Biology subjects

Mino-Kenudson, M.

Publications and source records attributed to Mino-Kenudson, M..

14 recordsLinked to original sources

bioRxiv2026

Prevalence and Actionability of MTAP Loss in Oncogene-Driven Lung Cancer

BackgroundMethylthioadenosine phosphorylase (MTAP) loss co-occurs with actionable genomic alterations in non-small cell lung cancer (NSCLC) and creates vulnerability to protein arginine methyltransferase 5 (PRMT5) inhibition. Estimates of prevalence of MTAP loss rely on next-generation sequencing which can underestimate copy losses. Moreover, the activity of PRMT5 inhibitors in oncogene-driven NSCLC is not well established. MethodsWe assessed MTAP expression by immunohistochemistry (IHC) in 243 NSCLCs (n=132 early stage, n=111 metastatic), including 33 specimens with paired lymph nodes. Antiproliferative activity of PRMT5 inhibitor monotherapy and in combination with tyrosine kinase inhibitors (TKIs) was evaluated in MTAP-deleted NSCLC cell lines harboring EGFR or KRAS mutations or ALK rearrangements. ResultsAmong 243 NSCLC specimens from 240 patients (72% with driver alterations, 90% adenocarcinoma), MTAP loss was identified in 43 (18%) specimens from 40 (17%) patients, including 18 (14%) early-stage and 22 (20%) metastatic tumors. MTAP loss occurred in 24% of stage 4 driver-positive NSCLCs versus 14% of driver-negative tumors (p=0.314). Twenty (61%) lung-nodal pairs demonstrated concordance; eight cases only exhibited decreased MTAP expression in nodes. Variable sensitivity to PRMT5 inhibitors was observed in 22 MTAP-deleted NSCLC cell lines (9 EGFR-mutant, 7 KRAS-mutant, 6 ALK-rearranged), with responses seen in TKI-sensitive and TKI-resistant lines. SDMA (symmetric dimethylarginine) expression did not predict PRMT5 inhibitor sensitivity. TKI + PRMT5 inhibitor combos had greater activity than monotherapy. ConclusionsMTAP loss occurs in 1-in-5 oncogene-driven metastatic NSCLCs. PRMT5 inhibitor activity is independent of TKI exposure, driver alteration, and SDMA expression and enhanced by addition of TKI. These findings support clinical evaluation of PRMT5 inhibitor + TKI combinations for advanced NSCLC.

cancer biology↗

bioRxiv2025

GLIS3 Marks a Neural-like Progenitor Cell State that Drives Metastasis in Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) has a high rate of recurrence and metastasis despite intensive therapy. The neural-like progenitor (NRP) transcriptional program is enriched in residual disease after neoadjuvant chemotherapy and radiotherapy; however, the mechanisms for increased NRP expression in the post-treatment setting remain unclear. Here, we find that NRP signatures are strongly enriched in tissue injury and regeneration, and NRP cancer cells co-express transcription factors involved in pancreatic development. We identify both cell autonomous and ligand mediated mechanisms for inducing NRP expression in vitro. We establish and characterize isogenic mouse organoid overexpression models for transcription factors associated with the NRP, classical, and basal-like states. We discovered that Glis3 is a key NRP-associated transcription factor that drives malignant properties including greater clonogenicity, tumor growth, and metastasis compared to isogenic models for the classical and basal-like states. Our work highlights the emergence of clinically relevant developmental regeneration programs in the post-treatment context.

cancer biology↗

bioRxiv2025

The Pdgfd-Pdgfrb axis orchestrates tumor-nerve crosstalk in pancreatic cancer

Nerves are an integral component of the tumor microenvironment, contributing to cancer progression, metastasis, morbidity, and mortality. In pancreatic ductal adenocarcinoma (PDAC), worse clinical outcomes are associated with perineural invasion (PNI), a process by which cancer cells surround and invade nerves. Here, we employed whole-transcriptome and single-cell spatial transcriptomics to identify candidate tumor-nerve interactions that promote PNI. We discovered that Pdgfd signaling promotes key features of nerve invasion. Mechanistically, Pdgfd stimulated cancer cell invasiveness, neurite outgrowth, and direct physical engagement with glia. Pharmacological blockade of this axis reduced each of these processes in vitro as well as PNI in vivo. Thus, Pdgfd-Pdgfrb signaling mediates PNI by coordinating multifaceted cancer-neuron-glia interactions and represents a promising therapeutic strategy aimed at disrupting harmful cancer-nerve crosstalk.

