Hepatocellular carcinoma (HCC) is one of the most common cancers globally with relatively high morbidity and mortality [
Accumulating evidence highlights the critical roles of long noncoding RNA (lncRNA) in the initiation and progression of HCC. The lncRNAs, which are defined as noncoding RNA
Previous studies have reported that serum PTENP1 can distinguish patients with gastric cancer or clear cell renal cell carcinoma from healthy controls [
A total of 298 individuals were enrolled in the study (129 patients with HCC, 27 patients with CHB, 49 patients with LC, and 93 healthy controls). All patients were recruited from the First Affiliated Hospital of Fujian Medical University between September 2017 and May 2019. The patients with HCC were histologically confirmed. Patients with CHB were diagnosed according to the Clinical Practice Guidelines on the management of hepatitis B virus infection of EASL in 2017. Patients with LC were verified according to the American Association for the Study of Liver Diseases Practice Guidelines. Clinical characteristics of patients were obtained from the medical records retrospectively, including age, gender, HBV surface antigen (HBsAg), tumor number, and tumor size. As a healthy control, 93 individuals who performed their annual health check at the hospital and did not have any liver diseases or other cancerous diseases were recruited. Written informed consent was obtained from each participant, and the study was approved by the Ethics Committee of the First Affiliated Hospital of Fujian Medical University (2018[048]).
Peripheral blood samples were collected in a separate vacuum tube from all participants before surgery, pharmacological intervention, or chemotherapy. The serum was isolated by centrifugation at 3,000 rpm for 10 min. After that, the isolated serum was immediately transferred and then stored at −80°C for further analysis.
Total RNA was extracted from serum samples using a Hipure Liquid RNA Kit (Cat# R4163-03, Magen, Guangzhou, China). The RNA quantity and purity were evaluated via the NanoDrop One spectrophotometer (Thermo Scientific, Wilmington, DE, USA). The purified RNA was reversely transcribed into cDNA using the M-MLV Reverse Transcriptase (Cat# M1701, Promega, Madison WI, USA). Then, the levels of lncRNAs were assessed by qRT-PCR using TB Green™ Premix Ex Taq (Cat# RR420A, Takara, Dalian, China) which was performed on the QuantStudio Real Time PCR system (Applied Biosystems, Foster City, CA, USA). All reactions were performed with the following conditions: 95°C for 30 seconds, 45 cycles of 95°C for 5 seconds, and 60°C for 30 seconds. The specificity of the PCR products was ensured by melting curve analysis following each reaction. The relative expression of each lncRNA was determined using the 2−
Sequences of primers used in this study.
qRT-PCR primers | Sequences | |
---|---|---|
HULC | Sense | ATCTGCAAGCCAGGAAGAGTC |
Antisense | CTTGCTTGATGCTTTGGTCTGT | |
MALAT1 | Sense | AAAGCAAGGTCTCCCCACAAG |
Antisense | GGTCTGTGCTAGATCAAAAGGCA | |
Linc00152 | Sense | GACTGGATGGTCGCTGCTTT |
Antisense | CCCAGGAACTGTGCTGTGAA | |
PTENP1 | Sense | CATTCTTGCATGTATTTGGGTTAGG |
Antisense | GGTATATGGTCCAGAGTCCAGC | |
PTTG3P | Sense | GGGGTCTGGACCTTCAATCAA |
Antisense | GCTTTAGGTAAGGATGTGGGA | |
SPRY4-IT1 | Sense | GTTTTTGCTGAGCTGGTGGTT |
Antisense | ATGGCTCCACTGGGCATATT | |
UBE2CP3 | Sense | AAGTGGTCTGCCCTGTATGATG |
Antisense | GAGCTATCAATGTTGGGTTTGC | |
UCA1 | Sense | TGCACCCTAGACCCGAAACT |
Antisense | CAAGTGTGACCAGGGACTGC | |
GAPDH | Sense | GGGAAACTGTGGCGTGAT |
Antisense | GAGTGGGTGTCGCTGTTGA |
Serum alanine aminotransferase (ALT), aspartic transaminase (AST), gamma-glutamyl transpeptidase (GGT), total protein (TP), and albumin (ALB) were measured on the ADVIA 2400 clinical chemistry analyzer (Siemens, Germany). Serum AFP was detected on the Roche Cobas analyzer (Roche Diagnostics, Mannheim, Germany).
