Clinical value of color Doppler ultrasound combined with serum CA153, CEA and TSGF detection in the diagnosis of breast cancer

Efficacy of color Doppler ultrasound signs combined with serum tumor-specific growth factor in the diagnosis of differentiated thyroid cancer

OBJECTIVE

To construct a diagnostic model for follicular thyroid carcinoma (FTC) and papillary thyroid carcinoma (PTC), both subtypes of differentiated thyroid carcinoma (DTC), using color Doppler ultrasound signs in conjunction with serum laboratory markers.

METHODS

We conducted a retrospective analysis of patients with thyroid nodules who underwent ultrasonography at Yulin Hospital from February 2021 to March 2023. The cohort included 269 subjects: 105 with benign nodules and 164 with DTC (59 with FTC and 105 with PTC). We compared baseline demographics and laboratory indices between the groups. Diagnostic values of ultrasound features and laboratory markers were assessed using receiver operating characteristic (ROC) curves, and logistic regression was employed to pinpoint independent diagnostic factors for FTC. A predictive nomogram was subsequently developed based on these factors.

RESULTS

There were significant differences between the benign and malignant groups regarding ultrasound signs (including border, morphology, echogenicity, calcification, blood flow, lymph node zoning) and laboratory indices (free triiodothyronine (FT3), free thyroxine (FT4), thyroglobulin (Tg), thyroid-stimulating hormone (TSH), vascular endothelial growth factor (VEGF), tumor-specific growth factor (TSGF)), with all P-values <0.05. The areas under the curve (AUCs) for FT3, FT4, Tg, TSH, VEGF, and TSGF were all above 0.75, with Tg achieving the highest at 0.91. Logistic regression identified borders, morphology, echogenicity, VEGF, and TSGF as independent diagnostic factors for distinguishing between FTC and PTC, with significant P-values. The constructed nomogram demonstrated an AUC of 0.853, indicating high diagnostic accuracy. Both calibration and decision curve analysis (DCA) validated the model's stability and clinical utility.

CONCLUSION

We successfully developed a nomogram combining ultrasound features and serum markers that enhances the diagnostic precision for FTC. This model offers a valuable tool for clinical diagnostics in differentiated thyroid cancer.

PPIH acts as a potential predictive biomarker for patients with common solid tumors

BACKGROUND

Our previous studies have indicated that mRNA and protein levels of PPIH are significantly upregulated in Hepatocellular Carcinoma (LIHC) and could act as predictive biomarkers for patients with LIHC. Nonetheless, the expression and implications of PPIH in the etiology and progression of common solid tumors have yet to be explored, including its potential as a serum tumor marker.

METHODS

We employed bioinformatics analyses, augmented with clinical sample evaluations, to investigate the mRNA and protein expression and gene regulation networks of PPIH in various solid tumors. We also assessed the association between PPIH expression and overall survival (OS) in cancer patients using Kaplan-Meier analysis with TCGA database information. Furthermore, we evaluated the feasibility and diagnostic efficacy of PPIH as a serum marker by integrating serological studies with established clinical tumor markers.

RESULTS

Through pan-cancer analysis, we found that the expression levels of PPIH mRNA in multiple tumors were significantly different from those in normal tissues. This study is the first to report that PPIH mRNA and protein levels are markedly elevated in LIHC, Colon adenocarcinoma (COAD), and Breast cancer (BC), and are associated with a worse prognosis in these cancer patients. Conversely, serum PPIH levels are decreased in patients with these tumors (LIHC, COAD, BC, gastric cancer), and when combined with traditional tumor markers, offer enhanced sensitivity and specificity for diagnosis.

CONCLUSION

Our findings propose that PPIH may serve as a valuable predictive biomarker in tumor patients, and its secreted protein could be a potential serum marker, providing insights into the role of PPIH in cancer development and progression.

Re-examining What the Results of "a Measurement of Oxygen Level in Tissues" Really Mean

Within this special issue, many eminent investigators report on measurements of oxygen (O2) levels in tissues. Given the complexities of spatial and temporal heterogeneities of O2 in tissues and its many sources, this commentary draws attention to what such measurements do and do not actually assess regarding O2 levels in tissues. Given this limitation, it also discusses how these results can be used most effectively. To provide a convenient mechanism to discuss these issues more fully, this analysis focuses on measurements using EPR oximetry, but these considerations apply to all other techniques. The nature of the delivery of O2 to tissues and the mechanisms by which O2 is consumed necessarily result in very different levels of O2 within the volume of each voxel of a measurement. Better spatial resolution cannot fully resolve the problem because the variations include O2 gradients within each cell. Improved resolution of the time-dependent variation in O2 is also very challenging because O2 levels within tissues can have fluctuations of O2 levels in the range of milliseconds, while most methods require longer times to acquire the data from each voxel. Based on these issues, we argue that the values obtained inevitably are complex aggregates of averages of O2 levels across space and time in the tissue. These complexities arise from the complex physiology of tissues and are compounded by the limitations of the technique and its ability to acquire data. However, one often can obtain very meaningful and useful results if these complexities and limitations are taken into account. We illustrate this, using results obtained with in vivo EPR oximetry, especially utilizing its capacity to make repeated measurements to follow changes in O2 levels that occur with interventions and/or over time.

