Nanobody-based heavy chain antibodies and chimeric antibodies.

Nanobodies are the products of an intriguing invention in the evolution of immunoglobulins. This invention can be traced back approximately 45 million years to the common ancestor of extant dromedaries, camels, llamas, and alpacas. Next to conventional heterotetrameric H2L2 antibodies, these camelids produce homodimeric nanobody-based heavy chain antibodies, composed of shortened heavy chains that a lack the CH1 domain. Nanobodies against human target antigens are derived from immunized animals and/or synthetic nanobody libraries. As a robust, highly soluble, single immunoglobulin domain, a nanobody can easily be fused to another protein, for example to another nanobody and/or the hinge and constant domains of other immunoglobulins. Nanobody-derived heavy chain antibodies hold promise as a new form of immunotherapeutics.

Instability of the HLA-E peptidome of HIV presents a major barrier to therapeutic targeting.

Naturally occurring T cells that recognize microbial peptides via HLA-E, a nonpolymorphic HLA class Ib molecule, could provide the foundation for new universal immunotherapeutics. However, confidence in the biological relevance of putative ligands is crucial, given that the mechanisms by which pathogen-derived peptides can access the HLA-E presentation pathway are poorly understood. We systematically interrogated the HIV proteome using immunopeptidomic and bioinformatic approaches, coupled with biochemical and cellular assays. No HIV HLA-E peptides were identified by tandem mass spectrometry analysis of HIV-infected cells. In addition, all bioinformatically predicted HIV peptide ligands (>80) were characterized by poor complex stability. Furthermore, infected cell elimination assays using an affinity-enhanced T cell receptor bispecific targeted to a previously reported HIV Gag HLA-E epitope demonstrated inconsistent presentation of the peptide, despite normal HLA-E expression on HIV-infected cells. This work highlights the instability of the HIV HLA-E peptidome as a major challenge for drug development.

DNA Anchoring Strength Directly Correlates with Spherical Nucleic Acid-Based HPV E7 Cancer Vaccine Potency.

Vaccination for cancers arising from human papillomavirus (HPV) infection holds immense potential, yet clinical success has been elusive. Herein, we describe vaccination studies involving spherical nucleic acids (SNAs) incorporating a CpG adjuvant and a peptide antigen (E711-19) from the HPV-E7 oncoprotein. Administering the vaccine to humanized mice induced immunity-dependent on the oligonucleotide anchor chemistry (cholesterol vs (C12)9). SNAs containing a (C12)9-anchor enhanced IFN-γ production >200-fold, doubled memory CD8+ T-cell formation, and delivered more than twice the amount of oligonucleotide to lymph nodes in vivo compared to a simple admixture. Importantly, the analogous construct with a weaker cholesterol anchor performed similar to admix. Moreover, (C12)9-SNAs activated 50% more dendritic cells and generated T-cells cytotoxic toward an HPV+ cancer cell line, UM-SCC-104, with near 2-fold greater efficiency. These observations highlight the pivotal role of structural design, and specifically oligonucleotide anchoring strength (which correlates with overall construct stability), in developing efficacious therapeutic vaccines.

Construction of a prognostic model with CAFs for predicting the prognosis and immunotherapeutic response of lung squamous cell carcinoma.

Lung squamous cell carcinoma (LUSC) is one of the subtypes of lung cancer (LC) that contributes to approximately 25%-30% of its prevalence. Cancer-associated fibroblasts (CAFs) are key cellular components of the TME, and the large number of CAFs in tumour tissues creates a favourable environment for tumour development. However, the function of CAFs in the LUSC is complex and uncertain. First, we processed the scRNA-seq data and classified distinct types of CAFs. We also identified prognostic CAFRGs using univariate Cox analysis and conducted survival analysis. Additionally, we assessed immune cell infiltration in CAF clusters using ssGSEA. We developed a model with a significant prognostic correlation and verified the prognostic model. Furthermore, we explored the immune landscape of LUSC and further investigated the correlation between malignant features and LUSC. We identified CAFs and classified them into three categories: iCAFs, mCAFs and apCAFs. The survival analysis showed a significant correlation between apCAFs and iCAFs and LUSC patient prognosis. Kaplan-Meier analysis showed that patients in CAF cluster C showed a better survival probability compared to clusters A and B. In addition, we identified nine significant prognostic CAFRGs (CLDN1, TMX4, ALPL, PTX3, BHLHE40, TNFRSF12A, VKORC1, CST3 and ADD3) and subsequently employed multivariate Cox analysis to develop a signature and validate the model. Lastly, the correlation between CAFRG and malignant features indicates the potential role of CAFRG in promoting tumour angiogenesis, EMT and cell cycle alterations. We constructed a CAF prognostic signature for identifying potential prognostic CAFRGs and predicting the prognosis and immunotherapeutic response for LUSC. Our study may provide a more accurate prognostic assessment and immunotherapy targeting strategies for LUSC.

