Search results for: breast cancer detection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5466

Search results for: breast cancer detection

5076 Physicochemical Properties, Antioxidant and Cytotoxic Activities of Extracts and Fractions from Phyllanthus amarus

Authors: Van Tang Nguyen, Jennette A. Sakoff, Christopher J. Scarlett

Abstract:

Phyllanthus amarus (P. amarus) has been used as a traditional herbal plant for the treatment of chronic ailments such as hepatitis, diabetes and cancer. The objectives of this study were to determine the physicochemical properties, antioxidant and cytotoxic activities of crude P. amarus extracts and fractions using MTT and CCK-8 assays for cytotoxic evaluation. The outcomes indicated that P. amarus methanol (PAM) extract had lower residual moisture (7.40%) and water activity (0.24) and higher contents of saponins, phenolics, flavonoids and proanthocyanidins (1657.86 mg escin equivalents, 250.45 mg gallic acid equivalents, 274.73 mg rutin equivalents and 61.22 mg catechin equivalents/g dried extract, respectively) than those of P. amarus water (PAW) extract, resulting antioxidant activity of PAM extract was significantly higher (P < 0.05) than that of PAW extract, PAM fractions and phyllanthin (a major compound in P. amarus). Cytotoxic activity of PAM extract for cancer cell lines of MiaPaCa-2 (pancreas), HT29 (colon), A2780 (ovarian), H460 (lung), A431 (skin), Du145 (prostate), BE2-C (neuroblastoma), MCF-7 (breast), MCF-10A (normal breast), and U87, SJ-G2, SMA (glioblastoma) was higher than those of PAW extract and PAM fractions. Therefore, we can conclude that the PA extracts are a potential source for the development of natural antioxidant products and/or novel anticancer drugs.

Keywords: antioxidant, cytotoxicity, Phyllanthus amarus, physicochemical

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5075 Electrochemical Biosensor Based on Chitosan-Gold Nanoparticles, Carbon Nanotubes for Detection of Ovarian Cancer Biomarker

Authors: Parvin Samadi Pakchin, Reza Saber, Hossein Ghanbari, Yadollah Omidi

Abstract:

Ovarian cancer is one of the leading cause of mortality among the gynecological malignancies, and it remains the one of the most prevalent cancer in females worldwide. Tumor markers are biochemical molecules in blood or tissues which can indicates cancers occurrence in the human body. So, the sensitive and specific detection of cancer markers typically recruited for diagnosing and evaluating cancers. Recently extensive research efforts are underway to achieve a simple, inexpensive and accurate device for detection of cancer biomarkers. Compared with conventional immunoassay techniques, electrochemical immunosensors are of great interest, because they are specific, simple, inexpensive, easy to handling and miniaturization. Moreover, in the past decade nanotechnology has played a crucial role in the development of biosensors. In this study, a signal-off electrochemical immunosensor for the detection of CA125 antigen has been developed using chitosan-gold nanoparticles (CS-AuNP) and multi-wall carbon nanotubes (MWCNT) composites. Toluidine blue (TB) is used as redox probe which is immobilized on the electrode surface. CS-AuNP is synthesized by a simple one step method that HAuCl4 is reduced by NH2 groups of chitosan. The CS-AuNP-MWCNT modified electrode has shown excellent electrochemical performance compared with bare Au electrode. MWCNTs and AuNPs increased electrochemical conductivity and accelerate electrons transfer between solution and electrode surface while excessive amine groups on chitosan lead to the effective loading of the biological material (CA125 antibody) and TB on the electrode surface. The electrochemical, immobilization and sensing properties CS-AuNP-MWCNT-TB modified electrodes are characterized by cyclic voltammetry, electrochemical impedance spectroscopy, differential pulse voltammetry and square wave voltammetry with Fe(CN)63−/4−as an electrochemical redox indicator.

Keywords: signal-off electrochemical biosensor, CA125, ovarian cancer, chitosan-gold nanoparticles

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5074 Optimizing Exposure Parameters in Digital Mammography: A Study in Morocco

Authors: Talbi Mohammed, Oustous Aziz, Ben Messaoud Mounir, Sebihi Rajaa, Khalis Mohammed

Abstract:

Background: Breast cancer is the leading cause of death for women around the world. Screening mammography is the reference examination, due to its sensitivity for detecting small lesions and micro-calcifications. Therefore, it is essential to ensure quality mammographic examinations with the most optimal dose. These conditions depend on the choice of exposure parameters. Clinically, practices must be evaluated in order to determine the most appropriate exposure parameters. Material and Methods: We performed our measurements on a mobile mammography unit (PLANMED Sofie-classic.) in Morocco. A solid dosimeter (AGMS Radcal) and a MTM 100 phantom allow to quantify the delivered dose and the image quality. For image quality assessment, scores are defined by the rate of visible inserts (MTM 100 phantom), obtained and compared for each acquisition. Results: The results show that the parameters of the mammography unit on which we have made our measurements can be improved in order to offer a better compromise between image quality and breast dose. The last one can be reduced up from 13.27% to 22.16%, while preserving comparable image quality.

Keywords: Mammography, Breast Dose, Image Quality, Phantom

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5073 Ultra-Sensitive Point-Of-Care Detection of PSA Using an Enzyme- and Equipment-Free Microfluidic Platform

Authors: Ying Li, Rui Hu, Shizhen Chen, Xin Zhou, Yunhuang Yang

Abstract:

Prostate cancer is one of the leading causes of cancer-related death among men. Prostate-specific antigen (PSA), a specific product of prostatic epithelial cells, is an important indicator of prostate cancer. Though PSA is not a specific serum biomarker for the screening of prostate cancer, it is recognized as an indicator for prostate cancer recurrence and response to therapy for patient’s post-prostatectomy. Since radical prostatectomy eliminates the source of PSA production, serum PSA levels fall below 50 pg/mL, and may be below the detection limit of clinical immunoassays (current clinical immunoassay lower limit of detection is around 10 pg/mL). Many clinical studies have shown that intervention at low PSA levels was able to improve patient outcomes significantly. Therefore, ultra-sensitive and precise assays that can accurately quantify extremely low levels of PSA (below 1-10 pg/mL) will facilitate the assessment of patients for the possibility of early adjuvant or salvage treatment. Currently, the commercially available ultra-sensitive ELISA kit (not used clinically) can only reach a detection limit of 3-10 pg/mL. Other platforms developed by different research groups could achieve a detection limit as low as 0.33 pg/mL, but they relied on sophisticated instruments to get the final readout. Herein we report a microfluidic platform for point-of-care (POC) detection of PSA with a detection limit of 0.5 pg/mL and without the assistance of any equipment. This platform is based on a previously reported volumetric-bar-chart chip (V-Chip), which applies platinum nanoparticles (PtNPs) as the ELISA probe to convert the biomarker concentration to the volume of oxygen gas that further pushes the red ink to form a visualized bar-chart. The length of each bar is used to quantify the biomarker concentration of each sample. We devised a long reading channel V-Chip (LV-Chip) in this work to achieve a wide detection window. In addition, LV-Chip employed a unique enzyme-free ELISA probe that enriched PtNPs significantly and owned 500-fold enhanced catalytic ability over that of previous V-Chip, resulting in a significantly improved detection limit. LV-Chip is able to complete a PSA assay for five samples in 20 min. The device was applied to detect PSA in 50 patient serum samples, and the on-chip results demonstrated good correlation with conventional immunoassay. In addition, the PSA levels in finger-prick whole blood samples from healthy volunteers were successfully measured on the device. This completely stand-alone LV-Chip platform enables convenient POC testing for patient follow-up in the physician’s office and is also useful in resource-constrained settings.

