Cellular Tumor Research Articles

Stromal cells regulate mechanics of tumour spheroid

The remarkable contractility and force generation ability exhibited by cancer cells empower them to overcome the resistance and steric hindrance presented by a three-dimensional, interconnected matrix. Cancer cells disseminate by actively remodelling and deforming their extracellular matrix (ECM). The process of tumour growth and its ECM remodelling have been extensively studied, but the effect of the cellular tumour microenvironment (TME) has been ignored in most studies that investigated tumour-cell-mediated ECM deformations and realignment. This study reports the integration of stromal cells in spheroid contractility assays that impacts the ECM remodelling and invasion abilities of cancer spheroids. To investigate this, we developed a novel multilayer in vitro assay that incorporates stromal cells and quantifies the contractile deformations that tumour spheroids exert on the ECM. We observed a negative correlation between the spheroid invasion potential and the levels of collagen deformation. The presence of stromal cells significantly increased cancer cell invasiveness and altered the cancer cells' ability to deform and realign collagen gel, due to upregulation of proinflammatory cytokines. Interestingly, this was observed consistently in both metastatic and non-metastatic cancer cells. Our findings contribute to a better understanding of the vital role played by the cellular TME in regulating the invasive outgrowth of cancer cells and underscore the potential of utilising matrix deformation measurements as a biophysical marker for evaluating invasiveness and informing targeted therapeutic opportunities.

Towards a platform quantitative systems pharmacology (QSP) model for preclinical to clinical translation of antibody drug conjugates (ADCs).

A next generation multiscale quantitative systems pharmacology (QSP) model for antibody drug conjugates (ADCs) is presented, for preclinical to clinical translation of ADC efficacy. Two HER2 ADCs (trastuzumab-DM1 and trastuzumab-DXd) were used for model development, calibration, and validation. The model integrates drug specific experimental data including in vitro cellular disposition data, pharmacokinetic (PK) and tumor growth inhibition (TGI) data for T-DM1 and T-DXd, as well as system specific data such as properties of HER2, tumor growth rates, and volumes. The model incorporates mechanistic detail at the intracellular level, to account for different mechanisms of ADC processing and payload release. It describes the disposition of the ADC, antibody, and payload inside and outside of the tumor, including binding to off-tumor, on-target sinks. The resulting multiscale PK model predicts plasma and tumor concentrations of ADC and payload. Tumor payload concentrations predicted by the model were linked to a TGI model and used to describe responses following ADC administration to xenograft mice. The model was translated to humans and virtual clinical trial simulations were performed that successfully predicted progression free survival response for T-DM1 and T-DXd for the treatment of HER2+ metastatic breast cancer, including differential efficacy based upon HER2 expression status. In conclusion, the presented model is a step toward a platform QSP model and strategy for ADCs, integrating multiple types of data and knowledge to predict ADC efficacy. The model has potential application to facilitate ADC design, lead candidate selection, and clinical dosing schedule optimization.

Spatially Resolved Whole Transcriptome Analysis of Histologically-Characterized Tissue Microarray of Patient-Matched Primary and Recurrent Glioblastomas to Identify Underlying Mechanisms of Treatment Resistance

Glioblastoma multiforme (GBM) is a lethal CNS malignancy. Radiation therapy increases overall survival, but tumors often recur in high-radiation dose regions. Additionally, recent investigations have underscored the importance of intra-tumoral heterogeneity as a driver of GBM biology. The purpose of this investigation is to characterize transcriptome differences in primary and recurrent GBM patient clinical samples using a digital spatial profiling approach to better appreciate treatment resistance mechanisms. To address the lack of understanding of molecular mechanisms of resistance in GBM, patient-matched primary and recurrent GBM pathological specimens were identified within the brain tissue biorepository and tissue cores were selected for generation of a tissue microarray (TMA). Hematoxylin and eosin staining with histomorphological (cellular tumor, pseudopalisading necrosis, invasive edge, and perivascular inflammation) scoring were performed in a blinded fashion for every core. This array was then molecularly characterized using digital spatial profiling of the transcriptome. Quality assurance including filtering of lowly expressed genes followed by downstream analyses of the data were performed using the manufacturer's recommended methods within their Bioconductor library. Gene Set Enrichment Analysis (GSEA) was then performed on the ranked gene lists. After recommended filtering, 6171 genes and 248 regions of interest remained for downstream analysis representing 22 unique patients across four different tumor histomorphological types. Significance testing revealed 679 genes that were differentially expressed between primary and recurrent tumor samples (at FDR<1%). On GSEA analysis, the chromosomal positional locus that contains genes most strongly up-regulated is 12q14, a locus that was previously identified as genomically amplified in multiple patient-derived xenograft lines after radiation selection. Additionally, recurrent tumors display a transcriptional profile more similar to the mesenchymal subtype, whereas primary tumors have a more classical transcriptional phenotype. The epithelial-to-mesenchymal transition pathway is particularly strongly up-regulated in recurrent tumors. Recurrent selection at previously identified genomic loci and molecular pathways underscores a possible conserved set of pathways for treatment resistance. This analysis has yielded a set of gene and molecular pathways that will guide future work in our lab targeting treatment resistance using novel therapeutics and radiation techniques in GBM. Future directions include assessing the feasibility of mapping these clinical samples onto our previously generated panel of comprehensively characterized patient-derived xenograft lines.

