Radiomic profiles improve prognostication and reveal targets for therapy in cervical cancer

Cervical cancer (CC) is a major global health problem with 570,000 new cases and 266,000 deaths annually. Prognosis is poor for advanced stage disease, and few effective treatments exist. Preoperative diagnostic imaging is common in high-income countries and MRI measured tumor size routinely guides treatment allocation of cervical cancer patients. Recently, the role of MRI radiomics has been recognized. However, its potential to independently predict survival and treatment response requires further clarification. This retrospective cohort study demonstrates how non-invasive, preoperative, MRI radiomic profiling may improve prognostication and tailoring of treatments and follow-ups for cervical cancer patients. By unsupervised clustering based on 293 radiomic features from 132 patients, we identify three distinct clusters comprising patients with significantly different risk profiles, also when adjusting for FIGO stage and age. By linking their radiomic profiles to genomic alterations, we identify putative treatment targets for the different patient clusters (e.g., immunotherapy, CDK4/6 and YAP-TEAD inhibitors and p53 pathway targeting treatments).

MRI radiomics captures early treatment response in patient-derived organoid endometrial cancer mouse models

Background

Radiomics can capture microscale information in medical images beyond what is visible to the naked human eye. Using a clinically relevant mouse model for endometrial cancer, the objective of this study was to develop and validate a radiomic signature (RS) predicting response to standard chemotherapy.

Methods

Mice orthotopically implanted with a patient-derived grade 3 endometrioid endometrial cancer organoid model (O-PDX) were allocated to chemotherapy (combined paclitaxel/carboplatin, n=11) or saline/control (n=13). During tumor progression, the mice underwent weekly T2-weighted (T2w) magnetic resonance imaging (MRI). Segmentation of primary tumor volume (vMRI) allowed extraction of radiomic features from whole-volume tumor masks. A radiomic model for predicting treatment response was derived employing least absolute shrinkage and selection operator (LASSO) statistics at endpoint images in the orthotopic O-PDX (RS_O), and subsequently applied on the earlier study timepoints (RS_O at baseline, and week 1-3). For external validation, the radiomic model was tested in a separate T2w-MRI dataset on segmented whole-volume subcutaneous tumors (RS_S) from the same O-PDX model, imaged at three timepoints (baseline, day 3 and day 10/endpoint) after start of chemotherapy (n=8 tumors) or saline/control (n=8 tumors).

Results

The RS_O yielded rapidly increasing area under the receiver operating characteristic (ROC) curves (AUCs) for predicting treatment response from baseline until endpoint; AUC=0.38 (baseline); 0.80 (week 1), 0.85 (week 2), 0.96 (week 3) and 1.0 (endpoint). In comparison, vMRI yielded AUCs of 0.37 (baseline); 0.69 (w1); 0.83 (week 2); 0.92 (week 3) and 0.97 (endpoint). When tested in the external validation dataset, RS_S yielded high accuracy for predicting treatment response at day10/endpoint (AUC=0.85) and tended to yield higher AUC than vMRI (AUC=0.78, p=0.18). Neither RS_S nor vMRI predicted response at day 3 in the external validation set (AUC=0.56 for both).

Conclusions

We have developed and validated a radiomic signature that was able to capture chemotherapeutic treatment response both in an O-PDX and in a subcutaneous endometrial cancer mouse model. This study supports the promising role of preclinical imaging including radiomic tumor profiling to assess early treatment response in endometrial cancer models.

Integrated mutational landscape analysis of poorly differentiated high-grade neuroendocrine carcinoma of the uterine cervix

High-grade neuroendocrine cervical cancers (NETc) are exceedingly rare, highly aggressive tumors. We analyzed 64 NETc tumor samples by whole-exome sequencing (WES). Human papillomavirus DNA was detected in 65.6% (42/64) of the tumors. Recurrent mutations were identified in PIK3CA, KMT2D/MLL2, K-RAS, ARID1A, NOTCH2, and RPL10. The top mutated genes included RB1, ARID1A, PTEN, KMT2D/MLL2, and WDFY3, a gene not yet implicated in NETc. Somatic CNV analysis identified two copy number gains (3q27.1 and 19q13.12) and five copy number losses (1p36.21/5q31.3/6p22.2/9q21.11/11p15.5). Also, gene fusions affecting the ACLY-CRHR1 and PVT1-MYC genes were identified in one of the eight samples subjected to RNA sequencing. To resolve evolutionary history, multiregion WES in NETc admixed with adenocarcinoma cells was performed (i.e., mixed-NETc). Phylogenetic analysis of mixed-NETc demonstrated that adenocarcinoma and neuroendocrine elements derive from a common precursor with mutations typical of adenocarcinomas. Over one-third (22/64) of NETc demonstrated a mutator phenotype of C > T at CpG consistent with deficiencies in MBD4, a member of the base excision repair (BER) pathway. Mutations in the PI3K/AMPK pathways were identified in 49/64 samples. We used two patient-derived-xenografts (PDX) (i.e., NET19 and NET21) to evaluate the activity of pan-HER (afatinib), PIK3CA (copanlisib), and ATR (elimusertib) inhibitors, alone and in combination. PDXs harboring alterations in the ERBB2/PI3K/AKT/mTOR/ATR pathway were sensitive to afatinib, copanlisib, and elimusertib (P < 0.001 vs. controls). However, combinations of copanlisib/afatinib and copanlisib/elimusertib were significantly more effective in controlling NETc tumor growth. These findings define the genetic landscape of NETc and suggest that a large subset of these highly lethal malignancies might benefit from existing targeted therapies.

