Gene signature of antigen processing and presentation machinery predicts response to checkpoint blockade in non-small cell lung cancer (NSCLC) and melanoma

Decoding the complex web: cellular and molecular interactions in the lung tumour microenvironment

The lung tumour microenvironment (TME) or stroma is a dynamic space of numerous cells and their released molecules. This complicated web regulates tumour progression and resistance to different modalities. Lung cancer cells in conjunction with their stroma liberate a wide range of factors that dampen antitumor attacks by innate immunity cells like natural killer (NK) cells and also adaptive responses by effector T cells. These factors include numerous growth factors, exosomes and epigenetic regulators, and also anti-inflammatory cytokines. Understanding the intricate interactions between tumour cells and various elements within the lung TME, such as immune and stromal cells can help provide novel strategies for better management and treatment of lung malignancies. The current article discusses the complex network of cells and signalling molecules, which mediate communications in lung TME. By elucidating these multifaceted interactions, we aim to provide insights into potential therapeutic targets and strategies for lung cancer treatment.

Unraveling UPR-mediated intercellular crosstalk: Implications for immunotherapy resistance mechanisms

Endoplasmic reticulum (ER) is the critical organelle that regulates essential cellular processes, including protein synthesis, folding, and post-translational modification, as well as lipid metabolism and calcium homeostasis. Disruption in ER homeostasis leads to a condition known as ER stress, characterized by the accumulation of misfolded or unfolded proteins. This triggers the unfolded protein response (UPR), an adaptive pathway mediated by three ER-resident sensors: inositol-requiring enzyme 1α (IRE1α), protein kinase R-like ER kinase (PERK), and activating transcription factor 6 (ATF6). Increasing evidence highlights sustained UPR activation in malignant and immune cells within the tumor microenvironment (TME), which promotes tumor progression and metastasis while simultaneously impairing antitumor immunity. This review explores how UPR-driven intercellular signaling influences immunotherapy resistance, focusing on the alterations occurring in tumor cells as well as in the surrounding immune environment. By providing insights into these mechanisms, we aim to highlight the therapeutic potential of targeting the UPR pathways in modulating cancer immunity.

Mevalonate kinase inhibits anti-tumor immunity by impairing the tumor cell-intrinsic interferon response in microsatellite instability colorectal cancer

Insufficient tumor cell-intrinsic interferon response represents a major obstacle in immune checkpoint blockade (ICB) therapy, particularly in anti-PD-1 treatment. Although cholesterol metabolism has been demonstrated to be a critical regulator of anti-tumor immune responses, whether cholesterol influences tumor cell-intrinsic interferon response in microsatellite instability (MSI) colorectal cancer (CRC) remains unknown. Through comprehensive siRNA library screening and Gene Set Enrichment Analysis (GSEA), we identified mevalonate kinase (MVK) as a crucial negative regulator of tumor cell-intrinsic interferon response in MSI CRC cells. Genetic ablation of MVK resulted in significant upregulation of Th1 type chemokines (CXCL9 and CXCL10) and enhanced CD8+T cell infiltration in MSI CRC, consequently leading to marked tumor growth suppression in immunocompetent mice. At the molecular level, we demonstrated that MVK physically interacts with the transcriptional activation domain (TAD) of signal transducer and activator of transcription 1 (STAT1). This interaction substantially impairs STAT1 nuclear translocation, thereby attenuating interferon signaling cascade. Furthermore, analyses of humanized PBMC-PDX models and clinical cohorts of MSI CRC patients revealed that reduced MVK expression in tumor tissues strongly correlates with favorable responses to anti-PD-1 therapy. Collectively, our findings establish MVK as a pivotal mediator in cholesterol synthesis pathway that negatively regulates tumor cell-intrinsic interferon response in MSI CRC. These results suggest that therapeutic targeting of MVK represents a promising strategy to enhance ICB efficacy through potentiation of interferon responses in MSI CRC patients.

IL-4 mediated TAP2 downregulation is a dominant and reversible mechanism of immune evasion and immunotherapy resistance in non-small cell lung cancer

BACKGROUND

Resistance to both naturally occurring anti-cancer immunity and to immunotherapy is common in patients with aggressive non-small cell lung cancer (NSCLC). Recent studies indicate a role of loss of the HLA class-I antigen presentation machinery (APM) protein β-2-microglobulin in acquired resistance to immune checkpoint blockers. However, the mechanisms, functional consequences and therapeutic potential of APM defects in NSCLC remain poorly understood.

METHODS

Using multiplexed immunofluorescence, we spatially mapped CD8+ effector Tumor-Infiltrating Lymphocytes (TILs) and the APM components TAP1 and TAP2 in 819 baseline/pre-treatment NSCLCs from patients treated with and without PD-1 axis blockers in 4 independent cohorts. The impact of TAP1/2 silencing in lung cancer cells using siRNAs and CRISPR/Cas9 was studied using transcriptomic analysis, phosphoprotein arrays, ATAC-sequencing, measurement of surface HLA-peptide complexes and in vitro tumor-antigen specific T-cell killing. We established autologous co-cultures of tumor and immune cells from primary human NSCLCs to study the functional impact of IL4Rα and/or PD-1 blockade using monoclonal antibodies. A high-throughput drug screen supported the identification of compounds able to increase TAP2 expression in NSCLC cells.

RESULTS

We identified cancer cell selective TAP2 protein downregulation in 42.4% of treatment naïve NSCLCs associated with reduced sensitivity to immune checkpoint blockers. TAP1 downregulation occurred in 24.4% of lung tumors without survival impact. Silencing of TAP2 in lung cancer cells altered key intracellular immunomodulatory pathways, limited sensitivity to proinflammatory cytokines, reduced the levels of surface peptide-HLA complexes and protected malignant cells from tumor antigen-specific T-cell killing via SOCS1 upregulation. TAP2 loss in human NSCLCs was associated with reduced TAP2 promoter chromatin accessibility and elevated IL-4 IL-4 expression. Treatment with IL-4 reduced TAP2 levels and the chromatin accessibility of the TAP2 gene promoter in NSCLC cells and reproduced all the functional consequences of TAP2 loss. In intact human NSCLC, IL-4 IL-4 transcripts were detected in intratumoral myeloid cells and IL-4Rα blockade increased human NSCLC cell killing by autologous TILs. Epigenetic modulators and other drugs with known anti-cancer activity increased TAP2 expression and its function in lung cancer cells.

CONCLUSIONS

Our study reveals previously unrecognized functions of TAP2 beyond antigen presentation and establishes a reversible multi-cellular axis mediating adaptive immune evasion and immunotherapy resistance with clinical potential.

Integrated bulk and single-cell transcriptomic analysis unveiled a novel cuproptosis-related lipid metabolism gene molecular pattern and a risk index for predicting prognosis and antitumor drug sensitivity in breast cancer

Breast cancer is the second most prevalent malignant tumor worldwide and is highly heterogeneous. Cuproptosis, a newly identified form of cell death, is intimately connected to lipid metabolism. This study investigated breast cancer heterogeneity through the lens of cuproptosis-related lipid metabolism genes (CLMGs), with the goal of predicting patient prognosis, immunotherapy efficacy, and sensitivity to anticancer drugs. By utilizing transcriptomic data from The Cancer Genome Atlas (TCGA) for breast cancer, we identified 682 CLMGs and applied the nonnegative matrix factorization (NMF) method to categorize breast cancer patients into four distinct clusters: cluster 1, ''immune-cold and stroma-poor''; cluster 2, ''immune-infiltrated''; cluster 3, ''stroma-rich''; and cluster 4, ''moderate infiltration''. We subsequently developed a risk model based on CLMGs that incorporates ACSL1, ATP2B4, ATP7B, ENPP6, HSPH1, PIP4K2C, SRD5A3, and ULBP1. This model demonstrated excellent prognostic predictive performance in both the internal (testing and entire sets) and external (GSE20685 and Kaplan-Meier Plotter sets) validation sets. High-risk patients presented lower expression levels of immune checkpoint-related genes and lower immunophenoscores (IPSs), whereas low-risk patients presented higher CD8+ T-cell infiltration levels and IPSs. Furthermore, the risk index was positively correlated with tumor cell stemness and could predict sensitivity to anticancer drugs. We also confirmed that SRD5A3 was highly expressed in breast cancer and participated in promoting the proliferation and migration of breast cancer cells. In conclusion, the results of this study provide new insights and strategies for assessing prognosis and implementing precision treatment for breast cancer through the lens of CLMGs.

