Baseline Gene Expression Profiles Research Articles

Insights into gemcitabine resistance in pancreatic cancer: association with metabolic reprogramming and TP53 pathogenicity in patient derived xenografts

BackgroundWith poor prognosis and high mortality, pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies. Standard of care therapies for PDAC have included gemcitabine for the past three decades, although resistance often develops within weeks of chemotherapy initiation through an array of possible mechanisms.MethodsWe reanalyzed publicly available RNA-seq gene expression profiles of 28 PDAC patient-derived xenograft (PDX) models before and after a 21-day gemcitabine treatment using our validated analysis pipeline to identify molecular markers of intrinsic and acquired resistance.ResultsUsing normalized RNA-seq quantification measurements, we first identified oxidative phosphorylation and interferon alpha pathways as the two most enriched cancer hallmark gene sets in the baseline gene expression profile associated with intrinsic gemcitabine resistance and sensitivity, respectively. Furthermore, we discovered strong correlations between drug-induced expression changes in glycolysis and oxidative phosphorylation genes and response to gemcitabine, which suggests that these pathways may be associated with acquired gemcitabine resistance mechanisms. Thus, we developed prediction models using baseline gene expression profiles in those pathways and validated them in another dataset of 12 PDAC models from Novartis. We also developed prediction models based on drug-induced expression changes in genes from the Molecular Signatures Database (MSigDB)’s curated 50 cancer hallmark gene sets. Finally, pathogenic TP53 mutations correlated with treatment resistance.ConclusionOur results demonstrate that concurrent upregulation of both glycolysis and oxidative phosphorylation pathways occurs in vivo in PDAC PDXs following gemcitabine treatment and that pathogenic TP53 status had association with gemcitabine resistance in these models. Our findings may elucidate the molecular basis for gemcitabine resistance and provide insights for effective drug combination in PDAC chemotherapy.

Predicting psychosocial intervention response from baseline gene expression

To address the challenge of predicting psychological response to a psychosocial intervention we tested the possibility that baseline gene expression profiles might provide information above and beyond baseline psychometric measures. The genomics strategy utilized individual level inferences of transcription factor activity to predict changes in loneliness and affect in response to two well-established meditation interventions. Initial algorithm development analyses focused on three a-priori defined stress-related gene regulation pathways (CREB, GR, and NF-ĸB) as inferred from TELiS promoter-based bioinformatic analysis of basal (pre-intervention) blood samples from a randomized-controlled trial comparing a compassion-based meditation (CM, n = 45) with mindfulness meditation (MM, n = 44). Greater baseline CREB activity (but not GR or NF-ĸB) predicted greater reductions from pre- to post-intervention in loneliness (b = −0.24, p = 0.016) and negative emotions (b = −0.23, p = 0.017) for CM, but not for MM. A second algorithm validation analysis applied the same approach to another randomized controlled trial comparing CM (n = 42) with MM (n = 38) and a health education control condition (n = 41). Similarly, greater baseline CREB activity predicted greater pre- to post-intervention decreases in loneliness (b = −0.24, p = 0.029) and greater increases in satisfaction with life (b = 0.21, p = 0.046) for the CM condition only. Baseline CREB activity was not associated with baseline psychometric measures in either study. Results raise the possibility that pre-intervention gene expression profiles may reflect non-conscious psychobiological states that affect psychological responses to distinct psychosocial interventions, and thereby help personalize intervention selection.

The modulatory effect of Al-Assi river trout fish meal on OCD manifestations and molecular mechanisms in BALB/c Mice

Background: Obsessive-Compulsive Disorder (OCD) is a type of anxiety disorder that is marked by intrusive and distressing thoughts, as well as repetitive behaviors. Trout fish (Oncorhynchus mykiss) is a functional food that might have potential therapeutic effects on many neurological disorders including OCD. Objective: This study aims to explore the effects of Al-Assi River trout fish meal, a dietary source of tryptophan, on obsessive-compulsive disorder (OCD) symptoms and related molecular pathways in BALB/c mice. Methods: OCD mice were divided into five groups: one control group without any treatment, one group treated with fluoxetine (a selective serotonin reuptake inhibitor), and three groups fed with different doses of trout fish meal (0, 7.5, and 15 g/kg body weight). The mice were subjected to various behavioral tests, such as the marble test, tail suspension test, sucrose preference test, and forced swim test, to evaluate OCD and depressive-like behaviors. Moreover, the expression and protein levels of genes involved in the serotonergic and GABAergic systems were measured. Results: The results indicated that trout fish meal had dose-dependent effects on OCD-like behaviors, revealing exacerbation at lower doses and improvement at higher doses. For instance, in the marble test, OCD mice fed with 7.5 g of trout fish/kg body weight buried more marbles than those fed with 15 g/kg of trout fish (4.5 vs 3.33 out of 6, p>0.05). In the tail suspension test, the immobility time of OCD mice treated with fluoxetine was numerically lower than that of the untreated OCD mice (63.6 vs 87.3 seconds, p>0.05). Furthermore, normal mice had different baseline gene expression profiles than OCD mice. Normal mice had the highest fold increase of Gabra gene expression (3.75) compared to the untreated OCD group, followed by groups treated with 7.5 and 15 g of trout fish/kg body weight (2.02 and 1.44, respectively). Conclusions: This study suggests that dietary interventions rich in tryptophan, such as trout fish meal, may have modulatory effects on OCD symptoms and molecular mechanisms in mice. However, the optimal dosing and individual variability need to be considered. More research is required to clarify the underlying mechanisms and to evaluate the potential efficacy of trout fish meal in treating OCD in humans. Keywords: BALB/c mice, OCD, qPCR, Western blotting, Gabra, Serotonin, Trout fish, Tryptophan.

