Serum-based protein biomarkers for detection of lung cancer

2014 ◽  
Vol 9 (4) ◽  
pp. 341-358
Author(s):  
Shilpa Bhatnagar ◽  
Deepshikha Katare ◽  
Swatantra Jain
Keyword(s):  
Lung Cancer ◽  
Cancer Biology ◽  
Early Stage ◽  
Expression Patterns ◽  
Cost Effective ◽  
Diagnostic Tools ◽  
Protein Biomarkers ◽  
Functional Studies ◽  
Molecular Tests ◽  
Effective Manner

AbstractLung cancer is one of the most common cancers in terms of both incidence and mortality.The major reasons for the increasing number of deaths from lung cancer are late detection and lack of effective therapies. To improve our understanding of lung cancer biology, there is urgent need for blood-based, non-invasive molecular tests to assist in its detection in a cost-effective manner at an early stage when curative interventions are still possible. Recent advances in proteomic technology have provided extensive, high throughput analytical tools for identification, characterization and functional studies of proteomes. Changes in protein expression patterns in response to stimuli can serve as indicators or biomarkers of biological and pathological processes as well as physiological and pharmacological responses to drug treatment, thus aiding in early diagnosis and prognosis of disease. However, only a few biomarkers have been approved by the FDA to date for screening and diagnostic purposes. This review provides a brief overview of currently available proteomic techniques, their applications and limitations and the current state of knowledge about important serum biomarkers in lung cancer and their potential value as prognostic and diagnostic tools.

scholarly journals MicroRNAs in Diabetic Kidney Disease

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Rong Li ◽  
Arthur C. K. Chung ◽  
Xueqing Yu ◽  
Hui Y. Lan
Keyword(s):  
Kidney Disease ◽  
Messenger Rna ◽  
Diabetic Kidney Disease ◽  
Target Genes ◽  
Therapeutic Potential ◽  
Expression Patterns ◽  
Diagnostic Tools ◽  
Diabetic Kidney ◽  
Functional Studies ◽  
Gene Expression Studies

Rapid growth of diabetes and diabetic kidney disease exerts a great burden on society. Owing to the lack of effective treatments for diabetic kidney disease, treatment relies on drugs that either reduces its progression or involve renal replacement therapies, such as dialysis and kidney transplantation. It is urgent to search for biomarkers for early diagnosis and effective therapy. The discovery of microRNAs had lead to a new era of post-transcriptional regulators of gene expression. Studies from cells, experimental animal models and patients under diabetic conditions demonstrate that expression patterns of microRNAs are altered during the progression of diabetic kidney disease. Functional studies indicate that the ability of microRNAs to bind 3′ untranslated region of messenger RNA not only shows their capability to regulate expression of target genes, but also their therapeutic potential to diabetic kidney disease. The presence of microRNAs in plasma, serum, and urine has been shown to be possible biomarkers in diabetic kidney disease. Therefore, identification of the pathogenic role of microRNAs possesses an important clinical impact in terms of prevention and treatment of progression in diabetic kidney disease because it allows us to design novel and specific therapies and diagnostic tools for diabetic kidney disease.

scholarly journals Diagnostic Limitation of Chikungunya Fever and its Future Prospect: A Review Update

2019 ◽  
Vol 5 (2) ◽  
pp. 64-70
Author(s):  
Mahmuda Yeasmin ◽  
Md Abdullah Yusuf ◽  
Muhibbur Rahman
Keyword(s):  
Chikungunya Virus ◽  
Early Stage ◽  
Treatment Strategies ◽  
Febrile Illness ◽  
Cost Effective ◽  
Disease Diagnosis ◽  
Diagnostic Tools ◽  
Viral Diseases ◽  
Infected Adult ◽  
Proper Diagnosis

