Combined BRAF, MEK, and heat-shock protein 90 inhibition in advanced BRAF V600-mutant melanoma

BACKGROUND

Resistance to BRAF and MEK inhibitors in BRAF V600-mutant melanoma is common. Multiple resistance mechanisms involve heat-shock protein 90 (HSP90) clients, and a phase 1 study of vemurafenib with the HSP90 inhibitor XL888 in patients with advanced melanoma showed activity equivalent to that of BRAF and MEK inhibitors.

METHODS

Vemurafenib (960 mg orally twice daily) and cobimetinib (60 mg orally once daily for 21 of 28 days) with escalating dose cohorts of XL888 (30, 45, 60, or 90 mg orally twice weekly) was investigated in a phase 1 trial of advanced melanoma, with a modified Ji dose-escalation design.

RESULTS

Twenty-five patients were enrolled. After two dose-limiting toxicities (DLTs) (rash and acute kidney injury) in the first cohort, lower doses of vemurafenib (720 mg) and cobimetinib (40 mg) were investigated with the same XL888 doses. Three DLTs (rash) were observed in 12 patients in the XL888 60-mg cohort, and this was determined as the maximum tolerated dose. Objective responses were observed in 19 patients (76%), and the median progression-free survival was 7.6 months, with a 5-year progression-free survival rate of 20%. The median overall survival was 41.7 months, with a 5-year overall survival rate of 37%. Single-cell RNA sequencing was performed on baseline and on-treatment biopsies; treatment was associated with increased immune cell influx (CD4-positive and CD8-positive T cells) and decreased melanoma cells.

CONCLUSIONS

Combined vemurafenib and cobimetinib plus XL888 had significant toxicity, requiring frequent dose reductions, which may have contributed to the relatively low progression-free survival despite a high tumor response rate. Given overlapping toxicities, caution must be used when combining HSP90 inhibitors with BRAF and MEK inhibitors.

Branched-chain keto acids promote an immune-suppressive and neurodegenerative microenvironment in leptomeningeal disease

Leptomeningeal disease (LMD) occurs when tumors seed into the leptomeningeal space and cerebrospinal fluid (CSF), leading to severe neurological deterioration and poor survival outcomes. We utilized comprehensive multi-omics analyses of CSF from patients with lymphoma LMD to demonstrate an immunosuppressive cellular microenvironment and identified dysregulations in proteins and lipids indicating neurodegenerative processes. Strikingly, we found a significant accumulation of toxic branched-chain keto acids (BCKA) in the CSF of patients with LMD. The BCKA accumulation was found to be a pan-cancer occurrence, evident in lymphoma, breast cancer, and melanoma LMD patients. Functionally, BCKA disrupted the viability and function of endogenous T lymphocytes, chimeric antigen receptor (CAR) T cells, neurons, and meningeal cells. Treatment of LMD mice with BCKA-reducing sodium phenylbutyrate significantly improved neurological function, survival outcomes, and efficacy of anti-CD19 CAR T cell therapy. This is the first report of BCKA accumulation in LMD and provides preclinical evidence that targeting these toxic metabolites improves outcomes.

Differential requirements for CD4+ T cells in the efficacy of the anti-PD-1+LAG-3 and anti-PD-1+CTLA-4 combinations in melanoma flank and brain metastasis models

BACKGROUND

Although the anti-PD-1+LAG-3 and the anti-PD-1+CTLA-4 combinations are effective in advanced melanoma, it remains unclear whether their mechanisms of action overlap.

METHODS

We used single cell (sc) RNA-seq, flow cytometry and IHC analysis of responding SM1, D4M-UV2 and B16 melanoma flank tumors and SM1 brain metastases to explore the mechanism of action of the anti-PD-1+LAG-3 and the anti-PD-1+CTLA-4 combination. CD4+ and CD8+ T cell depletion, tetramer binding assays and ELISPOT assays were used to demonstrate the unique role of CD4+T cell help in the antitumor effects of the anti-PD-1+LAG-3 combination.

RESULTS

The anti-PD-1+CTLA-4 combination was associated with the infiltration of FOXP3+regulatory CD4+ cells (Tregs), fewer activated CD4+T cells and the accumulation of a subset of IFNγ secreting cytotoxic CD8+T cells, whereas the anti-PD-1+LAG-3 combination led to the accumulation of CD4+T helper cells that expressed CXCR4, TNFSF8, IL21R and a subset of CD8+T cells with reduced expression of cytotoxic markers. T cell depletion studies showed a requirement for CD4+T cells for the anti-PD-1+LAG-3 combination, but not the PD-1-CTLA-4 combination at both flank and brain tumor sites. In anti-PD-1+LAG-3 treated tumors, CD4+T cell depletion was associated with fewer activated (CD69+) CD8+T cells and impaired IFNγ release but, conversely, increased numbers of activated CD8+T cells and IFNγ release in anti-PD-1+CTLA-4 treated tumors.

CONCLUSIONS

Together these studies suggest that these two clinically relevant immune checkpoint inhibitor (ICI) combinations have differential effects on CD4+T cell polarization, which in turn, impacted cytotoxic CD8+T cell function. Further insights into the mechanisms of action/resistance of these clinically-relevant ICI combinations will allow therapy to be further personalized.

HDAC8-mediated inhibition of EP300 drives a transcriptional state that increases melanoma brain metastasis

Melanomas can adopt multiple transcriptional states. Little is known about the epigenetic drivers of these cell states, limiting our ability to regulate melanoma heterogeneity. Here, we identify stress-induced HDAC8 activity as driving melanoma brain metastasis development. Exposure of melanocytes and melanoma cells to multiple stresses increases HDAC8 activation leading to a neural crest-stem cell transcriptional state and an amoeboid, invasive phenotype that increases seeding to the brain. Using ATAC-Seq and ChIP-Seq we show that increased HDAC8 activity alters chromatin structure by increasing H3K27ac and enhancing accessibility at c-Jun binding sites. Functionally, HDAC8 deacetylates the histone acetyltransferase EP300, causing its enzymatic inactivation. This, in turn, increases binding of EP300 to Jun-transcriptional sites and decreases binding to MITF-transcriptional sites. Inhibition of EP300 increases melanoma cell invasion, resistance to stress and increases melanoma brain metastasis development. HDAC8 is identified as a mediator of transcriptional co-factor inactivation and chromatin accessibility that drives brain metastasis.

PATH-SURVEYOR: pathway level survival enquiry for immuno-oncology and drug repurposing

Pathway-level survival analysis offers the opportunity to examine molecular pathways and immune signatures that influence patient outcomes. However, available survival analysis algorithms are limited in pathway-level function and lack a streamlined analytical process. Here we present a comprehensive pathway-level survival analysis suite, PATH-SURVEYOR, which includes a Shiny user interface with extensive features for systematic exploration of pathways and covariates in a Cox proportional-hazard model. Moreover, our framework offers an integrative strategy for performing Hazard Ratio ranked Gene Set Enrichment Analysis and pathway clustering. As an example, we applied our tool in a combined cohort of melanoma patients treated with checkpoint inhibition (ICI) and identified several immune populations and biomarkers predictive of ICI efficacy. We also analyzed gene expression data of pediatric acute myeloid leukemia (AML) and performed an inverse association of drug targets with the patient's clinical endpoint. Our analysis derived several drug targets in high-risk KMT2A-fusion-positive patients, which were then validated in AML cell lines in the Genomics of Drug Sensitivity database. Altogether, the tool offers a comprehensive suite for pathway-level survival analysis and a user interface for exploring drug targets, molecular features, and immune populations at different resolutions.

Quantifying Cell Heterogeneity and Subpopulations Using Single Cell Metabolomics

Mass spectrometry (MS) has become an indispensable tool for metabolomics studies. However, due to the lack of applicable experimental platforms, suitable algorithm, software, and quantitative analyses of cell heterogeneity and subpopulations, investigating global metabolomics profiling at the single cell level remains challenging. We combined the Single-probe single cell MS (SCMS) experimental technique with a bioinformatics software package, SinCHet-MS (Single Cell Heterogeneity for Mass Spectrometry), to characterize changes of tumor heterogeneity, quantify cell subpopulations, and prioritize the metabolite biomarkers of each subpopulation. As proof of principle studies, two melanoma cancer cell lines, the primary (WM115; with a lower drug resistance) and the metastatic (WM266-4; with a higher drug resistance), were used as models. Our results indicate that after the treatment of the anticancer drug vemurafenib, a new subpopulation emerged in WM115 cells, while the proportion of the existing subpopulations was changed in the WM266-4 cells. In addition, metabolites for each subpopulation can be prioritized. Combining the SCMS experimental technique with a bioinformatics tool, our label-free approach can be applied to quantitatively study cell heterogeneity, prioritize markers for further investigation, and improve the understanding of cell metabolism in human diseases and response to therapy.

IGF-binding proteins secreted by cancer-associated fibroblasts induce context-dependent drug sensitization of lung cancer cells

Cancer-associated fibroblasts (CAFs) in the tumor microenvironment are often linked to drug resistance. Here, we found that coculture with CAFs or culture in CAF-conditioned medium unexpectedly induced drug sensitivity in certain lung cancer cell lines. Gene expression and secretome analyses of CAFs and normal lung-associated fibroblasts (NAFs) revealed differential abundance of insulin-like growth factors (IGFs) and IGF-binding proteins (IGFBPs), which promoted or inhibited, respectively, signaling by the receptor IGF1R and the kinase FAK. Similar drug sensitization was seen in gefitinib-resistant, EGFR-mutant PC9GR lung cancer cells treated with recombinant IGFBPs. Conversely, drug sensitivity was decreased by recombinant IGFs or conditioned medium from CAFs in which IGFBP5 or IGFBP6 was silenced. Phosphoproteomics and receptor tyrosine kinase (RTK) array analyses indicated that exposure of PC9GR cells to CAF-conditioned medium also inhibited compensatory IGF1R and FAK signaling induced by the EGFR inhibitor osimertinib. Combined small-molecule inhibition of IGF1R and FAK phenocopied the CAF-mediated effects in culture and increased the antitumor effect of osimertinib in mice. Cells that were osimertinib resistant and had MET amplification or showed epithelial-to-mesenchymal transition also displayed residual sensitivity to IGFBPs. Thus, CAFs promote or reduce drug resistance in a context-dependent manner, and deciphering the relationship between the differential content of CAF secretomes and the signaling dependencies of the tumor may reveal effective combination treatment strategies.

