Prognostic and predictive biomarkers in melanoma: an update

Identification of Important Modules and Biomarkers That Are Related to Immune Infiltration Cells in Severe Burns Based on Weighted Gene Co-Expression Network Analysis

Background: Immunosuppression is an important trigger for infection and a significant cause of death in patients with severe burns. Nevertheless, the prognostic value of immune-related genes remains unclear. This study aimed to identify the biomarkers related to immunosuppression in severe burns. Methods: The gene expression profile and clinical data of 185 burn and 75 healthy samples were obtained from the GEO database. Immune infiltration analysis and gene set variation analysis were utilized to identify the disorder of circulating immune cells. A weighted gene co-expression network analysis (WGCNA) was carried out to select immune-related gene modules. Enrichment analysis and protein-protein interaction (PPI) network were performed to select hub genes. Next, LASSO and logistic regression were utilized to construct the hazard regression model with a survival state. Finally, we investigated the correlation between high- and low-risk patients in total burn surface area (TBSA), age, and inhalation injury. Results: Gene set variation analysis (GSVA) and immune infiltration analysis showed that neutrophils increased and T cells decreased in severe burns. In WGCNA, four modular differently expressed in burns and controls were related to immune cells. Based on PPI and enrichment analysis, 210 immune-related genes were identified, mainly involved in T-cell inhibition and neutrophil activation. In LASSO and logistic regression, we screened out key genes, including LCK, SKAP1 and GZMB, and LY9. In the ROC analysis, the area under the curve (AUC) of key genes was 0.945, indicating that the key genes had excellent diagnostic value. Finally, we discovered that the key genes were related to T cells, and the regression model performed well when accompanied by TBSA and age. Conclusion: We identified LCK, SKAP1, GZMB, and LY9 as good prognostic biomarkers that may play a role in post-burn immunosuppression against T-cell dysfunction and as potential immunotherapeutic targets for transformed T-cell dysfunction.

The role of PI3'-lipid signalling in melanoma initiation, progression and maintenance

Phosphatidylinositol-3'-kinases (PI3Ks) are a family of lipid kinases that phosphorylate the 3' hydroxyl (OH) of the inositol ring of phosphatidylinositides (PI). Through their downstream effectors, PI3K generated lipids (PI3K-lipids hereafter) such as PI(3,4,5)P3 and PI(3,4)P2 regulate myriad biochemical and biological processes in both normal and cancer cells including responses to growth hormones and cytokines; the cell division cycle; cell death; cellular growth; angiogenesis; membrane dynamics; and autophagy and many aspects of cellular metabolism. Engagement of receptor tyrosine kinase by their cognate ligands leads to activation of members of the Class I family of PI3'-kinases (PI3Kα, β, δ & γ) leading to accumulation of PI3K-lipids. Importantly, PI3K-lipid accumulation is antagonized by the hydrolytic action of a number of PI3K-lipid phosphatases, most notably the melanoma suppressor PTEN (lipid phosphatase and tensin homologue). Downstream of PI3K-lipid production, the protein kinases AKT1-3 are believed to be key effectors of PI3'-kinase signalling in cells. Indeed, in preclinical models, activation of the PI3K→AKT signalling axis cooperates with alterations such as expression of the BRAFV600E oncoprotein kinase to promote melanoma progression and metastasis. In this review, we describe the different classes of PI3K-lipid effectors, and how they may promote melanomagenesis, influence the tumour microenvironment, melanoma maintenance and progression to metastatic disease. We also provide an update on both FDA-approved or experimental inhibitors of the PI3K→AKT pathway that are currently being evaluated for the treatment of melanoma either in preclinical models or in clinical trials.

Autophagy Inhibition in BRAF-Driven Cancers

Simple Summary

BRAF is a protein kinase that is frequently mutationally activated in cancer. Mutant BRAF can be pharmacologically inhibited, which in combination with blockade of its direct effector, MEK1/2, is an FDA-approved therapeutic strategy for several BRAF-mutated cancer patients, such as melanoma, non-small-cell lung carcinoma, and thyroid cancer. However, therapy resistance is a major clinical challenge, highlighting the need for comprehensive investigations on the biological causes of such resistance, as well as to develop novel therapeutic strategies to improve patient survival. Autophagy is a cellular recycling process, which has been shown to allow cancer cells to escape from BRAF inhibition. Combined blockade of autophagy and BRAF signaling is a novel therapeutic strategy that is currently being tested in clinical trials. This review describes the relationship between BRAF-targeted therapy and autophagy regulation and discusses possible future treatment strategies.

