Biology subjects

Petti, A. A.

Publications and source records attributed to Petti, A. A..

11 recordsLinked to original sources

bioRxiv2026

Single-Cell Analysis of Non-Functioning Gonadotroph Tumors Identifies Lineage Infidelity and Tumor Growth Programs

Non-functioning gonadotroph (NFG) tumors are the most common type of non-functioning pituitary adenomas and can cause significant symptoms due to mass effect. However, the molecular programs underlying NFG tumor growth and their relationship to the normal anterior pituitary gland (APG) are poorly understood. To gain a deeper understanding of NFG tumor biology in the context of the normal APG, we performed single-cell/nucleus RNA-sequencing on 21 NFG tumors and 8 APG samples in human, generating the largest transcriptomic dataset of its kind. Single-cell/nucleus sequencing yielded 77,342, cells from APG samples and 152,649 cells from NFG tumor samples. Differential expression analysis within the APG identified novel marker genes of each neuroendocrine cell type and defined distinct transcriptional signatures of anterior and posterior pituitary stem cell populations. Comparison with tumor transcriptomes revealed that NFG tumor cells most closely resemble gonadotrophs, while also showing significant enrichment of thyrotroph and somatotroph markers. Notably, there was no significant overlap with stem cell markers, suggesting that NFG tumors most likely originate from differentiated gonadotrophs but can take on transcriptional characteristics of other neuroendocrine cell types. Pseudobulk profiling of NFG tumor cells demonstrated that tumor volume is significantly positively correlated with 83 genes including known oncogenes CAD, BRF2, and SOX12, along with 16 zinc finger transcription factors. Lastly, analysis of the tumor microenvironment revealed proportional increases in myeloid, endothelial, and mural cell populations in tumor samples compared to APG samples and highlighted cross talk between tumor and endothelial, mesenchymal, and immune populations via VEGF, PDGF, and MIF signaling pathways respectively. This study identifies novel transcriptomic signatures determining cell type identity in both APG neuroendocrine and NFG tumor cells. Our findings elucidate molecular programs driving NFG lineage infidelity and tumor growth, highlighting candidate predictors of patient outcomes and potential targets for therapeutic intervention.

cancer biology↗

bioRxiv2026

Integrated spatial and single-cell transcriptomic analysis of aggressive glioblastoma growth dynamics.

Glioblastoma (GBM) develops within a complex tumor ecosystem whose temporal dynamics remain poorly understood. Here, we performed longitudinal single-cell RNA sequencing and spatial transcriptomics across multiple timepoints in two widely used murine GBM models - CT2A and GL261 - which differ markedly in aggressiveness and response to immune checkpoint blockade. Tumor cell transcriptomes revealed model-specific programs: CT2A cells progressively upregulated epithelial-mesenchymal transition (EMT), non-classical MHC Class I, and progressively, hypoxia response pathways, resembling the human mesenchymal GBM cell state, while GL261 cells exhibited MHC Class II expression and developmental signatures resembling oligodendrocyte progenitor and astrocytic states. Ligand-receptor interaction analyses identified thrombospondins (Thbs1, Thbs2) and osteopontin (Spp1) as CT2A-specific tumor ligands mediating tumorigenic interactions with immune cells, with downstream targets enriched for EMT and TGF-{beta} pathways. Conversely, the GL261 model presented a differential potential to engage neuronal and perivascular guidance networks, with Glutamate and L1 cell adhesion molecule (L1cam) as lead signaling partners. The CT2A immune compartment exhibited progressive microglia-to-macrophage phenotypic conversion, enhanced macrophage infiltration driven by Spp1, and elevated T cell exhaustion, while GL261 maintained a distinct adaptive immune communication hub via MHC class II-CD4 signaling. Elevated THBS1, THBS2, and SPP1 expression correlated with poor survival in human GBM datasets. Together, these findings reveal divergent tumor-immune ecosystems in CT2A and GL261 that recapitulate distinct aspects of human GBM, with implications for therapeutic targeting.

