The Peptidoglycan Recognition Protein 1 confers immune evasive properties on pancreatic cancer stem cells.

OBJECTIVE: Pancreatic ductal adenocarcinoma (PDAC) has limited therapeutic options, particularly with immune checkpoint inhibitors. Highly chemoresistant 'stem-like' cells, known as cancer stem cells (CSCs), are implicated in PDAC aggressiveness. Thus, comprehending how this subset of cells evades the immune system is crucial for advancing novel therapies. DESIGN: We used the KPC mouse model (LSL-KrasG12D/+; LSL-Trp53R172H/+; Pdx-1-Cre) and primary tumour cell lines to investigate putative CSC populations. Transcriptomic analyses were conducted to pinpoint new genes involved in immune evasion. Overexpressing and knockout cell lines were established with lentiviral vectors. Subsequent in vitro coculture assays, in vivo mouse and zebrafish tumorigenesis studies, and in silico database approaches were performed. RESULTS: Using the KPC mouse model, we functionally confirmed a population of cells marked by EpCAM, Sca-1 and CD133 as authentic CSCs and investigated their transcriptional profile. Immune evasion signatures/genes, notably the gene peptidoglycan recognition protein 1 (PGLYRP1), were significantly overexpressed in these CSCs. Modulating PGLYRP1 impacted CSC immune evasion, affecting their resistance to macrophage-mediated and T-cell-mediated killing and their tumourigenesis in immunocompetent mice. Mechanistically, tumour necrosis factor alpha (TNFα)-regulated PGLYRP1 expression interferes with the immune tumour microenvironment (TME) landscape, promoting myeloid cell-derived immunosuppression and activated T-cell death. Importantly, these findings were not only replicated in human models, but clinically, secreted PGLYRP1 levels were significantly elevated in patients with PDAC. CONCLUSIONS: This study establishes PGLYRP1 as a novel CSC-associated marker crucial for immune evasion, particularly against macrophage phagocytosis and T-cell killing, presenting it as a promising target for PDAC immunotherapy.

PanDrugs2: prioritizing cancer therapies using integrated individual multi-omics data.

Genomics studies routinely confront researchers with long lists of tumor alterations detected in patients. Such lists are difficult to interpret since only a minority of the alterations are relevant biomarkers for diagnosis and for designing therapeutic strategies. PanDrugs is a methodology that facilitates the interpretation of tumor molecular alterations and guides the selection of personalized treatments. To do so, PanDrugs scores gene actionability and drug feasibility to provide a prioritized evidence-based list of drugs. Here, we introduce PanDrugs2, a major upgrade of PanDrugs that, in addition to somatic variant analysis, supports a new integrated multi-omics analysis which simultaneously combines somatic and germline variants, copy number variation and gene expression data. Moreover, PanDrugs2 now considers cancer genetic dependencies to extend tumor vulnerabilities providing therapeutic options for untargetable genes. Importantly, a novel intuitive report to support clinical decision-making is generated. PanDrugs database has been updated, integrating 23 primary sources that support >74K drug-gene associations obtained from 4642 genes and 14 659 unique compounds. The database has also been reimplemented to allow semi-automatic updates to facilitate maintenance and release of future versions. PanDrugs2 does not require login and is freely available at https://www.pandrugs.org/.

Mitochondrial RNA methyltransferase TRMT61B is a new, potential biomarker and therapeutic target for highly aneuploid cancers.

Despite being frequently observed in cancer cells, chromosomal instability (CIN) and its immediate consequence, aneuploidy, trigger adverse effects on cellular homeostasis that need to be overcome by anti-stress mechanisms. As such, these safeguard responses represent a tumor-specific Achilles heel, since CIN and aneuploidy are rarely observed in normal cells. Recent data have revealed that epitranscriptomic marks catalyzed by RNA-modifying enzymes change under various stress insults. However, whether aneuploidy is associated with such RNA modifying pathways remains to be determined. Through an in silico search for aneuploidy biomarkers in cancer cells, we found TRMT61B, a mitochondrial RNA methyltransferase enzyme, to be associated with high levels of aneuploidy. Accordingly, TRMT61B protein levels are increased in tumor cell lines with an imbalanced karyotype as well as in different tumor types when compared to control tissues. Interestingly, while TRMT61B depletion induces senescence in melanoma cell lines with low levels of aneuploidy, it leads to apoptosis in cells with high levels. The therapeutic potential of these results was further validated by targeting TRMT61B in transwell and xenografts assays. We show that TRM61B depletion reduces the expression of several mitochondrial encoded proteins and limits mitochondrial function. Taken together, these results identify a new biomarker of aneuploidy in cancer cells that could potentially be used to selectively target highly aneuploid tumors.