Abstract

Several BRAF-driven cancers, including advanced BRAF^V600E/K-driven melanoma, non-small-cell lung carcinoma, and thyroid cancer, are currently treated using first-line inhibitor combinations of BRAF^V600E plus MEK1/2. However, despite the success of this vertical inhibition strategy, the durability of patient response is often limited by the phenomenon of primary or acquired drug resistance. It has recently been shown that autophagy, a conserved cellular recycling process, is increased in BRAF-driven melanoma upon inhibition of BRAF^V600E signaling. Autophagy is believed to promote tumor progression of established tumors and also to protect cancer cells from the cytotoxic effects of chemotherapy. To this end, BRAF inhibitor (BRAFi)-resistant cells often display increased autophagy compared to responsive lines. Several mechanisms have been proposed for BRAFi-induced autophagy, such as activation of the endoplasmic reticulum (ER) stress gatekeeper GRP78, AMP-activated protein kinase, and transcriptional regulation of the autophagy regulating transcription factors TFEB and TFE3 via ERK1/2 or mTOR inhibition. This review describes the relationship between BRAF-targeted therapy and autophagy regulation, and discusses possible future treatment strategies of combined inhibition of oncogenic signaling plus autophagy for BRAF-driven cancers.

Combinatorial Therapies to Overcome BRAF/MEK Inhibitors Resistance in Melanoma Cells: An in vitro Study

BACKGROUND

Melanoma accounts for only 1% of all skin malignant tumors; however, it is the deadliest form of skin cancer. Since 2011, FDA (Food and Drug Administration) approved several novel therapeutic strategies, such as MAPK pathway targeted therapies, to treat cutaneous melanoma patients. However, their improvements in overall survival were limited, due to the development of resistance.

METHODS

In this work, several combinations of therapies, including the metabolic modulator DCA, were tested in melanoma cell lines, considering that MAPK and PI3K/AKT/mTOR pathways are deregulated and interconnected in melanoma and that the presence of the Warburg effect in melanoma cells may influence the response to therapy. The effect of the treatments was assessed in the proliferation and survival of melanoma cell lines with different genetic profiles. Also, the possibility to overcome resistance to the treatment with vemurafenib was tested.

RESULTS

In general, higher decrease in cell viability and cell proliferation and increase in apoptosis were obtained after the combination treatments, comparing with single treatments, in all the studied cell lines. The combination of cobimetinib and everolimus appear to be the best treatment option. The BRAFV600E -vemurafenib resistant melanoma cell line showed to retain sensitivity to both everolimus and DCA.

DISCUSSION AND CONCLUSION

Our results suggest that the combination of MAPK pathway inhibitors with mTOR pathway inhibitors and DCA should be considered as therapeutic options to treat melanoma patients, as the combinations potentiated the effects of each drug alone. In a cell line resistant to vemurafenib, we verified that combined MAPK inhibitors with inhibition of mTOR pathway and/or DCA metabolism modulation might constitute possible strategies in order to overcome resistance to MAPK inhibition.

Prognostic significance of an 11-gene RNA assay in archival tissue of cutaneous melanoma stage I-III patients

PURPOSE

The purpose of this study was to validate the results of an 11-gene expression profiling (GEP) assay which aims to improve the precision of individual prognosis beyond conventional American Joint Committee on Cancer staging for patients with cutaneous melanoma.

METHODS

The reverse transcriptase polymerase chain reaction test of 11 prospectively selected genes was performed on 291 formalin-fixed, paraffin-embedded primary tumours of patients with stage I-III cutaneous melanoma. The expression levels of eight prognostic and three reference genes were used in a predefined algorithm to calculate a numerical score (-0.84 to 3.53) and then assign each patient to a preselected risk group (low versus high score) for melanoma-specific survival (MSS).

