Cervical cancer is a preventable disease. This study aimed to share the results of the national cervical cancer screening program performed in primary health care institutions in Samsun between 2015 and 2019.Women aged 30–65 years who were screened for cervical cancer in screening centers of Samsun between January 01, 2015, and December 31, 2019, were included in this descriptive study. The data were obtained from the automation program of the “National Human Papilloma Virus (HPV) Laboratory Application” used by the Provincial Directorate of Health Cancer Unit through filtering the completion time of the tests, and all results were evaluated without sampling. Thus, data were presented using descriptive statistics.The mean age of 89,302 women included in the cervical cancer screening program was 45.9 ± 9.0 years. Of the samples obtained from the participants, 1.0% were determined as insufficient material, 94.1% as HPV-negative, and 4.9% as HPV-positive. The most common HPV genotypes were 16, 51, 31, and 52. Of the 4337 HPV-positive women, 74.7% of the pap smear results were negative , and the most common premalignant lesions were atypical squamous cells of undetermined significance in 7.1% and low-grade squamous intraepithelial lesions in 6.9%. HPV 16/18 was also observed in 31.7% of HPV-positive women. Seven hundred ninety-five women were referred to a specialist physician for further examination and treatment within the scope of the screening algorithm.Detecting HPV-positivity by reaching more women within the national cervical cancer screening program’s scope is vital in fighting against this disease. The effectiveness of cancer screening programs should be increased by ensuring community participation through awareness activities. Cervical cancer is one of the leading causes of cancer death among women. According to the data of 2018 from the World Health Organization (WHO), cervical cancer is the fourth most common type of cancer among women after breast, colorectal, and lung cancer. While approximately 570,000 women have cervical cancer every year worldwide, 311,000 women die due to this cancer, and 88% of these deaths occur in low-income countries [The most important cause of cervical cancer is type 16, 18, one of the high-risk oncogenic Human Papilloma Virus (HPV) types, and almost all cervical cancer cases develop due to HPV infection. HPV infection is one of the most frequent sexually transmitted diseases. HPV lesions in the genital system are common in some age groups, as most regress spontaneously and are asymptomatic . HoweverVaccination: 90% of girls being fully vaccinated with the HPV vaccine by the age of 15;Screening: 70% of women being screened using a high-performance test by the age of 35 and again by the age of 45;Treatment: 90% of women with pre-cancer being treated, and 90% of women with invasive cancer being managed .Thus, detecting the disease at an early stage and removing precursor lesions, such as cervical intraepithelial neoplasia (CIN), will reduce invasive cervical cancer cases . CervicaScreening tests available include HPV test, cytology (Pap smear test), and visual inspection with acetic acid . It is tThis study aimed to share the results of the national cervical cancer screening program conducted in primary health care institutions in Samsun.HPV DNA-based screening applied in our country started in 2014. Two national laboratories were established for the primary HPV screening program in Ankara and Istanbul. Samsun province samples are sent to the Ankara laboratory every Friday. The entire specimen testing is performed in the two laboratories by using fully automated operational procedures that allow tracing of specimens and timely delivery of results to the screened population. The Turkish Ministry of Health Cancer Control Department is responsible for the quality assurance and monitoring of the program. There is a standard working procedure with checkpoints for both HPV DNA analysis and the evaluation of pap smears, which are;Sampling adequacy: Inadequate sampling is monitored by four pathologists in the laboratory. Conventional cytology samples are double-blinded by at least two pathologists in at least 20% of the samples.Sampling Reports: Pap-smear samples of 10% of HPV-positive and normal cases are evaluated by the same four pathologists. The four pathologists working in the laboratories also evaluate each other’s reports. For this evaluation, about 10% of slides, which were reported as normal by one pathologist, are reviewed by the other to improve interobserver consistency and provide quality control targeting > 90% consistency in normal reports.HPV DNA analysis: Two control systems are used, internal and external. For internal control, one negative and one positive sampling are used for every 88 patients’ plates. For external quality control, re-evaluation is done in cooperation with UK National External Quality Assessment Service (UK NEQAS) at least twice a year, using ten external samples for validation .The national software program developed for the HPV screening program RUNLEK ensures that it is monitored at every stage of the screening process. This system monitors all stages from distribution of HPV kits, transportation and collection, and recording of samples to reports. In case of any problem, it informs the authorized person in the laboratory via message and ensures that the problem is detected and solved.https://hpvtarama.saglik.gov.tr/duyurular/sonucsorgula).d. Result reports: The screening results are reported online and sent to the family physician or the nurse at the center where the screening is performed. The medical staff can access the results themselves by logging in to the program. In addition, the person who has been screened can see her own report from this web-based system with her barcode number and citizenship number  for HPV DNA analysis. For women who are HPV positive by Hybrid Capture2 (Qiagen), genotyping is performed with the CLART kit (Genomica). CLART kit (Genomica) is a polymerase chain reaction (PCR) based genotyping method and can detect 35 genotypes . Thus, it is possible to study cytology in HPV-positive patients without the need to retake samples. Therefore, a more cost-effective approach can be possible, allowing resources to be used to increase cervical cancer attendance and follow-up of women with treatment and management needs. Samples of subjects with positive HPV DNA are evaluated in terms of cytology by two pathologists as double-blinded. The results reported as normal, infection, atypical squamous cells of undetermined significance (ASC-US), low-grade squamous intraepithelial lesions (LSIL), Atypical squamous cells-cannot exclude high-grade lesions (ASC-H), high-grade squamous intraepithelial lesions (HSIL), atypical glandular cells (AGC) in the cytological evaluation are again reported online to the center, in which scanning is performed, through a national software program created by the Ministry of Health. In this software program, whether the samples are sufficient, HPV positivity/negativity status, HPV genotypes for HPV-positive cases, and cytology reports are included . Women whttps://hpvtarama.saglik.gov.tr/hpvlab/Login?ReturnUrl=%2fhpvlab).The research sample consisted of 316,675 women aged 30–65 living in Samsun in 2019. It was determined 89,302 (28.2%) women aged 30–65 were screened for cervical cancer between January 01, 2015, and December 31, 2019. The screenings were performed in 4 KETEM, 3 HLC, and 142 FHC serving in the city. The kits used in the program are provided by the Ministry of Health through a central tender and delivered to the screening centers through the health directorate. In our country, population information is recorded nationally with a standard software system. The appropriate target population list for screening comes to each family physician automatically through this software. Women in the target population are invited by their family physicians and other screening centers by phone or face-to-face interview. If there is no response to the invitation, the invitation is sent again every year. If there is no response after five years, women are registered in the system as a “rejection scan.“ Screening data are recorded with a web-based central system. The data were obtained by filtering the “National HPV Laboratory Application” automation program used by the Provincial Health Directorate Cancer Unit in April-May 2020 over the time of completion of the tests, and all results were evaluated without sampling  and Samsun Provincial Health Directorate. Descriptive statistics of the data were expressed using mean ± standard deviation values and numbers (%). The Chi-square test was used in statistical analysis. Values of p < 0.05 were considered statistically significant.In the study, the mean age of 89,302 women screened for cervical cancer between 2015 and 2019 was 45.9 ± 9.0 years. 46.9% of the women were in the 30–44 age group, 32.9% were in the 45–54 age group, and 20.2% were in the 55–65 age group. The women included in the screening program were analyzed regarding age groups. While the rate of women in the 30–44 age group was 43.0% in 2015, this rate was 47.5%, 46.8%, 46.6%, and 50.9% in the following years, respectively. 1.0% of the samples taken were considered insufficient samples, 94.1% as HPV negative, and 4.9% (4337 samples) as HPV-positive. The numbers of samples taken by year and positive test results are presented in Table 2 = 122.725, p < 0.001) (Table Positive test results by years and age groups are presented in Table 1) Table . There w1) Table .Considering the cytology results of HPV-positive 4337 women, 441 (10.2%) were considered as inadequate, 3236 (74.7%) (including infection 36.5%) as negative, 308 (7.1%) as ASC-US, 298 ( 6.9%) as LSIL, 20 (0.5%) as ASC-H, 10 (0.2%) as HSIL, and 24 (0.6%) as AGC  women who were HPV-positive and had abnormal cytology or were HPV 16/18-positive, even if the cytology was normal, were referred to a specialist physician  other than women’s age since the data were obtained from the automation program. Another limitation was that not all follow-up results of women who participated in the screening program and were HPV-positive could be reached. Besides, another was that it was only performed on women admitted to health institutions, and the number of women included in screening programs was low.Our study determined that women who were included in the screening program in Samsun and who had abnormal HPV and Pap smear results were detected. However, it is necessary to reduce insufficient sample rates and include more women in the screening program. Identifying people who are HPV-positive and providing early diagnosis and treatment will decrease the number of cancer cases as well as the deaths from this cancer. These studies will also gain favor in improving women’s health. Hence, community participation should be ensured by carrying out awareness studies on screening programs, and the effectiveness and inclusiveness of cancer screening programs should be increased across the country.


