Ultra high content analyses of circulating and tumor associated hybrid cells reveal phenotypic heterogeneity.

Persistently high, worldwide mortality from cancer highlights the unresolved challenges of disease surveillance and detection that impact survival. Development of a non-invasive, blood-based biomarker would transform survival from cancer. We demonstrate the functionality of ultra-high content analyses of a newly identified population of tumor cells that are hybrids between neoplastic and immune cells in patient matched tumor and peripheral blood specimens. Using oligonucleotide conjugated antibodies (Ab-oligo) permitting cyclic immunofluorescence (cyCIF), we present analyses of phenotypes among tumor and peripheral blood hybrid cells. Interestingly, the majority of circulating hybrid cell (CHC) subpopulations were not identified in tumor-associated hybrids. These results highlight the efficacy of ultra-high content phenotypic analyses using Ab-oligo based cyCIF applied to both tumor and peripheral blood specimens. The combination of a multiplex phenotypic profiling platform that is gentle enough to analyze blood to detect and evaluate disseminated tumor cells represents a novel approach to exploring novel tumor biology and potential utility for developing the population as a blood-based biomarker in cancer.

Quantitative image analysis pipeline for detecting circulating hybrid cells in immunofluorescence images with human-level accuracy.

Circulating hybrid cells (CHCs) are a newly discovered, tumor-derived cell population found in the peripheral blood of cancer patients and are thought to contribute to tumor metastasis. However, identifying CHCs by immunofluorescence (IF) imaging of patient peripheral blood mononuclear cells (PBMCs) is a time-consuming and subjective process that currently relies on manual annotation by laboratory technicians. Additionally, while IF is relatively easy to apply to tissue sections, its application to PBMC smears presents challenges due to the presence of biological and technical artifacts. To address these challenges, we present a robust image analysis pipeline to automate the detection and analysis of CHCs in IF images. The pipeline incorporates quality control to optimize specimen preparation protocols and remove unwanted artifacts, leverages a ß-variational autoencoder (VAE) to learn meaningful latent representations of single-cell images, and employs a support vector machine (SVM) classifier to achieve human-level CHC detection. We created a rigorously labeled IF CHC data set including nine patients and two disease sites with the assistance of 10 annotators to evaluate the pipeline. We examined annotator variation and bias in CHC detection and provided guidelines to optimize the accuracy of CHC annotation. We found that all annotators agreed on CHC identification for only 65% of the cells in the data set and had a tendency to underestimate CHC counts for regions of interest (ROIs) containing relatively large amounts of cells (>50,000) when using the conventional enumeration method. On the other hand, our proposed approach is unbiased to ROI size. The SVM classifier trained on the ß-VAE embeddings achieved an F1 score of 0.80, matching the average performance of human annotators. Our pipeline enables researchers to explore the role of CHCs in cancer progression and assess their potential as a clinical biomarker for metastasis. Further, we demonstrate that the pipeline can identify discrete cellular phenotypes among PBMCs, highlighting its utility beyond CHCs.

Detection of neoplastic-immune hybrid cells with metastatic properties in uveal melanoma.

Background: Uveal melanoma is the most common non-cutaneous melanoma and is an intraocular malignancy affecting nearly 7,000 individuals per year worldwide. Of these, approximately 50% will progress to metastatic disease for which there are currently no effective therapies. Despite advances in molecular profiling and metastatic stratification of uveal melanoma tumors, little is known regarding their underlying biology of metastasis. Our group has identified a disseminated neoplastic cell population characterized by co-expression of immune and melanoma proteins, circulating hybrid cells (hybrids), in patients with uveal melanoma. Compared to circulating tumor cells, which lack expression of immune proteins, hybrids are detected at an increased prevalence in peripheral blood and can be used as a non-invasive biomarker to predict metastatic progression. Methods: To ascertain mechanisms underlying enhanced hybrid cell dissemination we identified hybrid cells within primary uveal melanoma tumors using single cell RNA sequencing and evaluated their gene expression and predicted ligand-receptor interactions in relation to other melanoma and immune cells within the primary tumor. We then verified expression of upregulated hybrid pathways within patient-matched tumor and peripheral blood hybrids using cyclic immunofluorescence and quantified their protein expression relative to other non-hybrid tumor and disseminated tumor cells. Results: Among the top upregulated genes and pathways in hybrid cells were those involved in enhanced cell motility and cytoskeletal rearrangement, immune evasion, and altered cellular metabolism. In patient-matched tumor and peripheral blood, we verified gene expression by examining concordant protein expression for each pathway category: TMSB10 (cell motility), CD74 (immune evasion) and GPX1 (metabolism). Both TMSB10 and GPX1 were expressed on significantly higher numbers of disseminated hybrid cells compared to circulating tumor cells, and CD74 and GPX1 were expressed on more disseminated hybrids than tumor-resident hybrids. Lastly, we identified that hybrid cells express ligand-receptor signaling pathways implicated in promoting metastasis including GAS6-AXL, CXCL12-CXCR4, LGALS9-P4HB and IGF1-IGFR1. Conclusion: These findings highlight the importance of TMSB10, GPX1 and CD74 for successful hybrid cell dissemination and survival in circulation. Our results contribute to the understanding of uveal melanoma tumor progression and interactions between tumor cells and immune cells in the tumor microenvironment that may promote metastasis.