Transcriptomic landscapes of effective and failed liver regeneration in humans

Although extensive experimental evidence on the process of liver regeneration exists, in humans, validation is largely missing. However, liver regeneration is critically affected by underlying liver disease. Within this project, we aimed to systematically assess early transcriptional changes during liver regeneration in humans and further assess how these processes differ in people with dysfunctional liver regeneration. Blood samples of 154 patients and intraoperative tissue samples of 46 patients undergoing liver resection were collected and classified with regard to dysfunctional postoperative liver regeneration. Of those, a matched cohort of 21 patients were used for RNA sequencing. Samples were assessed for circulating cytokines, gene expression dynamics, intrahepatic neutrophil accumulation, and spatial transcriptomics. Individuals with dysfunctional liver regeneration demonstrated an aggravated transcriptional inflammatory response with higher intracellular adhesion molecule-1 induction. Increased induction of this critical leukocyte adhesion molecule was associated with increased intrahepatic neutrophil accumulation and activation upon induction of liver regeneration in individuals with dysfunctional liver regeneration. Comparing baseline gene expression profiles in individuals with and without dysfunctional liver regeneration, we found that dual-specificity phosphatase 4 (DUSP4) expression, a known critical regulator of intracellular adhesion molecule-1 expression in endothelial cells, was markedly reduced in patients with dysfunctional liver regeneration. Mimicking clinical risk factors for dysfunctional liver regeneration, we found liver sinusoidal endothelial cells of two liver disease models to have significantly reduced baseline levels of DUSP4. Exploring the landscape of early transcriptional changes of human liver regeneration, we observed that people with dysfunctional regeneration experience overwhelming intrahepatic inflammation. Subclinical liver disease might account for DUSP4 reduction in liver sinusoidal endothelial cells, which ultimately primes the liver for an aggravated inflammatory response. Using a unique human biorepository, focused on liver regeneration (LR), we explored the landscape of circulating and tissue-level alterations associated with both functional and dysfunctional LR. In contrast to experimental animal models, people with dysfunctional LR demonstrated an aggravated transcriptional inflammatory response, higher intracellular adhesion molecule-1 (ICAM-1) induction, intrahepatic neutrophil accumulation and activation upon induction of LR. Although inflammatory responses appear rapidly after liver resection, people with dysfunctional LR have exaggerated inflammatory responses that appear to be related to decreased levels of LSEC DUSP4, challenging existing concepts of post-resectional LR.

“Proteotranscriptomic analysis of advanced colorectal cancer patient derived organoids for drug sensitivity prediction”

BackgroundPatient-derived organoids (PDOs) from advanced colorectal cancer (CRC) patients could be a key platform to predict drug response and discover new biomarkers. We aimed to integrate PDO drug response with multi-omics characterization beyond genomics.MethodsWe generated 29 PDO lines from 22 advanced CRC patients and provided a morphologic, genomic, and transcriptomic characterization. We performed drug sensitivity assays with a panel of both standard and non-standard agents in five long-term cultures, and integrated drug response with a baseline proteomic and transcriptomic characterization by SWATH-MS and RNA-seq analysis, respectively.ResultsPDOs were successfully generated from heavily pre-treated patients, including a paired model of advanced MSI high CRC deriving from pre- and post-chemotherapy liver metastasis. Our PDOs faithfully reproduced genomic and phenotypic features of original tissue. Drug panel testing identified differential response among PDOs, particularly to oxaliplatin and palbociclib. Proteotranscriptomic analyses revealed that oxaliplatin non-responder PDOs present enrichment of the t-RNA aminoacylation process and showed a shift towards oxidative phosphorylation pathway dependence, while an exceptional response to palbociclib was detected in a PDO with activation of MYC and enrichment of chaperonin T-complex protein Ring Complex (TRiC), involved in proteome integrity. Proteotranscriptomic data fusion confirmed these results within a highly integrated network of functional processes involved in differential response to drugs.ConclusionsOur strategy of integrating PDOs drug sensitivity with SWATH-mass spectrometry and RNA-seq allowed us to identify different baseline proteins and gene expression profiles with the potential to predict treatment response/resistance and to help in the development of effective and personalized cancer therapeutics.

