Liquid Biopsies in Oncology and the Current Regulatory Landscape

Proteomic Signature of Extracellular Vesicles Associated with Colorectal Cancer

The proteins of extracellular vesicles (EVs) provide proteomic signatures that reflect molecular features of EV-producing cells, including cancer cells. Detection of cancer cell EV proteins is of great interest due to the development of novel predictive diagnostic approaches. Using targeted mass spectrometry with stable-isotope-labeled peptide standards (SIS), we measured in this study the levels of 34 EV-associated proteins in vesicles and whole lysate derived from the colorectal cancer (CRC) cell lines Caco-2, HT29 and HCT116. We also evaluated the abundance of 13 EV-associated proteins (FN1, TLN1, ITGB3, HSPA8, TUBA4A, CD9, CD63, HSPG2, ITGB1, GNAI2, TSG101, PACSIN2, and CDC42) in EVs isolated from blood plasma samples from 11 CRC patients and 20 healthy volunteers. Downregulation of TLN1, ITGB3, and TUBA4A with simultaneous upregulation of HSPG2 protein were observed in cancer samples compared to healthy controls. The proteomic cargo of the EVs associated with CRC represents a promising source of potential prognostic markers.

Results from an IFCC Global Survey on Laboratory Practices for the Analysis of Circulating Tumor DNA

BACKGROUND

The clinical validity of ctDNA analysis as a diagnostic, prognostic and predictive biomarker has been demonstrated in many studies. The rapid spread of tests for the analysis of ctDNA raises questions regarding their standardization and quality assurance. The aim of this study was to provide a global overview of the test methods, laboratory procedures and quality assessment practices using ctDNA diagnostics.

METHODS

The Molecular Diagnostics Committee of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC C-MD) conducted a survey among international laboratories performing ctDNA analysis. Questions on analytical techniques, test parameters, quality assurance and the reporting of findings were included.

RESULTS

A total of 58 laboratories participated in the survey. The majority of the participating laboratories (87.7%) performed testing for patient care. Most laboratories conducted their assays for lung cancer (71.9%), followed by colorectal (52.6%) and breast (40.4%) cancer, and 55.4% of the labs used ctDNA analysis for follow-up/monitoring of treatment-resistant alterations. The most frequent gene analysed was EGFR (75.8%), followed by KRAS (65.5%) and BRAF (56.9%). Participation in external quality assessment programs was reported by only 45.6% of laboratories.

CONCLUSIONS

The survey indicates that molecular diagnostic methods for the analysis of ctDNA are not standardized across countries and laboratories. Furthermore, it reveals a number of differences regarding sample preparation, processing and reporting test results. Our findings indicate that ctDNA testing is being conducted without sufficient attention to analytical performance between laboratories and highlights the need for standarisation of ctDNA analysis and reporting in patient care.

Liquid Biopsy and Circulating Biomarkers for the Diagnosis of Precancerous and Cancerous Oral Lesions

Oral cancer is one of the most common malignancies worldwide, accounting for 2% of all cases annually and 1.8% of all cancer deaths. To date, tissue biopsy and histopathological analyses are the gold standard methods for the diagnosis of oral cancers. However, oral cancer is generally diagnosed at advanced stages with a consequent poor 5-year survival (~50%) due to limited screening programs and inefficient physical examination strategies. To address these limitations, liquid biopsy is recently emerging as a novel minimally invasive tool for the early identification of tumors as well as for the evaluation of tumor heterogeneity and prognosis of patients. Several studies have demonstrated that liquid biopsy in oral cancer could be useful for the detection of circulating biomarkers including circulating tumor DNA (ctDNA), microRNAs (miRNAs), proteins, and exosomes, thus improving diagnostic strategies and paving the way to personalized medicine. However, the application of liquid biopsy in oral cancer is still limited and further studies are needed to better clarify its clinical impact. The present manuscript aims to provide an updated overview of the potential use of liquid biopsy as an additional tool for the management of oral lesions by describing the available methodologies and the most promising biomarkers.

Evaluation of Liquid Biopsy in Patients with HER2-Positive Breast Cancer

Breast cancer is one of the common malignant tumors, and liquid biopsy has become a hot spot for clinical testing. To clarify the detection effect of liquid biopsy in breast cancer, we collected peripheral blood of HER2-positive (human epidermal growth factor receptor 2-positive) patients. Circulating tumor cells (CTCs) were isolated and analyzed. HER2 expression on CTCs was detected. The results showed that in the 198 HER2-positive samples, the CTC detection rate was 79.8% (158/198), and the mean number of CTCs was 21, ranging from 1 to 63/7.5 mL peripheral blood. Only 41.1% (65/158) of patients had histology and CTC HER2 status consistent with the remaining 58.9% (93/158) of patients, although their histological HER2 was positive, and CTC HER2 was negative. Our study confirmed the value of CTC HER2 real-time status testing in HER2-positive breast cancer patients. The inconsistency in HER2 status between CTCs and histology may be related to the time interval between CTCs and histological HER2 detection, suggesting that real-time HER2 detection is necessary for histological HER2-positive patients.

