TERT Promoter Mutations Combined with TP53 Mutations as Potential Biomarkers for Hepatocellular Carcinoma Recurrence and Prognosis

doi:10.21203/rs.3.rs-4767398/v1

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TERT Promoter Mutations Combined with TP53 Mutations as Potential Biomarkers for Hepatocellular Carcinoma Recurrence and Prognosis

https://doi.org/10.21203/rs.3.rs-4767398/v1

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Hepatocellular carcinoma (HCC) is the most prevalent form of liver cancer, and ranks among the most lethal malignancies globally, primarily due to its high rates of recurrence and metastasis. Despite the urgency, no reliable biomarkers currently exist for predicting tumor recurrence in HCC. Telomerase reverse transcriptase (TERT) promoter mutations (TERTpm) and cellular tumor antigen p53 mutations (TP53m) have been frequently documented in HCC, but their combined clinical significance remains undefined. In this study, we investigated the clinical implications of TERTpm, TP53m, and their co-occurrence in 50 HCC tissue samples using the next-generation sequencing (NGS) technology. We identified TERTpm (C228T) and TP53m in 16 (32%) and 24 (48%) samples, respectively. Our findings indicate that these mutations are more prevalent in male patients (100% for TERTpm, 83.33% for TP53m), in those with solitary tumors (87.5% for both), in individuals with G2-G3 hepatitis (100% / 83.3%), and in cases of moderately differentiated tumors (75.0% / 83.3%). Furthermore, patients with both TERTpm and TP53m exhibited a significantly higher risk of tumor relapse (P < 0.05) and shorter progression-free survival (P < 0.05). Collectively, our results suggest that presence of both TERTpm and TP53m may serve as a robust predictor of tumor recurrence and a marker of poor prognosis in HCC.

HCC

TERT promoter mutation

TP53 mutation

recurrence

prognosis

Liver cancer, as reported by GLOBOCAN, stands as one of the most prevalent and lethal malignancies globally, ranking fourth in mortality and sixth in incidence¹. This grim reality is exacerbated in China, where hepatocellular carcinoma (HCC) notably occupies the third and fourth positions in terms of mortality and incidence rates, respectively^1,2. HCC, the primary form of liver cancer, continues to challenge healthcare systems despite advancements in therapeutic strategies. Hepatic resection remains the gold standard for treatment, yet its applicability is limited to approximately 20% of patients, with a staggering 85% experiencing intrahepatic recurrence or metastasis within five years post-surgery^3–5. The recurrence rate is a significant contributor to the poor prognosis and high mortality rates among HCC patients, and current methods to predict and manage this remain suboptimal^6–8. Regular imaging and serum alpha fetoprotein (AFP) tests are standard, but they fall short in detecting early-stage recurrence, underscoring the urgent need for novel predictive biomarkers.

It’s well known that tumorigenesis is the result of an accumulation of multiple genetic alterations. However, the precise molecular mechanisms underlying the initiation and progression of HCC remain unclear. Recent years, remarkable improvements have been made in genomic studies of HCC, and a variety of mutated genes have been identified. Among all, the tumor antigen p53 mutations (TP53m) and telomerase reverse transcriptase promoter mutations (TERTpm) are detected the most frequent genomic alterations, affecting 18.7%~48% and 14.9%~60% of all HCC patients, respectively^7,9–16.

The TP53 gene is located in 17p13 and encode the cellular tumor antigen p53, a critical tumor suppressor protein containing transcriptional activation, DNA binding, and oligomerization domains¹⁷. p53 can prevent tumorigenesis by inducing cell-cycle arrest, apoptosis, cellular senescence, DNA repairing, and metabolism changes, etc¹⁸. Mutations in TP53 are linked to over 50% of human cancers, including lung, liver, and breast cancers^19–21. Conversely, the TERT gene is located in 5p15 and encode the telomerase reverse transcriptase, a rate-limiting and catalytic component of telomerase, which is an essential enzyme to extends telomeres, and plays an important role in the process of tumorigenesis, including cell growth, proliferation, invasion, metastasis, and angiogenesis^8,22. TERT is typically suppressed in most normal somatic cells but is frequently activated in the majority of cancers, facilitating the immortal and indefinite growth of cancer cells^22–24. TERTpm reported in many types of cancers are likely to introduce new binding sites for transcription factors such as ETS/TCF, which are associated with increased activity and expression of TERT^25–28.

