Biology subjects

Carbone, D. P.

Publications and source records attributed to Carbone, D. P..

8 recordsLinked to original sources

bioRxiv2026

Targeting alpha-ketoglutarate starvation within the tumor-immune microenvironment rescues T cell effector function in cancer immunotherapy

Given its status as the leading cause of global cancer mortality, there is a critical need to enhance immunotherapy strategies for lung cancer to overcome widespread resistance to current treatments. Immunotherapy recruits the patient's immune system to attack and destroy cancer cells. While highly effective in a subset of patients, chronic exposure of immune cells to cancer cells leads to a progressive loss of effector T cell function and progression of T cell exhaustion; now considered two well-established hallmarks of immunotherapy resistance. The tumor-immune microenvironment (TIME)-driven differentiation into the exhausted T cell phenotype is marked by a loss of metabolic plasticity and epigenome-wide changes in distribution of repressive histone marks such as histone H3 subunit methylation at lysine 27 (H3K27me3). Here, we studied how these processes are connected to metabolite availability within the TIME. In vitro, chronic antigen stimulation and hypoxia led to rapid loss of effector function, associated with a suppression of alpha-ketoglutarate (aKG) intracellular concentrations in T cells. Supplementation of cell-permeable aKG led to a rescue of effector cytokine production and to improved cytotoxic capacity despite chronic antigen stimulation and hypoxia. Increased intracellular aKG levels restored the activity of H3K27 demethylases UTX and JMJD3, consistent with epigenome-wide decreased H3K27me3. In vivo, dietary supplementation with commercially available calcium-aKG (Ca-aKG) supplements led to an elevation of serum and intratumoral aKG levels associated with a significant increase of immunotherapy effectiveness in mouse models of NSCLC. Clinical samples from patients with NSCLC contained significantly decreased serum aKG levels in older NSCLC patients (>65 years of age). Analysis identified a novel association between serum aKG levels and poor immunotherapy response. Thus, our work demonstrates that intratumoral metabolite starvation can be therapeutically exploited to improve immunotherapy outcomes in non-small cell lung cancer (NSCLC).

cancer biology↗

bioRxiv2025

Deep-learning-enabled multi-omics analyses for prediction of future metastasis in cancer

Metastasis remains the leading cause of cancer-related mortality, yet predicting future metastasis is a major clinical challenge due to the lack of validated biomarkers and effective assessment methods. Here, we present EmitGCL, a deep-learning framework that accurately predicts future metastasis and its corresponding biomarkers. Based on a comprehensive benchmarking comparison, EmitGCL outperformed other computational tools across six cancer types from seven cohorts of patients with superior sensitivity and specificity. It captured occult metastatic cells in a patient with a lymph node-negative breast cancer, who was declared to have no evidence of disease by conventional imaging methods but was later confirmed to have a metastatic disease. Notably, EmitGCL identified HSP90AA1 and HSP90AB1 as predictable biomarkers for future breast cancer metastasis, which was validated across five independent cohorts of patients (n=420). Furthermore, we demonstrated YY1 transcription factor as a key driver of breast cancer metastasis which was validated through in-silico and CRISPR-based migration assays, suggesting that YY1 is a potential therapeutic target for deterring metastasis.

bioinformatics↗

bioRxiv2024

An in vivo 'turning model' reveals new RanBP9 interactions in lung macrophages.

The biological functions of the scaffold protein Ran Binding Protein 9 (RanBP9) remain elusive in macrophages or any other cell type where this protein is expressed together with its CTLH (C-terminal to LisH) complex partners. We have engineered a new mouse model, named RanBP9-TurnX, where RanBP9 fused to three copies of the HA tag (RanBP9-3xHA) can be turned into RanBP9-V5 tagged upon Cre-mediated recombination. We created this model to enable stringent biochemical studies at cell type specific level throughout the entire organism. Here, we have used this tool crossed with LysM-Cre transgenic mice to identify RanBP9 interactions in lung macrophages. We show that RanBP9-V5 and RanBP9-3xHA can be both co-immunoprecipitated with the known members of the CTLH complex from the same whole lung lysates. However, more than ninety percent of the proteins pulled down by RanBP9-V5 differ from those pulled-down by RanBP9-HA. The lung RanBP9-V5 associated proteome includes previously unknown interactions with macrophage-specific proteins as well as with players of the innate immune response, DNA damage response, metabolism, and mitochondrial function. This work provides the first lung specific RanBP9-associated interactome in physiological conditions and reveals that RanBP9 and the CTLH complex could be key regulators of macrophage bioenergetics and immune functions.

