New biomarkers and liquid biopsies for prostate cancer diagnosis

Biomarkers come in various forms, from DNA, RNA, and proteins to chemicals produced by the body that indicate a given disease’s presence or severity.

Image Credit: Norgen Biotek Corp.

It is possible to leverage biomarkers as signals for the early detection of various conditions, helping to make effective treatment choices, monitor disease progression, or evaluate the response to a specific treatment.

Biomarkers can be detected in any fluid or tissue and are a key component in the personalized medicine approach to cancer treatment.

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The need for new biomarkers

The PSA test

The Prostate Specific Antigen (PSA) protein is produced by the prostate under normal circumstances. However, the levels of this protein increase in almost all cases of prostate cancer, meaning that its quantification represents a useful biomarker for prostate cancer.

The PSA test is currently the primary means of screening for prostate cancer. This method involves acquiring a blood sample from a patient before sending this to a laboratory to measure PSA levels in the blood.

The PSA test is the best screening tool currently available, but its sensitivity is low. Factors such as age and ethnicity can affect the normal range of PSA levels, which may increase due to urinary tract infections, excessive exercise, or recent ejaculation.

New data reveals that prostate cancer treatment may not be necessary in anywhere from 2% to 67% of cases where PSA has been used to detect tumors unlikely to impact the patient. This is a driver in the need to develop new biomarkers for prostate cancer.

Molecular profiling of tumors

While the PSA test remains the most commonly used screening tool, a definitive diagnosis is typically performed via tissue biopsy and subsequent histological analysis. Tumor molecular profiling has also been shown to enhance the selection of personalized cancer treatment, drug resistance detection, patient responses, and tumor relapse monitoring.

Androgen deprivation therapy (ADT) is key to the medical management of patients with metastatic prostate cancer, but a number of patients are resistant to some of the primary ADT drugs.

For example, ARV7 detection in cancer cells indicates that the patients are resistant to enzalutamide and abiraterone, with clinicians using this biomarker to enter the patient into clinical trials for new-generation ADT drugs.^1,2

Tissue biopsies remain highly invasive procedures and only offer a snapshot of information, despite the personalized molecular information obtained from them.

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Liquid biopsies: A new alternative

Continuous monitoring is required to effectively monitor treatment response, so it is important that any sampling procedure be minimally invasive.

Research into liquid biopsies over the past decade has shown their potential to replace tissue biopsies. Liquid biopsies offer straightforward sampling and the option to repeatedly and less invasively draw samples from the same patient.

The majority of liquid biopsies currently involve withdrawing blood to determine the presence of biomarkers, but promising research is ongoing involving the use of other fluids such as bile, saliva, urine, and cerebrospinal fluid.³

These liquids include a range of valuable analytes, such as RNA, DNA, and proteins. These analytes can be contained within vesicles such as an exosome, are cell-free, or are found within circulating tumor cells.

The importance of the pre-analytical workflow

The pre-analytical workflow is one of the primary considerations in the successful use of liquid biopsies for cancer biomarker detection. This involves careful analyte preservation at the site of sampling, alongside the use of detailed handling protocols, efficient transportation, and comprehensive sample processing.

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Blood collection and preservation

Blood can rarely be immediately processed at the site where it is drawn, so it is essential that analytes are preserved and stabilized during transportation and/or shipping.

For example, it is important to minimize leukocyte lysis because the presence of excessive genomic DNA can adversely affect cf-DNA/RNA analysis.

Different means of blood preservation are available. For example, Norgen tubes (Cat. 63950) rely on osmotic stabilization of nucleated cells, while other companies’ solutions use biological apoptosis inhibition or a chemical crosslinking approach.

Preservation devices that enable the shipment of samples at room temperature for extended periods ensure minimal biomarker degradation during transportation to the testing laboratory.

A recent research project compared a range of preservation tubes and extraction methods in order to determine their impact on downstream analysis. Norgen preservation tubes were determined to yield the most plasma with minimal hemolysis,³ enabling the parallel extraction of cfDNA and cfRNA from the same tube.

Subsequent droplet digital PCR amplification of both cell-free DNA and RNA facilitated the detection of tumor-specific alterations in low-coverage whole-genome sequencing and DNA methylation profiling.

Urine collection and preservation

While blood and plasma have garnered the most focus within the liquid biopsy field, the acquisition of patient blood samples requires trained professionals and continues to be relatively invasive.

The use of urine in detecting cancer biomarkers represents a truly non-invasive sampling method with no need to employ trained professionals in its collection.

Urine samples are accessible, boast high levels of patient compliance, and provide a useful representation of the body's health due to the ongoing filtration of blood via the kidneys. If urine is not adequately preserved, however, issues around microbial contamination and increased nucleases can compromise the analysis.

Urine samples collected from 43 patients with bladder cancer and healthy donors were collected using Norgen's urine preservation tubes (Cat. 18113). Cell-free DNA was extracted and processed using a target capture panel and deep sequencing analysis pipeline designed to detect genetic mutations for 118 cancers.

