scholarly journals TMOD-27. A NEURAL CREST CELL SUBPOPULATION UNDERLIES INTRATUMOR HETEROGENEITY IN MENINGIOMA

2019 ◽  
Vol 21 (Supplement_6) ◽  
pp. vi268-vi268 ◽  
Author(s):  
Stephen Magill ◽  
Harish Vasudevan ◽  
Kyounghee Seo ◽  
S John Liu ◽  
Stephanie Hilz ◽  
...  
Keyword(s):  
Neural Crest ◽  
Rna Sequencing ◽  
Clonal Evolution ◽  
Neural Crest Cell ◽  
Cell Subpopulation ◽  
Intratumor Heterogeneity ◽  
Tumor Evolution ◽  
Molecular Heterogeneity ◽  
High Grade ◽  
Who Grade

Abstract BACKGROUND Meningiomas are the most common primary intracranial tumor, and high grade meningiomas are resistant to most cancer therapies. Intratumor heterogeneity is a recognized source of resistance to treatment in numerous malignancies. Thus, we hypothesized that investigating molecular heterogeneity in meningiomas would elucidate biologic drivers and shed light on tumor evolution and mechanisms of resistance. METHODS We collected 86 spatially distinct samples at the time of resection from 13 meningiomas. Seven meningiomas were WHO grade I (46 samples), three were grade II (22 samples), and three were grade III (18 samples). Seven meningiomas were sampled at the time of salvage surgery (48 samples), and 6 were sampled at the time of initial diagnosis (38 samples). We performed multiplatform molecular profiling of these samples to identify drivers of intratumor heterogeneity, and validated our results using meningioma cells co-cultured with human cerebral organoids and RNA sequencing of paired primary and recurrent meningiomas. RESULTS Using bulk RNA sequencing, DNA methylation profiling and phylogenetic analysis of spatially distinct samples, we discovered significant transcriptomic, epigenomic and genomic heterogeneity in meningioma. In particular, we identified chromosomal structural alterations and differences in immune and neuronal signaling that underlie clonal evolution in high grade tumors. Using MRI-stratified bulk RNA sequencing, single nuclear RNA sequencing, RNA sequencing of paired primary and recurrent meningiomas, and live cell microscopy and single cell RNA sequencing of meningioma cells in co-culture with human cerebral organoids, we revealed a rare meningioma cell subpopulation with strong transcriptional concordance to the neural crest, a multipotent embryonic tissue that forms the meninges in development. CONCLUSIONS These data suggest that misactivation of a developmental cell population underlies intratumor heterogeneity in meningioma and that expression of neural crest and immediate early genes are an important step in meningeal oncogenesis.

scholarly journals CTIM-06. DENDRITIC CELL VACCINE STUDY FOR RECURRENT, HIGH-GRADE GLIOMA: TISSUE-BASED RNA SEQUENCING AND SERUM CYTOKINE LEVELS AS POTENTIAL BIOMARKERS

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii33-ii34
Author(s):  
Macarena De La Fuente ◽  
Tulay Koru-Sengul ◽  
Deborah Heros ◽  
Feng Miao ◽  
Alain Fernandez Marrero ◽  
...  
Keyword(s):  
Dendritic Cells ◽  
Rna Sequencing ◽  
Tumor Antigens ◽  
High Grade Glioma ◽  
Treatment Discontinuation ◽  
Sequencing Analysis ◽  
High Grade ◽  
Who Grade ◽  
Cytokine Levels ◽  
Grade 3

Abstract BACKGROUND Glioblastoma is the most common primary malignant brain tumor. Despite multimodality treatment approach, median progression-free survival (PFS) is only 8 months, median overall-survival (OS) 14 months and 5-year survival rate of under 10%. Dendritic cells (DCs) are the professional antigen presenting cells of the immune system. The rationale for sensitizing dendritic cells to a pool of non-selected tumor antigens is based on the marked heterogeneity present within glioblastoma tumor cells. METHODS Phase 1/feasibility study of DC vaccine for recurrent high-grade glioma was conducted. Pooled, non-selected tumor antigens collected via tumor cell lysate were used for DC sensitization. RNA sequencing analysis was performed on all tumor samples. Cytokine levels in serum were detected using a Luminex cytokine panel. RESULTS A total of 20 patients were enrolled onto this study (median age 58yrs, range: 39–74, 65% male). Pathology showed WHO grade IV glioblastoma in 14 (70%) and grade III anaplastic astrocytoma in 6 (30%) patients. IDH wild type in 19 (95%) patients. Treatment emergent adverse events (all grades, regardless of attribution) occurred in more than 15% of the patients (20% fatigue, 15% dizziness, 15% headache, none leading to treatment discontinuation). There were five grade 3–4 and none grade 5 events. One grade 4 event (seizure) probable related to investigational treatment leading to treatment discontinuation. Four grade 3 events (dysphasia, possible related; intracranial hemorrhage unrelated; muscle weakness, unlikely related and hematoma, unrelated). Median PFS was 3.8 months. Median OS was 11 months. RNA sequencing in tumor samples and correlation with cytokine levels in serum is currently been analyzed. CONCLUSION Tumor lysate pulsed DC vaccination demonstrates acceptable safety and tolerability in high-grade glioma patients. Evaluations of integrating molecular profiling RNA sequencing information and cytokine levels to identify potential subset of patients with significant clinical benefit will be provided.

