RNA-seq 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.

The Sprout Inhibitor 1,4-Dimethylnaphthalene Results in Common Gene Expression Changes in Potato Cultivars with Varying Dormancy Profiles

AbstractSprout suppression is a crucial aspect of maintaining postharvest Solanum tuberosum (potato) tuber quality. 1,4-dimethylnaphthalene (DMN) has demonstrated effective sprout suppression during long-term storage of potatoes. Its mode of action, however, remains unknown, and previous studies utilizing single cultivars preclude identification of a common response to treatment. Thus, the goal of this study was to identify common transcriptomic responses of multiple potato cultivars of varying dormancy lengths to DMN exposure during two dormancy stages. RNA-seq gene expression profiling supported differing sensitivity to DMN treatment dependent upon cultivar and dormancy stage. A limited number of genes with similar expression patterns were common to all cultivars. These were primarily identified in ecodormant tubers and were associated with cell cycle progression, hormone signaling, and biotic and abiotic stress response. DMN treatment resulted in significant upregulation of members of ANAC/NAC and WRKY transcription factor families. Investigation of affected protein-protein interaction networks revealed a small number of networks responsive to DMN in all cultivars. These results suggest that response to DMN is largely cultivar and dormancy stage-dependent, and the primary response is governed by a limited number of stress and growth-related genes and protein-protein interactions.

RNA-seq gene expression profiling of the bladder in a mouse model of urogenital schistosomiasis.

Parasitic flatworms of the Schistosoma genus cause schistosomiasis, which affects over 230 million people. Schistosoma haematobium causes the urogenital form of schistosomiasis (UGS), which can lead to hematuria, fibrosis, and increased risk of secondary infections by bacteria or viruses. UGS is also linked to bladder cancer. To understand the bladder pathology during S. haematobium infection, our group previously developed a mouse model that involves the injection of S. haematobium eggs into the bladder wall. Using this model, we studied changes in epigenetics profile, as well as changes in gene and protein expression in the host bladder tissues. In the current study, we expand upon this work by examining the expression level of both host and parasite genes using RNA sequencing (RNA-seq) in the mouse bladder wall injection model of S. haematobium infection. We used a mouse model of S. haematobium infection in which parasite eggs or vehicle control were injected into the bladder walls of female BALB/c mice. RNA-seq was performed on the RNA isolated from the bladders four days after bladder wall injection. RNA-seq analysis of egg- and vehicle control-injected bladders revealed the differential expression of 1025 mouse genes in the egg-injected bladders, including genes associated with cellular infiltration, immune cell chemotaxis, cytokine signaling, and inflammation We also observed the upregulation of immune checkpoint-related genes, which suggests that while the infection causes an inflammatory response, it also dampens the response to avoid excessive inflammation-related damage to the host. Identifying these changes in host signaling and immune responses improves our understanding of the infection and how it may contribute to the development of bladder cancer. Analysis of the differential gene expression of the parasite eggs between bladder-injected versus uninjected eggs revealed 119 S. haematobium genes associated with transcription, intracellular signaling, and metabolism. The analysis of the parasite genes also revealed fewer transcript reads compared to that found in the analysis of mouse genes, highlighting the challenges of studying parasite egg biology in the mouse model of S. haematobium infection.

The potential role of RNA sequencing in diagnosing unexplained insensitivity to conventional chemotherapy in pediatric patients with B-cell acute lymphoblastic leukemia

Pediatric B-cell acute lymphoblastic leukemia (B-ALL) is a highly heterogeneous disease. According to large-scale RNA sequencing (RNA-seq) data, B-ALL patients can be divided into more than 10 subgroups. However, many genomic defects associated with resistance mechanisms have not yet been identified. As an individual clinical tool for molecular diagnostic risk classification, RNA-seq and gene expression pattern-based therapy could be potential upcoming strategies. In this study, we retrospectively analyzed the RNA-seq gene expression profiles of 45 children whose molecular diagnostic classifications were inconsistent with the response to chemotherapy. The relationship between the transcriptome and chemotherapy response was analyzed. Fusion gene identification was conducted for the included patients who did not have known high-risk associated fusion genes or gene mutations. The most frequently detected fusion gene pair in the high-risk group was the DHRSX duplication, which is a novel finding. Fusions involving ABL1, LMNB2, NFATC1, PAX5, and TTYH3 at onset were more frequently detected in the high-risk group, while fusions involving LFNG, TTYH3, and NFATC1 were frequently detected in the relapse group. According to the pathways involved, the underlying drug resistance mechanism is related to DNA methylation, autophagy, and protein metabolism. Overall, the implementation of an RNA-seq diagnostic system will identify activated markers associated with chemotherapy response, and guide future treatment adjustments.

Protein arginine methyltransferases PRMT1, PRMT4/CARM1 and PRMT5 have distinct functions in control of osteoblast differentiation

Osteogenic differentiation of mesenchymal cells is controlled by epigenetic enzymes that regulate post-translational modifications of histones. Compared to acetyl or methyltransferases, the physiological functions of protein arginine methyltransferases (PRMTs) in osteoblast differentiation remain minimally understood. Therefore, we surveyed the expression and function of all nine mammalian PRMT members during osteoblast differentiation. RNA-seq gene expression profiling shows that Prmt1, Prmt4/Carm1 and Prmt5 represent the most prominently expressed PRMT subtypes in mouse calvarial bone and MC3T3 osteoblasts as well as human musculoskeletal tissues and mesenchymal stromal cells (MSCs). Based on effects of siRNA depletion, it appears that PRMT members have different functional effects: (i) loss of Prmt1 stimulates and (ii) loss of Prmt5 decreases calcium deposition of mouse MC3T3 osteoblasts, while (iii) loss of Carm1 is inconsequential for calcium deposition. Decreased Prmt5 suppresses expression of multiple genes involved in mineralization (e.g., Alpl, Ibsp, Phospho1) consistent with a positive role in osteogenesis. Depletion of Prmt1, Carm1 and Prmt5 has intricate but modest time-dependent effects on the expression of a panel of osteoblast differentiation and proliferation markers but does not change mRNA levels for select epigenetic regulators (e.g., Ezh1, Ezh2, Brd2 and Brd4). Treatment with the Class I PRMT inhibitor GSK715 enhances extracellular matrix mineralization of MC3T3 cells, while blocking formation of H3R17me2a but not H4R3me2a marks. In sum, Prmt1, Carm1 and Prmt5 have distinct biological roles during osteoblast differentiation, and different types histone H3 and H4 arginine methylation may contribute to the chromatin landscape during osteoblast differentiation.

