Clinicopathological and Prognostic Value of Gastric Carcinoma Highly Expressed Transcript 1 in Cancer: A Meta-Analysis

Zhou, Xi; Fan, Yanghua; He, Yu; Mou, Anna; Wang, Fu; Liu, Yong; Wu, Zhen

doi:https://doi.org/10.1155/2020/6341093

Journal of Oncology

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Abstract Background Materials and Methods Results Discussion Limitations Conclusions Abbreviations Data Availability Conflicts of Interest Authors’ Contributions Acknowledgments References Copyright Related Articles

Research Article | Open Access

Volume 2020 | Article ID 6341093 | https://doi.org/10.1155/2020/6341093

Clinicopathological and Prognostic Value of Gastric Carcinoma Highly Expressed Transcript 1 in Cancer: A Meta-Analysis

Xi Zhou,¹Yanghua Fan,²Yu He,³Anna Mou,⁴Fu Wang,⁵Yong Liu,¹and Zhen Wu²

Academic Editor: Nicola Silvestris

Received28 Apr 2020

Revised20 Jul 2020

Accepted24 Jul 2020

Published26 Aug 2020

Abstract

Background. Long noncoding RNA gastric cancer highly expressed transcript 1 (lncRNA GHET1) is often reported to be abnormally expressed in multiple cancers, but the situation is different in different cancers. Therefore, a meta-analysis is necessary to clarify the value of lncRNA GHET1 as a prognostic indicator in cancer. Methods. Relevant research studies on lncRNA GHET1 and cancer were retrieved from three electronic literature databases of Web of Science, PubMed, and OVID. Meanwhile, hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated to explore the relationship between lncRNA GHET1 expression and survival of cancer patients. The odds ratios (ORs) and 95% CIs were calculated to assess the association of lncRNA GHET1 expression with pathological parameters of cancer patients. Results. The meta-analysis included a total of 11 studies involving 714 cancer patients. The pooled HR suggests that high lncRNA GHET1 expression is associated with poor overall survival. In addition, high expression of lncRNA GHET1 was found to be associated with larger tumor size, poor histological grade, high tumor stage, lymph node metastasis, and distant metastasis. Conclusions. High lncRNA GHET1 expression can predict poor survival and pathological parameters. And lncRNA GHET1 could serve as a new indicator in multiple cancers.

1. Background

Cancer is still the main disease that threatens people's lives and health. The American Cancer Society estimates new cancer cases and deaths in the USA every year, and 1,806,590 new cancer cases and 606,520 cancer deaths are expected in the USA according to Cancer Statistics in 2020 [1]. Nevertheless, cancer is a genetically heterogeneous disease with a poor prognosis. Finding new gene therapy targets is still a hot topic.

Long noncoding RNA (lncRNA) is a type of RNA with a length >200 nt and lacking or no open reading frame (ORF). The number of lncRNA is much lower than that of encoding protein genes (mRNA). More and more studies show that lncRNA has important functions such as transcription and epigenetic regulation in diseases [2, 3]. At the same time, recent studies have shown that lncRNA is closely related to the occurrence, development, invasion, metastasis, and prognosis of cancer [4–7], and lncRNA may be used as a new cancer treatment marker [8–10].

lncRNA gastric carcinoma highly expressed transcript 1 (lncRNA GHET1, AK123072), a recently identified lncRNA discovered in 2014, is located on chromosome 7q36.1 in the human genome [11]. In the meantime, GHET1 is found to play a critical role in the progression of gastric carcinoma, which is achieved through promoting the c-Myc stability. An increasing number of studies have been carried out to examine the role of lncRNA GHET1 in cancers, which reveal that lncRNA GHET1 is dysregulated in multiple cancers and that it plays an important role in tumor growth, metastasis, and invasion, as well as poor patient survival [11, 12]. lncRNA GHET1 may affect tumor metastasis and prognosis; however, a majority of existing studies are limited by their small sample sizes and discrete outcomes. As a consequence, an updated meta-analysis was performed in this study to determine the prognostic value of lncRNA GHET1 in cancer patients.

