SIRT1 regulates DNA damage signaling through the PP4 phosphatase complex.

The Sirtuin family of NAD+-dependent enzymes plays an important role in maintaining genome stability upon stress. Several mammalian Sirtuins have been linked directly or indirectly to the regulation of DNA damage during replication through Homologous recombination (HR). The role of one of them, SIRT1, is intriguing as it seems to have a general regulatory role in the DNA damage response (DDR) that has not yet been addressed. SIRT1-deficient cells show impaired DDR reflected in a decrease in repair capacity, increased genome instability and decreased levels of γH2AX. Here we unveil a close functional antagonism between SIRT1 and the PP4 phosphatase multiprotein complex in the regulation of the DDR. Upon DNA damage, SIRT1 interacts specifically with the catalytical subunit PP4c and promotes its inhibition by deacetylating the WH1 domain of the regulatory subunits PP4R3α/ß. This in turn regulates γH2AX and RPA2 phosphorylation, two key events in the signaling of DNA damage and repair by HR. We propose a mechanism whereby during stress, SIRT1 signaling ensures a global control of DNA damage signaling through PP4.

Glioblastoma cells have increased capacity to repair radiation-induced DNA damage after migration to the olfactory bulb.

BACKGROUND: The invasive nature of GBM combined with the diversity of brain microenvironments creates the potential for a topographic heterogeneity in GBM radioresponse. Investigating the mechanisms responsible for a microenvironment-induced differential GBM response to radiation may provide insights into the molecules and processes mediating GBM radioresistance. METHODS: Using a model system in which human GBM stem-like cells implanted into the right striatum of nude mice migrate throughout the right hemisphere (RH) to the olfactory bulb (OB), the radiation-induced DNA damage response was evaluated in each location according to γH2AX and 53BP1 foci and cell cycle phase distribution as determined by flow cytometry and immunohistochemistry. RNAseq was used to compare transcriptomes of tumor cells growing in the OB and the RH. Protein expression and neuron-tumor interaction were defined by immunohistochemistry and confocal microscopy. RESULTS: After irradiation, there was a more rapid dispersal of γH2AX and 53BP1 foci in the OB versus in the RH, indicative of increased double strand break repair capacity in the OB and consistent with the OB providing a radioprotective niche. With respect to the cell cycle, by 6 h after irradiation there was a significant loss of mitotic tumor cells in both locations suggesting a similar activation of the G2/M checkpoint. However, by 24 h post-irradiation there was an accumulation of G2 phase cells in the OB, which continued out to at least 96 h. Transcriptome analysis showed that tumor cells in the OB had higher expression levels of DNA repair genes involved in non-homologous end joining and genes related to the spindle assembly checkpoint. Tumor cells in the OB were also found to have an increased frequency of soma-soma contact with neurons. CONCLUSION: GBM cells that have migrated to the OB have an increased capacity to repair radiation-induced double strand breaks and altered cell cycle regulation. These results correspond to an upregulation of genes involved in DNA damage repair and cell cycle control. Because the murine OB provides a source of radioresistant tumor cells not evident in other experimental systems, it may serve as a model for investigating the mechanisms mediating GBM radioresistance.

Long intergenic noncoding RNA profiles of pheochromocytoma and paraganglioma: A novel prognostic biomarker.

Many long intergenic noncoding RNAs (lincRNAs) serve as cancer biomarkers for diagnosis or prognostication. To understand the role of lincRNAs in the rare neuroendocrine tumors pheochromocytoma and paraganglioma (PCPG), we performed first time in-depth characterization of lincRNA expression profiles and correlated findings to clinical outcomes of the disease. RNA-Seq data from patients with PCPGs and 17 other tumor types from The Cancer Genome Atlas and other published sources were obtained. Differential expression analysis and a machine-learning model were used to identify transcripts specific to PCPGs, as well as established PCPG molecular subtypes. Similarly, lincRNAs specific to aggressive PCPGs were identified, and univariate and multivariate analysis was performed for metastasis-free survival. The results were validated in independent samples using RT-PCR. From a pan-cancer context, PCPGs had a specific and unique lincRNA profile. Among PCPGs, five different molecular subtypes were identified corresponding to the established molecular classification. Upregulation of 13 lincRNAs was found to be associated with aggressive/metastatic PCPGs. RT-PCR validation confirmed the overexpression of four lincRNAs in metastatic compared to non-metastatic PCPGs. Kaplan-Meier analysis identified five lincRNAs as prognostic markers for metastasis-free survival of patients in three subtypes of PCPGs. Stratification of PCPG patients with a risk-score formulated using multivariate analysis of lincRNA expression profiles, presence of key driver mutations, tumor location, and hormone secretion profiles showed significant differences in metastasis-free survival. PCPGs thus exhibit a specific lincRNA expression profile that also corresponds to the established molecular subgroups and can be potential marker for the aggressive/metastatic PCPGs.

