The availability of Medicare Part D pharmacy coverage may increase veterans’ options for obtaining medications outside of the Department of Veterans Affairs (VA) pharmacies. However, availability of Part D coverage raises the potential that veterans may be receiving similar medications from VA and non-VA pharmacies. The VA’s personal health record portal, My HealtheVet, allows veterans to self-enter the non-VA medications that they obtained from community-based pharmacies, including those reimbursed by Medicare Part D. The Blue Button medication view feature of My HealtheVet allows veterans to view and download their VA and self-entered non-VA medication history.To examine whether the use by veterans of the Blue Button feature of My HealtheVet was associated with less acquisition of similar medications from VA and community-based pharmacies reimbursed by Medicare Part D.This study included a national sample of veterans who were new My HealtheVet users during fiscal year 2013  and who used the Blue Button medication view feature of My HealtheVet at least once (users). We compared these veterans with a random sample of veterans who were not registered to use My HealtheVet (nonusers). From these groups, we identified veterans who were enrolled in Part D. We used multiple logistic regression analysis to assess the association of Blue Button medication view use with obtaining medications from the same drug classes (with overlap of 7 or more days) from VA and Part D-reimbursed pharmacies.P < 0.001). A larger percentage of users than nonusers obtained medications from VA and Part D-reimbursed pharmacies with overlapping days supply from the same drug classes . However, for veterans who obtained greater numbers of 30-day supplies (82 or more), a significantly smaller percentage of users than nonusers obtained overlapping medications from VA and Part D-reimbursed pharmacies. Moreover, controlling for the total number of 30-day supplies that veterans received, the odds of obtaining medications from VA and Part D-reimbursed pharmacies with days supply that overlapped by at least 7 days for the same drug classes was 18% lower for users than nonusers (P=0.002).There were 7,973 My HealtheVet medication view users and 65,985 nonusers. During a 12-month period, medication view users received more 30-day supplies of medications  than nonusers, on average (152.1 vs 71.3, Veterans who used the Blue Button medication view feature of My HealtheVet obtained a larger number of 30-day supplies of medications from VA pharmacies than nonusers. For veterans who obtained a larger number of 30-day supplies of medications, use of the Blue Button medication view feature of My HealtheVet was associated with less overlap in days supply of medication from the same drug class from VA and Part D-reimbursed pharmacies. What is already known about this subjectHealth care providers and patients have previously reported that use of personal health portal features such as the Blue Button feature of the Department of Veterans Affairs (VA) My HealtheVet patient portal can improve aspects of care coordination; however, effects on medication use are unknown.What this study addsThis study found that veterans using the Blue Button medication view feature of the My HealtheVet patient portal received more medications from VA pharmacies.Among veterans receiving larger numbers of medications, use of the Blue Button medication view feature of the My HealtheVet patient portal was associated with less acquisition of similar medications from VA and community-based pharmacies reimbursed by the Medicare Part D prescription drug benefit.1 Moreover, 46.8% of the US veteran population (over 9.1 million veterans) are enrolled in or use Department of Veterans Affairs (VA) health care.2 Veterans who receive care at VA health care facilities may obtain prescription medications from VA pharmacies. Many of these veterans have complex health care needs because they have multiple chronic conditions, need highly specialized care, and receive health care from VA and non-VA providers.6 Consequently, many of these veterans may be receiving medications from VA and non-VA prescribers. The US Medicare system is a national health insurance program for individuals who meet the age requirement, have a disability, or have end-stage kidney disease. For veterans who meet 1 or more of these requirements, non-VA care may be covered by the Medicare insurance program. In the Medicare system, Medicare Part D is an optional federal government program, which went into effect in January 2006 to create an outpatient prescription drug benefit to help Medicare beneficiaries, including veterans who are also receiving care at VA health care facilities, pay for self-administered prescription drugs. The availability of the Medicare Part D prescription drug benefit may facilitate access to non-VA medications. In 2018, the Survey of Veteran Enrollees’ Health and Use of Health Care estimated that approximately 17% of veterans enrolled in VA health care were also enrolled in Medicare Part D.7Approximately 13% of all adults in the United States are veterans, including over 50% of men who meet Medicare’s age requirement (≥ 65 years).8The availability of Medicare Part D prescription drug coverage may increase options for veterans to obtain medications. For example, VA users who are enrolled in Medicare may be receiving medications from non-VA prescribers that are reimbursed under Medicare Part D because of recent stays at non-VA hospitals, preferences for specialty care outside the VA, or closer proximity of non-VA providers to their homes. This additional source of coverage raises the potential that veterans may be receiving similar medications from VA and non-VA pharmacies. If veterans are treated by multiple VA and non-VA prescribers with limited information sharing, the VA’s ability to limit possible duplication of therapy and prevent untoward consequences of polypharmacy might be inhibited.11 including information sharing with their health care providers about their medications.12 Veterans can access the My HealtheVet portal and use its various features through multiple platforms, including web browsers accessed on a computer, tablet, or smartphone. The Blue Button feature in the portal enables veterans to access and download a copy of their VA health records into a text, PDF, or XML file that can be read, printed, or saved and then shared with health care providers.14 The Blue Button medication view feature provides access to information about the prescriptions processed by VA pharmacies in the previous 15 months and all medications self-entered into My HealtheVet by the veteran.15Online personal health record portals such as the VA’s My HealtheVet portal have tremendous potential to support access and organization of information about an individual’s health,17 However, other pilot randomized controlled trials of Blue Button that have compared the medical records of providers who care for veterans receiving VA and community-based care did not reveal improvements in medication reconciliation.18 Whether use of personal health record features such as Blue Button is associated with decreased acquisition of similar medications from multiple health care systems remains unknown.Health care providers and patients have previously reported that use of personal health portal features such as Blue Button can improve aspects of care coordination.In this study, we examined whether veterans’ use of the Blue Button medication view feature of the My HealtheVet patient portal was associated with less acquisition of similar medications from VA and community-based pharmacies reimbursed by the Medicare Part D prescription drug benefit.eVet use among veterans receiving VA health care, including effects on VA health care use and dual use of services from VA and community providers reimbursed by Medicare. The focus of this analysis was the association of My HealtheVet use with acquisition of similar medications from VA and community pharmacies. The study included a national sample of veterans who were newly authenticated users of My HealtheVet during fiscal year 2013  and who used the Blue Button medication view feature at least once (users). We compared these Blue Button users with a random sample of veterans who were not registered to use My HealtheVet .Data were collected as part of a retrospective analysis that examined My HealtheVet Blue Button medication view feature, the index date was defined as the date of the first use of this feature. For nonusers of My HealtheVet, the index date was July 1, 2013. The mean number of months on Medicare Part D was 9.5 for veterans in the medication view user group and 10.8 in the My HealtheVet nonuser group during the 12-month period following the index date. This study was approved by the Institutional Review Board at the Edward Hines, Jr. VA Hospital.From these 2 groups, we identified veterans who were also enrolled in Medicare Part D for at least 1 month following the index date. Veterans who were deceased, aged younger than 18 years or older than 104 years, or missing data on variables included as covariates in adjusted models  were excluded from the sample. For veterans who used the My Health19 The Centers for Medicare & Medicaid Services (CMS) requires that insurance companies submit data to CMS on all prescriptions that have been dispensed and paid through the Part D program. These prescriptions are recorded in the Prescription Drug Event file. The Part D Slim file contains a subset of variables from this file that are of particular interest to researchers .Medication acquisition was assessed during the 12-month period following the index date. We obtained data from the VA Managerial Cost Accounting (MCA) National Data Extract (NDE) Pharmacy datasets and the Medicare Part D “Slim” file. Medication acquisition was measured as the number of 30-day medication supplies  and the number of different drug classes that veterans received from VA and Part D-reimbursed pharmacies. The drug classes were based on the VA Drug Classification system, which separates drugs, supplies, and diagnostics into different categories based on their characteristics. Drug classes in this system may vary in their level of specificity; however, this classification system provides general categories of drugs and mostly follows the American Hospital Formulary Service drug classifications.For medications from VA pharmacies, the VA drug classes were obtained from the VA MCA NDEs. To assign VA drug classes to medications in the Part D Slim file, we linked records in this file with the VA’s National Drug File using National Drug Code numbers. The VA National Drug File contains product-level information about medications dispensed by VA pharmacies such as the product’s National Drug Code number and VA drug class. To assess whether veterans obtained similar medications from VA and community-based pharmacies, we determined the percentage of veterans who received medications from the same drug class with overlapping days supply from VA and community-based pharmacies reimbursed by the Medicare Part D drug benefit.Data for medications from the community-based pharmacies that we used to assess overlapping days supply was obtained from the Medicare Part D Slim file. Overlap of medication supplies from VA or community-based pharmacies of 7 days or more was operationalized dichotomously .20 The distance between the nearest VA facility to the veteran and the center of the ZIP code associated with the veteran’s address was used to estimate distance to the nearest VA. A veteran’s VA enrollment group, a classification system used to determine copayments for VA services based on disability rating, income, and other factors , was determined using the VA Enrollment file. The socioeconomic status of the veteran’s geographic area was estimated using data on the median household income in the veteran’s county of residence from the Area Health Resources Files. ZIP code information was used to determine the urbanicity of the veteran’s residence.21 Overall health status was estimated through the CMS Hierarchical Condition Category (HCC) risk-adjustment model for community-dwelling populations.23Characteristics were assessed during the 12-month period after the index date. Information about veterans’ characteristics were obtained from the VA Medical SAS Databases and included sex, age, race, ethnicity, and US geographic region of residence .eVet usage data.Registration for My HealtheVet and use of the Blue Button medication view feature were obtained from VA My Health24 We calculated