Specific mutations in TERT, such as C228T (-124 bp) and C250T (-146 bp), are recognized as early genetic events in hepatocarcinogenesis, while TP53 mutations are associated with later stages of HCC progression^10,29–32. Based on literature, these mutations not only play a pivotal role in HCC carcinogenesis and metastasis but also hold potential as prognostic indicators for HCC.

Despite the progress, the critical genes influencing HCC recurrence and progression are yet to be fully deciphered. Unraveling these genes could deepen our understanding of the molecular underpinnings of early recurrence in HCC and its associated poor outcomes, potentially leading to the discovery of new therapeutic targets.

This study aims to explore the clinical relevance of TERT promoter mutations, TP53 mutations, and their co-occurrence in HCC. Utilizing the next-generation sequencing technology, we conducted a mutational analysis to assess the prevalence and frequency of these genetic alterations. Additionally, we characterized the clinical and laboratory features of the patients and discussed their prognostic implications.

2.1 Ethics Statement

The study was approved by Biomedical Ethics Committee of West China Hospital of Sichuan University [Reference No. 2019 (203)], and all patients involved in this study had provided their written informed consent. Besides, we confirm that all methods were performed in accordance with the relevant guidelines and regulations.

2.2 Patients, tissue samples, and clinicopathologic data

From June 2019 to October 2020, a total of 50 HCC patients whom were reported and diagnosed as HCC for the first time at the West China Hospital of Sichuan University were randomly selected. Fresh tumor tissues (≥ 60 mg) were obtained by surgical resection, and paired clinicopathologic information were collected. The laboratory and clinical parameters of these patients were described in Supporting Table S1. Histopathological diagnoses were determined by at least two experienced pathologists. Informed consent was obtained from all subjects under protocols approved by Ethical Committee of the hospital. All patients provided written contents according to ethical regulations.

All patients after resection were followed up regularly from 2019 to January 28, 2024. The mean follow-up time was 49.2 ± 4.8 month (median, 51.0 months; range, 39.0–55.0 months). Laboratory, clinical, pathological, and radiographic parameters were evaluated to diagnose postoperative recurrence (including tumor marker levels, clinical symptoms, MRI, CT, PET-CT, MRI, and histopathological results). The internal between surgery and local recurrence, or distal metastasis, or death, was defined as progression-free survival (PFS).

2.3 DNA extraction

Genomic DNA was extracted from the fresh HCC tumor tissues of individual patients with the QIAamp DNA Mini Kit (Qiagen, Hilden, Germany) according to the standard procedures. In brief, tissue samples (less than 10 mg) were digested overnight at 56°C with protein K and Buffer ALT. After extraction with Buffer AL and reprecipitation in ethanol (97%), nucleic acids were then rinsed with Buffer AW1 and Buffer AW2. After that, DNA was solubilized in Buffer AE and stored at -20°C. The concentration and purity of extracted DNA were determined using Qubit 3.0 Fluorometer (Life Invitrogen, Villebon, France). After that, DNA degradation and contamination were detected with agarose gel electrophoresis.

2.4 Next-generation sequencing (NGS)

As previously described, genomic DNA derived from tissues after fragmentation and purification was used to construct DNA library³³. The human 1021 gene mutation detection kit (Gene+, Beijing, China) was used to capture the most common mutations in HCC, which including exons, introns, promoters, and fusion breakpoint regions of 1021 genes. Followed by hybridization and amplification, the Gene + Seq-2000 sequencer was applied to DNA sequencing.

After removing terminal adaptor sequences and low-quality data, remaining reads were mapped to the reference human genome (hg19) through the Burrows-Wheel Aligner (BWA) software. Then, duplicate reads were removed with Gene Analysis Toolkit. MuTect2 algorithm was utilized to call single-nucleotide variants (SNVs) and somatic insertions/deletions (InDel). GnomAD database was applied to filter germline mutations. Afterwards, mutated variant allele frequency (VAF) ≥ 0.01 was filtered.

2.5 Statistical analysis

Statistical analyses were performed by IBM SPSS Statistics 23.0 software and GraphPad Prism 9.1.1 software. Data were reported as frequencies (percentages), mean ± SD, or median (range).

Clinicopathological parameters of patients were compared using the Student’s t-test, Pearson’s chi-square (χ²) test, or Fisher’s exact test where appropriate. Recurrence odds ratios (ORs) and 95% confidence intervals (CIs) of patients were obtained via univariable and multivariable logistic regression. A two-tailed p value of < 0.05 was considered statistically significant.

