Specific Gene Expression Signature Research Articles

RNA-Seq analysis of human heart tissue reveals SARS-CoV-2 infection and inappropriate activation of the TNF-NF-κB pathway in cardiomyocytes

The negative impact of SARS-CoV-2 virus infection on cardiovascular disease (CVD) patients is well established. This research article explores the cellular pathways involved in underlying heart diseases after infection. The systemic inflammatory response to SARS-CoV-2 infection likely exacerbates this increased cardiovascular risk; however, whether the virus directly infects cardiomyocytes remains unknown due to limited multi-omics data. While public transcriptome data exists for COVID-19 infection in different cell types (including cardiomyocytes), infection times vary between studies. We used available RNA-seq data from human heart tissue to delineate SARS-CoV-2 infection and heart failure aetiology specific gene expression signatures. A total of fifty-four samples from four studies were analysed. Our aim was to investigate specific transcriptome changes occurring in cardiac tissue with SARS-CoV-2 infection compared to non-infected controls. Our data establish that SARS-CoV-2 infects cardiomyocytes by the TNF-NF-κB pathway, potentially triggering acute cardiovascular complications and increasing the long-term cardiovascular risk in COVID-19 patients.

Oscillatory hypoxia induced gene expression predicts low survival in human breast cancer patients.

Hypoxia is one of the key factors in the tumor microenvironment regulating nearly all steps in the metastatic cascade in many cancers, including in breast cancer. The hypoxic regions can however be dynamic with the availability of oxygen fluctuating or oscillating. The canonical response to hypoxia is relayed by transcription factorHypoxia-Inducible Factor 1(HIF-1), which is stabilized in hypoxia and acts as the master regulator of a large number of downstream genes. However, HIF-1 transcriptional activity can also fluctuate either due to unstable hypoxia, or by lactate mediated noncanonical degradation of HIF-1. Our understanding of how oscillatory hypoxia or HIF-1 activity specifically influences cancer malignancy is very limited. Here, using MDA-MB-231 cells as a model of triple negative breast cancer characterized by severe hypoxia, we measured the gene expression changes induced specifically by oscillatory hypoxia. We found that oscillatory hypoxia can specifically regulate gene expression differently, and at times opposite to stable hypoxia. Using the Cancer Genome Atlas RNAseq data of human cancer samples, we show that the oscillatory specific gene expression signature in MDA-MB-231 is enriched in most human cancers, and prognosticates low survival in breast cancer patients. In particular, we found that oscillatory hypoxia, unlike stable hypoxia, induces unfolded protein folding responsein cells resulting in gene expression predicting reduced survival.

Oscillatory Hypoxia Induced Unfolded Protein Folding Response Gene Expression Predicts Low Survival in Human Breast Cancer Patients.

Hypoxia is one of the key factors in the tumor microenvironment regulating nearly all steps in the metastatic cascade in many cancers, including in breast cancer. The hypoxic regions can however be dynamic with the availability of oxygen fluctuating or oscillating. The canonical response to hypoxia is relayed by transcription factor HIF-1, which is stabilized in hypoxia and acts as the master regulator of a large number of downstream genes. However, HIF-1 transcriptional activity can also fluctuate either due to unstable hypoxia, or by lactate mediated non-canonical degradation of HIF-1. Our understanding of how oscillatory hypoxia or HIF-1 activity specifically influence cancer malignancy is very limited. Here, using MDA-MB-231 cells as a model of triple negative breast cancer characterized by severe hypoxia, we measured the gene expression changes induced specifically by oscillatory hypoxia. We found that oscillatory hypoxia can specifically regulate gene expression differently, and at times opposite to stable hypoxia. Using The Cancer Genome Atlas (TCGA) RNAseq data of human cancer samples, we show that the oscillatory specific gene expression signature in MDA-MB-231 is enriched in most human cancers, and prognosticate low survival in breast cancer patients. In particular, we found that oscillatory hypoxia, unlike stable hypoxia, induces unfolded protein folding response (UPR) in cells resulting in gene expression predicting reduced survival.

Assessing transcriptomic heterogeneity of single-cell RNASeq data by bulk-level gene expression data

BackgroundSingle-cell RNA sequencing (sc-RNASeq) data illuminate transcriptomic heterogeneity but also possess a high level of noise, abundant missing entries and sometimes inadequate or no cell type annotations at all. Bulk-level gene expression data lack direct information of cell population composition but are more robust and complete and often better annotated. We propose a modeling framework to integrate bulk-level and single-cell RNASeq data to address the deficiencies and leverage the mutual strengths of each type of data and enable a more comprehensive inference of their transcriptomic heterogeneity. Contrary to the standard approaches of factorizing the bulk-level data with one algorithm and (for some methods) treating single-cell RNASeq data as references to decompose bulk-level data, we employed multiple deconvolution algorithms to factorize the bulk-level data, constructed the probabilistic graphical models of cell-level gene expressions from the decomposition outcomes, and compared the log-likelihood scores of these models in single-cell data. We term this framework backward deconvolution as inference operates from coarse-grained bulk-level data to fine-grained single-cell data. As the abundant missing entries in sc-RNASeq data have a significant effect on log-likelihood scores, we also developed a criterion for inclusion or exclusion of zero entries in log-likelihood score computation.ResultsWe selected nine deconvolution algorithms and validated backward deconvolution in five datasets. In the in-silico mixtures of mouse sc-RNASeq data, the log-likelihood scores of the deconvolution algorithms were strongly anticorrelated with their errors of mixture coefficients and cell type specific gene expression signatures. In the true bulk-level mouse data, the sample mixture coefficients were unknown but the log-likelihood scores were strongly correlated with accuracy rates of inferred cell types. In the data of autism spectrum disorder (ASD) and normal controls, we found that ASD brains possessed higher fractions of astrocytes and lower fractions of NRGN-expressing neurons than normal controls. In datasets of breast cancer and low-grade gliomas (LGG), we compared the log-likelihood scores of three simple hypotheses about the gene expression patterns of the cell types underlying the tumor subtypes. The model that tumors of each subtype were dominated by one cell type persistently outperformed an alternative model that each cell type had elevated expression in one gene group and tumors were mixtures of those cell types. Superiority of the former model is also supported by comparing the real breast cancer sc-RNASeq clusters with those generated by simulated sc-RNASeq data.ConclusionsThe results indicate that backward deconvolution serves as a sensible model selection tool for deconvolution algorithms and facilitates discerning hypotheses about cell type compositions underlying heterogeneous specimens such as tumors.

