10X Genomics Research Articles

Abstract 2780: Induced pluripotent stem cell (iPSC) based vaccines potentializes anti-CTLA4 immune response in a murine lung carcinoma model

Abstract Despite the development of new immunotherapy strategies, lung cancer remains the leading cause of cancer-related deaths. One of the reasons is attributed to the persistence of cancer stem cells (CSCs) within the tumor, contributing to drug resistance, dormancy and metastatic spread. To eradicate CSCs, iPSC-based vaccination represents a novel approach based on the paradigm that CSCs and iPSCs share common tumor associated antigens (TAAs) with the ability to elicit a strong anti-tumor immune response.We previously showed that induced allogeneic pluripotent stem cells (miPSCs), combined with a histone deacetylase inhibitor (HDACi), induced a major reduction of tumor growth and metastatic spread to lungs in an aggressive triple negative breast cancer model (4T1) in syngeneic mice. We report here the use of the same protocol in a lung carcinoma model using LLC1 cell line in combination with an anti-CTLA4 antibody. We compared the effectiveness of allogenic miPSCs treatment alone or with an anti-CTLA4 mouse antibody on mice-bearing LLC1-Luc tumors (mean+se: 17,5+0,6 mm3). Five mice received 5 subcutaneous (SC) injection of 2 × 106 miPSCs, 5 mice received 3 intraperitoneal injections of anti-CTLA4 antibody at 5mg/kg and 5 mice were treated with the combinatory regimen (miPSCs and anti- CTLA4) with the same doses. In addition, all treated mice received a HDACi in the drink water throughout the experience.After 24 days, all tumor volumes from the 3 groups were significantly reduced compared to the control mice receiving only PBS. We obtained a reduction of 72% (p=0.007) and 74% (p=0.009) respectively for the mice treated solely with miPSCs or anti-CTLA4. An important synergic effect was obtained for the mice treated with miPSCs and anti- CTLA4 with a reduction of the tumor size by 92% (p=0.005) compared to the control mice. We also found a significant inhibition of metastatic spread to lungs for the 3 groups that was more pronounced in mice receiving the combination treatment with a significant reduction of 91 % compared to the control group. All these therapeutic effects were correlated with a significant increase of CD4+ and CD8+ cells that was more pronounced in mice receiving the combinatory regimen.We also have performed single-cell RNA sequencing analysis (10x Genomics) of LLC1 tumors treated with miPSCs and anti- CTLA4 compared to mice treated with monotherapy and untreated mice. T-distributed stochastic neighbor embedding plot reveals distinct clusters of stromal and immune cells across tumors with a significant upregulation of CD8+ and CD4+ T cells in mice receiving the combinatory regimen.Overall, these results demonstrate for the first time the clinical relevance of using an off-the-shelf allogeneic iPSC-based vaccine combined with an anti-CTLA4 antibody as a new anti-cancer immunotherapy strategy against aggressive non-small cell lung cancer (NSCLC) with metastatic potential. Citation Format: Frank Griscelli, Diana Chaker, Noufissa Oudrhiri, Christophe Desterke, Ali G. Turhan, Annelise Bennaceur Griscelli. Induced pluripotent stem cell (iPSC) based vaccines potentializes anti-CTLA4 immune response in a murine lung carcinoma model [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 2780.

Abstract 2927: Optimization of sample preparation for single-cell RNA-sequencing using accumulated collection of preclinical and clinical specimens

Abstract Background: The heterogeneity of tumors became apparent with the introduction of single-cell RNA-sequencing technology, enabling the discovery of rare and novel cell types that were not attainable with bulk RNA-sequencing. Numerous papers have been published, and the data from single-cell RNA-sequencing are publicly available. While current literatures provide detailed guidance on effectively analyzing single-cell RNA sequencing data, documentation for sample preparations is less frequently reported in easily accessible protocols. Additionally, researchers hold diverse opinions on sample handling and practical information is scattered across multiple sources. Method: A total of 233 cases were included in the study, comprising 150 cases of clinical and 83 cases of preclinical samples. Among the 150 clinical samples, 58 were freshly obtained (32 biopsies and 26 surgical resections), and 92 were frozen. Of the 83 preclinical samples, 70 were fresh, and 13 were frozen. Sample preparations for 10X Genomics Chromium single-cell RNA-sequencing were carried out using the methods of 'Red blood cell lysis', 'Straining', and 'Dead cell removal using magnetic beads' with clinical specimens. Each method was applied based on specific situations involving the presence of red blood cells, cell aggregates, dead cells and debris. Results: There was a variation in the usage of red blood cell lysis, straining, and dead cell removal methods across different sample types. Specifically, 40.6% of clinical biopsy samples were primarily conducted with red blood cell lysis and/or straining without the removal of dead cells. Whereas, 96.2% of clinical surgical resections and 100% of clinical frozen samples predominantly utilized dead cell removal. The frequency of a double application of dead cell removal was higher in frozen samples, at 34.8% due to low viability as expected. For surgical resections, in comparison, only 15.4% required a second round of dead cell removal. In preclinical samples, both fresh and frozen, removal of dead cells was essential and implemented in 100% of cases. Among these, 62.9% of the fresh preclinical samples and 76.9% of the frozen preclinical samples underwent a second round of dead cell removal. Conclusions: The utilization of the methods red blood cell lysis, straining, and dead cell removal proved to be adequate in meeting the stipulated criteria of the 10x Genomics guidelines, demonstrating efficiency in terms of time. We have outlined a workflow for each sample type, accompanied by images illustrating pre- and post-conditions for plausible occurrences. Additionally, approximate cell numbers required, or percentages of cell loss are provided for each situation. We anticipate that this protocol will be beneficial for those new to the field, enabling them to generate samples for single-cell RNA-sequencing independently. Citation Format: Kyumin Lim, JuHyeon Lee, Kyoung-Ho Pyo, Byoung Chul Cho. Optimization of sample preparation for single-cell RNA-sequencing using accumulated collection of preclinical and clinical specimens [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 2927.

Abstract 6930: Spatial analysis of multi-ancestral tumors to understand how intercellular signaling impacts tumor invasion

Abstract Colorectal cancer (CRC) persists as a leading cause of cancer-related deaths in the United States. Intratumoral heterogeneity stems from a multi-ancestral origin or clonal divergence and contributes to treatment resistance. Unfortunately, tumors in existing mouse models are largely homogenous, rendering predictions of drug efficacy inaccurate. To investigate whether signaling between distinct neoplastic clones in a tumor and cells in the surrounding microenvironment impacts CRC biology, we performed spatial transcriptomic analysis on samples collected from a transgenic mouse model previously established in the Halberg laboratory. This model (referred to as B6.FCTG3KM) develops three types of tumors: homotypic Adenomatous Polyposis Coli (APC)-deficient tumors that express red fluorescent protein (RFP), homotypic APC-deficient tumors that express constitutively active phosphoinositide 3-kinase (PI3K) and green fluorescent protein (GFP), and heterotypic tumors. Previous characterization of the model clearly demonstrated that heterotypic tumors are significantly more aggressive than either type of homotypic tumor. Analysis was conducted on four serially sectioned slides containing three tumors and adjacent normal tissue obtained from the colon of a male B6.FCTG3KM mouse using the 10x Genomics Visium CytAssist platform with the mouse whole transcriptome probe set. Collected tumors were staged using traditional histopathology techniques by a board-certified pathologist (Matkowskyj). Immunohistochemistry and immunofluorescence were used to assess β-catenin localization and to re-probe for RFP and GFP expression. Sequencing was performed on the Illumina NovaSeqX platform to an average depth of 255,528,294 reads per sample. Data analysis was performed using the 10x Genomics SpaceRanger and Kendziorski laboratory R/SpatialView packages. A fold-change threshold of 1.5 and an adjusted p-value threshold of 0.05 were used when establishing marker genes for each of the 8 clusters identified. One distinct cluster was identified by marker genes including Notum, Wif1, and Dkk2, factors previously implicated in CRC tumorigenesis, and corresponded to the center of each region of surface-level dysplastic epithelia. The remainder of the surface-level dysplastic epithelia corresponded to a second cluster, with marker genes including those coding for TRIM family proteins (Trim5, Trim10, Trim40, Trim12c), and matrix metalloproteinases (Mmp12, Mmp9, Mmp10, Mmp13). A third cluster corresponded to the desmoplastic stroma underlying each neoplasm. Ongoing analyses are underway to identify clonal interactions that alter gene expression and tumor aggressiveness. Citation Format: Mary M. Stangis, Lingxin Cheng, Dawn Albrecht, Santina Snow, Tessa Wirtz, Kristina A. Matkowskyj, Huy Q. Dinh, Christina Kendziorski, Richard B. Halberg. Spatial analysis of multi-ancestral tumors to understand how intercellular signaling impacts tumor invasion [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 6930.

