Abstract
Background
Whether higher grade cervical intraepithelial neoplasia (CIN 2+) that develop due to human papillomavirus (HPV) genotypes not included in vaccines may progress to cervical cancer (CC) is largely unknown. The purpose of the study was to document p16INK4A as a biomarker of cervical carcinogenesis or malignant potential and evaluate whether its expression differs between lesions associated with vaccine and non-vaccine HR-HPV genotypes.
Methods
Study population consisted of 371 women who had not received HPV vaccines. Women were categorized into vaccine and non-vaccine HR-HPV genotypes and lesions associated with those types. Logistic regression analyses were used to determine the association between expression of p16INK4A positivity and risk of being diagnosed with CIN 2 or 3. Differences in the proportion of CIN 2+ lesions positive for the expression of p16INK4A by vaccine or non-vaccine related HR-HPV genotypes were determined using Pearson chi-square test.
Results
Results demonstrated that specimens positive for the expression of p16INK4A were 5.3 and 16.6 times more likely to be diagnosed with CIN 2 and CIN 3 lesions, respectively, compared to CIN 1 lesions. CIN 2+ lesions tested negative for bivalent and 9-valent HR-HPV genotypes had similar rate of p16INK4A positivity compared to lesions that were positive for those HR-HPV genotypes.
Conclusions
Lesions that may develop due to HR-HPV genotypes not included in HPV vaccines are likely to have similar malignant potential, suggesting that well developed screening programs combined with non-vaccine based approaches may be needed to manage the residual risk of developing CC in the post-vaccination era.
Keywords: cervix, p16, HPV, vaccine, CIN
Graphical Abstract
Precis: The purpose of the study was to determine whether cervical precancerous lesions that may develop due to HR-HPV genotypes not included in HPV vaccines are likely to have similar malignant potential using p16INK4A as a biomarker. Our results demonstrated that such higher grade precancerous lesions have similar malignant potential compared to similar lesions preventable by HPV vaccines.
Introduction
Infection with high-risk human papillomaviruses (HR-HPVs) is the main causative factor for developing cervical intraepithelial neoplasia (CIN), precursor lesions for cervical cancer (CC). CC is one of the greatest killers of women worldwide and it is the third most common genital tract malignancy in the US. The American Cancer Society estimates that approximately 12,990 new cases will be diagnosed and 4,120 women will die in 2016.1 In the United States (US), ~25 million women are infected with HPVs, and every year there is an estimated 5.5 million new cases of HPVs.2 Approximately, 400,000 women in the US are diagnosed with CIN annually, with annual costs of ~$2.3 billion for screening and $700 million for CIN treatment.3,4 It is important to prevent the development of CIN since the diagnosis and treatment of such lesions may lead to anxiety concerning cancer risk and sexual functioning as well as untoward reproductive and obstetrical complications.3,4,5,6
First generation of prophylactic vaccines against HPV 16 and 18 hold promise for preventing CIN 2+ lesions or CC associated with those HPV genotypes.7,8 However, the fact that a substantial proportion of CIN 2+ lesions are caused by HR-HPV types other than HPV 16 or 18 has begun to be appreciated.9 The inclusion of additional HR-HPV genotypes in the 9-valent HPV vaccine (31, 33, 45, 52, and 58) is expected to have better CIN preventive effects, but even this vaccine leaves out six HR-HPVs (35, 39, 51, 56, 59, 68). Even though these non-vaccine HPV genotypes are associated with CC risk10, precancerous lesions positive for the same genotypes may not necessarily transform to cancerous lesions. Therefore, it is important to evaluate the malignant potential of such precancerous lesions. No previous studies have reported the prevalence or the malignant potential of such lesions.
p16INK4A, a cyclin dependent kinase inhibitor is strongly over expressed in cervical-cancer cell lines in which RB has been functionally inactivated by the high-risk HPV E7 oncoproteins, but absent in normal cervical epithelia or lesions induced by low risk HPV types.11,12 Therefore, the overexpression of p16INK4A is considered as a marker, not only of HPV infections, but also of activated expression of viral oncogenes and of virus-induced deregulation of the cell cycle.13,14 A large majority of studies on p16INK4A immunostaining has focused on the correlation between the biomarker and the degree of cytological or histological abnormalities. Only a few studies have addressed its role as a biomarker of disease progression. A meta-analysis that included 61 studies documented that the proportion of cervical smears overexpressing p16INK4A increased with the severity of cytological or histological abnormalities, suggesting its involvement in the progression of CIN lesions.15 However, to our knowledge, no previous studies have evaluated the association between the expression of p16INK4A and the likelihood of being diagnosed with higher grades of CIN after controlling for important confounding variables or its expression in relation to CIN lesions associated with HR-HPV genotypes included or not included in currently available HPV vaccines.
