Lower-grade gliomas (WHO grade II/III) have been classified into clinically relevant molecular subtypes based on
and 1p/19q mutation status. The purpose was to investigate whether T2/FLAIR MRI ...features could distinguish between lower-grade glioma molecular subtypes.
MRI scans from the TCGA/TCIA lower grade glioma database (
= 125) were evaluated by two independent neuroradiologists to assess (i) presence/absence of homogenous signal on T2WI; (ii) presence/absence of "T2-FLAIR mismatch" sign; (iii) sharp or indistinct lesion margins; and (iv) presence/absence of peritumoral edema. Metrics with moderate-substantial agreement underwent consensus review and were correlated with glioma molecular subtypes. Somatic mutation, DNA copy number, DNA methylation, gene expression, and protein array data from the TCGA lower-grade glioma database were analyzed for molecular-radiographic associations. A separate institutional cohort (
= 82) was analyzed to validate the T2-FLAIR mismatch sign.
Among TCGA/TCIA cases, interreader agreement was calculated for lesion homogeneity
= 0.234 (0.111-0.358), T2-FLAIR mismatch sign
= 0.728 (0.538-0.918), lesion margins
= 0.292 (0.135-0.449), and peritumoral edema
= 0.173 (0.096-0.250). All 15 cases that were positive for the T2-FLAIR mismatch sign were
-mutant, 1p/19q non-codeleted tumors (
< 0.0001; PPV = 100%, NPV = 54%). Analysis of the validation cohort demonstrated substantial interreader agreement for the T2-FLAIR mismatch sign
= 0.747 (0.536-0.958); all 10 cases positive for the T2-FLAIR mismatch sign were
-mutant, 1p/19q non-codeleted tumors (
< 0.00001; PPV = 100%, NPV = 76%).
Among lower-grade gliomas, T2-FLAIR mismatch sign represents a highly specific imaging biomarker for the
-mutant, 1p/19q non-codeleted molecular subtype.
.
Visual inspection of histopathology slides is one of the main methods used by pathologists to assess the stage, type and subtype of lung tumors. Adenocarcinoma (LUAD) and squamous cell carcinoma ...(LUSC) are the most prevalent subtypes of lung cancer, and their distinction requires visual inspection by an experienced pathologist. In this study, we trained a deep convolutional neural network (inception v3) on whole-slide images obtained from The Cancer Genome Atlas to accurately and automatically classify them into LUAD, LUSC or normal lung tissue. The performance of our method is comparable to that of pathologists, with an average area under the curve (AUC) of 0.97. Our model was validated on independent datasets of frozen tissues, formalin-fixed paraffin-embedded tissues and biopsies. Furthermore, we trained the network to predict the ten most commonly mutated genes in LUAD. We found that six of them-STK11, EGFR, FAT1, SETBP1, KRAS and TP53-can be predicted from pathology images, with AUCs from 0.733 to 0.856 as measured on a held-out population. These findings suggest that deep-learning models can assist pathologists in the detection of cancer subtype or gene mutations. Our approach can be applied to any cancer type, and the code is available at https://github.com/ncoudray/DeepPATH .
In this chapter, we describe the use of Illumina
Infinium
HD Assay in conjunction with Illumina's EPIC Methylation 8-sample array platform to obtain glioblastoma molecular profiles. The procedure ...spans four days, and can be performed by a single laboratory technician. Starting with as little as 250 ng of DNA input, this method allows the flexibility to begin with DNA derived from either formalin-fixed, paraffin-embedded (FFPE) or fresh tissue and is compatible with an Illumina iScan or HiScan system.
Accurate histopathologic diagnosis is essential for providing optimal surgical management of pediatric brain tumors. Current methods for intraoperative histology are time- and labor-intensive and ...often introduce artifact that limit interpretation. Stimulated Raman histology (SRH) is a novel label-free imaging technique that provides intraoperative histologic images of fresh, unprocessed surgical specimens. Here we evaluate the capacity of SRH for use in the intraoperative diagnosis of pediatric type brain tumors. SRH revealed key diagnostic features in fresh tissue specimens collected from 33 prospectively enrolled pediatric type brain tumor patients, preserving tumor cytology and histoarchitecture in all specimens. We simulated an intraoperative consultation for 25 patients with specimens imaged using both SRH and standard hematoxylin and eosin histology. SRH-based diagnoses achieved near-perfect diagnostic concordance (Cohen's kappa,
> 0.90) and an accuracy of 92% to 96%. We then developed a quantitative histologic method using SRH images based on rapid image feature extraction. Nuclear density, tumor-associated macrophage infiltration, and nuclear morphology parameters from 3337 SRH fields of view were used to develop and validate a decision-tree machine-learning model. Using SRH image features, our model correctly classified 25 fresh pediatric type surgical specimens into normal versus lesional tissue and low-grade versus high-grade tumors with 100% accuracy. Our results provide insight into how SRH can deliver rapid diagnostic histologic data that could inform the surgical management of pediatric brain tumors.