Abstract PR004: In vivo tracking of clonal dynamics during UV-induced skin carcinogenesis

Background: The impact of chronic UV exposure on clonal dynamics and genomic diversity remains unclear. Our central hypothesis is that skin cancer is induced not by solely accumulation of somatic mutations, but rather a combination of mutations and disruption of the spatial and temporal constraints imposed by the skin’s 3-D architecture. Here we characterize clonal dynamics and transcriptional signatures during skin carcinogenesis using multicolor lineage tracing. Methods: We generated a K14Cre-ERT2 Confetti mice with inducible fluorophore (flr) expression. Mice were UV-irradiated for 3 months. Clones were 3-D digitized using confocal microscopy (z-stacks) and clone volumes estimated computationally. scRNAseq was used to compare UV-exposed (EXP) vs. non-exposed (NON) epidermis vs. skin tumors. Results: We generated 914 serial images of the EXP/NON skin over the course of 6 months following initiation of UV. We analyzed 16,135 clones from the EXP and 21,506 clones from the NON skin. We classified clone sizes into 3 classes represented by the small (<50,000 μm3), medium (50,000-500,000 μm3), and large “goliath” (> 500,000 μm3). The median size of clones does not differ between UV treatments and does not change with time. However, clones from EXP samples have significantly greater mean size than NON ones. Their mean sizes differed by some 1.5-fold, with an over 6-fold increase in variance, resulting in the sizes distribution to be highly skewed towards large clones with a long, narrow tail. Goliath clones are rarely present in the NON skin; however, they increase in number dramatically by months 3-4, plateauing between months 5-6. Using 3 ecological metrics (clone size, clone numbers, and coefficient of variation) we see phase shifts, which primarily distinguish months 1 & 2 from months 3 & 4. scRNAseq of EXP/NON epidermis and tumors revealed differential representation of 16 clusters, the majority of which could be mapped to previously defined keratinocyte populations. We observe dynamic changes to these clusters when progressing from normal skin to chronically exposed skin, and then to tumors. EXP clusters were associated with expression of cystatins (Scfa 3, BC100530), and alarmins/proliferative keratins (Krt16, Krt6a), which have been associated with skin injury. Clusters expressing cystatins and alarmins also increased in tumors. Flr-expressing keratinocytes harvested from large clones in EXP epidermis exhibited altered keratinocyte differentiation (downregulation of Krt77, Loricrin and Nfkbia, upregulation of cystatin), inflammation (downregulation of Nfkbia), and upregulation of metabolic regulators (carbonic anhydrase II and retinol transport (Rbp1)). Genes differentially expressed in exposed skin and retained in tumors may be required for carcinogenesis, while those expressed only in exposed skin likely required for adaptive responses to UV. Our findings have important implications for understanding cancer through an eco-evolutionary framework and designing novel approaches to cancer prevention.

Citation Format: Stanislav Avdieiev, Leticia Tordesillas, Omar Chavez Chiang, Zhihua Chen, Luiza Silva Simoes, Y. Ann Chen, Noemi Andor, Robert Gatenby, Elsa R. Flores, Joel S. Brown, Kenneth Y. Tsai. In vivo tracking of clonal dynamics during UV-induced skin carcinogenesis [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr PR004.

Abstract A017: In vivo tracking of clonal dynamics during UV-induced skin carcinogenesis

This abstract is being presented as a short talk in the scientific program. A full abstract is available in the Proffered Abstracts section (PR004) of the Conference Proceedings.

Citation Format: Stanislav Avdieiev, Leticia Tordesillas, Omar Chavez Chiang, Zhihua Chen, Luiza Silva Simoes, Y. Ann Chen, Noemi Andor, Robert Gatenby, Elsa R. Flores, Joel S. Brown, Kenneth Y. Tsai. In vivo tracking of clonal dynamics during UV-induced skin carcinogenesis [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr A017.

Single-cell Characterization of the Cellular Landscape of Acral Melanoma Identifies Novel Targets for Immunotherapy

PURPOSE

Acral melanoma is a rare subtype of melanoma that arises on the non-hair-bearing skin of the palms, soles, and nail beds. In this study, we used single-cell RNA sequencing (scRNA-seq) to map the transcriptional landscape of acral melanoma and identify novel immunotherapeutic targets.

EXPERIMENTAL DESIGN

We performed scRNA-seq on nine clinical specimens (five primary, four metastases) of acral melanoma. Detailed cell type curation was performed, the immune landscapes were mapped, and key results were validated by analysis of The Cancer Genome Atlas (TCGA) and single-cell datasets. Cell-cell interactions were inferred and compared with those in nonacral cutaneous melanoma.

RESULTS

Multiple phenotypic subsets of T cells, natural killer (NK) cells, B cells, macrophages, and dendritic cells with varying levels of activation/exhaustion were identified. A comparison between primary and metastatic acral melanoma identified gene signatures associated with changes in immune responses and metabolism. Acral melanoma was characterized by a lower overall immune infiltrate, fewer effector CD8 T cells and NK cells, and a near-complete absence of γδ T cells compared with nonacral cutaneous melanomas. Immune cells associated with acral melanoma exhibited expression of multiple checkpoints including PD-1, LAG-3, CTLA-4, V-domain immunoglobin suppressor of T cell activation (VISTA), TIGIT, and the Adenosine A2A receptor (ADORA2). VISTA was expressed in 58.3% of myeloid cells and TIGIT was expressed in 22.3% of T/NK cells.

CONCLUSIONS

Acral melanoma has a suppressed immune environment compared with that of cutaneous melanoma from nonacral skin. Expression of multiple, therapeutically tractable immune checkpoints were observed, offering new options for clinical translation.

Tumor Expression Quantitative Trait Methylation Screening Reveals Distinct CpG Panels for Deconvolving Cancer Immune Signatures

DNA methylation signatures in tumors could serve as reliable biomarkers that are accessible in archival tissues for tracking the epigenetic dynamics shaped by both cancer cells and the tumor microenvironment. However, given the ultrahigh dimensionality and noncollapsible nature of the data, it remains challenging to screen all CpG sites to identify the most promising marker panels. In this article, we introduce the concept of tumor-based expression quantitative trait methylation (eQTM) for the prioritization and systematic mining of predictive biomarkers. In melanoma as a disease model, eQTM CpGs and genes represent new and efficient candidate targets to be investigated for both prognostic and immune status monitoring purposes. Three cis-eQTM CpGs (cg07786657, cg12446199, and cg00027570) were strongly associated with and can serve as surrogate biomarkers for the tumor immune cytolytic activity score (CYT). In addition, multiple eQTM genes could be further exploited for predicting immunoregulatory phenotypes. A targeted gene panel analysis identified one eQTM in TCF7 (cg25947408) as a novel candidate biomarker for uncoupling overall T-cell differentiation and exhaustion status in a tumor. The prognostic significance of this eQTM as an independent signature to CYT was validated by both The Cancer Genome Atlas and Moffitt melanoma cohort data. Overall, eQTMs represent a mechanistically distinct class of potential biomarkers that can be used to predict patient prognosis and immune status.

SIGNIFICANCE

This study provides a novel and promising approach to identify targeted epigenetic biomarkers in cancer and will spur further analysis in tumor immune phenotyping.

Single-Cell Characterization of the Immune Microenvironment of Melanoma Brain and Leptomeningeal Metastases

PURPOSE

Melanoma brain metastases (MBM) and leptomeningeal melanoma metastases (LMM) are two different manifestations of melanoma CNS metastasis. Here, we used single-cell RNA sequencing (scRNA-seq) to define the immune landscape of MBM, LMM, and melanoma skin metastases.

EXPERIMENTAL DESIGN

scRNA-seq was undertaken on 43 patient specimens, including 8 skin metastases, 14 MBM, and 19 serial LMM specimens. Detailed cell type curation was performed, the immune landscapes were mapped, and key results were validated by IHC and flow cytometry. Association analyses were undertaken to identify immune cell subsets correlated with overall survival.

RESULTS

The LMM microenvironment was characterized by an immune-suppressed T-cell landscape distinct from that of brain and skin metastases. An LMM patient with long-term survival demonstrated an immune repertoire distinct from that of poor survivors and more similar to normal cerebrospinal fluid (CSF). Upon response to PD-1 therapy, this extreme responder showed increased levels of T cells and dendritic cells in their CSF, whereas poor survivors showed little improvement in their T-cell responses. In MBM patients, therapy led to increased immune infiltrate, with similar T-cell transcriptional diversity noted between skin metastases and MBM. A correlation analysis across the entire immune landscape identified the presence of a rare population of dendritic cells (DC3) that was associated with increased overall survival and positively regulated the immune environment through modulation of activated T cells and MHC expression.

CONCLUSIONS

Our study provides the first atlas of two distinct sites of melanoma CNS metastases and defines the immune cell landscape that underlies the biology of this devastating disease.

A Mutational Survey of Acral Nevi

Importance

Acral skin may develop nevi, but their mutational status and association with acral melanoma is unclear.

Objective

To perform targeted next-generation sequencing on a cohort of acral nevi to determine their mutational spectrum.

Design, Setting, and Participants

Acral nevi specimens (n = 50) that had been obtained for diagnostic purposes were identified from the pathology archives of a tertiary care academic cancer center and a university dermatology clinic. Next-generation sequencing was performed on DNA extracted from the specimens, and mutations called. A subset of samples was stained immunohistochemically for the BRAF V600E mutation.

Results

A total of 50 nevi from 49 patients (19 males and 30 females; median [range] age, 48 [13-85] years) were examined. Analysis of the sequencing data revealed a high prevalence of BRAF mutations (n = 43), with a lower frequency of NRAS mutations (n = 5). Mutations in BRAF and NRAS were mutually exclusive.

Conclusions and Relevance

In this cohort study, nevi arising on mostly sun-protected acral skin showed a rate of BRAF mutation similar to that of acquired nevi on sun-exposed skin but far higher than that of acral melanoma. These findings are in contrast to the well-characterized mutational landscape of acral melanoma.

Statistical and Bioinformatics Analysis of Data from Bulk and Single-Cell RNA Sequencing Experiments

High-throughput sequencing (HTS) has revolutionized researchers' ability to study the human transcriptome, particularly as it relates to cancer. Recently, HTS technology has advanced to the point where now one is able to sequence individual cells (i.e., "single-cell sequencing"). Prior to single-cell sequencing technology, HTS would be completed on RNA extracted from a tissue sample consisting of multiple cell types (i.e., "bulk sequencing"). In this chapter, we review the various bioinformatics and statistical methods used in the processing, quality control, and analysis of bulk and single-cell RNA sequencing methods. Additionally, we discuss how these methods are also being used to study tumor heterogeneity.

The Association of MUC16 Mutation with Tumor Mutation Burden and Its Prognostic Implications in Cutaneous Melanoma

BACKGROUND

MUC16 is a mucin marker that is frequently mutated in melanoma, but whether MUC16 mutations could be useful as a surrogate biomarker for tumor mutation burden (TMB) remains unclear.

METHODS

This study rigorously evaluates the MUC16 mutation as a clinical biomarker in cutaneous melanoma by utilizing genomic and clinical data from patient samples from The Cancer Genome Atlas (TCGA) and two independent validation cohorts. We further extended the analysis to studies with patients treated with immunotherapies.

RESULTS

Analysis results showed that samples with MUC16 mutations had a higher TMB than the samples of wild-type, with strong statistical significance (P < 0.001) in all melanoma cohorts tested. Associations between MUC16 mutations and TMB remained statistically significant after adjusting for potential confounding factors in the TCGA cohort [OR, 9.28 (95% confidence interval (CI), 5.18-17.39); P < 0.001], Moffitt cohort [OR, 31.95 (95% CI, 8.71-163.90); P < 0.001], and Yale cohort [OR, 8.09 (95% CI, 3.12-23.79); P < 0.01]. MUC16 mutations were also found to be associated with overall survival in the TCGA [HR, 0.62; (95% CI, 0.45-0.85); P < 0.01] and Moffitt cohorts [HR, 0.49 (95% CI, 0.28-0.87); P = 0.014]. Strikingly, MUC16 is the only top frequently mutated gene for which prognostic significance was observed. MUC16 mutations were also found valuable in predicting anti-CTLA-4 and anti-PD-1 therapy responses.