Analysis of uveal melanoma scRNA sequencing data identifies neoplastic-immune hybrid cells that exhibit metastatic potential.

Uveal melanoma (UM) is the most common non-cutaneous melanoma and is an intraocular malignancy that affects nearly 7,000 individuals per year worldwide. Of these, nearly 50% will progress to metastatic disease for which there are currently no effective therapies. Despite advances in the molecular profiling and metastatic stratification of class 1 and 2 UM tumors, little is known regarding the underlying biology of UM metastasis. Our group has identified a disseminated tumor cell population characterized by co-expression of immune and melanoma proteins, (circulating hybrid cells (CHCs), in patients with UM. Compared to circulating tumor cells, CHCs are detected at an increased prevalence in peripheral blood and can be used as a non-invasive biomarker to predict metastatic progression. To identify mechanisms underlying enhanced hybrid cell dissemination we sought to identify hybrid cells within a primary UM single cell RNA-seq dataset. Using rigorous doublet discrimination approaches, we identified UM hybrids and evaluated their gene expression, predicted ligand-receptor status, and cell-cell communication state in relation to other melanoma and immune cells within the primary tumor. We identified several genes and pathways upregulated in hybrid cells, including those involved in enhancing cell motility and cytoskeleton rearrangement, evading immune detection, and altering cellular metabolism. In addition, we identified that hybrid cells express ligand-receptor signaling pathways implicated in promoting cancer metastasis including IGF1-IGFR1, GAS6-AXL, LGALS9-P4HB, APP-CD74 and CXCL12-CXCR4. These results contribute to our understanding of tumor progression and interactions between tumor cells and immune cells in the UM microenvironment that may promote metastasis.

Updated Management of Colorectal Cancer Liver Metastases: Scientific Advances Driving Modern Therapeutic Innovations.

Colorectal cancer is the second leading cause of cancer-related deaths in the United States and accounts for an estimated 1 million deaths annually worldwide. The liver is the most common site of metastatic spread from colorectal cancer, significantly driving both morbidity and mortality. Although remarkable advances have been made in recent years in the management for patients with colorectal cancer liver metastases, significant challenges remain in early detection, prevention of progression and recurrence, and in the development of more effective therapeutics. In 2017, our group held a multidisciplinary state-of-the-science symposium to discuss the rapidly evolving clinical and scientific advances in the field of colorectal liver metastases, including novel early detection and prognostic liquid biomarkers, identification of high-risk cohorts, advances in tumor-immune therapy, and different regional and systemic therapeutic strategies. Since that time, there have been scientific discoveries translating into therapeutic innovations addressing the current management challenges. These innovations are currently reshaping the treatment paradigms and spurring further scientific discovery. Herein, we present an updated discussion of both the scientific and clinical advances and future directions in the management of colorectal liver metastases, including adoptive T-cell therapies, novel blood-based biomarkers, and the role of the tumor microbiome. In addition, we provide a comprehensive overview detailing the role of modern multidisciplinary clinical approaches used in the management of patients with colorectal liver metastases, including considerations toward specific molecular tumor profiles identified on next generation sequencing, as well as quality of life implications for these innovative treatments.

Quantitative image analysis pipeline for detecting circulating hybrid cells in immunofluorescence images with human-level accuracy.

