Significant Intratumoral Heterogeneity Research Articles

Understanding the heterogeneity in liver hepatocellular carcinoma with a special focus on malignant cell through single-cell analysis

IntroductionHepatocellular carcinoma (HCC) is the most common form of liver cancer globally and remains a major cause of cancer-related deaths. HCC exhibits significant intra-tumoral and interpatient heterogeneity, impacting treatment efficacy and patient prognosis.MethodsWe acquired transcriptome data from the TCGA and ICGC databases, as well as liver cancer chip data from the GEO database, and processed the data for subsequent analysis. We also obtained single cell data from the GEO database and performed data analysis using the Seurat package. To further investigate epithelial cell subgroups and their copy number variations, we used the Seurat workflow for subgroup classification and the InferCNV software for CNV analysis, utilizing endothelial cells as a reference. Pseudo-time analysis and transcription factor analysis of epithelial cells were performed using the monocle2 and SCENIC software, respectively. To assess intercellular communication, we employed the CellChat package to identify potential ligand-receptor interactions. We also analyzed gene expression differences and conducted enrichment analysis using the limma and clusterProfiler packages. Additionally, we established tumor-related risk characteristics using Cox analysis and Lasso regression, and predicted immunotherapy response using various datasets.ResultsThe samples were classified into 23 clusters, with malignant epithelial cells being the majority. Trajectory analysis revealed the differentiation states of the malignant epithelial cells, with cluster 1 being in the terminal state. Functional analysis revealed higher aggressiveness and epithelial-mesenchymal transition (EMT) scores in cluster 1, indicating a higher propensity for metastasis. RBP4+ tumor cells were highly enriched with hypoxia process and intensive cell-to-cell communication. A prognostic model was established, and immune infiltration analysis showed increased infiltration in the high-risk group. TP53 demonstrated significant differences in mutation rate between the two risk groups. Validation analysis confirmed the up-regulation of model genes, including AKR1B10, ARL6IP4, ATP6V0B, and BSG in tumor tissues.ConclusionA prognostic model was established based on HCC malignant cell associated gene signature, displaying decent prognosis guiding effectiveness in the multiple cohorts. The study provided comprehensive insights into the heterogeneity and potential therapeutic targets of LIHC.

Understanding clonal heterogeneity and mechanisms of methotrexate resistance in two osteosarcoma PDX models.

e23512 Background: Osteosarcoma is a primary malignant bone tumor that is known to have significant intratumoral heterogeneity with branched cancer evolution. The lung is the most frequent site of metastatic disease and relapse occurs in more than 30 % children and young adults. It has been revealed that the metastatic ability and resistance of cancers including osteosarcoma might be due to the presence of a subset of cells within the intra-tumorally heterogeneous population. We investigated the emergence of resistant clonal subpopulations following targeted methotrexate treatment in two patient derived xenograft (PDX) models in vitro and in vivo. Our aim was to not only track the subclonal population of cells that establish in the lungs but also to identify clonal drivers and the mutational signature of the genes and pathways involved in MTX resistance. Methods: We previously established 20 barcoded osteosarcoma PDX models and demonstrated that the application of methotrexate (MTX-IC95) treatment as a selective pressure in seven models produces clonal subpopulations that were more resistant to MTX. In the current work we used barcoded next generation and RNA sequencing techniques to map the clonal and transcriptomic architecture of MTX resistant single clones in M36 and OS252 PDX models. We next injected the barcoded PDX cells intratibially in twenty severe combined immunodeficiency disease (SCID) mice to track the clonal population/subpopulation of cells that metastasize to the lungs. Following primary tumor growth, limb amputation was carried out and mice were treated with methotrexate or vehicle for two weeks. Primary tumor, blood and lung samples were collected after death from metastasis or euthanasia. All samples collected were snap frozen in liquid nitrogen and stored at -800C. DNA and RNA was extracted and analyzed by PCR, NGS or WES to map clonality, mutational and evolutionary profiles. Results: MTX treated single clones showed diversity and barcode abundance when compared to vehicle; barcode abundance reduced in the resistant clonal subpopulations when compared to the vehicles. Ten unique subclones were shared in both vehicle and MTX resistant clones in M36 while OS252 had only one shared subclone respectively. More than 50% of the injected mice developed primary tumors and matched lung micrometastases. We are currently analyzing both targeted and RNA sequencing results to further understand clonality, the mutational signature of the genes (DHFR, MTR, FPGS, GGH) and pathways involved in MTX resistance. Conclusions: We investigated mechanism of methotrexate resistance in two barcoded PDX models in vitro and in vivo using cytotoxicity, next generation and RNA sequencing techniques. Targeted amplicon sequencing of key genes involved in antifolate pathway will yield new information on clonal evolution and mechanisms of resistance.

