Shuye Lin,Hanli Xu,Lin Qin,Mengdi Pang,Ziyu Wang,Meng Gu,Lishu Zhang,Cong Zhao,Xuefeng Hao,Zhiyun Zhang,Weimin Ding,Jianke Ren,Jiaqiang Huang
UHRF1/DNMT1–MZF1 axis-modulated intragenic site-specific CpGI methylation confers divergent expression and opposing functions of PRSS3 isoforms in lung cancer
Lung cancer,Intratumor heterogeneity,Splice variants,Intragenic CpG methylation,Protease serine 3,Myeloid zinc finger 1,UHRF1/DNMT1,5-Aza-CdR
As confusion mounts over RNA isoforms involved in phenotypic plasticity, aberrant CpG methylation-mediated disruption of alternative splicing is increasingly recognized as a driver of intratumor heterogeneity (ITH). Protease serine 3 (PRSS3), possessing four splice variants (PRSS3-SVs; PRSS3-V1–V4), is an indispensable trypsin that shows paradoxical effects on cancer development. Here, we found that PRSS3 transcripts and their isoforms were divergently expressed in lung cancer, exhibiting opposing functions and clinical outcomes, namely, oncogenic PRSS3-V1 and PRSS3-V2 versus tumor-suppressive PRSS3-V3, by targeting different downstream genes. We identified an intragenic CpG island (iCpGI) in PRSS3. Hypermethylation of iCpGI was mediated by UHRF1/DNMT1 complex interference with the binding of myeloid zinc finger 1 (MZF1) to regulate PRSS3 transcription. The garlic-derived compound diallyl trisulfide cooperated with 5-aza-2′-deoxycytidine to exert antitumor effects in lung adenocarcinoma cells through site-specific iCpGI demethylation specifically allowing MZF1 to upregulate PRSS3-V3 expression. Epigenetic silencing of PRSS3-V3 via iCpGI methylation (iCpGIm) in BALF and tumor tissues was associated with early clinical progression in patients with lung cancer but not in those with squamous cell carcinoma or inflammatory disease. Thus, UHRF1/DNMT1–MZF1 axis-modulated site-specific iCpGIm regulates divergent expression of PRSS3-SVs, conferring nongenetic functional ITH, with implications for early detection of lung cancer and targeted therapies.
UHRF1/DNMT1–MZF1 axis-modulated intragenic site-specific CpGI methylation confers divergent expression and opposing functions of PRSS3 isoforms in lung cancer

As confusion mounts over RNA isoforms involved in phenotypic plasticity, aberrant CpG methylation-mediated disruption of alternative splicing is increasingly recognized as a driver of intratumor heterogeneity (ITH). Protease serine 3 (PRSS3), possessing four splice variants (PRSS3-SVs; PRSS3-V1–V4), is an indispensable trypsin that shows paradoxical effects on cancer development. Here, we found that PRSS3 transcripts and their isoforms were divergently expressed in lung cancer, exhibiting opposing functions and clinical outcomes, namely, oncogenic PRSS3-V1 and PRSS3-V2 versus tumor-suppressive PRSS3-V3, by targeting different downstream genes. We identified an intragenic CpG island (iCpGI) in PRSS3. Hypermethylation of iCpGI was mediated by UHRF1/DNMT1 complex interference with the binding of myeloid zinc finger 1 (MZF1) to regulate PRSS3 transcription. The garlic-derived compound diallyl trisulfide cooperated with 5-aza-2′-deoxycytidine to exert antitumor effects in lung adenocarcinoma cells through site-specific iCpGI demethylation specifically allowing MZF1 to upregulate PRSS3-V3 expression. Epigenetic silencing of PRSS3-V3 via iCpGI methylation (iCpGIm) in BALF and tumor tissues was associated with early clinical progression in patients with lung cancer but not in those with squamous cell carcinoma or inflammatory disease. Thus, UHRF1/DNMT1–MZF1 axis-modulated site-specific iCpGIm regulates divergent expression of PRSS3-SVs, conferring nongenetic functional ITH, with implications for early detection of lung cancer and targeted therapies.

The accumulation of dynamic genetic and nongenetic variant alterations that disrupt the balance between the expression of oncogenes and tumor suppressor genes (TSGs) contributes to intratumor heterogeneity (ITH). Lung cancer is the current leading cause of global cancer-related mortality and morbidity and exhibits extensive ITH. Lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) are the two predominant histological subtypes of non-small cell lung cancer (NSCLC) and exhibit distinct pathological and clinical features that require different clinical management. ITH in NSCLC hinders the development of personalized biomarker-based therapeutic interventions and early diagnosis2, 3, 4. A growing number of studies stemming from a deeper understanding of “intradriver heterogeneity” have revealed that not all genetic abnormalities lead to functionality changes and that pervasive somatic mutations are detected in nonmalignant tissues1, 2, 3, 4. These findings have raised concerns that certain genetic variants act as “noise”, which may insufficiently indicate malignant transformation or yield unreliable biomarkers,,. In contrast, through large-scale characterization of sequence-function relations, nongenetic heterogeneity propagated by epigenomic and transcriptomic alterations has emerged as a driver of functional ITH,5, 6, 7. Among these alterations, alternative splicing (AS) is functionally important to ITH due to its capacity to generate tissue- and cell type-specific transcript variants or splice variants (SVs)8, 9, 10. Over 90% of human protein-coding genes undergo AS via alternative promoters (APs), exon skipping (ES), or alternative terminators (ATs),, which are preferentially present in cancer cells and further facilitate cellular phenotypic plasticity and functional diversity. These malignancy-associated splicing alterations have been proposed as hallmarks of cancer with implications in cancer diagnosis and treatment. However, to what extent abnormal SVs detected at the transcriptional level can be translated into distinct protein isoforms, thereby contributing to malignancy, remains unclear. As confusion mounts over the association between RNA isoforms and their functional diversity and phenotypic plasticity, studies have highlighted the importance of epigenetic regulation of AS through either interfering with RNA polymerase II-mediated elongation or an interplay between epigenetic modifiers at differentially methylated regions (DMRs) to change chromatin accessibility13, 14, 15. For instance, differential CpG methylation occurs within intergenic regions or the body of genes, preferentially enriched within the gene body at exons adjacent to the introns of expressed genes, which may regulate splicing decisions associated with differential occupancy of methyl-sensitive transcription factors that interfere with RNA polymerase II-mediated elongation16, 17, 18, 19. While the involvement of local promoter hypermethylation in the silencing of TSGs and global DNA hypomethylation in genome instability are two well-established characteristics of cancer cells, the impact of CpG methylation on AS in relation to the malignant transformation of tumors has not been well characterized. Until recently, novel effects of epigenetic regulators on AS have been uncovered, among which ubiquitin-like with PHD and RING finger domain 1 (UHRF1) is a key regulator that interacts with DNA methyltransferase 1 (DNMT1) for DNA methylation20, 21, 22, suggesting that UHRF1/DNMT1 may serve as a novel AS regulator that interacts with other DNA methylation regulators, such as zinc finger proteins, to maintain cell function,,. Human protease serine 3 (PRSS3), encoded by the trypsinogen gene PRSS3, is an indispensable member of the trypsin family of serine proteases that exerts diverse bioactivities in cellular processes and cancer development,. PRSS3 is composed of four annotated transcript variants or SVs (PRSS3-V1–V4). PRSS3-V1 or trypsinogen 4 (TRY-4) encodes PRSS3-V1 or TRY-4 with 304 predicted amino acids and an unconventional leader sequence; PRSS3-V2 or mesotrypsinogen (MTG) encodes PRSS3-V2/MTG consisting of 247 deduced amino acids. PRSS3-V3 shares a cotranscription start site (cTSS) with PRSS3-V1 but has a different in-frame exon, resulting in PRSS3-V3/isoform B with a deduced 261 amino acids. PRSS3-V4 or trypsinogen 5 was cloned from keratinocytes and shown to participate in terminal keratinocyte differentiation. While PRSS3 represents a promising cancer biomarker and candidate drug target,,, PRSS3 exhibits paradoxical effects on tumor malignancy; namely, it may facilitate cancer metastasis and recurrence as an oncogene27, 28, 29, 30, 31, 32, 33, 34, 35, 36 or inhibit tumor growth as a TSG37, 38, 39, 40, 41. Notably, the upregulation of PRSS3/MTG has been associated with NSCLC metastasis, and with the malignancy of LUAD, whereas promoter hypermethylation of PRSS3 has been reported as a diagnostic biomarker for primary NSCLC,. These findings may be attributed to different PRSS3-SVs with unknown patterns of expression and function. In this study, we report the differential expression of PRSS3 transcripts with distinct functionalities and clinical outcomes in lung cancer. We further identified a UHRF1/DNMT1–MZF1 axis that enables transcript heterogeneity and increased functional divergence of PRSS3 by regulating iCpGI methylation (iCpGIm).

