Degree Of Intratumoral Heterogeneity Research Articles

Abstract 1157: Uncovering transcriptional changes related to cisplatin treatment and mixing of TNBC subclones using single-cell RNA sequencing

Abstract Triple negative breast cancer (TNBC) has long been characterized by having a high degree of intratumoral heterogeneity. While significant contributions have been made in understanding the components of TNBC tumors, examining the dynamics of interaction between subclones in TNBC is relatively unexplored. By using single-cell RNA sequencing (scRNA-seq) technology, this study aims to focus on understanding changes in gene expression of two TNBC subclones: the cisplatin-resistant subclone (A50) and cisplatin-sensitive subclone (B), when cocultured in 3D organoids in the presence and absence of cisplatin. We hypothesized that there will be significant differentially expressed genes (DEGs) due to various concentrations of cisplatin and mixing effect. We found DEGs (ACTB, FOS, EIF5, BRD2, MAFG, SF3B4, ID1, MGMT, DDIT4 and LPP) due to treatment with cisplatin in both subclones, with the largest clear effect present at a high concentration of cisplatin. Additionally, the network analysis showed that cisplatin was an upstream regulator for 11 DEGs. Even though, gene expression changes due to mixing are much more subtle than effects due to treatment, we saw some DEGs caused by the mixing effect like MT1X which is related to cisplatin resistance. Taken together, the findings of this project will help in future studies when deducing which genes to target in TNBC chemotherapy treatments based on predictive molecular biomarkers. Citation Format: Shadae Nicholas, Patience Mukashyaka, Pooja Kumar, Jeffrey Chuang, Edison Liu. Uncovering transcriptional changes related to cisplatin treatment and mixing of TNBC subclones using single-cell RNA sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1157.

Intratumor heterogeneity analysis in lung adenocarcinoma by single-cell RNA sequencing and construction of a prognostic gene signature.

e20521 Background: Lung adenocarcinoma (LUAD), at the cellular level, has a high degree of intratumor heterogeneity. Advanced single-cell sequencing technologies have offered tools to analyze intratumor heterogeneity and identify the biomarkers, thereby aiding cancer diagnosis and prediction of the patient prognosis. Methods: From the Gene Expression Omnibus (GEO) (www.ncbi.nlm.nih.gov/geo) database, the single-cell RNA sequencing (scRNA-seq) data from two LUAD and two para-cancerous tissue samples were obtained. We performed a dimensionality reduction and unsupervised clustering to identify the different cell clusters within the tumor tissues. To identify the most relevant modules and important cell subpopulations (clusters) in LUAD tissues, a weighted gene co-expression network analysis (WGCNA) was performed. Subsequently, we classified the LUAD molecular subtypes according to the marker genes of these clusters. The Limma package ( www.bioconductor.org/packages/release/bioc/html/limma ) was used to screen for the differentially expressed genes (DEGs) between the subtypes. Using univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses, the gene signature most significantly associated with the prognosis of LUAD patients was determined. Results: A total of 14 cell clusters belonging to 10 cell types in LUAD was identified. The turquoise module was found to be the most relevant to LUAD among all the modules; cluster 10 (C10) was found to be the most strongly associated with the turquoise module. In The Cancer Genome Atlas (TCGA), patients with LUAD were divided into two groups of distinct molecular subtypes. Based on the 165 shared genes between the turquoise module and C10, 511 DEGs between the two molecular subtypes were obtained, and five of them were selected to construct the gene signature, which was validated to be an independent prognostic marker of LUAD. Conclusions: 14 cell clusters co-existed in LUAD, which contributed to its intratumor heterogeneity. In addition, two molecular subtypes of LUAD were identified and a five-gene signature was developed and validated to be significantly associated with prognostic and clinical characteristics of LUAD patients. Keywords: single-cell RNA sequencing, lung adenocarcinoma, intratumor heterogeneity, molecular subtypes, prognosis, five-gene signature.

Comparative genomics of primary prostate cancer and paired metastases: insights from 12 molecular case studies.

Primary prostate cancer (PCa) can show marked molecular heterogeneity. However, systematic analyses comparing primary PCa and matched metastases in individual patients are lacking. We aimed to address the molecular aspects of metastatic progression while accounting for the heterogeneity of primary PCa. In this pilot study, we collected 12 radical prostatectomy (RP) specimens from men who subsequently developed metastatic castration‐resistant prostate cancer (mCRPC). We used histomorphology (Gleason grade, focus size, stage) and immunohistochemistry (IHC) (ERG and p53) to identify independent tumors and/or distinct subclones of primary PCa. We then compared molecular profiles of these primary PCa areas to matched metastatic samples using whole‐exome sequencing (WES) and amplicon‐based DNA and RNA sequencing. Based on combined pathology and molecular analysis, seven (58%) RP specimens harbored monoclonal and topographically continuous disease, albeit with some degree of intratumor heterogeneity; four (33%) specimens showed true multifocal disease; and one displayed monoclonal disease with discontinuous topography. Early (truncal) events in primary PCa included SPOP p.F133V (one patient), BRAF p.K601E (one patient), and TMPRSS2:ETS rearrangements (eight patients). Activating AR alterations were seen in nine (75%) mCRPC patients, but not in matched primary PCa. Hotspot TP53 mutations, found in metastases from three patients, were readily present in matched primary disease. Alterations in genes encoding epigenetic modifiers were observed in several patients (either shared between primary foci and metastases or in metastatic samples only). WES‐based phylogenetic reconstruction and/or clonality scores were consistent with the index focus designated by pathology review in six out of nine (67%) cases. The three instances of discordance pertained to monoclonal, topographically continuous tumors, which would have been considered as unique disease in routine practice. Overall, our results emphasize pathologic and molecular heterogeneity of primary PCa, and suggest that comprehensive IHC‐assisted pathology review and genomic analysis are highly concordant in nominating the ‘index’ primary PCa area. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Targeting immunometabolism of neoplasms by interleukins: A promising immunotherapeutic strategy for cancer treatment.