Statistical analysis was carried out by SPSS 23.0 software (SPSS Inc., Chicago, IL, USA) and GraphPad prism 7.0 software (GraphPad Software, Inc., La Jolla, CA, USA). Specifically, the Kolmogorov-Smirnov test was performed to analyze the normal distribution of the variables. If the variables were normally distributed, they were presented as the
A total of 298 individuals including 129 patients with HCC, 27 patients with CHB, 49 patients with LC, and 93 healthy controls were enrolled into this study. Table
Demographics of healthy controls and patient with CHB, LC, and HCC.
Features | HC | CHB | LC | HCC |
---|---|---|---|---|
Number | 93 | 27 | 49 | 129 |
Age | 55 (21-79) | 52 (33-71) | 58 (35-87) | 59 (23-88) |
Male/female | 69/24 | 21/6 | 32/17 | 111/18 |
AFP (ng/mL) | 2.22 (0.68-6.70) | 2.62 (0.95-569.0) | 4.03 (0.61-759.0) | 38.50 (0.61-22484.0) |
GGT (U/L) | 16 (7-59) | 36 (8-209) | 64.5 (9-759) | 80 (13-2000) |
ALT (U/L) | 18 (9-46) | 28 (12-2112) | 29.5 (8-1688) | 37 (7-1198) |
AST (U/L) | 20 (14-38) | 25 (18-1856) | 54 (16-639) | 41 (17-1474) |
TP (g/L) | 73.7 (65.1-81.8) | 71.1 (59.1-77) | 63.7 (48.6-78.2) | 68.6 (43.4-84.8) |
ALB (g/L) | 45.5 (40.5-50.5) | 45.1 (28-49.2) | 28.8 (22.5-28.6) | 40.1 (21.4-48.9) |
HC: healthy control; HCC: hepatocellular carcinoma; CHB: chronic hepatitis B; LC: liver cirrhosis; AFP: alpha fetoprotein; GGT: gamma-glutamyl transpeptidase; ALT: alanine aminotransferase; AST: aspartic transaminase; TP: total protein; ALB: albumin.
As shown in Figure
The levels of eight serum lncRNAs in patients with HCC, CHB, LC and healthy controls. The relative expression levels of lncRNAs HULC (a), MALAT1 (b), Linc00152 (c), PTENP1 (d), PTTG3P (e), SPRY4-IT1 (f), UBE2CP3 (g), and UCA1 (h) in the serum of patients with HCC (
We further investigated the associations between the serum levels of eight lncRNAs and clinicopathological features in patients with HCC. Our results showed that serum Linc00152 were positively correlated with GGT (
Correlation between serum level of lncRNAs HULC, MALAT1, and Linc00152 and clinicopathological characteristics in 129 HCC patients.