Charting heterogeneity and spatial landscape of consensus molecular subtypes in colorectal cancer.

e15647 Background: High inter-patient heterogeneity and spatial diversity within tumors represent significant challenges to improving outcomes in colorectal cancer (CRC). Despite elucidation of consensus molecular subtypes (CMS), little progress has been made in translating this knowledge into clinical gain. Intratumoral CMS heterogeneity remains a relatively unexplored area and understanding of the interplay between subtypes holds promise for improving prognostication. We leverage spatial transcriptomics (ST) to enhance understanding of CMS heterogeneity and spatial distribution, with the goal of advancing personalized therapy through high resolution molecular sub-typing. Methods: ST using the 10x Genomics Visium platform was performed on paraffin-embedded CRC specimens for which comprehensive clinicopathological and long-term clinical outcome data were available. ST data were deconvoluted with respect to CMS single-cell RNA sequencing (scRNA-seq) data, yielding maps of CMS landscapes at a resolution of 55 microns. A pre-trained deep learning model was used to identify distinct CRC tissue classes (tumor epithelium, stroma, etc.) within H&E images, enabling spatial correlation of histomorphology with CMS. Cellular composition within these CMS maps was quantified through deconvolution of six major cell types using reference scRNA-seq data. Pseudo-bulk samples were generated from the ST data to evaluate CMS behaviors and compute pathway activities. Results: 40 CRC patients were assayed using ST and H&E profiling (13, 8, 14, and 5 from stages 1-4, respectively). Median follow-up was 112 months (Range 1–192). Intratumoral CMS heterogeneity was evident in all patients, with diverse CMS compositions. Using Simpson diversity index to quantify this heterogeneity, we observed significant correlation of heterogeneity with disease specific survival (DSS) (p = .03). CMS landscapes displayed spatial patterns that were distinct among tissue categories (average F1-score: testing = .92, validation = .89. Tissue categories based on deep learning from H&E images). Tumors with higher levels of CMS1 or 4 were associated with worse outcome. Stratification by the composite CMS biomarker (CMS1+CMS4)/(CMS2+CMS3) yielded significant separation of the Kaplan-Meier curve for DSS (p = .018). Conclusions: This study demonstrates that CRC tumors contain significant intratumoral CMS heterogeneity that is not detectable using bulk classification methods. Spatial patterns in CMS transcriptional topographies correlate with H&E-derived morphology, suggesting the potential for estimating CMS composition from histopathological features. Importantly, we show that spatially composite CMS-derived biomarkers possess strong prognostic potential. The capacity to decode CMS topographic patterns and associate these with clinical outcome offers great potential to advance personalized therapy for CRC.

Spatial genomic, biochemical and cellular mechanisms underlying meningioma heterogeneity and evolution.

Intratumor heterogeneity underlies cancer evolution and treatment resistance, but targetable mechanisms driving intratumor heterogeneity are poorly understood. Meningiomas are the most common primary intracranial tumors and are resistant to all medical therapies, and high-grade meningiomas have significant intratumor heterogeneity. Here we use spatial approaches to identify genomic, biochemical and cellular mechanisms linking intratumor heterogeneity to the molecular, temporal and spatial evolution of high-grade meningiomas. We show that divergent intratumor gene and protein expression programs distinguish high-grade meningiomas that are otherwise grouped together by current classification systems. Analyses of matched pairs of primary and recurrent meningiomas reveal spatial expansion of subclonal copy number variants associated with treatment resistance. Multiplexed sequential immunofluorescence and deconvolution of meningioma spatial transcriptomes using cell types from single-cell RNA sequencing show decreased immune infiltration, decreased MAPK signaling, increased PI3K-AKT signaling and increased cell proliferation, which are associated with meningioma recurrence. To translate these findings to preclinical models, we use CRISPR interference and lineage tracing approaches to identify combination therapies that target intratumor heterogeneity in meningioma cell co-cultures.

Spatial Heterogeneity of Immune Drivers Coordinates the Organisation of Antitumor Immunity in Pancreatic Cancer, Affecting Patient Outcome

Abstract Background Pancreatic ductal adenocarcinoma (PDAC) is considered low immunogenic with “cold” tumor microenvironment (TME) and is mostly unresponsive to immune checkpoint blockade therapies. Aims We aim to decipher the impact of intratumoral heterogeneity of immune determinants on antitumor response. Methods 130PDAC specimens were classified according to overall survival in long-term survivors (LTSs, n=29, OS≥60 months) and short-term survivors (STSs, n=101, OS<60 months). Spatial compartment masks were defined by immunofluorescence imaging (tumor cells: Pancytokeratin+CD45-, leukocytes: CD45+Pancytokeratin-, stroma cells: PanCK-CD45-). 4regions of interest from tumor center (TC) and the invasive front (IF) were examined by transcriptomic and proteomic analysis using the Nanostring platform for immune pathway targets. Results of NGS and morphological features were integrated. 20samples underwent immunophenotypic analysis by multiplex immunofluorescence. Results LTSs displayed mostly homogeneous morphology with extended glandular differentiation and immunogenic TME both at TC and IF, with increasing gradient towards the IF. There was higher presence of immune checkpoint-associated and immunogenic genes and proteins at the IF as compared to the TC, including CD40, CD3, CD8, CD4, GZMB and PD-L1. In contrast, STSs were characterized by morphologic heterogeneity, including areas with reduced glandular differentiation and high tumor budding, and a mostly immunosuppressive TME with negative gradient towards the IF. Moreover, there was reduced gene expression and protein abundance at the IF as compared to the TC, including CD3, CD8, CXCL10, GZMB, IFNG, HLA-DR and CD40. Conclusion LTSs display a highly immunogenic TME, underscoring their effective antitumor immunity, especially at the area of IF compared with STSs. A significant intratumoral heterogeneity between TC and IF exists with regards to immune determinants in both, LTSs and STSs, which might explain the different antitumor immune responses, affecting patient outcome. The differential expression of immune drivers may help selecting patients for combination therapies to improve antitumor immunity and harness the responsiveness to immune checkpoint inhibitors in PDAC.

