MicroRNAs in HPV-induced cervical cancer
Babion, I.
2020
document version
Publisher's PDF, also known as Version of record
Link to publication in VU Research Portal
citation for published version (APA)
Babion, I. (2020). MicroRNAs in HPV-induced cervical cancer: Triage markers for cervical screening and drivers
of carcinogenesis.
General rights
Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain
• You may freely distribute the URL identifying the publication in the public portal ?
Take down policy
If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.
E-mail address:
PART I: MiRNAs as Triage Markers in HPV-Based Cervical
Screening
Cervical Screening
After breast, colorectal, and lung cancer, cervical cancer is the fourth most common cancer in women worldwide and accounted for 6.9% of cancer related deaths in 20181,2. Screening for cervical disease allows for early detection and
treatment of high-grade precancerous lesions (CIN2/3) and has led to effective prevention of cervical cancer in developed countries3,4. The Netherlands have
recently implemented primary testing for high-risk human papillomavirus (hrHPV) for cervical screening, as it provides better protection against CIN2/3 and cervical cancer than cytological evaluation of cervical scrapes5,6.
To increase screening coverage, self-sampling of cervico-vaginal material is offered to women who do not react on a first invitation to participate in the regular screening6–8. Because primary hrHPV-testing also detects transient
hrHPV infections, it requires a triage test for colposcopy to identify women with clinically relevant disease (CIN2 or worse; CIN2+) among all hrHPV-positive women. Recommended triage strategies currently include cytology at baseline with repeat cytology after 6 or 12 months (The Netherlands) and baseline cytology in combination with HPV16/18 genotyping with or without repeat cytology after 6 months (USA)9. Cytology, however, is subjective and cannot be
reliably performed on self-collected material10. Women with a hrHPV-positive
self-sample consequently need to visit their physician for a cervical scrape, which results in a loss to follow-up7,8,11–13. Objective triage tests that are directly
applicable to both cervical scrapes and self-samples are therefore needed to further improve cervical screening. To date, a number of molecular changes associated to cervical disease have been suggested as triage markers.
Recent Developments for the Triage of hrHPV-Positive Women
The value of HPV genotyping, such as risk stratification based on HPV16/18 genotyping or full high-risk HPV genotyping, either or not combined with cytology triage, is currently widely studied14,15. While HPV16/18 genotyping
can be performed directly on cervical scrapes and self-samples, it offers limited sensitivity for CIN3 and cancer in population-based screening cohorts and should therefore not be used as stand-alone triage test9,16,17. Combining
HPV16/18 genotyping and viral load, however, potentially provides an alternative molecular triage test in the future14. HPV genotyping has been suggested to
become particularly important with the implementation of hrHPV-based screening in a growing number of countries and vaccinated women entering the
9
screening program, but follow-up algorithms are complicated and difficult to implement in clinical practice.
In addition, dual-stained cytology for p16inka4 and Ki-67 (CINtec® PLUS), a
surrogate marker for transformed cervical cells, has been shown to decrease inter-observer variability compared to conventional cytology, thereby increasing reproducibility18–20. For the detection of CIN3+ (CIN3 or worse), it offers higher
specificity than traditional cytology at comparable sensitivity21,22. While
dual-stained cytology partially eliminates the drawbacks posed by conventional cytology, it is not reliably applicable to self-sampled material either18,19,23.
Thirdly, molecular changes underlying the carcinogenic process are particularly promising, as they offer objective triage markers that are directly linked to cervical disease and can potentially be analyzed directly in cervical scrapes and self-samples in a high-throughput fashion. DNA methylation analysis of viral genes and host cell genes, in particular, is rapidly gaining interest24,25. DNA
methylation markers, such as FAM19A4 and miR124-2, have achieved promising results for the triage of hrHPV-positive cervical scrapes and self-samples26,27.
A negative FAM19A4/miR124-2 triage test was shown to provide a comparable risk for CIN3+ and a lower cancer risk as negative cytology triage after 14 years of follow-up28,29, indicating that molecular triage indeed offers an appropriate
alternative to cytology. More recently identified methylation markers, such as ASCL1, GHSR, LHX8, SST, ST6GALNAC5, and ZIC1, had a higher CIN3 detection rate than FAM19A4 and miR124-2 in comparable populations30,31. These markers
are amongst the presently most promising triage markers for cervical screening, but long-term CIN3+ risk data are lacking.
Next to DNA methylation markers, differentially expressed miRNAs have emerged as attractive molecular triage markers32. Although a great number
of differentially expressed miRNAs has been identified in cervical tissue samples33, the translation of miRNA expression analysis as triage method for
hrHPV-positive cervical scrapes and self-samples is lagging behind. Expression analysis of miRNAs has a number of potential advantages over DNA methylation analysis: (1) miRNAs are remarkably stable molecules that can be reliably quantified even in degraded RNA preparations34, and (2) expression analysis
of multiple miRNAs and reference genes by quantitative PCR following reverse transcription (qRT-PCR) requires as little as 20ng small RNA (Chapter 2-5)
compared to 250ng of DNA for methylation analysis. These advantages are exemplified in Chapter 3, where we successfully performed miRNA expression
analysis in archival cervical scrapes that had been stored at room temperature for at least one year. In addition, we showed in Chapter 5 that the technical
dropout rate on the same archival material was more than two times higher for DNA methylation analysis than miRNA expression analysis, while the latter also required less input. Robustness of the biomarker assay is particularly important when sample quality might get compromised due to suboptimal storage and/ or transportation conditions to central diagnostic laboratories, as is the case in low-resource settings.