Intertumoral lineage diversity and immunosuppressive transcriptional programs in well-differentiated gastroenteropancreatic neuroendocrine tumors.

Neuroendocrine tumors (NETs) are rare cancers that most often arise in the gastrointestinal tract and pancreas. The fundamental mechanisms driving gastroenteropancreatic (GEP)-NET growth remain incompletely elucidated; however, the heterogeneous clinical behavior of GEP-NETs suggests that both cellular lineage dynamics and tumor microenvironment influence tumor pathophysiology. Here, we investigated the single-cell transcriptomes of tumor and immune cells from patients with gastroenteropancreatic NETs. Malignant GEP-NET cells expressed genes and regulons associated with normal, gastrointestinal endocrine cell differentiation, and fate determination stages. Tumor and lymphoid compartments sparsely expressed immunosuppressive targets commonly investigated in clinical trials, such as the programmed cell death protein-1/programmed death ligand-1 axis. However, infiltrating myeloid cell types within both primary and metastatic GEP-NETs were enriched for genes encoding other immune checkpoints, including VSIR (VISTA), HAVCR2 (TIM3), LGALS9 (Gal-9), and SIGLEC10. Our findings highlight the transcriptomic heterogeneity that distinguishes the cellular landscapes of GEP-NET anatomic subtypes and reveal potential avenues for future precision medicine therapeutics.

Detecting Tumor Infiltration in Diffuse Gliomas with Deep Learning

Glioblastoma tumor recurrences often occur in brain tissue areas harboring infiltrating tumor cells, resembling healthy tissue in brain imaging. Demarcating infiltrative regions for aggressive resections is critical for improving prognostic outcomes but is challenging in neurosurgery. Herein, a multilayer sigmoid‐activated convolutional neural network (MLS‐CNN) is developed for rapidly distinguishing glioma tumor infiltration in brain tissue histology. Unlike conventional multiclass classifiers, the MLS‐CNN employs sigmoidal activation to accommodate coexisting classes within patch images. 59 811 image patches (25 807 infiltrating edge, 15 178 normal brain, 18 826 cellular tumor) from 73 brain tissue samples are extracted to train the classifier. The model achieves an accuracy of 91.70% (sensitivity: 91.62%; specificity: 91.78%) and area under the curve (AUC) of 0.964 in distinguishing infiltrating edges, outperforming the current state‐of‐the‐art Vision Transformer (ViT) (accuracy: 89.45; AUC: 0.947). The MLS‐CNN is computationally efficient, generating predictions within 11.5 s in comparison to 81.4 s for ViT. The predictions strongly correlate with In Situ Hybridization expression intensities, validating the utility of the MLS‐CNN model in spatial genomics investigations in gliomas. The robust model can therefore serve as an automatic and accurate classifier to help pathologists identify infiltrative glioma for better diagnosis and patient outcomes in brain oncology.

Multiparametric MRI for the Assessment of Treatment Effect and Tumor Recurrence in Soft-tissue Sarcoma of the Extremities

Soft-tissue sarcomas are a rare and complex group of malignant tumors. Advanced MRI sequences such as diffusion-weighted imaging (DWI) and perfusion-weighted imaging/dynamic contrast enhancement (PWI/DCE) can provide valuable tumor characterization and treatment response assessment. In the case of archetypical cellular tumors such as Pleomorphic Undifferentiated sarcoma (UPS), Good responders often display right-side displacement of the ADC intensity histogram, resulting in increased ADC-mean and decreased kurtosis and Skewness compared with Baseline and poor responders’ more left-sided curve. The PWI/DCE pattern most often associated with a good response is the presence of a “capsular-like” enhancement and a TIC type 2. Sarcoma hemorrhage patterns on SWI emerge during treatment, including “interstitial,” globular,” “luminal,” and incomplete and complete “peripheral ring-like” tumor wall hemosiderin impregnation. Treatment-induced bleeding is typically associated with low SWI-mean values and a left-sided intensity histogram with positive Skewness. During post-surgical surveillance, DCE MR imaging can reliably distinguish recurrent sarcoma from post-surgical scarring. TICs III, IV, and V raise the suspicion of local tumor recurrence, while TIC type II usually represents benign post-operative change such as granulation tissue. Advanced MRI is an essential tool for assessing sarcomas during and after therapy.

