Immunohistochemistry for identification of CCND1, NSD2, and MAF gene rearrangements in plasma cell myeloma

RNASeq Analysis for Accurate Identification of Fusion Partners in Tumor Specific Translocations Detected by Standard FISH Probes in Hematologic Malignancies

Background

Fluorescence labeled DNA probes and in situ hybridization methods had shorter turn round time for results revolutionized their clinical application. Signals obtained from these probes are highly specific, yet they can produce fusion signals not necessarily representing fusion of actual genes due to other genes included in the probe design. In this study we evaluated discordance between cytogenetic, FISH and RNAseq results in 3 different patients with hematologic malignancies and illustrated the need to perform next generation sequencing (NGS) or RNASeq to accurately interpret FISH results.

Methods

Bone marrow or peripheral blood karyotypes and FISH were performed to detect recurring translocations associated with hematologic malignancies in clinical samples routinely referred to our clinical cytogenetics laboratory. When required, NGS was performed on DNA and RNA libraries to detect somatic alterations and gene fusions in some of these specimens. Discordance in results between these methods is further evaluated.

Results

For a patient with plasma cell leukemia standard FGFR3 / IGH dual fusion FISH assay detected fusion that was interpreted as FGFR3-positive leukemia, whereas NGS/RNASeq detected NSD2::IGH. For a pediatric acute lymphoblastic leukemia patient, a genetic diagnosis of PDGFRB-positive ALL was rendered because the PDGFRB break-apart probe detected clonal rearrangement, whereas NGS detected MEF2D::CSF1R. A MYC-positive B-prolymphocytic leukemia was rendered for another patient with a cytogenetically identified t(8;14) and MYC::IGH by FISH, whereas NGS detected a novel PVT1::RCOR1 not previously reported.

Conclusions

These are 3 cases in a series of several other concordant results, nevertheless, elucidate limitations when interpreting FISH results in clinical applications, particularly when other genes are included in probe design. In addition, when the observed FISH signals are atypical, this study illustrates the necessity to perform complementary laboratory assays, such as NGS and/or RNASeq, to accurately identify fusion genes in tumorigenic translocations.

Clinical Characteristics and Outcomes of Cyclin D1-Positive AL Amyloidosis

OBJECTIVES

To demonstrate the clinical features and prognostic impact of cyclin D1 positivity in patients with amyloid light chain amyloidosis (AL).

METHODS

We consecutively included 71 patients diagnosed with AL with cyclin D1 positivity between February 2008 and January 2022. t(11;14) was examined through interphase fluorescence in situ hybridization using bone marrow cells.

RESULTS

The median age of the patients was 73 years, and 53.5% were male. The underlying diseases included symptomatic multiple myeloma, smoldering multiple myeloma, Waldenström macroglobulinemia, and monoclonal gammopathy of undetermined significance, representing 33.8%, 26.8%, 2.8%, and 36.6%, respectively. The prevalence of cyclin D1 and t(11;14) was 38.0% and 34.7%, respectively. Higher frequency of light chain paraprotein type was seen in cyclin D1-positive patients with AL than in cyclin D1-negative patients (70.4% vs 18.2%). The median overall survival (OS) of patients with AL with and without cyclin D1 expression was 18.9 months and 73.1 months, respectively (P = .019). Early death occurred in 44.4% of cyclin D1-positive patients and 31.8% of cyclin D1-negative patients. Moreover, 83.3% of cyclin D1-positive patients and 21.4% of cyclin D1-negative patients died of cardiac causes.

CONCLUSIONS

Cyclin D1 immunohistochemistry accurately identified patients with t(11;14). Cyclin D1-positive patients had significantly inferior OS compared with cyclin D1-negative patients.

hsa_circ_0007841: A Novel Potential Biomarker and Drug Resistance for Multiple Myeloma

Purpose: Circular RNA (circRNA) is a key regulatory factor in the development and progression of human tumors. However, the working mechanism and clinical significance of most circRNAs remain unknown in human cancers, including multiple myeloma (MM).

Patients and Methods: This study employs high-throughput circRNA microarray with bioinformatics to identify differentially expressed circRNAs in patients with MM. The hsa_circ_0007841 expressions were observed in the MM tissues of 86 patients. Drug-resistant cell lines and pathological features were also detected. In addition, the relationship between hsa_circ_0007841 expressions in the MM tissues and the pathological features of patients with MM were evaluated and role of hsa_circ_0007841 as a potential biomarker and therapeutic target was assessed.

Results: The results show that in the MM cell lines and drug-resistant cell lines, hsa_circ_0007841 expression was significantly upregulated, which was closely associated with disease prognosis. Specifically, hsa_circ_0007841 upregulation was correlated with chromosomal aberrations such as gain 1q21, t (4:14) and mutations in ATR and IRF4 genes. This finding was corroborated in large samples. Finally, bioinformatics analysis showed that eight differentially expressed miRNAs and 10 candidate mRNAs interacted with hsa_circ_0007841, shedding some new light on the basic functional research.

Conclusion: This study may be the first to report that hsa_circ_0007841 is significantly upregulated in MM. It also suggests that hsa_circ_0007841 may be a novel biomarker for MM and its involvement in the progression of MM.

Immunohistochemistry for identification of CCND1, NSD2, and MAF gene rearrangements in plasma cell myeloma

The t(11;14)/CCND1‐IGH, t(4;14)/NSD2(MMSET)‐IGH, and t(14;16)/IGH‐MAF gene rearrangements detected by fluorescence in situ hybridization (FISH) are used for risk stratification in patients with multiple myeloma (MM). Compared with conventional FISH techniques using fresh cells, immunohistochemistry (IHC) is much more cost‐ and time‐efficient, and can be readily applied to routinely prepared formalin‐fixed, paraffin‐embedded (FFPE) materials. In this study, we performed tissue FISH and IHC employing FFPE specimens, and examined the usefulness of IHC as a tool for detecting CCND1,NSD2, and MAF gene rearrangements. CD138 signals were used to identify plasma cells in tissue FISH and IHC analyses. With cohort 1 (n = 70), we performed tissue FISH and subsequently IHC, and determined IHC cut‐off points. In this cohort, the sensitivity and specificity for the 3 molecules were ≥.90 and ≥.96, respectively. With cohort 2, using MM cases with an unknown gene status (n = 120), we performed IHC, and the gene status was estimated using the cut‐off points determined with cohort 1. The subsequent FISH analysis showed that the sensitivity and specificity for the 3 molecules were ≥.92 and ≥.98, respectively. CCND1, NSD2, and MAF gene rearrangements were estimated accurately by IHC, suggesting that conventional FISH assays can be replaced by IHC.