In recent years, tumor metabolism has become a prevalent research topic for scientists and pharmaceutical companies. As research in the field has progressed, the metabolism-based therapy of tumors has ushered in new opportunities. Most tumors emerge and evolve under selective pressure from their microenvironment, which promotes the diversification of both neoplastic and non-neoplastic compartments of the tumor microenvironment (TME), and finally reaches a certain degree of intratumoral heterogeneity. As a result of the tumor intratumoral heterogeneity, tumor cells often possess a complex energy metabolism phenotype. During tumor progression, the metabolism for both tumor parenchyma and stroma is reprogrammed. The tumor stroma mainly consists of the extracellular matrix, fibroblasts, and immune cells. Interestingly, tumor-infiltrating immune cells utilize different metabolites based on their subtype and function, and these immunometabolic pathways can be modified in the TME. In particular, interleukins play a vital role in the activation and differentiation of immune cells and have exhibited multiple effects on tumor cell neoplasia, invasion, and metastasis. In this review, we summarize the common mechanisms of interleukins affecting the tumor and tumor-infiltrating immune cells metabolically and discuss how these mechanisms may lead to novel therapeutic opportunities. This review might contribute to the novel development of cancer immunotherapy.

KEAP1 and TP53 Frame Genomic, Evolutionary, and Immunologic Subtypes of Lung Adenocarcinoma With Different Sensitivity to Immunotherapy

IntroductionThe connection between driver mutations and the efficacy of immune checkpoint inhibitors is the focus of intense investigations. In lung adenocarcinoma (LUAD), KEAP1/STK11 alterations have been tied to immunoresistance. Nevertheless, the heterogeneity characterizing immunotherapy efficacy suggests the contribution of still unappreciated events. MethodsSomatic interaction analysis of top-ranking mutant genes in LUAD was carried out in the American Association for Cancer Research (AACR) Project Genomics Evidence Neoplasia Information Exchange (GENIE) (N = 6208). Mutational processes, intratumor heterogeneity, evolutionary trajectories, immunologic features, and cancer-associated signatures were investigated, exploiting multiple data sets (AACR GENIE, The Cancer Genome Atlas [TCGA], TRAcking Cancer Evolution through therapy [Rx]). The impact of the proposed subtyping on survival outcomes was assessed in two independent cohorts of immune checkpoint inhibitor–treated patients: the tissue-based sequencing cohort (Rome/Memorial Sloan Kettering Cancer Center/Dana-Farber Cancer Institute, tissue-based next-generation sequencing [NGS] cohort, N = 343) and the blood-based sequencing cohort (OAK/POPLAR trials, blood-based NGS cohort, N = 304). ResultsObserving the neutral interaction between KEAP1 and TP53, KEAP1/TP53-based subtypes were dissected at the molecular and clinical levels. KEAP1 single-mutant (KEAP1 SM) and KEAP1/TP53 double-mutant (KEAP1/TP53 DM) LUAD share a transcriptomic profile characterized by the overexpression of AKR genes, which are under the control of a productive superenhancer with NEF2L2-binding signals. Nevertheless, KEAP1 SM and KEAP1/TP53 DM tumors differ by mutational repertoire, degree of intratumor heterogeneity, evolutionary trajectories, pathway-level signatures, and immune microenvironment composition. In both cohorts (blood-based NGS and tissue-based NGS), KEAP1 SM tumors had the shortest survival; the KEAP1/TP53 DM subgroup had an intermediate prognosis matching that of pure TP53 LUAD, whereas the longest survival was noticed in the double wild-type group. ConclusionsOur data provide a framework for genomically-informed immunotherapy, highlighting the importance of multimodal data integration to achieve a clinically exploitable taxonomy.

Single Cell Genetic Profiling of Tumors of Breast Cancer Patients Aged 50 Years and Older Reveals Enormous Intratumor Heterogeneity Independent of Individual Prognosis.

Simple SummaryThe majority (69.7%) of women diagnosed with breast cancer are above the age of 55. The population of older breast cancer patients is growing. Nevertheless, older patients are underrepresented in cancer research. Therefore, our study set the focus on breast cancer patients aged 50 years and older with a median age of 67 years aiming to understand the influence of aneuploidy, genomic instability and inter- and intratumor heterogeneity on disease outcome, being a major obstacle for precise prognostication and successful treatment. We analyzed chromosomal copy number changes, ploidy and specific gene mutations and found an enormous degree of genomic instability and intratumor heterogeneity in our cohort. However, neither the ploidy, the degree of intratumor heterogeneity nor the presence of specific gene mutations was correlated with prognosis. Our findings provide a precise description of the degree of intratumor heterogeneity, genomic instability, and gene mutations in breast cancer patients aged 50 years and older, revealing significant differences between diploid and aneuploid tumors regarding copy number alterations and the extent of genomic instability.Purpose: Older breast cancer patients are underrepresented in cancer research even though the majority (81.4%) of women dying of breast cancer are 55 years and older. Here we study a common phenomenon observed in breast cancer which is a large inter- and intratumor heterogeneity; this poses a tremendous clinical challenge, for example with respect to treatment stratification. To further elucidate genomic instability and tumor heterogeneity in older patients, we analyzed the genetic aberration profiles of 39 breast cancer patients aged 50 years and older (median 67 years) with either short (median 2.4 years) or long survival (median 19 years). The analysis was based on copy number enumeration of eight breast cancer-associated genes using multiplex interphase fluorescence in situ hybridization (miFISH) of single cells, and by targeted next-generation sequencing of 563 cancer-related genes. Results: We detected enormous inter- and intratumor heterogeneity, yet maintenance of common cancer gene mutations and breast cancer specific chromosomal gains and losses. The gain of COX2 was most common (72%), followed by MYC (69%); losses were most prevalent for CDH1 (74%) and TP53 (69%). The degree of intratumor heterogeneity did not correlate with disease outcome. Comparing the miFISH results of diploid with aneuploid tumor samples significant differences were found: aneuploid tumors showed significantly higher average signal numbers, copy number alterations (CNAs) and instability indices. Mutations in PIKC3A were mostly restricted to luminal A tumors. Furthermore, a significant co-occurrence of CNAs of DBC2/MYC, HER2/DBC2 and HER2/TP53 and mutual exclusivity of CNAs of HER2 and PIK3CA mutations and CNAs of CCND1 and PIK3CA mutations were revealed. Conclusion: Our results provide a comprehensive picture of genome instability profiles with a large variety of inter- and intratumor heterogeneity in breast cancer patients aged 50 years and older. In most cases, the distribution of chromosomal aneuploidies was consistent with previous results; however, striking exceptions, such as tumors driven by exclusive loss of chromosomes, were identified.