RESULTS

One hundred twenty-seven patients were allocated to the low-score group, with a corresponding five-year disease-free survival (DFS) and MSS of 95% and 99%, respectively. 164 patients were allocated to the high-score group, with a corresponding five-year DFS and MSS of 78% and 88%. Continuous regression analysis demonstrated decreasing MSS probabilities with increasing scores. In a multivariate cox regression, only the 11-GEP, tumour thickness and age were statistically associated with MSS (p = 0.0068, 0.002 and 0.0159).

CONCLUSIONS

The 11-GEP has been validated as an independent predictor of outcome for melanoma patients. More specifically, using an 11-GEP score cut-off of ≤0, the assay can identify patient cohorts with 10-year survival probabilities well above 90%. This information may be used in the decision-making for a potential adjuvant therapy.

Pathogenic germline variants are associated with poor survival in stage III/IV melanoma patients

Patients with late stage resected cutaneous melanoma have poor overall survival (OS) and experience irreversible adverse events from systemic therapy. There is a clinical need to identify biomarkers to predict outcome. Performing germline/tumour whole-exome sequencing of 44 stage III/IV melanoma patients we identified pathogenic germline mutations in CDKN2A, CDK4, ATM, POLH, MRE11A, RECQL4 and XPC, affecting 7/44 patients. These mutations were associated with poor OS (p = 0.0082). We confirmed our findings in The Cancer Genome Atlas (TCGA) human skin cutaneous melanoma cohort where we identified pathogenic variants in 40/455 patients (p = 0.0203). Combining these cohorts (n = 499) further strengthened these findings showing germline carriers had worse OS (p = 0.0009). Additionally, we determined whether tumour mutation burden (TMB) or BRAF status were prognostic markers of survival. Low TMB rate (< 20 Mut/Mb; p = 0.0034) and BRAF p.V600 mutation (p = 0.0355) were associated with worse progression-free survival. Combining these biomarkers indicated that V600 mutant patients had significantly lower TMB (p = 0.0155). This was confirmed in the TCGA (n = 443, p = 0.0007). Integrative analysis showed germline mutation status conferred the highest risk (HR 5.2, 95% CI 1.72–15.7). Stage IV (HR 2.5, 0.74–8.6) and low TMB (HR 2.3, 0.57–9.4) were similar, whereas BRAF V600 status was the weakest prognostic biomarker (HR 1.5, 95% CI 0.44–5.2).

Retracted: Identification and validation of hypoxic markers of glioblastoma multiforme in methylation, somatic CNV characteristics based on large-scale samples

Retraction: Wang J, Xu S, Lv W, Shan A, Shi F, Xu J, Mei S, and Yang Y. Identification and validation of hypoxic markers of glioblastoma multiforme in methylation, somatic CNV characteristics based on large-scale samples. J Biochem Mol Toxicol. 2020; e22585. https://doi.org/10.1002/jbt.22585 The above article, published online on 24 July 2020 in Wiley Online Library (wileyonlinelibrary.com) has been retracted by agreement between the authors, the journal's Editor-in-Chief, Hari K. Bhat, and Wiley Periodicals, LLC. The retraction has been agreed due to the authors raising concerns about the accuracy of their data following their article's acceptance. The authors had agreed with the Editor-in-Chief to withdraw their manuscript before publication. However, unfortunately, the Version of Record was mistakenly published online on the journal's Early View service before it could be withdrawn. The Publisher apologizes to the authors for this error.

