Liquid Biopsy-Based Biomarkers of Treatment Response and Resistance

Biomechanics of circulating cellular and subcellular bioparticles: beyond separation

Biomechanical attributes have emerged as novel markers, providing a reliable means to characterize cellular and subcellular fractions. Numerous studies have identified correlations between these factors and patients' medical status. However, the absence of a thorough overview impedes their applicability in contemporary state-of-the-art therapeutic strategies. In this context, we provide a comprehensive analysis of the dimensions, configuration, rigidity, density, and electrical characteristics of normal and abnormal circulating cells. Subsequently, the discussion broadens to encompass subcellular bioparticles, such as extracellular vesicles (EVs) enriched either from blood cells or other tissues. Notably, cell sizes vary significantly, from 2 μm for platelets to 25 μm for circulating tumor cells (CTCs), enabling the development of size-based separation techniques, such as microfiltration, for specific diagnostic and therapeutic applications. Although cellular density is relatively constant among different circulating bioparticles, it allows for reliable density gradient centrifugation to isolate cells without altering their native state. Additionally, variations in EV surface charges (-6.3 to -45 mV) offer opportunities for electrophoretic and electrostatic separation methods. The distinctive mechanical properties of abnormal cells, compared to their normal counterparts, present an exceptional opportunity for diverse medical and biotechnological approaches. This review also aims to provide a holistic view of the current understanding of popular techniques in this domain that transcend conventional boundaries, focusing on early harvesting of malignant cells from body fluids, designing effective therapeutic options, cell targeting, and resonating with tissue and genetic engineering principles.

Frameshift mutations in peripheral blood as a biomarker for surveillance of Lynch syndrome

BACKGROUND

Lynch syndrome is a hereditary cancer predisposition syndrome caused by germline mutations in DNA mismatch repair genes, which lead to high microsatellite instability and frameshift mutations at coding mononucleotide repeats in the genome. Recurrent frameshift mutations in these regions are thought to play a central role in the increased risk of various cancers, but no biomarkers are currently available for the surveillance of high microsatellite instability-associated cancers.

METHODS

A frameshift mutation-based biomarker panel was developed and validated by targeted next-generation sequencing of supernatant DNA from cultured high microsatellite instability colorectal cancer cells. This panel supported selection of 122 frameshift mutation targets as potential biomarkers. This biomarker panel was then tested using matched tumor, adjacent normal tissue, and buffy coat samples (53 samples) and blood-derived cell-free DNA (cfDNA) (38 samples) obtained from 45 high microsatellite instability and mismatch repair-deficient patients. We also sequenced cfDNA from 84 healthy participants to assess background noise.

RESULTS

Recurrent frameshift mutations at coding mononucleotide repeats were detectable not only in tumors but also in cfDNA from high microsatellite instability and mismatch repair-deficient patients, including a Lynch syndrome carrier, with a varying range of target detection (up to 85.2%), whereas they were virtually undetectable in healthy participants. Receiver operating characteristic curve analysis showed high sensitivity and specificity (area under the curve = 0.94) of the investigated panel.

CONCLUSIONS

We demonstrated that frameshift mutations can be detected in cfDNA from high microsatellite instability and mismatch repair-deficient patients and asymptomatic carriers. The 122-target frameshift mutation panel described here has promise as a tool for improved surveillance of high microsatellite instability and mismatch repair-deficient patients, with the potential to reduce the frequency of invasive screening methods for this high-cancer-risk cohort.

Recent advances in chemical biology tools for protein and RNA profiling of extracellular vesicles

Extracellular vesicles (EVs) are nano-sized vesicles secreted by cells that contain various cellular components such as proteins, nucleic acids, and lipids from the parent cell. EVs are abundant in body fluids and can serve as circulating biomarkers for a variety of diseases or as a regulator of various biological processes. Considering these characteristics of EVs, analysis of the EV cargo has been spotlighted for disease diagnosis or to understand biological processes in biomedical research. Over the past decade, technologies for rapid and sensitive analysis of EVs in biofluids have evolved, but detection and isolation of targeted EVs in complex body fluids is still challenging due to the unique physical and biological properties of EVs. Recent advances in chemical biology provide new opportunities for efficient profiling of the molecular contents of EVs. A myriad of chemical biology tools have been harnessed to enhance the analytical performance of conventional assays for better understanding of EV biology. In this review, we will discuss the improvements that have been achieved using chemical biology tools.

Detection of lung cancer through SERS analysis of serum

Early detection and postoperative assessment are crucial for improving overall survival among lung cancer patients. Here, we report a non-invasive technique that integrates Raman spectroscopy with machine learning for the detection of lung cancer. The study encompassed 88 postoperative lung cancer patients, 73 non-surgical lung cancer patients, and 68 healthy subjects. The primary aim was to explore variations in serum metabolism across these cohorts. Comparative analysis of average Raman spectra was conducted, while principal component analysis was employed for data visualization. Subsequently, the augmented dataset was used to train convolutional neural networks (CNN) and Resnet models, leading to the development of a diagnostic framework. The CNN model exhibited superior performance, as verified by the receiver operating characteristic curve. Notably, postoperative patients demonstrated an increased likelihood of recurrence, emphasizing the crucial need for continuous postoperative monitoring. In summary, the integration of Raman spectroscopy with CNN-based classification shows potential for early detection and postoperative assessment of lung cancer.

A Molecular Voyage: Multiomics Insights into Circulating Tumor Cells

Circulating tumor cells (CTCs) play a pivotal role in metastasis, the leading cause of cancer-associated death. Recent improvements of CTC isolation tools, coupled with a steady development of multiomics technologies at single-cell resolution, have enabled an extensive exploration of CTC biology, unlocking insights into their molecular profiles. A detailed molecular portrait requires CTC interrogation across various levels encompassing genomic, epigenetic, transcriptomic, proteomic and metabolic features. Here, we review how state-of-the-art multiomics applied to CTCs are shedding light on how cancer spreads. Further, we highlight the potential implications of CTC profiling for clinical applications aimed at enhancing cancer diagnosis and treatment.

SIGNIFICANCE

Exploring the complexity of cancer progression through cutting-edge multiomics studies holds the promise of uncovering novel aspects of cancer biology and identifying therapeutic vulnerabilities to suppress metastasis.

Analysis of cell free DNA to predict outcome to bevacizumab therapy in colorectal cancer patients

To predict outcome to combination bevacizumab (BVZ) therapy, we employed cell-free DNA (cfDNA) to determine chromosomal instability (CIN), nucleosome footprints (NF) and methylation profiles in metastatic colorectal cancer (mCRC) patients. Low-coverage whole-genome sequencing (LC-WGS) was performed on matched tumor and plasma samples, collected from 74 mCRC patients from the AC-ANGIOPREDICT Phase II trial (NCT01822444), and analysed for CIN and NFs. A validation cohort of plasma samples from the University Medical Center Mannheim (UMM) was similarly profiled. 61 AC-ANGIOPREDICT plasma samples collected before and following BVZ treatment were selected for targeted methylation sequencing. Using cfDNA CIN profiles, AC-ANGIOPREDICT samples were subtyped with 92.3% accuracy into low and high CIN clusters, with good concordance observed between matched plasma and tumor. Improved survival was observed in CIN-high patients. Plasma-based CIN clustering was validated in the UMM cohort. Methylation profiling identified differences in CIN-low vs. CIN high (AUC = 0.87). Moreover, significant methylation score decreases following BVZ was associated with improved outcome (p = 0.013). Analysis of CIN, NFs and methylation profiles from cfDNA in plasma samples facilitates stratification into CIN clusters which inform patient response to treatment.

