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Genetic heterogeneity in tumors can show a remarkable selectivity when two or more independent genetic events occur in the same gene. This phenomenon, called composite mutation, points toward a selective pressure, which frequently causes therapy resistance to mutation-specific drugs. Since composite mutations have been described to occur in sub-clonal populations, they are not always captured through biopsy sampling. Here, we provide a proof of concept to predict composite mutations to anticipate which patients might be at risk for sub-clonally driven therapy resistance. We found that composite mutations occur in 5% of cancer patients, mostly affecting the PIK3CA, EGFR, BRAF, and KRAS genes, which are common precision medicine targets. Furthermore, we found a strong and significant relationship between the frequencies of composite mutations with commonly co-occurring mutations in a non-composite context. We also found that co-mutations are significantly enriched on the same chromosome. These observations were independently confirmed using cell line data. Finally, we show the feasibility of predicting compositive mutations based on their co-mutations (AUC 0.62, 0.81, 0.82, and 0.91 for EGFR, PIK3CA, KRAS, and BRAF, respectively). This prediction model could help to stratify patients who are at risk of developing therapy resistance-causing mutations., (© 2024 The Authors. Molecular Oncology published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.)

Introduction: Glioblastoma is the most common aggressive primary central nervous system cancer in adults characterised by uniformly poor survival. Despite maximal safe resection and postoperative radiotherapy with concurrent and adjuvant temozolomide-based chemotherapy, tumours inevitably recur. Imaging with O-(2-[ 18 F]-fluoroethyl)-L-tyrosine (FET) positron emission tomography (PET) has the potential to impact adjuvant radiotherapy (RT) planning, distinguish between treatment-induced pseudoprogression versus tumour progression as well as prognostication., Methods and Analysis: The FET-PET in Glioblastoma (FIG) study is a prospective, multicentre, non-randomised, phase II study across 10 Australian sites and will enrol up to 210 adults aged ≥18 years with newly diagnosed glioblastoma. FET-PET will be performed at up to three time points: (1) following initial surgery and prior to commencement of chemoradiation (FET-PET1); (2) 4 weeks following concurrent chemoradiation (FET-PET2); and (3) within 14 days of suspected clinical and/or radiological progression on MRI (performed at the time of clinical suspicion of tumour recurrence) (FET-PET3). The co-primary outcomes are: (1) to investigate how FET-PET versus standard MRI impacts RT volume delineation and (2) to determine the accuracy and management impact of FET-PET in distinguishing pseudoprogression from true tumour progression. The secondary outcomes are: (1) to investigate the relationships between FET-PET parameters (including dynamic uptake, tumour to background ratio, metabolic tumour volume) and progression-free survival and overall survival; (2) to assess the change in blood and tissue biomarkers determined by serum assay when comparing FET-PET data acquired prior to chemoradiation with other prognostic markers, looking at the relationships of FET-PET versus MRI-determined site/s of progressive disease post chemotherapy treatment with MRI and FET-PET imaging; and (3) to estimate the health economic impact of incorporating FET-PET into glioblastoma management and in the assessment of post-treatment pseudoprogression or recurrence/true progression. Exploratory outcomes include the correlation of multimodal imaging, blood and tumour biomarker analyses with patterns of failure and survival., Ethics and Dissemination: The study protocol V.2.0 dated 20 November 2020 has been approved by a lead Human Research Ethics Committee (Austin Health, Victoria). Other clinical sites will provide oversight through local governance processes, including obtaining informed consent from suitable participants. The study will be conducted in accordance with the principles of the Declaration of Helsinki and Good Clinical Practice. Results of the FIG study (TROG 18.06) will be disseminated via relevant scientific and consumer forums and peer-reviewed publications., Trial Registration Number: ANZCTR ACTRN12619001735145., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

