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NHS-muIL12 and avelumab combination treatment enhanced the necrotic fraction in EMT-6 tumors.

Purpose: To determine whether combination therapy with NHS-muIL12 and the anti-programmed death ligand 1 (PD-L1) antibody avelumab can enhance antitumor efficacy in preclinical models relative to monotherapies.Experimental Design: BALB/c mice bearing orthotopic EMT-6 mammary tumors and μMt− mice bearing subcutaneous MC38 tumors were treated with NHS-muIL12, avelumab, or combination therapy; tumor growth and survival were assessed. Tumor recurrence following remission and rechallenge was evaluated in EMT-6 tumor-bearing mice. Immune cell populations within spleen and tumors were evaluated by FACS and IHC. Immune gene expression in tumor tissue was profiled by NanoString® assay and plasma cytokine levels were determined by multiplex cytokine assay. The frequency of tumor antigen–reactive IFNγ-producing CD8+ T cells was evaluated by ELISpot assay.Results: NHS-muIL12 and avelumab combination therapy enhanced antitumor efficacy relative to either monotherapy in both tumor models. Most EMT-6 tumor–bearing mice treated with combination therapy had complete tumor regression. Combination therapy also induced the generation of tumor-specific immune memory, as demonstrated by protection against tumor rechallenge and induction of effector and memory T cells. Combination therapy enhanced cytotoxic NK and CD8+ T-cell proliferation and T-bet expression, whereas NHS-muIL12 monotherapy induced CD8+ T-cell infiltration into the tumor. Combination therapy also enhanced plasma cytokine levels and stimulated expression of a greater number of innate and adaptive immune genes compared with either monotherapy.Conclusions: These data indicate that combination therapy with NHS-muIL12 and avelumab increased antitumor efficacy in preclinical models, and suggest that combining NHS-IL12 and avelumab may be a promising approach to treating patients with solid tumors. Clin Cancer Res; 23(19); 5869–80. ©2017 AACR.

Supplementary Materials and Methods

We report the clinical activity, safety, and identification of a predictive biomarker for bintrafusp alfa, a first-in-class bifunctional fusion protein composed of the extracellular domain of TGFβRII (a TGF-β "trap") fused to a human IgG1 mAb blocking PD-L1, in patients with advanced triple-negative breast cancer (TNBC).In this expansion cohort of a global phase 1 study, patients with pretreated, advanced TNBC received bintrafusp alfa 1200 mg every 2 weeks intravenously until disease progression, unacceptable toxicity, or withdrawal. The primary objective was confirmed best overall response by RECIST 1.1 assessed per independent review committee (IRC).As of May 15, 2020, a total of 33 patients had received bintrafusp alfa, for a median of 6.0 (range, 2.0-48.1) weeks. The objective response rate was 9.1% (95% CI, 1.9%-24.3%) by IRC and investigator assessment. The median progression-free survival per IRC was 1.3 (95% CI, 1.2-1.4) months, and median overall survival was 7.7 (95% CI, 2.1-10.9) months. Twenty-five patients (75.8%) experienced treatment-related adverse events (TRAEs). Grade 3 TRAEs occurred in 5 patients (15.2%); no patients had a grade 4 TRAE. There was 1 treatment-related death (dyspnea, hemolysis, and thrombocytopenia in a patient with extensive disease at trial entry). Responses occurred independently of PD-L1 expression, and tumor RNAseq data identifiedBintrafusp alfa showed clinical activity and manageable safety in patients with heavily pretreated advanced TNBC.NCT02517398.

