Understanding heterogeneous tumor microenvironment in metastatic melanoma

Spatiotemporal spread of oncolytic virus in a heterogeneous cell population

Oncolytic (cancer-killing) virus treatment is a promising new therapy for cancer, with many viruses currently being tested for their ability to eradicate tumors. One of the major stumbling blocks to the development of this treatment modality has been preventing spread of the virus to non-cancerous cells. Our recent ability to manipulate RNA and DNA now allows for the possibility of creating designer viruses specifically targeted to cancer cells, thereby significantly reducing unwanted side effects in patients. In this study, we use a partial differential equation model to determine the characteristics of a virus needed to contain spread of an oncolytic virus within a spherical tumor and prevent it from spreading to non-cancerous cells outside the tumor. We find that oncolytic viruses that have different infection rates or different cell death rates in cancer and non-cancerous cells can be made to stay within the tumor. We find that there is a minimum difference in infection rates or cell death rates that will contain the virus and that this threshold value depends on the growth rate of the cancer. Identification of these types of thresholds can help researchers develop safer strains of oncolytic viruses allowing further development of this promising treatment.

Targeting anticancer immunity in melanoma tumour microenvironment: unleashing the potential of adjuvants, drugs, and phytochemicals

Melanoma poses a challenge in oncology because of its aggressive nature and limited treatment modalities. The tumour microenvironment (TME) in melanoma contains unique properties such as an immunosuppressive and high-density environment, unusual vasculature, and a high number of stromal and immunosuppressive cells. In recent years, numerous experiments have focused on boosting the immune system to effectively remove malignant cells. Adjuvants, consisting of phytochemicals, toll-like receptor (TLR) agonists, and cytokines, have shown encouraging results in triggering antitumor immunity and augmenting the therapeutic effectiveness of anticancer therapy. These adjuvants can stimulate the maturation of dendritic cells (DCs) and infiltration of cytotoxic CD8+ T lymphocytes (CTLs). Furthermore, nanocarriers can help to deliver immunomodulators and antigens directly to the tumour stroma, thereby improving their efficacy against malignant cells. The remodelling of melanoma TME utilising phytochemicals, agonists, and other adjuvants can be combined with current modalities for improving therapy outcomes. This review article explores the potential of adjuvants, drugs, and their nanoformulations in enhancing the anticancer potency of macrophages, CTLs, and natural killer (NK) cells. Additionally, the capacity of these agents to repress the function of immunosuppressive components of melanoma TME, such as immunosuppressive subsets of macrophages, stromal and myeloid cells will be discussed.

Subverting Attachment to Prevent Attacking: Alteration of Effector Immune Cell Migration and Adhesion as a Key Mechanism of Tumor Immune Evasion

Cell adhesion regulates specific migratory patterns, location, communication with other cells, physical interactions with the extracellular matrix, and the establishment of effector programs. Proper immune control of cancer strongly depends on all these events occurring in a highly accurate spatiotemporal sequence. In response to cancer-associated inflammatory signals, effector immune cells navigating the bloodstream shift from their patrolling exploratory migration mode to establish adhesive interactions with vascular endothelial cells. This interaction enables them to extravasate through the blood vessel walls and access the cancer site. Further adhesive interactions within the tumor microenvironment (TME) are crucial for coordinating their distribution in situ and for mounting an effective anti-tumor immune response. In this review, we examine how alterations of adhesion cues in the tumor context favor tumor escape by affecting effector immune cell infiltration and trafficking within the TME. We discuss the mechanisms by which tumors directly modulate immune cell adhesion and migration patterns to affect anti-tumor immunity and favor tumor evasion. We also explore indirect immune escape mechanisms that involve modifications of TME characteristics, such as vascularization, immunogenicity, and structural topography. Finally, we highlight the significance of these aspects in designing more effective drug treatments and cellular immunotherapies.

Investigation of tumour environments through advancements in microtechnology and nanotechnology

Cancer has a significant negative social and economic impact on both developed and developing countries. As a result, understanding the onset and progression of cancer is critical for developing therapies that can improve the well-being and health of individuals with cancer. With time, study has revealed, the tumor microenvironment has great influence on this process. Micro and nanoscale engineering techniques can be used to study the tumor microenvironment. Nanoscale and Microscale engineering use Novel technologies and designs with small dimensions to recreate the TME. Knowing how cancer cells interact with one another can help researchers develop therapeutic approaches that anticipate and counteract cancer cells' techniques for evading detection and fighting anti-cancer treatments, such as microfabrication techniques, microfluidic devices, nanosensors, and nanodevices used to study or recreate the tumor microenvironment. Nevertheless, a complicated action just like the growth and in cancer advancement, and their intensive association along the environment around it that has to be studied in more detail.

Cubosomes as versatile lipid nanocarriers for neurological disorder therapeutics: a comprehensive review

Cubosomes are novel vesicular drug delivery systems with lipidic liquid crystal nanoparticles formed of predetermined proportions of amphiphilic lipids. They have a honeycomb-like structure and are thermodynamically stable. These bicontinuous lipid layers are separated into two water-based channels internally that can be used by various bioactive substances, including drugs, proteins, and peptides. This complex structure is responsible for its high drug-loading capacity. Cubosomes are thought to be promising vehicles for various routes of administration because of their extraordinary characteristics, including bioadhesion, the capacity to encapsulate hydrophilic, and hydrophobic, as well as amphiphilic substances, high resistance to environmental stress, and their ability to achieve controlled release through modification. One of the essential elements for improving patient compliance is the ability of these well-defined nano-drug delivery systems to boost the effectiveness of targeting while lowering the side effects/toxicities of payloads. The large internal surface area, a sufficiently uncomplicated fabrication procedure, and biodegradability make it an attractive nano lipid carrier for drug delivery. This review outlines the recent advancement of cubosomes for managing various neurological disorders, highlighting their potential in this field.