Clinicopathological and radiological stratification within FIGO 2018 stages improves risk-prediction in cervical cancer

OBJECTIVE

Assess the added prognostic value of the updated International Federation of Gynecology and Obstetrics (FIGO) 2018 staging system, and to identify clinicopathological and radiological biomarkers for improved FIGO 2018 prognostication.

METHODS

Patient data were retrieved from a prospectively collected patient cohort including all consenting patients with cervical cancer diagnosed and treated at Haukeland University Hospital during 2001-2022 (n = 948). All patients were staged according to the FIGO 2009 and FIGO 2018 guidelines based on available data for individual patients. MRI-assessed maximum tumor diameter and stromal tumor invasion, as well as histopathologically assessed lymphovascular space invasion were applied to categorize patients according to the Sedlis criteria.

RESULTS

FIGO 2018 stage yielded the highest area under the receiver operating characteristic (ROC) curve (AUC) (0.86 versus 0.81 for FIGO 2009) for predicting disease-specific survival. The most common stage migration in FIGO 2018 versus FIGO 2009 was upstaging from stages IB/II to stage IIIC due to suspicious lymph nodes identified by PET/CT and/or MRI. In FIGO 2018 stage III patients, extent and size of primary tumor (p = 0.04), as well as its histological type (p = 0.003) were highly prognostic. Sedlis criteria were prognostic within FIGO 2018 IB patients (p = 0.04).

CONCLUSIONS

Incorporation of cross-sectional imaging increases prognostic precision, as suggested by the FIGO 2018 guidelines. The 2018 FIGO IIIC stage could be refined by including the size and extent of primary tumor and histological type. The FIGO IB risk prediction could be improved by applying MRI-assessed tumor size and stromal invasion.

MRI-based radiomic signatures for pretreatment prognostication in cervical cancer

BACKGROUND

Accurate pretherapeutic prognostication is important for tailoring treatment in cervical cancer (CC).

PURPOSE

To investigate whether pretreatment MRI-based radiomic signatures predict disease-specific survival (DSS) in CC.

STUDY TYPE

Retrospective.

POPULATION

CC patients (n = 133) allocated into training(T) (nT  = 89)/validation(V) (nV  = 44) cohorts.

FIELD STRENGTH/SEQUENCE

T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) at 1.5T or 3.0T.

ASSESSMENT

Radiomic features from segmented tumors were extracted from T2WI and DWI (high b-value DWI and apparent diffusion coefficient (ADC) maps).

STATISTICAL TESTS

Radiomic signatures for prediction of DSS from T2WI (T2rad ) and T2WI with DWI (T2 + DWIrad ) were constructed by least absolute shrinkage and selection operator (LASSO) Cox regression. Area under time-dependent receiver operating characteristics curves (AUC) were used to evaluate and compare the prognostic performance of the radiomic signatures, MRI-derived maximum tumor size ≤/> 4 cm (MAXsize ), and 2018 International Federation of Gynecology and Obstetrics (FIGO) stage (I-II/III-IV). Survival was analyzed using Cox model estimating hazard ratios (HR) and Kaplan-Meier method with log-rank tests.

RESULTS

The radiomic signatures T2rad and T2 + DWIrad yielded AUCT /AUCV of 0.80/0.62 and 0.81/0.75, respectively, for predicting 5-year DSS. Both signatures yielded better or equal prognostic performance to that of MAXsize (AUCT /AUCV : 0.69/0.65) and FIGO (AUCT /AUCV : 0.77/0.64) and were significant predictors of DSS after adjusting for FIGO (HRT /HRV for T2rad : 4.0/2.5 and T2 + DWIrad : 4.8/2.1). Adding T2rad and T2 + DWIrad to FIGO significantly improved DSS prediction compared to FIGO alone in cohort(T) (AUCT 0.86 and 0.88 vs. 0.77), and FIGO with T2 + DWIrad tended to the same in cohort(V) (AUCV 0.75 vs. 0.64, p = 0.07). High radiomic score for T2 + DWIrad was significantly associated with reduced DSS in both cohorts.

DATA CONCLUSION

Radiomic signatures from T2WI and T2WI with DWI may provide added value for pretreatment risk assessment and for guiding tailored treatment strategies in CC.

Visceral fat percentage for prediction of outcome in uterine cervical cancer

OBJECTIVE

The prognostic role of adiposity in uterine cervical cancer (CC) is largely unknown. Abdominal fat distribution may better reflect obesity than body mass index. This study aims to describe computed tomography (CT)-assessed abdominal fat distribution in relation to clinicopathologic characteristics, survival, and tumor gene expression in CC.

