Proteomic Biomarkers for the Detection of Endometrial Cancer

Identification and validation of serum metabolite biomarkers for endometrial cancer diagnosis

Endometrial cancer (EC) stands as the most prevalent gynecological tumor in women worldwide. Notably, differentiation diagnosis of abnormity detected by ultrasound findings (e.g., thickened endometrium or mass in the uterine cavity) is essential and remains challenging in clinical practice. Herein, we identified a metabolic biomarker panel for differentiation diagnosis of EC using machine learning of high-performance serum metabolic fingerprints (SMFs) and validated the biological function. We first recorded the high-performance SMFs of 191 EC and 204 Non-EC subjects via particle-enhanced laser desorption/ionization mass spectrometry (PELDI-MS). Then, we achieved an area-under-the-curve (AUC) of 0.957-0.968 for EC diagnosis through machine learning of high-performance SMFs, outperforming the clinical biomarker of cancer antigen 125 (CA-125, AUC of 0.610-0.684, p < 0.05). Finally, we identified a metabolic biomarker panel of glutamine, glucose, and cholesterol linoleate with an AUC of 0.901-0.902 and validated the biological function in vitro. Therefore, our work would facilitate the development of novel diagnostic biomarkers for EC in clinics.

Detection of endometrial cancer in cervico-vaginal fluid and blood plasma: leveraging proteomics and machine learning for biomarker discovery

BACKGROUND

The anatomical continuity between the uterine cavity and the lower genital tract allows for the exploitation of uterine-derived biomaterial in cervico-vaginal fluid for endometrial cancer detection based on non-invasive sampling methodologies. Plasma is an attractive biofluid for cancer detection due to its simplicity and ease of collection. In this biomarker discovery study, we aimed to identify proteomic signatures that accurately discriminate endometrial cancer from controls in cervico-vaginal fluid and blood plasma.

METHODS

Blood plasma and Delphi Screener-collected cervico-vaginal fluid samples were acquired from symptomatic post-menopausal women with (n = 53) and without (n = 65) endometrial cancer. Digitised proteomic maps were derived for each sample using sequential window acquisition of all theoretical mass spectra (SWATH-MS). Machine learning was employed to identify the most discriminatory proteins. The best diagnostic model was determined based on accuracy and model parsimony.

FINDINGS

A protein signature derived from cervico-vaginal fluid more accurately discriminated cancer from control samples than one derived from plasma. A 5-biomarker panel of cervico-vaginal fluid derived proteins (HPT, LG3BP, FGA, LY6D and IGHM) predicted endometrial cancer with an AUC of 0.95 (0.91-0.98), sensitivity of 91% (83%-98%), and specificity of 86% (78%-95%). By contrast, a 3-marker panel of plasma proteins (APOD, PSMA7 and HPT) predicted endometrial cancer with an AUC of 0.87 (0.81-0.93), sensitivity of 75% (64%-86%), and specificity of 84% (75%-93%). The parsimonious model AUC values for detection of stage I endometrial cancer in cervico-vaginal fluid and blood plasma were 0.92 (0.87-0.97) and 0.88 (0.82-0.95) respectively.

INTERPRETATION

Here, we leveraged the natural shed of endometrial tumours to potentially develop an innovative approach to endometrial cancer detection. We show proof of principle that endometrial cancers secrete unique protein signatures that can enable cancer detection via cervico-vaginal fluid assays. Confirmation in a larger independent cohort is warranted.

FUNDING

Cancer Research UK, Blood Cancer UK, National Institute for Health Research.

Enhancing intracellular mRNA precise imaging-guided photothermal therapy with a nucleic acid-based polydopamine nanoprobe

Despite significant advancements in cancer research, real-time monitoring and effective treatment of cancer through non-invasive techniques remain a challenge. Herein, a novel polydopamine (PDA) nucleic acid nanoprobe has been developed for imaging signal amplification of intracellular mRNA and precise photothermal therapy guidance in cancer cells. The PDA nucleic acid nanoprobe (PDA@DNA) is constructed by assembling an aptamer hairpin (H1) labeled with the Cy5 fluorophore and another nucleic acid recognition hairpin (H2) onto PDA nanoparticles (PDA NPs), which have exceptionally high fluorescence quenching ability and excellent photothermal conversion properties. The nanoprobe could facilitate cellular uptake of DNA molecules and their protection from nuclease degradation. Upon recognition and binding to the intracellular mRNA target, a catalytic hairpin assembly (CHA) reaction occurs. The stem of H1 unfolds upon binding, allowing the exposed H1 to hybridize with H2, forming a flat and sturdy DNA double-stranded structure that detaches from the surface of PDA NPs. At the same time, the target mRNA is displaced and engages in a new cyclic reaction, resulting in the recovery and significant amplification of Cy5 fluorescence. Using thymidine kinase1 (TK1) mRNA as a model mRNA, this nanoprobe enables the analysis of TK1 mRNA with a detection limit of 9.34 pM, which is at least two orders of magnitude lower than that of a non-amplifying imaging nucleic acid probe. Moreover, with its outstanding performance for in vitro detection, this nanoprobe excels in precisely imaging tumor cells. Through live-cell TK1 mRNA imaging, it can accurately distinguish between tumor cells and normal cells. Furthermore, when exposed to 808-nm laser irradiation, the nanoprobe fully harnesses exceptional photothermal conversion properties of PDA NPs. This results in a localized temperature increase within tumor cells, which ultimately triggers apoptosis in these tumor cells. The integration of PDA@DNA presents innovative prospects for tumor diagnosis and image-guided tumor therapy, offering the potential for high-precision diagnosis and treatment of tumors.

Proteomics: Unraveling the Cross Talk Between Innate Immunity and Disease Pathophysiology, Diagnostics, and Treatment Options

Inflammation is crucial in diseases, and proteins play a key role in the interplay between innate immunity and pathology. This review explores how proteomics helps understanding this relationship, focusing on diagnosis and treatment. We explore the dynamic innate response and the significance of proteomic techniques in deciphering the complex network of proteins involved in prevalent diseases, including infections, cancer, autoimmune and neurodegenerative disorders. Proteomics identifies key proteins in host-pathogen interactions, shedding light on infection mechanisms and inflammation. These discoveries hold promise for diagnostic tools, therapies, and vaccines. In cancer research, proteomics reveals innate signatures associated with tumor development, immune evasion, and therapeutic response. Additionally, proteomic analysis has unveiled autoantigens and dysregulation of the innate immune system in autoimmunity, offering opportunities for early diagnosis, disease monitoring, and new therapeutic targets. Moreover, proteomic analysis has identified altered protein expression patterns in neurodegenerative diseases like Alzheimer's and Parkinson's, providing insights into potential therapeutic strategies. Proteomics of the innate immune system provides a comprehensive understanding of disease mechanisms, identifies biomarkers, and enables effective interventions in various diseases. Despite still in its early stages, this approach holds great promise to revolutionize innate immunity research and significantly improve patient outcomes across a wide range of diseases.

Multiomic Approaches for Cancer Biomarker Discovery in Liquid Biopsies: Advances and Challenges

Cancer is a complex and heterogeneous disease that poses a significant threat to global health. Early diagnosis and treatment are critical for improving patient outcomes, and the use of liquid biopsies has emerged as a promising approach for cancer detection and monitoring. Traditionally, cancer diagnosis has relied on invasive tissue biopsies, the collection of which can prove challenging for patients and the results of which may not always provide accurate results due to tumor heterogeneity. Liquid biopsies have gained increasing attention as they provide a non-invasive and accessible source of cancer biomarkers, which can be used to diagnose cancer, monitor treatment response, and detect relapse. The integration of -omics technologies, such as proteomics, genomics, and metabolomics, has further enhanced the capabilities of liquid biopsies by introducing precision oncology and enabling the tailoring of treatment for individual patients based on their unique tumor biology. In this review, we will discuss the challenges and advances in the field of cancer liquid biopsies and the integration of -omics technologies for different types of liquid biopsies, including blood, tear, urine, sweat, saliva, and cerebrospinal fluid.

An ultrasound-based radiomics model for survival prediction in patients with endometrial cancer

PURPOSE

To establish a nomogram integrating radiomics features based on ultrasound images and clinical parameters for predicting the prognosis of patients with endometrial cancer (EC).

MATERIALS AND METHODS

A total of 175 eligible patients with ECs were enrolled in our study between January 2011 and April 2018. They were divided into a training cohort (n = 122) and a validation cohort (n = 53). Least absolute shrinkage and selection operator (LASSO) regression were applied for selection of key features, and a radiomics score (rad-score) was calculated. Patients were stratified into high risk and low-risk groups according to the rad-score. Univariate and multivariable COX regression analysis was used to select independent clinical parameters for disease-free survival (DFS). A combined model based on radiomics features and clinical parameters was ultimately established, and the performance was quantified with respect to discrimination and calibration.

