Heterogeneous Molecular Features Research Articles

Recent Advances in The Definition of the Molecular Alterations Occurring in Multiple Myeloma.

Multiple myeloma (MM) is a disorder of the monoclonal plasma cells and is the second most common hematologic malignancy. MM initiation and progression are dependent upon complex genomic abnormalities. The current pathogenic model of MM includes two types of primary events, represented by chromosome translocations or chromosome number alterations resulting in hyperdiploidy. These primary molecular events are observed both in MM and in monoclonal gammopathy, its premalignant precursor. Subsequent genetic events allow the progression of monoclonal gammopathy to MM and, together with primary events, contribute to the genetic complexity and heterogeneity of MM. Newer therapies have considerably improved patient outcomes; however, MM remains an incurable disease and most patients experience multiple relapses. The dramatic progresses achieved in the analysis of the heterogeneous molecular features of different MM patients allowed a comprehensive molecular classification of MM and the definition of an individualized prognostic model to predict an individual MM patient's response to different therapeutic options. Despite these progresses, prognostic models fail to identify a significant proportion of patients destined to early relapse. Treatment strategies are increasingly. Based on disease biology, trials are enriched for high-risk MMs, whose careful definition and categorization requires DNA sequencing studies.

Integrated genomic and transcriptomic characterization of neuroendocrine carcinomas for improved treatment decision-making.

e15138 Background: Neuroendocrine carcinomas (NECs) are poorly characterized due to their innate heterogeneity, thus limiting treatment and clinical trial options for patients. Here, we used whole exome sequencing (WES) and RNA sequencing (RNA-seq) to explore the genetic and microenvironmental landscape of NECs in order to understand the unique features of different NEC types, with the aim of improving treatment modalities. Methods: We analyzed 51 NEC clinical samples morphologically verified by a pathologist: lung NEC (20 small cell NEC and 1 large cell NEC cases), gastroenteropancreatic NEC (GEP, 12 cases), cancer of unknown primary (7 cases), Merkel cell carcinoma (MCC, 5 cases), genitourinary tract NEC (3 cases), and breast NEC (3 cases). Findings on tumor mutational burden (TMB, mut/Mb), microsatellite instability (MSI), gene expression signatures, and tumor microenvironment (TME) profiling were reported. Small cell lung cancer (SCLC) subtyping was performed as reported by Gay et al. on the entire NEC cohort. Results: Half of the patients with lung NEC and 84% of those with extrapulmonary NEC satisfied the molecular inclusion criteria for clinical trials, with the most frequent criterion being KRAS G12X or G13X mutations. Among the extrapulmonary NEC samples, 13.7% were deemed eligible for targeted therapy, specifically for cases with BRAF V600E mutation and/or high TMB (> 10 mut/Mb). We detected varying TMB and distinct gene expression features across the entire cohort. Specifically, we found 2 MCC cases to be Merkel cell polyomavirus-positive with low TMB and devoid of UV-associated mutations. One GEP-NEC case exhibited a high MSI (MSI-high) status. We detected 6 SCLC cases (3 non-smokers, 3 former smokers) with surprisingly low levels of tobacco-associated mutations (<10% of all mutations). Two GEP-NEC cases had high levels of mutations associated with tobacco smoking. While TME profiling showed no significant difference in cell population makeup across all samples, transcriptional SCLC subtyping revealed significant differences among the cases. Inflammatory SCLC (SCLC-I) samples showed statistically significant enrichment of all subpopulations of the immune microenvironment (i.e., B cells, T cells, NK cells), supporting the use of immune checkpoint blockade for treatment. The POU2F3+ SCLC (SCLC-P) samples showed low expression of all neuroendocrine diagnostic markers (i.e., INSM1, NCAM1, SYP, CHGA). Conclusions: Given the heterogeneous molecular features across diverse NEC tumors, a uniform treatment strategy is unlikely to benefit all NEC patients. Hence, our ability to detect these unique molecular features is crucial for matching individual NEC patients with specific clinical trials and targeted therapies that may improve their outcomes. Thus, a concerted effort using in-depth genomic, transcriptomic, and TME profiling for NEC tumors is warranted.

Immunohistochemical markers as predictors of prognosis in multifocal prostate cancer.

