Lessons from 3D Reconstruction of Cancer

The host microbiome in the gut and tumors have been shown to affect tumor growth and therapeutic response in cancer. Furthermore, the presence of specific fungal taxa are associated with tumor hypoxia, tumor progression, therapeutic response, and clinical outcomes in colorectal cancer (CRC). Preliminary data from our group found that the presence of Candida species increased tumor hypoxia and decreased overall survival in CRC. However, whether intratumoral Candida drive, support, or simply inhabit tumors with poor prognoses remains unclear. Here, we investigate a casual role for Candida albicans in tumor progression and therapy response using a syngeneic mouse model of microsatellite-instability high (MSI-H) colorectal cancer. We subcutaneously implanted MC38 colorectal cancer cells into C57BL/6 mice and then orally gavaged these mice with C. albicans, Saccharomyces cerevisiae, or PBS. The site of tumor formation was locally irradiated once (7.5 Gy), and growth of the tumor was measured over time. Differences in tumor volume were assessed by longitudinal mixed-effect models. Tumor sections were stained for fungi using calcofluor white (CFW) and underwent bulk RNA sequencing to detect differential gene expression, which were interpreted using gene set enrichment analysis (GSEA). Mice gavaged with C. albicans showed decreased response to radiation compared to mice gavaged with either S. cerevisiae (p<0.05) or PBS (p<0.001). Additionally, hyphae were observed in murine tumors gavaged with C. albicans, suggesting translocation of gavaged C. albicans from the gut to tumors. Further, tumors from mice gavaged with C. albicans displayed unique gene expression profiles, including decreased interferon alpha and IL-6 and STAT3 signaling, decreased oxidative phosphorylation, and decreased apoptosis-related gene expression. Here, we show that C. albicans may confer resistance to radiation therapy and affects immune and cancer cell activity in the MC38 (MSI-H) syngeneic in vivo model of colorectal cancer. Further, we show that hyphal fungi can be visualized in heterotopic murine tumors from our C. albicans gavage condition. These data establish that fungi can translocate from the gut to distal tumor sites, and that upon translocation, changes in gene expression and therapy response are observed. Future directions will explore the mechanism by which these effects occur and whether these findings can be leveraged to improve radiotherapy outcomes. Citation Format: Dennis J. Grencewicz, Alexander Loncar, Rebecca Hoyd, Aaditya Pallerla, Nyelia Williams, Martin Benej, McKenzie Kreamer, Yogita Mehra, Shiva Jahanbakhshi, Matthew Anderson, Nicholas Denko, Daniel Spakowicz. Gavage with Candida albicans leads to fungal colonization of colorectal tumors and decreased response to radiotherapy [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 1282.