CONCLUSIONS

MUC16 mutation appears to be a useful predictive marker of global TMB and patient survival in melanoma.

IMPACT

This is, to the best of our knowledge, the first systematic evaluation of MUC16 mutation as a clinical biomarker and a predictive biomarker for immunotherapy in melanoma.

GMSimpute: a generalized two-step Lasso approach to impute missing values in label-free mass spectrum analysis

Motivation

Missingness in label-free mass spectrometry is inherent to the technology. A computational approach to recover missing values in metabolomics and proteomics datasets is important. Most existing methods are designed under a particular assumption, either missing at random or under the detection limit. If the missing pattern deviates from the assumption, it may lead to biased results. Hence, we investigate the missing patterns in free mass spectrometry data and develop an omnibus approach GMSimpute, to allow effective imputation accommodating different missing patterns.

Results

Three proteomics datasets and one metabolomics dataset indicate missing values could be a mixture of abundance-dependent and abundance-independent missingness. We assess the performance of GMSimpute using simulated data (with a wide range of 80 missing patterns) and metabolomics data from the Cancer Genome Atlas breast cancer and clear cell renal cell carcinoma studies. Using Pearson correlation and normalized root mean square errors between the true and imputed abundance, we compare its performance to K-nearest neighbors’ type approaches, Random Forest, GSimp, a model-based method implemented in DanteR and minimum values. The results indicate GMSimpute provides higher accuracy in imputation and exhibits stable performance across different missing patterns. In addition, GMSimpute is able to identify the features in downstream differential expression analysis with high accuracy when applied to the Cancer Genome Atlas datasets.

Availability and implementation

GMSimpute is on CRAN: https://cran.r-project.org/web/packages/GMSimpute/index.html.

Supplementary information

Supplementary data are available at Bioinformatics online.

LncRNA RUSC1-AS1 promotes the proliferation of hepatocellular carcinoma cells through modulating NOTCH signaling

The long non-coding RNA (lncRNA) RUSC1-AS1 has been reported to be dysregulated in the progression of many cancers. Also, RUSC1-AS1 had been detected to be highly expressed in laryngeal squamous cell carcinoma and breast cancer cells, suggesting that RUSC1-AS1 may be a biomarker for cancers. However, the biological role and regulatory mechanism of RUSC1-AS1 in hepatocellular carcinoma (HCC) remain unknown. In this study, we found that RUSC1-AS1 was upregulated in HCC tissues and cells, and predicted unfavorable prognosis of HCC patients. The function assays including colony formation, EdU, TUNEL assay revealed that RUSC1-AS1 facilitated HCC cell proliferation and inhibited HCC cell apoptosis. Furthermore, mechanism assays including luciferase reporter assay and RIP assay demonstrated that RUSC1-AS1 could directly bind to hsa-miR-7-5p. Besides, hsa-miR-7-5p targeted and negatively regulated NOTCH3 expression. Moreover, RUSC1-AS1 sponged hsa-miR-7-5p to upregulate NOTCH3 and to trigger the NOTCH signaling pathway. The rescue assays depicted that RUSC1-AS1 regulated HCC cell proliferation and apoptosis through modulating NOTCH signaling. In conclusion, lncRNA RUSC1-AS1 promoted the proliferation and reduced the apoptosis of HCC cells through activation of NOTCH signaling via hsa-miR-7-5p/NOTCH3 axis.

Multi-Dimensional Flow Cytometry Analyses Reveal a Dichotomous Role for Nitric Oxide in Melanoma Patients Receiving Immunotherapy

Phenotyping of immune cell subsets in clinical trials is limited to well-defined phenotypes, due to technological limitations of reporting flow cytometry multi-dimensional phenotyping data. We developed a multi-dimensional phenotyping analysis tool and applied it to detect nitric oxide (NO) levels in peripheral blood immune cells before and after adjuvant ipilimumab co-administration with a peptide vaccine in melanoma patients. We analyzed inhibitory and stimulatory markers for immune cell phenotypes that were felt to be important in the NO analysis. The pipeline allows visualization of immune cell phenotypes without knowledge of clustering techniques and to categorize cells by association with relapse-free survival (RFS). Using this analysis, we uncovered the potential for a dichotomous role of NO as a pro- and anti-melanoma factor. NO was found in subsets of immune-suppressor cells associated with shorter-term (≤ 1 year) RFS, whereas NO was also present in immune-stimulatory effector cells obtained from patients with significant longer-term (> 1 year) RFS. These studies provide insights into the cell-specific immunomodulatory role of NO. The methods presented herein can be applied to monitor the pro- and anti-tumor effects of a variety of immune-based therapeutics in cancer patients. Clinical Trial Registration Number: NCT00084656 (https://clinicaltrials.gov/ct2/show/NCT00084656).

Predictive Value of Noncontrast Head CT with Negative Findings in the Emergency Department Setting

BACKGROUND AND PURPOSE

Noncontrast head CTs are routinely acquired for patients with neurologic symptoms in the emergency department setting. Anecdotally, noncontrast head CTs performed in patients with prior negative findings with the same clinical indication are of low diagnostic yield. We hypothesized that the rate of acute findings in noncontrast head CTs performed in patients with a preceding study with negative findings would be lower compared with patients being imaged for the first time.

MATERIALS AND METHODS

We retrospectively evaluated patients in the emergency department setting who underwent noncontrast head CTs at our institution during a 4-year period, recording whether the patient had undergone a prior noncontrast head CT, the clinical indication for the examination, and the examination outcome. Positive findings on examinations were defined as those that showed any intracranial abnormality that would necessitate a change in acute management, such as acute hemorrhage, hydrocephalus, herniation, or interval worsening of a prior finding.

RESULTS

During the study period, 8160 patients in the emergency department setting underwent a total of 9593 noncontrast head CTs; 88.2% (7198/8160) had a single examination, and 11.8% (962/8160) had at least 1 repeat examination. The baseline positive rate of the "nonrepeat" group was 4.3% (308/7198). The 911 patients in the "repeat" group with negative findings on a baseline/first CT had a total of 1359 repeat noncontrast head CTs during the study period. The rate of positive findings for these repeat examinations was 1.8% (25/1359), significantly lower than the 4.3% baseline rate (P < .001). Of the repeat examinations that had positive findings, 80% (20/25) had a study indication that was discordant with that of the prior examination, compared with only 44% (593/1334) of the repeat examinations that had negative findings (P < .001).

CONCLUSIONS

In a retrospective observational study based on approximately 10,000 examinations, we found that serial noncontrast head CT examinations in patients with prior negative findings with the same study indication are less likely to have positive findings compared with first-time examinations or examinations with a new indication. This finding suggests a negative predictive value of a prior noncontrast head CT examination with negative findings with the same clinical indication.

Leveraging transcriptional dynamics to improve BRAF inhibitor responses in melanoma

BACKGROUND

Melanoma is a heterogeneous tumour, but the impact of this heterogeneity upon therapeutic response is not well understood.

METHODS

Single cell mRNA analysis was used to define the transcriptional heterogeneity of melanoma and its dynamic response to BRAF inhibitor therapy and treatment holidays. Discrete transcriptional states were defined in cell lines and melanoma patient specimens that predicted initial sensitivity to BRAF inhibition and the potential for effective re-challenge following resistance. A mathematical model was developed to maintain competition between the drug-sensitive and resistant states, which was validated in vivo.

FINDINGS

Our analyses showed melanoma cell lines and patient specimens to be composed of >3 transcriptionally distinct states. The cell state composition was dynamically regulated in response to BRAF inhibitor therapy and drug holidays. Transcriptional state composition predicted for therapy response. The differences in fitness between the different transcriptional states were leveraged to develop a mathematical model that optimized therapy schedules to retain the drug sensitive population. In vivo validation demonstrated that the personalized adaptive dosing schedules outperformed continuous or fixed intermittent BRAF inhibitor schedules.

INTERPRETATION

Our study provides the first evidence that transcriptional heterogeneity at the single cell level predicts for initial BRAF inhibitor sensitivity. We further demonstrate that manipulating transcriptional heterogeneity through personalized adaptive therapy schedules can delay the time to resistance.

FUNDING

This work was funded by the National Institutes of Health. The funder played no role in assembly of the manuscript.

Estimation of immune cell content in tumor using single-cell RNA-seq reference data

Background

The rapid development of single-cell RNA sequencing (scRNA-seq) provides unprecedented opportunities to study the tumor ecosystem that involves a heterogeneous mixture of cell types. However, the majority of previous and current studies related to translational and molecular oncology have only focused on the bulk tumor and there is a wealth of gene expression data accumulated with matched clinical outcomes.

Results

In this paper, we introduce a scheme for characterizing cell compositions from bulk tumor gene expression by integrating signatures learned from scRNA-seq data. We derived the reference expression matrix to each cell type based on cell subpopulations identified in head and neck cancer dataset. Our results suggest that scRNA-Seq-derived reference matrix outperforms the existing gene panel and reference matrix with respect to distinguishing immune cell subtypes.

Conclusions

Findings and resources created from this study enable future and secondary analysis of tumor RNA mixtures in head and neck cancer for a more accurate cellular deconvolution, and can facilitate the profiling of the immune infiltration in other solid tumors due to the expression homogeneity observed in immune cells.

Electronic supplementary material

The online version of this article (10.1186/s12885-019-5927-3) contains supplementary material, which is available to authorized users.

Semiautomated Measure of Abdominal Adiposity Using Computed Tomography Scan Analysis

BACKGROUND

The obesity epidemic has prompted the need to better understand the impact of adipose tissue on human pathophysiology. However, accurate, efficient, and replicable models of quantifying adiposity have yet to be developed and clinically implemented. We propose a novel semiautomated radiologic method of measuring the visceral fat area (VFA) using computed tomography scan analysis.

MATERIALS AND METHODS

We obtained a cohort of 100 patients with rectal adenocarcinoma, with a median age of 60.9 y (age range: 35-87 y) and an average body mass index of 28.8 kg/m2 ± 6.56 kg/m2. The semiautomated quantification method of adiposity was developed using a commercial imaging suite. The method was compared to two manual delineations performed using two different picture archiving communication systems. We quantified VFA, subcutaneous fat area (SFA), total fat area (TFA), and visceral-to-subcutaneous fat ratio (V/S ratio) on computed tomography axial slices that were at the L4-L5 intervertebral level.

RESULTS

The semiautomated method was comparable to manual measurements for TFA, VFA, and SFA with intraclass correlation (ICC) of 0.99, 0.97, and 0.96, respectively. However, the ICC for the V/S ratio was only 0.44, which led to the identification of technical outliers that were identified using robust regression. After removal of these outliers, the ICC improved to 0.99 for TFA, VFA, and SFA and 0.97 for the V/S ratio. Measurements from the manual methodology highly correlated between the two picture archiving communication system platforms, with ICC of 0.98 for TFA, 0.98 for VFA, 0.96 for SFA, and 0.95 for the V/S ratio.

CONCLUSIONS

This semiautomated method is able to generate precise and reproducible results. In the future, this method may be applied on a larger scale to facilitate risk stratification of patients using measures of abdominal adiposity.

Genome-wide Analysis of Common Copy Number Variation and Epithelial Ovarian Cancer Risk

BACKGROUND

Germline DNA copy number variation (CNV) is a ubiquitous source of genetic variation and remains largely unexplored in association with epithelial ovarian cancer (EOC) risk.