Tumor immune infiltrates and overall survival in non-small cell lung cancer are associated with an unsupervised radiomic signature.

e20525 Background: We investigated whether radiomic features derived from computed tomography (CT) scans are predictive of survival and are correlated with immune cell types in non-small cell lung cancer (NSCLC), employing a mathematical network-based approach. Methods: DICOM data of pre-treatment CT scans and associated clinical variables for 116 NSCLC patients were downloaded from The Cancer Imaging Atlas (TCIA). RNA-Seq gene expression profiles for the matched cases were downloaded from the GEO database (GSE103584). CIBERSORT scores that consist of 22 immune cell types were generated using the R library (CIBERSORT) on the RNA-Seq gene expression profiles. From contoured tumors on CT scans, 83 radiomic features including tumor volume were extracted, utilizing the CERR radiomics toolbox. Radiomic networks were constructed with a threshold of Spearman correlation coefficient of 0.85 between each pair of radiomic features. The mathematical network-based k-means clustering method was applied to the largest connected network component that consists of 40 radiomic features, using the Wasserstein distance from optimal mass transport (OMT), to minimize the summed distance between k partitioned centroids and their respective data points. For the sub-groups identified, Kaplan-Meier survival analysis was conducted with log-rank test and CIBERSORT scores and clinical variables were then compared among the sub-groups using Kruskal-Wallis test. Results: The median age was 69 years (range: 46–85 years). Eighty-seven patients (75.0%) were males. Most patients were former (N = 75, 64.7%) or current smokers (N = 24, 20.7%). The median follow-up time (last follow-up or death) was 44 months and 75 patients were alive at last contact. The Wasserstein distance-based k-means method resulted in 3 sub-groups (high: N = 32, medium: N = 45, low-risk: N = 39). Kaplan-Meier analysis on the 3 sub-groups showed a significant difference in overall survival with log-rank p = 0.02. There were no significant differences for the variables mentioned above among the sub-groups. Two immune cell types showed statistically significant differences among the sub-groups: mast cells resting with p = 0.004 and M2 macrophages with p = 0.013 using Kruskal-Wallis test. The values for both immune cell types increased from high < medium < low-risk group. There was a significant volume difference with p < 0.001, but the difference did not fully account for the survival difference; the median volume was 30.8 cc, 2.7 cc, and 12.8 cc for high, medium, and low-risk groups, respectively. Conclusions: A radiomic network analysis, utilizing a mathematical network-based method, resulted in sub-groups with the survival difference in NSCLC patients. Furthermore, these sub-groups had significantly different immune cell types likely associated with the survival.

Abstract 6485: Oxidative phosphorylation-associated radiomic feature and survival of women with serous ovarian cancer

Abstract Novel biomarkers that can be utilized for clinical decision support to improve patient outcomes are critically needed for ovarian cancer. At present, there are no standard of care biomarkers to inform the first-line treatment regimen (neoadjuvant chemotherapy vs. upfront surgical debulking) best suited for each patient or which patients are at the highest risk of recurrence. To address this unmet need, we identified pre-treatment computed tomography (CT) image-based radiomic features predictive of outcomes and primary treatment response among 298 women diagnosed with serous ovarian cancer from 2008 to 2019. A decision tree analysis identified a single volumetric feature, region of interest (ROI) volume center of mass (CoM) in the X direction, as the most informative radiomic feature that stratified patients with upfront surgery into high- and low-risk groups for overall survival. The high-risk group consists of patients with higher values of the radiomic feature. In the training (N=91) and test (N=91) cohorts of women treated with upfront surgery, high-risk patients had worse survival compared to low-risk patients (HR=2.01, 95% CI=1.07, 3.77 and HR=2.23, 95% CI=1.19, 4.17, respectively). This radiomic feature was not associated with survival among women treated with neoadjuvant chemotherapy (N=116; HR=1.23, 95% CI=0.73, 2.07). To reveal potential underlying biology of this radiomic feature, we performed RNAseq gene expression profiling on 47 formalin-fixed paraffin-embedded tumor specimens and correlated gene expression with the radiomic feature using DESeq2 from RSEM estimates. Dichotomized analysis (high- vs. low-risk) yielded 7 significant genes and continuous analysis yielded 15 significant genes (adjusted p<0.05), with both approaches identifying AKT2 and PSMC4. Gene set enrichment analysis (GSEA) was used to identify enriched gene sets from continuous associations using the MSigDB Hallmarks pathways (adjusted p<0.05). GSEA identified the oxidative phosphorylation (OXPHOS) pathway as one of the gene sets most negatively associated with the predictive radiomic feature (Hallmark Normalized Enrichment Score=-2.28, adjusted p<0.001). We derived a PCA-based gene signature from significantly associated OXPHOS genes (p<0.01) resulting in a negative correlation with the radiomic feature (R=-0.65, p<0.001). Prior studies have shown that high OXPHOS ovarian tumors are associated with an increased response to conventional chemotherapy, suggesting that OXPHOS may be a key pathway for chemoresistance in ovarian cancer. In summary, we identified an OXPHOS-associated radiomic feature predictive of survival among women with serous ovarian cancer treated with upfront surgery. Further research is needed to elucidate the biologic and mechanistic underpinnings of the identified radiomic feature and to validate these findings in a larger cohort of women with ovarian cancer. Citation Format: Christelle Colin-Leitzinger, Jaileene Perez-Morales, Steven Eschrich, Jamie K. Teer, Sweta Sinha, Melissa J. McGettigan, Daniel K. Jeong, Olya Stringfield, Mahmoud A. Abdalah, Natarajan Raghunand, Robert J. Gillies, Jing-Yi Chern, Matthew Schabath, Lauren Cole Peres. Oxidative phosphorylation-associated radiomic feature and survival of women with serous ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6485.

