Detection of ovarian cancer using plasma cell-free DNA methylomes

In general, the various medical systems currently available provide insights into changes in the tumor genome of patients with tumor sequencing. Most of the tumor DNA sequencing can also be referred to as genetic specification or genetic testing. The sequence results help clinical decision-making to develop a personalized cancer treatment plan based on the molecular characteristics of the tumor rather than a one-size-fits-all treatment approach. The tumor sequencing also plays a major role in cancer research. In this paper, an improved method based on machine learning was proposed to analyze the sequencing and tumor sequencing patterns of the human gene. This proposed method analyzes the circulatory problems of patients with different tumor types for analysis in the public domain. It also constantly monitors large data sets of cancer or tumor genetic sequences to calculate tumor size and location. This allows the doctor to get an accurate report on the type of tumor and the problems it can cause to the patient. The Analysis of these datasets of cancer tumor gene sequences reveals that the genetic makeup of each patient is different and that no two cancers are the same.

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“…Antioxidants have the power to reduce its severity. That is why they are told to eat nutritious natural vegetables and fruits [21].…”

Section: Introductionmentioning

confidence: 99%

deep DNA machine learning model to classify the tumor genome of patients with tumor sequencing

Logeshwaran¹,

Adhikari

Joshi³

et al. 2022

ijhs

121

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“…We also analyzed whether miR-139-5p and miR-451a in early patients have similar diagnostic values in late patients. We found that the early model had weak diagnostic ability for patients with late patients, 29 indicating that early markers can be roughly presented in each stage of LUSC. However, this result confirms that early-stage markers can generally present the molecular characteristics of LUSC in all stages.…”

Section: Dovepressmentioning

confidence: 78%

miR-139-5p and miR-451a as a Diagnostic Biomarker in LUSC

Gao¹,

Li²,

Song³

et al. 2023

PGPM

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Background Lung squamous cell carcinoma (LUSC) is a type of lung cancer that originates from segmental or subsegmental bronchial mucosa. There is evidence that miRNA plays an important role in the occurrence and progression of tumors. Methods In this study, plasma samples of patients with early LUSC and healthy volunteers were subjected to miRNA sequencing, and the levels of differentially expressed miRNAs (DEMs) in LUSC tissues were analyzed using R language. Cox regression and Kaplan–Meier (K-M) survival curve analyses were performed to determine the relationship between DEMs and prognosis in LUSC, and PCR method was verified for the plasma expression level of DEMs in patients with LUSC. The levels of CYFRA21-1 and SCC-Ag in plasma were measured, and area under curve (AUC) was used to evaluate the diagnostic value of the DEMs. Results A total of 21 DEMs were screened out by sequencing. The expression levels of DEMs in tissue samples in the TCGA database were analyzed, and four DEMs with consistent expression levels were further screened from plasma and tissue samples. Regression analysis and K-M curve were performed to select two DEMs (miR-139-5p, miR-451a) that were correlated with the prognosis. PCR verification results showed that the levels of miR-451a and miR-139-5p were low in patients, and the level of miR-139-5p in late stages III & IV with the patients of LUSC was higher than that in stages I & II. The AUC values of the four indicators (SCC-Ag, CYFRA21-1, miR-451a and miR-139-5p) in the diagnosis of LUSC, early and late cases were 0.884, 0.935 and 0.778, respectively. Conclusion The detection of miR-139-5p and miR-451a levels in plasma has a certain potential in the non-invasive diagnosis, especially in patients with early stages of LUSC.

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“…The use of this approach is spreading in cancer studies (4)(5)(6)(7)(8). Direct detection of altered DNA methylation patterns under pathological conditions, regardless of cell or tissue contribution, has been thoroughly examined to determine its value as a strategy for searching for biomarkers (9)(10)(11)(12)(13)(14).…”

Section: Introductionmentioning

confidence: 99%