Increased blood draws for ultrasensitive ctDNA and CTCs detection in early breast cancer patients

Early breast cancer patients often experience relapse due to residual disease after treatment. Liquid biopsy is a methodology capable of detecting tumor components in blood, but low concentrations at early stages pose challenges. To detect them, next-generation sequencing has promise but entails complex processes. Exploring larger blood volumes could overcome detection limitations. Herein, a total of 282 high-volume plasma and blood-cell samples were collected for dual ctDNA/CTCs detection using a single droplet-digital PCR assay per patient. ctDNA and/or CTCs were detected in 100% of pre-treatment samples. On the other hand, post-treatment positive samples exhibited a minimum variant allele frequency of 0.003% for ctDNA and minimum cell number of 0.069 CTCs/mL of blood, surpassing previous investigations. Accurate prediction of residual disease before surgery was achieved in patients without a complete pathological response. A model utilizing ctDNA dynamics achieved an area under the ROC curve of 0.92 for predicting response. We detected disease recurrence in blood in the three patients who experienced a relapse, anticipating clinical relapse by 34.61, 9.10, and 7.59 months. This methodology provides an easily implemented alternative for ultrasensitive residual disease detection in early breast cancer patients.

Liquid biopsy in H3K27M diffuse midline glioma

Diffuse midline glioma (DMG) with H3K27M mutation is an aggressive and difficult to treat pediatric brain tumor. Recurrent gain of function mutations in H3.3 (H3.3A) and H3.1 (H3C2) at the 27th lysine to methionine (H3K27M) are seen in over 2/3 of DMGs, and are associated with a worse prognosis. Due to the anatomical location of DMG, traditional biopsy carries risk for neurologic injury as it requires penetration of vital midline structures. Further, radiographic (MRI) monitoring of DMG often shows nonspecific changes, which makes therapeutic monitoring difficult. This indicates a critical need for more minimally invasive methods, such as liquid biopsy, to understand, diagnose, and monitor H3K27M DMG. Here, we review the use of all modalities to date to detect biomarkers of H3K27M in cerebrospinal fluid (CSF), blood, and urine, and compare their effectiveness in detection, diagnosis, and monitoring treatment response. We provide specific detail of recent efforts to monitor CSF and plasma H3K27M cell-free DNA in patients undergoing therapy with the imipridone ONC201. Lastly, we discuss the future of therapeutic monitoring of H3K27M-DMG, including biomarkers such as mitochondrial DNA, mutant and modified histones, and novel sequencing-based approaches for improved detection methods.

Noninvasive Blood-Based Cancer Detection in Veterinary Medicine

The past decade has seen incredible advances in blood-based cancer detection in people and in dogs - yet this represents only a glimpse of the benefits these tests can provide to patients. The clinical uses of this technology range from screening asymptomatic individuals for early detection to use as an aid in diagnosis when cancer is suspected, to cancer monitoring both during and after treatment. This article summarizes the benefits of early cancer detection and examines use cases and methods of blood-based cancer detection in dogs, including quantitative, qualitative, and alternative approaches.

Circulating tumour DNA detects somatic variants contributing to spatial and temporal intra-tumoural heterogeneity in head and neck squamous cell carcinoma

Background

As circulating tumour DNA (ctDNA) liquid biopsy analysis is increasingly incorporated into modern oncological practice, establishing the impact of genomic intra-tumoural heterogeneity (ITH) upon data output is paramount. Despite advances in other cancer types the evidence base in head and neck squamous cell carcinoma (HNSCC) remains poor. We sought to investigate the utility of ctDNA to detect ITH in HNSCC.

Methods

In a pilot cohort of 9 treatment-naïve HNSCC patients, DNA from two intra-tumoural sites (core and margin) was whole-exome sequenced. A 9-gene panel was designed to perform targeted sequencing on pre-treatment plasma cell-free DNA and selected post-treatment samples.

Results

Rates of genomic ITH among the 9 patients was high. COSMIC variants from 19 TCGA HNSCC genes demonstrated an 86.9% heterogeneity rate (present in one tumour sub-site only). Across all patients, cell-free DNA (ctDNA) identified 12.9% (range 7.5-19.8%) of tumour-specific variants, of which 55.6% were specific to a single tumour sub-site only. CtDNA identified 79.0% (range: 55.6-90.9%) of high-frequency variants (tumour VAF>5%). Analysis of ctDNA in serial post-treatment blood samples in patients who suffered recurrence demonstrated dynamic changes in both tumour-specific and acquired variants that predicted recurrence ahead of clinical detection.

Conclusion

We demonstrate that a ctDNA liquid biopsy identified spatial genomic ITH in HNSCC and reliably detected high-frequency driver mutations. Serial sampling allowed post-treatment surveillance and early identification of treatment failure.

Assessing the complementary information from an increased number of biologically relevant features in liquid biopsy-derived RNA-Seq data

Liquid biopsy-derived RNA sequencing (lbRNA-seq) exhibits significant promise for clinic-oriented cancer diagnostics due to its non-invasiveness and ease of repeatability. Despite substantial advancements, obstacles like technical artefacts and process standardisation impede seamless clinical integration. Alongside addressing technical aspects such as normalising fluctuating low-input material and establishing a standardised clinical workflow, the lack of result validation using independent datasets remains a critical factor contributing to the often low reproducibility of liquid biopsy-detected biomarkers. Considering the outlined drawbacks, our objective was to establish a workflow/methodology characterised by: 1. Harness the rich diversity of biological features accessible through lbRNA-seq data, encompassing a holistic range of molecular and functional attributes. These components are seamlessly integrated via a Machine Learning-based Ensemble Classification framework, enabling a unified and comprehensive analysis of the intricate information encoded within the data. 2. Implementing and rigorously benchmarking intra-sample normalisation methods to heighten their relevance within clinical settings. 3. Thoroughly assessing its efficacy across independent test sets to ascertain its robustness and potential utility. Using ten datasets from several studies comprising three different sources of biological material, we first show that while the best-performing normalisation methods depend strongly on the dataset and coupled Machine Learning method, the rather simple Counts Per Million method is generally very robust, showing comparable performance to cross-sample methods. Subsequently, we demonstrate that the innovative biofeature types introduced in this study, such as the Fraction of Canonical Transcript, harbour complementary information. Consequently, their inclusion consistently enhances prediction power compared to models relying solely on gene expression-based biofeatures. Finally, we demonstrate that the workflow is robust on completely independent datasets, generally from different labs and/or different protocols. Taken together, the workflow presented here outperforms generally employed methods in prediction accuracy and may hold potential for clinical diagnostics application due to its specific design.

Small extracellular vesicles from surviving cancer cells as multiparametric monitoring tools of measurable residual disease and therapeutic efficiency

Although conventional anti-cancer therapies remove most cells of the tumor mass, small surviving populations may evolve adaptive resistance strategies, which lead to treatment failure. The size of the resistant population initially may not reach the threshold of clinical detection (designated as measurable residual disease/MRD) thus, its investigation requires highly sensitive and specific methods. Here, we discuss that the specific molecular fingerprint of tumor-derived small extracellular vesicles (sEVs) is suitable for longitudinal monitoring of MRD. Furthermore, we present a concept that exploiting the multiparametric nature of sEVs may help early detection of recurrence and the design of dynamic, evolution-adjusted treatments.

Tumor- and circulating-free DNA methylation identifies clinically relevant small cell lung cancer subtypes

Small cell lung cancer (SCLC) is an aggressive malignancy composed of distinct transcriptional subtypes, but implementing subtyping in the clinic has remained challenging, particularly due to limited tissue availability. Given the known epigenetic regulation of critical SCLC transcriptional programs, we hypothesized that subtype-specific patterns of DNA methylation could be detected in tumor or blood from SCLC patients. Using genomic-wide reduced-representation bisulfite sequencing (RRBS) in two cohorts totaling 179 SCLC patients and using machine learning approaches, we report a highly accurate DNA methylation-based classifier (SCLC-DMC) that can distinguish SCLC subtypes. We further adjust the classifier for circulating-free DNA (cfDNA) to subtype SCLC from plasma. Using the cfDNA classifier (cfDMC), we demonstrate that SCLC phenotypes can evolve during disease progression, highlighting the need for longitudinal tracking of SCLC during clinical treatment. These data establish that tumor and cfDNA methylation can be used to identify SCLC subtypes and might guide precision SCLC therapy.

