Background & Aims Increasing grade of pancreatic intraepithelial neoplasia (PanIN) has been associated with progression to pancreatic ductal adenocarcinoma (PDAC). However, the mechanisms that control progression from PanINs to PDAC are not well understood. We investigated the genetic alterations involved in this process. Methods Genomic DNA samples from laser-capture microdissected PDACs and adjacent PanIN2 and PanIN3 lesions from 10 patients with pancreatic cancer were analyzed by exome sequencing. Results Similar numbers of somatic mutations were identified in PanINs and tumors, but the mutational load varied greatly among cases. Ten of the 15 isolated PanINs shared more than 50% of somatic mutations with associated tumors. Mutations common to tumors and clonally related PanIN2 and PanIN3 lesions were identified as genes that could promote carcinogenesis. KRAS and TP53 were frequently altered in PanINs and tumors, but few other recurrently modified genes were detected. Mutations in DNA damage response genes were prevalent in all samples. Genes that encode proteins involved in gap junctions, the actin cytoskeleton, the mitogen-activated protein kinase signaling pathway, axon guidance, and cell cycle regulation were among the earliest targets of mutagenesis in PanINs that progressed to PDAC. Conclusions Early-stage PanIN2 lesions appear to contain many of the somatic gene alterations required for PDAC development.

The epithelial to mesenchymal transition (EMT) is a cellular program that is involved in embryonic development; wound healing, but also in tumorigenesis. Breast carcinoma (BC) is the most common cancer in women worldwide, and the majority of deaths (90%) are caused by invasion and metastasis. The EMT plays an important role in invasion and subsequent metastasis. Several distinct biological events integrate a cascade that leads not only to a change from an epithelial to mesenchymal phenotype, but allows for detachment, migration, invasion and ultimately, colonization of a second site. Understanding the biological intricacies of the EMT may provide important insights that lead to the development of therapeutic targets in pre-invasive and invasive breast cancer, and could be used as biomarkers identifying tumor subsets with greater chances of recurrence, metastasis and therapeutic resistance leading to death.

The nuclear proliferation biomarker Ki67 has potential prognostic, predictive, and monitoring roles in breast cancer. Unacceptable between-laboratory variability has limited its clinical value. The International Ki67 in Breast Cancer Working Group investigated whether Ki67 immunohistochemistry can be analytically validated and standardized across laboratories using automated machine-based scoring. Sets of pre-stained core-cut biopsy sections of 30 breast tumors were circulated to 14 laboratories for scanning and automated assessment of the average and maximum percentage of tumor cells positive for Ki67. Seven unique scanners and 10 software platforms were involved in this study. Pre-specified analyses included evaluation of reproducibility between all laboratories (primary) as well as among those using scanners from a single vendor (secondary). The primary reproducibility metric was intraclass correlation coefficient between laboratories, with success considered to be intraclass correlation coefficient >0.80. Intraclass correlation coefficient for automated average scores across 16 operators was 0.83 (95% credible interval: 0.73-0.91) and intraclass correlation coefficient for maximum scores across 10 operators was 0.63 (95% credible interval: 0.44-0.80). For the laboratories using scanners from a single vendor (8 score sets), intraclass correlation coefficient for average automated scores was 0.89 (95% credible interval: 0.81-0.96), which was similar to the intraclass correlation coefficient of 0.87 (95% credible interval: 0.81-0.93) achieved using these same slides in a prior visual-reading reproducibility study. Automated machine assessment of average Ki67 has the potential to achieve between-laboratory reproducibility similar to that for a rigorously standardized pathologist-based visual assessment of Ki67. The observed intraclass correlation coefficient was worse for maximum compared to average scoring methods, suggesting that maximum score methods may be suboptimal for consistent measurement of proliferation. Automated average scoring methods show promise for assessment of Ki67 scoring, but requires further standardization and subsequent clinical validation.