Co-prevalence of human Papillomaviruses (HPV) and Epstein–Barr virus (EBV) in healthy blood donors from diverse nationalities in Qatar
Authors: Moussa Alkhalaf
Anju Sharma
Ayesha Jabeen
Ali A Sultan
Maria K Smatti
Semir Vranic
Ishita Gupta
Ala-Eddin Al Moustafa
Gheyath K Nasrallah
Hamda A Al-Thawadi
Journal: Cancer Cell International (2020)
Discipline: MOLECULAR BIOLOGY & GENETICS
Keywords: EBV; HPV; Healthy blood donors; Qatar.
Affiliations: 1College of Medicine, QU Health, Qatar University, Doha, Qatar., 2Biomedical Research Centre, Qatar University, Doha, Qatar., Weill-Cornell Medicine-Qatar, Doha, Qatar., 4Faculty of Medicine, Kuwait University, Kuwait City, Kuwait.

Abstract:  Background: Infections by both human oncoviruses, human Papillomaviruses (HPV) and Epstein-Barr virus (EBV) are very common in the adult human population and are associated with various malignancies. While HPV is generally transmitted sexually or via skin-to-skin contact, EBV is frequently transmitted by oral secretions, blood transfusions and organ transplants. This study aims to determine the prevalence and circulating genotypes of HPV and EBV in healthy blood donors in Qatar. Methods: We explored the co-prevalence of high-risk HPVs and EBV in 378 males and only 7 females blood donors of different nationalities (mainly from Qatar, Egypt, Syria, Jordan, Pakistan, and India) residing in Qatar, using polymerase chain reaction (PCR). DNA was extracted from the buffy coat and genotyping was performed using PCR and nested-PCR targeting E6 and E7 as well as LMP-1 of HPV and EBV, respectively. Results: We found that from the total number of 385 cases of healthy blood donors studied, 54.8% and 61% of the samples are HPVs and EBV positive, respectively. Additionally, our data revealed that the co-presence of both high-risk HPVs and EBV is 40.4% of the total samples. More significantly, this study pointed out for the first time that the most frequent high-risk HPV types in Qatar are 59 (54.8%), 31 (53.7%), 52 (49.1%), 51 (48.6%), 58 (47%) and 35 (45.5%), while the most commonly expressed low-risk HPV types are 53 (50.6%), 11 (45.5), 73 (41.7%) and 6 (41.3%), with all the cases showing multiple HPVs infection. Conclusion: In this study, we demonstrated for the first time that HPV and EBV are commonly co-present in healthy blood donors in Qatar. On the other hand, it is important to highlight that these oncoviruses can also be co-present in several types of human cancers where they can cooperate in the initiation and/or progression of these cancers. Therefore, more studies regarding the co-presence of these oncoviruses and their interaction are necessary to understand their cooperative role in human diseases. 

Retracted: No

PubPeer comments:
 Fig.1 HPV6 PCR in EBV+ and EBV- samples appears more similar then expected ![file] Fig.2 Many HPV PCR samples in EBV+ and EBV- samples appears more similar then expected (see colored boxes ![file] , 
 Dear Mr. Heterochasta We are very thankful and grateful to you for pointing our unintentional error. We agree with you about the similarity in the gel images. This was an error in the copy pasting of the image from our part. We did not have any intention of deceiving our readers. In our publication we have unfortunately uploaded the wrong image. We are extremely sorry about this unintentional error. As it can be noted from the figure above, the other subtypes show difference of expression in both EBV-positive and EBV-negative samples. Moreover, these images are only for representative purposes and not for any quantitative purposes. The images do not affect the statistical data presented in the manuscript. I hope this clarifies your concern and we are once again very thankful for all your comments. We have now attached the correct version of both the figures for your kind reference. ![file] ![file] Hope we have answered all your queries. We are once again extremely sorry for this error. , 
 Dear authors, Thank you for your response. Even though the gel pictures are  only representative , your two only figures showing original unprocessed data contain a substantial number of errors, raising concerns about the reliability of data handling and analyses: out of the 21 rows of HPV PCRs on EBV + u2013 samples, 6 lines contain errors. Furthermore, after pointing out theses irregularities, you did not bother to check all your data for integrity, I just saw that HPV-73 (EBV+) and HPV-68 (EBV+) are identical as well: ![file] With this, I hope you understand my difficulties in being convinced by your study. , 
 Dear Mr Heterochasta Due to several images and the vast number of genotyping performed (21 genotypes for more than 300 samples), hence when the figures were prepared there was a probability of having errors. Also due to the high number of gel images there is a chance of getting biased and un-noticing these kind of errors, which we believe were not picked by the reviewers as well, which without a doubt is unintentional. Since these are only a few number of samples represented in the figure you cannot comprehend from this a negative impact on our data integrity. This was just missed from the eye and was not an intentional way of depicting our data. We believe, if we had to manipulate data, we would not have attached the figures. Since the population size is large, please focus on the statistics rather than the figures.![file] ![file] , 
 Dear authors, First, I never made accusations towards data manipulation. Second, of course, errors can happen, but it is the high frequency of errors in the original data you present in your manuscript that I criticize. I believe it is understandable that this causes some lack trust in your data analyses - since representative figures of original data usually serve to demonstrate the validity of your statistic data analyses. And latter ones one cannot evaluate, as a reader. Lets see what the journals editors suggest to do in this case. , 
 I share my concern about data handling for this paper with Heterochasta. The authors state that  due to the high number of gel images there is a chance of getting biased and un-noticing these kind of errors . Could Dr. Gupta please clarify what they mean by that? If a lab generates a lot of similar-looking photos that should actually trigger even more scrutiny in labeling these correctly and inserting them in a paper. For example, all chest-X-rays look very similar, but one would hope that the radiology department would be very careful to not mix them up. In this paper, it appears that at least 7 mix-ups of patient data have been made, and those are only the duplications detected by looking at the photos representing 30 of the 385 subjects, so not even 10% of the data. How certain can the readers be of the validity of the remaining 90% of the data, for which no photos are shown? , 
 **CORRECTION** *Correction to: Cancer Cell Int (2020) 20:107 https: doi.org 10.1186 s12935-020-01190-2* *In this article [1], there was a copy pasting error of the PCR image of the representative data provided in Figures 1 and 2. The corrected figures are published with this erratum (Figs. 1 and 2).* ,