Transcriptomic Analysis Reveals Prognostic Molecular Signatures of Stage I Melanoma

Prognostic and predictive biomarkers in melanoma

Biomarkers help to inform the clinical management of patients with melanoma. For patients with clinically localised primary melanoma, biomarkers can help to predict post-surgical outcome (including via the use of risk prediction tools), better select patients for sentinel lymph node biopsy, and tailor catch-all follow-up protocols to the individual. Systemic drug treatments, including immune checkpoint inhibitor (ICI) therapies and BRAF-targeted therapies, have radically improved the prognosis of metastatic (stage III and IV) cutaneous melanoma patients, and also shown benefit in the earlier setting of stage IIB/C primary melanoma. Unfortunately, a response is far from guaranteed. Here, we review clinically relevant, established, and emerging, prognostic, and predictive pathological biomarkers that refine clinical decision-making in primary and metastatic melanoma patients. Gene expression profile assays and nomograms are emerging tools for prognostication and sentinel lymph node risk prediction in primary melanoma patients. Biomarkers incorporated into clinical practice guidelines include BRAF V600 mutations for the use of targeted therapies in metastatic cutaneous melanoma, and the HLA-A∗02:01 allele for the use of a bispecific fusion protein in metastatic uveal melanoma. Several predictive biomarkers have been proposed for ICI therapies but have not been incorporated into Australian clinical practice guidelines. Further research, validation, and assessment of clinical utility is required before more prognostic and predictive biomarkers are fluidly integrated into routine care.

Molecular Classifiers in Skin Cancers: Challenges and Promises

Skin cancers are common and heterogenous malignancies affecting up to two in three Australians before age 70. Despite recent developments in diagnosis and therapeutic strategies, the mortality rate and costs associated with managing patients with skin cancers remain high. The lack of well-defined clinical and histopathological features makes their diagnosis and classification difficult in some cases and the prognostication difficult in most skin cancers. Recent advancements in large-scale "omics" studies, including genomics, transcriptomics, proteomics, metabolomics and imaging-omics, have provided invaluable information about the molecular and visual landscape of skin cancers. On many occasions, it has refined tumor classification and has improved prognostication and therapeutic stratification, leading to improved patient outcomes. Therefore, this paper reviews the recent advancements in omics approaches and appraises their limitations and potential for better classification and stratification of skin cancers.

ROR2 promotes epithelial-mesenchymal transition by hyperactivating ERK in melanoma

Receptor tyrosine kinase-like orphan receptor 2 (ROR2) is a protein with important functions during embryogenesis that is dysregulated in human cancer. An intriguing feature of this receptor is that it plays opposite roles in different tumor types either promoting or inhibiting tumor progression. Understanding the complex role of this receptor requires a more profound exploration of both the altered biological and molecular mechanisms. Here, we describe that ROR2 promotes Epithelial-Mesenchymal Transition (EMT) by inducing cadherin switch and the upregulation of the transcription factors ZEB1, Twist, Slug, Snail, and HIF1A, together with a mesenchymal phenotype and increased migration. We show that ROR2 activates both p38 and ERK mitogen-activated protein kinase pathways independently of Wnt5a. Further, we demonstrated that the upregulation of EMT-related proteins depends on the hyperactivation of the ERK pathway far above the typical high constitutive activity observed in melanoma. In addition, ROR2 also promoted ERK phosphorylation, EMT, invasion, and necrosis in xenotransplanted mice. ROR2 also associates with EMT in tumor samples from melanoma patients where analysis of large cohorts revealed that increased ROR2 levels are linked to EMT signatures. This important role of ROR2 translates into melanoma patient' s prognosis since elevated ROR2 levels reduced overall survival and distant metastasis-free survival of patients with lymph node metastasis. In sum, these results demonstrate that ROR2 contributes to melanoma progression by inducing EMT and necrosis and can be an attractive therapeutic target for melanoma.

