PCAT1: An oncogenic lncRNA in diverse cancers and a putative therapeutic target

Experimental and Molecular Pathology 114 (2020) 104429

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Experimental and Molecular Pathology journal homepage: www.elsevier.com/locate/yexmp

Review

PCAT1: An oncogenic lncRNA in diverse cancers and a putative therapeutic target

T

Soudeh Ghafouri-Farda, Sepideh Dashtib, Mohammad Taheric,

⁎

a

Urology and Nephrology Research Center(Ghafouri-Fard et al., 2020b), Shahid Beheshti University of Medical Sciences, Tehran, Iran Genomic Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran c Urogenital Stem Cell Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran b

ARTICLE INFO

ABSTRACT

Keywords: Prostate cancer associated transcript 1 PCAT1 lncRNA Cancer Biomarker

The critical roles of long non-coding RNAs (lncRNAs) in the regulation of diverse biological functions has potentiated them as cancer biomarkers. Among these transcripts is the prostate cancer associated transcript 1 (PCAT1) which has been initially shown to exert oncogenic roles in prostate cancer. Further studies revealed its similar roles in various kinds of human malignancies including both solid tumors and hematological malignancies. Animal studies have shown that down-regulation of this lncRNA can attenuate tumor growth in a wide array of cancers including prostate cancer, colorectal cancer, squamous cell carcinoma lung cancer and hepatocellular carcinoma. Studies aimed at identification of diagnostic value of this lncRNA in human cancers reported various values ranging from 0.66 to 0.89 in diverse cancers with the best value reported in multiple myeloma. This lncRNA has a number of putative functional genomic variants such as rs1902432, rs2632159, rs1026411, rs710886, rs16901904 and rs710886 which can modify expression or function of PCAT1 thus altering the risk of human cancers. Based on aberrant expression of PCAT1 in malignancies of diverse origins, this lncRNA can be regarded as a therapeutic target in a vast array of cancers. Thus, modalities for efficient reduction of its expression would be beneficial for several patients.

1. Introduction Long non-coding RNAs (lncRNAs) comprise a large number of transcripts encoded by human genome (Derrien et al., 2012). Their preferred localization in the chromatin and nucleus indicates a pivotal role for them in the regulation of gene expression. Notably, lncRNAs usually have lower expression levels compared with protein-coding genes, and show more tissue-specific signature (Derrien et al., 2012). LncRNAs participate in the regulation of gene expression at transcriptional, post-transcriptional, translational, and epigenetic levels (Shang et al., 2019; Ghafouri-Fard et al., 2020b; Ghafouri-Fard et al., 2020a; Ghafouri-Fard and Taheri, 2019). These transcripts have important effects in the regulation of various signaling pathways by interacting with several genes and that this implication has remarkable diagnostic and prognostic importance in clinical contexts (Abolghasemi et al., 2020a). Due to these versatile functions, abnormal expression or function of lncRNA is associated with several human diseases including cancer (Shang et al., 2019). Among lncRNAs whose participation in cancer is acknowledged is the prostate cancer associated transcript 1 (PCAT1) (Xiong et al., 2019). This lncRNA has been initially identified through

⁎

an RNA-Sequencing experiment on a cohort of 102 prostate tissues and cells lines (Prensner et al., 2011). Being nominated as a prostate-specific modulator of cell proliferation, it was recognized as a target of the Polycomb Repressive Complex 2 (PRC2). Notably, authors have established a molecular classification system based on expression level of PCAT1 and PRC2 (Prensner et al., 2011). This 1900 nt long lncRNA has 2 exons with the first one comprising a retroviral long terminal repeat unit and the second exon containing regions from the Hs Mariner 1 (HSMAR1) transposase (Prensner et al., 2011). Further evidence pointing to its role in carcinogenesis has come from its localization on chromosome 8q24 in vicinity of the c-Myc oncogene and in a region that is frequently amplified in prostate cancer tissues (Al Olama et al., 2009). As a transcriptional repressor, PCAT1 has been shown to downregulate expression of the BRCA2 tumor suppressor protein. Yet, it enhances expression of its neiboiring oncogene c-Myc (Prensner et al., 2014). Another possible mechanism for oncogenic functions of this lncRNA is its role as a sponge for tumor suppressor microRNAs (miRNAs) (Prensner et al., 2011). Several studies have indicated overexpression of PCAT1 in several human cancers. In the current review, we summarize the up-to-date evidence regarding the role of this

Corresponding author. E-mail address: [email protected] (M. Taheri).

https://doi.org/10.1016/j.yexmp.2020.104429 Received 4 March 2020; Received in revised form 18 March 2020; Accepted 22 March 2020 Available online 24 March 2020 0014-4800/ © 2020 Elsevier Inc. All rights reserved.

