72 research outputs found

    A set of microRNAs coordinately controls tumorigenesis, invasion, and metastasis.

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    MicroRNA-mediated gene regulation has been implicated in various diseases, including cancer. This study examined the role of microRNAs (miRNAs) during tumorigenesis and malignant progression of pancreatic neuroendocrine tumors (PanNETs) in a genetically engineered mouse model. Previously, a set of miRNAs was observed to be specifically up-regulated in a highly invasive and metastatic subtype of mouse and human PanNET. Using functional assays, we now implicate different miRNAs in distinct phenotypes: miR-137 stimulates tumor growth and local invasion, whereas the miR-23b cluster enables metastasis. An algorithm, Bio-miRTa, has been developed to facilitate the identification of biologically relevant miRNA target genes and applied to these miRNAs. We show that a top-ranked miR-137 candidate gene, Sorl1, has a tumor suppressor function in primary PanNETs. Among the top targets for the miR-23b cluster, Acvr1c/ALK7 has recently been described to be a metastasis suppressor, and we establish herein that it is down-regulated by the miR-23b cluster, which is crucial for its prometastatic activity. Two other miR-23b targets, Robo2 and P2ry1, also have demonstrable antimetastatic effects. Finally, we have used the Bio-miRTa algorithm in reverse to identify candidate miRNAs that might regulate activin B, the principal ligand for ALK7, identifying thereby a third family of miRNAs-miRNA-130/301-that is congruently up-regulated concomitant with down-regulation of activin B during tumorigenesis, suggestive of functional involvement in evasion of the proapoptotic barrier. Thus, dynamic up-regulation of miRNAs during multistep tumorigenesis and malignant progression serves to down-regulate distinctive suppressor mechanisms of tumor growth, invasion, and metastasis

    Pan-Cancer Landscape of Aberrant DNA Methylation across Human Tumors.

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    The discovery of cancer-associated alterations has primarily focused on genetic variants. Nonetheless, altered epigenomes contribute to deregulate transcription and promote oncogenic pathways. Here, we designed an algorithmic approach (RESET) to identify aberrant DNA methylation and associated cis-transcriptional changes across >6,000 human tumors. Tumors exhibiting mutations of chromatin remodeling factors and Wnt signaling displayed DNA methylation instability, characterized by numerous hyper- and hypo-methylated loci. Most silenced and enhanced genes coalesced in specific pathways including apoptosis, DNA repair, and cell metabolism. Cancer-germline antigens (CG) were frequently epigenomically enhanced and their expression correlated with response to anti-PD-1, but not anti-CTLA4, in skin melanoma. Finally, we demonstrated the potential of our approach to explore DNA methylation changes in pediatric tumors, which frequently lack genetic drivers and exhibit epigenomic modifications. Our results provide a pan-cancer map of aberrant DNA methylation to inform functional and therapeutic studies

    Synaptic proximity enables NMDAR signalling to promote brain metastasis.

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    Metastasis-the disseminated growth of tumours in distant organs-underlies cancer mortality. Breast-to-brain metastasis (B2BM) is a common and disruptive form of cancer and is prevalent in the aggressive basal-like subtype, but is also found at varying frequencies in all cancer subtypes. Previous studies revealed parameters of breast cancer metastasis to the brain, but its preference for this site remains an enigma. Here we show that B2BM cells co-opt a neuronal signalling pathway that was recently implicated in invasive tumour growth, involving activation by glutamate ligands of N-methyl-D-aspartate receptors (NMDARs), which is key in model systems for metastatic colonization of the brain and is associated with poor prognosis. Whereas NMDAR activation is autocrine in some primary tumour types, human and mouse B2BM cells express receptors but secrete insufficient glutamate to induce signalling, which is instead achieved by the formation of pseudo-tripartite synapses between cancer cells and glutamatergic neurons, presenting a rationale for brain metastasis.This work was principally supported by grants from the Swiss National Science Foundation and the European Research Council, and by a gift from the Biltema Foundation that was administered by the ISREC Foundation, Lausanne, Switzerland