Transcriptome analysis of Ganoderma lingzhi (Agaricomycetes) response to Trichoderma hengshanicum infection.

Green mold caused by Trichoderma spp. has become one of the most serious diseases which threatening the production of Ganoderma lingzhi. To understand the possible resistance mechanism of the G. lingzhi response to T. hengshanicum infection, we examined the G. lingzhi transcript accumulation at 0, 12, and 24 h after T. hengshanicum inoculation. The gene expression analysis was conducted on the interaction between G. lingzhi and T. hengshanicum using RNA-seq and digital gene expression (DGE) profiling methods. Transcriptome sequencing indicated that there were 162 differentially expressed genes (DEGs) at three infection time points, containing 15 up-regulated DEGs and 147 down-regulated DEGs. Resistance-related genes thaumatin-like proteins (TLPs) (PR-5s), phenylalanine ammonia-lyase, and Beta-1,3-glucan binding protein were significantly up-regulated. At the three time points of infection, the heat shock proteins (HSPs) genes of G. lingzhi were down-regulated. The down-regulation of HSPs genes led to the inhibition of HSP function, which may compromise the HSP-mediated defense signaling transduction pathway, leading to G. lingzhi susceptibility. Pathway enrichment analyses showed that the main enriched pathways by G. lingzhi after infection were sphingolipid metabolism, ether lipid metabolism, and valine, leucine and isoleucine degradation pathway. Overall, the results described here improve fundamental knowledge of molecular responses to G. lingzhi defense and contribute to the design of strategies against Trichoderma spp.

A Systems Biology Approach for Investigating Significant Biomarkers and Drug Targets Common Among Patients with Gonorrhea, Chlamydia, and Prostate Cancer: A Pilot Study.

Having a previous history of sexually transmitted diseases (STDs) such as gonorrhea and chlamydia increases the chance of developing prostate cancer, the second most frequent malignant cancer among men. However, the molecular functions that cause the development of prostate cancer in persons with gonorrhea and chlamydia are yet unknown. In this study, we studied RNA-seq gene expression profiles using computational biology methods to find out potential biomarkers that could help us in understanding the patho-biological mechanisms of gonorrhea, chlamydia, and prostate cancer. Using statistical methods on the Gene Expression Omnibus (GEO) data sets, it was found that a total of 22 distinct differentially expressed genes were shared among these 3 diseases of which 14 were up-regulated (PGRMC1, TSC22D1, SH3BGRL, NNT, CTSC, FRMD3, CCR2, FAM210B, VCL, PTGS1, SLFN11, SLC40A1, PROS1, and DSE) and the remaining 8 genes were down-regulated (PRNP, HINT3, MARCKSL1, TMED10, SH3KBP1, ENSA, DERL1, and KMT2B). Investigation on these 22 unique dysregulated genes using Gene Ontology, BioCarta, KEGG, and Reactome revealed multiple altered molecular pathways, including regulation of amyloid precursor protein catabolic process, ferroptosis, effects on gene expression of Homo sapiens PPAR pathway, and innate immune system R-HSA-168249. Four significant hub proteins namely VCL, SH3KBP1, PRNP, and PGRMC1 were revealed by protein-protein interaction network analysis. By analyzing gene-transcription factors and gene-miRNAs interactions, significant transcription factors (POU2F2, POU2F1, GATA6, and HIVEP1) and posttranscriptional regulator microRNAs (hsa-miR-7-5p) were also identified. Three potential therapeutic compounds namely INCB3284, CCX915, and MLN-1202 were found to interact with up-regulated protein C-C chemokine receptor type 2 (CCR2) in protein-drug interaction analysis. The proposed biomarkers and therapeutic potential molecules could be investigated for potential pharmacological targets and activity in the fight against in patients with gonorrhea, chlamydia, and prostate cancer.

Computationally Efficient Assembly of Pseudomonas aeruginosa Gene Expression Compendia.

Thousands of Pseudomonas aeruginosa RNA sequencing (RNA-seq) gene expression profiles are publicly available via the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA). In this work, the transcriptional profiles from hundreds of studies performed by over 75 research groups were reanalyzed in aggregate to create a powerful tool for hypothesis generation and testing. Raw sequence data were uniformly processed using the Salmon pseudoaligner, and this read mapping method was validated by comparison to a direct alignment method. We developed filtering criteria to exclude samples with aberrant levels of housekeeping gene expression or an unexpected number of genes with no reported values and normalized the filtered compendia using the ratio-of-medians method. The filtering and normalization steps greatly improved gene expression correlations for genes within the same operon or regulon across the 2,333 samples. Since the RNA-seq data were generated using diverse strains, we report the effects of mapping samples to noncognate reference genomes by separately analyzing all samples mapped to cDNA reference genomes for strains PAO1 and PA14, two divergent strains that were used to generate most of the samples. Finally, we developed an algorithm to incorporate new data as they are deposited into the SRA. Our processing and quality control methods provide a scalable framework for taking advantage of the troves of biological information hibernating in the depths of microbial gene expression data and yield useful tools for P. aeruginosa RNA-seq data to be leveraged for diverse research goals. IMPORTANCE Pseudomonas aeruginosa is a causative agent of a wide range of infections, including chronic infections associated with cystic fibrosis. These P. aeruginosa infections are difficult to treat and often have negative outcomes. To aid in the study of this problematic pathogen, we mapped, filtered for quality, and normalized thousands of P. aeruginosa RNA-seq gene expression profiles that were publicly available via the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA). The resulting compendia facilitate analyses across experiments, strains, and conditions. Ultimately, the workflow that we present could be applied to analyses of other microbial species.