We used publicly available datasets from the following websites: the Cancer Cell Line Encyclopedia (CCLE, http://www.broadinstitute.org/ccle); The Cancer Genome Atlas (TCGA, https://www.cancer.gov/); the Cancer Dependency Map Portal (RRID: SCR_017655) (DepMap, https://depmap.org/portal/, DepMap Public 20Q3); and the Broad Genome Data Analysis Center (http://gdac.broadinstitute.org).

All oligonucleotide sequences and cDNA clones used to construct recombinant plasmids and the antibodies used in this study are listed in Supporting Information Tables S1 and S2, respectively.

The human NSCLC cell lines A549, NCI-H1299 and NCI-H460 were purchased from American Type Culture Collection (ATCC, USA), and 801-D cells were acquired from the Chinese National Infrastructure of Cell Line Resource. All cell lines were authenticated by the short tandem repeat (STR) method. TransSafeTM Mycoplasma Prevention Reagent (TransGene) was used to prevent mycoplasma contamination. The cells were grown in 90% RPMI 1640 (cat# A1049101, Gibco) with 10% fetal bovine serum (FBS; cat# 10099141, Gibco). The cells were split to low density (30% confluence) in overnight culture and then treated with 5-aza-2′-deoxycytidine (5-Aza-CdR, Sigma; 0.5 μmol/L, 96 h, culture medium exchanged every 24 h).

Genomic deletion of the PRSS3 transcripts (PRSS3KO) or MZF1 (MZF1KO) was carried out in A549 and 801-D cells using a CRISPR/Cas9 bivector lentivirus that was custom ordered from GeneChem (Shanghai, China). The sgRNAs were GGCACTGAGTGCCTCATCTC (PRSS3) and AGGGCTCCATCTTCTCTGAT (MZF1). Puromycin (puro, cat# A3740, ApexBio Technology) selection (2 μg/mL) was performed for 2 weeks. Stable overexpression of the PRSS3 transcripts in NCI-H460 and NCI-H1299 cells was established by transfection with PRSS3-V1 to PRSS3-V4 constructs, followed by selection with 0.5 mg/mL G418 (Invitrogen) for 2 weeks. MZF1KO A549 or 801-D cells were transfected with the MZF1-V2 or MZF1-V3 construct to establish stable A549 cells or transient 801-D cells with restored expression of the MZF1 transcripts; these cells represented the MZF1KO+V cell model. Short hairpin RNA against the DNMT3A and DNMT3B plasmids and DNMT1-, DNMT3A- and DNMT3B-overexpression plasmids were purchased from GeneChem (Shanghai, China). The shRNA sequences used in this study are listed in Table S1. Short hairpin RNA against the DNMT1 plasmid and DNMT1-overexpression plasmid was donated by Professor Jiemin Weng from East China Normal University (Shanghai, China). Chemically synthesized fragments containing the predicted MZF1 motifs in the PRSS3 intergenic region were inserted into the KpnI/XhoI sites of the pGL3-Basic reporter (Promega), with the pRL-TK vector (RRID: Addgene_11313) used as an internal control (Promega). In vitro transfection was performed using Lipofectamine 3000 (Invitrogen) following the manufacturer's instructions.

This study was approved by the Ethics Committee of the Beijing Chest Hospital (JYS-2021-013 and JYS-2021-033). Two independent cohorts were used in this study, and none of the patients enrolled in these cohorts had undergone prior anticancer treatment. All patients provided their informed consent. The first study cohort consisted of 43 LUAD patients collected from the Department of Cancer Research Center, Beijing Chest Hospital (Supporting Information Table S3) and 94 specimens printed in a commercialized tissue array (cat# HLugA180Su03, Outdo Biotech Company) with follow-up for survival analysis (Table 1). The follow-up period ranged from the date of diagnosis to the date of death or the last date of information as the end point if no event was documented by March 5, 2021. The second cohort included 54 patients (Table 2 and Supporting Information Table S4). Fifteen of these patients had chronic pneumonia, 25 had LUAD, and 14 had LUSC. BALF specimens and in situ tissue samples were obtained through bronchoscopy and radical resection, respectively. BALF specimens were collected using a QIAsymphony PAXgene Blood ccfDNA Kit (QIAGEN). The tissue samples were snap-frozen in liquid nitrogen in preparation for RNA extraction. Clinicopathological data were obtained from clinical and histopathological reports. Histological evaluation of the specimens was carried out by two senior pathologists. The severity of NSCLC was classified according to the 7th edition tumor staging system recommended by the American Joint Committee on Cancer.

Total protein was prepared using RIPA lysis buffer (Beyotime Biotech). Cell culture supernatant was collected and concentrated using a Microcon-10 kDa Centrifugal Filter Unit with Ultracel (Millipore). The protein content was measured using a Compat-Able BCA Protein Assay Kit (Thermo Scientific). Proteins were resolved via sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and transferred onto PVDF membranes using a Bio-Rad Mini PROTEAN 3 system (Bio-Rad). The membranes were blocked with PBS containing 5% milk and 0.1% Tween-20 at room temperature for 1 h. The membranes were then immunoblotted with the desired primary antibodies and incubated with the corresponding horseradish peroxidase-conjugated anti-mouse or anti-rabbit secondary antibodies (Table S2). Immunoreactive bands were visualized using an Amersham ECL Western Blotting Detection Kit according to the manufacturer's instructions. β-Actin served as a loading control.