The value of color Doppler ultrasonography combined with serum tumor markers in differential diagnosis of gastric stromal tumor and gastric cancer

This study aimed to explore the value of color Doppler ultrasonography combined with carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9) in differential diagnosis of gastric stromal tumor (GST) and gastric cancer (GC). An analysis of the clinical data of 180 patients with clinically suspected gastric space occupying lesions. According to the postoperative pathological results, 180 suspected gastric space-occupying lesion patients were divided into GST group (n = 83) and GC group (n = 97). Color Doppler ultrasonography, serum tumor markers CEA and CA19-9 were compared. The research results showed that serum CEA and CA19-9 levels were lower in patients with GST group than those with GC group (both P < 0.001). With postoperative pathology as the gold standard, detection rates of GST and GC by combination of color Doppler ultrasound (CDUS), serum CEA, and CA19-9 were higher than those of each index alone (both P < 0.001). There was no difference between detection rates of GST and GC by combination of CDUS, serum CEA, and CA19-9 (P = 0.058). Color Doppler ultrasonography combined with serum tumor markers CEA and CA19-9 tests has a certain differential diagnostic value for GST and GC, which may provide a reliable reference basis for clinical diagnosis and treatment.

The predicting role of serum tumor-specific growth factor for prognosis of esophageal squamous cell carcinoma

OBJECTIVE

Tumor-specific growth factor (TSGF) is an immune-related factor that offers good performance in the clinical management of human cancers. However, the role of serum TSGF in esophageal squamous cell carcinoma (ESCC) has not been fully clarified.

METHODS

A total of 562 ESCC cases were collected in our study, with available information on preoperative serum levels of TSGF at diagnosis. Preoperative serum TSGF was detected using the rate method. We retrospectively analyzed its correlation with clinicopathological features of ESCC and survival.

RESULTS

The cut-off value of serum TSGF was determined to be 60.5 U/mL by receiver operating characteristic (ROC) analysis. Serum TSGF was associated with gender (P < 0.001), tumor location (P = 0.022), tobacco use (P < 0.001), alcohol consumption (P < 0.001), lymph node involvement (P = 0.007), and TNM staging (P = 0.004). The survival analysis revealed that ESCC patients with high levels of serum TSGF had poorer prognosis than those with high TSGF (P = 0.006), especially for male ESCC cases (P = 0.001), under 60 year (P = 0.036), male middle location (P = 0.023), tobacco consumption (P = 0.004), G1 + G2 (P = 0.031), advanced T staging (P = 0.033), lymph node involvement (P = 0.003), TNM staging (P = 0.003). Univariate Cox regression analysis indicated that exposure to smoking and drinking, tumor grade, T staging, lymph node metastasis, TNM staging, and serum TSGF level were the prognosis-related factors of ESCC. Multivariate regression analysis revealed that smoking history, higher serum TSGF levels, and advanced T stage enhanced the risk of ESCC-related death.

CONCLUSION

In brief, serum TSGF levels had in relation to malignant features of ESCC. It was positively correlated with survival but was identified as an independent risk factor for ESCC.

Tumor-Specific Growth Factor (TSGF): A Futuristic Tumor Biomarker in Early Diagnosis of Cancer

Despite the significant improvement in the treatment modalities, cancer is one of the fastest-growing chronic disease conditions all over the world. Genetic and Epigenetic alterations in the normal physiology of the cell are the key factor for tumor development. These changes can trigger the production of abnormal protein expressions through stimulation of different signaling pathways and can deeply affect normal cell growth and proliferation. Any altered protein expression, genetic variation, micro-RNA or post-translational protein modifications that indicate tumorigenesis can act as an early signal termed as biomarker. Cancer, being a multistep process with accumulating genetic and epigenetic alterations, could be detected early with suitable biomarkers. There are several proteins such as AFP, CA-125, PSA, troponin, CEA, osteopontin, CA 19-9 that act as biomarkers which help in early detection, prognosis, and monitoring of disease progression, a hunt for newer biomarkers with higher specificity and sensitivity is still ongoing. Tumor-specific growth factor (TSGF) is one such budding and prevailing tumor biomarker used for the early-stage detection of several types of carcinomas. TSGF is a gene that helps in tumor angiogenesis and gets released during the preliminary stages from cancer cells that ensure the vascular proliferation of the same. In this review, the clinical investigations of TSGF in different kinds of malignancy is discussed in detail and suggests the possibility of using TSGF as a biomarker in early diagnosis of cancer.