DiscoverSL: an R package for multi-omic data driven prediction of synthetic lethality in cancers.

SUMMARY: Synthetic lethality is a state when simultaneous loss of two genes is lethal to a cancer cell, while the loss of the individual genes is not. We developed an R package DiscoverSL to predict and visualize synthetic lethality in cancers using multi-omic cancer data. Mutation, copy number alteration and gene expression data from The Cancer Genome Atlas project were combined to develop a multi-parametric Random Forest classifier. The effects of selectively targeting the predicted synthetic lethal genes is tested in silico using shRNA and drug screening data from cancer cell line databases. The clinical outcome in patients with mutation in primary gene and over/under-expression in the synthetic lethal gene is evaluated using Kaplan-Meier analysis. The method helps to identify new therapeutic approaches by exploiting the concept of synthetic lethality. AVAILABILITY AND IMPLEMENTATION: DiscoverSL package with user manual and sample workflow is available for download from github url: https://github.com/shaoli86/DiscoverSL/releases/tag/V1.0 under GNU GPL-3. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Detection of glioblastoma intratumor heterogeneity in radiosensitivity using patient-derived neurosphere cultures.

PURPOSE: Glioblastoma (GBM) is characterized by extensive clonal diversity suggesting the presence of tumor cells with varying degrees of treatment sensitivity. Radiotherapy is an integral part of glioblastoma treatment. Whether GBMs are comprised of spatially distinct cellular populations with uniform or varying degrees of radiosensitivity has not been established. METHODS: Spatially distinct regions of three GBMs (J3, J7 and J14) were resected and unique cell lines were derived from each region. DNA from cell lines, corresponding tumor fragments, and patient blood was extracted for whole exome sequencing. Variants, clonal composition, and functional implications were compared and analyzed with superFreq and IPA. Limiting dilution assays were performed on cell lines to measure intrinsic radiosensitivity. RESULTS: Based on WES, cell lines generated from different regions of the same tumor were more closely correlated with their tumor of origin than the other GBMs. Variant and clonal composition comparisons showed that cell lines from distinct tumors displayed increasing levels of ITH with J3 and J14 having the lowest and highest, respectively. The radiosensitivities of the cell lines generated from the J3 tumor were similar as were those generated from the J7 tumor. However, the radiosensitivities of the 2 cell lines generated from the J14 tumor (J14T3 and J14T6) were significantly different with J14T6 being more sensitive than J14T3. CONCLUSION: Data suggest a tumor dependent ITH in radiosensitivity. The existence of ITH in radiosensitivity may impact not only the initial therapeutic response but also the effectiveness of retreatment protocols.

Microarray analysis of miRNA expression profiles following whole body irradiation in a mouse model.

CONTEXT: Accidental exposure to life-threatening radiation in a nuclear event is a major concern; there is an enormous need for identifying biomarkers for radiation biodosimetry to triage populations and treat critically exposed individuals. OBJECTIVE: To identify dose-differentiating miRNA signatures from whole blood samples of whole body irradiated mice. METHODS: Mice were whole body irradiated with X-rays (2 Gy-15 Gy); blood was collected at various time-points post-exposure; total RNA was isolated; miRNA microarrays were performed; miRNAs differentially expressed in irradiated vs. unirradiated controls were identified; feature extraction and classification models were applied to predict dose-differentiating miRNA signature. RESULTS: We observed a time and dose responsive alteration in the expression levels of miRNAs. Maximum number of miRNAs were altered at 24-h and 48-h time-points post-irradiation. A 23-miRNA signature was identified using feature selection algorithms and classifier models. An inverse correlation in the expression level changes of miR-17 members, and their targets were observed in whole body irradiated mice and non-human primates. CONCLUSION: Whole blood-based miRNA expression signatures might be used for predicting radiation exposures in a mass casualty nuclear incident.