Abstract PO2-23-08: High intratumor heterogeneity induced PSME2 confers endocrine resistance via ERα PARylation in hormone receptor-positive and HER2-negative breast cancer

Abstract Background: Hormone receptor-positive and HER2-negative breast cancer, characterized by its significant intratumor heterogeneity (ITH), poses increased recurrence, metastasis risk, and endocrine resistance. A comprehensive understanding of the genomic and biological characteristics underlying ITH is crucial for the development of effective therapeutic strategies. Methods: We leveraged the multiomics data from our large cohort of 381 hormone receptor-positive and HER2-negative breast tumors, supplemented with single-cell sequencing (scRNA-seq) data from 9 individual samples, to investigate ITH and its associated molecular features. Mechanistic investigations were conducted using Stable Isotope Labeling by Amino Acids in Cell culture (SILAC) proteomics, co-immunoprecipitation (Co-IP), Chromatin Immunoprecipitation followed by quantitative PCR (ChIP-qPCR), and dual-luciferase reporter assays. We specifically focused on the role of Proteasome activator subunit beta (PSME2), a potential regulator of drug resistance and metastasis. Results: We quantified the degree of ITH at sample level using multi-omics and scRNA-seq data and observed a correlation between higher ITH levels, increased genomic instability, upregulation of the STING type-I-interferon-dependent pathway, and poor efficacy of endocrine therapy. Both bulk and single-cell data revealed an enrichment of PSME2, associated with type-I interferon, in groups exhibiting high ITH. Patients with elevated PSME2 expression manifested a poorer prognosis and diminished responsiveness to endocrine therapy. Within the context of ITH, we discovered that IFN-I transcriptionally activated PSME2 via STAT1. Further investigation revealed a complex interplay among PSME2, PARP1, and EWS, wherein PSME2-mediated degradation of EWS relieved the transcriptional repression of PARP1, resulting in its overexpression. This series of events, orchestrated by PSME2, led to ERα PARylation and promoted tamoxifen resistance. In subsequent clinical translation studies employing mouse xenograft, patient-derived organoid (PDO), and patient-derived xenograft (PDX) models, we demonstrated that PARP1 inhibitors could effectively mitigate tamoxifen resistance induced by high PSME2 expression, providing new insights into therapeutic strategies. Conclusions: Our study highlights the importance of understanding ITH in hormone receptor-positive and HER2-negative breast cancer and identifies PSME2 as a key player in endocrine resistance and patient prognosis. The application of PARP1 inhibitors shows promise in improving treatment outcomes in tumors with elevated ITH and PSME2 expression. Working Modle Citation Format: Li-Ping Ge, Zi-Yu Wang, Xi Jin, Yi-Zhou Jiang, Zhi-Ming Shao. High intratumor heterogeneity induced PSME2 confers endocrine resistance via ERα PARylation in hormone receptor-positive and HER2-negative breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-23-08.

Quantitative Assessment of Preanalytic Variables on Clinical Evaluation of PI3/AKT/mTOR Signaling Activity in Diffuse Glioma

Biomarker-driven therapeutic clinical trials require the implementation of standardized, evidence-based practices for sample collection. In diffuse glioma, phosphatidylinositol 3 (PI3)-kinase/AKT/mTOR (PI3/AKT/mTOR) signaling is an attractive therapeutic target for which window-of-opportunity clinical trials could facilitate the identification of promising new agents. Yet, the relevant preanalytic variables and optimal tumor sampling methods necessary to measure pathway activity are unknown. To address this, we used a murine model for isocitrate dehydrogenase (IDH)-wildtype glioblastoma (GBM) and human tumor tissue, including IDH-wildtype GBM and IDH-mutant diffuse glioma. First, we determined the impact of delayed time-to-formalin fixation, or cold ischemia time (CIT), on the quantitative assessment of cellular expression of 6 phosphoproteins that are readouts of PI3K/AK/mTOR activity (phosphorylated-proline-rich Akt substrate of 40 kDa (p-PRAS40, T246), -mechanistic target of rapamycin (p-mTOR; S2448); -AKT (p-AKT, S473); -ribosomal protein S6 (p-RPS6, S240/244 and S235/236), and -eukaryotic initiation factor 4E–binding protein 1 (p-4EBP1, T37/46). With CITs ≥ 2 hours, typical of routine clinical handling, all had reduced or altered expression with p-RPS6 (S240/244) exhibiting relatively greater stability. A similar pattern was observed using patient tumor samples from the operating room with p-4EBP1 more sensitive to delayed fixation than p-RPS6 (S240/244). Many clinical trials utilize unstained slides for biomarker evaluation. Thus, we evaluated the impact of slide storage conditions on the detection of p-RPS6 (S240/244), p-4EBP1, and p-AKT. After 5 months, storage at −80°C was required to preserve the expression of p-4EBP1 and p-AKT, whereas p-RPS6 (240/244) expression was not stable regardless of storage temperature. Biomarker heterogeneity impacts optimal tumor sampling. Quantification of p-RPS6 (240/244) expression in multiple regionally distinct human tumor samples from 8 patients revealed significant intratumoral heterogeneity. Thus, the accurate assessment of PI3K/AKT/mTOR signaling in diffuse glioma must overcome intratumoral heterogeneity and multiple preanalytic factors, including time-to-formalin fixation, slide storage conditions, and phosphoprotein of interest.

