scispace - formally typeset
K

Kavita Mallya

Researcher at University of Nebraska Medical Center

Publications -  46
Citations -  6850

Kavita Mallya is an academic researcher from University of Nebraska Medical Center. The author has contributed to research in topics: Pancreatic cancer & Metastasis. The author has an hindex of 18, co-authored 37 publications receiving 5081 citations. Previous affiliations of Kavita Mallya include Eppley Institute for Research in Cancer and Allied Diseases.

Papers
More filters
Journal ArticleDOI

Tumour exosome integrins determine organotropic metastasis

TL;DR: It is demonstrated that exosomes from mouse and human lung-, liver- and brain-tropic tumour cells fuse preferentially with resident cells at their predicted destination, namely lung fibroblasts and epithelial cells, liver Kupffer cells and brain endothelial cells.
Journal ArticleDOI

Neural stem cell properties of Müller glia in the mammalian retina: regulation by Notch and Wnt signaling.

TL;DR: It is shown that Müller cells, when retrospectively enriched from the normal retina, display cardinal features of neural stem cells (NSCs), i.e., they self-renew and generate all three basic cell types of the CNS.
Journal ArticleDOI

Transcriptional profiling of peripheral blood mononuclear cells in pancreatic cancer patients identifies novel genes with potential diagnostic utility.

TL;DR: The first in-depth comparison of global gene expression profiles of PBMCs between PC patients and healthy controls is reported, and an eight-gene predictor set is identified that could distinguish PC patients from healthy controls with an accuracy in a blinded subset of samples from treatment naïve patients.
Journal ArticleDOI

Novel pancreatic cancer cell lines derived from genetically engineered mouse models of spontaneous pancreatic adenocarcinoma: Applications in diagnosis and therapy

TL;DR: The successful establishment and characterization of three cell lines derived from two PDAC mouse models that mimic the genetic compendium of human PDAC make them valuable models with a high potential of translational relevance for examining diagnostic markers and therapeutic drugs.