Abstract 1142: Spatial decomposition of lung adenocarcinoma expression subtypes reveals tumor microenvironment characteristics

Abstract The expression subtypes of lung adenocarcinoma (LUAD) capture tumors with distinct pathway activity, mutations and histopathology and also differentiate clinical outcomes. The microenvironments of these subtypes, proximal-inflammatory (PI), proximal-proliferative (PP), and terminal respiratory unit (TRU), have been described generally as immune hot, immune moderate and immune cold, respectively, but otherwise have not been analyzed at high resolution. Here, we aimed to characterize and compare tumor microenvironments between LUAD subtypes. Using spatially barcoded arrays and cDNA libraries (10x Genomics), we sequenced the spatial transcriptomes of a 6.5mm2 plane of 14 LUAD tumors from the Applied Proteogenomics and Organizational Learning Outcomes (APOLLO) program. Spatial transcriptomes had a median of 3,560 spots and a median of 4,026 genes detected per spot. First, collapsing the spatial array to a bulk measurement per sample, we applied our published expression subtype predictor classifying 4 PI, 5 PP, and 5 TRU cases. We then decomposed each tumor’s spatial expression profile by unsupervised clustering, followed by signature scoring and collapsing into tumor, immune, and stroma tumor microenvironment (TME) components. Twelve of the fourteen tumors harbored multiple components while two tumors had one component. The region areas of TME components showed trends among the subtypes, with PI having the greatest immune area and PP having the greatest tumor area. Within each tumor, we calculated differentially-expressed genes between each TME component. Comparing TME genes to the subtype predictor genes, we found significant overlap (chi-square p << 0.001). This indicates that genes that are variable among bulk tumors also have variability within tumors. We then predicted expression subtype for decomposed compartments. Five tumors had the same expression subtype across their TME components, which we refer to as single subtype tumors. However, six tumors had more than one expression subtype prediction among the tumor’s TME components, which we call ‘multi-subtype tumors’. Multi-subtype tumors had lower bulk subtype prediction scores than single-subtype tumors (p < 0.01), indicating that the TME diversity among tumors affects the bulk expression subtype. Interestingly, the six multi-subtype tumors were in the PP and PI subtypes, suggesting greater TME component diversity than TRU. Calculating the spatial compactness of the tumors through continuity indices, we found that PI subtype trended with greater intermixing of TME components. In summary, the bulk LUAD expression subtypes capture differences between tumors and within tumors related to the tumor microenvironment. The views expressed in this abstract are solely of the authors and do not reflect the official policy of the Departments of Army/Navy/Air Force, Department of Defense, USUHS, HJF, or U.S. Government. Citation Format: Shaoqiu He, Camille Alba, Savannah Kounelis-Wuillaume, Teri J. Franks, Martin L. Doughty, Robert F. Browning, Craig D. Shriver, Clifton L. Dalgard, APOLLO Research Network, Matthew D. Wilkerson. Spatial decomposition of lung adenocarcinoma expression subtypes reveals tumor microenvironment characteristics [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 1142.

Abstract 4343: Revealing ovarian cancer copy number variation in single cells

Abstract The mortality rate associated with ovarian cancer (OvCa) is disproportionately high in comparison to its incidence rate. This is partly due to the heterogeneous nature of the disease, which reduces treatment efficacy and contributes to high rates of relapse and chemotherapy resistance. Most OvCa are epithelial in origin and can be classified into four main subtypes: serous, mucinous, endometrioid, and clear cell. Of these, high grade serous ovarian cancer (HGSOC) is the deadliest. Epithelial ovarian carcinomas (EOC) typically exhibit widespread chromosomal and arm-level copy number abnormalities across most of the genome; in HGSOC, focal amplifications and microdeletions are especially prevalent and indicative of high genomic instability. To understand the heterogeneity of aneuploidy in EOC and HGSOC, we performed shallow single-cell whole genome sequencing on four EOC samples: two HGSOC, one clear cell, and one mixed clear cell and endometrioid. All samples were late stage and treatment naïve, and one sample had a known BRCA2 mutation. Sequencing data was processed by two complementary methods to call copy number alterations. First, we used the Cell Ranger DNA pipeline (10x Genomics) to align cell-identified sequencing reads to human reference genome GRCh38 for coverage-based copy number estimation. Resulting copy number calls were cleaned up for mappability, quality, and noisiness. Each sample was then subject to clustering and subclustering analysis using maximum likelihood genetic clustering algorithms. All samples exhibited a high level of aneuploidy, including characteristic alterations known to be associated with EOC. Two tumors contained readily distinguishable clonal populations, and all samples contained main tumor clones that could be further divided by unique subclonal characteristics. Evidence of polyploidy was also seen in all four specimens, with some tumor clusters exhibiting triploid and tetraploid baselines. In parallel, sequencing data was analyzed by the Copy-number Haplotype Inference in Single-cell by Evolutionary Links (CHISEL) algorithm. CHISEL utilizes both binned read depth ratio and B-allele frequency data to determine allele- and haplotype-specific copy numbers in single cells. Results from CHISEL confirmed the copy number calls from Cell Ranger DNA, and revealed widespread loss of heterozygosity in all samples. These findings were corroborated with allele-specific copy number data derived from matched tumor-normal whole exome sequencing. Furthermore, CHISEL detected polyploidy in one-third of the tumor cells with no preference for the A or B alleles. Overall, our findings highlight that the known heterogeneity of ovarian cancer extends to the level of aneuploidy and CNAs, shedding light on factors which pose significant barriers to effective personalized medicine implementation. Citation Format: Yuxin Jin, Rania Bassiouni, Lee D. Gibbs, Jing Qian, Solomon Rotimi, Michelle G. Webb, Seeta Rajpara, David W. Craig, Lynda D. Roman, John D. Carpten. Revealing ovarian cancer copy number variation in single cells [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 4343.

