Immunoproteasome expression is associated with better prognosis and response to checkpoint therapies in melanoma

Identification of key gene signatures for predicting chemo-immunotherapy efficacy in extensive-stage small-cell lung cancer using machine learning

OBJECTIVES

The lack of definitive biomarkers presents a significant challenge for chemo-immunotherapy in extensive-stage small-cell lung cancer (ES-SCLC). We aimed to identify key genes associated with chemo-immunotherapy efficacy in ES-SCLC through comprehensive gene expression analysis using machine learning (ML).

METHODS

A prospective multicenter cohort of patients with ES-SCLC who received first-line chemo-immunotherapy was analyzed. RNA sequencing was performed on tumor samples to assess gene expression levels. ML techniques were applied to identify key gene features associated with treatment efficacy. A panel of genes was then developed and validated using the nCounter system, and the model's performance in predicting 180-day progression-free survival (PFS) was evaluated.

RESULTS

A total of 93 patients were included in the analysis. ML-based gene selection identified a gene set comprising 83 genes from the comprehensive gene expression data. An nCounter panel was developed using these genes, and an ML model was developed based on their expression levels. In the validation set, the model achieved an accuracy of 0.93, precision of 1.00, a true positive rate of 0.83, and a true negative rate of 1.00. PFS was significantly longer in the high-efficacy group than in the low-efficacy group in the validation set (P < 0.001).

CONCLUSIONS

These findings provide a foundation for biomarker development in ES-SCLC and highlight the potential of this method as a cost-effective, simple, and rapid tool for assessing treatment efficacy in clinical practice.

Unlocking cancer vaccine potential: What are the key factors?

Cancer is a global health challenge, with changing demographics and lifestyle factors producing an increasing burden worldwide. Screening advancements are enabling earlier diagnoses, but current cancer immunotherapies only induce remission in a small proportion of patients and come at a high cost. Cancer vaccines may offer a solution to these challenges, but they have been mired by poor results in past decades. Greater understanding of tumor biology, coupled with the success of vaccine technologies during the COVID-19 pandemic, has reinvigorated cancer vaccine development. With the first signs of efficacy being reported, cancer vaccines may be beginning to fulfill their potential. Solid tumors, however, present different hurdles than infectious diseases. Combining insights from previous cancer vaccine clinical development and contemporary knowledge of tumor immunology, we ask: who are the 'right' patients, what are the 'right' targets, and which are the 'right' modalities to maximize the chances of cancer vaccine success?

Integration of Graph Neural Networks and multi-omics analysis identify the predictive factor and key gene for immunotherapy response and prognosis of bladder cancer

OBJECTIVE

The evaluation of the efficacy of immunotherapy is of great value for the clinical treatment of bladder cancer. Graph Neural Networks (GNNs), pathway analysis and multi-omics analysis have shown great potential in the field of cancer diagnosis and treatment.

METHODS

A GNNs model was constructed to predict the immunotherapy response and identify key pathways. Based on the genes of key pathways, bioinformatic methods were used to generate a simple linear scoring model, namely responseScore. The intrinsic mechanism of responseScore was explored from the perspectives of multi-omics analysis. The relationship between each gene involved in responseScore and prognosis was also explored. Transfection experiments with human bladder cancer cells were used to investigate the biological effects of PSMB9 gene.

RESULTS

The final GNNs model had an AUC of 0.785 on the training set and an AUC of 0.839 on the validation set. R-HSA-69620 and others were identified as key pathways. ResponseScore had a good performance in predicted the immunotherapy response and prognosis. Analysis results from genetic variation, pathways and tumor microenvironment, showed that responseScore was significantly associated with immune cell infiltration and anti-tumor immunity. The results of single-cell analysis showed that responseScore was closely related to the functional state of natural killer cells. Compared with the PCDH-NC group, cell migration and proliferation were significantly inhibited while cell apoptosis increased in the PCDH-PSMB9 group.

CONCLUSION

The GNNs predictive model and responseScore constructed in this study can reflect the immunotherapy response and prognosis of bladder cancer patients. ResponseScore can also reflect features such as tumor microenvironment, antitumor immunity, and natural killer cell function status in bladder cancer. PSMB9 was identified as a significant gene for prognosis. High expression of PSMB9 can inhibit bladder cancer cell migration and proliferation while increasing cell apoptosis.

Immunoproteasome Activation Expands the MHC Class I Immunopeptidome, Unmasks Neoantigens, and Enhances T-cell Anti-Myeloma Activity

Proteasomes generate antigenic peptides that are presented on the tumor surface to cytotoxic T-lymphocytes. Immunoproteasomes are highly specialized proteasome variants that are expressed at higher levels in antigen-presenting cells and contain replacements of the three constitutive proteasome catalytic subunits to generate peptides with a hydrophobic C-terminus that fit within the groove of MHC class I (MHC-I) molecules. A hallmark of cancer is the ability to evade immunosurveillance by disrupting the antigen presentation machinery and downregulating MHC-I antigen presentation. High-throughput screening was performed to identify compound A, a novel molecule that selectively increased immunoproteasome activity and expanded the number and diversity of MHC-I-bound peptides presented on multiple myeloma cells. Compound A increased the presentation of individual MHC-I-bound peptides by >100-fold and unmasked tumor-specific neoantigens on myeloma cells. Global proteomic integral stability assays determined that compound A binds to the proteasome structural subunit PSMA1 and promotes association of the proteasome activator PA28α/β (PSME1/PSME2) with immunoproteasomes. CRISPR/Cas9 silencing of PSMA1, PSME1, or PSME2 as well as treatment with immunoproteasome-specific suicide inhibitors abolished the effects of compound A on antigen presentation. Treatment of multiple myeloma cell lines and patient bone marrow-derived CD138+ cells with compound A increased the anti-myeloma activity of allogenic and autologous T cells. Compound A was well-tolerated in vivo and co-treatment with allogeneic T cells reduced the growth of myeloma xenotransplants in NOD/SCID gamma mice. Taken together, our results demonstrate the paradigm shifting impact of immunoproteasome activators to diversify the antigenic landscape, expand the immunopeptidome, potentiate T-cell-directed therapy, and reveal actionable neoantigens for personalized T-cell immunotherapy.

The Type 1 Diabetes-Associated Single Nucleotide Polymorphism rs1990760 in IFIH1 Is Associated with Increased Basal Type I IFNs and IFN-stimulated Gene Expression

Type 1 diabetes (T1D) is a chronic autoimmune disease that is caused by a combination of genetic and environmental risk factors. In this study, we sought to determine whether a known genetic risk factor, the rs1990760 single nucleotide polymorphism (SNP) (A946T) in IFIH1, resulted in a gain of function in the MDA5 protein and the effects of this mutation on the regulation of type I IFNs during infection with the diabetogenic virus coxsackievirus B3. We found that in cell lines overexpressing the risk variant IFIH1946T there was an elevated level of basal type I IFN signaling and increased basal IFN-stimulated gene expression. An investigation into the mechanism demonstrated that recombinant MDA5 with the A946T mutation had increased ATPase activity in vitro. We also assessed the effect of this SNP in primary human PBMCs from healthy donors to determine whether this SNP influenced their response to infection with coxsackievirus B3. However, we observed no significant changes in type I IFN expression or downstream induction of IFN-stimulated genes in PBMCs from donors carrying the risk allele IFIH1946T. These findings demonstrate the need for a deeper understanding of how mutations in T1D-associated genes contribute to disease onset in specific cellular contexts.

DHDH-mediated D-xylose metabolism induces immune evasion in triple-negative breast cancer

BACKGROUND

Although the prognosis of triple-negative breast cancer (TNBC) has significantly improved in the era of immunotherapy, many TNBC patients are resistant to therapies, and their disease progresses rapidly. Deciphering the metabolic mechanisms regulating anticancer immunity will provide new insights into therapeutic strategies for TNBC.

METHODS

In this study, we performed bioinformatics analysis in our multi-omics TNBC database and identified that a metabolic enzyme, dihydrodiol dehydrogenase (DHDH), might promote the phenotype of "cold tumor" in TNBC. The biological function of DHDH was verified by in vitro and in vivo functional experiments, and the potential molecular mechanism of DHDH promoting TNBC immune escape was further explored.