the propensity score for each veteran as the predicted probability of using the Blue Button medication view feature from multiple logistic regression analyses of patient characteristics shown in 24 We calculated the SDs in characteristics between the groups to ensure that characteristics were similar between comparison groups after weighting.Analyses were conducted using Stata version 14 (StataCorp). To balance characteristics between users and nonusers, we used propensity score weighting.25To examine the types and sources of medications, we assessed the number of 30-day supplies and the number of different medication classes that veterans received from VA, Part D-reimbursed, or both types of pharmacies. We compared these between users and nonusers. We also examined how medication acquisition was distributed between VA and Part D-reimbursed pharmacies. Additionally, for all pharmacy use groups, we examined the most frequently occurring drug classes for which the days supply of medications from VA or Part D-reimbursed pharmacies overlapped by 7 or more days, a time period used previously to assess medication overlap.26 We assessed whether a veteran had an overlap of medication supplies from VA or community-based pharmacies of 7 days or more as a dichotomous variable .To assess the association of Blue Button medication view use with obtaining medications from VA and community-based pharmacies with days supply from the same drug class that had overlap by 7 or more days, we used multivariable logistic regression analysis with double-robust estimation.26 Additionally, we determined the proportion of veterans in each group with 7 or more days supply overlap from the same drug class. We compared these proportions between the user and the nonuser groups overall and by decile of the number of 30-day supplies of medications that veterans obtained.With double-robust estimation, the logistic regression model included covariates and was estimated with inverse probability weighting as previously described. Results will be unbiased with double-robust estimation if either the propensity score or outcome (in this case logistic regression) model are specified correctly.There were 73,958 veterans who met the study inclusion and exclusion criteria: 7,973 were Blue Button medication view users, and 65,985 were nonusers. P < 0.001; P < 0.001). Combining VA and Medicare Part D-reimbursed pharmacies, users obtained on average (SD) 152.1 (106.0) total 30-day medication supplies; nonusers obtained, on average, 71.3 (49.1) total 30-day supplies (P < 0.001).During the 12-month period following the index date, users obtained on average (SD) 135.3 (108.4) 30-day supplies of medications from VA pharmacies, whereas nonusers obtained on average 41.9 (46.6) 30-day supplies of medications from VA pharmacies . On average, 49.0% of these classes (5.1/10.4) were from VA pharmacies only; 43.3% (4.5/10.4) were from non-VA pharmacies only; and 9.6% (1.0/10.4) classes were from both VA and non-VA pharmacies.Users obtained medications from an average (SD) of 12.0 (6.3) different VA drug classes. On average, 69.2% of these classes (8.3/12) were from VA pharmacies only; 22.5% (2.7/12) were from Part D-reimbursed pharmacies only; and 6.7% (0.8/12) classes were from both VA and Part D-reimbursed pharmacies . In compP < 0.001). However, the percentage of patients with overlap varied by the total number of 30-day supplies of medications that a veteran obtained. In P = 0.05); for veterans with more than 153 thirty-day supplies, the percentage of users with overlapping days supply of medication was 12 percentage points lower than for nonusers .For veterans with 82-96 thirty-day supplies, the percentage of users with overlapping days supply of medication was 4 percentage points lower than for nonusers , controlling for the number of 30-day supplies of medications that veterans received. Other characteristics associated with greater odds of having overlapping days supply of drug classes from VA and Part D-reimbursed pharmacies included age more than 45 years, living in an urban area, living further from a VA facility, and obtaining a larger number of 30-day supplies from VA pharmacies.Results from the double-robust estimation in The top drug classes for which the days supply from VA and non-VA pharmacies overlapped by 7 or more days are presented in eVet, this was because these users tended to have a higher number of prescriptions to fill.Veterans who were using the Blue Button medication view feature of the VA’s personal health record portal My HealtheVet obtained over 3 times the number of 30-day supplies of medications from VA pharmacies and over twice the number of total 30-day supplies from all sources  as nonusers. Nearly a third of users and nearly a quarter of nonusers obtained prescriptions with overlapping days supply of 7 or more days for medications from the same drug classes from both VA and Part D-reimbursed pharmacies. Although the overall percentage of veterans with overlapping days supply was significantly larger for veterans who used the Blue Button medication view feature of My HealtheVet’s health information management and communication features may be especially attractive to patients who are managing complex chronic diseases, and those managing multiple medications may be more likely to adopt the portal because of the convenience of online prescription refills and the Blue Button medication view feature.My HealthThe percentage of veterans with overlapping days supply from the same drug classes varied by the total number of 30-day supplies that veterans obtained. Among veterans with a need for a greater number of 30-day supplies of medications, the percentage with overlapping days supply was lower for veterans who used the Blue Button medication view feature than for nonusers. Moreover, adjusting for the number of medication supplies, the odds of obtaining overlapping days supply was over 18% lower for users.These findings highlight that a substantial portion of veterans receive medications with overlapping days supply from the same drug classes from both VA and non-VA pharmacies. However, among higher medication users, use of the Blue Button medication view feature of the VA’s personal health record portal was associated with less polypharmacy compared with veterans who had not signed up to use the VA’s personal record portal. Consequently, it might be useful for prescribers to encourage their patients who are obtaining larger numbers of medications to use the Blue Button medication view feature of My HealtheVet to assist with management of their prescription medications.28; however, patients remain the most important source of information about all medications that they are taking. This necessitates additional investigation and communication between providers and patients to ensure optimal medication reconciliation and continuity of care.For patients acquiring their medications from VA and non-VA pharmacies, the VA may have limited information of the patients’ non-VA medications. Efforts are underway to enhance information sharing across VA and non-VA settingsThis communication is particularly important because situations in which providers in one health care system do not know about medications prescribed by providers in another health care system may pose a safety risk, which is compounded by this study’s finding that some of the medications with overlapping days supply from VA and Part D-reimbursed pharmacies are drugs that can be dangerous if not used correctly. For example, among the 10 most frequent drug classes with overlapping days supply are opioid analgesics for which patients are at high risk of death secondary to opioid overdose.29 Use of the Blue Button medication view feature of the personal health record portal may enhance medication reconciliation and information sharing across health care systems, which may be warranted, since multiple previous studies have shown possible associations between dual health system use among veterans and increased morbidity and mortality.33 It should be noted that the Blue Button medication view includes only VA prescriptions and the non-VA medications that veterans self-enter into their personal health records, which may differ from the non-VA medication list in the VA’s electronic medical record. However, efforts are underway to make the non-VA medication list available in the patient portal too.There is limited information on medication reconciliation across health systems. One review suggests that medication reconciliation within health systems has the potential to identify many medication discrepancies and reduce potential harm.eVet—increased their ability to have an accurate medication list and assisted in making medication treatment decisions.16 Moreover, 50% reported that they did not order a laboratory test or another procedure because of information in the Continuity of Care document.16Results from previous studies assessing the potential for My HealtheVet to decrease duplication of services suggest that use of the Blue Button medication view feature might facilitate information sharing across health care systems. In an interventional study, 90% of providers stated that the Continuity of Care document—a standardized electronic file containing a VA health summary report that patients can share with health care providers available through the Blue Button feature of My Health18 Although not all veterans will download health care data and share it with their health care providers, a tool such as the VA Blue Button medication view feature of My HealtheVet may complement provider-mediated health information exchange until health care systems are designed to allow providers in different organizations to access key information, such as medications, across health care systems.In another study , veterans who were trained to share their Continuity of Care documents with non-VA providers had significantly fewer duplicate laboratory tests than the control group.There were limitations to these analyses. We only examined non-VA pharmacy data for veterans enrolled in Medicare Part D. Private-sector data were not available for medications that were not reimbursed by a Part D prescription plan. Consequently, our results provide a lower bound estimate of the percentage of VA enrollees who have overlapping medications from VA and non-VA pharmacies.There may be multiple approaches to assessing misuse of medications. In this study, we focused on a potential issue  that could arise when veterans are obtaining medications from VA pharmacies and community-based pharmacies that are covered by the Medicare Part D drug benefit. Additionally, the Blue Button medication view includes VA medications but only non-VA medications that veterans have self-entered into their personal health records. The non-VA medication list in the VA electronic medical record may differ from the Blue Button non-VA medication list. The effect of this potential inconsistency is uncertain.It should also be noted that ZIP codes were used to determine rural/urban status, but a veteran may have relocated during the study period. We used the HCC risk score to estimate overall health status of veterans; however, this health status may change over time.eVet features , reduced medication overlap could be a result of these services, as well.There may be different implications from overlapping days supply due to the same drug vs overlap due to a physician-directed change in treatment. However, we were unable to make this source distinction from our data. Moreover, because the viewing of the medication is highly likely to be correlated with other My HealtheVet may be different from those not using the feature because of unobservable factors .17Tying polypharmacy to adverse drug events was beyond the scope of this study; however, we recognize that this would be an important topic for future research. In addition, veterans using the Blue Button medication view feature of My HealthVeterans who used the Blue Button medication view feature of My HealtheVet obtained a larger number of 30-day supplies of medications from VA pharmacies than nonusers. For veterans who obtained a larger number of 30-day supplies of medications, use of the Blue Button medication view feature of My HealtheVet was associated with less overlap in days supply of medication from the same drug class from VA and Part D-reimbursed pharmacies than for nonusers. These results highlight the importance of sharing information and the need to educate patients about communicating with VA and non-VA providers about their medications.