Baseline gene expression profiling determines long-term benefit to programmed cell death protein 1 axis blockade

Treatment with immune checkpoint inhibitors has altered the course of malignant melanoma, with approximately half of the patients with advanced disease surviving for more than 5 years after diagnosis. Currently, there are no biomarker methods for predicting outcome from immunotherapy. Here, we obtained transcriptomic information from a total of 105 baseline tumor samples comprising two cohorts of patients with advanced melanoma treated with programmed cell death protein 1 (PD-1)-based immunotherapies. Gene expression profiles were correlated with progression-free survival (PFS) within consecutive clinical benefit intervals (i.e., 6, 12, 18, and 24 months). Elastic net binomial regression models with cross validation were utilized to compare the predictive value of distinct genes across time. Lasso regression was used to generate a signature predicting long-term benefit (LTB), defined as patients who remain alive and free of disease progression at 24 months post treatment initiation. We show that baseline gene expression profiles were consistently able to predict long-term immunotherapy outcomes with high accuracy. The predictive value of different genes fluctuated across consecutive clinical benefit intervals, with a distinct set of genes defining benefit at 24 months compared to earlier outcomes. A 12-gene signature was able to predict LTB following anti-PD-1 therapy with an area under the curve (AUC) equal to 0.92 and 0.74 in the training and validation set, respectively. Evaluation of LTB, via a unique signature may complement objective response classification and characterize the logistics of sustained antitumor immune responses.

Association between the baseline gene expression profile in periapical granuloma and periapical wound healing after surgical endodontic treatment

In this study, we have investigated the association between the baseline gene expression profile in periapical granuloma and periapical wound healing after surgical endodontic treatment. Twenty-seven patients aged between 15 and 57 years underwent periapical surgery. The retrieved periapical tissue sample was used for mRNA expression analysis of COL1A1, VTN, ITGA5, IL-4, TNF, ANGPT, VEGFA, and CTGF. All patients were recalled after 6 and 12 months for periapical healing evaluation. Healing was then correlated with baseline gene expression. Healing was observed in 15 patients at the end of 6 months, which increased to 21 patients after 12 months. Six patients showed no healing even after 12 months. Analysis of baseline expression levels of the tested genes with healing status showed the mean relative expression of VTN, VEGFA, ANGPT, TNF, and CTGF to be significantly different (p < 0.05) between the healing group (6 and 12 months) (72.99%) and the non-healing (94.42%) group. Periapical Index scores 3–5 exhibited a positive correlation with ITGA-5 expression. Overexpression of ANGPT and a strong positive correlation between ITGA5 and PAI scores in the non-healing group of patients may suggest these genes to be a potential prognostic biomarker for periapical wound non-healing after surgical endodontic treatment.

Intrahepatic transcriptomics reveals gene signatures in chronic hepatitis B patients responded to interferon therapy

ABSTRACT Chronic hepatitis B virus (HBV) infection remains a substantial public health burden worldwide. Alpha-interferon (IFNα) is one of the two currently approved therapies for chronic hepatitis B (CHB), to explore the mechanisms underlying IFNα treatment response, we investigated baseline and 24-week on-treatment intrahepatic gene expression profiles in 21 CHB patients by mRNA-seq. The data analyses demonstrated that PegIFNα treatment significantly induced antiviral responses. Responders who achieved HBV DNA loss and HBeAg or HBsAg seroconversion displayed higher fold change and larger number of up-regulated interferon-stimulated genes (ISGs). Interestingly, lower expression levels of certain ISGs were observed in responders in their baseline biopsy samples. In HBeAg+ patients, non-responders had relative higher baseline HBeAg levels than responders. More importantly, HBeAg− patients showed higher HBsAg loss rate than HBeAg+ patients. Although a greater fold change of ISGs was observed in HBeAg− patients than HBeAg+ patients, upregulation of ISGs in HBeAg+ responders exceeded HBeAg− responders. Notably, PegIFNα treatment increased monocyte and mast cell infiltration, but decreased CD8 T cell and M1 macrophage infiltration in both responders and non-responders, while B cell infiltration was increased only in responders. Moreover, co-expression analysis identified ribosomal proteins as critical players in antiviral response. The data also indicate that IFNα may influence the production of viral antigens associated with endoplasmic reticulum. Collectively, the intrahepatic transcriptome analyses in this study enriched our understanding of IFN-mediated antiviral effects in CHB patients and provided novel insights into the development of potential strategies to improve IFNα therapy.

Abstract 618: Discovery of predictive biomarkers of response to T cell-targeting biologics using ex vivo single-cell profiling coupled with TCR clonotype characterization

