Serum expression of tumor marker CA242 in patients with different gynecological diseases

OBJECTIVE

The aim of this study was to investigate the serum levels of CA242 in different types of gynecological diseases and its clinical significance.

METHODS

A total of 1021 patients with gynecological diseases and 499 healthy female controls were included in the study. The serum CA242 levels were detected and median value, -log10P value, and positive rate were calculated. Serum CA125 and HE4 levels of patients with ovarian lesions were measured, and the predictive value for ovarian cancer was statistically analyzed.

RESULTS

Higher serum CA242 levels were observed in patients with mature teratoma, ovarian cancer, and other gynecological tumor diseases than in healthy controls. In contrast, the CA242 levels in patients with cervical intraepithelial neoplasia, uterine polyps, or endometrial hyperplasia were comparable to that of controls. Moreover, serum CA242 expression was increased in malignant uterine and ovarian diseases compared with benign ones (P < .05). Specifically, combining CA242, CA125, and HE4 yielded a higher area under the receiver operating characteristic curve than single biomarkers (P < .05).

CONCLUSION

Heterogeneous increases in tumor marker CA242 expression levels are observed in different gynecological diseases, suggesting its potential value for clinical diagnosis.

Tumor Markers and Their Diagnostic Significance in Ovarian Cancer

Ovarian cancer (OC) is characterized by silent progression and late-stage diagnosis. It is critical to detect and accurately diagnose the disease early to improve survival rates. Tumor markers have emerged as valuable tools in the diagnosis and management of OC, offering non-invasive and cost-effective options for screening, monitoring, and prognosis.

PURPOSE

This paper explores the diagnostic importance of various tumor markers including CA-125, CA15-3, CA 19-9, HE4,hCG, inhibin, AFP, and LDH, and their impact on disease monitoring and treatment response assessment.

METHODS

Article searches were performed on PubMed, Scopus, and Google Scholar. Keywords used for the searching process were "Ovarian cancer", "Cancer biomarkers", "Early detection", "Cancer diagnosis", "CA-125","CA 15-3","CA 19-9", "HE4","hCG", "inhibin", "AFP", "LDH", and others.

RESULTS

HE4, when combined with CA-125, shows improved sensitivity and specificity, particularly in early-stage detection. Additionally, hCG holds promise as a prognostic marker, aiding treatment response prediction and outcome assessment. Novel markers like microRNAs, DNA methylation patterns, and circulating tumor cells offer potential for enhanced diagnostic accuracy and personalized management. Integrating these markers into a comprehensive panel may improve sensitivity and specificity in ovarian cancer diagnosis. However, careful interpretation of tumor marker results is necessary, considering factors such as age, menopausal status, and comorbidities. Further research is needed to validate and refine diagnostic algorithms, optimizing the clinical significance of tumor markers in ovarian cancer management. In conclusion, tumor markers such as CA-125, CA15-3, CA 19-9, HE4, and hCG provide valuable insights into ovarian cancer diagnosis, monitoring, and prognosis, with the potential to enhance early detection.

Application of Nonlinear Models Combined with Conventional Laboratory Indicators for the Diagnosis and Differential Diagnosis of Ovarian Cancer

Existing biomarkers for ovarian cancer lack sensitivity and specificity. We compared the diagnostic efficacy of nonlinear machine learning and linear statistical models for diagnosing ovarian cancer using a combination of conventional laboratory indicators. We divided 901 retrospective samples into an ovarian cancer group and a control group, comprising non-ovarian malignant gynecological tumor (NOMGT), benign gynecological disease (BGD), and healthy control subgroups. Cases were randomly assigned to training and internal validation sets. Two linear (logistic regression (LR) and Fisher's linear discriminant (FLD)) and three nonlinear models (support vector machine (SVM), random forest (RF), and artificial neural network (ANN)) were constructed using 22 conventional laboratory indicators and three demographic characteristics. Model performance was compared. In an independent prospectively recruited validation set, the order of diagnostic efficiency was RF, SVM, ANN, FLD, LR, and carbohydrate antigen 125 (CA125)-only (AUC, accuracy: 0.989, 95.6%; 0.985, 94.4%; 0.974, 93.4%; 0.915, 82.1%; 0.859, 80.1%; and 0.732, 73.0%, respectively). RF maintained satisfactory classification performance for identifying different ovarian cancer stages and for discriminating it from NOMGT-, BGD-, or CA125-positive control. Nonlinear models outperformed linear models, indicating that nonlinear machine learning models can efficiently use conventional laboratory indicators for ovarian cancer diagnosis.