Genetic Polymorphisms in MHC Classes I and II Predict Outcomes in Metastatic Colorectal Cancer

The immune system is alerted for virally infected cells in the body by the antigen presentation pathway, which is in turn mediated by the major histocompatibility complex (MHC) class I and II molecules. Cancer cells overcome immune evasion as a major hallmark by downregulation of the antigen presentation pathway. Therefore, the present study aimed to explore the effect of genetic variants in genes involved in MHC class I and II pathways in patients treated with first-line chemotherapy in combination with targeted antibodies in metastatic colorectal cancer (mCRC) patients. Genomic DNA from the blood samples of 775 patients enrolled in three independent, randomized, first-line trials, namely TRIBE (FOLFIRI-bevacizumab, N = 215), FIRE-3 (FOLFIRI-bevacizumab, N = 107; FOLFIRI-cetuximab, N = 129), and MAVERICC (FOLFIRI-bevacizumab, N = 163; FOLFOX6-bevacizumab, N = 161), was genotyped through OncoArray, a custom array manufactured by Illumina including approximately 530K SNP markers. The impact on the outcome of 40 selected SNPs in 22 genes of MHC class I and II pathways was analyzed. We identified several SNPs in multiple genes associated with targeted treatment benefits across different treatment arms in our study population (p < 0.05). Treatment-SNP interaction analyses confirmed a significant treatment interaction with the targeted agents (bevacizumab vs. cetuximab) and the chemotherapy backbone (FOLFIRI vs. FOLFOX) in certain selected SNPs. Our results highlight a potential role for MHC SNPs as prognostic and predictive biomarkers for first-line treatment in mCRC, with differential effects based on the biologic agent and chemotherapy backbone. These biomarkers, when further validated, may contribute to personalized treatment strategies for mCRC patients.

Molecular Heterogeneity and Immune Infiltration Drive Clinical Outcomes in Upper Tract Urothelial Carcinoma

BACKGROUND AND OBJECTIVE

Molecular classification of upper tract urothelial carcinoma (UTUC) can provide insight into divergent clinical outcomes and provide a biological rationale for clinical decision-making. As such, we performed multi-omic analysis of UTUC tumors to identify molecular features associated with disease recurrence and response to immune checkpoint blockade (ICB).

METHODS

Targeted DNA and whole transcriptome RNA sequencing was performed on 100 UTUC tumors collected from patients undergoing nephroureterectomy. Consensus non-negative matrix factorization was used to identify molecular clusters associated with clinical outcomes. Gene set enrichment and immune deconvolution analyses were performed. Weighted gene co-expression network analysis was employed for unsupervised identification of gene networks in each cluster.

KEY FINDINGS AND LIMITATIONS

Five molecular clusters with distinct clinical outcomes were identified. Favorable subtypes (C1 and C2) were characterized by a luminal-like signature and an immunologically depleted tumor microenvironment (TME). Subtype C3 was characterized by FGFR3 alterations and a higher tumor mutational burden, and included all tumors with microsatellite instability. Despite higher rates of recurrence and inferior survival, subtypes C4 and C5 harbored an immunologically rich TME favoring response to ICB. Limitations include extrapolation of molecular features of tumors from the primary site to determine response to systemic immunotherapy and the limited resolution of bulk sequencing to distinguish gene expression in the tumor, stroma, and immune compartments.

CONCLUSIONS AND CLINICAL IMPLICATIONS

RNA sequencing identified previously underappreciated UTUC molecular heterogeneity and suggests that UTUC patients at the highest risk of metastatic recurrence following surgery include those most likely to benefit from perioperative ICB.

Predicting immunotherapy response of advanced bladder cancer through a meta-analysis of six independent cohorts

Advanced bladder cancer patients show very variable responses to immune checkpoint inhibitors (ICIs) and effective strategies to predict response are still lacking. Here we integrate mutation and gene expression data from 707 advanced bladder cancer patients treated with anti-PD-1/anti-PD-L1 to build highly accurate predictive models. We find that, in addition to tumor mutational burden (TMB), enrichment in the APOBEC mutational signature, and the abundance of pro-inflammatory macrophages, are major factors associated with the response. Paradoxically, patients with high immune infiltration do not show an overall better response. We show that this can be explained by the activation of immune suppressive mechanisms in a large portion of these patients. In the case of non-immune-infiltrated cancer subtypes, we uncover specific variables likely to be involved in the response. Our findings provide information for advancing precision medicine in patients with advanced bladder cancer treated with immunotherapy.

Next-Generation Sequencing-Based MSI Scoring Predicts Benefit in Mismatch Repair-Deficient Tumors Treated with Nivolumab: Follow-up on NCI-MATCH Arm Z1D

PURPOSE

Mismatch repair-deficient (dMMR) tumors have demonstrated favorable responses to immune checkpoint inhibition targeting PD-1. However, more in-depth identification of predictors of response could further refine patient selection for immunotherapy treatment.

PATIENTS AND METHODS

We undertook integrated evaluation performed on samples collected from 28 of 42 patients enrolled on the NCI-Molecular Analysis for Therapy Choice arm Z1D trial that evaluated PD-1 inhibition treatment with nivolumab in patients with noncolorectal dMMR tumors. Genomic analyses were performed using next-generation sequencing (NGS), whole-exome sequencing, and RNA sequencing and supplemented by multiplex immunofluorescence performed on tissue samples.

RESULTS

In this dMMR population, more extensive alterations of microsatellites as assessed by measures of NGS were associated with clinical benefit and tumor mutational burden. RNA sequencing further revealed associations between clinical benefit and immune infiltration index. Gene sets enriched in patients with clinical benefit included IFN signaling, antigen processing, and PI3K-AKT-mTOR signaling, whereas hedgehog signaling was found to be enriched in subjects lacking clinical benefit.

CONCLUSIONS

These genomic data highlight the importance of immune infiltration and antigen presentation in dMMR tumors that respond to immune checkpoint blockade. In addition, they suggest that, even within a dMMR population, NGS-based measures of microsatellite instability could serve as biomarkers of immunotherapy response.

Identification of a gene score related to antigen processing and presentation machinery for predicting prognosis in head and neck squamous cell carcinoma and its potential implications for immunotherapy

BACKGROUND

Despite its crucial role in immune surveillance and cell survival of tumors, the significance of MHC antigen processing and presentation machinery (APM) is still not fully understood in head and neck squamous cell carcinoma (HNSCC). We sought to develop an APM gene score (APMGS) to predict prognosis and reveal the molecular and immune traits of the APMGS-defined subgroups in HNSCC.

METHODS

Based on the APM-related genes acquired from 6 databases, 117 combined machine learning algorithms were applied to develop APMGS with The Cancer Genome Atlas (TCGA)-HNSCC database and validated with the Gene Expression Omnibus (GEO) dataset. Comprehensive analysis was performed to investigate the molecular and immune features of APMGS subgroups.

RESULTS

The APMGS constructed by StepCox [both] + Ridge method achieved the highest C-index and area under curve (AUC) at 3 years and were thus adopted as the final model. Low-APMGS patients exhibited superior overall survival compared with high-APMGS patients in both TCGA and GEO cohorts. Subsequent analysis confirmed that a low APMGS was associated with immune response-related pathways; low TP53 mutation rate and low tumor mutation burden (TMB); a less aggressive phenotype; high infiltration of activated CD4+ memory T cells, CD8+ T cells, follicular helper T cells, and Tregs; active immunity; and higher sensitivity to chemotherapeutic and targeted agents. In contrast, a high APMGS linked to proteasome and protein export pathways; high TP53 mutation rate and high TMB; a more aggressive phenotype; high infiltration of M0 macrophages and eosinophils; suppressed immunity; and lower sensitivity to chemotherapeutic and targeted agents.

CONCLUSIONS

Our findings suggest that APMGS has potential to predict the prognosis, and molecular and immune characteristics of HNSCC, and may also serve as an indicator for immunotherapy benefit.