Serological Exosome Metabolic Biopsy of Hepatocellular Carcinoma via Designed Core-Shell Nanoparticles

Exosome metabolite-based liquid biopsy is a promising strategy for large-scale application in practical clinics toward precise medicine. Given the current challenges in successive isolation and analysis of exosomes and their metabolites in this field, we established a low-cost, high-throughput, and rapid platform for serological exosome metabolic biopsy of hepatocellular carcinoma (HCC) via designed core-shell nanoparticles. It starts with the efficient extraction of high-quality serum exosomes and exosome metabolic features, based on which significantly obvious sample clusters are observed by unsupervised cluster analysis. The following integration of feature selection and supervised machine learning enables the identification of six key metabolites and achieves high-performance prediction between HCC, liver cirrhosis, and healthy controls. Specifically, both sensitivity and accuracy achieve 100% among any pairwise intergroup discrimination in a blind test. The quality and reliability of six key metabolites are further evaluated and validated by using different machine learning algorithms and pathway exploration. Our platform contributes to the future growth of new liquid biopsy technologies for precision diagnosis and real-time monitoring of HCC, among other conditions.

Liquid biopsy for precision diagnostics and therapeutics

Liquid biopsy (LB) has emerged as a highly promising and non-invasive diagnostic approach, particularly in the field of oncology, and has garnered interest in various medical disciplines. This technique involves the examination of biomolecules released into physiological fluids, such as urine samples, blood, and cerebrospinal fluid (CSF). The analysed biomolecules included circulating tumour DNA (ctDNA), circulating tumour cells (CTCs), cell-free DNA (cfDNA), exosomes, and other cell-free components. In contrast to conventional tissue biopsies, LB provides minimally invasive diagnostics, offering invaluable insights into tumor characteristics, treatment response, and early disease detection. This Review explores the contemporary landscape of technologies and clinical applications in the realm of LB, with a particular emphasis on the isolation and analysis of ctDNA and/or cfDNA. Various methodologies have been employed, including droplet digital polymerase chain reaction (DDP), BEAMing (beads, emulsion, amplification, and magnetics), TAm-Seq (tagged-amplicon deep sequencing), CAPP-Seq (cancer personalized profiling by deep sequencing), WGBS-Seq (whole genome bisulfite sequencing), WES (whole exome sequencing), and WGS (whole-genome sequencing). Additionally, CTCs have been successfully isolated through biomarker-based cell capture, employing both positive and negative enrichment strategies based on diverse biophysical and other inherent properties. This approach also addresses challenges and limitations associated with liquid biopsy techniques, such as sensitivity, specificity, standardization and interpretability of findings. This review seeks to identify the current technologies used in liquid biopsy samples, emphasizing their significance in identifying tumor markers for cancer detection, prognosis, and treatment outcome monitoring.

liquid biopsy holds a promising approach for the early detection of cancer: Current information and future perspectives

Cancer is becoming a global pandemic, and its occurrence is increasing rapidly, putting a strain on people's families, health systems, and finances, in addition to their physical, mental, and emotional well-being. Many cancer types lack screening programs, and many people at high risk of developing cancer do not follow recommended medical screening regimens because of the nature of currently available screening tests and other compliance issues, despite cancer being the second leading cause of death worldwide. Furthermore, a lot of liquid biopsy methods for early cancer screening are not sensitive enough to catch cancer early. Cancer treatment costs increase with the time it takes to diagnose the disease; therefore, early detection is essential to enhance the quality of life and survival rates. The current status of the liquid biopsy sector is examined in this paper.

Cell-Free Tumor DNA Detection-Based Liquid Biopsy of Plasma and Bile in Patients with Various Pancreatic Neoplasms

The key challenge of cell-free tumor DNA (cftDNA) analysis in pancreatic ductal adenocarcinoma (PDAC) is overcoming its low detection rate, which is mainly explained by the overall scarcity of this biomarker in plasma. Obstructive jaundice is a frequent event in PDAC, which enables bile collection as a part of routine treatment. The aim of this study was to evaluate the performance of KRAS-mutated cftDNA detection-based liquid biopsy of plasma and bile in patients with pancreatic neoplasms using digital droplet PCR. The study included healthy volunteers (n = 38), patients with PDAC (n = 95, of which 20 had obstructive jaundice) and other pancreatic neoplasms (OPN) (n = 18). The sensitivity and specificity compared to the control group were 61% and 100% (AUC-ROC-0.805), and compared to the OPN group, they were 61% and 94% (AUC-ROC-0.794), respectively. Bile exhibited higher cftDNA levels than plasma (248.6 [6.743; 1068] vs. 3.26 [0; 19.225] copies/mL) and a two-fold higher detection rate (p < 0.01). Plasma cftDNA levels were associated with distant metastases, tumor size, and CA 19-9 (p < 0.05). The probability of survival was worse in patients with higher levels of cftDNA in plasma (hazard ratio-2.4; 95% CI: 1.3-4.6; p = 0.005) but not in bile (p > 0.05). Bile is a promising alternative to plasma in patients with obstructive jaundice, at least for the diagnostic purposes of liquid biopsy.

Predicting patient outcomes after treatment with immune checkpoint blockade: A review of biomarkers derived from diverse data modalities

Immune checkpoint blockade (ICB) therapy targeting cytotoxic T-lymphocyte-associated protein 4, programmed death 1, and programmed death ligand 1 has shown durable remission and clinical success across different cancer types. However, patient outcomes vary among disease indications. Studies have identified prognostic biomarkers associated with immunotherapy response and patient outcomes derived from diverse data types, including next-generation bulk and single-cell DNA, RNA, T cell and B cell receptor sequencing data, liquid biopsies, and clinical imaging. Owing to inter- and intra-tumor heterogeneity and the immune system's complexity, these biomarkers have diverse efficacy in clinical trials of ICB. Here, we review the genetic and genomic signatures and image features of ICB studies for pan-cancer applications and specific indications. We discuss the advantages and disadvantages of computational approaches for predicting immunotherapy effectiveness and patient outcomes. We also elucidate the challenges of immunotherapy prognostication and the discovery of novel immunotherapy targets.

Point-of-Care Testing for the Detection of MicroRNAs: Towards Liquid Biopsy on a Chip

Point-of-care (PoC) testing is revolutionizing the healthcare sector improving patient care in daily hospital practice and allowing reaching even remote geographical areas. In the frame of cancer management, the design and validation of PoC enabling the non-invasive, rapid detection of cancer markers is urgently required to implement liquid biopsy in clinical practice. Therefore, focusing on stable blood-based markers with high-specificity, such as microRNAs, is of crucial importance. In this work, we highlight the potential impact of circulating microRNAs detection on cancer management and the crucial role of PoC testing devices, especially for low-income countries. A detailed discussion about the challenges that should be faced to promote the technological transfer and clinical use of these tools has been added, to provide the readers with a complete overview of potentialities and current limitations.

Recommendations for Cell-Free DNA Assay Validations: A Joint Consensus Recommendation of the Association for Molecular Pathology and College of American Pathologists

Diagnosing, selecting therapy for, and monitoring cancer in patients using a minimally invasive blood test represents a significant advance in precision medicine. Wide variability exists in how circulating tumor DNA (ctDNA) assays are developed, validated, and reported in the literature, which hinders clinical adoption and may negatively impact patient care. Standardization is needed for factors affecting ctDNA assay performance and reporting, including pre-analytical variables, analytical considerations, and elements of laboratory assay reporting. The Association for Molecular Pathology Clinical Practice Committee's Liquid Biopsy Working Group (LBxWG), including organizational representation from the American Society of Clinical Oncology and the College of American Pathologists, has undertaken a full-text data extraction of 1228 ctDNA publications that describe assays performed in patients with lymphoma and solid tumor malignancies. With an emphasis on clinical assay validation, the LBxWG has developed a set of 13 best practice consensus recommendations for validating, reporting, and publishing clinical ctDNA assays. Recommendations include reporting key pre-analytical considerations and assay performance metrics; this analysis demonstrates these elements are inconsistently included in publications. The LBxWG recommendations are intended to assist clinical laboratories with validating and reporting ctDNA assays and to ensure high-quality data are included in publications. It is expected that these recommendations will need to be updated as the body of literature continues to mature.