3.1 Patients’ clinicopathological characteristics

Detailed characteristics of the enrolled 50 HCC patients are listed in (Supplement Table 1). The study cohort consisted of 41 women (82.0%) and 9 men (18.0%), with an average age at diagnosis of 55 (range, 24-87) years. All patients had chronic liver disease related to HBV infection, 27 patients had liver cirrhosis. Most of them (94.0%) had a single tumor, with a mean diameter of 5.80 ± 3.7 centimeters. Furthermore, 36 (72.0%) cases had moderately differentiated tumors, and 14 cases had poorly differentiated tumors. Besides, 17 (34.0%) cases were identified microvascular invasion (MVI) status from pathology reports.

Table 1

Mutation details of patients with *TERTpm*
Patient	Age	Gender	Start_Position	End_Position	DNA change of TERT	Variant classification	Variant type
1	M	62	1295228	1295228	G228A	5'Flank	SNP
3	M	87	1295228	1295228	G228A	5'Flank	SNP
4	M	63	1295228	1295228	G228A	5'Flank	SNP
8	M	56	1295228	1295228	G228A	5'Flank	SNP
12	M	66	1295228	1295228	G228A	5'Flank	SNP
15	M	47	1295228	1295228	G228A	5'Flank	SNP
17	M	53	1295228	1295228	G228A	5'Flank	SNP
20	M	67	1295228	1295228	G228A	5'Flank	SNP
21	M	53	1295228	1295228	G228A	5'Flank	SNP
26	M	51	1295228	1295228	G228A	5'Flank	SNP
32	M	51	1295228	1295228	G228A	5'Flank	SNP
37	M	77	1295228	1295228	G228A	5'Flank	SNP
38	M	69	1295228	1295228	G228A	5'Flank	SNP
40	M	49	1295228	1295228	G228A	5'Flank	SNP
45	M	41	1295228	1295228	G228A	5'Flank	SNP
49	M	48	1295228	1295228	G228A	5'Flank	SNP

Median duration of follow-up was 49 months (range, 39–55 months) after operation. Among these patients, 14 experienced local recurrence, 5 experienced distant metastasis, and 4 had both types of relapse during the follow-up period, with a median recurrence duration of 267 (range, 41-1131) days.

3.2 TERT promoter and TP53 are frequently mutated in hepatocellular carcinoma

To better delineate the genomic landscape of HCC, 50 tumor tissues obtained from paired patients were sequenced with a 1021 gene panel, which covering 1021 genes frequently mutated in HCC and other solid tumors. Sequencing results revealed that the most recurrently mutated genes were TP53 (48.0%, 24/50) and TERT (32.0%, 16/50), followed with LRP1B (26.0%, 13/50), CTNNB1 (18.0%, 9/50) and AXIN1 (14%, 7/50) (Fig. 1A), which were largely consistent with previous reports³⁴.

All TERTpm were found at the hotspot position of chr5, 1295228 G > A (C228T) (Fig. 1B and Table 1), while a total of 21 different TP53m were identified in 24 patients (Fig. 1C and Table 2). Among all TP53m, 17/24 were missense mutations, 3/24 were splice-site mutations, 2/24 were nonsense mutations, 1/24 was frameshift-deletion mutation, and 1/24 had coexistence of frameshift-deletion and missense mutations.

