Identification of putative pathogenic microRNA and its downstream targets in anaplastic lymphoma kinase–negative anaplastic large cell lymphoma

CD147 a direct target of miR-146a supports energy metabolism and promotes tumor growth in ALK+ ALCL

We recently reported that miR-146a is differentially expressed in ALK+ and ALK− anaplastic large cell lymphoma (ALCL). In this study, the downstream targets of miR-146a in ALK+ ALCL were investigated by transcriptome analysis, identifying CD147 as potential target gene. Because CD147 is differentially expressed in ALK+ ALCL versus ALK− ALCL and normal T cells, this gene emerged as a strong candidate for the pathogenesis of this tumor. Here we demonstrate that CD147 is a direct target of miR-146 and contributes to the survival and proliferation of ALK+ ALCL cells in vitro and to the engraftment and tumor growth in vivo in an ALK+ ALCL-xenotransplant mouse model. CD147 knockdown in ALK+ ALCL cells resulted in loss of monocarboxylate transporter 1 (MCT1) expression, reduced glucose consumption and tumor growth retardation, as demonstrated by [¹⁸F]FDG-PET/MRI analysis. Investigation of metabolism in vitro and in vivo supported these findings, revealing reduced aerobic glycolysis and increased basal respiration in CD147 knockdown. In conclusion, our findings indicate that CD147 is of vital importance for ALK+ ALCL to maintain the high energy demand of rapid cell proliferation, promoting lactate export, and tumor growth. Furthermore, CD147 has the potential to serve as a novel therapeutic target in ALK+ ALCL, and warrants further investigation.

Robust prognostic model based on immune infiltration-related genes and clinical information in ovarian cancer

Immune infiltration of ovarian cancer (OV) is a critical factor in determining patient's prognosis. Using data from TCGA and GTEx database combined with WGCNA and ESTIMATE methods, 46 genes related to OV occurrence and immune infiltration were identified. Lasso and multivariate Cox regression were applied to define a prognostic score (IGCI score) based on 3 immune genes and 3 types of clinical information. The IGCI score has been verified by K‐M curves, ROC curves and C‐index on test set. In test set, IGCI score (C‐index = 0.630) is significantly better than AJCC stage (C‐index = 0.541, p < 0.05) and CIN25 (C‐index = 0.571, p < 0.05). In addition, we identified key mutations to analyse prognosis of patients and the process related to immunity. Chi‐squared tests revealed that 6 mutations are significantly (p < 0.05) related to immune infiltration: BRCA1, ZNF462, VWF, RBAK, RB1 and ADGRV1. According to mutation survival analysis, we found 5 key mutations significantly related to patient prognosis (p < 0.05): CSMD3, FLG2, HMCN1, TOP2A and TRRAP. RB1 and CSMD3 mutations had small p‐value (p < 0.1) in both chi‐squared tests and survival analysis. The drug sensitivity analysis of key mutation showed when RB1 mutation occurs, the efficacy of six anti‐tumour drugs has changed significantly (p < 0.05).

Diagnosis and treatment of lymphomas in the era of epigenetics

Lymphomas represent a heterogeneous group of cancers characterized by clonal lymphoproliferation. Over the past decades, frequent epigenetic dysregulations have been identified in hematologic malignancies including lymphomas. Many of these impairments occur in genes with established roles and well-known functions in the regulation and maintenance of the epigenome. In hematopoietic cells, these dysfunctions can result in abnormal DNA methylation, erroneous chromatin state and/or altered miRNA expression, affecting many different cellular functions. Nowadays, it is evident that epigenetic dysregulations in lymphoid neoplasms are mainly caused by genetic alterations in genes encoding for enzymes responsible for histone or chromatin modifications. We summarize herein the recent epigenetic modifiers findings in lymphomas. We focus also on the most commonly mutated epigenetic regulators and emphasize on actual epigenetic therapies.

LOTUS: A single- and multitask machine learning algorithm for the prediction of cancer driver genes

Cancer driver genes, i.e., oncogenes and tumor suppressor genes, are involved in the acquisition of important functions in tumors, providing a selective growth advantage, allowing uncontrolled proliferation and avoiding apoptosis. It is therefore important to identify these driver genes, both for the fundamental understanding of cancer and to help finding new therapeutic targets or biomarkers. Although the most frequently mutated driver genes have been identified, it is believed that many more remain to be discovered, particularly for driver genes specific to some cancer types. In this paper, we propose a new computational method called LOTUS to predict new driver genes. LOTUS is a machine-learning based approach which allows to integrate various types of data in a versatile manner, including information about gene mutations and protein-protein interactions. In addition, LOTUS can predict cancer driver genes in a pan-cancer setting as well as for specific cancer types, using a multitask learning strategy to share information across cancer types. We empirically show that LOTUS outperforms five other state-of-the-art driver gene prediction methods, both in terms of intrinsic consistency and prediction accuracy, and provide predictions of new cancer genes across many cancer types.