cancer biology↗

bioRxiv2025

Mapping CD4+ T Cell Landscapes in Glioblastoma Reveals Effectors and Bystanders

The tumor immune microenvironment (TME) has been demonstrated to significantly shape glioblastoma (GBM) progression and therapeutic response, yet the role of CD4+ T cells remains incompletely defined. Here, by integrating single-cell RNA, surface-protein, and TCR profiling of 39,788 T cells from 16 high-grade gliomas with five matched blood samples, we mapped 23,550 CD4+ T cells across 11 states and revealed predominance of CD4+ T cells in primary, but not recurrent, tumors, alongside pronounced tumor-blood discordance. Clonal analyses revealed expansion of cytotoxic effector CD4+ T cells within tumors and TEMRA CD4+ T cells in blood. A small set of dominant clonotypes (0.2% of unique TCR{beta} sequences) accounted for >6% of all CD4+ T cells across both compartments and were shared across different transcriptional subsets, suggesting diverse transcriptional development stemming from a shared progenitor. In contrast, virally annotated clonotypes were broadly dispersed and largely unexpanded, consistent with bystander populations. Collectively, we investigated the cellular and clonal architecture of human CD4+ T cells in GBM and highlight the contrast between PBMC and TIL compartments.

immunology↗

bioRxiv2025

LLM-Assisted Functional Gene Annotation

Functional gene annotation is a highly manual and subjective process that requires analysis of large amounts of statistical and literature results. Here we present Artificial Intelligence Gene Enrichment (AIGE), a careful automation of the current state of the art process used by bioinformatic experts to deter-mine functions enriched in novel or experimentally derived gene lists. In 1206 test cases, AIGE is able to accurately recover 87% of biological functions, path-ways, and cell types, is robust to noise contamination, and accurately assesses its own self-confidence. AIGE reports provide accurate functional annotations and encourage further research in a broad set of contexts.

bioinformatics↗

bioRxiv2025

Single-Cell Analysis of Meningiomas Reveals Mutation-Associated Tumor and Immune Cell Gene Expression Programs

Genomic and epigenetic profiling, particularly DNA methylation analysis, have refined the molecular classification of meningiomas and revealed marked intratumoral heterogeneity. To further characterize heterogeneity within and between patients, we analyzed meningiomas using single-cell RNA sequencing (n=11), whole-exome sequencing (n=9), and spatial transcriptomics (n=3). Single-cell analysis revealed six transcriptionally distinct tumor cell states that corresponded to unique biological processes. Integration of the single-cell data with published exome and bulk RNA sequencing data from a large cohort revealed significant associations among somatic variants, tumor cell states, and immunological signatures. Notably, NF2-altered tumors were enriched for an epithelial-to-mesenchymal transition (EMT) cell state and immune cells, whereas NF2-intact tumors were enriched for a sterol metabolism cell state. Spatial transcriptomic analysis confirmed co-localization of immune cells and EMT tumor cells. Comparisons with immune cells from other brain tumors and peripheral tissues highlighted immunological cell states specific to meningioma. Collectively, these findings refine our genetic and molecular understanding of meningioma heterogeneity and underscore the link between genotype and molecular phenotype.

cancer biology↗

bioRxiv2025

Mapping the spatial architecture of glioblastoma from core to edge delineates niche-specific tumor cell states and intercellular interactions

Treatment resistance in glioblastoma (GBM) is largely driven by the extensive multi-level heterogeneity that typifies this disease. Despite significant progress toward elucidating GBMs genomic and transcriptional heterogeneity, a critical knowledge gap remains in defining this heterogeneity at the spatial level. To address this, we employed spatial transcriptomics to map the architecture of the GBM ecosystem. This revealed tumor cell states that are jointly defined by gene expression and spatial localization, and multicellular niches whose composition varies along the tumor core-edge axis. Ligand-receptor interaction analysis uncovered a complex network of intercellular communication, including niche- and region-specific interactions. Finally, we found that CD8 positive GZMK positive T cells colocalize with LYVE1 positive CD163 positive myeloid cells in vascular regions, suggesting a potential mechanism for immune evasion. These findings provide novel insights into the GBM tumor microenvironment, highlighting previously unrecognized patterns of spatial organization and intercellular interactions, and novel therapeutic avenues to disrupt tumor-promoting interactions and overcome immune resistance.

