Single-Cell Transcriptomic Analysis of Primary andMetastatic Tumor Ecosystems in Head and NeckCancer

The diverse malignant, stromal, and immune cells in tumors affect growth, metastasis, and response to therapy. Puram and colleagues from Center for Cancer Research, Massachusetts General Hospital (Boston, MA, USA),profiled transcriptomes of ~6,000 single cells from 18 head and neck squamous cell carcinoma(HNSCC) patients, including five matched pairs of primary tumors and lymph node metastases. Stromal and immune cells had consistent expression programs across patients. Conversely, malignant cells varied within and between tumors in their expression of signatures related to cell cycle, stress, hypoxia, epithelial differentiation, and partial epithelial-to-mesenchymal transition (p-EMT). Cells expressing the p-EMT program spatially localized to the leading edge of primary tumors. By integrating single-cell transcriptomes with bulk expression profiles for hundreds of tumors, HNSCC subtypes were refined by their malignant and stromal composition and p-EMT was established as an independent predictor of nodal metastasis, grade, and adverse pathologic features. Results provide insight into the HNSCC cosystem and define stromal interactions and ap-EMT program associated with metastasis.

Intra-tumoral heterogeneity among malignant and non-malignant cells and their interactions within the tumor microenvironment(TME) are critical to diverse aspects of tumor biology (Meacham and Morrison, 2013; Weinberg, 2014).Recent advances in single-cell genomics provide an avenue to explore genetic and functional heterogeneity at a cellular resolution(Navin, 2015; Tanay and Regev, 2017). Single-cell RNA-seq (scRNA-seq) studies have not deeply characterized epithelial tumors, despite their predominance. In these tumors, metastasis to draining lymph nodes and other organs represents a major cause of morbidity and mortality. In addition, Epithelial-to-mesenchymal transition (EMT) has been suggested as a driver of epithelial tumor spread (Gupta and Massagué, 2006; Lambert et al., 2017). Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous epithelial tumor with strong associations to alcohol and tobacco exposure (Puram and Rocco, 2015). Metastatic disease remains a central challenge, with patients often presenting at advanced stages with lymph node (LN) metastases. In this study Puram et al. profiled transcriptomes of ~ 6,000 single cells from 18 head and neck squamous cell carcinoma(HNSCC) patients, including five matched pairs of primary tumors and lymph node metastases. 2,215 malignant and 3,363 non-malignant cells were confidently distinguished by chromosomal copy-number variations (CNVs) profiles analysis; subsequently malignant cells were distinguished by their epithelial origin through epithelial marker expression. Finally, non-malignant cells were partitioned in eight main clusters by their expression states: T cells, B/plasma cells, macrophages, dendritic cells, mast cells, endothelial cells, fibroblasts and myocytes. In contrast to non-malignant cells, the 2,215 malignant cells were clustered according to their tumor of origin. Over 2,000 genes were preferentially expressed in individual tumors and differentially expressed genes were enriched within CNVs in order to assess intra-tumoral heterogeneity. Puram and colleagues next explored EMT (epithelial to mesechymal transition) associated with metastasis. Although reminiscent of an EMT-like process, the program lacks classical transcription factors thought to drive EMT, with exception of SNAIL2 (Nieto et al., 2016; Thiery et al.,2009; Ye and Weinberg, 2015) and overall expression of epithelial markers was clearly maintained. Given the absence of classical regulatory programs, the retention of epithelial markers, and the likely

transience of this expression state, scientists speculate that the artial-EMT program reflects a ‘‘metastable’’ state that recapitulates certain aspects of EMT but may be fundamentally different from those defined in vitro(Lundgren et al., 2009; Nieto et al., 2016). In addition, cells with p-EMT phenotype are dynamic and invasive and potentially responsive to tumor microenvironment (TME) cues. These malignant p-EMT cells closely localized to the leading edge in proximity to cancer associated fibroblasts (CAFs), suggesting paracrine interactions between these two cell types. Consequently, the in vivo p-EMT signature has been investigated for its predictive role in unfavorable pathological features or disease outcome in malignant-basal tumors. High p-EMT scores were associated with the existence and number of LN metastases, with higher nodal stage and with higher tumor grade, offering an explanation for the aggressiveness of poorly differentiated tumors. Interestingly, p-EMT was not associated with primary tumor size, suggesting a direct association with invasion and metastasis but not with tumor growth. In contrast, the epithelial differentiation program was negatively associated with metastasis, consistent with the observation of an inverse correlation between p-EMT and epithelial differentiation. Importantly, the p-EMT programis a stronger predictor of nodal metastasis and local invasion than either the TCGA (The Cancer Genome Atlas) mesenchymal programor conventional EMT signatures, both of which primarily reflect CAF frequency (Cancer Genome Atlas Network, 2015; Tan et al., 2014). For this reason, these data reveal a deep clinical significance that can open new interesting scenarios in cancer diagnosis and prognosis.

Fig. 1. Characterizing Intra-tumoral Expression Heterogeneity in HNSCC by Single-Cell RNA-Seq (A) Workflow shows collection and processing of fresh biopsy samples of primary oral cavity HNSCC tumors and matched metastatic LNs for scRNA-seq.(B) Heatmap shows large-scale CNVs for individual cells (rows) from a representative tumor (MEEI5), inferred based on the average expression of 100 genes surrounding each chromosomal position (columns). Red: amplifications; blue: deletions.(C) Heatmap shows expression of epithelial marker genes across 5,902 single cells (columns), sorted by the average expression of these genes.(D) Violin plot shows distributions of epithelial scores (average expression of epithelial marker genes) for cells categorized as malignant or non-malignant based on CNVs (from Puram et al., Single-Cell Transcriptomic Analysis of Primary and Metastatic Tumor Ecosystems in Head and Neck Cancer. Cell 172, 1– 14, 2018).

References

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