Bioinformatics roadmap for therapy selection in cancer genomics.

Tumour heterogeneity is one of the main characteristics of cancer and can be categorised into inter- or intratumour heterogeneity. This heterogeneity has been revealed as one of the key causes of treatment failure and relapse. Precision oncology is an emerging field that seeks to design tailored treatments for each cancer patient according to epidemiological, clinical and omics data. This discipline relies on bioinformatics tools designed to compute scores to prioritise available drugs, with the aim of helping clinicians in treatment selection. In this review, we describe the current approaches for therapy selection depending on which type of tumour heterogeneity is being targeted and the available next-generation sequencing data. We cover intertumour heterogeneity studies and individual treatment selection using genomics variants, expression data or multi-omics strategies. We also describe intratumour dissection through clonal inference and single-cell transcriptomics, in each case providing bioinformatics tools for tailored treatment selection. Finally, we discuss how these therapy selection workflows could be integrated into the clinical practice.

An in silico analysis identifies drugs potentially modulating the cytokine storm triggered by SARS-CoV-2 infection.

The ongoing COVID-19 pandemic is one of the biggest health challenges of recent decades. Among the causes of mortality triggered by SARS-CoV-2 infection, the development of an inflammatory "cytokine storm" (CS) plays a determinant role. Here, we used transcriptomic data from the bronchoalveolar lavage fluid (BALF) of COVID-19 patients undergoing a CS to obtain gene-signatures associated to this pathology. Using these signatures, we interrogated the Connectivity Map (CMap) dataset that contains the effects of over 5000 small molecules on the transcriptome of human cell lines, and looked for molecules which effects on transcription mimic or oppose those of the CS. As expected, molecules that potentiate immune responses such as PKC activators are predicted to worsen the CS. In addition, we identified the negative regulation of female hormones among pathways potentially aggravating the CS, which helps to understand the gender-related differences in COVID-19 mortality. Regarding drugs potentially counteracting the CS, we identified glucocorticoids as a top hit, which validates our approach as this is the primary treatment for this pathology. Interestingly, our analysis also reveals a potential effect of MEK inhibitors in reverting the COVID-19 CS, which is supported by in vitro data that confirms the anti-inflammatory properties of these compounds.

bollito: a flexible pipeline for comprehensive single-cell RNA-seq analyses.

SUMMARY: bollito is an automated, flexible and parallelizable computational pipeline for the comprehensive analysis of single-cell RNA-seq data. Starting from FASTQ files or preprocessed expression matrices, bollito performs both basic and advanced tasks in single-cell analysis integrating >30 state-of-the-art tools. This includes quality control, read alignment, dimensionality reduction, clustering, cell-marker detection, differential expression, functional analysis, trajectory inference and RNA velocity. bollito is built using the Snakemake workflow management system, which easily connects each execution step and facilitates the reproducibility of results. bollito's modular design makes it easy to incorporate other packages into the pipeline enabling its expansion with new functionalities. AVAILABILITY AND IMPLEMENTATION: Source code is freely available at https://gitlab.com/bu_cnio/bollito under the MIT license. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Beyondcell: targeting cancer therapeutic heterogeneity in single-cell RNA-seq data.

We present Beyondcell, a computational methodology for identifying tumour cell subpopulations with distinct drug responses in single-cell RNA-seq data and proposing cancer-specific treatments. Our method calculates an enrichment score in a collection of drug signatures, delineating therapeutic clusters (TCs) within cellular populations. Additionally, Beyondcell determines the therapeutic differences among cell populations and generates a prioritised sensitivity-based ranking in order to guide drug selection. We performed Beyondcell analysis in five single-cell datasets and demonstrated that TCs can be exploited to target malignant cells both in cancer cell lines and tumour patients. Beyondcell is available at: https://gitlab.com/bu_cnio/beyondcell .

