Intratumoral Molecular Heterogeneity Research Articles

EPCO-44. SPATIAL TRANSCRIPTOMICS ENABLES STATISTICAL MODELING OF SEX DIFFERENCE IN GENE CO-EXPRESSION NETWORK AND IMMUNE LANDSCAPE OF GLIOBLASTOMA

Abstract Glioblastoma (GBM) is characterized by inter- and intra-tumor molecular heterogeneity and demonstrated cell plasticity. Sex differences have been observed in various aspects: a male:female GBM incidence ratio is 1.6:1; standard of care treatments (debulking, radiation, and temozolomide) benefit females more than males. 14 human GBM samples from two study sites were subject to spatial profiling on the Vizgen Merscope platform to examine whether distinct biological and therapeutic niches in GBM were evident, to understand how the tumor microenvironments (TME) contributed to the heterogeneity of GBM, and to interrogate sex difference in the immune landscape of GBM. Multiple sets of spatial probes were designed to capture the cell identities (cancer stem cells, astrocytes, oligodendrocytes, microglia, macrophages, etc.) and the spatially-resolved expression patterns of genes with different functions. Two of the 14 GBM samples were also profiled on another FISH-based spatial platform (Veranome). The data from the two platforms exhibited a linear correlation. We explored the gene-gene co-expression network, and calculated the interaction probabilities between genes which were then compared for sex difference. We found that female samples showed significantly lower (two-fold) CD4+/CD8A+ T-cell count ratios than male samples. We also observed sample-specific spatial niches of different GBM cell subtypes and immune cell populations. Our large-scale spatial transcriptomics study revealed intrinsic sex-based differences in immune response to tumor and illuminated microenvironmental influences on GBM.

EPCO-15. INTRA-TUMORAL HETEROGENEITY OF DNA METHYLATION PROFILING AND CELLULAR COMPOSITION IN GLIOBLASTOMA

Abstract BACKGROUND DNA methylation profiling has become an important diagnostic and exploratory tool in neuro-oncology. Intra-tumoral molecular heterogeneity is a crucial factor in the treatment resistance of IDH-wildtype glioblastoma (GBM). However, the intra-tumoral heterogeneity of methylation profiles in GBM remains poorly elucidated. This study aimed to investigate the intra-tumoral heterogeneity of DNA methylation subclasses and deconvolve methylation profiles to infer the cellular composition of the tumor. METHODS We conducted genome-wide DNA methylation analysis and applied the DKFZ/Heidelberg CNS tumor classifier to FFPE tissue samples from a multi-sampling cohort with multiple samples per patient and a single-sampling cohort with one sample per patient. Only samples classified as GBM were included. We conducted two different methylation-based deconvolution analyses. Deconvolution 1 inferred the fractions of tumor subtypes (RTK_I, RTK_II, MES_TYP, and MES_ATYP) and cell types in the microenvironment. Deconvolution 2 estimated the abundance of malignant cell states (stem-like and differentiated cell components) and cell types in the microenvironment. RESULTS The multi-sampling cohort included 32 patients with 113 samples, and the single-sampling cohort included 87 patients with 87 samples. In the multi-sampling cohort, 8 patients (25%) exhibited intra-patient heterogeneity in methylation subclasses across their samples. Deconvolution 1 indicated that each tumor subclass component was heterogeneously distributed within samples, and the abundance of the myeloid cell component correlated with the MES_TYP component across samples. Deconvolution 2 similarly revealed heterogeneity in the immune component abundance across samples within patients. Integrating the results of Deconvolution 1 and Deconvolution 2 using the entire cohort revealed significant correlations between RTK_I and stem-like, RTK_II and differentiated, and MES_TYP and immune components. These findings were also replicated in TCGA dataset. CONCLUSIONS Our findings underscore the importance of considering intra-tumoral heterogeneity in methylation profiles and the biological characteristics of each methylation subclass in developing novel GBM therapies.

Spatial Transcriptome-Wide Profiling of Small Cell Lung Cancer Reveals Intra-Tumoral Molecular and Subtype Heterogeneity.

