Extrachromosomal DNA (ecDNA) in cancer: mechanisms, functions, and clinical implications

Detection of Gene Fusions and Rearrangements in Formalin-Fixed, Paraffin-Embedded Solid Tumor Specimens Using High-Throughput Chromosome Conformation Capture

Chromosomal structural variants (SVs) are major contributors to cancer development. Although multiple methods exist for detecting SVs, they are limited in throughput, such as fluorescent in situ hybridization and targeted panels, and use RNA, which degrades in formalin-fixed, paraffin-embedded (FFPE) blocks and is unable to detect SVs that do not produce a fusion transcript. High-throughput chromosome conformation capture (Hi-C) is a DNA-based next-generation sequencing (NGS) method that preserves the spatial conformation of the genome, capturing long-range genetic interactions and SVs. Herein, a retrospective study analyzing 71 FFPE specimens from 10 different solid tumors was performed. Results showed high concordance (98%) with clinical fluorescent in situ hybridization and RNA NGS in detecting known SVs. Furthermore, Hi-C provided insight into the mechanism of SV formation, including chromothripsis and extrachromosomal DNA, and detected rearrangements between genes and regulatory regions, all of which are undetectable by RNA NGS. Lastly, SVs were detected in 71% of cases in which previous clinical methods failed to identify a driver. Of these, 14% were clinically actionable based on current medical guidelines, and an additional 14% were not in medical guidelines but involve targetable biomarkers. Current data suggest that Hi-C is a robust and accurate method for genome-wide SV analyses from FFPE tissue and can be incorporated into current clinical NGS workflows.

A novel CRISPR-Cas9 nickase-mediated rolling circle amplification (CRIRCA) technique for gene identification and quantitative analysis of extrachromosomal DNA

INTRODUCTION

Extrachromosomal DNA (ecDNA) plays an important role in the initiation and progression of cancerous tumors. Although Circle-seq and other genetic technologies can be utilized for ecDNA analysis, they fail to provide multi-dimensional information from ecDNA, which is time-consuming and laborious.

OBJECTIVES

Herein, by combining the netlike rolling circle amplification (NRCA) with CRISPR, we developed a novel CRISPR-Cas9 nickase-mediated RCA (CRIRCA) technology that can meet the clinical analysis needs of ecDNA.

METHODS

Atomic force microscope (AFM) was applied to confirm the circular structure of the ecDNA. Agarose gel electrophoresis was performed to analyze the CRIRCA products. Fluorescent detection was applied to characterize the fluorescence signal of amplified products. qPCR and FISH techniques were applied to verify the CRIRCA results of gene identification of ecDNA.

RESULTS

Our data revealed that CRIRCA achieved more efficient signal amplification compared to traditional RCA methods, allowing it to sensitively analyze small amounts of ecDNA in single tumor cells. Utilizing computer-aided design, we successfully constructed the primer library and sgRNA library of oncogene in ecDNA, and adopted CRIRCA technology to identify the oncogenes of ecDNA in breast cancer cells.

CONCLUSION

Therefore, CRIRCA can simultaneously obtain the information from structure, sequence and quantitation of ecDNA. This work will fill the gap in the current research on the early monitoring of cancer targeting ecDNA, and provide support for the accurate diagnosis and treatment of cancer.