Serum markers improve current prediction of metastasis development in early-stage melanoma patients: a machine learning-based study

Metastasis development represents an important threat for melanoma patients, even when diagnosed at early stages and upon removal of the primary tumor. In this scenario, determination of prognostic biomarkers would be of great interest. Serum contains information about the general status of the organism and therefore represents a valuable source for biomarkers. Thus, we aimed to define serological biomarkers that could be used along with clinical and histopathological features of the disease to predict metastatic events on the early‐stage population of patients. We previously demonstrated that in stage II melanoma patients, serum levels of dermcidin (DCD) were associated with metastatic progression. Based on the relevance of the immune response on the cancer progression and the recent association of DCD with local and systemic immune response against cancer cells, serum DCD was analyzed in a new cohort of patients along with interleukin 4 (IL‐4), IL‐6, IL‐10, IL‐17A, interferon γ (IFN‐γ), transforming growth factor‐β (TGF‐ β), and granulocyte–macrophage colony‐stimulating factor (GM‐CSF). We initially recruited 448 melanoma patients, 323 of whom were diagnosed as stages I‐II according to AJCC. Levels of selected cytokines were determined by ELISA and Luminex, and obtained data were analyzed employing machine learning and Kaplan–Meier techniques to define an algorithm capable of accurately classifying early‐stage melanoma patients with a high and low risk of developing metastasis. The results show that in early‐stage melanoma patients, serum levels of the cytokines IL‐4, GM‐CSF, and DCD together with the Breslow thickness are those that best predict melanoma metastasis. Moreover, resulting algorithm represents a new tool to discriminate subjects with good prognosis from those with high risk for a future metastasis.

RAC1mutation is not a predictive biomarker for PI3'-kinase-β-selective pathway-targeted therapy

Mutational activation of RAC1 is detected in ~7% of cutaneous melanoma, with the most frequent mutation (RAC1^C85T ) encoding for RAC1^P29S . RAC1^P29S is a fast-cycling GTPase that leads to accumulation of RAC1^P29S -GTP, which has potentially pleiotropic regulatory functions in melanoma cell signaling and biology. However, the precise mechanism by which mutationally activated RAC1^P29S propagates its pro-tumorigenic effects remains unclear. RAC1-GTP is reported to activate the beta isoform of PI3'-kinase (PIK3CB/PI3Kβ) leading to downstream activation of PI3'-lipid signaling. Hence, we employed both genetic and isoform-selective pharmacological inhibitors to test if RAC1^P29S propagates its oncogenic signaling in melanoma through PI3Kβ. We observed that RAC1^P29S -expressing melanoma cells were largely insensitive to inhibitors of PI3Kβ. Furthermore, RAC1^P29S melanoma cell lines showed variable sensitivity to pan-class 1 (α/β/γ/δ) PI3'-kinase inhibitors, suggesting that RAC1-mutated melanoma cells may not rely on PI3'-lipid signaling for their proliferation. Lastly, we observed that RAC1^P29S -expressing cell lines also showed variable sensitivity to pharmacological inhibition of the RAC1 → PAK1 signaling pathway, questioning the relevance of inhibitors of this pathway for the treatment of patients with RAC1-mutated melanoma.

Clinical validation of a prognostic 11-gene expression profiling score in prospectively collected FFPE tissue of patients with AJCC v8 stage II cutaneous melanoma

BACKGROUND

Adjuvant therapies have been approved for patients with AJCC (American Joint Committee on Cancer) stage III and stage IV cutaneous melanoma (CM) after complete resection. These therapies might also be indicated for patients with high-risk stage II CM.

MATERIAL AND METHODS

We included patients diagnosed with stage II melanoma between 2000 and 2016 and for which primary tumour tissue was available. The prognostic value of the 11-gene expression profiling score (GEPS) was evaluated as a dichotomized parameter (GEPS ≤0 vs. >0). Endpoints of the analysis were melanoma specific survival (MSS), distant metastasis-free survival (DMFS) and relapse-free survival (RFS).

RESULTS

GEPS was determined in 245 patients ranging between -0.7 and 3.53. A total of 111 females and 134 males were included; the median follow-up was 41 months. Kaplan Meier analyses showed statistically significant survival differences between patients with high GEPS (n = 154) and low GEPS (n = 91) for MSS (p = 0.018), DMFS (p = 0.005) and RFS (p = 0.009). The 5-year and 10-year MSS was 92% in the low-GEPS and 82% and 67% in the high-GEPS group, respectively. Multivariate Cox regression analysis showed independent significance for MSS of GEPS (HR = 1.55; p = 0.006), tumor thickness (HR = 1.21; p < 0.001) and age (HR1.05; p = 0.002).