2. Materials and Methods

2.1. Literature Collection

First, this systematic review and meta-analysis is reported in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) Statement. Then, articles regarding lncRNA GHET1 as a prognostic biomarker for the survival of cancer patients were systematically retrieved in three online databases (PubMed, Web of Science, and OVID) from inception to January 20, 2019, by two authors independently in accordance with the standard guidelines for meta-analyses [13, 14]. Text word and MeSH strategy were adjusted according to the database in this retrieval, which included the following terms (“Long non-coding RNA Gastric Carcinoma High Expressed Transcript 1” or “Gastric Carcinoma Proliferation Enhancing Transcript 1” or “LncRNA GHET1”) and (“recurrence” or “outcome” or “survival,” “cancer” or “neoplasm” or “tumor” or “carcinoma,” “prognosis” or “prognostic”). Additionally, the reference lists of the relevant articles were also manually retrieved to prevent any missed articles.

2.2. Study Selection

All the included studies were evaluated, and data were extracted by two authors independently. The study inclusion criteria were as follows: (1) studies in which all tumors were confirmed by histological or pathological examinations; (2) studies in which lncRNA GHET1 expression in human tumor tissues was measured and patients were grouped in accordance with the lncRNA GHET1 expression level; (3) studies that performed statistical analyses on the pathological or patient survival parameters concerned with lncRNA GHET1 expression, such as overall survival (OS), high tumor stage (HTS), lymph node metastasis (LNM), or larger tumor size (LTS); and (4) studies with sufficient original data.

Besides, the study exclusion criteria were as follows: nonhuman studies and non-English studies; editorials, reviews, and expert opinions as well as letters; database analysis without original data; and studies concerning the functions of lncRNA GHET1 only but without the molecular mechanism analysis.

2.3. Data Extraction

Relevant data were examined and extracted from the original articles by two reviewers independently. Any disagreement between them was solved through the consensus with a third reviewer. A series of data were collected for this meta-analysis, including surname of the first author, publication year, country, tumor type, sample size, number of patients with LTS, poor histological grade (PHG), HTS, LNM, and distant metastasis (DM), reference gene and detection method of lncRNA GHET1, HRs and 95% CIs of elevated lncRNA GHET1 for OS, threshold of lncRNA GHET1 expression level, and the Newcastle–Ottawa scale (NOS) score.

2.4. Statistical Methods

The Stata version 12.0 software was adopted for all statistical analyses. In addition, the Q and I² tests were conducted to detect the potential heterogeneity, the results of which indicated significant heterogeneity in this meta-analysis (I² ≥ 50% and < 0.1) [15]. Typically, a fixed- or a random-effects model should be adopted according to the results of heterogeneity analysis. In our meta-analysis, the random-effects model should be adopted in the presence of significant heterogeneity among the studies. Afterwards, the potential publication bias was also assessed by Egger’s test and Begg’s funnel plot. Notably, the aggregated ORs and HRs should also be extracted from the published data, and the crude HRs should be adopted if they could be obtained directly from the publications. For HRs and the corresponding 95% CIs that were not directly reported in the studies, the survival data extracted from Kaplan–Meier curves would be utilized to estimate the HRs. To summarize the survival outcome, both the SE and the log HR should be adopted [16]. Moreover, 95% CIs and ORs were pooled to assess the relationships of clinicopathological parameters (such as LTS, DM, LNM, and HTS) with lncRNA GHET1.

3. Results

3.1. Study Characteristics

Details of the study selection process are displayed in Figure 1. Eleven studies involving seven hundred and fourteen patients were enrolled in this meta-analysis according to the study exclusion and inclusion criteria [11, 17–26]. Table 1 summarizes the features of the eleven studies included in this meta-analysis. Typically, the sample size in these studies ranged from 42 to 105, with an average of 64.9. Besides, all the enrolled studies were published between 2014 and 2018 and were carried out in China. Among these studies, respective one study had focused on hepatocellular carcinoma (HCC) [18], bladder cancer (BC) [19], esophageal squamous cell carcinoma (ESCC) [20], head and neck cancer (HNC) [21], breast cancer (BRC) [23], osteosarcoma (OSC) [25], and pancreatic cancer (PC) [26], while two focused on non-small-cell lung cancer (NSCLC) [17, 22], and two concentrated on gastric cancer (GC) [11, 24]. All clinicopathological parameters were dependent on pathology. Concretely, GAPDH was found to be the reference gene of lncRNA GHET1 in all these studies.