Abstract 6275: Exposure to neighborhood violence rewires glucocorticoid receptor binding and drives proliferation and invasiveness in lung tumor samples

Abstract Background: Despite smoking less, Black men experience higher incidence of lung cancer compared to white men. This health disparity is even more prevalent in Black men from Chicago, suggesting local neighborhood factors impacting tumorigenesis. Preliminary data indicate that, compared to white men, Black men are more likely to reside in neighborhoods with high levels of violence and have elevated levels of hair cortisol. Objective: To understand the link between lung tumorigenesis and exposure to neighborhood violence, our objective is to investigate the chromatin recruitment of the receptor for cortisol, called the glucocorticoid receptor (GR), and to correlate this recruitment with target gene expression levels. Methods: Utilizing CUT & RUN, we identified the gene binding sites of GR using 15 lung tumor and corresponding healthy tissue samples from lung cancer patients living in Chicago. GR recruitment to chromatin was correlated with the neighborhood homicide rate obtained using patients’ zip codes. Spatial transcriptome profiles for these 15 lung tumor samples were obtained from the Space Ranger pipeline and gene expression hot spots of GR target genes were visualized using Loupe Browser (10x Genomics). Results: GR recruitment to regulatory regions of chromatin increases with greater zip code level violence rates. In patients from high violence neighborhoods, tumor samples had higher magnitude of binding compared to normal neighboring tissue. In tumor samples from patients living in high violence compared to low violence neighborhoods, GR binding is seen in genes that are associated with increased tumor aggressiveness. Hot-spot analysis of these genes found strong co-expression of genes associated with proliferation and invasion in samples from high violence but not low violence neighborhoods. Conclusion: Exposure to neighborhood violence may impact tumor biology via increased GR recruitment to genes associated with proliferation and invasion. Citation Format: Hannah Heath, Jin Young Yoo, Vani Sharma, Hannah McGee, Aiman Soliman, Abeer Mohamed, Alicia K. Matthews, Robert Winn, Zeynep Madak-Erdogan, Sage Kim. Exposure to neighborhood violence rewires glucocorticoid receptor binding and drives proliferation and invasiveness in lung tumor samples [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 6275.

Abstract 7474: T-cell responses across heart, blood, and tumor in patients with immune checkpoint inhibitor-related myocarditis (irMyocarditis)

Abstract Introduction: Immune checkpoint inhibitor (ICI)-related myocarditis (irMyocarditis) is a potentially lethal complication of ICI use that is characterized by the presence of clonally expanded T cells in the heart. The antigens recognized by these expanded intracardiac T-cell clones and their relationships to T-cell clones in the blood and tumors of irMyocarditis patients are poorly understood. Methods: Paired single-cell RNA sequencing (scRNA-seq) and T-cell receptor (TCR) sequencing was performed on heart tissue (n = 13) and peripheral blood from patients with irMyocarditis (n = 25) and ICI-treated controls (n = 28) using the 10X Chromium (10X Genomics) system. TCR-β chain sequencing was performed (Adaptive Biotechnologies) on four autopsy cases of patients with available scRNA-seq data and irMyocarditis heart, tumor, and histologically normal tissue. An established high-throughput protocol was used to screen expanded intracardiac TCRs against candidate antigens (Oliveira G, et al. Nature 2021). Briefly, full-length TCRs were cloned, transduced into donor T cells, and screened against autologous or major histocompatibility complex (MHC) Class I-matched antigen presenting cell lines pulsed with peptide pools that covered the full length of the ⍺-myosin, troponin-I, and troponin-T proteins alongside pools of common viral antigens and appropriate controls. Results: scRNA-seq data showed that TCRs shared between heart and blood are predominantly found in circulating CD8 T cell subsets as compared to circulating CD4 T cell subsets. The gene expression patterns of these shared T-cell clones in circulation appear distinct in fatal and non-fatal irMyocarditis patients, with shared T-cell clones in fatal cases expressing cycling markers (MKI67, STMN1) and the chemokine receptor CXCR3. TCR-β chain sequences most enriched in irMyocarditis tissue relative to control tissues were distinct from those enriched in tumor tissues, and their full-length TCR sequences could be recovered from scRNA-seq data. In total, 52 cardiac-expanded TCRs across eight donors were screened against candidate antigens. None of the screened TCRs recognized the putative cardiac autoantigens. Conclusions: T-cell clones expanded in irMyocarditis are shared in circulation, where the gene expression of these clones may help to distinguish fatal from non-fatal irMyocarditis. TCRs enriched in irMyocarditis appear to be largely distinct from those enriched in tumor and likely recognize currently unknown cardiac autoantigens. Citation Format: Steven Blum, Daniel A. Zlotoff, Neal P. Smith, Isabela J. Kernin, Swetha Ramesh, Giacomo Oliveira, Leyre Zubiri, Joshua Caplin, Nandini Samanta, Sidney Martin, Mike Wang, Alice Tirard, Pritha Sen, Yuhui Song, Katherine Xu, Jaimie L. Barth, Kamil Slowikowski, Mazen Nasrallah, Jessica Tantivit, Kasidet Manakongtreecheep, Benjamin Y. Arnold, John McGuire, Alexander B. Afeyan, Christopher J. Pinto, Daniel McLoughlin, Monica Jackson, PuiYee Chan, Aleigha Lawless, William A. Michaud, Tatyana Sharova, Linda T. Nieman, Justin F. Gainor, Dejan Juric, Mari Mino-Kenudsen, Ryan J. Sullivn, Genevieve M. Boland, James R. Stone, Catherine J. Wu, Molly F. Thomas, Tomas G. Neilan, Kerry L. Reynolds, Alexandra-Chloé Villani. T-cell responses across heart, blood, and tumor in patients with immune checkpoint inhibitor-related myocarditis (irMyocarditis) [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 7474.

Abstract 1148: Multimodal spatial transcriptomics and proteomics analysis of the resectable NSCLC ecosystem following neoadjuvant chemoimmunotherapy

Abstract Neoadjuvant and perioperative immunotherapy with checkpoint inhibitors (ICIs), combined with chemotherapy (CT), have improved outcomes for patients with resectable non-small cell lung cancer (NSCLC). Pathologic tumor response has been utilized in clinical trials as a surrogate of clinical efficacy. Yet, over half of treated patients experience non-response, highlighting the need for novel markers to identify those who are most likely to derive therapeutic benefit. To dissect the spatial complexity of the tumor-associated immune landscape following neoadjuvant chemoimmunotherapy (CT+ICI), we selected patients (n =3) with a range of residual viable tumor (%RVT) - pathological complete response (pCR; 0% RVT), partial response (20% RVT), and no-response (100% RVT). We performed multimodal spatial transcriptomics (ST) and proteomics (using a 35-plex protein panel) on the same tissue sections using the Visium CytAssist from 10X Genomics. We also examined spatial patterns of 20-plex panel of immune and stromal markers at single-cell resolution in the same samples using the COMET Lunaphore platform. In the pCR patient, we studied two tumor areas to assess the impact of tumor response heterogeneity on the immune landscape. Our analysis identified distinct immune profiles across three patients with varying %RVT, reflecting the heterogeneity of the immune response. We found robust gene-protein correlation, such as MS4A1 gene expression and CD20 protein levels, in our multimodal spatial-omics analysis. Intriguingly, the arrangement of B cells and their interaction with surrounding plasma cells (PCs) varied notably across patients. Unlike in the patients with partial or no response, pronounced tertiary lymphoid structure (TLS) formation and signatures were observed in the pCR patient, with the CXCL13-CXCR5 axis overlapping with the TLS profile, suggesting a functional interplay that may be crucial in mediating response to therapy. Intriguingly, in the pCR patient, PCs uniquely arrayed around dense B cell aggregates, marked by MS4A1, CR2, FCER1, and CXCL13. PCs were not only less abundant in non-PCR patients but they also did not array around lymphoid aggregates. Our high-resolution and multimodal analysis identified spatially-resolved expression and patterns for B lineage cells that may be associated, and thus, underlie response of resectable NSCLC to neoadjuvant CT+ICI. Ongoing efforts on this expanding cohort will shed further light on transcriptional states and immunogenomic roles of B lineage cells in neoadjuvant CT+ICI-treated NSCLC. Citation Format: Zahraa Rahal, Tieling Zhou, Sujuan Yang, Alejandra Serrano, Jiping Feng, Ansam Sinjab, John T. Le, Xin Sun, Michael Wang, Wei Hu, Jianjun Zang, Tullia Bruno, Hai T. Tran, Stephen G. Swisher, Cheuk Hong Leung, Heather Y. Lin, J. Jack Lee, Jing Wang, John Victor Heymach, Don Lynn Gibbons, Ignacio Ivan Wistuba, Annikka Weissferdt, Jared K. Burks, Luisa Maren Solis Soto, Humam Kadara, Tina Cascone. Multimodal spatial transcriptomics and proteomics analysis of the resectable NSCLC ecosystem following neoadjuvant chemoimmunotherapy [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 1148.

