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Jeffrey A. Borgia

Marco Tomasetti Subscribe SciFeed Recommended Articles Related Info Link Google Scholar More by Authors Links on DOAJ Lucà, S. Franco, R. Napolitano, A. Soria, V. Ronchi, A. Zito Marino, F. Della Corte, C. Maria Morgillo, F. Fiorelli, A. Luciano, A. Palma, G. Arra, C. Battista, S. Cerchia, L. Fedele, M. on Google Scholar Lucà, S. Franco, R. Napolitano, A. Soria, V. Ronchi, A. Zito Marino, F. Della Corte, C. Maria Morgillo, F. Fiorelli, A. Luciano, A. Palma, G. Arra, C. Battista, S. Cerchia, L. Fedele, M. on PubMed Lucà, S. Franco, R. Napolitano, A. Soria, V. Ronchi, A. Zito Marino, F. Della Corte, C. Maria Morgillo, F. Fiorelli, A. Luciano, A. Palma, G. Arra, C. Battista, S. Cerchia, L. Fedele, M. /ajax/scifeed/subscribe Article Views Citations - Table of Contents Altmetric share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up ... Endorse textsms ... Comment Need Help? Support

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Get Information clear JSmol Viewer clear first_page settings Order Article Reprints Font Type: Arial Georgia Verdana Font Size: Aa Aa Aa Line Spacing:    Column Width:    Background: Open AccessArticle PATZ1 in Non-Small Cell Lung Cancer: A New Biomarker That Negatively Correlates with PD-L1 Expression and Suppresses the Malignant Phenotype by

Stefano Lucà 1,

Renato Franco 1,*,

Antonella Napolitano 2,

Valeria Soria 2,

Andrea Ronchi 1,

Federica Zito Marino 1,

Carminia Maria Della Corte 3,

Floriana Morgillo 3,

Alfonso Fiorelli 4 ORCID

Antonio Luciano 5,

Giuseppe Palma 5 ORCID

Claudio Arra 5,†,

Sabrina Battista 2 ORCID

Laura Cerchia 2 ORCID

and

Monica Fedele 2,* ORCID

1 Pathology Unit, Department of Mental and Physical Health and Preventive Medicine, University of Campania “Luigi Vanvitelli”, 80138 Naples, Italy 2 Institute for Experimental Endocrinology and Oncology (IEOS), National Research Council (CNR), 80145 Naples, Italy 3 Department of Precision Medicine, Medical Oncology, University of Campania “Luigi Vanvitelli”, 80138 Naples, Italy 4 Translational Medical and Surgical Science, Thoracic Surgery, University of Campania “Luigi Vanvitelli”, 80138 Naples, Italy 5 S.S.D. Sperimentazione Animale, Istituto Nazionale Tumori—IRCCS—Fondazione G. Pascale, 80131 Naples, Italy * Authors to whom correspondence should be addressed. † Current retired employee. Cancers 2023, 15(7), 2190; https://doi.org/10.3390/cancers15072190 Received: 10 February 2023 / Revised: 3 April 2023 / Accepted: 3 April 2023 / Published: 6 April 2023 (This article belongs to the Special Issue New Insight of Non-small Cell Lung Cancer) Download Download PDF Download PDF with Cover Download XML Download Epub Download Supplementary Material Browse Figures Versions Notes