6020 Background: Bintrafusp alfa is a first-in-class bifunctional fusion protein composed of the extracellular domain of the TGF-βRII receptor (a TGF-β “trap”) fused to a human IgG1 mAb blocking PD-L1. A previous report of an expansion cohort from a phase 1 study (NCT02517398) suggested that bintrafusp alfa had a manageable safety profile and early signs of clinical activity in patients with heavily pretreated, advanced SCCHN after a median follow-up of 86.4 weeks. Here we report long-term efficacy and safety for this cohort. Methods: Patients with advanced SCCHN that progressed/recurred after platinum therapy in the recurrent/metastatic setting, or < 6 months after platinum therapy in the locally advanced setting, received bintrafusp alfa 1200 mg every 2 weeks until confirmed progressive disease, unacceptable toxicity, or trial withdrawal. The primary endpoint was confirmed best overall response assessed per RECIST 1.1 assessed by independent review committee (IRC); safety was a secondary endpoint. Results: As of May 15, 2020, 32 patients had received bintrafusp alfa for a median of 2.8 months (range, 0.5-29.9 months), no patient remained on treatment, and median follow-up to data cutoff was 41.7 months (range, 39.8-43.5 months). The objective response rate (ORR; 13%) was unchanged since the previous report; median duration of response (DOR) was increased at 21.4 months (95% CI, 5.5 months to not reached [NR]). While the clinical activity of bintrafusp alfa may be improved in patients with HPV-positive tumors (Table), outcomes were generally similar between PD-L1 subgroups (≥1% vs < 1% tumor cells). The overall safety profile was consistent with the previous report for this cohort, without grade 4 nor 5 treatment-related adverse events (TRAEs); no new TRAEs of grade 3 or that led to discontinuation of bintrafusp alfa were reported. Conclusions: With a median follow-up of over 3 years in patients with heavily pretreated advanced SCCHN, bintrafusp alfa showed sustained clinical activity and 3-year OS of 24.0%, which compares favorably to historical data. Clinical activity appeared to be greater in patients with HPV-positive tumors than those with HPV-negative tumors. The safety profile was manageable and consistent with earlier analysis. Further investigation of bintrafusp alfa in SCCHN and other HPV-associated cancers is ongoing. Clinical trial information: NCT02517398. [Table: see text]

Background: The Phase 2/3 APRIL-SLE study evaluated the safety and efficacy of atacicept, a dual inhibitor of the B lymphocyte stimulator (BLyS) and a proliferation-inducing ligand (APRIL), in systemic lupus erythematosus (SLE). Objectives: The goal of this post-hoc analysis was to use cell-based gene signatures on gene expression data from the APRIL-SLE study to identify clusters of patients with potential to flare and to assess clusters for differences in treatment effects of atacicept vs placebo. Methods: A published immune cell deconvolution algorithm (Abbas et al, 2009) was applied to whole-blood gene expression data from APRIL-SLE patients to identify relative proportions of 17 immune cell types. Patients were then grouped into clusters based on these immune cell profiles using a k-medoid clustering algorithm and were compared to each other based on patient characteristics, biomarkers and clinical efficacy. In addition, baseline expression and change in expression of putative APRIL-responder genes were compared among clusters. APRIL-responder genes were identified by combining differential expression results from the APRIL-SLE study (Week 52 vs Day 1 randomization) and tabalumab (targets BLyS only) Phase 3 studies (Week 52 vs baseline; GSE88887). Results: Patient gene expression data (N=105; placebo, n=30; atacicept 75 mg, n=40; atacicept 150 mg, n=35) were used to group patients into five main clusters (P1-P5) by predominant characteristic cells: P1, T helper cells; P2, plasma cells; P3, neutrophils and B cells; P4, B cells; P5, activated dendritic cells. Patients in P2 and P5 were more likely to have positive anti-dsDNA antibodies (≥30 IU/ml), elevated BLyS; ≥1.6 ng/ml, and high interferon gene signature in the blood than other those in other clusters. Patients in P2 were most likely to have low complement C3 and C4 levels. Placebo-group flare rates in P2 (100%), P4 (100%) and P5 (83%) were markedly higher than in P1 (33%) and P3 (29%). In P2, P4, and P5 the median time-to-flare was much lower with placebo (85, 98.5, and 115.5 days, respectively) than with atacicept 150 mg (over 364 days for all three clusters). A comparison of differentially-expressed genes from clinical studies of SLE patients treated with atacicept and tabalumab revealed possible APRIL-responder genes: SDC1, PARM1 and MZB1. These genes had a higher baseline expression in P2 and P4 compared with other clusters. SDC1 was reduced from baseline more in P2, P4, and P5 after atacicept treatment, while PARM1 and MZB1 decreased after atacicept treatment in P2 and P4. Conclusion: These post-hoc analyses revealed different subsets of SLE patients based on their molecular profiles. Atacicept may have different treatment effects in the identified patient subsets vs placebo, providing insights into potential mechanisms of flare in SLE. References: [1] Abbas AR, Wolslegel K, Seshasayee D, Modrusan Z, Clark HF. Deconvolution of blood microarray data identifies cellular activation patterns in systemic lupus erythematosus. PLoS ONE. 2009;4(7):e6098. Disclosure of Interests: Eileen Samy Employee of: Current employees of EMD Serono, Matthew Studham Employee of: Current employees of EMD Serono, Amy Kao Employee of: Current employees of EMD Serono, Philipp Haselmayer Employee of: Current employee of Merck KGaA, Peter Chang Employee of: Current employees of EMD Serono, P. Alexander Rolfe Employee of: Current employees of EMD Serono, David Wofsy Consultant for: GlaxoSmithKline – Member, data safety monitoring board Novartis – Member, data safety monitoring board Celgene – member, scientific advisory board, Julie DeMartino Shareholder of: Shares in Merck & Co, Employee of: Current employees of EMD Serono; Past employee of Merck & Co. & Roche, Robert Townsend Employee of: Current employees of EMD Serono

