A Gene Signature Identifying CIN3 Regression and Cervical Cancer Survival

The purpose of this study was to establish a gene signature that may predict CIN3 regression and that may aid in selecting patients who may safely refrain from conization. Oncomine mRNA data including 398 immune-related genes from 21 lesions with confirmed regression and 28 with persistent CIN3 were compared. L1000 mRNA data from a cervical cancer cohort was available for validation (n = 239). Transcriptomic analyses identified TDO2 (p = 0.004), CCL5 (p < 0.001), CCL3 (p = 0.04), CD38 (p = 0.02), and PRF1 (p = 0.005) as upregulated, and LCK downregulated (p = 0.01) in CIN3 regression as compared to persistent CIN3 lesions. From these, a gene signature predicting CIN3 regression with a sensitivity of 91% (AUC = 0.85) was established. Transcriptomic analyses revealed proliferation as significantly linked to persistent CIN3. Within the cancer cohort, high regression signature score associated with immune activation by Gene Set enrichment Analyses (GSEA) and immune cell infiltration by histopathological evaluation (p < 0.001). Low signature score was associated with poor survival (p = 0.007) and large tumors (p = 0.01). In conclusion, the proposed six-gene signature predicts CIN regression and favorable cervical cancer prognosis and points to common drivers in precursors and cervical cancer lesions.

Impact of hormonal biomarkers on response to hormonal therapy in advanced and recurrent endometrial cancer

BACKGROUND

Approximately 20% of women with endometrial cancer have advanced-stage disease or suffer from a recurrence. For these women, prognosis is poor, and palliative treatment options include hormonal therapy and chemotherapy. Lack of predictive biomarkers and suboptimal use of existing markers for response to hormonal therapy have resulted in overall limited efficacy.

OBJECTIVE

This study aimed to improve the efficacy of hormonal therapy by relating immunohistochemical expression of estrogen and progesterone receptors and estrogen receptor pathway activity scores to response to hormonal therapy.

STUDY DESIGN

Patients with advanced or recurrent endometrial cancer and available biopsies taken before the start of hormonal therapy were identified in 16 centers within the European Network for Individualized Treatment in Endometrial Cancer and the Dutch Gynecologic Oncology Group. Tumor tissue was analyzed for estrogen and progesterone receptor expressions and estrogen receptor pathway activity using a quantitative polymerase chain reaction-based messenger RNA model to measure the activity of estrogen receptor-related target genes in tumor RNA. The primary endpoint was response rate defined as complete and partial response using the Response Evaluation Criteria in Solid Tumors. The secondary endpoints were clinical benefit rate and progression-free survival.

RESULTS

Pretreatment biopsies with sufficient endometrial cancer tissue and complete response evaluation were available in 81 of 105 eligible cases. Here, 22 of 81 patients (27.2%) with a response had estrogen and progesterone receptor expressions of >50%, resulting in a response rate of 32.3% (95% confidence interval, 20.9-43.7) for an estrogen receptor expression of >50% and 50.0% (95% confidence interval, 35.2-64.8) for a progesterone receptor expression of >50%. Clinical benefit rate was 56.9% for an estrogen receptor expression of >50% (95% confidence interval, 44.9-68.9) and 75.0% (95% confidence interval, 62.2-87.8) for a progesterone receptor expression of >50%. The application of the estrogen receptor pathway test to cases with a progesterone receptor expression of >50% resulted in a response rate of 57.6% (95% confidence interval, 42.1-73.1). After 2 years of follow-up, 34.3% of cases (95% confidence interval, 20-48) with a progesterone receptor expression of >50% and 35.8% of cases (95% confidence interval, 20-52) with an estrogen receptor pathway activity score of >15 had not progressed.

CONCLUSION

The prediction of response to hormonal treatment in endometrial cancer improves substantially with a 50% cutoff level for progesterone receptor immunohistochemical expression and by applying a sequential test algorithm using progesterone receptor immunohistochemical expression and estrogen receptor pathway activity scores. However, results need to be validated in the prospective Prediction of Response to Hormonal Therapy in Advanced and Recurrent Endometrial Cancer (PROMOTE) study.

Feasibility and utility of MRI and dynamic 18F-FDG-PET in an orthotopic organoid-based patient-derived mouse model of endometrial cancer

BACKGROUND

Pelvic magnetic resonance imaging (MRI) and whole-body positron emission tomography-computed tomography (PET-CT) play an important role at primary diagnostic work-up and in detecting recurrent disease in endometrial cancer (EC) patients, however the preclinical use of these imaging methods is currently limited. We demonstrate the feasibility and utility of MRI and dynamic 18F-fluorodeoxyglucose (FDG)-PET imaging for monitoring tumor progression and assessing chemotherapy response in an orthotopic organoid-based patient-derived xenograft (O-PDX) mouse model of EC.

METHODS

18 O-PDX mice (grade 3 endometrioid EC, stage IIIC1), selectively underwent weekly T2-weighted MRI (total scans = 32), diffusion-weighted MRI (DWI) (total scans = 9) and dynamic 18F-FDG-PET (total scans = 26) during tumor progression. MRI tumor volumes (vMRI), tumor apparent diffusion coefficient values (ADCmean) and metabolic tumor parameters from 18F-FDG-PET including maximum and mean standard uptake values (SUVmax/SUVmean), metabolic tumor volume (MTV), total lesion glycolysis (TLG) and metabolic rate of 18F-FDG (MRFDG) were calculated. Further, nine mice were included in a chemotherapy treatment study (treatment; n = 5, controls; n = 4) and tumor ADCmean-values were compared to changes in vMRI and cellular density from histology at endpoint. A Mann-Whitney test was used to evaluate differences between groups.