The data were gathered in September 2022 using computer-assisted telephone interviews. Most surveyed parents reported trusting their child’s physician regarding vaccine recommendations (89.2%) and vaccinated their child with all or most of the vaccines recommended by a national vaccination guideline (94.7%). However, 13.3% declared themselves as moderate or strong vaccine opponents, a group characterized by high (83.4%) distrust in physicians. There was no difference in the awareness of HPV in groups varying in trusting the physicians, but parents who trusted them were more frequently aware of the HPV vaccine. Parental willingness to vaccinate their child against HPV was highly differentiated by the level of trust in the child’s physician. The results highlight that trust in physicians is a critical factor shaping decisions for children’s vaccination, stressing a continuous need to improve strategies to communicate with patients.The vaccination of children against human papillomavirus (HPV) effectively prevents HPV infection and HPV-related cancers in women and men. However, HPV vaccination programs are met with vaccine hesitancy, which varies between countries. The coverage in Poland is low, although introducing nationally funded HPV vaccination for girls aged 12–13 in mid-2023 may increase it. The uptake of the HPV vaccine in adolescents is highly affected by parental decisions, which in turn can be influenced by interactions with the physician. The present representative study aimed to analyze the acceptance of the HPV vaccine among Polish parents ( As a major cause of cervical cancer (over 95% of cases), HPV remains a global issue . HPV is There are currently three HPV vaccines available worldwide: (1) a bivalent vaccine against HPV types 16 and 18 ,13; (2) According to the World Health Organization (WHO), as of the first quarter of 2023, 125 countries have introduced HPV vaccination in their national immunization programs . The higIn Poland, vaccination has been recommended for girls aged 12–13 years since 2008, with a catch-up program offered to girls aged 14–18 years from 2008 to 2012. However, for a long time Poland remained the only country in the European Union not to introduce reimbursed HPV vaccinations in the national immunization program. HPV vaccinations were exclusively local and scarcely funded  until miVarious factors can influence the parental decision to reject HPV vaccination of children, including perceived insufficient or inadequate information and knowledge about the vaccine, fear of side effects, mistrust in health authorities, doubts about the vaccine’s effectiveness, and low perceived risk of HPV infection or cervical cancer ,37,38,39Taking into account the risks arising from the currently low level of HPV vaccination in Poland, the opportunity to increase it due to the recent reimbursement vaccination program in adolescents, and the importance of physician–patient trust in the context of vaccination, the present study evaluated parents’ attitudes towards their children’s HPV vaccination with a particular focus on the level of trust in vaccination in the pediatrician/general practitioner who takes care of their children aged 9–15 years. Based on a literature review, an analysis of the studies conducted, and social and medical knowledge, we hypothesized that those parents who declare greater trust in the physician caring for their child declare greater willingness to vaccinate them against HPV.The present survey was conducted in September 2022 and involved 360 parents of children aged 9–15 years. A stratified random sampling technique was employed to ensure the sample’s representativeness . We prioThe data were gathered using computer-assisted telephone interviews (CATIs) conducted by trained interviewers who asked the questions from the questionnaire and entered the responses using specialized software. The software ensured the coherence of the answers and set control questions to maintain the survey’s quality. Furthermore, the responses were added to the database in real-time to minimize the risk of data loss. The present study utilized a survey questionnaire tailored explicitly for research purposes and developed by the authors, who have extensive expertise in sociological, methodological, and medical domains. To ensure the questionnaire’s accuracy and appropriateness for the study, an interdisciplinary team conducted an ad hoc validation process. The questionnaire comprised 18 questions, comprising nine metric and nine factual questions. All the questions were of the single-choice type, with some being dichotomous. The metric parameters included gender, age, education level, number of children, and gender of the youngest child. The factual questions assessed the participants’ attitude towards vaccination, level of trust in vaccine recommendations given by their child’s doctor, and willingness to vaccinate their child against HPV. The selection and phrasing of questions were based on our previous experiences in analyzing sociological and sociomedical issues in the context of vaccination ,47,48,49To guarantee the validity and reliability of the survey questionnaire, a pilot study was conducted involving 12 parents of children aged 9–15. It allowed us to assess the questionnaire’s conceptual validity, methodological soundness, and structural correctness. The results of the pilot study were not included in the main study but were helpful in refining the questionnaire for subsequent administration to a larger sample size. p-value of less than 0.05 was deemed statistically significant in all analyses. The demographic variables of the surveyed group were presented with descriptive statistics. The outcome variable was focused on the HPV vaccine, and the relationship between variables was evaluated by employing the Chi-squared test. All statistical analyses were performed using IBM SPSS Statistics v. 29.0.0.0 . A The survey was carried out by the Biostat, a research unit with Research and Development Center status registered under the Minister of Entrepreneurship and Technology in Poland. This registration guarantees that the survey was conducted ethically and complies with international ethical requirements for quantitative research. The study followed Polish law regarding protecting the subjects’ data and followed the ethical guidelines for implementing sociomedical research. The study did not have the nature of a clinical trial, and no sensitive data were collected during the study, so the consent of the ethics committee, according to Polish law, was not required. Each subject was informed about the purpose of the study and gave informed consent to participate. The study was anonymous and confidential. The study’s results were analyzed collectively, making it impossible to identify a specific person from the study’s results. The sociodemographic characteristics of the surveyed parents of children aged 9–15 years are summarized in p < 0.001) (Most respondents reported trusting their child’s doctor regarding their vaccination recommendations (89.2%) and vaccinated their child with all or most of the vaccines recommended by a national vaccination guideline (94.7%). The lower the trust in the doctor, the statistically significantly lower the percentage of parents who vaccinated their child with the available vaccines, according to the current vaccination calendar (< 0.001) .Based on the provided declarations, the studied parents were divided into four groups depending on their general attitude toward vaccines: (i) strong supporters (34.7%), (ii) moderate supporters (51.9%), (iii) moderate opponents (10.0%), and (iv) strong opponents (3.3%).p < 0.001)  . The dif< 0.001) .p = 0.052) (p = 0.005) (The frequency of parents who heard about HPV did not differ significantly between groups with varying levels of trust in the vaccination recommendations given by their child’s doctor (= 0.052) A. Howeve= 0.005) B.p < 0.001)  .The present study shows that the parental level of trust in a child’s physician is associated with better adherence to national guidelines for childhood vaccination, better awareness about HPV and the HPV vaccine, and willingness to vaccinate a child against HPV. The results indicate that trust is a critical factor in healthcare, especially for children. Studies show that patients who trust their healthcare providers are more likely to follow medical advice, have better outcomes, and have higher satisfaction with their care ,51,52. PAlthough vaccines are medical products, the decision to receive them is a social phenomenon that numerous factors, including trust in healthcare providers, can influence. The parents surveyed in the present study declared a relatively high trust in their children’s physicians, and most of them adhere to national childhood vaccination guidelines. These results indicate that there is a good groundswell of the wide acceptance of HPV vaccination among Polish parents. However, one should note that refusals of compulsory vaccines for children doubled in Poland over the last five years and have risen 21-fold since 2010 . MoreoveOur study shows that those parents who declare greater trust in the doctor caring for their child in the context of vaccination declare a greater willingness to vaccinate their child against HPV. The review by Harrington et al. indicates that trust in the doctor to vaccinate a child against HPV is very important, but other functional  and social  factors that may—despite high trust in the doctor—influence the ultimate failure to vaccinate a child cannot be ignored . MoreoveHowever, one should note that ensuring appropriate messaging for HPV vaccination is not limited to the physician–patient interaction. The studies show that the attitudes of healthcare providers toward the HPV vaccine can be influenced by their trust in the stakeholders involved in designing and implementing the HPV vaccination strategy . TherefoWe wish to stress study limitations that pertain to the methodology employed. Respondents may exhibit a Halo Effect when using the CATI technique to conduct surveys, which causes them to provide expected responses instead of expressing their factual thoughts and knowledge. Such an effect can particularly occur when assessing attitudes toward sensitive subjects such as child vaccination. A limited sample size was included in the study, if compared with the total population size of Poland. The findings might be reliable; however, the representativeness might be biased. One should also note that the present research was conducted at a time when national HPV vaccinations were about to be introduced in Poland, and, therefore, they may serve as a reference point for further studies on attitudes during the ongoing vaccination campaign.This study highlights that parental trust in the medical doctors taking care of their child is critical in the decision to vaccinate them against HPV. There is a groundswell for good acceptance of HPV vaccination among parents in Poland, but an effort must be undertaken to ensure good-quality and honest communication with those who oppose vaccines, declare distrust in healthcare providers, and are not willing to vaccinate their children against HPV.