BACKGROUNDImmune cell profiling of primary and metastatic CNS tumors has been focused on the tumor, not the tumor microenvironment (TME), or has been analyzed via biopsies.METHODSEn bloc resections of gliomas (n = 10) and lung metastases (n = 10) were analyzed via tissue segmentation and high-dimension Opal 7-color multiplex imaging. Single-cell RNA analyses were used to infer immune cell functionality.RESULTSWithin gliomas, T cells were localized in the infiltrating edge and perivascular space of tumors, while residing mostly in the stroma of metastatic tumors. CD163+ macrophages were evident throughout the TME of metastatic tumors, whereas in gliomas, CD68+, CD11c+CD68+, and CD11c+CD68+CD163+ cell subtypes were commonly observed. In lung metastases, T cells interacted with CD163+ macrophages as dyads and clusters at the brain-tumor interface and within the tumor itself and as clusters within the necrotic core. In contrast, gliomas typically lacked dyad and cluster interactions, except for T cell CD68+ cell dyads within the tumor. Analysis of transcriptomic data in glioblastomas revealed that innate immune cells expressed both proinflammatory and immunosuppressive gene signatures.CONCLUSIONOur results show that immunosuppressive macrophages are abundant within the TME and that the immune cell interactome between cancer lineages is distinct. Further, these data provide information for evaluating the role of different immune cell populations in brain tumor growth and therapeutic responses.FUNDINGThis study was supported by the NIH (NS120547), a Developmental research project award (P50CA221747), ReMission Alliance, institutional funding from Northwestern University and the Lurie Comprehensive Cancer Center, and gifts from the Mosky family and Perry McKay. Performed in the Flow Cytometry & Cellular Imaging Core Facility at MD Anderson Cancer Center, this study received support in part from the NIH (CA016672) and the National Cancer Institute (NCI) Research Specialist award 1 (R50 CA243707). Additional support was provided by CCSG Bioinformatics Shared Resource 5 (P30 CA046592), a gift from Agilent Technologies, a Research Scholar Grant from the American Cancer Society (RSG-16-005-01), a Precision Health Investigator Award from University of Michigan (U-M) Precision Health, the NCI (R37-CA214955), startup institutional research funds from U-M, and a Biomedical Informatics & Data Science Training Grant (T32GM141746).