Abstract 6836: Single-cell RNA sequencing of FUS::DDIT3 myxoid/round cell liposarcoma delineates mechanisms of oncogenic progression and immune escape

Abstract Myxoid/Round Cell Liposarcoma (MRCL) is an understudied soft tissue sarcoma that typically affects young adults and accounts for 30% of all liposarcomas. MRCL is characterized by oncogenic DDIT3 fusions, with FUS::DDIT3 being present in over 90% of cases. However, the cellular origins and oncogenic mechanisms of MRCL remain incompletely defined. Here we report oncogene transcription, and tumor-immune interactions in a cohort of 5 patient tumors with matched normal tissue for which we sequenced the transcriptomes of approximately 45,000 single cells using 10X Genomics, and full-length transcripts in approximately 20,000 single cells via Oxford Nanopore in 2 of these patients. Our results reveal two distinct cancer cell populations: Early Cancer Cells (ECC) and Advanced Cancer Cells (ACC). These cells appear to derive from adipose stem progenitor cells (ASPC) and fall along an ASPC→ECC→ACC pseudo-time axis. Along this axis, a distinct pattern emerges where oncogenes tend to be upregulated and tumor suppressor genes (TSG) tend to be downregulated and these appear to be mutually exclusive. Comparing ECC to ASPC we see increased expression of HIPPO and PI3K pathway oncogenes, FGFR2 and IGF1R RTKs, and downregulation of the TSG CDKN2A and CDKN1A. ACC show upregulation of hedgehog, ErbB, WNT, HIPPO, PI3K, and MAPK signaling pathways compared to ECC. Full-length transcript sequencing at the single-cell level shows a consistent expression of the FUS::DDIT3 fusion transcript in both ECC and ACC populations, confirming that these populations are cancer cells. Furthermore, MRCL displays several immune escape mechanisms, including poor immune infiltration and a marked decline of HLA Class I expression along the pseudo-time axis from ECC to ACC, suggesting a complex interplay between oncogenic signaling and immune evasion. These results suggest that MRCL likely originates from ASPC and expression of FUS:DDIT3 oncoprotein induces early HIPPO, PI3K, FGFR2, and insulin signaling pathway expression in ECC with further hedgehog, ErbB, MAPK, and WNT pathway activation in ACC. This progressive activation in oncogenic signaling is associated with immune evasion. This is the first single-cell RNA seq analysis to detect the presence of the FUS::DDIT3 fusion in ECC and ACC significantly advancing our understanding of the mechanisms of MRCL oncogenesis, immune escape, and identifies potential novel therapeutic targets. Citation Format: Rodrigo Gularte-Mérida, Evan Seffar, George Li, Young-Mi Kim, Narasimhan P. Agaram, Nicholas Socci, Francisco Sanchez-Vega, Nikolaus Schultz, Samuel Singer. Single-cell RNA sequencing of FUS::DDIT3 myxoid/round cell liposarcoma delineates mechanisms of oncogenic progression and immune escape [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 6836.

Abstract 5485: Spatial characterization of the immunosuppressive tumor microenvironment in estrogen receptor positive breast cancer at single cell level

Abstract We characterized immune cell exclusion in estrogen receptor positive (ER+) breast cancer through the study of spatial relationships among various subsets of cancer-associated fibroblasts (CAFs), tumor-associated macrophages (TAMs), and other immune cells using a novel in-situ spatial transcriptomic technology. ER+ breast cancer is the most common breast cancer subtype. While endocrine therapy and immune checkpoint inhibitors have considerably reduced relapse and mortality for breast cancer patients, tumor resistance to treatment remains a major challenge. The tumor microenvironment (TME) plays an important role in this mechanism of resistance. Our previous spatial proteomic analysis of ER+ breast FFPE samples demonstrated the intricate relationship between tumor and immunosuppressive cells such as CAFs and TAMs via the CXCR4-CXCL12 axis associated with the exclusion of CD8 T cells from the TME. However, the limited number of antibodies in the panel made it challenging to investigate the diversity of those CAF and TAM populations and better understand their contribution to T cell exclusion. For this purpose, we further characterized the TME of 4 human ER+ breast cancer FFPE cores using the Xenium in-situ transcriptomic platform with a breast cancer-focused panel of 280 genes from 10x Genomics plus 100 additional genes selected from literature and publicly available single cell datasets to delineate CAF and TAM sub-populations. Image analysis enabled the quantification and spatial mapping of the target genes within each cell boundary. Cells were manually annotated through unsupervised clustering of over 1 million cells. The cell phenotyping analysis allowed us to annotate major cell types including tumor cells, macrophages, T cells and fibroblasts. With our curated panel, we further characterized CAF and TAM sub-populations by identifying myofibroblastic CAFs (myCAFs), inflammatory CAFs (iCAFs), and antigen-presenting CAFs (apCAFs) in addition to M1 and M2-like macrophages as reported in the literature. We then performed spatial neighborhood analysis based on the similarity of the cell type composition in the vicinity of each cell. The results showed that myCAFs and M2-like macrophages are found in proximity to tumor cells and may play a role in T-cell exclusion. In addition, iCAFs mainly express CXCL12, a chemokine known to attract immunosuppressive cells such as regulatory T cells and M2-like macrophages as well as repel cytotoxic T cells from infiltrating the tumor via the CXCR4-CXCL12 axis. Overall, our work shows the potential of spatial transcriptomics to elucidate the spatial distribution of cells and their contribution to the immunosuppressive TME, which may enable researchers to improve understanding of tumor biology and drug target discovery efforts. Citation Format: Julien Tessier, Sandra Curras-Alonso, Joon Sang Lee, Fabien Delahaye, Hong Ma, Katie Malley, Dinesh Bangari, Donald Jackson, Angela Hadjipanayis. Spatial characterization of the immunosuppressive tumor microenvironment in estrogen receptor positive breast cancer at single cell level [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 5485.

