The Skp2-SCF E3 ligase regulates Akt ubiquitination, glycolysis, herceptin sensitivity, and tumorigenesis.

Akt kinase plays a central role in cell growth, metabolism, and tumorigenesis. The TRAF6 E3 ligase orchestrates IGF-1-mediated Akt ubiquitination and activation. Here, we show that Akt ubiquitination is also induced by activation of ErbB receptors; unexpectedly, and in contrast to IGF-1 induced activation, the Skp2 SCF complex, not TRAF6, is a critical E3 ligase for ErbB-receptor-mediated Akt ubiquitination and membrane recruitment in response to EGF. Skp2 deficiency impairs Akt activation, Glut1 expression, glucose uptake and glycolysis, and breast cancer progression in various tumor models. Moreover, Skp2 overexpression correlates with Akt activation and breast cancer metastasis and serves as a marker for poor prognosis in Her2-positive patients. Finally, Skp2 silencing sensitizes Her2-overexpressing tumors to Herceptin treatment. Our study suggests that distinct E3 ligases are utilized by diverse growth factors for Akt activation and that targeting glycolysis sensitizes Her2-positive tumors to Herceptin treatment.

Autoantibodies, antigen-autoantibody complexes and antigens complement CA125 for early detection of ovarian cancer.

BACKGROUND: Multiple antigens, autoantibodies (AAb), and antigen-autoantibody (Ag-AAb) complexes were compared for their ability to complement CA125 for early detection of ovarian cancer. METHODS: Twenty six biomarkers were measured in a single panel of sera from women with early stage (I-II) ovarian cancers (n = 64), late stage (III-IV) ovarian cancers (186), benign pelvic masses (200) and from healthy controls (502), and then split randomly (50:50) into a training set to identify the most promising classifier and a validation set to compare its performance to CA125 alone. RESULTS: Eight biomarkers detected ≥ 8% of early stage cases at 98% specificity. A four-biomarker panel including CA125, HE4, HE4 Ag-AAb and osteopontin detected 75% of early stage cancers in the validation set from among healthy controls compared to 62% with CA125 alone (p = 0.003) at 98% specificity. The same panel increased sensitivity for distinguishing early-stage ovarian cancers from benign pelvic masses by 25% (p = 0.0004) at 95% specificity. From 21 autoantibody candidates, 3 AAb (anti-p53, anti-CTAG1 and annt-Il-8) detected 22% of early stage ovarian cancers, potentially lengthening lead time prior to diagnosis. CONCLUSION: A four biomarker panel achieved greater sensitivity at the same specificity for early detection of ovarian cancer than CA125 alone.

Skp2-dependent ubiquitination and activation of LKB1 is essential for cancer cell survival under energy stress.

LKB1 is activated by forming a heterotrimeric complex with STRAD and MO25. Recent studies suggest that LKB1 has pro-oncogenic functions, besides acting as a tumor suppressor. How the LKB1 activity is maintained and how LKB1 regulates cancer development are largely unclear. Here we show that K63-linked LKB1 polyubiquitination by Skp2-SCF ubiquitin ligase is critical for LKB1 activation by maintaining LKB1-STRAD-MO25 complex integrity. We further demonstrate that oncogenic Ras acts upstream of Skp2 to promote LKB1 polyubiquitination by activating Skp2-SCF ubiquitin ligase. Moreover, Skp2-mediated LKB1 polyubiquitination is required for energy-stress-induced cell survival. We also detected overexpression of Skp2 and LKB1 in late-stage hepatocellular carcinoma (HCC), and their overexpression predicts poor survival outcomes. Finally, we show that Skp2-mediated LKB1 polyubiquitination is important for HCC tumor growth in vivo. Our study provides new insights into the upstream regulation of LKB1 activation and suggests a potential target, the Ras/Skp2/LKB1 axis, for cancer therapy.

Human epididymis protein 4 antigen-autoantibody complexes complement cancer antigen 125 for detecting early-stage ovarian cancer.

