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.

Identifying the determinants of face mask disposal behavior and policy implications: An application of the extended theory of planned behavior.

A study in Nigeria examined the psychological factors affecting face mask disposal behavior (DB) during the COVID-19 pandemic. The Theory of Planned Behavior (TPB) was used, with awareness of consequences and institutional barriers added. 1183 respondents completed an online survey, and structural equation modeling was used to analyze the data. The original TPB model revealed that attitudes, perceived behavioral control, and subjective norms explained 65% of the variance in respondents' behavior. Behavioral intention and perceived behavioral control accounted for 59.3% of the variance in DB. The extended TPB model, which included awareness of consequences and perceived institutional barriers, improved the model's explanatory power by 12.8%. Both TPB models adequately predicted face mask (FM) disposal behavior, with implications for policymakers and waste management authorities to design interventions to promote proper FM disposal behavior.

Urine CA125 and HE4 for the Detection of Ovarian Cancer in Symptomatic Women.

The symptoms of ovarian cancer are vague, and current risk assessment tools such as serum CA125 and transvaginal ultrasound scan fail to reliably detect the disease early. This study aimed to evaluate urine CA125 and HE4 as diagnostic biomarkers for ovarian cancer in symptomatic women. Paired urine and serum samples were collected from women undergoing treatment for ovarian cancer (cases) or investigations for gynaecological symptoms (controls). Biomarkers were measured using an automated chemiluminescent enzyme immunoassay analyser. Standard diagnostic accuracy metrics were calculated. In total, 114 women were included, of whom 17 (15%) were diagnosed with an epithelial ovarian malignancy. Levels of urine CA125 and HE4 were significantly elevated in women with ovarian cancer compared to controls [CA125: 8.5 U/mL (IQR: 2.4-19.5) vs. 2.3 U/mL (IQR: 1.0-6.4), p = 0.01. HE4: 12.0 nmol/L (IQR: 10.3-23.1) vs. 6.7 nmol/L (IQR: 3.4-13.6), p = 0.006]. Urine CA125 and HE4 detected ovarian cancer with an AUC of 0.69 (95% CI: 0.55-0.82) and 0.71 (95% CI: 0.69-0.82), respectively (p = 0.73). A combination of urine CA125 and HE4 at optimal thresholds had a sensitivity of 82.4% (95% CI: 56.6-96.2) and was comparable to the sensitivity of serum CA125 [88.2% (95% CI: 63.6-98.5)]. Larger studies are required to confirm our findings, standardise urine collection, and evaluate optimal biomarker thresholds. Urine CA125 and HE4 may be useful non-invasive diagnostic tools to triage women for formal ovarian cancer investigations.

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.

Computational approaches for network-based integrative multi-omics analysis.

Advances in omics technologies allow for holistic studies into biological systems. These studies rely on integrative data analysis techniques to obtain a comprehensive view of the dynamics of cellular processes, and molecular mechanisms. Network-based integrative approaches have revolutionized multi-omics analysis by providing the framework to represent interactions between multiple different omics-layers in a graph, which may faithfully reflect the molecular wiring in a cell. Here we review network-based multi-omics/multi-modal integrative analytical approaches. We classify these approaches according to the type of omics data supported, the methods and/or algorithms implemented, their node and/or edge weighting components, and their ability to identify key nodes and subnetworks. We show how these approaches can be used to identify biomarkers, disease subtypes, crosstalk, causality, and molecular drivers of physiological and pathological mechanisms. We provide insight into the most appropriate methods and tools for research questions as showcased around the aetiology and treatment of COVID-19 that can be informed by multi-omics data integration. We conclude with an overview of challenges associated with multi-omics network-based analysis, such as reproducibility, heterogeneity, (biological) interpretability of the results, and we highlight some future directions for network-based integration.

Serum CA125 and HE4 as Biomarkers for the Detection of Endometrial Cancer and Associated High-Risk Features.