Small cell lung cancer (SCLC) is a highly aggressive malignancy characterized by rapid growth and early metastasis and is susceptible to treatment resistance and recurrence. Understanding the intra-tumoral spatial heterogeneity in SCLC is crucial for improving patient outcomes and clinically relevant subtyping. In this study, a spatial whole transcriptome-wide analysis of 25 SCLC patients at sub-histological resolution using GeoMx Digital Spatial Profiling technology is performed. This analysis deciphered intra-tumoral multi-regional heterogeneity, characterized by distinct molecular profiles, biological functions, immune features, and molecular subtypes within spatially localized histological regions. Connections between different transcript-defined intra-tumoral phenotypes and their impact on patient survival and therapeutic response are also established. Finally, a gene signature, termed ITHtyper, based on the prevalence of intra-tumoral heterogeneity levels, which enables patient risk stratification from bulk RNA-seq profiles is identified. The prognostic value of ITHtyper is rigorously validated in independent multicenter patient cohorts. This study introduces a preliminary tumor-centric, regionally targeted spatial transcriptome resource that sheds light on previously unexplored intra-tumoral spatial heterogeneity in SCLC. These findings hold promise to improve tumor reclassification and facilitate the development of personalized treatments for SCLC patients.

Integrative multi-region molecular profiling of primary prostate cancer in men with synchronous lymph node metastasis

Localized prostate cancer is frequently composed of multiple spatially distinct tumors with significant inter- and intra-tumoral molecular heterogeneity. This genomic diversity gives rise to many competing clones that may drive the biological trajectory of the disease. Previous large-scale sequencing efforts have focused on the evolutionary process in metastatic prostate cancer, revealing a potential clonal progression to castration resistance. However, the clonal origin of synchronous lymph node (LN) metastases in primary disease is still unknown. Here, we perform multi-region, targeted next generation sequencing and construct phylogenetic trees in men with prostate cancer with synchronous LN metastasis to better define the pathologic and molecular features of primary disease most likely to spread to the LNs. Collectively, we demonstrate that a combination of histopathologic and molecular factors, including tumor grade, presence of extra-prostatic extension, cellular morphology, and oncogenic genomic alterations are associated with synchronous LN metastasis.

Development of Personalized Strategies for Precisely Battling Malignant Melanoma.

Melanoma is the most severe and fatal form of skin cancer, resulting from multiple gene mutations with high intra-tumor and inter-tumor molecular heterogeneity. Treatment options for patients whose disease has progressed beyond the ability for surgical resection rely on currently accepted standard therapies, notably immune checkpoint inhibitors and targeted therapies. Acquired resistance to these therapies and treatment-associated toxicity necessitate exploring novel strategies, especially those that can be personalized for specific patients and/or populations. Here, we review the current landscape and progress of standard therapies and explore what personalized oncology techniques may entail in the scope of melanoma. Our purpose is to provide an up-to-date summary of the tools at our disposal that work to circumvent the common barriers faced when battling melanoma.

Abstract 3764: Spatially resolved immune landscape revealed sex-biased T-cell infiltration in glioblastoma

Abstract Glioblastoma (GBM) multiforme is the most aggressive type of brain cancer. These lethal brain tumors are characterized by the inter- and intra-tumor molecular heterogeneity and demonstrated cell plasticity. A male:female distribution of 1.6:1; survival outcome from treatment (debulking, radiation, and temozolomide) benefits females nearly twice that for males. Through spatial transcriptomics, we interrogated the immune landscape of GBM, seeking to tease out whether distinct biological and therapeutic niches in GBM were evident, and to understand how the tumor microenvironments contributed to the heterogeneity of GBM. We designed a set of RNA hybridization probes specifically for portraying the cell identities and cell functional states within GBM tumor. The probe set was used to profile six human GBM samples from male and female cohorts on the Vizgen MERSCOPE platform. An integrated analysis of 505,614 cells from the six samples yielded a rich and varied spatial cell atlas of glioblastoma. Our preliminary findings depict distinct spatial niches of different tumor cell subpopulations that are associated with local environmental factors such as hypoxia. We identified a small cluster of cells that are in neuronal-like state, which could potentially drive invasion. We found spatial proximity of CD4+ cells and cells that express HIF1A, suggesting the dynamic interactions between tumor cells, regulatory T cells and tumor microenvironment. We also observed significant difference in the degree of CD8+ T-cell infiltration in female samples versus male samples. The average CD4+/CD8+ T-cell ratio in males is twice as high as that of females, suggesting intrinsic sex-based differences in immune response to tumor. Expansion of these studies in additional specimens will further illuminate microenvironmental influences on glioma progression and may instruct specific interventions leading to more effective and predictable immune-oncology of this disease. Citation Format: Yue Hao, George Reid, Angela Baker, Karen L. Fink, George J. Snipes, Bruce E. Mickey, Andrew E. Sloan, Jill S. Barnholtz-Sloan, Michael Berens. Spatially resolved immune landscape revealed sex-biased T-cell infiltration in glioblastoma [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 3764.