cancer biology↗

bioRxiv2025

Distinct malignant cell states and myeloid glutamate signaling associated with aggressive pancreatic neuroendocrine tumors

Pancreatic neuroendocrine tumors (PNET) are rare malignancies of the endocrine pancreas with diverse clinical outcomes. While some PNETs are indolent, others are aggressive and metastasize quickly. However, clinically-relevant molecular stratification for PNET to predict outcomes and guide therapeutic decision-making is limited. Thus, there is an urgent need to understand the molecular heterogeneity of PNETs to refine prognostication and discover novel therapeutic vulnerabilities. We performed single-nucleus RNA sequencing on resected primary and metastatic PNETs (n = 20), including two PNETs with neoadjuvant treatment. We inferred gene expression programs (GEPs) of malignant and non-malignant cells and investigated associations with clinical outcomes. Next, we inferred interactions in the tumor microenvironment (TME) and performed transwell assays for functional validation. Finally, we explored genomic and transcriptomic evolution in a unique case study of an untreated primary PNET with two asynchronous hepatic metastases. A malignant GEP enriched for neural/synaptic signaling genes was associated with worse overall survival, broad chromosomal loss of heterozygosity, and alternative lengthening of telomeres. Another malignant GEP enriched for VEGF signaling increased throughout metastatic progression in our case study. We found that macrophage-derived glutamate drives polarization towards an immunosuppressive phenotype and activates the MAPK/ERK pathway in malignant cells to increase migratory capacity. This study provides a detailed single-nucleus transcriptomic classification of malignant, stromal, and immune cell types and states in PNETs, their interactions in the TME, and associations with clinical outcomes. The refined molecular taxonomy of PNET may guide the development of more efficacious biomarkers and therapeutic strategies.

cancer biology↗

bioRxiv2025

Intraductal Papillary Mucinous Neoplasm Cellular Plasticity linked with Repeat Element Dysregulation

BackgroundIntraductal papillary mucinous neoplasms (IPMNs) are preinvasive pancreatic lesions with a spectrum of histologic phenotypes and variable risk in progressing to invasive cancer. Aberrant repetitive element expression has been shown to be functionally linked to cell state changes in pancreatic cancer. ObjectiveThis study utilized spatial transcriptomics with customized repeat element probes to better understand the relationship of histologic subtypes, repeat element dysregulation, and molecular profiles of different cell populations in IPMN. DesignA total of 52 lesions from 18 patients with resected IPMNs of different histologies and degrees of dysplasia were analyzed with whole transcriptome spatial analysis (GeoMx). Of these, 50 lesions from 17 patients were also processed for single-cell spatial molecular imaging (CosMx). Repeat element probes for LINE1, HSATII, HERVK, and HERVH were used for GeoMx and CosMx. ResultsPancreaticobiliary-type IPMN was enriched for basal-like epithelium and infiltration of Treg cells. Intestinal-type IPMN was enriched for classical epithelium and macrophage infiltrates. Gastric-type IPMN was found to have equal basal-like and classical epithelium with a diverse immune infiltrate. Repeat RNAs were expressed at high levels across IPMN phenotypes and enriched in high-grade dysplasia. Single-cell transcriptional trajectory analysis revealed a phylogeny starting from gastric toward intestinal and pancreaticobiliary branches associated with higher-grade dysplasia and repeat RNA expression. ConclusionSpatial transcriptomics of IPMN identified a molecular continuum between histological subtypes supporting a common gastric-type origin that transitions to intestinal and pancreatobiliary phenotypes. This cell state plasticity is linked with repeat element expression that can be a potential biomarker for IPMN progression. What is already known on this topicO_LIMolecular characterization of IPMN subtypes using regional spatial transcriptomics has described the differences between histologies C_LIO_LIRepeat element expression is associated with cell state changes in pancreatic ductal neoplasm C_LI What this study addsO_LISingle cell spatial molecular imaging of IPMN subtypes reveals a cellular and molecular continuum starting from gastric histology with distinct branches to Intestinal and pancreatobiliary subtypes C_LIO_LIRepeat element expression is associated with higher grade IPMN histology C_LIO_LIRepeat element expression is elevated in the histologic and molecular continuum from gastric to intestinal and pancreatobiliary-type IPMN C_LI How this study might affect research, practice, or policyO_LIThese results support a common gastric histology origin of IPMN subtypes with different molecular trajectories towards higher grade disease C_LIO_LIOur findings suggest that repeat RNA expression can be used in conjunction with other transcriptional markers of cell state as a biomarker for IPMN progression C_LI

cancer biology↗

bioRxiv2024

Multi-omic profiling of intraductal papillary neoplasms of the pancreas reveals distinct expression patterns and potential markers of progression

