Neuronal differentiation drives the antitumor activity of mitogen-activated protein kinase kinase (MEK) inhibition in glioblastoma.

Background: Epidermal growth factor receptor (EGFR) amplification is found in nearly 40%-50% of glioblastoma cases. Several EGFR inhibitors have been tested in glioblastoma but have failed to demonstrate long-term therapeutic benefit, presumably because of acquired resistance. Targeting EGFR downstream signaling with mitogen-activated protein kinase kinase 1 and 2 (MEK1/2) inhibitors would be a more effective approach to glioblastoma treatment. We tested the therapeutic potential of MEK1/2 inhibitors in glioblastoma using 3D cultures of glioma stem-like cells (GSCs) and mouse models of glioblastoma. Methods: Several MEK inhibitors were screened in an unbiased high-throughput platform using GSCs. Cell death was evaluated using flow cytometry and Western blotting (WB) analysis. RNA-seq, real-time quantitative polymerase chain reaction, immunofluorescence, and WB analysis were used to identify and validate neuronal differentiation. Results: Unbiased screening of multiple MEK inhibitors in GSCs showed antiproliferative and apoptotic cell death in sensitive cell lines. An RNA-seq analysis of cells treated with trametinib, a potent MEK inhibitor, revealed upregulation of neurogenesis and neuronal differentiation genes, such as achaete-scute homolog 1 (ASCL1), delta-like 3 (DLL3), and neurogenic differentiation 4 (NeuroD4). We validated the neuronal differentiation phenotypes in vitro and in vivo using selected differentiation markers (ß-III-tubulin, ASCL1, DLL3, and NeuroD4). Oral treatment with trametinib in an orthotopic GSC xenograft model significantly improved animal survival, with 25%-30% of mice being long-term survivors. Conclusions: Our findings demonstrated that MEK1/2 inhibition promotes neuronal differentiation in glioblastoma, a potential additional mechanism of action of MEK1/2 inhibitors. Thus, MEK inhibitors could be efficacious in glioblastoma patients with activated EGFR/MAPK signaling.

DNA Repair Genes as Drug Candidates for Early Breast Cancer Onset in Latin America: A Systematic Review.

The prevalence of breast cancer in young women (YWBC) has increased alarmingly. Significant efforts are being made to elucidate the biological mechanisms concerning the development, prognosis, and pathological response in early-onset breast cancer (BC) patients. Dysfunctional DNA repair proteins are implied in BC predisposition, progression, and therapy response, underscoring the need for further analyses on DNA repair genes. Public databases of large patient datasets such as METABRIC, TCGA, COSMIC, and cancer cell lines allow the identification of variants in DNA repair genes and possible precision drug candidates. This study aimed at identifying variants and drug candidates that may benefit Latin American (LA) YWBC. We analyzed pathogenic variants in 90 genes involved in DNA repair in public BC datasets from METABRIC, TCGA, COSMIC, CCLE, and COSMIC Cell Lines Project. Results showed that reported DNA repair germline variants in the LA dataset are underrepresented in large databases, in contrast to other populations. Additionally, only six gene repair variants in women under 50 years old from the study population were reported in BC cell lines. Therefore, there is a need for new approaches to study DNA repair variants reported in young women from LA.

Intrinsic Interferon Signaling Regulates the Cell Death and Mesenchymal Phenotype of Glioblastoma Stem Cells.

Interferon (IFN) signaling contributes to stemness, cell proliferation, cell death, and cytokine signaling in cancer and immune cells; however, the role of IFN signaling in glioblastoma (GBM) and GBM stem-like cells (GSCs) is unclear. Here, we investigated the role of cancer-cell-intrinsic IFN signaling in tumorigenesis in GBM. We report here that GSCs and GBM tumors exhibited differential cell-intrinsic type I and type II IFN signaling, and high IFN/STAT1 signaling was associated with mesenchymal phenotype and poor survival outcomes. In addition, chronic inhibition of IFN/STAT1 signaling decreased cell proliferation and mesenchymal signatures in GSCs with intrinsically high IFN/STAT1 signaling. IFN-ß exposure induced apoptosis in GSCs with intrinsically high IFN/STAT1 signaling, and this effect was abolished by the pharmacological inhibitor ruxolitinib and STAT1 knockdown. We provide evidence for targeting IFN signaling in a specific sub-group of GBM patients. IFN-ß may be a promising candidate for adjuvant GBM therapy.