Introduction: Grades 2 and 3 gliomas (G2/3 gliomas), when combined, are the second largest group of malignant brain tumours in adults. The outcomes for G2/3 gliomas at progression approach the dismal outcomes for glioblastoma (GBM), yet there is a paucity of trials for Australian patients with relapsed G2/3 gliomas compared with patients with GBM. LUMOS will be a pilot umbrella study for patients with relapsed G2/3 gliomas that aims to match patients to targeted therapies based on molecular screening with contemporaneous tumour tissue. Participants in whom no actionable or no druggable mutation is found, or in whom the matching drug is not available, will form a comparator arm and receive standard of care chemotherapy. The objective of the LUMOS trial is to assess the feasibility of this approach in a multicentre study across five sites in Australia, with a view to establishing a national molecular screening platform for patient treatment guided by the mutational analysis of contemporaneous tissue biopsies METHODS AND ANALYSIS: This study will be a multicentre pilot study enrolling patients with recurrent grade 2/3 gliomas that have previously been treated with radiotherapy and chemotherapy at diagnosis or at first relapse. Contemporaneous tumour tissue at the time of first relapse, defined as tissue obtained within 6 months of relapse and without subsequent intervening therapy, will be obtained from patients. Molecular screening will be performed by targeted next-generation sequencing at the reference laboratory (PathWest, Perth, Australia). RNA and DNA will be extracted from representative formalin-fixed paraffin embedded tissue scrolls or microdissected from sections on glass slides tissue sections following a review of the histology by pathologists. Extracted nucleic acid will be quantified by Qubit Fluorometric Quantitation (Thermo Fisher Scientific). Library preparation and targeted capture will be performed using the TruSight Tumor 170 (TST170) kit and samples sequenced on NextSeq 550 (Illumina) using NextSeq V.2.5 hi output reagents, according to the manufacturer's instructions. Data analysis will be performed using the Illumina BaseSpace TST170 app v1.02 and a custom tertiary pipeline, implemented within the Clinical Genomics Workspace software platform from PierianDx (also refer to section 3.2). Primary outcomes for the study will be the number of patients enrolled and the number of patients who complete molecular screening. Secondary outcomes will include the proportion of screened patients enrolled; proportion of patients who complete molecular screening; the turn-around time of molecular screening; and the value of a brain tumour specific multi-disciplinary tumour board, called the molecular tumour advisory panel as measured by the proportion of patients in whom the treatment recommendation was refined compared with the recommendations from the automated bioinformatics platform of the reference laboratory testing., Ethics and Dissemination: The study was approved by the lead Human Research Ethics Committee of the Sydney Local Health District: Protocol No. X19-0383. The study will be conducted in accordance with the principles of the Declaration of Helsinki 2013, guidelines for Good Clinical Practice and the National Health and Medical Research Council National Statement on Ethical Conduct in Human Research (2007, updated 2018 and as amended periodically). Results will be disseminated using a range of media channels including newsletters, social media, scientific conferences and peer-reviewed publications., Trial Registration Number: ACTRN12620000087954; Pre-results., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Despite considerable efforts, the mechanisms linking genomic alterations to the transcriptional identity of cancer cells remain elusive. Integrative genomic analysis, using a network-based approach, identified 407 master regulator (MR) proteins responsible for canalizing the genetics of individual samples from 20 cohorts in The Cancer Genome Atlas (TCGA) into 112 transcriptionally distinct tumor subtypes. MR proteins could be further organized into 24 pan-cancer, master regulator block modules (MRBs), each regulating key cancer hallmarks and predictive of patient outcome in multiple cohorts. Of all somatic alterations detected in each individual sample, >50% were predicted to induce aberrant MR activity, yielding insight into mechanisms linking tumor genetics and transcriptional identity and establishing non-oncogene dependencies. Genetic and pharmacological validation assays confirmed the predicted effect of upstream mutations and MR activity on downstream cellular identity and phenotype. Thus, co-analysis of mutational and gene expression profiles identified elusive subtypes and provided testable hypothesis for mechanisms mediating the effect of genetic alterations., Competing Interests: Declaration of interests A.C. is founder, equity holder, consultant, and director of DarwinHealth Inc., a company that has licensed some of the algorithms used in this manuscript from Columbia University. M.J.A. is Chief Scientific Officer and equity holder at DarwinHealth, Inc. Patent 10,790,040, titled “Virtual Inference of Protein Activity by Regulon Analysis” has issued on Sept. 29, 2020 related to the VIPER method. Columbia University is also an equity holder in DarwinHealth Inc., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Glioblastoma represents the most common primary malignancy of the central nervous system in adults and remains a largely incurable disease. The elucidation of disease subtypes based on mutational profiling, gene expression and DNA methylation has so far failed to translate into improved clinical outcomes. However, new knowledge emerging from the subtyping effort in the IDH-wild-type setting may provide directions for future precision therapies. Here, we review recent learnings in the field, and further consider how tumour microenvironment differences across subtypes may reveal novel contexts of vulnerability. We discuss recent treatment approaches and ongoing trials in the IDH-wild-type glioblastoma setting, and propose an integrated discovery stratagem incorporating multi-omics, single-cell technologies and computational approaches., Competing Interests: Disclosure AI reports grants and travel funding from Carthera, research grants from Transgene, Sanofi, Air Liquide and Nutritheragene travel funding from Leo Pharma, grants from outside the submitted work. All remaining authors have declared no conflicts of interest., (Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Glioblastoma (GBM) is the most common primary malignant brain tumor in adulthood. Despite multimodality treatments, including maximal safe resection followed by irradiation and chemotherapy, the median overall survival times range from 14 to 16 months. However, a small subset of GBM patients live beyond 5 years and are thus considered long-term survivors., Methods: A retrospective analysis of the clinical, radiographic, and molecular features of patients with newly diagnosed primary GBM who underwent treatment at The University of Texas MD Anderson Cancer Center was conducted. Eighty patients had sufficient quantity and quality of tissue available for next-generation sequencing and immunohistochemical analysis. Factors associated with survival time were identified using proportional odds ordinal regression. We constructed a survival-predictive nomogram using a forward stepwise model that we subsequently validated using The Cancer Genome Atlas., Results: Univariate analysis revealed 3 pivotal genetic alterations associated with GBM survival: both high tumor mutational burden ( P = .0055) and PTEN mutations ( P = .0235) negatively impacted survival, whereas IDH1 mutations positively impacted survival ( P < .0001). Clinical factors significantly associated with GBM survival included age ( P < .0001), preoperative Karnofsky Performance Scale score ( P = .0001), sex ( P = .0164), and clinical trial participation ( P < .0001). Higher preoperative T1-enhancing volume ( P = .0497) was associated with shorter survival. The ratio of TI-enhancing to nonenhancing disease (T1/T2 ratio) also significantly impacted survival ( P = .0022)., Conclusions: Our newly devised long-term survival - predictive nomogram based on clinical and genomic data can be used to advise patients regarding their potential outcomes and account for confounding factors in nonrandomized clinical trials., (© The Author(s) 2020. Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology.)

