Cervical cancer (CC) continues to be a major public health problem in Mexico, ranking second among cancers in women. A persistent infection with human papillomaviruses (HPV) is the main risk factor for CC development. In addition, a significant fraction of other cancers including those of the anus, oropharynx, and penis are also related to HPV infection. In CC, HPV-16 is the most prevalent high-risk HPV type, followed by HPV-18, both being responsible for 70% of cases. HPV intratype variant lineages differ in nucleotide sequences by 1–10%, while sublineages differ by 0.5–1%. Several studies have postulated that the nucleotide changes that occur between HPV intratype variants are reflected in functional differences and in pathogenicity. Moreover, it has been demonstrated that HPV-16 and -18 intratype variants differentially affect molecular processes in infected cells, changing their biological behavior that finally impacts in the clinical outcome of patients. Mexico has participated in providing knowledge on the geographical distribution of intratype variants of the most prevalent HPVs in premalignant lesions of the cervix and cervical cancer, as well as in other HPV-related tumors. In addition, functional studies have been carried out to assess the cellular effects of intratype variations in HPV proteins. This review addresses the state of the art on the epidemiology of HPV-16 and HPV-18 intratype variants in the Mexican population, as well as their association with persistence, precancer and cervical cancer, and functional aspects related to their biological behavior. Among the seven known human viruses associated with cancer, high-risk human papillomaviruses (HR-HPV) cause the greatest cancer burden, with more than 690,000 cancer cases attributed to HPV in 2018 . AdditioCervical cancer continues to be a public health problem, and it ranks fourth among cancers in women worldwide . In MexiHuman papillomaviruses (HPV) are small non-enveloped particles which infect skin and mucous membranes. Virus particles contain approximately 8000 bp of double-stranded DNA, covered by a viral capsid composed of L1 and L2 proteins. According to their genomic sequence similarity, more than 200 types of HPV have been described . Based oSequence diversity is also found within each HPV type, where intratype variant lineages differ by 1–10%, while sublineages differ by 0.5–1% ,17. BeinMany HPV intratype variants have been isolated in various clinical studies and a careful classification of variants of the most frequent HPV types in cancer has been achieved ,15,17. ISeveral epidemiological studies have been carried out on the geographical distribution of HPV types and intratype variants worldwide and Mexico is not the exception. In addition, functional studies have also been carried out regarding the participation of viral proteins and the transcriptional activity of the viral non-coding region with the goal of identifying differences in biological behavior towards the establishment of cancer, mainly focused on HPV-16 and -18 intratype variants.Deciphering the impact that HPV intratype variations have on cancer development, as well as on the clinical outcome of patients with HPV-related cancers, could eventually influence patient prognosis and the development of therapeutic strategies. This review addresses the state of the art on the epidemiology of HPV-16 and HPV-18 intratype variants worldwide and particularly in the Mexican population, as well as their association with persistence, precancer and cervical cancer, and functional aspects related to their biological behavior.The human papillomavirus genome consists of three functionally different regions: an early expressed region (E) that includes genes E1, E2, E4, E5, E6, and E7; a late expressed region (L) that contains the L1 and the L2 genes; and a long non-coding region (LCR) that contains elements that regulate viral replication and transcription .The HPV replicative cycle is dependent on the differentiation process of the epithelium. During the initial HPV infection, E viral genes are expressed from the undifferentiated basal epithelium where E1 and E2 products regulate viral genome replication and E2 controls the expression of E6 and E7 oncoproteins. In addition, E6 and E7 oncoproteins interact with a variety of cellular proteins that favor the replication of the viral genome. L1 and L2 proteins are produced in the most differentiated layers of the epithelium and after being assembled, virions are released by cellular desquamation in the most superficial layers.To establish a productive infection, HPV must infect the basal cells of a differentiating epithelium, where the viral genome is amplified and subsequently packaged, allowing for the generation of new viral particles. Through micro-wounds, HPVs reach and infect mitotically active basal cells that will eventually divide and enter the parabasal layer, undergoing differentiation. A specific receptor that mediates the entry of the virus into the host cell has not yet been described, although different receptors have been proposed . HPV entHPV interaction with HPSG exposes L2 on the capsid surface and mediates conformational changes in L1, allowing the kallikrein-8 (KLK8) protease to cleave L1, thereby exposing the RG-1 epitope within the N-terminus of the L2 protein . Furin pOnce inside the nucleus, HPV transcription is driven by the p97 and p105 promoters of HPV-16 and -18, respectively, allowing the expression of E6, E7, E1, and E2 genes, necessary for the early stages of viral genome amplification. E2 protein contains a DNA binding domain, and once it binds to its response elements located in the LCR, it negatively regulates the expression of the early expressed viral genes . MeanwhiImportantly, the expression of E6 and E7 is necessary for infected cells to enter mitosis, and the amplification of the HPV genome partially depends on the cell division program. Although the activity of E6 and E7 oncoproteins is crucial for the establishment of cancer, their expression is also necessary to carry out the replicative cycle of HPV.E7 is responsible for maintaining the continuity of the cell cycle, promoting the transition of the G1 to S phase, since E7 interacts with the tumor suppressor pRb and with the E3 ubiquitin ligase Cullin 2, which induces the degradation of pRb . These eGenerally, E6 and E7 proteins are produced from a bicistronic mRNA and the activities of both viral oncogenes in HPV-infected cells ensure the generation of viral progeny. In this context, it may be that when E7 induces excessive proliferation, then E6 could contribute by mitigating such effect.It has been described that E6 interacts with the tumor suppressor p53, forming a complex with E6AP (E6-associated protein), promoting the degradation of p53 through the proteasome. This event impedes p53 functions, such as induction of apoptosis and DNA damage repair [In addition, E6 and E7 regulate different signaling pathways, such as Wnt/β-catenin , PI3K/AkFurthermore, viral E5 protein maintains cell proliferation in the upper layers of the epithelium. E5 prevents endosomal acidification by binding to the 16-kDa subunit of vacuolar ATPase (vATPase), which allows the continuous membrane recycling of the EGFR receptor, producing its activation and the activation of downstream effectors. In addition, E5 promotes immune system evasion by preventing antigen presentation by the MHCI, since it indirectly interacts with the heavy chain of MHCI, preventing its correct trafficking to the membrane resulting in its accumulation in the Golgi apparatus and endoplasmic reticulum . At thisMeanwhile, the E4 protein has been shown to promote the collapse of the cytokeratin network, which makes cells fragile and more likely to release progeny virions . MoreoveFinally, viral capsid proteins are synthesized from the late promoter p670 and p811 for HPV-16 and -18, respectively, and assembled in terminally differentiated cells. The HPV genome is encapsidated in an icosahedral outer shell made up of 360 L1 molecules organized into 72 pentameric capsomeres, where L2 is localized at the center [During the infection process, reactive oxygen species, genomic instability, and DNA strand breaks are generated, which can favor the integration of the viral genome into the cellular genome. This integration process promotes the deregulated expression of E6 and E7 oncogenes, which is considered an initial step for cervical carcinogenesis. The interaction of E6 and E7 with tumor suppressors and with proteins involved in cellular signaling pathways alter normal cell function, leading to transformation ,61.Most women will be infected by HPV at least once in their lives ; howeverA minority of infections become persistent (10–20%) and are at increased risk of progression to cancer . It has Among the factors proposed to determine persistence that are inherent to the virus are viral load, viral type, and intratype variations, while those inherent to the host include genetic predisposition and lifestyle factors .Prior to the establishment of cancer, a series of clinical characteristics inherent to HPV infection occur, where the normal epithelium evolves into epithelial precursor lesions, causing cervical disease. Such lesions have been histologically classified into three groups, according to the progression of the lesion: cervical intraepithelial neoplasia (CIN) 1, 2, and 3 . Additionally, another classification based in cytological evaluation, divides the lesions into two groups known as low-grade squamous intraepithelial lesions (mild dysplasia) (LGSIL) and high-grade squamous intraepithelial lesions (moderate to severe dysplasia) (HGSIL) .CIN1 or LGSIL lesions have a low probability of progressing to cervical cancer and are caused by transient HPV infections and 90% of them revert to healthy epithelium. Conversely, CIN2 and 3 or HGSIL are