Despite advances in our understanding of tumor biology as well as radiation, chemotherapy, and surgical treatments, head and neck squamous cell carcinoma (HNSCC) remains the sixth leading cause of cancer-related mortality and a major cause of morbidity, with over 550,000 new cases per year. Although HNSCC mortality has slightly declined with improved tolerance of therapy, the majority of deaths in HNSCC are related to advanced disease with locoregional lymph node (LN) or distant metastasis. Indeed, the presence of LN metastases reduces survival by approximately 50% in all HNSCC patients. Unfortunately, a firm biologic understanding of pathways that underlie metastasis in HNSCC (and many other solid tumors) remains elusive. Tumor heterogeneity in HNSCC is a major challenge in clinical management and can manifest as variability among tumors (intertumoral heterogeneity) or among cells harboring distinct mutations or expressing unique transcriptional programs from the same tumor (intratumoral heterogeneity). Prior studies have suggested that intratumoral heterogeneity is present in HNSCC based on comparative genomic hybridization assays and DNA ploidy analyses, with recent studies validating intratumoral heterogeneity using whole-genome sequencing. In addition, there is growing interest in subpopulations of HNSCC cells, which may have unique properties such as the ability to self-renew or invade, contributing to recurrence or metastasis, respectively. The clinical significance of intratumoral heterogeneity has recently been demonstrated with a quantitative measure of genetic heterogeneity based on whole-exome sequencing (WES). This measure, termed mutant-allele tumor heterogeneity (MATH), suggests that intratumoral heterogeneity is associated with tumor progression and poor responses to treatment, supporting the idea that greater genetic variability predicts a worse clinical outcome in HNSCC. However, whether intratumoral transcriptional heterogeneity also contributes to clinical outcomes remained an open question. We recently utilized single cell RNA-sequencing (scRNA-seq), a powerful new approach to characterize expression heterogeneity present within oral cavity HNSCC (Puram et al., Cell 2017). The strength of these analyses is the ability to capture the transcriptional profile of each individual cell without contamination from other cells that may be present within the sample. As a result, single-cell sequencing offers 1) more detailed, nuanced expression data than analyses of tumor fragments and 2) captures the transcriptional profile of every cell, even rare populations, that might be overlooked in pooled RNA. We sequenced ~6000 single cells from 18 samples, including five matched primary/lymph node pairs. Our analyses reveal that stromal and immune populations have well-defined and consistent expression programs across tumors. In contrast, malignant cells are highly heterogeneous with variable gene signatures related to cell cycle, stress, hypoxia, epithelial structures, and partial epithelial-to-mesenchymal transition (p-EMT). Cells expressing the p-EMT program spatially localized to the leading edge of primary tumors and in further in vitro analyses, we found that p-EMT cells were more invasive. Integration of single-cell transcriptomes with bulk expression profiles for >500 tumors from The Cancer Genome Atlas using a deconvolution approach identified a malignant cell-specific signature for each of these samples. Remarkably, this analysis identified the p-EMT program as the primary source of variability in HNSCC, while enabling us to redefine HNSCC subtypes by their malignant and stromal composition. Further integration with clinical annotations uncovered a significant association between the p-EMT program and nodal metastasis, grade, and adverse pathologic features including lymphovascular invasion and extracapsular extension. Consistent with these findings, the p-EMT score was a significant predictor of occult nodal metastases in clinically N0 patients, with predictive power equivalent to tumor thickness/size. Our studies provide a detailed map of expression heterogeneity in the HNSCC ecosystem and define an in vivo p-EMT program associated with metastasis and disease progression. Citation Format: Sidharth V. Puram. Understanding programs of invasion and metastasis in head and neck cancer [abstract]. In: Proceedings of the AACR-AHNS Head and Neck Cancer Conference: Optimizing Survival and Quality of Life through Basic, Clinical, and Translational Research; 2019 Apr 29-30; Austin, TX. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(12_Suppl_2):Abstract nr IA08.

The IFN-γ cytokine plays a dual role in anti-tumor immunity, enhancing immune defense against cancer cells while promoting tumor survival and progression. Its influence on prognosis and therapeutic responses across cancer types remains unclear. This study aimed to perform a pan-cancer analysis of IFN-γ response genes to determine their prognostic significance and evaluate their impact on clinical outcomes and anti-PD1 immunotherapy responses. Using multiple datasets, 46 IFN-γ response genes were identified as prognostic for disease-specific survival, and their expression was used to construct the IFN-γ Response Gene Network Signature (IFGRNS) score. The prognostic and therapeutic relevance of the IFGRNS score was assessed across cancer types, considering tumor pathology, genomic alterations, tumor mutation burden, and microenvironment. Single-cell transcriptomic analysis identified cellular contributors, and a murine pancreatic cancer (PAN02) model was used to validate findings with anti-PD1 therapy. The IFGRNS score emerged as a robust prognostic indicator of survival, with higher scores correlating with worse outcomes in most cancer types. The prognostic significance of the score was influenced by factors such as cancer type, tumor pathology, and the tumor microenvironment. Single-cell analysis revealed that myeloid cells, particularly the M2 macrophage subtype, demonstrated high levels of IFGRNS expression, which was associated with tumor progression. A negative correlation was observed between the IFGRNS score and outcomes to anti-PD1 immunotherapy in urologic cancers, where patients with higher scores showed worse prognosis and lower response rates to therapy. Experimental validation in the PAN02 murine model confirmed that anti-PD1 therapy significantly reduced tumor size and IFGRNS expression in M2 macrophages, supporting the clinical findings. The IFGRNS score is a novel prognostic indicator for survival and therapeutic responses in cancer. These findings underline the complexity of IFN-γ signaling and suggest potential applications for the IFGRNS score in cancer diagnosis, prognosis, and immunotherapy. Novelty & impact statements: IFN-γ response genes play a significant role in tumour biology, yet comprehensive analysis across various cancers is limited. This study identifies a novel prognostic biomarker, the IFGRNS score, which is elevated in myeloid lineage cells and correlates with survival across multiple cancers. The IFGRNS score is also associated with tumour pathology, immune microenvironment, and immunotherapy response, highlighting its diagnostic and therapeutic potential in cancer management. IFN-γ cytokine plays a dual role in cancer, aiding immune defense but also promoting tumor progression. A novel IFGRNS score, based on 46 IFN-γ response genes, was identified as a strong prognostic marker for survival across cancer types. Higher IFGRNS scores correlate with worse prognosis and reduced response to anti-PD1 immunotherapy, particularly in urologic cancers. M2 macrophages were identified as key contributors to high IFGRNS scores, associated with tumor progression. Findings were validated in a murine cancer model, highlighting the potential of the IFGRNS score for cancer prognosis and therapy guidance.