Based on this background the purpose of this study was 1) to determine the association between expression of p16INK4A and risk of being diagnosed with higher grades of CIN (CIN 2+) after controlling for relevant risk factors of CC and 2) to determine whether the expression of p16INK4A differs in CIN 2+ lesions positive for HR-HPV genotypes included in the bivalent and quadrivalent vaccines (HPV 16 and18) and 9-valent vaccine (HPVs 16, 18, 31, 33, 45, 52 and 58) compared to CIN 2+ lesions that are a) negative for HPV 16 and 18 but positive for any other HR-HPV; b) negative for HPV 16, 18, 31, 33, 45, 52 and 58, but positive for any other HR-HPV.
Methods
Study population
The study population (N=371) included women enrolled by two studies funded by the National Cancer Institute (NCI) (R01CA105448 and R01CA102489) who had not received HPV vaccines. All women were diagnosed with abnormal cervical cells in clinics of the Health Departments in Jefferson County and surrounding counties in Alabama and were referred to the University of Alabama at Birmingham (UAB) for further examination by colposcopy and biopsy. Women were 19-50 years old, had no history of CC or other cancer of the lower genital tract, no history of hysterectomy or destructive therapy of the cervix; were not pregnant, and were not using anti-folate medications such as methotrexate, sulfasalazine, or phenytoin. All women included in this study were HR-HPV positive (any one of 13 types of HR-HPV, HPV 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, and 68). The distribution of CIN diagnosis of the population is the following: 296 women were diagnosed with CIN 2+ (cases, including CIN 2 [n=189], CIN 3 [n=107] and 75 women were diagnosed with CIN 1. All women included in this analysis participated in an interview that assessed socio-demographic variables and lifestyle risk factors. Height, weight and waist circumference (WC) measurements were obtained using standard protocols. The BMI was calculated using the height and weight measurements (weight kg/[height m]2). Pelvic examinations and collection of cervical cells and biopsies were carried out following the protocols of the colposcopy clinic. The study protocol and procedures were approved by the UAB Institutional Review Board.
Detection and determination of HPV genotypes
DNA was extracted from cervical cells using the QIAamp MiniElute Media kit (Qiagen, Inc.) following the manufacturer's instructions. HPV genotyping test (Linear array; Roche Diagnostics) was performed according to the manufacturer's instructions by a research associate trained by personnel from Roche Diagnostics. Briefly, target DNA was amplified by PCR using the PGMY09/11 L1 consensus primer system that included co-amplification of a human cellular target, β-globin that served as an internal control for adequate sample cellularity and extraction.
Detection and HPV genotyping were achieved using a reverse line-blot method, and this test included probes for 37 anogenital HPV genotypes [6, 11, 16, 18, 26, 31, 33, 35, 39, 40, 42, 45, 51, 52, 53, 54, 55, 56, 58, 59, 61, 62, 64, 66, 67, 68, 69, 70, 71, 72, 73 (MM9), 81, 82 (MM4), 83 (MM7), 84 (MM8), IS39, and CP6108]. HPV 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, and 68 were considered as HR-HPV genotypes and all other types as low risk HPV genotypes in this analysis.
Immunostaining for p16INK4A
The expression of p16INK4A in paraffin embedded, formalin fixed cervical biopsy specimens were determined using the Cintec p16INK4A (E6H4) Histology kit (Ventana Medical System, Inc), according to manufacturer instructions using an automated Ventana BenchMark ULTRA. Immunostaining results were evaluated as positive when groups of cells stained together, both cytoplasmic/nuclear as recommended by the Lower Anogential Squamous Terminology (LAST) for histopathological reporting of HPV associated squamous lesions of the lower genital tract.16 Positivity was assigned by the so-called “block positivity” defined as continuous staining, starting at the basal layer and extending upward at least 1/3 of the epithelial thickness.
Data Analysis
Differences in the demographic and lifestyle factors between CIN 2 and CIN 1 and between CIN 3 and CIN 1 were assessed by Wilcoxon rank-sum tests for continuous variables and χ2 tests for categorical variables. We determined whether the proportion of lesions positive for p16INK4A differs by the severity of the CIN lesions. Unconditional logistic regression models were used to determine the association between the expression of p16INK4A and risk of being diagnosed with CIN 2 and CIN 3 after adjusting for age, race, education, BMI, smoking status, parity, age at first intercourse and the use of hormonal contraceptives. We determined the distribution of CIN status based on the vaccine and non-vaccine-related HPV genotypes. The differences in the demographic and lifestyle factors of women diagnosed with CIN 2+ lesions associated with vaccine and non-vaccine HR-HPV genotypes were assessed by Wilcoxon rank-sum tests for continuous variables and χ2 tests for categorical variables. We determined whether the percentage of CIN lesions positive for the expression of p16INK4A differed by vaccine and non-vaccine related HR-HPV genotypes i.e. positive for HPV 16 or 18 vs negative for HPV 16 or 18 but positive any other HR-HPV, for 9-valent vaccine related HR-HPV genotypes vs negative for 9-valent HR-HPV genotypes but positive any other HR-HPV. We also performed this analysis stratified by variables that were significantly different in the univariate analysis.