Five-year overall survival (OS) and five-year relapse-free survival (RFS) rates were 74.6% and 69.9%, respectively. Our multivariate analysis showed that T category (T1–4a) and hemoglobin levels (≥13.7) were significant favorable prognostic factors for OS, while T category, performance status, and p16 overexpression were significantly associated with RFS. In patients with p16 overexpression, OS was 100% and RFS was 90%. Our findings suggest that p16 overexpression is a reliable surrogate marker for transcriptionally active HPV infection and predicts a favorable prognosis.p16 overexpression is often used as a surrogate marker for human papillomavirus (HPV) infection in oropharyngeal squamous cell carcinoma but remains an uncertain diagnostic tool for HPV-related sinonasal squamous cell carcinoma (SNSCC). Our study involved 79 consecutive SNSCC patients who were treated at a tertiary referral university hospital during 2006–2021. We retrospectively examined their clinical characteristics and conducted p16 immunohistochemistry and HPV detection. We found that 12.7% of the patients exhibited p16 overexpression, which was significantly more common in the nasal cavity and increased from 2015 onward. The HPV was a high-risk type and viral loads ranged from 4.2 to 1.6 × 10 Sinonasal malignancies, although infrequent, account for about 3–5% of all head and neck cancers . From 20High-risk human papillomavirus (HPV) types are well-established culprits in oropharyngeal squamous cell carcinoma (OPSCC) . In receThis study investigated in detail the diagnostic precision of p16 immunohistochemistry for detecting HPV DNA. Additionally, we aimed to shed light on the clinical features and survival outcomes associated with HPV-related SNSCC.In this retrospective observational study, we reviewed the clinical records of patients diagnosed with SNSCC (both keratinizing and nonkeratinizing SCC according to the update in the 5th edition of the WHO classification ) betweenAll participants provided written informed consent before the collection and analysis of tumor samples. This study was approved by the Institutional Review Board of the University of the Ryukyus (project ID: 156) and complied with the ethical guidelines of the 1975 Declaration of Helsinki, as revised in 2008.A multidisciplinary team, consisting of head and neck surgeons, radiation oncologists, and reconstructive surgeons, participated in pre-treatment evaluation and decision-making. This evaluation entailed an exhaustive review of the patient’s medical history, physical examination, performance status assessment, serum chemistry profiles, complete blood cell count, chest X-ray, computed tomography (CT), and magnetic resonance imaging (MRI). Positron emission tomography combined with CT was performed to identify lymph nodes or distant metastases.Data on clinical parameters and oncological outcomes were recorded up to the end of the follow-up period on 31 July 2023. We determined clinical and pathological tumor staging in line with the Union for International Cancer Control (UICC) TNM Classification  .Several parameters for nutritional status and general condition were assessed before treatment, including hemoglobin (Hb), albumin (Alb), neutrophil–lymphocyte ratio (NLR) , C-reactAfter primary treatment, we regularly checked for locoregional recurrence and distant metastasis through physical examinations, CT and/or MRI, and head and neck endoscopic examinations.2, two or three times triweekly), was applied to the primary site and/or neck within 6 weeks postoperatively for cases with close/positive surgical margins or extracapsular lymph node extension. In patients with renal issues and those aged over 75 years, radiation therapy was prioritized as the postoperative adjuvant treatment instead of CRT.Patients requiring total maxillectomy underwent combined neck dissection with reconstructive surgery in addition to removal of the primary lesion. Endoscopic sinus surgery was chosen for limited primary lesions where assured surgical margins were anticipated. Typically, postoperative radiation therapy (60 Gy), supplemented with platinum infusion (100 mg/m2) and nedaplatin (80 mg/m2) were administered to the target lesions through the deployed microcatheters two or three times every 4 weeks.This protocol, which has been described previously , is summ® p16 histology kit  [We assessed p16 expression using the CINtecGermany) . The thrGermany) ,22. p16 Cases showing p16 overexpression underwent further testing by polymerase chain reaction (PCR) analysis and HPV DNA in situ hybridization. For PCR, DNA extracted from fresh frozen tumor samples was processed using the MY09/MY11 and GP5+/GP6+ degenerate consensus primer sets targeting the L1 region, as documented in previous studies . The fulE6 and E2 genes of HPV strains 16, 18, 33, and 52. The assay system was designed to quantify the viral load and discern the viral integration status [We also introduced a novel quantitative real-time PCR assay system targeting the n status   and relapse-free survival (RFS). Events were defined as death due to any cause for OS and as recurrence at the primary site, neck lymph node recurrence, or distant metastasis for RFS.p-value of <0.05 was considered statistically significant, and all analyses were performed using JMP Pro 15.0.0 .A p = 0.004, chi-squared test). A temporal trend was observed, with p16 overexpression becoming more common in patients treated after 2015 .The clinical characteristics of the patients are shown in Most patients were diagnosed with T4 (58.2%) and stage IV disease (68.4%). Treatment modalities included radiation-based treatment (RT/CRT) in 61 patients (77.2%), with the remaining 18 patients (22.8%) undergoing radical surgery followed by adjuvant RT/CRT-based treatment according to the pathological findings. Laboratory and nutritional variables did not show significant differences between the two tumor types . There wOf the 79 patients with SNSCC, 10 (12.7%) exhibited p16 overexpression. 6 copies/ng genomic DNA, with each case displaying viral integration into the host genome . Although the 5-year OS rate for the p16-overexpression group was 100% (compared with 71.2% for the p16-negative group), this difference failed to achieve statistical significance by the log-rank test  and Hb levels ≥ 13.7 g/dL (p = 0.035). Since all patients with p16 overexpression were alive, the multivariate analysis did not provide a hazard rate.In multivariate analysis considering the T category, Hb levels, and CRP, the significant prognostic factors for OS were T1–4a . Since these nutritional indicators confound each other, mGPS and ECOG PS were included in the multivariate analysis. In the multivariate analysis of RFS, which included the T category, Hb levels, mGPS, ECOG PS, and p16 overexpression, T1–4a (p = 0.004), ECOG PS 0 (p = 0.026), and p16 overexpression (p = 0.012) were identified as significant prognostic markers.As visualized in E6/E7 mRNA expression of the HPV gene, which is considered to most accurately reflect active transcriptional infection, prevalence rates tend to decrease by approximately 25% [n = 10), and thus there might be a risk for bias in the present results. Further study is needed to confirm the importance of p16 overexpression in SNSCC, as shown in the present study, including the survival benefit, the characteristics of tumor location, and the increasing trend.The reported prevalence of HPV in SNSCC varies widely, ranging from 8.9% to 62% ,26,27,28tely 25% . While tIn OPSCC, the role of p16 overexpression as a surrogate marker for detecting active HPV infection has been well-established due to its robust predictive and prognostic value . However5 and 2.69 × 105 copies/ng DNA (median 2.666 × 104 copies/ng DNA). In contrast, the present study’s HPV-16 and HPV-33 viral loads in SNSCC ranged from 4.2 to 1.63 × 106 copies/ng DNA. Notwithstanding the limited sample size, viral loads in SNSCC did not significantly deviate from those in OPSCC, and all types showing p16 overexpression exhibited viral integration. These insights affirm the critical role of HPV, particularly in its relation to p16 overexpression, in shaping the landscape of SNSCC.Insights into the viral load and integration status of SNSCC remain scarce. In this investigation, we provided data on HPV DNA viral load and viral integration status for SNSCC with p16 overexpression . Our obsThe location of HPV-related sinonasal cancer remains unclear. Previous reports showed no significant difference in HPV prevalence among sinonasal regions . RecentlThe availability of HPV status in OPSCC increased with each subsequent year of diagnosis from 2008: 0.1–0.2% for 2004–2008, 1.4% for 2009, 30.6% for 2010, 45.6% for 2011, and 56.9% for 2012 . Recentlp16 overexpression combined with HPV DNA testing might be a reliable surrogate marker for HPV-related SNSCC and an accurate prognostic marker. High-risk HPV infection was the most frequently detected in the nasal cavity, and the prevalence of HPV-related SNSCC is increasing in Japan as in the United States. A larger multicenter prospective study is needed to clarify the prognostic significance of high-risk HPV infection in SNSCC patients treated with a multimodal approach.


Corallococcus coralloides. The linear peptide structure contains an unprecedented ‐γ‐N‐methyl‐β‐hydroxy‐histidine moiety. Corramycin exhibits anti‐Gram‐negative activity against Escherichia coli (E. coli) and is taken up via two transporter systems, SbmA and YejABEF. Furthermore, the Corramycin biosynthetic gene cluster (BGC) was identified and a biosynthesis model was proposed involving a 12‐modular non‐ribosomal peptide synthetase/polyketide synthase. Bioinformatic analysis of the BGC combined with the development of a total synthesis route allowed for the elucidation of the molecule's absolute configuration. Importantly, intravenous administration of 20 mg kg−1 of Corramycin in an E. coli mouse infection model resulted in 100 % survival of animals without toxic side effects. Corramycin is thus a promising starting point to develop a potent antibacterial drug against hospital‐acquired infections.Herein, we describe the myxobacterial natural product Corramycin isolated from  Corallococcus coralloides. The structure, extraordinary total synthesis and biosynthesis of the antibiotic is described for the first time. Its promise as an in vivo septicemia model, the absence of cross‐resistance with commonly used antibiotic classes, and the lack of cytotoxicity make Corramycin a potential new drug in the fight against multidrug‐resistant pathogens.Corramycin is a novel natural product produced by the myxobacterium  Enterobacterales, such as E. coli, have been ranked as critical priority by the World Health Organization (WHO).+ value of 1184.56, which could not be matched to known natural products in SciFinder and DNP database searches. Thus, we purified this natural product that was named Corramycin (1) from the fermentation broth of ST201330 shake flask cultures. Notably, we also identified another strain, C. coralloides MCy10984, producing the same compound. Detailed analysis of the 1D and 2D NMR spectra revealed the two‐dimensional structure of Corramycin , hydroxylated (3), double‐hydroxylated (4), and hydroxylated plus glycosylated (5) Corramycins .Corramycin exhibits a linear peptidic structure with eight α‐amino acids including several unique structural features such as the unprecedented γ‐E. coli strains and some other important human pathogens were determined. Good antibiotic activity was observed against E. coli ATCC35218 with a MIC of 1–4 μg mL−1, but also against additional E. coli strains, including MDR ones, and Salmonella typhimurium (S. typhimurium) (4 μg mL−1)  against several Staphylococcus aureus, Enterococci, Pseudomonas aeruginosa and Klebsiella pneumoniae (K. pneumoniae) (Supporting Information Table S4). To investigate if Corramycin exhibited a different MoA as compared to the antibiotics classes commonly used in the clinic, we assessed the MICs of Corramycin, Tobramycin, Cefotaxim, Cefoxitin, Ciprofloxacin, Tetracycline, and Rifampicin against 16 clinical isolate E. coli strains, which are classified Carbapenem‐resistant, Aminoglycoside‐resistant, or Quinolone‐resistant (Supporting Information Table S5). Notably, we could not observe cross‐resistance to any of the other antibiotics.However, Corramycin showed only weak or no activity against several other clinically relevant Gram‐positive and Gram‐negative pathogens such as comKLMNO, encoding a 12‐modular hybrid NRPS‐PKS assembly line (Supporting Information Table S6). To identify additional genes putatively belonging to the BGC, such as genes encoding tailoring enzymes, we determined the BGC borders by comparing the genomic regions surrounding comKLMNO in both producer strains with the phylogenetically closely related non‐producer strain C. coralloides DSM2259. Fifteen putative genes were identified that presumably belong to the Corramycin BGC .We next aimed for the identification of the corresponding BGC to gain insights into the biosynthesis and the stereochemistry of the unique structure of Corramycin. Considering the peptidic structure combined with the N‐terminal dihydroxy