CN110923315B - Application of multiple myeloma biomarker hsa_circ_0007841 - Google Patents

Abstract

The invention discloses application of a Multiple Myeloma (MM) biomarker hsa_circ_ 0007841. Hsa_circ_0007841 was found to be significantly up-regulated for the first time in MM patients, and this result was confirmed by qRT-PCR technique in large samples (n=86). The expression, diagnostic and prognostic value of hsa_circ_0007841 in MM was first elucidated. By combining with clinical pathology indexes of MM patients, we found that hsa_circ_0007841 expression levels are significantly different in terms of patient typing, staging and risk stratification, and studied disease progression during survival of MM patients for 1-4 years, high expression hsa_circ_0007841 was significantly correlated with poor prognosis of MM patients. The invention discusses the clinical value of the circRNA in the aspects of multiple myeloma diagnosis, prognosis analysis and the like, and simultaneously provides a preliminary clinical basis for subsequent researches.

Description

Application of multiple myeloma biomarker hsa_circ_0007841

Technical Field

The invention belongs to the technical field of molecular biology, and particularly relates to application of a multiple myeloma biomarker hsa_circ_ 0007841.

Background

Non-coding RNAs (ncrnas) include long Non-coding RNAs (lncrnas), short micrornas (mirnas/miRs), and circular RNAs (circrnas). ncrnas account for the vast majority of eukaryotic transcriptomes. Unlike traditional linear RNAs (containing 5 'and 3' ends), the circRNA molecule is in a closed loop structure, resulting from back splicing of introns and/or exonic RNAs, which were found in 1970 from viral RNAs, followed by eukaryotic cells, and in recent years high throughput sequencing combined with transcriptome analysis, was found to be present in large amounts in eukaryotic cells.

The circRNA rich in the miRNA binding site is a sponge adsorbent of miRNA, can inhibit the miRNA from binding with a target gene, and can be competitively bound with the miRNA through the sponge effect, so that the transcription inhibition effect of the circRNA on the downstream target gene is relieved. In addition to "sponging", circRNA also has the effect of regulating the expression of the parent gene, interacting with the protein to affect the level of gene transcription, and even translation of the protein. The circRNA is a relatively large group of RNAs that form a stable closed loop. Most ncrnas and circrnas are involved in regulating transcription and posttranscriptional gene expression. Play an important role in the development, metastasis and therapeutic response of cancer. Specificity of circrnas in disease states and stability in body fluids suggest that they may be useful in the diagnosis of cancer.

Multiple Myeloma (MM) is a hematological malignancy caused by abnormal proliferation of plasma cells in bone marrow, is the second most common hematological malignancy in clinic, accounts for 10% of hematological neoplasms, the incidence rate is estimated to be 2-3/10 ten thousand, and the ratio of men and women is 1.6:1. the clinical manifestations are various, and mainly include anemia, bone pain, renal insufficiency, infection, hemorrhage, neurological symptoms, hypercalcemia, amyloidosis, etc. Some genetic variation often occurs in the development process of MM, including cytogenetic abnormalities, primary or secondary chromosomal translocation, oncogene activation and the like, which has important significance for tumor pathogenesis, disease prognosis and therapeutic response. The present invention utilizes the latest bioinformatics methods to integrate small samples of circRNAs originally screened in a high throughput circRNA database that may affect myeloma patient treatment and prognosis. And then, amplifying a sample by Real-time quantitative PCR (Real-time quantitative polymerase chain reaction, qRT-PCR), finding that the expression level of hsa_circ_0007841 in MM patients and cell lines is obviously increased, evaluating the relation between the expression level of hsa_circ_0007841 and clinical pathological characteristics of the MM patients, and analyzing whether the expression level can be used as a reference factor for diagnosing and prognosing the MM patients. The method has important clinical significance in searching effective multiple myeloma prognosis markers and new therapeutic targets.

Disclosure of Invention

The invention provides a multiple myeloma marker hsa_circ_0007841, the sequence of which is shown as SEQ ID No. 1. The circular RNA provides a new molecular marker and detection path for the diagnosis and prognosis of multiple myeloma, and the molecular marker has high accuracy, good sensitivity and specificity and good application prospect.

A first object of the present invention is to provide a specific application of the molecular marker hsa_circ_ 0007841: in particular to application of a reagent for detecting the molecular marker in preparing an MM diagnostic reagent.

Further, the MM diagnostic reagent comprises PCR reagent.

Further, the PCR reagent contains a primer for detecting hsa_circ_0007841, and the sequence is:

F5'CTAACATCTGTGAAACCATCGT 3', SEQ ID No.2,

r is 5'TCATCACATACACGATAGACTGG 3', see SEQ ID No.3.

