Identification of tumor tissue-derived DNA methylation biomarkers for the detection and therapy response evaluation of metastatic castration resistant prostate cancer in liquid biopsies

A review on trends in development and translation of omics signatures in cancer

The field of cancer genomics and transcriptomics has evolved from targeted profiling to swift sequencing of individual tumor genome and transcriptome. The steady growth in genome, epigenome, and transcriptome datasets on a genome-wide scale has significantly increased our capability in capturing signatures that represent both the intrinsic and extrinsic biological features of tumors. These biological differences can help in precise molecular subtyping of cancer, predicting tumor progression, metastatic potential, and resistance to therapeutic agents. In this review, we summarized the current development of genomic, methylomic, transcriptomic, proteomic and metabolic signatures in the field of cancer research and highlighted their potentials in clinical applications to improve diagnosis, prognosis, and treatment decision in cancer patients.

Identification and Localization of Indolent and Aggressive Prostate Cancers Using Multilevel Bi-LSTM

Identifying indolent and aggressive prostate cancers is a critical problem for optimal treatment. The existing approaches of prostate cancer detection are facing challenges as the techniques rely on ground truth labels with limited accuracy, and histological similarity, and do not consider the disease pathology characteristics, and indefinite differences in appearance between the cancerous and healthy tissue lead to many false positive and false negative interpretations. Hence, this research introduces a comprehensive framework designed to achieve accurate identification and localization of prostate cancers, irrespective of their aggressiveness. This is accomplished through the utilization of a sophisticated multilevel bidirectional long short-term memory (Bi-LSTM) model. The pre-processed images are subjected to multilevel feature map-based U-Net segmentation, bolstered by ResNet-101 and a channel-based attention module that improves the performance. Subsequently, segmented images undergo feature extraction, encompassing various feature types, including statistical features, a global hybrid-based feature map, and a ResNet-101 feature map that enhances the detection accuracy. The extracted features are fed to the multilevel Bi-LSTM model, further optimized through channel and spatial attention mechanisms that offer the effective localization and recognition of complex structures of cancer. Further, the framework represents a promising approach for enhancing the diagnosis and localization of prostate cancers, encompassing both indolent and aggressive cases. Rigorous testing on a distinct dataset demonstrates the model's effectiveness, with performance evaluated through key metrics which are reported as 96.72%, 96.17%, and 96.17% for accuracy, sensitivity, and specificity respectively utilizing the dataset 1. For dataset 2, the model achieves the accuracy, sensitivity, and specificity values of 94.41%, 93.10%, and 94.96% respectively. These results surpass the efficiency of alternative methods.

Current Challenges of Methylation-Based Liquid Biopsies in Cancer Diagnostics

In current clinical practice, effective cancer testing and screening paradigms are limited to specific types of cancer, exhibiting varying efficiency, acceptance, and adherence. Cell-free DNA (cfDNA) methylation profiling holds promise in providing information about the presence of malignity regardless of its type and location while leveraging blood-based liquid biopsies as a method to obtain analytical samples. However, technical difficulties, costs and challenges resulting from biological variations, tumor heterogeneity, and exogenous factors persist. This method exploits the mechanisms behind cfDNA release but faces issues like fragmentation, low concentrations, and high background noise. This review explores cfDNA methylation's origins, means of detection, and profiling for cancer diagnostics. The critical evaluation of currently available multi-cancer early detection methods (MCEDs) as well as tests targeting single genes, emphasizing their potential and limits to refine strategies for early cancer detection, are explained. The current methodology limitations, workflows, comparisons of clinically approved liquid biopsy-based methylation tests for cancer, their utilization in companion diagnostics as well as the biological limitations of the epigenetics approach are discussed, aiming to help healthcare providers as well as researchers to orient themselves in this increasingly complex and evolving field of diagnostics.

Examining the Relationship and Prognostic Significance of Cell-Free DNA Levels and the PSMA-Positive Tumor Volume in Men with Prostate Cancer: A Retrospective-Prospective [68Ga]Ga-PSMA-11 PET/CT Study