BackgroundAlthough the involvement of intra-tumor genetic heterogeneity in tumor progression, treatment resistance, and metastasis is established, genetic heterogeneity is seldom examined in clinical trials or practice. Many studies of heterogeneity have had prespecified markers for tumor subpopulations, limiting their generalizability, or have involved massive efforts such as separate analysis of hundreds of individual cells, limiting their clinical use. We recently developed a general measure of intra-tumor genetic heterogeneity based on whole-exome sequencing (WES) of bulk tumor DNA, called mutant-allele tumor heterogeneity (MATH). Here, we examine data collected as part of a large, multi-institutional study to validate this measure and determine whether intra-tumor heterogeneity is itself related to mortality.Methods and FindingsClinical and WES data were obtained from The Cancer Genome Atlas in October 2013 for 305 patients with head and neck squamous cell carcinoma (HNSCC), from 14 institutions. Initial pathologic diagnoses were between 1992 and 2011 (median, 2008). Median time to death for 131 deceased patients was 14 mo; median follow-up of living patients was 22 mo. Tumor MATH values were calculated from WES results. Despite the multiple head and neck tumor subsites and the variety of treatments, we found in this retrospective analysis a substantial relation of high MATH values to decreased overall survival (Cox proportional hazards analysis: hazard ratio for high/low heterogeneity, 2.2; 95% CI 1.4 to 3.3). This relation of intra-tumor heterogeneity to survival was not due to intra-tumor heterogeneity’s associations with other clinical or molecular characteristics, including age, human papillomavirus status, tumor grade and TP53 mutation, and N classification. MATH improved prognostication over that provided by traditional clinical and molecular characteristics, maintained a significant relation to survival in multivariate analyses, and distinguished outcomes among patients having oral-cavity or laryngeal cancers even when standard disease staging was taken into account. Prospective studies, however, will be required before MATH can be used prognostically in clinical trials or practice. Such studies will need to examine homogeneously treated HNSCC at specific head and neck subsites, and determine the influence of cancer therapy on MATH values. Analysis of MATH and outcome in human-papillomavirus-positive oropharyngeal squamous cell carcinoma is particularly needed.ConclusionsTo our knowledge this study is the first to combine data from hundreds of patients, treated at multiple institutions, to document a relation between intra-tumor heterogeneity and overall survival in any type of cancer. We suggest applying the simply calculated MATH metric of heterogeneity to prospective studies of HNSCC and other tumor types.

