Phosphoprotein patterns predict trametinib responsiveness and optimal trametinib sensitisation strategies in melanoma

Plasma-generated RONS in liquid transferred into cryo-microneedles patch for skin treatment of melanoma

Malignant melanoma is the most lethal form of skin cancer. As a promising anti-cancer agent, plasma-activated water (PAW) rich in reactive oxygen and nitrogen species (RONS) has shown significant potential for melanoma treatment. However, rapid decay of RONS and inefficient delivery of PAW in conventional injection methods limit its practical applications. To address this issue, here we report a new approach for the production of plasma-activated cryo-microneedles (PA-CMNs) patches using custom-designed plasma devices and processes. Our innovation is to incorporate PAW into the PA-CMNs that are fabricated using a fast cryogenic micro-molding method. It is demonstrated that PA-CMNs can be easily inserted into skin to release RONS and slow the decay of RONS thereby prolonging their bioactivity and effectiveness. The new insights into the effective melanoma treatment suggest that the rich mixture of RONS within PA-CMNs prepared by custom-developed hybrid plasma-assisted configuration induces both ferroptosis and apoptosis to selectively kill tumor cells. A significant inhibition of subcutaneous A375 melanoma growth was observed in PA-CMNs-treated tumor-bearing nude mice without any signs of systemic toxicity. The new approach based on PA-CMNs may potentially open new avenues for a broader range of disease treatments.

CD9 shapes glucocorticoid sensitivity in pediatric B-cell precursor acute lymphoblastic leukemia

Resistance to glucocorticoids (GC), the common agents for remission induction in pediatric B-cell precursor acute lymphoblastic leukemia (BCP-ALL), poses a significant therapeutic hurdle. Therefore, dissecting the mechanisms shaping GC resistance could lead to new treatment modalities. Here, we showed that CD9- BCP-ALL cells were preferentially resistant to prednisone and dexamethasone over other standard cytotoxic agents. Concordantly, we identified significantly more poor responders to the prednisone prephase among BCP-ALL patients with a CD9- phenotype, especially for those with adverse presenting features including older age, higher white cell count and BCR-ABL1. Furthermore, gain- and loss-offunction experiments dictated a definitive functional linkage between CD9 expression and GC susceptibility, as demonstrated by the reversal and acquisition of relative GC resistance in CD9low and CD9high BCP-ALL cells, respectively. Despite physical binding to the GC receptor NR3C1, CD9 did not alter its expression, phosphorylation or nuclear translocation but potentiated the induction of GC-responsive genes in GC-resistant cells. Importantly, the MEK inhibitor trametinib exhibited higher synergy with GC against CD9- than CD9+ lymphoblasts to reverse drug resistance in vitro and in vivo. Collectively, our results elucidate a previously unrecognized regulatory function of CD9 in GC sensitivity, and inform new strategies for management of children with resistant BCP-ALL.

Integrated analysis reveals SMARCD1 is a potential biomarker and therapeutic target in skin cutaneous melanoma

OBJECTIVE

SMARCD1 is a part of the SWI/SNF chromatin remodeling complex family, which consists of transcription factors that are implicated in various types of cancer. Examining SMARCD1 expression in human cancers can provide valuable insights into the development and progression of skin cutaneous melanoma (SKCM).

METHODS

Our study comprehensively examined the association between SMARCD1 expression and numerous factors, including prognosis, tumor microenvironment (TME), immune infiltration, tumor mutational burden (TMB), and microsatellite instability (MSI) in SKCM. Then we utilized immunohistochemical staining to measure the SMARCD1 expression in both SKCM tissues and normal skin tissues. Furthermore, we conducted in vitro experimentation to evaluate the effects of SMARCD1 knockdown on SKCM cells.

RESULTS

We found that aberrant expression of SMARCD1 across 16 cancers was strongly correlated with overall survival (OS) and progression-free survival (PFS). In addition, our research revealed that SMARCD1 expression is associated with multiple factors in different types of cancer, including immune infiltration, TME, immune-related genes, MSI, TMB, and sensitivity to anti-cancer drugs. SMARCD1 is likely involved in various SKCM signaling pathways and biological processes. Additionally, our research revealed that an SMARCD1-based risk factor model accurately predicted OS in SKCM patients. Furthermore, the downregulation of SMARCD1 expression demonstrated a significant inhibition of SKCM cell proliferation and migration, as well as an increase in apoptosis and cell cycle arrest.

