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INTRODUCTION
Multiple myeloma (MM) is characterized by the abnormal proliferation of monoclonal plasma cells in the bone marrow (BM) [1]. Cytogenetic abnormalities (CAs) play a role in the development and progression of MM, and high-risk CAs are associated with poor patient prognosis [2]. They are important for risk stratification at diagnosis and for residual disease monitoring [3–8], and their detection is also crucial in smoldering MM and monoclonal gammopathy of undetermined significance (MGUS) [9]. Because of the low mitotic activity of plasma cells in vitro and the low level of tumor cell infiltration in BM specimens, chromosome analysis can detect only part of the CAs in cases of MM [10]. Interphase FISH is the method of choice for detecting CAs in MM [10]. Because the proportion of plasma cells is reduced in BM aspirates used for FISH analysis because of dilution with peripheral blood, plasma cells must be enriched to increase the analytical sensitivity [11].
For enrichment, plasma cells can be purified using magnetic beads (magnetic-activated cell sorting, MACS) or flow cytometry (fluorescence-activated cell sorting, FACS) [12]. Alternatively, the number of plasma cells analyzed can be increased through dual staining of cytoplasmic immunoglobulin and the target locus and analyzing only the plasma cells (fluorescence immunophenotyping and interphase cytogenetic as a tool for investigation of neoplasia, FICTION) [13]. Since FISH sensitivity is limited by plasma cell percentage in BM, as CA detection correlates with plasma cell concentration in unpurified BM samples [12], performing FISH in conjunction with such enrichment or targeting strategies has been suggested [14, 15]. Hartmann, et al. [12] reported that FACS purifies plasma cells more efficiently than MACS, with FACS-FISH able to detect CAs in samples containing as few as 1,500 plasma cells. However, the factors that influence the success of FACS and their effects on test positivity remained largely unexplored.
We previously demonstrated the usefulness of FACS-FISH by comparing the results of direct FISH and FICTION in patients with MM [13]. We have successfully implemented FACS-FISH at our institution since November 2016. Although FACS-FISH achieves high success and positivity rates, obtaining an appropriate amount of plasma cells within a reasonable time for downstream analysis can fail for some samples. When FACS failed, we conducted FISH using unsorted pellets (direct FISH). Because the success rate of FACS-FISH in real-world settings is less than 100%, we investigated the factors influencing the success of FACS-FISH and analyzed the positivity rate achievable through the application of direct FISH when FACS failed.
MATERIALS AND METHODS
Patient cohort and data collection
This study was approved by the Institutional Review Board of Severance Hospital, Yonsei University College of Medicine, Seoul, Korea (IRB No. 4-2022-1168). Informed consent was waived because of the retrospective nature of our study based on reviews of patient records. We included patients who requested MM FISH tests for the evaluation of plasma cell disorders at the Department of Laboratory Medicine, Severance Hospital, between November 1, 2016, and May 31, 2022. We hypothesized that two factors could affect the FACS success rate: the plasma cell percentage of BM aspirates and sample transfer time. The former was defined as the ratio of plasma cells among total nucleated cells counted using microscopy in the first BM aspirate slide. The latter was defined as the time interval between BM collection and the arrival of the sample in the laboratory. In addition, the positivity rate and ratio of abnormal cells in each FISH probe were calculated and analyzed.
FISH analysis
For FACS-FISH, BM aspirates in sodium heparin tubes were centrifuged at 1,000×g at 20°C for 5 mins. The buffy coat was treated with lysis solution and incubated in the dark for 20 mins. After centrifugation, the supernatants were collected and washed with phosphate-buffered saline (PBS) several times. The final concentration of cells (1×106 to 4×107 cells/mL) was adjusted with PBS depending on the amount of cell pellet. Next, the cells were purified using a ProFlow Cell Filter (Bio-Rad, Hercules, CA, USA) and stained with fluorescence-conjugated antibodies (fluorescein isothiocyanate-conjugated anti-CD38 and phycoerythrin-conjugated anti-CD138; Beckman Coulter, Brea, CA, USA) for 20 mins. Finally, plasma cells were sorted using an S3e Cell Sorter (Bio-Rad). FACS was considered successful when the proportion of CD38+ and CD138+ cells was more than 1% of the total number of cells.