RESULTS

Nine features were selected from 1130 features using LASSO regression in the training cohort, which yielded an area under the curve (AUC) of 0.823 and 0.792 to predict DFS in the training and validation cohorts, respectively. Patients with a higher rad-score were significantly associated with worse DFS. The combined nomogram, which was composed of clinically significant variables and radiomics features, showed a calibration and favorable performance for DFS prediction (AUC 0.893 and 0.885 in the training and validation cohorts, respectively).

CONCLUSION

The combined nomogram could be used as a tool in predicting DFS and may assist individualized decision making and clinical treatment.

Identification of Potentially Novel Molecular Targets of Endometrial Cancer Using a Non-Biased Proteomic Approach

The present study was aimed at identifying novel proteins in endometrial cancer (EC), employing proteomic analysis of tissues obtained after surgery. A differential MS-based proteomic analysis was conducted from whole tissues dissected from biopsies from post-menopausal women, histologically confirmed as endometrial cancer (two endometrioid and two serous; n = 4) or normal atrophic endometrium (n = 4), providing 888 differentially expressed proteins with 246 of these previously documented elsewhere as expressed in EC and 372 proteins not previously demonstrated to be expressed in EC but associated with other types of cancer. Additionally, 33 proteins not recorded previously in PubMed as being expressed in any forms of cancer were also identified, with only 26 of these proteins having a publication associated with their expression patterns or putative functions. The putative functions of the 26 proteins (GRN, APP, HEXA, CST3, CAD, QARS, SIAE, WARS, MYH8, CLTB, GOLIM4, SCARB2, BOD1L1, C14orf142, C9orf142, CCDC13, CNPY4, FAM169A, HN1L, PIGT, PLCL1, PMFBP1, SARS2, SCPEP1, SLC25A24 and ZC3H4) in other tissues point towards and provide a basis for further investigation of these previously unrecognised novel EC proteins. The developmental biology, disease, extracellular matrix, homeostatic, immune, metabolic (both RNA and protein), programmed cell death, signal transduction, molecular transport, transcriptional networks and as yet uncharacterised pathways indicate that these proteins are potentially involved in endometrial carcinogenesis and thus may be important in EC diagnosis, prognostication and treatment and thus are worthy of further investigation.

The crucial value of serum ferritin in assessing high-risk factors and prognosis for patients with endometrial carcinoma

BACKGROUND

Endometrial carcinoma is a common malignant tumor in female reproductive system. At present, there is no effective and economic prognostic index. This study aimed to investigate the effect of serum ferritin levels on the prognosis of endometrial carcinoma.

METHODS

Data of 367 patients who diagnosed with endometrial carcinoma at the First Affiliated Hospital of Chongqing Medical University between January 2012 and August 2018 was retrospectively analyzed. The prediction accuracy was evaluated by receiver operating characteristics curves and Youden's J statistics. Hosmer-lemeshow test was used to confirm the goodness of fit of the model. The prognostic value of serum ferritin on disease free survival (DFS) and overall survival (OS) of endometrial carcinoma was evaluated by univariate log-rank tests and multivariate cox regression models.

RESULTS

Preoperative high serum ferritin was correlated with older age, high grade, specific histological subtypes and recurrence of endometrial carcinoma (P < 0.05). The DFS and OS of 198 patients with elevated serum ferritin levels were significantly lower than those with low serum ferritin levels (P = 0.001 and P = 0.002, respectively). In multivariate analysis, serum ferritin was an independent prognostic factor for DFS and OS in endometrial carcinoma (P = 0.012, P = 0.028).

CONCLUSION

Through our research, we found that the high expression of serum ferritin level was not only related to low DFS and OS in patients with endometrial carcinoma, but also related to the high-risk factors of endometrial carcinoma recurrence. So serum ferritin levels may be used to predict the poor prognosis of patients with endometrial carcinoma.

Upgrading Treatment and Molecular Diagnosis in Endometrial Cancer-Driving New Tools for Endometrial Preservation?

One emerging problem for onco-gynecologists is the incidence of premenopausal patients under 40 years of age diagnosed with stage I Endometrial Cancer (EC) who want to preserve their fertility. Our review aims to define a primary risk assessment that can help fertility experts and onco-gynecologists tailor personalized treatment and fertility-preserving strategies for fertile patients wishing to have children. We confirm that risk factors such as myometrial invasion and The International Federation of Gynecology and Obstetrics (FIGO) staging should be integrated into the novel molecular classification provided by The Cancer Genome Atlas (TCGA). We also corroborate the influence of classical risk factors such as obesity, Polycystic ovarian syndrome (PCOS), and diabetes mellitus to assess fertility outcomes. The fertility preservation options are inadequately discussed with women with a diagnosis of gynecological cancer. A multidisciplinary team of gynecologists, oncologists, and fertility specialists could increase patient satisfaction and improve fertility outcomes. The incidence and death rates of endometrial cancer are rising globally. International guidelines recommend radical hysterectomy and bilateral salpingo-oophorectomy as the standard of care for this cancer; however, fertility-sparing alternatives should be tailored to motivated women of reproductive age, establishing an appropriate cost-benefit balance between childbearing desire and cancer risk. New molecular classifications such as that of TCGA provide a robust supplementary risk assessment tool that can tailor the treatment options to the patient's needs, curtail over- and under-treatment, and contribute to the spread of fertility-preserving strategies.

Quantitative SWATH-based proteomic profiling of urine for the identification of endometrial cancer biomarkers in symptomatic women

BACKGROUND

A non-invasive endometrial cancer detection tool that can accurately triage symptomatic women for definitive testing would improve patient care. Urine is an attractive biofluid for cancer detection due to its simplicity and ease of collection. The aim of this study was to identify urine-based proteomic signatures that can discriminate endometrial cancer patients from symptomatic controls.

METHODS

This was a prospective case-control study of symptomatic post-menopausal women (50 cancers, 54 controls). Voided self-collected urine samples were processed for mass spectrometry and run using sequential window acquisition of all theoretical mass spectra (SWATH-MS). Machine learning techniques were used to identify important discriminatory proteins, which were subsequently combined in multi-marker panels using logistic regression.

RESULTS

The top discriminatory proteins individually showed moderate accuracy (AUC > 0.70) for endometrial cancer detection. However, algorithms combining the most discriminatory proteins performed well with AUCs > 0.90. The best performing diagnostic model was a 10-marker panel combining SPRR1B, CRNN, CALML3, TXN, FABP5, C1RL, MMP9, ECM1, S100A7 and CFI and predicted endometrial cancer with an AUC of 0.92 (0.96-0.97). Urine-based protein signatures showed good accuracy for the detection of early-stage cancers (AUC 0.92 (0.86-0.9)).

CONCLUSION

A patient-friendly, urine-based test could offer a non-invasive endometrial cancer detection tool in symptomatic women. Validation in a larger independent cohort is warranted.

Application value of Ki67 and serum CA125 in the deep myometrial invasion of endometrial adenocarcinoma

OBJECTIVE

To investigate the application value of Ki67 and serum CA125 in diagnosing the deep myometrial invasion of endometrial adenocarcinoma.

METHODS

This study retrospectively analyzed 80 patients with endometrial adenocarcinoma, who underwent procedure from January 2018 to June 2021 at Senior Department of Obstetrics & Gynecology, the Seventh Medical Center of PLA General Hospital assigned to the Fourth Medical Center. The general clinical data, serum CA125 and Ki67 levels were compared between the superficial muscular infiltration group and the deep myometrial invasion group. We investigated the application value of Ki67 and serum CA125 in diagnosing the deep myometrial invasion of endometrial adenocarcinoma by the ROC curve.

RESULTS

80 patients were retrospectively analyzed, and 53 cases were superficial muscular infiltration, 27 cases were deep myometrial invasion. There was significant difference in age, tumor diameter, lymph node metastasis, Ki67, serum CA125, p53 status, serum CA125 and Ki67 levels between the two groups (p < 0.05). As high as 35% of Ki67 was the optimal cutoff value for predicting DMI in endometrial adenocarcinoma, and the area under ROC curve was 0.691, the sensitivity and specificity of diagnosis were 88.9% and 56.6%. As high as 43.645 U/ml of serum CA125 was the optimal cutoff value for predicting DMI in endometrial adenocarcinoma, and the area under ROC curve was 0.668, the sensitivity and specificity of diagnosis were 40.7% and 92.5%. After combined detection of both, the area under ROC curve was 0.719, and its sensitivity and specificity of diagnosis were 96.3% and 43.4%.

CONCLUSION

Serum CA125 and Ki67 may be used to evaluate DMI in patients with endometrial adenocarcinoma, and the diagnostic value of combination is higher, which provide reference for clinical treatment.

