Melanoma immunotherapy: strategies to overcome pharmacological resistance

A spheroid whole mount drug testing pipeline with machine-learning based image analysis identifies cell-type specific differences in drug efficacy on a single-cell level

BACKGROUND

The growth and drug response of tumors are influenced by their stromal composition, both in vivo and 3D-cell culture models. Cell-type inherent features as well as mutual relationships between the different cell types in a tumor might affect drug susceptibility of the tumor as a whole and/or of its cell populations. However, a lack of single-cell procedures with sufficient detail has hampered the automated observation of cell-type-specific effects in three-dimensional stroma-tumor cell co-cultures.

METHODS

Here, we developed a high-content pipeline ranging from the setup of novel tumor-fibroblast spheroid co-cultures over optical tissue clearing, whole mount staining, and 3D confocal microscopy to optimized 3D-image segmentation and a 3D-deep-learning model to automate the analysis of a range of cell-type-specific processes, such as cell proliferation, apoptosis, necrosis, drug susceptibility, nuclear morphology, and cell density.

RESULTS

This demonstrated that co-cultures of KP-4 tumor cells with CCD-1137Sk fibroblasts exhibited a growth advantage compared to tumor cell mono-cultures, resulting in higher cell counts following cytostatic treatments with paclitaxel and doxorubicin. However, cell-type-specific single-cell analysis revealed that this apparent benefit of co-cultures was due to a higher resilience of fibroblasts against the drugs and did not indicate a higher drug resistance of the KP-4 cancer cells during co-culture. Conversely, cancer cells were partially even more susceptible in the presence of fibroblasts than in mono-cultures.

CONCLUSION

In summary, this underlines that a novel cell-type-specific single-cell analysis method can reveal critical insights regarding the mechanism of action of drug substances in three-dimensional cell culture models.

Prediction of immunotherapy responsiveness in melanoma through single-cell sequencing-based characterization of the tumor immune microenvironment

Immune checkpoint inhibitors (ICB) therapy have emerged as effective treatments for melanomas. However, the response of melanoma patients to ICB has been highly heterogenous. Here, by analyzing integrated scRNA-seq datasets from melanoma patients, we revealed significant differences in the TiME composition between ICB-resistant and responsive tissues, with resistant or responsive tissues characterized by an abundance of myeloid cells and CD8+ T cells or CD4+ T cell predominance, respectively. Among CD4+ T cells, CD4+ CXCL13+ Tfh-like cells were associated with an immunosuppressive phenotype linked to immune escape-related genes and negative regulation of T cell activation. We also develop an immunotherapy response prediction model based on the composition of the immune compartment. Our predictive model was validated using CIBERSORTx on bulk RNA-seq datasets from melanoma patients pre- and post-ICB treatment and showed a better performance than other existing models. Our study presents an effective immunotherapy response prediction model with potential for further translation, as well as underscores the critical role of the TiME in influencing the response of melanomas to immunotherapy.

Fibroblast Growth Factor Receptor Inhibitors Decrease Proliferation of Melanoma Cell Lines and Their Activity Is Modulated by Vitamin D

Regardless of the unprecedented progress in malignant melanoma treatment strategies and clinical outcomes of patients during the last twelve years, this skin cancer remains the most lethal one. We have previously documented that vitamin D and its low-calcaemic analogues enhance the anticancer activity of drugs including a classic chemotherapeutic-dacarbazine-and an antiangiogenic VEGFRs inhibitor-cediranib. In this study, we explored the response of A375 and RPMI7951 melanoma lines to CPL304110 (CPL110), a novel selective inhibitor of fibroblast growth factor receptors (FGFRs), and compared its efficacy with that of AZD4547, the first-generation FGFRs selective inhibitor. We also tested whether 1,25(OH)2D3, the active form of vitamin D, modulates the response of the cells to these drugs. CPL304110 efficiently decreased the viability of melanoma cells in both A375 and RPMI7951 cell lines, with the IC50 value below 1 µM. However, the metastatic RPMI7951 melanoma cells were less sensitive to the tested drug than A375 cells, isolated from primary tumour site. Both tested FGFR inhibitors triggered G0/G1 cell cycle arrest in A375 melanoma cells and increased apoptotic/necrotic SubG1 fraction in RPMI7951 melanoma cells. 1,25(OH)2D3 modulated the efficacy of CPL304110, by decreasing the IC50 value by more than 4-fold in A375 cell line, but not in RPMI7951 cells. Further analysis revealed that both inhibitors impact vitamin D signalling to some extent, and this effect is cell line-specific. On the other hand, 1,25(OH)2D3, have an impact on the expression of FGFR receptors and phosphorylation (FGFR-Tyr653/654). Interestingly, 1,25(OH)2D3 and CPL304110 co-treatment resulted in activation of the ERK1/2 pathway in A375 cells. Our results strongly suggested possible crosstalk between vitamin D-activated pathways and activity of FGFR inhibitors, which should be considered in further clinical studies.