Radiation-Induced Alteration of the Brain Proteome: Understanding the Role of the Sirtuin 2 Deacetylase in a Murine Model.

Whole brain radiotherapy (WBRT) produces unwanted sequelae, albeit via unknown mechanisms. A deacetylase expressed in the central nervous system, Sirtuin 2 (SIRT2), has been linked to neurodegeneration. Therefore, we sought to challenge the notion that a single disease pathway is responsible for radiation-induced brain injury in Sirt2 wild-type (WT) and knockout (KO) mice at the proteomic level. We utilized isobaric tag for relative and absolute quantitation to analyze brain homogenates from Sirt2 WT and KO mice with and without WBRT. Selected proteins were independently verified, followed by ingenuity pathway analysis. Canonical pathways for Huntington's, Parkinson's, and Alzheimer's were acutely affected by radiation within 72 h of treatment. Although loss of Sirt2 preferentially affected both Huntington's and Parkinson's pathways, WBRT most significantly affected Huntington's-related proteins in the absence of Sirt2. Identical protein expression patterns were identified in Mog following WBRT in both Sirt2 WT and KO mice, revealing a proteomic radiation signature; however, long-term radiation effects were found to be associated with altered levels of a small number of key neurodegeneration-related proteins, identified as Mapt, Mog, Snap25, and Dnm1. Together, these data demonstrate the principle that the presence of Sirt2 can have significant effects on the brain proteome and its response to ionizing radiation.

Corrigendum: Glioblastoma survival is associated with distinct proteomic alteration signatures post chemoirradiation in a large-scale proteomic panel.

[This corrects the article DOI: 10.3389/fonc.2023.1127645.].

Multiomic-Based Molecular Landscape of FaDu Xenograft Tumors in Mice after a Combinatorial Treatment with Radiation and an HSP90 Inhibitor Identifies Adaptation-Induced Targets of Resistance and Therapeutic Intervention.

Treatments involving radiation and chemotherapy alone or in combination have improved patient survival and quality of life. However, cancers frequently evade these therapies due to adaptation and tumor evolution. Given the complexity of predicting response based solely on the initial genetic profile of a patient, a predetermined treatment course may miss critical adaptation that can cause resistance or induce new targets for drug and immunotherapy. To address the timescale for these evasive mechanisms, using a mouse xenograft tumor model, we investigated the rapidity of gene expression (mRNA), molecular pathway, and phosphoproteome changes after radiation, an HSP90 inhibitor, or combination. Animals received radiation, drug, or combination treatment for 1 or 2 weeks and were then euthanized along with a time-matched untreated group for comparison. Changes in gene expression occur as early as 1 week after treatment initiation. Apoptosis and cell death pathways were activated in irradiated tumor samples. For the HSP90 inhibitor and combination treatment at weeks 1 and 2 compared with Control Day 1, gene-expression changes induced inhibition of pathways including invasion of cells, vasculogenesis, and viral infection among others. The combination group included both drug-alone and radiation-alone changes. Our data demonstrate the rapidity of gene expression and functional pathway changes in the evolving tumor as it responds to treatment. Discovering these phenotypic adaptations may help elucidate the challenges in using sustained treatment regimens and could also define evolving targets for therapeutic efficacy.

De novo TLK1 and MDM1 mutations in a patient with a neurodevelopmental disorder and immunodeficiency.