cell biology↗

bioRxiv2022

A Community Challenge to Predict Clinical Outcomes After Immune Checkpoint Blockade in Non-Small Cell Lung Cancer

PurposePredictive biomarkers of immune checkpoint inhibitors (ICIs) efficacy are currently lacking for non-small cell lung cancer (NSCLC). Here, we describe the results from the Anti-PD-1 Response Prediction DREAM Challenge, a crowdsourced initiative that enabled the assessment of predictive models by using data from two randomized controlled clinical trials (RCTs) of ICIs in first-line metastatic NSCLC. MethodsParticipants developed and trained models using public resources. These were evaluated with data from the CheckMate 026 trial (NCT02041533), according to the model-to-data paradigm to maintain patient confidentiality. The generalizability of the models with the best predictive performance was assessed using data from the CheckMate 227 trial (NCT02477826). Both trials were phase III RCTs with a chemotherapy control arm, which supported the differentiation between predictive and prognostic models. Isolated model containers were evaluated using a bespoke strategy that considered the challenges of handling transcriptome data from clinical trials. ResultsA total of 59 teams participated, with 417 models submitted. Multiple predictive models, as opposed to a prognostic model, were generated for predicting overall survival, progression-free survival, and progressive disease status with ICIs. Variables within the models submitted by participants included tumor mutational burden (TMB), programmed death ligand 1 (PD-L1) expression, and gene-expression-based signatures. The bestperforming models showed improved predictive power over reference variables, including TMB or PD-L1. ConclusionThis DREAM Challenge is the first successful attempt to use protected phase III clinical data for a crowdsourced effort towards generating predictive models for ICIs clinical outcomes and could serve as a blueprint for similar efforts in other tumor types and disease states, setting a benchmark for future studies aiming to identify biomarkers predictive of ICIs efficacy. Context summaryO_ST_ABSKey objectiveC_ST_ABSNot all patients with non-small cell lung cancer (NSCLC) eligible for immune checkpoint inhibitor (ICIs) respond to treatment, but accurate predictive biomarkers of ICIs clinical outcomes are currently lacking. This crowdsourced initiative enabled the robust assessment of predictive models using data from two randomized clinical trials of first-line ICI in metastatic NSCLC. Knowledge generatedModels submitted indicate that a combination of programmed death ligand 1 (PD-L1), tumor mutational burden (TMB), and immune gene signatures might be able to identify patients more likely to respond to ICIs. TMB and PD-L1 seemed important to predict progression-free survival and overall survival. Mechanisms including apoptosis, T-cell crosstalk, and adaptive immune resistance appeared essential to predict response. Relevance

cancer biology↗

bioRxiv2022

Exogenous sequences in tumors and immune cells (exotic): a tool for estimating the microbe abundances in tumor RNAseq data

The microbiome affects cancer, from carcinogenesis to response to treatments. New evidence suggests that microbes are also present in many tumors, though the scope of how they affect tumor biology and clinical outcomes is unclear. A broad survey of tumor microbiome samples across several independent datasets is needed to identify robust correlations for follow-up testing. We created a tool to carefully identify the tumor microbiome within RNAseq datasets and then applied it to samples collected through the Oncology Research Information Exchange Network (ORIEN) and The Cancer Genome Atlas (TCGA). We showed how the processing removes contaminants and batch effects to yield microbe abundances consistent with non-high-throughput sequencing-based approaches. We sought to establish clinical relevance by correlating the microbe abundances with various clinical and tumor measurements, such as age and tumor hypoxia. This process leveraged the two datasets and raised up only the concordant (significant and in the same direction) associations. We identify associations with survival and clinical variables that are highly cancer-specific and relatively few associations with immune composition. Finally, we explore potential mechanisms by which microbes and tumors may interact using a network approach. Alistipes, a common gut commensal, showed the highest network degree centrality and was associated with genes related to metabolism and inflammation. The exotic tool can support the discovery of microbes in tumors in a way that leverages the many existing and growing RNAseq datasets. Statement of SignificanceThe intrinsic tumor microbiome holds great potential for its ability to predict various aspects of cancer biology and as a target for rational manipulation. Here, we describe a tool to quantify microbes from within tumor RNAseq and apply it to two independent datasets. We show new associations with clinical variables that justify biomarker uses and more experimentation into the mechanisms by which tumor microbiomes affect cancer outcomes.