Evaluation of miRNAs as Triage Markers in hrHPV-Based Cervical Screening
Quantitative RT-PCR is currently the gold standard for expression analysis of individual miRNAs and potentially allows for high-throughput analysis of clinical samples. Analysis of miRNA expression by qRT-PCR, however, requires adequate data normalization to account for non-biological variability introduced during the experimental procedure. In Chapter 2, we therefore evaluated the suitability
of 11 candidate reference genes for the normalization of miRNA qRT-PCR data obtained from cervical tissues, scrapes, and self-samples and propose an easily applicable strategy for the selection and evaluation of reference genes. By this means, we defined different reference panels for the three sample types and confirmed that adequate normalization indeed reduces technical variability and increased signal-to-noise ratios when applied to two candidate miRNA markers. These data demonstrate that reference genes need to be carefully selected, even if sample types originate from the same anatomical source. Importantly, identification of suitable miRNA reference genes for cervical specimens will improve reproducibility between studies and thereby facilitate reliable miRNA profiling studies for triage purposes in the future.
Following the identification of suitable reference genes, we used two approaches to select candidate miRNA markers for cervical cancer screening: (1) to warrant biological relevance, miRNAs that become either genetically or epigenetically deregulated during cervical disease progression35,36 were selected as candidate
triage markers (Chapter 3), and (2) the clinically most promising miRNAs were
identified following a discovery screen using small RNA sequencing (sRNA-Seq) directly on self-samples (Chapter 4). When comparing the two approaches
with respect to discriminatory marker panels, however, caution should be taken due to the different sample types included in both studies (Chapter 3: scrapes, Chapter 4: self-samples). As suggested by the different selection of reference genes for cervical scrapes and self-samples (Chapter 2), the optimal miRNA
9
triage markers might be different for both sample types as well. Results from
Chapter 3 showed that the (epi)genetically deregulated miRNAs miR-15b-5p
and miR-375 are promising triage markers, enabling the detection of a subset of CIN3 and all carcinomas in hrHPV-positive cervical scrapes. Besides their triage potential, these miRNAs were found to affect viability of cervical cancer cells in vitro, indicating that they directly contribute to cervical disease progression. Our whole miRNome approach on hrHPV-positive self-samples in Chapter 4
demonstrated that altered miRNA expression is also detectable in self-samples. Validation of selected miRNA candidates by qRT-PCR yielded a 5-miRNA panel with comparable performance as found for cervical scrapes in Chapter 3.
Notwithstanding the difference in sample type analyzed, two miRNAs included in our (epi)genetically deregulated candidate miRNA panel from Chapter 3
(miR-9-5p and miR-15b-5p) were also among the clinically most promising
miRNAs identified with the whole miRNome approach (Chapter 4). This overlap
further supports our hypothesis that functionally relevant miRNAs are clinically meaningful, too. In Chapter 5, we therefore analyzed the ten most promising
miRNAs from Chapter 3 and Chapter 4 in hrHPV-positive cervical scrapes from
a gynecological outpatient cohort. As the final 3-miRNA panel in this cohort consisted of miRNAs from both approaches, this indicates that both selection strategies are valid and complementary.
Notably, a combination of multiple miRNAs generally improved detection of cervical disease (Chapter 3-5). The fact that the individually most discriminatory
miRNAs were not always included in the final miRNA panel (Chapter 3 and Chapter 5) illustrates the benefit of combining several complementary miRNAs.
MiRNAs, which are transcribed in unison from so-called miRNA clusters37 (e.g.
miR-100-5p and miR-125-5p in Chapter 3), are unlikely to provide additional
information to each other. In the future, a discovery screen in hrHPV-positive scrapes obtained from the current screening program in combination with functional screens offers a promising approach for the identification of the most discriminatory miRNA markers. The selection of valuable candidate miRNAs is further ensured by integration of externally obtained data, so-called co-data, such as miRNA abundance, conservation status, and functional relevance38,39.
Fully molecular screening requires molecular triage markers that are at least as sensitive and specific as the current triage method, i.e. cytology. Currently, a direct comparison between cytology and miRNA expression analysis as triage tool for hrHPV-based screening is still missing. HrHPV-positive
cervical scrapes included in our studies were either initially triaged by cytology (Chapter 3) or originated from a gynecological outpatient cohort
(Chapter 5). Due to the resulting cytology bias and the selection of CIN0/1
lesions with normal cytology, respectively, miRNA expression analysis and cytology could not be directly compared. To allow for a direct comparison between the two triage strategies, the optimal miRNA panel should be tested in parallel with cytology on consecutive hrHPV-positive women in the Dutch screening program. Women, who are positive for one and/or both triage tests, should be referred for colposcopy. Similarly, future studies investigating whether miRNA expression analysis in self-samples offers the same protection against cervical disease as cytological examination of hrHPV-positive cervical scrapes are warranted.