The Tousled-like kinases 1 and 2 (TLK1/TLK2) regulate DNA replication, repair and chromatin maintenance. TLK2 variants underlie the neurodevelopmental disorder (NDD) 'Intellectual Disability, Autosomal Dominant 57' (MRD57), characterized by intellectual disability and microcephaly. Several TLK1 variants have been reported in NDDs but their functional significance is unknown. A male patient presenting with ID, seizures, global developmental delay, hypothyroidism, and primary immunodeficiency was determined to have a heterozygous TLK1 variant (c.1435C>G, p.Q479E), as well as a mutation in MDM1 (c.1197dupT, p.K400∗). Cells expressing TLK1 p.Q479E exhibited reduced cytokine responses and elevated DNA damage, but not increased radiation sensitivity or DNA repair defects. The TLK1 p.Q479E variant impaired kinase activity but not proximal protein interactions. Our study provides the first functional characterization of NDD-associated TLK1 variants and suggests that, such as TLK2, TLK1 variants may impact development in multiple tissues and should be considered in the diagnosis of rare NDDs.

Glioma-BioDP: database for visualization of molecular profiles to improve prognosis of brain cancer.

Cancer researchers often seek user-friendly interactive tools for validation, exploration, analysis, and visualization of molecular profiles in cancer patient samples. To aid researchers working on the both low- and high-grade gliomas, we developed Glioma-BioDP, a web tool for exploration and visualization of RNA and protein expression profiles of interest in these tumor types. Glioma-BioDP is user friendly application that include expression data from both the low- and high-grade glioma patient samples from The Cancer Genome Atlas and enabled querying by mRNA, microRNA, and protein level expression data from Illumina HiSeq and RPPA platforms respectively. Glioma-BioDP provides advance query interface and enables users to explore the association of genes, proteins, and miRNA expression with molecular and/or histological subtypes of gliomas, surgical resection status and survival. The prognostic significance and visualization of the selected expression profiles can be explored using interactive utilities provided. This tool may also enable validation and generation of new hypotheses of novel therapies impacting gliomas that aid in personalization of treatment for optimum outcomes.

Comparative Analysis of miRNA Expression after Whole-Body Irradiation Across Three Strains of Mice.

Whole- or partial-body exposure to ionizing radiation damages major organ systems, leading to dysfunction on both acute and chronic timescales. Radiation medical countermeasures can mitigate acute damages and may delay chronic effects when delivered within days after exposure. However, in the event of widespread radiation exposure, there will inevitably be scarce resources with limited countermeasures to distribute among the affected population. Radiation biodosimetry is necessary to separate exposed from unexposed victims and determine those who requires the most urgent care. Blood-based, microRNA signatures have great potential for biodosimetry, but the affected population in such a situation will be genetically heterogeneous and have varying miRNA responses to radiation. Thus, there is a need to understand differences in radiation-induced miRNA expression across different genetic backgrounds to develop a robust signature. We used inbred mouse strains C3H/HeJ and BALB/c mice to determine how accurate miRNA in blood would be in developing markers for radiation vs. no radiation, low dose (1 Gy, 2 Gy) vs. high dose (4 Gy, 8 Gy), and high risk (8 Gy) vs. low risk (1 Gy, 2 Gy, 4 Gy). Mice were exposed to whole-body doses of 0 Gy, 1 Gy, 2 Gy, 4 Gy, or 8 Gy of X rays. MiRNA expression changes were identified using NanoString nCounter panels on blood RNA collected 1, 2, 3 or 7 days postirradiation. Overall, C3H/HeJ mice had more differentially expressed miRNAs across all doses and timepoints than BALB/c mice. The highest amount of differential expression occurred at days 2 and 3 postirradiation for both strains. Comparison of C3H/HeJ and BALB/c expression profiles to those previously identified in C57BL/6 mice revealed 12 miRNAs that were commonly expressed across all three strains, only one of which, miR-340-5p, displayed a consistent regulation pattern in all three miRNA data. Notably multiple Let-7 family members predicted high-dose and high-risk radiation exposure (Let-7a, Let-7f, Let-7e, Let-7g, and Let-7d). KEGG pathway analysis demonstrated involvement of these predicted miRNAs in pathways related to: Fatty acid metabolism, Lysine degradation and FoxO signaling. These findings indicate differences in the miRNA response to radiation across various genetic backgrounds, and highlights key similarities, which we exploited to discover miRNAs that predict radiation exposure. Our study demonstrates the need and the utility of including multiple animal strains in developing and validating biodosimetry diagnostic signatures. From this data, we developed highly accurate miRNA signatures capable of predicting exposed and unexposed subjects within a genetically heterogeneous population as quickly as 24 h of exposure to radiation.