DU145 HT-29, SW480, Caco-2 and HTC-116 Caco-2 and HT-29 SW480, SW620, LOVO, HT29 and NCM460 KYSE30 and KYSE180 Normal esophageal epithelial cells, KYSE30, KYSE450, and Eca109 KYSE30, KYSE70, KYSE140, KYSE150, KYSE180, KYSE410, KYSE450, KYSE510 and COLO680N Cal27, JHU029 and JHU022 M4E, Hep-2, M2E and NP69 A549, SPC-A-1, H460 and 16HBE SK-MES-1, H1299 and 16HBE A549

– c-Myc, Caspase-3, PARP, bax, bcl-2 c-Myc

miR-149-5p – –

Colorectal cancer

Esophageal squamous cell carcinoma

2

miR-124-3p/ cyclin D1, CDK6, p53, Bax, cleaved caspase-3, metallopeptidases, vimentin, Wnt3a, β-catenin, protein kinase B and mechanistic target of rapamycin kinase

NEK2/ Wnt pathway

KLF6 cyclin D1/CDK4

RBM5 – – miR-129-5p

Pancreatic cancer Bladder cancer Cervical cancer Ovarian cancer

BXPC3, CFPAC-1, Panc-1, Capan-2 and H6C7 T24 and 5637 HeLa cells, C-33A cells A2780, SK-OV-3, OVCA429, HO8910 and IOSE80 A2780, TOV112D, OVCAR-3, SKOV3 and ISOE80 SKOV-3, OVCAR-3, HEY-A8, HO8910-PM and ISOE80 SKOV3, A2780, OVCA429, OVCAR3, OVCA433 and HOSE A2780, SKOV3

HIBEC, QBC939 and MKBC

AGS, BGC-823, MKN-45, HGC-27 and GES-1 BGC823, SGC7901 and GES-1 HepG2, Bel-7402 and L02 MHCC-97H, SMMC-7721, Huh7, HepG2, HCCLM3 and HL-7702 SMMC7721 and Huh7

– miR-128/ZEB1 – miR-129-5p/HMGB1

Extrahepatic cholangiocarcinoma

AGS, MGC-803, BGC-823, GES-1 and MKN-45

CDKN1A

c-Myc, AKT1 and p38 signaling pathways miR-210-3p – miR-149-5p/LRIG2 miR-324-5p/RAP1A

TP53/miR-215/ CRKL axis miR-122/ Wnt/ b-catenin-signaling pathway

Hepatocellular carcinoma

Gastric cancer

Lung cancer

Head and neck squamous cell carcinoma Laryngeal cancer Non-small cell lung cancer

LNCaP, C4–2 PC3, DU145, LNCap, C4–2, RWPE-1 Du145, RWPE

PHLPP/FKBP51/IKKα, AKT and NF-κB signaling miR-145-5p/ FSCN1 c-Myc/ miR-3667-3p, miR-34a

miR-326, cyclin B1 and CDC2

LNCaP

BRCA2, CENPE, CENPF, PRC2, SUZ12

Prostate cancer

Assessed cell lines

Targets/ regulators and signaling pathways

Cancer type

PCAT1: PCAT1: PCAT1: PCAT1:

↓ ↓ ↓ ↓

migration, ↓ invasion proliferation, ↑ apoptosis proliferation, ↓ invasion, ↓ metastasis proliferation, ↑ apoptosis

(Min and Chu, 2020)

∆ PCAT1: ↓ proliferation, ↓ migration, ↓ invasion, ↑ apoptosis

(continued on next page)

(Liu et al., 2019b)

(Liu et al., 2019a) (Ding et al., 2019)

(Zhang et al., 2017b) (Wang et al., 2019) (Liu et al., 2015) (Ma et al., 2018) (Gu et al., 2019)

(Cui et al., 2017) (Guo et al., 2019) (Wen et al., 2016) (Zhang et al., 2017a) (Ren et al., 2017)

(Huang et al., 2019a) (Sur et al., 2019) (Hu et al., 2019) (Zhao et al., 2015) (Li et al., 2019) (Huang et al., 2019b) (Bi et al., 2017)

(Li et al., 2019) (Qin et al., 2016) (Zhen et al., 2018)

(Prensner et al., 2011) (Shang et al., 2019) (Xu et al., 2017) (Prensner et al., 2014) (Yuan et al., 2018) (Qiao et al., 2017) (Qiao et al., 2018)