Currently, our miRNA panels (Chapter 3-5) do not meet the established criteria
to be acceptable for triage40. Further panel optimization is therefore required
before analysis of miRNA markers can offer reliable molecular triage testing. As the translation from sRNA-Seq, the present gold standard to study global miRNA profiles, to valuable qPCR markers proved difficult in Chapter 4, the discovery
method of choice remains to be determined. The relatively high discrepancy between sRNA-Seq and qPCR41,42 is likely explained by the fact that sRNA-Seq also
detects miRNA length variants, so-called isomiRs43,44, whereas these isomiRs are
not or not fully captured by the qPCRs designed for canonical miRNAs45. IsomiRs
may themselves constitute a novel class of biomarkers according to a recent study demonstrating that isomiR profiles can differentiate between 32 cancer types46. Before isomiRs can provide useful triage markers applicable to cervical
screening, however, advances in the detection of individual isomiRs are required to guarantee reliable quantification. Considering that next-generation sequencing (NGS) becomes increasingly affordable, targeted sequencing approaches might eventually replace qPCR for the expression analysis of selected miRNAs and potentially allow for the detection of individual isomiRs.
Complementarity between miRNAs and Other Molecular Triage Markers
To improve triage of hrHPV-positive women, it has frequently been suggested to combine cytology with HPV16/18 genotyping (reviewed in 47,48). Data on the
complementarity of miRNAs with other molecular markers, however, is still very limited. Combining miRNA expression analysis with HPV16/18 genotyping in
Chapter 3 improved the clinical performance of the miRNA panel, indicating
9
DNA methylation markers have yielded promising results for the triage of hrHPV-positive women13,17,26,30,31,49,50. In Chapter 5, we directly compared the triage
capacity of our 3-miRNA panel (miR-149-5p, miR-20a-5p, and miR-93-5p) to the established methylation marker FAM19A451 in the same set of samples and found
that the performance of our miRNA panel was not significantly different from that of FAM19A4 methylation for the detection of CIN3. Stratification of CIN2 and CIN3 lesions by lesion volume (low and high) and hrHPV type (HPV16, HPV18, and other hrHPV types) suggested that FAM19A4 methylation is particularly predictive for high-volume and HPV16-associated CIN3. The 3-miRNA panel, on the other hand, was independent of hrHPV type and detected more CIN2 lesions, suggesting that expression changes of at least some miRNAs precede DNA methylation of FAM19A4. Alternatively, miRNA expression changes might be easier to detect, as a single cell may contain hundreds of copies of one particular miRNA, whereas DNA methylation has a lower dynamic range. Interestingly, when we combined miRNA expression analysis with FAM19A4 methylation analysis we obtained a significantly better performance than the 3-miRNA panel or FAM19A4 methylation analysis alone, indicating complementarity between the two marker types for CIN3 detection. In line with our results, a panel of two miRNAs (miR-31 and miR-210) and two methylation markers (RASSF1A and 3OST2) has been shown to offer higher sensitivity and specificity for the detection of non-small-cell lung cancer in sputum than panels consisting of either three miRNAs or three methylation markers52. Likewise, the
so-called miMe panel comprised of nine miRNAs and three methylation markers has recently been demonstrated to predict prostate cancer outcome after radical prostatectomy53. While the combination of miRNAs and methylation markers is
promising, the technical implementation is still rather challenging. Advancing (targeted) sequencing techniques might overcome this drawback in the future by allowing simultaneous analysis of miRNA expression and DNA methylation. Above data indicate that the CIN2/3 lesions detected by miRNA markers may be partially different from those detected by methylation markers. CIN2/3 lesions are known to represent a heterogeneous disease, reflected by a variable duration of existence and a variable risk of progression to cancer54. In a subset of CIN2/3
lesion, high levels of DNA methylation markers and increased copy number aberrations similar to cervical cancers have been observed and associated with a presumed high cancer risk26,30,55. These so-called advanced lesions with high
risk molecular profiles would require immediate referral and treatment. CIN lesions with low risk molecular profiles on the other hand could potentially
be managed by a watch-and-wait policy, which will reduce over-referral and overtreatment54. To further optimize miRNA-based triage strategies for the
detection of CIN lesions in need of referral a better understanding of the role of miRNAs in cervical carcinogenesis is required.