Table 2

Mutation details of patients with *TP53m*
Patient	Age	Gender	Start_Position	End_Position	Variant classification	Variant type	Reference allele	Seq allele	dbSNP_RS
2	M	64	7577018	7577018	Splice_Site	SNP	C	A
4	M	63	7577098	7577098	Missense_Mutation	SNP	T	A
5	M	49	7578534	7578534	Missense_Mutation	SNP	C	A	rs866775781
7	M	24	7577018	7577018	Splice_Site	SNP	C	A
9	F	64	7577121	7577121	Missense_Mutation	SNP	G	A	rs121913343
10	M	49	7579485	7579485	Nonsense_Mutation	SNP	C	A	rs869312782
11	M	52	7579329	7579329	Missense_Mutation	SNP	T	C	rs121912658
12	M	66	7573987	7573994	Frame_Shift_Del	DEL	GCCTCATT	-	novel
14	F	45	7577534	7577534	Missense_Mutation	SNP	C	A	rs28934571
15	M	47	7577098	7577098	Frame_Shift_Del	DEL	T	-
			7577580	7577580	Missense_Mutation	SNP	T	C	rs587780073
			7578535	7578535	Missense_Mutation	SNP	T	A	rs1057519996
21	M	53	7578412	7578412	Missense_Mutation	SNP	A	G
25	F	57	7577534	7577534	Missense_Mutation	SNP	C	A	rs28934571
29	F	58	7578455	7578455	Missense_Mutation	SNP	C	G	rs730882000
32	M	51	7577551	7577551	Missense_Mutation	SNP	C	A
33	M	55	7573976	7573976	Missense_Mutation	SNP	T	C	rs141402957
34	F	67	7577534	7577534	Missense_Mutation	SNP	C	A	rs28934571
35	M	69	7578235	7578235	Missense_Mutation	SNP	T	C
36	M	33	7577559	7577559	Missense_Mutation	SNP	G	C	rs28934573
37	M	77	7579362	7579362	Missense_Mutation	SNP	A	C	rs1057523496
39	F	52	7578190	7578190	Missense_Mutation	SNP	T	C	rs121912666
40	M	49	7578556	7578556	Splice_Site	DEL	T	-
48	M	56	7579485	7579485	Nonsense_Mutation	SNP	C	A	rs869312782
49	M	48	7578541	7578541	Missense_Mutation	SNP	A	T
50	M	48	7577534	7577534	Missense_Mutation	SNP	C	A	rs28934571

3.3 Association of TERTpm with TP53m in HCC

As summarized in Table 3, 16 cases harbored TERTm, and 24 cases harbored TP53m. Out of them, 16 cases harbored TP53m only, 8 cases harbored TERTm only, 8 cases harbored both TP53m and TERTm, and none of the two mutation types were detected in the other 18 cases.

Table 3

Association of *TERTpm* with *TP53m* in HCC~
TERTpm+ (n = 16)		TERTpm- (n = 34)
TP53m-	TP53m+	TP53m-	TP53m+
8/26 (30.8%)	8/24 (33.3%)	18/26 (76.5%)	16/24 (70.6%)
P > 1		P > 1
+: positive, -: negative.

In total, TERTm C228T was found in 33.3% (8 of 24) of TP53m-positive HCC vs 30.8% of (8 of 26) TP53m-negative HCC, showing a higher trend of TERTm C228T in the TP53m-positive HCC, but the association was not statistically significant. Accordingly, these data indicate that there was an undeniable association of TERTm C228T with the TP53m in HCC.

3.4 Association of TERTpm and TP53m with clinical-pathological parameters in HCC

We next evaluated the relationship of TERTpm and TP53m with the classical clinicopathological features of HCC, respectively. As shown in Table 4, TERTpm C228T and TP53m were more frequent in male patients (100% / 83.33%), in patients with single tumor (87.5% / 87.5%), in patients with G2-G3 hepatitis disease (100% / 83.3%), and in patients with well differentiated tumors (75.0% / 83.3%). Although, patients with TERTpm had significantly lower AFP level (≤ 20 ng/mL, P < 0.05) than negative ones, we did not find any association with other laboratory tests, which including total bilirubin (TBIL), LDH, AST, etc.