3.2. Association of lncRNA GHET1 Expression with Survival

To assess the function of lncRNA GHET1 in the OS for cancer patients, the cumulative meta-analysis was carried out in this meta-analysis. In addition, the relationship of OS with lncRNA GHET1 was reported in eight studies involving 553 patients (Table 2). Typically, the fixed-effects model was adopted since there was no significant heterogeneity (I² = 0.0% and P_Q = 0.676). Our results indicated that OS was evidently related to lncRNA GHET1 (pooled HR = 2.28, 95% CI: 1.85–2.82; Figure 2(a)) in cancer patients. Besides, a sensitivity analysis was also performed, which had confirmed the robustness of these results (Figure 2(b)). Subsequently, subgroup analyses were further conducted based on the cancer type, sample size, and NOS score, and the results were consistent with those described previously (Table 3 and Figure 3).

(a)

(b)

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(b)

(c)

Taken together, these results revealed that a shorter OS might be associated with high lncRNA GHET1 expression in cancer patients; as a result, lncRNA GHET1 might serve as an independent factor of survival for cancer patients.

3.3. Association of the lncRNA GHET1 Expression Level with LTS

Figure 4(a) shows the association between LTS and lncRNA GHET1 expression identified from nine studies recruiting 582 patients. The random-effects model was adopted since there was a significant heterogeneity among these studies (I² = 44.8% and P_Q = 0.070). The pooled OR was 2.80 upon analysis (95% CI: 1.74–4.49; high versus low lncRNA GHET1 expression). Afterwards, a sensitivity analysis was carried out among all the included studies, and the heterogeneity had disappeared after excluding the study by Xia et al. (I² = 4% and P_Q = 0.399), with the OR between high versus low lncRNA GHET1 expression groups of 3.28 (95% CI: 2.30–4.67) (Figures 4(b) and 4(c)).

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(b)

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In accordance with these results, a significant difference was noted between the two groups. As far as the cancer patients were concerned, high lncRNA GHET1 expression could remarkably predict a higher risk of LTS.

3.4. Association between the lncRNA GHET1 Expression Level and PHG

In this meta-analysis, data regarding the association between the lncRNA GHET1 expression level and PHG were collected from the 409 cancer patients recruited in seven eligible studies. The fixed-effects model was adopted since no obvious heterogeneity was detected (I² = 13.1% and P_Q = 0.330). The OR between the high and low lncRNA GHET1 expression groups was 2.36 (95% CI: 1.56–3.57; Figure 5). Consistently, a significant difference was detected in the incidence of PHG between these two groups, suggesting a significant relationship between the risk of PHG and high lncRNA GHET1 expression.

3.5. Association between the lncRNA GHET1 Expression Level and HTS

In this meta-analysis, the correlation of HTS with lncRNA GHET1 expression was explored in seven eligible studies involving 438 patients. The fixed-effects model was selected (I² = 0.0% and P_Q = 0.975) in the absence of obvious heterogeneity. Our results indicated that HTS in cancer patients was associated with high lncRNA GHET1 expression (pooled OR = 4.06 and 95% CI: 2.71–6.09; Figure 6). Our results suggested that, compared with the low lncRNA GHET1 expression group, the HTS in the high expression group was evidently upregulated, demonstrating that the risk of HTS was notably correlated with high lncRNA GHET1 expression.

3.6. Association between the lncRNA GHET1 Expression Level and LNM

In this meta-analysis, data collected from the eight eligible studies involving 502 cancer patients would be examined. Similarly, the fixed-effects model would be adopted since there was no obvious heterogeneity (I² = 40.3% and P_Q = 0.110). The OR of the high versus low lncRNA GHET1 expression groups was 3.83 (95% CI: 2.60–5.65; Figure 7). Accordingly, a significant difference in the incidence of LNM was also discovered between these two groups. For cancer patients, high lncRNA GHET1 expression could well predict the high risk of LNM.

3.7. Association between the lncRNA GHET1 Expression Level and DM

In this meta-analysis, the correlation of HTS with lncRNA GHET1 expression was examined in five eligible studies recruiting 294 patients. The fixed-effects model was selected in this study since there was limited heterogeneity (I² = 0.0% and P_Q = 0.858). In addition, the OR of high versus low lncRNA GHET1 expression groups was 3.90 (95% CI: 2.12–7.15; Figure 8). Accordingly, a significant difference was detected in the incidence of DM between these two groups, which revealed that high lncRNA GHET1 expression could significantly predict a higher risk of incidence of DM in cancer patients.