caused by persistent and unproductive HPV infections, yet 60% of such lesions clear spontaneously in immunologically competent individuals . In thisAmong the first studies that described the existence of intratype variants of HPV-16, that performed in 1993 by Ho et al.  stands oHPV-18 variants were initially classified according to nucleotide changes in the L1 gene as European (E), Asian-Amerindian (AsAi), and African (Af) . SubsequAccording to the Papillomavirus Episteme (PaVE) portal , the E6 Regarding HPV-16, the greatest number of variations are detected in the B4 sublineage with 7 nucleotide substitutions in the E6 gene, impacting in 4 amino acid changes. Meanwhile for the E7 gene, sublineages B2, C1, C4, D2 and D3 present 3 mutations each. In the E7 protein, the A4, B2, C1 and C4 sublineages were affected with one amino acid change. In relation to HPV-18, the B1 sublineage is the most different in relation to the A1 reference sublineage, with 9 nucleotide changes in E6 gene and 2 amino acid substitutions; while in the E7 gene, B1, B2 and B3 sublineages exhibit 4 sequence mutations. Interestingly, the B2 sublineage contains 3 amino acid substitutions in the E7 protein, being the most different variant. The nucleotide and amino acid alignments of HPV-16 and -18 sublineages available in PaVE are described in detail in the The distribution of HPV intratype variants varies significantly in different geographical areas ,77,78,79In regard to HPV-18, several studies, although controversial, support an association of certain sublineages with infection persistence or CC risk. A Brazilian study shows that HPV-18 European variants are more likely to develop persistent infections ; in contFurthermore, it has been determined that some HPV-16 intratype variants are preferentially associated with specific histological types of cancer ,86. Howep = 0.04); while women with non-A sublineages  had a higher risk of CIN 3 and CC , which is in agreement with data that non-European variants are associated with a higher risk of developing cancer.Knowing the distribution of high-risk HPV intratype variants in different populations, particularly of HPV-16 and HPV-18, will help to identify their risk of developing cervical cancer. A study by Mirabello et al. (2016) included cervical smears from 3200 HPV-16 positive women who routinely attended a clinical center in the US . In thisOne of the studies with the largest number of samples carried out by Clifford G. et al. (2019) , and it All this information supports that even though the distribution of the different variant sublineages of HPV-16 varies widely throughout the world, non-European variants have a higher risk of developing high-grade premalignant lesions and CC.In Mexico, some studies have been performed to determine HPV intratype variant distribution. An initial work, based on E6 and L1 genes stated that nearly 40% of HPV-16 positive cervical cancer cases in Mexican women belong to Asian–American lineages D2 (AA-c) and D3 (AA-a), which also presented a higher risk of developing cervical cancer than European lineages A1/2 , with anSimilar results were found when the HPV-16 E6 gene was sequenced in 40 cases of CC and cervical premalignant lesions from women from the southeast of Mexico (Yucatan) . In thisAnother analysis carried out in 277 samples of premalignant lesions and 133 samples of CC of women who attended primary health care centers and a cancer institute in Mexico City  showed tSubsequently, Escobar Escamilla et al.  analyzedIn contrast, in a population of northeastern Mexico (state of Nuevo Leon) where cervical smears of women attending primary health care centers were analyzed, the most common HPV-16 variants found had an AA origin (87%), while European variants were present in 13% of the samples . This cop = 0.001), followed by AA-c*E7-C732/C789/G795 .Other studies analyzed the distribution of HPV-16 E6 and E7 variants from women residents from Guerrero state in southern Mexico and their association with CC and premalignant lesions ,99. AnalLittle information is available regarding the distribution of HPV-18 variants in Mexico and their association with the risk of developing CC. In a study including 33 cases of premalignant lesions and CC that were positive for HPV-18, significant data was obtained in this regard. The HPV-18 Af variant predominated in normal cytologies and premalignant lesions, while the E variant was exclusively found in CC, being present in 62% of CC cases, which suggests a higher oncogenicity for this E variant .Moreover, cervical swab analysis from a cohort of women attending primary health care centers in Monterrey, Nuevo Leon, showed that in 15 cases positive to HPV-18 the most frequent variants were European, with 13 cases, while 2 cases corresponded to the African variant; however, no information is available regarding HPV-18 variants and cancer risk in this population .It’s worth mentioning that intratype variants of HPV types 31, 35, 62, and 58 have been also characterized from cervical samples of Mexican women from different states of Mexico ,100,101.The most prevalent variants of HPV-16 and -18 found in the Mexican population are summarized in Until now, many research groups have focused on functional studies of intratype variants, mainly on the most prevalent types found in the Mexican population. These studies focus on elucidating the mechanisms by which these variants participate in cancer progression and the establishment of persistent infections. Assays that assess transcriptional and replication activity in the LCR, as well as early proteins, such as E6, E7, E1, and E2, are essential to understand the outcome of HPV-related cancers. Notably, most of the performed functional studies focus on deciphering the involvement of E6 variants in processes related to cancer, probably because among HPV oncogenes, E6 harbors more nucleotide variations compared to E7 .Epidemiological studies reveal that AA HPV-16 variants are more oncogenic than E variants, and such oncogenicity could be due to E6 and E7 activity, viral replication, or transcription enhancement. It was previously suggested that E2 may be involved in the increased oncogenicity of the AA variants through the regulation of E6/E7 transcription. The presence of intact E1/E2 in cervical tumors was shown to correlate with a higher viral copy number than those with a disruption in the E1/E2 region, where a low viral copy number was observed. Moreover, in tumors positive for HPV-16, it was shown that those containing E2 AA (170 ± 38.9) had a higher number of viral copies per cell than those positive for E2 E (67.6 ± 13.5)  Figure a. FurtheIn addition to containing E2 binding sites that regulate E6/E7 expression, the LCR also harbors an origin of replication (Ori site), important for the amplification of the viral genome. Another study revealed that variations in HPV-18 E1 and in the LCR differentially affect viral replication. The Ori site of the AsAi variant was found to exhibit a higher replication rate than the Ori site of the E and Af variants, when the E1 and the E2 of AsAi were present c. FurthePreviously, it was reported that the LCR of the HPV-18 Af variant contains the highest number of nucleotide changes compared to E and AsAi variants, especially in the tissue enhancer region, impacting low transcriptional activity, probably affecting the binding of transcription factors, including KRF-1/OCT1 and OCT-1/TEF1 e. IntereOne way to characterize the specific involvement of high-risk HPV E6 intratype variants is through bioinformatic analyses of gene expression profiles that may ultimately impact in the modulation of cellular processes and cell signaling pathways associated with carcinogenesis.Expression patterns were assessed in C-33 A cells stably transfected with HPV-16 E6 E-P, AA-a, AA-c, E-A176/G350, E-C188/G350, and E-G350. It was found that AA-c and E-G350 variants induced the most dramatic changes in transcription, affecting 229 and 132 genes, respectively. Additionally, 436 genes were differentially affected by E6 non-E-P variants in relation to E-P. When biological processes affected by gene expression patterns were analyzed, it was demonstrated that E6 non-E-P variants mainly regulated cell signaling (20.3%), transcription (16.7%), and adhesion (14.6%) a. ParticTo determine the genome wide expression modulated by E6 variants of HPV-18 found in the Mexican population, an analysis of expression patterns in HaCaT immortalized cells transiently transfected with HPV-18 E6 AsAi and Af variants was carried out. It was found that E6 Af regulates the expression of 2236 genes, while the E6 AsAi variant affected the expression of 1945 genes, and both variants regulated 414 genes in common, suggesting that the E6 HPV protein regulates cellular transcriptional programs regardless of the variant in question. As expected, both variants were able to alter genes related with cancer pathways, E6 AsAi preferentially altered elements of PI3K, Notch, and ErbB signaling, while E6 Af altered processes, such as cell migration, cell cycle, DNA replication, and mTOR signaling and Wnt signaling pathways. In cell proliferation assays, it was observed that E6 AsAi had a greater increase in proliferation than E6 Af. Conversely, migration was higher in cells harboring E6 Af than those with AsAi .Another study showed that HPV-16 E6 variants E-P, AA-c, E-G350, and E-C188/G350 differentially regulate the expression of long non-coding RNAs, including MALAT1, FLVCR1-AS1, CASC15, ZNF667-AS1, SNHG8, CASC19, and MINCR. Interestingly, it was found that MINCR was overexpressed (8-fold) in C-33 A cells harboring E6 AA-c in comparison with the control group. Through bioinformatic analysis, it was found that MINCR is a competitive endogenous RNA (ceRNA) of miR-28-5p, and that RAP1B transcript is a target of miR-28-5p. Furthermore, using data from TCGA of