scholarly journals ClonArch: Visualizing the Spatial Clonal Architecture of Tumors

2020 ◽  
Author(s):  
Jiaqi Wu ◽  
Mohammed El-Kebir
Keyword(s):  
Visual Analytics ◽  
Phylogenetic Trees ◽  
Cancer Genomics ◽  
Clonal Evolution ◽  
Response To Treatment ◽  
Intratumor Heterogeneity ◽  
Tumor Evolution ◽  
Web Based ◽  
Clonal Architecture ◽  
Spatial Coordinates

AbstractMotivationCancer is caused by the accumulation of somatic mutations that lead to the formation of distinct populations of cells, called clones. The resulting clonal architecture is the main cause of relapse and resistance to treatment. With decreasing costs in DNA sequencing technology, rich cancer genomics datasets with many spatial sequencing samples are becoming increasingly available, enabling the inference of high-resolution tumor clones and prevalences across different spatial coordinates. While temporal and phylogenetic aspects of tumor evolution, such as clonal evolution over time and clonal response to treatment, are commonly visualized in various clonal evolution diagrams, visual analytics methods that reveal the spatial clonal architecture are missing.ResultsThis paper introduces ClonArch, a web-based tool to interactively visualize the phylogenetic tree and spatial distribution of clones in a single tumor mass. ClonArch uses the marching squares algorithm to draw closed boundaries representing the presence of clones in a real or simulated tumor. ClonArch enables researchers to examine the spatial clonal architecture of a subset of relevant mutations at different prevalence thresholds and across multiple phylogenetic trees. In addition to simulated tumors with varying number of biopsies, we demonstrate the use of ClonArch on a hepatocellular carcinoma tumor with ~280 sequencing biopsies. ClonArch provides an automated way to interactively examine the spatial clonal architecture of a tumor, facilitating clinical and biological interpretations of the spatial aspects of intratumor heterogeneity.Availabilityhttps://github.com/elkebir-group/ClonArch

Measuring Clonal Evolution in Cancer with Genomics

2019 ◽  
Vol 20 (1) ◽  
pp. 309-329 ◽  
Author(s):  
Marc J. Williams ◽  
Andrea Sottoriva ◽  
Trevor A. Graham
Keyword(s):  
Evolutionary Biology ◽  
Quantitative Measurement ◽  
Clonal Evolution ◽  
Evolutionary Process ◽  
Treatment Resistance ◽  
Genetic Alterations ◽  
Cell Number ◽  
Intratumor Heterogeneity ◽  
Tumor Evolution ◽  
Powerful Means

Cancers originate from somatic cells in the human body that have accumulated genetic alterations. These mutations modify the phenotype of the cells, allowing them to escape the homeostatic regulation that maintains normal cell number. Viewed through the lens of evolutionary biology, the transformation of normal cells into malignant cells is evolution in action. Evolution continues throughout cancer growth, progression, treatment resistance, and disease relapse, driven by adaptation to changes in the cancer's environment, and intratumor heterogeneity is an inevitable consequence of this evolutionary process. Genomics provides a powerful means to characterize tumor evolution, enabling quantitative measurement of evolving clones across space and time. In this review, we discuss concepts and approaches to quantify and measure this evolutionary process in cancer using genomics.

scholarly journals The genomic and epigenomic evolutionary history of papillary renal cell carcinomas

2018 ◽  
Author(s):  
Bin Zhu ◽  
Maria Luana Poeta ◽  
Manuela Costantini ◽  
Tongwu Zhang ◽  
Jianxin Shi ◽  
...  
Keyword(s):  
Kidney Cancer ◽  
Renal Cell ◽  
Large Scale ◽  
Clonal Evolution ◽  
Prognostic Significance ◽  
Intratumor Heterogeneity ◽  
Tumor Evolution ◽  
Driver Gene ◽  
Renal Cell Carcinomas ◽  
Cancer Subtypes

