Liquid-based Cytology Research Articles

The incidence of HPV infection of high carcinogenic risk in women of the Kemerovo region

Aim. Toassess the prevalence of various types of human papillomavirus (HPV) of high carcinogenic risk (HCR) and the rate of abnormal findings of cytological examination in HPV-positive and HPV-negative women of the Kemerovo region.
 Materials and methods. A continuous cross-sectional study was conducted. The study included 675 women aged 21 to 65 (mean age 40.510.6 years) residing in the Kemerovo region. Patients were sampled from the cervical canal for semi-quantitative HPV-typing and cytological examination with Papanicolaou staining (PAP-test) using a liquid-based cytology method. For HPV-positive patients, an HPV typing with the quantification of 14 HCR HPV types was performed by polymerase chain reaction with real-time detection. Statistical data processing was performed using the StatSoft Statistica 6.1 software bundle.
 Results. The mean rate of HCR HPV detection in women of the Kemerovo region in the age group of 2165 years is 17.8% and decreases with age. HPV type 16 prevailed and was detected in 31.6% of women. In 19.2% of women, the HPV subtype 31 was diagnosed; in 18.3%, the subtype 35; in 16.7%, the subtype 33. The HPV subtypes 39, 56, and 66 were the rarest. One subtype of HCR HPV was detected in 26.7% of women, two subtypes in 6.7%, and three or more subtypes in 66.6% of women. According to the cytological examination, CIN 1, 2, and 3 rates were 3.3, 0.8, and 0.7%, respectively. HSIL (CIN 23) was detected in 1.5% of cases, LSIL (CIN 1) in 3.3%. The rate of CIN 1 in HPV(+) women was higher: 13.3% vs 1.0% in HPV(-) (2=43.197; p0.001). CIN 2 and CIN 3 were reported in HPV(+) patients only. HSIL+ was diagnosed in 7.9% of HPV(+) females (2=39.778; p0.001).
 Conclusion. Thus, the study results showed that the mean infection rate of HCR HPV in women of the Kemerovo region at the age of 2165 years is 17.8% and decreases with age. HPV subtype 16 is predominant; subtypes 31, 35, and 33 were less common. In HPV-positive women, abnormal findings of cytological examination were significantly more common.

Cervical human papillomavirus prevalence according to socioeconomic and demographic characteristics in a large Danish screening population.

The aim of this study was to investigate high-risk human papillomavirus (hrHPV) prevalence according to socioeconomic and demographic characteristics in a Danish screening population. We used data from HPV SCREEN DENMARK, which was an implementation study embedded into the routine cervical cancer screening programme. During 2017-2020, women aged 30-59 years screened in the Region of Southern Denmark were offered HPV testing or cytology. In the HPV group, liquid-based cytology samples were tested for 14 hrHPV types. We obtained registry information on socioeconomic and demographic characteristics and used log-binomial regression to estimate the prevalence ratio (PR) of hrHPV in three age groups (30-39, 40-49, 50-59 years), adjusting for age and marital status. We included 31,124 HPV unvaccinated women. In all age groups, the age-adjusted hrHPV prevalence was higher in women with basic versus higher education (e.g. age 30-39: 11.9% vs. 9.5%; PRage-adjusted=1.24; 95% confidence interval (CI): 1.02-1.50); women who were unemployed vs. employed (e.g. age 30-39: 11.6% vs. 10.4%; PRage-adjusted=1.11; 95% CI: 0.95-1.28); and in women with highest vs. lowest income (e.g. age 30-39: 11.6% vs. 9.5%, PRage-adjusted=1.18, 95% CI: 0.98-1.44). In models adjusted for marital status, these associations largely disappeared. We found slightly higher hrHPV prevalences in women with basic education, low income and unemployment. The differences largely disappeared when taking into account marital status as a potential proxy for sexual behaviour. Our findings support a need for targeted information on safe sexual practices and promoting socioeconomic equality in HPV vaccination and cervical cancer screening participation.