Inducible overexpression of a FAM3C/ILEI transgene has pleiotropic effects with shortened life span, liver fibrosis and anemia in mice.

FAM3C/ILEI is an important factor in epithelial-to-mesenchymal transition (EMT) induction, tumor progression and metastasis. Overexpressed in many cancers, elevated ILEI levels and secretion correlate with poor patient survival. Although ILEI's causative role in invasive tumor growth and metastasis has been demonstrated in several cellular tumor models, there are no available transgenic mice to study these effects in the context of a complex organism. Here, we describe the generation and initial characterization of a Tet-ON inducible Fam3c/ILEI transgenic mouse strain. We find that ubiquitous induction of ILEI overexpression (R26-ILEIind) at weaning age leads to a shortened lifespan, reduced body weight and microcytic hypochromic anemia. The anemia was reversible at a young age within a week upon withdrawal of ILEI induction. Vav1-driven overexpression of the ILEIind transgene in all hematopoietic cells (Vav-ILEIind) did not render mice anemic or lower overall fitness, demonstrating that no intrinsic mechanisms of erythroid development were dysregulated by ILEI and that hematopoietic ILEI hyperfunction did not contribute to death. Reduced serum iron levels of R26-ILEIind mice were indicative for a malfunction in iron uptake or homeostasis. Accordingly, the liver, the main organ of iron metabolism, was severely affected in moribund ILEI overexpressing mice: increased alanine transaminase and aspartate aminotransferase levels indicated liver dysfunction, the liver was reduced in size, showed increased apoptosis, reduced cellular iron content, and had a fibrotic phenotype. These data indicate that high ILEI expression in the liver might reduce hepatoprotection and induce liver fibrosis, which leads to liver dysfunction, disturbed iron metabolism and eventually to death. Overall, we show here that the novel Tet-ON inducible Fam3c/ILEI transgenic mouse strain allows tissue specific timely controlled overexpression of ILEI and thus, will serve as a versatile tool to model the effect of elevated ILEI expression in diverse tissue entities and disease conditions, including cancer.

Cellular senescence: a double-edged sword in cancer therapy.

Over the past few decades, cellular senescence has been identified in cancer patients undergoing chemotherapy and radiotherapy. Senescent cells are generally characterized by permanent cell cycle arrest as a response to endogenous and exogenous stresses. In addition to exiting the cell cycle process, cellular senescence also triggers profound phenotypic changes such as senescence-associated secretory phenotype (SASP), autophagy modulation, or metabolic reprograming. Consequently, cellular senescence is often considered as a tumor-suppressive mechanism that permanently arrests cells at risk of malignant transformation. However, accumulating evidence shows that therapy-induced senescence can promote epithelial-mesenchymal transition and tumorigenesis in neighboring cells, as well as re-entry into the cell cycle and activation of cancer stem cells, thereby promoting cancer cell survival. Therefore, it is particularly important to rapidly eliminate therapy-induced senescent cells in patients with cancer. Here we review the hallmarks of cellular senescence and the relationship between cellular senescence and cancer. We also discuss several pathways to induce senescence in tumor therapy, as well as strategies to eliminate senescent cells after cancer treatment. We believe that exploiting the intersection between cellular senescence and tumor cells is an important means to defeat tumors.

OS03.6.A UNSUPERVISED CLUSTERING OF MORPHOLOGY PATTERNS ON WHOLE SLIDE IMAGES GUIDE PROGNOSTIC STRATIFICATION OF GLIOBLASTOMA PATIENTS

Abstract BACKGROUND Glioblastoma is the most common malignant adult brain tumor with a poor prognosis and heterogeneous morphology. Stratifying glioblastoma patients according to overall survival (OS) from H&amp;E-stained histopathology whole slide images (WSI) using advanced computational methods is a challenging task with direct clinical implications. We hypothesize that quantifying morphology patterns present in WSI can yield biomarkers of prognostic relevance contributing to optimizing clinical decision-making. MATERIAL AND METHODS This work is based on 188 glioblastoma (IDH-wt, grade 4) cases identified in the TCGA-GBM and TCGA-LGG, based on the 2021 WHO classification criteria. One Diagnostic WSI from each patient at 10X magnification was selected (ntraining/nhold-out-test =152 /36) and labeled as short (&amp;lt;9 months, n=94) or long (&amp;gt;13 months, n=94) survivors. The WSI is split into non-overlapping 256x256 patches, and extensive patch-level WSI curation is conducted to discard artifactual content, i.e., glass reflections, pen markings, black lines on the slide, and tissue tearing. Each patch is described by a feature vector of 512 dimensions using a pre-trained VGG16. Principal component analysis reduced the dimensionality of these vectors to 236 such that 85% variance is retained. Unsupervised k-means clustering revealed distinct groups of morphology patterns, where the number of clusters is automatically determined based on the rand index and silhouette coefficient. The proportions of these patterns describe the tumor’s spatial heterogeneity and are used to distinguish between short and long survivors using a random forest classifier. RESULTS We identified seven clusters of distinct morphology patterns, including 3 categories of tumor cellularity (low/intermediate/high), necrosis/macrophages, and other prognostically-relevant characteristics. The patient-level short vs long survivor prediction is driven by the proportion of these patterns present in WSI achieving classification accuracy, sensitivity and specificity of 83.83%, 94.44%, and 72.72% respectively on the hold-out test set. The high sensitivity signifies the algorithm’s ability to accurately predict the short survivors which is important in treatment planning and patient management. CONCLUSION The interpretability analysis of various morphologic patterns in distinct histologic sub-regions of glioblastoma may uncover correlations with short and long survivors, providing a deeper understanding of the complex relationship between histologic features and clinical outcomes and shedding light on the heterogeneity of glioblastoma. This association could offer additional prognostic information to clinical neuropathologists during microscopic assessment, leading to more refined prognostication and potentially impacting clinical decision-making for improved patient outcomes.