Keywords: point-of-care detection, microfluidics, PSA, ultra-sensitive

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5072 Differentially Expressed Protein Biomarkers in Early and Advanced Stage Young Triple-Negative Breast Cancer Patients

Authors: Shamim Mushtaq, Moazzam Shahid

Abstract:

Breast cancer (BC) claims the lives of half a million women every year and is the most common cause of death in the developing world. In 2019, it was estimated that BC alone accounts for 15% of all cancer deaths in younger women (aged < 45 years old) with advanced-stage lung metastasis. According to the World Health Organization & International Union against Cancer, in Asia, a high number of cancer-related deaths will be observed in 2020, whereas the burden will be reduced in Western countries due to awareness about the disease, better health facilities and advanced treatments. In the last 15 years, it has been reported that the incidence of BC has increased by 1.1% among Asian compared to the US population from 2003 to 2012. To date, several BC biological subtypes have been reported so far, which are associated with different treatment responses. The heterogeneity and diversity of BC reflected these different subtypes, including Luminal A (23.7% prevalence) and B (38.8% prevalence) that have pathological estrogen receptor (ER+)-positive tumors, the human epidermal growth factor receptor 2 (HER2) (11.2% prevalence) and triple-negative breast cancer (TNBC) (25% prevalence). According to Shaukat Khanum Memorial Cancer Hospital and Research Centre – Pakistan, ten years of data showed that among 636 BC patients, 30.5% had TNBC who were <40 years of age, which is an extremely alarming situation. Therefore, there is a dire need to explore and develop therapeutic targets for the treatment of early TNBC. Since the last decade, unfortunately, there has been little success in understanding the complexity of TNBC and in discovering new biological therapeutic targets. However, conventional chemotherapy is the only choice of treatment for TNBC patients. Many investigators revealed advances in multi-omics (multiple "omes", e.g., genome, proteome, transcriptome, epigenome, and microbiome) which were later identified as actionable targets and increased prevalence in TNBC patients. However, various drugs have been identified so far which are related to a particular diagnostic and prognostic biomarker. For example, Epidermal growth factor receptor ( EGFR or ErbB-1), HER-2/neu (ErbB-2), HER-3 (ErbB-3), and HER-4 (ErbB-4). Protein Transglin-2 (TAGLN 2 ) and Profilins-1 (Pfn-1 ) are the ubiquitously expressed large family of proteins present in all eukaryotes, enabling actin cytoskeletal reorganization. It is known that the oncogenic transformation of cells is accompanied by alteration in the actin cytoskeleton. There are causal connections between altered expression of actin cytoskeletal regulators and cancer progression. Our case-control study identified TAGLN-2 and Pfn-1 proteins in TNBC blood by mass spectrometry. Both TAGLN-2 and Pfn-1 proteins are differentially expressed in early and advanced stages of TNBS patients, which could be potential predictors or therapeutic targets for TNBC.

Keywords: TNBC, blood biomarkers, mass spectrometry, qPCR, ELISA

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5071 Exhaled Breath Condensate in Lung Cancer: A Non-Invasive Sample for Easier Mutations Detection by Next Generation Sequencing

Authors: Omar Youssef, Aija Knuuttila, Paivi Piirilä, Virinder Sarhadi, Sakari Knuutila

Abstract:

Exhaled breath condensate (EBC) is a unique sample that allows studying different genetic changes in lung carcinoma through a non-invasive way. With the aid of next generation sequencing (NGS) technology, analysis of genetic mutations has been more efficient with increased sensitivity for detection of genetic variants. In order to investigate the possibility of applying this method for cancer diagnostics, mutations in EBC DNA from lung cancer patients and healthy individuals were studied by using NGS. The key aim is to assess the feasibility of using this approach to detect clinically important mutations in EBC. EBC was collected from 20 healthy individuals and 9 lung cancer patients (four lung adenocarcinomas, four 8 squamous cell carcinoma, and one case of mesothelioma). Mutations in hotpot regions of 22 genes were studied by using Ampliseq Colon and Lung cancer panel and sequenced on Ion PGM. Results demonstrated that all nine patients showed a total of 19 cosmic mutations in APC, BRAF, EGFR, ERBB4, FBXW7, FGFR1, KRAS, MAP2K1, NRAS, PIK3CA, PTEN, RET, SMAD4, and TP53. In controls, 15 individuals showed 35 cosmic mutations in BRAF, CTNNB1, DDR2, EGFR, ERBB2, FBXW7, FGFR3, KRAS, MET, NOTCH1, NRAS, PIK3CA, PTEN, SMAD4, and TP53. Additionally, 45 novel mutations not reported previously were also seen in patients’ samples, and 106 novel mutations were seen in controls’ specimens. KRAS exon 2 mutations G12D was identified in one control specimen with mutant allele fraction of 6.8%, while KRAS G13D mutation seen in one patient sample showed mutant allele fraction of 17%. These findings illustrate that hotspot mutations are present in DNA from EBC of both cancer patients and healthy controls. As some of the cosmic mutations were seen in controls too, no firm conclusion can be drawn on the clinical importance of cosmic mutations in patients. Mutations reported in controls could represent early neoplastic changes or normal homeostatic process of apoptosis occurring in lung tissue to get rid of mutant cells. At the same time, mutations detected in patients might represent a non-invasive easily accessible way for early cancer detection. Follow up of individuals with important cancer mutations is necessary to clarify the significance of these mutations in both healthy individuals and cancer patients.

Keywords: exhaled breath condensate, lung cancer, mutations, next generation sequencing

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5070 A Sui Generis Technique to Detect Pathogens in Post-Partum Breast Milk Using Image Processing Techniques

Authors: Yogesh Karunakar, Praveen Kandaswamy

Abstract:

Mother’s milk provides the most superior source of nutrition to a child. There is no other substitute to the mother’s milk. Postpartum secretions like breast milk can be analyzed on the go for testing the presence of any harmful pathogen before a mother can feed the child or donate the milk for the milk bank. Since breast feeding is one of the main causes for transmission of diseases to the newborn, it is mandatory to test the secretions. In this paper, we describe the detection of pathogens like E-coli, Human Immunodeficiency Virus (HIV), Hepatitis B (HBV), Hepatitis C (HCV), Cytomegalovirus (CMV), Zika and Ebola virus through an innovative method, in which we are developing a unique chip for testing the mother’s milk sample. The chip will contain an antibody specific to the target pathogen that will show a color change if there are enough pathogens present in the fluid that will be considered dangerous. A smart-phone camera will then be acquiring the image of the strip and using various image processing techniques we will detect the color development due to antigen antibody interaction within 5 minutes, thereby not adding to any delay, before the newborn is fed or prior to the collection of the milk for the milk bank. If the target pathogen comes positive through this method, then the health care provider can provide adequate treatment to bring down the number of pathogens. This will reduce the postpartum related mortality and morbidity which arises due to feeding infectious breast milk to own child.