ABSTRACTIntratumor heterogeneity (ITH) and tumor evolution have been well described for clear cell renal cell carcinomas (ccRCC), but they are less studied for other kidney cancer subtypes. Here we investigate ITH and clonal evolution of papillary renal cell carcinoma (pRCC) and rarer kidney cancer subtypes, integrating whole-genome sequencing and DNA methylation data. In 29 tumors, up to 10 samples from the center to the periphery of each tumor, and metastatic samples in 2 cases, enable phylogenetic analysis of spatial features of clonal expansion, which shows congruent patterns of genomic and epigenomic evolution. In contrast to previous studies of ccRCC, in pRCC driver gene mutations and most arm-level somatic copy number alterations (SCNAs) are clonal. These findings suggest that a single biopsy would be sufficient to identify the important genetic drivers and targeting large-scale SCNAs may improve pRCC treatment, which is currently poor. While type 1 pRCC displays near absence of structural variants (SVs), the more aggressive type 2 pRCC and the rarer subtypes have numerous SVs, which should be pursued for prognostic significance.

scholarly journals Next-Generation Rapid Autopsies Enable Tumor Evolution Tracking and Generation of Preclinical Models

2017 ◽  
pp. 1-13 ◽  
Author(s):  
David J. Pisapia ◽  
Steven Salvatore ◽  
Chantal Pauli ◽  
Erika Hissong ◽  
Ken Eng ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Precision Medicine ◽  
Cancer Biology ◽  
Clonal Evolution ◽  
Tumor Evolution ◽  
Molecular Heterogeneity ◽  
Rna Seq ◽  
Next Generation ◽  
Preclinical Models ◽  
Rapid Autopsy

Purpose Patients with cancer who graciously consent for autopsy represent an invaluable resource for the study of cancer biology. To advance the study of tumor evolution, metastases, and resistance to treatment, we developed a next-generation rapid autopsy program integrated within a broader precision medicine clinical trial that interrogates pre- and postmortem tissue samples for patients of all ages and cancer types. Materials and Methods One hundred twenty-three (22%) of 554 patients who consented to the clinical trial also consented for rapid autopsy. This report comprises the first 15 autopsies, including patients with metastatic carcinoma (n = 10), melanoma (n = 1), and glioma (n = 4). Whole-exome sequencing (WES) was performed on frozen autopsy tumor samples from multiple anatomic sites and on non-neoplastic tissue. RNA sequencing (RNA-Seq) was performed on a subset of frozen samples. Tissue was also used for the development of preclinical models, including tumor organoids and patient-derived xenografts. Results Three hundred forty-six frozen samples were procured in total. WES was performed on 113 samples and RNA-Seq on 72 samples. Successful cell strain, tumor organoid, and/or patient-derived xenograft development was achieved in four samples, including an inoperable pediatric glioma. WES data were used to assess clonal evolution and molecular heterogeneity of tumors in individual patients. Mutational profiles of primary tumors and metastases yielded candidate mediators of metastatic spread and organotropism including CUL9 and PIGM in metastatic ependymoma and ANKRD52 in metastatic melanoma to the lung. RNA-Seq data identified novel gene fusion candidates. Conclusion A next-generation sequencing–based autopsy program in conjunction with a premortem precision medicine pipeline for diverse tumors affords a valuable window into clonal evolution, metastasis, and alterations underlying treatment. Moreover, such an autopsy program yields robust preclinical models of disease.

scholarly journals Ovarian Cancers: Genetic Abnormalities, Tumor Heterogeneity and Progression, Clonal Evolution and Cancer Stem Cells

Medicines ◽  
2018 ◽  
Vol 5 (1) ◽  
pp. 16 ◽  
Author(s):  
Ugo Testa ◽  
Eleonora Petrucci ◽  
Luca Pasquini ◽  
Germana Castelli ◽  
Elvira Pelosi
Keyword(s):  
Ovarian Cancer ◽  
Stem Cells ◽  
Cancer Stem Cells ◽  
Clonal Evolution ◽  
Cell Subpopulation ◽  
Ovarian Cancer Cells ◽  
High Grade ◽  
Histological Subtypes ◽  
Ovarian Cancer Stem Cells ◽  
Ovarian Cancers