cancer biology↗

bioRxiv2023

NF2 Loss-of-Function and Hypoxia Drive Radiation Resistance in Grade 2 Meningiomas

BackgroundWorld Health Organization Grade 2 meningiomas (G2Ms) exhibit an aggressive natural history characterized by recurrence and therapy resistance. G2Ms with histopathological necrosis have been associated with worse local control (LC) following radiation therapy, but drivers and biomarkers of radiation resistance in these G2Ms remain unknown. MethodsWe performed genetic sequencing and histopathological analysis of 113 G2Ms and investigated the role of intratumoral hypoxia as well as genes of interest through knockdown and clonogenic survival following ionizing radiation. Lastly, we performed transcriptional profiling of our in vitro model and 18 G2M tumors using RNA sequencing. ResultsNF2 loss-of-function (LOF) mutations were associated with necrosis in G2Ms (p=0.0127). Tumors with NF2 mutation and necrosis had worse post-radiation LC compared to NF2 wildtype tumors without necrosis (p=0.035). Under hypoxic conditions, NF2 knockdown increased radiation resistance in vitro (p<0.001). Bulk RNA sequencing of our in vitro model revealed NF2- and hypoxia-specific changes and a 50-gene set signature specific to radiation resistant, NF2 knockdown and hypoxic cells, which could distinguish NF2 mutant and necrotic patient G2Ms by unsupervised clustering. Gene set enrichment analysis of patient tumor and in vitro data revealed downregulation of apoptosis and upregulation of proliferation in NF2-deficient and hypoxic cells, which we validated with functional assays. ConclusionsNF2 LOF in the setting of hypoxia confers radiation resistance through transcriptional programs that reduce apoptosis and promote proliferation. These pathways may identify tumors resistant to radiation and represent therapeutic targets that in the future could improve LC in patients with radiation resistant G2Ms. KEY POINTS1. Spontaneous necrosis with NF2 mutations is associated with radio-resistance in WHO G2Ms. 2. NF2 knockdown in the setting of hypoxia confers radio-resistance to meningioma cells in vitro and is driven by increased cell proliferation and decreased apoptosis. IMPORTANCE OF THE STUDYWorld Health Organization Grade 2 meningiomas (G2M) are often treated with surgical resection followed by radiation, especially in the case of recurrence. However, the mechanisms underlying radiation resistance in G2Ms remain to be identified, and moreover, we lack biomarkers to distinguish G2Ms that will respond to radiotherapy from those that are refractory. In this study we perform histological and molecular analysis of a large cohort of G2Ms to identify predictors of radiation resistance. Using these data and an in vitro model of radiation therapy, we demonstrate that radiation resistance in G2Ms is likely driven by the combination of NF2 gene mutations and the hypoxia that accompanies tumor necrosis. Patients whose tumors bear these two features may therefore benefit from alternative treatments that target specific pathways implicated in radiation resistance.

molecular biology↗

bioRxiv2023

Glioblastoma-infiltrating CD8+ T cells are predominantly a clonally expanded GZMK+ effector population

Recent clinical trials have highlighted the limited efficacy of T cell-based immunotherapy in patients with glioblastoma (GBM). To better understand the characteristics of tumor-infiltrating lymphocytes (TIL) in GBM, we performed cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) and single-cell RNA sequencing (scRNA-seq) with paired V(D)J sequencing, respectively, on TIL from two cohorts of patients totaling 15 patients with high grade glioma, including GBM or astrocytoma, IDH mutant, grade 4 (G4A). Analysis of the CD8+ TIL landscape reveals an enrichment of clonally expanded GZMK+ effector T cells in the tumor compared to matched blood, which was validated at the protein level. Furthermore, integration with other cancer types highlights the lack of a canonically exhausted CD8+ T cell population in GBM TIL. These data suggest that GZMK+ effector T cells represent an important T cell subset within the GBM microenvironment and which may harbor potential therapeutic implications. SignificanceIn order to understand the limited efficacy of immune checkpoint blockade in GBM, we endeavor to understand the TIL landscape through a multi-omics approach. In this study, by highlighting the enrichment of GZMK+ effector T cells and lack of exhausted T cells, we provide a new potential mechanism of resistance to immunotherapy in GBM.