Abstract The discovery of predictive biomarkers of response is critical for forecasting patient benefit from novel immune-modulatory therapeutics. However, their discovery is hindered by the complexity of the drug modes of action and the lack of adequate biological models. We designed an approach to define biomarkers of response by subjecting dissociated tissue from human tumors to T cell-targeting biologics or their combinations, followed by single-cell transcriptomic profiling and TCR clonotype characterization. Responding cells are identified as those showing treatment-specific shifts in gene expression profiles. Specifically for T cells, TCR clonotypes can be used to match responding T cells in treatment conditions to their sister clones in the baseline state. Comparing the baseline gene expression profiles between T cell clonotypes that responded to the treatment and those that did not allows the discovery of gene expression signatures that can predict response. We processed over 20 tumor samples obtained from cancer patients and treated them ex vivo with two novel biologics currently under clinical development - HFB301001, a potentially best-in-class 2nd generation OX40 agonist, and HFB200301, a potentially first-in-class TNFR2 agonist. We applied our biomarker discovery strategy to the pooled scRNA-seq and scTCR-seq data from these samples to define predictive signatures of response to these drugs. To further validate this strategy, we also generated single-cell data in our ex vivo system to characterize response to anti-PD-1 treatment. In the anti-PD-1 predictive response signature, we identified genes involved in inflammatory response and genes in the pathway of other co-inhibitory checkpoints. Application of the anti-PD-1 predictive response signature to bulk transcriptomic data from clinical studies with checkpoint inhibitors successfully stratified patients into two groups with significantly different risk of progression. The predictive response signatures for the two novel agonistic antibodies shared genes involved in inflammatory pathway with the anti-PD-1 signature, but also contained other distinct gene sets. Application of these predictive response signatures to bulk transcriptomic data from TCGA was able to stratify patients across cancer indications by predicted likelihood of response to individual treatments or combinations. The predictive biomarkers of response for the novel OX40 and TNFR2 agonist antibodies will be validated in our Phase I clinical trials. Ex vivo single-cell profiling coupled with TCR clonotype characterization enabled the discovery of predictive response signatures that informed patient selection strategies for the early clinical development of novel therapeutics. Citation Format: Dean Lee, Monika Manne, Roshan Kumar, Rebecca Silver, Alexandra Staskus, Julianna Crivello, Zhiyuan Wang, Dohyun Lee, Ross Fulton, Zhizhan Gu, Christos Hatzis, Francisco Adrian, Andreas Raue, Liang Schweizer. Discovery of predictive biomarkers of response to T cell-targeting biologics using ex vivo single-cell profiling coupled with TCR clonotype characterization [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 618.

Integrative analysis reveals mouse strain-dependent responses to acute ozone exposure associated with airway macrophage transcriptional activity.

Acute ozone (O3) exposure is associated with multiple adverse cardiorespiratory outcomes, the severity of which varies across individuals in human populations and inbred mouse strains. However, molecular determinants of response, including susceptibility biomarkers that distinguish who will develop severe injury and inflammation, are not well characterized. We and others have demonstrated that airway macrophages (AMs) are an important resident immune cell type that are functionally and transcriptionally responsive to O3 inhalation. Here, we sought to explore influences of strain, exposure, and strain-by-O3 exposure interactions on AM gene expression and identify transcriptional correlates of O3-induced inflammation and injury across six mouse strains, including five Collaborative Cross (CC) strains. We exposed adult mice of both sexes to filtered air (FA) or 2 ppm O3 for 3 h and measured inflammatory and injury parameters 21 h later. Mice exposed to O3 developed airway neutrophilia and lung injury with strain-dependent severity. In AMs, we identified a common core O3 transcriptional response signature across all strains, as well as a set of genes exhibiting strain-by-O3 exposure interactions. In particular, a prominent gene expression contrast emerged between a low- (CC017/Unc) and high-responding (CC003/Unc) strain, as reflected by cellular inflammation and injury. Further inspection indicated that differences in their baseline gene expression and chromatin accessibility profiles likely contribute to their divergent post-O3 exposure transcriptional responses. Together, these results suggest that aspects of O3-induced respiratory responses are mediated through altered AM transcriptional signatures and further confirm the importance of gene-environment interactions in mediating differential responsiveness to environmental agents.

Gene Expression Profiling (GEP) As a Prognostic Indicator of Multiple Myeloma, Irrespective of Disease Stage, Prior Treatment and Prior Transplant - a Single Center Experience

