Predictive immunotherapeutic markers of adenocarcinomas and adenosquamous carcinoma of the cervix

Aim. To identify the features of the systemic effect on hematopoiesis and the blood coagulation system of different histological subtypes of cervical cancer (CC).Materials and methods. A single-center retrospective cohort study of 428 patients (61 patients with high grade squamous intraepithelial lesion (carcinoma in situ) and 367 patients with CC) examined from 1997 to 2022 in the Polyclinic of P. Hertzen Moscow Oncology Research Institute – branch of the National Medical Research Radiology Center, Ministry of Health of Russia. The age of patients was from 18 to 90 years (median age – 42 [34; 51] years). Patients were divided into 4 groups: group 1 – patients with high grade squamous intraepithelial lesion and 3 groups depending on tumor’s histological subtype (squamous cell, glandular squamous cell, adenocarcinoma). Demographic and clinical data were analyzed including laboratory tests (general blood count, biochemical blood test and iron metabolism and coagulograms (total 32 variables)) compared to clinical and surgical stages of CC.Results. High grade squamous intraepithelial lesion does not have a systemic effect on the parameters of general, biochemical blood tests and hemostasis (p >0.05). On the other hand, statistically significant changes were found in the parameters of routine laboratory blood tests, which correlate with the results of microinvasive analysis of CC, thus revealing the systemic effect of a malignant tumor: at p ≤0.001 for thrombin time, total protein, alkaline phosphatase levels; at p ≤0.05 for alanine aminotransferase, aspartate aminotransferase, C-reactive protein, serum iron and urea levels. Among patients with CC, statistically significant (p<0.001) correlations were obtained between hematological, hemostasiological and biochemical blood parameters. Of statistical significance, the presence of the glandular component in the tumor increases the systemic effect of CC on blood parameters, hemostasis, markers of inflammation and iron metabolism: leukocytosis and maximum erythrocyte sedimentation rate values compared to CC, high fibrinogen and the level of soluble fibrin-monomer complexes which increased activation of coagulation hemostasis along the common coagulation pathway (thrombin time) (p<0.001). It leads to an increase in the risk of venous thromboembolic complications in this category of patients.Conclusion. The identified changes in blood parameters made it possible to reveal the unique biological characteristics of each histological subtype of CC, including biochemical ones, which will help in developing an improved diagnosis of CC depending on the histological subtype and stage of the disease, along with developing preventive measures and treatment methods adapted to each specific case.

Cancer subtypes identification is very important for the advancement of precision cancer disease diagnosis and therapy. It is one of the important components of the personalized medicine framework. Cervical cancer (CC) is one of the leading gynecological cancers that causes deaths in women worldwide. However, there is a lack of studies to identify histological subtypes among the patients suffering from tumor of the uterine cervix. Hence, sub-typing of cancer can help in analyzing shared molecular profiles between different histological subtypes of solid tumors of uterine cervix. With the advancement in technology, large scale multi-omics data are generated. The integration of genomics data generated from different platforms helps in capturing complementary information about the patients. Several computational approaches have been developed that integrate muti-omics data for cancer sub-typing. In this study, mRNA (messenger RNA) and miRNA (microRNA) expression data are integrated to identify the histological subtypes of CC. In this regard, a method is proposed that ranks the biomarkers (mRNA and miRNA) on the basis of their varying expression across the samples. The ranking method generates a weight for every biomarker which is further used to identify the similarity between the samples. A well-known approach named Similarity Network Fusion (SNF) is then applied, followed by Spectral clustering, to identify groups of related samples. This study focuses on the role of weighing the biomarkers prior to their integration and application of the clustering algorithm. The weighing method proposed in this study is compared with some other methods and proved to be more efficient. The proposed method helps in identifying histological subtypes of CC and can also be applied to other types of cancer data where histological subtypes play a key role in designing treatments and therapies.