Direct Proteomic Detection and Prioritization of 19 Onchocerciasis Biomarker Candidates in Humans

Onchocerca volvulus, the causative agent of onchocerciasis, infects over 20 million people and can cause severe dermatitis and ocular conditions including blindness. Current treatments employed in mass drug administration programs do not kill adult female worms, and common diagnostic tests cannot reliably assess viability of adult worms. There is an urgent need for better diagnostic tests to facilitate monitoring the efficacy of new treatments and disease elimination efforts. Here, eight plasma samples collected from individuals infected with O. volvulus and seven from uninfected individuals were analyzed by MS/MS spectrometry to directly identify O. volvulus proteins present in infected but absent in uninfected control samples. This direct proteomic approach for biomarker discovery had not been previously employed for onchocerciasis. Among all detected proteins, 19 biomarker candidates were supported by two or more unique peptides, identified in the plasma of at least three O. volvulus-infected human samples and absent in all control samples. Comprehensive analysis and ranking of these candidates included detailed functional annotation and a review of RNA-seq gene expression profiles. Isotope-labeled standard peptides were run in parallel and validated MS/MS peptide identifications for 15 peptides from 11 of the 19 proteins, and two infected urine and one uninfected urine sample was used for additional validation. A major antigen/OVOC11613 was identified as the most promising candidate with eight unique peptides across five plasma samples and one urine sample. Additional strong candidates included OVOC1523/ATP synthase, OVOC247/laminin and OVOC11626/PLK5, and along with OVOC11613, and were also detected in urine samples from onchocerciasis patients. This study has identified a promising novel set of proteins that will be carried forward to develop assays that can be used for diagnosis of O. volvulus infections and for monitoring treatment efficacy.

The Differential Paracrine Role of the Endothelium in Prostate Cancer Cells.

Simple SummaryA growing body of literature supports the concept that a tumor mass is under the strict control of the microvascular endothelium and that the perfusion of oxygen and nutrients by capillary vessels to the tumor mass is reinforced by potent paracrine activity from the vascular endothelial cells. In our study, we investigate the biological and molecular implications of the paracrine crosstalk between vascular endothelial cells and prostate cancer cells. Our results indicate that the endothelial cells were able to secrete molecular signals that promote the proliferation and growth of low and highly aggressive prostate cancer cells and selectively increased the migration, invasion and metastatic potential of highly aggressive prostate cancer cells. The molecular analyses indicated that endothelial cells induced a differential effect on gene expression profile when comparing low versus highly aggressive prostate cancer cells, causing an enrichment of epigenetic changes in migratory pathways in highly aggressive prostate cancer cells. In conclusion, our results indicate that endothelial cells release signals that favor tumor growth and aggressiveness and that this interaction may play an important role in the progression of prostate cancer.The survival of patients with solid tumors, such as prostate cancer (PCa), has been limited and fleeting with anti-angiogenic therapies. It was previously thought that the mechanism by which the vasculature regulates tumor growth was driven by a passive movement of oxygen and nutrients to the tumor tissue. However, previous evidence suggests that endothelial cells have an alternative role in changing the behavior of tumor cells and contributing to cancer progression. Determining the impact of molecular signals/growth factors released by endothelial cells (ECs) on established PCa cell lines in vitro and in vivo could help to explain the mechanism by which ECs regulate tumor growth. Using cell-conditioned media collected from HUVEC (HUVEC-CM), our data show the stimulated proliferation of all the PCa cell lines tested. However, in more aggressive PCa cell lines, HUVEC-CM selectively promoted migration and invasion in vitro and in vivo. Using a PCa-cell-line-derived xenograft model co-injected with HUVEC or preincubated with HUVEC-CM, our results are consistent with the in vitro data, showing enhanced tumor growth, increased tumor microvasculature and promoted metastasis. Gene set enrichment analyses from RNA-Seq gene expression profiles showed that HUVEC-CM induced a differential effect on gene expression when comparing low versus highly aggressive PCa cell lines, demonstrating epigenetic and migratory pathway enrichments in highly aggressive PCa cells. In summary, paracrine stimulation by HUVEC increased PCa cell proliferation and tumor growth and selectively promoted migration and metastatic potential in more aggressive PCa cell lines.