Identifying the Transcriptional Drivers of Metastasis Embedded within Localized Melanoma

In melanoma, predicting which tumors will ultimately metastasize guides treatment decisions. Transcriptional signatures of primary tumors have been utilized to predict metastasis, but which among these are driver or passenger events remains unclear. We used data from the adjuvant AVAST-M trial to identify a predictive gene signature in localized tumors that ultimately metastasized. Using a zebrafish model of primary melanoma, we interrogated the top genes from the AVAST-M signature in vivo. This identified GRAMD1B, a cholesterol transfer protein, as a bona fide metastasis suppressor, with a majority of knockout animals rapidly developing metastasis. Mechanistically, excess free cholesterol or its metabolite 27-hydroxycholesterol promotes invasiveness via activation of an AP-1 program, which is associated with increased metastasis in humans. Our data demonstrate that the transcriptional seeds of metastasis are embedded within localized tumors, suggesting that early targeting of these programs can be used to prevent metastatic relapse.

SIGNIFICANCE

We analyzed human melanoma transcriptomics data to identify a gene signature predictive of metastasis. To rapidly test clinical signatures, we built a genetic metastasis platform in adult zebrafish and identified GRAMD1B as a suppressor of melanoma metastasis. GRAMD1B-associated cholesterol overload activates an AP-1 program to promote melanoma invasion. This article is highlighted in the In This Issue feature, p. 1.

Defining novel causal SNPs and linked phenotypes at melanoma-associated loci

A number of genomic regions have been associated with melanoma risk through genome-wide association studies; however, the causal variants underlying the majority of these associations remain unknown. Here, we sequenced either the full locus or the functional regions including exons of 19 melanoma-associated loci in 1959 British melanoma cases and 737 controls. Variant filtering followed by Fisher's exact test analyses identified 66 variants associated with melanoma risk. Sequential conditional logistic regression identified the distinct haplotypes on which variants reside, and massively parallel reporter assays provided biological insights into how these variants influence gene function. We performed further analyses to link variants to melanoma risk phenotypes and assessed their association with melanoma-specific survival. Our analyses replicate previously known associations in the melanocortin 1 receptor (MC1R) and tyrosinase (TYR) loci, while identifying novel potentially causal variants at the MTAP/CDKN2A and CASP8 loci. These results improve our understanding of the architecture of melanoma risk and outcome.

Analysis of Melanoma Gene Expression Signatures at the Single-Cell Level Uncovers 45-Gene Signature Related to Prognosis

Since the current melanoma clinicopathological staging system remains restricted to predicting survival outcomes, establishing precise prognostic targets is needed. Here, we used gene expression signature (GES) classification and Cox regression analyses to biologically characterize melanoma cells at the single-cell level and construct a prognosis-related gene signature for melanoma. By analyzing publicly available scRNA-seq data, we identified six distinct GESs (named: “Anti-apoptosis”, “Immune cell interactions”, “Melanogenesis”, “Ribosomal biogenesis”, “Extracellular structure organization”, and “Epithelial-Mesenchymal Transition (EMT)”). We verified these GESs in the bulk RNA-seq data of patients with skin cutaneous melanoma (SKCM) from The Cancer Genome Atlas (TCGA). Four GESs (“Immune cell interactions”, “Melanogenesis”, “Ribosomal biogenesis”, and “Extracellular structure organization”) were significantly correlated with prognosis (p = 1.08 × 10−5, p = 0.042, p = 0.001, and p = 0.031, respectively). We identified a prognostic signature of melanoma composed of 45 genes (MPS_45). MPS_45 was validated in TCGA-SKCM (HR = 1.82, p = 9.08 × 10−6) and three other melanoma datasets (GSE65904: HR = 1.73, p = 0.006; GSE19234: HR = 3.83, p = 0.002; and GSE53118: HR = 1.85, p = 0.037). MPS_45 was independently associated with survival (p = 0.002) and was proved to have a high potential for predicting prognosis in melanoma patients.