CONCLUSION

We conclude that SMARCD1 is a promising diagnostic, prognostic, and therapeutic biomarker for SKCM, and its expression has significant clinical implications for the development of novel treatment strategies.

LSM2 is associated with a poor prognosis and promotes cell proliferation, migration, and invasion in skin cutaneous melanoma

BACKGROUND

Skin cutaneous melanoma (SKCM) is an extremely malignant tumor that is associated with a poor prognosis. LSM2 has been found to be related to different types of tumors; however, its role in SKCM is poorly defined. We aimed to determine the value of LSM2 as a prognostic biomarker for SKCM.

METHODS

The expression profile of LSM2 mRNA was compared between tumor and normal tissues in public databases, such as TCGA, GEO, and BioGPS. LSM2 protein expression was explored using immunohistochemistry (IHC) on a tissue microarray containing 44 SKCM tissues and 8 normal samples collected at our center. Kaplan-Meier analysis was performed to assess the prognostic value of LSM2 expression in patients with SKCM. SKCM cell lines with LSM2 knockdown were used to determine the effects of LSM2. Cell counting kit-8 (CCK8) and colony formation assays were conducted to assess cell proliferation, whereas wound healing and transwell assays were carried out to assess the migration and invasion abilities of SKCM cells.

RESULTS

LSM2 was more highly expressed at the mRNA and protein levels in SKCM than that in normal skin. Moreover, elevated expression of LSM2 was associated with shorter survival time and early recurrence in patients with SKCM. The in vitro results revealed that the silencing of LSM2 in SKCM cells significantly inhibited cell proliferation, migration, and invasion.

CONCLUSION

Overall, LSM2 contributes to malignant status and poor prognosis in patients with SKCM and may be identified as a novel prognostic biomarker and therapeutic target.

miR-100-5p Is a Novel Biomarker That Suppresses the Proliferation, Migration, and Invasion in Skin Cutaneous Melanoma

Objective

To better understand the role and underlying mechanisms of SKCM, we conducted bioinformatics analysis and in vivo experiments.

Results

We found its role as a tumor suppressor gene in SKCM and its effect on prognosis. In addition, this study found that miR-100-5p had a bidirectional effect on SKCM microenvironment. After exploring the relationship between the two, it was found that tumors with intermediate miR-100-5p expression had the highest level of immune cell infiltration. In addition, the value of miR-100-5p was assessed by survival analysis, univariate Cox regression analysis, and nomogram prognostic prediction. Finally, we constructed a regulatory network to illustrate the regulatory relationship of miR-100-5p.

Conclusions

In conclusion, the antitumor effect of miR-100-5p is revealed, and the present study is followed by a discussion of its molecular regulatory network, followed by novel insights into SKCM therapy.

MECHANISTIC AND DATA-DRIVEN MODELS OF CELL SIGNALING: TOOLS FOR FUNDAMENTAL DISCOVERY AND RATIONAL DESIGN OF THERAPY

A full understanding of cell signaling processes requires knowledge of protein structure/function relationships, protein-protein interactions, and the abilities of pathways to control phenotypes. Computational models offer a valuable framework for integrating that knowledge to predict the effects of system perturbations and interventions in health and disease. Whereas mechanistic models are well suited for understanding the biophysical basis for signal transduction and principles of therapeutic design, data-driven models are particularly suited to distill complex signaling relationships among samples and between multivariate signaling changes and phenotypes. Both approaches have limitations and provide incomplete representations of signaling biology, but their careful implementation and integration can provide new understanding for how manipulating system variables impacts cellular decisions.

