Spatial multiomics map of trophoblast development in early pregnancy.

The relationship between the human placenta-the extraembryonic organ made by the fetus, and the decidua-the mucosal layer of the uterus, is essential to nurture and protect the fetus during pregnancy. Extravillous trophoblast cells (EVTs) derived from placental villi infiltrate the decidua, transforming the maternal arteries into high-conductance vessels1. Defects in trophoblast invasion and arterial transformation established during early pregnancy underlie common pregnancy disorders such as pre-eclampsia2. Here we have generated a spatially resolved multiomics single-cell atlas of the entire human maternal-fetal interface including the myometrium, which enables us to resolve the full trajectory of trophoblast differentiation. We have used this cellular map to infer the possible transcription factors mediating EVT invasion and show that they are preserved in in vitro models of EVT differentiation from primary trophoblast organoids3,4 and trophoblast stem cells5. We define the transcriptomes of the final cell states of trophoblast invasion: placental bed giant cells (fused multinucleated EVTs) and endovascular EVTs (which form plugs inside the maternal arteries). We predict the cell-cell communication events contributing to trophoblast invasion and placental bed giant cell formation, and model the dual role of interstitial EVTs and endovascular EVTs in mediating arterial transformation during early pregnancy. Together, our data provide a comprehensive analysis of postimplantation trophoblast differentiation that can be used to inform the design of experimental models of the human placenta in early pregnancy.

Excess weight and anti-PD-1 immune checkpoint inhibitor’s outcomes in non-small cell lung cancer

Immune checkpoint inhibitors are one of the most effective treatments available in advanced non-small cell lung cancer. However, at present, there are no clinical or analytical biomarkers that define which patients benefit with certainty from these treatments. In our study, we evaluated whether excess weight could be a good predictive biomarker of benefit from these drugs.MethodsWe studied a population of 79 patients, divided into a study group with 39 patients diagnosed with non-small cell lung cancer treated with immunotherapy and 40 patients in a control group, diagnosed with different advanced cancers, treated with non-immunotherapy treatment. We analyzed according to the presence of excess weight or not, the treatment’s outcome in the study group and in the control group (objective response, and progression-free and overall survival).ResultsIn our study, we detected a better response rate to immunotherapy in patients with excess weight (62.50 vs 26.08%, OR 4.72, p = 0.02), and a better median progression-free survival (14.19 vs 5.03 months, HR 0.50, p = 0.058) and median overall survival (33.84 months vs 20.76 months, HR 0.43, p = 0.01) in the study group. These findings were specific to the immunotherapy group since in the control group, with patients who did not receive immune checkpoint inhibitors, these findings were not found.ConclusionOur study suggests that patients with excess weight who receive anti-PD-1 immune checkpoint inhibitors diagnosed with non-small cell lung cancer have a better outcome. This effect is specific to patients receiving immunotherapy. (AU)

Excess weight and anti-PD-1 immune checkpoint inhibitor's outcomes in non-small cell lung cancer.

PURPOSE: Immune checkpoint inhibitors are one of the most effective treatments available in advanced non-small cell lung cancer. However, at present, there are no clinical or analytical biomarkers that define which patients benefit with certainty from these treatments. In our study, we evaluated whether excess weight could be a good predictive biomarker of benefit from these drugs. METHODS: We studied a population of 79 patients, divided into a study group with 39 patients diagnosed with non-small cell lung cancer treated with immunotherapy and 40 patients in a control group, diagnosed with different advanced cancers, treated with non-immunotherapy treatment. We analyzed according to the presence of excess weight or not, the treatment's outcome in the study group and in the control group (objective response, and progression-free and overall survival). RESULTS: In our study, we detected a better response rate to immunotherapy in patients with excess weight (62.50 vs 26.08%, OR 4.72, p = 0.02), and a better median progression-free survival (14.19 vs 5.03 months, HR 0.50, p = 0.058) and median overall survival (33.84 months vs 20.76 months, HR 0.43, p = 0.01) in the study group. These findings were specific to the immunotherapy group since in the control group, with patients who did not receive immune checkpoint inhibitors, these findings were not found. CONCLUSION: Our study suggests that patients with excess weight who receive anti-PD-1 immune checkpoint inhibitors diagnosed with non-small cell lung cancer have a better outcome. This effect is specific to patients receiving immunotherapy.

Peripheral Blood Mononuclear Cells Predict Therapeutic Efficacy of Immunotherapy in NSCLC.