BACKGROUND: Early detection of ovarian cancer could significantly improve patient outcomes. Cancer antigen 125 (CA 125) is elevated in sera from approximately 60% of patients with early-stage (I/II) disease. Sensitivity might be improved through the combination of CA 125 with other biomarkers. Among potential biomarkers, antigen-autoantibody (Ag-AAb) complexes have received relatively little attention. METHODS: Luminex-based immunoassays were used to measure human epididymis protein 4 (HE4), anti-HE4 autoantibody, and HE4 Ag-AAb complexes in sera from patients with early- (n = 73) and late-stage ovarian cancers (n = 49) at the time of diagnosis and from asymptomatic women with (n = 15) or without ovarian cancer (n = 212) enrolled in the Normal Risk Ovarian Cancer Screening Study. RESULTS: At 98% specificity for healthy, asymptomatic women, 7% of patients with early-stage (I/II) ovarian cancer and 4% of patients with late-stage (III/IV) disease had elevated levels of HE4 autoantibody, whereas elevated levels of HE4 Ag-AAb complexes were detected in sera from 38% of early-stage cases and 31% of late-stage cases. Complementarity was observed in receiver operating characteristic (ROC) curves between HE4 Ag-AAb complexes and CA 125 levels in early-stage ovarian cancer (P < .001). CA 125 detected 63% of cases, and a combination of CA 125 and HE4 Ag-AAb complexes detected 81%. Complementarity was also observed in ROC curves for an independent validation set with 69 early-stage patients (P = .039). HE4 Ag-AAb complexes were detected in serial preclinical serum samples from women destined to develop ovarian cancer: they correlated with CA 125 but did not provide a lead time. CONCLUSIONS: HE4 Ag-AAb complexes could complement CA 125 in detecting a higher fraction of early-stage ovarian cancers.

Toll-like receptor-mediated IRE1α activation as a therapeutic target for inflammatory arthritis.

In rheumatoid arthritis (RA), macrophage is one of the major sources of inflammatory mediators. Macrophages produce inflammatory cytokines through toll-like receptor (TLR)-mediated signalling during RA. Herein, we studied macrophages from the synovial fluid of RA patients and observed a significant increase in activation of inositol-requiring enzyme 1α (IRE1α), a primary unfolded protein response (UPR) transducer. Myeloid-specific deletion of the IRE1α gene protected mice from inflammatory arthritis, and treatment with the IRE1α-specific inhibitor 4U8C attenuated joint inflammation in mice. IRE1α was required for optimal production of pro-inflammatory cytokines as evidenced by impaired TLR-induced cytokine production in IRE1α-null macrophages and neutrophils. Further analyses demonstrated that tumour necrosis factor (TNF) receptor-associated factor 6 (TRAF6) plays a key role in TLR-mediated IRE1α activation by catalysing IRE1α ubiquitination and blocking the recruitment of protein phosphatase 2A (PP2A), a phosphatase that inhibits IRE1α phosphorylation. In summary, we discovered a novel regulatory axis through TRAF6-mediated IRE1α ubiquitination in regulating TLR-induced IRE1α activation in pro-inflammatory cytokine production, and demonstrated that IRE1α is a potential therapeutic target for inflammatory arthritis.

Skp2 targeting suppresses tumorigenesis by Arf-p53-independent cellular senescence.

Cellular senescence has been recently shown to have an important role in opposing tumour initiation and promotion. Senescence induced by oncogenes or by loss of tumour suppressor genes is thought to critically depend on induction of the p19(Arf)-p53 pathway. The Skp2 E3-ubiquitin ligase can act as a proto-oncogene and its aberrant overexpression is frequently observed in human cancers. Here we show that although Skp2 inactivation on its own does not induce cellular senescence, aberrant proto-oncogenic signals as well as inactivation of tumour suppressor genes do trigger a potent, tumour-suppressive senescence response in mice and cells devoid of Skp2. Notably, Skp2 inactivation and oncogenic-stress-driven senescence neither elicit activation of the p19(Arf)-p53 pathway nor DNA damage, but instead depend on Atf4, p27 and p21. We further demonstrate that genetic Skp2 inactivation evokes cellular senescence even in oncogenic conditions in which the p19(Arf)-p53 response is impaired, whereas a Skp2-SCF complex inhibitor can trigger cellular senescence in p53/Pten-deficient cells and tumour regression in preclinical studies. Our findings therefore provide proof-of-principle evidence that pharmacological inhibition of Skp2 may represent a general approach for cancer prevention and therapy.