FINDINGS

Mechanistically, DHDH mediated the synthesis and depletion of the substrate D-xylose and inhibited the activation of the proteasome subunit beta type 9 (PSMB9) and further induction of the immune response. We demonstrated that D-xylose supplementation could enhance the proliferation of CD8+ T cells and the expression of cytotoxic markers against cocultured DHDH-wild type (WT) cells. Consistently, D-xylose supplementation in vivo promoted CD8+ T cell infiltration and the expression of cytotoxic markers and increased the sensitivity of DHDH-overexpressing tumors to immune checkpoint blockade (ICB).

CONCLUSIONS

Our findings reveal that a D-xylose-regulated PSMB9-dependent pathway governs tumor-intrinsic immunogenicity and, hence, the sensitivity to ICB, which may provide approaches to promote the "cold-to-hot" transition in TNBC.

FUNDING

This study was funded by the National Key Research and Development Plan of China, Shanghai Science and Technology Commission, National Natural Science Foundation of China, and China Postdoctoral Science Foundation.

Neoantigen prioritization based on antigen processing and presentation

Somatic mutations in tumor cells give rise to mutant proteins, fragments of which are often presented by MHC and serve as neoantigens. Neoantigens are tumor-specific and not expressed in healthy tissues, making them attractive targets for T-cell-based cancer immunotherapy. On the other hand, since most somatic mutations differ from patient to patient, neoantigen-targeted immunotherapy is personalized medicine and requires their identification in each patient. Computational algorithms and machine learning methods have been developed to prioritize neoantigen candidates. In fact, since the number of clinically relevant neoantigens present in a patient is generally limited, this process is like finding a needle in a haystack. Nevertheless, MHC presentation of neoantigens is not random but follows certain rules, and the efficiency of neoantigen detection may be further improved with technological innovations. In this review, we discuss current approaches to the detection of clinically relevant neoantigens, with a focus on antigen processing and presentation.

DNA-PK inhibition enhances neoantigen diversity and increases T cell responses to immunoresistant tumors

Effective antitumor T cell activity relies on the expression and MHC presentation of tumor neoantigens. Tumor cells can evade T cell detection by silencing the transcription of antigens or by altering MHC machinery, resulting in inadequate neoantigen-specific T cell activation. We identified the DNA-protein kinase inhibitor (DNA-PKi) NU7441 as a promising immunomodulator that reduced immunosuppressive proteins, while increasing MHC-I expression in a panel of human melanoma cell lines. In tumor-bearing mice, combination therapy using NU7441 and the immune adjuvants stimulator of IFN genes (STING) ligand and the CD40 agonist NU-SL40 substantially increased and diversified the neoantigen landscape, antigen-presenting machinery, and, consequently, substantially increased both the number and repertoire of neoantigen-reactive, tumor-infiltrating lymphocytes (TILs). DNA-PK inhibition or KO promoted transcription and protein expression of various neoantigens in human and mouse melanomas and induced sensitivity to immune checkpoint blockade (ICB) in resistant tumors. In patients, protein kinase, DNA-activated catalytic subunit (PRKDC) transcript levels were inversely correlated with MHC-I expression and CD8+ TILs but positively correlated with increased neoantigen loads and improved responses to ICB. These studies suggest that inhibition of DNA-PK activity can restore tumor immunogenicity by increasing neoantigen expression and presentation and broadening the neoantigen-reactive T cell population.

Identification of immunogenic HLA class I and II neoantigens using surrogate immunopeptidomes

Neoantigens arising from somatic mutations are tumor specific and induce antitumor host T cell responses. However, their sequences are individual specific and need to be identified for each patient for therapeutic applications. Here, we present a proteogenomic approach for neoantigen identification, named Neoantigen Selection using a Surrogate Immunopeptidome (NESSIE). This approach uses an autologous wild-type immunopeptidome as a surrogate for the tumor immunopeptidome and allows human leukocyte antigen (HLA)-agnostic identification of both HLA class I (HLA-I) and HLA class II (HLA-II) neoantigens. We demonstrate the direct identification of highly immunogenic HLA-I and HLA-II neoantigens using NESSIE in patients with colorectal cancer and endometrial cancer. Fresh or frozen tumor samples are not required for analysis, making it applicable to many patients in clinical settings. We also demonstrate tumor prevention by vaccination with selected neoantigens in a preclinical mouse model. This approach may benefit personalized T cell-mediated immunotherapies.

Immunoproteasome acted as immunotherapy 'coffee companion' in advanced carcinoma therapy

Immunoproteasome is a specialized form of proteasome which plays a crucial role in antigen processing and presentation, and enhances immune responses against malignant cells. This review explores the role of immunoproteasome in the anti-tumor immune responses, including immune surveillance and modulation of the tumor microenvironment, as well as its potential as a target for cancer immunotherapy. Furthermore, we have also discussed the therapeutic potential of immunoproteasome inhibitors, strategies to enhance antigen presentation and combination therapies. The ongoing trials and case studies in urology, melanoma, lung, colorectal, and breast cancers have also been summarized. Finally, the challenges facing clinical translation of immunoproteasome-targeted therapies, such as toxicity and resistance mechanisms, and the future research directions have been addressed. This review underscores the significance of targeting the immunoproteasome in combination with other immunotherapies for solid tumors and its potential broader applications in other diseases.

Spatially Informed Gene Signatures for Response to Immunotherapy in Melanoma

PURPOSE

We aim to improve the prediction of response or resistance to immunotherapies in patients with melanoma. This goal is based on the hypothesis that current gene signatures predicting immunotherapy outcomes show only modest accuracy due to the lack of spatial information about cellular functions and molecular processes within tumors and their microenvironment.

EXPERIMENTAL DESIGN

We collected gene expression data spatially from three cellular compartments defined by CD68+ macrophages, CD45+ leukocytes, and S100B+ tumor cells in 55 immunotherapy-treated melanoma specimens using Digital Spatial Profiling-Whole Transcriptome Atlas. We developed a computational pipeline to discover compartment-specific gene signatures and determine if adding spatial information can improve patient stratification.

RESULTS

We achieved robust performance of compartment-specific signatures in predicting the outcome of immune checkpoint inhibitors in the discovery cohort. Of the three signatures, the S100B signature showed the best performance in the validation cohort (N = 45). We also compared our compartment-specific signatures with published bulk signatures and found the S100B tumor spatial signature outperformed previous signatures. Within the eight-gene S100B signature, five genes (PSMB8, TAX1BP3, NOTCH3, LCP2, and NQO1) with positive coefficients predict the response, and three genes (KMT2C, OVCA2, and MGRN1) with negative coefficients predict the resistance to treatment.

CONCLUSIONS

We conclude that the spatially defined compartment signatures utilize tumor and tumor microenvironment-specific information, leading to more accurate prediction of treatment outcome, and thus merit prospective clinical assessment.

Enhancing the immunogenicity of Wilms tumor 1 epitope in mesothelioma cells with immunoproteasome inhibitors

The immunogenicity of cancer cells is influenced by several factors, including the expression of the major histocompatibility complex class I (MHC-I), antigen expression, and the repertoire of proteasome-produced epitope peptides. The malignant pleural mesothelioma cell line ACC-MEOS-4 (MESO-4) expresses high levels of MHC-I and Wilms tumor 1 (WT1) tumor antigens. Using a functional T cell reporter assay specific for the HLA-A*24:02 restricted WT1 epitope (WT1235, CMTWNQMNL), we searched for factors that augmented the immunogenicity of MESO-4, focusing on proteasomes, which have a central role in the antigen processing machinery. ONX-0914, a selective inhibitor of the immunoproteasome subunit β5i, enhanced immunogenicity dose-dependently at low concentrations without cytotoxicity. In addition, CD8+ T lymphocytes recognizing WT1 showed greater cytotoxicity against MESO-4 pre-treated with ONX-0914. MESO-4 expresses a standard proteasome (SP) and immunoproteasome (IP). Notably, IP has distinct catalytic activity from SP, favoring the generation of antigenic peptides with high affinity for MHC-I in antigen-presenting cells and cancer cells. In vitro, immunoproteasome digestion assay and mass spectrometry analysis showed that IP cleaved WT1235 internally after the hydrophobic residues. Importantly, this internal cleavage of the WT1235 epitope was mitigated by ONX-0914. These results suggest that ONX-0914 prevents the internal destructive cleavage of WT1235 by IP, thereby promoting the specific presentation of the WT1 epitope by MESO-4. In conclusion, selective IP inhibitors might offer a means to modulate cancer cell immunogenicity by directing the presentation of particular tumor epitopes.