The antibodies used in the staining are listed in Table S2. IF and IHC were performed as previously described. The cells for IF were fixed with 4% paraformaldehyde at room temperature for 10 min followed by washing and preblocking. The cells were incubated overnight at 4 °C with primary antibodies followed by incubation with CoraLite 488- or CoraLite 549-conjugated secondary antibodies for 1 h. DAPI was used for nuclear staining (10 μg/mL in PBS, Invitrogen, Life Technologies). Images were then recorded via laser confocal microscopy (Olympus FV1000 Laser Scanning Confocal Microscope). The xenograft tumors isolated from nude mice were paraffin-embedded and sectioned at 5 mm for staining and histological analysis. Slices were incubated with primary antibodies overnight at 4 °C. The Dako REAL EnVision Detection System, Peroxidase/diaminobenzidine (DAB, DAKO), was used to visualize the staining in accordance with the manufacturer's instructions. Sections were counterstained with H&E. mIHC analysis of the tissue array was performed using an Opal 7-color fluorescent IHC kit (Akoya Biosciences) according to the manufacturer's instructions. The tissue array slides were first dewaxed and subjected to heat-induced antigen retrieval at 95 °C for 20 min and then incubated overnight with primary antibodies. The antibodies were stripped by microwave treatment before the next primary antibody was added. Finally, the slides were mounted after counterstaining with DAPI for 5 min. After washing, the slides were incubated at room temperature for 1 h with anti-mouse or anti-rabbit secondary antibodies labeled with horseradish peroxidase (HRP) (Akoya Biosciences). For opal signal generation, one of the following fluorophore tyramines was added to the slides to detect antibody staining: Opal Polaris 520, 570, 620, 650, or 690 for PRSS3 isoforms V1, V2, V3, V4 and pan-CK (dilution 1:2 to 1:1000, see Table S2). Images of the multiple-color Opal slides were obtained using a TissueFAXS Spectra S system (TissueGnostics), and quantitative analysis of protein expression was performed using an automated quantitative analysis system (TissueGnostics, StrataQuest_7.0.1.165).

The viability of A549, 801-D, NCI-H460 and NCI-H1299 cells seeded into 96-well plates at 2 × 103 cells/well was measured every day using a 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay kit (Abcam). A microplate reader was used to detect the absorbance at 490 nm as previously described,.

Cells were seeded in 6-well tissue culture plates (0.3 × 103 cells/well) in triplicate. Colonies containing more than 50 cells were counted after 1 week. The cells were fixed with 75% ethanol for 30 min and stained with 0.2% crystal violet (Beyotime Biotech, China) for 20 min following a previous protocol,.

Membranes with 8-μm pores (Corning) were inserted into a Transwell apparatus. The upper chamber of the apparatus was coated with Matrigel and seeded with 2 × 104 cells, which were incubated for 24 h,.

RNA was isolated using TRIzol Reagent (Invitrogen), and first-strand cDNA was synthesized with a Superscript First-Strand Synthesis System (Invitrogen). mRNA expression levels were analyzed using 2 × SYBR Green-based qPCR reagent on an ABI 7500 qPCR instrument (Applied Biosystems). The relative expression level of each gene was normalized to that of the same cDNA using the 2–ΔΔCt method and compared to its own control.

Genomic DNA was extracted using a QIAamp DNA Mini Kit (QIAGEN). DNA was extracted from the BALF and tissue samples using a QIAsymphony PAXgene Blood ccfDNA Kit (QIAGEN) following the manufacturer's standard protocol. A NanoDrop 1000 spectrophotometer (Thermo Fisher Scientific, Inc.) was used for DNA quantification. DNA was bisulfite modified using a Zymo DNA Methylation Kit (Zymo Research) and further analyzed via PCR or qPCR using methylated or unmethylated primer pairs. The positive and negative controls were from the Human Methylated & Nonmethylated DNA Set (Zymo Research). The relative levels of methylated and unmethylated PRSS3 determined by qPCR were normalized to β-actin expression using the 2–ΔΔCt method. The methylation of PRSS3 at the CpG site was also detected using a MassARRAY Compact system (Sequenom) provided by Oebiotech Company in Beijing. The primer pairs used to amplify the target regions are shown in Table S1. MassARRAY EpiTYPER (Sequenom) was used for data analysis to generate quantitative results for each CpG site or an aggregate of the results for multiple CpG sites.

For MeDIP, genomic DNA was extracted from lung cancer cells with/without transfection or 5-Aza-CdR treatment. After sonication, the fragmented DNA was immunoprecipitated with a monoclonal antibody against 5-methylcytidine (anti-5mC) or nonspecific IgG at 4 °C overnight. Ten percent of the sonicated DNA was saved as an input control. Immunoprecipitated DNA fragments were released by proteinase K digestion and then purified using a QIAquick purification kit (QIAGEN). The enrichment of the precipitated DNA was determined by qPCR and is presented as “% of input” after normalization to the genomic DNA pulled down by nonspecific IgG. ChIP assays were performed as previously described. Chromatin was prepared by sonication of cell lysates and preclearing with protein A beads. Aliquots of a precleared chromatin solution, named IP fractions, were incubated with 2 μg of antibody against DNMT1, UHRF1, or MZF1 or preimmune rabbit IgG on a rotating platform at 4 °C overnight. One percent of the IP fraction served as the ChIP input control. The antibody-enriched protein–DNA complexes were precipitated with protein A beads from the IP fractions. DNA fragments were released by reverse crosslinking and purified using a QIAquick purification kit. The immunoprecipitated DNA fractions were analyzed via qPCR.

A luciferase reporter assay was performed using a Dual-Luciferase Reporter Assay System (Promega) with the pGL3-Basic luciferase reporter system. Cells were transfected with promoter-specific luciferase constructs and controls using Lipofectamine 3000 (Invitrogen). The luciferase signal was first normalized to the reference luciferase signal and then to the signal from the control group.

The animal handling protocols and all in vivo experimental procedures were approved by the Institutional Animal Ethics Committee of Beijing Chest Hospital (Beijing, China). For the in vivo gain-of-function experiment, NCI-H460 cells (1 × 106) transfected with PRSS3-V1, PRSS3-V2, PRSS3-V3, PRSS3-V4 or control vector (Vector) in 0.1 mL of PBS were subcutaneously injected into both flanks of 4-week-old BALB/c female athymic mice (Vital River Laboratories, Beijing, China). To assess the effect of both 5-Aza-CdR and DATS on lung tumorigenicity, A549 cells (2 × 106) transfected with MZF1L or control vector (Vector) in 0.1 mL of PBS were injected into mice. Eight days after subcutaneous implantation, the mice were treated with DATS (i.p., 20 mg/kg) and/or 5-Aza-CdR (i.p., 0.5 mg/kg) or saline once per week. The tumor diameters and body weights were measured and documented every 4 days until the NCI-H460 cell xenograft tumor-bearing nude mice were sacrificed on Day 16 or every 8 days until the animals implanted with A549 cells were sacrificed on Day 32. NSCLC tumor xenografts were isolated and weighed. Tumor volume was calculated by measuring the longest (a) and shortest (b) dimensions of the tumor and calculated using the formula Eq. (1):where a is the longest dimension and b is the shortest dimension.

The data are expressed as the mean ± standard deviation (SD) of at least three independent experiments. The expression levels of the PRSS3 transcripts and their epigenetic alterations were analyzed using a two-tailed Student's t-test or one-way analysis of variance (ANOVA) with Tukey's post hoc test. The relationships between the expression of PRSS3-SVs and clinicopathologic characteristics were measured with χ2 exact tests. Spearman's rank test and Fisher's exact test were used to analyze clinicopathological correlations. Overall survival (OS) was calculated from the date of surgery to the date of death from NSCLC or the last follow-up. Cancer-related survival and prognostic value were analyzed using the Kaplan–Meier method and compared using log-rank tests. Statistical signiﬁcance was regarded as P < 0.05. All statistical analyses were performed using SPSS (RRID: SCR_002865) version 23.0 (IBM Corp.) and R package (R Studio).

