Correlation of tumor-infiltrating immune cells of melanoma with overall survival by immunogenomic analysis

Spatial transcriptomic analysis of tumour-immune cell interactions in melanoma arising from congenital melanocytic nevus

BACKGROUND

Studies on the interaction between tumour-infiltrating immune cells (TIICs) and tumour cells in melanoma arising from congenital melanocytic nevus (CMN) are lacking.

OBJECTIVE

The aim of this study was to determine the intratumoral immune landscape of TIICs and tumour cells during invasion and metastasis.

METHODS

Tissue specimens were obtained from patients with melanoma originating from CMN. Differential gene expression in melanoma cells and TIICs during invasion and metastasis was determined using spatial transcriptomics.

RESULTS

As invasion depth increased, the expression of LGALS3, known to induce tumour-driven immunosuppression, increased in melanoma cells. In T cells, the expression of genes that inhibit T-cell activation increased with increasing invasion depth. In macrophages, the expression of genes related to the anti-inflammatory M2 phenotype was upregulated with increasing invasion depth. Compared to primary tumour cells, melanoma cells in metastatic lesions showed upregulated expression of genes associated with cancer immune evasion, including AXL and EPHA2, which impede T-cell recruitment, and BST2, associated with M2 polarization. Furthermore, T cells showed increased expression of genes related to immunosuppression, and macrophages exhibited increased expression of genes associated with the M2 phenotype.

CONCLUSIONS

The interaction between melanomas arising from CMN and TIICs may be important for tumour progression and metastasis.

New insights into immune cells in cancer immunotherapy: from epigenetic modification, metabolic modulation to cell communication

Cancer is one of the leading causes of death worldwide, and more effective ways of attacking cancer are being sought. Cancer immunotherapy is a new and effective therapeutic method after surgery, radiotherapy, chemotherapy, and targeted therapy. Cancer immunotherapy aims to kill tumor cells by stimulating or rebuilding the body's immune system, with specific efficiency and high safety. However, only few tumor patients respond to immunotherapy and due to the complex and variable characters of cancer immune escape, the behavior and regulatory mechanisms of immune cells need to be deeply explored from more dimensions. Epigenetic modifications, metabolic modulation, and cell-to-cell communication are key factors in immune cell adaptation and response to the complex tumor microenvironment. They collectively determine the state and function of immune cells through modulating gene expression, changing in energy and nutrient demands. In addition, immune cells engage in complex communication networks with other immune components, which are mediated by exosomes, cytokines, and chemokines, and are pivotal in shaping the tumor progression and therapeutic response. Understanding the interactions and combined effects of such multidimensions mechanisms in immune cell modulation is important for revealing the mechanisms of immunotherapy failure and developing new therapeutic targets and strategies.

MET receptor serves as a promising target in melanoma brain metastases

The development of brain metastases hallmarks disease progression in 20-40% of melanoma patients and is a serious obstacle to therapy. Understanding the processes involved in the development and maintenance of melanoma brain metastases (MBM) is critical for the discovery of novel therapeutic strategies. Here, we generated transcriptome and methylome profiles of MBM showing high or low abundance of infiltrated Iba1high tumor-associated microglia and macrophages (TAMs). Our survey identified potential prognostic markers of favorable disease course and response to immune checkpoint inhibitor (ICi) therapy, among them APBB1IP and the interferon-responsive gene ITGB7. In MBM with high ITGB7/APBB1IP levels, the accumulation of TAMs correlated significantly with the immune score. Signature-based deconvolution of MBM via single sample GSEA revealed enrichment of interferon-response and immune signatures and revealed inflammation, stress and MET receptor signaling. MET receptor phosphorylation/activation maybe elicited by inflammatory processes in brain metastatic melanoma cells via stroma cell-released HGF. We found phospho-METY1234/1235 in a subset of MBM and observed a marked response of brain metastasis-derived cell lines (BMCs) that lacked druggable BRAF mutations or developed resistance to BRAF inhibitors (BRAFi) in vivo to MET inhibitors PHA-665752 and ARQ197 (tivantinib). In summary, the activation of MET receptor in brain colonizing melanoma cells by stromal cell-released HGF may promote tumor self-maintenance and expansion and might counteract ICi therapy. Therefore, therapeutic targeting of MET possibly serves as a promising strategy to control intracranial progressive disease and improve patient survival.