3.8. Publication Bias

To evaluate the potential publication bias, Begg’s funnel plot and Egger's test were carried out in this meta-analysis. As could be observed from Figure 9, there was no evidence of obvious asymmetry for OS (Pr > |z| = 0.536; Figure 9(a)), LTS (Pr > |z| = 0.917 and P > |t| = 0.984; Figure 9(b)), PHG (Pr > |z| = 0.548 and P > |t| = 0.608; Figure 9(c)), HTS (Pr > |z| = 0.133 and P > |t| = 0.243; Figure 9(d)), LNM (Pr > |z| = 0.174 and P > |t| = 0.096; Figure 9(e)), and DM (Pr > |z| = 0.462 and P > |t| = 0.285; Figure 9(f)), upon analysis.

(a)

(b)

(c)

(d)

(e)

(f)

4. Discussion

As mentioned in our previous meta-analysis [27], cancer still poses a serious threat to human health, and the incidence of cancer is gradually increased in recent years [1]. However, the exact mechanism of metastasis remains unclear in cancer patients despite the fact that the occurrence of metastasis is an important indicator of poor prognosis for patients [28, 29]. On this account, it is necessary to identify the new molecular markers to predict tumor metastasis, which have been found to play critical roles in cancer treatment and prediction [30]. lncRNAs are one of these molecular markers, which can affect tumor genesis and development, and can easily collect biomarkers useful for monitoring and diagnosing tumors [31].

According to previous studies, lncRNA GHET1 has been proved to be an important oncogene in various human cancers, including NSCLC, HCC, BC, ESCC, HNC, BRC, GC, and PC [17–26]. It can be found based on the literature that lncRNA GHET1 may play an important role in cancer progression, which is achieved through regulating the LATS1/YAP signaling pathway and epithelial-mesenchymal transition (EMT). Additionally, it is confirmed based on recent studies that lncRNA GHET1 expression is aberrantly high in HCC tissues and that lncRNA GHET1 silencing can inhibit the migration, proliferation, invasion, and EMT of HCC cells [32]. Moreover, the study by Shen et al. suggested that lncRNA GHET1 expression was remarkably higher in lung NSCLC specimens than in paracarcinoma tissues, and the progression-free survival (PFS) and OS of lncRNA NSCLC patients with lncRNA GHET1 overexpression are shorter than those of the patients with low expression [22]. lncRNA GHET1 has been proved that it could promote osteosarcoma and cervical cancer development and progression via Wnt/β-catenin signaling pathway [33, 34], and WNT might be an important marker for targeted cancer therapy [35].

Drug resistance is the main obstacle to successful chemotherapy for patients with cancer. The relationship between lncRNA GHET1 and drug resistance has been studied in gastric cancer and other solid tumors. It is to provide preclinical data for the translational research of lncRNA GHET1 in cancer treatment. Li et al. [36] found that high expression of lncRNA GHET1 was related with the low sensitivity to gemcitabine of BC, lncRNA GHET1 contributed to chemotherapeutic resistance to gemcitabine in BC through upregulating ABCC1 expression. Wei et al. summarized that ncRNAs may be a new therapeutic target and prognostic biomarker for GC [37]. And Zhang et al. reported that high lncRNA GHET1 expression could promote the development of multidrug resistance which was related to the Bax, Bcl-2, MDR1, and MRP1 gene expression in GC cells [38]. Besides, previous studies have shown that there is a specific regulatory relationship between lncRNA GHET1 and c-Myc in GC [11, 39]. Myc is a nuclear transcription factor that mainly regulates cell growth, cell cycle, metabolism, and survival. A number of studies have reported that c-Myc is closely related to the drug sensitivity of GC [40, 41]. These results suggest that lncRNA GHET1 and its associated molecules are closely related to tumor progression and drug sensitivity. Since the role of the hypoxic tumor microenvironment in chemotherapy failure has been increasingly considered in GC and other tumors recently [42,43], this might be a further direction to study the mechanism of lncRNA GHET1 regulating tumor drug resistance.

To further investigate the underlying mechanism, target, and function of lncRNA GHET1 in cancer, the potential targets, pathways, and related miRNA of lncRNA GHET1 had been systematically reviewed (Table 4). As mentioned above, the expression of lncRNA GHET1 is closely related to OS and clinicopathological characteristics. The reason may be that lncRNA GHET1 is closely related to P21, c-Myc, WNT, and other tumor proliferation, invasion, and prognosis molecular markers. However, the underlying mechanisms by which lncRNA GHET1 influenced the cancer remained unknown yet. This meta-analysis had discussed the prognostic value and clinicopathological significance of lncRNA GHET1 in cancer patients.