Gene polymorphisms of interleukin 10 (− 819 C/T and − 1082 G/A) in women with ovarian cancer

Background

Ovarian cancer (OC) is the leading cause of death associated with gynecologic cancer. IL-10 plays an important role in tumorigenesis. We investigated IL-10 gene polymorphisms in OC patients. The current case–control study screened forty-eight women with OC and forty-eight healthy women who did not have OC. The genotyping of SNPs (− 1082 G > A; rs1800896 and − 819 C > T; rs1800871) of the IL-10 gene was done by tetra primers sequence-specific primer polymerase chain reaction (SSP-PCR) technique. The plasma levels of IL-10 were measured using an enzyme-linked immunosorbent assay (ELISA).

Results

For IL-10 (− 1082 G/A) polymorphism, the G (wild allele) was significantly associated with increasing the risk of OC (OR = 2.054 with CI = 1.154–3.657; P < 0.05), while the A (variant allele) and AA genotype was significantly associated with decreasing the risk of OC (OR = 0.487 with CI = 0.273–0.867; P < 0.05) and (OR = 0.15; 95% CI = 0.04–0.63; P < 0.05), respectively. For IL-10 (− 819C/T) polymorphisms, the T allele (variant allele) and (TT, CT genotypes) were significantly associated with increasing the risk of OC (OR = 2.800 with 95% CI = 1.577–5.037; P < 0.05), (OR = 18.33 with 95% CI = 3.46–97.20; P < 0.001), and (OR = 9.44 with 95% CI = 2.52–35.40; P < 0.001), respectively, while the C (wild allele) was significantly associated with decreasing the risk of OC (OR = 0.357 with 95% CI = 0.199–0.642; P < 0.05). The haplotype analysis for (− 1082 G > A and − 819 C > T shows the GT haplotype was significantly associated with increasing the risk of OC (OR = 50.09 with CI = 6.34–395.92; P < 0.001). OC was substantially correlated with IL-10 level (r = 0.457; p < 0.001). There is no linkage disequilibrium (LD) between IL 10 − 1082 G/A and IL 10 − 819 C/T (D′ = 0.1315, r2 = 0.016; P = NS). A statistically significant positive relationship existed between IL-10 and CA125 and ALT (P < 0.05). IL-10 and albumin showed a strong negative association (P < 0.05), whereas the correlation of IL10 plasma level with BUN, AST, T. Bil., TLC, PLT, Cr., and HB has not any significant value (P > 0.05).

Conclusions

Overall, this study supports an association of IL-10 (− 1082 G/A and − 819C/T) polymorphisms with the risk of ovarian cancer.

Crystal-reconstructed BiVO4 semiconductor photoelectrochemical sensor for ultra-sensitive tumor biomarker detection

In this study, we developed a crystal-reconstructed-BiVO₄ aptamer photoelectrochemical (PEC) biosensor by a high-energy laser treatment technique. This biosensor achieves a limit of detection (LOD) (0.82 ag mL^-1), linear detection range (1 ag mL^-1 to 2 ng mL^-1), and resolution ratio (∼18 molecules per mL) for prostate-specific antigen (PSA) tumor biomarker detection. Furthermore, reconstructed surface microstructure and oxygen vacancy doping energy formation after crystal reconstruction induce the stereo-hindrance effect and photogenerated hole energy is reduced during PSA target detection. In this case, a photocurrent inhibition phenomenon for PSA detection is noticed. Based on this photocurrent inversion phenomenon, some dysoxidizable nucleonic acid tumor (miRNA-21) and virus biomarkers (RdRp-COVID) can be detected with a LOD level of ∼10^-16 M by linking the corresponding base paring probe on the surface of the crystal-reconstructed photoanode. In addition to high sensitivity, this PEC biosensor presents high detection specificity, stability, and accuracy in clinical verification. Thus, this crystal-reconstructed PEC biosensor shows application potential in the fields of multi-tumor or viral biomarker detection.