Abstract: Simple SummaryLung cancer is the leading cause of cancer death worldwide. Most lung cancers are classified as non-small cell lung cancer (NSCLC), which is diagnosed at an advanced stage when various treatments cannot be curative. Immunotherapy is a promising treatment for many cancers, including NSCLC, and the big challenge is the identification of new tumor biomarkers able to predict its success. In this framework, the aim of our study was to evaluate the expression of PATZ1, an emerging cancer-related protein suggested as a diagnostic marker in different cancers, in correlation with the expression of PD-L1, a major target of immunotherapy, in NSCLC. Our analysis, conducted in different NSCLC tumor samples and two NSCLC cell lines, indicated that PATZ1 and PD-L1 expressions are negatively associated and that PATZ1 overexpression downregulates PD-L1 expression. Furthermore, we show that deletion or halving of PATZ1 expression induces NSCLC in mice, whereas overexpression of PATZ1 in NSCLC cells reduces their ability to proliferate, migrate, and invade, compared to controls, suggesting that PATZ1 functions as a suppressor of NSCLC. AbstractNon-small cell lung cancer (NSCLC), the leading cause of cancer death worldwide, is still an unmet medical problem due to the lack of both effective therapies against advanced stages and markers to allow a diagnosis of the disease at early stages before its progression. Immunotherapy targeting the PD-1/PD-L1 checkpoint is promising for many cancers, including NSCLC, but its success depends on the tumor expression of PD-L1. PATZ1 is an emerging cancer-related transcriptional regulator and diagnostic/prognostic biomarker in different malignant tumors, but its role in lung cancer is still obscure. Here we investigated expression and role of PATZ1 in NSCLC, in correlation with NSCLC subtypes and PD-L1 expression. A cohort of 104 NSCLCs, including lung squamous cell carcinomas (LUSCs) and adenocarcinomas (LUADs), was retrospectively analyzed by immunohistochemistry for the expression of PATZ1 and PD-L1. The results were correlated with each other and with the clinical characteristics, showing on the one hand a positive correlation between the high expression of PATZ1 and the LUSC subtype and, on the other hand, a negative correlation between PATZ1 and PD-L1, validated at the mRNA level in independent NSCLC datasets. Consistently, two NSCLC cell lines transfected with a PATZ1-overexpressing plasmid showed PD-L1 downregulation, suggesting a role for PATZ1 in the negative regulation of PD-L1. We also showed that PATZ1 overexpression inhibits NSCLC cell proliferation, migration, and invasion, and that Patz1-knockout mice develop LUAD. Overall, this suggests that PATZ1 may act as a tumor suppressor in NSCLC. Keywords: PATZ1; lung cancer; PD-L1; tumor suppressor; LUSC; LUAD 1. IntroductionLung cancer is a heterogeneous group of diseases with respect to biology and clinical behavior and is one of the most common and aggressive cancers with the highest incidence and lethality. Indeed, the World Health Organization (WHO) has recently estimated a further increase worldwide in the coming years [1,2]. The most common lung cancer type is non-small cell lung cancer (NSCLC), representing about 85% of cases. It includes adenocarcinoma (LUAD), squamous cell carcinoma (LUSC), and large cell carcinoma, with LUAD and LUSC representing the largest NSCLC subgroups. The molecular pathogenesis of lung cancer involves the accumulation of genetic and epigenetic alterations, including the activation of proto-oncogenes and the inactivation of tumor suppressor genes, which differ among the lung cancer subgroups [3]. Overall, approximately 70% of lung cancer patients are diagnosed in advanced stages of the disease and are ineligible for tumor resection [3], prompting the identification of early diagnostic markers. Current treatment options for all NSCLCs include chemotherapy, radiotherapy, molecular targeted therapy, and immunotherapy, with subsets of patients treated according to the genetic alterations of their tumor and the status of programmed death ligand-1 (PD-L1), which predict for benefit from targeted therapies or immune checkpoint blockers, respectively [3,4]. However, LUSC and non-G12C KRAS mutant LUAD have no specific targetable therapeutic strategies to date [5].Immune checkpoints are a strategic weapon of most cancer cells capable of inducing immunosuppression and