Single cell transcriptomes of pancreatic pre-invasive lesions and cancer reveal acinar metaplastic cells’ heterogeneity
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ABSTRACT:
PROVIDER: PRJNA604712 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR11013800_1.fastq.gz | Fastqsanger.gz | |||
| SRR11013800_2.fastq.gz | Fastqsanger.gz | |||
| SRR11013900_1.fastq.gz | Fastqsanger.gz | |||
| SRR11013900_2.fastq.gz | Fastqsanger.gz | |||
| SRR11014000_1.fastq.gz | Fastqsanger.gz |
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Project description:In this project we have used single cell RNA-seq to profile pancreatic cancer development in a mouse model, from pre-invasive stage to cancer, and in human PDAC sample. Using a reporter gene, we were able to dissect metaplastic acinar cell heterogeneity, profiled six different acinar metaplastic cell types and states, validated their localization to pre-invasive lesions and correlated findings with human PDAC. In addition, we detected transcription factors, Onecut2 and Foxq1, that strictly expressed in metaplastic cells.
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Project description:Rationale: Lung carcinoma-in-situ (CIS) lesions are the pre-malignant precursor to lung squamous cell carcinoma. However, only half progress to invasive cancer in three years, while a third spontaneously regress. Whether modern molecular profiling techniques can identify those preinvasive lesions that will subsequently progress and distinguish them from those that will regress is unknown. We performed gene expression microarrays on CIS lesions, with a view to deriving a molecular signature predictive of future progression to invasive cancer.
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Project description:BACKGROUND Autofluorescence bronchoscopy (AFB) is a valid strategy for detecting premalignant endobronchial lesions. However, no biomarker can reliably predict lung cancer risk of subjects with AFB-visualized premalignant lesions. Our present study was set out to identify AFB-visualized squamous metaplastic lesions with malignant potential by DNA copy number profiling. METHODS Regular AFB-examinations in 474 subjects at risk of lung cancer identified 6 subjects with SqM lesions at baseline and carcinoma (in situ) at the initial SqM site at follow-up bronchoscopy. These progressive SqM lesions were compared for immunostaining pattern and arrayCGH-based chromosomal profiles to 23 SqM of subjects who remained cancer-free. Specific copy number alterations (CNAs) linked to cancer risk were identified and accuracy of CNAs to predict endobronchial cancer in this series was determined. RESULTS At baseline, p53, p63 and Ki-67 immunostaining were not predictive for a differential clinical outcome of SqM lesions. The mean number of CNAs in baseline SqM of cases was significantly higher compared to controls (p<0.01). Chromosomal regions significantly more frequently altered in SqM of cases were 3p26.3-p11.1, 3q26.2-q29, 9p13.3-p13.2, and 17p13.3-p11.2 (FWER<0.10). CNAs were specifically detected at the site of future cancer. In cases, baseline-detected CNAs persisted in subsequent biopsies taken from the initial site, and levels increased towards cancer progression. CNAs at 3p26.3-p11.1, 3q26.2-29, and 6p25.3-24.3, predicted cancer risk for AFB-visualized SqM with 97% accuracy. CONCLUSION Our data strongly suggest that the presence of specific DNA copy number alterations in endobronchial SqM lesions predict endobronchial cancer.
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