The phospholipid transporter PITPNC1 links KRAS to MYC to prevent autophagy in lung and pancreatic cancer.

BACKGROUND: The discovery of functionally relevant KRAS effectors in lung and pancreatic ductal adenocarcinoma (LUAD and PDAC) may yield novel molecular targets or mechanisms amenable to inhibition strategies. Phospholipids availability has been appreciated as a mechanism to modulate KRAS oncogenic potential. Thus, phospholipid transporters may play a functional role in KRAS-driven oncogenesis. Here, we identified and systematically studied the phospholipid transporter PITPNC1 and its controlled network in LUAD and PDAC. METHODS: Genetic modulation of KRAS expression as well as pharmacological inhibition of canonical effectors was completed. PITPNC1 genetic depletion was performed in in vitro and in vivo LUAD and PDAC models. PITPNC1-deficient cells were RNA sequenced, and Gene Ontology and enrichment analyses were applied to the output data. Protein-based biochemical and subcellular localization assays were run to investigate PITPNC1-regulated pathways. A drug repurposing approach was used to predict surrogate PITPNC1 inhibitors that were tested in combination with KRASG12C inhibitors in 2D, 3D, and in vivo models. RESULTS: PITPNC1 was increased in human LUAD and PDAC, and associated with poor patients' survival. PITPNC1 was regulated by KRAS through MEK1/2 and JNK1/2. Functional experiments showed PITPNC1 requirement for cell proliferation, cell cycle progression and tumour growth. Furthermore, PITPNC1 overexpression enhanced lung colonization and liver metastasis. PITPNC1 regulated a transcriptional signature which highly overlapped with that of KRAS, and controlled mTOR localization via enhanced MYC protein stability to prevent autophagy. JAK2 inhibitors were predicted as putative PITPNC1 inhibitors with antiproliferative effect and their combination with KRASG12C inhibitors elicited a substantial anti-tumour effect in LUAD and PDAC. CONCLUSIONS: Our data highlight the functional and clinical relevance of PITPNC1 in LUAD and PDAC. Moreover, PITPNC1 constitutes a new mechanism linking KRAS to MYC, and controls a druggable transcriptional network for combinatorial treatments.

Genome-wide reconstitution of chromatin transactions reveals that RSC preferentially disrupts H2AZ-containing nucleosomes.

Chromatin transactions are typically studied in vivo, or in vitro using artificial chromatin lacking the epigenetic complexity of the natural material. Attempting to bridge the gap between these approaches, we established a system for isolating the yeast genome as a library of mononucleosomes harboring the natural epigenetic signature, suitable for biochemical manipulation. Combined with deep sequencing, this library was used to investigate the stability of individual nucleosomes and, as proof of principle, the nucleosome preference of the chromatin remodeling complex, RSC. This approach uncovered a distinct preference of RSC for nucleosomes derived from regions with a high density of histone variant H2AZ, and this preference is indeed markedly diminished using nucleosomes from cells lacking H2AZ. The preference for H2AZ remodeling/nucleosome ejection can also be reconstituted with recombinant nucleosome arrays. Together, our data indicate that, despite being separated from their genomic context, individual nucleosomes can retain their original identity as promoter- or transcription start site (TSS)-nucleosomes. Besides shedding new light on substrate preference of the chromatin remodeler RSC, the simple experimental system outlined here should be generally applicable to the study of chromatin transactions.

Consensus clustering applied to multi-omics disease subtyping.

BACKGROUND: Facing the diversity of omics data and the difficulty of selecting one result over all those produced by several methods, consensus strategies have the potential to reconcile multiple inputs and to produce robust results. RESULTS: Here, we introduce ClustOmics, a generic consensus clustering tool that we use in the context of cancer subtyping. ClustOmics relies on a non-relational graph database, which allows for the simultaneous integration of both multiple omics data and results from various clustering methods. This new tool conciliates input clusterings, regardless of their origin, their number, their size or their shape. ClustOmics implements an intuitive and flexible strategy, based upon the idea of evidence accumulation clustering. ClustOmics computes co-occurrences of pairs of samples in input clusters and uses this score as a similarity measure to reorganize data into consensus clusters. CONCLUSION: We applied ClustOmics to multi-omics disease subtyping on real TCGA cancer data from ten different cancer types. We showed that ClustOmics is robust to heterogeneous qualities of input partitions, smoothing and reconciling preliminary predictions into high-quality consensus clusters, both from a computational and a biological point of view. The comparison to a state-of-the-art consensus-based integration tool, COCA, further corroborated this statement. However, the main interest of ClustOmics is not to compete with other tools, but rather to make profit from their various predictions when no gold-standard metric is available to assess their significance. AVAILABILITY: The ClustOmics source code, released under MIT license, and the results obtained on TCGA cancer data are available on GitHub: https://github.com/galadrielbriere/ClustOmics .

hiCLIP reveals the in vivo atlas of mRNA secondary structures recognized by Staufen 1.