METHODS

CNV was quantified in the DNA of approximately 3,500 cases and controls genotyped with the Illumina 610k and HumanOmni2.5M arrays. We performed a genome-wide association study of common (>1%) CNV regions (CNVRs) with EOC and high-grade serous (HGSOC) risk and, using The Cancer Genome Atlas (TCGA), performed in silico analyses of tumor-gene expression.

RESULTS

Three CNVRs were associated (P < 0.01) with EOC risk: two large (∼100 kb) regions within the 610k set and one small (<5 kb) region with the higher resolution 2.5M data. Large CNVRs included a duplication at LILRA6 (OR = 2.57; P = 0.001) and a deletion at CYP2A7 (OR = 1.90; P = 0.007) that were strongly associated with HGSOC risk (OR = 3.02; P = 8.98 × 10^-5). Somatic CYP2A7 alterations correlated with EGLN2 expression in tumors (P = 2.94 × 10^-47). An intronic ERBB4/HER4 deletion was associated with reduced EOC risk (OR = 0.33; P = 9.5 × 10^-2), and somatic deletions correlated with ERBB4 downregulation (P = 7.05 × 10^-5). Five CNVRs were associated with HGSOC, including two reduced-risk deletions: one at 1p36.33 (OR = 0.28; P = 0.001) that correlated with lower CDKIIA expression in TCGA tumors (P = 2.7 × 10^-7), and another at 8p21.2 (OR = 0.52; P = 0.002) that was present somatically where it correlated with lower GNRH1 expression (P = 5.9 × 10^-5).

CONCLUSIONS

Though CNV appears to not contribute largely to EOC susceptibility, a number of low-to-common frequency variants may influence the risk of EOC and tumor-gene expression.

IMPACT

Further research on CNV and EOC susceptibility is warranted, particularly with CNVs estimated from high-density arrays.

Abstract 1616: Novel caged hapten proximity assay platform enables detection of oncogenic signaling-associated complexes in the clinical pathology laboratory setting

Assays measuring protein complexes represent a novel class of protein-based biomarkers. Using proximity-based readouts, we and others have previously shown utility in monitoring signaling-associated complexes to predict response to targeted therapeutics in lung cancer. However, fluorescence-based proximity assay readouts are difficult to implement in a clinical setting and are not conducive to typical pathology laboratory workflow. Here, we provide evidence of a novel proximity-based technology platform that utilizes a “caged hapten” proximity readout followed by chromogenic immunohistochemistry (IHC) detection. We have synthesized haptens modified with a phosphorylated quinone methide precursor. This enzyme- labile caging group abrogates antibody binding; however, upon exposure to alkaline phosphatase (AP) the native hapten is regenerated. These caged haptens may be applied in a proximity assay format by the use of a first antibody labeled with caged haptens that can be uncaged by AP conjugated to the second antibody. Only when the two epitopes of interest are in close proximity to one another will the AP interact with the caged hapten and uncage it. The native hapten, which represents the protein complex population, can then be visualized by an anti-hapten antibody conjugated to horseradish peroxidase (HRP) followed by 3,3'-diaminobenzidine (DAB) detection. These reagents and assays are fully automated on the VENTANA DISCOVERY ULTRA platform. We demonstrate detection of β-Catenin:E-Cadherin, EGFR:GRB2 and MET:GRB2 complexes in formalin-fixed paraffin embedded (FFPE) lung cancer cell lines, patient-derived xenografts (PDX) and non-small cell lung cancer (NSCLC) patient specimens. Assay specificity was confirmed through technical controls involving reagent omission experiments, and biologically by treatment with small molecule kinase inhibitors that disrupt kinase:adaptor interactions. We revealed heterogeneous EGFR and MET signaling in MET-amplified PDX specimens, replicating previously-published findings. For EGFR:GRB2, we developed a pathologist-guided ordinal scoring system and evaluated inter-rater concordance using a tissue microarray containing 120 NSCLC cores. Kappa statistics and inter-rater correlations reveal excellent correlation among multiple raters.Collectively, these data support the adaptation of proximity-based approaches in clinical pathology settings. The use of caged hapten proximity assays on VENTANA automated slide stainers provides a novel and robust platform to evaluate protein complexes as potential biomarkers that may be incorporated as molecular correlates in ongoing early phase clinical trials. This approach also facilitates analysis of a large number of slides in a reproducible assay format enabling retrospective evaluation of tumor specimens from completed trials.

Citation Format: Brian D. Kelly, Nathan W. Polaske, Yuri Belosludtsev, Matthew A. Smith, Theresa Boyle, Y. Ann Chen, Eric B. Haura. Novel caged hapten proximity assay platform enables detection of oncogenic signaling-associated complexes in the clinical pathology laboratory setting [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1616.

SinCHet: a MATLAB toolbox for single cell heterogeneity analysis in cancer

Summary

Single-cell technologies allow characterization of transcriptomes and epigenomes for individual cells under different conditions and provide unprecedented resolution for researchers to investigate cellular heterogeneity in cancer. The SinCHet (Single Cell Heterogeneity) toolbox is developed in MATLAB and has a graphical user interface (GUI) for visualization and user interaction. It analyzes both continuous (e.g. mRNA expression) and binary omics data (e.g. discretized methylation data). The toolbox does not only quantify cellular heterogeneity using Shannon Profile (SP) at different clonal resolutions but also detects heterogeneity differences using a D statistic between two populations. It is defined as the area under the Profile of Shannon Difference (PSD). This flexible tool provides a default clonal resolution using the change point of PSD detected by multivariate adaptive regression splines model; it also allows user-defined clonal resolutions for further investigation. This tool provides insights into emerging or disappearing clones between conditions, and enables the prioritization of biomarkers for follow-up experiments based on heterogeneity or marker differences between and/or within cell populations.

Availability and implementation

The SinCHet software is freely available for non-profit academic use. The source code, example datasets, and the compiled package are available at http://labpages2.moffitt.org/chen/software/.

Supplementary information

Supplementary data are available at Bioinformatics online.

Combined BRAF and HSP90 Inhibition in Patients with Unresectable BRAF V600E-Mutant Melanoma

Purpose: BRAF inhibitors are clinically active in patients with advanced BRAF^V600-mutant melanoma, although acquired resistance remains common. Preclinical studies demonstrated that resistance could be overcome using concurrent treatment with the HSP90 inhibitor XL888.Patients and Methods: Vemurafenib (960 mg p.o. b.i.d.) combined with escalating doses of XL888 (30, 45, 90, or 135 mg p.o. twice weekly) was investigated in 21 patients with advanced BRAF^V600-mutant melanoma. Primary endpoints were safety and determination of a maximum tolerated dose. Correlative proteomic studies were performed to confirm HSP inhibitor activity.Results: Objective responses were observed in 15 of 20 evaluable patients [75%; 95% confidence interval (CI), 51%-91%], with 3 complete and 12 partial responses. Median progression-free survival and overall survival were 9.2 months (95% CI, 3.8-not reached) and 34.6 months (6.2-not reached), respectively. The most common grade 3/4 toxicities were skin toxicities, such as rash (n = 4, 19%) and cutaneous squamous cell carcinomas (n = 3, 14%), along with diarrhea (n = 3, 14%). Pharmacodynamic analysis of patients' peripheral blood mononuclear cells (PBMC) showed increased day 8 HSP70 expression compared with baseline in the three cohorts with XL888 doses ≥45 mg. Diverse effects of vemurafenib-XL888 upon intratumoral HSP client protein expression were noted, with the expression of multiple proteins (including ERBB3 and BAD) modulated on therapy.Conclusions: XL888 in combination with vemurafenib has clinical activity in patients with advanced BRAF^V600-mutant melanoma, with a tolerable side-effect profile. HSP90 inhibitors warrant further evaluation in combination with current standard-of-care BRAF plus MEK inhibitors in BRAF^V600-mutant melanoma. Clin Cancer Res; 24(22); 5516-24. ©2018 AACR See related commentary by Sullivan, p. 5496.

Relative protein quantification and accessible biology in lung tumor proteomes from four LC-MS/MS discovery platforms

Discovery proteomics experiments include many options for sample preparation and MS data acquisition, which are capable of creating datasets for quantifying thousands of proteins. To define a strategy that would produce a dataset with sufficient content while optimizing required resources, we compared (1) single-sample LC-MS/MS with data-dependent acquisition to single-sample LC-MS/MS with data-independent acquisition and (2) peptide fractionation with label-free (LF) quantification to peptide fractionation with relative quantification of chemically labeled peptides (sixplex tandem mass tags (TMT)). These strategies were applied to the same set of four frozen lung squamous cell carcinomas and four adjacent tissues, and the overall outcomes of each experiment were assessed. We identified 6656 unique protein groups with LF, 5535 using TMT, 3409 proteins from single-sample analysis with data-independent acquisition, and 2219 proteins from single-sample analysis with data-dependent acquisition. Pathway analysis indicated the number of proteins per pathway was proportional to the total protein identifications from each method, suggesting limited biological bias between experiments. The results suggest the use of single-sample experiments as a rapid tissue assessment tool and digestion quality control or as a technique to maximize output from limited samples and use of TMT or LF quantification as methods for larger amounts of tumor tissue with the selection being driven mainly by instrument time limitations. Data are available via ProteomeXchange with identifiers PXD004682, PXD004683, PXD004684, and PXD005733.

MET-GRB2 Signaling-Associated Complexes Correlate with Oncogenic MET Signaling and Sensitivity to MET Kinase Inhibitors

Purpose: Targeting MET in cancer is hampered by lack of diagnostics that accurately reflect high MET signaling and dependence. We hypothesized that assays reflecting MET signaling associated protein complexes could redefine tumors dependent on MET and could add additional precision beyond genomic assessments.Experimental Design: We used biochemical approaches, cellular viability studies, and proximity ligation assays to assess MET dependence. We examined MET signaling complexes in lung cancer patient specimens (N = 406) and patient-derived xenograft (PDX) models of solid tumors (N = 308). We evaluated response to crizotinib in a MET-amplified cohort of PDX models of lung cancer (N = 6) and provide a case report of a lung cancer patient harboring a Δexon14 MET splice variant.Results: We found the interaction of MET with the adaptor protein GRB2 is necessary for oncogenic survival signaling by MET. MET-GRB2 complexes were identified only within MET-amplified PDX models and patient specimens but exhibit substantial variability. Lack of MET-GRB2 complexes was associated with lack of response to MET TKI in cell lines and PDX models. Presence of MET-GRB2 complexes can further subtype tumors with Δexon14 MET splice variants. Presence of these complexes correlated with response to crizotinib in one patient with Δexon14 MET lacking MET gene amplification.Conclusions: Proximity assays measuring MET-GRB2 signaling complexes provide novel insights into MET-mediated signaling and could complement current clinical genomics-based assay platforms. Clin Cancer Res; 23(22); 7084-96. ©2017 AACR.

Abstract 1565: OnPLS-based integrative proteogenomics analysis of lung squamous cell cancer

Introduction: Multivariate projection methods such as PCA and PLS has been widely applied for analysis of biological and chemical data. OnPLS is a recent extension to these methods suitable for integrative analysis of omics data. With OnPLS it is possible to compare multiple omics datasets to identify joint variation and variation locally unique for each of the studied datasets. OnPLS is a new approach for truly integrative analysis of omics data to be contrasted to commonly applied approaches limiting analysis to 1) comparing findings from individually analyzed blocks of data 2) pairwise comparison of individual probes.