HPV-16 positive cervical cancer cases, it was demonstrated that RAP1B expression was higher, compared to HPV negative cases b; howeveUsing proteomic analysis, it was demonstrated that E-P, E-G350, E-A176/G350, E-C188/G350, AA-a, and AA-c HPV-16 E6 variants differentially regulate proteins mainly involved in metabolism, including KCNH1, PPP2R1A, CCT8, ALDH1A1, ZN554, ENOA, G6PD, ARMX1, GRHPR, CPT1A, CENP, and ZNF93. In addition, qPCR assays showed that E-A176/G350 and AA-a variants repressed ALDHA1 compared to C-33 A cells transfected with the empty vector, while CCT8 expression was diminished in cells containing E6 E-A176/G350, E-P, and AA-a . CurrentMCF-7 and C-33 A cells stably expressing AsAi, E, and Af variants were used to investigate the specific contribution of HPV-18 E6 variants. E6 splicing patterns were shown to be different among the tested variants. Cells expressing E6 AsAi and E6-E exhibited high levels of full-length E6 transcript with low levels of E6*I transcript. In contrast, E6 Af produced high levels of E6*I with low amounts of full-length E6 c. IntereIn agreement with these data, using MCF-7 cells stably transfected with HPV-18 E6 AsAi, E, and Af variants, differences in E6/E6*I ratio among variants were confirmed, showing that E6 Af produced a higher proportion of the E6*I transcript. Subsequently, p53 protein levels and its downstream effector p14ARF were evaluated in the presence of E6 variants. As expected, p53 protein was ablated in E6 AsAi and E expressing cells, whereas a low reduction of p53 levels was observed in cells with E6 Af. In contrast, p14ARF, a gene negatively regulated by p53, was augmented in the presence of E6 AsAi and E variants and decreased in cells with E6 Af c. Those HPV-18 E6 variants were shown to differentially regulate the activation of cell signaling pathways involved in proliferation, such as Wnt/β-catenin and PI3K/Akt. In C-33 A cells transiently transfected with the E6 AsAi variant, a 1.5-fold increase in TCF-4 transcriptional activity was observed compared to those cells transfected with the empty vector. Interestingly, the E6 Af variant induced a significant increase (2.5-fold) in TCF-4 transcriptional activity above that seen with the E6 AsAi variant d. Such aThe effect of HPV-18 E6 variations on the PI3K/Akt pathway was evaluated. Protein levels of PTEN, an inhibitor of PI3K kinase, were found to remain unchanged in MCF-7 and C-33 A cells expressing E6 AsAi, E6 E variants, or without E6. However, when phospho-PTEN was assessed, virtually no phospho-PTEN was found in cells with E6 AsAi or E6 E, while reduced phospho-PTEN levels were found in cells expressing E6 Af compared to cells with no E6 e. AdditiTo elucidate the specific participation of the intratype variants of E7 in cancer processes, one in silico study has been carried out to establish differences in the three-dimensional structure of HPV-16 E7 N29S and H51N variants in comparison with the E-prototype. Those variants have been most frequently associated with cervical cancer. The amino acid changes within variants are located in CR2 and CR3 domains for N29S and H51N, respectively. Interestingly, it was reported that the change of N29S is susceptible for phosphorylation that may reinforce nearby sites (S31 and S32) also susceptible to phosphorylation which could affect the structure of E7. Molecular dynamics (MD) analysis revealed that the N29S variant exhibits a more compact structure than the E7 E-P and H51N variants. Furthermore, 3D structure was evaluated comparing E7 variants, revealing major changes in the CR2 and CR3 domains that may affect the interaction with different cellular proteins, including pRb. Further, when analyzing the 2D structure by MD, it was demonstrated that E7 E-P lost its α-helix and β-sheets, while the H51N variant conserved the α-helix but lost the β-sheets, while most of the secondary structures of N29S were preserved. These results indicate that N29S variant is more structurally stable than the reference E7 and H51N. Finally, using analysis of electrostatic potential, differences in the charge on the LXCXE motif were also observed. The E7 E-P variant essentially presents a negative charge in this region, while the N29S variant harbors a combination of negative, electrostatically positive, and neutral charges in this region. Meanwhile, the H51N variant contains negative, neutral, and positive regions in the LXCXE motif. These interesting findings suggest that the affinity of cellular proteins for E7, which is dependent on the LXCXE motif may differ between variants, which may affect their oncogenic potential .In relation to the participation of E2 variants in cancer, hitherto only one functional study has been carried out. In order to have a more comprehensive idea of the participation of E2 AsAi and-Af variants of HPV-18 in processes associated with cancer, the transcriptional profiles altered by E2 and its variants were assessed in different cell lines, including MCF-7, C-33 A, and HEK293. The analyses included the results of the three cell lines in order to evaluate the effect of the E2 variants regardless of the cellular context, that is, the aim was to show the genes that were exclusively deregulated by the E2 variants regardless of the cell type. It was demonstrated that E2 variants differentially regulated gene transcription patterns where expression of 1361 genes were affected by E2 AsAi, while E2 Af altered the expression of 235 genes, and only 34 genes were shared between the E2 tested variants. Interestingly, gene ontology analysis demonstrated that both AsAi and Af variants regulated cellular processes, including metabolism (523 vs. 73 genes), proliferation (78 vs. 15 genes), cellular communication (252 vs. 59 genes), and death (93 vs. 18 genes), respectively. It was demonstrated that the effect of E2 variants on gene regulation was maintained in different cell contexts. Moreover, it was previously demonstrated that E2 induced cell death; however, when comparing the effects of E2 variants it was found that E2 AsAi favors gene expression related to the extrinsic apoptotic pathway, while E2 Af favors the intrinsic apoptotic pathway. Through viability assays, it was shown that both variants reduced cell viability in comparison to control cells ; however, the strongest effect was observed in those cells with E2 Af. Similar results were obtained when apoptosis was evaluated, it was found that both variants differentially induced apoptosis in relation to the control cells, being 29.4% attributable to E2 AsAi, while E2 Af induced 53.3%. These results suggest that E2 variants differentially regulate cellular viability and apoptosis, probably due to the different gene expression profiles induced by the variants .Cervical cancer continues to be a serious public health problem in Mexico, since mortality related to this type of cancer has had a significant increase from 3357 cases reported in 2012 to 4335 cases in 2020 . The vac


Purpose: We analyzed data from the National Health Insurance Research Database (NHIRD) in Taiwan, collected information regarding human papillomavirus (HPV) and breast cancer prevalence, and explored the association between HPV infection and the risk of breast carcinoma. Methods: We included the NHIRD data of 30,936 insured patients aged 20 years an older without breast cancer prior to the index date (date of HPV diagnosis) and matched each patient with a reference subject according to age, comorbidities, and index year (1:1 ratio). We calculated the incidence rates of breast cancer in the cohorts, age groups, and comorbidity groups, as well as the relative risk of breast cancer stratified by age and comorbidity in the HPV and non-HPV groups. Results: The patients with and without HPV had incidence rates of 12.5 and 9.81 per 10,000 person years, respectively. The risk of breast cancer for the 50−64 and ≥65 age groups was 1.67 and 1.36 times higher than that in patients younger than 49 years, respectively, and hypertension, chronic obstructive pulmonary disease, and diabetes mellitus were significant risk factors for breast cancer. The HPV group had a higher risk of developing breast cancer than the non-HPV group, regardless of age group and the presence or absence of comorbidities. Patients with HPV in the 50–64 age group were 1.39 times more likely to develop breast cancer than patients of the same age without HPV. Conclusion: Patients older than 49 were more likely to develop breast cancer, and patients with HPV had a higher likelihood of developing breast cancer, regardless of age and the presence or absence of comorbidities. HPV likely plays a causal role in breast cancer. Breast cancer is one of the cancers with the highest global prevalence among women and is the leading cause of death from cancer in women. According to American Cancer Society, breast cancer is the most common cancer in women in the United States, accounting for about 30% or 1 in 3) of all new female cancers each year. In Taiwan, the incidence of invasive breast cancer increased from 66.1/100,000 in 2007 to 107.2/100,000 in 2018 [ in 3 of Human papillomavirus (HPV) infection is a sexually transmitted disease with the highest prevalence among both women and men. The CDC (Center for Disease Control and Prevention) reported that HPV is the most common STI, with about 43 million HPV infections in 2018, many among people in their late teens and early 20s. There are many different types of HPV. Some types can cause health problems, including genital warts and cancers. Approximately 90% of HPV infections cause no evident symptoms and resolve within 2 years . HPV hasIn the United States, where the epidemiology of HPV infection was first established, the HPV prevalence is much higher among women than among men . FurtherThe aim of our study was to analyze data from the National Health Insurance Research Database (NHIRD) in