Identification of PPAR-related differentially expressed genes liver hepatocellular carcinoma and construction of a prognostic model based on data analysis and molecular docking.

Liver hepatocellular carcinoma (LIHC) is a significant global health issue with limited treatment options. In this study, single-cell RNA sequencing (scRNA-seq) data were used to explore the molecular mechanisms of LIHC development and identify potential targets for therapy. The expression of peroxisome proliferator-activated receptors (PPAR)-related genes was analysed in LIHC samples, and primary cell populations, including natural killer cells, T cells, B cells, myeloid cells, endothelial cells, fibroblasts and hepatocytes, were identified. Analysis of the differentially expressed genes (DEGs) between normal and tumour tissues revealed significant changes in gene expression in various cell populations. PPAR activity was evaluated using the 'AUCell' R software, which indicated higher scores in the normal versus the malignant hepatocytes. Furthermore, the DEGs showed significant enrichment of pathways related to lipid and glucose metabolism, cell development, differentiation and inflammation. A prognostic model was then constructed using 8 PPARs-related genes, including FABP5, LPL, ACAA1, PPARD, FABP4, PLIN1, HMGCS2 and CYP7A1, identified using least absolute shrinkage and selection operator-Cox regression analysis, and validated in the TCGA-LIHC, ICGI-LIRI and GSE14520 datasets. Patients with low-risk scores had better prognosis in all cohorts. Based on the expression of the eight model genes, two clusters of patients were identified by ConsensusCluster analysis. We also predicted small-molecule drugs targeting the model genes, and identified perfluorohexanesulfonic acid, triflumizole and perfluorononanoic acid as potential candidates. Finally, wound healing assay confirmed that PPARD can promote the migration of liver cancer cells. Overall, our study offers novel perspectives on the molecular mechanisms of LIHC and potential areas for therapeutic intervention, which may facilitate the development of more effective treatment regimens.

Metabolic Heterogeneity and Potential Immunotherapeutic Responses Revealed by Single-Cell Transcriptomics of Breast Cancer.

BACKGROUND: Breast cancer (BC) exhibits remarkable heterogeneity. However, the transcriptomic heterogeneity of BC at the single-cell level has not been fully elucidated. METHODS: We acquired BC samples from 14 patients. Single-cell RNA sequencing (scRNA-seq), bioinformatic analyses, along with immunohistochemistry (IHC) and immunofluorescence (IF) assays were carried out. RESULTS: According to the scRNA-seq results, 10 different cell types were identified. We found that Cancer-Associated Fibroblasts (CAFs) exhibited distinct biological functions and may promote resistance to therapy. Metabolic analysis of tumor cells revealed heterogeneity in glycolysis, gluconeogenesis, and fatty acid synthetase reprogramming, which led to chemotherapy resistance. Furthermore, patients with multiple metastases and progression were predicted to benefit from immunotherapy based on a heterogeneity analysis of T cells and tumor cells. CONCLUSIONS: Our findings provide a comprehensive understanding of the heterogeneity of BC, provide comprehensive insight into the correlation between cancer metabolism and chemotherapy resistance, and enable the prediction of immunotherapy responses based on T-cell heterogeneity.

A correlation study of adhesion G protein-coupled receptors as potential therapeutic targets for breast cancer.

