SERS analysis of serum for detection of early and locally advanced breast cancer

n this contribution, we investigated whether surface-enhanced Raman scattering (SERS) of serum can be a candidate method for detecting \u201cluminal A\u201d breast cancer (BC) at different stages. We selected three groups of participants aged over 50 years: 20 healthy women, 20 women with early localized small BC, and 20 women affected by BC with lymph node involvement. SERS revealed clear spectral differences between these three groups. A predictive model using principal component analysis (PCA) and linear discriminant analysis (LDA) was developed based on spectral data, and its performance was estimated with cross-validation. PCA-LDA of SERS spectra could distinguish healthy from BC subjects (sensitivity, 92 %; specificity, 85 %), as well as subjects with BC at different stages, with a promising diagnostic performance (sensitivity and specificity, 6580 %; overall accuracy, 84 %). Our data suggest that SERS spectroscopy of serum, combined with multivariate data analysis, represents a minimally invasive, easy to use, and fast approach to discriminate healthy from BC subjects and even to distinguish BC at different clinical stages

Surface-enhanced Raman spectroscopy of urine for prostate cancer detection: a preliminary study

Surface-enhanced Raman scattering (SERS) spectra were obtained from urine samples from subjects diagnosed with prostate cancer as well as from healthy controls, using Au nanoparticles as substrates. Principal component analysis (PCA) of the spectral data, followed by linear discriminant analysis (LDA), leads to a classification model with a sensitivity of 100 %, a specificity of 89 %, and an overall diagnostic accuracy of 95 %. Even considering the very limited number of samples involved in this report, preliminary results from this approach are extremely promising, encouraging further investigation

Focal adhesion kinase plays a dual role in TRAIL resistance and metastatic outgrowth of malignant melanoma

Despite remarkable advances in therapeutic interventions, malignant melanoma (MM) remains a life-threating disease. Following high initial response rates to targeted kinase-inhibition metastases quickly acquire resistance and present with enhanced tumor progression and invasion, demanding alternative treatment options. We show 2nd generation hexameric TRAIL-receptor-agonist IZI1551 (IZI) to effectively induce apoptosis in MM cells irrespective of the intrinsic BRAF/NRAS mutation status. Conditioning to the EC50 dose of IZI converted the phenotype of IZI-sensitive parental MM cells into a fast proliferating and invasive, IZI-resistant metastasis. Mechanistically, we identified focal adhesion kinase (FAK) to play a dual role in phenotype-switching. In the cytosol, activated FAK triggers survival pathways in a PI3K- and MAPK-dependent manner. In the nucleus, the FERM domain of FAK prevents activation of wtp53, as being expressed in the majority of MM, and consequently intrinsic apoptosis. Caspase-8-mediated cleavage of FAK as well as FAK knockdown, and pharmacological inhibition, respectively, reverted the metastatic phenotype-switch and restored IZI responsiveness. FAK inhibition also re-sensitized MM cells isolated from patient metastasis that had relapsed from targeted kinase inhibition to cell death, irrespective of the intrinsic BRAF/NRAS mutation status. Hence, FAK-inhibition alone or in combination with 2nd generation TRAIL-receptor agonists may be recommended for treatment of initially resistant and relapsed MM, respectively

Mechanistic insight into the consequences of sublethal IZI1551 doses in unwanted proliferation and migration of melanoma metastases

