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Anaplastic large-cell lymphoma (ALCL) is a clinical and biological heterogeneous disease that includes systemic anaplastic lymphoma kinase (ALK)-positive and ALK-negative entities. To discover biomarkers and/or genes involved in ALK-negative ALCL pathogenesis, we applied the cancer outlier profile analysis algorithm to a gene expression profiling data set including 249 cases of T-cell non-Hodgkin lymphoma and normal T cells. Ectopic coexpression of ERBB4 and COL29A1 genes was detected in 24% of ALK-negative ALCL patients. RNA sequencing and 5' RNA ligase-mediated rapid amplification of complementary DNA ends identified 2 novel ERBB4-truncated transcripts displaying intronic transcription start sites. By luciferase assays, we defined that the expression of ERBB4-aberrant transcripts is promoted by endogenous intronic long terminal repeats. ERBB4 expression was confirmed at the protein level by western blot analysis and immunohistochemistry. Lastly, we demonstrated that ERBB4-truncated forms show oncogenic potentials and that ERBB4 pharmacologic inhibition partially controls ALCL cell growth and disease progression in an ERBB4-positive patient-derived tumorgraft model. In conclusion, we identified a new subclass of ALK-negative ALCL characterized by aberrant expression of ERBB4-truncated transcripts carrying intronic 5' untranslated regions. © 2016 by The American Society of Hematology.

Multiple myeloma (MM) is a clonal proliferation of bone marrow plasma cells characterized by highly heterogeneous genetic background and clinical course, whose pathogenesis remains largely unknown. Long ncRNAs (lncRNAs) are a large class of non-protein-coding RNA, involved in many physiological cellular and genomic processes as well as in carcinogenesis and tumor evolution. Although still in its infancy, the role of lncRNAs in MM is progressively expanding. Besides studies on selected candidates, lncRNAs expression at genome-wide transcriptome level is confined to microarray technologies, thus investigating a limited collection of transcripts. In the present study investigating a cohort of 30 MM patients, a deep RNA-sequencing analysis overwhelmed previous array studies and allowed the most accurate definition of lncRNA transcripts structure and expression, ultimately providing a comprehensive catalogue of lncRNAs specifically associated with the main MM molecular subgroups and genetic alterations. Despite the small number of analyzed samples, the high accuracy of RNA-sequencing approach for complex transcriptome processing led to the identification of 391 deregulated lncRNAs, 67% of which were also detectable and validated by whole-transcript microarrays. In addition, we identified a list of lncRNAs, with potential relevance in MM, co-expressed and in close proximity to genes that might undergo a cis-regulatory relationship.

Introduction and purposes. Multiple myeloma (MM) is a heterogeneous disease. The discovery of a class of small non-coding RNAs (miRNAs) has revealed a new level of biological complexity underlying the regulation of gene expression. It may be possible to use this interesting new biology to improve our ability to risk stratify patients in the clinic. Methods and experimental design. We performed global miRNA expression profiling analysis of 163 primary tumors included in the UK Myeloma IX clinical trial. miRNA expression profiling was carried out using Affymetrix GeneChip miRNA 2.0; expression values for 847 hsa-miRNAs were extracted using Affymetrix miRNA QC tool and RMA-normalized. There are also 153 matching samples with gene expression profiles (GEP) and 72 matching cases with genotyping data available for integrative analyses. GEP was generated on Affymetrix HG-U133 Plus 2.0 and the expression values were RMA normalized; genotyping was performed on Affymetrix GeneChip Mapping 500K Array and the copy number values were obtained using GTYPE and dChip and were inferred against normal germ-line counterpart for each sample. Results. Firstly we have defined 8 miRNAs linked to 3 Translocation Cyclin D (TC) subtypes of MM with distinct prognoses, including miR-99b/let-7e/miR-125a upregulation and miR-150/miR-155/miR-34a upregulation in unfavourable 4p16 and MAF cases respectively as well as miR-1275 upregulation and miR-138 downregulation in favourable 11q13 cases. The expression levels of the miRNA cluster miR-99b/let-7e/miR-125a at 13q13 have been shown to be associated with shorter progression free survival in our dataset. Interestingly unsupervised hierarchical clustering analysis using these 8 miRNAs identified two subclusters among 11q13 cases, which have differential effect on overall survival (OS). We then evaluated the association of miRNA expression with OS and identified 3 significantly associated miRNAs (miR-17, miR-18 and miR-886-5p) after multiple testing corrections, either per se or in concerted fashion. We went on to develop an ?outcome classifier? based on the expression of two miRNAs (miR-17 and miR-886-5p), which is able to stratify patients into three risk groups (median OS 19.4 months vs 40.6 months vs 65.3 months, log-rank test P = 0.001). The robustness of the miRNA-based classifier has been validated using 1000 bootstrap replications with an estimated error rate of 1.6%. The miRNA-stratified risk groups are independent from main adverse fluorescence in situ hybridization (FISH) abnormalities (1q gain, 17p deletion and t(4;14)), International Staging System (ISS) and Myeloma IX treatment arm (intensive or non-intensive). Using the miRNA-based classifier in the context of ISS/FISH risk stratification showed that it can significantly improve the predictive power (likelihood-ratio test P = 0.0005) and this classifier is also independent from GEP-derived prognostic signatures including UAMS, IFM and Myeloma IX 6-gene signature (P < 0.002). Integrative analyses didn't show enough evidence that the miRNAs comprising the classifier were deregulated via copy number changes; however, our data supported that the mir-17~92 cluster was activated by Myc and E2F3, highlighting the potential importance of Myc/E2F/miR-17~92 negative feedback loop in myeloma pathogenesis. We developed an approach to identify the putative targets of the OS-associated miRNAs and show that they regulate a large number of genes involved in MM biology such as proliferation, apoptosis, angiogenesis and drug resistance. Conclusion. In this study we developed a simple miRNA-based classifier to stratify patients into three risk groups, which is independent from current prognostic approaches in MM such as ISS, FISH abnormalities and GEP-derived signatures. The miRNAs comprising the classifier are biologically relevant and have been shown to regulate a large number of genes involved in MM biology. This is the first report to show that miRNAs can be built into molecular diagnostic strategies for risk stratification in MM.