Circulating tumor DNA as liquid biopsy in lung cancer: Biological characteristics and clinical integration

Lung cancer maintains high morbidity and mortality rate globally despite significant advancements in diagnosis and treatment in the era of precision medicine. Pathological analysis of tumor tissue, the current gold standard for lung cancer diagnosis, is intrusive and intrinsically confined to evaluating the limited amount of tissues that could be physically extracted. However, tissue biopsy has several limitations, including the invasiveness of the procedure and difficulty in obtaining samples for patients at advanced stages., there Additionally,has been no major breakthrough in tumor biomarkers with high specificity and sensitivity, particularly for early-stage lung cancer. Liquid biopsy has been considered a feasible auxiliary tool for tearly dianosis, evaluating treatment responses and monitoring prognosis of lung cancer. Circulating tumor DNA (ctDNA), an ideal biomarker of liquid biopsy, has emerged as one of the most reliable tools for monitoring tumor processes at molecular levels. Herein, this review focuses on tumor heterogeneity to elucidate the superiority of liquid biopsy and retrospectively discussdeciphersolution. We systematically elaborate ctDNA biological characteristics, introduce methods for ctDNA detection, and discuss the current role of plasma ctDNA in lung cancer management. Finally, we summarize the drawbacks of ctDNA analysis and highlight its potential clinical application in lung cancer.

Integration of liquid biopsy and immunotherapy: opening a new era in colorectal cancer treatment

Immunotherapy has revolutionized the conventional treatment approaches for colorectal cancer (CRC), offering new therapeutic prospects for patients. Liquid biopsy has shown significant potential in early screening, diagnosis, and postoperative monitoring by analyzing circulating tumor cells (CTC) and circulating tumor DNA (ctDNA). In the era of immunotherapy, liquid biopsy provides additional possibilities for guiding immune-based treatments. Emerging technologies such as mass spectrometry-based detection of neoantigens and flow cytometry-based T cell sorting offer new tools for liquid biopsy, aiming to optimize immune therapy strategies. The integration of liquid biopsy with immunotherapy holds promise for improving treatment outcomes in colorectal cancer patients, enabling breakthroughs in early diagnosis and treatment, and providing patients with more personalized, precise, and effective treatment strategies.

Extracellular vesicle-based liquid biopsy biomarkers and their application in precision immuno-oncology

While the field of precision oncology is rapidly expanding and more targeted options are revolutionizing cancer treatment paradigms, therapeutic resistance particularly to immunotherapy remains a pressing challenge. This can be largely attributed to the dynamic tumor-stroma interactions that continuously alter the microenvironment. While to date most advancements have been made through examining the clinical utility of tissue-based biomarkers, their invasive nature and lack of a holistic representation of the evolving disease in a real-time manner could result in suboptimal treatment decisions. Thus, using minimally-invasive approaches to identify biomarkers that predict and monitor treatment response as well as alert to the emergence of recurrences is of a critical need. Currently, research efforts are shifting towards developing liquid biopsy-based biomarkers obtained from patients over the course of disease. Liquid biopsy represents a unique opportunity to monitor intercellular communication within the tumor microenvironment which could occur through the exchange of extracellular vesicles (EVs). EVs are lipid bilayer membrane nanoscale vesicles which transfer a plethora of biomolecules that mediate intercellular crosstalk, shape the tumor microenvironment, and modify drug response. The capture of EVs using innovative approaches, such as microfluidics, magnetic beads, and aptamers, allow their analysis via high throughput multi-omics techniques and facilitate their use for biomarker discovery. Artificial intelligence, using machine and deep learning algorithms, is advancing multi-omics analyses to uncover candidate biomarkers and predictive signatures that are key for translation into clinical trials. With the increasing recognition of the role of EVs in mediating immune evasion and as a valuable biomarker source, these real-time snapshots of cellular communication are promising to become an important tool in the field of precision oncology and spur the recognition of strategies to block resistance to immunotherapy. In this review, we discuss the emerging role of EVs in biomarker research describing current advances in their isolation and analysis techniques as well as their function as mediators in the tumor microenvironment. We also highlight recent lung cancer and melanoma studies that point towards their application as predictive biomarkers for immunotherapy and their potential clinical use in precision immuno-oncology.

Gene Expression and DNA Methylation as Prognostic Markers in Metastatic Castration-Resistant Prostate Cancer: Analysis of Circulating Tumor Cells and Paired Plasma-Derived Exosomes

Prostate cancer (PCa) is the most prevalent cancer among men and is the second leading cause of cancer-related death in the United States [...].

5-hydroxymethylcytosine sequencing in plasma cell-free DNA identifies unique epigenomic features in prostate cancer patients resistant to androgen deprivation therapy

Background

Currently there are no biomarkers to identify resistance to androgen-deprivation therapy (ADT) in men with hormone-naive prostate cancer. 5-hydroxymethylcytosines (5hmC) in the gene body are associated with gene activation and are critical for epigenomic regulation of cancer progression.

Objective

To evaluate whether 5hmC signature in cell-free DNA (cfDNA) predicts early ADT resistance.

Design Setting and Participants

Serial plasma samples from 55 prostate cancer patients receiving ADT were collected at three timepoints including baseline (prior to initiating ADT, N=55), 3-month (after initiating ADT, N=55), and disease progression (N=15) within 24 months or 24-month if no progression was detected (N=14). 20 of the 55 patients showed disease progression during the 24-month follow-up. The remaining 35 patients showed no progression in the same follow-up period.

Outcome Measurements and Statistical Analysis

cfDNA (5-10ng) was used for selective chemical labeling (hMe-Seal) sequencing to map 5hmC abundance across the genome. Read counts in gene bodies were normalized with DESeq2. Differential methylation and gene set enrichment analyses were performed to identify the 5hmC-enriched genes and biological processes that were associated with disease progression. Kaplan-Meir analysis was utilized to determine the association of 5hmC signatures with progression-free survival.

Results and Limitations

5hmC-sequencing generated an average of 18.6 (range 6.03 to 42.43) million reads per sample with 98% (95-99%) mappable rate. Baseline sample comparisons identified significant 5hmC difference in 1,642 of 23,433 genes between 20 patients with progression and 35 patients without progression (false discovery rate, FDR<0.1). Patients with progression showed significant enrichments in multiple hallmark gene sets with androgen responses as the top enriched gene set (FDR=1.19E-13). Interestingly, this enrichment was driven by a subgroup of patients with disease progression featuring a significant 5hmC hypermethylation of the gene sets involving AR, FOXA1 and GRHL2. To quantify overall activities of these gene sets, we developed a gene set activity score algorithm using a mean value of log2 ratios of gene read counts in an entire gene set. We found that the activity scores in these gene sets were significantly higher in this subgroup of patients with progression than in the remaining patients regardless of the progression status. Furthermore, the high activity scores in these gene sets were associated with poor progression-free survival (p <0.05). Longitudinal analysis showed that activity scores in this subgroup with progression were significantly reduced after 3-month ADT but returned to high levels when the disease was progressed.

Conclusions

5hmC-sequencing in cfDNA identified a subgroup of prostate cancer patients with preexisting activation (5hmC hypermethylation) of gene sets involving AR, FOXA1 and GRHL2 before initiating ADT. Activity scores in these gene sets may serve as sensitive biomarkers to determine treatment resistance, monitor disease progression and potentially identify patients who would benefit from upfront treatment intensification. More studies are needed to validate this initial finding.

Patient summary

There are no clinical tests to identify prostate cancer patients who will develop early resistance to androgen deprivation therapy within 24 months. In this study, we evaluated cell-free DNA epigenomic modification in blood and identified significant enrichment of 5-hydroxymethylation in androgen response genes in a subgroup of patients with treatment resistance. High level 5-hydroxylmethylation in these genes may serve as a discriminative biomarker to diagnose patients who are likely to experience early failure during androgen deprivation therapy.