Integrating Spatial and Morphological Characteristics into Melanoma Prognosis: A Computational Approach

In this study, the prognostic value of cellular morphology and spatial configurations in melanoma has been examined, aiming to complement traditional prognostic indicators like mitotic activity and tumor thickness. Through a computational pipeline using machine learning and deep learning methods, we quantified nuclei sizes within different spatial regions and analyzed their prognostic significance using univariate and multivariate Cox models. Nuclei sizes in the invasive band demonstrated a significant hazard ratio (HR) of 1.1 (95% CI: 1.03, 1.18). Similarly, the nuclei sizes of tumor cells and Ki67 S100 co-positive cells in the invasive band achieved HRs of 1.07 (95% CI: 1.02, 1.13) and 1.09 (95% CI: 1.04, 1.16), respectively. Our findings reveal that nuclei sizes, particularly in the invasive band, are potentially prognostic factors. Correlation analyses further demonstrated a meaningful relationship between cellular morphology and tumor progression, notably showing that nuclei size within the invasive band correlates substantially with tumor thickness. These results suggest the potential of integrating spatial and morphological analyses into melanoma prognostication.

Integrative analysis of bulk and single-cell RNA-seq reveals the molecular characterization of the immune microenvironment and oxidative stress signature in melanoma

Background

The immune microenvironment and oxidative stress of melanoma show significant heterogeneity, which affects tumor growth, invasion and treatment response. Single-cell and bulk RNA-seq data were used to explore the heterogeneity of the immune microenvironment and oxidative stress of melanoma.

Methods

The R package Seurat facilitated the analysis of the single-cell dataset, while Harmony, another R package, was employed for batch effect correction. Cell types were classified using Uniform Manifold Approximation and Projection (UMAP). The Secreted Signaling algorithm from CellChatDB.human was applied to elucidate cell-to-cell communication patterns within the single-cell data. Consensus clustering analysis for the skin cutaneous melanoma (SKCM) samples was executed with the R package ConsensusClusterPlus. To quantify immune infiltrating cells, we utilized CIBERSORT, ESTIMATE, and TIMERxCell algorithms provided by the R package Immuno-Oncology Biological Research (IOBR). Single nucleotide variant (SNV) analysis was conducted using Maftools, an R package specifically designed for this purpose. Subsequently, the expression levels of PXDN and PAPSS2 genes were assessed in melanoma tissues compared to adjacent normal tissues. Furthermore, in vitro experiments were conducted to evaluate the proliferation and reactive oxygen species expression in melanoma cells following transfection with siRNA targeting PXDN and PAPSS2.

Results

Malignant tumor cell populations were reclassified based on a comprehensive single-cell dataset analysis, which yielded six distinct tumor subsets. The specific marker genes identified for these subgroups were then used to interrogate the Cancer Genome Atlas Skin Cutaneous Melanoma (TCGA-SKCM) cohort, derived from bulk RNA sequencing data, resulting in the delineation of two immune molecular subtypes. Notably, patients within the cluster2 (C2) subtype exhibited a significantly more favorable prognosis compared to those in the cluster1 (C1) subtype. An alignment of immune characteristics was observed between the C2 subtype and unique immune functional tumor cell subsets. Genes differentially expressed across these subtypes were subsequently leveraged to construct a predictive risk model. In vitro investigations further revealed elevated expression levels of PXDN and PAPSS2 in melanoma tissue samples. Functional assays indicated that modulation of PXDN and PAPSS2 expression could influence the production of reactive oxygen species (ROS) and the proliferative capacity of melanoma cells.

Conclusion

The constructed six-gene signature can be used as an immune response and an oxidative stress marker to guide the clinical diagnosis and treatment of melanoma.

Exploiting Unique Features of Microneedles to Modulate Immunity

Microneedle arrays (MNAs) are small patches containing hundreds of short projections that deliver signals directly to dermal layers without causing pain. These technologies are of special interest for immunotherapy and vaccine delivery because they directly target immune cells concentrated in the skin. The targeting abilities of MNAs result in efficient immune responses-often more protective or therapeutic-compared to conventional needle delivery. MNAs also offer logistical benefits, such as self-administration and transportation without refrigeration. Thus, numerous preclinical and clinical studies are exploring these technologies. Here the unique advantages of MNA, as well as critical challenges-such as manufacturing and sterility issues-the field faces to enable widespread deployment are discussed. How MNA design parameters can be exploited for controlled release of vaccines and immunotherapies, and the application to preclinical models of infection, cancer, autoimmunity, and allergies are explained. Specific strategies are also discussed to reduce off-target effects compared to conventional vaccine delivery routes, and novel chemical and manufacturing controls that enable cargo stability in MNAs across flexible intervals and temperatures. Clinical research using MNAs is then examined. Drawbacks of MNAs and the implications, and emerging opportunities to exploit MNAs for immune engineering and clinical use are concluded.

Micro-engineering and nano-engineering approaches to investigate tumour ecosystems

The interactions among tumour cells, the tumour microenvironment (TME) and non-tumour tissues are of interest to many cancer researchers. Micro-engineering approaches and nanotechnologies are under extensive exploration for modelling these interactions and measuring them in situ and in vivo to investigate therapeutic vulnerabilities in cancer and extend a systemic view of tumour ecosystems. Here we highlight the greatest opportunities for improving the understanding of tumour ecosystems using microfluidic devices, bioprinting or organ-on-a-chip approaches. We also discuss the potential of nanosensors that can transmit information from within the TME or elsewhere in the body to address scientific and clinical questions about changes in chemical gradients, enzymatic activities, metabolic and immune profiles of the TME and circulating analytes. This Review aims to connect the cancer biology and engineering communities, presenting biomedical technologies that may expand the methodologies of the former, while inspiring the latter to develop approaches for interrogating cancer ecosystems.