PART II: MiRNAs and Other Molecular Changes as Drivers
of HPV-Induced Transformation
MiRNA Function and miRNA Targets in Cervical Cancer Cells
Many molecular alterations have been associated to hrHPV-induced transformation based on genome-wide analyses of cervical tissue specimens. To understand how miRNAs contribute to cervical carcinogenesis, nevertheless, it is important to study both the mechanisms remodeling the miRNA profile and the consequences of deregulated miRNA expression. Alterations in the miRNA-processing machinery can cause miRNA expression changes or result in the generation of isomiRs as found in Chapter 4. In Chapter 8, we provide
an overview of current literature on miRNA-modifying enzymes in hrHPV-associated cancers. Besides altered miRNA-processing enzymes, genetic and epigenetic changes affect miRNA expression. To study the molecular interactions driving carcinogenesis and to assess the biological consequences of deregulated miRNA expression, combined analysis of tissue specimens with in vitro cell line models provide a useful tool. Figure 1 provides an overview of the molecular interplay during hrHPV-induced transformation studied in this thesis.
SiHa, CaSki, and HeLa cells were established from cervical carcinomas and are widely used to elucidate the mechanisms underlying the development of cervical disease. To date, a vast number of miRNA-mRNA interactions have been predicted and cell lines are widely used to validate these interactions. One of our most promising markers,miR-15b-5p, plays an oncogenic role by promoting cell viability in SiHa and CaSki (Chapter 3). Integration of mRNA and miRNA
expression profiles obtained from cervical tissue samples has identified RECK as direct target of miR-15b-5p and this interaction was confirmed by luciferase assay in vitro (unpublished data). RECK is a membrane-anchored glycoprotein that has been described to inhibit migration and invasion of cervical cancer cells by promotion of p53 signaling56. Strikingly, RECK has also been identified as
direct target of miR-15b-5p in prostate cancer57.A HITS-CLIP (high-throughput
9
designed to identify miR-15b-5p targets and related pathways is currently ongoing.
In Chapter 7, we used both tissue specimens and SiHa and HeLa cells to
investigate the varying results concerning the role of miR-9-5p in cervical cancer that have been reported in the past35,59,60. We confirmed upregulation of
5p in cervical squamous cell carcinomas (SCC), while low expression of miR-9-5p in cervical adenocarcinomas (AC) seemed to be caused by DNA methylation of miR-9-5p precursor genes. These differences in miR-9-5p expression and methylation were attributable to both cervical cancer histotype and hrHPV type (HPV16 vs HPV18/other). In vitro experiments confirmed that miR-9-5p functions as oncomiR in SCC (SiHa, HPV16), while the opposite was observed in AC cells (HeLa, HPV18). TWIST1, a transcription factor involved in epithelial-to-mesenchymal transition (EMT), was identified and confirmed as novel direct target of miR-9-5p, which might (partly) explain the dual role of miR-9-5p observed in the two major cervical cancer histotypes. Results in cervical AC cell line HeLa suggest that low levels of miR-9-5p in AC might be necessary to allow the induction of EMT via TWIST1. In cervical SCC cell line SiHa, on the other hand, miR-9-5p plays an oncogenic role, most likely by targeting cell-cell adhesion molecule CDH161–67. The dual role of miR-9-5p in carcinogenesis is not
unique to cervical cancers, but has also been found in other tumors (reviewed in 60). Hence, it is important to take the cell type of origin and other clinical and
molecular characteristics, such as hrHPV type, into account when studying the biological relevance of miRNAs in cell line models.
Molecular Interactions during hrHPV-Induced Transformation In Vitro
Transfection of primary keratinocytes with either HPV16 or HPV18 has created the opportunity to study hrHPV-induced transformation in a longitudinal fashion68,69.
In Chapter 6, we used these cell line models to study the interplay between
the different molecular events associated with hrHPV-induced transformation to gain insight in their biological relevance for cervical carcinogenesis. Chromosomal, mRNA, and miRNA expression profiles were determined in four individual hrHPV-transformed keratinocyte cell lines. Eight different passages representing different stages of hrHPV-induced transformation were included for every cell line. Using the same model, we previously found a set of miRNAs that become increasingly methylated during transformation. These findings were confirmed in cervical tissue samples70, underlining the clinical relevance
Integrative analyses identified novel miRNA-mRNA interactions, for which the exact contribution to cervical carcinogenesis remains to be elucidated. In addition, we found that the acquisition of anchorage independence is associated with increased chromosomal instability and that approximately one third of the observed differential m(i)RNA expression was associated with the resulting chromosomal alterations. This is in contrast to previous reports, where 12.0% of differentially expressed mRNAs and only 4.7% of differentially expressed miRNAs were linked to copy number changes in cervical tissues35,71. The discrepancies might
be explained by different experimental approaches and statistical methods used to study the association between copy number and gene expression. While other studies analyzed cross-sectional clinical material, we had the unique opportunity to follow copy number and gene expression changes within the specific cellular background of our four transforming cell lines over time.
The clear molecular distinction between anchorage-dependent and -independent passages of our cell line model of hrHPV-induced transformation suggests that
Figure 1. Overview of the interplay between different molecular levels contributing to hrHPV-induced transformation. This overview is not exhaustive but provides a summary of molecular changes discussed in this thesis. * Wilting et al.35,36, here analyzed as candidate triage markers
9
anchorage-independent cell growth represents a highly relevant functional read-out when studying cervical carcinogenesis in vitro. Based on this observation, a functional screen investigating the miRNA and mRNA drivers of anchorage independence is currently being performed in the same cell line model. Integration of our longitudinal multi-level data from Chapter 6 with results
obtained from this functional screen will provide new insights on the biological relevance of individual molecular changes and contribute to the selection of the most promising markers. Here, we found that pathways enriched among copy number related mRNAs, i.e. focal adhesion, mTOR, and TGF-β signaling, are implicated in the resistance of detachment-induced cell death (anoikis) and EMT, which are both important for the acquisition of anchorage-independence72.