For samples with FACS failure, direct FISH was conducted using total BM aspirates in sodium heparin tubes that were centrifuged at 1,800×g for 10 min. Leukocytes from the buffy coat layer were collected and incubated in a water bath at 37°C for 30–40 mins, followed by the addition of potassium chloride (0.068 M). The cells were fixed with methyl alcohol and acetic acid at a 3:1 v/v ratio and air-dried at room temperature.
We used six commercial locus-specific probes, including XL TP53/17cen, XL t(4;14) FGFR3/IGH DF, XL t(11;14) MYEOV/IGH DF, XL t(14;16) IGH/MAF DF, XL DLEU/LAMP, and XL CDKN2C/CKS1B (MetaSystems, Altlussheim, Germany). Fluorescence images were captured using a Metafer slide scanning system (MetaSystems). For each probe, 200 interphase nuclei were analyzed. The cut-off for each probe was determined using a beta inverse method and was validated regularly [16]. Cut-off values for the six probes were as follows: 7.8% for del(17p13.1), 5.4% for del(13q14.3), 7.3% for t(4;14), 7% for t(11;14), 7.8% for t(14;16), and 6.2% for amp(1q21).
Statistical analysis
The Shapiro–Wilk test was used to evaluate the normality of continuous variables, and these were found to be non-normally distributed. Consequently, the correlations between FISH success and positivity rates and continuous and/or categorical variables were analyzed using the Mann–Whitney U-test and Fisher’s exact test. Comparisons of abnormal cell percentages between FACS-FISH and direct FISH analyses were performed using the Mann–Whitney U-test. Differences with a two-sided P<0.05 were considered statistically significant. To evaluate potential multicollinearity between sample transfer time and plasma cell percentage, Pearson correlation coefficient analyses and variance inflation factor (VIF) tests were performed for the complete dataset, the FACS-FISH subset, and the direct FISH subset. A correlation coefficient <0.7 indicates low collinearity between the variables, whereas a VIF >5 suggests a high degree of correlation [17, 18]. Statistical analyses were performed using GraphPad Prism 4.03 (GraphPad Software, San Diego, CA, USA) and R software 4.2.3 (Posit Software, Boston, MA, USA).
RESULTS
Patient characteristics
In total, 457 BM samples were subjected to MM FISH analysis. Patient characteristics are summarized in Supplemental Data Table S1. Patients with newly diagnosed MM accounted for 69.8% (319/457), and those with MGUS accounted for 16.2% (74/457) of the patient population. In 5.9% of cases (27/457), the FISH test was requested to monitor the CA identified at the time of diagnosis.
FACS success rates depend on sample transfer time
Among the 457 BM samples analyzed, FACS-FISH was successful in 324 samples, with a success rate of 70.9% (324/457), and 133 samples were subjected to direct FISH. The median and interquartile range (IQR) of the sample transfer time were 152.0 min and 106.0–674.0, respectively. Samples with successful FACS (FACS-success group) had a shorter median arrival time of 146.0 min (IQR=95.0 to 747.4) than FACS-failure samples (FACS-failure group; median 155 min, IQR 120.0–424.0), although the difference was not statistically significant (P=0.1965, Mann–Whitney U-test, Fig. 1A). When the sample transfer time was <2 hrs, the FACS success rate (77.1%, 118/153) was significantly higher than when the transfer time was >2 hrs (67.8%, 206/304; P=0.0388, Fisher’s exact test).
FACS success rates depend on plasma cell percentage
Next, we determined whether the percentage of plasma cells in BM aspirates affected the success of FACS-FISH. The percentage of plasma cells was determined by dividing the number of plasma cells by the number of all nucleated cells as determined via microscopic examination of BM aspiration slides.
The median and IQR of plasma cell percentage were 24.3% and 10.0–53.4, respectively. The FACS-success group (median 31.2%, IQR 14.3–58.2) had a significantly higher percentage of plasma cells than the FACS-failure group (median 8.5%, IQR 3.1–41.9) (P<0.0001, Mann–Whitney U-test, Fig. 1B). When the plasma cell percentage was ≥10%, the FACS success rate (81.0%; 278/343) was significantly higher than when the percentage was <10% (40.4% (46/114, P<0.0001, Fisher’s exact test).