Chikungunya is a febrile illness which is usually self-limiting caused by Chikungunya virus (CHIKV). It is transmitted bythe bites of infected adult female mosquitoes mainly Aedesaegypti and Aedesalbopictus from human to human; these vectors also transmit other viral diseases including dengue, zika virus and yellow fever. These viral diseases presented in a similar manner in their early stage of infection specially dengue and chikungunya since neither of them possesses any specific feature to be distinguished clinically. Their outcome and treatment strategies are distinct so early and accurate diagnosis is mandatory for better management and taking appropriate measures to prevent or reduce severity of complications. An early confirmation of any infection demands diagnostic tools that are highly specific and cost effective. Currently no diagnostic tool is available for CHIKV detection which can fulfill these criteria. Moreover effective surveillance, outbreak control, vaccine design and drug development all this demand proper diagnosis. In this review we focus on limitation of available laboratory tests related to diagnosis of chikungunya virus and discuss priorities for further studies needed for disease diagnosis in early stage to control the outbreaks Bangladesh Journal of Infectious Diseases, December 2018;5(2):65-70

scholarly journals 3D-Printed Immunosensor Arrays for Cancer Diagnostics

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4514 ◽  
Author(s):  
Mohamed Sharafeldin ◽  
Karteek Kadimisetty ◽  
Ketki S. Bhalerao ◽  
Tianqi Chen ◽  
James F. Rusling
Keyword(s):  
3D Printing ◽  
Early Stage ◽  
Point Of Care ◽  
Low Cost ◽  
Cancer Diagnostics ◽  
Diagnostic Tools ◽  
Protein Biomarkers ◽  
Protein Biomarker ◽  
Subtractive Manufacturing ◽  
3D Printed

Detecting cancer at an early stage of disease progression promises better treatment outcomes and longer lifespans for cancer survivors. Research has been directed towards the development of accessible and highly sensitive cancer diagnostic tools, many of which rely on protein biomarkers and biomarker panels which are overexpressed in body fluids and associated with different types of cancer. Protein biomarker detection for point-of-care (POC) use requires the development of sensitive, noninvasive liquid biopsy cancer diagnostics that overcome the limitations and low sensitivities associated with current dependence upon imaging and invasive biopsies. Among many endeavors to produce user-friendly, semi-automated, and sensitive protein biomarker sensors, 3D printing is rapidly becoming an important contemporary tool for achieving these goals. Supported by the widely available selection of affordable desktop 3D printers and diverse printing options, 3D printing is becoming a standard tool for developing low-cost immunosensors that can also be used to make final commercial products. In the last few years, 3D printing platforms have been used to produce complex sensor devices with high resolution, tailored towards researchers’ and clinicians’ needs and limited only by their imagination. Unlike traditional subtractive manufacturing, 3D printing, also known as additive manufacturing, has drastically reduced the time of sensor and sensor array development while offering excellent sensitivity at a fraction of the cost of conventional technologies such as photolithography. In this review, we offer a comprehensive description of 3D printing techniques commonly used to develop immunosensors, arrays, and microfluidic arrays. In addition, recent applications utilizing 3D printing in immunosensors integrated with different signal transduction strategies are described. These applications include electrochemical, chemiluminescent (CL), and electrochemiluminescent (ECL) 3D-printed immunosensors. Finally, we discuss current challenges and limitations associated with available 3D printing technology and future directions of this field.

scholarly journals snoRNAs Offer Novel Insight and Promising Perspectives for Lung Cancer Understanding and Management

Cells ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 541 ◽  
Author(s):  
Nour-El-Houda Mourksi ◽  
Chloé Morin ◽  
Tanguy Fenouil ◽  
Jean-Jacques Diaz ◽  
Virginie Marcel
Keyword(s):  
Lung Cancer ◽  
Cancer Biology ◽  
Biological Fluids ◽  
Diagnostic Tools ◽  
Cellular Functions ◽  
Non Invasive ◽  
Tumorigenesis And Progression ◽  
The 1960S ◽  
Definition Of ◽  
Nucleolar Rnas

Small nucleolar RNAs (snoRNAs) are non-coding RNAs localized in the nucleolus, where they participate in the cleavage and chemical modification of ribosomal RNAs. Their biogenesis and molecular functions have been extensively studied since their identification in the 1960s. However, their role in cancer has only recently started to emerge. In lung cancer, efforts to profile snoRNA expression have enabled the definition of snoRNA-related signatures, not only in tissues but also in biological fluids, exposing these small RNAs as potential non-invasive biomarkers. Moreover, snoRNAs appear to be essential actors of lung cancer onset and dissemination. They affect diverse cellular functions, from regulation of the cell proliferation/death balance to promotion of cancer cell plasticity. snoRNAs display both oncogenic and tumor suppressive activities that are pivotal in lung cancer tumorigenesis and progression. Altogether, we review how further insight into snoRNAs may improve our understanding of basic lung cancer biology and the development of innovative diagnostic tools and therapies.

scholarly journals Early Stage Detection of Crack in Glasses by Hybrid CNN Transformation Approach