Targeting Microglial Immunoproteasome: A Novel Approach in Neuroinflammatory-Related Disorders

It is widely acknowledged that the aging process is linked to the accumulation of damaged and misfolded proteins. This phenomenon is accompanied by a decrease in proteasome (c20S) activity, concomitant with an increase in immunoproteasome (i20S) activity. These changes can be attributed, in part, to the chronic neuroinflammation that occurs in brain tissues. Neuroinflammation is a complex process characterized by the activation of immune cells in the central nervous system (CNS) in response to injury, infection, and other pathological stimuli. In certain cases, this immune response becomes chronic, contributing to the pathogenesis of various neurological disorders, including chronic pain, Alzheimer's disease, Parkinson's disease, brain traumatic injury, and others. Microglia, the resident immune cells in the brain, play a crucial role in the neuroinflammatory response. Recent research has highlighted the involvement of i20S in promoting neuroinflammation, increased activity of which may lead to the presentation of self-antigens, triggering an autoimmune response against the CNS, exacerbating inflammation, and contributing to neurodegeneration. Furthermore, since i20S plays a role in breaking down accumulated proteins during inflammation within the cell body, any disruption in its activity could lead to a prolonged state of inflammation and subsequent cell death. Given the pivotal role of i20S in neuroinflammation, targeting this proteasome subtype has emerged as a potential therapeutic approach for managing neuroinflammatory diseases. This review delves into the mechanisms of neuroinflammation and microglia activation, exploring the potential of i20S inhibitors as a promising therapeutic strategy for managing neuroinflammatory disorders.

HDAC6 Inhibition Releases HR23B to Activate Proteasomes, Expand the Tumor Immunopeptidome and Amplify T-cell Antimyeloma Activity

Proteasomes degrade intracellular proteins to generate antigenic peptides that are recognized by the adaptive immune system and promote anticancer immunity. However, tumors subvert the antigen presentation machinery to escape immunosurveillance. We hypothesized that proteasome activation could concomitantly increase antigen abundance and diversity in multiple myeloma cells. High-throughput screens revealed that histone deacetylase 6 (HDAC6) inhibitors activated proteasomes to unmask neoantigens and amplify the tumor-specific antigenic landscape. Treatment of patient CD138+ cells with HDAC6 inhibitors significantly promoted the antimyeloma activity of autologous CD8+ T cells. Pharmacologic blockade and genetic ablation of the HDAC6 ubiquitin-binding domain released HR23B, which shuttles ubiquitinylated cargo to proteasomes, while silencing HDAC6 or HR23B in multiple myeloma cells abolished the effect of HDAC6 inhibitors on proteasomes, antigen presentation, and T-cell cytotoxicity. Taken together, our results demonstrate the paradigm-shifting translational impact of proteasome activators to expand the myeloma immunopeptidome and have revealed novel, actionable antigenic targets for T cell-directed immunotherapy.

SIGNIFICANCE

The elimination of therapy-resistant tumor cells remains a major challenge in the treatment of multiple myeloma. Our study identifies and functionally validates agents that amplify MHC class I-presented antigens and pave the way for the development of proteasome activators as immune adjuvants to enhance immunotherapeutic responses in patients with multiple myeloma.

PA200-Mediated Proteasomal Protein Degradation and Regulation of Cellular Senescence

Cellular senescence is closely related to DNA damage, proteasome inactivity, histone loss, epigenetic alterations, and tumorigenesis. The mammalian proteasome activator PA200 (also referred to as PSME4) or its yeast ortholog Blm10 promotes the acetylation-dependent degradation of the core histones during transcription, DNA repair, and spermatogenesis. According to recent studies, PA200 plays an important role in senescence, probably because of its role in promoting the degradation of the core histones. Loss of PA200 or Blm10 is a major cause of the decrease in proteasome activity during senescence. In this paper, recent research progress on the association of PA200 with cellular senescence is summarized, and the potential of PA200 to serve as a therapeutic target in age-related diseases is discussed.

Multikinase inhibitors modulate non-constitutive proteasome expression in colorectal cancer cells

Introduction: Proteasomes are multi-subunit protein complexes responsible for protein degradation in cells. Immunoproteasomes and intermediate proteasomes (together non-constitutive proteasomes) are specific forms of proteasomes frequently associated with immune response, antigen presentation, inflammation and stress. Expression of non-constitutive proteasome subunits has a prognostic value in several types of cancer. Thus, factors that modulate non-constitutive proteasome expression in tumors are of particular interest. Multikinase inhibitors (MKIs) demonstrate promising results in treatment of cancer. At the same time, their immunomodulatory properties and effects on non-constitutive proteasome expression in colorectal cancer cells are poorly investigated. Methods: Proteasome subunit expression in colorectal cancer was evaluated by bioinformatic analysis of available datasets. Two colorectal cancer cell lines, expressing fluorescent non-constitutive proteasomes were treated with multikinase inhibitors: regorafenib and sorafenib. The proteasome subunit expression was assessed by real-time PCR, Western blotting and flow cytometry. The proteasome activity was studied using proteasome activity-based probe and fluorescent substrates. Intracellular proteasome localization was revealed by confocal microscopy. Reactive oxygen species levels following treatment were determined in cells. Combined effect of proteasome inhibition and treatment with MKIs on viability of cells was estimated. Results: Expression of non-constitutive proteasomes is increased in BRAF-mutant colorectal tumors. Regorafenib and sorafenib stimulated the activity and synthesis of non-constitutive proteasomes in examined cell lines. MKIs induced oxidative stress and redistribution of proteasomes within cells. Sorafenib stimulated formation of cytoplasmic aggregates, containing proteolyticaly active non-constitutive proteasomes, while regorafenib had no such effect. MKIs caused no synergistic action when were combined with the proteasome inhibitor. Discussion: Obtained results indicate that MKIs might affect the crosstalk between cancer cells and immune cells via modulation of intracellular proteasome pool. Observed phenomenon should be considered when MKI-based therapy is applied.

Current Landscape of Cancer Immunotherapy: Harnessing the Immune Arsenal to Overcome Immune Evasion

Cancer immune evasion represents a leading hallmark of cancer, posing a significant obstacle to the development of successful anticancer therapies. However, the landscape of cancer treatment has significantly evolved, transitioning into the era of immunotherapy from conventional methods such as surgical resection, radiotherapy, chemotherapy, and targeted drug therapy. Immunotherapy has emerged as a pivotal component in cancer treatment, harnessing the body's immune system to combat cancer and offering improved prognostic outcomes for numerous patients. The remarkable success of immunotherapy has spurred significant efforts to enhance the clinical efficacy of existing agents and strategies. Several immunotherapeutic approaches have received approval for targeted cancer treatments, while others are currently in preclinical and clinical trials. This review explores recent progress in unraveling the mechanisms of cancer immune evasion and evaluates the clinical effectiveness of diverse immunotherapy strategies, including cancer vaccines, adoptive cell therapy, and antibody-based treatments. It encompasses both established treatments and those currently under investigation, providing a comprehensive overview of efforts to combat cancer through immunological approaches. Additionally, the article emphasizes the current developments, limitations, and challenges in cancer immunotherapy. Furthermore, by integrating analyses of cancer immunotherapy resistance mechanisms and exploring combination strategies and personalized approaches, it offers valuable insights crucial for the development of novel anticancer immunotherapeutic strategies.

Single cell atlas of human gastric muscle immune cells and macrophage-driven changes in idiopathic gastroparesis

Gastrointestinal immune cells, particularly muscularis macrophages (MM) interact with the enteric nervous system and influence gastrointestinal motility. Here we determine the human gastric muscle immunome and its changes in patients with idiopathic gastroparesis (IG). Single cell sequencing was performed on 26,000 CD45+ cells obtained from the gastric tissue of 20 subjects. We demonstrate 11 immune cell clusters with T cells being most abundant followed by myeloid cells. The proportions of cells belonging to the 11 clusters were similar between IG and controls. However, 9/11 clusters showed 578-11,429 differentially expressed genes. In IG, MM had decreased expression of tissue-protective and microglial genes and increased the expression of monocyte trafficking and stromal activating genes. Furthermore, in IG, IL12 mediated JAK-STAT signaling involved in the activation of tissue-resident macrophages and Eph-ephrin signaling involved in monocyte chemotaxis were upregulated. Patients with IG had a greater abundance of monocyte-like cells. These data further link immune dysregulation to the pathophysiology of gastroparesis.