Comparative Study of the Immune Microenvironment in Heterotopic Tumor Models

The tumor microenvironment (TME) is pivotal in cancer progression and the response to immunotherapy. A "hot" tumor typically contains immune cells that promote anti-tumor immunity, predicting positive prognosis. "Cold" tumors lack immune cells, suggesting a poor outlook across various cancers. Recent research has focused on converting "cold" tumors into "hot" tumors to enhance the success of immunotherapy. A prerequisite for the studies of the TME is an accurate knowledge of the cell populations of the TME. This study aimed to describe the immune TME of lung and colorectal cancer and melanoma, focusing on lymphoid and myeloid cell populations. We induced heterotopic immunocompetent tumors in C57BL/6 mice, using KP and LLC (Lewis lung carcinoma) cells for lung cancer, MC38 cells for colorectal cancer, and B16-F10 cells for melanoma. Immune cell infiltration was analyzed using multicolor flow cytometry in single-cell suspensions after tumor excision. KP cell tumors showed an abundance of neutrophils and eosinophils; however, they contained much less adaptive immune cells, while LLC cell tumors predominated in monocytes, neutrophils, and monocyte-derived dendritic cells. Monocytes and neutrophils, along with a significant T cell infiltration, were prevalent in MC38 tumors. Lastly, B16-F10 tumors were enriched in macrophages, while showing only moderate T cell presence. In conclusion, our data provide a detailed overview of the immune TME of various heterotopic tumors, highlighting the variabilities in the immune cell profiles of different tumor entities. Our data may be a helpful basis when investigating new immunotherapies, and thus, this report serves as a helpful tool for preclinical immunotherapy research design.

Refining mutanome-based individualised immunotherapy of melanoma using artificial intelligence

Using the particular nature of melanoma mutanomes to develop medicines that activate the immune system against specific mutations is a game changer in immunotherapy individualisation. It offers a viable solution to the recent rise in resistance to accessible immunotherapy alternatives, with some patients demonstrating innate resistance to these drugs despite past sensitisation to these agents. However, various obstacles stand in the way of this method, most notably the practicality of sequencing each patient's mutanome, selecting immunotherapy targets, and manufacturing specific medications on a large scale. With the robustness and advancement in research techniques, artificial intelligence (AI) is a potential tool that can help refine the mutanome-based immunotherapy for melanoma. Mutanome-based techniques are being employed in the development of immune-stimulating vaccines, improving current options such as adoptive cell treatment, and simplifying immunotherapy responses. Although the use of AI in these approaches is limited by data paucity, cost implications, flaws in AI inference capabilities, and the incapacity of AI to apply data to a broad population, its potential for improving immunotherapy is limitless. Thus, in-depth research on how AI might help the individualisation of immunotherapy utilising knowledge of mutanomes is critical, and this should be at the forefront of melanoma management.

A novel STAT3/ NFκB p50 axis regulates stromal-KDM2A to promote M2 macrophage-mediated chemoresistance in breast cancer

BACKGROUND

Lysine Demethylase 2A (KDM2A) plays a crucial role in cancer cell growth, differentiation, metastasis, and the maintenance of cancer stemness. Our previous study found that cancer-secreted IL-6 can upregulate the expression of KDM2A to promote further the transition of cells into cancer-associated fibroblasts (CAFs). However, the molecular mechanism by which breast cancer-secreted IL-6 regulates the expression of KDM2A remains unclear. Therefore, this study aimed to elucidate the underlying molecular mechanism of IL-6 in regulating KDM2A expression in CAFs and KDM2A-mediated paclitaxel resistance in breast cancer.

METHODS

The ectopic vector expression and biochemical inhibitor were used to analyze the KDM2A expression regulated by HS-578 T conditioned medium or IL-6 in mammary fibroblasts. Immunoprecipitation and chromatin immunoprecipitation assays were conducted to examine the interaction between STAT3 and NFκB p50. M2 macrophage polarization was assessed by analyzing M2 macrophage-specific markers using flow cytometry and RT-PCR. ESTIMATE algorithm was used to analyze the tumor microenvironment-dominant breast cancer samples from the TCGA database. The correlation between stromal KDM2A and CD163 + M2 macrophages was analyzed using the Pearson correlation coefficient. Cell viability was determined using trypan blue exclusion assay.