L. gasseri–dominated and L. jensenii–dominated clusters were significantly absence. Microbial alpha diversity was significantly higher in HPV-infected and cervical intraepithelial neoplasia (CIN)–diagnosed groups than in healthy control group. Certain bacteria were associated with HPV infection and CIN, including Streptococcus, Prevotella, Chlamydia, Bifidobacterium, Ralstonia, and Aerococcus. With the development of disease, the proportions of community state type III (CST-III) and CST-IV-B gradually increased, whereas the proportions of CST-I and CST-IV-A gradually decreased. In addition, age was an influential factor for HPV infection. With aging, the probability of HPV infection and the proportion of CST-IV-B increase. In conclusion, our study was a large cross-sectional study that evaluated the relationship between vaginal microbiota and HPV infection, and brought essential comparable data.Human papillomavirus (HPV) infection is one of the most common sexually transmitted diseases. After studying 602 unvaccinated Chinese women using 16S rRNA to detect cervical-vaginal microecology, we analyzed the relationship between HPV infection and vaginal microecology including 20 HPV types. In Chinese women,  Cervical cancer (CC) is a malignant tumor originating in the cervix. Cervical intraepithelial neoplasia (CIN) is a precancerous lesion closely related to invasive CC that includes cervical atypical hyperplasia and carcinoma in situ (Human papillomavirus (HPV), a major CC pathogenic factor, belongs to the family Papillomaviridae and the genus Papillomavirus  are the vaginal microorganisms present in a woman of reproductive age. VMB are normally dominated by Lactobacillus spp. that breaks down glycogen to secret lactic acid, which makes the pH of the vaginal environment acidic  that destroy the original protection mechanism of VMB , and other infectious diseases; e) diagnosed with bacterial vaginosis (BV), vaginal candidiasis, Trichomonas vaginalis (TV), Neisseria gonorrhoeae, Chlamydia trachomatis, etc.; and f) patients with immune system disorders or chronic diseases . Participants were also asked and collected questions related to HPV infection, including number of pregnancy and gestation, number of recent sexual partners, whether they smoked, whether they used vaginal douche, whether they used contraception, and methods of contraception. Details could see All study participants provided written informed consent according to good clinical practice guidelines. The study was approved by the Aviation General Hospital Ethics Committee, and the certificate number was 2021-KY-01-02. The inclusion criteria were as follows: a) age range from 20 to 70 years; b) willing to cooperate during the collection of cervical and vaginal samples; c) voluntarily participate and sign written informed consent; and d) no plan to move out of Beijing within 2 years and willing to cooperate with follow-up. The exclusion criteria were as follows: a) pregnancy; b) vaccinated against HPV; c) sexual activity, vaginal irrigation, or drug application performed within 48 h before sampling; d) diagnosis with tuberculosis, hepatitis B virus (HBV), hepatitis C virus (HCV), sexually transmitted infections  was rinsed in a vial of normal saline solution, placed in a temporary sample transport box (0°C), and transferred to a 4°C refrigerator as soon as possible. The samples could be stored at 4°C for a month .Metagenomic DNA samples were extracted by using the Fast DNA SPIN extraction kits  . BacteriAfter genomic DNA extraction, sterile water was used to dilute the sample to 1 ng/μl, using specific primers with barcode. The Phusion High-Fidelity PCR Master Mix with GC Buffer  was used for PCR. The TruSeq DNA PCR-free Sample Preparation Kit  was used for library construction. The constructed library was quantified by Qubit and Q-PCR and then sequenced using the NovaSeq high-throughput sequencing platform (PE250)  .http://ccb.jhu.edu/software/FLASH/), and the Raw Tags were obtained. The Raw Tags need to go through strict filtering to get high-quality Clean Tags data. The Reference Qiime  Tags quality control process was used to get the final Effective Tags using the Uparse algorithm  for all samples (http://drive5.com/uparse/). By default, sequences are clustered into operational taxonomic units (OTUs) with 97% identity. The OTU sequences were annotated by species using the Mothur method and SSUrRNA database of SILVA138 (http://www.arb-silva.de/). We used the MUSCLE software  for rapid multiple sequence alignment  was used to calculate OTUs, Chao1, Shannon, Simpson, abundance-based coverage estimator (ACE), Good’s coverage, and PD_whole_tree indices, and R software (version 2.15.3) was used to map dilution curves, rank abundance curves, species accumulation curves, and principal coordinates analysis (PCoA) plots. The LEfSe analysis was performed using LEfSe software, and the default value of the linear discriminant analysis (LDA) score was 4.Women with cervical lesions detected by colposcopy were biopsied for pathology. The pathology results and CIN diagnosis were obtained from the Aviation General Hospital of China Medical University. The Hybrid Capture 2 assay (HC2) was used to detect HR-HPV types and low-risk types. Women who were positive for HR-HPV also accepted TCT (Thinprep Cytologic Test) to define the cytological lesion. The clinician will examine the cervix under a colposcope and will perform cervical biopsy for suspected lesions. Immunohistochemical methods were used to classify cervical tissues.2 test  group (n = 113), an HPV-infected group (n = 159), and a CIN-diagnosed group (n = 84). In the HPV group, participants were also grouped into those with a simple HPV (HPV-S) infection (n = 107) and multiple HPV (HPV-M) infections (n = 52). The CIN-diagnosed participants were grouped into CIN1 group (n = 47), CIN2 group (n = 24), and CIN3 group (n = 13) Table 1.In all samples, the percentage of HPV negative samples was 31.74% (n = 113), the percentage of HPV-S infections was 42.70% (n = 152), and the percentage of HPV-M infections was 25.56% (n = 91). The top three HPV types were 2HR-HPV infection , HPV16 , and HR-HPV plus LR-HPV infection   and HPV-M infection . In the participants with HPV-S infection, the top three HPV types were HPV16 , HPV52 , and HPV58 ; whereas, in the participants with HPV-M infections, the top three HPV types were 2HR-HPV infection , HR-HPV plus LR-HPV infection , and 3HR-HPV infection  , whereas that of L. iners was increased . The proportion of Lactobacillus-dominated categories was decreased  and that of non-Lactobacillus–dominated categories was increased  , whereas the HPV and CIN groups had no participants with CST-II   and contraception  were risk factors for HPV infection, whereas CST types , number of pregnancy , number of sexual partners , and IUD implant  were protective factors for HPV infection. In addition, we also conducted logistic regression analysis on possible risk factors for CIN, which included HPV-S infection and HPV-M infection, and we just found that HPV infection was a risk factor for  CIN. We chose HPV-S and HPV-M and special HPV types, with CIN 1/2/3, by using the χ2 test, and we did not find significantly change  implant, number of sexual partners, smoking characteristics, and usage of vaginal douche, which were collected in the questionnaire. As shown in Logistic regression analysis showed that age was significantly associated with the risk of being HPV-infected  were classed under CST-II or CST-V, which are dominated by ur study . This sulearance . The lacL. iners was an intermediate state that changed to L. crispatus domination when the vaginal environment became better and to non-Lactobacillus spp. domination when it became worse. CST-IV-B was considered a risk factor for persistent HPV infection because SCFAs, which destroy the vaginal mucosa, are secreted. The changes in CST-III and CST-IV-B clusters in our results suggest that the balance of VMB may be disrupted in the HPV and CIN groups. HPV infection may break the healthy vaginal microenvironment and build it suitable for the growth of pathogenic bacteria. L. crispatus forms a film on the surface of vaginal mucosa and secretes lactic acid to inhibit pathogenic bacteria. Its decrease indicates that the protective effect of VMB in the vagina is downregulated.In all three groups, the proportions of CST-III and CST-IV-B were gradually increased, whereas the proportions of CST-I and CST-IV-A were gradually decreased. Previous studies indicated that domination with Lactobacillus spp. result in a weakened VMB homeostasis and a higher risk of HPV infection and growth of pathogenic bacteria. In addition, with the logistic regression analysis, during so many factors, only HPV infection was the risk factor for CIN. We wanted to find out the relationship between HPV infection and CIN, and we did not have a positive result.According to the logistic regression analysis, some factors including age, contraception, CST types, number of pregnancy, number of sexual partners, and IUD implant have relationship with HPV infection. Because the age was a continuous variable, we chose it and we wanted to find the trend with the increasing of age. The possibility of HPV infection, cervical lesions, and proportion of CST-IV-B gradually increased with age, but other CST clusters gradually decreased. This suggests that the status of VMB in Chinese women became worse with age. Factors such as reduced L. gasseri deficiency in Chinese women, it is necessary to study both genetic and social factors by exploring the differences in gene expression in their reproductive tract and their unique living, eating, and cleaning habits. We also need protracted studies that track the average time Chinese women clear HPV infection or develop cervical lesions. This could be compared with studies in other countries and regions to examine if L. gasseri deficiency in Chinese women delays HPV infection clearance and promotes cervical lesions. If true, then they are possibly at higher risk of HPV infection than women in other regions, thus making HPV vaccination more important. The promotion of the HPV preventive vaccine in China came 10 years later than that in other countries. It is not included in China’s medical insurance, so there is no official vaccination rate available. Because of the possible delayed HPV infection clearance in Chinese women, it is necessary to be fully vaccinated against HPV. Further studies should explore the preventive effect of the vaccine in Chinese women.To understand the reasons for Aging is a