Serum lipidomic profiling by UHPLC-MS/MS may be able to detect early-stage endometrial cancer

Nowadays, screening for endometrial cancer (EC) primarily relies on clinical symptoms and imaging, which makes it difficult to detect early-stage disease. Here, we conducted a widely targeted lipidomic analysis of 38 human serum samples in a discovery set and 40 human serum samples in a validation set to profile the dysregulated lipid species and establish lipid biomarkers for early-stage EC. This comprehensive lipidomic determination of 616 serum lipids indicated significant differences between early-stage EC patients and healthy controls. Three phases of lipid biomarker investigation (discovery, validation, and determination of the lipid biomarker panel) were performed, which revealed the upregulation of some sphingolipid, glycerophospholipid, and glycerolipids and downregulation of some carnitine. Consistently, the perturbation of sphingolipid and glycerophospholipid metabolism was also observed from pathway enrichment analysis. Moreover, a lipid biomarker panel, including ursodeoxycholic acid, PC(O-14:0_20:4), and Cer(d18:1/18:0), was established. This panel was assessed as an effective diagnostic model to distinguish early-stage EC patients from healthy controls and atypical endometrial hyperplasia patients within the area under the receiver operating characteristic curve (AUC) reaching 0.903 and 0.928, respectively. In particular, the comparison results of the diagnostic efficacy indicated that the lipid biomarker panel was superior to clinically established indicators for EC diagnosis, including HE4, CA125, CA153, and CA199, suggesting that it could be used as an excellent supplementary method for the diagnosis of early-stage EC. In conclusion, we established a novel and non-invasive lipid biomarker for early-stage EC detection and these findings may provide new insight into the pathological mechanisms of EC.

Protein biomarkers in cervicovaginal lavages for detection of endometrial cancer

BACKGROUND

Rates of endometrial cancer (EC) are increasing. For a definitive diagnosis, women undergo various time-consuming and painful medical procedures, such as endometrial biopsy with or without hysteroscopy, and dilation and curettage, which may create a barrier to early detection and treatment, particularly for women with inadequate healthcare access. Thus, there is a need to develop robust EC diagnostics based on non- or minimally-invasive sampling. The objective of this study was to quantify a broad range of immuno-oncology proteins in cervicovaginal lavage (CVL) samples and investigate these proteins as predictive diagnostic biomarkers for EC.

METHODS

One hundred ninety-two women undergoing hysterectomy for benign or malignant indications were enrolled in this cross-sectional study. Classification of women to four disease groups: benign conditions (n = 108), endometrial hyperplasia (n = 18), low-grade endometrioid carcinoma (n = 53) and other EC subtypes (n = 13) was based on histopathology of biopsy samples collected after the surgery. CVL samples were collected in the operating room during the standard-of-care hysterectomy procedure. Concentrations of 72 proteins in CVL samples were evaluated using multiplex immunoassays. Global protein profiles were assessed using principal component and hierarchical clustering analyses. The relationships between protein levels and disease groups and disease severity were determined using Spearman correlation, univariate and multivariate receiver operating characteristics, and logistic regression analyses.

RESULTS

Women with EC and benign conditions exhibited distinctive cervicovaginal protein profiles. Several proteins in CVL samples (e.g., an immune checkpoint protein, TIM-3, growth factors, VEGF, TGF-α, and an anti-inflammatory cytokine, IL-10) discriminated EC from benign conditions, particularly, when tested in combinations with CA19-9, CA125, eotaxin, G-CSF, IL-6, MCP-1, MDC, MCP-3 and TRAIL (sensitivity of 86.1% and specificity of 87.9%). Furthermore, specific biomarkers (e.g., TIM-3, VEGF, TGF-α, TRAIL, MCP-3, IL-15, PD-L2, SCF) associated with histopathological tumor characteristics, including histological type and grade, tumor size, presence and depth of myometrial invasion or mismatch repair protein status, implying their potential utility for disease prognosis or monitoring therapies.

CONCLUSIONS

This proof-of-principle study demonstrated that cervicovaginal sampling coupled with multiplex immunoassay technology can offer a minimally to non-invasive method for EC detection.

Ion Channels in Endometrial Cancer

Simple Summary

Uterine or endometrial cancer is one of the most common types of cancer among the female population. Different alterations of molecules are related to many types of cancer. Some molecules called ion channels have been described as involved in the development of cancer, including endometrial cancer. We review the scientific evidence about the involvement of the ion channels in endometrial cancer and how some treatments can be developed with these molecules as a target. Even though they are involved in the progression of endometrial cancer, since they are present throughout the whole body, some possible treatments based on these could be studied.

Abstract

Uterine or endometrial cancer (EC) is the sixth most common neoplasia among women worldwide. Cancer can originate from a myriad of causes, and increasing evidence suggests that ion channels (IC) play an important role in the process of carcinogenesis, taking part in many pathways such as self-sufficiency in growth signals, proliferation, evasion of programmed cell death (apoptosis), angiogenesis, cell differentiation, migration, adhesion, and metastasis. Hormones and growth factors are well-known to be involved in the development and/or progression of many cancers and can also regulate some ion channels and pumps. Since the endometrium is responsive and regulated by these factors, the ICs could make an important contribution to the development and progression of endometrial cancer. In this review, we explore what is beyond (ion) flow regulation by investigating the role of the main families of ICs in EC, including as possible targets for EC treatment.

Urine CA125 and HE4 for the Triage of Symptomatic Women with Suspected Endometrial Cancer

A simple, noninvasive and accurate detection tool that can triage women with suspected endometrial cancer for definitive testing will transform patient care. The aim of this study was to evaluate urine CA125 and HE4 levels for the detection of endometrial cancer in symptomatic women. This was a cross-sectional diagnostic accuracy study of 153 symptomatic women who underwent urgent diagnostic investigations for suspected endometrial cancer at a large gynecological cancer center. Urine samples were collected prior to routine clinical procedures. Urine CA125 and HE4 levels were determined using automated chemiluminescent enzyme immunoassays. Univariate and multivariable receiver operating characteristic (ROC) curve analyses were performed. Urine CA125 and HE4 were discovered to be significantly elevated in women with endometrial cancer, compared to controls (p < 0.001 and p = 0.01, respectively). Urine CA125 and HE4 detected endometrial cancer with an area under the ROC curve (AUC) of 0.89 (0.81, 0.98) and 0.69 (0.55, 0.83), respectively. CA125 exhibited good discriminatory potential for Type I and early-stage tumors (AUC 0.93 and 0.90, respectively). A diagnostic model that combined urine CA125 and transvaginal ultrasound-measured endometrial thickness predicted endometrial cancer with an AUC of 0.96 (0.91, 1.00). Urine CA125 displays potential as a diagnostic tool for symptomatic women with suspected endometrial cancer. When combined with transvaginal ultrasound-measured endometrial thickness, this patient-friendly, urine-based test could help triage women for invasive diagnostics or safe reassurance, reducing costs and improving patient experience.

Tissue-Based Proteomic Profiling in Patients with Hyperplasia and Endometrial Cancer

Uterine cancers are among the most prevalent gynecological malignancies, and endometrial cancer (EC) is the most common in this group. This study used tissue-based proteomic profiling analysis in patients with endometrial cancer and hyperplasia, and control patients. Conventional 2D gel electrophoresis, followed by a mass spectrometry approach with bioinformatics, including a network pathway analysis pipeline, was used to identify differentially expressed proteins and associated metabolic pathways between the study groups. Thirty-six patients (twelve with endometrial cancer, twelve with hyperplasia, and twelve controls) were enrolled in this study. The mean age of the participants was 46–75 years. Eighty-seven proteins were significantly differentially expressed between the study groups, of which fifty-three were significantly differentially regulated (twenty-eight upregulated and twenty-five downregulated) in the tissue samples of EC patients compared to the control (Ctrl). Furthermore, 26 proteins were significantly dysregulated (8 upregulated and 18 downregulated) in tissue samples of hyperplasia (HY) patients compared to Ctrl. Thirty-two proteins (nineteen upregulated and thirteen downregulated) including desmin, peptidyl prolyl cis-trans isomerase A, and zinc finger protein 844 were downregulated in the EC group compared to the HY group. Additionally, fructose bisphosphate aldolase A, alpha enolase, and keratin type 1 cytoskeletal 10 were upregulated in the EC group compared to those in the HY group. The proteins identified in this study were known to regulate cellular processes (36%), followed by biological regulation (16%). Ingenuity pathway analysis found that proteins that are differentially expressed between EC and HY are linked to AKT, ACTA2, and other signaling pathways. The panels of protein markers identified in this study could be used as potential biomarkers for distinguishing between EC and HY and early diagnosis and progression of EC from hyperplasia and normal patients.