Evaluating Urine Cytology Slide Digitization Efficiency: A Comparative Study Using an Artificial Intelligence-Based Heuristic Scanning Simulation and Multiple Z-Plane Scanning.

INTRODUCTION: Digitizing cytology slides presents challenges because of their three-dimensional features and uneven cell distribution. While multi-Z-plane scan is a prevalent solution, its adoption in clinical digital cytopathology is hindered by prolonged scanning times, increased image file sizes, and the requirement for cytopathologists to review multiple Z-plane images. METHODS: This study presents heuristic scan as a novel solution, using an artificial intelligence (AI)-based approach specifically designed for cytology slide scanning as an alternative to the multi-Z-plane scan. Both the 21 Z-plane scan and the heuristic scan simulation methods were used on 52 urine cytology slides from three distinct cytopreparations (Cytospin, ThinPrep, and BD CytoRich™ [SurePath]), generating whole-slide images (WSIs) via the Leica Aperio AT2 digital scanner. The AI algorithm inferred the WSI from 21 Z-planes to quantitate the total number of suspicious for high-grade urothelial carcinoma or more severe cells (SHGUC+) cells. The heuristic scan simulation calculated the total number of SHGUC+ cells from the 21 Z-plane scan data. Performance metrics including SHGUC+ cell coverage rates (calculated by dividing the number of SHGUC+ cells identified in multiple Z-planes or heuristic scan simulation by the total SHGUC+ cells in the 21 Z-planes for each WSI), scanning time, and file size were analyzed to compare the performance of each scanning method. The heuristic scan's metrics were linearly estimated from the 21 Z-plane scan data. Additionally, AI-aided interpretations of WSIs with scant SHGUC+ cells followed The Paris System guidelines and were compared with original diagnoses. RESULTS: The heuristic scan achieved median SHGUC+ cell coverage rates similar to 5 Z-plane scans across three cytopreparations (0.78-0.91 vs. 0.75-0.88, p = 0.451-0.578). Notably, it substantially reduced both scanning time (137.2-635.0 s vs. 332.6-1,278.8 s, p < 0.05) and image file size (0.51-2.10 GB vs. 1.16-3.10 GB, p < 0.05). Importantly, the heuristic scan yielded higher rates of accurate AI-aided interpretations compared to the single Z-plane scan (62.5% vs. 37.5%). CONCLUSION: We demonstrated that the heuristic scan offers a cost-effective alternative to the conventional multi-Z-plane scan in digital cytopathology. It achieves comparable SHGUC+ cell capture rates while reducing both scanning time and image file size, promising to aid digital urine cytology interpretations with a higher accuracy rate compared to the conventional single (optimal) plane scan. Further studies are needed to assess the integration of this new technology into compatible digital scanners for practical cytology slide scanning.

Evaluating artificial intelligence-enhanced digital urine cytology for bladder cancer diagnosis.

BACKGROUND: This study evaluated the diagnostic effectiveness of the AIxURO platform, an artificial intelligence-based tool, to support urine cytology for bladder cancer management, which typically requires experienced cytopathologists and substantial diagnosis time. METHODS: One cytopathologist and two cytotechnologists reviewed 116 urine cytology slides and corresponding whole-slide images (WSIs) from urology patients. They used three diagnostic modalities: microscopy, WSI review, and AIxURO, per The Paris System for Reporting Urinary Cytology (TPS) criteria. Performance metrics, including TPS-guided and binary diagnosis, inter- and intraobserver agreement, and screening time, were compared across all methods and reviewers. RESULTS: AIxURO improved diagnostic accuracy by increasing sensitivity (from 25.0%-30.6% to 63.9%), positive predictive value (PPV; from 21.6%-24.3% to 31.1%), and negative predictive value (NPV; from 91.3%-91.6% to 95.3%) for atypical urothelial cell (AUC) cases. For suspicious for high-grade urothelial carcinoma (SHGUC) cases, it improved sensitivity (from 15.2%-27.3% to 33.3%), PPV (from 31.3%-47.4% to 61.1%), and NPV (from 91.6%-92.7% to 93.3%). Binary diagnoses exhibited an improvement in sensitivity (from 77.8%-82.2% to 90.0%) and NPV (from 91.7%-93.4% to 95.8%). Interobserver agreement across all methods showed moderate consistency (κ = 0.57-0.61), with the cytopathologist demonstrating higher intraobserver agreement than the two cytotechnologists across the methods (κ = 0.75-0.88). AIxURO significantly reduced screening time by 52.3%-83.2% from microscopy and 43.6%-86.7% from WSI review across all reviewers. Screening-positive (AUC+) cases required more time than negative cases across all methods and reviewers. CONCLUSIONS: AIxURO demonstrates the potential to improve both sensitivity and efficiency in bladder cancer diagnostics via urine cytology. Its integration into the cytopathological screening workflow could markedly decrease screening times, which would improve overall diagnostic processes.