In this meta-analysis, data collected from the eleven eligible studies involving seven hundred and fourteen cancer patients were analyzed. Subsequently, a fixed- or a random-effects model was adopted depending on the results of heterogeneity analysis. For cancer patients, high lncRNA GHET1 expression might potentially serve as an indicator of poor prognosis. A significant difference in OS was detected between the high and low lncRNA GHET1 expression groups after pooling HRs from Cox multivariate analyses. In addition, high lncRNA GHET1 expression was found to be dramatically correlated with poor OS in various cancer types. Furthermore, high lncRNA GHET1 expression was also remarkably related to the clinicopathological parameters in cancer patients, including LTS, PHG, HTS, LNM, and DM. To sum up, findings in this study indicated that lncRNA GHET1 might serve as a valuable prognostic biomarker for the poor prognosis of most cancers.

5. Strengths and Limitations

When interpreting the conclusions of the current meta-analysis, several limitations should be taken into consideration. Firstly, all studies included in this meta-analysis were retrieved from three online databases; as a result, it was likely that some related papers might be missed. Secondly, after searching the database according to the inclusion and exclusion criteria, only ten studies came from China, so more research from other countries in the future is still needed to prove our conclusions. Thirdly, the cutoff values of the high- and low-expressed lncRNA GHET1 in these studies were not consistent. In addition, as bone spreading is also an important clinical feature related to tumor progression and prognosis, the role of lncRNA GHET1 in tumor-associated bone skeletal diffusion can be studied in the future. Finally, other factors that may affect cancer prognosis, such as treatment and tumor subgroup, were not included in this study. Because these included studies do not include these data, this may be an inherent shortcoming of this systematic review and meta-analysis.

6. Conclusions

To sum up, high lncRNA GHET1 expression in a series of cancers is associated with poor OS, LTS, PHG, HTS, LNM, and DM. As a result, lncRNA GHET1 can be used as a promising biomarker to predict tumor metastasis and prognosis in cancer patients.

Abbreviations

lncRNA GHET1:	Long noncoding RNA gastric carcinoma highly expressed transcript 1
LTS:	Larger tumor size
PHG:	Poor histological grade
HTS:	High tumor stage
LNM:	Lymph node metastasis
DM:	Distant metastasis
NSCLC:	Non-small-cell lung cancer
HCC:	Hepatocellular carcinoma
BC:	Bladder cancer
ESCC:	Esophageal squamous cell carcinoma
HNC:	Head and neck cancer
BRC:	Breast cancer
GC:	Gastric cancer
PC:	Pancreatic cancer
OS:	Overall survival
HR:	Hazard ratio
CI:	Confidence interval
NOS:	Newcastle–Ottawa scale
PCR:	Polymerase chain reaction
GAPDH:	Glyceraldehyde-3-phosphate dehydrogenase.

Data Availability

Meta-analysis is a secondary analysis, in which the data are all fully available without restriction, and all the material can be found in the included original studies.

Conflicts of Interest

The authors declare that there are no conflicts of interest regarding the publication of this paper.

Authors’ Contributions

XZ and YHF searched the electronic databases of PubMed, OVID, and Web of Science. XZ, YH, ANM, and YHF evaluated all of the included studies and extracted the data independently. YHF and YL extracted and examined the data from the original articles independently. YL, ZW, and FW resolved the disagreements in the literature assessment, and YHF was a major contributor in writing the manuscript. XZ, YHF, and YH contributed equally to this work.

Acknowledgments

This article was supported by the Graduate Innovation Fund of Peking Union Medical College (2018-1002-01-10) and the Science and Technology Development Program of Shandong Province (no. 2015GSF118110).