Bladder cancer was detected with 83.7% sensitivity and 100% specificity.⁴

This study in question relates to a urological cancer, but there is the potential for novel methods designed to extract and evaluate ultra-short cfDNA also advancing the liquid biopsy field for use with non-urological cancers.

A further interesting application saw researchers develop a modified LC/MS approach for untargeted metabolomics. This approach allowed them to perform metabolite analysis on urine preserved in Norgen devices, detecting prostate cancer-specific metabolites.⁵

Nucleic acid extraction

Cell-free DNA/RNA

cfDNAs are degraded DNA fragments primarily secreted from apoptotic or malignant cells. Most cfDNA in healthy individuals is generated from apoptotic cells with a length of 185-200 base pairs, but levels of cfDNA in cancer patients are higher and with more uneven fragment lengths.

A recent meta-analysis and systematic review of cell-free DNA as a diagnostic biomarker in prostate cancer highlighted favorable specificity but unacceptable levels of sensitivity. cf-DNA still holds promise as an accurate biomarker for prostate cancer (PCa), however, as increased research and more specific analysis from cf-DNA continues, for example, epigenetic or fragmentomic studies.⁶

Another useful biomarker for the early detection of cancer stems from the detection of circulating microRNA (miRNA)-based biomarkers. The low concentration of miRNAs released in bodily fluids means that their clinical use as effective cancer biomarkers remains limited, however.

A recent study aimed to address this issue, highlighting how ultrasound treatment has the potential to amplify the release of extracellular cancer biomarkers. Sonoporation was shown to amplify the release of miRNAs from both androgen-dependent (AD) and androgen-independent (AI) PCa cells.

It was possible to identify four PCa-related miRNAs whose levels increased following ultrasound treatment and were found to be upregulated in PCa patients versus controls.

This confirms their clinical relevance, as well as highlighting the potential of using ultrasound to in identifying novel cell-free miRNAs released from cancer cells, potentially leading to the development of new biomarkers with diagnostic and predictive value.⁷

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Exosomal DNA/RNA

Exosomes are 40-150 nm-sized extracellular vesicles that are released by all cell types, including tumor cells. Exosomes often contain DNA, RNA, and proteins, and their lipid bilayer membrane means they are stable in body fluids.

They are involved in extracellular communication, with the ability to traverse the body in order to localize to a specific cell. Once localized, the exosome will fuse with the target cell’s membrane and release its contents. This released cargo often contributes to tumor progression.

It is well established that tumors and other types of diseases release higher numbers of exosomes versus healthy cells, which alone may be indicative of disease presence or tumor burden.

Recent research involved the profiling of exosomal serum miRNAs (ex-miRNA) from a range of different individuals, including healthy controls, people with benign prostatic hyperplasia (BPH), and patients with aggressive prostate cancer.

Subsequent miRNA profiling was performed using a Nanostring nCounter, identifying a number of differentially expressed miRNAs. One of these, a tumor-suppressing miR-1246, was found to be downregulated in prostate cancer clinical tissues and cell lines. It was determined that miR-126 represents a promising prostate cancer biomarker with diagnostic potential for the prediction of disease aggressiveness.⁸

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Biomarker detection methods

Genomics

Specific inherited, or germline, variants can predispose individuals to a higher risk of developing cancer, and rare variants with high penetrance are especially useful biomarkers for cancer risk assessment.

For example, BRCA1 and BRCA2 high-penetrance variants have been closely linked to ovarian and breast cancer, while men who carry germline BRCA1/2 mutations are at increased risk of developing prostate cancer, as well as being at risk of a more aggressive prostate cancer phenotype.⁹

Somatic variations are also key cancer biomarkers, with genomic instability proving to be an important feature of cancer cells. Many cancers accumulate somatic mutations as they adapt to the rapidly changing microenvironment, with genetic alterations ranging from single base pair changes to large structural abnormalities like copy number alterations, translocation, or chromothripsis.

It is possible to detect these mutations in tumor tissue, and also in cell-free DNA originating from cancer cell lysis/death or active secretion, referred to as circulating tumor DNA (ctDNA).

Epigenomics

Epigenetic variation triggers changes in DNA methylation, or histone protein modifications, without impacting DNA’s coding sequence. These variations impact gene and protein expression, however, making them useful cancer biomarkers.

DNA methylation is a particularly important modification, because a loss of DNA methylation is common in many tumors, while also being linked to genomic instability and damage.

Detecting DNA-methylation-based biomarkers in liquid biopsies could offer a number of advantages versus mutation detection. For example, this approach offers higher sensitivity and specificity in terms of its ability to detect the early stages of cancer and residual disease, because these tissue-specific changes occur early.

Chen et al. have successfully developed the ‘PanSeer’ plasma DNA methylation panel, which comprises 477 differentially methylated regions (10,613 CpG sites).

This panel was tested with a large cohort of more than 120,000 individuals, many of whom were asymptomatic for cancer. The cohort was followed for a total of 4 years following an initial blood draw, with 191 individuals later diagnosed with esophageal, colorectal, stomach, lung, or liver cancer.