BACKGROUND: Adhesion G protein-coupled receptors (aGPCRs), a distinctive subset of the G protein-coupled receptor (GPCR) superfamily, play crucial roles in various physiological and pathological processes, with implications in tumor development. Despite the global prevalence of breast cancer (BRCA), specific aGPCRs as potential drug targets or biomarkers remain underexplored. METHODS: UALCAN, GEPIA, Kaplan-Meier Plotter, MethSurv, cBiopportal, String, GeneMANIA, DAVID, Timer, Metascape, and qPCR were applied in this work. RESULTS: Our analysis revealed significantly increased transcriptional levels of ADGRB2, ADGRC1, ADGRC2, ADGRC3, ADGRE1, ADGRF2, ADGRF4, and ADGRL1 in BRCA primary tumors. Further analysis indicated a significant correlation between the expressions of certain aGPCRs and the pathological stage of BRCA. High expression of ADGRA1, ADGRF2, ADGRF4, ADGRG1, ADGRG2, ADGRG4, ADGRG6, and ADGRG7 was significantly correlated with poor overall survival (OS) in BRCA patients. Additionally, high expression of ADGRF2 and ADGRF4 indicated inferior recurrence-free survival (RFS) in BRCA patients. The RT-qPCR experiments also confirmed that the mRNA levels of ADGRF2 and ADGRF4 were higher in BRCA cells and tissues. Functional analysis highlighted the diverse roles of aGPCRs, encompassing GPCR signaling and metabolic energy reserves. Moreover, aGPCRs may exert influence or actively participate in the development of BRCA through their impact on immune status. CONCLUSION: aGPCRs, particularly ADGRF2 and ADGRF4, hold promise as immunotherapeutic targets and prognostic biomarkers in BRCA.

Spleen tyrosine kinase inhibitor R406 has both antiviral and anti-inflammatory effects on severe influenza A infection.

Death due to severe influenza is usually a fatal complication of a dysregulated immune response more than the acute virulence of an infectious agent. Although spleen tyrosine kinase (SYK) as a critical immune signaling molecule and therapeutic target plays roles in airway inflammation and acute lung injury, the role of SYK in influenza virus infection is not clear. Here, we investigated the antiviral and anti-inflammatory effects of SYK inhibitor R406 on influenza infection through a coculture model of human alveolar epithelial (A549) and macrophage (THP-1) cell lines and mouse model. The results showed that R406 treatment increased the viability of A549 and decreased the pathogenicity and mortality of lethal influenza virus in mice with influenza A infection, decreased levels of intracellular signaling molecules under the condition of inflammation during influenza virus infection. Combination therapy with oseltamivir further ameliorated histopathological damage in the lungs of mice and further delayed the initial time to death compared with R406 treatment alone. This study demonstrated that phosphorylation of SYK is involved in the pathogenesis of influenza, and R406 has antiviral and anti-inflammatory effects on the treatment of the disease, which may be realized through multiple pathways, including the already reported SYK/STAT/IFNs-mediated antiviral pathway, as well as TNF-α/SYK- and SYK/Akt-based immunomodulation pathway.

Chemical tools for the opioids.

The opioids are potent and widely used pain management medicines despite also possessing severe liabilities that have fueled the opioid crisis. The pharmacological properties of the opioids primarily derive from agonism or antagonism of the opioid receptors, but additional effects may arise from specific compounds, opioid receptors, or independent targets. The study of the opioids, their receptors, and the development of remediation strategies has benefitted from derivatization of the opioids as chemical tools. While these studies have primarily focused on the opioids in the context of the opioid receptors, these chemical tools may also play a role in delineating mechanisms that are independent of the opioid receptors. In this review, we describe recent advances in the development and applications of opioid derivatives as chemical tools and highlight opportunities for the future.

Identification of CRKL as an oncogenic biomarker for prognosis and immunotherapy in melanoma, and its potential molecular mechanism.

