Early Diagnosis of Pancreatic Cancer: The Key for Survival

Gheorghe, Gina; Bungău, Simona; Ilie, Mădălina; Behl, Tapan; Vesa, Cosmin Mihai; Brisc, Ciprian; Bacalbaşa, Nicolae; Turi, Vladiana; Costache, Raluca; Diaconu, Camelia Cristina

doi:10.3390/diagnostics10110869

Cited by 56 publications

(45 citation statements)

References 105 publications

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“…At the moment there are two major types of blood data used in cancer diagnosis: genomic and proteomic. Genomic data can be epigenetic, circulating tumor DNA, MicroRNAs and stool-based tests [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence in Colorectal Cancer Diagnosis Using Clinical Data: Non-Invasive Approach

et al. 2021

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Colorectal cancer is the third most common and second most lethal tumor globally, causing 900,000 deaths annually. In this research, a computer aided diagnosis system was designed that detects colorectal cancer, using an innovative dataset composing of both numeric (blood and urine analysis) and qualitative data (living environment of the patient, tumor position, T, N, M, Dukes classification, associated pathology, technical approach, complications, incidents, ultrasonography-dimensions as well as localization). The intelligent computer aided colorectal cancer diagnosis system was designed using different machine learning techniques, such as classification and shallow and deep neural networks. The maximum accuracy obtained from solving the binary classification problem with traditional machine learning algorithms was 77.8%. However, the regression problem solved with deep neural networks yielded with significantly better performance in terms of mean squared error minimization, reaching the value of 0.0000529.

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Section: Introductionmentioning

confidence: 99%

Artificial Intelligence in Colorectal Cancer Diagnosis Using Clinical Data: Non-Invasive Approach

et al. 2021

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“…In the case of their development in the same patient, should they be considered as two independent diseases, or one of them is a natural consequence of the other? Most studies of pancreatic exocrine function in diabetic patients have reported mild and moderate exocrine pancreatic insufficiency, which has been expressed in a relative decrease of bicarbonate and enzyme production, and severe pancreatic exocrine insufficiency with steatorrhea is relatively rare [35][36][37] . According to Sirchak et al, in patients with T2DM, CP is formed on the background of biliary pathology, while the functional capacity of the pancreas is greater than in T1DM 38 .…”

Section: Discussionmentioning

confidence: 99%

Does comorbid obesity or chronic pancreatitis influence the choice and effectiveness of glucose-lowering therapy in type 2 diabetic patients?

Hevko

Krynytska

Danylevych

et al. 2021

Arch Balk Med Union

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Obésité comorbide ou pancréatite chronique, influencent-t-elles le choix et l'efficacité de la thérapie de réduction du glucose chez les patients avec diabète de type 2 ?Introduction. La complexité de l'interaction entre le diabète sucré de type 2 (DT2), les comorbidités et les complications émergentes nécessite une approche clinique qui gère le risque tout en maintenant les objectifs thérapeutiques indiqués. L'objectif de l'étude. Le but de cette étude était d'analyser la fréquence et l'efficacité des traitements hypoglycémiants mono-et combinés chez les patients diabétiques de type 2 souffrant d'obésité et de pancréatite chronique (PC). Matériel et méthodes. L'étude rétrospective a analysé 579 dossiers médicaux des patients atteints de DT2: groupe 1 -patients de poids corporel normal et sans

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“…Despite advances made in the last few decades in understanding PDAC biology and developing new targeted therapies [3][4][5][6], PDAC patients continue to have a dismal prognosis, with a 5-year survival rate of less than 20% [7,8]. Tumor stage is the main prognostic determinant, early-stage tumors being associated with a longer survival than that of locally advanced or metastatic tumors [9].…”

Section: Introductionmentioning

confidence: 99%

“…In the PDAC setting, several studies in the literature have evaluated different miRNAs panels as diagnostic and/or prognostic tools by analyzing tissue expression [26,27], serum levels [24], blood levels [28] and ascitic fluid levels [25]. New biomarkers of PDAC should aid early diagnosis and, as prognostic indices in early-stage cases, should be helpful in distinguishing between patients with long or short life expectancies, thus allowing a more tailored therapeutic approach [7,29].…”

Section: Introductionmentioning

confidence: 99%

Serum miRNA Profiling for Early PDAC Diagnosis and Prognosis: A Retrospective Study

et al. 2021

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Background: Tumor stage predicts pancreatic cancer (PDAC) prognosis, but prolonged and short survivals have been described in patients with early-stage tumors. Circulating microRNA (miRNA) are an emerging class of suitable biomarkers for PDAC prognosis. Our aim was to identify whether serum miRNA signatures predict survival of early-stage PDAC. Methods: Serum RNA from archival 15 stage I-III PDAC patients and 4 controls was used for miRNAs expression profile (Agilent microarrays). PDAC patients with comparable age, gender, diabetes, jaundice and surgery were classified according to survival: less than 14 months (7/15 pts, group A) and more than 22 months (8/15 pts, group B). Bioinformatic data analysis was performed by two-class Significance Analysis of Microarray (SAM) algorithm. Binary logistic regression analyses considering PDAC diagnosis and outcome as dependent variables, and ROC analyses were also performed. Results: 2549 human miRNAs were screened out. At SAM, 76 differentially expressed miRNAs were found among controls and PDAC (FDR = 0.4%), the large majority (50/76, 66%) of them being downregulated in PDAC with respect to controls. Six miRNAs were independently correlated with early PDAC, and among these, hsa-miR-6821-5p was associated with the best ROC curve area in distinguishing controls from early PDAC. Among the 71 miRNAs differentially expressed between groups A and B, the most significant were hsa-miR-3135b expressed in group A only, hsa-miR-6126 and hsa-miR-486-5p expressed in group B only. Eight miRNAs were correlated with the presence of lymph-node metastases; among these, hsa-miR-4669 is of potential interest. hsa-miR-4516, increased in PDAC and found as an independent predictor of survival, has among its putative targets a series of gens involved in key pathways of cancer progression and dissemination, such as Wnt and p53 signalling pathways. Conclusions: A series of serum miRNAs was identified as potentially useful for the early diagnosis of PDAC, and for establishing a prognosis.

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Early Diagnosis of Pancreatic Cancer: The Key for Survival

Cited by 56 publications

References 105 publications

Artificial Intelligence in Colorectal Cancer Diagnosis Using Clinical Data: Non-Invasive Approach

Artificial Intelligence in Colorectal Cancer Diagnosis Using Clinical Data: Non-Invasive Approach

Does comorbid obesity or chronic pancreatitis influence the choice and effectiveness of glucose-lowering therapy in type 2 diabetic patients?

Serum miRNA Profiling for Early PDAC Diagnosis and Prognosis: A Retrospective Study

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