Abstract 15: Confirmatory integrated proteogenomic characterization of clear cell renal cell carcinoma

Abstract Clear cell renal cell carcinoma (ccRCC) is the most predominant histology of renal cell carcinoma (RCC), representing 75% of all RCC cases and accounting for the majority of associated deaths. Previously, the Clinical Proteomics Tumor Analysis Consortium (CPTAC) leveraged a proteogenomic approach to characterize a cohort of 103 ccRCC tumors and 80 paired normal adjacent tissue (NAT) samples to better understand the impact of genomic alterations on the functional modules that drive ccRCC tumorigenesis. Results of our report included delineating chromosomal translocations as a possible mechanism for 3p loss in ccRCC, detecting phospho-substrate targets for FDA-approved kinase inhibitors, and identifying four immune-based subtypes of ccRCC. In this report, we sought to verify these initial findings in an independent cohort comprised of 112 RCC tumors and 87 paired NAT samples. Leveraging data-independent acquisition mass spectrometry based proteomic strategies with comprehensive genomic and transcriptomic analyses, we integrated proteomic and phosphoproteomic analyses with genomic, epigenomic, microRNA, and transcriptomic data for tumor and NAT samples in a confirmatory cohort to elucidate the dysregulated cellular mechanism resulting from genomic alterations. We observed a high degree of concordance of genomic and transcriptomic signatures, as well as comparable tumor microenvironment cell compositions in this confirmatory cohort with our previous discovery cohort, indicating that many of the molecular characteristics defined in our first report are robustly maintained. Proteomic characterization identified protein profiles associated with disparate genomic alterations associated with ccRCC, as well as protein features specific to the four immune-based subtypes of ccRCC: CD8+ Inflamed, CD8- Inflamed, VEGF Immune Desert, and Metabolic Immune Desert. Investigation of the impact of FDA-approved kinase inhibitors, prioritized by our phosphoproteomic results, allowed for the examination of the functional consequences of these therapies respective to their mechanisms of action in ccRCC cells via the targeting of ERK/MAPK and PI3K/AKT signaling pathways, and G2/M cell cycle regulation. Finally, we explored the degree of intratumor heterogeneity of ccRCC at the genomic, transcriptomic, and proteomic levels, revealing molecular profiles that were maintained or altered in distinct regions of tumors, and further linked these molecular signatures to observed histopathological features. Overall, our study advances our understanding of functional consequences of the genomic alterations on gene and protein expression as well as subsequent cell signaling pathways related to targets for potential new therapeutic intervention, while further supporting the rationale for integrating multi-level “omics” analyses to characterize the proteogenomic landscape of ccRCC pathobiology. Citation Format: David J. Clark, Yize Li, Clinical Proteomic Tumor Analysis Consortium. Confirmatory integrated proteogenomic characterization of clear cell renal cell 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 15.

Thyroid Cancer Stem-Like Cells: From Microenvironmental Niches to Therapeutic Strategies.

Thyroid cancer (TC) is the most common endocrine malignancy. Recent progress in thyroid cancer biology revealed a certain degree of intratumoral heterogeneity, highlighting the coexistence of cellular subpopulations with distinct proliferative capacities and differentiation abilities. Among those subpopulations, cancer stem-like cells (CSCs) are hypothesized to drive TC heterogeneity, contributing to its metastatic potential and therapy resistance. CSCs principally exist in tumor areas with specific microenvironmental conditions, the so-called stem cell niches. In particular, in thyroid cancer, CSCs’ survival is enhanced in the hypoxic niche, the immune niche, and some areas with specific extracellular matrix composition. In this review, we summarize the current knowledge about thyroid CSCs, the tumoral niches that allow their survival, and the implications for TC therapy.

Abstract PO-082: Automated tumor segmentation, grading, and analysis of tumor heterogeneity in preclinical models of lung adenocarcinoma

Abstract Preclinical mouse models of lung adenocarcinoma are invaluable for the discovery of molecular drivers of tumor formation, progression, and therapeutic resistance. Histological analyses of these preclinical models require significant investments of time and training to ensure accuracy and consistency. Analysis by a clinical pathologist is the gold standard in this approach, but may be difficult to obtain due to the cost and availability of their services. As an alternative we have developed a digital pathology tool to identify, segment, grade, and analyze tumors in mouse models of lung adenocarcinoma. This convolutional neural network (CNN) model, based on ResNet18, was trained to classify normal lung tissue, normal airways, and the different grades (1 – 4) of lung adenocarcinoma from 100,000 224 × 224 pixel image patches (~16,000 patches per class). Our training dataset was constructed from whole slide images of hematoxylin and eosin stained lung sections from 4 different mouse models of lung adenocarcinoma with oncogenic Kras (KrasG12D/+), in combination with oncogenic p53 mutations (KrasG12D/+; p53R172H/+ and KrasG12D/+;p53R270H/+), or with the loss of the tumor suppressive TAp73 (KrasG12D/+;TAp7fltd/fltd). Our CNN demonstrated a strong correspondence with human pathologists on our holdout dataset, achieving a micro-F1 score of 0.81 on a pixel-by-pixel basis. As a test of our CNN, we analyzed two mouse models to better understand the role of TAp73 in lung adenocarcinoma: KrasG12D/+ (“K”) and KrasG12D/+;TAp73fltd/fltd (“TK”). Both human raters and our CNN reported a significant increase in the tumor burden of the compound mutant “TK” mice compared to the single mutant “K” mice. According to our CNN, this increased tumor burden was driven primarily by an increase in tumor size and not an increased number of tumors in “TK” mice. Because our CNN can assign different grades to regions within the same image patch and tumor, we also uncovered a high degree of intratumor heterogeneity that was not reported by the human pathologists, who are trained to assign one grade to a single tumor with a bias for the highest grade present in a given tumor. The finer grading resolution allowed our CNN to uncover the increased tumor size observed in the “TK” mice was due to expansion of Grade 2 regions (characterized by enlarged nuclei without irregular shape) within tumors that would be considered a higher grade by pathologists. Our CNN also provides a detailed map of tumor grades overlaid on the H&E images used for analysis, allowing for precise targeting of regions within tumors with other assays. We are currently utilizing these outputs in conjunction with other assays, such as spatial transcriptomic analysis and immunohistochemistry, to investigate the molecular mechanisms that underlie the expansion of Grade 2 tumor regions in “TK” mice. Future work will expand this tool into a multidimensional digital pathology pipeline that can accelerate current investigations and reveal new therapeutic targets and prognostic markers. Citation Format: John H. Lockhart, Hayley D. Ackerman, Kyubum Lee, Mahmoud Abdalah, Andrew Davis, Nicole Montey, Theresa Boyle, James Saller, Ayensur Keske, Kay Hänggi, Brian Ruffell, Olya Stringfield, Aik Choon Tan, Elsa R. Flores. Automated tumor segmentation, grading, and analysis of tumor heterogeneity in preclinical models of lung adenocarcinoma [abstract]. In: Proceedings of the AACR Virtual Special Conference on Artificial Intelligence, Diagnosis, and Imaging; 2021 Jan 13-14. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(5_Suppl):Abstract nr PO-082.