P11.33.B A PATIENT WITH GLIOBLASTOMA AND EXTENSIVE EXTRANEURAL METASTASES - DOES MOLECULAR BIOLOGY PLAY A CRUCIAL ROLE?

Abstract BACKGROUND Extraneural metastases of glioblastoma (GBM) are rare, reported incidence in literature is 0.4% to 2%. There is a lack in epidemiological data, and what little exists is outdated. The most commonly reported sites of metastases are bone, lymph node and lung. There is an insufficient understanding of the biological mechanism of metastasis, nevertheless, surgical intervention and peritoneal seeding through a ventriculoperitoneal shunt have been postulated as rational routes for the tumor cells. However, reports show metastasizing GBM in patients where neither of these procedures have been performed and therefore biological aspects should be elucidated. Previously, some few genomic studies have shown high mutational burden and that some mutations are only detected in the metastases, indicating clonal evolution. Commonly TP53, TERT, PTEN and CDKN2A/B have been revealed as shared mutations. MATERIAL AND METHODS A 55-year-old man presented with approximately 2 months of progressive headache and behavioral changes. Brain MRI revealed a left temporal lesion suspicious of GBM and no extracranial metastasis was detected. The patient underwent near total surgical resection and completed Stupp protocol. Nine months later, he was admitted to the local hospital with reduced general condition, tachypneic and lower back pain, but subsequent CT of thorax and abdomen revealed multiple pathological lesions in mediastinum, bones, lung, soft tissue, and mesentery. MRI confirmed the findings and a large soft tissue lesion at the level of the 6th thoracic vertebrae, was biopsied and showed metastasis from GBM. There was also local progression of the primary tumor in the brain. Treatment strategy was changed to a combination of lomustine, vincristine and bevacizumab. It was collected blood samples from the patient in respect of circulating tumor cells. A molecular characterization of the tumor samples was performed. RESULTS The primary tumor was MGMT promotor methylated, IDH-1/-2 wildtype, had no TERT promotor mutation, TP53 wildtype and ATRX was intact. The biopsy of the paravertebral lesion showed infiltration of a low differentiated, highly cellular tumor. Immunohistochemically the tumor cells were positive for GFAP, OLIG2 and S100. The molecular features revealed no mutation in BRAF or NTRK. Interestingly, PD-L1 was extremely upregulated, may indicating a potential benefit of immune-checkpoint inhibitors for extraneural metastases. A literature survey is done to find out any risk factors for metastasis. CONCLUSION We report a rare case of GBM with extensive extraneural metastases. This underlines the importance of comparing molecular biology, localization, and other patient and tumoral factors in order to identify any specific risk factor for metastasis. In turn, helping to stratify the follow up of this subgroup in the future.

Differential gene expression and protein-protein interaction network profiling of sulfur mustard-exposed rabbit corneas employing RNA-seq data and bioinformatics tools