In order to advance our understanding of precancers in the pancreas, 69 pancreatic intraductal papillary neoplasms (IPNs), including 64 intraductal papillary mucinous neoplasms (IPMNs) and 5 intraductal oncocytic papillary neoplasms (IOPNs), 32 pancreatic cyst fluid samples, 104 invasive pancreatic ductal adenocarcinomas (PDACs), 43 normal adjacent tissues (NATs), and 76 macro-dissected normal pancreatic ducts (NDs) were analyzed by mass spectrometry. A total of 10,246 proteins and 22,284 glycopeptides were identified in all tissue samples, and 756 proteins with more than 1.5-fold increase in abundance in IPMNs relative to NDs were identified, 45% of which were also identified in cyst fluids. The over-expression of selected proteins was validated by immunolabeling. Proteins and glycoproteins overexpressed in IPMNs included those involved in glycan biosynthesis and the immune system. In addition, multiomics clustering identified two subtypes of IPMNs. This study provides a foundation for understanding tumor progression and targets for earlier detection and therapies. SignificanceThis multilevel characterization of intraductal papillary neoplasms of the pancreas provides a foundation for understanding the changes in protein and glycoprotein expression during the progression from normal duct to intraductal papillary neoplasm, and to invasive pancreatic carcinoma, providing a foundation for informed approaches to earlier detection and treatment.

cancer biology↗

bioRxiv2024

Patho-transcriptomic analysis of invasive mucinous adenocarcinoma of the lung (IMA): comparison with lung adenocarcinoma with signet ring cell features (SRCC)

BackgroundInvasive mucinous adenocarcinoma (IMA) comprises [~]5% of lung adenocarcinoma. There is no effective therapy for IMA when surgical resection is not possible. IMA is sometimes confused with adenocarcinoma with signet ring cell features (SRCC) pathologically since both adenocarcinomas feature tumor cells with abundant intracellular mucin. The molecular mechanisms by which such mucin-producing lung adenocarcinomas develop remain unknown. MethodsUsing a Visium spatial transcriptomics approach, we analyzed IMA and compared it with SRCC patho-transcriptomically. Combining spatial transcriptomics data with in vitro studies using RNA-seq and ChIP-seq, we assessed downstream targets of transcription factors HNF4A and SPDEF that are highly expressed in IMA and/or SRCC. ResultsSpatial transcriptomics analysis indicated that there are 6 distinct cell clusters in IMA and SRCC. Notably, two clusters (C1 and C3) of mucinous tumor cells exist in both adenocarcinomas albeit at a different ratio. Importantly, a portion of genes (e.g., NKX2-1, GKN1, HNF4A and FOXA3) are distinctly expressed while some mucous-related genes (e.g., SPDEF and FOXA2) are expressed in both adenocarcinomas. We determined that HNF4A induces MUC3A/B and TM4SF4 and that BI 6015, an HNF4A antagonist, suppressed the growth of IMA cells. Using mutant SPDEF that is associated with COVID-19, we also determined that an intact DNA-binding domain of SPDEF is required for SPDEF-mediated induction of mucin genes (MUC5AC, MUC5B and AGR2). Additionally, we found that XMU-MP-1, a SPDEF inhibitor, suppressed the growth of IMA cells. ConclusionThese results revealed that IMA and SRCC contain heterogenous tumor cell types, some of which are targetable.

cancer biology↗

bioRxiv2023

Therapy-associated remodeling of pancreatic cancer revealed by single-cell spatial transcriptomics and optimal transport analysis

In combination with cell intrinsic properties, interactions in the tumor microenvironment modulate therapeutic response. We leveraged high-plex single-cell spatial transcriptomics to dissect the remodeling of multicellular neighborhoods and cell-cell interactions in human pancreatic cancer associated with specific malignant subtypes and neoadjuvant chemotherapy/radiotherapy. We developed Spatially Constrained Optimal Transport Interaction Analysis (SCOTIA), an optimal transport model with a cost function that includes both spatial distance and ligand-receptor gene expression. Our results uncovered a marked change in ligand-receptor interactions between cancer-associated fibroblasts and malignant cells in response to treatment, which was supported by orthogonal datasets, including an ex vivo tumoroid co-culture system. Overall, this study demonstrates that characterization of the tumor microenvironment using high-plex single-cell spatial transcriptomics allows for identification of molecular interactions that may play a role in the emergence of chemoresistance and establishes a translational spatial biology paradigm that can be broadly applied to other malignancies, diseases, and treatments.