Results
The study population consisted of 80% of women diagnosed with CIN 2+ (51% CIN 2 and 29% CIN 3) and 20% of women diagnosed with CIN 1. Differences in the demographic and lifestyle factors by CIN status are shown in Table 1. We observed that the median age of women diagnosed with CIN 2 or CIN 3 was lower compared to the median age of women diagnosed with CIN 1 (P<0.0001) and a higher percentage of women diagnosed with CIN 2 or CIN 3 had BMI < 25 kg/m2 compared to women diagnosed with CIN 1 (P=0.0012, P=0.0374, respectively). We also observed that a higher proportion of women diagnosed with CIN 2 had higher parity compared to women diagnosed with CIN 1 (P=0.0486) and a higher proportion of women diagnosed with CIN 3 were CA compared to women diagnosed with CIN 1 (P=0.0312). None of the other variables were significantly different by CIN status. As shown in Figure 1, we observed a stepwise increase in the percentage of p16INK4A positivity by the severity of the lesions and the differences in the percentage of p16INK4A positivity between the CIN 1, CIN 2 and CIN 3 were statistically significant. In the unconditional logistic regression models, we observed that women who were positive for the expression of p16INK4A were 5.3 times and 16.6 times more likely to be diagnosed with CIN 2 and CIN 3 lesions, respectively, compared to women diagnosed with CIN 1 lesions independent of all other relevant risk factors of CC, namely, age, race, education, BMI, smoking status, age at first intercourse, parity and use of hormonal contraceptives (OR=5.3, 95%CI=2.6-10.9, P<0.0001 and OR=16.6, 95%CI=6.2-52.4, P<0.0001, respectively) (Figure 2). We observed that age and BMI were associated with case status. With every unit increase in age there was 20% and 10% lower likelihood of being diagnosed with CIN 2+ and CIN 3, respectively (OR=0.8, 95%CI=0.7-0.9, P<0.0001; OR=0.9, 95%CI=0.8-0.9, P=0.0003 respectively). We also observed that women with BMI ≥ 25 kg/m2 were less likely to be diagnosed with either CIN 2 or CIN 3 (OR=0.4, 95%CI=0.2-0.8, P=0.0127; OR=0.3, 95%CI=0.1-0.8, P=0.0113, respectively). None of the other variables were significantly associated with either CIN 2 or CIN 3.
Table 1.
Demographic and lifestyle factors of the study population by CIN status
| Risk factors | CIN 1 N=75 |
CIN 2 N=189 |
CIN 3 N=107 |
P-valuea | P-valueb |
|---|---|---|---|---|---|
| Age (years) | 28 | 24 | 25 | <0.0001 | <0.0001 |
| Race: Caucasian American | 32 (43%) | 75 (40%) | 63 (59%) | 0.6560 | 0.0312 |
| African American | 43 (57%) | 114 (60%) | 44 (41%) | ||
| Education: High school education or higher | 64 (85%) | 34 (18%) | 82 (77%) | 0.5173 | 0.1471 |
| Less than high school education | 11 (15%) | 155 (82%) | 25 (23%) | ||
| BMI: < 25 kg/m2 | 19 (25%) | 100 (53%) | 43 (40%) | 0.0012 | 0.0374 |
| ≥ 25 kg/m2 | 56 (75%) | 89 (47%) | 64 (60%) | ||
| Smoking status: Never | 42 (57%) | 100 (53%) | 66 (62%) | 0.6021 | 0.5066 |
| Ever | 32 (43%) | 88 (47%) | 41 (38%) | ||
| Parity: 0 live births | 13 (17%) | 55 (29%) | 21 (20%) | 0.0486 | 0.6961 |
| ≥ 1 live births | 62 (83%) | 134 (71%) | 86 (80%) | ||
| Median age at first intercourse: > 16 | 39 (56%) | 108 (61%) | 64 (62%) | 0.4149 | 0.3983 |
| ≤ 16 | 31 (44%) | 68 (39%) | 39 (38%) | ||
| Use of hormonal contraceptives : No | 14 (19%) | 32 (17%) | 15 (14%) | 0.7374 | 0.3991 |
| Yes | 61 (81%) | 157 (83%) | 92 (86%) |
P-value for the difference in proportion between CIN 1 and CIN 2
P-value for the difference in proportion between CIN 1 and CIN 3
Figure 1.
Expression of p16 INK4A by the severity of CIN lesions
Figure 2.