Bowel obstruction as a serious complication of patients with femoral hernia.

PURPOSE: The implications of bowel obstruction occurring secondary to femoral hernia have not been discussed in the literature recently. Thus, we report our experience of treating patients with femoral hernias complicated by bowel obstruction versus patients with femoral hernias not complicated by bowel obstruction. METHODS: The subjects of this retrospective study were patients admitted to our hospital for the treatment of femoral hernias between 2016 and 2019. We used the Fisher and Student's T test to compare the preoperative characteristics, treatment, and outcomes of patients with bowel obstruction versus those without bowel obstruction. RESULTS: A total of 53 patients (mean age, 66.9 ± 15.1 years) were treated, 18 (33.9%) of whom underwent elective surgery and 35 (66%) of whom required emergency surgery (p = 0.001). The mean time between the development of symptoms and hospitalization was 4.5 ± 3.1 days for the patients with bowel obstruction and 1.6 ± 3.2 days for those without bowel obstruction (p = 0.001). The length of hospital stay was 11.1 ± 21.1 days for the patients with bowel obstruction and 1 ± 1.8 days for those without bowel obstruction (p = 0.028). Overall morbidity and mortality rates were 13.2% and 5.6%, respectively. CONCLUSION: Femoral hernias causing bowel obstruction are associated with greater time between the development of symptoms, hospitalization, and with a longer hospital stay.

Computational methods for detecting cancer hotspots.

Cancer mutations that are recurrently observed among patients are known as hotspots. Hotspots are highly relevant because they are, presumably, likely functional. Known hotspots in BRAF, PIK3CA, TP53, KRAS, IDH1 support this idea. However, hundreds of hotspots have never been validated experimentally. The detection of hotspots nevertheless is challenging because background mutations obscure their statistical and computational identification. Although several algorithms have been applied to identify hotspots, they have not been reviewed before. Thus, in this mini-review, we summarize more than 40 computational methods applied to detect cancer hotspots in coding and non-coding DNA. We first organize the methods in cluster-based, 3D, position-specific, and miscellaneous to provide a general overview. Then, we describe their embed procedures, implementations, variations, and differences. Finally, we discuss some advantages, provide some ideas for future developments, and mention opportunities such as application to viral integrations, translocations, and epigenetics.

Depletion of CLK2 sensitizes glioma stem-like cells to PI3K/mTOR and FGFR inhibitors.

The Cdc2-like kinases (CLKs) regulate RNA splicing and have been shown to suppress cell growth. Knockdown of CLK2 was found to block glioma stem-like cell (GSC) growth in vivo through the AKT/FOXO3a/p27 pathway without activating mTOR and MAPK signaling, suggesting that these pathways mediate resistance to CLK2 inhibition. We identified CLK2 binding partners using immunoprecipitation assays and confirmed their interactions in vitro in GSCs. We then tested the cellular viability of several signaling inhibitors in parental and CLK2 knockdown GSCs. Our results demonstrate that CLK2 binds to 14-3-3τ isoform and prevents its ubiquitination in GSCs. Stable CLK2 knockdown increased PP2A activity and activated PI3K signaling. Treatment with a PI3K/mTOR inhibitor in CLK2 knockdown cells led to a modest reduction in cell viability compared to drug treatment alone at a lower dose. However, FGFR inhibitor in CLK2 knockdown cells led to a decrease in cell viability and increased apoptosis. Reduced expression of CLK2 in glioblastoma, in combination with FGFR inhibitors, led to synergistic apoptosis induction and cell cycle arrest compared to blockade or either kinase alone.

Comparative Molecular Life History of Spontaneous Canine and Human Gliomas.