Development of a stemness-related prognostic index to provide therapeutic strategies for bladder cancer

Bladder cancer (BC) is a heterogeneous disease with varying clinical outcomes. Recent evidence suggests that cancer progression involves the acquisition of stem-like signatures, and assessing stemness indices help uncover patterns of intra-tumor molecular heterogeneity. We used the one-class logistic regression algorithm to compute the mRNAsi for each sample in BLCA cohort. We subsequently classified BC patients into two subtypes based on 189 mRNAsi-related genes, using the unsupervised consensus clustering. Then, we identified nine hub genes to construct a stemness-related prognostic index (SRPI) using Cox regression, LASSO regression and Random Forest methods. We further validated SRPI using two independent datasets. Afterwards, we examined the molecular and immune characterized of SRPI. Finally, we conducted multiply drug screening and experimental approaches to identify and confirm the most proper agents for patients with high SRPI. Based on the mRNAsi-related genes, BC patients were classified into two stemness subtypes with distinct prognosis, functional annotations, genomic variations and immune profiles. Using the SRPI, we identified a specific subgroup of BC patients with high SRPI, who had a poor response to immunotherapy, and were less sensitive to commonly used chemotherapeutic agents, FGFR inhibitors, and EGFR inhibitors. We further identified that dasatinib was the most promising therapeutic agent for this subgroup of patients. This study provides further insights into the stemness classification of BC, and demonstrates that SRPI is a promising tool for predicting prognosis and therapeutic opportunities for BC patients.

Intra-tumoral molecular heterogeneity of grade 3 astrocytomas and oligodendrogliomas and its significance in disease prognosis

Introduction. Malignant brain tumors, such as anaplastic astrocytomas and anaplastic oligodendrogliomas grade 3, are characterized by high aggressiveness and pose a serious clinical problem. This study focuses on assessing intratumoral heterogeneity in anaplastic astrocytomas and anaplastic oligodendrogliomas and its impact on disease prognosis.Aim. To study characteristics of intratumoral heterogeneity, in particular such morphological criteria as necrosis, vascular proliferation, mitoses, and mutations in the most significant for glioma progression genes in the groups of grade III astrocytomas and oligodendrogliomas, as well as analysis of prognostic significance of these parameters.Materials and methods. The study included 389 patients with IDH-mutant astrocytomas and 200 patients with oligodendrogliomas. The mean Ki-67 labeling index of astrocytomas was 12.78 %, while that of oligodendrogliomas was 8.54 %.Results. The presence of vascular proliferation, necrosis, of more than 20 % of the area of the specimen occupied by sarcomatous-like areas and the number of mitoses significantly affected not only disease-free survival but also overall survival of patients. In the clinical setting, mutations in the TERT promoter gene, amplification and mutation of the EGFR gene, deletion of the CDKN2A gene, and TP53 gene had a significant negative impact on recurrence-free and overall survival.Conclusion. The results of single-cell RNA sequencing showed additional factors, including sarcomatous-like areas, as well as TERT, EGFR, CDKN2A and TP53 mutations, in the progression of the tumors under consideration and in ensuring an increase in their malignant potential.

Chimeric Antigen Receptor-T Cell and Oncolytic Viral Therapies for Gastric Cancer and Peritoneal Carcinomatosis of Gastric Origin: Path to Improving Combination Strategies

Precision immune oncology capitalizes on identifying and targeting tumor-specific antigens to enhance anti-tumor immunity and improve the treatment outcomes of solid tumors. Gastric cancer (GC) is a molecularly heterogeneous disease where monoclonal antibodies against human epidermal growth factor receptor 2 (HER2), vascular endothelial growth factor (VEGF), and programmed cell death 1 (PD-1) combined with systemic chemotherapy have improved survival in patients with unresectable or metastatic GC. However, intratumoral molecular heterogeneity, variable molecular target expression, and loss of target expression have limited antibody use and the durability of response. Often immunogenically “cold” and diffusely spread throughout the peritoneum, GC peritoneal carcinomatosis (PC) is a particularly challenging, treatment-refractory entity for current systemic strategies. More adaptable immunotherapeutic approaches, such as oncolytic viruses (OVs) and chimeric antigen receptor (CAR) T cells, have emerged as promising GC and GCPC treatments that circumvent these challenges. In this study, we provide an up-to-date review of the pre-clinical and clinical efficacy of CAR T cell therapy for key primary antigen targets and provide a translational overview of the types, modifications, and mechanisms for OVs used against GC and GCPC. Finally, we present a novel, summary-based discussion on the potential synergistic interplay between OVs and CAR T cells to treat GCPC.

