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. 2026 Feb 19;293(15):4592–4603. doi: 10.1111/febs.70465

Disruption of the ∆40p53/miR‐4671‐5p/SGSH axis results in intra‐S‐phase arrest and poor cancer prognosis

Apala Pal 1, Pritam Kumar Ghosh 1, Sahana Ghosh 2, Sachin Kumar Tripathi 1, Subrata Patra 2, Debjit Khan 1,3, Arindam Maitra 2, Saumitra Das 1,2,✉
PMCID: PMC13440581  PMID: 41714115

Abstract

Parsing the functions of the tumor suppressor tumor protein p53 (TP53) is complex due to the multiple isoforms it encodes. ∆40p53, an N‐terminally truncated p53 isoform and the only translational isoform, modulates full‐length p53 (FLp53) activity and independently regulates targets such as the miR‐186‐5p/transcriptional repressor protein YY1 axis. To identify additional miRNAs regulated by ∆40p53, we performed small RNA sequencing. We found that ectopic overexpression of ∆40p53, but not FLp53, significantly downregulated miR‐4671‐5p. Expression of both isoforms at varying ratios revealed that miR‐4671‐5p may be modulated by FLp53 in a ∆40p53‐dependent manner. In silico analysis identified N‐sulfoglucosamine sulfohydrolase (SGSH) as a potential miR‐4671‐5p target. SGSH expression showed an inverse correlation with miR‐4671‐5p in cancer datasets and had prognostic significance. SGSH mRNA and protein levels were reduced upon miR‐4671‐5p overexpression or si∆40p53 treatment, confirming regulatory linkage. Functionally, miR‐4671‐5p overexpression induced intra‐S‐phase cell cycle arrest, implicating SGSH in cell cycle regulation. These results reveal a previously unknown ∆40p53/miR‐4671‐5p/SGSH axis that, when dysregulated, induces intra‐S‐phase cell cycle arrest and may contribute to cancer outcomes. Our findings highlight the distinct regulatory role of ∆40p53, independent of FLp53, in maintaining cellular and metabolic homeostasis via miRNA‐mediated mechanisms.

Keywords: ∆40p53 role, miR‐4671‐5p expression, p53 isoform, SGSH role in cell cycle regulation

The small RNA sequencing in the background of ∆40p53 overexpression revealed that miR‐4671‐5p was significantly downregulated by ∆40p53. The expression of SGSH (in silico target of miR‐4671‐5p) showed an inverse correlation with miR‐4671‐5p in cancer datasets and cell culture experiments. The overexpression of miR‐4671‐5p resulted in intra‐S‐phase cell cycle arrest. Our findings reveal the ∆40p53/miR‐4671‐5p/SGSH axis and an independent role of ∆40p53 in maintaining cell cycle regulation and homeostasis via microRNA.

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Abbreviations

CDK

cyclin‐dependent kinase

COAD

colon adenocarcinoma

DMEM

Dulbecco's Modified Eagle Medium

FBS

fetal bovine serum

GO

gene Ontology

HS

heparan sulfate

IRES

internal ribosome entry site

LUAD

lung adenocarcinoma

MPS

mucopolysaccharidosis

P53

tumor protein p53 gene

PCR

polymerase chain reaction

RIN

RNA integrity number

RPM

reads per million

RT

reverse transcription

SGSH

N‐sulfoglucosamine sulfohydrolase

TCGA

The Cancer Genome Atlas

UTR

untranslated region

YY1

Yin Yang 1 transcriptional repressor

Introduction

Genome integrity relies on rapid recognition and repair of DNA damage. Central to this response is p53, which halts the cell cycle, limits proliferation of damaged cells, and is frequently inactivated by mutation in cancer [1, 2]. p53 activity is further shaped by 12 naturally occurring isoforms that differ at the N‐ and C‐termini [3, 4]. Their relative abundance varies across normal tissues and tumors, altering transcriptional output and cellular fate [5, 6]. ∆40p53 is the sole translational isoform, produced from an internal ribosome entry site (IRES) within the TP53 5′‐UTR [7]. A second IRES yields full‐length p53 (FLp53); the two proteins share oligomerization domains and form homo‐ and hetero‐tetramers [8]. IRES usage is stress‐ and cell‐cycle phase dependent: translation of FLp53 peaks at the G2/M transition, whereas ∆40p53 is preferentially produced at G1/S [7, 9, 10].