Deep learning and ultrasound feature fusion model predicts the malignancy of complex cystic and solid breast nodules with color Doppler images

This study aimed to evaluate the performance of traditional-deep learning combination model based on Doppler ultrasound for diagnosing malignant complex cystic and solid breast nodules. A conventional statistical prediction model based on the ultrasound features and basic clinical information was established. A deep learning prediction model was used to train the training group images and derive the deep learning prediction model. The two models were validated, and their accuracy rates were compared using the data and images of the test group, respectively. A logistic regression method was used to combine the two models to derive a combination diagnostic model and validate it in the test group. The diagnostic performance of each model was represented by the receiver operating characteristic curve and the area under the curve. In the test cohort, the diagnostic efficacy of the deep learning model was better than traditional statistical model, and the combined diagnostic model was better and outperformed the other two models (combination model vs traditional statistical model: AUC: 0.95 > 0.70, P = 0.001; combination model vs deep learning model: AUC: 0.95 > 0.87, P = 0.04). A combination model based on deep learning and ultrasound features has good diagnostic value.

Artificial neural network-based diagnostic models for lung cancer combining conventional indicators with tumor markers

This study set out to establish a lung cancer diagnosis and prediction model uses conventional laboratory indicators combined with tumor markers, so as to help early screening and auxiliary diagnosis of lung cancer through a convenient, fast, and cheap way, and improve the early diagnosis rate of lung cancer. A total of 221 patients with lung cancer, 100 patients with benign pulmonary diseases, and 184 healthy subjects were retrospectively studied. General clinical data, the results of conventional laboratory indicators, and tumor markers were collected. Statistical Product and Service Solutions 26.0 was used for data analysis. The diagnosis and prediction model of lung cancer was established by artificial neural network - multilayer perceptron. After correlation and difference analysis, five comparison groups (lung cancer-benign lung disease group, lung cancer-health group, benign lung disease-health group, early-stage lung cancer-benign lung disease group, and early-stage lung cancer-health group) obtained 5, 28, 25, 16, and 25 valuable indicators for predicting lung cancer or benign lung disease, and then established five diagnostic prediction models, respectively. The area under the curve (AUC) of each combined diagnostic prediction model (0.848, 0.989, 0.949, 0.841, and 0.976) was higher than that of the diagnostic prediction model established only using tumor markers (0.799, 0.941, 0.830, 0.661, and 0.850), and the difference in the lung cancer-health group, the benign lung disease-health group, the early-stage lung cancer-benign lung disease group, and early-stage lung cancer-health group was statistically significant (P < 0.05). The artificial neural network-based diagnostic models for lung cancer combining conventional indicators with tumor markers have high performance and clinical significance in assisting the diagnosis of early lung cancer.

Interleukins (Cytokines) as Biomarkers in Colorectal Cancer: Progression, Detection, and Monitoring

Cancer is the primary cause of death in economically developed countries and the second leading cause in developing countries. Colorectal cancer (CRC) is the third most common cause of cancer-related deaths worldwide. Risk factors for CRC include obesity, a diet low in fruits and vegetables, physical inactivity, and smoking. CRC has a poor prognosis, and there is a critical need for new diagnostic and prognostic biomarkers to reduce related deaths. Recently, studies have focused more on molecular testing to guide targeted treatments for CRC patients. The most crucial feature of activated immune cells is the production and release of growth factors and cytokines that modulate the inflammatory conditions in tumor tissues. The cytokine network is valuable for the prognosis and pathogenesis of colorectal cancer as they can aid in the cost-effective and non-invasive detection of cancer. A large number of interleukins (IL) released by the immune system at various stages of CRC can act as "biomarkers". They play diverse functions in colorectal cancer, and include IL-4, IL-6, IL-8, IL-11, IL-17A, IL-22, IL-23, IL-33, TNF, TGF-β, and vascular endothelial growth factor (VEGF), which are pro-tumorigenic genes. However, there are an inadequate number of studies in this area considering its correlation with cytokine profiles that are clinically useful in diagnosing cancer. A better understanding of cytokine levels to establish diagnostic pathways entails an understanding of cytokine interactions and the regulation of their various biochemical signaling pathways in healthy individuals. This review provides a comprehensive summary of some interleukins as immunological biomarkers of CRC.

Assessing early changes in plasma HER2 levels is useful for predicting therapeutic response in advanced breast cancer: A multicenter, prospective, noninterventional clinical study

BACKGROUND

Early prediction of treatment response is crucial for the optimal treatment of advanced breast cancer. We aimed to explore whether monitoring early changes in plasma human epidermal growth factor receptor 2 (HER2) levels using digital PCR (dPCR) could predict the treatment response in advanced breast cancer.

METHODS

This was a multicenter, prospective, noninterventional clinical study of patients with advanced breast cancer. All enrolled patients underwent blood testing to measure the HER2 levels by digital PCR before treatment initiation and once every 3 weeks during the study. The primary endpoints were^a the diagnostic value of dPCR for detecting HER2 status in the blood and^b the relevance of potential changes in the plasma HER2 level at 3 weeks from baseline for predicting treatment response.

