Tumor cell lineage diversity and composition in gastric cancer progression and therapy resistance

Gastric adenocarcinoma (GAC) remains one of the deadliest forms of cancer due to its rapid progression, resistance to therapy, and a high rate of metastatic spread. A common site of metastases is the peritoneal cavity that occurs in 40-50% of patients and leads to development of peritoneal carcinomatosis (PC). PC is almost a universally lethal diagnosis with survival of less than 6 months due to limited therapeutic options that are currently available. Intratumoral heterogeneity (ITH) is a fundamental property of GAC that contributes to therapy resistance, disease progression and metastasis. We and others have characterized the genomic and molecular ITH in GAC and PC, however, tumor cell lineage plasticity−the non-genetic, cell intrinsic origin of ITH remains poorly understood. In our preliminary efforts to dissect the cellular and molecular ITH using single-cell analysis, we discovered that the diversity in tumor cell lineage/state compositions appears to be an upstream key regulator of phenotypic ITH of PC, beyond the genetic factors. We also find that tumors classified based on tumor cell lineage/state compositions (cellular subtypes) are strongly associated with survival, exhibiting differential activation of oncogenic pathways and distinct immune phenotypes. We therefore hypothesize that tumor cell lineages/states dynamically evolve to resist treatment and promote tumor growth and its composition determines phenotypes and outcomes of GACs. The goal of Aim 1 is to characterize tumor cell lineage/state diversity and compositions in clinically defined GAC cohorts, determine their impacts on tumor cell clonal evolution, and identity lineage features associated with GAC progression and metastasis. We will also profile changes in tumor cell lineages and states in paired baseline and progressive tumors following chemotherapy or immunotherapy, determine their impact on immune phenotypes and patient responses to anti-cancer therapies, and identify lineage features associated with therapy resistance. In Aim 2, we will leverage our genetically engineered mouse models (GEMMs) of GAC, follow the expansion and dissemination of cancer cells in GEMMs over a period of time to longitudinally track and characterize dynamic changes in tumor cell lineage identity and transcriptome states at single-cell resolution. We will investigate the clonal architecture of tumor cells in different lineages/states and examine the dynamics of clonal populations that sustain tumor growth at the primary sites, seed and colonize distant organs; we will also profile how tumor cells in different lineages interact with TIME at the primary tumor site and influence invasion and dissemination. In Aim 3, we will investigate tumor cell lineage plasticity in response to chemotherapy and immunotherapy in GEMMs. We will characterize therapy-induced emergence of resistant cell lineages/states and identify the fundamental pathways and drivers of lineage/state transition. This study will link tumor cell lineage/state plasticity to GAC therapy resistance, progression, and metastasis. A better understanding of sources of phenotype heterogeneity and dynamics underlying GAC progression is paramount to identifying effective treatments.