Detection of genomic alterations in breast cancer with circulating tumour DNA sequencing

m6Am sequesters PCF11 to suppress premature termination and drive neuroblastoma differentiation

N6,2'-O-dimethyladenosine (m6Am) is an abundant mRNA modification that impacts multiple diseases, but its function remains controversial because the m6Am reader is unknown. Using quantitative proteomics, we identified transcriptional terminator premature cleavage factor II (PCF11) as a m6Am-specific reader in human cells. Direct quantification of mature versus nascent RNAs reveals that m6Am does not regulate mRNA stability but promotes nascent transcription. Mechanistically, m6Am functions by sequestering PCF11 away from proximal RNA polymerase II (RNA Pol II). This suppresses PCF11 from dissociating RNA Pol II near transcription start sites, thereby promoting full-length transcription of m6Am-modified RNAs. m6Am's unique relationship with PCF11 means m6Am function is enhanced when PCF11 is reduced, which occurs during all-trans-retinoic-acid (ATRA)-induced neuroblastoma-differentiation therapy. Here, m6Am promotes expression of ATF3, which represses neuroblastoma biomarker MYCN. Depleting m6Am suppresses MYCN repression in ATRA-treated neuroblastoma and maintains their tumor-stem-like properties. Collectively, we characterize m6Am as an anti-terminator RNA modification that suppresses premature termination and modulates neuroblastoma's therapeutic response.

Can we define breast cancer HER2 status by liquid biopsy?

Human Epidermal growth factor Receptor 2 (HER2) assessment is crucial for breast cancer treatment. Therapeutic decisions for recurrent cases often rely on primary tumor status. However, mounting evidence suggests that tumors show dynamic changes and up to 10% of breast cancer modify their initial status during progression. It is still debated whether these changes reflect a biological evolution of the disease or are secondary to primary tumor heterogeneity. Certainly, repeating HER2 assessment during breast cancer trajectory is important for the increasing availability of effective anti-HER2 drugs. In response to this need, circulating biomarkers such as circulating tumor cells (CTCs) and cell-free circulating tumor DNA (ctDNA) offer the potential to safely and repeatedly assess HER2 status over time. This chapter outlines current methods for testing HER2 in CTCs and ctDNA, and reviews clinical trials evaluating its prognostic and predictive value in patients with breast cancer, as well as recent advances in the field.

Clinical Evidence of Circulating Tumor DNA Application in Aggressive Breast Cancer

Breast cancer is clinically and biologically heterogeneous and is classified into different subtypes according to the molecular landscape of the tumor. Triple-negative breast cancer is a subtype associated with higher tumor aggressiveness, poor prognosis, and poor response to treatment. In metastatic breast cancer, approximately 6% to 10% of new breast cancer cases are initially staged IV (de novo metastatic disease). The number of metastatic recurrences is estimated to be 20-30% of all existing breast tumor cases, whereby the need to develop specific genetic markers to improve the prognosis of patients suffering from these deadly forms of breast cancer. As an alternative, liquid biopsy methods can minutely identify the molecular architecture of breast cancer, including aggressive forms, which provides new perspectives for more precise diagnosis and more effective therapeutics. This review aimed to summarize the current clinical evidence for the application of circulating tumor DNA in managing breast cancer by detailing the increased usefulness of this biomarker as a diagnostic, prognostic, monitoring, and surveillance marker for breast cancer.

DETexT: An SNV detection enhancement for low read depth by integrating mutational signatures into TextCNN

Detecting SNV at very low read depths helps to reduce sequencing requirements, lowers sequencing costs, and aids in the early screening, diagnosis, and treatment of cancer. However, the accuracy of SNV detection is significantly reduced at read depths below ×34 due to the lack of a sufficient number of read pairs to help filter out false positives. Many recent studies have revealed the potential of mutational signature (MS) in detecting true SNV, understanding the mutational processes that lead to the development of human cancers, and analyzing the endogenous and exogenous causes. Here, we present DETexT, an SNV detection method better suited to low read depths, which classifies false positive variants by combining MS with deep learning algorithms to mine correlation information around bases in individual reads without relying on the support of duplicate read pairs. We have validated the effectiveness of DETexT on simulated and real datasets and conducted comparative experiments. The source code has been uploaded to https://github.com/TrinaZ/extra-lowRD for academic use only.

Leveraging the Fragment Length of Circulating Tumour DNA to Improve Molecular Profiling of Solid Tumour Malignancies with Next-Generation Sequencing: A Pathway to Advanced Non-invasive Diagnostics in Precision Oncology?

Circulating cell-free DNA (ccfDNA) has emerged as a promising diagnostic tool in oncology. Identification of tumour-derived ccfDNA (i.e. circulating tumour DNA [ctDNA]) provides non-invasive access to a malignancy’s molecular landscape to diagnose, inform therapeutic strategies, and monitor treatment efficacy. Current applications of ccfDNA to detect somatic mutations, however, have been largely constrained to tumour-informed searches and identification of common mutations because of the interaction between ctDNA signal and next-generation sequencing (NGS) noise. Specifically, the low allele frequency of ctDNA associated with non-metastatic and early-stage lesions may be indistinguishable from artifacts that accrue during sample preparation and NGS. Thus, using ccfDNA to achieve non-invasive and personalized molecular profiling to optimize individual patient care is a highly sought goal that remains limited in clinical practice. There is growing evidence, however, that further advances in the field of ccfDNA diagnostics may be achieved by improving detection of somatic mutations through leveraging the inherently shorter fragment lengths of ctDNA compared to non-neoplastic ccfDNA. Here, the origins and rationale for seeking to improve the mutation-based detection of ctDNA by using ccfDNA size profiling are reviewed. Subsequently, in vitro and in silico methods to enrich for a target ccfDNA fragment length are detailed to identify current practices and provide perspective into the potential of using ccfDNA size profiling to impact clinical applications in oncology.

The Detection of Cancer Epigenetic Traces in Cell-Free DNA

Nucleic acid fragments found in blood circulation originate mostly from dying cells and carry signs pointing to specific features of the parental cell types. Deciphering these clues may be transformative for numerous research and clinical applications but strongly depends on the development and implementation of robust analytical methods. Remarkable progress has been achieved in the reliable detection of sequence alterations in cell-free DNA while decoding epigenetic information from methylation and fragmentation patterns requires more sophisticated approaches. This review discusses the currently available strategies for detecting and analyzing the epigenetic marks in the liquid biopsies.