RESULTS

Overall, 85 patients were enrolled between October 9, 2018, and January 23, 2020. dPCR had a specificity of 91.67% (95% CI: 80.61% to 97.43%) for detecting HER2 amplification, and the area under the receiver operating characteristic (ROC) curve was 0.84 (p < 0.01). A clinically relevant specificity threshold of approximately 90%, which was equivalent to a ≥15% decrease in the plasma HER2 ratio at 3 weeks from baseline, showed a positive predictive value of 97.37% (95% CI: 77.11% to 98.65%) in terms of predicting clinical benefit. Patients whose plasma HER2 ratio was reduced by ≥15% had a longer median progression-free survival (PFS) than those whose ratio was reduced by <15% (9.20 months vs. 4.50 months, p < 0.01).

CONCLUSIONS

Early changes in the plasma HER2 ratio may predict the treatment response in patients with advanced breast cancer and could facilitate optimal treatment selection.

Development and validation of a nomogram to predict Chinese breast cancer risk based on clinical serum biomarkers

Background: This study investigated and compared clinical serum biomarkers and developed a diagnostic nomogram for breast cancer. Methods: A total of 1224 breast cancer and 1280 healthy controls were enrolled. Univariate and multivariate analyses were performed to identify factors and a nomogram was developed. Discrimination, accuracy and clinical utility values were evaluated by receiver operating characteristic, Hosmer-Lemeshow, calibration plots, decision curve analysis and clinical impact plots. Results: carcinoembryonic antigen, CA125, CA153, lymphocyte-to-monocyte ratio, platelet-to-lymphocyte ratio, fibrinogen and platelet distributing width were effectively identified to predict breast cancer. The nomogram showed the area under the curve of 0.708 and 0.710 in the training and validation set. Calibration plots, Hosmer-Lemeshow, decision curve analysis and clinical impact plots confirmed great accuracy and clinical utility. Conclusion: We developed and validated a nomogram that is effectively used for risk prediction of Chinese breast cancer.

The Preliminary Application of Simultaneous Display of Contrast-Enhanced Ultrasound and Micro-Flow Imaging Technology in the Diagnosis of Hepatic Tumors

OBJECTIVES

To evaluate the value of simultaneous display of contrast-enhanced ultrasound and micro-flow imaging technology (CEUS-MFI) in intra-tumoral vessel detection and hepatic tumor diagnosis.

METHODS

A total of 82 patients with 82 focal liver lesions were enrolled in this study. Each patient received ultrasound exams including color Doppler flow imaging (CDFI), micro-flow imaging (MFI), contrast-enhanced ultrasound (CEUS), and CEUS-MFI with a Philips EPIQ7 ultrasound imaging system. The intra-tumoral vessels detected by CDFI, MFI, and CEUS-MFI were compared, respectively. The accuracy and confidence of using CEUS and CEUS-MFI in diagnosing hepatic tumors were also compared.

RESULTS

CEUS-MFI was capable of detecting more hepatic intra-tumoral vessels than MFI (P = .000) and CDFI (P = .000). Compared with CEUS, CEUS-MFI improved the diagnostic accuracy of hepatic lesions (P = .009). Particularly, among the correctly diagnosed hepatic lesions, the number of cases where radiologists diagnosed with great confidence was increased from 88.4% (61/69) with CEUS only to 92.4% (73/79) with CEUS-MFI (P = .041).

CONCLUSIONS

CEUS-MFI is sensitive in detecting hepatic intra-tumoral vessels and can improve the accuracy and confidence of radiologists in diagnosing hepatic lesions.

A study comparing the oncogenic microRNA-21-5p and the CA15-3 characteristics as an effective tumor marker in breast cancer patients from Iraq

Breast cancer (BC) is a genetic disease in the mammary glands' ducts and lobules, with ductal cancers comprising most of the malignancies. Biomarkers can provide an assessment of cancer diagnosis and prediction. The study aims to compare the expression of serum (miR-21-5p) and CA 15-3 expression in the Iraqi population as more efficient biomarkers, then checked MiRNA-21 main characters as a biomarker comparison with (CA15-3) levels. Circulating serum miRNA-21 expression was measured using (the quantitative Real Time-PCR technique) in 50 patients at various stages of breast cancer compared to 27 healthy controls. Meanwhile, CA 15-3 levels were quantified using electro-chemo luminescence immunoassay (ECLIA) methods. The results show the expression of miRNA-21 and the concentration of CA15-3 increased significantly (p>0.01) in patients as compared to control, but the higher median level of MiRNA-21 than of CA15-3. The ROC curve analysis shows that the accuracy, Overall Model Quality, AUC, sensitivity and specificity of miRNA-21 as a biomarker is much higher than the CA 15-3. In conclusion, miRNA-21 may fill the gap that CA 15-3 still lacks in detecting breast cancer at an early stage. Keywords: Breast cancer, microRNA-21, CA15-3, gene expression, RT-q PCR