immunology↗

bioRxiv2022

Single-cell multi-omic analysis of the vestibular schwannoma ecosystem uncovers a nerve injury-like state

Vestibular schwannomas (VS) are benign tumors that lead to significant neurologic and otologic morbidity. How VS heterogeneity and the tumor microenvironment (TME) contribute to the pathogenesis of these tumors remains poorly understood. We performed scRNA-seq on 15 VS samples, with paired scATAC-seq in six samples. We identified diverse Schwann cell (SC), stromal, and immune populations in the VS TME and found that repair-like and MHC-II antigen presenting subtype SCs are associated with increased myeloid cell infiltrate, implicating a nerve injury-like process. Deconvolution analysis of RNA-expression data from 175 tumors revealed Injury-like tumors are associated with larger tumor size, and scATAC-seq identified transcription factors associated with nerve repair among SCs from Injury-like tumors. Ligand-receptor analysis and functional in vitro experiments suggested that SCs recruit monocytes. Our study indicates that Injury-like SCs may cause tumor growth via myeloid cell recruitment and identifies molecular pathways that may be targeted to prevent tumor progression.

cancer biology↗

bioRxiv2021

Single Cell Atlas of Human Dura Reveals Cellular Meningeal Landscape and Insights into Meningioma Immune Response

Recent investigation of the meninges, specifically the dura layer, has highlighted its importance in CNS immune surveillance beyond a purely structural role. However, most of our understanding of the meninges stems from the use of pre-clinical models rather than human samples. In this study, we use single cell RNA-sequencing to perform the first characterization of both non-tumor-associated human dura and meningioma samples. First, we reveal a complex immune microenvironment in human dura that is transcriptionally distinct from that of meningioma. In addition, through T cell receptor sequencing, we show significant TCR overlap between matched dura and meningioma samples. We also identify a functionally heterogeneous population of non-immune cell types and report copy-number variant heterogeneity within our meningioma samples. Our comprehensive investigation of both the immune and non-immune cell landscapes of human dura and meningioma at a single cell resolution provide new insight into previously uncharacterized roles of human dura.

immunology↗

bioRxiv2018

Mutation detection in thousands of acute myeloid leukemia cells using single cell RNA-sequencing

Virtually all tumors are genetically heterogeneous, containing subclonal populations of cells that are defined by distinct mutations1. Subclones can have unique phenotypes that influence disease progression2, but these phenotypes are difficult to characterize: subclones usually cannot be physically purified, and bulk gene expression measurements obscure interclonal differences. Single-cell RNA-sequencing has revealed transcriptional heterogeneity within a variety of tumor types, but it is unclear how this expression heterogeneity relates to subclonal genetic events - for example, whether particular expression clusters correspond to mutationally defined subclones3,4,5,6-9. To address this question, we developed an approach that integrates enhanced whole genome sequencing (eWGS) with the 10x Genomics Chromium Single Cell 5 Gene Expression workflow (scRNA-seq) to directly link expressed mutations with transcriptional profiles at single cell resolution. Using bone marrow samples from five cases of primary human Acute Myeloid Leukemia (AML), we generated WGS and scRNA-seq data for each case. Duplicate single cell libraries representing a median of 20,474 cells per case were generated from the bone marrow of each patient. Although the libraries were 5 biased, we detected expressed mutations in cDNAs at distances up to 10 kbp from the 5 ends of well-expressed genes, allowing us to identify hundreds to thousands of cells with AML-specific somatic mutations in every case. This data made it possible to distinguish AML cells (including normal-karyotype AML cells) from surrounding normal cells, to study tumor differentiation and intratumoral expression heterogeneity, to identify expression signatures associated with subclonal mutations, and to find cell surface markers that could be used to purify subclones for further study. The data also revealed transcriptional heterogeneity that occurred independently of subclonal mutations, suggesting that additional factors drive epigenetic heterogeneity. This integrative approach for connecting genotype to phenotype in AML cells is broadly applicable for analysis of any sample that is phenotypically and genetically heterogeneous.

cancer biology↗