We analyzed the expression of PRSS3 and its transcripts (PRSS3-SVs, V1–V4) in lung cancer cell lines. Analysis of CCLE RNA-seq data revealed divergent expression of PRSS3, defined as PRSS3Low (71%) and PRSS3High (29%), in 187 lung cancer cell lines compared to the immortalized lung cell line SALE (Supporting Information Fig. S1A, Table S5). In contrast to the infrequently or barely expressed PRSS3-V3 and/or PRSS3-V4 transcripts, PRSS3-V2 and/or PRSS3-V1 (PRSS3-V1/V2) were the major transcripts contributing to PRSS3 expression in both PRSS3High and PRSS3Low lung cancer cells (Fig. 1A, Fig. S1B and 1C). RT-qPCR with transcript-specific primers (Fig. S1D) showed that PRSS3 was differentially expressed in lung cancer cells (Fig. 1B) and that the PRSS3-V1/V2 transcripts were predominantly expressed (Fig. 1C). TCGA RNA-seq data from FIREHOSE Broad GDAC showed that, in addition to minimal expression of PRSS3-V3 and the absence of PRSS3-V4, PRSS3-V1/V2 were differentially expressed in tumor tissues of patients with LUAD (n = 515) (Supporting Information Table S6) compared to normal control lung tissues (n = 59), similar to the expression of PRSS3 in the above cell lines (Fig. 1D). RT-qPCR showed that PRSS3High was due to increased expression of PRSS3-V1/V2 (PRSS3-V1/V2High) and that the decreased expression of PRSS3-V3 (PRSS3-V3Low) was evident in LUAD tissues compared to matched adjacent tissues, including 13 pairs of LUAD tissues and adjacent noncancerous lung tissues (Fig. 1E) and 30 additional LUAD tissues (Fig. S1E, Table S3); thus, the aberrant expression of PRSS3 mRNA was a result of the divergent expression of the PRSS3 transcripts in lung cancer. Characterization The characterization of the four PRSS3-SVs at the protein level was not clear owing to a lack of isoform-specific antibodies. We thus used a commercial rabbit polyclonal antibody against PRSS3 (panantibody) and generated antibodies against the PRSS3-V1 to PRSS3-V4 isoforms (Supporting Information Fig. S2). Western blot analysis of PRSS3 using the anti-pan-PRSS3 antibody revealed multiple bands in the lysates of A549 and 801-D lung cancer cells in addition to a single band in the culture supernatants collected from A549 cells (Fig. 1F). Further analysis showed that the PRSS3 isoforms V1 to V3 were detected in A549 cells, and among these isoforms, PRSS3-V2 was present in both cell lysates and supernatants; additionally, PRSS3-V1 and PRSS3-V2 were identified in the lysate of 801-D cells (Fig. 1G). Interestingly, immunofluorescence (IF) assays revealed distinct subcellular localizations of the PRSS3 isoforms in A549 cells, specifically, cytoplasmic PRSS3-V1 and PRSS3-V4, cytoplasmic/nuclear PRSS3-V3, and cytoplasmic/membranous PRSS3-V2, despite PRSS3-V4 being undetectable by Western blotting (Fig. 1H). We next examined PRSS3 isoforms in a tissue array consisting of a cohort of 180 tissue samples (TissueArray Cohort) (Table 1) using multiplexed immunohistochemistry (mIHC) with antibodies against PRSS3 isoforms and cytokeratin (CK), a cancer-specific protein (Supporting Information Fig. S3). The staining images showed that PRSS3-V1/V2 and PRSS3-V4 were localized in the CK-positive (CK+) tissue area, while PRSS3-V3 was localized in the CK-negative (CK−) tissue area (Fig. 1I). Quantitative analysis revealed PRSS3-V1/V2High but PRSS3-V3Low in LUAD tumor tissues compared to adjacent noncancerous lung tissues, consistent with the finding of PRSS3-V1/V2High and PRSS3-V3Low in CK+ tumor specimens (Fig. 1J). These results suggest that the divergent expression of the PRSS3 transcripts (PRSS3-V1/V2High and PRSS3-V3Low) is consistently distinct not only at the mRNA level but also at the protein level. The distinct distribution of the PRSS3 isoforms suggests their functional divergence.

To assess the functional roles of PRSS3-SVs in lung cancer, PRSS3 was deleted from PRSS3High A549 and 801-D cells via CRISPR/Cas9 genome editing, while PRSS3Low NCI-H460 and NCI-H1299 cells were stably transfected with PRSS3-V1–V4 cDNA (Supporting Information Fig. S4). PRSS3 deletion significantly reduced A549 and 801-D cell proliferation and migration capacity (Fig. 2A), whereas ectopic expression of PRSS3-SVs resulted in a dual effect consisting of protumorigenic PRSS3-V1/V2 and antitumorigenic PRSS3-V3 on NCI-H460 and NCI-H1299 cells despite the absence of a significant effect observed in PRSS3-V4-overexpressing cells (Fig. 2B). Moreover, NCI-H460 cells overexpressing PRSS3-V1–V4 were then injected subcutaneously into nude mice. PRSS3-V3 overexpression resulted in a significant reduction in the volume of xenograft tumors formed by NCI-H460 cells. Conversely, PRSS3-V1/V2 overexpression significantly promoted xenograft tumor growth (Fig. 2C, Supporting Information Fig. S5). These results suggest distinct functions of PRSS3-SVs in lung cancer: oncogenic PRSS3-V1/V2, tumor-suppressive PRSS3-V3 and nonfunctional PRSS3-V4. Clinical association studies of the TissueArray cohort revealed a significant association of PRSS3-V1High with early cancer stages and PRSS3-V2High with early tumor invasion (Table 1). This association was confirmed by analysis of the TCGA cohort, which showed cancer stage-associated increases in PRSS3 and PRSS3-V1/V2 (Supporting Information Fig. S6) and early clinical relevance of PRSS3-V1High (Supporting Information Table S6). Kaplan–Meier survival analysis of the TissueArray cohort revealed that LUAD patients with PRSS3-V1High or PRSS3-V2High had worse OS than those with low protein levels of PRSS3-V1 or PRSS3-V2, although the difference was not statistically significant. In contrast, PRSS3-V3High was associated with favorable outcomes (Supporting Information Fig. S7). To explore the functional basis of the PRSS3 transcripts, potential PRSS3-targeted downstream genes were profiled using network analysis of a dataset available from SEEK (http://seek.princeton.edu). Gain- and loss-of-function analyses of the 8 key hub genes in the network (PRSS1, LGALS4, CFTR, REG1A, IL22RA1, F2RL1, REG4 and MUC13) (Supporting Information Fig. S8A) showed specific associations between MUC13 and PRSS3-V1, F2RL1 (PAR2) and PRSS3-V2, and CFTR/REG1A and PRSS3-V3 at both the mRNA and protein levels (Fig. 2D). RT-qPCR analysis further showed a significant positive correlation between PRSS3-SVs and the associated genes in LUAD tissues (n = 30) (Fig. 2E, Table S3). Kaplan–Meier survival analysis showed a significantly worse OS for LUAD patients with MUC13High or F2RL1High but a favorable outcome for LUAD patients with CFTRHigh or REG1AHigh in the TCGA cohort (n = 502) (Fig. S8B), suggesting that PRSS3 transcripts confer diverse functional outcomes by targeting different molecular pathways. Taken together, these findings suggest that divergent expression of PRSS3 transcripts exerts dual cellular functions, namely, the oncogenic function of PRSS3-V1/V2 and the tumor-suppressive function of PRSS3-V3, with correlated clinical relevance based on different downstream target genes. Therefore, these transcripts contribute to functional heterogeneity during cancer progression.