Dual-Channel Detection of Breast Cancer Biomarkers CA15-3 and CEA in Human Serum Using Dialysis-Silicon Nanowire Field Effect Transistor

BACKGROUND

Breast cancer (BC) is the most common malignant tumors and the leading cause of cancer deaths among women. The early diagnosis and treatment of BC are effective measures that can increase survival rates and reduce mortality. Carbohydrate antigens 15-3 (CA15-3) and carcinoma embryonic antigens (CEA) have been regarded as the most two valuable tumor markers of BC. The combined detection of CA15-3 and CEA could improve the sensitivity and accuracy of early diagnosis for BC.

METHODS

The multi-channel double-gate silicon nanowire field effect transistor (SiNW-FET) biosensors were fabricated by using the top-down semiconductor manufacturing technology. By surface modification of the different SiNW surfaces with monoclonal CA15-3 and CEA antibodies separately, the prepared SiNW-FET was processed into biosensor for dual-channel detection of CA15-3 and CEA.

RESULTS

The prepared SiNW-FET biosensors were proved to have high sensitivity and specificity for the dual-channel detection of CA15-3 and CEA, and the detection limit is as low as 0.1U/mL CA15-3 and 0.01 ng/mL CEA. Moreover, the SiNW-FET biosensors were able to detect CA15-3 and CEA in serum by connecting a miniature hemodialyzer.

CONCLUSION

The present study reported a SiNW-FET biosensor for dual-channel detection of breast cancer biomarkers CA15-3 and CEA in serum, which has potential clinical application value for the early diagnosis and curative effect observation of BC.

The Predicting Role of Serum TSGF and sIL-2R for the Lymph Node Metastasis of Papillary Thyroid Carcinoma

Objective

To explore the clinical utility of tumor-specific growth factor (TSGF) and the soluble interleukin-2 (IL-2) receptor (sIL-2R) as immune-related factors for predicting lymph node metastases (LNM) of papillary thyroid carcinoma (PTC).

Methods

A total of 206 patients with PTC subjected to curative surgery were enrolled. All patients had complete medical records. Serum levels of TSGF were detected using Automatic Biochemistry Analyzer and the serum sIL-2R concentration was detected by enzyme-linked immunosorbent assay (ELISA). Furthermore, we analyzed the relationship between the two indicators and the clinicopathological characteristics and assessed their effect on lymphatic metastasis in patients with PTC by logistic regression analysis.

Results

Receiver operating characteristic (ROC) analysis revealed that the determined cut-off value of serum TSGF and sIL-2R was 63.35 U/mL and 507 U/mL, respectively. Serum TSGF was associated with focality (χ² = 4.97, P = 0.026) and lymphatic metastasis (χ² = 4.154, P = 0.042), while serum sIL-2R was remarkably related to gender (χ² = 4.464, P = 0.035). Univariate logistic regression analysis indicated that age, tumor size, serum TSGF level, capsule invasion, and nodular goiter were the lymphatic metastasis-related factor of PTC. Multivariate regression analysis revealed that age > 45 years was a protective factor (OR: 0.4, 95% CI: 0.206-0.777, P = 0.007). Conversely, larger tumor size (OR: 4.594, 95% CI: 2.127-9.921, P = 0.000), higher serum TSGF levels (OR: 1.888, 95% CI: 1.009-3.533, P = 0.047), and capsule invasion (OR: 1.939, 95% CI: 1.009-3.726, P = 0.047) were associated with an increased risk of LNM.

Conclusion

Serum TSGF levels were identified as an independent factor for LNM in patients with PTC.

The correlation between neutrophil-to-lymphocyte ratio, carcinoembryonic antigen, and carbohydrate antigen 153 levels with chemotherapy-related cognitive impairment in early-stage breast cancer patients

Background

The changes in inflammation and tumor biomarkers are associated with the anti-tumor immunological processes. Early detection and intervention are of great significance to the clinical management of cancer-related diseases. Peripheral blood biomarkers [e.g., neutrophil-to-lymphocyte ratio (NLR), carcinoembryonic antigen (CEA), and carbohydrate antigen 153 (CA153)] are obtained in real-timely, conveniently, and less invasively, and proved to availably predicted the disease states and prognosis of various cancers, including breast cancer (BC). Inflammation and poor disease management promote cognitive impairment. Chemotherapy-related cognitive impairment (CRCI) hazard long-term survival and quality of life (QOL) of BC patients, but its correlation with NLR, CEA, and CA153 is not clear.

Purpose

This study aimed to investigate changes in NLR, CEA, and CA153 levels before and after chemotherapy and their correlation with CRCI in patients with early-stage BC.