BackgroundBintrafusp alfa is a first-in-class bifunctional fusion protein composed of the extracellular domain of transforming growth factor (TGF)-βRII (a TGF-β ‘trap’) fused to a human IgG1 mAb blocking programmed cell death ligand 1. This is the largest analysis of patients with advanced, pretreated human papillomavirus (HPV)-associated malignancies treated with bintrafusp alfa.MethodsIn these phase 1 (NCT02517398) and phase 2 trials (NCT03427411), 59 patients with advanced, pretreated, checkpoint inhibitor-naive HPV-associated cancers received bintrafusp alfa intravenously every 2 weeks until progressive disease, unacceptable toxicity, or withdrawal. Primary endpoint was best overall response per Response Evaluation Criteria in Solid Tumors (RECIST) V.1.1; other endpoints included safety.ResultsAs of April 17, 2019 (phase 1), and October 4, 2019 (phase 2), the confirmed objective response rate per RECIST V.1.1 in the checkpoint inhibitor-naive, full-analysis population was 30.5% (95% CI, 19.2% to 43.9%; five complete responses); eight patients had stable disease (disease control rate, 44.1% (95% CI, 31.2% to 57.6%)). In addition, three patients experienced a delayed partial response after initial disease progression, for a total clinical response rate of 35.6% (95% CI, 23.6% to 49.1%). An additional patient with vulvar cancer had an unconfirmed response. Forty-nine patients (83.1%) experienced treatment-related adverse events, which were grade 3/4 in 16 patients (27.1%). No treatment-related deaths occurred.ConclusionBintrafusp alfa showed clinical activity and manageable safety and is a promising treatment in HPV-associated cancers. These findings support further investigation of bintrafusp alfa in patients with advanced, pretreated HPV-associated cancers.

Purpose HTG EdgeSeq Next Generation Sequencing (NGS) technology is a targeted RNA Sequencing (RNA-Seq) platform based on quantitative nuclease protection chemistry, which requires substantially less sample input than RNA-Seq (one formalin-fixed paraffin-embedded (FFPE) slide versus 4-6 slides). The automated library processor allows fast downstream NGS analysis, making it a promising technology for clinical application and companion diagnostics, especially in samples with limited availability. Given the differences from standard RNA-Seq protocols, it is critical to investigate the performance of HTG EdgeSeq compared to whole transcriptome RNA-Seq technology. We investigated the concordance between HTG EdgeSeq and RNA-Seq on a set of FFPE samples. Procedure The HTG EdgeSeq Oncology Biomarker Panel (OBP) is comprised of 2558 genes including genes relevant to immuno-oncology and oncology pathways. To evaluate the concordance between the two platforms, 57 FFPE samples from diverse tumor types and varying tumor content (16-100%) were analyzed. One slide was analyzed per sample with the HTG EdgeSeq OBP, while four to six slides were analyzed with whole transcriptome analysis using the Illumina TruSeq Total RNA library kit. A subset of samples and genes were selected for analysis by RT-qPCR using a customized Taqman 15 gene array. Data from the three platforms was analyzed and compared for concordance. Data Summary Fifty-three samples passed QC on the HTG EdgeSeq platform, while only 29 samples passed a distribution-based QC of the RNA-Seq. For samples that passed QC using both technologies, the median Spearman correlation was 0.73 (25th percentile was 0.70), indicating good, but not linear correlation. In the samples that failed RNA-Seq QC, the median Spearman correlation was 0.30. Probes with low correlation ( Conclusions HTG EdgeSeq produced fewer QC failures compared to whole transcriptome RNA-Seq while using less tissue. The resulting data showed sound correlation between RNA-Seq, HTG EdgeSeq, and RT-qPCR platforms, especially for genes with moderate to high expression, enabling relatively low risk translation between biomarker platforms. Further, these results were consistent across various cancer types. The characteristics demonstrated in this study support the potential use of HTG EdgeSeq for clinical biomarker applications. Citation Format: Dennis O'Rourke, Jorge F. Sanchez-Garcia, P. Alexander Rolfe, Alice Huang, Danyi Wang, Juergen Scheuenpflug, Zheng Feng. Comparison of HTG-edge targeted RNA sequencing platform with whole transcriptome RNA sequencing for clinical biomarker studies [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2016.

