13 research outputs found
Paxillin-Y118 phosphorylation contributes to the control of Src-induced anchorage-independent growth by FAK and adhesion
<p>Abstract</p> <p>Background</p> <p>Focal adhesion kinase (FAK) and Src are protein tyrosine kinases that physically and functionally interact to facilitate cancer progression by regulating oncogenic processes such as cell motility, survival, proliferation, invasiveness, and angiogenesis.</p> <p>Method</p> <p>To understand how FAK affects oncogenesis through the phosphorylation of cellular substrates of Src, we analyzed the phosphorylation profile of a panel of Src substrates in parental and v-Src-expressing FAK+/+ and FAK-/- mouse embryo fibroblasts, under conditions of anchorage-dependent (adherent) and -independent (suspension) growth.</p> <p>Results</p> <p>Total Src-induced cellular tyrosine phosphorylation as well as the number of phosphotyrosyl substrates was higher in suspension versus adherent cultures. Although the total level of Src-induced cellular phosphorylation was similar in FAK+/+ and FAK-/- backgrounds, the phosphorylation of some substrates was influenced by FAK depending on adherence state. Specifically, in the absence of FAK, Src induced higher phosphorylation of p190RhoGAP, paxillin (poY118) and Crk irrespective of adhesion state, PKC-δ (poY311), connexin-43 (poY265) and Sam68 only under adherent conditions, and p56Dok-2 (poY351) and p120catenin (poY228) only under suspension conditions. In contrast, FAK enhanced the Src-induced phosphorylation of vinculin (poY100 and poY1065) and p130CAS (poY410) irrespective of adherence state, p56Dok-2 (poY351) and p120catenin (poY228) only under adherent conditions, and connexin-43 (poY265), cortactin (poY421) and paxillin (poY31) only under suspension conditions. The Src-induced phosphorylation of Eps8, PLC-γ1 and Shc (poY239/poY240) were not affected by either FAK or adherence status. The enhanced anchorage-independent growth of FAK-/-[v-Src] cells was selectively decreased by expression of paxillin<sup>Y118F</sup>, but not by WT-paxillin, p120catenin<sup>Y228F </sup>or Shc<sup>Y239/240F</sup>, identifying for the first time a role for paxillin<sup>poY118 </sup>in Src-induced anchorage-independent growth. Knockdown of FAK by siRNA in the human colon cancer lines HT-25 and RKO, resulted in increased paxillin<sup>poY118 </sup>levels under suspension conditions as well as increased anchorage-independent growth, supporting the notion that FAK attenuates anchorage-independent growth by suppressing adhesion-dependent phosphorylation of paxillin<sup>Y118</sup>.</p> <p>Conclusion</p> <p>These data suggest that phosphorylation of Src substrates is a dynamic process, influenced temporally and spatially by factors such as FAK and adhesion.</p
FMT: Removing Backdoor Feature Maps via Feature Map Testing in Deep Neural Networks
Deep neural networks have been widely used in many critical applications,
such as autonomous vehicles and medical diagnosis. However, their security is
threatened by backdoor attack, which is achieved by adding artificial patterns
to specific training data. Existing defense strategies primarily focus on using
reverse engineering to reproduce the backdoor trigger generated by attackers
and subsequently repair the DNN model by adding the trigger into inputs and
fine-tuning the model with ground-truth labels. However, once the trigger
generated by the attackers is complex and invisible, the defender can not
successfully reproduce the trigger. Consequently, the DNN model will not be
repaired since the trigger is not effectively removed.
In this work, we propose Feature Map Testing~(FMT). Different from existing
defense strategies, which focus on reproducing backdoor triggers, FMT tries to
detect the backdoor feature maps, which are trained to extract backdoor
information from the inputs. After detecting these backdoor feature maps, FMT
will erase them and then fine-tune the model with a secure subset of training
data. Our experiments demonstrate that, compared to existing defense
strategies, FMT can effectively reduce the Attack Success Rate (ASR) even
against the most complex and invisible attack triggers. Second, unlike
conventional defense methods that tend to exhibit low Robust Accuracy (i.e.,
the model's accuracy on the poisoned data), FMT achieves higher RA, indicating
its superiority in maintaining model performance while mitigating the effects
of backdoor attacks~(e.g., FMT obtains 87.40\% RA in CIFAR10). Third, compared
to existing feature map pruning techniques, FMT can cover more backdoor feature
maps~(e.g., FMT removes 83.33\% of backdoor feature maps from the model in the
CIFAR10 \& BadNet scenario).Comment: 12 pages, 4 figure
Feature Map Testing for Deep Neural Networks
Due to the widespread application of deep neural networks~(DNNs) in
safety-critical tasks, deep learning testing has drawn increasing attention.
During the testing process, test cases that have been fuzzed or selected using
test metrics are fed into the model to find fault-inducing test units (e.g.,
neurons and feature maps, activating which will almost certainly result in a
model error) and report them to the DNN developer, who subsequently repair
them~(e.g., retraining the model with test cases). Current test metrics,
however, are primarily concerned with the neurons, which means that test cases
that are discovered either by guided fuzzing or selection with these metrics
focus on detecting fault-inducing neurons while failing to detect
fault-inducing feature maps.