Glioblastoma survival is associated with distinct proteomic alteration signatures post chemoirradiation in a large-scale proteomic panel.

Background: Glioblastomas (GBM) are rapidly progressive, nearly uniformly fatal brain tumors. Proteomic analysis represents an opportunity for noninvasive GBM classification and biological understanding of treatment response. Purpose: We analyzed differential proteomic expression pre vs. post completion of concurrent chemoirradiation (CRT) in patient serum samples to explore proteomic alterations and classify GBM by integrating clinical and proteomic parameters. Materials and methods: 82 patients with GBM were clinically annotated and serum samples obtained pre- and post-CRT. Serum samples were then screened using the aptamer-based SOMAScan® proteomic assay. Significant traits from uni- and multivariate Cox models for overall survival (OS) were designated independent prognostic factors and principal component analysis (PCA) was carried out. Differential expression of protein signals was calculated using paired t-tests, with KOBAS used to identify associated KEGG pathways. GSEA pre-ranked analysis was employed on the overall list of differentially expressed proteins (DEPs) against the MSigDB Hallmark, GO Biological Process, and Reactome databases with weighted gene correlation network analysis (WGCNA) and Enrichr used to validate pathway hits internally. Results: 3 clinical clusters of patients with differential survival were identified. 389 significantly DEPs pre vs. post-treatment were identified, including 284 upregulated and 105 downregulated, representing several pathways relevant to cancer metabolism and progression. The lowest survival group (median OS 13.2 months) was associated with DEPs affiliated with proliferative pathways and exhibiting distinct oppositional response including with respect to radiation therapy related pathways, as compared to better-performing groups (intermediate, median OS 22.4 months; highest, median OS 28.7 months). Opposite signaling patterns across multiple analyses in several pathways (notably fatty acid metabolism, NOTCH, TNFα via NF-κB, Myc target V1 signaling, UV response, unfolded protein response, peroxisome, and interferon response) were distinct between clinical survival groups and supported by WGCNA. 23 proteins were statistically signficant for OS with 5 (NETO2, CST7, SEMA6D, CBLN4, NPS) supported by KM. Conclusion: Distinct proteomic alterations with hallmarks of cancer, including progression, resistance, stemness, and invasion, were identified in serum samples obtained from GBM patients pre vs. post CRT and corresponded with clinical survival. The proteome can potentially be employed for glioma classification and biological interrogation of cancer pathways.

Revisiting Concurrent Radiation Therapy, Temozolomide, and the Histone Deacetylase Inhibitor Valproic Acid for Patients with Glioblastoma-Proteomic Alteration and Comparison Analysis with the Standard-of-Care Chemoirradiation.