CRKL (CRK Like Proto-Oncogene) belongs to the Crk family and is a 39-kDa adapter protein that encodes SH2 and SH3 (src homologs) domains. To identify its oncogenic role in malignant melanoma, we investigated the association between CRKL and mutation, prognosis, tumor mutation burden, immune cell infiltration of melanoma, and explored the associations between CRKL and immunotherapy response. Our results showed that abnormal CRKL expression is associated with poor prognosis in melanoma and is significantly correlated with immune-activated pathways and processes, immune cell infiltrations, and expression of immunoregulators. Importantly, we found that CRKL expression is a predictive biomarker for anti-PD1 therapy response in melanoma patients. Furthermore, inhibiting CRKL expression in melanoma cell lines suppressed their proliferation and metastasis, as well as activated the pyroptosis-related pathway. Our study provides potential mechanisms of melanoma pathogenesis, which may suggest new avenues for targeted therapy in this disease.

Identification of the MMP family as therapeutic targets and prognostic biomarkers in the microenvironment of head and neck squamous cell carcinoma.

BACKGROUND: Head and Neck Squamous Cell Carcinoma is a malignant tumor with high morbidity and mortality. The MMP family plays an important role in tumor invasion and metastasis. However, the mechanistic value of the MMP family as a therapeutic target and prognostic biomarker in HNSC has not been fully elucidated. METHODS: Oncomine, UALCAN, GEPIA, cBioportal, GeneMANIA, STRING, DAVID6.8, TRRUST, TIMER and Linkedomics were used for analysis. RESULTS: The mRNA expression levels of MMP1, MMP3, ILF3, MMP7, MMP9, MMP10, MMP11, MMP12, MMP13 and MMP16 were higher in HNSC than those in normal tissues, while the mRNA expression level of MMP15 was reduced. The relative expression levels of MMP1 and MMP14 were the highest in HNSC tissues. A significant correlation was found between the expression of MMP3, MMP11, MMP25 and the pathological stage of HNSC patients. There was no significant associations between all the MMP family members expression levels and DFS. Increased mRNA levels of MMP1, MMP8 and MMP25 were significantly associated with OS. In addition, we investigated the genetic changes of the MMP family in HNSC and found that all the MMP family members had genetic changes, most of which were amplification and depth loss. In the analysis of neighbor gene network and protein interaction, we found that the MMP family interacted with 25 neighboring genes, except for ILF3, MMP19, MMP20, MMP21, MMP23B, MMP27 and MMP28, other MMP proteins interacted with each other. Functional enrichment analysis showed that the MMP family could be present in the extracellular matrix, regulate peptidase activity, and participate in the catabolism of collagen. Meanwhile, we identified the transcription factor targets and kinase targets of the MMP family and found that ATM and ATR were the two most common kinase targets in the MMP family. We also found a significant correlation between the MMP family expression and immune cell infiltration. Cox proportional risk model analysis showed that macrophages, MMP14, MMP16, and MMP19 were significantly associated with clinical outcomes in HNSC patients. CONCLUSION: The MMP family might serve as therapeutic target and prognostic biomarker in HNSC.

Molecular and cellular features of CTLA-4 blockade for relapsed myeloid malignancies after transplantation.

Relapsed myeloid disease after allogeneic stem cell transplantation (HSCT) remains largely incurable. We previously demonstrated the potent activity of immune checkpoint blockade in this clinical setting with ipilimumab or nivolumab. To define the molecular and cellular pathways by which CTLA-4 blockade with ipilimumab can reinvigorate an effective graft-versus-leukemia (GVL) response, we integrated transcriptomic analysis of leukemic biopsies with immunophenotypic profiling of matched peripheral blood samples collected from patients treated with ipilimumab following HSCT on the Experimental Therapeutics Clinical Trials Network 9204 trial. Response to ipilimumab was associated with transcriptomic evidence of increased local CD8+ T-cell infiltration and activation. Systemically, ipilimumab decreased naïve and increased memory T-cell populations and increased expression of markers of T-cell activation and costimulation such as PD-1, HLA-DR, and ICOS, irrespective of response. However, responding patients were characterized by higher turnover of T-cell receptor sequences in peripheral blood and showed increased expression of proinflammatory chemokines in plasma that was further amplified by ipilimumab. Altogether, these data highlight the compositional T-cell shifts and inflammatory pathways induced by ipilimumab both locally and systemically that associate with successful GVL outcomes. This trial was registered at www.clinicaltrials.gov as #NCT01822509.