The association between the expression of p16 INK4A and CIN status*
To determine if differences exists in the proportion of CIN 2+ lesions positive for p16INK4A expression by vaccine and non-vaccine related HR-HPV genotypes, we first categorized our study population in to vaccine and non-vaccine related HR-HPV groups and calculated the distribution of CIN lesions in these groups for the entire population and by race (Table 2). We observed that a higher percentage of women positive for HPV 16 or 18 only were diagnosed with CIN 3 lesions while a higher percentage of women negative for HPV 16 or 18 but positive for other HR-HPV were diagnosed with CIN 2 lesions (P=0.0001). A higher percentage of women positive for 9-valent vaccine HR-HPV genotypes only were diagnosed with CIN 3 compared to women negative for 9 valent vaccine HPV genotypes but positive for other HR-HPVs (P=0.0160). When stratified by race, we observed a similar trend, a higher percentage of AA women and CA women positive for HPV 16 or 18 were diagnosed with CIN 3 lesions while a higher percentage of AA women and CA women negative for HPV 16 or 18 but positive for other HR-HPV were diagnosed with CIN 2 lesions (P=0.0001 and 0.0031, respectively). Further, a higher percentage of AA women and CA women positive only for 9-valent vaccine HR-HPV genotypes were diagnosed with CIN 3 compared to women negative for 9 valent vaccine HPV genotypes but positive for other HR-HPVs was observed but the difference was not statistically significant (P=0.0986 and P=0.0915, respectively).
Table 2.
CIN status by HPV genotype groups
| HPV groups | CIN 1 | CIN 2 | CIN 3 | P-value |
|---|---|---|---|---|
| Entire population | ||||
| Positive for HPV 16 or 18 only (n=79) | 14 (18%) | 23 (29%) | 42 (53%) | 0.0001 |
| Negative for HPV 16 and 18 but positive for other HR-HPV types (n=202) | 52 (26%) | 115 (57%) | 35 (17%) | |
| Positive for 9-valent HR-HPV vaccine genotypes only (n=202) | 43 (21%) | 88 (44%) | 71 (35%) | 0.0160 |
| Negative for 9-valent HR-HPV vaccine genotypes but positive for other HR-HPV genotypes (n=71) | 19 (27%) | 40 (56%) | 12 (17%) | |
| African American | ||||
| Positive for HPV 16 or 18 only (n=31) | 5 (16%) | 11 (35%) | 15 (48%) | <0.0001 |
| Negative for HPV 16 and 18 but positive for other HR-HPV types (n=135) | 34 (25%) | 83 (61%) | 18 (13%) | |
| Positive for 9-valent HR-HPV genotypes only (n=112) | 88 (21%) | 59 (53%) | 29 (26%) | 0.0986 |
| Negative for 9-valent HR-HPV vaccine types but positive for other HR-HPV genotypes (n=40) | 12 (30%) | 24 (60%) | 4 (10%) | |
| Caucasian American | ||||
| Positive for HPV 16 or 18 only (n=48) | 9 (19%) | 12 (25%) | 27 (56%) | 0.0031 |
| Negative for HPV 16 and 18 18 but positive for other HR-HPV types (n=67) | 18 (27%) | 32 (48%) | 17 (25%) | |
| Positive for 9-valent HR-HPV vaccine genotypes only (n=90) | 19 (21%) | 29 (32%) | 42 (47%) | 0.0915 |
| Negative for 9-valent HR-HPV vaccine genotypes but positive for other HR-HPV genotypes (n=31) | 7 (23%) | 16 (52%) | 8 (26%) |
The differences in demographic and life-style factors between women diagnosed with CIN 2+ lesions associated with vaccine and non-vaccine HPV genotypes are shown in Table 3. We observed that HPV 16 or 18 positive CIN 2+ lesions were more common among CAs while HPV 16 or 18 negative CIN 2+ lesions were more common among AAs (P= 0.0002). We did not observe a racial difference for 9-valent HPV vaccine genotype positive CIN 2+ lesions and 9-valent HR-HPV vaccine genotype negative CIN 2+ lesions. The proportions of CIN 2+ lesions associated with vaccine or non-vaccine HPV genotypes did not differ by other variables.
Table 3.