Table 4

Clinicopathological parameters of the HCC cohort
Variables		Total (n = 50)	TERTpm+ (n = 16, 32%)	TERTpm- (n = 34, 68%)	P-value	TP53m+ (n = 24, 48%)	TP53m- (n = 26,52%)	P-value
Age (years)		55 (24–87)	59 (41–87)	53 (24–69)	0.090	56 (24–87)	54 (33–77)	0.553
Gender: n (percentage)	F	9 (18.0%)	0	9 (26.5%)	0.043	4 (16.7%)	5 (19.2%)	> 1
	M	41 (82.0%)	16 (100%)	25 (73.5%)	0.043	20 (83.3%)	21 (80.8%)	> 1
Height (cm): mean (range)		165 (149–180)	164 (150–172)	165 (149–180)	0.815	166 (149–180)	163 (150–178)	0.089
Weight (kg)		64 (33–103)	67 (50–84)	63 (33–103)	0.235	66 (33–103)	63 (41–82)	0.881
Clinical-pathological data
Tumor numbers	Single	47 (94.0%)	14 (87.5%)	33 (97.1%)	0.237	21 (87.5%)	26 (100%)	0.103
	Multiple	3 (6.0%)	2 (12.5%)	1 (2.9%)		3 (12.5%)	0
Tumor diameter (cm): mean ± SD		5.80 ± 3.7	5.2 ± 2.1	6.1 ± 4.2	0.221	5.1 ± 3.3	6.4 ± 3.9	0.509
Differentiation	Poor	14 (28.0%)	4 (25.0%)	10 (29.4%)	0.746	4 (16.7%)	10 (41.7%)	0.119
	Moderate	36 (72.0%)	14 (75.0%)	24 (70.6%)	0.746	20 (83.3%)	16 (61.5%)	0.119
WHO grade	II	38 (76%)	14 (87.5%)	24 (70.6%)	0.292	16 (66.7%)	22 (84.6%)	0.190
	III	12 (24%)	2 (22.5%)	10 (29.4%)	0.292	8 (33.3%)	4 (15.4%)	0.190
Hepatitis	G1	7 (14.0%)	0	7 (20.6%)	0.081	4 (16.7%)	3 (11.5%)	0.697
	G2-G3	43 (86.0%)	16 (100%)	27 (79.4%)	0.081	20 (83.3%)	23 (88.5%)	0.697
Cirrhosis	Yes	27 (54.0%)	8 (55.0%)	19 (55.9%)	0.767	14 (58.3%)	13 (50.0%)	0.584
	No	23 (46.0%)	8 (55.0%)	15 (44.1%)	0.767	10 (41.7%)	13 (50.0%)	0.584
Macrovascular invasion	Yes	17 (34.0%)	5 (31.2%)	12 (35.3%)	> 1	10 (41.7%)	7 (26.9%)	0.373
	No	33 (66.0%)	11 (68.8%)	22 (64.7%)	> 1	14 (58.3%)	19 (73.1%)	0.373
Recurrence	Yes	23 (46.0%)	9 (56.3%)	14 (41.2%)	0.373	15 (62.5%)	8 (30.8%)	0.046
	No	27 (54.0%)	7 (43.7%)	20 (58.8%)	0.373	9 (37.5%)	18 (69.2%)	0.046
PFS (days)		462 ± 395	479 ± 396	463 ± 395	0.172	462 ± 395	511 ± 402	0.806
Early recurrence (≤ 12 month)	Yes	15 (30%)	7 (43.8%)	8 (23.5%)	0.191	11 (45.8%)	4 (15.4%)	0.030
	No	35 (70%)	9 (56.2%)	26 (76.5%)	0.191	13 (54.2%)	22 (84.6%)	0.030
Lab data
AFP (ng/mL)	> 20	28 (56.0%)	5 (31.2%)	23 (67.6%)	0.031	11 (45.8%)	17 (65.4%)	0.2542
	≤ 20	22 (44.0%)	11 (68.8%)	11 (32.4%)	0.031	13 (54.2%)	9 (34.6%)	0.2542
HBV-DNA	Positive	29 (58.0%)	7 (43.7%)	22 (64.7%)	0.2224	13 (54.2%)	16 (61.5%)	0.7749
	Negative	21 (42.0%)	9 (56.3%)	12 (35.3%)	0.2224	11 (45.8%)	10 (41.7%)	0.7749
TBIL (µmol/L)		13.67 ± 6.9	13.70 ± 6.3	13.65 ± 7.2	0.497	13.22 ± 8.0	14.08 ± 5.8	0.557
ALB (g/L)		41.8 ± 4.5	42.7 ± 4.5	41.4 ± 4.5	0.715	41.2 ± 5.5	42.4 ± 3.3	0.457
AST (IU/L)		63 (16–477)	36 (18 − 16)	76 (16–477)	0.675	58 (16–477)	68 (19–385)	0.245
ALT (IU/L)		64 (12–663)	44 (12–26)	73 (13–663)	0.520	58 (12–369)	70 (13–663)	0.710
GLB (g/L)		27.4 ± 6.5	28.7 ± 5.8	26.8 ± 6.8	0.467	28.3 ± 5.4	26.7 ± 7.4	0.603
ALP (IU/L)		118 (49–451)	107 (55–76)	123 (49–451)	0.582	113 (49–451)	123 (58–405)	0.457
GGT (IU/L)		84 (14–440)	95 (18–329)	79 (14–440)	0.537	88 (15–440)	81 (14–329)	0.561
TP		68.9 ± 6.6	71.5 ± 6.8	67.7 ± 6.3	0.516	68.8 ± 7.6	69.0 ± 5.7	0.429
LDH		198 (101–828)	172 (136–240)	210 (101–828)	0.435	178 (117–444)	217 (101–828)	0.501
UREA		5.1 ± 1.3	5.6 ± 1.2	4.9 ± 1.3	0.312	5.3 ± 1.2	5.0 ± 1.4	0.298
CREA		77 ± 14	80 ± 10	75 ± 15	0.525	74 ± 13	80 ± 14	0.111
EGFR		92.89 ± 13.88	89.66 ± 13.38	94.41 ± 14.04	0.485	95.12 ± 13.15	90.83 ± 14.46	0.473
CYSC		3.0 (0.6-102.6)	1.0 (0.7–1.4)	3.9 (0.6-102.6)	0.605	5.2 (0.6-102.6)	1.0 (0.6–1.2)	0.597
GLU		5.62 ± 2.20	6.37 ± 3.07	5.27 ± 1.59	0.394	5.74 ± 2.75	5.51 ± 1.60	0.473