METHODS

The study included 316 CC patients diagnosed during 2004-2017 who had pre-treatment abdominal CT. CT-based 3D segmentation of total-, subcutaneous- and visceral abdominal fat volumes (TAV, SAV and VAV) allowed for calculation of visceral fat percentage (VAV% = VAV/TAV). Liver density (LD) and waist circumference (at L3/L4-level) were also measured. Associations between CT-derived adiposity markers, clinicopathologic characteristics and disease-specific survival (DSS) were explored. Gene set enrichment of primary tumors were examined in relation to fat distribution in a subset of 108 CC patients.

RESULTS

High TAV, VAV and VAV% and low LD were associated with higher age (≥44 yrs.; p ≤ 0.017) and high International Federation of Gynecology and Obstetrics (FIGO) (2018) stage (p ≤ 0.01). High VAV% was the only CT-marker predicting high-grade histology (p = 0.028), large tumor size (p = 0.016) and poor DSS (HR 1.07, p < 0.001). Patients with high VAV% had CC tumors that exhibited increased inflammatory signaling (false discovery rate [FDR] < 5%).

CONCLUSIONS

High VAV% is associated with high-risk clinical features and predicts reduced DSS in CC patients. Furthermore, patients with high VAV% had upregulated inflammatory tumor signaling, suggesting that the metabolic environment induced by visceral adiposity contributes to tumor progression in CC.

Single-cell profiling of low-stage endometrial cancers identifies low epithelial vimentin expression as a marker of recurrent disease

BACKGROUND

Identification of aggressive low-stage endometrial cancers is challenging. So far, studies have failed to pinpoint robust features or biomarkers associated with risk of recurrence for these patients.

METHODS

Imaging mass cytometry was used to examine single-cell expression of 23 proteins in 36 primary FIGO IB endometrial cancers, of which 17 recurred. Single-cell information was extracted for each tumor and unsupervised clustering was used to identify cellular phenotypes. Distinct phenotypes and cellular neighborhoods were compared in relation to recurrence. Cellular differences were validated in a separate gene expression dataset and the TCGA EC dataset. Vimentin protein expression was evaluated by IHC in pre-operative samples from 518 patients to validate its robustness as a prognostic marker.

FINDINGS

The abundance of epithelial, immune or stromal cell types did not associate with recurrence. Clustering of patients based on tumor single cell marker expression revealed distinct patient clusters associated with outcome. A cell population neighboring CD8+ T cells, defined by vimentin, ER, and PR expressing epithelial cells, was more prevalent in non-recurrent tumors. Importantly, lower epithelial vimentin expression and lower gene expression of VIM associated with worse recurrence-free survival. Loss and low expression of vimentin was validated by IHC as a robust marker for recurrence in FIGO I stage disease and predicted poor prognosis also when including all patients and in endometrioid patients only.

INTERPRETATION

This study reveals distinct characteristics in low-stage tumors and points to vimentin as a clinically relevant marker that may aid in identifying a here to unidentified subgroup of high-risk patients.

FUNDING

A full list of funding that contributed to this study can be found in the Acknowledgements section.

Molecular and phenotypic characteristics influencing the degree of cytoreduction in high-grade serous ovarian carcinomas

BACKGROUND

High-grade serous ovarian carcinoma (HGSOC) is the deadliest ovarian cancer subtype, and survival relates to initial cytoreductive surgical treatment. The existing tools for surgical outcome prediction remain inadequate for anticipating the outcomes of the complex relationship between tumour biology, clinical phenotypes, co-morbidity and surgical skills. In this genotype-phenotype association study, we combine phenotypic markers with targeted DNA sequencing to discover novel biomarkers to guide the surgical management of primary HGSOC.

METHODS

Primary tumour tissue samples (n = 97) and matched blood from a phenotypically well-characterised treatment-naïve HGSOC patient cohort were analysed by targeted massive parallel DNA sequencing (next generation sequencing [NGS]) of a panel of 360 cancer-related genes. Association analyses were performed on phenotypic traits related to complete cytoreductive surgery, while logistic regression analysis was applied for the predictive model.

RESULTS

The positive influence of complete cytoreductive surgery (R0) on overall survival was confirmed (p = 0.003). Before surgery, low volumes of ascitic fluid, lower CA125 levels, higher platelet counts and relatively lower clinical stage at diagnosis were all indicators, alone and combined, for complete cytoreduction (R0). Mutations in either the chromatin remodelling SWI_SNF (p = 0.036) pathway or the histone H3K4 methylation pathway (p = 0.034) correlated with R0. The R0 group also demonstrated higher tumour mutational burden levels (p = 0.028). A predictive model was developed by combining two phenotypes and the mutational status of five genes and one genetic pathway, enabling the prediction of surgical outcomes in 87.6% of the cases in this cohort.

CONCLUSION

Inclusion of molecular biomarkers adds value to the pre-operative stratification of HGSOC patients. A potential preoperative risk stratification model combining phenotypic traits and single-gene mutational status is suggested, but the set-up needs to be validated in larger cohorts.