Demographic and life-style factors of women diagnosed with CIN 2+ lesions associated with vaccine and non-vaccine HR-HPV genotypes
| Risk factors | Positive for HPV 16 or 18 N=65 |
Negative for HPV 16 or 18 N=150 |
P-value | Positive for 9-valent N=159 |
Negative for 9-valent HPV types N=52 |
P-value |
|---|---|---|---|---|---|---|
| Age (years) | 24 | 25 | 0.3211 | 25 | 25 | 0.9687 |
| Race: Caucasian American | 39 (60%) | 49 (33%) | 0.0002 | 71 (45%) | 24 (46%) | 0.8503 |
| African American | 26 (40%) | 101 (67%) | 88 (55%) | 28 (54%) | ||
| Education: High school education or higher | 55 (85%) | 124 (83%) | 0.7252 | 130 (82%) | 45 (87%) | 0.4266 |
| Less than high school education | 10 (15%) | 26 (17%) | 29 (18%) | 7 (13%) | ||
| BMI: < 25 kg/m2 | 23 (35%) | 69 (46%) | 0.1485 | 67 (42%) | 19 (37%) | 0.4756 |
| ≥ 25 kg/m2 | 42 (65%) | 81 (54%) | 92 (58%) | 33 (63%) | ||
| Smoking status: Never | 27 (42%) | 70 (47%) | 0.4877 | 87 (55%) | 27 (52%) | 0.6934 |
| Ever | 38 (58%) | 80 (53%) | 71 (45%) | 25 (48%) | ||
| Parity: 0 live births | 14 (22%) | 39 (26%) | 0.8193 | 38 (24%) | 14 (27%) | 0.6605 |
| ≥ 1 live births | 51 (78%) | 111 (74%) | 121 (76%) | 38 (73%) | ||
| Median age at first intercourse: > 16 | 41 (66%) | 91 (65%) | 0.8268 | 90 (59%) | 33 (70%) | 0.1748 |
| ≤ 16 | 21 (34%) | 50 (35%) | 62 (41%) | 14 (30%) | ||
| Use of hormonal contraceptives : No | 11(17%) | 26 (17%) | 0.9417 | 24 (15%) | 12 (23%) | 0.1841 |
| Yes | 54 (83%) | 124 (83%) | 135 (85%) | 40 (77%) |
Table 4 shows the proportion of CIN 2+ lesions positive for p16 INK4A expression by HPV vaccine related genotypes. As shown in Figure 3, we observed that CIN 2+ lesions tested negative for bivalent and 9-valent HR-HPV genotypes have similar rate of p16INK4A positivity compared to lesions that are positive for bivalent or 9-valent HR-HPV genotypes and these observations remained similar after stratifying by race.
Table 4.
The proportion of CIN 2+ lesions positive for p16 INK4A expression by HPV vaccine related genotypes
| HPV groups | Positive for p16INK4A N (%) |
Negative for p16INK4A N (%) |
P-value |
|---|---|---|---|
| Entire Population | |||
| Positive for HPV 16 or 18 only (n=65) | 57 (88%) | 8 (12%) | 0.7387 |
| Negative for HPV 16 and 18 but positive for other HR-HPV types (n=150) | 129 (86%) | 21 (14%) | |
| Positive for 9-valent vaccine HR-HPV genotypes only (n=159) | 138 (87%) | 21 (13%) | 0.6953 |
| Negative for 9-valent HR-HPV vaccine genotypestypes but positive for other HR-HPV types (n=51) | 44 (86%) | 7 (14%) | |
| African American | |||
| Positive for HPV 16 or 18 only (n=26) | 22 (85%) | 4 (15%) | 0.8426 |
| Negative for HPV 16 and 18 but positive for other HR-HPV types (n=101) | 87 (86%) | 14 (14%) | |
| Positive for 9-valent vaccine HR-HPV genotypes only (n=159) | 76 (86%) | 12 (14%) | 0.9308 |
| Negative for 9-valent HR-HPV vaccine genotypes but positive for other HR-HPV genotypes (n=51) | 24 (86%) | 4 (14%) | |
| Caucasian American | |||
| Positive for HPV 16 or 18 genotypes only (n=39) | 35 (90%) | 4 (10%) | 0.5702 |
| Negative for HPV 16 and 18 but positive for other HR-HPV types (n=49) | 42 (86%) | 7 (14%) | |
| Positive for 9-valent vaccine HR-HPV genotypes only (n=159) | 62 (87%) | 9 (13%) | 0.6229 |
| Negative for 9-valent HR-HPV vaccine genotypes but positive for other HR-HPV genotypes (n=51) | 20 (83%) | 4 (17%) |
Figure 3.
Expression of p16 INK4A in a CIN 3 lesion of A) Positive for HPV 16 or 18 B) Negative for HPV 16 and 18 C) Positive for HPV 16, 18, 31, 33, 45, 52 or 58 D) Negative for HPV 16, 18, 31, 33, 45, 52 and 58
Discussion
Among >100 HPV genotypes, 40 types are sexually transmitted and 13 of these 40 genotypes are oncogenic and also referred to as HR-HPVs (HPV 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, and 68).17 Even though it has been generally accepted for many decades that HPV 16 and 18 have the most carcinogenic potential, recent studies are beginning to report that the nominal transition probabilities observed for CIN 2 and CIN 3 were comparable to or greater with HPV types such as HPV 33 and 35 compared to HPV 16.18 A study that evaluated HPV types in carcinoma in situ/adenocarcinoma similarly found a relative risk for HPV 16 analogous to that for HPV 33.19 Further, contrary to the common belief that HPV 16 and 18 produce higher concentrations of mRNA of E6/E7 oncoproteins, a recent study demonstrated that other HR-HPV genotypes, such as HPV 45, may produce higher concentrations of E6/E7 mRNA than HPV16/18.20 These observations are important since the oncogenic potential of HR-HPVs is due to the expression of E6 and E7 oncoproteins21 via binding to tumor suppressor genes such as retinoblastoma (RB) which leads to loss of cell cycle control and accumulation of DNA damage 21,22, and also via their effects on expression of telomerase reverse transcriptase (TERT), telomerase activity, and telomere length, subsequently leading to cellular immortalization and malignant transformation.23,24 Even though these findings strongly suggest that women infected with other HR-HPVs, even in the absence of HPV 16/18, may produce similar concentrations of E6/E7 mRNA, which may in turn result in the development of lesions with similar malignant potential, no studies have tested molecular differences between these lesion types.