The impact of tumor focality on prostate cancer (PCa) prognosis has been addressed in several studies with conflicting results. Tumor foci from multifocal (MF) PCa can show highly heterogeneous molecular features. Our aim was to analyze the protein expression of PTEN, SPOP, SLC45A3, ETV1, ERG and the "triple hit" (ERG overexpression, PTEN plus SLC45A3 loss) in unifocal (UF) and MF PCa, to evaluate their value as prognostic markers according to focality, and the role of tumor heterogeneity in MF disease. PTEN, SPOP, SLC45A3, ETV1 and ERG immunohistochemical expression was evaluated in 185 PCa from 9 TMAs, 51 UF and 134 MF. In a subset of 69 MF cases, the dominant and secondary foci (DF and SF) were compared. Heterogeneity was considered when both tumor foci presented different expression patterns. Relationship with clinicopathological features was also analyzed. MF PCa was diagnosed in significantly younger patients when compared to UF ones (p = 0.007). ETV1 overexpression was associated with UF disease (p = 0.028). A shorter time to PSA recurrence was related to SLC45A3 wt expression in UF PCa (p = 0.052), and to SPOP expression loss (p = 0.043) or "triple hit" phenotype in MF PCa (p = 0.041). In MF cases, PTEN loss, SLC45A3 loss and "triple hit" phenotype were associated with the DF and had significant heterogeneity. In conclusion, our results indicate that UF and MF PCa have relevant and consistent molecular differences. The analysis of an immunohistochemical panel, composed by PTEN, SPOP, SLC45A3, ETV1 and ERG, could be useful to predict outcome in MF cases.

Epigenetic targets in B- and T-cell lymphomas: latest developments.

Non-Hodgkin's lymphomas (NHLs) comprise a diverse group of diseases, either of mature B-cell or of T-cell derivation, characterized by heterogeneous molecular features and clinical manifestations. While most of the patients are responsive to standard chemotherapy, immunotherapy, radiation and/or stem cell transplantation, relapsed and/or refractory cases still have a dismal outcome. Deep sequencing analysis have pointed out that epigenetic dysregulations, including mutations in epigenetic enzymes, such as chromatin modifiers and DNA methyltransferases (DNMTs), are prevalent in both B- cell and T-cell lymphomas. Accordingly, over the past decade, a large number of epigenetic-modifying agents have been developed and introduced into the clinical management of these entities, and a few specific inhibitors have already been approved for clinical use. Here we summarize the main epigenetic alterations described in B- and T-NHL, that further supported the clinical development of a selected set of epidrugs in determined diseases, including inhibitors of DNMTs, histone deacetylases (HDACs), and extra-terminal domain proteins (bromodomain and extra-terminal motif; BETs). Finally, we highlight the most promising future directions of research in this area, explaining how bioinformatics approaches can help to identify new epigenetic targets in B- and T-cell lymphoid neoplasms.

Emerging integrated SERS-microfluidic devices for analysis of cancer-derived small extracellular vesicles.

Cancer-derived small extracellular vesicles (sEVs) are specific subgroups of lipid bilayer vesicles secreted from cancer cells to the extracellular environment. They carry distinct biomolecules (e.g., proteins, lipids and nucleic acids) from their parent cancer cells. Therefore, the analysis of cancer-derived sEVs can provide valuable information for cancer diagnosis. However, the use of cancer-derived sEVs in clinics is still limited due to their small size, low amounts in circulating fluids, and heterogeneous molecular features, making their isolation and analysis challenging. Recently, microfluidic technology has gained great attention for its ability to isolate sEVs in minimal volume. In addition, microfluidics allows the isolation and detection of sEVs to be integrated into a single device, offering new opportunities for clinical application. Among various detection techniques, surface-enhanced Raman scattering (SERS) has emerged as a promising candidate for integrating with microfluidic devices due to its ultra-sensitivity, stability, rapid readout, and multiplexing capability. In this tutorial review, we start with the design of microfluidics devices for isolation of sEVs and introduce the key factors to be considered for the design, and then discuss the integration of SERS and microfluidic devices by providing descriptive examples of the currently developed platforms. Lastly, we discuss the current limitations and provide our insights for utilising integrated SERS-microfluidics to isolate and analyse cancer-derived sEVs in clinical settings.