Abstract 6924: Structural variant dynamics in melanoma: Unraveling tumor heterogeneity and evolution

Abstract Melanoma is characterized by significant intratumoral heterogeneity and complex evolutionary dynamics. This diversity in genomic alterations leads to the emergence of various subclonal populations within a single tumor. In our research, we established a new model system composed of 24 single-cell-derived clonal sublines (C1-C24), originating from the M4 melanoma model. This model was developed using a genetically engineered hepatocyte growth factor (HGF)-transgenic mouse. We employed Trisicell (Triple-toolkit for single-cell intratumor heterogeneity inference), a cutting-edge computational tool for scalable analysis of intratumor heterogeneity and evaluation based on single-cell RNA mutations. This enabled us to construct a phylogeny tree, revealing melanoma’s intricate branching evolutionary patterns. These patterns show ancestral clones evolving into genetically distinct subclones, which demonstrate varied phenotypic traits such as drug sensitivity or resistance, cellular plasticity, and immunogenicity. In our study, we conducted long-read sequencing on these clonal sublines in the phylogeny and identified structural variants (SVs) using Severus, a tool optimized for phasing in long-read sequencing. The types of SVs we discovered include deletions, insertions, amplifications, translocations, and inversions. We explored their roles in subclonal evolution, particularly focusing on how they disrupt genes and accumulate during melanoma progression. Our initial data from eleven sublines indicated a higher prevalence of ancestral SVs, shared by all sublines, compared to subline-specific SVs, representing later events. Notably, the individual sublines showed a higher rate of gene disruption by SVs, hinting at potential functional selection. Our analysis further revealed that SVs common to all sublines are linked with genes in key cell growth pathways, such as Rap1, Hippo, and calcium signaling pathways. In contrast, subline-specific SVs primarily affect genes involved in neurophysiological pathways, such as glutamatergic synapse and morphine addiction pathways. These findings suggest that different genes, associated with various pathways, are disrupted at distinct stages of melanoma progression, providing insights into the genetic factors that may predispose individual melanocytes to melanomagenesis. This methodology presents a comprehensive tool for characterizing tumor genomes and understanding their relationship with disease progression and therapy resistance. We are continuing our analysis to map SVs across the entire mutation-based phylogeny of all sublines, which will further our understanding of melanoma’s genomic landscape. Citation Format: Xiwen Cui, Ayse G. Keskus, Farid R. Mehrabadi, Salem Malikic, Mikhail Kolmogorov, Chi-Ping Day, Glenn Merlino, S. Cenk Sahinalp. Structural variant dynamics in melanoma: Unraveling tumor heterogeneity and evolution [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6924.

Abstract 7567: In-depth mass cytometry analysis reveals different immune cell composition of unique molecular subtypes in extensive stage small-cell lung cancer

Abstract Background: A novel molecular subtype classification was fashionable for small cell lung cancer (SCLC). However, the distribution of SCLC molecular subtype classification in Chinese patients were unknown, especially extensive stage (ES)-SCLC. It should validate and define their associated microenvironments across subtypes in ES-SCLC. Method: We used immunohistochemical (IHC) to evaluate SCLC markers of the subtypes including ASCL1, NEUROD1, POU2F3, SCLC-A/N/P in 135 ES-SCLC tumors. Peripheral blood of 24 ES-SCLC patients was test by mass cytometry using time-of-flight (CyTOF) to evaluate the differences in immune subsets regard to the subtype tumor microenvironment (TME). Validation was performed using flow cytometry and multiplex IF. Results: ASCL1, NEUROD1, POU2F3, and Inflamed were account for 60.7%, 28.9%, 7.4%, and 18.5% of SCLC tumors, respectively. Significant intratumoral heterogeneity was observed with 15.6% of the tumors being both positive for SCLC-A and -N subtype markers, respectively. The SCLC-I type possessed more CD8+ T-cells infiltration and had higher frequency an ‘inflamed’ immunophenotyped. CyTOF data showed greater CD161+CD127+CD8+T cells proportion in SCLC-I than SCLC-N subtypes before and after anti-immunotherapy. Furthermore, we validated that lung tissue of SCLC-I were infiltrated more CD161+CD127+CD8+T cells compared to SCLC-N subpopulation(P=0.0281). Flow cytometry further showed the stronger immune activation of CD161+CD127+CD8+T cells in SCLC-I types induced higher expression of GZMB and GNLY and lower-expression of T-cell exhaustion markers PD-1,TIGIT and LAG3 in comparison with SCLC-N types. We further confirmed that the high level of CD161+CD127+CD8+T associated with a favorable treatment response and prolonged overall survival. Conclusion: The present study validated the molecular subtypes in ES-SCLC patients. Furthermore, SCLC-I subtype has longer PFS and OS than SCLC-A, -N and -P patients. Our research not only provides an insight into the immune landscape of ES-SCLC but also sheds light on a special subset of CD161+CD127+CD8+T cells with prognostic and therapeutic significance. Citation Format: Yuekang Li, Jingjing Qu, Binggen Wu, Qian Shen, Wenjia Sun, Lijun Chen, Bo Wang, Lixiong Ying, Jianya Zhou, Jianying Zhou. In-depth mass cytometry analysis reveals different immune cell composition of unique molecular subtypes in extensive stage small-cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7567.