butyric acid and the 5 ‐amino‐2,3‐dihydroxy‐4‐methoxy valeroyl moiety, we assumed that Corramycin was produced by a hybrid NRPS‐PKS. Thus, we sequenced the genomic DNA of both producer strains and screened for the BGC in the genomes, eventually identifying five streamlined core genes, Based on the in silico analysis of the putative genes involved in the Corramycin biosynthesis and feeding experiments with isotope‐labelled precursors, we were able to propose a model for the biosynthesis , a member of the adenylate forming enzymes. FAALs are often associated with NRPS/PKS pathways as a starter unit catalyzing the acylation of the first building block.E. coli BL21 (DE3) and performed a malachite green assay.N‐terminal peptide signal for periplasmic localization, the membrane‐bound ComC might export the acylated Corramycin precursors to the periplasm, where hydrolysis by ComB potentially facilitates maturation to the final, active product. However, further investigations are required in future experiments.The first module of the assembly line, encoded by comK, harbors an Fkbh‐like domain belonging to the haloacid dehalogenase (HAD) superfamily. The same architecture of the first two modules (FAAL‐ACP‐C‐HAD‐T) was described for the Vioprolide assembly line, in which an unusual esterification process leads to the incorporation of a glycerate building block.N‐terminal C‐4 butyric acid moiety and glycerate only contains three C‐atoms. Thus, we assume that a glycerate moiety is incorporated and subsequently C‐methylated in Corramycin biosynthesis. Based on the feeding of d3‐methionine during fermentation of C. coralloides MCy10984 with subsequent analysis using LC–MS (Supporting Information section 4), we propose this reaction to be performed by ComJ, a radical‐SAM methyltransferase.The second module in Corramycin biosynthesis, also encoded by N‐methyl‐β‐hydroxy‐histidine moiety. Based on the architecture of module 3 including a putative N‐methyltransferase (N‐MT) domain and an epimerization (E) domain, we assume that l‐histidine is activated by the A domain, N‐methylated by the N‐MT domain and subsequently epimerized to γ‐N‐methyl‐d‐histidine by the E domain. To our knowledge no NRPS‐associated N‐MT domain acting on the side chain of an aromatic amino acid was described before. On the contrary, the biosynthetic pathway for the β‐hydroxylation of histidine has been described. NikQ, a heme‐protein, has been shown to facilitate the β‐hydroxylation of histidine in Nikkomycin biosynthesis.One intriguing chemical feature of Corramycins is the unprecedented γ‐in cis by an O‐methyltransferase domain, and finally extended by a C‐2 body by the type I PKS module 5.Another unique feature of Corramycins is the unusual 5‐amino‐2,3‐dihydroxy‐4‐methoxy valeroyl moiety. Based on the in silico analysis of modules 4 and 5 coupled with feeding experiments (Supporting Information Table S3), we propose that aspartate is decarboxylated by ComE to β‐alanine, which is incorporated by module 4, hydroxylated, methylated 8‐l‐valine, d6‐l‐hydroxy‐valine and 13C4‐15N‐l‐threonine during fermentation showed that only valine was accepted by the NRPS . Consequently, the hydroxylation of this building block occurs either on‐line or after product release. The β‐hydroxy‐valine moiety was also found in the myxobacterial non‐ribosomal peptide Myxoprincomide,Interestingly, two β‐hydroxy‐valines are found in Corramycins, which is a rarely observed building block in natural products. Independent supplementation of d−1) by fermentation was low and the knowledge about optimal strain cultivation, production scale‐up procedures as well as genetic manipulability of the natural producer were limited, we aimed to develop a total synthesis route. However, structure elucidation by NMR only revealed at that point the two‐dimensional structure of Corramycin  and a DCL architecture of the C domain of module 4. Since module 3 harbors an E domain, we postulate that l‐histidine is activated by module 3 and subsequently epimerized to a d‐histidine, which leads to an R configuration at the position 5 in Corramycin. The C domain subtypes of modules 6 and 8–12 were determined as LCL subtype and no additional E domains were identified. Consequently, we proposed the S configuration for phenylalanine, both β‐hydroxy‐valines, both serines and leucine. Since the remaining five stereocenters biosynthetically either arose by hydroxylation through tailoring enzymes or by downstream PKS modifications, we were not able to predict configurations due to a lack of bioinformatics tools. To fully elucidate the stereochemistry of Corramycin (1), we performed a total hydrolysis followed by chiral GC/MS analysis of the obtained amino acids. The hydrolysis revealed the absolute configuration of six stereocenters .Since the Corramycin production titer <0.1 mg L mg L−1 bn Figure . The HADl‐serine. The non‐proteinogenic protected amino acids β‐hydroxy‐valine (10), 2,3‐dihydroxybutyric acid (7), N‐methyl‐β‐hydroxy‐histdine (8), and 5‐amino‐2,3‐dihydroxy‐4‐methoxyvaleric acid (9) were synthesized from commercially available building blocks as shown in the retrosynthetic scheme  as well as building block 7, which was obtained via saponification of commercially available ester 11 .Based on this analysis, we started to synthesize all possible remaining 16 diastereomers of Corramycin to compare the respective NMR data with those of the isolated natural product. A solid‐phase peptide synthesis (SPPS) approach with a traditional Fmoc‐strategy and adequate protecting groups on the different hydroxyl groups was used to synthesize Corramycin starting from 9 , starting from a protected and commercial derivative of l‐ribose (14). Transformation of the free alcohol as leaving group, followed by azido formation, lactone opening with a protected phenylalanine derivative (15) and several protection‐, oxidation‐ and reduction‐steps allowed to obtain building block 9 in an overall acceptable yield. For the last building block 8, we achieved to create the two stereocenters by enantioselective aldolisation using a titanium enolate derived from a chiral iminoglycinate . Using α‐pinene as a chiral auxiliary, an oxidation step followed by imine formation with protected glycine (12) delivered the starting compound for the aldolization step, followed by a few protection/deprotection steps. The synthesis route was finalized via a traditional Fmoc‐SPPS in standard conditions  starting from Fmoc‐l‐TBDMSO‐serine . Comparison of the NMR data of all 16 diastereomers with the NMR data of the isolated Corramycin confirmed the configurational correctness of the analysis and the in silico prediction. Furthermore, we elucidated the configuration of the missing stereocenters, providing the absolute configuration of Corramycin ). The complete total synthesis is described in detail in the Supporting Information.More steps were necessary for the synthesis of building block E. coli ATCC25922 cultivated in the MHB rich medium or in the M9 minimal medium, . This experiment revealed that Corramycin is rapidly bactericidal, independent of the medium used. However, we observed re‐growth in MHB after 6 hours, indicating rapid selection of mutants resistant to Corramycin under these conditions. Therefore, we performed a FoR experiment using E. coli ATCC25922 in MHB and M9 medium at 4x MIC of Corramycin. Importantly, the FoR was much higher in MHB medium (3.8×10−6) compared to M9 medium (3×10−10) (Supporting Information Table S9). Next, we sequenced the genome of the resistant E. coli clones cultivated in MHB medium to identify potentially responsible mutations.After establishing a total synthesis route to avoid dependance on the low yield fermentation process and to elucidate the absolute configuration of Corramycin, we planned to further investigate the potential of Corramycin as a starting point for the development of a new antibacterial drug. Therefore, we first performed a time‐kill curve experiment at 4x and 8x MIC of Corramycin using sbmA and yejEF in E. coli ATCC25922 by λ red‐mediated homologous recombination (Supporting Information section 13) resulted in strains that showed cultivation medium‐dependent resistance towards Corramycin  in YejE or YejF. Independent or combined deletions of E. coli and K. pneumoniae but absent in other Enterobacteriaceae. where an ortholog can be identified under the name of YddA.E. coli was cultivated in MHB medium.One recognized bottleneck for the identification of new anti‐Gram‐negative scaffolds is the difficulty for compounds to penetrate the both the outer and inner membranes due to their differing properties.Since the transport and accumulation of compounds in bacteria is one of the major bottlenecks in antibiotic development, potential drugs hijacking only a single transporter make quick resistance development likely, which was, e.g., shown for Fosfomycin,E. coli ATCC35218 and subsequently treated with different doses of Corramycin ranging from a total of 10 to 30 mg per kg body weight divided into two doses, 1 hour and 3 hours after infection. We observed a remarkable dose‐dependent reduction of the bacterial load 4 hours after infection resulting in survival of the mice up to 100 % after 4 days starting from the 20 mg kg‐1 total dose  of 23.3 mg kg−1 and 21.4 mg kg−1, respectively, compared to the wild type control strain (6.1 mg kg−1) (Supporting Information section 14.3). The double deletion of SbmA and YejEF, however, lead to a significant increase in resistance with an ED50 of >40 mg kg−1.Considering the two potential Corramycin uptake transporters SbmA and YejEF, we investigated the susceptibility of E. coli strain lacking the SbmA and YejEF transporter systems resulted in an increased ED50 in the infected mice, thus complementing the results that we had obtained in our in vitro experiments.Taken together, Corramycin showed promising in vivo efficacy in a mouse septicemia model despite poor pharmacokinetic properties and a moderate MIC. The decreased susceptibility towards Corramycin in an E. coli strains and S. typhimurium. Based on the unprecedented chemical structure of Corramycin and no observed cross‐resistance with antibiotic classes commonly used in the clinic, we assume a novel, not yet elucidated, MoA. The identification of the biosynthetic pathway in C. coralloides underpins that myxobacterial species are a promising source of new antibiotic natural products with completely different chemistry compared to previously identified antibiotics, e.g., from actinobacteria. Furthermore, we proposed a biosynthesis model including a possible detoxification mechanism involving fatty acid‐linked Corramycin precursors, which are exported and deacylated to secrete the active compound. Nevertheless, many proposed biosynthetic steps require further experimental investigations. Notably, the correct prediction of eight stereocenters based on the in silico analysis of the assembly line underlines the potential of bioinformatic tools in combination with chemical analysis methods in structure prediction of NRPS‐derived natural products.In summary, Corramycin is a new antibiotic scaffold with unique or in natural products rarely observed structural features while displaying moderate to good anti‐Gram‐negative activity against numerous We found a huge discrepancy between the FoR in rich medium compared to minimal medium due to the involvement of two transport systems in the Corramycin uptake. It is important to note that the typical development of an antibiotic would have been stopped with the high FoR found in the rich media. We here show that this process may be ineffective as the rich media typically employed in standardized FoR methods are certainly not appropriate to simulate infection processes. Minimal media might mimick in vivo conditions more realistically. Thus, antibiotics potentially useful for application in human or veterinary medicine may have been lost in the past. Corramycin serves as a prime example for such a scenario and our data clearly show the importance of more detailed studies using various media and of determining the potential mode(s) of resistance in the pathogen early in the drug discovery process.In summary, the structural originality of Corramycin, the possibility to prepare analogues by total synthesis, the anti‐Gram‐negative activity, the lack of cross‐resistance with existing antibacterial classes, the mode of penetration and the promising efficacy in a mouse septicemia model, led to the conclusion that Corramycin is an attractive starting point for an antibacterial drug development program. Subsequent efforts aim at preparing new Corramycin analogues with more potent antimicrobial activities, a broadened spectrum against Gram‐negative pathogens and improved pharmaceutical properties, with the objective to identify a preclinical development candidate.Sanofi holds a patent on the Corramycin molecule, its synthesis and antibiotic activity (WO 2019/053265A1).The authors declare no conflict of interest.1As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re‐organized for online delivery, but are not copy‐edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors.Supporting InformationClick here for additional data file.