RESULTS

Tumors with large tumor volumes (vMRI) had higher metabolic activity (MTV and TLG) in a clear linear relationship (r2 = 0.92 and 0.89, respectively). Non-invasive calculation of MRFDG from dynamic 18F-FDG-PET (mean MRFDG = 0.39 μmol/min) was feasible using an image-derived input function. Treated mice had higher tumor ADCmean (p = 0.03), lower vMRI (p = 0.03) and tumor cellular density (p = 0.02) than non-treated mice, all indicating treatment response.

CONCLUSION

Preclinical imaging mirroring clinical imaging methods in EC is highly feasible for monitoring tumor progression and treatment response in the present orthotopic organoid mouse model.

Patient-derived organoids reflect the genetic profile of endometrial tumors and predict patient prognosis

Background

A major hurdle in translational endometrial cancer (EC) research is the lack of robust preclinical models that capture both inter- and intra-tumor heterogeneity. This has hampered the development of new treatment strategies for people with EC.

Methods

EC organoids were derived from resected patient tumor tissue and expanded in a chemically defined medium. Established EC organoids were orthotopically implanted into female NSG mice. Patient tissue and corresponding models were characterized by morphological evaluation, biomarker and gene expression and by whole exome sequencing. A gene signature was defined and its prognostic value was assessed in multiple EC cohorts using Mantel-Cox (log-rank) test. Response to carboplatin and/or paclitaxel was measured in vitro and evaluated in vivo. Statistical difference between groups was calculated using paired t-test.

Results

We report EC organoids established from EC patient tissue, and orthotopic organoid-based patient-derived xenograft models (O-PDXs). The EC organoids and O-PDX models mimic the tissue architecture, protein biomarker expression and genetic profile of the original tissue. Organoids show heterogenous sensitivity to conventional chemotherapy, and drug response is reproduced in vivo. The relevance of these models is further supported by the identification of an organoid-derived prognostic gene signature. This signature is validated as prognostic both in our local patient cohorts and in the TCGA endometrial cancer cohort.

Conclusions

We establish robust model systems that capture both the diversity of endometrial tumors and intra-tumor heterogeneity. These models are highly relevant preclinical tools for the elucidation of the molecular pathogenesis of EC and identification of potential treatment strategies.

To study the biology of cancer and test new potential treatments, it is important to use models that mimic patients’ tumors. Such models have largely been lacking in endometrial cancer. We therefore aimed to developing miniature tumors, called “organoids”, directly from patient tumor tissue. Our organoids maintained the characteristics and genetic features of the tumors from which they were derived, would grow into endometrial tumors in mice, and exhibited patient-specific responses to chemotherapy drugs. In summary, we have developed models that will help us better understand the biology of endometrial tumors and can be used to potentially identify new effective drugs for endometrial cancer patients.

Berg et al. establish a panel of patient-derived endometrial cancer organoids and xenograft models. They show that their models recapitulate the genetic profile of the donor tumor and can be used for drug testing and development of a prognostic gene signature.

A 10-gene prognostic signature points to LIMCH1 and HLA-DQB1 as important players in aggressive cervical cancer disease

BACKGROUND

Advanced cervical cancer carries a particularly poor prognosis, and few treatment options exist. Identification of effective molecular markers is vital to improve the individualisation of treatment. We investigated transcriptional data from cervical carcinomas related to patient survival and recurrence to identify potential molecular drivers for aggressive disease.

METHODS

Primary tumour RNA-sequencing profiles from 20 patients with recurrence and 53 patients with cured disease were compared. Protein levels and prognostic impact for selected markers were identified by immunohistochemistry in a population-based patient cohort.

RESULTS

Comparison of tumours relative to recurrence status revealed 121 differentially expressed genes. From this gene set, a 10-gene signature with high prognostic significance (p = 0.001) was identified and validated in an independent patient cohort (p = 0.004). Protein levels of two signature genes, HLA-DQB1 (n = 389) and LIMCH1 (LIM and calponin homology domain 1) (n = 410), were independent predictors of survival (hazard ratio 2.50, p = 0.007 for HLA-DQB1 and 3.19, p = 0.007 for LIMCH1) when adjusting for established prognostic markers. HLA-DQB1 protein expression associated with programmed death ligand 1 positivity (p < 0.001). In gene set enrichment analyses, HLA-DQB1high tumours associated with immune activation and response to interferon-γ (IFN-γ).

CONCLUSIONS

This study revealed a 10-gene signature with high prognostic power in cervical cancer. HLA-DQB1 and LIMCH1 are potential biomarkers guiding cervical cancer treatment.

Immunohistochemical biomarkers are prognostic relevant in addition to the ESMO-ESGO-ESTRO risk classification in endometrial cancer

OBJECTIVE

Pre-operative immunohistochemical (IHC) biomarkers are not incorporated in endometrial cancer (EC) risk classification. We aim to investigate the added prognostic relevance of IHC biomarkers to the ESMO-ESGO-ESTRO risk classification and lymph node (LN) status in EC.