Abstract IA004: Mesenchymal progenitors and sarcomagenesis

Abstract Synovial sarcoma (SS) is an aggressive soft-tissue malignancy that can arise in any area of the body, and most frequently affects adolescents and young adults. The 10-year survival rate has been estimated at 50%. SS is characterized by a pathognomonic t(X;18)(p11.2;q11.2) translocation which produces a fusion oncogene named SS18-SSX. In mouse models, expression of SS18-SSX is sufficient to drive the development of SS-like tumors. Despite recent advancements in our understanding of SS biology, the cell of origin remains undefined. In most instances, it is likely mesenchymal in nature. We previously generated a mesenchymal progenitor (MP) specific Cre line that has enabled us to identify MPs within the embryo [MOU1], and characterize and define their lineage trajectories through development into the adult. This line has been used to generate a unique mouse model of SS where the human SS18-SSX fusion oncogene with an EGFP marker is conditionally expressed in adult MPs. This model shows 100% penetrant SS tumor formation with a median latency period of 16 weeks. Histologic analyses of tumors reveal characteristic cellular morphology and the expression of common markers of SS. Single-cell (sc) RNA-seq gene expression profiles of murine tumors recapitulate those observed in human SS samples and highlight genetic programs involved in sarcomagenesis. Using this model, we can identify and isolate neoplastic lesions prior to the development of grossly visible tumors and trace these cells through the complete transformation continuum. By comparing tumor cells to normal MPs, we aim to better understand the mechanisms underlying the SS18-SSX induced transformation of MPs. Together, this model identifies a cell of origin for SS and provides us with a unique opportunity to address the molecular and cellular drivers of SS. Citation Format: T. Michael Underhill. Mesenchymal progenitors and sarcomagenesis [abstract]. In: Proceedings of the AACR Special Conference: Sarcomas; 2022 May 9-12; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2022;28(18_Suppl):Abstract nr IA004.

Identification of key molecules in COVID-19 patients significantly correlated with clinical outcomes by analyzing transcriptomic data.

BackgroundAlthough several key molecules have been identified to modulate SARS-CoV-2 invasion of human host cells, the molecules correlated with outcomes in COVID-19 caused by SARS-CoV-2 infection remain insufficiently explored.MethodsThis study analyzed three RNA-Seq gene expression profiling datasets for COVID-19 and identified differentially expressed genes (DEGs) between COVID-19 patients and normal people, commonly in the three datasets. Furthermore, this study explored the correlation between the expression of these genes and clinical features in COVID-19 patients.ResultsThis analysis identified 13 genes significantly upregulated in COVID-19 patients’ leukocyte and SARS-CoV-2-infected nasopharyngeal tissue compared to normal tissue. These genes included OAS1, OAS2, OAS3, OASL, HERC6, SERPING1, IFI6, IFI44, IFI44L, CMPK2, RSAD2, EPSTI1, and CXCL10, all of which are involved in antiviral immune regulation. We found that these genes’ downregulation was associated with worse clinical outcomes in COVID-19 patients, such as intensive care unit (ICU) admission, mechanical ventilatory support (MVS) requirement, elevated D-dimer levels, and increased viral loads. Furthermore, this analysis identified two COVID-19 clusters based on the expression profiles of the 13 genes, termed COV-C1 and COV-C2. Compared with COV-C1, COV-C2 more highly expressed the 13 genes, had stronger antiviral immune responses, were younger, and displayed more favorable clinical outcomes.ConclusionsA strong antiviral immune response is essential in reducing severity of COVID-19.

Feasibility of an explainable AI-based therapeutic recommendation-tool utilizing tumor gene expression profiles in advanced and refractory solid tumors.

1554 Background: Precision oncology aims to guide patient (pts) treatment decisions by matching biological features with available drugs. Extensive genomic analysis allows to identify an actionable alteration in 40-60% of patients. In a recent study of 50 pts with advanced refractory diseases included in PROFILER (NCT01774409), whole exome and fusion transcripts had a limited value over a 90-tumor gene panel (TGP) to increase molecular-based treatment recommendations (MBTR). Herein, we evaluated the feasibility, in the same cohort of pts, of the AI-transcriptional-based therapeutic recommendation-tool OncoKEM to guide treatment recommendations. Methods: 77 fresh frozen (FF) and/or FFPE samples including paired specimens for 53 pts with available RNA-Seq gene expression profiles were included. For each pts, a tumor transcriptional profile (TTP) was generated by identifying differentially expressed genes between the pts tumor and a cohort of matched healthy tissue. A large database of drug transcriptional signatures (DTS) was queried in order to identify a “reversal relationship” between the TTP and a DTS. A total of 205 drugs were ranked, including a subset of 61 FDA and/or EMA approved targeted therapies (aTT). Results: Most common diagnoses were breast cancers (21% of which 63% were TNBC), followed by ovarian cancers (OC, 18%) and soft-tissue sarcomas (STS, 13%). The median number of previous treatment lines was 4 (range: 1 - 10). Among the 77 tumor samples analyzed, 54 (70%) specimens led to the generation of an OncoKEM report, with no differences between FF and FFPE samples (p = 0.85). The overlap between the top 10 proposed drugs between paired FF and FFPE samples was 56% on average. All patients had at least 2 propositions (range: 2-9) of aTT among the top 10 ranked drugs in the Onco KEM reports. Most frequently proposed drugs among the top 10 were palbociclib, talazoparib, infigratinib in TNBC; bosutinib, sapanisertib, SAR125844 in OC; ipilimumab, cabozantinib, sapanisertib in STS. Among the 30 pts (79%) without any MBTR based on TGP/WES/fusion transcript analysis, all had at least 2 proposed aTT in the Onco KEM report (median: 4, range: 2-9). Top ranked drugs were MET (18%), VEGFR (12%), Abl (12%), FGFR (11%), PI3K/AKT/mTOR (11%), PARP (10%) and CDK4/6 inhibitors (7%). Conclusions: AI-transcriptional-based therapeutic recommendation-tool OncoKEM is feasible and has the potential to expand personalized cancer treatment in pts with advanced & refractory diseases without tractable genomic alterations. The clinical relevance assessment is planned in an upcoming clinical trial.