RESULTS

IL-6 regulates gene expression via activation and dimerization of STAT3 or collaboration of STAT3 and NFκB. However, STAT3, a downstream transcription factor of the IL-6 signaling pathway, was directly complexed with NFκB p50, not NFκB p65, to upregulate the expression of KDM2A in CAFs. Enrichment analysis of immune cells/stromal cells using TCGA-breast cancer RNA-seq data unveiled a positive correlation between stromal KDM2A and the abundance of M2 macrophages. CXCR2-associated chemokines secreted by KDM2A-expressing CAFs stimulated M2 macrophage polarization, which in turn secreted CCL2 to increase paclitaxel resistance in breast cancer cells by activating CCR2 signaling.

CONCLUSION

This study revealed the non-canonical molecular mechanism of IL-6 secreted by breast cancer upregulated KDM2A expression in CAFs via a novel STAT3/NFκB p50 axis, which STAT3 complexed with NFκB p50 in NFκB p50 binding motif of KDM2A promoter. KDM2A-expressing CAFs dominantly secreted the CXCR2-associated chemokines to promote M2 macrophage polarization and enhance paclitaxel resistance in breast cancer. These findings underscore the therapeutic potential of targeting the CXCR2 or CCR2 pathway as a novel strategy for paclitaxel-resistant breast cancer.

A pan-cancer analysis of pituitary tumor-transforming 3, pseudogene

BACKGROUND

Although evidence regarding pituitary tumor-transforming 3, pseudogene (PTTG3P) involvement in human cancers has been acquired via human and animal model-based molecular studies, there is a lack of pan-cancer analysis of this gene in human tumors.

METHODS

Tumor-causing effects of PTTG3P in 24 human tumors were explored using The Cancer Genome Atlas (TCGA) datasets from different bioinformatics databases and applying in silico tools such as The University of ALabama at Birmingham CANcer (UALCAN), Human Protein Atlas (HPA), Kaplan Meier (KM) plotter, cBioPortal, Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), Cytoscape, Database for Annotation, Visualization, and Integrated Discovery (DAVID), Tumor IMmune Estimation Resource (TIMER), and Comparative Toxicogenomics Database (CTD). Then, via in vitro experiments, including RNA sequencing (RNA-seq) and targeted bisulfite sequencing (bisulfite-seq), expression and promoter methylation levels of PTTG3P were verified in cell lines.

RESULTS

The PTTG3P expression was overexpressed across 23 malignancies and its overexpression was further found significantly effecting the overall survival (OS) durations of the esophageal carcinoma (ESCA) and head and neck cancer (HNSC) patients. This important information helps us to understand that PTTG3P plays a significant role in the development and progression of ESCA and HNSC. As for PTTG3P functional mechanisms, this gene along with its other binding partners was significantly concentrated in "Oocyte meiosis", "Cell cycle", "Ubiquitin mediated proteolysis", and "Progesterone-mediated oocyte maturation". Moreover, ESCA and HNSC tissues having the higher expression of PTTG3P were found to have lower promoter methylation levels of PTTG3P and higher CD8+ T immune cells level. Additionally, PTTG3P expression-regulatory drugs were also explored in the current manuscript for designing appropriate treatment strategies for ESCA and HNSC with respect to PTTG3P expression.

CONCLUSION

Our pan-cancer based findings provided a comprehensive account of the oncogenic role and utilization of PTTG3P as a novel molecular biomarker of ESCA and HNSC.

