Determination of 5-methyl-cytosine and cytosine in tumor DNA of cancer patients

2005 ◽  
Vol 26 (6) ◽  
pp. 1057-1062 ◽  
Author(s):  
Karina Sandoval Guerrero ◽  
Alma Revilla Vázquez ◽  
Blanca Segura-Pacheco ◽  
Alfonso Dueñas-Gonzalez
Keyword(s):  
Cancer Patients ◽  
Methyl Cytosine ◽  
Tumor Dna

DETERMINATION OF P53 GENE CODON 72 POLYMORPHISMS IN PATIENTS WITH GASTRIC CANCER

2013 ◽  
pp. 11-17
Author(s):  
Thi Tuy Ha Nguyen ◽  
Thi Minh Thi Ha
Keyword(s):  
Gastric Cancer ◽  
Cancer Patients ◽  
P53 Gene ◽  
Diffuse Gastric Cancer ◽  
Codon 72 ◽  
Cancer Group ◽  
Pcr Rflp ◽  
Gastric Cancer Patients ◽  
The Relationship

Background: The role of p53 gene in the gastric cancer is still controversial. This study is aimed at determining the rate of the p53 gene codon 72 polymorphisms in gastric cancer patients and evaluating the relationship between these polymorphisms and endoscopic and histopathological features of gastric cancer. Patients and methods: Sixty eight patients with gastric cancer (cases) and one hundred and thirty six patients without gastric cancer (controls) were enrolled. p53 gene codon 72 polymorphisms were determined by PCR-RFLP technique with DNA extracted from samples of gastric tissue. Results: In the group of gastric cancer, Arginine/Argnine, Arginine/Proline and Proline/Proline genotypes were found in 29.4%, 42.7% and 27.9%, respectively. The differences of rates were not statistically significant between cases and controls (p > 0,05). In males, the Proline/Proline genotype was found in 38.1% in patients with gastric cancer and more frequent in patients without gastric cancer (15.7%, p = 0,01). An analysis of ROC curve showed that the cut-off was the age of 52 in the Proline/Proline genotype, but it was 65 years old in the Arginine/Proline genotype. The Proline/Proline genotype was found in 41.9% in Borrmann III/IV gastric cancer, this rate was higher than Borrmann I/II gastric cancer (16.2%, p = 0.037) and also higher than controls (18.4%, p = 0,01). The rate of Proline/Proline genotype was 41.7% in the diffuse gastric cancer, it was higher than in controls (p = 0,023). Conclusion: No significative difference of rate was found in genotypes between gastric cancer group and controls. However, there was the relationship between Proline/Proline genotype and gastric cancer in males, Borrmann types of gastric cancer, the diffuse gastric cancer. Key words: polymorphism, codon 72, p53 gene, PCR - RFLP, gastric cancer.

ctDNA as a prognostic factor in operable colon cancer patients: a systematic review and meta-analysis

2020 ◽  
Author(s):  
Emre Yekedüz ◽  
Elif Berna Köksoy ◽  
Hakan Akbulut ◽  
Yüksel Ürün ◽  
Güngör Utkan
Keyword(s):  
Colon Cancer ◽  
Prognostic Factor ◽  
Cancer Patients ◽  
Meta Analysis ◽  
Circulating Tumor Dna ◽  
Random Effects Model ◽  
Inverse Variance ◽  
Increased Risk ◽  
Significant Step ◽  
Tumor Dna

Aim: Using circulating tumor DNA (ctDNA) instead of historical clinicopathological factors to select patients for adjuvant chemotherapy (ACT) may reduce inappropriate therapy. Material & methods: MEDLINE was searched on March 31, 2020. Studies, including data related to the prognostic value of ctDNA in the colon cancer patients after surgery and after ACT, were included. The generic inverse-variance method with a random-effects model was used for meta-analysis. Results: Four studies were included for this meta-analysis. ctDNA-positive colon cancer patients after surgery and ACT had a significantly increased risk of recurrence compared with ctDNA-negative patients. Conclusions: ctDNA is an independent prognostic factor, and this meta-analysis is a significant step for using ctDNA instead of historical prognostic factors in the adjuvant setting.

scholarly journals An SPRi Biosensor for Determination of the Ovarian Cancer Marker HE4 in Human Plasma

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3567
Author(s):  
Beata Szymanska ◽  
Zenon Lukaszewski ◽  
Beata Zelazowska-Rutkowska ◽  
Kinga Hermanowicz-Szamatowicz ◽  
Ewa Gorodkiewicz
Keyword(s):  
Ovarian Cancer ◽  
Cancer Patients ◽  
Tumor Resection ◽  
Analytical Signal ◽  
Cancer Marker ◽  
Human Epididymis Protein 4 ◽  
Pearson Coefficient ◽  
Rabbit Polyclonal Antibody ◽  
Good Agreement

Human epididymis protein 4 (HE4) is an ovarian cancer marker. Various cut-off values of the marker in blood are recommended, depending on the method used for its determination. An alternative biosensor for HE4 determination in blood plasma has been developed. It consists of rabbit polyclonal antibody against HE4, covalently attached to a gold chip via cysteamine linker. The biosensor is used with the non-fluidic array SPRi technique. The linear range of the analytical signal response was found to be 2–120 pM, and the biosensor can be used for the determination of the HE4 marker in the plasma of both healthy subjects and ovarian cancer patients after suitable dilution with a PBS buffer. Precision (6–10%) and recovery (101.8–103.5%) were found to be acceptable, and the LOD was equal to 2 pM. The biosensor was validated by the parallel determination of a series of plasma samples from ovarian cancer patients using the Elecsys HE4 test and the developed biosensor, with a good agreement of the results (a Pearson coefficient of 0.989). An example of the diagnostic application of the developed biosensor is given—the influence of ovarian tumor resection on the level of HE4 in blood serum.

