RNA-seq Gene Expression Research Articles

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.

Abstract P5-05-01: Metabolite profiling and RNA-seq identifies novel metabolomic-genomic biomarker and therapeutic options for rapidly proliferating breast cancers

Abstract Metabolic dysregulation is one of the distinctive features of breast cancer, yet remains under-characterized in different subtypes of breast cancer. In this study, we performed full metabolome profiling and RNA-seq gene expression analyses on patient samples comprised of Triple Negative Breast Cancer (TNBC) and Estrogen Receptor (ER) positive breast cancers, as well as TNBC patient-derived xenografts (PDX). We identified two major metabolic groups using hierarchical clustering analysis of global metabolite levels: a Nucleotide/Carbohydrate-Enriched group and a Lipid/Fatty Acid-Enriched group. The Nucleotide/Carbohydrate-Enriched group is populated by the majority of TNBCs and all TNBC PDX samples, and shows high levels of energy consumption and nucleotide biosynthesis related metabolites, while the Lipid/Fatty Acid-Enriched group contained all ER+ cancers (and normal breast tissues) and showed high levels of lipids and fatty acids. Using these two metabolite-defined groups, we compared metabolic signatures to RNA-seq expression data and identified gene expression signatures that correlated with each metabolic group. This novel integrated signature identified classic proliferation-associated genes as highly expressed in the Nucleotide/Carbohydrate-Enriched metabolomics group. We next sought to therapeutically target the Nucleotide/Carbohydrate-Enriched group through targeting of nucleotide metabolism using a pyrimidine biosynthesis inhibitor (DHODH inhibitor, Brequinar), and/or a glutaminase inhibitor (CB-839), and observed tumor volume reductions and improved survival times using the TNBC PDX models. Notably,. when the DHODH inhibitor Brequinar was tested on four different immune-competent TNBC mouse models, it showed significant single agent activity, and in 3/4 cases had better activity than carboplatin/paclitaxel combination, and with less toxicity. Our study reveals a new molecularly targeted therapy for rapidly proliferating TNBCs, guided by a novel set of metabolic-genomic biomarkers, which might be translated quickly as DHODH inhibitors are already FDA approved for use in other diseases. Citation Format: Cherise R Glodowski, Chengheng Liao, Cheng Fan, Juan Liu, Kevin R Mott, Akash Kaushik, Hieu Vu, Jason W Locasale, Samuel K McBrayer, Ralph J DeBerardinis, Charles M Perou, Qing Zhang. Metabolite profiling and RNA-seq identifies novel metabolomic-genomic biomarker and therapeutic options for rapidly proliferating breast cancers [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 P5-05-01.

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.

Nampt activator P7C3 ameliorates diabetes and improves skeletal muscle function modulating cell metabolism and lipid mediators.