Gemcitabine Modulates HLA-I Regulation to Improve Tumor Antigen Presentation by Pancreatic Cancer Cells

Pancreatic cancer is a lethal disease, harboring a five-year overall survival rate of only 13%. Current treatment approaches thus require modulation, with attention shifting towards liberating the stalled efficacy of immunotherapies. Select chemotherapy drugs which possess inherent immune-modifying behaviors could revitalize immune activity against pancreatic tumors and potentiate immunotherapeutic success. In this study, we characterized the influence of gemcitabine, a chemotherapy drug approved for the treatment of pancreatic cancer, on tumor antigen presentation by human leukocyte antigen class I (HLA-I). Gemcitabine increased pancreatic cancer cells' HLA-I mRNA transcripts, total protein, surface expression, and surface stability. Temperature-dependent assay results indicated that the increased HLA-I stability may be due to reduced binding of low affinity peptides. Mass spectrometry analysis confirmed changes in the HLA-I-presented peptide pool post-treatment, and computational predictions suggested improved affinity and immunogenicity of peptides displayed solely by gemcitabine-treated cells. Most of the gemcitabine-exclusive peptides were derived from unique source proteins, with a notable overrepresentation of translation-related proteins. Gemcitabine also increased expression of select immunoproteasome subunits, providing a plausible mechanism for its modulation of the HLA-I-bound peptidome. Our work supports continued investigation of immunotherapies, including peptide-based vaccines, to be used with gemcitabine as new combination treatment modalities for pancreatic cancer.

Converging and evolving immuno-genomic routes toward immune escape in breast cancer

The interactions between tumor and immune cells along the course of breast cancer progression remain largely unknown. Here, we extensively characterize multiple sequential and parallel multiregion tumor and blood specimens of an index patient and a cohort of metastatic triple-negative breast cancers. We demonstrate that a continuous increase in tumor genomic heterogeneity and distinct molecular clocks correlated with resistance to treatment, eventually allowing tumors to escape from immune control. TCR repertoire loses diversity over time, leading to convergent evolution as breast cancer progresses. Although mixed populations of effector memory and cytotoxic single T cells coexist in the peripheral blood, defects in the antigen presentation machinery coupled with subdued T cell recruitment into metastases are observed, indicating a potent immune avoidance microenvironment not compatible with an effective antitumor response in lethal metastatic disease. Our results demonstrate that the immune responses against cancer are not static, but rather follow dynamic processes that match cancer genomic progression, illustrating the complex nature of tumor and immune cell interactions.

Deciphering the tumor-suppressive role of PSMB9 in melanoma through multi-omics and single-cell transcriptome analyses

Skin cutaneous melanoma (SKCM) poses a significant challenge in skin cancers. Recent immunotherapy breakthroughs have revolutionized melanoma treamtment, yet tumor heterogeneity persists as an obstacle. Epigenetic modifications orchestrated by DNA methylation contributed to tumorigenesis, thus potentially unveiling melanoma prognosis. Here, we identified an interferon-gamma (IFN-g) sensitive subtype, which possesses favorable outcomes, robust infiltration CD8+T cells, and IFN-g score in bulk RNA-seq profile. Subsequently, we established an IFN-g sensitivity signature based on machine learning. We validated that PSMB9 is strongly correlated with immunotherapy response in both methylation and expression cohorts in this 10-probe signature. We assumed that PSMB9 acts as a putative melanoma suppressor, for its activation of CD8+T cell; capacity to modulate IFN-γ secretion; and dynamics altering IFN-g receptors in bulk tissue. We performed single-cell RNA-seq on immunotherapy patients' tissue to uncover the nuanced role of PSMB9 in activating CD8T + cells, enhancing IFN-g, and influencing malignant cells receptors and transcriptional factors. Overexpress PSMB9 in two SKCM cell lines to mimic the hypomethylated state to approve our conjecture. Strong cell proliferation and migration inhibition were detected on both cells, indicating that PSMB9 is present in tumor cells and that high expression is detrimental to tumor growth and migration. Overall, comprehensive integrated analysis shows that PSMB9 emerges as a vital prognostic marker, acting predictive potential regarding immunotherapy in melanoma. This evidence not only reveals the multifaceted impact of PSMB9 on both malignant and immune cells but also serves as a prospective target for undergoing immunotherapeutic strategies in the future.

LncRNA PSMB8-AS1 Instigates Vascular Inflammation to Aggravate Atherosclerosis

BACKGROUND

Increasing evidence suggests that long noncoding RNAs play significant roles in vascular biology and disease development. One such long noncoding RNA, PSMB8-AS1, has been implicated in the development of tumors. Nevertheless, the precise role of PSMB8-AS1 in cardiovascular diseases, particularly atherosclerosis, has not been thoroughly elucidated. Thus, the primary aim of this investigation is to assess the influence of PSMB8-AS1 on vascular inflammation and the initiation of atherosclerosis.

METHODS

We generated PSMB8-AS1 knockin and Apoe (Apolipoprotein E) knockout mice (Apoe-/-PSMB8-AS1KI) and global Apoe and proteasome subunit-β type-9 (Psmb9) double knockout mice (Apoe-/-Psmb9-/-). To explore the roles of PSMB8-AS1 and Psmb9 in atherosclerosis, we fed the mice with a Western diet for 12 weeks.

RESULTS

Long noncoding RNA PSMB8-AS1 is significantly elevated in human atherosclerotic plaques. Strikingly, Apoe-/-PSMB8-AS1KI mice exhibited increased atherosclerosis development, plaque vulnerability, and vascular inflammation compared with Apoe-/- mice. Moreover, the levels of VCAM1 (vascular adhesion molecule 1) and ICAM1 (intracellular adhesion molecule 1) were significantly upregulated in atherosclerotic lesions and serum of Apoe-/-PSMB8-AS1KI mice. Consistently, in vitro gain- and loss-of-function studies demonstrated that PSMB8-AS1 induced monocyte/macrophage adhesion to endothelial cells and increased VCAM1 and ICAM1 levels in a PSMB9-dependent manner. Mechanistic studies revealed that PSMB8-AS1 induced PSMB9 transcription by recruiting the transcription factor NONO (non-POU domain-containing octamer-binding protein) and binding to the PSMB9 promoter. PSMB9 (proteasome subunit-β type-9) elevated VCAM1 and ICAM1 expression via the upregulation of ZEB1 (zinc finger E-box-binding homeobox 1). Psmb9 deficiency decreased atherosclerotic lesion size, plaque vulnerability, and vascular inflammation in Apoe-/- mice in vivo. Importantly, endothelial overexpression of PSMB8-AS1-increased atherosclerosis and vascular inflammation were attenuated by Psmb9 knockout.

CONCLUSIONS

PSMB8-AS1 promotes vascular inflammation and atherosclerosis via the NONO/PSMB9/ZEB1 axis. Our findings support the development of new long noncoding RNA-based strategies to counteract atherosclerotic cardiovascular disease.

Antibody dependent cell-mediated cytotoxicity selection pressure induces diverse mechanisms of resistance

Targeted monoclonal antibody therapy has emerged as a powerful therapeutic strategy for cancer. However, only a minority of patients have durable responses and the development of resistance remains a major clinical obstacle. Antibody-dependent cell-mediated cytotoxicity (ADCC) represents a crucial therapeutic mechanism of action; however, few studies have explored ADCC resistance. Using multiple in vitro models of ADCC selection pressure, we have uncovered both shared and distinct resistance mechanisms. Persistent ADCC selection pressure yielded ADCC-resistant cells that are characterized by a loss of NK cell conjugation and this shared resistance phenotype is associated with cell-line dependent modulation of cell surface proteins that contribute to immune synapse formation and NK cell function. We employed single-cell RNA sequencing and proteomic screens to interrogate molecular mechanisms of resistance. We demonstrate that ADCC resistance involves upregulation of interferon/STAT1 and DNA damage response signaling as well as activation of the immunoproteasome. Here, we identify pathways that modulate ADCC sensitivity and report strategies to enhance ADCC-mediated elimination of cancer cells. ADCC resistance could not be reversed with combinatorial treatment approaches. Hence, our findings indicate that tumor cells utilize multiple strategies to inhibit NK cell mediated-ADCC. Future research and development of NK cell-based immunotherapies must incorporate plans to address or potentially prevent the induction of resistance.