    Evolutionary Characterization of Lung Adenocarcinoma Morphology in TRACERx

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    Lung adenocarcinomas (LUADs) display a broad histological spectrum from low-grade lepidic tumors through to mid-grade acinar and papillary and high-grade solid, cribriform and micropapillary tumors. How morphology reflects tumor evolution and disease progression is poorly understood. Whole-exome sequencing data generated from 805 primary tumor regions and 121 paired metastatic samples across 248 LUADs from the TRACERx 421 cohort, together with RNA-sequencing data from 463 primary tumor regions, were integrated with detailed whole-tumor and regional histopathological analysis. Tumors with predominantly high-grade patterns showed increased chromosomal complexity, with higher burden of loss of heterozygosity and subclonal somatic copy number alterations. Individual regions in predominantly high-grade pattern tumors exhibited higher proliferation and lower clonal diversity, potentially reflecting large recent subclonal expansions. Co-occurrence of truncal loss of chromosomes 3p and 3q was enriched in predominantly low-/mid-grade tumors, while purely undifferentiated solid-pattern tumors had a higher frequency of truncal arm or focal 3q gains and SMARCA4 gene alterations compared with mixed-pattern tumors with a solid component, suggesting distinct evolutionary trajectories. Clonal evolution analysis revealed that tumors tend to evolve toward higher-grade patterns. The presence of micropapillary pattern and \u27tumor spread through air spaces\u27 were associated with intrathoracic recurrence, in contrast to the presence of solid/cribriform patterns, necrosis and preoperative circulating tumor DNA detection, which were associated with extra-thoracic recurrence. These data provide insights into the relationship between LUAD morphology, the underlying evolutionary genomic landscape, and clinical and anatomical relapse risk

    DNA methylation cooperates with genomic alterations during non-small cell lung cancer evolution

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    Abstract Aberrant DNA methylation has been described in nearly all human cancers, yet its interplay with genomic alterations during tumor evolution is poorly understood. To explore this, we performed reduced representation bisulfite sequencing on 217 tumor and matched normal regions from 59 patients with non-small cell lung cancer from the TRACERx study to deconvolve tumor methylation. We developed two metrics for integrative evolutionary analysis with DNA and RNA sequencing data. Intratumoral methylation distance quantifies intratumor DNA methylation heterogeneity. M R /M N classifies genes based on the rate of hypermethylation at regulatory (M R ) versus nonregulatory (M N ) CpGs to identify driver genes exhibiting recurrent functional hypermethylation. We identified DNA methylation-linked dosage compensation of essential genes co-amplified with neighboring oncogenes. We propose two complementary mechanisms that converge for copy number alteration-affected chromatin to undergo the epigenetic equivalent of an allosteric activity transition. Hypermethylated driver genes under positive selection may open avenues for therapeutic stratification of patients

    Oncogenic Signaling Pathways in The Cancer Genome Atlas.

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    Genetic alterations in signaling pathways that control cell-cycle progression, apoptosis, and cell growth are common hallmarks of cancer, but the extent, mechanisms, and co-occurrence of alterations in these pathways differ between individual tumors and tumor types. Using mutations, copy-number changes, mRNA expression, gene fusions and DNA methylation in 9,125 tumors profiled by The Cancer Genome Atlas (TCGA), we analyzed the mechanisms and patterns of somatic alterations in ten canonical pathways: cell cycle, Hippo, Myc, Notch, Nrf2, PI-3-Kinase/Akt, RTK-RAS, TGFβ signaling, p53 and β-catenin/Wnt. We charted the detailed landscape of pathway alterations in 33 cancer types, stratified into 64 subtypes, and identified patterns of co-occurrence and mutual exclusivity. Eighty-nine percent of tumors had at least one driver alteration in these pathways, and 57% percent of tumors had at least one alteration potentially targetable by currently available drugs. Thirty percent of tumors had multiple targetable alterations, indicating opportunities for combination therapy

    The evolution of non-small cell lung cancer metastases in TRACERx

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    Metastatic disease is responsible for the majority of cancer-related deaths1. We report the longitudinal evolutionary analysis of 126 non-small cell lung cancer (NSCLC) tumours from 421 prospectively recruited patients in TRACERx who developed metastatic disease, compared with a control cohort of 144 non-metastatic tumours. In 25% of cases, metastases diverged early, before the last clonal sweep in the primary tumour, and early divergence was enriched for patients who were smokers at the time of initial diagnosis. Simulations suggested that early metastatic divergence more frequently occurred at smaller tumour diameters (less than 8 mm). Single-region primary tumour sampling resulted in 83% of late divergence cases being misclassified as early, highlighting the importance of extensive primary tumour sampling. Polyclonal dissemination, which was associated with extrathoracic disease recurrence, was found in 32% of cases. Primary lymph node disease contributed to metastatic relapse in less than 20% of cases, representing a hallmark of metastatic potential rather than a route to subsequent recurrences/disease progression. Metastasis-seeding subclones exhibited subclonal expansions within primary tumours, probably reflecting positive selection. Our findings highlight the importance of selection in metastatic clone evolution within untreated primary tumours, the distinction between monoclonal versus polyclonal seeding in dictating site of recurrence, the limitations of current radiological screening approaches for early diverging tumours and the need to develop strategies to target metastasis-seeding subclones before relapse