Resistance to anti-PD1 therapies in patients with advanced melanoma: systematic literature review and application of the Society for Immunotherapy of Cancer Immunotherapy Resistance Taskforce anti-PD1 resistance definitions

Nearly half of advanced melanoma patients do not achieve a clinical response with anti-programmed cell death 1 protein (PD1) therapy (i.e. primary resistance) or initially achieve a clinical response but eventually progress during or following further treatment (i.e. secondary resistance). A consensus definition for tumor resistance to anti-PD1 monotherapy was published by Society for Immunotherapy of Cancer Immunotherapy Resistance Taskforce (SITC) in 2020. A systematic literature review (SLR) of clinical trials and observational studies was conducted to characterize the proportions of advanced melanoma patients who have progressed on anti-PD1 therapies. The SLR included 55 unique studies and the SITC definition of primary resistance was applied to 37 studies that specified disease progression by best overall response. Median and range of patients with primary resistance in studies that specified first-line and second-line or higher anti-PD1 monotherapy was 35.50% (21.19-39.13%; n = 4 studies) and 41.54% (30.00-56.41%, n = 3 studies); median and range of patients with primary resistance in studies that specified first-line and second-line or higher combination therapy was 30.23% (15.79-33.33%; n = 6 studies), and 70.00% (61.10-73.33%; n = 3 studies). Primary resistance to anti-PD1 monotherapies and when in combination with ipilimumab are higher in patients receiving second-line or higher therapies, in patients with acral, mucosal, and uveal melanoma, and in patients with active brain metastases. The percentage of patients with primary resistance was generally consistent across clinical trials, with variability in resistance noted for observational studies. Limitations include applying the SITC definitions to combination therapies, where consensus definitions are not yet available. Future studies should highly consider utilizing the SITC definitions to harmonize how resistance is classified and facilitate meaningful context for clinical activity.

Identification of fatty acid metabolism-related molecular subtype biomarkers and their correlation with immune checkpoints in cutaneous melanoma

PURPOSE

Fatty acid metabolism (FAM) affects the immune phenotype in a metabolically dynamic tumor microenvironment (TME), but the use of FAM-related genes (FAMGs) to predict the prognosis and immunotherapy response of cutaneous melanoma (CM) patients has not been investigated. In this study, we aimed to construct FAM molecular subtypes and identify key prognostic biomarkers in CM.

METHODS

We used a CM dataset in The Cancer Genome Atlas (TCGA) to construct FAM molecular subtypes. We performed Kaplan-Meier (K-M) analysis, gene set enrichment analysis (GSEA), and TME analysis to assess differences in the prognosis and immune phenotype between subtypes. We used weighted gene co-expression network analysis (WGCNA) to identify key biomarkers that regulate tumor metabolism and immunity between the subtypes. We compared overall survival (OS), progression-free survival (PFS), and disease-specific survival (DSS) between CM patients with high or low biomarker expression. We applied univariable and multivariable Cox analyses to verify the independent prognostic value of the FAM biomarkers. We used GSEA and TME analysis to investigate the immune-related regulation mechanism of the FAM subtype biomarker. We evaluated the immune checkpoint inhibition (ICI) response and chemotherapy sensitivity between CM patients with high or low biomarker expression. We performed real-time fluorescent quantitative PCR (qRT-PCR) and semi-quantitative analysis of the immunohistochemical (IHC) data from the Human Protein Atlas to evaluate the mRNA and protein expression levels of the FAM biomarkers in CM.