METHODS

Retrospective multicenter study within the European Network for Individualized Treatment of Endometrial Cancer (ENITEC), analyzing pre-operative IHC expression of p53, L1 cell-adhesion molecule (L1CAM), estrogen receptor (ER) and progesterone receptor (PR), and relate to ESMO-ESGO-ESTRO risk groups, LN status and outcome.

RESULTS

A total of 763 EC patients were included with a median follow-up of 5.5-years. Abnormal IHC expression was present for p53 in 112 (14.7%), L1CAM in 79 (10.4%), ER- in 76 (10.0%), and PR- in 138 (18.1%) patients. Abnormal expression of p53/L1CAM/ER/PR was significantly related with higher risk classification groups, and combined associated with the worst outcome within the 'high and advanced/metastatic' risk group. In multivariate analysis p53-abn, ER/PR- and ESMO-ESGO-ESTRO 'high and advanced/metastatic' were independently associated with reduced disease-specific survival (DSS). Patients with abnormal IHC expression and lymph node metastasis (LNM) had the worst outcome. Patients with LNM and normal IHC expression had comparable outcome with patients without LNM and abnormal IHC expression.

CONCLUSION

The use of pre-operative IHC biomarkers has important prognostic relevance in addition to the ESMO-ESGO-ESTRO risk classification and in addition to LN status. For daily clinical practice, p53/L1CAM/ER/PR expression could serve as indicator for surgical staging and refine selective adjuvant treatment by incorporation into the ESMO-ESGO-ESTRO risk classification.

Nuclear upregulation of class I phosphoinositide 3-kinase p110β correlates with high 47S rRNA levels in cancer cells

The class I phosphoinositide 3-kinase (PI3K) catalytic subunits p110α and p110β are ubiquitously expressed but differently targeted in tumours. In cancer, PIK3CB (encoding p110β) is seldom mutated compared with PIK3CA (encoding p110α) but can contribute to tumorigenesis in certain PTEN-deficient tumours. The underlying molecular mechanisms are, however, unclear. We have previously reported that p110β is highly expressed in endometrial cancer (EC) cell lines and at the mRNA level in primary patient tumours. Here, we show that p110β protein levels are high in both the cytoplasmic and nuclear compartments in EC cells. Moreover, high nuclear:cytoplasmic staining ratios were detected in high-grade primary tumours. High levels of phosphatidylinositol (3,4,5)-trisphosphate [PtdIns(3,4,5)P ₃] were measured in the nucleus of EC cells, and pharmacological and genetic approaches showed that its production was partly dependent upon p110β activity. Using immunofluorescence staining, p110β and PtdIns(3,4,5)P ₃ were localised in the nucleolus, which correlated with high levels of 47S pre-rRNA. p110β inhibition led to a decrease in both 47S rRNA levels and cell proliferation. In conclusion, these results present a nucleolar role for p110β that may contribute to tumorigenesis in EC.This article has an associated First Person interview with Fatemeh Mazloumi Gavgani, joint first author of the paper.

Mendelian randomization analyses suggest a role for cholesterol in the development of endometrial cancer

Blood lipids have been associated with the development of a range of cancers, including breast, lung and colorectal cancer. For endometrial cancer, observational studies have reported inconsistent associations between blood lipids and cancer risk. To reduce biases from unmeasured confounding, we performed a bidirectional, two-sample Mendelian randomization analysis to investigate the relationship between levels of three blood lipids (low-density lipoprotein [LDL] and high-density lipoprotein [HDL] cholesterol, and triglycerides) and endometrial cancer risk. Genetic variants associated with each of these blood lipid levels (P < 5 × 10-8 ) were identified as instrumental variables, and assessed using genome-wide association study data from the Endometrial Cancer Association Consortium (12 906 cases and 108 979 controls) and the Global Lipids Genetic Consortium (n = 188 578). Mendelian randomization analyses found genetically raised LDL cholesterol levels to be associated with lower risks of endometrial cancer of all histologies combined, and of endometrioid and non-endometrioid subtypes. Conversely, higher genetically predicted HDL cholesterol levels were associated with increased risk of non-endometrioid endometrial cancer. After accounting for the potential confounding role of obesity (as measured by genetic variants associated with body mass index), the association between genetically predicted increased LDL cholesterol levels and lower endometrial cancer risk remained significant, especially for non-endometrioid endometrial cancer. There was no evidence to support a role for triglycerides in endometrial cancer development. Our study supports a role for LDL and HDL cholesterol in the development of non-endometrioid endometrial cancer. Further studies are required to understand the mechanisms underlying these findings.

Maintained survival outcome after reducing lymphadenectomy rates and optimizing adjuvant treatment in endometrial cancer

OBJECTIVE

Main controversies in endometrial cancer treatment include the role of lymphadenectomy and optimal adjuvant treatment. We assessed clinical outcome in a population-based endometrial cancer cohort in relation to changes in treatment management over two decades.

METHODS

All consenting endometrial cancer patients receiving primary treatment at Haukeland University Hospital from 2001 to 2019 were included (n = 1308). Clinicopathological variables were evaluated for year-to-year changes. Clinical outcome before and after discontinuing adjuvant radiotherapy and individualizing extent of lymphadenectomy was analyzed.