An in-Depth Analysis of Ovarian Cancer: Pathogenesis and Clinical Manifestation

Ovarian cancer is characterized by the establishment of tolerance, the recurrence of disease, as well as a poor prognosis. Gene signatures in ovarian cancer cells enable cancer medicine research, therapy, prevention, & management problematic. Notwithstanding advances in tumor puncture surgery, novel combinations regimens, and abdominal radiation, which can provide outstanding reaction times, the bulk of gynecological tumor patients suffer from side effects & relapse. As a consequence, more therapy alternatives for individuals with ovarian cancer must always be studied to minimize side effects and improve progression-free and total response rates. The development of cancer medications is presently undergoing a renaissance in the quest for descriptive and prognostic ovarian cancer biomarkers. Nevertheless, abnormalities in the BRCA2 or BRCA1 genes, a variety of hereditary predispositions, unexplained onset and progression, molecular tumor diversity, and illness staging can all compromise the responsiveness and accuracy of such indicators. As a result, current ovarian cancer treatments must be supplemented with broad-spectrum & customized targeted therapeutic approaches. The objective of this review is to highlight recent contributions to the knowledge of the interrelations between selected ovarian tumor markers, various perception signs, and biochemical and molecular signaling processes, as well as one's interpretation of much more targeted and effective treatment interventions.

Inflammation-Related LncRNAs Signature for Prognosis and Immune Response Evaluation in Uterine Corpus Endometrial Carcinoma

Backgrounds

Uterine corpus endometrial carcinoma (UCEC) is one of the greatest threats on the female reproductive system. The aim of this study is to explore the inflammation-related LncRNA (IRLs) signature predicting the clinical outcomes and response of UCEC patients to immunotherapy and chemotherapy.

Methods

Consensus clustering analysis was employed to determine inflammation-related subtype. Cox regression methods were used to unearth potential prognostic IRLs and set up a risk model. The prognostic value of the prognostic model was calculated by the Kaplan-Meier method, receiver operating characteristic (ROC) curves, and univariate and multivariate analyses. Differential abundance of immune cell infiltration, expression levels of immunomodulators, the status of tumor mutation burden (TMB), the response to immune checkpoint inhibitors (ICIs), drug sensitivity, and functional enrichment in different risk groups were also explored. Finally, we used quantitative real-time PCR (qRT-PCR) to confirm the expression patterns of model IRLs in clinical specimens.

Results

All UCEC cases were divided into two clusters (C1 = 454) and (C2 = 57) which had significant differences in prognosis and immune status. Five hub IRLs were selected to develop an IRL prognostic signature (IRLPS) which had value in forecasting the clinical outcome of UCEC patients. Biological processes related to tumor and immune response were screened. Function enrichment algorithm showed tumor signaling pathways (ERBB signaling, TGF-β signaling, and Wnt signaling) were remarkably activated in high-risk group scores. In addition, the high-risk group had a higher infiltration level of M2 macrophages and lower TMB value, suggesting patients with high risk were prone to a immunosuppressive status. Furthermore, we determined several potential molecular drugs for UCEC.

Conclusion

We successfully identified a novel molecular subtype and inflammation-related prognostic model for UCEC. Our constructed risk signature can be employed to assess the survival of UCEC patients and offer a valuable reference for clinical treatment regimens.

Long Non-Coding RNA TMPO-AS1 Promotes GLUT1-Mediated Glycolysis and Paclitaxel Resistance in Endometrial Cancer Cells by Interacting With miR-140 and miR-143

Increased glycolysis in tumor cells is frequently associated with drug resistance. Overexpression of glucose transporter-1 (GLUT1) promotes the Warburg effect and mediates chemoresistance in various cancers. Aberrant GLUT1 expression is considered as an essential early step in the development of endometrial cancer (EC). However, its role in EC glycolysis and chemoresistance and the upstream mechanisms underlying GLUT1 overexpression, remain undefined. Here, we demonstrated that GLUT1 was highly expressed in EC tissues and cell lines and that high GLUT1 expression was associated with poor prognosis in EC patients. Both gain-of-function and loss-of-function studies showed that GLUT1 increased EC cell proliferation, invasion, and glycolysis, while also making them resistant to paclitaxel. The long non-coding RNA TMPO-AS1 was found to be overexpressed in EC tissues and to be negatively associated with EC patient outcomes. RNA-immunoprecipitation and luciferase reporter assays confirmed that TMPO-AS1 elevated GLUT1 expression by directly binding to two critical tumor suppressor microRNAs (miR-140 and miR-143). Downregulation of TMPO-AS1 remarkably reduced EC cell proliferation, invasion, glycolysis, and paclitaxel resistance in EC cells. This study established that dysregulation of the TMPO-AS1-miR-140/miR-143 axis contributes to glycolysis and drug resistance in EC cells by up-regulating GLUT1 expression. Thus, inhibiting TMPO-AS1 and GLUT1 may prove beneficial in overcoming glycolysis-induced paclitaxel resistance in patients with EC.

Improving the Diagnosis of Endometrial Hyperplasia Using Computerized Analysis and Immunohistochemical Biomarkers

Endometrial hyperplasia (EH) is a precursor lesion to endometrial carcinoma (EC). Risks for EC include genetic, hormonal and metabolic factors most notably those associated with obesity: rates are rising and there is concern that cases in pre-menopausal women may remain undetected. Making an accurate distinction between benign and pre-malignant disease is both a challenge for the pathologist and important to the gynecologist who wants to deliver the most appropriate care to meet the needs of the patient. Premalignant change may be recognized by histological changes of endometrial hyperplasia (which may occur with or without atypia) and endometrial intraepithelial neoplasia (EIN). In this study we created a tissue resource of EH samples diagnosed between 2004 and 2009 (n = 125) and used this to address key questions: 1. Are the EIN/WHO2014 diagnostic criteria able to consistently identify premalignant endometrium? 2. Can computer aided image analysis inform identification of EIN? 3. Can we improve diagnosis by incorporating analysis of protein expression using immunohistochemistry. Our findings confirmed the inclusion of EIN in diagnostic criteria resulted in a better agreement between expert pathologists compared with the previous WHO94 criteria used for the original diagnosis of our sample set. A computer model based on assessment of stromal:epithelial ratio appeared most accurate in classification of areas of tissue without EIN. From an extensive panel of putative endometrial protein tissue biomarkers a score based on assessment of HAND2, PTEN, and PAX2 was able to identify four clusters one of which appeared to be more likely to be benign. In summary, our study has highlighted new opportunities to improve diagnosis of pre-malignant disease in endometrium and provide a platform for further research on this important topic.

Developing a novel DNA methylation risk score for survival and identification of prognostic gene mutations in endometrial cancer: a study based on TCGA data

Background

Few studies have focused on DNA methylation in endometrial cancer. The aim of our study is identify its role in endometrial cancer prognosis.

Methods

A publicly available dataset was retrieved from The Cancer Genome Atlas. For validation of expression alteration due to methylation, RNA sequencing data were obtained from other independent cohorts. MethSurv was used to search for candidate CpG probes, which were then filtered by least absolute shrinkage and selection operator Cox regression and multivariate Cox regression analyses to identify final set of CpG probes for overall survival. A methylation-based risk model was developed and receiver operating characteristic analysis with area under curve was used for evaluation. Patients were divided into high- and low-risk groups using an optimal cut-off point. Comprehensive bioinformatic analyses were conducted to identify hub genes, key transcription factors, and enriched cancer-related pathways. Kaplan–Meier curve was used for survival analysis.

Results

A 5-CpG signature score was established. Its predictive value for 5-year overall survival was high, with area under curve of 0.828, 0.835 and 0.816 for the training, testing and entire cohorts. cg27487839 and cg12885678 had strong correlation with their gene expression, XKR6 and PTPRN2, and lower PTPRN2 expression was associated with poorer survival in both The Cancer Genome Atlas and the validation datasets. Low-risk group was associated with significantly better survival. Low-risk group harboured more mutations in hub genes and key transcription factors, and mutations in SP1 and MECP2 represented favourable outcome.

Conclusion

We developed a methylation-based prognostic stratification system for endometrial cancer. Low-risk group was associated with better survival and harboured more mutations in the key regulatory genes.

Current and Emerging Prognostic Biomarkers in Endometrial Cancer

Endometrial cancer is the most common gynaecological malignancy in high income countries and its incidence is rising. Whilst most women with endometrial cancer are diagnosed with highly curable disease and have good outcomes, a significant minority present with adverse clinico-pathological characteristics that herald a poor prognosis. Prognostic biomarkers that reliably select those at greatest risk of disease recurrence and death can guide management strategies to ensure that patients receive appropriate evidence-based and personalised care. The Cancer Genome Atlas substantially advanced our understanding of the molecular diversity of endometrial cancer and informed the development of simplified, pragmatic and cost-effective classifiers with prognostic implications and potential for clinical translation. Several blood-based biomarkers including proteins, metabolites, circulating tumour cells, circulating tumour DNA and inflammatory parameters have also shown promise for endometrial cancer risk assessment. This review provides an update on the established and emerging prognostic biomarkers in endometrial cancer.

High expression of S100A2 predicts poor prognosis in patients with endometrial carcinoma

Background

S100A2, a member of the S100 protein family, is abnormally expressed and plays a vital role in multiple cancers. However, little is known about the clinical significance of S100A2 in endometrial carcinoma.