The digital expression profile of BMP7, CDKN2C, HIST1H3G, and PKMYT1 genes improves high-grade cervical lesion detection in liquid-based cytology.

Some studies reported that differential gene expression could be used as a biomarker for high-grade cervical lesion identification. The aim was to evaluate the gene expression profile of cervical intraepithelial neoplasia (CIN) to identify a gene expression signature of CIN2+ in liquid-based cytology (LBC) samples. LBC samples (n=85) obtained from women who underwent colposcopy were included with benign (n=13), CIN1 (n=26), CIN2 (n=16), and CIN3 (n=30) diagnoses. After RNA isolation, gene expression profiling was performed using the nCounter PanCancer Pathways, which consists of 730 cancer-related genes. The genes identified were in silico expression evaluated using the UALCAN database. An accurate prediction model to discriminate CIN2+ from <CIN2 lesions was determined. Immunohistochemistry was performed to assess the expression of p16 and Ki67 proteins. This study identified a gene expression profile that significantly differentiates CIN2+ cases from <CIN2. The gene signature comprised 18 genes, two genes downregulated and 16 upregulated. In silico analysis corroborated the differential expression of 11 of those genes. Further observed was that high expression of BMP7 (odds ratio [OR],4.202), CDKN2C (OR,5.326), HIST1H3G (OR,3.522), PKMYT1 (OR,4.247), and menarche age (OR,1.608) were age-adjusted and associated with CIN2+. This model demonstrates a probabilityof43% leading to an area under the curve (of.979; sensitivity of 94.9%, and specificityof91.2% for CIN2+ prediction. It was observed that p16 expression was significantly associated with CDKN2A mRNA overexpression (p=.0015). A gene expression profile that may be helpful in the identification of patients with CIN2+ was identified. This approach could be used together with currently used LBC in a clinical setting, allowing the identification of patients with high risk of CIN2+.

Comparison of the Hologic Genius Digital Diagnostics System with the ThinPrep Imaging System-A retrospective assessment.

Digital cytology (DC) with artificial intelligence (AI) is a new approach. The authors compared DC with liquid-based cytology (LBC) using computer assistance (CAS) in a retrospective, noninterventional study. In total, 1994 ThinPrep LBC slides (Hologic), which were previously analyzed in 2020 using an imaging system with CAS in routine cotesting for cytology/human papillomavirus, were reviewed in a blinded mode using the Genius Digital Diagnostics System (Hologic). In 555 cases, a histology result was available. The slides were digitally scanned (volumetric scan) at 14 levels integrated into one. AI algorithms were used to present a gallery of six tiles each (containing objects of interest) in five categories. Six additional tile rows were available, from which the diagnoses were made. All cases with a mismatch between DC and imaging system results were reviewed by an additional cytopathologist. In 86.56% of cases, a complete match between both systems was observed using the same cytology categories. When also considering the histology results, the match was 90.37%. In addition, when a cytology follow-up and/or a retrospective review was applied, the match reached 97.34%. In only 0.65% of cases was a major discrepancy observed (two grades of cytology or a low-grade squamous intraepithelial lesion/high-grade squamous intraepithelial lesion [LSIL/HSIL] shift), and none were identified by DC. Significantly more cases of higher severity (atypical squamous cells cannot exclude high grade [ASC-H], high-grade squamous intraepithelial lesion [HSIL]) were identified with DC, and its negative predictive value was higher. The screening time was significantly shorter with DC. With the Genius system for DC, the sensitivity for HSIL+/ASC-H and the specificity for LSIL and HSIL were superior to LBC and CAS. Screening time was significantly lower.

CDKN2A/p16 evaluation in cytology specimens.

CDKN2A/p16 evaluation in cytology specimens.

Relationship between a deep learning model and liquid-based cytological processing techniques.