AS within the 5′ region of PRSS3 involves multiple transcription start sites (TSSs), among which the cotranscription start site (cTSS) of PRSS3-V1 and PRSS3-V3 (PRSS3-V1/V3) is closer to the downstream TSS of PRSS3-V4 (356 nt) and far from the downstream TSS of PRSS3-V2 (45,296 nt) (Fig. 3A). Considering the epigenetic regulation of the AS process, and the epigenetic alteration of PRSS3 reported in several cancer types37, 38, 39, 40, 41, we analyzed the epigenetic contribution to the differential expression of the PRSS3-SVs (except for PRSS3-V4 due to its absence) in lung cancer cells and tissues using PRSS3 methylation data from CCLE and TCGA datasets, respectively. Two-way hierarchical clustering heatmap analysis of PRSS3 methylation within 3 CpG islands (defined as CpGI_1-3) (Fig. 3A) in CCLE lung cancer cell lines showed frequent upstream hypermethylation (CpGI_1) to more differential downstream methylation (CpGI_2 and _3) (Supporting Information Fig. S9A). Further analyses of a TCGA-LUAD dataset showed PRSS3 methylation occurring at 6 CpG sites scattered along a broad genomic region from –170 to 34,654 nt to the cTSS (defined as CpG sites A to F) (Fig. 3A). As shown in Fig. S9B, a CpG site-correlated methylation pattern was observed to be distinct between upstream hypermethylation (CpG site A) and differential intragenic methylation, such as hypomethylation of CpG sites B and C, versus frequently altered methylation of CpG sites E, D and F. These data suggest a dynamic methylation status in PRSS3 genomic loci from a hypermethylated upstream region to more dynamically and differentially methylated intragenic regions or gene bodies in both lung cancer cell lines and tissues. Comparative analysis showed that PRSS3 expression was inversely correlated with the methylation of all three CpGIs in lung cancer cell lines. However, the expression of PRSS3-SVs was differentially associated with CpGI methylation; PRSS3-V1 expression was negatively correlated with the methylation of CpGI_1-3, and a negative correlation was observed between PRSS3-V2 and CpGI_2 and 3 methylation and between PRSS3-V3 and CpGI_3 methylation (Fig. 3B, Supporting Information Fig. S10A). PRSS3 methylation of 6 CpG sites in TCGA LUAD tissue specimens revealed a significant inverse association of CpG sites E, D, F and A methylation with PRSS3-V1, CpG sites E, D and F methylation with PRSS3-V2, and CpG sites E and D with PRSS3-V3 (Fig. 3C, Fig. S10B). Although differential methylation was negatively associated with the expression of PRSS3 transcripts in lung cancer cells and tissues, an intragenic region (relative to the cTSS) covering CpGI_3 and CpG sites D and E was found to be more specifically correlated with PRSS3-V3 expression (Fig. 3B and C, Fig. S10A and S10B), suggesting that this intragenic CpG island (iCpGI) (relative to the cTSS) may be a DMR (Fig. 3G) specific for epigenetic regulation of the differential expression of PRSS3 transcripts in lung cancer. We then validated the methylation-specific effect on the expression of PRSS3 transcripts in lung cancer cells and tissues. MSP-qPCR showed nonmethylation in PRSS3High (umPRSS3High) A549 and 801-D cells and partial methylation or methylation in PRSS3Low (mPRSS3Low) NCI-H1299 and NCI-H460 cells (Fig. 3D). Consistently, an increased methylation frequency was determined in 13 paired LUAD tissues (Fig. 3E). A MassARRAY assay was then performed on lung cancer cells to quantitatively measure iCpGI methylation. Although overall iCpGI hypomethylation (iCpGIum) was observed in A549 and 801-D cells in contrast to iCpGI hypermethylation (iCpGIm) in NCI-H1299 and NCI-H460 cells (Fig. 3F), CpG sites in iCpGI were observed to exhibit a range of hypomethylation to hypermethylation in PRSS3High cells but showed consistent hypermethylation in PRSS3Low cells, similar to CpG site methylation around exon 4 (Fig. 3G). However, CpG sites located at 459–623 (CpG_459–623) showed relatively constitutive hypermethylation in all examined cells, in which CpG sites at 545 and 551 (CpG_545, 551) displayed the most differential methylation in association with the expression of PRSS3 transcripts (Fig. 3G, Supporting Information Fig. S11). These results confirm the dynamic and differential methylation of iCpGI in lung cancer, which may specifically regulate the expression of PRSS3 transcripts. In support of this conclusion, the demethylation agent 5-Aza-CdR led to increased overall expression of PRSS3 in PRSS3Low lung cancer cells but decreased PRSS3 expression in PRSS3High lung cancer cells (Fig. 3H), a bipolar effect attributed to its capacity to upregulate PRSS3-V1/V3 but downregulate PRSS3-V2, resulting in the differential expression of PRSS3 as a whole (Fig. 3I). MassARRAY analysis revealed an iCpGI-demethylation effect of 5-Aza-CdR in both A549 and NCI-H460 cells, except for the less pronounced change in CpG_545,551 in A549 cells (Fig. 3J), suggesting a specific regulation of iCpGIm associated with PRSS3 transcript expression in lung cancer.

To clarify the epigenetic mechanism regulating the expression of PRSS3-SVs, three DNA methyltransferases (DNMTs) were examined. All three DNMTs were found to be expressed in 801-D cells, but DNMT1 was shown to be weakly expressed in PRSS3High A549 cells and relatively highly expressed in PRSS3Low NCI-H460 and NCI-H1299 cells (Fig. 4A). MeDIP-qPCR was performed to determine whether DNMT1-mediated methylation is specifically associated with PRSS3, and the results show that the anti-CpG methylation antibody enriched many more genomic DNA fragments associated with iCpGIs in DNMT1-overexpressing A549 cells than in control cells, whereas DNMT1 knockdown or 5-Aza-CdR treatment yielded fewer fragments from this region (Fig. 4B and C). MassARRAY further showed that DNMT1 promoted CpG methylation of iCpGI despite having less effect on the constitutively hypermethylated CpG_545,551 (Fig. 4D), in line with the results shown in Fig. 3, suggesting that DNMT1 mediates PRSS3 methylation by specifically targeting iCpGI. UHRF1 expression was parallel with that of DNMT1 (Fig. 4A) in both PRSS3High and PRSS3Low lung cancer cells (Fig. 4E), and their expression was associated with UHRF1-overexpressing A549 cells (Fig. 4F), suggesting the concomitant expression of DNMT1 and UHRF1 in lung cancer cells. Moreover, ChIP-qPCR using an anti-UHRF1 antibody showed that overexpressed UHRF1 in A549 cells was associated with significantly more iCpGI fragments (Fig. 4G). Furthermore, iCpGI fragments enriched by either anti-DNMT1 or anti-UHRF1 antibody were significantly more abundant in DNMT1-overexpressing A549 cells but less abundant in DNMT1-knockdown NCI-H460 cells (Fig. 4H). These results suggest that UHRF1 interacts with DNMT1 to target iCpGIm in the regulation of PRSS3 expression. To this end, overexpression of DNMT1 resulted in decreased PRSS3-V1/V3 but increased PRSS3-V2 expression in A549 cells, whereas an opposite expression pattern of PRSS3 transcripts was observed in DNMT1-knockdown NCI-H460 cells (Fig. 4I). Consistently, UHRF1 overexpression in A549 cells effectively downregulated PRSS3-V1/V3 but upregulated PRSS3-V2 expression (Fig. 4J and K). Additionally, overexpression or knockdown experiments showed that DNMT3A may regulate the expression of PRSS3-V2 more specifically, while DNMT3B tends to exert a regulatory effect on both PRSS3-V1 and PRSS3-V2 (Supporting Information Fig. S12). Thus, the UHRF1/DNMT1 complex modulated the divergent expression of PRSS3 transcripts by regulating iCpGIm.