The second object of the invention is to provide a second specific application of the molecular marker hsa_circ_0007841, in particular to the application of a reagent for detecting the molecular marker in preparing an MM prognosis reagent.

Further, the multiple myeloma prognostic reagent includes a PCR reagent.

Further, the PCR reagent contains a primer for detecting hsa_circ_0007841, and the sequence is:

F:5’CTAACATCTGTGAAACCATCGT 3’

R:5’TCATCACATACACGATAGACTGG 3’。

the third purpose of the invention is to provide a third specific application of the molecular marker hsa_circ_0007841, in particular to an application of a reagent for detecting the molecular marker in preparation of a reagent for detecting bortezomib drug resistance of MM patients.

Further, the reagent for detecting bortezomib resistance of patients with multiple myeloma comprises a PCR reagent.

Further, the PCR reagent contains a primer for detecting hsa_circ_0007841, and the sequence is:

F:5’CTAACATCTGTGAAACCATCGT 3’

R:5’TCATCACATACACGATAGACTGG 3’。

the fourth object of the present invention is to provide a fourth specific application of the molecular marker hsa_circ_0007841, specifically, the application of the agent for reducing the expression of the molecular marker in preparing a preparation for treating multiple myeloma.

The recent trend toward aging of the population has led to an increase in the incidence of MM year by year. Although the new treatment method has great results, the prognosis of patients is obviously improved, and multiple myeloma is still an incurable disease, and the reason is mainly that the multiple myeloma cells are strong in heterogeneity, so that the patients are easy to relapse and resist. The MM individuation treatment according to the biomarker can maximally improve the curative effect and reduce the recurrent drug resistance. Certain biomarkers for multiple myeloma can serve as prognostic and predictive indicators, whereby selection of an appropriate treatment regimen can have a tremendous impact on patient outcome.

According to the invention, the bone marrow tissue differential expression circRNAs molecules of MM patients are screened by a high-throughput sequencing technology, a plurality of circRNAs are up-regulated for the first time, wherein hsa_circ_0007841 up-regulation is remarkable, and the result is confirmed in a large sample (n=86) by a qRT-PCR technology. To our knowledge, this is the first elucidation of the expression, diagnostic and prognostic value of hsa_circ_0007841 in MM. By combining with clinical pathology indexes of MM patients, we found that hsa_circ_0007841 expression levels are significantly different in terms of patient typing, staging and risk stratification, and studied disease progression during survival of MM patients for 1-4 years, high expression hsa_circ_0007841 was significantly correlated with poor prognosis of MM patients. Furthermore, since the circ-miRNA axis has a significant influence on the occurrence and development of human diseases, hsa_circ_0007841 may affect the occurrence of multiple myeloma through its miRNA-mediated proto-oncogene expression in the present invention. Annotation and functional prediction studies revealed that hsa_circ_0007841 interacted with 8 mirnas and 10 related targeting mrnas, where hsa_circ_0007841 is hsa-miR-29b-2-5p "sponge adsorbate", whereas highly expressed miR29b was able to inhibit osteoclast differentiation and overcome osteoclast activation triggered by MM cells, helping to delay progression of multiple myeloma bone disease, and miR-29b induced BTZ (bortezomib) apoptosis of multiple myeloma cells by activating the feedback loop of transcription factor Sp 1. In the invention, the high expression of hsa_circ_0007841 is closely related to the bone-dissolving bone destruction of multiple myeloma, and the high expression of hsa_circ_0007841 in the BTZ drug-resistant cell strain of MM is proved by the former study, so that the hsa_circ_0007841 is further suggested to be closely related to the diagnosis and prognosis of multiple myeloma patients.

The invention takes hsa_circ_0007841 as an example, discusses the clinical value of circRNA in aspects of multiple myeloma diagnosis, prognosis analysis and the like, and simultaneously provides a preliminary clinical basis for subsequent researches.

Drawings

Fig. 1: the microarray chip of the invention is analyzed;

(A) Cluster analysis graphs of differentially expressed circrnas; a1, A2 and A3 are control groups, and B1, B2 and B3 are MM groups.

(B) The block diagram represents the expression intensity of two sets of labeled circrnas;

(C) Volcanic images show significantly up-regulated genes in MM samples.

Fig. 2: the differentially expressed circRNA of the invention.

(A) The key circRNA is looped through exons;

(B) qRT-PCR validation was performed on 20 MM patients and 10 IDA patients;

(C) Expression of hsa_circ_0007841 in bone marrow of 86 MM patients and 30 control patients;

(D) Expression of hsa_circ_0007841 in Bortezomib (BTZ) sensitive and Bortezomib (BTZ) resistant patients (n=21) (n=36);

(E) hsa_circ_0007841 expression in MM patients, MM cell lines and control, MM is a multiple myeloma bone marrow tissue sample and control is a healthy bone marrow tissue sample.