Methods

Clinicopathological data were obtained from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), Gene Expression Omnibus (GEO), and Clinical Proteomic Tumor Analysis Consortium (CPTAC). First, the expression and prognostic value of different S100 family members in endometrial carcinoma were evaluated. Subsequently, the Kaplan–Meier plotter and Cox regression analysis were used to assess the prognostic significance of S100A2, while the association between S100A2 expression and clinical characteristics in endometrial carcinoma was also analyzed using logistic regression. A receiver operating characteristic (ROC) curve and a nomogram were constructed. The putative underlying cellular mechanisms were explored using Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and gene set enrichment analysis (GSEA).

Results

Our results revealed that S100A2 expression was significantly higher in endometrial carcinoma tissue than in non-cancerous tissue at both the mRNA and protein levels. Analysis of Kaplan–Meier plotter data revealed that patients with high S100A2 expression had shorter overall survival (OS) and disease specific survival (DSS) compared with those of patients with low S100A2 expression. Multivariate Cox analysis further confirmed that high S100A2 expression was an independent risk factor for OS in patients with endometrial carcinoma. Other clinicopathologic features found to be related to worse prognosis in endometrial carcinoma included age, clinical stage, histologic grade, and tumor invasion. Importantly, ROC analysis also confirmed that S100A2 has a high diagnostic value in endometrial carcinoma. KEGG enrichment analysis and GSEA revealed that the estrogen and IL-17 signaling pathways were significantly upregulated in the high S100A2 expression group, in which estrogen response, JAK-STAT3, K-Ras, and TNFα/NF-κB were differentially enriched.

Conclusions

S100A2 plays an important role in endometrial carcinoma progression and may represent an independent diagnostic and prognostic biomarker for endometrial carcinoma.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09180-5.

New Trends in the Detection of Gynecological Precancerous Lesions and Early-Stage Cancers

The prevention and early diagnostics of precancerous stages are key aspects of contemporary oncology. In cervical cancer, well-organized screening and vaccination programs, especially in developed countries, are responsible for the dramatic decline of invasive cancer incidence and mortality. Cytological screening has a long and successful history, and the ongoing implementation of HPV triage with increased sensitivity can further decrease mortality. On the other hand, endometrial and ovarian cancers are characterized by a poor accessibility to specimen collection, which represents a major complication for early diagnostics. Therefore, despite relatively promising data from evaluating the combined effects of genetic variants, population screening does not exist, and the implementation of new biomarkers is, thus, necessary. The introduction of various circulating biomarkers is of potential interest due to the considerable heterogeneity of cancer, as highlighted in this review, which focuses exclusively on the most common tumors of the genital tract, namely, cervical, endometrial, and ovarian cancers. However, it is clearly shown that these malignancies represent different entities that evolve in different ways, and it is therefore necessary to use different methods for their diagnosis and treatment.

Expression of c-MET, EGFR and HER-2 in gastric adenocarcinoma tissue and its relationship with clinicopathological characteristics

OBJECTIVE

To determine the expression of tyrosine protein kinase Met (c-MET), epidermal growth factor receptor (EGFR), and human epidermal growth factor receptor 2 (HER-2) in cases with gastric adenocarcinoma (GA).

METHODS

The positive rates of the c-MET, EGFR, and HER-2 proteins between cancerous tissues and normal tissues sampled from 87 patients with GA were compared. The patients were assigned to different subgroups according to their clinicopathological characteristics and analyzed. Then the relationship between the above three indexes and the positive expression of Ki-67 were analyzed. In addition, the patients were assigned to positive and negative groups based on the situation of c-MET, EGFR and HER-2 proteins, and followed up for three years. These groups were compared in terms of recurrence-free survival, overall survival, and risks factors of prognosis.

RESULTS

The positive rates of c-MET, EGFR and HER-2 proteins in GA tissues were all higher than those in corresponding non-tumor tissues (all P<0.001), and the positive rates of them were greatly different in subgroups with different differentiation, invasion depth, TNM stage, lymph node metastasis (LNM), distant metastasis and presence of tumor thrombus (all P<0.05) and were positively correlated with the expression of Ki-67 protein (P<0.05). Moreover, the survival analysis results revealed lower recurrence-free survival and overall survival rates in groups with negative expression of c-MET, EGFR, and HER-2 than those in groups with positive expression of them (both P<0.001). Furthermore, the positive EGFR was an independent prognostic factor affecting the survival of patients with GA.

CONCLUSION

The expression of c-MET, EGFR and HER-2 proteins is correlated with clinical characteristics of patients with GA, and patients with positive expression of them face a higher recurrence rate. Additionally, EGFR protein may affect patients' survival.

Prospects and challenges of cancer systems medicine: from genes to disease networks

It is becoming evident that holistic perspectives toward cancer are crucial in deciphering the overwhelming complexity of tumors. Single-layer analysis of genome-wide data has greatly contributed to our understanding of cellular systems and their perturbations. However, fundamental gaps in our knowledge persist and hamper the design of effective interventions. It is becoming more apparent than ever, that cancer should not only be viewed as a disease of the genome but as a disease of the cellular system. Integrative multilayer approaches are emerging as vigorous assets in our endeavors to achieve systemic views on cancer biology. Herein, we provide a comprehensive review of the approaches, methods and technologies that can serve to achieve systemic perspectives of cancer. We start with genome-wide single-layer approaches of omics analyses of cellular systems and move on to multilayer integrative approaches in which in-depth descriptions of proteogenomics and network-based data analysis are provided. Proteogenomics is a remarkable example of how the integration of multiple levels of information can reduce our blind spots and increase the accuracy and reliability of our interpretations and network-based data analysis is a major approach for data interpretation and a robust scaffold for data integration and modeling. Overall, this review aims to increase cross-field awareness of the approaches and challenges regarding the omics-based study of cancer and to facilitate the necessary shift toward holistic approaches.

Role of miRNAs in Normal Endometrium and in Endometrial Disorders: Comprehensive Review

The molecular responses to hormonal stimuli in the endometrium are modulated at the transcriptional and post-transcriptional stages. Any imbalance in cellular and molecular endometrial homeostasis may lead to gynecological disorders. MicroRNAs (miRNAs) are involved in a wide variety of physiological mechanisms and their expression patterns in the endometrium are currently attracting a lot of interest. miRNA regulation could be hormone dependent. Conversely, miRNAs could regulate the action of sexual hormones. Modifications to miRNA expression in pathological situations could either be a cause or a result of the existing pathology. The complexity of miRNA actions and the diversity of signaling pathways controlled by numerous miRNAs require rigorous analysis and findings need to be interpreted with caution. Alteration of miRNA expression in women with endometriosis has been reported. Thus, a potential diagnostic test supported by a specific miRNA signature could contribute to early diagnosis and a change in the therapeutic paradigm. Similarly, specific miRNA profile signatures are expected for RIF and endometrial cancer, with direct implications for associated therapies for RIF and adjuvant therapies for endometrial cancer. Advances in targeted therapies based on the regulation of miRNA expression are under evaluation.

Comprehensive Library Generation for Identification and Quantification of Endometrial Cancer Protein Biomarkers in Cervico-Vaginal Fluid

Simple Summary

Endometrial cancer is the most common cancer of the female reproductive tract, and its incidence is rising. Early diagnosis has the potential to improve survival as women can receive care at the earliest possible stage when curative treatment is likely. Current tests for endometrial cancer diagnosis are sequentially invasive with low patient acceptability. A detection tool based on minimally invasive samples such as cervico-vaginal fluid would be a major advance in the field. This study focuses on the potential of detecting endometrial cancer based on the proteins and peptides expressed in cervico-vaginal fluid. Using Sequential window acquisition of all theoretical mass spectra (SWATH-MS), we present a spectral library of thousands of proteins in the cervico-vaginal fluid of women with or at risk of endometrial cancer. This important resource will enable the identification of endometrial cancer biomarkers in cervico-vaginal fluid and advances our knowledge of the role of proteomics in endometrial cancer detection.

Abstract

Endometrial cancer is the most common gynaecological malignancy in high-income countries and its incidence is rising. Early detection, aided by highly sensitive and specific biomarkers, has the potential to improve outcomes as treatment can be provided when it is most likely to effect a cure. Sequential window acquisition of all theoretical mass spectra (SWATH-MS), an accurate and reproducible platform for analysing biological samples, offers a technological advance for biomarker discovery due to its reproducibility, sensitivity and potential for data re-interrogation. SWATH-MS requires a spectral library in order to identify and quantify peptides from multiplexed mass spectrometry data. Here we present a bespoke spectral library of 154,206 transitions identifying 19,394 peptides and 2425 proteins in the cervico-vaginal fluid of postmenopausal women with, or at risk of, endometrial cancer. We have combined these data with a library of over 6000 proteins generated based on mass spectrometric analysis of two endometrial cancer cell lines. This unique resource enables the study of protein biomarkers for endometrial cancer detection in cervico-vaginal fluid. Data are available via ProteomeXchange with unique identifier PXD025925.