Lipid Alterations in Glioma: A Systematic Review.

Gliomas are highly lethal tumours characterised by heterogeneous molecular features, producing various metabolic phenotypes leading to therapeutic resistance. Lipid metabolism reprogramming is predominant and has contributed to the metabolic plasticity in glioma. This systematic review aims to discover lipids alteration and their biological roles in glioma and the identification of potential lipids biomarker. This systematic review was conducted using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. Extensive research articles search for the last 10 years, from 2011 to 2021, were conducted using four electronic databases, including PubMed, Web of Science, CINAHL and ScienceDirect. A total of 158 research articles were included in this study. All studies reported significant lipid alteration between glioma and control groups, impacting glioma cell growth, proliferation, drug resistance, patients' survival and metastasis. Different lipids demonstrated different biological roles, either beneficial or detrimental effects on glioma. Notably, prostaglandin (PGE2), triacylglycerol (TG), phosphatidylcholine (PC), and sphingosine-1-phosphate play significant roles in glioma development. Conversely, the most prominent anti-carcinogenic lipids include docosahexaenoic acid (DHA), eicosapentaenoic acid (EPA), and vitamin D3 have been reported to have detrimental effects on glioma cells. Furthermore, high lipid signals were detected at 0.9 and 1.3 ppm in high-grade glioma relative to low-grade glioma. This evidence shows that lipid metabolisms were significantly dysregulated in glioma. Concurrent with this knowledge, the discovery of specific lipid classes altered in glioma will accelerate the development of potential lipid biomarkers and enhance future glioma therapeutics.

Prognostic value and therapeutic implications of an integrative molecular subtype and immune content classifier in localized muscle-invasive bladder cancer.

530 Background: Localized muscle-invasive bladder cancer (MIBC) exhibits heterogeneous molecular features and outcomes, with a 5-year mortality rate of approximately 30%. Immune checkpoint blockade (ICB) has the potential to improve oncological outcomes but molecular tools are needed to identify those most likely to benefit. Here, we integrate transcriptomically derived tumor immune microenvironment (TIME) data with molecular subtypes to create a novel integrative classifier with prognostic and therapeutic implications. Methods: RNAseq data from patients with localized muscle-invasive bladder cancer (MIBC) from the Cancer Genome Atlas BLCA (TCGA-BLCA) project was utilized (n = 187). CIBERSORT was used for immune cell deconvolution, and unsupervised hierarchical clustering divided the cohort based on similar immune profiles. Consensus molecular clustering information for the cohort was obtained from Kamoun et al. Overall survival (OS) of each cluster were analyzed. The tumor immune dysfunction and exclusion (TIDE) tool, which uses a genomic signature validated on immunotherapy treated melanoma patients to model tumor immune evasion, was then used to predict response to ICB. Results: In the TCGA-BLCA cohort, there were two distinct clusters enriched with macrophages, CL1-M0Hi (n = 18) and CL5-M2Hi (n = 35). Compared to the rest of the cohort, these two macrophage enriched clusters combined exhibited a decreased OS (33.1 mo vs. NR, p = 0.01). TIDE tool predicted ICB response was lowest in CL1 (6/18, 33%; p = 0.09), CL5 (12/35, 34%; p = 0.02), and the Ba/Sq molecular cluster (16/57, 28%; p = 1.3x10-5). Patients designated as CL1 or CL5 by immune clustering and Ba/Sq by molecular consensus were combined into a subgroup (n = 20). Compared to the rest of the cohort, this Ba/Sq_MacrophageHi subgroup had a higher body mass index (31.0 vs. 25.8 BMI, p = 0.0004), more whites (95% vs. 64%, p = 0.03), and had a higher stage (80% Stage III/IV vs. 20% Stage I/II, p = 0.05). The Ba/Sq_MacrophageHi cluster demonstrated higher PD-L1 expression (mean Z score 0.15 vs. -0.09; p = 0.008), there was a higher degree of T cell exclusion (mean Z score 0.16 vs. -0.06; p = 0.003) and cancer-associated fibroblasts (mean Z score 0.03 vs. -0.02; p = 3.4x10-5). Overall, the predicted response to ICB by TIDE in the Ba/Sq_MacrophageHi was lower (OR 0.15, 0.03-0.55 p = 0.002) and OS was significantly shorter (median 16.7 mos vs. 54.9 mo, p = 0.04). Conclusions: We demonstrated the prognostic significance of the Basal/Squamous subtype with macrophage enrichment in patients with localized MIBC. Pending further prospective validation, this sub-population may be less amenable to ICB treatment.