Integrated longitudinal circulating tumor DNA profiling predicts immunotherapy response of metastatic urothelial carcinoma in the POLARIS-03 trial

Non-invasive biomarkers for immunotherapy response remain a compelling unmet medical need. POLARIS-03 is a multicenter phase II trial to evaluate the safety and efficacy of toripalimab (anti-programmed cell death 1) in refractory metastatic urothelial carcinoma (mUC). We assessed the predictive utility of longitudinal circulating tumor DNA (ctDNA) analysis from a single-institution biomarker cohort. Twenty-seven mUC patients receiving toripalimab (3 mg/kg Q2W) at Ren Ji Hospital were enrolled. Serial plasma specimens were obtained at baseline and then every two cycles during treatment. The 600-gene panel (PredicineATLAS™) liquid biopsy assay was applied to probe somatic variants and cancer cell fraction (CCF). Low-pass whole genome sequencing was used to determine the copy number abnormality (CNA) score. Across the entire cohort, we observed different degrees of concordance between somatic aberrations detected by ctDNA and those inferred by matched tumor samples. Although the baseline CCF or CNA had limited predictive value, early ctDNA response at week 8 was associated with toripalimab efficacy and prolonged patient survival. Integrating CCF and CNA decrease achieved a superior accuracy of 90.5% in classifying responders and non-responders and predicted long-term benefit from toripalimab. Dynamic changes in the CCF and CNA in blood exquisitely reflected radiographic assessment of malignant lesions, including those with FGFR3-TACC3 gene fusion or microsatellite instability. This study demonstrates the feasibility and effectiveness of integrated longitudinal ctDNA profiling as a potential biomarker in mUC patients undergoing immunotherapy and supports further clinical evaluation of minimally invasive liquid biopsy assays for treatment stratification and therapy monitoring. © 2023 The Pathological Society of Great Britain and Ireland.

Precision cancer medicine: Concepts, current practice, and future developments

Precision cancer medicine is a multidisciplinary team effort that requires involvement and commitment of many stakeholders including the society at large. Building on the success of significant advances in precision therapy for oncological patients over the last two decades, future developments will be significantly shaped by improvements in scalable molecular diagnostics in which increasingly complex multilayered datasets require transformation into clinically useful information guiding patient management at fast turnaround times. Adaptive profiling strategies involving tissue- and liquid-based testing that account for the immense plasticity of cancer during the patient's journey and also include early detection approaches are already finding their way into clinical routine and will become paramount. A second major driver is the development of smart clinical trials and trial concepts which, complemented by real-world evidence, rapidly broaden the spectrum of therapeutic options. Tight coordination with regulatory agencies and health technology assessment bodies is crucial in this context. Multicentric networks operating nationally and internationally are key in implementing precision oncology in clinical practice and support developing and improving the ecosystem and framework needed to turn invocation into benefits for patients. The review provides an overview of the diagnostic tools, innovative clinical studies, and collaborative efforts needed to realize precision cancer medicine.

Genomic and Phenotypic Biomarkers for Precision Medicine Guidance in Advanced Prostate Cancer

OPINION STATEMENT

Prostate cancer (PCa) is the second most diagnosed malignant neoplasm and is one of the leading causes of cancer-related death in men worldwide. Despite significant advances in screening and treatment of PCa, given the heterogeneity of this disease, optimal personalized therapeutic strategies remain limited. However, emerging predictive and prognostic biomarkers based on individual patient profiles in combination with computer-assisted diagnostics have the potential to guide precision medicine, where patients may benefit from therapeutic approaches optimally suited to their disease. Also, the integration of genotypic and phenotypic diagnostic methods is supporting better informed treatment decisions. Focusing on advanced PCa, this review discusses polygenic risk scores for screening of PCa and common genomic aberrations in androgen receptor (AR), PTEN-PI3K-AKT, and DNA damage response (DDR) pathways, considering clinical implications for diagnosis, prognosis, and treatment prediction. Furthermore, we evaluate liquid biopsy, protein biomarkers such as serum testosterone levels, SLFN11 expression, total alkaline phosphatase (tALP), neutrophil-to-lymphocyte ratio (NLR), tissue biopsy, and advanced imaging tools, summarizing current phenotypic biomarkers and envisaging more effective utilization of diagnostic and prognostic biomarkers in advanced PCa. We conclude that prognostic and treatment predictive biomarker discovery can improve the management of patients, especially in metastatic stages of advanced PCa. This will result in decreased mortality and enhanced quality of life and help design a personalized treatment regimen.

Plasma exosomal miR-1290 and miR-29c-3p as diagnostic biomarkers for lung cancer

Background

Enhancing the diagnostic efficacy of early-stage lung cancer is crucial for improving prognosis. The objective of this study was to ascertain dependable exosomal miRNAs as biomarkers for the diagnosis of lung cancer.

Methods

Exosomal miRNA candidates were identified through miRNA sequencing and subsequently validated in various case-control sets using real-time quantitative reverse transcription-polymerase chain reaction (RT-qPCR). The correlation between the expression of exosomal miRNAs and the clinicopathological features of lung cancer was investigated. To assess the diagnostic efficacy of exosomal miRNAs for lung cancer, the receiver operating characteristic (ROC) curve analysis was conducted. The optimal cutoff value of exosomal miRNAs was determined in the testing cohort and subsequently confirmed in the validation cohort.

Results

The results showed that the expression of exosomal miR-1290 was significantly elevated, while that of miR-29c-3p was significantly decreased in the plasma of lung cancer patients, especially in those with early-stage lung cancer, compared to individuals with benign lung conditions (P < 0.01). Exosomal miR-1290 and miR-29c-3p demonstrated superior diagnostic efficacy compared to conventional tumor biomarkers in distinguishing between lung cancer and benign lung diseases, as evidenced by their respective area under the curve (AUC) values of 0.934 and 0.868. Furthermore, exosomal miR-1290 and miR-29c-3p exhibited higher diagnostic efficiency in early-stage lung cancer than traditional tumor markers, with AUC values of 0.947 and 0.895, respectively. Notably, both exosomal miR-1290 and miR-29c-3p displayed substantial discriminatory capacity in distinguishing between non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC), as indicated by their respective AUC values of 0.810 and 0.842.

Conclusions

The findings of this study provided evidence that exosomal miR-1290 and miR-29c-3p hold significant potential as biomarkers for the early detection of lung cancer, as well as for differentiating between NSCLC and SCLC.

Early death after a diagnosis of metastatic solid cancer-raising awareness and identifying risk factors from the SEER database

BACKGROUND

Cancer death rates are declining, in part due to smoking cessation, better detection and new treatments; nevertheless, a large fraction of metastatic cancer patients die soon after diagnosis. Few studies and interventions focus on these patients. Our study aims to characterize early mortality in a wide range of metastatic solid tumors.

METHODS

We retrieved data on adult patients diagnosed with pathologically confirmed de- novo metastatic solid tumors between the years 2004-2016 from the Surveillance, Epidemiology, and End Results database (SEER). Our primary outcome was cancer specific early death rate (defined as death within two months of diagnosis). Additional data extracted included socio-demographical data, tumor primary, sites of metastases, and cause of death.

RESULTS

109,207 (20.8%) patients died of de-novo metastatic cancer within two months of diagnosis. The highest rates of early death were found in hepatic (36%), pancreato-biliary (31%) and lung (25%) primaries. Factors associated with early death included primary site, liver, and brain metastases, increasing age, and lower income. Cancer was the cause of death in 92.1% of all early deaths. Two-month mortality rates have moderately improved during the study period (from 22.4% in 2004 to 18.8% in 2016).

CONCLUSION

A fifth of de-novo metastatic cancer patients die soon after diagnosis, with little improvement over the last decade. Further research is required to better classify and identify patients at risk for early mortality, which patients might benefit from faster diagnostic tracks, and which might avoid invasive and futile diagnostic procedures.

