The United States Appalachian region harbors a higher cancer burden than the rest of the nation, with disparate incidence of head and neck squamous cell carcinomas (HNSCC), including oral cavity and pharynx (OC/P) cancers. Whether elevated HNSCC incidence generates survival disparities within Appalachia is unknown. To address this, HNSCC survival data for 259,737 tumors from the North American Association for Central Cancer Registries 2007–2013 cohort were evaluated, with age-adjusted relative survival (RS) calculated based on staging, race, sex, and Appalachian residence. Tobacco use, a primary HNSCC risk factor, was evaluated through the Behavioral Risk Factor Surveillance System from Appalachian states. Decreased OC/P RS was found in stage IV Appalachian white males within a subset of states. The survival disparity was confined to human papillomavirus (HPV)-associated oropharyngeal cancers, specifically the oropharynx subsite. This correlated with significantly higher smoking and male smokeless tobacco use in most Appalachian disparity states. Lower survival of Appalachian males with advanced-stage HPV-associated oropharyngeal cancers suggests pervasive tobacco consumption likely generates more aggressive tumors at HPV-associated oropharynx subsites than national averages. Comprehensive tobacco and HPV status should therefore be evaluated prior to considering treatment de-intensification regimens for HPV-associated oropharyngeal cancers in populations with high tobacco consumption. Risk factors include tobacco and alcohol use, and high-risk human papillomavirus (HPV) infection3. OC/P cancers are subdivided into HPV-associated oropharynx (HPV-associated) and non-HPV-associated oral cavity, hypopharynx, and nasopharynx (non-HPV-associated) cancers4. These designations are supported by studies indicating that non-HPV-associated cancers are primarily tobacco/alcohol induced, whereas HPV-associated cancers are predominantly caused by HPV infection5. Furthermore, HPV-negative or non-HPV-associated cancers consistently have poorer outcomes than HPV-positive or HPV-associated cancers, segregating these cancers as distinct diseases with differential clinical management7. While national incidence of non-HPV-associated cancers is decreasing due to tobacco cessation, HPV-associated cancers are increasing due to rising infection rates8. Regarding race, blacks with HNSCC present with more advanced disease, are older and have worse survival than whites, denoting a racial disparity11. Increased screening for HPV coupled with subsite analysis indicates that blacks with HNSCC have less HPV-positive cancer than whites, explaining differences in survival13. Consistent with this, HPV-associated cancers continue to increase in white males and in rural areas15.HNSCC involves the epithelium of the oral cavity, pharynx and larynx. OC/P cancers are a major HNSCC subset, with nearly 11,000 deaths predicted in the US in 202016. Forty-two percent of Appalachia is rural, with poverty rates in many counties 1.5 times above the national mean16. The region is over 80% white, with several states having higher percentages of oral and other HPV-associated cancers, and higher smoking and smokeless tobacco use19. Aggregate risk factors experienced by Appalachian residents contribute to a high allostatic load capable of generating cancer disparities in a region with low ethnic diversity20. Incidence disparities within Appalachia are well recognized21 with rates higher for HPV- and tobacco-related malignancies24. Elevated risk factor exposure has been suggested as the prime reason for disparate incidence in Appalachian male HNSCC25. However, due to gaps in data availability and small patient numbers at the county level, details on how increased incidence impacts HNSCC survival in Appalachia have not been rigorously evaluated25. Here we have evaluated the RS of all HNSCC in the majority of Appalachian states from 2007–2013 and have identified an outcome disparity in white males with oropharynx cancers that corresponds with elevated smoking and smokeless tobacco use in the region.The Appalachian region encompasses 205,000 square miles across 420 counties in 13 contiguous states26. Appalachian states with survival data fit for use through the reporting period included New York, Pennsylvania, West Virginia, Kentucky, North Carolina, South Carolina, Georgia, and Alabama27. The majority of cases were white , stage IV , and male . Cases were evaluated using the Ederer II method and the “U.S. by race  and Canada 1995–2012, Ages 0–99, State-county (modeled by varied state-county-ses)” life table. Included cases were microscopically confirmed for malignant behavior and followed at monthly intervals. Excluded cases were those that were diagnosed solely via death certificate or autopsy, and alive cases with no survival time. Age-adjusted RS, defined as net survival measure representing cancer survival in the absence of other causes of death28, was calculated using SEER*Stat for each patient stratification, with z-tests for significance testing between each group using an alpha level of 0.05. Cumulative (C)RS was used to compare groups with 5 years of available RS data and the maximum available follow-up RS was used to compare groups that failed to reach 5 years of follow-up.All methods were carried out in accordance with relevant guidelines and regulations. Survival data were generated by NAACCR and provided in Surveillance, Epidemiology, and End Results (SEER)*Stat approved under NAACCR IRB protocol 16–14, where all patient data was obtained following informed consent. Patients were diagnosed from 2007–2013 with tumors of International Classification of Diseases for Oncology (ICD-O)-3 histology types 8,050–8,084, 8,120–8,131 . Selecting all primary tumors matching selection criteria, the cohort includes tumors of the oral cavity  including ICD-O-3 site groups of tongue , floor of mouth (C04.0–04.9), and gum and other mouth ; oropharynx  including ICD-O-3 site groups of tongue , gum and other mouth (C05.1–05.2), tonsil (C09.0–09.9), oropharynx (C10.0–10.9), and “other oral cavity and pharynx” (C14.0–14.8); “other pharynx”  including ICD-O-3 site groups of nasopharynx (C11.0–11.9) and hypopharynx (C12.9–13.9); and larynx  including ICD-O-3 site group larynx (C32.0–32.9). Remaining tumors are additional primaries of miscellaneous ICD-O-3 site groups . The cohort includes variables denoting whether or not patients were Appalachian county residents at the time of diagnosis, and county economic status from the Appalachian Regional Commission (ARC)29 and Quantum Geographic Information System (QGIS) 3.2.2 software30. Appalachian state-Appalachian county refers to a county within Appalachia. Appalachian state-non-Appalachian county refers to a county outside of the Appalachian region, but within a state containing Appalachian counties. Non-Appalachian states lack Appalachian counties.Maps were generated using 2014 cartographic boundary shapefiles from the United States Census Bureau32. OC/P patients were stratified by HPV-associated or non-HPV-associated subsite defined by the Centers for Disease Control (CDC)33 and by confirmed HPV status. All patients were evaluated for HPV in the All_CDEs.txt file, denoted by variable “hpv_status”. Kaplan–Meier P values were calculated using Mantel-Cox log-rank test and were validated by an independent biostatistician.Data from The Cancer Genome Atlas (TCGA) were obtained from the Broad Genomic Data Analysis Center (GDAC) Firehose 2016_01_28 TCGA-HNSC cohort consisting of 529 patients with tumors of the oral cavity , pharynx , and larynx . Clinical data and patient characteristics were retrieved from the level 4 TCGA clinical data file All_CDEs.txt and cBioPortal19. Statistical significance was determined within states and between regions using G-tests for independence without Yates’ correction using BRFSS frequency (N) values and an alpha value of 0.05. BRFSS recommends caution interpreting results with less than 50 respondents. Bonferroni correction was used where applicable to reduce type I error. Due to changes in sample composition and weighting methodology in 2011, data from years after 2011 cannot be directly compared to previous years34.Data for 2016 current smoker and smokeless tobacco user frequency, weighted frequency, prevalence, and confidence intervals for Appalachian and non-Appalachian counties were calculated and provided by BRFSS coordinators from Appalachian states. Current smoker status was calculated using CDC BRFSS Tobacco Use Question 1 and 2 from the 2016 questionnaire. Current smokeless status was calculated using CDC BRFSS Tobacco Use Question 3. Non-Appalachian state tobacco use data were acquired from CDC BRFSS35. The OC/P and laryngeal cohorts reflect overall Appalachian demographics, with a higher percentage of white cases and lower percentage of ethnic minorities than non-Appalachia  and white non-Appalachian females  , P = 0.00032  displayed a significantly lower CRS compared to Appalachian states-non-Appalachian counties , P = 0.0006, Kentucky , P = 0.0101, Pennsylvania , P = 0.0047, and West Virginia , P = 0.007 compared to non-Appalachian states  , 6%) Fig. .33. Remaining subsites are not associated with HPV infection and represent non-HPV-associated cancer  displayed a significantly lower CRS compared to HPV-associated patients in non-Appalachian states , P = 0.0399 as well as non-Appalachian states , P = 0.0394  and non-Appalachian counties , Regarding survival driven by oropharyngeal tumors, “other HPV-associated” and non-HPV-associated stratification reveals three distinct outcomes in non-Appalachia Fig. h: “Other19, and current smoker prevalence rates have remained higher in West Virginia  than the nation for several decades36 , New York (P = 2.55e−04), Ohio (P = 0.02965), and Virginia (P = 0.008904) , New York (P = 9.03e−7), North Carolina (P = 5.44e−6), Ohio (P = 1.87e−12), South Carolina (P = 0.00419), and Virginia (P = 6.63e−9). Significant differences were also observed in Maryland and Pennsylvania, but these regions had fewer than 50 respondents.In males, smoking prevalence rates were significantly higher in Appalachian counties compared to non-Appalachian counties, West Virginia contains no non-Appalachian counties for comparison, but the smoking tobacco rate of 25.8% and the smokeless tobacco rate of 15.9% are similar to that of other states with significant differences in the region Fig. b, top. IP < 2.2e−16, and non-Appalachian states, P < 2.2e−16 , Kentucky (P = 1.33e−9), Maryland (P = 0.02284), New York (P = 3.4e−9), Ohio (P = 9.38e−5), Pennsylvania (P = 1.44e−4), and Virginia (P = 0.0362). Female smokeless tobacco prevalence rates were significantly higher in Appalachian counties compared to non-Appalachian counties, P = 8.76e−4 and non-Appalachian states, P = 2.912e−05, and were significantly different than that of Appalachian males , P < 2.2e−16  within the CDC-defined HPV-associated oropharyngeal region. This disparity predominantly occurs in states with significantly higher male smoking and smokeless tobacco use, consistent with high risk-factor exposure in Appalachia known to contribute to increased HNSCC incidence25.With a majority of population and geographical coverage, our direct, non-exploratory analysis of HNSCC survival from available states representing all ARC-defined Appalachian subregions25. When stratified by stage, race and sex, our multivariate analysis indicates that the only significant difference in CRS occurs in white Appalachian stage IV male OC/P patients diagnosed under AJCC-637. RS values for stage IV white Appalachian and non-Appalachian male OC/P are higher than that of black males