Integrating single-cell RNA-seq and spatial transcriptomics reveals MDK-NCL dependent immunosuppressive environment in endometrial carcinoma

Objectives

The tumor microenvironment (TME) play important roles in progression of endometrial carcinoma (EC). We aimed to assess the cell populations in TME of EC.

Methods

We downloaded datasets of single-cell RNA-seq (scRNA-seq) and spatial transcriptome (ST) for EC from GEO, and downloaded RNA-Seq (FPKM) and clinical data of TCGA-UCEC project from TCGA. The datasets were analyzed using R software.

Results

We obtained 5 datasets of scRNA-seq, 1 of ST and 569 samples of RNA-seq. Totally, 0.2 billion transcripts and 33,408 genes were detected in 33,162 cells from scRNA-seq. The cells were classified into 9 clusters, and EC cells were originated from epithelial cells and ciliated cells. Gene set variation analysis (GSVA) indicated that the pathways enriched in the subclusters of epithelial cells and endothelial cells were significantly different, indicating great heterogeneity in EC. Cell-cell communication analyses showed that EC cells emitted the strongest signals, and endothelial cells received more signals than other cells. Further analysis found that subclusters of 1 and 2 of epithelial cells were showed a more malignant phenotype, which may confer malignant phenotype to subcluster of 0 of endothelial cells through MK pathway by MDL-NCL signal. We also analyzed communications between spatial neighbors with ST data and confirmed the findings on MDL-NCL in cell-cell communication. TCGA and GEO analyses indicated that the expression levels of NCL was inversely correlated with ImmuneScore.

Conclusion

Our study revealed EC cells can confer malignant phenotype to endothelial cells by MDK-NCL signal, and NCL is associated with suppressed immune activity. EC cells may shape TME by inhibiting immune cells and “educating” stromal cells via MDK-NCL signal.

Extracellular vesicles microRNA-592 of melanoma stem cells promotes metastasis through activation of MAPK/ERK signaling pathway by targeting PTPN7 in non-stemness melanoma cells

Melanoma, one of the most aggressive malignancies, its high mortality and low survival rates are associated with effective metastatic colonization. Melanoma metastasis hinges on the bidirectional cell-cell communication within the complex metastatic microenvironments (MME). Extracellular vesicles (EVs) are recognized as a new class of molecular mediator in MME programing. Published studies show that melanoma EVs can educate MME stromal cells to acquire the pro-metastatic phenotype to enhance metastatic colonization. Whether EVs can mediate the interactions between heterogenous cancer cells within the MME that alter the course of metastasis has not been investigated at the mechanistic level. In this study, melanoma parental cells (MPCs) and paired derivative cancer stem cell line melanoma stem cells (MSCs) that were derived from melanoma cell line M14 were used. We demonstrate that the EVs-mediated crosstalk between the MSCs and the MPCs is a novel mechanism for melanoma metastasis. We characterized miR-592, a relatively novel microRNA of prognostic potential, in mediation of such intercellular crosstalk. EVs can encapsulate and deliver miR-592 to target MPCs. Upon entering, miR-592 inhibits the expression of its gene target protein tyrosine phosphatase non-receptor type7 (PTPN7), a phosphatase targeting MAPKs. This leads to the relief of the inhibitory effect of PTPN7 on MAPK/ERK signaling and consequently the augmentation of metastatic colonization of MPCs. Thus, via the extracellular vesicle miR-592/PTPN7/MAPK axis, melanoma-CSCs can transfer their metastatic ability to the low-metastatic non-CSC melanoma cells.

A Ferroptosis-Related Gene Signature for Predicting Survival and Immunotherapy Effect in Renal Cancer

Background

Most recently, no efficient prognostic indictor is present for kidney cancer. Thus, we aimed to build and validate a new prognostic gene signature for renal cancer patients using the Cancer Genomic Atlas (TCGA).

Methods

A “time-dependent receiver operating characteristic (tROC)” curve was generated, and a log-rank test was performed to assess the performance of the biomarker in training and validation. A “ferroptosis-related gene signature” was developed. In different training and validations sets, tROC and log-rank test were used to validate the biomarker's performance.

Results

In the training set with a P value less than 0.01 and the validation set, the “gene signature” was significantly correlated with survival. Eventually, it was found that the ferroptosis-related gene signature was directly correlated with immune score and the score of tumor mutation, suggesting its role in predicting response to immunotherapy.

Conclusion

We developed and validated a “ferroptosis-related gene signature” that can be sued for patients with kidney cancer. It can also assist in facilitating the plan for treatment and risk stratification.

Coronas of micro/nano plastics: a key determinant in their risk assessments

As an emerging pollutant in the life cycle of plastic products, micro/nanoplastics (M/NPs) are increasingly being released into the natural environment. Substantial concerns have been raised regarding the environmental and health impacts of M/NPs. Although diverse M/NPs have been detected in natural environment, most of them display two similar features, i.e.,high surface area and strong binding affinity, which enable extensive interactions between M/NPs and surrounding substances. This results in the formation of coronas, including eco-coronas and bio-coronas, on the plastic surface in different media. In real exposure scenarios, corona formation on M/NPs is inevitable and often displays variable and complex structures. The surface coronas have been found to impact the transportation, uptake, distribution, biotransformation and toxicity of particulates. Different from conventional toxins, packages on M/NPs rather than bare particles are more dangerous. We, therefore, recommend seriously consideration of the role of surface coronas in safety assessments. This review summarizes recent progress on the eco-coronas and bio-coronas of M/NPs, and further discusses the analytical methods to interpret corona structures, highlights the impacts of the corona on toxicity and provides future perspectives.

Heparanase is a prognostic biomarker independent of tumor purity and hypoxia based on bioinformatics and immunohistochemistry analysis of esophageal squamous cell carcinoma

Background

Esophageal squamous cell carcinoma (ESCC) is a common malignant tumor of the digestive tract with a poor prognosis. The tumor microenvironment (TME) is mainly composed of tumor cells, stromal cells, and immune cells and plays an important role in ESCC development. There are substantial differences in tumor purity among different parts of ESCC tissues, consisting of distinct immune and stromal cells and variations in the status of hypoxia. Thus, prognostic models of ESCC based on bioinformatic analysis of tumor tissues are unreliable.