Early detection of endometrial cancer improves survival. Non-invasive diagnostic biomarkers would improve triage of symptomatic women for investigations. This study aimed to determine the diagnostic accuracy of serum Cancer Antigen 125 (CA125) and Human Epididymis 4 (HE4) for endometrial cancer and associated high-risk features. Serum samples from women investigated for gynaecological symptoms or diagnosed with endometrial cancer were analysed for CA125 and HE4. Conventional diagnostic metrics were calculated. In total, 755 women were included; 397 had endometrial cancer. Serum CA125 and HE4 were significantly elevated in cases compared with controls (both p < 0.001), and with pathological markers of disease severity (p < 0.05). A combination of CA125 and HE4 detected endometrial cancer with an area under the curve (AUC) of 0.77 (95% CI: 0.74−0.81). In a model with body mass index (BMI) and parity, HE4 predicted endometrial cancer in pre-menopausal women with an AUC of 0.91 [sensitivity = 84.5%, specificity = 80.9% (p < 0.001)]. In women with abnormal ultrasound, HE4 ≥ 77 pmol/L improved specificity compared with imaging alone [68.6% (95% CI: 75.0−83.6) vs. 34.4% (95% CI: 27.1−42.3), respectively], but at a cost to sensitivity. HE4 ≥ 77 pmol/L improved the detection of myometrial invasion ≥50% in women with stage I disease compared with magnetic resonance imaging (MRI) alone [sensitivity = 100% (95% CI: 54.1−100)]. CA125 ≥ 35 U/mL did not add to imaging. HE4 is a good predictor of poor prognostic features which could assist staging investigations.

Impact of pre-treatment prognostic nutritional index and the haemoglobin, albumin, lymphocyte and platelet (HALP) score on endometrial cancer survival: A prospective database analysis.

PURPOSE: The Onodera's prognostic nutritional index (PNI) and the haemoglobin, albumin, lymphocyte and platelet (HALP) score are immune-nutritional indices that correlate with survival outcomes in several adult solid malignancies. The aim of this study was to investigate whether PNI and HALP are associated with survival outcomes in endometrial cancer. PATIENTS AND METHODS: Women undergoing management for endometrial cancer were recruited to a single centre prospective cohort study. Pre-treatment PNI and HALP scores were computed for study participants and analysed as continuous variables and by selecting cut-off values based on previous publications. Both parameters were analysed in relation to overall, endometrial cancer-specific and recurrence-free survival using Kaplan-Meier estimation and multivariable Cox proportional regression. RESULTS: A total of 439 women, with a median age of 67 years (interquartile range (IQR), 58, 74) and BMI of 31kg/m2 (IQR 26, 37) were included in the analysis. Most had low-grade (63.3%), early-stage (84.4% stage I/II) endometrial cancer of endometrioid histological subtype (72.7%). Primary treatment was surgery in 98.2% of cases. Adjusted overall mortality hazard ratios for PNI and HALP as continuous variables were 0.97(95%CI 0.94-1.00, p = 0.136) and 0.99(95%CI 0.98-1.01, p = 0.368), respectively. Women with pre-treatment PNI ≥45 had a 45% decrease in both overall (adjusted HR = 0.55, 95% CI 0.33-0.92, p = 0.022) and cancer-specific mortality risk (adjusted HR = 0.55, 95%CI 0.30-0.99, p = 0.048) compared to those with PNI <45. There was no evidence for an effect of PNI on recurrence free survival. HALP scores were associated with adverse clinico-pathologic factors, but not overall, cancer-specific or recurrence-free survival in the multivariable analysis. CONCLUSION: PNI is an independent prognostic factor in endometrial cancer and has the potential to refine pre-operative risk assessment.

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.

Characterization of hydrocarbon degrading microorganisms from Glycine max and Zea mays phytoremediated crude oil contaminated soil.

Microbe-plant partnership in phytoremediation involves a synergistic interaction that leads to degradation of contaminants. The identification and characterization of these microorganisms is fundamental in environmental management. This study is aimed at investigating the influence of Glycine max and Zea mays on microbial make-up and differentiation of soil bacterial and fungal isolates in crude oil contaminated soil. We employed conventional technique of microbial isolation and gene sequencing to evaluate the microbial composition in crude oil contaminated soil. The microorganisms were isolated from crude oil contaminated soil (0%, 4%, 8%) and were identified using 16S rRNA gene (for bacteria) and Internal Transcribed Spacer (ITS) gene (for fungi). We observed a change in the microbial cell density with respect to treatment conditions implying a shift in microbial dynamics to total hydrocarbon utilizing bacteria as the dominant microbes. The sequence data revealed five bacteria strain; Klebsiella aerogenes strain 77, Klebsiella aerogenes strain UISO178, Salmonella enterica strain ABUH7, Klebsiella aerogenes strain M242 and Enterobacter sp. NCCP-607 and three fungi strains; Galactomyces geotrichum strain CBS, Aspergillus niger strain YMCHA73 and Trichoderma virens isolate A701. Annotation analysis using FGENESB and gene scan revealed proteins involved in various metabolic processes and hydrocarbon utilization. GHOSTKOLA output revealed several genetic elements and pathways such as DnaA, PYG, mrcA, environmental, cellular and genetic information processing and degradation enhancers. Our findings show that G. max and Z. mays in association with bacteria can enhance ecosystem restoration of crude oil contaminated soil.