An Artificial Intelligence-assisted Diagnostic System Improves Upper Urine Tract Cytology Diagnosis.

BACKGROUND/AIM: To evaluate efficacy of the AIxURO system, a deep learning-based artificial intelligence (AI) tool, in enhancing the accuracy and reliability of urine cytology for diagnosing upper urinary tract cancers. MATERIALS AND METHODS: One hundred and eighty-five cytology samples of upper urine tract were collected and categorized according to The Paris System for Reporting Urinary Cytology (TPS), yielding 168 negative for High-Grade Urothelial Carcinoma (NHGUC), 14 atypical urothelial cells (AUC), 2 suspicious for high-grade urothelial carcinoma (SHGUC), and 1 high-grade urothelial carcinoma (HGUC). The AIxURO system, trained on annotated cytology images, was employed to analyze these samples. Independent assessments by a cytotechnologist and a cytopathologist were conducted to validate the initial AIxURO assessment. RESULTS: AIxURO identified discrepancies in 37 of the 185 cases, resulting in a 20% discrepancy rate. The cytotechnologist achieved an accuracy of 85% for NHGUC and 21.4% for AUC, whereas the cytopathologist attained accuracies of 95% for NHGUC and 85.7% for AUC. The cytotechnologist exhibited overcall rates of roughly 15% and undercall rates of greater than 50%, while the cytopathologist showed profoundly lower miscall rates from both undercall and overcall. AIxURO significantly enhanced diagnostic accuracy and consistency, particularly in complex cases involving atypical cells. CONCLUSION: AIxURO can improve the accuracy and reliability of cytology diagnosis for upper urine tract urothelial carcinomas by providing precise detection on atypical urothelial cells and reducing subjectivity in assessments. The integration of AIxURO into clinical practice can significantly ameliorate diagnostic outcomes, highlighting the synergistic potential of AI technology and human expertise in cytology.

Comparative evaluation of slide scanners, scan settings, and cytopreparations for digital urine cytology.

Background: Acquiring well-focused digital images of cytology slides with scanners can be challenging due to the 3-dimensional nature of the slides. This study evaluates performances of whole-slide images (WSIs) obtained from 2 different cytopreparations by 2 distinct scanners with 3 focus modes. Methods: Fourteen urine specimens were collected from patients with urothelial carcinoma. Each specimen was equally divided into 2 portions, prepared with Cytospin and ThinPrep methods and scanned for WSIs using Leica (Aperio AT2) and Hamamatsu (NanoZoomer S360) scanners, respectively. The scan settings included 3 focus modes (default, semi-auto, and manual) for single-layer scanning, along with a manual focus mode for 21 Z-layers scanning. Performance metrics were evaluated including scanning success rate, artificial intelligence (AI) algorithm-inferred atypical cell numbers and coverage rate (atypical cell numbers in single or multiple Z-layers divided by the total atypical cell numbers in 21 Z-layers), scanning time, and image file size. Results: The default mode had scanning success rates of 85.7% or 92.9%, depending on the scanner used. The semi-auto mode increased success to 92.9% or 100%, and manual even further to 100%. However, these changes did not affect the standardized median atypical cell numbers and coverage rates. The selection of scanners, cytopreparations, and Z-stacking influenced standardized median atypical cell numbers and coverage rates, scanning times, and image file sizes. Discussion: Both scanners showed satisfactory scanning. We recommend using semi-auto or manual focus modes to achieve a scanning success rate of up to 100%. Additionally, a minimum of 9-layer Z-stacking at 1 µm intervals is required to cover 80% of atypical cells. These advanced focus methods do not impact the number of atypical cells or their coverage rate. While Z-stacking enhances the AI algorithm's inferred quantity and coverage rates of atypical cells, it simultaneously results in longer scanning times and larger image file sizes.

