The molecular validation of miRNA's as specific biomarkers for early diagnosis of ovarian cancer

Magister Scientiae - MSc (Biotechnology)Ovarian Cancer (OC) is the most common reproductive and the most lethal gynaecological malignant tumour. The majority of Ovarian Cancers, comprising more than 95% of cases, emanate from the surface epithelium of the ovary, commonly referred to as Epithelial Ovarian Cancer (EOC). OC is the eighth most common form of cancer in women world-wide and in South Africa approximately 800 women die annually from the disease without diagnosis. OC is located deep within the pelvic region making early diagnosis and monitoring of the disease challenging. A minute group of cancer cells presents itself on the surface of one or both of the ovaries. The current diagnostic tests for OC include pelvic examination, imaging studies, diagnostic imaging and a serum protein biomarker, CA-125. These diagnostic tools have low specificity, poor sensitivity, reduced positive predictive value and are quite invasive. Therefore, a method for early diagnosis is required that is less invasive and overcome the limitations regarding specificity, sensitivity and positive predictive value. Biomarkers are identified as feasible alternatives for early detection of Ovarian Cancer for example biological indicators such as DNA, RNA, proteins and microRNAs (miRNAs)

Serum microRNA array analysis identifies miR-140-3p, miR-33b-3p and miR-671-3p as potential osteoarthritis biomarkers involved in metabolic processes.

Background: MicroRNAs (miRNAs) in circulation have emerged as promising biomarkers. In this study, we aimed to identify a circulating miRNA signature for osteoarthritis (OA) patients and in combination with bioinformatics analysis to evaluate the utility of selected differentially expressed miRNAs in the serum as potential OA biomarkers. Methods: Serum samples were collected from 12 primary OA patients, and 12 healthy individuals were screened using the Agilent Human miRNA Microarray platform interrogating 2549 miRNAs. Receiver Operating Characteristic (ROC) curves were constructed to evaluate the diagnostic performance of the deregulated miRNAs. Expression levels of selected miRNAs were validated by quantitative real-time PCR (qRT-PCR) in all serum and in articular cartilage samples from OA patients (n = 12) and healthy individuals (n = 7). Bioinformatics analysis was used to investigate the involved pathways and target genes for the above miRNAs. Results: We identified 279 differentially expressed miRNAs in the serum of OA patients compared to controls. Two hundred and five miRNAs (73.5%) were upregulated and 74 (26.5%) downregulated. ROC analysis revealed that 77 miRNAs had area under the curve (AUC) > 0.8 and p < 0.05. Bioinformatics analysis in the 77 miRNAs revealed that their target genes were involved in multiple signaling pathways associated with OA, among which FoxO, mTOR, Wnt, pI3K/akt, TGF-β signaling pathways, ECM-receptor interaction, and fatty acid biosynthesis. qRT-PCR validation in seven selected out of the 77 miRNAs revealed 3 significantly downregulated miRNAs (hsa-miR-33b-3p, hsa-miR-671-3p, and hsa-miR-140-3p) in the serum of OA patients, which were in silico predicted to be enriched in pathways involved in metabolic processes. Target-gene analysis of hsa-miR-140-3p, hsa-miR-33b-3p, and hsa-miR-671-3p revealed that InsR and IGFR1 were common targets of all three miRNAs, highlighting their involvement in regulation of metabolic processes that contribute to OA pathology. Hsa-miR-140-3p and hsa-miR-671-3p expression levels were consistently downregulated in articular cartilage of OA patients compared to healthy individuals. Conclusions: A serum miRNA signature was established for the first time using high density resolution miR-arrays in OA patients. We identified a three-miRNA signature, hsa-miR-140-3p, hsa-miR-671-3p, and hsa-miR-33b-3p, in the serum of OA patients, predicted to regulate metabolic processes, which could serve as a potential biomarker for the evaluation of OA risk and progression.Peer reviewedFinal Published versio

Identification of novel microRNAs as potential biomarkers for the early diagnosis of ovarian cancer using an in-silico approach

Philosophiae Doctor - PhDOvarian cancer (OC) is the most fatal gynaecologic malignancy that is generally diagnosed in the advanced stages, resulting in a low survival rate of about 40%. This emphasizes the need to identify a biomarker that can allow for accurate diagnosis at stage I. MicroRNAs (miRNAs) are appealing as biomarkers due to their stability, non-invasiveness, and differential expression in tumour tissue compared to healthy tissue. Since they are non-coding, their biological functions can be uncovered by examining their target genes and thus identifying their regulatory pathways and processes. This study aimed to identify miRNAs and genes as candidate biomarkers for early stage OC diagnosis, through two distinct in silico approaches. The first pipeline was based on sequence similarity between miRNAs with a proven mechanism in OC and miRNAs with no known role. This resulted in 9 candidate miRNAs, that have not been previously implicated in OC, that showed 90-99% similarity to a miRNA involved in OC. Following a series of in silico experimentations, it was uncovered that these miRNAs share 12 gene targets that are expressed in the ovary and also have proven implications in the disease. Since the miRNAs target genes contribute to OC onset and progression, it strengthens the notion that the miRNAs may be dysregulated as well. Using TCGA, the second pipeline involved analysing patient clinical data along with implementing statistical measures to isolate miRNAs and genes with high expression in OC. This resulted in 26 miRNAs and 25 genes being shortlisted as the potential candidates for OC management. It was also noted that targeting interactions occur between 15 miRNAs and 16 genes identified through this pipeline. In total, 35 miRNAs and 37 genes were identified from both pipelines