ATRT-28. SINGLE NUCLEI SEQUENCING REVEALS THE DIFFERENT PHENOTYPIC COMPOSITION OF THE ATRT SUBGROUPS

Atypical teratoid/rhabdoid tumors (ATRT) represents a genomically homogeneous disease characterized by loss of SMARCB1 protein in the vast majority of cases. In recent years, it has become clear that these tumors display a high degree of intertumoral heterogeneity with three molecularly distinct subgroups. However, the degree of intratumoral heterogeneity and the information on cellular subpopulations currently remains largely an unchartered territory. To explore the transcriptomic composition of ATRTs, we performed single nuclei RNA sequencing for 16 ATRTs representing all three molecular subgroups (5 ATRT-TYR, 7 ATRT-SHH, 4 ATRT-MYC). By performing tSNE cluster analyses of all the single cell data (~50.000 cells have been sequenced), we were able to gain unprecedented insights into the phenotypic composition of ATRTs and unravelled substantial differences between the three subgroups. Integrating transcriptomic information from non-neoplastic brain cells and the data derived from single nuclei sequencing, we found an OPC like gene signature in ATRT-SHH. In contrast, ATRT-TYR subpopulations overexpressed more markers of neuronal stem cells suggesting a larger fraction of undifferentiated cells in this subgroup. We also identified a subpopulation of cells with a clear overexpression of cell cycle associated genes (CDK4, CDKN3), predominantly present in ATRT-MYC samples, a finding which may harbour important consequences for a targeted therapy with e.g. CDK inhibitors. In summary, our analyses reveal different cellular compartments in ATRT and provide important insights into the cellular differentiation of the three ATRT-subgroups. Further analyses to achieve a specific mapping of ATRT to its physiological cell of origin are currently being pursued.

Abstract PO-023: Spatial genomics coupled with machine learning to identify p53-driven molecular signatures that are predictive of lung adenocarcinoma progression

Abstract P53 is frequently mutated in a wide variety of tumors; yet, the regulation and expression of downstream targets during tumor progression and response to therapy is unknown. Here, we use Kras/p53-driven lung adenocarcinoma in the mouse as a model system to identify p53-driven molecular signatures that predict lung adenocarcinoma progression. Using these tumors, we have developed a digital pathology tool using machine learning to grade lung adenocarcinomas. To do this, we analyzed hematoxylin and eosin (H&E) from mouse models of lung adenocarcinoma with Kras (KrasG12D/+) and in combination with p53 mutations (KrasG12D/+; p53R172H/+ and KrasG12D/+; p53R270H/+) and loss of TAp73 (KrasG12D/+; TAp73Δtd/Δtd). After grading, slides were divided into approximately 100,000 patches with dimensions of 224 × 224 pixels (113 × 113 µm). A convolutional neural network (CNN) model based on ResNet18 was trained to classify normal lung tissue, normal airways, and the different grades (1–4) of lung adenocarcinoma using 16,000 patches of each class. The resulting classification maps were used for analyses of tumor burden and progression. Adjacent tissue sections used for immunohistochemistry were co-registered to mapped H&E sections to investigate correlation between protein expression and tumor grade. Our CNN demonstrated a strong correspondence with human pathologists on our holdout dataset (81% agreement). Because our CNN can assign different grades to different regions within an image patch, we also uncovered a high degree of intratumor heterogeneity that was missed by human pathologists who assigned grades to entire tumors in a homogeneous manner. Both the pathologists and the CNN reported a significant increase in the tumor burden of compound mutant mice (KrasG12D/+; p53R172H/+, KrasG12D/+; p53R270H/+, and KrasG12D/+; TAp73Δtd/Δtd) compared to KrasG12D/+ mice. In addition, compound mutant mice were noted to have a greater proportion of high-grade (3-4) tumors by both approaches. In conclusion, our CNN demonstrates a high degree of agreement with human pathologists. Furthermore, this computational approach drastically increases the resolution of tumor grading in our mouse models and can detect regions of different grades within a single tumor. We are currently using single cell transcriptome analysis to define p53-molecular signatures that predict lung adenocarcinoma progression and grade. Future work will expand this tool into a multidimensional digital pathology pipeline that can accelerate current investigations and reveal new therapeutic targets and prognostic markers. Citation Format: John H. Lockhart, Kyubum Lee, Hayley D. Ackerman, Mahmoud Abdulah, Andrew Davis, Nicole Montey, Theresa Boyle, James Saller, Aysenur Keske, Kay Hanggi, Olya Stringfield, Aik Choon Tan, Elsa R. Flores. Spatial genomics coupled with machine learning to identify p53-driven molecular signatures that are predictive of lung adenocarcinoma progression [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PO-023.

