Identification of epithelial and mesenchymal circulating tumor cells in clonal lineage of an aggressive prostate cancer case

Polyploid cancer cells reveal signatures of chemotherapy resistance

Therapeutic resistance in cancer significantly contributes to mortality, with many patients eventually experiencing recurrence after initial treatment responses. Recent studies have identified therapy-resistant large polyploid cancer cells in patient tissues, particularly in late-stage prostate cancer, linking them to advanced disease and relapse. Here, we analyzed bone marrow aspirates from 44 advanced prostate cancer patients and found the presence of circulating tumor cells with increased genomic content (CTC-IGC) was significantly associated with poorer progression-free survival. Single cell copy number profiling of CTC-IGC displayed clonal origins with typical CTCs, suggesting complete polyploidization. Induced polyploid cancer cells from PC3 and MDA-MB-231 cell lines treated with docetaxel or cisplatin were examined through single cell DNA sequencing, RNA sequencing, and protein immunofluorescence. Novel RNA and protein markers, including HOMER1, TNFRSF9, and LRP1, were identified as linked to chemotherapy resistance. These markers were also present in a subset of patient CTCs and are associated with recurrence in public gene expression data. This study highlights the prognostic significance of large polyploid tumor cells, their role in chemotherapy resistance, and the expression of markers tied to cancer relapse, offering new potential avenues for therapeutic development.

Unsupervised Detection of Rare Events in Liquid Biopsy Assays

The use of liquid biopsies in the detection, diagnosis and treatment monitoring of different types of cancers and other diseases often requires identifying and enumerating instances of analytes that are rare. Most current techniques that aim to computationally isolate these rare instances or events first learn the signature of the event, and then scan the appropriate biological assay for this signature. While such techniques have proven to be very useful, they are limited because they must first establish what signature to look for, and only then identify events that are consistent with this signature. In contrast to this, in this study, we present an automated approach that does not require the knowledge of the signature of the rare event. It works by breaking the assay into a sequence of components, learning the probability distribution of these components, and then isolating those that are rare. This is done with the help of deep generative algorithms in an unsupervised manner, meaning without a-priori knowledge of the rare event associated with an analyte. In this study, this approach is applied to immunofluorescence microscopy images of peripheral blood, where it is shown that it successfully isolates biologically relevant events in blood from normal donors spiked with cancer-related cells and in blood from patients with late-stage breast cancer.

Clinical significance of stratifying prostate cancer patients through specific circulating genes

Patient stratification remains a challenge for optimal treatment of prostate cancer (PCa). This clinical heterogeneity implies intra-tumoural heterogeneity, with different prostate epithelial cell subtypes not all targeted by current treatments. We reported that such cell subtypes are traceable in liquid biopsies through representative transcripts. Expanding on this concept, we included 57 genes representing cell subtypes, drug targets and relevant to resistance as non-invasive biomarkers for stratification. This panel was tested by RT-qPCR (quantitative reverse transcription polymerase chain reaction) in blood of controls and different categories of PCa patients. Overall, circulating transcripts showed predictive value throughout the disease. Those with aggressive pathological features such as intra-ductal carcinoma at diagnosis showed more genes over-expressed. In metastatic patients, signatures of subtypes or resistance were associated with treatments, progression-free survival and overall survival. Altogether, testing markers of cell diversity, an intrinsic feature of tumours, and drug targets via liquid biopsies represents a valuable means to stratify patients and predict responses to current or new therapeutic modalities. Over-expressed drug target genes suggest potential benefit from targeted treatments, justifying new clinical trials to offer patient-tailored strategies to eventually impact on PCa mortality.

Advanced single-cell and spatial analysis with high-multiplex characterization of circulating tumor cells and tumor tissue in prostate cancer: Unveiling resistance mechanisms with the CoDuCo in situ assay

BACKGROUND

Metastatic prostate cancer is a highly heterogeneous and dynamic disease and practicable tools for patient stratification and resistance monitoring are urgently needed. Liquid biopsy analysis of circulating tumor cells (CTCs) and circulating tumor DNA are promising, however, comprehensive testing is essential due to diverse mechanisms of resistance. Previously, we demonstrated the utility of mRNA-based in situ padlock probe hybridization for characterizing CTCs.