Keywords: postpartum, fluids, camera, HIV, HCV, CMV, Zika, Ebola, smart-phones, breast milk, pathogens, image processing techniques

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5069 Automatic Threshold Search for Heat Map Based Feature Selection: A Cancer Dataset Analysis

Authors: Carlos Huertas, Reyes Juarez-Ramirez

Abstract:

Public health is one of the most critical issues today; therefore, there is great interest to improve technologies in the area of diseases detection. With machine learning and feature selection, it has been possible to aid the diagnosis of several diseases such as cancer. In this work, we present an extension to the Heat Map Based Feature Selection algorithm, this modification allows automatic threshold parameter selection that helps to improve the generalization performance of high dimensional data such as mass spectrometry. We have performed a comparison analysis using multiple cancer datasets and compare against the well known Recursive Feature Elimination algorithm and our original proposal, the results show improved classification performance that is very competitive against current techniques.

Keywords: biomarker discovery, cancer, feature selection, mass spectrometry

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5068 The Power of the Proper Orthogonal Decomposition Method

Authors: Charles Lee

Abstract:

The Principal Orthogonal Decomposition (POD) technique has been used as a model reduction tool for many applications in engineering and science. In principle, one begins with an ensemble of data, called snapshots, collected from an experiment or laboratory results. The beauty of the POD technique is that when applied, the entire data set can be represented by the smallest number of orthogonal basis elements. It is the such capability that allows us to reduce the complexity and dimensions of many physical applications. Mathematical formulations and numerical schemes for the POD method will be discussed along with applications in NASA’s Deep Space Large Antenna Arrays, Satellite Image Reconstruction, Cancer Detection with DNA Microarray Data, Maximizing Stock Return, and Medical Imaging.

Keywords: reduced-order methods, principal component analysis, cancer detection, image reconstruction, stock portfolios

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5067 Construction of Ovarian Cancer-on-Chip Model by 3D Bioprinting and Microfluidic Techniques

Authors: Zakaria Baka, Halima Alem

Abstract:

Cancer is a major worldwide health problem that has caused around ten million deaths in 2020. In addition, efforts to develop new anti-cancer drugs still face a high failure rate. This is partly due to the lack of preclinical models that recapitulate in-vivo drug responses. Indeed conventional cell culture approach (known as 2D cell culture) is far from reproducing the complex, dynamic and three-dimensional environment of tumors. To set up more in-vivo-like cancer models, 3D bioprinting seems to be a promising technology due to its ability to achieve 3D scaffolds containing different cell types with controlled distribution and precise architecture. Moreover, the introduction of microfluidic technology makes it possible to simulate in-vivo dynamic conditions through the so-called “cancer-on-chip” platforms. Whereas several cancer types have been modeled through the cancer-on-chip approach, such as lung cancer and breast cancer, only a few works describing ovarian cancer models have been described. The aim of this work is to combine 3D bioprinting and microfluidic technics with setting up a 3D dynamic model of ovarian cancer. In the first phase, alginate-gelatin hydrogel containing SKOV3 cells was used to achieve tumor-like structures through an extrusion-based bioprinter. The desired form of the tumor-like mass was first designed on 3D CAD software. The hydrogel composition was then optimized for ensuring good and reproducible printability. Cell viability in the bioprinted structures was assessed using Live/Dead assay and WST1 assay. In the second phase, these bioprinted structures will be included in a microfluidic device that allows simultaneous testing of different drug concentrations. This microfluidic dispositive was first designed through computational fluid dynamics (CFD) simulations for fixing its precise dimensions. It was then be manufactured through a molding method based on a 3D printed template. To confirm the results of CFD simulations, doxorubicin (DOX) solutions were perfused through the dispositive and DOX concentration in each culture chamber was determined. Once completely characterized, this model will be used to assess the efficacy of anti-cancer nanoparticles developed in the Jean Lamour institute.

Keywords: 3D bioprinting, ovarian cancer, cancer-on-chip models, microfluidic techniques

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5066 Compartmental Model Approach for Dosimetric Calculations of ¹⁷⁷Lu-DOTATOC in Adenocarcinoma Breast Cancer Based on Animal Data

Authors: M. S. Mousavi-Daramoroudi, H. Yousefnia, S. Zolghadri, F. Abbasi-Davani

Abstract:

Dosimetry is an indispensable and precious factor in patient treatment planning; to minimize the absorbed dose in vital tissues. In this study, In accordance with the proper characteristics of DOTATOC and ¹⁷⁷Lu, after preparing ¹⁷⁷Lu-DOTATOC at the optimal conditions for the first time in Iran, radionuclidic and radiochemical purity of the solution was investigated using an HPGe spectrometer and ITLC method, respectively. The biodistribution of the compound was assayed for treatment of adenocarcinoma breast cancer in bearing BALB/c mice. The results have demonstrated that ¹⁷⁷Lu-DOTATOC is a profitable selection for therapy of the tumors. Because of the vital role of internal dosimetry before and during therapy, the effort to improve the accuracy and rapidity of dosimetric calculations is necessary. For this reason, a new method was accomplished to calculate the absorbed dose through mixing between compartmental model, animal dosimetry and extrapolated data from animal to human and using MIRD method. Despite utilization of compartmental model based on the experimental data, it seems this approach may increase the accuracy of dosimetric data, confidently.

Keywords: ¹⁷⁷Lu-DOTATOC, biodistribution modeling, compartmental model, internal dosimetry

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5065 Automatic Identification of Pectoral Muscle

Authors: Ana L. M. Pavan, Guilherme Giacomini, Allan F. F. Alves, Marcela De Oliveira, Fernando A. B. Neto, Maria E. D. Rosa, Andre P. Trindade, Diana R. De Pina

Abstract:

