scholarly journals Deconstructing Pancreatic Cancer Using Next Generation-Omic Technologies–From Discovery to Knowledge-Guided Platforms for Better Patient Management

2022 ◽  
Vol 9 ◽  
Author(s):  
Daniel Schreyer ◽  
John P. Neoptolemos ◽  
Simon T. Barry ◽  
Peter Bailey
Keyword(s):  
Single Cell ◽  
Patient Management ◽  
Imaging Techniques ◽  
Ductal Adenocarcinoma ◽  
Liquid Biopsies ◽  
Tumour Heterogeneity ◽  
Cellular Targets ◽  
Spatially Resolved ◽  
Early Disease Detection ◽  
Brighter Future

Comprehensive molecular landscaping studies reveal a potentially brighter future for pancreatic ductal adenocarcinoma (PDAC) patients. Blood-borne biomarkers obtained from minimally invasive “liquid biopsies” are now being trialled for early disease detection and to track responses to therapy. Integrated genomic and transcriptomic studies using resectable tumour material have defined intrinsic patient subtypes and actionable genomic segments that promise a shift towards genome-guided patient management. Multimodal mapping of PDAC using spatially resolved single cell transcriptomics and imaging techniques has identified new potentially therapeutically actionable cellular targets and is providing new insights into PDAC tumour heterogeneity. Despite these rapid advances, defining biomarkers for patient selection remain limited. This review examines the current PDAC cancer biomarker ecosystem (identified in tumour and blood) and explores how advances in single cell sequencing and spatially resolved imaging modalities are being used to uncover new targets for therapeutic intervention and are transforming our understanding of this difficult to treat disease.

scholarly journals ctDNA-Based Liquid Biopsy of Cerebrospinal Fluid in Brain Cancer

Cancers ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1989
Author(s):  
Laura Escudero ◽  
Francisco Martínez-Ricarte ◽  
Joan Seoane
Keyword(s):  
Cerebrospinal Fluid ◽  
Brain Cancer ◽  
Liquid Biopsy ◽  
Therapeutic Strategy ◽  
Residual Disease ◽  
Imaging Techniques ◽  
Prognostic Information ◽  
Tumour Heterogeneity ◽  
Diagnosis And Prognosis ◽  
Cns Malignancies

The correct characterisation of central nervous system (CNS) malignancies is crucial for accurate diagnosis and prognosis and also the identification of actionable genomic alterations that can guide the therapeutic strategy. Surgical biopsies are performed to characterise the tumour; however, these procedures are invasive and are not always feasible for all patients. Moreover, they only provide a static snapshot and can miss tumour heterogeneity. Currently, monitoring of CNS cancer is performed by conventional imaging techniques and, in some cases, cytology analysis of the cerebrospinal fluid (CSF); however, these techniques have limited sensitivity. To overcome these limitations, a liquid biopsy of the CSF can be used to obtain information about the tumour in a less invasive manner. The CSF is a source of cell-free circulating tumour DNA (ctDNA), and the analysis of this biomarker can characterise and monitor brain cancer. Recent studies have shown that ctDNA is more abundant in the CSF than plasma for CNS malignancies and that it can be sequenced to reveal tumour heterogeneity and provide diagnostic and prognostic information. Furthermore, analysis of longitudinal samples can aid patient monitoring by detecting residual disease or even tracking tumour evolution at relapse and, therefore, tailoring the therapeutic strategy. In this review, we provide an overview of the potential clinical applications of the analysis of CSF ctDNA and the challenges that need to be overcome in order to translate research findings into a tool for clinical practice.

scholarly journals Cryopreservation of human cancers conserves tumour heterogeneity for single-cell multi-omics analysis

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Sunny Z. Wu ◽  
Daniel L. Roden ◽  
Ghamdan Al-Eryani ◽  
Nenad Bartonicek ◽  
Kate Harvey ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
High Throughput ◽  
Single Cells ◽  
Cellular Heterogeneity ◽  
Tumour Heterogeneity ◽  
Fresh Tissue ◽  
Human Cancers ◽  
Cryopreserved Cell ◽  
Single Cell Rna Sequencing