Sulfur mustard (SM) ocular exposure severely damages the cornea and causes vision impairment. At present, no specific therapy exists to mitigate SM-induced corneal injury and vision loss. This study performed transcriptome profiling of naïve, SM-damaged, and SM-undamaged rabbit corneas using RNA-seq analysis and bioinformatic tools to gain a better mechanistic understanding and develop SM-specific medical countermeasures. The mRNA profiles of rabbit corneas 4 weeks post SM vapor exposure were generated using Illumina-NextSeq deep sequencing (Gene Expression Omnibus accession # GSE127708). The RNA sequences of naïve (n = 4), SM-damaged (n = 5), and SM-undamaged (n = 5) corneas were subjected to differential expression (DE) analysis after quality control profiling with FastQC. DE analysis was performed using HISAT2, StringTie, and DESeq2. The log2(FC)±2 and adjusted p˂0.05 were chosen to identify the most relevant genes. A total of 5930 differentially expressed genes (DEGs) (upregulated: 3196, downregulated: 2734) were found in SM-damaged corneas compared to naïve corneas, whereas SM-undamaged corneas showed 1884 DEGs (upregulated: 1029, downregulated: 855) compared to naïve corneas. DE profiling of SM-damaged corneas to SM-undamaged corneas revealed 985 genes (upregulated: 308, downregulated: 677). The DE profiles were subsequently subjected to signaling pathway enrichment, and protein‒protein interactions (PPIs) were analyzed. Pathway enrichment was performed for the genes associated with cellular apoptosis, death, adhesion, migration, differentiation, proliferation, extracellular matrix, and tumor necrosis factor production. To identify novel targets, we narrowed the pathway analysis to upregulated and downregulated genes associated with cell proliferation and differentiation, and PPI networks were developed. Furthermore, protein targets associated with cell differentiation and proliferation that may play vital roles in corneal fibrosis and wound healing post SM injury were identified.

LncRNA NEAT1 suppresses cellular senescence in hepatocellular carcinoma via KIF11-dependent repression of CDKN2A.

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths worldwide. Therapeutic options for advanced HCC are limited, which is due to a lack of full understanding of pathogenesis. Cellular senescence is a state of cell cycle arrest, which plays important roles in the pathogenesis of HCC. Mechanisms underlying hepatocellular senescence are not fully understood. LncRNA NEAT1 acts as an oncogene and contributes to the development of HCC. Whether NEAT1 modulates hepatocellular senescence in HCC is unknown. The role of NEAT1 and KIF11 in cellular senescence and tumor growth in HCC was assessed both in vitro and in vivo. RNA pulldown, mass spectrometry, Chromatin immunoprecipitation (ChIP), luciferase reporter assays, RNA FISH and immunofluorescence (IF) staining were used to explore the detailed molecular mechanism of NEAT1 and KIF11 in cellular senescence of HCC. We found that NEAT1 was upregulated in tumor tissues and hepatoma cells, which negatively correlated with a senescence biomarker CDKN2A encoding p16INK4a and p14ARF proteins. NEAT1 was reduced in senescent hepatoma cells induced by doxorubicin (DOXO) or serum starvation. Furthermore, NEAT1 deficiency caused senescence in cultured hepatoma cells, and protected against the progression of HCC in a mouse model. During senescence, NEAT1 translocated into cytosol and interacted with a motor protein KIF11, resulting in KIF11 protein degradation and subsequent increased expression of CDKN2A in cultured hepatoma cells. Furthermore, KIF11 knockdown caused senescence in cultured hepatoma cells. Genetic deletion of Kif11 in hepatocytes inhibited the development of HCC in a mouse model. Conclusively, NEAT1 overexpression reduces senescence and promotes tumor progression in HCC tissues and hepatoma cells, whereas NEAT1 deficiency causes senescence and inhibits tumor progression in HCC. This is associated with KIF11-dependent repression of CDKN2A. These findings lay the foundation to develop potential therapies for HCC by inhibiting NEAT1 and KIF11 or inducing senescence.

Molecular mechanism of Ruxian Shuhou prescription in the treatment of triple-negative breast cancer based on network pharmacology.

We aimed to explore the molecular mechanism of Ruxian Shuhou prescription in the treatment of triple-negative breast cancer (TNBC) by using network pharmacology. The active components and targets of the prescription were obtained by Traditional Chinese medicine systems pharmacology database. Gencards database, online mendelian inheritance in man database, therapeutic target database, and DRUGBANK database were used to search for the TNBC-related targets. The potential targets of Ruxian Shuhou prescription for TNBC were screened out by the intersection of effective ingredient action targets and disease targets. A herb-active ingredient-target network was constructed and analyzed for key ingredients. A protein-protein interaction network was constructed for studying key targets. Furthermore, gene ontology analysis and Kyoto encyclopedia of genes and genomes pathway enrichment analysis were carried out. Finally, the relationship between key ingredients and key genes was evaluated by molecular docking. The key ingredients of Ruxian Shuhou prescription for the treatment of TNBC may be Quercetin, Luteolin and Kaempferol, while the key therapeutic targets may be protein kinase B, interleukin-6, cellular tumor antigen p53, and vascular endothelial growth factor A. The related signaling pathways were mainly involved in tumor, apoptosis and virus infection, among which the PI3K-Akt signaling pathway was the most closely related to TNBC. Molecular docking showed that the key ingredients had high binding activity with the key targets. The molecular mechanisms of Ruxian Shuhou prescription for TNBC are likely to involve multi-ingredient, multi-target and multi-pathway.

