Genome-wide MicroRNA profiling of mantle cell lymphoma reveal a distinct subgroup with poor prognosis

MicroRNA (miRNA) deregulation has been implicated in the pathogenesis of mantle cell lymphoma (MCL). Using a high-throughput quantitative real-time PCR platform, we performed miRNA profiling on cyclin D1- positive MCL (n=30) and cyclin D1-negative MCL (n=7) and compared them with small lymphocytic leukemia/lymphoma (SLL, n=12), aggressive B-cell lymphomas (n=138), normal B-cell subsets and stromal cells. We identified a 19-miRNA classifier which included six upregulated miRNAs (miR-135a, miR-708, miR-150, miR-363, miR-184, miR-342-5p) and 13 downregulated miRNAs, that was able to distinguish MCL from other aggressive lymphomas with \u3e90% probability. Some of these upregulated miRNAs are highly expressed in naïve B-cells. MicroRNA classifier showed consistent results in FFPE tissues and was able to distinguish cyclin D1-negative MCL from other lymphomas. A 26-miRNA classifier could distinguish MCL from SLL, dominated by 23 upregulated miRNAs in MCL. Unsupervised hierarchical clustering of MCL cases demonstrated a cluster characterized by high expression of miRNAs from polycistronic miR17~92 cluster and its paralogs miR-106a-363 and miR-106b-25, which was distinct from the other clusters showing enrichment of stroma associated miRNAs. The corresponding gene-expressionprofiling (GEP) data showed that the former cluster of MCL had significantly higher proliferation genesignature (PS), while the other subsets had higher expression of stroma associated genes. Clinical outcome analysis suggests that miRNAs can serve as prognosticators

Genome-wide miRNAprofiling of mantle cell lymphoma reveals a distinct subgroup with poor prognosis

miRNA deregulation has been implicated in the pathogenesis of mantle cell lymphoma (MCL). Using a high-throughput quantitative real-time PCR platform, we performed miRNA profiling on cyclin D1–positive MCL (n = 30) and cyclin D1–negative MCL (n =7) and compared them with small lymphocytic leukemia/ lymphoma (n =12), aggressive B-cell lymphomas (n =138), normal B-cell subsets, and stromal cells.We identified a 19-miRNA classifier that included 6 up-regulated miRNAs and 13 down regulated miRNA that was able to distinguish MCL from other aggressive lymphomas. Some of the up-regulated miRNAs are highly expressed in naive B cells. This miRNAclassifier showed consistent results in formalinfixed paraffin-embedded tissues and was able to distinguish cyclin D1–negative MCL from other lymphomas. A 26-miRNA classifier could distinguish MCL from small lymphocytic leukemia/lymphoma, dominated by 23 up-regulated miRNAs in MCL. Unsupervised hierarchical clustering of MCL patients demonstrated a cluster characterized by high expression of miRNAs from the polycistronic miR17-92 cluster and its paralogs, miR-106a-363 and miR-106b-25, and associated with high proliferation gene signature. The other clusters showed enrichment of stroma-associated miRNAs, and also had higher expression of stroma-associated genes. Our clinical outcome analysis in the present study suggested that miRNAs can serve as prognosticators

Congenital Neutropenia with Specific Granulocyte Deficiency Caused by Novel Double Heterozygous SMARCD2 Mutations

SMARCD2 (SWI/SNF-related, matrix-associated, actin-dependent regulator of chromatin, subfamily D, member 2) is critical for myelopoiesis. Recently, bi-allelic SMARCD2 mutations have been reported in five children, causing autosomal recessive congenital neutropenia with specific granulocytes deficiency (CN-SGD); a syndrome resulting in G-CSF resistant neutropenia, recurrent infections, and dysplastic myelopoiesis. We report a new case with CN-SGD caused by two novel heterozygous pathogenic variants in the SMARCD2 gene (c.1081del (p.Gln361Argfs*15)), and (c.217C>T (p.Arg73*)). Treatment with the weekly dosing of thrombopoietin receptor agonist, Romiplostim, along with daily G-CSF transformed her clinical course, implying potential synergism. This report advances the understanding of CN-SGD caused by SMARCD2 mutations

Primary central nervous system Epstein-Barr virus-positive diffuse large B-cell lymphoma of the elderly: a clinicopathologic study of five cases.

We report five cases of primary central nervous system (CNS) Epstein-Barr virus (EBV)-positive lymphoma of the elderly. This represented an incidence of 4 % of primary CNS diffuse large B-cell lymphoma (DLBCL) after EBV screening in 134 cases. All five patients were 65 years or older with no previous history of congenital or iatrogenic immune deficiencies. The histologic morphology of all the cases was DLBCL, with variable amounts of necrosis. The cell of origin (COO) as determined by the Hans algorithm disclosed germinal center type in 2 cases and non-germinal center type in 3 cases. MYC translocation was not detected, and MYC overexpression was detected in only one case. Three patients died shortly after diagnosis, and the remaining 2 patients were in complete remission for 2 and 10 years, respectively. We conclude that EBV+ DLBCL among the elderly is uncommon in primary CNS lymphoma in the Eastern United States. The patients usually present with a single mass lesion with headache and sensorimotor symptoms. The histologic morphology is DLBCL, but clonal T-cell gene rearrangement may be detected. The outcome varies from case to case and appears to be unrelated to the COO or MYC status

MicroRNA Expression Profiling Identifies Molecular Diagnostic Signatures for Anaplastic Large Cell Lymphoma

Medicine, Research & ExperimentalPathologySCI(E)CPCI-S(ISTP)0MEETING ABSTRACT342A-342A9