Artificial intelligence (AI)-based cytopathology studies conducted using deep learning have enabled cell detection and classification. Liquid-based cytology (LBC) has facilitated the standardisation of specimen preparation; however, cytomorphology varies according to the LBC processing technique used. In this study, we elucidated the relationship between two LBC techniques and cell detection and classification using a deep learning model. Cytological specimens were prepared using the ThinPrep and SurePath methods. The accuracy of cell detection and cell classification was examined using the one- and five-cell models, which were trained with one and five cell types, respectively. When the same LBC processing techniques were used for the training and detection preparations, the cell detection and classification rates were high. The model trained on ThinPrep preparations was more accurate than that trained on SurePath. When the preparation types used for training and detection were different, the accuracy of cell detection and classification was significantly reduced (P < 0.01). The model trained on both ThinPrep and SurePath preparations exhibited slightly reduced cell detection and classification rates but was highly accurate. For the two LBC processing techniques, cytomorphology varied according to cell type; this difference affects the accuracy of cell detection and classification by deep learning. Therefore, for highly accurate cell detection and classification using AI, the same processing technique must be used for both training and detection. Our assessment also suggests that a deep learning model should be constructed using specimens prepared via a variety of processing techniques to construct a globally applicable AI model.

Diagnostic significance of GATA 3, TTF-1, PTH, chromogranin expressions in parathyroid fine needle aspirations via immuonocytochemical method.

Additional studies may be needed when evaluating parathyroid fine needle aspirates (FNA) due to cytomorphologic similarities. The liquid-based cytology (LBC) is an effective cytology method which provides additional slides for ancillary techniques. We aimed to examine the immunocytochemical (ICC) GATA 3, TTF-1, which chromogranin and PTH expressions and to determine their diagnostic importance in parathyroid FNAs which were prepared via LBC technique. In total, 45 parathyroid FNA cases were examined in our laboratory for 12-month period. Thirty five cases without cell blocks were included in the study. Ten cases were excluded from study (five cases were nondiagnostic, five cases had cell blocks). For main LBC cytology slides SurePath pap test kit was used. For ICC study 4 PAP-stained LBC slides were obtained from each case's residual material. The slides were then stained with GATA 3, TTF-1, PTH and chromogranin. Of 35 cases, 8 were male and 27 were female. The mean age of the cases was 52.25 ± 11.44 (range 27-72). The mean diameter of the lesions was 18.54 ± 7.66 mm (range 6-32 mm).The most used antibody was TTF-1 (in all 35 cases). The positivity rates were 84.8%, 83.9% and 81.8% for GATA 3, PTH and chromogranin, respectively. TTF-1 was completely negative in 100% of cases. All patients had high PTH washout values (29 patients, PTH washout value was >5000 pg/mL). In 30 cases, histopathologic follow-up was available. The cyto-histological correlation was 100%. Based on the PTH washout values for cases without resection, the diagnostic accuracy of FNA was determined as 100% in detecting the parathyroid origin. Among the antibodies, the most specific and sensitive antibody was TTF-1 (100%). The sensitivity values of the antibodies indicating parathyroid origin for GATA3, PTH and chromogranin were 86.67%, 83.33% and 81.82%, respectively. The addition of ICC studies applied to LBC slides is also very helpful in diagnosis, especially in FNAs with limited material such as parathyroid. GATA3 is a more reliable ICC marker determining parathyroid origin. In differentiation from thyroid origin, the addition of TTF-1 to the ICC panel increases the diagnostic accuracy to 96.67%. Although PTH and chromogranin have lower sensitivity, they are still reliable markers to detect parathyroid origin.

A global perspective on cervical cancer screening: a literature review

Cervical cancer is a significant health issue for women globally, with over 600,000 new cases and 342,000 deaths in 2020. Effective cervical screening programs, including primary screening methods such as Pap tests, human papillomaviruses (HPV) deoxyribonucleic acid (DNA) testing, and liquid-based cytology, can prevent and detect early cancer cases, improving morbidity and mortality rates. However, screening uptake varies widely across countries, with high-income countries have achieved over 70% uptake but low- and middle-income countries lagging due to a lack of recommendations and centralised screening systems. Even in high-income countries in the Middle East, uptake remains low, requiring further investigation. This review explores barriers to screening programme delivery and highlights centralised and multi-level interventions that have proven effective worldwide. Future research should focus on culturally sensitive approaches, healthcare infrastructure strengthening, and community education and outreach programs to address uptake disparities and barriers.

