Citations

AbstractImmunotherapy is a class of promising anticancer treatments that has recently gained attention due to surging numbers of FDA approvals and extensive preclinical studies demonstrating efficacy. Nevertheless, further clinical implementation has been limited by high variability in patient response to different immunotherapeutic agents. These treatments currently do not have reliable predictors of efficacy and may lead to side effects. The future development of additional immunotherapy options and the prediction of patient‐specific response to treatment require advanced screening platforms associated with accurate and rapid data interpretation. Advanced engineering approaches ranging from sequencing and gene editing, to tumor organoids engineering, bioprinted tissues, and organs‐on‐a‐chip systems facilitate the screening of cancer immunotherapies by recreating the intrinsic and extrinsic features of a tumor and its microenvironment. High‐throughput platform development and progress in artificial intelligence can also improve the efficiency and accuracy of screening methods. Here, these engineering approaches in screening cancer immunotherapies are highlighted, and a discussion of the future perspectives and challenges associated with these emerging fields to further advance the clinical use of state‐of‐the‐art cancer immunotherapies are provided.

AbstractIntroductionAbnormal gene expression patterns may contribute to the onset and progression of late‐onset Alzheimer's disease (LOAD).MethodsWe performed transcriptome‐wide meta‐analysis (N = 1440) of blood‐based microarray gene expression profiles as well as neuroimaging and cerebrospinal fluid (CSF) endophenotype analysis.ResultsWe identified and replicated five genes (CREB5, CD46, TMBIM6, IRAK3, and RPAIN) as significantly dysregulated in LOAD. The most significantly altered gene, CREB5, was also associated with brain atrophy and increased amyloid beta (Aβ) accumulation, especially in the entorhinal cortex region. cis‐expression quantitative trait loci mapping analysis of CREB5 detected five significant associations (P < 5 × 10−8), where rs56388170 (most significant) was also significantly associated with global cortical Aβ deposition measured by [18F]Florbetapir positron emission tomography and CSF Aβ1‐42.DiscussionRNA from peripheral blood indicated a differential gene expression pattern in LOAD. Genes identified have been implicated in biological processes relevant to Alzheimer's disease. CREB, in particular, plays a key role in nervous system development, cell survival, plasticity, and learning and memory.

3022 Background: Axi-cel is a US and EU-approved autologous anti-CD19 chimeric antigen receptor (CAR) T cell therapy for pts with relapsed/refractory large B cell lymphoma after ≥ 2 prior therapies. In ZUMA-1 (NCT02348216), the objective response rate was 83% (58% complete response rate; Locke et al. Lancet Oncol. 2019). T cell-related biology (Immunosign 21; Immunoscore) measured pretreatment in the tumor microenvironment (TME) was associated with response to axi-cel (Rossi et al. AACR 2018. #LB-016; Rossi et al. AACR 2019. #CT153). This expanded analysis characterized the pretreatment TME immune contexture and examined associations between immune cell subsets and response. Methods: In ZUMA-1, pts received axi-cel at a target dose of 2.0 × 106 CAR T cells/kg. Archival pretreatment tumor biopsy samples were analyzed by multiplex immunohistochemistry (Brightplex). Two panels were developed and applied to assess T cell (CD3, CD8, FoxP3, PD-1, LAG-3, TIM-3) and myeloid cell (CD11b, CD14, CD15, LOX1, S100A9, CD68) subsets (n = 14 total). The association between T cell and myeloid cell subset density, prespecified immune scores (Immunosign 21; Immunoscore), and objective response was evaluated. T test values were based on Brightplex analysis. Results: Pretreatment tumor biopsy samples from 18 pts were analyzed (14 objective responders and 4 nonresponders). The pretreatment TME comprised all major myeloid and T cell subsets, with diverse distribution across samples analyzed. The median TME density of monocytes (CD11b+ CD15− CD14+; 1215 cells/mm2) and macrophages (CD68+; 530 cells/mm2) was greater than that of the total CD8+ T cell subset (312 cells/mm2). The pretreatment Immunosign 21 and Immunoscore scores associated positively with the density of all major T cell subsets and some myeloid subsets. The density of activated CD8+ T cells (PD-1+ LAG-3+/− TIM-3−) was most significantly associated with clinical response versus other T cell subsets. The density of nonactivated CD8+ T cells (PD-1− LAG-3− TIM-3−) and exhausted CD8+ T cells (PD-1+ LAG-3+ TIM-3+) were not significantly associated with response. Additional characterization of the immune contexture and correlative analysis of cell subsets will be presented. Conclusions: These results suggest that a TME associated with increased density of activated PD-1+ LAG-3+/− TIM-3− CD8+ T cells, measurable pretreatment, facilitates clinical response in pts post–axi-cel.