Deciphering a cell death-associated signature for predicting prognosis and response to immunotherapy in lung squamous cell carcinoma.

BACKGROUND: Lung squamous cell carcinoma (LUSC) is a subtype of non-small cell carcinoma, accounting for about 30% of all lung cancers. Yet, the evaluation of prognostic outcome and therapy response of patients with LUSC remains to be resolved. This study aimed to explore the prognostic value of cell death pathways and develop a cell death-associated signature for predicting prognosis and guiding treatment in LUSC. METHODS: Transcriptome profiles and corresponding clinical information of LUSC patients were gathered from The Cancer Genome Atlas (TCGA-LUSC, n = 493) and Gene Expression Omnibus database (GSE74777, n = 107). The cell death-related genes including autophagy (n = 348), apoptosis (n = 163), and necrosis (n = 166) were retrieved from the Kyoto Encyclopedia of Genes and Genomes and Gene Ontology databases. In the training cohort (TCGA-LUSC), LASSO Cox regression was used to construct four prognostic signatures of respective autophagy, apoptosis, and necrosis pathway and genes of three pathways. After comparing the four signatures, the cell death index (CDI), the signature of combined genes, was further validated in the GSE74777 dataset. We also investigated the clinical significance of the CDI signature in predicting the immunotherapeutic response of LUSC patients. RESULTS: The CDI signature was significantly associated with the overall survival of LUSC patients in the training cohort (HR, 2.13; 95% CI, 1.62‒2.82; P < 0.001) and in the validation cohort (HR, 1.94; 95% CI, 1.01‒3.72; P = 0.04). The differentially expressed genes between the high- and low-risk groups contained cell death-associated cytokines and were enriched in immune-associated pathways. We also found a higher infiltration of naive CD4+ T cells, monocytes, activated dendritic cells, neutrophils, and lower infiltration of plasma cells and resting memory CD4+ T cells in the high-risk group. Tumor stemness indices, mRNAsi and mDNAsi, were both negatively correlated with the risk score of the CDI. Moreover, LUSC patients in the low-risk group are more likely to respond to immunotherapy than those in the high-risk group (P = 0.002). CONCLUSIONS: This study revealed a reliable cell death-associated signature (CDI) that closely correlated with prognosis and the tumor microenvironment in LUSC, which may assist in predicting the prognosis and response to immunotherapy for patients with LUSC.

Advances in the Delivery and Development of Epigenetic Therapeutics for the Treatment of Cancer.

Gene expression at the transcriptional level is altered by epigenetic modifications such as DNA methylation, histone methylation, and acetylation, which can upregulate, downregulate, or entirely silence genes. Pathological dysregulation of epigenetic processes can result in the development of cancer, neurological problems, metabolic disorders, and cardiovascular diseases. It is of promising therapeutic interest to find medications that target these epigenetic alterations. Despite the enormous amount of work that has been done in this area, very few molecules have been approved for clinical purposes. This article provides a comprehensive review of recent advances in epigenetic therapeutics for cancer, with a specific focus on emerging delivery and development strategies. Various delivery systems, including pro-drugs, conjugated molecules, nanoparticles (NPs), and liposomes, as well as remedial strategies such as combination therapies, and epigenetic editing, are being investigated to improve the efficacy and specificity of epigenetic drugs (epi-drugs). Furthermore, the challenges associated with available epi-drugs and the limitations of their translation into clinics have been discussed. Target selection, isoform selectivity, physiochemical properties of synthesized molecules, drug screening, and scalability of epi-drugs from preclinical to clinical fields are the major shortcomings that are addressed. This Review discusses novel strategies for the identification of new biomarkers, exploration of the medicinal chemistry of epigenetic modifiers, optimization of the dosage regimen, and design of proper clinical trials that will lead to better utilization of epigenetic modifiers over conventional therapies. The integration of these approaches holds great potential for improving the efficacy and precision of epigenetic treatments, ultimately benefiting cancer patients.

Immunotherapeutics in lung cancers: from mechanistic insight to clinical implications and synergistic perspectives.

