Testing breast cancer serum biomarkers for early detection and prognosis in pre-diagnosis samples

Development and validation of machine learning models for early diagnosis and prognosis of lung adenocarcinoma using miRNA expression profiles

ObjectiveStudy aims to develop diagnostic and prognostic models for lung adenocarcinoma (LUAD) using Machine learning（ML）algorithms, aiming to enhance clinical decision-making accuracy.MethodsData from The Cancer Genome Atlas (TCGA) for LUAD patients were split into training (n = 196) and test sets (n = 133). Feature selection (Least Absolute Shrinkage and Selection Operator (LASSO), Random Forest (RF), and Support Vector Machine (SVM)) identified miRNAs distinguishing stage I LUAD. Six ML algorithms predicted pulmonary node classification. Model performance was evaluated using Receiver Operating Characteristic (ROC) curve, Precision-Recall (PR) curves, and Error Rates (CE). A prognostic model was constructed using Lasso Cox regression. Risk score plots were generated, and model performance was assessed using Kaplan-Meier (K-M) and time-dependent ROC curves. Functional enrichment analyses investigated miRNA function and mechanism.ResultsThe feature selection results identified five miRNA molecules as distinguishing characteristics between early-stage LUAD and adjacent non-cancerous tissues. A prognostic model using 13 miRNAs predicted poorer outcomes for patients with higher risk scores, supported by time-dependent ROC curves and a nomogram. Functional enrichment analysis identified cancer-related signaling pathways for the biomarkers.ConclusionML identified a diagnostic five-miRNA signature and a prognostic 13-miRNA model for LUAD, both robust and reliable.

Salivary Metabolites in Breast Cancer and Fibroadenomas: Focus on Menopausal Status and BMI

This study of the features of the biochemical composition of biological fluids in patients with breast cancer, including saliva, allows us to identify some indicators as metabolic predictors of the presence of the disease.

OBJECTIVES

to study the influence of the menopause factor and body mass index (BMI) on the biochemical composition of saliva and to evaluate the applicability of metabolic markers of saliva for the diagnosis of breast cancer.

METHODS

The case-control study involved 1438 people (breast cancer, n = 543; fibroadenomas, n = 597; control, n = 298). A comprehensive study of the biochemical composition of saliva was carried out using 36 parameters.

RESULTS

When comparing the salivary biochemical composition in breast cancer, fibroadenomas, and controls, it is necessary to take into account the menopausal status, as well as BMI (less than 25 or more) for the group of patients with preserved menstrual function. A complex of biochemical parameters has been identified that change in saliva during breast cancer, regardless of menopause and BMI (total protein, urea, uric acid, NO, α-amino acids, GGT), as well as specific parameters that must be taken into account when analyzing individual subgroups (imidazole compounds, LDH, catalase, α-amylase). During the study of a separate group of patients with leaf-shaped (phyllodes) tumors, we found similarities with breast cancer in the changes in some biochemical parameters that can be attributed to metabolites of malignant growth (protein, α-amino acids, calcium, NO, pyruvate, peroxidase, α-amylase).

CONCLUSIONS

We demonstrated changes in a wide range of salivary biochemical parameters depending on the presence of fibroadenomas and breast cancer. From the point of view of clinical practice, this may be useful information for monitoring the condition of patients with fibroadenomas, which are difficult to unambiguously classify based on instrumental diagnostics alone.

Chemoprotective and immunomodulatory potential of Lactobacillus reuteri against cadmium chloride-induced breast cancer in mice

INTRODUCTION

The current study aimed to investigate the role of probiotic Lactobacillus reuteri for the treatment and prevention of breast cancer.

MATERIALS AND METHODS

Breast cancer was induced by using Cadmium Chloride (Cd) (2 mg/kg) in group II. Tamoxifen was administered to group III. Group IV was treated with Lactobacillus reuteri. Group V was treated with Cd for one month and divided into three subgroups including VA, VB, and VC which were treated with tamoxifen, Lactobacillus reuteri, and tamoxifen + Lactobacillus reuteri, respectively.

RESULTS

Significantly higher levels of TNF-α (40.9 ± 4.2 pg/mL), IL-6 (28.0 ± 1.5 pg/mL), IL-10 (60.2 ± 2.0 pg/mL), IFN-γ (60.2 ± 2.0 pg/mL), ALAT (167.2 ± 6.2 U/l), ASAT (451.6 ± 13.9 U/l), and MDA (553.8 ± 19.6 U/l) was observed in Cd group. In comparison, significantly lower levels of TNF-α (18.0 ± 1.1 pg/mL), IL-6 (9.4 ± 0.4 pg/mL), IL-10 (20.8 ± 1.1 pg/mL), IFN-γ (20.8 ± 1.1 pg/mL), ALAT (85.2 ± 3.6 U/l), ASAT (185 ± 6.9 U/l), and MDA (246.0 ± 7.5 U/l) were observed in group Cd + Tam + LR. Liver histopathology of the Cd group showed hemorrhage and ductal aberrations. However, mild inflammation and healthier branched ducts were observed in treatment groups. Furthermore, the renal control group showed normal glomerular tufts, chronic inflammation from the Cd group, and relatively healthier glomerulus with mild inflammation in treatment groups.

CONCLUSION

Hence, the preventive and anticancerous role of probiotic Lactobacillus reuteri is endorsed by the findings of the current study.

Screening Nonlinear miRNA Features of Breast Cancer by Using Ensemble Regularized Polynomial Logistic Regression

Differentiating breast cancer subtypes based on miRNA data helps doctors provide more personalized treatment plans for patients. This paper explored the interaction between miRNA pairs and developed a novel ensemble regularized polynomial logistic regression method for screening nonlinear features of breast cancer. Three different types of second-order polynomial logistic regression with elastic network penalty (SOPLR-EN) in which each type contains 10 identical models were integrated to determine the most suitable sample set for feature screening by using bootstrap sampling strategy. A single feature and 39 nonlinear features were obtained by screening features that appeared at least 15 times in 30 integrations and were involved in the classification of at least 4 subtypes. The second-order polynomial logistic regression with ridge penalty (SOPLR-R) built on screened feature set achieved 82.30% classification accuracy for distinguishing breast cancer subtypes, surpassing the performance of other six methods. Further, 11 nonlinear miRNA biomarkers were identified, and their significant relevance to breast cancer was illustrated through six types of biological analysis.

The expression of miR-21, HSP90a and gGASP-1 in serum of patients with lung cancer and their correlation with pathological subtypes

Background

To investigate the expression of miR-21, heat shock protein-90a (HSP90a) and G protein-coupled receptorrelated sorting protein 1(GASP-1) in the serum of lung cancer patients and their correlation with pathological subtypes.

Methods

Eighty patients with lung cancer were included in the lung cancer group from May 2020 to May 2022, and 40 volunteers who underwent physical examination were randomly included in the control group according to the group ratio of 2:1. This ratio balances the need for a sufficiently large experimental group to detect significant effects with the practicality of recruiting a manageable control group. To ensure the validity of our findings, we meticulously calculated the sample size to achieve adequate statistical power, thus enabling us to draw reliable conclusions. Serum miR-21, HSP90a and GASP-1 levels of patients in the two groups were detected. We quantitatively assessed the serum levels of miR-21, HSP90a, and GASP1 in lung cancer patients and healthy volunteers. We employed enzyme-linked immunosorbent assay (ELISA) for HSP90a and GASP-1, and reverse transcription-polymerase chain reaction (RT-PCR) for miR-21, ensuring precise quantification. To explore the correlation between it and pathological subtypes, TNM stage and lymph node metastasis of lung cancer patients. TNM stands for Tumor, Node, and Metastasis. This system is widely used for staging cancer and describes the size and extent of the primary tumor (T), the absence or presence of cancer in nearby lymph nodes (N), and whether the cancer has spread to other parts of the body (M).