Features | HULC | MALAT1 | Linc00152 | ||||||
---|---|---|---|---|---|---|---|---|---|
Low ( | High ( | Low ( | High ( | Low ( | High ( | ||||
Gender | 0.327 | 0.327 | 0.636 | ||||||
Male | 54 | 57 | 54 | 57 | 55 | 56 | |||
Female | 11 | 7 | 11 | 7 | 10 | 8 | |||
Age | 0.333 | 0.333 | 0.801 | ||||||
≤55 | 24 | 29 | 24 | 29 | 26 | 27 | |||
>55 | 41 | 35 | 41 | 35 | 39 | 37 | |||
HBsAg | 0.270 | 0.314 | 0.796 | ||||||
Positive | 53 | 47 | 48 | 52 | 51 | 49 | |||
Negative | 12 | 17 | 17 | 12 | 14 | 15 | |||
AFP level | 0.781 | 0.323 | 0.127 | ||||||
≤20 ng/mL | 29 | 27 | 31 | 25 | 33 | 41 | |||
>20 ng/mL | 36 | 37 | 34 | 39 | 32 | 23 | |||
Tumor size | 0.897 | 0.530 | 0.315 | ||||||
≤3 cm | 21 | 20 | 19 | 22 | 18 | 23 | |||
>3 cm | 44 | 44 | 46 | 42 | 47 | 41 | |||
Tumor number | 0.611 | 0.668 | 0.611 | ||||||
Single | 55 | 52 | 53 | 54 | 55 | 52 | |||
Multiple | 10 | 12 | 12 | 10 | 10 | 12 | |||
GGT (U/L) | 80 (14-2000) | 77 (13-1034) | 0.944 | 80 (13-2000) | 84 (14-1034) | 0.265 | 61 (13-697) | 98 (15-2000) | 0.012 |
ALT (U/L) | 40 (7-451) | 37 (12-1198) | 0.944 | 37 (7-621) | 37.5 (12-1198) | 0.929 | 34 (7-668) | 40 (12-1198) | 0.378 |
AST (U/L) | 47 (17-577) | 41 (17-1474) | 0.901 | 38 (18-577) | 51 (17-1474) | 0.142 | 36 (17-577) | 48 (17-1474) | 0.077 |
TP (g/L) | 69.5 (56.0-80.6) | 68.3 (43.4-84.8) | 0.376 | 68.8 (55.3-84.8) | 68.3 (43.4-84.2) | 0.232 | 68.4 (46.8-79) | 68.7 (43.4-84.8) | 0.644 |
ALB (g/L) | 40.3 (23.9-48.9) | 39.3 (21.4-48.6) | 0.564 | 40.3 (23.8-48.9) | 39.2 (21.4-47.7) | 0.170 | 40.0 (23.9-47.2) | 40.2 (21.4-48.9) | 0.888 |
Correlation between serum lncRNAs and clinicopathological characteristics. (a) The level of GGT in patients with low level of Linc00152 (
Correlation between serum level of lncRNAs PTENP1, PTTG3P, and SPRY4-IT1 and clinicopathological characteristics in 129 HCC patients.
Features | PTENP1 | PTTG3P | SPRY4-IT1 | ||||||
---|---|---|---|---|---|---|---|---|---|
Low ( | High ( | Low ( | High ( | Low ( | High ( | ||||
Gender | 0.972 | 0.136 | 0.636 | ||||||
Male | 56 | 55 | 53 | 58 | 55 | 56 | |||
Female | 9 | 9 | 12 | 6 | 10 | 8 | |||
Age | 0.124 | 0.185 | 0.016 | ||||||
≤55 | 31 | 22 | 23 | 30 | 20 | 33 | |||
>55 | 34 | 42 | 42 | 34 | 45 | 31 | |||
HBsAg | 0.558 | 0.870 | 0.496 | ||||||
Positive | 49 | 51 | 50 | 50 | 52 | 48 | |||
Negative | 16 | 13 | 15 | 14 | 13 | 16 | |||
AFP level | 0.064 | 0.089 | 0.858 | ||||||
≤20 ng/mL | 23 | 33 | 33 | 23 | 28 | 27 | |||
>20 ng/mL | 42 | 31 | 32 | 41 | 36 | 37 | |||
Tumor size | 0.897 | 0.612 | 0.530 | ||||||
≤3 cm | 21 | 20 | 22 | 19 | 19 | 22 | |||
>3 cm | 44 | 44 | 43 | 45 | 46 | 42 | |||
Tumor number | 0.968 | 0.329 | 0.329 | ||||||
Single | 54 | 53 | 56 | 51 | 56 | 51 | |||
Multiple | 11 | 11 | 9 | 13 | 9 | 13 | |||
GGT (U/L) | 90 (14-1034) | 79.5 (13-2000) | 0.611 | 70 (13-2000) | 85.5 (14-1034) | 0.042 | 86 (13-2000) | 65 (15-710) | 0.517 |
ALT (U/L) | 38 (12-1198) | 35 (7-402) | 0.202 | 33 (7-402) | 42.5 (12-1198) | 0.316 | 33.5 (12-621) | 49 (7-1198) | 0.016 |
AST (U/L) | 50 (17-1474) | 38 (17-577) | 0.306 | 37 (18-577) | 52 (17-1474) | 0.095 | 36.5 (17-412) | 50 (18-1474) | 0.097 |
TP (g/L) | 68.2 (43.4-84.8) | 69.1 (55.5-80.6) | 0.504 | 68.6 (55.5-80.6) | 68.6 (43.4-84.8) | 0.983 | 68.6 (46.8-80.6) | 68.7 (43.4-84.8) | 0.243 |
ALB (g/L) | 39.4 (21.4-48.6) | 40.5 (23.8-48.9) | 0.301 | 40.3 (23.8-48.9) | 39.5 (21.4-48.6) | 0.539 | 39.6 (21.4-48.9) | 40.2 (23.6-48.6) | 0.468 |
Correlation between serum level of lncRNAs UBE2CP3 and UCA1 and clinicopathological characteristics in 129 HCC patients.