In Japan, cervical cancer has the highest incidence rate among cancers affecting women aged 15–39, with human papillomavirus (HPV) infection reported as the primary cause.One compelling reason for men to receive the HPV vaccine is to prevent oropharyngeal cancer. Indeed, epidemiological statistics indicate that oropharyngeal cancers are the most common HPV‐associated cancer among men, with about 70% of the cases attributable to HPV infection.In the United States, the Centers for Disease Control and Prevention approved the vaccination for men in 2009, and since 2011, 11–12‐year‐old boys have been actively recommended for routine vaccination. Consequently, vaccination among adolescents progressed, and between 2013 and 2018, the vaccination rate for men aged 18–26 increased from 7.7% to 27.0%, reaching half of the rate for women (53.6%).On the contrary, despite the Japanese government's declaration to include men in its HPV vaccination strategy in 2020, the actual implementation process is still insufficient; as it stands, it has yet to be included in the legally mandated vaccination protocol for men. The cost for the three‐dose HPV vaccination ranges approximately from 50,000 to 100,000 yen (350–700 USD) at medical institutions and is believed to be a significant barrier to vaccination for men. By making HPV vaccination accessible and inculcating it in routine immunization for men is a suggested solution. Indeed, some local governments such as Hirakawa City in Aomori Prefecture offer free vaccinations also for men, but nationwide efforts are still insufficient.Additionally, it is considered that trusted individuals, such as primary care physicians, play a crucial role in recommending vaccination to increase HPV vaccination coverage among men. However, as the current situation resulting from the past suspension of active HPV vaccine promotion for women in Japan demonstrates, without routine vaccination, the number of medical institutions actively administering HPV vaccines to men may be limited. To protect both themselves and their partners from cancer, it is important for both men and women to receive the vaccine before reaching the age when the risk of HPV infection increases. Given the recent reconsideration of HPV vaccination for adolescent girls in Japan, we believe it is a public health imperative that similar considerations be extended to adolescent boys nationwide.Yudai Kaneda: Conceptualization; Data curation; Writing—original draft. Mira Namba: Writing—review & editing. Tshewang Gyeltshen: Writing—review & editing.The authors declare no conflicts of interest.Yudai Kaneda affirms that this manuscript is an honest, accurate, and transparent account of the research reported, that no important aspects of the research have been omitted, and that any differences from the planned research  are explained by Yudai Kaneda.


Anal squamous cell cancer (ASCC) incidence in Kentucky is increasing at an alarming rate. In 2009, the incidence surpassed the US national average , and currently, Kentucky ranks second by state per capita. The reasons for this rise are unclear. We hypothesize individuals with ASCC in Kentucky have some unique risk factors associated with worse outcomes.Individuals with ASCC in a population‐level state database (1995–2016), as well as those treated at two urban university‐affiliated tertiary care centers (2011–2018), were included and analyzed separately. We evaluated patient‐level factors including demographics, tobacco use, stage of disease, HIV‐status, and HPV‐type. We evaluated factors associated with treatment and survival using univariable and multivariable survival analyses.p > 0.05). Poorly controlled HIV (CD4 count <500) at time of ASCC diagnosis was associated disease persistence (p = 0.032). Stage III disease  and local excision  were significantly associated with reduced recurrence‐free survival.There were 1698 individuals in state data and 101 in urban center data. In the urban cohort, 77% of patients were ever‐smokers. Eighty‐four percent of patients had positive HPV testing, and 58% were positive for HPV 16. Seventy‐two percent of patients were positive for p16. Neither smoking, HPV, nor p16 status were associated with disease persistence, recurrence‐free survival, or overall survival (all The rate of ASCC in Kentucky has doubled over the last 10 years, which is outpacing anal SCC rates in the US with the most dramatic rates seen in Kentucky women. The underlying reasons for this are unclear and require further study. There may be other risk factors unique to Kentucky. The incidence of Anal Squamous Cell carcinoma is markedly increasing in Kentucky and in the United States overall. This difference is more pronounced in women and may be due to the interplay of factors including smoking and human papilloma virus infection. The incidence, however, is increasing globally.The rise of ASCC in Kentucky is perplexing but is in accordance with our clinical practice. The driving factors behind Kentucky's upward trend are unknown. Known risk factors for ASCC include (1) human papilloma virus (HPV), notably types 16 and 18, with associated precancerous anal intraepithelial neoplasia (AIN),The aim of this study was to investigate factors associated with these temporal trends, treatment, and outcomes in a population‐based Kentucky state cancer registry. An analysis of more granular data from two urban tertiary referral centers was also performed. We hypothesize the following: (1) risk factors are discordant with national trends, and (2) there may be increased treatment failure and worse survival among those diagnosed with ASCC in Kentucky compared to US reports.2Two separate cohorts were examined for this study; (1) The Kentucky Cancer Registry and (2) University of Louisville affiliated Cancer Centers (University of Louisville Brown Cancer Center and the Norton Cancer Institute). The latter group will be referred to the “Urban cohort” throughout the text.2.1The Kentucky Cancer Registry (KCR) is a premier population‐based cancer registry. Since 2000, it has been a part of the National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) program and the Center for Disease Control and Prevention's (CDC) National Program of Cancer Registries (NPCR).All individual diagnosed with ASCC who reside in Kentucky between 1995 and 2016 were included in our cohort. Cases were identified by KCR using International Classification of Diseases for Oncology, 3rd Edition (ICD‐O‐3) site and histology codes for anal SCC (C21‐C21.8). The following histologic types were excluded from anal SCC: melanomas (8720–8790), sarcomas (8800–8991), mesotheliomas (9050–9055), Kaposi sarcomas (9140), and leukemias/lymphomas (9590–9992). Individual‐level factors available included the following: demographics, stage of disease, initial treatment, disease recurrence, and overall survival. Individuals were followed from the date of initial diagnosis to the date of last contact or date of death. National and Kentucky anal SCC incidence rates were identified from the SEER database and KCR.2.2Individuals treated for ASCC at two large urban tertiary centers in the same city in Kentucky between 2014 and 2019 were evaluated in a separate analysis to provide more granular data on individuals with ASCC. This convenient sample of patients are also included in our KCR cohort; however, we did not attempt to link or re‐identify these individuals. Patients with American Joint Commission on Cancer (AJCC) Stage I‐III were included for analysis. Additional individual‐level factors available that are known risk factors for ASCC were included, specifically: tobacco smoking history, Human Papilloma Virus (HPV), p16, and human immunodeficiency virus (HIV). HPV typing was performed at the Moffitt Cancer Center, University of South Florida. HPV types were classified using a hierarchical attribution into two mutually exclusive categories: (1) HPV16 positive regardless of multiple HPV infections, (2) all other HPV types, or (3) HPV negative.INK4A (p16 positive) is strongly correlated with HPV infection, but there is known discordance between the two.Immunohistochemistry (IHC) expression of p16 was determined by using paraffin‐embedded tumor biopsies; this was performed by the Special Procedures Laboratory in the Department of Pathology, University of Louisville. Expression of p16Comorbidities were classified using the Charlson comorbidity index (CCI).2.3Primary: (1) Incidence of ASCC in Kentucky compared to US. (2) Temporal changes in individual factors associated with an ASCC diagnosis in Kentucky from 1996–2007 compared to 2008–2016.Secondary: Patients were followed from the date of diagnosis to the date of last contact or the date of death. If an individual was never recorded as becoming free from disease , disease persistence was recorded. Recurrence was defined a local or distant cancer recurrence following an interval‐free period from disease between initial