Reference

∆ PCAT1: ↓ proliferation, ↓ migration, ↑ apoptosis

∆ PCAT1: ↓ proliferation, ↓ migration, ↓ invasion ∆ PCAT1: ↓ proliferation, ↓ migration, ↓ invasion

∆ ∆ ∆ ∆

∆ PCAT1: ↓ cell growth, ↑ apoptosis, ↓ migration, ↓ invasion

∆ PCAT1: ↓ proliferation

∆ PCAT1: ↓ proliferation, ↑ cell cycle arrest, ↑ apoptosis, ↓ migration, ↓ invasion, ∆ PCAT1: ↓ proliferation, ↓ migration, ↓ invasion ∆ PCAT1: ↓ cisplatin-resistant ∆ PCAT1: ↓ proliferation, ↓ migration, ↑ apoptosis ∆ PCAT1: ↓ migration, ↓ invasion

↑ PCAT1: ↑ proliferation, ↓ apoptosis ∆ PCAT1: ↓ proliferation, ↑ cell cycle arrest, ↑ apoptosis ∆ PCAT1: ↑ The susceptibility of CRC cells to 5-Fu-induced apoptosis (↓ drug resistance), ↓ invasion ∆ PCAT1: ↓ proliferation, ↓ migration, ↓ invasion, ↑ apoptosis ↑ PCAT1: ↑ growth, ↑ colony formation ∆ PCAT1: ↓ proliferation, ↓ cell growth, ↓ cisplatin-resistance of cancer cells ∆ PCAT1: ↓ cell growth, ↑ cell cycle arrest at G2/M phase, ↑ sensitivity to paclitaxel ∆ PCAT1: ↓ cell growth, ↑ apoptosis ∆ PCAT1: ↓ migration, ↓ invasion ∆ PCAT1: ↓ proliferation, ↓ migration, ↓ invasion ∆ PCAT1: ↓ cell growth, ↑ cell cycle arrest, ↑ apoptosis ∆ PCAT1: ↓ proliferation, ↑ cell cycle arrest, ↑ apoptosis

∆ PCAT1: ↓ cell proliferation ↑ PCAT1: ↑ proliferation, ↑ migration, ↑ invasion, ↓ apoptosis ∆ PCAT1: ↓ cell proliferation

∆ PCAT1: ↓ cell proliferation

Function

Table 1 Summarized results of studies which assessed expression of PCAT1 in cell lines (∆: knock-down, Normal human prostate epithelial cell lines (RWPE-1), Normal liver epithelial cell line (L02), Normal human immortalized liver cell line (HL-7702), High mobility group box 1 (HMGB1), Human gastric epithelial cell line (GES-1), Normal bronchial epithelial cell line (16HBE), Normal human osteoblasts (hFOB 1.19), The normal bone cell line (NHost), Human normal ovarian cell line (IOSE80), Normal ovarian epithelial cell line (HOSE), THe normal endometrial stromal cell line (ESC), Immortalized pancreatic ductal epithelial cell line (H6C7), Normal nasopharyngeal epithelial cell line (NP69), human bone marrow stromal cells (HS-5)).

S. Ghafouri-Fard, et al.

Experimental and Molecular Pathology 114 (2020) 104429

Experimental and Molecular Pathology 114 (2020) 104429

lncRNA in human cancers. Such evidence has come from diverse cell line investigations as well as animal and human studies.

(Shen et al., 2020)

(Yuan et al., 2019)

2. Cell line studies Apart from the original study which reported oncogenic function of PCAT1 in prostate cancer cell lines and identified BRCA2, CENPE, CENPF, PRC2 and SUZ12 as targets/ regulators of PCAT1 (Prensner et al., 2011), other studies in this kind of cancer have led to identification of a number of miRNAs as well as cancer-related AKT and NF-κB signaling pathways as molecules/ proteins that have interaction with this lncRNA (Prensner et al., 2014; Shang et al., 2019; Xu et al., 2017). Moreover, PCAT1 has an almost mutual exclusive relation with EZH2, a core protein of PRC2 which is up-regulated in cancers and participates in metastatic potential of tumor cells (Xiong et al., 2019). The interaction between PCAT1 and AKT and NF-κB signaling pathways has been verified in some other kinds of human cancer such as head and neck squamous cell carcinoma and multiple myeloma, respectively (Sur et al., 2019; Shen et al., 2020). Activity of MAPK and Wnt/β-catenin pathways is also influenced by PCAT1 in these cancers (Sur et al., 2019; Shen et al., 2019). It is worth mentioning that apart from the diverse identified molecules and signaling pathways that are affected by PCAT1 in different cancer types, all cell line studies indicated that PCAT1 silencing decreases cell proliferation and malignant behavior of cancer cells, while its forced over-expression has the opposite effects. Table 1 summarizes the results of studies which assessed expression and function of PCAT1 in cell lines.

