We describe the landscape of somatic genomic alterations based on multidimensional and comprehensive characterization of more than 500 glioblastoma tumors (GBMs). We identify several novel mutated genes as well as complex rearrangements of signature receptors, including EGFR and PDGFRA. TERT promoter mutations are shown to correlate with elevated mRNA expression, supporting a role in telomerase reactivation. Correlative analyses confirm that the survival advantage of the proneural subtype is conferred by the G-CIMP phenotype, and MGMT DNA methylation may be a predictive biomarker for treatment response only in classical subtype GBM. Integrative analysis of genomic and proteomic profiles challenges the notion of therapeutic inhibition of a pathway as an alternative to inhibition of the target itself. These data will facilitate the discovery of therapeutic and diagnostic target candidates, the validation of research and clinical observations and the generation of unanticipated hypotheses that can advance our molecular understanding of this lethal cancer.

The somatic genomic landscape of glioblastoma

This review describes the definition, incidence, clinical implications, and magnetic resonance imaging (MRI) findings of pseudoprogression of brain tumors, in particular, but not limited to, high‐grade glioma. Pseudoprogression is an important clinical problem after brain tumor treatment, interfering not only with day‐to‐day patient care but also the execution and interpretation of clinical trials. Radiologically, pseudoprogression is defined as a new or enlarging area(s) of contrast agent enhancement, in the absence of true tumor growth, which subsides or stabilizes without a change in therapy. The clinical definitions of pseudoprogression have been quite variable, which may explain some of the differences in reported incidences, which range from 9–30%. Conventional structural MRI is insufficient for distinguishing pseudoprogression from true progressive disease, and advanced imaging is needed to obtain higher levels of diagnostic certainty. Perfusion MRI is the most widely used imaging technique to diagnose pseudoprogression and has high reported diagnostic accuracy. Diagnostic performance of MR spectroscopy (MRS) appears to be somewhat higher, but MRS is less suitable for the routine and universal application in brain tumor follow‐up. The combination of MRS and diffusion‐weighted imaging and/or perfusion MRI seems to be particularly powerful, with diagnostic accuracy reaching up to or even greater than 90%. While diagnostic performance can be high with appropriate implementation and interpretation, even a combination of techniques, however, does not provide 100% accuracy. It should also be noted that most studies to date are small, heterogeneous, and retrospective in nature. Future improvements in diagnostic accuracy can be expected with harmonization of acquisition and postprocessing, quantitative MRI and computer‐aided diagnostic technology, and meticulous evaluation with clinical and pathological data.

Level of Evidence: 3

Technical Efficacy: Stage 2

J. Magn. Reson. Imaging 2018;48:571–589.

/pdf/pseudoprogression-of-brain-tumors-2cl4gg3hf2.pdf

Pseudoprogression of brain tumors

Glioblastoma is the most frequent and aggressive form among malignant central nervous system primary tumors in adults. Standard treatment for newly diagnosed glioblastoma consists in maximal safe resection, if feasible, followed by radiochemotherapy and adjuvant chemotherapy with temozolomide; despite this multimodal treatment, virtually all glioblastomas relapse. Once tumors progress after first-line therapy, treatment options are limited and management of recurrent glioblastoma remains challenging. Loco-regional therapy with re-surgery or re-irradiation may be evaluated in selected cases, while traditional systemic therapy with nitrosoureas and temozolomide rechallenge showed limited efficacy. In recent years, new clinical trials using, for example, regorafenib or a combination of tyrosine kinase inhibitors and immunotherapy were performed with promising results. In particular, molecular targeted therapy could show efficacy in selected patients with specific gene mutations. Nonetheless, some molecular characteristics and genetic alterations could change during tumor progression, thus affecting the efficacy of precision medicine. We therefore reviewed the molecular and genomic landscape of recurrent glioblastoma, the strategy for clinical management and the major phase I-III clinical trials analyzing recent drugs and combination regimens in these patients.

/pdf/recurrent-glioblastoma-from-molecular-landscape-to-new-4sgyigvh61.pdf

Recurrent Glioblastoma: From Molecular Landscape to New Treatment Perspectives.

Immunotherapy has achieved unprecedented clinical efficacy in patients with various types of advanced tumors; however, some patients experience delayed tumor shrinkage following an increase in tumor burden after such a therapeutic method. This phenomenon is called pseudoprogression and can lead to premature cessation of efficacious immunotherapeutic agents. Consequently, we summarized the available data on methods to differentiate pseudoprogression from true progression in patients who have been treated with immunotherapy including biomarkers, medical imaging techniques and biopsy. We also introduce hyperprogression and special pseudoprogression for improved evaluation of immunotherapy.

How to differentiate pseudoprogression from true progression in cancer patients treated with immunotherapy.