Scores and Misses With New Technology—Walking the Narrow Path of Evidence

3D MR elastography-based stiffness as a marker for predicting tumor grade and subtype in cervical cancer

Pan-cancer analysis of non-coding transcripts reveals the prognostic onco-lncRNA HOXA10-AS in gliomas.

Objective : Our purpose was to evaluate the prevalence and genotypic distribution of HPV infection by newly developed HPV DNA chip in various cervical lesions and to assess the relationship between HPV genotypes and different grades of cervical intraepithelial neoplasia (CIN) and cervical cancer. Methods : Between December 2001 and May 2003, 394 patients who visited Busan Paik hospital due to abnormal Pap smear or colposcopic finding, were involved and classified into 5 groups according to their cytologic diagnoses: nonspecific chronic cervicitis (n=36), ASCUS/AGUS (n=36), LSIL (n=46), HSIL (n=131), cervical cancer (n=145). We examined HPV positivity and genotype of the specimens using HPV DNA chip, which detects 22 HPV genotypes including 15 high-risk HPV groups (16/18/31/33/35/39/45/51/52/56/58/59/66/68/69) and 7 low-risk HPV groups (6/11/34/40/42/43/44). Results : The overall detection rate of HPV infection was 71.1% (280/394), and the detection rate of high-risk HPV infection was 67.0% (264/394). According to the grade of the lesions, the detection rates of high-risk of HPV infection were 19.4% (7/36) in nonspecific chronic cervicitis, 16.7% (6/36) in ASCUS/AGUS, 63.0% (29/46) in LSIL, 83.2% (109/131) in HSIL, and 77.9% (113/145) in cervical cancer. The major prevailing HPV genotypes in this study were HPV types 16, 58, 18, 35, and 52 in descending order of incidence, which averaged 86.7% for all. HPV 16 was the most common type in all the HPV-positive cases as well as HSIL and cervical cancer. HPV 18 was the second most common type in cervical cancer and HPV 58 was the second most common type in HSIL. The odds ratio was estimated to evaluate the relationship of HSIL and cervical cancer versus HPV type. HPV 16 and 35 were found to be significantly related to HSIL, cervical cancer, or HSIL and cervical cancer. HPV 58 was found to be significantly related to HSIL, or HSIL and cervical cancer. Conclusion : In our study, HPV type 16, 18, 35, 52, and 58 were confirmed to be major prevailing subtypes in CIN and cervical cancer. Our results suggest that HPV 16, 35, and 58 positive patients have a tendency to develop HSIL and cervical cancer than other HPV positive patients.

To evaluate the diagnostic potential of diffusion kurtosis imaging (DKI) functional maps with whole-tumor texture analysis in differentiating cervical cancer (CC) subtype and grade. Seventy-six patients with CC were enrolled. First-order texture features of the whole tumor were extracted from DKI and DWI functional maps, including apparent kurtosis coefficient averaged over all directions (MK), kurtosis along the axial direction (Ka), kurtosis along the radial direction (Kr), mean diffusivity (MD), fractional anisotropy (FA), and ADC maps, respectively. The Mann-Whitney U test and ROC curve were used to select the most representative texture features. Models based on each individual and combined functional maps were established using multivariate logistic regression analysis. Conventional parameters-the average values of ADC and DKI parameters derived from the conventional ROI method-were also evaluated. The combined model based on Ka, Kr, MD, and FA maps yielded the best diagnostic performance in discrimination of cervical squamous cell cancer (SCC) and cervical adenocarcinoma (CAC) with the highest AUC (0.932). Among individual functional map derived models, Kr map-derived model showed the best performance when differentiating tumor subtypes (AUC = 0.828). MK_90th percentile was useful for distinguishing high-grade and low-grade in SCC tumors with an AUC of 0.701. The average values of MD, FA, and ADC were significantly different between SCC and CAC, but no conventional parameters were useful for tumor grading. The whole-tumor texture analysis applied to DKI functional maps can be used for differential diagnosis of cervical cancer subtypes and grading SCC. • The whole-tumor texture analysis applied to DKI functional maps allows accurate differential diagnosis of CC subtype and grade. • The combined model derived from multiple functional maps performs significantly better than the single models when differentiating tumor subtypes. • MK_90th percentile was useful for distinguishing poorly and well-/moderately differentiated SCC tumors with an AUC of 0.701.