Abstract 225: Frequent abnormalities in TP53 and increased genetic instability in myxofibrosarcoma

Abstract Myxofibrosarcoma (MFS) is a rare subtype of soft tissue sarcomas (STSs) preferentially affecting the elderly. Histologically, MFS is distinct from other STSs, in that it is characterized by the proliferation of pleomorphic spindle cells with varying degrees of myxoid components. However, the molecular pathogenesis of MSF is poorly understood. We conducted an integrated molecular study involving 70 samples from primary MFS patients, in which samples were analyzed by whole-genome sequencing (WGS, n=5), whole-exome sequencing (WES, n=44), targeted-capture sequencing (TS, n=65), RNA sequencing (n=3), and immunohistochemistry (IHC, n=50). Copy number (CN) alterations were detected by sequencing-based CN analysis. We combined our STS data with those from from the Cancer Genome Atlas and European Genome-phenome Archive cohort, including 116 MSF samples, and compared to the data from other STS samples (n=189). To further investigate the genetic basis of mixed histological components and chronological changes in MFS, we performed WES of multi-regional and/or multi-time-point samples from 8 MSF cases. A total of 9,246 mutations were identified by WES in 130 primary MFS samples with a median of 55.5 mutations/sample. Mutations were dominated by age-related C to T transitions at CpG sites. When combining the results from TS, among 188 primary MFS samples, most frequently mutated and/or CN-altered genes included TP53 (n=82, 43.6%), RB1 (n=31, 16.5%), ATRX (n=29, 15.4%), and CDKN2A (n=19, 10.2%). A fusion gene involving TRIO was newly identified by RNA sequencing (n=1). A similar mutational profile was observed in undifferentiated pleomorphic sarcoma (UPS), in which TP53 (59.1%), ATRX (34.0%), RB1 (22.7%), and CDKN2A (20.5%) were the major mutational targets, suggesting the common molecular pathogenesis between these two subtypes. Combined with frequent positive staining in IHC (n=22, 44.0%), TP53 was affected in 55.3% of the MFS cases (n=104). Five MFS cases evaluated by WGS showed complex structural abnormalities suggestive of increased genetic instability, where a median of 179 structural variations were detected per sample. WES with multi-regional sampling (n=5) disclosed a high level of intratumor heterogeneity, in which less than 29.0% of mutations were shared by different samples taken from the same tumor. An analysis of longitudinal samples (n=6) revealed significantly higher numbers of mutations in relapse samples (1.6 times on average, p = 0.03). In all cases, TP53 lesions were present from at the time of the initial diagnosis, while most of other lesions were subclonal and acquired during the clinical course. In summary, the genetic profile of MFS is characterized by frequent abnormalities in TP53, RB1, CDKN2A and ATRX, and closely related to other STSs, particularly to UPS. Clonal TP53 abnormalities resulted in complex chromosomal structure and a high degree of intratumor heterogeneity. Citation Format: Yasuhide Takeuchi, Annegret Kunitz, Adriane Halik, Hiromichi Suzuki, Kenichi Yoshida, Yuichi Shiraishi, Kenichi Chiba, Hiroko Tanaka, Nobuyuki Kakiuchi, Yusuke Shiozawa, Akira Yokoyama, Yoshikage Inoue, Tetsuichi Yoshizato, Kosuke Aoki, Yoichi Fujii, Yasuhito Nannya, Hideki Makishima, Satoru Miyano, Hironori Haga, Frederik Damm, Seishi Ogawa. Frequent abnormalities in TP53 and increased genetic instability in myxofibrosarcoma [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 225.

Abstract 4426: Redox regulation of tumor cell heterogeneity in the PyMT mammary tumor model revealed by single cell RNA sequencing

Abstract Tumor heterogeneity is known to drive breast cancer progression and metastasis. Current therapies target mostly inter-tumor heterogeneity (different patients) without taking into consideration intratumor heterogeneity (individual tumor). Hypoxia is a hallmark of aggressive tumors that is known to select for intratumor cells that are prone for metastasis. Here we show that knockdown of a ROS scavenging enzyme, Glutathione Peroxidase 2, in the PyMT mammary tumor model results in highly hypoxic and metastatic tumors. Single cell RNA-seq on both GPx2 knockdown and control tumors revealed a high degree of intratumor heterogeneity resulting in several clusters that were either of luminal/epithelial or basal-like/mesenchymal type shared by both tumors. Interestingly, GPx2 loss caused increases in a mesenchymal-like/quiescent and a highly proliferative luminal population, implying that GPx2 loss might drive a cancer stem-like population that is conducive of metastasis. Metascape pathway analysis of differentially expressed genes identified pathways that were significantly overrepresented in GPx2 knockdown tumors involving mitochondrial oxidative phosphorylation and response to hypoxia, consistent with the high levels of reactive oxygen species in these tumors. Finally, differential gene expression analysis on mesenchymal and luminal subpopulations predicts novel candidate gene signatures stimulated by GPx2 loss, that might be used to identify or target metastatic cells in tumors. In sum, our data imply that oxidative stress conveys a metastatic phenotype via effects on tumor cell heterogeneity. Citation Format: Zuen Ren, Malindrie Dharmaratne, Ameya Kulkarni, Atefeh Taherian Fard, Jessica Mar, Phillip M. Galbo, Yang Liu, Deyou Zheng, Huizhi Liang, Outhiriaradjou Benard, Kimita Suyama, Michael B. Prystowsky, Larry Norton, Rachel B. Hazan. Redox regulation of tumor cell heterogeneity in the PyMT mammary tumor model revealed by single cell RNA sequencing [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4426.

