Mutational and putative neoantigen load predict clinical benefit of adoptive T cell therapy in melanoma

Decoding Strategies to Evade Immunoregulators Galectin-1, -3, and -9 and Their Ligands as Novel Therapeutics in Cancer Immunotherapy

Galectins are a family of ß-galactoside-binding proteins that play a variety of roles in normal physiology. In cancer, their expression levels are typically elevated and often associated with poor prognosis. They are known to fuel a variety of cancer progression pathways through their glycan-binding interactions with cancer, stromal, and immune cell surfaces. Of the 15 galectins in mammals, galectin (Gal)-1, -3, and -9 are particularly notable for their critical roles in tumor immune escape. While these galectins play integral roles in promoting cancer progression, they are also instrumental in regulating the survival, differentiation, and function of anti-tumor T cells that compromise anti-tumor immunity and weaken novel immunotherapies. To this end, there has been a surge in the development of new strategies to inhibit their pro-malignancy characteristics, particularly in reversing tumor immunosuppression through galectin-glycan ligand-targeting methods. This review examines some new approaches to evading Gal-1, -3, and -9-ligand interactions to interfere with their tumor-promoting and immunoregulating activities. Whether using neutralizing antibodies, synthetic peptides, glyco-metabolic modifiers, competitive inhibitors, vaccines, gene editing, exo-glycan modification, or chimeric antigen receptor (CAR)-T cells, these methods offer new hope of synergizing their inhibitory effects with current immunotherapeutic methods and yielding highly effective, durable responses.

Surveying lncRNA-lncRNA cooperations reveals dominant effect on tumor immunity cross cancers

Long non-coding RNAs (lncRNAs) can crosstalk with each other by post-transcriptionally co-regulating genes involved in the same or similar functions; however, the regulatory principles and biological insights in tumor-immune are still unclear. Here, we show a multiple-step model to identify lncRNA-lncRNA immune cooperation based on co-regulating functional modules by integrating multi-omics data across 20 cancer types. Moreover, lncRNA immune cooperative networks (LICNs) are constructed, which are likely to modulate tumor-immune microenvironment by regulating immune-related functions. We highlight conserved and rewired network hubs which can regulate interactions between immune cells and tumor cells by targeting ligands and activating or inhibitory receptors such as PDCD1, CTLA4 and CD86. Immune cooperative lncRNAs (IC-lncRNAs) playing central roles in many cancers also tend to target known anticancer drug targets. In addition, these IC-lncRNAs tend to be highly expressed in immune cell populations and are significantly correlated with immune cell infiltration. The similar immune mechanisms cross cancers are revealed by the LICNs. Finally, we identify two subtypes of skin cutaneous melanoma with different immune context and prognosis based on IC-lncRNAs. In summary, this study contributes to a comprehensive understanding of the cooperative behaviours of lncRNAs and accelerating discovery of lncRNA-based biomarkers in cancer.

Comprehensive Pan-Cancer Analyses of Immunogenic Cell Death as a Biomarker in Predicting Prognosis and Therapeutic Response

Immunogenic cell death (ICD), a form of regulated cell death, is related to anticancer therapy. Due to the absence of widely accepted markers, characterizing ICD-related phenotypes across cancer types remained unexplored. Here, we defined the ICD score to delineate the ICD landscape across 33 cancerous types and 31 normal tissue types based on transcriptomic, proteomic and epigenetics data from multiple databases. We found that ICD score showed cancer type-specific association with genomic and immune features. Importantly, the ICD score had the potential to predict therapy response and patient prognosis in multiple cancer types. We also developed an ICD-related prognostic model by machine learning and cox regression analysis. Single-cell level analysis revealed intra-tumor ICD state heterogeneity and communication between ICD-based clusters of T cells and other immune cells in the tumor microenvironment in colon cancer. For the first time, we identified IGF2BP3 as a potential ICD regulator in colon cancer. In conclusion, our study provides a comprehensive framework for evaluating the relation between ICD and clinical relevance, gaining insights into identification of ICD as a potential cancer-related biomarker and therapeutic target.