or black females, in agreement with a recognized national survival disparity for black OC/P cancers attributed to lower overall SES and cultural barriers11. In addition, female white stage IV OC/P patients have a lower CRS than male white stage IV OC/P regardless of Appalachian status, likely reflecting the lower rate of HPV-positive oropharyngeal disease in females39. Emerging national trends indicate that HPV-associated oropharyngeal cancers occur more frequently in younger, white male patients with limited tobacco use, and within rural areas38. These factors, coupled with blacks and white females having higher percentages of HPV-negative disease13 are congruent with HPV-positive and/or HPV-associated white male oropharyngeal patients having higher survival at the national level.Previous work evaluating Appalachian oral cancer survival using 2004 SEER data identified lower combined male and female survival in 10 states without consideration of stage or race41 , C10.1 (anterior surface of epiglottis), C10.2 , C10.3  and C10.4 . These oropharyngeal regions exclude palatine and lingual tonsils, as well as most other HPV-associated oropharyngeal sites containing the reticular epithelium lining the tonsillar crypts that constitute the primary sites of oropharyngeal HPV infection and neoplasia51. Higher aggregate tobacco use by Appalachian males may therefore result in more frequent carcinogen-induced malignancy at oropharynx subsites, resulting in a greater percentage of HPV-negative disease in the oropharynx and corresponding worse CRS, similar to that observed in other tobacco-heavy oropharyngeal cohorts53.Our findings also indicate that Appalachian smoking tobacco prevalence rates, represented by West Virginia, have been higher than national averages for several decades Fig. a, and wh54, where treatment de-escalation of HPV-associated oropharyngeal cancers continues to be evaluated57. Future efforts towards definitively determining the extent of HPV involvement in Appalachian OC/P and oropharynx through comprehensive p16 staining and PCR58 will be required to better clarify the predominant factors underlying oropharynx-driven, stage-based disparities in past and future Appalachian cohorts.The Appalachian-specific OC/P and oropharynx-specific disparities found in this study were diagnosed under the AJCC-6 timeframe, having clinical and pathological staging guidelines independent of HPV status. Restaging of HPV-positive oropharynx in 2018 under AJCC-8 due to the favorable prognosis of HPV-positive oropharyngeal cancers would shift most HPV-positive oropharynx in AJCC-6 to lower clinical stages. Such restaging would have the effect of potentially eliminating or downstaging the Appalachian male disparity described in this report. However, an additional ramification from this work is that male Appalachian or other populations with multi-factorial oropharyngeal tobacco exposure may actually be under-staged using current AJCC-8 guidelines. This is an important consideration, since National Comprehensive Cancer Network (NCCN) guidelines recommend staging and treatment dependent on p16 status60, underscore the need for the comprehensive tobacco history of any HPV-positive oropharynx patient to be considered prior to treatment. In addition to smoking, the significantly higher smokeless tobacco use by the male Appalachian population further increases the risk of tobacco-induced cancer at HPV-associated oropharyngeal sites, leading to oropharynx tumors that are either HPV-negative, or are HPV-positive but exhibit aggressive HPV-negative tumor behavior.While the current study covers the majority of the Appalachian population and is the most comprehensive study of HNSCC survival of the region to date, lack of available qualified survival data from five Appalachian states prevented complete assessment of survival in the region. The association between heavy aggregate tobacco use and poor male stage IV oropharyngeal survival in states with significantly different CRS suggests that stage IV oropharyngeal patients from states with Appalachian regions containing similar tobacco use patterns may also harbor disparate outcomes. Our findings, in conjunction with the poor survival of HPV-positive oropharynx patients with high smoking histories61. Inclusion of patient use of these products as standard registry variables should be considered for improved monitoring of tobacco-related disparities in future populations. The described male oropharynx disparity may also be present in male patients from other regions with heavy smoking, smokeless tobacco62 or betel-quid63 use, and should be monitored accordingly for similar poor survival and continued cessation intervention policies.These findings provide novel and in-depth insight into a specific demographic within a chronically underserved, rural population that is at higher clinical risk for poor OC/P outcome. Persistent high tobacco usage in Appalachia, in spite of increased tobacco cessation efforts, reinforces the need for continued targeted risk awareness. This includes emerging forms of supposed safer nitrosamine-containing products, such as e-cigarettes, that contribute to the cumulative patient tobacco loadSupplementary file1 (DOCX 774 kb)


The ESCRT-I factor Tsg101 is essential for sorting endocytic cargo and is exploited by viral pathogens to facilitate egress from cells. Both the nucleocapsid (NC) domain and p6 domain in HIV-1 Gag contribute to recruitment of the protein. However, the role of NC is unclear when the P(S/T)AP motif in p6 is intact, as the motif recruits Tsg101 directly. The zinc fingers in NC bind RNA and membrane and are critical for budding. Tsg101 can substitute for the distal ZnF (ZnF2) and rescue budding of a mutant made defective by deletion of this element. Here, we report that the ubiquitin (Ub) E2 variant (UEV) domain in Tsg101 binds tRNA in vitro. We confirmed that Tsg101 can substitute for ZnF2 when provided at the viral assembly site as a chimeric Gag-Tsg101 protein (Gag-ΔZnF2-Tsg101) and rescue budding. The UEV was not required in this context; however, mutation of the RNA binding determinants in UEV prevented Tsg101 recruitment from the cell interior when Gag and Tsg101 were co-expressed. The same Tsg101 mutations increased recognition of Gag-Ub, suggesting that tRNA and Ub compete for binding sites. This study identifies a novel Tsg101 binding partner that may contribute to its function in recognition of Ub-modified cargo. This motif binds the cellular ESCRT adaptor ALIX through its V domain. The Bro domain in ALIX associates with RNA that is bound to the NC domain in Gag , where α = 0.13 = (Hmax − Hmin) / (Nmax − Nmin) using backbone amide 1H and 15N chemical shifts [For binding studies using NMR spectroscopy, yeast tRNA  was added to  NMRPipe  and anal NMRPipe . Assignm NMRPipe . 1H/15N-eriments  owing tol shifts .The plasmid encoding HIV-1 Gag C-terminally tagged with green fluorescent protein (pCMV-Gag-EGFP) and the plasmid encoding full-length human Tsg101 N-terminally tagged with myc (pLLEXP1-hTSG101-myc) were previously described . Using s2, 1 mM EDTA, 1% Triton X-100, Roche cOmplete mini protease inhibitor cocktail) and centrifuged at 1000× g for 15 min. Supernatants were analyzed by Western blotting. Primary antibodies were: Rb anti-CA [293T cells (ATCC CRL-3216) were transfected with plasmids as indicated in the figure legends using Roche X-tremeGene transfection reagent . At 24 h post-transfection, media was filtered (0.45 micron), and pelleted through a 20% sucrose cushion . Pellets (virus-like particles) were resuspended in sample buffer and examined by Western blotting. For cell-associated Gag analysis, cell pellets were lysed  grown on poly-l-lysine treated cover slips were transfected with pCMV-Gag-EGFP alone or together with pLLEXP1-hTsg101-myc using Roche X-tremeGene transfection reagent. After 48 h, cells were fixed in 4% formaldehyde  and permeabilized in 0.1% Triton X-100/PBS. Tsg101 was detected in samples by indirect immunofluorescence using anti-myc Mab  and Texas Red tagged goat anti-mouse IgG . Nuclei were stained with NucBlue reagent (Thermo Fisher). Z-stack images were captured on an inverted fluorescence/differential-interference contrast (dic) Zeiss Axiovert 200M deconvolving fluorescence microscope operated by AxioVision Version 4.5 software . Deconvolution image processing used the constrained iterative method (Zeiss AxioVision software). Protein co-localization was assessed in cells by determination of Pearson’s coefficient of correlation of the entire cell using Image J software .Saccharomyces cerevisiae strain Y190  was used to test protein-protein interactions between HIV-1 Gag p6 or p6-Ub and Tsg101 wild-type or mutants using the Matchmaker GAL4 Yeast Two Hybrid beta-galactosidase assay . pGAD plasmids and pGBT plasmids were co-transformed into Y190 and selected on minimal media plates lacking leucine and tryptophan. Transformants were inoculated intoselective liquid media , grown overnight at 30 °C, and then supplemented with an equal volume of yeast peptone-dextrose-media (YPD) to promote rapid growth for 4 h at 30 °C. Cell density was measured by reading OD650. Yeast cultures (1 mL) were washed in Z Buffer  and resuspended in 0.5 mL reaction mix . Reactions (0.5 mL) were stopped by the addition of 0.25 mL of 1 M Na2CO3, cells pelleted, and the β-Gal signal read at OD415. A blank consisting of reaction mix was run in parallel and subtracted from the sample values. For the analysis of the Tsg101 mutants, two to three separate plasmid constructs were transformed and tested. Values were adjusted for cell density (OD650) and normalized to co-transformants of Tsg101 WT and p6 or p6-Ub run in parallel. Co-transformants of Tsg101 WT plus Gag p6 P7L (negative control) and Tsg101 WT plus Gag p6 2XPTAP (positive control) were run in parallel for each assay.The fact that (i), RNA is involved in the NC-Alix interface ,39,40; . AttemptTo determine whether binding tRNA might interfere with Ub binding, we took advantage of the fact that small molecules in the prazole family , panel A2-Tsg101 construct was sufficient to rescue the release of a mutant lacking ZnF2 (2 (creating Gag-ΔZnF2-Tsg101) promoted release of the Gag-ΔZnF2 mutant . Quantitative analysis (panel C) indicated that providing WT Tsg101 in the context of the chimeric Gag-Tsg101 protein to the ΔZnF2 mutant promoted egress of the mutant about five-fold. The UEV domain alone (aa 1–140) or extended to include the coiled-coil region  rescued ΔZnF2 to a lesser but reproducible degree . In contrast, determinant(s) downstream of the UEV (aa 140–390) had significant impact and more closely approximated the full-length Tsg101 protein . In all cases, the cell lysate signal was normalized for total protein content using the cellular protein actin as an internal marker . We conclude that the UEV region was not required when Tsg101 was provided at the budding site. This observation supports the conclusion that the NC domain contributes to Tsg101 recruitment, which is the function that is mediated through the UEV domain.Chamontin et al. demonstrated that providing Tsg101 at the assembly site in the context of the chimeric Gag-ΔZnF2 was co-expressed with the chimeric Gag-Tsg101 protein, two deletion mutations, Δ303-371 and Δ368-371, were engineered within the full-length Tsg101 protein (2 egress to a significant degree (panel 5B), indicating that the missing residues were critical. Finding that this region is required for egress of ΔZnF2 suggests that recruitment of the ESCRT-I partners is part of the NC contribution to budding rather than a role fulfilled by Tsg101 recruited by the p6 domain. Possibly, the Vps28 binding site on Tsg101 is not accessible prior to Gag recruitment of Tsg101 to the cell periphery and/or its recruitment requires the Gag/Tsg101 multimerization that occurs at the assembly site.Previous studies demonstrated that the C-terminal helical domain of Tsg101, in particular residues 303-371, binds to Vps28 . The corAs noted above, the UEV domain of Tsg101 recognizes K63-linked di-Ub . 2 binding, and electrostatic interactions, including tRNA binding to MA . Using lysates from cells expressing non-coding HIV-1 gRNA, GST-tagged NCp15, GST-tagged NCp9, GST-tagged NCp15ΔZnFn et al.  identifieraction ,54. Alteeraction ,59. We peraction ,60. An iA model suggesting that RNA binding interferes with recognition of UEV Ub-binding sites important for productive Gag-Tsg101 interaction is proposed in 2 rescue when Tsg101 was provided at the assembly site AP-Tsg101 interaction. Possibly, tRNA binding to the UEV facilitates and stabilizes Tsg101 recruitment by promoting interaction with NC-RNA. Any factor or event that disfavors the RNA-UEV interaction could permit the UEV Ub-binding site to interact with Ub molecules on Gag, Tsg101 itself or another ESCRT. Such “capping” might preclude chain growth beyond one or two molecules and, thereby, prevent non-productive targeting of the Tsg101-Ub-capped complex to the proteasome for degradation. Indeed, previous studies suggested the existence of two distinct types of E2/E3 substrates ,62. One te c.f., , howeverte c.f., . Conceiv