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.

Spleen plays a major role in DLL4-driven acute T-cell lymphoblastic leukemia.

The Notch pathway is highly active in almost all patients with T-cell acute lymphoblastic leukemia (T-ALL), but the implication of Notch ligands in T-ALL remains underexplored. Methods: We used a genetic mouse model of Notch ligand delta like 4 (DLL4)-driven T-ALL and performed thymectomies and splenectomies in those animals. We also used several patient-derived T-ALL (PDTALL) models, including one with DLL4 expression on the membrane and we treated PDTALL cells in vitro and in vivo with demcizumab, a blocking antibody against human DLL4 currently being tested in clinical trials in patients with solid cancer. Results: We show that surgical removal of the spleen abrogated T-ALL development in our preclinical DLL4-driven T-ALL mouse model. Mechanistically, we found that the spleen, and not the thymus, promoted the accumulation of circulating CD4+CD8+ T cells before T-ALL onset, suggesting that DLL4-driven T-ALL derives from these cells. Then, we identified a small subset of T-ALL patients showing higher levels of DLL4 expression. Moreover, in mice xenografted with a DLL4-positive PDTALL model, treatment with demcizumab had the same therapeutic effect as global Notch pathway inhibition using the potent γ-secretase inhibitor dibenzazepine. This result demonstrates that, in this PDTALL model, Notch pathway activity depends on DLL4 signaling, thus validating our preclinical mouse model. Conclusion: DLL4 expression in human leukemic cells can be a source of Notch activity in T-ALL, and the spleen plays a major role in a genetic mouse model of DLL4-driven T-ALL.

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.

Global hyperactivation of enhancers stabilizes human and mouse naive pluripotency through inhibition of CDK8/19 Mediator kinases.

Pluripotent stem cells (PSCs) transition between cell states in vitro, reflecting developmental changes in the early embryo. PSCs can be stabilized in the naive state by blocking extracellular differentiation stimuli, particularly FGF-MEK signalling. Here, we report that multiple features of the naive state in human and mouse PSCs can be recapitulated without affecting FGF-MEK signalling or global DNA methylation. Mechanistically, chemical inhibition of CDK8 and CDK19 (hereafter CDK8/19) kinases removes their ability to repress the Mediator complex at enhancers. CDK8/19 inhibition therefore increases Mediator-driven recruitment of RNA polymerase II (RNA Pol II) to promoters and enhancers. This efficiently stabilizes the naive transcriptional program and confers resistance to enhancer perturbation by BRD4 inhibition. Moreover, naive pluripotency during embryonic development coincides with a reduction in CDK8/19. We conclude that global hyperactivation of enhancers drives naive pluripotency, and this can be achieved in vitro by inhibiting CDK8/19 kinase activity. These principles may apply to other contexts of cellular plasticity.

Tumor regression and resistance mechanisms upon CDK4 and RAF1 inactivation in KRAS/P53 mutant lung adenocarcinomas.

KRAS mutant lung adenocarcinomas remain intractable for targeted therapies. Genetic interrogation of KRAS downstream effectors, including the MAPK pathway and the interphase CDKs, identified CDK4 and RAF1 as the only targets whose genetic inactivation induces therapeutic responses without causing unacceptable toxicities. Concomitant CDK4 inactivation and RAF1 ablation prevented tumor progression and induced complete regression in 25% of KRAS/p53-driven advanced lung tumors, yet a significant percentage of those tumors that underwent partial regression retained a population of CDK4/RAF1-resistant cells. Characterization of these cells revealed two independent resistance mechanisms implicating hypermethylation of several tumor suppressors and increased PI3K activity. Importantly, these CDK4/RAF1-resistant cells can be pharmacologically controlled. These studies open the door to new therapeutic strategies to treat KRAS mutant lung cancer, including resistant tumors.

TGF-ß-induced IGFBP-3 is a key paracrine factor from activated pericytes that promotes colorectal cancer cell migration and invasion.

