Cancer Research Communications

BackgroundThe ketogenic diet is being explored as an adjuvant intervention in breast cancer because it lowers circulating glucose and elevates ketone bodies such as {beta}-hydroxybutyrate (BHB), but how individual ER+ breast cancer subtypes adapt to these conditions remains poorly characterized. We examined metabolic responses to BHB supplementation under glucose restriction in two ER+ breast cancer cell lines, asking whether metabolic adaptation patterns differ between models. MethodsMCF-7 and T47D cells were cultured under high glucose, glucose-restricted (5% of standard), or glucose-restricted with 10 mM BHB conditions and profiled by comprehensive two-dimensional gas chromatography-mass spectrometry (GCxGC-MS). Pairwise Welchs t-tests with Benjamini-Hochberg false discovery rate (FDR) correction were applied to identify treatment-responsive metabolites. Targeted assays quantified intracellular glycine, SHMT1 protein, and total branched-chain amino acid (BCAA) concentrations across a BHB dose range (2.5-15 mM). Patient tumor transcriptomic data from TCGA (n=1,084) and paired tumor-normal samples from GSE58135 (n=20) were analyzed for genes involved in one-carbon, ketone body, and BCAA metabolism. ResultsMCF-7 and T47D cells exhibited markedly divergent metabolic responses to BHB. In MCF-7 cells, BHB supplementation produced a broad pattern-level metabolic shift: 75% of detected metabolites trended upward when BHB was added to glucose-restricted cultures (C vs. B comparison), with 1,4-butanediol reaching nominal significance (FC=2.35, p=0.016) and a 4.1-fold trend increase in lactic acid (p=0.11), although no individual metabolite survived FDR correction. T47D cells showed essentially no metabolic response to BHB at the global level. Targeted assays detected an elevation in glycine at 5 mM BHB in both cell lines that did not follow a monotonic dose response and was not accompanied by changes in SHMT1 protein expression. Total BCAA levels were elevated by BHB in T47D cells but remained unchanged in MCF-7 cells. In paired patient samples, OXCT1 (log2FC = -1.41), SHMT1 (log2FC = -1.31), and ACAT1 (log2FC = -1.07) were significantly downregulated in ER+ tumors relative to matched normal tissue (adjusted p < 0.001 for all three). ConclusionsER+ breast cancer cell lines show heterogeneous metabolic responses to BHB supplementation under glucose restriction. The broad pattern of metabolite elevation in MCF-7 but not T47D cells suggests that capacity to utilize ketone bodies as metabolic substrate varies between ER+ models. The downregulation of OXCT1, ACAT1, and SHMT1 in ER+ tumors compared to normal tissue identifies these enzymes as candidate biomarkers that may help stratify which patients are likely to benefit from ketogenic interventions. Findings related to individual metabolites should be regarded as exploratory and require validation in larger, adequately powered cohorts.

BackgroundOpportunistic nutrient uptake is a hallmark of cancer metabolism. Cancer cells upregulate macropinocytosis to acquire extracellular nutrients to support growth and stress adaptation. We previously showed that extracellular ATP (eATP) is internalized by macropinocytosis and promotes multiple cancer phenotypes. Here, we tested whether eATP uptake is prevalent across cancers and whether eATP also induces senescence through purinergic receptor (PR) signaling. MethodsIntracellular ATP (iATP) levels were measured following eATP exposure across multiple cancer cell lines. eATP internalization was visualized in vitro and in vivo using a non-hydrolyzable fluorescent ATP analog together with high-molecular-weight dextran as a macropinocytosis marker. Senescence was quantified using three SA-{beta}-galactosidase assays and flow cytometry. Pharmacologic inhibitors of macropinocytosis and purinergic receptors were used to define pathway dependence. Combination treatments with the glucose transporter inhibitor DRB18 and the senolytic navitoclax were evaluated for antiproliferative effects. ResultseATP produced dose- and time-dependent increases in iATP across diverse cancer cell types. Imaging demonstrated widespread macropinocytic internalization of ATP in vitro and in tumor xenografts. eATP induced senescence in NSCLC cells, confirmed by multiple {beta}-gal assays and flow cytometry. PR inhibition significantly reduced senescence, whereas macropinocytosis inhibition had minimal effect on senescence induction. ConclusionseATP acts through dual pathways in cancer cells: macropinocytic internalization that elevates iATP and PR signaling that drives senescence. Targeting metabolic uptake together with senolytic therapy may offer a novel anticancer strategy.