Abstract 3952: Multiomic single-cell tumor evolution models of minimal residual disease in pediatric B-cell acute lymphoblastic leukemia

Abstract Detection of minimal residual disease (MRD) after initial diagnosis (IDX) and therapy is a strong prognostic marker for relapse in pediatric B-cell acute lymphoblastic leukemia (B-ALL). Previous studies have explored clonal genetic and gene expression changes between initial diagnosis and relapse. However, studying tumor cells present at MRD is challenging due to their low abundance. Examining the genomic profiles of leukemia cells that resist induction chemotherapy and understanding their evolutionary relationship to cells present at diagnosis may lead to a better understanding of the cells that eventually seed relapse. We analyzed somatic point mutations, indels, and copy number variants from 41 pediatric B-ALL patients with high-risk B-ALL. We specifically focused on patients from the following four common high-risk subtypes: KMT2A-rearranged, Ph+, Ph-like, and iAMP21, who had detectable disease at the end of induction. Leukemic burden at end-induction (day 29) ranged from 0.03% to 66.00%. Data were generated in partnership with the National Cancer Institute’s Human Tumor Atlas Network and the Children’s Oncology Group. Our data set of 41 patients includes 39 with paired initial diagnostic and end-induction samples that we used to create tumor evolution models based on single cells across disease stages. We produced single-cell multiome gene expression (scRNA) and chromatin accessibility (scATAC) profiles (10x Genomics) with a median of 7428 leukemic blast cells at IDX (range: 2490-14219) and 1907 at MRD (range: 240-10167) after filtering. We called somatic mutations from scRNA and scATAC using SComatic and Monopogen, and we detected copy number changes using Numbat and EpiAneufinder. We also designed a targeted DNA sequencing panel including 335 variants based on B-ALL literature and database searches to produce scDNA (Mission Bio) for 24 patients (16 IDX-MRD pairs) with a median of 2346 cells profiled at IDX (range: 340-8849) and 1828 at MRD (range: 596-5133). We built tumor phylogenies based on somatic SNVs and CNVs with COMPASS. Using multiple tools and complementary single-cell omics data types to detect somatic changes improved our confidence in the events used for tumor evolution tree construction. Our approach allowed us to define recurrent genomic events and patterns across pediatric B-ALL subtypes and to describe the clonal evolution of cells measured at initial diagnostic and end-induction disease stages. We were also able to link cell-specific mutation events to their transcriptional and epigenomic signatures, including mapping mutation events along the B-cell development trajectory and within differentially expressed gene pathways. Some cases showed dramatic shifts in subclonal structure between IDX and MRD that may be related to therapy-induced clonal selection, such as a loss of NRAS hotspot mutation. Citation Format: Steven M. Foltz, Avi Loren, Changya Chen, Rushabh Mehta, Elizabeth Li, Jason Xu, Fatemeh Alikarami, Kathrin M. Bernt, Kai Tan. Multiomic single-cell tumor evolution models of minimal residual disease in pediatric B-cell acute lymphoblastic leukemia [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 3952.

Abstract 1146: Pan-cancer characterization of cancer cell state and plasticity using spatially resolved transcriptomics

Abstract Cancer cell state heterogeneity constitutes a foundational characteristic of cancer, posing a formidable barrier to the discovery of biomarkers and the efficacy of therapeutic interventions. However, current understanding of cancer cell heterogeneity and plasticity remains limited, especially in the spatial context. Previous studies underscored that cancer cell states are not strictly governed by genetics, but rather display a remarkable degree of plasticity. Recent pan-cancer single-cell studies have unveiled dozens of recurrent cancer cell states. Nevertheless, the relationship between these cancer cell states and tumor microenvironment (TME) remains poorly understood, especially when considering the diversity across different tumor types. Recent advancements in spatial transcriptomics (ST) have paved the way for a novel approach to spatially profile cell location, organization, and interaction within the tumor microenvironment. In this study, we curated ST data (Visium, 10x Genomics) from public repositories and in-house datasets, encompassing a total of >200 tissue sections across 11 cancer types. By incorporating histological annotations and inferred copy number variations, we systematically investigated the spatial heterogeneity of cancer cell states and inferred clonal architectures of cancer cell-enriched spots. Non-negative matrix factorization was applied to identify highly recurrent cancer states and transcriptional hallmarks associated with intra-tumor heterogeneity. By employing this approach, we uncover a diverse curated gene set of meta-programs. Notably, we observe a high level of reproducibility of these meta-programs when compared to the findings from single-cell level. Furthermore, we observe significant variations of cell states across different cancer types, even among two cancer subtypes within a specific tissue. We noted a unique distribution of 'hypoxia' and 'epithelial-mesenchymal transition' in the basal lineage tumor. Following this, we perform single-cell and ST co-embedding using available tools, including CellTrek and CytoSPACE. We noticed the cell type composition of tumor’s neighbor spots play a significant role in influencing tumor states, especially for myofibroblastic CAFs and the tumor state in epithelial-mesenchymal transition. These findings contribute valuable insights into the relationship between cancer cell state plasticity and interactions with the TME, offering potential targets for further exploration and therapeutic intervention. Citation Format: Guangsheng Pei, Kyung S. Cho, Yunhe Liu, Serrano Alejandra, Rossana Lazcano, Enyu Dai, Guangchun Han, Fuduan Peng, Daiwei Zhang, Yanshuo Chu, Ansam F. Sinjab, Jiahui Jiang, Mingyao Li, Cassian Yee, Andrew Futreal, Alex Lazar, Humam Kadara, Jianjun Gao, Luisa M. Soto, Anirban Maitra, Jaffer Ajani, Linghua Wang. Pan-cancer characterization of cancer cell state and plasticity using spatially resolved transcriptomics [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 1146.

Abstract 6835: Profiling of new prostate cancer vulnerabilities through single-nucleus RNAseq implicates the CAF-specific TGF-β pathway in tumor progression

Abstract Background: Transcriptomic profiles of primary high grade prostate cancer (hgPCa) have been extensively studied and prognostic gene expression signatures to classify patients for risk have been identified. However, such studies have employed bulk genomic techniques that blur the contributions of the different cell types. Indeed, tumor microenvironment (TME) cells can significantly contribute to these transcriptomic signatures thereby confounding the lineage of potential therapeutic targets. These challenges underscore the potential of single-nucleus (sn)RNAseq to elucidate new PCa vulnerabilities. We set out to assess whether the TME, particularly cancer-associated fibroblasts (CAFs) drive poor outcome in PCa. Methods: We obtained 15 treatment-naïve frozen primary high risk PCa tissue samples, mostly Gleason >=8. A PCa nuclei dissociation protocol was adapted for single nucleus snRNAseq (10X Genomics). Sample profiling included all cell populations in the tissue including tumor and TME. Output was analyzed using Seurat (v.4.1.1), corrected for ambient RNA expression with CellBender (v.0.3.1) and detected and removed doublets with Scds (v.3.9). Tumor cells were distinguished from normal epithelium cells by a combination of inferCNV (v.1.12.0) and supervised learning with random forests classification. Results: Through snRNAseq, we show that CAFs, and not tumor cells, entirely drive the expression of previously validated poor prognostic signatures (Mortensen, 2015). Our analysis revealed that the TGFβ pathway expression, TGF-β1 in particular, is upregulated in CAFs rather than PCa cells. This pathway, along with poor prognosis signatures are selectively elevated in CAFs from patients with Gleason high compared to low, implicating the TGFb axis as a PCa vulnerability. We also derived a snRNAseq CAF signature that differentiates non-responders to immune checkpoint therapy in mCRPC (Nivolumab+Ipilimumab). Furthermore, cluster profiling of tumor nuclei revealed that hgPCa harbors high heterogeneity with distinct niches of hgPC, mCRPC or neuroendocrine phenotypes for each patient. Conclusions: Through snRNAseq we show that CAFs are the main contributors to prior bulk RNAseq classifiers of poor response, resulting in a refined CAF signature that allows for direct investigation of the contribution of CAFs in other patient segments (mCRPC). Our findings point to a hgPCa patient segment with high CAF representation that may benefit from the addition of a CAF targeting agent (ie.TGFbi) to androgen deprivation therapy. This data has the potential to help refine our prognostic classifiers for patient selection and clinical applicability. Further study of the reported tumor heterogeneity will inform rational combination therapies to tackle resistance mechanisms. Citation Format: Alexandre P. Alloy, Sharmila Chamling Rai, Brendan O'Brien, Anna Lyubetskaya, Arnaud Amzallag, Benjamin Chen, Ana Lako. Profiling of new prostate cancer vulnerabilities through single-nucleus RNAseq implicates the CAF-specific TGF-β pathway in tumor progression [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 6835.