Further integrated longitudinal analysis the TGF-β signaling pathway identified PITX2 as one of the key regulators of TGF-β signaling. Overexpression of PITX2 inhibited cell growth of hrHPV-transformed keratinocytes in vitro, supporting its importance in hrHPV-induced transformation.
Besides being a relevant functional read-out, molecular changes driving anchorage independence will likely provide useful markers for disease in the future. As the anchorage-independent phenotype appears specifically associated with chromosomal abnormalities, the analysis of chromosomal changes for diagnostic purposes, by for example Fast-SeqS ( Fast Aneuploidy Screening Test-Sequencing System) or MLPA (multiplex ligation-dependent probe amplification), should therefore be reconsidered73–75.
Conclusions
MiRNA expression analysis represents an attractive triage alternative to cytology, as it offers the possibility to accomplish hrHPV-based cervical screening in a fully molecular fashion. Our early clinical studies have shown the potential of miRNA marker panels for the triage of hrHPV-positive women, both for application on cervical scrapes and self-samples. However, future implementation in screening requires further optimization of miRNA/isomiR detection methods and miRNA triage panels. Towards the latter, more insights into the role of miRNAs in cervical carcinogenesis are essential. Our in-depth molecular analyses of our cell line model of hrHPV-induced transformation and cervical cancer cell lines provide an important contribution to this knowledge. Furthermore, our studies on hrHPV-positive cell line models, which are not specific for the cervix, imply that current findings might be of importance to other hrHPV-induced cancers, too.
REFERENCES
1. Ferlay J., Colombet M., Soerjomataram I., et al. 2018. Estimating the global cancer incidence and mortality in 2018: GLOBOCAN sources and methods. Int. J. Cancer 144(8):1941–1953. 2. Bray F., Ferlay J., Soerjomataram I., et al. 2018. Global cancer statistics 2018: GLOBOCAN
estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA. Cancer
J. Clin. 68(6):394–424.
3. Bulk S., Visser O., Rozendaal L., et al. 2003. Incidence and survival rate of women with cervical cancer in the Greater Amsterdam area. Br. J. Cancer 89(5):834–839.
4. Peto P.J., Gilham P.C., Fletcher O., et al. 2004. The cervical cancer epidemic that screening has prevented in the UK. Lancet 364(9430):249–256.
5. Meijer C.J.L.M., Berkhof J., Castle P.E., et al. 2009. Guidelines for human papillomavirus DNA test requirements for primary cervical cancer screening in women 30 years and older. Int. J.
Cancer 124(3):516–520.
6. RIVM. Bevolkingsonderzoek baarmoederhalskanker - RIVM. Available at: https://www.rivm. nl/Onderwerpen/B/Bevolkingsonderzoek_baarmoederhalskanker [Accessed on 31 August 2018]
7. Gök M., Heideman D.A.M., van Kemenade F.J., et al. 2010. HPV testing on self collected cervicovaginal lavage specimens as screening method for women who do not attend cervical screening: cohort study. BMJ 340:c1040.
8. Gök M., van Kemenade F.J., Heideman D.A.M., et al. 2012. Experience with high-risk human papillomavirus testing on vaginal brush-based self-samples of non-attendees of the cervical screening program. Int. J. Cancer 130(5):1128–1135.
9. Rijkaart D.C., Berkhof J., van Kemenade F.J., et al. 2012. Evaluation of 14 triage strategies for HPV DNA-positive women in population-based cervical screening. Int. J. Cancer 130(3):602– 610.
10. Brink A.A.T.P., Meijer C.J.L.M., Wiegerinck M.A.H.M., et al. 2006. High concordance of results of testing for human papillomavirus in cervicovaginal samples collected by two methods, with comparison of a novel self-sampling device to a conventional endocervical brush. J. Clin.
Microbiol. 44(7):2518–2523.
11. Bais A.G., van Kemenade F.J., Berkhof J., et al. 2007. Human papillomavirus testing on self-sampled cervicovaginal brushes: an effective alternative to protect nonresponders in cervical screening programs. Int. J. Cancer 120(7):1505–1510.
12. Racey C.S., Withrow D.R. & Gesink D. 2013. Self-collected HPV testing improves participation in cervical cancer screening: a systematic review and meta-analysis. Can. J. Public Health 104(2):e159–e166.
13. Verhoef V.M.J., Bosgraaf R.P., van Kemenade F.J., et al. 2014. Triage by methylation-marker testing versus cytology in women who test HPV-positive on self-collected cervicovaginal specimens (PROHTECT-3): a randomised controlled non-inferiority trial. Lancet. Oncol. 15(3):315–322.