Identification of biomarkers associated with cervical cancer: a combined in silico and molecular approach

>Magister Scientiae - MScCervical cancer is the leading cause of cancer mortality among black women in South Africa. It is estimated that this disease kills approximately 8 women in South Africa every day. Cervical cancer is caused by the human papillomavirus (HPV) with the most common screening method for cervical cancer being Papanicolaou (Pap) smear, test amongst others. However, less than 20% of South African women go for these tests. There are several reasons why women do not go for these tests but the invasiveness of the test is one of the major causes for the low rate of screening. Lateral flow devices offer medical diagnosis at the point- of-care, allowing for the quick initiation of the appropriate therapeutic response. These tests are more cost-effective for the healthcare delivery industry, and can potentially be used by patients to self-test in the privacy of their homes and allow them to make informed decisions about their health. Therefore, the aim of this study was to use computational methods to identify serum biomarkers for cervical cancer that can be used to develop a point-of-care diagnostic device for cervical cancer. An in silico approach was used to identify genes implicated in the initiation and development of cervical cancer. Several bioinformatics tools were employed to extract a list of genes from publicly available cancer repositories. Multiple gene enrichment analysis tools were employed to analyze the selected candidate genes. Through this pipeline, ~28190 genes were identified from the various databases and were further refined to only 10 genes. The 10 genes were identified as potential cervical cancer biomarkers. A subcellular compartmentalization analysis clustered the proteins encoded by these genes as cell surface, secretory granules and extracellular space/matrix proteins. The selected candidate genes were predicted to be specific for cervical cancer tissue in a cancer tissue specificity meta-analysis study. The expression levels of the candidate genes were compared relative to each other and a graph constructed using gene expression data generated by GeneHub-GEPIS and TiGER databases. Further gene enrichment analysis was performed such as protein-protein interactions, transcription factor analysis, pathway analysis and co-expression analysis, with 9 out of the10 of the candidate genes showing co-expression. A gene expression analysis done on cervical cancer cell lines, other cancer cell lines and normal fibroblast cell line revealed differential expression of the candidate genes. Three candidate genes were significantly expressed in cervical cancer, while the seven remaining genes showed over expression in other cancer types. The study serves as basis for future investigations to diagnosis of cervical cancer, as well as for cancers. Thus, they could also serve as potential drug targets for cancer therapeutics and diagnostics

Candidate RNA biomarkers in biofluids for early diagnosis of ovarian cancer : a systematic review

Ovarian cancer is often diagnosed in an advanced stage and is associated with a high mortality rate. It is assumed that early detection of ovarian cancer could improve patient outcomes. Unfortunately, effective screening methods for early diagnosis of ovarian cancer are still lacking. Extracellular RNAs circulating in human biofluids can reliably be measured and are emerging as potential biomarkers in cancer. In this systematic review, we present 75 RNA biomarkers detectable in human biofluids that have been studied for early diagnosis of ovarian cancer. The majority of these markers are microRNAs identified using RT-qPCR or microarrays in blood-based fluids. A handful of studies used RNA-sequencing and explored alternative fluids, such as urine and ascites. Candidate RNA biomarkers that were more abundant in biofluids of ovarian cancer patients compared to controls in at least two independent studies include miR-21, the miR-200 family, miR-205, miR-10a and miR-346. Amongst the markers confirmed to be lower in at least two studies are miR-122, miR-193a, miR-223, miR-126 and miR-106b. While these biomarkers show promising diagnostic potential, further validation is required before implementation in routine clinical care. Challenges related to biomarker validation and reflections on future perspectives to accelerate progress in this field are discussed

Recent Developments in Cancer Systems Biology

This ebook includes original research articles and reviews to update readers on the state of the art systems approach to not only discover novel diagnostic and prognostic biomarkers for several cancer types, but also evaluate methodologies to map out important genomic signatures. In addition, therapeutic targets and drug repurposing have been emphasized for a variety of cancer types. In particular, new and established researchers who desire to learn about cancer systems biology and why it is possibly the leading front to a personalized medicine approach will enjoy reading this book

In silico Approach for Validating and Unveiling New Applications for Prognostic Biomarkers of Endometrial Cancer

