Functional precision medicine identifies new therapeutic candidates for medulloblastoma (expression dataset)
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ABSTRACT: Medulloblastoma (MB) is among the most common malignant brain tumors in children. Recent studies have identified at least four subgroups of the disease that differ in terms of molecular characteristics and patient outcomes. Despite this heterogeneity, most MB patients receive similar therapies, including surgery, radiation and intensive chemotherapy. Although these treatments prolong survival, many patients still die from the disease, and survivors suffer severe long-term side effects from therapy. We hypothesize that each MB patient is sensitive to different therapies, and that tailoring therapy based on the molecular and cellular characteristics of patients’ tumors will improve outcomes. To test this, we have assembled a panel of orthotopic patient-derived xenografts (PDXs) and subjected them to DNA sequencing, gene expression profiling and high-throughput drug screening. Analysis of DNA sequencing suggests that most MBs do not have actionable mutations that point to effective therapies. In contrast, gene expression and drug response data provide valuable information about potential therapies for every tumor. For example, drug screening demonstrates that actinomycin D – which is used for treatment of sarcoma but rarely for MB – is active against PDXs representing Group 3 MB, the most aggressive form of the disease. Finally, we show that functional analysis of tumor cells can be used in a clinical setting to identify more treatment options than sequencing alone. These studies suggest that it should be possible to move away from a one-size-fits-all approach and begin to treat each patient with therapies that are effective against their tumor.
Project description:Medulloblastoma (MB) is among the most common malignant brain tumors in children. Recent studies have identified at least four subgroups of the disease that differ in terms of molecular characteristics and patient outcomes. Despite this heterogeneity, most MB patients receive similar therapies, including surgery, radiation and intensive chemotherapy. Although these treatments prolong survival, many patients still die from the disease, and survivors suffer severe long-term side effects from therapy. We hypothesize that each MB patient is sensitive to different therapies, and that tailoring therapy based on the molecular and cellular characteristics of patients’ tumors will improve outcomes. To test this, we have assembled a panel of orthotopic patient-derived xenografts (PDXs) and subjected them to DNA sequencing, gene expression profiling and high-throughput drug screening. Analysis of DNA sequencing suggests that most MBs do not have actionable mutations that point to effective therapies. In contrast, gene expression and drug response data provide valuable information about potential therapies for every tumor. For example, drug screening demonstrates that actinomycin D – which is used for treatment of sarcoma but rarely for MB – is active against PDXs representing Group 3 MB, the most aggressive form of the disease. Finally, we show that functional analysis of tumor cells can be used in a clinical setting to identify more treatment options than sequencing alone. These studies suggest that it should be possible to move away from a one-size-fits-all approach and begin to treat each patient with therapies that are effective against their tumor.
Project description:Osteosarcoma (OS) and Ewing’s sarcoma (EW) are the two most common pediatric solid tumors, after brain tumors. Multimodal treatments have significantly improved prognosis in localized disease but outcome is still poor in metastatic patients, for whom therapeutic options are often inadequate. Preclinical drug testing to identify promising treatment options that match the molecular make-up of these tumors is hampered by the lack of appropriate and molecularly well-characterized patient-derived models. To address this need, a panel of patient-derived xenografts (PDX) was established by subcutaneous implantation of fresh, surgically resected OS and EW tumors in NSG mice. Tumors were re-transplanted to next mice generations and fragments were collected for histopathological and molecular characterization. A model was considered established after observing stable histological and molecular features for at least three passages. To evaluate the similarity of the model with primary tumor, we performed a global gene expression profiling and tissue microarrays (TMA), to assess tumor specific biomarkers on tissues from OS/EW tumors and their PDXs (1st and 3rd passage). Moreover, we verified the feasibility of these models for preclinical drug testing. We implanted 61 OS and 29 EW samples: 14/38 (37%) primary OS and 9/23 (39%) OS lung metastases successfully engrafted; while among EW, 5/26 (19%) primary samples and 1/3 (33%) metastases were established. Comparison between patient samples and PDXs, highlighted that histology and genetic characteristics of PDXs were stable and maintained over passages. In particular, correlative analysis between OS and EW samples and their PDXs was extremely high (Pearson’s r range r=0.94-0.96), while patient-derived primary cultures displayed reduced correlation with human samples (r=0.90-0.93), indicating that in vitro adaptation superimpose molecular alterations that create genetic diversion from original tumors. No significant differentially expressed gene profile was observed from the comparison between EW samples and PDXs (fold change > 2, adjusted p <0.05 at paired t-test). In OS, the comparison between OS patient-derived tumors and PDX indicated differences in 397 genes, mostly belonging to immune system functional category. This is in line with the idea that human immune cells are gradually replaced by murine counterparts upon engraftment in the mouse. As proof-of concept, two EW PDX and one OS PDX have been treated with conventional and innovated drugs to test their value in terms of drug-sensitivity prediction. Overall, our study indicated that PDX models maintained the histological and genetic markers of the tumor samples and represent reliable models to test sensitivity to novel drug associations.