Machine Learning Protocols in Early Cancer Detection Based on Liquid Biopsy: A Survey

With the advances of liquid biopsy technology, there is increasing evidence that body fluid such as blood, urine, and saliva could harbor the potential biomarkers associated with tumor origin. Traditional correlation analysis methods are no longer sufficient to capture the high-resolution complex relationships between biomarkers and cancer subtype heterogeneity. To address the challenge, researchers proposed machine learning techniques with liquid biopsy data to explore the essence of tumor origin together. In this survey, we review the machine learning protocols and provide corresponding code demos for the approaches mentioned. We discuss algorithmic principles and frameworks extensively developed to reveal cancer mechanisms and consider the future prospects in biomarker exploration and cancer diagnostics.

Early diagnosis of lung cancer: which is the optimal choice?

The prognosis of lung cancer patients with different clinical stages is significantly different. The 5-year survival of stage IA groups can exceed 90%, while patients with stage IV can be less than 10%. Therefore, early diagnosis is extremely important for lung cancer patients. This research focused on various diagnosis methods of early lung cancer, including imaging screening, bronchoscopy, and emerging potential liquid biopsies, as well as volatile organic compounds, autoantibodies, aiming to improve the early diagnosis rate and explore feasible and effective early diagnosis strategies.

Post-SELEX Optimization and Characterization of a Prostate Cancer Cell-Specific Aptamer for Diagnosis

The RNA aptamer A4 binds specifically to tumor prostate cells. A4 was modified (mA4) by adding deoxyribonucleotides to its ends to remove the reactive 2' hydroxyl groups of RNA's sugar at the ends of the aptamer and to make it more stable to widespread RNase contamination in laboratories. Thus, mA4 would be more suitable to use in the clinical settings of prostate cancer (PCa). We aimed to characterize this optimized oligonucleotide to verify its potential as a diagnostic tool. The sequences and structures of A4 and mA4 were compared through in silico approaches to corroborate their similarity. Then, the degradation of mA4 was measured in appropriate media and human plasma for in vitro tests. In addition, the binding abilities of A4 to prostate cells were contrasted with those of mA4. The effects of mA4 were assessed on the viability, proliferation, and migration of human prostate cell lines RWPE-1 and PC-3 in three-dimensional (3D) cell cultures. mA4 showed configurational motifs similar to those of A4, displayed a half-life in plasma substantially higher than A4, and exhibited a comparable binding capacity to that of A4 and unaltered viability, proliferation, and migration of prostatic cells. Therefore, mA4 maintains the crucial 3D structures of A4 that would allow binding to its target, as suggested by in silico and binding analyses. mA4 may be a good PCa reporter as it does not change cellular parameters of prostate cells when incubated with it. Its additional deoxyribonucleotides make mA4 inherently more chemically stable than A4, avoiding its degradation and favoring its storage and handling for clinical applications. These characteristics support the potential of mA4 to be used in diagnostic systems for PCa.

Cell-free DNA diagnostics: current and emerging applications in oncology

Liquid biopsy is a noninvasive dynamic approach for monitoring disease over time. It offers advantages including limited risks of blood sampling, opportunity for more frequent sampling, lower costs and theoretically non-biased sampling compared with tissue biopsy. There is a high degree of concordance between circulating tumor DNA mutations versus primary tumor mutations. Remote sampling of circulating tumor DNA can serve as viable option in clinical diagnostics. Here, we discuss the progress toward broad adoption of liquid biopsy as a diagnostic tool and discuss knowledge gaps that remain to be addressed.

Radiomics and liquid biopsy in oncology: the holons of systems medicine

Abstract

Radiomics is a process of extraction and analysis of quantitative features from diagnostic images. Liquid biopsy is a test done on a sample of blood to look for cancer cells or for pieces of tumourigenic DNA circulating in the blood. Radiomics and liquid biopsy have great potential in oncology, since both are minimally invasive, easy to perform, and can be repeated in patient follow-up visits, enabling the extraction of valuable information regarding tumour type, aggressiveness, progression, and response to treatment. Both methods are in their infancy, with major evidence of application in lung and gastrointestinal cancer, while still undergoing evaluation in other cancer types. In this paper, the main oncologic applications of radiomics and liquid biopsy are reviewed, and a synergistic approach incorporating both tests for cancer diagnosis and follow-up is discussed within the context of systems medicine.

Teaching Points

• Radiomics is a process of extraction and analysis of quantitative features from diagnostic images.

• Most clinical applications of radiomics are in the field of oncologic imaging.

• Radiomics applies to all imaging modalities.

• A cluster of radiomic features is a “radiomic signature”.