BACKGROUND: Lung cancer is one of the highly lethal forms of cancer whose incidence has worldwide rapidly increased over the past few decades. About 80-85% of all lung cancer cases constitute non-small cell lung cancer (NSCLC), with adenocarcinoma, squamous cell carcinoma and large cell carcinoma as the main subtypes. Immune checkpoint inhibitors have led to significant advances in the treatment of a variety of solid tumors, significantly improving cancer patient survival rates. METHODS AND RESULTS: The cytotoxic drugs in combination with anti-PD-(L)1 antibodies is a new method that aims to reduce the activation of immunosuppressive and cancer cell prosurvival responses while also improving direct cancer cell death. The most commonly utilized immune checkpoint inhibitors for patients with non-small cell lung cancer are monoclonal antibodies (Atezolizumab, Cemiplimab, Ipilimumab, Pembrolizumab etc.) against PD-1, PD-L1, and CTLA-4. Among them, Atezolizumab (TECENTRIQ) and Cemiplimab (Libtayo) are engineered monoclonal anti programmed death ligand 1 (PD-L1) antibodies that inhibit binding of PD-L1 to PD-1 and B7.1. As a result, T-cell proliferation and cytokine synthesis are inhibited leading to restoring the immune homeostasis to fight cancer cells. CONCLUSIONS: In this review article, the path leading to the introduction of immunotherapeutic options in lung cancer treatment is described, with analyzing the benefits and shortages of the current immunotherapeutic drugs. In addition, possibilities to co-administer immunotherapeutic agents with standard cancer treatment modalities are also considered.

The Clinical Significance of CD73 in Cancer.

The search for new and effective treatment targets for cancer immunotherapy is an ongoing challenge. Alongside the more established inhibitory immune checkpoints, a novel potential target is CD73. As one of the key enzymes in the purinergic signalling pathway CD73 is responsible for the generation of immune suppressive adenosine. The expression of CD73 is higher in tumours than in the corresponding healthy tissues and associated with a poor prognosis. CD73, mainly by the production of adenosine, is critical in the suppression of an adequate anti-tumour immune response, but also in promoting cancer cell proliferation, tumour growth, angiogenesis, and metastasis. The upregulation of CD73 and generation of adenosine by tumour or tumour-associated immune cells is a common resistance mechanism to many cancer treatments such as chemotherapy, radiotherapy, targeted therapy, and immunotherapy. Therefore, the inhibition of CD73 represents a new and promising approach to increase therapy efficacy. Several CD73 inhibitors have already been developed and successfully demonstrated anti-cancer activity in preclinical studies. Currently, clinical studies evaluate CD73 inhibitors in different therapy combinations and tumour entities. The initial results suggest that inhibiting CD73 could be an effective option to augment anti-cancer immunotherapeutic strategies. This review provides an overview of the rationale behind the CD73 inhibition in different treatment combinations and the role of CD73 as a prognostic marker.

Strategies to Overcome Resistance to Immune-Based Therapies in Osteosarcoma.

Improving the prognosis and cure rate of HGOSs (high-grade osteosarcomas) is an absolute need. Immune-based treatment approaches have been increasingly taken into consideration, in particular for metastatic, relapsed and refractory HGOS patients, to ameliorate the clinical results currently achieved. This review is intended to give an overview on the immunotherapeutic treatments targeting, counteracting or exploiting the different immune cell compartments that are present in the HGOS tumor microenvironment. The principle at the basis of these strategies and the possible mechanisms that HGOS cells may use to escape these treatments are presented and discussed. Finally, a list of the currently ongoing immune-based trials in HGOS is provided, together with the results that have been obtained in recently completed clinical studies. The different strategies that are presently under investigation, which are generally aimed at abrogating the immune evasion of HGOS cells, will hopefully help to indicate new treatment protocols, leading to an improvement in the prognosis of patients with this tumor.

Emerging Immunotherapy Approaches for Treating Prostate Cancer.