Photonic crystal barcodes assembled from dendritic silica nanoparticles for the multiplex immunoassays of ovarian cancer biomarkers

The combined detection of CA125, CEA and AFP is of great significance in the diagnosis of ovarian cancer. Photonic crystal (PhC) barcodes have apparent advantages in multiplex immunoassays of ovarian cancer markers. In this paper, a novel PhC barcode was assembled from dendritic silica nanoparticles (dSiO₂) for multiplex detection of ovarian cancer biomarkers. The interconnected macroporous structure of the dSiO₂ PhC beads and the open porous topography of dendritic silica particles could increase the surface area to volume ratio for antibody immobilization. We simultaneously detected multiple ovarian cancer markers in one test tube using the sandwich immunization method by utilizing dSiO₂ PhC beads as a barcode and CdTe QDs as a detection signal. The detection limits of the three ovarian cancer markers, AFP, CEA and CA125, were 0.52 ng mL^-1, 0.64 ng mL^-1 and 0.79 U mL^-1, respectively (the signal-to-noise ratio was 3). Compared with the classic silica colloidal crystal bead (SCCB) suspension array, the sensitivity of the dSiO₂ PhC bead suspension array was increased. In addition, the results showed that this barcode suspension array had acceptable accuracy and good reproducibility.

Comprehensive analysis of serum tumor markers and BRCA1/2 germline mutations in Chinese ovarian cancer patients

Background

The serum tumor markers has been widely used in ovarian cancer diagnosis. BRCA1/2 germline mutations are the most common predisposing factors for ovarian cancer development. This study aimed to comprehensively investigate serum tumor markers and BRCA1/2 germline mutations and analyze their associations with ovarian cancer.

Methods

Levels of 11 serum tumor markers were examined in ovarian cancer patients and controls with benign gynecologic diseases. By integrating multiplex PCR and next‐generation sequencing technologies, BRCA1/2 germline mutations were analyzed and confirmed by Sanger sequencing. The discriminative models with serum tumor markers and BRCA1/2 mutation status were constructed for ovarian cancer detection and patient stratification.

Results

Among 11 markers, six of them were significantly elevated and only beta‐human chorionic gonadotropin (β‐HCG) was significantly reduced in ovarian cancer patients. A total of 54 (23.3%) ovarian cancer patients were found to harbor BRCA1/2 deleterious mutations, and BRCA1/2 mutations were significantly associated with Hereditary Breast and Ovarian Cancer‐related tumors and family history of cancer. Carbohydrate antigen 125 showed a good performance in ovarian cancer detection as a single marker (AUC = 0.799), while a panel of eight markers showed a good performance in BRCA1 mutation detection with an AUC value of 0.974. In addition, a panel of five serum tumor markers combined with BRCA1/2 mutation status showed a good performance in lymph node metastasis prediction (AUC = 0.843).

Conclusions

We found the association between BRCA1/2 germline mutation status and serum tumor marker levels, and identified discriminative models that combined serum tumor markers with BRCA1/2 mutation status for ovarian cancer detection and patient stratification.

Immunohistochemical Characterization Improves the Reproducibility of the Histological Diagnosis of Ovarian Carcinoma

Background: Ovarian cancer is the leading cause of gynecologic cancer-related death. Histological assessment remains the standard clue for the diagnosis of ovarian carcinoma. Misinterpretation and inconsistent application of histological criteria may lead to significant interobserver variability and poor reproducibility of the diagnosis. In this study, we investigated the discrepancy in histological diagnosis and the significance of a designed panel of immunohistochemical markers for the improvement of the diagnostic reproducibility of ovarian carcinomas. Methods: We performed a retrospective study on 74 ovarian carcinomas. All tumor slides were independently reviewed by two pathologists. The results for seven available immunomarkers as p53, WT-1, p16INK4A, CK7, CK20, and estrogen and progesterone receptors were determined for all cases by immunohistochemistry. Results: The histological diagnosis review performed using standard histology showed a concordance of diagnoses in 86% of cases with Cohen’s kappa of 0.80. Immunohistochemical results increased significantly the diagnosis reproducibility with a concordance of 91% and a Cohen’s kappa of 0.86 (P = 0.001). Conclusion: Although the histological diagnosis remains reliable, the use of a designed panel of immunohistochemical markers improves significantly the interobserver concordance and the classification accuracy of ovarian carcinomas.