BACKGROUND: Glioblastoma (GBM) is the most common brain tumor with an overall survival (OS) of less than 30% at two years. Valproic acid (VPA) demonstrated survival benefits documented in retrospective and prospective trials, when used in combination with chemo-radiotherapy (CRT). PURPOSE: The primary goal of this study was to examine if the differential alteration in proteomic expression pre vs. post-completion of concurrent chemoirradiation (CRT) is present with the addition of VPA as compared to standard-of-care CRT. The second goal was to explore the associations between the proteomic alterations in response to VPA/RT/TMZ correlated to patient outcomes. The third goal was to use the proteomic profile to determine the mechanism of action of VPA in this setting. MATERIALS AND METHODS: Serum obtained pre- and post-CRT was analyzed using an aptamer-based SOMAScan® proteomic assay. Twenty-nine patients received CRT plus VPA, and 53 patients received CRT alone. Clinical data were obtained via a database and chart review. Tests for differences in protein expression changes between radiation therapy (RT) with or without VPA were conducted for individual proteins using two-sided t-tests, considering p-values of <0.05 as significant. Adjustment for age, sex, and other clinical covariates and hierarchical clustering of significant differentially expressed proteins was carried out, and Gene Set Enrichment analyses were performed using the Hallmark gene sets. Univariate Cox proportional hazards models were used to test the individual protein expression changes for an association with survival. The lasso Cox regression method and 10-fold cross-validation were employed to test the combinations of expression changes of proteins that could predict survival. Predictiveness curves were plotted for significant proteins for VPA response (p-value < 0.005) to show the survival probability vs. the protein expression percentiles. RESULTS: A total of 124 proteins were identified pre- vs. post-CRT that were differentially expressed between the cohorts who received CRT plus VPA and those who received CRT alone. Clinical factors did not confound the results, and distinct proteomic clustering in the VPA-treated population was identified. Time-dependent ROC curves for OS and PFS for landmark times of 20 months and 6 months, respectively, revealed AUC of 0.531, 0.756, 0.774 for OS and 0.535, 0.723, 0.806 for PFS for protein expression, clinical factors, and the combination of protein expression and clinical factors, respectively, indicating that the proteome can provide additional survival risk discrimination to that already provided by the standard clinical factors with a greater impact on PFS. Several proteins of interest were identified. Alterations in GALNT14 (increased) and CCL17 (decreased) (p = 0.003 and 0.003, respectively, FDR 0.198 for both) were associated with an improvement in both OS and PFS. The pre-CRT protein expression revealed 480 proteins predictive for OS and 212 for PFS (p < 0.05), of which 112 overlapped between OS and PFS. However, FDR-adjusted p values were high, with OS (the smallest p value of 0.586) and PFS (the smallest p value of 0.998). The protein PLCD3 had the lowest p-value (p = 0.002 and 0.0004 for OS and PFS, respectively), and its elevation prior to CRT predicted superior OS and PFS with VPA administration. Cancer hallmark genesets associated with proteomic alteration observed with the administration of VPA aligned with known signal transduction pathways of this agent in malignancy and non-malignancy settings, and GBM signaling, and included epithelial-mesenchymal transition, hedgehog signaling, Il6/JAK/STAT3, coagulation, NOTCH, apical junction, xenobiotic metabolism, and complement signaling. CONCLUSIONS: Differential alteration in proteomic expression pre- vs. post-completion of concurrent chemoirradiation (CRT) is present with the addition of VPA. Using pre- vs. post-data, prognostic proteins emerged in the analysis. Using pre-CRT data, potentially predictive proteins were identified. The protein signals and hallmark gene sets associated with the alteration in the proteome identified between patients who received VPA and those who did not, align with known biological mechanisms of action of VPA and may allow for the identification of novel biomarkers associated with outcomes that can help advance the study of VPA in future prospective trials.

Immune signature of pheochromocytoma and paraganglioma in context of neuroendocrine neoplasms associated with prognosis.

PURPOSE: To understand prognostic immune cell infiltration signatures in neuroendocrine neoplasms (NENs), particularly pheochromocytoma and paraganglioma (PCPG), we analyzed tumor transcriptomic data from The Cancer Genome Atlas (TCGA) and other published tumor transcriptomic data of NENs. METHODS: We used CIBERSORT to infer immune cell infiltrations from bulk tumor transcriptomic data from PCPGs, in comparison to gastroenteropancreatic neuroendocrine tumors (GEPNETs) and small cell lung carcinomas (SCLCs). PCPG immune signature was validated with NanoString immune panel in an independent cohort. Unsupervised clustering of the immune infiltration scores from CIBERSORT was used to find immune clusters. A prognostic immune score model for PCPGs and the other NENs were calculated as a linear combination of the estimated infiltration of activated CD8+/CD4+ T cells, activated NK cells, and M0 and M2 macrophages. RESULTS: In PCPGs, we found five dominant immune clusters, associated with M2 macrophages, monocytes, activated NK cells, M0 macrophages and regulatory T cells, and CD8+/CD4+ T cells respectively. Non-metastatic tumors were associated with activated NK cells and metastatic tumors were associated with M0 macrophages and regulatory T cells. In GEPNETs and SCLCs, M0 macrophages and regulatory T cells were associated with unfavorable outcomes and features, such as metastasis and high-grade tumors. The prognostic immune score model for PCPGs and the NENs could predict non-aggressive and non-metastatic diseases. In PCPGs, the immune score was also an independent predictor of metastasis-free survival in a multivariate Cox regression analysis. CONCLUSION: The transcriptomic immune signature in PCPG correlates with clinical features like metastasis and prognosis.