The expression, biological functions and underlying molecular mechanisms of endothelial cell-specific molecule 1 (ESM1) in human cervical cancer remain unclear. Bioinformatics analysis revealed that ESM1 expression was significantly elevated in human cervical cancer tissues, correlating with patients’ poor prognosis. Moreover, ESM1 mRNA and protein upregulation was detected in local cervical cancer tissues and various cervical cancer cells. In established and primary cervical cancer cells, ESM1 shRNA or CRISPR/Cas9-induced ESM1 KO hindered cell proliferation, cell cycle progression, in vitro cell migration and invasion, and induced significant apoptosis. Whereas ESM1 overexpression by a lentiviral construct accelerated proliferation and migration of cervical cancer cells. Further bioinformatics studies and RNA sequencing data discovered that ESM1-assocaited differentially expressed genes (DEGs) were enriched in PI3K-Akt and epithelial-mesenchymal transition (EMT) cascades. Indeed, PI3K-Akt cascade and expression of EMT-promoting proteins were decreased after ESM1 silencing in cervical cancer cells, but increased following ESM1 overexpression. Further studies demonstrated that SYT13 (synaptotagmin 13) could be a primary target gene of ESM1. SYT13 silencing potently inhibited ESM1-overexpression-induced PI3K-Akt cascade activation and cervical cancer cell migration/invasion. In vivo, ESM1 knockout hindered SiHa cervical cancer xenograft growth in mice. In ESM1-knockout xenografts tissues, PI3K-Akt inhibition, EMT-promoting proteins downregulation and apoptosis activation were detected. In conclusion, overexpressed ESM1 is important for cervical cancer growth in vitro and in vivo, possibly by promoting PI3K-Akt activation and EMT progression. ESM1 represents as a promising diagnostic marker and potential therapeutic target of cervical cancer.

Breast cancer and reproductive system cancers remain significant public health threats for Chinese women. This study aimed to evaluate the latest epidemiological patterns and trends of four female-specific cancers in China. The year- and age-specific estimates of the incidence, mortality, and disability-adjusted life-years (DALYs) associated with breast, cervical, ovarian, and uterine cancers in China from 1990 to 2021 were generated from the Global Burden of Disease, Injuries, and Risk Factors 2021 study. The epidemiological characteristics were analyzed with age-period-cohort models. A Bayesian age-period-cohort model was applied to forecast disease burden from 2022 to 2050. In 2021, China reported 385.84 thousand (95% uncertainty interval [UI], 294.10-489.01 thousand) incident cases of female breast cancer, followed by cervical cancer (132.79 thousand [95% UI, 95.96-172.60 thousand]), uterine cancer (72.02 thousand [95% UI, 53.31-100.00 thousand]), and ovarian cancer (41.24 thousand [95% UI, 30.30-54.55 thousand]). Breast cancer ranked as the primary cause of cancer-related deaths, followed by cervical cancer. The age-specific incidence rate for breast, cervical, ovarian, and uterine cancers are projected to occur in the age groups 60-64 years, 55-59 years, 65-69 years, and 60-64 years, respectively. Breast, ovarian, and uterine cancer cases are projected to rise by 2050, which will exceed those recorded in 2021. Various inequities have been identified across four types of cancers affecting women, which underscores the need for tailored national cancer control strategies. Emphasis should be placed on primary prevention and screening for breast and cervical cancers, whereas efforts for uterine and ovarian cancers should focus on implementing early diagnosis and treatment measures. This study examines the burdens and trends of breast, cervical, ovarian, and uterine cancers among Chinese women from 1990 to 2021. In 2021, breast cancer emerged as the most prevalent, followed by cervical, uterine, and ovarian cancers, with breast cancer also exhibiting the highest mortality rate. The age groups projected to exhibit the highest incidence rates for breast, cervical, ovarian, and uterine cancers are 60-64 years, 55-59 years, 65-69 years, and 60-64 years, respectively. Projections indicate that by 2050, the incidence of breast, ovarian, and uterine cancers will surpass 2021 levels, which underscores the necessity for targeted prevention, early detection, and treatment strategies.

