Detection Of Breast Cancer In Patients Research Articles

Serum Biomarkers for Chemotherapy Cardiotoxicity Risk Detection of Breast Cancer Patients.

Objective:This study aimed to investigate level fluctuations of serum biomarkers that are associated with cardiotoxicity risk, such as high-sensitivity C-reactive protein (hs-CRP) and apolipoprotein-B (Apo-B) in response to chemotherapy treatment for breast cancer. Method:The serum levels of hs-CRP and Apo-B were evaluated in 56 breast cancer patients with main inclusion criteria: HER2 negative and who received adjuvant chemotherapy AC [A: Adriamycin, C: Cyclophosphamide] or AC→T [A: Adriamycin, C: Cyclophosphamide, T: Taxane] regimes at early II (n = 26) and late IV (n = 30) clinical stages by using particle enhanced turbidimetric assay. Results:The results of this study suggest that a high level of pre-treatment hs-CRP is a good prognostic marker in comparison to Apo-B. Moreover, the AC-T chemotherapy regime treatment in both early and late stages exhibited a significantly higher level of hs-CRP compared to that in the AC regime. Hs-CRP was significantly elevated in the early stage in comparison to the late stage among cancer patients, meanwhile Apo-B behaved inversely. Furthermore, the results showed that hs-CRP levels were significantly higher in late-stage cancer patients compared with those in early-stage in both chemotherapy regimens groups. On the other hand, Apo-B showed no significant differences. Conclusion:Monitoring hs-CRP level changes in comparison to Apo-B can be used to assist the side effect risk difference among different chemotherapy regimens, and staging reflecting a positive correlation between them more notable in the late stage.

Circulating status of microRNAs 660-5p and 210-3p in breast cancer patients.

MicroRNAs (miRs), which are stable in the blood, comprise small non-coding RNAs that regulate gene expression. They have important roles in almost all biological pathways, especially in cancer-relevant processes, and have an abnormal expression in breast cancer. In recent studies, the aberrant expression level of various microRNAs has been demonstrated in human cancer. In the present study, the status of serum microRNA-210-3p and microRNA-660-5p expression levels in breast cancer patients was determined compared to healthy controls. Serum samples were collected from 40 newly diagnosed breast cancer patients and 40 healthy controls. A real-time quantitative polymerase chain reaction was utilized to detect the expression levels of these microRNAs. Data analysis was conducted with p < 0.05 being considered statistically significant. The data obtained showed that serum levels of miR-660-5p and miR-210-3p were significantly up-regulated in breast cancer patients compared to healthy controls (p < 0.001 and p = 0.001, respectively). In addition, significant up-regulation was observed in the early stage (in situ, stage I and II) of breast cancer patients (n = 25) compared to healthy (n = 40) controls (p < 0.001 and p < 0.05, respectively). Receiver-operating characteristic curve analysis indicated that the serum miR-660-5p and miR-210-3p levels have reasonable sensitivity (79% and 68%) and specificity (61% and 51%) for the detection of breast cancer patients (area under the receiver-operating curve = 0.774 and 0.716, respectively). Although the results show a reasonable diagnostic accuracy of these microRNAs for detection of breast cancer in this small and preliminary study, further large-scale studies are essential to confirm the presented results.

Accuracy for cytological evaluation in the detection of breast cancer among patients with pathologic nipple discharge: a PRISMA-compliant meta-analysis.

