Genomic insights in gynecologic cancer

Comprehensive Approach to Genomic and Immune Profiling: Insights of a Real-World Experience in Gynecological Tumors

Gynecological cancer accounts for an elevated incidence worldwide requiring responsiveness regarding its care. The comprehensive genomic approach agrees with the classification of certain tumor types. We evaluated 49 patients with gynecological tumors undergoing high-throughput sequencing to explore whether identifying alterations in cancer-associated genes could characterize concrete histological subtypes. We performed immune examination and analyzed subsequent clinical impact. We found 220 genomic aberrations mostly distributed as single nucleotide variants (SNV, 77%). Only 3% were classified as variants of strong clinical significance in BRCA1 and BRCA2 of ovarian high-grade serous (HGSC) and uterine endometrioid carcinoma. TP53 and BRCA1 occurred in 72% and 28% of HGSC. Cervical squamous cell carcinoma was entirely HPV-associated and mutations occurred in PIK3CA (60%), as well as in uterine serous carcinoma (80%). Alterations were seen in PTEN (71%) and PIK3CA (60%) of uterine endometrioid carcinoma. Elevated programmed death-ligand 1 (PD-L1) was associated with high TILs. Either PD-L1 augmented in deficient mis-matched repair (MMR) proteins or POLE mutated cases when compared to a proficient MMR state. An 18% received genotype-guided therapy and a 4% immunotherapy. The description of tumor subtypes is plausible through high-throughput sequencing by recognizing clinically relevant alterations. Additional concomitant assessment of immune biomarkers identifies candidates for immunotherapy.

TPX2 Serves as a Cancer Susceptibility Gene and Is Closely Associated with the Poor Prognosis of Endometrial Cancer

Background. Endometrial cancer (EC) is a common tumor of the genital tract that affects the female reproductive system but with only limited treatment options. We aimed to discover new prognostic biomarkers for EC. Methods. We used mRNA-seq data to detect differentially expressed genes (DEGs) between EC and control tissues. Detailed clinicopathological information was collected, and changes in the mRNA and protein levels of hub DEGs were analyzed in EC. Copy number variation (CNV) was also evaluated for its association with the pathogenesis of EC. Gene set enrichment analysis (GSEA) was conducted to enrich significant pathways driven by the hub genes. Cox regression analysis was used to select variables to create a nomogram. The nomogram was calibrated by applying the concordance index (C-index), and net benefits of the nomogram at different threshold probabilities were quantified using decision curve analysis (DCA). Results. Differential expression analysis identified 24 DEGs as potential risk factors for EC. Survival analysis revealed that TPX2 expression was related to worsening overall survival in patients with advanced EC. A high CNV was associated with the overexpression of TPX2; this suggested that modifications in the cell-cycle pathway might be crucial in the advancement of EC. Moreover, an individualized nomogram was developed for TPX2 incorporating clinical factors; this was also evaluated for its ability to predict EC. Calibration and DCA analyses confirmed the robustness and clinical usefulness of the nomogram. Conclusion. We offer novel insights into the pathogenesis and molecular mechanisms of EC. The overexpression of TPX2 was related to a poorer prognosis and could serve as a biomarker for predicting prognostic outcomes in EC patients.

The impact of uterine adenomyosis on the histopathological risk factors and survival in patients with endometrial adenocarcinoma