Personalized cancer treatments using combinations of drugs with a synergistic effect is attractive but proves to be highly challenging. Here we present an approach to uncover the efficacy of drug combinations based on the analysis of mono-drug effects. For this we used dose-response data from pharmacogenomic encyclopedias and represent these as a drug atlas. The drug atlas represents the relations between drug effects and allows to identify independent processes for which the tumor might be particularly vulnerable when attacked by two drugs. Our approach enables the prediction of combination-therapy which can be linked to tumor-driving mutations. By using this strategy, we can uncover potential effective drug combinations on a pan-cancer scale. Predicted synergies are provided and have been validated in glioblastoma, breast cancer, melanoma and leukemia mouse-models, resulting in therapeutic synergy in 75% of the tested models. This indicates that we can accurately predict effective drug combinations with translational value.

Despite advances in therapy, glioblastoma remains an incurable disease with a dismal prognosis. Recent studies have implicated cancer stem cells within glioblastoma (glioma stem cells, GSCs) as mediators of therapeutic resistance and tumor progression. In this study, we investigated the role of the transforming growth factor-β (TGF-β) superfamily, which has been found to play an integral role in the maintenance of stem cell homeostasis within multiple stem cell systems, as a mediator of stem-like cells in glioblastoma. We find that BMP and TGF-β signaling define divergent molecular and functional identities in glioblastoma, and mark relatively quiescent and proliferative GSCs, respectively. Treatment of GSCs with BMP inhibits cell proliferation, but does not abrogate their stem-ness, as measured by self-renewal and tumorigencity. Further, BMP pathway activation confers relative resistance to radiation and temozolomide chemotherapy. Our findings define a quiescent cancer stem cell population in glioblastoma that may be a cellular reservoir for tumor recurrence following cytotoxic therapy.

Glioblastoma is highly enriched with macrophages, and osteopontin (OPN) expression levels correlate with glioma grade and the degree of macrophage infiltration; thus, we studied whether OPN plays a crucial role in immune modulation. Quantitative PCR, immunoblotting, and ELISA were used to determine OPN expression. Knockdown of OPN was achieved using complementary siRNA, shRNA, and CRISPR/Cas9 techniques, followed by a series of in vitro functional migration and immunological assays. OPN gene-deficient mice were used to examine the roles of non-tumor-derived OPN on survival of mice harboring intracranial gliomas. Patients with mesenchymal glioblastoma multiforme (GBM) show high OPN expression, a negative survival prognosticator. OPN is a potent chemokine for macrophages, and its blockade significantly impaired the ability of glioma cells to recruit macrophages. Integrin αvβ5 (ITGαvβ5) is highly expressed on glioblastoma-infiltrating macrophages and constitutes a major OPN receptor. OPN maintains the M2 macrophage gene signature and phenotype. Both tumor-derived and host-derived OPN were critical for glioma development. OPN deficiency in either innate immune or glioma cells resulted in a marked reduction in M2 macrophages and elevated T cell effector activity infiltrating the glioma. Furthermore, OPN deficiency in the glioma cells sensitized them to direct CD8+ T cell cytotoxicity. Systemic administration in mice of 4-1BB-OPN bispecific aptamers was efficacious, increasing median survival time by 68% (P < 0.05). OPN is thus an important chemokine for recruiting macrophages to glioblastoma, mediates crosstalk between tumor cells and the innate immune system, and has the potential to be exploited as a therapeutic target.