CONCLUSION

GEPS was validated as independent prognostic factor for MSS in stage II CM and could be used for therapeutic decisions when systemic therapies become available in stage II CM.

Twenty Metabolic Genes Based Signature Predicts Survival of Glioma Patients

Background: Glioma, caused by carcinogenesis of brain and spinal glial cells, is the most common primary malignant brain tumor. To find the important indicator for glioma prognosis is still a challenge and the metabolic alteration of glioma has been frequently reported recently.

Methods: In our current work, a risk score model based on the expression of twenty metabolic genes was developed using the metabolic gene expressions in The Cancer Genome Atlas (TCGA) dataset, the methods of which included the cox multivariate regression and the random forest variable hunting, a kind of machine learning algorithm, and the risk score generated from this model is used to make predictions in the survival of glioma patients in the training dataset. Subsequently, the result was further verified in other three verification sets (GSE4271, GSE4412 and GSE16011). Risk score related pathways collected in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database were identified using Gene Set Enrichment Analysis (GSEA).

Results: The risk score generated from our model makes good predictions in the survival of glioma patients in the training dataset and other three verification sets. By assessing the relationships between clinical indicators and the risk score, we found that the risk score was an independent and significant indicator for the prognosis of glioma patients. Simultaneously, we conducted a survival analysis of the patients who received chemotherapy and who did not, finding that the risk score was equally valid in both cases. And signaling pathways related to the genesis and development of multiple cancers were also identified.

Conclusions: In summary, our risk score model is predictive for 967 glioma patients' survival from four independent datasets, and the risk score is a meaningful and independent parameter of the clinicopathological information.

Precision Medicine and Radiogenomics in Breast Cancer: New Approaches toward Diagnosis and Treatment

Precision medicine is medicine optimized to the genotypic and phenotypic characteristics of an individual and, when present, his or her disease. It has a host of targets, including genes and their transcripts, proteins, and metabolites. Studying precision medicine involves a systems biology approach that integrates mathematical modeling and biology genomics, transcriptomics, proteomics, and metabolomics. Moreover, precision medicine must consider not only the relatively static genetic codes of individuals, but also the dynamic and heterogeneous genetic codes of cancers. Thus, precision medicine relies not only on discovering identifiable targets for treatment and surveillance modification, but also on reliable, noninvasive methods of identifying changes in these targets over time. Imaging via radiomics and radiogenomics is poised for a central role. Radiomics, which extracts large volumes of quantitative data from digital images and amalgamates these together with clinical and patient data into searchable shared databases, potentiates radiogenomics, which is the combination of genetic and radiomic data. Radiogenomics may provide voxel-by-voxel genetic information for a complete, heterogeneous tumor or, in the setting of metastatic disease, set of tumors and thereby guide tailored therapy. Radiogenomics may also quantify lesion characteristics, to better differentiate between benign and malignant entities, and patient characteristics, to better stratify patients according to risk for disease, thereby allowing for more precise imaging and screening. This report provides an overview of precision medicine and discusses radiogenomics specifically in breast cancer. ^© RSNA, 2018.

Molecular paleopathology and paleo-oncology-State of the art, potentials, limitations and perspectives

This paper reviews the current knowledge on molecular paleopathology with respect to oncological information. This covers both the information on the protein level (proteome) as well as the gene level (genome) and includes data on carcinogenic factors - such as molecular evidence for oncogenic viral infections. Currently, relatively little data is available for neoplastic disease in paleopathology. Likewise, few studies describe the biochemical or immunohistochemical analysis of tumors - a tool to potentially classify the tumor type and the underlying primary tumor in metastases. On the gene level, two studies described distinct molecular mutations in either a tumor-driving oncogene or a tumor suppressor gene, both being excellent examples for paleo-oncological studies. The paucity of historic tumor material - particularly when only osseous remains are available - represents the most hindering factor for molecular paleo-oncology. This can only be overcome in future by both the thorough investigation of mummified archaeological biomaterial and the improvement of analytical assays in order to trace even minute amounts of tumor material in osseous lesions.