Results

The serum levels of miR-21, HSP90a and GASP1 in lung cancer group were higher than those in control group (P < 0.05). ROC curve analysis showed that serum miR-21, HSP90a and GASP-1 levels had certain value in the diagnosis of lung cancer, and their AUC values were 0.901, 0.874 and 0.865, respectively (P < 0.05). There was no difference in the relative expression level of serum miR-21 between squamous cell carcinoma group and adenocarcinoma group (P>0.05), but the levels of HSP90a and GASP-1 in adenocarcinoma group were higher than those in squamous cell carcinoma group (P < 0.05). There was no difference in the levels of serum miR-21, HSP90a and GASP-1 between stage I and stage II groups (P>0.05). The levels of serum miR-21, HSP90a and GASP-1 in stage III and stage IV groups were higher than those in stage I and stage II groups, and those in stage IV were higher than those in stage III group (P < 0.05). The serum levels of miR-21, HSP90a and GASP-1 in patients with metastasis were higher than those in patients without metastasis (P < 0.05).

Conclusions

Our study concludes that there is a notable association between elevated serum levels of miR-21, HSP90a, and GASP-1 and lung cancer. However, it is crucial to acknowledge that these findings are preliminary and further statistical analysis is needed to strengthen these associations. Future studies with comprehensive statistical evaluation will be vital to validate these potential biomarkers for lung cancer diagnosis and prognosis.

Elucidating the relationship between metabolites and breast cancer: A Mendelian randomization study

The evidence about the causal roles of metabolites in breast cancer is lacking. This study conducted a systematic evaluation of the potential causal relationship between 1091 human blood metabolites, 309 metabolite ratios, and the likelihood of developing breast cancer and its subtype by employing a two-sample bidirectional Mendelian randomization (MR) approach Four metabolites, including tryptophan betaine (Odds Ratio [OR] = 1.07, 95%CI = 1.04-1.10, Bonferroni-corrected P = 0.007), X-21312 (OR = 0.90, 95%CI = 0.86-0.94, Bonferroni-corrected P = 0.02), 3-bromo-5-chloro-2,6-dihydroxybenzoic acid (OR = 0.94, 95%CI = 0.91-0.96, Bonferroni-corrected P = 0.03) and X-18921 (OR = 0.96, 95%CI = 0.94-0.98, Bonferroni-corrected P = 0.04) were significantly associated with overall breast cancer using inverse-variance weighted (IVW) method. Tryptophan betaine was also significantly associated with estrogen receptor (ER)-positive breast cancer (OR = 1.08, 95%CI = 1.04-1.11, Bonferroni-corrected P = 0.03). X-23680 (OR = 1.10, 95%CI = 1.05-1.15, Bonferroni-corrected P = 0.04) and glycine to phosphate ratio (OR = 1.07, 95%CI = 1.04-1.10, Bonferroni-corrected P = 0.04) were associated with ER-negative breast cancer. Reverse MR analysis showed no significant associations between breast cancer and metabolites. This MR study indicated compelling evidence of a causal association between metabolites and the risk of breast cancer and its subtypes, underscoring the potential impact of metabolic interference on breast cancer risk and indicating the drug targets for breast cancer.

Expression of Soluble Form of Aurora A as a Predictive Factor for Neoadjuvant Therapy in Breast Cancer Patients: A Single-Center Pilot Study

PURPOSE

To search for new predictive breast cancer biomarkers. We analyzed the serum concentrations of biomarkers involved in carcinogenesis, which can also be targeted by therapy.

METHODS

In a single-center prospective study, the serum levels of Aurora A, thymidine kinase 1, and human epidermal growth factor receptor type 3 (HER3) were determined in 119 women with BC before neoadjuvant treatment using ELISA kits.

RESULTS

The following clinical data were analyzed: age; TNM; the expression of ER, PGR, HER2, and Ki67; histological grade (G); and the response to neoadjuvant treatment (NAT) in the residual tumor burden classification (RCB). A complete pathological response (pCR) was achieved after NAT in 41 patients (34%). The highest proportion of the patients with a confirmed pCR was found for triple negative breast cancer (TNBC) (62.5%); non-luminal HER2-positive (52.6%) cancer subtypes (p = 0.0003); and in the G3 group (50%; p = 0.0078). The patients with higher levels of Aurora A were more likely to achieve pCR (p = 0.039). In the multivariate analysis, the serum Aurora A levels ≥ 4.75 ng/mL correlated with a higher rate of pCR (OR: 3.5; 95% CI: 1.2-10.1; p = 0.023).

CONCLUSIONS

We showed that in a biologically heterogeneous group of BC patients, the pretreatment serum Aurora A levels were of significant value in predicting the response to NAT.

One-pot wet-chemical fabrication of 3D urchin-like core-shell Au@PdCu nanocrystals for electrochemical breast cancer immunoassay

Carbohydrate antigen 15-3 (CA15-3) is an important biomarker for early diagnosis of breast cancer. Herein, a label-free electrochemical immunosensor was built based on three-dimensional (3D) urchin-like core-shell Au@PdCu nanocrystals (labeled Au@PdCu NCs) for highly sensitive detection of CA15-3, where K3[Fe(CN)6] behaved as an electroactive probe. The Au@PdCu NCs were synthesized by a simple one-pot wet-chemical approach and the morphology, structures, and electrocatalytic property were investigated by several techniques. The Au@PdCu NCs prepared worked as electrode material to anchor more antibodies and as signal magnification material by virtue of its exceptional catalytic property. The developed biosensor exhibited a wide linear detection range from 0.1 to 300 U mL-1 and a low limit of detection (0.011 U mL-1, S/N = 3) for determination of CA15-3 under the optimal conditions. The established biosensing platform exhibits some insights for detecting other tumor biomarkers in clinical assays and early diagnosis.

Evaluation of Serum Fructosamine as Diagnostic Marker of Postoperative Recurrence in the Patients with Breast Cancer

Objectives

A series of laboratory parameters were screened to identify the proper serum markers that could be used to predict breast cancer recurrence at an early stage.

Methods

A case-control retrospective study on 224 patients without postoperative recurrence and 43 patients with postoperative recurrence of breast cancer was performed. The edgeR software package was used to identify the test indicators expressed differently between the two groups. Univariate analysis was used to screen for diagnostic marker that could predict postoperative recurrence of breast cancer. In addition, the differential test indicators at different time points from surgery to recurrence were collected in patients with postoperative recurrence of breast cancer as a verification database.

Results

We screened out three test indicators (TBA, GSP, and URBC) for differential expression, which were all expressed downregulated in the postoperative recurrence group of breast cancer. Univariate analysis suggested that only the difference in GSP levels between the two groups was statistically significant (P = 0.001). ROC curve analysis showed that the area under the curve of GSP was 0.662, while the area under the curve of GSP+AFP+CEA+CA125+CA153+age was increased to 0.828. In addition, serum GSP levels were significantly reduced after recurrence compared with before recurrence in breast cancer patients (P < 0.01).

Conclusions

In summary, GSP could be used for early diagnosis of breast cancer recurrence after surgery, and the predicted value of combining GSP, tumor markers, and age was better than that of individual indicators.

Quantitative analysis of serum cell-free DNA as a predictive and prognostic marker in breast cancer patients

Introduction

According to the GLOBOCAN (Global Cancer Observatory) 2020 report, 13,028 new cases of breast cancer (19%) were diagnosed in the United States, and 6,783 of them succumbed to the disease, making it the most common cancer among women. The clinical stage at the time of diagnosis is one of the most significant survival predictors in breast cancer. With delayed illness detection comes a lower survival rate. The prognosis of breast cancer may be predicted using circulating cell-free DNA (cfDNA), a non-invasive diagnosis technique.

Objective

This study aimed to determine the most sensitive and effective method for detecting changes in cfDNA levels and for using cfDNA as a diagnostic and prognostic marker of breast cancer.

Methods

The potential function of serum cfDNA levels as a marker for early breast cancer diagnosis was investigated using UV spectrophotometric, fluorometric, and real-time qPCR assays.