Categorization of HPVs as high- and low-risk is based on their association with invasive CC and this association is based, in part, on the relative affinity that the HPV-genotype specific oncoproteins E6 and E7 bind to cellular regulatory proteins, specifically, tumor suppressor proteins of p53 and RB. Degradation of p53 or functional inactivation of Rb, leads to disruption of the cell cycle and increased proliferation, thought to ultimately give rise to CC.25 Since the inactivation of Rb by E7 leads to markedly increased levels of p16INK4A, its degree of expression could be reflective of the malignant potential of CIN lesions caused by specific HPV genotypes.
Our observation that older women were less likely to be diagnosed with CIN 2+ lesions has been noted by previous studies.26 The reason for the inverse association between BMI and risk of CIN 2+ is unclear, but could be due to the fact that older women in our study population had higher BMI compared to younger women. As expected, we observed that the proportion of p16INK4A positivity increased with the severity of any HR-HPV associated CIN lesions. In addition, we document that p16INK4A positive lesions had 5.3 and 16.6 times higher odds of being CIN 2 and CIN 3, respectively. These observations were indicative of the involvement of this marker in the process of cervical carcinogenesis or the malignant potential of CIN lesions.
In the post HPV vaccine era, it is important to know the proportion of CIN lesions caused by HPV genotypes included or not included in the vaccines and whether these lesions have similar malignant potential. Studies from United States and other countries have demonstrated reductions in CIN 2+ lesions attributable to HR-HPV genotypes targeted by the bivalent and quadrivalent vaccines.27,28,29 Studies have also estimated that if 9-valent HR-HPV vaccination programs are effectively implemented, the majority of CIN 2 and CIN 3 lesions could be prevented.30 In our study, we observed that 56-57% CIN 2 and 17% CIN 3 were detected among women tested negative for HPV 16 and18 or 9-valent HR-HPV genotypes. Even with 100% efficacy of these vaccines, these lesions, especially, CIN 3 lesions of CA women, will remain as a concern for health professionals as well as for women diagnosed with such lesions, especially if those lesions have the potential to progress to CC. Our observation that CIN 2+ lesions of women tested negative for bivalent and 9-valent HR-HPV genotypes have similar rate of p16INK4A positivity compared to lesions associated with HR-HPV genotypes included in vaccines suggests that lesions that may develop after HPV vaccination are likely to have similar malignant potential and well developed screening programs combined with non-vaccine based approaches such as nutrient and probiotic therapy may be needed to manage the residual risk of developing CC in the post-vaccination era. Our previous studies have shown that specific micronutrients such as folate and vitamin B12 and overall healthy dietary patterns play a significant role in altering the natural history of any HR-HPV and are protective against any HR-HPV related CIN 2+ and specific cervical microbial profiles are associated with risk of CIN 2+, suggesting the usefulness of such combined approaches to reduce the overall risk of CC.31,32,33,34,35
In conclusion, newly approved vaccines against the most common types of HPV genotypes that cause CC may represent a significant advancement in the prevention of this disease. However, it is imperative that follow-up screening and non-vaccine based primary preventive strategies be adapted to and meshed with one another in order to manage lesions that develop due to HR-HPV genotypes that are not included in HPV vaccines.
Acknowledgments
Supported by P30CA013148 (UAB Comprehensive Cancer Center), R01 CA102489, R01 CA105448 and R21 CA188066 (C. Piyathilake) funded by the National Cancer Institute
Footnotes
Conflict of interest: None
Author's contribution:
Formulation of research goals and aims-CJP
Generation of data and verification-IAE, MMC, CJP, SB
Data analysis and interpretation-CJP, SB
Writing original draft and presentation of results-CJP, SB
Review and editing of the final manuscript-CJP, SB, IAE, WH, MMC
REFERENCES
- 1. [June 16 2016]; http://www.cancer.org/cancer/cervicalcancer/detailedguide/cervical-cancer-key-statistics.