BackgroundMultiple myeloma (MM) risk is classified using fluorescence in situ hybridization (FISH) routine cytogenetics, and gene expression profiling (GEP). GEP is a clinically validated tool for prognostication of MM in newly diagnosed and relapsed patients (pts), its role in very heavily treated stages is less clear. A study (Nishihori et al, ASH, 2016) concluded that GEP is useful regardless of disease stage. We aim to determine the prognostic significance of GEP heavily pre-treated MM cohort.Methods299 pts with MyPRSTM GEP results at Hackensack University Medical Center (NJ) between 2012 and 2016 were included. High risk GEP was defined with the validated cutoff score of >45.2, high risk FISH was determined according to the mSMART classification as del17p, t(14,16), t(14,20). Chi-square tests were performed on categorical data and Wilcoxon rank sum tests on continuous data. Overall survival (OS) and progression free survival (PFS) were performed using Kaplan-Meier.ResultsMedian age was 63 years (range, 25-91), 170 pts (56%) were men, 81 pts (28%) had International Staging System (ISS) 3 and 191 pts (62%) had Durie-Salmon Staging (DSS) III. 245 pts (81%) had at least one bone marrow transplant (BMT). Median time from myeloma diagnosis to GEP was 30.1 (range 0.1-178.4) months. Most pts had GEP on diagnosis but 24% were heavily pretreated (range, 1-6 lines of treatment), and 13% had a BMT prior to GEP testing. 77 pts (25%) had high-risk disease based on GEP with a median score of 36.5 (range, 9.03-84.05). Molecular subtypes were hyperdiploidy (HY) 31%, cyclin family (CD)-2 20%, low bone disease (LB) 13%, proliferation (PR) 11%, MAF associated (MF) 10%, CD-1 8%, and MMSET associated (MS) 6%. Median OS and PFS were significantly inferior in patients with high-risk by GEP, 25 vs 33 months (p<0.021), 13 vs 21 months (p<0.004) respectively. Molecular subtypes were not individual predictors of OS (p<0.2). When MF, MS and PR subtypes were combined, they had inferior OS compared to other subtypes but this was not statistically significant (p<0.3).ConclusionsGEP can accurately predict risk status in heavily pre-treated and post-transplant MM pts. In conclusion, our data confirm that GEP is a good prognostic indicator in MM pts irrespective of disease stage and prior treatments. Further prospective studies with larger samples and correlating with baseline and intra-treatment GEP are needed. DisclosuresRichter:Janssen: Speakers Bureau; BMS: Speakers Bureau; Takeda: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Amgen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Vesole:Takeda: Speakers Bureau; Celgene: Speakers Bureau. Siegel:Celgene, Takeda, Amgen Inc, Novartis and BMS: Consultancy, Speakers Bureau; Merck: Consultancy. Biran:Takeda: Speakers Bureau; Celgene, Amgen: Consultancy, Speakers Bureau.

Social boldness correlates with brain gene expression in male green anoles

Within populations, some individuals tend to exhibit a bold or shy social behavior phenotype relative to the mean. The neural underpinnings of these differing phenotypes – also described as syndromes, personalities, and coping styles – is an area of ongoing investigation. Although a social decision-making network has been described across vertebrate taxa, most studies examining activity within this network do so in relation to exhibited differences in behavioral expression. Our study instead focuses on constitutive gene expression in bold and shy individuals by isolating baseline gene expression profiles that influence social boldness predisposition, rather than those reflecting the results of social interaction and behavioral execution. We performed this study on male green anole lizards (Anolis carolinensis), an established model organism for behavioral research, which provides a crucial comparison group to investigations of birds and mammals. After identifying subjects as bold or shy through repeated reproductive and agonistic behavior testing, we used RNA sequencing to compare gene expression profiles between these groups within various forebrain, midbrain, and hindbrain regions. The ventromedial hypothalamus had the largest group differences in gene expression, with bold males having increased expression of neuroendocrine and neurotransmitter receptor and calcium channel genes compared to shy males. Conversely, shy males express more integrin alpha-10 in the majority of examined regions. There were no significant group differences in physiology or hormone levels. Our results highlight the ventromedial hypothalamus as an important center of behavioral differences across individuals and provide novel candidates for investigations into the regulation of individual variation in social behavior phenotype.

Predicting breast cancer drug response using a multiple-layer cell line drug response network model

BackgroundPredicting patient drug response based on a patient’s molecular profile is one of the key goals of precision medicine in breast cancer (BC). Multiple drug response prediction models have been developed to address this problem. However, most of them were developed to make sensitivity predictions for multiple single drugs within cell lines from various cancer types instead of a single cancer type, do not take into account drug properties, and have not been validated in cancer patient-derived data. Among the multi-omics data, gene expression profiles have been shown to be the most informative data for drug response prediction. However, these models were often developed with individual genes. Therefore, this study aimed to develop a drug response prediction model for BC using multiple data types from both cell lines and drugs.MethodsWe first collected the baseline gene expression profiles of 49 BC cell lines along with IC50 values for 220 drugs tested in these cell lines from Genomics of Drug Sensitivity in Cancer (GDSC). Using these data, we developed a multiple-layer cell line-drug response network (ML-CDN2) by integrating a one-layer cell line similarity network based on the pathway activity profiles and a three-layer drug similarity network based on the drug structures, targets, and pan-cancer IC50 profiles. We further used ML-CDN2 to predict the drug response for new BC cell lines or patient-derived samples.ResultsML-CDN2 demonstrated a good predictive performance, with the Pearson correlation coefficient between the observed and predicted IC50 values for all GDSC cell line-drug pairs of 0.873. Also, ML-CDN2 showed a good performance when used to predict drug response in new BC cell lines from the Cancer Cell Line Encyclopedia (CCLE), with a Pearson correlation coefficient of 0.718. Moreover, we found that the cell line-derived ML-CDN2 model could be applied to predict drug response in the BC patient-derived samples from The Cancer Genome Atlas (TCGA).ConclusionsThe ML-CDN2 model was built to predict BC drug response using comprehensive information from both cell lines and drugs. Compared with existing methods, it has the potential to predict the drug response for BC patient-derived samples.