Functionally, ∆40p53 fine‐tunes FLp53 activity [11, 12] yet also acts independently. It retains the second transactivation domain of p53, driving gene expression in p53‐null cells [13, 14, 15]. Reported activities include induction of 14–3‐3σ and G2 arrest [16, 17], activation of pro‐apoptotic BAX and GADD45 [18], modulation of the Nanog‐IGF1 axis during stem‐cell differentiation [19], and control of β‐cell proliferation and glucose homeostasis [20]. At baseline, ∆40p53 and FLp53 suppress migration and proliferation in breast cancer [21]. Conversely, ∆40p53 can promote survival by transactivating netrin‐1 [22]. Growing evidence links ∆40p53 to non‐coding RNA networks. We previously showed that ∆40p53, but not FLp53, upregulates miR‐186‐5p, which represses the oncogenic transcription factor YY1 and limits proliferation [23]. ∆40p53 also controls the lncRNA LINC00176, influencing multiple miRNAs and mRNAs that govern cell fate [24]. These findings suggest that isoform‐specific miRNA programs are key to ∆40p53 function, yet a systematic catalog of such miRNAs is lacking.

We performed small RNA sequencing to globally identify miRNAs differentially regulated by ∆40p53 and FLp53. Using lung (H1299) and colon (HCT116) cancer cell lines engineered to express FLp53, ∆40p53, or both, we discovered miR‐4671‐5p as a ∆40p53‐specific target. Downstream analyses revealed its repression of N‐sulfoglucosamine sulfohydrolase (SGSH), linkage to S‐phase arrest, and prognostic significance in multiple tumors. Here, we delineate the ∆40p53/miR‐4671‐5p/SGSH axis and its impact on cell‐cycle control, providing fresh insight into isoform‐specific p53 signaling.

Results

Small RNA sequencing reveals miRNA targets of p53 and ∆40p53

H1299 cells, which lack endogenous p53 isoforms, were transfected to express FLp53, ∆40p53, both isoforms (14A), or GFP (control) (Fig. 1A–C). Total RNA was extracted, quality‐checked, and subjected to small RNA sequencing. From the dataset, 135 miRNAs with consistent unidirectional fold changes across replicates were selected. A heatmap visualized their expression profiles under each isoform condition (Fig. 1D). A statistically significant cluster of differentially expressed miRNAs (P ≤ 0.05) was identified (Fig. 1E). Among these, four miRNAs stood out for their isoform‐specific regulation. miR‐4671‐5p was significantly downregulated by ∆40p53 and slightly by 14A condition but unaffected by FLp53. In contrast, miR‐301b‐5p was upregulated by ∆40p53 and reduced in FLp53 and 14A expressing cells. miR‐34a‐5p, a known p53 target [25] was significantly upregulated not only in FLp53 but also in 14A and slightly with ∆40p53. Similarly, miR‐548ae‐5p was upregulated across FLp53, ∆40p53, and 14A conditions, indicating potential co‐regulation. These results reveal distinct and overlapping miRNA regulatory profiles for FLp53 and ∆40p53, with miR‐4671‐5p emerging as a prominent ∆40p53‐specific target for further investigation.

Fig. 1.

Fig. 1

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Regulation of miRNA expression by p53 and its isoform ∆40p53. (A) Schematic of constructs used in study (B) Experimental setup prior to RNA sequencing. (C) Western blot analysis of cell extracts from H1299 cells expressing control, p53 only, ∆40p53 only, and 14A construct, probed with CM1 after 48 h. (D) The cluster of differentially expressed miRNAs obtained from the small RNA sequencing data set. (E) The compressed cluster of significantly differentially expressed miRNAs with P‐value ≤ 0.05 (generated using rstudio). The top differentially regulated miRNAs that were selected for further study are highlighted in the box. All experiments were performed in three biological replicates (n = 3).

Selection and validation of miRNAs for further studies

To validate small RNA sequencing results, H1299 cells were transfected with FLp53, ∆40p53, 14A (both isoforms), or control vector (Fig. 2A), and miRNA levels were measured by qRT‐PCR. miR‐4671‐5p was significantly downregulated by ∆40p53 and 14A, but not by FLp53 alone (Fig. 2B). In contrast, miR‐548ae‐5p was consistently upregulated across all isoform conditions (Fig. 2D). miR‐34a‐5p was induced by both p53 and ∆40p53, whereas miR‐301b‐5p was specifically upregulated by ∆40p53 alone (Fig. 2C,E). Expression patterns for miR‐4671‐5p, miR‐548ae‐5p, and miR‐34a‐5p were largely consistent with the sequencing data (Fig. 2F). While miR‐301b‐5p showed a possible ∆40p53‐specific effect in the initial validation (Fig. 2E), the change was not statistically significant in subsequent experiments due to which we did not pursue it further in the current study.