Abstract 1870: The impact of the microenvironment on heterogeneity and trametinib response in HCC1143 triple negative breast cancer cells

Abstract Triple negative breast cancer (TNBC) lacks expression of hormone receptors (ER and PR) and HER2 and is characterized by aggressive disease with poor outcomes. Recent work suggests that TNBC also has a high degree of intratumoral heterogeneity, as measured by lineage differentiation status. This heterogeneity may impact therapeutic response, as it has been shown that treatment with PI3K/mTOR (BEZ235) or MEK (trametinib) inhibitors can drive TNBC cells into more homogeneous states, but that the surviving cells are resistant to the targeted therapy. In this study, we sought to understand how the microenvironment impacts differentiation state heterogeneity and response to targeted therapeutics in HCC1143 cells using our microenvironment microarray (MEMA) platform. Under low serum growth conditions, we found that several ligands could drive the growth of HCC1143, particularly EGF family ligands like AREG and EGF. With respect to differentiation state and heterogeneity, EGF and TGFB1 drove HCC1143 cells into a more mesenchymal like state, with increased expression of VIM and decreased expression of KRT14. In contrast, BMP2 led to higher levels of KRT14 and lower levels of VIM, leading to a more basal-like state. We also grew HCC1143 on MEMA with trametinib treatment. Here we found that combinations of collagen-based substrates and NRG1, HGF, and EGF ligands all led to higher cell counts and EdU incorporation rates compared to PBS-control treated cells. However, the levels of resistance conferred by the microenvironment was less than we had previously seen in HER2 positive MEMA, as the GR50 values (dose required to inhibit growth by 50%) only increased modestly (18 nM for untreated cells, 40 nM for NRG1, 45 nM for HGF). Interestingly, in that HER2 positive MEMA study, we identified HGF and NRG1 as potent resistance factors to lapatinib, but that they functioned in a subtype specific manner. HGF was effective in basal subtype cells and NRG1 in luminal, but not vice versa. We postulated that the modest resistance we observed was due to ligands acting on subsets of cells. We thus treated cells with a combination of NRG1 plus HGF, and found that this resulted in increased resistance (GR50= 91 nM). Imaging showed that trametinib drove HCC1143 cells to a homogenous KRT14 positive state, but surprisingly, addition of ligands reverted the cells to a more heterogeneous state that was resistant to trametinib. These data demonstrate that the microenvironment can impact the differentiation state of TNBC cells and is also capable of conferring resistance within subsets of the heterogeneous cell populations. Citation Format: Rebecca Smith, Kaylyn Devlin, Moqing Liu, Tiera Liby, David Kilburn, Elmar Bucher, Damir Sudar, Guillaume Thibault, Mark Dane, Joe Gray, Laura Heiser, James E. Korkola. The impact of the microenvironment on heterogeneity and trametinib response in HCC1143 triple negative breast cancer cells [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1870.

Abstract C030: Gastric tumors from Latino patients show extensive intratumor heterogeneity

Abstract Gastric cancer (GC) is the 2nd leading cause of cancer-related death worldwide, with a five-year survival rate lower than 30%. GC is diagnosed in 25,000 Americans each year, with Latinos twice as likely to succumb compared to non-Hispanic whites. Treatment is currently limited to only two molecularly guided therapies. The Cancer Genome Atlas (TCGA) data show that 70% of GC patients have a mutation in a gene targetable with existing drugs. Significant spatial mutational intratumoral heterogeneity (ITH) has been identified in a variety of tumor types to date, although a GC ITH study has yet to be investigated. ITH is an important consideration for personalized therapy. Driver gene mutations are frequently found to be nonclonal, a crucial factor when assessing effective druggability. The goal of the present study was to examine GC ITH in Latino GC patients using targeted multiregional sequencing (MSEQ). Two to five biopsies from different tumor regions and adjacent normal tissue were obtained from 34 GC patients; DNA was extracted from the tumor and the normal tissues and the coding regions of 783 cancer genes were sequenced using Agilent enrichment and Illumina sequencing. Somatic mutations were called in each tumor sample, using joint analysis of all samples for each patient. Tumor cell fractions were estimated for each mutation in each sample, and phylogenetic trees were made for visualize each patient's somatic mutational patterns. We found a high degree of ITH, both intratumoral and interpatient, with the fraction of functional somatic mutations that are clonal ranging from 0 to 52%, the fraction private to one tumor sample ranging from 48% to 94%, and the fraction shared between multiple but not all samples ranging from 0 to 21%. There was at least one known drug interaction with a gene containing a clonal functional mutation for 11 of the 16 samples, and in 6 samples there were two or more known drug interactions. Our study is the first one to assess ITH in GC, and our results are important to understand the clonal architecture of these GCs and to improve molecular diagnostics. Citation Format: Ted Toal, Guadalupe M. Polanco-Echevery, Ruta Sahasrabudhe, Ana Estrada, Mabel Bohorquez, Magdalena Echeverry, Javier Torres, Luis G. Carvajal-Carmona. Gastric tumors from Latino patients show extensive intratumor heterogeneity [abstract]. In: Proceedings of the Eleventh AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2018 Nov 2-5; New Orleans, LA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl):Abstract nr C030.

High Levels of Chromosomal Copy Number Alterations and TP53 Mutations Correlate with Poor Outcome in Younger Breast Cancer Patients

Prognosis in young patients with breast cancer is generally poor, yet considerable differences in clinical outcomes between individual patients exist. To understand the genetic basis of the disparate clinical courses, tumors were collected from 34 younger women, 17 with good and 17 with poor outcomes, as determined by disease-specific survival during a follow-up period of 17 years. The clinicopathologic parameters of the tumors were complemented with DNA image cytometry profiles, enumeration of copy numbers of eight breast cancer genes by multicolor fluorescence in situ hybridization, and targeted sequence analysis of 563 cancer genes. Both groups included diploid and aneuploid tumors. The degree of intratumor heterogeneity was significantly higher in aneuploid versus diploid cases, and so were gains of the oncogenes MYC and ZNF217. Significantly more copy number alterations were observed in the group with poor outcome. Almost all tumors in the group with long survival were classified as luminal A, whereas triple-negative tumors predominantly occurred in the short survival group. Mutations in PIK3CA were more common in the group with good outcome, whereas TP53 mutations were more frequent in patients with poor outcomes. This study shows that TP53 mutations and the extent of genomic imbalances are associated with poor outcome in younger breast cancer patients and thus emphasize the central role of genomic instability vis-a-vis tumor aggressiveness.