AbstractIntroductionMAPT H1 haplotype is implicated as a risk factor for neurodegenerative diseases including Alzheimer's disease (AD).MethodsUsing Alzheimer's Disease Genetics Consortium (ADGC) genome‐wide association study (GWAS) data (n = 18,841), we conducted a MAPT H1/H2 haplotype–stratified association to discover MAPT haplotype–specific AD risk loci.ResultsWe identified 11 loci—5 in H2‐non‐carriers and 6 in H2‐carriers—although none of the MAPT haplotype–specific associations achieved genome‐wide significance. The most significant H2 non‐carrier–specific association was with a NECTIN2 intronic (P = 1.33E‐07) variant, and that for H2 carriers was near NKX6‐1 (P = 1.99E‐06). The GABRG2 locus had the strongest epistasis with MAPT H1/H2 variant rs8070723 (P = 3.91E‐06). Eight of the 12 genes at these loci had transcriptome‐wide significant differential expression in AD versus control temporal cortex (q < 0.05). Six genes were members of the brain transcriptional co‐expression network implicated in “synaptic transmission” (P = 9.85E‐59), which is also enriched for neuronal genes (P = 1.0E‐164), including MAPT.DiscussionThis stratified GWAS identified loci that may confer AD risk in a MAPT haplotype–specific manner. This approach may preferentially enrich for neuronal genes implicated in synaptic transmission.

Abstract Background: Growing evidence supports the critical role of preexisting immune response in triple negative breast cancer (TNBC). However, there are limitations with current evaluation approaches: inability to functionally assess the type of immune infiltration with traditional pathologic evaluation and loss of spatial distribution in conventional high-plex gene or protein expression analyses from the whole tumor section. Here, we report the initial analysis of immune protein expression as a function of spatial distribution and clinical outcomes in TNBC samples. Methods: NanoString GeoMxTM Digital Spatial Profiling (DSP) was used to quantify 39 immune-related proteins in stromal and tumor segments from 44 TNBC samples from the FinXX trial. Samples were matched for patient characteristics, treatment arm (capecitabine vs. 5-fluorouracil), and outcome based on recurrence-free survival (RFS) with 22 samples from patients who recurred and 22 samples from patients with durable RFS. Regions of interest (ROIs) were selected based on expression of cytokeratin (tumor), CD45 (leukocytes), or CD68 (macrophages). Each ROI was segmented into tumor (pancytokeratin-positive area) and stroma (pancytokeratin-negative/nuclear SYTO13-positive area). The general linear model was used for statistical analysis of differential expression with RFS as a categorical variable (recur yes or no). Results: A total of 950 tumor and stroma segments were included in this initial analysis. In both tumor and stroma segments, over-expression of T cell activation markers (CD137, GITR) was associated with better outcome, whereas T cell markers (CD3, CD4, CD8) were not significantly associated with outcome. In tumor segments alone, improved outcome was significantly associated with increased protein expression [&gt; 2-fold change (FC) at p&lt;0.001] of CD56, PD-L2, HLA-DR, CD137, GITR, and CD40. In CD45-enriched stroma, improved outcome was associated with elevated expression (FC&gt;2.0, p&lt;0.001) of PD-L2; whereas durable RFS was associated with elevated PD-L2 and IDO1 expression in CD68-enriched stroma. In contrast, macrophage/dendritic cell markers CD68 and CD11c were not associated with outcome. In tumor cells adjacent to CD45-enriched stroma, durable RFS was associated with increased abundance (FC&gt;2.0, p&lt;0.001) of PD-L2, CD56, CD27, GITR, CD20, HLA-DR, and IDO1. Similarly, in tumor segment associated with CD68-enriched stroma, proteins associated with RFS included PD-L2, HLA-DR, CD56, GITR, and CD137. Among 39 immune function proteins, only elevated CTLA4 expression in CD68-enriched stroma was associated with recurrence (FC=0.55, p&lt;0.001), whereas tumor-segment CTLA4 was associated with RFS. Conclusions: Using an in-depth analysis to precisely quantify the abundance of multiple immune function proteins in a spatially defined manner, we observed that PD-L2, IDO1, and T cell activation markers were robustly associated with durable RFS in both tumor and stromal segments. In contrast, MHC components (HLA-DR, beta-2-microglobulin), B cell markers (CD20), and NK cell markers (CD56) were strongly associated with favorable outcome in tumor but not in stromal segments. Our study highlights the conclusion that the immune landscape of TNBC is far too complex to be encompassed by any single molecular marker, and more detailed analyses of the DSP data reported here are ongoing with a view towards using quantitative multiplex analyses to refine our understanding of how therapeutic outcome is influenced by interactions among immune cells and between immune and tumor cells. Acknowledgements: Supported by the Breast Cancer Research Foundation (BCRF18-161), Bankhead Coley (6BC05 Florida Department of Health), 26.2 with Donna Foundation, US National Cancer Institute (CA15083), and the Canadian Cancer Center Citation Format: Saranya Chumsri, Douglas Hinerfeld, Jennifer M. Kachergus, Yaohua Ma, Heather A Brauer, Sarah Warren, Xue Wang, Torsten O. Nielsen, Karama Asleh, Heikki Joensuu, Edith A. Perez, E. A. Thompson. Digital spatial mapping of the immune landscape of triple negative breast cancer reveals novel features of immune-tumor cell interaction [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr PD5-06.

