Discriminating Human Papillomavirus Genotypes Using an Innovative High-Resolution Nested Fusion Technique
Due to the importance of identifying low-risk genotypes, high-risk genotypes, and mixed infections, a rapid and cost-effective method is needed to overcome barriers to HPV genotyping.
Cervical cancer is the second most common malignancy in women and poses a serious threat to women’s health. Although cervical cancer is preventable, more than 500,000 women worldwide are diagnosed with cervical cancer and more than 250,000 women die from cervical cancer each year.26. According to the World Health Organization (WHO), the human papillomavirus is currently the most common sexually transmitted disease in terms of unprotected sex, and the most important consequence of the virus is cervical cancer.27, 28.
The diagnosis of precancerous cells that is part of cervical cancer screening can be invaluable. Therefore, cervical cancer screening for eligible and high-risk individuals, as well as discrimination against HPV genotypes, is crucial in the prevention, diagnosis and early treatment of the disease.29. Therefore, in addition to screening methods, discrimination between HPV-DNA genotypes and copy number determination might be important, which was the main focus of our study. The copy number of HPV infection is known to determine the duration and severity of the disease30.
Therefore, considering the factors mentioned above, fusion-based curves, especially HRM, can be used as an alternative method in the simultaneous identification and discrimination of HPV genotypes. Moreover, the acquisition of a new technique by targeted selection of primers gives acceptable results and can be useful to discriminate between different genotypes.
Previous studies have shown that the HRM method can diagnose different influenza A subtypes31astrovirus32, C. meleagridis23and Yersinia pseudotuberculosis33. Also, the alteration of the melting curve in the HRM method discriminated the Iranian Leishmania pests of L major, L. tropic and mixed infection in the study by Ghafari SM et al.34. In addition, Mosawi SH et al., on the status of asymptomatic malaria in eastern Afghanistan, were able to distinguish P. vivax, P. falciparumand mixed infections using high-resolution fusion analysis35. The differentiation of Mitragyna ally speciosa Mitragyna species was performed using high-resolution DNA barcode fusion analysis by Chayapol Tungphatthong et al.36.
This study could identify important epidemiological and carcinogenic genotypes of HPV using the semi-imposed approach of HRM. These results were very promising as they provided acceptable results with less time and cost than conventional methods in the market.
The separation of the two main carcinogenic genotypes, HPV18 and HPV16, as well as the predominant genotype, HPV 6, in the research region was a significant obstacle in our investigation.37. Preliminary studies on the analysis of the melting temperature of these three genotypes with insilico tests have shown that bioinformatically it is impossible to separate HPV18 and HPV6 despite the difference of six nucleotides between these two genotypes in the region of the gene studied with a temperature difference of 0.03°C. However, HPV16 could be distinguished with a Tm = 82°C but a temperature difference of 0.7°C between HPV6 and HPV18. Moreover, in the first approach to the study, without considering the in vitro results, there was consistency with the bioinformatics analysis. The melting temperatures of HPV18, HPV16 and HPV6 were 81.67°C, 81.04°C and 81.52°C respectively. HPV18, a high-risk type being the second most common type in cervical cancer and HPV6, a low-risk genotype being the most common genotype in our study population37, did not have a unique profile and therefore could not be distinguished from each other. However, five HPVs, 16, 52, 59, 66 and 89, with unique characteristics were distinguished. To solve this problem, and in light of the findings of Lee et al., we used an unlabeled probe for HPV18 in the second method with the aim of differentiating HPV18 from HPV6, although the results were surprising. Unlike Lee et al. investigation, in which an unlabeled HPV-18 probe resulted in an additional melting peak for HPV18 that separated it from HPV4566, unlabeled probes for HPV6 had additional melting points; therefore, HPV6 and HPV18 could separate indefinitely, where this contradiction is still unknown.
Although the results of our approaches with the sequencing method as the gold standard have shown our great success in designing this assay, comparing the samples identified using the microarray method with our study method provided new challenges. However, the discrepancy between microarray results and these two methods is still debatable because the microarray method has sufficient accuracy to simultaneously detect known HPV subtypes.