Flexible Dual-Branched Message-Passing Neural Network for a Molecular Property Prediction.

A molecule is a complex of heterogeneous components, and the spatial arrangements of these components determine the whole molecular properties and characteristics. With the advent of deep learning in computational chemistry, several studies have focused on how to predict molecular properties based on molecular configurations. MA message-passing neural network provides an effective framework for capturing molecular geometric features with the perspective of a molecule as a graph. However, most of these studies assumed that all heterogeneous molecular features, such as atomic charge, bond length, or other geometric features, always contribute equivalently to the target prediction, regardless of the task type. In this study, we propose a dual-branched neural network for molecular property prediction based on both the message-passing framework and standard multilayer perceptron neural networks. Our model learns heterogeneous molecular features with different scales, which are trained flexibly according to each prediction target. In addition, we introduce a discrete branch to learn single-atom features without local aggregation, apart from message-passing steps. We verify that this novel structure can improve the model performance. The proposed model outperforms other recent models with sparser representations. Our experimental results indicate that, in the chemical property prediction tasks, the diverse chemical nature of targets should be carefully considered for both model performance and generalizability. Finally, we provide the intuitive analysis between the experimental results and the chemical meaning of the target.

Application of immune checkpoint inhibitors in EGFR-mutant non-small-cell lung cancer: from bed to bench

Targeted therapies are efficient in the context of oncogenic driver mutations. Epidermal growth factor receptor (EGFR)-mutant lung cancers represent a distinct subset of non-small-cell lung cancer (NSCLC) with marked sensitivity to EGFR tyrosine kinase inhibitors (TKIs). Despite the high response rate to EGFR TKIs in EGFR-mutant lung cancer, resistance and tumor recurrence are unavoidable. Therapeutic options are restricted in patients after exhaustion of targeted therapies. Immune checkpoint inhibitors (ICIs) represent a novel therapeutic option for advanced NSCLC with significant overall survival benefit in registration trials. No superiority in terms of long-term survival was observed in the EGFR mutation subgroup when ICIs were given as monotherapy in second-line treatment in earlier studies. Thus, the appropriate application of ICIs to patients harboring EGFR mutations remains an important field of ongoing research. Here, we discuss different immune checkpoint blockade strategies, including ICIs alone and in combination with TKIs, chemotherapy, radiation, and antiangiogenic agents in EGFR-mutant NSCLC as first-line and subsequent treatments. We also summarize the evidence concerning the heterogeneous molecular features and immune signatures of EGFR mutations and their associations with ICI therapy outcomes. This study was performed to improve our understanding of the optimal mode of immune-based treatment approaches in EGFR-mutant NSCLC.