Features | UBE2CP3 | UCA1 | ||||
---|---|---|---|---|---|---|
Low ( | High ( | Low ( | High ( | |||
Gender | 0.636 | 0.972 | ||||
Male | 55 | 56 | 55 | 56 | ||
Female | 10 | 8 | 9 | 9 | ||
Age | 0.092 | 0.058 | ||||
≤55 | 22 | 31 | 21 | 32 | ||
>55 | 43 | 33 | 43 | 33 | ||
HBsAg | 0.796 | 0.558 | ||||
Positive | 51 | 49 | 51 | 49 | ||
Negative | 14 | 15 | 13 | 16 | ||
AFP level | 0.372 | 0.702 | ||||
≤20 ng/mL | 30 | 25 | 26 | 29 | ||
>20 ng/mL | 34 | 39 | 37 | 36 | ||
Tumor size | 0.803 | 0.803 | ||||
≤3 cm | 20 | 21 | 21 | 20 | ||
>3 cm | 45 | 43 | 43 | 45 | ||
Tumor number | 0.329 | 0.668 | ||||
Single | 56 | 51 | 54 | 53 | ||
Multiple | 9 | 13 | 10 | 12 | ||
GGT (U/L) | 67 (13-888) | 83.5 (14-2000) | 0.182 | 72.5 (13-2000) | 81 (14-1034) | 0.156 |
ALT (U/L) | 36 (7-338) | 38 (12-1198) | 0.617 | 42 (7-402) | 37 (12-1198) | 0.871 |
AST (U/L) | 37 (18-577) | 47.5 (17-1474) | 0.170 | 38.5 (17-577) | 42 (17-1474) | 0.821 |
TP (g/L) | 69.5 (56.8-80.6) | 67.8 (43.4-84.8) | 0.171 | 69.1 (55.3-80.6) | 68.4 (43.4-84.8) | 0.858 |
ALB (g/L) | 40.3 (23.9-48.9) | 39.2 (21.4-48.6) | 0.414 | 40.4 (23.8-47.2) | 39.4 (21.4-48.9) | 0.391 |
AFP: alpha fetoprotein; GGT: gamma-glutamyl transpeptidase; ALT: alanine aminotransferase; AST: aspartic transaminase; TP: total protein; ALB: albumin.
Figures
The diagnostic value of serum lncRNAs in patients with HCC. (a) The diagnostic value of HULC, MALAT1, Linc00152, PTENP1, PTTG3P, SPRY4-IT1, UBE2CP3, and UCA1 was evaluated by ROC analysis when patients with HCC were tested against patients with healthy controls. (b) Diagnosis efficacy for HULC, MALAT1, Linc00152, PTENP1, PTTG3P, SPRY4-IT1, UBE2CP3, and UCA1 to distinguish HCC patients from CHB patients, LC patients, and healthy controls. (c) Diagnosis efficacy of the combinations of serum lncRNAs with AFP to discriminate HCC from CHB patients, LC patients, and healthy controls. (d) Diagnosis efficacy of the diagnostic panel established by serum lncRNAs (Linc00512 and UCA1) and AFP.