Method

Differentially expressed genes (DEGs) independent of tumor purity and hypoxia were screened by Spearman correlation analysis of public ESCC cohorts. Subsequently, the DEGs were subjected to Cox regression analysis. Then, we constructed a protein–protein interaction (PPI) network of the DEGs using Cytoscape. Intersection analysis of the univariate Cox and PPI results indicated that heparanase (HPSE), an endo-β-D-glucuronidase capable of cleaving heparan sulfate side chains, was a predictive factor. Gene set enrichment analysis (GSEA) was used to reveal the potential function of HPSE, and single-cell sequencing data were analyzed to evaluate the distribution of HPSE in immune cells. Furthermore, a human ESCC tissue microarray was used to validate the expression and prognostic value of HPSE.

Result

We found that HPSE was downregulated in ESCC tissues and was not correlated with tumor purity or hypoxia status. HPSE is involved in multiple biological processes. ESCC patients with low HPSE expression in cancerous tissues exhibited poor prognosis.

Conclusions

These results indicate that low HPSE expression in cancerous tissues correlates with poor prognosis in patients with ESCC. HPSE is a novel prognostic biomarker independent of tumor purity and hypoxia status in ESCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-022-02698-9.

Modulation of Lymphocyte Functions in the Microenvironment by Tumor Oncogenic Pathways

Despite the broad application of different immunotherapeutic strategies for the treatment of solid as well as hematopoietic cancers, the efficacy of these therapies is still limited, with only a minority of patients having a long-term benefit resulting in an improved survival rate. In order to increase the response rates of patients to the currently available immunotherapies, a better understanding of the molecular mechanisms underlying the intrinsic and/or extrinsic resistance to treatment is required. There exist increasing evidences that activation of different oncogenic pathways as well as inactivation of tumor suppressor genes (TSG) in tumor cells inhibit the immune cell recognition and influegnce the composition of the tumor microenvironment (TME), thus leading to an impaired anti-tumoral immune response. A deeper understanding of the link between the tumor milieu and genomic alterations of TSGs and oncogenes is indispensable for the optimization of immunotherapies and to predict the patients’ response to these treatments. This review summarizes the role of different cancer-related, oncogene- and TSG-controlled pathways in the context of anti-tumoral immunity and response to different immunotherapies.

Stratification of chemotherapy-treated stage III colorectal cancer patients using multiplexed imaging and single-cell analysis of T-cell populations

Colorectal cancer (CRC) has one of the highest cancer incidences and mortality rates. In stage III, postoperative chemotherapy benefits <20% of patients, while more than 50% will develop distant metastases. Biomarkers for identification of patients at increased risk of disease recurrence following adjuvant chemotherapy are currently lacking. In this study, we assessed immune signatures in the tumor and tumor microenvironment (TME) using an in situ multiplexed immunofluorescence imaging and single-cell analysis technology (Cell DIVETM) and evaluated their correlations with patient outcomes. Tissue microarrays (TMAs) with up to three 1 mm diameter cores per patient were prepared from 117 stage III CRC patients treated with adjuvant fluoropyrimidine/oxaliplatin (FOLFOX) chemotherapy. Single sections underwent multiplexed immunofluorescence staining for immune cell markers (CD45, CD3, CD4, CD8, FOXP3, PD1) and tumor/cell segmentation markers (DAPI, pan-cytokeratin, AE1, NaKATPase, and S6). We used annotations and a probabilistic classification algorithm to build statistical models of immune cell types. Images were also qualitatively assessed independently by a Pathologist as 'high', 'moderate' or 'low', for stromal and total immune cell content. Excellent agreement was found between manual assessment and total automated scores (p < 0.0001). Moreover, compared to single markers, a multi-marker classification of regulatory T cells (Tregs: CD3+/CD4+FOXP3+/PD1-) was significantly associated with disease-free survival (DFS) and overall survival (OS) (p = 0.049 and 0.032) of FOLFOX-treated patients. Our results also showed that PD1- Tregs rather than PD1+ Tregs were associated with improved survival. These findings were supported by results from an independent FOLFOX-treated cohort of 191 stage III CRC patients, where higher PD1- Tregs were associated with an increase overall survival (p = 0.015) for CD3+/CD4+/FOXP3+/PD1-. Overall, compared to single markers, multi-marker classification provided more accurate quantitation of immune cell types with stronger correlations with outcomes.

Personalized models of heterogeneous 3D epithelial tumor microenvironments: Ovarian cancer as a model

Intractable human diseases such as cancers, are context dependent, unique to both the individual patient and to the specific tumor microenvironment. However, conventional cancer treatments are often nonspecific, targeting global similarities rather than unique drivers. This limits treatment efficacy across heterogeneous patient populations and even at different tumor locations within the same patient. Ultimately, this poor efficacy can lead to adverse clinical outcomes and the development of treatment-resistant relapse. To prevent this and improve outcomes, it is necessary to be selective when choosing a patient's optimal adjuvant treatment. In this review, we posit the use of personalized, tumor-specific models (TSM) as tools to achieve this remarkable feat. First, using ovarian cancer as a model disease, we outline the heterogeneity and complexity of both the cellular and extracellular components in the tumor microenvironment. Then we examine the advantages and disadvantages of contemporary cancer models and the rationale for personalized TSM. We discuss how to generate precision 3D models through careful and detailed analysis of patient biopsies. Finally, we provide clinically relevant applications of these versatile personalized cancer models to highlight their potential impact. These models are ideal for a myriad of fundamental cancer biology and translational studies. Importantly, these approaches can be extended to other carcinomas, facilitating the discovery of new therapeutics that more effectively target the unique aspects of each individual patient's TME. STATEMENT OF SIGNIFICANCE: In this article, we have presented the case for the application of biomaterials in developing personalized models of complex diseases such as cancers. TSM could bring about breakthroughs in the promise of precision medicine. The critical components of the diverse tumor microenvironments, that lead to treatment failures, include cellular- and extracellular matrix- heterogeneity, and biophysical signals to the cells. Therefore, we have described these dynamic components of the tumor microenvironments, and have highlighted how contemporary biomaterials can be utilized to create personalized in vitro models of cancers. We have also described the application of the TSM to predict the dynamic patterns of disease progression, and predict effective therapies that can produce durable responses, limit relapses, and treat any minimal residual disease.