Abstract Background Cranial radiotherapy (RT) is associated with risk for cognitive and adaptive dysfunction. Proton RT (PRT) is a technique hypothesized to spare cognition by reducing exposure to nontarget brain tissue. However, little is known regarding functional outcomes in survivors of pediatric brain tumor (BT) treated with PRT. The present study examined the relationship between cognitive and adaptive outcomes in pediatric BT survivors post‐PRT. Methods Survivors treated with either focal (n = 33) or craniospinal irradiation (CSI; n = 37) PRT completed neurocognitive evaluations approximately 5 years post‐treatment. Results of intelligence testing and ratings of adaptive functioning are reported. Mediation models examined the relationship among radiation field, cognition, and adaptive functioning. Results The PRT CSI group demonstrated worse cognitive outcomes than the PRT Focal group across each cognitive index (Cohen's d = 0.56–0.70). Parent ratings of adaptive functioning were also worse in the PRT CSI group than the PRT Focal group (Global Adaptive Composite, d = 0.53; conceptual skills, d = 0.67). Cognitive performance fully mediated the relationship between radiation field and adaptive outcomes, while controlling for group differences in tumor histology and RT dose. Conclusions Focal PRT survivors demonstrated generally positive outcomes with weaknesses in processing speed and aspects of adaptive functioning. CSI exposure was associated with more consistently poor cognitive and adaptive outcomes. The increased risk for adaptive dysfunction in the PRT CSI group appeared due to the effects of CSI on cognition. Efforts to reduce the volume of tissue exposure to RT remain important.