The role of Skp2 in hematopoietic stem cell quiescence, pool size, and self-renewal.

Although the maintenance of HSC quiescence and self-renewal are critical for controlling stem cell pool and transplantation efficiency, the mechanisms by which they are regulated remain largely unknown. Understanding the factors controlling these processes may have important therapeutic potential for BM failure and cancers. Here, we show that Skp2, a component of the Skp2 SCF complex, is an important regulator for HSC quiescence, frequency, and self-renewal capability. Skp2 deficiency displays a marked enhancement of HSC populations through promoting cell cycle entry independently of its role on apoptosis. Surprisingly, Skp2 deficiency in HSCs reduces quiescence and displays increased HSC cycling and proliferation. Importantly, loss of Skp2 not only increases HSC populations and long-term reconstitution ability but also rescues the defect in long-term reconstitution ability of HSCs on PTEN inactivation. Mechanistically, we show that Skp2 deficiency induces Cyclin D1 gene expression, which contributes to an increase in HSC cycling. Finally, we demonstrate that Skp2 deficiency enhances sensitivity of Lin(-) Sca-1(+) c-kit(+) cells and leukemia cells to chemotherapy agents. Our findings show that Skp2 is a novel regulator for HSC quiescence and self-renewal and that targeting Skp2 may have therapeutic implications for BM transplantation and leukemia stem cell treatment.

Amyloid-like p53 as prognostic biomarker in serous ovarian cancer-a study of the OVCAD consortium.

TP53 is the most commonly mutated gene in cancer and has been shown to form amyloid-like aggregates, similar to key proteins in neurodegenerative diseases. Nonetheless, the clinical implications of p53 aggregation remain unclear. Here, we investigated the presence and clinical relevance of p53 aggregates in serous ovarian cancer (OC). Using the p53-Seprion-ELISA, p53 aggregates were detected in 46 out of 81 patients, with a detection rate of 84.3% in patients with missense mutations. High p53 aggregation was associated with prolonged progression-free survival. We found associations of overall survival with p53 aggregates, but they did not reach statistical significance. Interestingly, p53 aggregation was significantly associated with elevated levels of p53 autoantibodies and increased apoptosis, suggesting that high levels of p53 aggregates may trigger an immune response and/or exert a cytotoxic effect. To conclude, for the first time, we demonstrated that p53 aggregates are an independent prognostic marker in serous OC. P53-targeted therapies based on the amount of these aggregates may improve the patient's prognosis.

Critical role of monoubiquitination of histone H2AX protein in histone H2AX phosphorylation and DNA damage response.

DNA damage response is an important surveillance mechanism used to maintain the integrity of the human genome in response to genotoxic stress. Histone variant H2AX is a critical sensor that undergoes phosphorylation at serine 139 upon genotoxic stress, which provides a docking site to recruit the mediator of DNA damage checkpoint protein 1 (MDC1) and DNA repair protein complex to sites of DNA breaks for DNA repair. Here, we show that monoubiquitination of H2AX is induced upon DNA double strand breaks and plays a critical role in H2AX Ser-139 phosphorylation (γ-H2AX), in turn facilitating the recruitment of MDC1 to DNA damage foci. Mechanistically, we show that monoubiquitination of H2AX induced by RING finger protein 2 (RNF2) is required for the recruitment of active ataxia telangiectasia mutated to DNA damage foci, thus affecting the formation of γ-H2AX. Importantly, a defect in monoubiquitination of H2AX profoundly enhances ionizing radiation sensitivity. Our study therefore suggests that monoubiquitination of H2AX is an important step for DNA damage response and may have important clinical implications for the treatment of cancers.

Evaluation of an artificial intelligence algorithm for assisting the Paris System in reporting urinary cytology: A pilot study.