Abstract Background High throughput single-cell RNA sequencing (scRNA-Seq) has emerged as a powerful tool for exploring cellular heterogeneity among complex human cancers. scRNA-Seq studies using fresh human surgical tissue are logistically difficult, preclude histopathological triage of samples, and limit the ability to perform batch processing. This hindrance can often introduce technical biases when integrating patient datasets and increase experimental costs. Although tissue preservation methods have been previously explored to address such issues, it is yet to be examined on complex human tissues, such as solid cancers and on high throughput scRNA-Seq platforms. Methods Using the Chromium 10X platform, we sequenced a total of ~ 120,000 cells from fresh and cryopreserved replicates across three primary breast cancers, two primary prostate cancers and a cutaneous melanoma. We performed detailed analyses between cells from each condition to assess the effects of cryopreservation on cellular heterogeneity, cell quality, clustering and the identification of gene ontologies. In addition, we performed single-cell immunophenotyping using CITE-Seq on a single breast cancer sample cryopreserved as solid tissue fragments. Results Tumour heterogeneity identified from fresh tissues was largely conserved in cryopreserved replicates. We show that sequencing of single cells prepared from cryopreserved tissue fragments or from cryopreserved cell suspensions is comparable to sequenced cells prepared from fresh tissue, with cryopreserved cell suspensions displaying higher correlations with fresh tissue in gene expression. We showed that cryopreservation had minimal impacts on the results of downstream analyses such as biological pathway enrichment. For some tumours, cryopreservation modestly increased cell stress signatures compared to freshly analysed tissue. Further, we demonstrate the advantage of cryopreserving whole-cells for detecting cell-surface proteins using CITE-Seq, which is impossible using other preservation methods such as single nuclei-sequencing. Conclusions We show that the viable cryopreservation of human cancers provides high-quality single-cells for multi-omics analysis. Our study guides new experimental designs for tissue biobanking for future clinical single-cell RNA sequencing studies.

scholarly journals Single-cell transcriptomic analysis of mIHC images via antigen mapping

2021 ◽  
Vol 7 (10) ◽  
pp. eabc5464
Author(s):  
Kiya W. Govek ◽  
Emma C. Troisi ◽  
Zhen Miao ◽  
Rachael G. Aubin ◽  
Steven Woodhouse ◽  
...  
Keyword(s):  
Single Cell ◽  
Spatial Patterns ◽  
Cell Types ◽  
Level Of Detail ◽  
Cell Populations ◽  
Sequencing Data ◽  
Spatially Resolved ◽  
Murine Spleen ◽  
Single Cell Rna Sequencing ◽  
Antibody Panel

Highly multiplexed immunohistochemistry (mIHC) enables the staining and quantification of dozens of antigens in a tissue section with single-cell resolution. However, annotating cell populations that differ little in the profiled antigens or for which the antibody panel does not include specific markers is challenging. To overcome this obstacle, we have developed an approach for enriching mIHC images with single-cell RNA sequencing data, building upon recent experimental procedures for augmenting single-cell transcriptomes with concurrent antigen measurements. Spatially-resolved Transcriptomics via Epitope Anchoring (STvEA) performs transcriptome-guided annotation of highly multiplexed cytometry datasets. It increases the level of detail in histological analyses by enabling the systematic annotation of nuanced cell populations, spatial patterns of transcription, and interactions between cell types. We demonstrate the utility of STvEA by uncovering the architecture of poorly characterized cell types in the murine spleen using published cytometry and mIHC data of this organ.

scholarly journals TAMI-45. PHENOGENOMIC CHARACTERIZATION OF IMMUNOMODULATORY PURINERGIC SIGNALING IN GLIOBLASTOMA

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii222-ii223
Author(s):  
Shannon Coy ◽  
Rumana Rashid ◽  
Sylwia Stopka ◽  
Jia-Ren Lin ◽  
Philipp Euskirchen ◽  
...  
Keyword(s):  
Clinical Outcome ◽  
Single Cell ◽  
Purinergic Signaling ◽  
Progression Free Survival ◽  
Tissue Imaging ◽  
Phenotypic Properties ◽  
Spatially Resolved ◽  
Therapeutic Benefits ◽  
Adenosine Concentration ◽  
Cd73 Expression