Circulating hybrid cells (CHCs) are a newly discovered, tumor-derived cell population identified in the peripheral blood of cancer patients and are thought to contribute to tumor metastasis. However, identifying CHCs by immunofluorescence (IF) imaging of patient peripheral blood mononuclear cells (PBMCs) is a time-consuming and subjective process that currently relies on manual annotation by laboratory technicians. Additionally, while IF is relatively easy to apply to tissue sections, its application on PBMC smears presents challenges due to the presence of biological and technical artifacts. To address these challenges, we present a robust image analysis pipeline to automate the detection and analyses of CHCs in IF images. The pipeline incorporates quality control to optimize specimen preparation protocols and remove unwanted artifacts, leverages a ß-variational autoencoder (VAE) to learn meaningful latent representations of single-cell images and employs a support vector machine (SVM) classifier to achieve human-level CHC detection. We created a rigorously labeled IF CHC dataset including 9 patients and 2 disease sites with the assistance of 10 annotators to evaluate the pipeline. We examined annotator variation and bias in CHC detection and then provided guidelines to optimize the accuracy of CHC annotation. We found that all annotators agreed on CHC identification for only 65% of the cells in the dataset and had a tendency to underestimate CHC counts for regions of interest (ROI) containing relatively large amounts of cells (>50,000) when using conventional enumeration methods. On the other hand, our proposed approach is unbiased to ROI size. The SVM classifier trained on the ß-VAE encodings achieved an F1 score of 0.80, matching the average performance of annotators. Our pipeline enables researchers to explore the role of CHCs in cancer progression and assess their potential as a clinical biomarker for metastasis. Further, we demonstrate that the pipeline can identify discrete cellular phenotypes among PBMCs, highlighting its utility beyond CHCs.

Biology-inspired graph neural network encodes reactome and reveals biochemical reactions of disease.

Functional heterogeneity of healthy human tissues complicates interpretation of molecular studies, impeding precision therapeutic target identification and treatment. Considering this, we generated a graph neural network with Reactome-based architecture and trained it using 9,115 samples from Genotype-Tissue Expression (GTEx). Our graph neural network (GNN) achieves adjusted Rand index (ARI) = 0.7909, while a Resnet18 control model achieves ARI = 0.7781, on 370 held-out healthy human tissue samples from The Cancer Genome Atlas (TCGA), despite the Resnet18 using over 600 times the parameters. Our GNN also succeeds in separating 83 healthy skin samples from 95 lesional psoriasis samples, revealing that upregulation of 26S- and NUB1-mediated degradation of NEDD8, UBD, and their conjugates is central to the largest perturbed reaction network component in psoriasis. We show that our results are not discoverable using traditional differential expression and hypergeometric pathway enrichment analyses yet are supported by separate human multi-omics and small-molecule mouse studies, suggesting future molecular disease studies may benefit from similar GNN analytical approaches.

Flexible Cyclic Immunofluorescence (cyCIF) Using Oligonucleotide Barcoded Antibodies.

Advances in our understanding of the complex, multifaceted interactions between tumor epithelia, immune infiltrate, and tumor microenvironmental cells have been driven by highly multiplexed imaging technologies. These techniques are capable of labeling many more biomarkers than conventional immunostaining methods. However, multiplexed imaging techniques suffer from low detection sensitivity, cell loss-particularly in fragile samples-, and challenges with antibody labeling. Herein, we developed and optimized an oligonucleotide antibody barcoding strategy for cyclic immunofluorescence (cyCIF) that can be amplified to increase the detection efficiency of low-abundance antigens. Stained fluorescence signals can be readily removed using ultraviolet light treatment, preserving tissue and fragile cell sample integrity. We also extended the oligonucleotide barcoding strategy to secondary antibodies to enable the inclusion of difficult-to-label primary antibodies in a cyCIF panel. Using both the amplification oligonucleotides to label DNA barcoded antibodies and in situ hybridization of multiple fluorescently labeled oligonucleotides resulted in signal amplification and increased signal-to-background ratios. This procedure was optimized through the examination of staining parameters including staining oligonucleotide concentration, staining temperature, and oligonucleotide sequence design, resulting in a robust amplification technique. As a proof-of-concept, we demonstrate the flexibility of our cyCIF strategy by simultaneously imaging with the original oligonucleotide conjugated antibody (Ab-oligo) cyCIF strategy, the novel Ab-oligo cyCIF amplification strategy, as well as direct and indirect immunofluorescence to generate highly multiplexed images.

Circulating Neoplastic-Immune Hybrid Cells Predict Metastatic Progression in Uveal Melanoma.