Melanoma Cell Reprogramming and Awakening of Antitumor Immunity as a Fingerprint of Hyper-Harmonized Hydroxylated Fullerene Water Complex (3HFWC) and Hyperpolarized Light Application In Vivo

In our recent study, we showed that in vitro treatment of melanoma cells with hyperpolarized light (HPL) as well as with the second derivative of fullerene, hyper-harmonized hydroxylated fullerene water complex (3HFWC) reduced viability of cells by decreasing their proliferative capacity and inducing senescence and reprogramming towards a normal, melanocytic phenotype. Therefore, we wanted to determine whether these effects persisted in vivo in the syngeneic mouse melanoma model with a combined treatment of HPL irradiation and 3HFWC per os. Our results demonstrated the potent antitumor effects of 3HFWC nanosubstance assisted by HPL irradiation. These effects were primarily driven by the stimulation of melanoma cell growth arrest, the establishment of a senescent phenotype, and melanocytic differentiation on the one hand, and the awakening of the antitumor immune response on the other. In addition, the combined treatment reduced the protumorigenic activity of immune cells by depleting T regulatory cells, myeloid-derived suppressors, and M2 macrophages. The support of the 3HFWC substance by HPL irradiation may be the axis of the new approach design based on tumor cell reprogramming synchronized with the mobilization of the host's protective immune response.

LPCAT1 acts as an independent prognostic biomarker correlated with immune infiltration in hepatocellular carcinoma

Background

Lysophosphatidylcholine acyltransferase 1 (LPCAT1) is overexpressed in multiple human tumors. However, the role of LPCAT1 in hepatocellular carcinoma (HCC) has not been understood. We aim to explore the relationships between LPCAT1 expression and prognosis, clinicopathological features, tumor microenvironment (TME), immune cell infiltration, immune checkpoint gene expression, and related signaling pathways in HCC. Furthermore, we also explored the relationship between LPCAT1 expression and drug sensitivity to HCC treatment.

Methods

The expression profiles were acquired from the Cancer Genome Atlas (TCGA) and the Human Protein Atlas (THPA). Immune status and infiltration in cancer tissues were explored using the single sample gene set enrichment analysis (ssGSEA) and CIBERSORT algorithm.

Results

LPCAT1 was overexpressed in HCC, and its expression was related to poor prognosis, LPCAT1 was an independent prognostic biomarker in HCC. Expression of LPCAT1 increased statistically with the increase of clinical stage and grade of HCC patients. GO and KEGG network analysis revealed that LPCAT1 positively associated molecules were mostly enriched in functions related to cell adhesion. The TME score of high-LPCAT1 group was significantly higher than that of low-LPCAT1 group. Immune infiltrating cells positively correlated with LPCAT1 expression were Macrophages M0, B cells memory, Dendritic cells activated, T cells regulatory and T cells gamma delta in HCC. We found a positive correlation between LPCAT1 and most immune checkpoint gene expression. The IC50 of 5-Fluorouracil, Gemcitabine, Mitomycin C, Sorafenib and Cabozantinib in patients with high-LPCAT1 expression was lower than that in patients with low-LPCAT1 expression. Our findings provide a wealth of information for further understanding of the biological functions and signaling pathways of LPCAT1 in HCC.

Conclusions

LPCAT1 is an independent prognostic biomarker and associated with tumor microenvironment, immune cell infiltration, immune checkpoint expression and drug sensitivity in hepatocellular carcinoma.

Unravelling the landscape of skin cancer through single-cell transcriptomics

The human skin is a complex organ that forms the first line of defense against pathogens and external injury. It is composed of a wide variety of cells that work together to maintain homeostasis and prevent disease, such as skin cancer. The exponentially rising incidence of skin malignancies poses a growing public health challenge, particularly when the disease course is complicated by metastasis and therapeutic resistance. Recent advances in single-cell transcriptomics have provided a high-resolution view of gene expression heterogeneity that can be applied to skin cancers to define cell types and states, understand disease evolution, and develop new therapeutic concepts. This approach has been particularly valuable in characterizing the contribution of immune cells in skin cancer, an area of great clinical importance given the increasing use of immunotherapy in this setting. In this review, we highlight recent skin cancer studies utilizing bulk RNA sequencing, introduce various single-cell transcriptomics approaches, and summarize key findings obtained by applying single-cell transcriptomics to skin cancer.

Bioinformatics Analysis and Structure of Gastric Cancer Prognosis Model Based on Lipid Metabolism and Immune Microenvironment

OBJECTIVES

The reprogramming of lipid metabolism is a new trait of cancers. However, the role of lipid metabolism in the tumor immune microenvironment (TIME) and the prognosis of gastric cancer remains unclear.