Functional and spatial proteomics profiling reveals intra- and intercellular signaling crosstalk in colorectal cancer

Precision oncology approaches for patients with colorectal cancer (CRC) continue to lag behind other solid cancers. Functional precision oncology-a strategy that is based on perturbing primary tumor cells from cancer patients-could provide a road forward to personalize treatment. We extend this paradigm to measuring proteome activity landscapes by acquiring quantitative phosphoproteomic data from patient-derived organoids (PDOs). We show that kinase inhibitors induce inhibitor- and patient-specific off-target effects and pathway crosstalk. Reconstruction of the kinase networks revealed that the signaling rewiring is modestly affected by mutations. We show non-genetic heterogeneity of the PDOs and upregulation of stemness and differentiation genes by kinase inhibitors. Using imaging mass-cytometry-based profiling of the primary tumors, we characterize the tumor microenvironment (TME) and determine spatial heterocellular crosstalk and tumor-immune cell interactions. Collectively, we provide a framework for inferring tumor cell intrinsic signaling and external signaling from the TME to inform precision (immuno-) oncology in CRC.

FAK suppresses antigen processing and presentation to promote immune evasion in pancreatic cancer

OBJECTIVE

Immunotherapy for the treatment of pancreatic ductal adenocarcinoma (PDAC) has shown limited efficacy. Poor CD8 T-cell infiltration, low neoantigen load and a highly immunosuppressive tumour microenvironment contribute to this lack of response. Here, we aimed to further investigate the immunoregulatory function of focal adhesion kinase (FAK) in PDAC, with specific emphasis on regulation of the type-II interferon response that is critical in promoting T-cell tumour recognition and effective immunosurveillance.

DESIGN

We combined CRISPR, proteogenomics and transcriptomics with mechanistic experiments using a KrasG12Dp53R172H mouse model of pancreatic cancer and validated findings using proteomic analysis of human patient-derived PDAC cell lines and analysis of publicly available human PDAC transcriptomics datasets.

RESULTS

Loss of PDAC cell-intrinsic FAK signalling promotes expression of the immunoproteasome and Major Histocompatibility Complex class-I (MHC-I), resulting in increased antigen diversity and antigen presentation by FAK-/- PDAC cells. Regulation of the immunoproteasome by FAK is a critical determinant of this response, optimising the physicochemical properties of the peptide repertoire for high affinity binding to MHC-I. Expression of these pathways can be further amplified in a STAT1-dependent manner via co-depletion of FAK and STAT3, resulting in extensive infiltration of tumour-reactive CD8 T-cells and further restraint of tumour growth. FAK-dependent regulation of antigen processing and presentation is conserved between mouse and human PDAC, but is lost in cells/tumours with an extreme squamous phenotype.

CONCLUSION

Therapies aimed at FAK degradation may unlock additional therapeutic benefit for the treatment of PDAC through increasing antigen diversity and promoting antigen presentation.

EMT-induced immune evasion: connecting the dots from mechanisms to therapy

Epithelial-mesenchymal transition (EMT) is a dynamic program crucial for organismal development and tissue regeneration. Unfortunately, this program is often hijacked by epithelial tumors to facilitate metastasis. Beyond its role in cancer spread, EMT increases cancer cell survival by activating stem cell programs and bypassing apoptotic programs. Importantly, the capacity of EMT to enforce tumor progression by altering the tumor cell phenotype without triggering immune responses opens the intriguing possibility of a mechanistic link between EMT-driven cancers and immune evasion. Indeed, EMT has been acknowledged as a of driver immune evasion, but the mechanisms are still evolving. Here, we review recent insights into the influence of EMT on tumor immune evasion. Specifically, we focus on the mechanistic roles of EMT in immune escape as the basis that may provide a platform for innovative therapeutic approaches in advanced tumors. We summarize promising therapeutic approaches currently in clinical trials and trending preclinical studies aimed at reinvigorating the tumor microenvironment to create immune-permissive conditions that facilitates immune-mediated tumor clearance. We anticipate that this will assist researchers and pharmaceutical companies in understanding how EMT compromises the immune response, potentially paving the way for effective cancer therapies.

Proteasome inhibition potentiates Kv1.3 potassium channel expression as therapeutic target in drug-sensitive and -resistant human melanoma cells

Primary and acquired therapy resistance is a major problem in patients with BRAF-mutant melanomas being treated with BRAF and MEK inhibitors (BRAFI, MEKi). Therefore, development of alternative therapy regimes is still required. In this regard, new drug combinations targeting different pathways to induce apoptosis could offer promising alternative approaches. Here, we investigated the combination of proteasome and Kv1.3 potassium channel inhibition on chemo-resistant, BRAF inhibitor-resistant as well as sensitive human melanoma cells. Our experiments demonstrated that all analyzed melanoma cell lines were sensitive to proteasome inhibitor treatment at concentrations that are not toxic to primary human fibroblasts. To further reduce proteasome inhibitor-associated side effects, and to foster apoptosis, potassium channels, which are other targets to induce pro-apoptotic effects in cancer cells, were blocked. In support, combined exposure of melanoma cells to proteasome and Kv1.3 channel inhibitor resulted in synergistic effects and significantly reduced cell viability. On the molecular level, enhanced apoptosis correlated with an increase of intracellular Kv1.3 channels and pro-apoptotic proteins such as Noxa and Bak and a reduction of anti-apoptotic proteins. Thus, use of combined therapeutic strategies triggering different apoptotic pathways may efficiently prevent the outgrowth of drug-resistant and -sensitive BRAF-mutant melanoma cells. In addition, this could be the basis for an alternative approach to treat other tumors expressing mutated BRAF such as non-small-cell lung cancer.

Temporal genomic analysis of melanoma rejection identifies regulators of tumor immune evasion

Decreased intra-tumor heterogeneity (ITH) correlates with increased patient survival and immunotherapy response. However, even highly homogenous tumors may display variability in their aggressiveness, and how immunologic-factors impinge on their aggressiveness remains understudied. Here we studied the mechanisms responsible for the immune-escape of murine tumors with low ITH. We compared the temporal growth of homogeneous, genetically-similar single-cell clones that are rejected vs. those that are not-rejected after transplantation in-vivo using single-cell RNA sequencing and immunophenotyping. Non-rejected clones showed high infiltration of tumor-associated-macrophages (TAMs), lower T-cell infiltration, and increased T-cell exhaustion compared to rejected clones. Comparative analysis of rejection-associated gene expression programs, combined with in-vivo CRISPR knockout screens of candidate mediators, identified Mif (macrophage migration inhibitory factor) as a regulator of immune rejection. Mif knockout led to smaller tumors and reversed non-rejection-associated immune composition, particularly, leading to the reduction of immunosuppressive macrophage infiltration. Finally, we validated these results in melanoma patient data.

Integrative analysis reveals early epigenetic alterations in high-grade serous ovarian carcinomas

High-grade serous ovarian carcinoma (HGSOC) is the most lethal gynecological malignancy. To date, the profiles of gene mutations and copy number alterations in HGSOC have been well characterized. However, the patterns of epigenetic alterations and transcription factor dysregulation in HGSOC have not yet been fully elucidated. In this study, we performed integrative omics analyses of a series of stepwise HGSOC model cells originating from human fallopian tube secretory epithelial cells (HFTSECs) to investigate early epigenetic alterations in HGSOC tumorigenesis. Assay for transposase-accessible chromatin using sequencing (ATAC-seq), chromatin immunoprecipitation sequencing (ChIP-seq), and RNA sequencing (RNA-seq) methods were used to analyze HGSOC samples. Additionally, protein expression changes in target genes were confirmed using normal HFTSECs, serous tubal intraepithelial carcinomas (STICs), and HGSOC tissues. Transcription factor motif analysis revealed that the DNA-binding activity of the AP-1 complex and GATA family proteins was dysregulated during early tumorigenesis. The protein expression levels of JUN and FOSL2 were increased, and those of GATA6 and DAB2 were decreased in STIC lesions, which were associated with epithelial-mesenchymal transition (EMT) and proteasome downregulation. The genomic region around the FRA16D site, containing a cadherin cluster region, was epigenetically suppressed by oncogenic signaling. Proteasome inhibition caused the upregulation of chemokine genes, which may facilitate immune evasion during HGSOC tumorigenesis. Importantly, MEK inhibitor treatment reversed these oncogenic alterations, indicating its clinical effectiveness in a subgroup of patients with HGSOC. This result suggests that MEK inhibitor therapy may be an effective treatment option for chemotherapy-resistant HGSOC.