Fig. 2.

Fig. 2

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Selection and validation of miRNAs for further studies.(A) Western blot analysis of cell extracts from H1299 cells expressing control, p53 only, ∆40p53 only and 14A construct, probed with CM1 after 48 h. (B–E) Quantitative PCR for validation of miR‐4671‐5p, miR‐34a‐5p, miR‐548ae‐5p, miR‐301b‐5p, respectively, in H1299 cells expressing control, p53 only, ∆40p53 only and 14A construct. (F) Table for comparative analysis of fold changes obtained in sequencing versus validation result. (G) Western blot analysis of cell extracts from HCT116+/+ and HCT116−/− cells probed with CM1. (H) Quantitative PCR for validations of miR‐4671‐5p, miR‐34a‐5p and miR‐548ae‐5p in HCT116+/+ and HCT116−/− cells. (I) Quantitative PCR of miR‐4671‐5p, miR‐34a‐5p and miR‐548ae‐5p in HCT116+/+ cells transfected with si p53 (30 nm) and non‐specific si (si Nsp). (J) Western blot analysis of cell extracts from HCT116+/+ cells transfected with either si p53 (30 nm) and non‐specific si (si Nsp), probed with CM1. (K) Quantitative PCR of miR‐4671‐5p, miR‐34a‐5p and miR‐548ae‐5p in HCT116−/− cells transfected with si ∆40p53 (30 nm) and non‐specific si (si Nsp). (L) Western blot analysis of cell extracts from HCT116−/− cells transfected with si ∆40p53 (30 nm) and non‐specific si (si Nsp), probed with CM1. Error bars indicate SD (Standard deviation). All experiments were performed in three biological replicates (n = 3). The criterion for statistical significance with the two‐tailed Student's t‐test was P ≤ 0.05 (*) or P ≤ 0.01 (**).

To assess physiological relevance, we examined these miRNAs in colon cancer cell lines HCT116+/+ (predominantly FLp53) and HCT116−/− (predominantly ∆40p53) (Fig. 2G). At baseline, HCT116−/− cells showed lower miR‐4671‐5p and higher miR‐548ae‐5p and miR‐34a‐5p levels than HCT116+/+ cells (Fig. 2H). siRNA‐mediated knockdown of p53 in HCT116+/+ cells reduced miR‐548ae‐5p and miR‐34a‐5p but did not significantly affect miR‐4671‐5p (Fig. 2I,J). Conversely, ∆40p53 knockdown in HCT116−/− cells increased miR‐4671‐5p and decreased miR‐548ae‐5p and miR‐34a‐5p (Fig. 2K,L). These results suggest that ∆40p53 specifically suppresses miR‐4671‐5p and enhances miR‐548ae‐5p and miR‐34a‐5p expression, while FLp53 does not regulate miR‐4671‐5p.

Given that p53 isoform expression varies widely across cancer types [5], we next examined whether the expression patterns of these miRNAs, particularly miR‐4671‐5p, also show variability in clinical samples. To explore this, we analyzed publicly available cancer transcriptome datasets.

Regulation of miRNAs by ∆40p53 and p53

Bioinformatic analysis using dbDEMC 2.0 revealed that miR‐34a‐5p is widely expressed in many cancers, while miR‐4671‐5p expression was detected in colon, lung, and pancreatic cancers, with levels elevated in pancreatic cancers but reduced in colon and lung cancers (Fig. 3A). These observations suggest that the differential expression of these miRNAs may reflect the tissue‐specific abundance of p53 and ∆40p53. To test this, we overexpressed p53 and ∆40p53 in varying ratios in H1299 cells and analyzed miRNA expression (Fig. 3B). Expression of miR‐34a‐5p was induced by either isoform alone; however, certain combinations of both isoforms reduced its expression, suggesting dose‐dependent co‐regulation (Fig. 3C), consistent with previous reports of p53/∆40p53 interactions [8].

Fig. 3.