A Comprehensive Analysis of Baseline Clinical Characteristics and Biomarkers Associated with Outcome in Advanced Melanoma Patients Treated with Pembrolizumab

Simple SummaryPembrolizumab, a monoclonal antibody targeting programmed cell death 1, improves the survival of patients with advanced melanoma. This study aimed to investigate the association of baseline clinical characteristics, laboratory and imaging variables, and gene expression profiling scores on tumor tissue analysis of advanced melanoma patients who were treated with pembrolizumab, with survival using univariate and multivariate analysis. Baseline organ function (reflected by the presence of active brain metastases, number of metastatically affected organs, albumin) and systemic inflammatory/immunologic status (reflected by albumin, C-reactive protein, absolute lymphocyte count, neutrophil-to-lymphocyte ratio) are the most important clinical and/or laboratory parameters predictive of survival. Novel biomarkers include the baseline presence of BRAFV600 or NRASQ61/G12/G13 mutant circulating tumor DNA and baseline total metabolic tumor volume assessed by whole-body 18F-FDG-PET/CT. Gene expression profiling scores by the NanoString PanCancer IO360 panel were not conclusive in our patient population.Background: Pembrolizumab improves the survival of patients with advanced melanoma. A comprehensive analysis of baseline variables that predict the benefit of pembrolizumab monotherapy has not been conducted. Methods: Survival data of patients with advanced melanoma who were treated with pembrolizumab in a single university hospital were collected. A multivariate Cox regression analysis was performed to correlate baseline clinical, laboratory, and radiologic characteristics and NanoString IO360 gene expression profiling (GEP) with survival. Results: 183 patients were included (stage IV 85.2%, WHO performance status ≥1 31.1%; pembrolizumab first-line 25.7%), of whom 112 underwent baseline 18F-FDG-PET/CT imaging, 58 had circulating tumor DNA (ctDNA) assessments, and GEP was available in 27 patients. Active brain metastases, a higher number of metastatic sites, lower albumin and absolute lymphocyte count (ALC), higher C-reactive protein (CRP) and neutrophil-to-lymphocyte ratio, higher total metabolic tumor volume (TMTV), and higher ctDNA levels were associated with worse survival. Elevated lactate dehydrogenase (LDH) ≥ 2ULN (upper limit of normal), CRP ≥ 10ULN, or ALC < 750/mm3 delineate a subpopulation where treatment with pembrolizumab is futile. A TMTV ≥ 80 mL encompassed 17/21 patients with LDH ≥ 2ULN, CRP ≥ 10ULN, or ALC < 750/mm3. No significant associations were observed between baseline GEP scores and survival. Conclusion: Multiple baseline variables correlate with survival on pembrolizumab. TMTV is a more comprehensive baseline biomarker than CRP, LDH, or ALC in predicting the futility of pembrolizumab.

Gene expression signatures associated with sensitivity to azacitidine in myelodysplastic syndromes

Allogeneic stem cell transplantation is currently the only curative treatment option for myelodysplastic syndromes (MDS). Pre-transplant debulking treatment have been employed for advanced MDS and we previously reported that marrow response (blast ≤ 5%) following the bridging therapy with hypomethylating agent was an independent favorable factor for survival; however, it is still not clear which patients will respond to hypomethylating agent and which genomic features can predict the response. In this study, we performed RNAseq for 23 MDS patients among which 14 (61%) and 9 (39%) patients showed marrow complete remission and primary resistance to azacitidine, respectively. Differential expression-based analyses of treatment-naive, baseline gene expression profiles revealed that molecular functions representing mitochondria and apoptosis were up-regulated in responders. In contrast, we identified genes involved in the Wnt pathway were relatively up-regulated in non-responders. In independent validation cohorts of MDS patients, the expression of gene sets specific to non-responders and responders distinguished the patients with favorable prognosis and those responded to azacitidine highlighting the prognostic and predictive implication. In addition, a systems biology approach identified genes involved in ubiquitination, such as UBC and PFDN2, which may be key players in the regulation of differential gene expression in treatment responders and non-responders. Taken together, identifying the gene expression signature may advance our understanding of the molecular mechanisms of azacitidine and may also serve to predict patient responses to drug treatment.

Integrative DNA Methylation and Gene Expression Analysis Reveals Candidate Biomarkers Associated with Dichotomized Response to Chemoimmunotherapy in Diffuse Large B-Cell Lymphoma