Two Dimensional-Difference in Gel Electrophoresis (2D-DIGE) Proteomic Approach for the Identification of Biomarkers in Endometrial Cancer Serum

Endometrial cancer is the most common gynecologic malignancy arising from the endometrium. Identification of serum biomarkers could be beneficial for its early diagnosis. We have used 2D-Difference In Gel Electrophoresis (2D-DIGE) coupled with Mass Spectrometry (MS) procedures to investigate the serum proteome of 15 patients with endometrial cancer and 15 non-cancer subjects. We have identified 16 proteins with diagnostic potential, considering only spots with a fold change in %V ≥ 1.5 or ≤0.6 in intensity, which were statistically significant (p < 0.05). Western blotting data analysis confirmed the upregulation of CLU, ITIH4, SERPINC1, and C1RL in endometrial and exosome cancer sera compared to those of control subjects. The application of the logistic regression constructed based on the abundance of these four proteins separated the controls from the cancers with excellent levels of sensitivity and specificity. After a validation phase, our findings support the potential of using the proposed algorithm as a diagnostic tool in the clinical stage.

The role of CCR2 in prognosis of patients with endometrial cancer and tumor microenvironment remodeling

Tumor microenvironment (TME) plays a core role in the genesis and progress of endometrial carcinoma (EC). The immune system, a crucial element of TME, functions in various immune cells. In this paper, we have tried to evaluate the prognosis in EC patients by the status of TME. The ESTIMATE algorithm was implemented to computer the number of immune and stromal components in EC tissues from the Cancer Genome Atlas dataset. The CIBERSORT algorithm was employed to assess the proportion of tumor-infiltrating immune cells in EC tissues, which were quantified as Stromal score and Immune score. After the construction of protein–protein interaction network, cell–cell chemokine receptor 2 (CCR2) was identified as a potential predictive element for EC. Further analysis indicated that a higher expression of CCR2 in EC patients was correlated with a better prognosis and a prolonged disease-free survival. According to the transcript level of CCR2, samples were separated into low- and high-expression groups. Gene Set Enrichment Analysis unveiled that metabolism-related pathways were mostly abundant in groups with high-expression, the other one was primarily correlated to immune-related activities. We figured out that some immune cells were positively related to CCR2, suggesting that CCR2 might serve as the immune-dominant status of TME, which was verified by qRT-PCR and HPA analysis in transcriptome and protein level, respectively. Also, CCR2 showed high correlation with immune modulators and chemokine signaling pathway. Thus, the level of CCR2 might have a prognostic value for EC patients, which provides a novel insight for therapeutic strategies of EC.

Development and validation of m6A regulators' prognostic significance for endometrial cancer

BACKGROUND

Endometrial cancer (EC) is the sixth most common cancer in women globally. It has been found that the expression levels of m6A regulators can be potentially used for prognostic stratification in some cancers, but the role of m6A regulators in EC prognosis remains unclear.

METHODS

The data of 584 EC samples were downloaded from The Cancer Genome Atlas and the mRNA expression profiles of 20 m6A regulators were analyzed, followed by functional enrichment analysis, immune infiltration analysis, and least absolute shrinkage and selection operator method-COX regression analysis.

RESULTS

The mRNA expression levels of 20 m6A regulators were significantly different between cancer samples across different grades. The 548 EC samples could be clearly divided into 2 clusters. Kaplan-Meier survival analysis proved that these two groups had highly different overall survival probabilities. Besides, the univariate regression analysis further reserved eight genes related to overall survival from the 20 m6A regulators. We established a prognostic signature including two genes, that is, IGF2BP1 and YTHDF3, that showed a strong ability for stratifying prognostically different EC patients. We identified 3239 differentially expressed genes between the high- and low-risk groups, involving in multiple biological processes and signaling pathways. Meanwhile, 6 differentially infiltrated immune cell types between the high- and low-risk groups could effectively distinguish the high- and low-risk EC groups. The expressions of immune checkpoints were different between high- and low-risk EC patients.

CONCLUSION

We first report the prognostic role of m6A regulators in EC, which should contribute to a better understanding of the underlying mechanisms of EC pathogenesis and progression.

Long non-coding RNA DLEU2 drives EMT and glycolysis in endometrial cancer through HK2 by competitively binding with miR-455 and by modulating the EZH2/miR-181a pathway

Background

Epithelial-to-mesenchymal transition (EMT) and aerobic glycolysis are fundamental processes implicated in cancer metastasis. Although increasing evidence demonstrates an association between EMT induction and enhanced aerobic glycolysis in human cancer, the mechanisms linking these two conditions in endometrial cancer (EC) cells remain poorly defined.

Methods

We characterized the role and molecular mechanism of the glycolytic enzyme hexokinase 2 (HK2) in mediating EMT and glycolysis and investigated how long noncoding RNA DLEU2 contributes to the stimulation of EMT and glycolysis via upregulation of HK2 expression.

Results

HK2 was highly expressed in EC tissues, and its expression was associated with poor overall survival. Overexpression of HK2 effectively promoted EMT phenotypes and enhanced aerobic glycolysis in EC cells via activating FAK and its downstream ERK1/2 signaling. Moreover, microRNA-455 (miR-455) served as a tumor suppressor by directly interacting with HK2 mRNA and inhibiting its expression. Furthermore, DLEU2 displayed a significantly higher expression in EC tissues, and increased DLEU2 expression was correlated with worse overall survival. DLEU2 acted as an upstream activator for HK2-induced EMT and glycolysis in EC cells through two distinct mechanisms: (i) DLEU2 induced HK2 expression by competitively binding with miR-455, and (ii) DLEU2 also interacted with EZH2 to silence a direct inhibitor of HK2, miR-181a.

Conclusions

This study identified DLEU2 as an upstream activator of HK2-driven EMT and glycolysis in EC cells and provided significant mechanistic insights for the potential treatment of EC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13046-021-02018-1.

Discovery and Evaluation of Protein Biomarkers as a Signature of Wellness in Late-Stage Cancer Patients in Early Phase Clinical Trials

TARGET (tumour characterisation to guide experimental targeted therapy) is a cancer precision medicine programme focused on molecular characterisation of patients entering early phase clinical trials. Performance status (PS) measures a patient's ability to perform a variety of activities. However, the quality of present algorithms to assess PS is limited and based on qualitative clinician assessment. Plasma samples from patients enrolled into TARGET were analysed using the mass spectrometry (MS) technique: sequential window acquisition of all theoretical fragment ion spectra (SWATH)-MS. SWATH-MS was used on a discovery cohort of 55 patients to differentiate patients into either a good or poor prognosis by creation of a Wellness Score (WS) that showed stronger prediction of overall survival (p = 0.000551) compared to PS (p = 0.001). WS was then tested against a validation cohort of 77 patients showing significant (p = 0.000451) prediction of overall survival. WS in both sets had receiver operating characteristic curve area under the curve (AUC) values of 0.76 (p = 0.002) and 0.67 (p = 0.011): AUC of PS was 0.70 (p = 0.117) and 0.55 (p = 0.548). These signatures can now be evaluated further in larger patient populations to assess their utility in a clinical setting.

Associations between Genetically Predicted Circulating Protein Concentrations and Endometrial Cancer Risk

Simple Summary

Endometrial cancer is the leading female reproductive tract cancer in developed countries. Discovering new biomarkers is critical for understanding the etiology this cancer and identifying women with a higher risk of this cancer from the general population. Several blood protein biomarkers have been linked to endometrial cancer in previous studies, but these studies have assessed only a limited number of biomarkers usually among a small number of participants. The current study aimed at identifying novel circulating protein biomarkers of endometrial cancer by using the largest available dataset to date. Our finding suggested nine proteins to be associated with endometrial cancer risk, and five of the identified associations showed suggestive associations with risk of non-endometrioid EC, a much more lethal subtype. If validated by additional studies, our findings may contribute to understanding the pathogenesis of endometrial tumor development and facilitating the risk assessment of endometrial cancer.

Abstract

Endometrial cancer (EC) is the leading female reproductive tract malignancy in developed countries. Currently, genome-wide association studies (GWAS) have identified 17 risk loci for EC. To identify novel EC-associated proteins, we used previously reported protein quantitative trait loci for 1434 plasma proteins as instruments to evaluate associations between genetically predicted circulating protein concentrations and EC risk. We studied 12,906 cases and 108,979 controls of European descent included in the Endometrial Cancer Association Consortium, the Epidemiology of Endometrial Cancer Consortium, and the UK Biobank. We observed associations between genetically predicted concentrations of nine proteins and EC risk at a false discovery rate of <0.05 (p-values range from 1.14 × 10⁻¹⁰ to 3.04 × 10⁻⁴). Except for vascular cell adhesion protein 1, all other identified proteins were independent from known EC risk variants identified in EC GWAS. The respective odds ratios (95% confidence intervals) per one standard deviation increase in genetically predicted circulating protein concentrations were 1.21 (1.13, 1.30) for DNA repair protein RAD51 homolog 4, 1.27 (1.14, 1.42) for desmoglein-2, 1.14 (1.07, 1.22) for MHC class I polypeptide-related sequence B, 1.05 (1.02, 1.08) for histo-blood group ABO system transferase, 0.77 (0.68, 0.89) for intestinal-type alkaline phosphatase, 0.82 (0.74, 0.91) for carbohydrate sulfotransferase 15, 1.07 (1.03, 1.11) for D-glucuronyl C5-epimerase, and 1.07 (1.03, 1.10) for CD209 antigen. In conclusion, we identified nine potential EC-associated proteins. If validated by additional studies, our findings may contribute to understanding the pathogenesis of endometrial tumor development and identifying women at high risk of EC along with other EC risk factors and biomarkers.