Background: Uveal melanoma is an aggressive cancer with high metastatic risk. Recently, we identified a circulating cancer cell population that co-expresses neoplastic and leukocyte antigens, termed circulating hybrid cells (CHCs). In other cancers, CHCs are more numerous and better predict oncologic outcomes compared to circulating tumor cells (CTCs). We sought to investigate the potential of CHCs as a prognostic biomarker in uveal melanoma. Methods: We isolated peripheral blood monocular cells from uveal melanoma patients at the time of primary treatment and used antibodies against leukocyte and melanoma markers to identify and enumerate CHCs and CTCs by immunocytochemistry. Results: Using a multi-marker approach to capture the heterogeneous disseminated tumor cell population, detection of CHCs was highly sensitive in uveal melanoma patients regardless of disease stage. CHCs were detected in 100% of stage I-III uveal melanoma patients (entire cohort, n = 68), whereas CTCs were detected in 58.8% of patients. CHCs were detected at levels statically higher than CTCs across all stages (p = 0.05). Moreover, CHC levels, but not CTCs, predicted 3 year progression-free survival (p < 0.03) and overall survival (p < 0.04). Conclusion: CHCs are a novel and promising prognostic biomarker in uveal melanoma.

Circulating Cells with Macrophage-like Characteristics in Cancer: The Importance of Circulating Neoplastic-Immune Hybrid Cells in Cancer.

Cancer remains a significant cause of mortality in developed countries, due in part to difficulties in early detection, understanding disease biology, and assessing treatment response. If effectively harnessed, circulating biomarkers promise to fulfill these needs through non-invasive "liquid" biopsy. While tumors disseminate genetic material and cellular debris into circulation, identifying clinically relevant information from these analytes has proven difficult. In contrast, cell-based circulating biomarkers have multiple advantages, including a source for tumor DNA and protein, and as a cellular reflection of the evolving tumor. While circulating tumor cells (CTCs) have dominated the circulating cell biomarker field, their clinical utility beyond that of prognostication has remained elusive, due to their rarity. Recently, two novel populations of circulating tumor-immune hybrid cells in cancer have been characterized: cancer-associated macrophage-like cells (CAMLs) and circulating hybrid cells (CHCs). CAMLs are macrophage-like cells containing phagocytosed tumor material, while CHCs can result from cell fusion between cancer and immune cells and play a role in the metastatic cascade. Both are detected in higher numbers than CTCs in peripheral blood and demonstrate utility in prognostication and assessing treatment response. Additionally, both cell populations are heterogeneous in their genetic, transcriptomic, and proteomic signatures, and thus have the potential to inform on heterogeneity within tumors. Herein, we review the advances in this exciting field.

Label-free enrichment of rare unconventional circulating neoplastic cells using a microfluidic dielectrophoretic sorting device.

Cellular circulating biomarkers from the primary tumor such as circulating tumor cells (CTCs) and circulating hybrid cells (CHCs) have been described to harbor tumor-like phenotype and genotype. CHCs are present in higher numbers than CTCs supporting their translational potential. Methods for isolation of CHCs do not exist and are restricted to low-throughput, time consuming, and biased methodologies. We report the development of a label-free dielectrophoretic microfluidic platform facilitating enrichment of CHCs in a high-throughput and rapid fashion by depleting healthy peripheral blood mononuclear cells (PBMCs). We demonstrated up to 96.5% depletion of PBMCs resulting in 18.6-fold enrichment of cancer cells. In PBMCs from pancreatic adenocarcinoma patients, the platform enriched neoplastic cells identified by their KRAS mutant status using droplet digital PCR with one hour of processing. Enrichment was achieved in 75% of the clinical samples analyzed, establishing this approach as a promising way to non-invasively analyze tumor cells from patients.

Circulating Hybrid Cells: A Novel Liquid Biomarker of Treatment Response in Gastrointestinal Cancers.