Impact of Type 2 Diabetes Mellitus on Endometrial Cancer Survival: A Prospective Database Analysis.

Purpose: Type 2 diabetes mellitus (T2DM) is an established risk factor for endometrial cancer but its impact on endometrial cancer survival outcomes is unclear. The aim of this study was to investigate whether pre-existing T2DM impacts survival outcomes in endometrial cancer. Patients and Methods: Women diagnosed with endometrial cancer were recruited to a single centre prospective cohort study. Relevant sociodemographic and clinico-pathological data were recorded at baseline. T2DM status was based on clinical and biochemical assessment, verified by general practitioner records and analysed in relation to overall, cancer-specific and recurrence-free survival using Kaplan-Meier estimation and multivariable Cox-regression. Results: In total, 533 women with median age and BMI of 66 years (Interquartile range (IQR), 56, 73) and 32kg/m2 (IQR 26, 39) respectively, were included in the analysis. The majority had low-grade (67.3%), early-stage (85.1% stage I/II), endometrial cancer of endometrioid histological phenotype (74.7%). A total of 107 (20.1%) had pre-existing T2DM. Women with T2DM had a two-fold increase in overall mortality (adjusted HR 2.07, 95%CI 1.21-3.55, p=0.008), cancer-specific mortality (adjusted HR 2.15, 95% CI 1.05-4.39, p=0.035) and recurrence rates (adjusted HR 2.22, 95% CI 1.08-4.56, p=0.030), compared to those without, in multivariable analyses. Conclusion: T2DM confers an increased risk of death in endometrial cancer patients. Well-designed longitudinal studies with large sample sizes are now needed to confirm these findings.

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.

Urinary biomarkers for the detection of ovarian cancer: a systematic review.

Currently, the only definitive method for diagnosing ovarian cancer involves histological examination of tissue obtained at time of surgery or by invasive biopsy. Blood has traditionally been the biofluid of choice in ovarian cancer biomarker discovery; however, there has been a growing interest in exploring urinary biomarkers, particularly as it is non-invasive. In this systematic review, we present the diagnostic accuracy of urinary biomarker candidates for the detection of ovarian cancer. A comprehensive literature search was performed using the MEDLINE/PubMed and EMBASE, up to 1 April 2021. All included studies reported the diagnostic accuracy using sensitivity and/or specificity and/or receiver operating characteristics (ROC) curve. Risk of bias and applicability of included studies were assessed using the QUADAS-2 tool. Twenty-seven studies were included in the narrative synthesis. Protein/peptide biomarkers were most commonly described (n = 18), with seven studies reporting composite scores of multiple protein-based targets. The most frequently described urinary protein biomarker was HE4 (n = 5), with three studies reporting a sensitivity and specificity > 80%. Epigenetic (n = 1) and metabolomic/organic compound biomarkers (n = 8) were less commonly described. Overall, six studies achieved a sensitivity and specificity of >90% and/or an AUC > 0.9. Evaluation of urinary biomarkers for the detection of ovarian cancer is a dynamic and growing field. Currently, the most promising biomarkers are those that interrogate metabolomic pathways and organic compounds, or quantify multiple proteins. Such biomarkers require external validation in large, prospective observational studies before they can be implemented into clinical practice.

Pre-treatment inflammatory parameters predict survival from endometrial cancer: A prospective database analysis.