To determine how UHRF1/DNMT1 anchors iCpGI to regulate the differential expression of PRSS3 transcripts, putative transcription factors that bind PRSS3 were searched in the PROMO and JASPAR databases. Along the 2-kb sequence of PRSS3 from −1000 nt to 1000 nt from the cTSS, four GC-rich consensus sequences located in the iCpGI with the top scores were identified as motif sites that bind myeloid zinc finger 1 (MZF1) and were named Motifs_1 through _4, all of which are close to or within PRSS3 iCpGI (Fig. 5A). MZF1 exerts transcriptional regulatory activity through its C-terminal zinc finger domain to bind GC-rich consensus sequences in target genes. However, among the three known SVs of MZF1 (MZF1-V1, MZF1-V2 and MZF1-V3), despite different 5′-UTRs and TSSs, MZF1-V1 and MZF1-V2 encode complete isoform 1 (MZF1L), whereas MZF1-V3 encodes C-terminal-truncated isoform 2 (MZF1S). Functionally unknown MZF1S lacks a zinc finger domain and may act as a “decoy” mutant of MZF1 (Fig. 5B). Considering that zinc finger proteins preferentially bind GC-rich motifs,,, we hypothesized that MZF1 is a methyl-sensitive transcription factor that participates in the epigenetic regulation of PRSS3 transcripts via UHRF1/DNMT1-regulated methylation. We therefore examined the effect of MZF1 on the expression of PRSS3 transcripts by establishing an MZF1KO+V A549 cell model in which endogenous MZF1 transcripts were deleted by CRISPR/Cas9 followed by transfection with constructs containing MZF1L (MZF1-V2) or MZF1S (MZF1-V3), with the resulting cells named MZF1KO+L and MZF1KO+S A549 cells, respectively (Fig. 5C). In addition, the transfection efficiency at the mRNA level of MZF1 transcripts was validated (Fig. 5D). The protein levels and nuclear localization of MZF1 isoforms were visualized using antibodies that specifically recognize MZF1L or MZF1S (Fig. 5E). Unlike the effects on PRSS3-V1 and PRSS3-V2, MZF1 deletion (MZF1KO) resulted in decreased expression of PRSS3-V3, and this effect was remarkably reversed by re-expression of the complete (MZF1KO+L), but not the truncated, (MZF1KO+S) isoform in A549 cells (Fig. 5F), suggesting that MZF1 transcriptionally regulates the differential expression of PRSS3 transcripts and more specific upregulation of PRSS3-V3, possibly through its C-terminal zinc finger domain binding to motifs in the PRSS3 iCpGI. To verify the specific binding of MZF1, four DNA fragments containing different MZF1-binding motifs (from FA containing all 4 motifs to FD containing only motif_4) were cloned and cotransfected with PRSS3-V1 or PRSS3-V3 into PRSS3-Low NCI-H460 cells. Luciferase activity was increased in cells transfected with fragments containing two to three motifs and was most dependent on motif_3 (Fig. 5G). ChIP-qPCR analysis revealed increased iCpGI fragments enriched by anti-MZF1 antibody in cells overexpressing MZF1KO+L but not MZF1KO+S (Fig. 5H), confirming the specific binding of MZF1 to iCpGI through its C-terminal zinc finger domain. In accordance with the immunofluorescence staining results, which showed that DNMT1 inhibited the nuclear colocalization of MZF1 (Fig. 5I), ChIP assays further showed the inhibitory effect of DNMT1 on the binding of MZF1 to iCpGI in either DNMT1-overexpressing A549 cells or DNMT1-deleted NCI-H460 cells (Fig. 5J). Considering the MZF1 motifs located in iCpGI, these results suggest an essential role of CpG site methylation status in the accessibility of MZF1 targeting to its motifs. These results reveal an epigenetic mechanism by which UHRF1/DNMT1-mediated site-specific iCpGI hypermethylation hampers the anchoring of MZF1 on its motifs to specifically regulate the differential expression of PRSS3 transcripts in lung cancer cells. Thus, this pathway was termed the UHRF1/DNMT1–MZF1 axis.

We previously showed that the garlic-derived compound diallyl trisulfide (DATS) acts as an epigenetic regulator and is capable of regulating MZF1 expression to exert its anticancer activity. To explore the role of UHRF1/DNMT1–MZF1 axis-mediated iCpGIm in specifically regulating the expression of PRSS3 transcripts, we established a DATS-treated A549 cell model (Supporting Information Fig. S13), a cell line with coexpression of PRSS3 transcripts. Compared to the lower doses (12.5 and 25 μmol/L), DATS treatment at a higher dose (50 μmol/L) achieved diminished antiproliferative and anti-invasive effects in A549 cells (Fig. 6A). The antitumor capacity of DATS was in parallel with the inhibition of PRSS3 transcript expression in A549 cells (low-dose for PRSS3-V1/V2 versus high-dose for all) (Fig. 6B) and the upregulation of UHRF1/DNMT1 (Fig. 6C). In DATS-treated cells, UHRF1/DNMT1 enriched more DNA fragments within the PRSS3 iCpGI at the high dose of DATS (Fig. 6D). Additionally, the upregulation of UHRF1/DNMT1 induced by 25 μmol/L DATS (Fig. 6C) was less associated with PRSS3 iCpGI (Fig. 6D), in line with the decreased expression of PRSS3-SVs induced by DATS at this concentration (Fig. 6B). This suggests that DATS at low doses may have a broad inhibitory effect on PRSS3-SVs in a dose-independent manner, rather than specifically targeting PRSS3 iCpGI, the methylation of which more specifically contributes to PRSS3-V3 expression (Fig. 3). This was correlated with more methylated iCpG fragments enriched by anti-5mC antibody in high-dose cells than in low-dose cells (Fig. 6E), suggesting that DATS enhanced iCpGm associated with UHRF1/DNMT1 at a high dose but reduced iCpGm at a low dose. The anticancer activity of DATS may be associated with its differential epigenetic regulation of PRSS3 transcripts in A549 cells, in which low-dose DATS may impair oncogenic PRSS3-V1/V2 but more robustly affect PRSS3-V3 at high doses. As supporting evidence, when PRSS3-SVs were ectopically expressed in high-dose DATS-treated A549 cells (Supporting Information Fig. S14), ectopic PRSS3-V3 displayed a more significant inhibitory effect than either PRSS3-V1 or PRSS3-V2 (Fig. 6F). Moreover, the ectopic expression of MZF1L showed an inhibitory effect on DATS-treated A549 cells comparable to that of 5-Aza-CdR (Fig. 6G), accompanied by upregulation of the expression of MZF1L and PRSS3-V3 (Fig. 6H). ChIP–qPCR assays showed that 5-Aza-CdR treatment significantly upturned the reduction of MZF1-associated PRSS3 iCpGI fragments in DATS-treated A549 cells (Fig. 6I). These results demonstrate a similar effect of ectopic MZF1L and 5-Aza-CdR treatment on PRSS3-V3 expression in DATS-treated A549 cells. Furthermore, as shown in Fig. 6J, in contrast to the demethylation effect of 5-Aza-CdR on A549 cells, MassARRAY analysis revealed that DATS was capable of demethylating the hypermethylated CpG sites and methylating the hypomethylated sites in iCpGI, which resulted in a higher average iCpGIm consistent with more methylated iCpG fragments enriched by high-dose DATS due to its ability to upregulate UHRF1/DNMT1 (Fig. 6C–E). Notably, 5-Aza-CdR displayed much more demethylating efficiency at the constitutively hypermethylated CpG sites located in or close to the MZF1 motifs in DATS-treated A549 cells (Figure 5, Figure 6K), where constitutive methylation was difficult to be erased by either DATS or 5-Aza-CdR treatment or DNMT1 disruption (Fig. 4D). Supportively, the comparable effects of DATS interacting with 5-Aza-CdR in the regulation of PRSS3 expression were observed in 801-D cells (Supporting Information Fig. S15). The results thus suggest that DATS acts antagonistically against 5-Aza-CdR at hypomethylated CpG sites but cooperates with 5-Aza-CdR to demethylate some constitutively hypermethylated CpG sites within PRSS3 iCpGI to increase the accessibility of the iCpGI, allowing MZF1 to specifically regulate PRSS3-V3 transcription. We next assessed the effect of 5-Aza-CdR and/or DATS in vivo. The combination of DATS and 5-Aza-CdR showed a significant synergistic effect in inhibiting lung tumorigenicity, which was comparable to the effect of MZF1L overexpression with or without DATS (Fig. 6L). Therefore, the findings suggest the epigenetic therapeutic potential of DATS in cooperation with 5-Aza-CdR to specifically regulate PRSS3 expression via the UHRF1/DNMT1–MZF1 axis.