Bioinformática; Cáncer de endometrio; Biomarcador pronósticoBioinformàtica; Càncer d'endometri; Biomarcador pronòsticBioinformatics; Endometrial cancer; Prognostic biomarkerEndometrial cancer (EC) mortality is directly associated with the presence of prognostic factors. Current stratification systems are not accurate enough to predict the outcome of patients. Therefore, identifying more accurate prognostic EC biomarkers is crucial. We aimed to validate 255 prognostic biomarkers identified in multiple studies and explore their prognostic application by analyzing them in TCGA and CPTAC datasets. We analyzed the mRNA and proteomic expression data to assess the statistical prognostic performance of the 255 proteins. Significant biomarkers related to overall survival (OS) and recurrence-free survival (RFS) were combined and signatures generated. A total of 30 biomarkers were associated either to one or more of the following prognostic factors: histological type (n = 15), histological grade (n = 6), FIGO stage (n = 1), molecular classification (n = 16), or they were associated to OS (n = 11), and RFS (n = 5). A prognostic signature composed of 11 proteins increased the accuracy to predict OS (AUC = 0.827). The study validates and identifies new potential applications of 30 proteins as prognostic biomarkers and suggests to further study under-studied biomarkers such as TPX2, and confirms already used biomarkers such as MSH6, MSH2, or L1CAM. These results are expected to advance the quest for biomarkers to accurately assess the risk of EC patients.This research was funded by grants from the Instituto de Salud Carlos III (ISCIII) grant number PI17/02155, PI20/00644, and the IFI19/00029 to E.C.-d.l.R., the Ministerio de ciencia, Innovación y Universidades through a RETOS Colaboración (RTC-2017-6261-1), both co-financed by the European Regional Development Fund (FEDER); from Fundación Científica Asociación Española Contra el Cáncer (AECC) grant number GCTRA1804MATI and CIBERONC network grant number CB16/12/00328; and Grups Consolidats de la Generalitat de Catalunya (2017SGR1661). E.C. is supported by an Investigator Grant from AECC (INVES20051COLA). E.M.-G. was supported by Televie grant F5/20/5-TLV/DD

E2F5 status significantly improves malignancy diagnosis of epithelial ovarian cancer

<p>Abstract</p> <p>Background</p> <p>Ovarian epithelial cancer (OEC) usually presents in the later stages of the disease. Factors, especially those associated with cell-cycle genes, affecting the genesis and tumour progression for ovarian cancer are largely unknown. We hypothesized that over-expressed transcription factors (TFs), as well as those that are driving the expression of the OEC over-expressed genes, could be the key for OEC genesis and potentially useful tissue and serum markers for malignancy associated with OEC.</p> <p>Methods</p> <p>Using a combination of computational (selection of candidate TF markers and malignancy prediction) and experimental approaches (tissue microarray and western blotting on patient samples) we identified and evaluated E2F5 transcription factor involved in cell proliferation, as a promising candidate regulatory target in early stage disease. Our hypothesis was supported by our tissue array experiments that showed E2F5 expression only in OEC samples but not in normal and benign tissues, and by significantly positively biased expression in serum samples done using western blotting studies.</p> <p>Results</p> <p>Analysis of clinical cases shows that of the E2F5 status is characteristic for a different population group than one covered by CA125, a conventional OEC biomarker. E2F5 used in different combinations with CA125 for distinguishing malignant cyst from benign cyst shows that the presence of CA125 or E2F5 increases sensitivity of OEC detection to 97.9% (an increase from 87.5% if only CA125 is used) and, more importantly, the presence of both CA125 and E2F5 increases specificity of OEC to 72.5% (an increase from 55% if only CA125 is used). This significantly improved accuracy suggests possibility of an improved diagnostics of OEC. Furthermore, detection of malignancy status in 86 cases (38 benign, 48 early and late OEC) shows that the use of E2F5 status in combination with other clinical characteristics allows for an improved detection of malignant cases with sensitivity, specificity, F-measure and accuracy of 97.92%, 97.37%, 97.92% and 97.67%, respectively.</p> <p>Conclusions</p> <p>Overall, our findings, in addition to opening a realistic possibility for improved OEC diagnosis, provide an indirect evidence that a cell-cycle regulatory protein E2F5 might play a significant role in OEC pathogenesis.</p

Identification of novel miRNAs as diagnostic and prognostic biomarkers for prostate cancer using an in silico approach

Magister Scientiae - MSc (Biotechnology)Cancer is known as uncontrollable cell growth which results in the formation of tumours in the areas that are affected by the cancer. There are two types of tumours: benign and malignant. This study focus is on prostate cancer (PCa) as one of the most common cancers in men around the world. A previous study has reported that there were 27,132 new cases of cancer in South Africa in 2010. Out of those, 4652 were prostate cancer cases, which make it a considerable issue. The prostate is a gland that forms part of the male reproductive system. Prostate cancer is more apparent in men over the age of 65 years however it can be present in men of a lower age. However it is rare in men under 45 years of age. Prostate cancer start as a small group of cancer cells that can grow into a mature tumour. In the advanced stages, the tumour cells can spread to other tissue by metastases and can lead to death. Current diagnostic tools include Digital Rectal Examination (DRE), the Prostate-Specific Antigen test (PSA) ultra sound, and biopsy

Integrative, In Silico and Comparative Analysis of Breast Cancer Secretome Highlights Invasive-Ductal-Carcinoma-Grade Progression Biomarkers

Funding: This research was funded by NHS Grampian Endowment Fund grant number NER11101 Acknowledgments: The authors would like to thank the NHS Grampian Breast Cancer Endowment Fund body for supporting the publication of the present manuscript and funding publication fees.Peer reviewedPublisher PD