Experimental: A Java based implementation of OnPLS was used for the statistical modeling. 116 lung squamous cell cancer samples were characterized using gene expression profiling and global proteomics. The OnPLS model was applied to jointly model variation between mRNA and protein expression. Enrichment analysis of factor loadings was performed using the Enrichr tools to identify biological mechanisms explained by the different joint and unique components of the OnPLS model.

Results: Using a cross-validation procedure the model with the highest predictive ability was calculated having two joint components and one locally unique component for each of the proteomics and gene expression datasets. The model explained 21.9% of the variation in the expression data and 26.1% of the variation in the proteomics data. The first joint component captures the highest degree of common variation between mRNA and protein activity. From the mRNA data, this component is related to immune infiltrates, especially monocytes and B-cells, whereas this component is related to extracellular matrix activity from the protein data. This suggests covariance of mRNA immune-related gene expression and extracellular matrix-related protein expression. As expected, local variation specific to the protein measurements involved regulation of protein activation and processing. mRNA-specific variation is related to keratinization, a key process in squamous cell cancer.

Conclusion: OnPLS offers an interesting approach for integrative analysis of omics data. Applying this approach to proteo-genomics data of lung squamous cell cancers suggest similar patterns of activity is represented in protein and gene expression data, however the biological processes associated with this activity may be distinct.

Citation Format: Fredrik Pettersson, Paul A. Stewart, Robbert J. Slebos, Eric A. Welsh, Ling Cen, Yonghong Zhang, Zhihua Chen, Chia-Ho Cheng, Guolin Zhang, Bin Fang, Victoria Izumi, Sean Yoder, Katherine Fellows, Y Ann Chen, Jamie K. Teer, Steven Eschrich, John M. Koomen, Anders Berglund, Eric B. Haura. OnPLS-based integrative proteogenomics analysis of lung squamous cell cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1565. doi:10.1158/1538-7445.AM2017-1565

Abstract 206: Proteogenomic classifications and outcome in squamous cell carcinoma of the lung

Introduction: Genomic analyses have yielded a tremendous amount of knowledge on the genetic changes in lung cancers, but translating this information into actionable data benefitting patients has proven difficult. The integration of proteomic analyses with genomics and gene expression profiling allows a more detailed description of the biological processes, thus improving our understanding of cancer phenotypes. These insights can potentially be used for better classification and help to guide patient selection for targeted therapies.

Experimental: We analyzed 116 surgically resected squamous cell lung carcinoma samples for copy-number alterations, gene expression profiling, targeted exome-sequencing and global proteomic profiling. The cohort consisted of mostly early stage tumors (83% Stage I or II) with complete follow-up (median 58 months). Copy number status was analyzed using the Affymetrix CytoScan array, DNA mutation status was assessed using a customized version of the Agilent Comprehensive Cancer Panel for targeted sequencing, and gene expression profiling was carried out by RNA-sequencing. Proteomic analysis was performed using TMT labeling, 12- fraction bRPLC separation and LC-MS/MS analysis with a Thermo Q-Exactive mass spectrometer. Database searches were performed using multiple search engines against RefSeq version 78, and summarized using IDPicker 3.

Results: The non-redundant protein inventory consisted of more than 6,000 protein groups with a protein FDR &lt;5%. Tumors were classified according to well established gene expression criteria into 4 classes: Classical, Basal, Primitive and Secretory. At the protein level, the Classical subtype was associated with xenobiotic and energy metabolism; the Basal subtype with defense responses and extracellular matrix changes; the Primitive subtype with nucleic acid metabolism; and the Secretory subtype with p38 signaling. These findings confirm and expand on previous mRNA expression studies of squamous cell lung carcinoma. Proteomics-based classification identified two sub-categories within the Classical subtype, which were characterized by inflammatory and stress response signaling. Within this group, patients with high expression of inflammation-associated proteins had better cancer-specific survival than those with low expression (p=0.04, Log-rank test). Targeted exome sequencing of 154 cancer-associated genes revealed frequent mutations in TP53, CDKN2A, NFE2L2, and other genes. Proteomic expression of genes located in amplified chromosomal regions was used to identify driver genes in squamous cell lung carcinoma.

Conclusion: Our results provide new biological insights from the addition of protein measurements to genomic datasets that have the potential to improve classification. The data suggest that proteins involved in immune responses are important for the biological behavior and outcome of the Classical subtype in squamous cell lung carcinoma.

Citation Format: Robbert J.C. Slebos, Paul A. Stewart, Eric A. Welsh, Ling Cen, Yonghong Zhang, Zhihua Chen, Chia-Ho Cheng, Fredrik Pettersson, Anders E. Berglund, Guolin Zhang, Bin Fang, Victoria Izumi, Sean J. Yoder, Katherine M. Fellows, Y Ann Chen, Jamie Teer, Steven Eschrich, John Koomen, Eric Haura. Proteogenomic classifications and outcome in squamous cell carcinoma of the lung [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 206. doi:10.1158/1538-7445.AM2017-206

Self-adjustment and disintegration threshold of Langmuir solitons in inhomogeneous plasmas

Dynamics of Langmuir solitons in the presence of a background density gradient is investigated numerically, including cases with steep gradients to the extent the solitons can disintegrate. The disintegration threshold is explained by regarding the electric field part of the soliton as a point mass moving along the self-generated potential well corresponding to the density cavity. On the other hand, it is demonstrated that the Langmuir solitons are robust when the density gradient is below the threshold. During the acceleration phase toward low density regions, Langmuir solitons adjust themselves to balance the electric field pressure and the negative plasma pressure by expelling the imbalanced portion as density cavities at the sound velocity. When the density gradient is below the disintegration threshold, the electric field part of the soliton bounces back and forth within the potential well suggesting the solitons have internal structures.

Integration of Population-Level Genotype Data with Functional Annotation Reveals Over-Representation of Long Noncoding RNAs at Ovarian Cancer Susceptibility Loci

BACKGROUND

Genome-wide association studies (GWAS) have identified multiple loci associated with epithelial ovarian cancer (EOC) susceptibility, but further progress requires integration of epidemiology and biology to illuminate true risk loci below genome-wide significance levels (P < 5 × 10-8). Most risk SNPs lie within non-protein-encoding regions, and we hypothesize that long noncoding RNA (lncRNA) genes are enriched at EOC risk regions and represent biologically relevant functional targets.

METHODS

Using imputed GWAS data from about 18,000 invasive EOC cases and 34,000 controls of European ancestry, the GENCODE (v19) lncRNA database was used to annotate SNPs from 13,442 lncRNAs for permutation-based enrichment analysis. Tumor expression quantitative trait locus (eQTL) analysis was performed for sub-genome-wide regions (1 × 10-5 > P > 5 × 10-8) overlapping lncRNAs.

RESULTS

Of 5,294 EOC-associated SNPs (P < 1.0 × 10-5), 1,464 (28%) mapped within 53 unique lncRNAs and an additional 3,484 (66%) SNPs were correlated (r2 > 0.2) with SNPs within 115 lncRNAs. EOC-associated SNPs comprised 130 independent regions, of which 72 (55%) overlapped with lncRNAs, representing a significant enrichment (P = 5.0 × 10-4) that was more pronounced among a subset of 5,401 lncRNAs with active epigenetic regulation in normal ovarian tissue. EOC-associated lncRNAs and their putative promoters and transcription factors were enriched for biologically relevant pathways and eQTL analysis identified five novel putative risk regions with allele-specific effects on lncRNA gene expression.

CONCLUSIONS

lncRNAs are significantly enriched at EOC risk regions, suggesting a mechanistic role for lncRNAs in driving predisposition to EOC.

IMPACT

lncRNAs represent key candidates for integrative epidemiologic and functional studies. Further research on their biologic role in ovarian cancer is indicated. Cancer Epidemiol Biomarkers Prev; 26(1); 116-25. ©2016 AACR.

A phase IB study of ipilimumab with peginterferon alfa-2b in patients with unresectable melanoma

Background

Ipilimumab and peginterferon alfa-2b are established systemic treatment options for melanoma that have distinct mechanisms of action. Given the need for improved therapies for advanced melanoma, we conducted an open-label, single institution, phase Ib study to assess the safety and tolerability of using these two agents in combination.

Methods

Study treatment consisted of ipilimumab given every 3 weeks, for a total of four infusions, concurrent with peginterferon alfa-2b administered subcutaneous weekly for a total of 12 weeks. This was followed by maintenance therapy with peginterferon alfa-2b administered subcutaneously weekly for up to 144 additional weeks. The study was designed as a two-stage dose escalation scheme with continuous dose-limiting toxicity monitoring during the induction phase.

Results

Thirty one patients received at least 1 dose of study treatment and 30 were assessable for efficacy endpoints. We found that ipilimumab at 3 mg/kg dosing with peginterfeon alfa-2b at 2 μg/kg/week was the maximum tolerated dose of this combination. The incidence of grade 3 drug-related adverse events (AEs) was 45.2%. There were no grade 4/5 AEs. The overall response rate was 40% by immune-related response criteria. Median progression-free survival was 5.9 months. The median overall survival was not reached with at a median follow-up of 35.8 months.

Conclusions

We report that the combination of ipilimumab at 3 mg/kg dosing combined with peginterfeon alfa-2b at 2 μg/kg/week demonstrated an acceptable toxicity profile and a promising efficacy signal. Further study of this combination is warranted.

Trial registration

ClinicalTrials.gov identifier: NCT01496807, Registered December 19th, 2011.

PALB2, CHEK2 and ATM rare variants and cancer risk: data from COGS

BACKGROUND

The rarity of mutations in PALB2, CHEK2 and ATM make it difficult to estimate precisely associated cancer risks. Population-based family studies have provided evidence that at least some of these mutations are associated with breast cancer risk as high as those associated with rare BRCA2 mutations. We aimed to estimate the relative risks associated with specific rare variants in PALB2, CHEK2 and ATM via a multicentre case-control study.

METHODS

We genotyped 10 rare mutations using the custom iCOGS array: PALB2 c.1592delT, c.2816T>G and c.3113G>A, CHEK2 c.349A>G, c.538C>T, c.715G>A, c.1036C>T, c.1312G>T, and c.1343T>G and ATM c.7271T>G. We assessed associations with breast cancer risk (42 671 cases and 42 164 controls), as well as prostate (22 301 cases and 22 320 controls) and ovarian (14 542 cases and 23 491 controls) cancer risk, for each variant.

RESULTS

For European women, strong evidence of association with breast cancer risk was observed for PALB2 c.1592delT OR 3.44 (95% CI 1.39 to 8.52, p=7.1×10-5), PALB2 c.3113G>A OR 4.21 (95% CI 1.84 to 9.60, p=6.9×10-8) and ATM c.7271T>G OR 11.0 (95% CI 1.42 to 85.7, p=0.0012). We also found evidence of association with breast cancer risk for three variants in CHEK2, c.349A>G OR 2.26 (95% CI 1.29 to 3.95), c.1036C>T OR 5.06 (95% CI 1.09 to 23.5) and c.538C>T OR 1.33 (95% CI 1.05 to 1.67) (p≤0.017). Evidence for prostate cancer risk was observed for CHEK2 c.1343T>G OR 3.03 (95% CI 1.53 to 6.03, p=0.0006) for African men and CHEK2 c.1312G>T OR 2.21 (95% CI 1.06 to 4.63, p=0.030) for European men. No evidence of association with ovarian cancer was found for any of these variants.