References

R. L. Siegel, K. D. Miller, and A. Jemal, “Cancer statistics, 2020,” CA: A Cancer Journal for Clinicians, vol. 70, no. 1, pp. 7–30, 2020.
View at: Publisher Site | Google Scholar
P. Johnsson, L. Lipovich, D. Grandér, and K. V. Morris, “Evolutionary conservation of long non-coding RNAs; sequence, structure, function,” Biochimica et Biophysica Acta (BBA) - General Subjects, vol. 1840, no. 3, pp. 1063–1071, 2014.
View at: Publisher Site | Google Scholar
Y.-H. Fan, H. Fang, C.-x. Ji, H. Xie, B. Xiao, and X.-G. Zhu, “Long noncoding RNA CCAT2 can predict metastasis and poor prognosis: a meta-analysis,” Clinica Chimica Acta, vol. 466, pp. 120–126, 2017.
View at: Publisher Site | Google Scholar
W. Dai, C. Tian, and S. Jin, “Effect of lncRNA ANRIL silencing on anoikis and cell cycle in human glioma via microRNA-203a,” OncoTargets and Therapy, vol. 11, pp. 5103–5109, 2018.
View at: Publisher Site | Google Scholar
Y. Zhou, D. L. Wang, and Q. Pang, “Long noncoding RNA SPRY4-IT1 is a prognostic factor for poor overall survival and has an oncogenic role in glioma,” European Review for Medical and Pharmacological Sciences, vol. 20, no. 14, pp. 3035–3039, 2016.
View at: Google Scholar
Y. Zheng, Y. Gao, X. Li et al., “Long non-coding RNA NAP1L6 promotes tumor progression and predicts poor prognosis in prostate cancer by targeting Inhibin-β A,” OncoTargets and Therapy, vol. 11, pp. 4965–4977, 2018.
View at: Publisher Site | Google Scholar
Q. Liu, H. Liu, H. Cheng, Y. Li, X. Li, and C. Zhu, “Downregulation of long noncoding RNA TUG1 inhibits proliferation and induces apoptosis through the TUG1/miR-142/ZEB2 axis in bladder cancer cells,” OncoTargets and Therapy, vol. 10, pp. 2461–2471, 2017.
View at: Publisher Site | Google Scholar
Z. Ma, H. Huang, Y. Xu et al., “Current advances of long non-coding RNA highly upregulated in liver cancer in human tumors,” OncoTargets and Therapy, vol. 10, pp. 4711–4717, 2017.
View at: Publisher Site | Google Scholar
Y. Fan, T. Yan, Y. Chai, Y. Jiang, and X. Zhu, “Long noncoding RNA HOTTIP as an independent prognostic marker in cancer,” Clinica Chimica Acta, vol. 482, pp. 224–230, 2018.
View at: Publisher Site | Google Scholar
Z. Du, T. Fei, R. G. W. Verhaak et al., “Integrative genomic analyses reveal clinically relevant long noncoding RNAs in human cancer,” Nature Structural & Molecular Biology, vol. 20, no. 7, pp. 908–913, 2013.
View at: Publisher Site | Google Scholar
F. Yang, X. Xue, L. Zheng et al., “Long non-coding RNA GHET1 promotes gastric carcinoma cell proliferation by increasing c-Myc mRNA stability,” FEBS Journal, vol. 281, no. 3, pp. 802–813, 2014.
View at: Publisher Site | Google Scholar
J. Zhou, X. Li, M. Wu, C. Lin, Y. Guo, and B. Tian, “Knockdown of long noncoding RNA GHET1 inhibits cell proliferation and invasion of colorectal cancer,” Oncology Research Featuring Preclinical and Clinical Cancer Therapeutics, vol. 23, no. 6, pp. 303–309, 2016.
View at: Publisher Site | Google Scholar
D. G. Altman, L. M. McShane, W. Sauerbrei, and S. E. Taube, “Reporting recommendations for tumor marker prognostic studies (REMARK): explanation and elaboration,” PLoS Medicine, vol. 9, no. 5, Article ID e1001216, 2012.
View at: Publisher Site | Google Scholar
A. L. Harris, “REporting recommendations for tumour MARKer prognostic studies (REMARK),” British Journal of Cancer, vol. 93, no. 4, pp. 385-386, 2005.
View at: Publisher Site | Google Scholar
Y.-H. Fan, C.-X. Ji, B. Xu, H.-Y. Fan, Z.-J. Cheng, and X.-G. Zhu, “Long noncoding RNA activated by TGF-β in human cancers: a meta-analysis,” Clinica Chimica Acta, vol. 468, pp. 10–16, 2017.