Dermatopontin as a potential pathogenic factor in endometrial cancer

The present study aimed to determine the differential expression profiles of proteins in endometrial carcinoma and to screen the proteins associated with the occurrence and development of endometrial cancer (EC). In total, 15 samples of human EC and paracancerous tissues were selected for proteomic analysis using a label-free quantification method based on liquid chromatography-tandem mass spectrometry. The differential proteins were analysed using bioinformatics and verified using reverse transcription-quantitative PCR (RT-qPCR) and western blotting. Finally, the expression of differential proteins in 75 endometrial carcinoma samples and 30 normal endometrial tissue samples were detected using immunohistochemical staining, and the associations between differential protein expression and clinicopathological features were analysed. In total, 579 up-regulated proteins and 346 down-regulated proteins were identified between the two groups and seven proteins with the most significant differences were selected; these proteins included interferon-induced protein with tetratricopeptide repeats 3, poly(ADP-ribose) polymerase family member 9, solute carrier family 34 member 2, cytochrome b5 reductase 1, protein tyrosine phosphatase non-receptor type 1, dermatopontin (DPT) and secretory leukocyte peptidase inhibitor. RT-qPCR and western blotting showed that DPT expression was down-regulated (P<0.001), which was consistent with the mass spectrometry results. The immunohistochemical staining results showed that the positive expression of DPT in EC and normal endometrial tissues was statistically significant (P<0.001). The positive expression of DPT was significantly decreased in poorly differentiated, late stage, lymph node metastasis and myometrial invasion depth ≥1/2 samples (P<0.05). DPT expression was significantly lower in EC, which might play role in the pathogenesis of EC.

Proteomic Analysis of Low-Grade, Early-Stage Endometrial Carcinoma Reveals New Dysregulated Pathways Associated with Cell Death and Cell Signaling

Simple Summary

Low-grade, early-stage endometrial cancer (EC) is the most frequent malignant tumor of the uterine corpus. Our study aimed to assess dysregulated pathways in this specific subset of EC through proteomic analysis. We describe and validate the dysregulation of the SLIT/ROBO signaling pathway, as well as cellular death processes such as necroptosis and ferroptosis. We identify several immune-related pathways, with a dominance of innate immune response associated pathways. Our findings reveal the singular biology of low-grade, early-stage ECs and could guide future research in the field.

Abstract

Low-grade, early-stage endometrial carcinoma (EC) is the most frequent malignant tumor of the uterine corpus. However, the molecular alterations that underlie these tumors are far from being fully understood. The purpose of this study is to describe dysregulated molecular pathways from EC patients. Sixteen samples of tumor tissue and paired healthy controls were collected and both were subjected to mass spectrometry (MS)/MS proteomic analysis. Gene ontology and pathway analysis was performed to discover dysregulated pathways and/or proteins using different databases and bioinformatic tools. Dysregulated pathways were cross-validated in an independent external cohort. Cell signaling, immune response, and cell death-associated pathways were robustly identified. The SLIT/ROBO signaling pathway demonstrated dysregulation at the proteomic and transcriptomic level. Necroptosis and ferroptosis were cell death-associated processes aberrantly regulated, in addition to apoptosis. Immune response-associated pathways showed a dominance of innate immune responses. Tumor immune infiltrates measured by immunofluorescence demonstrated diverse lymphoid and myeloid populations. Our results suggest a role of SLIT/ROBO, necroptosis, and ferroptosis, as well as a prominent role of innate immune response in low-grade, early-stage EC. These results could guide future research in this group of tumors.

Metabolomic Biomarkers for the Detection of Obesity-Driven Endometrial Cancer

Simple Summary

Endometrial cancer is the commonest cancer of the female genital tract and obesity is its main modifiable risk factor. Over 80% of endometrial cancers develop in the context of obesity-induced metabolic changes. This study focuses on the potential of plasma-based metabolites to enable the early detection of endometrial cancer in a cohort of women with body mass index (BMI) ≥ 30 kg/m². Specific lipid metabolites including phospholipids and sphingolipids (sphingomyelins) demonstrated good accuracy for the detection of endometrial cancer, especially when combined in a diagnostic model. This study advances our knowledge of the role of metabolomics in endometrial cancer and provides a basis for the minimally invasive screening of women with elevated BMI.

Abstract

Endometrial cancer is the most common malignancy of the female genital tract and a major cause of morbidity and mortality in women. Early detection is key to ensuring good outcomes but a lack of minimally invasive screening tools is a significant barrier. Most endometrial cancers are obesity-driven and develop in the context of severe metabolomic dysfunction. Blood-derived metabolites may therefore provide clinically relevant biomarkers for endometrial cancer detection. In this study, we analysed plasma samples of women with body mass index (BMI) ≥ 30 kg/m² and endometrioid endometrial cancer (cases, n = 67) or histologically normal endometrium (controls, n = 69), using a mass spectrometry-based metabolomics approach. Eighty percent of the samples were randomly selected to serve as a training set and the remaining 20% were used to qualify test performance. Robust predictive models (AUC > 0.9) for endometrial cancer detection based on artificial intelligence algorithms were developed and validated. Phospholipids were of significance as biomarkers of endometrial cancer, with sphingolipids (sphingomyelins) discriminatory in post-menopausal women. An algorithm combining the top ten performing metabolites showed 92.6% prediction accuracy (AUC of 0.95) for endometrial cancer detection. These results suggest that a simple blood test could enable the early detection of endometrial cancer and provide the basis for a minimally invasive screening tool for women with a BMI ≥ 30 kg/m².

GYNOCARE Update: Modern Strategies to Improve Diagnosis and Treatment of Rare Gynecologic Tumors—Current Challenges and Future Directions

Simple Summary

More than 50% of all the tumors affecting the female genital tract can be classified as rare and usually have a poor prognosis owing to delayed diagnosis and treatment. Currently, gynecologic cancer research, due to distinct scientific and technological challenges, is lagging behind. Moreover, the overall efforts for addressing these challenges are fragmented across different countries. The European Network for Gynecological Rare Cancer Research: GYNOCARE aims to address these challenges by creating a unique network between key stakeholders covering distinct domains from basic research to cure. GYNOCARE is part of a European Collaboration in Science and Technology (COST) with the aim to focus on the development of new approaches to improve the diagnosis and treatment of rare gynecological tumors. Here, we provide a brief overview describing the goals of this COST Action and its future challenges with the aim to continue fighting against this rare cancer.

Abstract

More than 50% of all gynecologic tumors can be classified as rare (defined as an incidence of ≤6 per 100,000 women) and usually have a poor prognosis owing to delayed diagnosis and treatment. In contrast to almost all other common solid tumors, the treatment of rare gynecologic tumors (RGT) is often based on expert opinion, retrospective studies, or extrapolation from other tumor sites with similar histology, leading to difficulty in developing guidelines for clinical practice. Currently, gynecologic cancer research, due to distinct scientific and technological challenges, is lagging behind. Moreover, the overall efforts for addressing these challenges are fragmented across different European countries and indeed, worldwide. The GYNOCARE, COST Action CA18117 (European Network for Gynecological Rare Cancer Research) programme aims to address these challenges through the creation of a unique network between key stakeholders covering distinct domains from concept to cure: basic research on RGT, biobanking, bridging with industry, and setting up the legal and regulatory requirements for international innovative clinical trials. On this basis, members of this COST Action, (Working Group 1, “Basic and Translational Research on Rare Gynecological Cancer”) have decided to focus their future efforts on the development of new approaches to improve the diagnosis and treatment of RGT. Here, we provide a brief overview of the current state-of-the-art and describe the goals of this COST Action and its future challenges with the aim to stimulate discussion and promote synergy across scientists engaged in the fight against this rare cancer worldwide.