Biomarkers for immunotherapy resistance in non-small cell lung cancer

Immunotherapy has revolutionised the treatment landscape of non-small cell lung cancer (NSCLC), significantly improving survival outcomes and offering renewed hope to patients with advanced disease. However, the majority of patients experience limited long-term benefits from immune checkpoint inhibition (ICI) due to the development of primary or acquired immunotherapy resistance. Accurate predictive biomarkers for immunotherapy resistance are essential for individualising treatment strategies, improving survival outcomes, and minimising potential treatment-related harm. This review discusses the mechanisms underlying resistance to immunotherapy, addressing both cancer cell-intrinsic and cancer cell-extrinsic resistance processes. We summarise the current utility and limitations of two clinically established biomarkers: programmed death ligand 1 (PD-L1) expression and tumour mutational burden (TMB). Following this, we present a comprehensive review of emerging immunotherapy biomarkers in NSCLC, including tumour neoantigens, epigenetic signatures, markers of the tumour microenvironment (TME), genomic alterations, host-microbiome composition, and circulating biomarkers. The potential clinical applications of these biomarkers, along with novel approaches to their biomarker identification and targeting, are discussed. Additionally, we explore current strategies to overcome immunotherapy resistance and propose incorporating predictive biomarkers into an adaptive clinical trial design, where specific immune signatures guide subsequent treatment selection.

A patient stratification signature mirrors the immunogenic potential of high grade serous ovarian cancers

BACKGROUND

While high-grade serous ovarian cancer (HGSC) has proven largely resistant to immunotherapy, sporadic incidents of partial and complete response have been observed in clinical trials and case reports. These observations suggest that a molecular basis for effective immunity may exist within a subpopulation of HGSC. Herein, we developed an algorithm, CONSTRU (Computing Prognostic Marker Dependencies by Successive Testing of Gene-Stratified Subgroups), to facilitate the discovery and characterization of molecular backgrounds of HGSC that confer resistance or susceptibility to protective anti-tumor immunity.

METHODS

We used CONSTRU to identify genes from tumor expression profiles that influence the prognostic power of an established immune cytolytic activity signature (CYTscore). From the identified genes, we developed a stratification signature (STRATsig) that partitioned patient populations into tertiles that varied markedly by CYTscore prognostic power. The tertile groups were then analyzed for distinguishing biological, clinical and immunological properties using integrative bioinformatics approaches.

RESULTS

Patient survival and molecular measures of immune suppression, evasion and dysfunction varied significantly across STRATsig tertiles in validation cohorts. Tumors comprising STRATsig tertile 1 (S-T1) showed no immune-survival benefit and displayed a hyper-immune suppressed state marked by activation of TGF-β, Wnt/β-catenin and adenosine-mediated immunosuppressive pathways, with concurrent T cell dysfunction, reduced potential for antigen presentation, and enrichment of cancer-associated fibroblasts. By contrast, S-T3 tumors exhibited diminished immunosuppressive signaling, heightened antigen presentation machinery, lowered T cell dysfunction, and a significant CYTscore-survival benefit that correlated with mutational burden in a manner consistent with anti-tumor immunoediting. These tumors also showed elevated activity of DNA damage/repair, cell cycle/proliferation and oxidative phosphorylation, and displayed greater proportions of Th1 CD4 + T cells. In these patients, but not those of S-T1 or S-T2, validated predictors of immunotherapy response were prognostic of longer patient survival. Further analyses showed that STRATsig tertile properties were not explained by known HGSC molecular or clinical subtypes or singular immune mechanisms.

CONCLUSIONS

STRATsig is a composite of parallel immunoregulatory pathways that mirrors tumor immunogenic potential. Approximately one-third of HGSC cases classify as S-T3 and display a hypo-immunosuppressed and antigenic molecular composition that favors immunologic tumor control. These patients may show heightened responsiveness to current immunotherapies.

Actin Dysregulation Induces Neuroendocrine Plasticity and Immune Evasion: A Vulnerability of Small Cell Lung Cancer

Small cell lung cancer (SCLC) is aggressive with limited therapeutic options. Despite recent advances in targeted therapies and immunotherapies, therapy resistance is a recurring issue, which might be partly due to tumor cell plasticity, a change in cell fate. Nonetheless, the mechanisms underlying tumor cell plasticity and immune evasion in SCLC remain elusive. CRACD, a capping protein inhibitor that promotes actin polymerization, is frequently inactivated in SCLC. Cracd knockout (KO) transforms preneoplastic cells into SCLC tumor-like cells and promotes in vivo SCLC development driven by Rb1, Trp53, and Rbl2 triple KO. Cracd KO induces neuroendocrine (NE) plasticity and increases tumor cell heterogeneity of SCLC tumor cells via dysregulated NOTCH1 signaling by actin cytoskeleton disruption. CRACD depletion also reduces nuclear actin and induces EZH2-mediated H3K27 methylation. This nuclear event suppresses the MHC-I genes and thereby depletes intratumoral CD8+ T cells for accelerated SCLC tumorigenesis. Pharmacological blockade of EZH2 inhibits CRACD-negative SCLC tumorigenesis by restoring MHC-I expression and immune surveillance. Unsupervised single-cell transcriptomics identifies SCLC patient tumors with concomitant inactivation of CRACD and downregulated MHC-I pathway. This study defines CRACD, an actin regulator, as a tumor suppressor that limits cell plasticity and immune evasion and proposes EZH2 blockade as a viable therapeutic option for CRACD-negative SCLC.

β2-microglobulin expression is associated with aggressive histology, activated tumor immune milieu, and outcome in colon carcinoma

OBJECTIVES

We sought to assess the expression of human leukocyte antigen (HLA) proteins and β2-microglobulin (B2M) in tumor cells and the relationship with immune microenvironment and outcome in colorectal cancer (CRC).

METHODS

A total of 953 CRC cases were evaluated by immunohistochemistry for HLA class I, HLA class II, and B2M. The expression level of these biomarkers was correlated with clinicopathologic information, BRAF V600E and mismatch repair (MMR) proteins, and the quantitated expression levels of immune cells (CD8 and CD163) and immune regulatory proteins (FoxP3, programmed cell death 1 ligand 1 [PD-L1], and LAG3).

RESULTS

We found that B2M-low tumors were statistically correlated with aggressive histologic features, including higher stage, higher grade, extramural venous invasion, perineural invasion, and distant metastasis. Expression of B2M was positively correlated (R2 = 0.3) and significantly associated with MMR-deficient tumors (P < .001); B2M-low tumors were also associated with an "immune cold"' microenvironment, including a reduced number of immune cells (CD8 and CD163), reduced expression of immune regulatory proteins by immune cells (PD-L1, FoxP3, and LAG3), and reduced tumor cell expression of PD-L1. These B2M-low tumors correlated with lower disease-specific survival (P = .018), a finding that maintained significance only for the proficient MMR cohort (P = .037).

CONCLUSIONS

Our findings suggest that B2M expression may support predictive models for both outcome and checkpoint inhibitor therapy treatment response for colorectal adenocarcinoma.

Mouse Corneal Immune Cell Heterogeneity Revealed by Single-Cell RNA Sequencing

Purpose

This study aimed to define the heterogeneity, spatial localization, and functional roles of immune cells in the mouse cornea using single-cell RNA sequencing (scRNA-seq) and immunofluorescent staining.

Methods

Enriched mouse corneal immune cells (C57BL/6 strain, age 16-20 weeks) underwent single-cell RNA sequencing library preparation, sequencing, and analysis with Seurat, Monocle 3, and CellChat packages in R. Pathway analysis used Qiagen Ingenuity Pathway Analysis software. Immunostaining confirmed cell distribution.

Results

We identified 14 distinct immune cell clusters (56% myeloid and 44% lymphoid). Myeloid populations included resident macrophages, conventional dendritic cells (cDC2s), Langerhans cells, neutrophils, monocytes, and mast cells. Additionally, lymphocyte subsets (B, CD8, CD4, γδT, natural killer, natural killer T, and group 2 innate lymphoid cells) were found. We also found three new subtypes of resident macrophages in the cornea. Trajectory analysis suggested a differentiation pathway from monocytes to conventional dendritic cells, resident macrophages, and LCs. Intercellular communication network analysis using cord diagram identified amyloid precursor protein, chemokine (C-C motif) ligands (2, 3, 4, 6, 7, 9, and 12), Cxcl2, Mif, Tnf, Tgfb1, Igf1, and Il10 as prominent ligands involved in these interactions. Sexually dimorphic gene expression patterns were observed, with male myeloid cells expressing genes linked to immune regulation (Egr1, Foxp1, Mrc1, and Il1rn) and females showing higher expression of antigen presentation genes (Clic1, Psmb8, and Psmb9). Finally, immunostaining confirmed the spatial distribution of these cell populations within the cornea.

Conclusions

This study unveils a diverse immune landscape in the mouse cornea, with evidence for cell differentiation and sex-based differences. Immunostaining validates the spatial distribution of these populations, furthering our knowledge of corneal immune function.