METHODS

We have developed a novel combinatorial dual-color (CoDuCo) assay for in situ mRNA detection, with enhanced multiplexing capacity, enabling the simultaneous analysis of up to 15 distinct markers. This approach was applied to CTCs, corresponding tumor tissue, cancer cell lines, and peripheral blood mononuclear cells for single-cell and spatial gene expression analysis. Using supervised machine learning, we trained a random forest classifier to identify CTCs. Image analysis and visualization of results was performed using open-source Python libraries, CellProfiler, and TissUUmaps.

RESULTS

Our study presents data from multiple prostate cancer patients, demonstrating the CoDuCo assay's ability to visualize diverse resistance mechanisms, such as neuroendocrine differentiation markers (SYP, CHGA, NCAM1) and AR-V7 expression. In addition, druggable targets and predictive markers (PSMA, DLL3, SLFN11) were detected in CTCs and formalin-fixed, paraffin-embedded tissue. The machine learning-based CTC classification achieved high performance, with a recall of 0.76 and a specificity of 0.99.

CONCLUSIONS

The combination of high multiplex capacity and microscopy-based single-cell analysis is a unique and powerful feature of the CoDuCo in situ assay. This synergy enables the simultaneous identification and characterization of CTCs with epithelial, epithelial-mesenchymal, and neuroendocrine phenotypes, the detection of CTC clusters, the visualization of CTC heterogeneity, as well as the spatial investigation of tumor tissue. This assay holds significant potential as a tool for monitoring dynamic molecular changes associated with drug response and resistance in prostate cancer.

Multi-Omic Characterization of Single Cells and Cell-Free Components Detected in the Cerebrospinal Fluid of Patients with Leptomeningeal Disease

BACKGROUND/OBJECTIVES

Up to 30% of patients with breast cancers will develop brain or leptomeningeal metastases, and this risk is especially high with HER2-positive cancers. For patients with central nervous system metastases, cerebrospinal fluid (CSF) liquid biopsies are a promising opportunity to monitor disease, inform treatment, and predict prognosis. This pilot study investigated CSF liquid biopsy analytes from three patients diagnosed with central nervous system metastases based on imaging but not confirmed via clinical cytology.

METHODS

The detection of cellular analytes with the non-enrichment high-definition single-cell assay (HDSCA3.0) workflow was compared between the CSF and matched peripheral blood (PB) samples.

RESULTS

Circulating tumor cells (CTCs) were detected in the CSF but not the PB and were subsequently molecularly characterized using single-cell genomics and targeted multiplexed proteomics to reveal a clonal population of phenotypically heterogeneous cells. There was a lack of concordance in the copy number alteration profiles between CTCs and cell-free DNA (cfDNA) in the CSF. Extracellular vesicle surface marker analysis in CSF revealed a prominent signal among tetraspanins (CD9/CD63/CD81), with CD81 exhibiting the highest signal across all patients.

CONCLUSIONS

The data presented suggest that CSF could be a useful tool for diagnosing and assessing disease severity.

Diversity of the Circulating Tumor Markers: Perspectives of a Multimodal Liquid Biopsy

Over the past decade, liquid biopsy (LB) has become a routine diagnostic test essential for the treatment of malignant tumors of various localizations. Its capabilities include early diagnosis, molecular genotyping, prognosis, prediction, and monitoring of tumor response. Typically, liquid biopsy involves the extraction of a single type of tumor-derived molecules or cellular elements from blood and subsequent molecular analysis. These elements may include circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), circulating tumor RNA (ctRNA), or contents of extracellular vesicles (exosomes). Despite the technical sophistication of molecular analysis methods for circulating biomarkers, this diagnostic approach has limited relevance. In a significant proportion of cancer patients (ranging from 10 to 50%, depending on the tumor type), none of these analytes can be detected and analyzed, even in the presence of large, progressing neoplastic foci in the body. It seems reasonable to suggest that heterogeneous fractions of the circulating tumor-specific biomarkers complement each other, thus simultaneous analysis of several fractions will not only increase sensitivity of the method but also more accurately characterize and predict the clinical situation. This review examines the possibilities and advantages of applying a combined multiparametric approach to liquid biopsy, which involves testing multiple circulating analytes in a single blood sample.

