Bladder cancer is the fourth and the 11th most common cancer in men and women, respectively, representing 6.6% of all cancer types (Rubio, et al., 2021).
The need for non-invasive tools for diagnosis and follow up led to the identification of biomarkers in the urine (Georgantzoglou, et al., 2021).
Liquid biopsies are increasingly used for the diagnosis and follow-up of cancer patients. Urine is a body fluid that can be used to detect cancers and others diseases. It is noninvasive and easy to collect (Charpentier, et al., 2021).
In the present study, we have analysed the TP53 mutational spectra in urine sediments of urinary bladder tumors by studying the mutation frequency in exons (2 + 3), 4 and 5 in a material consisting of TCCs and SqCCs of various stage and grade. We used PCR technique for mutation screening followed by sequencing for confirmation and identification of mutations.
Our results indicated that 54 (36%) patients of 150 enrolled in this study were mutated in exon (2 + 3) with statistically higher significant in patients when compared to controls (P = 0.001), while 96 patients (64.0%) in Exon 4 (P = 0.001), and 111 patients (74.0%) in Exon 5 (P = 0.001).
For double mutation, it was indicated that 48 patients (32%) had mutations in exon (2 + 3) and exon 4 together, 51 patients (34%) had mutations in exon (2 + 3) in combination with exon 5, 78 patients (52%) were mutated in exon 4 and 5, while 48 (32%) were mutated in the 3 studied exons.
Wallerand et al., 2005 indicated that of the 110 tumors studied, 22 harbored
TP53 mutations (20%). These mutations were located in exons 4–9; one mutation was located at a splice acceptor site of intron 6. Wallerand also reported that no mutations were found in exons 2, 3 which is on the contrary to our results as the mutation frequency in exon (2 + 3) was 36%, his study detected only 4 patients had double mutation (3.6%) while our results indicated that the highest percentage of double mutation was 52% in exons 4 and 5.
Al-Kashwan et al., 2012 reported that the sequencing results confirmed 10 cases of the 29 harbored one or more TP53 mutations (37.9%) and among them 7 patients (63.6%) showed single mutation and 3 (27.3%) had double mutations. On the other hand, Noel et al., 2015 revealed that the functional TP53 mutations were 56 out of the 103 analyzed tumors (54% of cases).
The study of Ecke et al., 2008 has reported that the mutations were detected in 26 of 75 patients (34.7%) and only 6 mutations (8%) were detected in exon 5 and these results contradict our results which showed a large percentage of mutations (74%) in exon 5.
The univariate logistic regression analysis of the present study revealed that all the studied exons were statistically associated with BC and the prevelence of mutations of exons (2 + 3), 4 and 5 of TP53 gene may be used as predictor and/or prognostic parameters for BC prospection.
Regarding sensitivity, the probabilities of detecting a TP53 mutation in the urinary
sediment for exons (2 + 3), 4 and 5 were 36%, 64% and 74% respectively for the urine test. Moreover, the specificity and the positive predictive value of the 3 studied exons were 100% and the negative predictive value of (2 + 3), 4 and 5 exons were 34.2%, 48.1% and 56.2% respectively while the results of Noel et al., 2015 indicated that the sensitivity was 34% and the specificity was 87%, with a positive predictive value of 76% and a negative predictive value of 53%.
Our results demonstrated that in exon (2 + 3), smoking, TCC cases were significantly associated with mutation frequency. Whilst, in exon 4, significant association was observed with TCC cases, positive patients for CIS. Furthermore to the previous factors, age and bilharzial patients were significantly associated with mutation frequency in exon 5. Futhermore, the present study revealed a significant association between the 3 studied exons and lymph node metastasis and as a consequence, it may be considered as a useful prognostic indicator for tumor metastasis.
Notably, our results support the notion that a higher proportion of mutations was found in high tumor grade than in low grade and in advanced stage. In addition, a significant association was observed in exon (2 + 3) between mutation occurrence and patients pathologically classified as GIII and T3 with P (0.001, 0.02) respectively. Regarding exon 4, significant association was also observed in cases with GIII and T3 with P (0.001, 0.02) respectively, while in exon 5, the association was with patients with GII and T3 with P (0.001, 0.001) respectively.
The above findings matched those of Liao et al., 2021 who stated that high stage of BC has obviously higher level of TP53 mutation than the lower stage and also consistent with those of Shao et al., 2021 who reported that TP53 mutations were most frequent among BC patients with high tumor grade. The overall analysis provides a strong support to the initial findings, which further confirmed the potential diagnosis role of TP53 mutation in advanced BC.