Materials and methods

The 187 patients with BC who were measured for NLR, CEA, and CA153 values within the first 24 hours of admission, were assigned into two groups: the before/after chemotherapy group (BCG/ACG). The ACG was assigned into two subgroups based on the cognitive assessment results: the cognitive normal/impaired group (CNG/CIG). Patients’ self-perceived cognitive impairments were evaluated using a mini-mental state examination (MMSE), prospective and retrospective memory (PM and RM) questionnaire (PRMQ), and functional assessment of cancer therapy-cognitive function version 3 (FACT-Cog, version 3, including CogPCI, CogOth, CogPCA, and CogQOL). Their QOL was also evaluated.

Results

The NLR and CA153 levels were elevated after chemotherapy (BCG vs ACG: Z = −1.996 and −1.615, P = 0.046 and 0.106, respectively), and significantly elevated in patients with CRCI (BCG vs CIG: Z = −2.444 and -2.293, P = 0.015 and 0.022; respectively). However, there was not reach significant difference in CEA levels between the four groups. In addition, there was a weak to moderate correlation between peripheral blood biomarkers (NLR, CEA, and CA153) levels and CRCI (r = −0.404, −0.205, −0.322; respectively; P < 0.001). Cognitive impairment scores (MMSE, PM, RM, and FACT-Cog) had a strong correlation with QOL in patients with early-stage BC (r = −0.786, 0.851, 0.849, and 0.938; respectively; P < 0.001).

Conclusion

NLR and CA153 m be valuable diagnostic adjuncts of CRCI, and CRCI has a strong correlation with QOL in patients with early-stage BC.

Prognosis value of IL-6, IL-8, and IL-1β in serum of patients with lung cancer: A fresh look at interleukins as a biomarker

Interleukins are assumed to be closely related to the occurrence and development of human malignant tumors, while a few of them were commonly used as diagnostic markers in clinical cancer, including lung cancer. This study aimed to explore the value of serum interleukin-1β (IL-1β), interleukin-6 (IL-6), and interleukin-8 (IL-8) combined with carcinoembryonic antigen (CEA) as biomarker panel for the diagnosis and metastasis prediction of lung cancer. IL-1β, IL-6, IL-8, and CEA in serum were determined using electrochemiluminescence immunoassay (ECLIA) and flow cytometry, and the diagnostic value of each marker was analyzed using receiver operating characteristic (ROC) curves and logistic fitting regression. We found that the levels of serum IL-1β, IL-6, and IL-8 showed no significant difference among squamous cell carcinoma, adenocarcinoma, and small cell carcinoma, while they were significantly higher in the lung cancer group or benign group than those in the healthy group. The levels of IL-8 and CEA were positively correlated with clinical stages respectively. Importantly, the panel of CEA + IL-6 + IL-8 has the highest efficacy for the diagnosis of lung cancer (AUC = 0.883) among all the detected panels, while the panel of IL-8 + CEA showed the most promising predictive value for the lymph node metastasis (AUC = 0.686) and distant metastasis of lung cancer (AUC = 0.793). In conclusion, IL-6 and IL-8 could be used as promising molecular biomarkers to diagnose and predict the metastasis of lung cancer independent of pathological types, improving the specificity and sensitivity of diagnosis for lung cancer when they were combined with CEA.

Diagnostic efficacy of the new prospective biomarker's combination CA 15-3 and CA-62 for early-stage breast cancer detection: Results of the blind prospective-retrospective clinical study

BACKGROUND

Combination of different cancer markers is often used for predicting tumor growth, for the response to cancer therapy, and for increase in the positive diagnosis ratio in the malignant tumors.

OBJECTIVE

Evaluation of the diagnostic efficacy of CA 15-3 and CA-62 cancer markers combination for early stages of breast cancer (BC) detection.

METHODS

This retrospective blind study was performed on 2 clinically validated Sets that included serum measurements of CA 15-3 ELISA and CLIA-CA-62 assays in 488 serum samples with TNM classification. A study included 300 BC patients (254 at Stages I and II, 20 with ductal carcinoma in situ (DCIS), and 26 Stages III and IV patients), 47 patients with breast benign diseases, and 141 healthy controls.

RESULTS

Sensitivity for DCIS & Stage I breast cancer detection was 75% at 100% Specificity (AUC = 0.895) using a following combination of two antigens: 10 < CA15-3 < 46 U/ml and CA-62 ⩾ 6300 U/ml, which allows eliminating false positive results.

CONCLUSIONS

The results obtained in a blind study demonstrate that a combination of CA15-3 with CA-62 yields 75% Sensitivity at 100% Specificity for DCIS and Stage I breast cancer detection, which has a potential to be integrated into existing screening programs.

Prognostic Evaluation of Metastasis-Related Lymphocyte/Monocyte Ratio in Stage Ⅰ-Ⅲ Breast Cancer Receiving Chemotherapy

Purpose

This study aims to clarify the prognostic significance of metastasis-related indicators in peripheral blood in stage I-III breast cancer (BC).