NIMG-83. ELUCIDATING INTRA-TUMORAL HETEROGENEITY AND DISTINCT RADIOMIC FEATURES IN GLIOBLASTOMA METHYLATION SUBCLASSES

Abstract Glioblastoma, IDH-wildtype (GBM), is characterized by the inter- and intra-tumoral molecular heterogeneity. Genome-wide DNA methylation profiling has recently emerged as a promising tool offering complementary value to the classification of central nervous system tumors. In adult GBM patients, the most common methylation subclasses comprise RTK I, RTK II, and MES. We hypothesize that quantification of intricate and spatially complex radiomic features extracted from multi-parametric MRI (mpMRI) is informative to non-invasively determining characteristics of GBM methylation subclasses and their heterogeneity. In this study, mpMRI scans (T1, T1-Gd, T2, T2-FLAIR, DSC, DTI) of newly diagnosed 23 GBM patients were retrospectively collected. We derived 6339 radiomic features, including histograms, morphologic and textural descriptors. For each case, 3-4 multiple samplings from different parts of the tumor were conducted. DNA was extracted from FFPE for each of sample and analyzed for genome-wide DNA methylation patterns using the Illumina EPIC array. Classification of methylation subclasses was performed using the MNP brain tumor classifier v12b6 of the DKFZ. Analysis of variance (ANOVA) with Bonferroni correction was employed to extract subclass-specific radiomic features. Of the 23 patients, 7 indicated intra-tumoral heterogeneity in methylation subclasses. We identified 68 radiomic features (p< 0.05) and 12 radiomic features (p< 0.01) that showed statistically significant differences among the methylation subclasses as determined by ANOVA with Bonferroni correction. A heatmap illustrating the relationships between subclasses and extracted radiomic features displayed distinct trends among subclasses and between heterogeneous and homogeneous cases within the same subclass. Our findings suggest the presence of heterogeneity within methylation subclasses and distinctive imaging patterns for each subclass. These findings potentially pave the way for a more personalized approach to glioblastoma management, highlighting the importance of further validation through the analysis of additional cases.

Transcriptomic Profiling of Upper Tract Urothelial Carcinoma: Bladder Cancer Consensus Classification Relevance, Molecular Heterogeneity, and Differential Immune Signatures

Analyses of large transcriptomics data sets of muscle-invasive bladder cancer (MIBC) have led to a consensus classification. Molecular subtypes of upper tract urothelial carcinomas (UTUCs) are less known. Our objective was to determine the relevance of the consensus classification in UTUCs by characterizing a novel cohort of surgically treated ≥pT1 tumors. Using immunohistochemistry (IHC), subtype markers GATA3-CK5/6-TUBB2B in multiplex, CK20, p16, Ki67, mismatch repair system proteins, and PD-L1 were evaluated. Heterogeneity was assessed morphologically and/or with subtype IHC. FGFR3 mutations were identified by pyrosequencing. We performed 3’RNA sequencing of each tumor, with multisampling in heterogeneous cases. Consensus classes, unsupervised groups, and microenvironment cell abundance were determined using gene expression. Most of the 66 patients were men (77.3%), with pT1 (n = 23, 34.8%) or pT2-4 stage UTUC (n = 43, 65.2%). FGFR3 mutations and mismatch repair–deficient status were identified in 40% and 4.7% of cases, respectively. Consensus subtypes robustly classified UTUCs and reflected intrinsic subgroups. All pT1 tumors were classified as luminal papillary (LumP). Combining our consensus classification results with those of previously published UTUC cohorts, LumP tumors represented 57.2% of ≥pT2 UTUCs, which was significantly higher than MIBCs. Ten patients (15.2%) harbored areas of distinct subtypes. Consensus classes were associated with FGFR3 mutations, stage, morphology, and IHC. The majority of LumP tumors were characterized by low immune infiltration and PD-L1 expression, in particular, if FGFR3 mutated. Our study shows that MIBC consensus classification robustly classified UTUCs and highlighted intratumoral molecular heterogeneity. The proportion of LumP was significantly higher in UTUCs than in MIBCs. Most LumP tumors showed low immune infiltration and PD-L1 expression and high proportion of FGFR3 mutations. These findings suggest differential response to novel therapies between patients with UTUC and those with MIBC.