Farklı görünür diffüzyon katsayısı değerlerinin pediatrik abdomen ve pelvisin solid malign ve benign tümörlerini ayırt etmedeki yeri

Background and Aims: Diffusion-weighted magnetic resonance imaging is a non-invasive method that can be used in the characterization of tumors, by the quantification of highly cellular tumor components with the use of region of interest measurements on the generated apparent diffusion coefficient maps. The diffusion characteristics of the solid benign tumors of the abdomen and pelvis in children, and the role of apparent diffusion coefficient values in distinguishing solid malignant from solid benign tumors are not well defined. Materials and Method: This study retrospectively evaluated the role of different fractions of the measured and calculated apparent diffusion coefficient values in 49 children with a solid mass lesion of the abdomen or pelvis to determine whether those values allow for distinguishing malignant from benign solid lesions. A subgroup evaluation included the analysis of the apparent diffusion coefficient values in distinguishing Wilms tumor from neuroblastoma. Results: All fractions of apparent diffusion coefficient values were statistically significantly lower in the solid malignant tumors than in the solid benign tumors, with the mean normalized apparent diffusion coefficient values having higher sensitivity and specificity rates. The apparent diffusion coefficient values did not significantly differ between Wilms tumor and neuroblastoma. Conclusions: Apparent diffusion coefficient values can help differentiate malignant from benign solid tumors. Their role can be limited in differentiating Wilms tumor from neuroblastoma.

347. LASER CAPTURE MICRODISSECTION AND WHOLE GENOME SEQUENCING OF ESOPHAGEAL ADENOCARCINOMA SAMPLES WITH MINIMAL TUMOUR

Abstract Background Esophageal adenocarcinoma (EAC) samples, particularly biopsies, can have low tumour cellularity, which limits their use for sequencing. Previous studies have focused on untreated resection specimens with high cellularity (i.e. TCGA requiring 60% cellularity on histology). Laser capture microdissection (LCM) is a method to enrich tumour cells from histological specimens and has been successfully used in other samples. We hypothesize that LCM can enrich for tumour from biopsies and resection specimens with very low cellularity. Methods Biopsy and resection EAC specimens were subjected to laser capture microdissection and whole genome sequencing (N = 49 biopsies and N = 15 resections) as part of the MOCHA trial (NCT04219137). LCM samples were reviewed by a board-certified pathologist to quantify tumour cellularity prior to LCM. Matched germline DNA was extracted from patient blood. Samples were processed using an in-house pipeline to call somatic single nucleotide variants (SNVs), insertions, deletions, copy number changes, and structural variants. Post LCM tumour cellularity was estimated from the WGS data. Results We had slightly higher WGS tumour cellularity for biopsies (66.2% +/− 16.8) and resections (71.3% +/− 18.0) than TCGA (58.1% +/− 17.5), while our histological cellularity was much lower than TCGA’s 60% cutoff at 32.2% +/− 24.5 for biopsies and 31.0% +/− 22.7 for resections. Overall, our LCM strategy led to an increase of 35.4 +/− 25.1% for cellularity by WGS compared to the histology. Finally, we observed a similar tumour ploidy and SNV composition as TCGA, which further verified that our tumour enrichment strategy was successful. Conclusion We have successfully applied an LCM strategy to enrich for tumour cells from low cellularity specimens. For example, we have successfully enriched for tumour cells from specimens with as low as 1% histological cellularity. We are currently exploring the results of this dataset including clinical correlations, changes in potential driver mutations from biopsy to resection, and comparing our results to treatment response.

348. IDENTIFYING NOVEL MOLECULAR SUBTYPES OF ESOPHAGEAL ADENOCARCINOMA USING LASER CAPTURE MICRODISSECTED RNA-SEQ SAMPLES

Abstract Background Treatment options for esophageal adenocarcinoma (EAC) are limited by a lack of disease stratification methods. In other cancers, gene expression profiling has been successfully used to identify prognostically-relevant and treatment-susceptible molecular subtypes. Previous efforts to subtype EAC have been hindered by low biopsy and resection tumour cellularity. We hypothesize that laser-capture microdissection (LCM) tumour cell enrichment will permit the classification EAC tumours into multiple molecular subtypes that will be important for future therapeutic strategies. Methods Treatment naïve patient samples (N = 52) were collected from primary biopsies (N = 37), resections (N = 10) and metastatic biopsies (N = 5). Samples were laser-capture microdissected to enrich tumour cells followed by total RNA-seq. Gene expression was quantified using salmon and non-negative matrix factorization with 10 components was used to identify gene expression programs. The components identified were validated on a publicly available normal tissue cohort (N = 13 esophagus, gastric, intestinal, Barrett’s samples) and the TCGA EAC cohort (N = 80). We applied NMF with 4 components to the normal tissue (K = cohort) to identify normal tissue gene signatures to validate our RNA-seq data. Results We verified that our RNA-seq samples were depleted for normal tissue using the four NMF signatures from normal tissue cohort and, as expected, our samples were depleted for gene expression from the gastric and esophagus tissues compared to TCGA. Next, we explored the gene expression programs from our tumour samples and identified seven tumour-intrinsic components and three tumour microenvironmental components. The top 50 genes from each tumour intrinsic components were used with consensus cluster plus to identify K = 6 subtypes (Figure 1). Interestingly, two of these subtypes would be difficult to separate from normal tissue contamination without the use of LCM. Conclusion We have successfully used LCM to deplete normal tissue gene expression from our esophageal adenocarcinoma cohort and identified six molecular subtypes. We are currently evaluating the treatment and clinical implications of these subtypes and aiming to accumulate an additional (N = 50) EAC RNA-seq samples.

