Temporal and spatial topography of cell proliferation in cancer.

Abstract

3122 Background: Tumors are complex ecosystems where exogenous and endogenous cues are integrated to either stimulate or inhibit cancer cell proliferation. However, the nature of these complex cell cycle states, their spatial organization, response to perturbation, and implications for clinical outcomes, are poorly characterized in tumor tissues. Methods: We used multiplexed tissue imaging to develop a robust classifier of proliferation, the multivariate proliferation index (MPI), using 513 unique tumors across five cancer types. Next, we used dimensionality reduction analysis to assess how the patterns of cell cycle protein expression in tumors were altered in response to perturbation. Results: The MPI outperforms single markers, like Ki67, when classifying proliferative index across diverse tumor types and reveals the proliferative architecture of tumors in situ. We find that proliferative and non-proliferative cancer cells are organized across microscopic (cell-to-cell) and macroscopic (tissue-level) scales. Both domains are reshaped by therapy, and local clusters of proliferative and non-proliferative tumor cells preferentially neighbor distinct tumor-infiltrating immune cells. We further phenotyped non-proliferating cancer cells using markers of quiescent cancer cells, cancer stem cells, and dormant cancer cells. We found that these types of non-proliferating cancer cells can occupy distinct regions within the same primary tumor. In high-dimensional marker space, populations of proliferative cancer cells express canonical patterns of cell cycle protein markers, a property we refer to as “cell cycle coherence”. Untreated tumors exist in a continuum of coherence states, ranging from optimal coherence, akin to freely cycling cells in culture, to reduced coherence characterized by either cell cycle polarization or non-canonical marker expression. Coherence can be stereotypically altered by induction and abrogation of mitogen signaling in a HER2-driven model of breast cancer. Cell cycle coherence is modulated by neoadjuvant therapy in patients with localized breast cancer, and coherence is associated with disease-free survival after adjuvant therapy in patients with colorectal cancer, mesothelioma and glioblastoma. Conclusions: The MPI robustly defines proliferating and non-proliferating cells in tissues, with immediate implications for clinical practice and research. The coherence metrics capture the diversity of post-treatment cell cycle states directly in clinical samples, a fundamental step in advancing precision medicine. More broadly, replacing binary metrics with multivariate traits provides a quantitative framework to study temporal processes from fixed static images and to investigate the rich spatial biology of human cancers.