Performance of AFP, HULC, MALAT1, Linc00152, PTENP1, PTTG3P, SPRY4-IT1, UBE2CP3, and UCA1 in HC and patients with HCC, CHB, and LC.
Method | HCC vs. HC | HCC vs. others# | ||||
---|---|---|---|---|---|---|
AUC (95% CI) | SEN (%) | SPE (%) | AUC (95% CI) | SEN (%) | SPE (%) | |
AFP | 0.862 (0.815-0.909) | 65.9 | 97.8 | 0.811 (0.761-0.861) | 65.1 | 85.8 |
HULC | 0.796 (0.734-0.858) | 86.0 | 62.4 | 0.756 (0.702-0.810) | 86.0 | 55.6 |
MALAT1 | 0.768 (0.706-0.830) | 59.7 | 80.6 | 0.733 (0.676-0.790) | 59.7 | 75.7 |
Linc00152 | 0.895 (0.854-0.936) | 78.3 | 89.2 | 0.877 (0.835-0.918) | 81.4 | 82.8 |
PTENP1 | 0.602 (0.526-0.678) | 89.1 | 29.0 | 0.530 (0.465-0.596) | 89.1 | 23.1 |
PTTG3P | 0.785 (0.723-0.847) | 82.9 | 61.3 | 0.768 (0.715-0.820) | 82.9 | 57.4 |
SPRY4-IT1 | 0.808 (0.750-0.866) | 76.7 | 71.0 | 0.768 (0.715-0.821) | 76.7 | 67.5 |
UBE2CP3 | 0.812 (0.754-0.870) | 88.4 | 62.4 | 0.756 (0.702-0.810) | 78.3 | 60.4 |
UCA1 | 0.858 (0.810-0.907) | 81.4 | 75.3 | 0.809 (0.761-0.857) | 67.4 | 80.5 |
#Others include HC, CHB patients, and LC patients. HCC: hepatocellular carcinoma; HC: healthy control; CHB: chronic hepatitis B; LC: liver cirrhosis; AFP: alpha fetoprotein; AUC: area under curve; CI: confidence interval; SEN: sensitivity; SPE: specificity.
We further explored whether the relative levels of the 8 lncRNAs could discriminate HCC patients from patients with CHB and LC. As shown in Figure
Given the fact that AFP is one of the most common markers used for HCC screening and diagnosis, we also evaluated the combinations of these seven lncRNAs with AFP for the diagnosis of HCC. The AUC value, 95% CI, sensitivity, and specificity for the combinations of serum lncRNAs and AFP to discriminate HCC from CHB patients, LC patients, and healthy individuals are listed in Table
The performance for the combination of serum lncRNAs and AFP in HC, HCC patients, CHB patients, and LC patients.