PanSeer was shown to detect five common types of cancer in 95% of asymptomatic individuals, up to 4 years before diagnosis.¹⁰

Fragmentomics

A new approach known as fragmentomics is gaining traction within the liquid biopsy cell-free DNA research field. Fragmentomic analysis examines the fragmentation patterns of the whole cfDNA population, rather than being limited to the detection of relatively few specific mutations.

This fragmentomic pattern is non-random and is representative of epigenetic regulation, with many of the fragment pool’s resultant properties useful for the detection of cancer and even its origin tissue. These properties include:

1. Fragment length distribution
2. End-motif sequences
3. Nucleosome footprint.

One recently published paper saw researchers develop novel patient-derived organoids from normal gastric, normal lung, and gastric cancer tissue.

cfDNA was extracted from the culture medium of these organoids via Norgen's plasma/serum cell-free circulating DNA purification mini kit (Cat. 55100) in both its proliferative and apoptotic states before performing fragmentomic analysis.¹¹

Fragmentomic analysis showed differences between cells in apoptosis and cells in proliferation. For example, proliferative tissues were found to be enriched for short fragments.

This study showcased the usefulness of in vitro organoid models in the study of cfDNA biology and its associated fragmentation patterns.

Helzer et al. performed fragmentomic analysis of cfDNA from plasma in research linked to prostate cancer. Fragmentation patterns covering coding regions from targeted panels were analyzed in order to lower the costs associated with whole genome sequencing.

Machine learning models of the fragmentation patterns were used to distinguish between cancer and non-cancer patients, and the specific tumor type and subtype.

This classification model worked best for prostate cancer, highest ROC AUC, highlighting that the fragmentomic analysis of cf-DNA could prove to be a promising tool for prostate cancer screening.¹²

References and further reading

1. Sobhani, N., et al. (2021). AR-V7 in Metastatic Prostate Cancer: A Strategy beyond Redemption. International Journal of Molecular Sciences, (online) 22(11), p.5515. https://doi.org/10.3390/ijms22115515.
2. Cato, L., et al. (2019). ARv7 Represses Tumor-Suppressor Genes in Castration-Resistant Prostate Cancer. Cancer Cell, 35(3), pp.401-413.e6. https://doi.org/10.1016/j.ccell.2019.01.008.
3. Maass, K.K., et al. (2021). From Sampling to Sequencing: A Liquid Biopsy Pre-Analytic Workflow to Maximize Multi-Layer Genomic Information from a Single Tube. Cancers, 13(12), p.3002. https://doi.org/10.3390/cancers13123002.
4. Lee, D., et al. (2023). Accurate Detection of Urothelial Bladder Cancer Using Targeted Deep Sequencing of Urine DNA. Cancers, 15(10), p.2868. https://doi.org/10.3390/cancers15102868.
5. Pinto, F.G., et al. (2020). Rapid Prostate Cancer Noninvasive Biomarker Screening Using Segmented Flow Mass Spectrometry-Based Untargeted Metabolomics. Journal of Proteome Research, 19(5), pp.2080–2091. https://doi.org/10.1021/acs.jproteome.0c00006.
6. Zhang, C., et al. (2022). Cell-free DNA as a Promising Diagnostic Biomarker in Prostate Cancer: A Systematic Review and Meta-Analysis. Journal of Oncology, 2022, pp.1–13. https://doi.org/10.1155/2022/1505087.
7. Cornice, J., et al. (2021). Ultrasound-Based Method for the Identification of Novel MicroRNA Biomarkers in Prostate Cancer. Genes, 12(11), pp.1726–1726. https://doi.org/10.3390/genes12111726.
8. Bhagirath, D., et al. (2018). microRNA-1246 Is an Exosomal Biomarker for Aggressive Prostate Cancer. Cancer Research, (online) 78(7), pp.1833–1844. https://doi.org/10.1158/0008-5472.CAN-17-2069.
9. Castro, E., et al. (2013). GermlineBRCAMutations Are Associated With Higher Risk of Nodal Involvement, Distant Metastasis, and Poor Survival Outcomes in Prostate Cancer. Journal of Clinical Oncology, (online) 31(14), pp.1748–1757. https://doi.org/10.1200/jco.2012.43.1882.
10. Chen, X., et al. (2020). Non-invasive early detection of cancer four years before conventional diagnosis using a blood test. Nature Communications, (online) 11(1), p.3475. https://doi.org/10.1038/s41467-020-17316-z.
11. Kim, J., et al. (2023). Multidimensional fragmentomic profiling of cell-free DNA released from patient-derived organoids. Human Genomics, 17(1). https://doi.org/10.1186/s40246-023-00533-0.
12. Helzer, K.T., et al. (2023). Fragmentomic analysis of circulating tumor DNA-targeted cancer panels. Annals of Oncology, 34(9), pp.813–825. https://doi.org/10.1016/j.annonc.2023.06.001.

Acknowledgments

Produced from materials originally authored by Norgen Biotek Corporation.

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