In lung cancer immunotherapy, biomarkers to guide clinical decisions are limited. We now explore whether the detailed immunophenotyping of circulating peripheral blood mononuclear cells (PBMCs) can predict the efficacy of anti-PD-1 immunotherapy in patients with advanced non-small-cell lung cancer (NSCLC). We determined 107 PBMCs subpopulations in a prospective cohort of NSCLC patients before starting single-agent anti-PD-1 immunotherapy (study group), analyzed by flow cytometry. As a control group, we studied patients with advanced malignancies before initiating non-immunotherapy treatment. The frequency of PBMCs was correlated with treatment outcome. Patients were categorized as having either high or low expression for each biomarker, defined as those above the 55th or below the 45th percentile of the overall marker expression within the cohort. In the study group, three subpopulations were associated with significant differences in outcome: high pretreatment levels of circulating CD4+CCR9+, CD4+CCR10+, or CD8+CXCR4+ T cells correlated with poorer overall survival (15.7 vs. 35.9 months, HR 0.16, p = 0.003; 22.0 vs. NR months, HR 0.10, p = 0.003, and 22.0 vs. NR months, HR 0.29, p = 0.02). These differences were specific to immunotherapy-treated patients. High baseline levels of circulating T cell subpopulations related to tissue lymphocyte recruitment are associated with poorer outcomes of immunotherapy-treated advanced NSCLC patients.

Stratification of radiosensitive brain metastases based on an actionable S100A9/RAGE resistance mechanism.

Whole-brain radiotherapy (WBRT) is the treatment backbone for many patients with brain metastasis; however, its efficacy in preventing disease progression and the associated toxicity have questioned the clinical impact of this approach and emphasized the need for alternative treatments. Given the limited therapeutic options available for these patients and the poor understanding of the molecular mechanisms underlying the resistance of metastatic lesions to WBRT, we sought to uncover actionable targets and biomarkers that could help to refine patient selection. Through an unbiased analysis of experimental in vivo models of brain metastasis resistant to WBRT, we identified activation of the S100A9-RAGE-NF-κB-JunB pathway in brain metastases as a potential mediator of resistance in this organ. Targeting this pathway genetically or pharmacologically was sufficient to revert the WBRT resistance and increase therapeutic benefits in vivo at lower doses of radiation. In patients with primary melanoma, lung or breast adenocarcinoma developing brain metastasis, endogenous S100A9 levels in brain lesions correlated with clinical response to WBRT and underscored the potential of S100A9 levels in the blood as a noninvasive biomarker. Collectively, we provide a molecular framework to personalize WBRT and improve its efficacy through combination with a radiosensitizer that balances therapeutic benefit and toxicity.

A comprehensive database for integrated analysis of omics data in autoimmune diseases.

BACKGROUND: Autoimmune diseases are heterogeneous pathologies with difficult diagnosis and few therapeutic options. In the last decade, several omics studies have provided significant insights into the molecular mechanisms of these diseases. Nevertheless, data from different cohorts and pathologies are stored independently in public repositories and a unified resource is imperative to assist researchers in this field. RESULTS: Here, we present Autoimmune Diseases Explorer ( https://adex.genyo.es ), a database that integrates 82 curated transcriptomics and methylation studies covering 5609 samples for some of the most common autoimmune diseases. The database provides, in an easy-to-use environment, advanced data analysis and statistical methods for exploring omics datasets, including meta-analysis, differential expression or pathway analysis. CONCLUSIONS: This is the first omics database focused on autoimmune diseases. This resource incorporates homogeneously processed data to facilitate integrative analyses among studies.

RANK links senescence to stemness in the mammary epithelia, delaying tumor onset but increasing tumor aggressiveness.

Rank signaling enhances stemness in mouse and human mammary epithelial cells (MECs) and mediates mammary tumor initiation. Mammary tumors initiated by oncogenes or carcinogen exposure display high levels of Rank and Rank pathway inhibitors have emerged as a new strategy for breast cancer prevention and treatment. Here, we show that ectopic Rank expression in the mammary epithelia unexpectedly delays tumor onset and reduces tumor incidence in the oncogene-driven Neu and PyMT models. Mechanistically, we have found that ectopic expression of Rank or exposure to Rankl induces senescence, even in the absence of other oncogenic mutations. Rank leads to DNA damage and senescence through p16/p19. Moreover, RANK-induced senescence is essential for Rank-driven stemness, and although initially translates into delayed tumor growth, eventually promotes tumor progression and metastasis. We uncover a dual role for Rank in the mammary epithelia: Rank induces senescence and stemness, delaying tumor initiation but increasing tumor aggressiveness.