Abstract P1-04-02: Immune milieu associated with PD-L1 status in TNBC is dependent on time of biomarker assessment and treatment received: A secondary analysis of the NeoTRIPaPDL1 trial

Abstract Background - In the NeoTRIPaPDL1 phase III trial, triple-negative breast cancer (TNBC) patients were randomized to receive nab-paclitaxel/carboplatin for 8 cycles (CT arm) with or without atezolizumab (CT/A arm). We previously reported that the majority of patients (65%) with PD-L1- at baseline converted to PD-L1+ (the majority with IC2/IC3) after the first cycle of treatment in the atezolizumab arm. Here we studied treatment associated changes in the molecular tumour features and immune microenvironment by PD-L1 expression. Methods – A total of 158 (56.4%) of patients enrolled in the NeoTRIPaPDL1 trial (76 and 82 from CT/A and CT arm, respectively) were included in this analysis by satisfying the following criteria: i) availability of a paired core biopsy at baseline and at day 1 of the second treatment cycle (D1C2); ii) evaluation of stromal TILs (sTILs) and staining for PD-L1 (Ventana SP142); iii) successful RNA-seq gene expression profiling. PD-L1 groups were defined as IC0/IC1 (<5% PD-L1low) vs IC2/IC3 (>=5% PD-L1high). Presence of different immune cell populations was quantified by gene expression profile deconvolution using ConsensusTME R package. Cancer hallmark gene set collection and custom signature activation status were estimated in each sample using singscore R package. Differences in score distribution were evaluated by 2-sided t-test. Results At baseline, both sTILs and immune cell signatures were upregulated in PD-L1high compared to PD-L1low tumours (p<0.001). No significant differences were found between the two treatment arms in the PD-L1high subpopulation. In the PD-L1low cases, both sTILs and immune related signatures were slightly downregulated in the CT/A arm (p<0.05), suggesting a modest unbalance among treatment arms with CT arm being slightly more inflamed than CT/A arm.At D1C2, PD-L1high tumours in the CT arm systematically had high sTILs (median=70%, range=30-90%), while PD-L1low tumours receiving CT/A had low sTILs in a significant proportion of cases (median=30%, range=0-90%; p<0.001). Similarly, at D1C2 several gene expression-estimated immune cell populations and immune-related signatures were upregulated in the CT arm compared to CT/A arm in PD-L1high tumours, with the weakest association observed for M2 macrophages (p=0.058). No tumour-related signatures were differentially expressed among the two treatment arms within groups with PD-L1high, suggesting that different treatment. modulate PD-L1 by engaging a different immune mileau instead of modulating tumor related features.Considering PD-L1low groups at D1C2, in the CT arm 21 tumors had >30% sTILs (n=21/69, 30.4%), while in the CT/A arm only 2 had sTILs >30% (2/27, 7.4%) (p<0.001). Analysis of gene expression data identified IFN-related signatures as the most upregulated in the CT compared to CT/A arm in PD-L1low cases at D1C2 (p<0.05). Conclusions Integrated dynamic analysis of PD-L1 expression and gene expression data highlighted significant treatment-specific changes of the immune landscape according to PD-L1 expression, when this biomarker is assessed during treatment. This indicates that the immune milieu associated with PD-L1 status is strongly dependent on the time of assessment in relationship to treatment received. Such observation may explain why in the NeoTRIP trial, baseline PD-L1 but not on-treatment PD-L1 was predictive of pCR in CT/A arm. In addition, our findings could have implications related to the use of PD-L1 as a predictive biomarker in pre-treated patients, especially when assessed early on during treatment. Citation Format: Maurizio Callari, Chiun-Sheng Huang, Daniel Egle, Begoña Bermejo, Claudio Zamagni, Matteo Dugo, Marc Thill, Antonio Anton, Marco Barreca, Stefania Russo, Eva Maria Ciruelos, Richard Greil, Stefania Zambelli, Balázs Gyorffy, Chanel Smart, Olivia Biasi, Pinuccia Valagussa, Giuseppe Viale, Luca Gianni, Giampaolo Bianchini. Immune milieu associated with PD-L1 status in TNBC is dependent on time of biomarker assessment and treatment received: A secondary analysis of the NeoTRIPaPDL1 trial [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P1-04-02.

Anti-microRNA-21 Therapy on Top of ACE Inhibition Delays Renal Failure in Alport Syndrome Mouse Models.

Col4a3−/− Alport mice serve as an animal model for renal fibrosis. MicroRNA-21 (miR-21) expression has been shown to be increased in the kidneys of Alport syndrome patients. Here, we investigated the nephroprotective effects of Lademirsen anti-miR-21 therapy. We used a fast-progressing Col4a3−/− mouse model with a 129/SvJ background and an intermediate-progressing F1 hybrid mouse model with a mixed genetic background, with angiotensin-converting enzyme inhibitor (ACEi) monotherapy in combination with anti-miR-21 therapy. In the fast-progressing model, the anti miR-21 and ACEi therapies showed an additive effect in the reduction in fibrosis, the decline of proteinuria, the preservation of kidney function and increased survival. In the intermediate-progressing F1 model, the anti-miR-21 and ACEi therapies individually improved kidney pathology. Both also improved kidney function and survival; however, the combination showed a significant additive effect, particularly for survival. RNA sequencing (RNA-seq) gene expression profiling revealed that the anti-miR-21 and ACEi therapies modulate several common pathways. However, anti-miR-21 was particularly effective at normalizing the expression profiles of the genes involved in renal tubulointerstitial injury pathways. In conclusion, significant additive effects were detected for the combination of anti-miR-21 and ACEi therapies on kidney function, pathology and survival in Alport mouse models, as well as a strong differential effect of anti-miR-21 on the renal expression of fibrotic factors. These results support the addition of anti-miR-21 to the current standard of care (ACEi) in ongoing clinical trials in patients with Alport syndrome.