Taiwan, collect information regarding HPV and breast cancer prevalence, and explore the association between HPV infection and the risk of breast carcinoma.Taiwan launched a single-payer National Health Insurance program in 1995. Since that time, 99% of the residents of Taiwan have been enrolled in the program. The NHIRD was subsequently established. The Longitudinal Health Insurance Database (LHID) contains a subset of the NHIRD data. One million patients insured through the National Health Insurance program were randomly selected to become part of the LHID, and their registration and original claims data were recorded. The diseases recorded in the database were defined according to the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM). We conducted a cohort study using data from the LHID from 2000 to 2013. We included insured patients aged 20 years and older without breast cancer prior to the index date, which was the date of HPV diagnosis . A total of 61,872 patients were included and divided into HPV and non-HPV groups. The patients with HPV were matched to a reference subject according to age, comorbidities, and index year (1:1 ratio).Breast cancer (ICD-9-CM code 174) was the study end point. The follow-up time was the interval between the index date and the date of breast cancer diagnosis, missing data, death, or the end of 2013. We also considered comorbidities related to breast cancer, including hypertension , coronary artery disease , chronic obstructive pulmonary disease , stroke (ICD-9-CM codes 43 and A29), diabetes mellitus (ICD-9-CM codes 250 and A181), hyperlipidemia (ICD-9-CM codes 272 and A182), and obesity (ICD-9-CM codes 278 and A183).t test. We calculated the incidence rates of breast cancer in the cohorts, age groups, and comorbidity groups. The hazard ratio of each variable was estimated using a Cox regression model. We adjusted the hazard ratios by including the variables that were significant in the univariate Cox regression model in a multivariate Cox model. The relative risk of breast cancer, stratified by age and comorbidity in the HPV compared with the non-HPV groups, was also analyzed. The Kaplan–Meier method was used to assess the cumulative incidence of breast cancer in the cohorts, and the differences were compared using a log-rank test. Significance was set at a p value of <0.05.The chi-square test was used to compare the proportional distribution of the age groups  and comorbidities in the HPV and non-HPV cohorts. The mean ages of the groups were determined using a two-sample p value of <0.05.The distributions of the baseline characteristics in the case and control groups are presented in The global incidence and mortality rates of breast cancer are increasing. Because the etiology of breast cancer is complex, identifying new potential risk factors for breast cancer is essential for both its treatment and prevention. HPV is transmitted through sustained skin-to-skin contact. The virus infects the epithelium and mucosa, inducing inflammation and production of oncogenic protein. This process of transmission and its carcinogenicity renders HPV a highly suspected risk factor for breast cancer development. Viral infection causes 18–20% of cancers , and theIn this study, we paired the data of 30,936 women reported to be infected with HPV between 2000 and 2013 in the NHIRD with those of a non-HPV group, with an average follow-up of 7.2 years. We demonstrated that the hazard ratio (HR) for HPV in women aged between 20 and 49 was 1.27 (95% CI = 1.20–1.34), with a relative risk of 27%. Among women aged 50–64, the adjusted ratio was 1.39 , with a 39% increased relative risk; among women aged 20–49, the adjusted ratio was 1.21 , with a 21% increased relative risk. The adjusted ratio was 1.36 , with a 36% increased relative risk, among women aged >65 years. For all ages, women who were infected with HPV had a 21%–36% increased risk of breast cancer compared with women without HPV. The incidence rate of breast cancer in women with HPV was 12.5/10,000 person years, and that in women without HPV was 9.81/10,000 person years. The breast cancer incidence for all women in Taiwan from 2010 to 2015 ranged between 6.32/10,000 and 7.3/10,000 after age standardization.Most studies on HPV and breast cancer test HPV DNA in both benign breast lesions and breast cancer lesions ,30,31,32Saimul et al. conducted a retrospective study in India in which they analyzed benign and malignant breast tissue. The results revealed a high frequency of HPV infection (63.9% in pretherapeutic women and 71% in women who received neoadjuvant therapy) in breast cancer tissue and only a 9.5% frequency in adjacent normal breast tissue. HPV16 and HPV18 were responsible for 69% and 35% of the infections, respectively, and HPV33 was responsible for 2.9% of the infections. In the same study, of the women with HIV, 30% had fibroadenomas, and 71.5% had benign phylloides, whereas only 9.5% of the normal women were HIV-infected.In a 2017 review of the molecular evidence of HPV and breast cancer, Carolina et al. included 43 studies that tested HPV in breast cancer tissue with and without normal breast tissue. Most of the studies employed initial PCR amplification using commercially available primers to screen HPV in cervical cancer. Some studies further obtained primers from the E6 and E7 regions or primers sequenced to identify specific subtypes. The percentage of women who had breast cancer who were also identified as infected with HPV ranged from 0% to 86.2%, and the percentage ranged from 0% to 32% in women with nonmalignant tumors. The included studies analyzed both benign and malignant specimens, with 17 studies achieving statistical significance, compared to 6 studies in which statistical significance was not achieved. The heterogeneity maybe due to racial differences, age differences, a lack of standardization in optimizing DNA amplification, or differing epidemiologies between counties. Because the prevalence of HPV among women aged older than 18 was 7.3% in the United States from 2011 to 2014, 4.1% to 17.2% in different parts of Asia, and 2.1%–6.1% in different parts of Europe, the results of these studies must be interpreted with caution.Our study is the first to apply data from a national health program to explore the effects of HPV on breast cancer by matching the data of women with HPV with data of women without HPV of the same age and with the same comorbidities. Atique et al. also used the NHIRD to explore the risk of breast cancer in women with HPV . HoweverMost studies that have compared breast cancer and normal breast specimens have investigated HPV genotypes 16, 18, and 33. Three types of HPV vaccines are commercially available. Cervarix protects against initial infection with HPV 16 and 18; Gardasil protects against HPV 6, 11, 16, and 18; and protects against HPV 6, 11, 16, 18, 31, 33, 45, 52, and 58. However, these vaccines primarily benefit women who have not been exposed to HPV. The actual effectiveness and protective effects against breast cancer of HPV vaccines remain unclear and warrant further investigation.Our result of a 27% total increased relative risk among women with HPV infection supports that the risk of breast cancer increases with HPV infection.The limitations of this study include its observational nature, selection biases related to the data being obtained from a registry of patients screened for suspected diseases rather than an unselected population-based cohort, and the lack of information on behavioral risk factors reported to affect risk of infection. Furthermore, we included no subgroups for other risk factors for breast cancer, such as insomnia, air pollution exposure, and other viral infections.Because 90% of HPV infections have no observable symptoms and resolve within 2 years, the number of infected individuals may have been underestimated. The average follow-up was 7.22 years. New cases of infection may have occurred after that period.The prevalence of HPV in breast cancer indicates that prophylactic vaccination against HPV is required to limit infection in women. Moreover, the presence of HPV in breast tissue could be a powerful biomarker that could be implemented in a treatment protocol for HPV-infected breast cancer. Furthermore, HPV vaccines primarily benefit women who have not been exposed to HPV. Therefore, the vaccine’s actual effectiveness and protective effects against breast cancer remain unclear and warrant further investigation.The strengths of our study include a large sample size and robust event rate, analytic control for known risk factors in the matched cohort, and independent confirmation of the magnitude and direction in the unmatched cohort.Several HPV families, such as HPV16 and HPV18, have been linked to an increased risk of several types of cancer. In our study, we discovered that these families increase the risk of breast cancer.People who were older than 49 years had a greater risk of developing breast cancer. The risk of breast cancer for the 50−64 and the >65 age groups was 1.67 and 1.36 times higher than that of people younger than 49 years, respectively. The patients with HPV had a higher risk of breast cancer than patients without HPV, regardless of age group and the presence or absence of comorbidities. Moreover, the patients with HPV in the 50–64 age group were 1.39 times more likely to develop breast cancer than the patients without HPV in the same age group. HPV may play a causal role in breast cancer.According to the CDC, HPV is the most common sexually transmitted infection. When used correctly and consistently, condoms represent one of the most effective methods of protection. HPV vaccines primarily benefit women who have not been exposed to HPV. Therefore, the vaccine’s actual effectiveness and protective effects against breast cancer remain unclear and warrant further investigation.