Four main histological subtypes of ovarian cancer exist: serous (the most frequent), endometrioid, mucinous and clear cell; in each subtype, low and high grade. The large majority of ovarian cancers are diagnosed as high-grade serous ovarian cancers (HGS-OvCas). TP53 is the most frequently mutated gene in HGS-OvCas; about 50% of these tumors displayed defective homologous recombination due to germline and somatic BRCA mutations, epigenetic inactivation of BRCA and abnormalities of DNA repair genes; somatic copy number alterations are frequent in these tumors and some of them are associated with prognosis; defective NOTCH, RAS/MEK, PI3K and FOXM1 pathway signaling is frequent. Other histological subtypes were characterized by a different mutational spectrum: LGS-OvCas have increased frequency of BRAF and RAS mutations; mucinous cancers have mutation in ARID1A, PIK3CA, PTEN, CTNNB1 and RAS. Intensive research was focused to characterize ovarian cancer stem cells, based on positivity for some markers, including CD133, CD44, CD117, CD24, EpCAM, LY6A, ALDH1. Ovarian cancer cells have an intrinsic plasticity, thus explaining that in a single tumor more than one cell subpopulation, may exhibit tumor-initiating capacity. The improvements in our understanding of the molecular and cellular basis of ovarian cancers should lead to more efficacious treatments.

scholarly journals Understanding EGFR heterogeneity in lung cancer

ESMO Open ◽  
2020 ◽  
Vol 5 (5) ◽  
pp. e000919
Author(s):  
Antonio Passaro ◽  
Umberto Malapelle ◽  
Marzia Del Re ◽  
Ilaria Attili ◽  
Alessandro Russo ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Genetic Diversity ◽  
Kinase Inhibitors ◽  
Clonal Evolution ◽  
Clinical Trial Design ◽  
Egfr Mutations ◽  
Intratumor Heterogeneity ◽  
Molecular Heterogeneity ◽  
Cancer Disease ◽  
The Way

The advances in understanding the inherited biological mechanisms of non-small cell lung cancer harbouring epidermal growth factor receptor (EGFR) mutations led to a significant improvement in the outcomes of patients treated with EGFR tyrosine kinase inhibitors. Despite these clinically impressive results, clinical results are not always uniform, suggesting the need for deepening the molecular heterogeneity of this molecularly defined subgroup of patients beyond the clinical and biological surface.The availability of tissue and blood-based tumour genotyping allows us to improve the understanding of molecular and genetic intratumor heterogeneity, driving the measurement of clonal evaluation in patients with lung cancer carrying EGFR mutations. Genetic diversification, clonal expansion and selection are highly variable patterns of genetic diversity, resulting in different biological entities, also a prerequisite for Darwinian selection and therapeutic failure.Such emerging pieces of evidence on the genetic diversity, including adaptive and immunomodulated aspects, provide further evidence for the role of the tumour microenvironment (TME) in drug-resistance and immune-mediated mechanisms. Matching in daily clinical practice, the detailed genomic profile of lung cancer disease and tracking the clonal evolution could be the way to individualise the further target treatments in EGFR-positive disease. Characterising the tumour and immune microenvironment during the time of the cancer evaluation could be the way forward for the qualitative leap needed from bench to bedside. Such a daring approach, aiming at personalising treatment selection in order to exploit the TME properties and weaken tumour adaptivity, should be integrated into clinical trial design to optimise patient outcome.

scholarly journals Single-cell atlas of tumor clonal evolution in liver cancer

2020 ◽  
Author(s):  
Lichun Ma ◽  
Limin Wang ◽  
Ching-Wen Chang ◽  
Sophia Heinrich ◽  
Dana Dominguez ◽  
...  
Keyword(s):  
Liver Cancer ◽  
Tumor Cell ◽  
Single Cell ◽  
Immune Cell ◽  
Clonal Evolution ◽  
Response To Therapy ◽  
Intratumor Heterogeneity ◽  
Tumor Evolution ◽  
Liver Cancers ◽  
Cell Clonality

SUMMARYTumor evolution is a key feature of tumorigenesis and plays a pivotal role in driving intratumor heterogeneity, treatment failure and patients’ prognosis. Here we performed single-cell transcriptome profiling of 46 primary liver cancers from 37 patients enrolled for interventional studies. We surveyed the landscape of ~57,000 malignant and non-malignant cells and determined tumor cell clonality by developing a machine learning-based consensus clustering method. We found evidence of tumor cell branching evolution using hierarchical clustering, RNA velocity as well as reverse graph embedding methods. Interestingly, an increasing tumor cell clonality was tightly linked to patients’ prognosis, accompanied by a polarized immune cell landscape. We identified osteopontin as a key player for tumor cell evolution and microenvironmental reprogramming. Our study offers insight into the collective behavior of tumor cell communities in liver cancer as well as potential drivers for tumor evolution in response to therapy.

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