Abstract 5286: M2 to M1 repolarization of tumor-associated macrophages via the lysosomal effect of itraconazole

Abstract Objective: Itraconazole (ITZ), an antifungal agent, has been reported to have tumor agnostic anticancer effects. Previous reports have shown prolonged survival in patients with lung and ovarian cancer who received ITZ. The anticancer mechanisms vary depending on the cancer type and stromal cells. Based on our previous studies, we focused on tumor-associated macrophages (TAMs). Methods: Anti-tumorigenic M1 and pro-tumorigenic M2 macrophages were established from THP-1 cells and their phenotypes were determined based on morphology, cell surface antigens by Western blotting, and secreted proteins by ELISA. Bulk proteomic analysis of cell proteins was conducted using liquid chromatography-tandem mass spectrometry. The viability of CaSki cervical cancer cells was evaluated both in culture with the supernatant and co-culture with M2 macrophages after treatment with ITZ (10-5 M). Single-cell RNA sequencing (scRNA-seq) with surface labeling of M2 macrophages with and without the ITZ was performed. Using LoupeBrowser (10x Genomics, Inc.), ITZ-treated M2 macrophages were divided into two groups, one with newly emerged clusters after ITZ treatment (group 1) and the other (group 2). Differentially expressed genes between group 1 and group 2 were identified based on a two-fold and a 0.05 adjusted p value and were subjected to Reactome pathway analysis. Significant pathways were identified based on both p value < 0.05 and FDR <0.3. A triple-labeling immunofluorescence study was conducted to detect cholesterol, IL-1β, and organelles (the endoplasmic reticulum, phagosome, and lysosome). Results: ITZ changed M2 macrophages to M1-like morphology and protein expression. While co-culture with M2 macrophages promoted cancer cell proliferation, both culture with the supernatant and co-culture with ITZ-treated M2 macrophages significantly inhibited CaSki cell growth. scRNA-seq identified newly emerged clusters (group 1) among M2 macrophages following ITZ treatment. Group 1 had elevated mRNA expression of M1 markers, including IL1β, IL6, CD86, TL4, GAPDH, and RKM, compared to group 2. Group 1 expressed the CD86 and TLR4 surface antigen proteins. Pathway analysis identified 176 significant pathways including lysosome vesicle biogenesis. Immunofluorescence analysis showed that M1-like macrophages in ITZ-treated M2 macrophages had enlarged lysosomes containing cholesterol. Conclusion: ITZ repolarized THP-1 derived M2 macrophage to an M1-like phenotype. The mechanism of repolarization involves intracellular cholesterol accumulation via lysosomal dysfunction. Citation Format: Yumi Takimoto, Hiroshi Tsubamoto, Kazuko Sakata, Roze Isono-Taniguchi, Tomoko Ueda, Hiroaki Shibahara. M2 to M1 repolarization of tumor-associated macrophages via the lysosomal effect of itraconazole [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 5286.

Abstract 6694: Gut microbial drivers of response to bladder-sparing therapy in human muscle-invasive bladder cancer enhance immunotherapy efficacy and limit immunosuppression following fecal microbiome transplantation in vivo

Abstract BACKGROUND: Radiation therapy (RT) is a bladder-sparing option for Muscle-Invasive Bladder Cancer (MIBC), yet encounters a 30% non-response rate, with half of the patients succumbing to metastasis. Preclinical models demonstrate enhanced antitumor responses with RT combined with PD-1/PD-L1 blockade but give limited insight into the determinants of success for such combination therapies (CT). The gut microbiome, pivotal in conditioning local and peripheral immunity, influences PD-1-based immunotherapy efficacy in various cancers. Immune profiling indicates heightened systemic and antitumor immunity in responders with a favorable gut microbiome, enriched in Akkermansia muciniphila, Bifidobacterium, and Faecalibacterium. Oral gavage of immunogenic bacteria further enhances combined RT and anti-PD-L1 therapy. We thus aim to 1) elucidate the role of patients’ microbiome in shaping anti-tumor immune responses to CT, and 2) use its composition as a predictive factor for CT success. METHODS: We performed shotgun metagenomics on microbial DNA from fecal materials of MIBC RT responders (R, n=26) and non-responders (NR, n=11). Fecal homogenates from donors were gavaged into germ-free (GF) mice. Three weeks post-gavage, MB49 tumor cells were subcutaneously delivered to mice, randomized into four groups: control, anti-PD-L1, RT, and RT + anti-PD-L1. Tumors were harvested seven days post-treatment for single-cell RNA-seq and TCR sequencing (10X Genomics), while stool samples were collected weekly for 16S sequencing. RESULTS: Significant gut microbial disparities were observed between R and NR MIBC patients, with particular enrichment in known promoters of anti-PD-L1 response, such as Phocaeicola dorei in R. Transplantation of R microbiome into GF mice resulted in significant increases in predicted survival, tumor growth delay, and counts of effector CD4+ T cell infiltration in the RT+PD-L1 arm. Conversely, NR microbiome transplantation correlated with increased neutrophil and Treg infiltration, abrogating the survival tumor growth delay benefits of the combination arm. Spatial tissue analyses revealed higher neutrophil densities around CD8+ T cells in all NR arms. Single-cell RNA-seq of tumor-infiltrating immune cells unveiled skewed CD4 and CD8 polarization between R and NR in vivo batches. SIGNIFICANCE: To our knowledge, this is the first study to use FMT as a modulator of response in the context of radiation therapy combinations in MIBC. Our results highlight that the gut microbiome alone may condition a favorable immune terrain for combinatorial therapies involving radiation. This offers strong predictive value for personalized therapeutic approaches in selecting patients who will benefit the most from bladder-sparing therapies. Citation Format: Eva Michaud, Sabina Fehric, Cynthia Faubert, Bertrand Routy, Irah King, José Joao Mansure, Wassim Kassouf. Gut microbial drivers of response to bladder-sparing therapy in human muscle-invasive bladder cancer enhance immunotherapy efficacy and limit immunosuppression following fecal microbiome transplantation in vivo [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 6694.