Cancer research has long sought to understand the complex tumor microenvironment and the molecular underpinnings of tumor progression. Traditional methods often fail to capture the spatial organization and cell-cell interactions within tumors. The CosMx® Spatial Molecular Imager (SMI) with its CosMx Whole Transcriptome (WTX) panel offers a transformative solution, providing spatially resolved, single-cell transcriptomics with nanometer-scale precision. This platform enables the mapping of RNA molecules within their native tissue context, which is essential for uncovering critical biological insights related to cancer cell behavior, tumor microenvironment interactions, and therapeutic responses. We developed and optimized a tailored protocol for in vitro cell-based assays using the CosMx WTX platform. Key steps, including permeabilization and enzymatic digestion, were fine-tuned to preserve RNA integrity and cellular morphology, ensuring high-quality transcript detection. Cancer cell lines, U2OS (osteosarcoma) and SH-SY5Y (neuroblastoma), were cultured and analyzed using CosMx WTX to map the spatial distribution of RNA transcripts. The data were compared to bulk RNA-seq results to validate reproducibility and accuracy. The assay’s spatial resolution allows for precise mapping of individual RNA molecules within their spatial context, facilitating phenotype-associated spatial transcriptomics. In our analysis, the CosMx WTX platform successfully quantified approximately 7,300 transcripts per cell in U2OS cells and 1,900 transcripts per cell in SH-SY5Y cells, showing high reproducibility and strong agreement with bulk RNA-seq data. This high-throughput capability allows for robust transcriptomic profiling of diverse cancer cell types. By correlating gene expression data with morphological and functional phenotypes, we were able to visualize the spatial organization of transcripts within cells. The platform’s nanometer-scale resolution also supports mapping of cancer organoids, offering insights into intratumoral heterogeneity, treatment resistance, and metastatic processes. The CosMx WTX cell-based assay represents a significant advancement in spatially resolved transcriptomics. By enabling high-resolution analyses, this platform provides valuable insights into cancer biology and offers a powerful tool for drug screening and companion diagnostic development. The integration of spatial transcriptomics with protein-level data holds the potential to transform our approach to cancer diagnostics and therapy, advancing precision medicine and improving patient outcomes. Citation Format: Yi Cui, Margaret Hoang, Shanshan He, Rachel Liu, Tushar Rane, Rustem Khafizov, Haiyan Zhai, Christine Kang, Michael Rhodes, Joseph Beechem. Whole transcriptome spatial exploration of cultured tumor cells at subcellular resolution [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2779.

One of the challenging features of cancer is intratumoral heterogeneity (ITH). The existence of ITH can have profound consequences on tumor progression and drug sensitivity. However it is been essentially impossible to monitor the extent to which individual clonal populations contribute to and affect tumor behavior because of our inability to culture tumor cells from patients in vitro without loosing initial heterogeneity resulting from clonal selection under culture conditions. Through our collaboration with Dr. Tan Ince, we have access to cell culture medium (WIT-OC media) that allows primary tumor cells to undergo continuous population doublings without selecting for or against specific clones under culture conditions. By utilizing this media we have generated 80 single cell clones from a Clear cell Carcinoma (CCC) patient sample and monitored the extent of phenotypic and genomic heterogeneity among 12 of the clonal populations. These clones showed striking heterogeneity in copy number alterations as well as phenotypic heterogeneity in vitro as assessed by anoikis, growth in soft agar, doubling time, and growth in 3D reconstituted basement membrane cultures. We also examined correlations between in vitro properties and tumor formation in vivo using clones tagged with Gaussia-Luciferase (Gluc), a secreted luciferase that is secreted from cells and can be assayed in whole blood. We found that only three clones were transplantable by themselves; however, the clone which showed the most rapid expansion in the mouse was limited in it tumorigenic capacity, generating only ascitic tumor populations. To address whether clonal heterogeneity could contribute to tumor progression, we transplanted mixtures of clones and utilized barcoded clones to analyze the clonal composition of tumor masses. Interestingly, mixtures of the 12 clones resulted in the generation of more aggressive tumors, including the formation of solid tumors and metastases to lungs, liver and brain and allow in vivo growth; these metastatic growths contain distinct mixtures of individual clonal populations. Moreover, clones that could not initiate tumor formation individually could generate metastatic tumors, suggesting that there is cooperativity between the clones to enhance growth and induce metastasis. The study has provided evidence that cell lines generated from individual clones vary significantly in their functional activities in vitro and in vivo. Moreover, by studying the single cell clones, we have found evidence for the existence of interclonal crosstalk during tumor progression and are currently studying the nature and impact of such crosstalk on tumor progression and metastasis. Citation Format: Suha Naffar-Abu Amara, Laura Selfors, Marit Krohn, Tan Ince, Gordon Mills, Joan Brugge. Intratumoral cellular heterogeneity of epithelial ovarian carcinoma and its impact on tumor behavior. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2976. doi:10.1158/1538-7445.AM2014-2976