Methods

The clinicopathological data of 938 breast cancer patients and 509 benign breast disease patients were retrospectively analyzed, and fasting blood samples were collected before treatment. Univariate and multivariate regression analyses were used to evaluate factors related to metastasis risk and prognosis. The Kaplan-Meier method was used to generate survival curves, and the log-rank test was used to measure differences in survival between groups.

Results

Use the cut-off value (3.433) of LMR, the logistic regression analysis revealed that high carbohydrate antigen 153 (CA153), carbohydrate antigen 125 (CA125), carcinoembryonic antigen (CEA), killer T cell level, and low lymphocyte to monocyte ratio (LMR) level were significantly associated with BC distant metastasis. In contrast, LMR>=3.433 (HR: 0.409, 95%CI: 0.193–0.867, P = 0.020), Th/Tc ratio >=1.946 (HR: 0.378, 95% CI: 0.158–0.904, P =0.029) is regarded as a protective factor in the multivariate cox analyses. LMR is an independent prognostic factor for DFS in HER2-negative BC patients.

Conclusion

Peripheral blood parameters play an important role in predicting distant metastasis and prognosis of BC patients. As a potential marker, LMR can predict the metastasis and prognosis of patients with stage I-III BC.

Prognostic Value of Combined Lactate Dehydrogenase, C-Reactive Protein, Cancer Antigen 153 and Cancer Antigen 125 in Metastatic Breast Cancer

Background

Breast cancer (BC), especially metastatic BC, is one of the most lethal diseases in women. CA 125 and CA 15-3 are commonly used indicators for diagnosis and prognosis of BC. Some serological indicators, such as lactate dehydrogenase (LDH) and C-reactive protein (CRP), can also be used to assess the prognosis and progression in BC.

Methods

Univariate Cox regression analysis and LASSO regression analysis were performed to identify prognostic factors and build prognostic models. We distributed the patients into 2 groups based on the median risk score, analyzed prognosis by Kaplan–Meier curve, and screened independent prognostic factors by multivariate Cox regression analysis.

Result

We identified 4 indicators-LDH, CRP, CA 15-3, and CA 125—related to the prognosis in BC and established a prognostic model. The high LDH group showed worse overall survival (OS) than low LDH group (P = .017; hazard ratio (HR), 1.528; 95% confidence interval (CI), 1.055-2.215). The high CRP group showed worse OS than low CRP group (P = .004; HR, 1.666; 95% CI, 1.143-2.429). The high CA153 group showed worse OS than low CA 15-3 group (P=.011; HR, 1.563; 95% CI, 1.075-2.274). The high CA 125 group showed worse OS than low CA 125 group (P = .021; HR, 1.499; 95% CI, 1.031-2.181). The area under the curve for risk score was .824, Ki-67 was .628, age was .511, and grade was .545. Risk score was found to be an independent prognostic factor using multivariate Cox regression analysis.

Conclusion

We successfully established an optimization model by combining 4 prognosis-related indicators to assess the prognosis in patients with metastatic BC.

Tumor-Specificity Growth Factor Combined with Tumor Markers in Nuclear Medicine Imaging to Identify Prostate Cancer Osteonosus

Objective

This study has explored the application value of malignant tumor SPE growth factor (TSGF) combined with tumor markers (TM) (TSGF + TM) in nuclear medicine imaging to identify prostate cancer osteonosus (PCO).

Methods

A retrospective analysis for 70 patients with prostate cancer and bone disease admitted to our hospital was performed, 30 healthy persons in the same period were selected as the control group, and the advantages and disadvantages of various examinations were analyzed. All patients were diagnosed with PET whole body bone imaging. Suspicious lesions could be examined by MRI or CT. According to the results of imaging examination, patients were divided into 40 cases of malignant prostate cancer and 30 cases of benign prostate cancer. All the patients underwent 18F-FDG-PET imaging, alpha-fetoprotein (AFP), and TSGF + TM determination. The case diagnosis results were compared and analyzed, and the sensitivity (SEN), specificity (SPE), and accuracy (ACC) of various detection methods were calculated. The SEN, SPE, and ACC of positron emission tomography (PET) were 90.9%, 57.8%, and 81.2%, respectively; those of TM were 79.2%, 94.6%, and 69.8%, respectively; and those of TSGF + TM were 95.9%, 100%, and 97.3%, respectively. The accuracy of combined diagnosis of tumors can reach 100%. The AFP and TSGF levels of serum TM were compared and analyzed, and it was found that the benign lesion group and the malignant lesion group showed significant increases compared with the control group, and the difference between the malignant lesion group and the control group was obvious (P < 0.05). SGF combined with TM could obtain a more definite diagnosis in PCO.