Mammography is a worldwide image modality used to diagnose breast cancer, even in asymptomatic women. Due to its large availability, mammograms can be used to measure breast density and to predict cancer development. Women with increased mammographic density have a four- to sixfold increase in their risk of developing breast cancer. Therefore, studies have been made to accurately quantify mammographic breast density. In clinical routine, radiologists perform image evaluations through BIRADS (Breast Imaging Reporting and Data System) assessment. However, this method has inter and intraindividual variability. An automatic objective method to measure breast density could relieve radiologist’s workload by providing a first aid opinion. However, pectoral muscle is a high density tissue, with similar characteristics of fibroglandular tissues. It is consequently hard to automatically quantify mammographic breast density. Therefore, a pre-processing is needed to segment the pectoral muscle which may erroneously be quantified as fibroglandular tissue. The aim of this work was to develop an automatic algorithm to segment and extract pectoral muscle in digital mammograms. The database consisted of thirty medio-lateral oblique incidence digital mammography from São Paulo Medical School. This study was developed with ethical approval from the authors’ institutions and national review panels under protocol number 3720-2010. An algorithm was developed, in Matlab® platform, for the pre-processing of images. The algorithm uses image processing tools to automatically segment and extract the pectoral muscle of mammograms. Firstly, it was applied thresholding technique to remove non-biological information from image. Then, the Hough transform is applied, to find the limit of the pectoral muscle, followed by active contour method. Seed of active contour is applied in the limit of pectoral muscle found by Hough transform. An experienced radiologist also manually performed the pectoral muscle segmentation. Both methods, manual and automatic, were compared using the Jaccard index and Bland-Altman statistics. The comparison between manual and the developed automatic method presented a Jaccard similarity coefficient greater than 90% for all analyzed images, showing the efficiency and accuracy of segmentation of the proposed method. The Bland-Altman statistics compared both methods in relation to area (mm²) of segmented pectoral muscle. The statistic showed data within the 95% confidence interval, enhancing the accuracy of segmentation compared to the manual method. Thus, the method proved to be accurate and robust, segmenting rapidly and freely from intra and inter-observer variability. It is concluded that the proposed method may be used reliably to segment pectoral muscle in digital mammography in clinical routine. The segmentation of the pectoral muscle is very important for further quantifications of fibroglandular tissue volume present in the breast.

Keywords: active contour, fibroglandular tissue, hough transform, pectoral muscle

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5064 Correlation Between Different Radiological Findings and Histopathological diagnosis of Breast Diseases: Retrospective Review Conducted Over Sixth Years in King Fahad University Hospital in Eastern Province, Saudi Arabia

Authors: Sadeem Aljamaan, Reem Hariri, Rahaf Alghamdi, Batool Alotaibi, Batool Alsenan, Lama Althunayyan, Areej Alnemer

Abstract:

The aim of this study is to correlate between radiological findings and histopathological results in regard to the breast imaging-reporting and data system scores, size of breast masses, molecular subtypes and suspicious radiological features, as well as to assess the concordance rate in histological grade between core biopsy and surgical excision among breast cancer patients, followed by analyzing the change of concordance rate in relation to neoadjuvant chemotherapy in a Saudi population. A retrospective review was conducted over 6-year period (2017-2022) on all breast core biopsies of women preceded by radiological investigation. Chi-squared test (χ2) was performed on qualitative data, the Mann-Whitney test for quantitative non-parametric variables, and the Kappa test for grade agreement. A total of 641 cases were included. Ultrasound, mammography, and magnetic resonance imaging demonstrated diagnostic accuracies of 85%, 77.9% and 86.9%; respectively. magnetic resonance imaging manifested the highest sensitivity (72.2%), and the lowest was for ultrasound (61%). Concordance in tumor size with final excisions was best in magnetic resonance imaging, while mammography demonstrated a higher tendency of overestimation (41.9%), and ultrasound showed the highest underestimation (67.7%). The association between basal-like molecular subtypes and the breast imaging-reporting and data system score 5 classifications was statistically significant only for magnetic resonance imaging (p=0.04). Luminal subtypes demonstrated a significantly higher percentage of speculation in mammography. Breast imaging-reporting and data system score 4 manifested a substantial number of benign pathologies in all the 3 modalities. A fair concordance rate (k= 0.212 & 0.379) was demonstrated between excision and the preceding core biopsy grading with and without neoadjuvant therapy, respectively. The results demonstrated a down-grading in cases post-neoadjuvant therapy. In cases who did not receive neoadjuvant therapy, underestimation of tumor grade in biopsy was evident. In summary, magnetic resonance imaging had the highest sensitivity, specificity, positive predictive value and accuracy of both diagnosis and estimation of tumor size. Mammography demonstrated better sensitivity than ultrasound and had the highest negative predictive value, but ultrasound had better specificity, positive predictive value and accuracy. Therefore, the combination of different modalities is advantageous. The concordance rate of core biopsy grading with excision was not impacted by neoadjuvant therapy.

Keywords: breast cancer, mammography, MRI, neoadjuvant, pathology, US

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5063 Comparison of 18F-FDG and 11C-Methionine PET-CT for Assessment of Response to Neoadjuvant Chemotherapy in Locally Advanced Breast Carcinoma

Authors: Sonia Mahajan Dinesh, Anant Dinesh, Madhavi Tripathi, Vinod Kumar Ramteke, Rajnish Sharma, Anupam Mondal

Abstract:

Background: Neo-adjuvant chemotherapy plays an important role in treatment of breast cancer by decreasing the tumour load and it offers an opportunity to evaluate response of primary tumour to chemotherapy. Standard anatomical imaging modalities are unable to accurately reflect the response to chemotherapy until several cycles of drug treatment have been completed. Metabolic imaging using tracers like 18F-fluorodeoxyglucose (FDG) as a marker of glucose metabolism or amino acid tracers like L-methyl-11C methionine (MET) have potential role for the measurement of treatment response. In this study, our objective was to compare these two PET tracers for assessment of response to neoadjuvant chemotherapy, in locally advanced breast carcinoma. Methods: In our prospective study, 20 female patients with histology proven locally advanced breast carcinoma underwent PET-CT imaging using FDG and MET before and after three cycles of neoadjuvant chemotherapy (CAF regimen). Thereafter, all patients were taken for MRM and the resected specimen was sent for histo-pathological analysis. Tumour response to the neoadjuvant chemotherapy was evaluated by PET-CT imaging using PERCIST criteria and correlated with histological results. Responses calculated were compared for statistical significance using paired t- test. Results: Mean SUVmax for primary lesion in FDG PET and MET PET was 15.88±11.12 and 5.01±2.14 respectively (p<0.001) and for axillary lymph nodes was 7.61±7.31 and 2.75±2.27 respectively (p=0.001). Statistically significant response in primary tumour and axilla was noted on both FDG and MET PET after three cycles of NAC. Complete response in primary tumour was seen in only 1 patient in FDG and 7 patients in MET PET (p=0.001) whereas there was no histological complete resolution of tumor in any patient. Response to therapy in axillary nodes noted on both PET scans were similar (p=0.45) and correlated well with histological findings. Conclusions: For the primary breast tumour, FDG PET has a higher sensitivity and accuracy than MET PET and for axilla both have comparable sensitivity and specificity. FDG PET shows higher target to background ratios so response is better predicted for primary breast tumour and axilla. Also, FDG-PET is widely available and has the advantage of a whole body evaluation in one study.