    Representation of genomic intratumor heterogeneity in multi-region non-small cell lung cancer patient-derived xenograft models

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    Patient-derived xenograft (PDX) models are widely used in cancer research. To investigate the genomic fidelity of non-small cell lung cancer PDX models, we established 48 PDX models from 22 patients enrolled in the TRACERx study. Multi-region tumor sampling increased successful PDX engraftment and most models were histologically similar to their parent tumor. Whole-exome sequencing enabled comparison of tumors and PDX models and we provide an adapted mouse reference genome for improved removal of NOD scid gamma (NSG) mouse-derived reads from sequencing data. PDX model establishment caused a genomic bottleneck, with models often representing a single tumor subclone. While distinct tumor subclones were represented in independent models from the same tumor, individual PDX models did not fully recapitulate intratumor heterogeneity. On-going genomic evolution in mice contributed modestly to the genomic distance between tumors and PDX models. Our study highlights the importance of considering primary tumor heterogeneity when using PDX models and emphasizes the benefit of comprehensive tumor sampling

    The evolution of lung cancer and impact of subclonal selection in TRACERx

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    Lung cancer is the leading cause of cancer-associated mortality worldwide1. Here we analysed 1,644 tumour regions sampled at surgery or during follow-up from the first 421 patients with non-small cell lung cancer prospectively enrolled into the TRACERx study. This project aims to decipher lung cancer evolution and address the primary study endpoint: determining the relationship between intratumour heterogeneity and clinical outcome. In lung adenocarcinoma, mutations in 22 out of 40 common cancer genes were under significant subclonal selection, including classical tumour initiators such as TP53 and KRAS. We defined evolutionary dependencies between drivers, mutational processes and whole genome doubling (WGD) events. Despite patients having a history of smoking, 8% of lung adenocarcinomas lacked evidence of tobacco-induced mutagenesis. These tumours also had similar detection rates for EGFR mutations and for RET, ROS1, ALK and MET oncogenic isoforms compared with tumours in never-smokers, which suggests that they have a similar aetiology and pathogenesis. Large subclonal expansions were associated with positive subclonal selection. Patients with tumours harbouring recent subclonal expansions, on the terminus of a phylogenetic branch, had significantly shorter disease-free survival. Subclonal WGD was detected in 19% of tumours, and 10% of tumours harboured multiple subclonal WGDs in parallel. Subclonal, but not truncal, WGD was associated with shorter disease-free survival. Copy number heterogeneity was associated with extrathoracic relapse within 1 year after surgery. These data demonstrate the importance of clonal expansion, WGD and copy number instability in determining the timing and patterns of relapse in non-small cell lung cancer and provide a comprehensive clinical cancer evolutionary data resource

    Prospective validation of ORACLE, a clonal expression biomarker associated with survival of patients with lung adenocarcinoma

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    Human tumors are diverse in their natural history and response to treatment, which in part results from genetic and transcriptomic heterogeneity. In clinical practice, single-site needle biopsies are used to sample this diversity, but cancer biomarkers may be confounded by spatiogenomic heterogeneity within individual tumors. Here we investigate clonally expressed genes as a solution to the sampling bias problem by analyzing multiregion whole-exome and RNA sequencing data for 450 tumor regions from 184 patients with lung adenocarcinoma in the TRACERx study. We prospectively validate the survival association of a clonal expression biomarker, Outcome Risk Associated Clonal Lung Expression (ORACLE), in combination with clinicopathological risk factors, and in stage I disease. We expand our mechanistic understanding, discovering that clonal transcriptional signals are detectable before tissue invasion, act as a molecular fingerprint for lethal metastatic clones and predict chemotherapy sensitivity. Lastly, we find that ORACLE summarizes the prognostic information encoded by genetic evolutionary measures, including chromosomal instability, as a concise 23-transcript assay
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