Extracting Efficient Fuzzy If-Then Rules from Mass Spectra of Blood Samples to Early Diagnosis of Ovarian Cancer

Author(s):  
A. Assareh ◽  
M.H. Moradi
Author(s):  
Eva Hulstaert ◽  
Annelien Morlion ◽  
Keren Levanon ◽  
Jo Vandesompele ◽  
Pieter Mestdagh

2002 ◽  
Vol 3 (3) ◽  
pp. 221-225

In recent months a bumper crop of genomes has been completed, including the fission yeast (Schizosaccharomyces pombe) and rice (Oryza sativa). Two large-scale studies ofSaccharomyces cerevisiaeprotein complexes provided a picture of the eukaryotic proteome as a network of complexes. Amongst the other stories of interest was a demonstration that proteomic analysis of blood samples can be used to detect ovarian cancer, perhaps even as early as stage I.


2021 ◽  
Author(s):  
Bhargav N. Waghela ◽  
Ramesh J. Pandit ◽  
Apurvasinh Puvar ◽  
Franky D. Shah ◽  
Prabhudas S. Patel ◽  
...  

Abstract Background Breast and ovarian cancers are the most common cancer types in females in India which pertain to higher mortality and morbidity due to late diagnosis and poor prognosis. Early diagnosis for better prognosis improve the patient’s treatment and survival. The next-generation sequencing (NGS)-based screening has accelerated molecular diagnosis of various cancers. Methods We performed whole exome sequencing (WES) of 30 patients who had a first or second degree relative with breast or ovarian cancer. Further, all these patients are tested negative for BRCA1/2 or other high and moderate risk genes reported for HBOC. WES data from 30 patients were analyzed and variants were called using bcftools. Functional annotation of variants and variant prioritization was performed by Exomiser. The clinical significance of variants was determined by Varsome tool. The functional analysis of genes was determined by STRING analysis and disease association was determined by open target tool. Results We examined the variants based on the prevalence of variants among 30 patients i.e. frequency and disease association determined by the phenotype score of exomiser. From both the approaches, we found novel variants and novel gene candidates associated with HBOC conditions. The variants in HYDIN, AVIL, IWS1, PLA2G6, PRDM4, ST3GAL2, and ZNF717 were predicted highly oncogenic. Moreover, we also found 59 genes having higher phenotype score (phenotype score >0.75) and which are associated with various biological processes such as DNA integrity maintenance, transcriptional regulation, cell cycle and apoptosis. Conclusion The gene variants associated with HBOC condition in West Indian cohort have been revisited. Our findings provide novel as well as highly prevalent variants in the population which could be further studied in detail for their use in early diagnosis and better prognosis of HBOC patients.


2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Pedro Pesini ◽  
Virginia Pérez-Grijalba ◽  
Inmaculada Monleón ◽  
Mercè Boada ◽  
Lluís Tárraga ◽  
...  

The present study was aimed at assessing the capability of Aβ1-40 and Aβ1-42 levels in undiluted plasma (UP), diluted plasma (DP), and cell bound (CB) to distinguish between early stages of Alzheimer's disease (AD), amnesic mild cognitive impairment (MCI), and healthy control (HC). Four blood samples from each participant were collected during one month and the levels of Aβ1-40 and Aβ1-42 were determined by a blinded proprietary ELISA sandwich (Araclon Biotech. Zaragoza, Spain). First striking result was that the amount of Aβ1-40 and Aβ1-42 in UP represented only a small proportion (~15%) of the total beta-amyloid pool in blood (βAPB) described here as the sum of Aβ1-40 and Aβ1-42 in blood where they are free in plasma, bound to plasma proteins, and bound to blood cells. Furthermore, we found that levels of Aβ1-40 and Aβ1-42 in UP, DP, and CB were significantly higher in MCI when compared to HC. On average, the totalβAPB was 1.8 times higher in MCI than in HC (P=0.03) and allowed to discriminate between MCI and HC with a sensitivity and specificity over 80%. Thus, quantification of several markers of theβAPB could be useful and reliable in the discrimination between MCI and HC.


2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Pavla Valkova ◽  
Miroslav Pohanka

Background. Alzheimer’s disease (AD) is a multifactorial progressive and irreversible neurodegenerative disorder affecting mainly the population over 65 years of age. It is becoming a global health and socioeconomic problem, and the current number of patients reaching 30–50 million people will be three times higher over the next thirty years. Objective. Late diagnosis caused by decades of the asymptomatic phase and invasive and cost-demanding diagnosis are problems that make the whole situation worse. Electrochemical biosensors could be the right tool for less invasive and inexpensive early diagnosis helping to reduce spend sources— both money and time. Method. This review is a survey of the latest advances in the design of electrochemical biosensors for the early diagnosis of Alzheimer’s disease. Biosensors are divided according to target biomarkers. Conclusion. Standard laboratory methodology could be improved by analyzing a combination of currently estimated markers along with neurotransmitters and genetic markers from blood samples, which make the test for AD diagnosis available to the wide public.


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