e21539 Background: Assessment of programmed death ligand-1 (PD-L1) protein expression using immunohistochemistry (IHC)-based tests is currently the only approved biomarker guiding treatment of non-small cell lung cancer (NSCLC) with checkpoint inhibitors. Robust scoring guidelines and suitable cut-offs should be defined specifically for each PD-L1 IHC assay and are critical for appropriate treatment decisions. Methods: We retrospectively applied a novel digital pathology (DP) solution that mimics the conventional tumor proportion scoring (TPS) of PD-L1. The exploratory DP solution was developed and validated using samples from 340 patients enrolled in the first- and second-line (1L and 2L) NSCLC cohorts of the avelumab phase 1 JAVELIN Solid Tumor trial (NCT01772004) and 792 patients with NSCLC enrolled in the avelumab phase 3 JAVELIN Lung 200 trial (NCT02395172). Efficacy analyses were conducted for overall survival (OS) and progression-free survival (PFS) using the full analysis set with evaluable imaging data (n = 136 and n = 544, respectively). Results: Comparison of DP and conventional, semiquantitative pathologist scoring resulted in a high correlation overall (Spearman correlation coefficient, 0.86), with comparable performance for prediction of outcome to treatment with avelumab in 2L NSCLC. Consistent with conventional scoring, median OS and median PFS in avelumab-treated patients increased with higher PD-L1 expression cut-offs: in patients with ≥1%, ≥50%, and ≥80% PD-L1 expression on tumors cells, median OS was 10.0 months (95% CI: 8.6-14.3), 13.8 months (95% CI: 9.6-20.4) and 18.5 months (95% CI: 9.6-not estimable), respectively; median PFS, 3.1 months (95% CI: 2.7-4.9), 5.5 months (95% CI: 2.8-8.3) and 5.6 months (95% CI: 2.8-9.9). Conclusions: Our results demonstrate the technical feasibility, robustness, and utility of DP in scoring PD-L1 IHC in clinical trial samples, achieving comparable performance to conventional, semiquantitative pathologist scoring. Furthermore, our study supports the manual pathologist scoring algorithm (TPS scoring) in NSCLC and the selection of higher cut-offs for the PD-L1 IHC Ab clone 73-10.

Introduction: Hepatocellular carcinoma (HCC) typically develops in cirrhotic livers, with increased programed death ligand 1 (PD-L1) and transforming growth factor beta (TGF-β) activity implicated in immunosuppression. Methods: In an observational study of HCC liver samples, we determined the incidence of PD-L1 and immune cell (IC) infiltrates, and signs of TGF-β activity. HCCs were characterized by the incidence and distribution of PD-L1+ cells, and CD8+, CD68+, and FoxP3+ infiltrating ICs in HCC and surrounding liver. Gene expression signatures (GESs) associated with TGF-β activity and ICs were evaluated by RNAseq. Results: In non-neoplastic cirrhotic and non-cirrhotic liver, PD-L1 occurred on sinusoidal lining cells (mostly Kupffer cells), endothelial cells and ICs. In HCC, PD-L1+ tumor cells were rare. Most PD-L1+ cells were identified as ICs. CD8+, CD68+, and FoxP3+ ICs were associated with HCC, particularly in the invasive margin. CD8+ cell incidence correlated with PD-L1+ cells, consistent with PD-L1 being upregulated in response to pre-existing cytotoxic T-lymphocyte activity. TGFB1 mRNA levels and TGF-β activation GES correlated with the strength of the tumor-associated macrophage GES. Conclusion: Inhibition of PD-L1+ ICs and TGF-β activity and their respective immunomodulatory pathways may contribute to antitumor effects in HCC.