INK4a, S100, p63 and CD117 and tested for the presence of the MYB-NFIB fusion transcript. Notably, no samples were HPyV-positive, while one sinonasal and two tonsillar carcinomas were HPV- and p16-positive. After re-evaluating the micromorphology, immunohistochemistry and presence of fusion transcripts, all tumours had the same appearance and fitted within the diagnosis of HMSC, but in all these three cases, the morphology of the HMSC and basaloid squamous cell carcinoma was overlapping. We conclude that HPV and HPyV have no major role in AdCC. However, based on our data, we also suggest that HMSC should be considered as a basaloid variant of squamous cell carcinoma, and not its own entity, until better characterized.An aetiological role of human papillomavirus (HPV) and/or human polyomaviruses (HPyVs) has been proposed in adenoid cystic carcinoma (AdCC). Moreover, HPV-related multiphenotypic carcinoma (HMSC) was recently introduced as an emerging entity of the sinonasal region. Here, we primarily want to study the role of HPV/HPyV in a large AdCC cohort and, secondly, possibly identify and characterize HMSC. Tumour DNA from 68 patients initially diagnosed with AdCC between 2000 and 2012 was, therefore, tested for 27 HPV types and 10 HPyVs. HPV DNA-positive samples were micromorphologically re-evaluated, further stained for p16 Infection with human papillomavirus (HPV) is now an established risk factor for many head and neck carcinomas (HNSCCs), including tonsillar and base-of-tongue squamous cell carcinomas , and a subset of sinonasal nonkeratinizing squamous cell carcinomas (NKSCCs) . HoweverAdenoid cystic carcinomas (AdCCs) are rare salivary gland malignancies, with a varying clinical outcome . Their rIn 2013, however, a new additional HPV-related form of sinonasal carcinoma, now entitled HPV-related multiphenotypic sinonasal carcinoma (HMSC), was presented in a case report by Bishop and colleagues . Since tInitially, HMSC was entitled HPV-related carcinoma with adenoid cystic carcinoma-like features due to histomorphological resemblances with AdCC. Nevertheless, despite different histological origins, many HMSC cases may have in the past, before this form was recognized in 2013, been diagnosed as AdCC .The aim of this study is, therefore, two-fold: Primarily, we want to examine the presence of HPV and HPyV in the so far, to our knowledge, largest cohort of patients with AdCC in the head and neck region, to determine a possible aetiological role of these oncogenic viruses. Secondly, in the same cohort, we want to identify and characterize possible patients with HMSC diagnosed in Stockholm 2000–2012, either in, or possibly also outside, the sinonasal region.In total, 94 patients were identified through the Swedish Cancer Registry (Cancerregistret) as diagnosed with AdCC within the head and neck region  between 2000 and 2012 in the County of Stockholm. For the continued analysis, haematoxylin–eosin (HE)-stained slides and formalin-fixed paraffin-embedded (FFPE) tumour samples from these patients were collected, when possible, from the Pathology Dept. at Karolinska University Hospital. Sufficient amount and quality of FFPE tumour material was available in 73 samples from 68/94 patients. More specifically, these were from 66 primary tumours; 1 metastasis and 1 local recurrence where no primary was available; finally, 3 local recurrences and 3 metastases where the primaries were available. The study was conducted according to ethical permissions 99-237, 2005/431-31/4, 2009/1278-31/4, 2012/83-31/2, 2017/1035-31/2 and 2019-05211 from the Ethics Committee at Karolinska Institutet, Stockholm, Sweden.For every patient case, tumour and adjacent normal control tissue were dissected from 10 μm FFPE tissue sections from the same FFPE tissue block. DNA was extracted from tumour and normal tissue sections using the QIAamp DNA FFPE Tissue Kit  following the manufacturer’s instructions and as described previously . PresencFor HPyV DNA analysis, a similar bead-based multiplex assay was used as previously described (3). This assay detects the ST and VP1 regions of 10 HPyVs; BKPyV, JCPyV, KIPyV, WUPyV, MCPyV, TSPyV, HPyV6, HPyV7, HPyV9 and HPyV10, as well as the primate viruses SV40 and LPyV, as described previously ,22. β-gl®, Tucson, AZ, USA), and immunohistochemistry was performed using the Ventana Benchmark Ultra platform . Primary antibodies were directed against p63 , CD117 , S100  and p16 . Overexpression of p16 was defined as a strong nuclear and cytoplasmatic staining in ≥70% tumour cells, as described elsewhere [Tumour sections were deparaffinized using EZ-prep . The quality and quantity of the RNA were estimated through Nanodrop technology . cDNA was, subsequently, synthesized using the High-Capacity cDNA reverse transcription Kit  and RT-PCR was performed in duplicate for targeting the fusion gene transcripts corresponding to MYB-NFIB variants on the LightCycler® 480 II instrument (Roche Diagnostics), according to Fehr et al. [Total RNA was extracted from the FFPE material using the Maxwellr et al. . SamplesAltogether, 73 tumour samples and corresponding adjacent normal tissues from 68 patients diagnosed with AdCC within the head and neck region were analysed for the presence of HPV and HPyV DNA. The patients and their tumour characteristics are summarized in In patients with HPV DNA-positive tumours, of which one had a sinonasal and two had a tonsillar primary location, patient and tumour characteristics were examined and scrutinized in more detail. Furthermore, to ultimately be defined as HPV-positive, here, we also required the presence of p16 overexpression (see below), since the presence of HPV DNA together with p16 overexpression has earlier been shown to be very close to disclosing the presence of HPV RNA .In all cases, a nonkeratinizing squamous cell carcinoma, a basaloid squamous cell carcinoma or a solid variant of an AdCC were considered as differential diagnoses by the pathology reports. However, the overall conclusion at the time of diagnosis, considering both the histomorphology and immunohistochemistry, was that these tumours represented solid variants of AdCC.After reviewing the histomorphology, all three primary tumours showed a similar morphology. All were basaloid by their appearance, with small blue basaloid cells with a mainly solid growth pattern and focal areas with tubular- and/or cribriform-like areas. Focally, a tendency to nuclear palisading was observed in all three tumours. In addition, necrotic areas, as well as numerous apoptotic and mitotic bodies, were observed. No clear associated dysplastic squamous epithelium was noticed .n = 4) and were largely diffusely p63-positive. Focal minimal areas with CD117 were also observed in all three primary samples, as indicated in According to the immunohistochemistry, all tumour samples overexpressed p16  with basaloid features, rather than an AdCC, was more likely in these three HPV DNA-positive cases. In fact, it is well recognized that a solid variant of an AdCC in many cases may be hard to distinguish from a basaloid SCC  and, theIn similar studies on the occurrence of HPV in AdCC, very few have examined the presence of HPyV in AdCC. In a publication by Hämetoja et al., the presence of two HPyVs (JCPyV and BKPyV) as well as SV40 was analysed in 68 AdCC, and there, 10.3% of the tumours were described to harbour JCPyV in very low copy numbers . The datNotably, here, we identified three patient cases, one sinonasal and two tonsillar primary tumours with a molecular and a micromorphological profile that fit within the new emerging entity of HMSC, with the exception that two of them were situated outside the sinonasal region. However, in a recent meta-analysis, including all published cases with HMSC so far, two other patients were identified as having HMSC-like tumours outside the sinonasal region . Here, wIn line with previous reports  about thIn the last WHO Classification of Head and Neck Tumours from 2017, HMSC was introduced, but was not considered as its own entity due to too few reported cases in the literature, variable histology with focal overlap with nonkeratinizing SCCs and unknown prognostic significance . Due to In analogy with this possibility, a study of basaloid SCCs of the anus is worth mentioning . In thatWe acknowledge limitations in this study. This was a retrospective registry-based study. Patients were identified through a national-based cancer registry and identified patients’ pathology and clinical reports were reviewed. Only tumours from the three patients with HPV-positive neoplasms were re-evaluated micromorphologically and with molecular and immunohistochemical analysis. Unfortunately, histological and immunohistology slides were not available for all patients, and it was, therefore, possible that some virus-negative tumours could also have been misclassified as AdCC.In summary, we suggest that the role of HPV and HPyV is minor, if present at all, in AdCC. We also suggest that HMSC could be considered as a basaloid variant of squamous cell carcinoma, and not as its own entity, since a need for further characterization was indicated.To conclude, we found that the role of HPV and HPyV is minor, if present at all, in AdCC. In addition, we indicated that HMSC could be considered as a basaloid variant of squamous cell carcinoma, and not as its own entity.