Fig. 3

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Regulation of miRNAs by ∆40p53 and p53. (A) Differential expression profile of miRNAs in cancer vs. normal obtained from dbDEMC 3.0 database. (B) Western blot analysis of cell extracts from H1299 transfected cells with different ratios of p53 and ∆40p53 probed with CM1. (C, D) Quantitative PCR of miR‐34a‐5p and miR‐4671‐5p respectively in H1299 transfected with different ratios of p53 and ∆40p53. (E) Table for miR‐4671‐5p targets selected in the study. (F–I) Kaplan–Meier estimates of survival for pancreatic adenocarcinoma (F, G) and colon tumor (H, I) classified by SGSH mRNA expression levels. The number of patients at risk is indicated for time increments of 12 or 24 months. P values were calculated using a log rank test. (J–L) Quantitative PCR of mRNA targets (SGSH, CDK11B, and CDK5R1) in H1299 transfected cells with different ratios of p53 and ∆40p53. (M) Western blot analysis of cell extracts from HCT116+/+ and HCT116−/− cells probed with SGSH, CDK11B, and CDK5R1 antibodies. Error bars indicate SD (Standard deviation). All experiments were performed in three biological replicates (n = 3). The criterion for statistical significance with the two‐tailed Student's t‐test was P ≤ 0.05 (*) or P ≤ 0.01 (**) or P ≤ 0.001(***).

Notably, FLp53 overexpression alone did not significantly affect miR‐4671‐5p levels, whereas increasing Δ40p53 expression either alone or in combination with FLp53 consistently suppressed it (Fig. 3D). A similar pattern was observed with the 14A construct (Fig. 2B, fourth bar), where the presence of FLp53 partially attenuated Δ40p53‐mediated repression. These observations suggest that FLp53 can modulate Δ40p53‐dependent regulation of miR‐4671‐5p but is not itself sufficient to alter its expression.

These data reinforce that ∆40p53 is the primary regulator of miR‐4671‐5p and that isoform balance is critical for miRNA output.

Cellular role of miR‐4671‐5p

Because miR‐4671‐5p was uniquely repressed by ∆40p53, we explored its downstream functions. TargetScan 7.2 and miRDB yielded 786 non‐redundant putative targets, with GO enrichment for ‘protein‐serine‐kinase activity’ indicating that many predicted targets of miR‐4671‐5p may be involved in cell cycle regulation. From this list we prioritized two cell‐cycle kinases, CDK11B and CDK5R1 for experimental follow‐up (Fig. 3E and Tables S1–S3). Additionally, we prioritized SGSH (N‐sulfoglucosamine sulfohydrolase), the top‐scoring miR‐4671‐5p target in TargetScan, despite its uncharacterized role in cancer.

SGSH is a lysosomal enzyme whose deficiency causes mucopolysaccharidosis IIIA (MPS IIIA), leading to GAG and heparan sulfate accumulation and resulting in severe neurological and skeletal pathology [26]. Although SGSH has recently been linked to monkeypox and interstitial lung disease [27, 28], its role in tumor biology remains unknown. Analysis of patient datasets revealed that low SGSH expression correlates with poor survival in pancreatic cancer, while high SGSH is associated with poor outcomes in colon tumors (Fig. 3F–I and Table S1). These trends are opposite to miR‐4671‐5p levels observed in the same cancers (Fig. 3A), suggesting a biologically relevant interaction. While we examined SGSH expression using publicly available cancer datasets, these data are not stratified by TP53 mutation status and do not distinguish FLp53 from Δ40p53, as the latter arises by alternative translation from the same transcript. To further explore SGSH expression in the context of TP53 mutation status, we analyzed TCGA data via UALCAN. In lung adenocarcinoma (LUAD), SGSH expression was significantly reduced in TP53‐mutant tumors compared with TP53–wild‐type tumors (Fig. S1A). In contrast, in colon adenocarcinoma (COAD), SGSH expression was significantly higher in TP53‐mutant compared with TP53–wild‐type cancers (Fig. S1B). These data suggest that TP53 mutation status influences SGSH expression differently across tumor types, consistent with the context‐dependent role of p53 and its isoforms in transcriptional regulation.

We next validated the regulation of these targets under varying p53/∆40p53 expression in H1299 cells. SGSH, CDK11B, and CDK5R1 mRNA levels were upregulated only under ∆40p53 overexpression (Fig. 3J–L). Similarly, in HCT116−/− cells, these proteins were more abundant than in HCT116+/+ cells (Fig. 3M), consistent with lower miR‐4671‐5p expression (Fig. 2K). Partial knockdown of ∆40p53 reduced expression of all three targets (Fig. 4A,B), while overexpression of miR‐4671‐5p in HCT116−/− cells led to reduced SGSH, CDK11B, and CDK5R1 mRNA levels, most prominently for SGSH (Fig. 4C,D). Corresponding decreases in SGSH protein were observed under both conditions (Fig. 4E,F). To better understand physiological conditions, we next examined the effects of Δ40p53 in wild‐type p53 backgrounds by overexpressing Δ40p53 in A549, HeLa, and HCT116+/+ cells at levels comparable to those achieved in HCT116−/− cells (Fig. S2A,D,G). Under these conditions, Δ40p53 reduced miR‐4671‐5p levels in A549 and HCT116+/+ cells, while HeLa cells showed no significant change (Fig. S2B,E,H), thereby suggesting cell‐type specific modulation. Despite this reduction in miR‐4671‐5p, SGSH mRNA levels did not uniformly increase (Fig. S2C,F,I), likely reflecting regulatory buffering caused by the co‐existence of endogenous p53 and Δ40p53 in these wild‐type settings. This interpretation is consistent with observations in H1299 cells (Fig. 3J), where introducing full‐length p53 diminished the regulatory impact of Δ40p53.