A new imaging method simplifies diagnosis and informs decision making during pediatric brain tumor surgery.
.
The stress harbored by the solid phase of tumors is known as solid stress. Solid stress can be either applied externally by the surrounding normal tissue or induced by the tumor itself due to its ...growth. Fluid pressure is the isotropic stress exerted by the fluid phase. We recently showed that growth-induced solid stress is on the order of 1.3 to 13.0 kPa (10-100 mmHg)--high enough to cause compression of fragile blood vessels, resulting in poor perfusion and hypoxia. However, the evolution of growth-induced stress with tumor progression and its effect on cancer cell proliferation in vivo is not understood. To this end, we developed a mathematical model for tumor growth that takes into account all three types of stresses: growth-induced stress, externally applied stress, and fluid pressure. First, we conducted in vivo experiments and found that growth-induced stress is related to tumor volume through a biexponential relationship. Then, we incorporated this information into our mathematical model and showed that due to the evolution of growth-induced stress, total solid stress levels are higher in the tumor interior and lower in the periphery. Elevated compressive solid stress in the interior of the tumor is sufficient to cause the collapse of blood vessels and results in a lower growth rate of cancer cells compared with the periphery, independently from that caused by the lack of nutrients due to vessel collapse. Furthermore, solid stress in the periphery of the tumor causes blood vessels in the surrounding normal tissue to deform to elliptical shapes. We present histologic sections of human cancers that show such vessel deformations. Finally, we found that fluid pressure increases with tumor growth due to increased vascular permeability and lymphatic impairment, and is governed by the microvascular pressure. Crucially, fluid pressure does not cause vessel compression of tumor vessels.
DNA methylation as a diagnostic tool Galbraith, Kristyn; Snuderl, Matija
Acta neuropathologica communications,
05/2022, Letnik:
10, Številka:
1
Journal Article
Recenzirano
Odprti dostop
DNA methylation of cytosines in CpG sites throughout the genome is an epigenetic mark contributing to gene expression regulation. DNA methylation patterns are specific to tissue type, conserved ...throughout life and reflect changes during tumorigenesis. DNA methylation recently emerged as a diagnostic tool to classify tumors based on a combination of preserved developmental and mutation induced signatures. In addition to the tumor classification, DNA methylation data can also be used to evaluate copy number variation, assess promoter methylation status of specific genes, such as MGMT or MLH1, and deconvolute the tumor microenvironment, assessing the tumor immune infiltrate as a potential biomarker for immunotherapy. Here we review the role for DNA methylation in tumor diagnosis.
The prognosis of patients with glioblastoma (GBM) remains dismal, with a median survival of approximately 15 months. Current preclinical GBM models are limited by the lack of a “normal” human ...microenvironment and the inability of many tumor cell lines to accurately reproduce GBM biology. To address these limitations, we have established a model system whereby we can retro-engineer patient-specific GBMs using patient-derived glioma stem cells (GSCs) and human embryonic stem cell (hESC)-derived cerebral organoids. Our cerebral organoid glioma (GLICO) model shows that GSCs home toward the human cerebral organoid and deeply invade and proliferate within the host tissue, forming tumors that closely phenocopy patient GBMs. Furthermore, cerebral organoid tumors form rapidly and are supported by an interconnected network of tumor microtubes that aids in the invasion of normal host tissue. Our GLICO model provides a system for modeling primary human GBM ex vivo and for high-throughput drug screening.
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•Glioma stem cells home toward, invade, and proliferate in human cerebral organoids•GLICO (cerebral organoid glioma) tumors phenocopy patient glioblastoma•Tumor microtubes promote the invasion of GLICO tumors into normal host tissue•The GLICO model is a tool to study GBM biology in a human brain environment
To address limitations with current preclinical glioblastoma (GBM) models, Linkous et al. establish a “GLICO” (cerebral organoid glioma) model to retro-engineer patient-specific GBMs using patient-derived glioma stem cells and human cerebral organoids. Resulting tumors closely phenocopy patient GBMs and are supported by tumor microtubes that promote invasion into host tissue.