Project description:Patient-derived tumor xenografts (PDXs) increasingly are being used as preclinical models to study human cancers and to evaluate novel therapeutics, as they reflect clinical cancers more closely than established tumor cell lines. With >100 PDXs established from resected non-small cell lung carcinomas (NSCLC), we reported previously that xenograftability correlates significantly with poorer patient prognosis. In this study, genomic, transcriptomic, and proteomic profiling of 36 PDXs showed greater similarity in somatic alterations between PDX and primary tumors than with cell lines, using publicly available data on the latter. A higher number of somatic alterations among 865 frequently altered genes in the PDX tumors was associated with better overall patient survival (HR=0.15, p=0.00015) compared to patients with corresponding PDXs characterized by a lower number of alterations; this was validated with the TCGA lung cancer patient dataset (HR=0.28, p=0.000022). These passenger-like alterations, identified in PDXs, link cell-cell signaling and adhesion to patient prognosis. Total RNAs from xenograftswere amplified by DASL kit and hybridized to Illumina HT12v4 chip
Project description:Circular extrachromosomal DNA (ecDNA) in patient tumor genomes is an important driver of oncogenic gene expression, evolution of drug resistance, and poor patient outcomes. Applying computational methods for detection and reconstruction of ecDNA across a retrospective cohort of 481 medulloblastoma (MB) tumors from 465 patients, we identify circular ecDNA in 82 patients (18%). Patients with ecDNA+ MB were more than twice as likely to relapse and three times as likely to die within 5 years of diagnosis. Individual tumors harbor multiple ecDNA lineages, each containing distinct amplified oncogenes. Multimodal sequencing, imaging, and CRISPR inhibition experiments in MB models reveal intratumoral heterogeneity of ecDNA copy number per cell and frequent putative "enhancer rewiring" events on ecDNA. This study reveals the frequency and diversity of ecDNA in a subset of highly aggressive MB tumors, and suggests copy number heterogeneity and enhancer rewiring as clinically relevant features of ecDNA in MB.
Project description:Circular extrachromosomal DNA (ecDNA) in patient tumor genomes is an important driver of oncogenic gene expression, evolution of drug resistance, and poor patient outcomes. Applying computational methods for detection and reconstruction of ecDNA across a retrospective cohort of 481 medulloblastoma (MB) tumors from 465 patients, we identify circular ecDNA in 82 patients (18%). Patients with ecDNA+ MB were more than twice as likely to relapse and three times as likely to die within 5 years of diagnosis. Individual tumors harbor multiple ecDNA lineages, each containing distinct amplified oncogenes. Multimodal sequencing, imaging, and CRISPR inhibition experiments in MB models reveal intratumoral heterogeneity of ecDNA copy number per cell and frequent putative "enhancer rewiring" events on ecDNA. This study reveals the frequency and diversity of ecDNA in a subset of highly aggressive MB tumors, and suggests copy number heterogeneity and enhancer rewiring as clinically relevant features of ecDNA in MB.
Project description:Circular extrachromosomal DNA (ecDNA) in patient tumor genomes is an important driver of oncogenic gene expression, evolution of drug resistance, and poor patient outcomes. Applying computational methods for detection and reconstruction of ecDNA across a retrospective cohort of 481 medulloblastoma (MB) tumors from 465 patients, we identify circular ecDNA in 82 patients (18%). Patients with ecDNA+ MB were more than twice as likely to relapse and three times as likely to die within 5 years of diagnosis. Individual tumors harbor multiple ecDNA lineages, each containing distinct amplified oncogenes. Multimodal sequencing, imaging, and CRISPR inhibition experiments in MB models reveal intratumoral heterogeneity of ecDNA copy number per cell and frequent putative "enhancer rewiring" events on ecDNA. This study reveals the frequency and diversity of ecDNA in a subset of highly aggressive MB tumors, and suggests copy number heterogeneity and enhancer rewiring as clinically relevant features of ecDNA in MB.