consequently promoting tumor progression [6]. One of the major immune checkpoints is PD-L1, encoded by the CD274 gene, which can inhibit T cell priming against tumor antigens and induce tumor growth and progression in multiple tumors [7]. Aside from its tumor extrinsic role involving the tumor microenvironment, PD-L1 has a tumor intrinsic oncogenic role by inducing growth proliferation, migration, and invasive capability in several cancers including NSCLC [8].PATZ1 (POZ/BTB and AT-hook-containing Zinc finger protein 1), also known as MAZR (MAZ Related factor), ZSG (Zinc finger Sarcoma Gene), or ZNF278 (Zinc finger protein 278), is an architectural transcription factor that regulates gene expression in a cell context-dependent manner by binding to gene promoter regions either directly, recognizing specific consensus sequences, or indirectly through its interaction with other proteins [9,10]. In particular, PATZ1 may be involved in the modulation of histone acetylation/deacetylation to maintain the transcriptional “off” state of different genes through interaction with corepressors and histone deacetylases, such as NCoR and SIRT1, respectively [11,12]. Consistently, Patz1+/− mouse embryonic fibroblasts display epigenetic histone modifications characteristic of transcriptionally active chromatin [13]. PATZ1 expression is strongly related to cancer signatures and cellular proliferation, as recently assessed by PATZ1 ChIP-seq and gene expression microarray analyses [14]. Indeed, it has been shown to act as an oncogene in colon cancer and glioblastoma cells [15,16,17,18] and a tumor suppressor in glioblastoma [19], thyroid [20,21,22], ovarian [23], and liver cancer cells [14]. Additionally, PATZ1 has been proposed as a diagnostic/prognostic biomarker in different neoplasia, including testicular germ cell tumors [24], renal cell carcinoma [25,26,27], CNS neoplasms [28,29,30], round cell sarcomas [31], large cell B lymphomas [32], thyroid cancer [20], and ovarian cancer [23], where lower levels and cytoplasmic localization of the PATZ1 protein are often predictive of a more aggressive phenotype and, consequently, the worst prognosis [20,23,28,32]. The expression and role of PATZ1 in NSCLC still remain undetermined.In the present study, we detected the expression of PATZ1 in NSCLC tissues, including LUSC and LUAD, by immunohistochemistry and bioinformatic analysis. Then, we evaluated the correlation of PATZ1 expression and localization with clinicopathological features, patient survival, and PD-L1 expression, showing a positive association with the LUSC subtype, where PATZ1 behaves as a favorable prognostic marker, and a negative association with PD-L1 expression, which suggests that PATZ1 may be involved in its negative regulation. On the other hand, nuclear expression of PATZ1 is negatively associated with the LUAD subtype, and Patz1-knockout mice develop lung adenocarcinomas. Consistently, overexpression of PATZ1 in LUAD cells inhibits cell proliferation, migration, and invasion, suggesting a tumor suppressor role of this gene in NSCLC, likely by counteracting the epithelial–mesenchymal transition. 2. Materials and Methods 2.1. Patient Cohorts and Public DatasetsA cohort of 104 histologically confirmed NSCLC specimens, including 43 LUSCs and 61 LUADs, were collected from the Department of Pathology of the Università degli Studi della Campania “L. Vanvitelli”, Naples, Italy, and evaluated retrospectively in this study. All cases were reviewed according to the most up-to-date WHO classification criteria, using standard tissue sections stained with hematoxylin/eosin and analyzed by immunohistochemistry.Other cohorts were collected from publicly available datasets from the Gene Expression Omnibus (GEO) database and the Cancer Genome Atlas Program (TCGA). They include the GSE31552 dataset, from the Albert Einstein College of Medicine, NY, USA, from which we selected 50 NSCLC (23 LUSC and 27 LUAD) and 50 paired normal perilesional alveolar epithelial tissues for the analysis of PATZ1 expression in tumor vs. non-tumor tissues, and the whole dataset of 131 paired and unpaired tumor and non-tumor tissues for the analysis of the correlation between PATZ1 and SOX2 expression levels; the GSE19804 dataset, consisting of 60 pairs of tumor and adjacent normal NSCLC tissue specimens from nonsmoking women in Taiwan, and the GSE33532 dataset, including 4 different sites of individual primary tumors and matched distant