PURPOSE: Inflammation predisposes to tumorigenesis by damaging DNA, stimulating angiogenesis and potentiating pro-proliferative and anti-apoptotic processes. The aim of this study was to investigate whether pre-treatment biomarkers of systemic inflammation are associated with survival outcomes in endometrial cancer. PATIENTS AND METHODS: Women with endometrial cancer were recruited to a prospective database study. Pre-treatment systemic markers of inflammation, including C-reactive protein (CRP), Glasgow Prognostic Score and lymphocyte-based ratios [neutrophil-lymphocyte ratio (NMR), monocyte-lymphocyte ratio (MLR), systemic immune-inflammation index (SII)], were analysed in relation to overall, endometrial cancer-specific and recurrence-free survival using Kaplan-Meier estimation and multivariable Cox regression. RESULTS: In total, 522 women of mostly White British ethnicity, with a median age of 66 years (interquartile range (IQR), 56, 73) and BMI of 32 kg/m2 (IQR 26, 39) were included in the analysis. Most had low-grade (67.2%), early-stage (85.4% stage I/II), endometrioid (74.5%) tumors. Women with pre-treatment CRP ≥5.5 mg/L had a 68% increase in overall (adjusted HR = 1.68, 95% CI 1.00-2.81, p = 0.049) and a two-fold higher cancer-specific mortality risk than those with CRP <5.5 mg/L (adjusted HR = 2.04, 95%CI 1.03-4.02, p = 0.04). Absolute lymphocyte count, NLR, MLR and SII were associated with adverse clinico-pathologic factors, but not overall, cancer-specific or recurrence-free survival in the multivariable analysis. CONCLUSION: If confirmed in an independent cohort, CRP may offer a simple, low-cost test to refine pre-treatment risk assessment and guide personalised care in endometrial cancer. Our participants were mostly of White British ethnicity and further studies are needed to confirm the utility of CRP as a prognostic biomarker in other populations.

Does Clinical and Biochemical Thyroid Dysfunction Impact on Endometrial Cancer Survival Outcomes? A Prospective Database Study.

Endometrial cancer is the commonest gynaecological malignancy in developed countries, and women presenting with high risk or advanced disease have poor outcomes. Thyroid hormones play a key role in cellular metabolism and can influence cancer growth and invasion. Our aim was to evaluate the association between clinical and biochemical thyroid dysfunction and endometrial cancer survival outcomes. This was a prospective cohort study of women treated for endometrial cancer at a specialist centre. Clinical diagnosis of hypothyroidism was based on clinical and biochemical assessment, verified by general practitioner (GP) records. Pre-treatment serum samples were tested for thyrotropin (TSH), thyroid hormones (free T4 and total T3), and thyroid peroxidase antibodies. Kaplan-Meier survival estimates and log-rank tests were used to compare survival between groups, while Cox regression was used for multivariable analysis, adjusting for known confounders and effect modifications. In total, 333 women with median age and body mass index (BMI) of 66 years (interquartile range (IQR) 56, 73) and 33 kg/m2 (IQR 27, 41) respectively were included. A total of 51 (15.3%) women had a diagnosis of hypothyroidism, 39 (11.9%) had biochemical evidence of overt or subclinical hypothyroidism. Median follow-up was 35 months (IQR 21, 45) with 38 (11.7%) relapses and 50 (15.0%) deaths. Women with a diagnosis of hypothyroidism had improved overall survival (adjusted HR = 0.22, 95%CI 0.06-0.74, p = 0.02), cancer-specific survival (adjusted HR = 0.21, 95%CI 0.05-0.98, p = 0.04) and fewer recurrences (adjusted HR = 0.17, 95%CI 0.04-0.77, p = 0.02) than those who did not. Confirmatory studies should explore underlying mechanisms and the potential for therapeutic exploitation.

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

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.

DEveloping Tests for Endometrial Cancer deTection (DETECT): protocol for a diagnostic accuracy study of urine and vaginal samples for the detection of endometrial cancer by cytology in women with postmenopausal bleeding.

INTRODUCTION: Postmenopausal bleeding (PMB), the red flag symptom for endometrial cancer, triggers urgent investigation by transvaginal ultrasound scan, hysteroscopy and/or endometrial biopsy. These investigations are costly, invasive and often painful or distressing for women. In a pilot study, we found that voided urine and non-invasive vaginal samples from women with endometrial cancer contain malignant cells that can be identified by cytology. The aim of the DEveloping Tests for Endometrial Cancer deTection (DETECT) Study is to determine the diagnostic test accuracy of urine and vaginal cytology for endometrial cancer detection in women with PMB. METHODS AND ANALYSIS: This is a multicentre diagnostic accuracy study of women referred to secondary care with PMB. Eligible women will be asked to provide a self-collected voided urine sample and a vaginal sample collected with a Delphi screener before routine clinical procedures. Pairs of specialist cytologists, blinded to participant cancer status, will assess and classify samples independently, with differences settled by consensus review or involving a third cytologist. Results will be compared with clinical outcomes from standard diagnostic tests. A sample size of 2000 women will have 80% power to establish a sensitivity of vaginal samples for endometrial cancer detection by cytology of ≥85%±7%, assuming 5% endometrial cancer prevalence. The primary objective is to determine the diagnostic accuracy of urogenital samples for endometrial cancer detection by cytology. Secondary objectives include the acceptability of urine and vaginal sampling to women. ETHICS AND DISSEMINATION: This study has been approved by the North West-Greater Manchester West Research Ethics Committee (16/NW/0660) and the Health Research Authority. Results will be disseminated through publication in peer-reviewed scientific journals, presentation at conferences and via charity websites. TRIAL REGISTRATION NUMBER: ISRCTN58863784.