Geotemporal Fluorophore Biodistribution Mapping of Colorectal Cancer: Micro and Macroscopic Insights.

Fifty consenting patients undergoing treatment for suspected/confirmed colorectal neoplasia provided near infrared (NIR) video and imagery of transanally recorded and ex vivo resected rectal lesions following intravenous ICG administration (0.25 mg/kg), with a subgroup providing tissue samples for microscopic (including near infrared) analysis. Computer vision techniques detailed macroscopic 'early' (<15 min post ICG administration) and 'late' (>2 h) tissue fluorescence appearances from surgical imagery with digital NIR scanning (Licor, Lincoln, NE, USA) and from microscopic analysis (Nikon, Tokyo, Japan) undertaken by a consultant pathologist detailing tissue-level fluorescence distribution over the same time. Significant intra-tumoural fluorescence heterogeneity was seen 'early' in malignant versus benign lesions. In all 'early' samples, fluorescence was predominantly within the tissue stroma, with uptake within plasma cells, blood vessels and lymphatics, but not within malignant or healthy glands. At 'late' stage observation, fluorescence was visualised non-uniformly within the intracellular cytoplasm of malignant tissue but not retained in benign glands. Fluorescence also accumulated within any present peritumoural inflammatory tissue. This study demonstrates the time course diffusion patterns of ICG through both benign and malignant tumours in vivo in human patients at both macroscopic and microscopic levels, demonstrating important cellular drivers and features of geolocalisation and how they differ longitudinally after exposure to ICG.

Abstract B033: Mapping subclonal epigenetic evolution in colorectal cancer by spatial analysis of DNA hypermethylation

Abstract Aberrant patterns of DNA methylation (DNAme) have long been noted in colorectal cancer (CRC). Early studies found overall hypomethylation of the cancer genome, while subsequent work revealed focal hypermethylation at specific loci, especially CpG-rich promoters. Loci occupied by polycomb repressive complex 2 in stem cells are remarkably enriched in cancer-specific hypermethylation events. These Polycomb Target Genes (PTGs) include important transcriptional regulators of lineage specification and differentiation, suggesting that hypermethylation-mediated silencing of PTGs could play an active role in CRC initiation or progression. Despite these findings, we have limited knowledge of when, where, and how this hypermethylation arises. Preliminary evidence from bulk tumor samples in the Cancer Genome Atlas suggests that many of these PTG hypermethylation events may be almost completely clonal. Additionally, we have noted rare, densely methylated reads covering PTGs in cancer-adjacent, histologically normal tissue. These observations suggest that PTG hypermethylation may be a very early event in carcinogenesis and may play a permissive or even active role in that process. To better understand the timing and evolution of PTG hypermethylation events in CRC, we have developed a protocol that allows us to extract dozens of small (20µL), spatially annotated mini-bulk samples from live tumors. These mini-bulks may be frozen or dissociated to viable single-cell suspensions. Remaining tumor tissue is preserved in the form of spatially annotated FFPE blocks, which can be used for analyses such as high-plex immunofluorescence or spatial transcriptomics. Using this process, we have collected over 500 spatially annotated samples from 6 CRC cases, including 196 micro-bulk samples profiled using the Infinium MethylationEPIC array. Additionally, we have profiled DNAme in 147 single cells using a dramatically improved single-cell whole-genome bisulfite sequencing protocol developed in our lab. Analysis of EPIC array data reveals wide variation in DNAme heterogeneity between tumors. While in some tumors, the vast majority of DNA hypermethylation events are clonal, other tumors reveal significant intra-tumor heterogeneity, including two or more prominent DNAme subclones as well as a substantial number of ‘private’ hypermethylation events that occur in only one sample. Mapping DNAme information back onto our spatial data reveals that in at least one case, DNAme clones are spatially partitioned and are associated with distinct histology. Ongoing work includes inference of phylogenetic trees from DNA hypermethylation events using non-reversible models of methylation accumulation, allowing us to measure the relative timing of hypermethylation events, as well as integration of array, whole-genome, and single-cell methylation data to more completely characterize DNAme subclones, characterize cellular DNAme heterogeneity at variably methylated sites, and shed further light on the evolution of cancer-related DNA hypermethylation. Citation Format: Nathan J. Spix, Hsiao-yun Milliron, Manpreet Kalkat, Emily Eugster, David W. Chesla, David Sokol, Emily Jung, Paula Nolte, Kelly K. Krzyzanowski, Toshinori Hinoue, Hui Shen, Peter W. Laird. Mapping subclonal epigenetic evolution in colorectal cancer by spatial analysis of DNA hypermethylation [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr B033.