BackgroundNicotinamide phosphoribosyltransferase (Nampt), a key enzyme in NAD salvage pathway is decreased in metabolic diseases, and its precise role in skeletal muscle function is not known. We tested the hypothesis, Nampt activation by P7C3 (3,6‐dibromo‐α‐[(phenylamino)methyl]‐9H‐carbazol‐9‐ethanol) ameliorates diabetes and muscle function.MethodsWe assessed the functional, morphometric, biochemical, and molecular effects of P7C3 treatment in skeletal muscle of type 2 diabetic (db/db) mice. Nampt+/− mice were utilized to test the specificity of P7C3.ResultsInsulin resistance increased 1.6‐fold in diabetic mice compared with wild‐type mice and after 4 weeks treatment with P7C3 rescued diabetes (P < 0.05). In the db‐P7C3 mice fasting blood glucose levels decreased to 0.96‐fold compared with C57Bl/6J wild‐type naïve control mice. The insulin and glucose tolerance tests blood glucose levels were decreased to 0.6‐fold and 0.54‐folds, respectively, at 120 min along with an increase in insulin secretion (1.76‐fold) and pancreatic β‐cells (3.92‐fold) in db‐P7C3 mice. The fore‐limb and hind‐limb grip strengths were increased to 1.13‐fold and 1.17‐fold, respectively, together with a 14.2‐fold increase in voluntary running wheel distance in db‐P7C3 mice. P7C3 treatment resulted in a 1.4‐fold and 7.1‐fold increase in medium‐sized and larger‐sized myofibres cross‐sectional area, with a concomitant 0.5‐fold decrease in smaller‐sized myofibres of tibialis anterior (TA) muscle. The transmission electron microscopy images also displayed a 1.67‐fold increase in myofibre diameter of extensor digitorum longus muscle along with 2.9‐fold decrease in mitochondrial area in db‐P7C3 mice compared with db‐Veh mice. The number of SDH positive myofibres were increased to 1.74‐fold in db‐P7C3 TA muscles. The gastrocnemius and TA muscles displayed a decrease in slow oxidative myosin heavy chain type1 (MyHC1) myofibres expression (0.46‐fold) and immunostaining (6.4‐fold), respectively. qPCR analysis displayed a 2.9‐fold and 1.3‐fold increase in Pdk4 and Cpt1, and 0.55‐fold and 0.59‐fold decrease in Fgf21 and 16S in db‐P7C3 mice. There was also a 3.3‐fold and 1.9‐fold increase in Fabp1 and CD36 in db‐Veh mice. RNA‐seq differential gene expression volcano plot displayed 1415 genes to be up‐regulated and 1726 genes down‐regulated (P < 0.05) in db‐P7C3 mice. There was 1.02‐fold increase in serum HDL, and 0.9‐fold decrease in low‐density lipoprotein/very low‐density lipoprotein ratio in db‐P7C3 mice. Lipid profiling of gastrocnemius muscle displayed a decrease in inflammatory lipid mediators n‐6; AA (0.83‐fold), and n‐3; DHA (0.69‐fold) and EPA (0.81‐fold), and a 0.66‐fold decrease in endocannabinoid 2‐AG and 2.0‐fold increase in AEA in db‐P7C3 mice.ConclusionsOverall, we demonstrate that P7C3 activates Nampt, improves type 2 diabetes and skeletal muscle function in db/db mice.

Iterative bicluster-based Bayesian principal component analysis and least squares for missing-value imputation in microarray and RNA-sequencing data.

Microarray and RNA-sequencing (RNA-seq) techniques each produce gene expression data that can be expressed as a matrix that often contains missing values. Thus, a process of missing-value imputation that uses coherence information of the dataset is necessary. Existing imputation methods, such as iterative bicluster-based least squares (bi-iLS), use biclustering to estimate the missing values because genes are only similar under correlative experimental conditions. Also, they use the row average to obtain a temporary complete matrix, but the use of the row average is considered to be a flaw. The row average cannot reflect the real structure of the dataset because the row average only uses the information of an individual row. Therefore, we propose the use of Bayesian principal component analysis (BPCA) to obtain the temporary complete matrix instead of using the row average in bi-iLS. This alteration produces new missing values imputation method called iterative bicluster-based Bayesian principal component analysis and least squares (bi-BPCA-iLS). Several experiments have been conducted on two-dimension independent gene expression datasets, which are microarray (e.g., cell-cycle expression dataset of yeast saccharomyces cerevisiae) and RNA-seq (gene expression data from schizosaccharomyces pombe) datasets. In the case of the microarray dataset, our proposed bi-BPCA-iLS method showed a significant overall improvement in the normalized root mean square error (NRMSE) values of 10.6% from the local least squares (LLS) and 0.6% from the bi-iLS. In the case of the RNA-seq dataset, our proposed bi-BPCA-iLS method showed an overall improvement in the NRMSE values of 8.2% from the LLS and 3.1% from the bi-iLS. The additional computational time of bi-BPCA-iLS is not significant compared to bi-iLS.

Bioinformatics Approach to Identify Significant Biomarkers, Drug Targets Shared Between Parkinson's Disease and Bipolar Disorder: A Pilot Study.