Rhizoremediation of hydrocarbon contaminated soil using Luffa aegyptiaca (Mill) and associated fungi.

The potentials of Luffa aegyptiaca and its rhizospheric, non-mycorrhizal fungi in biodegrading and bio-remediating hydrocarbon contaminated soil were investigated in-vitro and in-situ. Biodegradation study was done in two stages: preliminary study using hydrocarbon treated filter paper and in-vitro with Mineral Salt Media (MSM) read on Spectrophotometer at two photo synthetically active wavelengths (530 nm and 620 nm) while rhizoremediation study was done in-situ in contaminated plot of land. Hydrocarbon utilization ability of the fungi and plant were confirmed using total petroleum hydrocarbon (TPH) analysis and gas chromatography mass spectroscopy (GC-MS). Results show differing rates of hydrocarbon utilization by isolated fungi. In-vitro biodegradation study showed that Aspergillus niger, Fusarium solani, Curvularia lunata and Trichoderma harzianum were best in degrading kerosene (78%), diesel (70%), spent engine oil (83%) and crude oil (77%) respectively. Rhizoremediation study using L. aegyptiaca and C. lunata show that remediation was enhanced to 72.15% as against 32.32% and 14% when only the plant or fungus is used respectively. Hydrocarbon accumulation by L. aegyptiaca also decreased in the presence of the fungus. Curvularia lunata is shown in this study to enhance the germination, survival, growth and bioremediation efficiency of L. aegyptiaca in polluted environment.Novelty statement The potentials of Curvularia lunata, a non-mycorrhizal fungi associated with L. aegyptiaca in survival, growth and phytoremediation of petroleum hydrocarbon polluted soil by L. aegyptiaca is highlighted in this study. Luffa aegyptiaca and its associated fungi is shown to bio-remediate petroleum hydrocarbon through phyto-accumulation and rhizosphere effect.

Metabolomic Biomarkers for the Detection of Obesity-Driven Endometrial Cancer.

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) ≥30kg/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.

Long-term multicentre experience of adjuvant radiotherapy for pN3 squamous cell carcinoma of the penis.

OBJECTIVE: To present the long-term adjuvant radiotherapy outcomes of patients with pN3 squamous cell carcinoma of the penis (SCCp) treated at two UK centres. PATIENTS AND METHODS: We conducted a retrospective audit of all pN3 SCCp patients, deemed suitable for adjuvant therapy by a specialist multidisciplinary team at St George's and Leeds Hospitals, who received adjuvant radiotherapy. Primary outcomes were recurrence-free survival (RFS), cancer-specific survival (CSS) and overall survival (OS). Secondary outcomes were time to adjuvant treatment, frequency of in-field recurrence, site and side of recurrence, and dose and schedule of radiotherapy. RESULTS: A total of 146 patients were included: 121 completed radiotherapy, 4 did not complete radiotherapy and 21 did not start it. The median (interquartile range [IQR]) age was 59 (54-70)years. The 5-year RFS was 51%, CSS was 51% and OS was 44%. Adjuvant radiotherapy was started at a median (IQR) of 75 (48-106) days. A dose of 45 Gy in 20 fractions was most commonly used. Of the 125 patients who started adjuvant treatment, 55 relapsed. Of these relapses, 30 occurred in an inguinal or pelvic nodal station and 26 of the 30 were in a radiation field. Relapses in 18 of the 55 cases were in visceral sites only and seven were in both nodal (non-irradiated sites) and visceral sites. Doses of <50 Gy were used more commonly before 2013 and higher doses (>50 Gy) were more commonly used after 2013. CONCLUSIONS: Application of a standard radiotherapy protocol within a centralized supra-network setting has achieved survival outcomes that would appear better than those previously documented for either radiotherapy or chemotherapy in a cohort with solely pN3 disease. The addition of adjuvant chemotherapy may improve these outcomes further. These data suggest that adjuvant radiotherapy has a role to play in the management of men with pN3 SCCp.

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.