Fig. 4.

Fig. 4

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Cellular role of miR‐4671‐5p. (A) Quantitative PCR of SGSH, CDK11B and CDK5R1 in HCT116−/− cells transfected with si ∆40p53 (30 nm) and non‐specific si (si Nsp). (B) Western blot analysis of cell extracts from HCT116−/− cells transfected with si∆40p53 (30 nm) and non‐specific si (si Nsp), probed with CM1. (C) Quantitative PCR of miR‐4671‐5p in HCT116−/− cells transfected with miR‐4671‐5p overexpression construct. (D) Quantitative PCR of SGSH, CDK11B and CDK5R1 in HCT116−/− cells transfected with miR‐4671‐5p overexpression construct. (E) Western blot analysis of cell extracts from HCT116−/− cells transfected with si∆40p53 (30 nm) and non‐specific si (si Nsp), probed with CM1 and SGSH. (F) Western blot analysis of cell extracts from HCT116−/− cells transfected with miR‐4671‐5p overexpression construct, probed with SGSH. (G) Analysis of different cell cycle phases of fixed cell extracts from HCT116−/− cells transfected with miR‐4671‐5p overexpression construct. Error bars indicate SD (Standard deviation). Error bars indicate SD (Standard deviation). All experiments were performed in three biological replicates (n = 3). The criterion for statistical significance with the two‐tailed Student's t‐test was P ≤ 0.05 (*) or P ≤ 0.01 (**). (H) Left (Normal condition): Under physiological conditions, high levels of the p53 translational isoform ∆40p53 suppress the expression of miR‐4671‐5p. Reduced levels of miR‐4671‐5p relieve its inhibitory effect on SGSH, leading to elevated SGSH expression. High SGSH levels support normal cell cycle progression through G1, S, G2, and M phases. Right (Pathological condition): In conditions where ∆40p53 expression is low, miR‐4671‐5p is upregulated. Increased miR‐4671‐5p inhibits SGSH expression, resulting in reduced SGSH levels. This suppression contributes to intra‐S‐phase cell cycle arrest, which is associated with impaired proliferation control and poor cancer prognosis.

Finally, miR‐4671‐5p overexpression caused significant S‐phase accumulation and reduced G2‐phase cells, indicating intra‐S phase arrest (Fig. 4G). Together, these findings establish that ∆40p53 suppresses miR‐4671‐5p to maintain SGSH and other cell cycle regulators, enabling proper S‐phase progression.

Discussion

MicroRNAs (miRNAs) play critical roles in regulating development, cell cycle progression, and survival. Their dysregulation is a common feature in cancer [29]. While many miRNAs are known to be transcriptionally regulated by full‐length p53 (FLp53) [30] the contribution of p53 isoforms, especially ∆40p53, to miRNA regulation has only recently been explored. We previously demonstrated that ∆40p53 selectively upregulates miR‐186‐5p, which targets and represses the oncogene YY1, leading to reduced cell proliferation [23]. Despite this, the full functional scope of ∆40p53 remains understudied, even though it has been implicated in key cellular processes such as apoptosis, senescence, migration, and the cell cycle [18]. A key open question is: which non‐coding RNAs are specifically regulated by ∆40p53, and how might these contribute to its distinct roles? This is particularly relevant in cancers, where differential isoform expression [5] may reshape downstream gene regulatory networks.

Here, we identified several miRNAs regulated by ∆40p53, either uniquely or in parallel with p53. Among these, miR‐4671‐5p was exclusively repressed by ∆40p53, prompting further investigation. Overexpression of ∆40p53 significantly reduced miR‐4671‐5p levels, whereas p53 alone had no effect. Interestingly, the dual‐isoform construct (14A) also reduced miR‐4671‐5p expression (Fig. 2B), suggesting that p53 may modulate ∆40p53‐mediated repression. Similarly, varying p53/∆40p53 ratios consistently decreased miR‐4671‐5p expression in the presence of both isoforms (Fig. 3D). These findings indicate that relative isoform abundance modulates miR‐4671‐5p levels, which could contribute to context‐dependent regulation of downstream targets in different cancers.