Multi-omics Characterization of Response to PD-1 Inhibitors in Advanced Melanoma

Immunotherapy improves the survival of patients with advanced melanoma, 40% of whom become long-term responders. However, not all patients respond to immunotherapy. Further knowledge of the processes involved in the response and resistance to immunotherapy is still needed. In this study, clinical paraffin samples from fifty-two advanced melanoma patients treated with anti-PD-1 inhibitors were assessed via high-throughput proteomics and RNA-seq. The obtained proteomics and transcriptomics data were analyzed using multi-omics network analyses based on probabilistic graphical models to identify those biological processes involved in the response to immunotherapy. Additionally, proteins related to overall survival were studied. The activity of the node formed by the proteins involved in protein processing in the endoplasmic reticulum and antigen presentation machinery was higher in responders compared to non-responders; the activity of the immune and inflammatory response node was also higher in those with complete or partial responses. A predictor for overall survival based on two proteins (AMBP and PDSM5) was defined. In summary, the response to anti-PD-1 therapy in advanced melanoma is related to protein processing in the endoplasmic reticulum, and also to genes involved in the immune and inflammatory responses. Finally, a two-protein predictor can define survival in advanced disease. The molecular characterization of the mechanisms involved in the response and resistance to immunotherapy in melanoma leads the way to establishing therapeutic alternatives for patients who will not respond to this treatment.

Antigen presentation in cancer - mechanisms and clinical implications for immunotherapy

Over the past decade, the emergence of effective immunotherapies has revolutionized the clinical management of many types of cancers. However, long-term durable tumour control is only achieved in a fraction of patients who receive these therapies. Understanding the mechanisms underlying clinical response and resistance to treatment is therefore essential to expanding the level of clinical benefit obtained from immunotherapies. In this Review, we describe the molecular mechanisms of antigen processing and presentation in tumours and their clinical consequences. We examine how various aspects of the antigen-presentation machinery (APM) shape tumour immunity. In particular, we discuss genomic variants in HLA alleles and other APM components, highlighting their influence on the immunopeptidomes of both malignant cells and immune cells. Understanding the APM, how it is regulated and how it changes in tumour cells is crucial for determining which patients will respond to immunotherapy and why some patients develop resistance. We focus on recently discovered molecular and genomic alterations that drive the clinical outcomes of patients receiving immune-checkpoint inhibitors. An improved understanding of how these variables mediate tumour-immune interactions is expected to guide the more precise administration of immunotherapies and reveal potentially promising directions for the development of new immunotherapeutic approaches.

Adaptation of the Tumor Antigen Presentation Machinery to Ionizing Radiation

Ionizing radiation (IR) can reprogram proteasome structure and function in cells and tissues. In this article, we show that IR can promote immunoproteasome synthesis with important implications for Ag processing and presentation and tumor immunity. Irradiation of a murine fibrosarcoma (FSA) induced dose-dependent de novo biosynthesis of the immunoproteasome subunits LMP7, LMP2, and Mecl-1, in concert with other changes in the Ag-presentation machinery (APM) essential for CD8+ T cell-mediated immunity, including enhanced expression of MHC class I (MHC-I), β2-microglobulin, transporters associated with Ag processing molecules, and their key transcriptional activator NOD-like receptor family CARD domain containing 5. In contrast, in another less immunogenic, murine fibrosarcoma (NFSA), LMP7 transcripts and expression of components of the immunoproteasome and the APM were muted after IR, which affected MHC-I expression and CD8+ T lymphocyte infiltration into NFSA tumors in vivo. Introduction of LMP7 into NFSA largely corrected these deficiencies, enhancing MHC-I expression and in vivo tumor immunogenicity. The immune adaptation in response to IR mirrored many aspects of the response to IFN-γ in coordinating the transcriptional MHC-I program, albeit with notable differences. Further investigations showed divergent upstream pathways in that, unlike IFN-γ, IR failed to activate STAT-1 in either FSA or NFSA cells while heavily relying on NF-κB activation. The IR-induced shift toward immunoproteasome production within a tumor indicates that proteasomal reprogramming is part of an integrated and dynamic tumor-host response that is specific to the stressor and the tumor and therefore is of clinical relevance for radiation oncology.

Genomic and transcriptomic analysis of checkpoint blockade response in advanced non-small cell lung cancer

Anti-PD-1/PD-L1 agents have transformed the treatment landscape of advanced non-small cell lung cancer (NSCLC). To expand our understanding of the molecular features underlying response to checkpoint inhibitors in NSCLC, we describe here the first joint analysis of the Stand Up To Cancer-Mark Foundation cohort, a resource of whole exome and/or RNA sequencing from 393 patients with NSCLC treated with anti-PD-(L)1 therapy, along with matched clinical response annotation. We identify a number of associations between molecular features and outcome, including (1) favorable (for example, ATM altered) and unfavorable (for example, TERT amplified) genomic subgroups, (2) a prominent association between expression of inducible components of the immunoproteasome and response and (3) a dedifferentiated tumor-intrinsic subtype with enhanced response to checkpoint blockade. Taken together, results from this cohort demonstrate the complexity of biological determinants underlying immunotherapy outcomes and reinforce the discovery potential of integrative analysis within large, well-curated, cancer-specific cohorts.

The proteasome regulator PSME4 modulates proteasome activity and antigen diversity to abrogate antitumor immunity in NSCLC

Immunotherapy revolutionized treatment options in cancer, yet the mechanisms underlying resistance in many patients remain poorly understood. Cellular proteasomes have been implicated in modulating antitumor immunity by regulating antigen processing, antigen presentation, inflammatory signaling and immune cell activation. However, whether and how proteasome complex heterogeneity may affect tumor progression and the response to immunotherapy has not been systematically examined. Here, we show that proteasome complex composition varies substantially across cancers and impacts tumor-immune interactions and the tumor microenvironment. Through profiling of the degradation landscape of patient-derived non-small-cell lung carcinoma samples, we find that the proteasome regulator PSME4 is upregulated in tumors, alters proteasome activity, attenuates presented antigenic diversity and associates with lack of response to immunotherapy. Collectively, our approach affords a paradigm by which proteasome composition heterogeneity and function should be examined across cancer types and targeted in the context of precision oncology.

Design and Computational Analysis of an MMP9 Inhibitor in Hypoxia-Induced Glioblastoma Multiforme

The main therapeutic difficulties in treating hypoxia-induced glioblastoma multiforme (GBM) are toxicity of current treatments and the resistance brought on by the microenvironment. More effective therapeutic alternatives are urgently needed to reduce tumor lethality. Hence, we screened plant-based natural product panels intending to identify novel drugs without elevating drug resistance. We explored GEO for the hypoxia GBM model and compared hypoxic genes to non-neoplastic brain cells. A total of 2429 differentially expressed genes expressed exclusively in hypoxia were identified. The functional enrichment analysis demonstrated genes associated with GBM, further PPI network was constructed, and biological pathways associated with them were explored. Seven webtools, including GEPIA2.0, TIMER2.0, TCGA-GBM, and GlioVis, were used to validate 32 hub genes discovered using Cytoscape tool in GBM patient samples. Four GBM-specific hypoxic hub genes, LYN, MMP9, PSMB9, and TIMP1, were connected to the tumor microenvironment using TIMER analysis. 11 promising hits demonstrated positive drug-likeness with nontoxic characteristics and successfully crossed blood-brain barrier and ADMET analyses. Top-ranking hits have stable intermolecular interactions with the MMP9 protein according to molecular docking, MD simulation, MM-PBSA, PCA, and DCCM analyses. Herein, we have reported flavonoids, 7,4'-dihydroxyflavan, (3R)-3-(4-hydroxybenzyl)-6-hydroxy-8-methoxy-3,4-dihydro-2H-1-benzopyran, and 4'-hydroxy-7-methoxyflavan, to inhibit MMP9, a novel hypoxia gene signature that could serve as a promising predictor in various clinical applications, including GBM diagnosis, prognosis, and targeted therapy.

The impact of immunopeptidomics: From basic research to clinical implementation

The immunopeptidome is the set of peptides presented by the major histocompatibility complex (MHC) molecules, in humans also known as the human leukocyte antigen (HLA), on the surface of cells that mediate T-cell immunosurveillance. The immunopeptidome is a sampling of the cellular proteome and hence it contains information about the health state of cells. The peptide repertoire is influenced by intra- and extra-cellular perturbations - such as in the case of drug exposure, infection, or oncogenic transformation. Immunopeptidomics is the bioanalytical method by which the presented peptides are extracted from biological samples and analyzed by high-performance liquid chromatography coupled to tandem mass spectrometry (MS), resulting in a deep qualitative and quantitative snapshot of the immunopeptidome. In this review, we discuss published immunopeptidomics studies from recent years, grouped into three main domains: i) basic, ii) pre-clinical and iii) clinical research and applications. We review selected fundamental immunopeptidomics studies on the antigen processing and presentation machinery, on HLA restriction and studies that advanced our understanding of various diseases, and how exploration of the antigenic landscape allowed immune targeting at the pre-clinical stage, paving the way to pioneering exploratory clinical trials where immunopeptidomics is directly implemented in the conception of innovative treatments for cancer patients.