MicroRNA-Directed Cancer Therapies: Implications in Melanoma Intervention

Acquired tumor resistance to cancer therapies poses major challenges in the treatment of cancers including melanoma. Among several signaling pathways or factors that affect neocarcinogenesis, cancer progression, and therapies, altered microRNAs (miRNAs) expression has been identified as a crucial player in modulating the key pathways governing these events. While studies in the miRNA field have grown exponentially in the last decade, much remains to be discovered, particularly with respect to their roles in cancer therapies. Since immune and nonimmune signaling cascades prevail in cancers, identification and evaluation of miRNAs, their molecular mechanisms and cellular targets involved in the underlying development of cancers, and acquired therapeutic resistance would help in devising new strategies for the prognosis, treatment, and an early detection of recurrence. Importantly, in-depth validation of miRNA-targeted molecular events could lead to the development of accurate progression-risk biomarkers, improved effectiveness, and improved patient responses to standard therapies. The current review focuses on the roles of miRNAs with recent updates on regulated cell cycle and proliferation, immune responses, oncogenic/epigenetic signaling pathways, invasion, metastasis, and apoptosis, with broader attention paid to melanomagenesis and melanoma therapies.

Immune profiling of melanoma tumors reflecting aggressiveness in a preclinical model

Melanoma, like most solid tumors, is highly heterogeneous in terms of invasive, proliferative, and tumor-initiating potential. This heterogeneity is the outcome of differential gene expression resulting from conditions in the tumor microenvironment and the selective pressure of the immune system. To investigate possible signatures combining immune-related gene expression and lymphocyte infiltration, we established a preclinical model using B16.F1-derived clones, in the context of melanoma aggressiveness. Combinatorial analyses revealed that tumors concomitantly expressing low levels of Tnf-a, Pd-1, Il-10, Il-1ra, Ccl5, Ido, high Il-9, and with low infiltration by CD45+, CD3+, CD4+ and CD8+ cells and a high CD4+:CD8+ T cell ratio exhibited the most aggressive growth characteristics. Overall, these results support the notion that the intratumoral immunologic network molds aggressive melanoma phenotypes.

Prospective Validation of Molecular Prognostic Markers in Cutaneous Melanoma: A Correlative Analysis of E1690

Purpose: To validate the prognostic impact of combined expression levels of three markers (SPP1, RGS1, and NCOA3) in melanoma specimens from patients enrolled in the E1690 clinical trial of high-dose or low-dose IFNα-2b versus observation.Experimental Design: Tissue was available from 248 patients. Marker expression was determined by digital imaging of immunohistochemically stained slides. The prognostic impact of each marker was first assessed by recording its expression value relative to the median. A multimarker index was then developed to combine marker expression levels by counting for each patient the number of markers with high expression. The impact of the multimarker index on relapse-free survival (RFS) and overall survival (OS) was assessed using Kaplan-Meier analysis, and both univariate and multivariate Cox regression analyses.Results: By Kaplan-Meier analysis, high multimarker expression scores were significantly predictive of RFS (P < 0.001) and OS (P < 0.001). Stepwise multivariate Cox regression analysis with backward elimination that included routine clinical and histologic prognostic factors revealed high multimarker expression scores and tumor thickness as the only factors significantly and independently predicting RFS and OS. Stepwise multivariate Cox regression analyses that also included treatment type and number of positive lymph nodes generated identical results for both RFS and OS. In the molecularly defined low-risk subgroup, patients treated with high-dose IFN had a significantly improved RFS compared with patients in the other two subgroups (P < 0.05).Conclusions: These results validate the independent impact of combined expression levels of SPP1, RGS1, and NCOA3 on survival of melanoma in a prospectively collected cohort. Clin Cancer Res; 23(22); 6888-92. ©2017 AACR.