Abstract 3776: Spatially resolved immunogenomic analyses reveal diverse sub tumoral microenvironments in the context of melanoma immunotherapy

Abstract Sustained periods of apparent clinical benefit despite lack of objective response are well known in a subpopulation of advanced melanoma patients. Inter-individual heterogeneity in response of separate tumors is common, characterizing complex overall response patterns. The molecular and cellular dynamics facilitating such long-term survival and heterogeneous response is poorly understood, particularly in the era of exposure to multiple potentially active therapies. We studied an exceptional case of long-term survival in a patient with non-responding metastatic melanoma in order to characterize the clonal and microenvironmental factors active across 3 time points. We performed immunogenomic analyses of 3 metachronous tumors, including a systemic therapy-naïve mass, 67 intratumor sub-regions of a non-responding mass during PD-1 inhibitor therapy, and a post-PD-1 inhibitor mass. We profiled samples using whole exome sequencing, RNA-sequencing (RNA-seq), immunohistochemistry (IHC), and T cell receptor sequencing. Longitudinal, spatial, and cross-modal analyses were performed. Longitudinal analyses identified mutations in several genes known to be associated with targeted or immune therapy resistance affecting distinct metastases. Genomic intratumoral heterogeneity (ITH) was primarily driven by subclonal copy number alterations that showed evidence of spatially-distinct evolution which may be in response to selective pressures at the tumor margin. RNA-seq revealed an unexpectedly high degree of ITH characterized by limited group-level gene or pathway associations with physical or immune characteristics of each site. Spatially-distinct pockets of immune activation and suppression were observed throughout the PD-1 inhibitor resistant metastasis despite a largely immune-excluded phenotype seen on IHC. A specific T cell Vβ CDR3 rearrangement was identified as dominant and recurrent not only across multiple spatial points within a single tumor mass, but also across metachronous tumors spanning the patient’s disease course. Immunophenotyping of the T cell population with single-cell RNA-seq suggested repeated T-cell priming events leading to the persistence of both activated and exhausted T cells bearing the same TCR-β at any given time. Our findings highlight an unexpected level of genomic and immune heterogeneity in metastatic melanoma tumors of a long-term surviving patient. The observed degree of ITH across local tumor microenvironments reiterates the inherent limitations to identifying robust and reproducible predictive biomarkers of therapy response based on limited physical sampling of tumors. Further spatiotemporal analysis of metastatic lesions in the context of immune checkpoint blockade will be required to determine how the mechanisms driving convergent microenvironmental phenotypes may be harnessed for therapeutic gain. Citation Format: Akash Mitra, Miles C. Andrews, Whijae Roh, Mariana P. de Macedo, Alexandre Reuben, Fernando Carapeto, Feng Wang, Sangeetha M. Reddy, Khalida Wani, Christine Spencer, John Miller, Aislyn Schalck, Latasha D. Little, Donald A. Sakellariou-Thompson, Curtis Gumbs, Wen-Jen Hwu, Chantale Bernatchez, Jianhua Zhang, Patrick Hwu, Nicholas Navin, Padmanee Sharma, James P. Allison, Jennifer Wargo, Alexander J. Lazar, Philip A. Futreal. Spatially resolved immunogenomic analyses reveal diverse sub tumoral microenvironments in the context of melanoma immunotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3776.

Abstract 738: Myxofibrosarcoma is characterized by frequent abnormalities in TP53 and increased genetic instability

Abstract Myxofibrosarcoma (MFS) is a rare subtype of soft tissue sarcomas (STSs) preferentially affecting the elderly. Histologically, MFS is distinct from other STSs, in that it is characterized by the proliferation of pleomorphic spindle cells with varying degrees of myxoid components. However, the molecular pathogenesis of MSF is poorly understood. We conducted an integrated molecular study involving 70 samples from primary MFS patients, in which samples were analyzed by whole-genome sequencing (WGS) (n=5), whole-exome sequencing (WES) (n=44), targeted-capture sequencing (n=65), RNA sequencing (n=3), and immunohistochemistry (IHC, n=50). Copy number (CN) alterations were detected by sequence-based CN analysis. The obtained genomic data were combined with those from STS cases from the Cancer Genome Atlas (TCGA) cohort, including 17 MSF samples and compared to the data from other STS samples (n=189). To further investigate the genetic basis of mixed histological components and chronological changes in MFS, we performed WES of multi-regional and/or multi-time-point samples from 8 MSF cases. A total of 4,613 mutations were identified by WES in 61 primary MFS samples with a median of 44.0 mutations/sample. Mutations were dominated by age-related C to T transitions at CpG sites. Among 84 primary MFS samples, most frequently mutated and/or CN-altered genes included TP53 (n=64, 76.2%), RB1 (n=29, 34.5%), CDKN2A (n=25, 30.0%), and ATRX (n=18, 21.4%). A fusion gene involving TRIO was newly identified by RNA sequencing in a single case. A similar mutational profile was observed in undifferentiated pleomorphic sarcoma (UPS), in which TP53 (59.1%), ATRX (34.0%), RB1 (22.7%), and CDKN2A (20.5%)) were the major mutational targets, suggesting the common molecular pathogenesis between these two subtypes. Combined with frequent positive staining in IHC (n=22, 44.0%), TP53 was affected in as many as 83.3% of the MFS cases (n=70). Five MFS cases evaluated by WGS showed complex structural abnormalities suggestive of increased genetic instability, where a median of 179 structural variations were detected per sample. WES with multi-regional sampling (n=5) disclosed a high level of intratumor heterogeneity, in which less than 29.0% of mutations were shared by different samples taken from the same tumor. Finally, an analysis of longitudinal samples (n=6) revealed significantly higher numbers of mutations in relapse samples (1.6 times on average, p = 0.03). In all cases, TP53 lesions were present from at the time of initial diagnosis, while most of the other lesions were subclonal and acquired during the clinical course. In summary, the genetic profile of MFS is characterized by frequent abnormalities in TP53, RB1, CDKN2A and ATRX, and closely related to other STSs, particularly to UPS. Clonal TP53 abnormalities resulted in complex chromosomal structure and a high degree of intratumor heterogeneity. Citation Format: Yasuhide Takeuchi, Annegret Kunitz, Hiromichi Suzuki, Kenichi Yoshida, Yuichi Shiraishi, Kenichi Chiba, Hiroko Tanaka, Teppei Shimamura, Nobuyuki Kakiuchi, Yusuke Shiozawa, Akira Yokoyama, Tetsuichi Yoshizato, Kosuke Aoki, Yoichi Fujii, Yasuhito Nannya, Hideki Makishima, Satoru Miyano, Hironori Haga, Frederik Damm, Seishi Ogawa. Myxofibrosarcoma is characterized by frequent abnormalities in TP53 and increased genetic instability [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 738.