DREIMT: a drug repositioning database and prioritization tool for immunomodulation.

MOTIVATION: Drug immunomodulation modifies the response of the immune system and can be therapeutically exploited in pathologies such as cancer and autoimmune diseases. RESULTS: DREIMT is a new hypothesis-generation web tool, which performs drug prioritization analysis for immunomodulation. DREIMT provides significant immunomodulatory drugs targeting up to 70 immune cells subtypes through a curated database that integrates 4960 drug profiles and ∼2600 immune gene expression signatures. The tool also suggests potential immunomodulatory drugs targeting user-supplied gene expression signatures. Final output includes drug-signature association scores, FDRs and downloadable plots and results tables. AVAILABILITYAND IMPLEMENTATION: http://www.dreimt.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Midkine rewires the melanoma microenvironment toward a tolerogenic and immune-resistant state.

An open question in aggressive cancers such as melanoma is how malignant cells can shift the immune system to pro-tumorigenic functions. Here we identify midkine (MDK) as a melanoma-secreted driver of an inflamed, but immune evasive, microenvironment that defines poor patient prognosis and resistance to immune checkpoint blockade. Mechanistically, MDK was found to control the transcriptome of melanoma cells, allowing for coordinated activation of nuclear factor-κB and downregulation of interferon-associated pathways. The resulting MDK-modulated secretome educated macrophages towards tolerant phenotypes that promoted CD8+ T cell dysfunction. In contrast, genetic targeting of MDK sensitized melanoma cells to anti-PD-1/anti-PD-L1 treatment. Emphasizing the translational relevance of these findings, the expression profile of MDK-depleted tumors was enriched in key indicators of a good response to immune checkpoint blockers in independent patient cohorts. Together, these data reveal that MDK acts as an internal modulator of autocrine and paracrine signals that maintain immune suppression in aggressive melanomas.

Oncogenic Rag GTPase signaling enhances B cell activation and drives follicular lymphoma sensitive to pharmacological inhibition of mTOR.

The humoral immune response demands that B cells undergo a sudden anabolic shift and high cellular nutrient levels which are required to sustain the subsequent proliferative burst. Follicular lymphoma (FL) originates from B cells that have participated in the humoral response, and 15% of FL samples harbor point, activating mutations in RRAGC, an essential activator of mTORC1 downstream of the sensing of cellular nutrients. The impact of recurrent RRAGC mutations in B cell function and lymphoma is unexplored. RRAGC mutations, targeted to the endogenous locus in mice, confer a partial insensitivity to nutrient deprivation, but strongly exacerbate B cell responses and accelerate lymphomagenesis, while creating a selective vulnerability to pharmacological inhibition of mTORC1. This moderate increase in nutrient signaling synergizes with paracrine cues from the supportive T cell microenvironment that activates B cells via the PI3K-Akt-mTORC1 axis. Hence, Rragc mutations sustain induced germinal centers and murine and human FL in the presence of decreased T cell help. Our results support a model in which activating mutations in the nutrient signaling pathway foster lymphomagenesis by corrupting a nutrient-dependent control over paracrine signals from the T cell microenvironment.

Cutaneous Immune Cell-Microbiota Interactions Are Controlled by Epidermal JunB/AP-1.

Atopic dermatitis (AD) is a multi-factorial skin disease with a complex inflammatory signature including type 2 and type 17 activation. Although colonization by S. aureus is common in AD, the mechanisms rendering an organism prone to dysbiosis, and the role of IL-17A in the control of S. aureus-induced skin inflammation, are not well understood. Here, we show several pathological aspects of AD, including type 2/type 17 immune responses, elevated IgE, barrier dysfunction, pruritus, and importantly, spontaneous S. aureus colonization in JunBΔep mice, with a large transcriptomic overlap with AD. Additionally, using Rag1-/- mice, we demonstrate that adaptive immune cells are necessary for protection against S. aureus colonization. Prophylactic antibiotics, but not antibiotics after established dysbiosis, reduce IL-17A expression and skin inflammation, examined using Il17a-eGFP reporter mice. Mechanistically, keratinocytes lacking JunB exhibit higher MyD88 levels in vitro and in vivo, previously shown to regulate S. aureus colonization. In conclusion, our data identify JunB as an upstream regulator of microbiota-immune cell interactions and characterize the IL-17A response upon spontaneous dysbiosis.

Clonal dynamics monitoring during clinical evolution in chronic lymphocytic leukaemia.

