Biomarkers for Diagnosis, Prognosis and Response to Immunotherapy in Melanoma

A neutrophil extracellular trap-related risk score predicts prognosis and characterizes the tumor microenvironment in multiple myeloma

Multiple myeloma (MM) is a distinguished hematologic malignancy, with existing studies elucidating its interaction with neutrophil extracellular traps (NETs), which may potentially facilitate tumor growth. However, systematic investigations into the role of NETs in MM remain limited. Utilizing the single-cell dataset GSE223060, we discerned active NET cell subgroups, namely neutrophils, monocytes, and macrophages. A transcriptional trajectory was subsequently constructed to comprehend the progression of MM. Following this, an analysis of cellular communication in MM was conducted with a particular emphasis on neutrophils, revealing an augmentation in interactions albeit with diminished strength, alongside abnormal communication links between neutrophils and NK cells within MM samples. Through the intersection of differentially expressed genes (DEGs) between NET active/inactive cells and MM versus healthy samples, a total of 316 genes were identified. This led to the development of a 13-gene risk model for prognostic prediction based on overall survival, utilizing transcriptomics dataset GSE136337. The high-risk group manifested altered immune infiltration and heightened sensitivity to chemotherapy. A constructed nomogram for predicting survival probabilities demonstrated encouraging AUCs for 1, 3, and 5-year survival predictions. Collectively, our findings unveil a novel NET-related prognostic signature for MM, thereby providing a potential avenue for therapeutic exploration.

A Narrative Review of Current Knowledge on Cutaneous Melanoma

Cutaneous melanoma is a public health problem. Efforts to reduce its incidence have failed, as it continues to increase. In recent years, many risk factors have been identified. Numerous diagnostic systems exist that greatly assist in early clinical diagnosis. The histopathological aspect illustrates the grim nature of these cancers. Currently, pathogenic pathways and the tumor microclimate are key to the development of therapeutic methods. Revolutionary therapies like targeted therapy and immune checkpoint inhibitors are starting to replace traditional therapeutic methods. Targeted therapy aims at a specific molecule in the pathogenic chain to block it, stopping cell growth and dissemination. The main function of immune checkpoint inhibitors is to boost cellular immunity in order to combat cancer cells. Unfortunately, these therapies have different rates of effectiveness and side effects, and cannot be applied to all patients. These shortcomings are the basis of increased incidence and mortality rates. This study covers all stages of the evolutionary sequence of melanoma. With all these data in front of us, we see the need for new research efforts directed at therapies that will bring greater benefits in terms of patient survival and prognosis, with fewer adverse effects.

Construction and validation of a novel prognostic signature for cutaneous melanoma based on ferroptosis-related genes

Ferroptosis, a recently uncovered iron-dependent, non-apoptotic cell death process, has been increasingly linked to cancer development. In this study, our objective was to develop a prognostic model centered on ferroptosis-related genes (FRGs) and assess its efficacy as an overall survival (OS) prediction biomarker. We conducted a systematic analysis of cutaneous melanoma (CM) and devised a novel ferroptosis-related prognostic signature (FRGSig) using the TCGA database. An independent dataset from GSE65904 was employed to corroborate the validity of the FRGSig. Both univariate and multivariate Cox proportional hazard regression analyses were utilized to construct a FRGSig composed of five FRGs. mRNA expression and immunohistochemistry (IHC) analysis demonstrated that the expression of FRGSig genes varied between tumor and normal tissues. According to Kaplan-Meier analysis, patients with elevated FRGsig scores faced a worse prognosis. The predictive accuracy of FRGSig was evaluated using the time-dependent receiver operating characteristic curve (ROC), with the area under the curve (AUC) values for 1, 3, and 5 OS at 0.682, 0.711, 0.735 in the TCGA cohort, and 0.662, 0.695, 0.712 in the validation dataset, respectively. Univariate and multivariate Cox regression analyses demonstrated that FRGSig served as an independent prognostic factor. Further analysis revealed a significant relationship between FRGSig and Tumor Mutational Burden (TMB) as well as immune infiltration levels. Gene set enrichment analysis (GSEA) disclosed functional disparities between high- and low-risk groups, suggesting that immune checkpoint-related pathways could be instrumental in the improved prognosis of the low-risk group. Taken together, the FRGSig has potential guidance for prognosis prediction and clinical treatment of CM.

Identification and validation of a muscle failure index to predict prognosis and immunotherapy in lung adenocarcinoma through integrated analysis of bulk and single-cell RNA sequencing data

Background

It was previously reported that the production of exerkines is positively associated with the beneficial effects of exercise in lung adenocarcinoma (LUAD) patients. This study proposes a novel scoring system based on muscle failure-related genes, to assist in clinical decision making.