Background: Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin lymphoma. While 60% of DLBCL patients achieve complete remission with frontline therapy, relapsed/refractory (R/R) DLBCL patients have a poor prognosis with median overall survival below one year, necessitating investigation into the biological principles that distinguish cured from R/R DLBCL. Recent analyses have identified unfavorable molecular signatures when accounting for gene expression, copy number alterations and mutational profiles in R/R DLBCL. However, an integrative analysis of the relationship between epigenetic and transcriptomic changes has yet to be described. In this study, we compared baseline methylation and gene expression profiles of DLBCL patients with dichotomized clinical outcomes. Methods: Diagnostic DLBCL biopsies were obtained from two patient cohorts: patients who relapsed or were refractory following chemoimmunotherapy ("R/R"), and patients who entered durable clinical remission following therapy ("cured"). The median age for R/R and cured cohorts were 62 (range 35-86) years vs. 64 (range 28-83) years (P= 0.27). High-intermediate or high IPI scores were present in 14 vs. 6 patients (P= 0.08) in the R/R and cured cohorts, respectively. All patients were treated with frontline R-CHOP or R-EPOCH. DNA and RNA were extracted simultaneously from formalin-fixed, paraffin embedded biopsy samples. An Illumina 850k Methylation Array was used to identify DNA methylation levels in 29 R/R patients and 20 cured patients. RNA sequencing was performed on 9 R/R patients and 7 cured patients at diagnosis using Illumina HiSeq4000. Differentially methylated probes were identified using the DMRcate package, and differentially expressed genes were identified using the DESeq2 package. Gene set enrichment analysis was performed using canonical pathway gene sets from MSigDB. Results: At the time of diagnosis, we found significant epigenetic and transcriptomic differences between cured and R/R patients. Comparing cured to R/R samples, there were 8,159 differentially methylated probes (FDR&amp;lt;0.05). Differentially methylated regions between R/R and cured cohorts overlap with genes previously identified as mutation hotspots in DLBCL. Upon comparing transcriptomic profiles between R/R and cured, 267 genes were found to be differentially expressed (Log2FC&amp;gt;|1| and FDR&amp;lt;0.05). Gene set enrichment analysis revealed gene sets related to cell cycle, membrane trafficking, Rho and Rab family GTPase function, and transcriptional regulation were upregulated in the R/R samples. Gene sets related to innate immune signaling, Type I and II interferon signaling, fatty acid and carbohydrate metabolism were upregulated in the cured samples. To identify genes likely to be regulated by specific changes in methylation, we selected genes that were both differentially expressed and differentially methylated between the R/R and cured cohorts. In the R/R samples, 13 genes (ARMC5, ARRDC1, C12orf57, CCSER1, D2HGDH, DUOX2, FAM189B, FKBP2, KLF5, MFSD10, NEK8, NT5C, and WDR18) were significantly hypermethylated and underexpressed when compared to cured specimens, suggesting that epigenetic silencing of these genes is associated with lack of response to chemoimmunotherapy. In contrast, 12 genes (ATP2B1, C15orf41, FAM102B, FAM3C, FHOD3, FYTTD1, GPR180, KIAA1841, LRMP, MEF2A, RRAS2, and TPD52) were significantly hypermethylated and underexpressed in cured patients, suggesting that epigenetic silencing of these genes is favorable for treatment response. Many of these epigenetically modified genes have been previously implicated in cancer biology, including roles in NOTCH signaling, chromosomal instability, and biomarkers of prognosis. Conclusions: This is the first integrative epigenetic and transcriptomic analysis of diagnostic biopsies from cured and R/R DLBCL patients following chemoimmunotherapy. At the time of diagnosis, both the methylation and gene expression profiles significantly differ between patients that enter durable remission as opposed to those who are R/R to therapy. Soon, the hypomethylating agent CC-486 (i.e. oral azacitidine) will be explored in combination with mini-R-CHOP for older DLBCL patients in whom DNA methylation is likely increased. These data support the use of hypomethylating agents to potentially restore sensitivity of DLBCL to chemoimmunotherapy. Disclosures Hsi: Eli Lilly: Research Funding; Abbvie: Research Funding; Miltenyi: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; CytomX: Consultancy, Honoraria. Hill:Celgene: Consultancy, Honoraria, Research Funding; BMS: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria; Kite, a Gilead Company: Consultancy, Honoraria, Research Funding; AstraZenica: Consultancy, Honoraria, Research Funding; Pharmacyclics: Consultancy, Honoraria, Research Funding; Takeda: Research Funding; Beigene: Consultancy, Honoraria, Research Funding; Genentech: Consultancy, Honoraria, Research Funding; Abbvie: Consultancy, Honoraria, Research Funding; Karyopharm: Consultancy, Honoraria, Research Funding.

Pediatric Patients with Relapsed/Refractory Acute Lymphoblastic Leukemia Harboring Heterogeneous Genomic Profiles Respond to Venetoclax in Combination with Chemotherapy

Pediatric Patients with Relapsed/Refractory Acute Lymphoblastic Leukemia Harboring Heterogeneous Genomic Profiles Respond to Venetoclax in Combination with Chemotherapy

Immune profiling and clinical outcomes in patients treated with ramucirumab and pembrolizumab in phase I study JVDF.