Preoperative CA125 Significantly Improves Risk Stratification in High-Grade Endometrial Cancer

Patients with high-grade endometrial carcinoma (EC) have an increased risk of tumor spread and lymph node metastasis (LNM). Preoperative imaging and CA125 can be used in work-up. As data on cancer antigen 125 (CA125) in high-grade EC are limited, we aimed to study primarily the predictive value of CA125, and secondarily the contributive value of computed tomography (CT) for advanced stage and LNM. Patients with high-grade EC (n = 333) and available preoperative CA125 were included retrospectively. The association of CA125 and CT findings with LNM was analyzed by logistic regression. Elevated CA125 ((>35 U/mL), (35.2% (68/193)) was significantly associated with stage III-IV disease (60.3% (41/68)) compared with normal CA125 (20.8% (26/125), [p < 0.001]), and with reduced disease-specific-(DSS) (p < 0.001) and overall survival (OS) (p < 0.001). The overall accuracy of predicting LNM by CT resulted in an area under the curve (AUC) of 0.623 (p < 0.001) independent of CA125. Stratification by CA125 resulted in an AUC of 0.484 (normal), and 0.660 (elevated). In multivariate analysis elevated CA125, non-endometrioid histology, pathological deep myometrial invasion ≥50%, and cervical involvement were significant predictors of LNM, whereas suspected LNM on CT was not. This shows that elevated CA125 is a relevant independent predictor of advanced stage and outcome specifically in high-grade EC.

PIK3CA mutations and their impact on survival outcomes of patients with endometrial cancer: A systematic review and meta-analysis

Several studies have highlighted the frequent alterations of the PI3K pathway in endometrial cancer leading to increased signaling activation with potential for targeted treatment. The objective of this meta-study was to evaluate how PIK3CA exon 9/20 mutations affect survival in endometrial cancer patients, based on available literature. Topic-based search strategies were applied to databases including CENTRAL, MEDLINE, Embase, Web of Science and COSMIC. All studies assessing the impact of mutations in exon 9 and exon 20 of PIK3CA on survival rates of endometrial cancer patients were selected for inclusion. Statistical meta-analysis was performed with the 'meta' package in RStudio. Overall, 7 of 612 screened articles were included in the present study, comprising 1098 women with endometrial cancer. Meta-analysis revealed a tendency of impaired survival for patients with PIK3CA exon 9 and/or exon 20 mutations (RR 1.28; 95% CI 0.84, 1.94; p = 0.25). This tendency was consistent in subgroup analyses stratified by histologic type or -grade, with the most prominent effect in low-grade endometrial cancers (RR 2.04; 95% CI 0.90, 4.62; p = 0.09). In summary, these results suggest that PIK3CA mutations negatively influence survival outcomes of patients with endometrial cancer, including those with low-grade tumors.

Mismatch repair markers in preoperative and operative endometrial cancer samples; expression concordance and prognostic value

BACKGROUND

The endometrial cancer mismatch repair (MMR) deficient subgroup is defined by loss of MSH6, MSH2, PMS2 or MLH1. We compare MMR status in paired preoperative and operative samples and investigate the prognostic impact of differential MMR protein expression levels.

METHODS

Tumour lesions from 1058 endometrial cancer patients were immunohistochemically stained for MSH6, MSH2, PMS2 and MLH1. MMR protein expression was evaluated as loss or intact to determine MMR status, or by staining index to evaluate the prognostic potential of differential expression. Gene expression data from a local (n = 235) and the TCGA (n = 524) endometrial cancer cohorts was used for validation.

RESULTS

We identified a substantial agreement in MMR status between paired curettage and hysterectomy samples. Individual high expression of all four MMR markers associated with non-endometrioid subtype, and high MSH6 or MSH2 strongly associated with several aggressive disease characteristics including high tumour grade and FIGO stage, and for MSH6, with lymph node metastasis. In multivariate Cox analysis, MSH6 remained an independent prognostic marker, also within the endometrioid low-grade subgroup (P < 0.001).

CONCLUSION

We demonstrate that in addition to determine MMR status, MMR protein expression levels, particularly MSH6, may add prognostic information in endometrial cancer.

APOBEC3A /B deletion polymorphism and endometrial cancer risk

BACKGROUND

A common 30 kb deletion affecting the APOBEC3A and APOBEC3B genes has been linked to increased APOBEC activity and APOBEC-related mutational signatures in human cancers. The role of this deletion as a cancer risk factor remains controversial.

MATERIALS AND METHODS

We genotyped the APOBEC3A/B deletion in a sample of 1,470 Norwegian endometrial cancer cases and compared to 1,918 healthy controls. For assessment across Caucasian populations, we mined genotypes of the SNP rs12628403, which is in strong linkage disequilibrium with the deletion, in a GWAS dataset of 4,274 cases and 18,125 healthy controls, through the ECAC consortium.