cancer biology↗

bioRxiv2023

Spatial analysis of human lung cancer reveals organized immune hubs enriched for stem-like CD8 T cells and associated with immunotherapy response

The organization of immune cells in human tumors is not well understood. Immunogenic tumors harbor spatially-localized multicellular immunity hubs defined by expression of the T cell-attracting chemokines CXCL10/CXCL11 and abundant T cells. Here, we examined immunity hubs in human pre-immunotherapy lung cancer specimens, and found that they were associated with beneficial responses to PD-1-blockade. Immunity hubs were enriched for many interferon-stimulated genes, T cells in multiple differentiation states, and CXCL9/10/11+ macrophages that preferentially interact with CD8 T cells. Critically, we discovered the stem-immunity hub, a subtype of immunity hub strongly associated with favorable PD-1-blockade outcomes, distinct from mature tertiary lymphoid structures, and enriched for stem-like TCF7+PD-1+ CD8 T cells and activated CCR7+LAMP3+ dendritic cells, as well as chemokines that organize these cells. These results elucidate the spatial organization of the human intratumoral immune response and its relevance to patient immunotherapy outcomes.

immunology↗

bioRxiv2022

Integrative Analysis of Checkpoint Blockade Response in Advanced Non-Small Cell Lung Cancer

Anti-PD-1/PD-L1 agents have transformed the treatment landscape of advanced non-small cell lung cancer (NSCLC). While our understanding of the biology underlying immune checkpoint blockade in NSCLC is still incomplete, studies to date have established predictive roles for PD-L1 tumor expression and tumor mutational burden (TMB). To expand our understanding of the molecular features underlying response to checkpoint inhibitors in NSCLC, we describe here the first joint analysis of the Stand Up 2 Cancer - Mark Foundation (SU2C-MARK) Cohort, a resource of whole exome and/or RNA sequencing from 393 patients with NSCLC treated with anti-PD-(L)1 therapy, along with matched clinical response annotation. We identify a number of associations between molecular features and outcome, including: 1) favorable (e.g., ATM altered), and unfavorable (e.g., TERT amplified) genomic subgroups, 2) distinct immune infiltration signatures associated with wound healing (unfavorable) and immune activation (favorable), and 3) a novel de-differentiated tumor-intrinsic subtype characterized by expression of endodermal lineage genes, immune activation, and enhanced response rate. Taken together, results from this cohort extend our understanding of NSCLC-specific predictors, providing a rich set of molecular and immunologic hypotheses with which to further our understanding of the biology of checkpoint blockade in NSCLC.

genomics↗

bioRxiv2021

Structural and functional analysis of lorlatinib analogs reveals roadmap for targeting diverse compound resistance mutations in ALK-positive lung cancer

The treatment approach to advanced, ALK-positive non-small cell lung cancer (NSCLC) utilizing sequential ALK tyrosine kinase inhibitors (TKIs) represents a paradigm of precision oncology. Lorlatinib is currently the most advanced, potent and selective ALK tyrosine kinase inhibitor (TKI) in the clinic. However, tumors invariably acquire resistance to lorlatinib, and after sequential ALK TKIs culminating with lorlatinib, diverse refractory compound ALK mutations can emerge. Here, we determine the spectrum of lorlatinib-resistant compound ALK mutations identified in patients after treatment with lorlatinib, the majority of which involve ALK G1202R or I1171N/S/T. By assessing a panel of lorlatinib analogs against compound ALK mutant in vitro and in vivo models, we identify structurally diverse lorlatinib analogs that harbor differential selective profiles against G1202R- versus I1171N/S/T-based compound ALK mutations. Structural analysis revealed that increased potency against compound mutations was achieved primarily through two different mechanisms of improved targeting of either G1202R- or I1171N/S/T-mutant kinases. Based on these results, we propose a classification of heterogenous ALK compound mutations designed to focus the development of distinct therapeutic strategies for precision targeting of compound resistance mutations following sequential TKIs.

cancer biology↗

bioRxiv2020

Adaptation of pancreatic cancer cells to nutrient deprivation is reversible and requires glutamine synthetase stabilization by mTORC1