Functional imaging with prostate-specific membrane antigen (PSMA) ligands has emerged as the standard imaging method for prostate cancer (PCA). In parallel, the analysis of blood-derived, cell-free DNA (cfDNA) has been shown to be a promising quantitative biomarker of PCA aggressiveness and patient outcome. This study aimed to evaluate the relationship and prognostic value of cfDNA concentrations and the PSMA-positive tumor volume (PSMA-TV) in men with PCA undergoing [68Ga]Ga-PSMA-11 PET/CT imaging. Methods: We recruited 148 men with histologically proven PCA (mean age, 70.7 ± 7.7 y) who underwent [68Ga]Ga-PSMA-11 PET/CT (184.9 ± 18.9 MBq) and blood sampling between March 2019 and August 2021. Among these, 74 (50.0%) had hormone-sensitive PCA and 74 (50.0%) had castration-resistant PCA (CRPC). All patients provided written informed consent before blood sample collection and imaging. The cfDNA was extracted and quantified, and PSMA-expressing tumor lesions were delineated to extract the PSMA-TVs. The Spearman coefficient assessed correlations between PSMA-TV and cfDNA concentrations and cfDNA's relation with clinical parameters. The Kruskal-Wallis test examined the mean cfDNA concentration differences based on PSMA-TV quartiles for significantly correlated patient groups. Log-rank and multivariate Cox regression analyses evaluated the prognostic significance of high and low cfDNA and PSMA-TV levels for overall survival. Results: Weak positive correlations were found between cfDNA concentration and PSMA-TV in the overall group (r = 0.16, P = 0.049) and the CRPC group (r = 0.31, P = 0.007) but not in hormone-sensitive PCA patients (r = -0.024, P = 0.837). In the CRPC cohort, cfDNA concentrations significantly differed between PSMA-TV quartiles 4 and 1 (P = 0.002) and between quartiles 4 and 2 (P = 0.016). Survival outcomes were associated with PSMA-TV (P < 0.0001, P = 0.004) but not cfDNA (P = 0.174, P = 0.12), as per the log-rank and Cox regression analysis. Conclusion: These findings suggest that cfDNA might serve as a biomarker of advanced, aggressive CRPC but does not reliably reflect total tumor burden or prognosis. In comparison, [68Ga]Ga-PSMA-11 PET/CT provides a highly granular and prognostic assessment of tumor burden across the spectrum of PCA disease progression.

Circulating Tumor DNA Biomarkers for Response Assessment in Prostate Cancer

Circulating tumor DNA (ctDNA) is measurable in the majority of metastatic castration-resistant prostate cancer patients. Data indicate that ctDNA present at baseline can serve as a prognostic biomarker and changes in the ctDNA posttreatment can rapidly predict both time to progression and survival. See related article by Tolmeijer et al., p. 2835.

Recent advances in understanding DNA methylation of prostate cancer

Epigenetic modifications, such as DNA methylation, is widely studied in cancer. DNA methylation patterns have been shown to distinguish between benign and malignant tumors in various cancers, including prostate cancer. It may also contribute to oncogenesis, as it is frequently associated with downregulation of tumor suppressor genes. Aberrant patterns of DNA methylation, in particular the CpG island hypermethylator phenotype (CIMP), have shown associative evidence with distinct clinical features and outcomes, such as aggressive subtypes, higher Gleason score, prostate-specific antigen (PSA), and overall tumor stage, overall worse prognosis, as well as reduced survival. In prostate cancer, hypermethylation of specific genes is significantly different between tumor and normal tissues. Methylation patterns could distinguish between aggressive subtypes of prostate cancer, including neuroendocrine prostate cancer (NEPC) and castration resistant prostate adenocarcinoma. Further, DNA methylation is detectable in cell-free DNA (cfDNA) and is reflective of clinical outcome, making it a potential biomarker for prostate cancer. This review summarizes recent advances in understanding DNA methylation alterations in cancers with the focus on prostate cancer. We discuss the advanced methodology used for evaluating DNA methylation changes and the molecular regulators behind these changes. We also explore the clinical potential of DNA methylation as prostate cancer biomarkers and its potential for developing targeted treatment of CIMP subtype of prostate cancer.

Cell-free DNA methylation biomarker for the diagnosis of papillary thyroid carcinoma

BACKGROUND

Cell-free DNA (cfDNA) is being explored as biomarker for non-invasive diagnosis of cancer. We aimed to establish a cfDNA-based DNA methylation marker panel to differentially diagnose papillary thyroid carcinoma (PTC) from benign thyroid nodule (BTN).

METHODS

220 PTC- and 188 BTN patients were enrolled. Methylation markers of PTC were identified from patients' tissue and plasma by reduced representation bisulfite sequencing and methylation haplotype analyses. They were combined with PTC markers from literatures and were tested on additional PTC and BTN samples to verify PTC-detecting ability using targeted methylation sequencing. Top markers were developed into ThyMet and were tested in 113 PTC and 88 BTN cases to train and validate a PTC-plasma classifier. Integration of ThyMet and thyroid ultrasonography was explored to improve accuracy.