View at: Publisher Site | Google Scholar
P.-J. Ma, Q.-K. Guan, D.-W. Xu, J. Zhao, N. Qin, and B.-Z. Jin, “LncRNA PANDAR as a prognostic marker in Chinese cancer,” Clinica Chimica Acta, vol. 475, pp. 172–177, 2017.
View at: Publisher Site | Google Scholar
Z.-B. Guan, Y.-S. Cao, Y. Li, W.-N. Tong, and A.-S. Zhuo, “Knockdown of lncRNA GHET1 suppresses cell proliferation, invasion and LATS1/YAP pathway in non small cell lung cancer,” Cancer Biomarkers, vol. 21, no. 3, pp. 557–563, 2018.
View at: Publisher Site | Google Scholar
L. Jin, Y. He, S. Tang, and S. Huang, “LncRNA GHET1 predicts poor prognosis in hepatocellular carcinoma and promotes cell proliferation by silencing KLF2,” Journal of Cellular Physiology, vol. 233, no. 6, pp. 4726–4734, 2018.
View at: Publisher Site | Google Scholar
L. J. Li, J. L. Zhu, W. S. Bao, D. K. Chen, W. W. Huang, and Z. L. Weng, “Long noncoding RNA GHET1 promotes the development of bladder cancer,” International Journal of Clinical and Experimental Pathology, vol. 7, no. 10, pp. 7196–7205, 2014.
View at: Google Scholar
H. Liu, Q. Zhen, and Y. Fan, “LncRNA GHET1 promotes esophageal squamous cell carcinoma cells proliferation and invasion via induction of EMT,” The International Journal of Biological Markers, vol. 32, no. 4, pp. e403–e408, 2017.
View at: Publisher Site | Google Scholar
H. Liu and Y. Wu, “Long non-coding RNA gastric carcinoma highly expressed transcript 1 promotes cell proliferation and invasion in human head and neck cancer,” Oncology Letters, vol. 15, no. 5, pp. 6941–6946, 2018.
View at: Google Scholar
Q. M. Shen, H. Y. Wang, and S. Xu, “LncRNA GHET1 predicts a poor prognosis of the patients with non-small cell lung cancer,” European Review for Medical and Pharmacological Sciences, vol. 22, no. 8, pp. 2328–2333, 2018.
View at: Google Scholar
R. Song, J. Zhang, J. Huang, and T. Hai, “Long non-coding RNA GHET1 promotes human breast cancer cell proliferation, invasion and migration via affecting epithelial mesenchymal transition,” Cancer Biomarkers, vol. 22, no. 3, pp. 565–573, 2018.
View at: Publisher Site | Google Scholar
Y. Xia, Z. Yan, Y. Wan et al., “Knockdown of long noncoding RNA GHET1 inhibits cellcycle progression and invasion of gastric cancer cells,” Molecular Medicine Reports, vol. 18, no. 3, pp. 3375–3381, 2018.
View at: Google Scholar
W. Yang, Z. Shan, X. Zhou et al., “Knockdown of lncRNA GHET1 inhibits osteosarcoma cells proliferation, invasion, migration and EMT in vitro and in vivo,” Cancer Biomarkers, vol. 23, no. 4, pp. 589–601, 2018.
View at: Publisher Site | Google Scholar
H. Y. Zhou, H. Zhu, X. Y. Wu et al., “Expression and clinical significance of long-non-coding RNA GHET1 in pancreatic cancer,” European Review for Medical and Pharmacological Sciences, vol. 21, no. 22, pp. 5081–5088, 2017.
View at: Google Scholar
Y. Fan, Y. He, X. Zhou, Y. Liu, and F. Wang, “Meta-analysis of the prognostic value of lncRNA DANCR for cancer patients in China,” Cancer Management and Research, vol. 11, pp. 2027–2037, 2019.
View at: Publisher Site | Google Scholar
H. Guan, Y. Mei, Y. Mi et al., “Downregulation of lncRNA ANRIL suppresses growth and metastasis in human osteosarcoma cells,” OncoTargets and Therapy, vol. 11, pp. 4893–4899, 2018.
View at: Publisher Site | Google Scholar
H. Liu, Y. Pan, X. Han, J. Liu, and R. Li, “MicroRNA-216a promotes the metastasis and epithelial-mesenchymal transition of ovarian cancer by suppressing the PTEN/AKT pathway,” OncoTargets and Therapy, vol. 10, pp. 2701–2709, 2017.
View at: Publisher Site | Google Scholar