Parkinson’s disease (PD) is a neurodegenerative disorder responsible for shaking, rigidity, and trouble in walking and patients’ coordination ability and physical stability deteriorate day by day. Bipolar disorder (BD) is a psychiatric disorder which is the reason behind extreme shiftiness in mood, and frequent mood inversion may reach too high called mania. People with BD have a greater chance of developing PD during the follow-up period. A lot of work has been done to understand the key factors for developing these 2 diseases. But the molecular functionalities that trigger the development of PD in people with BD are not clear yet. In our study, we are intended to identify the molecular biomarkers and pathways shared between BD and PD. We have investigated the RNA-Seq gene expression data sets of PD and BD. A total of 45 common unique genes (32 up-regulated and 13 down-regulated) abnormally expressed in both PD and BD were identified by applying statistical methods on the GEO data sets. Gene ontology (GO) and BioCarta, KEGG, and Reactome pathways analysis of these 45 common dysregulated genes identified numerous altered molecular pathways such as mineral absorption, Epstein-Barr virus infection, HTLV-I infection, antigen processing, and presentation. Analysis of protein-protein interactions revealed 9 significant hub-proteins, namely RPL21, RPL34, CKS2, B2M, TNFRSF10A, DTX2, HLA-B, ATP2A3, and TAPBP. Significant transcription factors (IRF8, SPI1, RUNX1, and FOXA1) and posttranscriptional regulator microRNAs (hsa-miR-491-3p and hsa-miR-1246) are also found by analyzing gene-transcription factors and gene-miRNAs interactions, respectively. Protein-drug interaction analysis revealed hub-protein B2M’s interaction with molecular drug candidates like N-formylmethionine, 3-indolebutyric acid, and doxycycline. Finally, a link between pathological processes of PD and BD is identified at transcriptional level. This study may help us to predict the development of PD among the people suffering from BD and gives some clue to understand significant pathological mechanisms.

Multi-Omics Analysis of Cancer Cell Lines with High/Low Ferroptosis Scores and Development of a Ferroptosis-Related Model for Multiple Cancer Types.

Background: Ferroptosis is a newly identified regulated cell death characterized by iron-dependent lipid peroxidation and subsequent membrane oxidative damage, which has been implicated in multiple types of cancers. The multi-omics differences between cancer cell lines with high/low ferroptosis scores remain to be elucidated. Methods and Materials: We used RNA-seq gene expression, gene mutation, miRNA expression, metabolites, copy number variation, and drug sensitivity data of cancer cell lines from DEPMAP to detect multi-omics differences associated with ferroptosis. Based on the gene expression data of cancer cell lines, we performed LASSO-Logistic regression analysis to build a ferroptosis-related model. Lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), esophageal cancer (ESCA), bladder cancer (BLCA), cervical cancer (CESC), and head and neck cancer (HNSC) patients from the TCGA database were used as validation cohorts to test the efficacy of this model. Results: After stratifying the cancer cell lines into high score (HS) and low score (LS) groups according to the median of ferroptosis scores generated by gene set variation analysis, we found that IC50 of 66 agents such as oxaliplatin (p < 0.001) were significantly different, among which 65 were higher in the HS group. 851 genes such as KEAP1 and NRAS were differentially muted between the two groups. Differentially expressed genes, miRNAs and metabolites were also detected—multiple items such as IL17F (logFC = 6.58, p < 0.001) differed between the two groups. Unlike the TCGA data generated by bulk RNA-seq, the gene expression data in DEPMAP are from pure cancer cells, so it could better reflect the traits of tumors in cancer patients. Thus, we built a 15-signature model (AUC = 0.878) based on the gene expression data of cancer cell lines. The validation cohorts demonstrated a higher mutational rate of NFE2L2 and higher expression levels of 12 ferroptosis-related genes in HS groups. Conclusion: This article systemically analyzed multi-omics differences between cancer cell lines with high/low ferroptosis scores and a ferroptosis-related model was developed for multiple cancer types. Our findings could improve our understanding of the role of ferroptosis in cancer and provide new insight into treatment for malignant tumors.

UCHL1 promotes proliferation and metastasis in head and neck squamous cell carcinoma and could be a potential therapeutic target