SYST-27 INTERROGATION OF THE TUMOR IMMUNE MICROENVIRONMENT REVEALS DISTINCT IMMUNOSUPPRESSIVE LANDSCAPES IN GLIOBLASTOMA

Abstract High-resolution sequencing technologies have revealed significant inter-and intra-tumoral molecular heterogeneity in glioblastoma (GBM), leading to an urgent need for novel targeted therapies. Our research using representative murine GBM models and various experimental techniques has shown that classical GBMs (e.g., EGFRvIII+, TIMElow) and mesenchymal GBMs (e.g., NF1ko/PTENko/p53ko, TIMEhigh) are both immunosuppressive but in distinct ways. TIMElow GBMs have a more impaired and less functional tumor vasculature, resulting in low infiltration of T cells with anergic features. TIMEhigh GBMs have a more intact BBB revealing overall more adaptive and innate immune cell infiltrates, but with highly dysfunctional T cells and immunosuppressive TME. Congruently, GSEA analysis of both human and murine GBM scRNA-seq data demonstrated enriched immunosuppressive signatures in the myeloid cell populations of TIMEhigh GBM compared to TIMElow GBM. Our findings have also revealed potential adaptive and intrinsic resistant mechanisms to antiangiogenic immunotherapy in TIMElow and TIMEhigh GBMs, respectively, with TIMElow GBMs exhibiting a transitory response to the treatment, while TIMEhigh GBMs being intrinsically resistant due to their intact tumor vasculature and reliance on dysfunctional T cells. We then tested the efficacy of different immunotherapies, including dendritic cell vaccination, a CD40 agonist, and a myeloid cell PI3K activity inhibitor in TIMElow and TIMEhigh tumors. Surprisingly, our results revealed that the response to these treatments can be either beneficial or detrimental and may depend on factors such as tumor antigenicity and TIME subtype. Overall, our study provides new insights into the intricate immune landscape of GBMs, emphasizes the importance of considering tumor subtypes as they may lead to potential unintended consequences of immunotherapies.

The circadian clock circuitry deconvolutes colorectal cancer and lung adenocarcinoma heterogeneity in a dynamic time-related framework.

Increasing evidence imputes cancer progression and resistance to therapy to intra-tumor molecular heterogeneity set off by cancer cell plasticity. Re-activation of developmental programs strictly linked to epithelial-to-mesenchymal transition and gaining of stem cells properties are crucial in this setting. Many biological processes involved in cancer onset and progression show rhythmic fluctuations driven by the circadian clock circuitry. Novel cancer patient stratification tools taking into account the temporal dimension of these biological processes are definitely needed. Lung cancer and colorectal cancer (CRC) are the leading causes of cancer death worldwide. Here, by developing an innovative computational approach we named Phase-Finder, we show that the molecular heterogeneity characterizing the two deadliest cancers, CRC and lung adenocarcinoma (LUAD), rather than a merely stochastic event is the readout of specific cancer molecular states which correlate with time-qualified patterns of gene expression. We performed time-course transcriptome analysis of CRC and LUAD cell lines and upon computing circadian genes expression-based correlation matrices we derived pseudo-time points to infer time-qualified patterns in the transcriptomic analysis of real-world data (RWD) from large cohorts of CRC and LUAD patients. Our temporal classification of CRC and LUAD cohorts was able to effectively render time-specific patterns in cancer phenotype switching determining dynamical distribution of molecular subtypes impacting patient prognosis.

Pacpaint: a histology-based deep learning model uncovers the extensive intratumor molecular heterogeneity of pancreatic adenocarcinoma

Two tumor (Classical/Basal) and stroma (Inactive/active) subtypes of Pancreatic adenocarcinoma (PDAC) with prognostic and theragnostic implications have been described. These molecular subtypes were defined by RNAseq, a costly technique sensitive to sample quality and cellularity, not used in routine practice. To allow rapid PDAC molecular subtyping and study PDAC heterogeneity, we develop PACpAInt, a multi-step deep learning model. PACpAInt is trained on a multicentric cohort (n = 202) and validated on 4 independent cohorts including biopsies (surgical cohorts n = 148; 97; 126 / biopsy cohort n = 25), all with transcriptomic data (n = 598) to predict tumor tissue, tumor cells from stroma, and their transcriptomic molecular subtypes, either at the whole slide or tile level (112 µm squares). PACpAInt correctly predicts tumor subtypes at the whole slide level on surgical and biopsies specimens and independently predicts survival. PACpAInt highlights the presence of a minor aggressive Basal contingent that negatively impacts survival in 39% of RNA-defined classical cases. Tile-level analysis ( > 6 millions) redefines PDAC microheterogeneity showing codependencies in the distribution of tumor and stroma subtypes, and demonstrates that, in addition to the Classical and Basal tumors, there are Hybrid tumors that combine the latter subtypes, and Intermediate tumors that may represent a transition state during PDAC evolution.