A retrospective cohort study was performed on patients diagnosed with endometrial adenocarcinoma (EC) during a 9-year period to investigate the impact of co-existing adenomyosis on patients with EC. Group A included women with EC and adenomyosis and Group B EC cases without the presence of adenomyosis. Group A was more likely to have early-stage disease, tumours without deep myometrial invasion, low-grade tumours and tumours with negative lymphovascular space invasion when compared to Group B (p = 0.012, p = 0.004, p < 0.001, p = 0.02). There were no statistically significant difference between Group A and Group B for lymph node metastasis (p = 0.064). There was no significant relation between the adenomyosis and survival outcomes in the multivariant analysis (p = 0.437). As a conclusion, patients with adenomyosis were more likely to accompany good histopathologic prognostic factors. Multivariate analysis showed no significant effect of adenomyosis on recurrence and survival parameters.IMPACT STATEMENTWhat is already known on this subject? Adenomyosis is one of the most common accompanying benign histopathological findings of type 1 endometrial carcinomas (EC). Adenomyosis comprises some characteristics similar to malignant tumours, such as invasion, abnormal tissue growth and angiogenesis. Despite concerns have arisen due to both their high incidence and similar molecular links, the possible relation between EC and adenomyosis is still not well grounded.What the results of this study add? We presented a 9-year period retrospective cohort of a tertiary referring single centre and evaluated the prognostic effect of adenomyosis in patients with EC as well as the survival outcomes of these patients. The co-occurrence of adenomyosis was more likely to accompany early-stage (stages 1-2) disease, low-grade tumours (grades 1-2) and tumours with negative LVSI in patients with EC. However, multivariate and survival analysis showed no significant effect of adenomyosis on recurrence and survival parameters.What the implications are of these findings for clinical practice and/or further research? Based on these findings, we suggest that the presence of adenomyosis should not be considered as a prognostic factor in EC. Our results support the overriding opinion about the prognostic value of co-occurrence of adenomyosis and EC. However, further studies exploring the molecular and genomic markers in these two groups are needed to uncover the exact relation of adenomyosis on the prognosis of EC.

Machine Learning for Recurrence Prediction of Gynecologic Cancers Using Lynch Syndrome-Related Screening Markers

Simple Summary

Recurrent patients with gynecologic cancer experience a difficult situation when using immune checkpoint inhibitors based on mismatch repair gene immunohistochemistry and microsatellite instability. Six machine learning algorithms were used to create predictive models with seven prospective features (four MMR IHC [MLH1, MSH2, MSH6, and PMS2], MSI, Age 60, and tumor size). The experimental results showed that the RF-based model performed best at predicting gynecologic cancer recurrence, with AUCs of 0.818 and 0.826 for the 5-fold cross-validation (CV) and 5-fold CV with 10 repetitions, respectively. This provides novel and baseline results of patients with recurrent gynecologic cancer using immune checkpoint inhibitors by using machine learning methods based on Lynch syndrome-related screening markers.

Abstract

To support the implementation of genome-based precision medicine, we developed machine learning models that predict the recurrence of patients with gynecologic cancer in using immune checkpoint inhibitors (ICI) based on clinical and pathologic characteristics, including Lynch syndrome-related screening markers such as immunohistochemistry (IHC) and microsatellite instability (MSI) tests. To accomplish our goal, we reviewed the patient demographics, clinical data, and pathological results from their medical records. Then we identified seven potential characteristics (four MMR IHC [MLH1, MSH2, MSH6, and PMS2], MSI, Age 60, and tumor size). Following that, predictive models were built based on these variables using six machine learning algorithms: logistic regression (LR), support vector machine (SVM), naive Bayes (NB), random forest (RF), gradient boosting (GB), and extreme gradient boosting (EGB) (XGBoost). The experimental results showed that the RF-based model performed best at predicting gynecologic cancer recurrence, with AUCs of 0.818 and 0.826 for the 5-fold cross-validation (CV) and 5-fold CV with 10 repetitions, respectively. This study provides novel and baseline results about predicting the recurrence of gynecologic cancer in patients using ICI by using machine learning methods based on Lynch syndrome-related screening markers.

Personalized Medicine in Gynecologic Cancer: Fact or Fiction?

Personalized medicine in gynecologic oncology is an evolving field. In recent years, tumor profiling and large databases such as TCGA and NCI-Match have provided us with enormous amounts of molecular data. Several therapies that capitalize on novel genetic and immune discoveries including VEGF inhibitors, PARP inhibitors, and cancer vaccinations are discussed in this article. Additionally, we have seen direct to consumer marketing play an important role in cancer care and prevention as patients have increased ability to access genetic testing. This presents a unique challenge to gynecologic oncology providers as we learn to navigate the world of personalized medicine.

m6A RNA Methylation Regulators Contribute to Eutopic Endometrium and Myometrium Dysfunction in Adenomyosis