FINDINGS

From 859 potential PTC plasma-discriminating markers that include 81 markers identified by us, the top 98 most PTC plasma-discriminating markers were selected for ThyMet. A 6-marker ThyMet classifier for PTC plasma was trained. In validation it achieved an Area Under the Curve (AUC) of 0.828, similar to thyroid ultrasonography (0.833) but at higher specificity (0.722 and 0.625 for ThyMet and ultrasonography, respectively). A combinatorial classifier by them, ThyMet-US, improved AUC to 0.923 (sensitivity = 0.957, specificity = 0.708).

INTERPRETATION

The ThyMet classifier improved the specificity of differentiating PTC from BTN over ultrasonography. The combinatorial ThyMet-US classifier may be effective in preoperative diagnosis of PTC.

FUNDING

This work was supported by the grants from National Natural Science Foundation of China (82072956 and 81772850).

Cell-free DNA in the management of prostate cancer: Current status and future prospective

Objective

With the escalating prevalence of prostate cancer (PCa) in China, there is an urgent demand for novel diagnostic and therapeutic approaches. Extensive investigations have been conducted on the clinical implementation of circulating free DNA (cfDNA) in PCa. This review aims to provide a comprehensive overview of the present state of cfDNA as a biomarker for PCa and to examine its merits and obstacles for future clinical utilization.

Methods

Relevant peer-reviewed manuscripts on cfDNA as a PCa marker were evaluated by PubMed search (2010-2022) to evaluate the roles of cfDNA in PCa diagnosis, prognosis, and prediction, respectively.

Results

cfDNA is primarily released from cells undergoing necrosis and apoptosis, allowing for non-invasive insight into the genomic, transcriptomic, and epigenomic alterations within various PCa disease states. Next-generation sequencing, among other detection methods, enables the assessment of cfDNA abundance, mutation status, fragment characteristics, and epigenetic modifications. Multidimensional analysis based on cfDNA can facilitate early detection of PCa, risk stratification, and treatment monitoring. However, standardization of cfDNA detection methods is still required to expedite its clinical application.

Conclusion

cfDNA provides a non-invasive, rapid, and repeatable means of acquiring multidimensional information from PCa patients, which can aid in guiding clinical decisions and enhancing patient management. Overcoming the application barriers of cfDNA necessitates increased data sharing and international collaboration.

Sequencing impact and prognostic factors in metastatic castration-resistant prostate cancer patients treated with cabazitaxel: A systematic review and meta-analysis

BACKGROUND

Cabazitaxel is an effective treatment of post-docetaxel metastatic castration-resistant prostate cancer (mCRPC). We aimed to assess the sequencing impact and identify prognostic factors of oncologic outcomes in mCRPC patients treated with cabazitaxel.

METHODS

PUBMED, Web of Science, and Scopus databases were searched for articles published before January 2022 according to the PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analyses) statement. Studies were deemed eligible if they investigated pretreatment clinical or hematological prognostic factors of overall survival (OS) in mCRPC patients with progression after docetaxel treated with available treatments including cabazitaxel.

RESULTS

Overall, 22 studies were eligible for the meta-analysis. In mCRPC patients treated with docetaxel, subsequent treatment with cabazitaxel was associated with better OS compared to that without cabazitaxel (pooled hazard ratio [HR]: 0.70, 95% confidence interval [CI]: 0.56-0.89). Among the patients treated with cabazitaxel, several pretreatment clinical features and hematologic biomarkers were associated with worse OS as follows: poor performance status (PS) (pooled HR: 1.92, 95% CI: 1.33-2.77), presence of visceral metastasis (pooled HR: 2.13, 95% CI: 1.62-2.81), symptomatic disease (pooled HR: 1.47, 95% CI: 1.25-1.73), high PSA (pooled HR: 1.76, 95% CI: 1.27-2.44), high alkaline phosphatase (ALP) (pooled HR: 1.45, 95% CI: 1.28-1.65), high lactate dehydrogenase (LDH) (pooled HR: 1.54, 95% CI: 1.00-2.38), high c-reactive protein (CRP) (pooled HR: 4.40, 95% CI: 1.52-12.72), low albumin (pooled HR:1.09, 95% CI: 1.05-1.12) and low hemoglobin (pooled HR:1.55, 95% CI: 1.20-1.99).

CONCLUSIONS

Sequential therapy with cabazitaxel significantly improves OS in post-docetaxel mCRPC patients. In mCRPC patients treated with cabazitaxel, patients with poor PS, visceral metastasis, and symptomatic disease were associated with worse OS. Further, pretreatment high PSA, ALP, LDH or CRP as well as low hemoglobin or albumin, were blood-based prognostic factors for OS. These findings might help guide the clinical decision-making for the use of cabazitaxel and prognostication of its OS benefit.