Cervical carcinomas with serous-like papillary and micropapillary components: illustrating the heterogeneity of primary cervical carcinomas

Coinactivation of the Switch/Sucrose Nonfermenting Complex SMARCA4/BRG1 and SMARCB1/INI1 in a Cervical Mixed Carcinoma: A Case Report

SMARCB1/SMARCA4-deficient malignancies of the female genital tract are rare entities, characterized by similar histologic features, such as sheet-like growth patterns and rhabdoid cells. Previous studies have shown mutually exclusive loss of SMARCA4/BRG1 and SMARCB1/INI1. Herein, we describe a unique cervical mixed carcinoma in a 77-year-old patient. The tumor consisted of 3 components, gastric-type adenocarcinoma, squamous carcinoma, and undifferentiated carcinoma. While the undifferentiated carcinoma was negtive for CK7, CK5/6 and p63, it was positive for pan-CK. DNA-based next-generation sequencing revealed a nonsense mutation in SMARCA4, copy number loss in SMARCB1, and a nonsense mutation in ARID1A. Different molecular alterations of the switch/sucrose nonfermenting complex subunits in the present case may provide further insights into the functions of the switch/sucrose nonfermenting complex in the progression of tumors.

Research progress on human papillomavirus-negative cervical cancer: A review

Cervical cancer is the fourth most common cancer in women worldwide. The vast majority of cervical cancers are associated with human papillomavirus (HPV) infection, but a small proportion of cervical cancers occur independently of HPV infection, with different subtypes having varying rates of occurrence. Despite the presence of false negatives in current testing, improving the accuracy of detection is crucial for studying the pathogenesis of HPV-negative cervical cancer and improving the prognosis of these patients. Existing research suggests that HPV-negative cervical cancer has a different pathogenesis from HPV-positive cervical cancer, although the exact mechanism is not yet clear. It is currently believed to be associated with the immune microenvironment, certain tumor gene mutations, and some long noncoding RNAs. This article provides an overview of the latest research progress on HPV-negative cervical cancer, including possible reasons, pathogenesis, pathological features, and clinical characteristics, aiming to provide new insights for diagnosis, treatment, and prognosis improvement.

Bioinformatics analysis to identify the relationship between human papillomavirus-associated cervical cancer, toll-like receptors and exomes: A genetic epidemiology study

INTRODUCTION

Genetic variants may influence Toll-like receptor (TLR) signaling in the immune response to human papillomavirus (HPV) infection and lead to cervical cancer. In this study, we investigated the pattern of TLR expression in the transcriptome of HPV-positive and HPV-negative cervical cancer samples and looked for variants potentially related to TLR gene alterations in exomes from different populations.

MATERIALS AND METHODS

A cervical tissue sample from 28 women, which was obtained from the Gene Expression Omnibus database, was used to examine TLR gene expression. Subsequently, the transcripts related to the TLRs that showed significant gene expression were queried in the Genome Aggregation Database to search for variants in more than 5,728 exomes from different ethnicities.

RESULTS

Cancer and HPV were found to be associated (p<0.0001). TLR1(p = 0.001), TLR3(p = 0.004), TLR4(221060_s_at)(p = 0.001), TLR7(p = 0.001;p = 0.047), TLR8(p = 0.002) and TLR10(p = 0.008) were negatively regulated, while TLR4(1552798_at)(p<0.0001) and TLR6(p = 0.019) were positively regulated in HPV-positive patients (p<0.05). The clinical significance of the variants was statistically significant for TLR1, TLR3, TLR6 and TLR8 in association with ethnicity. Genetic variants in different TLRs have been found in various ethnic populations. Variants of the TLR gene were of the following types: TLR1(5_prime_UTR), TLR4(start_lost), TLR8(synonymous;missense) and TLR10(3_prime_UTR). The "missense" variant was found to have a risk of its clinical significance being pathogenic in South Asian populations (OR = 56,820[95%CI:40,206,80,299]).

CONCLUSION

The results of this study suggest that the variants found in the transcriptomes of different populations may lead to impairment of the functional aspect of TLRs that show significant gene expression in cervical cancer samples caused by HPV.