Intratumor functional heterogeneity is the presence of multiple subpopulations or localized regions with different physiological properties that affect cancer biology (e.g., motility, invasion) and/or response to systemic therapy. Functional heterogeneity may reflect unique aspects of the tumor microenvironment or cellular genetic diversity including, but not limited to, the consequences of different localized patterns of vascular perfusion, stromal infiltration, somatic mutation, epigenetic modifications. Given the continuing improvements in tumor imaging technologies and the biological importance of tumor vascularization as a major driver of functional heterogeneity, the goal of the present work was to develop novel mathematical models to study vascular heterogeneity and its changes in tumors using data from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). DCE-MRI provides a noninvasive in vivo method to evaluate tumor vasculature architectures based on contrast accumulation and washout. Understanding the role of vascular heterogeneity in tumors has significant implications for advancing individualized cancer diagnosis and treatment. To improve vascular characterization, we developed multi-tissue compartment modeling (MTCM). Notably, MTCM is a fully unsupervised method for deconvoluting dynamic imaging series data from heterogeneous tumors that contain unknown numbers of distinct vascular compartments. The pixel-wise tracer concentration in a particular vascular compartment is modeled as being proportional to the local volume transfer constant of the vascular compartment. However, the imaging data often contain significant numbers of partial-volume pixels. To address this limitation, MTCM estimates pharmacokinetic parameters (flux rate constants) using the time-courses of pure-volume pixels, i.e., the signals from those pixels highly enriched in a particular vascular compartment. A convex analysis of mixtures scheme is applied to identify those pure-volume pixels present at the vertices of the clustered pixel time series scatter simplex, without any knowledge of compartment distribution. Thus, MTCM offers an unsupervised approach to characterize intratumor heterogeneity. Applying MTCM to dynamic contrast-enhanced MRI of breast cancers revealed characteristic intratumor vascular heterogeneity and therapeutic responses that were otherwise undetectable. We identified differential and heterogeneous changes in tissue-specific vascular pharmacokinetics in tumors during treatment that were undetected using standard analysis, including tumor islands of persistent enhancement that have escaped the effects of therapy. While it is not yet possible to assign causality, these in vivo results allowed us to propose new hypotheses regarding the complex relationships between intratumor heterogeneity, clonal repopulation, cancer stem-cell, and therapeutic efficacy. Citation Format: Li Chen, peter Choyke, Robert Clarke, Zaver Bhujwalla, Yue Wang. Unsupervised deconvolution of dynamic imaging reveals intratumor vascular heterogeneity and repopulation dynamics. [abstract]. In: Abstracts: AACR Special Conference on Cellular Heterogeneity in the Tumor Microenvironment; 2014 Feb 26-Mar 1; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(1 Suppl):Abstract nr A10. doi:10.1158/1538-7445.CHTME14-A10

BACKGROUND Glioblastoma (GBM) is the most common and aggressive primary brain tumor in adults, marked by extensive inter- and intratumoral heterogeneity and pronounced therapy resistance. Microglia is a major contributor to this complexity and plays a pivotal role in shaping tumor behavior and modulating responses to therapy. Yet its precise phenotypic and functional states across distinct tumor regions and model systems remain poorly defined. In this study, we employ patient-derived organoids (PDOs) alongside matched primary tissue (PT) to characterize microglial diversity and investigate how microglia contributes to the cellular inter- and intratumoral heterogeneity of GBM. MATERIAL AND METHODS Fresh tumor tissue was obtained from 13 GBM patients and sampled from six spatially distinct regions per tumor. PDOs were generated from these regions and compared to matched PT to evaluate microglial presence, distribution, and morphology. To assess intertumoral heterogeneity, we compared microglial characteristics across patients, while intratumoral heterogeneity was examined by analyzing differences between regions within individual tumors. Subsequently, PDOs were treated with temozolomide (TMZ), and microglia was visualized and quantified using Iba1 immunofluorescence to evaluate treatment-induced morphological changes and shifts in microglial abundance. RESULTS Microglia in PT exhibited a microglia morphology more similar to PDOs than to healthy brain tissue. Distinct microglial distribution patterns emerged across PDOs, with microglia typically arranged in one of four configurations: (1) perinuclear, (2) ring-like, (3) at the PDO margin, or (4) diffusely dispersed throughout the PDO. In 5/13 PDOs we found significantly higher microglial abundance compared to PT (PPDO 4 = 0.0013, PPDO 7 = 0.0424, PPDO 8 = 0.0153, PPDO 10 = 0.0162, PPDO 12 = 0.0083). Analysis across patients revealed significant intertumoral heterogeneity in microglial characteristics (p = 0.0405). In terms of intratumoral heterogeneity, regional differences in microglial abundance and morphology were observed within individual PDOs, with statistically significant variation only found in PDO 10 (p = 0.0211). Following TMZ treatment, 4/13 PDOs showed a significant recline in microglial abundance (PDO 2: p < 0.0001; PDO 4: p = 0.0041; PDO 7: p = 0.0015; PDO 10: p = 0.0297). CONCLUSION Our findings reveal significant inter- and intratumoral microglial heterogeneity in PDOs. Distinct microglial distribution patterns and variable responses to TMZ highlight the complex and patient-specific nature of microglial involvement in the GBM microenvironment. These results underscore the relevance of PDOs as a model system for studying tumor-immune interactions and therapeutic responses in a personalized context.