Keywords: 11C-methionine, 18F-FDG, breast carcinoma, neoadjuvant chemotherapy

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5062 Identification of Clinical Characteristics from Persistent Homology Applied to Tumor Imaging

Authors: Eashwar V. Somasundaram, Raoul R. Wadhwa, Jacob G. Scott

Abstract:

The use of radiomics in measuring geometric properties of tumor images such as size, surface area, and volume has been invaluable in assessing cancer diagnosis, treatment, and prognosis. In addition to analyzing geometric properties, radiomics would benefit from measuring topological properties using persistent homology. Intuitively, features uncovered by persistent homology may correlate to tumor structural features. One example is necrotic cavities (corresponding to 2D topological features), which are markers of very aggressive tumors. We develop a data pipeline in R that clusters tumors images based on persistent homology is used to identify meaningful clinical distinctions between tumors and possibly new relationships not captured by established clinical categorizations. A preliminary analysis was performed on 16 Magnetic Resonance Imaging (MRI) breast tissue segments downloaded from the 'Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging and Molecular Analysis' (I-SPY TRIAL or ISPY1) collection in The Cancer Imaging Archive. Each segment represents a patient’s breast tumor prior to treatment. The ISPY1 dataset also provided the estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status data. A persistent homology matrix up to 2-dimensional features was calculated for each of the MRI segmentation. Wasserstein distances were then calculated between all pairwise tumor image persistent homology matrices to create a distance matrix for each feature dimension. Since Wasserstein distances were calculated for 0, 1, and 2-dimensional features, three hierarchal clusters were constructed. The adjusted Rand Index was used to see how well the clusters corresponded to the ER/PR/HER2 status of the tumors. Triple-negative cancers (negative status for all three receptors) significantly clustered together in the 2-dimensional features dendrogram (Adjusted Rand Index of .35, p = .031). It is known that having a triple-negative breast tumor is associated with aggressive tumor growth and poor prognosis when compared to non-triple negative breast tumors. The aggressive tumor growth associated with triple-negative tumors may have a unique structure in an MRI segmentation, which persistent homology is able to identify. This preliminary analysis shows promising results in the use of persistent homology on tumor imaging to assess the severity of breast tumors. The next step is to apply this pipeline to other tumor segment images from The Cancer Imaging Archive at different sites such as the lung, kidney, and brain. In addition, whether other clinical parameters, such as overall survival, tumor stage, and tumor genotype data are captured well in persistent homology clusters will be assessed. If analyzing tumor MRI segments using persistent homology consistently identifies clinical relationships, this could enable clinicians to use persistent homology data as a noninvasive way to inform clinical decision making in oncology.

Keywords: cancer biology, oncology, persistent homology, radiomics, topological data analysis, tumor imaging

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5061 Production of Single-Chain Antibodies against Common Epitopes of ErbB1 and ErbB2 Using Phage Display Antibody Library

Authors: Gholamreza Hashemitabr, Reza Valadan, Alireza Rafiei, Mohammad Reza Bassami

Abstract:

Breast cancer is the most common malignancy among women worldwide. Cancer cells use a complex multilayer network of epidermal growth factor receptors (EGFRs) signaling pathways to support their survival and growth. The overlapping networks of EGFRs signaling pathways account for the failure of most ErbB-targeted therapies. The aim of this study was to enrich a pool of recombinant antibody fragments against common epitopes of ErbB1 and ErbB2 in order to simultaneous blockade of ErbBs signaling pathways. ErbB1 and ErbB2 were expressed stably in VERO cells. Selection of recombinant antibodies was performed on live cells expressing either of ErbB1 and ErbB2 receptors using subtractive phage display approach. The results of PCR and DNA fingerprinting in the last round of panning showed that most clones contained insert (80% and 85% for ErbB1 and ErbB2 respectively) with an identical restriction pattern. The selected clones showed positive reaction to both ErbB1 and ErbB2 receptors in phage-ELISA test. Furthermore, the resulting soluble antibody fragments recognized common epitopes of both immunoprecipitated ErbB1 and ErbB2 in western blot. Additionally, the antibodies directed against the dimerization domain of ErbB1 demonstrated a significant absorbance in EGF-stimulated VERO/ErbB1 cells than non-stimulated cells (1.91 and 1.09 respectively). Moreover, the results of dimerization inhibition test showed that these antibodies blocked ErbB1 and ErbB2 dimerization on the surface of ErbB1 and ErbB2 expressing VERO cells. Regarding the importance of pan-ErbB approach to cancer therapy, the antibodies developed here might provide novel therapeutics for simultaneous blockade of ErbBs signaling pathways.

Keywords: breast cancer, single-chain antibody, ErbB1, ErbB2, epitope

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5060 Antioxidant and Anticancer Activities of Ethanolic Extract from Monascus purpureus

Authors: M. Pourshirazi, M. Esmaelifar, A. Aliahmadi, F. Yazdian, A. S. Hatamian Zarami, S. J. Ashrafi

Abstract:

Medicinal fungi are the new potential source of drugs to improve the treatment of diseases with association to oxidative agents such as cancers. Monascus purpureus contains functional components potentially effective in improving human health. In the present work, ethanolic extract of Monascus purpureus (EEM) was evaluated for health improving potential mainly focusing on antioxidant and anticancer activities. Ferric ion reducing power (FRAP), scavenging of DPPH radicals and determining viability of breast carcinoma MCF-7 and cervical carcinoma HeLa cells with MTT assay were evaluated. Our data showed a significant antioxidant activity of EEM with 142.45 µg/ml inhibition concentration of 50% DPPH radicals and 2112.33 µg eq.Fe2+/mg extract of FRAP assay. These results might be caused by antioxidant components such as pigments and phenolic compounds. Further, the results demonstrated that EEM caused significant reduction in the viability of MCF-7 with IC50 of 7 µg/ml but not have good effect against viability of HeLa cells. Accordingly, Monascus purpureus is presented as a strong potential of breast cancer treatment. In further study, the mechanistic studies are needed to determine the mechanisms of anticancer activity of EEM.

Keywords: Monascus purpureus, antioxidant, cancer, ethanolic extract

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5059 Content-Based Mammograms Retrieval Based on Breast Density Criteria Using Bidimensional Empirical Mode Decomposition

Authors: Sourour Khouaja, Hejer Jlassi, Nadia Feddaoui, Kamel Hamrouni

Abstract:

Most medical images, and especially mammographies, are now stored in large databases. Retrieving a desired image is considered of great importance in order to find previous similar cases diagnosis. Our method is implemented to assist radiologists in retrieving mammographic images containing breast with similar density aspect as seen on the mammogram. This is becoming a challenge seeing the importance of density criteria in cancer provision and its effect on segmentation issues. We used the BEMD (Bidimensional Empirical Mode Decomposition) to characterize the content of images and Euclidean distance measure similarity between images. Through the experiments on the MIAS mammography image database, we confirm that the results are promising. The performance was evaluated using precision and recall curves comparing query and retrieved images. Computing recall-precision proved the effectiveness of applying the CBIR in the large mammographic image databases. We found a precision of 91.2% for mammography with a recall of 86.8%.