Tumour-associated antigens and their anti-cancer applications

So far, a number of tumour-associated antigens (TAAs), such as heat shock proteins, alpha-fetoprotein, carcino-embryonic antigen and others have been identified in a variety of malignant tumours. Differences in the expression levels of TAAs in cancers compared with normal cells have led to these antigens being investigated as diagnostic and prognostic biomarkers or exciting targets in cancer treatment. Here, we systematically list the current representative TAAs to shed some light on current approaches and challenges for their anti-cancer application in cancer therapy. In this review, we discuss the ongoing pre-clinical studies and clinical development of TAAs in human cancers, and the potential application of these TAAs in the diagnosis and prognosis for cancer treatment.

Top-down nanofabrication of silicon nanoribbon field effect transistor (Si-NR FET) for carcinoembryonic antigen detection

Sensitive and quantitative detection of tumor markers is highly required in the clinic for cancer diagnosis and consequent treatment. A field-effect transistor-based (FET-based) nanobiosensor emerges with characteristics of being label-free, real-time, having high sensitivity, and providing direct electrical readout for detection of biomarkers. In this paper, a top–down approach is proposed and implemented to fulfill a novel silicon nano-ribbon FET, which acts as biomarker sensor for future clinical application. Compared with the bottom–up approach, a top–down fabrication approach can confine width and length of the silicon FET precisely to control its electrical properties. The silicon nanoribbon (Si-NR) transistor is fabricated on a Silicon-on-Insulator (SOI) substrate by a top–down approach with complementary metal oxide semiconductor (CMOS)-compatible technology. After the preparation, the surface of Si-NR is functionalized with 3-aminopropyltriethoxysilane (APTES). Glutaraldehyde is utilized to bind the amino terminals of APTES and antibody on the surface. Finally, a microfluidic channel is integrated on the top of the device, acting as a flowing channel for the carcinoembryonic antigen (CEA) solution. The Si-NR FET is 120 nm in width and 25 nm in height, with ambipolar electrical characteristics. A logarithmic relationship between the changing ratio of the current and the CEA concentration is measured in the range of 0.1–100 ng/mL. The sensitivity of detection is measured as 10 pg/mL. The top–down fabricated biochip shows feasibility in direct detecting of CEA with the benefits of real-time, low cost, and high sensitivity as a promising biosensor for tumor early diagnosis.

Coptisine from Rhizoma Coptidis Suppresses HCT-116 Cells-related Tumor Growth in vitro and in vivo

Colorectal cancer is one of the most common causes of cancer-related death in humans. Coptisine (COP) is a natural alkaloid from Coptidis Rhizoma with unclear antitumor mechanism. Human colon cancer cells (HCT-116) and xenograft mice were used to systematically explore the anti-tumor activity of COP in this study. The results indicated that COP exhibited remarkably cytotoxic activities against the HCT-116 cells by inducing G1-phase cell cycle arrest and increasing apoptosis, and preferentially inhibited the survival pathway and induced the activation of caspase proteases family of HCT-116 cells. Experimental results on male BALB/c nude mice confirmed that orally administration of COP at high-dose (150 mg/kg) could suppress tumor growth, and may reduce cancer metastasis risk by inhibiting the RAS-ERK pathway in vivo. Taken together, the results suggested that COP may be potential as a novel anti-tumor candidate in the HCT-116 cells-related colon cancer, further studies are still needed to suggest COP for the further use.