PF362 A FIRST HIGH-DEFINITION LANDSCAPE OF SOMATIC MUTATIONS IN CHRONIC LYMPHOPROLIFERATIVE DISORDER OF NK CELLS

Background: Chronic Lymphoproliferative Disorder of NK cells (CLPD-NK) is included in the 2017 WHO classification of mature T- and NK-cell neoplasms as provisional entity. Similarly to T-cell large granular lymphocytes leukemia (T-LGLL), CLPD-NK is characterized by an indolent clinical course and is clearly distinguished from the aggressive NK cell leukemia (ANKL), this latter behaving as an acute severe disease. CLPD-NK and T-LGLL patients mostly present cytopenias when symptomatic. Accumulating evidence on the genomic landscape of T-LGLL pointed to a key role of somatic mutations within JAK-STAT (mostly in STAT3 and STAT5B genes) and RAS-MAPK pathways (Coppe et al. Leukemia 2017) in this form. Recent data highlighted more heterogeneous molecular features in ANKL, involving JAK2 and STAT3 mutations, lesions of epigenetic modifiers, tumour suppressors and a putative role of Epstein Barr Virus (Dufva et al. Nat Comm. 2018). Aims: In our cohort of 57 CLPD-NK patients the frequency of STAT mutations has been found significantly lower (<10% of all cases) compared to literature data (Barilà et al. Blood Cancer J. 2018). The genomic landscape of CLPD-NK patients negative for STAT mutations was thus investigated to better elucidate the molecular basis of the disease. Methods: Ten CLPD-NK patients were recruited according to negativity for STAT mutations and typical immunophenotype (CD16+/CD57±/CD56±). WES profiling (Agilent SureSelect 60 Mbp, Illumina sequencing, paired end reads) of immunomagnetically purified leukemic clone (>95% purity) and of normal granulocytes, as control, was obtained for each patient. Sequencing data were analyzed by an in-house bioinformatic pipeline encompassing data cleaning, read mapping against the reference genome and somatic variant calling with complementary approaches (MuTect, MuTect2 and Strelka2). Variants were next filtered according to population allele frequency (gnomAD <5%), clinical significance (COSMIC and ClinVar) and predicted functional impact on proteins (SnpEff, MetaSVM and MetaLR). Results: High sequencing depth was obtained with a mean coverage of 150 reads. From over 6,000 somatic variants detected in the cohort, 869 SNPs and 14 indels, rare and of high predicted impact were prioritized. Number of variants (88 per patient in average) and mutation spectra were very homogeneous in the cohort. Of note, the high discovery power of our settings disclosed an extensive subclonality of somatic variants, with over 78% with an allele variant frequency (VAF) lower than 5% in the leukemic clone (Figure 1A). Nevertheless, 20 deleterious and high VAF somatic variants occurred in each patient in average (Figure 1B). Very low recurrence of mutated genes in CLPD-NK patients was found. Pathway-derived mutation network analysis (Lovisa et al. Haematologica 2019) revealed functional connections among genes mutated in different patients. A major involvement of JAK-STAT pathway is likely to be ruled out, but all cases presented deleterious high VAF mutations of genes and pathways potentially impacting on cell survival, proliferation and chromatin-remodelling. In addition, somatic lesions in proteins involved in innate immunity and NK-cells activation seem particularly interesting.Summary/Conclusion: Ongoing comparison of genes and pathways mutated in CLPD-NK with available data for T-LGLL and ANKL is providing new clues on biological similarities and differences of these clinical entities. This study contributes to a better definition of the molecular mechanisms accounting for CLPD-NK, thus opening new areas of investigation.

Is the future of personalized therapy in triple-negative breast cancer based on molecular subtype?

Significant research has been conducted to better understand the extensive, heterogeneous molecular features of triple-negative breast cancer (TNBC). We reviewed published TNBC molecular classifications to identify major groupings that have potential for clinical trial development. With the ultimate aim to streamline translational medicine, we linked these categories of TNBC according to their gene-expression signatures, biological function, and clinical outcome. To this end, we define five potential clinically actionable groupings of TNBC: 1) basal-like TNBC with DNA-repair deficiency or growth factor pathways; 2) mesenchymal-like TNBC with epithelial-to-mesenchymal transition and cancer stem cell features; 3) immune-associated TNBC; 4) luminal/apocrine TNBC with androgen-receptor overexpression; and 5) HER2-enriched TNBC. For each defined subtype, we highlight the major biological pathways and discuss potential targeted therapies in TNBC that might abrogate disease progression. However, many of these potential targets need clinical validation by clinical trials. We have yet to know how we can enrich the targets by molecular classifications.