Background:Nipple discharge cytology is a simple non-invasive method that may provide valuable information for detecting underlying malignancy. Several studies have investigated the diagnostic value of cytology in breast cancer patients with pathological nipple discharge, but the results have been highly variable. Herein we presented a systematic review and meta-analysis of published studies pertaining to the diagnostic capacity of nipple discharge cytology in patients with breast cancer.Methods:A systematic literature search was performed (Medline/PubMed, Embase, Cochrane Library databases, and Google Scholar) to identify studies that investigated the diagnostic capacity of cytology with regard to breast cancer in patients with pathologic nipple discharge. Two independent researchers identified articles that assessed the sensitivity and specificity of cytological evaluation for breast cancer detection in patients with pathologic nipple discharge published between January 2000 and October 2018. Articles were only included in the meta-analysis if they met predetermined criteria. The characteristics of each study and the data they yielded were summarized. Quality assessment of all articles included was performed using the Methodological Index for Non-randomized Studies Criteria (MINORS) and the Quality Assessment of Diagnostic Accuracy Study 2 (QUADAS-2). Heterogeneity was tested via Cochran Q test and the I2 statistic using Stata 12.0 and Meta-DiSc 1.4 software, and meta-analysis was performed.Results:A total of 286 articles were identified, of which 12 articles including a total of 1476 patients were deemed eligible for inclusion in the meta-analysis. A random-effects model assessing the capacity of nipple discharge cytology to predict breast cancer yielded pooled sensitivity 63% (95% confidence interval [CI]: 53%–72%), specificity 95% (95% CI: 87%–98%), positive likelihood ratio 12.35 (95% CI: 4.87–31.34), and negative likelihood ratio 0.39 (95% CI: 0.30–0.50). The diagnostic odds ratio was 31.88 (95% CI: 11.30–89.98). The area under the summary receiver operating characteristic curve was 0.79 (95% CI: 0.75–0.82).Conclusion:The current meta-analysis suggests that nipple discharge cytology is a useful diagnostic modality for detection of breast cancer in patients with pathological nipple discharge, with moderate sensitivity and high specificity.

Expression of Mammaglobin and Carcinoembryonic Antigen in Peripheral Blood of Patients with Breast Cancer Using Real Time Polymerase Chain Reaction

Background and Objectives: Breast cancer is among the most common causes of cancer related mortality in women worldwide. Early detection and prompt diagnosis of tumor is the first step to prevent cancer-related morbidity and mortality, and a comprehensive understanding of the involved molecular mechanisms can greatly help in this respect. Breast cancer, like many other types of cancer, is caused by a combination of genetic and epigenetic changes such as inactivation of tumor suppressor genes. Materials and Methods: This study was performed on 40 breast cancer patients and 40 healthy controls. Quantitative real time reverse transcription polymerase chain reaction (real time qRT-PCR) was used to assess the expression of carcinoembryonic antigen (CEA) and mammaglobin mRNA in the peripheral blood of patients and healthy controls. The two groups were compared using t-test. Results: The two groups were not significantly different in terms of the mean age. Twenty-nine out of 40 cancer patients were positive for CEA mRNA and its sensitivity was calculated to be 72.5%. Twelve out of 40 healthy controls were positive for CEA mRNA. Twenty-six out of 40 patients were positive for mammaglobin mRNA indicative of 65% sensitivity while only five out of 40 healthy controls were positive for mammaglobin mRNA. Conclusion: Both CEA and mammaglobin mRNA had high sensitivity in cancer patients; thus, they can be used for screening and early detection of breast cancer patients. Further studies with larger sample sizes are required to confirm the current findings.

Breast Density Legislation: Discussion of Patient Utilization and Subsequent Direct Financial Ramifications for Insurance Providers

Now that New Jersey has become the 14th state in the United States to enact legislation regarding dense breast screening, its patients are eligible to receive screening breast sonography coverage from their insurance carriers. This law is intended to improve breast cancer detection in patients with dense breasts and create awareness of unique issues that come with dense breast tissue, while reinforcing already present efforts to reduce the incidence of and morbidity related to the diagnosis of breast cancer. The aim of this study was to examine data from months preceding the effective date of this legislation in a community hospital setting and compare these data with data from months immediately after, and 6 months after, its enactment to present patient participation data and estimate the legislation’s direct financial ramifications. Detractors of this type of legislation worry about overburdening the health care system with an influx of patients. Although there is a lack of present studies confirming this suspicion in other states with dense breast legislation, this study confirms a large increase in patient utilization after enactment, showing a minimum relative increase of 176.90% and a maximum relative increase of 335.56% in patient utilization of screening breast sonography. The investigators further include an estimation of an increased direct cost for insurers of $4,910,899.18 to $9,848,897.96 for a given month.

Breast Cancer Detection by B7-H3-Targeted Ultrasound Molecular Imaging.

