Therapeutic implications of GIPC1 silencing in cancer.

GIPC1 is a cytoplasmic scaffold protein that interacts with numerous receptor signaling complexes, and emerging evidence suggests that it plays a role in tumorigenesis. GIPC1 is highly expressed in a number of human malignancies, including breast, ovarian, gastric, and pancreatic cancers. Suppression of GIPC1 in human pancreatic cancer cells inhibits in vivo tumor growth in immunodeficient mice. To better understand GIPC1 function, we suppressed its expression in human breast and colorectal cancer cell lines and human mammary epithelial cells (HMECs) and assayed both gene expression and cellular phenotype. Suppression of GIPC1 promotes apoptosis in MCF-7, MDA-MD231, SKBR-3, SW480, and SW620 cells and impairs anchorage-independent colony formation of HMECs. These observations indicate GIPC1 plays an essential role in oncogenic transformation, and its expression is necessary for the survival of human breast and colorectal cancer cells. Additionally, a GIPC1 knock-down gene signature was used to interrogate publically available breast and ovarian cancer microarray datasets. This GIPC1 signature statistically correlates with a number of breast and ovarian cancer phenotypes and clinical outcomes, including patient survival. Taken together, these data indicate that GIPC1 inhibition may represent a new target for therapeutic development for the treatment of human cancers.

Mucormycosis in immunochallenged patients.

Mucorales species are deadly opportunistic fungi with a rapidly invasive nature. A rare disease, mucormycosis is most commonly reported in patients with diabetes mellitus, because the favorable carbohydrate-rich environment allows the Mucorales fungi to flourish, especially in the setting of ketoacidosis. However, case reports over the past 20 years show that a growing number of cases of mucormycosis are occurring during treatment following bone marrow transplants (BMT) and hematological malignancies (HM) such as leukemia and lymphoma. This is due to the prolonged treatment of these patients with steroids and immunosuppressive agents. Liposomal amphotericin B treatment and posaconazole are two pharmacologic agents that seem to be effective against mucormycosis, but the inherently rapid onset and course of the disease, in conjunction with the difficulty in correctly identifying it, hinder prompt institution of appropriate antifungal therapy. This review of the literature discusses the clinical presentation, diagnosis, and treatment of mucormycosis among the BMT and HM populations.

Feature-guided clustering of multi-dimensional flow cytometry datasets.

BACKGROUND: Flow cytometry produces large multi-dimensional datasets of the physical and molecular characteristics of individual cells. The objective of this study was to simplify the cytometry datasets by arranging or clustering "objects" (cells) into a smaller number of relatively homogeneous groups (clusters) on the basis of interobject similarities and dissimilarities. RESULTS: The algorithm was designed to be driven by histogram features; that is, the relevant single parameter histogram features were used to guide multidimensional k-means clustering without an a priori estimate of cluster number. To test this approach, we simulated cell-derived datasets using protein-coated microspheres (artificial "cells"). The microspheres were constructed to provide 119 populations in 40 samples. The feature-guided (FG) approach accurately identified 100% of the predetermined cluster combinations. In contrast, an approach based on the partition index (PI) cluster validity measure accurately identified 83.2% of the clusters. Direct comparisons of the two methods indicated that the FG method was significantly more accurate than PI in identifying both the number of clusters and the number of objects within the clusters (p<.0001). CONCLUSION: We conclude that parameter feature analysis can be used to effectively guide k-means clustering of flow cytometry datasets.