Identification of molecular heterogeneity in pancreatic ductal adenocarcinoma by multivariate profiling of unfolded protein response
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| Year of publication | 2022 |
| Type | Conference abstract |
| MU Faculty or unit | |
| Citation | |
| Description | Introduction: Ductal adenocarcinoma of the pancreas (PDAC) accounts for nearly 90% of pancreatic tumors. The prognosis is poor due to both delayed diagnosis and the complicated molecular pathway involved in development, progression and metastasis of PDAC. Markers enabling identification of early stages and their distinguishing from too advanced cases remain a challenge. Understanding the role of endoplasmatic reticulum (ER) stress response, which plays a key microenvironmental role, would enable personalized-medicine approach by identifying aggressive and treatment-resistant PDAC varieties. Purpose: To identify the relation between heterogeneity in PDAC and the ER stress response, we analyzed 1) the proteosynthetic stress response of ex-vivo cultured cells by revealing the unfolded protein response (UPR) status, 2) alterations in spectral profiles corresponding to metabolome, lipidome and low proteome of intact PDAC cells. Integrated data were used as inputs for sophisticated biostatistics and machine learning. Materials and methods: Primary cancer cell lines were established from explanted, histopathologically-validated PDAC tumors. Cells were analyzed for canonical and noncanonical UPR regulators by immunoblotting and immunofluorescence microscopy. For mass spectrometry, whole (intact) cells were used as described previously [1]. Statistical analysis was performed in R environment. Results: We revealed distinct UPR and spectral profiles of patient-specific PDAC cancer cell lines, documenting the intrinsic variability in the cohort of patient-derived samples. Global analyses of mass spectra based on pattern recognition and spectral fingerprinting provided clear discrimination of pancreatic cancer types with distinct histopathology. Conclusions: We proved the applicability of combined molecular and mass spectrometry-based approach in identifying the heterogeneity in PDAC and demonstrated that unique molecular and metabolic profiles of patient-specific PDAC cells can provide an unbiased tool for revealing PDAC heterogeneity with clinical implications. |
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