Keywords: BEMD, breast density, contend-based, image retrieval, mammography

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5058 Adherence to Dietary Approaches to Stop Hypertension-Style Diet and Risk of Mortality from Cancer: A Systematic Review and Meta-Analysis of Cohort Studies

Authors: Roohallah Fallah-Moshkani, Mohammad Ali Mohsenpour, Reza Ghiasvand, Hossein Khosravi-Boroujeni, Seyed Mehdi Ahmadi, Paula Brauer, Amin Salehi-Abargouei

Abstract:

Purpose: Several investigations have proposed the protective association between dietary approaches to stop hypertension (DASH) style diet and risk of cancers; however, they have led to inconsistent results. The present study aimed to systematically review the prospective cohort studies conducted in this regard and, if possible, to quantify the overall effect of using meta-analysis. Methods: PubMed, EMBASE, Scopus, and Google Scholar were searched for cohort studies published up to December 2017. Relative risks (RRs) which were reported for fully adjusted models and their confidence intervals were extracted for meta-analysis. Random effects model was incorporated to combine the RRs. Results: Sixteen studies were eligible to be included in the systematic review from which 8 reports were conducted on the effect of DASH on the risk of mortality from all cancer types, four on the risk of colorectal cancer, and three on the risk of colon and rectal cancer. Four studies examined the association with other cancers (breast, hepatic, endometrial, and lung cancer). Meta-analysis showed that high concordance with DASH significantly decreases the risk of all cancer types (RR=0.83, 95% confidence interval (95%CI):0.80-0.85); furthermore participants who highly adhered to the DASH had lower risk of developing colorectal (RR=0.79, 95%CI: 0.75-0.83), colon (RR=0.81, 95%CI: 0.74-0.87) and rectal (RR=0.79, 95%CI: 0.63-0.98) cancer compared to those with the lowest adherence. Conclusions: DASH-style diet should be suggested as a healthy approach to protect from cancer in the community. Prospective studies exploring the effect on other cancer types and from regions other than the United States are highly recommended.

Keywords: cancer, DASH-style diet, dietary patterns, meta-analysis, systematic review

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5057 Lung Cancer Detection and Multi Level Classification Using Discrete Wavelet Transform Approach

Authors: V. Veeraprathap, G. S. Harish, G. Narendra Kumar

Abstract:

Uncontrolled growth of abnormal cells in the lung in the form of tumor can be either benign (non-cancerous) or malignant (cancerous). Patients with Lung Cancer (LC) have an average of five years life span expectancy provided diagnosis, detection and prediction, which reduces many treatment options to risk of invasive surgery increasing survival rate. Computed Tomography (CT), Positron Emission Tomography (PET), and Magnetic Resonance Imaging (MRI) for earlier detection of cancer are common. Gaussian filter along with median filter used for smoothing and noise removal, Histogram Equalization (HE) for image enhancement gives the best results without inviting further opinions. Lung cavities are extracted and the background portion other than two lung cavities is completely removed with right and left lungs segmented separately. Region properties measurements area, perimeter, diameter, centroid and eccentricity measured for the tumor segmented image, while texture is characterized by Gray-Level Co-occurrence Matrix (GLCM) functions, feature extraction provides Region of Interest (ROI) given as input to classifier. Two levels of classifications, K-Nearest Neighbor (KNN) is used for determining patient condition as normal or abnormal, while Artificial Neural Networks (ANN) is used for identifying the cancer stage is employed. Discrete Wavelet Transform (DWT) algorithm is used for the main feature extraction leading to best efficiency. The developed technology finds encouraging results for real time information and on line detection for future research.

Keywords: artificial neural networks, ANN, discrete wavelet transform, DWT, gray-level co-occurrence matrix, GLCM, k-nearest neighbor, KNN, region of interest, ROI

Procedia PDF Downloads 153
5056 Cytotoxic Metabolites from Tagetes minuta L. Growing in Saudi Arabia

Authors: Ali A. A. Alqarni, Gamal A. Mohamed, Hossam M. Abdallah, Sabrin R. M. Ibrahim

Abstract:

Phytochemical investigation of the methanolic extract of aerial parts of Tagetes minuta L. (Family: Asteraceae) using different chromatographic techniques led to the isolation of five compounds; ecliptal (1), scopoletin (2), P-hydroxy benzoic acid (3), patuletin (4), and patuletin-7-O-β-D-glucopyranoside (5) (Figure 1). Their structures were established based on physical, chemical, and spectral data [Ultraviolet (UV), Proton ¹H, Carbon thirteen ¹³C, and Heteronuclear Multiple Bond Correlation (HMBC) NMR], as well as Electrospray Ionization Mass Spectroscopy (ESIMS) and comparison with literature data. Their cytotoxic activity was assessed towards human liver hepatocellular carcinoma (HepG2), human breast cancer (MCF-7), and human colon cancer (HCT116) cancer cell lines using sulphorhodamine B (SRB) assay. It is noteworthy that compound 1 demonstrated a significant cytotoxic potential towards HepG2, MCF7, and HCT116 cells with IC₅₀s ranging from 2.74 to 7.01 μM, compared to doxorubicin (IC₅₀ 0.18, 0.60, and 0.20 μM, respectively), whereas compounds 2, 4, and 5 showed moderate cytotoxic potential with IC50s ranging from 11.71 to 35.64 μM. However, 3 was inactive up to a concentration of 100 μM towards the three tested cancer cell lines.

Keywords: Asteraceae, cytotoxicity, metabolites, Tagetes minuta

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5055 Synthesis and Biological Activity Evaluation of U Complexes

Authors: Mohammad Kazem Mohammadi

Abstract:

The use of anticancer agents forms an important part of the treatment of cancer of various types. Uranyl Complexes with DPHMP ligand have been used for the prevention and treatment of cancers. U(IV) metal complexes prepared by reaction of uranyl salt UO2 (NO3)2.6H2O with DPHMP in dry acetonitrile. Characterization of the ligand and its complexes was made by microanalyses, FT-IR, 1H NMR, 13C NMR and UV–Visible spectroscopy. These new complex showed excellent antitumor activity against two kinds of cancer cells that that are HT29:Haman colon adenocarcinoma cell line and T47D:human breast adenocarcinoma cell line.

Keywords: uranyl complexes, DPHMP ligand, antitumor activity, HT29, T47D

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5054 Assessment of the Radiation Absorbed Dose Produced by Lu-177, Ra-223, AC-225 for Metastatic Prostate Cancer in a Bone Model

Authors: Maryam Tajadod

Abstract:

The treatment of cancer is one of the main challenges of nuclear medicine; while cancer begins in an organ, such as the breast or prostate, it spreads to the bone, resulting in metastatic bone. In the treatment of cancer with radiotherapy, the determination of the involved tissues’ dose is one of the important steps in the treatment protocol. Comparing absorbed doses for Lu-177 and Ra-223 and Ac-225 in the bone marrow and soft tissue of bone phantom with evaluating energetic emitted particles of these radionuclides is the important aim of this research. By the use of MCNPX computer code, a model for bone phantom was designed and the values of absorbed dose for Ra-223 and Ac-225, which are Alpha emitters & Lu-177, which is a beta emitter, were calculated. As a result of research, in comparing gamma radiation for three radionuclides, Lu-177 released the highest dose in the bone marrow and Ra-223 achieved the lowest level. On the other hand, the result showed that although the figures of absorbed dose for Ra and Ac in the bone marrow are near to each other, Ra spread more energy in cortical bone. Moreover, The alpha component of the Ra-223 and Ac-225 have very little effect on bone marrow and soft tissue than a beta component of the lu-177 and it leaves the highest absorbed dose in the bone where the source is located.