Ultrasound complements mammography as an imaging modality for breast cancer detection, especially in patients with dense breast tissue, but its utility is limited by low diagnostic accuracy. One emerging molecular tool to address this limitation involves contrast-enhanced ultrasound using microbubbles targeted to molecular signatures on tumor neovasculature. In this study, we illustrate how tumor vascular expression of B7-H3 (CD276), a member of the B7 family of ligands for T-cell coregulatory receptors, can be incorporated into an ultrasound method that can distinguish normal, benign, precursor, and malignant breast pathologies for diagnostic purposes. Through an IHC analysis of 248 human breast specimens, we found that vascular expression of B7-H3 was selectively and significantly higher in breast cancer tissues. B7-H3 immunostaining on blood vessels distinguished benign/precursors from malignant lesions with high diagnostic accuracy in human specimens. In a transgenic mouse model of cancer, the B7-H3-targeted ultrasound imaging signal was increased significantly in breast cancer tissues and highly correlated with ex vivo expression levels of B7-H3 on quantitative immunofluorescence. Our findings offer a preclinical proof of concept for the use of B7-H3-targeted ultrasound molecular imaging as a tool to improve the diagnostic accuracy of breast cancer detection in patients.

Ionizing radiation-induced DNA injury and damage detection in patients with breast cancer.

Breast cancer is the most common malignancy in women. Radiotherapy is frequently used in patients with breast cancer, but some patients may be more susceptible to ionizing radiation, and increased exposure to radiation sources may be associated to radiation adverse events. This susceptibility may be related to deficiencies in DNA repair mechanisms that are activated after cell-radiation, which causes DNA damage, particularly DNA double strand breaks. Some of these genetic susceptibilities in DNA-repair mechanisms are implicated in the etiology of hereditary breast/ovarian cancer (pathologic mutations in the BRCA 1 and 2 genes), but other less penetrant variants in genes involved in sporadic breast cancer have been described. These same genetic susceptibilities may be involved in negative radiotherapeutic outcomes. For these reasons, it is necessary to implement methods for detecting patients who are susceptible to radiotherapy-related adverse events. This review discusses mechanisms of DNA damage and repair, genes related to these functions, and the diagnosis methods designed and under research for detection of breast cancer patients with increased radiosensitivity.

The relationship between skeletal-related events and bone scan index for the treatment of bone metastasis with breast cancer patients.

The aim of the present study was to investigate the relationships between the automated bone scan index (aBSI) and skeletal-related events (SRE) in breast cancer patients with bone metastasis. A computer-aided software (BONENAVI™) that was developed using an Artificial Neural Network (Artificial Neural Network) was used for the present analysis.Forty-five patients diagnosed with bone metastasis due to breast cancer from April 2005 through March 2013 were retrospectively analyzed. Before and after the time of initial treatment, aBSI, Artificial Neural Network score, and hotspot number were calculated, and the relationships between these scores and SRE were analyzed.Twenty cases showed decreased (improved) aBSI values after initial treatment (Group A), and 25 cases showed unchanged/increased (worsened) aBSI values (Group B). Chi-square analysis revealed a significant difference in incident numbers of SRE between the two groups—one case in Group A and 12 in Group B (P < 0.001). Event-free survival was significantly shorter in Group B (hazard ratio: 8.31, 95% CI: 1.33–12.14, log-rank test; P < 0.05). The groups were also divided by the results of 2 radiologists’ visual scan interpretations, and no significant differences were shown in the number of SRE (P = 0.82, P = 0.10). When correlation analyses were performed between aBSI and bone metabolic or tumor markers, alkaline phosphatase was significantly correlated with aBSI at the time of initial treatment (R = 0.69, P < 0.05).In conclusion, aBSI is proposed as a useful and objective imaging biomarker in the detection of breast-cancer patients with bone metastasis at high risk of SRE.

Molecular Markers in Peripheral Blood of Iranian Women with Breast Cancer

A biomarker is a quantifiable laboratory measure of a disease specific biologically relevant molecule that can act as an indicator of a current or future disease state. The purpose of this study is to detect the expression of RNA biomarkers using Cytokeratin 19 (CK-19), Mammaglobin (MAM), Carcinoembryonic antigen (CEA), Mucin (MUC), C-Myc, erb-B2, a proliferation marker (Ki-67), Epidermal growth factor receptor (Her2/neu) and Estrogen receptor (ER) in Iranian women who were diagnosed with breast cancer. In this study, 90 samples; 60 cancer patients and 30 healthy controls were considered. 73.4% patients were in stage I/II and 26.6% were in stage III/IV. Patients were selected prior to the administration of any adjuvant systemic therapy. Total RNA extraction was obtained from peripheral blood of each patient and healthy control. Reverse transcription polymerase chain reaction (RT-PCR) method was used for detection of mRNA of the selected biomarkers of circulating breast cancer cells in blood. Molecular characterization is assessed as a method for early detection of breast cancer. For this purpose, eleven specific primers were selected and RT-PCR was used. The data of RT-PCR revealed that expression of MUC1, CK19, CEA, MAM, erbB-2, Ki67 and C-Myc biomarkers were significantly different between breast cancer patients and healthy controls. On the other hand, ERα, ERβ and Her2 markers were not significantly different between the two mentioned groups. Biomarkers detection of breast cancer patients could be assessed as a diagnostic factor and its potential for conveying as a prognostic factor require further studies, with a larger number of patients.

