’Bochen Kelayot’ - Kidney cancer in Single Cell

Yishai Yehdua ^1,2 Yaron Trink ¹ Nissim Ben-Haim ¹ Oneg Itzhak ¹ Iddo Ben-Dov ³ Tomer Kalisky ¹

¹Faculty of Engineering and Bar Ilan Insitute of Nanotechnology and Advanced Materials (BINA), Bar Ilan University, Israel
²Department of Bioinformatics, Jerusalem College of Technology, Israel
³Department of Nephrology and Hypertension, Hadassah-Hebrew University Medical Center, Israel

Renal Cell Carcinoma (RCC), a type of kidney cancer, is the seventh most common type of cancer in the Western world. Treatment is difficult since even after surgical removal of the tumor, a metastatic tumor develops in ~30% of patients and does not respond well to conventional cancer therapies. Treatment is further complicated by the fact that these tumors considerably vary between different patients and each contains different cell types. In order to properly diagnose the disease and plan a personalized treatment, it is important to classify the tumor sub-type and understand which types of cells it contains.

We established an in-house single-cell RNA-seq (scRNA-seq) Drop-Seq system based on the Macosko protocol. and used it to study the cellular and transcriptomic heterogeneity of various patient RCC samples.

This data enables us to identify the main cell populations within RCC tumors and to deeply characterize their transcriptional states, trajectories, and cross-interactions. Using this dataset together with computational cellular “deconvolution” algorithms, allows us to deduce the cellular composition of hundreds of tumors from existing databases.

we hope that our results will pave the way for new targeted therapies for RCC and finding better markers for early and non-invasive detection and diagnosis.