Background: Metastatic melanoma remains a life-threatening disease because most tumours develop resistance in response to conventional treatment. Even though targeted drugs represent promising therapeutics, the clinical outcome remains poor, with high relapse rates coinciding with pronounced metastatic outgrowth. Therefore, successful therapy is still challenging, and alternative treatment options are demanded as first or second line therapy to overcome acquired resistance. In this context, cell death induction by the tumour-selective death ligand TRAIL (Tumour necrosis factor-Related Apoptosis-Inducing Ligand) might serve as an alternative single or co-treatment option. Unfortunately, melanoma cells were shown to stay largely resistant against conventional TRAIL treatment and the first-generation TRAIL-based therapeutics failed in clinical trials due to the limited therapeutic activity in patients. To overcome this therapeutic limitation, a second-generation hexavalent TRAIL receptor agonist IZI1551 has been developed showing increased bioactivity thereby enhancing the cytotoxic effects on cancer cells. Questions and Hypothesis. We hypothesized that cells that do not receive the full but only a sublethal drug-dose may not only be responsible for drug resistance but may also confer tumour relapse and metastatic outgrowth. By switching the signal transduction from pro-apoptotic to anti-apoptotic and pro-survival, these cells may foster an aggressive phenotype with enhanced proliferation and migration. Therefore, an in depth understanding of the underlying mechanisms of emerging drug resistance that may additionally trigger secondary metastasis formation is required to identify new therapeutic targets and alternative treatment options. Methodology. Melanoma cell lines were conditioned to the TRAIL receptor agonist IZI1551 and the expression of members of the anti-apoptotic NFκB and MAPK pathways as well as of the TRAIL receptor-driven apoptotic pathway were investigated by semi-quantitative Western-blot analysis. Protein expression/activation data of parental IZI1551-sensitive versus conditioned IZI1551-resistant melanoma cells were implemented into a network topology derived from literature. A Dynamic Bayesian Network (DBN) model was combined with a sophisticated regularisation strategy resulting in sparse and context-sensitive networks to identify cell line-specific deregulations within the signalling network. Predictions of the model were confirmed by siRNA-mediated knock down. Enhanced proliferation and migration of resistant-cells were investigated by proliferation, clonogenic, and scratch assays. Following the 2D studies, migration and invasion were monitored by confocal microscopy in 3D migration/invasion assays and 3D spheroids models. Expression of pro-metastatic cell adhesion molecules was evaluated by flow cytometry. In order to identify potential regulators of the aggressive phenotype, quantitative transcriptome analysis (RNA-seq) was performed. The therapeutic outcome of the new identified treatment options with IZI1551 alone or in combination with Smac mimetics or bortezomib was evaluated by cell death detection ELISA. Results. In this thesis, IZI1551 was shown to induce pronounced apoptotic cell death in melanoma cells compared to mutation specific targeted kinase inhibitors, as being used in the clinic. Comparing IZI1551-sensitive to IZI1551-resistant melanoma cells, the DBN model accurately predicted activation of NFκB in concert with upregulation of the anti-apoptotic protein XIAP to be the key mediator of IZI1551 resistance. Moreover, XIAP was identified to serve as a potential biomarker for TRAIL responsiveness. According to these findings, human melanoma cell lines were re-sensitised to TRAIL in vitro by co-application of the IAP antagonists Smac mimetics as well as bortezomib, a proteasome inhibitor currently used in cancer treatment. In addition, by triggering survival instead of apoptotic signalling pathways, resistant cells caused an aggressive phenotype with enhanced proliferation and migration/invasion into 3D collagen matrices, coinciding with upregulation of the cell adhesion molecules MelCAM and αVβ3 integrin, which are known to promote tumour progression and metastasis. Combining in silico studies of RNA-seq and protein expression data, YAP, an intracellular transducer of mechanical stimuli, and its upstream regulator FAK, a component of the focal adhesion complex, were identified as key promoters of proliferation and migration. Conclusions. Identification of new biomolecular markers or targets combining experimental and computational approaches is a promising avenue to assess the effects of drug combinations and to identify responders to selected combination therapies. In this thesis, IZI1551 was identified as an alternative treatment option for metastatic melanoma. Our data also suggest that XIAP expression may serve as a potential predictive marker for the sensitivity of tumour cells to TRAIL-induced apoptosis. Above this, we demonstrated that three alternative treatment options with IZI1551 in combination with Smac mimetics, bortezomib or FAK inhibitors may represent a promising approach for the treatment of TRAIL-resistant melanomas and to prevent undesired metastatic outgrowth

Systemic network analysis identifies XIAP and IkappaBalpha as potential drug targets in TRAIL resistant BRAF mutated melanoma.

Metastatic melanoma remains a life-threatening disease because most tumors develop resistance to targeted kinase inhibitors thereby regaining tumorigenic capacity. We show the 2nd generation hexavalent TRAIL receptor-targeted agonist IZI1551 to induce pronounced apoptotic cell death in mutBRAF melanoma cells. Aiming to identify molecular changes that may confer IZI1551 resistance we combined Dynamic Bayesian Network modelling with a sophisticated regularization strategy resulting in sparse and context-sensitive networks and show the performance of this strategy in the detection of cell line-specific deregulations of a signalling network. Comparing IZI1551-sensitive to IZI1551-resistant melanoma cells the model accurately and correctly predicted activation of NFkappaB in concert with upregulation of the anti-apoptotic protein XIAP as the key mediator of IZI1551 resistance. Thus, the incorporation of multiple regularization functions in logical network optimization may provide a promising avenue to assess the effects of drug combinations and to identify responders to selected combination therapies

Metabolic modelling-based in silico drug target prediction identifies six novel repurposable drugs for melanoma

Despite high initial response rates to targeted kinase inhibitors, the majority of patients suffering from metastatic melanoma present with high relapse rates, demanding for alternative therapeutic options. We have previously developed a drug repurposing workflow to identify metabolic drug targets that, if depleted, inhibit the growth of cancer cells without harming healthy tissues. In the current study, we have applied a refined version of the workflow to specifically predict both, common essential genes across various cancer types, and melanoma-specific essential genes that could potentially be used as drug targets for melanoma treatment. The in silico single gene deletion step was adapted to simulate the knock-out of all targets of a drug on an objective function such as growth or energy balance. Based on publicly available, and in-house, large-scale transcriptomic data metabolic models for melanoma were reconstructed enabling the prediction of 28 candidate drugs and estimating their respective efficacy. Twelve highly efficacious drugs with low half-maximal inhibitory concentration values for the treatment of other cancers, which are not yet approved for melanoma treatment, were used for in vitro validation using melanoma cell lines. Combination of the top 4 out of 6 promising candidate drugs with BRAF or MEK inhibitors, partially showed synergistic growth inhibition compared to individual BRAF/MEK inhibition. Hence, the repurposing of drugs may enable an increase in therapeutic options e.g., for non- responders or upon acquired resistance to conventional melanoma treatment