large research area associated with a variety of factors including decreased hormone levels, metabolic changes, and nutrient loss. In addition to the continuous variable of age, other factors also played a role in HPV infection. Non-use of contraception was a risk factor, whereas CST, pregnancy, number of sexual partners, and IUD were protective factors. In the research of CIN, HPV infection was the only risk factor and other factors did not have effect in CIN. Further research is needed on the mechanism between increased HPV infection and age. Previous studies focused on specific physiological stages such as pregnancy, perimenopause, and adolescence, but our research covered all women of reproductive age. It was a cross-sectional study, lacking long follow-up and mechanism research.Chinese scholars started to study VMB later than foreign scholars. At present, studies are still focused on the stage of phenomenon observation, with a small amount of data from mostly cross-sectional studies. Further research can be extended to gene expression, epidemiological statistics, and mechanism studies. The effect of HPV preventive vaccination on the cervical health of Chinese women is also worth studying. Although the mechanism of aging is complex and there is no consensus, its effect on HPV infection and VMB is worth studying as well.L. gasseri domination in Chinese women was different compared with studies in other countries. The large sample size showed the changing trend of CST subtypes with HPV infection and cervical lesion progression. Aging was a risk factor of HPV infection, but there is a need to study the mechanism of HPV infection and cervical lesion development.In conclusion, our research brings essential comparable data to the Chinese vaginal microbiome research. We found that the lack of The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: NCBI; PRJNA787754.The studies involving human participants were reviewed and approved by Aviation General Hospital Ethics Committee. The patients/participants provided their written informed consent to participate in this study.YiZ: experiment design, sample collection, experimental operation, and article writing. XX: sample collection and experimental operation. LY, XS, MM, and LX: sample collection. JP: partly data analysis. YoZ: provision of laboratory. PL and GW: experiment guidance. GG: experiment design and experiment guidance. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


During the pandemic, restrictions set by the Italian Government were primarily based on the regional level of key parameters including hospitalization and incidence rates. We aimed to build a specific plot to monitor trends and trigger early alerts, with daily updates publicly available on a National Portal.A multidisciplinary team conceived and implemented a new composite plot, developing ad hoc R scripts on top of a specialised database, built in collaboration with the Ministry of Health. We calculated the doubling time Td as log(2)/log(1+r/100), where r is the daily change of target parameters and Td ranges between , and not determined for constant or missing values. We calculated Td daily, as either doubling (growth) or halving (decrease) time. To visualize trends, we assembled two different types of graphs: a bivariate plot showing the path of each point  over time, and a line plot of Td over time. The Y axis was inverted for doubling times, as lower Td indicate higher alert in this case. The two graphs were arranged in lines, using cutoffs for excessive high values for doubling times and low values for halving times. A third line was included to display trends of the target parameter over time.https://www.agenas.gov.it/covid19/web/index.php?r=english%2Fdoubling&q=ITA&t=0). Since July 2021, we used the doubling plot to monitor the three main parameters adopted to set restrictions for Covid-19: a) occupancy rates in intensive care; b) occupancy rates in medical wards; c) weekly incidence rates. The plot highlighted growth trends and early alerts, particularly in the initial phases of growth.The plot was successfully realized and published on the Portal for all regions in February 2021 (The doubling plot can provide useful information to trigger early responses for pandemic control in decentralised governance. R code is available open source from AGENAS for free use.• The doubling plot was conceived and implemented on a National Portal to trigger early alerts of Covid-19 progression in Italian Regions and Autonomous Provinces.• The plot could be rapidly adapted to legislative parameters and can be useful in different situations to monitor epidemic growth and support public health policies.


Drawing from the stimulus–organism–response (S-O-R) model, this study explores the impact on consumer attitudes in the context of Chinese online influencers' e-commerce live streaming. To examine this impact, we distributed our survey questionnaire to Chinese consumers with live streaming shopping experiences. Using data from 430 valid questionnaires, a hierarchical regression analysis was used to examine our hypotheses. The results show that expertise, bargaining power, post-sales services, and live streaming schedules of online influencers affect consumer trust in online influencers. The expertise, bargaining power, and livestreaming schedules of online influencers affect consumer impulsivity. Moreover, the trust and impulsiveness of online influencers increase consumer purchasing intentions. The implications and future research directions are discussed in this article. The live streaming economy started in 2019. With the outbreak of COVID-19 in the spring of 2020, a large number of Chinese residents restrained from outdoor activities and started watching live streaming on their mobile phones at home, thus fueling the rapid rise of live streaming platforms such as Tik Tok and Kuaishou. By the late 2020, the number of users watching live streaming in China reached 617 million, accounting for 62.4% of the total number of Internet users  is the earliest concept proposed by Lazarsfeld et al.  in the PThe stimulus–organism–response (S-O-R) model , which iSince the S-O-R model has become one of the key theories for studying and explaining user behavior, it has been introduced into different research contexts, including information systems, advertising, e-commerce, and education, covering user behavior, participation behavior, and user comments  in this survey. Some of questions of trust are designed according to the article by McAllister . Zhou etThis study uses the Statistical Package for the Social Science Software Automatically  and projects. As can be seen from Regression analysis mainly determines the causal relationship between variables. In this analysis, the expertise, live streaming schedule, bargaining power, and post-sales services of online influencers are considered independent variables X; trust and impulsiveness as intermediary variables M; and purchase intentions as dependent variables Y. The influence relationship between them is analyzed by hierarchical regression. The reason for using hierarchical regression in this study is that the theoretical model includes some mediator variables. The study by Chen et al.  showed tIt can be seen from * Live streaming schedule + 0.267 * Bargaining power + 0.003 * Post-sales service + 0.269 * Expertise.Purchase intentions = −0.121 + 0.387 * Live streaming schedule + 0.166 * Bargaining power + 0.057* Post-sales service.Impulsiveness = 0.211 + 0.531 * Live streaming schedule + 0.313 * Bargaining power – 0.078 ast Post-sales service + 0.393 * expertise.Trust = 0.129 + 0.264 * Live streaming schedule + 0.096* Bargaining Power – 0.003* Post-sales service + 0.080* Expertise + 0.493 * Impulsiveness + 0.285 * Trust.Purchase intentions = −0.262 + 0.050 There are six relevant indicators involved in the study of mediation effects, which are described in * B is the product of A and B, that is, the mediating effect; and 95% BootCI indicates the 95% confidence interval calculated using bootstrap sampling. It is significant if the interval does not contain 0. If both A and B are significant and C′ is trivial, then this is a complete concord. If A and B are significant, C′ is significant, and A * B is of the same sign as C′, it is a partial mediating effect. If at least one of A and B is not significant and the 95% BootCI of A * B includes the number 0 (not significant), the mediating effect is not significant. If at least one of A and B is not significant, the 95% BootCI of A * B does not include the number 0 (significant), and C′ is not significant, it is fully mediated. If at least one of A and B is not significant, the 95% BootCI of A * B does not include the number 0 (significant), C′ is significant, and A * B and C′ have the same sign, then it is a partial mediation effect.A is the regression coefficient of X on M; B is the regression coefficient of M on Y; A To further test our hypotheses, we performed a series of hierarchical multivariate regression analyses. The final results are shown in The validation results show that impulsivity has a moderating effect on professionalism, bargaining power, live streaming schedule, and purchasing intentions, and professionalism, bargaining power, live streaming time, and purchasing intentions are positively correlated. Thus, assumptions 5, 6, 7, and 9 are supported.There are three theoretical contributions to our study. First, by reviewing relevant literature on influencing factors of consumer behavior on live streaming platforms, this study contributes to the literature on e-commerce (Wongkitrungrueng and Assarut, In this study, the S-O-R model and two mediating variables, trust and impulsiveness, are used to further explore the relationship between the professionalism, bargaining power, post-sales services, and live streaming schedules of online influencers, and consumer purchasing intentions. The results show: first, professionalism, bargaining power, post-sales services, and live streaming schedules of online influencers can enhance consumer trust in them. The higher the consumers' trust in an online influencer, the more favorable it will be for improving the consumers' purchasing intentions. In other words, trust acts as an intermediary between professionalism, bargaining power, post-sales services, and live streaming schedules of online influencers, and consumer purchasing intentions. Second, professionalism, bargaining power, and live streaming schedules of online influencers can enhance the impulsive nature of consumer purchasing intentions. The more