METHODS

Consensus clustering was applied to identify novel subgroups. ESTIMATE, TIMER, and MCPcounter algorithms were used to determine the TIME of the subgroups. The underlying mechanisms were elucidated using functional analysis. The prognostic model was established using the LASSO algorithm and multivariate Cox regression analysis.

RESULTS

Three molecular subgroups with significantly different survival were identified. The subgroup with relatively low lipid metabolic expression had a lower immune score and immune cells. The differentially expressed genes (DEGs) were concentrated in immune biological processes and cell migration via GO and KEGG analyses. GSEA analysis showed that the subgroups were mainly enriched in arachidonic acid metabolism. Gastric cancer survival can be predicted using risk models based on lipid metabolism genes.

CONCLUSIONS

The TIME of gastric cancer patients is related to the expression of lipid metabolism genes and could be used to predict cancer prognosis accurately.

SIRGs score may be a predictor of prognosis and immunotherapy response for esophagogastric junction adenocarcinoma

Background

Esophagogastric junction adenocarcinoma (EGJA) is a special malignant tumor with unknown biological behavior. PD-1 checkpoint inhibitors have been recommended as first-line treatment for advanced EGJA patients. However, the biomarkers for predicting immunotherapy response remain controversial.

Methods

We identified stromal immune-related genes (SIRGs) by ESTIMATE from the TCGA-EGJA dataset and constructed a signature score. In addition, survival analysis was performed in both the TCGA cohort and GEO cohort. Subsequently, we explored the differences in tumor-infiltrating immune cells, immune subtypes, immune-related functions, tumor mutation burden (TMB), immune checkpoint gene expression, immunophenoscore (IPS) between the high SIRGs score and low SIRGs score groups. Finally, two validation cohorts of patients who had accepted immunotherapy was used to verify the value of SIRGs score in predicting immunotherapy response.

Results

Eight of the SIRGs were selected by LASSO regression to construct a signature score (SIRGs score). Univariate and multivariate analyses in the TCGA and GEO cohort suggested that SIRGs score was an independent risk factor for the overall survival (OS) and it could increase the accuracy of clinical prediction models for survival. However, in the high SIRGs score group, patients had more immune cell infiltration, more active immune-related functions, higher immune checkpoint gene expression and higher IPS-PD1 and IPS-PD1-CTLA4 scores, which indicate a better response to immunotherapy. The external validation illustrated that high SIRGs score was significantly associated with immunotherapy response and immune checkpoint inhibitors (ICIs) can improve OS in patients with high SIRGs score.

Conclusion

The SIRGs score may be a predictor of the prognosis and immune-therapy response for esophagogastric junction adenocarcinoma.

High Expression of RRM1 Mediated by ncRNAs Correlates with Poor Prognosis and Tumor Immune Infiltration of Hepatocellular Carcinoma

Introduction

Hepatocellular carcinoma (HCC) is one of several tumors with poor prognosis and causes a significant social burden. A growing number of studies have shown that RRM1 plays a crucial role in the development and progression of multiple human cancers. However, the specific role and mechanism of RRM1 have not been fully defined in HCC.

Methods

TCGA and GTEx data were used for the first time to conduct a pan-cancer analysis of RRM1 expression and prognosis, and identified RRM1 as a possible potential oncogene in HCC. At the same time, a combination of analyses (including expression analysis, correlation analysis or survival analysis) identified non-coding RNAs (ncRNAs) that contribute to RRM1 overexpression.

Results

MIR4435-2HG/miR-22-3p and SNHG6/miR-101-3p were identified as the most promising RRM1 upstream ncRNA-related pathways in HCC. In addition, RRM1 levels were significantly and positively correlated with tumor immune cell infiltration, immune cell biomarker or immune checkpoint expression.

Conclusion

These results suggest that high expression of RRM1 mediated by ncRNAs is associated with poor prognosis and tumor immune infiltration in HCC.