3D open-top light-sheet microscopy and 3D microdissection of neuoadjuvant-treated primary prostate cancer reveals latent subclonal mutations.

e17109 Background: Intratumoral molecular heterogeneity is a well described phenomenon in primary prostate cancer. Increased genomic heterogeneity is associated with more aggressive clinical behavior, including recurrence and metastasis. However, current methods to characterize heterogeneity suffer from tradeoffs between generating high quality morphologic information, correlating morphology with genomic alterations, and workflow considerations. We describe a technology to image prostate samples in 3D, perform 3D microdissection of regions of interest (ROIs), and preserve nucleic acids for DNA sequencing. Methods: Samples (N = 18) were obtained from patients (N = 12) enrolled in an open-label, single-site, Phase II neoadjuvant trial in men with NCCN high to very-high risk PC. Patients received 12 weeks of apalutamide, abiraterone acetate plus prednisone, degarelix, and indomethacin followed by radical prostatectomy (RP). Fresh frozen prostate samples (~2x2x0.4cm) were obtained from RP specimens. Frozen samples were fixed in an ethanol-based fixative, stained with nuclear (TOPRO-3) and general protein (eosin) fluorescent dyes, cleared with ethyl cinnamate, and imaged using 3D open-top light-sheet (OTLS) fluorescence microscopy. Image-guided 3D microdissection was performed on ROIs with distinct morphologies. Microdissected ROIs measured 0.5x0.5x2mm. Microdissected samples were sent for DNA extraction and sequencing using the comprehensive clinically-validated UW-OncoPlex NGS assay. Results: The tissue from neoadjuvant-treated patients contained sparse carcinoma, with cancer volumes ranging from 0.01-0.3 cm2 and cellularity ranging from 2%-30%. Molecular alterations were detected in a sample with only 0.07 cm2 volume of carcinoma with 5% cellularity. The read depth of 3D microdissected samples was 3.9 times greater than the read depth of FFPE samples from the same patients. At least two morphologically distinct ROIs were 3D microdissected from 11 of 12 patients. Four of the 18 samples had molecular alterations that differed between ROIs, i.e. intra-sample molecular heterogeneity. For example, one sample with three microdissected ROIs had a PTEN alteration exclusive to a single ROI. Conclusions: The findings show the potential for 3D microdissection of morphologically distinct subclones in samples from neoadjuvant-treated patient, to enable sequencing of specific cellular populations. The sparsity of carcinoma necessitated a spatially targeted approach for extracting material for sequencing. The increased yield from avoiding FFPE processing and carcinoma enrichment from targeted 3D microdissection of carcinoma ROIs enabled the detection of spatially distinct molecular subclones. Future work will include the analysis of additional samples and implementation of AI-guided ROI detection to streamline workflows.

Abstract 6779: Spatial and single-nucleus transcriptomics of human glioblastoma

Abstract Glioblastoma (GBM) multiforme is the most aggressive type of brain cancer. These lethal brain tumors are characterized by the inter- and intra-tumor molecular heterogeneity and diverse cell plasticity. We sought to interrogate the immune landscape of GBM, tease out the distinct biological and therapeutic niches in GBM and to understand how the tumor microenvironments mediated the heterogeneity of GBM. We have collected six human GBM samples for spatial profiling and single-nucleus RNA sequencing. Multiple sets of spatial gene panels were designed to capture the cell identities (cancer stem cells, astrocytes, oligodendrocytes, microglia, macrophages, endothelial cells, etc.) and the spatially-resolved expression patterns of genes indicative of different functional states. We also aim to find altered neurovascular units by examining the spatial correlation between cells that highly express angiogenesis markers such as VEGFA with tumor-associated macrophages, which could be recruited to the angiogenic niche by GBM tumor cells. From the spatial RNA dataset of the first two samples, we observed close proximity of tumor-associated macrophages and endothelial cells that form the microvasculature. Our preliminary results from the single-nucleus RNA sequencing and spatial transcriptomics of two samples shed light on the complex cell landscape and the dynamic interaction between tumor cells and infiltrating or resident immune cells in the GBM tumor tissue. Citation Format: Yue Hao, Angela Baker, Brian Hilbush, Marcos Otero, Chris Streck, Karen L. Fink, George J. Snipes, Bruce E. Mickey, Michael Berens. Spatial and single-nucleus transcriptomics of human glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6779.