Cancer development is driven by mutations and dysfunction of important, so-called cancer driver genes, that could be targeted by specific therapies. While a number of such cancer genes have already been identified, it is believed that many more remain to be discovered. To help prioritize experimental investigations of candidate genes, several computational methods have been proposed to rank promising candidates based on their mutations in large cohorts of cancer cases, or on their interactions with known driver genes in biological networks. We propose LOTUS, a new computational approach to identify genes with high oncogenic potential. LOTUS implements a machine learning approach to learn an oncogenic potential score from known driver genes, and brings two novelties compared to existing methods. First, it allows to easily combine heterogeneous sources of information into the scoring function, which we illustrate by learning a scoring function from both known mutations in large cancer cohorts and interactions in biological networks. Second, using a multitask learning strategy, it can predict different driver genes for different cancer types, while sharing information between them to improve the prediction for every type. We provide experimental results showing that LOTUS significantly outperforms several state-of-the-art cancer gene prediction software.

Crosstalk between microRNA and DNA Methylation Offers Potential Biomarkers and Targeted Therapies in ALK-Positive Lymphomas

The discovery of microRNA (miRNA) has provided new and powerful tools for studying the mechanism, diagnosis and treatment of human cancers. The down-regulation of tumor suppressive miRNA by hypermethylation of CpG island (CpG is shorthand for 5′-C-phosphate-G-3′, that is, cytosine and guanine separated by only one phosphate) is emerging as a common hallmark of cancer and appears to be involved in drug resistance. This review discusses the role of miRNA and DNA methylation in drug resistance mechanisms and highlights their potential as anti-cancer therapies in Anaplastic Lymphoma Kinase (ALK)-positive lymphomas. These are a sub-type of non-Hodgkin’s lymphomas that predominantly affect children and young adults and are characterized by the expression of the nucleophosmin (NPM)/ALK chimeric oncoprotein. Dysregulation of miRNA expression and regulation has been shown to affect several signaling pathways in ALK carcinogenesis and control tumor growth, both in cell lines and mouse models. These data suggest that the modulation of DNA methylation and/or the expression of these miRNA could serve as new biomarkers and have potential therapeutic applications for ALK-positive malignancies.

Diagnostic and predictive biomarkers for lymphoma diagnosis and treatment in the era of precision medicine

Lymphomas are a group of hematological malignancies derived from lymphocytes. Lymphomas are clinically and biologically heterogeneous and have overlapping diagnostic features. With the advance of new technologies and the application of efficient and feasible detection platforms, an unprecedented number of novel biomarkers have been discovered or are under investigation at the genetic, epigenetic, and protein level as well as the tumor microenvironment. These biomarkers have enabled new clinical and pathological insights into the mechanisms underlying lymphomagenesis and also have facilitated improvements in the diagnostic workup, sub-classification, outcome stratification, and personalized therapy for lymphoma patients. However, integrating these biomarkers into clinical practice effectively and precisely in daily practice is challenging. More in-depth studies are required to further validate these novel biomarkers and to assess other parameters that can affect the reproducibility of these biomarkers such as the selection of detection methods, biological reagents, interpretation of data, and cost efficiency. Despite these challenges, there are many reasons to be optimistic that novel biomarkers will facilitate better algorithms and strategies as we enter a new era of precision medicine to better refine diagnosis, prognostication, and rational treatment design for patients with lymphomas.

Molecular Pathogenesis of Peripheral T Cell Lymphoma

Understanding the molecular pathogenesis of peripheral T cell lymphomas (PTCLs) has lagged behind that of B cell lymphomas due to disease rarity. However, novel approaches are gradually clarifying these mechanisms, and gene profiling has identified specific signaling pathways governing PTCL cell survival and growth. For example, genetic alterations have been discovered, including signal transducer and activator of transcription (STAT)3 and STAT5b mutations in several PTCLs, disease-specific ras homolog family member A (RHOA) mutations in angioimmunoblastic T cell lymphoma (AITL), and recurrent translocations at the dual specificity phosphatase 22 (DUSP22) locus in anaplastic lymphoma receptor tyrosine kinase (ALK)-negative anaplastic large cell lymphomas (ALCLs). Intriguingly, some PTCL-relevant mutations are seen in apparently normal blood cells as well as tumor cells, while others are confined to tumor cells. These data have dramatically changed our understanding of PTCL origins: once considered to originate from mature T lymphocytes, some PTCLs are now believed to emerge from immature hematopoietic progenitor cells.