Challenges of small cell lung cancer heterogeneity and phenotypic plasticity

Small cell lung cancer (SCLC) is an aggressive neuroendocrine malignancy with ~7% 5-year overall survival reflecting early metastasis and rapid acquired chemoresistance. Immunotherapy briefly extends overall survival in ~15% cases, yet predictive biomarkers are lacking. Targeted therapies are beginning to show promise, with a recently approved delta-like ligand 3 (DLL3)-targeted therapy impacting the treatment landscape. The increased availability of patient-faithful models, accumulating human tumour biobanks and numerous comprehensive molecular profiling studies have collectively facilitated the mapping and understanding of substantial intertumoural and intratumoural heterogeneity. Beyond the almost ubiquitous loss of wild-type p53 and RB1, SCLC is characterized by heterogeneously mis-regulated expression of MYC family members, yes-associated protein 1 (YAP1), NOTCH pathway signalling, anti-apoptotic BCL2 and epigenetic regulators. Molecular subtypes are based on the neurogenic transcription factors achaete-scute homologue 1 (ASCL1) and neurogenic differentiation factor 1 (NEUROD1), the rarer non-neuroendocrine transcription factor POU class 2 homeobox 3 (POU2F3), and immune- and inflammation-related signatures. Furthermore, SCLC shows phenotypic plasticity, including neuroendocrine-to-non-neuroendocrine transition driven by NOTCH signalling, which is associated with disease progression, chemoresistance and immune modulation and, in mouse models, with metastasis. Although these features pose substantial challenges, understanding the molecular vulnerabilities of transcription factor subtypes, the functional relevance of plasticity and cell cooperation offer opportunities for personalized therapies informed by liquid and tissue biomarkers.

The viral landscape in metastatic solid cancers

Here, we analyze the viral landscape in blood and tissue from 4918 metastatic cancer patients across 38 solid cancer types from the Hartwig Medical Foundation (HMF) cohort, the largest pan-cancer study on metastatic cancer. Using a coverage-based filtering approach, we detected 25 unique viral genera across 32 different cancer types, with a total of 747 unique virus-positive tissue samples. We detected 336 virus-positive blood samples across 29 cancer types, dominated by Torque teno virus and Alphatorquevirus. The tissue samples were dominated by Alphapapillomavirus and Roseolovirus. Alphapapillomavirus was significantly enriched in genital, anal, and colorectal cancers and was associated with host mutational signatures and transcriptional programs related to immunity and DNA repair. Host genes with Alphapapillomavirus integration tended to be more highly expressed and samples with HPV integration had higher somatic mutation rates and higher number of extrachromosomal DNA elements. Alphapapillomavirus was also detected in a significant proportion of blood samples from cervix and anal cancers, suggesting a potential blood-based biomarker.

Extrachromosomal circular DNA: a double-edged sword in cancer progression and age-related diseases

Extrachromosomal circular DNA (eccDNA) is a fascinating form of genetic material found outside the usual chromosomal DNA in eukaryotic cells, including humans. Since its discovery in the 1960s, eccDNA has been linked to critical roles in cancer progression and age-related diseases. This review thoroughly explores eccDNA, covering its types, how it forms, and its significant impact on diseases, particularly cancer. EccDNA, especially in its extrachromosomal DNA (ecDNA) form, contributes to the genetic diversity of tumour cells, helping them evolve quickly and resist treatments. Beyond cancer, eccDNA is also connected to age-related conditions like Werner syndrome, amyotrophic lateral sclerosis (ALS), and type 2 diabetes mellitus (T2DM), where it may affect genomic stability and disease development. The potential of eccDNA as a biomarker for predicting disease outcomes and as a target for new treatments is also highlighted. This review aims to deepen our understanding of eccDNA and inspire further research into its roles in human health and disease, paving the way for innovative diagnostic and therapeutic approaches.

Cell-free and extrachromosomal DNA profiling of small cell lung cancer

Small cell lung cancer (SCLC) is highly aggressive with poor prognosis. Despite a relative prevalence of circulating tumour DNA (ctDNA) in SCLC, liquid biopsies are not currently implemented, unlike non-SCLC where cell-free DNA (cfDNA) mutation profiling in the blood has utility for guiding targeted therapies and assessing minimal residual disease. cfDNA methylation profiling is highly sensitive for SCLC detection and holds promise for disease monitoring and molecular subtyping; cfDNA fragmentation profiling has also demonstrated clinical potential. Extrachromosomal DNA (ecDNA), that is often observed in SCLC, promotes tumour heterogeneity and chemotherapy resistance and can be detected in blood. We discuss how these cfDNA profiling modalities can be harnessed to expand the clinical applications of liquid biopsy in SCLC.