scholarly journals Small EVs-Associated DNA as Complementary Biomarker to Circulating Tumor DNA in Plasma of Metastatic Colorectal Cancer Patients

2021 ◽  
Vol 14 (2) ◽  
pp. 128
Author(s):  
Silvia Galbiati ◽  
Francesco Damin ◽  
Dario Brambilla ◽  
Lucia Ferraro ◽  
Nadia Soriani ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Metastatic Colorectal Cancer ◽  
Cancer Patients ◽  
Digital Pcr ◽  
Extracellular Vesicle ◽  
Circulating Tumor Dna ◽  
Mutation Status ◽  
Promising Practice ◽  
Colorectal Cancer Patients ◽  
Tumor Dna

It is widely accepted that assessing circular tumor DNA (ctDNA) in the plasma of cancer patients is a promising practice to evaluate somatic mutations from solid tumors noninvasively. Recently, it was reported that isolation of extracellular vesicles improves the detection of mutant DNA from plasma in metastatic patients; however, no consensus on the presence of dsDNA in exosomes has been reached yet. We analyzed small extracellular vesicle (sEV)-associated DNA of eleven metastatic colorectal cancer (mCRC) patients and compared the results obtained by microarray and droplet digital PCR (ddPCR) to those reported on the ctDNA fraction. We detected the same mutations found in tissue biopsies and ctDNA in all samples but, unexpectedly, in one sample, we found a KRAS mutation that was not identified either in ctDNA or tissue biopsy. Furthermore, to assess the exact location of sEV-associated DNA (outside or inside the vesicle), we treated with DNase I sEVs isolated with three different methodologies. We found that the DNA inside the vesicles is only a small fraction of that surrounding the vesicles. Its amount seems to correlate with the total amount of circulating tumor DNA. The results obtained in our experimental setting suggest that integrating ctDNA and sEV-associated DNA in mCRC patient management could provide a complete real-time assessment of the cancer mutation status.

scholarly journals The Origin of Tumor DNA in Urine of Urogenital Cancer Patients: Local Shedding and Transrenal Excretion

Cancers ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 535
Author(s):  
Anouk E. Hentschel ◽  
Rianne van den Helder ◽  
Nienke E. van Trommel ◽  
Annina P. van Splunter ◽  
Robert A. A. van Boerdonk ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Bladder Cancer ◽  
Cancer Patients ◽  
Liquid Biopsy ◽  
Bladder Tumor ◽  
Great Promise ◽  
Tumor Tissues ◽  
Catheter Urine ◽  
Tumor Dna ◽  
Urogenital Cancers

In urogenital cancers, urine as a liquid biopsy for non-invasive cancer detection holds great promise for future clinical application. Their anatomical position allows for the local shedding of tumor DNA, but recent data indicate that tumor DNA in urine might also result from transrenal excretion. This study aims to assess the origin of tumor-associated DNA in the urine of 5 bladder and 25 cervical cancer patients. Besides natural voided urine, paired urine samples were collected in which contact with the local tumor was circumvented to bypass local shedding. The latter concerned nephrostomy urine in bladder cancer patients, and catheter urine in cervical cancer patients. Methylation levels of GHSR, SST, and ZIC1 were determined using paired bladder tumor tissues and cervical scrapes as a reference. Urinary methylation levels were compared to natural voided urine of matched controls. To support methylation results, mutation analysis was performed in urine and tissue samples of bladder cancer patients. Increased methylation levels were not only found in natural voided urine from bladder and cervical cancer patients, but also in the corresponding nephrostomy and catheter urine. DNA mutations detected in bladder tumor tissues were also detectable in all paired natural voided urine as well as in a subset of nephrostomy urine. These results provide the first evidence that the suitability of urine as a liquid biopsy for urogenital cancers relies both on the local shedding of tumor cells and cell fragments, as well as the transrenal excretion of tumor DNA into the urine.

scholarly journals Deep Learning Based HPV Status Prediction for Oropharyngeal Cancer Patients

Cancers ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 786
Author(s):  
Daniel M. Lang ◽  
Jan C. Peeken ◽  
Stephanie E. Combs ◽  
Jan J. Wilkens ◽  
Stefan Bartzsch
Keyword(s):  
Deep Learning ◽  
Cancer Patients ◽  
Oropharyngeal Cancer ◽  
Characteristic Curve ◽  
Learning Models ◽  
Convolutional Network ◽  
Hpv Status ◽  
3D Information ◽  
External Test

Infection with the human papillomavirus (HPV) has been identified as a major risk factor for oropharyngeal cancer (OPC). HPV-related OPCs have been shown to be more radiosensitive and to have a reduced risk for cancer related death. Hence, the histological determination of HPV status of cancer patients depicts an essential diagnostic factor. We investigated the ability of deep learning models for imaging based HPV status detection. To overcome the problem of small medical datasets, we used a transfer learning approach. A 3D convolutional network pre-trained on sports video clips was fine-tuned, such that full 3D information in the CT images could be exploited. The video pre-trained model was able to differentiate HPV-positive from HPV-negative cases, with an area under the receiver operating characteristic curve (AUC) of 0.81 for an external test set. In comparison to a 3D convolutional neural network (CNN) trained from scratch and a 2D architecture pre-trained on ImageNet, the video pre-trained model performed best. Deep learning models are capable of CT image-based HPV status determination. Video based pre-training has the ability to improve training for 3D medical data, but further studies are needed for verification.

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