Metabolomics for Diagnosis and Prognosis of Uterine Diseases? A Systematic Review

This systematic review analyses the contribution of metabolomics to the identification of diagnostic and prognostic biomarkers for uterine diseases. These diseases are diagnosed invasively, which entails delayed treatment and a worse clinical outcome. New options for diagnosis and prognosis are needed. PubMed, OVID, and Scopus were searched for research papers on metabolomics in physiological fluids and tissues from patients with uterine diseases. The search identified 484 records. Based on inclusion and exclusion criteria, 44 studies were included into the review. Relevant data were extracted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) checklist and quality was assessed using the QUADOMICS tool. The selected metabolomics studies analysed plasma, serum, urine, peritoneal, endometrial, and cervico-vaginal fluid, ectopic/eutopic endometrium, and cervical tissue. In endometriosis, diagnostic models discriminated patients from healthy and infertile controls. In cervical cancer, diagnostic algorithms discriminated patients from controls, patients with good/bad prognosis, and with/without response to chemotherapy. In endometrial cancer, several models stratified patients from controls and recurrent from non-recurrent patients. Metabolomics is valuable for constructing diagnostic models. However, the majority of studies were in the discovery phase and require additional research to select reliable biomarkers for validation and translation into clinical practice. This review identifies bottlenecks that currently prevent the translation of these findings into clinical practice.

Peptidomics-Driven Strategy Reveals Peptides and Predicted Proteases Associated With Oral Cancer Prognosis

Protease activity has been associated with pathological processes that can lead to cancer development and progression. However, understanding the pathological unbalance in proteolysis is challenging because changes can occur simultaneously at protease, their inhibitor, and substrate levels. Here, we present a pipeline that combines peptidomics, proteomics, and peptidase predictions for studying proteolytic events in the saliva of 79 patients and their association with oral squamous cell carcinoma (OSCC) prognosis. Our findings revealed differences in the saliva peptidome of patients with (pN+) or without (pN0) lymph-node metastasis and delivered a panel of ten endogenous peptides correlated with poor prognostic factors plus five molecules able to classify pN0 and pN+ patients (area under the receiver operating characteristic curve > 0.85). In addition, endopeptidases and exopeptidases putatively implicated in the processing of differential peptides were investigated using cancer tissue gene expression data from public repositories, reinforcing their association with poorer survival rates and prognosis in oral cancer. The dynamics of the OSCC-related proteolysis were further explored via the proteomic profiling of saliva. This revealed that peptidase/endopeptidase inhibitors exhibited reduced levels in the saliva of pN+ patients, as confirmed by selected reaction monitoring-mass spectrometry, while minor changes were detected in the level of saliva proteases. Taken together, our results indicated that proteolytic activity is accentuated in the saliva of patients with OSCC and lymph-node metastasis and, at least in part, is modulated by reduced levels of salivary peptidase inhibitors. Therefore, this integrated pipeline provided better comprehension and discovery of molecular features with implications in the oral cancer metastasis prognosis.

Endometrial cancer-is our knowledge changing?

In developed countries, endometrial cancer (EC) is the most frequent gynecologic malignancy in postmenopausal women. At the same time, EC has become one of the most common cancers in numerous developing countries, probably influenced by global epidemic of obesity. The majority of patients have low-grade endometrioid cancer with a high 5-year survival rate, but with high-risk EC, the survival rates are still rather low. However, despite intensive research in last decades, our knowledge of the mechanisms, risk factors, diagnosis and treatment have not significantly improved. The standard treatment of all types of EC is still a traditional combination of surgery, irradiation and/or chemotherapy, despite the fact that each of these options is not without having some negative side effects. Despite the fact that on the molecular level, EC is relatively well-studied, but the efforts to transform these findings into either diagnosis or therapies of EC remain elusive. In addition, some research into risk factors involved in the development or progression of EC seems to be more a fishing expedition than a well thought-out approach. The purpose of this review is to summarize the most recent developments in the search for biomarkers and prognostic markers and to discuss the progress in EC treatment.

Urinary Biomarkers and Their Potential for the Non-Invasive Detection of Endometrial Cancer

Endometrial cancer is the most common malignancy of the female genital tract and its incidence is rising in parallel with the mounting prevalence of obesity. Early diagnosis has great potential to improve outcomes as treatment can be curative, especially for early stage disease. Current tests and procedures for diagnosis are limited by insufficient accuracy in some and unacceptable levels of invasiveness and discomfort in others. There has, therefore, been a growing interest in the search for sensitive and specific biomarkers for endometrial cancer detection based on non-invasive sampling methodologies. Urine, the prototype non-invasive sample, is attractive for biomarker discovery as it is easily accessible and can be collected repeatedly and in quantity. Identification of urinary biomarkers for endometrial cancer detection relies on the excretion of systemic biomarkers by the kidneys or urinary contamination by biomarkers shed from the uterus. In this review, we present the current standing of the search for endometrial cancer urinary biomarkers based on cytology, genomic, transcriptomic, proteomic, and metabolomic platforms. We summarize the biomarker candidates and highlight the challenges inherent in urinary biomarker discovery. We review the various technologies with promise for biomarker detection and assess these novel approaches for endometrial cancer biomarker research.

Metabolomic Biomarkers for Detection, Prognosis and Identifying Recurrence in Endometrial Cancer

Metabolic reprogramming is increasingly recognised as one of the defining hallmarks of tumorigenesis. There is compelling evidence to suggest that endometrial cancer develops and progresses in the context of profound metabolic dysfunction. Whilst the incidence of endometrial cancer continues to rise in parallel with the global epidemic of obesity, there are, as yet, no validated biomarkers that can aid risk prediction, early detection, prognostic evaluation or surveillance. Advances in high-throughput technologies have, in recent times, shown promise for biomarker discovery based on genomic, transcriptomic, proteomic and metabolomic platforms. Metabolomics, the large-scale study of metabolites, deals with the downstream products of the other omics technologies and thus best reflects the human phenotype. This review aims to provide a summary and critical synthesis of the existing literature with the ultimate goal of identifying the most promising metabolite biomarkers that can augment current endometrial cancer diagnostic, prognostic and recurrence surveillance strategies. Identified metabolites and their biochemical pathways are discussed in the context of what we know about endometrial carcinogenesis and their potential clinical utility is evaluated. Finally, we underscore the challenges inherent in metabolomic biomarker discovery and validation and provide fresh perspectives and directions for future endometrial cancer biomarker research.

Long non‑coding RNA SNHG12 regulates cell proliferation, invasion and migration in endometrial cancer by targeting miR‑4429

Long non-coding RNA small nucleolar RNA host gene 12 (SNHG12) has been demonstrated to be oncogenic. The aim of the present study was to examine the effects of SNHG12 on the progression of endometrial cancer (EC). The expression levels of SNHG12 and microRNA (miR)-4429 were assessed in EC cell lines by reverse transcription-quantitative PCR. Plasmids, including SNHG12 short hairpin RNAs (shRNAs), shRNA negative control (NC), SNHG12 overexpression (OV), OV-NC, miR-4429 mimic and mimic-NC, were transfected into RL95-2 cells. Post-transfection, Cell Counting Kit-8, Transwell Matrigel and wound-healing assays were performed to assess cell proliferation, invasion and migration, respectively. Cell cycle phase distribution was assessed by flow cytometry. The protein expression levels of matrix metalloproteinase (MMP)2 and MMP9 were detected by western blotting. miR-4429 target genes were predicted by bioinformatics analysis using target prediction online tools; the findings of this analysis were verified using a dual-luciferase reporter system. Identified as a target of miR-4429, SNHG12 was overexpressed in EC cell lines with decreased expression of miR-4429. Further experiments demonstrated that SNHG12 silencing and overexpression of miR-4429 markedly suppressed proliferation, migration and invasion of RL95-2 cells, arrested cells in the G₁ phase, and markedly downregulated the expression of MMP2 and MMP9. The opposite effects were observed in miR-4429 mimic-transfected RL95-2 cells after SNHG12 was overexpressed. The findings of the present study established the role of SNHG12 and miR-4429 in EC. Therefore, targeting the SNHG12/miR-4429 axis could serve as a potential future therapeutic target for treatment of EC.

Simultaneous FTIR and Raman Spectroscopy in Endometrial Atypical Hyperplasia and Cancer

Currently, endometrial carcinoma (EC) is the most common genital cancer in high-income countries. Some types of endometrial hyperplasia (EH) may be progressing to this malignancy. The diagnosis of EC and EH is based on time consuming histopathology evaluation, which is subjective and causes discrepancies in reassessment. Therefore, there is a need to create methods of objective evaluation allowing the diagnosis of early changes. The study aimed to simultaneously asses Fourier Transform Infrared (FTIR) and Raman spectroscopy combined with multidimensional analysis to identify the tissues of endometrial cancer, atypical hyperplasia and the normal control group, and differentiate them. The results of FTIR and Raman spectroscopy revealed quantitative and qualitative changes in the nucleic acid and protein in the groups of cancer and atypical hyperplasia, in comparison with the control group. Changes in the lipid region were also observed in Raman spectra. Pearson correlation coefficient demonstrated a statistically significant correlation between Raman spectra for the cancer and atypical hyperplasia groups (0.747, p < 0.05) and for atypical hyperplasia and the controls (0.507, p < 0.05), while FTIR spectra demonstrated a statistically significant positive correlation for the same group as in Raman data and for the control and cancer groups (0.966, p < 0.05). To summarize, the method of spectroscopy enables differentiation of atypical hyperplasia and endometrial cancer tissues from the physiological endometrial tissue.