Disruption of DNA methylation patterns is one of the hallmarks of cancer. Similar to other cancer types, human papillomavirus (HPV)-driven head and neck cancer (HNC) also reveals alterations in its methylation profile. The intrinsic ability of HPV oncoproteins E6 and E7 to interfere with DNA methyltransferase activity contributes to these methylation changes. There are many genes that have been reported to be differentially methylated in HPV-driven HNC. Some of these genes are involved in major cellular pathways, indicating that DNA methylation, at least in certain instances, may contribute to the development and progression of HPV-driven HNC. Furthermore, the HPV genome itself becomes a target of the cellular DNA methylation machinery. Some of these methylation changes appearing in the viral long control region (LCR) may contribute to uncontrolled oncoprotein expression, leading to carcinogenesis. Consistent with these observations, demethylation therapy appears to have significant effects on HPV-driven HNC. This review article comprehensively summarizes DNA methylation changes and their diagnostic and therapeutic indications in HPV-driven HNC. Head and neck cancers (HNCs) are a diverse group of cancers arising in the upper aerodigestive tract, which includes the oral cavity, pharynx, larynx, nasal cavity, and paranasal sinuses . ConventThe oropharynx can be considered as the hotspot of HPV-driven cancers in the head and neck region, as the vast majority of these cancers arise in the palatine tonsils and base of the tongue ,7. TheseDisruption of normal methylation patterns is one of the hallmarks of cancer. These changes are often associated with the tumorigenic process and tumor characteristics, such as tumor progression and metastasis . HoweverPapillomaviridae family [Papillomaviruses are non-enveloped, icosahedral viruses, which belong to the e family . Over 40e family ,15. Papie family . These hThe oncogenic potential of HPV is mainly attributed to HPV oncoproteins E5, E6, and E7 . ThroughMoreover, HPV oncoproteins E6 and E7 are also known for their ability to interact with cellular epigenetic machinery . These iThe covalent modification of bases in the DNA strand by the addition of methyl groups is referred to as DNA methylation. In eukaryotes, DNA methylation primarily involves cytosine ,23. In hCytosine methylation is known to play a crucial role in genome stabilization. It is involved in gene imprinting, X chromosome inactivation, and repression of transposons and retroviral sequences in the genome . In syncDNA methyltransferases (DNMT) are the enzymes that catalyze DNA methylation and are involved in both the establishment and maintenance of DNA methylation. DNMT1 is responsible for the transfer of methylation patterns to the newly synthesized DNA strand following DNA replication . DNMT3A At the functional level, interpretation of the established epigenetic annotation involves many protein factors, such as the methyl-CpG-binding domain (MBD) family of proteins ,37. ThesDisruption of DNA methylation patterns is often observed in cancer. In many cancer types, it has been observed that the genomes of cancer cells undergo an overall decrease in the level of 5-methylcytosines, while having increased 5-methylcytosines in the regulatory regions ,42. In cSimilar to other cancer types, HPV-driven HNCs also reveal alterations in their methylation profiles ,46. HoweIt has been shown that global cytosine methylation levels are altered when p53 is inactivated ,48. WildThe ability of HPV E7 protein to promote E2F activity by downregulating retinoblastoma protein (pRb) also promotes DNMT1 transcription, as E2F transcription factors have the ability to activate DNMT1 promoter ,51. FurtStudies conducted to investigate methylation patterns of HPV-driven HNC have demonstrated the ability of HPV oncoproteins to promote DNMT activity. Many of these studies have also revealed a significant increase in methylation levels, especially in the promoter regions, in HPV-driven HNC ,52. MoreCDKN2A gene have been reported in several studies. This gene, positioned at 9p21.3, encodes two regulatory proteins, namely p16INK4a and p14ARF [CDKN2A gene resulting in expression changes have been observed in many types of cancer [CDKN2A expression is considered even more imperative in HPV-driven HNC, as p16INK4a expression itself is considered as an independent prognosticator of HPV-driven oropharyngeal cancer (OPC) [CDKN2A gene is expected to be active and to have hypomethylated or unmethylated regulatory sequences.Changes in methylation patterns of the d p14ARF . Both thd p14ARF , while pd p14ARF . Geneticf cancer ,80,81,82er (OPC) . HPV-drier (OPC) ,84. ThusCDKN2A locus in HPV-driven HNC compared to non-HPV-driven HNC [CKND2A has also been reported in salivary samples of HPV-positive HNC patients compared to healthy controls [Several studies have reported lower methylation levels in the iven HNC ,65,70. Tcontrols .CDKN2A gene compared to adjacent normal mucosa [CDKN2A promoter hypermethylation in HPV-positive HNC compared to normal control tissue [CKDN2A locus compared to precancer [CDKN2A hypermethylation in HPV-driven HNC in subjects with decreased P16 expression [CKDN2A methylation in HPV-driven HNC have not detected any significant methylation changes, indicating the heterogeneity of CKDN2A methylation patterns in HPV-driven cancers [In contrast to these findings, several other studies have suggested that the gene is hypermethylated in HPV-driven HNCs compared to their non-HPV-driven counterparts. Schlecht et al. 2015) reported hypermethylation in non-promoter CpG islands in the 5 reportel tissue ,60. Simirecancer ,87,88,89pression ,64. A si cancers ,72.RASSF1) gene located in the 3p21.3 position encodes for several protein isoforms containing a Ras association domain [RASSF1A is considered to have tumor suppressor properties and has been shown to be silenced by genetic and epigenetic mechanisms in several types of cancer [RASSF1 gene has been reported to be hypermethylated in HPV-related cancers, such as cervical cancer and penile cancer [RASSF1 gene in HPV-driven HNCs compared to non-HPV-driven HNCs [The Ras association domain family 1  in HPV-driven HNC [CDH11 locus also has been reported in HPV-driven HNC in a different study [CDH1 and CDH13, have been reported in cervical cancer [The cadherin family of proteins is considered as the major class of cellular adhesion molecules, which are known to play crucial roles in cell signalling and communication, especially in solid tissues . Proper  studies ,53,59. P studies . Furthernt study . Similarl cancer ,106,107.PCDHB11) locus has been reported to be hypermethylated in HPV-driven HNC compared to non-HPV-driven HNC [PCDH8, PCDH9, PCDHB3, PCDH10, PCDH15, PCDHB1, PCDHB4, and PCDHB15, has also been reported in HPV-driven HNC (53). When other HPV-associated cancers are considered, promoter methylation in PCDHA4, PCDH10, and PCDHA 13 has been reported in cervical cancer [Moreover, promoter hypermethylation of several protocadherin genes has also been reported in the literature. Among them, the protocadherin beta 11  gene has also been reported to be hypermethylated in HPV-driven HNC in a few studies . ITGA4 gene has also been reported to be hypermethylated in cervical cancer [Integrin alpha 4  acts as the natural inhibitor of MMPs and is known to play a role as a tumor suppressor [TIMP3 gene located at 22q12.3 has been reported in a few studies in HPV-driven HNCs compared to non-HPV-driven HNCs [Matrix metalloproteinases (MMPs), one of the families of natural endopeptidases, are capable of degrading extracellular matrix components and are known to play a significant role in tumor progression . Tissue ppressor ,120,121.ven HNCs ,67.ELMO1), encoded by the ELMO1 gene located at 7p14.2-p14.1, is known to promote cellular migration [Engulfment and cell motility 1 protein  reported the promoter of the iven HNC . The geniven HNC . A functLINE1) is one of the most abundant types of retrotransposons accumulated in the human genome, which accounts for approximately 17% of the total DNA [LINE1 have been inactivated by truncations, rearrangements, and mutations, and only several copies retain their ability for retrotransposition [LINE1 sequences [LINE1 region, in comparison to HPV-negative HNC, has been reported in HPV-driven HNC [LINE1 methylation in HPV-driven HNC compared to healthy controls is not clear, as it has been reported that HPV-negative tumors tend to have hypomethylated LINE1 regions [Long interspersed nuclear element 1 4CGGT . E2 bind4CGGT . However4CGGT . As such4CGGT ,146. Stu4CGGT ,148,149.4CGGT ,151,152.L1 and L2 genes have been reported to have higher methylation levels in cancers compared to low-grade precancer [Not only in viral LCR, CpG methylation has also been observed in other CpG sites of the HPV genome. In cervical cancer, viral recancer ,154. HPVrecancer . HoweverEven though studies have proposed methylation signatures characteristic to HPV-driven HNC, these signatures are not consistent among studies. Except for a few genes, most of the genes reported to be differentially methylated have been reported only in a single study. Thus, the methylation profiles of HPV-driven HNCs appear to be considerably heterogeneous. However, extrapolating the results from different studies and drawing conclusions are challenging issues, as methodologies of the studies are considerably dissimilar in terms of identification of the HPV status of the tumor, evaluation of the methylation status, and the comparisons used.The majority of studies have reported on methylation status by comparing HPV-driven and non-HPV-driven HNCs, an approach that does not allow identification of methylation changes from normal methylation patterns. Furthermore, these comparisons may erroneously identify hypermethylation in one group as hypomethylation in the other group. Despite these challenges, several genes and loci have been identified to be differentially methylated by independent studies. However, the available information is not sufficient to make firm conclusions. As such, more comprehensive multicentered studies with uniform methodologies are necessary to identify diagnostic