RESULTS

The rate of lymphadenectomy was reduced from 78% in 2001-2012 to 53% in 2013-2019. The rate of patients with verified lymph node metastases was maintained (9% vs 8%, p = 0.58) and FIGO stage I patients who did not undergo lymphadenectomy had stable 3-year recurrence-free survival (88% vs 90%, p = 0.67). Adjuvant chemotherapy for completely resected FIGO stage III patients increased from 27% to 97% from 2001 to 2009 to 2010-2019, while adjuvant radiotherapy declined from 57% to 0% (p < 0.001). These patients had improved 5-year overall- and recurrence-free survival; 0.49 [95% CI: 0.37-0.65] in 2001-2009 compared to 0.61 [0.45-0.83] in 2010-2019, p = 0.04 and 0.51 [0.39-0.68] to 0.71 [0.60-0.85], p = 0.03, respectively. For stage I, II and IV, survival rates were unchanged.

CONCLUSIONS

Our study demonstrates that preoperative stratification by imaging and histological assessments permits a reduction in lymphadenectomy to around 50%, and is achievable without an increase in recurrences at 3 years. In addition, our findings support that adjuvant chemotherapy alone performs equally to adjuvant radiotherapy with regard to survival, and is likely superior in advanced stage patients.

Whole-Volume Tumor MRI Radiomics for Prognostic Modeling in Endometrial Cancer

Background

In endometrial cancer (EC), preoperative pelvic MRI is recommended for local staging, while final tumor stage and grade are established by surgery and pathology. MRI‐based radiomic tumor profiling may aid in preoperative risk‐stratification and support clinical treatment decisions in EC.

Purpose

To develop MRI‐based whole‐volume tumor radiomic signatures for prediction of aggressive EC disease.

Study Type

Retrospective.

Population

A total of 138 women with histologically confirmed EC, divided into training (n_T = 108) and validation cohorts (n_V = 30).

Field Strength/Sequence

Axial oblique T₁‐weighted gradient echo volumetric interpolated breath‐hold examination (VIBE) at 1.5T (71/138 patients) and DIXON VIBE at 3T (67/138 patients) at 2 minutes postcontrast injection.

Assessment

Primary tumors were manually segmented by two radiologists with 4 and 8 years' of experience. Radiomic tumor features were computed and used for prediction of surgicopathologically‐verified deep (≥50%) myometrial invasion (DMI), lymph node metastases (LNM), advanced stage (FIGO III + IV), nonendometrioid (NE) histology, and high‐grade endometrioid tumors (E3). Corresponding analyses were also conducted using radiomics extracted from the axial oblique image slice depicting the largest tumor area.

Statistical Tests

Logistic least absolute shrinkage and selection operator (LASSO) was applied for radiomic modeling in the training cohort. The diagnostic performances of the radiomic signatures were evaluated by area under the receiver operating characteristic curve in the training (AUC_T) and validation (AUC_V) cohorts. Progression‐free survival was assessed using the Kaplan–Meier and Cox proportional hazard model.

Results

The whole‐tumor radiomic signatures yielded AUC_T/AUC_V of 0.84/0.76 for predicting DMI, 0.73/0.72 for LNM, 0.71/0.68 for FIGO III + IV, 0.68/0.74 for NE histology, and 0.79/0.63 for high‐grade (E3) tumor. Single‐slice radiomics yielded comparable AUC_T but significantly lower AUC_V for LNM and FIGO III + IV (both P < 0.05). Tumor volume yielded comparable AUC_T to the whole‐tumor radiomic signatures for prediction of DMI, LNM, FIGO III + IV, and NE, but significantly lower AUC_T for E3 tumors (P < 0.05). All of the whole‐tumor radiomic signatures significantly predicted poor progression‐free survival with hazard ratios of 4.6–9.8 (P < 0.05 for all).

Data Conclusion

MRI‐based whole‐tumor radiomic signatures yield medium‐to‐high diagnostic performance for predicting aggressive EC disease. The signatures may aid in preoperative risk assessment and hence guide personalized treatment strategies in EC.

Level of Evidence

4

Technical Efficacy Stage

2

Cancer awareness in the general population varies with sex, age and media coverage: A population-based survey with focus on gynecologic cancers

OBJECTIVES

There is a need for more knowledge about the public awareness and attitudes towards gynecologic cancers. We employed a research-purpose population-based citizen panel to assess how often people recall gynecologic cancers compared to other cancer types and to explore the relative importance of different information channels in relaying cancer information.

STUDY DESIGN

We conducted an online survey using the Norwegian Citizen Panel (n = 1441 respondents), exploring associations between demographic factors and frequency of mentioning specific cancer types. We also searched The Norwegian Media Archive to assess the media coverage of different cancer types. Factors affecting likelihood of mentioning different cancers were assessed by multivariate regression.

RESULTS

Only 41 % of respondents listed one or more cancers in female genital organs. Of the gynecological cancers, cervical cancer was most frequently mentioned (28 %), followed by ovarian (12 %) and endometrial cancer (11 %). Female responders were more likely to mention cervical (OR 2.47, 95 % CI 2.16-2.78) and ovarian cancer (OR 2.09, 95 % CI 1.60-2.58) than male responders, but not endometrial cancer. Family and friends who have had cancer (50 %) and different types of media coverage (41 %) were reported as the most common sources of cancer information. The three most frequently mentioned cancer types in our survey were breast (77 %), hematologic (76 %) and lung cancer (75 %), which also were the cancer types having most media coverage.