Purpose: To determine whether combination therapy with NHS-muIL12 and the anti-programmed death ligand 1 (PD-L1) antibody avelumab can enhance antitumor efficacy in preclinical models relative to monotherapies. Experimental Design: BALB/c mice bearing orthotopic EMT-6 mammary tumors and μMt− mice bearing subcutaneous MC38 tumors were treated with NHS-muIL12, avelumab, or combination therapy; tumor growth and survival were assessed. Tumor recurrence following remission and rechallenge was evaluated in EMT-6 tumor-bearing mice. Immune cell populations within spleen and tumors were evaluated by FACS and IHC. Immune gene expression in tumor tissue was profiled by NanoString® assay and plasma cytokine levels were determined by multiplex cytokine assay. The frequency of tumor antigen–reactive IFNγ-producing CD8+ T cells was evaluated by ELISpot assay. Results: NHS-muIL12 and avelumab combination therapy enhanced antitumor efficacy relative to either monotherapy in both tumor models. Most EMT-6 tumor–bearing mice treated with combination therapy had complete tumor regression. Combination therapy also induced the generation of tumor-specific immune memory, as demonstrated by protection against tumor rechallenge and induction of effector and memory T cells. Combination therapy enhanced cytotoxic NK and CD8+ T-cell proliferation and T-bet expression, whereas NHS-muIL12 monotherapy induced CD8+ T-cell infiltration into the tumor. Combination therapy also enhanced plasma cytokine levels and stimulated expression of a greater number of innate and adaptive immune genes compared with either monotherapy. Conclusions: These data indicate that combination therapy with NHS-muIL12 and avelumab increased antitumor efficacy in preclinical models, and suggest that combining NHS-IL12 and avelumab may be a promising approach to treating patients with solid tumors. Clin Cancer Res; 23(19); 5869–80. ©2017 AACR.

2567 Background: No biomarker satisfactorily predict response to anti-PD-L1 therapies. Biomarker studies suffer from small sample size, presence of disease subtypes, and lack of simultaneous measurement of multiple biomarkers. The IMvigor210 dataset (Mariathasan et al., Nature 2018) provides baseline measurements for multiple biomarkers of response to atezolizumab (n range: 105-298) coupled with genomewide RNAseq profiles. We examined predictive performance of individual biomarkers and combined information from multiple biomarkers to measure changes in predictive performance. Methods: We built classification models (PR/CR vs. PD/SD) using genes and gene sets that provide information on pathways (mSigDB), immune components (xCell, Cibersort), and predictors of response (IMPRES, Immunophenoscore, and TIDE). Prognostic features were removed based on survival association in TCGA. All experiments were done with repeated five-fold double cross validation. Predictions from the gene sets model were used as a single biomarker. PD-L1 expression by IHC in tumor core and immune cells, tumor mutation burden(TMB), neo-antigen burden (NB), location of metastatic disease, immune phenotype and genomic subtypes were then systematically merged with the gene set based model. Results: NB was the best predictor of response (AUC 0.77), while a model combining NB, TMB, ECOG and expression signatures was marginally better (AUC 0.81) with a chance of over fitting. Chi-square tests for independence suggested that examined biomarkers do not provide independent information explaining lack of increase in AUC. Signatures for TP53 mutations, M1 macrophages, CD8+ T effector cell and DNA repair, among others, were present frequently in classification using gene expression information (AUC 0.71), suggesting their independent contributions to response. Adding gene expression information to NB didn’t improve AUC for response but provided better survival stratification. Conclusions: Integration of examined biomarkers with machine learning did not improve response prediction significantly. We are now examining sizes of subgroups defined by combination of low NB/TMB with these biomarkers.