methylation targets.L1 and L2 genes can be used to discriminate cervical cancer from low-grade precancer [The diagnostic value of HPV DNA methylation patterns also needs to be further investigated. Cervical cancer studies have suggested that methylation changes in HPV recancer ,154. EveThe majority of the studies have considered only HPV16, as it is the most common type involved in HPV-driven cancers, irrespective of the site. Studies that have considered other high risk (HR-HPV) types have not reported separate data for these HR-HPV types, possibly due to the lower number of samples. Even though these findings are generalized for HR-HPV, characteristic features may exist in cancers caused by different HPV types. However, such interpretations are not possible due to the paucity of available data.Despite the differences between studies in terms of their methodologies many studies have shown that HPV-driven HNCs have higher overall methylation levels compared to their HPV-negative equivalents ,46,52,53Consistent with these findings, demethylation therapy has shown to be effective against HPV-driven HNCs. In both HPV-positive HNCs and cervical cell lines, demethylating agent 5-aza-2′-deoxycytidine (DAC) has shown efficacy in downregulating HPV E6 and E7 expression . In addiTIMP3 gene, which encodes a natural metalloproteinase, is commonly seen in HPV-driven HNC [Furthermore, an increased interferon response in certain HPV-driven HNC cell lines and a decrease in matrix metalloproteinases (MMP) expression in both mouse models and HPV-driven HNC patients following demethylation therapy were reported in the same study . There iiven HNC ,67. ActiSeveral clinical trials have been conducted to evaluate the effectiveness of demethylation therapy on HNC . A speciMany changes in the host’s methylation landscape have been observed in HPV-driven HNC. However, the proposed methylation signatures are not consistent among studies; except for a few genes and loci, the vast majority have not been repeatedly reported in studies. Despite these inconsistencies, many studies have reported overall higher methylation levels in HPV-driven HNC. Furthermore, several genes that are known to be associated with tumorigenesis, tumor progression, and metastasis have been reported to be differentially methylated in HPV-driven HNC. In addition to methylation changes in the host genome, methylation changes in the HPV genome have also been reported. Consistent with these findings, demethylation therapy has been shown to have significant effects on HPV-driven HNC cancer.


Participation in screening was 60.8% among vaccinated, and 56.6% among unvaccinated, women (p < 0.0001). Detection rates (DR) for high-grade lesions were lower in vaccinated women . The DR of CIN3+ increased with age at vaccination, scoring respectively 0.0‰, 0.83‰, and 4.68‰ for women vaccinated when they were 15–16, 17–20, and 21–25 years old (p = 0.17). Conclusions: In comparison to unvaccinated women, higher compliance with cervical cancer screening invitation and lower CIN3+ DR among vaccinated women was observed. Age at vaccination was inversely correlated to vaccination efficacy.Background: Efficacy for cervical cancer prevention of opportunistic HPV vaccination in post-pubertal girls is lower than in 11-year-olds. Methods: Women born between 1986 and 1992 vaccinated at 15–25 years of age  and screened at 24–27 years of age were included. Frequency of opportunistic vaccination, overall and by birth cohort, was calculated; screening outcomes were compared between vaccinated and unvaccinated women. Results: Overall, 4718 (4.9%) HPV-vaccinated, and 91,512 unvaccinated, women were studied. The frequency of vaccination increased by birth cohort, ranging between 1.8% and 9.8%; age at vaccination decreased progressively by birth cohort ( Human papillomaviruses (HPVs) are responsible of epithelial infections that can either regress spontaneously or, less frequently, cause carcinomas and preneoplastic lesions. Persistent infection of the cervix by high-risk types is the cause of invasive cervical carcinoma .The natural history of cervical HPV infection and the long time between initial infection and lesion progression have led to the development of protocols for cervical cancer screening programs. Secondary prevention practice through population-based organized screening started in Italy in the late 1990s, and important decreases in both incidence and mortality have been obtained . The recSince 2007, prophylactic vaccines for the prevention of HPV infection by specific types have also been used. Three different formulations, targeting high-risk types only  for HPV16/18), or high- and low-risk types , for HPV16/18 and HPV6/11; nonavalent (9v) for HPV16/18/31/33/45/52/58 and HPV6/11), have been in place [v, for HPAn efficacy of 95–100% in preventing persistent infections and lesions related to vaccine types has been demonstrated by randomized clinical trials conducted for vaccine authorization . SubsequSince vaccination efficacy is type-dependent, vaccinated women are still in need of secondary prevention by cervical screening, but, owing to their reduced risk, less intensive protocols can be applied. In Italy, a national consensus conference defined tailored screening protocols for women vaccinated at 11–12 years  and highlighted the need of linkage between vaccination and screening databases, and of additional studies to optimize the screening interval .Here we present the results of a survey among young women of birth cohorts not included in active vaccination campaigns, living in the Veneto region . We investigated the frequency of opportunistic HPV vaccination and the outcomes of the first cervical cancer screening round in vaccinated girls, in comparison to non-vaccinated peers.The Veneto region (4.9 million inhabitants) is divided into nine local health units (LHU) that operate all prevention activities by following national recommendations and prevention plans. Procedures for periodic monitoring are in place for both primary and secondary prevention.Population-based cervical cancer screening  for women in the 25–64 age group has been active since 1997, the roll out phase being completed by 2002. From 1997 to the first months of 2015, all women were invited to undergo a pap smear every 3 years; thereafter, HPV-DNA testing every 5 years was implemented for 30–64-year-old women, while a pap smear every 3 years was maintained for women aged 25–29 years. The HPV screening protocol included HPV testing with cytology triage for HPV positives (HPV+) ; HPV+ woAn active campaign of HPV vaccination for girls born in 1996 was introduced in Veneto in 2008. Vaccination was free-of-charge up to the 18th (and later 25th) birthday for girls born from 1996 onward. 4v and 9v vaccines were used in 2008–mid2017, and from mid2017 onward, respectively. Vaccination coverage of girls ranged between 75 and 82%, with a recent decrease for the last birth cohorts . Women nThe study was performed in the following LHUs: Marca Trevigiana, Serenissima, Euganea, Pedemontana, and Scaligera. Although the COVID-19 pandemic precluded the inclusion of all the LHUs of the region, the study covered about 77% of the population living in Veneto.n = 491), and accounted for 0.5%  of the entire cohort.In this large cohort study, women resident in the study areas who were born between 1986 and 1992, and who had been invited for the first time by the screening program between 2011 and 2017, were identified. Through record linkage with the LHUs’ vaccination databases, we identified the women who underwent opportunistic HPV vaccination, and built two study cohorts: vaccinated and non-vaccinated. We included in the vaccinated cohort all the women: (i) who received at least one dose of vaccine, (ii) who were vaccinated (first dose) before the 26th birthday, (iii) whose vaccination date (first dose) was between January 2008 and December 2017, and (iv) who were vaccinated (first dose) before the date of the first screening invitation. The non-vaccinated cohort included non-vaccinated women and women who were vaccinated after the date of the first screening invitation; the number of the latter group was small  among vaccinated and non-vaccinated women, computed as the proportion of women with a CIN3+ lesion detected by the end of the follow up among all women who attended screening. The results of the two cohorts were also compared by calculating the relative risk (RR) along with 95% confidence intervals (CI). Results were reported overall and separately for women invited to cytology or to HPV testing, according to the LHU organization. Vaccinated women were analyzed overall, and stratified according to age at vaccination .For women invited to cytology, the following additional indicators were calculated: compliance with invitation; proportion of positive cytology (cyto+) among screened women, overall and by cytology grade (low grade (LG), including atypical squamous cells of undetermined significance (ASC-US) and low-grade squamous intraepithelial lesion (LSIL); or high grade (HG+), including atypical squamous cells-cannot exclude high-grade SIL (ASC-H), high-grade squamous intraepithelial lesion (H-SIL), atypical glandular cells favor neoplastic (AGC), adenocarcinoma in situ (AIS), squamous cell carcinoma, adenocarcinoma); detection of CIN3+ and CIN2+ among screened women; and positive predictive value (PPV) for CIN3+ of cyto+ at colposcopy.For women invited to HPV testing, the following indicators were reported: compliance with invitation; proportion of positive HPV (HPV+) among screened women; positive triage cytology among HPV+; detection of CIN3+ and CIN2+; and PPV for CIN3+ of HPV+cyto+ at colposcopy.2), and Fisher’s exact test in case of small sample size.Differences in outcome distributions among cohorts were tested using the chi-square test  and R-software environment, version 4.0.2.The Italian legislation identifies cancer registries as collectors of personal data for surveillance purposes without explicit individual consent. The approval of a research ethics committee was not required, since this study is a descriptive analysis of individual data without any direct or indirect intervention on patients.p < 0.0001). No vaccination before 17 years of age was observed in women born before 1991, compared respectively with 14.7% and 36.7% of vaccinated women born in 1991 and 1992 , with statistically significant differences both for women invited to perform cytology  and HPV testing . Compliance with first screening invitation was 20.7% higher for cytology protocol than HPV-protocol (p < 0.0001).Most women were invited to cytology-based screening (84.2%), and only 15.8% to perform an HPV test . Compliap = 0.24). No cancer was found among HPV-vaccinated, while 10 cervical cancers were detected in the non-vaccinated cohort , leading to a detection of 0.22 per 1000 screened women .Considering all the lesions detected in women screened both with cytology and with HPV test (including follow up), five CIN3+ were diagnosed in the vaccinated cohort and 174 in the non-vaccinated cohort. The detection of CIN3+ was halved in those HPV-vaccinated as compared with non-vaccinated . However, this difference was not statistically significant (p = 0.08). Overall, 18 CIN2+ were diagnosed in the HPV-vaccinated cohort  and 529 in the non-vaccinated cohort (11.71 × 1000), leading to a RR of 0.6 (95%CI 0.4–1.0) with borderline statistical significance (p = 0.02) when they were 15–16, 17–20, and 21–25 years old, respectively. The five CIN3 cases found among vaccinated women included one woman vaccinated at 17–20 years and four at 21–25 years. Age at vaccination affected the