BACKGROUND: Cervical cancer (CC) remains a leading cause of gynaecological cancer-related mortality worldwide and constitutes the second most common malignancy in women. CC exhibits differences in clinical behavior; infection by high-risk Human Papilloma Virus (HPV) remains an important initiating event in tumorigenesis and the most important risk factors for CC. As HPV integration types may be specific biomarkers for prediction of clinical outcomes, we analyzed the association between the different viral integration signatures and clinic-pathological parameters in CC patients. EXPERIMENTAL DESIGN: Patients included in this study were enrolled in the EU-funded RAIDs Network (Rational Molecular Assessment and Innovative Drug Selection, www.raids-fp7.eu) prospective CC BioRAIDs study [NCT02428842]. HPV double capture method followed by NGS was used to define the different integration signatures. Correlations between HPV integration signatures and clinical, biological and molecular features were assessed in a large series of 272 CC BioRAIDs patients. RESULTS: The distribution of HPV signatures differed from that previously described in HPV-positive anal squamous cell carcinoma (p<0.001). We identified more than 250 HPV insertions sites (inter-genic or intra-genic) and reported MACROD2 gene as the most frequent integration site followed by the MIPOL1/TTC6, TP63, ERBB2, KLF12. The seven patients with HPV integration in the MACROD2 gene tend to have a worse progression free survival (PFS) compared to other patients. HPV integration signatures were not associated with treatment type, histological subtype or FIGO staging, but were associated with PIK3CA mutational status (p=0.023) and HPV genotype status (p<0.0001). HPV45 and HPV18 genotypes were always integrated in our patients' population, as compared to other HPV genotypes. There was no significant association between the different HPV integration signatures and PFS. High viral load was associated with longer PFS (p=0.011). CONCLUSION: This is the first study assessing the prognostic value of HPV integration in a prospectively annotated CC patient cohort, which reports a hot-spot of HPV integrations at the MACROD2 gene, known to be implicated in impaired PARP1 activity and chromosome instability. Citation Format: Maud Kamal, Sonia Lameiras, Adeline Morel, Charlotte Lecerf, Sophie Vacher, Celia Dupain, Emmanuelle Jeannot, Marc Deloger, Nicolas Servant, Elodie Girard, Sylvain Baulande, Gemma Kenter, Ekaterina Jordanova, Els Berns, Roman Rouzier, Wulfran Cacheux, Christophe Le Tourneau, Alain Nicolas, Suzy Scholl, Ivan Bieche. HPV double capture NGS method in cervical cancer: Identification of MACROD2 gene as HPV hot spot integration site and viral load status as a prognostic factor [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4330.