RESULTS

We identified 2 FAM molecular subtypes (cluster 1 and cluster 2). K-M analysis showed that cluster 2 had better OS and PFS than cluster 1 did. GSEA showed that, compared with cluster 1, cluster 2 had significantly upregulated immune response pathways. The TME analysis indicated that immune cell subpopulations and immune functions were highly enriched in cluster 2 as compared with cluster 1. WGCNA identified 6 hub genes (ACSL5, ALOX5AP, CD1D, CD74, IL4I1, and TBXAS1) as FAM biomarkers. CM patients with high expression levels of the six biomarkers had better OS, PFS, and DSS than those with low expression levels of the biomarkers. The Cox regression analyses verified that the 6 FAM biomarkers can be independent prognostic factors for CM patients. The single-gene GSEA showed that the high expression levels of the 6 genes were mainly enriched in T-cell antigen presentation, the PD-1 signaling pathway, and tumor escape. The TME analysis confirmed that the FAM subtype biomarkers were not only related to immune infiltration but also highly correlated with immune checkpoints such as PD-1, PD-L1, and CTLA-4. TIDE scores confirmed that patients with high expression levels of the 6 biomarkers had worse immunotherapy responses. The 6 genes conveyed significant sensitivity to some chemotherapy drugs. qRT-PCR and IHC analyses verified the expression levels of the 6 biomarkers in CM cells.

CONCLUSION

Our FAM subtypes verify that different FAM reprogramming affects the function and phenotype of infiltrating immune cells in the CM TME. The FAM molecular subtype biomarkers can be independent predictors of prognosis and immunotherapy response in CM patients.

Disease Recurrence during Adjuvant Immune Checkpoint Inhibitor Treatment in Metastatic Melanoma: Clinical, Laboratory, and Radiological Characteristics in Patients from a Single Tertiary Referral Center

Despite the dramatic improvements in recurrence-free survival in patients with metastatic melanoma treated with immune checkpoint inhibitors (ICI), a number of patients develop metastases during adjuvant therapy. It is not currently possible to predict which patients are most likely to develop disease recurrence due to a lack of reliable biomarkers. Thus, we retrospectively analyzed the case records of all patients who commenced adjuvant ICI therapy between January 2018 and December 2021 in a single university skin cancer center (n = 46) (i) to determine the rates of disease recurrence, (ii) to examine the utility of established markers, and (iii) to examine whether re-challenge with immunotherapy resulted in clinical response. Twelve out of forty-six (26%) patients developed a relapse on adjuvant immunotherapy in our cohort, and the median time to relapse was 139 days. Adjuvant immunotherapy was continued in three patients. Of the twelve patients who developed recurrence during adjuvant immunotherapy, seven had further disease recurrence within the observation period, with a median time of 112 days after the first progress. There was no significant difference comparing early recurrence (<180 days after initiation) on adjuvant immunotherapy to late recurrence (>180 days after initiation) on adjuvant immunotherapy. Classical tumor markers, including serum lactate dehydrogenase (LDH) and S-100, were unreliable for the detection of disease recurrence. Baseline lymphocyte and eosinophil counts and those during immunotherapy were not associated with disease recurrence. Interestingly, patients with NRAS mutations were disproportionately represented (60%) in the patients who developed disease recurrence, suggesting that these patients should be closely monitored during adjuvant therapy.

Gene Identification and Potential Drug Therapy for Drug-Resistant Melanoma with Bioinformatics and Deep Learning Technology

Background. Melanomas are skin malignant tumors that arise from melanocytes which are primarily treated with surgery, chemotherapy, targeted therapy, immunotherapy, radiation therapy, etc. Targeted therapy is a promising approach to treating advanced melanomas, but resistance always occurs. This study is aimed at identifying the potential target genes and candidate drugs for drug-resistant melanoma effectively with computational methods. Methods. Identification of genes associated with drug-resistant melanomas was conducted using the text mining tool pubmed2ensembl. Further gene screening was carried out by GO and KEGG pathway enrichment analyses. The PPI network was constructed using STRING database and Cytoscape. GEPIA was used to perform the survival analysis and conduct the Kaplan-Meier curve. Drugs targeted at these genes were selected in Pharmaprojects. The binding affinity scores of drug-target interactions were predicted by DeepPurpose. Results. A total of 433 genes were found associated with drug-resistant melanomas by text mining. The most statistically differential functional enriched pathways of GO and KEGG analyses contained 348 genes, and 27 hub genes were further screened out by MCODE in Cytoscape. Six genes were identified with statistical differences after survival analysis and literature review. 16 candidate drugs targeted at hub genes were found by Pharmaprojects under our restrictions. Finally, 11 ERBB2-targeted drugs with top affinity scores were predicted by DeepPurpose, including 10 ERBB2 kinase inhibitors and 1 antibody-drug conjugate. Conclusion. Text mining and bioinformatics are valuable methods for gene identification in drug discovery. DeepPurpose is an efficient and operative deep learning tool for predicting the DTI and selecting the candidate drugs.