Radiogenomic profiling of prostate tumors prior to external beam radiotherapy converges on a transcriptomic signature of TGF-ß activity driving tumor recurrence.

Background: Patients with localized prostate cancer have historically been assigned to clinical risk groups based on local disease extent, serum prostate specific antigen (PSA), and tumor grade. Clinical risk grouping is used to determine the intensity of treatment with external beam radiotherapy (EBRT) and androgen deprivation therapy (ADT), yet a substantial proportion of patients with intermediate and high risk localized prostate cancer will develop biochemical recurrence (BCR) and require salvage therapy. Prospective identification of patients destined to experience BCR would allow treatment intensification or selection of alternative therapeutic strategies. Methods: Twenty-nine individuals with intermediate or high risk prostate cancer were prospectively recruited to a clinical trial designed to profile the molecular and imaging features of prostate cancer in patients undergoing EBRT and ADT. Whole transcriptome cDNA microarray and whole exome sequencing were performed on pretreatment targeted biopsy of prostate tumors (n=60). All patients underwent pretreatment and 6-month post EBRT multiparametric MRI (mpMRI), and were followed with serial PSA to assess presence or absence of BCR. Genes differentially expressed in the tumor of patients with and without BCR were investigated using pathways analysis tools and were similarly explored in alternative datasets. Differential gene expression and predicted pathway activation were evaluated in relation to tumor response on mpMRI and tumor genomic profile. A novel TGF-ß gene signature was developed in the discovery dataset and applied to a validation dataset. Findings: Baseline MRI lesion volume and PTEN/TP53 status in prostate tumor biopsies correlated with the activation state of TGF-ß signaling measured using pathway analysis. All three measures correlated with the risk of BCR after definitive RT. A prostate cancer-specific TGF-ß signature discriminated between patients that experienced BCR vs. those that did not. The signature retained prognostic utility in an independent cohort. Interpretation: TGF-ß activity is a dominant feature of intermediate-to-unfavorable risk prostate tumors prone to biochemical failure after EBRT with ADT. TGF-ß activity may serve as a prognostic biomarker independent of existing risk factors and clinical decision-making criteria. Funding: This research was supported by the Prostate Cancer Foundation, the Department of Defense Congressionally Directed Medical Research Program, National Cancer Institute, and the Intramural Research Program of the NIH, National Cancer Institute, Center for Cancer Research.

Identification of a de novo mutation in TLK1 associated with a neurodevelopmental disorder and immunodeficiency.

Background: The Tousled-like kinases 1 and 2 (TLK1/TLK2) regulate DNA replication, repair and chromatin maintenance. TLK2 variants are associated with 'Intellectual Disability, Autosomal Dominant 57' (MRD57), a neurodevelopmental disorder (NDD) characterized by intellectual disability (ID), autism spectrum disorder (ASD) and microcephaly. Several TLK1 variants have been reported in NDDs but their functional significance is unknown. Methods: A male patient presenting with ID, seizures, global developmental delay, hypothyroidism, and primary immunodeficiency was determined to have a novel, heterozygous variant in TLK1 (c.1435C>G, p.Q479E) by genome sequencing (GS). Single cell gel electrophoresis, western blot, flow cytometry and RNA-seq were performed in patient-derived lymphoblast cell lines. In silico, biochemical and proteomic analysis were used to determine the functional impact of the p.Q479E variant and previously reported NDD-associated TLK1 variant, p.M566T. Results: Transcriptome sequencing in patient-derived cells confirmed expression of TLK1 transcripts carrying the p.Q479E variant and revealed alterations in genes involved in class switch recombination and cytokine signaling. Cells expressing the p.Q479E variant exhibited reduced cytokine responses and higher levels of spontaneous DNA damage but not increased sensitivity to radiation or DNA repair defects. The p.Q479E and p.M566T variants impaired kinase activity but did not strongly alter localization or proximal protein interactions. Conclusion: Our study provides the first functional characterization of TLK1 variants associated with NDDs and suggests potential involvement in central nervous system and immune system development. Our results indicate that, like TLK2 variants, TLK1 variants may impact development in multiple tissues and should be considered in the diagnosis of rare NDDs.