Global microRNA expression profiling uncovers molecular markers for classification and prognosis in aggresive B-cell lymphoma

We studied the global microRNA (miRNA) expression in diffuse large B-cell lymphoma (DLBCL; n = 79), Burkitt lymphoma (BL; n = 36), primary mediastinal B-cell lymphoma (PMBL; n = 12), B-cell lines (n = 11), and normal subsets of naïve B cells, centroblasts (CBs), and peripheral blood B cells along with their corresponding gene expression profiles (GEPs). The normal B-cell subsets have well-defined miRNA signatures. The CB miRNA signature was significantly associated with germinal center B-cell (GCB)–DLBCL compared with activated B-cell (ABC)–DLBCL (P = .002). We identified a 27-miRNA signature that included v-myc avian myelomatosis viral oncogene homolog (MYC) targets and enabled the differentiation of BL from DLBCL, a distinction comparable with the “gold standard” GEP-defined diagnosis. Distinct miRNA signatures were identified for DLBCL subgroups, including GCB-DLBCL, activated B-cell (ABC)-DLBCL, and PMBL. Interestingly, most of the unclassifiable-DLBCL by GEP showed a strong similarity to the ABC-DLBCL by miRNA expression profiling. Consistent results for BL and DLBCL subgroup classification were observed in formalin-fixed, paraffin-embedded tissue, making such tests practical for clinical use. We also identified predictive miRNA biomarker signatures in DLBCL, including high expression of miR-155, which is significantly associated with rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) treatment failure. This finding was further supported by the observation that high expression of miR-155 sensitizes cells to v-akt murine thymoma viral oncogene homolog-1 inhibitors in vitro, suggesting a novel treatment option for resistant DLBCL

Gene Expression Signatures for the Accurate Diagnosis of Peripheral T-Cell Lymphoma Entities in the Routine Clinical Practice

Peripheral T-cell lymphoma (PTCL) includes heterogeneous clinicopathologic entities with numerous diagnostic and treatment challenges. We previously defined robust transcriptomic signatures that distinguish common PTCL entities and identified two novel biologic and prognostic PTCL-not otherwise specified subtypes (PTCL-TBX21 and PTCL-GATA3). We aimed to consolidate a gene expression-based subclassification using formalin-fixed, paraffin-embedded (FFPE) tissues to improve the accuracy and precision in PTCL diagnosis. We assembled a well-characterized PTCL training cohort (n = 105) with gene expression profiling data to derive a diagnostic signature using fresh-frozen tissue on the HG-U133plus2.0 platform (Affymetrix, Inc, Santa Clara, CA) subsequently validated using matched FFPE tissues in a digital gene expression profiling platform (nCounter, NanoString Technologies, Inc, Seattle, WA). Statistical filtering approaches were applied to refine the transcriptomic signatures and then validated in another PTCL cohort (n = 140) with rigorous pathology review and ancillary assays. In the training cohort, the refined transcriptomic classifier in FFPE tissues showed high sensitivity (> 80%), specificity (> 95%), and accuracy (> 94%) for PTCL subclassification compared with the fresh-frozen-derived diagnostic model and showed high reproducibility between three independent laboratories. In the validation cohort, the transcriptional classifier matched the pathology diagnosis rendered by three expert hematopathologists in 85% (n = 119) of the cases, showed borderline association with the molecular signatures in 6% (n = 8), and disagreed in 8% (n = 11). The classifier improved the pathology diagnosis in two cases, validated by clinical findings. Of the 11 cases with disagreements, four had a molecular classification that may provide an improvement over pathology diagnosis on the basis of overall transcriptomic and morphological features. The molecular subclassification provided a comprehensive molecular characterization of PTCL subtypes, including viral etiologic factors and translocation partners. We developed a novel transcriptomic approach for PTCL subclassification that facilitates translation into clinical practice with higher precision and uniformity than conventional pathology diagnosis

MicroRNA expression profiling identifies molecular signatures associated with anaplastic large cell lymphoma

Anaplastic large-cell lymphomas (ALCLs) encompass at least 2 systemic diseases distinguished by the presence or absence of anaplastic lymphoma kinase (ALK) expression. We performed genome-wide microRNA (miRNA) profiling on 33 ALK-positive (ALK[1]) ALCLs, 25 ALK-negative (ALK[2]) ALCLs, 9 angioimmunoblastic T-cell lymphomas, 11 peripheral T-cell lymphomas not otherwise specified (PTCLNOS), and normal T cells, and demonstrated that ALCLs express many of the miRNAs that are highly expressed in normal T cells with the prominent exception of miR-146a. Unsupervised hierarchical clustering demonstrated distinct clustering of ALCL, PTCL-NOS, and the AITL subtype of PTCL. Cases of ALK(1) ALCL and ALK(-) ALCL were interspersed in unsupervised analysis, suggesting a close relationship at the molecular level. We identified an miRNA signature of 7 miRNAs (5 upregulated: miR-512-3p, miR-886-5p, miR-886-3p, miR-708, miR-135b; 2 downregulated: miR-146a, miR-155) significantly associated with ALK(1) ALCL cases. In addition, we derived an 11-miRNA signature (4 upregulated: miR-210, miR-197, miR-191, miR-512-3p; 7 downregulated: miR-451, miR-146a, miR-22, miR-455-3p, miR-455-5p, miR-143, miR-494) that differentiates ALK(-) ALCL from other PTCLs. Our in vitro studies identified a set of 32 miRNAs associated with ALK expression. Of these, themiR-17 similar to 92 cluster and its paralogues were also highly expressed in ALK(1) ALCL and may represent important downstream effectors of the ALK oncogenic pathway.HematologySCI(E)18ARTICLE122083-209212