MLKL deficiency in BrafV600EPten−/− melanoma model results in a modest delay of nevi development and reduced lymph node dissemination in male mice

Cancers acquire several capabilities to survive the multistep process in carcinogenesis. Resisting cell death is one of them. Silencing of the necroptosis initiator Ripk3 occurs in a wide variety of cancer types including melanoma. Little is known about the role of the necroptosis executioner MLKL in tumor development. Studies often indicate opposing roles for MLKL as a tumor-suppressing or a tumor-promoting protein. This study investigates the role of MLKL during melanoma initiation and progression using a tamoxifen-inducible melanoma mouse model driven by melanocyte-specific overexpression of mutated Braf and simultaneous deletion of Pten (Braf^V600EPten^−/−). In this model we observed a clear sex difference: melanoma initiation and progression were faster in females mice. Mlkl deficiency in male mice resulted in a modest but significant reduction of nevi growth rate compared to the littermate control. In these mice, infiltration and expansion of melanoma cells in the inguinal lymph node were also modestly decreased. This is likely to be a consequence of the delay in nevi development. No significant difference was observed in the Mlkl-deficient condition in female mice in which melanoma development was faster. Overall, our results indicate that in this genetic model MLKL has a minor role during melanoma initiation and progression.

Vitamin D Enhances Anticancer Properties of Cediranib, a VEGFR Inhibitor, by Modulation of VEGFR2 Expression in Melanoma Cells

Regardless of the recent groundbreaking introduction of personalized therapy, melanoma continues to be one of the most lethal skin malignancies. Still, a substantial proportion of patients either fail to respond to the therapy or will relapse over time, representing a challenging clinical problem. Recently, we have shown that vitamin D enhances the effectiveness of classical chemotherapeutics in the human malignant melanoma A375 cell line. In search for new combination strategies and adjuvant settings to improve melanoma patient outcomes in the current study, the effects of cediranib (AZD2171), an oral tyrosine kinase inhibitor of VEGFR1-3, PDGFR, and c-KIT, used in combination either with 1,25(OH)₂D₃ or with low-calcemic analog calcipotriol were tested on four human malignant melanoma cell lines (A375, MNT-1, RPMI-7951, and SK-MEL-28). Melanoma cells were pretreated with vitamin D and subsequently exposed to cediranib. We observed a marked decrease in melanoma cell proliferation (A375 and SK-MEL-28), G2/M cell cycle arrest, and a significant decrease in melanoma cell mobility in experimental conditions used (A375). Surprisingly, concurrently with a very desirable decrease in melanoma cell proliferation and mobility, we noticed the upregulation of VEGFR2 at both protein and mRNA levels. No effect of vitamin D was observed in MNT-1 and RPMI-7951 melanoma cells. It seems that vitamin D derivatives enhance cediranib efficacy by modulation of VEGFR2 expression in melanoma cells expressing VEGFR2. In conclusion, our experiments demonstrated that vitamin D derivatives hold promise as novel adjuvant candidates to conquer melanoma, especially in patients suffering from vitamin D deficiency. However, further extensive research is indispensable to reliably assess their potential benefits for melanoma patients.

Individualized Treatment Strategy for Cutaneous Melanoma: Where Are We Now and Where Are We Going?

In the past several decades, innovative research in cancer biology and immunology has contributed to novel therapeutics, such as targeted therapy and immunotherapy, which have transformed the management of patients with melanoma. Despite the remarkable therapeutic outcomes of targeted treatments targeting MAPK signaling and immunotherapy that suppresses immune checkpoints, some individuals acquire therapeutic resistance and disease recurrence. This review summarizes the current understanding of melanoma genetic variations and discusses individualized melanoma therapy options, particularly for advanced or metastatic melanoma, as well as potential drug resistance mechanisms. A deeper understanding of individualized treatment will assist in improving clinical outcomes for patients with cutaneous melanoma.