IL-5 Targeted Therapies for Nervous System Tumors – Progress, Pitfalls, and Prospects

Abstract The molecular genetic understanding of nervous system tumors has expanded rapidly offering insight into potentially targetable oncogenic driver alterations. In monogenic tumor susceptibility syndromes such as tuberous sclerosis, neurofibromatosis type 1, and von Hippel Lindau syndrome targeted drugs have demonstrated efficacy and are now approved in the United States for the treatment of subependymal giant cell astrocytoma, plexiform neurofibroma, and hemangioblastoma, respectively. Some genetic alterations like BRAF V600E mutations or neurotrophic receptor tyrosine kinase (NTRK) fusions, occur across multiple cancers, including certain types of gliomas. Dabrafenib in combination with trametinib is approved for use in gliomas that harbor BRAF V600E mutations and larotrectinib is approved in gliomas that harbor certain NTRK fusions. In pediatric low-grade astrocytoma, one of the most common solid tumors of childhood, BRAF truncation-fusion events may render these tumors susceptible to tovorafenib, a type 2 RAF inhibitor, which is under study in clinical trials. Mutations in the isocitrate dehydrogenase (IDH) gene occur in the majority of low-grade and anaplastic gliomas, create specific metabolic vulnerabilities, and several IDH-mutant targeting strategies are under investigation. Glioblastoma is characterized by intratumoral molecular heterogeneity so strategies that target single genetic alterations may not be as effective as in other types of gliomas although a number of novel targeted strategies have been advanced to clinical trials. Other types of nervous system tumors such as medulloblastoma, meningioma, primary central nervous system diffuse large B-cell lymphoma, and craniopharyngioma harbor targetable genetic alterations and clinical trials are ongoing. Finally, metastatic brain tumors may harbor targetable genetic alterations that may differ from the primary site of cancer highlighting the importance of biopsy and molecular analysis of the brain metastases in order to enroll patients in clinical trials of targeted therapies.

Diffuse astrocytoma with mosaic IDH1-R132H-mutant immuno-phenotype and low subclonal allele frequency.

Molecular alterations found in gliomas are now considered entity-defining features. The World Health Organization (WHO) classification system currently classifies the vast majority of gliomas utilizing an integrated genotype-phenotype approach. We present a case of diffuse astrocytoma with a mosaic isocitrate dehydrogenase (IDH)1-R132H-mutant immunophenotype and low subclonal allele frequency. A 35-year-old patient with a history of IDH1-R132H mutated diffuse astrocytoma in 20014 presented to the hospital again in 2019. MRI examination showed a non-enhancing abnormal signal in the periphery of her previous surgical cavity. Histopathological examination revealed that the tumor was hypercellular and without high grade histopathological features. The neoplastic cells were immunohistologically positive for GFAP, Olig2, and ATRX. However, only some scattered tumor cells were positive for IDH1-R132H. Cytogenetic studies revealed a lack of chromosomal 1p/19q co-deletion. Further next-generation sequencing (NGS) demonstrated a low-level IDH1-R132H mutation and allele frequency. Based on these findings, the diagnosis of diffuse astrocytoma with mosaic IDH1- R132H-mutant immunophenotype and low subclonal allele frequency (WHO grade II) was generated. This case indicates that gliomas may have heterogeneous molecular profile and the intra-tumoral molecular heterogeneity highlights the need to further characterize the molecular profile for glioma classification and clinical management.

Modulation of the Tumor Microenvironment with Trastuzumab Enables Radiosensitization in HER2+ Breast Cancer.

Simple SummaryTrastuzumab and radiation are used clinically to treat HER2-overexpressing breast cancers; however, the mechanistic synergy of anti-HER2 and radiation therapy has not been investigated. In this study, we identify that a subtherapeutic dose of trastuzumab sensitizes the tumor microenvironment to fractionated radiation. This results in longitudinal sustained response by triggering a state of innate immune activation through reduced DNA damage repair and increased tumor oxygenation. As positron emission tomography imaging can be used to longitudinally evaluate changes in tumor hypoxia, synergy of combination therapies is the result of both cellular and molecular changes in the tumor microenvironment.DNA damage repair and tumor hypoxia contribute to intratumoral cellular and molecular heterogeneity and affect radiation response. The goal of this study is to investigate anti-HER2-induced radiosensitization of the tumor microenvironment to enhance fractionated radiotherapy in models of HER2+ breast cancer. This is monitored through in vitro and in vivo studies of phosphorylated γ-H2AX, [18F]-fluoromisonidazole (FMISO)-PET, and transcriptomic analysis. In vitro, HER2+ breast cancer cell lines were treated with trastuzumab prior to radiation and DNA double-strand breaks (DSB) were quantified. In vivo, HER2+ human cell line or patient-derived xenograft models were treated with trastuzumab, fractionated radiation, or a combination and monitored longitudinally with [18F]-FMISO-PET. In vitro DSB analysis revealed that trastuzumab administered prior to fractionated radiation increased DSB. In vivo, trastuzumab prior to fractionated radiation significantly reduced hypoxia, as detected through decreased [18F]-FMISO SUV, synergistically improving long-term tumor response. Significant changes in IL-2, IFN-gamma, and THBS-4 were observed in combination-treated tumors. Trastuzumab prior to fractionated radiation synergistically increases radiotherapy in vitro and in vivo in HER2+ breast cancer which is independent of anti-HER2 response alone. Modulation of the tumor microenvironment, through increased tumor oxygenation and decreased DNA damage response, can be translated to other cancers with first-line radiation therapy.

