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Introduction: Defining the transition from benign to malignant tissue is fundamental to improve early diagnosis of cancer. In order to obtain spatial information of clonal genetic events, prior studies have used methods such as laser capture microdissection, which results in assessment of small regions or even single cells. These studies have an inherent bias as a limited number of regions per tissue section can be retrieved and examined. Furthermore, because investigators have selected such regions based on morphology, previous studies have limited their analyses to histologically defined tumour areas while excluding regions populated by benign cells. The possibility to perform unsupervised genome and tissue-wide analysis would therefore provide an important contribution to delineate clonal events. We sought study spatial genome integrity in situ to gain molecular insight into clonal relationships. Materials and Methods: We employed spatially resolved transcriptomics (Visium, 10x Genomics) to infer spatial copy number variations in >120 000 spatial regions across multiple organs, including three whole axial prostates and additional tissues from skin, breast and brain tumors. We used this information to deduce clonal relationships between regions harboring 5-20 cells. Results: We demonstrate that genome-wide copy number variation reveals distinct clonal patterns within tumours and in nearby benign tissue. We perform an in-depth spatial analysis of cancers that includes an unprecedented interrogation of up to 50,000 tissue domains in a single patient, and 120,000 tissue domains across 10 patients. In a prostate section, we observed that many CNVs occurred in histologically benign luminal epithelial cells, most notably in chromosomes 8 and 10. This clone constituted a region of exclusively benign acinar cells branching off a duct lined by largely copy neutral cells. The changes in these cells were shared with the nearby intermediate risk prostate cancer cells in the same tissue section. We observed similar findings in another patient’s cutaneous squamous cell carcinoma (cSCC), wherein benign squamous epithelial had alterations in chromosomes 1 and 12 that were shared with nearby cSCC. Our results suggest a model for how genomic instability arises in histo-pathologically benign tissue that may represent early events in cancer evolution. Furthermore the spatial information allowed us to identify small clonal units not evident from morphology and hence would be overlooked by pathologists. Conclusions: We present the first large-scale, comprehensive atlas of genomic evolution at high spatial resolution in prostate cancer. Our study adds an important new approach to the armamentarium of cancer molecular pathology. We highlight the power of an unsupervised approach to capture the molecular and spatial continuums in a tissue context and challenge the rationale for focal therapy in prostate cancer. Citation Format: Andrew Erickson, Emelie Berglund, Mengxiao He, Maja Marklund, Reza Mirzazadeh, Niklas Schultz, Linda Kvastad, Alma Andersson, Ludvig Bergenstråhle, Joseph Bergenstråhle, Ludvig Larsson, Alia Shamikh, Elisa Basmaci, Teresita Diaz De Ståhl, Timothy Rajakumar, Kim Thrane, Andrew L. Ji, Paul A. Khavari, Firaz Tarish, Anna Tanoglidi, Jonas Maaskola, Richard Colling, Tuomas Mirtti, Freddie Hamdy, Dan J. Woodcock, Thomas Helleday, Ian G. Mills, Alastair D. Lamb, Joakim Lundenberg. The spatial landscape of clonal somatic mutations in benign and malignant tissue [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 2171.