The distribution of the extrachromosomal DNA molecules in early lung cancer

Lung cancer (LC) is a highly lethal cancer worldwide. Research on the distribution and nature of extrachromosomal DNA molecules (EcDNAm) in early LC is scarce. In this study, after removing linear DNA and mitochondrial circular DNA, EcDNAm were extracted from two paired LC tissue samples and amplified using rolling circle amplification. High throughput extrachromosomal DNA (EcDNA) or RNA sequencing and bioinformatics analysis were subsequently utilized to explore the distribution and nature of the EcDNAm. Additionally, to elucidate the role of oncogenes with large EcDNAm sizes, gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses were performed. The RNA sequencing results revealed significant differences in certain genes between tumors and corresponding normal samples. At the same time, slight distinctions were observed between relapsed and non-relapsed tumor samples. The nature of the EcDNAm was compared between LC samples and matched normal samples. There was a tendency for the number of EcDNAm with longer size (EcDNA) and its containing driver oncogenes to be higher in cancer samples. Enrichment analysis of the cancer samples revealed enrichment in biological processes, such as positive regulation of protein localization, axon development, and in-utero embryonic development. This study highlights the universal distribution and characteristics of EcDNAm in early LC. Moreover, our work fills the investigation of the EcDNAm gap and future studies should focus on the application of EcDNA as a potential biomarker in patients with early LC.

Multi-OMICS approaches in cancer biology: New era in cancer therapy

Innovative multi-omics frameworks integrate diverse datasets from the same patients to enhance our understanding of the molecular and clinical aspects of cancers. Advanced omics and multi-view clustering algorithms present unprecedented opportunities for classifying cancers into subtypes, refining survival predictions and treatment outcomes, and unravelling key pathophysiological processes across various molecular layers. However, with the increasing availability of cost-effective high-throughput technologies (HTT) that generate vast amounts of data, analyzing single layers often falls short of establishing causal relations. Integrating multi-omics data spanning genomes, epigenomes, transcriptomes, proteomes, metabolomes, and microbiomes offers unique prospects to comprehend the underlying biology of complex diseases like cancer. This discussion explores algorithmic frameworks designed to uncover cancer subtypes, disease mechanisms, and methods for identifying pivotal genomic alterations. It also underscores the significance of multi-omics in tumor classifications, diagnostics, and prognostications. Despite its unparalleled advantages, the integration of multi-omics data has been slow to find its way into everyday clinics. A major hurdle is the uneven maturity of different omics approaches and the widening gap between the generation of large datasets and the capacity to process this data. Initiatives promoting the standardization of sample processing and analytical pipelines, as well as multidisciplinary training for experts in data analysis and interpretation, are crucial for translating theoretical findings into practical applications.

Multiple HPV integration mode in the cell lines based on long-reads sequencing

Background

The integration of human papillomavirus (HPV) is closely related to the occurrence of cervical cancer. However, little is known about the complete state of HPV integration into the host genome.

Methods

In this study, three HPV-positive cell lines, HeLa, SiHa, and CaSki, were subjected to NANOPORE long-read sequencing to detect HPV integration. Analysis of viral integration patterns using independently developed software (HPV-TSD) yielded multiple complete integration patterns for the three HPV cell lines.

Results

We found distinct differences between the integration patterns of HPV18 and HPV16. Furthermore, the integration characteristics of the viruses were significantly different, even though they all belonged to HPV16 integration. The HPV integration in the CaSki cells was relatively complex. The HPV18 integration status in HeLa cells was the dominant, whereas the percentage of integrated HPV 16 in SiHa and CaSki cells was significantly lower. In addition, the virus sequences in the HeLa cells were incomplete and existed in an integrated state. We also identified a large number of tandem repeats in HPV16 and HPV18 integration. Our study not only clarified the feasibility of high-throughput long-read sequencing in the study of HPV integration, but also explored a variety of HPV integration models, and confirmed that viral integration is an important form of HPV in cell lines.

Conclusion

Elucidating HPV integration patterns will provide critical guidance for developing a detection algorithm for HPV integration, as well as the application of virus integration in clinical practice and drug research and development.