The purpose of this study was to research the physiological roles of ubiquitin carboxyl-terminal esterase L1 (UCHL1) in head and neck squamous cell carcinoma (HNSCC). Ten HNSCC samples and matched normal oral mucosal tissues were collected. UCHL1 expression of these tissues was detected by the immunohistochemical staining and real-time quantitative polymerase chain reaction. The human HNSCC cell line HN6 UCHL1 knockout (UCHL1 KO) cell line was constructed using CRISPR/CAS9 gene editing and verified by western blotting. Wound healing assay, cell proliferation assay, cell invasion assay, and flow cytometric analysis of the cell cycle and apoptosis were applied to research the role of UCHL1 in HNSCC. Also, an RNAseq gene expression data set and HNSCC patient survival data from The Cancer Genome Atlas were analyzed. UCHL1 was highly expressed in HNSCC tissues compared with normal oral mucosal tissues (P=.032). A decreased proliferation (P < .0001), migration (P < .0001), and invasion (P = .0049) ability of HN6 cells was exhibited after knockout of UCHL1. However, HN6 UCHL1 KO cells showed no significant differences in the cell cycle or apoptosis. The progression, nodal metastasis status, and stage of HNSCC had a positive correlation with the expression of UCHL1. UCHL1 plays an important role in HNSCC, and we consider that targeting UCHL1 may be a feasible therapeutic strategy for HNSCC.

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.

Bone Marrow Lymphoid Infiltrates and Aplasia after CD19-Directed CAR T Cell Therapy in Pediatric B-Lymphoblastic Leukemia

IntroductionChimeric Antigen Receptor (CAR) T cell therapy is used to treated relapsed/refractory B-Acute Lymphoblastic Leukemia (B-ALL) patients. Long term side effects include B cell aplasia and cytopenia that are treated with supportive therapy. Prolonged cytopenia is seen in 16% of CAR T-cell treated B-ALL patients. The etiology of cytopenia is not clear, and could be attributed to the impact of chemotherapy, CAR T cells and disease or patient-specific factors. The impact of CAR T cell infusion on bone marrow cellularity, lymphocyte compartment and its correlation with cytopenia has not been investigated.MethodsWe analyzed pre- and post-CAR bone marrow biopsies in 178 B-ALL patients who received a CD19-directed CAR T-cell product between 2012-2017 and followed for at least 12 months. Responses were categorized into sustained responders, non-responders, CD19-positive relapses and CD19-negative relapses as previously described. Bone Marrow biopsy (BMB) overall cellularity, complete blood counts (CBC) in a 12-month post infusion period were analyzed. BMB were considered mildly, moderately and severely hypocellular based on cellularity of 50, 25 and 5% respectively. Hypocellularity was further stratified by CBC per aplastic anemia (AA) classification guidelines: Non-Severe Aplastic Anemia (NSAA) and Very Severe Aplastic Anemia (VSAA). Immunohistochemistry (IHC) for CD3, CD4, CD8, CD163, granzyme and perforin were performed on pre- and post-CAR BMB. CD3 IHC was digitally scanned and analyzed quantitatively (Leica Aperio ImageScope) and qualitatively. Targeted RNA sequencing-based gene expression profiling (EdgeSeq Immuno-Oncology Panel, HTG Diagnostics) was performed on pre-and post-treatment biopsies, with differential expression assessed by DESeq2 within HTG Reveal software. RNAseq gene expression was deconvoluted to impute relative expression of immune cell subsets.Results31% of patients were mildly hypocellular but none were severely hypocellular at baseline pre-CAR timepoints. The highest proportion of hypocellularity was at the 1-month time point. 81% of patients were mildly hypocellular (≤50%), 42% were markedly hypocellular (≤25%), and 13% were severely hypocellular (≤5%) at the 1-month time point. By month 12, the proportion of mildly hypocellular patients was 74%, markedly hypocellular patients was 26%, and severely hypocellular patients was 7% (Figure 1). The proportion of NSAA and VSAA was 57% and 10% in moderately hypocellular BMB. The proportion of NSAA and VSAA was 64% and 18% in severely hypocellular BMB. Severely hypocellular patients had a higher average day minus 1 disease burden (33% involvement) compared to their moderate (24%) and non-hypocellular patients (16%). VSAA patients had a lower baseline BMB cellularity (47%) compared to NSAA patients (71%) and those without AA (60%)Increased CD3+ T cells were noted in the post-CAR BMB compared to the pre-CAR BMB (Figure 1B). Lymphocyte were singly scattered or formed loose aggregates and tight lymphohistiocytic clusters. IHC and RNAseq analysis showed increased CD8+ granzyme+ cells in the post-CAR BMB compared to pre-CAR BMB. Sustained responders showed higher T cell infiltration compared to other categories of patients (Figure 1C and D). Lymphoid infiltrates did not correlate with hypocellularity or cytopenia.ConclusionWe describe for the first time the changes in bone marrow cellularity and lymphocyte compartment after CD19-directed CAR T-cell infusion in B-ALL. A subset of patients were moderately or severely hypocellular and met criteria for aplastic anemia. However, most of them recovered bone marrow cellularity and CBC. Hypocellularity and AA were correlated with pre-CAR disease burden and baseline cellularity rather than post-CAR lymphocyte infiltration. We also show for the first time that sustained responders to CD19-CAR showed increased CD3+ CD8+ T cell infiltrates compared to CD19-positive relapses and non-responders.Figure 1. A. Bone marrow hypocellularity post-CAR T-cell infusion. Proportion of patients who were mildly hypocellular, markedly hypocellular, and severely hypocellular in the 12month follow up period. B. Increased CD3+ T cells and aggregates after CAR T cell infusion. C and D. Sustained responders show significantly greater CD3+ T cells after CAR T cell infusion compared to other categories. *P<0.05. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