The structure of messenger RNA is important for post-transcriptional regulation, mainly because it affects binding of trans-acting factors. However, little is known about the in vivo structure of full-length mRNAs. Here we present hiCLIP, a biochemical technique for transcriptome-wide identification of RNA secondary structures interacting with RNA-binding proteins (RBPs). Using this technique to investigate RNA structures bound by Staufen 1 (STAU1) in human cells, we uncover a dominance of intra-molecular RNA duplexes, a depletion of duplexes from coding regions of highly translated mRNAs, an unexpected prevalence of long-range duplexes in 3' untranslated regions (UTRs), and a decreased incidence of single nucleotide polymorphisms in duplex-forming regions. We also discover a duplex spanning 858 nucleotides in the 3' UTR of the X-box binding protein 1 (XBP1) mRNA that regulates its cytoplasmic splicing and stability. Our study reveals the fundamental role of mRNA secondary structures in gene expression and introduces hiCLIP as a widely applicable method for discovering new, especially long-range, RNA duplexes.

Modulation of the ATM/autophagy pathway by a G-quadruplex ligand tips the balance between senescence and apoptosis in cancer cells.

G-quadruplex ligands exert their antiproliferative effects through telomere-dependent and telomere-independent mechanisms, but the inter-relationships among autophagy, cell growth arrest and cell death induced by these ligands remain largely unexplored. Here, we demonstrate that the G-quadruplex ligand 20A causes growth arrest of cancer cells in culture and in a HeLa cell xenografted mouse model. This response is associated with the induction of senescence and apoptosis. Transcriptomic analysis of 20A treated cells reveals a significant functional enrichment of biological pathways related to growth arrest, DNA damage response and the lysosomal pathway. 20A elicits global DNA damage but not telomeric damage and activates the ATM and autophagy pathways. Loss of ATM following 20A treatment inhibits both autophagy and senescence and sensitizes cells to death. Moreover, disruption of autophagy by deletion of two essential autophagy genes ATG5 and ATG7 leads to failure of CHK1 activation by 20A and subsequently increased cell death. Our results, therefore, identify the activation of ATM by 20A as a critical player in the balance between senescence and apoptosis and autophagy as one of the key mediators of such regulation. Thus, targeting the ATM/autophagy pathway might be a promising strategy to achieve the maximal anticancer effect of this compound.

Leiomyosarcomas: whole genome sequencing for a whole biology characterization.

PURPOSE OF REVIEW: Leiomyosarcoma (LMS) is among the more aggressive sarcomas and still suffers from the lack of efficient systemic treatment after, or before, surgery. During the last decades, one provider of therapeutic improvement has been the targeting of genome alterations. Efforts have thus been done to apply next-generation sequencing approaches to those tumours to decipher their oncogenesis and find out such targets. RECENT FINDINGS: Sequencing performed so far, based on exome, mostly confirmed that p53 and RB1 are the two main pathways altered in LMS oncogenesis. There are few point mutations in LMS genome, which is mainly characterized by numerous chromosomal rearrangements. Data from whole genome sequencing are now mandatory to decipher mechanisms triggering chromosomal instability and mutational process. SUMMARY: Although each LMS appears to have quite private genetic alterations leading to oncogenesis, it is likely that the altered biological pathways are relatively homogeneous within each of the LMS subgroups. Understanding this oncogenesis, thanks to integrated approaches involving whole genome and transcriptome sequencing together with functional and clinical characterizations will certainly give us the keys to relevant and effective new therapeutic approaches.

The pluripotent regulatory circuitry connecting promoters to their long-range interacting elements.

The mammalian genome harbors up to one million regulatory elements often located at great distances from their target genes. Long-range elements control genes through physical contact with promoters and can be recognized by the presence of specific histone modifications and transcription factor binding. Linking regulatory elements to specific promoters genome-wide is currently impeded by the limited resolution of high-throughput chromatin interaction assays. Here we apply a sequence capture approach to enrich Hi-C libraries for >22,000 annotated mouse promoters to identify statistically significant, long-range interactions at restriction fragment resolution, assigning long-range interacting elements to their target genes genome-wide in embryonic stem cells and fetal liver cells. The distal sites contacting active genes are enriched in active histone modifications and transcription factor occupancy, whereas inactive genes contact distal sites with repressive histone marks, demonstrating the regulatory potential of the distal elements identified. Furthermore, we find that coregulated genes cluster nonrandomly in spatial interaction networks correlated with their biological function and expression level. Interestingly, we find the strongest gene clustering in ES cells between transcription factor genes that control key developmental processes in embryogenesis. The results provide the first genome-wide catalog linking gene promoters to their long-range interacting elements and highlight the complex spatial regulatory circuitry controlling mammalian gene expression.