The occurrence or recurrence of BC is a molecular biological change or process that is effected by occupational factors, non-occupational factors, genomics and proteomics factors (Fan, et al., 2021).
The clinical value of TP53 in bladder cancer as a predictive marker of tumor recurrence and treatment selection is still in debate (Sobhani et al., 2021). But the results of our study settled this matter and statistically proved the the clinical value of TP53 in bladder cancer as a predictive marker of both tumor metastasis and recurrence.
Analysis of the data using Log Rank Mantel-Cox for tumor recurrence showed a significant association between mutation frequency in exons (2 + 3), 4 and tumor recurrence with P = 0.001, 0.008 respectively while no significant association was observed in exon 5. Hence, TP53 mutation is an independent predictor of tumor recurrence in mutant BC patients in exons (2 + 3) and 4. However, other studies have shown a cosiderable discrepancy regarding tumor recurrence as Ecke et al., 2008 who stated that Kaplan-Meier analysis for tumor recurrence showed that the tumor recurrence frequency was 69.4% in patients with TP53 wild-type, and 88.5% in patients with TP53 mutation.
Previous studies reported the vital role of TP53 in urothelial carcinogenesis, however, other factors may contribute to it and to tumor recurrence because not all the mutant patients who were followed up have recurrence. Accordingly, the present study clarified the association between tumor recurrence and clinicopathological parameters in BC patients according to TP53 mutation frequency. It was noted that tumor recurrence was significantly associated with multiple number of tumor mass, tumor size, patients with carcinoma in situ and patients with GII while no association was observed among patients with GIII and T3. These results can be explained by the little chance of recurrence to occur in stage 3 BC because the line of treatment is usually radical cystectomy, which is not the case in treating lower stages of BC.
Saoud et al., 2021 reported in his case study that he presented this case to highlight how even patients with NMIBC disease may rapidly progress towards metastatic MIBC and death and hypothesized that in addition to histological analysis of the tumor, early molecular and cytogenetic characterization of resected tissue is essential in predicting prognosis of the disease based on identifiable gene mutations. Interestingly, our results revealed a significant assosiation between TP53 mutation frequency and tumor metastasis in all the studied exons with the same P value of 0.001.
Generally, our results demonstrated a higher abundance of double mutation comparing to the data published in previous studies, the findings revealed 48 patients (32%) had mutations in exon (2 + 3) and exon 4 together, 51 patients (34%) had mutations in exon (2 + 3) in combination with exon 5, 78 patients (52%) were mutated in exon 4 and 5, while 48 (32%) were mutated in the 3 studied exons. These results do not coincide with Erill et al., 2004 ’s results who detected only 2 cases displayed double mutation of 76 BC patients while Ecke et al., 2008 detected five patients had mutations in two TP53 exons of 75 BC patients.
Furthermore, the double mutation frequency with all the probabilities and triple mutations were significantly associated with lymph node positivity expressing tumor metastasis, but no links were observed between mutation frequency and tumor recurrence in double and triple mutation patients.
Notably, our results unveils the evidence that the most common mutations observed in TP53 DNA were missense mutations while frameshift and silent types were found to be less frequent.
Our results suggest a larger number of missense mutation, C→G in 33 mutants and T→G in 21 mutant patients in exon (2 + 3), this genomic instability may reflect the role of other factors in carcinogenesis as smoking (77.8%) and mutant patients with bilharziasis (83.3%),
it was also found a high frequency of missense mutation C→T (45/96, 46.8%) in mutant patients in exon 4, silent mutation G→T (27/96, 28.1%), an insertion of C nucleotide at codon 151 (9/96, 9.3%) and a frameshift mutation G→A at codon 152 (15/96, 15.6%). Surprisingly, Schroeder et al, 2003 reported a nucleotide substitution at codon 110 G→A that leads to amino acid change (Arginine→Histidine), while at the same codon and exon, Wallerand et al., 2005 reported a nucleotide substitution G→T, leads the Arginie to be changed to Leucine in mutation of exon 4.
It has been indicated that missense mutations were the most prevalent type of TP53 mutation in exon 5, A→C in 22 mutants, T→C in 19 and G→A in 57 mutants (98/111, 88.2%) and finally 13 silent mutations T→C were observed at codon 180 13/111, 11.7%) where Tyrosine unaltered than reference, the detected silent mutation at codon 180 in exon 5 catches our attention because Schlichtholz, 2004 and his team mates detected a missense mutation at which G→A leads to amino acid change (Glutamic acid→Lysine).