Using a Clinicopathologic and Gene Expression (CP-GEP) Model to Identify Stage I-II Melanoma Patients at Risk of Disease Relapse

Background: The current standard of care for patients without sentinel node (SN) metastasis (i.e., stage I−II melanoma) is watchful waiting, while >40% of patients with stage IB−IIC will eventually present with disease recurrence or die as a result of melanoma. With the prospect of adjuvant therapeutic options for patients with a negative SN, we assessed the performance of a clinicopathologic and gene expression (CP-GEP) model, a model originally developed to predict SN metastasis, to identify patients with stage I−II melanoma at risk of disease relapse. Methods: This study included patients with cutaneous melanoma ≥18 years of age with a negative SN between October 2006 and December 2017 at the Sahlgrenska University Hospital (Sweden) and Erasmus MC Cancer Institute (The Netherlands). According to the CP-GEP model, which can be applied to the primary melanoma tissue, the patients were stratified into high or low risk of recurrence. The primary aim was to assess the 5-year recurrence-free survival (RFS) of low- and high-risk CP-GEP. A secondary aim was to compare the CP-GEP model with the EORTC nomogram, a model based on clinicopathological variables only. Results: In total, 535 patients (stage I−II) were included. CP-GEP stratification among these patients resulted in a 5-year RFS of 92.9% (95% confidence interval (CI): 86.4−96.4) in CP-GEP low-risk patients (n = 122) versus 80.7% (95%CI: 76.3−84.3) in CP-GEP high-risk patients (n = 413; hazard ratio 2.93 (95%CI: 1.41−6.09), p < 0.004). According to the EORTC nomogram, 25% of the patients were classified as having a ‘low risk’ of recurrence (96.8% 5-year RFS (95%CI 91.6−98.8), n = 130), 49% as ‘intermediate risk’ (88.4% 5-year RFS (95%CI 83.6−91.8), n = 261), and 26% as ‘high risk’ (61.1% 5-year RFS (95%CI 51.9−69.1), n = 137). Conclusion: In these two independent European cohorts, the CP-GEP model was able to stratify patients with stage I−II melanoma into two groups differentiated by RFS.

Genes regulated by DNA methylation are involved in distinct phenotypes during melanoma progression and are prognostic factors for patients

In addition to mutations, epigenetic alterations are important contributors to malignant transformation and tumor progression. The aim of this work was to identify epigenetic events in which promoter or gene body DNA methylation induces gene expression changes that drive melanocyte malignant transformation and metastasis. We previously developed a linear mouse model of melanoma progression consisting of spontaneously immortalized melanocytes, premalignant melanocytes, a nonmetastatic tumorigenic, and a metastatic cell line. Here, through the integrative analysis of methylome and transcriptome data, we identified the relationship between promoter and/or gene body DNA methylation alterations and gene expression in early, intermediate, and late stages of melanoma progression. We identified adenylate cyclase type 3 (Adcy3) and inositol polyphosphate 4-phosphatase type II (Inpp4b), which affect tumor growth and metastatic potential, respectively. Importantly, the gene expression and DNA methylation profiles found in this murine model of melanoma progression were correlated with available clinical data from large population-based primary melanoma cohorts, revealing potential prognostic markers.

Comprehensive analysis of ferroptosis-related genes and prognosis of cutaneous melanoma

BACKGROUND

Cutaneous Melanoma (CM) is a malignant disease with increasing incidence and high mortality. Ferroptosis is a new kind of cell death and related to tumor blood and lymphatic metastasis. This study aims at using bioinformatics technology to construct a prognostic signature and identify ferroptosis-related biomarkers to improve the prognosis and treatment of cutaneous melanoma.

METHODS

We used bioinformatics tools to analyze RNA sequencing expression data with clinical information from multiple databases, utilized varieties of statistical methods to construct a ferroptosis-related prognostic signature of cutaneous melanoma and screened out specific genes with independent prognostic ability.

RESULTS

We obtained 22 ferroptosis-related (P < 0.05) prognostic DEGs in the uniCox regression analysis, among which 10 high-expressed genes (ATG5, CHAC1, FANCD2, FBXL5, HMOX2, HSPB1, NQO1, PEBP1, PRNP, SLC3A2) were screened out by LASSO regression analysis to establish a predictive model. Meanwhile, the ferroptosis-related signature and the nomogram we drew performed an excellent performance based on Kaplan-Meier (K-M), Receiver operating characteristic (ROC) and calibration curves. Univariate and multivariable cox analyses displayed that our model was greater than other prognostic features. GO and KEGG analyses revealed that 10-biomarker signature was mainly related to epidermis differentiation and immunity. ssGSEA analysis indicated that the immune status between the two risk groups was highly different. Besides, we found that two genes (CP, ZEB1) had independent prognostic ability and can be applied for drug research. Both genes were highly related to immunity. GSEA illustrated that ZEB1 may be involved in cellular functions such as proliferation, apoptosis, and migration, while CP was closely connected to immune cell related functions.