Results

This research suggests that the most successful way to measure the amount of cfDNA described decades ago could be used as a "liquid biopsy" to track cancer in real time. The RT-qPCR (ALU115) method produced the most statistically significant results (p=0.000). At the threshold concentration of 395.65 ng/ml of cfDNA, the ROC curve reflects the maximum AUC= 0.7607, with a sensitivity of 0.65 and specificity of 0.80.

Conclusion

For a preliminary assessment of total circulating cfDNA, a combination of all of the above techniques will be most efficacious. Based on our results, we conclude that the RT-qPCR technique combined with fluorometric measurement can identify a statistically significant difference in cfDNA levels between cohorts of breast cancer patients and healthy controls.

Overexpression of C19orf48 correlates with poor prognosis in breast cancer

As one of the most commonly diagnosed cancers in women around the world, breast cancer has been detailed studied. This study aimed to identify the expression of c19orf48 in several kinds of cancers including liver, lung and breast cancers etc. The driving factors behind it were analysed and it found that the amplification of c19orf48 may relate with the elevated expression. At the same time, the correlation between the expression of it and the survival time in breast cancer patients was explored. It was found that the c19orf48 expression at transcriptional level elevated in breast cancer tissue samples compared with the normal. It was inferred that the c19orf48 play its oncogenic role in development of breast cancer by involving in cell-cycle related biological process. In conclusion, c19orf48 may be a useful and predictive biomarker for the prognosis of breast cancer patients. To the best of our knowledge, this is the first report describing the expression of c19orf48, the potential driving factor led to this and its effect.

Clinical and Translational Applications of Serological and Histopathological Biomarkers in Metastatic Breast Cancer: A Comprehensive Review

Breast cancer is one of the most common malignancies worldwide and the most common form of cancer in women. A large proportion of patients begin with localized disease and undergo treatment with curative intent, while another large proportion of patients debuts with disseminated metastatic disease. In the last subgroup of patients, the prognosis in recent years has changed radically, given the existence of different targeted therapies thanks to the discovery of different biomarkers. Serological, histological, and genetic biomarkers have demonstrated their usefulness in the initial diagnosis, in the follow-up to detect relapses, to guide targeted treatment, and to stratify the prognosis of the most aggressive tumors in those with breast cancer. Molecular markers are currently the basis for the diagnosis of metastatic disease, given the wide variety of chemotherapy regions and existing therapies. These markers have been a real revolution in the therapeutic arsenal for breast cancer, and their diagnostic validity allows the classification of tumors with higher rates of relapse, aggressiveness, and mortality. In this sense, the existence of therapies targeting different molecular alterations causes a series of changes in tumor biology that can be assessed throughout the course of the disease to provide information on the underlying pathophysiology of metastatic disease, which allows us to broaden our knowledge of the different mechanisms of tissue invasion. Therefore, the aim of the present article is to review the clinical, diagnostic, predictive, prognostic utility and limitations of the main biomarkers available and under development in metastatic breast cancer.

Therapeutic Effects of Coumarins with Different Substitution Patterns

The use of derivatives of natural and synthetic origin has gained attention because of their therapeutic effects against human diseases. Coumarins are one of the most common organic molecules and are used in medicine for their pharmacological and biological effects, such as anti-inflammatory, anticoagulant, antihypertensive, anticonvulsant, antioxidant, antimicrobial, and neuroprotective, among others. In addition, coumarin derivates can modulate signaling pathways that impact several cell processes. The objective of this review is to provide a narrative overview of the use of coumarin-derived compounds as potential therapeutic agents, as it has been shown that substituents on the basic core of coumarin have therapeutic effects against several human diseases and types of cancer, including breast, lung, colorectal, liver, and kidney cancer. In published studies, molecular docking has represented a powerful tool to evaluate and explain how these compounds selectively bind to proteins involved in various cellular processes, leading to specific interactions with a beneficial impact on human health. We also included studies that evaluated molecular interactions to identify potential biological targets with beneficial effects against human diseases.

Reflective FT-NIR and SERS studies of HER-II breast cancer biomarker using plasmonic-active nanostructured thin film immobilized oriented antibody

We describe the fabrication of plasmonic-active nanostructured thin film substrate as a label-free surface-enhanced Raman scattering (SERS)-based biosensor immobilized covalently with monoclonal HER-II antibody (mAb) to detect overexpressed HER-II as a biomarker in breast cancer serum (BCS). Oriented conjugation of mAb via hydrazone linkage to provide higher mAb accessibility was characterized by UV-vis and reflective Fourier transform near-infrared (FT-NIR) spectroscopic techniques. The interaction of BCS with mAb was studied by FT-NIR and nonresonant SERS at 637 nm. The results showed detection of glycoprotein content at different laser powers including a rise in amino acid and glycan content with varying results at higher power. With nonresonant SERS we observed nonlinear behavior of peak intensity. Analysis of variance was implemented to determine the effect of laser power which was found not to be a contributing factor. However, at the nanoscale, factors including the heating effect and aggregation of molecules can contribute to the nonlinearity of peak intensity.

Clinical trial-identified inflammatory biomarkers in breast and pancreatic cancers

Breast cancer and pancreatic cancer are two common cancer types characterized by high prevalence and high mortality rates, respectively. However, breast cancer has been more well-studied than pancreatic cancer. This narrative review curated inflammation-associated biomarkers from clinical studies that were systematically selected for both breast and pancreatic cancers and discusses some of the common and unique elements between the two endocrine-regulated malignant diseases. Finding common ground between the two cancer types and specifically analyzing breast cancer study results, we hoped to explore potential feasible methods and biomarkers that may be useful also in diagnosing and treating pancreatic cancer. A PubMed MEDLINE search was used to identify articles that were published between 2015-2022 of different kinds of clinical trials that measured immune-modulatory biomarkers and biomarker changes of inflammation defined in diagnosis and treatment of breast cancer and pancreatic cancer patients. A total of 105 papers (pancreatic cancer 23, breast cancer 82) were input into Covidence for the title and abstract screening. The final number of articles included in this review was 73 (pancreatic cancer 19, breast cancer 54). The results showed some of the frequently cited inflammatory biomarkers for breast and pancreatic cancers included IL-6, IL-8, CCL2, CD8+ T cells and VEGF. Regarding unique markers, CA15-3 and TNF-alpha were two of several breast cancer-specific, and CA19 and IL-18 were pancreatic cancer-specific. Moreover, we discussed leptin and MMPs as emerging biomarker targets with potential use for managing pancreatic cancer based on breast cancer studies in the future, based on inflammatory mechanisms. Overall, the similarity in how both types of cancers respond to or result in further disruptive inflammatory signaling, and that point to a list of markers that have been shown useful in diagnosis and/or treatment method response or efficacy in managing breast cancer could potentially provide insights into developing the same or more useful diagnostic and treatment measurement inflammatory biomarkers for pancreatic cancer. More research is needed to investigate the relationship and associated inflammatory markers between the similar immune-associated biological mechanisms that contribute to breast and pancreatic cancer etiology, drive disease progression or that impact treatment response and reflect survival outcomes.