Methods

A comprehensive analysis of bulk and single cell RNA sequencing (scRNA-seq) of early, advanced and brain metastatic LUAD tissues and normal lung tissues was performed to identify muscle failure-related genes in LUAD and to determine the distribution of muscle failure-related genes in different cell populations. A novel scoring system, named MFI (Muscle failure index), was developed and validated. The differences in biological functions, immune infiltration, genomic alterations, and clinical significance of different subtypes were also investigated.

Results

First, we conducted single cell analysis on the dataset GSE131907 and identified eight cell subpopulations. We found that four muscle failure-related genes (BDNF, FNDC5, IL15, MSTN) were significantly increased in tumor cells. In addition, IL15 was widely distributed in the immune cell population. And we have validated it in our own clinical cohort. Then we created the MFI model based on 10 muscle failure-related genes using the LASSO algorithm, and MFI remained an independent prognostic factor of OS in both the training and validation cohorts. Moreover, we generated MFI in the single-cell dataset, in which cells with high MFI received and sent more signals compared to those with low MFI. Biological function analysis of both subtypes revealed stronger anti-tumor immune activity in the low MFI group, while tumor cells with high MFI had stronger metabolic and proliferative activity. Finally, we systematically assessed the immune cell activity and immunotherapy responses in LUAD patients, finding that the low MFI group was more sensitive to immunotherapy.

Conclusion

Overall, our study can improve the understanding of the role of muscle failure-related genes in tumorigenesis and we constructed a reliable MFI model for predicting prognosis and guiding future clinical decision making.

A general class of promotion time cure rate models with a new biological interpretation

Over the last decades, the challenges in survival models have been changing considerably and full probabilistic modeling is crucial in many medical applications. Motivated from a new biological interpretation of cancer metastasis, we introduce a general method for obtaining more flexible cure rate models. The proposal model extended the promotion time cure rate model. Furthermore, it includes several well-known models as special cases and defines many new special models. We derive several properties of the hazard function for the proposed model and establish mathematical relationships with the promotion time cure rate model. We consider a frequentist approach to perform inferences, and the maximum likelihood method is employed to estimate the model parameters. Simulation studies are conducted to evaluate its performance with a discussion of the obtained results. A real dataset from population-based study of incident cases of melanoma diagnosed in the state of São Paulo, Brazil, is discussed in detail.

Identification and Validation of Ferroptosis-Related DNA Methylation Signature for Predicting the Prognosis and Guiding the Treatment in Cutaneous Melanoma

Cutaneous melanoma (CM) is one of the most aggressive skin tumors with a poor prognosis. Ferroptosis is a newly discovered form of regulated cell death that is closely associated with cancer development and immunotherapy. The aim of this study was to establish and validate a ferroptosis-related gene (FRG) DNA methylation signature to predict the prognosis of CM patients using data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. A reliable four-FRG DNA methylation prognostic signature was constructed via Cox regression analysis based on TCGA database. Kaplan-Meier analysis showed that patients in the high-risk group tended to have a shorter overall survival (OS) than the low-risk group in both training TCGA and validation GEO cohorts. Time-dependent receiver operating characteristic (ROC) analysis showed the areas under the curve (AUC) at 1, 3, and 5 years were 0.738, 0.730, and 0.770 in TCGA cohort and 0.773, 0.775, and 0.905 in the validation cohort, respectively. Univariate and multivariate Cox regression analyses indicated that the signature was an independent prognostic indicator of OS in patients with CM. Immunogenomic profiling showed the low-risk group of patients had a higher immunophenoscore, and most immune checkpoints were negatively associated with the risk signature. Functional enrichment analysis revealed that immune response and immune-related pathways were enriched in the low-risk group. In conclusion, we established and validated a four-FRG DNA methylation signature that independently predicts prognosis in CM patients. This signature was strongly correlated with the immune landscape, and may serve as a biomarker to guide clinicians in making more precise and personalized treatment decisions for CM patients.

Identification of a Tumor Cell Associated Type I IFN Resistance Gene Expression Signature of Human Melanoma, the Components of Which Have a Predictive Potential for Immunotherapy

We developed a human melanoma model using the HT168-M1 cell line to induce IFN-α2 resistance in vitro (HT168-M1res), which was proven to be maintained in vivo in SCID mice. Comparing the mRNA profile of in vitro cultured HT168-M1res cells to its sensitive counterpart, we found 79 differentially expressed genes (DEGs). We found that only a 13-gene core of the DEGs was stable in vitro and only a 4-gene core was stable in vivo. Using an in silico cohort of IFN-treated melanoma tissues, we validated a differentially expressed 9-gene core of the DEGs. Furthermore, using an in silico cohort of immune checkpoint inhibitor (ICI)-treated melanoma tissues, we tested the predictive power of the DEGs for the response rate. Analysis of the top four upregulated and top four downregulated genes of the DEGs identified WFDC1, EFNA3, DDX10, and PTBP1 as predictive genes, and analysis of the "stable" genes of DEGs for predictive potential of ICI response revealed another 13 genes, out of which CDCA4, SOX4, DEK, and HSPA1B were identified as IFN-regulated genes. Interestingly, the IFN treatment associated genes and the ICI-therapy predictive genes overlapped by three genes: WFDC1, BCAN, and MT2A, suggesting a connection between the two biological processes.