The effects of iCpGIm on PRSS3 transcripts were evaluated in a cohort of BALF specimens (Table S4). RT-qPCR analysis showed that unlike PRSS3-V1High in LUSC samples and PRSS3-V2High in LUAD samples, PRSS3-V3 expression was significantly lower in BALF specimens from patients with LUAD or LUSC than in samples from patients with chronic pneumonia (Fig. 7A). MSP-qPCR analysis demonstrated that 72% of the LUAD samples (18 of 25) were hypermethylated, whereas all the samples from patients with chronic pneumonia (15/15) or LUSC (14/14) were hypomethylated (Fig. 7B, Table 2). Importantly, iCpGIm was correlated with LUAD (P < 0.001) and early lung cancer invasion depth (P = 0.047) (Table 2). Although differences in the association between iCpGIm and the expression of PRSS3-SVs were shown in BALF specimens (Fig. 7C), Spearman correlation analysis revealed that iCpGIm was significantly correlated with the expression of PRSS3-V1 and PRSS3-V3 in BALF samples from patients with LUSC and LUAD compared to inflammatory BALF samples (Fig. 7D). Importantly, iCpGI hypermethylation was more significantly associated with PRSS3-V3Low in BALF specimens from LUAD patients (Fig. 7C, D), consistent with the epigenetic silencing of PRSS3-V3 in lung cancer and tissues (Fig. 3B, C).