RESULTS

We found the APOBEC3A/B deletion variant to be significantly associated with reduced risk of endometrial cancer among Norwegian women (OR = 0.75; 95% CI = 0.62-0.91; p = 0.003; dominant model). Similar results were found in the subgroup of endometrioid endometrial cancer (OR = 0.64; 95% CI = 0.51-0.79; p = 3.6 × 10^-5 ; dominant model). The observed risk reduction was particularly strong among individuals in the range of 50-60 years of age (OR = 0.51; 95% CI = 0.33-0.78; p = 0.002; dominant model). In the different populations included in the ECAC dataset, the ORs varied from 0.85 to 1.05. Although five out of six populations revealed ORs <1.0, the overall estimate was nonsignificant and, as such, did not formally validate the findings in the Norwegian cohort.

CONCLUSION

The APOBEC3A/B deletion polymorphism is associated with a decreased risk of endometrial cancer in the Norwegian population.

Integrated analysis of cervical squamous cell carcinoma cohorts from three continents reveals conserved subtypes of prognostic significance

Human papillomavirus (HPV)-associated cervical cancer is a leading cause of cancer deaths in women. Here we present an integrated multi-omic analysis of 643 cervical squamous cell carcinomas (CSCC, the most common histological variant of cervical cancer), representing patient populations from the USA, Europe and Sub-Saharan Africa and identify two CSCC subtypes (C1 and C2) with differing prognosis. C1 and C2 tumours can be driven by either of the two most common HPV types in cervical cancer (16 and 18) and while HPV16 and HPV18 are overrepresented among C1 and C2 tumours respectively, the prognostic difference between groups is not due to HPV type. C2 tumours, which comprise approximately 20% of CSCCs across these cohorts, display distinct genomic alterations, including loss or mutation of the STK11 tumour suppressor gene, increased expression of several immune checkpoint genes and differences in the tumour immune microenvironment that may explain the shorter survival associated with this group. In conclusion, we identify two therapy-relevant CSCC subtypes that share the same defining characteristics across three geographically diverse cohorts.

Human papillomavirus (HPV) is a known cause of cervical cancer. Here, the authors perform a multi-omic analysis using published cervical squamous cell carcinoma cohorts from the USA, Europe, and SubSaharan Africa and identify two cervical squamous cell carcinoma subtypes that display prognostic differences.

What MRI-based tumor size measurement is best for predicting long-term survival in uterine cervical cancer?

Background

Tumor size assessment by MRI is central for staging uterine cervical cancer. However, the optimal role of MRI-derived tumor measurements for prognostication is still unclear.

Material and methods

This retrospective cohort study included 416 women (median age: 43 years) diagnosed with cervical cancer during 2002–2017 who underwent pretreatment pelvic MRI. The MRIs were independently read by three radiologists, measuring maximum tumor diameters in three orthogonal planes and maximum diameter irrespective of plane (MAX_imaging). Inter-reader agreement for tumor size measurements was assessed by intraclass correlation coefficients (ICCs). Size was analyzed in relation to age, International Federation of Gynecology and Obstetrics (FIGO) (2018) stage, histopathological markers, and disease-specific survival using Kaplan–Meier-, Cox regression-, and time-dependent receiver operating characteristics (tdROC) analyses.

Results

All MRI tumor size variables (cm) yielded high areas under the tdROC curves (AUCs) for predicting survival (AUC 0.81–0.84) at 5 years after diagnosis and predicted outcome (hazard ratios [HRs] of 1.42–1.76, p < 0.001 for all). Only MAX_imaging independently predicted survival (HR = 1.51, p = 0.03) in the model including all size variables. The optimal cutoff for maximum tumor diameter (≥ 4.0 cm) yielded sensitivity (specificity) of 83% (73%) for predicting disease-specific death after 5 years. Inter-reader agreement for MRI-based primary tumor size measurements was excellent, with ICCs of 0.83–0.85.

Conclusion

Among all MRI-derived tumor size measurements, MAX_imaging was the only independent predictor of survival. MAX_imaging ≥ 4.0 cm represents the optimal cutoff for predicting long-term disease-specific survival in cervical cancer. Inter-reader agreement for MRI-based tumor size measurements was excellent.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13244-022-01239-y.

Abstract 513: Radiomic profiles revealing targets for therapy in cervical cancer

Magnetic resonance imaging (MRI) has emerged as an important part of the diagnostic work-up in cervical cancer, with tumor volume and extent as important prognosticators. MRI radiomic tumor features may aid in prognostication and tailoring of treatment in cervical cancer. We extracted whole-volume radiomic texture features from 124 manually segmented tumors and performed unsupervised clustering yielding two distinct clusters. Overlapping clinicopathologic, genomic (whole exome sequencing, n=61), transcriptomic (L1000 arrays, n= 65) and molecular biomarker (n=82) data were applied to characterize the clusters. Independent of tumor size parameters, patients in cluster II had significantly reduced disease-specific survival as compared to those in cluster I (p&gt;0.001), also within squamous cell carcinomas (n=96, p&lt;0.001). Cluster II associated with high age (p=0.02), high FIGO-2009 stage (p&lt;0.001), high BMI (p=0.03) and PR negative tumors (p=0.004). Distinct mutational and copy-number profiles were detected for the two clusters. By gene set enrichment analyses, gene sets associated to immune activation were enriched in cluster I tumors, whilst gene sets associated with oxidative phosphorylation and epithelial to mesenchymal transition associated to cluster II tumors. This study links radiomic signatures to distinct genomic profiles that may potentially aid in prognostication and tailoring of treatments in cervical cancer patients.