Additive Intralesional Interleukin-2 Improves Progression-Free Survival in a Distinct Subgroup of Melanoma Patients with Prior Progression under Immunotherapy

Simple Summary

Despite the immense progress in systemic treatment of advanced unresectable melanoma with immunotherapies, there is still an unmet need for patients showing primary resistance. We show that addition of intratumoral injections of the immune modulator Interleukin-2 can overcome primary resistance in a distinct subset of patients and this effect is associated with an intratumoral increase of certain inflammatory cells supporting the paradigm of turning a “cold” into a “hot” tumor.

Abstract

A considerable amount of melanoma patients show primary resistance to PD-1 and CTLA-4 inhibitors. We have previously reported a beneficial role of intralesional Interleukin-2 (IL-2) in 9 melanoma patients developing new locoregional metastases under immunotherapy. We have now expanded this retrospective cohort to 27 patients. Patients were evaluated for their tumor characteristics, treatment response and progression-free and overall survival (PFS/OS). In 16 patients, tumor biopsies before and under IL-2 treatment were evaluated for immune markers. The median follow-up time was 16 (1–59) months from start of IL-2 treatment. Treatment response of locoregional metastases was seen in 74% of all patients and response of distant organ metastases in 37% of stage IV patients, respectively. A prolonged PFS and OS was significantly associated with absence of active distant metastases (p = 0.008), response of locoregional metastases (p = 0.002), increase of absolute eosinophil count (AEC) (p < 0.001) and an influx of CD8⁺ tumor infiltrating lymphocytes (TILs) (p = 0.003). Additional intralesional treatment with IL-2 in patients with locoregional progression under immunotherapy is a well-tolerated, easily feasible therapeutic option especially in patients lacking active distant metastases. A careful patient selection can lead to an improved PFS and OS.

The Role of the Vitamin D Receptor in the Pathogenesis, Prognosis, and Treatment of Cutaneous Melanoma

Melanoma is the malignant transformation of melanocytes and represents the most lethal form of skin cancer. While early-stage melanoma localized to the skin can be cured with surgical excision, metastatic melanoma often requires a multi-pronged approach and even then can exhibit treatment resistance. Understanding the molecular mechanisms involved in the pathogenesis of melanoma could lead to novel diagnostic, prognostic, and therapeutic strategies to ultimately decrease morbidity and mortality. One emerging candidate that may have value as both a prognostic marker and in a therapeutic context is the vitamin D receptor (VDR). VDR is a nuclear steroid hormone receptor activated by 1,25 dihydroxy-vitamin D3 [calcitriol, 1,25(OH)2D3]. While 1,25 dihydroxy-vitamin D3 is typically thought of in relation to calcium metabolism, it also plays an important role in cell proliferation, differentiation, programmed-cell death as well as photoprotection. This review discusses the role of VDR in the crosstalk between keratinocytes and melanocytes during melanomagenesis and summarizes the clinical data regarding VDR polymorphisms, VDR as a prognostic marker, and potential uses of vitamin D and its analogs as an adjuvant treatment for melanoma.

Harness the functions of gut microbiome in tumorigenesis for cancer treatment

It has been shown that gut microbiota dysbiosis leads to physiological changes and links to a number of diseases, including cancers. Thus, many cancer categories and treatment regimens should be investigated in the context of the microbiome. Owing to the availability of metagenome sequencing and multiomics studies, analyses of species characterization, host genetic changes, and metabolic profile of gut microbiota have become feasible, which has facilitated an exponential knowledge gain about microbiota composition, taxonomic alterations, and host interactions during tumorigenesis. However, the complexity of the gut microbiota, with a plethora of uncharacterized host‐microbe, microbe‐microbe, and environmental interactions, still contributes to the challenge of advancing our knowledge of the microbiota‐cancer interactions. These interactions manifest in signaling relay, metabolism, immunity, tumor development, genetic instability, sensitivity to cancer chemotherapy and immunotherapy. This review summarizes current studies/molecular mechanisms regarding the association between the gut microbiota and the development of cancers, which provides insights into the therapeutic strategies that could be harnessed for cancer diagnosis, treatment, or prevention.