ETS Family Transcription Factor Fusions in Childhood AML: Distinct Expression Networks and Clinical Implications

The ETS family of genes encode transcription factors (TFs) containing the ETS DNA binding domain, which have roles in cellular growth and development, including embryonic hematopoiesis. Dysregulation of these genes is associated with malignant transformation and tumorigenesis. In childhood acute myeloid leukemia (AML), the MNX1-ETV6 t(7;12)(q36;p13) and FUS-ERG t(16;21)(p11;q22) fusions are associated with adverse outcome. However, the biological and clinical implications of other ETS oncofusions in pediatric AML remain unknown.We identified 62 ETS gene fusions in 1,473 primary diagnostic AML samples (4.2%) using whole transcriptome RNA-sequencing and karyotype data. Four ETS family genes were identified to be involved in fusions with various partner genes: ETV6, ERG, FEV, and FLI1. Fusions with ETV6 were the most abundant (58%, 36/62) while FEV and FLI1 were the least; 21 fusion partners were identified where many function as TFs and co-activators (Figure 1A). MNX1-ETV6 (N=16) is enriched in infants (87.5% < 3 years, p < 0.001, Figure 1B), consistent with previous reports. ETV6 fusions with various partners (ETV6-Other, N=20) were likewise enriched in infants (50% < 3 years) and were significantly younger than patients without ETS fusions (median age: 3.0 vs 9.6 years, p = 0.025). FUS-ERG (N=10), HNRNPH1-ERG (N=8), and ETS fusions with various partners (ETS-Other, N=8) were primarily identified in patients 5-18 years old.Outcomes for patients with ETS fusions was determined after censoring for stem cell transplantation. Patients with ETS fusions as a collective group had adverse outcome with an EFS of 17.7% vs 39.9% (p = 0.047, Figure 1C), similar to high-risk cases in the reference group (22%), suggesting that patients with any ETS fusion may be considered high risk. Evaluation of outcomes by individual fusion groups at 3 years from diagnosis demonstrated an EFS of 0% for HNRNPH1-ERG, 18.0% for FUS-ERG, 14.2% for ETV6-Other, 20.8% for ETS-Other, and 28.4% for those with MNX1-ETV6. Twenty-one patients (37.5%) with ETS family fusions received stem cell transplant (SCT) in first complete remission, including HNRNPH1-ERG (N=5), FUS-ERG (N=3), ETV6-Other (N=5), ETS-Other (N=2), and MNX1-ETV6 (N=6). For these SCT recipients, OS at 3 years after transplant was 60.2%.We investigated whether ETS family fusions might have similar transcriptome profiles. Unsupervised uniform manifold approximation and projection (UMAP) on RNA-seq gene expression data followed by Leiden clustering found that individual fusions clustered in the same 3D space. More importantly, ETS fusion groups clustered closely to one another, indicating a shared transcriptional profile (Figure 1D, circle). Next, ETS fusion groups were each independently compared to the reference cohort (N=1421) using differential expression (DE) analysis. Intersection of DE genes revealed 17 overexpressed genes common to ETS fusions and 9/17 (52%) were also dysregulated when contrasting ETS cohorts to healthy normal marrows' transcriptome (N=68, Figure 1E). The minimal set of dysregulated genes included an adhesion molecule EDIL3, a prostaglandin (PG) enzyme HPGD, and a tyrosine phosphatase PTP4A3, which is strongly associated with progression in lymphoblastic leukemia and multiple myeloma. EDIL3 was reported to be overexpressed in MNX1-ETV6 and we found this molecule is a common feature of ETS fusions and their cellular dysregulation. The minimal set of 9 genes were further investigated using protein interaction networks defined from Pathway Commons v11. FUS-ERG and HNRNPH1-ERG both had significantly (adj. p < 0.001) activated HPGD networks; PG-E synthase and > 10 PG metabolism genes were upregulated. PG metabolism has important roles in regulating hematopoietic stem and progenitor (HSPC) functions and PG-E2 was shown to increase HSPC survival. ETV6-MXN1, ETV6-Other, and FUS-ERG had activated PTP4A3 networks and its expression was associated with sensitivity to BET inhibitors (BETi) in myeloma. They also exhibited increased activity of an ERG network with the overexpression of upstream regulators CBFA2T3 and GATA, and downstream targets like VWF and ZBTB16.Overall, we show that ETS fusions are uniformly high risk and share dysregulated cell adhesion (EDIL3) and transcriptional networks for ERG, HPGD, and PTP4A3, which provide opportunities for further research into the metabolome and therapeutics (BETi) in these fusions. [Display omitted] DisclosuresShaw: T-Cell and/or Gene Therapy for Cancer: Patents & Royalties.