In this work, we propose DeepFeature, which tests DNNs from the feature map
level. When testing is conducted, DeepFeature will scrutinize every internal
feature map in the model and identify vulnerabilities that can be enhanced
through repairing to increase the model's overall performance. Exhaustive
experiments are conducted to demonstrate that (1) DeepFeature is a strong tool
for detecting the model's vulnerable feature maps; (2) DeepFeature's test case
selection has a high fault detection rate and can detect more types of
faults~(comparing DeepFeature to coverage-guided selection techniques, the
fault detection rate is increased by 49.32\%). (3) DeepFeature's fuzzer also
outperforms current fuzzing techniques and generates valuable test cases more
efficiently.Comment: 12 pages, 5 figures. arXiv admin note: text overlap with
arXiv:2307.1101
Thiazolyl N-Benzyl-Substituted Acetamide Derivatives: Synthesis, Src Kinase Inhibitory and Anticancer Activities
KX2-391 (KX-01/Kinex Pharmaceuticals), N-benzyl-2-(5-(4-(2-morpholinoethoxy)phenyl)pyridin-2-yl)acetamide, is a highly selective Src substrate binding site inhibitor. To understand better the role of pyridine ring and N-benzylsubstitution in KX2-391 and establish the structure-activity relationship, a number of N-benzyl substituted (2-morpholinoethoxy)phenyl)thiazol-4-yl)acetamide derivatives containing thiazole instead of pyridine were synthesized and evaluated for Src kinase inhibitory activities. The unsubstituted N-benzyl derivative (8a) showed the inhibition of c-Src kinase with GI50 values of 1.34 μM and 2.30 M in NIH3T3/c-Src527F and SYF/c-Src527F cells, respectively. All the synthesized compounds were evaluated for inhibition of cell proliferation of human colon carcinoma (HT-29), breast carcinoma (BT-20), and leukemia (CCRF-CEM) cells. 4-Fluorobenzylthiazolyl derivative 8b exhibited 64-71% inhibition in the cell proliferation of BT-20 and CCR5 cells at concentration of 50 μM
SSeCKS Metastasis-Suppressing Activity in MatLyLu Prostate Cancer Cells Correlates with Vascular Endothelial Growth Factor Inhibition
Discovery and Characterization of Potent Dual P-Glycoprotein and CYP3A4 Inhibitors: Design, Synthesis, Cryo-EM Analysis, and Biological Evaluations
Targeted concurrent inhibition of intestinal drug efflux transporter P-glycoprotein (P-gp) and drug metabolizing enzyme cytochrome P450 3A4 (CYP3A4) is a promising approach to improve oral bioavailability of their common substrates such as docetaxel, while avoiding side effects arising from their pan inhibitions. Herein, we report the discovery and characterization of potent small molecule inhibitors of P-gp and CYP3A4 with encequidar (minimally absorbed P-gp inhibitor) as a starting point for optimization. To aid in the design of these dual inhibitors, we solved the high-resolution cryo-EM structure of encequidar hound to human P-gp. The structure guided us to prudently decorate the encequidar scaffold with CYP3A4 pharmacophores, leading to the identification of several analogues with dual potency against P-gp and CYP3A4. In vivo, dual P-gp and CYP3A4 inhibitor 3a improved the oral absorption of docetaxel by 3-fold as compared to vehicle, while 3a itself remained poorly absorbed.ISSN:1520-4804ISSN:0022-262
Peptidomimetic Src/Pretubulin Inhibitor KX-01 Alone and in Combination with Paclitaxel Suppresses Growth, Metastasis in Human ER/PR/HER2-Negative Tumor Xenografts
Ion Current-Based Proteomic Profiling for Understanding the Inhibitory Effect of Tumor Necrosis Factor Alpha on Myogenic Differentiation
Despite a demonstrated role for TNF-α
in promoting muscle
wasting and cachexia, the associated molecular mechanisms and signaling
pathways of myoblast differentiation dysregulated by TNF-α remain
poorly understood. This study presents well-controlled proteomic profiling
as a means to investigate the mechanisms of TNF-α-regulated
myogenic differentiation. Primary human muscle precursor cells (MPCs)
cultured in growth medium (GM), differentiation medium (DM) to induce
myogenic differentiation, and DM with 20 ng/mL of TNF-α (<i>n</i> = 5/group) were comparatively analyzed by an ion current-based
quantitative platform consisting of reproducible sample preparation/on-pellet
digestion, a long-column nano-LC separation, and ion current-based
differential analysis. The inhibition of myogenic differentiation
by TNF-α was confirmed by reduced formation of multinucleated
myotubes and the recovered expression of altered myogenic proteins
such as MYOD and myogenin during myogenic differentiation. Functional
analysis and validation by immunoassay analysis suggested that the
cooperation of NF-κB and STAT proteins is responsible for dysregulated
differentiation in MPCs by TNF-α treatment. Increased MHC class
I components such as HLA-A, HLA-B, HLA-C, and beta-2-microglobulin
were also observed in cultures in DM treated with TNF-α. Interestingly,
inhibition of the cholesterol biosynthesis pathway during myogenic
differentiation induced by serum starvation was not recovered by TNF-α
treatment, which combined with previous reports, implies that this
process may be an early event of myogenesis. This finding could lay
the foundation for the potential use of statins in modulating myogenesis
through cholesterol, for example, in stem cell-based myocardial infarction
treatment, where differentiation of myoblasts and stem cells into
force-generating mature muscle cells is a key step to the therapeutic
capacity. In conclusion, the landscapes of altered transcription regulators,
metabolic processes, and signaling pathways in MPCs are revealed in
the regulation of myogenic differentiation by TNF-α, which is
valuable for myogenic cellular therapeutics