treatment and recurrence. The number of days from the date initial diagnosis to cancer recurrence was calculated for each patient.2.4p‐values were reported as an overall effect for categorical factors with more than two levels. Multivariable Cox models were constructed using all predictors that were significant on marginal analysis, and the appropriateness of the proportional hazards assumption was confirmed using the Schoenfeld residuals global test.Statistical analysis was performed using SPSS v26  and R statistical software v4.2.1 . Categorical variables are presented as number and frequency. Continuous variables are presented as median (interquartile range). Categorical variables were compared using Fisher's exact test. Continuous variables were compared using the Mann–Whitney U‐test, unless otherwise stated. Univariable analyses between groups were performed using the Fisher's exact test and the Mann–Whitney U‐test. Recurrence‐free survival and overall survival rates were computed using Kaplan–Meier plots. Associations with categorical and continuous variables were investigated using the Cox proportional hazards model; log‐rank 2.5This study was approved by the Institutional Review Boards of the University of Louisville and the University of Kentucky .33.1p < 0.01). There was no difference in the incidence between the male patients in Kentucky compared to the US. Figure Between 1995 and 2016, 1698 individuals were diagnosed with ASCC in Kentucky. The annual incidence rose from 2.4 to 3.3/100,000 individuals during this study period, which surpassed the national average in 2005, Figure p = 0.049, as well as a decrease in age at diagnosis . An increasing number of individuals were insured with Medicaid, 11% to 16%, or managed care insurance, 20% to 29%. There was a significant difference in the distribution of AJCC stage between the time periods (p = 0.021), Table In Kentucky, there were differences in demographics and stage of disease at diagnosis between the pre‐ and post‐2008, Table n = 1201), the persistence rate was 37%. Chemoradiotherapy was associated with increased rates of disease persistence , followed by chemoradiotherapy (40%) Table . Among tce Table . Overallce Table . In stagce Table . Howeverp = 0.001).When we compared pre‐ and post‐Medicaid expansion (1995–2012 vs 2013–2016) in the KCR data set, there was an increase in the percentage of individuals insured by Medicaid  was not associated with HPV‐ or HPV‐16 status. Interestingly, p16 negativity was associated with greater disease persistence . HIV with a low CD4 count at ASCC diagnosis (CD4 < 500) was associated with higher rates of disease persistence when compared to HIV‐negative or HIV‐positive patients with CD4 > 500 . There were no differences in disease persistence rates by tobacco smoking or treatment type. Disease persistence tended to be more likely for Stage III patients, although this did not reach statistical significance (p = 0.086) . For recurrence‐free survival (RFS), there were 39 events observed, and 1‐year and 3‐year RFS rates were estimated to be 87% (95%CI: 80–94) and 63% (53–74) , long‐term HIV disease , poor ECOG status , and AJCC stage III  were associated with worse RCF. On multivariate analysis, chemoradiotherapy was associated with improved RFS and Stage III disease with worse RFS, Table There were 26 events of disease recurrence and 27 death events in the urban cohort  Figure . On univp = 0.001) and AJCC stage III  were associated with worse overall survival. On multivariable analysis, both of these variables remained significant risk factors for overall survival. Neither smoking nor HPV status were associated with overall survival, Table Overall survival at one‐year post‐diagnosis is found to be 92% (95%CI: 87–98) and 74% (65–84) at 3 years Figure . On univ4Rates of ASCC have increased over time in Kentucky. This state now has the second highest incidence in the US. Demographic changes that occurred over our study period include Medicaid expansion and increasing tobacco smoking rates among individuals diagnosed with ASCC in Kentucky. In general, rates of tobacco use in Kentucky have remained higher than the national average, with one of the highest smoking rates in the country with nearly 25% of adults reporting smoking at least 100 cigarettes in their lifetime.Increased rates of ASCC are presumed to be the result of changing sex practices and screening in the HIV‐population, particularly men who have sex with men (MSM). There is no evidence to suggest this is significantly contributing to the rising incidence in Kentucky. While ASCC is more common in the HIV‐positive population, HIV is less common in Kentucky compared to other states in the US. The HIV prevalence rate in Kentucky is 196 cases/100,000 individuals, which ranks 18th lowest by state. Similarly, rates of new HIV infection Kentucky have remained steady at approximately 8 cases/100,000 individuals with a male to female ratio of 4:1.The median age at diagnosis of ASCC was 57 years in the urban cohort and 56 in KCR. These results are similar to national trends. Deshmukh et al. found the highest increases in ASCC incidence and mortality in those over the age of 50.We did find rates of new cases of ASCC in females are outpacing males, Figure In our urban center cohort, 84% and 72% of individuals with ASCC had HPV infection and p16 positivity. Other studies have reported >90% of ACCC cases are associated with HPV‐positive specimens.After initial treatment for ASCC, prior studies indicate that approximately 25% of individuals can expect to have disease persistence or recurrence.Our goal was to shed light on the changing trends seen in clinical practice. We used available data and factors available, which are inherently limited. Before 2018, HPV status was not reported to KCR. The urban cohort was used to augment this but is not without its own limitations. The relatively small cohort limits the interpretation and generalizability of our findings. A number of the analyses were limited by sample size and could be subject to a type 2 error. Demographic factors such as household incomeThere are other limitations to consider in this study. As with any population or registry database, there are inherent limitations with the individual capturing the data and with information available from an individual patient's medical records. Although we postulate that HPV infection is a factor associated with increasing incidence in Kentucky and the US, but there is a paucity of national data of HPV infection in the US.In sum, rates of ASCC in Kentucky are outpacing national trends and the driving factors remain unclear. High rates of tobacco smoking and increased access to care are associated with this trend. Clinical outcomes may be negatively affected by lower rates of HPV and p16 in ASCC cases in Kentucky. Future work will investigate additional lifestyle‐factors and genetic blueprints with the aim of uncovering novel factors associated with the increased incidence and worse clinical outcomes for individuals with ASCC especially in Kentucky.Stephen J. O'brien: Conceptualization ; data curation ; formal analysis ; funding acquisition ; methodology ; project administration ; resources ; software ; writing – original draft ; writing – review and editing . Jeremy Gaskins: Data curation ; formal analysis ; investigation ; methodology ; software ; validation ; writing – review and editing . Clayton Tyler Ellis: Formal analysis ; funding acquisition ; investigation ; methodology ; resources ; supervision ; writing – original draft ; writing – review and editing . Brock Martin: Formal analysis ; investigation ; methodology ; project administration ; resources ; software ; supervision ; writing – original draft ; writing – review and editing . Jaclyn K McDowell: Conceptualization ; data curation ; formal analysis ; methodology ; resources ; supervision ; validation ; writing – review and editing . Dibson Gondim: Conceptualization ; data curation ; formal analysis ; methodology ; project administration ; resources ; supervision ; visualization ; writing – original draft ; writing – review and editing . Susan Galandiuk: Conceptualization ; data curation ; funding acquisition ; investigation ; methodology ; project administration ; resources ; software ; supervision ; validation ; writing – original draft ; writing – review and editing .This study was supported by the Transdisciplinary/Multidisciplinary Collaboration Research Planning Grant (TCRPG) from the University of Louisville and Price Trust. Presented in part at the American Society of Colon and Rectal Surgeons Annual Scientific Meeting Tampa, Florida 2nd May 2022.The authors declare no conflict of interest.Figure S1.Click here for additional data file.Figure S2.Click here for additional data file.Figure S3.Click here for additional data file.Figure S4.Click here for additional data file.Table S1–S4Click here for additional data file.