3089 Background: In Study JVDF (NCT02443324), we combined ramucirumab (VEGFR2 antagonist) and pembrolizumab (PD-1 antagonist) to simultaneously target the tumor microenvironment and immune checkpoints in patients with advanced non-small cell lung cancer (NSCLC), gastric or gastroesophageal junction adenocarcinoma (G/GEJ), urothelial carcinoma (UC) or biliary tract cancer (BTC). We reported that this combination was associated with increased antitumor activity in patients with PD-L1 positive tumors by immunohistochemistry (IHC) compared with PD-L1 negative tumors.1) Here we explore the association between baseline gene expression profiles and clinical outcomes. Methods: JVDF was a nonrandomized phase 1a/b trial that treated patients with intravenous ramucirumab at 8 mg/kg on days 1 and 8 (G/GEJ, BTC) or 10 mg/kg on day 1 (G/GEJ, NSCLC, UC) plus pembrolizumab (200 mg day 1) every 3 weeks.1 Baseline tumor samples from 53 patients across 7 study cohorts were analyzed with the NanoString PanCancer Immune Profiling Panel for RNA expression and the DAKO PD-L1 IHC 22C3 pharmDx assay for PD-L1 protein expression. Clinical outcomes included progression-free survival (PFS), overall survival (OS), and objective response rate (ORR). Results: Across cohorts, PD-L1 gene expression was correlated with increased IFNγ gene expression and immune-related gene signatures (T effector, T cell-inflamed (TIS)), and trended with PD-L1 protein expression. Expression of immune checkpoint-related genes and myeloid-derived suppressor cell /regulatory T cell markers was increased in the NSCLC TPS≥50% PD-L1 IHC subgroup (N=8), while no clear pattern of expression was observed in other cohorts. Higher T effector and TIS scores appeared associated with better survival and response in NSCLC cohorts (mean TIS: 1.21±0.80 in responders (N=7) vs -0.13±0.57 in non-responders (N=7); p=0.004), and a trend was observed in G/GEJ cohorts (mean TIS: -0.18±0.30 (N=5) vs -0.39±0.21 (N=13); p=0.207). Of note, partial responses and stable disease were also observed in NSCLC and G/GEJ patients with a low baseline inflammatory signature score. Additional analyses are ongoing and will be presented. Conclusions: Baseline PD-L1 gene and protein expression tends to correlate with immune-related gene expression, and an inflamed tumor microenvironment may be associated with better clinical outcomes with ramucirumab and pembrolizumab. However, interpretation is limited by lack of control arm and sample size.1) Herbst et al. Lancet Oncol. 2019 Aug; 20 (8):1109-1123. Clinical trial information: NCT02443324 .

Predicting radiation-induced immune trafficking and activation in localized prostate cancer.

340 Background: Prostate cancer is frequently cured with high-dose rate brachytherapy as a front-line treatment. However, a significant number unfortunately develop intrinsic resistance. Although considered to be an immune-excluded tissue, immune responses are implicated in driving tumour-eradication in prostate cancer. This has not been proven, and yet is used as the rationale for numerous clinical trials combining radiation and immunotherapies. We hypothesise that there is a predictable but differential relationship between radiation and the immune responses in prostate cancer that could be used to fulfil a clinical need - identifying patients that would benefit from immune intervention in conjunction with radiation. Methods: We present here the results of comprehensive immunological profiling of a cohort of world-unique pre- and post-radiation tissues from 24 patients (RadBank cohort). These were assessed using pathological classification, tissue segmentation (cancer/surrounding stroma), multiplex IHC, gene expression profiling, T-cell receptor sequencing, and spatial computational analysis. Results: Our data resolved three classes of prostate cancer tissue based on immune infiltrate level, immune-activation and -checkpoint gene signatures, spatial clustering and T cell clone sequencing: We have begun to resolve clear patient and clinical classifiers based on immune responses to radiation, and identified patients groups likely to benefit from immune therapy alongside radiation. Conclusions: Importantly, these classifications are associated with baseline gene expression profiles that may be used for pre-clinical stratification and more sophisticated treatment paradigms.

A bendamustine resistance gene signature in diffuse large B-cell lymphoma and multiple myeloma.

Aim: Bendamustine is primarily used for treatment of indolent lymphomas but has shown efficacy in some patients with diffuse large B-cell lymphoma (DLBCL) and multiple myeloma (MM). Molecular-based patient stratification for identification of resistant patients, who will benefit from alternative treatments, is important. The aim of this study was to develop a resistance gene signature (REGS) from bendamustine dose-response assays in cultures of DLBCL and MM cell lines, enabling prediction of bendamustine response in DLBCL and MM patients.Methods: Bendamustine response was determined in 14 DLBCL and 11 MM cell lines. Using baseline gene expression profiles and degree of growth inhibition after bendamustine exposure, a bendamustine REGS was developed and examined for the risk stratification potential in DLBCL (n = 971) and MM (n = 1,126) patients divided into prognostic subtypes.Results: Bendamustine resistance significantly correlated with resistance to cyclophosphamide in DLBCL and melphalan in MM cell lines. The bendamustine REGS showed significantly lower bendamustine resistance probabilities in DLBCL patients with GCB subtype tumors and in tumors of the differentiation dependent centrocyte and plasmablast subtypes. In MM patients, pre-BII classified tumors displayed high bendamustine resistance probabilities and the plasma cell subtype had lower bendamustine resistance probability than memory cells. Furthermore, tumors belonging to the 4p14, MAF, and D2 TC subclasses consistently displayed high bendamustine resistance probabilities.Conclusion: Significant differences in predicted response to bendamustine were found in molecular subtypes of DLBCL and MM, encouraging validation in prospective bendamustine-treated cohorts with available gene expression profiles and follow-up data.