Proximity labeling and other novel mass spectrometric approaches for spatiotemporal protein dynamics

BACKGROUND

Proteins are highly dynamic and their biological function is controlled by not only temporal abundance changes but also via regulated protein-protein interaction networks, which respond to internal and external perturbations. A wealth of novel analytical reagents and workflows allow studying spatiotemporal protein environments with great granularity while maintaining high throughput and ease of analysis.

AREAS COVERED

We review technology advances for measuring protein-protein proximity interactions with an emphasis on proximity labeling, and briefly summarize other spatiotemporal approaches including protein localization, and their dynamic changes over time, specifically in human cells and mammalian tissues. We focus especially on novel technologies and workflows emerging within the past 5 years. This includes enrichment-based techniques (proximity labeling and crosslinking), separation-based techniques (organelle fractionation and size exclusion chromatography), and finally sorting-based techniques (laser capture microdissection and mass spectrometry imaging).

EXPERT OPINION

Spatiotemporal proteomics is a key step in assessing biological complexity, understanding refined regulatory mechanisms, and forming protein complexes and networks. Studying protein dynamics across space and time holds promise for gaining deep insights into how protein networks may be perturbed during disease and aging processes, and offer potential avenues for therapeutic interventions, drug discovery, and biomarker development.

EVI2B Is a New Prognostic Biomarker in Metastatic Melanoma with IFNgamma Associated Immune Infiltration

Simple Summary

Ecotropic viral integration site 2B (EVI2B) is a protein-coding gene known as a lymphocyte-specific marker in peripheral blood. However, the prognostic value of EVI2B expression in metastatic melanoma tissue and its detailed profile of tumor-infiltrating lymphocytes are still unclear. In publicly available datasets, we found that increased EVI2B was significantly associated with longer prognoses such as overall survival and disease-specific survival. The EVI2B-high melanoma tissue had a favorable distribution/clustering pattern of infiltrating lymphocytes with increased CD8+ T cells over regulatory T cells. Moreover, EVI2B expression correlated with multiple immunomodulatory genes including IFN-γ signature genes. In conclusion, EVI2B is a prognostic biomarker with IFN-γ associated immune infiltration in metastatic melanoma.

Abstract

Background: To assess the prognostic role and the antitumor immunological relevance of ecotropic viral integration site 2B (EVI2B) in metastatic melanoma. Methods: In this study, we integrated clinical data, mRNA expression data, and the distribution and fraction of tumor infiltrating lymphocytes (TILs) using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets (GSE65904 and GSE19234). Results: The univariate and multivariate analyses showed that higher gene expression of EVI2B was significantly associated with longer prognoses. The EVI2B-high melanoma tissue had favorable histological parameters such as a brisk global distribution pattern and clustering structure of TILs (i.e., Banfield and Raftery index) with enriched CD8+ T cells over regulatory T cells and increased cytotoxicity scores. In addition, EVI2B expression positively correlated with IFN-γ signature genes (CXCL10, CXCL9, HLA-DRA, IDO1, IFNG, and STAT1) and other various immunomodulatory genes. Conclusion: EVI2B is a novel prognostic biomarker with IFN-γ associated immune infiltration in metastatic melanoma.

From bench to bedside: Single-cell analysis for cancer immunotherapy

Single-cell technologies are emerging as powerful tools for cancer research. These technologies characterize the molecular state of each cell within a tumor, enabling new exploration of tumor heterogeneity, microenvironment cell-type composition, and cell state transitions that affect therapeutic response, particularly in the context of immunotherapy. Analyzing clinical samples has great promise for precision medicine but is technically challenging. Successfully identifying predictors of response requires well-coordinated, multi-disciplinary teams to ensure adequate sample processing for high-quality data generation and computational analysis for data interpretation. Here, we review current approaches to sample processing and computational analysis regarding their application to translational cancer immunotherapy research.

Integration of tumor inflammation, cell proliferation, and traditional biomarkers improves prediction of immunotherapy resistance and response

BACKGROUND

Contemporary to the rapidly evolving landscape of cancer immunotherapy is the equally changing understanding of immune tumor microenvironments (TMEs) which is crucial to the success of these therapies. Their reliance on a robust host immune response necessitates clinical grade measurements of immune TMEs at diagnosis. In this study, we describe a stable tumor immunogenic profile describing immune TMEs in multiple tumor types with ability to predict clinical benefit from immune checkpoint inhibitors (ICIs).

METHODS

A tumor immunogenic signature (TIGS) was derived from targeted RNA-sequencing (RNA-seq) and gene expression analysis of 1323 clinical solid tumor cases spanning 35 histologies using unsupervised analysis. TIGS correlation with ICI response and survival was assessed in a retrospective cohort of NSCLC, melanoma and RCC tumor blocks, alone and combined with TMB, PD-L1 IHC and cell proliferation biomarkers.