Cervical cancer screening and prevention among female gynecologic oncologists in Indonesia

Background: Cervical cancer has become a significant health problem in developing countries. We researched cervical cancer screening and prevention among all female gynecologic oncologists (FGO) registered with the Indonesian Society of Gynecologic Oncologists (INASGO). Methods: Participant data and cervical cancer screening and prevention data were collected using an online questionnaire. A total sampling technique was conducted, and 18 of 20 FGOs responded to the survey. All data were analyzed descriptively. Results: Fourteen FGOs (77.8%) had their first cervical screening at the age of 31-40 years old, primarily using Pap smears (77.8%) and Pap-human papillomavirus (HPV) co-testing (22.2%). Half of the included FGOs (50%) had irregular cervical cancer screening due to lack of time (66.7%), followed by forgetting (33.3%). Most FGOs preferred liquid-based cytology (77.8%) over conventional Pap smears (22.2%). Half of the FGOs preferred the HPV genotyping and half the HPV non-genotyping test. Most of the FGOs had screenings performed by female gynecologists (77.8%), male gynecologists (11.1%), and female general practitioners (5.6%). Most FGOs underwent screenings at health facilities outside their workplace (88.9%) and were funded by themselves (94.4%). Most FGOs were vaccinated with the HPV vaccine (77.8%), and most were with the quadrivalent (85.7%) over the bivalent vaccine (14.3%). All respondents were completely (three doses) vaccinated. Conclusion: Most of the FGOs in Indonesia have been vaccinated against HPV and screened for cervical cancer, although half are still not regularly screened. The liquid-based cytology Pap smear and the quadrivalent HPV vaccine are the preferred cervical screening and prevention methods among FGOs in Indonesia

Artificial Intelligence-driven Digital Cytology-based Cervical Cancer Screening: Is the Time Ripe to Adopt This Disruptive Technology in Resource-constrained Settings? A Literature Review.

Cervical cancer is still a public health scourge in the developing countries due to the lack of organized screening programs. Though liquid-based cytology methods improved the performance of cervical cytology, the interpretation still suffers from subjectivity. Artificial intelligence (AI) algorithms have offered objectivity leading to better sensitivity and specificity of cervical cancer screening. Whole slide imaging (WSI) that converts a glass slide to a virtual slide provides a new perspective to the application of AI, especially for cervical cytology. In the recent years, there have been a few studies employing various AI algorithms on WSI images of conventional or LBC smears and demonstrating differing sensitivity/specificity or accuracy at detection of abnormalities in cervical smears. Considering the interest in AI-based screening modalities, this well-timed review intends to summarize the progress in this field while highlighting the research gaps and providing future research directions.

Deep Learning and Transfer Learning Methods to Effectively Diagnose Cervical Cancer from Liquid-Based Cytology Pap Smear Images

As cervical cancer is considered one of the leading causes of death for women globally, different screening techniques have emerged. As the Papanicolaou technique generates high numbers of false negatives due to only testing 20% of a sample, the liquid-based cytology technique was developed to test 100% of the sample and improve accuracy. However, as the larger sample size has made it difficult to detect the lesion images through a microscope, studies have looked for ways to intelligently analyze sample. The aim of this study is to develop an artificial intelligence image recognition system that detects the lesion level of cervical cancer of liquid-based Pap smears under the Bethesda classification of cancer (NI/LSIEL/HSIEL/SCC). For this purpose, six activities were carried out: dataset selection, data augmentation, optimization, model development, evaluation and system construction. A dataset built from publicly available Pap smear images and passed through data augmentation algorithms generated a total of 2,676 images. Two models, ResNet50V2 and ResNet101V2, were developed under Deep Learning and Transfer Learning protocols. The evaluation showed that the ResNet50V2 model obtained better performance, where the classification of HSIL and SCC type images obtained a precision of 0.98 and achieved an accuracy of 0.97. Finally, the system based on the ResNet50V2 model was built and its performance was validated.