Convergence of pathway analysis and pattern recognition predicts sensitization to latest generation TRAIL therapeutics by IAP antagonism

Second generation TRAIL-based therapeutics, combined with sensitising co-treatments, have recently entered clinical trials. However, reliable response predictors for optimal patient selection are not yet available. Here, we demonstrate that a novel and translationally relevant hexavalent TRAIL receptor agonist, IZI1551, in combination with Birinapant, a clinically tested IAP antagonist, efficiently induces cell death in various melanoma models, and that responsiveness can be predicted by combining pathway analysis, data-driven modelling and pattern recognition. Across a panel of 16 melanoma cell lines, responsiveness to IZI1551/Birinapant was heterogeneous, with complete resistance and pronounced synergies observed. Expression patterns of TRAIL pathway regulators allowed us to develop a combinatorial marker that predicts potent cell killing with high accuracy. IZI1551/Birinapant responsiveness could be predicted not only for cell lines, but also for 3D tumour cell spheroids and for cells directly isolated from patient melanoma metastases (80–100% prediction accuracies). Mathematical parameter reduction identified 11 proteins crucial to ensure prediction accuracy, with x-linked inhibitor of apoptosis protein (XIAP) and procaspase-3 scoring highest, and Bcl-2 family members strongly represented. Applied to expression data of a cohort of n = 365 metastatic melanoma patients in a proof of concept in silico trial, the predictor suggested that IZI1551/Birinapant responsiveness could be expected for up to 30% of patient tumours. Overall, response frequencies in melanoma models were very encouraging, and the capability to predict melanoma sensitivity to combinations of latest generation TRAIL-based therapeutics and IAP antagonists can address the need for patient selection strategies in clinical trials based on these novel drugs.

An ultrasensitive fiveplex activity assay for cellular kinases

Protein kinases are enzymes whose abundance, protein-protein interactions, and posttranslational modifications together determine net signaling activity in cells. Large-scale data on cellular kinase activity are limited, because existing assays are cumbersome, poorly sensitive, low throughput, and restricted to measuring one kinase at a time. Here, we surmount the conventional hurdles of activity measurement with a multiplexing approach that leverages the selectivity of individual kinase-substrate pairs. We demonstrate proof of concept by designing an assay that jointly measures activity of five pleiotropic signaling kinases: Akt, IκB kinase (IKK), c-jun N-terminal kinase (JNK), mitogen-activated protein kinase (MAPK)-extracellular regulated kinase kinase (MEK), and MAPK-activated protein kinase-2 (MK2). The assay operates in a 96-well format and specifically measures endogenous kinase activation with coefficients of variation less than 20%. Multiplex tracking of kinase-substrate pairs reduces input requirements by 25-fold, with ~75 µg of cellular extract sufficient for fiveplex activity profiling. We applied the assay to monitor kinase signaling during coxsackievirus B3 infection of two different host-cell types and identified multiple differences in pathway dynamics and coordination that warrant future study. Because the Akt-IKK-JNK-MEK-MK2 pathways regulate many important cellular functions, the fiveplex assay should find applications in inflammation, environmental-stress, and cancer research.

The cancer cell proteome and transcriptome predicts sensitivity to targeted and cytotoxic drugs

This study shows that the proteomic and transcriptomic states of cancer cells are more predictive of drug sensitivity than genomic markers for most drugs, both within and across tumor types.

Tumors of different molecular subtypes can show strongly deviating responses to drug treatment, making stratification of patients based on molecular markers an important part of cancer therapy. Pharmacogenomic studies have led to the discovery of selected genomic markers (e.g., BRAF^V600E), whereas transcriptomic and proteomic markers so far have been largely absent in clinical use, thus constituting a potentially valuable resource for further substratification of patients. To systematically assess the explanatory power of different -omics data types, we assembled a panel of 49 melanoma cell lines, including genomic, transcriptomic, proteomic, and pharmacological data, showing that drug sensitivity models trained on transcriptomic or proteomic data outperform genomic-based models for most drugs. These results were confirmed in eight additional tumor types using published datasets. Furthermore, we show that drug sensitivity models can be transferred between tumor types, although after correcting for training sample size, transferred models perform worse than within-tumor–type predictions. Our results suggest that transcriptomic/proteomic signals may be alternative biomarker candidates for the stratification of patients without known genomic markers.