Background: Glioblastoma, the most aggressive primary brain tumor, is genetically heterogeneous. Alternative splicing (AS) plays a key role in numerous pathologies, including cancer. The objectives of our study were to determine whether aberrant AS could play a role in the malignant phenotype of glioma and to understand the mechanism underlying its aberrant regulation., Methods: We obtained surgical samples from patients with glioblastoma who underwent 5-aminolevulinic fluorescence-guided surgery. Biopsies were taken from the tumor center as well as from adjacent normal-appearing tissue. We used a global splicing array to identify candidate genes aberrantly spliced in these glioblastoma samples. Mechanistic and functional studies were performed to elucidate the role of our top candidate splice variant, BAF45d, in glioblastoma., Results: BAF45d is part of the switch/sucrose nonfermentable complex and plays a key role in the development of the CNS. The BAF45d/6A isoform is present in 85% of over 200 glioma samples that have been analyzed and contributes to the malignant glioma phenotype through the maintenance of an undifferentiated cellular state. We demonstrate that BAF45d splicing is mediated by polypyrimidine tract-binding protein 1 (PTBP1) and that BAF45d regulates PTBP1, uncovering a reciprocal interplay between RNA splicing regulation and transcription., Conclusions: Our data indicate that AS is a mechanism that contributes to the malignant phenotype of glioblastoma. Understanding the consequences of this biological process will uncover new therapeutic targets for this devastating disease.

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., Competing Interests: CONFLICTS OF INTEREST John de Groot is consulting/advisory board member for Genentech, Novartis, Celldex, VBL Therapeutics, Celldex, Deciphera Pharmaceuticals and MundiPharma.

Glioblastoma presents as a heterogeneous disease with poor prognosis despite the use of multimodal therapy. Analysis of genomic DNA changes between initial diagnosis and recurrence in response to standard treatment protocols would enhance understanding of disease progression and better inform new treatment strategies. A cohort of 21 patients with primary glioblastoma were examined between diagnosis and first recurrence. This study presented a rare opportunity to characterize molecular alterations in tumors observed in three patients who received no therapeutic intervention, other than surgery, offering a unique control. We focused this study by comparing the dynamic mutation profiles between the primary tumors and their matched recurrent counterparts. Molecular profiling of tumors was performed using multiplexed targeted deep sequencing of 409 well characterized cancer-associated genes, achieving a mean read depth of 1272 x. Three levels of evidence suggested an evolutionary pattern consistent with a response to therapy-mediated selection pressures exists in treated patients: 1) variant burden was reduced in recurrent tumors, 2) neutral evolutionary dynamics apparent in untreated tumors shifted toward a non-neutral mode of evolution in treated patients at recurrence, and 3) the recurrent tumor of one patient displayed an increased mutation rate attributable to a temozolomide-associated hypermutator phenotype. Our observations suggest that current treatment modalities are likely to fail in achieving long term remission with the majority of relapse samples containing distinct mutations when compared to primary diagnostic samples., Competing Interests: CONFLICTS OF INTEREST The authors declare no potential conflicts of interest.