Positivity rates and abnormal cell percentages of FACS-FISH and direct FISH
The overall positivity rate was 94.8% (307/324) for FACS-FISH (Table 1) and 43.6% (58/133) for direct FISH (Table 2). Both methods had a higher positivity rate for translocation probes than for deletion/amplification probes. The distribution of abnormal cell percentages detected with each FISH probe is shown in Fig. 2. Next, we summarized the positivity rate according to the plasma cell percentage in the BM aspirates. Even in samples with <10% plasma cells, FACS-FISH and direct FISH had a positivity rate of 80.4% (37/46) and 18.8% (13/69), respectively (Tables 1 and 2). When FACS-FISH failed and direct FISH was applied, CAs were detected in 43.6% (58/133) of the samples.
Correlation and covariance analyses
To assess the potential confounding relationship between sample transfer time and plasma cell percentage, we conducted correlation and covariance analyses for the complete dataset, FACS-FISH subset, and direct FISH subset. Across all three datasets, the correlation coefficients between sample transfer time and plasma cell percentage were <0.7, and the VIF values were close to 1. Specifically, Pearson correlation coefficients and VIF values were 0.03 and 1.00 (complete dataset), 0.01 and 1.00 (FACS-FISH subset), and 0.06 and 1.00 (direct FISH subset), respectively. These findings suggested that no significant association or collinearity existed between the two variables.
DISCUSSION
We analyzed 457 BM samples from patients with suspected MM or related conditions, such as MGUS, referred for FISH analysis. The cohort mostly comprised newly diagnosed MM cases (69.8%), with a small subset (5.9%) undergoing follow-up testing for residual CAs (Supplemental Data Table S1). The predominance of newly diagnosed MM cases underscores the value of FISH in detecting CA for both diagnostic and prognostic purposes in patients with MM [10, 14, 19–21]. The presence of MGUS and other plasma cell-related disorders emphasizes the importance of identifying CAs even in pre-malignant conditions. While the incidence of MGUS is higher than that of MM [22], the higher proportion of MM cases than that of MGUS cases in our cohort likely reflects the referral of these patients specifically for FISH testing because of suspected MM. Our cohort provides valuable insights into the use of FISH in various plasma cell disorders.
Our findings indicate that timely sample transfer significantly influences the success rate of FACS-FISH. The overall success rate was 70.9% and was substantially higher (77.1%) when the sample transfer time was <2 hrs than when it exceeded this threshold (67.8%). Although the difference in median sample arrival times between FACS-success and -failure groups was not statistically significant, the data suggest that rapid handling and processing of BM samples improve FACS-FISH success rates. This finding highlights the importance of efficient logistics in ensuring the integrity and reliability of cytogenetic testing. Delays in sample transfer can interfere with plasma cell enrichment using FACS, potentially affecting its sensitivity, underscoring the importance of streamlined sample processing protocols to ensure optimal FACS-FISH outcomes. Previous studies have also shown the influence of sample handling on FISH analysis, emphasizing that cell viability is essential for the accurate detection of CAs in MM [23, 24]. Accordingly, timely processing and standardized protocols for sample handling have been recommended [25, 26]. However, few studies have specifically examined the effect of sample transfer time or suggested a time limit for sample transfers [11, 12]. Our findings, which indicate a 2-hr window for optimal transfer, provide valuable insights for clinical laboratories applying FISH techniques and can help guide best practices in clinical settings.