CONCLUSION

The present study suggested a 10-biomarker signature can be clinically used to predict the prognosis of cutaneous melanoma, which was better than conventional factors. CP and ZEB1 were independent prognostic genes and can be applied to guide treatment. In addition, ZEB1 mutation was highly related to overall survival in cutaneous melanoma, while CP may be associated with tumor progression. Our study comprehensively analyzed the relationship between iron metabolism, ferroptosis-related genes, and the prognosis of cutaneous melanoma, provided new insight for molecular mechanisms and treatment of ferroptosis and cutaneous melanoma.

Machine learning directed sentinel lymph node biopsy in cutaneous head and neck melanoma

BACKGROUND

The specificity of sentinel lymph node biopsy (SLNB) for detecting lymph node metastasis in head and neck melanoma (HNM) is low under current National Comprehensive Cancer Network (NCCN) treatment guidelines.

METHODS

Multiple machine learning (ML) algorithms were developed to identify HNM patients at very low risk of occult nodal metastasis using National Cancer Database (NCDB) data from 8466 clinically node negative HNM patients who underwent SLNB. SLNB performance under NCCN guidelines and ML algorithm recommendations was compared on independent test data from the NCDB (n = 2117) and an academic medical center (n = 96).

RESULTS

The top-performing ML algorithm (AUC = 0.734) recommendations obtained significantly higher specificity compared to the NCCN guidelines in both internal (25.8% vs. 11.3%, p < 0.001) and external test populations (30.1% vs. 7.1%, p < 0.001), while achieving sensitivity >97%.

CONCLUSION

Machine learning can identify clinically node negative HNM patients at very low risk of nodal metastasis, who may not benefit from SLNB.

Revisiting miRNA Association with Melanoma Recurrence and Metastasis from a Machine Learning Point of View

The diagnostic and prognostic value of miRNAs in cutaneous melanoma (CM) has been broadly studied and supported by advanced bioinformatics tools. From early studies using miRNA arrays with several limitations, to the recent NGS-derived miRNA expression profiles, an accurate diagnostic panel of a comprehensive pre-specified set of miRNAs that could aid timely identification of specific cancer stages is still elusive, mainly because of the heterogeneity of the approaches and the samples. Herein, we summarize the existing studies that report several miRNAs as important diagnostic and prognostic biomarkers in CM. Using publicly available NGS data, we analyzed the correlation of specific miRNA expression profiles with the expression signatures of known gene targets. Combining network analytics with machine learning, we developed specific non-linear classification models that could successfully predict CM recurrence and metastasis, based on two newly identified miRNA signatures. Subsequent unbiased analyses and independent test sets (i.e., a dataset not used for training, as a validation cohort) using our prediction models resulted in 73.85% and 82.09% accuracy in predicting CM recurrence and metastasis, respectively. Overall, our approach combines detailed analysis of miRNA profiles with heuristic optimization and machine learning, which facilitates dimensionality reduction and optimization of the prediction models. Our approach provides an improved prediction strategy that could serve as an auxiliary tool towards precision treatment.

Unsupervised Phenotype-Based Clustering of Clinicopathologic Features in Cutaneous Melanoma

Pathogenic phenotypes in cutaneous melanoma have been vastly cataloged, although these classifications lack concordance and are confined to either morphological or molecular contexts. In this study, we perform unsupervised k-medoids clustering as a machine learning technique of 2,978 primary cutaneous melanomas at Mass General Brigham and apply this information to elucidate computer-defined subsets within the clinicopathologic domain. We identified five optimally separated clusters of melanoma that occupied two distinct clinicopathologic subspaces: a lower-grade partition associated with common or dysplastic nevi (i.e., nevus-associated melanomas) and a higher-grade partition lacking precursor lesions (i.e., de novo melanomas). Our model found de novo melanomas to be more mitogenic, more ulcerative, and thicker than nevus-associated melanomas, in addition to harboring previously unreported differences in radial and vertical growth phase status. The utilization of mixed clinicopathologic variables, reflective of actual clinical data contained in surgical pathology reports, has the potential to increase the biological relevance of existing melanoma classification schemes and facilitate the discovery of new genomic subtypes.