CONCLUSIONS

This report adds to accumulating evidence that at least some variants in these genes are associated with an increased risk of breast cancer that is clinically important.

Inherited variants affecting RNA editing may contribute to ovarian cancer susceptibility: results from a large-scale collaboration

RNA editing in mammals is a form of post-transcriptional modification in which adenosine is converted to inosine by the adenosine deaminases acting on RNA (ADAR) family of enzymes. Based on evidence of altered ADAR expression in epithelial ovarian cancers (EOC), we hypothesized that single nucleotide polymorphisms (SNPs) in ADAR genes modify EOC susceptibility, potentially by altering ovarian tissue gene expression. Using directly genotyped and imputed data from 10,891 invasive EOC cases and 21,693 controls, we evaluated the associations of 5,303 SNPs in ADAD1, ADAR, ADAR2, ADAR3, and SND1. Unconditional logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI), with adjustment for European ancestry. We conducted gene-level analyses using the Admixture Maximum Likelihood (AML) test and the Sequence-Kernel Association test for common and rare variants (SKAT-CR). Association analysis revealed top risk-associated SNP rs77027562 (OR (95% CI)= 1.39 (1.17-1.64), P=1.0x10-4) in ADAR3 and rs185455523 in SND1 (OR (95% CI)= 0.68 (0.56-0.83), P=2.0x10-4). When restricting to serous histology (n=6,500), the magnitude of association strengthened for rs185455523 (OR=0.60, P=1.0x10-4). Gene-level analyses revealed that variation in ADAR was associated (P<0.05) with EOC susceptibility, with PAML=0.022 and PSKAT-CR=0.020. Expression quantitative trait locus analysis in EOC tissue revealed significant associations (P<0.05) with ADAR expression for several SNPs in ADAR, including rs1127313 (G/A), a SNP in the 3' untranslated region. In summary, germline variation involving RNA editing genes may influence EOC susceptibility, warranting further investigation of inherited and acquired alterations affecting RNA editing.

Coexpression and expression quantitative trait loci analyses of the angiogenesis gene-gene interaction network in prostate cancer

BACKGROUND

Prostate cancer (PCa) shows a substantial clinical heterogeneity. The existing risk classification for PCa prognosis based on clinical factors is not sufficient. Although some biomarkers for PCa aggressiveness have been identified, their underlying functional mechanisms are still unclear. We previously reported a gene-gene interaction network associated with PCa aggressiveness based on single nucleotide polymorphism (SNP)-SNP interactions in the angiogenesis pathway. The goal of this study is to investigate potential functional evidence of the involvement of the genes in this gene-gene interaction network.

METHODS

A total of 11 angiogenesis genes were evaluated. The crosstalks among genes were examined through coexpression and expression quantitative trait loci (eQTL) analyses. The study population is 352 Caucasian PCa patients in the Cancer Genome Atlas (TCGA) study. The pairwise coexpressions among the genes of interest were evaluated using the Spearman coefficient. The eQTL analyses were tested using the Kruskal-Wallis test.

RESULTS

Among all within gene and 55 possible pairwise gene evaluations, 12 gene pairs and one gene (MMP16) showed strong coexpression or significant eQTL evidence. There are nine gene pairs with a strong correlation (Spearman correlation ≥0.6, P<1×10^-13). The top coexpressed gene pairs are EGFR-SP1 (r=0.73), ITGB3-HSPG2 (r=0.71), ITGB3-CSF1 (r=0.70), MMP16-FBLN5 (r=0.68), ITGB3-MMP16 (r=0.65), ITGB3-ROBO1 (r=0.62), CSF1-HSPG2 (r=0.61), CSF1-FBLN5 (r=0.6), and CSF1-ROBO1 (r=0.60). One cis-eQTL in MMP16 and five trans-eQTLs (MMP16-ESR1, ESR1-ROBO1, CSF1-ROBO1, HSPG2-ROBO1, and FBLN5-CSF1) are significant with a false discovery rate q value less than 0.2.

CONCLUSIONS

These findings provide potential biological evidence for the gene-gene interactions in this angiogenesis network. These identified interactions between the angiogenesis genes not only provide information for PCa etiology mechanism but also may serve as integrated biomarkers for building a risk prediction model for PCa aggressiveness.

Cross-Cancer Genome-Wide Analysis of Lung, Ovary, Breast, Prostate, and Colorectal Cancer Reveals Novel Pleiotropic Associations

Identifying genetic variants with pleiotropic associations can uncover common pathways influencing multiple cancers. We took a two-stage approach to conduct genome-wide association studies for lung, ovary, breast, prostate, and colorectal cancer from the GAME-ON/GECCO Network (61,851 cases, 61,820 controls) to identify pleiotropic loci. Findings were replicated in independent association studies (55,789 cases, 330,490 controls). We identified a novel pleiotropic association at 1q22 involving breast and lung squamous cell carcinoma, with eQTL analysis showing an association with ADAM15/THBS3 gene expression in lung. We also identified a known breast cancer locus CASP8/ALS2CR12 associated with prostate cancer, a known cancer locus at CDKN2B-AS1 with different variants associated with lung adenocarcinoma and prostate cancer, and confirmed the associations of a breast BRCA2 locus with lung and serous ovarian cancer. This is the largest study to date examining pleiotropy across multiple cancer-associated loci, identifying common mechanisms of cancer development and progression. Cancer Res; 76(17); 5103-14. ©2016 AACR.

Exome genotyping arrays to identify rare and low frequency variants associated with epithelial ovarian cancer risk

Rare and low frequency variants are not well covered in most germline genotyping arrays and are understudied in relation to epithelial ovarian cancer (EOC) risk. To address this gap, we used genotyping arrays targeting rarer protein-coding variation in 8,165 EOC cases and 11,619 controls from the international Ovarian Cancer Association Consortium (OCAC). Pooled association analyses were conducted at the variant and gene level for 98,543 variants directly genotyped through two exome genotyping projects. Only common variants that represent or are in strong linkage disequilibrium (LD) with previously-identified signals at established loci reached traditional thresholds for exome-wide significance (P < 5.0 × 10 -  7). One of the most significant signals (Pall histologies = 1.01 × 10 -  13;Pserous = 3.54 × 10 -  14) occurred at 3q25.31 for rs62273959, a missense variant mapping to the LEKR1 gene that is in LD (r2 = 0.90) with a previously identified 'best hit' (rs7651446) mapping to an intron of TIPARP. Suggestive associations (5.0 × 10 -  5 > P≥5.0 ×10 -  7) were detected for rare and low-frequency variants at 16 novel loci. Four rare missense variants were identified (ACTBL2 rs73757391 (5q11.2), BTD rs200337373 (3p25.1), KRT13 rs150321809 (17q21.2) and MC2R rs104894658 (18p11.21)), but only MC2R rs104894668 had a large effect size (OR = 9.66). Genes most strongly associated with EOC risk included ACTBL2 (PAML = 3.23 × 10 -  5; PSKAT-o = 9.23 × 10 -  4) and KRT13 (PAML = 1.67 × 10 -  4; PSKAT-o = 1.07 × 10 -  5), reaffirming variant-level analysis. In summary, this large study identified several rare and low-frequency variants and genes that may contribute to EOC susceptibility, albeit with possible small effects. Future studies that integrate epidemiology, sequencing, and functional assays are needed to further unravel the unexplained heritability and biology of this disease.

Tyrosine Kinase Signaling in Clear Cell and Papillary Renal Cell Carcinoma Revealed by Mass Spectrometry-Based Phosphotyrosine Proteomics

PURPOSE

Targeted therapies in renal cell carcinoma (RCC) are limited by acquired resistance. Novel therapeutic targets are needed to combat resistance and, ideally, target the unique biology of RCC subtypes.

EXPERIMENTAL DESIGN

Tyrosine kinases provide critical oncogenic signaling and their inhibition has significantly impacted cancer care. To describe a landscape of tyrosine kinase activity in RCC that could inform novel therapeutic strategies, we performed a mass spectrometry-based system-wide survey of tyrosine phosphorylation in 10 RCC cell lines as well as 15 clear cell and 15 papillary RCC human tumors. To prioritize identified tyrosine kinases for further analysis, a 63 tyrosine kinase inhibitor (TKI) drug screen was performed.

RESULTS

Among the cell lines, 28 unique tyrosine phosphosites were identified across 19 kinases and phosphatases including EGFR, MET, JAK2, and FAK in nearly all samples. Multiple FAK TKIs decreased cell viability by at least 50% and inhibited RCC cell line adhesion, invasion, and proliferation. Among the tumors, 49 unique tyrosine phosphosites were identified across 44 kinases and phosphatases. FAK pY576/7 was found in all tumors and many cell lines, whereas DDR1 pY792/6 was preferentially enriched in the papillary RCC tumors. Both tyrosine kinases are capable of transmitting signals from the extracellular matrix and emerged as novel RCC therapeutic targets.

CONCLUSIONS

Tyrosine kinase profiling informs novel therapeutic strategies in RCC and highlights the unique biology among kidney cancer subtypes. Clin Cancer Res; 22(22); 5605-16. ©2016 AACR.

Fibronectin induction abrogates the BRAF inhibitor response of BRAF V600E/PTEN-null melanoma cells

The mechanisms by which some melanoma cells adapt to Serine/threonine-protein kinase B-Raf (BRAF) inhibitor therapy are incompletely understood. In the present study, we used mass spectrometry-based phosphoproteomics to determine how BRAF inhibition remodeled the signaling network of melanoma cell lines that were BRAF mutant and PTEN null. Short-term BRAF inhibition was associated with marked changes in fibronectin-based adhesion signaling that were PTEN dependent. These effects were recapitulated through BRAF siRNA knockdown and following treatment with chemotherapeutic drugs. Increased fibronectin expression was also observed in mouse xenograft models as well as specimens from melanoma patients undergoing BRAF inhibitor treatment. Analysis of a melanoma tissue microarray showed loss of PTEN expression to predict for a lower overall survival, with a trend for even lower survival being seen when loss of fibronectin was included in the analysis. Mechanistically, the induction of fibronectin limited the responses of these PTEN-null melanoma cell lines to vemurafenib, with enhanced cytotoxicity observed following the knockdown of either fibronectin or its receptor α5β1 integrin. This in turn abrogated the cytotoxic response to BRAF inhibition via increased AKT signaling, which prevented the induction of cell death by maintaining the expression of the pro-survival protein Mcl-1. The protection conveyed by the induction of FN expression could be overcome through combined treatment with a BRAF and PI3K inhibitor.

NSD1 mutations generate a genome-wide DNA methylation signature

Sotos syndrome (SS) represents an important human model system for the study of epigenetic regulation; it is an overgrowth/intellectual disability syndrome caused by mutations in a histone methyltransferase, NSD1. As layered epigenetic modifications are often interdependent, we propose that pathogenic NSD1 mutations have a genome-wide impact on the most stable epigenetic mark, DNA methylation (DNAm). By interrogating DNAm in SS patients, we identify a genome-wide, highly significant NSD1^+/−-specific signature that differentiates pathogenic NSD1 mutations from controls, benign NSD1 variants and the clinically overlapping Weaver syndrome. Validation studies of independent cohorts of SS and controls assigned 100% of these samples correctly. This highly specific and sensitive NSD1^+/− signature encompasses genes that function in cellular morphogenesis and neuronal differentiation, reflecting cardinal features of the SS phenotype. The identification of SS-specific genome-wide DNAm alterations will facilitate both the elucidation of the molecular pathophysiology of SS and the development of improved diagnostic testing.