∆ PCAT1: ↓ the tumor-promoting effect caused by miR-129

FZD6/ Wnt/βcatenin signaling pathway miR-129 /MAP3K7/ NF-κB pathway Acute myeloid leukemia

∆ PCAT1: ↓ proliferation, ↓ cell cycle progression, ↑ apoptosis

NCI-H929, RIMP 8226 and U266 cells Kasumi-6, HL-60, MOLT-3, AML-193, BDCM and HS-5 U266, NCI-H929 and RIMP 8226 p38 and JNK-MAPK pathways Multiple myeloma

(Shen et al., 2019)

∆ PCAT1: ↓ proliferation, ↓ migration, ↓ invasion, ↓ EMT, ↑ apoptosis, ↑ cell population at G0/G1 phase, ↓ cell population at S phase ∆ PCAT1: ↓ cell division, ↑ apoptosis, ↑ sensitivity to bortezomib NHost, LM7, KHOS, MG-63 and U2OS E-cadherin, N-cadherin

(Huang et al., 2018) (Zhang et al., 2018) EZH2, p21 Osteosarcoma

hFOB 1.19, Saos-2, U2OS, MG-63 and 143B

∆ PCAT1: ↓ proliferation, ↓ migration, ↓ invasion, ↑ apoptosis ∆ PCAT1: ↓ proliferation, ↓ sphere-formation, ↑ apoptosis, ↑ radio sensitivity ∆ PCAT1: ↓ proliferation, ↓ migration, ↓ invasion HEC-1B, Ishikawa, RL95–2, AN3CA and ESC CD133+ human glioma stem cells Bcl-2, vimentin, N-cadherin, E-cadherin and Bad miR-129-5p/ HMGB1 signaling pathway Endometrial carcinoma Glioma

(Zhao et al., 2019) (Zhang et al., 2019)

Function Assessed cell lines Targets/ regulators and signaling pathways Cancer type

Table 1 (continued)

Reference

S. Ghafouri-Fard, et al.

3. Animal studies As another type of investigations for assessment of function of PCAT1, transplantation of genetically-modified human cancer cell lines to animal models has verified oncogenic effects of PCAT1. Shang et al. have recently injected lentiviruses carrying shRNA against PCAT1 into castration-resistant prostate cancer cells. Notably, they observed the effects of PCAT1 silencing on attenuating the growth of the LNCaP-AI tumors in xenograft models (Shang et al., 2019). Similar studies in other types of cancer led to comparable results (summarized in Table 2). Notably, PCAT1 silencing has been shown to increase the cytotoxic effect of cisplatin in a mouse gastric cancer xenograft model. This results has been obtained through stable expression of sh-PCAT1 in BGC823/DDP cells and subcutaneous transplantation of these cells into nude mice (Guo et al., 2019). 4. Human studies Expression of PCAT1 in clinical samples from cancer patients has been compared with its expression in paracencerous or benign tissues of the same origin. Almost all studies have reported up-regulation of this lncRNA in cancerous samples compared with the mentioned controls (summarized in Table 3). Notably, expression level of this lncRNA has been associated with survival of patients with diverse types of cancers including colorectal cancer (Ge et al., 2013), esophageal squamous cell carcinoma (Shi et al., 2015), non-small cell lung cancer (NSCLC) (Li et al., 2019), gastric cancer (Cui et al., 2017), hepatocellular carcinoma (Yan et al., 2015), cervical cancer (Ma et al., 2018), ovarian cancer (Liu et al., 2019b), endometrial cancer (Zhao et al., 2019) and osteosarcoma (Huang et al., 2018). Moreover, analysis of TCGA datasets revealed association between amplification of PCAT1 and overall survival of patients with prostate cancer (Shang et al., 2019). Over-expression of PCAT1 has been correlated with invasive properties of cancer cells, clinical stage and metastasis in a number of human malignancies (Shi et al., 2015). 3

Experimental and Molecular Pathology 114 (2020) 104429

S. Ghafouri-Fard, et al.

Table 2 Summary of studies which assessed function of PCAT1 in animal models (∆: knock down or deletion). Cancer type

Animal models

Function and comments

Reference

Prostate cancer Colorectal cancer Esophageal squamous cell carcinoma

Male nude mice Male BABL/c nude mice Male nude mice Male athymic nude mice Female BALB/c athymic nude mice NOD/SCID mice nude mice BALB/c nude mice Female BALB/c nude mice Male BABL/c nude mice Female BALB/c nude mice