Data from the Genotype-Tissue Expression (GTEx) resource revealed the ubiquitous distribution but differential expression of PRSS3 in human tissues, suggesting a tissue-selective expression pattern. Studies of PRSS3 in malignant tumors have been hindered by a lack of isoform-specific antibodies to comparably delineate the function and distribution of the isoforms in different tissues. By using tailored isoform-specific antibodies and qPCR combined with the analysis of RNA-seq datasets, we found that the divergent expression of PRSS3 transcript isoforms in lung cancer was distinguished by high and low expression levels not only for each transcript but also between different transcripts (PRSS3-V1/V2High versus PRSS3-V3Low); additionally, minimal expression of PRSS3-V4 was observed. Moreover, all four PRSS3-SVs were differentially translated and presented different subcellular localizations, albeit with an abundance of PRSS3-V1/V2 observed in both lung cancer cells and tissues. In addition to the well-known property of secreted PRSS3-V2/MTG, which has been shown to be a pancreatic secretory protein exclusively expressed in human pancreatic tissue and fluid, scarcely expressed PRSS3-V3 was retained in the nucleus, suggesting its nuclear retention in lung cancer cells, a mechanism of defective mRNA assembly caused by aberrant splicing,. PRSS3-V3 is distinct through transcription to translation, which may confer an unpredictable function. Thus, these findings support divergent expression of transcripts in cell- and tissue type-specific regulation facilitating nongenetic ITH5, 6, 7, 8, 9, 10, 11, 12. The paradoxical effects of PRSS3 in several cancer types27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, were thought to be due to a dependence on cellular sources and the cancer microenvironment,,,, where aberrant expression of PRSS3 either by tumor cells themselves or by tumor-associated stromal cells plays a pleiotropic role in metastatic progression by preferentially targeting diverse substrates, such as the cell surface protein CD109 in malignant breast cells, amyloid precursor protein (APP)/protease nexin 2 in prostate cancer cells, tissue factor pathway inhibitor-2 (TFPI-2) in tumor endothelial cells (EC) isolated from ovarian carcinomas, and kallikrein-related peptidases (KLKs) in lung cancer cells. Moreover, esophageal adenocarcinoma cells (EACs) secrete PRSS3 via an autocrine loop to promote cell proliferation and survival. Pancreatic PRSS3/MTG and cathepsin B are continually coexpressed in human cholangiocarcinomas (CC) and hepatocellular carcinomas (HCC), contributing to CC invasion by degrading extracellular matrix proteins. However, others have reported that PRSS3 may play a tumor suppressive role in lung, esophageal, gastric, bladder, and HCC cancers due to epigenetic silencing of PRSS3 through promoter hypermethylation. In fact, diverse roles or conflicting effects of PRSS3 in cells have been shown even through cleaving protease-activated receptors (PARs), a PRSS3-mediated common pathway attributed to the differential expression and regulation of both PRSS3-SVs and PAR members (PAR1, PAR2, PAR3, and PAR4) and their various interactions,, e.g., mesotrypsin/trypsin IV did not activate PAR-2 or PAR-1 in human epithelial cells but activated PAR-1 in human and rat astrocytoma cells. We thus speculated that the functionality of PRSS3 is attributable to its cell- and tissue type-dependent differential transcript expression. By using gain- and loss-of-function approaches, we revealed that PRSS3 isoforms exert divergent biofunctions in lung cancer cells by interacting with different genes or pathways. While it is well established that the tissue-associated interplay between PRSS3-V2/MTG and PAR2 modulates inflammation and tumorigenesis in a manner unfavorable to the OS of patients with colon cancer32, 33, 34, we found that PRSS3-V1 may enhance the proliferation and metastasis of lung cancer cells, causing inferior survival associated with the mucin family member MUC13. However, PRSS3-V3 may exert its antitumor properties by targeting CFTR or REG1A, and the epigenetic silencing of PRSS3-V3 showed potential for the early diagnosis of cancer. These results uncover for the first time the molecular basis of the contradictory effects of PRSS3 in lung cancer and provide evidence of dual roles of PRSS3 depending on divergent expression of its transcripts, which are associated with different functionalities and phenotypic plasticity in a cell-type specific manner, thereby supporting SVs as nongenetic determinants that contribute to tumor functional heterogeneity,,. Our study also revealed epigenetic heterogeneity in the dysregulation of PRSS3 expression, as evidenced by the dynamic divergence of CpG methylation across the extended PRSS3 protomer region associated with the expression of PRSS3-SVs in lung cancer cells and tissues. Among the multiple DMRs identified in PRSS3 (data not shown), we found that the most differentially expressed iCpGIm was modulated by UHRF1 associated with DNMT1 but not DNMT3A/B. Although DNMT3A may tend to regulate PRSS3-V2, while DNMT3B has a regulatory effect on PRSS3-V1 and PRSS3-V2, UHRF1/DNMT1-MZF1 axis-modulated iCpGIm is more robust for the regulation of PRSS3-V3. The coordinated expression of UHRF1 and DNMT1 undergoes coregulation in various tissues and cells, in which UHRF1 recruits and regulates DNMT1 in multiple ways, including stimulation of the activity and specificity of DNMT1, nonspecific recruitment of DNMTs for DNA methylation and other posttranslational processes,,,54, 55, 56. The interaction of DNMT1 with UHRF1 is required to not only maintain DNA methylation but is also responsible for de novo methylation,. Therefore, the UHRH1/DNMT1 complex plays an essential role in CpG methylation and is an emerging oncogenic target in cancer,58, 59, 60. We showed a CpG site-specific epigenetic effect of UHRH1/DNMT1 on controlling the differential expression of PRSS3 transcripts, supporting its capacity for regulating splicing variants in tumorigenesis,,. Moreover, UHFR1/DNMT1 exhibited an inhibitory effect on MZF1 targeting of the iCpGI. The capacity of MZF1 to regulate the expression of PRSS3-SVs was also abolished by MZF1S, suggesting that the zinc finger protein-binding domain of MZF1 is indispensable for PRSS3 regulation,,,. Therefore, MZF1 is a methyl-sensitive transcription factor (TF), and its binding affinity depends on epigenetic DNA modification at its targeted motifs,,. Rather than investigating the predictable effects of histone modifications on splicing regulation,,, we have shown that PRSS3 iCpGI is a DMR, where differential CpG methylation may specifically interfere with the ability of methyl-sensitive proteins such as MZF1 to anchor on GC-rich consensus sequences,,. Among the UHRF1/DNMT1-modulated iCpGIm patterns associated with differentially expressed PRSS3-SVs, we observed that MZF1 motifs (motif_2 with CpG_485, motif_3 with CpG_545, 551 and motif_4 with CpG_621, 623) in the iCpGI are constitutively hypermethylated, which is imperative for epigenetic silencing of PRSS3-V3, especially motif_3, since only 5-Aza-CdR cooperating with high-dose DATS was effective in specifically demethylating these CpG sites associated with PRSS3-V3 restoration. Although observations through high-throughput sequencing have shown that some TFs, such as the zinc finger proteins CTCF and ZFP354B,, regulate transcriptional activity by specifically changing CpG methylation of consensus sequences at promoters or distal regulatory elements, such as alternative promoters or enhancers, we suggest that UHRF1/DNMT1-associated hypermethylation may provide an inaccessible chromatin template for MZF1 occupancy to regulate PRSS3-SVs in cancer cells, especially for epigenetic silencing of PRSS3-V3, possibly through exon skipping, thereby supporting gene regulation by a methyl-sensitive TF in a methylation-dependent manner,,,. In addition to the increasing nongenetic heterogeneity of MZF1-SVs in transcriptional regulation, considering that MZF1 is a crucial TF that couples with many molecular pathways,, it would be of great value to compare MZF1S and MZF1L to interpret the role of interplay between CpG methylation and TF occupancy in the precise regulation of tissue-specific AS,,. Interestingly, CpG demethylation via UHRF1/DNMT1 dysfunction (“endogenous model”) or 5-Aza-CdR treatment (“responding model”) led to the upregulation of PRSS3-V1/V3High and downregulation of PRSS3-V2Low, which demonstrated that the differential expression of PRSS3 may differ from cell to cell but ultimately depends on the amalgamation of expression changes in its transcripts. Since epigenetic dysregulation of splicing is a nongenetic mechanism frequently linked to therapy escape, we propose functional SVs rather than the overall expression of differentially expressed multiple-transcript genes as biomarkers to more precisely estimate the clinical effectiveness of anticancer drugs such as 5-Aza-CdR (decitabine, DAC) or 5-azacytidine (5-aza-CR, Vidaza),. In addition, demethylation treatment may up- or downregulate both oncogenic and tumor-suppressive transcript variants, causing tumor functional heterogeneity and phenotypic diversity, providing evidence for the importance of epigenetic regulation of mRNA splicing in ITH,,,,. Notably, we observed dose-related bipolar effects of DATS on PRSS3 expression and functionality in lung cancer cells (low-dose: PRSS3-V1/V2; high-dose: PRSS3-V1/V2/V3). High-dose DATS exhibited protumor activity associated with its capacity to upregulate UHRF1/DNMT1 and downregulate MZF1, resulting in the inhibition of PRSS-V3 expression. Garlic-derived compounds, such as DATS and S-allylmercaptocystein (SAMC), have demonstrated protective effects, and anticancer properties,66, 67, 68. However, DATS is capable of both methylation at hypomethylated sites and demethylation at hypermethylated sites in PRSS3 iCpGI, especially in cooperation with 5-Aza-CdR, eliciting synergistic efficiency on demethylation of the MZF1 motifs, hypermethylation of which was hard to be erased by either 5-Aza-CdR or DATS. Thus, DATS plays a distinct dual role in balancing iCpGm. This may fine-tune the nonspecific demethylation effect of 5-Aza-CdR on the iCpGI to form DNA loop domains specifically for anchoring zinc finger proteins. 5-Aza-CdR is a well-established anticancer drug showing therapeutic efficiency with combined epigenetic or immuno-epigenetic therapy69, 70, 71, 72. Therefore, the combination of DATS with 5-Aza-CdR to regulate PRSS3 via the UHRF1/DNMT1–MZF1 axis may represent an efficient and safer therapeutic option for personalized treatment. Further investigation will be required to determine whether/how the combined strategy can be specifically used in targeted therapy. Given the early occurrence and reversible nature of the epigenetic alterations featured in cancer, we explored the translational potential of PRSS3 iCpGIm for the early diagnosis of lung cancer using a cohort of BALF specimens. Although PRSS3 iCpGIm was shown in specimens from LUAD patients but not in patients with inflammation or LUSC, further studies with larger numbers of lung cancer tissues are warranted to validate PRSS3 iCpGIm as a noninvasive biomarker specific for the early prediction or determination of the prognosis of LUAD. Furthermore, our study demonstrates the importance of epigenetically dysregulated AS in functional isoforms that also frequently show genetic variations,,,,. Therefore, further study of the interplay between nongenetic determinants of PRSS3-SVs and their genetic alterations that contribute to tumor functional heterogeneity should provide a novel avenue toward understanding malignant transformation in lung cancer.

In conclusion, by dissecting the nongenomic contributions of PRSS3 transcript variants to functional ITH, we found that divergent expression of PRSS3 transcripts facilitates functional tumor heterogeneity, among which epigenetic regulation of PRSS3-V3 by UHRF1/DNMT1–MZF1 axis-modulated iCpGIm has implications for the early detection of lung cancer and targeted therapy (Fig. 7E).