Fig. 3: diagnostic and prognostic value analysis of hsa_circ_ 0007841;

(A) ROC analysis of MM patients by hsa_circ_ 0007841;

(B) Kaplan-Meier survival curves for hsa_circ_0007841 under-and over-expression in MM patients.

Fig. 4: functional analysis of the circRNA;

(A) Establishing an hsa_circ_0007841-miRNA-mRNA co-expression network by using hsa_circ_ 0007841;

(B) geneOntology_enrichment analysis.

Detailed Description

The following examples are intended to further illustrate the invention, but not to limit it.

1. Materials and methods

1.1 clinical data

86 MM patients collected and treated by Xiangya three hospitals in the university of south China 1 month 2012 to 2018 are selected as case groups, bone marrow samples and clinical case data of the patients are collected, and 53 men and 33 women of the whole group of patients are treated; the median age of onset was 55 years (44 years-78 years). The diagnosis, staging and risk status of MM are all performed according to the National Comprehensive Cancer Network (NCCN) and all have complete clinical pathology data. Because of the lack of clinical normal donor bone marrow samples, as little sample difference as possible, 30 Iron Deficiency Anemia (IDA) patients were selected as a control group and their bone marrow samples were collected. Bone marrow samples were cryopreserved at-80 ℃. All samples of this study were collected for APProval by the hospital ethical committee (APProval number: 2014123) and informed consent was obtained from the patient.

1.2 cell culture

Normal human monocyte strain THP-1, multiple myeloma cell lines KM3, U266, RPMI-8226 were each supplied by the basic laboratory of the Xiang ya medical college, university of south China, drug resistant cell lines KM3/BTZ, U266/BTZ, RPMI-8226/BTZ were obtained by stepwise increasing drug concentration tolerance, and cells were cultured in 1640 medium (HyClone, logan, UT, USA) plus 10% fetal bovine serum (Excell Biology, shanghai, china), 50U/mL penicillin and 50g/mL streptomycin (HyClone). Culturing at 37deg.C in a 5% carbon dioxide incubator. The experiment uses cells in logarithmic growth phase.

1.3 RNA extraction

First, bone marrow samples from patients with multiple myeloma and normal persons were enriched for plasma cells by CD138 immunomagnetic bead sorting (MACS), total RNA from the enriched plasma cells was extracted according to TRIzol kit (Invitrogen, USA), and total RNA from the corresponding cells was included and stored at-80 ℃. RNA concentration and activity were first checked by NanoDrop ND-1000, and then the purity and integrity of RNA was checked by formaldehyde denaturing agarose gel electrophoresis.

1.4 high throughput circRNA chip data analysis and differential expression

Sample preparation and microarray hybridization were performed according to Arraystar's standard protocols, first using RNaseR (Epicentre, USA) to remove linear RNA from total RNA from the sample, enriching for circRNA, and then using random primer method to amplify and transcribe the enriched circular RNAs into fluorescent cRNA. The labeled circRNA was hybridized in alignment with Arraystar Human circRNA Array V (8X 15K, arraystar). Then washed with a washing liquid kit (Agilent company, usa). the Agilent Scanner G2505C scans the chip. The acquired array images were analyzed using Agilent Feature Extraction software (version 11.0.1.1). The bits are normalized and subsequently processed using the R software limma package. Selection of differentially expressed circrnas was identified by fold change and p-value, the threshold set for significantly up-and down-regulated genes was fold change >2.0 and p-value <0.05.

1.5 quantitative RT-PCR verification

The RNA of the samples was reverse transcribed into cDNA using a SuperScript III Reverse Transcriptase (Invitrogen, grand Island, NY, USA) kit according to the guidelines, and quantitative Real-time qRT-PCR (Arraystar) was performed using a ViiA 7Real-time PCR System (Applied Biosystems) and a2 XPCR Master Mix. Each reaction mixture (10. Mu.L) contained 2 XMaster Mix 5ul, PCR specific primer F0.5. Mu.L, PCR specific primer R0.5. Mu.L, 2. Mu.L cDNA. The mixture was added to each well corresponding to 384-PCR plates. The 384-PCR plate was placed on a real time PCR apparatus for PCR reaction. The reaction conditions were as follows: incubation was performed at 95℃for 10 minutes, followed by 40 cycles of 95℃for 10 seconds and 60℃for 1 minute. Beta-actin served as an endogenous reference transcript and was normalized, and the delta Ct value reflects the expression level of circRNA. The gene amounts for each sample were calculated by reference correction, and each gene primer list is shown in Table 1.