An accurate estimation of pipe attributes, pose of pipeline inspection gauge (PIG), and downstream pipeline topology is essential for successful in-line inspection (ILI) of underground compressible gas pipelines. Taking a 3D point cloud of light detection and ranging (LiDAR) or time-of-flight (ToF) camera as the input, in this paper, we present the simultaneous pipe-attribute and PIG-pose estimation (SPPE) approach that estimates the optimal pipe-attribute and PIG-pose parameters to transform a 3D point cloud onto the inner pipe wall surface: major- and minor-axis lengths, roll, pitch, and yaw angles, and 2D deviation from the center of the pipe. Since the 3D point cloud has all spatial information of the inner pipe wall measurements, this estimation problem can be modeled by an optimal transformation matrix estimation problem from a PIG sensor frame to the global pipe frame. The basic idea of our SPPE approach is to decompose this transformation into two sub-transformations: The first transformation is formulated as a non-linear optimization problem whose solution is iteratively updated by the Levenberg–Marquardt algorithm (LMA). The second transformation utilizes the gravity vector to calculate the ovality angle between the geometric and navigation pipe frames. The extensive simulation results from our PIG simulator based on the robot operating system (ROS) platform demonstrate that the proposed SPPE can estimate the pipe attributes and PIG pose with excellent accuracy and is also applicable to real-time and post-processing non-destructive testing (NDT) applications thanks to its high computational efficiency. In the ILI, a pipeline inspection gauge (PIG) moves inside of an operational pipeline and collects sensor data, including magnetic, acoustic, optical, inertial, pressure, etc., to identify and localize corrosion, cracks and other defects that may lead to catastrophic failure [Pipelines are the most economical way to transport large quantities of liquid or gas such as oil, water, sewage, natural gas, and hydrogen gas over a long distance. As a result, pipeline transport occupies 70 % of the crude oil and petroleum supply in the United States and 97 % of the natural gas and oil supply in Canada ,2. To as failure ,4,5. Aftnon-destructive testing (NDT) sensors mounted in the circumferential direction of PIG simultaneously sample their signals for successful assessment of pipeline integrity. For example, a geometry PIG senses its caliper arm angle to detect dents and pipeline fixtures, such as weld, bend, tee, valve, etc. [exteroceptive sensing of PIG, which helps to better recognize pipe attributes and PIG pose.In this paper, we focus on the ILI of compressible gas pipelines, where a PIG is driven by the differential pressure between the compressed upstream gas and the operating downstream gas. While a PIG moves forward inside the gas pipeline, multiple ve, etc. ,7. On thve, etc. ,9. Our pspeed excursions [A key challenge in the ILI of gas pipelines is to keep the PIG speed below a threshold to acquire NDT sensor data of sufficient quality to meet the specifications . Althougcursions ,11,12. Tcursions  that a Plaser image processing and visual odometry. The laser image processing approach irradiates a laser beam pattern on the inner wall of the pipeline and estimates the pipe attributes or robot pose through the mathematical modeling of the reflected light captured at a camera image [For the success of PIG speed control, it is essential to accurately estimate the pipe attributes, pose of PIG body, and downstream pipeline topology. To aim this, in-pipe robots are usually equipped with exteroceptive sensors. Two major approaches to exteroceptive sensing have received significant attention from academia and industry: ra image ,16,17,18ra image ,20,21,22Although both exteroceptive sensing approaches are suitable for tethered or self-propelled in-pipe robots, they still face three common limitations in the long-distance ILI of compressible gas pipelines: First, the projection of the inner pipe wall surface onto the camera image plane results in an intrinsic loss of depth information that needs to be recovered from either the complex mathematical model of laser image processing or the association of visual features over subsequent frames. Second, their estimation is incomplete in the sense that they require prior information such as pipe radius with an assumption of a perfectly round cross section in ,19,20,213D point cloud from the light detection and ranging (LiDAR) [simultaneous pipe-attribute and PIG-pose estimation (SPPE) approach that estimates the optimal seven pipe geometry and PIG pose parameters for the transformation of a 3D point cloud into the inner pipe wall surface: major- and minor-axis lengths, roll, pitch, yaw angles of PIG, and 2D deviation from the center of pipe in the cross section plane. The basic idea of our SPPE approach is to decompose the whole transformation into two sub-transformations: The first transformation uses the Levenberg–Marquardt algorithm (LMA) [Taking into account these limitations, we advocate the use of  (LiDAR)  or time- (LiDAR)  as an exhm (LMA) ,26,27,28The remainder of this paper is organized as follows: In The objective of ILI is to detect defects on the surface of pipe and accurately estimate their location and attributes for successful pipeline integrity management . In compTo mitigate this problem, two exteroceptive sensing approaches have been investigated in the literature: laser image processing and visual odometry. The laser image processing approach estimates the robot pose or pipe diameter by analyzing the shape of the reflected laser image patterns projected onto the camera image plane ,16,17,18On the other hand, the visual odometry approach extracts the keypoints that commonly exist in multiple camera images, and estimates the robot pose by formulating the pixel differences of these keypoints as the relative differences in the robot poses ,20,21,22f, w, x, and Furthermore, both exteroceptive sensing approaches face a few common limitations in their application to the ILI of large-diameter gas pipelines. First, the projection of the inner pipe wall surface onto the camera image plane results in an intrinsic loss of depth information that can be hardly recoverable from the mathematical modeling of laser image processing or the association of visual features over subsequent frames. To overcome this limitation, the approaches in ,19,20,21In this paper, we propose an alternative exteroceptive sensing approach that uses a 3D point cloud of a LiDAR or ToF camera for the ease of detecting pipe attributes, PIG pose, and downstream pipeline topology. Since the -D point cloud retains all spatial information of the inner pipe wall measurements, this approach can avoid the limitation originating from their projection onto a 2D camera image plane, and provide a principled methodology to address a few fundamental issues of pipe-attribute and PIG-pose estimation: first, this estimation problem is modeled by the transformation matrix estimation problem from a 3D point cloud in the PSF to a 3D point cloud in the global NPF. Second, the PIG-pose parameters are clearly distinguished from the pipe-attribute parameters in our problem specification—the former constitutes the rotation and translation matrices, while the latter is used for the objective function of the optimization formulation. Third, our iterative solution based on the LMA can estimate the pipe attributes and PIG pose with excellent accuracy and be used for many real-time and post-processing NDT applications.In this section, we first formulate the model for the reference frames, and describe the transformation invariance of 3-D point cloud measurement in X-, Y-, and Z-axes are defined as the front direction  in  allows uGiven the PSF point cloud rface in .(5)f ,26,27.The GDA iteratively updates the parameters in the steepest-descent direction, i.e.,βg(k+1)=βon S(βg) .On the other hand, the GNA exploits the second-derivative (curvature) information to compute the increment vector :(9)J⊺JδkTo mitigate this problem, the LMA adaptively combines the GDA and GNA using the damping factor  follows ,26,27: element of Denoting the   frameworN different PIG poses, and for each of them, generates the input point cloud for m pipe inner wall measurements. Based on this point cloud, it executes the SPPE to obtain the estimate of pipe attribute and PIG pose. Once all PIG poses are processed, the PIG simulator evaluates the performance of SPPE.The pipe component supports two pipe topologies (straight and bend), where our focus in this paper is on the cylindrical straight pipe with elliptical cross section. Four different pipe diameters , the estimation accuracy of our SPPE with LMA input size Next, we investigate the performance of our SPPE depending on the LMA input size, which must be at least seven to obtain a feasible solution to transformation parameter m, the LMA takes a longer time to converge to an optimal point due to its large searching area for the solution in the parametric space. The computation time of our SPPE is also scalable to a large LMA input size so that it can be a promising solution to real-time estimation of pipe attributes and PIG pose.This paper has presented a novel SPPE approach to the pipe-attribute and PIG-pose estimation based on 3D point clouds. We formulate this problem into an optimal transformation matrix estimation problem from a point cloud in the PSF to a point cloud in the global NPF. The basic idea of our SPPE is to decompose this transformation into two sub-transformations: the first one from PSF to GPF, and the second one from GPF to NPF. The extensive simulation results from our PIG simulator demonstrate that our SPPE approach can achieve millimeter-level accuracy for pipe-diameter estimation, sub-degree-level accuracy for PIG-pose estimation, and sub-millimeter-level accuracy for displacement estimation.