Overcoming Resistance to Immunotherapy in Advanced Cutaneous Squamous Cell Carcinoma

Cutaneous squamous cell carcinoma (CSCC) is the second most frequent cancer in humans, and is now responsible for as many deaths as melanoma. Immunotherapy has changed the therapeutic landscape of advanced CSCC after the FDA approval of anti-PD1 molecules for the treatment of locally advanced and metastatic CSCC. However, roughly 50% of patients will not respond to this systemic treatment and even those who do respond can develop resistance over time. The etiologies of primary and secondary resistance to immunotherapy involve changes in the neoplastic cells and the tumor microenvironment. Indirect modulation of immune system activation with new therapies, such as vaccines, oncolytic viruses, and new immunotherapeutic agents, and direct modulation of tumor immunogenicity using other systemic treatments or radiotherapy are now under evaluation in combined regimens. The identification of predictors of response is an important area of research. In this review, we focus on the features associated with the response to immunotherapy, and the evaluation of combination treatments and new molecules, a more thorough knowledge of which is likely to improve the survival of patients with advanced CSCC.

Data mining of immune-related prognostic genes in metastatic melanoma microenvironment

Skin cutaneous melanoma (SKCM) is one of the most deadly malignancies. Although immunotherapies showed the potential to improve the prognosis for metastatic melanoma patients, only a small group of patients can benefit from it. Therefore, it is urgent to investigate the tumor microenvironment in melanoma as well as to identify efficient biomarkers in the diagnosis and treatments of SKCM patients. A comprehensive analysis was performed based on metastatic melanoma samples from the Cancer Genome Atlas (TCGA) database and ESTIMATE algorithm, including gene expression, immune and stromal scores, prognostic immune‐related genes, infiltrating immune cells analysis and immune subtype identification. Then, the differentially expressed genes (DEGs) were obtained based on the immune and stromal scores, and a list of prognostic immune‐related genes was identified. Functional analysis and the protein–protein interaction network revealed that these genes enriched in multiple immune-related biological processes. Furthermore, prognostic genes were verified in the Gene Expression Omnibus (GEO) databases and used to predict immune infiltrating cells component. Our study revealed seven immune subtypes with different risk values and identified T cells as the most abundant cells in the immune microenvironment and closely associated with prognostic outcomes. In conclusion, the present study thoroughly analyzed the tumor microenvironment and identified prognostic immune‐related biomarkers for metastatic melanoma.

The Role of Antigen Processing and Presentation in Cancer and the Efficacy of Immune Checkpoint Inhibitor Immunotherapy

Recent clinical successes of cancer immunotherapy using immune checkpoint inhibitors (ICIs) are rapidly changing the landscape of cancer treatment. Regardless of initial impressive clinical results though, the therapeutic benefit of ICIs appears to be limited to a subset of patients and tumor types. Recent analyses have revealed that the potency of ICI therapies depends on the efficient presentation of tumor-specific antigens by cancer cells and professional antigen presenting cells. Here, we review current knowledge on the role of antigen presentation in cancer. We focus on intracellular antigen processing and presentation by Major Histocompatibility class I (MHCI) molecules and how it can affect cancer immune evasion. Finally, we discuss the pharmacological tractability of manipulating intracellular antigen processing as a complementary approach to enhance tumor immunogenicity and the effectiveness of ICI immunotherapy.

P53 in skin cancer: From a master player to a privileged target for prevention and therapy

The increasing incidence of skin cancer (SC) is a global health concern. The commonly reported side effects and resistance mechanisms have imposed the pursuit for new therapeutic alternatives. Moreover, additional preventive strategies should be adopted to strengthen prevention and reduce the rising number of newly SC cases. This review provides relevant insights on the role of p53 tumour suppressor protein in melanoma and non-melanoma skin carcinogenesis, also highlighting the therapeutic potential of p53-targeting drugs against SC. In fact, several evidences are provided demonstrating the encouraging outcomes achieved with p53-activating drugs, alone and in combination with currently available therapies in SC. Another pertinent perspective falls on targeting p53 mutations, as molecular signatures in premature phases of photocarcinogenesis, in future SC preventive approaches. Overall, this review affords a critical and timely discussion of relevant issues related to SC prevention and therapy. Importantly, it paves the way to future studies that may boost the clinical translation of p53-activating agents, making them new effective alternatives in precision medicine of SC therapy and prevention.