LedPred: an R/bioconductor package to predict regulatory sequences using support vector machines.

UNLABELLED: Supervised classification based on support vector machines (SVMs) has successfully been used for the prediction of cis-regulatory modules (CRMs). However, no integrated tool using such heterogeneous data as position-specific scoring matrices, ChIP-seq data or conservation scores is currently available. Here, we present LedPred, a flexible SVM workflow that predicts new regulatory sequences based on the annotation of known CRMs, which are associated to a large variety of feature types. LedPred is provided as an R/Bioconductor package connected to an online server to avoid installation of non-R software. Due to the heterogeneous CRM feature integration, LedPred excels at the prediction of regulatory sequences in Drosophila and mouse datasets compared with similar SVM-based software. AVAILABILITY AND IMPLEMENTATION: LedPred is available on GitHub: https://github.com/aitgon/LedPred and Bioconductor: http://bioconductor.org/packages/release/bioc/html/LedPred.html under the MIT license. CONTACT: aitor.gonzalez@univ-amu.fr SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Transcriptional and epigenetic signatures of zygotic genome activation during early Drosophila embryogenesis.

BACKGROUND: In all Metazoa, transcription is inactive during the first mitotic cycles after fertilisation. In Drosophila melanogaster, Zygotic Genome Activation (ZGA) occurs in two waves, starting respectively at mitotic cycles 8 (approximately 60 genes) and 14 (over a thousand genes). The regulatory mechanisms underlying these drastic transcriptional changes remain largely unknown. RESULTS: We developed an original gene clustering method based on discretized transition profiles, and applied it to datasets from three landmark early embryonic transcriptome studies. We identified 417 genes significantly up-regulated during ZGA. De novo motif discovery returned nine motifs over-represented in their non-coding sequences (upstream, introns, UTR), three of which correspond to previously known transcription factors: Zelda, Tramtrack and Trithorax-like (Trl). The nine discovered motifs were combined to scan ZGA-associated regions and predict about 1300 putative cis-regulatory modules. The fact that Trl is known to act as chromatin remodelling factor suggests that epigenetic regulation might play an important role in zygotic genome activation. We thus systematically compared the locations of predicted CRMs with ChIP-seq profiles for various transcription factors, 38 epigenetic marks from ModENCODE, and DNAse1 accessibility profiles. This analysis highlighted a strong and specific enrichment of predicted ZGA-associated CRMs for Zelda, CBP, Trl binding sites, as well as for histone marks associated with active enhancers (H3K4me1) and for open chromatin regions. CONCLUSION: Based on the results of our computational analyses, we suggest a temporal model explaining the onset of zygotic genome activation by the combined action of transcription factors and epigenetic signals. Although this study is mainly based on the analysis of publicly available transcriptome and ChiP-seq datasets, the resulting model suggests novel mechanisms that underly the coordinated activation of several hundreds genes at a precise time point during embryonic development.

Comprehensive Immune Profiling Unveils a Subset of Leiomyosarcoma with "Hot" Tumor Immune Microenvironment.

Purpose: To investigate the immune biomarker in Leiomyosarcoma (LMS), which is rare and recognized as an immune cold cancer showing a poor response rate (<10%) to immune checkpoint inhibitors (ICIs). However, durable response and clinical benefit to ICIs has been observed in a few cases of LMS, including, but not only, LMS with tertiary lymphoid structure (TLS) structures. Patients and methods: We used comprehensive transcriptomic profiling and a deconvolution method extracted from RNA-sequencing gene expression data in two independent LMS cohorts, the International Cancer Genome Consortium (ICGC, N = 146) and The Cancer Genome Atlas (TCGA, N = 75), to explore tumor immune microenvironment (TIME) in LMS. Results: Unsupervised clustering analysis using the previously validated two methods, 90-gene signature and Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT), identified immune hot (I-H) and immune high (I-Hi) LMS, respectively, in the ICGC cohort. Similarly, immune active groups (T-H, T-Hi) were identified in the TCGA cohort using these two methods. These immune active ("hot") clusters were significantly associated, but not completely overlapping, with several validated immune signatures such as sarcoma immune class (SIC) classification and TLS score, T cell inflamed signature (TIS) score, immune infiltration score (IIS), and macrophage score (M1/M2), with more patients identified by our clustering as potentially immune hot. Conclusions: Comprehensive immune profiling revealed a subset of LMS with a distinct active ("hot") TIME, consistently associated with several validated immune signatures in other cancers. This suggests that the methodologies that we used in this study warrant further validation and development, which can potentially help refine our current immune biomarkers to select the right LMS patients for ICIs in clinical trials.