ROR2 has a protective role in melanoma by inhibiting Akt activity, cell-cycle progression, and proliferation

BACKGROUND

Receptor tyrosine kinase-like orphan receptor 2 (ROR2) is a Wnt5a receptor aberrantly expressed in cancer that was shown to either suppress or promote carcinogenesis in different tumor types. Our goal was to study the role of ROR2 in melanoma.

METHODS

Gain and loss-of-function strategies were applied to study the biological function of ROR2 in melanoma. Proliferation assays, flow cytometry, and western blotting were used to evaluate cell proliferation and changes in expression levels of cell-cycle and proliferation markers. The role of ROR2 in tumor growth was assessed in xenotransplantation experiments followed by immunohistochemistry analysis of the tumors. The role of ROR2 in melanoma patients was assessed by analysis of clinical data from the Leeds Melanoma Cohort.

RESULTS

Unlike previous findings describing ROR2 as an oncogene in melanoma, we describe that ROR2 prevents tumor growth by inhibiting cell-cycle progression and the proliferation of melanoma cells. The effect of ROR2 is mediated by inhibition of Akt phosphorylation and activity which, in turn, regulates the expression, phosphorylation, and localization of major cell-cycle regulators including cyclins (A, B, D, and E), CDK1, CDK4, RB, p21, and p27. Xenotransplantation experiments demonstrated that ROR2 also reduces proliferation in vivo, resulting in inhibition of tumor growth. In agreement with these findings, a higher ROR2 level favors thin and non-ulcerated primary melanomas with reduced mitotic rate and better prognosis.

CONCLUSION

We conclude that the expression of ROR2 slows down the growth of primary tumors and contributes to prolonging melanoma survival. Our results demonstrate that ROR2 has a far more complex role than originally described.

Road to Metastasis: The TWEAK Pathway as a Discriminant between Metastasizing and Non-Metastasizing Thick Melanomas

Cutaneous melanoma (CM) is the most aggressive form of skin cancer, and its worldwide incidence is rapidly increasing. Early stages can be successfully treated by surgery, but once metastasis has occurred, the prognosis is poor. However, some 5-10% of thick (≥2 mm) melanomas do not follow this scenario and run an unpredictable course. Little is known about the factors that contribute to metastasis in some patient with thick melanomas and the lack thereof in thick melanoma patients who never develop metastatic disease. We were therefore interested to study differential gene expression and pathway analysis and compare non-metastatic and metastatic thick melanomas. We found that the TNF-like weak inducer of apoptosis (TWEAK) pathway was upregulated in thick non-metastasizing melanomas. MAP3K14 (NIK1), BIRC2 (cIAP1), RIPK1, CASP7, CASP8, and TNF play an important role in inhibiting proliferation and invasion of tumor cells via the activation of the non-canonical NF-κB signaling pathway. In particular, this pathway sensitizes melanoma cells to TNF-alpha and activates the apoptosis module of the TWEAK pathway in thick non-metastasizing melanomas. Hence, our study suggests a potential role of the TWEAK pathway in inhibiting thick melanoma from metastasis. Exploitation of these genes and the pathway they control may open future therapeutic avenues.

Bioinformatics-based study to identify immune infiltration and inflammatory-related hub genes as biomarkers for the treatment of rheumatoid arthritis