1.6 statistical analysis

Data were statistically analyzed using SPSS 20.0 software and data are expressed as mean ± standard deviation. When comparing only 2 groups we used the Mann-Whitney test, when comparing >2 groups we used the Kruskal-Wallis H test. When the analysis is carried out by combining clinical data, a Kaplan-Meier survival curve is adopted, and a Log-rank test is applied for significance test. Analysis of the relationship of high/low circrnas to chromosomal and genetic mutations using the Chi-square test, all statistical test significance levels defined as p <0.01 as differences were statistically significant.

2. Results

2.1 Analysis of the expression profile of circRNA

To identify specific circRNAs differentially expressed by MM patients, high-throughput circRNA chips detected 3 MM patients and 3 IDA patients, we detected thousands of expressed circRNAs, including 4727 upregulated lncRNAs and 5283 downregulated lncRNAs (fig. 1A). Of these, 147 (including 131 upregulated and 16 downregulated), were expressed by fold change >2, and the box plot shows the normalized intensities of the two groups (FIG. 1B). Volcanic images show different expression of circular RNAs (fig. 1C).

2.2 hsa_circ_0007841 is up-regulated in MM cells

We screened 4 upregulated apparent circRNAs (see Table 1) and performed qRT-PCR on 20 MM patients and 10 IDA patients, as shown in FIG. 2B, and found that the hsa_circ_0007841 upregulation was most apparent in MM patients. hsa_circ_0007841 is located in chr3:127778944-127779504 and is obtained by back splicing of exons 6 and 7 of the sec61a1 gene (FIG. 2A). We further examined the level expression of hsa_circ_0007841 in bone marrow of MM patients (86 cases) (fig. 2C). The results suggest hsa_circ_0007841 is a better biomarker for MM. At the same time, we examined hsa_circ_0007841 expression levels in 21 bortezomib-resistant and 36 bortezomib-sensitive multiple myeloma patient samples, fig. 2D. We also examined hsa_circ_0007841 expression levels in normal human monocyte strains THP-1 and multiple myeloma cell lines KM3, U266, 8226, drug resistant cell lines KM3/BTZ, U266/BTZ,8226/BTZ (FIG. 2E). hsa_circ_0007841 is selectively expressed in multiple myeloma cell lines and bortezomib-resistant multiple myeloma patients, whereas it is expressed relatively low in normal human cell lines, with statistical significance (P < 0.05). In addition, the content of hsa_circ_0007841 in bortezomib resistant strains (KM 3/BTZ, U266/BTZ) is higher than that of KM3 and U266 cell strains, and the result shows that hsa_circ_0007841 is up-regulated and possibly participates in a bortezomib resistant mechanism of patients with multiple myeloma.

2.3 Relationship of hsa_circ_0007841 expression to clinical pathological parameters of patients with multiple myeloma

According to the NCCN up-to-date guidelines in 2018, we listed and analyzed the expression levels of hsa_circ_0007841 as a function of MM patient age, sex, typing, staging, risk stratification (IMWG), and determined the clinical relevance of hsa_circ_0007841 to multiple myeloma. The results show (table 2) that hsa_circ_0007841 is associated with typing (P < 0.001), cytogenetic variation (p=0.001), bone destruction, R-ISS staging (p=0.010), risk stratification (p=0.009), so it is closely related to the progression and prognosis of multiple myeloma and can be used as an indicator molecule.

2.4 Diagnostic value of hsa_circ_0007841 in MM

ROC curve is a comprehensive index reflecting continuous variable specificity and sensitivity, we calculated ROC curve by comparing the diagnostic potential of hsa_circ_0007841 in MM patients in MM group and control group (fig. 3A), verifying hsa_circ_0007841 sensitivity and specificity, area under curve is 0.907 (95% ci 0.8476-0.9663). Thus hsa_circ_0007841 has the potential to be a diagnostic indicator of MM. 2.5 Prognostic value of hsa_circ_0007841 in MM

We constructed a survival curve to analyze the correlation analysis of hsa_circ_0007841 on MM patient prognosis (fig. 3B), 86 MM patients were not given 1 no visit during the follow-up period, and the median of hsa_circ_0007841 expression level in bone marrow of MM patients was used as a dividing boundary value and divided into two groups of hsa_circ_0007841 high and low expression. The value of hsa_circ_0007841 for MM prognosis was evaluated based on disease Progression Free Survival (PFS). Survival analysis showed that hsa_circ_0007841 high expression was significantly correlated with MM poor prognosis (log-rank p=0.0206).