Immune cell gene expression signatures in diffuse glioma are associated with IDH mutation status, patient outcome and malignant cell state, and highlight the importance of specific cell subsets in glioma biology

The tumor micro-environment (TME) plays an important role in various cancers, including gliomas. We estimated immune cell type-specific gene expression profiles in 3 large clinically annotated glioma datasets using CIBERSORTx and LM22/LM10 blood-based immune signatures and found that the proportions and estimated gene expression patterns of specific immune cells significantly varied according to IDH mutation status. When IDH-WT and IDH-MUT tumors were considered separately, cluster-of-cluster analyses of immune cell gene expression identified groups with distinct survival outcomes. We confirmed and extended these findings by applying a signature matrix derived from single-cell RNA-sequencing data derived from 19 glioma tumor samples to the bulk profiling data, validating findings from the LM22/LM10 results. To link immune cell signatures with outcomes in checkpoint therapy, we then showed a significant association of monocytic lineage cell gene expression clusters with patient survival and with mesenchymal gene expression scores. Integrating immune cell-based gene expression with previously described malignant cell states in glioma demonstrated that macrophage M0 abundance significantly correlated with mesenchymal state in IDH-WT gliomas, with evidence of a previously implicated role of the Oncostatin-M receptor and macrophages in the mesenchymal state. Among IDH-WT tumors that were enriched for the mesenchymal cell state, the estimated M0 macrophage expression signature coordinately also trended to a mesenchymal signature. We also examined IDH-MUT tumors stratified by 1p/19q status, showing that a mesenchymal gene expression signature the M0 macrophage fraction was enriched in IDH-MUT, non-codeleted tumors. Overall, these results highlight the biological and clinical significance of the immune cell environment related to IDH mutation status, patient prognosis and the mesenchymal state in diffuse gliomas.

Proximity of immune and tumor cells underlies response to BRAF/MEK-targeted therapies in metastatic melanoma patients

Acquired resistance to BRAF/MEK-targeted therapy occurs in the majority of melanoma patients that harbor BRAF mutated tumors, leading to relapse or progression and the underlying mechanism is unclear in many cases. Using multiplex immunohistochemistry and spatial imaging analysis of paired tumor sections obtained from 11 melanoma patients prior to BRAF/MEK-targeted therapy and when the disease progressed on therapy, we observed a significant increase of tumor cellularity in the progressed tumors and the close association of SOX10⁺ melanoma cells with CD8⁺ T cells negatively correlated with patient's progression-free survival (PFS). In the TCGA-melanoma dataset (n = 445), tumor cellularity exhibited additive prognostic value in the immune score signature to predict overall survival in patients with early-stage melanoma. Moreover, tumor cellularity prognoses OS independent of immune score in patients with late-stage melanoma.

Screening of Autophagy-Related Prognostic Genes in Metastatic Skin Melanoma

Cutaneous melanoma refers to a common skin tumor that is dangerous to health with a great risk of metastasis. Previous researches reported that autophagy is associated with the progression of cutaneous melanoma. Nevertheless, the role played by genes with a relation to autophagy (ARG) in the prediction of the course of metastatic cutaneous melanoma is still largely unknown. We observed that thirteen ARGs showed relations to overall survival (OS) in the Cox regression investigation based on a single variate. We developed 2-gene signature, which stratified metastatic cutaneous melanoma cases to groups at great and small risks. Cases suffering from metastatic cutaneous melanoma in the group at great risks had power OS compared with cases at small risks. The risk score, T phase, N phase, and age were proved to be individual factors in terms of the prediction of OS. Besides, the risk scores identified by the two ARGs were significantly correlated with metastatic cutaneous melanoma. Receiver operating characteristic (ROC) curve analysis demonstrated accurate predicting performance exhibited by the 2-gene signature. We also found that the immunization and stromal scores achieved by the group based on large risks were higher compared with those achieved by the group based on small risks. The metastatic cutaneous melanoma cases achieving the score based on small risks acquired greater expression of immune checkpoint molecules as compared with the high-risk group. In conclusion, the 2-ARG gene signature indicated a novel prognostic indicator for prognosis prediction of metastatic cutaneous melanoma, which served as an important tool for guiding the clinical treatment of cutaneous melanoma.

