Expression patterns of mismatch repair proteins in cervical cancer uncover independent prognostic value of MSH-2.

OBJECTIVE: Although early-detected cervical cancer is associated with good survival, the prognosis for late-stage disease is poor and treatment options are sparse. Mismatch repair deficiency (MMR-D) has surfaced as a predictor of prognosis and response to immune checkpoint inhibitor(s) in several cancer types, but its value in cervical cancer remains unclear. This study aimed to define the prevalence of MMR-D in cervical cancer and assess the prognostic value of MMR protein expression. METHODS: Expression of the MMR proteins MLH-1, PMS-2, MSH-2, and MSH-6 was investigated by immunohistochemical staining in a prospectively collected cervical cancer cohort (n=508) with corresponding clinicopathological and follow-up data. Sections were scored as either loss or intact expression to define MMR-D, and by a staining index, based on staining intensity and area, evaluating the prognostic potential. RNA and whole exome sequencing data were available for 72 and 75 of the patients and were used for gene set enrichment and mutational analyses, respectively. RESULTS: Five (1%) tumors were MMR-deficient, three of which were of neuroendocrine histology. MMR status did not predict survival (HR 1.93, p=0.17). MSH-2 low (n=48) was associated with poor survival (HR 1.94, p=0.02), also when adjusting for tumor stage, tumor type, and patient age (HR 2.06, p=0.013). MSH-2 low tumors had higher tumor mutational burden (p=0.003) and higher frequency of (frameshift) mutations in the double-strand break repair gene RAD50 (p<0.01). CONCLUSION: MMR-D is rare in cervical cancer, yet low MSH-2 expression is an independent predictor of poor survival.

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).

Age-related phenotypes in breast cancer: A population-based study.

Breast cancer in young (<40 years) is associated with a higher frequency of aggressive tumor types and poor prognosis. It remains unclear if there is an underlying age-related biology that contributes to the unfavorable outcome. We aim to investigate the relationship between age and breast cancer biology, with emphasis on proliferation. Clinico-pathologic information, immunohistochemical markers and follow-up data were obtained for all patients aged <50 (Bergen cohort-1; n = 355, not part of a breast screening program) and compared to previously obtained information on patients aged 50 to 69 years (Bergen cohort-2; n = 540), who participated in the Norwegian Breast Cancer Screening Program. Young breast cancer patients presented more aggressive tumor features such as hormone receptor negativity, HER2 positivity, lymph-node metastasis, the HER2-enriched and triple-negative subtypes and shorter survival. Age <40 was significantly associated with higher proliferation (by Ki67). Ki67 showed weaker prognostic value in young patients. We point to aggressive phenotypes and increased tumor cell proliferation in breast cancer of the young. Hence, tumors of young breast cancer patients may present unique biological features, also when accounting for screen/interval differences, that may open for new clinical opportunities, stratifying treatment by age.

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.

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.

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.

An MRI-Based Radiomic Prognostic Index Predicts Poor Outcome and Specific Genetic Alterations in Endometrial Cancer.

Integrative tumor characterization linking radiomic profiles to corresponding gene expression profiles has the potential to identify specific genetic alterations based on non-invasive radiomic profiling in cancer. The aim of this study was to develop and validate a radiomic prognostic index (RPI) based on preoperative magnetic resonance imaging (MRI) and assess possible associations between the RPI and gene expression profiles in endometrial cancer patients. Tumor texture features were extracted from preoperative 2D MRI in 177 endometrial cancer patients. The RPI was developed using least absolute shrinkage and selection operator (LASSO) Cox regression in a study cohort (n = 95) and validated in an MRI validation cohort (n = 82). Transcriptional alterations associated with the RPI were investigated in the study cohort. Potential prognostic markers were further explored for validation in an mRNA validation cohort (n = 161). The RPI included four tumor texture features, and a high RPI was significantly associated with poor disease-specific survival in both the study cohort (p < 0.001) and the MRI validation cohort (p = 0.030). The association between RPI and gene expression profiles revealed 46 significantly differentially expressed genes in patients with a high RPI versus a low RPI (p < 0.001). The most differentially expressed genes, COMP and DMBT1, were significantly associated with disease-specific survival in both the study cohort and the mRNA validation cohort. In conclusion, a high RPI score predicts poor outcome and is associated with specific gene expression profiles in endometrial cancer patients. The promising link between radiomic tumor profiles and molecular alterations may aid in developing refined prognostication and targeted treatment strategies in endometrial cancer.