BackgroundImmune checkpoint inhibitors (ICIs) have improved outcomes across multiple cancer types, yet reliable predictors of survival remain limited. While genomic features such as tumor mutational burden (TMB) are widely used, their contribution to predictive modeling in heterogeneous real-world cohorts remains unclear. We evaluated the relative contributions of clinical and whole-genome sequencing (WGS) features in pan-cancer survival modeling. MethodsWe analyzed 658 patients treated with ICIs with matched WGS data from the Genomics England. Using a leakage-controlled machine learning framework with strict train-test separation, we compared four models: TMB-only, clinical-only, clinical+TMB, and an integrated 11-feature clinico-genomic XGBoost survival model. Model performance was assessed using Harrells concordance index (C-index) with bootstrap confidence intervals. ResultsTMB alone demonstrated near-random discrimination (C-index 0.50; 95% CI 0.44-0.56). Clinical variables substantially improved predictive performance (0.59; 95% CI 0.53-0.64), with marginal gain from adding TMB (0.59). The integrated model achieved a C-index of 0.60 (95% CI 0.55-0.65). While improvement over TMB alone was significant, incremental gain beyond optimized clinical models was modest. Feature attribution analysis showed that model performance was dominated by clinical variables, with genomic features contributing limited additional signal. ConclusionsThese findings suggest that, in heterogeneous pan-cancer cohorts, predictive performance is constrained by the underlying data structure, in which dominant clinical signals overshadow genome-scale features. This study highlights fundamental limitations in integrating genomic data into survival models across diverse cancer types and provides a benchmark for future computational approaches.

PurposePancreatic ductal adenocarcinoma (PDAC) is characterized by a nutrient-deprived and hypoxic tumor microenvironment (TME) that imposes severe metabolic stress on cancer cells. Under these conditions, tumor cells frequently activate the integrated stress response (ISR) to adapt to TME and develop resistance to therapies. However, how TME components support tumor adaptation to mitochondrial metabolic stress remains incompletely understood. Here, we aimed to identify key metabolite involved in ISR adaptation under oxidative phosphorylation (OXPHOS) inhibition and to elucidate the metabolic symbiosis between cancer-associated fibroblasts (CAFs) and PDAC cells. MethodsWe integrated transcriptomic and metabolomic analyses with functional assays. ISR activation was evaluated by assessing the phosphorylation of eIF2 (p-eIF2) following treatment with carboxyamidotriazole orotate (CTO), an Complex I inhibitor. Metabolomic profiling was used to identify metabolites involved in ISR activation alleviation. Mouse models were used to assess therapeutic responses following depletion of the identified metabolite under CTO treatment. Genetic perturbation of Slc38a4 was performed to assess its functional role in tumor cell adaptation to metabolic stress. ResultsWe identified asparagine (ASN) as a critical metabolite supplied by CAFs to PDAC cells under OXPHOS inhibition. A minimum level of ASN is required for PDAC cells to execute ISR downstream adaptation. ASN depletion significantly enhanced the anti-tumor efficacy of OXPHOS inhibition both in vitro and in vivo. SLC38A4 emerged as a potential mediator of this interaction. SLC38A4 expression was associated with c-Myc, and its loss increased the sensitivity of PDAC cells to CTO-induced metabolic stress. ConclusionOur findings reveal a CAF-tumor metabolic crosstalk in which stromal-derived ASN supports PDAC cell adaptation to mitochondrial metabolic stress. Adaptive outcome of ISR signaling depends on the availability of key metabolic substrates such as ASN. When extracellular ASN supply is limited, the ATF4-dependent adaptive program collapses, converting ISR from a pro-survival response into a therapeutic vulnerability. SLC38A4 may function as a key mediator of this metabolic coupling and represents a potential target for enhancing the efficacy of OXPHOS inhibition in PDAC.