Interestingly, TP53m-positive patients revealed a significantly higher recurrence risk than TP53m-negative (62.5% / 30.8%, P < 0.05) ones. Though it was not statistically significant, there do have a higher trend of recurrence rate in TERTpm-positive patients (56.3% / 41.2%). Further, we found that patients with TERTpm (43.8% / 23.5%) or TP53m (45.8% / 15.4%, P < 0.05) have a tumor relapse earlier (< 12 month) than those negative ones.

Taken together, the analyses above suggest potential prognostic value of TERTpm and TP53m in HCC.

3.5 TERTpm coexistence with TP53m was associated with worse prognostic in HCC

As presented in Table 5, to further explore the potential prognostic value of TERTpm and TP53m, we also examined the individual effects of TERTpm alone, TP53m alone, and coexistence of TERTpm and TP53m on clinicopathological outcomes of HCC. Surprisingly, whereas the effects of TP53m alone and TERTpm alone were lost, coexistence of TERTpm and TP53m was more commonly and more significantly associated with the aggressive clinicopathological characteristics of HCC, including higher risk of recurrence (P < 0.05), and earlier relapse period (≤ 12 month, P < 0.05).

Table 5

Association of *TERTpm*, *TP53m*, and their co-existence with tumor recurrence
Variables		TERTpm- / TP53m- (n = 18, 36%)	TERTpm+ / TP53m- (n = 8, 16%)	P value	TERTpm- / TP53m+ (n = 16, 32%)	P value	TERTpm+ / TP53m+ (n = 8, 16%)	P value
Age (years)		54 (39–67)	61 (41–87)	0.110	56 (24–69)	0.763	54 (47–66)	0.420
Gender	F	3 (16.7%)	0	0.529	6 (37.5%)	0.250	0	0.529
	M	15 (83.3%)	8 (100%)	0.529	10 (62.5%)		8 (100%)	0.529
Height (cm)		162 (153–180)	167 (162–170)	0.947	160 (149–170)	0.279	164 (150–172)	0.267
Weight (kg)		64 (49–83)	63 (50–78)	0.679	60 (33–103)	0.413	65 (61–84)	0.114
Tumor numbers	Single	17 (94.4%)	8 (100%)	> 1	16 (100%)	> 1	6 (75.0%)	0.215
	Multiple	1 (5.6%)	0	> 1	0	> 1	2 (25.0%)	0.215
Tumor diameter (cm)		5.6 ± 3.6	5.45 ± 1.92	0.749	6.75 ± 4.31	0.859	5.6 ± 3.5	0.476
Differentiation	Poor	4 (22.2%)	0	0.277	6 (37.5%)	0.457	4 (50.0%)	0.197
	Moderate	14 (77.8%)	8 (100%)	0.277	10 (62.5%)	0.457	4 (50.0%)	0.197
WHO grade	II	14 (77.8%)	8 (100%)	0.277	10 (62.5%)	0.457	6 (75.0%)	> 1
	III	4 (22.2%)	0	0.277	6 (37.5%)	0.457	2 (25.0%)	> 1
Hepatitis	G1	3 (16.7%)	0	0.529	4 (25%)	0.682	0	0.529
	G2-G3	15 (83.3%)	8 (100%)	0.529	12 (57%)	0.682	8 (100%)	0.529
Cirrhosis	Yes	10 (55.6%)	3 (37.5%)	0.673	9 (56.3%)	> 1	5 (62.5%)	> 1
	No	8 (44.4%)	5 (62.5%)	0.673	7 (43.7%)	> 1	3 (27.5%)	> 1
Macrovascular invasion	Yes	7 (38.9%)	0	0.062	5 (31.3%)	0.729	5 (62.5%)	0.401
	No	11 (61.1%)	8 (100%)	0.062	11 (68.8%)	0.729	3 (27.5%)	0.401
Recurrence	Yes	5 (27.8%)	3 (37.5%)	0.667	9 (56.3%)	0.163	6 (75.0%)	0.038
	No	13 (72.2%)	5 (62.5%)	0.667	7 (43.7%)	0.163	2 (25.0%)	0.038
Recurrence (≤ 12 month)	Yes	2 (11.1%)	2 (25%)	0.563	6 (37.5%)	0.110	5 (62.5%)	0.014
	No	16 (88.9%)	6 (75%)	0.563	10 (62.5%)	0.110	3 (27.5%)	0.014