impulsive consumers are when watching live streaming shopping, the better it is for boosting consumer buying intentions. As a result, impulsivity mediates the relationship between the professionalism, bargaining power, and live streaming schedules of online influencers and consumer buying intentions.From a business and brand perspective, live streaming provides a better sales channel than traditional retail and online shopping. The most popular online influencers such as Li Jiaqi and Luo Yonghao have created sales records: Li's sales reached 12.13 billion yuan on 20 October 2021 (Bai et al., From the point of view of online influencers, the four characteristics discussed in this study can be used to increase the purchasing intentions of consumers and hence the turnover of live streams. The most famous example is Jiaqi Li, who is called “Lipstick Brother No. 1” on the Internet. He used to work in cosmetics sales, and his knowledge of cosmetics is highly professional. His fan base is made up of beauty-conscious young women, and he mainly recommends women's cosmetics. Because of his expertise, female cosmetics consumers trust him so much that they are willing to buy cosmetics from his studio. At the same time, because of its huge sales, for instance, his sales reached 12.13 billion yuan on 20 October 2021, brands always offer him the lowest price in the whole Internet so as to attract more consumers and form a virtuous circle (Brodie et al., From a consumer perspective, the professionalism of influencers, their bargaining power, post-sales services, and live streaming schedules discussed in this study are all criteria for consumers to measure influencers, thus continuously raising the threshold for influencers to enter the industry. As a result of the market competition in this industry, a large number of influencers have been gradually eliminated by the market, which proves that the market competition is constantly improving the professional quality of influencers and standardizing e-commerce live streaming, so as to better meet the rights and interests of consumers. Influencers need to accurately target their audience and schedule their live content accordingly. It is also necessary to continuously improve product quality and enhance customer trust to achieve healthy product sales development.The government argues that live streaming appears to lack regulation, such as Viya's tax evasion. In addition to tax evasion, false claims, data fraud, the sale of counterfeit goods, poor post-sales services, and the additional problems that keep popping up, the industry as a whole has uncovered a large number of normative loopholes during its massive growth. The government is continuously optimizing the environment for e-commerce live streaming. Consumers should understand ways to safeguard their rights and interests. The code of conduct for e-commerce live streaming was published for the first time in 2020 in China, clarifying the duties, obligations, and rights of merchants, influencers, platforms, and other participants in the e-commerce live streaming industry. Consumers can understand the relevant content and enhance their risk awareness. Consumers can use laws to protect their rights and interests, such as the Consumer Rights and Interests Protection Act of the People's Republic of China, to safeguard their legitimate rights and interests and protect themselves.Although our study has yielded certain results, there are some gaps. First, in terms of the study sample, although the questionnaire was publicly available on the Internet, the non-probabilistic sampling resulted in a regionally selective bias in the study sample. Most of the samples were from a limited number of Chinese provinces, while fewer samples were from different provinces. The convenience of having samples from the same region and in the same company allowed educational background and income and other conditions to deviate from reality. There is a large gap between the two sets of data in the analysis of the multi-group structure equation model. It is expected that future studies will continue to improve the collection of sample data. Second, the choice of variables is not comprehensive. The environmental stimulus variables involved in e-commerce live streaming are limited, and other forms of stimulus, such as text, are not included. Third, the recall method used in data collection does not guarantee data recovery quality. Therefore, in future, relatively immediate feedback methods such as neurophysiology can be used to identify research variables and improve the precision of variable measurements.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent from the patients/participants or patients/participants legal guardian/next of kin was not required to participate in this study in accordance with the national legislation and the institutional requirements.XW developed the theoretical framework and worked on literature review, data collection and analysis, and manuscript writing. NA contributed to the literature review, theoretical implications, and manuscript writing. AA worked on the manuscript. All authors contributed to this article and approved the submitted version.Author XW was employed by Gansu Province Highway Traffic Construction Group Co., Ltd. Author AA was employed by Beijing Changping Technology Innodevelop Group. The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Human papillomavirus (HPV) E7 proteins bind to host cell proteins to facilitate virus replication. Interactions between HPV E7 and host cell proteins can also drive cancer progression. We hypothesize that HPV E7-host protein interactions specific for high-risk E7 contribute to the carcinogenic activity of high-risk HPV. The cellular protein ZER1 interacts with the E7 protein from HPV16, the genotype most frequently associated with human cancers. The HPV16 E7-ZER1 interaction is unique among HPV E7 tested to date. Other E7 proteins, even from closely related HPV genotypes, do not bind ZER1, which is a substrate specificity factor for a CUL2-RING ubiquitin ligase. In the present study, we investigated the contribution of ZER1 to the carcinogenic activity of HPV16 E7. First, we mapped the ZER1 binding site to specific residues on the C terminus of HPV16 E7. We showed that the mutant HPV16 E7 that cannot bind ZER1 is impaired in the ability to promote the growth of primary keratinocytes. We found that ZER1 and CUL2 contribute to, but are not required for, HPV16 E7 to degrade RB1. Cancer dependency data show that ZER1 is an essential gene in most HPV-positive, but not HPV-negative, cancer cell lines. Depleting ZER1 impaired the growth of primary keratinocytes expressing HPV16 E7 or HPV18 E7 and of HPV16-and HPV18-positive cervical cancer cell lines. Taken together, our work demonstrates that ZER1 contributes to HPV-mediated carcinogenesis and is essential for the growth of HPV-positive cells. Human papillomaviruses (HPVs) are a diverse family of small double-stranded DNA viruses with a specific tropism for keratinocytes in stratified mucosal or cutaneous epithelia. Several hundred HPV genotypes have been identified, but only up to 15 “high-risk” HPVs from the genus alpha cause cancer at mucosal sites , 3.HPV16 and HPV18 are the high-risk genotypes most commonly associated with human cancers . HPV16 i6–1 to the S phase of the cell cycle and promote cellular proliferation  with the amino acids corresponding to HPV16 E80 and D81  mutated 10.1128/mbio.02033-22.1FIG S1P < 0.0001). (B) Primary HFKs stably expressing Flag-HA-tagged wild-type HPV16 E7, HPV18 E7, HPV16 E7 E80A/D81A, HPV18 E7 Q87E/Q88D, or an empty vector were subjected to anti-HA immunoprecipitation. Whole-cell lysates and immunoprecipitates were separated by SDS-PAGE and Western blotted with antibodies to HA, ZER1, and RB1. Download FIG S1, EPS file, 1.5 MB.Introduction of E80 and D81 to the C terminus of HPV18 E7 does not enable increased cell growth or ZER1 binding. (A) Primary HFK were transduced with retroviral vectors encoding HPV E7. Population doublings were calculated based on the number of cells plated and collected at every passage. Statistical significance of the difference between HPV16 E7 and HPV16 E7 E80A/D81A, HPV18 E7 and HPV18 E7 Q87E/Q88D, and HPV16 E7 and HPV18 E7 conditions at day 26 was determined by two-way ANOVA with Sidak’s correction for multiple comparisons  of 0 h. The half-life of RB1 (t1/2) was calculated for each condition based on a linear regression of each data set. Download FIG S2, EPS file, 1.3 MB.HPV16 E7 E80A/D81A prolongs the half-life of RB1. Quantification of RB1 protein levels in the cycloheximide experiment. The intensity of the bands in the RB1 Western blotting was quantified using ImageJ software. The graph indicates the amount of RB1 protein at each time point after cycloheximide treatment relative to the empty vector control at time -selected RNA from HFK transduced with GFP, wild-type HPV16 E7, or HPV16 E7 E80A/D81A. We selected gene ontology (GO) term 0006270, DNA replication initiation as a representative list of E2F target genes . Comparehttps://depmap.org/). Nearly all the cell lines in which ZER1 is predicted to be an essential gene were from cancers caused by HPV (The Cancer Dependency Map (DepMap) project uses genome-wide loss-of-function screens to determine which genes are essential in hundreds of different cancer cell lines , 55. Gend by HPV . We grapd by HPV . The HPV10.1128/mbio.02033-22.3FIG S3https://depmap.org/). Each dot represents a cell line. A score of 0 denotes that a gene is nonessential, whereas a score of −1 corresponds to the median of all common essential genes. All but two of the cell lines with Chronos scores of less than or equal to −0.5 contain HPV DNA. Download FIG S3, EPS file, 1.5 MB.HPV-positive cells depend on ZER1 to survive. ZER1 Chronos dependency scores of multiple cancer cell lines were downloaded from the DepMap website , HeLa (HPV18-positive), and C33A (HPV-negative) cells with a retrovirus encoding Flag-HA-tagged HPV16 E7, and we performed IP-WB analysis. ZER1 interacted with HPV16 E7 in all cervical cancer cell lines, demonstrating that ZER1 is expressed and can bind to HPV16 E7 in each cell line . Then, wAlthough many HPV E7-host protein-protein interactions have been identified, the biological role of most of them remains to be elucidated. In addition, it is unclear which of these interactions contributes to the carcinogenic activity of high-risk HPV E7. One well-characterized activity of high-risk HPV E7 proteins is to bind and degrade RB1 to promote cell cycle reentry