Adenomyosis is a prevalent, estrogen-dependent uterine disorder wherein endometrial cells are abnormally present in the myometrium and are surrounded by hyperplastic/hypertrophic smooth muscle. Its etiology is unclear, although endometrial cell invasion into the myometrium has been postulated. RNA methylation, particularly N6-methyladenosine (m6A), plays an important role in regulating various physiological processes and invasive disorders. The goal of this in silico and lab-based experimental study was to explore a possible role for m6A in adenomyosis. Gene expression profiles of both the endometrium and myometrium of women with adenomyosis (cases) and without disease (controls) were obtained from the publicly available Gene Expression Omnibus (GEO) database. In the endometrium, STRING database analysis revealed that METTL3 functions as a "hub" gene of m6A RNA methylation regulators, and the genes involved in m6A regulation, including METTL3, FTO, ZC3H13, and YTHDC1 expression, were significantly decreased in cases versus controls. Functional, co-expression, and correlational analyses of endometrium from cases versus controls revealed decreased total m6A levels, induced by METTL3, and the downstream elevated insulin-like growth factor-1(IGF1) and D-Dopachrome Tautomerase (DDT), with the latter two having known functions in epithelial proliferation and cell migration, which are important processes in the pathogenesis of adenomyosis in endometrium. m6A RNA methylation regulators, including RBM15/15B, ALKBH5, FTO, YTHDF1/2, KIAA1429, HNRNPC, METTL3, ZC3H13, and YTHDC2, were also differentially expressed in the myometrium from cases versus controls. We validated decreased total m6A levels and differential expression of m6A RNA methylation regulators in the myometrium of patients with adenomyosis using qRT-PCR, immunohistochemistry and tissues available from our biorepository. Possible target genes, including cadherin 3(CDH3), sodium channelβ-subunit 4 (SCN4B), and placenta-specific protein 8 (PLAC8), which are involved in cell adhesion, muscle contraction and immune response in the myometrium of adenomyosis patients were also validated. Thus, through extensive public database mining and validation of select genes, this study, for the first time, implicates m6A and its methylation regulators in the pathogenesis of adenomyosis. Follow on functional studies are anticipated to elucidate mechanisms involving m6A and its regulators and down-stream effectors in the pathogenesis of this enigmatic reproductive disorder and potentially identify druggable targets to control its associated symptoms.

Personalized Medicine in Gynecologic Cancer: Fact or Fiction?

Personalized medicine in gynecologic oncology is an evolving field. In recent years, tumor profiling and large databases such as TCGA and NCI-Match have provided us with enormous amounts of molecular data. Several therapies that capitalize on novel genetic and immune discoveries including VEGF inhibitors, PARP inhibitors, and cancer vaccinations are discussed in this article. Additionally, we have seen direct to consumer marketing play an important role in cancer care and prevention as patients have increased ability to access genetic testing. This presents a unique challenge to gynecologic oncology providers as we learn to navigate the world of personalized medicine.

Detection of high-risk human papillomavirus DNA in tissue from primary cervical cancer tumor, pelvic lymph nodes and recurrent disease

Objectives

The present study investigated Human Papillomavirus (HPV) DNA genotyping in primary tumor, pelvic lymph nodes (PLN) and recurrence in early-stage cervical cancer patients.

Methods

We conducted a hospital-based case-control study. From 2003 to 2015, 282 patients underwent surgery for cervical cancer in the Department of Gynecology, Aarhus University Hospital, Denmark. Twenty-nine recurrent cases were identified. HPV DNA genotyping was performed on formalin-fixed, paraffin-embedded tissue specimens from the primary tumor, PLN, and recurrent disease.

Results

In the primary tumor, HPV DNA was detectable in 18(72%) of 25 tissue specimens from recurrent cases and in 15(83%) of 18 controls. HPV DNA-positive PLN was significantly associated with recurrence, 83%(95%CI: 52–98%), compared to patients with HPV-negative PLN, 38%(95%CI: 18–62%)(p < 0.05). HPV DNA genotyping was positive in eight of 12(67%) patients with recurrent disease. The genotype was identical in all three tissues types.

The positive predictive value for recurrence was the same for detection of HPV-DNA and metastases in the PLN, with reasonable sensitivity. The negative predictive value for recurrence, however, was best for HPV-DNA, 62%(95%CI: 38–98%).

Conclusions

In conclusion, our data suggest that the presence of HPV in pelvic lymph nodes is associated with an increased risk of recurrence.