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.

Erratum: Author Correction: Patient-derived organoids reflect the genetic profile of endometrial tumors and predict patient prognosis.

[This corrects the article DOI: 10.1038/s43856-021-00019-x.].

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.

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.

High degree of heterogeneity of PD-L1 and PD-1 from primary to metastatic endometrial cancer.

OBJECTIVE: PD-L1 and PD-1 are predictive markers for immunotherapy and increasingly relevant in endometrial cancer. The reported fraction of positive primary tumors has been inconsistent. We investigated the expression of PD-L1 and PD-1 in primary tumors, also stratified by MSI. As immunotherapy is foremost relevant for metastatic disease, PD-L1 and PD-1 expression was also assessed in corresponding metastatic lesions. METHODS: PD-L1 and PD-1 was investigated in a prospective, population based endometrial cancer cohort of 700 patients with corresponding metastatic lesions from 68 and 74 patients respectively. Fresh tissue was used for gene expression analysis. RESULTS: In primary tumors, PD-L1 and PD-1 are expressed in 59% and 63%, respectively, but with no impact on survival, nor when stratified for MSS and MSI. Expression patterns of PD-L1 and PD-1 are similar in MSI and MSS tumors. Available metastatic lesions show heterogeneous expression of PD-L1 and PD-1. In gene expression analysis several genes related to immunological activity, including CD274 (encoding for PD-L1), were upregulated in PD-1 positive tumors. CONCLUSION: PD-L1 and PD-1 are frequently expressed in endometrial cancer and expression patterns are similar across MSS and MSI tumors. Expression in corresponding metastatic lesions is discordant compared to primary tumors. These findings are in particular relevant for treatment decisions in advanced and recurrent disease.

Blood Metabolites Associate with Prognosis in Endometrial Cancer.

Endometrial cancer has a high prevalence among post-menopausal women in developed countries. We aimed to explore whether certain metabolic patterns could be related to the characteristics of aggressive disease and poorer survival among endometrial cancer patients in Western Norway. Patients with endometrial cancer with short survival (n = 20) were matched according to FIGO (International Federation of Gynecology and Obstetrics, 2009 criteria) stage, histology, and grade, with patients with long survival (n = 20). Plasma metabolites were measured on a multiplex system including 183 metabolites, which were subsequently determined using liquid chromatography-mass spectrometry. Partial least square discriminant analysis, together with hierarchical clustering, was used to identify patterns which distinguished short from long survival. A proposed signature of metabolites related to survival was suggested, and a multivariate receiver operating characteristic (ROC) analysis yielded an area under the curve (AUC) of 0.820-0.965 (p ≤ 0.001). Methionine sulfoxide seems to be particularly strongly associated with poor survival rates in these patients. In a subgroup with preoperative contrast-enhanced computed tomography data, selected metabolites correlated with the estimated abdominal fat distribution parameters. Metabolic signatures may predict prognosis and be promising supplements when evaluating phenotypes and exploring metabolic pathways related to the progression of endometrial cancer. In the future, this may serve as a useful tool in cancer management.

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.

Class I Phosphoinositide 3-Kinase PIK3CA/p110α and PIK3CB/p110ß Isoforms in Endometrial Cancer.

The phosphoinositide 3-kinase (PI3K) signalling pathway is highly dysregulated in cancer, leading to elevated PI3K signalling and altered cellular processes that contribute to tumour development. The pathway is normally orchestrated by class I PI3K enzymes and negatively regulated by the phosphatase and tensin homologue, PTEN. Endometrial carcinomas harbour frequent alterations in components of the pathway, including changes in gene copy number and mutations, in particular in the oncogene PIK3CA, the gene encoding the PI3K catalytic subunit p110α, and the tumour suppressor PTEN. PIK3CB, encoding the other ubiquitously expressed class I isoform p110ß, is less frequently altered but the few mutations identified to date are oncogenic. This isoform has received more research interest in recent years, particularly since PTEN-deficient tumours were found to be reliant on p110ß activity to sustain transformation. In this review, we describe the current understanding of the common and distinct biochemical properties of the p110α and p110ß isoforms, summarise their mutations and highlight how they are targeted in clinical trials in endometrial cancer.

Identification of highly connected and differentially expressed gene subnetworks in metastasizing endometrial cancer.