number of CIN2+ lesions detected . The detp = 0.86). A HG+ cytology was diagnosed in 0.6%  of HPV-vaccinated vs. 0.7%  of non-vaccinated women (p = 0.89). Among the 2715 women who were referred to colposcopy, compliance was 90.9% and 94.3% for HPV-vaccinated and non-vaccinated, respectively. The percentage of women who did not perform colposcopy because they reported that they had undergone a non-programmatic examination outside the screening centers was higher for HPV-vaccinated compared to non-vaccinated women . The detection rate of CIN3+ among cyto+ women was 2.68‰  overall; 1.48‰ among HPV-vaccinated (3/2021) and 2.75‰ for non-vaccinated women  (p = 0.49).Overall, 81,063 women were invited to screening with cytology. Among the 41,342 compliers, 2021 were HPV-vaccinated and 39,321 non-vaccinated . A positp = 0.4) . The PPVp = 0.33).During follow-up, one CIN3+ was diagnosed in HPV-vaccinated and 36 in non-vaccinated women. Considering all the lesions detected by the end of the follow up, the relative risk of CIN3+ for HPV-vaccinated was lower, although statistically non-significant . Among HPV positives, triage cytology was positive in 51.7% (31/60) in the HPV-vaccinated and 49.4% (545/1103) in the non-vaccinated. Overall, 576 women were referred to colposcopy with a compliance of 90.3% and 90.0% for HPV-vaccinated and non-vaccinated, respectively. The detection rate of CIN3+ was 2.74‰ (17/6216) overall, and similar for HPV-vaccinated (2.89‰) and non-vaccinated . The PPV for CIN3+ at colposcopy was 3.3% overall, 3.6% in the HPV-vaccinated and 3.3% in the non-vaccinated (p = 1).Overall, 15,167 women were invited to screening with HPV test. Among the 6215 compliers, 346 were HPV-vaccinated and 5869 non-vaccinated . Overallp = 0.51) (p = 1).Among HPV+cyto- women who repeated the HPV test after one year, HPV positivity was non-significantly lower for HPV vaccinated than for non-vaccinated  . At one-Cervical cancer prevention relies on the integrated use of HPV vaccination and screening. Vaccinated women will need to continue screening but, owing to the lower cancer risk conferred by vaccination, their screening protocols need to be modified. Our study was nested within a multicenter project aimed at evaluating the screening outcomes in women vaccinated within organized campaigns or as the result of a spontaneous decision, in order to gain data useful to define how to modify the screening protocols  for vaccinated women. We performed a survey on young women who spontaneously chose to be vaccinated at 15–25 years of age, and found that the frequency of vaccination increased over time  and that vaccinated women had a lower detection of high-grade lesions than their unvaccinated peers . However, the efficacy was inversely associated with age at vaccination. Our data are in line with those of other studies [Compliance with screening invitation was about 4% higher among vaccinated than unvaccinated women; higher uptake among vaccinated women was also reported in other studies ,17. Sincp = 0.24 and p = 0.08, respectively), most probably due to the low number of events  in the vaccinated group. A similar result was observed for the frequency of abnormal cytology in another Italian study, where the number of women in the two study cohorts was similar [In comparison to unvaccinated women, the detection of CIN3+ and of CIN2+ decreased by 50% and 60%, respectively, in vaccinated women. Such differences did not reach statistical significance  of the population living in the Veneto region, and the use of both screening protocols . The results add new information on the preventive attitudes of girls and women, and on the efficacy of opportunistic vaccination. On the other hand, the relatively low representation of vaccinated women (about 5%) in the study population and the absence of data on sociodemographic characteristics limit the generalizability of our findings.In conclusion, our survey indicates that implementation of HPV vaccination among adolescents, particularly before age 17, plays an important role in the prevention of cervical cancer (and possibly of other HPV-driven cancers).


High risk human Papillomavirus (HPV) infections ultimately cause cervical cancer. Human Immunodeficiency Virus (HIV) infected women often present with multiple high-risk HPV infections and are thus at a higher risk of developing cervical cancer. However, information on the circulating high-risk HPV genotypes in Kenya in both HIV-infected and HIV-uninfected women is still scanty. This study is aimed at determining the phylogeny and the HPV genotypes in women with respect to their HIV status and at correlating this with cytology results. This study was carried out among women attending the Reproductive Health Clinic at Kenyatta National Hospital, a referral hospital in Nairobi, Kenya. A cross-sectional study recruited a total of 217 women aged 18 to 50 years. Paired blood and cervical samples were obtained from consenting participants. Blood was used for serological HIV screening while cervical smears were used for cytology followed by HPV DNA extraction, HPV DNA PCR amplification, and phylogenetic analysis. Out of 217 participants, 29 (13.4%) were HIV seropositive, while 68 (31.3%) were positive for HPV DNA. Eight (3.7%) of the participants had abnormal cervical cytology. High-risk HPV 16 was the most prevalent followed by HPV 81, 73, 35, and 52. One participant had cervical cancer, was HIV infected, and had multiple high-risk infections with HPV 26, 35, and 58. HPV 16, 6, and 81 had two variants each. HPV 16 in this study clustered with HPV from Iran and Africa. This study shows the circulation of other HPV 35, 52, 73, 81, 31, 51, 45, 58, and 26 in the Kenyan population that play important roles in cancer etiology but are not included in the HPV vaccine. Data from this study could inform vaccination strategies. Additionally, this data will be useful in future epidemiological studies of HPV in Nairobi as the introduction or development of new variants can be detected. Human Papillomaviruses (HPVs) are divided into three groups . Group 1Compared to HIV-uninfected women, HIV-infected women are at an increased risk for HPV infection and tend to be infected with multiple genotypes of HPV –7. HIV-iA sequence of the L1 region of HPV is used for taxonomic analysis where more than 10%, 2-10% and less than 2% in sequence difference would represent different types, subtypes, and variants, respectively . PhylogeA cross-sectional study was done at the National Reproductive Health Clinic at Kenyatta National Hospital, a referral hospital in Nairobi, Kenya. This was after study approval by the National Ethical Review Committees at the Kenya Medical Research Institute and Kenyatta National Hospital. The Reproductive Health Clinic at Kenyatta National Hospital is a referral center for cervical cancer screening, family planning services, and fistula care.Recruitment of participants was done as they walked into the KNH Reproductive Health Clinic between August 2013 and April 2014. A minimum sample size was arrived at by using a HPV prevalence of 27% . HoweverA questionnaire was used to collect demographic information including age of the participants, marital status, level of education, and parity.All consenting participants were given pre- and post-HIV counseling and tested for HIV infection using the Kenya National HIV Testing Algorithm . DetermiThe patient was requested to get on the couch and lie on their back in a lithotomy position. A speculum examination was done, and the cervical os (opening of the cervix) was visualized. Cervical smears were then collected by a nurse by inserting a cytology brush into the endocervical canal making sure ectocervical and endocervical cells are taken. The brush was rotated one full turn and then removed gently. The cervical epithelial cells obtained were spread on a microscopic slide for cytology, after which the brush was immediately rinsed in vials containing virus transport media and the brush detached into the media. The vials were tightly closed and stored at -20°C awaiting viral DNA extraction, PCR amplification, and phylogenetic studies.The cervical smears were analyzed under the strict supervision of a cytotechnologist who was supervised by a resident pathologist at the Kenya Medical Research Institute. An independent pathologist and a second cytotechnologist were involved to ensure the quality of cytology results. The patients were called back for repeat pap smear if the sample was unsatisfactory due to blurring by blood, presence of a lot of pus cells, or insufficient cells to allow adequate assessment . Fixed sμl of RNAse and DNAse free water. PCR amplification of the HPV LI region was done using HPV consensus primers that target a 450 base pair region in the L1 open reading frame of HPV using the MY09/MY11 primers and then reamplified using the nested GP5+/GP6+ primers that amplify a 150 bp region [μl of the extracted product, 2.0 mM MgCl2, 500 nM MY09, 500 nM MY11, and 400 μM of dNTPs were used. The thermocycler programming was set as follows: initial activation at 95°C for 10 minutes followed by 40 cycles of denaturation at 95°C for 30 seconds, annealing at 48°C for 30 seconds, and extension at 72°C for 30 seconds [μl of the primary PCR product, 2.0 mM MgCl2, 500 nM of GP5+, 500 nM of GP6+, and 400 μM of dNTPs were used. The thermocycler programming was set as follows: initial activation at 94°C for 10 minutes followed by 40 cycles of denaturation at 94°C for 30 seconds, annealing at 43°C for 30 seconds, and extension at 72°C for 30 seconds. The final extension was at 72°C for 10 minutes. Amplitaq Gold Applied Biosystems was used in each PCR run. DNAse free RNAse free water was used as the negative control in each PCR run.Vials containing the cytology brush were thawed and vortexed to release the material from the brush into the medium. HPV DNA extraction was done for all the samples using the QIAamp DNA kit  following the blood and body fluid spin protocol. The DNA was eluted in 50 p region . L1 geno seconds . The finμl aliquot of the PCR product. Samples showing a band of approximately 140 bp were confirmed as positive for HPV [Electrophoresis was done using a 2% agarose gel with 5  for HPV , 23. Thep value was less than 0.05.Demographic data was analyzed using SPSS software version 18.0. A Chi-square test was used for comparison of categorical data. Fisher's exact test was used for data with a frequency of less than 5. Continuous data was represented in terms of means and standard deviation. Statistical significance was set when http://blast.ncbi.nlm.gov/blast.cgi. Representative sequences of the same type with unique differences were selected for phylogenetic analysis [The phylogenetic tree was constructed using the sequences of the L1 region. Partial sequences of the amplified HPV L1 region were edited in Chromas software Version 2.4.3. The sequences were then blasted on NCBI analysis . Referenanalysis . The evoanalysis . Initialanalysis .A total of 217 women were recruited into the study with a median age of 36 years, mean age of 35.73 years, and standard deviation of 7.4. Over half of the women (60.8%) were between 25 and 39 years while 78.8% (171/217) of the women sampled were married .p = 0.123). When HPV infection was assessed by marital status, single women had the highest rates of infection (p = 0.004). There was no association between HPV infection and level of education (p = 0.714), family planning (p = 0.072), and the number of children (p = 0.089).Out of the 217 samples, 68 (31.3%) were positive for HPV DNA by PCR . The prep = 0.022) and marital status (p = 0.001) were seen to significantly influence HIV infection  were infected