The crosstalk between cancer cells and the tumor microenvironment has been implicated in cancer progression and metastasis. Fibroblasts and immune cells are widely known to be attracted to and modified by cancer cells. However, the role of pericytes in the tumor microenvironment beyond endothelium stabilization is poorly understood. Here, we report that pericytes promoted colorectal cancer (CRC) cell proliferation, migration, invasion, stemness, and chemoresistance in vitro, as well as tumor growth in a xenograft CRC model. We demonstrate that coculture with human CRC cells induced broad transcriptomic changes in pericytes, mostly associated with TGF-ß receptor activation. The prognostic value of a TGF-ß response signature in pericytes was analyzed in CRC patient data sets. This signature was found to be a good predictor of CRC relapse. Moreover, in response to stimulation by CRC cells, pericytes expressed high levels of TGF-ß1, initiating an autocrine activation loop. Investigation of secreted mediators and underlying molecular mechanisms revealed that IGFBP-3 is a key paracrine factor from activated pericytes affecting CRC cell migration and invasion. In summary, we demonstrate that the interplay between pericytes and CRC cells triggers a vicious cycle that stimulates pericyte cytokine secretion, in turn increasing CRC cell tumorigenic properties. Overall, we provide another example of how cancer cells can manipulate the tumor microenvironment.

The Hippo Pathway Transducers YAP1/TEAD Induce Acquired Resistance to Trastuzumab in HER2-Positive Breast Cancer.

Trastuzumab is the first-line targeted therapeutic drug for HER2-positive breast cancer, leading to improved overall survival. However, acquired resistance inevitably occurs. We aimed to identify, quantify, and assess the mechanisms of acquired resistance to trastuzumab. We established an acquired trastuzumab-resistant model in vitro from BT-474, a trastuzumab-sensitive, HER2-amplified breast-cancer cell line. A multi-omic strategy was implemented to obtain gene, proteome, and phosphoproteome signatures associated with acquired resistance to trastuzumab in HER2-positive breast cancer, followed by validation in human clinical samples. YAP1 dephosphorylation and TEAD2 overexpression were detected as significant alterations in the Hippo pathway in trastuzumab-resistant breast cancer. Because of the emerging role of these proteins as mediators of normal growth and tumorigenesis, we assessed the exogenous modulation of their activity, either by in vitro gene silencing or by pharmacological inhibition of the YAP1/TEAD complexes, both in vitro and in vivo. Moreover, we identified increased signaling through the Hippo pathway in human samples after progression following trastuzumab treatment. Finally, YAP1/TAZ nuclear accumulation in malignant cells in HER2 breast tumor was significantly associated with worse progression-free and overall survival in metastatic HER2-positive breast-cancer patients. Our results suggest the involvement of Hippo signaling in acquired trastuzumab resistance in breast cancer. Additionally, we provide novel evidence for a potential breast-cancer treatment strategy based on dual targeting of HER2 and Hippo pathway effectors, which may improve the antitumor activity of trastuzumab and help overcome resistance.

Autocrine CCL5 Effect Mediates Trastuzumab Resistance by ERK Pathway Activation in HER2-Positive Breast Cancer.

HER2-positive breast cancer is currently managed with chemotherapy in combination with specific anti-HER2 therapies, including trastuzumab. However, a high percentage of patients with HER2-positive tumors do not respond to trastuzumab (primary resistance) or either recur (acquired resistance), mostly due to molecular alterations in the tumor that are either unknown or undetermined in clinical practice. Those alterations may cause the tumor to be refractory to treatment with trastuzumab, promoting tumor proliferation and metastasis. Using continued exposure of a HER2-positive cell line to trastuzumab, we generated a model of acquired resistance characterized by increased expression of several cytokines. Differential gene expression analysis indicated an overexpression of 15 genes, including five different chemokines, and highlighting CCL5/RANTES as the most overexpressed one. Functional studies, either by in vitro gene silencing or by in vitro and in vivo pharmacologic inhibition of the CCL5/CCR5 interaction with maraviroc, confirmed that CCL5 overexpression was implicated in acquired resistance to trastuzumab, which was mediated by ERK activation. In patient samples, increased CCL5 expression significantly correlated with lower rates of complete response after neoadjuvant therapy, confirmed by detection of high serum CCL5 levels by ELISA. Overexpression of CCL5 correlated with ERK phosphorylation in tumor cells and was statistically associated with worse disease-free survival and overall cancer survival in patients with early HER2-positive breast cancer.