Immune-related lncRNA pairs as novel signature to predict prognosis and immune landscape in melanoma patients

To investigate immune-related long non-coding RNA (irlncRNA) signatures for predicting survival and the immune landscape in melanoma patients.We retrieved gene expression files from The Cancer Genome Atlas and the Genotype-Tissue Expression database and extracted all the long non-coding RNAs from the original data. Then, we selected immune-related long non-coding RNAs (irlncRNAs) using co-expression networks and screened differentially expressed irlncRNAs (DEirlncRNAs) to form pairs. We also performed univariate analysis and Least absolute shrinkage and selection operator (LASSO) penalized regression analysis to identify prognostic DEirlncRNA pairs, constructed receiver operating characteristic curves, compared the areas under the curves, and calculated the optimal cut-off point to divide patients into high-risk and low-risk groups. Finally, we performed multivariate Cox regression analysis, Kaplan-Meier (K-M) survival analysis, clinical correlation analysis, and investigated correlations with tumor-infiltrating immune cells, chemotherapeutic effectiveness, and immunogene biomarkers.A total of 297 DEirlncRNAs were identified, of which 16 DEirlncRNA pairs were associated with prognosis in melanoma. After grouping patients by the optimal cut-off value, we could better distinguish melanoma patients with different survival outcomes, clinical characteristics, tumor immune status changes, chemotherapeutic drug sensitivity, and specific immunogene biomarkers.The DEirlncRNA pairs showed potential as novel biomarkers to predict the prognosis of melanoma patients. Furthermore, these DEirlncRNA pairs could be used to evaluate treatment efficacy in the future.

Microdissection of the Bulk Transcriptome at Single-Cell Resolution Reveals Clinical Significance and Myeloid Cells Heterogeneity in Lung Adenocarcinoma

Background

Tumor infiltrating myeloid (TIM) cells constitute a vital element of the tumor microenvironment. The cell-type heterogeneity of TIM has yet to be fully investigated.

Methods

We used a time saving approach to generate a single-cell reference matrix, allowing quantification of cell-type proportions and cell-type-specific gene abundances in bulk RNA-seq data.

Results

Two distinct clusters, MSC1 and MSC2 (MSC subtype) were newly identified in lung adenocarcinoma (LUAD) patients, both significantly associated with overall survival and immune blockade therapy responses. Twenty myeloid cell types were detected. Thirteen of these had distinct enrichment patterns between MSC1 and MSC2. LAMP3+ dendritic cells, being a mature and transportable subtype of dendritic cell that may migrate to lymph nodes, were noted as associated with non-responsiveness to immunotargeted therapy. High infiltration level of IFIT3+ neutrophils was strongly related to the response to immune-targeted therapy and was seen to activate CD8+ T cells, partly through inflammasome activation. The infiltration levels of TIMP1+ macrophages and S100A8+ neutrophils were both significantly associated with poor prognosis. TIMP1+ macrophages were noted to recruit S100A8+ neutrophils via the CXCL5-CXCR2 axes and promote LUAD progression.

Conclusion

Altogether, we performed virtual microdissection of the bulk transcriptome at single-cell resolution and provided a promising TIM infiltration landscape that may shed new light on the development of immune therapy.

Effects of RNA methylation N6-methyladenosine regulators on malignant progression and prognosis of melanoma

Background

Melanoma is an extremely aggressive type of skin cancer and experiencing a expeditiously rising mortality in a current year. Exploring new potential prognostic biomarkers and therapeutic targets of melanoma are urgently needed. The ambition of this research was to identify genetic markers and assess prognostic performance of N6-methyladenosine (m6A) regulators in melanoma.

Methods

Gene expression data and corresponding clinical informations of melanoma patients as well as sequence data of normal controls are collected from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases. Quantitative real-time PCR (qRT-PCR) analysis was carried out to detect the RNA expression of IGF2BP3 in A375 cell line, melanoma tissues, and normal tissues. Western blot, cell proliferation, and migration assays were performed to assess the ability of IGF2BP3 in A375 cell line.

Results

Differently expressed m6A regulators between tumor samples and normal samples were analyzed. A three-gene prognostic signature including IGF2BP3, RBM15B, and METTL16 was constructed, and the risk score of this signature was identified to be an independent prognostic indicator for melanoma. In addition, IGF2BP3 was verified to promote melanoma cell proliferation and migration in vitro and associate with lymph node metastasis in clinical samples. Moreover, risk score and the expression of IGF2BP3 were positively associated with the infiltrating immune cells and these hub genes made excellent potential drug targets in melanoma.