Citation Format: Mari Kyllesø Halle, Erlend Hodneland, Erling Hoivik, Kari Wagner-Larsen, Njål G. Lura, Julie Dybvik, David Forsse, Bjørn I. Bertelsen, Camilla Krakstad, Ingfrid S. Haldorsen, Olivera Bozickovic, Kathrine Woie. Radiomic profiles revealing targets for therapy in cervical cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 513.

Abstract 3879: High dimensional analysis of tumor microenvironment and heterogeneity in FIGO IB endometrial carcinomas using imaging mass cytometry

Patients with localized endometrial carcinomas (FIGO IA and IB) have a 5-year relative survival rate of &gt; 90%. Still, some patients with an expected good prognosis experience recurrence of disease which dramatically reduces survival rates. Currently, we lack the knowledge to predict which patients will get recurrence. We used Imaging Mass Cytometry to examine 27 proteins in tissue microarrays of 36 primary FIGO IB endometrial carcinomas, of which 17 later recurred. High dimensional images were segmented to extract single-cell information for each tumor. Distinct epithelial-, stromal- and immune cell types of the tumor microenvironment were identified and phenotyped, using protein expression intensities and unsupervised cell clustering. Neighboring cells of CD8+ cells were extracted and phenotyped. In non-recurrent tumors, more cytotoxic T cells were identified adjacent to two epithelial cell populations characterized by high vimentin and progesterone receptor expression (p &lt; 0.01 and p = 0.02). Tumors that were enriched for vimentin showed significantly better recurrence-free survival than tumors with low vimentin or high alpha-smooth muscle actin (a-SMA) signal (p = 0.026). This study reveals distinct characteristics in the microenvironment of low stage tumors that may aid in identifying high-risk patients. Further, the study provides new insight on the pathogenic processes involved in tumor progression of endometrial cancer.

Citation Format: Hilde Eide Lien, Hege Fredriksen Berg, Erling Andre Hoivik, Jone Trovik, Ingfrid Salvesen Haldorsen, Lars Andreas Akslen, Camilla Krakstad. High dimensional analysis of tumor microenvironment and heterogeneity in FIGO IB endometrial carcinomas using imaging mass cytometry [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3879.

MRI-assessed tumor-free distance to serosa predicts deep myometrial invasion and poor outcome in endometrial cancer

OBJECTIVES

To explore the diagnostic accuracy of preoperative magnetic resonance imaging (MRI)-derived tumor measurements for the prediction of histopathological deep (≥ 50%) myometrial invasion (pDMI) and prognostication in endometrial cancer (EC).

METHODS

Preoperative pelvic MRI of 357 included patients with histologically confirmed EC were read independently by three radiologists blinded to clinical information. The radiologists recorded imaging findings (T1 post-contrast sequence) suggesting deep (≥ 50%) myometrial invasion (iDMI) and measured anteroposterior tumor diameter (APD), depth of myometrial tumor invasion (DOI) and tumor-free distance to serosa (iTFD). Receiver operating characteristic (ROC) curves for the prediction of pDMI were plotted for the different MRI measurements. The predictive and prognostic value of the MRI measurements was analyzed using logistic regression and Cox proportional hazard model.

RESULTS

iTFD yielded highest area under the ROC curve (AUC) for the prediction of pDMI with an AUC of 0.82, whereas DOI, APD and iDMI yielded AUCs of 0.74, 0.81 and 0.74, respectively. Multivariate analysis for predicting pDMI yielded highest predictive value of iTFD <  6 mm with OR of 5.8 (p < 0.001) and lower figures for DOI ≥ 5 mm (OR = 2.8, p = 0.01), APD ≥ 17 mm (OR = 2.8, p < 0.001) and iDMI (OR = 1.1, p = 0.82). Patients with iTFD < 6 mm also had significantly reduced progression-free survival with hazard ratio of 2.4 (p < 0.001).

CONCLUSION

For predicting pDMI, iTFD yielded best diagnostic performance and iTFD < 6 mm outperformed other cutoff-based imaging markers and conventional subjective assessment of deep myometrial invasion (iDMI) for diagnosing pDMI. Thus, iTFD at MRI represents a promising preoperative imaging biomarker that may aid in predicting pDMI and high-risk disease in EC.

Interobserver agreement and prognostic impact for MRI-based 2018 FIGO staging parameters in uterine cervical cancer

OBJECTIVES

To evaluate the interobserver agreement for MRI-based 2018 International Federation of Gynecology and Obstetrics (FIGO) staging parameters in patients with cervical cancer and assess the prognostic value of these MRI parameters in relation to other clinicopathological markers.

METHODS

This retrospective study included 416 women with histologically confirmed cervical cancer who underwent pretreatment pelvic MRI from May 2002 to December 2017. Three radiologists independently recorded MRI-derived staging parameters incorporated in the 2018 FIGO staging system. Kappa coefficients (κ) for interobserver agreement were calculated. The predictive and prognostic values of the MRI parameters were explored using ROC analyses and Kaplan-Meier with log-rank tests, and analyzed in relation to clinicopathological patient characteristics.