Abstract P6-11-01: A broad spectrum therapeutic strategy for TNBC revealed by a new pathway that coordinates oncogenic RTKs

Abstract Triple-negative breast cancer (TNBC) is a collection of diseases with distinct clinical behaviors and heterogeneous molecular features. Such clinical and genetic heterogeneity has called into question whether there are common pathogenic mechanisms (and potential therapeutic targets) driving the TNBC subtype of breast cancer. Herein, we present evidence of a novel tumor suppressor network that is frequently compromised in TNBC, and a broadly-effective strategy to target this pathway for TNBC therapeutic intervention. Using an unbiased genetic screen, we identified a tumor suppressor network governing tumor survival of TNBCs in vitro and in vivo. We define the tyrosine phosphatase PTPN12 as a core component in this network. PTPN12 is a potent suppressor of mammary epithelial cell survival and transformation, and PTPN12 function is compromised in more than 70% of human TNBCs. Notably, the tumorigenic and metastatic potential of PTPN12-deficient TNBCs is severely impaired by restoring PTPN12, suggesting that strategies to mimic PTPN12 function have substantive therapeutic potential. Using integrative proteomic, genetic, and pharmacologic approaches, we demonstrate that PTPN12 suppresses TNBC survival by inhibiting multiple oncogenic receptor tyrosine kinases (TKs) including MET, PDGFRβ, and others. Frequent inactivation of PTPN12 in human TNBC unleashes these oncogenic TKs in a concerted manner. Importantly, combination inhibitors targeting these PTPN12-regulated TKs significantly impair TNBC cell survival and confer robust tumor regression across a panel of 18 patient-derived xenograft ("PDX") models of human TNBC. This suggests that TNBCs are broadly dependent on a distinct combination of proto-oncogenic tyrosine kinases constrained by PTPN12. Collectively, these data identify PTPN12 as a commonly inactivated tumor suppressor in TNBC and provide a rationale for combinatorially targeting select receptor tyrosine kinases in TNBC and other cancers based on their defects in tyrosine phosphatase activity. Citation Format: Thomas F Westbrook, Amritha Nair, Tingting Sun, Kristen L Karlin, Jessica Kessler, Ilenia Migliaccio, Don X Nguyen, Ronald J Bernardi, Alex Renwick, Chad J Creighton, Noah Dephoure, Steven P Gygi, Chad A Shaw, Richard Gibbs, David Wheeler, Rachel Schiff, James G Christensen, David J Shields, C Kent Osborne, Stephen J Elledge, Susan G Hilsenbeck, Michael T Lewis. A broad spectrum therapeutic strategy for TNBC revealed by a new pathway that coordinates oncogenic RTKs [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P6-11-01.

In-depth molecular profiling of the biphasic components of uterine carcinosarcomas.

Uterine carcinosarcoma is a clinically aggressive malignancy composed of a mix of carcinomatous and sarcomatous elements. We performed targeted next‐generation sequencing of 27 uterine cancer and sarcoma genes together with immunohistochemical analyses of selected proteins in 30 uterine carcinosarcomas. This included 13 cases in which the distinct carcinoma and sarcoma components were sequenced separately and 10 cases where the metastatic tumours were analysed in addition to the primary tumours. We identified non‐synonymous somatic mutations in 90% of the cases, with 27 of 30 cases (90%) harbouring TP53 alterations. The PI3K pathway was the most commonly mutated signalling pathway with mutations identified in PIK3CA, PTEN, PIK3R1, and/or PIK3R2 in two‐thirds of the cases. Mutations in FBXW7, PPP2R1A, ARID1A and KRAS were demonstrated in a minority of cases. In cases where the carcinomatous and sarcomatous components were separately analysed, most of the mutations identified were present in both components, indicating a common origin for the two components. Furthermore, the same TP53 alterations and/or PI3K pathway mutations seen in the primary tumours were also identified in the metastatic sites. Overall, carcinosarcomas exhibited heterogeneous molecular features that resemble the heterogeneity seen in endometrial carcinomas, with some showing endometrioid carcinoma‐like and others showing serous carcinoma‐like mutation profiles. While patients with serous‐like tumours presented more frequently with advanced‐stage disease compared to patients with endometrioid‐like tumours, there was no statistical difference in outcome between the two groups. Our results provide insights into the oncogenesis of uterine carcinosarcoma and identify targetable mutations that represent early oncogenic events. The findings of the different molecular types of uterine carcinosarcoma that parallel the different molecular types in endometrial carcinoma may have future treatment implications with targeted therapies.

Emerging therapies for glioblastoma.