Introduction: Defining the transition from benign to malignant tissue is fundamental to improve early diagnosis of cancer. In order to obtain spatial information of clonal genetic events, prior studies have used methods such as laser capture microdissection, which results in assessment of small regions or even single cells. These studies have an inherent bias as a limited number of regions per tissue section can be retrieved and examined. Furthermore, because investigators have selected such regions based on morphology, previous studies have limited their analyses to histologically defined tumor areas while excluding regions populated by benign cells. The possibility to perform unsupervised genome and tissue-wide analysis would therefore provide an important contribution to delineate clonal events. We sought study spatial genome integrity in situ to gain molecular insight into clonal relationships. Materials and Methods: We employed spatially resolved transcriptomics (Visium, 10x Genomics) to infer spatial copy number variations in >120 000 spatial regions across multiple organs, including three whole axial prostates and additional tissues from skin, breast and brain tumors. We additionally performed in silico assessment of spatial copy number inference. We used this information to deduce clonal relationships between regions harboring 5-20 cells. Results: We demonstrate that genome-wide copy number variation reveals distinct clonal patterns within tumors and in nearby benign tissue. We perform an in-depth spatial analysis of cancers that includes an unprecedented interrogation of up to 50,000 tissue domains in a single patient, and 120,000 tissue domains across 10 patients. In a prostate section, we observed that many CNVs occurred in histologically benign luminal epithelial cells, most notably in chromosomes 8 and 10. This clone constituted a region of exclusively benign acinar cells branching off a duct lined by largely copy neutral cells. The changes in these cells were shared with the nearby intermediate risk prostate cancer cells in the same tissue section. We observed similar findings in another patient’s cutaneous squamous cell carcinoma (cSCC), wherein benign squamous epithelial had alterations in chromosomes 1 and 12 that were shared with nearby cSCC. Our results suggest a model for how genomic instability arises in histo-pathologically benign tissue that may represent early events in cancer evolution. Furthermore the spatial information allowed us to identify small clonal units not evident from morphology and hence would be overlooked by pathologists. Conclusions: We present the first large-scale, comprehensive atlas of genomic evolution at high spatial resolution in prostate cancer. Our study adds an important new approach to the armamentarium of cancer molecular pathology. We highlight the power of an unsupervised approach to capture the molecular and spatial continuums in a tissue context and challenge the rationale for focal therapy in prostate cancer Citation Format: Andrew Erickson, Emelie Berglund, Mengxiao He, Maja Marklund, Reza Mirzazadeh, Niklas Schultz, Ludvig Bergenstråhle, Linda Kvastad, Alma Andersson, Joseph Bergenstråhle, Ludvig Larsson, Alia Shamikh, Elisa Basmaci, Teresita Diaz De Ståhl, Timothy Rajakumar, Kim Thrane, Andrew L. Ji, Paul A. Khavari, Firaz Tarish, Anna Tanoglidi, Jonas Maaskola, Richard Colling, Tuomas Mirtti, Freddie C. Hamdy, Dan J. Woodcock, Thomas Helleday, Ian G. Mills, Alastair D. Lamb, Joakim Lundeberg. The spatial landscape of clonal somatic mutations in benign and malignant tissue [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr PR016.

Cutaneous malignant melanoma (melanoma) is characterized by a high mutational load, extensive intertumoral and intratumoral genetic heterogeneity, and complex tumor microenvironment (TME) interactions. Further insights into the mechanisms underlying melanoma are crucial for understanding tumor progression and responses to treatment. Here we adapted the technology of spatial transcriptomics (ST) to melanoma lymph node biopsies and successfully sequenced the transcriptomes of over 2,200 tissue domains. Deconvolution combined with traditional approaches for dimensional reduction of transcriptome-wide data enabled us to both visualize the transcriptional landscape within the tissue and identify gene expression profiles linked to specific histologic entities. Our unsupervised analysis revealed a complex spatial intratumoral composition of melanoma metastases that was not evident through morphologic annotation. Each biopsy showed distinct gene expression profiles and included examples of the coexistence of multiple melanoma signatures within a single tumor region as well as shared profiles for lymphoid tissue characterized according to their spatial location and gene expression profiles. The lymphoid area in close proximity to the tumor region displayed a specific expression pattern, which may reflect the TME, a key component to fully understanding tumor progression. In conclusion, using the ST technology to generate gene expression profiles reveals a detailed landscape of melanoma metastases. This should inspire researchers to integrate spatial information into analyses aiming to identify the factors underlying tumor progression and therapy outcome. Significance: Applying ST technology to gene expression profiling in melanoma lymph node metastases reveals a complex transcriptional landscape in a spatial context, which is essential for understanding the multiple components of tumor progression and therapy outcome. Cancer Res; 78(20); 5970–9. ©2018 AACR.