BackgroundHomozygous deletion of the methylthioadenosine phosphorylase (MTAP) gene is a frequent genetic alteration in cancer. MTAP, which creates adenine from 5-methylthioadenosine (MTA), is constitutively expressed in all tissues throughout the body. Previously, we described a novel strategy to specifically target MTAP-deleted cancer cells by combining the antipurine prodrug 2-fluoroadenine (2FA) with MTA. In vitro, this combination efficiently killed MTAP- cancer cells, but in vivo the combination was much less effective in vivo. Here, we explored the role of xanthine oxidase (XO) in this process. Materials and MethodsVarious combinations of 2FA, MTA, and the xanthine oxidase inhibitor febuxostat (FX) were tested in various cancer cell lines grown in vitro and in mice. LC-MS/MS was used to examine the levels and ratio of intracellular 2-FA-containing nucleotides compared to adenine-containing nucleotides. Results and conclusionsThe treatment of cells with 2FA+MTA in vitro resulted in much higher 2FANP/ANP ratios than the same treatment in vivo. The addition of XO to culture media in vitro effectively abolished the killing by 2FA, and this effect was fully reversed by the addition of febuxostat (FX), a xanthine oxidase inhibitor. In vivo, the addition of FX to 2FA results in increased cell killing and toxicity and a 1000% increase in the amount of 2FA converted to 2-FA-monophosphate (2FAMP). Xenograft studies using MTAP- HT1080 and MiaPaCa-2 cell lines have shown that a 2FA/MTA/FX cocktail can cause tumor regression in vivo. These studies suggest that the combination of 2FA/MTA/FX should be explored as a treatment for MTAP- cancer.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy where metabolic homeostasis is maintained by tumor and stromal cells within the tumor microenvironment (TME). To better assess pathways supporting macromolecule biosynthesis in PDAC tumors, we apply 13C metabolic flux analysis (MFA) to slice cultures of treatment-naive human tumors and mouse models that retain the native TME. Glycans, lipid headgroups, and very long-chain fatty acids are the most dynamic metabolic pools, while long chain fatty acids, purines, and pyrimidines are predominantly salvaged locally in situ. We use targeted pharmacological modulators to highlight the importance of recycling pathways and metabolic redundancies which mitigate changes in lipid abundances. Finally, we leverage targeted lipid fluxomics and the distinct ganglioside and globoside profiles of tumor and stromal cells, respectively, to demonstrate the role of the lipid kinase PIKfyve in supporting ganglioside homeostasis via sialic acid and ceramide salvage. These data establish application of MFA to slice cultures of PDAC tumors as an effective approach for assessing metabolic mechanisms and therapeutic responses within an intact TME.

Nutrient availability is a critical environmental factor that influences the metabolism and adaptability of cancer cells, including acute lymphoblastic leukaemia (ALL) cells, prone to relapse in the central nervous system (CNS). Currently available cell culture media contain supraphysiological nutrient levels and do not represent the restricted metabolic environment of CNS-ALL which resides in the leptomeninges surrounded by cerebrospinal fluid (CSF). Therefore, we formulated a novel physiological CSF-like cell culture medium (CSFmax) that recapitulates the unique metabolite composition of the CSF. Through in vitro and in vivo metabolic and functional studies, we demonstrate that ALL cells cultured in CSFmax rewire their metabolism, closely mimicking the metabolic phenotype of CNS-ALL, including their metabolic activity and redox state. Utilising CSFmax, in comparison to conventional nutrient-rich culture media, we identified an essential role for autophagy in ALL adaptation to the CNS niche. This was evident by increased autophagic activity and selective sensitisation of ALL cells to pharmacological inhibition of autophagy and genetic knockout of Unc-51 Like Autophagy Activating Kinase 1 (ULK1) or autophagy related 7 (ATG7). Importantly, using a robust preclinical in vivo model, mice xenografted with ULK1 and ATG7 deficient ALL cells exhibited reduced CNS disease burden when compared to mice xenografted with control cells. Overall, our findings provide strong evidence that physiological CSFmax is superior to current in vitro culture systems in recapitulating the metabolic signature of CNS resident ALL cells. By exploiting this system, we revealed for the first time autophagy as a targetable therapeutic vulnerability in CNS-ALL. Key PointsO_LICulturing ALL cells in bespoke CSF-like medium (CSFmax) recapitulates the metabolic adaptation of ALL cells in the CNS niche C_LIO_LIAutophagy is critical for metabolic adaptation and survival of CNS resident ALL cells C_LI