- 2.Dunne EF, Unger ER, Sternberg M, et al. Prevalence of HPV infection among females in the United States. JAMA. 2007;297:813–819. doi: 10.1001/jama.297.8.813. [DOI] [PubMed] [Google Scholar]
- 3.Henk HJ, Insinga RP, Singhal PK, et al. Incidence and costs of cervical intraepithelial neoplasia in a US commercially insured population. J Low Genit Tract Dis. 2010;14:29–36. doi: 10.1097/LGT.0b013e3181ac05e9. [DOI] [PubMed] [Google Scholar]
- 4.Insinga RP, Dasbach EJ, Elbasha EH. Assessing the annual economic burden of preventing and treating anogenital human papillomavirus-related disease in the US: analytic framework and review of the literature. Pharmacoeconomics. 2005;23:1107–1122. doi: 10.2165/00019053-200523110-00004. [DOI] [PubMed] [Google Scholar]
- 5.Ferreira SE. Cervical intraepithelial neoplasia diagnosis: emotional impact and nursing implications. Clin Excell Nurse Pract. 1998;2:218–224. [PubMed] [Google Scholar]
- 6.McDonald TW, Neutens JJ, Fischer LM, et al. Impact of cervical intraepithelial neoplasia diagnosis and treatment on self-esteem and body image. Gynecol Oncol. 1989;34:345–349. doi: 10.1016/0090-8258(89)90170-4. [DOI] [PubMed] [Google Scholar]
- 7.Rana MM, Huhtala H, Apter D, et al. Understanding long-term protection of human papillomavirus vaccination against cervical carcinoma: Cancer registry-based follow-up. Int J Cancer. 2013;132:2833–2838. doi: 10.1002/ijc.27971. [DOI] [PubMed] [Google Scholar]
- 8.Coutlée F, Ratnam S, Ramanakumar AV, et al. Distribution of human papillomavirus genotypes in cervical intraepithelial neoplasia and invasive cervical cancer in Canada. J Med Virol. 2011;83:1034–1041. doi: 10.1002/jmv.22081. [DOI] [PubMed] [Google Scholar]
- 9.Niccolai LM, Russ C, Julian PJ, et al. Individual and geographic disparities in human papillomavirus types 16/18 in high-grade cervical lesions: Associations with race, ethnicity, and poverty. Cancer. 2013;119:3052–3058. doi: 10.1002/cncr.28038. [DOI] [PubMed] [Google Scholar]
- 10.Muñoz N, Bosch FX, de Sanjosé S, et al. Epidemiologic classification of human papillomavirus types associated with cervical cancer. N Engl J Med. 2003;348:518–27. doi: 10.1056/NEJMoa021641. [DOI] [PubMed] [Google Scholar]
- 11.Khleif SN, DeGregori J, Yee CL, et al. Inibition of cyclin D-CDK4/CDK6 activity is associated with E2F-mediated induction of cyclin kinase inibitor activity. Proc Natl Acad Sci USA. 1996;93:4350–54. doi: 10.1073/pnas.93.9.4350. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Nakao Y, Yang X, Yokoyama M, et al. Induction of p16 during immortalization by HPV 16 and 18 and not during malignant transformation. Br J Cancer. 1997;75:1410–16. doi: 10.1038/bjc.1997.243. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.von Knebel Doeberitz M. New molecular tools for efficient screening of cervical cancer. Dis Markers. 2001;17:123–28. doi: 10.1155/2001/249506. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.von Knebel Doeberitz M. New markers for cervical dysplasia to visualise genomic chaos created by aberrant oncogenic papillomavirus infection. Eur J Cancer. 2002;38:2229–2242. doi: 10.1016/s0959-8049(02)00462-8. [DOI] [PubMed] [Google Scholar]
- 15.Tsoumpou I, Arbyn M, Kyrgiou M, et al. p16INK4a immunostaining in cytological and histological specimens from theuterine cervix: A systematic review and meta-analysis. Cancer treatment reviews. 2009;35:210–220. doi: 10.1016/j.ctrv.2008.10.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Nayar R. At LAST: Consensus Recommendations for Histopathology Reporting of HPV-Associated Squamous Lesions of the Lower Anogenital Tract. The ASC Bulletin. 2013;L:26–29. [Google Scholar]
- 17. http://cancer.gov/cancertopics/factsheet/cancer-advances-in-focus/cervical.