The stress protein TP53INP1 plays a tumor suppressive role by regulating metabolic homeostasis

In the recent years, we have provided evidence that Tumor Protein 53-Induced Nuclear Protein 1 (TP53INP1) is a key stress protein with antioxidant-associated tumor suppressive function. The TP53INP1 gene, which is highly conserved in mammals, is over-expressed during stress responses including inflammation. This gene encodes two protein isoforms with nuclear or cytoplasmic subcellular localization depending on the context. TP53INP1 contributes to stress responses, thus preventing stress-induced dysfunctions leading to pathologies such as cancer. Two major mechanisms by which TP53INP1 functions have been unveiled. First, in the nucleus, TP53INP1 was shown to regulate the transcriptional activity of p53 and p73 by direct interaction, and to mediate the antioxidant activity of p53. Second, independently of p53, TP53INP1 contributes to autophagy and more particularly mitophagy through direct interaction with molecular actors of autophagy. TP53INP1 is thus required for the homeostasis of the mitochondrial compartment, and is therefore involved in the regulation of energetic metabolism. Finally, the antioxidant function of TP53INP1 stems from the control of mitochondrial reactive oxygen species production. In conclusion, TP53INP1 is a multifaceted protein endowed with multiple functions, including metabolic regulation, as is its main functional partner p53.

Genetics of anaplastic large cell lymphoma

Anaplastic large cell lymphoma (ALCL) comprises a group of T-cell non-Hodgkin lymphomas unified by common morphologic and immunophenotypic characteristics, but with a spectrum of clinical presentations and behaviors. Early identification of anaplastic lymphoma kinase (ALK) gene rearrangements in some ALCLs led to recognition of ALK as an important diagnostic and prognostic biomarker, and a key driver of ALCL pathobiology. Rearrangements and other genetic abnormalities of ALK subsequently were identified in diverse other human malignancies. Recent clinical, pathologic, and genetic data have begun to shed light on ALK-negative ALCLs, revealing significant heterogeneity within this more ill-defined entity.

Oncogenic role of miR-155 in anaplastic large cell lymphoma lacking the t(2;5) translocation

Anaplastic large cell lymphoma (ALCL) is a rare, aggressive, non-Hodgkin's lymphoma that is characterized by CD30 expression and disease onset in young patients. About half of ALCL patients bear the t(2;5)(p23;q35) translocation, which results in the formation of the nucleophosmin-anaplastic lymphoma tyrosine kinase (NPM–ALK) fusion protein (ALCL ALK⁺). However, little is known about the molecular features and tumour drivers in ALK-negative ALCL (ALCL ALK⁻), which is characterized by a worse prognosis. We found that ALCL ALK⁻, in contrast to ALCL ALK⁺, lymphomas display high miR-155 expression. Consistent with this, we observed an inverse correlation between miR-155 promoter methylation and miR-155 expression in ALCL. However, no direct effect of the ALK kinase on miR-155 levels was observed. Ago2 immunoprecipitation revealed miR-155 as the most abundant miRNA, and enrichment of target mRNAs C/EBPβ and SOCS1. To investigate its function, we over-expressed miR-155 in ALCL ALK⁺ cell lines and demonstrated reduced levels of C/EBPβ and SOCS1. In murine engraftment models of ALCL ALK⁻, we showed that anti-miR-155 mimics are able to reduce tumour growth. This goes hand-in-hand with increased levels of cleaved caspase-3 and high SOCS1 in these tumours, which leads to suppression of STAT3 signalling. Moreover, miR-155 induces IL-22 expression and suppresses the C/EBPβ target IL-8. These data suggest that miR-155 can act as a tumour driver in ALCL ALK⁻ and blocking miR-155 could be therapeutically relevant. Original miRNA array data are to be found in the supplementary material (Table S1). © 2015 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Advances in understanding the pathogenesis of systemic anaplastic large cell lymphomas

The currently used 2008 World Health Organization classification recognizes two types of systemic anaplastic large T cell lymphoma according to ALK protein expression in tumour cells. First, the 'anaplastic large cell lymphoma, ALK positive' (ALK(+) ALCL) that is characterized by the presence of ALK gene rearrangements and consequent ALK protein expression, and, second, the 'anaplastic large cell lymphoma, ALK negative' (ALK(-) ALCL) that is a provisional entity lacking ALK protein expression but cannot be distinguished morphologically from ALK(+) ALCL. In this review we summarize the current knowledge on the genetic lesions and biological features that underlie the pathogenesis of ALK(+) and the ALK(-) ALCL and that can lead to the use of targeted anti-cancer agents.