Tumors are typically mosaics of mutant clones that have evolved from a common ancestral cell1–3. This intra-tumor heterogeneity (ITH) is thought to drive both neoplastic progression and acquired therapeutic resistance4–6. Availability of just one sample per tumor and moderate sequencing depth have limited systematic analysis of ITH during previous TCGA pan-cancer analyses7–9, confining the study of ITH to a small numbers of tumor samples and cancer types10–13. The molecular and histopathological causes of ITH and its prognostic significance have thus far remained uncertain14–17. To overcome these limitations, we used an analysis method called EXPANDS18 that estimates the proportion of cells harboring specific mutations from exome sequencing data, as well as other methods that quantify ITH15,19. We extrapolate the number of genetically diverse clonal subpopulations in 1,165 primary tumors among 12 different cancer types from TCGA and investigate mechanisms underpinning ITH as well as the correlation of ITH and genomic instability with prognosis. Lastly we validate the prognostic significance of genomic instability in an independent, high-density SNP-array dataset consisting of 2010 tumor samples, across seven additional cancer types. We found evidence of ITH in the vast majority of tumors. Driver gene mutations, prevalence of copy number gains and tumor microenvironment composition were significantly associated with increased ITH. Mutations in driver genes tended to have a characteristic clone size, suggesting differential fitness effects of those mutations. The detection of a mutation in a driver gene that typically appears in a small clone was a predictor of poor survival. In general, ITH was a universal biomarker of prognosis: across cancer types poor prognosis was associated with intermediate, rather than very low or high, levels of ITH. This was also true for the fraction of tumor genome affected by copy number alterations16,20: tumors with intermediate copy number burden (50 to 75% of the genome affected by copy number alterations) progressed faster than tumors with higher copy number burden, independent of cancer type. Chemo-radiation therapy administration was more efficient in decelerating tumor progression among patients with intermediate copy number burden than among patients with low or high copy number burden. These results were validated and confirmed in the independent SNP-array dataset. This study suggests a tradeoff exists between the costs and benefits of genomic instability21,22 that impacts both the evolvability and fitness of the tumor cell population. In the future, this tradeoff might be exploited to improve survival. In summary, we have shown that ITH is a universal feature of human cancers that predicts survival.

In the United States and globally, prostate cancer (PCa) mortality rates are the highest among men of African descent. 24% of the disparities in PCa remains even when controlled for access to care and stage at presentation. Moreover, the tumor microenvironment plays an essential role in tumor progression, aggressiveness, therapeutic response, and patient outcomes. Additionally, the association of the genomic findings with patient ancestry and other characteristics, such as tumor biology and transcriptomic alterations, remains poorly understood. Here, we performed a multi-Omics approach (N=447) to unravel the complexity of tumor heterogeneity and understand disease progression & distinct tumor biology influenced by genetic ancestry. We performed Whole Exome (Normal/tumor paired) Sequencing matched with Methyl Seq and Whole transcriptomic Sequencing for three datasets of our African, African American Men (AAM), and European Men (EAM). Additionally, we ran Spatial NanoString high-plex GeoMx-DSP for a total of 118 treatment-naive PCa patients (around 500 ROIs). Simultaneously, we added matched whole transcriptome Sequencing for these patients. The cohort comprised 87 AAM, 3 unknown, and 28 EAM self-reported individuals. To verify the self-reported race, the genomic ancestry was qualified using genotype and Admixture analysis. To further validate differentially expressed genes at the protein level, we performed multi-plex histological staining of 40 markers to determine the spatial resolution and neighborhood clustering within the tumor and the microenvironment. In parallel, we performed scMultiOmics sequencing (scRNA & scATAC-Seq) at a single-cell resolution (6000 cells/sample at 25K reads per cell) from an additional 12 patients (9 AAM & 3 EAM). We reconstructed a 3D model of the distinct tumor microenvironment at subcellular resolution using serially sectioned hematoxylin and eosin- stained tissue sections (CODA technology). Our results demonstrate that patients who self-report as AAM or Nigerian are assigned to high African (> 70%) Ancestry with either Yoruba (Nigeria) and/or Bantu subpopulation in the Sub-Saharan area. Additionally, high African Ancestry patients are diagnosed at a younger age and show advanced pathology stages compared to patients with European Ancestry. AAM of Yoruba descent expresses significantly higher immune-inflammatory signatures (STAT/IFNG-signaling pathway) compared to the Nigerian-Yoruba subpopulation. Our scRNA-Seq analysis shows that AAM has suppressive myeloid cells infiltrate within the tumor cells. The infiltrations of these cells change with age, Gleason Grade, and pathology stage. Moreover, AAM-tumor cells (scATAC-Seq) have increased open Chromatin accessibility with STAT motifs enrichment (p-value;0.0001), which could be the driver regulators of the immune-suppressive signature as well as influence the upregulation of STAT/IFNG signature within African Ancestry patients. Our study provides new insight into how genetic ancestry impacts immune signatures in AAM/African and contributes to PCa racial disparities. Citation Format: Isra Elhussin, Ezra Baraban1, Ashley Kiemen, Tamara L Lotan, Cathy Handy Marshall, Emmanuel Antonarakis, Moray J Campbell, Melissa Davis, Michael Dixon, Isaac Kim, Stefan Ambs, Rick Kittles, Adam B Murphy, Clayton Yates. Integrative multi-omics profiling in patients of African descent diagnosed with prostate cancer reveals distinct tumor-promoting immunosuppressive niches at a single-cell level and spatial resolution [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr C117.