To explore the downstream role of miR‐4671‐5p, we initially selected SGSH, CDK11B, and CDK5R1 as candidate targets based on bioinformatic predictions and GO enrichment analysis (Table S2). Among these, SGSH was prioritized for further investigation due to its strong prediction score, metabolic function, and uncharacterized role in cancer. SGSH expression also showed prognostic significance: low SGSH associated with poor survival in pancreatic cancer, whereas high SGSH correlated with worse outcome in colon cancer, glioblastoma (Fig. 3F–I; Table S3) and other datasets. Notably, SGSH and miR‐4671‐5p levels were inversely related across these tumors (Fig. 3A), supporting functional linkage. The bidirectional prognostic pattern suggests SGSH is neither a classic oncogene nor tumor suppressor but may operate within tumor‐specific rewiring of the Δ40p53/miR‐4671‐5p/SGSH axis; an area that merits deeper investigation.

Overexpression of ∆40p53 increased the mRNA levels of all three targets SGSH, CDK11B, and CDK5R1 (Fig. 3J–L) with SGSH showing the most pronounced upregulation. Protein levels of all three were also higher in cells with endogenous ∆40p53 (Fig. 3M). Although co‐expression of FLp53 and ∆40p53 reduced miR‐4671‐5p levels (Fig. 3D), this was not mirrored at the target mRNA level (Fig. 3J–L), This suggests that miR‐4671‐5p repression is necessary but may not be sufficient for maximal upregulation of these targets, and that additional Δ40p53‐dependent mechanisms may contribute to the effects observed under Δ40p53 only conditions. It is also possible that the presence of full‐length p53 in the ratio combinations counterbalances Δ40p53‐driven activity, thereby influencing target gene levels. Additionally, other miRNAs co‐regulated by the isoform combination could also contribute to modulation of target gene expression.

To validate the ∆40p53/miR‐4671‐5p/mRNA axis, we overexpressed miR‐4671‐5p or silenced ∆40p53, both of which led to reduced expression of all three targets, with SGSH showing the most substantial decrease (Fig. 4A,D). This trend was confirmed at the protein level, where SGSH levels dropped consistently under both conditions (Fig. 4E,F), highlighting SGSH as the primary and most responsive target within the ∆40p53‐miR‐4671‐5p regulatory network.

To assess the physiological relevance of SGSH/miR‐4671‐5p regulation, we considered SGSH's established role in lysosomal degradation of heparan sulfate (HS), a glycosaminoglycan [31, 32]. In MPS Type IIIA, SGSH mutations impair this process, leading to intracellular accumulation of heparan sulfate. Notably, flow cytometry analyses in MPS models have revealed disrupted cell cycle profiles, including elevated S‐phase and reduced G2‐phase populations [33], suggesting a potential link between SGSH activity and cell cycle control. Since CDK11B and CDK5R1, which are also miR‐4671‐5p targets, are known cell cycle regulators, we evaluated whether miR‐4671‐5p overexpression influenced cell cycle progression. We observed a significant increase in S‐phase cells and a reduction in G2‐phase cells (Fig. 4G), indicative of intra‐S‐phase arrest. While this is consistent with the known roles of CDK11B and CDK5R1 in S/G2 transition, SGSH may also contribute to this effect through HS accumulation. Heparan sulfate accumulation is known to inhibit topoisomerase I, which disrupts DNA replication and induces intra‐S‐phase arrest [34, 35].

Thus, miR‐4671‐5p may induce intra‐S arrest through dual mechanisms: direct repression of cell cycle kinases and indirect effects mediated by SGSH inhibition and subsequent glycosaminoglycan accumulation. However, the precise contribution of SGSH to this arrest phenotype and its interaction with canonical cell cycle regulators warrants further investigation to clarify its mechanistic role in this regulatory axis.

In addition, it is important to note that public cancer datasets used in this study do not distinguish full‐length p53 from its translational isoform Δ40p53, as both are derived from the same TP53 transcript. Consequently, correlations between SGSH expression and cancer type reflect general p53‐associated trends rather than direct evidence of Δ40p53 regulation in tumors. Our mechanistic conclusions are therefore based on defined cell systems with controlled isoform expression. Isoform‐resolved and mutant TP53 models will be required to determine whether the Δ40p53/miR‐4671‐5p/SGSH axis operates similarly in diverse cancer contexts.