Background: HPV primary screening has shown effectiveness for cancer prevention; however, gynaecological examination is considered uncomfortable. Self-sampling methods increase the acceptance of screening. The aim of this study is to compare the sensitivity and specificity of clinician sampling versus vaginal and urine self-sampling for HPV diagnosis. Methods: A diagnostic test study was conducted in a rural parish of Cuenca, Ecuador. A total of 120 women participated. Each participant self-collected urine and vaginal samples and underwent clinician sampling for HPV testing. The latter was considered as the golden standard. All three samples were processed with the same amplification and hybridization protocol for HPV detection (Hybribio) following the manufacturer’s instructions. Results: Characteristics of the participants were: median age 35 years; 40.8% married; 46.7% had a primary level of education; and median age of sexual onset, 17.6 years. The prevalence of any type of HPV with clinician sampling was 15.0%, 17.5% with urine sampling and 18.3% with vaginal self-sampling. Self-sampling sensitivity reached 94.4% (IC 74.2–99.9), and specificity 92.1% (IC 85.2–95.9). Urine sampling had a sensitivity of 88.8% , and specificity 94.1% (IC 67.2–96.9). The negative predictive value was 98.9% (IC 94.2–99.8) for vaginal self-sampling and 97.6% (IC 92.6–99.4) for urine sampling. Conclusions: This study shows that vaginal and urine self-sampling methods have similar sensitivity and specificity compared with clinician sampling for the diagnosis of HPV. The correlation between HPV genotypes among the three tests is satisfactory. Since the pap smear was implemented for population screening in 1970 for cervical cancer (CC) prevention, mortality has decreased by 70% worldwide ,3. Due tThe detection of human papilloma virus (HPV) used as a primary screening method has a higher sensitivity 95%) and specificity (94% to 95%) than cytology to detect premalignant lesions % and spe,7. A negScreening and vaccination against HPV are reducing CC mortality in countries with strong preventative programs . HoweverSeveral barriers have been identified for access to cervical CC screening services; according to the socio-ecological model, they interact at different levels: organizational , interpersonal (stigma and lack of family support) and personal (lack of risk perception and fear of examination) ,14,15. FSelf-sampling methods, such as vaginal self-sampling and urine sampling for HPV diagnosis, have demonstrated high acceptability and sensitivity for cervical cancer screening ,18. CompOn the other hand, doubts about the sensitivity of self-sampling tests could discourage women to choose those tests. There are limited studies that compare the sensitivity and specificity of vaginal self-sampling and urine sampling for HPV detection at the same time and in the same population. Type of SampleSensitivitySpecificityAuthorVaginal self-sampling83.3%73.9%Asciutto et al., 2018Vaginal self-sampling84%93%Arbyn et al., 2018Vaginal self-sampling84.6%62.9%Wang et al., 2020Vaginal self-sampling50%98% Esber et al., 2018Vaginal self-sampling98.9%100%Kuriakos et al., 2019Urine self-sampling48.1%82.8%Asciutto et al., 2018Urine self-sampling90.5%74.0%Combita et al., 2016A literature review reflects a wide range of variation in sensitivity and specificity among tests and techniques ,24,25,26This is the first study of self-sampling effectiveness conducted in Ecuador; the aim of this research is to compare sensitivity, specificity, predictive values and correlation for the diagnosis of HPV from vaginal self-sampling and urine self-sampling versus clinician sampling in a rural setting.This study was approved under the guidance of the Declaration of Helsinki and the Council for International Organizations of Medical Sciences (CIOMS). All procedures involving human participants were approved by the bioethical committee of the University of Cuenca  and the National Directory of Intelligence in Health (DIS) of the Ministry of Health of Ecuador . All the participants were informed about the purpose of the study and signed an informed consent form before the sample collection.A diagnostic test study was conducted in the rural parish of El Valle of Cuenca Ecuador from May to August 2021. Through flyers delivered in public places, households and in healthcare centres, women of El Valle were invited to participate. The inclusion criteria included being sexually active; being between 18 and 70 years old; not having undergone an excision or destructive treatment of the cervical intraepithelial neoplasm; not having used vaginal medication at least a week before the examination; not having had sexual intercourse for at least 48 h previous to the examination; not being pregnant; and the absence of menstrual bleeding at the time of examination. One hundred twenty women participated and provided three samples: urine, a vaginal sample and a physician-taken cervical assay. Prior to sample collection, patients who agreed to participate were taught how to take the samples: a pictographic representation of each technique was given to all participants and the same graphics were present in the bathroom where the patients were instructed to obtain the samples. The first sample obtained was a urine sample; it was obtained directly in a sterile urine container after self-made asepsis by the patient in the bathroom of the consultation room. All patients were asked to collect at least 30 cc of urine. ® Brush from Rovers Medical Devices was the selected tool for this sampling. Fabricant instructions were used for sample collection; researchers waited outside of the bathroom for any additional explanation and to receive the sample after its collection. Finally, the patient was directed to a gynaecological examination table. After the insertion of the speculum, endocervix and exocervix samples were obtained by using a Hybribio cervical brush, rotating 360° twice. The cervical brush was placed in Roche Cell Collection Medium for transportation. This medium was selected because it contains 20 cc of preservant, which allows the researcher to centrifuge and obtain material for HPV diagnosis.After urine sampling, a self-sampling device for vaginal sampling was given to the patient. An EvalynAll the samples were paired, labelled, coded and transported to the laboratory of molecular biology of the University of Cuenca within the first 6 h of collection. The results for HPV were delivered to the patients within 10 days after the sample collection. Once in the laboratory, the 3 samples  from each patient were processed to obtain the genetic material. For urine DNA purification, we used the DNA prep kit  following the manufacturer’s instructions. For the conventional collection samples, we used the Cell Lysis Kit (Hybribio) following the manufacturer’s protocol. Finally, the self-sampling brushes were washed for about 1 min in Hybribio Female Sample Collection media to release the cells and purify the genetic material using the same extraction kit as the conventional collection. All the material obtained was stored at −20 °C until further use. For amplification, we used the 37 HPV GENOARRAY kit (Hybribio), which allows the simultaneous amplification of 37 different genotypes, including high-risk genotypes: 16, 18, 31, 33, 35, 39, 45, 51, 52, 53, 56, 58, 59, 66, and 68; and the low-risk (LR) ones: 6, 11, 42, 43, 44, and CP8304 (81); and 26, 34, 40, 54, 55, 57, 61, 67, 69, 70, 71, 72, 73, 82, 83, 84 categorized as undetermined risk. The PCR mix was performed according to the manufacturer’s instructions to obtain a final reaction volume of 25 μL . For urine samples, the final volume was 26 μL because we added 2 μL of DNA template. Amplification was performed in the Veriti Thermal Cycler  with the following programming: initial denaturation at 95 °C for 5 min, 40 cycles of denaturation at 95 °C for 20 s, annealing at 55 °C for 30 s and elongation at 72 °C for 30 s, to finish with a final elongation at 72 °C for 5 min.Finally, all the amplicons were denatured for 5 min at 95 °C and placed on ice before continuing the hybridization. The process was carried out in the HibriMax (Hybribio) according to the manufacturer’s instructions. We used HPV-37 Hybrimem membranes containing the immobilized probes of the genotypes of interest. Streptavidin–horseradish peroxidase conjugate was added to bind to the biotinylated PCR products. The direct visualization of the breakdown product (purple precipitate) of the substrate nitroblue tetrazolium-5-bromo-4-chloro3-indolylphosphate was interpreted as positive for the corresponding HPV DNA type as indicated on the schematic diagram of the membrane provided with the test kit.Completed questionaries with sociodemographic data and the results of HPV tests were transcribed to a Microsoft Excel 2016 spreadsheet for cleaning and coding and were subsequently transferred to the Statistical Package for the Social Sciences for Windows version 17.0 . Descriptive statistics were presented using means and standard deviation (SD) for continuous variables and percentages for categorical variables. Open-Source Epidemiologic Statistics for Public Health  was used to calculate sensitivity, specificity, positive predictive value, negative predictive value, likelihood positive ratio, likelihood and Cohen’s kappa. The kappa statistic was calculated to determine the level of chance agreement between the two methods, with a kappa value of 0 indicating no agreement better than chance, 1 indicating perfect agreement better than chance, and intermediate values of 0.00–0.20, 0.21–0.40, 0.41–0.60, 0.61–0.80 and >0.81 indicating poor, fair, moderate, good and excellent agreement. Clinician cervical sampling with a speculum is the standard method for the diagnosis of HPV; therefore, the sensitivity and specificity of HPV detection in urine and vaginal self-sample were calculated using cervical sampling as reference. The width of the confidence intervals of kappa and the diagnostic accuracy parameters show the precision of our estimates.A total of 120 women participated in this study, all of them living in the rural parish. The sociodemographic characteristics of the participants are shown in The prevalence of any type of HPV with clinician sampling was 15.0%, 17.5% with urine self-sampling and 18.3% with vaginal self-sampling.The urine sampling had a sensitivity of 88.8% ; specificity of 94.1% ; PPV of 72.2% ; PNV of 97.6% (IC 51.85–86.85); PLR of 15 (IC 10.73–21.27); and NLR 0.11 (IC 0.04–0.315). The agreement with clinician sampling was 0.76 (kappa).This study demonstrates that urine self-sampling and vaginal self-sampling have similar sensitivity and specificity to clinician sampling for the diagnosis of HPV.The general prevalence of HR and LR HPV genotypes is highly variable in the literature. In Europe, the range of HPV positivity goes from 2% in Spain to 12% in Belgium . In EcuaThe prevalence of any type of HPV was slightly higher in vaginal self-sampling (18.3%) and urine sampling (17.5%); similar results were found by Polman N. et al. in 2019 in the Netherlands, where the HPV positivity rate with self-sampling was 7.4% vs. 7.2% with clinician sampling . In urinHPV genotype also presents variation worldwide. In Europe, the most prevalent genotypes are 16, 18, 31, and 33 , and in The values of the sensitivity and specificity of vaginal self-sampling are comparable to the findings of Arbyn et al., 2018 (84% and 93%) , and areFor urine sampling, our results are similar to the sensitivity and specificity reported by Combita et al. in 2016 (90.5–74.0%) . HoweverA pap smear has a mean sensitivity of 51% . Both meOur research reported a good kappa correlation with clinician sampling; similar results are reported by Swift et al., 2020, with agreement reaching 0.73 . This siSelf-sampling methods  have a high acceptability among populations in rural areas , which cA limitation of the study is that participants were selected by convenience, and all patients who agreed to participate and met the study criteria were included in the study. However, women that participated had similar sociodemographic characteristics, making them comparable. Another limitation is that an important number of women below 30 years old participated in the research, which could increase the prevalence rates of HPV in this study. This affects PPV and NPV in our sample; typically, in populations with a lower prevalence, NPV would be better.Including young women was intentional in order to find more HPV-positive patients and to have a sufficient number of positive results to calculate sensitivity and specificity. Previous research conducted in Ecuador demonstrated a lower prevalence of HPV in rural areas compared with urban.This research study is the first conducted in Ecuador evaluating the effectiveness of self-sampling methods in a rural community in Cuenca, Ecuador.This study shows that vaginal and urine self-sampling methods have similar sensitivity and specificity to clinician sampling for the diagnosis of HPV. The Kappa correlation between HPV genotype among the three tests is good.Self-sampling methods have a high diagnostic capacity and a capability for the detection of positive cases of HR HPV.The positive results of LR HPV and absence of HPV have a high relevance in clinical practice for detecting or discarding risk for cervical cancer.Self-sampling methods have high sensitivity and specificity and have demonstrated reliability in rural settings.