Non-invasive optical characterization and detection of CA 15-3 breast cancer biomarker in blood serum using monoclonal antibody-conjugated gold nanourchin and surface-enhanced Raman scattering

A proof-of-concept of colloidal surface-enhanced Raman scattering (SERS) substrate for rapid selective detection of overexpressed CA 15-3 biomarker in breast cancer serum (BCS) is suggested using PEGylated gold nanourchins (GNUs) conjugated with anti-CA 15-3 monoclonal antibody (mAb). UV-vis spectroscopy provided conformational information about mAb where the initial aromatic amino acid peak was red-shifted from 271 to 291 nm. The fluorescence peak of tyrosine in mAb was reduced by ≈ 77%, and red-shifted by ≈ 3 nm after incubation in BCS. Fourier transform near-infrared spectroscopy and SERS were used to study the composition and the molecular structure of the mAb and BCS. Some of the most dominant Raman shifts after GNU-PEG-mAb interaction with BCS are 498, 736, 818, 1397, 1484, 2028, 2271, and 3227 cm-1 mainly corresponding to C-N-C in amines, vibrational modes of amino acids, C-H out-of-plane bend, C-O stretching carboxylic acid, the vibrational mode in phospholipids, NH3+ amine salt, C≡N stretching in nitriles, and O-H stretching. The intensity of SERS signals varied per trial due to the statistical behavior of GNU in BCS, agglomeration, laser power, and the heating effect. Despite very small amount of plasmonic heating, the result of the ANOVA test demonstrated that under our experimental conditions, the heating effect on signal variation is negligible and that the differences in the laser power are insignificant for all SERS observations (p > 0.6); thus, other parameters are responsible. The absorbance of mAb-conjugated GNU was decreased after five minutes of irradiation at 8 mW in the BCS.

Recent advances in multifunctional dendrimer-based nanoprobes for breast cancer theranostics

Breast cancer (BC) undoubtedly is one of the most common type of cancers amongst women, which causes about 5 million deaths annually. The treatments and diagnostic therapy choices currently available for Breast Cancer is very much limited . Advancements in novel nanocarrier could be a promising strategy for diagnosis and treatments of this deadly disease. Dendrimer nanoformulation could be functionalized and explored for efficient targeting of overexpressed receptors on Breast Cancer cells to achieve targeted drug delivery, for diagnostics and to overcome the resistance of the cells towards particular chemotherapeutic. Additionally, the dendrimer have shown promising potential in the improvement of therapeutic value for Breast Cancer therapy by achieving synergistic co-delivery of chemotherapeutics and genetic materials for multidirectional treatment. In this review, we have highlighted the application of dendrimer as novel multifunctional nanoplatforms for the treatment and diagnosis of Breast Cancer.

Exosomal microRNAs in breast cancer and their potential in diagnosis, prognosis and treatment prediction

The significance of exosomal microRNAs (EmiRs) in breast cancer (BC) diagnosis has been widely addressed over the past decades. However, little information is still available regarding these reliable biomarkers' impacts on BC early diagnosis, prognosis, and treatment outcome predictions, but their great potential in spotting BC early and their predictive essence in BC prognosis and treatment results are promising against this common cancer. The present review focuses on the most recent findings and advancements of EmiRs applications in BC early diagnosis and treatment prediction and identifies current helpful EmiRs that are widely used in this regard.

Circulating proteins as predictive and prognostic biomarkers in breast cancer

Breast cancer (BC) is the most common cancer and among the leading causes of cancer death in women. It is a heterogeneous group of tumours with numerous morphological and molecular subtypes, making predictions of disease evolution and patient outcomes difficult. Therefore, biomarkers are needed to help clinicians choose the best treatment for each patient. For the last years, studies have increasingly focused on biomarkers obtainable by liquid biopsy. Circulating proteins (from serum or plasma) can be used for inexpensive and minimally invasive determination of disease risk, early diagnosis, treatment adjusting, prognostication and disease progression monitoring. We provide here a review of the main published studies on serum proteins in breast cancer and elaborate on the potential of circulating proteins to be predictive and/or prognostic biomarkers in breast cancer.

Tumor biomarkers CEA, CA19.9, CA15.3 and AFP levels in the serum of patients with COVID-19

Early diagnosis is very important to reduce morbidity and mortality in COVID-19 infected patients. The aim of this study was to detect of tumor antigens CEA, CA19.9, CA15.3, and AFP and to compare their levels in the serum of 69 COVID-19 patients and 69 healthy individuals who did not have COVID-19. The levels of CEA, CA19.9, CA15.3, and AFP in the serum were measured using ELISA. The levels of the tumor biomarkers in the serum of COVID-19 patients were found to be 7.74 ± 4.65 ng/ml for CEA, 29.33 ± 16.35 U/ml for CA19.9, 23.24 ± 13.48 U/ml for CA15.3 and 7.46 ± 5.57 ng/ml for AFP, while in the serum of healthy control patients 9.73 ± 43.58 ng/ml for CEA, 20.66 ± 11.1 for CA19.9, 19.64 ± 10.99 U/ml for CA15.3, and 3.83 ± 9.20 ng/ml for AFP, indicating no differences in the levels of the studied tumor biomarkers in the two experimental groups. It is concluded that tumor biomarkers CEA, CA19.9, CA15.3, and AFP cannot be used as effective screening tools for patients with COVID-19.

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.

Exosomes in breast cancer management: Where do we stand? A literature review

BACKGROUND

Exosomes constitute cellular molecular fingertips that participate in intercellular communication both in health and disease states. Hence, exosomes emerge as critical mediators of cancer development and progression, as well as potential biomarkers and novel therapeutic targets.

OBJECTIVE

To review literature data regarding applications of circulating exosomes in breast cancer management.

METHODS

This is a literature review of relevant published studies until April 2020 in PubMed and Google Scholar databases. Original papers in the English language concerning exosome related studies were included.

RESULTS

Exosomes represent molecular miniatures of their parent cells. Several homeostatic mechanisms control exosomal secretion and synthesis. Exosomal exchange among cells creates an intricate intercellular crosstalk orchestrating almost every tissue process, as well as carcinogenesis. Available data highlight exosomes as major mediators of cancer development and progression. The secretion of specific exosomal molecules, particularly miRNAs, correlates with the underlying processes and can be used as a means of tumor detection and prognostic assessment.

CONCLUSIONS

Exosomal miRNAs expression profiles and levels closely relate to cancer extent, type and prognosis. Deep comprehension of such correlations and systematization of experimental outcomes will offer a novel approach in cancer detection and management.

Circulating proteins reveal prior use of menopausal hormonal therapy and increased risk of breast cancer

Accessible risk predictors are crucial for improving the early detection and prognosis of breast cancer. Blood samples are widely available and contain proteins that provide important information about human health and disease, however, little is still known about the contribution of circulating proteins to breast cancer risk prediction. We profiled EDTA plasma samples collected before diagnosis from the Swedish KARMA breast cancer cohort to evaluate circulating proteins as molecular predictors. A data-driven analysis strategy was applied to the molecular phenotypes built on 700 circulating proteins to identify and annotate clusters of women. The unsupervised analysis of 183 future breast cancer cases and 366 age-matched controls revealed five stable clusters with distinct proteomic plasma profiles. Among these women, those in the most stable cluster (N = 19; mean Jaccard index: 0.70 ± 0.29) were significantly more likely to have used menopausal hormonal therapy (MHT), get a breast cancer diagnosis, and were older compared to the remaining clusters. The circulating proteins associated with this cluster (FDR < 0.001) represented physiological processes related to cell junctions (F11R, CLDN15, ITGAL), DNA repair (RBBP8), cell replication (TJP3), and included proteins found in female reproductive tissue (PTCH1, ZP4). Using a data-driven approach on plasma proteomics data revealed the potential long-lasting molecular effects of menopausal hormonal therapy (MHT) on the circulating proteome, even after women had ended their treatment. This provides valuable insights concerning proteomics efforts to identify molecular markers for breast cancer risk prediction.

Diagnostic performance improvement with combined use of proteomics biomarker assay and breast ultrasound

PURPOSE

To investigate the combined use of blood-based 3-protein signature and breast ultrasound (US) for validating US-detected lesions.

METHODS

From July 2011 to April 2020, women who underwent whole-breast US within at least 6 months from sampling period were retrospectively included. Blood-based 3-protein signature (Mastocheck®) value and US findings were evaluated. Following outcome measures were compared between US alone and the combination of Mastocheck® value with US: sensitivity, specificity, positive predictive value (PPV), negative predictive value, area under the receiver operating characteristic curve (AUC), and biopsy rate.