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.

Supervised learning based on tumor imaging and biopsy transcriptomics predicts response of hepatocellular carcinoma to transarterial chemoembolization

SummaryAlthough transarterial chemoembolization (TACE) is the most widely used treatment for intermediate-stage, unresectable hepatocellular carcinoma (HCC), it is only effective in a subset of patients. In this study, we combine clinical, radiological, and genomics data in supervised machine-learning models toward the development of a clinically applicable predictive classifier of response to TACE in HCC patients. Our study consists of a discovery cohort of 33 tumors through which we identify predictive biomarkers, which are confirmed in a validation cohort. We find that radiological assessment of tumor area and several transcriptomic signatures, primarily the expression of FAM111B and HPRT1, are most predictive of response to TACE. Logistic regression decision support models consisting of tumor area and RNA-seq gene expression estimates for FAM111B and HPRT1 yield a predictive accuracy of ∼90%. Reverse transcription droplet digital PCR (RT-ddPCR) confirms these genes in combination with tumor area as a predictive classifier for response to TACE.

Androgen Receptor Pathway Gene Expression After High Dose Rate Prostate Brachytherapy

<h3>Purpose/Objective(s)</h3> Androgen deprivation therapy (ADT) is commonly used after radiation therapy in the treatment of prostate cancer. Though radiation has generally been shown to upregulate androgen receptor (AR) expression, the effect of high dose rate (HDR) brachytherapy on AR expression is unknown. We hypothesize that expression of AR and corresponding target genes will be altered by HDR brachytherapy. <h3>Materials/Methods</h3> 10 Patients with intermediate risk prostate cancer (age 51-78; 7 GS 3+4, 3 GS 4+3) underwent HDR brachytherapy (2 implants, 13.5 Gy per implant, 1 week apart). Patients consented to biopsies before each fraction at the first and second implant. Tumor content percentage was evaluated on stained H&E slides. Bulk RNA-seq gene expression was performed on the formalin-fixed, paraffin-embedded pre- vs. post-RT tumor samples, and differential gene expression was performed to assess changes in AR, KLK2, KLK3, TMPRSS2. <h3>Results</h3> AR pathway genes showed significant downregulation (log2 fold change, adjusted <i>P</i>-value): AR (-0.83, 2.38E-4), KLK2 (-1.65, 2.09E-5), KLK3 (-1.76, 9.7E-4), TMPRSS2 (-1.98, 4.13E-7). Therefore, AR pathway gene expression was 25-56% of baseline expression 1 week after radiation treatment with 13.5 Gy. Meanwhile, post-radiation tumor content (mean fold change +/- standard deviation) was observed to remain 73% +/- 25% of baseline content. <h3>Conclusion</h3> Differential gene expression analysis of prostate tumor suggests AR and its target genes may be downregulated relative to tumor content after HDR brachytherapy.