BACKGROUND: Real-time monitoring of treatment response with a liquid biomarker has potential to inform treatment decisions for patients with rectal adenocarcinoma (RAC), esophageal adenocarcinoma (EAC), and colorectal liver metastasis (CRLM). Circulating hybrid cells (CHCs), which have both immune and tumor cell phenotypes, are detectable in the peripheral blood of patients with gastrointestinal cancers, but their potential as an indicator of treatment response is unexplored. METHODS: Peripheral blood specimens were collected from RAC and EAC patients after neoadjuvant therapy (NAT) or longitudinally during therapy and evaluated for CHC levels by immunostaining. Receiver operating characteristics (ROCs) and the Kaplan-Meier method were used to analyze the CHC level as a predictor of pathologic response to NAT and disease-specific survival (DSS), respectively. RESULTS: Patients with RAC (n = 23) and EAC (n = 34) were sampled on the day of resection, and 11 patients (32%) demonstrated a pathologic complete response (pCR) to NAT. On ROC analysis, CHC levels successfully discriminated pCR from non-pCR with an area under the curve of 0.82 (95% confidence interval [CI], 0.71-0.92; P < 0.001). Additionally, CHC levels in the EAC patients correlated with residual nodal involvement (P = 0.026) and 1-year DSS (P = 0.029). The patients with RAC who were followed longitudinally during NAT (n = 2) and hepatic arterial infusion therapy for CRLM (n = 2) had CHC levels that decreased with therapy response and increased before clinical evidence of disease progression. CONCLUSION: Circulating hybrid cells are a novel blood-based biomarker with potential for monitoring treatment response and disease progression to help guide decisions for further systemic therapy, definitive resection, and post-therapy surveillance. Additional validation studies of CHCs are warranted.

Relevance of circulating hybrid cells as a non-invasive biomarker for myriad solid tumors.

Metastatic progression defines the final stages of tumor evolution and underlies the majority of cancer-related deaths. The heterogeneity in disseminated tumor cell populations capable of seeding and growing in distant organ sites contributes to the development of treatment resistant disease. We recently reported the identification of a novel tumor-derived cell population, circulating hybrid cells (CHCs), harboring attributes from both macrophages and neoplastic cells, including functional characteristics important to metastatic spread. These disseminated hybrids outnumber conventionally defined circulating tumor cells (CTCs) in cancer patients. It is unknown if CHCs represent a generalized cancer mechanism for cell dissemination, or if this population is relevant to the metastatic cascade. Herein, we detect CHCs in the peripheral blood of patients with cancer in myriad disease sites encompassing epithelial and non-epithelial malignancies. Further, we demonstrate that in vivo-derived hybrid cells harbor tumor-initiating capacity in murine cancer models and that CHCs from human breast cancer patients express stem cell antigens, features consistent with the potential to seed and grow at metastatic sites. Finally, we reveal heterogeneity of CHC phenotypes reflect key tumor features, including oncogenic mutations and functional protein expression. Importantly, this novel population of disseminated neoplastic cells opens a new area in cancer biology and renewed opportunity for battling metastatic disease.

Circulating hybrid cells predict presence of occult nodal metastases in oral cavity carcinoma.

BACKGROUND: Levels of circulating hybrid cells (CHCs), a newly identified circulating tumor cell (CTC), correlate with disease stage and progression in cancer. We investigated their utility to risk-stratify patients with clinically N0 (cN0) oral cavity squamous cell carcinoma (OCSCC), and to identify patients with occult cervical lymph node metastases (pN+). METHODS: We analyzed peripheral blood samples for CHCs with co-expression of cytokeratin (tumor) and CD45 (leukocyte) from 22 patients with cN0 OCSCC using immunofluorescence microscopy, then correlated levels with pathologic lymph node status. RESULTS: CHC levels exceeded CTCs and correlated with the presence of both clinically overt (p = 0.002) and occult nodal metastases (p = 0.006). CONCLUSIONS: For evaluated cN0 OCSCC patients, those with cN0 → pN+ status harbored elevated CHC levels compared to patients without occult disease. Our findings highlight a promising blood-based biologic assay with potential utility to determine the necessity of surgical neck dissection for staging and treatment.

Randomized Controlled Trial Comparing Femtosecond Laser-Assisted with Conventional Phacoemulsification on Dense Cataracts.