Clinically relevant molecular hallmarks of PFA ependymomas display intratumoral heterogeneity and correlate with tumor morphology

Posterior fossa type A (PF-EPN-A, PFA) ependymoma are aggressive tumors that mainly affect children and have a poor prognosis. Histopathology shows significant intratumoral heterogeneity, ranging from loose tissue to often sharply demarcated, extremely cell-dense tumor areas. To determine molecular differences in morphologically different areas and to understand their clinical significance, we analyzed 113 PF-EPN-A samples, including 40 corresponding relapse samples. Cell-dense areas ranged from 0 to 100% of the tumor area and displayed a higher proportion of proliferating tumor cells (p < 0.01). Clinically, cell density was associated with poor progression-free and overall survival (pPFS = 0.0026, pOS < 0.01). Molecularly, tumor areas with low and high cell density showed diverging DNA methylation profiles regarding their similarity to distinct previously discovered PF-EPN-A subtypes in 9/21 cases. Prognostically relevant chromosomal changes at 1q and 6q showed spatial heterogeneity within single tumors and were significantly enriched in cell-dense tumor areas as shown by single-cell RNA (scRNA)-sequencing as well as copy number profiling and fluorescence in situ hybridization (FISH) analyses of different tumor areas. Finally, spatial transcriptomics revealed cell-dense areas of different tumors to be more similar than various different areas of the same tumor. High-density areas distinctly overexpressed genes encoding histone proteins, WNT5A, TGFB1, or IGF2. Relapsing tumors displayed a higher proportion of cell-dense areas (p = 0.036), a change in PF-EPN-A methylation subtypes (13/32 patients), and novel chromosome 1q gains and 6q losses (12/32 cases) compared to corresponding primary tumors. Our data suggest that PF-EPN-A ependymomas habor a previously unrecognized intratumoral heterogeneity with clinical implications, which has to be accounted for when selecting diagnostic material, inter alia, by histological evaluation of the proportion of cell-dense areas.

Abstract B021: Clonal heterogeneity in human pancreatic adenocarcinoma and its contribution to therapeutic resistance

Abstract PDAC is a highly aggressive cancer with poor prognosis, largely due to its late diagnosis, rapid progression, and lack of responsiveness to standard therapies. The advent of large-scale genomics, single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) has illuminated potential genomic targets, the intricate role of the PDAC tumor microenvironment (TME), and gene activity orchestrating cellular arrangements within cancer tissues. In recent work by our group, we characterized the composition of human PDAC at the single-cell level, revealing significant intra-tumoral heterogeneity in transcriptional subtypes and TME composition. We also found that chemotherapy profoundly alters the PDAC TME and may lead to further resistance to immunotherapy by reduced inhibitory checkpoint molecule expression and interactions involving CD8+ T cells. We have since determined that specific clones in human PDAC tumors have unique influences on the biological and clinical features of PDAC. In this study, we tested the hypothesis that the distinct genomic profiles of individual clones within PDAC tumors influence their transcriptional state and their interaction with the TME, ultimately governing disease progression and response to chemotherapy. scRNA-seq analysis was performed on 61 freshly collected human primary PDAC samples from 58 patients, either prior to or following chemotherapy treatment, including 3 matched pre- and post- treatment pairs from the same patient. CNV analysis of PDAC samples revealed significant inter- and intra- tumoral clonal heterogeneity. Using the results of differential gene expression and gene set enrichment analysis, we identified a set of common transcriptional states associated with specific CNV profiles. Further, we found that specific PDAC clones often correlated with classical and basal subtypes. Using a combination of ligand-receptor-interaction (LRI) analysis and spatial transcriptomics, we observed that distinct clones within tumors exhibited heterogeneous interactions with different cell types in the TME, and that the composition of individual clones within tumors and their LRI were significantly and differentially altered in response to chemotherapy. Our findings indicate the presence of distinct clonal neighborhoods in PDAC, and allow interrogation of clonal and cell communication network changes that occur in response to chemotherapy. This data provide new insight into potential mechanisms of treatment resistance and may help identify potential strategies to intercept or more effectively treat metastasis and improve patient outcomes. Citation Format: Despoina Kalfakakou, Emily A. Kawaler, Dylan Tamayo, Lidong Wang, Rosmel Hernandez, Amanda Ackermann, Xiaohong Jing, Cristina Hajdu, Cynthia Loomis, Adrianna Heguy, Amanda W. Lund, Theodore H. Welling, Igor Dolgalev, Aristotelis Tsirigos, Diane M. Simeone. Clonal heterogeneity in human pancreatic adenocarcinoma and its contribution to therapeutic resistance [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr B021.

Analysis of DNA methylation profiles confirms a high proportion of immune cells in glioblastoma samples

Glioblastomas are malignant tumors that belong to the central nervous system and are challenging to diagnose due to their significant intratumoral heterogeneity, which makes molecular testing and diagnosis confirmation particularly difficult. In addition to identifying typical genetic mutations such as IDH, H3F3A G34 and K27, WHO recommendations emphasize the importance of analyzing the tumor epigenome to define its class based on DNA methylation patterns and methylation status of specific genomic regions, particularly the MGMT promoter region. Based on our clinical experience, molecular genetic studies sometimes yield contradictory results due to the heterogeneous cellular composition of glioblastomas. In this study, we present a series of observations made on 35 glioblastoma samples in which we compare the morphological features and the results of cell type detection by deconvolution method based on total DNA methylation profiles. Our results suggest that samples of mesenchymal class glioblastomas may contain over 50 % non-tumor immune cells, which should be considered in genetic testing of these tumors.