A Collection of Multimodal Melanoma Data

Computer-aided diagnosis, prognosis and therapy systems have been of great interest for a number of years. The availability of big volumes of data and of powerful computational resources have allowed artificial intelligence approaches to emerge in melanoma related studies. However, for such approaches to have good predictive performances data availability is of crucial importance. Melanoma related imaging, biological and clinical data can be found partially and scattered in various repositories. Thus, in this work, we assemble in a web accessible database, named ebioMelDB, the widest collection of clinical and dermoscopy images accompanied with patient clinical data and the widest collection of RNA-Seq gene expression data accompanied with patient clinical data. The database organization allows users to select the data that are appropriate for their application of interest (diagnosis, prognosis and therapy). Keywords: melanoma database, integrated data, dermoscopy, imaging, RNA-Seq, clinical data.

Metabolic Reprogramming of Nasal Airway Epithelial Cells Following Infant Respiratory Syncytial Virus Infection.

Respiratory syncytial virus (RSV) is a seasonal mucosal pathogen that infects the ciliated respiratory epithelium and results in the most severe morbidity in the first six months of life. RSV is a common cause of acute respiratory infection during infancy and is an important early-life risk factor strongly associated with asthma development. While this association has been repeatedly demonstrated, limited progress has been made on the mechanistic understanding in humans of the contribution of infant RSV infection to airway epithelial dysfunction. An active infection of epithelial cells with RSV in vitro results in heightened central metabolism and overall hypermetabolic state; however, little is known about whether natural infection with RSV in vivo results in lasting metabolic reprogramming of the airway epithelium in infancy. To address this gap, we performed functional metabolomics, 13C glucose metabolic flux analysis, and RNA-seq gene expression analysis of nasal airway epithelial cells (NAECs) sampled from infants between 2–3 years of age, with RSV infection or not during the first year of life. We found that RSV infection in infancy was associated with lasting epithelial metabolic reprogramming, which was characterized by (1) significant increase in glucose uptake and differential utilization of glucose by epithelium; (2) altered preferences for metabolism of several carbon and energy sources; and (3) significant sexual dimorphism in metabolic parameters, with RSV-induced metabolic changes most pronounced in male epithelium. In summary, our study supports the proposed phenomenon of metabolic reprogramming of epithelial cells associated with RSV infection in infancy and opens exciting new venues for pursuing mechanisms of RSV-induced epithelial barrier dysfunction in early life.

Legacy Metal Contaminants and Excess Nutrients in Low Flow Estuarine Embayments Alter Composition and Function of Benthic Bacterial Communities.

Coastal systems such as estuaries are threatened by multiple anthropogenic stressors worldwide. However, how these stressors and estuarine hydrology shape benthic bacterial communities and their functions remains poorly known. Here, we surveyed sediment bacterial communities in poorly flushed embayments and well flushed channels in Sydney Harbour, Australia, using 16S rRNA gene sequencing. Sediment samples were collected monthly during the Austral summer-autumn 2014 at increasing distance from a large storm drain in each channel and embayment. Bacterial communities differed significantly between sites that varied in proximity to storm drains, with a gradient of change apparent for sites within embayments. We explored this pattern for embayment sites with analysis of RNA-Seq gene expression patterns and found higher expression of multiple genes involved in bacterial stress response far from storm drains, suggesting that bacterial communities close to storm drains may be more tolerant of localised anthropogenic stressors. Several bacterial groups also differed close to and far from storm drains, suggesting their potential utility as bioindicators to monitor contaminants in estuarine sediments. Overall, our study provides useful insights into changes in the composition and functioning of benthic bacterial communities as a result of multiple anthropogenic stressors in differing hydrological conditions.

Locus-specific analysis of Transposable Elements during the progression of ALS in the SOD1G93A mouse model.