Treatment of advanced head and neck squamous cell carcinoma (HNSCC) often involves radiotherapy combined with chemotherapy, targeted therapy, or immunotherapy. However, due to its anatomical and molecular heterogeneity, identifying the most effective treatment for each patient remains a major clinical challenge. To address this need, we developed a high-throughput organoid-based drug screening platform that uses patient-derived organoids to assess candidate treatment regimens. We validated the platform by establishing bioprinted 3D organoids of human HNSCC cell lines and exposing them to X-ray radiation in combination with various small-molecule drugs and biologics. We quantified viability using ATP release assays and assessed extracellular matrix (ECM) invasion with a machine learning-based brightfield image analysis pipeline. Proof-of-concept experiments with HPV-negative HNSCC lines (HN30 and HN31, established from primary and metastatic disease from the same patient) and HPV-positive HNSCC cells (SCC154) revealed different therapy agents that can radiosensitize each cell line. Image analysis showed that copanlisib, afatinib, and ibrutinib could limit ECM invasion of HN31, while the AKT inhibitor ipatasertib promotes invasion of HN30 cells, consistent with previous studies. Application of the platform to patient-derived HPV+ oropharyngeal tumor organoids showed that they shared sensitivity to several agents while also exhibiting differences against certain therapies. Cetuximab, sorafenib, and nedisertib significantly radiosensitized organoids from two clinical samples. This work demonstrates the feasibility of performing sensitivity screening by integrating bioprinting, conventional viability assays, and advanced image analysis techniques. This platform has the potential to enable a personalized therapeutic pipeline for patients with advanced HNSCC, optimizing responses to radiotherapy and targeted agents to improve clinical outcomes while avoiding modulators that may promote tumor invasion.

BackgroundPrimary and secondary resistance to immune checkpoint blockade (ICB) remains a critical challenge in advanced melanoma. Oncolytic Viruses (OV) selectively lyse tumor cells while generating systemic anti-tumor immune responses with minimal side effects. Yet their clinical use is limited to refractory melanoma patients and are only given in combination with second-line ICB regimens. ICB can both help and hinder OV efficacy depending on the source of checkpoint interactions across the tumor-immune microenvironment (TiME). However, functional checkpoint interactions are typically inferred from gene or protein expression and rarely contextualized within myeloid- and antigen presenting cell-associated immune niches during OV therapy, despite these populations dominating melanoma TiMEs and serving as key regulators of anti-viral immunity. MethodsAn integrated multi-omics framework combining Nanostring GeoMx digital spatial profiling (DSP), COMET sequential immunofluorescence (seqIF) and functional oncology mapping (FuncOmap) was applied to melanoma patient tissues collected pre- and post-neoadjuvant Talimogene Laherparepvec (T-VEC) to characterize immune remodeling and directly quantify checkpoint interaction dynamics associated with pathologic responses to OV therapy. ResultsT-VEC induced broad lymphocyte- and myeloid-associated immune transcriptional activation across melanoma TiMEs; however, pathologic responses could not be defined by bulk transcriptomics or cellular deconvolution alone. COMET seqIF analysis identified that HSV-associated M1/APC-like tumor-associated macrophages (TAMs) were enriched in complete pathologic response (CR) tissues and were a major source of PD-1/PD-L1 interaction niches. While partial (PR) and non-pathologic response (NR) tissues retained melanoma-centered PD-1/PD-L1 interaction niches and were enriched for B cell and M2-like TAM populations. FuncOmap analysis indicated that post-T-VEC PD-1/PD-L1 interaction states were consistently elevated in tumor bed, but not in lymph node tissues, across all pathologic response groups. Suggesting that immune checkpoint interactions may benefit T-VEC therapeutic responses depending on their spatial and immune context relative to OV infection. ConclusionsThese findings highlight the importance of integrated transcriptomic and functional proteomic analyses for resolving the spatial distribution and functional status of immune niches during OV therapy. Resolving PD-1/PD-L1 interaction states to specific M1/APC-like TAM and B cell niches may define mechanisms of responses and resistance to OV therapy.