MEK inhibition enhances the response to tyrosine kinase inhibitors in acute myeloid leukemia.

FMS-like tyrosine kinase 3 (FLT3) is a key driver of acute myeloid leukemia (AML). Several tyrosine kinase inhibitors (TKIs) targeting FLT3 have been evaluated clinically, but their effects are limited when used in monotherapy due to the emergence of drug-resistance. Thus, a better understanding of drug-resistance pathways could be a good strategy to explore and evaluate new combinational therapies for AML. Here, we used phosphoproteomics to identify differentially-phosphorylated proteins in patients with AML and TKI resistance. We then studied resistance mechanisms in vitro and evaluated the efficacy and safety of rational combinational therapy in vitro, ex vivo and in vivo in mice. Proteomic and immunohistochemical studies showed the sustained activation of ERK1/2 in bone marrow samples of patients with AML after developing resistance to FLT3 inhibitors, which was identified as a common resistance pathway. We examined the concomitant inhibition of MEK-ERK1/2 and FLT3 as a strategy to overcome drug-resistance, finding that the MEK inhibitor trametinib remained potent in TKI-resistant cells and exerted strong synergy when combined with the TKI midostaurin in cells with mutated and wild-type FLT3. Importantly, this combination was not toxic to CD34+ cells from healthy donors, but produced survival improvements in vivo when compared with single therapy groups. Thus, our data point to trametinib plus midostaurin as a potentially beneficial therapy in patients with AML.

In Silico Drug Prescription for Targeting Cancer Patient Heterogeneity and Prediction of Clinical Outcome.

In silico drug prescription tools for precision cancer medicine can match molecular alterations with tailored candidate treatments. These methodologies require large and well-annotated datasets to systematically evaluate their performance, but this is currently constrained by the lack of complete patient clinicopathological data. Moreover, in silico drug prescription performance could be improved by integrating additional tumour information layers like intra-tumour heterogeneity (ITH) which has been related to drug response and tumour progression. PanDrugs is an in silico drug prescription method which prioritizes anticancer drugs combining both biological and clinical evidence. We have systematically evaluated PanDrugs in the Genomic Data Commons repository (GDC). Our results showed that PanDrugs is able to establish an a priori stratification of cancer patients treated with Epidermal Growth Factor Receptor (EGFR) inhibitors. Patients labelled as responders according to PanDrugs predictions showed a significantly increased overall survival (OS) compared to non-responders. PanDrugs was also able to suggest alternative tailored treatments for non-responder patients. Additionally, PanDrugs usefulness was assessed considering spatial and temporal ITH in cancer patients and showed that ITH can be approached therapeutically proposing drugs or combinations potentially capable of targeting the clonal diversity. In summary, this study is a proof of concept where PanDrugs predictions have been correlated to OS and can be useful to manage ITH in patients while increasing therapeutic options and demonstrating its clinical utility.

Specific Contributions of Cohesin-SA1 and Cohesin-SA2 to TADs and Polycomb Domains in Embryonic Stem Cells.

Cohesin exists in two variants carrying either STAG/SA1 or SA2. Here we have addressed their specific contributions to the unique spatial organization of the mouse embryonic stem cell genome, which ensures super-enhancer-dependent transcription of pluripotency factors and repression of lineage-specification genes within Polycomb domains. We find that cohesin-SA2 facilitates Polycomb domain compaction through Polycomb repressing complex 1 (PRC1) recruitment and promotes the establishment of long-range interaction networks between distant Polycomb-bound promoters that are important for gene repression. Cohesin-SA1, in contrast, disrupts these networks, while preserving topologically associating domain (TAD) borders. The diverse effects of both complexes on genome topology may reflect two modes of action of cohesin. One, likely involving loop extrusion, establishes overall genome arrangement in TADs together with CTCF and prevents excessive segregation of same-class compartment regions. The other is required for organization of local transcriptional hubs such as Polycomb domains and super-enhancers, which define cell identity.