CONCLUSIONS

Gynecological cancers are less frequently mentioned by Norwegian citizens when compared to several other cancer types such as breast-, hematologic- and lung cancer. Sex and age are important factors that affect awareness of cancer types. Media is likely to play an important role in what cancer types the public recalls.

Tumour texture features from preoperative CT predict high-risk disease in endometrial cancer

BACKGROUND

To enable more individualised treatment of endometrial cancer, improved methods for preoperative tumour characterization are warranted. Texture analysis is a method for quantification of heterogeneity in images, increasingly reported as a promising diagnostic tool in oncological imaging, but largely unexplored in endometrial cancer AIM: To explore whether tumour texture features from preoperative computed tomography (CT) are related to known prognostic histopathological features and to outcome in endometrial cancer patients.

MATERIALS AND METHODS

Preoperative pelvic contrast-enhanced CT was performed in 155 patients with histologically confirmed endometrial cancer. Tumour ROIs were manually drawn on the section displaying the largest cross-sectional tumour area, using dedicated texture analysis software. Using the filtration-histogram technique, the following texture features were calculated: mean, standard deviation, entropy, mean of positive pixels (MPP), skewness, and kurtosis. These imaging markers were evaluated as predictors of histopathological high-risk features and recurrence- and progression-free survival using multivariable logistic regression and Cox regression analysis, including models adjusting for high-risk status based on preoperative biopsy, magnetic resonance imaging (MRI) findings, and age.

RESULTS

High tumour entropy independently predicted deep myometrial invasion (odds ratio [OR] 3.7, p=0.008) and cervical stroma invasion (OR 3.9, p=0.02). High value of MPP (MPP5 >24.2) independently predicted high-risk histological subtype (OR 3.7, p=0.01). Furthermore, high tumour kurtosis tended to independently predict reduced recurrence- and progression-free survival (HR 1.1, p=0.06).

CONCLUSION

CT texture analysis yields promising imaging markers in endometrial cancer and may supplement other imaging techniques in providing a more refined preoperative risk assessment that may ultimately enable better tailored treatment strategies.

Abstract A16: Patient-derived organoid-based models for endometrial cancer

Introduction: Comprehensive profiling of tumors using omics technologies has improved our understanding of the molecular landscape of endometrial cancer (EC), building the foundation for precision medicine. However, targeted therapies that show promise in preclinical research are failing clinical trials, which is partly explained by the lack of models that mimic the physiopathology of patients. We aimed at establishing organoids and organoid-based patient-derived xenograft (O-PDX) models as part of a new preclinical platform for endometrial cancer.

Methods: Aggregates of tumor cells were isolated from fresh tumor samples, followed by long-term culturing as organoids in a chemically defined medium. Established organoids were implanted into the left uterine horn of NSG mice, and tumor growth was monitored using near-infrared fluorescence imaging (NIRF). Patient tissue, organoids, and corresponding O-PDXs were characterized by histology and whole-exome sequencing and by immunohistochemical staining of important endometrial cancer biomarkers. For proof of concept, selected models were treated with conventional therapeutic agents, including in vivo treatment with carboplatin.

Results: Organoids and orthotopic O-PDXs representing different subtypes of endometrial cancer were successfully established. Histologic and molecular profiles of organoids are similar to patient tissue, also after long-term culturing, and characteristics of O-PDXs were sustained after rederivation in vivo. Proof-of-concept drug testing shows heterogenous sensitivity to clinically administered chemotherapeutics.

Conclusion: We have extended the collection of EC organoids and established O-PDX models for in vivo studies. This state-of-the-art preclinical platform enables more clinically relevant drug testing that will facilitate translation into relevant clinical trials.

Citation Format: Hege F. Berg, Tina Fonnes, Elin Strand, Heidi Espedal, Ingunn M. Stefansson, Emmet McCormack, Line Bjørge, Jone Trovik, Ingfrid S. Haldorsen, Erling A. Hoyvik, Camilla Krakstad. Patient-derived organoid-based models for endometrial cancer [abstract]. In: Proceedings of the AACR Special Conference on the Evolving Landscape of Cancer Modeling; 2020 Mar 2-5; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2020;80(11 Suppl):Abstract nr A16.

Improving response to progestin treatment of low-grade endometrial cancer

OBJECTIVES

This review examines how response rates to progestin treatment of low-grade endometrial cancer can be improved. In addition to providing a brief overview of the pathogenesis of low-grade endometrial cancer, we discuss limitations in the current classification of endometrial cancer and how stratification may be refined using molecular markers to reproducibly identify 'low-risk' cancers which may represent the best candidates for progestin therapy. We also discuss constraints in current approaches to progestin treatment of low-grade endometrial cancer and perform a systematic review of predictive biomarkers.

METHODS

PubMed, ClinicalTrials.gov, and Cochrane Library were searched for studies reporting pre-treatment biomarkers associated with outcome in women with low-grade endometrial cancer or endometrial hyperplasia with an intact uterus who received progestin treatment. Studies of fewer than 50 women were excluded. The study protocol was registered in PROSPERO (ID 152374). A descriptive synthesis of pre-treatment predictive biomarkers reported in the included studies was conducted.