Method | AUC (95% CI) | SEN (%) | SPE (%) |
---|---|---|---|
HULC+AFP | 0.848 (0.806-0.890) | 81.4 | 73.4 |
MALAT1+AFP | 0.820 (0.771-0.870) | 62.0 | 92.3 |
Linc00152+AFP | 0.906 (0.870-0.942) | 85.3 | 84.0 |
PTTG3P+AFP | 0.837 (0.793-0.881) | 69.0 | 81.1 |
SPRY4-IT1+AFP | 0.847 (0.803-0.890) | 72.9 | 79.3 |
UBE2CP3+AFP | 0.837 (0.792-0.882) | 63.6 | 87.0 |
UCA1+AFP | 0.878 (0.841-0.916) | 71.3 | 88.8 |
Panel# | 0.912 (0.878-0.945) | 82.9 | 88.2 |
HCC: hepatocellular carcinoma; HC: healthy control; CHB: chronic hepatitis B; LC: liver cirrhosis; AFP: alpha fetoprotein; AUC: area under curve; CI: confidence interval; SEN: sensitivity; SPE: specificity. #Panel includes Linc00152, UCA1, and AFP. Backward stepwise selection was used to determine the diagnostic values of serum lncRNAs for HCC. In this study, the combination of Linc00152, PTENP1, UCA1, and AFP (3-lncRNA panel) was chosen as the strongest panel for diagnostic markers. The other lncRNAs were excluded by a stepwise procedure. The regression equation:
Based on these data, a stepwise regression model was established to get the strongest panel for predicting HCC. Finally, two lncRNAs (Linc00152 and UCA1) and AFP were enrolled. The final formula was listed as follows:
HCC is an aggressive tumor with high rates of recurrence and metastasis, which leads to the poor prognosis. Therefore, it is of great value to find an effective biomarker for the early diagnosis and therapy of HCC. Previous studies have confirmed that lncRNAs are detectable and also stable in serum of cancer patients, making it possible to be utilized as diagnostic biomarkers for various cancers [
In this study, we selected eight lncRNAs (HULC, MALAT1, Linc00152, PTENP1, PTTG3P, SPRY4-IT1, UBE2CP3, and UCA1) from previously published HCC-related studies [
Next, we also investigated the correlations between these circulating lncRNAs and clinicopathological features. A significant association between serum Linc00152 and GGT as well as serum PTTG3P and GGT was demonstrated in patients with HCC. GGT is an enzyme which can be induced by intrahepatic obstruction or directly synthesized by liver cancer cells in HCC [
To further investigate the diagnostic values of these lncRNAs, ROC curve analysis was performed. The AUC of the single lncRNA in our study is similar to some previous studies [
Previously, most of the HCC-related lncRNAs focus on single molecule when exploring the potential of lncRNA as novel biomarkers. However, the diagnostic accuracy of any single index is limited. Several studies have already developed several multiple biomarker panels to increase diagnostic accuracy, such as the lncRNA panel established by lncRNA-LET, PVT1, PANDAR, PTENP1, and linc00963 for the diagnosis of clear cell renal cell carcinoma [
There are a few limitations to our study. First, we did not validate the diagnostic efficacy of the panel in another set. Second, our study was performed at a single center with relatively limited sample size. Thus, further investigations and large-scale multicenter studies are strongly recommended to fully validate this novel panel. Third, apart from AFP, AFPL3 and PIVKA-II are also common markers for HCC diagnosis. The comparisons between the diagnostic values of these serum lncRNAs and AFPL3 and PIVKA-II for HCC are also recommended for a further study.
In summary, we established a diagnostic panel consisting of serum lncRNA linc00152, UCA1, and tumor marker AFP with superior sensitivity and specificity to diagnose HCC. This panel might serve as a novel and noninvasive biomarker for HCC diagnosis.
Alpha fetoprotein
Albumin
Alanine aminotransferase
Aspartic transaminase
Area under curve
Chronic hepatitis B
Confidence interval
Gamma-glutamyl transpeptidase
HBV surface antigen
Healthy control
Hepatocellular carcinoma
Highly upregulated in liver cancer
Liver cirrhosis
Long noncoding RNA
Metastasis-associated lung adenocarcinoma transcript 1
Phosphatase and tensin homolog pseudogene 1
Pituitary tumor-transforming 3, pseudogene
Quantitative real-time polymerase chain reaction
Receiver operating characteristic curve
SPRY4 intronic transcript 1
Total protein
Ubiquitin conjugating enzyme E2 C pseudogene 3
Urothelial carcinoma-associated 1.
The data that support the findings of this study are not publicly available due to privacy and ethical restrictions but are available from the corresponding author on reasonable request.
The authors declare no conflict of interest.
Jinlan Huang and Yansong Zheng contributed equally to this work.
This work was supported by grants from the National Natural Science Foundation of China (81802087), the youth project of Fujian Provincial Health and Family Planning Commission (2017-1-47), the Natural Science Foundation of Fujian Province (2018J05130), and the Qihang Project of Fujian Medical University (2017XQ1053). We thank the biomedical laboratory scientists for the excellent technical assistance with handling of blood samples. We also thank the patients for their participation in this study.