Evaluation of Effects of Metformin in Primary Ovarian Cancer Cells

BACKGROUND

Ovarian cancer is the third most common cause of cancer in Indian women. Despite an initial 70-80% response rate, most patients relapse within 1-2 years and develop chemoresistance. Hence, identification or repositioning of drugs to resensitise ovarian cancer cells to existing chemotherapy is needed. Traditionally immortalized cell lines have been used in research, but these may contain genetic aberrations and chromosomal abnormalities serving as poor indicators of normal cell phenotype and progression of early-stage disease. The use of primary cells, maintained for only short periods of time in vitro, may serve as the best representative for studying in vivo conditions of the tissues from which they are derived. In this study we have attempted to evaluate the effect of metformin (an antidiabetic drug) in primary ovarian cancer cells because of its promising effect in other solid tumours.

MATERIALS AND METHODS

Primary cultures of epithelial ovarian cancer cells established from ascitic fluid of untreated ovarian cancer patients were used. The cells were treated with metformin at doses standardized by MTT assay and its ability to induce apoptosis was studied. The cells were analysed for apoptosis and apoptosis related proteins by flow cytometry and western blotting respectively.

RESULTS

Metformin induced apoptosis in ovarian cancer cells, provoking cell cycle arrest in the G0/G1 and S phase. It induced apoptosis in ovarian cancer cells by, down-regulating Bcl-2 and up-regulating Bax expression.

CONCLUSIONS

Metformin was able to induce apoptosis in primary ovarian cancer cells by modulating the expression of Bcl-2 family proteins. These data are relevant to ongoing translational research efforts exploring the chemotherapeutic potential of metformin.

Tumor infiltrating lymphocytes in ovarian cancer

Several improvements in ovarian cancer treatment have been achieved in recent years, both in surgery and in combination chemotherapy with targeting. However, ovarian tumors remain the women's cancers with highest mortality rates. In this scenario, a pivotal role has been endorsed to the immunological environment and to the immunological mechanisms involved in ovarian cancer behavior. Recent evidence suggests a loss of the critical balance between immune-activating and immune-suppressing mechanisms when oncogenesis and cancer progression occur. Ovarian cancer generates a mechanism to escape the immune system by producing a highly suppressive environment. Immune-activated tumor infiltrating lymphocytes (TILs) in ovarian tumor tissue testify that the immune system is the trigger in this neoplasm. The TIL mileau has been demonstrated to be associated with better prognosis, more chemosensitivity, and more cases of optimal residual tumor achieved during primary cytoreduction. Nowadays, scientists are focusing attention on new immunologically effective tumor biomarkers in order to optimize selection of patients for recruitment in clinical trials and to identify relationships of these biomarkers with responses to immunotherapeutics. Assessing this point of view, TILs might be considered as a potent predictive immunotherapy biomarker.

Role of neoadjuvant chemotherapy in the management of advanced ovarian cancer

OBJECTIVE

To analyze efficacy of neoadjuvant chemotherapy for advanced ovarian cancer.

MATERIALS AND METHODS

A total of 107 patients with advanced ovarian cancer undergoing cytoreductive surgery were divided into a neoadjuvant chemotherapy group (n=61) and a primary debulking group (n=46) and retrospectively analyzed. Platinum-based adjuvant chemotherapy was applied to both groups after cytoreductive surgery ande overall and progression-free survival times were calculated.

RESULTS

No significant difference was observed in duration of hospitalization (20.8±6.1 vs. 20.2±5.4 days, p>0.05). The operation time of neoadjuvant chemotherapy group was shorter than the initial surgery group (3.1±0.7 vs. 3.4±0.8 h, p<0.05). There were no significant differences in median overall survival time between neoadjuvant chemotherapy group and surgery group (42 vs. 55 months, p>0.05). Similarly, there was no difference in median progression-free survival between neoadjuvant chemotherapy group and surgery group (16 vs. 17 months, p>0.05). The surgical residual tumor size demonstrated no significant difference between initial surgery and neoadjuvant chemotherapy groups (p>0.05). Multivariate analysis showed that more than 3 cycles of regimen with neoadjuvant chemotherapy was associated with more resistance to chemotherapy compared with patients without receiving neoadjuvant chemotherapy (OR: 5.962, 95%CI: 1.184-30.030, p<0.05).

CONCLUSIONS

Neoadjuvant chemotherapy can shorten the operation time. However, it does not improve survival rates of advanced ovarian cancer patients.