Abstract 4633: A novel screening marker for breast cancer composed of plasma free amino acid concentrations “AminoIndex”

Abstract Introduction Amino acids balance is changed in patients of various diseases due to metabolic transition while it is maintained in healthy human. For example, it is known to change in liver dysfunction, renal failure, and cancers. Therefore, it is expected that the detection of metabolic transition using amino acid profiles is a promising screening marker of various cancers. We previously showed significant changes of plasma amino acid profiles and discriminating functions using plasma amino acid concentrations “AminoIndex” in various cancer patients including breast cancer. In this study, further possibilities of “AminoIndex” for breast cancer were investigated by case-control study from multiple medical facilities. Subjects and Methods Plasma samples were collected from Japanese breast cancer patients those were hospitalized in three hospitals and finally diagnosed before any medical treatment (N=295). Those of controls were also collected from subjects who were undergone comprehensive medical examination at two hospitals (N=2,147). Plasma amino acid concentrations were measured by LC-MS. Among them, 90 patients (30 from each hospital) in chronological order and 450 age-matched control subjects were chosen as training data set. And the rest (205 patients and 1,697 controls, respectively) were used as test data set to valid the inferred “AminoIndex”. Using training data set, plasma amino acid concentration were compared and then “AminoIndex”, multivariate logistic regression function composed of plasma amino acid concentrations, was inferred to discriminate breast cancer from control subjects. Results Plasma concentrations of several amino acids were significantly changed in breast cancer patients compared to control subjects. Predicted “AminoIndex” for breast cancer was resulted the multivariate logistic function composed with six amino acids. To evaluate the performance of the index predicted, the ROC curve for each predictive score was calculated, and this gave an AUC of ROC of 0.764 using the study data. Then, validation of predicted “AminoIndex” was performed using test data set, resulting almost same diagnostic performance. Furthermore, predicted “AminoIndex” showed notably features; the index could discriminate breast cancer patients almost equally in any stages, and the index showed not only higher discrimination performance than those of existing tumor markers but also distributed independently of the levels of various tumor markers. Therefore, predicted “AminoIndex” would be suitable for screening and early detection of breast cancer patients. Conclusion and Perspectives In this study, we demonstrated that change of plasma amino acid profile would be an indicator of breast cancer and a helpful tool for early detection of breast cancer patients. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 4633.

P8 Mutagen sensitivity and p53 in suprabasal layers of tumor-distant oral mucosa in patients with oral squamous cell carcinoma

the rest were used as test data set to valid the predicted “AminoIndex”. Results: Plasma concentrations of several amino acids were significantly changed in breast cancer patients compared to control subjects in study data set. Finally, “AminoIndex” for breast cancer composed with six amino acids (Gln, Ala, ABA, Trp, Orn, and Arg) was predicted. To evaluate the performance, the ROC curve was calculated, and this gave an AUC of ROC of 0.832 using the study data. Validation of predicted “AminoIndex” using test data set resulted same discriminating performance (AUC of ROC of 0.822), suggesting the robustness of the predicted classifier. Furthermore, predicted AminoIndex showed notably features. 1. The index could discriminate breast cancer patients in early stages. 2. The index showed higher discrimination performance than those of existing tumor markers especially in stages 0, I, and II patients. 3. The index could equally discriminate breast cancer patients of any histological types. Therefore, predicted “AminoIndex” would be suitable for screening and early detection of breast cancer patients. Conclusion and Perspectives: In this study, we demonstrated that change of plasma amino acid profile would be a helpful tool for early detection of breast cancer patients. “AminoIndex” would be useful to concentrate and inspire the candidates for further survey such as mammography. To evaluate the efficacy of this method, cohort studies are ongoing.