Assessment of Cytological Changes in the Oral Mucosa in Young Hematological Patients Treated with Systemic Chemotherapy

The primary objective of the undertaken study was to determine the morphological changes that occur within the oral epithelium in children undergoing chemotherapy following a diagnosis of hematological malignancies. The study group consisted of 18 patients diagnosed with leukemia or lymphoma undergoing treatment with chemotherapy. Swabs (liquid-based cytology) were collected from the oral cavity for microscopic evaluation at baseline, during the chemotherapy cycle with oral mucositis symptoms present, and upon completion of the cycle. Both the neutrophil count and oral mucositis (OM) were registered using the WHO (World Health Organization) scale. The control group included 41 children who were generally healthy. All samples underwent microscopical analyses at the Department of Pathology, Medical University of Gdansk, Poland. A total of 190 cytological preparations were evaluated. The baseline preparations revealed similar cytological images, and the superficial cells of the epithelial layers were seen. A significant (p < 0.01) increase in the number of cells in the intermediate layer of the oral epithelium, as well as a decrease (p < 0.01) in the volume of cells in the superficial layers, was observed in further stages of cytostatic treatment. A decrease in the percentage of superficial epithelial cells with a corresponding increase in the number of intermediate epithelial cells is considered to be a result of toxic damage to the oral mucosa during chemotherapy.

A Comparison of Conventional Pap Smear and Liquid-Based Cytology for Cervical Cancer Screening.

Early diagnosis and treatment of preinvasive lesions have made cervical cytology one of the most effective methods of cancer screening in industrialized nations, which have seen a sharp decline in the incidence and death of invasive cancer. The aim of this study is to compare liquid-based cytology (LBC) and conventional Pap on cervical smears. From July 2018 to June 2022, 600 patients were included in this cross-sectional study, which was done at the Pathology Department of a Tertiary Care Facility in Western Maharashtra. Of the 600 patients, 570 (95%) had good conventional Pap smear (CPS), whereas 30 (5%) had poor ones. Five hundred and ninety-two (98.6%) LBC smears were satisfactory, whereas 8 (1.4%) were unsatisfactory. Endocervical cells were seen in 294 (49%) CPS, whereas 360 (60%) LBC smears showed endocervical cells. The morphology of inflammatory cells was similar in both techniques. Hemorrhagic background was seen in 212 (35%) CPS and 76 (12.6%) LBC smears. Only two samples showed diathetic background, which was seen on both CPS and smear. Out of the satisfactory smears in the case of CPS, 512 (85%) cases were reported as negative for intraepithelial lesion or malignancy (NILM), whereas 58 (9.7%) cases were reported as epithelial cell abnormality. In LBC smears, 526 (87.3%) were reported as NILM, whereas 66 (11%) were reported as epithelial cell abnormality. Organisms were detected in 208 (34%) CPS and 162 (27%) LBC smears. Screening time was 5 ± 1 min for CPS, whereas it was 3 ± 1 min for LBC smear. Mortality will be decreased using LBC on a bigger scale in nations where many smears can be made and screened in a short amount of time, with the provision of doing human papillomavirus-based testing on the remaining sample.

Validation of cytopathology specimens for digital pathology.