Rheumatoid arthritis (RA) is a systemic autoimmune disease whose principal pathological change is aggressive chronic synovial inflammation; however, the specific etiology and pathogenesis have not been fully elucidated. We downloaded the synovial tissue gene expression profiles of four human knees from the Gene Expression Omnibus database, analyzed the differentially expressed genes in the normal and RA groups, and assessed their enrichment in functions and pathways using bioinformatics methods and the STRING online database to establish protein-protein interaction networks. Cytoscape software was used to obtain 10 hub genes; receiver operating characteristic (ROC) curves were calculated for each hub gene and differential expression analysis of the two groups of hub genes. The CIBERSORT algorithm was used to impute immune infiltration. We identified the signaling pathways that play important roles in RA and 10 hub genes: Ccr1, Ccr2, Ccr5, Ccr7, Cxcl5, Cxcl6, Cxcl13, Ccl13, Adcy2, and Pnoc. The diagnostic value of these 10 hub genes for RA was confirmed using ROC curves and expression analysis. Adcy2, Cxcl13, and Ccr5 are strongly associated with RA development. The study also revealed that the differential infiltration profile of different inflammatory immune cells in the synovial tissue of RA is an extremely critical factor in RA progression. This study may contribute to the understanding of signaling pathways and biological processes associated with RA and the role of inflammatory immune infiltration in the pathogenesis of RA. In addition, this study shows that Adcy2, Cxcl13, and Ccr5 have the potential to be biomarkers for RA treatment.

Loss of Ambra1 promotes melanoma growth and invasion

Melanoma is the deadliest skin cancer. Despite improvements in the understanding of the molecular mechanisms underlying melanoma biology and in defining new curative strategies, the therapeutic needs for this disease have not yet been fulfilled. Herein, we provide evidence that the Activating Molecule in Beclin-1-Regulated Autophagy (Ambra1) contributes to melanoma development. Indeed, we show that Ambra1 deficiency confers accelerated tumor growth and decreased overall survival in Braf/Pten-mutated mouse models of melanoma. Also, we demonstrate that Ambra1 deletion promotes melanoma aggressiveness and metastasis by increasing cell motility/invasion and activating an EMT-like process. Moreover, we show that Ambra1 deficiency in melanoma impacts extracellular matrix remodeling and induces hyperactivation of the focal adhesion kinase 1 (FAK1) signaling, whose inhibition is able to reduce cell invasion and melanoma growth. Overall, our findings identify a function for AMBRA1 as tumor suppressor in melanoma, proposing FAK1 inhibition as a therapeutic strategy for AMBRA1 low-expressing melanoma.

MX2 mediates establishment of interferon response profile, regulates XAF1, and can sensitize melanoma cells to targeted therapy

MX2 is an interferon inducible gene that is mostly known for its antiviral activity. We have previously demonstrated that MX2 is also associated with the tumorigenesis process in melanoma. However, it remains unknown which molecular mechanisms are regulated by MX2 in response to interferon signaling in this disease. Here, we report that MX2 is necessary for the establishment of an interferon‐induced transcriptional profile partially through regulation of STAT1 phosphorylation and other interferon‐related downstream factors, including proapoptotic tumor suppressor XAF1. MX2 and XAF1 expression tightly correlate in both cultured melanoma cell lines and in patient‐derived primary and metastatic tumors, where they also are significantly related with survival. MX2 mediates IFN growth‐inhibitory signals in both XAF1 dependent and independent ways and in a cell type and context‐dependent manner. Higher MX2 expression renders melanoma cells more sensitive to targeted therapy drugs such as vemurafenib and trametinib; however, this effect is XAF1 independent. In summary, we uncovered a new mechanism in the complex regulation of interferon signaling in melanoma that can influence both survival and response to therapy.

Tumour gene expression signature in primary melanoma predicts long-term outcomes

Adjuvant systemic therapies are now routinely used following resection of stage III melanoma, however accurate prognostic information is needed to better stratify patients. We use differential expression analyses of primary tumours from 204 RNA-sequenced melanomas within a large adjuvant trial, identifying a 121 metastasis-associated gene signature. This signature strongly associated with progression-free (HR = 1.63, p = 5.24 × 10-5) and overall survival (HR = 1.61, p = 1.67 × 10-4), was validated in 175 regional lymph nodes metastasis as well as two externally ascertained datasets. The machine learning classification models trained using the signature genes performed significantly better in predicting metastases than models trained with clinical covariates (pAUROC = 7.03 × 10-4), or published prognostic signatures (pAUROC < 0.05). The signature score negatively correlated with measures of immune cell infiltration (ρ = -0.75, p < 2.2 × 10-16), with a higher score representing reduced lymphocyte infiltration and a higher 5-year risk of death in stage II melanoma. Our expression signature identifies melanoma patients at higher risk of metastases and warrants further evaluation in adjuvant clinical trials.

