Nature Biotechnology

Ovarian tumor cells gain competitive advantage by actively reducing the cellular fitness of microenvironment cells

Cell competition and fitness comparison between cancer and tumor microenvironment (TME) cells determine oncogenic fate. Our previous study established a role for human Flower isoforms as fitness fingerprints, where the expression of Flower Win isoforms in tumor cells leads to growth advantage over TME cells expressing Lose isoforms. Here we demonstrate that the expression of Flower Lose and reduced microenvironment fitness is not a pre-existing condition but, rather, a cancer-induced phenomenon. Cancer cells actively reduce TME fitness by the exosome-mediated release of a cancer-specific long non-coding RNA, Tu-Stroma, which controls the splicing of the Flower gene in the TME cells and expression of Flower Lose isoform, which leads to reduced fitness status. This mechanism controls cancer growth, metastasis and host survival in ovarian cancer. Targeting Flower protein with humanized monoclonal antibody (mAb) in mice significantly reduces cancer growth and metastasis and improves survival. Pre-treatment with Flower mAb protects intraperitoneal organs from developing lesions despite the presence of aggressive tumor cells.

Single-cell mapping of combinatorial target antigens for CAR switches using logic gates

Identification of optimal target antigens that distinguish cancer cells from normal surrounding tissue cells remains a key challenge in chimeric antigen receptor (CAR) cell therapy for tumors with intratumoral heterogeneity. In this study, we dissected tissue complexity to the level of individual cells through the construction of a single-cell expression atlas that integrates ~1.4 million tumor, tumor-infiltrating normal and reference normal cells from 412 tumors and 12 normal organs. We used a two-step screening method using random forest and convolutional neural networks to select gene pairs that contribute most to discrimination between individual malignant and normal cells. Tumor coverage and specificity are evaluated for the AND, OR and NOT logic gates based on the combinatorial expression pattern of the pairing genes across individual single cells. Single-cell transcriptome-coupled epitope profiling validates the AND, OR and NOT switch targets identified in ovarian cancer and colorectal cancer.