normal lung tissue from 20 patients with early-stage NSCLC in Heidelberg, Germany, for the analysis of the correlation between expressions of PATZ1 and either CD274, CDH1, or VIM; the GSE10072 dataset, including 58 LUAD samples and 49 non-tumor adjacent tissues collected from several hospitals in Italy, for correlation analyses between expressions of PATZ1 and either CDH1, VIM, or SOX2. From the TCGA, we used a dataset of 515 LUAD samples for overall survival and correlation analysis between PATZ1 and CD274; a dataset of 81 LUSC samples for the analysis of the correlation between PATZ1 and SOX2 expression levels; and metadata from 994 patients, including 494 with LUSC and 500 with LUAD, for survival analysis. Finally, an integrated database from the Cancer Biomedical Informatics Grid (caBIG), GEO, and TCGA repositories [32] was used for overall survival (OS) analysis in 524 LUSC patients and progression-free survival (PFS) after immunotherapy in 463 PAN-cancer patients, through the Kaplan–Meier platform [33]. 2.2. Tissue-Microarray and Immunohistochemical StudyThe tumor area of the preliminarily selected NSCLC samples was cored for the development of the Tissue Micro Array (TMA). TMA building and immunohistochemical staining was performed as previously described [34]. Primary antibodies were directed to PATZ1 (custom polyclonal antibody R1P1, Primm, Milano, Italy) and PD-L1 (monoclonal antibody SP263, Ventana Medical Systems, Tucson, AZ, USA). The primary antibody against PATZ1 is a previously described rabbit polyclonal antibody [20,28,34] raised against a peptide in the N-terminal region of the human PATZ1 protein (aa 1-276). Immunohistochemistry in mouse tissues was performed using the avidin–biotin–peroxidase LSAB+ kit (Dako, Glostrup, Denmark) on 5 μm thick sections as previously described [24]. Briefly, endogen peroxidases were quenched by incubation in 0.1% sodium azide with 0.3% hydrogen peroxide for 30 min at room temperature. Non-specific binding was blocked by incubation with nonimmune serum. The antibodies used were E-cadherin (24E10) Rabbit mAb #3195 (Cell signaling, Danvers, MA, USA) diluted 1:400, N-cadherin (D4R1H) XP Rabbit mAb #13116 (Cell signaling) diluted 1:100, vimentin (D21H3) XP Rabbit mAb #5741 (Cell signaling) diluted 1:200, and PD-L1 (E1L3N) XP Rabbit mAb #13684 (Cell signaling) diluted 1:200. 2.3. Cell Culture, Transfections, and PATZ1 Subcellular LocalizationA549 and H1299 human LUAD cells were obtained from the American Type Culture Collection (Rockville, MD, USA) and grown in Dulbecco’s Modified Eagle Medium (DMEM, with 4500 mg glucose/L, 110 mg sodium pyruvate/L, and L-glutamine, Sigma, St. Louis, MO, USA) supplemented with 10% fetal bovine serum (FBS) (Sigma) and 1% penicillin–streptomycin. All cells were cultivated at 37 °C and 5% CO2 and were split every 2–3 days.Transfections were performed using jetPRIME® (Polyplus transfections, Illkirch, France), with pHa-PATZ1 plasmid or the empty vector pCEFL-HA as a negative control [10], following the manufacturer’s instructions. At 5 h after transfection, cells were harvested, washed twice in PBS, and plated for the different assays.For PATZ1 subcellular localization, the PATZ1-EGFP-C2 plasmid, carrying the PATZ1 cDNA fused with the enhanced green fluorescent protein [20], was transfected as above. Green fluorescence (485 nm excitation, 510 nm emission wavelengths) was measured on a Nikon eclipse Ti2 microscopy using the NIS-elements AR software (Nikon Instruments Inc., Melville, NY, USA). To further assess the nuclear localization of the PATZ1-EGFP protein, cells that were previously seeded on a coverslip for 24 h were fixed in 4% paraformaldehyde (PFA) for 20 min at room temperature and stained for 5 min at RT with 1.5 μM 4′,6-Diamidino-2-phenylindole (DAPI, D9542, Sigma). After three washes with Dulbecco’s phosphate-buffered saline (DPBS), coverslips were mounted with glycerol/DPBS. Samples were visualized by green fluorescence (then converted in red on the images), for the PATZ1-EGFP protein, and blue fluorescence (359 nm excitation, 457 nm wavelengths), for DAPI-stained nuclei, using Zeiss LSM 700 META confocal microscopy equipped with a Plan-Apochromat 63×/1.4 Oil DIC objective. 