Analysis of the Peritumoral Tissue Unveils Cellular Changes Associated with a High Risk of Recurrence.

BACKGROUND: The management of soft-tissue sarcoma (STS) relies on a multidisciplinary approach involving specialized oncological surgery combined with other adjuvant therapies to achieve optimal local disease control. Purpose and Results: Genomic and transcriptomic pseudocapsules of 20 prospective sarcomas were analyzed and revealed to be correlated with a higher risk of recurrence after surgery. CONCLUSIONS: A peritumoral environment that has been remodeled and infiltrated by M2 macrophages, and is less expressive of healthy tissue, would pose a significant risk of relapse and require more aggressive treatment strategies.

Distinct Cellular Origins and Differentiation Process Account for Distinct Oncogenic and Clinical Behaviors of Leiomyosarcomas.

In leiomyosarcoma (LMS), a very aggressive disease, a relatively transcriptionally uniform subgroup of well-differentiated tumors has been described and is associated with poor survival. The question raised how differentiation and tumor progression, two apparently antagonist processes, coexist and allow tumor malignancy. We first identified the most transcriptionally homogeneous LMS subgroup in three independent cohorts, which we named 'hLMS'. The integration of multi-omics data and functional analysis suggests that hLMS originate from vascular smooth muscle cells and show that hLMS transcriptional program reflects both modulations of smooth muscle contraction activity controlled by MYOCD/SRF regulatory network and activation of the cell cycle activity controlled by E2F/RB1 pathway. We propose that the phenotypic plasticity of vascular smooth muscle cells coupled with MYOCD/SRF pathway amplification, essential for hLMS survival, concomitant with PTEN absence and RB1 alteration, could explain how hLMS balance this uncommon interplay between differentiation and aggressiveness.

ATRX Alteration Contributes to Tumor Growth and Immune Escape in Pleomorphic Sarcomas.

Whole genome and transcriptome sequencing of a cohort of 67 leiomyosarcomas has been revealed ATRX to be one of the most frequently mutated genes in leiomyosarcomas after TP53 and RB1. While its function is well described in the alternative lengthening of telomeres mechanism, we wondered whether its alteration could have complementary effects on sarcoma oncogenesis. ATRX alteration is associated with the down-expression of genes linked to differentiation in leiomyosarcomas, and to immunity in an additional cohort of 60 poorly differentiated pleomorphic sarcomas. In vitro and in vivo models showed that ATRX down-expression increases tumor growth rate and immune escape by decreasing the immunity load of active mast cells in sarcoma tumors. These data indicate that an alternative to unsuccessful targeting of the adaptive immune system in sarcoma could target the innate system. This might lead to a better outcome for sarcoma patients in terms of ATRX status.

Triarylpyridine Compounds and Chloroquine Act in Concert to Trigger Lysosomal Membrane Permeabilization and Cell Death in Cancer Cells.

Lysosomes play a key role in regulating cell death in response to cancer therapies, yet little is known on the possible role of lysosomes in the therapeutic efficacy of G-quadruplex DNA ligands (G4L) in cancer cells. Here, we investigate the relationship between the modulation of lysosomal membrane damage and the degree to which cancer cells respond to the cytotoxic effects of G-quadruplex ligands belonging to the triarylpyridine family. Our results reveal that the lead compound of this family, 20A promotes the enlargement of the lysosome compartment as well as the induction of lysosome-relevant mRNAs. Interestingly, the combination of 20A and chloroquine (an inhibitor of lysosomal functions) led to a significant induction of lysosomal membrane permeabilization coupled to massive cell death. Similar effects were observed when chloroquine was added to three new triarylpyridine derivatives. Our findings thus uncover the lysosomal effects of triarylpyridines compounds and delineate a rationale for combining these compounds with chloroquine to increase their anticancer effects.

Inhibition of DDR1 enhances in vivo chemosensitivity in KRAS-mutant lung adenocarcinoma.