Sotos syndrome is an growth syndrome characterized by advanced growth in childhood, characteristic facial appearance and intellectual disability. Here the authors identify a genome-wide DNA methylation signature that accurately diagnoses Sotos Syndrome and distinguishes it from similar conditions.

Epithelial-Mesenchymal Transition (EMT) Gene Variants and Epithelial Ovarian Cancer (EOC) Risk

Epithelial-mesenchymal transition (EMT) is a process whereby epithelial cells assume mesenchymal characteristics to facilitate cancer metastasis. However, EMT also contributes to the initiation and development of primary tumors. Prior studies that explored the hypothesis that EMT gene variants contribute to epithelial ovarian carcinoma (EOC) risk have been based on small sample sizes and none have sought replication in an independent population. We screened 15,816 single-nucleotide polymorphisms (SNPs) in 296 genes in a discovery phase using data from a genome-wide association study of EOC among women of European ancestry (1,947 cases and 2,009 controls) and identified 793 variants in 278 EMT-related genes that were nominally (P < 0.05) associated with invasive EOC. These SNPs were then genotyped in a larger study of 14,525 invasive-cancer patients and 23,447 controls. A P-value <0.05 and a false discovery rate (FDR) <0.2 were considered statistically significant. In the larger dataset, GPC6/GPC5 rs17702471 was associated with the endometrioid subtype among Caucasians (odds ratio (OR) = 1.16, 95% CI = 1.07-1.25, P = 0.0003, FDR = 0.19), whereas F8 rs7053448 (OR = 1.69, 95% CI = 1.27-2.24, P = 0.0003, FDR = 0.12), F8 rs7058826 (OR = 1.69, 95% CI = 1.27-2.24, P = 0.0003, FDR = 0.12), and CAPN13 rs1983383 (OR = 0.79, 95% CI = 0.69-0.90, P = 0.0005, FDR = 0.12) were associated with combined invasive EOC among Asians. In silico functional analyses revealed that GPC6/GPC5 rs17702471 coincided with DNA regulatory elements. These results suggest that EMT gene variants do not appear to play a significant role in the susceptibility to EOC.

Abstract 4635: Inherited variants affecting RNA editing may contribute to ovarian cancer susceptibility

Background: Recent bioinformatic analyses and high-throughput sequencing efforts have revealed that RNA editing is a widespread post-transcriptional modification that affects non-coding repetitive elements throughout the genome. This modification, which involves the conversion of adenosine into inosine, is mediated by the action of the adenosine deaminases acting on RNA (ADAR) family of enzymes. Based on reports of dysfunctional ADAR expression in epithelial ovarian cancers (EOC), we hypothesized that single nucleotide polymorphisms (SNPs) in five ADAR genes (ADAD1, ADAR1, ADAR2, ADAR3, SND1) may contribute to EOC susceptibility, potentially by altering the expression of corresponding genes in ovarian tissues.

Methods: Using directly genotyped and imputed data from 10,891 invasive EOC cases and 21,693 healthy controls of European ancestry represented in the international Collaborative Oncological Gene-environment Study, we evaluated the frequency of 7,133 SNPs in 5 RNA editing genes. Unconditional logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) between genotypes and case status under a log-additive genetic model, with adjustment for the first five principal components representing European ancestry. Subgroup analysis was conducted for the four main histologic sub-types of EOC. We also aggregated SNP-level data and conducted gene-level analyses using the Admixture Maximum Likelihood (AML) test and the Sequence-Kernel Association test for the combined effect of common and rare variants (SKAT-CR).

Results: Association analysis revealed a top risk-associated SNP (OR (95% CI) = 1.39 (1.17-1.64)) in ADAR3 with P = 1.3 x10−4, 17 additional SNPs in ADAR1, ADAR3, or SND1 with P = 10−4, and 51 SNPs with P = 10−3; this observed number of statistically-significant SNPs was greater than expected. When restricting to the 6,500 invasive serous adenocarcinomas, the magnitude of association strengthened for numerous SNPs. Exploratory analysis for the less common histologic subtypes (endometrioid (n = 1,439), mucinous (n = 696), and clear cell (n = 660)) revealed SNP-level associations (P&lt;10−3) unique to each sub-type. Gene-level analyses based on AML and SKAT-CR revealed that ADAR1 was globally associated (P&lt;0.10) with susceptibility to invasive EOC, with P = 0.024 and P = 0.023, respectively. Expression quantitative trait locus analysis is underway to evaluate associations between genotype and gene expression in EOC and precursor tissues using data from The Cancer Genome Atlas Project and other sources.

Conclusions: Preliminary data from this large-scale collaboration suggest that germline variation involving RNA editing genes may influence susceptibility to EOC. This novel finding warrants further investigation, as inherited and acquired alterations affecting RNA editing may serve as important biological mechanisms that promote the development of EOC and possibly other malignancies.

Citation Format: Jennifer Permuth-Wey, Brett M. Reid, Y. Ann Chen, Hui-Yi Lin, Alvaro Monteiro, Zhihua Chen, Andrew Berchuck, Georgia Chenevix-Trench, Jennifer Doherty, Simon Gayther, Ellen Goode, Edwin Iversen, Leigh Pearce, Paul D. P. Pharoah, Catherine Phelan, Susan Ramus, Mary Anne Rossing, Joellen Schildkraut, Thomas Sellers, on behalf of the Ovarian Cancer Association Consortium. Inherited variants affecting RNA editing may contribute to ovarian cancer susceptibility. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4635. doi:10.1158/1538-7445.AM2015-4635

Abstract 4633: Evidence that long non-coding RNA variants associate with epithelial ovarian cancer risk

Background: Genome wide association studies (GWAS) have identified 20 loci associated with epithelial ovarian cancer (EOC) risk. Additional EOC risk loci await identification, and biological approaches may represent a useful strategy for overcoming sample size limitations. The ENCODE project recently concluded that only ∼1.2% of the genome encodes proteins, but at least 20% exhibits biological function and over 80% exhibits biochemical indices of function. Post-GWAS follow-up studies have firmly established that some associations are due to inter-individual differences in non-coding RNAs (ncRNAs). To estimate the magnitude of impact of variants in long non-coding RNAs (lncRNAs), we assessed enrichment of EOC-associated SNPs in lncRNA regions by comparing the density of EOC-associated loci between lncRNA regions, non-lncRNA regions, and the whole genome.

Methods: The study population included ∼18,000 invasive EOC cases and 34,000 healthy controls of European ancestry from the Ovarian Cancer Association Consortium with GWAS data imputed to 1000 Genomes Project (1KGP) density. Density was compared with two measures: average chromosome length required for one EOC-associated SNP (kb/locus) and average number of tested SNPs containing one EOC-associated SNP (SNPs/locus). Coordinates and annotation for 13,870 lncRNA genes were downloaded from the publicly available GENCODE (v19) database and were used to annotate SNPs from the 1KGP imputed GWAS data, yielding 13,192 lncRNA genes with biallelic variants imputed at rsquare ≥0.25. A SNP was considered EOC-associated if it reached a significance level of P&lt;10−5.

Results: Genome-wide, 11.6% of the 15,123,646 tested SNPs fell within lncRNA regions. Of 5,294 EOC-associated SNPs that were identified, 27.7% were located within lncRNAs, a higher frequency than expected (&lt;v:shape style = “WIDTH: 16.5pt; HEIGHT: 18pt” id = _x0000_i1026 equationxml = ‘14pχ2′ type = “#_x0000_t75”&gt; = 9.35×10−22). Additionally, EOC-associated SNPs were located on average every 237.6 kb (or 1204 tested SNPs) in lncRNA regions versus every 657.7 kb (or 3489 SNPS) in non-lncRNA regions and every 541.5 kb (or 2857 SNPs) in the whole genome, clearly demonstrating an enrichment of EOC-associated loci in lncRNA regions. A total of 1,464 lncRNA SNPs from 53 unique lncRNAs associated with EOC risk (P&lt;10−5); 70 of the identified lncRNA SNPs had P-values between 10−20 and 10−32, and 221 had P-values between 10−10 and 10−15, representing 21 unique regions &gt; 500kb apart.

Conclusions: These results justify efforts to integrate functional and population level genetic data on lncRNA regions to explore a new paradigm that addresses the problem of the missing heritability for cancer where restrictions in sample size and statistical power limit the ability to discover additional risk loci.

Citation Format: Thomas A. Sellers, Brett M. Reid, Y. Ann Chen, Hui-Yi Lin, Edward Richards, Jamie Teer, Alvaro Monteiro, Zhihua Chen, Andrew Berchuck, Georgia Chenevix-Trench, Jennifer Doherty, Ellen Goode, Edwin Iverson, Leigh Pearce, Paul Pharoah, Catherine Phelan, Susan Ramus, Mary Anne Rossing, Joellen Schildkraut, Jin Cheng, Simon Gayther, Jennifer Permuth-Wey, on behalf of the Ovarian Cancer Association Consortium. Evidence that long non-coding RNA variants associate with epithelial ovarian cancer risk. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4633. doi:10.1158/1538-7445.AM2015-4633

Abstract 4634: Variants within super-enhancer regulatory elements associate with epithelial ovarian cancer risk

Background: Cell-type-specific super enhancers, or large clusters of mediator-rich enhancers, are highly transcribed regions of the genome with key functions in the maintenance of cell identity and control. These regulatory elements are easily perturbed and enriched for disease-associated sequence variation. Identification of disease-associated super-enhancers and investigation of their sequence variants may help identify important, biologically relevant associations previously overlooked by genome-wide studies. Thus, we sought to identify variants within ovarian tissue specific super-enhancers and investigate their association with epithelial ovarian cancer (EOC) susceptibility.

Methods: We utilized genotype data from a European population of ∼11,000 invasive EOC cases and 22,000 healthy controls from the Ovarian Cancer Association Consortium. A public catalog of 478 super-enhancers, identified by peak histone H3K27ac ChIP-seq signal in ovarian tissue, was used to identify 72,116 variants located within 344 super-enhancer regions. Unconditional logistic regression (log-additive model) was used to assess individual SNP-EOC risk associations. Additionally, we reviewed associations within 500 kb of super-enhancer regions to identify proximal associated variants. When LD structure indicated, we employed conditional analysis to determine independence of the super-enhancer signal. Gene-EOC risk associations were assessed with the Admixture Maximum Likelihood (AML) test and Sequence-Kernel Association Test (SKAT) for the combined effect of common and rare (MAF&lt;0.01) variants. Models were adjusted for population stratification using the first five principal components. To adjust for multiple comparisons, a false discovery rate of 10% was used.