2.4. Cell Viability, Tripan Blue Exclusion, and Colony Formation AssaysCells plated in 96-well plates (5000/well) were analyzed for cell viability at 24 h after transfection (Time 0) and in the following 24 h and 48 h by using CellTiter96 AQueous Non-radioactive Assay (Promega, Milano, Italy), following the manufacturer’s instructions. To assess the presence of dead cells, nonadherent and adherent cells were collected, and aliquots were mixed with an equal volume of 0.4% trypan blue (Life Technologies, Monza, Italy). All cells that incorporated the blue color were counted as dead cells. For the colony formation assay, cells were seeded out in appropriate dilutions to form colonies in 2 weeks. During this period, the transfected cells were selected with a standard medium containing 800 μg/mL G418 (D.B.A. Segrate, MI, Italy). G418-resistant colonies were fixed with methanol (25% v/v) and stained with crystal violet (0.1% w/v). The crystal violet was eluted with 10% SDS, and the absorbance was measured at 594 nm. Data are representative of at least three independent culture dishes per time point. 2.5. Cell Migration and Invasion AssaysThe migratory capacity of cells was analyzed using Transwell® inserts with 8.0 μm pore size (AlfaMed, Giugliano, NA, Italy). To the upper compartments, 50,000 cells in 0.1 mL of serum-free medium were added, while the lower compartments were filled with 0.6 mL of DMEM containing 10% FBS as a source of chemoattractants. The inserts were incubated for 48 h at 37 °C and 5% CO2. After incubation, cells were fixed in methanol (25% v/v) and stained with 600 µL crystal violet (0.1% w/v) for 30 min at 4 °C. Cells on the top surface of the filters were wiped off with cotton swabs. For A549, cells that had migrated into the lower compartment and attached to the lower surface of the filter were counted under the microscope. The migration rate was expressed as number of migrated cells per field of view. Alternatively, for H1299 cells, crystal violet was eluted in 10% SDS, and the absorbance was measured at 594 nm. Data are representative of at least three independent culture dishes per time point.For the invasion assay, Matrigel was thawed and liquefied on ice at 4 °C for about 5 h. The upper chambers of 24-well transwell inserts were coated with 50 μL of a mixture of serum-free medium and Matrigel (6:1; Euroclone, Pero, MI, Italy) and allowed to solidify at 37 °C for minimum 45 min. Cells were re-suspended in 100 µL of serum-free cell culture media, plated (100,000/well) on top of the filter membrane, and incubated for 48–72 h at 37 °C in 5% CO2. The lower chambers were filled with 500 μL DMEM containing 10% FBS for H1299 and 20% FBS for A549. The quantification of migrated cells through the extracellular matrix was performed counting the number of cells in 5 randomly selected fields after fixing and staining with methanol 25%/crystal violet 0.1% for 15 min, washing with PBS and drying off. 2.6. RNA Extraction, Reverse Transcription, and RTqPCRTotal RNA was extracted from cells using TRI-reagent solution (Sigma) following the manufacturer’s protocol. Reverse transcription was performed according to standard procedures using a SensiFAST™ cDNA Synthesis Kit (Aurogene, Rome, Italy). An Applied Biosystems 7900 Real-Time PCR Detection System (ABI 7900HT—Applied Biosystems, Waltham, MA, USA) was used to amplify each cDNA with iTaq Universal SYBR Green Supermix (Bio-Rad, Hercules, CA, USA). The PCR conditions were as follows: 95 °C for 10 min followed by 40 cycles at 95 °C for 15 s and 60 °C for 1 min. Subsequently, the dissociation curve was calculated to verify the amplification specificity. Each amplification reaction was repeated in duplicate. Primer pairs used were as follows: PATZ1 all variants: 5′-TACATCTGCCAGAGCTGTGG-3′/5′-TGCA CCTGCTTGATATGTCC-3′; ꞵ-ACTIN: 5′-CAAGAGATGGCCACGGCTGCT-3′/5′-TCCTTCTGCATCCTGTCGGCA -3′; CDH1: 5′-GCCTCCTGAAAAGAGAGTGGAAG-3′/5′-TGGCAGTGTCTCTCCAAATCCG-3′; VIM: 5′-GACCAGCTAACCAACGACAAA-3′/5′-GAAGCATCTCCTCCTGCAAT-3′.The 2−ΔΔCT method was used to calculate the gene expression levels [35]. Beta-ACTIN was used as the internal normalizer for gene expression. 