PURPOSE: To compare the benefit of femtosecond laser-assisted cataract surgery (FLACS) versus phacoemulsification (PE) and 2 fragmentation patterns in managing dense cataracts. DESIGN: Randomized controlled trial. METHODS: Patients with nuclear opacity (NO) grade >5 (Lens Opacities Classification System III) were enrolled at the Singapore National Eye Centre. Patients who were unsuitable for FLACS, whose corneal endothelial cell count (ECC) was <1,500 cells/mm2, or had cataracts with additional complexities were excluded from the study. Eyes were randomized to PE, 600 µm grid (FLACSg), or 16-segment fragmentation (FLACS16) in 2:1:1 ratio. The Victus (Bausch & Lomb) laser platform and in situ phacoemulsification chop technique was used. Data for patient demographics, preoperative, and 1 month postoperative best-corrected visual acuity (BCVA), ECC, effective phacoemulsification time (EPT), and perioperative complications were collected. Outcome measurements were the loss of ECC at 1 month and EPT. RESULTS: Ninety-three patients were randomized to PE (48), FLACSg (22), and FLACS16 (23). Majority were Chinese (87; 93.5%). Mean age was 74.3 ± 8.8 years of age. Cataracts were mostly graded as NO 5-6 (49; 61.3%). EPT among treatment arms was not different (P = .097, one-way ANOVA) but was significantly higher for NO >6 than NO <6 (P < .001, general linear model). ECC loss was significantly less in FLACSg than in PE (P = .018, Bonferroni correction). Mean 1-month postoperative LogMAR BCVA (0.23 ± 0.20) was significantly better than preoperative BCVA (1.02 ± 0.85; P < .001, paired t test) but not different between PE and FLACS. CONCLUSIONS: FLACSg but not FLACS16 significantly lowered the mean ECC loss during phacoemulsification in dense cataracts.

Deconstructing tumor heterogeneity: the stromal perspective.

Significant advances have been made towards understanding the role of immune cell-tumor interplay in either suppressing or promoting tumor growth, progression, and recurrence, however, the roles of additional stromal elements, cell types and/or cell states remain ill-defined. The overarching goal of this NCI-sponsored workshop was to highlight and integrate the critical functions of non-immune stromal components in regulating tumor heterogeneity and its impact on tumor initiation, progression, and resistance to therapy. The workshop explored the opposing roles of tumor supportive versus suppressive stroma and how cellular composition and function may be altered during disease progression. It also highlighted microenvironment-centered mechanisms dictating indolence or aggressiveness of early lesions and how spatial geography impacts stromal attributes and function. The prognostic and therapeutic implications as well as potential vulnerabilities within the heterogeneous tumor microenvironment were also discussed. These broad topics were included in this workshop as an effort to identify current challenges and knowledge gaps in the field.

Stem Cell Marker Expression in Early Stage Colorectal Cancer is Associated with Recurrent Intestinal Neoplasia.

BACKGROUND: Colorectal cancer (CRC) ranks second in cancer deaths worldwide and presents multiple management challenges, one of which is identifying high risk stage II disease that may benefit from adjuvant therapy. Molecular biomarkers, such as ones that identify stem cell activity, could better stratify high-risk cohorts for additional treatment. METHODS: To identify possible biomarkers of high-risk disease in early-stage CRC, a discovery set (n = 66) of advanced-stage tumors were immunostained with antibodies to stemness proteins (CD166, CD44, CD26, and LGR5) and then digitally analyzed. Using a second validation cohort (n = 54) of primary CRC tumors, we analyzed protein and gene expression of CD166 across disease stages, and extended our analyses to CD166-associated genes (LGR5, ASCL2, BMI1, POSTN, and VIM) by qRT-PCR. RESULTS: Stage III and metastatic CRC tumors highly expressed stem cell-associated proteins, CD166, CD44, and LGR5. When evaluated across stages, CD166 protein expression was elevated in advanced-stage compared to early-stage tumors. Notably, a small subset of stage I and II cancers harbored elevated CD166 protein expression, which correlated with development of recurrent cancer or adenomatous polyps. Gene expression analyses of CD166-associated molecules revealed elevated ASCL2 in primary tumors from patients who recurred. CONCLUSIONS: We identified a protein signature prognostic of aggressive disease in early stage CRC. Stem cell-associated protein and gene expression identified a subset of early-stage tumors associated with cancer recurrence and/or subsequent adenoma formation. Signatures for stemness offer promising fingerprints for stratifying early-stage patients at high risk of recurrence.

Measure Twice: Promise of Liquid Biopsy in Pediatric High-Grade Gliomas.

PURPOSE: To review and critique the current state of liquid biopsy in pHGG. MATERIALS AND METHODS: Published literature was reviewed for articles related to liquid biopsy in pediatric glioma and adult glioma with a focus on high-grade gliomas. RESULTS: This review discusses the current state of liquid biomarkers of pHGG and their potential applications for liquid biopsy development. CONCLUSIONS: While nascent, the progress toward identifying circulating analytes of pHGG primes the field of neuro-oncoogy for liquid biopsy development.