RESULTS

Of 1908 records reviewed, 19 studies were included. Clinical features such as age or body mass index cannot predict progestin response. Lesions defined as 'low-risk' by FIGO criteria (stage 1A, grade 1) can respond well; however, the reproducibility and prognostic ability of the current histopathological classification system is suboptimal. Molecular markers can be reproducibly assessed, have been validated as prognostic biomarkers, and may inform patient selection for progestin treatment. DNA polymerase epsilon (POLE)-ultramutated tumors and a subset of p53 wild-type or DNA mismatch repair (MMR)-deficient tumors with 'low-risk' features (eg, progesterone and estrogen receptor-positive) may have improved response rates, though this needs to be validated.

DISCUSSION

Molecular markers can identify cases which may be candidates for progestin treatment. More work is needed to validate these biomarkers and potentially identify new ones. Predictive biomarkers are anticipated to inform future research into progestin treatment of low-grade endometrial cancer and ultimately improve patient outcomes.

Development of prediction models for lymph node metastasis in endometrioid endometrial carcinoma

BACKGROUND

In endometrioid endometrial cancer (EEC), current clinical algorithms do not accurately predict patients with lymph node metastasis (LNM), leading to both under- and over-treatment. We aimed to develop models that integrate protein data with clinical information to identify patients requiring more aggressive surgery, including lymphadenectomy.

METHODS

Protein expression profiles were generated for 399 patients using reverse-phase protein array. Three generalised linear models were built on proteins and clinical information (model 1), also with magnetic resonance imaging included (model 2), and on proteins only (model 3), using a training set, and tested in independent sets. Gene expression data from the tumours were used for confirmatory testing.

RESULTS

LNM was predicted with area under the curve 0.72-0.89 and cyclin D1; fibronectin and grade were identified as important markers. High levels of fibronectin and cyclin D1 were associated with poor survival (p = 0.018), and with markers of tumour aggressiveness. Upregulation of both FN1 and CCND1 messenger RNA was related to cancer invasion and mesenchymal phenotype.

CONCLUSIONS

We demonstrate that data-driven prediction models, adding protein markers to clinical information, have potential to significantly improve preoperative identification of patients with LNM in EEC.

Preoperative 18F-FDG PET/CT tumor markers outperform MRI-based markers for the prediction of lymph node metastases in primary endometrial cancer

Objectives

To compare the diagnostic accuracy of preoperative 18F-FDG PET/CT and MRI tumor markers for prediction of lymph node metastases (LNM) and aggressive disease in endometrial cancer (EC).

Methods

Preoperative whole-body 18F-FDG PET/CT and pelvic MRI were performed in 215 consecutive patients with histologically confirmed EC. PET/CT-based tumor standardized uptake value (SUV_max and SUV_mean), metabolic tumor volume (MTV), and PET-positive lymph nodes (LNs) (SUV_max > 2.5) were analyzed together with the MRI-based tumor volume (V_MRI), mean apparent diffusion coefficient (ADC_mean), and MRI-positive LN (maximum short-axis diameter ≥ 10 mm). Imaging parameters were explored in relation to surgicopathological stage and tumor grade. Receiver operating characteristic (ROC) curves were generated yielding optimal cutoff values for imaging parameters, and regression analyses were used to assess their diagnostic performance for prediction of LNM and progression-free survival.

Results

For prediction of LNM, MTV yielded the largest area under the ROC curve (AUC) (AUC = 0.80), whereas V_MRI had lower AUC (AUC = 0.72) (p = 0.03). Furthermore, MTV > 27 ml yielded significantly higher specificity (74%, p < 0.001) and accuracy (75%, p < 0.001) and also higher odds ratio (12.2) for predicting LNM, compared with V_MRI > 10 ml (58%, 62%, and 9.7, respectively). MTV > 27 ml also tended to yield higher sensitivity than PET-positive LN (81% vs 50%, p = 0.13). Both V_MRI > 10 ml and MTV > 27 ml were significantly associated with reduced progression-free survival.

Conclusions

Tumor markers from 18F-FDG PET/CT outperform MRI markers for the prediction of LNM. MTV > 27 ml yields a high diagnostic performance for predicting aggressive disease and represents a promising supplement to conventional PET/CT reading in EC.

Key Points

• Metabolic tumor volume (MTV) outperforms other 18F-FDG PET/CT and MRI markers for preoperative prediction of lymph node metastases (LNM) in endometrial cancer patients.

• Using cutoff values for tumor volume for prediction of LNM, MTV > 27 ml yielded higher specificity and accuracy than V_MRI> 10 ml.

• MTV represents a promising supplement to conventional PET/CT reading for predicting aggressive disease in EC.

Electronic supplementary material

The online version of this article (10.1007/s00330-019-06622-w) contains supplementary material, which is available to authorized users.

Blood steroid levels predict survival in endometrial cancer and reflect tumor estrogen signaling

OBJECTIVE

Blood-based biomarkers are attractive due to ease of sampling and standardized measurement technology, reducing obstacles to clinical implementation. The objective of this study was to evaluate a clinically available method of steroid hormone measurement for its prognostic potential in endometrial cancer.