14. Adcock R., Cuzick J., Hunt W.C., et al. 2019. Role of HPV genotype, multiple infections and viral load on the risk of high-grade cervical neoplasia. Cancer Epidemiol. Biomarkers Prev. 28(11):1816–1824.
15. Bonde J.H., Sandri M.-T., Gary D.S., et al. 2019. Clinical Utility of Human Papillomavirus Genotyping in Cervical Cancer Screening. J. Low. Genit. Tract Dis. 24(1):1–13.
16. Castle P.E., Stoler M.H., Wright T.C., et al. 2011. Performance of carcinogenic human papillomavirus (HPV) testing and HPV16 or HPV18 genotyping for cervical cancer screening of women aged 25 years and older: a subanalysis of the ATHENA study. Lancet Oncol. 12(9):880–890.
9
17. Verhoef V.M.J., Heideman D.A.., van Kemenade F.J., et al. 2014. Methylation marker analysis and HPV16/18 genotyping in high-risk HPV positive self-sampled specimens to identify women with high grade CIN or cervical cancer. Gynecol. Oncol. 135(1):58–63.
18. Wentzensen N., Fetterman B., Tokugawa D., et al. 2014. Interobserver reproducibility and accuracy of p16/Ki-67 dual-stain cytology in cervical cancer screening. Cancer Cytopathol. 122(12):914–920.
19. Allia E., Ronco G., Coccia A., et al. 2015. Interpretation of p16 INK4a /Ki-67 dual immunostaining for the triage of human papillomavirus-positive women by experts and nonexperts in cervical cytology. Cancer Cytopathol. 123(4):212–218.
20. Gustinucci D., Rossi P.G., Cesarini E., et al. 2016. Use of Cytology, E6/E7 mRNA, and p16
INK4a –Ki-67 to Define the Management of Human Papillomavirus (HPV)–Positive Women in
Cervical Cancer Screening. Am. J. Clin. Pathol. 145(1):35–45.
21. Wentzensen N., Fetterman B., Castle P.E., et al. 2015. p16/Ki-67 Dual Stain Cytology for Detection of Cervical Precancer in HPV-Positive Women. J. Natl. Cancer Inst. 107(12):djv257. 22. Luttmer R., Dijkstra M.G., Snijders P.J.F., et al. 2016. p16/Ki-67 dual-stained cytology for
detecting cervical (pre)cancer in a HPV-positive gynecologic outpatient population. Mod.
Pathol. 29(8):870–878.
23. Yoshida T., Sano T., Kanuma T., et al. 2011. Usefulness of CINtec® PLUS p16INK4a/Ki-67 Double-Staining in Cytological Screening of Cervical Cancer. Acta Cytol. 55(5):413–420. 24. Kelly H., Benavente Y., Pavon M.A., et al. 2019. Performance of DNA methylation assays for
detection of high-grade cervical intraepithelial neoplasia (CIN2+): a systematic review and meta-analysis. Br. J. Cancer 121(11):954–965.
25. Bowden S.J., Kalliala I., Veroniki A.A., et al. 2019. The use of human papillomavirus DNA methylation in cervical intraepithelial neoplasia: A systematic review and meta-analysis.
EBioMedicine (50):246–259.
26. De Strooper L.M.A., Meijer C.J.L.M., Berkhof J., et al. 2014. Methylation analysis of the FAM19A4 gene in cervical scrapes is highly efficient in detecting cervical carcinomas and advanced CIN2/3 lesions. Cancer Prev. Res. 7(12):1251–1257.
27. De Strooper L.M.A., Verhoef V.M.J., Berkhof J., et al. 2016. Validation of the FAM19A4 / mir124-2 DNA methylation test for both lavage- and brush-based self-samples to detect cervical (pre)cancer in HPV-positive women. Gynecol. Oncol. 141(2):341–347.
28. De Strooper L.M.A., Berkhof J., Steenbergen R.D.M., et al. 2018. Cervical cancer risk in HPV-positive women after a negative FAM19A4/mir124-2 methylation test: A post hoc analysis in the POBASCAM trial with 14 year follow-up. Int. J. cancer 143(6):1541–1548.
29. Dick S., Kremer W.W., De Strooper L.M.A., et al. 2019. Long-term CIN3+ risk of HPV positive women after triage with FAM19A4/miR124-2 methylation analysis. Gynecol. Oncol. 154(2):368–373.
30. Verlaat W., Snijders P.J.F., Novianti P.W., et al. 2017. Genome-wide DNA Methylation Profiling Reveals Methylation Markers Associated with 3q Gain for Detection of Cervical Precancer and Cancer. Clin. Cancer Res. 23(14):3813–3822.
31. Verlaat W., Snoek B.C., Heideman D.A.M., et al. 2018. Identification and Validation of a 3-Gene Methylation Classifier for HPV-Based Cervical Screening on Self-Samples. Clin.
Cancer Res. 24(14):3456–3464.