Purpose: Following recent Immunotherapy successes by targeting the checkpoints PD1, PD-L1, and CTLA-4, additional checkpoint inhibitors and their counter-structures are being explored as therapeutic targets to reverse T cell exhaustion and increase T-cell anti-tumor activity. One such inhibitory receptor, TIM3, has been reported to be expressed on severely dysfunctional T cells in preclinical cancer models and in multiple human cancers. While TIM3 expression is significantly upregulated on TILs, including exhausted CD8+ T cells and Tregs, constitutive expression of TIM3 on myeloid cells has also been shown to negatively regulate anti-tumor activity of T cells. Inhibitory signaling in T-cells is activated by engagement of TIM3 by Galectin 9 (GAL9, LGALS9) and putatively by ligands CEACAM1, HMGB1, and Phosphatidylserine. GAL9 has also been shown to induce T cell apoptosis in the TME. Given the complex nature of TIM3 biology, we sought to characterize expression of TIM3 and its ligands across multiple tumor indications. Experimental Design: TIM3, LGALS9, CEACAM1, HMGB1, and signatures capturing T and myeloid populations were examined in TCGA RNASeq data. TIM3 and LGALS9 in various cell subsets was evaluated using public single-cell RNASeq. Multiplex immunofluorescence (mIF) staining was performed on tumor TMAs procured from commercial sources. Results: Analysis of TCGA data showed that TIM3 expression strongly correlates with macrophages and with T cells. TIM3 expression strongly correlates with LGALS9 but not with CEACAM1 or HMGB1 across essentially all TCGA indications. LGALS9 expression was observed to correlate more strongly with T cells, macrophages, and IFNγ expression signatures compared to HMGB1 and CEACAM1, suggesting it may be the most relevant ligand as adaptive mechanism of resistance to cytotoxic activity. Interestingly, the genes most correlated with TIM3 and its ligands were largely distinct between cell types in the single-cell data. This allows for cell type-specific expression signatures to predict levels of these genes from bulk tumor expression data. Such signatures combined with overall survival data from TCGA suggest that TIM3+ T cells are active in immune response and that TIM3+ macrophages have a negative predictive value. Experiments to confirm findings for TIM3 and its ligands from TCGA using mIF analysis are ongoing. Results will be reported in detail in the poster. Conclusions: These results suggest that interaction of TIM3 and GAL9, as opposed to its other ligands, may be an important mechanism of immune suppression in the TME. Thus, blocking TIM3/GAL9 interaction would potentially reactivate anti-tumor activity by modulating both T cell intrinsic and extrinsic functions involving multiple immune cells subsets. Future correlative and clinical investigations should consider the potential combined role of TIM3 and Gal9 for development of next generation IO therapeutics. Citation Format: Amit M. Deshpande, Rachel Fontana, Yue Zhang, Mary Ruisi, Dong Zhang, Tilo Senger, P. Alexander Rolfe. Galectin-9 drives TIM-3 mediated immune suppression [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 2725.

Still-emerging evidence suggests that HCC is at least moderately responsive to therapeutic agents that target tumor immune suppression pathways, specifically the programmed death 1/programmed death ligand 1 (PD-L1) pathway. Prior studies raise the possibility that PD-L1 is a prognostic biomarker in HCC, where its expression levels have been reported to correlate with tumor aggressiveness and recurrence following surgical resection. The purpose of this study was to evaluate the expression of PD-L1 in non-cirrhotic liver tissue adjacent to HCC and HCC itself in 68 procured tissue samples, as well as elucidate the immune cell composition of the HCC tumor microenvironment. All cases showed the typical morphology of HCC and were classified as low- to high-grade trabecular, pseudoglandular, or solid with the common cytoplasmic features. Immunohistochemical (IHC) staining for PD-L1 in tumor-free liver (TFL) revealed PD-L1 staining in sinusoidal lining cells (macrophages [Mϕ] and endothelial cells [EC], as confirmed by double labeling for CD68 and CD31), although there was considerable heterogeneity in the extent of PD-L1 staining. More specifically, in TFL, some but not all CD68+ Mϕ were also PD-L1+, whereas most CD31+ EC were also PD-L1+. Furthermore, we evaluated PD-L1 staining qualitatively and semiquantitatively in HCC. Only few tumor cells displayed membranous PD-L1 staining, and 62/68 of the cases (91.2%) were categorized as PD-L1- vs 6/68 (8.8%) PD-L1+ (≥1% and Citation Format: Christian Ihling, Sienna Yoast, Yue Zhang, Bartholomew Naughton, Miriam Urban, P. Alexander Rolfe, Eveline Frick-Krieger, Isabelle Dussault. Characterization of PD-L1 expression and the immune cell microenvironment in hepatocellular carcinoma (HCC) and non-cirrhotic liver tissue adjacent to HCC [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 624. doi:10.1158/1538-7445.AM2017-624

Thirty-two carbapenem-resistant Klebsiella pneumoniae isolates, representative of different resistance mechanisms and clonal lineages, were analyzed with the Pathogenica HAI BioDetection system, based on targeted next-generation sequencing (NGS) technology. With most strains, the system simultaneously yielded comprehensive information on relevant β-lactam resistance determinants and accurate discrimination of clonal lineages, in a shorter time frame and in a less labor-intensive manner than currently available methods for molecular epidemiology analysis. Results supported the usefulness of targeted NGS-based technologies for similar applications.