Keywords: bone metastases, lutetium-177, radium-223, actinium-225, absorbed dose

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5053 In silico Analysis of Differentially Expressed Genes in High-Grade Squamous Intraepithelial Lesion and Squamous Cell Carcinomas Stages of Cervical Cancer

Authors: Rahul Agarwal, Ashutosh Singh

Abstract:

Cervical cancer is one of the women related cancers which starts from the pre-cancerous cells and a fraction of women with pre-cancers of the cervix will develop cervical cancer. Cervical pre-cancers if treated in pre-invasive stage can prevent almost all true cervical squamous cell carcinoma. The present study investigates the genes and pathways that are involved in the progression of cervical cancer and are responsible in transition from pre-invasive stage to other advanced invasive stages. The study used GDS3292 microarray data to identify the stage specific genes in cervical cancer and further to generate the network of the significant genes. The microarray data GDS3292 consists of the expression profiling of 10 normal cervices, 7 HSILs and 21 SCCs samples. The study identifies 70 upregulated and 37 downregulated genes in HSIL stage while 95 upregulated and 60 downregulated genes in SCC stages. Biological process including cell communication, signal transduction are highly enriched in both HSIL and SCC stages of cervical cancer. Further, the ppi interaction of genes involved in HSIL and SCC stages helps in identifying the interacting partners. This work may lead to the identification of potential diagnostic biomarker which can be utilized for early stage detection.

Keywords: cervical cancer, HSIL, microarray, SCC

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5052 Sensitive Electrochemical Sensor for Simultaneous Detection of Endocrine Disruptors, Bisphenol A and 4- Nitrophenol Using La₂Cu₂O₅ Modified Glassy Carbon Electrode

Authors: S. B. Mayil Vealan, C. Sekar

Abstract:

Bisphenol A (BIS A) and 4 Nitrophenol (4N) are the most prevalent environmental endocrine-disrupting chemicals which mimic hormones and have a direct relationship to the development and growth of animal and human reproductive systems. Moreover, intensive exposure to the compound is related to prostate and breast cancer, infertility, obesity, and diabetes. Hence, accurate and reliable determination techniques are crucial for preventing human exposure to these harmful chemicals. Lanthanum Copper Oxide (La₂Cu₂O₅) nanoparticles were synthesized and investigated through various techniques such as scanning electron microscopy, high-resolution transmission electron microscopy, X-ray diffraction, X-ray photoelectron spectroscopy, and electrochemical impedance spectroscopy. Cyclic voltammetry and square wave voltammetry techniques are employed to evaluate the electrochemical behavior of as-synthesized samples toward the electrochemical detection of Bisphenol A and 4-Nitrophenol. Under the optimal conditions, the oxidation current increased linearly with increasing the concentration of BIS A and 4-N in the range of 0.01 to 600 μM with a detection limit of 2.44 nM and 3.8 nM. These are the lowest limits of detection and the widest linear ranges in the literature for this determination. The method was applied to the simultaneous determination of BIS A and 4-N in real samples (food packing materials and river water) with excellent recovery values ranging from 95% to 99%. Better stability, sensitivity, selectivity and reproducibility, fast response, and ease of preparation made the sensor well-suitable for the simultaneous determination of bisphenol and 4 Nitrophenol. To the best of our knowledge, this is the first report in which La₂Cu₂O₅ nano particles were used as efficient electron mediators for the fabrication of endocrine disruptor (BIS A and 4N) chemical sensors.

Keywords: endocrine disruptors, electrochemical sensor, Food contacting materials, lanthanum cuprates, nanomaterials

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5051 Tumor-Biological Characteristics of Invasive Lobular Carcinoma

Authors: Sabine Danzinger, Nora Hielscher, Miriam Izso, Johanna Metzler, Carmen Trinkl, Christian Pfeifer, Kristina Tendl-Schulz, Christian F. Singer

Abstract:

The objective of this study is to analyze the characteristics of invasive lobular carcinoma (ILC) compared with invasive ductal carcinoma (IDC) and to investigate the impact of histology on axillary lymph node (ALN) involvement in luminal A subtype tumors. Methods: We retrospectively analyzed patients diagnosed with ILC or IDC from 2012 to 2016 who underwent surgery. Patients constituted 493 primary early breast cancer cases (82 ILC; 411 IDC). Results: Compared with IDC, ILC tumors were significantly more likely to be grade 2, estrogen receptor- (ER) positive (þ), have a lower proliferation rate (Ki67 <14%), and a higher patholog- ical T stage (pT2–4). The luminal A subtype was significantly more common in ILC compared with IDC. In a multivariate regression model, grade 2, ERþ, progesterone receptor-positive, pT2, and pT3 were significantly associated with ILC. Additionally, with the luminal A subtype, ALN involvement (pathological node stage (pN)1–3) was significantly more frequent with ILC versus IDC. Conclusions: Our data suggests that grade 2, positive hormone receptor status, and higher pathological T stage are associated with ILC. With the luminal A subtype, ALN involvement was more frequent with ILC versus IDC.

Keywords: breast cancer, lobular histology, tumor biology, hormone receptor, ki67

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5050 Apoptosis Activity of Persea declinata (Bl.) Kosterm Bark Methanolic Crude Extract

Authors: P. Narrima, C. Y. Looi, M. A. Mohd, H. M. Ali

Abstract:

Persea declinata (Bl.) Kosterm is a member of the Lauraceae family, widely distributed in Southeast Asia. It is from the same genus with avocado (Persea americana Mill), which is widely consumed as food and for medicinal purposes. In the present study, we examined the anticancer properties of Persea declinata (Bl.) Kosterm bark methanolic crude extract (PDM). PDM exhibited a potent antiproliferative effect in MCF-7 human breast cancer cells, with an IC50 value of 16.68 µg/mL after 48h of treatment. We observed that PDM caused cell cycle arrest and subsequent apoptosis in MCF-7 cells, as exhibited by increased population at G0/G1 phase, higher lactate dehydrogenase (LDH) release, and DNA fragmentation. Mechanistic studies showed that PDM caused significant elevation in ROS production, leading to perturbation of mitochondrial membrane potential, cell permeability, and activation of caspases-3/7. On the other hand, real-time PCR and Western blot analysis showed that PDM treatment increased the expression of the proapoptotic molecule, Bax, but decreased the expression of prosurvival proteins, Bcl-2 and Bcl-xL, in a dose-dependent manner. These findings imply that PDM could inhibit proliferation in MCF-7 cells via cell cycle arrest and apoptosis induction, indicating its potential as a therapeutic agent worthy of further development.