Abstract Background: Waldenstršms macroglobulinemia (WM) is an indolent B-lymphoplasmacytic lymphoma, which is highly sensitive to 20S proteasome inhibitors such as bortezomib. However, clinical resistance to the drug can be observed early at onset of therapy (primary or inherent resistance) or develop over time, through repeated exposure to the drug (acquired resistance). Although prior investigations into the biological mechanisms associated with bortezomib resistance (BR) have identified aberrations at the genomic (PSMB5 mutation) and transcriptional level (loss of XPB-1), there is limited data on the epigenetic abnormalities that support resistance to 20S proteasome inhibition. With this in mind, we conducted a comprehensive methylation and mRNA expression analysis in WM cells focusing on the molecular patterns that characterize inherent BR (iBR) as well as acquired BR (aBR). Materials and Methods: Bortezomib sensitive (BS) human WM cell lines, BCWM.1 and MWCL-1, the iBR WM cell line RPCI-WM1 (developed from a bortezomib-refractory WM patient) as well as aBR subclones (BCWM.1/BR, MWCL-1/BR) were used in the study. Methylation status of WM cells was profiled by Illumina Infinium 450k methylation array. Methylation IDAT files were background subtracted using GenomeStudio v1.9. Beta mixture quantile dilation (BMIQ) method in R watermelon package was used to adjust type II probes into distribution characteristic of type I probes. For each gene, probes were partitioned into 6 regions using R IMA package and the ones belonging to the same region were averaged, including transcription start sites (TSS; both 200 bp and 1500 bp upstream), 5' untranslated region (UTR), and 3'UTR, the first exon, and genebody. Gene regions showing a significant adjusted p-value and a beta difference of >0.1 or <-0.1 were selected for differential hypermethylation and hypomethylation, respectively. Correlation with gene expression was conducted only on genes showing >1.5 fold change in expression. Overview of methodology is shown in Figure 1. Results: We first assessed the differential methylation pattern (TSS, 200bp upstream of gene body) of bortezomib-sensitive (BS, BCWM.1, IC50 6nM) and iBR cells, (RPCI-WM1). A total of 3,801 hypermethylated and 1,865 hypomethylated DNA regions were observed in iBR cells relative to BS cells (Figure 2A). In iBR cells, a negative correlation between hypermethylated DNA and corresponding gene expression was found in 1,039 genes (Spearman r = -0.12) (Figure 2B). In parallel, we compared the methylation pattern (TSS 200bp) of BS WM cells (BCWM.1 and MWCL-1) with their aBR derivatives, which display ~20 – 50 fold resistance to bortezomib. aBR subclones showed differential hypermethylation of 1,521 DNA regions and hypomethylation of 651 genomic regions relative to BS WM cells. These findings were not unexpected as aBR cell lines, being derivatives of BS WM cells, are clonally related to the former, whereas iBR cells are derived from a different clone. Meta-analysis of iBR and aBR followed by pathway enrichment (NextBio, Illumina Inc), revealed a significant clustering of commonly hypermethylated genes within the Validated Transcriptional Targets of TP63 isoforms Canonical Pathway (p<1.9-E5, Figure 2C) and the CEBPA binding site Geneset 2 (p<8.2-E9, Figure 2D); pathways whose genes are actively involved in suppression of cell growth and differentiation. Further validation and functional relevance of candidate gene targets from this analysis, which are relevant to WM pathobiology, are currently being investigated. Conclusion: This is the first study to examine and correlate the global methylation and gene expression profiles in WM tumor cells that are inherently wired to resist 20S proteasome inhibition as well as tumor cells, which have acquired resistance through continuous exposure to bortezomib. Although considerable differences were observed in the methylation profiles of WM cells displaying inherent vs. acquired resistance, a number of common genes emerged and pointed towards transcriptional repressors, whose inactivation through methylation has been linked to other cancers. Altogether, these findings uncover cellular systems in WM cells, which are affected by DNA methylation, subsequent mRNA suppression and which may be associated as a whole with both inherent and acquired forms of bortezomib resistance. Disclosures No relevant conflicts of interest to declare.

Abstract OBJECTIVE Our goal is to identify new pathways perturbed in and which may lead to GRS. METHODS We collected brain transcriptome levels from healthy controls (n=5), patients with GRS (n=9), glioma without seizures (non-GRS, n=8), and idiopathic temporal lobe epilepsy (iTLE, n=7) using Illumina-based poly-A capture high-throughput RNA sequencing approach. Differential gene expression analysis was conducted to ascertain expression differences between the four groups. We identified molecular pathways enriched for differentially expressed genes (DEG) using Ingenuity Pathway Analysis. DEGs were defined as those with log2 fold change ≥ 2 and q-value < 0.01 when compared to GRS. RESULTS Principal component analysis revealed that diagnostic grouping was the main determinant of the transcriptome variance. We identified 212 DEGs in the GRS vs. non-GRS analysis. Among these, 108 genes were up-regulated and 104 genes were down-regulated. Among the genes that were down‐regulated, there was significant enrichment for those involved in acute phase response signaling and immune cell trafficking (e.g. H19, BMP5, CXCL8). Compared to iTLE samples, there were 1015 DEGs in the GRS samples. Among these 877 genes were up-regulated and 138 genes were down-regulated. There was significant enrichment for genes involved in cell-to-cell signaling among those that were either uniquely up‐regulated (e.g. NRK, RGS10, SLC4A4, and SELPLG) or down‐regulated in the GRS samples (e.g. SLC9A3 –Na+/H+ exchanger; SLC5A5-sodium-glucose co-transporter family). Further, two of the most down-regulated genes in samples with GRS, SCLC17A6- vesicular glutamate transporter 2 and FOSB, have previously been shown to be involved in glutamatergic transmission. CONCLUSIONS Our findings suggest that inflammation-related processes and alterations in cell-to cell signaling may underlie the pathogenesis of GRS. Our results also provide support for perturbations in glutamatergic transmission in GRS. Our findings require replication in larger human cohorts and functional experiments to explore the function of the genes perturbed in GRS.