Malignant glioma is an often fatal type of cancer. Aberrant activation of STAT3 leads to glioma tumorigenesis. STAT3-induced transcription of protein-coding genes has been extensively studied; however, little is known about STAT3-regulated miRNA gene transcription in glioma tumorigenesis. In this study, we found that abnormal activation or decreased expression of STAT3 promotes or inhibits the expression of miR-182-5p, respectively. Bioinformatics analyses determined that tumor suppressor protocadherin-8 (PCDH8) is a candidate target gene of miR-182-5p. miR-182-5p negatively regulated PCDH8 expression by directly targeting its 3'-untranslated region. PCDH8 knockdown induced the proliferative and invasive capacities of glioma cells. Silencing of PCDH8 or miR-182-5p mimics could reverse the inhibitory effect of WP1066, a STAT3 inhibitor, or STAT3 knockdown in vitro and in vivo on glioma progression. Clinically, expression levels of PCDH8 were inversely correlated with those of p-STAT3 or miR-182-5p in glioblastoma tissues. These findings reveal that the STAT3/miR-182-5p/PCDH8 axis has a critical role in glioma tumorigenesis and that targeting the axis may provide a new therapeutic approach for human glioma. Cancer Res; 76(14); 4293-304. ©2016 AACR., Competing Interests: of Potential Conflicts of Interest: No potential conflicts of interest were disclosed., (©2016 American Association for Cancer Research.)

Glioblastoma (GBM) represents a compelling disease for kinase inhibitor therapy because most of these tumors harbor genetic alterations that result in aberrant activation of growth factor-signaling pathways. The PI3K/mammalian target of the rapamycin (mTOR) pathway is dysregulated in over 50% of human GBM but remains a challenging clinical target. Inhibitors against PI3K/mTOR mediators have limited clinical efficacy as single agents. We investigated potential bypass mechanisms to PI3K/mTOR inhibition using gene expression profiling before and after PI3K inhibitor treatment by Affymetrix microarrays. Mitogen- and stress-activated protein kinase 1 (MSK1) was markedly induced after PI3K/mTOR inhibitor treatment and disruption of MSK1 by specific shRNAs attenuated resistance to PI3K/mTOR inhibitors in glioma-initiating cells (GIC). Further investigation showed that MSK1 phosphorylates β-catenin and regulates its nuclear translocation and transcriptional activity. The depletion of β-catenin potentiated PI3K/mTOR inhibitor-induced cytotoxicity and the inhibition of MSK1 synergized with PI3K/mTOR inhibitors to extend survival in an intracranial animal model and decreased phosphorylation of β-catenin at Ser(552) These observations suggest that MSK1/β-catenin signaling serves as an escape survival signal upon PI3K/mTOR inhibition and provides a strong rationale for the combined use of PI3K/mTOR and MSK1/β-catenin inhibition to induce lethal growth inhibition in human GBM. Mol Cancer Ther; 15(7); 1656-68. ©2016 AACR., (©2016 American Association for Cancer Research.)

Adrenocortical carcinoma is a rare malignancy with poor prognosis and limited response to chemotherapy. Hepatocyte growth factor (HGF) and its receptor cMET augment cancer growth and resistance to chemotherapy, but their role in adrenocortical carcinoma has not been examined. In this study, we investigated the association between HGF/cMET expression and cancer hallmarks of adrenocortical carcinoma. Transcriptomic and immunohistochemical analyses indicated that increased HGF/cMET expression in human adrenocortical carcinoma samples was positively associated with cancer-related biologic processes, including proliferation and angiogenesis, and negatively correlated with apoptosis. Accordingly, treatment of adrenocortical carcinoma cells with exogenous HGF resulted in increased cell proliferation in vitro and in vivo while short hairpin RNA-mediated knockdown or pharmacologic inhibition of cMET suppressed cell proliferation and tumor growth. Moreover, exposure of cells to mitotane, cisplatin, or radiation rapidly induced pro-cMET expression and was associated with an enrichment of genes (e.g., CYP450 family) related to therapy resistance, further implicating cMET in the anticancer drug response. Together, these data suggest an important role for HGF/cMET signaling in adrenocortical carcinoma growth and resistance to commonly used treatments. Targeting cMET, alone or in combination with other drugs, could provide a breakthrough in the management of this aggressive cancer., (©2015 American Association for Cancer Research.)

