Cell-cell Frontiers

Robustly and comprehensively deciphering cell-cell communication from distinct single-cell omics with a unified framework combining LIANA and Tensor-cell2cell

Erick Armingol (PhD candidate), University of California, San Diego, Advisor: Nathan E. Lewis

Daniel Dimitrov (PhD candidate) Heidelberg University, Advisor: Julio Saez-Rodriguez

Hratch Baghdassarian (PhD candidate), University of California, San Diego, Advisor: Nathan E. Lewis

Problem or question being addressed:

Virtually all cellular processes are influenced by environmental context, enacted in part through binding interactions between secreted ligands and their cognate receptors expressed on cell surfaces. Receptor-ligand (R-L) -mediated communication events are critical to establishment of cellular heterogeneity in healthy tissues, and may also present opportunities for therapeutic intervention when such interactions drive disease phenotypes. To maximize the potential impact of any investigation into these events, approaches should thus be applicable to suggest key communication mechanisms in normal tissue homeostasis, or lack thereof.

Indeed, a comprehensive data source profiling cell-cell communication across broad tissue states already exists: the recent surge in genomics technologies, particularly those capturing single cell measurements, has provided a massive amount of (yet un-tapped) information speaking to R-L usage across the phenotypic landscape. We propose that further development of computational approaches to dissect such events from single cell RNA sequencing (scRNA-seq) data would be invaluable in deriving…

Erika Morera, PhD (Postodc)

University of Oslo. Advisors: Vessela Kristensen & Pascal Duijf

Problem or question being addressed:

Breast cancer (BC) is the most prevalent cancer type in women worldwide [1]. BC classification depends on the overexpression of estrogen receptor (ER), progesterone receptor (PR), and the amplification of HER2 [2]. This molecular classification is routinely used in clinics for prognostic purposes and to choose specific treatment modalities. However, a high percentage of breast cancer (BC) tumors are still difficult to treat. Therefore, there is an urgent need to provide better or new treatment options for these patients.

Immune cells in the tumor microenvironment have an important role in tumor progression and affect BC therapy response. Immune cells can recognize and inhibit tumor growth [3] and, in breast cancer, high immune cell infiltration has been associated with better prognosis [4, 5] and increased response to chemotherapy [6]. However, immune cells can…

Functional and molecular characterization of avatar model systems to elucidate cancer cell – adipocyte communication

Problem and rational

Precision oncology has revolutionized cancer therapy and opened a new path to patient-tailored treatment options. Still, only few patients benefit from comprehensive analysis of targetable transcriptional or genomic alterations. Functional precision oncology can complement the information on targetable vulnerabilities, particularly in heterogenous diseases where standard therapy is not equally effective (1). Standard therapy of ovarian cancer is an example of a “one-size-fits-all” strategy. Patients with all subtypes of ovarian cancer receive a combination of cytoreductive surgery and platinum-based chemotherapy regardless of the underlying molecular drivers or individual pathobiology (2). Under this paradigm most patients suffer from relapse within two years and for certain disease subtypes, such as low-grade serous ovarian cancer, objective patient benefit from chemotherapy is extremely low. Understanding the underlying pathobiology is critical to identify personalized treatment options and to…