Three-dimensional DNA biomimetic networks (B-3D Net)-based ratiometric fluorescence platform for cancer-related gene biosensing

Efficient detection of cancer-related nucleic acids is pivotal for early cancer diagnosis. This study introduces a target induced three-dimensional DNA biomimetic networks (B-3D Net)-based ratiometric fluorescence platform using manganese dioxide nanosheets (MnO2 NS)/o-phenylenediamine in combination with hybridization chain reaction to detect cancer-related genes (p53 gene). The incorporation of multiple signals within the B-3D networks can significantly enhance catalytic activity and amplify the output signals, enabling a high sensitivity. Compared with traditional ratio fluorescence platforms, there is no demand to synthesize fluorescent nanoprobes due to the in-situ formation of fluorescence species, which is simple and cost-effective. The corresponding assay demonstrated exceptional sensitivity (with a detection limit as low as 2 fM), selectivity, reproducibility, and accuracy, which mitigates disturbances caused by instrument errors, an inaccurate probe count, and the microenvironment. Furthermore, the ease and straightforwardness of discerning changes in fluorescent brightness and colour by the naked eye are evident. Using the relevant software, a linear relationship between fluorescent images using a smartphone and target concentration was obtained. Hence, the novel ratiometric sensing system will demonstrate new opportunities on determination of target DNA samples in complex biological environments.

Predicting Lymph Node Metastasis From Primary Cervical Squamous Cell Carcinoma Based on Deep Learning in Histopathologic Images

We developed a deep learning framework to accurately predict the lymph node status of patients with cervical cancer based on hematoxylin and eosin-stained pathological sections of the primary tumor. In total, 1524 hematoxylin and eosin-stained whole slide images (WSIs) of primary cervical tumors from 564 patients were used in this retrospective, proof-of-concept study. Primary tumor sections (1161 WSIs) were obtained from 405 patients who underwent radical cervical cancer surgery at the Fudan University Shanghai Cancer Center (FUSCC) between 2008 and 2014; 165 and 240 patients were negative and positive for lymph node metastasis, respectively (including 166 with positive pelvic lymph nodes alone and 74 with positive pelvic and para-aortic lymph nodes). We constructed and trained a multi-instance deep convolutional neural network based on a multiscale attention mechanism, in which an internal independent test set (100 patients, 228 WSIs) from the FUSCC cohort and an external independent test set (159 patients, 363 WSIs) from the Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma cohort of the Cancer Genome Atlas program database were used to evaluate the predictive performance of the network. In predicting the occurrence of lymph node metastasis, our network achieved areas under the receiver operating characteristic curve of 0.87 in the cross-validation set, 0.84 in the internal independent test set of the FUSCC cohort, and 0.75 in the external test set of the Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma cohort of the Cancer Genome Atlas program. For patients with positive pelvic lymph node metastases, we retrained the network to predict whether they also had para-aortic lymph node metastases. Our network achieved areas under the receiver operating characteristic curve of 0.91 in the cross-validation set and 0.88 in the test set of the FUSCC cohort. Deep learning analysis based on pathological images of primary foci is very likely to provide new ideas for preoperatively assessing cervical cancer lymph node status; its true value must be validated with cervical biopsy specimens and large multicenter datasets.

Recent Advances in the Classification of Gynecological Tract Tumors: Updates From the 5th Edition of the World Health Organization "Blue Book"

CONTEXT.—

The World Health Organization Classification of Tumours: Female Genital Tract Tumors, 5th edition, published in September 2020, comes 6 years after the 4th edition, and reflects the monumental leaps made in knowledge about the biology of gynecological tumors. Major changes include revised criteria for the assignment of the site of origin of ovarian and fallopian tube tumors, a revision in the classification of squamous and glandular lesions of the lower genital tract based on human papillomavirus association, and an entire chapter devoted to genetic tumor syndromes. This article highlights the changes in the 5th edition relative to the 4th edition, with a focus on areas of value to routine clinical practice.

OBJECTIVE.—

To provide a comprehensive update on the World Health Organization classification of gynecological tumors, highlighting in particular updated diagnostic criteria and terminology.