ACAP1 Deficiency Predicts Inferior Immunotherapy Response in Solid Tumors

BACKGROUND

ACAP1 plays a key role in endocytic recycling, which is essential for the normal function of lymphocytes. However, the expression and function of ACAP1 in lymphocytes have rarely been studied.

METHODS

Large-scale genomic data, including multiple bulk RNA-sequencing datasets, single-cell sequencing datasets, and immunotherapy cohorts, were exploited to comprehensively characterize ACAP1 expression, regulation, and function. Gene set enrichment analysis (GSEA) was used to uncover the pathways associated with ACAP1 expression. Eight algorithms, including TIMER, CIBERSORT, CIBERSORT-ABS, QUANTISEQ, xCELL, MCPCOUNTER, EPIC, and TIDE, were applied to estimate the infiltrating level of immune cells. Western blotting, qPCR, and ChIP-PCR were used to validate the findings from bioinformatic analyses. A T-cell co-culture killing assay was used to investigate the function of ACAP1 in lymphocytes.

RESULTS

ACAP1 was highly expressed in immune-related tissues and cells and minimally in other tissues. Moreover, single-cell sequencing analysis in tumor samples revealed that ACAP1 is expressed primarily in tumor-infiltrating lymphocytes (TILs), including T, B, and NK cells. ACAP1 expression is negatively regulated by promoter DNA methylation, with its promoter hypo-methylated in immune cells but hyper-methylated in other cells. Furthermore, SPI1 binds to the ACAP1 promoter and positively regulates its expression in immune cells. ACAP1 levels positively correlate with the infiltrating levels of TILs, especially CD8+ T cells, across a broad range of solid cancer types. ACAP1 deficiency is associated with poor prognosis and immunotherapeutic response in multiple cancer types treated with checkpoint blockade therapy (ICT). Functionally, the depletion of ACAP1 by RNA interference significantly impairs the T cell-mediated killing of tumor cells.

CONCLUSIONS

Our study demonstrates that ACAP1 is essential for the normal function of TILs, and its deficiency indicates an immunologically "cold" status of tumors that are resistant to ICT.

Integration of cancer stemness and neoantigen load to predict responsiveness to anti-PD1/PDL1 therapy

Background: Anti-programmed cell death 1/programmed cell death ligand 1 (PD1/PDL1) therapy is an important part of comprehensive cancer therapy. However, many patients suffer from non-response to therapy. Tumor neoantigen burden (TNB) and cancer stemness play essential roles in the responsiveness to therapy. Therefore, the identification of drug candidates for anti-PD1/PDL1 therapy remains an unmet need.

Methods: Three anti-PD1/PDL1 therapy cohorts were obtained from GEO database and published literatures. Cancer immune characteristics were analyzed using CIBERSORTX, GSVA, and ESTIMATE. WGCNA was employed to identify the gene modules correlated with cancer TNB and stemness. A machine-learning method was used to construct the immunotherapy resistance score (TSIRS). Pharmacogenomic analysis was conducted to explore the potential alternative drugs for anti-PD1/PDL1 therapy resistant patients. CCK-8 assay, EdU assay and wound healing assay were used to validate the effect of the predicted drug on cancer cells.

Results: The therapy response and non-response cancer groups have different microenvironment features. TSIRS was developed based on tumor neoantigen and stemness. TSIRS can effectively predict the outcomes of patients with anti-PD1/PDL1 therapy in training, validation and meta cohorts. Meanwhile, TSIRS can reflect the characteristics of tumor microenvironment during anti-PD1/PDL1 therapy. PF-4708671 is identified as a potential alternative drug for patients with resistance to anti-PD1/PDL1 therapy. It possesses significant inhibitive effect on the proliferation and migration of BGC-823 cells.

Conclusion: TSIRS is an effective tool in the identification of candidate patients who will be benefit from anti-PD1/PDL1 therapy. Small molecule drug PF-4708671 has the potential to be used in anti-PD1/PDL1 therapy resistant patients.