Predictive Signatures for Responses to Checkpoint Blockade in Small-Cell Lung Cancer in Second-Line Therapy Do Not Predict Responses in First-Line Patients

Although immune checkpoint blockade (ICB) is currently approved for the treatment of extensive-stage small-cell lung cancer (SCLC) in combination with chemotherapy, relatively few patients have demonstrated durable clinical benefit (DCB) to these therapies. Biomarkers predicting responses are needed. Biopsies from 35 SCLC patients treated with ICB were subjected to transcriptomic analysis; gene signatures were assessed for associations with responses. Twenty-one patients were treated with ICB in the first-line setting in combination with platinum-based chemotherapy; fourteen patients were treated in the second-line setting with ICB alone. DCB after ICB in SCLC in the second-line setting (3 of 14 patients) was associated with statistically higher transcriptomic levels of genes associated with inflammation (p = 0.003), antigen presentation machinery (p = 0.03), interferon responses (p < 0.05), and increased CD8 T cells (p = 0.02). In contrast, these gene signatures were not significantly different in the first-line setting. Our data suggest that responses to ICB in SCLC in the second-line setting can be predicted by the baseline inflammatory state of the tumor; however, this strong association with inflammation was not seen in the first-line setting. We postulate that chemotherapy alters the immune milieu allowing a response to ICB. Other biomarkers will be needed to predict responses in first-line therapy patients.

The crosstalk between lung cancer and the bone marrow niche fuels emergency myelopoiesis

Modest response rates to immunotherapy observed in advanced lung cancer patients underscore the need to identify reliable biomarkers and targets, enhancing both treatment decision-making and efficacy. Factors such as PD-L1 expression, tumor mutation burden, and a 'hot' tumor microenvironment with heightened effector T cell infiltration have consistently been associated with positive responses. In contrast, the predictive role of the abundantly present tumor-infiltrating myeloid cell (TIMs) fraction remains somewhat uncertain, partly explained by their towering variety in terms of ontogeny, phenotype, location, and function. Nevertheless, numerous preclinical and clinical studies established a clear link between lung cancer progression and alterations in intra- and extramedullary hematopoiesis, leading to emergency myelopoiesis at the expense of megakaryocyte/erythroid and lymphoid differentiation. These observations affirm that a continuous crosstalk between solid cancers such as lung cancer and the bone marrow niche (BMN) must take place. However, the BMN, encompassing hematopoietic stem and progenitor cells, differentiated immune and stromal cells, remains inadequately explored in solid cancer patients. Subsequently, no clear consensus has been reached on the exact breadth of tumor installed hematopoiesis perturbing cues nor their predictive power for immunotherapy. As the current era of single-cell omics is reshaping our understanding of the hematopoietic process and the subcluster landscape of lung TIMs, we aim to present an updated overview of the hierarchical differentiation process of TIMs within the BMN of solid cancer bearing subjects. Our comprehensive overview underscores that lung cancer should be regarded as a systemic disease in which the cues governing the lung tumor-BMN crosstalk might bolster the definition of new biomarkers and druggable targets, potentially mitigating the high attrition rate of leading immunotherapies for NSCLC.

Establishment and validation of a gene mutation-based risk model for predicting prognosis and therapy response in acute myeloid leukemia

Background

Acute myeloid leukemia (AML) is a malignant clonal proliferative disease of hematopoietic system. Despite tremendous progress in uncovering the AML genome, only a small number of mutations have been incorporated into risk stratification and used as therapeutic targets. In this research, we performed to construct a predictive prognosis risk model for AML patients according to gene mutations.

Methods

Next-generation sequencing (NGS) technology was utilized to detect gene mutation from 118 patients. mRNA expression profiles and related clinical information were mined from TCGA and GEO databases. Consensus cluster analysis was applied to obtain molecular subtypes, and differences in clinicopathological features, prognosis, and immune microenvironment of different clusters were systematically compared. According to the differentially expressed genes (DEGs) between clusters, univariate and LASSO regression analysis were applied to identify gene signatures to build a prognostic risk model. Patients were classified into high-risk (HR) and low-risk (LR) groups according to the median risk score (RS). Differences in prognosis, immune profile, and therapeutic sensitivity between two groups were analyzed. The independent predictive value of RS was assessed and a nomogram was developed.

Results

NGS detected 24 mutated genes, with higher mutation frequencies in CBL (63 %) and SETBP1 (49 %). Two clusters exhibited different immune microenvironments and survival probability (p = 0.0056) were identified. A total of 444 DEGs were screened in two clusters, and a mutation-associated risk model was constructed, including MPO, HGF, SH2B3, SETBP1, HLA-DRB1, LGALS1, and KDM5B. Patients in LR had a superior survival time compared to HR. Predictive performance of this model was confirmed and the developed nomogram further improved the applicability of the risk model with the AUCs for predicting 1-, 3-, 5-year survival rate were 0.829, 0.81 and 0.811, respectively. HR cases were more sensitive to erlotinib, CI-1040, and AZD6244.

Conclusion

These findings supplemented the understanding of gene mutations in AML, and constructed models had good application prospect to provide effective information for predicting prognosis and treatment response of AML.

Assessment of cancer cell-expressed HLA class I molecules and their immunopathological implications

Immunotherapy using immune checkpoint inhibitors (ICIs) has shown superior efficacy compared with conventional chemotherapy in certain cancer types, establishing immunotherapy as the fourth standard treatment alongside surgical intervention, chemotherapy, and radiotherapy. In cancer immunotherapy employing ICIs, CD8-positive cytotoxic T lymphocytes are recognized as the primary effector cells. For effective clinical outcomes, it is essential that the targeted cancer cells express HLA class I molecules to present antigenic peptides derived from the tumor. However, cancer cells utilize various mechanisms to downregulate or lose HLA class I molecules from their surface, resulting in evasion from immune surveillance. Correlations between prognosis and the integrity of HLA class I molecules expressed by cancer cells have been consistently found across different types of cancer. This paper provides an overview of the regulatory mechanisms of HLA class I molecules and their role in cancer immunotherapy, with a particular emphasis on the significance of utilizing pathological tissues to evaluate HLA class I molecules expressed in cancer cells.

Prognostic models for immunotherapy in non-small cell lung cancer: A comprehensive review

The introduction of immune checkpoint inhibitors (ICIs) has revolutionized the treatment of lung cancer. Given the limited clinical benefits of immunotherapy in patients with non-small cell lung cancer (NSCLC), various predictors have been shown to significantly influence prognosis. However, no single predictor is adequate to forecast patients' survival benefit. Therefore, it's imperative to develop a prognostic model that integrates multiple predictors. This model would be instrumental in identifying patients who might benefit from ICIs. Retrospective analysis and small case series have demonstrated the potential role of these models in prognostic prediction, though further prospective investigation is required to evaluate more rigorously their application in these contexts. This article presents and summarizes the latest research advancements on immunotherapy prognostic models for NSCLC from multiple omics perspectives and discuss emerging strategies being developed to enhance the domain.

Bacteria-derived nanovesicles enhance tumour vaccination by trained immunity

Trained immunity enhances the responsiveness of immune cells to subsequent infections or vaccinations. Here we demonstrate that pre-vaccination with bacteria-derived outer-membrane vesicles, which contain large amounts of pathogen-associated molecular patterns, can be used to potentiate, and enhance, tumour vaccination by trained immunity. Intraperitoneal administration of these outer-membrane vesicles to mice activates inflammasome signalling pathways and induces interleukin-1β secretion. The elevated interleukin-1β increases the generation of antigen-presenting cell progenitors. This results in increased immune response when tumour antigens are delivered, and increases tumour-antigen-specific T-cell activation. This trained immunity increased protection from tumour challenge in two distinct cancer models.

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.

Genomic and transcriptomic analysis of breast cancer identifies novel signatures associated with response to neoadjuvant chemotherapy

BACKGROUND

Neoadjuvant chemotherapy (NAC) has become a standard treatment strategy for breast cancer (BC). However, owing to the high heterogeneity of these tumors, it is unclear which patient population most likely benefit from NAC. Multi-omics offer an improved approach to uncovering genomic and transcriptomic changes before and after NAC in BC and to identifying molecular features associated with NAC sensitivity.

METHODS

We performed whole-exome and RNA sequencing on 233 samples (including matched pre- and post-treatment tumors) from 50 BC patients with rigorously defined responses to NAC and analyzed changes in the multi-omics landscape. Molecular features associated with NAC response were identified and validated in a larger internal, and two external validation cohorts, as well as in vitro experiments.