Molecular profiling indicates orthotopic xenograft of glioma cell lines simulate a subclass of human glioblastoma.

Cell line models have been widely used to investigate glioblastoma multiforme (GBM) pathobiology and in the development of targeted therapies. However, GBM tumours are molecularly heterogeneous and how cell lines can best model that diversity is unknown. In this report, we investigated gene expression profiles of three preclinical growth models of glioma cell lines, in vitro and in vivo as subcutaneous and intracerebral xenografts to examine which cell line model most resembles the clinical samples. Whole genome DNA microarrays were used to profile gene expression in a collection of 25 high-grade glioblastomas, and comparisons were made to profiles of cell lines under three different growth models. Hierarchical clustering revealed three molecular subtypes of the glioblastoma patient samples. Supervised learning algorithm, trained on glioma subtypes predicted the intracerebral cell line model with one glioma subtype (r = 0.68; 95% bootstrap CI -0.41, 0.46). Survival analysis of enriched gene sets (P < 0.05) revealed 19 biological categories (146 genes) belonging to neuronal, signal transduction, apoptosis- and glutamate-mediated neurotransmitter activation signals that are associated with poor prognosis in this glioma subclass. We validated the expression profiles of these gene categories in an independent cohort of patients from 'The Cancer Genome Atlas' project (r = 0.62, 95% bootstrap CI: -0.42, 0.43). We then used these data to select and inhibit a novel target (glutamate receptor) and showed that LY341595, a glutamate receptor specific antagonist, could prolong survival in intracerebral tumour-implanted mice in combination with irradiation, providing an in vivo cell line system of preclinical studies.

Predicting drug sensitivity and resistance: profiling ABC transporter genes in cancer cells.

For analysis of multidrug resistance, a major barrier to effective cancer chemotherapy, we profiled mRNA expression of the 48 known human ABC transporters in 60 diverse cancer cell lines (the NCI-60) used by the National Cancer Institute to screen for anticancer activity. The use of real-time RT-PCR avoided artifacts commonly encountered with microarray technologies. By correlating the results with the growth inhibitory profiles of 1,429 candidate anticancer drugs tested against the cells, we identified which transporters are more likely than others to confer resistance to which agents. Unexpectedly, we also found and validated compounds whose activity is potentiated, rather than antagonized, by the MDR1 multidrug transporter. Such compounds may serve as leads for development.

Analytical Considerations of Large-Scale Aptamer-Based Datasets for Translational Applications.

The development and advancement of aptamer technology has opened a new realm of possibilities for unlocking the biocomplexity available within proteomics. With ultra-high-throughput and multiplexing, alongside remarkable specificity and sensitivity, aptamers could represent a powerful tool in disease-specific research, such as supporting the discovery and validation of clinically relevant biomarkers. One of the fundamental challenges underlying past and current proteomic technology has been the difficulty of translating proteomic datasets into standards of practice. Aptamers provide the capacity to generate single panels that span over 7000 different proteins from a singular sample. However, as a recent technology, they also present unique challenges, as the field of translational aptamer-based proteomics still lacks a standardizing methodology for analyzing these large datasets and the novel considerations that must be made in response to the differentiation amongst current proteomic platforms and aptamers. We address these analytical considerations with respect to surveying initial data, deploying proper statistical methodologies to identify differential protein expressions, and applying datasets to discover multimarker and pathway-level findings. Additionally, we present aptamer datasets within the multi-omics landscape by exploring the intersectionality of aptamer-based proteomics amongst genomics, transcriptomics, and metabolomics, alongside pre-existing proteomic platforms. Understanding the broader applications of aptamer datasets will substantially enhance current efforts to generate translatable findings for the clinic.