Abstract INTRODUCTION Purinergic signaling plays critical roles in the regulation of tumor growth and anti-tumor immunity via autocrine/paracrine binding of metabolites to receptors on neoplastic and non-neoplastic populations. Extracellular purine concentrations are mediated by the ectonucleotidase enzymes CD39 and CD73, which catabolize ATP to adenosine. Within tumors such as glioblastoma, neoplastic, immune, and stromal cells expressing these enzymes may co-localize to generate immunosuppressive adenosine-rich environments. However, the composition, architecture, and phenotypic properties of these tumor ecosystems and their relationship to tumor genotype are poorly characterized. METHODS We quantified CD73 expression by immunohistochemistry in a cohort of CNS tumors [meningiomas(n=222), gliomas(n=244), ependymomas(n=44), medulloblastomas(n=24), and craniopharyngiomas(n=38)]. We used publicly-available single-cell RNA-seq data and 36-marker multiplexed tissue imaging (t-CyCIF) of 139 clinically and genomically annotated glioblastoma resections to characterize CD39 and CD73-expressing populations, define the immune architecture and tumor cell-states at single cell resolution, and identify markers of clinical outcome. We used mass spectrometry imaging (MALDI-MSI) to generate spatially-resolved quantification of purine metabolite levels in glioblastoma resections (n=10). RESULTS CD73 exhibited strong expression in a subset of gliomas and meningiomas but was typically not expressed in ependymomas or medulloblastomas. CD73 expression correlated with poor progression-free-survival in IDH-wildtype glioblastoma (p=0.04). scRNA-seq and t-CyCIF in glioblastoma showed CD73 expression in tumor cells, and CD39 expression in macrophages and endothelial cells. MALDI-MSI showed significantly greater adenosine concentrations (3.5-fold;p=0.04) in glioblastomas with high CD73 expression. scRNA-seq showed direct correlations between stem-like mRNA expression, proliferation, and CD73 expression in DIPG. CD73 expression significantly correlated with EGFR amplification, interferon signaling, and PD-L1 expression in glioblastoma. CONCLUSIONS Phenogenomic analysis of purinergic immunomodulatory signaling revealed significant interplay between CD73 activity and genotype, adenosine concentration, differentiation-state, clinical outcome, and possible interaction between CD39-positive macrophages and CD73-positive neoplastic cells. Anti-CD73 therapy may provide therapeutic benefits in glioblastoma by blunting immunosuppressive and oncogenic adenosine signaling.

scholarly journals High Clinical Value of Liquid Biopsy to Detect Circulating Tumor Cells and Tumor Exosomes in Pancreatic Ductal Adenocarcinoma Patients Eligible for Up-Front Surgery

Cancers ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 1656 ◽  
Author(s):  
Etienne Buscail ◽  
Catherine Alix-Panabières ◽  
Pascaline Quincy ◽  
Thomas Cauvin ◽  
Alexandre Chauvet ◽  
...  
Keyword(s):  
Pancreatic Ductal Adenocarcinoma ◽  
Tumor Cells ◽  
Circulating Tumor Cells ◽  
Liquid Biopsy ◽  
Neoadjuvant Treatment ◽  
Digital Pcr ◽  
Portal Blood ◽  
Ductal Adenocarcinoma ◽  
Clinical Value ◽  
Liquid Biopsies

Purpose: Expediting the diagnosis of pancreatic ductal adenocarcinoma (PDAC) would benefit care management, especially for the start of treatments requiring histological evidence. This study evaluated the combined diagnostic performance of circulating biomarkers obtained by peripheral and portal blood liquid biopsy in patients with resectable PDAC. Experimental design: Liquid biopsies were performed in a prospective translational clinical trial (PANC-CTC #NCT03032913) including 22 patients with resectable PDAC and 28 noncancer controls from February to November 2017. Circulating tumor cells (CTCs) were detected using the CellSearch® method or after RosetteSep® enrichment combined with CRISPR/Cas9-improved KRAS mutant alleles quantification by droplet digital PCR. CD63 bead-coupled Glypican-1 (GPC1)-positive exosomes were quantified by flow cytometry. Results: Liquid biopsies were positive in 7/22 (32%), 13/22 (59%), and 14/22 (64%) patients with CellSearch® or RosetteSep®-based CTC detection or GPC1-positive exosomes, respectively, in peripheral and/or portal blood. Liquid biopsy performance was improved in portal blood only with CellSearch®, reaching 45% of PDAC identification (5/11) versus 10% (2/22) in peripheral blood. Importantly, combining CTC and GPC1-positive-exosome detection displayed 100% of sensitivity and 80% of specificity, with a negative predictive value of 100%. High levels of GPC1+-exosomes and/or CTC presence were significantly correlated with progression-free survival and with overall survival when CTC clusters were found. Conclusion: This study is the first to evaluate combined CTC and exosome detection to diagnose resectable pancreatic cancers. Liquid biopsy combining several biomarkers could provide a rapid, reliable, noninvasive decision-making tool in early, potentially curable pancreatic cancer. Moreover, the prognostic value could select patients eligible for neoadjuvant treatment before surgery. This exploratory study deserves further validation.