Abstract P1-05-02: Intratumor molecular tumor heterogeneity in low ER-expressing primary breast tumors

Abstract Background: Change in estrogen receptor (ER) status between primary breast cancer and distant recurrence are seen in the clinic in up to 15-20% of patients. This is difficult to reconcile with the current understanding of breast cancer molecular subtypes, the large-scale molecular differences between ER-positive (ER+) and ER-negative (ER-) cancers suggest different cellular origins, luminal versus basal breast epithelium, respectively. A potential explanation for ER status switch is the presence of mixed molecular subtypes at diagnosis. ER+ cancers with less than 100% positivity may be composed by both luminal and basal-like cancer cells, and a recurrence might arise from one subtype that survived adjuvant therapy. The goal of this study was to test if molecular subtype heterogeneity exists at diagnosis in less than 100% ER+ breast cancer using the NanoString GeoMx™ platform. Methods: GeoMx™ is a highly multiplexed assay that quantifies RNA expression from spatially discrete regions of interest (ROIs) within formalin fixed paraffin embedded (FFPE) tissue sections. We identified 4 cancers with 30-40% ER-positivity on routine immunohistochemistry (IHC) staining (clone SP1). Eight ROIs per case were selected to represent both ER-high and -low regions of the section using ER IHC (clone 1D5). Invasive tumor cells were defined as PanCK positive cells. 1,825 mRNA species were measured separately in each ROI. mRNA expression results (unique molecular index [UMI] counts) were quantile normalized and differential expression analyses for all genes, ESR1, ER-regulated gene set, and PAM50 gene set were performed between ROIs within the same cancer. We also assessed PAM50 subtypes of each cases on bulk RNA using NanoString BC360 panel. Results: Three of the 4 cases had heterogenous ER IHC (1D5) staining; the fourth case was uniformly ER-negative during ROI selection. For this last case, ROIs were selected based on PanCK staining from different locations in the cancer. Bulk PAM50 subtyping indicated 1 basal-like, 2 HER2-enriched (HER2-E), and 1 luminal (lum)A cancer. We also attempted ROI-level subtyping; however, Pearson correlations to the nearest centroid were low (<0.5) for all ROIs, possibly due to low expression of PAM50 genes or to the exploratory methodology used. There was substantial within cancer, between ROI, expression heterogeneity for many genes including ESR1 and sensitivity to endocrine therapy (SET) index genes. Conclusions: ER- and ER+ cells are intermixed which makes defining low and high ER regions challenging. We observed region to region variation in ESR1 and SET index gene expression. ROI-level PAM50 subtyping was unstable. The novel NanoString GeoMx™ DSP technology can be used to study intratumor molecular heterogeneity in regions of interest on FFPE breast cancer tissue sections. We found substantial region-to-region gene expression differences within tissue sections. Case ID1234ER IHC SP130%40%40%30%ER IHC 1D50%40%40%30%Bulk PAM50 SubtypeBasalHER2-ELumAHER2-EESR1 UMI average (range across ROIs)28.45 (22.4-34.6)64.9 (18.8-173)179.9 (114-245)34.8 (25.1-45.4)SET Index (genes positively correlated with ESR1) UMI average (range across ROIs)41.5 (39.1-44.8)120.1 (86.9-182.9)94.9 (72.9-118.4)143.5 (124.9-150.3)SET Index (genes negatively correlated with ESR1) UMI average (range across ROIs)57.6 (45-75.3)43.4 (38.8-52.6)33.7 (31.8-36.7)44.8 (41.4-50.6) Citation Format: Julia Foldi, Emily Reisenbichler, Liuliu Pan, Krsitina Sorg, Sarah E. Church, Lajos Pusztai. Intratumor molecular tumor heterogeneity in low ER-expressing primary breast tumors [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P1-05-02.