Mantle cell lymphoma (MCL) is one of the deadliest forms of Non-Hodgkins B-cell lymphoma. Typically, patients present with both overexpression of CyclinD1 and secondary mutations identified by genomic sequencing. Although MCL patients may initially respond to treatment, they eventually relapse and succumb to disease, highlighting the essential need to identify new targets for treatment. Here we performed proteomic profiling of healthy B cells and three different forms of B-cell malignancies, including MCL, to define the proteomic signature of MCL. We compared the proteome of each to MCL and identified 10 proteins that are specifically upregulated in MCL. Of these 10 proteins, seven of them show no transcriptional changes and have been overlooked by conventional RNA expression analysis. Further analysis of the proteomic signature reveals potential avenues for dual targeting in CAR T-cell therapy and provides guidance for personalized therapeutics based on protein expression. STATEMENT OF SIGNIFICANCEWe present a resource defining the protein landscape of MCL, CLL, and FL as compared to healthy b cells identified utilizing quantitative proteomics from primary patient samples. Applied to MCL, our results identify 10 proteins specifically upregulated in MCL that may prove to be therapeutic targets to treat the disease.

BackgroundLong non-coding RNAs (lncRNAs) have emerged as key regulators of tumor biology, however, thus far none have translated to cancer therapies. The lncRNA MALAT1 is overexpressed in more than 20 cancers, including breast cancer and has been shown to function via various mechanisms in a context-dependent manner, in 2D cell lines and mouse models. However, its functional role and therapeutic potential have not been evaluated in clinically relevant patient-derived models. MethodsWe investigated the therapeutic potential of a MALAT1-targeting antisense oligonucleotide (ASO) for breast cancer, using clinically relevant 3D human patient-derived organoids (PDOs) and PDO-xenograft (PDO-X) models. We systematically evaluated the efficiency of MALAT1-targeting ASOs using a biobank of 28 PDO models. Using three independent PDO-X models of triple negative breast cancer (TNBC), we targeted MALAT1 in vivo to study its impact on transcription, alternative splicing, stromal remodeling and metastasis. ResultsAcross PDO-X models, MALAT1 depletion reproducibly drove widespread alternative splicing changes across all event types, particularly intron retention events, accompanied by modest gene expression alterations. Differentially spliced transcripts were enriched for targets of shared cancer-associated transcription factors, and MALAT1 knockdown altered the relative abundance of previously unannotated splicing isoforms. Beyond tumor-intrinsic effects, tumor-specific MALAT1 depletion induced a consistent reduction in macrophage-associated gene signatures and reduced lung metastatic burden. ConclusionsOur data define MALAT1s multifaceted role in TNBC, coordinating alternative splicing, transcriptional fine-tuning, tumor-stroma crosstalk, and metastatic progression. Our study provides strong preclinical evidence supporting MALAT1-targeted ASO therapy and establishes PDO-X models as a clinically relevant platform for functional interrogation of TNBC therapies.

Network biology traditionally identifies gene correlations that reflect biological pathways. While LIONESS enables individualized gene networks, the influence of replication timing on these correlations remains unexplored. Replication timing reflects the temporal order of DNA synthesis and is tightly linked to chromatin state, methylation, and transcriptional stability, all of which affect tumor behavior. Integrating replication-timing proxies derived from methylation data therefore offers a bridge between epigenetic state and functional gene coordination, while morphology provides an additional route for inferring gene expression. This is the first study to integrate replication-timing proxies and morphological embeddings into individualized LIONESS gene networks. The aim is to determine how replication timing and morphology derived from bulk methylation and image embeddings influence gene coexpression in pancreatic cancer. Patient-specific networks were generated for basal and classical pancreatic ductal adenocarcinoma subtypes using TCGA data. Results show an 80% AUC for RNA-replication-timing-based subtype prediction modules and a 75% AUC for morphology-based networks. Incorporating replication timing and morphology increased network robustness while maintaining classification performance. Notably, the 80% AUC was achieved using only 17 of the 50 Moffitt genes, with 16 overlapping the PURIST gene set, indicating that replication timing captures clinically relevant regulatory structure. These findings suggest that replication-timing proxies can act as epigenetic indicators of mechanistic gene coordination and may help identify patients with distinct replication stress or chromatin accessibility profiles relevant to therapeutic response.