In survival analysis, we found that coexistence of TERTpm and TP53m had the shortest PFS (P < 0.05) (Fig. 2). Given that there was no patients died in the follow-up duration, another 207 HCC patients with complete outcome information was obtained from The Cancer Genome Atlas (TCGA) liver hepatocellular carcinoma database for survival analysis (Supplementary Table 2). Among these, 8 patients had TP53m alone, 52 had TERTpm C228T alone, 19 had both, and 128 had neither. The median follow-up time overall was 953 days (range, 3-1826 days), and 115 patients died during this period. The all-cause mortality rates of patients with both negative, TP53m alone, TERTpm alone, and both positive were 52.34% (67/128), 87.5% (7/8), 50% (26/52), and 78.95% (15/19), respectively (Supplementary Table 3).

Based on these data, it was clear that the coexistence of TERTpm and TP53m had considerably worse survival outcome.

Hepatocellular carcinoma (HCC) is a formidable adversary in the landscape of global health, with its high recurrence rate being a major contributor to the poor prognosis and elevated mortality rates among patients. Despite the utility of laboratory markers like alpha-fetoprotein (AFP) and imaging techniques in diagnosing recurrence, the early detection of this phenomenon remains elusive^6–8. This study, therefore, aimed to identify predictive biomarkers that could foresee recurrences in HCC, a pursuit that is both timely and crucial.

The genesis of tumors is a complex tapestry woven by multiple genetic alterations, and while the molecular underpinnings of HCC's initiation and progression are not fully elucidated, certain mutations stand out. TP53 mutations and TERT promoter mutations are reported to be the most common somatic alterations in hepatocellular carcinoma^7,9–16. Notably, TERTpm have been linked to enhanced telomerase activity and TERT mRNA expression across various cancers, including meningioma, urothelial carcinoma, glioblastoma, and HCC. These alterations are associated with cellular immortalization and a grim prognosis^{10,27,35–37}. TP53 mutations, in turn, often result in the inactivation of TP53 and p53 protein, leading to chromosomal instability and unchecked proliferation, hallmarks of many cancers^38,39. However, the interplay between TERTpm and TP53 mutations and their collective impact on HCC recurrence is not well understood, a gap this study sought to bridge.

For this reason, using the next-generation sequencing technology, we identified the genetic landscape and mutation signatures of HCC in liver tumor tissues from 50 HCC patients. The association of TP53m, TERTpm, and their coexistence with clinicopathological features and outcome was explored to further clarify their potential value in HCC.

We identified that all tumor tissues involved in this study harbored genetic alterations, among which TP53m and TERTpm (C228T) were the most frequent, with a prevalence of 48% and 32%, respectively. Previous published studies showed that the incidence of TP53m and TERTpm (C228T) in HCC were 18.7%~48% and 14.9%~60%, respectively^7,9–16. Overall, our results were consistent with those of most previous findings, indicating the importance of TP53m and TERTpm (C228T) in HCC. After that, other mutated genes such as LRP1B (26%), CTNNB1 (18%) and AXIN1 (14%) were also identified in the present study, which were similar to the previous researches^{10,13,29,40,41}. Our results showed that patients with TP53m were significantly associated with moderately differentiated tumors and early recurrence. Meanwhile, TERTpm were considerably associated with male gender and lower serum AFP levels. However, neither TP53m nor TERTpm was linked to age, body measurements, tumor characteristics, or other clinical features and laboratory features, suggesting a more nuanced relationship between these genetic alterations and clinical manifestations..

