Abstract
Simple SummaryPancreatic cancer has a poor prognosis, which is largely due to resistance to treatment. Tumor heterogeneity is a known cause for treatment failure and has been studied at the molecular level. Morphological heterogeneity is common but has not been investigated, despite the fact that pathology examination is an integral part of clinical diagnostics. This study assessed whether morphological heterogeneity reflects structural and functional diversity in key cancer biological processes. Using archival tissues from resected pancreatic cancer, we selected four common and distinct morphological phenotypes and demonstrated that these differed significantly for a panel of 26 structural and functional features of the cancer-cell and stromal compartments. The strong link between these features and morphological phenotypes allowed prediction of the latter based on the results for the panel of features. The findings of this study indicate that morphological heterogeneity reflects biological diversity and that its assessment may potentially provide clinically relevant information.Inter- and intratumor heterogeneity is an important cause of treatment failure. In human pancreatic cancer (PC), heterogeneity has been investigated almost exclusively at the genomic and transcriptional level. Morphological heterogeneity, though prominent and potentially easily assessable in clinical practice, remains unexplored. This proof-of-concept study aims at demonstrating that morphological heterogeneity reflects structural and functional divergence. From the wide morphological spectrum of conventional PC, four common and distinctive patterns were investigated in 233 foci from 39 surgical specimens. Twenty-six features involved in key biological processes in PC were analyzed (immuno-)histochemically and morphometrically: cancer cell proliferation (Ki67) and migration (collagen fiber alignment, MMP14), cancer stem cells (CD44, CD133, ALDH1), amount, composition and spatial arrangement of extracellular matrix (epithelial proximity, total collagen, collagen I and III, fibronectin, hyaluronan), cancer-associated fibroblasts (density, αSMA), and cancer-stroma interactions (integrins α2, α5, α1; caveolin-1). All features differed significantly between at least two of the patterns. Stromal and cancer-cell-related features co-varied with morphology and allowed prediction of the morphological pattern. In conclusion, morphological heterogeneity in the cancer-cell and stromal compartments of PC correlates with structural and functional diversity. As such, histopathology has the potential to inform on the operationality of key biological processes in individual tumors.
Highlights
Ductal adenocarcinoma of the pancreas, often referred to as pancreatic cancer (PC), has a dismal prognosis with an overall five-year survival of less than 7% [1,2]
Further results from this study extend the nature of the stromal subtypes: high Matrix metalloproteinase 14 (MMP14)-expression by both cancer-associated fibroblasts (CAFs) and cancer cells in FP fits with a dynamic stroma, undergoing active remodeling
Intratumor heterogeneity has been reported for several of the individual features analyzed in this study: amount of hyaluronan [77,102] and collagen [19], degree of collagen alignment [19,65], expression of CD44 [34], CD133 [50], ALDH1 [99] and MMP14 [123], and proliferative activity [97,106]. While in these studies intratumor heterogeneity for individual features was reported without further characterization of the morphological phenotype of PC, the results of our study indicate that features do not vary randomly between and within tumors but rather co-vary with the tumor morphology
Summary
Ductal adenocarcinoma of the pancreas, often referred to as pancreatic cancer (PC), has a dismal prognosis with an overall five-year survival of less than 7% [1,2]. In addition to late diagnosis, limited efficacy of current treatment is the main reason for the poor prognosis. Precision medicine holds the promise of improved outcome through treatment that is tailored to intrinsic properties of the individual tumor. This approach requires a classification system with well-defined tumor subtypes of a cancer entity, as it is established, for example, for breast cancer. Several classification systems have been proposed for PC, which are based on gene expression profiling [3,4,5,6] The latter is not without its practical obstacles, including the need for RNA of sufficient quantity and quality. There is the unresolved problem of intratumor heterogeneity
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