Cell-free chromatin immunoprecipitation can determine tumor gene expression in lung cancer patients

Cell-free epigenomes enhanced fragmentomics-based model for early detection of lung cancer

BACKGROUND

Lung cancer is a leading cause of cancer mortality, highlighting the need for innovative non-invasive early detection methods. Although cell-free DNA (cfDNA) analysis shows promise, its sensitivity in early-stage lung cancer patients remains a challenge. This study aimed to integrate insights from epigenetic modifications and fragmentomic features of cfDNA using machine learning to develop a more accurate lung cancer detection model.

METHODS

To address this issue, a multi-centre prospective cohort study was conducted, with participants harbouring suspicious malignant lung nodules and healthy volunteers recruited from two clinical centres. Plasma cfDNA was analysed for its epigenetic and fragmentomic profiles using chromatin immunoprecipitation sequencing, reduced representation bisulphite sequencing and low-pass whole-genome sequencing. Machine learning algorithms were then employed to integrate the multi-omics data, aiding in the development of a precise lung cancer detection model.

RESULTS

Cancer-related changes in cfDNA fragmentomics were significantly enriched in specific genes marked by cell-free epigenomes. A total of 609 genes were identified, and the corresponding cfDNA fragmentomic features were utilised to construct the ensemble model. This model achieved a sensitivity of 90.4% and a specificity of 83.1%, with an AUC of 0.94 in the independent validation set. Notably, the model demonstrated exceptional sensitivity for stage I lung cancer cases, achieving 95.1%. It also showed remarkable performance in detecting minimally invasive adenocarcinoma, with a sensitivity of 96.2%, highlighting its potential for early detection in clinical settings.

CONCLUSIONS

With feature selection guided by multiple epigenetic sequencing approaches, the cfDNA fragmentomics-based machine learning model demonstrated outstanding performance in the independent validation cohort. These findings highlight its potential as an effective non-invasive strategy for the early detection of lung cancer.

KEYPOINTS

Our study elucidated the regulatory relationships between epigenetic modifications and their effects on fragmentomic features. Identifying epigenetically regulated genes provided a critical foundation for developing the cfDNA fragmentomics-based machine learning model. The model demonstrated exceptional clinical performance, highlighting its substantial potential for translational application in clinical practice.

Histone modifications of circulating nucleosomes are associated with changes in cell-free DNA fragmentation patterns

The analysis of tissues of origin of cell-free DNA (cfDNA) is of research and diagnostic interest. Many studies focused on bisulfite treatment or immunoprecipitation protocols to assess the tissues of origin of cfDNA. DNA loss often occurs during such processes. Fragmentomics of cfDNA molecules has uncovered a wealth of information related to tissues of origin of cfDNA. There is still much room for the development of tools for assessing contributions from various tissues into plasma using fragmentomic features. Hence, we developed an approach to analyze the relative contributions of DNA from different tissues into plasma, by identifying characteristic fragmentation patterns associated with selected histone modifications. We named this technique as FRAGmentomics-based Histone modification Analysis (FRAGHA). Deduced placenta-specific histone H3 lysine 27 acetylation (H3K27ac)-associated signal correlated well with the fetal DNA fraction in maternal plasma (Pearson's r = 0.96). The deduced liver-specific H3K27ac-associated signal correlated with the donor-derived DNA fraction in liver transplantation recipients (Pearson's r = 0.92) and was significantly increased in patients with hepatocellular carcinoma (HCC) (P < 0.01, Wilcoxon rank-sum test). Significant elevations of erythroblasts-specific and colon-specific H3K27ac-associated signals were observed in patients with β-thalassemia major and colorectal cancer, respectively. Furthermore, using the fragmentation patterns from tissue-specific H3K27ac regions, a machine learning algorithm was developed to enhance HCC detection, with an area under the curve (AUC) of up to 0.97. Finally, genomic regions with H3K27ac or histone H3 lysine 4 trimethylation (H3K4me3) were found to exhibit different fragmentomic patterns of cfDNA. This study has shed light on the relationship between cfDNA fragmentomics and histone modifications, thus expanding the armamentarium of liquid biopsy.

Integration of Cell-Free DNA End Motifs and Fragment Lengths Can Identify Active Genes in Liquid Biopsies

Multiple studies have shown that cell-free DNA (cfDNA) from cancer patients differ in both fragment length and fragment end motif (FEM) from healthy individuals, yet there is a lack of understanding of how the two factors combined are associated with cancer and gene transcription. In this study, we conducted cfDNA fragmentomics evaluations using plasma from lung cancer patients (n = 12) and healthy individuals (n = 7). A personal gene expression profile was established from plasma using H3K36me3 cell-free chromatin immunoprecipitation sequencing (cfChIP-seq). The genes with the highest expression displayed an enrichment of short cfDNA fragments (median = 19.99%, IQR: 16.94-27.13%, p < 0.0001) compared to the genes with low expression. Furthermore, distinct GC-rich FEMs were enriched after cfChIP. Combining the frequency of short cfDNA fragments with the presence of distinct FEMs resulted in an even further enrichment of the most expressed genes (median = 37.85%, IQR: 30.10-39.49%, p < 0.0001). An in vitro size selection of <150 bp cfDNA could isolate cfDNA representing active genes and the size-selection enrichment correlated with the cfChIP-seq enrichment (Spearman r range: 0.499-0.882, p < 0.0001). This study expands the knowledge regarding cfDNA fragmentomics and sheds new light on how gene activity is associated with both cfDNA fragment lengths and distinct FEMs.