Monitoring of circulating tumour DNA in advanced pancreatic ductal adenocarcinoma predicts clinical outcome and reveals disease progression earlier than radiological imaging

Pancreatic ductal adenocarcinoma (PDAC) is a lethal disease with a need for better tools to guide treatment selection and follow-up. The aim of this prospective study was to investigate the prognostic value and treatment monitoring potential of longitudinal circulating tumour DNA (ctDNA) measurements in patients with advanced PDAC undergoing palliative chemotherapy. Using KRAS peptide nucleic acid clamp-PCR, we measured ctDNA levels in plasma samples obtained at baseline and every 4 weeks during chemotherapy from 81 patients with locally advanced and metastatic PDAC. Cox proportional hazard regression showed that ctDNA detection at baseline was an independent predictor of progression-free and overall survival. Joint modelling demonstrated that the dynamic ctDNA level was a strong predictor of time to first disease progression. Longitudinal ctDNA measurements during chemotherapy successfully revealed disease progression in 20 (67%) of 30 patients with ctDNA detected at baseline, with a median lead time of 23 days (P = 0.01) over radiological imaging. Here, we confirmed the clinical relevance of ctDNA in advanced PDAC with regard to both the prediction of clinical outcome and disease monitoring during treatment.

Models to study CTCs and CTC culture methods

The vast majority of cancer-related deaths are due to the presence of disseminated disease. Understanding the metastatic process is key to achieving a reduction in cancer mortality. Particularly, there is a need to understand the molecular mechanisms that drive cancer metastasis, which will allow the identification of curative treatments for metastatic cancers. Liquid biopsies have arisen as a minimally invasive approach to gain insights into the biology of metastasis. Circulating tumour cells (CTCs), shed to the circulation from the primary tumour or metastatic lesions, are a key component of liquid biopsy. As metastatic precursors, CTCs hold the potential to unravel the mechanisms involved in metastasis formation as well as new therapeutic strategies for treating metastatic disease. However, the complex biology of CTCs together with their low frequency in circulation are factors hampering an in-depth mechanistic investigation of the metastatic process. To overcome these problems, CTC-derived models, including CTC-derived xenograft (CDX) and CTC-derived ex vivo cultures, in combination with more traditional in vivo models of metastasis, have emerged as powerful tools to investigate the biological features of CTCs facilitating cancer metastasis and uncover new therapeutic opportunities. In this chapter, we provide an up to date view of the diverse models used in different cancers to study the biology of CTCs, and of the methods developed for CTC culture and expansion, in vivo and ex vivo. We also report some of the main challenges and limitations that these models are facing.

A Liquid Biopsy Signature for the Early Detection of Gastric Cancer in Patients

BACKGROUND & AIMS

Diagnosing gastric cancer (GC) while the disease remains eligible for surgical resection is challenging. In view of this clinical challenge, novel and robust biomarkers for early detection thus improving prognosis of GC are necessary. The present study is to develop a blood-based long noncoding RNA (LR) signature for the early-detection of GC.

METHODS

The present 3-step study incorporated data from 2141 patients, including 888 with GC, 158 with chronic atrophic gastritis, 193 with intestinal metaplasia, 501 healthy donors, and 401 with other gastrointestinal cancers. The LR profile of stage I GC tissue samples were analyzed using transcriptomic profiling in discovery phase. The extracellular vesicle (EV)-derived LR signature was identified with a training cohort (n = 554) and validated with 2 external cohorts (n = 429 and n = 504) and a supplemental cohort (n = 69).

RESULTS

In discovery phase, one LR (GClnc1) was found to be up-regulated in both tissue and circulating EV samples with an area under the curve (AUC) of 0.9369 (95% confidence interval [CI], 0.9073-0.9664) for early-stage GC (stage I/II). The diagnostic performance of this biomarker was further confirmed in 2 external validation cohorts (Xi'an cohort, AUC: 0.8839; 95% CI: 0.8336-0.9342; Beijing cohort, AUC: 0.9018; 95% CI: 0.8597-0.9439). Moreover, EV-derived GClnc1 robustly distinguished early-stage GC from precancerous lesions (chronic atrophic gastritis and intestinal metaplasia) and GC with negative traditional gastrointestinal biomarkers (CEA, CA72-4, and CA19-9). The low levels of this biomarker in postsurgery and other gastrointestinal tumor plasma samples indicated its GC specificity.

CONCLUSIONS

EV-derived GClnc1 serves as a circulating biomarker for the early detection of GC, thus providing opportunities for curative surgery and improved survival outcomes.

Full spectrum flow cytometry-powered comprehensive analysis of PBMC as biomarkers for immunotherapy in NSCLC with EGFR-TKI resistance

BACKGROUND

Clinical studies suggest that immune checkpoint inhibitor (ICI) monotherapy has limited benefits in non-small cell lung cancer (NSCLC) patients after epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI) failure. However, data about efficacy of ICI plus chemotherapy remain controversial, probably attributed to the heterogeneity among such population, and robust efficacy biomarkers are urgent to explore.

METHODS

A total of 60 eligible patients who received ICI plus chemotherapy after EGFR-TKI treatment failure were enrolled, 24 of whom peripheral blood mononuclear cell (PBMC) samples were collected at baseline and after 2 cycles of treatment. We have designed a 23-color-antibody panel to detect PBMC by full spectrum flow cytometry.

RESULTS

For EGFR-TKI resistant NSCLC patients: 1) ICI plus chemotherapy achieved an objective response rate (ORR) of 21.7% and a median progression-free survival (PFS) of 6.4 months. 2) clinical characteristics associated with worse efficacy included liver metastasis and platelet-to-lymphocyte ratio (PLR) > 200. 3) the proportion of immune cell subset associated with better efficacy was higher baseline effective CD4⁺T cells (E4). 4) the baseline expression of immune checkpoint proteins (ICPs) on cell subsets associated with better efficacy included: higher expression of CD25 on dendritic cells (DC) and central memory CD8⁺T cells (CM8), and higher expression of Lymphocyte activation gene 3 (LAG-3) on effective memory CD8⁺T cells (EM8). 5) the expression of ICPs after 2 cycles of treatment associated with better efficacy included: higher expression of CD25 on CD8⁺T/EM8 /natural killer (NK) cells. 6) the dynamic changes of ICPs expression associated with worse efficacy included: significantly decrease of T cell immunoglobulin and ITIM domain (TIGIT) expression on regular T cells (Tregs) and decrease of V-domain immunoglobulin suppressor of T cell activation (VISTA) expression on Th1. 7) a prediction model for the efficacy of ICI plus chemotherapy was successfully constructed with a sensitivity of 62.5%, specificity of 100%, and area under curve (AUC) = 0.817.

CONCLUSIONS

Some EGFR-TKI-resistant NSCLC patients could indeed benefit from ICI plus chemotherapy, but most patients are primary resistant to immunotherapy. Comprehensive analysis of peripheral immune cells using full spectrum flow cytometry showed that compared to the proportion of cell subsets, the expression type and level of ICPs on immune cells, especially CD25, were significantly correlated with the efficacy of immunotherapy.

Orchestrating smart therapeutics to achieve optimal treatment in small cell lung cancer: recent progress and future directions

Small cell lung cancer (SCLC) is a recalcitrant malignancy with elusive mechanism of pathogenesis and dismal prognosis. Over the past decades, platinum-based chemotherapy has been the backbone treatment for SCLC. However, subsequent chemoresistance after initial effectiveness urges researchers to explore novel therapeutic targets of SCLC. Recent years have witnessed significant improvements in targeted therapy in SCLC. New molecular candidates such as Ataxia telangiectasia and RAD3-related protein (ATR), WEE1, checkpoint kinase 1 (CHK1) and poly-ADP-ribose polymerase (PARP) have shown promising therapeutic utility in SCLC. While immune checkpoint inhibitor (ICI) has emerged as an indispensable treatment modality for SCLC, approaches to boost efficacy and reduce toxicity as well as selection of reliable biomarkers for ICI in SCLC have remained elusive and warrants our further investigation. Given the increasing importance of precision medicine in SCLC, optimal subtyping of SCLC using multi-omics have gradually applied into clinical practice, which may identify more drug targets and better tailor treatment strategies to each individual patient. The present review summarizes recent progress and future directions in SCLC. In addition to the emerging new therapeutics, we also focus on the establishment of predictive model for early detection of SCLC. More importantly, we also propose a multi-dimensional model in the prognosis of SCLC to ultimately attain the goal of accurate treatment of SCLC.