Circulating tumor cells (CTCs), particularly multicellular clusters, are associated with poor prognosis and may provide insight into mechanisms of metastasis and therapy resistance. Unbiased approaches for functionally characterizing CTCs in liquid biopsies are therefore urgently needed. Here, we evaluate multiplex imaging mass cytometry (IMC) for CTC analysis in mice bearing human xenograft tumors. In a single-step workflow, IMC uses metal-conjugated antibodies to simultaneously detect numerous proteins and post-translational modifications in minimally processed, small-volume blood samples collected from the tail vein or heart. Using breast cancer cell lines and a patient-derived xenograft (PDX), we assessed a panel of antibodies, including human-specific markers such as Lamin B1 (LMNB1), to enable cross-species interpretation. Combined with manual review, HALO AI-based cell segmentation was used to identify CTCs and quantify marker expression. This approach enables studies of how genetic and pharmacologic interventions alter the properties of single CTCs and CTC clusters in tumor-bearing mice.

BackgroundDrug responses in pancreatic ductal adenocarcinoma (PDAC) vary sharply across in vitro culture formats, but most 2D-3D comparisons conflate microenvironmental cues with time-dependent cellular adaptation. As a result, conventional assays frequently overestimate drug efficacy and poorly reflect clinical pharmacology. Main findingsWe profiled MiaPaCa-2, PANC-1, and CFPAC-1 grown in an extracellular-matrix (ECM) hydrogel for 1-12 days, defining extended 3D cultures ([&ge;]10 days) as mature tumoroids, and quantified 72 h drug responses to a multi-class oncology panel using growth-rate (GR) metrics to normalize for proliferation across formats and durations. Prolonged 3D pre-culture induced broad tolerance, with typical 10-100x reductions in sensitivity to standards of care (5-fluorouracil, SN38, oxaliplatin, gemcitabine, paclitaxel), following a reproducible susceptibility hierarchy (MiaPaCa-2 > PANC-1 > CFPAC-1) after GR correction. In mature tumoroids, GR values closely approximated clinically observed plasma exposures (e.g., within <4x for 5-FU and <0.5x for gemcitabine), whereas 2D and short-term organoid assays markedly underestimated resistance, often by >100x, thereby overstating drug activity. Notably, CFPAC-1 exhibited increased sensitivity to SN38 and trametinib under mature-organoid conditions, demonstrating that microenvironmental conditioning can invert responses for selected mechanisms. Transcriptomic profiling revealed coordinated up-regulation of multiple ABC transporters with extended 3D residence, tracking resistance phenotypes across lines and implicating transporter-linked tolerance programs. SignificanceTogether, these data identify time-in-3D and the emergence of mature tumoroids as dominant, previously under-controlled determinants of PDAC pharmacology that both induce tolerance and unmask context-dependent vulnerabilities. We propose incorporating both short-term and mature-tumoroid screening arms into preclinical workflows, reporting pre-culture duration alongside GR-normalized effect sizes, and leveraging transporter-informed biomarkers to guide regimen prioritization and sequencing. This framework enhances physiological relevance, reproducibility, and translational fidelity in PDAC drug discovery.