Polyploid cancer cells reveal signatures of chemotherapy resistance

Therapeutic resistance in cancer significantly contributes to mortality, with many patients eventually experiencing recurrence after initial treatment responses. Recent studies have identified therapy-resistant large polyploid cancer cells in patient tissues, particularly in late-stage prostate cancer, linking them to advanced disease and relapse. Here, we analyzed bone marrow aspirates from 44 advanced prostate cancer patients and found the presence of CTC-IGC was significantly associated with poorer progression-free survival. Single cell copy number profiling of CTC-IGC displayed clonal origins with typical CTCs, suggesting complete polyploidization. Induced polyploid cancer cells from PC3 and MDA-MB-231 cell lines treated with docetaxel or cisplatin were examined through single cell DNA sequencing, RNA sequencing, and protein immunofluorescence. Novel RNA and protein markers, including HOMER1, TNFRSF9, and LRP1, were identified as linked to chemotherapy resistance. These markers were also present in a subset of patient CTCs and associated with recurrence in public gene expression data. This study highlights the prognostic significance of large polyploid tumor cells, their role in chemotherapy resistance, and their expression of markers tied to cancer relapse, offering new potential avenues for therapeutic development.

Circulation of rare events in the liquid biopsy for early detection of lung mass lesions

BACKGROUND

Lung cancer screening with low-dose computed tomography (CT) scans (LDCT) has reduced mortality for patients with high-risk smoking histories, but it has significant limitations: LDCT screening implementation remains low, high rates of false-positive scans, and current guidelines exclude those without smoking histories. We sought to explore the utility of liquid biopsy (LBx) in early cancer screening and diagnosis of lung cancer.

METHODS

Using the high-definition single-cell assay workflow, we analyzed 99 peripheral blood samples from three cohorts: normal donors (NDs) with no known pathology (n = 50), screening CT patients (n = 25) with Lung-RADS score of 1-2, and biopsy (BX) patients (n = 24) with abnormal CT scans requiring tissue biopsy.

RESULTS

For CT and BX patients, demographic information was roughly equivalent; however, average pack-years smoked differed. A total of 14 (58%) BX patients were diagnosed with primary lung cancer (BX+). The comparison of the rare event enumerations among the cohorts revealed a greater incidence of total events, rare cells, and oncosomes, as well as specific cellular phenotypes in the CT and BX cohorts compared with the ND cohort. LBx analytes were also significantly elevated in the BX compared with the CT samples, but there was no difference between BX+ and BX- samples.

CONCLUSIONS

The data support the utility of the LBx in distinguishing patients with an alveolar lesion from those without, providing a potential avenue for prescreening before LDCT.

Polyploid cancer cells reveal signatures of chemotherapy resistance

Therapeutic resistance in cancer significantly contributes to mortality, with many patients eventually experiencing recurrence after initial treatment responses. Recent studies have identified therapy-resistant large polyploid cancer cells in patient tissues, particularly in late-stage prostate cancer, linking them to advanced disease and relapse. Here, we analyzed bone marrow aspirates from 44 advanced prostate cancer patients and found the presence of circulating tumor cells with increased genomic content (CTC-IGC) was significantly associated with poorer progression-free survival. Single cell copy number profiling of CTC-IGC displayed clonal origins with typical CTCs, suggesting complete polyploidization. Induced polyploid cancer cells from PC3 and MDA-MB-231 cell lines treated with docetaxel or cisplatin were examined through single cell DNA sequencing, RNA sequencing, and protein immunofluorescence. Novel RNA and protein markers, including HOMER1, TNFRSF9, and LRP1, were identified as linked to chemotherapy resistance. These markers were also present in a subset of patient CTCs and associated with recurrence in public gene expression data. This study highlights the prognostic significance of large polyploid tumor cells, their role in chemotherapy resistance, and their expression of markers tied to cancer relapse, offering new potential avenues for therapeutic development.

Determining the efficacy of ExThera Seraph100 blood filtration in patients diagnosed with pancreatic cancer through the liquid biopsy

BACKGROUND

Cancer becomes lethal as it spreads from the primary site to the rest of the body. Circulating tumor cells (CTCs) are biomarkers of disease progression and have been associated with decreased overall survival. Blood filtration is a novel concept for removing CTCs from circulation to improve patient prognosis.