In conclusion, this study identifies a previously uncharacterized Δ40p53/miR‐4671‐5p/SGSH regulatory axis that contributes to cell‐cycle control. Under physiological conditions, Δ40p53 suppresses miR‐4671‐5p expression, maintaining SGSH and other S‐phase regulators to support normal proliferation. When Δ40p53 levels are reduced, miR‐4671‐5p is derepressed, leading to SGSH down‐regulation and intra‐S‐phase arrest (Fig. 4H). These findings highlight the importance of isoform‐specific p53 signaling in maintaining cellular homeostasis and suggest that altered Δ40p53 expression could have broad implications in cancer biology.

Materials and methods

Cell lines and transfections

Five human cell lines were used: H1299 (lung adenocarcinoma, p53‐null), HCT116 p53+/+ (referred to as HCT116+/+; RRID:CVCL_0291), HCT116 p53−/− (referred to as HCT116−/−; RRID:CVCL_HD97) HCT116+/+ cells predominantly express full‐length p53α, along with lower‐abundance β and γ splice variants and N‐terminally truncated isoforms such as Δ40p53, Δ133p53, and Δ160p53 (all at low levels). HCT116−/− cells, although commonly referred to as p53‐null, lack full‐length p53 but primarily express Δ40p53α, with minor levels of other N‐terminally truncated isoforms (Δ133p53 and Δ160p53). The principal distinction between the two lines lies in the presence of full‐length p53 in HCT116+/+ and its absence in HCT116−/−, where Δ40p53 is the predominant isoform. A549 (lung adenocarcinoma; wild‐type p53; RRID:CVCL_0023) and HeLa (cervical carcinoma; wild‐type p53; RRID:CVCL_0030). All cell lines were procured from the National Centre for Cell Science (NCCS), Pune, India. All experiments were done in cells where mycoplasma were not detected.

Cells were cultured in Dulbecco's Modified Eagle Medium (DMEM, Sigma, Schnelldorf, Germany) supplemented with 10% fetal bovine serum (FBS, GIBCO, Invitrogen) and 1% penicillin/streptomycin. Transfections were performed using Lipofectamine 2000 and Turbofect (Invitrogen, Carlsbad, CA, USA) in Opti‐MEM (GIBCO) according to the manufacturer's instructions. After 4 h, transfection medium was replaced with complete DMEM, and cells were harvested at indicated time points.

Plasmid constructs included pGFP‐hp‐p53‐5′UTR vectors expressing FLp53, ∆40p53, or both (14A). These were generously provided by Dr. Robin Fahraeus (INSERM U716, Paris, France). To achieve Δ40p53 overexpression in A549, HeLa, and HCT116+/+ cells, the Δ40p53 coding sequence was cloned into the pcDNA expression vector. To overexpress miR‐4671‐5p, the mature sequence was cloned into the pSUPER vector. For knockdown studies, a 30 nm siRNA targeting the 3′UTR of TP53 (Integrated DNA Technologies, IDT, Coralville, IA, USA) was used. This siRNA downregulates both the full‐length p53 (FLp53) and the translational isoform Δ40p53, as it targets a region common to both transcripts. Accordingly, in HCT116+/+ cells, this siRNA reduces FLp53 expression, whereas in HCT116−/− cells, it predominantly decreases Δ40p53 levels. Throughout the text, ‘si‐p53’ and ‘si‐Δ40p53’ refer to the same siRNA; a non‐targeting control siRNA (Dharmacon, Lafayette, CO, USA) was used in parallel.

Small RNA sequencing

RNA extraction

Total RNA was isolated from H1299 cells transfected with vector, FL p53, ∆40p53, or 14A using TRIzol followed by the PureLink kit (Ambion). RNA quality (Bioanalyzer 2100, Agilent) and quantity (NanoDrop, Qubit) were assessed; only samples with RIN > 7 were used for library preparation.

Library preparation and sequencing

One μg of high‐quality RNA was processed with the Illumina TruSeq Small RNA kit. 3′/5′ adapters were ligated, cDNA was synthesized, PCR‐amplified, and fragments of 145–160 bp were gel‐purified. Libraries were pooled and sequenced (1 × 50 bp) on an Illumina HiSeq‐2500.

RNA‐seq data analysis

FASTQ files were trimmed with Cutadapt v1.8.1 and mapped to hg19 using miRDeep2. Known and novel miRNAs were quantified as reads‐per‐million (RPM); multi‐precursor miRNAs were averaged. Differential expression was determined with DESeq2.