RESULTS

Unsupervised clustering of RNA-seq profiles uncovered a 161 gene signature where T cell and B cell activation, IFNg, chemokine, cytokine and interleukin pathways are over-represented. Mean expression of these genes produced three distinct TIGS score categories: strong (n = 384/1323; 29.02%), moderate (n = 354/1323; 26.76%), and weak (n = 585/1323; 44.22%). Strong TIGS tumors presented an improved ICI response rate of 37% (30/81); with highest response rate advantage occurring in NSCLC (ORR = 36.6%; 16/44; p = 0.051). Similarly, overall survival for strong TIGS tumors trended upward (median = 25 months; p = 0.19). Integrating the TIGS score categories with neoplastic influence quantified via cell proliferation showed highly proliferative and strong TIGS tumors correlate with significantly higher ICI ORR than poorly proliferative and weak TIGS tumors [14.28%; p = 0.0006]. Importantly, we noted that strong TIGS and highly [median = not achieved; p = 0.025] or moderately [median = 16.2 months; p = 0.025] proliferative tumors had significantly better survival compared to weak TIGS, highly proliferative tumors [median = 7.03 months]. Importantly, TIGS discriminates subpopulations of potential ICI responders that were considered negative for response by TMB and PD-L1.

CONCLUSIONS

TIGS is a comprehensive and informative measurement of immune TME that effectively characterizes host immune response to ICIs in multiple tumors. The results indicate that when combined with PD-L1, TMB and cell proliferation, TIGS provides greater context of both immune and neoplastic influences on the TME for implementation into clinical practice.

ATF-3 expression inhibits melanoma growth by downregulating ERK and AKT pathways

Activating transcription factor 3 (ATF-3), a cyclic AMP-dependent transcription factor, has been shown to play a regulatory role in melanoma, although its function during tumor progression remains unclear. Here, we demonstrate that ATF-3 exhibits tumor suppressive function in melanoma. Specifically, ATF-3 nuclear expression was significantly diminished with melanoma progression from nevi to primary to metastatic patient melanomas, correlating low expression with poor prognosis. Significantly low expression of ATF-3 was also found in cultured human metastatic melanoma cell lines. Importantly, overexpression of ATF-3 in metastatic melanoma cell lines significantly inhibited cell growth, migration, and invasion in vitro; as well as abrogated tumor growth in a human melanoma xenograft mouse model in vivo. RNA sequencing analysis revealed downregulation of ERK and AKT pathways and upregulation in apoptotic-related genes in ATF-3 overexpressed melanoma cell lines, which was further validated by Western-blot analysis. In summary, this study demonstrated that diminished ATF-3 expression is associated with melanoma virulence and thus provides a potential target for novel therapies and prognostic biomarker applications.

Using the R Package Spatstat to Assess Inhibitory Effects of Microregional Hypoxia on the Infiltration of Cancers of the Head and Neck Region by Cytotoxic T Lymphocytes

Simple Summary

Progress in the field of in situ proteomics allows for the simultaneous detection of multiple biomarkers within one cancer tissue specimen. As a result, biological hypotheses previously only assessable ex vivo can now be studied in human cancer tissue. However, methods for objective analysis have so far been lacking behind. In this study, we established a free, objective, and entirely open-source-based method for the analysis of multiplexed immunofluorescence specimens. This will gain further importance with the availability of more advanced multiplexing methods in the future.

Abstract

(1) Background: The immune system has physiological antitumor activity, which is partially mediated by cytotoxic T lymphocytes (CTL). Tumor hypoxia, which is highly prevalent in cancers of the head and neck region, has been hypothesized to inhibit the infiltration of tumors by CTL. In situ data validating this concept have so far been based solely upon the visual assessment of the distribution of CTL. Here, we have established a set of spatial statistical tools to address this problem mathematically and tested their performance. (2) Patients and Methods: We have analyzed regions of interest (ROI) of 22 specimens of cancers of the head and neck region after 4-plex immunofluorescence staining and whole-slide scanning. Single cell-based segmentation was carried out in QuPath. Specimens were analyzed with the endpoints clustering and interactions between CTL, normoxic, and hypoxic tumor areas, both visually and using spatial statistical tools implemented in the R package Spatstat. (3) Results: Visual assessment suggested clustering of CTL in all instances. The visual analysis also suggested an inhibitory effect between hypoxic tumor areas and CTL in a minority of the whole-slide scans (9 of 22, 41%). Conversely, the objective mathematical analysis in Spatstat demonstrated statistically significant inhibitory interactions between hypoxia and CTL accumulation in a substantially higher number of specimens (16 of 22, 73%). It showed a similar trend in all but one of the remaining samples. (4) Conclusion: Our findings provide non-obvious but statistically rigorous evidence of inhibition of CTL infiltration into hypoxic tumor subregions of cancers of the head and neck. Importantly, these shielded sites may be the origin of tumor recurrences. We provide the methodology for the transfer of our statistical approach to similar questions. We discuss why versions of the Kcross and pcf.cross functions may be the methods of choice among the repertoire of statistical tests in Spatstat for this type of analysis.

ESDN inhibits melanoma progression by blocking E-selectin expression in endothelial cells via STAT3

An interactive crosstalk between tumor and stroma cells is essential for metastatic melanoma progression. We evidenced that ESDN/DCBLD2/CLCP1 plays a crucial role in endothelial cells during the spread of melanoma. Precisely, increased extravasation and metastasis formation were revealed in ESDN-null mice injected with melanoma cells, even if the primary tumor growth, vessel permeability, and angiogenesis were not enhanced. Interestingly, improved adhesion of melanoma cells to ESDN-depleted endothelial cells was observed, due to the presence of higher levels of E-selectin transcripts/proteins in ESDN-defective cells. In accordance with these results, anticorrelation was observed between ESDN and E-selectin in human endothelial cells. Most importantly, our data revealed that cimetidine, an E-selectin inhibitor, was able to block cell adhesion, extravasation, and metastasis formation in ESDN-null mice, underlying a major role of ESDN in E-selectin transcription upregulation, which according to our data, may presumably be linked to STAT3. Based on our results, we propose a protective role for ESDN during the spread of melanoma and reveal its therapeutic potential.