METHODS

This study utilizes liquid biopsy to assess the efficacy of ExThera Medical's Seraph® 100 Microbind® Affinity Blood Filter on the blood of patients with pancreatic ductal adenocarcinoma (PDAC) using the third generation high-definition single cell assay workflow. Blood samples from treatment-naïve PDAC patients were collected and analyzed to characterize the CTCs and other rare cells present before and after filtration.

RESULTS

Examination of 6 paired portal vein blood (PoVB) samples demonstrated a statistically significant decrease in total rare cells, total cytokeratin (CK)+ cells, and CTCs across all patients due to filtration. Furthermore, analysis of 2 paired peripheral blood (PB) samples showed a decrease in total rare cells, total CK+ cells, and specific phenotypes of rare cells after filtration.

DISCUSSION

These preliminary results demonstrate initial proof of concept that this filtration device can remove CTCs from circulation and may therefore be useful as a therapy or adjunct in PDAC patient care.

Resolving tumor evolution: a phylogenetic approach

The evolutionary dynamics of cancer, characterized by its profound heterogeneity, demand sophisticated tools for a holistic understanding. This review delves into tumor phylogenetics, an essential approach bridging evolutionary biology with oncology, offering unparalleled insights into cancer's evolutionary trajectory. We provide an overview of the workflow, encompassing study design, data acquisition, and phylogeny reconstruction. Notably, the integration of diverse data sets emerges as a transformative step, enhancing the depth and breadth of evolutionary insights. With this integrated perspective, tumor phylogenetics stands poised to redefine our understanding of cancer evolution and influence therapeutic strategies.

Longitudinal tracking of circulating rare events in the liquid biopsy of stage III-IV non-small cell lung cancer patients

In the United States, lung cancer is the second most common type of cancer with non-small cell lung cancer (NSCLC) encompassing around 85% of total lung cancer cases. Late-stage patients with metastatic disease have worsening prognosis, highlighting the importance of longitudinal disease monitoring. Liquid biopsy (LBx) represents a way for physicians to non-invasively track tumor analytes, such as circulating tumor cells (CTCs), and understand tumor progression in real-time through analyzing longitudinal blood samples. CTCs have been shown to be effective predictive biomarkers in measuring treatment efficacy and survival outcomes. We used the third-generation High-Definition Single Cell Assay (HDSCA3.0) workflow to analyze circulating rare events longitudinally during treatment in a cohort of 10 late-stage NSCLC patients, identifying rare events including circulating cancer cells (i.e., CTCs), and oncosomes. Here, we show (1) that there is a cancer specific LBx profile, (2) there is considerable heterogeneity of rare cells and oncosomes, and (3) that LBx data elements correlated with patient survival outcomes. Additional studies are warranted to understand the biological significance of the rare events detected, and the clinical potential of the LBx to monitor and predict response to treatment in NSCLC patient care.

Cancer-related cells and oncosomes in the liquid biopsy of pancreatic cancer patients undergoing surgery

Pancreatic ductal adenocarcinoma (PDAC) has a five-year survival rate of less than 10% due to its late diagnosis, rapid metastasis, and chemotherapeutic resistance. For a small proportion (10-20%) of early-stage patients however, surgical resection of the pancreatic tumor offers the best chance for survival but the effect of surgery on disease dissemination is unknown. The primary objective of this study was to characterize cellular and acellular blood-based analytes in portal and peripheral blood before pancreatic manipulation, during tumor dissection and immediately after surgical resection to determine the effects of the surgery. This study used the non-enriching third generation High-Definition Single Cell Assay (HDSCA3.0) workflow to investigate heterogeneous circulating rare cell population in the blood. Blood from both sites taken before surgical manipulation of the pancreas had significantly greater incidence of total rare cellular and acellular analytes than normal donor samples. Post-surgery portal and peripheral blood had significantly greater incidence of specific cellular and acellular subtypes compared to the matched pre- and during-surgery samples. Our results reveal that in patients with PDAC liquid biopsy analytes are increased in both the portal and peripheral blood; portal blood contains a higher frequency of analytes than in the peripheral blood; total analytes in the portal and peripheral blood samples were significantly associated with the tumor volume and pathological T stage; and the surgical procedure increased the blood levels of circulating cellular and acellular analytes, but not Epi.CTCs or Mes.CTCs. This study demonstrates liquid biopsy's utility in monitoring patients with PDAC with surgically resectable disease.