This challenge occurred for isolates that were reported as HPV 11, 45, 83, and 84 using the microarray method, whose melting temperature curves were similar to the HPV 59 diagnostic standard in the method. semi-nested-qPCR-HRM in the first and third approaches which were genotyped by the sequencing method as HPV59. According to these views, incorrect genotyping or inaccurate differentiation between low-risk genotypes (HPV11 and HPV84) and high-risk genotypes (HPV45, HPV83 and HPV59) could have irreversible effects.38.
Another notable point is that although all HPV-DNA samples from isolates G40, G11 and G42 were genotyped by sequencing as HPV11, they did not show identical melting curves. This may be because in G40 only HPV11 was a single infection, but in G11 and G42 HPV-DNA was a mixed infection. The predominant genotypes of these isolates were identified as 59 and 45, respectively.
In the case of the G11 isolates, the presence of HPV-DNA 11 and 59 was genotyped after sequencing. In the first approach, the different HRM profile of this isolate compared to other isolates that confirmed the presence of HPV-DNA 59, despite the same peaks, could prove the hypothesis of a mixed infection. This justifies the discrepancy between microarray results with high-resolution nested fusion and sequencing methods.
In the third approach, the patterns were nearly identical to the first approach, with the addition of GP primers, confirming the difference between G11/HPV-DNA isolation and HPV59 as a pure diagnostic standard. Comparison of the three methods, nested qPCR-HRM, Sanger sequencing, and microarray, showed that the nested qPCR-HRM approaches nearly matched Sanger sequencing as the gold standard diagnosis.
These contradictions have been observed in other studies; for example, in the study by Alexander Harlé et al. one sample contained HPV 6/11 DNA, which was detected by conventional PCR and not by the Cobas test. Additionally, one sample had HPV 16 DNA detected with the Cobas test and not with conventional PCR, one sample had high-risk HPV DNA that was detected with conventional PCR and not with the test Cobas, one sample had HPV 16 DNA detected with the Cobas test and HPV 16 and HPV HR DNA with conventional PCR, one sample had HPV 16 DNA detected with the Cobas test and not with conventional PCR and one sample had HPV 18 DNA detected with the Cobas test and not with conventional PCR. The different reason could be the lack of consensus probes designed by the Cobas test39. However, several HPV genotyping assays have recently been reported that are able to type a relatively broad spectrum of HPV genotypes, but they cannot be automated or deployed in a high-throughput platform.13, 40, 41, 42, 43.
In population-based cervical screening, human papillomavirus (HPV) types 16, 18, 31, 33, 45, and 52 are associated with 85% of cervical cancers associated with HPV44, and we anticipated that we would be able to clone more genotypes as a diagnostic standard, the discrepancy between the results obtained by the microarray method and sequencing prevented us from achieving this goal. The genotypes cloned in this study represent common low- and high-risk HPVs in the Middle East37, 45. In this regard, the study by Lee et al. showed eight HPV genotypes 16, 18, 39, 45, 52, 56, 58 and 68 with a prevalence of more than 75% in Asia, Europe and the United States. Given the limited HPV genotypes conserved in our study, large-scale typing was limited for different HPV genotypes. It is expected that by obtaining more genotypes in the future, this method can be further evaluated and analyzed.
In conclusion, we assessed the validation of HPV genotyping via Tm value and HRM analysis of nested real-time PCR, which displayed the differential melting curves of different human papillomaviruses.
This approach has the potential to improve the discrimination of seven HPV genotypes, including HPV 16 and HPV 18, as cervical cancer carcinogens. The test can be suitable for routine analysis to detect HPV DNA in molecular laboratories as an alternative to Pap test and enables effective treatment management, which is very convenient for successful implementation of HIV programs. women’s health in low-resource areas.
To implement this technique, it is necessary to verify all the diagnostic standards provided in the kit with all the samples that are in the workflow and to determine the HPV genotype using the HRM technique, a decision is taken based on the comparison of Tm diagnostic standards with the Tm sample. It is both simple and quick to perform, which has been shown to have high sensitivity and specificity. Moreover, when used to screen samples, it can significantly reduce cost and time.