RESULTS

The most frequently altered genes were TP53, TTN, and MUC16 in both pre- and post-treatment tumors. In comparison with pre-treatment tumors, there was a significant decrease in C > A transversion mutations in post-treatment tumors (P = 0.020). NAC significantly decreased the mutation rate (P = 0.006) of the DNA repair pathway and gene expression levels (FDR = 0.007) in this pathway. NAC also significantly changed the expression level of immune checkpoint genes and the abundance of tumor-infiltrating immune and stroma cells, including B cells, activated dendritic cells, γδT cells, M2 macrophages and endothelial cells. Furthermore, there was a higher rate of C > T substitutions in NAC nonresponsive tumors than responsive ones, especially when the substitution site was flanked by C and G. Importantly, there was a unique amplified region at 8p11.23 (containing ADGRA2 and ADRB3) and a deleted region at 3p13 (harboring FOXP1) in NAC nonresponsive and responsive tumors, respectively. Particularly, the CDKAL1 missense variant P409L (p.Pro409Leu, c.1226C > T) decreased BC cell sensitivity to docetaxel, and ADGRA2 or ADRB3 gene amplifications were associated with worse NAC response and poor prognosis in BC patients.

CONCLUSIONS

Our study has revealed genomic and transcriptomic landscape changes following NAC in BC, and identified novel biomarkers (CDKAL1P409L, ADGRA2 and ADRB3) underlying chemotherapy resistance and poor prognosis, which could guide the development of personalized treatments for BC.

NLRC5 overexpression in ovarian tumors remodels the tumor microenvironment and increases T-cell reactivity toward autologous tumor-associated antigens

Introduction

Epithelial ovarian cancer (OC) stands as one of the deadliest gynecologic malignancies, urgently necessitating novel therapeutic strategies. Approximately 60% of ovarian tumors exhibit reduced expression of major histocompatibility complex class I (MHC I), intensifying immune evasion mechanisms and rendering immunotherapies ineffective. NOD-like receptor CARD domain containing 5 (NLRC5) transcriptionally regulates MHC I genes and many antigen presentation machinery components. We therefore explored the therapeutic potential of NLRC5 in OC.

Methods

We generated OC cells overexpressing NLRC5 to rescue MHC I expression and antigen presentation and then assessed their capability to respond to PD-L1 blockade and an infected cell vaccine.

Results

Analysis of microarray datasets revealed a correlation between elevated NLRC5 expression and extended survival in OC patients; however, NLRC5 was scarcely detected in the OC tumor microenvironment. OC cells overexpressing NLRC5 exhibited slower tumor growth and resulted in higher recruitment of leukocytes in the TME with lower CD4/CD8 T-cell ratios and increased activation of T cells. Immune cells from peripheral blood, spleen, and ascites from these mice displayed heightened activation and interferon-gamma production when exposed to autologous tumor-associated antigens. Finally, as a proof of concept, NLRC5 overexpression within an infected cell vaccine platform enhanced responses and prolonged survival in comparison with control groups when challenged with parental tumors.

Discussion

These findings provide a compelling rationale for utilizing NLRC5 overexpression in "cold" tumor models to enhance tumor susceptibility to T-cell recognition and elimination by boosting the presentation of endogenous tumor antigens. This approach holds promise for improving antitumoral immune responses in OC.

Gene expression profiles (GEPs) of immuno-oncologic pathways as predictors of response to checkpoint inhibitors in advanced NSCLC

BACKGROUND

Immune checkpoint inhibitors (ICIs) revolutionized non-small-cell lung cancer (NSCLC) treatment. However, improving patients' selection for this therapy is needed. Gene expression profile (GEP) is a promising biomarker tool. We assessed the predictive value of 48 onco-immune GEPs in an NSCLC real-world scenario.

METHODS

Retrospective cohort of Brazilian NSCLC patients treated with ICIs in any line. GEP was assessed in FFPE tumor tissue using the nCounter PanCancer IO360 panel, comprising 770 cancer immune genes.

RESULTS

The median age of the 135 patients was 61 years old, most male (57.8 %), history of smoking (83.6 %), ECOG-PS 0-1 (88.7 %), clinical stage IV (91.9 %) and adenocarcinoma (65.1 %). First-line ICI in 40 % of cases, alone or in combination with chemotherapy. The median follow-up was 28 months, overall survival after starting immunotherapy (post-immunotherapy survival - PIS) was 17.8 months, and real-world progression-free survival was 5.5 months. The GEP analysis was possible in 66 patients. We found that 14 different GEPs associated with PIS, namely IDO1, PD-L2, Cytotoxicity, Cytotoxic Cells, IFN Downstream, CTLA4, PD-L1, TIGIT, Lymphoid, Immunoproteasome, Exhausted CD8, IFN Gamma, TIS and APM. TIS and IFN-γ were the most significant GEPs associated with favorable outcomes. The median PIS for patients with high TIS expression was 29.2 versus 15.5 months (HR 0.42; 95 %CI; 0.17-0.67; p<0.05) for those with low expression. Similar results were observed for IFN-γ.

CONCLUSIONS

The TIS (tumor inflammation signature) and IFN-γ signatures constitute predictive biomarkers to identify patients with NSCLC patients who would possibly benefit from ICI therapies.

Predictive Factors in Metastatic Melanoma Treated with Immune Checkpoint Inhibitors: From Clinical Practice to Future Perspective

The introduction of immunotherapy revolutionized the treatment landscape in metastatic melanoma. Despite the impressive results associated with immune checkpoint inhibitors (ICIs), only a portion of patients obtain a response to this treatment. In this scenario, the research of predictive factors is fundamental to identify patients who may have a response and to exclude patients with a low possibility to respond. These factors can be host-associated, immune system activation-related, and tumor-related. Patient-related factors can vary from data obtained by medical history (performance status, age, sex, body mass index, concomitant medications, and comorbidities) to analysis of the gut microbiome from fecal samples. Tumor-related factors can reflect tumor burden (metastatic sites, lactate dehydrogenase, C-reactive protein, and circulating tumor DNA) or can derive from the analysis of tumor samples (driver mutations, tumor-infiltrating lymphocytes, and myeloid cells). Biomarkers evaluating the immune system activation, such as IFN-gamma gene expression profile and analysis of circulating immune cell subsets, have emerged in recent years as significantly correlated with response to ICIs. In this manuscript, we critically reviewed the most updated literature data on the landscape of predictive factors in metastatic melanoma treated with ICIs. We focus on the principal limits and potentiality of different methods, shedding light on the more promising biomarkers.

The coenzyme A precursor pantethine enhances antitumor immunity in sarcoma

The tumor microenvironment is a dynamic network of stromal, cancer, and immune cells that interact and compete for resources. We have previously identified the Vanin1 pathway as a tumor suppressor of sarcoma development via vitamin B5 and coenzyme A regeneration. Using an aggressive sarcoma cell line that lacks Vnn1 expression, we showed that the administration of pantethine, a vitamin B5 precursor, attenuates tumor growth in immunocompetent but not nude mice. Pantethine boosts antitumor immunity, including the polarization of myeloid and dendritic cells towards enhanced IFNγ-driven antigen presentation pathways and improved the development of hypermetabolic effector CD8+ T cells endowed with potential antitumor activity. At later stages of treatment, the effect of pantethine was limited by the development of immune cell exhaustion. Nevertheless, its activity was comparable with that of anti-PD1 treatment in sensitive tumors. In humans, VNN1 expression correlates with improved survival and immune cell infiltration in soft-tissue sarcomas, but not in osteosarcomas. Pantethine could be a potential therapeutic immunoadjuvant for the development of antitumor immunity.

Genomic profiling of subcutaneous patient-derived xenografts reveals immune constraints on tumor evolution in childhood solid cancer

Subcutaneous patient-derived xenografts (PDXs) are an important tool for childhood cancer research. Here, we describe a resource of 68 early passage PDXs established from 65 pediatric solid tumor patients. Through genomic profiling of paired PDXs and patient tumors (PTs), we observe low mutational similarity in about 30% of the PT/PDX pairs. Clonal analysis in these pairs show an aggressive PT minor subclone seeds the major clone in the PDX. We show evidence that this subclone is more immunogenic and is likely suppressed by immune responses in the PT. These results suggest interplay between intratumoral heterogeneity and antitumor immunity may underlie the genetic disparity between PTs and PDXs. We further show that PDXs generally recapitulate PTs in copy number and transcriptomic profiles. Finally, we report a gene fusion LRPAP1-PDGFRA. In summary, we report a childhood cancer PDX resource and our study highlights the role of immune constraints on tumor evolution.