Conclusion

We identified the genetic changes in m6A regulatory genes and constructed a three-gene risk signature with distinct prognostic value in melanoma. This research provided new insights into the epigenetic understanding of m6A regulators and novel therapeutic strategies in melanoma.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02163-9.

Identification of two immune subtypes in osteosarcoma based on immune gene sets

Osteosarcoma (OS) is a highly aggressive cancer with poor prognosis, which mainly occurs in teenagers. Recent studies have shown that tumor-infiltrating immune cells play an important role in the progression of OS. In the present study, we identified two immune subtypes of OS (referred to as high and low immune cell infiltration subtypes, respectively) based on immune-related gene sets using TARGET and GEO cohort datasets. Elevated immune scores, increased stromal scores, decreased tumor purities, and higher infiltration of CD8 + T cells and M1 macrophages were observed for the high immune cell infiltration subtype. Moreover, the high immune cell infiltration subtype was characterized by high expression of immune checkpoint molecules. Gene set enrichment analysis showed that "B cell receptor signaling pathway" and "T cell receptor signaling pathway" gene sets were enriched in the high immune cell infiltration subtype. In addition, patients in the high immune cell infiltration subtype had better prognosis than patients in the low immune cell infiltration subtype. Furthermore, differentially expressed genes were screened according to the two OS subtypes and a risk model was generated by multivariate Cox regression analysis to predict the prognosis of OS patients. These results in this study showed that OS patients could be divided into two immune subtypes and offered a novel two-gene risk signature to predict the prognosis of patients with OS.

Immune classification of osteosarcoma

Tumor immune microenvironment has been shown to be important in predicting the tumor progression and the outcome of treatments. This work aims to identify different immune patterns in osteosarcoma and their clinical characteristics. We use the latest and best performing deconvolution method, CIBERSORTx, to obtain the relative abundance of 22 immune cells. Then we cluster patients based on their estimated immune abundance and study the characteristics of these clusters, along with the relationship between immune infiltration and outcome of patients. We find that abundance of CD8 T cells, NK cells and M1 Macrophages have a positive association with prognosis, while abundance of γδ T cells, Mast cells, M0 Macrophages and Dendritic cells have a negative association with prognosis. Accordingly, the cluster with the lowest proportion of CD8 T cells, M1 Macrophages and highest proportion of M0 Macrophages has the worst outcome among clusters. By grouping patients with similar immune patterns, we are also able to suggest treatments that are specific to the tumor microenvironment.

Correlation of tumor-infiltrating immune cells of melanoma with overall survival by immunogenomic analysis

AIMS

Different types of tumor-infiltrating immune cells not only augment but also dampen antitumor immunity in the microenvironment of melanoma. Therefore, it is critical to provide an overview of tumor-infiltrating immune cells in melanoma and explore a novel strategy for immunotherapies.

METHODS

We analyzed the immune states of different stages in melanoma patients by the immune, stromal, and estimation of stromal and immune cells in malignant tumor tissues using expression data (ESTIMATE) scores. Immune cell types were identified by the estimating relative subsets of RNA transcripts (CIBERSORTx) algorithm in 471 melanoma and 324 healthy tissues. Moreover, we performed a gene set variation analysis (GSVA) to determine the differentially regulated pathways in the tumor microenvironment.

RESULTS

In melanoma cohorts, we found that ESTIMATE and immune scores were involved in survival or tumor clinical stage. Among the 22 immune cells, CD8⁺ T cells, M2 macrophages, and regulatory T cells (Tregs) showed significant differences using the CIBERSORTx algorithm. Furthermore, GSVA identified the immune cell-related pathways; the primary immunodeficiency pathway, intestinal immune network for IgA, and TGF-β pathways were identified as participants of the crosstalk in CD8⁺ T cells, Tregs, and M2 macrophages in the melanoma microenvironment.

CONCLUSION

These results reveal the cellular and molecular characteristics of immune cells in melanoma, providing a method for selecting targets of immunotherapies and promoting the efficacy of therapies for the treatment of melanoma.