Prediction of blood-based biomarkers and subsequent design of bisulfite PCR-LDR-qPCR assay for breast cancer detection

Pan-cancer landscape of abnormal ctDNA methylation across human tumors

BACKGROUND

The aim of this paper is to explore the correlation between circulating tumor DNA (ctDNA) methylation and mutations and its value in clinical early cancer screening.

METHODS

We performed target region methylation sequencing and genome sequencing on plasma samples. Methylation models to distinguish cancer from healthy individuals have been developed using hypermethylated genes in tumors and validated in training set and prediction set.

RESULTS

We found that patients with cancer had higher levels of ctDNA methylation compared to healthy individuals. The level of ctDNA methylation in cell cycle, p53, Notch pathway in pan-cancer was significantly correlated with the number of mutations, and mutation frequency. Methylation burden in some tumors was significantly correlated with tumor mutational burden (TMB), microsatellite instability (MSI) and PD-L1. The ctDNA methylation differences in cancer patients were mainly concentrated in the Herpes simplex virus 1 infection pathway. The area under curve (AUC) of the training and prediction sets of the methylation model distinguishing cancer from healthy individuals were 0.93 and 0.92, respectively.

CONCLUSION

Our study provides a landscape of methylation levels of important pathways in pan-cancer. ctDNA methylation significantly correlates with mutation type, frequency and number, providing a reference for clinical application of ctDNA methylation in early cancer screening.

Breast cancer diagnosis in an early stage using novel deep learning with hybrid optimization technique

Breast cancer is one of the primary causes of death that is occurred in females around the world. So, the recognition and categorization of initial phase breast cancer are necessary to help the patients to have suitable action. However, mammography images provide very low sensitivity and efficiency while detecting breast cancer. Moreover, Magnetic Resonance Imaging (MRI) provides high sensitivity than mammography for predicting breast cancer. In this research, a novel Back Propagation Boosting Recurrent Wienmed model (BPBRW) with Hybrid Krill Herd African Buffalo Optimization (HKH-ABO) mechanism is developed for detecting breast cancer in an earlier stage using breast MRI images. Initially, the MRI breast images are trained to the system, and an innovative Wienmed filter is established for preprocessing the MRI noisy image content. Moreover, the projected BPBRW with HKH-ABO mechanism categorizes the breast cancer tumor as benign and malignant. Additionally, this model is simulated using Python, and the performance of the current research work is evaluated with prevailing works. Hence, the comparative graph shows that the current research model produces improved accuracy of 99.6% with a 0.12% lower error rate.

Advances of Exosomal miRNAs in Breast Cancer Progression and Diagnosis

Breast cancer is one of the most commonly diagnosed malignancies and the leading cause of cancer death in women worldwide. Although many factors associated with breast cancer have been identified, the definite etiology of breast cancer is still unclear. In addition, early diagnosis of breast cancer remains challenging. Exosomes are membrane-bound nanovesicles secreted by most types of cells and contain a series of biologically important molecules, such as lipids, proteins, and miRNAs, etc. Emerging evidence shows that exosomes can affect the status of cells by transmitting substances and messages among cells and are involved in various physiological and pathological processes. In breast cancer, exosomes play a significant role in breast tumorigenesis and progression through transfer miRNAs which can be potential biomarkers for early diagnosis of breast cancer. This review discusses the potential utility of exosomal miRNAs in breast cancer progression such as tumorigenesis, metastasis, immune regulation and drug resistance, and further in breast cancer diagnosis.

Automatic Detection of the Circulating Cell-Free Methylated DNA Pattern of GCM2, ITPRIPL1 and CCDC181 for Detection of Early Breast Cancer and Surgical Treatment Response

The early detection of cancer can reduce cancer-related mortality. There is no clinically useful noninvasive biomarker for early detection of breast cancer. The aim of this study was to develop accurate and precise early detection biomarkers and a dynamic monitoring system following treatment. We analyzed a genome-wide methylation array in Taiwanese and The Cancer Genome Atlas (TCGA) breast cancer (BC) patients. Most breast cancer-specific circulating methylated CCDC181, GCM2 and ITPRIPL1 biomarkers were found in the plasma. An automatic analysis process of methylated ccfDNA was established. A combined analysis of CCDC181, GCM2 and ITPRIPL1 (CGIm) was performed in R using Recursive Partitioning and Regression Trees to establish a new prediction model. Combined analysis of CCDC181, GCM2 and ITPRIPL1 (CGIm) was found to have a sensitivity level of 97% and an area under the curve (AUC) of 0.955 in the training set, and a sensitivity level of 100% and an AUC of 0.961 in the test set. The circulating methylated CCDC181, GCM2 and ITPRIPL1 was also significantly decreased after surgery (all p < 0.001). The aberrant methylation patterns of the CCDC181, GCM2 and ITPRIPL1 genes means that they are potential biomarkers for the detection of early BC and can be combined with breast imaging data to achieve higher accuracy, sensitivity and specificity, facilitating breast cancer detection. They may also be applied to monitor the surgical treatment response.