We demonstrate that the binding sites for highly conserved transcription factors vary extensively between human and mouse. We mapped the binding of four tissue-specific transcription factors (FOXA2, HNF1A, HNF4A and HNF6) to 4,000 orthologous gene pairs in hepatocytes purified from human and mouse livers. Despite the conserved function of these factors, from 41% to 89% of their binding events seem to be species specific. When the same protein binds the promoters of orthologous genes, approximately two-thirds of the binding sites do not align.

Despite the known relevance of genomic structural variants to pathogen behavior, cancer, development, and evolution, certain repeat based structural variants may evade detection by existing high-throughput techniques. Here, we present ruler arrays, a technique to detect genomic structural variants including insertions and deletions (indels), duplications, and translocations. A ruler array exploits DNA polymerase’s processivity to detect physical distances between defined genomic sequences regardless of the intervening sequence. The method combines a sample preparation protocol, tiling genomic microarrays, and a new computational analysis. The analysis of ruler array data from two genomic samples enables the identification of structural variation between the samples. In an empirical test between two closely related haploid strains of yeast ruler arrays detected 78% of the structural variants larger than 100 bp., United States. National Institutes of Health (Grant R01GM069676)

Background: The advent of high-throughput sequencing has enabled sequencing based measurements of cellular function, with an individual measurement potentially consisting of more than 108 reads. While tools are available for aligning sets of reads to genomes and interpreting the results, fewer tools have been developed to address the storage and retrieval requirements of large collections of aligned datasets. We present ReadDB, a network accessible column store database system for aligned high-throughput read datasets. Results: ReadDB stores collections of aligned read positions and provides a client interface to support visualization and analysis. ReadDB is implemented as a network server that responds to queries on genomic intervals in an experiment with either the set of contained reads or a histogram based interval summary. Tests on datasets ranging from 105 to 108 reads demonstrate that ReadDB performance is generally within a factor of two of local-storage based methods and often three to five times better than other network-based methods. Conclusions: ReadDB is a high-performance foundation for ChIP-Seq and RNA-Seq analysis. The client-server model provides convenient access to compute cluster nodes or desktop visualization software without requiring a shared network filesystem or large amounts of local storage. The client code provides a simple interface for fast data access to visualization or analysis. ReadDB provides a new way to store genome-aligned reads for use in applications where read sequence and alignment mismatches are not needed., National Institutes of Health (U.S.) (grant 5TL1EB008540), National Institutes of Health (U.S.) (grant 5R01HG002668), National Institutes of Health (U.S.) (grant P01-NS055923-01), National Institutes of Health (U.S.) (grant 1-UL1-RR024920)

We present GSE, the Genomic Spatial Event database, a system to store, retrieve, and analyze all types of high-throughput microarray data. GSE handles expression datasets, ChIP-chip data, genomic annotations, functional annotations, the results of our previously published Joint Binding Deconvolution algorithm for ChIP-chip, and precomputed scans for binding events. GSE can manage data associated with multiple species; it can also simultaneously handle data associated with multiple 'builds' of the genome from a single species. The GSE system is built upon a middle software layer for representing streams of biological data; we outline this layer, called GSEBricks, and show how it is used to build an interactive visualization application for ChIP-chip data. The visualizer software is written in Java and communicates with the GSE database system over the network. We also present a system to formulate and record binding hypotheses--simple descriptions of the relationships that may hold between different ChIP-chip experiments. We provide a reference software implementation for the GSE system.

We mapped the transcriptional regulatory circuitry for six master regulators in human hepatocytes using chromatin immunoprecipitation and high-resolution promoter microarrays. The results show that these regulators form a highly interconnected core circuitry, and reveal the local regulatory network motifs created by regulator–gene interactions. Autoregulation was a prominent theme among these regulators. We found that hepatocyte master regulators tend to bind promoter regions combinatorially and that the number of transcription factors bound to a promoter corresponds with observed gene expression. Our studies reveal portions of the core circuitry of human hepatocytes.