Revealing metastatic castration-resistant prostate cancer master regulator through lncRNAs-centered regulatory network.

Metastatic castration-resistant prostate cancer (mCRPC) is an aggressive form of cancer unresponsive to androgen deprivation therapy (ADT) that spreads quickly to other organs. Despite reduced androgen levels after ADT, mCRPC development and lethality continues to be conducted by the androgen receptor (AR) axis. The maintenance of AR signaling in mCRPC is a result of AR alterations, androgen intratumoral production, and the action of regulatory elements, such as noncoding RNAs (ncRNAs). ncRNAs are key elements in cancer signaling, acting in tumor growth, metabolic reprogramming, and tumor progression. In prostate cancer (PCa), the ncRNAs have been reported to be associated with AR expression, PCa proliferation, and castration resistance. In this study, we aimed to reconstruct the lncRNA-centered regulatory network of mCRPC and identify the lncRNAs which act as master regulators (MRs). We used publicly available RNA-sequencing to infer the regulatory network of lncRNAs in mCRPC. Five gene signatures were employed to conduct the master regulator analysis. Inferred MRs were then subjected to functional enrichment and symbolic regression modeling. The latter approach was applied to identify the lncRNAs with greater predictive capacity and potential as a biomarker in mCRPC. We identified 31 lncRNAs involved in cellular proliferation, tumor metabolism, and invasion-metastasis cascade. SNHG18 and HELLPAR were the highlights of our results. SNHG18 was downregulated in mCRPC and enriched to metastasis signatures. It accurately distinguished both mCRPC and primary CRPC from normal tissue and was associated with epithelial-mesenchymal transition (EMT) and cell-matrix adhesion pathways. HELLPAR consistently distinguished mCRPC from primary CRPC and normal tissue using only its expression. Our results contribute to understanding the regulatory behavior of lncRNAs in mCRPC and indicate SNHG18 and HELLPAR as master regulators and potential new diagnostic targets in this tumor.

Inhibition of NAD+-Dependent Metabolic Processes Induces Cellular Necrosis and Tumor Regression in Rhabdomyosarcoma Models.

Deregulated metabolism in cancer cells represents a vulnerability that may be therapeutically exploited to benefit patients. One such target is nicotinamide phosphoribosyltransferase (NAMPT), the rate-limiting enzyme in the NAD+ salvage pathway. NAMPT is necessary for efficient NAD+ production and may be exploited in cells with increased metabolic demands. We have identified NAMPT as a dependency in rhabdomyosarcoma (RMS), a malignancy for which novel therapies are critically needed. Here we describe the effect of NAMPT inhibition on RMS proliferation and metabolism in vitro and in vivo. Assays of proliferation and cell death were used to determine the effects of pharmacologic NAMPT inhibition in a panel of ten molecularly diverse RMS cell lines. Mechanism of the clinical NAMPTi OT-82 was determined using measures of NAD+ and downstream NAD+-dependent functions, including energy metabolism. We used orthotopic xenograft models to examine tolerability, efficacy, and drug mechanism in vivo. Across all ten RMS cell lines, OT-82 depleted NAD+ and inhibited cell growth at concentrations ≤1 nmol/L. Significant impairment of glycolysis was a universal finding, with some cell lines also exhibiting diminished oxidative phosphorylation. Most cell lines experienced profound depletion of ATP with subsequent irreversible necrotic cell death. Importantly, loss of NAD and glycolytic activity were confirmed in orthotopic in vivo models, which exhibited complete tumor regressions with OT-82 treatment delivered on the clinical schedule. RMS is highly vulnerable to NAMPT inhibition. These findings underscore the need for further clinical study of this class of agents for this malignancy.