Digital cytopathology is being progressively implemented in centres worldwide, but impediments such as the three-dimensionality of specimens and the size of scanned images have prevented its use from becoming widespread. This study aimed to validate the use of digital whole slide image scanning of cytopathology samples for routine sign-out. Specimens were scanned using the Leica Aperio GT 450 System. The following sample types were used: liquid-based cytology, direct conventional smears from fine needle aspirates and cytospins. Cases were validated by the same pathologist who originally rendered the conventional diagnosis, with a washout of at least 3 months. Final digital diagnoses were compared to the original analogical diagnoses, and cases were considered concordant up to a one-degree difference between the original and digital diagnoses. Reasons for the unsuccessful scanning of slides were also noted. The technical procedures followed the College of American Pathologists' guidelines for digital pathology validation. A total of 730 slides from 383 cases (337 female, 51 male; median age 42) were successfully scanned. These cases consisted of the following sample types: 81 (21.1%) conventional smears, 240 (62.7%) liquid-based cytology samples and 62 (16.2%) cytospins. There were only five discordant cases, with a 98.7% agreement between original and digital diagnoses using the difference rate of up to one degree. Seventy-seven slides (10.5%) had to be rescanned due to technical problems. The main reasons for unsuccessful scanning were paucicellular samples (44; 57.1%), the thickness of the smears (18; 23.4%) and issues with the coverslip (15; 19.5%). Cytological specimens can be successfully scanned and used for digital pathology, with excellent agreement with the original diagnoses.

Calibration of the Becton Dickinson FocalPoint GS slide profiler is essential for optimal performance: Avoiding the algorithm supersaturation cascade effect pitfall.

The MAVARIC study supported the use of the FocalPoint GS (FPGS) imaging system "No Further Review" (NFR) technology for cervical screening and recommended further investigation. A validation study (Nuttall etal.) was performed by Cervical Screening Wales before implementing the NFR slide reporting technology within the cervical screening program in Wales, United Kingdom. A total of 45,317 SurePath liquid-based cytology cervical screening samples were submitted for FPGS scanning within four Welsh cytology laboratories between 2006 and 2011. The study, Computer Assisted Evaluation, Screening and Reporting, involved scanning the slides using the FPGS and comparing the results with manual screening performed under established Cervical Screening Wales protocols. An increased number of abnormal cases presented in the NFR reporting category, significantly greater than that previously encountered. This anomaly resulted in higher false-negative rates with potentially life-changing consequences for the screening participant. Subsequent investigation determined that this increase in cases created an algorithm cascade or "sump" effect, which resulted in an unprecedented increased number of samples categorized as NFR. This exceeded the calibration parameters set for the FPGS and was thought to be caused by an increase in the number of younger women attending for screening following the death of a young reality television celebrity from cervical cancer. Adequate and timely calibration of FPGS technology is vital for quality assurance of the results produced, particularly following events that may impact on cervical precancer incidence rates. Failure to do so can result in potentially catastrophic screening incidents that are avoidable.

Performance of a 7-Type HPV mRNA Test in Triage of HPV DNA Primary Screen Positive Women Compared to Liquid-Based Cytology

Background: A plethora of data supports HPV-based screening to be the preferred strategy for cervical cancer prevention. The shift to a more sensitive first-line test brings the need of effective triage up for discussion. Currently, most algorithms apply cytology as a triage of HPV-DNA positive women. This study compared the performance of a 7-type HPV-mRNA test to cytology. Methods: From 1 January 2019 until 31 December 2021, cervical samples from 58,029 women were examined at the University Hospital of North Norway. A total of 30.5% (17,684/58,029) fulfilled the criteria for HPV-DNA primary screening. All positive samples were triaged by cytology and followed-up according to national guidelines through 2022. Additionally, a 7-type HPV-mRNA test was applied. The study endpoint was a histologically confirmed high-grade lesion (CIN2+). Results: A total of 5.6% (990/17,684) had positive HPV-DNA test, 97.2% (962/990) with valid HPV-mRNA results. A total of 55.5% (534/962) had abnormal cytology (ASC-US+), and 35.1% (338/962) had a positive HPV-mRNA test. A total of 13.9% (134/962) had CIN2+. The sensitivity (CIN2+) of cytology versus the HPV-mRNA test was 76.1% (102/134) versus 73.1% (98/134), p = 0.67. The specificity was 47.8% (396/828) versus 71.0% (588/624), p &lt; 0.001. PPV was 19.1% (102/534) and 29.0% (98/338), p &lt; 0.001, respectively. The number of colposcopies per CIN2+ detected by cytology and HPV-mRNA test was 5.2 and 3.1. Conclusion: The 7-type HPV mRNA test was significantly more specific than cervical cytology in a triage of HPV-DNA positive women. Using this biomarker as the threshold for colposcopy may better balance the benefits and harms of screening.