Characterization of patient-derived intestinal organoids for modelling fibrosis in Inflammatory Bowel Disease

Background and aimsIntestinal fibrosis is a common complication of Inflammatory Bowel Disease (IBD), namely Crohn's disease (CD) and ulcerative colitis (UC), but the precise mechanism by which it occurs is incompletely understood hampering the development of effective therapeutic strategies. Here, we aimed at inducing and characterizing an inflammation-mediated fibrosis in patient-derived organoids (PDOs) issued from crypts isolated from colonic mucosal biopsies of IBD pediatric patients and age matched-control subjects (CTRLs).MethodsInflammatory-driven fibrosis was induced by exposing CTRL-, CD- and UC-PDOs to the pro-inflammatory cytokine TNF-α for one day, followed by a co-treatment with TNF-α and TGF-β1 for three days. Fibrotic response was proven by analyzing inflammatory and fibrotic markers by RT-qPCR and immunofluorescence. Transcriptomic changes were assessed by RNA-sequencing.ResultsCo-treatment with TNF-α and TGF-β1 caused in CTRL- and IBD-PDOs morphological changes towards a mesenchymal-like phenotype and up-regulation of inflammatory, mesenchymal, and fibrotic markers. Transcriptomic profiling highlighted that in all intestinal PDOs, regardless of the disease, the co-exposure to TNF-α and TGF-β1 regulated EMT genes and specifically increased genes involved in positive regulation of cell migration. Finally, we demonstrated that CD-PDOs display a specific response to fibrosis compared to both CTRL- and UC-PDOs, mainly characterized by upregulation of nuclear factors controlling transcription.ConclusionsThis study demonstrates that intestinal PDOs may develop an inflammatory-derived fibrosis thus representing a promising tool to study fibrogenesis in IBD. Fibrotic PDOs show increased expression of EMT genes. In particular, fibrotic CD-PDOs display a specific gene expression signature compared to UC and CTRL-PDOs.

Single-cell analysis defines highly specific leukemia-induced neutrophils and links MMP8 expression to recruitment of tumor associated neutrophils during FGFR1 driven leukemogenesis

BackgroundLeukemias driven by activated, chimeric FGFR1 kinases typically progress to AML which have poor prognosis. Mouse models of this syndrome allow detailed analysis of cellular and molecular changes occurring during leukemogenesis. We have used these models to determine the effects of leukemia development on the immune cell composition in the leukemia microenvironment during leukemia development and progression.MethodsSingle cell RNA sequencing (scRNA-Seq) was used to characterize leukemia associated neutrophils and define gene expression changes in these cells during leukemia progression.ResultsscRNA-Seq revealed six distinct subgroups of neutrophils based on their specific differential gene expression. In response to leukemia development, there is a dramatic increase in only two of the neutrophil subgroups. These two subgroups show specific gene expression signatures consistent with neutrophil precursors which give rise to immature polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs). Analysis of gene expression in these precursor cells identified pathways that were specifically upregulated, the most pronounced of which involved matrix metalloproteinases Mmp8 and Mmp9, during leukemia progression. Pharmacological inhibition of MMPs using Ilomastat preferentially restricted in vitro migration of neutrophils from leukemic mice and led to a significantly improved survival in vivo, accompanied by impaired PMN-MDSC recruitment. As a result, levels of T-cells were proportionally increased. In clinically annotated TCGA databases, MMP8 was shown to act as an independent indicator for poor prognosis and correlated with higher neutrophil infiltration and poor pan-cancer prognosis.ConclusionWe have defined specific leukemia responsive neutrophil subgroups based on their unique gene expression profile, which appear to be the precursors of neutrophils specifically associated with leukemia progression. An important event during development of these neutrophils is upregulation MMP genes which facilitated mobilization of these precursors from the BM in response to cancer progression, suggesting a possible therapeutic approach to suppress the development of immune tolerance.