∆ ∆ ∆ ∆ ∆ ∆ ∆ ∆ ∆ ∆ ∆

(Shang et al., 2019) (Qiao et al., 2017) (Zhen et al., 2018) (Huang et al., 2019a) (Sur et al., 2019) (Hu et al., 2019) (Li et al., 2019) (Guo et al., 2019) (Ren et al., 2017) (Huang et al., 2018) (Shen et al., 2019)

Head and neck squamous cell carcinoma Laryngeal cancer Non-small cell lung cancer Gastric cancer Hepatocellular carcinoma Osteosarcoma Multiple myeloma

PCAT1: PCAT1: PCAT1: PCAT1: PCAT1: PCAT1: PCAT1: PCAT1: PCAT1: PCAT1: PCAT1:

↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓

Tumor growth Tumor growth Tumor growth Tumor growth, ↓ tumor weight Tumor growth, ↑ apoptosis Tumor growth Tumor growth Cisplatin-resistant Tumor growth Tumor growth Tumor growth

not clear in all cases. Although gene amplification is a possible mechanism, a single study in colorectal cancer revealed copy number variation in only a small proportion of PCAT1 overexpressing tissues (Ge et al., 2013). Thus, future studies are needed to find the underlying cause of its up-regulation. As 8q24 locus is a region with cancer-specific DNA methylation pattern (Barry et al., 2017), epigenetic mechanisms are another explanation for altered expression of PCAT1 in cancers. Although the original study by Prensner et al. showed PCAT1 silencing alters expression of 370 genes (Prensner et al., 2011), among diverse molecular targets of PCAT1, regulation of the c-Myc expression and related proliferative pathways by this lncRNA is probably the most meaningful mechanism of its participation in the carcinogenesis. Moreover, matrix metalloproteinases that are regulated by PCAT1 are critical regulators of invasion and metastasis in human cancers. Other targets of PCAT1 are cyclins, cyclin dependent kinases, EMT-associated genes such as vimentin, N-cadherin and E-cadherin as well as apoptosisrelated genes. Thus, PCAT1 is expected to influence several cancer-related targets. PCAT1 can also regulate expression of several miRNAs. As miRNAs are implicated in the regulation of cancer-related pathways such as TGF-β, Wnt, Notch, NF-κB and PI3K/Akt/mTOR (Abolghasemi et al., 2020b), it is possible that lncRNAs such as PCAT1 have indirect roles on regulation of these pathways. The observed correlations between over-expression of PCAT1 and invasive properties of cancer cells, clinical stage and metastasis is a clear indicative of the prominent role of this lncRNA in the carcinogenesis process. Besides, such reported correlations imply potential of this lncRNA for early detection of cancer. Based on the consistent results of function of PCAT1 in diverse malignancies, adjuvant therapy targeting this lncRNA is expected to be effective in the treatment almost all cancers. Although expression pattern of PCAT1 has been assessed in a wide range of human cancers, data regarding the association between genomic variants of this lncRNA and susceptibility to human cancers are scarce. Therefore, future studies should focus on evaluation of such associations in diverse populations to complete the puzzle of PCAT1 participation in the carcinogenesis. Such studies would also propose another mechanism for the observed up-regulation of this lncRNA in cancerous tissues. Finally, based on the results of animal studies that indicate the influence of PCAT1 silencing on attenuation of tumor growth, PCAT1 targeting is a promising method for cancer treatment. However, this research area lacks proofs from human studies.