Tumor Evolution and Intratumor Heterogeneity of an Oropharyngeal Squamous Cell Carcinoma Revealed by Whole-Genome Sequencing

Background: Tumor cells and their stromal cell counterparts that comprise the tumor microenvironment (TME) reciprocally coevolve to generate heterocellular communication networks. A distinctive characteristic of the functional organization of this continuously evolving ecosystem is spatial intratumoral heterogeneity (ITH), a key determinant of disease progression landmarks in multiple carcinomas that include colorectal cancer. To optimize diagnosis, prognosis, therapeutic strategies and to identify novel therapeutic targets it is important to define spatial ITH in the tumors of individual patients and determine the mechanistic underpinnings of its relationship to metastatic potential, immune evasion, recurrence, therapeutic response and drug resistance. Methods: The first step in investigating spatial ITH is to identify the cell phenotypes within the TME. This, however, is a challenging task owing not only to the diversity of well-defined cell types within the TME but also the intrinsic plasticity of many of these cell types in response to the selection pressures within their particular confines (i.e., microdomains). There has been a recent explosion of hyperplexed (> 9 fluorescence or mass spec-based) biomarker labeling and imaging modalities utilizing various reagent technologies to probe the same tissue sections with several dozens of biomarkers at cellular and subcellular resolutions. The challenge now is to accurately characterize the complex spatial and high-dimensional output of these hyperplexed techniques. Results: We propose LEAPH an unsupervised machine learning algorithm for characterizing in situ phenotypic heterogeneity in tissue samples. LEAPH builds a phenotypic hierarchy of cell types, cell states and their spatial configurations. The recursive modeling steps involve determining cell types with low-ranked mixtures of factor analyzers and optimizing cell states with spatial regularization. We applied LEAPH to hyperplexed (51 biomarkers) immunofluorescence images of colorectal carcinoma primary tumors (N=213). LEAPH, combined with pointwise mutual information (PMI), enables the discovery of phenotypically distinct microdomains, composed of spatially configured computational phenotypes. Harnessing network biology. LEAPH identified a subset of microdomains composed of cancer stem cells driving a Wnt signaling- based immunosuppressive program in patients who exhibited recurrence within 3 years of surgical resection. The LEAPH framework, when combined with microdomain discovery and microdomain-specific network biology, has the potential to provide insights into pathophysiological mechanisms, identify novel drug targets and inform therapeutic strategies for individual patients. Citation Format: Samantha Furman, Andrew Stern, Shikhar Uttam, Taylor D. Lansing, Pullara Filippo, S. CHAKRA Chennubhotla. 1 Unsupervised cellular phenotypic hierarchy enables spatial intratumor heterogeneity characterization, recurrence-associated microdomains discovery, and harnesses network biology from hyperplexed in-situ fluorescence images of colorectal carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 3172.