We have identified nine highly connected and differentially expressed gene subnetworks between aggressive primary tumors and metastatic lesions in endometrial carcinomas. We implemented a novel pipeline combining gene set and network approaches, which here allows integration of protein-protein interactions and gene expression data. The resulting subnetworks are significantly associated with disease progression across tumor stages from complex atypical hyperplasia, primary tumors to metastatic lesions. The nine subnetworks include genes related to metastasizing features such as epithelial-mesenchymal transition (EMT), hypoxia and cell proliferation. TCF4 and TWIST2 were found as central genes in the subnetwork related to EMT. Two of the identified subnetworks display statistically significant association to patient survival, which were further supported by an independent validation in the data from The Cancer Genome Atlas data collection. The first subnetwork contains genes related to cell proliferation and cell cycle, while the second contains genes involved in hypoxia such as HIF1A and EGLN3. Our findings provide a promising context to elucidate the biological mechanisms of metastasis, suggest potential prognostic markers and further identify therapeutic targets. The pipeline R source code is freely available, including permutation tests to assess statistical significance of the identified subnetworks.

Deletion of exchange proteins directly activated by cAMP (Epac) causes defects in hippocampal signaling in female mice.

Previous studies demonstrate essential roles for the exchange proteins directly activated by cAMP 1 and 2 (Epac1 and Epac2; here collectively referred to as Epac) in the brain. In the hippocampus, Epac contributes to the control of neuronal growth and differentiation and has been implicated in memory and learning as well as in anxiety and depression. In the present study we address the hypothesis that Epac affects hippocampal cellular responses to acute restraint stress. Stress causes activation of the hypothalamus-pituitary-adrenal (HPA)-axis, and glucocorticoid receptor (GR) signaling is essential for proper feedback regulation of the stress response, both in the brain and along the HPA axis. In the hippocampus, GR expression is regulated by cAMP and the brain enriched micro RNA miR-124. Epac has been associated with miR-124 expression in hippocampal neurons, but not in regulation of GR. We report that hippocampal expression of Epac1 and Epac2 increased in response to acute stress in female wild type mice. In female mice genetically deleted for Epac, nuclear translocation of GR in response to restraint stress was significantly delayed, and moreover, miR-124 expression was decreased in these mice. Male mice lacking Epac also showed abnormalities in miR-124 expression, but the phenotype was less profound than in females. Serum corticosterone levels were slightly altered immediately after stress in both male and female mice deleted for Epac. The presented data indicate that Epac1 and Epac2 are involved in controlling cellular responses to acute stress in the mouse hippocampus and provide novel insights into the underlying transcriptional and signaling networks. Interestingly, we observe sex specific differences when Epac is deleted. As the incidence and prevalence of stress-related diseases are higher in women than in men, the Epac knockout models might serve as genetic tools to further elucidate the cellular mechanisms underlying differences between male and female with regard to regulation of stress.

High visceral fat percentage is associated with poor outcome in endometrial cancer.

Despite evidence of increased endometrial cancer (EC) risk in obese women, the impact of obesity on clinical and histological phenotype is poorly understood. This study explored abdominal fat volumes and fat distribution quantified by computed tomography (CT), in relation to tumor characteristics and outcome. 227 EC patients with preoperative abdominal CT scans were included. Total abdominal fat volume (TAV), subcutaneous abdominal fat volume (SAV) and visceral abdominal fat volume (VAV) were quantified, and visceral fat percentage calculated (VAV%=[VAV/TAV]x100). Waist circumference (WC) and liver density (LD) were measured, and body mass index (BMI) calculated. Data for estrogen, progesterone and androgen receptor (ERα/PR/AR) expression by immunohistochemistry were available for 149 tumors, and global gene expression data for 105 tumors. High BMI, TAV, SAV, VAV and WC, and low LD, were associated with low grade endometrioid tumors and PR and AR positivity (all p≤0.03). High VAV% was associated with high age (p<0.001), aneuploidy (p=0.01) and independently predicted reduced disease-specific survival (HR 1.05, 95% CI 1.00-1.11, p=0.041). Tumors from patients with low VAV% showed enrichment of gene sets related to immune activation and inflammation. In conclusion, high VAV% independently predicts reduced EC survival. Tumors arising in patients with low VAV% show enrichment of immune and inflammation related gene sets, suggesting that the global metabolic setting may be important for tumor immune response.