RESULTS

Among the 237 women included, 59 (24.9%) were healthy individuals and 178 (75.1%) cancer patients. Mean size of cancers was 1.2 ± 0.8 cm. Median value of Mastocheck® was significantly different between nonmalignant (- 0.24, interquartile range [IQR] - 0.48, - 0.03) and malignant lesions (0.55, IQR - 0.03, 1.42) (P < .001). Utilizing Mastocheck® value with US increased the AUC from 0.67 (95% confidence interval [CI] 0.61, 0.73) to 0.81 (95% CI 0.75, 0.88; P < .001), and specificity from 35.6 (95% CI 23.4, 47.8) to 64.4% (95% CI 52.2, 76.6; P < .001) without loss in sensitivity. PPV was increased from 82.2 (95% CI 77.1, 87.3) to 89.3% (95% CI 85.0, 93.6; P < .001), and biopsy rate was significantly decreased from 79.3 (188/237) to 72.1% (171/237) (P < .001). Consistent improvements in specificity, PPV, and AUC were observed in asymptomatic women, in women with dense breast, and in those with normal/benign mammographic findings.

CONCLUSION

Mastocheck® is an effective tool that can be used with US to improve diagnostic specificity and reduce false-positive findings and unnecessary biopsies.

Identification and validation of plasma biomarkers for diagnosis of breast cancer in South Asian women

Breast cancer is the most common malignancy among women globally. Development of a reliable plasma biomarker panel might serve as a non-invasive and cost-effective means for population-based screening of the disease. Transcriptomic profiling of breast tumour, paired normal and apparently normal tissues, followed by validation of the shortlisted genes using TaqMan® Low density arrays and Quantitative real-time PCR was performed in South Asian women. Fifteen candidate protein markers and 3 candidate epigenetic markers were validated first in primary breast tumours and then in plasma samples of cases [N = 202 invasive, 16 DCIS] and controls [N = 203 healthy, 37 benign] using antibody array and methylation specific PCR. Diagnostic efficiency of single and combined markers was assessed. Combination of 6 protein markers (Adipsin, Leptin, Syndecan-1, Basic fibroblast growth factor, Interleukin 17B and Dickopff-3) resulted in 65% sensitivity and 80% specificity in detecting breast cancer. Multivariate diagnostic analysis of methylation status of SOSTDC1, DACT2, WIF1 showed 100% sensitivity and up to 91% specificity in discriminating BC from benign and controls. Hence, combination of SOSTDC1, DACT2 and WIF1 was effective in differentiating breast cancer [non-invasive and invasive] from benign diseases of the breast and healthy individuals and could help as a complementary diagnostic tool for breast cancer.

Decreased serum levels of glycerol-3- phosphate dehydrogenase 1 and monoacylglycerol lipase act as diagnostic biomarkers for breast cancer

BACKGROUND

Breast cancer (BC) is one of the most life-threatening cancer types among women. Despite major developments in medical sciences and technologies, the incidence and mortality rates of BC cases are still increasing. One of the reasons for this increase is the absence of an easy to perform early-diagnostic tool. Although there are defined BC biomarkers routinely used for diagnostic and prognostic purposes, none of these biomarkers is useful for early diagnosis. Therefore, early diagnosis of BC remains an important challenge and there is a great need for the early-diagnostic biomarker(s).

OBJECTIVE

In this study, we aimed to evaluate the diagnostic and prognostic values of glycerol-3-phosphate dehydrogenase (GPD1) and monoacylglycerol lipase (MAGL) proteins as non-invasive serum biomarkers.

METHODS

GPD1 and MAGL serum levels were determined by ELISA for BC patients (n= 100) from five different subtypes, and healthy controls (n= 20), and a comparative analysis was performed to determine statistically significant expression differences among the groups.

RESULTS

The results provided evidence that GPD1 acted as a diagnostic biomarker in distinguishing triple-negative breast cancer (TNBC) patients from other subtypes, and MAGL acted as a diagnostic biomarker in distinguishing healthy individuals from BC patients.

CONCLUSION

GPD1 and MAGL might be proposed as non-invasive diagnostic biomarkers for BC with high sensitivity and specificity.

Genome-Wide DNA Methylation Signatures Predict the Early Asymptomatic Doxorubicin-Induced Cardiotoxicity in Breast Cancer

Chemotherapy with doxorubicin (DOX) may cause unpredictable cardiotoxicity. This study aimed to determine whether the methylation signature of peripheral blood mononuclear cells (PBMCs) prior to and after the first cycle of DOX-based chemotherapy could predict the risk of cardiotoxicity in breast cancer patients. Cardiotoxicity was defined as a decrease in left ventricular ejection fraction (LVEF) by >10%. DNA methylation of PBMCs from 9 patients with abnormal LVEF and 10 patients with normal LVEF were examined using Infinium HumanMethylation450 BeadChip. We have identified 14,883 differentially methylated CpGs at baseline and 18,718 CpGs after the first cycle of chemotherapy, which significantly correlated with LVEF status. Significant differentially methylated regions (DMRs) were found in the promoter and the gene body of SLFN12, IRF6 and RNF39 in patients with abnormal LVEF. The pathway analysis found enrichment for regulation of transcription, mRNA splicing, pathways in cancer and ErbB2/4 signaling. The preliminary results from this study showed that the DNA methylation profile of PBMCs may predict the risk of DOX-induced cardiotoxicity prior to chemotherapy. Further studies with larger cohorts of patients are needed to confirm these findings.

Heat shock protein 90α in nipple discharge as a potential tumor marker for breast cancer

Heat shock protein 90α (HSP90α) has been confirmed to be upregulated in the blood in various types of tumors and may therefore serve as a potential tumor marker. However, whether HSP90α exists in nipple discharge remains unknown, and its expression and diagnostic value in nipple discharge remain unclear. In this study, the expression of HSP90α, carcinoembryonic antigen (CEA), and cancer antigen 153 in nipple discharge and blood from 128 patients was measured. Receiver operating characteristic curve was used to assess the diagnostic value of HSP90α. Further, its relationship with clinicopathological parameters of patients with breast cancer was analyzed. The results showed that the expression of HSP90α in nipple discharge was significantly higher in patients with breast cancer than in those with benign disease, and its diagnostic value was better than that of CEA. Combination of HSP90α and CEA showed better diagnostic efficacy than HSP90α or CEA alone. Moreover, the expression of HSP90α displayed a stepwise increase from benign lesions, followed by carcinoma in situ to invasive ductal carcinoma. HSP90α was positively correlated with Ki67 expression. However, there was no significant difference in the expression of HSP90α in blood between patients with breast cancer and benign disease. Further, the expression of HSP90α was higher in nipple discharge than in blood. In summary, HSP90α was upregulated in the nipple discharge of patients with breast cancer, and it may be related to the occurrence and progression of breast cancer. HSP90α in nipple discharge may serve as a potential diagnostic marker for breast cancer.

Evaluation of early post-natal pig mammary gland development and human breast cancer gene expression

Breast cancer is the second leading cause of death in women after lung cancer, and only 5% of patients with metastatic breast cancer survive beyond ten years of diagnosis. Considering the heterogeneous subclasses of breast cancer, current cancer models have shortfalls due to copy number variants, and genetic differences of humans and immunocompromised animal models. Preclinical studies indicate stem cell activity in early post-natal mammary development may be reactivated in the human adult as a trigger to initiate cell proliferation leading to breast cancer. The goal of the work reported herein was to compare genetic expression of early development, post-natal pig mammary glands to the literature reported genes implicated in different subclasses of human breast cancer. Differentially expressed genes associated with breast cancer and present in early developing pig samples include NUCB2, ANGPTL4 and ACE. Histological staining confirmed E-cadherin, Vimentin, N-cadherin, and Claudin-1, which are all implicated in malignant cancer. Due to the homology of gene expression patterns in the developing pig mammary gland and reported genes in human breast cancer profiles, this research is worthy of further study to address a potential model using mammary development cues to unravel breast cancer biology.