Transposable Elements (TEs) are ubiquitous genetic elements with the ability to move within a genome. TEs contribute to a large fraction of the repetitive elements of a genome, and because of their nature, they are not routinely analyzed in RNA-Seq gene expression studies. Amyotrophic Lateral Sclerosis (ALS) is a lethal neurodegenerative disease, and a well-accepted model for its study is the mouse harboring the human SOD1G93A mutant. In this model, landmark stages of the disease can be recapitulated at specific time points, making possible to understand changes in gene expression across time. While there are several works reporting TE activity in ALS models, they have not explored their activity through the disease progression. Moreover, they have done it at the expense of losing their locus of expression. Depending on their genomic location, TEs can regulate genes in cis and in trans, making locus-specific analysis of TEs of importance in order to understand their role in modulating gene expression. Particularly, the locus-specific role of TEs in ALS has not been fully elucidated. In this work, we analyzed publicly available RNA-Seq datasets of the SOD1G93A mouse model, to understand the locus-specific role of TEs. We show that TEs become up-regulated at the early stages of the disease, and via statistical associations, we speculate that they can regulate several genes, which in turn might be contributing to the genetic dysfunction observed in ALS.

A laminar augmented cascading flexible neural forest model for classification of cancer subtypes based on gene expression data

BackgroundCorrectly classifying the subtypes of cancer is of great significance for the in-depth study of cancer pathogenesis and the realization of personalized treatment for cancer patients. In recent years, classification of cancer subtypes using deep neural networks and gene expression data has gradually become a research hotspot. However, most classifiers may face overfitting and low classification accuracy when dealing with small sample size and high-dimensional biology data.ResultsIn this paper, a laminar augmented cascading flexible neural forest (LACFNForest) model was proposed to complete the classification of cancer subtypes. This model is a cascading flexible neural forest using deep flexible neural forest (DFNForest) as the base classifier. A hierarchical broadening ensemble method was proposed, which ensures the robustness of classification results and avoids the waste of model structure and function as much as possible. We also introduced an output judgment mechanism to each layer of the forest to reduce the computational complexity of the model. The deep neural forest was extended to the densely connected deep neural forest to improve the prediction results. The experiments on RNA-seq gene expression data showed that LACFNForest has better performance in the classification of cancer subtypes compared to the conventional methods.ConclusionThe LACFNForest model effectively improves the accuracy of cancer subtype classification with good robustness. It provides a new approach for the ensemble learning of classifiers in terms of structural design.

Integrated genomic analysis of proteasome alterations across 11,057 patients with 33 cancer types: clinically relevant outcomes in framework of 3P medicine.

Proteasome, a cylindrical complex containing 19S regulatory particle lid, 19S regulatory particle base, and 20S core particle, acted as a major mechanism to regulate the levels of intracellular proteins and degrade misfolded proteins, which involved in many cellular processes, and played important roles in cancer biological processes. Elucidation of proteasome alterations across multiple cancer types will directly contribute to cancer medical services in the context of predictive, preventive, and personalized medicine (PPPM /3P medicine). This study aimed to investigate proteasome gene alterations across 33 cancer types for discovery of effective biomarkers and therapeutic targets in the framework of PPPM practice in cancers. Proteasome gene data, including gene expression RNAseq, somatic mutation, tumor mutation burden (TMB), copy number variant (CNV), microsatellite instability (MSI) score, clinical characteristics, immune phenotype, 22 immune cells, cancer stemness index, drug sensitivity, and related pathways, were systematically analyzed with publically available database and bioinformatics across 11,057 patients with 33 cancer types. Differentially expressed proteasome genes were extensively found between tumor and control tissues. PSMB4 occurred the top mutation event among proteasome genes, and those proteasome genes were significantly associated with TMB and MSI score. Most of proteasome genes were positively related to CNV among single deletion, control copy number, and single gain. Kaplan-Meier curves and COX regression survival analysis showed proteasome genes were significantly associated with patient survival rate across 33 cancer types. Furthermore, the expressions of proteasome genes were significantly different among different clinical stages and immune subtypes. The expressions of proteasome genes were correlated with immune-related scores (ImmuneScore, StromalScore, and ESTIMATEScore), 22 immune cells, and cancer stemness. The sensitivities of multiple drugs were closely related to proteasome gene expressions. The identified proteasome and proteasome-interacted proteins were significantly enriched in various cancer-related pathways. This study provided the first landscape of proteasome alterations across 11,057 patients with 33 cancer types and revealed that proteasome played a significant and wide functional role in cancer biological processes. These findings are the precious scientific data to reveal the common and specific alterations of proteasome genes among 33 cancer types, which benefits the research and practice of PPPM in cancers. The online version contains supplementary material available at 10.1007/s13167-021-00256-z.