Sporadic gliomas in companion dogs provide a window on the interaction between tumorigenic mechanisms and host environment. We compared the molecular profiles of canine gliomas with those of human pediatric and adult gliomas to characterize evolutionarily conserved mammalian mutational processes in gliomagenesis. Employing whole-genome, exome, transcriptome, and methylation sequencing of 83 canine gliomas, we found alterations shared between canine and human gliomas such as the receptor tyrosine kinases, TP53 and cell-cycle pathways, and IDH1 R132. Canine gliomas showed high similarity with human pediatric gliomas per robust aneuploidy, mutational rates, relative timing of mutations, and DNA-methylation patterns. Our cross-species comparative genomic analysis provides unique insights into glioma etiology and the chronology of glioma-causing somatic alterations.

EGFR Amplification Induces Increased DNA Damage Response and Renders Selective Sensitivity to Talazoparib (PARP Inhibitor) in Glioblastoma.

PURPOSE: Exploration of novel strategies to extend the benefit of PARP inhibitors beyond BRCA-mutant cancers is of great interest in personalized medicine. Here, we identified EGFR amplification as a potential biomarker to predict sensitivity to PARP inhibition, providing selection for the glioblastoma (GBM) patient population who will benefit from PARP inhibition therapy. EXPERIMENTAL DESIGN: Selective sensitivity to the PARP inhibitor talazoparib was screened and validated in two sets [test set (n = 14) and validation set (n = 13)] of well-characterized patient-derived glioma sphere-forming cells (GSC). FISH was used to detect EGFR copy number. DNA damage response following talazoparib treatment was evaluated by γH2AX and 53BP1 staining and neutral comet assay. PARP-DNA trapping was analyzed by subcellular fractionation. The selective monotherapy of talazoparib was confirmed using in vivo glioma models. RESULTS: EGFR-amplified GSCs showed remarkable sensitivity to talazoparib treatment. EGFR amplification was associated with increased reactive oxygen species (ROS) and subsequent increased basal expression of DNA-repair pathways to counterelevated oxidative stress, and thus rendered vulnerability to PARP inhibition. Following talazoparib treatment, EGFR-amplified GSCs showed enhanced DNA damage and increased PARP-DNA trapping, which augmented the cytotoxicity. EGFR amplification-associated selective sensitivity was further supported by the in vivo experimental results showing that talazoparib significantly suppressed tumor growth in EGFR-amplified subcutaneous models but not in nonamplified models. CONCLUSIONS: EGFR-amplified cells are highly sensitive to talazoparib. Our data provide insight into the potential of using EGFR amplification as a selection biomarker for the development of personalized therapy.

BRCA1 identified as a modulator of temozolomide resistance in P53 wild-type GBM using a high-throughput shRNA-based synthetic lethality screening.

Glioblastoma multiforme (GBM), the most common type of primary brain tumor, is universally fatal, with a median survival duration ranging from 12-15 months despite maximum treatment efforts. Temozolomide (TMZ) is the current standard of care for GBM patients; however patients usually develop resistance to TMZ and limits its benefit. The identification of novel synergistic targets in GBM will lead to the development of new targeted drugs, which could be combined with broad-spectrum cytotoxic agents. In this study, we used a high-throughput synthetic lethality screen with a pooled short hairpin DNA repair library, in combination with TMZ, to identify targets that will enhance TMZ-induced antitumor effects. Using an unbiased bioinformatical analysis, we identified BRCA1 as a potential promising candidate gene that induced synthetic lethality with TMZ in glioma sphere-forming cells (GSCs). BRCA1 knockdown resulted in antitumor activity with TMZ in P53 wild-type GSCs but not in P53 mutant GSCs. TMZ treatment induced a DNA damage repair response; the activation of BRCA1 DNA repair pathway targets and knockdown of BRCA1, together with TMZ, led to increased DNA damage and cell death in P53 wild-type GSCs. Our study identified BRCA1 as a potential target that sensitizes TMZ-induced cell death in P53 wild-type GBM, suggesting that the combined inhibition of BRCA1 and TMZ treatment will be a successful targeted therapy for GBM patients.

Landscape of Germline Mutations in DNA Repair Genes for Breast Cancer in Latin America: Opportunities for PARP-Like Inhibitors and Immunotherapy.