Quantifying the impact of immunotherapy on RNA dynamics in cancer

BACKGROUND

Checkpoint inhibitor (CPI) immunotherapies have provided durable clinical responses across a range of solid tumor types for some patients with cancer. Nonetheless, response rates to CPI vary greatly between cancer types. Resolving intratumor transcriptomic changes induced by CPI may improve our understanding of the mechanisms of sensitivity and resistance.

METHODS

We assembled a cohort of longitudinal pre-therapy and on-therapy samples from 174 patients treated with CPI across six cancer types by leveraging transcriptomic sequencing data from five studies.

RESULTS

Meta-analyses of published RNA markers revealed an on-therapy pattern of immune reinvigoration in patients with breast cancer, which was not discernible pre-therapy, providing biological insight into the impact of CPI on the breast cancer immune microenvironment. We identified 98 breast cancer-specific correlates of CPI response, including 13 genes which are known IO targets, such as toll-like receptors TLR1, TLR4, and TLR8, that could hold potential as combination targets for patients with breast cancer receiving CPI treatment. Furthermore, we demonstrate that a subset of response genes identified in breast cancer are already highly expressed pre-therapy in melanoma, and additionally we establish divergent RNA dynamics between breast cancer and melanoma following CPI treatment, which may suggest distinct immune microenvironments between the two cancer types.

CONCLUSIONS

Overall, delineating longitudinal RNA dynamics following CPI therapy sheds light on the mechanisms underlying diverging response trajectories, and identifies putative targets for combination therapy.

Targeting myeloid checkpoint Siglec-10 reactivates antitumor immunity and improves anti-programmed cell death 1 efficacy in gastric cancer

OBJECTIVE

Immunotherapy has not yielded satisfactory therapeutic responses in gastric cancer (GC). However, targeting myeloid checkpoints holds promise for expanding the potential of immunotherapy. This study aims to evaluate the critical role of Siglec-10+ tumor-associated macrophages (TAMs) in regulating antitumor immunity and to explore the potential of the myeloid checkpoint Siglec-10 as an interventional target.

DESIGN

Siglec-10+ TAMs were assessed based on immunohistochemistry on tumor microarrays and RNA-sequencing data. Flow cytometry, RNA sequencing, and single-cell RNA-sequencing analysis were employed to characterize the phenotypic and transcriptional features of Siglec-10+ TAMs and their impact on CD8+ T cell-mediated antitumor immunity. The effectiveness of Siglec-10 blockade, either alone or in combination with anti-programmed cell death 1 (PD-1), was evaluated using an ex vivo GC tumor fragment platform based on fresh tumor tissues.

RESULTS

Siglec-10 was predominantly expressed on TAMs in GC, and associated with tumor progression. In Zhongshan Hospital cohort, Siglec-10+ TAMs predicted unfavorable prognosis (n=446, p<0.001) and resistance to adjuvant chemotherapy (n=331, p<0.001), which were further validated in exogenous cohorts. In the Samsung Medical Center cohort, Siglec-10+ TAMs demonstrated inferior response to pembrolizumab in GC (n=45, p=0.008). Furthermore, Siglec-10+ TAMs exhibited an immunosuppressive phenotype and hindered T cell-mediated antitumor immune response. Finally, blocking Siglec-10 reinvigorated the antitumor immune response and synergistically enhances anti-PD-1 immunotherapy in an ex vivo GC tumor fragment platform.

CONCLUSIONS

In GC, the myeloid checkpoint Siglec-10 contributes to the regulation of immunosuppressive property of TAMs and promotes the depletion of CD8+ T cells, ultimately facilitating immune evasion. Targeting Siglec-10 represents a potential strategy for immunotherapy in GC.

Integration of bioinformatics and machine learning strategies identifies APM-related gene signatures to predict clinical outcomes and therapeutic responses for breast cancer patients

BACKGROUND

Tumor antigenicity and efficiency of antigen presentation jointly influence tumor immunogenicity, which largely determines the effectiveness of immune checkpoint blockade (ICB). However, the role of altered antigen processing and presentation machinery (APM) in breast cancer (BRCA) has not been fully elucidated.

METHODS

A series of bioinformatic analyses and machine learning strategies were performed to construct APM-related gene signatures to guide personalized treatment for BRCA patients. A single-sample gene set enrichment analysis (ssGSEA) algorithm and weighted gene co-expression network analysis (WGCNA) were combined to screen for BRCA-specific APM-related genes. The non-negative matrix factorization (NMF) algorithm was used to divide the cohort into different clusters and the fgsea algorithm was applied to investigate the altered signaling pathways. Random survival forest (RSF) and the least absolute shrinkage and selection operator (Lasso) Cox regression analysis were combined to construct an APM-related risk score (APMrs) signature to predict overall survival. Furthermore, a nomogram and decision tree were generated to improve predictive accuracy and risk stratification for individual patients. Based on Tumor Immune Dysfunction and Exclusion (TIDE) method, random forest (RF) and Lasso logistic regression model were combined to establish an APM-related immunotherapeutic response score (APMis). Finally, immune infiltration, immunomodulators, mutational patterns, and potentially applicable drugs were comprehensively analyzed in different APM-related risk groups. IHC staining was used to assess the expression of APM-related genes in clinical samples.

RESULTS

In this study, APMrs and APMis showed favorable performances in risk stratification and therapeutic prediction for BRCA patients. APMrs exhibited more powerful prognostic capacity and accurate survival prediction compared to conventional clinicopathological features. APMrs was closely associated with distinct mutational patterns, immune cell infiltration and immunomodulators expression. Furthermore, the two APM-related gene signatures were independently validated in external cohorts with prognosis or immunotherapeutic responses. Potential applicable drugs and targets were mined in the APMrs-high group. APM-related genes were further validated in our in-house samples.

CONCLUSION

The APM-related gene signatures established in our study could improve the personalized assessment of survival risk and guide ICB decision-making for BRCA patients.

The Influence of Obesity on Outcomes with Immune Checkpoint Blockade: Clinical Evidence and Potential Biological Mechanisms

Immune checkpoint blockade (ICB) is a mainstay of treatment for advanced cancer, yet tumor response and host toxicity are heterogenous in those patients who receive ICB. There is growing interest in understanding how host factors interact with tumor intrinsic properties and the tumor microenvironment to influence the therapeutic index with ICB. Obesity, defined by body mass index, is a host factor associated with improved outcomes in select cancers when treated with ICB. While the biological mechanism for this obesity paradox is not fully understood, pre-clinical and translational studies suggest obesity may potentially impact tumor metabolism, inflammation, and angiogenesis. Herein, we summarize clinical studies that support an obesity paradox with ICB, explore potential biological mechanisms that may account for the obesity paradox, and address methodological challenges to consider when studying obesity and treatment outcomes.

Increased expression of IDO1 is associated with improved survival and increased number of TILs in patients with high-grade serous ovarian cancer

BACKGROUND

The enzyme indoleamine 2,3-dioxygenase 1 (IDO1) plays a crucial role in regulating the immune system's response to tumors, but its exact role in cancer, especially in high-grade serous ovarian cancer (HGSOC), remains controversial. We aimed to investigate the prognostic impact of IDO1 expression and its correlation with tumor-infiltrating lymphocytes (TILs) in HGSOC.

METHODS

Immunohistochemical (IHC) staining and bioimage analysis using the QuPath software were employed to assess IDO1 protein expression in a well-characterized cohort of 507 patients with primary HGSOC. Statistical evaluation was performed using SPSS, and in silico validation considering IDO1 mRNA expression in bulk and single-cell gene expression datasets was conducted. Additionally, IDO1 expression in interferon-gamma (IFNG) stimulated HGSOC cell lines was analyzed.

RESULTS

Our findings revealed that IDO1 protein and mRNA expression serve as positive prognostic markers for overall survival (OS) and progression-free survival (PFS) in HGSOC. High IDO1 expression was associated with a significant improvement in OS by 21 months (p < 0.001) and PFS by 6 months (p = 0.016). Notably, elevated IDO1 expression correlated with an increased number of CD3+ (p < 0.001), CD4+ (p < 0.001), and CD8+ TILs (p < 0.001). Furthermore, high IDO1 mRNA expression and protein level were found to be associated with enhanced responsiveness to pro-inflammatory cytokines, particularly IFNG.

CONCLUSIONS

Our study provides evidence that IDO1 expression serves as a positive prognostic marker in HGSOC and is associated with an increased number of CD3+, CD4+ and CD8+ TILs. Understanding the intricate relationship between IDO1, TILs, and the tumor microenvironment may hold the key to improving outcomes in HGSOC.