The transcriptional regulatory networks that specify and maintain human tissue diversity are largely uncharted. To gain insight into this circuitry, we used chromatin immunoprecipitation combined with promoter microarrays to identify systematically the genes occupied by the transcriptional regulators HNF1alpha, HNF4alpha, and HNF6, together with RNA polymerase II, in human liver and pancreatic islets. We identified tissue-specific regulatory circuits formed by HNF1alpha, HNF4alpha, and HNF6 with other transcription factors, revealing how these factors function as master regulators of hepatocyte and islet transcription. Our results suggest how misregulation of HNF4alpha can contribute to type 2 diabetes.

A detailed understanding of the circulating pathogens in a particular geographic location aids in effectively utilizing targeted, rapid diagnostic assays, thus allowing for appropriate therapeutic and containment procedures. This is especially important in regions prevalent for highly pathogenic viruses co-circulating with other endemic pathogens such as the malaria parasite. The importance of biosurveillance is highlighted by the ongoing Ebola virus disease outbreak in West Africa. For example, a more comprehensive assessment of the regional pathogens could have identified the risk of a filovirus disease outbreak earlier and led to an improved diagnostic and response capacity in the region. In this context, being able to rapidly screen a single sample for multiple pathogens in a single tube reaction could improve both diagnostics as well as pathogen surveillance. Here, probes were designed to capture identifying filovirus sequence for the ebolaviruses Sudan, Ebola, Reston, Taï Forest, and Bundibugyo and the Marburg virus variants Musoke, Ci67, and Angola. These probes were combined into a single probe panel, and the captured filovirus sequence was successfully identified using the MiSeq next-generation sequencing platform. This panel was then used to identify the specific filovirus from nonhuman primates experimentally infected with Ebola virus as well as Bundibugyo virus in human sera samples from the Democratic Republic of the Congo, thus demonstrating the utility for pathogen detection using clinical samples. While not as sensitive and rapid as real-time PCR, this panel, along with incorporating additional sequence capture probe panels, could be used for broad pathogen screening and biosurveillance.

Cell size increases significantly with increasing ploidy. Differences in cell size and ploidy are associated with alterations in gene expression, although no direct connection has been made between cell size and transcription. Here we show that ploidy-associated changes in gene expression reflect transcriptional adjustment to a larger cell size, implicating cellular geometry as a key parameter in gene regulation. Using RNA-seq, we identified genes whose expression was altered in a tetraploid as compared with the isogenic haploid. A significant fraction of these genes encode cell surface proteins, suggesting an effect of the enlarged cell size on the differential regulation of these genes. To test this hypothesis, we examined expression of these genes in haploid mutants that also produce enlarged size. Surprisingly, many genes differentially regulated in the tetraploid are identically regulated in the enlarged haploids, and the magnitude of change in gene expression correlates with the degree of size enlargement. These results indicate a causal relationship between cell size and transcription, with a size-sensing mechanism that alters transcription in response to size. The genes responding to cell size are enriched for those regulated by two mitogen-activated protein kinase pathways, and components in those pathways were found to mediate size-dependent gene regulation. Transcriptional adjustment to enlarged cell size could underlie other cellular changes associated with polyploidy. The causal relationship between cell size and transcription suggests that cell size homeostasis serves a regulatory role in transcriptome maintenance., National Institutes of Health (U.S.) (grant GM035010), National Institutes of Health (U.S.) (grant GM040266)

We generated a high-resolution whole-genome sequence and individually deleted 5100 genes in Sigma1278b, a Saccharomyces cerevisiae strain closely related to reference strain S288c. Similar to the variation between human individuals, Sigma1278b and S288c average 3.2 single-nucleotide polymorphisms per kilobase. A genome-wide comparison of deletion mutant phenotypes identified a subset of genes that were conditionally essential by strain, including 44 essential genes unique to Sigma1278b and 13 unique to S288c. Genetic analysis indicates the conditional phenotype was most often governed by complex genetic interactions, depending on multiple background-specific modifiers. Our comprehensive analysis suggests that the presence of a complex set of modifiers will often underlie the phenotypic differences between individuals.