BACKGROUND: The Paris System for Reporting Urinary Cytology (TPS) has been shown to improve bladder cancer diagnosis. Advances in artificial intelligence (AI) may assist and improve the clinical workflow by applying TPS in routine diagnostic services. METHODS: A deep-learning-based algorithm was developed to identify urothelial cancer candidate cells using whole-slide images (WSIs). In the testing cohort, 131 urine cytology slides were retrospectively retrieved and analyzed using this AI algorithm. The authors compared the performance of one cytopathologist and two cytotechnologists using AI-assisted digital urine cytology. Then, the AI-assisted WSIs were evaluated in the clinical workflow. The cytopathologist first made a diagnosis by reviewing the AI-inferred WSIs and quantitative data (nuclear-to-cytoplasmic ratio and nuclear size) for each sample. After a washout period, the same cytopathologist made a diagnosis for the same samples using direct microscopy. All diagnosis results were compared with the expert panel consensus. RESULTS: The AI-assisted diagnosis by the two cytotechnologists and the one cytopathologist demonstrated performance results that were comparable to the expert panel consensus (sensitivity, 79.5% and 82.1% vs. 92.3%, respectively; specificity, 100% and 98.9% vs. 100%, respectively). Furthermore, the performance of the AI-assisted WSIs compared with the microscopic diagnosis by the cytopathologist demonstrated superior sensitivity (92.3% vs. 87.2%) and negative predictive value (96.8% vs. 94.8%). In addition, the AI-assisted reporting demonstrated near perfect agreement with the expert panel consensus (κ = 0.944) and the microscopic diagnosis (κ = 0.862). CONCLUSIONS: The AI algorithm developed by the authors effectively assisted TPS-based reporting by providing AI-inferred WSIs and quantitative data.

Multi-Marker Longitudinal Algorithms Incorporating HE4 and CA125 in Ovarian Cancer Screening of Postmenopausal Women.

Longitudinal CA125 algorithms are the current basis of ovarian cancer screening. We report on longitudinal algorithms incorporating multiple markers. In the multimodal arm of United Kingdom Collaborative Trial of Ovarian Cancer Screening (UKCTOCS), 50,640 postmenopausal women underwent annual screening using a serum CA125 longitudinal algorithm. Women (cases) with invasive tubo-ovarian cancer (WHO 2014) following outcome review with stored annual serum samples donated in the 5 years preceding diagnosis were matched 1:1 to controls (no invasive tubo-ovarian cancer) in terms of the number of annual samples and age at randomisation. Blinded samples were assayed for serum human epididymis protein 4 (HE4), CA72-4 and anti-TP53 autoantibodies. Multimarker method of mean trends (MMT) longitudinal algorithms were developed using the assay results and trial CA125 values on the training set and evaluated in the blinded validation set. The study set comprised of 1363 (2-5 per woman) serial samples from 179 cases and 181 controls. In the validation set, area under the curve (AUC) and sensitivity of longitudinal CA125-MMT algorithm were 0.911 (0.871-0.952) and 90.5% (82.5-98.6%). None of the longitudinal multi-marker algorithms (CA125-HE4, CA125-HE4-CA72-4, CA125-HE4-CA72-4-anti-TP53) performed better or improved on lead-time. Our population study suggests that longitudinal HE4, CA72-4, anti-TP53 autoantibodies adds little value to longitudinal serum CA125 as a first-line test in ovarian cancer screening of postmenopausal women.

Proteome Profiling Uncovers an Autoimmune Response Signature That Reflects Ovarian Cancer Pathogenesis.

Harnessing the immune response to tumor antigens in the form of autoantibodies, which occurs early during tumor development, has relevance to the detection of cancer at early stages. We conducted an initial screen of antigens associated with an autoantibody response in serous ovarian cancer using recombinant protein arrays. The top 25 recombinants that exhibited increased reactivity with cases compared to controls revealed TP53 and MYC, which are ovarian cancer driver genes, as major network nodes. A mass spectrometry based independent analysis of circulating immunoglobulin (Ig)-bound proteins in ovarian cancer and of ovarian cancer cell surface MHC-II bound peptides also revealed a TP53-MYC related network of antigens. Our findings support the occurrence of a humoral immune response to antigens linked to ovarian cancer driver genes that may have utility for early detection applications.

Osteopontin, Macrophage Migration Inhibitory Factor and Anti-Interleukin-8 Autoantibodies Complement CA125 for Detection of Early Stage Ovarian Cancer.