The percentage of plasma cells in BM aspirates was a critical determinant of FACS-FISH success in our study. Our study is unique in that it demonstrated a strong association between higher plasma cell percentages and the success of FACS-FISH, with a median plasma cell percentage of 31.2% in successful cases compared with 8.5% in failed cases. Notably, when the plasma cell percentage was 10%, the FACS success rate was 81.0%, and the rate dropped to 40.4% in cases with plasma cell percentages <10%. A previous study by Ha, et al. [13] in our institution that focused on cases in which FACS was successful revealed a substantially higher positivity rate for FACS-FISH than for direct or FICTION-FISH (95.5% vs. 38.0% and 56.3%, respectively). However, the study failed to find a significant association between plasma cell percentage and FACS-FISH positivity, whereas the plasma cell percentage significantly influenced FISH positivity in direct or FICTION-FISH. This highlighted that FACS-FISH maintained its detection strength even in BM samples with low plasma cell percentages as long as FACS was successful. However, in practical laboratory settings, successful FACS enrichment is a prerequisite for conducting subsequent FISH analysis. Our current study revealed that the plasma cell percentage has a significant effect on the FACS success rate and affects the overall success of the FACS-FISH procedure. Given that the plasma cell percentage is a critical factor in FACS-FISH in clinical laboratories, our findings provide valuable additional insights for real-world application in clinical laboratories.
FACS-FISH had a high positivity rate (94.8%) in our study. Even in samples with low plasma cell percentages (<10%), FACS-FISH achieved a high detection rate (80.4%), underscoring its excellent sensitivity in detecting CAs. These findings are consistent with those reported by Ha, et al. [12], who demonstrated the superior detection capability of FACS-FISH over FICTION or direct FISH. Importantly, when FACS-FISH failed and direct FISH was applied as a secondary strategy, CAs were detected in 43.6% of cases, demonstrating the complementary role of direct FISH in scenarios where plasma cell purification is not feasible. These findings suggest that while FACS-FISH is the preferred method for CA detection, direct FISH remains a valuable backup option, particularly in cases with lower plasma cell percentages or logistical challenges affecting sample integrity. To the best of our knowledge, few studies have evaluated the complementary role of direct FISH in relation to FACS-FISH. Our study offers new insights in this area, highlighting the potential benefit of a two-step FISH strategy, i.e., first performing FACS-FISH, followed by direct FISH when FACS-FISH fails. This approach would not only enhance the detectability but also provide a direction for future research to refine FISH protocols in practice.
Correlation and covariance analyses revealed minimal collinearity between sample transfer time and plasma cell percentage, with Pearson correlation coefficients <0.7 and VIF values close to 1 across three datasets. These findings indicate that no significant association exists between the two variables, supporting their independence and minimizing their potential confounding effect on our analysis of factors influencing FACS success. Therefore, our results on the FACS success rates seem reliable, despite the influence of these variables.
Our study has several limitations, including its single-center, retrospective design. Future research should include larger, multicenter studies to validate our findings. A second limitation is the heterogeneity of the study population, which included patients at various stages of plasma cell disorders. For example, the MM group included patients at diagnosis and those undergoing follow-up. As a result, differences in patient characteristics, particularly disease severity, may have influenced the comparisons of the FISH success or positivity rates. However, given that cytogenetic laboratories in real-world practice frequently receive samples from patients with unclear diagnoses at the time of BM collection, our findings offer valuable insights into the practical application of FACS-FISH in clinical settings. The wide variability in sample transfer times is a third limitation. While we found a significant association between shorter transfer times and FACS-FISH success, the broad range of times (106–674 min) suggests that confounding factors, such as storage conditions or handling during transit, may have influenced the results. As these factors were not fully controlled, they may have affected the outcomes. In addition, because direct FISH was performed only on samples for which FACS failed, we could not compare the two methods in parallel. Therefore, we could not evaluate other potential influences on FACS-FISH success, such as sample quality or operator experience. Our study also lacked longitudinal clinical data tracking long-term clinical outcomes in relation to FISH success or failure. As cytogenetic abnormalities detected using FISH affect prognoses [27], correlating FISH success with clinical outcomes such as therapy response or overall survival would provide a more comprehensive understanding of the clinical implications of the results. Incorporating such data in future studies would enhance our ability to assess the broader significance of FACS-FISH performance.
In conclusion, our findings demonstrate the significant influence of sample transfer time and plasma cell percentage on the utility of FACS-FISH analysis in patients with MM. Our findings also suggest that a two-step approach employing initial FACS-FISH followed by direct FISH, whenever required, can enhance detection rates and provide comprehensive diagnostic information. The results offer practical guidance for the application of FACS-FISH in clinical laboratories and emphasize the potential of a two-step strategy to maximize CA detection in plasma cell disorders.
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