Platinum-based chemotherapy in combination with immune-checkpoint inhibitors is the current standard of care for patients with advanced lung adenocarcinoma (LUAD). However, tumor progression evolves in most cases. Therefore, predictive biomarkers are needed for better patient stratification and for the identification of new therapeutic strategies, including enhancing the efficacy of chemotoxic agents. Here, we hypothesized that discoidin domain receptor 1 (DDR1) may be both a predictive factor for chemoresistance in patients with LUAD and a potential target positively selected in resistant cells. By using biopsies from patients with LUAD, KRAS-mutant LUAD cell lines, and in vivo genetically engineered KRAS-driven mouse models, we evaluated the role of DDR1 in the context of chemotherapy treatment. We found that DDR1 is upregulated during chemotherapy both in vitro and in vivo. Moreover, analysis of a cohort of patients with LUAD suggested that high DDR1 levels in pretreatment biopsies correlated with poor response to chemotherapy. Additionally, we showed that combining DDR1 inhibition with chemotherapy prompted a synergistic therapeutic effect and enhanced cell death of KRAS-mutant tumors in vivo. Collectively, this study suggests a potential role for DDR1 as both a predictive and prognostic biomarker, potentially improving the chemotherapy response of patients with LUAD.

Deciphering the complex role of thrombospondin-1 in glioblastoma development.

We undertook a systematic study focused on the matricellular protein Thrombospondin-1 (THBS1) to uncover molecular mechanisms underlying the role of THBS1 in glioblastoma (GBM) development. THBS1 was found to be increased with glioma grades. Mechanistically, we show that the TGFß canonical pathway transcriptionally regulates THBS1, through SMAD3 binding to the THBS1 gene promoter. THBS1 silencing inhibits tumour cell invasion and growth, alone and in combination with anti-angiogenic therapy. Specific inhibition of the THBS1/CD47 interaction using an antagonist peptide decreases cell invasion. This is confirmed by CD47 knock-down experiments. RNA sequencing of patient-derived xenograft tissue from laser capture micro-dissected peripheral and central tumour areas demonstrates that THBS1 is one of the gene with the highest connectivity at the tumour borders. All in all, these data show that TGFß1 induces THBS1 expression via Smad3 which contributes to the invasive behaviour during GBM expansion. Furthermore, tumour cell-bound CD47 is implicated in this process.

A putative role for Discoidin Domain Receptor 1 in cancer chemoresistance.

The Discoidin Domain Receptor 1 (DDR1) receptor tyrosine kinase performs pleiotropic functions in the control of cell adhesion, proliferation, survival, migration, and invasion. Aberrant DDR1 function as a consequence of either mutations or increased expression has been associated with various human diseases including cancer. Pharmacological inhibition of DDR1 results in significant therapeutic benefit in several pre-clinical cancer models. Here, we discuss the potential implication of DDR1-dependent pro-survival functions in the development of cancer resistance to chemotherapeutic regimens and speculate on the molecular mechanisms that might mediate such important feature.

Divergent wiring of repressive and active chromatin interactions between mouse embryonic and trophoblast lineages.

The establishment of the embryonic and trophoblast lineages is a developmental decision underpinned by dramatic differences in the epigenetic landscape of the two compartments. However, it remains unknown how epigenetic information and transcription factor networks map to the 3D arrangement of the genome, which in turn may mediate transcriptional divergence between the two cell lineages. Here, we perform promoter capture Hi-C experiments in mouse trophoblast (TSC) and embryonic (ESC) stem cells to understand how chromatin conformation relates to cell-specific transcriptional programmes. We find that key TSC genes that are kept repressed in ESCs exhibit interactions between H3K27me3-marked regions in ESCs that depend on Polycomb repressive complex 1. Interactions that are prominent in TSCs are enriched for enhancer-gene contacts involving key TSC transcription factors, as well as TET1, which helps to maintain the expression of TSC-relevant genes. Our work shows that the first developmental cell fate decision results in distinct chromatin conformation patterns establishing lineage-specific contexts involving both repressive and active interactions.

GOTHiC, a probabilistic model to resolve complex biases and to identify real interactions in Hi-C data.

Hi-C is one of the main methods for investigating spatial co-localisation of DNA in the nucleus. However, the raw sequencing data obtained from Hi-C experiments suffer from large biases and spurious contacts, making it difficult to identify true interactions. Existing methods use complex models to account for biases and do not provide a significance threshold for detecting interactions. Here we introduce a simple binomial probabilistic model that resolves complex biases and distinguishes between true and false interactions. The model corrects biases of known and unknown origin and yields a p-value for each interaction, providing a reliable threshold based on significance. We demonstrate this experimentally by testing the method against a random ligation dataset. Our method outperforms previous methods and provides a statistical framework for further data analysis, such as comparisons of Hi-C interactions between different conditions. GOTHiC is available as a BioConductor package (http://www.bioconductor.org/packages/release/bioc/html/GOTHiC.html).