Germline mutations in BRCA1 and BRCA2 (BRCA1/2) genes are present in about 50% of cases of hereditary breast cancer. Proteins encoded by these genes are key players in DNA repair by homologous recombination (HR). Advances in next generation sequencing and gene panels for breast cancer testing have generated a large amount of data on gene variants implicated in hereditary breast cancer, particularly in genes such as PALB2, ATM, CHEK2, RAD51, MSH2, and BARD1. These genes are involved in DNA repair. Most of these variants have been reported for Caucasian, Jewish, and Asian population, with few reports for other communities, like those in Latin American (LA) countries. We reviewed 81 studies from 11 LA countries published between 2000 and 2019 but most of these studies focused on BRCA1/2 genes. In addition to these genes, breast cancer-related variants have been reported for PALB2, ATM, CHEK2, BARD1, MLH1, BRIP1, MSH2, NBN, MSH6, and PMS2 genes. Some of these variants are unique to LA populations. This analysis may contribute to enhance breast cancer variant characterization, and thus to find therapies and implement precision medicine for LA communities.

Wild-type TP53 defined gamma-secretase inhibitor sensitivity and synergistic activity with doxorubicin in GSCs.

Glioblastoma (GBM) is the most common and lethal primary intracranial tumor. Aggressive surgical resection plus radiotherapy and temozolomide have prolonged patients' median survival to only 14.6 months. Therefore, there is a critical need to develop novel therapeutic strategies for GBM. In this study, we evaluated the effect of NOTCH signaling intervention by gamma-secretase inhibitors (GSIs) on glioma sphere-forming cells (GSCs). GSI sensitivity exhibited remarkable selectivity among wild-type TP53 (wt-p53) GSCs. GSIs significantly impaired the sphere formation of GSCs harboring wt-p53. We also identified a concurrence between GSI sensitivity, NOTCH1 expression, and wt-p53 activity in GSCs. Through a series of gene editing and drug treatment experiments, we found that wt-p53 did not modulate NOTCH1 pathway, whereas NOTCH1 signaling positively regulated wt-p53 expression and activity in GSCs. Finally, GSIs (targeting NOTCH signaling) synergized with doxorubicin (activating wt-p53) to inhibit proliferation and induce apoptosis in wt-p53 GSCs. Taken together, we identified wt-p53 as a potential marker for GSI sensitivity in GSCs. Combining GSI with doxorubicin synergistically inhibited the proliferation and survival of GSCs harboring wt-p53.

Tie2-FGFR1 Interaction Induces Adaptive PI3K Inhibitor Resistance by Upregulating Aurora A/PLK1/CDK1 Signaling in Glioblastoma.

PI3K-targeting therapy represents one of the most sought-after therapies for glioblastoma (GBM). Several small-molecule inhibitors have been evaluated in clinical trials, however, the emergence of resistance limits treatment potential. Here, we generated a patient-derived glioma sphere-forming cell (GSC) xenograft model resistant to the PI3K-specific inhibitor BKM-120. Integrated RNA sequencing and high-throughput drug screening revealed that the Aurora A kinase (Aurora A)/Polo-like kinase 1 (PLK1)/cyclin-dependent kinase 1 (CDK1) signaling pathway was the main driver of PI3K inhibitor resistance in the resistant xenografts. Aurora kinase was upregulated and pCDK1 was downregulated in resistant tumors from both xenografts and tumor tissues from patients treated with the PI3K inhibitor. Mechanistically, the tyrosine kinase receptor Tie2 physically interacted with FGFR1, promoting STAT3 phosphorylation and binding to the AURKA promoter, which increased Aurora A expression in resistant GSCs. Concurrent inhibition of Aurora A and PI3K signaling overcame PI3K inhibitor-induced resistance. This study offers a proof of concept to target PI3K and the collateral-activated pathway to improve GBM therapy. SIGNIFICANCE: These findings provide novel insights into the mechanisms of PI3K inhibitor resistance in glioblastoma.

The polo-like kinase 1 inhibitor volasertib synergistically increases radiation efficacy in glioma stem cells.

