Islands of genomic stability in the face of genetically unstable metastatic cancer.

Introduction: Metastatic cancer affects millions of people worldwide annually and is the leading cause of cancer-related deaths. Most patients with metastatic disease are not eligible for surgical resection, and current therapeutic regimens have varying success rates, some with 5-year survival rates below 5%. Here, we test the hypothesis that metastatic cancer can be genetically targeted by exploiting single base substitution mutations unique to individual cells that occur as part of normal aging prior to transformation.

Tumor-associated neutrophils upregulate Nectin2 expression, creating the immunosuppressive microenvironment in pancreatic ductal adenocarcinoma.

Background: Tumor-associated neutrophils (TANs) constitute an abundant component among tumor-infiltrating immune cells and have recently emerged as a critical player in pancreatic ductal adenocarcinoma (PDAC) progression. This study aimed to elucidate the pro-tumor mechanisms of TAN and identify a novel target for effective immunotherapy against PDAC.

Methods: Microarray and cytokine array analyses were performed to identify the mechanisms underlying the function of TANs.

Power-law growth models explain incidences and sizes of pancreatic cancer precursor lesions and confirm spatial genomic findings.

Pancreatic ductal adenocarcinoma is a rare but lethal cancer. Recent evidence suggests that pancreatic intraepithelial neoplasia (PanIN), a microscopic precursor lesion that gives rise to pancreatic cancer, is larger and more prevalent than previously believed. Better understanding of the growth-law dynamics of PanINs may improve our ability to understand how a miniscule fraction makes the transition to invasive cancer.

CRISPR-Cas9 for selective targeting of somatic mutations in pancreatic cancers.

Somatic mutations are desirable targets for selective elimination of cancer, yet most are found within noncoding regions. We have adapted the CRISPR-Cas9 gene editing tool as a novel, cancer-specific killing strategy by targeting the subset of somatic mutations that create protospacer adjacent motifs (PAMs), which have evolutionally allowed bacterial cells to distinguish between self and non-self DNA for Cas9-induced double strand breaks. Whole genome sequencing (WGS) of paired tumor minus normal (T-N) samples from three pancreatic cancer patients (Panc480, Panc504, and Panc1002) showed an average of 417 somatic PAMs per tumor produced from single base substitutions.

Clinical Relevance of Cancerization of Ducts in Resected Pancreatic Ductal Adenocarcinoma.

Objectives: Although prevalent in 50%-90% of pancreatic ductal adenocarcinomas, the clinical relevance of "cancerization of ducts" (COD) remains unknown.

Methods: Pathologists retrospectively reviewed slides classifying prevalence of COD. Histopathological parameters, location of first recurrence, recurrence-free survival (RFS), and overall survival (OS) were collected from the institutional pancreatectomy registry.

Benign Islet Cells Within Peripancreatic Lymph Nodes: A Potential Diagnostic Pitfall.

The presence of epithelial cells within lymph node parenchyma is typically indicative of a metastatic malignancy. However, there are rare instances in which non-neoplastic epithelial or epithelioid cells may be found within lymph nodes, either due to aberrant embryologic migration, mechanical displacement, or physiological trafficking. These can potentially lead to serious potential diagnostic pitfalls, as when such situations are encountered by surgical pathologists, there is substantial risk of overdiagnosing these as metastatic malignancy.

Understanding familial risk of pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a deadly disease that is the result of an accumulation of sequential genetic alterations. These genetic alterations can either be inherited, such as pathogenic germline variants that are associated with an increased risk of cancer, or acquired, such as somatic mutations that occur during the lifetime of an individual. Understanding the genetic basis of inherited risk of PDAC is essential to advancing patient care and outcomes through improved clinical surveillance, early detection initiatives, and targeted therapies.

Generative interpolation and restoration of images using deep learning for improved 3D tissue mapping.

The development of novel imaging platforms has improved our ability to collect and analyze large three-dimensional (3D) biological imaging datasets. Advances in computing have led to an ability to extract complex spatial information from these data, such as the composition, morphology, and interactions of multi-cellular structures, rare events, and integration of multi-modal features combining anatomical, molecular, and transcriptomic (among other) information. Yet, the accuracy of these quantitative results is intrinsically limited by the quality of the input images, which can contain missing or damaged regions, or can be of poor resolution due to mechanical, temporal, or financial constraints.

Islands of genomic stability in the face of genetically unstable metastatic cancer.

Introduction: Metastatic cancer affects millions of people worldwide annually and is the leading cause of cancer-related deaths. Most patients with metastatic disease are not eligible for surgical resection, and current therapeutic regimens have varying success rates, some with 5-year survival rates below 5%. Here we test the hypothesis that metastatic cancer can be genetically targeted by exploiting single base substitution mutations unique to individual cells that occur as part of normal aging prior to transformation.

Precursor lesions in familial and hereditary pancreatic cancer.

Infiltrating ductal adenocarcinoma of the pancreas, referred to here as "pancreatic cancer," is one of the deadliest of all of the solid malignancies. The five-year survival rate in the United States for individuals diagnosed today with pancreatic cancer is a dismal 12%. Many invasive cancers, including pancreatic cancer, however, arise from histologically and genetically well-characterized precursor lesions, and these precancers are curable.

Three-dimensional assessments are necessary to determine the true, spatially-resolved composition of tissues.

Methods for spatially resolved cellular profiling using thinly cut sections have enabled in-depth quantitative tissue mapping to study inter-sample and intra-sample differences in normal human anatomy and disease onset and progression. These methods often profile extremely limited regions, which may impact the evaluation of heterogeneity due to tissue sub-sampling. Here, we applied CODA, a deep learning-based tissue mapping platform, to reconstruct the three-dimensional (3D) microanatomy of grossly normal and cancer-containing human pancreas biospecimens obtained from individuals who underwent pancreatic resection.

Power-law growth models explain incidences and sizes of pancreatic cancer precursor lesions and confirm spatial genomic findings.

Pancreatic ductal adenocarcinoma is a rare but lethal cancer. Recent evidence reveals that pancreatic intraepithelial neoplasms (PanINs), the microscopic precursor lesions in the pancreatic ducts that can give rise to invasive pancreatic cancer, are significantly larger and more prevalent than previously believed. Better understanding of the growth law dynamics of PanINs may improve our ability to understand how a miniscule fraction of these lesions makes the transition to invasive cancer.

Deep neural network-based segmentation of normal and abnormal pancreas on abdominal CT: evaluation of global and local accuracies.

Purpose: Delay in diagnosis can contribute to poor outcomes in pancreatic ductal adenocarcinoma (PDAC), and new tools for early detection are required. Recent application of artificial intelligence to cancer imaging has demonstrated great potential in detecting subtle early lesions. The aim of the study was to evaluate global and local accuracies of deep neural network (DNN) segmentation of normal and abnormal pancreas with pancreatic mass.

Aneuploidy Landscape in Precursors of Ovarian Cancer.

Purpose: Serous tubal intraepithelial carcinoma (STIC) is now recognized as the main precursor of ovarian high-grade serous carcinoma (HGSC). Other potential tubal lesions include p53 signatures and tubal intraepithelial lesions. We aimed to investigate the extent and pattern of aneuploidy in these epithelial lesions and HGSC to define the features that characterize stages of tumor initiation and progression.