• Machine learning may improve the efficacy of radiomics analysis.

[Progress of Liquid Biopsy in Early Diagnosis of Lung Cancer]

肺癌的早期诊断有利于提高患者的生存率。应用影像学方法对肺癌高风险人群进行筛查，可以起到早发现、早诊断的作用。越来越多的研究显示，液体活检（liquid biopsy）可以对该方法进行替代和补充。检测肺癌患者外周血中的循环肿瘤细胞（circulating tumor cells, CTCs）、循环肿瘤DNA（circulating tumor DNA, ctDNA）、微小核糖核酸（microRNA, miRNA）、外泌体（exosomes）、肿瘤血小板（tumor educated platelets, TEPs）可以用于肺癌的早期诊断，并且可能为影像学检查阴性的高风险人群提供相应的诊疗建议。全文就以上标志物的检测手段、在肺癌早期诊断中的价值以及存在优势与局限性进行综述，以期促进液体活检在肺癌早期诊断、与其他筛查手段相结合方面的应用。

Liquid biopsy for early detection of lung cancer

PURPOSE OF REVIEW

The possibility of complete recovery for a lung cancer patient depends on very early diagnosis, as it allows total surgical resection. Screening for this cancer in a high-risk population can be performed using a radiological approach, but this holds a certain number of limitations. Liquid biopsy could become an alternative and complementary screening approach to chest imaging for early diagnosis of lung cancer.

RECENT FINDINGS

Several circulating biomarkers indicative of lung cancer can be investigated in blood, such as circulating tumor cells, circulating free nucleic acids (RNA and DNA) and proteins. However, none of these biomarkers have yet been adopted in routine clinical practice and studies are ongoing to confirm or not the usefulness and practical interest in routine early diagnosis and screening for lung cancers.

SUMMARY

Several potential circulating biomarkers for the early detection of lung cancer exist. When coupled to thoracic imaging, these biomarkers must give diagnosis of a totally resectable lung cancer and potentially provide new recommendations for surveillance by imagery of high-risk populations without a detectable nodule. Optimization of the specificity and sensitivity of the detection methods as well as standardization of the techniques is essential before considering for daily practice a liquid biopsy as an early diagnostic tool, or possibly as a predictive test, of lung cancer.

Implementation of a Precision Pathology Program Focused on Oncology-Based Prognostic and Predictive Outcomes

Personalized or precision medicine as a diagnostic and therapeutic paradigm was introduced some 10-15 years ago, with the advent of biomarker discovery as a mechanism for identifying prognostic and predictive attributes associated with treatment indication and outcome. While the concept is not new, the successful development and implementation of novel 'companion diagnostics', especially in oncology, continues to represent a significant challenge and is currently at the forefront of smart trial design and therapeutic choice. The ability to determine patient selection for a specific therapy has broad implications including better chances for a positive outcome, limited exposure to potentially toxic drugs and improved health economics. Importantly, a significant step in this paradigm is the role of predictive pathology or the accurate assessment of morphology at the microscopic level. In breast cancer, this has been most useful where histologic attributes such as the classification of tubular and cribriform carcinoma dictates surgery while neoadjuvant studies suggest that patients with lobular carcinoma are not likely to benefit from chemotherapy. The next level of 'personalized pathology' at the tissue-cellular level is the use of 'protein biomarker panels' to classify the disease process and ultimately drive tumor characterization and treatment. The following review article will focus on the evolution of predictive pathology from a subjective, 'opinion-based' approach to a quantitative science. In addition, we will discuss the individual components of the precise pathology platform including advanced image analysis, biomarker quantitation with mathematical modeling and the integration with fluid-based (i.e. blood, urine) analytics as drivers of next generation precise patient phenotyping.

Integrating precision cancer medicine into healthcare-policy, practice, and research challenges

Precision medicine (PM) can be defined as a predictive, preventive, personalized, and participatory healthcare service delivery model. Recent developments in molecular biology and information technology make PM a reality today through the use of massive amounts of genetic, ‘omics’, clinical, environmental, and lifestyle data. With cancer being one of the most prominent public health threats in developed countries, both the research community and governments have been investing significant time, money, and efforts in precision cancer medicine (PCM). Although PCM research is extremely promising, a number of hurdles still remain on the road to an optimal integration of standardized and evidence-based use of PCM in healthcare systems. Indeed, PCM raises a number of technical, organizational, ethical, legal, social, and economic challenges that have to be taken into account in the development of an appropriate health policy framework. Here, we highlight some of the more salient issues regarding the standards needed for integration of PCM into healthcare systems, and we identify fields where more research is needed before policy can be implemented. Key challenges include, but are not limited to, the creation of new standards for the collection, analysis, and sharing of samples and data from cancer patients, and the creation of new clinical trial designs with renewed endpoints. We believe that these issues need to be addressed as a matter of priority by public health policymakers in the coming years for a better integration of PCM into healthcare.