Identification of cancer chemosensitivity by ODE and GMM modeling of heterogeneous cellular response to perturbations in fluorescent sphingolipid metabolism

Abstract

Abstract-Cancer refers to a group of diseases in which cells display uncontrolled growth. Chemotherapy options are usually conditioned by generating resistance which is explained in part by the intrinsic heterogeneity of the population in the tumor. Because the study of resistance requires biosensors able to report the response at the single cell level, we propose to use fluorescently labeled SL to estimate pathway dynamics at the single cell level and investigate its possible application as gemcitabine (GMZ) response sensor in pancreatic cancer by comparing the dynamics between GMZ resistant (Panc-1, MiaPaca-2) and sensitive (BxPC3) cell lines. We used imaging flow cytometry to extract multiple image features and classify cells using gaussian-mixture model (GMM) to generate response fingerprints upon known perturbations. The results suggest that GMZ inhibits the Sphingomyelin-Synthase of BxPC3. Also, we constructed and fitted a dynamical mathematical model to simulate these perturbations and formulate cell line models revealing a striking heterogeneity among them. Predictions of the model respect the effect of GMZ in the accumulation of ceramide in BxPC3 and glucosyl-ceramide in MiaPaca-4 were confirm experimentally. Altogether, these results indicate that fluorescent-SL analogues can be used as sensors of chemotherapy in pancreatic cancer and reveal pathway dynamics between different cell lines, and its potential usage for the development of in vitro chemosensitivy assays able to dissect pathway dynamics to overcome resistance.

Sphingolipid-Based Synergistic Interactions to Enhance Chemosensitivity in Lung Cancer Cells

“…We inferred the SL metabolic pathway topology related to the probe movement in different cell compartments [23]. Moreover, SM-BOD was used to analyze the SL distribution in plasma membranes [42]. Afterward, we constructed and fitted a dynamic mathematical model based on the metabolism kinetics of the SM-BOD probe to simulate the total fluorescent level changes upon perturbations.…”

Analysis and Identification of Dermatological Diseases Using Gaussian Mixture Modeling

“…In [42], Equal-Variance GMM has been used to model the characteristics of images, where, equal variance is shared by all the GMM variables. It has also been used in identification of cancer chemosensitivity of heterogeneous cellular response to perturbations in fluorescent sphingolipid metabolism [43] for extracting texture and intensity from the cellular images of the flow cytometry assay. GMM-based approach has also been used in [44] to multiparametrically characterize prostate tissue on transrectal dynamic contrastenhanced ultrasonography giving an accuracy of 81%.…”