Proteomics and its applications in breast cancer

Breast cancer is an individually unique, multi-faceted and chameleonic disease, an eternal challenge for the new era of high-integrated precision diagnostic and personalized oncomedicine. Besides traditional single-omics fields (such as genomics, epigenomics, transcriptomics and metabolomics) and multi-omics contributions (proteogenomics, proteotranscriptomics or reproductomics), several new "-omics" approaches and exciting proteomics subfields are contributing to basic and advanced understanding of these "multiple diseases termed breast cancer": phenomics/cellomics, connectomics and interactomics, secretomics, matrisomics, exosomics, angiomics, chaperomics and epichaperomics, phosphoproteomics, ubiquitinomics, metalloproteomics, terminomics, degradomics and metadegradomics, adhesomics, stressomics, microbiomics, immunomics, salivaomics, materiomics and other biomics. Throughout the extremely complex neoplastic process, a Breast Cancer Cell Continuum Concept (BCCCC) has been modeled in this review as a spatio-temporal and holistic approach, as long as the breast cancer represents a complex cascade comprising successively integrated populations of heterogeneous tumor and cancer-associated cells, that reflect the carcinoma's progression from a "driving mutation" and formation of the breast primary tumor, toward the distant secondary tumors in different tissues and organs, via circulating tumor cell populations. This BCCCC is widely sustained by a Breast Cancer Proteomic Continuum Concept (BCPCC), where each phenotype of neoplastic and tumor-associated cells is characterized by a changing and adaptive proteomic profile detected in solid and liquid minimal invasive biopsies by complex proteomics approaches. Such a profile is created, beginning with the proteomic landscape of different neoplastic cell populations and cancer-associated cells, followed by subsequent analysis of protein biomarkers involved in epithelial-mesenchymal transition and intravasation, circulating tumor cell proteomics, and, finally, by protein biomarkers that highlight the extravasation and distant metastatic invasion. Proteomics technologies are producing important data in breast cancer diagnostic, prognostic, and predictive biomarkers discovery and validation, are detecting genetic aberrations at the proteome level, describing functional and regulatory pathways and emphasizing specific protein and peptide profiles in human tissues, biological fluids, cell lines and animal models. Also, proteomics can identify different breast cancer subtypes and specific protein and proteoform expression, can assess the efficacy of cancer therapies at cellular and tissular level and can even identify new therapeutic target proteins in clinical studies.

Inhibition of heat shock protein (HSP) 90 reverses signal transducer and activator of transcription (STAT) 3-mediated muscle wasting in cancer cachexia mice

BACKGROUND AND PURPOSE

Cancer cachexia is a common cause of death among cancer patients with no currently effective treatment available. In animal models, aberrant activation of STAT3 in skeletal muscle contributes to muscle wasting. However, clinically the factors regulating STAT3 activation and the molecular mechanisms involved remain incompletely understood.

EXPERIMENTAL APPROACH

The expression of HSP90 and the activation of STAT3 were detected in muscle from the patients with cancer cachexia or the tumour-bearing cachectic mice. HSP90 inhibitors, including 17DMAG (alvespimycin) and PU-H71, were administered to cachexic mice and cachexia parameters, weight loss, food intake, survival rate, body composition, serum metabolites, muscle wasting pathology and catabolic activation were analysed. The co-culture of C2C12 myotube cells with C26 conditioned media was performed to investigate the pathological mechanism involved in catabolic muscle wasting. The roles of HSP90, STAT3 and FOXO1 in myotube atrophy were explored via overexpression or knockdown.

RESULTS

An enhanced interaction between activated STAT3 and HSP90 in the skeletal muscle of cancer cachexia patients, is a crucial for the development of cachectic muscle wasting. HSP90 inhibitors 17DMAG and PU-H71 alleviated the muscle wasting in C26 and models or the myotube atrophy of C2C12 cells induced by C26 conditional medium. Prolonged STAT3 activation transactivated FOXO1 by binding directly to its promoter and triggered the muscle wasting in a FOXO1-dependent manner in muscle cells.

CONCLUSION AND IMPLICATIONS

The HSP90/STAT3/FOXO1 axis plays a critical role in cachectic muscle wasting, which might be a potential therapeutic target for the treatment of cancer cachexia.

The Signal Transducer IL6ST (gp130) as a Predictive and Prognostic Biomarker in Breast Cancer

Novel biomarkers are needed to continue to improve breast cancer clinical management and outcome. IL6-like cytokines, whose pleiotropic functions include roles in many hallmarks of malignancy, rely on the signal transducer IL6ST (gp130) for all their signalling. To date, 10 separate independent studies based on the analysis of clinical breast cancer samples have identified IL6ST as a predictor. Consistent findings suggest that IL6ST is a positive prognostic factor and is associated with ER status. Interestingly, these studies include 4 multigene signatures (EndoPredict, EER4, IRSN-23 and 42GC) that incorporate IL6ST to predict risk of recurrence or outcome from endocrine or chemotherapy. Here we review the existing evidence on the promising predictive and prognostic value of IL6ST. We also discuss how this potential could be further translated into clinical practice beyond the EndoPredict tool, which is already available in the clinic. The most promising route to further exploit IL6ST's promising predicting power will likely be through additional hybrid multifactor signatures that allow for more robust stratification of ER+ breast tumours into discrete groups with distinct outcomes, thus enabling greater refinement of the treatment-selection process.

Aptamer-based fluorescent sensors for the detection of cancer biomarkers

Aptamers are short single-stranded RNA or DNA molecules that can recognize a series of targets with high affinity and specificity. Known as "chemical antibodies", aptamers have many unique merits, including ease of chemical synthesis, high chemical stability, low molecular weight, lack of immunogenicity, and ease of modification and manipulation compared to their protein counterparts. Using aptamers as the recognition groups, fluorescent aptasensors provide exciting opportunities for sensitive detection and quantification of analytes. Herein, we give an overview on the recent development of aptamer-based fluorescent sensors for the detection of cancer biomarkers. Based on various nanostructured sensor designs, we extended our discussions on sensitivity, specificity and the potential applications of aptamer-based fluorescent sensors in early diagnosis, treatment and prognosis of cancers.

Clinical impact of LncRNA XIST and LncRNA NEAT1 for diagnosis of high-risk group breast cancer patients

Long noncoding RNAs (lncRNAs) are evolving as contributing biomarkers for many diseases. Among these lncRNAs, X inactive-specific transcript (XIST), and nuclear paraspeckle assembly transcript 1 (NEAT1) were studied as undesirable upregulated nucleic acid markers for unfavorable prognosis of cancer. The authors aimed to investigate their role as diagnostic markers for breast cancer (BC) patients with high-risk factors. Serum samples were obtained from BC patients (n = 121), patients with benign breast lesions (n = 35), and healthy volunteers (n = 22). Assessment of lncRNA XIST, and lncRNA NEAT1 expression was performed using real time PCR. Expression levels of the investigated lncRNAs were significantly higher in BC patients as compared to the other groups. Both lncRNAs were significantly correlated with BC laterality, lymph node involvement, and clinical stages. LncRNA NEAT1 reported a significant aberrant expression with pathological types, histological grading and, hormonal status. The sensitivity of lncRNA NEAT1 was superior for detection of BC with high risk-factors as compared to lncRNA XIST. In conclusion, the detection of lncRNAs in body fluids has demonstrated a significant importance for detecting BC patients with high-risk factors, and was related to hormonal receptors, thus may be used for determining the direction of treatment strategy.

Sandwich-Type Electrochemical Paper-Based Immunosensor for Claudin 7 and CD81 Dual Determination on Extracellular Vesicles from Breast Cancer Patients

This study is focused on identifying novel epithelial markers in circulating extracellular vesicles (EVs) through the development of a dual sandwich-type electrochemical paper-based immunosensor for Claudin 7 and CD81 determination, as well as its validation in breast cancer (BC) patients. This immunosensor allows for rapid, sensitive, and label-free detection of these two relevant BC biomarkers. Under optimum conditions, the limit of detection for Claudin 7 was 0.4 pg mL^-1, with a wide linear range of 2 to 1000 pg mL^-1, while for CD81, the limit of detection was 3 pg mL^-1, with a wide linear range of 0.01 to 10 ng mL^-1. Finally, we validated Claudin 7 and CD81 determination in EVs from 60 BC patients and 20 healthy volunteers, reporting higher diagnostic accuracy than the one observed with classical diagnostic markers. This analysis provides a low-cost, specific, versatile, and user-friendly strategy as a robust and reliable tool for early BC diagnosis.