5. Diagnostic value of PCAT1 in human cancers One important aspect of assessment of PCAT1 expression in patients with cancer is its potential to discriminate patients from healthy subjects. A recent systematic review and meta-analysis of PCAT1 expression in diverse cancers indicated that PCAT1 has a sensitivity of 0.59 and specificity of 0.66 for cancer diagnosis. Besides, authors have depicted the receiver operating characteristic (ROC) curve by plotting the sensitivity versus 1-Specifity values. Their results showed that pooled area under curve was 0.62 (95% CI: 0.58–0.69) (Talebi et al., 2019). Table 4 summarizes the results of available studies which assessed diagnostic power of PCAT1 in human malignancies. 6. Association between PCAT1 genomic variants and risk of human cancers PCAT1 has a number of putative functional polymorphisms that modulate risk of human cancers. A recent study has investigated the association between for PCAT1 polymorphisms namely the rs1026411, rs12543663, rs710886 and rs16901904 and risk of lung cancer in Chinese population. While the rs1026411 and rs710886 were associated with susceptibility to NSCLC, the rs1026411 was associated with lung adenocarcinoma risk. Besides, the rs710886 and rs16901904 were associated with susceptibility to lung squamous cell carcinoma (Bi et al., 2019). Clues for functionality of the rs710886 polymorphism has come from a single study in bladder cancer patients which showed its role in modulation of expression of PCAT1 (Lin et al., 2017). Table 5 summarizes the results of studies which evaluated the role of mentioned polymorphisms in conferring risk of human cancers. The rs710886 is perhaps the mostly assessed PCAT1 SNP in this regard. 7. Discussion Initially recognized as an oncogene in prostate cancer, PCAT1 was soon identified as an lncRNA that exerts oncogenic effects in diverse cancer types. Not compatible with the supposed tissue-specific pattern of lncRNAs (Derrien et al., 2012), expression of this lncRNA has been detected in almost all human tissues. Most notably, PCAT1 has a similar role in the regulation of cell proliferation, apoptosis, invasion and metastasis in all assessed cell lines. As revealed in prostate cancer and osteosarcoma cells, the encoded transcript is mostly perceived in the cytoplasm, but it is also detected in the nucleus (Prensner et al., 2014). Such dual cellular localization indicates the broad range of physiological activities for this lncRNA. Consistent with the results of cell line studies, its expression has been up-regulated in clinical samples from patients with cancer. However, the mechanism for its up-regulation is

Declaration of Competing Interest The authors declare they have no conflict of interest.

4

5

Non-small cell lung cancer (NSCLC)

Head and neck squamous cell carcinoma (HNSCC) Laryngeal cancer

Oral squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC)

Colorectal cancer (CRC)

47 localized tumors, 14 metastatic tumors and 20 benign adjacent prostate tissues 8 ADPC tissue samples, 6 CRPC tissue samples, 498 cases of PCa from TCGA

Prostate cancer (PCa)

321 pairs of ESCC tissues and adjacent normal tissues 35 ESCC tissues including 14 primary tumors and 21 secondary tumors and 9 healthy control 39 pairs of ESCC tissues and adjacent normal tissues 75 pairs of ESCC tissues and adjacent normal tissues 60 oral squamous cell carcinoma, and 52 non-cancer oral tissues 23 paired human HNSCC tissues and adjacent non-tumor tissue 50 paired human HNSCC tissues and adjacent non-tumor tissue 34 pairs of NSCLC tissues and normal adjacent tissues 36 pairs of NSCLC tissues and normal adjacent tissues 106 pairs of NSCLC tissues and normal adjacent tissues

23 CRC tissues and their paired paracarcinoma tissues 55 pairs of CRC tissues and adjacent normal tissues 130 pairs of ESCC tissues and adjacent normal tissues

20 PC tumor tissues samples and 20 adjacent pericancerous tissues 108 cases of CRC tissues and 81 matched adjacent normal tissues

Numbers of clinical samples (tissues, serum, etc.)

Cancer type

Based on TCGA datasets, PCa patients with PCAT1 gene amplification had worse RFS and OS when compared to patients without PCAT1 amplification (including patients with normal copies or deletion of the PCAT1 locus). –

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No significant difference Up

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PCAT1 expression was an independent prognostic factor in patients with NSCLC.

–

– Patients with NSCLC with the high PCAT1 expression had shorter OS and DFS.

–

–

–

–

–

–

Higher PCAT1 expression had a worse prognosis. –

–

–

–

High expression of PCAT1 was a prognostic factor.

–

–

–

Univariate cox regression

–

Based on TCGA dataset, PCAT1 alteration might be associated with poor OS. –

–

–

Up Up

–

Up

Up

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Up

The patients with high levels of PCAT1 had poorer survival time than those with low levels of PCAT1. Over-expression of PCAT1 was correlated with poorer survival. –

–

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CRC patients with PCAT1 higher expression have shown significant poorer OS than those with lower PCAT1 expression. –

Up

Up

–

Kaplan-Meier analysis

Up

Expression Tumor vs. Normal

(Li et al., 2019)

(Zhao et al., 2015)

(Shi et al., 2015)

(Hu et al., 2019)

(Sur et al., 2019)

(Huang et al., 2019a) (Razavi and Ghorbian, 2019) (Yang et al., 2019)

(Zhen et al., 2018)

(Qin et al., 2016)

(Shi et al., 2015)

(Li et al., 2019)

(Qiao et al., 2018)

(Ge et al., 2013)

(Xu et al., 2017)

(Shang et al., 2019)

(Prensner et al., 2011)

Reference

(continued on next page)

PCAT-1 expression was an independent prognostic factor in patients with NSCLC.