in differentiated keratinocytes. Several HPV E7 proteins also recruit the ubiquitin ligase UBR4 to target PTPN14 for degradation, thereby repressing keratinocyte commitment to differentiation and promoting carcinogenesis , 57. In ZER1 ligase complex to target RB1 for degradation, so we tested whether the inability to degrade RB1 could account for the growth defect exhibited by the HPV16 E7 ZER1 binding-deficient mutant. In gel filtration experiments, we found that HPV16 E7, ZER1, and CUL2 coeluted together with some RB1 but that HPV16 E7 and RB1 also exist in fractions separate from CUL2/ZER1  restored some, but likely not all, hypophosphorylated RB1 protein in HPV16 E7-expressing cells  experiment, ll lines . The obsZER1 is required for the growth-promoting activity of HPV16 E7. However, we have not ruled out the possibility that an activity of ZER1 unrelated to CUL2 is essential in HPV-positive cells. Future work will focus on determining whether the ligase activity of CUL2ZER1 is required for the growth-promoting activity of HPV16 E7 and, if so, what substrates are targeted for ubiquitination by HPV16 E7/CUL2ZER1. Given that ZER1 is essential in HPV-transformed cells regardless of HPV genotype, future studies will investigate the role of ZER1 in cancer cells caused by other high-risk HPV. Specifically, we aim to determine whether ZER1 affects the same pathways and/or substrates in HPV16-positive cells as in cells transformed by other high-risk HPVs. Inhibiting ZER1 and/or the HPV16 E7-ZER1 interaction could limit the growth of cancers caused by high-risk HPV.Our results emphasize the importance of future studies on HPV and ZER1. Most existing data on ZER1 are related to its function as a substrate specificity factor of a CUL2 E3 ligase complex. We therefore favor the model that the ubiquitin ligase activity associated with CUL2Chimeric HPV16 and HPV18 E7 genes were cloned using splicing by overlap extension PCR. N-terminal and C-terminal HPV16 E7 and HPV18 E7 sequences were amplified using a pDONR-Kozak-HPV16 E7 plasmid see . A list 10.1128/mbio.02033-22.4TABLE S1Table S1, PDF file, 0.02 MB.Chimeric HPV16-18 E7 cloning. Download Copyright © 2022 Nouel and White.2022Nouel and White.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the 10.1128/mbio.02033-22.5TABLE S2Table S2, PDF file, 0.02 MB.Plasmids used in the study. Download Copyright © 2022 Nouel and White.2022Nouel and White.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the 2, and penicillin-streptomycin. SiHa, HeLa, Caski, and C33A cells were cultured in Dulbecco’s modified Eagle medium (DMEM) supplemented with 10% fetal bovine serum and penicillin-streptomycin. During cycloheximide treatments, cells were treated with 40 μg/mL cycloheximide in cell culture media and harvested at the indicated time points.Primary human foreskin keratinocytes (HFKs) were obtained from the Skin Biology and Diseases Resource-based Center (SBDRC) at the University of Pennsylvania. HFK and N/Tert-1 cells   were culRetroviral and lentiviral constructs were packaged in 293 Phoenix or 293T cells, respectively, as described in reference For anti-HA immunoprecipitation experiments, N/Tert-1 cells were grown at high density using a 1:1 mixture of K-SFM and DF-K media (DF-K mix) as previously described . BrieflyPrimary HFKs were engineered and cultured as described in cell culture and transductions. Population doublings were calculated based on the number of cells collected and plated at every passage. The growth of the cells was monitored for 1 to 2 months.Western blotting was performed by separating protein lysates on 4 to 20% gradient polyacrylamide gels (Bio-Rad) and transferring protein to polyvinylidene difluoride (PVDF) membranes as previously described . Membran10.1128/mbio.02033-22.6TABLE S3Table S3, PDF file, 0.01 MB.Antibody information. Download Copyright © 2022 Nouel and White.2022Nouel and White.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the Fresh N/Tert-1 cell pellets were lysed in mammalian cell lysis buffer  containing protease and phosphatase inhibitors at a final concentration of 10 mM sodium fluoride, 0.1 mM sodium orthovanadate, 5 mM β-glycerophosphate, 0.5 mM phenylmethylsulfonyl fluoride, 5 μg/mL leupeptin, and 1 μg/mL pepstatin A. The cell lysate was incubated for 15 min on ice and then centrifuged at maximum speed for 10 min. The supernatant was further filtered using a 0.2-μm PVDF syringe filter (Cytiva). The Superose 6 10/300 GL column (Cytiva) was loaded with about 6 mg of total protein and run on a Pure fast protein liquid chromatography (FPLC) system with a flow rate of 0.5 mL/min. Five-hundred-microliter fractions were collected. The even-numbered fractions were subjected to HA immunoprecipitation and analyzed by Western blotting. Size standards were generated using a gel filtration marker kit of protein molecular weights that ranges from 29,000 to 700,000 Daltons (Sigma-Aldrich).The RNeasy minikit (Qiagen) was used to isolate total RNA from three independently transduced populations of HFK-GFP, HFK-16E7, and HFK 16E7 E80A/D81A cells. Poly(A) selection, reverse transcription, library construction, sequencing, and initial analysis were conducted by Novogene. Relative expression data for selected genes were extracted using Novosmart analysis software.https://depmap.org/). The data set was graphed based on the type of cancer and HPV status.ZER1 Chronos dependency scores were downloaded from the DepMap website  with accession number


Head and neck squamous cell carcinoma (HNSCC) tumor phenotypes and clinical outcomes are significantly influenced by etiological agents, such as HPV infection, smoking, and alcohol consumption. Accordingly, the intratumor microbiome has been increasingly implicated in cancer progression and metastasis. However, few studies characterize the intratumor microbial landscape of HNSCC with respect to these etiological agents. In this study, we aimed to investigate the bacterial and fungal landscape of HNSCC in association with HPV infection, smoking, and alcohol consumption. RNA-sequencing data were extracted from The Cancer Genome Atlas (TCGA) regarding 449 tissue samples and 44 normal samples. Pathoscope 2.0 was used to extract the microbial reads. Microbe abundance was compared to clinical variables, oncogenic signatures, and immune-associated pathways. Our results demonstrated that a similar number of dysregulated microbes was overabundant in smokers and nonsmokers, while heavy drinkers were characterized by an underabundance of dysregulated microbes. Conversely, the majority of dysregulated microbes were overabundant in HPV+ tumor samples when compared to HPV- tumor samples. Moreover, we observed that many dysregulated microbes were associated with oncogenic and metastatic pathways, suggesting their roles in influencing carcinogenesis. These microbes provide insights regarding potential mechanisms for tumor pathogenesis and progression with respect to the three etiological agents. HNSCC is the seventh most common cancer in the world, accounting for over 930,000 new cases and 467,000 deaths in 2020 . Head anF. nucleatum and Porphyromonas gingivalis within the oral cavity, were found to promote tumor progression in mice [Recent studies of the human microbiome have revealed its crucial role in the development of a variety of human diseases, including arthritis ,10, infl in mice . A panca in mice , demonst in mice . FurtherA defining feature of HNSCC is the distinct phenotypes and varying efficacies of those treatments influenced by etiology. Infection with the human papilloma virus (HPV), tobacco usage, and alcohol consumption are the most influential risk factors of HNSCC . The incIn this study, we characterized the similarities and differences in the HNSCC intratumor microbiome according to HPV, smoking, and alcohol etiologies using RNA-sequencing data from TCGA. We first identified those microbes differentially abundant according to these cohorts, evaluated their associations with clinical patient variables, and finally studied their correlations with cancer and immunological pathways . With thhttp://gdac.broadinstitute.org/), accessed on 27 September 2022. For the purposes of this project, we investigated three patient etiologies associated with HNSCC occurrence and progression: smoking, alcohol consumption, and HPV infection. Previous studies have suggested that each of these etiologies may independently alter the intratumor microbial landscape of HNSCC [In order to identify intratumor microbes in head and neck squamous cell carcinoma (HNSCC), we extracted raw RNA-sequencing data from The Cancer Genome Atlas (TCGA). Specifically, we extracted bacterial read counts for 449 primary tissue samples and 44 normal samples, and fungal read counts for 443 primary tissue samples and 43 normal samples . The cliof HNSCC ,36,37, aAfter successfully extracting bacterial and fungal reads from 493 and 485 patients, respectively, we removed any potential contaminants with three methods of contamination correction. The bacterial and fungal contaminants are shown in Due to the known impact of localization, age, and sex on HNSCC prognosis and outcomes, we first checked for any distinct differences in the microbial landscape of HNSCC according to these factors using principal component analysis (PCA) . We did p-value of <0.05 and a log-fold change (FC) > 1. The Bonferroni method was used to correct the p-values for multiple hypothesis testing. We identified 161 total microbes dysregulated between tumor and normal tissue  and tumor neoplasm presence, which suggests that the dysregulation of these particular microbes may contribute to cancer pathogenesis and metastasis.We found that eight fungal species underabundant in the tumor samples were significantly dysregulated in clinical variable comparisons . SpecifiInosperma fulvum, Phlyctochytrium arcticum, and uncultured Cryptomycota displayed the strongest statistical significance in differential abundance analyses and comparisons with clinical patient data  and an absence of perineural invasion in the HPV- tumor samples. Interestingly, the presence of Pseudogymnoascus destructans 20631-21 is associated with a lower pathological stage but patient death in vital status follow-up. In total, we found that the abundance of 13 microbes was significantly associated with clinical patient variables. As such, our results show that HPV+ HNSCC and HPV- HNSCC are characterized by distinct intratumor microbial landscapes, which are clinically relevant to patient prognosis.We found 31 fungi and two bacteria to be differentially abundant