In summary, our results show, that the mutation of exons (2 + 3), 4 and 5 of TP53 gene may be used as predictor and/or prognostic parameters for BCa prospection. Furthermore, our study provides a foundation could help clinicians to predict tumor recurrence and metastasis, this finding is even more valuable, because TP53 mutations can be analyzed in sediments of urine cells by non-invasive methods. Since TP53 mutation frequency is significantly associated to clinicopathological features of
BC patients, consequently, the inclusion of both TP53 mutation status and genetic analysis into the predictive panel of tumor markers for bladder cancer is recommended.
Patients and samples
A total of 150 patients and 50 healthy volunteers as controls were enrolled in this study, it included a patient criterion of diagnosed BC patients who did not receive any type of therapy, and the diagnosis was confirmed by histo-pathological examination of the removed tumor tissues by 2 independent pathologists. Before recruitment, a signed informed consent was obtained from all participants. The research protocol was conducted according to the guidelines of the ethical principles outlined in the declaration of Helsinki and was approved by the institutional review board of the Ethics Committee of Theodor Bilharz Research Institute, in accordance with the institutional guidelines. Urine samples were collected from patients and controls, samples were centrifuged at 3000 rpm for 20 min, The supernatant was decanted and the pellet was re-suspended in 1x pbs (PH7.2), centrifuged again and the pellet was stored at − 80°C until the DNA extraction.
DNA extraction from urine samples:
DNA extraction was carried out using Qiagen DNeasy kit (Hilden, Germany) as per manufacturer instructions, the purified DNA was dissolved in 50 µl of water, measured on a Nanodrop ND-2000c (Thermo Scientific, Waltham, MA, USA), and stored at − 20°C for further analyses.
TP53 mutation analysis for exons 2 + 3, 4 and 5 by PCR
For TP53, we screened for mutations in exons 2 + 3, 4 and 5 by PCR in a final volume of 25 µl containing 100 ng of urine sediment DNA, exons (2 + 3), 4 and 5 of the TP53 gene were amplified using the primers shown in (Table 1) (Bakkar, et al., 2003). Cycling conditions were as follows: initial denaturation at 95°C for 5 minutes, 35 cycles at 95°C for 30 seconds, annealing at 58°C for 30 seconds, and extension at 72°C for 30 seconds, The mixture was then heated at 72°C for 10 min as a final extension step.
PCR products were resolved on 3% agarose gel, electrophoresed on a Bio-RAD electrophoresis chamber, with 5 µl of 100–1000 bp DNA ladder RTU used as a marker and visualized by ethidium bromide staining. The gel image was analyzed using Cleaver Scientific’s micro DOC gel documentation system.
DNA Sequence analysis
The PCR products for all exons were subjected to Exonuclease I-Shrimp Alkaline Phosphatase PCR product treatment (Thermo Fisher, catalogue no. 78200). This enzymatic treatment hydrolyzes excess primers and nucleotides in a single step. The Exonuclease I‐Shrimp Alkaline Phosphatase‐purified samples were subjected to bidirectional sequencing on an ABI PRISM 3100 Genetic Analyzer (Applied Biosystems). The abnormal sequencing results were reconfirmed by at least 2 repeats right from PCR amplification. Furthermore, a wild‐type sequencing control was run for comparison of abnormal sequencing results.
Nucleotide sequencing and analysis
Exons sequences of TP53 gene were matched with reference sequences registered in the GenBank database through BLAST-NCBI (https://blast.ncbi.nlm.nih.gov), after that, all sequences were aligned by using the BioEdit software which depending on the ClustalW multiple alignment conditions.
Statistical analysis methods
The data were analysed using Microsoft Excel 2016 and statistical package for social science ‘IBM SPSS Statistics for Windows, version 26 (IBM Corp., Armonk, N.Y., USA)'. Continuous normally distributed variables were represented as mean ± SD. with 95% confidence interval, while nonnormal variables were summarized as median with 25 and 75 percentile, and using the frequencies and percentage for categorical variables; a P value < 0.05 was considered statistically significant. To compare the means of normally distributed variables between groups, the Student’s t test was performed, and Mann-Whitney U test was used in non-normal variables. Chi-square (χ2) test or Fisher’s exact test were used to determine the distribution of categorical variables between groups. Logistic regression analysis was performed to identify predictor associated with the risk of BC occurrence. The diagnostic performance of the studied exons was assessed by receiver operating characteristic (ROC) curves. The area under the ROC (AUC) was calculated as an accuracy index for prognostic performance of selected tests.