Abstract 6243: Rapid autopsy reveals the interplay of tumor heterogeneity at genomic, transcriptomic, and spatial dimensions
Authors: Yao Ning , Vanguri Rami , Patel Juber , Lihm Jayon , Fisher Andrew , Jarchum Irene , Umeda Shigeaki , Li Hao , Ely Scott , Hollmann Travis , Iacobuzio-Donahue Christine , Greenbaum Benjamin 
Published: March 2024

Incomplete understanding of tumor heterogeneity across primary and metastatic sites often lead to ineffective cancer treatments. To comprehensively interrogate tumor heterogeneity at genomic, transcriptomic, and spatial levels, we established a novel rapid autopsy protocol to obtain multiregional tri-omic data consisted of whole exome sequencing, mRNA-sequencing, and multiplexed immunohistochemistry on primary and metastatic tumors and associated microenvironments (TMEs). We applied this protocol to six patients with various primary tumor types: non-small cell lung cancer (NSCLC), small cell lung cancer (SCLC), urothelial cancer, and one mixed case with both NSCLC and SCLC. A total of 50 tumor samples with paired tri-omic data were obtained across 16 different primary and metastatic organs to interrogate heterogeneities underlying tumor evolution and treatment resistance mechanisms.

We constructed mutation-based phylogeny trees to reveal structural differences in tumor evolution trajectories across patients and infer heterogeneous tumor antigen landscape. We uncovered highly entropic phylogenetic structures having unique variants gained at each metastasis as well as low entropic structures with high sharing across sites. The mixed case had a clonal sweep structure with two metastases developed prior to the rest of the metastasis. In this case, older clones were shown to have strong association with APOBEC mutation signatures, enhanced subclonal mutation burden and loss of human leukocyte antigen heterozygosity as mechanisms of immune evasion.

Integrating transcriptome and spatial profiles, we revealed that tumor intrinsic expressions and extrinsic immune infiltration levels covary with tissue types rather than with mutation-based phylogenetic clusters. Across patients, samples that had high similarities in mutational landscape varied in their pro-tumor expression programs and the cellular composition of TMEs. In particular, lung samples across patients had the highest effector T cell population and major histocompatibility complex (MHC) class I, II presentations compared to other tissue types. Contrasting small cell carcinoma (SCC) and adenocarcinoma (Adeno) samples from lung tissues further revealed that SCC had more immunosuppressive TMEs with downregulation of MHC class II. Liver metastasis samples were further characterized to have the most aggressive phenotypes enriched in genomic instability measured by aneuploidy compared to other metastatic sites.

In sum, we present a novel technology and computational framework that enables a three-dimensional profiling of tumor heterogeneity. This work suggests that single-site biopsies are insufficient to capture tumor heterogeneity and calls for multi-modal integrations to design treatments that can overcome tumor-specific resistance mechanisms.

Citation Format: Ning Yao, Rami Vanguri, Juber Patel, Jayon Lihm, Andrew Fisher, Irene Jarchum, Shigeaki Umeda, Hao Li, Scott Ely, Travis Hollmann, Christine Iacobuzio-Donahue, Benjamin Greenbaum. Rapid autopsy reveals the interplay of tumor heterogeneity at genomic, transcriptomic, and spatial dimensions [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 6243.