between the HPV+ tumor samples and the HPV- tumor samples . Specifient data . In the Leptotrichia buccalis C-1013-b displayed the most significant overabundance in the nonsmoking HPV- tumor samples , while Saccharomyces cervisiae YJM244 displayed the most significant overabundance in the smoking HPV- tumor samples . Four microbes, Leptotrichia buccalis C-1013-b, Haemophilus parainfluenzae T3T1, Punctularia strigosozonata HHB-11173 SS5, and Fomitiporia mediterranea MF3/22, were overabundant in the HPV- HNSCC nonsmokers and were significantly correlated with clinical patient variables, whereas no overabundant microbes in the HPV+ HNSCC smokers displayed significant correlations with clinical patient variables , accessed on 2 September 2022. we classified all available pathways into the following collections from the literature: Antitumor, Cell Cycle/Growth, DNA damage, Inflammation, Metabolism, Metastasis, Oncogenic, Protumor, and Tumor-Suppressive. Only statistically, significantly  < 0.25)-enriched signatures were included.We used gene set enrichment analysis (GSEA) to correlate microbial abundance with known oncogenic and immunological signatures ,45. Fromn = 31,919), followed by those signatures associated with metastasis  in both HNSCC and the adjacent normals. Across HNSCC cancer patients, we observed that many dysregulated fungal microbes and several dysregulated bacterial microbes were associated with the enriched oncogenic, tumor-suppressive, and immune-associated (IA) pathways. Similar trends were observed in the adjacent normal samples as well. As such, we more closely examined the correlations between the dysregulated microbes and the known oncogenic and immune-associated pathways with respect to each of the three main etiologies discussed in this study.In both the HNSCC tumor samples and the adjacent normals, the dysregulated fungal microbes disproportionately accounted for the enriched pathways when compared to the dysregulated bacteria species A. The dyWe found that a disproportionately small number of microbes significantly enriched the oncogenic and IA signatures in HPV+ and HPV- HNSCC when compared to the other etiology groups B. In HPVUncultured bacterium enriched the oncogenic signatures in both the HPV- HNSCC and HPV+ HNSCC groups. In the HPV- tumor samples, we found that the overabundance of the uncultured bacterium was correlated with the upregulation of the REACTOME_OLFACTORY_SIGNALING_PATHWAY oncogenic pathway , metastasis , and carcinogenesis  (n = 606) vs. smokers (n = 0). In particular, the overabundance of Agaricus bisporus in the HPV- smoking tumor samples was correlated with an increased expression of the following pathways: REACTOME_SHC1_EVENTS_IN_ERBB2_SIGNALING, PID_HIF1_PATHWAY, and PID_EPO_PATHWAY  C. Overal_PATHWAY B.Fomitiporia mediterranea MF3/22 and Haemophilus parainfluenzae T3T1 was correlated with the upregulation of several pathways corresponding to carcinogenesis and metastasis , while bacteria species predominantly contributed to the enriched pathways in nondrinkers  , followed by pathways associated with metabolism . In HNSCC heavy drinkers, the oncogenic (n = 35) and antitumor pathways (n = 25) were primarily enriched by fungal species, although a higher prevalence of enriched oncogenic  and antitumor  pathways was observed in the HNSCC nondrinkers. Notably, we observed that the abundance of Gromochytrium mamkaevae in heavy drinkers was closely associated with the REACTOME_MET_PROMOTES_CELL_MOTILITY and REACTOME_INTEGRIN_CELL_SURFACE_INTERACTIONS oncogenic signatures  D. Interegnatures C. PrevioHaemophilus parainfluenzae T3T1 is correlated with all three mechanisms of decreased carcinogenesis, while Leptotrichia buccalis C-1013-b is associated with downregulated oncogenic pathways and better patient prognosis, and Fomitiporia mediterranea MF3/22 is associated with upregulated tumor-suppressive pathways and better patient prognosis. Additionally, we found 11 bacteria and 15 fungal microbes associated with increased carcinogenesis. A total of four unique fungal species were associated with the upregulation of oncogenic pathways pertaining to metastasis, cell growth, and inflammation. Moreover, we observed that four fungal species and six bacterial species were correlated with the downregulation of tumor-suppressive pathways, while 10 unique microbes were identified to be representative of a worse overall prognosis.We further classified the GSEA results to identify those microbes associated with increased and decreased carcinogenesis . We defiPunctularia strigosozonata HHB-11173 SS5 is associated with upregulated oncogenic pathways and worsened patient prognosis. Interestingly, the microbe Haemophilus parainfluenzae T3T1 was also associated with decreased carcinogenesis, specifically, the upregulation of oncogenic pathways and downregulation of tumor-suppressive pathways. Given the dual role of Haemophilus parainfluenzae T3T1 as both a cancer-promoting and -inhibiting microbe, further studies are required to fully elucidate the mechanisms and circumstances in which it may act as a cancer promoter or inhibitor.Notably, we found that In this study, we characterized the intratumor microbiome in HNSCC according to its most significant etiologies: HPV infection, tobacco smoking, and alcohol consumption. Previous studies have demonstrated that tumor profiles, mutations, and infiltrating immune cells are uniquely modulated by HPV status ,55 and tActinomycetaceae, Prevotellaceae, Veillonellaceae, Campylobacteraceae, and Bacteroidetes and a lower abundance of Gemellaceae [Proteobacteria phylum in smokers, among other dysregulated species [Microbes residing within the oral cavity and the nearby tissues are also significantly dysregulated according to these etiologies. In a study of 495 patients, those with oral HPV exhibited significant oral microbiome beta-diversity when compared to those without HPV, specifically, with a higher abundance of ellaceae . Further species . Studies species . HoweverSaccharomyces Cerevisiae YJM195 was positively associated with advanced pathological N-stage. However, evidence has shown that Saccharomyces Cerevisiae species have a tumor-suppressive role in colorectal cancer and are implicated in cell growth inhibition, B cell activation, and epithelial cell apoptosis [Saccharomyces Cerevisiae within the HNSCC tumor microenvironment, which was negatively associated with patient prognosis in our study.In this study, we extracted RNA-sequencing from TCGA for 449 HNSCC primary tumor samples and 44 adjacent solid tissue normal samples. After removing any potential contaminants, we found that the vast majority of the dysregulated microbes were overabundant in the normal samples when compared to the tumor samples. Our results are consistent with previous findings that microbial species are underabundant in tumor tissue when compared to adjacent normal tissue. We additionally found that several fungal microbes were relevant to pathological staging. In particular, poptosis ,62. ThusWhile current studies on the microbiome and HPV infection in HNSCC are limited, one study reported the overabundance of several bacterial species in HPV+ HNSCC saliva samples . As suchuncultured Cryptomycota, an overabundant fungus in HPV+ HNSCC samples, was associated with neoplasm presence and a higher pathological stage. As a newly discovered phylum, many Cryptomycota species have yet to be cultured. We predict that this novel microbe may have critical implications in the modulation of cancer outcomes and may act as a biomarker for HPV-associated HNSCC. However, further studies are required to fully understand the role that this microbe may play in cancer onset and progression.Interestingly, we found that the majority of dysregulated fungal and bacterial microbes were overabundant in HPV+ tumor tissue when compared to HPV- tumor tissue. Specifically, we found that Candidatus Mycoplasms haemolamae and Saccharomyces cerevisiae YJM244, were commonly dysregulated, whereas the majority of the dysregulated microbes were unique to smoking or HPV+ patients. Further studies invitro are needed to validate the mechanisms that contribute to the distinct microbial landscapes observed in these patients.When considering HPV- smoking and HPV- nonsmoking comparisons, we observed that the direction of microbial dysregulation was more balanced, with a similar number of microbes overabundant in both the smokers and nonsmokers. Only those microbes significantly overabundant in nonsmokers, however, were associated with clinical variables. Interestingly, all clinically significant microbes were associated with a lower pathological stage, indicating that these microbes may play protective roles in patient prognosis. Given that smoking is known to deplete and alter the function of microbes in the oral epithelia , it is pFurthermore, our findings suggest that HNSCC-heavy drinkers experience an underabundance of bacterial and fungal species. Despite previous studies that have noted significant differences in the oral microbiome between drinkers and nondrinkers , our finWhile most studies of the oral microbiome and intratumor microbiome in HNSCC focus on those bacterial species sequenced through 16s sequencing, we found that microbial dysregulation in cancer, HPV, and smoking were characterized primarily by a dysregulation in the fungal species. Fungal species additionally accounted for the vast majority of the enriched oncogenic and immune-associated signatures across these etiological cohorts. However, among the alcohol cohorts, we observed that, primarily, the fungal species contributed to the enriched oncogenic and immune-associated pathways in heavy drinkers, while the bacterial species contributed to the majority of the enriched pathways in nondrinkers. As such, further studies should investigate the mechanisms by which alcohol consumption may modulate the functional pathways and interactions of bacteria and fungi in the intratumor microbiome, with an emphasis on the oncogenic effects of fungal species in drinkers and bacterial species in nondrinkers.Haemophilus parainfluenzae T3T1 is associated with signatures that both regulate increased and decreased carcinogenic activity. Haemophilus parainfluenzae is a normal oral florum, a known inflammatory agent, and the cause of several acute diseases in the respiratory tract [Haemophilus parainfluenzae is associated with an increased risk of EGFR+ nonsmall cell lung cancer [Our analysis of the oncogenic and immunological signatures revealed that ry tract . Additiog cancer  and may g cancer . While