Cervical cancer is one of the most deadly cancers for women worldwide. Its incidence is, in virtually all cases, causally tied to a human papillomavirus (HPV) infection that had not been cleared by the immune response of the host. There is a small subset of cervical cancers, however, that do not show evidence of HPV presence, thus representing a rare gynecological cancer entity. While HPV-related cervical cancer is studied extensively, HPV-independent cervical cancer studies are lacking, together with appropriate models. We obtained a cervical cancer cell line, DoTc2 4510, described in the literature as HPV-negative. After suspicous preliminary results showing HPV presence, we proceeded to characterize the cell line in detail, proving it is truly HPV-transformed. With this publication, we aim to inform the community about the HPV status of the studied cell line, as well as emphasize the importance of stringent controls in cancer model establishment, especially for rare cancers.INK4a, to assess E6/E7 functionality. Finally, to attest to the survival dependence of DoTc2 4510 cells on HPV16, we performed an HPV16 E6/E7-targeted siRNA knock-down, which indeed led to senescence induction. Together, these findings demonstrate that DoTc2 4510 is an HPV16-transformed cell line.Cervical cancer is the fourth leading cause of cancer deaths in women, with over 340,000 women dying from this disease in 2020. Almost all cases have an underlying persistent infection with an oncogenic high-risk type of human papillomavirus (HPV), mainly HPV16. While cervical squamous cell carcinoma is hardly ever HPV-negative, a small subset of adenocarcinoma exhibits absence of HPV, even after disproval of false-negative testing results due to low viral load. This proportion is evident in many cervical cancer studies and is reflected in the repertoire of model cell lines commonly used in research. As the viral origin of cervical cancer makes it a disease preventable and potentially treatable by immunotherapeutic approaches, it is the focus of many studies. For pertinent research, both a broad set of HPV-infected cervical carcinoma models are required, as well as stringent negative controls. A ubiquitously used HPV-negative cervical adenocarcinoma cell line is C-33A. Another cervical cancer cell line is available for purchase from the American Type Culture Collection (ATCC), namely DoTc2 4510, described to be HPV-negative and thus as a model for a rare gynecological malignancy. Here, we present findings proving that DoTc2 4510 is, in fact, an HPV16-positive cell line. This we assessed using a highly sensitive nested multiplex PCR protocol adapted for the identification of 12 carcinogenic HPV types and a second PCR targeting the HPV16 oncogenes E6 and E7. Subsequently, the protein expression of E6 and E7 was examined, as well as the expression of their target proteins p53, p21, and p16 Cervical cancer (CxCa) is considered to be the fourth leading cause of cancer-related death in women worldwide, with around 340,000 women dying of CxCa only in 2020 . Nearly INK4a expression is upregulated. Simultaneously, the E6 oncoprotein binds to p53 and consequently leads to its destruction [While the carcinogenesis of HPV-positive cervical cancer is well understood, much less is known about HPV-negative cancer development. The mechanism of carcinogenesis deployed by high-risk HPV is through the E6 and E7 oncoproteins. They do so by dysregulating the cell cycle by inhibiting/degrading the tumor suppressor proteins p53 and Retinoblastoma protein (pRb). The E7 oncoprotein interferes with the normal transcription complex containing pRb. E7 binds to pRb, blocking it, thus disturbing the cell cycle and driving the cell from the G1 into the S phase. With pRb inactive, downstream tumor suppressor protein p16Research on the rare HPV-independent cervical cancer is limited in both scope and appropriate models. To understand the mechanism of HPV-independent cervical carcinogenesis, there is a pressing demand for appropriate models to study . A ubiquAt the time of starting a new project, thorough characterization and authentication of model cell lines is recommended . FollowiThis work included four cell lines, HPV-negative normal oral keratinocytes, NOK , HPV16-positive cervical cancer cell line CaSki , HPV-negative cervical cancer cell line C-33 A  and the cervical cancer cell line DoTc2 4510 . NOK was cultured in Keratinocyte SFM (1×) supplemented with Human Recombinant EGF, Bovine Pituitary Extract , and 10% Fetal Bovine Serum (FBS). CaSki, C-33 A, and DoTc 2 4510 were grown in DMEM (Gibco) supplemented with 10% FBS, 1% Penicillin/Streptomycin, and 1% L-Glutamine.https://hml.nmdp.org/MacUI/ (accessed on 20 June 2023). CaSki, NOK, and C-33 A were previously examined in the same manner.Upon delivery of DoTc2 4510, total DNA extraction was performed using the QIA-amp DNA Mini Kit  according to the manufacturer’s instructions, and DNA was prepared following testing service providers ‘requests. Cells were put in culture in quarantine until results from standard routine cell authentication and contamination tests were received. Both tests were performed by Multiplexion GmbH . The cell line was authenticated by determining genetic characteristics via STR-profiling technology, while contamination testing was run against 14 Mycoplasma species, Epstein–Barr virus, Squirrel Monkey Retrovirus, and 12 contaminating cell lines. HLA-typing was performed by Deutsche Knochenmarkspenderdatei (DKMS) Life Science Lab GmbH . HLA typing results are provided in accordance with the current HLA nomenclature as G codes, NMDP codes (MAC), or 2-field allele names. NMDP (MAC) codes can be decoded under ® ReadyMix PCR-Reaction mix and 15 picomols of each primer . Total DNA extraction was as described above. Nested multiplex PCR (NM-PCR) was performed following a published protocol . In brie® ReadyMix PCR-Reaction mix and 25 picomol of each primer .The same extracted total DNA was subsequently also inspected for the presence of HPV16-specific E6 and E7 gene sequences adhering to a protocol shared by Tarik Gheit . Shortly, amplification was performed using forward 5′CGA AAC CGG TTA GTA TAA 3′ and reverse 5′ GTA TCT CCA TGC ATG ATT 3′ primers to detect E6, and forward 5′ ATA ATA TAA GGG GTC GGT GG 3′ and reverse 5′ CAT TTT CGT TCT CGT CAT CTG 3′ for E7. PCR conditions were initial denaturation at 95 °C for 15 min, then 35 cycles of denaturation at 94 °C for one minute, annealing at 55 °C for one minute, elongation at 72 °C for two minutes, and final elongation at 72 °C for 10 min. Both reactions were performed in a total volume of 50 microliters containing 25 microliters of of REDTaq® Nucleic Acid Stain 10,000×  and photographed with INTAS Gel capture. Furthermore, products were cleaned up using NucleoSpin Gel and PCR Clean-up  according to the manufacturer’s instructions and sequenced . Sequence alignment was performed using Human papillomavirus type 16, complete genome, GenBank: K02718.1.Ten microliters of each amplification product were analyzed by electrophoresis on a 2% agarose gel stained with GelRed2, 1% Triton X-100, 1 mM DTT, 1 mM PMSF, and protease inhibitor cocktail . Samples were incubated for 20 min on ice with periodic mixing followed by 10 min centrifugation at 14,000× g at 4 °C. Proteins were mixed with 4× Laemmli-buffer-containing β-mercaptoethanol and then boiled at 95 °C for 5 min. Isolated proteins were separated by SDS-PAGE and then transferred to a PVDF membrane using semi-dry transfer. Membranes were blocked followed by overnight incubation at 4°C with primary antibodies , HPV16 E7 NM2 (in-house produced), p21 Waf1/Cip1 (F-5), P16INK4A (DCS-50)sc-65476, p53 (DO-1)sc-126 , β-actin AC-74 (Sigma-Aldrich), GAPDH (GT239) . HRP-coupled secondary antibodies (IgG anti-Mouse IgG (H+L)-HRPO  were then incubated with the membrane for 1 h. After adding the chromogenic substrate ECL™ Prime Western Blotting detection reagents , a chemiluminescence signal was observed in a Biorad Chemiluminescence Detector .For protein expression analysis by Western blot, cells were lysed using lysis buffer consisting of 10 mM tris-HCL pH 7.5, 50 mM KCl, 2 mM MgClSynthetic siRNAs  were transfected with Lipofectamine RNAiMAX , according to the manufacturer’s instructions to a final siRNA concentration of 10 nM. Three different siRNAs blocking HPV16 E6/E7 oncogene expression were pooled at equimolar concentrations to minimize potential off-target effects, as detailed previously . The siRFor colony formation assays, DoTc2 4510 cells were transfected with siRNA, as described above. Three days after the transfection, cells were reseeded and incubated for 11 days. Later, cells were fixed with formaldehyde and stained with crystal violet, as previously described ,16.DoTc2 4510 were seeded three days after siRNA transfection and grown for 4 days.Then, cell morphology was examined for typical characteristics of senescence , and senescence-associated β-galactosidase activity was assessed, as previously described ,16.Authentication testing by STR-Profiling confirmed the cell line is indeed DoTc2 4510, and contamination testing showed no presence of any of the examined-for entities. HLA-typing results showed DoTc2 4510 cells to be homozygous or hemizygous  for both HLA class-I and HLA-class-II, carrying A*03:01:01, B*55:01:01, C*03:DJUJV, DRB1*03:RPXT, DQB1*02:CGRKD, DQB1*02:CGRKD, DPB1*10:AWFCR. (Letters represent NMDP (MAC) codes; see Methods for decoding information.) The HLA class-I allotype is the same as previously reported for this cell line . After confirming the identity of DoTc2 4510, cells were cultured and examined for HPV to confirm they were HPV-negative. Nested multiplex PCR, testing for the potential presence of 12 high-risk HPV types, showed the presence of HPV16 a. PCR anTo determine if HPV16 E6 and E7 are present on a translational level, protein expression was examined by Western blot . Figure With HPV16 DNA presence and HPV16 oncoprotein expression confirmed, the next step was to examine if DoTc2 4510 cells are dependent for survival on the HPV16 oncoproteins, which is another typical feature of HPV16-transformed cells . HPV16 EHPV-negative cervical cancer represents a rare disease entity. An indispensable prerequisite for constructive research comparing HPV-positive and HPV-negative cervical cancers is good and appropriate in vitro models. Cancer cell lines representing both subtypes of the disease, as well as stringent negative controls for virus-related research, are crucial. Alertness is particularly important in working with models of rare disease subtypes due to the increased difficulty of obtaining material that was accurately classified at the time of patient diagnosis. In the process of diagnostics, HPV-negative results are often false negatives due to differences in sensitivity in approved and used detection procedures . More riDoTc2 4510 is available for purchase from ATCC as a component of the cervical cell line panel. Disclosed is scarce information on the characterization of the cells, limited to the description of the cell line as epithelial and originating from a female with cervical carcinoma. In some of the referenced papers, HPV status is not reported, while several studies used and published DoTc2 4510 as an HPV-negative cell line, some of them grouping it to SCC while others refer to it as AC ,22,23,24The focus of our group is developing a therapeutic HPV vaccine by detecting HPV target epitopes using sensitive mass spectrometry methods requiring stringent controls. We thus acquired the DoTc2 4510 cell line to use it as an additional HPV-negative control cervical cancer cell line. For this reason, as a first step, we applied our routine highly sensitive nested multiplex PCR (NMPCR), which was developed to detect even low levels of 12 high-risk HPV types  to confiThe fact that DoTc2 4510 is widely accepted as HPV-negative in the scientific community may stem from two circumstances: ATCC describes cell lines on their website as submitted by the depositor, and customers tend not to question descriptions found on the ATCC website. We want to stress again that the cell line is not indicated to be either HPV-negative or HPV-positive on the ATCC website but just described by references .The case of DoTc2 4510 highlights the importance of good scientific practices, especially in regard to the diligent management of experimental material. This is particularly important when working with cell lines that supposedly stem from rare oncologic entities, such as HPV-negative cervical cancer. There is a problem recognized within the scientific community of erroneously published data and conclusions due to research performed on inappropriate and irrelevant material. This is visible in the lack of reproducibility and paper retractions, which have been the subject of several publications ,28. The In this study, we have characterized the DoTc2 4510 cervical carcinoma cell line. Our data show that DoTc2 4510 cells are, in fact, HPV16-transformed, with evidence on genomic, translational, and functional levels. These findings exclude them from the HPV-negative cervical carcinoma subtype, a rare gynecological cancer that is in great need of representative models and comprehensive studies. Another inference of this work lies in highlighting the importance of routine cell authentication and a conscientious approach in conducting cell line-based studies, as inadequately designated cell lines seriously harm research on a fundamental level.