities, median age ≥70 years, and no full-dose F in the comparator arm. A manual review, validated by external experts, of all studies that met at least one of these criteria was also performed to confirm that they evaluated first-line therapeutic options for unfit patients with CLL. RESULTS: In unfit patients, the main NMA (five studies for PFS and four for OS) demonstrated clear preference in terms of PFS for obinutuzumab + chlorambucil (G-Clb) versus rituximab + chlorambucil (R-Clb), ofatumumab + chlorambucil (O-Clb), fludarabine and chlorambucil (median hazard ratios [HRs] 0.43, 0.33, 0.20, and 0.19, respectively), and a trend for better efficacy versus rituximab + bendamustine (R-Benda) and RFC-Lite (median HR 0.81 and 0.88, respectively). OS results were generally consistent with PFS data, (median HR 0.48, 0.53, and 0.81, respectively) for G-Clb versus Clb, O-Clb, and R-Clb 0.35 and 0.81 versus F and R-Benda, respectively); however, the OS findings were associated with higher uncertainty. Treatment ranking reflected improved PFS and OS with G-Clb over other treatment strategies (median rank of one for both endpoints). CONCLUSION: G-Clb is likely to show superior efficacy to other treatment options selected in our NMA for unfit treatment-naïve patients with CLL. FUNDING: F. Hoffmann-La Roche Ltd.

Multivariate gene-set testing based on graphical models.

The identification of predefined groups of genes ("gene-sets") which are differentially expressed between two conditions ("gene-set analysis", or GSA) is a very popular analysis in bioinformatics. GSA incorporates biological knowledge by aggregating over genes that are believed to be functionally related. This can enhance statistical power over analyses that consider only one gene at a time. However, currently available GSA approaches are based on univariate two-sample comparison of single genes. This means that they cannot test for multivariate hypotheses such as differences in covariance structure between the two conditions. Yet interplay between genes is a central aspect of biological investigation and it is likely that such interplay may differ between conditions. This paper proposes a novel approach for gene-set analysis that allows for truly multivariate hypotheses, in particular differences in gene-gene networks between conditions. Testing hypotheses concerning networks is challenging due the nature of the underlying estimation problem. Our starting point is a recent, general approach for high-dimensional two-sample testing. We refine the approach and show how it can be used to perform multivariate, network-based gene-set testing. We validate the approach in simulated examples and show results using high-throughput data from several studies in cancer biology.

A pan-cancer proteomic perspective on The Cancer Genome Atlas.

Protein levels and function are poorly predicted by genomic and transcriptomic analysis of patient tumours. Therefore, direct study of the functional proteome has the potential to provide a wealth of information that complements and extends genomic, epigenomic and transcriptomic analysis in The Cancer Genome Atlas (TCGA) projects. Here we use reverse-phase protein arrays to analyse 3,467 patient samples from 11 TCGA 'Pan-Cancer' diseases, using 181 high-quality antibodies that target 128 total proteins and 53 post-translationally modified proteins. The resultant proteomic data are integrated with genomic and transcriptomic analyses of the same samples to identify commonalities, differences, emergent pathways and network biology within and across tumour lineages. In addition, tissue-specific signals are reduced computationally to enhance biomarker and target discovery spanning multiple tumour lineages. This integrative analysis, with an emphasis on pathways and potentially actionable proteins, provides a framework for determining the prognostic, predictive and therapeutic relevance of the functional proteome.

Boundary cap cells are peripheral nervous system stem cells that can be redirected into central nervous system lineages.

Boundary cap cells (BC), which express the transcription factor Krox20, participate in the formation of the boundary between the central nervous system and the peripheral nervous system. To study BC stemness, we developed a method to purify and amplify BC in vitro from Krox20(Cre/+), R26R(YFP/+) mouse embryos. We show that BC progeny are EGF/FGF2-responsive, form spheres, and express neural crest markers. Upon growth factor withdrawal, BC progeny gave rise to multiple neural crest and CNS lineages. Transplanted into the developing murine forebrain, they successfully survived, migrated, and integrated within the host environment. Surprisingly, BC progeny generated exclusively CNS cells, including neurons, astrocytes, and myelin-forming oligodendrocytes. In vitro experiments indicated that a sequential combination of ventralizing morphogens and glial growth factors was necessary to reprogram BC into oligodendrocytes. Thus, BC progeny are endowed with differentiation plasticity beyond the peripheral nervous system. The demonstration that CNS developmental cues can reprogram neural crest-derived stem cells into CNS derivatives suggests that BC could serve as a source of cell type-specific lineages, including oligodendrocytes, for cell-based therapies to treat CNS disorders.

Normal immune system development in mice lacking the Deltex-1 RING finger domain.

The Notch signaling pathway controls several cell fate decisions during lymphocyte development, from T-cell lineage commitment to the peripheral differentiation of B and T lymphocytes. Deltex-1 is a RING finger ubiquitin ligase which is conserved from Drosophila to humans and has been proposed to be a regulator of Notch signaling. Its pattern of lymphoid expression as well as gain-of-function experiments suggest that Deltex-1 regulates both B-cell lineage and splenic marginal-zone B-cell commitment. Deltex-1 was also found to be highly expressed in germinal-center B cells. To investigate the physiological function of Deltex-1, we generated a mouse strain lacking the Deltex-1 RING finger domain, which is essential for its ubiquitin ligase activity. Deltex-1(Delta/Delta) mice were viable and fertile. A detailed histological analysis did not reveal any defects in major organs. T- and B-cell development was normal, as were humoral responses against T-dependent and T-independent antigens. These data indicate that the Deltex-1 ubiquitin ligase activity is dispensable for mouse development and immune function. Possible compensatory mechanisms, in particular those from a fourth Deltex gene identified during the course of this study, are also discussed.