Gene expression of protein synthesis, immunity and brain pathways specifically altered in Anorexia Nervosa

IntroductionAnorexia nervosa (AN) is a severe and chronic psychiatric disorder, resulting from a voluntary food restriction, vomiting, use of laxatives and excessive exercises, leading in dramatic weight loss and high mortality. AN is a multifactorial disease involving genetic and epigenetic factors supporting that AN is a metabo-psychiatric disorder. The molecular mechanisms involved in the etiology of AN remain unclear. One work reported gene expression by RNA sequencing in peripheral blood before and after weight restoration in 6 AN patients (Kim 2013), and one RNA sequencing in human iiPSC-derived neurons from 4 patients and 4 controls (Negraes 2017). To date, the profile of expression of genes and proteins in AN is undetermined.ObjectivesIn this study, our goal is to identify specific gene expression signatures from circulating blood nuclear cells to decipher the pathophysiology of AN and characterize biomarkers that can be used for diagnostic or prognostic of AN.MethodsAll consented participants are recruited at Sainte-Anne Hospital, Paris, France, using DSM5 criteria. They had a blood draw in Paxgene tube for the collection of RNAs. Total RNA was extracted from peripheral blood mononuclear cells of 15 patients suffering of AN and 15 healthy controls. All messenger RNAs are sequenced on a Novaseq plateform. Reads are aligned to the human genome 19 and statistical analyses on the read counts for differentially expressed genes are computed with DESeq2.ResultsThe total RNA sequencing allows us to identify 673 dysregulates genes (p adjusted value <0.01, fold change >1,5). Among them, 248 are down-regulated and 425 are up-regulated genes in AN patients compared to controls. From them, 151 transcripts are annotated as pseudogene and 45 are referenced as antisense RNA. Of the 522 remaining transcripts, 424 correspond to a transcript or protein annotated by HGNC and ENSEMBL and 93 are known pseudogenes. A large number of proteins resulting from the expression of deregulated genes interact with each other and form a statistically enriched network impacting biological processes. They are mainly increased and acting in the cellular machinery allowing protein synthesis (biological process: transcription, ribosome, spliceosome and mitochondria). In contrast, down-regulated genes present an enrichment in genes involved in immunity pathways. Finally, several genes are also expressed in the brain. We observed a significant enrichment of genes expressed in the blood and brain tissues.ConclusionsWe identify specific profiles of gene expression in AN. Several genes are both blood and brain tissue expression. Some genes are good candidates for biomarker of the diagnostic in AN that need to be investigated in a longitudinal study to evaluate their useful as prognostic biomarker of AN.This work is supported by Fondation de France & Fédération Recherche sur le Cerveau.Disclosure of InterestNone Declared

Abstract 6560: Cell-free RNA analysis for non-invasive cancer detection and characterization

Abstract Blood-based liquid biopsies enable non-invasive characterization of cancers. Cell-free RNA (cfRNA) analysis could potentially complement circulating tumor DNA (ctDNA) analysis and allow broader molecular characterization of cancers but has not been extensively explored. Here, we describe RARE-Seq, a novel cfRNA sequencing method designed to maximize sensitivity by targeting rare, tissue-specific transcripts, and simultaneously detecting both tumor-derived expression signatures and somatic mutations in circulating tumor RNA (ctRNA). To interrogate samples for specific gene expression signatures, we developed and optimized a framework to measure tumor- and tissue-specific enrichment scores (ES) within cfRNA. We then empirically determined the limit of detection (LOD95) of RARE-Seq using admixtures of tumor cell line RNA and control cfRNA across a wide range of fractions. We found RARE-Seq to have an estimated LOD95 of 0.05% for cancer-derived RNA, which was 52-fold better than whole transcriptome cfRNA profiling. To explore its potential clinical utility, we profiled 192 samples from 170 subjects with various cancers and non-cancer controls using RARE-Seq. Non-small cell lung cancer (NSCLC) expression signatures were significantly detected in 40 out of 51 NSCLC samples (78% sensitivity at 90% specificity). Detection increased with stage, ranging from 40% in stage I to 87% in stage IV. In a subset of stage IV NSCLC patients with matching ctDNA data (n=16), ctRNA levels were significantly correlated with ctDNA allele frequencies (Pearson R=0.84, P=0.005). Intriguingly, 86% of samples with undetectable ctDNA contained detectable ctRNA, suggesting potential complementarity of ctRNA and ctDNA analysis for cancer detection. We also developed and benchmarked a direct ctRNA genotyping approach, allowing noninvasive detection of driver mutations in 42% of patients with advanced NSCLC. When applied to other tumors, RARE-Seq demonstrated 80-100% sensitivity at 90% specificity for detection of pancreatic adenocarcinomas (PAAD), prostate adenocarcinomas (PRAD), and hepatocellular carcinomas (LIHC). Furthermore, when evaluating tissue of origin (TOO) classification performance, RARE-Seq achieved 85% median accuracy for the top predicted tissue and 96% median accuracy for the top two tissues. These results highlight the potential value of ultrasensitive cfRNA analysis, providing proof-of-principle for detection of multiple tumor types using RARE-Seq. Citation Format: Monica C. Nesselbush, Bogdan A. Luca, Young-Jun Jeon, Isabel Jabara, Catherine B. Meador, Michael S. Binkley, Nova Xu, Angela B. Hui, Andrea Garofalo, William Y. Shi, Kevin J. Liu, Takeshi Sugio, Noah Kastelowitz, Emily G. Hamilton, Rene F. Bonilla, Yi Peng Wang, Alice Jiang, Brianna Lau, Jordan Eichholz, Mandeep Banwait, Joseph Schroers-Martin, Jan Boegeholz, Daniel A. King, Mohammad S. Esfahani, Tyler Raclin, Robert Tibshirani, Sandy Srinivas, Viswam S. Nair, James M. Isbell, Bob T. Li, Zofia Piotrowska, Lecia V. Sequist, Aaron N. Hata, Joel W. Neal, Heather A. Wakelee, Andrew J. Gentles, Ash A. Alizadeh, Maximilian Diehn. Cell-free RNA analysis for non-invasive cancer detection and characterization [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6560.