Immunologic constant of rejection as a predictive biomarker of immune checkpoint inhibitors efficacy in non-small cell lung cancer

BACKGROUND

Anti-PD1/PDL1 immune checkpoint inhibitors (ICI) transformed the prognosis of patients with advanced non-small cell lung cancer (NSCLC). However, the response rate remains disappointing and toxicity may be life-threatening, making urgent identification of biomarkers predictive for efficacy. Immunologic Constant of Rejection signature (ICR) is a 20-gene expression signature of cytotoxic immune response with prognostic value in some solid cancers. Our objective was to assess its predictive value for benefit from anti-PD1/PDL1 in patients with advanced NSCLC.

METHODS

We retrospectively profiled 44 primary tumors derived from NSCLC patients treated with ICI as single-agent in at least the second-line metastatic setting. Transcriptomic analysis was performed using the nCounter® analysis system and the PanCancer Immune Profiling Panel. We then pooled our data with clinico-biological data from four public gene expression data sets, leading to a total of 162 NSCLC patients treated with single-agent anti-PD1/PDL1. ICR was applied to all samples and correlation was searched between ICR classes and the Durable Clinical Benefit (DCB), defined as stable disease or objective response according to RECIST 1.1 for a minimum of 6 months after the start of ICI.

RESULTS

The DCB rate was 29%; 22% of samples were classified as ICR1, 30% ICR2, 22% ICR3, and 26% ICR4. These classes were not associated with the clinico-pathological variables, but showed enrichment from ICR1 to ICR4 in quantitative/qualitative markers of immune response. ICR2-4 class was associated with a 5.65-fold DCB rate when compared with ICR1 class. In multivariate analysis, ICR classification remained associated with DCB, independently from PDL1 expression and other predictive immune signatures. By contrast, it was not associated with disease-free survival in 556 NSCLC TCGA patients untreated with ICI.

CONCLUSION

The 20-gene ICR signature was independently associated with benefit from anti-PD1/PDL1 ICI in patients with advanced NSCLC. Validation in larger retrospective and prospective series is warranted.

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.

Biomarkers for immune checkpoint inhibition in sarcomas - are we close to clinical implementation?

Sarcomas are a group of diverse and complex cancers of mesenchymal origin that remains poorly understood. Recent developments in cancer immunotherapy have demonstrated a potential for better outcomes with immune checkpoint inhibition in some sarcomas compared to conventional chemotherapy. Immune checkpoint inhibitors (ICIs) are key agents in cancer immunotherapy, demonstrating improved outcomes in many tumor types. However, most patients with sarcoma do not benefit from treatment, highlighting the need for identification and development of predictive biomarkers for response to ICIs. In this review, we first discuss United States (US) Food and Drug Administration (FDA)-approved and European Medicines Agency (EMA)-approved biomarkers, as well as the limitations of their use in sarcomas. We then review eight potential predictive biomarkers and rationalize their utility in sarcomas. These include gene expression signatures (GES), circulating neutrophil-to-lymphocyte ratio (NLR), indoleamine 2,3-dioxygenase (IDO), lymphocyte activation gene 3 (LAG-3), T cell immunoglobin and mucin domain-containing protein 3 (TIM-3), TP53 mutation status, B cells, and tertiary lymphoid structures (TLS). Finally, we discuss the potential for TLS as both a predictive and prognostic biomarker for ICI response in sarcomas to be implemented in the clinic.

Machine learning-based signature of necrosis-associated lncRNAs for prognostic and immunotherapy response prediction in cutaneous melanoma and tumor immune landscape characterization

Background

Cutaneous melanoma (CM) is one of the malignant tumors with a relative high lethality. Necroptosis is a novel programmed cell death that participates in anti-tumor immunity and tumor prognosis. Necroptosis has been found to play an important role in tumors like CM. However, the necroptosis-associated lncRNAs' potential prognostic value in CM has not been identified.

Methods

The RNA sequencing data collected from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression Project (GTEx) was utilized to identify differentially expressed genes in CM. By using the univariate Cox regression analysis and machine learning LASSO algorithm, a prognostic risk model had been built depending on 5 necroptosis-associated lncRNAs and was verified by internal validation. The performance of this prognostic model was assessed by the receiver operating characteristic curves. A nomogram was constructed and verified by calibration. Furthermore, we also performed sub-group K-M analysis to explore the 5 lncRNAs' expression in different clinical stages. Function enrichment had been analyzed by GSEA and ssGSEA. In addition, qRT-PCR was performed to verify the five lncRNAs' expression level in CM cell line (A2058 and A375) and normal keratinocyte cell line (HaCaT).

Results

We constructed a prognostic model based on five necroptosis-associated lncRNAs (AC245041.1, LINC00665, AC018553.1, LINC01871, and AC107464.3) and divided patients into high-risk group and low-risk group depending on risk scores. A predictive nomogram had been built to be a prognostic indicator to clinical factors. Functional enrichment analysis showed that immune functions had more relationship and immune checkpoints were more activated in low-risk group than that in high-risk group. Thus, the low-risk group would have a more sensitive response to immunotherapy.

Conclusion

This risk score signature could be used to divide CM patients into low- and high-risk groups, and facilitate treatment strategy decision making that immunotherapy is more suitable for those in low-risk group, providing a new sight for CM prognostic evaluation.

Immune checkpoint therapy-current perspectives and future directions

Immune checkpoint therapy (ICT) has dramatically altered clinical outcomes for cancer patients and conferred durable clinical benefits, including cure in a subset of patients. Varying response rates across tumor types and the need for predictive biomarkers to optimize patient selection to maximize efficacy and minimize toxicities prompted efforts to unravel immune and non-immune factors regulating the responses to ICT. This review highlights the biology of anti-tumor immunity underlying response and resistance to ICT, discusses efforts to address the current challenges with ICT, and outlines strategies to guide the development of subsequent clinical trials and combinatorial efforts with ICT.

PVRIG Expression Is an Independent Prognostic Factor and a New Potential Target for Immunotherapy in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a frequent and deadly cancer in need of new treatments. Immunotherapy has shown promising results in several solid tumors. The TIGIT/DNAM-1 axis gathers targets for new immune checkpoint inhibitors (ICIs). Here, we aimed at highlighting the potential of this axis as a new therapeutic option for HCC. For this, we built a large transcriptomic database of 683 HCC samples, clinically annotated, and 319 normal liver tissues. We interrogated this database for the transcriptomic expression of each member of the TIGIT/DNAM-1 axis and tested their prognostic value for survival. We then focused on the most discriminant one for these criteria, i.e., PVRIG, and analyzed the clinical characteristics, the disease-free and overall survivals, and biological pathways associated with PVRIG High tumors. Among all members of the TIGIT/DNAM-1 axis, PVRIG expression was higher in tumors than in normal liver, was heterogeneous across tumors, and was the only member with independent prognostic value for better survival. PVRIG High tumors were characterized by a higher lymphocytic infiltrate and enriched for signatures associated with tertiary lymphoid structures and better anti-tumor immune response. These results suggest that patients with PVRIG High tumors might be good candidates for immune therapy involving ICIs, notably ICIs targeting the TIGIT/DNAM-1 axis. Further functional and clinical validation is urgently required.

Immunotherapy resistance in non-small-cell lung cancer: From mechanism to clinical strategies

The high primary resistance incidence and unavoidable secondary resistance are the major clinical obstacle to lasting long-term benefits in Non-small-cell lung cancer (NSCLC) patients treated with immunotherapy. The mechanisms of immunotherapy resistance in NSCLC are complex, mainly involving tumor cells and tumor microenvironment (TME) infiltrating immune cells, including TAMs, B cells, NK cells, and T cells. The selection of clinical strategies for NSCLC progression after immunotherapy resistance should depend on the progressive mode. The progression pattern of NSCLC patients after immunotherapy resistance can be divided into oligo-progression and systemic/multiple progression, which should be considered for further treatment selection. In the future, it needs to explore how to optimize the combined therapy and explore strategies to reprogram infiltrating immune cells under various genetic backgrounds of tumor cells and timely reshape TME during antitumor treatments.