with HIV. The mean age for HIV-infected women was 40.7 years with a standard deviation of 6.6 and a median of 42 years. Of the 29 HIV-infected women, 16 (55.2%) were over 40 years. All the six women (100%) who were widowed or divorced were infected with HIV while 15/171 (8.8%) of the married women were infected with HIV. Age (nfection .p = 0.031).The prevalence of coinfections of HPV and HIV was 6.5%. Fourteen of the 217 (6.5%) women studied had both HIV and HPV infection. HPV infections were significantly more prevalent in HIV-infected women (p = 0.028). Six out of the eight women with abnormal cytology were HIV-HPV coinfected. There was 100% HPV infection in women with HSIL and cancer while only 1 out of 3 patients with ASCUS was HPV infected. A total of 102 women had normal cytology (Eight of the 217 (3.7%) women had abnormal smears  with precytology . A furthcytology . Of the Out of the 68 positive samples, only 60 were successfully identified as being HPV genotypes using BLAST . The othA total of 7/29 (24.1%) HIV-infected women were infected with multiple high-risk HPV genotypes compared to 7/188 (3.7%) HIV-uninfected women . InfectiThe patient who had presented with adenocarcinoma had multiple high-risk infections. This patient had HPV 35, 58, and 26 which are all high-risk types. HPV-infected women with normal cytology results had all risk types of HPV. A woman with HSIL had only low-risk HPV 81 .The sequences of samples with single HPV infections were used for phylogenetic analysis. These included HPV 6, 11, 16, 31, 33, 35, 51, 52, 58, 66, 81, and 83. Among all the HPV 16 samples, two variants were detected. HPV 81 and HPV 6 samples also had two variants each. A representative of each of the variants was used for the analysis.Phylogenetic analysis was also able to cluster the HPV genotypes into high-risk types and low-risk types based on oncogenicity. Phylogeny clustered the sequences into two major groups. One that had HPV 51, 66, 81, and 83 and the second with the rest of the HPV types forming their own clade. This second clade was further clustered into three with HPV 6 and 11 forming a clade, HPV 16 variants forming another clade, and HPV 31, 35, 33, 52, and 58 forming a clade. Variant 1 of HPV 16 clustered with HPV 16 from Iran  while variant 2 clustered with HPV 16 from Africa specifically Mali and Congo .This study has described the HPV DNA prevalence of both HIV-infected and HIV-uninfected women attending the Kenyatta National Hospital Reproductive Health Clinic in Kenya. This clinic supports women for cervical cancer screening through pap test, family planning, fistula care, and STI clinic. Of these women, an overall HPV DNA prevalence of 31.3% is reported in this study. This is similar to the results of other studies in Kenya. Studies in Nairobi with 488 women and Tigoni with 438 women assessed HPV infection and cytology, and HIV infection revealed a HPV prevalence of 27% and 32.7%, respectively . This clThe prevalence of HPV was 28.7% in HIV-uninfected women and 48.3% in HIV-infected women. The high prevalence particularly for the HIV-uninfected women in this study may be due to high parity, increased number of sexual partners, and STI infection which are risky behavior for HPV acquisition . This hiThe prevalence of HPV in this study in women with normal cytology was 31.3% which is slightly higher than 20.7% reported in other studies previously done in Kenya . The preHPV 16 was the most prevalent type in this study 32.4%). The high prevalence of HPV 16 has also been demonstrated in Kenya and worldwide .4%. The , 36, 37.In the present study, one patient presented with adenocarcinoma after cytology examination. A cervical sample revealed multiple HPV infections of HPV 35, 58, and 26 which are all high-risk types. HPV 35 has been noted to be common in Africa compared to the rest of the world in women with adenocarcinoma . In a stThe prevalence of high-risk HPV types in Kenya that are not included in the HPV vaccines available is a major concern, especially for HIV-infected women. This emphasizes the need for a regionally tailored vaccine in Kenya since other high-risk HPV types circulating in Kenya seem to play important roles in cervical cancer etiology. A meta-analysis study in Kenya showed that in women with abnormal cytology high-risk HPV 16, 35, and 52 are prominent and HPV 16/18 is common in women with invasive cervical cancer , 37. AnoThe phylogenetic analysis was able to cluster the HPV types in the current study based on the genotypes in addition to their oncogenic potential and pathogenicity. Genotypes that group together share common carcinogenicity and the kind of host tissues they infect . CutaneoThe present study established a HPV prevalence of 31.3% and HPV-HIV coinfection of 6.5% among HIV-infected and HIV-uninfected women attending the Kenyatta National Hospital Reproductive Health Clinic in Kenya. This study showed that HPV 16 is the most prevalent HPV genotype in these women. This study also revealed the circulation of other HPV types: HPV 81, 35, 31, 51, 45, 73, 58, and 26 in the Kenyan population which play an important role in cancer etiology but are not included in the HPV vaccine. This study recommends fast-tracking HPV screening especially of HIV-infected women and those women with abnormal cytology. There is need to improve the current vaccine by including the other high-risk types prevalent in this region.


HPV16 genotype, viral load, physical status  and tumour p16INK4a expression were determined. Oral HPV16 prevalence was higher in OC than in OPMD, but this difference was not statistically significant (7.5% (8/106) versus 3.6% (3/83), odds ratio (OR): 2.18, 95% confidence interval (CI): 0.56, 8.48, p = 0.26). There was a significant association (p < 0.05) between oral HPV16 infection and heavy tobacco consumption. Real-time PCR results indicated that no integration events occurred in either OPMD or OC cases based on the HPV16 E2/E6 ratio. HPV16 positive OPMD and OC patients had similar HPV16 E2 and E6 viral loads. The inter-rater agreement between tumour p16INK4a expression and oral HPV16 infection was considered as fair (k = 0.361) for OC. Our data suggest that the involvement of HPV16 in oral carcinogenesis is limited.The role of human papillomavirus type 16 (HPV16) in oral potentially malignant disorders (OPMD) and oral cavity carcinoma (OC) is still under debate. We investigated HPV16 prevalence in unstimulated saliva, oral rinse samples, oral swabs and tumour biopsies collected from OPMD ( Oral cavity carcinoma (OC), which includes carcinomas of the mucosal part of the lip, is the most common subset of head and neck carcinomas (HNC), affecting approximately 300,000 patients annually worldwide . DespiteThe widely accepted risk factors for carcinogenesis of OC are tobacco consumption use and alcohol consumption. Ample evidence suggests that the oral potentially malignant disorders (OPMD), which include leukoplakia, erythroplakia, oral lichen planus, oral submucous fibrosis, actinic cheilosis, and snuff patch, may also contribute to the development of OC . In addiProgression of precursor lesions of HPV associated to invasive carcinomas is closely related with integration of HPV DNA into the human genome . Most clWhile HPV plays a significant role in OPC, to date it is unclear to what extent this also applies to OC. The first aim of this study was to determine the HPV16 prevalence in OPMD and OC using different sampling methods . The second aim was to investigate any associations between oral HPV16 infection and lifestyle risk factors  in OPMD and OC. The final aim was to investigate whether the integration of HPV DNA into the human genome was a critical factor in oral carcinogenesis.n = 86) or OC (n = 118) were recruited from the Royal Brisbane and Women’s Hospital, Logan Hospital, Princess Alexandra Hospital, University of Queensland Dental School clinics, and private dental practices (® p16INK4a Histology Kit (E6H4 clone) . p16INK4a was considered positive when there was a strong, diffuse nuclear and cytoplasmic staining pattern in the majority (>70%) of tumour cells. The clinical stages of OC patients were classified according to the American Joint Committee on Cancer  based on Tumour–Nodal–Metastasis (TNM). All participants gave written informed consent prior to sampling.This study was approved by institutional ethics committees from the University of Queensland [HREC No: 2014000679 and 2014000862], Queensland University of Technology [HREC No: 1400000617 and 1400000641], the Princess Alexandra Hospital [HREC Number: HREC/12/QPAH/381] and the Royal Brisbane and Women’s Hospital [HREC/16/QRBW/447]. A total of 204 patients who had been diagnosed with OPMD (ractices . The p16n = 85) and OC (n = 118), as described in our previous studies , this did not reach statistical significance. HPV16 in saliva fractions  correlated positively with the detection of HPV DNA in tumour biopsies of patients with OPMD and OC (n = 23) (The details of patients with OPMD ((n = 23) .p = 0.036).Patient clinical and epidemiological characteristics in relation to oral HPV16 infection are detailed in A purely episomal form of HPV16 with the E2/E6 ratio equal to or more than 1 was detected in all 11 HPV16-positive OPMD and OC cases, as summarized in 65 (61%) OC biopsies were examined by p16INK4a IHC analysis. A total of 19 out of 65 (29%) OC biopsies were positive for p16INK4a staining, while 46 (71%) were negative. Among the 19 p16INK4a-positive OC cases, 6 (32%) were positive for HPV16 DNA. On the other hand, 1 of the 46 (2%) p16INK4a-negative OC cases was positive for HPV16 DNA. The inter-rater agreement between tumour p16INK4a expression and oral HPV16 infection was considered as fair  for OC, as shown in Sensitivity 0.32 , Specificity 0.98 , Positive Predictive Value (PPV) 0.86 , Negative Predictive Value (NPV) 0.78 .HPV is the most common sexually transmitted infection, causing an estimated 630,000 (4.5%) new cancer cases globally ,22. GrowThe reported HPV prevalence in both OPMD and OC varies from 0% to 100% ,26. ThisWe found no statistically significant association between oral HPV16 infection and socio-demographic parameters, except for tobacco consumption. Heavy tobacco consumption has been found to facilitate HPV viral persistence, which may contribute to the malignant transformation of cervical cancer ,42. HoweHigh-risk HPV DNA integration into the human cellular genome, followed by the upregulation of E6 and E7, often trigger malignant transformation of cells in cervical and anal cancer as well as in OPC ,49. Our Based on decades of accumulated evidence, accurate HPV testing is crucial for clinical decision making and treatment planning in HNC patients . The curThe major limitations of the present study are the relatively small sample sizes, the limited availability of fresh tumour samples of OPMD and OC cases, and the use of saliva for HPV testing which might not reflect the HPV positivity in both OPMD and OC samples. Furthermore, additional studies will be needed to confirm whether our findings apply to all regions in Australia. In this study, p16INK4a IHC analysis was only performed in OC tumour samples with features suspicious of HPV infection. Finally, an additional robust method is needed for future studies of HPV integration events. In conclusion, we found a low oral HPV16 prevalence in both OPMD and OC. Interestingly, we observed a statistically significant association between oral HPV16 infection and heavy tobacco consumption. However, no integration events occurred in both OPMD and OC cases that were examined. Taken together, our results do not support a major role of HPV in oral carcinogenesis.