There are currently seven approved immune checkpoint inhibitors (ICIs) for the treatment of various cancers. These drugs are associated with profound, durable responses in a subset of patients with advanced cancers. Unfortunately, in addition to individuals whose tumors show resistance, there is a minority subgroup treated with ICIs who demonstrate a paradoxical acceleration in the rate of growth or their tumors-hyperprogressive disease. Hyperprogressive disease is associated with significantly worse outcomes in these patients. This phenomenon, though still a matter of dispute, has been recognized by multiple groups of investigators across the globe and in diverse types of cancers. There are not yet consensus standardized criteria for defining hyperprogressive disease, but most commonly time to treatment failure less than 2 months and an increase in pace of progression of at least twofold between pre-immunotherapy and on-treatment imaging has been used. In some patients, the change in rate of progression can be especially dramatic-up to 35- to 40-fold. MDM2 amplification and EGFR mutations have been suggested as genomic correlates of increased risk of hyperprogression, but these correlates require validation. The underlying mechanism for hyperprogression is not known but warrants urgent investigation.

/pdf/hyperprogression-and-immune-checkpoint-inhibitors-hype-or-4ubzv9wfg1.pdf

Hyperprogression and Immune Checkpoint Inhibitors: Hype or Progress?

We explored predictive factors of pseudoprogression (PsP) and its impact on prognosis in a retrospective series of uniformly treated glioblastoma patients. Patients were classified as having PsP, early progression (eP) or neither (nP). We examined potential associations with clinical, molecular, and basal imaging characteristics and compared overall survival (OS), progression-free survival (PFS), post-progression survival (PPS) as well as the relationship between PFS and PPS in the three groups. Of the 256 patients studied, 56 (21.9%) were classified as PsP, 70 (27.3%) as eP, and 130 (50.8%) as nP. Only MGMT methylation status was associated to PsP. MGMT methylated patients had a 3.5-fold greater possibility of having PsP than eP (OR: 3.48; 95% CI: 1.606–7.564; P = 0.002). OS was longer for PsP than eP patients (18.9 vs. 12.3 months; P = 0.0001) but was similar for PsP and nP patients (P = 0.91). OS was shorter–though not significantly so—for PsP than nP patients (OS: 19.5 vs. 27.9 months; P = 0.63) in methylated patients. PPS was similar for patients having PsP, eP or nP (PPS: 7.2 vs. 5.4 vs. 6.7; P = 0.43). Neurological deterioration occurred in 64.3% of cases at the time they were classified as PsP and in 72.8% of cases of eP (P = 0.14). PsP confounds the evaluation of disease and does not confer a survival advantage in glioblastoma.

/pdf/pseudoprogression-as-an-adverse-event-of-glioblastoma-18yfpxshhr.pdf

Pseudoprogression as an adverse event of glioblastoma therapy

Purpose: Molecular subtype classifications in glioblastoma may detect therapy sensitivities. IHC would potentially allow the identification of molecular subtypes in routine clinical practice. Experimental Design: Formalin-fixed, paraffin-embedded tumor samples of 124 uniformly treated, newly diagnosed patients with glioblastoma were submitted to RNA sequencing, IHC, and immune-phenotyping to identify differences in molecular subtypes associated with treatment sensitivities. Results: We detected high molecular and IHC overlapping of the The Cancer Genome Atlas (TCGA) mesenchymal subtype with instrinsic glioma subtypes (IGS) cluster 23 and of the TCGA classical subtype with IGS cluster 18. IHC patterns, gene fusion profiles, and immune-phenotypes varied across subtypes. IHC revealed that the TCGA classical subtype was identified by high expression of EGFR and low expression of PTEN, while the mesenchymal subtype was identified by low expression of SOX2 and high expression of two antibodies, SHC1 and TCIRG1, selected on the basis of RNA differential transcriptomic expression. The proneural subtype was identified by frequent positive IDH1 expression and high Olig2 and Ki67 expression. Immune-phenotyping showed that mesenchymal and IGS 23 tumors exhibited a higher positive effector cell score, a higher negative suppressor cell score, and lower levels of immune checkpoint molecules. The cell-type deconvolution analysis revealed that these tumors are highly enriched in M2 macrophages, resting memory CD4+ T cells, and activated dendritic cells, indicating that they may be ideal candidates for immunotherapy, especially with anti-M2 and/or dendritic cell vaccination. Conclusions: There is a subset of tumors, frequently classified as mesenchymal or IGS cluster 23, that may be identified with IHC and could well be optimal candidates for immunotherapy.

Glioblastoma TCGA Mesenchymal and IGS 23 Tumors are Identifiable by IHC and have an Immune-phenotype Indicating a Potential Benefit from Immunotherapy.

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Pseudoprogression as an adverse event of glioblastoma therapy

Glioblastoma TCGA Mesenchymal and IGS 23 Tumors are Identifiable by IHC and have an Immune-phenotype Indicating a Potential Benefit from Immunotherapy.