- 18.Insinga RP, Perez G, Wheeler CM, et al. FUTURE I Investigators. Incident cervical HPV infections in young women: transition probabilities for CIN and infection clearance. Cancer Epidemiol Biomarkers Prev. 2011;20:287–296. doi: 10.1158/1055-9965.EPI-10-0791. [DOI] [PubMed] [Google Scholar]
- 19.Wheeler CM, Hunt WC, Joste NE, et al. Human papillomavirus genotype distributions: implications for vaccination and cancer screening in the United States. J Natl Cancer Inst. 2009;101:475–87. doi: 10.1093/jnci/djn510. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Andersson E, Kärrberg C, Rådberg T, et al. Type-dependent E6/E7 mRNA expression of single and multiple high-risk human papillomavirus infections in cervical neoplasia. J Clin Virol. 2012;54:61–65. doi: 10.1016/j.jcv.2012.01.012. [DOI] [PubMed] [Google Scholar]
- 21.Münger K, Howley PM. Human papillomavirus immortalization and transformation functions. Virus Res. 2002;89:213–228. doi: 10.1016/s0168-1702(02)00190-9. [DOI] [PubMed] [Google Scholar]
- 22.Furumoto H, Irahara M. Human papilloma virus (HPV) and cervical cancer. J Med Invest. 2002;49:124–133. [PubMed] [Google Scholar]
- 23.Veldman T, Horikawa I, Barrett JC, et al. Transcriptional activation of the telomerase hTERT gene by human papillomavirus type 16 E6 oncoprotein. J Virol. 2001;75:4467–4472. doi: 10.1128/JVI.75.9.4467-4472.2001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Zhang Y, Sturgis EM, Dahlstrom KR, et al. Telomere Length in Peripheral Blood Lymphocytes Contributes to the Development of HPV-Associated Oropharyngeal Carcinoma. Cancer Res. 2013;73:5996–6003. doi: 10.1158/0008-5472.CAN-13-0881. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Alani RM, Munger K. Human papillomaviruses and associated malignancies. J Clin Oncol. 1998;16:330–337. doi: 10.1200/JCO.1998.16.1.330. [DOI] [PubMed] [Google Scholar]
- 26.Ting J, Kruzikas DT, Smith JS. A global review of age-specific and overall prevalence of cervical lesions. Int J Gynecol Cancer. 2010;20:1244–1249. doi: 10.1111/igc.0b013e3181f16c5f. [DOI] [PubMed] [Google Scholar]
- 27.Hariri S, Bennett NM, Niccolai LM, et al. Reduction in HPV 16/18-associated high grade cervical lesions following HPV vaccine introduction in the United States - 2008-2012. Vaccine. 2015;33:1608–1613. doi: 10.1016/j.vaccine.2015.01.084. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Ogilvie GS, Naus M, Money DM, et al. Reduction in cervical intraepithelial neoplasia in young women in British Columbia after introduction of the HPV vaccine: An ecological analysis. Int J Cancer. 2015;137:1931–1937. doi: 10.1002/ijc.29508. [DOI] [PubMed] [Google Scholar]
- 29.Baldur-Felskov B, Dehlendorff C, Junge J, et al. Incidence of cervical lesions in Danish women before and after implementation of a national HPV vaccination program. Cancer Causes Control. 2014;25:915–922. doi: 10.1007/s10552-014-0392-4. [DOI] [PubMed] [Google Scholar]
- 30.Joura EA, Ault KA, Bosch FX, et al. Attribution of 12 high-risk human papillomavirus genotypes to infection and cervical disease. Cancer Epidemiol Biomarkers Prev. 2014;23:1997–2008. doi: 10.1158/1055-9965.EPI-14-0410. [DOI] [PubMed] [Google Scholar]
- 31.Piyathilake CJ, Henao OL, Macaluso M, et al. Folate is associated with the natural history of high-risk human papillomaviruses. Cancer Res. 2004;64:8788–8793. doi: 10.1158/0008-5472.CAN-04-2402. [DOI] [PubMed] [Google Scholar]
- 32.Piyathilake CJ, Macaluso M, Alvarez RD, et al. Lower risk of cervical intraepithelial neoplasia in women with high plasma folate and sufficient vitamin B12 in the post-folic acid fortification era. Cancer Prev Res (Phila) 2009;2:658–664. doi: 10.1158/1940-6207.CAPR-08-0175. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Piyathilake CJ, Badiga S, Paul P, et al. Indian women with higher serum concentrations of folate and vitamin B12 are significantly less likely to be infected with carcinogenic or high-risk (HR) types of human papillomaviruses (HPVs). Int J Womens Health. 2010;2:7–12. doi: 10.2147/ijwh.s6522. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Piyathilake CJ, Badiga S, Kabagambe EK, et al. A dietary pattern associated with LINE-1 methylation alters the risk of developing cervical intraepithelial neoplasia. Cancer Prev Res (Phila) 2012;5:385–392. doi: 10.1158/1940-6207.CAPR-11-0387. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Piyathilake CJ, Ollberding NJ, Kumar R, et al. Cervical Microbiota Associated with Risk of Higher Grade Cervical Intraepithelial Neoplasia in Women Infected with High-Risk Human Papillomaviruses. Cancer Prev Res (Phila) . 2016;9:357–366. doi: 10.1158/1940-6207.CAPR-15-0350. [DOI] [PMC free article] [PubMed] [Google Scholar]