Effect of Specimen Processing Technique on Cell Detection and Classification by Artificial Intelligence.

Cytomorphology is known to differ depending on the processing technique, and these differences pose a problem for automated diagnosis using deep learning. We examined the as-yet unclarified relationship between cell detection or classification using artificial intelligence (AI) and the AutoSmear (Sakura Finetek Japan) and liquid-based cytology (LBC) processing techniques. The "You Only Look Once" (YOLO), version 5x, algorithm was trained on the AutoSmear and LBC preparations of 4 cell lines: lung cancer (LC), cervical cancer (CC), malignant pleural mesothelioma (MM), and esophageal cancer (EC). Detection and classification rates were used to evaluate the accuracy of cell detection. When preparations of the same processing technique were used for training and detection in the 1-cell (1C) model, the AutoSmear model had a higher detection rate than the LBC model. When different processing techniques were used for training and detection, detection rates of LC and CC were significantly lower in the 4-cell (4C) model than in the 1C model, and those of MM and EC were approximately 10% lower in the 4C model. In AI-based cell detection and classification, attention should be paid to cells whose morphologies change significantly depending on the processing technique, further suggesting the creation of a training model.

Human Papillomavirus E7 and p16INK4a mRNA Multiplexed Quantification by a QuantiGeneTM Proof-of-Concept Assay Sensitively Detects Infection and Cervical Dysplasia Severity.

Persistent infection with human papillomavirus (HPV) can lead to cervical cancer (CxCa). During the progression to CxCa, the expression of HPV oncogenes E6 and E7 is upregulated. In turn, cellular proteins such as p16INK4a are also modulated. The combined detection of HPV oncogenes and cellular biomarkers indicative for dysplasia could be informative and convey better specificity than the current HPV tests that cannot discriminate transient infection from dysplastic changes. The QuantiGeneTM 2.0 Plex Assay platform was chosen for the effective multiplexing and quantitative detection of seven HPV-E7 mRNA targets (HPV6, 16, 18, 31, 45, 59, and 68) and the cellular mRNA of p16INK4a as a biomarker for HPV-induced transformation. Actin-beta (ACTB) and hypoxanthine-guanine phosphoribosyltransferase 1 (HPRT1) were included as reference markers. Sequences for the specific capture and detector probes were customized and developed by ThermoFisher and formulated as a QuantiGene proof-of-concept (QG-POC) plex-set. The crude lysates of the HPV-positive cervical cancer cell lines CaSki (HPV16), HeLa (HPV18), MRHI-215 (HPV45), Erin59 (HPV59), ME180 (HPV68), and the HPV-negative cell line C33A, as well as liquid-based cytology smear samples (n = 441) were analyzed. The study was a proof-of-concept evaluating the feasibility of the platform. Logistic regression and receiver operating characteristic (ROC) analyses were performed to test for the sensitivity and specificity of HPV detection and dysplastic stage discrimination. A QG-POC assay specifically and sensitively detects the HPV-E7 mRNA of seven different genotypes with an assay linearity between 20 and 13,000 cells. Cellular mRNA was detected from the crude lysates of cell lines and of cellular material from clinical liquid-based cytology smear samples. By combining HPV-E7 and p16INK4a expression normalized to ACTB, high-grade dysplasia (HCIN) and invasive cervical cancer (CxCa) were detectable, discriminable, and correlated to the biomarker expression strength. The ROC analysis from the multivariate logistic regression model including HPV-E7 and p16 INK4a resulted in an AUC of 0.74, at the optimal cut-off (sensitivity: 70.4%; specificity: 66.0%) for HCIN detection. CxCa was detected with an AUC of 0.77 (sensitivity: 81.8%, specificity: 77.4%). The QG-POC assay is sufficiently sensitive to detect and quantify HPV-E7 and cellular mRNA species. Multiplexing allows the specific detection of at least 10 analytes in a single reaction. Determining the abundance of E7 and p16INK4a transcripts when normalized to ACTB is informative about the presence of cervical dysplasia and potentially discriminates between low-grade and high-grade dysplasia and invasive cervical cancer. Further studies including more HPV genotypes and biomarkers are warranted.