5hmC Gene Signature Predicts the Treatment Response to Azacitidine with High-Dose Cytarabine and Mitoxantrone in AML

IntroductionAcute myeloid leukemia (AML) is an aggressive disease with genetic and phenotypic heterogeneity that results in a highly variable response to standard chemotherapy. Azacitidine (AZA) is a hypomethylating agent (HMA) and has been investigated in combination with intensive chemotherapy as an epigenetic primer to sensitize leukemic cells to treatment. In a phase 1 trial, this regimen was safe and well-tolerated with overall response rate (CR+CRi) of 61% and complete remission rate of 41% (Cahill et al, Blood Adv 2020). Predictive biomarkers for response to this treatment strategy have not yet been identified. Since 5-hydroxymethylcytosine (5hmC) is an epigenetic biomarker in cancer, we hypothesized that Nano-5hmC-Seal sequencing technology may serve as a novel approach to identifying 5hmC profiles predictive of treatment response to epigenetic priming.MethodsWe performed RNA-seq gene expression and Nano-5hmC-Seal DNA profiling from peripheral blood/bone marrow samples of patients with high-risk AML to identify potential 5hmC profile biomarkers and gene expression changes (Figure 1A). Patients (n=46) were treated in a 3+3 dose-escalation scheme of AZA (37.5 mg/m 2, 50 mg/m 2, or 75 mg/m 2) on days 1-5 followed by high-dose cytarabine (3000 mg/m 2) and mitoxantrone (30 mg/m 2) (AZA-HiDAC-Mito) on day 6 and day 10 in a phase 1 trial previously reported (Cahill et al, Blood Adv 2020). We compared pre-treatment RNA-seq gene expression and 5hmC DNA profiles between responders (CR+CRi) and non-responders, as well as between pre-treatment and after 5 days of AZA for individual patients. We used an XGBoost machine learning model in Python based on a training set of patients to develop a 5hmC gene signature to predict response to AZA-HiDAC-Mito in an independent test set of patients. We compared continuous variables with two-tailed Student's t-test and used the Kaplan-Meier method with log-rank test for survival analysis.ResultsThirty-three patients (72%) had adequate RNA samples for RNA-seq gene expression analysis. Eighteen responded to treatment (CR +CRi) and were enriched with gene expression patterns involved in cell-cell interaction and activation of cell cycle, while non-responders (n=15) had a higher expression of leukemic stem cell (LSC) signatures. There was no difference in gene expression profile when comparing pre-treatment samples to day 5 samples after AZA exposure. From the 5hmC profiling [n=40 (87%) patients with adequate samples], increased 5hmC in LSC genes was associated with treatment resistance to AZA-HiDAC-Mito (p=0.044). The number of differentially hydroxy-methylated genes (DhMGs) increased with higher doses of AZA exposure suggesting a dose-dependent epigenetic effect from AZA. Patients with a greater number of DhMGs following 5 days of AZA treatment had improved survival (p=0.015) (Figure 1B). Using the 5hmC-based XGBoost machine learning model comparing 5hmC profiles between responders to non-responders from a training set of patients (n=22), we developed an 11-gene 5hmC pre-treatment signature (including SKP1, WNT8A, CYP2E1, and NBPF9) to predict treatment response. The model was highly effective in predicting response to therapy, with an area under the curve (AUC) of 0.86 in an independent test set of patients (n=18) treated with AZA-HiDAC-Mito (Figure 1C).ConclusionIn patients with AML treated with AZA-HiDAC-Mito, a pre-treatment LSC gene expression signature enriched with 5hmC was associated with treatment resistance. More DhMGs at day 5 appear to be a dose-dependent epigenetic effect that is induced by AZA and is associated with longer survival despite the absence of an immediate change in gene expression levels. An 11-gene 5hmC pre-treatment signature may be a predictive biomarker for AZA-HiDAC-Mito therapy and other HMA-based approaches. These findings warrant validation in a larger prospective trial. [Display omitted] DisclosuresZhang: Bristol-Myers Squibb: Current Employment. Stock: Pfizer: Consultancy, Honoraria, Research Funding; amgen: Honoraria; agios: Honoraria; jazz: Honoraria; kura: Honoraria; kite: Honoraria; morphosys: Honoraria; servier: Honoraria; syndax: Consultancy, Honoraria; Pluristeem: Consultancy, Honoraria. Odenike: Celgene, Incyte, AstraZeneca, Astex, NS Pharma, AbbVie, Gilead, Janssen, Oncotherapy, Agios, CTI/Baxalta, Aprea: Research Funding; AbbVie, Celgene, Impact Biomedicines, Novartis, Taiho Oncology, Takeda: Consultancy. He: Epican Genetech: Current holder of individual stocks in a privately-held company, Current holder of stock options in a privately-held company.