DATA SOURCES.—

The 4th and 5th editions of the World Health Organization Classification of Tumours.

CONCLUSIONS.—

The World Health Organization has made several changes in the 5th edition of the update on female genital tumors. Awareness of the changes is needed for pathologists' translation into contemporary practice.

Detection rates and factors affecting thereof in endometrial hyperplasia, endometrial carcinoma, and cervical glandular lesions on cervical smear

INTRODUCTION

Endometrial lesions are morphologically diverse and uncommon on cervical smears, with its detection rate and associated diagnostic categories uncharacterized. In this study, cervical smears matched to histologically proven endometrial hyperplasias and carcinomas were reviewed and compared with cervical in-situ-carcinomas/carcinomas, aiming to detail the diagnostic performance of cervical smears for upper tract and glandular lesions.

METHODS

Pathology reports of cervical smears, hysterectomies, endometrial and cervical biopsies from 1995 to 2021 were retrieved. Diagnoses of cervical smears were matched to endometrial hyperplasias and carcinomas, or cervical carcinomas and reviewed.

RESULTS

Totally 832 cervical smears (272 cervical carcinomas, 312 endometrial carcinomas, and 248 hyperplasias) were included. Considering all cytologic glandular diagnosis as positive, the detection rate of cervical adenocarcinoma-in-situ was the highest (64.3%), followed by cervical adenocarcinoma (63.8%), endometrial carcinoma (31.7%), and hyperplasia (with atypia-8.5%; without atypia-2.3%) (p < 0.001). Endometrial hyperplasia was most often diagnosed as atypical squamous cells of undetermined significance (ASCUS) (5.0%) or atypical glandular cells, not otherwise specified (3.6%) without indication of endometrial origin. For endometrial carcinomas, higher FIGO grading and endocervical involvement were associated with higher detection rates across all diagnostic categories (p = 0.002-0.028). High FIGO grade was associated with suspicious/favor neoplastic (C4) (31.1%vs10.3%, p < 0.001) and carcinoma (C5) (17.8% vs. 5.6%, p = 0.005) categories, but not for all glandular diagnoses combined (33.3% vs. 31.0%, p = 0.761).

CONCLUSION

Detection rates for endometrial lesions are lower than cervical lesions but not insignificant. Endometrial hyperplasia should be recognized as a differential of human papilloma virus-negative ASCUS and prompt consideration of investigation of the upper genital tract.

Dataset for the Reporting of Carcinoma of the Cervix: Recommendations From the International Collaboration on Cancer Reporting (ICCR)

Cervical carcinoma remains one of the most common cancers affecting women worldwide, despite effective screening programs being implemented in many countries for several decades. The International Collaboration on Cancer Reporting (ICCR) dataset for cervical carcinoma was first developed in 2017 with the aim of developing evidence-based standardized, consistent and comprehensive surgical pathology reports for resection specimens. This 4th edition update to the ICCR dataset on cervical cancer was undertaken to incorporate major changes based upon the updated International Federation of Obstetricians and Gynecologists (FIGO) staging for carcinoma of the cervix published in 2018 and the 5th Edition World Health Organization (WHO) Classification of Female Genital Tumors published in 2020 and other significant developments in pathologic aspects of cervical cancer. This updated dataset was developed by a panel of expert gynecological pathologists and an expert gynecological oncologist, with a period of open consultation. The revised dataset includes "core" and "noncore" elements to be reported; these are accompanied by detailed explanatory notes and references providing the rationale for the updates. Standardized reporting using datasets such as this helps facilitate consistency and accuracy, data collection across different sites and comparison of epidemiological and pathologic parameters for quality and research purposes.