oIn all, our findings suggest that the intratumor microbiome in HNSCC differs greatly according to HPV infection, smoking history, and alcohol consumption. Previous studies of the intratumor microbiome in HNSCC have largely focused on bacterial species through 16s sequencing. To the best of our knowledge, we are the first to investigate the fungal microbial landscape across these three primary etiologies. Subsequently, the fungal microbial landscape appeared to have a more characteristic role in etiology-based HNSCC. In particular, we identified overabundant microbes in each etiology, some of which were associated with clinical patient and prognostic variables. Furthermore, microbial species demonstrated unique correlations between oncogenic and immunological pathways across these cohorts, indicating their unique involvement and roles in cancer pathogenesis within the tumor microenvironment according to these etiologies. Nonetheless, the results in our study are correlative; therefore, further invitro validation is necessary to elucidate the exact role and mechanisms by which these microbes may contribute to tumor growth or inhibition according to these etiologies.Raw whole transcriptome RNA-sequencing data were downloaded from The Cancer Genome Atlas (TCGA) for 528 HNSCC primary tumor samples and 44 adjacent solid tissue normal samples. Clinical patient data were obtained from the Broad Genome Data Analysis Center (GDAC) Firehose.RNA-sequencing data were filtered for bacterial and fungal reads through direct alignment to a reference library of known bacterial and fungal signatures, using the PathoScope 2.0 framework and the NCBI nucleotide database. A total of 79 tumor samples failed to yield successful alignments for bacterial genomes, and 85 tumor samples and one normal sample failed to yield successful alignments for fungal genomes and were thus eliminated from the dataset. Our final dataset consisted of 449 primary tissue samples and 44 normal samples for analyses concerning bacteria, and 443 primary tissue samples and 43 normal samples for analyses concerning fungi. Aitchonson’s log-ratio transformation was conducted to normalize extracted read counts and reduce variability between samples.We analyzed all data in the following four cohorts based on etiology to limit the effect of confounding variables: (1) 449 HNSCC samples and 44 adjacent normals, (2) 99 HPV+ cancer samples and 427 HPV- cancer samples, (3) 153 HPV- smoking cancer samples and 92 HPV- nonsmoking cancer samples, and (4) 60 nondrinkers, 97 moderate drinkers, and 63 heavy drinkers, all of which were cancer samples. For the HPV cohorts, only HPV+ or HPV- patients were included. Some of our patients did not have either an HPV+ or HPV- diagnosis so they were excluded. All clinical information was extracted from the clinical patient file, which was obtained from the Broad Genome Data Analysis Center (GDAC) Firehose. We did not analyze HPV- nonsmoking samples for those analyses concerning nondrinkers, moderate drinkers, and heavy drinkers, as we did not have a substantial number of patients to do so. We categorized nondrinkers, moderate drinkers, and heavy drinkers according to the frequency of alcohol consumption, as defined by Urashima et al. . For theIn order to account for contamination in our samples, we conducted contamination correction by sequencing date and plate to identify potential contaminants and remove them from our datasets. First, boxplots were created to correlate microbial abundance to each respective sequencing plate. Microbes that were disproportionately overabundant across sequencing plates were identified as potential contaminants. Next, scatterplots were created to correlate microbial abundance with date of sequencing. Microbes that were disproportionately overabundant for less than three sequencing dates were identified as potential contaminants. Lastly, we compiled a list of common hospital and sequencing contaminants from previously published studies. We identified and removed these respective contaminants if they were found to be present in our datasets.p-value < 0.05. Significantly dysregulated microbes were used in further analyses.Differential abundance analysis was conducted on the following four defined patient cohorts: (1) primary tumor samples and adjacent normal samples, (2) HPV+ cancer samples and HPV- cancer samples, (3) HPV- smoking cancer samples and HPV- nonsmoking cancer samples, and (4) nondrinkers and heavy drinkers, both of which were cancer samples. Differential abundance analysis was conducted on each of the cohorts for bacterial and fungal data, using the Kruskal–Wallis testing in the edge-R library. Statistically significant results were defined as We also compared differentially abundant microbes in the following two cohorts: (1) HPV+ cancer samples and HPV- cancer samples and (2) HPV- smoking cancer samples and HPV- nonsmoking cancer samples. In order to do so, we examined our differential abundance analysis results for each of these independent cohorts. We then compared the expression of these differentially abundant microbes in each of the two cohorts. We were able to identify microbes that were uniquely abundant in HPV- HNSCC smokers or HPV+ HNSCC nonsmokers. We were also able to identify microbes that were common to both of these independent cohorts.p-value < 0.05). We also adjusted our p-values with the Bonferroni method to correct for multiple hypothesis testing. For the purposes of this study, we examined comparisons to six main clinical variables and features: patient age at diagnosis, neoplasm cancer status, perineural invasion, follow-up vital status, pathologic stage, and cancer TNM staging. Specifically, we examined the comparisons of dysregulated microbes with clinical variables in the following cohorts: HPV+ tumor samples, HPV- tumor samples, HPV- smokers, HPV- nonsmokers, heavy drinkers, and nondrinkers. We did not observe significant clinical variable comparisons for our drinking cohorts, and as such, we did not include them in our results.We compared significantly dysregulated microbes to clinical variables using the Kruskal–Wallis testing in the edge-R library  < 0.25).We conducted Gene Set Enrichment Analysis (GSEA) to correlate microbial abundance to known oncogenic and immunological pathways and signatures. Three primary input files were used for GSEA: the expression file, the phenotype file, and the gene set file. The expression file contained the abundance of the microbes in our sequencing data, the phenotype file contained expression of IA genes, and the gene set file contained differentially abundant microbes that could be targeting IA genes. We used the following GSEA parameters: the Pearson metric for ranking genes, one gene set at a time, and the minimum size for exclusion of the smaller sets as 0. GSEA signatures were from the C2, C6, and C7 collections from the Molecular Signatures Database. We classified all signatures and pathways into the following categories based on a literature search: Antitumor, Cell Cycle/Growth, DNA damage, Inflammation, Metabolism, Metastasis, Oncogenic, Protumor, and Tumor-Suppressive. The specific classification files are included in Saccharomyces cerevisiae EC1118 is underabundant in tumor tissue and associated with a higher pathological staging. Uncultured Cryptomycota is overabundant in HPV+ nonsmoking tumor samples and is associated with neoplasm presence and a higher pathological stage. When comparing the HPV-, smoking, and nonsmoking samples, we found that Fomitiporia mediterranea MF3/22 was overabundant in the nonsmoking tumor samples and was associated with a lower pathological stage. We found that Uncultured Cryptomycota is also significantly overabundant in nondrinkers. Interestingly, we also found that Saccharomyces cerevisiae YJM244 is commonly dysregulated in smokers and HPV+ patients when compared to normal tissue, suggesting potential commonalities in their respective microbial landscapes. We found that fungal species primarily enrich the oncogenic and immunological signatures across these etiologies. Within the alcohol comparisons, however, it was found that fungal species primarily enrich these pathways in heavy drinkers, while bacterial species primarily enrich similar pathways in nondrinkers. Finally, Haemophilus parainfluenzae T3T1 was associated with those enriched signatures that promote cases of both increased and decreased carcinogenic activity. Further invitro experiments are needed to validate these differences within these microbial landscapes and further elucidate the mechanisms underlying microbial activity and oncogenesis.In conclusion, our study significantly advances the understanding of intratumor microbial expression in head and neck squamous cell carcinoma. The intratumor microbiome in HNSCC, across cancer samples, and in HPV, tobacco smoking, and alcohol consumption etiologies were compared with clinical patient variables pertaining to cancer prognosis and occurrence. Overall, the microbial signatures are underabundant in tumor tissue compared to adjacent normals, and the majority of the dysregulated microbes across cancer and etiology comparisons are fungal species. Specifically,