Liquid biopsy approach to monitor the efficacy and response to CAR-T cell therapy

BACKGROUND

Chimeric antigen receptor (CAR)-T cells are approved for use in the treatment of hematological malignancies. Axicabtagene ciloleucel (YESCARTA) and brexucabtagene autoleucel (TECARTUS) genetically modified autologous T cells expressing an anti-CD19 scFv based on the FMC63 clone have shown impressive response rates for the treatment of CD19+B cell malignancies, but there remain challenges in monitoring long-term persistence as well as the functional characterization of low-level persisting CAR-T cells in patients. Furthermore, due to CD19-negative driven relapse, having the capability to monitor patients with simultaneous detection of the B cell malignancy and persisting CAR-T cells in patient peripheral blood is important for ensuring timely treatment optionality and understanding relapse.

METHODS

This study demonstrates the development and technical validation of a comprehensive liquid biopsy, high-definition single cell assay (HDSCA)-HemeCAR for (1) KTE-X19 CAR-T cell identification and analysis and (2) simultaneously monitoring the CD19-epitope landscape on neoplastic B cells in cryopreserved or fresh peripheral blood. Proprietary anti-CD19 CAR reagents, healthy donor transduced CAR-T cells, and patient samples consisting of malignant B cell fractions from manufacturing were used for assay development.

RESULTS

The CAR-T assay showed an approximate limit of detection at 1 cell in 3 million with a sensitivity of 91%. Genomic analysis was additionally used to confirm the presence of the CAR transgene. This study additionally reports the successful completion of two B cell assays with multiple CD19 variants (FMC63 and LE-CD19) and a unique fourth channel biomarker (CD20 or CD22). In patient samples, we observed that CD19 isoforms were highly heterogeneous both intrapatient and interpatient.

CONCLUSIONS

With the simultaneous detection of the CAR-T cells and the B cell malignancy in patient peripheral blood, the HDSCA-HemeCAR workflow may be considered for risk monitoring and patient management.

New insights into the correlations between circulating tumor cells and target organ metastasis

Organ-specific metastasis is the primary cause of cancer patient death. The distant metastasis of tumor cells to specific organs depends on both the intrinsic characteristics of the tumor cells and extrinsic factors in their microenvironment. During an intermediate stage of metastasis, circulating tumor cells (CTCs) are released into the bloodstream from primary and metastatic tumors. CTCs harboring aggressive or metastatic features can extravasate to remote sites for continuous colonizing growth, leading to further lesions. In the past decade, numerous studies demonstrated that CTCs exhibited huge clinical value including predicting distant metastasis, assessing prognosis and monitoring treatment response et al. Furthermore, increasingly numerous experiments are dedicated to identifying the key molecules on or inside CTCs and exploring how they mediate CTC-related organ-specific metastasis. Based on the above molecules, more and more inhibitors are being developed to target CTCs and being utilized to completely clean CTCs, which should provide promising prospects to administer advanced tumor. Recently, the application of various nanomaterials and microfluidic technologies in CTCs enrichment technology has assisted to improve our deep insights into the phenotypic characteristics and biological functions of CTCs as a potential therapy target, which may pave the way for us to make practical clinical strategies. In the present review, we mainly focus on the role of CTCs being involved in targeted organ metastasis, especially the latest molecular mechanism research and clinical intervention strategies related to CTCs.