32. Tian Q., Li Y., Wang F., et al. 2014. MicroRNA Detection in Cervical Exfoliated Cells as a Triage for Human Papillomavirus – Positive Women. J. Natl. Cancer Inst. 106(9):dju241. 33. Sharma G., Dua P. & Agarwal S.M. 2014. A Comprehensive Review of Dysregulated miRNAs
Involved in Cervical Cancer. Curr. Genomics 15(4):310–323.
34. Jung M., Schaefer A., Steiner I., et al. 2010. Robust MicroRNA Stability in Degraded RNA Preparations from Human Tissue and Cell Samples. Clin. Chem. 56(6):998–1006.
35. Wilting S.M., Snijders P.J.F., Verlaat W., et al. 2013. Altered microRNA expression associated with chromosomal changes contributes to cervical carcinogenesis. Oncogene 32(1):106–116. 36. Wilting S.M., Verlaat W., Jaspers A., et al. 2013. Methylation-mediated transcriptional
repression of microRNAs during cervical carcinogenesis. Epigenetics 8(2):220–228.
37. Altuvia Y., Landgraf P., Lithwick G., et al. 2005. Clustering and conservation patterns of human microRNAs. Nucleic Acids Res. 33(8):2697–2706.
38. van de Wiel M.A., Lien T.G., Verlaat W., et al. 2016. Better prediction by use of co-data: Adaptive group-regularized ridge regression. Stat. Med. 35(3):368–381.
39. Novianti P.W., Snoek B.C., Wilting S.M., et al. 2017. Better diagnostic signatures from RNAseq data through use of auxiliary co-data. Bioinformatics 33:1572–1574.
40. Dijkstra M.G., van Niekerk D., Rijkaart D.C., et al. 2014. Primary hrHPV DNA Testing in Cervical Cancer Screening: How to Manage Screen-Positive Women? A POBASCAM Trial Substudy. Cancer Epidemiol. Biomarkers Prev. 23(1):55–63.
41. Sapre N., Hong M.K.H., Macintyre G., et al. 2014. Curated MicroRNAs in Urine and Blood Fail to Validate as Predictive Biomarkers for High-Risk Prostate Cancer. PLoS One 9(4):e91729. 42. Koppers-Lalic D., Hackenberg M., de Menezes R., et al. 2016. Non‑invasive prostate cancer
detection by measuring miRNA variants (isomiRs) in urine extracellular vesicles. Oncotarget 7(16):22566–22578.
43. Lee L.W., Zhang S., Etheridge A., et al. 2010. Complexity of the microRNA repertoire revealed by next-generation sequencing. RNA 16(11):2170–2180.
44. Neilsen C.T., Goodall G.J. & Bracken C.P. 2012. IsomiRs – the overlooked repertoire in the dynamic microRNAome. Trends Genet. 28(11):544–549.
45. Schamberger A. & Orbán T.I. 2014. 3′ IsomiR Species and DNA Contamination Influence Reliable Quantification of MicroRNAs by Stem-Loop Quantitative PCR. PLoS One 9(8):e106315.
46. Telonis A.G., Magee R., Loher P., et al. 2017. Knowledge about the presence or absence of miRNA isoforms (isomiRs) can successfully discriminate amongst 32 TCGA cancer types.
Nucleic Acids Res. 45(6):2973–2985.
47. Luttmer R., De Strooper L.M.A., Steenbergen R.D.M., et al. 2016. Management of high-risk HPV-positive women for detection of cervical (pre)cancer. Expert Rev. Mol. Diagn. 16(9):961– 974.
48. Polman N.J., Snijders P.J.F., Kenter G.G., et al. 2019. HPV-based cervical screening: Rationale, expectations and future perspectives of the new Dutch screening programme. Prev. Med.
(Baltim). 119:108–117.
49. De Strooper L.M., van Zummeren M., Steenbergen R.D., et al. 2014. CADM1 , MAL and miR124-2 methylation analysis in cervical scrapes to detect cervical and endometrial cancer.
J. Clin. Pathol. 67:1067–1071.
50. Cook D.A., Krajden M., Brentnall A.R., et al. 2019. Evaluation of a validated methylation triage signature for human papillomavirus positive women in the HPV FOCAL cervical cancer screening trial. Int. J. Cancer 144(10):2587–2595.
51. Luttmer R., De Strooper L.M.A., Berkhof J., et al. 2016. Comparing the performance of FAM19A4 methylation analysis, cytology and HPV16/18 genotyping for the detection of cervical (pre)cancer in high-risk HPV-positive women of a gynecologic outpatient population (COMETH study). Int. J. Cancer 138(4):992–1002.
52. Su Y., Fang H. & Jiang F. 2016. Integrating DNA methylation and microRNA biomarkers in sputum for lung cancer detection. Clin. Epigenetics 8(1):109.
53. Strand S.H., Bavafaye‐Haghighi E., Kristensen H., et al. 2019. A novel combined miRNA and methylation marker panel (miMe) for prediction of prostate cancer outcome after radical prostatectomy. Int. J. Cancer 145(12):3445–3452.
9
54. Steenbergen R.D.M., Snijders P.J.F., Heideman D.A.M., et al. 2014. Clinical implications of (epi)genetic changes in HPV-induced cervical precancerous lesions. Nat. Rev. Cancer 14(6):395–405.
