Banca de DEFESA: CATARINA ROSA E SILVA SANTOS

Integration of single cell RNA and spatial transcriptome data for investigation of perineural invasion and circadian rhythm in pancreatic adenocarcinoma

scRNA, pancreas, spatial transcriptomics

The association between circadian rhythm, perineural invasion, and pancreatic
adenocarcinoma is a topic of growing interest in medical and scientific research. Pancreatic
adenocarcinoma is an aggressive form of cancer that originates from the mucus-producing
cells in the pancreas. These cells are located in the pancreatic ducts and play an important role
in digestion. Perineural invasion is a process in which cancer cells penetrate the nerves
surrounding the pancreas. This can occur when neoplastic cells spread beyond the primary
tumor, affecting adjacent nerve structures. Several studies have shown that disruption of the
circadian rhythm can promote tumor growth, perineural invasion, and metastasis in patients
with pancreatic adenocarcinoma. It is believed that the dysregulation of genes involved in the
circadian rhythm, such as the PER2 gene, may contribute to disease progression. Additionally,
changes in sleep patterns, night shift work, and exposure to artificial light at night have been
associated with an increased risk of developing this type of cancer. The present study aims to
understand the interaction between circadian rhythm and perineural invasion in the context of
pancreatic adenocarcinoma. For this purpose, scRNA (single-cell RNA) and spatial
transcriptome data will be used to analyze the molecular and spatial characteristics of cancer
cells, nerve cells, and the surrounding environment. A systematic review of pancreatic
adenocarcinoma studies was conducted using the Gene Expression Omnibus (GEO-NCBI)
database, from which studies were selected to identify the inflammatory processes associated
with the injury. These studies were analyzed using a pipeline developed in the R programming
language to standardize the processing of single-cell RNA sequencing and spatial
transcriptome gene expression data. The pipeline allows for downloading data from GEO,
quality control analysis, normalization, identification and removal of potential outliers,
summarization of gene expression data, gene annotation, identification of cells present in the
samples, and analysis of differentially expressed genes (DEGs). The processed scRNA-seq
data and annotation tables were downloaded from the GEO database. The dataset consisted of
180,000 cells corresponding to 36 patients with brain metastasis. Untreated samples were
specified and investigated to eliminate unnecessary factors. Separately, the cell count matrices
of the selected samples were introduced into R (4.1.0) and analyzed for cellular composition,
cell-cell interaction, and spatial transcriptome. The data were analyzed using specific
packages in R software, demonstrating that there are gene expression patterns in the different
analyzed samples. Our observations expand the notion by identifying that proliferative and
inflammatory processes coexist as opposing main cellular states and suggest that immune
escape and proliferation act as combined events. The present study identifies neoplastic,
stromal, and immune cell types in different types of pancreatic adenocarcinoma and presents
hypotheses to understand the interaction between intrinsic characteristics of tumor cells and
host environment characteristics in human metastasis.