Abstract 6191: Simultaneous prediction of tumor microenvironment biomarkers from pathology slides using multi-task deep regression

Abstract Understanding the Tumor Microenvironment (TME) is crucial for tailoring personalized cancer treatments and improving patient outcomes. Using deep learning, we can predict properties of the TME from standard Hematoxylin and Eosin (H&E) stained slides, including specific gene expression signatures. While past models were limited to single signature predictions, we explore the potential of multi-task deep learning to identify multiple biomarkers at once, allowing more complex relationships and interactions to be modeled simultaneously. Our study focuses on the prediction of expression patterns of tumor, stromal, and immune cells in breast cancer (BC). We developed a multi-task transformer-based deep regression model, trained in a weakly-supervised setting, to predict biomarkers in the TME from routine H&E-stained pathology slides of a BC cohort (n=876). The performance was evaluated using Pearson’s correlation coefficient (r) and spatial heatmaps generated via gradient-weighted class activation mapping. Our model achieved a significant correlation coefficient above 0.40 (p<0.0001) for all predicted TME biomarkers in the holdout test set (n=176). This includes the biomarkers lymphocyte infiltrating signature score (r=0.46, p<0.0001), tumor infiltrating lymphocyte regional fraction (r=0.48, p<0.0001), leukocyte fraction (r=0.43, p<0.0001), stromal fraction (r=0.42, p<0.0001), and tumor cell proliferation (r=0.47, p<0.0001). Notably, the model's heatmaps highlighted the pertinent cells and histological characteristics for its predictions. These data show that our deep learning model accurately predicts multiple TME biomarkers concurrently from routine pathology slides. This approach offers a promising avenue for cost-effective and efficient biomarker quantification in the TME, with potential applicability across various cancer types. Citation Format: Omar S. El Nahhas, Marta Ligero, Jakob N. Kather. Simultaneous prediction of tumor microenvironment biomarkers from pathology slides using multi-task deep regression [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6191.

MYB alternative promoter activity is increased in adenoid cystic carcinoma metastases and is associated with a specific gene expression signature

ObjectiveAdenoid cystic carcinoma (ACC) is a head and neck cancer with a poor long-term prognosis that shows frequent local recurrences and distant metastases. The tumors are characterized by MYB oncogene activation and are notoriously unresponsive to systemic therapies. The biological underpinnings behind therapy resistance of disseminated ACC are largely unknown. Here, we have studied the molecular and clinical significance of MYB alternative promoter (TSS2) usage in ACC metastases. Materials and methodsMYB TSS2 activity was investigated in primary tumors and metastases from 26 ACC patients using RNA-sequencing and quantitative real-time PCR analysis. Differences in global gene expression between MYB TSS2 high and low cases were studied, and pathway analyses were performed. ResultsMYB TSS2 activity was significantly higher in ACC metastases than in primary tumors (median activity 15.1 vs 3.0, P = 0.0003). MYB TSS2 high ACC metastases showed a specific gene expression signature, including increased expression of multi-drug resistance genes and canonical MYB target genes, and suppression of the p53 and NOTCH pathways. ConclusionsCollectively, our findings indicate that elevated MYB TSS2 activity is associated with metastases, potential drug resistance, and augmented MYB-driven gene expression in ACC. Our study advocates the need for new therapies that specifically target MYB and drug resistance mechanisms in disseminated ACC.

Long-term Sudan virus Ebola survivors maintain multiple antiviral defense mechanisms.

The critical issues of sustained memory immunity following ebolavirus disease among long-term survivors (EVD) are still unclear. Here, we examine virus-specific immune and inflammatory responses in 12 Sudan virus (SUDV) long-term survivors from Uganda's 2000-1 Gulu outbreak, 15 years after recovery following in vitro challenge. Total RNA from isolated SUDV-stimulated and unstimulated PBMCs was extracted and analyzed. Matched serum samples were also collected to determine SUDV IgG levels and functionality. We detected persistent humoral (58%, 7 of 12) and cellular (33%, 4 of 12) immune responses in SUDV long-term survivors and identified critical molecular mechanisms of innate and adaptive immunity. Gene expression in immune pathways, the IFN signaling system, antiviral defense response, and activation and regulation of T- and B-cell responses were observed. SUDV long-term survivors also maintained robust virus-specific IgG antibodies capable of polyfunctional responses, including neutralizing and innate Fc effector functions. Data integration identified significant correlations among humoral and cellular immune responses and pinpointed a specific innate and adaptive gene expression signature associated with long-lasting immunity. This could help identify natural and vaccine correlates of protection against ebolavirus disease.