Automated Image Analysis for Characterization of Circulating Tumor Cells and Clusters Sorted by Magnetic Levitation

Magnetic levitation-based sorting technologies have revolutionized the detection and isolation of rare cells, including circulating tumor cells (CTCs) and circulating tumor cell clusters (CTCCs). Manual counting and quantification of these cells are prone to time-consuming processes, human error, and inter-observer variability, particularly challenging when heterogeneous cell types in 3D clusters are present. To overcome these challenges, we developed "Fastcount," an in-house MATLAB-based algorithm for precise, automated quantification and phenotypic characterization of CTCs and CTCCs, in both 2D and 3D. Fastcount is 120 times faster than manual counting and produces reliable results with a ±7.3% deviation compared to a trained laboratory technician. By analyzing 400 GB of fluorescence imaging data, we showed that Fastcount outperforms manual counting and commercial software when cells are aggregated in 3D or staining artifacts are present, delivering more accurate results. We further employed Fastcount for automated analysis of 3D image stacks obtained from CTCCs isolated from colorectal adenocarcinoma and renal cell carcinoma blood samples. Interestingly, we observed a highly heterogeneous spatial cellular composition within CTCCs, even among clusters from the same patient. Overall, Fastcount can be employed for various applications with lab-chip devices, such as CTC detection, CTCC analysis in 3D and cell detection in biosensors.

Cells in the polyaneuploid cancer cell (PACC) state have increased metastatic potential

Although metastasis is the leading cause of cancer deaths, it is quite rare at the cellular level. Only a rare subset of cancer cells (~ 1 in 1.5 billion) can complete the entire metastatic cascade: invasion, intravasation, survival in the circulation, extravasation, and colonization (i.e. are metastasis competent). We propose that cells engaging a Polyaneuploid Cancer Cell (PACC) phenotype are metastasis competent. Cells in the PACC state are enlarged, endocycling (i.e. non-dividing) cells with increased genomic content that form in response to stress. Single-cell tracking using time lapse microscopy reveals that PACC state cells have increased motility. Additionally, cells in the PACC state exhibit increased capacity for environment-sensing and directional migration in chemotactic environments, predicting successful invasion. Magnetic Twisting Cytometry and Atomic Force Microscopy reveal that cells in the PACC state display hyper-elastic properties like increased peripheral deformability and maintained peri-nuclear cortical integrity that predict successful intravasation and extravasation. Furthermore, four orthogonal methods reveal that cells in the PACC state have increased expression of vimentin, a hyper-elastic biomolecule known to modulate biomechanical properties and induce mesenchymal-like motility. Taken together, these data indicate that cells in the PACC state have increased metastatic potential and are worthy of further in vivo analysis.

Investigation of liquid biopsy analytes in peripheral blood of individuals after SARS-CoV-2 infection

BACKGROUND

Post-acute COVID-19 syndrome (PACS) is linked to severe organ damage. The identification and stratification of at-risk SARS-CoV-2 infected individuals is vital to providing appropriate care. This exploratory study looks for a potential liquid biopsy signal for PACS using both manual and machine learning approaches.

METHODS

Using a high definition single cell assay (HDSCA) workflow for liquid biopsy, we analysed 100 Post-COVID patients and 19 pre-pandemic normal donor (ND) controls. Within our patient cohort, 73 had received at least 1 dose of vaccination prior to SARS-CoV-2 infection. We stratified the COVID patients into 25 asymptomatic, 22 symptomatic COVID-19 but not suspected for PACS and 53 PACS suspected. All COVID-19 patients investigated in this study were diagnosed between April 2020 and January 2022 with a median 243 days (range 16-669) from diagnosis to their blood draw. We did a histopathological examination of rare events in the peripheral blood and used a machine learning model to evaluate predictors of PACS.

FINDINGS

The manual classification found rare cellular and acellular events consistent with features of endothelial cells and platelet structures in the PACS-suspected cohort. The three categories encompassing the hypothesised events were observed at a significantly higher incidence in the PACS-suspected cohort compared to the ND (p-value < 0.05). The machine learning classifier performed well when separating the NDs from Post-COVID with an accuracy of 90.1%, but poorly when separating the patients suspected and not suspected of PACS with an accuracy of 58.7%.

INTERPRETATION

Both the manual and the machine learning model found differences in the Post-COVID cohort and the NDs, suggesting the existence of a liquid biopsy signal after active SARS-CoV-2 infection. More research is needed to stratify PACS and its subsyndromes.

FUNDING

This work was funded in whole or in part by Fulgent Genetics, Kathy and Richard Leventhal and Vassiliadis Research Fund. This work was also supported by the National Cancer InstituteU54CA260591.