Senescence Rewires Microenvironment Sensing to Facilitate Antitumor Immunity

Cellular senescence involves a stable cell-cycle arrest coupled to a secretory program that, in some instances, stimulates the immune clearance of senescent cells. Using an immune-competent liver cancer model in which senescence triggers CD8 T cell-mediated tumor rejection, we show that senescence also remodels the cell-surface proteome to alter how tumor cells sense environmental factors, as exemplified by type II interferon (IFNγ). Compared with proliferating cells, senescent cells upregulate the IFNγ receptor, become hypersensitized to microenvironmental IFNγ, and more robustly induce the antigen-presenting machinery-effects also recapitulated in human tumor cells undergoing therapy-induced senescence. Disruption of IFNγ sensing in senescent cells blunts their immune-mediated clearance without disabling the senescence state or its characteristic secretory program. Our results demonstrate that senescent cells have an enhanced ability to both send and receive environmental signals and imply that each process is required for their effective immune surveillance.

SIGNIFICANCE

Our work uncovers an interplay between tissue remodeling and tissue-sensing programs that can be engaged by senescence in advanced cancers to render tumor cells more visible to the adaptive immune system. This new facet of senescence establishes reciprocal heterotypic signaling interactions that can be induced therapeutically to enhance antitumor immunity. See related article by Marin et al., p. 410. This article is highlighted in the In This Issue feature, p. 247.

Increased expression of the immunoproteasome subunits PSMB8 and PSMB9 by cancer cells correlate with better outcomes for triple-negative breast cancers

Proteasome dependency is a feature of many cancers that can be targeted by proteasome inhibitors. For some cancer types, notably breast cancer and triple-negative breast cancer (TNBC), high mRNA expression of a modified form of the proteasome, called the immunoproteasome (ImP), correlates with better outcomes and higher expression of one ImP subunit was associated with slower tumor growth in a small patient cohort. While these findings are in line with an anti-tumoral role of the ImP in breast cancer, studies investigating ImP expression at the protein level in large patient cohorts are lacking. Furthermore, while ImPs can be found in both immune and non-immune cells, the cellular source is often ignored in correlative studies. In order to determine the impact of ImP expression on breast cancer outcomes, we assessed the protein expression and cellular source of the ImP subunits PSMB8 and PSMB9 in a cohort of 2070 patients. Our data show a clear correlation between high ImP expression and better outcomes, most notably for TNBC patients and when tumor cells rather than stromal or immune cells express PSMB8 or PSMB9. Our results therefore suggest that ImP expression by tumor cells could be used as prognostic markers of TNBC outcomes.

Mechanisms of resistance to immune checkpoint inhibitors in melanoma: What we have to overcome?

Marching into the second decade after the approval of ipilimumab, it is clear that immune checkpoint inhibitors (ICIs) have dramatically improved the prognosis of melanoma. Although the current edge is already high, with a 4-year OS% of 77.9% for adjuvant nivolumab and a 6.5-year OS% of 49% for nivolumab/ipilimumab combination in the metastatic setting, a high proportion of patients with advanced melanoma have no benefit from immunotherapy, or experience an early disease relapse/progression in the first few months of treatment, surviving much less. Reasonably, the primary and acquired resistance to ICIs has entered into the focus of clinical research with positive (e.g., nivolumab and relatlimab combination) and negative feedbacks (e.g., nivolumab with pegylated-IL2, pembrolizumab with T-VEC, nivolumab with epacadostat, and combinatorial triplets of BRAF/MEK inhibitors with immunotherapy). Many intrinsic (intracellular or intra-tumoral) but also extrinsic (systematic) events are considered to be involved in the development of this resistance to ICIs: i) melanoma cell immunogenicity (e.g., tumor mutational burden, antigen-processing machinery and immunogenic cell death, neoantigen affinity and heterogeneity, genomic instability, melanoma dedifferentiation and phenotypic plasticity), ii) immune cell trafficking, T-cell priming, and cell death evasion, iii) melanoma neovascularization, cellular TME components(e.g., T_regs, CAFs) and extracellular matrix modulation, iv) metabolic antagonism in the TME(highly glycolytic status, upregulated CD39/CD73/adenosine pathway, iDO-dependent tryptophan catabolism), v) T-cell exhaustion and negative immune checkpoints, and vi) gut microbiota. In the present overview, we discuss how these parameters compromise the efficacy of ICIs, with an emphasis on the lessons learned by the latest melanoma studies; and in parallel, we describe the main ongoing approaches to overcome the resistance to immunotherapy. Summarizing this information will improve the understanding of how these complicated dynamics contribute to immune escape and will help to develop more effective strategies on how anti-tumor immunity can surpass existing barriers of ICI-refractory melanoma.

Identification and validation of a TTN-associated immune prognostic model for skin cutaneous melanoma

TTN is the most commonly mutated gene in skin cutaneous melanoma (SKCM). Tumor mutational burden (TMB) can generate new antigens that regulate the recognition of T cells, which will significantly affect the prognosis of patients. The TTN gene has a long coding sequence and a high number of mutant sites, which allows SKCM patients to produce higher TMB and may influence the immune response. It has been found that the overall survival (OS) of SKCM patients with TTN mutation was significantly higher than that of wild-type patients. However, the effect of TTN mutation on the immune microenvironment of SKCM has not been fully investigated. Here, we systematically explored the relationship and potential mechanisms between TTN mutation status and the immune response. We first revealed that TTN mutated SKCM were significantly associated with four immune-related biological processes. Next, 115 immune genes differentially expressed between TTN mutation and wild-type SKCM patients were found to significantly affect the OS of SKCM patients. Then, we screened four immune-related genes (CXCL9, PSMB9, CD274, and FCGR2A) using LASSO regression analysis and constructed a TTN mutation-associated immune prognostic model (TM-IPM) to distinguish the SKCM patients with a high or low risk of poor prognosis, independent of multiple clinical characteristics. SKCM in the low-risk group highly expressed a large number of immune-related genes, and functional enrichment analysis of these genes showed that this group was involved in multiple immune processes and pathways. Furthermore, the nomogram constructed by TM-IPM with other clinicopathological parameters can provide a predictive tool for clinicians. Moreover, we found that CD8+ T cells were significantly enriched in the low-risk group. The expression level of immune checkpoints was higher in the low-risk group than in the high-risk group. Additionally, the response to chemotherapeutic agents was higher in the low-risk group than in the high-risk group, which may be related to the long survival in the low-risk group. Collectively, we constructed and validated a TM-IPM using four immune-related genes and analyzed the potential mechanisms of TM-IPM to predict patient prognosis and response to immunotherapy from an immunological perspective.

Pan-cancer analysis identifies proteasome 26S subunit, ATPase (PSMC) family genes, and related signatures associated with prognosis, immune profile, and therapeutic response in lung adenocarcinoma