ADCY8, CDH8 and ZNF582 CpG-methylation as a predictive classifier of cervical cytology. This prospective, cross-sectional study used an independent cohort of residual liquid-based cytology for HPV genotyping and epigenetic analysis. Extracted DNA underwent parallel PCR using 3 primer sets for HPV DNA amplification. HPV-infected samples were genotyped by Sanger sequencing. Promoter methylation levels of 3 tumor suppressor genes were quantified by bisulfite-pyrosequencing of genomic DNA on the newest high-resolution PyroMark Q48 platform. Logistic model performance was compared, and model parameters were used to predict and classify binary cytological outcomes. A total of 883 samples were analyzed. HPV DNA positivity correlated with worsening grade: 125/237 (53%) NILM; 136/235 (58%) ASCUS; 222/229 (97%) LSIL; and 157/182 (86%) HSIL samples. The proportion of carcinogenic HPV-types in PCR-positive sequenceable samples correlated with worsening grade: NILM 34/98 (35%); ASCUS 50/113 (44%); LSIL 92/214 (43%); HSIL 129/152 (85%). Additionally, ADCY8, CDH8, and ZNF582 methylation levels increased in direct correlation with worsening grade. Overall, the multi-marker modeling parameters predicted binarized cytological outcomes better than HPV-type alone with significantly higher area under the receiver operator curve (AUC)s, respectively: NILM vs. > NILM (AUC 0.728 vs. 0.709); NILM/ASCUS vs. LSIL/HSIL (AUC 0.805 vs. 0.776); and <HSIL vs. HSIL (AUC 0.830 vs. 0.761). Our expanded findings validated the multivariable prediction model developed for cytological classification. The sequencing-based “Molecular Pap smear” outperformed HPV-type alone in predicting four grades of cervical cytology. Additional host epigenetic markers that evolved with disease progression decidedly contributed to the overall classification accuracy.Primary high-risk Human Papillomavirus (hrHPV) screening has recently become an accepted standalone or co-test with conventional cytology. Unfortunately, hrHPV singularly lacks specificity for cytopathological grade. However, mechanisms and markers of evolving virus-host interactions at the epigenome level may be harnessed as a better predictor of carcinogenesis. This study aimed to validate and expand the clinical performance of a multiparametric biomarker panel, referred to as the “Molecular Pap smear” based, on HPV genotype and  May 13, 2019 marked the 136th birthday of Dr. George Papanicolaou who was honored globally with an iconic image of his pioneering work on cervical cancer screening and the Papanicolaou (Pap) smear . Armed wOn World Cancer Day (4 February 2020), the World Health Organization (WHO) announced that a 60% increase in cancer cases worldwide is projected over the next two decades . CurrentADCY8, CDH8, and ZNF582 promoter hypermethylation as well as 3) grade of cervical pathology were quantifiable and distinctive.To circumvent the formidable economic and infrastructural requirements associated with cytology-based screening programs and limitations of commercial HPV diagnostics, we developed a molecular diagnostic test called “Molecular Pap smear” which is based on HPV genotyping and quantitative DNA methylation. Fundamentally, the test harnesses the evolutionary characteristics of the pathogen, the host and infected host-tissue throughout carcinogenesis for use as biomarkers . Our priIn this study, we aimed to validate and expand the clinical performance of our multiparametric biomarker panel with an independent sample set inclusive of four cytological categories . Secondarily, we sought to validate quantitative CpG-methylation by pyrosequencing (PSQ) on the newest high-resolution PyroMark 48 Autoprep platform, which to our knowledge has not yet been reported in the literature in contrast to the preceding models, Q24 and Q96 . The resn = 237), ASCUS (n = 235), LSIL (n = 229), and HSIL (n = 182)].This prospective cross-sectional study was conducted after approval by the Institutional Review Board of Brooke Army Medical Center (BAMC), Texas. Cervical specimens were collected from adult women ≥ 18 years of age undergoing cervical cytology screening. Cervical specimens with low cellularity (cell pellet volume < 200 uL) were excluded from analysis. Liquid-based cytology collected for clinical testing at the Department of Pathology of BAMC was consecutively procured after completion of analysis for cytological diagnosis. Samples were stored at room temperature until weekly batch DNA extraction. Demographic data were abstracted from the electronic health record (AHLTA) of the Department of Defense (DoD) and code-linked to each specimen. Four categories of samples were collected until target accrual numbers totaling 883 samples were met [NILM (The laboratory schema is illustrated in Cellular DNA extraction and HPV DNA amplification were performed as described previously . Brieflyappliedbiosystems.com), where a “high quality” Trace Score (TS)  was defined as ≥20 and a QV20 + value  as ≥100. Quality sequences were filter selected for entry into the Basic Local Alignment Search Tool (BLAST®) and queried against HPV sequences in GenBank® under Virus Taxonomy ID#151340  < 10E–50. For each sample, if the identified HPV genotype differed among the primer-specific amplicons, the genotype with the lowest E-value took precedence. Furthermore, if the E-values were equal between sequenced amplicons , the genotype was assigned in descending order of precedence by the primer-specific amplicon: E6/E7, MY09/11, and FAP59/64. The rationale for this ranking was based on the clinical significance of HPV E6/E7 over L1 gene function in respect to carcinogenic potential. The proportions of samples in which HPV was detected according to genotype and genotype-specific carcinogenic potential within each cytological category were compared.Sanger sequencing of the amplicons (∼200 ng DNA/sample) was performed by using sequencing primers MY11, FAP59, and GP-E6-3F at Eurofins Genomics . Sequence quality was assessed using the Sequence Scanner 2.0  per the manufacturer’s instructions. The PSQ assays including primer sequences were performed as described previously  was bisulfite-converted to convert unmethylated cytosine residues to uracil using the EpiTect Fast 96 Bisulfite Conversion kit (Qiagen) per the manufacturer’s instructions. Loci-specific PCR amplification of the bisulfite-converted gDNA (10–20 ng) was performed using 3 primer pairs targeting eviously . The PCRThe biotinylated PCR product was analyzed using high-resolution capillary gel electrophoresis (QIAxcel) for expected size in base pairs and adequacy of DNA concentration (>1 ng/uL) prior to PSQ . The PCRThe WHO International Agency for Research on Cancer (IARC) Working Group classifies HPV carcinogenic potential into three primary categories  (1) carcTo compare the prevalence of HPV genotypes grouped by carcinogenicity among the 4 cytological categories, the HPV genotype found in each sample was coded on an ordinal scale: HPV undetected (0), not classifiable/not carcinogenic (1), possibly carcinogenic (2), carcinogenic (3), and highly carcinogenic, (4). Cytology was also coded on an ordinal scale, NILM (0), ASC-US (1), LSIL (2), and HSIL (3), to determine the correlation between HPV carcinogenicity and cytological grade. For CpG-methylation levels (%), a percentile definition was used. The 95th percentile value for each CpG derived from NILM cytology (HPV-negative) was used as the cut-off for normal methylation (coded as 0); >95th percentile was deemed hypermethylated (coded as 1).ADCY8, CDH8, and ZNF582) and a binarized cytological outcome of interest. Outcome Model 1 aimed to distinguish normal (NILM) from abnormal (ASC-US/LSIL/HSIL) cytology, Model 2 distinguished NILM/ASC-US from LSIL/HSIL cytology, and Model 3 distinguished HSIL cytology from all others (NILM/ASC-US/LSIL). The covariates (CpG site(s) selected from each gene) that had the highest association with the response variable  were entered in a 2nd multivariable logistic regression jointly with HPV carcinogenicity to select the explanatory variables most predictive of the cytological outcome. The 2nd model equation is as follows:Preceding logistic regression modeling, missing data from the explanatory variables were handled by chained multiple imputation, which fills in missing values of multiple variables iteratively by using chained specifications of prediction equations based on the distribution of each variable . Multiva1,…, X4.Multiple explanatory variables: X1 = HPV carcinogenicity .X2 = ADCY8 CpG-site i methylation .X3 = CDH8 CpG-site i methylation .X4 = ZNF582 CpG-site i methylation .XBinarized Model 1 Outcome (Y) coding: NILM (0), ASC-US/LSIL/HSIL (1).Binarized Model 2 Outcome (Y) coding: NILM/ASC-US (0), LSIL/HSIL (1).Binarized Model 3 Outcome (Y) coding: NILM/ASC-US/LSIL (0), HSIL (1).For the final regression models, post estimation receiver operating characteristic (ROC) curves were constructed and predictions at specified values were computed. After estimating the classification threshold or cut-off for each model by using Youden’s index (maximum sum of sensitivity and specificity), diagnostic performance characteristics were determined . Of noteN = 306 and n = 153 per group was required. The quota sampling strategy assured adequate representation from each cytological grade. Additional samples were collected to compensate for potential sample inadequacy and laboratory errors.This study was designed to have a 90% power to detect a 10% difference in DNA methylation (%) between successive categories of cytology. From the literature, locus-specific promoter methylation levels (%) for NILM, LSIL/HSIL and cervical cancer have ranged from 0–5%, 15–30%, and 30–60%, respectively . To detep-values < 0.05 were considered statistically significant. Statistical analyses were performed using STATA/IC 16.0 (StataCorp LP).Data were summarized using means (95% CI), medians (IQR), and proportions. For hypothesis testing, Wilcoxon