Y. H. Fan, M. H. Ye, L. Wu et al., “Overexpression of miR-98 inhibits cell invasion in glioma cell lines via downregulation of IKKepsilon,” European Review for Medical and Pharmacological Sciences, vol. 19, no. 19, pp. 3593–3604, 2015.
View at: Google Scholar
P. Qi and X. Du, “The long non-coding RNAs, a new cancer diagnostic and therapeutic gold mine,” Modern Pathology, vol. 26, no. 2, pp. 155–165, 2013.
View at: Publisher Site | Google Scholar
G. Ding, W. Li, J. Liu et al., “LncRNA GHET1 activated by H3K27 acetylation promotes cell tumorigenesis through regulating ATF1 in hepatocellular carcinoma,” Biomed Pharmacother, vol. 94, pp. 326–331, 2017.
View at: Publisher Site | Google Scholar
Z. Liu, S. Luo, M. Wu, C. Huang, H. Shi, and X. Song, “LncRNA GHET1 promotes cervical cancer progression through regulating AKT/mTOR and Wnt/beta-catenin signaling pathways,” Bioscience Reports, vol. 40, no. 1, 2020.
View at: Publisher Site | Google Scholar
X. Chen, W. Zhao, and W. Fan, “Long noncoding RNA GHET1 promotes osteosarcoma development and progression via Wnt/betacatenin signaling pathway,” Oncology Reports, vol. 44, no. 1, pp. 349–359, 2020.
View at: Google Scholar
A. Argentiero, S. De Summa, R. Di Fonte et al., “Gene expression comparison between the lymph node-positive and -negative reveals a peculiar immune microenvironment signature and a theranostic role for WNT targeting in pancreatic ductal adenocarcinoma: a pilot study,” Cancers, vol. 11, no. 7, 2019.
View at: Publisher Site | Google Scholar
B. Li, D. Xie, and H. Zhang, “Long non-coding RNA GHET1 contributes to chemotherapeutic resistance to Gemcitabine in bladder cancer,” Cancer Chemotherapy and Pharmacology, vol. 84, no. 1, pp. 187–194, 2019.
View at: Publisher Site | Google Scholar
L. Wei, J. Sun, N. Zhang et al., “Noncoding RNAs in gastric cancer: implications for drug resistance,” Molecular Cancer, vol. 19, no. 1, p. 62, 2020.
View at: Publisher Site | Google Scholar
X. Zhang, P. Bo, L. Liu, X. Zhang, and J. Li, “Overexpression of long non-coding RNA GHET1 promotes the development of multidrug resistance in gastric cancer cells,” Biomedicine & Pharmacotherapy, vol. 92, pp. 580–585, 2017.
View at: Publisher Site | Google Scholar
A. Kladi-Skandali, K. Michaelidou, A. Scorilas, and K. Mavridis, “Long noncoding RNAs in digestive system malignancies: a novel class of cancer biomarkers and therapeutic targets?” Gastroenterology Research and Practice, vol. 2015, Article ID 319861, 18 pages, 2015.
View at: Publisher Site | Google Scholar
X. Yang, H. Cai, Y. Liang et al., “Inhibition of c-Myc by let-7b mimic reverses mutidrug resistance in gastric cancer cells,” Oncology Reports, vol. 33, no. 4, pp. 1723–1730, 2015.
View at: Publisher Site | Google Scholar
F. Zhang, K. Li, X. Yao et al., “A miR-567-PIK3AP1-PI3K/AKT-c-Myc feedback loop regulates tumour growth and chemoresistance in gastric cancer,” EBioMedicine, vol. 44, pp. 311–321, 2019.
View at: Publisher Site | Google Scholar
K. Danza, N. Silvestris, G. Simone et al., “Role of miR-27a, miR-181a and miR-20b in gastric cancer hypoxia-induced chemoresistance,” Cancer Biology & Therapy, vol. 17, no. 4, pp. 400–406, 2016.
View at: Publisher Site | Google Scholar
L. Porcelli, R. M. Iacobazzi, R. Di Fonte et al., “CAFs and TGF-beta signaling activation by mast cells contribute to resistance to gemcitabine/nabpaclitaxel in pancreatic cancer,” Cancers, vol. 11, no. 3, 2019.
View at: Publisher Site | Google Scholar

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Copyright © 2020 Xi Zhou et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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