Pancreatic ductal adenocarcinoma (PDA) is a lethal, therapy-resistant cancer that thrives in a highly desmoplastic, nutrient-deprived microenvironment. Several studies investigated the effects of depriving PDA of either glucose or glutamine alone. However, the consequences on PDA growth and metabolism of limiting both preferred nutrients have remained largely unknown. Here, we report the selection for clonal human PDA cells that survive and adapt to limiting levels of both glucose and glutamine. We find that adapted clones exhibit increased growth in vitro and enhanced tumor-forming capacity in vivo. Mechanistically, adapted clones share common transcriptional and metabolic programs, including amino acid use for de novo glutamine and nucleotide synthesis. They also display enhanced mTORC1 activity that prevents the proteasomal degradation of glutamine synthetase (GS), the rate-limiting enzyme for glutamine synthesis. This phenotype is notably reversible, with PDA cells acquiring alterations in open chromatin upon adaptation. Silencing of GS suppresses the enhanced growth of adapted cells and mitigates tumor growth. These findings identify non-genetic adaptations to nutrient deprivation in PDA and highlight GS as a dependency that could be targeted therapeutically in pancreatic cancer patients. SignificancePancreatic ductal adenocarcinoma (PDA) is a highly lethal malignancy with no effective therapies. PDA aggressiveness partly stems from its ability to grow within a uniquely dense stroma restricting nutrient access. This study demonstrates that PDA clones that survive chronic nutrient deprivation acquire reversible non-genetic adaptations allowing them to switch between metabolic states optimal for growth under nutrient-replete or nutrient-deprived conditions. One contributing factor to this adaptation mTORC1 activation, which stabilizes glutamine synthetase (GS) necessary for glutamine generation in nutrient-deprived cancer cells. Our findings imply that although total GS levels may not be a prognostic marker for aggressive disease, GS inhibition is of high therapeutic value, as it targets specific cell clusters adapted to nutrient starvation, thus mitigating tumor growth.

cancer biology↗

bioRxiv2019

Tumor mutational landscape is a record of the pre-malignant state

Chromatin structure has a major influence on the cell-specific density of somatic mutations along the cancer genome. Here, we present a pan-cancer study in which we searched for the putative cancer cell-of-origin of 2,550 whole genomes, representing 32 cancer types by matching their mutational landscape to the regional patterns of chromatin modifications ascertained in 104 normal tissue types. We found that, in almost all cancer types, the cell-of-origin can be predicted solely from their DNA sequences. Our analysis validated the hypothesis that high-grade serous ovarian cancer originates in the fallopian tube and identified distinct origins of breast cancer subtypes. We also demonstrated that the technique is equally capable of identifying the cell-of-origin for a series of 2,044 metastatic samples from 22 of the tumor types available as primaries. Moreover, cancer drivers, whether inherited or acquired, reside in active chromatin regions in the respective cell-of-origin. Taken together, our findings highlight that many somatic mutations accumulate while the chromatin structure of the cell-of-origin is maintained and that this historical record, captured in the DNA, can be used to identify the often elusive cancer cell-of-origin.

genomics↗

bioRxiv2018

Comprehensive analysis of tumour initiation, spatial and temporal progression under multiple lines of treatment

Driver mutations alter cells from normal to cancer through several evolutionary epochs: premalignancy, early malignancy, subclonal diversification, metastasis and resistance to therapy. Later stages of disease can be explored through analyzing multiple samples collected longitudinally, on or between successive treatments, and finally at time of autopsy. It is also possible to study earlier stages of cancer development through probabilistic reconstruction of developmental trajectories based on mutational information preserved in the genome. Here we present a suite of tools, called Phylogic N-Dimensional with Timing (PhylogicNDT), that statistically model phylogenetic and evolutionary trajectories based on mutation and copy-number data representing samples taken at single or multiple time points. PhylogicNDT can be used to infer: (i) the order of clonal driver events (including in pre-cancerous stages); (ii) subclonal populations of cells and their phylogenetic relationships; and (iii) cell population dynamics. We demonstrate the use of PhylogicNDT by applying it to whole-exome and whole-genome data of 498 lung adenocarcinoma samples (434 previously available and 64 of newly generated data). We identify significantly different progression trajectories across subtypes of lung adenocarcinoma (EGFR mutant, KRAS mutant, fusion-driven and EGFR/KRAS wild type cancers). In addition, we study the progression of fusion-driven lung cancer in 21 patients by analyzing samples from multiple timepoints during treatment with 1st and next generation tyrosine kinase inhibitors. We characterize their subclonal diversification, dynamics, selection, and changes in mutational signatures and neoantigen load. This methodology will enable a systematic study of tumour initiation, progression and resistance across cancer types and therapies.

bioinformatics↗