RESULTS

Overall agreement was substantial for the staging parameters: tumor size > 2 cm (κ = 0.80), tumor size > 4 cm (κ = 0.76), tumor size categories (≤ 2 cm; > 2 and ≤ 4 cm; > 4 cm) (κ = 0.78), parametrial invasion (κ = 0.63), vaginal invasion (κ = 0.61), and enlarged lymph nodes (κ = 0.63). Higher MRI-derived tumor size category (≤ 2 cm; > 2 and ≤ 4 cm; > 4 cm) was associated with a stepwise reduction in survival (p ≤ 0.001 for all). Tumor size > 4 cm and parametrial invasion at MRI were associated with aggressive clinicopathological features, and the incorporation of these MRI-based staging parameters improved risk stratification when compared to corresponding clinical assessments alone.

CONCLUSION

The interobserver agreement for central MRI-derived 2018 FIGO staging parameters was substantial. MRI improved the identification of patients with aggressive clinicopathological features and poor survival, demonstrating the potential impact of MRI enabling better prognostication and treatment tailoring in cervical cancer.

KEY POINTS

• The overall interobserver agreement was substantial (κ values 0.61-0.80) for central MRI staging parameters in the 2018 FIGO system. • Higher MRI-derived tumor size category was linked to a stepwise reduction in survival (p ≤ 0.001 for all). • MRI-derived tumor size > 4 cm and parametrial invasion were associated with aggressive clinicopathological features, and the incorporation of these MRI-derived staging parameters improved risk stratification when compared to clinical assessments alone.

Longitudinal effects of adjuvant chemotherapy and lymph node staging on patient-reported outcomes in endometrial cancer survivors: a prospective cohort study

BACKGROUND

Most patients with endometrial cancer with localized disease are effectively treated and survive for a long time. The primary treatment is hysterectomy, to which surgical staging procedures may be added to assess the need for adjuvant therapy. Longitudinal data on patient-reported outcomes comparing different levels of primary treatment are lacking, especially when adjuvant radiotherapy is omitted.

OBJECTIVE

We assessed the impact of lymphadenectomy and adjuvant chemotherapy on patient-reported symptoms, function, and quality of life. We hypothesized that these treatment modalities would substantially affect patient-reported outcomes at follow-up.

STUDY DESIGN

We prospectively included patients with endometrial cancer enrolled in the ongoing MoMaTEC2 study (ClinicalTrials.gov Identifier: NCT02543710). Patients were asked to complete the patient-reported outcome questionnaires European Organization for Research and Treatment of Cancer Quality of Life Questionnaire C30 and European Organization for Research and Treatment of Cancer Quality of Life Questionnaire EN24 preoperatively and at 1 and 2 years of follow-up. Functional domains and symptoms were analyzed for the whole cohort and by treatment received. To assess the effect of the individual treatment modifications, we used mixed regression models.

RESULTS

Baseline data were available for 448 patients. Of these patients, 339 and 219 had reached 1-year follow-up and 2-year follow-up, respectively. Treatment included hysterectomy (plus bilateral salpingo-oophorectomy) alone (n=177), hysterectomy and lymph node staging without adjuvant therapy (n=133), or adjuvant chemotherapy irrespective of staging procedure (n=138). Overall, patients reported improved global health status and quality of life (+9 units; P<.001), increased emotional and social functioning, and increased sexual interest and activity (P<.001 for all) from baseline to year 1, and these outcomes remained stable at year 2. Means of functional scales and quality of life were similar to age- and sex-weighted reference cohorts. Mean tingling and numbness and lymphedema increased after treatment. The group who received adjuvant chemotherapy had a larger mean reduction in physical functioning (-6 vs +2; P=.002) at year 1, more neuropathy (+30 vs +5; P<.001; year 1) at years 1 and 2, and more lymphedema at year 1 (+11 vs +2; P=.007) than the group treated with hysterectomy and salpingo-oophorectomy only. In patients not receiving adjuvant chemotherapy, patient-reported outcomes were similar regardless of lymph node staging procedures. Adjuvant chemotherapy independently increased fatigue, lymphedema, and neuropathy in mixed regression models.

CONCLUSION

Patients with endometrial cancer receiving adjuvant chemotherapy reported significantly reduced functioning and more symptoms up to 2 years after treatment. For patients treated by surgery alone, surgical staging did not seem to affect the quality of life or symptoms to a measurable degree at follow-up. Therefore, subjecting patients to lymph node removal to tailor adjuvant therapy seems justified from the patient's viewpoint; however, efforts should increase to find alternatives to traditional chemotherapy.