Nanocarrier-Based Drug Delivery for Melanoma Therapeutics

Melanoma, as a tumor cell derived from melanocyte transformation, has the characteristics of malignant proliferation, high metastasis, rapid recurrence, and a low survival rate. Traditional therapy has many shortcomings, including drug side effects and poor patient compliance, and so on. Therefore, the development of an effective treatment is necessary. Currently, nanotechnologies are a promising oncology treatment strategy because of their ability to effectively deliver drugs and other bioactive molecules to targeted tissues with low toxicity, thereby improving the clinical efficacy of cancer therapy. In this review, the application of nanotechnology in the treatment of melanoma is reviewed and discussed. First, the pathogenesis and molecular targets of melanoma are elucidated, and the current clinical treatment strategies and deficiencies of melanoma are then introduced. Following this, we discuss the main features of developing efficient nanosystems and introduce the latest reports in the literature on nanoparticles for the treatment of melanoma. Subsequently, we review and discuss the application of nanoparticles in chemotherapeutic agents, immunotherapy, mRNA vaccines, and photothermal therapy, as well as the potential of nanotechnology in the early diagnosis of melanoma.

Integrated TCGA and GEO analysis showed that SMAD7 is an independent prognostic factor for lung adenocarcinoma

The lack of effective markers leads to missed optimal treatment times, resulting in poorer prognosis in most cancers. Drosophila mothers against decapentaplegic protein (SMAD) family members are important cytokines in the transforming growth factor-beta family. They jointly regulate the processes of cell growth, differentiation, and apoptosis. However, the expression of SMAD family genes in pan-cancers and their impact on prognosis have not been elucidated. Perl software and R software were used to perform expression analysis and survival curve analysis on the data collected by TCGA, GTEx, and GEO, and the potential regulatory pathways were determined through gene ontology enrichment and kyoto encyclopedia of genes and genomes enrichment analysis. It was found that SMAD7 and SMAD9 expression decreased in lung adenocarcinoma (LUAD), and their expression was positively correlated with survival time. Additionally, SMAD7 could be used as an independent prognostic factor for LUAD. In general, SMAD7 and SMAD9 can be used as prognostic markers of LUAD. Further, SMAD7 is expected to become a therapeutic target for LUAD.

Robust gene expression programs underlie recurrent cell states and phenotype switching in melanoma

Melanoma cells can switch between a melanocytic and a mesenchymal-like state. Scattered evidence indicates that additional intermediate state(s) may exist. Here, to search for such states and decipher their underlying gene regulatory network (GRN), we studied 10 melanoma cultures using single-cell RNA sequencing (RNA-seq) as well as 26 additional cultures using bulk RNA-seq. Although each culture exhibited a unique transcriptome, we identified shared GRNs that underlie the extreme melanocytic and mesenchymal states and the intermediate state. This intermediate state is corroborated by a distinct chromatin landscape and is governed by the transcription factors SOX6, NFATC2, EGR3, ELF1 and ETV4. Single-cell migration assays confirmed the intermediate migratory phenotype of this state. Using time-series sampling of single cells after knockdown of SOX10, we unravelled the sequential and recurrent arrangement of GRNs during phenotype switching. Taken together, these analyses indicate that an intermediate state exists and is driven by a distinct and stable 'mixed' GRN rather than being a symbiotic heterogeneous mix of cells.

Study of the Female Sex Survival Advantage in Melanoma-A Focus on X-Linked Epigenetic Regulators and Immune Responses in Two Cohorts

BACKGROUND

Survival from melanoma is strongly related to patient sex, with females having a survival rate almost twice that of males. Many explanations have been proposed but have not withstood critical scrutiny. Prior analysis of different cancers with a sex bias has identified six X-linked genes that escape X chromosome inactivation in females and are, therefore, potentially involved in sex differences in survival. Four of the genes are well-known epigenetic regulators that are known to influence the expression of hundreds of other genes and signaling pathways in cancer.

METHODS

Survival and interaction analysis were performed on the skin cutaneous melanoma (SKCM) cohort in The Cancer Genome Atlas (TCGA), comparing high vs. low expression of KDM6A, ATRX, KDM5C, and DDX3X. The Leeds melanoma cohort (LMC) on 678 patients with primary melanoma was used as a validation cohort.