cancer biology↗

bioRxiv2021

An Immunogold Single Extracellular Vesicular RNA and Protein (AuSERP) Biochip to Predict Responses to Immunotherapy in Non-Small Cell Lung Cancer Patients

Conventional PD-L1 immunohistochemical tissue biopsies only predict 20~40% of non-small cell lung cancer (NSCLC) patients that will respond positively to anti-PD-1/PD-L1 immunotherapy. Herein, we present an immunogold biochip to quantify single extracellular vesicular RNA and protein (AuSERP) as a non-invasive alternative. With only 3 L of serum, PD-1/PD-L1 proteins on the surface of extracellular vesicles (EVs) and EV PD-1/PD-L1 messenger RNA (mRNA) cargo were detected at a single-vesicle resolution and exceeded the sensitivities of ELISA and qRT-PCR by 1000 times. By testing a cohort of 27 non-responding and 27 responding NSCLC patients, AuSERP indicated that the single-EV mRNA biomarkers surpass the single-EV protein biomarkers at predicting patient responses to immunotherapy. Dual single-EV PD-1/PD-L1 mRNA detection differentiated responders from non-responders with an accuracy of 72.2% and achieved an NSCLC diagnosis accuracy of 93.2%, suggesting the potential for AuSERP to provide enhanced immunotherapy predictions and cancer diagnoses within the clinical setting.

immunology↗

bioRxiv2020

IWS1 phosphorylation promotes cell proliferation and predicts poor prognosis in EGFR mutant lung adenocarcinoma patients, through the cell cycle-regulated U2AF2 RNA splicing.

The authors have withdrawn their manuscript. While attempting to reproduce the data on the alternative splicing of exon 2 of U2AF2, they observed that the proposed splicing mechanism could not give rise to a functional U2AF2 protein. In addition, they observed evidence of manipulation in the electropherogram of the splicing junction between exons 1 and 3 and in the primary data on which this electropherogram was based, which were deposited in Mendeley by the first author. These observations raise questions on the integrity of the reported results. In light of this information, the authors have no confidence in the key findings of the paper, and therefore, do not wish it to be cited. If you have any questions, please contact the corresponding author.

cancer biology↗

bioRxiv2019

Identification of frequent activating HER2 mutations in primary canine pulmonary adenocarcinoma

Naturally occurring primary canine lung cancers are aggressive malignancies that are increasingly common in pet dogs. They share clinicopathologic features with human lung cancers in never-smokers, but their genetic underpinnings are unknown. Through multi-platform sequencing of 88 primary canine lung tumors or cell lines, we discovered somatic, coding HER2 (ERRB2) point mutations in 38% of canine pulmonary adenocarcinomas (cPAC, 28/74), but none in adenosquamous (cPASC, 0/11) or squamous cell (cPSCC, 0/3) carcinomas. In cPASC, PTEN was the most frequently mutated gene (18%) while one case each bore likely pathogenic HRAS, KRAS, EGFR, MET, TP53, or VHL somatic mutations. In cPSCC, no recurrently mutated genes were identified, but individual somatic coding mutations were found in BRAF and PTPN11. In cPAC, we also identified recurrent somatic mutation of TP53 (13.5%), SMAD4 (5.4%), PTEN (4.1%), and VHL (2.7%). cPACs assessed by exome sequencing displayed a low somatic mutation burden (median 64 point mutations, 19 focal copy number variants, and 1 translocation). The majority (93%) of HER2 mutations were hotspot V659E transmembrane domain (TMD) mutations comparable to activating mutations at this same site in human cancer. Other HER2 mutations identified in this study were located in the extracellular domain and TMD. HER2V659E was detected in the plasma of 33% (2/6) of dogs with localized HER2V659E tumors. HER2V659E correlated with constitutive phosphorylation of AKT in cPAC cell lines and HER2V659E lines displayed hypersensitivity to the HER2 inhibitors lapatinib and neratinib relative to HER2-wild-type cell lines. These findings have translational and comparative relevance for lung cancer and HER2 inhibition.

cancer biology↗