Baseline lncRNA PCAT1 high expression and its longitude increment during induction therapy predict worse prognosis in multiple myeloma patients

Abstract Background Long noncoding RNA PCAT1 (lnc‐PCAT1) involves in the proliferation and drug sensitivity of multiple myeloma (MM), while its prognostic role in MM patients is still obscure. This study aimed to explore the association of lnc‐PCAT1 with MM risk, clinical characteristics, treatment response, progression‐free survival (PFS), and overall survival (OS). Methods A total of 83 symptomatic MM patients were enrolled in this study. Additionally, 30 healthy bone marrow donors as health controls were also recruited. Bone marrow plasma cell samples of MM patients and health donors were collected. Lnc‐PCAT1 in bone marrow plasma cells was detected by reverse transcription‐quantitative polymerase chain reaction. Results Lnc‐PCAT1 was increased in MM patients than in health donors (p < 0.001), and receiver operating characteristic (ROC) curve showed that lnc‐PCAT1 had excellent capability of discriminating MM patients from health donors (area under curve: 0.932, 95% confidence interval: 0.889–0.976). In MM patients, lnc‐PCAT1 was correlated with bone lesion (p = 0.024), higher β2‐MG (p = 0.005), LDH (p = 0.037), and presence of Del (17p) (p = 0.029). Lnc‐PCAT1 was also associated with poor ISS stage (p = 0.013) and R‐ISS stage (p = 0.005). Besides, lnc‐PCAT1 was reduced after treatment (p < 0.001); meanwhile, lnc‐PCAT1 before treatment was correlated with lower CR (p = 0.046) but not ORR (p = 0.185). Additionally, lnc‐PCAT1 after treatment was associated with lower CR (p = 0.003) and ORR (p = 0.010). Furthermore, baseline Inc‐PCAT1 high and Inc‐PCAT1 increase after treatment were correlated with worse PFS and OS (all p < 0.05). Conclusion Lnc‐PCAT1 dysregulation serves as a biomarker for diagnosis and prognosis for MM.


| INTRODUC TI ON
Accounting for approximately 10% of hematologic malignancies, multiple myeloma (MM) is a heterogeneous disease characterized by uncontrolled growth of monoclonal plasma cells in the bone marrow. 1,2 Although there are several therapeutic methods for newly diagnosed MM, many patients still develop refractory or relapsed conditions, especially among elderly patients. 3 Simultaneously, the 5-year survival rate of MM disease is under 50%. 4,5 According to a previous report, there were estimated 16,500 new cases and 10,300 deaths of MM in China in 2016, while its mortality rate increased annually by 4.5% from 2006 to 2014. 6 Therefore, it would be essential to find out more biomarkers for predicting the MM prognosis, which might strengthen the management of MM patients.
Long noncoding RNAs (lncRNAs) are transcripts with more than 200 nucleotides (nts) but with little protein-coding ability. 7 It is re- Among the commonly investigated lncRNAs, lncRNA prostate cancer-associated transcript 1 (lnc-PCAT1) involves in the progression of several malignancies. 8 For example, overexpression of lnc-PCAT1 expedites cell proliferation and migration in diffuse large B-cell lymphoma through miR-508-3p/NFIB axis 9 ; lnc-PCAT1 promotes esophageal squamous cell proliferation by sponging miR-326. 10 Apart from these malignancies, lnc-PCAT1 also participates in the progression of MM. For instance, a recent study shows that dysregulated lnc-PCAT1 promotes proliferation in MM cells via p38 and jun N-terminal kinase/mitogen-activated protein kinase (JNK/MAPK) pathways. 11 Additionally, enhanced lnc-PCAT1 promotes plasma cell proliferation and inhibits apoptosis by downregulating microRNA-129 (miR-129) and further regulating mitogen-activated protein kinase kinase kinase 7/nuclear factor-kappaB (MAP3K7/NF-κB) pathways in MM. 12 Moreover, via modulating the protein kinase B/β-catenin signaling pathway, lnc-PCAT1 facilitates plasma cell proliferation, thus participating in the occurrence and progression of MM. 13 Based on the abovementioned information, we hypothesized that lnc-PCAT1 might be a potential biomarker for MM. However, no previous studies have been performed on this.
The present study was designed to investigate the association of lnc-PCAT1 with MM risk and its clinical characteristics. Besides, this study also aimed to explore the correlation of lnc-PCAT1 with MM prognosis, including treatment response, progression-free survival (PFS), and overall survival (OS).  were used to sort out plasma cells from the bone marrow samples.