Keywords: antiproliferative, apoptosis, MCF-7 human breast cancer, Persea declinata

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5049 Role of Human Epididymis Protein 4 as a Biomarker in the Diagnosis of Ovarian Cancer

Authors: Amar Ranjan, Julieana Durai, Pranay Tanwar

Abstract:

Background &Introduction: Ovarian cancer is one of the most common malignant tumor in the female. 70% of the cases of ovarian cancer are diagnosed at an advanced stage. The five-year survival rate associated with ovarian cancer is less than 30%. The early diagnosis of ovarian cancer becomes a key factor in improving the survival rate of patients. Presently, CAl25 (carbohydrate antigen125) is used for the diagnosis and therapeutic monitoring of ovarian cancer, but its sensitivity and specificity is not ideal. The introduction of HE4, human epididymis protein 4 has attracted much attention. HE4 has a sensitivity and specificity of 72.9% and 95% for differentiating between benign and malignant adnexal masses, which is better than CA125 detection.  Methods: Serum HE4 and CA -125 were estimated using the chemiluminescence method. Our cases were 40 epithelial ovarian cancer, 9 benign ovarian tumor, 29 benign gynaecological diseases and 13 healthy individuals. This group include healthy woman those who have undergoing family planning and menopause-related medical consultations and they are negative for ovarian mass. Optimal cut off values for HE4 and CA125 were 55.89pmol/L and 40.25U/L respectively (determined by statistical analysis). Results: The level of HE4 was raised in all ovarian cancer patients (n=40) whereas CA125 levels were normal in 6/40 ovarian cancer patients, which were the cases of OC confirmed by histopathology. There is a significant decrease in the level of HE4 with comparison to CA125 in benign ovarian tumor cases. Both the levels of HE4 and CA125 were raised in the nonovarian cancer group, which includes cancer of endometrium and cervix. In the healthy group, HE4 was normal in all patients except in one case of the rudimentary horn, and the reason for this raised HE4 level is due to the incomplete development of uterus whereas CA125 was raised in 3 cases. Conclusions: Findings showed that the serum level of HE4 is an important indicator in the diagnosis of ovarian cancer, and it also distinguishes between benign and malignant pelvic masses. However, a combination of HE4 and CA125 panel will be extremely valuable in improving the diagnostic efficiency of ovarian cancer. These findings of our study need to be validated in the larger cohort of patients.

Keywords: human epididymis protein 4, ovarian cancer, diagnosis, benign lesions

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5048 Automated Prediction of HIV-associated Cervical Cancer Patients Using Data Mining Techniques for Survival Analysis

Authors: O. J. Akinsola, Yinan Zheng, Rose Anorlu, F. T. Ogunsola, Lifang Hou, Robert Leo-Murphy

Abstract:

Cervical Cancer (CC) is the 2nd most common cancer among women living in low and middle-income countries, with no associated symptoms during formative periods. With the advancement and innovative medical research, there are numerous preventive measures being utilized, but the incidence of cervical cancer cannot be truncated with the application of only screening tests. The mortality associated with this invasive cervical cancer can be nipped in the bud through the important role of early-stage detection. This study research selected an array of different top features selection techniques which was aimed at developing a model that could validly diagnose the risk factors of cervical cancer. A retrospective clinic-based cohort study was conducted on 178 HIV-associated cervical cancer patients in Lagos University teaching Hospital, Nigeria (U54 data repository) in April 2022. The outcome measure was the automated prediction of the HIV-associated cervical cancer cases, while the predictor variables include: demographic information, reproductive history, birth control, sexual history, cervical cancer screening history for invasive cervical cancer. The proposed technique was assessed with R and Python programming software to produce the model by utilizing the classification algorithms for the detection and diagnosis of cervical cancer disease. Four machine learning classification algorithms used are: the machine learning model was split into training and testing dataset into ratio 80:20. The numerical features were also standardized while hyperparameter tuning was carried out on the machine learning to train and test the data. Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), and K-Nearest Neighbor (KNN). Some fitting features were selected for the detection and diagnosis of cervical cancer diseases from selected characteristics in the dataset using the contribution of various selection methods for the classification cervical cancer into healthy or diseased status. The mean age of patients was 49.7±12.1 years, mean age at pregnancy was 23.3±5.5 years, mean age at first sexual experience was 19.4±3.2 years, while the mean BMI was 27.1±5.6 kg/m2. A larger percentage of the patients are Married (62.9%), while most of them have at least two sexual partners (72.5%). Age of patients (OR=1.065, p<0.001**), marital status (OR=0.375, p=0.011**), number of pregnancy live-births (OR=1.317, p=0.007**), and use of birth control pills (OR=0.291, p=0.015**) were found to be significantly associated with HIV-associated cervical cancer. On top ten 10 features (variables) considered in the analysis, RF claims the overall model performance, which include: accuracy of (72.0%), the precision of (84.6%), a recall of (84.6%) and F1-score of (74.0%) while LR has: an accuracy of (74.0%), precision of (70.0%), recall of (70.0%) and F1-score of (70.0%). The RF model identified 10 features predictive of developing cervical cancer. The age of patients was considered as the most important risk factor, followed by the number of pregnancy livebirths, marital status, and use of birth control pills, The study shows that data mining techniques could be used to identify women living with HIV at high risk of developing cervical cancer in Nigeria and other sub-Saharan African countries.

Keywords: associated cervical cancer, data mining, random forest, logistic regression

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5047 TiO₂ Nanotube Array Based Selective Vapor Sensors for Breath Analysis

Authors: Arnab Hazra

Abstract:

Breath analysis is a quick, noninvasive and inexpensive technique for disease diagnosis can be used on people of all ages without any risk. Only a limited number of volatile organic compounds (VOCs) can be associated with the occurrence of specific diseases. These VOCs can be considered as disease markers or breath markers. Selective detection with specific concentration of breath marker in exhaled human breath is required to detect a particular disease. For example, acetone (C₃H₆O), ethanol (C₂H₅OH), ethane (C₂H₆) etc. are the breath markers and abnormal concentrations of these VOCs in exhaled human breath indicates the diseases like diabetes mellitus, renal failure, breast cancer respectively. Nanomaterial-based vapor sensors are inexpensive, small and potential candidate for the detection of breath markers. In practical measurement, selectivity is the most crucial issue where trace detection of breath marker is needed to identify accurately in the presence of several interfering vapors and gases. Current article concerns a novel technique for selective and lower ppb level detection of breath markers at very low temperature based on TiO₂ nanotube array based vapor sensor devices. Highly ordered and oriented TiO₂ nanotube array was synthesized by electrochemical anodization of high purity tatinium (Ti) foil. 0.5 wt% NH₄F, ethylene glycol and 10 vol% H₂O was used as the electrolyte and anodization was carried out for 90 min with 40 V DC potential. Au/TiO₂ Nanotube/Ti, sandwich type sensor device was fabricated for the selective detection of VOCs in low concentration range. Initially, sensor was characterized where resistive and capacitive change of the sensor was recorded within the valid concentration range for individual breath markers (or organic vapors). Sensor resistance was decreased and sensor capacitance was increased with the increase of vapor concentration. Now, the ratio of resistive slope (mR) and capacitive slope (mC) provided a concentration independent constant term (M) for a particular vapor. For the detection of unknown vapor, ratio of resistive change and capacitive change at any concentration was same to the previously calculated constant term (M). After successful identification of the target vapor, concentration was calculated from the straight line behavior of resistance as a function of concentration. Current technique is suitable for the detection of particular vapor from a mixture of other interfering vapors.

Keywords: breath marker, vapor sensors, selective detection, TiO₂ nanotube array

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