Discovery and Proof-of-Concept Study of Nuclease Activity as a Novel Biomarker for Breast Cancer Tumors

Simple Summary

A diagnostic biomarker for the detection of breast cancer remains an unmet clinical need despite decades of intensive research efforts. Herein, we describe, for the first time, the use of nuclease activity as a biomarker to discriminate between healthy and cancer biopsy samples. We have identified a panel of three nucleic acid probes able to target nucleases derived from breast cancer tumors with high sensitivity and specificity. These results are in good agreement with histopathological analysis as the diagnostic gold standard. Moreover, these findings support nuclease activity as a potential adjacent diagnostic tool and shed light on the use of nuclease activity as a detection biomarker in breast cancer.

Abstract

Breast cancer is one of the most common pathologies diagnosed in the clinical practice. Despite major advancements in diagnostic approaches, there is no widely accepted biomarker in the clinical practice that can diagnose breast malignancy. Confirmatory diagnosis still relies on the pathological assessment of tissue biopsies by expert pathologists. Thus, there is an unmet need for new types of biomarkers and novel platform technologies that can be easily and robustly integrated into the clinic and that can assist pathologists. Herein, we show that nuclease activity associated to malignant tumors can be used as a novel biomarker in breast cancer, which can be detected via specific degradation of nucleic acid probes. In this study we have identified a set of three chemically modified nucleic acid probes that can diagnose malignancy in biopsy samples with high accuracy (89%), sensitivity (82%) and specificity (94%). This work represents a breakthrough for the potential clinical use of nuclease activity as biomarker, which can be detected via nucleic acids probes, for the clinical diagnosis of malignancy in breast tissue biopsies. This platform technology could be readily implemented into the clinic as adjunct to histopathological diagnostic.

Cardiac, Hepatic and Renal Dysfunction and IL-18 Polymorphism in Breast, Colorectal, and Prostate Cancer Patients

INTRODUCTION

The present study aimed to determine the alterations in the serum levels of tumor markers used to evaluate cardiac, renal and liver function, and detect the interleukin (IL)-18 rs1946518 polymorphism in breast (BC), colorectal (CRC) and prostate cancer (PCa) patients.

METHODS

Blood samples were collected from 65 female BC, 116 CRC, 79 PCa and 88 myocardial infarction (MI) patients, and 110 healthy individuals to determine the concentration of tumor and cardiac markers. Furthermore, the IL-18 rs1946518 polymorphism was assessed using amplification refractory mutation system (ARMS)-PCR.

RESULTS

The serum levels of the tumor markers cancer antigen 15-3 (CA 15-3), carbohydrate antigen 19-9 (CA 19-9), carcinoembryonic antigen (CEA) and total prostate-specific antigen (TPSA) were significantly increased in cancer patients compared with healthy controls. Furthermore, the activity of high-sensitivity cardiac troponin T (hs-cTnT) and creatine kinase‑myocardial band (CK-MB) was enhanced in MI patients, however, their activity was unchanged in cancer patients. The activity of alkaline phosphatase (ALP), and the serum concentration of aspartate aminotransferase (AST), alanine aminotransferase (ALT) and urea were markedly elevated in CRC and PCa patients, respectively, compared with the control group. Although, no significant differences were observed in the -607 C/A polymorphism and allele frequency of IL-18 among BC, CRC patients and healthy individuals, the odds ratio (OR) was 1.75 for both C and A allele in BC patients. Therefore, the -607 C/A polymorphism could be considered as a risk factor for BC.

CONCLUSION

The aforementioned results suggested that tumor markers could be considered as excellent biomarkers for the early detection of BC, CRC and PCa, whereas the concentration of liver enzymes could serve as an alternative indicator for the diagnosis of CRC and PCa. Additionally, the rs1946518 polymorphism in the IL-18 gene could be considered as a risk factor for the occurrence of BC, CRC and PCa.<br />.

Non-Invasive Biomarkers for Early Detection of Breast Cancer

Breast cancer is the most common cancer in women worldwide. Accurate early diagnosis of breast cancer is critical in the management of the disease. Although mammogram screening has been widely used for breast cancer screening, high false-positive and false-negative rates and radiation from mammography have always been a concern. Over the last 20 years, the emergence of "omics" strategies has resulted in significant advances in the search for non-invasive biomarkers for breast cancer diagnosis at an early stage. Circulating carcinoma antigens, circulating tumor cells, circulating cell-free tumor nucleic acids (DNA or RNA), circulating microRNAs, and circulating extracellular vesicles in the peripheral blood, nipple aspirate fluid, sweat, urine, and tears, as well as volatile organic compounds in the breath, have emerged as potential non-invasive diagnostic biomarkers to supplement current clinical approaches to earlier detection of breast cancer. In this review, we summarize the current progress of research in these areas.

Differential Expression of Blood Group Precursor Antigen in Human Breast Cancer Tissue

There is a pressing need for biomarkers for targeted immunotherapy against breast cancer (BCA), the leading cause of cancer death in women. Previously, a blood group precursor O-core epitope gp^Cl was found to be highly expressed in breast circulating tumor cells (BCTCs) and BCA cell lines with cancer stem cell (BCSC) features. In this pilot study, the breast tissue distribution of gp^C1 was examined using tissue microarrays (TMAs). Notably, gp^C1 positive cells were detected in the major histological types of neoplastic breast tissues. Conversely, none of the breast tissues derived from subjects without BCA were gp^C1 positive. Thus, gp^C1 expression seems to be tumor-specific but not histological type-dependent, reflecting perhaps its characteristics as a conserved epitope of oncofetal blood group precursor antigens.

Liquid biopsy for breast cancer using extracellular vesicles and cell-free microRNAs as biomarkers

Improvement of breast cancer (BC) patient's outcome is directly related to early detection. However, there is still a lack of reliable biomarkers for diagnosis, prognosis and, treatment follow up in BC, leading researchers to study the potential of liquid biopsy based on circulating microRNAs (c-miRNAs). These c-miRNAs can be cell-free or associated with extracellular vesicles (EVs), and have great advantages such as stability in biofluids, noninvasive accessibility compared to current techniques (core-biopsy and surgery), and expression associated with pathogenic conditions. Recently, a new promising field of EV-derived miRNAs (EV-miRNAs) as cancer biomarkers has emerged, receiving special attention due to their selective vesicle sorting which makes them accurate for disease detection. In this review, we discuss new findings about c-miRNA and their potential as biomarkers for BC diagnosis, prognosis, and therapy. Additionally, we address the impact of limitations associated with the standardization of analysis techniques and methods on the implementation of these biomarkers in the clinical setting.

Challenges and Opportunities in Clinical Applications of Blood-Based Proteomics in Cancer

Simple Summary

The traditional approach in identifying cancer related protein biomarkers has focused on evaluation of a single peptide/protein in tissue or circulation. At best, this approach has had limited success for clinical applications, since multiple pathological tumor pathways may be involved during initiation or progression of cancer which diminishes the significance of a single candidate protein/peptide. Emerging sensitive proteomic based technologies like liquid chromatography mass spectrometry (LC-MS)-based quantitative proteomics can provide a platform for evaluating serial serum or plasma samples to interrogate secreted products of tumor–host interactions, thereby revealing a more “complete” repertoire of biological variables encompassing heterogeneous tumor biology. However, several challenges need to be met for successful application of serum/plasma based proteomics. These include uniform pre-analyte processing of specimens, sensitive and specific proteomic analytical platforms and adequate attention to study design during discovery phase followed by validation of discovery-level signatures for prognostic, predictive, and diagnostic cancer biomarker applications.