Transcriptomic and genomic profiling of multiple primary colorectal cancers reveals intratumor heterogeneity and a distinct immune microenvironment

This study reported on the intratumor genomic and immunological heterogeneity of different tumor lesions from a single patient with multiple primary colorectal cancer (MPCC). The goal of this study was to explore the molecular and microenvironment characteristics of tumor lesions from different primary sites in a patient with MPCC.A total of three tumor lesions located in the hepatic flexure of the transverse colon, sigmoid colon, and rectum were collected from a 72-year-old male patient with MPCC. All three tumor samples were examined by using whole-exome sequencing (WES) and single-cell RNA sequencing (scRNA-seq). The transcriptome data of The Cancer Genome Atlas (TCGA) colon cancer (COAD) dataset were explored to characterize the biological impacts of certain immune cells. Only three nonsynonymous mutations were shared by all of the tumor lesions, whereas a number of single nucleotide variant (SNV) and copy number variation (CNV) mutations were shared by tumor samples from the sigmoid colon and rectum. Transcriptomic analysis showed that tumor lesions derived from the transverse colon had decreased levels of RTK, ERK, and AKT pathway activity, thus suggesting lower oncogenic properties in the transverse lesion compared to the other two samples. Further immune landscape evaluation by using single-cell transcriptomic analysis displayed significant intratumor heterogeneity in MPCC. Specifically, more abundant mucosal-associated invariant T (MAIT) cell infiltration was found in transverse colon tumor lesions. Afterwards, we found that higher MAIT cell infiltration may correlate with a better prognosis of patients with colon cancer (immunohistochemical status was MSI-L/pMMR) by using a publicly available TCGA dataset.

CTIM-16. DEVELOPING PATIENT SPECIFIC TUMOR INFILTRATING LYMPHOCYTES (TILS) WITH INCREASED TUMOR SPECIFICITY AS A THERAPY FOR GLIOBLASTOMA

Abstract Immunotherapy failure in glioblastoma results from three main hurdles; limited numbers of T cells within the tumor, T cell exhaustion and significant intra-tumoral and intra-patient heterogeneity leading to lack of T cell tumor recognition. Our group has developed an expansion protocol to isolate and expand less exhausted tumor infiltrating lymphocytes (TILs) from the tumor periphery, selecting for TILs that recognize tumor antigen ex vivo. This process will increase the number of T-cells specific for an individual patient’s diverse tumor neoantigens. We have successfully expanded glioblastoma associated TILs from 66% of the novel Lukens trap substrate, which collects TILs and tumor from the tumor periphery. Cells are expanded in two stages, preREP and REP, through novel methods based on a protocol with clinical success in lung cancer and modified to increase the percent of tumor specific T cells. Through co-culture with patient matched glioma neurospheres we have identified activated T cells from each stage of culture (initial product, preREP, REP) based on CD137+ expression and tumor specific cytokine release (IFNy+TNFa+IL2+IL17a+) by flow cytometry. Through 5’scRNA sequencing paired with TCR repertoire analysis we can identify activation specific TCRs. Overrepresented TCR alpha and beta chains will be linked by a P2A site, cloned into a lentiviral vector, and transduced into TCR negative Jurkat cells to confirm tumor reactivity. This strategy will allow us to enrich and assess tumor specific TCR activity compared to bystander activation in our TIL product. Following additional preclinical assessment of cytotoxicity against autologous tumor, we will evaluate safety and feasibility of by administering our novel TIL product intrathecally in patients with glioblastoma.

Clinically impactful metabolic subtypes of pancreatic ductal adenocarcinoma (PDAC).

Background: Pancreatic ductal adenocarcinoma (PDAC) is a lethal disease characterized by a diverse tumor microenvironment. The heterogeneous cellular composition of PDAC makes it challenging to study molecular features of tumor cells using extracts from bulk tumor. The metabolic features in tumor cells from clinical samples are poorly understood, and their impact on clinical outcomes are unknown. Our objective was to identify the metabolic features in the tumor compartment that are most clinically impactful. Methods: A computational deconvolution approach using the DeMixT algorithm was applied to bulk RNASeq data from The Cancer Genome Atlas to determine the proportion of each gene's expression that was attributable to the tumor compartment. A machine learning algorithm designed to identify features most closely associated with survival outcomes was used to identify the most clinically impactful metabolic genes. Results: Two metabolic subtypes (M1 and M2) were identified, based on the pattern of expression of the 26 most important metabolic genes. The M2 phenotype had a significantly worse survival, which was replicated in three external PDAC cohorts. This PDAC subtype was characterized by net glycogen catabolism, accelerated glycolysis, and increased proliferation and cellular migration. Single cell data demonstrated substantial intercellular heterogeneity in the metabolic features that typified this aggressive phenotype. Conclusion: By focusing on features within the tumor compartment, two novel and clinically impactful metabolic subtypes of PDAC were identified. Our study emphasizes the challenges of defining tumor phenotypes in the face of the significant intratumoral heterogeneity that typifies PDAC. Further studies are required to understand the microenvironmental factors that drive the appearance of the metabolic features characteristic of the aggressive M2 PDAC phenotype.