The National Cancer Institute (NCI) Cancer Imaging Program organized two related workshops on June 26-27, 2013, entitled "Correlating Imaging Phenotypes with Genomics Signatures Research" and "Scalable Computational Resources as Required for Imaging-Genomics Decision Support Systems." The first workshop focused on clinical and scientific requirements, exploring our knowledge of phenotypic characteristics of cancer biological properties to determine whether the field is sufficiently advanced to correlate with imaging phenotypes that underpin genomics and clinical outcomes, and exploring new scientific methods to extract phenotypic features from medical images and relate them to genomics analyses. The second workshop focused on computational methods that explore informatics and computational requirements to extract phenotypic features from medical images and relate them to genomics analyses and improve the accessibility and speed of dissemination of existing NIH resources. These workshops linked clinical and scientific requirements of currently known phenotypic and genotypic cancer biology characteristics with imaging phenotypes that underpin genomics and clinical outcomes. The group generated a set of recommendations to NCI leadership and the research community that encourage and support development of the emerging radiogenomics research field to address short-and longer-term goals in cancer research.

Genomic alterations of the epidermal growth factor receptor (EGFR) gene play a crucial role in pathogenesis of glioblastoma multiforme (GBM). By systematic analysis of GBM genomic data, we have identified and characterized a novel exon 27 deletion mutation occurring within the EGFR carboxyl-terminus domain (CTD), in addition to identifying additional examples of previously reported deletion mutations in this region. We show that the GBM-derived EGFR CTD deletion mutants are able to induce cellular transformation in vitro and in vivo in the absence of ligand and receptor autophosphorylation. Treatment with the EGFR-targeted monoclonal antibody, cetuximab, or the small molecule EGFR inhibitor, erlotinib, effectively impaired tumorigenicity of oncogenic EGFR CTD deletion mutants. Cetuximab in particular prolonged the survival of intracranially xenografted mice with oncogenic EGFR CTD deletion mutants, compared with untreated control mice. Therefore, we propose that erlotinib and, especially, cetuximab treatment may be a promising therapeutic strategy in GBM patients harboring EGFR CTD deletion mutants.

Somatic genetic alterations in cancers have been linked with response to targeted therapeutics by creation of specific dependency on activated oncogenic signaling pathways. However, no tools currently exist to systematically connect such genetic lesions to therapeutic vulnerability. We have therefore developed a genomics approach to identify lesions associated with therapeutically relevant oncogene dependency. Using integrated genomic profiling, we have demonstrated that the genomes of a large panel of human non-small cell lung cancer (NSCLC) cell lines are highly representative of those of primary NSCLC tumors. Using cell-based compound screening coupled with diverse computational approaches to integrate orthogonal genomic and biochemical data sets, we identified molecular and genomic predictors of therapeutic response to clinically relevant compounds. Using this approach, we showed that v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations confer enhanced Hsp90 dependency and validated this finding in mice with KRAS-driven lung adenocarcinoma, as these mice exhibited dramatic tumor regression when treated with an Hsp90 inhibitor. In addition, we found that cells with copy number enhancement of v-abl Abelson murine leukemia viral oncogene homolog 2 (ABL2) and ephrin receptor kinase and v-src sarcoma (Schmidt-Ruppin A-2) viral oncogene homolog (avian) (SRC) kinase family genes were exquisitely sensitive to treatment with the SRC/ABL inhibitor dasatinib, both in vitro and when it xenografted into mice. Thus, genomically annotated cell-line collections may help translate cancer genomics information into clinical practice by defining critical pathway dependencies amenable to therapeutic inhibition.

Although prognostic gene expression signatures for survival in early-stage lung cancer have been proposed, for clinical application, it is critical to establish their performance across different subject populations and in different laboratories. Here we report a large, training-testing, multi-site, blinded validation study to characterize the performance of several prognostic models based on gene expression for 442 lung adenocarcinomas. The hypotheses proposed examined whether microarray measurements of gene expression either alone or combined with basic clinical covariates (stage, age, sex) could be used to predict overall survival in lung cancer subjects. Several models examined produced risk scores that substantially correlated with actual subject outcome. Most methods performed better with clinical data, supporting the combined use of clinical and molecular information when building prognostic models for early-stage lung cancer. This study also provides the largest available set of microarray data with extensive pathological and clinical annotation for lung adenocarcinomas.