Metastatic cancer cells (seeds) preferentially grow in the secondary sites with a permissive microenvironment (soil). We show that the metastatic cells can bring their own soil—stromal components ...including activated fibroblasts—from the primary site to the lungs. By analyzing the efferent blood from tumors, we found that viability of circulating metastatic cancer cells is higher if they are incorporated in heterotypic tumor-stroma cell fragments. Moreover, we show that these cotraveling stromal cells provide an early growth advantage to the accompanying metastatic cancer cells in the lungs. Consistent with this hypothesis, we demonstrate that partial depletion of the carcinoma-associated fibroblasts, which spontaneously spread to the lung tissue along with metastatic cancer cells, significantly decreases the number of metastases and extends survival after primary tumor resection. Finally, we show that the brain metastases from lung carcinoma and other carcinomas in patients contain carcinoma-associated fibroblasts, in contrast to primary brain tumors or normal brain tissue. Demonstration of the direct involvement of primary tumor stroma in metastasis has important conceptual and clinical implications for the colonization step in tumor progression.
Recent genomic studies have shed light on the biology and inter-tumoral heterogeneity underlying pineal parenchymal tumors, in particular pineoblastomas (PBs) and pineal parenchymal tumors of ...intermediate differentiation (PPTIDs). Previous reports, however, had modest sample sizes and lacked the power to integrate molecular and clinical findings. The different proposed molecular group structures also highlighted a need to reach consensus on a robust and relevant classification system. We performed a meta-analysis on 221 patients with molecularly characterized PBs and PPTIDs. DNA methylation profiles were analyzed through complementary bioinformatic approaches and molecular subgrouping was harmonized. Demographic, clinical, and genomic features of patients and samples from these pineal tumor groups were annotated. Four clinically and biologically relevant consensus PB groups were defined: PB-miRNA1 (
n
= 96), PB-miRNA2 (
n
= 23), PB-MYC/FOXR2 (
n
= 34), and PB-RB1 (
n
= 25). A final molecularly distinct group, designated PPTID (
n
= 43), comprised histological PPTID and PBs. Genomic and transcriptomic profiling allowed the characterization of oncogenic drivers for individual tumor groups, specifically, alterations in the microRNA processing pathway in PB-miRNA1/2,
MYC
amplification and
FOXR2
overexpression in PB-MYC/FOXR2,
RB1
alteration in PB-RB1, and
KBTBD4
insertion in PPTID. Age at diagnosis, sex predilection, and metastatic status varied significantly among tumor groups. While patients with PB-miRNA2 and PPTID had superior outcome, survival was intermediate for patients with PB-miRNA1, and dismal for those with PB-MYC/FOXR2 or PB-RB1. Reduced-dose CSI was adequate for patients with average-risk, PB-miRNA1/2 disease. We systematically interrogated the clinical and molecular heterogeneity within pineal parenchymal tumors and proposed a consensus nomenclature for disease groups, laying the groundwork for future studies as well as routine use in tumor diagnostic classification and clinical trial stratification.
Inhibition of the vascular endothelial growth factor (VEGF) pathway has failed to improve overall survival of patients with glioblastoma (GBM). We previously showed that angiopoietin-2 (Ang-2) ...overexpression compromised the benefit from anti-VEGF therapy in a preclinical GBM model. Here we investigated whether dual Ang-2/VEGF inhibition could overcome resistance to anti-VEGF treatment. We treated mice bearing orthotopic syngeneic (Gl261) GBMs or human (MGG8) GBMxenografts with antibodies inhibiting VEGF (B20), or Ang-2/VEGF (CrossMab, A2V). We examined the effects of treatment on the tumor vasculature, immune cell populations, tumor growth, and survival in both the Gl261 and MGG8 tumor models. We found that in the Gl261 model, which displays a highly abnormal tumor vasculature, A2V decreased vessel density, delayed tumor growth, and prolonged survival compared with B20. In the MGG8 model, which displays a low degree of vessel abnormality, A2V induced no significant changes in the tumor vasculature but still prolonged survival. In both the Gl261 and MGG8 models A2V reprogrammed protumor M2 macrophages toward the antitumor M1 phenotype. Our findings indicate that A2V may prolong survival in mice with GBM by reprogramming the tumor immune microenvironment and delaying tumor growth.
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