| Lnc-PCAT1 determination
Subsequently, reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was carried out to determine the expression of lnc-PCAT1 in the plasma cells. The plasma cells were treated by TRIzol™ Reagent (Thermo Fisher Scientific) to extract total RNA, which were then submitted to perform reverse transcription using iScript™ cDNA Synthesis Kit (with random primer) (Bio-Rad). After that, qPCR was carried out with QuantiNova SYBR Green PCR Kit (Qiagen). GAPDH was served as reference gene. The relative quantitative analysis of lnc-PCAT1 expression was conducted with the use of 2 −ΔΔCt method.
Primers were designed referring to a previous study. 12

| Data collection and assessment
Baseline clinical features and staging information (Durie-Salmon (DS) stage, International Staging System (ISS) stage, and revised ISS (R-ISS) stage [15][16][17] ) of MM patients were documented after initial examinations. Induction therapy with regimen of lenalidomide/bortezomib/dexamethasone was administered for patients as recommended in the IMWG guideline. 18 Response to induction therapy was evaluated at the completion of 3 to 4 cycles of induction therapy according to the IMWG criteria. 19 For study analysis, patients with complete response (CR), very good partial response (VGPR), or partial response (PR) were recorded, and objective response rate (ORR) was calculated as the ratio of CR, VGPR, and PR patients in total patients. Patients without induction therapy response evaluation due to early death or loss of follow-up were not included in the final analysis. Follow-up and monitoring of patients were managed as recommended in the IMWG guideline. 18 In the present study, the last follow-up date was3/31/2021. Progressionfree survival (PFS) and overall survival (OS) were evaluated in accordance with IMWG guideline. 19 Inc.) were used for data analysis and graph plotting, respectively. Categorical data were described as count with percentage.

| Statistical analysis
Continuous data distribution was analyzed using Kolmogorov-

| Lnc-PCAT1 expression in MM patients and health donors as well as its relation to MM risk
Lnc-PCAT1 expression was higher in the MM patients (N = 83) than in the health donors (N = 30) (p < 0.001) ( Figure 1A). Besides, the ROC curve showed that lnc-PCAT1 expression possessed excellent potential in discriminating MM patients from health donors with AUC of 0.932 (95% confidence interval (CI): 0.889-0.976) ( Figure 1B).

| Correlation of lnc-PCAT1 with characteristics of MM patients
As shown in Table 2 Table 2). In addition, as suggested in Figure 2, lnc-PCAT1 expression was correlated with elevated ISS stage (p = 0.013) ( Figure 2B) and R-ISS stage (p = 0.005) ( Figure 2C)

| Lnc-PCAT1 expression after induction treatment in MM
Lnc-PCAT1 expression was decreased after treatment (median value: patients after treatment (Figure 3). In this study, MM patients mainly received bortezomib, cyclophosphamide, and dexamethasone (BCD) as well as bortezomib, lenalidomide, and dexamethasone (BLD) regimens as treatment methods. No difference was observed in lnc-PCAT1 expression between patients received BCD and BLD before treatment or after treatment (both p > 0.05) ( Figure 4A and B).
Besides, no difference was observed in the change in lnc-PCAT1 expression before and after treatment between MM patients received BCD and BLD (p > 0.05) ( Figure 4C). However, in both patients received BCD (p = 0.002) and BLD regimens (p < 0.001), lnc-PCAT1 expression was decreased after treatment ( Figure 4D and E).

| Correlation of lnc-PCAT1 expression with treatment response in MM
Lnc-PCAT1 expression before treatment in the CR patients (n = 23) was lower than that in the non-CR patients (n = 60) (p = 0.046) ( Figure 5A). Otherwise, lnc-PCAT1 expression before treatment was similar between the ORR patients (n = 59) and the non-ORR patients (n = 24) (p = 0.185) ( Figure 5B). In addition, lnc-PCAT1 expression after treatment was reduced in the CR patients (n = 23) than the non-CR patients (n = 60) (p = 0.003) ( Figure 5C). Moreover, lnc-PCAT1 expression after treatment was declined in the ORR patients (n = 59) compared with that in the non-ORR patients (n = 24) (p = 0.010) ( Figure 5D). Additionally, lnc-PCAT1 expression showed a more predominant reduction in CR patients. In detail, lnc-PCAT1 expression was greatly decreased in both CR patients (p = 0.010) ( Figure 6A) and non-CR patients (p < 0.001) ( Figure 6B) after treatment compared with before treatment. No obvious difference was found in the change in lnc-PCAT1 expression before and after treatment between CR and non-CR patients (p > 0.05) ( Figure 6C). In addition, lnc-PCAT1 expression was declined in both ORR (p < 0.001) patients and non-ORR patients (p = 0.013) after treatment compared with before treatment (Figure 6D and E). No obvious difference was found in the change in lnc-PCAT1 expression before and after treatment between ORR and non-ORR patients ( Figure 6F) (p > 0.05). As to lnc-PCAT1 expression in the hematological malignancies, lnc-PCAT1 is enhanced in acute myeloid leukemia patients. 9

| Correlation of lnc-PCAT1 expression with accumulating PFS and OS in MM
Our study found that lnc-PCAT1 was increased in the MM patients  (2) lnc-PCAT1 expression was associated with poor risk stratification Conclusively, lnc-PCAT1 associates with elevated disease risk and unfavorable ISS stage, R-ISS stage, treatment response, and survival of MM. It may potentially serve as a biomarker to predict MM prognosis, further improving the management of MM patients.

ACK N OWLED G M ENTS
None.

CO N FLI C T S O F I NTE R E S T
The authors declare that they have no conflicts of interest.

DATA AVA I L A B I L I T Y S TAT E M E N T
Data sharing was not applicable to this article as no datasets were generated or analyzed during the current study.