Results: The most significant SNP observed was rs147487657 (p = 7.7×10−6) on locus 2q37.3 in the HDAC4 gene and there were an additional 12 SNPs with p&lt;1.0×10−4, although not significant at 10% FDR. Gene-level analyses identified two super-enhancers significantly associated with EOC risk. An enhancer at the previously reported 2q31 locus, containing HOXD8 and HOXD-AS2, associated (SKAT p = 4.3×10−5; AML p&lt;0.001) with the top SNP located within the 5′UTR of HOXD8 transcription factor (rs847163 (T&gt;C); p&lt;2.08×10−5). Conditional analysis did not identify an independent association within the super-enhancer region. The second EOC-associated super-enhancer identified was at locus 1q32 (SKAT p = 0.00052, AML p = 0.001) containing the CSRP1 gene. There were 6 SNPs with p&lt;0.001 and 16 SNPs with p&lt;0.01, all were inversely associated with risk and consistent with the top hit at rs927901 T&gt;C (OR = 0.94; 95% CI: 0.90-0.97; p = 2.1×10−4). Associations varied by histologic subtype, possibly due to variance in disease relevant super-enhancer cell-type.Conclusion: These findings suggest germline variation within super-enhancer regions may contribute to EOC susceptibility

Citation Format: Brett M. Reid, Jennifer Permuth-Wey, Y. Ann Chen, Hui-Yi Lin, Alvaro Monteiro, Zhihua Chen, Andrew Berchuck, Georgia Chenevix-Trench, Jennifer Doherty, Simon Gayther, Ellen L. Goode, Edwin Iversen, Leigh Pearce, Paul Pharoah, Catherine Phelan, Susan Ramus, Mary Anne Rossing, Joellen Schildkraut, Thomas Sellers, on behalf of the Ovarian Cancer Association Consortium. Variants within super-enhancer regulatory elements associate with epithelial ovarian cancer risk. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4634. doi:10.1158/1538-7445.AM2015-4634

A genome-wide investigation of microRNA expression identifies biologically-meaningful microRNAs that distinguish between high-risk and low-risk intraductal papillary mucinous neoplasms of the pancreas

BACKGROUND

Intraductal papillary mucinous neoplasms (IPMNs) are pancreatic ductal adenocarcinoma (PDAC) precursors. Differentiating between high-risk IPMNs that warrant surgical resection and low-risk IPMNs that can be monitored is a significant clinical problem, and we sought to discover a panel of mi(cro)RNAs that accurately classify IPMN risk status.

METHODOLOGY/PRINCIPAL FINDINGS

In a discovery phase, genome-wide miRNA expression profiling was performed on 28 surgically-resected, pathologically-confirmed IPMNs (19 high-risk, 9 low-risk) using Taqman MicroRNA Arrays. A validation phase was performed in 21 independent IPMNs (13 high-risk, 8 low-risk). We also explored associations between miRNA expression level and various clinical and pathological factors and examined genes and pathways regulated by the identified miRNAs by integrating data from bioinformatic analyses and microarray analysis of miRNA gene targets. Six miRNAs (miR-100, miR-99b, miR-99a, miR-342-3p, miR-126, miR-130a) were down-regulated in high-risk versus low-risk IPMNs and distinguished between groups (P<10-3, area underneath the curve (AUC) = 87%). The same trend was observed in the validation phase (AUC = 74%). Low miR-99b expression was associated with main pancreatic duct involvement (P = 0.021), and serum albumin levels were positively correlated with miR-99a (r = 0.52, P = 0.004) and miR-100 expression (r = 0.49, P = 0.008). Literature, validated miRNA:target gene interactions, and pathway enrichment analysis supported the candidate miRNAs as tumor suppressors and regulators of PDAC development. Microarray analysis revealed that oncogenic targets of miR-130a (ATG2B, MEOX2), miR-342-3p (DNMT1), and miR-126 (IRS-1) were up-regulated in high- versus low-risk IPMNs (P<0.10).

CONCLUSIONS

This pilot study highlights miRNAs that may aid in preoperative risk stratification of IPMNs and provides novel insights into miRNA-mediated progression to pancreatic malignancy. The miRNAs identified here and in other recent investigations warrant evaluation in biofluids in a well-powered prospective cohort of individuals newly-diagnosed with IPMNs and other pancreatic cysts and those at increased genetic risk for these lesions.

Does ethnic variability exist in the systemic exposures of oatp1a2 substrates–fexofenadine in taiwanese?

The aim of this study was to investigate differences in organic anion transporting polypeptide 1A2 activity among the Taiwanese population via an analysis of 3 pharmacokinetic studies completed in a total of 103 healthy male Taiwanese subjects. The pharmacokinetics of fexofenadine was measured as an indicator of organic anion transporting polypeptide 1A2 activity. Using the Kolmogorov-Smirnov test and quantile plots, the frequency distributions of area under the concentration-time curve and concentration were shown to be tri-modal and to represent 3 pharmacokinetic phenotypes. In a comparison with published data, the mean area under the concentration-time curve of fexofenadine in the Taiwanese subjects was similar to that in American, German, and Indian subjects, but significantly different from that in some Asian populations, including Korean and Japanese ethnic groups. These results suggested that Taiwanese subjects showed genetic variation in fexofenadine pharmacokinetics that was associated with differences in organic anion transporting polypeptide 1A2 activity.

Abstract 1614: Kinases in lung squamous cell carcinoma and inhibitor matching using quantitative activity-based protein profiling

Introduction: Squamous cell carcinoma (SCC) of the lung is an aggressive tumor even at an early stage, leading to poor patient outcomes. Furthermore, few treatment options are currently available. In order to address these clinical needs and add to the arsenal of treatment options, we combine activity-based protein profiling (ABPP) and liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM) biomarker measurements to evaluate ATP uptake by ∼200 kinases in frozen specimens acquired from 50 SCC patients. ABPP-LC-MRM also quantifies the displacement of ATP probes in these kinases by promiscuous inhibitors. The combination of kinase ATP uptake patterns and the interference between the drug and the ATP probe enables matching of therapeutics to individual patients. These surveys of kinase signaling landscapes can lead to novel options for patient treatment.

Experimental Procedures: ABPP-LC-MRM for enrichment and quantification of kinase ATP uptake was optimized using SCC cell lines, and a library of assays was developed from extensive LC-MS/MS data from different tumor types. Biomarker measurements were made for frozen tumor and normal specimens from 50 patients. In a pooled tumor proteome, ABPP-LC-MRM evaluated the reduction in ATP probe binding to map a panel of drugs to their target kinases.

Data Summary: The panel of ABPP-enriched proteins consists of &gt;200 kinases (&gt;15 tyrosine kinases). ABPP-LC-MRM analysis of SCC cell lines, including H157, H1581, H1703, H2170, H2286, H520, H596, and HCC366, indicates the ability to detect previously characterized oncogenic drivers. Because cancer cells have many drivers or significant plasticity in signaling, the ABPP-LC-MRM strategy enables readout of multiple kinases as targets for inhibition, which could support the design of rational combinations. For example, H2170 cells have high levels of ATP uptake by ErbB2 (matching its gene amplification), the Src family kinase, YES, and MEK isoforms. Therefore, combinations using MEKi, SRCi, and Lapatinib could have potential for treatment. In cell lines, viability assays were used to examine synergy of kinase inhibitors suggested by ABPP-LC-MRM. Comparison of kinase ATP uptake in tumor and normal tissues indicates potential drivers for each cancer that can be used for patient classification and matched to therapeutic strategies, including novel combinations of kinase inhibitors.

Conclusions: Proteomic quantification of kinase ATP uptake enables the evaluation of numerous hypotheses within the same sample. Evaluation of ABPP-LC-MRM analysis in cell lines and subsequent comparison of tumor and normal tissue specimens indicates the ability to detect oncogenic kinases that may be tumor drivers. The implementation of this platform can be a first step for understanding drug resistance and classifying patients for molecularly-driven selection of targeted therapy combinations.

Citation Format: Bin Fang, Elizabeth R. Wood, Jiannong Li, Y. Ann Chen, Stephen G. Brantley, Fumi Kinose, Wei Guan, Andrew R. Myers, Steven A. Eschrich, Eric B. Haura, John M. Koomen. Kinases in lung squamous cell carcinoma and inhibitor matching using quantitative activity-based protein profiling. [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 1614. doi:10.1158/1538-7445.AM2014-1614

Abstract 946: Exome genotyping array identifies rare and low-frequency variants that may be associated with ovarian cancer risk

Background: Common genetic variants identified by genome-wide association studies and follow-up genotyping initiatives only explain a small proportion of the heritability of epithelial ovarian cancer (EOC). We hypothesized that some of the missing heritability may be explained by rare (minor allele frequency (MAF) &lt;0.5%) and low-frequency (MAF 0.5-5%) protein-coding variants that are not well captured by genotyping arrays that focus on common variants. Methods: To examine the association between uncommon variants and EOC susceptibility, we genotyped 7,060 EOC cases and 6,712 controls from the Ovarian Cancer Association Consortium using the Affymetrix Axiom Exome Genotyping Array. This platform contains 300,785 putative functional coding variants selected from exome sequences of 12,000+ individuals representing multiple ethnicities and complex traits. After performing quality control (QC), we used unconditional logistic regression treating the number of minor alleles carried as an ordinal variable (log-additive model) to evaluate SNP-EOC risk associations. Genotype cluster plots were visually inspected for top-ranking variants to determine assay success, and allele frequencies of samples from the 1000 Genomes Project and other cohorts were evaluated for QC purposes. Results: A total of 13,318 samples (97%) passed QC, and 12,779 eligible samples (6,293 invasive serous and endometrioid cases and 6,486 controls) were included in the analyses. 280,737 (93%) of the 300,785 attempted markers were successfully genotyped and had call rates &gt;90%. After removing 31,436 monomorphic markers, the 249,301 remaining markers were included in association analyses. We confirmed variants at previously reported EOC susceptibility loci (9p22, 3q25, 17cen-q21.3, and 8q24), with p-values between 10-5 and 10-11. Several correlated low-frequency non-synonymous variants (MAF=5%) residing in a novel EOC susceptibility gene at 3q25.31 were risk-associated. The most significant variant at 3q25.31 had an OR=1.36 and p = 5.58x10-8. Also noteworthy is a rare variant at 15q15.1-q21.1 (MAF=0.5%) that introduces a stop codon in a gene belonging to the tyrosine kinase family (OR=0.39, CI=0.26-0.58, p = 4.52x10-6). We also identified a more common synonymous coding variant in a phosphatase at 6q21.3 that was associated with increased risk (OR=1.22, CI=1.13-1.33, p = 1.84x10-6, MAF=9.6%). Population stratification and gene-based analyses are underway to further examine the impact of the newly-identified variants on EOC risk. A meta-analysis to include data from an additional 2104 EOC cases and 2516 controls genotyped with Illumina's HumanExome Beadchip rare variant array is also underway. Functional analysis of the most promising variants will follow. Conclusions: Preliminary data from this large-scale study reveals novel rare and low-frequency variants that may influence susceptibility to epithelial ovarian cancer.

Citation Format: Jennifer Permuth-Wey, Y. Ann Chen, Zhihua Chen, Andrew Berchuck, Georgia Chenevix-Trench, Jennifer Doherty, Simon Gayther, Ellen L. Goode, Edwin Iversen, Alvaro N.A. Monteiro, Leigh Pearce, Paul D.P. Pharoah, Catherine M. Phelan, Ailith Pirie, Susan Ramus, Mary Ann Rossing, Joellen M. Schildkraut, Thomas A. Sellers, on behalf of the Ovarian Cancer Association Consortium. Exome genotyping array identifies rare and low-frequency variants that may be associated with ovarian cancer risk. [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 946. doi:10.1158/1538-7445.AM2014-946