Prognostic markers can be used to identify the likelihood of disease recurrence and to predict patient survival. Since MM patient prognosis is closely related to gene mutation, we analyzed the correlation of bone marrow hsa_circ_0007841 expression with cytogenetic variation, and found that high expression hsa_circ_0007841 correlated with MM patient chromosome t (4; 14), t (14; 16), with gene TP53, ATR and EGR1 mutations, but with 13q14 deletion (p=0.0288), and with supercoloid (p= 0.3722) (table 3).

2.6 Prediction and annotation of hsa_circ_0007841 targeting miRNA and mRNA networks

We predicted the circRNA-miRNA-mRNA network using the Arraystar miRNA target prediction software TargetScan and MiRanda, identified miRNA and candidate mRNAs that bound to hsa_circ_220, and we performed the circRNA-miRNA interaction network prediction on the circinterome database (FIG. 4A). A total of 8 differential mirnas and 10 candidate mrnas interacted with hsa_circ_0007841, and fig. 4B shows that predicted mRNA might be involved in multiple pathways. Therefore, there is a need to further study the mechanism of hsa_circ_0007841 in the MM process.

TABLE 1 primer sequences of candidate circRNA for qRT-PCR validation

Table 2: correlation of the relative expression of hsa_circ_0007841 in 86 MM patients with clinical pathology

MM: multiple myeloma; SD: standard deviation; RISS: a revised international staging system; * P <0.05

Table 3: cytogenetic abnormal status distribution between low/high hsa_circ_0007841 expression groups of MM patients

MM: multiple myeloma; * P <0.05

Sequence listing

<110> Xiangya three Hospital at university of south China

<120> application of multiple myeloma biomarker hsa_circ_0007841

<160> 11

<170> SIPOSequenceListing 1.0

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<211> 264

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tatttggcat gatcattact atcggccagt ctatcgtgta tgtgatgacc gggatgtatg 60

gggacccttc tgaaatgggt gctggaattt gcctgctaat caccattcag ctctttgttg 120

ctggcttaat tgtcctactt ttggatgaac tcctgcaaaa aggatatggc cttggctctg 180

gtatttctct cttcattgca actaacatct gtgaaaccat cgtatggaag gcattcagcc 240

ccactactgt caacactggc cgag 264

<210> 2

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<212> DNA

<213> Artificial sequence (Artificial Sequence)

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ctaacatctg tgaaaccatc gt 22

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tcatcacata cacgatagac tgg 23

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acaaatctgg ctctggcacc 20

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gaggtagaca gatgagacgc ca 22

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ctggacttca accgaaattt ga 22

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gctcctcatg gacatccttt g 21

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ctacctgagc cagttctcct aa 22

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gggttcctca tcggtgtaat 20

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gtggccgagg actttgattg 20

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cctgtaacaa cgcatctcat att 23

Claims (9)

1. Application of a reagent for detecting hsa_circ_0007841 in preparation of a multiple myeloma diagnostic reagent, wherein the sequence of hsa_circ_0007841 is shown as SEQ ID No. 1.

2. The use of claim 1, wherein the diagnostic reagent for multiple myeloma comprises a PCR reagent.

3. The use according to claim 2, wherein the PCR reagents comprise primers for detecting hsa_circ_0007841, having the sequence:

F:5’CTAACATCTGTGAAACCATCGT 3’

R:5’TCATCACATACACGATAGACTGG 3’。

4. application of a reagent for detecting hsa_circ_0007841 in preparation of a multiple myeloma prognostic reagent, wherein the sequence of hsa_circ_0007841 is shown as SEQ ID No. 1.

5. The use of claim 4, wherein the prognostic reagent for multiple myeloma comprises a PCR reagent.

6. The use according to claim 5, wherein the PCR reagent comprises primers for detecting hsa_circ_0007841, the sequence being:

F:5’CTAACATCTGTGAAACCATCGT 3’

R:5’TCATCACATACACGATAGACTGG 3’。

7. application of a reagent for detecting hsa_circ_0007841 in preparation of a bortezomib drug resistance reagent for detecting patients with multiple myeloma is provided, wherein the sequence of hsa_circ_0007841 is shown in SEQ ID No. 1.

8. The use according to claim 7, wherein the agent for detecting bortezomib resistance in patients with multiple myeloma comprises a PCR agent.

9. The use according to claim 8, wherein the PCR reagents comprise primers for detecting hsa_circ_0007841, having the sequence:

F:5’CTAACATCTGTGAAACCATCGT 3’

R:5’TCATCACATACACGATAGACTGG 3’。

Images