Reproducibility of Morphologic Parameters of the International Endocervical Adenocarcinoma Criteria and Classification System and Correlation With Clinicopathologic Parameters: A Multi-Institutional Study

Endocervical adenocarcinomas (ECAs) have been recently reclassified according to their morphologic features linked to etiology by the International Endocervical Adenocarcinoma Criteria and Classification (IECC) and this system is adopted by WHO 2020. This classification separates the ECAs as human papillomavirus (HPV)-associated (HPVA) and HPV-independent (HPVI) subtypes. According to WHO 2020, high risk (HR)-HPV association can be histologically recognized by the presence of luminal mitoses and apoptosis. Therefore, investigating the reproducibility of the morphologic criteria of this new classification will be important in observing the recognizability of tumor types. Full slide sets of 94 ECAs were collected from 4 institutions in Turkey and reclassified on the basis of IECC/WHO 2020 criteria and the presence or absence of HR-HPV. HR-HPV presence was confirmed by HPV DNA in situ hybridization, p16 immunohistochemistry and in conflicted cases with real time-polymerase chain reaction. The final diagnoses were given based on the combination of the histologic evaluation and ancillary test results. Our cohort consisted of 73.4% HPVA and 26.6% HPVI cases. According to the WHO 2020 criteria 92.7% of HPVAs and 88% of HPVIs were easily classified. HPV DNA in situ hybridization was positive in 91.3% of the HPVAs and p16 was positive in all HPVAs, and also positive in 8% of the HPVIs. In conclusion, most of the ECAs can be diagnosed by their characteristic morphologic features by the WHO 2020 criteria. However, we want to emphasize that mitosis/apoptosis criteria may not be helpful especially in mucinous ECAs and ancillary tests for HR-HPV should be used in challenging cases.

Molecular Pathology of Human Papilloma Virus-Negative Cervical Cancers

Cervical cancer is the fourth most common cancer in women worldwide and is predominantly caused by infection with human papillomavirus (HPV). However, a small subset of cervical cancers tests negative for HPV, including true HPV-independent cancers and false-negative cases. True HPV-negative cancers appear to be more prevalent in certain pathological adenocarcinoma subtypes, such as gastric- and clear-cell-type adenocarcinomas. Moreover, HPV-negative cervical cancers have proven to be a biologically distinct tumor subset that follows a different pathogenetic pathway to HPV-associated cervical cancers. HPV-negative cervical cancers are often diagnosed at an advanced stage with a poor prognosis and are expected to persist in the post-HPV vaccination era; therefore, it is important to understand HPV-negative cancers. In this review, we provide a concise overview of the molecular pathology of HPV-negative cervical cancers, with a focus on their definitions, the potential causes of false-negative HPV tests, and the histology, genetic profiles, and pathogenesis of HPV-negative cancers.

Prevalence of HER2 overexpression and amplification in cervical cancer: A systematic review and meta-analysis

The reported rates of HER2 positivity in cervical cancer (CC) range from 0% to 87%. The importance of HER2 as an actionable target in CC would depend on HER2 positivity prevalence. Our aim was to provide precise estimates of HER2 overexpression and amplification in CC, globally and by relevant subgroups. We conducted a PRISMA compliant meta-analytic systematic review. We searched Medline, EMBASE, Cochrane database, and grey literature for articles reporting the proportion of HER2 positivity in CC. Studies assessing HER2 status by immunohistochemistry or in situ hybridization in invasive disease were eligible. We performed descriptive analyses of all 65 included studies. Out of these, we selected 26 studies that used standardized American Society of Clinical Oncology / College of American Pathologists (ASCO/CAP) Guidelines compliant methodology. We conducted several meta-analyses of proportions to estimate the pooled prevalence of HER2 positivity and subgroup analyses using geographic region, histology, tumor stage, primary antibody brand, study size, and publication year as moderators. The estimated pooled prevalence of HER2 overexpression was 5.7% (CI 95%: 1.5% to 11.7%) I2 = 87% in ASCO/CAP compliant studies and 27.0%, (CI 95%: 19.9% to 34.8%) I2 = 96% in ASCO/CAP non-compliant ones, p < 0.001. The estimated pooled prevalence of HER2 amplification was 1.2% (CI 95%: 0.0% to 5.8%) I2 = 0% and 24.9% (CI 95%: 12.6% to 39.6%) I2 = 86%, respectively, p = 0.004. No other factor was significantly associated with HER2 positivity rates. Our results suggest that a small, but still meaningful proportion of CC is expected to be HER2-positive. High heterogeneity was the main limitation of the study. Variations in previously reported HER2 positivity rates are mainly related to methodological issues.