High-Grade Cervical Intraepithelial Neoplasia (CIN) Associates with Increased Proliferation and Attenuated Immune Signaling

Implementation of high-risk human papilloma virus (HPV) screening and the increasing proportion of HPV vaccinated women in the screening program will reduce the percentage of HPV positive women with oncogenic potential. In search of more specific markers to identify women with high risk of cancer development, we used RNA sequencing to compare the transcriptomic immune-profile of 13 lesions with cervical intraepithelial neoplasia grade 3 (CIN3) or adenocarcinoma in situ (AIS) and 14 normal biopsies from women with detected HPV infections. In CIN3/AIS lesions as compared to normal tissue, 27 differential expressed genes were identified. Transcriptomic analysis revealed significantly higher expression of a number of genes related to proliferation, (CDKN2A, MELK, CDK1, MKI67, CCNB2, BUB1, FOXM1, CDKN3), but significantly lower expression of genes related to a favorable immune response (NCAM1, ARG1, CD160, IL18, CX3CL1). Compared to the RNA sequencing results, good correlation was achieved with relative quantitative PCR analysis for NCAM1 and CDKN2A. Quantification of NCAM1 positive cells with immunohistochemistry showed epithelial reduction of NCAM1 in CIN3/AIS lesions. In conclusion, NCAM1 and CDKN2A are two promising candidates to distinguish whether women are at high risk of developing cervical cancer and in need of frequent follow-up.

A radiogenomics application for prognostic profiling of endometrial cancer

Prognostication is critical for accurate diagnosis and tailored treatment in endometrial cancer (EC). We employed radiogenomics to integrate preoperative magnetic resonance imaging (MRI, n = 487 patients) with histologic-, transcriptomic- and molecular biomarkers (n = 550 patients) aiming to identify aggressive tumor features in a study including 866 EC patients. Whole-volume tumor radiomic profiling from manually (radiologists) segmented tumors (n = 138 patients) yielded clusters identifying patients with high-risk histological features and poor survival. Radiomic profiling by a fully automated machine learning (ML)-based tumor segmentation algorithm (n = 336 patients) reproduced the same radiomic prognostic groups. From these radiomic risk-groups, an 11-gene high-risk signature was defined, and its prognostic role was reproduced in orthologous validation cohorts (n = 554 patients) and aligned with The Cancer Genome Atlas (TCGA) molecular class with poor survival (copy-number-high/p53-altered). We conclude that MRI-based integrated radiogenomics profiling provides refined tumor characterization that may aid in prognostication and guide future treatment strategies in EC.

Risk Stratification of Endometrial Cancer Patients: FIGO Stage, Biomarkers and Molecular Classification

Endometrial cancer (EC) is the most common gynaecologic malignancy in developed countries. The main challenge in EC management is to correctly estimate the risk of metastases at diagnosis and the risk to develop recurrences in the future. Risk stratification determines the need for surgical staging and adjuvant treatment. Detection of occult, microscopic metastases upstages patients, provides important prognostic information and guides adjuvant treatment. The molecular classification subdivides EC into four prognostic subgroups: POLE ultramutated; mismatch repair deficient (MMRd); nonspecific molecular profile (NSMP); and TP53 mutated (p53abn). How surgical staging should be adjusted based on preoperative molecular profiling is currently unknown. Moreover, little is known whether and how other known prognostic biomarkers affect prognosis prediction independent of or in addition to these molecular subgroups. This review summarizes the factors incorporated in surgical staging (i.e., peritoneal washing, lymph node dissection, omentectomy and peritoneal biopsies), and its impact on prognosis and adjuvant treatment decisions in an era of molecular classification of EC. Moreover, the relation between FIGO stage and molecular classification is evaluated including the current gaps in knowledge and future perspectives.

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.

PIK3CA Amplification Associates with Aggressive Phenotype but Not Markers of AKT-MTOR Signaling in Endometrial Carcinoma

PURPOSE

Amplification of PIK3CA, encoding the PI3K catalytic subunit alpha, is common in uterine corpus endometrial carcinoma (UCEC) and linked to an aggressive phenotype. However, it is unclear whether PIK3CA amplification acts via PI3K activation. We investigated the association between PIK3CA amplification, markers of PI3K activity, and prognosis in a large cohort of UCEC specimens.

EXPERIMENTAL DESIGN

UCECs from 591 clinically annotated patients including 83 tumors with matching metastasis (n = 188) were analyzed by FISH to determine PIK3CA copy-number status. These data were integrated with mRNA and protein expression and clinicopathologic data. Results were verified in The Cancer Genome Atlas dataset.

RESULTS

PIK3CA amplifications were associated with disease-specific mortality and with other markers of aggressive disease. PIK3CA amplifications were also associated with other amplifications characteristic of the serous-like somatic copy-number alteration (SCNA)-high subgroup of UCEC. Tumors with PIK3CA amplification also demonstrated an increase in phospho-p70S6K but had decreased levels of activated phospho-AKT1-3 as assessed by Reverse Phase Protein Arrays and an mRNA signature of MTOR inhibition.

CONCLUSIONS

PIK3CA amplification is a strong prognostic marker and a potential marker for the aggressive SCNA-high subgroup of UCEC. Although PIK3CA amplification associates with some surrogate measures of increased PI3K activity, markers for AKT1-3 and MTOR signaling are decreased, suggesting that this signaling is not a predominant pathway to promote cancer growth of aggressive serous-like UCEC. Moreover, these associations may reflect features of the SCNA-high subgroup of UCEC rather than effects of PIK3CA amplification itself.