BACKGROUND: Despite the availability of hundreds of cancer drugs, there is insufficient data on the efficacy of these drugs on the extremely heterogeneous tumor cell populations of glioblastoma (GBM). RESULTS: The PKIS of 357 compounds was initially evaluated in 15 different GSC lines which then led to a more focused screening of the 21 most highly active compounds in 11 unique GSC lines using HTS screening for cell viability. We further validated the HTS result with the second-generation PLK1 inhibitor volasertib as a single agent and in combination with ionizing radiation (IR). In vitro studies showed that volasertib inhibited cell viability, and high levels of the anti-apoptotic protein Bcl-xL expression were highly correlated with volasertib resistance. Volasertib sensitized GSCs to radiation therapy by enhancing G2/M arrest and by inducing apoptosis. Colony-formation assay demonstrated that volasertib plus IR synergistically inhibited colony formation. In intracranial xenograft mouse models, the combination of volasertib and radiation significantly inhibited GSC tumor growth and prolonged median survival compared with radiation treatment alone due to inhibition of cell proliferation, enhancement of DNA damage, and induction of apoptosis. CONCLUSIONS: Our results reinforce the potential therapeutic efficacy of volasertib in combination with radiation for the treatment of GBM. METHODS: We used high-throughput screening (HTS) to identify drugs, out of 357 compounds in the published Protein Kinase Inhibitor Set, with the greatest efficacy against a panel of glioma stem cells (GSCs), which are representative of the classic cancer genome atlas (TCGA) molecular subtypes.

TumorFusions: an integrative resource for cancer-associated transcript fusions.

Gene fusion represents a class of molecular aberrations in cancer and has been exploited for therapeutic purposes. In this paper we describe TumorFusions, a data portal that catalogues 20 731 gene fusions detected in 9966 well characterized cancer samples and 648 normal specimens from The Cancer Genome Atlas (TCGA). The portal spans 33 cancer types in TCGA. Fusion transcripts were identified via a uniform pipeline, including filtering against a list of 3838 transcript fusions detected in a panel of 648 non-neoplastic samples. Fusions were mapped to somatic DNA rearrangements identified using whole genome sequencing data from 561 cancer samples as a means of validation. We observed that 65% of transcript fusions were associated with a chromosomal alteration, which is annotated in the portal. Other features of the portal include links to SNP array-based copy number levels and mutational patterns, exon and transcript level expressions of the partner genes, and a network-based centrality score for prioritizing functional fusions. Our portal aims to be a broadly applicable and user friendly resource for cancer gene annotation and is publicly available at http://www.tumorfusions.org.

Tumor Evolution of Glioma-Intrinsic Gene Expression Subtypes Associates with Immunological Changes in the Microenvironment.

We leveraged IDH wild-type glioblastomas, derivative neurospheres, and single-cell gene expression profiles to define three tumor-intrinsic transcriptional subtypes designated as proneural, mesenchymal, and classical. Transcriptomic subtype multiplicity correlated with increased intratumoral heterogeneity and presence of tumor microenvironment. In silico cell sorting identified macrophages/microglia, CD4+ T lymphocytes, and neutrophils in the glioma microenvironment. NF1 deficiency resulted in increased tumor-associated macrophages/microglia infiltration. Longitudinal transcriptome analysis showed that expression subtype is retained in 55% of cases. Gene signature-based tumor microenvironment inference revealed a decrease in invading monocytes and a subtype-dependent increase in macrophages/microglia cells upon disease recurrence. Hypermutation at diagnosis or at recurrence associated with CD8+ T cell enrichment. Frequency of M2 macrophages detection associated with short-term relapse after radiation therapy.

Revealing protein networks and gene-drug connectivity in cancer from direct information.

The connection between genetic variation and drug response has long been explored to facilitate the optimization and personalization of cancer therapy. Crucial to the identification of drug response related genetic features is the ability to separate indirect correlations from direct correlations across abundant datasets with large number of variables. Here we analyzed proteomic and pharmacogenomic data in cancer tissues and cell lines using a global statistical model connecting protein pairs, genes and anti-cancer drugs. We estimated this model using direct coupling analysis (DCA), a powerful statistical inference method that has been successfully applied to protein sequence data to extract evolutionary signals that provide insights on protein structure, folding and interactions. We used Direct Information (DI) as a metric of connectivity between proteins as well as gene-drug pairs. We were able to infer important interactions observed in cancer-related pathways from proteomic data and predict potential connectivities in cancer networks. We also identified known and potential connections for anti-cancer drugs and gene mutations using DI in pharmacogenomic data. Our findings suggest that gene-drug connections predicted with direct couplings can be used as a reliable guide to cancer therapy and expand our understanding of the effects of gene alterations on drug efficacies.