rank sum and Kruskal-Wallis tests were used for non-parametric, numerical, or ordinal data. Categorical data were compared using the chi-square test. Correlation between ordinal variables was determined by Spearman’s rho. p < 0.05): NILM 237/883 (27%); ASC-US 235/883 (26%); LSIL 229/883 (26%), and HSIL 181/883 (21%). Sample #503 was classified as HSIL/SCC and the 66-year old patient was subsequently diagnosed of Stage IIA invasive SCC. This sample thus served as the positive control for this study. The median concentrations of extracted DNA among the 4 cytological categories were adequate and statistically equivalent    .n = 640) increased coincidently with cytological grade: NILM (27%), ASC-US (37%), LSIL (41%), and HSIL (82%) .HPV prevalence determined by PCR and gel electrophoresis increased significantly with worsening grade: NILM (53%), ASC-US (58%), LSIL (97%), and HSIL (86%) . SimilarIL (82%) . ConversThe HPV genotype distribution of 577 sequenced cytology samples spanned the continuum of IARC-defined carcinogenic potentials . The remA representative Neighbor-Joining tree constructed from reference sequences of 57 HPV genotypes (one for each genotype identified in the 577 sequenced samples) is presented in ADCY8, CDH8, and ZNF582 except for ADCY8 at CpG sites 1-5 . Pairwise comparisons of methylation for each CpG site between cytological grades  revealed significantly higher levels at multiple sites for the worse grade denoted by a star in ∗p < 0.05 by the Wilcoxon rank-sum test). The upper limit of normal for CpG-methylation levels summarized as the median of the 95th percentile of each CpG site per assay were: ADCY8 (10.11%), CDH8 (7.61%), and ZNF582 (5.22%). Positive control sample #503 bore methylation levels 2-fold and 3-fold that of NILM cytology for ADCY8 and CDH8/ZNF582 assays, respectively . Overall, the number of missing observations for HPV genotype 63/883 (7.1%) and site-specific CpG-methylation ranging from 1 to 9/883 (≤ 1%) were low prior to imputation and predictive modeling. The variables with counts of missing observations are listed in ROC curve analysis after multivariable logistic regression for three logit models are presented in CpG site . The besCpG site . Additiocytology . All thrPredicted probabilities plots of binarized cytological outcomes using HPV carcinogenicity as a singular or integrated predictor variable are shown in HPV carcinogenicity and host loci-specific methylation as predictors of cytological outcome are shown in The diagnostic performance characteristics of the three logit models were presented in ADCY8, CDH8, and ZNF582 in addition to the four cytological grades . PCR-sequencing revealed a steep rise in the proportion of carcinogenic genotypes as cytology progressed to HSIL with the 3 topmost being HPV-16 (45%), HPV-58 (10%), and HPV-31 (9%). In contrast, the possibly carcinogenic and non-carcinogenic HPV genotypes declined precipitously in prevalence and diversity indicative of extinction of the “weaker competitors” within the dynamic virus-host ecosystem. This phenomenon, demonstrated previously by our deep sequencing study, may be explained by the principles of competitive exclusion followed by clonal expansion of HPV-infected transformed cells . The comADCY8, CDH8, and ZNF582 and cytological grade   . The loc DNMT3B) . However DNMT3B) . High-re DNMT3B) .Model refitting was performed due to sample size expansion, ASC-US sample inclusion, and PSQ technological advancement in this cohort. The combination of HPV carcinogenicity and methylation markers remained significant predictors of cytological outcome after multivariable logistic regression. The addition of methylation status improved the sensitivity and/or specificity for the binarized outcome of interest for all 3 models. The predicted probability for the outcome escalated in a stepwise fashion as HPV carcinogenicity reached its pinnacle, i.e., HPV-16. This finding is consistent with a longitudinal study where HPV-16, in comparison to other carcinogenic HPV types, was found to convey a uniquely elevated risk for severe cervical intraepithelial neoplasia (CIN3 +) . FurtherDiscriminatory performance of the 3 multi-parametric models demonstrated greater accuracy than the univariate HPV carcinogenicity. Specifically, models 1 and 2 inclusive of methylation markers showed greater sensitivity and a lower negative likelihood ratio. This implies that HPV with methylation markers performed better at predicting absence of disease (more true negative results). Conversely, model 3 performed better at predicting presence of disease (more true positive results) with greater specificity and a higher positive likelihood ratio of 5.55. Likelihood ratios, akin to signal-to-noise ratios, are robust measures of diagnostic accuracy that are independent of disease prevalence . This stADCY8, CDH8, and ZNF582 has expanded recently and hypermethylation of one or more of these loci have been found in cancers of the breast, oropharynx, esophagus, and anus  expressed herein are those of the authors and do not reflect the official policy or position of Brooke Army Medical Center, the United States Army Medical Department, the United States Army Office of the Surgeon General, the Department of the Army, the Department of the Air Force, or the Department of Defense or the United States Government.Presented virtually at the 33rd International Papillomavirus Conference (IPVC 2020) on July 23, 2020.Primary sequence data will be deposited in the NCBI GenBank upon patent issuance.This study was approved by the institutional review board of Brooke Army Medical Center, Fort Sam Houston, Texas.JS-G conceived and designed the study and analyzed and interpreted the data. JS-G, QX, WS, and HA participated in the acquisition of data and wrote the manuscript. All authors read and approved the final manuscript.The United States Army Medical Research and Development Command has filed a patent application on the invention described herein. The inventor is JS-G. No potential conflicts of interest were disclosed by the other authors.


TTN, are emerging as a common cause of myopathies. The diagnosis of a TTN-related myopathy is, however, often not straightforward due to clinico-pathological overlap with other myopathies and the prevalence of TTN variants in control populations. Here, we present a combined clinico-pathological, genetic and biophysical approach to the diagnosis of TTN-related myopathies and the pathogenicity ascertainment of TTN missense variants. We identified 30 patients with a primary TTN-related congenital myopathy (CM) and two truncating variants, or one truncating and one missense TTN variant, or homozygous for one TTN missense variant. We found that TTN-related myopathies show considerable overlap with other myopathies but are strongly suggested by a combination of certain clinico-pathological features. Presentation was typically at birth with the clinical course characterized by variable progression of weakness, contractures, scoliosis and respiratory symptoms but sparing of extraocular muscles. Cardiac involvement depended on the variant position. Our biophysical analyses demonstrated that missense mutations associated with CMs are strongly destabilizing and exert their effect when expressed on a truncating background or in homozygosity. We hypothesise that destabilizing TTN missense mutations phenocopy truncating variants and are a key pathogenic feature of recessive titinopathies that might be amenable to therapeutic intervention.Mutations in the sarcomeric protein titin, encoded by The online version contains supplementary material available at 10.1007/s00401-020-02257-0. TTN gene, which assembles the primary ~ 100 kb transcript from 364 exons in a 300 kb gene  utations . It is pTTN pathogenic variants previously reported , demonsent 4 in  (includeThe impact of TMD/LGMD2J-linked mutations in Ig-169 (M10) and HMERF-linked mutations in Fn3-119 have been attributed to misfolding and/or thermal destabilisation of the domains . AlongsiIt is striking that structural “mirror images” of five of the twelve missense variants in our cohort have previously been linked to titinopathies. Analogous to Fn3-119 being a hotspot for HMERF-linked mutations, particular residue positions within titin domains may be hotspots for titinopathies, at least in trans with truncating variants; this observation may be of importance for the interpretation of missense variants identified in future.TTN truncating/missense variants is very similar to that found in patients carrying two recessive truncating variants, raising the question how these recessive TTN variants impact on the titin protein in vivo [TTN missense variants on proteostasis could be a key pathogenic feature of recessive titinopathies, a hypothesis supported by the observations of variant titin fragments co-localising with p62/SQSTM1 in C2C12 and HEK293 cells. We hypothesise that TTN missense variants can derail proteostasis by inducing local cleavage or accelerated protein turnover, causing disintegration of titin  or cleaD/LGMD2J . AlteratTTN-related myopathies, and emphasizes the need for a combined clinico-pathological, genetic and molecular approach to optimize diagnostic accuracy. Rare missense variants should be experimentally assessed at the protein domain level, with thermal destabilisation by more than approximately 15 degrees or complete misfolding/unfolding of the expressed domain supporting a pathogenic diagnosis for the variant when inherited in trans with a second TTN truncating or destabilising missense variant. These criteria should also prove helpful to assess the possible impact of suspicious missense variants in cardiomyopathies.The present study offers clear strategies addressing the challenges of an accurate assessment of patients with suspected Supplementary file1 (XLSX 19 KB)Supplementary file2 (PDF 20076 KB)Supplementary file3 (XLSX 82 KB)Below is the link to the electronic supplementary material.