Among the 50 HCC patients, 23 cases experienced intrahepatic tumor recurrence or distant metastases, 9 harbored TP53m alone, 3 harbored TERTpm alone, 6 harbored both, and 5 harbored neither. According to these data, we can infer that patients with TP53 mutations were more likely to experience tumor recurrence than negative ones. While the recurrence rate of HCC in patients with TERTpm was not statistically different from those TERTpm-negative ones, the presence of TERTpm did elevate the probability of tumor recurrence in patients from 41.2–56.3%, especially the early recurrence rate was improved from 23.5–43.8%. However, there was no significant difference of recurrence rate in patients with neither TP53m alone nor TERTpm alone, compared to those with negative TP53m and negative TERTpm. By contrast, coexistence of TERTpm and TP53m indicated a higher likelihood of tumor recurrence, and poor progression-free survival. This finding is intriguing, as it points to a potential synergistic effect between these mutations, a hypothesis supported by the known interaction between p53 and TERT.

Previous studies have found a strong interaction between p53 and TERT. On the one hand, p53 as a transcription factor have been shown to repress TERT mRNA level ^42,43. On the other hand, suppression of TERT could induce DNA damage and apoptosis in a p53-dependent way^44–46. Further, both TERTpm and TP53m are associated with tumorigenesis. Thus, we speculated that genomic mutations of both TERT and TP53 have strengthened the interaction between the two, which promote tumor progression and lead to poorer prognosis in HCC patients.

To address this hypothesis, we consulted the current literature on p53-TERT and found that p53 was a powerful inhibitor of the TERT promoter activity. TP53m were responsible for upregulation of TERT mRNA level, by physically interacting with other transcription factors such as Sp1 (activate transcription of TERT) to nucleated onto the TERT promoter^47–49. Since TERTpm could introduce new binding sites for transcription factors such as ETS/TCF, and TERT promoter also contain Sp1 binding motifs. Taken together, it is thus overwhelmingly probable that TERTpm C228T may introduce a new binding site for Sp1, facilitating increased p53 binding and TERT activation. However, further work is required to investigate the exact mechanisms and their functional effects, since there is a lack of evidence at this point to support our hypothesis.

In conclusion, this study provides a comprehensive genomic portrait of HCC, identifying TP53m and TERTpm as common somatic alterations. The coexistence of these mutations appears to be a promising marker for tumor recurrence and poor prognosis, offering valuable insights for postoperative surveillance and personalized treatment strategies. While our findings are promising, they also underscore the need for larger-scale studies to validate these observations and explore the underlying mechanisms, potentially paving the way for novel therapeutic interventions in HCC.

Author contributions statement

Jin Li: Formal analysis, investigation, visualization, writing & editing of the manuscript

Ling Bai: Formal analysis, investigation, visualization, writing & editing of the manuscript

Zhaodan Xin: Formal analysis, investigation, writing & editing of the manuscript

Jiajia Song: Investigation, writing & editing of the manuscript

Hao Chen: Investigation, writing & editing of the manuscript, funding acquisition

Xingbo Song: Supervision, project administration, reviewing & editing of the manuscript

Juan Zhou : Supervision, funding acquisition, project administration, reviewing & editing of the manuscript

Data availability statement

Raw data for the sequencing analysis included in this study have been deposited in Gene Expression Omnibus (GEO), accession number GSE273254.

Acknowledgements

This work was supported by the Department of Liver Surgery and Liver Transplantation Center, West China Hospital of Sichuan University, thanks for their assistance in patients materials and samples provision.

Competing interests

The authors declare no competing interests.

Ethics statement

The studies involving human participants were reviewed and approved by the Biomedical Ethics Committee of West China Hospital of Sichuan University [Reference No. 2019 (203)]. The patients/participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.

Funding

This work was supported by grants from the National Natural Science Foundation of China (82372331), and the Project of Science and Technology Department of Sichuan Province (2023NSFC0716).

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TERT Promoter Mutations Combined with TP53 Mutations as Potential Biomarkers for Hepatocellular Carcinoma Recurrence and Prognosis

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Abstract

Figures

1 Instruction

2 Materials and methods

2.1 Ethics Statement

2.2 Patients, tissue samples, and clinicopathologic data

2.3 DNA extraction

2.4 Next-generation sequencing (NGS)

2.5 Statistical analysis

3 Results

3.1 Patients’ clinicopathological characteristics

3.2 TERT promoter and TP53 are frequently mutated in hepatocellular carcinoma

3.3 Association of TERTpm with TP53m in HCC

3.4 Association of TERTpm and TP53m with clinical-pathological parameters in HCC

3.5 TERTpm coexistence with TP53m was associated with worse prognostic in HCC

4 Discussion

Declarations

References

Additional Declarations

Supplementary Files

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