Conclusion

TSGF + TM combined with 18F-FDG-PET imaging showed important clinical value to diagnose the PCO. The imaging accuracy of TSGF + TM combined with 18F-FDG-PET is 97.3%, and the specificity of tumor diagnosis is 100%. Therefore, the TSGF + TM applied in medical imaging and identification of PCO was worthy of clinical promotion.

Carboxypeptidase N1 is anticipated to be a synergy metrics for chemotherapy effectiveness and prognostic significance in invasive breast cancer

BACKGROUND

The incidence and mortality of invasive breast cancer (IBC) are increasing annually. Hence, it is urgently needed to determine reliable biomarkers for not only monitoring curative effects, but evaluating prognosis. In present study, we aim to determine the potential role of Carboxypeptidase N1 (CPN1) in IBC tissues on chemotherapeutic efficacy and poor prognosis.

METHODS

The expression level of CPN1 in IBC tissue samples (n = 123) was quantified by tissue microarray technique and immunohistochemical staining. Moreover, sera of IBC patients (n = 34) that underwent three to five consecutive chemotherapy sessions were collected. The patients were randomly stratified into a training (n = 15) as well as a validation group (n = 19). The expression of serum CA153 and CPN1 was quantified by electrochemiluminescence and ELISA assay, respectively.

RESULTS

By univariate and multivariate Cox regression analysis, we show that CPN1 expression in IBC tissues, as an independent risk factor, is related to a poor overall survival (OS) and progression-free survival (PFS) (P < 0.05). Analysis of the data revealed that CPN1 over-expression could be consistently linked to adverse clinicopathological features such as lymph node metastasis and the pathological stage (pTNM) (P < 0.05). The serum CPN1 level trajectory of individual patients generally decreased during chemotherapy. In line with these findings were changes in the follow-up ultrasonography and a consistent decrease in serum CPN1 levels. The comparison of the area under the receiver operating curves (ROC) revealed that CPN1 has a better surveillance value than CA153 in the training (AUCCPN1 = 0.834 vs. AUCCA153 = 0.724) as well as the validation set (AUCCPN1 = 0.860 vs. AUCCA153 = 0.720) when comparing cycle2 versus cycle3.

CONCLUSIONS

CPN1 is a suitable potential biomarker for chemotherapeutic surveillance purposes as well as being an appropriate prognostic indicator which would support an improved chemotherapy regimen.

Clinical effect of robot-assisted radical cystectomy in bladder cancer

OBJECTIVE

This study aimed to determine whether robot-assisted radical cystectomy (RARC) can accelerate recovery, improve pelvic lymph node dissection effects, and reduce serum tumor marker tumor specific growth factor (TSGF) levels in patients with bladder cancer.

METHODS

A total of 96 patients with bladder cancer admitted to our hospital were recruited as the research participants. Among them, 43 patients who adopted radical cystectomy were enrolled in the control group (CG), and 53 patients treated with RARC were included in the research group (RG). The operation time, intraoperative blood loss, postoperative bowel recovery time, gastrointestinal function recovery, complication rate, clinical efficacy, changes of TSGF levels before and after operation, postoperative satisfaction and quality of life were observed.

RESULTS

Compared with the CG, patients in the RG experienced longer operation times (P<0.05), less intraoperative blood loss (P<0.05), and faster time to bowel recovery, anal exhaust, and anal defecation (P<0.05); moreover, the RG had a lower incidence rate of complications (P=0.025) and TSGF levels (P<0.05), higher effective cure rate (P=0.023) and satisfaction degree (P=0.048), as well as superior quality of life scores in six dimensions (P<0.05).

CONCLUSION

The application of RARC can accelerate the recovery of patients with bladder cancer, improve the pelvic lymph node dissection effects, and reduce the serum levels of tumor marker TSGF.

Unique structural features of the adenylate kinase hCINAP/AK6 and its multifaceted functions in carcinogenesis and tumor progression

Human coilin-interacting nuclear ATPase protein (hCINAP), also known as adenylate kinase 6 (AK6), is an atypical adenylate kinase with critical roles in many biological processes, including gene transcription, ribosome synthesis, cell metabolism, cell proliferation and apoptosis, DNA damage responses, and genome stability. Furthermore, hCINAP/AK6 dysfunction is associated with cancer and various inflammatory diseases. In this review, we summarize the structural features and biological roles of hCINAP in several important signaling pathways, as well as its connection with tumor onset and progression.

Current strategies of virotherapy in clinical trials for cancer treatment

As a novel immune-active agent for cancer treatment, viruses have the ability of infecting and replicating in tumor cells. The safety and efficacy of viruses has been tested and confirmed in preclinical and clinical trials. In the last decade, virotherapy has been adopted as a monotherapy or combined therapy with immunotherapy, chemotherapy, or radiotherapy, showing promising outcomes against cancer. In this review, the current strategies of viruses used in clinical trials are classified and described. Besides this, the challenge and future prospects of virotherapy in the management for cancer patients are discussed in this review.