Western blot analysis

Cells were lysed in RIPA buffer, and protein concentrations were determined via the Bradford assay. Equal amounts of lysate were resolved by SDS‐PAGE and transferred to nitrocellulose membranes. Primary antibodies used were: anti‐p53 (CM1; kindly provided by Dr. Robin Fahraeus (INSERM, France) and Prof. J.C. Bourdon (University of Dundee, UK)), anti‐SGSH (A8148; Abclonal, Woburn, MA, USA), anti‐CDK11B (A12830; Ablconal), and anti‐CDK5R1 (A14497; Ablconal). Blots were developed using HRP‐conjugated secondary antibodies (Sigma) and detected with enhanced chemiluminescence (ECL).

RNA isolation and real‐time PCR

Total RNA was extracted using TRI Reagent™ (Sigma) and treated with DNase I (Promega Biotech India Pvt. Ltd., New Delhi, India) to remove DNA contamination. RNA was purified by acidic phenol‐chloroform extraction and ethanol precipitation, then quantified using a Nano‐spectrophotometer. cDNA was synthesized from 2 to 5 μg total RNA for mRNAs or 50 ng for miRNAs using gene‐specific primers and Revertaid™ MMLV RT (Thermo Scientific, Vilnius, Lithuania) at 42 °C for 1 h.

Cell cycle analysis

HCT116−/− cells were transfected with miR‐4671‐5p or miR‐34a‐5p overexpression constructs. After 48 h, cells were fixed in methanol, treated with RNase A (10 μg/mL), stained with propidium iodide (1 μg/mL), and analyzed on a BD FACSCalibur flow cytometer.

Bioinformatics and statistics

dbDEMC2.0 has been used to perform a meta‐profiling of selected miRNAs [36]. TargetScan 7.2 has been used to predict target mRNAs of miRNAs [37]. miRDB has been used to predict target miRNAs [38, 39]. GO‐term analysis was done on PANTHER release 17.0. Kaplan–Meier survival analysis was done on R2: Genomics Analysis and Visualization Platform. Heat map for Fig. 1E has been generated using rstudio platform. The mRNA expression analysis of p53 mutant vs non‐mutant was done in UALCAN (https://ualcan.path.uab.edu/). All experiments were performed in three biological replicates. Error bars indicate SD (Standard deviation). Data were analyzed using two‐tailed Student's t‐test; P ≤ 0.05 (*) or P ≤ 0.01 (**) or P ≤ 0.001(***).

Author contributions

AP and SD: conception and design of studies analysis, interpretation, and article writing. AP, SKT, and PKG: performing experiments, interpretation of results, and article editing. DK: bioinformatic analysis, interpretation of results, article writing, and editing. SG, SP, and AM: RNA sequencing and analysis. SD: funding acquisition, supervision, and project management.

Conflict of interest

The authors declare no conflict of interest.

Supporting information

Table S1. miR‐4671‐5p target genes.

Table S2. Result of PANTHER Statistical Overrepresentation Test of “GO molecular function.”

Table S3. Survival analysis of patients as classified by SGSH mRNA expression levels in different cancers.

Fig. S1. Expression of SGSH in different cancer datasets based on TP53 mutation status.

Fig. S2. Δ40p53–miR‐4671‐5p–SGSH relationship in wild‐type p53 cell lines (A549, HeLa and HCT116+/+).

FEBS-293-4592-s001.pdf (511.9KB, pdf)

Acknowledgements

We thank Prof. J.C. Bourdon (University of Dundee) and Dr. Robin Fahraeus (INSERM) for the anti‐p53 antibody. We acknowledge NIBMG (Kalyani, India) for RNA sequencing facilities and the SD lab members, particularly Milky Mittal, for helpful discussions. This work was supported by a DBT research grant to SD, who also received the J.C. Bose grant. Additional financial support was obtained from the DBT‐IISc partnership, DST‐FIST Level II, and the UGC Centre of Advanced Studies.

Apala Pal and Pritam Kumar Ghosh contributed as joint first authors.

Data availability statement

The sequencing data files obtained are available in the online biorepository forum with the SRP BioProject ID PRJEB47067 (https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJEB47067).

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Table S1. miR‐4671‐5p target genes.

Table S2. Result of PANTHER Statistical Overrepresentation Test of “GO molecular function.”

Table S3. Survival analysis of patients as classified by SGSH mRNA expression levels in different cancers.

Fig. S1. Expression of SGSH in different cancer datasets based on TP53 mutation status.

Fig. S2. Δ40p53–miR‐4671‐5p–SGSH relationship in wild‐type p53 cell lines (A549, HeLa and HCT116+/+).

FEBS-293-4592-s001.pdf (511.9KB, pdf)

Data Availability Statement

The sequencing data files obtained are available in the online biorepository forum with the SRP BioProject ID PRJEB47067 (https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJEB47067).

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