Clinical application of the anti-human telomerase reverse transcriptase (hTERT) antibody (SCD-A7) immunocytochemistry in liquid-based urine cytology: Aprospective, single institute study.

Urine cytology is the most widely used noninvasive screening tool for urothelial carcinoma diagnosis and surveillance. Although highly specific, urine cytology exhibits suboptimal sensitivity. This study aimed to determine whether hTERT immunocytochemistry (ICC) could be applicable as an ancillary test in routine cytology practice. A total of 561 urinary tract samples were initially screened in this study. All of them were prepared using SurePath liquid-based cytology (LBC), while additional LBC slides were made and subsequently used for hTERT (SCD-A7) ICC. From the 561 samples screened, 337 were finally analyzed, all having an adequate cellularity and available follow-up histology. The hTERT ICC-positive rate was 95.9% (n=208/217), 96% (n=24/25), and 100% (n=4/4) in cytology samples with high-grade urothelial carcinoma, carcinoma in situ, and low-grade urothelial carcinoma subsequent histology. Among the 64 atypical cytology cases histologically confirmed as urothelial carcinomas, 92.2% (n=59/64) were immunoreactive to hTERT, whereas the two histologically benign cases were ICC-negative. 87/90 (96.7%) of the cytology cases confirmed to be benign in follow-up were hTERT-negative. The overall sensitivity and specificity of hTERT ICC were 96.3% and 98.8%, respectively (AUROC=0.963; 95% CI=0.960-0.967). The hTERT ICC test exhibited consistent and intense staining in malignant urothelial cells, suggesting its value as an ancillary test in liquid-based urine cytology.

Next-Generation Sequencing Analysis of Pancreatic Cancer Using Residual Liquid Cytology Specimens from Endoscopic Ultrasound—Guided Fine-Needle Biopsy: A Prospective Comparative Study with Tissue Specimens

This study evaluated the feasibility and clinical utility of liquid-based cytology (LBC) specimens via endoscopic ultrasound-guided fine-needle biopsy (EUS-FNB) for next-generation sequencing (NGS) of pancreatic cancer (PC). We prospectively evaluated the performance of DNA extraction and NGS using EUS-FNB samples obtained from PC. Thirty-three consecutive patients with PC who underwent EUS-FNB at our hospital were enrolled. DNA samples were obtained from 96.8% of the patients. When stratified with a variant allele frequency (VAF) > 10% tumor burden, the NGS success rate was 76.7% (n = 23) in formalin-fixed paraffin-embedded (FFPE), 83.3% (n = 25) in LBC, and 76.7% (n = 23) in frozen samples. The overall NGS success rate was 86.7% (n = 26) using FFPE, LBC, or frozen samples. The detection rates for the main mutated genes were as follows: 86.7% for KRAS, 73.3% for TP53, 66.7% for CDKN2A, 36.7% for SMAD4, and 16.7% for ARID1A. LBC had the highest median value of VAF (23.5%) for KRAS and TP53. PC mutation analysis using NGS was successfully performed using LBC compared with FFPE and frozen samples. This approach provides an alternative and affordable source of molecular testing materials.