Trans-Regulation of Alternative PD-L1 mRNA Processing by CDK12 in Non-Small-Cell Lung Cancer Cells

Immunotherapy using checkpoint inhibitors targeting the interaction between PD-1 on T cells and PD-L1 on cancer cells has shown significant results in non-small-cell lung cancer (NSCLC). Not all patients respond to the therapy, and PD-L1 expression heterogeneity is proposed to be one determinant for this. The alternative processing of PD-L1 RNA, which depends on an alternative poly-A site in intron 4, generates a shorter mRNA variant (PD-L1v4) encoding soluble PD-L1 (sPD-L1), relative to the canonical PD-L1v1 mRNA encoding membrane-associated PD-L1 (mPD-L1). This study aimed to identify factors influencing the ratio between these two PD-L1 mRNAs in NSCLC cells. First, we verified the existence of the alternative PD-L1 RNA processing in NSCLC cells, and from in silico analyses, we identified a candidate list of regulatory factors. Examining selected candidates showed that CRISPR/Cas9-generated loss-of-function mutations in CDK12 increased the PD-L1v4/PD-L1v1 mRNA ratio and, accordingly, the sPD-L1/mPD-L1 balance. The CDK12/13 inhibitor THZ531 could also increase the PD-L1v4/PD-L1v1 mRNA ratio and impact the PD-L1 transcriptional response to IFN-γ stimulation. The fact that CDK12 regulates PD-L1 transcript variant formation in NSCLC cells is consistent with CDK12's role in promoting transcriptional elongation over intron-located poly-A sites. This study lays the groundwork for clinical investigations to delineate the implications of the CDK12-mediated balancing of sPD-L1 relative to mPD-L1 for immunotherapeutic responses in NSCLC.

Cell-free chromatin immunoprecipitation to detect molecular pathways in heart transplantation

Existing monitoring approaches in heart transplantation lack the sensitivity to provide deep molecular assessments to guide management, or require endomyocardial biopsy, an invasive and blind procedure that lacks the precision to reliably obtain biopsy samples from diseased sites. This study examined plasma cell-free DNA chromatin immunoprecipitation sequencing (cfChIP-seq) as a noninvasive proxy to define molecular gene sets and sources of tissue injury in heart transplant patients. In healthy controls and in heart transplant patients, cfChIP-seq reliably detected housekeeping genes. cfChIP-seq identified differential gene signals of relevant immune and nonimmune molecular pathways that were predominantly down-regulated in immunosuppressed heart transplant patients compared with healthy controls. cfChIP-seq also identified cell-free DNA tissue sources. Compared with healthy controls, heart transplant patients demonstrated greater cell-free DNA from tissue types associated with heart transplant complications, including the heart, hematopoietic cells, lungs, liver, and vascular endothelium. cfChIP-seq may therefore be a reliable approach to profile dynamic assessments of molecular pathways and sources of tissue injury in heart transplant patients.

Advancements in Focal Amplification Detection in Tumor/Liquid Biopsies and Emerging Clinical Applications

Focal amplifications (FAs) are crucial in cancer research due to their significant diagnostic, prognostic, and therapeutic implications. FAs manifest in various forms, such as episomes, double minute chromosomes, and homogeneously staining regions, arising through different mechanisms and mainly contributing to cancer cell heterogeneity, the leading cause of drug resistance in therapy. Numerous wet-lab, mainly FISH, PCR-based assays, next-generation sequencing, and bioinformatics approaches have been set up to detect FAs, unravel the internal structure of amplicons, assess their chromatin compaction status, and investigate the transcriptional landscape associated with their occurrence in cancer cells. Most of them are tailored for tumor samples, even at the single-cell level. Conversely, very limited approaches have been set up to detect FAs in liquid biopsies. This evidence suggests the need to improve these non-invasive investigations for early tumor detection, monitoring disease progression, and evaluating treatment response. Despite the potential therapeutic implications of FAs, such as, for example, the use of HER2-specific compounds for patients with ERBB2 amplification, challenges remain, including developing selective and effective FA-targeting agents and understanding the molecular mechanisms underlying FA maintenance and replication. This review details a state-of-the-art of FA investigation, with a particular focus on liquid biopsies and single-cell approaches in tumor samples, emphasizing their potential to revolutionize the future diagnosis, prognosis, and treatment of cancer patients.

Clinical application of liquid biopsy based on circulating tumor DNA in non-small cell lung cancer

Lung cancer is a widely occurring and deadly malignancy, with high prevalence rates in China and across the globe. Specifically, non-small cell lung cancer (NSCLC) represents about 85% of all lung cancer cases. The 5-year disease-free survival rate after surgery for stage IB-IIIB NSCLC patients (disease-free survival, DFS) has notably declined from 73% to 13%. Early detection of abnormal cancer molecules and subsequent personalized treatment plans are the most effective ways to address this problem. Liquid biopsy, surprisingly, enables safe, accurate, non-invasive, and dynamic tracking of disease progression. Among the various modalities, circulating tumor DNA (ctDNA) is the most commonly used liquid biopsy modality. ctDNA serves as a credible "liquid biopsy" diagnostic tool that, to a certain extent, overcomes tumor heterogeneity and harbors genetic mutations in malignancies, thereby providing early information on tumor genetic alterations. Despite considerable academic interest in the clinical significance of ctDNA, consensus on its utility remains lacking. In this review, we assess the role of ctDNA testing in the diagnosis and management of NSCLC as a reference for clinical intervention in this disease. Lastly, we examine future directions to optimize ctDNA for personalized therapy.