Chronic lymphocytic leukaemia is the most prevalent leukaemia in Western countries. It is an incurable disease characterized by a highly variable clinical course. Chronic lymphocytic leukaemia is an ideal model for studying clonal heterogeneity and dynamics during cancer progression, response to therapy and/or relapse because the disease usually develops over several years. Here we report an analysis by deep sequencing of sequential samples taken at different times from the affected organs of two patients with 12- and 7-year disease courses, respectively. One of the patients followed a linear pattern of clonal evolution, acquiring and selecting new mutations in response to salvage therapy and/or allogeneic transplantation, while the other suffered loss of cellular tumoral clones during progression and histological transformation.

PanDrugs: a novel method to prioritize anticancer drug treatments according to individual genomic data.

BACKGROUND: Large-sequencing cancer genome projects have shown that tumors have thousands of molecular alterations and their frequency is highly heterogeneous. In such scenarios, physicians and oncologists routinely face lists of cancer genomic alterations where only a minority of them are relevant biomarkers to drive clinical decision-making. For this reason, the medical community agrees on the urgent need of methodologies to establish the relevance of tumor alterations, assisting in genomic profile interpretation, and, more importantly, to prioritize those that could be clinically actionable for cancer therapy. RESULTS: We present PanDrugs, a new computational methodology to guide the selection of personalized treatments in cancer patients using the variant lists provided by genome-wide sequencing analyses. PanDrugs offers the largest database of drug-target associations available from well-known targeted therapies to preclinical drugs. Scoring data-driven gene cancer relevance and drug feasibility PanDrugs interprets genomic alterations and provides a prioritized evidence-based list of anticancer therapies. Our tool represents the first drug prescription strategy applying a rational based on pathway context, multi-gene markers impact and information provided by functional experiments. Our approach has been systematically applied to TCGA patients and successfully validated in a cancer case study with a xenograft mouse model demonstrating its utility. CONCLUSIONS: PanDrugs is a feasible method to identify potentially druggable molecular alterations and prioritize drugs to facilitate the interpretation of genomic landscape and clinical decision-making in cancer patients. Our approach expands the search of druggable genomic alterations from the concept of cancer driver genes to the druggable pathway context extending anticancer therapeutic options beyond already known cancer genes. The methodology is public and easily integratable with custom pipelines through its programmatic API or its docker image. The PanDrugs webtool is freely accessible at http://www.pandrugs.org .

Saa3 is a key mediator of the protumorigenic properties of cancer-associated fibroblasts in pancreatic tumors.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by the presence of abundant desmoplastic stroma primarily composed of cancer-associated fibroblasts (CAFs). It is generally accepted that CAFs stimulate tumor progression and might be implicated in drug resistance and immunosuppression. Here, we have compared the transcriptional profile of PDGFRα+ CAFs isolated from genetically engineered mouse PDAC tumors with that of normal pancreatic fibroblasts to identify genes potentially implicated in their protumorigenic properties. We report that the most differentially expressed gene, Saa3, a member of the serum amyloid A (SAA) apolipoprotein family, is a key mediator of the protumorigenic activity of PDGFRα+ CAFs. Whereas Saa3-competent CAFs stimulate the growth of tumor cells in an orthotopic model, Saa3-null CAFs inhibit tumor growth. Saa3 also plays a role in the cross talk between CAFs and tumor cells. Ablation of Saa3 in pancreatic tumor cells makes them insensitive to the inhibitory effect of Saa3-null CAFs. As a consequence, germline ablation of Saa3 does not prevent PDAC development in mice. The protumorigenic activity of Saa3 in CAFs is mediated by Mpp6, a member of the palmitoylated membrane protein subfamily of the peripheral membrane-associated guanylate kinases (MAGUK). Finally, we interrogated whether these observations could be translated to a human scenario. Indeed, SAA1, the ortholog of murine Saa3, is overexpressed in human CAFs. Moreover, high levels of SAA1 in the stromal component correlate with worse survival. These findings support the concept that selective inhibition of SAA1 in CAFs may provide potential therapeutic benefit to PDAC patients.

Growth rate controls mRNA turnover in steady and non-steady states.

Gene expression has been investigated in relation with growth rate in the yeast Saccharomyces cerevisiae, following different experimental strategies. The expression of some specific gene functional categories increases or decreases with growth rate. Our recently published results have unveiled that these changes in mRNA concentration with growth depend on the relative alteration of mRNA synthesis and decay, and that, in addition to this gene-specific transcriptomic signature of growth, global mRNA turnover increases with growth rate. We discuss here these results in relation with other previous and concurrent publications, and we add new evidence which indicates that growth rate controls mRNA turnover even under non-steady-state conditions.