–

–

–

–

–

–

–

High PCAT1 expression was an independent predictor of poor survival in ESCC. Higher PCAT1 expression had a worse prognosis. –

–

PCAT1 overexpression was an independent prognostic factor for CRC. –

–

–

–

Multivariate cox regression

Table 3 Summary of studies reported expression of PCAT1 in clinical samples (Androgen-sensitive prostate cancer (ADPC), Castration-resistant prostate cancer (CRPC), The Cancer Genome Atlas (TCGA), Recurrence-free survival (RFS), Overall survival (OS), disease-free survival (DFS).

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Experimental and Molecular Pathology 114 (2020) 104429

6

Osteosarcoma

Endometrial carcinoma (EC)

30 pairs of ovarian cancer tissues and adjacent non-tumor areas 52 pairs of ovarian cancer tissues and adjacent non-tumor areas Ovarian cancer tissue of 32 patient and 20 controls (postoperative pathological examination confirmed benign ovarian tumors) 40 pairs of ovarian cancer tissues and adjacent non-tumor areas

Ovarian cancer

Up Up

30 pairs of OS tumor tissues and adjacent normal bone tissues

Up

Up

High levels of PCAT1 had statistically significantly worse overall and progression-free survival. Patients with high expression level of PCAT1 in osteosarcoma tissues had shorter survival rates.

Patients with higher PCAT1 expression had poor OS.

PCAT1 may be an important prognostic factor for the clinical outcomes in patients with osteosarcoma.

PCAT1 expression were independent prognostic factors for overall survival in EC. High PCAT1 expression was related to poor prognosis.

–

–

(Zhang et al., 2018)

(Huang et al., 2018)

(Min and Chu, 2020) (Zhao et al., 2019)

(continued on next page)

PCAT1 may be an important prognostic factor for the clinical outcomes in patients with osteosarcoma.

High PCAT1 expression is independent predictors of OS.

PCAT1 expression were independent prognostic factors for overall survival in EC.

–

–

(Liu et al., 2019a)

(Gu et al., 2019)

(Ma et al., 2018)

(Liu et al., 2019b)

Patients with high expression of PCAT1 tended to have shorter OS. (Analyzed by Gehan-Breslow-Wilcoxon test) –

–

–

–

(Sarrafzadeh et al., 2017)

Up

–

–

–

–

(Liu et al., 2015)

(Zhang et al., 2017a) (Zhang et al., 2017b) (Guo et al., 2019)

(Wen et al., 2016)

(Shi et al., 2015)

(Shi et al., 2015)

(Guo et al., 2019)

(Cui et al., 2017)

(Bi et al., 2017)

Reference

(Ding et al., 2019)

–

The patients with high expression of PCAT1 tended to have shorter OS. –

–

–

–

–

–

–

PCAT1 expression level was an independent prognostic factor for the OS rate of HCC patients. –

–

PCAT1 expression was an independent poor prognostic factor for OS in GC. –

–

Multivariate cox regression

Up

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Up in 12/47 (25.5%) of tumor tissues Up

–

–

–

–

PCAT1 expression was significantly related to postoperative survival. –

–

High expression of PCAT1 was evaluated to correlate closely with poor OS. –

–

Univariate cox regression

–

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Up Up

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A high expression level of PCAT1 resulted in a significantly poor OS.

A high expression level of PCAT1 resulted in a significantly poor OS. –

Over-expression of PCAT1 was correlated with poor OS in GC patients. Increased PCAT1 expression contributed to poor OS.

Kaplan-Meier analysis

Up

No significant difference Up

Up

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Up

Expression Tumor vs. Normal

62 pairs of tumor tissues and normal adjacent tissues

20 pairs of ovarian cancer tissues and adjacent non-tumor areas 89 pairs of EC tissues and adjacent nontumor areas

75 pairs of cancer specimens and adjacent non-tumor areas

82 pairs of HCC tissues and normal adjacent tissues 72 pairs of HCC tissues and normal adjacent tissues 6 pairs of ECC tissues and normal adjacent tissues 50 pairs of Pancreatic cancer tissues and normal adjacent tissues 36 pairs of Bladder cancer tissues and normal adjacent tissues 47 cases of breast cancer tumor tissues and adjacent normal tissues

Cervical cancer

Breast cancer

Bladder cancer

Extrahepatic cholangiocarcinoma (ECC) Pancreatic cancer

Hepatocellular carcinoma (HCC)

110 pairs of GC tissues and normal adjacent tissues 175 pairs of GC tissues and normal adjacent tissues

Gastric cancer (GC)

38 pairs of GC tissues and normal adjacent tissues 30 pairs of GC tissues and normal adjacent tissues 117 pairs of HCC tissues and normal adjacent tissues

Numbers of clinical samples (tissues, serum, etc.)