55. Bierkens M., Wilting S.M., van Wieringen W.N., et al. 2012. Chromosomal profiles of high-grade cervical intraepithelial neoplasia relate to duration of preceding high-risk human papillomavirus infection. Int. J. Cancer 131(4):E579–E585.
56. Liu Y., Li L., Liu Y., et al. 2018. RECK inhibits cervical cancer cell migration and invasion by promoting p53 signaling pathway. J. Cell. Biochem. 119(4):3058–3066.
57. Chen R., Sheng L., Zhang H.-J., et al. 2018. miR-15b-5p facilitates the tumorigenicity by targeting RECK and predicts tumour recurrence in prostate cancer. J. Cell. Mol. Med. 22(3):1855–1863.
58. Darnell R.B. 2010. HITS-CLIP: Panoramic views of protein-RNA regulation in living cells.
Wiley Interdiscip. Rev. RNA 1(2):266–286.
59. Zhang J., Jia J., Zhao L., et al. 2016. Down-regulation of microRNA-9 leads to activation of IL-6/Jak/STAT3 pathway through directly targeting IL-6 in HeLa cell. Mol. Carcinog. 55(5):732–742.
60. Nowek K., Wiemer E.A.C. & Jongen-Lavrencic M. 2018. The versatile nature of miR-9/9* in human cancer. Oncotarget 9(29):20838–20854.
61. Seashols-Williams S.J., Budd W., Clark G.C., et al. 2016. miR-9 Acts as an OncomiR in Prostate Cancer through Multiple Pathways That Drive Tumour Progression and Metastasis.
PLoS One 11(7):e0159601.
62. Guinde J., Frankel D., Perrin S., et al. 2018. Lamins in Lung Cancer: Biomarkers and Key Factors for Disease Progression through miR-9 Regulation? Cells 7(7):78.
63. Ma L., Young J., Prabhala H., et al. 2010. miR-9, a MYC/MYCN-activated microRNA, regulates E-cadherin and cancer metastasis. Nat. Cell Biol. 12(3):247–256.
64. Lu M.-H., Huang C.-C., Pan M.-R., et al. 2012. Prospero Homeobox 1 Promotes Epithelial-Mesenchymal Transition in Colon Cancer Cells by Inhibiting E-cadherin via miR-9. Clin.
Cancer Res. 18(23):6416–6425.
65. Song Y., Li J., Zhu Y., et al. 2014. MicroRNA-9 promotes tumor metastasis via repressing E-cadherin in esophageal squamous cell carcinoma. Oncotarget 5(22):11669–11680. 66. Wang H., Wu Q., Zhang Y., et al. 2017. TGF-β1-induced epithelial–mesenchymal transition in
lung cancer cells involves upregulation of miR-9 and downregulation of its target, E-cadherin.
Cell. Mol. Biol. Lett. 22(1):22.
67. Xu X.-Z., Li X.-A., Luo Y., et al. 2019. MiR-9 promotes synovial sarcoma cell migration and invasion by directly targeting CDH1. Int. J. Biochem. Cell Biol. 112:61–71.
68. Steenbergen R.D.M., Walboomers J.M., Meijer C.J.L.M., et al. 1996. Transition of human papillomavirus type 16 and 18 transfected human foreskin keratinocytes towards immortality: activation of telomerase and allele losses at 3p, 10p, 11q and/or 18q. Oncogene 13(6):1249–1257.
69. Steenbergen R.D.M., de Wilde J., Wilting S.M., et al. 2005. HPV-mediated transformation of the anogenital tract. J. Clin. Virol. 32:25–33.
70. Wilting S.M., Miok V., Jaspers A., et al. 2016. Aberrant methylation-mediated silencing of microRNAs contributes to HPV-induced anchorage independence. Oncotarget 7(28):43805– 43819.
71. Medina-Martinez I., Barrón V., Roman-Bassaure E., et al. 2014. Impact of Gene Dosage on Gene Expression, Biological Processes and Survival in Cervical Cancer: A Genome-Wide Follow-Up Study. PLoS One 9(5):e97842.
72. Guadamillas M.C., Cerezo A. & del Pozo M.A. 2011. Overcoming anoikis – pathways to anchorage-independent growth in cancer. J. Cell Sci. 124(19):3189–3197.
73. Belic J., Koch M., Ulz P., et al. 2015. Rapid Identification of Plasma DNA Samples with Increased ctDNA Levels by a Modified FAST-SeqS Approach. Clin. Chem. 61(6):838–849. 74. Wilting S., Snijders P., Meijer G., et al. 2006. Increased gene copy numbers at chromosome
20q are frequent in both squamous cell carcinomas and adenocarcinomas of the cervix. J.
Pathol. 209(2):220–230.
75. Thakral D., Kaur G., Gupta R., et al. 2019. Rapid Identification of Key Copy Number Alterations in B- and T-Cell Acute Lymphoblastic Leukemia by Digital Multiplex Ligation-Dependent Probe Amplification. Front. Oncol. 9:871.