BackgroundNon Small Cell Lung Cancer is a highly heterogeneous tumor. Histologic intratumor heterogeneity could be ‘major’, characterized by a single tumor showing two different histologic types, and ‘minor’, due to at least 2 different growth patterns in the same tumor. Therefore, a morphological heterogeneity could reflect an intratumor molecular heterogeneity. To date, few data are reported in literature about molecular features of the mixed adenocarcinoma. The aim of our study was to assess EGFR-mutations and ALK-rearrangements in different intratumor subtypes and/or growth patterns in a series of mixed adenocarcinomas and adenosquamous carcinomas.Methods590 Non Small Cell Lung Carcinomas tumor samples were revised in order to select mixed adenocarcinomas with available tumor components. Finally, only 105 mixed adenocarcinomas and 17 adenosquamous carcinomas were included in the study for further analyses. Two TMAs were built selecting the different intratumor histotypes. ALK-rearrangements were detected through FISH and IHC, and EGFR-mutations were detected through IHC and confirmed by RT-PCR.Results10/122 cases were ALK-rearranged and 7 from those 10 showing an intratumor heterogeneity of the rearrangements. 12/122 cases were EGFR-mutated, uniformly expressing the EGFR-mutated protein in all histologic components.ConclusionOur data suggests that EGFR-mutations is generally homogeneously expressed. On the contrary, ALK-rearrangement showed an intratumor heterogeneity in both mixed adenocarcinomas and adenosquamous carcinomas. The intratumor heterogeneity of ALK-rearrangements could lead to a possible impact on the therapeutic responses and the disease outcomes.

In the study of cancer, omics technologies are supporting the transition from traditional clinical approaches to precision medicine. Intra-tumoral heterogeneity (ITH) is detectable within a single tumor in which cancer cell subpopulations with different genome features coexist in a patient in different tumor areas or may evolve/differ over time. Colorectal carcinoma (CRC) is characterized by heterogeneous features involving genomic, epigenomic, and transcriptomic alterations. The study of ITH is a promising new frontier to lay the foundation towards successful CRC diagnosis and treatment. Genome and transcriptome sequencing together with editing technologies are revolutionizing biomedical research, representing the most promising tools for overcoming unmet clinical and research challenges. Rapid advances in both bulk and single-cell next-generation sequencing (NGS) are identifying primary and metastatic intratumoral genomic and transcriptional heterogeneity. They provide critical insight in the origin and spatiotemporal evolution of genomic clones responsible for early and late therapeutic resistance and relapse. Single-cell technologies can be used to define subpopulations within a known cell type by searching for differential gene expression within the cell population of interest and/or effectively isolating signal from rare cell populations that would not be detectable by other methods. Each single-cell sequencing analysis is driven by clustering of cells based on their differentially expressed genes. Genes that drive clustering can be used as unique markers for a specific cell population. In this review we analyzed, starting from published data, the possible achievement of a transition from clinical CRC research to precision medicine with an emphasis on new single-cell based techniques; at the same time, we focused on all approaches and issues related to this promising technology. This transition might enable noninvasive screening for early diagnosis, individualized prediction of therapeutic response, and discovery of additional novel drug targets.

Cancer initiation and development engage extremely complicated pathological processes which involve alterations of a large number of cell signaling cascades and functional networks in temporal and spatial orders. During last decades, microRNAs (miRNAs), a class of non-coding RNAs, have emerged as critical players in cancer pathogenesis and progression by modulating many pathological aspects related to tumor development, growth, metastasis, and drug resistance. The major function of miRNAs is to post-transcriptionally regulate gene expression depending on recognition of complementary sequence residing in target mRNAs. Commonly, a particular miRNA recognition sequence could be found in a number of genes, which allows a single miRNA to regulate multiple functionally connected genes simultaneously and/or chronologically. Furthermore, a single gene can be targeted and regulated by multiple miRNAs. However, previous studies have demonstrated that miRNA functions are highly context-dependent, which leads to distinct pathological outcomes in different types of cancer as well as at different stages by alteration of the same miRNA. Here we summarize recent progress in studies on miRNA function in cancer initiation, metastasis and therapeutic response, focusing on breast cancer. The varying functions of miRNAs and potential application of using miRNAs as biomarkers as well as therapeutic approaches are further discussed in the context of different cancers.