Lactobacillus in the vaginal environment as a supplement to interferon therapy. Our results indicated that patients with high risk HPV (Hr-HPV) 16/18 infection had a significantly higher alpha diversity compared with the healthy control (p < 0.01), while there was no significant difference between the non-Hr-HPV16/18 group and the controls (p > 0.05). Patients with multiple HPV infection had insignificantly higher alpha diversity compared with single HPV infection (p > 0.05). The vaginal flora of patients with HPV infection exhibited different compositions when compared to the healthy controls. The dominant bacteria with the highest prevalence in HPV-positive group were Lactobacillus iners , and the top 3 dominant bacteria in the HPV-persistent group were Lactobacillus iners , Sneathia amnii , and Lactobacillus delbrueckii . Patients with HPV clearance had significantly lower alpha diversity, and the flora pattern was also different between groups displaying HPV clearance vs. persistence. The patients with persistent HPV infection had significantly higher levels of Bacteroidaceae, Erysipelotrichaceae, Helicobacteraceae, Neisseriaceae, Streptococcaceae (family level), and Fusobacterium, Bacteroides, Neisseria, and Helicobacter (genus level) than patients who had cleared HPV (p < 0.05).Vaginal flora plays a vital role in human papillomavirus (HPV) infection and progression to cancer. To reveal a role of the vaginal flora in HPV persistence and clearance, 90 patients with HPV infection and 45 healthy individuals were enrolled in this study and their vaginal flora were analyzed. Women with HPV infection were treated with Our study revealed differences in vaginal flora patterns are associated with HPV persistence and its clearance. Interferon plus probiotics can greatly improve virus clearance in some patients. Distinguishing bacterial features associated with HPV clearance in patients would be helpful for early intervention and reverse persistent infection. Human papillomavirus (HPV) infection is one of the most common sexually transmitted infections, and is also the leading cause of cervical cancers . Up to nLactobacillus species: Lactobacillus crispatus (L. crispatus), Lactobacillus iners (L. iners), Lactobacillus gasseri (L. gasseri), and Lactobacillus jensenii (L. jensenii). Lactobacillus spp. form barriers against colonization of bacterial vaginosis (BV)-associated bacteria by maintaining a low pH -β1 mRNA, indicating its immunosuppressive effect in the microenvironment of the invasive cervical cancer  of bacteria in addition to Lactobacilli might be helpful for vaginal microbiome studies  were used to treat the patients with HPV infection, and the entire composition of vaginal microbiota was studied. We also discuss the impact of vaginal flora on HPV clearance.It has been reported that a vaginal flora dominated by non-sistence . Some Lae of HPV . The proobserved . Oral probserved , but itsobserved . Probiotobserved . Given tA participant was eligible if she (a) was 18-60 years old without HPV vaccination, (b) had not undergone a gynecological reproductive surgery such as cervical conization, hysterectomy, appendectomy, hysteroscopy, etc, (c) had no vaginal flushing and had abstained from sex for at least 72 h, (d) had no history of vaginal medication within 3 days, and no systematic use of antibiotics or antifungal drugs, probiotics, antibiotics or glucocorticoids within 1 month, and (e) was HPV-positive upon initial screening. The 21 HPV GenoArray Diagnostic Kit  was used to conducted HPV typing. Genotypes of 21 HPV genotypes ) were detected. Healthy women were enrolled from the physical examination center of Chenghai district people’s hospital; all were HPV-negative. Exclusion criteria: (a) had a vaginal lavage or had sexual activity within 72 hours, (b) used probiotic bacteria, antibiotics, or corticosteroids within the past 30 days, (c) with cancer, diabetes, autoimmune diseases and other serious diseases that may affect the results of this study, (d) was pregnant.A total of 135 participants were included on the basis of the inclusion and exclusion criteria. All procedures for this study were approved by the Research Ethics Committee of the First Affiliated Hospital of Shantou University Medical College (No. 201561).Cervical specimens were collected from female patients between January 2016 and June 2018.® High Fidelity PCR Master Mix with GC Buffer  and Phusion® High-Fidelity DNA polymerase  were used for PCR. After mixing in equal amounts according to the PCR product concentration, electrophoresis purification was performed on a 1× TAE 2% agarose gel, shearing to obtain the band of interest, and the sheared target bands were recovered using a DNA purification kit . The construction of library was performed using Ion Plus Fragment Library Kit 48 , which was sequenced using an Ion S5™XL  after Qubit quantification and library detection.Genomic DNA was extracted from the samples by using the CTAB (Cetyltrimethylammonium Bromide) method. After the detection of purity and concentration of genomic DNA, using genomic DNA diluted with sterile water to 1 ng/μL, specific primers with barcode, New England Biolabs PhusionLow-quality data was removed by using Cutadapt (V1.9.1) . Then bap < 0.05, Dunn’s Test was used to perform pairwise comparisons between each independent group. Measurement data for demographic and clinical characteristics were analyzed using the Kruskal-Wallis test, while the ordinal categorical variable was analyzed using the Wilcoxon rank-sum test. The association between HPV and age, cleaning degree of the vagina, menopause, contraception, non-menstrual bleeding, the number of pregnancies, births, miscarriages, and the number of white blood cells were analyzed by Spearman rank correlation analysis in SPSS 26.0.Alpha diversities were visualized in the box plot using the package “ggplot2” in R software (Version 4.3.0). Principal co-ordinates analysis (PCoA) was conducted on basis of the unweighted UniFrac distance matrix using “vegan”, “Parseq”, and “ggplot2” packages. PERMANOVA analysis was conducted using the “vegan” package. Linear discriminant analysis Effect Size (LEfSe) analysis was done by using LEfSe software, with the default value of the linear discriminant analysis (LDA) score being 2. The Chord diagram was performed using the “circlize” package in R. Kruskal-Wallis tests were employed to analyze differences in microbial α diversity among multiple groups. If p > 0.05) was not statistically significant. Only a small number of women in the three groups were in menopause; the ratio of women in menopause was 13.33% (n = 6) in the controls, 7.14% (n = 2) in Hr-HPV16/18, and 17.74% (n = 11) in non-Hr-HPV16/18 patients, respectively. But patients with non-menstrual bleeding had significant differences among the Hr-HPV16/18, non-Hr-HPV16/18, and the controls (p < 0.01). No positive cases of BV were found, but some cases (n = 14) have tested positive for Ureaplasma urealyticum, M. hominis, and Chlamydia trachomatis, and only one positive case of trichomoniasis. Other parameters, including squamous intraepithelial disease (SIL) grade, menopause, and IUD/tubal ligation/condom, the number of pregnancies, births, miscarriages, and white blood cells, were measured and showed no significant difference (p > 0.05). Detailed demographics and clinical characteristics of participants were showed in In total, 135 participants were included in the research Figure 1p > 0.05), and there was no significant difference between the non-Hr-HPV16/18 groups and the controls (p > 0.05). These results show a higher microbial diversity in the Hr-HPV16/18 groups. No clear separation of samples between the HPV-uninfected and infected groups was showed in PCoA analysis, indicating there were no significant similarity differences in microbial composition among the three groups ; Gardnerella spp. ; Sneathia spp. ; Prevotella spp. ; Klebsiella spp. ; Streptococcus spp. ; Enterococcus spp. ; Staphylococcus spp. ; Atopobium spp. , and Sphingomonas spp.   were:  < 0.05) 5.L. iners ; Sneathia amnii (S. amnii) ; Enterococcus faecalis  ; Sneathia sanguinegens (S. sanguinegens) ; L. gasseri ; Staphylococcus haemolyticus (S. haemolyticus) ; Atopobium vaginae (A. vaginae) ; Prevotella amnii (P. amnii) ; Acinetobacter nosocomialis  , and Prevotella bivia (P. bivia)   were:  < 0.05) Figure 6p > 0.05) (Klebsiella (p < 0.05). In the dual HPV type group, the predominant species were Parvimonas, unidentified Christensenellacea, Candidatus competibacter, unidentified Gammaproteobacteria, Terrimonas, Leisingera, Hyphomicrobium, Terrabacter, unidentified Alphaproteobacteria and Enhydrobacter (p < 0.05). In the multiple HPV type group, the predominant species were Ferruginibacter, Haloactinopolyspora, unidentified Rhizobiaceae, Blastochloris, Vibrio, Ornithinimicrobium, Tetragenococcus, and Castellaniella.We divided patients into three groups: infected by a single HPV type (n = 56), infected by two HPV types (n = 26), and infected by multiple HPV types (n = 8). We further analyzed whether vaginal microbial diversity would be influenced by the number of infected HPV types. Women infected with multiple HPV types tended to have higher alpha diversity than those infected with a single HPV type, but the difference was not statistically significant ( > 0.05) 8. To idWe further analyzed whether vaginal flora affects HPV clearance. There were 26 patients who had HPV clearance within a year, with most turning negative within six months. Analysis of vaginal flora characteristics showed the women with HPV clearance had significantly lower bacterial diversity, with scores of 0.046 for Chao1, and 0.04 for ACE diversity, respectively (p > 0.05), Proteobacteria , Actinobacteria , Fusobacteria , and Bacteroidetes . At the genus level, no significant changes were observed for Lactobacillus , Gardnerella , Sneathia , Prevotella , Klebsiella , Enterococcus , Streptococcus , Staphylococcus , Atopobium , and Sphingomonas  , S. amnii , E. faecalis , S haemolyticus , A. vaginae , Streptococcus intermedius (S. intermedius) , S. sanguinegens , Prevotella timonensis (P. timonensis) , P. amnii , and L. gasseri .The top 20 bacteria were analyzed by heat mapping  than patients who had cleared HPV (p < 0.05).To identify bacteria specifically linked with HPV clearance, LEfSe modeling was conducted (p < 0.05) and ρ = 0.327 (p < 0.05), respectively. The main HPV subtypes and the dominant bacteria detected in all patient samples were selected for a chord diagram  and S. amnii-dominant . The top 3 dominant bacteria in the HPV-persistent group were L. iners , S. amnii , and L. delbrueckii .Spearman correlation analysis was exploited to analyze the correlation between HPV infection and clinical biomarkers. Our results showed that vaginal cleanliness and non-menstrual bleeding were two related factors, with correlation coefficients of ρ = 0.195 , and species , were observed significantly higher in the persistent HPV group than those in the cleared HPV group. LDA analysis showed that Fusobacterium, Bacteroides, Neisseria, and Helicobacter are characteristic bacterial genera that are significantly different between patients with persistent HPV and in patients who cleared HPV. Women with a certain specific composition of vaginal flora might be more susceptible to HPV infection or show faster progression of dysplasia  diversity and prevalence of Hr-HPV infection and/or cervical abnormalities (vs. HPV negative)  . Increasegative) . Consistegative) . Of noteegative) . Becauseegative) .lactobacillus administered vaginally by suppository or vaginal ovule have been explored . Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.JC conceived the study and designed the experiments. MZ and XL performed experiments and analyzed data. XJ and JC wrote the manuscript. FY, SX, XH, and XC revised the manuscript extensively. All of the authors have discussed and approved the final version of the manuscript.