Proteomic-based identification of HSP70 as a tumor-associated antigen in ovarian cancer

Protein expression profiling identifies a prognostic model for ovarian cancer

Background

Owing to the high morbidity and mortality, ovarian cancer has seriously endangered female health. Development of reliable models can facilitate prognosis monitoring and help relieve the distress.

Methods

Using the data archived in the TCPA and TCGA databases, proteins having significant survival effects on ovarian cancer patients were screened by univariate Cox regression analysis. Patients with complete information concerning protein expression, survival, and clinical variables were included. A risk model was then constructed by performing multiple Cox regression analysis. After validation, the predictive power of the risk model was assessed. The prognostic effect and the biological function of the model were evaluated using co-expression analysis and enrichment analysis.

Results

394 patients were included in model construction and validation. Using univariate Cox regression analysis, we identified a total of 20 proteins associated with overall survival of ovarian cancer patients (p < 0.01). Based on multiple Cox regression analysis, six proteins (GSK3α/β, HSP70, MEK1, MTOR, BAD, and NDRG1) were used for model construction. Patients in the high-risk group had unfavorable overall survival (p < 0.001) and poor disease-specific survival (p = 0.001). All these six proteins also had survival prognostic effects. Multiple Cox regression analysis demonstrated the risk model as an independent prognostic factor (p < 0.001). In receiver operating characteristic curve analysis, the risk model displayed higher predictive power than age, tumor grade, and tumor stage, with an area under the curve value of 0.789. Analysis of co-expressed proteins and differentially expressed genes based on the risk model further revealed its prognostic implication.

Conclusions

The risk model composed of GSK3α/β, HSP70, MEK1, MTOR, BAD, and NDRG1 could predict survival prognosis of ovarian cancer patients efficiently and help disease management.

Serum Anti-14-3-3 Zeta Autoantibody as a Biomarker for Predicting Hepatocarcinogenesis

Hepatocellular carcinoma (HCC) is a common malignancy worldwide. Alpha-fetoprotein (AFP) is still the only serum biomarker widely used in clinical settings. However, approximately 40% of HCC patients exhibit normal AFP levels, including very early HCC and AFP-negative HCC; for these patients, serum AFP is not applicable as a biomarker of early detection. Thus, there is an urgent need to identify novel biomarkers for patients for whom disease cannot be diagnosed early. In this study, we screened and identified novel proteins in AFP-negative HCC and evaluated the feasibility of using autoantibodies to those protein to predict hepatocarcinogenesis. First, we screened and identified differentially expressed proteins between AFP-negative HCC tissue and adjacent non-tumor liver tissue using SWATH-MS proteome technology. In total, 2,506 proteins were identified with a global false discovery rate of 1%, of which 592 proteins were expressed differentially with 175 upregulated and 417 downregulated (adjusted p-value <0.05, fold-change FC ≥1.5 or ≤0.67) between the tumor and matched benign samples, including 14-3-3 zeta protein. For further serological verification, autoantibodies against 14-3-3 zeta in serum were evaluated using enzyme-linked immunosorbent, Western blotting, and indirect immunofluorescence assays. Five serial serum samples from one patient with AFP-negative HCC showed anti-14-3-3 zeta autoantibody in sera 9 months before the diagnosis of HCC, which gradually increased with an increase in the size of the nodule. Based on these findings, we detected the prevalence of serum anti-14-3-3 zeta autoantibody in liver cirrhosis (LC) patients, which is commonly considered a premalignant liver disease of HCC. We found that the prevalence of autoantibodies against 14-3-3 zeta protein was 16.1% (15/93) in LC patient sera, which was significantly higher than that in patients with chronic hepatitis (0/75, p = 0.000) and normal human sera (1/60, 1.7%, p = 0.01). Therefore, we suggest that anti-14-3-3 zeta autoantibody might be a biomarker for predicting hepatocarcinogenesis. Further follow-up and research of patients with positive autoantibodies will be continued to confirm the relationship between anti-14-3-3 zeta autoantibody and hepatocarcinogenesis.

Drugs Repurposing in High-Grade Serous Ovarian Cancer

BACKGROUND

Ovary Carcinoma (OC) is the most lethal gynecological neoplasm due to the late diagnoses and to the common development of resistance to platinum-based chemotherapy. Thus, novel therapeutic approaches are urgently required. In this regard, the strategy of drug repurposing is becoming attractive. By this approach, the effectiveness of a drug originally developed for another indication is tested in a different pathology. The advantage is that data about pharmacokinetic properties and toxicity are already available. Thus, in principle, it is possible to reduce research costs and to speed up drug usage/marketing.

RESULTS

Here, some noticeable examples of repurposed drugs for OC, such as amiodarone, ruxolitinib, statins, disulfiram, ormeloxifenem, and Quinacrine, are reported. Amiodarone, an antiarrhythmic agent, has shown promising anti-OC activity, although the systemic toxicity should not be neglected. The JAK inhibitor, Ruxolitinib, may be employed particularly in coadministration with standard OC therapy as it synergistically interacts with platinum-based drugs. Particularly interesting is the use of statin which represent one of the most commonly administered drugs in aged population to treat hypercholesterolemia. Disulfiram, employed in the treatment of chronic alcoholism, has shown anti-OC properties. Ormeloxifene, commonly used for contraception, seems to be promising, especially due to the negligible side effects. Finally, Quinacrine used as an antimicrobial and anti-inflammatory drug, is able to downregulate OC cell growth and promote cell death.