FLT3 Inhibition Downregulates EZH2 in AML and Promotes Myeloid Differentiation

Internal tandem duplication mutations in the Fms-like tyrosine kinase 3 (FLT3-ITD) are frequently recurring in AML and confer a poor prognosis. FLT3 inhibitors (FLT3i) such as gilteritinib are efficacious in relapsed AML. Clinical responses to FLT3i include myeloid differentiation of the FLT3-ITD clone in about 50% of patients. How FLT3i induce this response in a subset of patients is unknown.The FLT3i-induced differentiation response seen in clinical trials has not previously been demonstrated in animal models. We modeled FLT3i-induced differentiation in murine Flt3 ITD/ITDDnmt3a -/- AML model (Meyer et al., Cancer Discovery, 2016). Treatment with FLT3i in vitro accelerated differentiation of cKIT+ leukemic splenocytes as assessed by colony morphology in serial re-plating assays. To characterize the differentiation response in vivo, we transplanted CD45.2+ leukemic splenocytes from moribund mice into sub-lethally irradiated healthy congenic CD45.1+ mice. After confirmation of engraftment at 2 weeks post-irradiation, mice were treated with vehicle or gilteritinib for 4 weeks. Animals treated with gilteritinib demonstrated increased neutrophil and decreased stem/progenitor cell populations, recapitulating the clinically observed increase in granulocytic differentiation of the FLT3-ITD clone.We next sought to understand the molecular mechanism of FLT3i-induced differentiation. We used a proteomic-based screen in a human AML cell line treated with FLT3i to identify novel targets of FLT3-ITD that could be potential mediators of the differentiation response. We identified downregulation of Enhancer of Zeste Homolog 2 (EZH2), the catalytic component of the Polycomb Repressive Complex 2 (PRC2). EZH2 and PRC2 were previously shown to be required for leukemic maintenance in mouse models of MLL-AF9 AML. We treated murine Flt3 ITD/ITDDnmt3a -/- cKIT+ leukemic splenocytes with FLT3i or the EZH1/2 inhibitor (EZH1/2i). Both promoted myeloid differentiation to similar degrees as assessed by colony morphology in this model. We hypothesized that FLT3-ITD regulates EZH2 to maintain leukemia cells in a stem/progenitor cell state. We, therefore, characterized the effect of FLT3i on PRC2 in more detail. We confirmed that FLT3i decreases EZH2 protein levels in FLT3-ITD cell lines and primary human AML within 24 hours of treatment as suggested by our proteomic data (Figure 1A-B). We found that the mechanism of EZH2 downregulation is complex with both transcriptional effects and a decrease in EZH2 protein half-life. ChIP-Seq for H3K27me3 demonstrated decreased peaks at the transcription start sites of PRC2 target genes (Figure 1C). RNA-Seq gene expression profiles of FLT3i- and EZH1/2i-treated human AML cells overlapped at 253 differentially expressed genes (Figure 1D). Critically, both FLT3i and EZH1/2i expression profiles enriched in differentiated myeloid cell gene signatures.Overall, we found that EZH2 is a novel, unexpected, and clinically relevant target of FLT3-ITD. Our data suggest that reduced EZH2 activity following FLT3 inhibition promotes myeloid differentiation of FLT3-ITD leukemic cells, providing a mechanistic explanation for the FLT3i-induced differentiation response seen in patients. These data demonstrate that FLT3-ITD has at least two functions in leukemogenesis, the well described activation of signaling pathways, and second, a previously undefined, regulation of PRC2 to maintain a myeloid stem cell state. Our results may lead to improved approaches to therapy for FLT3 mutated AML. [Display omitted] DisclosuresBernt: Syndax: Research Funding; Merck: Other: Spouse is an employee of Merck.. Carroll: Incyte Pharmaceuticals: Research Funding; Janssen Pharmaceutical: Consultancy.

Abstract 2226: Prioritizing tumor types for clinical study of novel Sec61 inhibitors by searching for expression profiles of sensitive cell lines in tumor sample databases

Abstract Blockade of secreted and transmembrane protein translocation into the endoplasmic reticulum represents a potentially multifactorial approach to inhibiting tumor growth. We have shown that small molecule inhibitors of the Sec61 translocon can inhibit expression of autocrine growth factors, receptor oncogenes, and immune checkpoints. We nominated KZR-261 for clinical development and describe here bioinformatic analysis of in vitro cancer cell line screens and primary tumor samples that prioritizes potentially sensitive tumor types for clinical evaluation. Anti-tumor activity of KZR-834, a structurally related analog of KZR-261, was assessed in two cell line cytotoxicity screens totaling over 400 cell lines. Broad anti-cancer activity across tumor types was observed in both screens, with median IC50 of 0.39 µM and 0.15 µM. We next demonstrated that KZR-261 has equivalent activity to KZR-834 by testing it on a subset of 48 cell lines (R2=0.91). For cell lines with RNA-Seq gene expression profiles available in CCLE (N=232), we correlated sensitivity to KZR-834 with each gene's expression. This analysis revealed a modest correlation between expression and cell line sensitivity for many genes. However, even the gene with the strongest correlation between expression and sensitivity provided only a partial explanation for KZR-834 sensitivity (CCND2, Spearman ρ = 0.31, P-val = 10−4). Levels of Sec61 were not associated with cell line sensitivity (SEC61A1, ρ = -0.05, P-val = 0.57). We therefore surveyed the gene-level results for enrichment of over 7,000 modules by performing fGSEA analysis. Enriched modules were hierarchically clustered revealing 6 primary clusters associated with sensitivity. The 6 clusters highlighted processes such as transcription, translation, metabolism, golgi vesicle transport, as well as genes encoding proteins that are secreted or plasma membrane localized. While fGSEA did not identify basal levels of ER stress as a process correlated with sensitivity, cell lines treated with KZR-834 have consistently shown activation of ER stress pathways at the mRNA and protein level, which led to its inclusion in subsequent analyses. Modules representing these 7 processes were then utilized to search tumor and normal tissue gene expression data from TCGA, TARGET and GTEx. Tumor types such as ALL, DLBCL, uveal and cutaneous melanoma, and mesothelioma were more enriched for expression of these modules than other tumor types and the vast majority of normal tissues. Our novel small molecule inhibitors of Sec61 dependent protein translocation exhibit broad anti-tumor activity in vitro. Large cell line screens and bioinformatic analyses identifying tumor intrinsic sensitivities led to a prioritized list of potentially sensitive tumor types that has guided tumor type selection for our initial Phase 1 clinical trial of KZR-261 in solid tumors. Citation Format: Eric Lowe, R. Andrea Fan, Henry W.B. Johnson, Christopher J. Kirk, Dustin McMinn, Yu Qian, Brian Tuch. Prioritizing tumor types for clinical study of novel Sec61 inhibitors by searching for expression profiles of sensitive cell lines in tumor sample databases [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2226.