Abstract 7041: Tumor-immune interactions and cisplatin resistance in localized muscle-invasive bladder cancer

Abstract Background: Cisplatin-based chemotherapy followed by radical cystectomy remains the standard-of-care treatment for patient with localized muscle-invasive bladder cancer (MIBC). Neoadjuvant clinical trials studying the combination of cisplatin-based chemotherapy and immune checkpoint blockade (ICB) in MIBC reported encouraging pathologic complete response rates. However, the molecular mechanisms and cellular programs involved in response and resistance to cisplatin and ICB in MIBC remain incompletely characterized. Our goal is to define cellular transcriptional programs and chromatin accessible regions in cancer cells and infiltrating immune cells associated with response and resistance to neoadjuvant systemic therapy. Methods: We performed single-cell Multiome ATAC and Gene expression sequencing (simultaneous identification of gene expression and open chromatin regions within the same cell) of tumors that had a complete response – “responders” – and tumors that had no response or progressed – “non-responders” – through neoadjuvant cisplatin-based chemotherapy (n=15). Single cell suspensions were prepared following the 10x Genomics protocol. Cell Ranger ARC was used for sequence alignment, peak calling, and generation of count matrices. Downstream single-cell gene expression analysis was performed with Scanpy and ATAC-seq with Seurat. Results: We identified two distinct urothelial cell populations in "responders" vs "non-responders" based on single cell gene expression and genome wide chromatin accessibility regions. Cancer cells in “non-responders” preferentially express basal cell gene expression signatures. “Non-responders” were significantly enriched in suppressive tumor-associated macrophages (TAMs). Interestingly, SPP1+ TAMs known to have a pro-tumoral role and promote resistance to ICB were exclusively identified in “non-responders”. Conclusion: Single cell and genome wide chromatin accessibility regions identify heterogenous urothelial cell populations expressing basal cell markers in tumors resistant to neoadjuvant cisplatin-based chemotherapy. “Non-responders” are significantly enriched with TAMs implicated in resistance to ICB. Future studies will better define the implications of these findings in cancer therapeutics for patients with MIBC. Citation Format: Filipe La Fuente De Carvalho, Jihyun Lee, Kevin Bi, Breanna Titchen, Konrad Stawiski, Jihye Park, Amanda Garza, Daniel Michaud, Jennifer Guerriero, Elizabeth Mittendorf, Kent Mouw, Eliezer Van Allen. Tumor-immune interactions and cisplatin resistance in localized muscle-invasive bladder 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 7041.

Abstract 6868: Exploring myeloid landscapes according to EGFR mutated NSCLC tumor microenvironment

Abstract Introduction: Although the use of immune checkpoint inhibitors (ICIs) has improved the survival rate of some patients, EGFR mutant (MT) NSCLC patients exhibit a poor response to ICIs compared to EGFR wild-type (WT) patients. It has been demonstrated that EGFR MT NSCLC cells contribute to immunosuppressive tumor microenvironments (TMEs) by secreting inhibitory cytokines and metabolites and recruiting pro-tumor immunogenic cells, thereby diminishing ICI efficacy. In particular, myeloid cells represent a major component of the TME and are involved in regulating tumor progression and metastasis, indicating anti- and pro-inflammatory heterogeneous functions. While single-cell based analyses have been conducted in various cell types, studies on the diversity of myeloid cells between EGFR WT and EGFR MT NSCLCs are insufficient. Therefore, we explored to reveal the presence of multifaceted myeloid cell populations and to modulate its functions to augment ICI response in NSCLC patients with EGFR MT using single-cell RNA analysis. Methods: Using the 10x Genomics Chromium system, we have generated single-cell RNA expression of a total of 904,174 cells from primary lung tissues of 95 patients with EGFR-WT (n=35), EGFR-MT TKI naïve (n=55), TKI post (n=5) and matched normal (n=22). Nine distinct cell lineages were annotated with canonical marker gene expression, focusing particularly on the myeloid (n=212,673 cells). Results: We characterized 22 transcriptional states of myeloid cells: 4 clusters of alveolar macrophages (AMs; PPARG+), 4 clusters of interstitial macrophages (IMs; SPP1+, FOLR2+, CCL2+), 4 clusters of conventional DCs (cDCs; CLEC9A+, CD1C+, LAMP3+), 2 clusters of mast cells (KIT+), 1 cluster of plasmacytoid DCs (pDCs; LILRA4+), proliferating cells (MKI67+), monocytes (FCN1+), neutrophil like cells (CSF3R+) and 4 other unidentified clusters. In tumor tissues, IMs constituted a significantly higher proportion compared to normal tissues (p<0.001), with EGFR-WT and EGFR-MT IMs exhibiting distinct characteristics. EGFR-WT IMs had a high proportion of cluster expressing FOLR2, a marker of tissue resident macrophages associated with CD8 T cell infiltration and activation. On the other hand, a major component of IMs from EGFR-MT was a cluster expressing SPP1 and its regulator MIF. SPP1 is well known to be involved in cancer cell progression, epithelial-mesenchymal transition, autophagy, and epigenetic alterations. The abundance of SPP1 IMs in the EGFR-MT TME refers to the formation of an immunosuppressive TME, potentially compromising the effectiveness of ICIs. Conclusions: We found that EGFR-MT TME comprised a high proportion of immunosuppressive IM cluster expressing SPP1, implying that it contributes to an immunosuppressive TME. Our findings suggest the possibility of developing strategies to enhance ICI responses by targeting SPP1-induced immunosuppressive TME in EGFR-mutant NSCLC patients. Citation Format: Eun Ji Lee, Juwon Ahn, You Won Lee, Minyeop Kim, Seung Yeon Oh, Yong Joon Park, Su-Jin Choi, JuHyeon Lee, Kyumin Lim, Kyoung-Ho Pyo, Jae Hwan Kim, Jii Bum Lee, Min Hee Hong, Sun Min Lim, Mi Ran Yun, Byoung Chul Cho. Exploring myeloid landscapes according to EGFR mutated NSCLC tumor microenvironment [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 6868.

Abstract 6848: Analysis of the bone microenvironment cells by single cell transcriptomics reveals altered features in multiple myeloma patients compared to pre-malignant monoclonal gammopathies

Abstract Multiple myeloma (MM) is a malignant plasma cell dyscrasia that can be preceded by monoclonal gammopathy of undetermined significance (MGUS) and smoldering MM (SMM). How the bone microenvironment (BME) changes and contributes to tumoral progression in MM remains unresolved. Published data on BME are mainly produced in vitro and few data are on MGUS/SMM patients. Up to date, no single-cell RNA sequencing database of the BME cells has been described in MM. The aim of this project was to characterize for the first time at single cell level, the BME in patients with newly diagnosed MM (MMD) and MGUS/SMM to identify alterations involved in tumoral progression. From 15 bone biopsies of MMD, MGUS and SMM patients, we depleted CD235a+, CD45+, CD31+, and CD138+ cells to enrich the rare BME non-hemopoietic cells. The CD45-CD31-CD235a-CD138- cells were analyzed by scRNAseq. Data were generated on Chromium 10X Genomics. Cellranger and Seurat pipeline in R software has been used. Cell identities were assigned by manual curation. The trajectory analysis has been made by Monocle3. Decouple R and FindMarkers were used to compare pathways, and differential gene expression (DGE) of the samples throughout the different conditions. A total of 35723 cells were profiled. We identified 13 BME cell type clusters: 7 mesenchymal stromal cells (MSCs) clusters (proliferating MSC, MSC DDK-OPG-, MSC DKK+, MSC RUNX2-, MSC OPG+, MSC Osteogenic, Perivascular MSC) and 6 osteoblasts (OBs) clusters (OB precursor, OB precursor LEPR+, OB BGLAP+, OB SPP1+, OB NFkB+, OB late). Psdeudotime analyses highlighted a complex trajectory of differentiation from more immature cell clusters (proliferating MSC) to late OB cluster, confirming the ability of the dataset to snapshot the in vivo complexity of BME and we highlighted an alteration of the MSCs clusters trajectories starting in SMM samples till a disruption in MM. Pathway analyses, in MMD compared to MGUS/SMM, revealed an upregulation of VEGF and PI3K activity in proliferating MSC, perivascular MSC and OB clusters. TRAIL pathway activity, known to suppress MM cell proliferation, was upregulated in MSC osteogenic and OB BGLAP+ in MGUS. Finally, DGE analyses revealed the modulation of different genes, many not yet described in MM. MGUS MSCs clusters showed an upregulation of FBLN1, SERPNF1 and MMD MSCs clusters dramatically downregulated WISP2 and upregulated SRGN, involved in MM cell proliferation. Interestingly, in SMM samples, we reported an upregulation of genes involved both in the promotion of osteoblastogenesis (SCARA3, SPON2) and inhibition (GREM1), likely underling the attempt to contrast the establishment of altered BME, characteristic of MM. Our approach is able to dissect the complex organization of the BME and to highlight at single cells level the alterations of the BME in patients with MM compared to MGUS and SMM. Citation Format: Paola Storti, Tommaso Torelli, Cristina Manferdini, Denise Toscani, Alessandro Guidi, Rosanna Vescovini, Nicolas Thomas Iannozzi, Benedetta Dalla Palma, Matteo Scita, Federica Librale, Stefania Ricci, Vincenzo Raimondi, Oxana Lungu, Giannalisa Todaro, Gabriella Sammarelli, Emanuela Aleo, Gina Lisignoli, Luca Agnelli, Nicola Giuliani. Analysis of the bone microenvironment cells by single cell transcriptomics reveals altered features in multiple myeloma patients compared to pre-malignant monoclonal gammopathies [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 6848.