Recent advances in melanoma research via "omics" platforms

Melanoma has a high mortality rate and metastatic melanoma is highly resistant to conventional therapies. "Omics" fields such as proteomics and microRNA and exosome studies have provided new knowledge to complement the information generated by genomic studies. This work aimed to review the current status of biomarker discovery for melanoma through multi-"omics" platforms. A few sets of novel microRNAs and proteins are described, some of them with important implications in suppressing melanoma at different stages. Upregulation of genes involved in angiogenesis, immunosuppressive factors, modification of stroma, capture of melanoma cells in lymph nodes and factors responsible for tumour cell recruitment have been identified in exosomes, among molecules with other functions. A remarkable series of proteins involved in epithelial-mesenchymal/mesenchymal-epithelial transitions, inflammation, motility, proliferation and progression processes, centrosome amplification, aneuploidy, inhibition of CD8+ effector T-cells, and metastasis in general were identified. Genomic and protein-protein interactions or metabolome levels were not analysed. Proteomics tools such as Orbitrap shotgun mass spectrometry or deep mining proteomic analysis utilizing high-resolution reversed phase nanoseparation in combination with mass spectrometry are also discussed. The application of these tools together with bioinformatics approaches applied to the clinical setting will enable the implementation of personalized medicine in the near future.

Baicalein Inhibits the Migration and Invasion of B16F10 Mouse Melanoma Cells through Inactivation of the PI3K/Akt Signaling Pathway

Baicalein, a natural flavonoid obtained from the rhizome of Scutellaria baicalensis Georgi, has been reported to have anticancer activities in several human cancer cell lines. However, its antimetastatic effects and associated mechanisms in melanoma cells have not been extensively studied. The current study examined the effects of baicalein on cell motility and anti-invasive activity using mouse melanoma B16F10 cells. Within the noncytotoxic concentration range, baicalein significantly inhibited the cell motility and invasiveness of B16F10 cells in a concentration-dependent manner. Baicalein also reduced the activity and expression of matrix metalloproteinase (MMP)-2 and -9; however, the levels of tissue inhibitor of metalloproteinase-1 and -2 were concomitantly increased. The inhibitory effects of baicalein on cell motility and invasiveness were found to be associated with its tightening of tight junction (TJ), which was demonstrated by an increase in transepithelial electrical resistance and downregulation of the claudin family of proteins. Additionally, treatment with baicalein markedly reduced the expression levels of lipopolysaccharide-induced phosphorylated Akt and the invasive activity in B16F10 cells. Taken together, these results suggest that baicalein inhibits B16F10 melanoma cell migration and invasion by reducing the expression of MMPs and tightening TJ through the suppression of claudin expression, possibly in association with a suppression of the phosphoinositide 3-kinase/Akt signaling pathway.

Towards standardization of next-generation sequencing of FFPE samples for clinical oncology: intrinsic obstacles and possible solutions

BACKGROUND

Next generation sequencing has a potential to revolutionize the management of cancer patients within the framework of precision oncology. Nevertheless, lack of standardization decelerated entering of the technology into the clinical testing space. Here we dissected a number of common problems of NGS diagnostics in oncology and introduced ways they can be resolved.

METHODS

DNA was extracted from 26 formalin fixed paraffin embedded (FFPE) specimens and processed with the TrueSeq Amplicon Cancer Panel (Illumina Inc, San Diego, California) targeting 48 cancer-related genes and sequenced in single run. Sequencing data were comparatively analyzed by several bioinformatics pipelines.

RESULTS

Libraries yielded sufficient coverage to detect even low prevalent mutations. We found that the number of FFPE sequence artifacts significantly correlates with pre-normalization concentration of libraries (rank correlation -0.81; p < 1e-10), thus, contributing to sample-specific variant detection cut-offs. Surprisingly, extensive validation of EGFR mutation calls by a combination of aligners and variant callers resulted in identification of two false negatives and one false positive that were due to complexity of underlying genomic change, confirmed by Sanger sequencing. Additionally, the study of the non-EGFR amplicons revealed 33 confirmed unique mutations in 17 genes, with TP53 being the most frequently mutated. Clinical relevance of these finding is discussed.

CONCLUSIONS

Reporting of entire mutational spectrum revealed by targeted sequencing is questionable, at least until the clinically-driven guidelines on reporting of somatic mutations are established. The standardization of sequencing protocols, especially their data analysis components, requires assay-, disease-, and, in many cases, even sample-specific customization that could be performed only in cooperation with clinicians.