Abstract

Blood is a readily accessible biofluid containing a plethora of important proteins, nucleic acids, and metabolites that can be used as clinical diagnostic tools in diseases, including cancer. Like the on-going efforts for cancer biomarker discovery using the liquid biopsy detection of circulating cell-free and cell-based tumor nucleic acids, the circulatory proteome has been underexplored for clinical cancer biomarker applications. A comprehensive proteome analysis of human serum/plasma with high-quality data and compelling interpretation can potentially provide opportunities for understanding disease mechanisms, although several challenges will have to be met. Serum/plasma proteome biomarkers are present in very low abundance, and there is high complexity involved due to the heterogeneity of cancers, for which there is a compelling need to develop sensitive and specific proteomic technologies and analytical platforms. To date, liquid chromatography mass spectrometry (LC-MS)-based quantitative proteomics has been a dominant analytical workflow to discover new potential cancer biomarkers in serum/plasma. This review will summarize the opportunities of serum proteomics for clinical applications; the challenges in the discovery of novel biomarkers in serum/plasma; and current proteomic strategies in cancer research for the application of serum/plasma proteomics for clinical prognostic, predictive, and diagnostic applications, as well as for monitoring minimal residual disease after treatments. We will highlight some of the recent advances in MS-based proteomics technologies with appropriate sample collection, processing uniformity, study design, and data analysis, focusing on how these integrated workflows can identify novel potential cancer biomarkers for clinical applications.

Impact of Granulocyte Colony-Stimulating Factor (G-CSF) and Epoetin (EPO) on Hematologic Toxicities and Quality of Life in Patients During Adjuvant Chemotherapy in Early Breast Cancer: Results From the Multi-Center Randomized ADEBAR Trial

BACKGROUND

Hematologic toxicities are one of the greatest challenges in adjuvant chemotherapy for breast cancer. This analysis of the ADEBAR trial aims to evaluate application and effect of granulocyte colony-stimulating factor (G-CSF) and epoetin alfa (EPO) on hematologic parameters and fatigue in patients with breast cancer during chemotherapy.

PATIENTS AND METHODS

In the ADEBAR trial, 1493 patients with node-positive primary breast cancer were randomized to either 6 × 5-fluorouracil, epirubicin, and cyclophosphamide (FEC120) or 4 × epirubicin and cyclophosphamide followed by 4 × docetaxel (EC-DOC). Co-medication with G-CSF or EPO was applied to treat chemotherapy-induced leukopenia or anemia. Fatigue was assessed at baseline and after one-half of the chemotherapy.

RESULTS

In total, 899 patients could be included in the analysis. There was no evidence for an association between leucocyte or hemoglobin levels and application of G-CSF and EPO in the preceding cycle, respectively. Hemoglobin levels (B = -0.41; P < .001) were affected by treatment regimen. Fatigue during chemotherapy was mostly affected by the level of fatigue before the start of chemotherapy (B = 0.41; P < .001). Patients with G-CSF application in the preceding cycle showed an increased fatigue score (B = 5.43; P = .02).

CONCLUSION

We showed that fatigue during adjuvant chemotherapy was mostly affected by the level of fatigue present before the start of chemotherapy. This result suggests that the level of fatigue before the start of treatment should be included as an important factor when deciding on type and toxicity of chemotherapy in early breast cancer.

Protein Conformational Changes in Breast Cancer Sera Using Infrared Spectroscopic Analysis

Protein structural alterations, including misfolding and aggregation, are a hallmark of several diseases, including cancer. However, the possible clinical application of protein conformational analysis using infrared spectroscopy to detect cancer-associated structural changes in proteins has not been established yet. The present study investigates the applicability of Fourier transform infrared spectroscopy in distinguishing the sera of healthy individuals and breast cancer patients. The cancer-associated alterations in the protein structure were analyzed by fitting the amide I (1600-1700 cm-1) band of experimental curves, as well as by comparing the ratio of the absorbance values at the amide II and amide III bands, assigning those as the infrared spectral signatures. The snapshot of the breast cancer-associated alteration in circulating DNA and RNA was also evaluated by extending the spectral fitting protocol to the complex region of carbohydrates and nucleic acids, 1140-1000 cm-1. The sensitivity and specificity of these signatures, representing the ratio of the α-helix and β-pleated sheet in proteins, were both 90%. Likewise, the ratio of amides II and amide III (I1556/I1295) had a sensitivity and specificity of 100% and 80%, respectively. Thus, infrared spectroscopy can serve as a powerful tool to understand the protein structural alterations besides distinguishing breast cancer and healthy serum samples.

Induction of ZCCHC6 expression in peripheral blood mononuclear cells by HNSCC secretions

Cancer secretion can change the properties of adjacent cells, including peripheral blood mononuclear cells (PBMCs). We investigated whether such secretion influences messenger RNA expression in PBMCs of patients with head and neck squamous cell carcinoma (HNSCC). In the present study, co-culture model of normal PBMCs and HNSCC cell lines were established. The PBMCs were subsequently subjected to RNA sequencing for transcriptome analysis. Furthermore, expression data from the Gene Expression Omnibus repository, platform GPL4133, series GSE39400, were gathered to analyze, afterward identify zinc finger CysCysHisCys (CCHC)-type domain-containing protein 6 (ZCCHC6) as the main gene involved in HNSCC. This gene was then validated by a quantitative real-time polymerase chain reaction. The results showed that ZCCHC6 was expressed at significantly higher levels in the patients with HNSCC than in the healthy controls, and the sensitivity and specificity of these findings for diagnostic purposes were 100.00% and 70.83%, respectively. In summary, our findings demonstrated that the secretion of HNSCC cells could cause the alterations in messenger RNA expression by PBMCs. The ZCCHC6 expression level may apply in HNSCC screening.

Combined Evaluation of Preoperative Serum CEA and CA125 as an Independent Prognostic Biomarker in Patients with Early-Stage Cervical Adenocarcinoma

Purpose

There is currently a lack of research on preoperative prognostic analysis of early-stage cervical adenocarcinoma (ADC). The purpose of our study was to clarify whether preoperative serum tumor-marker levels were of prognostic value in early-stage ADC.

Patients and Methods

We performed a retrospective study of patients with International Federation of Gynecology and Obstetrics (FIGO) stage IA1–IIA1 and pathology-proven invasive ADC. We evaluated the relationship between preoperative serum tumor-marker levels and clinicopathological characteristics, and identified the relative preoperative risk factors affecting disease-free survival (DFS) and overall survival (OS). The optimal cut-off point of meaningful tumor markers was determined by the analysis of receiver operating characteristics (ROC), and the accuracy of the results was evaluated by the area under the curve (AUC).

Results

Elevated carcinoembryonic antigen (CEA), carbohydrate antigen 125 (CA125), squamous cell carcinoma antigen (SCC-Ag), alpha-fetoprotein (AFP), carbohydrate antigen 153 (CA153) and carbohydrate antigen 199 (CA199) were associated with certain clinicopathologic features of early-stage ADC. The combination of elevated serum CEA and CA125 was significantly associated with FIGO stage, body mass index (BMI) and LNM. Kaplan–Meier survival curve and Cox regression analyses revealed that CEA and CA125 might have significant prognostic implications in early-stage ADC patients, and the combination of elevated serum CEA and CA125 served as an independent predictor of early-stage ADC. The optimal cut-off point of serum CA125 for prediction DFS and OS was 32.60 U/mL and of serum CEA were 2.85 ng/mL and 2.05 ng/mL, respectively. The AUC showed that serum CEA was a moderate predictor of OS.

Conclusion

The preoperative serum levels of CEA and CA125 might have significant prognostic implications in early-stage ADC patients. Combined preoperative serum CEA and CA125 levels independently predicted the prognosis of early-stage ADC.