Cell-Free DNA-Methylation-Based Methods and Applications in Oncology

Liquid biopsy based on cell-free DNA (cfDNA) enables non-invasive dynamic assessment of disease status in patients with cancer, both in the early and advanced settings. The analysis of DNA-methylation (DNAm) from cfDNA samples holds great promise due to the intrinsic characteristics of DNAm being more prevalent, pervasive, and cell- and tumor-type specific than genomics, for which established cfDNA assays already exist. Herein, we report on recent advances on experimental strategies for the analysis of DNAm in cfDNA samples. We describe the main steps of DNAm-based analysis workflows, including pre-analytics of cfDNA samples, DNA treatment, assays for DNAm evaluation, and methods for data analysis. We report on protocols, biomolecular techniques, and computational strategies enabling DNAm evaluation in the context of cfDNA analysis, along with practical considerations on input sample requirements and costs. We provide an overview on existing studies exploiting cell-free DNAm biomarkers for the detection and monitoring of cancer in early and advanced settings, for the evaluation of drug resistance, and for the identification of the cell-of-origin of tumors. Finally, we report on DNAm-based tests approved for clinical use and summarize their performance in the context of liquid biopsy.

The future of cancer screening after COVID-19 may be at home

LAY SUMMARY

During the coronavirus disease 2019 (COVID-19) pandemic, cancer screening decreased precipitously; home screening for colorectal cancer diminished less than that for colonoscopy and breast and cervical cancer screening. The authors have highlighted approaches for home cancer screening in addition to telemedicine.

Precision Medicine for Breast Cancer Utilizing Circulating Tumor DNA: It Is in the Blood

OPINION STATEMENT

Liquid biopsy using blood components to assess circulating tumor DNA (ctDNA) is rapidly becoming a new standard-of-care technology in many tumor types, including breast cancer, due to the potential to provide predictive and prognostic information. The minimally invasive and repeatable nature of plasma based mutational testing is appealing for patients and facilitates enhanced disease monitoring. It is important for the clinician to understand the benefits and limitations of this emerging assay and the potential applications in breast cancer. Multiple technologies have been employed to assess breast cancer ctDNA with high sensitivity and specificity leading to assays that have been useful in research trials and are entering widespread clinical application. ctDNA analysis of breast cancer is of clinical utility today in selecting targeted therapy for advanced breast cancer, most notably by assessing PIK3CA mutations in hormone receptor-positive, HER2-negative disease. It will be employed in the near future in a variety of clinical settings including early detection of primary breast cancer, minimal residual disease after initial therapy, and use in advanced breast cancer for prognosis, early identification of non-response, and monitoring genomic markers of resistance.

Application of Multiplex Bisulfite PCR-Ligase Detection Reaction-Real-Time Quantitative PCR Assay in Interrogating Bioinformatically Identified, Blood-Based Methylation Markers for Colorectal Cancer

The analysis of CpG methylation in circulating tumor DNA fragments has emerged as a promising approach for the noninvasive early detection of solid tumors, including colorectal cancer (CRC). The most commonly employed assay involves bisulfite conversion of circulating tumor DNA, followed by targeted PCR, then real-time quantitative PCR (alias methylation-specific PCR). This report demonstrates the ability of a multiplex bisulfite PCR-ligase detection reaction-real-time quantitative PCR assay to detect seven methylated CpG markers (CRC or colon specific), in both simulated (approximately 30 copies of fragmented CRC cell line DNA mixed with approximately 3000 copies of fragmented peripheral blood DNA) and CRC patient-derived cell-free DNAs. This scalable assay is designed for multiplexing and incorporates steps for improved sensitivity and specificity, including the enrichment of methylated CpG fragments, ligase detection reaction, the incorporation of ribose bases in primers, and use of uracil DNA glycosylase. Six of the seven CpG markers (located in promoter regions of PPP1R16B, KCNA3, CLIP4, GDF6, SEPT9, and GSG1L) were identified through integrated analyses of genome-wide methylation data sets for 31 different types of cancer. These markers were mapped to CpG sites at the promoter region of VIM; VIM and SEPT9 are established epigenetic markers of CRC. Additional bioinformatics analyses show that the methylation at these CpG sites negatively correlates with the transcription of their corresponding genes.

Single-molecule detection of cancer mutations using a novel PCR-LDR-qPCR assay

Detection of low-abundance mutations in cell-free DNA is being used to identify early cancer and early cancer recurrence. Here, we report a new PCR-LDR-qPCR assay capable of detecting point mutations at a single-molecule resolution in the presence of an excess of wild-type DNA. Major features of the assay include selective amplification and detection of mutant DNA employing multiple nested primer-binding regions as well as wild-type sequence blocking oligonucleotides, prevention of carryover contamination, spatial sample dilution, and detection of multiple mutations in the same position. Our method was tested to interrogate the following common cancer somatic mutations: BRAF:c.1799T>A (p.Val600Glu), TP53:c.743G>A (p.Arg248Gln), KRAS:c.35G>C (p.Gly12Ala), KRAS:c.35G>T (p.Gly12Val), KRAS:c.35G>A (p.Gly12Asp), KRAS:c.34G>T (p.Gly12Cys), and KRAS:c.34G>A (p.Gly12Ser). The single-well version of the assay detected 2-5 copies of these mutations, when diluted with 10,000 genome equivalents (GE) of wild-type human genomic DNA (hgDNA) from buffy coat. A 12-well (pixel) version of the assay was capable of single-molecule detection of the aforementioned mutations at TP53, BRAF, and KRAS (specifically p.Gly12Val and p.Gly12Cys), mixed with 1,000-2,250 GE of wild-type hgDNA from plasma or buffy coat. The assay described herein is highly sensitive, specific, and robust, and potentially useful in liquid biopsies.