Systematic Epigenomic Analysis Reveals Chromatin States Associated with Melanoma Progression.

The extent and nature of epigenomic changes associated with melanoma progression is poorly understood. Through systematic epigenomic profiling of 35 epigenetic modifications and transcriptomic analysis, we define chromatin state changes associated with melanomagenesis by using a cell phenotypic model of non-tumorigenic and tumorigenic states. Computation of specific chromatin state transitions showed loss of histone acetylations and H3K4me2/3 on regulatory regions proximal to specific cancer-regulatory genes in important melanoma-driving cell signaling pathways. Importantly, such acetylation changes were also observed between benign nevi and malignant melanoma human tissues. Intriguingly, only a small fraction of chromatin state transitions correlated with expected changes in gene expression patterns. Restoration of acetylation levels on deacetylated loci by histone deacetylase (HDAC) inhibitors selectively blocked excessive proliferation in tumorigenic cells and human melanoma cells, suggesting functional roles of observed chromatin state transitions in driving hyperproliferative phenotype. Through these results, we define functionally relevant chromatin states associated with melanoma progression.

Multigene signature for predicting prognosis of patients with 1p19q co-deletion diffuse glioma.

Background: Co-deletion of 1p and 19q marks a diffuse glioma subtype associated with relatively favorable overall survival; however, heterogeneous clinical outcomes are observed within this category. Methods: We assembled gene expression profiles and sample annotation of 374 glioma patients carrying the 1p/19q co-deletion. We predicted 1p/19q status using gene expression when annotation was missing. A first cohort was randomly split into training (n = 170) and a validation dataset (n = 163). A second validation set consisted of 41 expression profiles. An elastic-net penalized Cox proportional hazards model was applied to build a classifier model through cross-validation within the training dataset. Results: The selected 35-gene signature was used to identify high-risk and low-risk groups in the validation set, which showed significantly different overall survival (P = .00058, log-rank test). For time-to-death events, the high-risk group predicted by the gene signature yielded a hazard ratio of 1.78 (95% confidence interval, 1.02-3.11). The signature was also significantly associated with clinical outcome in the The Cancer Genome Atlas (CGA) IDH-mutant 1p/19q wild-type and IDH-wild-type glioma cohorts. Pathway analysis suggested that high risk was associated with increased acetylation activity and inflammatory response. Tumor purity was found to be significantly decreased in high-risk IDH-mutant with 1p/19q co-deletion gliomas and IDH-wild-type glioblastomas but not in IDH-wild-type lower grade or IDH-mutant, non-co-deleted gliomas. Conclusion: We identified a 35-gene signature that identifies high-risk and low-risk categories of 1p/19q positive glioma patients. We have demonstrated heterogeneity amongst a relatively new glioma subtype and provided a stepping stone towards risk stratification.

Identification of outcome-related driver mutations in cancer using conditional co-occurrence distributions.

Previous methods proposed for the detection of cancer driver mutations have been based on the estimation of background mutation rate, impact on protein function, or network influence. In this paper, we instead focus on those factors influencing patient survival. To this end, an approximation of the log-rank test has been systematically applied, even though it assumes a large and similar number of patients in both risk groups, which is violated in cancer genomics. Here, we propose VALORATE, a novel algorithm for the estimation of the null distribution for the log-rank, independent of the number of mutations. VALORATE is based on conditional distributions of the co-occurrences between events and mutations. The results, achieved through simulations, comparisons with other methods, analyses of TCGA and ICGC cancer datasets, and validations, suggest that VALORATE is accurate, fast, and can identify both known and novel gene mutations. Our proposal and results may have important implications in cancer biology, bioinformatics analyses, and ultimately precision medicine.