Project description:Circular extrachromosomal DNA (ecDNA) in patient tumor genomes is an important driver of oncogenic gene expression, evolution of drug resistance, and poor patient outcomes. Applying computational methods for detection and reconstruction of ecDNA across a retrospective cohort of 481 medulloblastoma (MB) tumors from 465 patients, we identify circular ecDNA in 82 patients (18%). Patients with ecDNA+ MB were more than twice as likely to relapse and three times as likely to die within 5 years of diagnosis. Individual tumors harbor multiple ecDNA lineages, each containing distinct amplified oncogenes. Multimodal sequencing, imaging, and CRISPR inhibition experiments in MB models reveal intratumoral heterogeneity of ecDNA copy number per cell and frequent putative "enhancer rewiring" events on ecDNA. This study reveals the frequency and diversity of ecDNA in a subset of highly aggressive MB tumors, and suggests copy number heterogeneity and enhancer rewiring as clinically relevant features of ecDNA in MB.
Project description:Availability of patient-derived sarcoma models that closely mimic human tumors remains a significant gap in cancer research as these models may not recapitulate the spectrum of sarcoma heterogeneity seen in patients. To characterize patient-derived models for functional studies, we made proteomic comparisons with originating sarcomas representative of the three intrinsic subtypes by mass spectrometry. Human protein profiling was found to be retained with high fidelity in patient-derived models. Patient derived xenografts locally invade and colonize stroma in mice which enables unambiguous molecular discrimination of human proteins in the tumor from mouse proteins in the microenvironment. We characterized protein profiling of patient sarcoma tumors and mouse stroma by species-specific quantitative proteomics. We found that protein expression in mouse stroma was affected by the primary human tumor. Our results showed that levels of stromal proteins derived from the tumor were lowered in PDXs and cell lines and part of human stromal proteins were replaced by corresponding mouse proteins in PDXs. This suggests that the effects of the microenvironment on drug response may not reflect those in the primary tumor. This cross-species proteomic analysis in PDXs could potentially improve preclinical evaluation of treatment modalities and enhance the ability to predict clinical trial responses.
Project description:Precision oncology requires the timely selection of effective drugs or drug combinations for individual patients. The ideal platform would enable rapid screening of cell type-specific drug sensitivities directly in patient tumor tissue and reveal strategies to overcome intratumoral heterogeneity. Here we combine multiplexed drug perturbation in acute slice culture from freshly resected tumors with single-cell RNA sequencing (scRNA-seq) to profile transcriptome-wide drug responses in individual patients. We applied this approach to glioblastoma (GBM) and demonstrated that acute slice cultures recapitulate the cellular and molecular features of the originating tumor tissue. Detailed investigation of etoposide, a topoisomerase poison, and the histone deacetylase (HDAC) inhibitor Panobinostat in acute slice cultures revealed cell type-specific responses across multiple patients, including unexpected effects on the immune microenvironment. We anticipate that this approach will facilitate rapid, personalized drug screening to identify effective therapies for solid tumors.
Project description:Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal diseases, characterized by a treatment-resistant and invasive nature. In line with these inherent aggressive characteristics, only a subset of patients shows a clinical response to the standard of care therapies, thereby highlighting the need for a more personalized treatment approach. In this study, we comprehensively unraveled the intra-patient response heterogeneity and intrinsic aggressive nature of PDAC on bulk and single-organoid resolution. We leveraged a fully characterized PDAC organoid panel (N=8) and matched our artificial intelligence-driven, live-cell organoid image analysis with retrospective clinical patient response. In line with the clinical outcomes, we identified patient-specific sensitivities to the standard of care therapies (gemcitabine-paclitaxel and FOLFIRINOX) using a growth rate-based and normalized drug response metric. Moreover, the single-organoid analysis was able to detect resistant as well as invasive PDAC organoid clones, which was orchestrates on a patient, therapy, drug, concentration and time-specific level. Furthermore, our in vitro organoid analysis indicated a strong correlation with the matched patient progression-free survival (PFS) compared to the current, conventional drug response readouts. This work not only provides valuable insights on the response complexity in PDAC, but it also highlights the potential applications (extendable to other tumor types) and clinical translatability of our approach in drug discovery and the emerging era of personalized medicine.