Additional file 1.

Additional file 1.

© 2019 Wiley Periodicals, Inc. The histological diagnosis of peripheral T-cell lymphoma (PTCL) can represent a challenge, particularly in the case of closely related entities such as angioimmunoblastic T-lymphoma (AITL), PTCL-not otherwise specified (PTCL-NOS), and ALK-negative anaplastic large-cell lymphoma (ALCL). Although gene expression profiling and next generations sequencing have been proven to define specific features recurrently associated with distinct entities, genomic-based stratifications have not yet led to definitive diagnostic criteria and/or entered into the routine clinical practice. Herein, to improve the current molecular classification between AITL and PTCL-NOS, we analyzed the transcriptional profiles from 503 PTCLs stratified according to their molecular configuration and integrated them with genomic data of recurrently mutated genes (RHOA G17V , TET2, IDH2 R172 , and DNMT3A) in 53 cases (39 AITLs and 14 PTCL-NOSs) included in the series. Our analysis unraveled that the mutational status of RHOA G17V , TET2, and DNMT3A poorly correlated, individually, with peculiar transcriptional fingerprints. Conversely, in IDH2 R172 samples a strong transcriptional signature was identified that could act as a surrogate for mutational status. The integrated analysis of clinical, mutational, and molecular data led to a simplified 19-gene signature that retains high accuracy in differentiating the main nodal PTCL entities. The expression levels of those genes were confirmed in an independent cohort profiled by RNA-sequencing.

Primary plasma cell leukemia (pPCL) is a rare and aggressive variant of multiple myeloma (MM) which may represent a valid model for high-risk MM. This disease is associated with a very poor prognosis, and unfortunately, it has not significantly improved during the last three decades. New high-throughput technologies have allowed a better understanding of the molecular basis of this disease and moved toward risk stratification, providing insights for targeted therapy studies. This knowledge, added to the pharmacogenetic profile of new and old agents in the analysis of efficacy and safety, could contribute to help clinical decisions move toward a precision medicine and a better clinical outcome for these patients. In this review, we describe the available literature concerning the genomic characterization and pharmacogenetics of plasma cell leukemia (PCL).

In this study we investigated specific biological and clinical features associated with chronic lymphocytic leukemia (CLL) patients carrying stereotyped BCR subset #4 (IGHV4-34) among a prospective cohort of 462 CLL/MBL patients in early stage (Binet A). All subset #4 patients (n = 16) were characterized by the IGHV mutated gene configuration, and absence of unfavorable cytogenetic lesions, NOTCH1 or SF3B1 mutations. Gene and miRNA expression profiling evidenced that the leukemic cells of subset #4 cases showed significant downregulation of WDFY4, MF2A and upregulation of PDGFA, FGFR1 and TFEC gene transcripts, as well as the upregulation of miR-497 and miR-29c. The transfection of miR-497 mimic in primary leukemic CLL cells induced a downregulation of BCL2, a known validated target of this miRNA. Our data identify biological characteristics associated with subset #4 patients, providing further evidence for the putative role of BCR in shaping the features of the tumor cells in CLL.