scholarly journals A Spatial Quantitative Systems Pharmacology Platform spQSP-IO for Simulations of Tumor—Immune Interactions and Effects of Checkpoint Inhibitor Immunotherapy

Cancers ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 3751
Author(s):  
Chang Gong ◽  
Alvaro Ruiz-Martinez ◽  
Holly Kimko ◽  
Aleksander S. Popel
Keyword(s):  
Spatial Heterogeneity ◽  
Spatial Data ◽  
Immune Cell ◽  
Imaging Techniques ◽  
Tumor Development ◽  
Systems Pharmacology ◽  
Quantitative Systems Pharmacology ◽  
Spatially Resolved ◽  
Biomarker Analysis ◽  
Model Platform

Quantitative systems pharmacology (QSP) models have become increasingly common in fundamental mechanistic studies and drug discovery in both academic and industrial environments. With imaging techniques widely adopted and other spatial quantification of tumor such as spatial transcriptomics gaining traction, it is crucial that these data reflecting tumor spatial heterogeneity be utilized to inform the QSP models to enhance their predictive power. We developed a hybrid computational model platform, spQSP-IO, to extend QSP models of immuno-oncology with spatially resolved agent-based models (ABM), combining their powers to track whole patient-scale dynamics and recapitulate the emergent spatial heterogeneity in the tumor. Using a model of non-small-cell lung cancer developed based on this platform, we studied the role of the tumor microenvironment and cancer–immune cell interactions in tumor development and applied anti-PD-1 treatment to virtual patients and studied how the spatial distribution of cells changes during tumor growth in response to the immune checkpoint inhibition treatment. Using parameter sensitivity analysis and biomarker analysis, we are able to identify mechanisms and pretreatment measurements correlated with treatment efficacy. By incorporating spatial data that highlight both heterogeneity in tumors and variability among individual patients, spQSP-IO models can extend the QSP framework and further advance virtual clinical trials.

scholarly journals Single-Cell Transcriptomics Reveals the Expression of Aging- and Senescence-Associated Genes in Distinct Cancer Cell Populations

Cells ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 3126
Author(s):  
Dominik Saul ◽  
Robyn Laura Kosinsky
Keyword(s):  
Single Cell ◽  
Myelogenous Leukemia ◽  
Ductal Adenocarcinoma ◽  
Cell Populations ◽  
Rna Seq ◽  
Healthy Control ◽  
Transcriptional Changes ◽  
The Relationship ◽  
Senescence Associated Genes

The human aging process is associated with molecular changes and cellular degeneration, resulting in a significant increase in cancer incidence with age. Despite their potential correlation, the relationship between cancer- and ageing-related transcriptional changes is largely unknown. In this study, we aimed to analyze aging-associated transcriptional patterns in publicly available bulk mRNA-seq and single-cell RNA-seq (scRNA-seq) datasets for chronic myelogenous leukemia (CML), colorectal cancer (CRC), hepatocellular carcinoma (HCC), lung cancer (LC), and pancreatic ductal adenocarcinoma (PDAC). Indeed, we detected that various aging/senescence-induced genes (ASIGs) were upregulated in malignant diseases compared to healthy control samples. To elucidate the importance of ASIGs during cell development, pseudotime analyses were performed, which revealed a late enrichment of distinct cancer-specific ASIG signatures. Notably, we were able to demonstrate that all cancer entities analyzed in this study comprised cell populations expressing ASIGs. While only minor correlations were detected between ASIGs and transcriptome-wide changes in PDAC, a high proportion of ASIGs was induced in CML, CRC, HCC, and LC samples. These unique cellular subpopulations could serve as a basis for future studies on the role of aging and senescence in human malignancies.

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