scholarly journals A liquid biopsy gene panel for pancreatic cancer detection

2017 ◽  
Vol 28 ◽  
pp. x9
Author(s):  
K. Kato ◽  
K. Ohkawa ◽  
R. Takada ◽  
H. Uehara ◽  
Y. Kukita ◽  
...  
2014 ◽  
Vol 20 (1) ◽  
pp. 73-80 ◽  
Author(s):  
Osama Alian ◽  
Philip Philip ◽  
Fazlul Sarkar ◽  
Asfar Azmi

Genes ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 507
Author(s):  
Bernd Timo Hermann ◽  
Sebastian Pfeil ◽  
Nicole Groenke ◽  
Samuel Schaible ◽  
Robert Kunze ◽  
...  

Detection of genetic variants in clinically relevant genomic hot-spot regions has become a promising application of next-generation sequencing technology in precision oncology. Effective personalized diagnostics requires the detection of variants with often very low frequencies. This can be achieved by targeted, short-read sequencing that provides high sequencing depths. However, rare genetic variants can contain crucial information for early cancer detection and subsequent treatment success, an inevitable level of background noise usually limits the accuracy of low frequency variant calling assays. To address this challenge, we developed DEEPGENTM, a variant calling assay intended for the detection of low frequency variants within liquid biopsy samples. We processed reference samples with validated mutations of known frequencies (0%–0.5%) to determine DEEPGENTM’s performance and minimal input requirements. Our findings confirm DEEPGENTM’s effectiveness in discriminating between signal and noise down to 0.09% variant allele frequency and an LOD(90) at 0.18%. A superior sensitivity was also confirmed by orthogonal comparison to a commercially available liquid biopsy-based assay for cancer detection.


Cancers ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1986
Author(s):  
Victoria Heredia-Soto ◽  
Nuria Rodríguez-Salas ◽  
Jaime Feliu

Pancreatic ductal adenocarcinoma (PDAC) exhibits the poorest prognosis of all solid tumors, with a 5-year survival of less than 10%. To improve the prognosis, it is necessary to advance in the development of tools that help us in the early diagnosis, treatment selection, disease monitoring, evaluation of the response and prognosis. Liquid biopsy (LB), in its different modalities, represents a particularly interesting tool for these purposes, since it is a minimally invasive and risk-free procedure that can detect both the presence of genetic material from the tumor and circulating tumor cells (CTCs) in the blood and therefore distantly reflect the global status of the disease. In this work we review the current status of the main LB modalities (ctDNA, exosomes, CTCs and cfRNAs) for detecting and monitoring PDAC.


Life ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 638
Author(s):  
Linjing Liu ◽  
Xingjian Chen ◽  
Olutomilayo Olayemi Petinrin ◽  
Weitong Zhang ◽  
Saifur Rahaman ◽  
...  

With the advances of liquid biopsy technology, there is increasing evidence that body fluid such as blood, urine, and saliva could harbor the potential biomarkers associated with tumor origin. Traditional correlation analysis methods are no longer sufficient to capture the high-resolution complex relationships between biomarkers and cancer subtype heterogeneity. To address the challenge, researchers proposed machine learning techniques with liquid biopsy data to explore the essence of tumor origin together. In this survey, we review the machine learning protocols and provide corresponding code demos for the approaches mentioned. We discuss algorithmic principles and frameworks extensively developed to reveal cancer mechanisms and consider the future prospects in biomarker exploration and cancer diagnostics.


2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 3048-3048
Author(s):  
Juan Pablo Hinestrosa ◽  
Razelle Kurzrock ◽  
Jean Lewis ◽  
Nick Schork ◽  
Ashish M. Kamat ◽  
...  

3048 Background: Many cancers are lethal because they present with metastatic disease. Because localized/resectable tumors produce vague symptoms, diagnosis is delayed. In pancreatic cancer, only ̃10% of patients survive five years, and it will soon become the second leading cause of cancer-related deaths in the USA. For patients with metastatic disease, the 2- and 5-year survival is < 10% and ̃3%, respectively. For the few patients with local disease, 5-year survival is ̃40%. Many other cancers have comparable differences between early- and late-stage disease. It is apparent a diagnostic assay for early-stage cancers would transform the field by minimizing the need for aggressive surgeries and other harsh interventions, and by its potential to increase survival. Identifying cancer-specific aberrations in blood-based “liquid” biopsies offers a prospect for a non-invasive cancer detection tool. In the bloodstream, there are extracellular vesicles (EVs) with cargoes including membrane and cytosolic proteins, as well as RNA and lipids derived from their parent cells. Methods: We used an alternating current electrokinetics (ACE) microarray to isolate EVs from the plasma of stage I and II bladder (N = 48), ovarian (N = 42), and pancreatic cancer patients (N = 44), and healthy volunteers (N = 110). EVs were analyzed using multiplex protein immunoassays for 54 cancer-related proteins. EV protein expression patterns were analyzed using stepwise logistic regression followed by a split between training and test sets (67%/33% respectively). This process enabled biomarker selection and generation of a classifier to discriminate between cancer and healthy donors. Results: The EV protein-based classifier had an overall area under curve (AUC) of 0.95 with a sensitivity of 71.2% (69.4% – 73.0%, at 95% confidence interval) at > 99% specificity. The classifier’s performance for the pancreatic cancer cohort was very strong, with overall sensitivity of 95.7% (94.6% – 96.9%, at 95% confidence interval) at > 99% specificity. Conclusions: EV-associated proteins may enable early cancer detection where surgical resection is most likely to improve outcomes. The classifier’s performance for the initial three cancers studied showed encouraging results. Future efforts will include examining additional cancer types and evaluating the classifier performance using samples from donors with related benign conditions with the aim of a pan-cancer early detection assay.


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