Clinical implication of genetic intratumor heterogeneity for targeted therapy in head and neck cancer

Background Genomic profiling is increasingly used both in therapeutic decision-making and as inclusion criteria for trials testing targeted therapies. However, the mutational landscape may vary across different areas of a tumor and intratumor heterogeneity will challenge treatments or clinical decisions based on single tumor biopsies. The purpose of this study was to assess the clinical relevance of genetic intratumor heterogeneity in head and neck squamous cell carcinomas (HNSCC) using the ESMO Scale for Clinical Actionability of Molecular Targets (ESCAT). Materials and methods This prospective study included 33 whole tumor specimens from 28 patients with primary or recurrent HNSCC referred for surgery. Three tumor blocks were selected from central, semi-peripheral, and peripheral positions, mimicking biopsies in three different locations. Genetic analysis of somatic copy number alterations (SCNAs) was performed on the three biopsies using Oncoscan, focusing on 45 preselected HNSCC genes of interest. Clinical relevance was assessed using the ESCAT score to investigate whether and how treatment decisions would change based on the three biopsies from the same tumor. Results The SCNAs identified among 45 preselected genes within the three tumor biopsies derived from the same tumor revealed distinct variations. The detected discrepancies could potentially influence treatment approaches or clinical decisions in 36% of the patients if only one tumor biopsy was used. Recurrent tumors exhibited significantly higher variation in SCNAs than primary tumors (p = .024). No significant correlation between tumor size and heterogeneity (p = .7) was observed. Conclusion In 36% of patients diagnosed with HNSCC, clinically significant intratumor heterogeneity was observed which may have implications for patient management. This finding substantiates the need for future studies that specifically investigate the clinical implications associated with intratumor heterogeneity.

Single-cell RNA sequencing reveals pro-invasive cancer-associated fibroblasts in hypopharyngeal squamous cell carcinoma

BackgroundHypopharyngeal squamous cell carcinoma (HPSCC) has the worst prognosis among all head-and-neck cancers, and treatment options are limited. Tumor microenvironment (TME) analysis can help identify new therapeutic targets and combined treatment strategies.MethodsSix primary HPSCC tissues and two adjacent normal mucosae from six treatment-naïve patients with HPSCC were analyzed using scRNA-seq. Cell types were curated in detail, ecosystemic landscapes were mapped, and cell–cell interactions were inferred. Key results were validated with The Cancer Genome Atlas and cell biology experiments.ResultsMalignant HPSCC epithelial cells showed significant intratumor heterogeneity. Different subtypes exhibited distinct histological features, biological behaviors, and spatial localization, all affecting treatment selection and prognosis. Extracellular matrix cancer-associated fibroblasts (mCAFs) expressing fibroblast activation protein were the dominant CAFs in HPSCC tumors. mCAFs, constituting an aggressive CAF subset, promoted tumor cell invasion, activated endothelial cells to trigger angiogenesis, and synergized with SPP1+ tumor associated macrophages to induce tumor progression, ultimately decreasing the overall survival of patients with HPSCC. Moreover, the LAMP3+ dendritic cell subset was identified in HPSCC and formed an immunosuppressive TME by recruiting Tregs and suppressing CD8+ T cell function.ConclusionsmCAFs, acting as the communication center of the HPSCC TME, enhance the invasion ability of HPSCC cells, mobilizing surrounding cells to construct a tumor-favorable microenvironment. Inhibiting mCAF activation offers a new anti-HPSCC therapeutic strategy.Graphical 3rZBJkNLzDco4s_zE23WXSVideo

Small extrachromosomal circular DNA harboring targeted tumor suppressor gene mutations supports intratumor heterogeneity in mouse liver cancer induced by multiplexed CRISPR/Cas9

BackgroundPrimary liver cancer has significant intratumor genetic heterogeneity (IGH), which drives cancer evolution and prevents effective cancer treatment. CRISPR/Cas9-induced mouse liver cancer models can be used to elucidate how IGH is developed. However, as CRISPR/Cas9 could induce chromothripsis and extrachromosomal DNA in cells in addition to targeted mutations, we wondered whether this effect contributes to the development of IGH in CRISPR/Cas9-induced mouse liver cancer.MethodsCRISPR/Cas9-based targeted somatic multiplex-mutagenesis was used to target 34 tumor suppressor genes (TSGs) for induction of primary liver tumors in mice. Target site mutations in tumor cells were analyzed and compared between single-cell clones and their subclones, between different time points of cell proliferation, and between parental clones and single-cell clones derived from mouse subcutaneous allografts. Genomic instability and generation of extrachromosomal circular DNA (eccDNA) was explored as a potential mechanism underlying the oscillation of target site mutations in these liver tumor cells.ResultsAfter efficiently inducing autochthonous liver tumors in mice within 30–60 days, analyses of CRISPR/Cas9-induced tumors and single-cell clones derived from tumor nodules revealed multiplexed and heterogeneous mutations at target sites. Many target sites frequently displayed more than two types of allelic variations with varying frequencies in single-cell clones, indicating increased copy number of these target sites. The types and frequencies of targeted TSG mutations continued to change at some target sites between single-cell clones and their subclones. Even the proliferation of a subclone in cell culture and in mouse subcutaneous graft altered the types and frequencies of targeted TSG mutations in the absence of continuing CRISPR/Cas9 genome editing, indicating a new source outside primary chromosomes for the development of IGH in these liver tumors. Karyotyping of tumor cells revealed genomic instability in these cells manifested by high levels of micronuclei and chromosomal aberrations including chromosomal fragments and chromosomal breaks. Sequencing analysis further demonstrated the generation of eccDNA harboring targeted TSG mutations in these tumor cells.ConclusionsSmall eccDNAs carrying TSG mutations may serve as an important source supporting intratumor heterogeneity and tumor evolution in mouse liver cancer induced by multiplexed CRISPR/Cas9.