CONCLUSION

Whereas further testing in patients are necessary to better clarify the therapeutic potential of repurposed drugs for OC, it is believed that their use, better if combined with OC targeted delivery systems, can significantly contribute to the development of novel and effective anti-OC treatments.

A high-performance microfluidic detection platform to conduct a novel multiple-biomarker panel for ovarian cancer screening

Ovarian cancer is an important leading cause of cancer-related deaths among females, and a single biomarker does not have the sensitivity and specificity required for an effective ovarian cancer screening. Herein, we investigate a high-performance microfluidic detection platform to conduct a novel panel of multiple biomarkers for the early detection of ovarian carcinoma, which include CA125, HE4, OPN, MSLN, Hsp70, CA153, AFP, IL-6, and IL-8 using a microfluidic chip. High-throughput microfluidic chips and graphene oxide-assembled substrate are used to microprint repeatable capture antibody arrays and conduct multiple biomarkers in microscale volume samples. The proposed microfluidic platform achieves an ultralow detection limit of ∼1 pg mL⁻¹ and 0.01 U mL⁻¹ with excellent detection selectivity and a short detection time of 30 min. The analysis of serum biomarkers in 18 ovarian cancer patients and 4 healthy persons indicates a clear subgroup sorting between the high-grade serous ovarian carcinoma, borderline, and benign tumor patients, and healthy persons. The proposed detection platform and the biomarker panel are promising to conduct an early detection of ovarian cancer.

A high-performance microfluidic detection platform is developed to conduct a novel panel of multiple biomarkers for the early detection of ovarian carcinoma, which is promising for the early detection of ovarian cancer.

Heat Shock Proteins and Ovarian Cancer: Important Roles and Therapeutic Opportunities

Ovarian cancer is a serious cause of death in gynecological oncology. Delayed diagnosis and poor survival rates associated with late stages of the disease are major obstacles against treatment efforts. Heat shock proteins (HSPs) are stress responsive molecules known to be crucial in many cancer types including ovarian cancer. Clusterin (CLU), a unique chaperone protein with analogous oncogenic criteria to HSPs, has also been proven to confer resistance to anti-cancer drugs. Indeed, these chaperone molecules have been implicated in diagnosis, prognosis, metastasis and aggressiveness of various cancers. However, relative to other cancers, there is limited body of knowledge about the molecular roles of these chaperones in ovarian cancer. In the current review, we shed light on the diverse roles of HSPs as well as related chaperone proteins like CLU in the pathogenesis of ovarian cancer and elucidate their potential as effective drug targets.

Systematic review: Tumor-associated antigen autoantibodies and ovarian cancer early detection

OBJECTIVES

Tumor-associated autoantibodies (AAbs), produced as an immune response to tumor-associated antigens (TAAs), are a novel pathway of early detection markers.

METHODS

We conducted a systematic review on AAbs and ovarian cancer to summarize the diagnostic performance of individual AAbs and AAb panels. A total of 29 studies including 85 AAbs were included; 27 of the studies were conducted in prevalent cases and cancer-free controls and 2 investigations included pre-diagnosis samples. The majority of studies were hypothesis-driven, evaluating AAbs to target TAAs; 10 studies used screening approaches such as serological expression cloning (SEREX) and nucleic acid-programmable protein arrays (NAPPA).

RESULTS

The highest sensitivities for individual AAbs were reported for RhoGDI-AAbs (89.5%) and TUBA1C-AAbs (89%); however, specificity levels were relatively low (80% and 75%, respectively). High sensitivities at high specificities were reported for HOXA7-AAbs for detection of moderately differentiated ovarian tumors (66.7% sensitivity at 100% specificity) and IL8-AAbs in stage I-II ovarian cancer (65.5% sensitivity at 98% specificity). A panel of 11 AAbs (ICAM3, CTAG2, p53, STYXL1, PVR, POMC, NUDT11, TRIM39, UHMK1, KSR1, and NXF3) provided 45% sensitivity at 98% specificity for serous ovarian cancer, when at least 2 AAbs were above a threshold of 95% specificity. Twelve of the AAbs identified in this review were investigated in more than one study. Data on diagnostic discrimination by tumor histology and stage at diagnosis are sparse. Limited data suggest select AAb markers improve diagnostic discrimination when combined with markers such as CA125 and HE4.

CONCLUSIONS

AAbs for ovarian cancer early detection is an emerging area, and large-scale, prospective investigations considering histology and stage are required for discovery and validation. However, data to date suggests panels of AAbs may eventually reach sufficient diagnostic discrimination to allow earlier detection of disease as a complement to existing markers and transvaginal ultrasound.