The current "gold standard" for diagnosing and assessing treatment response is tumor biopsy; however, biopsies are not always feasible, safe or easily repeated during treatment. Utilization of peripheral blood mononuclear cells (PBMCs) as a surrogate for tumor biopsy allows for longitudinal sampling and is a safer, more readily available option. However, collection conditions, sample transfer time across multiple clinical sites, and PBMC processing conditions are external pre-analytical factors that must be understood and controlled to mitigate bias in downstream functional analyses. This study aims to systematically evaluate the pre-analytical variables affecting PBMC integrity and functional immune readouts as a prerequisite for downstream translational biomarker applications. Peripheral blood samples were collected from 80 treatment-naive patients with a diagnosis of head and neck squamous cell carcinoma. Blood was collected in cell preparation tubes (BD Vacutainer(R) CPT), potassium ethylenediaminetetraacetic acid (EDTA), or sodium heparin (SH) tubes and diluted 1:1 with sterile PBS or remained undiluted. PBMCs were processed and cryopreserved immediately or held for 8- and 24-hours before processing. PBMC viability was measured at cryopreservation and upon thawing. CD8+ T cells or natural killer (NK) cells derived from PBMCs were subjected to cytotoxicity assays using flow cytometry. CPT tubes provided lower cell viability and yield at cryopreservation and upon thaw compared to EDTA and SH tubes while dilution had no effect on viability. NK cell cytotoxicity was similar between EDTA and SH tubes irrespective of dilution. However, diluted EDTA tubes resulted in lower T cell cytotoxicity after 24-hour hold. Viability and NK and T cell cytotoxicity were equivalent between cryopreserved PBMCs that were processed immediately or processed after 8- or 24-hour hold. Here we report cryopreservation methods for reproducibility of viable cells that maintain functional immunological capacity even after significant delay in processing allowing flexibility and feasibility for collection from multiple clinical sites for deferred processing.

While distinct environmental exposures imprint unique mutational signatures on cancer genomes, the specific causal patterns for many known carcinogens remain uncharacterized in relevant human tissues. To address this gap, we developed a novel, physiologically relevant system that uses a combination of airway epithelial cells and whole genome sequencing to characterize mutational patterns induced by genotoxic carcinogens associated with lung cancer. After validating the platforms accuracy by successfully recapturing the known signature for Benzo(a)pyrene (BaP), we used this system to gain detailed insights into the types of mutations that occur with exposure to N-nitrosotris-(2-chloroethyl) urea (NTCU) and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK), genotoxic compounds that induce lung squamous cell carcinoma and lung adenocarcinoma in mouse models, respectively. Cells exposed to NTCU had significantly more somatic SNVs compared to control samples. An average of 82.3% of mutations in NTCU samples were attributed to a novel mutational signature distinct from those in the COSMIC database but highly correlated with recent in vivo mouse models. In contrast, NNK exposure did not demonstrate a distinct mutational pattern above background at both high and low concentrations. Ultimately, this in vitro system provides a robust platform to define causal links between environmental exposures and mutational patterns in lung cancer mutagenesis. Statement of SignificanceIn vitro exposure of N-nitrosotris-(2-chloroethyl) urea to airway epithelial cells revealed a distinct mutational signature.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer characterized by a high abundance of cancer-associated fibroblasts (CAFs), which influence therapy response, tumor biology and tumor aggressiveness. CAFs are a heterogeneous cell type and previous single-cell RNA sequencing (scRNAseq) of PDAC tumors identified three main CAF subtypes: myofibroblastic, inflammatory and antigen-presenting CAFs (myCAF, iCAF, apCAF, respectively). However, scRNAseq on large patient cohorts is often not feasible due to costs and technical constraints. Therefore, bulk RNAseq deconvolution can be used to identify cell types within the heterogeneous tumor microenvironment. Here, Statescope deconvolution was used to identify different cell types of the tumor microenvironment within an early onset PDAC cohort, comprising 74 patients aged under 60. Three CAF populations were identified (iCAFs, myCAFs and desmoplastic CAFs), and their correlations with tumor microenvironment components, mutational signatures and survival were examined. iCAFs were associated with classical-like tumor cells, whereas myCAFs and desmoplastic CAFs correlated with basal-like tumor cells. Desmoplastic CAFs are associated with inflammatory granulocytes/neutrophils, while negatively associating with monocyte-derived macrophages and immature/transitional B cells. No associations were observed between mutational signatures and the abundance of CAF and epithelial tumor subtypes. Interestingly, a high abundance of CAFs, and specifically increased iCAF abundance, was associated with improved survival. This iCAF-mediated survival effect was predominantly apparent in female patients. All in all, deconvolution of bulk RNA sequencing data, followed by its integration with clinical and biological parameters, reveals the heterogeneity and prognostic implications of CAF subpopulations in the tumor microenvironment of early onset PDAC patients.