RESULTS

Analysis of TCGA data revealed that two of these genes-KDM6A and ATRX-were associated with improved survival from melanoma. Tumoral KDM6A was expressed at higher levels in females and was associated with inferred lymphoid infiltration into melanoma. Gene set analysis of high KDM6A showed strong associations with immune responses and downregulation of genes associated with Myc and other oncogenic pathways. The LMC analysis confirmed the prognostic significance of KDM6A and its interaction with EZH2 but also revealed the expression of KDM5C and DDX3X to be prognostically significant. The analysis also confirmed a partial correlation of KDM6A with immune tumor infiltrates.

CONCLUSION

When considered together, the results from these two series are consistent with the involvement of X-linked epigenetic regulators in the improved survival of females from melanoma. The identification of gene signatures associated with their expression presents insights into the development of new treatment initiatives but provides a basis for exploration in future studies.

Systematic analysis of the ABC transporter family in hepatocellular carcinoma reveals the importance of ABCB6 in regulating ferroptosis

AIMS

ATP-binding cassette (ABC) transporters constitute one of the largest families of membrane proteins in most organisms; however, their functions in hepatocellular carcinoma (HCC) remain unclear.

MAIN METHODS

A set of bioinformatic tools was integrated to analyze the expression of 49 members of the ABC transporter family. The function of members which had prognostic values in HCC was explored by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis.

KEY FINDINGS

ABCA8 and ABCA9 were significantly down-regulated in HCC. Prognostic analysis indicated that HCC patients with low expression of ABCA8 and ABCA9 had significantly shorter survival time. On the contrary, ABCB6 was over-expressed in the disease and high expression of ABCB6 was associated with worse prognosis. Co-expression analysis, and subsequently GO and KEGG analysis indicated that ABCA8 and ABCA9 might participate in the catabolic processes of multiple metabolites, while ABCB6 might regulate ferroptosis.

SIGNIFICANCE

This study reveals a previously unrecognized function of ABCB6 in HCC, by regulating ferroptosis. Since ABCB6 is over-expressed in HCC and ferroptosis involves in cancer development, ABCB6 might be a promising therapeutic target in the disease.

Breast Heterogeneity: Obstacles to Developing Universal Biomarkers of Breast Cancer Initiation and Progression

BACKGROUND

Predicting outcomes and response to therapy through biomarkers is a major challenge in cancer research. In previous studies, we suggested that inappropriate "normal" tissue samples used for comparison with tumors, inter-individual heterogeneity in gene expression, and genetic ancestry all influence biomarker expression in tumors. The aim of this study was to investigate these factors in breast cancer using breast tissues from healthy women and normal tissue adjacent to tumor (NAT) with matrix metalloproteinase 7 (MMP7) as a candidate biomarker.

STUDY DESIGN

RNA sequencing was performed on primary luminal progenitor cells from healthy breast, NATs, and tumors to identify transcriptomes enriched in NATs and breast cancer. Expression of select genes was validated via quantitative reverse transcription polymerase chain reaction of RNA and via immunohistochemistry of a tissue microarray of normal, NAT, and tumor samples of different genetic ancestry.

RESULTS

Twenty-six genes were significantly overexpressed in NATs and tumors compared with healthy controls at messenger RNA level and formed a para-inflammatory network. MMP7 had the greatest expression in tumor cells, with upregulation confirmed by quantitative reverse transcription polymerase chain reaction. Tumor-enriched but not NAT-enriched expression of MMP7 compared with healthy controls was reproduced at protein levels. When stratified by genetic ancestry, tumor-specific increase of MMP7 reached statistical significance in women of European ancestry.

CONCLUSIONS

Transcriptome differences across healthy, NAT, and tumor tissue in breast cancer demonstrate an active para-inflammatory network in NATs and indicate unsuitability of NATs as "normal controls" in biomarker discovery. The discordance between transcriptomic and proteomic MMP7 expression in NATs and the influence of genetic ancestry on its protein expression highlight the complexity in developing universally acceptable biomarkers of breast cancer and the importance of genetic ancestry in biomarker development.