Optimizing of MALDI-ToF-based low-molecular-weight serum proteome pattern analysis in detection of breast cancer patients; the effect of albumin removal on classification performance.

Mass spectrometry-based analysis of the serum proteome allows identifying multi-peptide patterns/signatures specific for blood of cancer patients, thus having high potential value for cancer diagnostics. However, because of problems with optimization and standardization of experimental and computational design, none of identified proteome patterns/signatures was approved for diagnostics in clinical practice as yet. Here we compared two methods of serum sample preparation for mass spectrometry-based proteome pattern analysis aimed to identify biomarkers that could be used in early detection of breast cancer patients. Blood samples were collected in a group of 92 patients diagnosed at early (I and II) stages of the disease before the start of therapy, and in a group of age-matched healthy controls (104 women). Serum specimens were purified and analyzed using MALDI-ToF spectrometry, either directly or after membrane filtration (50 kDa cut-off) to remove albumin and other large serum proteins. Mass spectra of the low-molecular-weight fraction (2-10 kDa) of the serum proteome were resolved using the Gaussian mixture decomposition, and identified spectral components were used to build classifiers that differentiated samples from breast cancer patients and healthy persons. Mass spectra of complete serum and membrane-filtered albumin-depleted samples have apparently different structure and peaks specific for both types of samples could be identified. The optimal classifier built for the complete serum specimens consisted of 8 spectral components, and had 81% specificity and 72% sensitivity, while that built for the membrane-filtered samples consisted of 4 components, and had 80% specificity and 81% sensitivity. We concluded that pre-processing of samples to remove albumin might be recommended before MALDI-ToF mass spectrometric analysis of the low-molecular-weight components of human serum Keywords: albumin removal; breast cancer; clinical proteomics; mass spectrometry; pattern analysis; serum proteome.

The Case For Treating Partial Breast Over Five Days

Over the past couple decades, the integration of screening mammography has resulted in earlier detection of breast cancer patients. For favorable early stage patients, studies have shown that breast conserving therapy with lumpectomy followed by whole breast radiation is equivalent to mastectomy. Due to the logistical challenges of an extended six-week whole breast radiation course, the concept of treating only the portion of the breast at greatest risk of recurrence following lumpectomy has been increasingly investigated. This notion is nested in the fact that the vast majority of recurrences following surgery occur in the peri-lumpectomy region (not in other regions of the breast) and thus a more limited volume may suffice in appropriately selected patients. The reduction of normal tissues that receive high-dose radiation allows an increased daily dose to be safely delivered, thereby allowing shortening the overall treatment time to one week. This treatment algorithm has been coined accelerated partial breast irradiation or APBI and is the context of this review article.

Accuracy of MR imaging in the work-up of suspicious breast lesions: A diagnostic meta-analysis

The authors performed a systematic, critical review of the literature on magnetic resonance (MR) imaging for primary breast cancer detection in patients with suspicious breast lesions, analyzed MR test performance in the articles meeting study criteria, and used this information to examine the cost-effectiveness of preoperative MR imaging. A structured, predefined MEDLINE search was conducted to identify potentially relevant, peer-reviewed, English-language references from January 1996 through August 1997 on the diagnostic accuracy of breast MR imaging. This information was supplemented by manually searching bibliographies of the retrieved articles for additional potentially relevant references. All studies were independently abstracted by two reviewers using a prospectively designed worksheet. Abstraction results were analyzed with the summary receiver operating characteristic (ROC) method. Of 41 identified studies, 16 met the inclusion criteria. These studies reported sensitivities ranging from 63% to 100% and specificities ranging from 21% to 100%. Maximum joint sensitivity and specificity of the summary ROC curve was 89% (95% confidence interval [CI]: 82%, 93%). At a sensitivity of 95%, specificity was 67%. When test performance values were applied to a previous cost-effectiveness analysis, the cost-effectiveness of preoperative MR imaging relative to that of excisional biopsy was confirmed, but its cost-effectiveness relative to that of needle core biopsy varied widely. For MR imaging to be a cost-effective alternative to excisional biopsy for diagnosis of suspicious breast lesions, its diagnostic test performance must be equal to or better than the best results in recently published studies.