Glioblastoma is the most common primary malignant brain tumor, but despite multimodal treatment with surgery, radiotherapy, and temozolomide chemotherapy, the prognosis is poor, with a median survival of 16 to 19 months and poor quality of life throughout the disease course. New treatments are needed. Articles were identified through a search of PubMed references from March 2005 through January 2014, using the terms glioblastoma, glioma, malignant glioma, and brain neoplasm, as well as by search of the authors' files. Clinical trials were identified in the Clinicaltrials.gov registry. Advances in the understanding of the molecular biology of glioblastoma are being rapidly translated into innovative clinical trials, capitalizing on improved genomic, epigenetic, transcriptional, and proteomic characterization of glioblastomas as well as host factors, including the brain microenvironment and immune system interactions. Therapies targeting tumor growth factor receptors and downstream pathways, angiogenesis, modulation of cancer stemlike cells, cell cycle regulation, oncolytic viruses, new radiotherapy techniques, and immunotherapy, including vaccines and modulation of immune checkpoints (eg, programmed cell death 1 and cytotoxic T-lymphocyte antigen 4), are under investigation. In addition to novel agents, techniques to circumvent the blood-brain barrier to facilitate central nervous system drug exposure are being developed. Glioblastoma is an aggressive tumor with heterogeneous molecular features and complex host interactions, many of which are amenable to therapeutic intervention. Meaningful treatment advances will depend on identifying agents that target mechanistic vulnerabilities that are relevant to specific subgroups of patients; increasing patient enrollment into clinical trials is essential to accelerate the development of patient-tailored treatments.

Abstract 3880: Targeting the root of cancer: a data-driven approach for identification of lung cancer stem cell biomarkers

Abstract Cancer stem cells (CSCs) are a small group of cancer cells with stem cell-like properties and have been revealed to be the drive force of tumorigenesis, metastasis and drug resistance in many cancers. Current CSC surface biomarkers, such as CD133, CD44 and CD166, have been used to isolate CSC population. However, they are often not specific and unassociated with tumor outcome. Here, we applied a data-driven approach to identify new and functional biomarkers of CSC. We systematically screened for genes whose expressions are statistically correlated with CSC surface biomarkers. Normalized DNA microarray data of 160 cases of squamous carcinoma and 33 cases of adenocarcinoma and 8 cases of normal lung were analyzed for association with CD133, CD44 and CD166 respectively. Multiple hypothesis testing was corrected with the false discovery rate (FDR) less than 1%. We find CD133, CD44 and CD166 each has a different set of statistically associated genes in either adeno or squamous subtypes. Moreover, correlated genes with each of the surface marker are different between adeno and squamous subtypes. Among the highly correlated receptor genes with CD133 in squamous subtype is a hormone receptor of the reproduction regulator oxytocin (OXTR, r=0.4276, p=1.699e-8). We experimentally validated the correlation between OXTR and CD133 in human lung cancer tissues and cell lines. Further with functional assays, we discovered a new role of OXTR in promoting the self-renewal and differentiation of lung CSC. Our study suggests highly heterogeneous molecular features of CSC in different lung cancer types and demonstrates that association studies of CSC surface markers can be applied to identify new CSC biomarkers, which can be potentially used for development of probes for CSC imaging and targeting. Citation Format: Hua Fan-Minogue, Atul Butte. Targeting the root of cancer: a data-driven approach for identification of lung cancer stem cell biomarkers. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3880. doi:10.1158/1538-7445.AM2014-3880

Combating the Epigenome: Epigenetic Drugs Against Non-Hodgkin‘S Lymphoma

Non-Hodgkin's lymphomas (NHLs) comprise a large and diverse group of neoplasms of lymphocyte origin with heterogeneous molecular features and clinical manifestations. Current therapies are based on standard chemotherapy, immunotherapy, radiation or stem cell transplantation. The discovery of recurrent mutations in epigenetic enzymes, such as chromatin modifiers and DNA methyltransferases, has provided researchers with a rationale to develop novel inhibitors targeting these enzymes. Several clinical and preclinical studies have demonstrated the efficacy of epigenetic drugs in NHL therapy and a few specific inhibitors have already been approved for clinical use. Here, we provide an overview of current NHL classification and a review of the present literature describing epigenetic alterations in NHL, including a summary of different epigenetic drugs, and their use in preclinical and clinical studies.