A Nomogram Combining a Four-Gene Biomarker and Clinical Factors for Predicting Survival of Melanoma

Background

Currently there is no effective prognostic indicator for melanoma, the deadliest skin cancer. Thus, we aimed to develop and validate a nomogram predictive model for predicting survival of melanoma.

Methods

Four hundred forty-nine melanoma cases with RNA sequencing (RNA-seq) data from TCGA were randomly divided into the training set I (n = 224) and validation set I (n = 225), 210 melanoma cases with RNA-seq data from Lund cohort of Lund University (available in GSE65904) were used as an external test set. The prognostic gene biomarker was developed and validated based on the above three sets. The developed gene biomarker combined with clinical characteristics was used as variables to develop and validate a nomogram predictive model based on 379 patients with complete clinical data from TCGA (Among 470 cases, 91 cases with missing clinical data were excluded from the study), which were randomly divided into the training set II (n = 189) and validation set II (n = 190). Area under the curve (AUC), concordance index (C-index), calibration curve, and Kaplan-Meier estimate were used to assess predictive performance of the nomogram model.

Results

Four genes, i.e., CLEC7A, CLEC10A, HAPLN3, and HCP5 comprise an immune-related prognostic biomarker. The predictive performance of the biomarker was validated using tROC and log-rank test in the training set I (n = 224, 5-year AUC of 0.683), validation set I (n = 225, 5-year AUC of 0.644), and test set I (n = 210, 5-year AUC of 0.645). The biomarker was also significantly associated with improved survival in the training set (P < 0.01), validation set (P < 0.05), and test set (P < 0.001), respectively. In addition, a nomogram combing the four-gene biomarker and six clinical factors for predicting survival in melanoma was developed in the training set II (n = 189), and validated in the validation set II (n = 190), with a concordance index of 0.736 ± 0.041 and an AUC of 0.832 ± 0.071.

Conclusion

We developed and validated a nomogram predictive model combining a four-gene biomarker and six clinical factors for melanoma patients, which could facilitate risk stratification and treatment planning.

The role of tumor heterogeneity in immune-tumor interactions

The development of cancer stems from genetic instability and changes in genomic sequences, and hence, the heterogeneity exhibited by tumors is integral to the nature of cancer itself. Tumor heterogeneity can be further altered by factors that are not cancer cell intrinsic, i.e., by the microenvironment, including the patient's immune responses to tumors and administered therapies (immunotherapies, chemotherapies, and/or radiation therapies). The focus of this review is the impact of tumor heterogeneity on the interactions between immune cells and the tumor, taking into account that heterogeneity can exist at several levels. These levels include heterogeneity within an individual tumor, within an individual patient (particularly between the primary tumor and metastatic lesions), among the subtypes of a specific type of cancer, or within cancers that originate from different tissues. Because of the potential for immunity (either the natural immune system or via immunotherapeutics) to halt the progression of cancer, major clinical significance exists in understanding the impact of tumor heterogeneity on the associations between immune cells and tumor cells. Increased knowledge of why, whether, and how immune-tumor interactions occur provides the means to guide these interactions and improve outcomes for patients.

Radiotherapy, immunotherapy, and the tumour microenvironment: Turning an immunosuppressive milieu into a therapeutic opportunity

Immune checkpoint blockade (ICB) has revolutionised the treatment of solid tumours, yet most patients do not derive a clinical benefit. Resistance to ICB is often contingent on the tumour microenvironment (TME) and modulating aspects of this immunosuppressive milieu is a goal of combination treatment approaches. Radiation has been used for over a century in the management of cancer with more than half of all cancer patients receiving radiotherapy. Here, we outline the rationale behind combining radiotherapy with ICB, a potential synergy through mutually beneficial remodelling of the TME. We discuss the pleiotropic effects radiation has on the TME including immunogenic cell death, activation of cytosolic DNA sensors, remodelling the stroma and vasculature, and paradoxical infiltration of both anti-tumour and suppressive immune cell populations. These events depend on the radiation dose and fractionation and optimising these parameters will be key to develop safe and effective combination regimens. Finally, we highlight ongoing efforts that combine radiation, immunotherapy and inhibitors of DNA damage response, which can help achieve a favourable equilibrium between the immunogenic and tolerogenic effects of radiation on the immune microenvironment.

Cancer stem cells, epigenetics, tumor microenvironment and future therapeutics in cutaneous malignant melanoma: a review

This review provides an overview of the current understanding of the ontogeny and biology of melanoma stem cells in cutaneous malignant melanoma. This article also summarizes and evaluates the current knowledge of the underlying epigenetic mechanisms, the regulation of melanoma progress by the tumor microenvironment as well as the therapeutic implications and applications of these novel insights, in the setting of personalized medicine. Unraveling the complex ecosystem of cutaneous malignant melanoma and the interplay between its components, aims to provide novel insights into the establishment of efficient therapeutic strategies.

Metastatic melanoma: therapeutic agents in preclinical and early clinical development

Introduction: Advanced melanoma historically had a very poor outcome but targeted therapies and immune checkpoint inhibitors (IC) have changed the course of the disease and made durable responses possible. However, most patients will develop progressive disease, so further strategies to overcome treatment resistance are needed. Areas covered: Current treatment strategies and landmark trials are discussed. Novel targeted agents, immune checkpoint inhibitors, and further immune-modulatory drugs, cancer vaccines and tumor infiltrating lymphocytes and their potential role in the treatment of melanoma are described. Current trials investigating these emerging agents and treatment strategies were searched for on ClinicalTrials.gov and are presented on the background of the current literature explaining the rationale for employing these new agents and strategies. Combinations of tumor-directed agents with those causing immune augmentation as well as a new adjuvant and neoadjuvant strategies are discussed. Expert opinion: Questions regarding treatment combination, personalization, and sequence of treatment will become increasingly important and will be guided by new biomarkers. New treatment settings will broaden the patient selection and will highlight the need for further discussions regarding toxicity in long-term survivorship.