Early detection of ovarian cancer promises to reduce mortality. While serum CA125 can detect more than 60% of patients with early stage (I-II) disease, greater sensitivity might be observed with a panel of biomarkers. Ten protein antigens and 12 autoantibody biomarkers were measured in sera from 76 patients with early stage (I-II), 44 patients with late stage (III-IV) ovarian cancer and 200 healthy participants in the normal risk ovarian cancer screening study. A four-biomarker panel (CA125, osteopontin (OPN), macrophage inhibitory factor (MIF), and anti-IL-8 autoantibodies) detected 82% of early stage cancers compared to 65% with CA125 alone. In early stage subjects the area under the receiver operating characteristic curve (AUC) for the panel (0.985) was significantly greater (p < 0.001) than the AUC for CA125 alone (0.885). Assaying an independent validation set of sera from 71 early stage ovarian cancer patients, 45 late stage patients and 131 healthy women, AUC in early stage disease was improved from 0.947 with CA125 alone to 0.974 with the four-biomarker panel (p = 0.015). Consequently, OPN, MIF and IL-8 autoantibodies can be used in combination with CA125 to distinguish ovarian cancer patients from healthy controls with high sensitivity. Osteopontin appears to be a robust biomarker that deserves further evaluation in combination with CA125.

Bortezomib enhances radiosensitivity in oral cancer through inducing autophagy-mediated TRAF6 oncoprotein degradation.

BACKGROUND: Oral squamous cell carcinoma (OSCC) is a malignant tumor that may occur anywhere within the oral cavity. The survival rate of OSCC patients has not improved over the past decades due to its heterogeneous etiology, genetic aberrations, and treatment outcomes. We investigated the role of tumor necrosis factor receptor-associated factor 6 (TRAF6) in OSCC cells treated with bortezomib (a proteasome inhibitor) combined with irradiation (IR) treatment. METHODS: The effects of combined treatment in OSCC cells were investigated using assays of cell viability, autophagy, apoptosis, western blotting, and immunofluorescence staining. The ubiquitination of proteins was analyzed by immunoprecipitation. Stable knockdown of TRAF6 in OSCC cells was constructed with lentivirus. The xenograft murine models were used to observe tumor growth. RESULTS: We found synergistic effects of bortezomib and IR on the viability of human oral cancer cells. The combination of bortezomib and IR treatment induced autophagic cell death. Furthermore, bortezomib inhibited IR-induced TRAF6 ubiquitination and inhibited TRAF6-mediated Akt activation. Bortezomib reduced TRAF6 protein expression through autophagy-mediated lysosomal degradation. TRAF6 played an oncogenic role in tumorigenesis of human oral cancer cells and oral tumor growth was suppressed by bortezomib and IR treatment. In addition, OSCC patients with expression of TRAF6 showed a trend towards poorer cancer-specific survival when compared with patients without TRAF6 expression. CONCLUSIONS: A combination of a proteasome inhibitor, IR treatment and TRAF6 inhibition could be a novel therapeutic strategy in OSCC.

The role of biomarkers in the management of epithelial ovarian cancer.

INTRODUCTION: Despite advances in surgery and chemotherapy for ovarian cancer, 70% of women still succumb to the disease. Biomarkers have contributed to the management of ovarian cancer by monitoring response to treatment, detecting recurrence, distinguishing benign from malignant pelvic masses and attempting to detect disease at an earlier stage. Areas covered: This review focuses on recent advances in biomarkers and imaging for management of ovarian cancer with particular emphasis on early detection. Relevant literature has been reviewed and analyzed. Expert commentary: Rising or persistent CA125 blood levels provide a highly specific biomarker for epithelial ovarian cancer, but not an optimally sensitive biomarker. Addition of HE4, CA 72.4, anti-TP53 autoantibodies and other biomarkers can increase sensitivity for detecting early stage or recurrent disease. Detecting disease recurrence will become more important as more effective therapy is developed. Early detection will require the development not only of biomarker panels, but also of more sensitive and specific imaging strategies. Effective biomarker strategies are already available for distinguishing benign from malignant pelvic masses, but their use in identifying and referring patients with probable ovarian cancer to gynecologic oncologists for cytoreductive operations must be encouraged.