Association between circulating tumor cells in the peripheral blood and the prognosis of gastric cancer patients: a meta-analysis

Background

Research on the correlation between circulating tumor cells (CTCs) and gastric cancer (GC) has increased rapidly in recent years. However, whether CTCs are associated with GC patient prognosis is highly controversial.

Objective

This study aims to evaluate the value of CTCs to predict the prognosis of GC patients.

Design

A meta-analysis.

Data Sources and Methods

We searched the PubMed, Embase, and Cochrane Library databases for studies that reported the prognostic value of CTCs in GC patients before October 2022. The association between CTCs and overall survival (OS) and disease-free survival (DFS)/recurrence-free survival (RFS) and progression-free survival (PFS) of GC patients was assessed. Subgroup analyses were stratified by sampling times (pre-treatment and post-treatment), detection targets, detection method, treatment method, tumor stage, region, and HR (Hazard Ratio) extraction methods. Sensitivity analysis was performed by removing individual studies to assess the stability of the results. Publication bias was evaluated using funnel plots, Egger's test, and Begg's test.

Results

We initially screened 2000 studies, of which 28 were available for further analysis, involving 2383 GC patients. The pooled analysis concluded that the detection of CTCs was associated with poor OS (HR = 1.933, 95% CI 1.657-2.256, p < 0.001), DFS/RFS (HR = 3.228, 95% CI 2.475-4.211, p < 0.001), and PFS (HR = 3.272, 95% CI 1.970-5.435, p < 0.001). Furthermore, the subgroup analysis stratified by tumor stage (p < 0.01), HR extraction methods (p < 0.001), detection targets (p < 0.001), detection method (p < 0.001), sampling times (p < 0.001), and treatment method (p < 0.001) all showed that CTC detection was associated with poor OS and DFS/RFS for GC patients. Furthermore, the study showed that CTCs were associated with the poor DFS/RFS of GC when CTCs were detected for patients from Asian or No-Asian regions (p < 0.05). In addition, higher CTCs predicted poorer OS for GC patients who are from Asian regions (p < 0.001), but without statistical difference for GC patients from No-Asian regions (p = 0.490).

Conclusion

CTC detection in peripheral blood was associated with poor OS, DFS/RFS, and PFS in patients with GC.

Advancements and Applications of Liquid Biopsies in Oncology: A Narrative Review

According to the World Health Organization (WHO), nearly 10 million people died from cancer worldwide in 2020, making it the leading cause of mortality. Liquid biopsies, which provide non-invasive and real-time monitoring of tumor dynamics, have evolved into innovative diagnostic techniques in the field of oncology. Liquid biopsies offer important insights into tumor heterogeneity, treatment response, minimum residual disease identification, and personalized treatment of cancer through the analysis of circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), extracellular vesicles, and microRNAs. They offer several advantages over traditional tissue biopsies, such as being less invasive, more convenient, more representative of tumor heterogeneity and dynamics, and more informative for guiding personalized treatment decisions. Liquid biopsies are being utilized increasingly in clinical oncology, particularly for patients with metastatic disease who require ongoing monitoring and treatment modification. In this narrative review article, we review the latest developments of liquid biopsy technologies, their applications and limitations, and their potential to transform diagnosis, prognosis, and management of cancer patients.

Single-cell omics: a new perspective for early detection of pancreatic cancer?

Pancreatic cancer is one of the most lethal cancers, mostly due to late diagnosis and limited treatment options. Early detection of pancreatic cancer in high-risk populations bears the potential to greatly improve outcomes, but current screening approaches remain of limited value despite recent technological advances. This review explores the possible advantages of liquid biopsies for this application, particularly focusing on circulating tumour cells (CTCs) and their subsequent single-cell omics analysis. Originating from both primary and metastatic tumour sites, CTCs provide important information for diagnosis, prognosis and tailoring of treatment strategies. Notably, CTCs have even been detected in the blood of subjects with pancreatic precursor lesions, suggesting their suitability as a non-invasive tool for the early detection of malignant transformation in the pancreas. As intact cells, CTCs offer comprehensive genomic, transcriptomic, epigenetic and proteomic information that can be explored using rapidly developing techniques for analysing individual cells at the molecular level. Studying CTCs during serial sampling and at single-cell resolution will help to dissect tumour heterogeneity for individual patients and among different patients, providing new insights into cancer evolution during disease progression and in response to treatment. Using CTCs for non-invasive tracking of cancer features, including stemness, metastatic potential and expression of immune targets, provides important and readily accessible molecular insights. Finally, the emerging technology of ex vivo culturing of CTCs could create new opportunities to study the functionality of individual cancers at any stage and develop personalised and more effective treatment approaches for this lethal disease.

ICAM-1-suPAR-CD11b Axis Is a Novel Therapeutic Target for Metastatic Triple-Negative Breast Cancer

Accumulating evidence demonstrates that circulating tumor cell (CTC) clusters have higher metastatic ability than single CTCs and negatively correlate with cancer patient outcomes. Along with homotypic CTC clusters, heterotypic CTC clusters (such as neutrophil-CTC clusters), which have been identified in both cancer mouse models and cancer patients, lead to more efficient metastasis formation and worse patient outcomes. However, the mechanism by which neutrophils bind to CTCs remains elusive. In this study, we found that intercellular adhesion molecule-1 (ICAM-1) on triple-negative breast cancer (TNBC) cells and CD11b on neutrophils mediate tumor cell-neutrophil binding. Consequently, CD11b deficiency inhibited tumor cell-neutrophil binding and TNBC metastasis. Furthermore, CD11b mediated hydrogen peroxide (H2O2) production from neutrophils. Moreover, we found that ICAM-1 in TNBC cells promotes tumor cells to secrete suPAR, which functions as a chemoattractant for neutrophils. Knockdown of uPAR in ICAM-1+ TNBC cells reduced lung-infiltrating neutrophils and lung metastasis. Bioinformatics analysis confirmed that uPAR is highly expressed in TNBCs, which positively correlates with higher neutrophil infiltration and negatively correlates with breast cancer patient survival. Collectively, our findings provide new insight into how neutrophils bind to CTC to facilitate metastasis and discover a novel potential therapeutic strategy by blocking the ICAM-1-suPAR-CD11b axis to inhibit TNBC metastasis.

Skeletal muscle omics signatures in cancer cachexia: perspectives and opportunities

Cachexia is a life-threatening complication of cancer that occurs in up to 80% of patients with advanced cancer. Cachexia reflects the systemic consequences of cancer and prominently features unintended weight loss and skeletal muscle wasting. Cachexia impairs cancer treatment tolerance, lowers quality of life, and contributes to cancer-related mortality. Effective treatments for cancer cachexia are lacking despite decades of research. High-throughput omics technologies are increasingly implemented in many fields including cancer cachexia to stimulate discovery of disease biology and inform therapy choice. In this paper, we present selected applications of omics technologies as tools to study skeletal muscle alterations in cancer cachexia. We discuss how comprehensive, omics-derived molecular profiles were used to discern muscle loss in cancer cachexia compared with other muscle-wasting conditions, to distinguish cancer cachexia from treatment-related muscle alterations, and to reveal severity-specific mechanisms during the progression of cancer cachexia from early toward severe disease.