Cancer type

Table 3 (continued)

S. Ghafouri-Fard, et al.

Experimental and Molecular Pathology 114 (2020) 104429

Serum samples of 60 newly diagnosed untreated MM patients, and 48 healthy controls. 18 clinically confirmed MM patients and 7 healthy donors Bone marrow samples from 58 AML patients and 30 healthy donors

Multiple myeloma (MM)

7 High PCAT1group vs. low PCAT1 group High PCAT1group vs. low PCAT1 group

321 pairs of ESCC tissues and adjacent normal tissues

117 pairs of HCC tissues and normal adjacent tissues

175 pairs of GC tissues and normal adjacent tissues

Serum samples of 60 newly diagnosed untreated MM patients, and 48 healthy controls.

Hepatocellular carcinoma (HCC)

Gastric cancer (GC)

Multiple myeloma (MM)

Esophageal squamous cell carcinoma (ESCC)

–

–

–

0.892

0.65

0.66

0.62

0.7

0.71

Area Under Curve

–

–

–

71.7

42

61

58

58

78

93.8

81

63

60

70

54

Specificity (%)

(Yuan et al., 2019)

(Shen et al., 2019)

(Shen et al., 2017)

Reference

(Ge et al., 2013, Talebi et al., 2019) (Shi et al., 2015, Talebi et al., 2019) (Qin et al., 2016, Talebi et al., 2019) (Shi et al., 2015, Talebi et al., 2019) (Cui et al., 2017, Talebi et al., 2019) (Shen et al., 2017)

Reference

Multivariate cox regression

Sensitivity (%)

Univariate cox regression

Serum PCAT1 levels from patients with MM vs. healthy controls.

High PCAT1group vs. low PCAT1 group

High PCAT1group vs. low PCAT1 group

High PCAT1group vs. low PCAT1 group

108 cases of CRC tissues and 81 matched adjacent normal tissues 130 pairs of ESCC tissues and adjacent normal tissues

Colorectal cancer (CRC)

Distinguish between

Numbers of clinical samples

–

–

Up Up

–

Kaplan-Meier analysis

Up

Expression Tumor vs. Normal

Cancer Type

Table 4 Diagnostic value of PCAT1 in cancers.

Acute myeloid leukemia (AML)

Numbers of clinical samples (tissues, serum, etc.)

Cancer type

Table 3 (continued)

S. Ghafouri-Fard, et al.

Experimental and Molecular Pathology 114 (2020) 104429

Experimental and Molecular Pathology 114 (2020) 104429

S. Ghafouri-Fard, et al.

Table 5 PCAT1 polymorphisms and their association with cancer risk. Cancer type

Cases/ Control

SNP ID

OR (95%CI)

p-value

Description

Ref

Prostate cancer (PCa)

850/860

rs1902432

0.014

Colorectal cancer (CRC)

436/510

rs2632159

Non-small cell lung cancer (NSCLC)

407/561

rs1026411

243/561

rs1026411

Squamous cell carcinoma

155/561

rs710886

Individual carrying rs1902432 CC genotype had higher risk of PCa compared with those with TT/CT genotype. C allele genotypes of rs2632159 (rs2632159 TC and CC) were significantly associated with increased CRC risk. A allele genotypes of rs1026411 (rs1026411 AA and AG) were significantly associated with decreased NSCLC risk. C allele genotypes of rs710886 (rs710886 CC and CT) were significantly associated with decreased NSCLC risk. A allele genotypes of rs1026411 (rs1026411 AA and AG) were significantly associated with decreased NSCLC risk. CC or CT genotype of rs710886 had a significantly decreased risk compared with TT genotype carrier. In comparison with the TT genotype carrier, the risk of squamous cell carcinoma significantly increased in the CC genotype Individuals with GG genotype had lower risk of bladder cancer compared with those carrying AA genotype. G allele was consistent with lower PCAT1 expression.

(Yuan et al., 2018) (Yang et al., 2019) (Bi et al., 2019)

Lung adenocarcinoma

1.19 (1.04–1.37) 2.38 (1.11–5.09) 0.701 (0.520–0.946) 0.723 (0.525–0.995) 0.685 (0.497–0.943) 0.638 (0.416–0.980) 2.582 (1.078–6.186) 0.83 (0.74–0.93)

rs710886

rs16901904 Bladder cancer

578/1006

rs710886

0.026 0.020 0.047 0.020 0.040 0.033 0.001

Acknowledgment

(Bi et al., 2019) (Bi et al., 2019) (Lin et al., 2017)

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