Cervical cancer is one of the main causes of cancer death all over the world. Most diseases such as cervical epithelial atypical hyperplasia and invasive cervical cancer are closely related to the continuous infection of high-risk types of human papillomavirus. Therefore, the high-risk types of human papillomavirus are the key to the prevention and treatment of cervical cancer. With the accumulation of high-throughput and clinical data, the use of systematic and quantitative methods for mathematical modeling and computational prediction has become more and more important. This paper summarizes the mathematical models and prediction methods of the risk types of human papillomavirus, especially around the key steps such as feature extraction, feature selection, and prediction algorithms. We summarized and discussed the advantages and disadvantages of existing algorithms, which provides a theoretical basis for follow-up research. Human papillomavirus (HPV) usually causes benign papillomas and epithelial malignancies . About 3The early region encodes and produces six proteins. Their functions are as follows: E1 protein mainly controls virus replication and replication inhibition and is expressed in the early stage of virus infection; E2 protein is a specific DNA binding protein , which cMore than 200 HPV types have been identified, and about 40 types can invade the female reproductive tract . When thThe distribution of HPV types has obvious geographical characteristics. Research shows that among the high-risk types worldwide, HPV16 accounts for 51% , followeDifferent types of HPV have different clinical manifestations. According to the tissues invaded, HPV can be divided into high (low) risk type of skin and high (low) risk type of mucosa . Low-risNow, there are many epidemiological and experimental methods to identify HPV types –21. TheyIn this paper, we introduce the development of HPV typing in cervical cancer, mainly focusing on sequence characteristics and predicted secondary structure characteristics. The feature fusion method and feature selection algorithm are discussed. Finally, we review the multiple classification and various machine learning algorithms in HPV typing of cervical cancer.HPV database is from Los Alamos National Laboratory (LANL), with a total of 72 HPV types. HPV risk types were manually determined based on the HPV profile . If HPV The extraction of HPV sequence information is transforming from complex structure to extraction of mathematical features . Directl(1) K-Mer. Protein sequences and peptides can be regarded as a set of signs  × ∑⟶ℜ is used to describe a function M, L is the length of a function M. The PSSM of the sequence Seq0 will be transformed into a RedPSSM of its reduced sequence Seqs,Seq0 and ∑Seqr are finite alphabet sets of the original and reduced sequences. [RedPSSM]ij is defined asgs(j) represents the size of the reduced group which is made up with the reduced amino acid j, and j belongs to 1 ≤ j ≤ |∑seqr|.ACj,g(S) can indicate the interaction between two spacer g residues. But it can just calculate the residue interaction in the same column . The Gaussian radial basis kernel function with strong learning ability and small error is often selected as the kernel function, which is defined asσ is the coefficient of the kernel function and has high flexibility.where PCA is a statistical analysis method that converts multiple indicators into a few comprehensive indicators. The idea of PCA is to replace the original more with fewer comprehensive variables . The firZ:The second step of PCA is to obtain the correlation of coefficient matrix for k-nearest neighbor samples in the feature space [k-nearest neighbor classification algorithm needs global search, which has high computational complexity and slow computing speed. In order to reduce the influence of the same feature function in the traditional KNN algorithm, different weights can be assigned to the features in the distance formula to measure the similarity. For example, in Euclidean distance formula, different weights are assigned to different features, as shown in the formula:KNN is an important nonparametric classification method, which classifies the samples according to the categories of most re space . HoweverPLS-DA is a standard high-dimensional data analysis method, and it is especially suitable for situations where there are a large number of explanatory variables , multicoY represents categorical variables, and q is a dummy variable. The relationship model between explanatory variables, response variables is established by least square regression, and then, the category of each sample is determined by comparing the predicted values of model response variables. If the predicted value of the dummy variable component is the largest, it is determined that the sample belongs to the category corresponding to the dummy variable.where C , the Gini impurity of node A can be expressed by the following formula:pk is the proportion of the sample which belongs to class k. If class A can be divided into B and C. The probability of B in the sample A is p and C is q. And the size of impurities will be expressed by the following formula:CART is a nonparametric statistical process of data analysis. Its characteristic is to make full use of the binary tree structure in the calculation process, that is, the root node contains all samples, and the root node is divided into two children under certain partition rules . The prow, the k sets of m metadata are mapped into another lower-dimensional direction. Then classify with the sample in the new space. LDA is a statistical analysis method used to determine the type of sample , which hSB is an interclass deviation matrix:Sw is an intraclass deviation matrix:xi, i = 1, 2, ⋯, Nx} represents class p, {yi, i = 1, 2, ⋯, Ny} represents class n. Where mx and my, respectively, represent the average of class p and class n.xi to predict a target variable yi.The gradient boosting algorithm framework supports a variety of different loss functions . In addin represents the number of trees, l is the training loss function, and Ω is the regularization term.First of all, the objective function can be calculated ast can be describes asgi and hi can be described as follows:Then, the XGBoost takes the Taylor expansion of the loss function up to the second order and removes all the constants, so the specific objective at step gi and hi.The value of the objective function only depends on It can optimize every loss function, including logistic regression and pairwise ranking, and it is simple to parallel and can greatly enhance the program efficiency with a fast model exploration .k-fold cross validation [k is equal to sample size n, and it can be regarded as n-fold cross validation.After realizing HPV prediction, we need to use statistical test method to evaluate the efficiency of prediction model. Leave-one-out cross-validation (LOO-CV) is a more common method of Bayesian model and a special case of lidation , becauseP) and the true result is also positive, it is called true positive (TP). If the predicted result is negative (N), the real result is also positive, which is called false positive (FP). The results can be calculated by the following formula:HPV typing is a two or three classification problem. If the HPV model predicts a positive result . If the information of mutation information is considered in HPV classification model, it is also an effective way to improve HPV typing detection.Mutations usually lead to cell dysfunction, cell death, and even cancer in higher organisms. Therefore, mutations in HPV protein may make the virus more easily induced or carcinogenic and increase the chance of reinfecting the host or fleeing the host immune system. For example, the carcinogenicity of HPV is mainly controlled by E6 and E7 proteins, which often produce internal variation. The mutation frequency of E6 in cancer is 20% ~90%, and that of E7 is 60% ~90% . A study