A systematic review and meta-analysis of miRNAs for the detection of cervical cancer

Aim: This study aimed to critically appraise the evidence of the diagnostic effectiveness of miRNAs for the detection of cervical cancer. Methods & materials: A systematic review and meta-analysis was performed, searching PubMed, EMBASE and Web of Science. An umbrella meta-analysis of meta-analyses of individual biomarkers was performed. A Grading of Recommendations, Assessment, Development and Evaluations (GRADE) assessment of evidence was also performed. Results: A total of 52 miRNAs were included. Umbrella meta-analysis revealed significant heterogeneity in terms of sensitivity, specificity, receiver operating characteristic (ROC), positive predictive value and/or negative predictive value. Umbrella effects were 0.76 (95% CI: 0.73-0.78), 0.78 (95% CI: 0.75-0.81), 0.77 (95% CI: 0.75-0.80), 0.75 (95% CI: 0.71-0.79) and 0.76 (95% CI: 0.74-0.79), respectively. Conclusion: Moderate quality evidence suggested miR199a-5p, miR21-5p and miR-141a had excellent diagnostic performance.

Emerging role of non-invasive and liquid biopsy biomarkers in pancreatic cancer

A global increase in the incidence of pancreatic cancer (PanCa) presents a major concern and health burden. The traditional tissue-based diagnostic techniques provided a major way forward for molecular diagnostics; however, they face limitations based on diagnosis-associated difficulties and concerns surrounding tissue availability in the clinical setting. Late disease development with asymptomatic behavior is a drawback in the case of existing diagnostic procedures. The capability of cell free markers in discriminating PanCa from autoimmune pancreatitis and chronic pancreatitis along with other precancerous lesions can be a boon to clinicians. Early-stage diagnosis of PanCa can be achieved only if these biomarkers specifically discriminate the non-carcinogenic disease stage from malignancy with respect to tumor stages. In this review, we comprehensively described the non-invasive disease detection approaches and why these approaches are gaining popularity for their early-stage diagnostic capability and associated clinical feasibility.

Extracellular Vesicles as Potential Bladder Cancer Biomarkers: Take It or Leave It?

Bladder cancer (BC) is the 10th most frequently diagnosed cancer worldwide. Although urine cytology and cystoscopy are current standards for BC diagnosis, both have limited sensitivity to detect low-grade and small tumors. Moreover, effective prognostic biomarkers are lacking. Extracellular vesicles (EVs) are lipidic particles that contain nucleic acids, proteins, and metabolites, which are released by cells into the extracellular space, being crucial effectors in intercellular communication. These particles have emerged as potential tools carrying biomarkers for either diagnosis or prognosis in liquid biopsies namely urine, plasma, and serum. Herein, we review the potential of liquid biopsies EVs’ cargo as BC diagnosis and prognosis biomarkers. Additionally, we address the emerging advantages and downsides of using EVs within this framework.

Longitudinal ctDNA profiling in precision oncology and immunο-oncology

Serial analysis of circulating tumor DNA (ctDNA) over the disease course is emerging as a prognostic, predictive and patient-monitoring biomarker. In the metastatic setting, several multigene ctDNA assays have been approved or recommended by regulatory organizations for personalized targeted therapy, especially for lung cancer. By contrast, in nonmetastatic disease, detection of ctDNA resulting from minimal residual disease (MRD) following multimodal treatment with curative intent presents major technical challenges. Several studies using tumor genotyping-informed serial ctDNA profiling have provided promising findings on the sensitivity and specificity of ctDNA in predicting the risk of recurrence. We discuss progress, limitations and future perspectives relating to the use of ctDNA as a biomarker to guide targeted therapy in metastatic disease, as well as the use of ctDNA MRD detection to guide adjuvant treatment in the nonmetastatic setting.

Knowledge and expectations about miRNAs as biomarkers in head and neck squamous cell cancers

Head and neck squamous cell cancer patients suffer from a high postoperative recurrence rate and poor prognosis. Thus, it is essential to better understand the underlying molecular mechanisms and identify the role of new biomarkers. Recent research has shown that the dysregulation of microRNAs is a potential biomarker as a screening or prognostic tool. Moreover, the literature reveals its promising usefulness to select the best treatment strategy and monitor tumour response. The purpose of this review is to identify and synthesize the available literature on microRNAs as biomarkers that could help manage patients with head and neck squamous cell cancer. A search in scientific databases was completed, including all relevant articles related to circulating microRNAs in head and neck squamous cell cancer published in English or Spanish. We focused on articles whose main findings were related to their usefulness in diagnosis and prognosis. Conclusion: Knowledge of microRNAs opens the possibilities that these molecules offer in terms of monitoring cancer disease in a less-invasive, simple manner, allowing for serial sampling to assess the response to treatment and minimal residual disease. It is yet to be determined whether liquid biopsy will replace the traditional biopsy in the future but it represents a change in the paradigm of management of head and neck squamous cell cancer.

Diagnostic value of liquid biopsy in the era of precision medicine: 10 years of clinical evidence in cancer

Liquid biopsy is a diagnostic repeatable test, which in last years has emerged as a powerful tool for profiling cancer genomes in real-time with minimal invasiveness and tailoring oncological decision-making. It analyzes different blood-circulating biomarkers and circulating tumor DNA (ctDNA) is the preferred one. Nevertheless, tissue biopsy remains the gold standard for molecular evaluation of solid tumors whereas liquid biopsy is a complementary tool in many different clinical settings, such as treatment selection, monitoring treatment response, cancer clonal evolution, prognostic evaluation, as well as the detection of early disease and minimal residual disease (MRD). A wide number of technologies have been developed with the aim of increasing their sensitivity and specificity with acceptable costs. Moreover, several preclinical and clinical studies have been conducted to better understand liquid biopsy clinical utility. Anyway, several issues are still a limitation of its use such as false positive and negative results, results interpretation, and standardization of the panel tests. Although there has been rapid development of the research in these fields and recent advances in the clinical setting, many clinical trials and studies are still needed to make liquid biopsy an instrument of clinical routine. This review provides an overview of the current and future clinical applications and opening questions of liquid biopsy in different oncological settings, with particular attention to ctDNA liquid biopsy.

Recent advances of small extracellular vesicle biomarkers in breast cancer diagnosis and prognosis

Current clinical tools for breast cancer (BC) diagnosis are insufficient but liquid biopsy of different bodily fluids has recently emerged as a minimally invasive strategy that provides a real-time snapshot of tumour biomarkers for early diagnosis, active surveillance of progression, and post-treatment recurrence. Extracellular vesicles (EVs) are nano-sized membranous structures 50-1000 nm in diameter that are released by cells into biological fluids. EVs contain proteins, nucleic acids, and lipids which play pivotal roles in tumourigenesis and metastasis through cell-to-cell communication. Proteins and miRNAs from small EVs (sEV), which range in size from 50-150 nm, are being investigated as a potential source for novel BC biomarkers using mass spectrometry-based proteomics and next-generation sequencing. This review covers recent developments in sEV isolation and single sEV analysis technologies and summarises the sEV protein and miRNA biomarkers identified for BC diagnosis, prognosis, and chemoresistance. The limitations of current sEV biomarker research are discussed along with future perspective applications.

Molecular MRI-Based Monitoring of Cancer Immunotherapy Treatment Response

Immunotherapy constitutes a paradigm shift in cancer treatment. Its FDA approval for several indications has yielded improved prognosis for cases where traditional therapy has shown limited efficiency. However, many patients still fail to benefit from this treatment modality, and the exact mechanisms responsible for tumor response are unknown. Noninvasive treatment monitoring is crucial for longitudinal tumor characterization and the early detection of non-responders. While various medical imaging techniques can provide a morphological picture of the lesion and its surrounding tissue, a molecular-oriented imaging approach holds the key to unraveling biological effects that occur much earlier in the immunotherapy timeline. Magnetic resonance imaging (MRI) is a highly versatile imaging modality, where the image contrast can be tailored to emphasize a particular biophysical property of interest using advanced engineering of the imaging pipeline. In this review, recent advances in molecular-MRI based cancer immunotherapy monitoring are described. Next, the presentation of the underlying physics, computational, and biological features are complemented by a critical analysis of the results obtained in preclinical and clinical studies. Finally, emerging artificial intelligence (AI)-based strategies to further distill, quantify, and interpret the image-based molecular MRI information are discussed in terms of perspectives for the future.