ObjectiveTo assess the mortality trends of four major histological subtypes of cervical cancer diagnosed between 1994 and 2018.MethodsThis population-based retrospective cohort study was conducted using the Osaka Cancer Registry data from 1994 to 2018. A total of 12,003 patients with cervical cancer, squamous cell carcinoma (SCC), adenocarcinoma (A), adenosquamous cell carcinoma (AS), or small cell neuroendocrine carcinoma (SCNEC) were identified. Patients were classified into groups according to the extent of disease (localized, regional, or distant), year of diagnosis (1994–2002, 2003–2010, or 2011–2018), and histological subtype (SCC, A/AS, or SCNEC). Then, their survival rates were assessed using univariate and multivariate analyses.ResultsOverall, improved survival rates were observed according to the year of diagnosis in patients with local, regional, and distant cervical cancers. When examined according to the histological subtypes, improved survival rates according to the year of diagnosis were observed in patients with local, regional, and distant SCCs and in those with local and regional A/AS. In patients with distant A/AS, the survival rates did not improve since 2003. In patients with cervical cancer with SCNEC, the survival rates did not improve since 1994 irrespective of the extent of the disease. In the multivariate analysis, non-SCC histology was found to be an independent prognostic factor for OS.ConclusionIn contrast to SCC histology associated with improved survival between 1994 and 2018, SCNEC histology and advanced (stage IVB) A/AS remain to be the unmet medical needs for the management of cervical cancer.

BackgroundHuman papillomavirus-positive (HPV+) cervical cancers are highly heterogeneous in molecular and clinical features. However, the molecular classification of HPV+ cervical cancers remains insufficiently unexplored.MethodsBased on the expression profiles of 50 genes having the largest expression variations across the HPV+ cervical cancers in the TCGA-CESC dataset, we hierarchically clustered HPV+ cervical cancers to identify new subtypes. We further characterized molecular, phenotypic, and clinical features of these subtypes.ResultsWe identified two subtypes of HPV+ cervical cancers, namely HPV+G1 and HPV+G2. We demonstrated that this classification method was reproducible in two validation sets. Compared to HPV+G2, HPV+G1 displayed significantly higher immune infiltration level and stromal content, lower tumor purity, lower stemness scores and intratumor heterogeneity (ITH) scores, higher level of genomic instability, lower DNA methylation level, as well as better disease-free survival prognosis. The multivariate survival analysis suggests that the disease-free survival difference between both subtypes is independent of confounding variables, such as immune signature, stemness, and ITH. Pathway and gene ontology analysis confirmed the more active tumor immune microenvironment in HPV+G1 versus HPV+G2.ConclusionsHPV+ cervical cancers can be classified into two subtypes based on the expression profiles of the 50 genes with the largest expression variations across the HPV+ cervical cancers. Both subtypes have significantly different molecular, phenotypic, and clinical features. This new subtyping method captures the comprehensive heterogeneity in molecular and clinical characteristics of HPV+ cervical cancers and provides potential clinical implications for the diagnosis and treatment of this disease.

Two ultrastaging protocols for the detection of lymph node metastases in early-stage cervical and endometrial cancers

Provision of screening services for cervical and breast cancer – A scientific study commissioned by the European Board & College of Obstetrics and Gynaecology (EBCOG)

To review the scientific evidence related to predictive biomarkers in cervical adenocarcinoma (ADC). The authors reviewed the literature regarding predictive biomarkers in cervical ADC. There were several limitations: (1) there is an overlap between predictive and prognostic biomarkers, as the vast majority of patients are treated with anticancer strategies; (2) in many studies and clinical trials, cervical ADC patients are included in a large series of patients predominantly composed of cervical squamous cell carcinomas; and (3) in most of the studies, and clinical trials, there is no distinction between human papillomavirus (HPV)-associated and HPV-independent cervical ADCs, or between various histologic subtypes. Results obtained from a small group of studies confirm that cervical ADCs exhibit distinct molecular features as compared with squamous carcinomas, and that there are different molecular features between different types of cervical ADCs. Promising areas of interest include ERBB2 (HER2) mutations and PD-L1 expression as predictive biomarkers for anti-HER2 treatment and immunotherapy, respectively. To date, no definitive data can be obtained from the literature regarding predictive biomarkers for cervical ADC. Clinical trials specifically designed for endocervical ADC patients are required to elucidate the predictive value of HER2 mutations and PD-L1 expression. The distinction between HPV-associated and HPV-independent cervical ADCs as well as early involvement of pathologists in the design of future clinical trials are needed to identify new predictive biomarkers in cervical ADC.