Genetic and Cytometric Characteristics of Pediatric B-Other Acute Lymphoblastic Leukemia Cohort

Background: According to WHO-HAEM5, the majority of precursor B-cell acute lymphoblastic leukemia (B-ALL) cases are classified based on cytogenetic testing according to ploidy changes or well-known chromosomal rearrangements. Approximately 30% of patients with B-ALL, however, display none of the major chromosomal abnormalities. This population is classified together as B-other-ALL, a highly diverse subgroup with heterogenous genetic profiles, clinical characteristics, and outcomes. Recent advances in gene expression profiling and sequencing allowed to identify multiple genetic drivers that confer distinct clinical and prognostic features in B-other ALL resulting in better understanding of this subgroup. Among them, B-ALL with specific gene expression signatures (i.e. BCR-ABL1-like and ETV6-RUNX1-like) have been described and included in the classification. However, due to the complex mechanisms underlying the phenotype, standard molecular and cytogenetic workup is not sufficient to make a diagnosis and there is still no universally accepted definition or diagnostic algorithm. Therefore, there is a need to improve our understanding of genetic aberrations driving B-other ALL, screen for unknown lesions, and associate these findings with clinical picture. Aims: Genetic and cytometric characteristics of pediatric B-other ALL cohort treated in a single center in Poland to evaluate population frequencies of known ALL subtypes, genetic aberrations, immunophenotypes, and evaluate their associations with outcome and clinical and demographic parameters. Methods The study included 54 consecutive children (aged 1-18 years) diagnosed in 2014-2022 with B-other ALL, i.e. excluding hyperdiploidy, hypodiploidy, ETV6-RUNX1, BCR-ABL1, TCF3-PBX1, and KMT2A-fusions. In all samples, targeted RNA sequencing using FusionPlex Acute Lymphoblastic Leukemia library preparation kit (ArcherDx) and digital MLPA using SALSA digital MLPA assay were performed. The samples were sequenced on Illumina MiSeq platform. RNAseq data were analyzed using Archer Analysis software v7.0 and aimed to identify fusions, point mutations and expression levels in 81 genes, including fusion transcripts with unknown partners. MLPA data were analyzed using Coffalyser digitalMLPA software. All novel in-frame fusion transcripts were confirmed with Sanger sequencing. Cytometric evaluation included both standard and extended panel of immunophenotypic markers, i.e. CD45, CD3, CD19, CD34, HLA-DR, phospho-TYR, phospho-STAT3, phospho-STAT5, phospho-CRKL, CRLF2 CD127, CD115, CD25, SOCS1, BLNK, CD97, CD99, CD140A, CD140B, and viability stains (FVS780 and/or 7AAD). Clinical data was obtained retrospectively from medical records. Results: The cohort included 35% of BCR-ABL1-like cases, 2% ETV6-RUNX-like, and 5,5% PAX5 rearranged (1 fusion, 2 mutations). Mutations activating RAS/RAF-MAPK signaling were observed in 64% of cases and spread across all subtypes. JAK-STAT class aberrations were observed in 37% cases whereas ABL-class aberrations - in 7,2%. Three novel in-frame fusion transcripts were detected, including two lesions affecting cytokine/kinase signaling related to BCR-ABL1-like phenotype (TCOF3/PDGFRB and CD74/PDGFRB) and one affecting DNA repair mechanisms (SSBP2/CHD1). Novel aberrations were associated with poor prognosis. In addition, HOOK3/FGFR1 fusion transcript previously described for other hematological malignancies, but not in ALL, was detected in a single subject. Except for CRLF2, none of the single markers alone allowed to distinguish new subtypes of ALL. However, multiparameter statistical analysis of the data allowed to build a Ph-like ALL predictor for the identification of Ph-like ALL cases Conclusion: Our study shows population-based frequencies of novel ALL subtypes, including both recurrent and novel genetic aberrations. This data widens our knowledge on the interplay between molecular aberrations and clinical course of the disease and provides clues for diagnostics optimization.

Alterations in Intratumoral Immune Response before and during Early-On Nivolumab Treatment for Unresectable Advanced or Recurrent Gastric Cancer

We investigated the tumor immune response in gastric cancer patients receiving third-line nivolumab monotherapy to identify immune-related biomarkers for better patient selection. Nineteen patients (10 males, median age 67 years) who received nivolumab as a third- or later-line therapy were enrolled. We analyzed the tumor immune response in durable clinical benefit (DCB) and non-DCB patients. Pre-treatment and early-on-treatment tumor transcriptomes were examined, and gene expression profiles, immunograms, and T cell receptor (TCR) repertoire were analyzed. DCB was observed in 15.8% of patients, with comparable secondary endpoints (ORR; objective response rate, OS; overall survival, PFS; progression-free survival) to previous trials. The immunograms of individual subjects displayed no significant changes before or early in the treatment, except for the regulatory T cell (Treg) score. Moreover, there were no consistent alterations observed among cases experiencing DCB. The intratumoral immune response was suppressed by previous treatments in most third- or later-line nivolumab recipients. TCR repertoire analysis revealed newly emerged clonotypes in early-on-treatment tumors, but clonal replacement did not impact efficacy. High T cell/Treg ratios and a low UV-radiation-response gene signature were linked to DCB and treatment response. This study emphasizes the tumor immune response’s importance in nivolumab efficacy for gastric cancer. High T cell/Treg ratios and specific gene expression signatures show promise as potential biomarkers for treatment response. The tumor-infiltrating immune response was compromised by prior treatments in third-line therapy, implying that, to enhance immunotherapeutic outcomes, commencing treatment at an earlier stage might be preferable. Larger cohort validation is crucial to optimize immune-checkpoint inhibitors in gastric cancer treatment.