Abstract 6433: Anti-CD36 monoclonal antibody can sensitize the neoadjuvant chemotherapy response in PDAC by eliminating the senescent tertiary lymphatic structure

Abstract Objective: Pancreatic ductal adenocarcinoma (PDAC) is deadly and aggressive. Neoadjuvant chemotherapy (NAC) may reduce tumor volume and alter the resectability of the tumor. The efficacy of neoadjuvant chemotherapy in patients is still limited. Tertiary lymphoid structures (TLSs) develop in peripheral non-lymphoid tissues and are essential for the immune response and correlate with chemotherapy in various tumor types. However, more research is needed to determine how TLSs affect neoadjuvant chemotherapy in PDAC. We aim to determine how neoadjuvant chemotherapy affects tumor-infiltrating lymphocytes (TLSs) in PDAC patients. We also want to find a biomarker to boost PDAC neoadjuvant chemotherapy response. Methods: We retrospectively collected formalin-fixed paraffin embedded (FFPE) tissues from 115 PDAC patients without preoperative treatment and 72 patients pretreated with neoadjuvant chemotherapy. Multispectral images were processed using AI-powered image analysis software (Tissue Gnostics; Zeiss, Germany). The 10X Genomics platform was used to sequence single cells in tissue samples from five patients who received neoadjuvant chemotherapy (NAC) and five patients who had not received any treatment before analysis (pretreatment naïve, PN). TLS was separated using Laser Microdissection. The mouse model was created by orthotopically injecting tumor cells into the pancreas. Results: Patients who received NAC have a senescent microenvironment. High-throughput single-cell sequencing showed that the senescent gene signature score was enriched in the NAC group, especially in immune cells. The percentage of p16+ CD20+ B cells and P16+ CD3+ T cells in TLSs also increased in the NAC group. Spatial transcriptomics analysis exhibited that CD36 is highly expressed in senescent TLSs, which suggested that CD36 may be a marker for senescent TLSs. Moreover, CD36+ TLSs induced the infiltration of MDSCs and regulatory T cells. CD36+ TLSs were an independent prognostic factor for poor overall survival (OS) (HR=0.67, p=0.002) and progression-free survival (PFS) (HR=0.71, p=0.003). A mice orthotopic xenograft model showed that an anti-CD36 monoclonal antibody eliminated senescent TLSs in pancreatic tissue. MDSCs and Tregs in the surrounding tissue also decreased. Additionally, in vivo KPC mice model showed that the combination of an anti-CD36 and chemotherapy reduced tumor volume and increased survival compared to chemotherapy alone. Conclusion: NAC has the potential to induce the senescence of tumor-associated TLSs, a phenomenon that has been linked to unfavorable prognosis in PDAC. CD36 serves as a viable marker for senescent TLSs that can be targeted. The administration of an anti-CD36 monoclonal antibody can potentially enhance the efficacy of chemotherapy in PDAC by selectively eliminating CD36+ senescent TLSs in mouse models. Citation Format: Jingrui Yan, Tianxing Zhou, Chao Yang, Yongjie Xie, Jun Yu, Jihui Hao. Anti-CD36 monoclonal antibody can sensitize the neoadjuvant chemotherapy response in PDAC by eliminating the senescent tertiary lymphatic structure [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 6433.

Abstract 4949: Multimodal analysis of metals, spatial transcriptomics, and histological structures in colorectal cancer

Abstract Colorectal Cancer (CRC) accounts for nearly 10% of all cancer cases and is the second-leading cause of cancer-related deaths worldwide. The increased incidence of CRC in younger demographics underscores the need for improved screening and prognostication. These enhancements are crucial to augment staging practices which focus on accurate evaluation of local lymph node involvement and distant metastasis. Essential trace elements such as copper and iron within the tumor microenvironment (TME) present novel therapeutic strategies- e.g., copper in cell proliferation/signaling and iron in pro-tumorigenic pathways, amongst other multifaceted roles. Despite advancements in spatial imaging/sequencing for detailed mapping of elemental abundance and gene expression profiles at near-subcellular resolution, the understanding of metal signaling and transport pathways in tumors is limited. This gap highlights the need for sophisticated informatics software for data integration and analysis. We developed a computational workflow for spatial multimodal analysis of elements, genes, cell-types, and histological features, applied to a unique CRC case (pT3) as proof-of-concept. Elemental imaging at 5-micron resolution was performed using laser ablation inductively coupled plasma time-of-flight mass spectrometry (LA-ICPTOF-MS). The 10x Genomics Visium spatial transcriptomic (ST) CytAssist assay captured spatial variation in gene expression within 55-micron spots, with 40X H&E-stained whole slide imaging (Leica Aperio GT450). Cell type proportions within spots were determined through integration of single cell RNASeq. Regions within, around and away from tumor were annotated by a pathologist. ST and LA-ICPTOF-MS were integrated through co-registration software developed at Biomedical National Elemental Imaging Resource. Local Getis-Ord spatial statistics defined hotspots with high elemental concentration. Wilcoxon tests were used to perform differential expression analysis based on metal hotspots, followed by identification of associated biological pathways through Enrichr with Bonferroni adjustment. Preliminary findings revealed distinct trace element distributions in the TME. For instance, Copper was localized within tumor, correlating with pathways related to immune response and activation (overlap=10/89, p<0.0001). Iron was found concentrated at the proliferative front of the tumor, associated with the epithelial to mesenchymal transition pathway and extracellular matrix remodeling (overlap=25/291, p<0.0001), as well as with a mesenchymal phenotype (W=11.7, p<0.0001), identified through cell type deconvolution. Future work will expand on these findings across multiple tissue contexts as means to capture biological processes governing tumor metastasis, recurrence and survival for biomarker discovery and therapeutics development. Citation Format: Aruesha Srivastava, Neha Shaik, Yunrui Lu, Matthew Chan, Alos Diallo, Serin Han, Ramsey Steiner, Tracy Punshon, Brian Jackson, Linda Vahdat, Louis Vaickus, Jack Hoopes, Fred Kolling, Jonathan Marotti, Joshua Levy. Multimodal analysis of metals, spatial transcriptomics, and histological structures in colorectal 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 4949.