METHODS

We quantified seven steroid hormones by liquid chromatography-tandem mass spectrometry in 100 endometrial cancer patients from a prospective cohort. Abdominal fat distribution was assessed from abdominal computed tomography (CT) scans. Steroid hormone levels were compared to clinical characteristics, fat distribution and gene expression in primary tumor samples.

RESULTS

Low levels of 17OH-progesterone, 11-deoxycortisol and androstenedione were associated with aggressive tumor characteristics and poor disease specific survival (p = .003, p = .001 and p = .02 respectively). Adjusting for preoperative risk based on histological type and grade, low 17OH-progesterone and 11-deoxycortisol independently predicted poor outcome with hazard ratios of 2.69 (p = .033, 95%CI: 1.09-6.68) and 3.40 (p = .020, 1.21-9.51), respectively. Tumors from patients with low steroid level displayed increased expression of genes related to mitosis and cell cycle progression, whereas high steroid level was associated with upregulated estrogen signaling and genes associated with inflammation. Estrone and estradiol correlated to abdominal fat volume in all compartments (total, visceral, subcutaneous, p < .001 for all), but not to the visceral fat proportion. Patients with higher levels of circulating estrogens had increased expression of estrogen signaling related genes.

CONCLUSION

Low levels of certain endogenous steroids are associated with aggressive tumor traits and poor survival and may provide preoperative information independent of histological biomarkers already in use.

Imaging of Preclinical Endometrial Cancer Models for Monitoring Tumor Progression and Response to Targeted Therapy

Endometrial cancer is the most common gynecologic malignancy in industrialized countries. Most patients are cured by surgery; however, about 15% of the patients develop recurrence with limited treatment options. Patient-derived tumor xenograft (PDX) mouse models represent useful tools for preclinical evaluation of new therapies and biomarker identification. Preclinical imaging by magnetic resonance imaging (MRI), positron emission tomography-computed tomography (PET-CT), single-photon emission computed tomography (SPECT) and optical imaging during disease progression enables visualization and quantification of functional tumor characteristics, which may serve as imaging biomarkers guiding targeted therapies. A critical question, however, is whether the in vivo model systems mimic the disease setting in patients to such an extent that the imaging biomarkers may be translatable to the clinic. The primary objective of this review is to give an overview of current and novel preclinical imaging methods relevant for endometrial cancer animal models. Furthermore, we highlight how these advanced imaging methods depict pathogenic mechanisms important for tumor progression that represent potential targets for treatment in endometrial cancer.

Abstract 4879: Poor outcome in hypoxic endometrial carcinoma is related to vascular density

Optimal identification of endometrial carcinoma (EC) patients at high risk of recurrence is currently lacking. Hypoxia is an important feature of aggressive EC leading to activation of hypoxic and angiogenetic target genes. The present study investigates the prognostic role of hypoxia and angiogenesis in EC. Data and tissues were used from 11 collaborating European Network for Individualized Treatment of Endometrial Cancer (ENITEC) centers. Tumor slides were stained for CAIX as a hypoxic marker and CD-34 for assessment of microvessel density (MVD) as a marker for angiogenesis. Complete slides were digitalized and analyzed using ImageJ software after exclusion of areas without tumor. A cutoff of 1% for the fraction of CAIX positive tumor cells was used. The MVD was assessed according to the Weidner method with the median as cutoff. Correlations with disease-specific survival (DSS), disease-free survival (DFS) and distant disease-free survival (DDFS) were calculated using Cox regression analysis. Sixty-three (16.4%) of 385 ECs showed positive CAIX-expression with high vascular density. Multivariable analysis showed that ECs with combined positive CAIX-expression and high vascular density had a reduced DSS (hazard ratio [HR] 3.71, p = 0.002) and DDFS (HR 2.68, p = 0.009) and a trend for reduced DFS (HR 1.87, p = 0.054). Multivariable analyses with CAIX-expression and vascular density as separate markers, showed that both were independent prognostic markers as well. This study found an impaired DSS and DDFS in ECs with positive CAIX-expression and high vascular density. Differential adjuvant treatment might be indicated for these ECs.

Citation Format: Casper Reijnen, Willem Jan van Weelden, Martijn SJP Arts, Johan P. Peters, Paul F. Rijken, Koen van de Vijver, Maria Santacana, Peter Bronsert, Johan Bulten, Marc Hirschfeld, Eva Colas, Antonio Gil-Moreno, Amando Reques, Gemma Mancebo, Fransesc Alameda, Camilla Krakstad, Jone Trovik, Ingfrid S. Haldorsen, Jutta Huvila, Stefanie Schrouwen, Martin Koskas, Francine Walker, Vit Weinberger, Lubos Minar, Eva Jandakova, Marc PLM Snijders, Saskia van den Berg-van Erp, Heidi VN Küsters-Vandevelde, Xavier Matias-Guiu, Frederic Amant, ENITEC-consortium, Leon FAG Massuger, Johan Bussink, Johanna MA Pijnenborg. Poor outcome in hypoxic endometrial carcinoma is related to vascular density [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4879.