Indicators of Response to the Wee1 Inhibitor Adavosertib in Acute Myeloid Leukemia

Wee1 is a nuclear kinase that regulates cell cycle progression by inhibiting Cdk1, which is essential for G2 to M phase transition. Inhibition of Wee1 leads to high Cdk1 activity, causing cells to bypass proper DNA repair at the G2/M checkpoint, resulting in mitotic catastrophe and cell death, plus increased Cdk2 activity, causing abnormal DNA replication and DNA double-stranded breaks. Inhibitors of Wee1 are being investigated for the treatment of a variety of cancers including AML. In this study, we aimed to identify biomarkers for Wee1 inhibitor (Wee1i) response in AML using ex vivo drug sensitivity data, bulk RNA sequence, exome sequence, and associated clinical data for a large set of primary AML samples tested against the Wee1i adavosertib. Mononuclear cells from bone marrow aspirates (n=136) or peripheral blood samples (n=11) were collected from AML patients using approved protocols and after informed consent. 101 samples were collected at the time of diagnosis and 35 samples were from relapsed/refractory (R/R) patients. For ex vivo drug-sensitivity testing, freshly isolated cells were tested against a library of up to 634 oncology drugs (215 approved drugs) including adavosertib. The drugs were pre-plated in 5 concentrations in a 10,000-fold concentration range and incubated with cells for 72h. Cell viability was assessed using the CellTiter Glo (CTG) assay, and a drug sensitivity score (DSS) calculated based on the area under the dose response curve. Somatic alterations of the drug tested samples were identified via exome sequencing of DNA from the AML samples and matched skin biopsy controls. Gene expression data were obtained from bulk RNA sequence data of the AML samples. Out of 136 samples analyzed, the median DSS for adavosertib was 8.45. We found positive and significant correlations between sensitivity to adavosertib and two factors: 1) malignant cell percentage (R= 0.31, p-value= 0.0097), and 2) final relative viability percentage (R=0.58, p-value= 4.3e-13). Correlation analysis between the DSS of adavosertib and 633 other drugs revealed several strong positive and significant correlations. These included drugs with specific mechanisms of actions including HSP90 inhibitors (n=5), JAK2 inhibitors (n=4), topoisomerase II inhibitors (n=4), CDK4/6 inhibitors (n=3), mitotic inhibitors, vinca alkaloid microtubule depolymerizers (n=3), and PLK1 inhibitors (n=3). Since adavosertib also targets PLK1 in addition to Wee1, the correlation with PLK1 inhibitor activity confirms the similar target profiles. Based on the specific adavosertib DSS thresholds, the samples were separated in two groups. Samples sensitive to adavosertib (n=35) had DSS between 21.3 (max) and 11.9 (3rd quartile). Samples resistant to adavosertib (n=34) had DSS between 0.0 (min) and 5.65 (1st quartile). Differential gene expression analysis between the sensitive vs resistant samples showed that multiple isoforms of the PCDH and HOXB genes were upregulated in adavosertib sensitive samples. The GLI2, PI15, and SKIDA1 genes were also upregulated in the sensitive samples (Figure A). In contrast, genes such DNTT, PF4V1, TRH, CD1B, S100A16, and CD34 were overexpressed in resistant samples (Figure B). Gene set enrichment analysis revealed positive enrichment of pathways related to MYC targets v2 in the sensitive samples. On the other hand, hallmark pathways associated with cell cycle, apoptosis, RAS signaling, and p53 showed significant negative enrichment scores in the sensitive samples. No statistically significant associations were observed between drug response and frequently occuring somatic mutations in our dataset. However, genetic abberations related MLLT4-MLL/MLL-fusions were only observed in sensitive samples. Collectively, our current findings show that there may be specific gene expression signatures associated with Wee1i sensitivity such high expression of PCDH and HOXB. Also, the positive enrichment of the MYC target v2 pathway in adavosertib sensitive samples suggests that highly proliferating tumor cells might be more sensitive to Wee1i. In addition, high CD34 expression in resistant samples suggests that immature stem and progenitor cells may be less susceptible to Wee1i. In summary, targeting of Wee1 in AML - as studied in NCT05682170 azenosertib study - may be effective for a molecularly defined subset of patients.

Post-COVID symptoms are associated with endotypes reflecting poor inflammatory and hemostatic modulation.

Persistent symptoms after COVID-19 infection ("long COVID") negatively affects almost half of COVID-19 survivors. Despite its prevalence, its pathophysiology is poorly understood, with multiple host systems likely affected. Here, we followed patients from hospital to discharge and used a systems-biology approach to identify mechanisms of long COVID. RNA-seq was performed on whole blood collected early in hospital and 4-12 weeks after discharge from 24 adult COVID-19 patients (10 reported post-COVID symptoms after discharge). Differential gene expression analysis, pathway enrichment, and machine learning methods were used to identify underlying mechanisms for post-COVID symptom development. Compared to patients with post-COVID symptoms, patients without post-COVID symptoms had larger temporal gene expression changes associated with downregulation of inflammatory and coagulation genes over time. Patients could also be separated into three patient endotypes with differing mechanistic trajectories, which was validated in another published patient cohort. The "Resolved" endotype (lowest rate of post-COVID symptoms) had robust inflammatory and hemostatic responses in hospital that resolved after discharge. Conversely, the inflammatory/hemostatic responses of "Suppressive" and "Unresolved" endotypes (higher rates of patients with post-COVID symptoms) were persistently dampened and activated, respectively. These endotypes were accurately defined by specific blood gene expression signatures (6-7 genes) for potential clinical stratification. This study allowed analysis of long COVID whole blood transcriptomics trajectories while accounting for the issue of patient heterogeneity. Two of the three identified and externally validated endotypes ("Unresolved" and "Suppressive") were associated with higher rates of post-COVID symptoms and either persistently activated or suppressed inflammation and coagulation processes. Gene biomarkers in blood could potentially be used clinically to stratify patients into different endotypes, paving the way for personalized long COVID treatment.

