Unraveling dedifferentiation and metastasis traces in pancreatic ductal adenocarcinoma ductal cells: Insights from single-cell RNA sequencing analysis of ITGB4 and C19orf33

Volume 253, January 2024, 155012

Author links open overlay panel, , , , , , Abstract

Pancreatic Ductal Adenocarcinoma (PDAC) ranks among the most prevalent gastrointestinal malignancies, with risk factors including smoking, alcohol abuse, diabetes mellitus, obesity, age, family history, and genetic predisposition. Extensive research has focused on unraveling biomarkers and molecular intricacies associated with PDAC. Leveraging data from the Gene Expression Omnibus microarray and single-cell RNA sequencing datasets, our study identified ITGB4 and C19orf33 as potentially differentially expressed genes in PDAC samples when contrasted with non-malignant tissues. Notably, these genes exhibited a strong correlative expression pattern, primarily within ductal cells. Gene Expression Profiling Interactive Analysis corroborated our findings, further confirming the correlation between ITGB4 and C19orf33. Additionally, we conducted experiments involving two pivotal PDAC-related cell lines, MIA PaCa-2 and PANC-1, treated with oxaliplatin and 5-Fluorouracil. We also assessed the expression of these candidate genes in PDAC samples in comparison to adjacent normal tissues. Our findings revealed that C19orf33 is upregulated in PDAC samples, and treatment of PDAC cells with chemotherapeutic agents led to a correlated decrease in the expression of both ITGB4 and C19orf33. These co-expressed and correlated genes are implicated in relevant signaling pathways, suggesting shared biological activities that may contribute to the promotion of metastasis within malignant ductal cells. This study identifies ITGB4 and C19orf33 as key genes potentially shedding light on the molecular mechanisms driving tumorigenesis and metastasis in PDAC. These genes hold promise as potential diagnostic and therapeutic targets, offering valuable insights into the management of this challenging disease.

Section snippetsBackground

Pancreatic Ductal Adenocarcinoma (PDAC) is one of the most prevalent malignant gastrointestinal tumors. PDAC is continuing on the rise, and it is now the fourth-largest cause of cancer-related mortality in both men and women, with a 5-year survival rate of only around 9% [1], [2]. Smoking, alcohol abuse, diabetes mellitus, obesity, age, family history, and genetic factors are the main risk factors for PDAC. PDAC has a bad prognosis due to a number of variables, including a low rate of early

Dataset selection

The Gene Expression Omnibus (GEO) database of NCBI was investigated to obtain relevant PDAC datasets. After a comprehensive search, the GSE32676 dataset containing 25 PDAC samples and 7 non-malignant pancreatic tissues as the control group was selected for the current study [17]. Also, the GPL570 [HG-U133_Plus_2] Affymetrix Human Genome U133 Plus 2.0 Array platform was utilized in this study to quantitate and annotate the expression of a wide scale of genes. The samples of PDAC patients were

Sample normalization and clustering

Using hierarchical clustering and Euclidean distance correlation, all the samples were clustered according to the expression pattern of platform gene set. The results showed that 6 PDAC samples and 1 non-malignant sample have different expression pattern contrary to their statuses, “cancer” and “normal”, respectively, and they were excluded from the study (Fig S1A). After downloading the raw data, boxplot showed that the samples are not normalized and need to be normalized according to the

Discussion

PDAC has the highest mortality rate among all neoplasms worldwide and its detailed mechanism remains poorly detected. Rising evidence presents that abnormal expression and gene variants are associated with the tumorigenesis and development of PDAC [29]. The increasing availability of multi-level expression data from cancer and normal tissue has formed a new chance to integrate and extract knowledge from large datasets that promise a more comprehensive understanding of cancer. Bioinformatics

Conclusion

In conclusion, the systems biology approach alongside scRNA-seq analysis of PDAC and normal adjacent tissue that we adopted in this study allowed us to recognize two modules of co-expressed genes, ITGB4, and C19orf33, related to PDAC. Co-expressed genes are considered to be involved in associated signaling pathways and play a similar biological activity, which mostly highlights the ability of these genes in promoting metastasis in PDAC. Altogether, ITGB4 and C19orf33 genes recognized in this

Ethics approval and consent to participate

All selected patients signed a consent for participation form according to the policy of Ethical Committee located in Tabriz University of Medical Sciences. Ethical Committee Approval code for this study is IR.TBZMED.VCR.REC.1401.036.

Funding

Not applicable.

CRediT authorship contribution statement

Zahra Asadzadeh and Nima Hemmat: first co-authors, microarray and scRNA-seq data analyzing, doing wet lab experiments, preparing the manuscript; Hamidreza Hassanian and Ahad Mokhtarzadeh: preparing and revising the manuscript; Mahdi Jafarlou: English editing; Behzad Baradaran: supervising the project, resources, revising manuscript.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

This study was supported by the Immunology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.

Consent for publication

All selected patients signed a consent for publication form.

References (44)S. Naganuma et al.Nuclear translocation of H2RSP is impaired in regenerating intestinal epithelial cells of murine colitis model

Virchows Arch.

(2006)

W. Guo et al.Integrin signalling during tumour progression

Nat. Rev. Mol. Cell Biol.

(2004)

H. Ni et al.Upregulation of a functional form of the beta4 integrin subunit in colorectal cancers correlates with c-Myc expression

Oncogene

(2005)

M. Li et al.ITGB4 is a novel prognostic factor in colon cancer

J. Cancer

(2019)

T. Rivera Vargas et al.Danger signals: chemotherapy enhancers?

Immunol. Rev.

(2017)

N. Maisey et al.Multicenter randomized phase III trial comparing protracted venous infusion (PVI) fluorouracil (5-FU) with PVI 5-FU plus mitomycin in inoperable pancreatic cancer

J. Clin. Oncol.

(2002)

J. Long et al.Overcoming drug resistance in pancreatic cancer

Expert Opin. Ther. Targets

(2011)

D.B. Longley et al.5-fluorouracil: mechanisms of action and clinical strategies

Nat. Rev. Cancer

(2003)

J. Hua et al.Current status and dilemma of second-line treatment in advanced pancreatic cancer: is there a silver lining?

OncoTargets Ther.

(2018)

O.M. Alian et al.Network insights on oxaliplatin anti-cancer mechanisms