Impact of body mass index and fat distribution on sex steroid levels in endometrial carcinoma: a retrospective study

Background

Obesity is an important cause of multiple cancer types, amongst which endometrial cancer (EC). The relation between obesity and cancer is complicated and involves alterations in insulin metabolism, response to inflammation and alterations in estradiol metabolism. Visceral obesity is assumed to play the most important role in the first two mechanisms, but its role in estradiol metabolism is unclear. Therefore, this retrospective study explores the relationship of body mass index (BMI), visceral fat volume (VAV) and subcutaneous fat volume (SAV) and serum levels of sex steroids and lipids in patients with endometrial cancer.

Methods

Thirty-nine postmenopausal EC patients with available BMI, blood serum and Computed Tomography (CT) scans were included. Serum was analyzed for estradiol, dehydroepiandrosterone sulfate (DHEAS), androstenedione, testosterone, cholesterol, triglycerides and high (HDL), low (LDL) and non-high density (NHDL) lipoprotein. VAV and SAV were quantified on abdominal CT scan images. Findings were interpreted using pearson correlation coefficient and linear regression with commonality analysis.

Results

Serum estradiol is moderately correlated with BMI (r = 0.62) and VAV (r = 0.58) and strongly correlated with SAV (r = 0.74) (p < 0.001 for all). SAV contributes more to estradiol levels than VAV (10.3% for SAV, 1.4% for VAV, 35.9% for SAV and VAV, p = 0.01). Other sex steroids and lipids have weak and moderate correlations with VAV or SAV.

Conclusions

This study shows that serum estradiol is correlated with BMI and other fat-distribution measures in postmenopausal endometrial cancer patients. Subcutaneous fat tissue contributes more to the estradiol levels indicating that subcutaneous fat might be relevant in endometrial cancer carcinogenesis.

Electronic supplementary material

The online version of this article (10.1186/s12885-019-5770-6) contains supplementary material, which is available to authorized users.

Epithelial to mesenchymal transition (EMT) is associated with attenuation of succinate dehydrogenase (SDH) in breast cancer through reduced expression of SDHC

BACKGROUND

Epithelial to mesenchymal transition (EMT) is a well-characterized process of cell plasticity that may involve metabolic rewiring. In cancer, EMT is associated with malignant progression, tumor heterogeneity, and therapy resistance. In this study, we investigated the role of succinate dehydrogenase (SDH) as a potential key regulator of EMT.

METHODS

Associations between SDH subunits and EMT were explored in gene expression data from breast cancer patient cohorts, followed by in-depth studies of SDH suppression as a potential mediator of EMT in cultured cells.

RESULTS

We found an overall inverse association between EMT and the SDH subunit C (SDHC) when analyzing gene expression in breast tumors. This was particularly evident in carcinomas of basal-like molecular subtype compared to non-basal-like tumors, and a low SDHC expression level tended to have a prognostic impact in those patients. Studies in cultured cells revealed that EMT was induced by SDH inhibition through SDHC CRISPR/Cas9 knockdown or by the enzymatic inhibitor malonate. Conversely, overexpression of EMT-promoting transcription factors TWIST and SNAI2 caused decreased levels of SDHB and C and reduced rates of SDH-linked mitochondrial respiration. Cells overexpressing TWIST had reduced mitochondrial mass, and the organelles were thinner and more fragmented compared to controls.

CONCLUSIONS

Our findings suggest that downregulation of SDHC promotes EMT and that this is accompanied by structural remodeling of the mitochondrial organelles. This may confer survival benefits upon exposure to hostile microenvironment including oxidative stress and hypoxia during cancer progression.

Addition of IMP3 to L1CAM for discrimination between low- and high-grade endometrial carcinomas: a European Network for Individualised Treatment of Endometrial Cancer collaboration study

Discrimination between low- and high-grade endometrial carcinomas (ECs) is clinically relevant but can be challenging for pathologists, with moderate interobserver agreement. Insulin-like growth factor-II mRNA-binding protein 3 (IMP3) is an oncofoetal protein that is associated with nonendometrioid endometrial carcinomas but has been limited studied in endometrioid carcinomas. The aim of this study is to investigate the diagnostic and prognostic value of IMP3 in the discrimination between low- and high-grade ECs and its added value to L1CAM. IMP3 and L1CAM expression was assessed in tumors from 378 patients treated for EC at 1 of 9 participating European Network for Individualised Treatment of Endometrial Cancer centers. IMP3 was expressed in 24.6% of the tumors. In general, IMP3 was more homogeneously expressed than L1CAM. IMP3 expression was significantly associated with advanced stage, nonendometrioid histology, grade 3 tumors, deep myometrial invasion, lymphovascular space invasion, distant recurrences, overall mortality, and disease-related mortality. Simultaneous absence of IMP3 and L1CAM expression showed the highest accuracy for identifying low-grade carcinomas (area under the curve 0.766), whereas simultaneous expression of IMP3 and L1CAM was strongly associated with high-grade carcinomas (odds ratio 19.7; 95% confidence interval 9.2-42.2). Even within endometrioid carcinomas, this combination remained superior to IMP3 and L1CAM alone (odds ratio 8.6; 95% confidence interval 3.4-21.9). In conclusion, IMP3 has good diagnostic value and together with L1CAM represents the optimal combination of diagnostic markers for discrimination between low- and high-grade ECs compared to IMP3 and L1CAM alone. Because of the homogenous expression of IMP3, this marker might be valuable in preoperative biopsies when compared to the more patchy L1CAM expression.