Immunotherapy has emerged as an important approach for cancer treatment, but its clinical efficacy has been limited in prostate cancer compared to other malignancies. This review summarizes key immunotherapy strategies under evaluation for prostate cancer, including immune checkpoint inhibitors, bispecific T cell-engaging antibodies, chimeric antigen receptor (CAR) T cells, therapeutic vaccines, and cytokines. For each modality, the rationale stemming from preclinical studies is discussed along with outcomes from completed clinical trials and strategies to improve clinical efficacy that are being tested in ongoing clinical trials. Imperative endeavors include biomarker discovery for patient selection, deciphering resistance mechanisms, refining cellular therapies such as CAR T cells, and early-stage intervention were reviewed. These ongoing efforts instill optimism that immunotherapy may eventually deliver significant clinical benefits and expand treatment options for patients with advanced prostate cancer.

Crosstalk between Mesenchymal Stem Cells and Cancer Stem Cells Reveals a Novel Stemness-Related Signature to Predict Prognosis and Immunotherapy Responses for Bladder Cancer Patients.

Mesenchymal stem cells (MSCs) and cancer stem cells (CSCs) maintain bladder cancer (BCa) stemness and facilitate the progression, metastasis, drug resistance, and prognosis. Therefore, we aimed to decipher the communication networks, develop a stemness-related signature (Stem. Sig.), and identify a potential therapeutic target. BCa single-cell RNA-seq datasets (GSE130001 and GSE146137) were used to identify MSCs and CSCs. Pseudotime analysis was performed by Monocle. Stem. Sig. was developed by analyzing the communication network and gene regulatory network (GRN) that were decoded by NicheNet and SCENIC, respectively. The molecular features of the Stem. Sig. were evaluated in TCGA-BLCA and two PD-(L)1 treated datasets (IMvigor210 and Rose2021UC). A prognostic model was constructed based on a 101 machine-learning framework. Functional assays were performed to evaluate the stem traits of the hub gene. Three subpopulations of MSCs and CSCs were first identified. Based on the communication network, the activated regulons were found by GRN and regarded as the Stem. Sig. Following unsupervised clustering, two molecular subclusters were identified and demonstrated distinct cancer stemness, prognosis, immunological TME, and response to immunotherapy. Two PD-(L)1 treated cohorts further validated the performance of Stem. Sig. in prognosis and immunotherapeutic response prediction. A prognostic model was then developed, and a high-risk score indicated a poor prognosis. Finally, the hub gene SLC2A3 was found exclusively upregulated in extracellular matrix-related CSCs, predicting prognosis, and shaping an immunosuppressive tumor microenvironment. Functional assays uncovered the stem traits of SLC2A3 in BCa by tumorsphere formation and western blotting. The Stem. Sig. derived from MSCs and CSCs can predict prognosis and response to immunotherapy for BCa. Besides, SLC2A3 may serve as a promising stemness target facilitating cancer effective management.

The immune subtypes and landscape of sarcomas.

BACKGROUND: Considering the molecular heterogeneity of sarcomas and their immunologically quiet character, immunotherapy (e.g., immune checkpoint inhibitors) plays a viable role in only a subset of these tumors. This study aimed to determine the immune subtypes (IMSs) of sarcomas for selecting suitable patients from an extremely heterogeneous population. RESULTS: By performing consensus clustering analysis of the gene expression profiles of 538 patients with sarcomas in online databases, we stratified sarcomas into three IMSs characterized by different immune cell features, tumor mutational burdens (TMBs), gene mutations, and clinical outcomes. IMS1 showed an immune "hot" and immunosuppressive phenotype, the highest frequencies of CSMD3 mutation but the lowest frequencies of HMCN1 and LAMA2 mutations; these patients had the worst progression-free survival (PFS). IMS2 was defined by a high TMB and more gene mutations, but had the lowest frequency of MND1 mutations. IMS3 displayed the highest MDN1 expression level and an immune "cold" phenotype, these patients had the worst PFS. Each subtype was associated with different expression levels of immunogenic cell death modulators and immune checkpoints. Moreover, we applied graph learning-based dimensionality reduction to the immune landscape and identified significant intra-cluster heterogeneity within each IMS. Finally, we developed and validated an immune gene signature with good prognostic performance. CONCLUSIONS: Our results provide a conceptual framework for understanding the immunological heterogeneity of sarcomas. The identification of immune-related subtypes may facilitate optimal selection of sarcoma patients who will respond to appropriate therapeutic strategies.