Biospecimen and Data Core

ABSTRACT/SUMMARY: BIOSPECIMEN AND DATA CORE Our CCSB will dissect how interactions between malignant, stromal and immune cells in the primary tumor and lymph nodes (LN) influence systemic immunity and facilitate distant metastasis, across multiple cancer types. Accordingly, the goal of our Biospecimen and Data Core is to provide expertise and facilities for fresh and

archived specimen acquisition, genomic and image data processing, and sharing. This will ensure the provision of high-quality, richly annotated datasets that serve the needs of our Research Projects in mouse and human; to make them widely available to the CSBC and broader community; and to integrate them with external data

sources. We will perform the following aims to fulfill our Center goals: (1) We will develop a fresh tissue biospecimen repository of human head and neck cancer (HNSCC) and lung cancer, as well as mouse models of metastasis for single cell RNA sequencing (scRNA-seq) and CODEX analysis. Human specimens including

matched primary tumor, LN and distant metastases (when available) from multiple tumor regions will be assigned unique identifiers connecting them to human clinical annotations to develop and populate a HIPAA-compliant REDcap database, while mouse specimens will be linked to detailed experimental information for cross-species

phenotypic validation and mechanism study. (2) We will construct TMAs of fixed primary, LN and distant metastases with detailed clinical annotations in order to validate findings from our Research Projects on large independent cohorts. Our TMAs will be constructed from treatment-naïve archived FFPE specimens for head

and neck cancer and lung cancer. The TMAs will consist of cores from primary tumors and uninvolved LNs from LN-negative (N0) patients; primary tumors, involved and uninvolved LNs from LN-positive (N+) patients; and distant metastases for a subset of LN-positive patients. Individuals’ tissues will be sampled at multiple locations.

The clinical follow-up (survival, occurrence of metastasis) will enable us to infer prognostic significance of our work. (3) we will perform QC, processing, and basic analyses using existing robust pre-processing and analysis pipelines for scRNA-seq, CODEX and IHC data. (4) we will leverage Center-generated data in the context of

larger publicly available cohorts. We will identify, curate, pre-process, and analyze public data relevant to the Center’s aims, performing baseline meta-analysis of the relationship between gene expression data and LN/distant metastasis which we can link to insights from our internally generated datasets. We will coordinate

with the broader CSBC to make data and analyses available, contribute to standardizing reporting of assay data, and make computational tools widely available. Taken together, the centralization of the acquisition of single-cell proteomic expression (CODEX), scRNA-seq, and spatial transcriptomic data for the two research projects in this

proposed BDC will allow studies that employ human and mouse specimens and mouse models to be carried out in a reproducible, efficient, and consistent manner.