Characterization of the Cellular Origin and Oncogenic Mechanisms of Chromophobe Renal Cell Carcinoma (ChRCC) and Renal Oncocytic Neoplasms

Abstract Background ChRCC is a rare form of kidney cancer and presents with a poor prognosis in the metastatic setting, with limited response to immune checkpoint inhibitors (ICI) and targeted therapy. While previous studies suggested that ChRCC originates from intercalated cells of the kidney, its exact cellular origin has not been clearly defined. We therefore investigated the cellular origin of ChRCC and renal oncocytic neoplasms at single-cell resolution. Methods ChRCC, renal oncocytoma (RO) and low-grade oncocytic tumor (LOT) samples with matched normal kidney specimens were analyzed using single-cell RNA sequencing (scRNA-seq). Epithelial cells from normal samples were clustered and annotated into the distinct known cellular types found in the adult healthy human kidney. A logistic regression model (Young M.D. et al., Science, 2018) was trained on the normal epithelial clusters, using a comprehensive set of 74 marker genes (features). Subsequently, the model was tested on tumor clusters from ChRCC, RO and LOT to investigate their cellular origin through the identification of the highest predicted probabilities of similarity between normal epithelial cellular types and tumor cells. Differential gene expression and pathway analyses between ChRCC and its cell of origin were then conducted to investigate mechanisms of oncogenesis. Results Following quality-control, 46,817 cells from 5 tumors (ChRCC: n=3, RO: n=1 and LOT: n=1) and 4 normal samples were isolated for scRNA-seq analysis. Among normal samples, 784 epithelial cells were clustered and annotated into the following cellular entities: proximal tubule (PT), loop of Henle – distal tubule (LOH-DT), principal cells (PC), α-intercalated cells (ICA) and β-intercalated cells (ICB). Across all ChRCC and oncocytic tumors, 7,573 tumor cells were identified, among which 7,425 corresponded to ChRCC. For ChRCC, RO, and LOT neoplasms, the highest predicted probability of similarity was consistently identified with ICA cells (ranging from 0.60 to 0.80). This finding was validated using an external and previously published (Zhang Y. et al., Proc Natl Acad Sci USA, 2021) scRNA-seq dataset from a patient with ChRCC (n=2,853 cells). Additionally, evaluation of previously defined ChRCC-specific markers (i.e. FOXI1, RHCG, KIT, CLCNKA, and CLCNKB) in scRNA-seq data of normal kidney epithelial cells consistently showed the highest expression in ICA cells. Differential gene expression between ChRCC and ICA cells revealed a significant downregulation of MHC class I genes (i.e. HLA-A , HLA-B, and HLA-C) and HSP70 (family A) genes (i.e. HSPA1A, HSPA1B, HSPA6, and HSPA8) in ChRCC. Differential pathway analysis between ChRCC and ICA cells showed a significant enrichment of the ferroptosis, glutathione metabolism, mTOR signaling and IL-15 pathways in ChRCC. Conclusions Renal oncocytic tumors, including ChRCC, appear to originate from the α-intercalated cells of the normal human kidney. As compared to α-intercalated cells, ChRCC downregulates MHC class I genes, which may be associated with its poor response to immunotherapy. Further, the selective downregulation of HSP70 genes may in part explain ChRCC’s increased sensitivity to ferroptosis. CDMRP DOD Funding: yes

CELLULAR PHENOTYPES OF GLIOBLASTOMA AND PROGNOSIS OF TUMOR OUTCOME

In solid malignant tumors, as well as in hematological tumors, cancer stem cells (CSCs), quiescent, pluripotent, self-renewing neoplastic, also known as tumor initiating cells, have been identified. CSC tumors are resistant not only to chemotherapy, but also to radiation therapy, as well as they play their role in the occurrence of relapses after surgical treatment, An unfavorable prognosis due to an aggressive course and complications after treatment of the most common primary brain tumor - glioblastoma multiforme (GBM), is also associated with CSC. One of the mechanisms that affect the physiological regeneration of tissues, but do not work under conditions of malignancy, is the environment and composition of the cellular tumor ensemble, represented by the phenotypes of cellular and adaptive immunity. Using immunohistochemical phenotyping methods, the authors identified immunocytes/phagocytes and established the features of their localization in the malignant tissue and at the border around the tumor. It was concluded that due to apoptosis around the tumor, intercellular signaling and migration of immunocytes/phagocytes to the focus of the tumor process are disrupted. The primary tumor process is not associated with damage to the tissue cambium genome, but with the migration of immature stem cells of the hematogenous pool, capable of proliferating and partially entering into incomplete differentiation under conditions of hypoxia and the absence of blood vessels. At the second stage, connective tissue is formed, which grows into vessels, the wall of which is represented by immature endothelium, with impaired transport function. According to the authors, metastasis of cancer cells does not occur by hematogenous and lymphogenous pathways, but is associated with the development of additional foci of hematopoiesis as a result of the adaptation of the human body to the loss of stem and semi-stem cells, precursors for normal regeneration of the nervous tissue.