2021 ◽  
Vol 3 (4) ◽  
pp. 353-364
Author(s):  
R. Kanthavel
Keyword(s):  
Early Detection ◽  
Crack Detection ◽  
Early Stage ◽  
Cost Effective ◽  
Detection Algorithm ◽  
Detection Methods ◽  
Research Article ◽  
Effective Manner ◽  
Main Fracture ◽  
Fracture Identification

Recently, glass crack detection methods have been emerging in Artificial intelligence programming. The early detection of the crack in glass could save many lives. Glass fractures can be detected automatically using machine vision. However, this has not been extensively researched. As a result, a detection algorithm is a benefit to study the mechanics of glass cracking. To test the algorithm, benchmark data are used and analysed. According to the first findings, the algorithm is capable of figuring out the screen more or less correctly and identifying the main fracture structures with sufficient efficiency required for majority of the applications. This research article has addressed the early detection of glass cracks by using edge detection, which delivers excellent accuracy in fracture identification. Following the pre-processing stage, the CNN technique extracts additional characteristics from the input pictures that have been provided due to dense feature extraction. The "Adam" optimizer is used to update the bias weights of networks in a cost-effective manner. Early identification is achievable with high accuracy metrics when using these approaches, as shown in the findings and discussion part of this paper.

Cost-effectiveness of robot-assisted lobectomy compared with VATS lobectomy for early-stage lung cancer in the National Health Insurance Program of Korea.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. e16534-e16534
Author(s):  
Hyun-Sung Lee ◽  
Hee-Jin Jang ◽  
Seong Yong Park ◽  
Jungnam Joo ◽  
Jae Ill Zo
Keyword(s):  
Lung Cancer ◽  
Adverse Events ◽  
Early Stage ◽  
Operation Time ◽  
Cost Effective ◽  
Robot Assisted ◽  
Vats Lobectomy ◽  
Early Stage Lung Cancer ◽  
Insurance Program ◽  
Stage Lung Cancer

e16534 Background: Robotic surgery has proven to be one of the most effective cutting-edge technologies for successful minimally invasive surgery. This study aimed to evaluate the cost-effectiveness of robot-assisted lobectomy (RAL) for the treatment of early stage lung cancer with video-assisted thoracic surgery (VATS) lobectomy. Methods: From February 2009 to April 2011, one hundred twenty patients underwent RAL for clinical stage I or II non-small cell lung cancer. The consecutive 100 patients who underwent RAL were compared with 100 patients who underwent VATS lobectomy during the similar period under intent-to-treat analysis. Clinicopathologic characteristics and surgical outcomes were analyzed. Adverse events were defined as operative morbidities, mortality and conversion to open thoracotomy. The adverse events were adjusted by NCI-CTCAE 3.0 grade. Incremental cost-effective ratio (ICER) was defined as difference of total cost divided by difference of adjusted adverse events. Results: Tumor size was slightly larger in RAL group with 3.2cm in mean size of tumor. RAL needed longer operation time than VATS group. However, the console time during operation was similar with operation time in VATS lobectomy. The median length of postoperative stay was significantly shorter after robotic surgery than VATS. Operative morbidities developed in 9 patients in RAL and 21 in VATS (p=0.028). Conversions to thoracotomy were happened in 2 cases in RAL and 7 cases in VATS (p=0.170). The total hospital costs were higher in RAL than those in VATS ($14,186 vs. $11,509, p<0.001). ICER between RAL and VATS was $16,111 (80% CI; $9,190~$33,860) and NNT (numbers needed to treat) was 6.01. If six patients are treated by RAL, one case of adverse operative events could be diminished and its additional cost is $16,111. Conclusions: Robot-assisted lobectomy for early stage lung cancer is safe as well as feasible, and it results in a satisfying postoperative outcome compared with those after VATS lobectomy. Despite higher total costs, RAL is highly cost-effective to treat early stage lung cancer in National Health Insurance Program of Korea.

scholarly journals Five Top Stories in Cytopathology

2013 ◽  
Vol 137 (7) ◽  
pp. 894-906 ◽  
Author(s):  
Andrew H. Fischer ◽  
Cynthia C. Benedict ◽  
Mojgan Amrikachi
Keyword(s):  
Cancer Biology ◽  
Imaging Techniques ◽  
Cost Effective ◽  
Active Role ◽  
Needle Aspiration ◽  
New Techniques ◽  
Health Care Outcomes ◽  
Fine Needle ◽  
Molecular Tests ◽  
Care Outcomes