Response to Immune Checkpoint Inhibitors Is Affected by Deregulations in the Antigen Presentation Machinery: A Systematic Review and Meta-Analysis

Immune checkpoint inhibitors (ICI) targeting programmed death 1 (PD-1), its ligand (PD-L1), or cytotoxic T-lymphocyte antigen 4 (CTLA-4) have shown promising results against multiple cancers, where they reactivate exhausted T cells primed to eliminate tumor cells. ICI therapies have been particularly successful in hypermutated cancers infiltrated with lymphocytes. However, resistance may appear in tumors evading the immune system through alternative mechanisms than the PD-1/PD-L1 or CTLA-4 pathways. A systematic pan-cancer literature search was conducted to examine the association between alternative immune evasion mechanisms via the antigen presentation machinery (APM) and resistance towards ICI treatments targeting PD-1 (pembrolizumab and nivolumab), PD-L1 (durvalumab, avelumab, and atezolizumab), and CTLA-4 (ipilimumab). The APM proteins included the human leucocyte antigen (HLA) class I, its subunit beta-2 microglobulin (B2M), the transporter associated with antigen processing (TAP) 1, TAP2, and the NOD-like receptor family CARD domain containing 5 (NLRC5). In total, 18 cohort studies (including 21 original study cohorts) containing 966 eligible patients and 9 case studies including 12 patients were reviewed. Defects in the APM significantly predicted poor clinical benefit with an odds ratio (OR) of 0.39 (95% CI 0.24−0.63, p < 0.001). The effect was non-significant, when considering complete and partial responses only (OR = 0.52, 95% CI 0.18−1.47, p = 0.216). In summary, the APM contains important targets for tumorigenic alterations which may explain insensitivity towards ICI therapy.

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.

CSPG4 expression in soft tissue sarcomas is associated with poor prognosis and low cytotoxic immune response

Background

Soft tissue sarcomas (STS) are heterogeneous and pro-metastatic tumors. Identification of accurate prognostic factors and novel therapeutic targets are crucial. CSPG4 is a cell surface proteoglycan with oncogenic functions. It recently emerged as a potential target for immunotherapy, including cell therapy based on CSPG4-specific chimeric antigen receptor (CAR)-redirected cytokine-induced killer lymphocytes (CSPG4-CAR.CIKs) in STS. However, expression of CSPG4 is poorly known in STS so far.

Methods

We analyzed CSPG4 gene expression in 1378 localized STS clinical samples, and searched for correlations with clinicopathological data, including disease-free survival (DFS), and with tumor immune features.

Results

CSPG4 expression was heterogeneous across samples. High expression was associated with younger patients’ age, more frequent undifferentiated pleomorphic sarcoma and myxofibrosarcoma pathological subtypes, more frequent internal trunk tumor site, and more CINSARC high-risk samples. No correlation existed with pathological tumor size and grade, and tumor depth. Patients with high CSPG4 expression displayed 49% (95% CI 42–57) 5-year DFS versus 61% (95% CI 56–68) in patients with low expression (p = 3.17E−03), representing a 49% increased risk of event in the “CSPG4-high” group (HR = 1.49, 95% CI 1.14–1.94). This unfavorable prognostic value persisted in multivariate analysis, independently from other variables. There were significant differences in immune variables between “CSPG4-high” and “CSPG4-low” tumors. The "CSPG4-low" tumors displayed profiles suggesting higher anti-tumor cytotoxic immune response and higher potential vulnerability to immune checkpoint inhibitors (ICI). By contrast, the "CSPG4-high" tumors displayed profiles implying an immune-excluded tumor microenvironment, potentially induced by hypoxia, resulting from an immature chaotic microvasculature, and/or the presence of contractile myofibroblasts.

Conclusions

Patients with “CSPG4-high” STS, theoretically candidate for CAR.CIKs, display shorter DFS and an immune environment unfavorable to vulnerability to CAR.CIKs, which could be improved by combining anti-angiogenic drugs able to normalize the tumor vasculature. By contrast, “CSPG4-low” STS are better candidates for immune therapy involving ICI.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03679-y.

The immune-related role of beta-2-microglobulin in melanoma

Despite the remarkable success of immunotherapy in the treatment of melanoma, resistance to these agents still affects patient prognosis and response to therapies. Beta-2-microglobulin (β2M), an important subunit of major histocompatibility complex (MHC) class I, has important biological functions and roles in tumor immunity. In recent years, increasing studies have shown that B2M gene deficiency can inhibit MHC class I antigen presentation and lead to cancer immune evasion by affecting β2M expression. Based on this, B2M gene defect and T cell-based immunotherapy can interact to affect the efficacy of melanoma treatment. Taking into account the many recent advances in B2M-related melanoma immunity, here we discuss the immune function of the B2M gene in tumors, its common genetic alteration in melanoma, and its impact on and related improvements in melanoma immunotherapy. Our comprehensive review of β2M biology and its role in tumor immunotherapy contributes to understanding the potential of B2M gene as a promising melanoma therapeutic target.

CD69 and SBK1 as potential predictors of responses to PD-1/PD-L1 blockade cancer immunotherapy in lung cancer and melanoma

Background

PD-1/PD-L1 blockade is a promising immunotherapeutic strategy with the potential to improve the outcomes of various cancers. However, there is a critically unmet need for effective biomarkers of response to PD-1/PD-L1 blockade.

Materials and methods

Potential biomarkers of response to PD-1/PD-L1 blockade were obtained from the Cancer Treatment Response gene signature Database (CTR-DB). A comprehensive pan-cancer analysis was done on The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) datasets. Correlations between gene expression and infiltration by immune cells were assessed using TIMER, EPIC, MCPcounter, xCell, CIBERSORT, and quanTIseq. Immunophenoscore (IPS) was used to assess the potential application of the biomarkers to all TCGA tumors.

Results

Analysis of CTR-DB data identified CD69 and SBK1 as potential biomarkers of response to PD-1/PD-L1 blockade. Correlation analysis revealed that in various TCGA cancer datasets, CD69 expression level correlated positively with most immune checkpoints and tumor-infiltrating immune cells, while SBK1 expression level correlated negatively with infiltrating immune cells. IPS analysis demonstrated the ability of CD69 and SBK1 to predict PD-1/PD-L1 blockade responses in various cancers.

Conclusion

CD69 and SBK1 are potential predictors of response to cancer immunotherapy using PD-1/PD-L1 blockade. These biomarkers may guide treatment decisions, leading to precise treatment and minimizing the waste of medical resources.

Inference of age-associated transcription factor regulatory activity changes in single cells

Transcription factors (TFs) control cell identity and function. How their activity is altered during healthy aging is critical for an improved understanding of aging and disease risk, yet relatively little is known about such changes at cell-type resolution. Here we present and validate a TF activity estimation method for single cells from the hematopoietic system that is based on TF regulons, and apply it to a mouse single-cell RNA-sequencing atlas, to infer age-associated differentiation activity changes in the immune cells of different organs. This revealed an age-associated signature of macrophage dedifferentiation, which is shared across tissue types, and aggravated in tumor-associated macrophages. By extending the analysis to all major cell types, we reveal cell-type and tissue-type-independent age-associated alterations to regulatory factors controlling antigen processing, inflammation, collagen processing and circadian rhythm, that are implicated in age-related diseases. Finally, our study highlights the limitations of using TF expression to infer age-associated changes, underscoring the need to use regulatory activity inference methods.

HLA Class I Downregulation in Progressing Metastases of Melanoma Patients Treated With Ipilimumab

Characterization of the molecular mechanisms underlying antitumor immune responses and immune escape mechanisms has resulted in the development of more effective immunotherapeutic strategies, including immune checkpoint inhibitor (ICI) therapy. ICIs can induce durable responses in patients with advanced cancer in a wide range of cancer types, however, the majority of the patients fail to respond to this therapy or develop resistance in the course of the treatment. Information about the molecular mechanisms underlying primary and acquired resistance is limited. Although HLA class I molecules are crucial in the recognition of tumor antigens by cytotoxic T lymphocytes, only a few studies have investigated the role of their expression level on malignant cells in ICI resistance. To address this topic, utilizing immunohistochemical staining with monoclonal antibodies (mAbs) we analyzed HLA class I expression level in pre-treatment and post-treatment tumor samples from melanoma patients treated with ipilimumab. Twenty-nine metastases removed from six patients were available for the study, including 18 pre-treatment and 11 post-treatment lesions. Compared to metastases excised before ipilimumab therapy, post-treatment lesions displayed a significantly lower HLA class I expression level on melanoma cells; HLA class I downregulation was most marked in progressing metastases from nonresponding patients. We also evaluated the level of infiltration by CD8⁺ T cells and NK cells but did not find consistent changes between pre- and post-treatment samples. Our results indicate the potential role of HLA class I downregulation as a mechanism of ICI resistance.