Abstract P2-08-21: Mismatch repair protein loss is a prognostic and predictive biomarker in breast cancers regardless of microsatellite instability

Abstract Despite the approval of pembrolizumab in all tumors showing mismatch-repair (MMR) deficiency and/or microsatellite instability (MSI), there are currently no companion diagnostics for MMR status assessment in breast cancer. Here, we sought to define the diagnostic and prognostic role of MMR and MSI testing in breast cancer patients. We subjected 444 breast cancers to MMR immunohistochemistry (IHC) and MSI analysis. Cases were classified as MMR-proficient (pMMR), MMR-deficient (dMMR), and MMR-heterogeneous (hMMR) based on the loss of immunoreactivity; MSI was defined by the instability in the five indicators recommended by the National Cancer Institute for endometrial and colorectal cancers. Correlation of MMR status with patients' survival was assessed using the Kaplan-Meier estimator. In 75 patients (17%) the loss of MMR proteins was homogeneous, classified as dMMR, while 55 cases (12%) were hMMR. The prevalence of cancers with loss of the MMR proteins was homogeneous across ER+ breast cancers (15-19% for dMMR and 10-18% for hMMR tumors). The level of overlap between IHC and MSI analysis was 9% (p<0.0001). Among ER+/HER2- carcinomas, pMMR and hMMR patients displayed better survival rates (p=0.008). In chemo-treated ER-/HER2- breast cancers, the dMMR status was a marker of good prognosis (p<0.001). Our study documents the clinical impact of MMR testing in a large series of breast cancers, using the most commonly adopted diagnostic tools and criteria. We show that MMR protein loss is a rather common event in breast cancer and has a remarkable degree of intra-tumor heterogeneity, therefore making the analysis of a small area of the tumor, or a small biopsy, of little clinical value. Our investigation supports the concept that MSI occurs rarely in breast cancer and demonstrate that this condition is restricted to a minority of tumors with MMR protein loss. These data suggest that MMR IHC and MSI analysis should not be considered as interchangeable tests in the diagnostic workup of breast carcinomas. Finally, our observations indicate that the complete loss of at least one of the MMR proteins assessed by IHC is able to identify high-risk ER+/HER2- breast cancers that can potentially benefit from pembrolizumab therapy, whereas first-line chemotherapy shows comparatively good results in dMMR ER-/HER2- breast cancers. Citation Format: Fusco N, Lopez G, Corti C, Pesenti C, Colapietro P, Ercoli G, Gaudioso G, Faversani A, Gambini D, Despini L, Blundo C, Vaira V, Miozzo M, Ferrero S, Bosari S. Mismatch repair protein loss is a prognostic and predictive biomarker in breast cancers regardless of microsatellite instability [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P2-08-21.

Prognostic value of intratumour and intra field heterogeneity rate in predicting second events in oral squamous cell carcinoma

Event Abstract Back to Event prognostic value of intratumour and intra field heterogeneity rate in predicting second events in oral squamous cell carcinoma Andrea Gabusi1*, Davide Bartolomeo Gissi1, Roberto Rossi1 and Luca Morandi1 1 University of Bologna, Department of Biomedical and Neuro-Muscular Sciences - Section of Oral Science, Italy Aim. Improvements in sequencing technologies have revealed that genetic differences among neoplastic cells may reflect clonal expansion and thereby the coexistence of multiple subclones in a single tumour. Prognostic implications of intratumour heterogeneity are not fully understood. Aim of this project was to investigate if the degree of intratumour heterogeneity was related to tumour progression in oral squamous cell carcinoma (OSCC). Materials and Methods. Patients operated for OSCC and attending regular follow up for disease relapse at the Unit of Oral Medicine and Maxillofacial Surgery S.Orsola Hospital, University of Bologna were recruited for the study in order to include both recurrent and non recurrent OSCC. Inclusion criteria: diagnosis of primary tumor of T2-T4 according to the p-TNM classification of tumours, absence of nodal involvement, history of non-smokers, absence of lichenoid inflammation in tumour microenvironment, surgical margin of resection free from neoplasia, Follow up ≥ 3 years after surgical resection. Multiple samples were obtained from each tumour and from related adjacent non neoplastic mucosa. Next generation sequencing for mutational analysis was applied for 10 OSCC tumour specific genes: KRAS ,NRAS, HRAS, BRAF, PIK3CA, TP53, NOTCH1, PTEN , CDKN2A, EGFR. The degree of ITH for OSCC somatic mutations was derived by calculating the heterogeneity rates (HR) of all affected genes and dividing that sum by the number of affected genes not shared by all tumor regions. These values were used to compare the ITH in the group of recurrent and non recurrent OSCCs. Results. HR values between groups were then statistically compared using the non parametric U-Mann-Whitney test for independent samples (IBM® SPSS Software v.21). P value in primary tumours scored 0,095 and did not reach significativity indicating the absence of a statistical difference in the degree of intratumor heterogeneity among the groups of recurrent and non recurrent OSCC.By contrast, U-Mann-Whitney test performed on samples from non neoplastic adjacent mucosa disclosed that non recurrent OSCC tends to exhibit statistically lower values of HR if compared to recurrent OSCCs ( p= 0,032). Discussion. According to our results , in primary tumours, no particular degree of heterogeneity was able to distinguish OSCC with aggressive local behaviors. Genetic instability in tumours may produce heterogeneous subclones but not all subclones may reflect aggressive behaviors. On the other hand, ITH analysis of non neoplastic adjacent mucosa disclosed that non recurrent OSCC tends to exhibit statistically lower values of HR if compared to recurrent OSCCs ( p= 0,032). Fields of less aggressive OSCCs are thus more homogeneous. A prognostic implication of genetic heterogeneity of pre neoplastic field is here documented for the first time.