Context.—Cytology relies heavily on morphology to make diagnoses, and morphologic criteria have not changed much in recent years. The field is being shaped predominantly by new techniques for imaging and for acquiring and processing samples, advances in molecular diagnosis and therapeutics, and regulatory issues. Objective.—To review the importance of classical morphology in the future of cytopathology, to identify areas in which cytology is expanding or contracting in its scope, and to identify factors that are shaping the field. Data Sources.—Literature review. Conclusions.—Five stories paint a picture in which classical cytomorphology will continue to have essential importance, both for diagnosis and for improving our understanding of cancer biology. New endoscopy and imaging techniques are replacing surgical biopsies with cytology samples. New molecularly targeted therapies offer a chance for cytology to play a major role, but they pose new challenges. New molecular tests have the potential to synergize with, but not replace, morphologic interpretation of thyroid fine-needle aspirations. Ultrasound-guided fine-needle aspiration performed by cytopathologists is opening a new field of “interventional cytopathology” with unique value. For the productive evolution of the field, it will be important for cytopathologists to play an active role in clinical trials that document the ability of cytology to achieve cost-effective health care outcomes.

scholarly journals Strategies for Functional Interrogation of Big Cancer Data Using Drosophila Cancer Models

2020 ◽  
Vol 21 (11) ◽  
pp. 3754 ◽  
Author(s):  
Erdem Bangi
Keyword(s):  
Big Data ◽  
Large Scale ◽  
Molecular Mechanisms ◽  
Rapid Development ◽  
Cost Effective ◽  
Experimental Models ◽  
Cancer Data ◽  
Functional Studies ◽  
Cancer Models ◽  
Effective Manner

Rapid development of high throughput genome analysis technologies accompanied by significant reduction in costs has led to the accumulation of an incredible amount of data during the last decade. The emergence of big data has had a particularly significant impact in biomedical research by providing unprecedented, systems-level access to many disease states including cancer, and has created promising opportunities as well as new challenges. Arguably, the most significant challenge cancer research currently faces is finding effective ways to use big data to improve our understanding of molecular mechanisms underlying tumorigenesis and developing effective new therapies. Functional exploration of these datasets and testing predictions from computational approaches using experimental models to interrogate their biological relevance is a key step towards achieving this goal. Given the daunting scale and complexity of the big data available, experimental systems like Drosophila that allow large-scale functional studies and complex genetic manipulations in a rapid, cost-effective manner will be of particular importance for this purpose. Findings from these large-scale exploratory functional studies can then be used to formulate more specific hypotheses to be explored in mammalian models. Here, I will discuss several strategies for functional exploration of big cancer data using Drosophila cancer models.

scholarly journals Harnessing CRISPR-Cas to Combat COVID-19: From Diagnostics to Therapeutics

Life ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 1210
Author(s):  
Kok Gan Chan ◽  
Geik Yong Ang ◽  
Choo Yee Yu ◽  
Chan Yean Yean
Keyword(s):  
Nucleic Acid ◽  
Point Of Care ◽  
Antiviral Agent ◽  
Cost Effective ◽  
Rapid Identification ◽  
Diagnostic Tools ◽  
Nucleic Acid Detection ◽  
Molecular Tests ◽  
Skilled Personnel ◽  
Global Threat

The coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), remains a global threat with an ever-increasing death toll even after a year on. Hence, the rapid identification of infected individuals with diagnostic tests continues to be crucial in the on-going effort to combat the spread of COVID-19. Viral nucleic acid detection via real-time reverse transcription polymerase chain reaction (rRT-PCR) or sequencing is regarded as the gold standard for COVID-19 diagnosis, but these technically intricate molecular tests are limited to centralized laboratories due to the highly specialized instrument and skilled personnel requirements. Based on the current development in the field of diagnostics, the programmable clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated proteins (Cas) system appears to be a promising technology that can be further explored to create rapid, cost-effective, sensitive, and specific diagnostic tools for both laboratory and point-of-care (POC) testing. Other than diagnostics, the potential application of the CRISPR–Cas system as an antiviral agent has also been gaining attention. In this review, we highlight the recent advances in CRISPR–Cas-based nucleic acid detection strategies and the application of CRISPR–Cas as a potential antiviral agent in the context of COVID-19.

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