Deciphering the senescence-based tumoral heterogeneity and characteristics in pancreatic cancer: Results from parallel bulk and single-cell transcriptome data.

IUBMB Life

Department of Hepatopancreatobiliary Surgery, Ningbo Medical Center Lihuili Hospital (The Affiliated Lihuili Hospital, Ningbo University), Ningbo, Zhejiang, People's Republic of China.

Published: January 2025

The prevalent intra- and intertumoral heterogeneity results in undesirable prognosis and therapy failure of pancreatic cancer, potentially resulting from cellular senescence. Herein, integrated analysis of bulk and single-cell RNA-seq profiling was conducted to characterize senescence-based heterogeneity in pancreatic cancer. Publicly available bulk and single-cell RNA sequencing from pancreatic cancer patients were gathered from TCGA-PAAD, PACA-AU, PACA-CA, and GSE154778 datasets. The activity of three senescence-related pathways (cell cycle, DNA repair, and inflammation) was scored utilizing ssGSEA algorithm. A series of functional verifications of crucial genes were accomplished in patient tissue and pancreatic cancer cells. Based upon them, unsupervised clustering analysis was executed to classify pancreatic cancer samples into distinct senescence-based clusters at the bulk and single-cell levels. For single-cell transcriptome profiling, cell clustering and annotation were implemented, and malignant cells were recognized utilizing infercnv algorithm. Two senescence-based clusters were established and highly reproducible at the bulk level, with the heterogeneity in prognosis, clinicopathological features, genomic CNVs, oncogenic pathway activity, immune microenvironment and immune checkpoints. Senescence-relevant gene CHGA, UBE2C and MCM10 were proved to correlate with the migration and prognosis of pancreatic cancer. At the single-cell level, seven cell types were annotated, comprising ductal cells 1, ductal cells 2, fibroblasts, macrophages, T cells, stellate cells, and endothelial cells. The senescence-based classification was also proven at the single-cell level. Ductal cells were classified as malignant cells and non-malignant cells. In the tumor microenvironment of malignant cells, hypoxia and angiogenesis affected senescent phenotype. The heterogeneity in senescence was also observed between and within cell types. Altogether, our findings unveil that cellular senescence contributes to intra- and intertumoral heterogeneity in pancreatic cancer, which might facilitate the development of therapeutics and precision therapy in pancreatic cancer.

Download full-text PDF

Source
http://dx.doi.org/10.1002/iub.70001DOI Listing

Publication Analysis

Top Keywords

pancreatic cancer
36
bulk single-cell
16
malignant cells
12
ductal cells
12
cells
11
pancreatic
9
cancer
9
single-cell transcriptome
8
intra- intertumoral
8
intertumoral heterogeneity
8

Similar Publications

Background: Pancreatic cancer (PAC) has a complex tumor immune microenvironment, and currently, there is a lack of accurate personalized treatment. Establishing a novel consensus machine learning driven signature (CMLS) that offers a unique predictive model and possible treatment targets for this condition was the goal of this study.

Methods: This study integrated multiple omics data of PAC patients, applied ten clustering techniques and ten machine learning approaches to construct molecular subtypes for PAC, and created a new CMLS.

View Article and Find Full Text PDF

mSphere of Influence: Seeking the unseen fungi in tumors.

mSphere

January 2025

State Key Laboratory of Systems Medicine for Cancer, Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Ningning Liu works in the field of fungal infection and cancer progression, with a particular focus on the mechanism of host-pathogen interaction. In this mSphere of influence article, he reflects on how papers entitled "The fungal mycobiome promotes pancreatic oncogenesis via activation of MBL," by B. Aykut, S.

View Article and Find Full Text PDF

Background The relationship between physical activity and incident pancreatic cancer is poorly defined, and the evidence to date is inconsistent, largely due to small sample sizes and insufficient incident outcomes. Using the UK Biobank cohort dataset, the association between physical activity levels at recruitment and incident pancreatic ductal adenocarcinoma (PDAC) at follow-up was analysed. Method Physical activity, the key exposure, was quantified using Metabolic Equivalent Task (MET) values and categorised into walking, moderate, and vigorous activity.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!