2.7. Protein Extraction, Western Blotting, and AntibodiesHarvested cells were lysed in high-salt extraction buffer (10 mM Hepes pH 7.8, 400 mM NaCl, 0.1 EGTA, 0.5 mM DTT, 5% glycerol, and 0.5 mM PMSF) supplemented with 25% proteinase inhibitor cocktail (Complete Mini—Roche, Basel, Switzerland). The concentration of proteins in cell lysates was quantified by the Bio-Rad Protein Assay Dye Reagent Concentrate (Bio-Rad), and 40 μg protein was loaded in each lane. Samples were electrophoresed with SDS–PAGE (10%) and blotted for 1 h onto PDVF membranes (Immobilon-P, Millipore, Milano, Italy). The membranes were activated with methanol (100%) and blocked with 5% non-fat milk for 1 h at room temperature (RT). Blots were incubated with the primary antibodies overnight at 4 °C, and then with the secondary antibodies for 1 h at RT, before being visualized by Clarity Western ECL Substrate (Bio-Rad). Five to seven washes in TTBS buffer were done after each antibody incubation. The antibodies used were as follows: anti-PATZ1 [20]; anti-PD-L1 (Cell Signaling, Danvers, MA, USA #13684, 1:1000); anti-vimentin (Cell Signaling, D21H3, 1:1000); anti-vinculin (Santa Cruz, Dallas, TX, USA, sc-73614, 1:1000); HRP-conjugated goat-anti-rabbit IgG (Santa Cruz, sc-2004, 1:2000); and HRP-conjugated goat-anti-mouse IgG (Santa Cruz, sc-2005, 1:2000). 2.8. Statistical Analysis and Kaplan–Meier Survival CurvesPearson’s χ2 test was used to evaluate the correlations between the PATZ1 score and the clinical variables (age, gender, grade, subtype, metastases). All correlations within the publicly available datasets were assessed by one-way analysis of variance (ANOVA), through the R2: genomic Analysis and Visualization platform [36].Kaplan–Meier survival curves were used to analyze OS/PFS, and statistical significance was assessed by the log-rank test. The stratification of High/Low PATZ1 in the analysis of public datasets was based on RNA expression resulting from the scan expression function of the above mentioned R2 platform, where the best expression cut off is established based on statistical testing (log-rank test).All other statistical analyses were performed using GraphPad Prism 6 software (GraphPad Software, La Jolla, CA, USA). Each experiment was independently repeated three times, and the results are presented as the mean ± standard error (SE). A t-test was performed to determine the differences between two groups. A probability (p) value less than 0.05 was considered statistically significant. 2.9. AnimalsPatz1-knockout mice and their pathological phenotype were previously described [9,37]. Briefly, the Patz1 gene targeting vector was derived from a λΦXII phage library of a 129SvJ mouse strain (Stratagene, La Jolla, CA, USA). It was designed to delete a 2317-bp PstI-XhoI fragment including the start codon, the coding region for the POZ domain, the AT-hook, and the first four zinc fingers. The targeting construct was electroporated into 129SvJ-derived embryonic stem cells (ES). Two correctly targeted ES clones were injected into C57Bl/6J blastocysts. Both gave rise to germ line chimeras that were backcrossed to C57Bl/6J females to obtain heterozygous Patz1-knockout (ko) offspring. All Patz1-ko mice and their wild-type controls were maintained, in a mixed 129SvJ/C57Bl/6J genetic background, under standardized non-barrier conditions in the Laboratory Animal Facility of the Istituto dei Tumori di Napoli. All studies were conducted in accordance with Italian regulations for experimentations on animals. For histologic examination, dissected tissues were fixed by immersion in 10% formalin and embedded in paraffin. Mounted sections (5 μm thick) were stained with hematoxylin and eosin using routine procedures. 3. Results 3.1. Tissue Micro-Array Design and Clinicopathological DataOne hundred and four NSCLC tissue samples were used for TMA building, using three tissue cores taken from two to three discrete but representative regions of each individual case. The main clinicopathological data included in the TMA are set out in Table 1. The series included 29 (27.9%) women and 75 (72.1%) men, with a median age of 65.6 ± 2.77 years. In our histological samples, there were 43 (41.3%) LUSCs and 61 (58.7%) LUADs. Most women (72.4%) developed LUAD rather than LUSC, while men developed LUAD or LUSC at almost the same frequency. Indeed, 81.4% of LUSCs were diagnosed in men, consistent with most recent studies showing men are more likely to get LUSC [38]. Regarding tumor cell differentiation, both LUSCs and LUADs in the TMA included well-differentiated (G1), moderately differentiated (G2), and poorly differentiated (G3) tumors in the percentages indicated in Table 1. 3.2. PATZ1 Is Differently Expressed and Mislocalized in NSCLCWe analyzed PATZ1 expression by immunohistochemistry in the TMA described above. In the normal peritumoral tissue (bronchiolar and alveolar), PATZ1 was expressed in a low percentage of cells (

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