Background: Proteasome 26S subunit, ATPase gene (PSMC) family members play a critical role in regulating protein degradation and are essential for tumor development. However, little is known about the integrative function and prognostic significance of the PSMC gene family members in lung cancer. Methods: First, we assessed the expression and prognostic features of six PSMC family members in pan-cancer from The Cancer Genome Atlas (TCGA) dataset. Hence, by focusing on the relationship between PSMC genes and the prognostic, genomic, and tumor microenvironment features in lung adenocarcinoma (LUAD), a PSMC-based prognostic signature was established using consensus clustering and multiple machine learning algorithms, including the least absolute shrinkage and selection operator (LASSO) Cox regression, CoxBoost, and survival random forest analysis in TCGA and GSE72094. We then validated it in three independent cohorts from GEO and estimated the correlation between risk score and clinical features: genomic features (alterations, tumor mutation burden, and copy number variants), immune profiles (immune score, TIDE score, tumor-infiltrated immune cells, and immune checkpoints), sensitivity to chemotherapy (GDSC, GSE42127, and GSE14814), and immunotherapy (IMvigor210, GSE63557, and immunophenoscore). Twenty-one patients with LUAD were included in our local cohort, and tumor samples were submitted for evaluation of risk gene and PD-L1 expression. Results: Nearly all six PSMC genes were overexpressed in pan-cancer tumor tissues; however, in LUAD alone, they were all significantly correlated with overall survival. Notably, they all shared a positive association with increased TMB, TIDE score, expression of immune checkpoints (CD276 and PVR), and more M1 macrophages but decreased B-cell abundance. A PSMC-based prognostic signature was established based on five hub genes derived from the differential expression clusters of PSMC genes, and it was used to dichotomize LUAD patients into high- and low-risk groups according to the median risk score. The area under the curve (AUC) values for predicting survival at 1, 3, and 5 years in the training cohorts were all >.71, and the predictive accuracy was also robust and stable in the GSE72094, GSE31210, and GSE13213 datasets. The risk score was significantly correlated with advanced tumor, lymph node, and neoplasm disease stages as an independent risk factor for LUAD. Furthermore, the risk score shared a similar genomic and immune feature as PSMC genes, and high-risk tumors exhibited significant genomic and chromosomal instability, a higher TIDE score but lower immune score, and a decreased abundance of B and CD8⁺ T cells. Finally, high-risk patients were suggested to be less sensitive to immunotherapy but had a higher possibility of responding to platinum-based chemotherapy. The LUAD samples from the local cohort supported the difference in the expression levels of these five hub genes between tumor and normal tissues and the correlation between the risk score and PD-L1 expression. Conclusion: Overall, our results provide deep insight into PSMC genes in LUAD, especially the prognostic effect and related immune profile that may predict therapeutic responses.

Analysis on methylation and expression of PSMB8 and its correlation with immunity and immunotherapy in lung adenocarcinoma

Aim: To find biomarkers for immunity and immunotherapy in lung adenocarcinoma (LUAD) through multiomics analysis. Materials & methods: The multiomics data of patients with LUAD were downloaded from the TCGA and GEO databases. CIBERSORT, quanTIseq, ESTIMATEScore, k-means clustering, gene set enrichment analysis, gene set variation analysis, immunophenoscore and logistic regression were used in this study. Results: PSMB8 HypoMet-HighExp group patients have more active immune-related pathways, more antitumor immune cells, less protumor immune cells, higher immunophenoscore and longer progression-free survival of immune checkpoint inhibitor therapy than HyperMet-LowExp group. In multivariate analysis, PSMB8 showed an independent value. Conclusion: The combination of DNA methylation and mRNA expression of PSMB8 could independently distinguish types of tumor immune microenvironment and predict programmed cell death protein 1/programmed cell death-ligand 1 inhibitors' effects in patients with LUAD.

The Expression of the Immunoproteasome Subunit PSMB9 Is Related to Distinct Molecular Subtypes of Uterine Leiomyosarcoma

Simple Summary

Uterine leiomyosarcoma (uLMS) is a rare, aggressive, and highly heterogeneous tumor. Knockout female mice for the catalytic subunit of the immunoproteasome PSMB9 develops spontaneous uLMS. In this study, we used molecular data from 3 non-related uLMS cohorts that were integrated and analyzed by proteotranscriptomics. We observed overexpression of the immunoproteasome pathway in uLMS, and then further classified the samples as low or high PSMB9 gene expression levels and we provide evidence that; (i) in the group high there is an enrichment of pathways related to the immune system and in the group low, the ECM formation; (ii) samples with high CD8+/PSMB9 ratio shows better OS; and (iii) the main regulator in the high group is IFNγ and in the low, the proto-oncogene SRC. These findings contribute to the understanding of potential therapeutic or prognostic markers in uLMS.

Abstract

Background: Uterine leiomyosarcoma (uLMS) are rare and malignant tumors that arise in the myometrium cells and whose diagnosis is based on histopathological features. Identifying diagnostic biomarkers for uLMS is a challenge due to molecular heterogeneity and the scarcity of samples. In vivo and in vitro models for uLMS are urgently needed. Knockout female mice for the catalytic subunit of the immunoproteasome PSMB9 (MIM:177045) develop spontaneous uLMS. This study aimed to analyze the role of PSMB9 in uLMS tumorigenesis and patient outcome. Methods: Molecular data from 3 non-related uLMS cohorts were integrated and analyzed by proteotranscriptomic using gene expression and protein abundance levels in 68 normal adjacent myometrium (MM), 66 uterine leiomyoma (LM), and 67 uLMS. Results: the immunoproteasome pathway is upregulated and the gene PMSB9 shows heterogeneous expression values in uLMS. Quartile group analysis showed no significant difference between groups high and low PSMB9 expression groups at 3-years overall survival (OS). Using CYBERSORTx analysis we observed 9 out of 17 samples in the high group clustering together due to high M2 macrophages and CD4 memory resting, and high CD8+/PSMB9 ratio was associated with better OS. The main pathway regulated in the high group is IFNγ and in the low is the ECM pathway dependent on the proto-oncogene SRC. Conclusion: these findings suggest 2 subtypes of uLMS (immune-related and ECM-related) with different candidate mechanisms of malignancy.

Identification of Melanoma Subsets Based on DNA Methylation Sites and Construction of a Prognosis Evaluation Model

Background

Melanoma is a lethal skin malignant tumor, and its formation or development is regulated by various genetic and epigenetic molecules. Although there are traditional methods provided for the doctors to evaluate the patients' prognosis or make the diagnosis, the novel method based on epigenetic markers is still needed to make the early diagnosis.

Results

We identified 256 melanoma-independent prognosis-related methylation sites (P < 0.0001) and divided patients into seven methylation subgroups. Methylation levels and survival time in the C2 subgroup were lower than that of other clusters (P < 0.05). We established the predicted model of prognosis risk for melanoma using the significantly changed methylation sites in C2. The model efficiently divided patients into high- and low-risk groups (area under the receiver operating characteristic curve, 0.833). Risk scores and patient survival time were negatively correlated (r_s = −0.325, P < 0.0001). Genes corresponding to the independent prognosis-associated methylation sites were enriched in cancer- and immunology-related pathways. We identified 35 hub genes. DOK2, GBP4, PSMB9, and NLRC5 were significantly changed according to methylation subgroups, survival, tumor stages, and T categories and were positively correlated, which was validated in the testing group (P < 0.05). The levels of DOK2, GBP4, PSMB9, and NLRC5 had an opposite trend to their methylation sites in patients with poor prognosis.

Conclusions

We identified seven DNA methylation subtypes and constructed a highly effective prognosis risk assessment model. The transcript levels of key genes corresponding to the independent prognosis-related methylation sites were significantly changed in patients according to prognosis and positively correlated with each other, indicating they may collaboratively promote melanoma formation. These findings further our understanding of the mechanism of melanoma and provide new targets for diagnosis and treatment.

Systematic evaluation of tumor microenvironment and construction of a machine learning model to predict prognosis and immunotherapy efficacy in triple-negative breast cancer based on data mining and sequencing validation

Background: The role of the tumor microenvironment (TME) in predicting prognosis and therapeutic efficacy has been demonstrated. Nonetheless, no systematic studies have focused on TME patterns or their function in the effectiveness of immunotherapy in triple-negative breast cancer.

Methods: We comprehensively estimated the TME infiltration patterns of 491 TNBC patients from four independent cohorts, and three cohorts that received immunotherapy were used for validation. The TME subtypes were comprehensively evaluated based on immune cell infiltration levels in TNBC, and the TRG score was identified and systematically correlated with representative tumor characteristics. We sequenced 80 TNBC samples as an external validation cohort to make our conclusions more convincing.

Results: Two TME subtypes were identified and were highly correlated with immune cell infiltration levels and immune-related pathways. More representative TME-related gene (TRG) scores calculated by machine learning could reflect the fundamental characteristics of TME subtypes and predict the efficacy of immunotherapy and the prognosis of TNBC patients. A low TRG score, characterized by activation of immunity and ferroptosis, indicated an activated TME phenotype and better prognosis. A low TRG score showed a better response to immunotherapy in TNBC by TIDE (Tumor Immune Dysfunction and Exclusion) analysis and sensitivity to multiple drugs in GDSC (Genomics of Drug Sensitivity in Cancer) analysis and a significant therapeutic advantage in patients in the three immunotherapy cohorts.

Conclusion: TME subtypes played an essential role in assessing the diversity and complexity of the TME in TNBC. The TRG score could be used to evaluate the TME of an individual tumor to enhance our understanding of the TME and guide more effective immunotherapy strategies.