Transcriptional and spatial profiling of the kidney allograft unravels a central role for FcyRIII+ innate immune cells in rejection

Rejection remains the main cause of premature graft loss after kidney transplantation, despite the use of potent immunosuppression. This highlights the need to better understand the composition and the cell-to-cell interactions of the alloreactive inflammatory infiltrate. Here, we performed droplet-based single-cell RNA sequencing of 35,152 transcriptomes from 16 kidney transplant biopsies with varying phenotypes and severities of rejection and without rejection, and identified cell-type specific gene expression signatures for deconvolution of bulk tissue. A specific association was identified between recipient-derived FCGR3A+ monocytes, FCGR3A+ NK cells and the severity of intragraft inflammation. Activated FCGR3A+ monocytes overexpressed CD47 and LILR genes and increased paracrine signaling pathways promoting T cell infiltration. FCGR3A+ NK cells overexpressed FCRL3, suggesting that antibody-dependent cytotoxicity is a central mechanism of NK-cell mediated graft injury. Multiplexed immunofluorescence using 38 markers on 18 independent biopsy slides confirmed this role of FcγRIII+ NK and FcγRIII+ nonclassical monocytes in antibody-mediated rejection, with specificity to the glomerular area. These results highlight the central involvement of innate immune cells in the pathogenesis of allograft rejection and identify several potential therapeutic targets that might improve allograft longevity.

Immunological modifications following chemotherapy are associated with delayed recurrence of ovarian cancer.

Ovarian cancer recurs in most High Grade Serous Ovarian Cancer (HGSOC) patients, including initial responders, after standard of care. To improve patient survival, we need to identify and understand the factors contributing to early or late recurrence and therapeutically target these mechanisms. We hypothesized that in HGSOC, the response to chemotherapy is associated with a specific gene expression signature determined by the tumor microenvironment. In this study, we sought to determine the differences in gene expression and the tumor immune microenvironment between patients who show early recurrence (within 6 months) compared to those who show late recurrence following chemotherapy. Paired tumor samples were obtained before and after Carboplatin and Taxol chemotherapy from 24 patients with HGSOC. Bioinformatic transcriptomic analysis was performed on the tumor samples to determine the gene expression signature associated with differences in recurrence pattern. Gene Ontology and Pathway analysis was performed using AdvaitaBio's iPathwayGuide software. Tumor immune cell fractions were imputed using CIBERSORTx. Results were compared between late recurrence and early recurrence patients, and between paired pre-chemotherapy and post-chemotherapy samples. There was no statistically significant difference between early recurrence or late recurrence ovarian tumors pre-chemotherapy. However, chemotherapy induced significant immunological changes in tumors from late recurrence patients but had no impact on tumors from early recurrence patients. The key immunological change induced by chemotherapy in late recurrence patients was the reversal of pro-tumor immune signature. We report for the first time, the association between immunological modifications in response to chemotherapy and the time of recurrence. Our findings provide novel opportunities to ultimately improve ovarian cancer patient survival.

Lymph-Node-Based CD3+ CD20+ Cells Emerge from Membrane Exchange between T Follicular Helper Cells and B Cells and Increase Their Frequency following Simian Immunodeficiency Virus Infection.

CD4+ T follicular helper (TFH) cells are key targets for human immunodeficiency virus (HIV)/simian immunodeficiency virus (SIV) replication and contribute to the virus reservoir under antiretroviral therapy (ART). Here, we describe a novel CD3+ CD20+ double-positive (DP) lymphocyte subset, resident in secondary lymphoid organs of humans and rhesus macaques (RMs), that appear predominantly after membrane exchange between TFH and B cells. DP lymphocytes are enriched in cells displaying a TFH phenotype (CD4+ PD1hi CXCR5hi), function (interleukin 21 positive [IL-21+]), and gene expression profile. Importantly, expression of CD40L upon brief in vitro mitogen stimulation identifies, by specific gene-expression signatures, DP cells of TFH-cell origin versus those of B-cell origin. Analysis of 56 RMs showed that DP cells (i) significantly increase following SIV infection, (ii) are reduced after 12 months of ART in comparison to pre-ART levels, and (iii) expand to a significantly higher frequency following ART interruption. Quantification of total SIV-gag DNA on sorted DP cells from chronically infected RMs showed that these cells are susceptible to SIV infection. These data reinforce earlier observations that CD20+ T cells are infected and expanded by HIV infection, while suggesting that these cells phenotypically overlap activated CD4+ TFH cells that acquire CD20 expression via trogocytosis and can be targeted as part of therapeutic strategies aimed at HIV remission. IMPORTANCE The HIV reservoir is largely composed of latently infected memory CD4+ T cells that persist during antiretroviral therapy and constitute a major barrier toward HIV eradication. In particular, CD4+ T follicular helper cells have been demonstrated as key targets for viral replication and persistence under ART. In lymph nodes from HIV-infected humans and SIV-infected rhesus macaques, we show that CD3+ CD20+ lymphocytes emerge after membrane exchange between T cells and B cells and are enriched in phenotypic, functional, and gene expression profiles found in T follicular helper cells. Furthermore, in SIV-infected rhesus macaques, these cells expand following experimental infection and after interruption of ART and harbor SIV DNA at levels similar to those found in CD4+ T cells; thus, CD3+ CD20+ lymphocytes are susceptible to SIV infection and can contribute to SIV persistence.