The clinical heterogeneity of cancer poses a major challenge for precision medicine. Limited cohort sizes across evolving assay platforms impede reliable biomarker discovery. Here, we systematically evaluate how to integrate data from four transcriptomics platforms: bulk and single-cell (sc) RNA sequencing (RNA-seq), NanoString, and microarray for predictive modeling in cancer. We use high-grade serous carcinoma (HGSC) of tube-ovarian origin as a model system, as it is highly heterogeneous in both biology and assay data. We find that using fold-change of gene expression in patients with matched pre- and post-neoadjuvant chemotherapy samples reduces inter-patient and inter-assay variability but is insufficient to overcome platform-specific biases. Microarray and scRNA-seq data exhibit systematic biases, while RNA-seq and NanoString show the most promise for combination into a single training cohort. To mitigate inter-assay limitations, we generate a new data set of HGSC tumor samples profiled with both RNA-seq and NanoString, and use it to identify the limits of detection and optimal harmonization strategies. Our approaches enable integration of cohorts for separate and combined RNA-seq and NanoString predictive models of disease recurrence (test-set AUROCs > 0.8), validated in external microarray cohorts. We leverage single-cell and bulk RNA-seq network-based analyses to provide mechanistic context for genes in the predictive models. Our models indicate that GBP4 expression is a key predictor of recurrence and marks immune remodeling towards cytotoxicity. We provide an interactive web portal to facilitate exploration of data and results. These findings guide cross-assay harmonization of transcriptomic data and enable improved predictive modeling in heterogeneous cancers. Statement of SignificanceWe present a framework for integrating RNA-seq, NanoString, microarray, and single-cell transcriptomic data for predictive modeling, enabling robust biomarker discovery in heterogeneous cancers and identifying GBP4 as a marker of immune remodeling.

Ionizing radiation can be an effective therapy for prostate cancer. Unfortunately, however, more aggressive prostate cancers such as neuroendocrine prostate cancer (NEPC) are often radiation resistant, which contributes to their high degree of morbidity and mortality. In this study, we used an unbiased approach to identify novel mechanisms that contribute to resistance to radiation and that are associated with neuroendocrine differentiation. Specifically, we compared the expression of cell surface proteins by mass spectrometry in prostate cancer cell lines that had been either untreated or treated with radiation to induce resistance, a process that also promotes neuroendocrine differentiation. Among the proteins identified by this screen, we focused on folate receptor (FR) because of its known biological functions and the fact that it is a validated therapeutic target. Our data reveal that FR has a causal role in enabling prostate cancer cells to resist radiation. Importantly, we also demonstrate that the expression of FR is regulated by HIF-1, which also has a causal role in radiation resistance and neuroendocrine differentiation. Given that the ability of cells to resist damage and death in response to ionizing radiation depends largely on their ability to buffer the substantial increase in reactive oxygen species (ROS) that is generated by radiation, we also demonstrate that the folate-FR axis promotes radiation resistance by sustaining intracellular glutathione levels that buffer this increase in ROS. In summary, the data reported here highlight a novel role for FR in resistance to ionizing radiation that is intimately associated with the hypoxic microenvironment of NEPC and the ability of the folate-FRa axis to maintain redox homeostasis.

Anti-hormonal therapies such as selective estrogen receptor modulators like tamoxifen or aromatase inhibitors like letrozole represent a cornerstone for breast cancer prevention and therapy of estrogen receptor-positive breast cancer. Therapeutic monitoring can include blood tests and imaging; however, genetically-based approaches are not yet in practice. Ideally, a test would be able to detect a positive molecular response across different estrogen pathway-suppressive approaches. Circular RNAs are a species of non-coding RNAs detectable in plasma that have been proposed as non-invasive therapeutic biomarkers. To determine whether a set of specific circular RNAs is altered across estrogen-suppressive pathway approaches, we analyzed mammary gland-specific total RNA sequencing data from two individual genetically engineered mouse models (GEMMs) of estrogen pathway-induced breast cancer, with or without exposure to tamoxifen or letrozole. The nf-core/circrna pipeline was used to identify circRNAs that were differentially expressed in response to either tamoxifen or letrozole. We then screened for circRNAs that were differentially regulated by both anti-hormonals. Four up-regulated and 31 down-regulated circRNAs with host genes known to be expressed in human breast epithelial cells were identified as showing reproducible differential regulation in response to anti-hormonal treatment.