National Cancer Institute Think-Tank Meeting Report on Proteomic Cartography and Biomarkers at the Single-Cell Level: Interrogation of Premalignant Lesions

A Think-Tank Meeting was convened by the National Cancer Institute (NCI) to solicit experts' opinion on the development and application of multiomic single-cell analyses, and especially single-cell proteomics, to improve the development of a new generation of biomarkers for cancer risk, early detection, diagnosis, and prognosis as well as to discuss the discovery of new targets for prevention and therapy. It is anticipated that such markers and targets will be based on cellular, subcellular, molecular, and functional aberrations within the lesion and within individual cells. Single-cell proteomic data will be essential for the establishment of new tools with searchable and scalable features that include spatial and temporal cartographies of premalignant and malignant lesions. Challenges and potential solutions that were discussed included (i) The best way/s to analyze single-cells from fresh and preserved tissue; (ii) Detection and analysis of secreted molecules and from single cells, especially from a tissue slice; (iii) Detection of new, previously undocumented cell type/s in the premalignant and early stage cancer tissue microenvironment; (iv) Multiomic integration of data to support and inform proteomic measurements; (v) Subcellular organelles-identifying abnormal structure, function, distribution, and location within individual premalignant and malignant cells; (vi) How to improve the dynamic range of single-cell proteomic measurements for discovery of differentially expressed proteins and their post-translational modifications (PTM); (vii) The depth of coverage measured concurrently using single-cell techniques; (viii) Quantitation - absolute or semiquantitative? (ix) Single methodology or multiplexed combinations? (x) Application of analytical methods for identification of biologically significant subsets; (xi) Data visualization of N-dimensional data sets; (xii) How to construct intercellular signaling networks in individual cells within premalignant tumor microenvironments (TME); (xiii) Associations between intrinsic cellular processes and extrinsic stimuli; (xiv) How to predict cellular responses to stress-inducing stimuli; (xv) Identification of new markers for prediction of progression from precursor, benign, and localized lesions to invasive cancer, based on spatial and temporal changes within individual cells; (xvi) Identification of new targets for immunoprevention or immunotherapy-identification of neoantigens and surfactome of individual cells within a lesion.

Development of a minimal physiologically-based pharmacokinetic/pharmacodynamic model to characterize target cell depletion and cytokine release for T cell-redirecting bispecific agents in humans

T cell-redirecting bispecific antibodies (bsAbs) are highly potent tumor-killing molecules. Following bsAb mediated engagement with target cells, T cells get activated and kill target cells while inducing cytokine release, which at higher levels may lead to life-threatening cytokine release syndrome (CRS). Clinical evidence suggests that CRS can be mitigated by implementing a stepwise dosing strategy. Here, we developed a mechanism-based minimal physiologically-based pharmacokinetic/pharmacodynamic (mPBPK/PD) model using reported preclinical and clinical data from blinatumomab. The mPBPK/PD model reasonably captured blinatumomab PK and B cell depletion profiles in blood and in various tissue sites of action (i.e., red marrow perivascular niche, spleen, and lymph nodes) in patients with non-Hodgkin's lymphoma (NHL) and acute lymphoblastic leukemia (ALL). Using interleukin 6 (IL-6) as an example, our model quantitatively characterized the mitigation of cytokine release by a blinatumomab 5-15-60 µg/m²/day stepwise dosing regimen comparing to a 60 µg/m²/day flat dose in NHL patients. Furthermore, by only modifying the system parameters specific for ALL patients, the mPBPK/PD model successfully predicted the mitigation of IL-6 release by a blinatumomab 5-15 µg/m²/day stepwise dosing regimen comparing to a 15 µg/m²/day flat dose. Our work provided a case example to show how mPBPK/PD model can be used to support the discovery and clinical development of T cell-redirecting bsAbs.

Hypoxic Gene Signature of Primary and Metastatic Melanoma Cell Lines: Focusing on HIF-1β and NDRG-1

Background:

Hypoxia is an important microenvironmental factor significantly affecting tumor proliferation and progression. The importance of hypoxia is, however, not well known in oncogenesis of malignant melanoma.

Aims:

To evaluate the difference of hypoxic gene expression signatures in primary melanoma cell lines and metastatic melanoma cell lines and to find the expression changes of hypoxia-related genes in primary melanoma cell lines at experimental hypoxic conditions.

Study Design:

Cell study.

Methods:

The mRNA expression levels of hypoxia-related genes in primary melanoma cell lines and metastatic melanoma cell lines and at experimental hypoxic conditions in primary melanoma cell lines were evaluated by using real-time polymerase chain reaction. Depending on the experimental data, we focused on two genes/proteins, the hypoxia-inducible factor-1 beta and the N-myc downstream regulated gene-1. The expression levels of the two proteins were investigated by immunohistochemistry methods in 16 primary and metastatic melanomas, 10 intradermal nevi, and a commercial tissue array comprised of 208 cores including 192 primary and metastatic malignant melanomas.

Results:

The real-time polymerase chain reaction study showed that hypoxic gene expression signature was different between metastatic melanoma cell lines and primary melanoma cell lines. Hypoxic experimental conditions significantly affected the hypoxic gene expression signature. In immunohistochemical study, N-myc downstream regulated gene-1 expression was found to be lower in primary cutaneous melanoma compared to in intradermal nevi (p=0.001). In contrast, the cytoplasmic expression of hypoxia-inducible factor-1 beta was higher in primary cutaneous melanoma than in intradermal nevi (p=0.001). We also detected medium/strong significant correlations between the two proteins studied in the study groups.

Conclusion:

Hypoxic response consists of closely related proteins in more complex pathways. These findings will shed light on hypoxic processes in melanoma and unlock a Pandora’s box for development of new therapeutic strategies.