Gene expression profiling of peripheral blood mononuclear cells from women with cervical lesions reveals new markers of cancer.

Cervical cancer (CC) is a multifactorial disease of which human papillomavirus (HPV) is the main etiological agent. Despite cervical Pap smear screening and anti‑HPV vaccination, CC remains a major public health issue. Identification of specific gene expression signatures in the blood could allow better insight into the immune response of CC and could provide valuable information for the development of novel biomarkers. The present study performed a transcriptomic analysis of peripheral blood mononuclear cells (PBMCs) from Senegalese patients with CC (n=31), low‑grade cervical intraepithelial neoplasia (CIN1; n=27) and from healthy control (CTR) subjects (n=29). Individuals in the CIN1 and CTR groups exhibited similar patterns in gene expression. A total of 182 genes were revealed to be differentially expressed in patients with CC compared with individuals in the CIN1 and CTR groups. The IL1R2, IL18R1, MMP9 and FKBP5 genes were the most upregulated, whereas the T‑cell receptor α gene TRA was the most downregulated in the CC group compared with in the CIN1 and CTR groups. The pathway enrichment analysis of the differentially expressed genes revealed pathways directly and indirectly linked to inflammation. To the best of our knowledge, the present study is the first large transcriptomic study on CC performed using PBMCs from African women; the results revealed the involvement of genes and pathways related to inflammation, most notably the IL‑1 pathway, and the involvement of downregulation of the T‑cell receptor α, a key component of the immune response. Several of the stated genes have already been reported in other cancer studies as putative blood biomarkers, thus reinforcing the requirement for deeper investigation. These findings may aid in the development of innovative clinical biomarkers for CC prevention and should be further replicated in other populations.

Abstract 3520: Single cell-derived spheroids capture functional and genetic heterogeneity of head and neck cancer

Abstract Introduction: Single cell transcriptome is used for mapping the genetic heterogeneity of a tumour; however, it does not reflect the functional heterogeneity. Currently, no model is available to provide a genotype to phenotype correlations for the heterogeneity. We developed the HNSCC spheroids from single cell that showed hyperproliferation/hypomigration or hypoproliferation/hypermigration properties, and performed transcriptome and proteomics approach to identify the underlaying mechanisms. Materials and methods: Two cells/well from HNSCC cell line UMSCC-22B were cultured in ultra-low attachment plate to develop spheroids, which were identified for their functionality by monitoring growth and cell migration. Hyperproliferative/hypomigratory or hypoproliferative/hypermigratory spheroids were pooled to perform single cell transcriptome. sSpheroid were used for proteomic analysis. Results: Single cell analysis showed four distinct clusters of cells in hyperproliferative/hypomigratory spheroids and six clusters in hypoproliferative/hypermigratory spheroids. Each cluster showed specific gene expression signature enriching a specific pathways. The hyperproliferative/hypomigratory spheroids clusters showed enrichment of cell cycle, anti-apoptosis, and pro-survival genes associated with EGFR, Wnt and Notch signalling pathways. Whereas hypoproliferative/hypermigratory spheroids cluster showed enrichment of TGF-beta, VEGF, and wound healing related pathways. Cell ontology tracing with gene signatures revealed the dominance of neoplastic cells with enrichment of EGFR, MAP Kinase, Wnt signalling pathways in the hyperproliferative/hypomigratory spheroids. The fibroblast cell cluster showed expression of stem cell markers and enrichment of ERK and EGFR related pathways. Bayesians and non-bayesians network analyses identified the surface proteins, ITGA6, Met, CD63, ICAM, and Kit as unique driver genes for hyperproliferative/hypomigratory spheroids whereas ITGB3, CD44, and EGFR were the driver genes for hypoproliferative/hypermigratory spheroids. Proteomic analysis also conformed the enrichment of antiapoptosis and cell survival related pathways in hyperproliferative/hypomigratory spheroids. While epithelial cell differentiation to keratinized cells and wound healing pathways were enriched in hypoproliferative/hypermigratory spheroids. TCGA data shows correlation with our analysis for survival/stage/progression of the disease. Conclusions: Our results suggest that single cell-derived clonal spheroid represents the genetic heterogeneity of cell population and correlates with functionality of the spheroids. These spheroids can be used as tools and the identification of cell clusters in head and neck cancer patients can be used for deciding the optimal therapeutics as well as to predict the progression of the cancer. Citation Format: Jyoti Pandey, Md Jubbair Malik, Ritis K. Shyanti, Jee Min Lee, Dhanir Tailor, Sanjay V. Malhotra, Rupesh Chaturvedi, Rana P. Singh. Single cell-derived spheroids capture functional and genetic heterogeneity of head and neck 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 3520.