Tumor Microenvironment Characterization in Breast Cancer Identifies Prognostic Pathway Signatures

Breast cancer is one of the most common female malignancies worldwide. Due to its early metastases formation and a high degree of malignancy, the 10 year-survival rate of metastatic breast cancer does not exceed 30%. Thus, more precise biomarkers are urgently needed. In our study, we first estimated the tumor microenvironment (TME) infiltration using the xCell algorithm. Based on TME infiltration, the three main TME clusters were identified using consensus clustering. Our results showed that the three main TME clusters cause significant differences in survival rates and TME infiltration patterns (log-rank test, p = 0.006). Then, multiple machine learning algorithms were used to develop a nine-pathway-based TME-related risk model to predict the prognosis of breast cancer (BRCA) patients (the immune-related pathway-based risk score, defined as IPRS). Based on the IPRS, BRCA patients were divided into two subgroups, and patients in the IPRS-low group presented significantly better overall survival (OS) rates than the IPRS-high group (log-rank test, p < 0.0001). Correlation analysis revealed that the IPRS-low group was characterized by increases in immune-related scores (cytolytic activity (CYT), major histocompatibility complex (MHC), T cell-inflamed immune gene expression profile (GEP), ESTIMATE, immune, and stromal scores) while exhibiting decreases in tumor purity, suggesting IPRS-low patients may have a strong immune response. Additionally, the gene-set enrichment analysis (GSEA) result confirmed that the IPRS-low patients were significantly enriched in several immune-associated signaling pathways. Furthermore, multivariate Cox analysis revealed that the IPRS was an independent prognostic biomarker after adjustment by clinicopathologic characteristics. The prognostic value of the IPRS model was further validated in three external validation cohorts. Altogether, our findings demonstrated that the IPRS was a powerful predictor to screen out certain populations with better prognosis in breast cancer and may serve as a potential biomarker guiding clinical treatment decisions.

Tumor-infiltrating lymphocytes for treatment of solid tumors: It takes two to tango?

Tumor-infiltrating lymphocytes (TILs), frontline soldiers of the adaptive immune system, are recruited into the tumor site to fight against tumors. However, their small number and reduced activity limit their ability to overcome the tumor. Enhancement of TILs number and activity against tumors has been of interest for a long time. A lack of knowledge about the tumor microenvironment (TME) has limited success in primary TIL therapies. Although the advent of engineered T cells has revolutionized the immunotherapy methods of hematologic cancers, the heterogeneity of solid tumors warrants the application of TILs with a wide range of specificity. Recent advances in understanding TME, immune exhaustion, and immune checkpoints have paved the way for TIL therapy regimens. Nowadays, TIL therapy has regained attention as a safe personalized immunotherapy, and currently, several clinical trials are evaluating the efficacy of TIL therapy in patients who have failed conventional immunotherapies. Gaining favorable outcomes following TIL therapy of patients with metastatic melanoma, cervical cancer, ovarian cancer, and breast cancer has raised hope in patients with refractory solid tumors, too. Nevertheless, TIL therapy procedures face several challenges, such as high cost, timely expansion, and technical challenges in selecting and activating the cells. Herein, we reviewed the recent advances in the TIL therapy of solid tumors and discussed the challenges and perspectives.

Genomic landscape of the immunogenicity regulation in skin melanomas with diverse tumor mutation burden

Skin melanoma cells are tightly interconnected with their tumor microenvironment (TME), which influences their initiation, progression, and sensitivity/resistance to therapeutic interventions. An immune-active TME favors patient response to immune checkpoint inhibition (ICI), but not all patients respond to therapy. Here, we assessed differential gene expression in primary and metastatic tumors from the TCGA-SKCM dataset, compared to normal skin samples from the GTEx project and validated key findings across 4 independent GEO datasets, as well as using immunohistochemistry in independent patient cohorts. We focused our attention on examining the expression of various immune receptors, immune-cell fractions, immune-related signatures and mutational signatures across cutaneous melanomas with diverse tumor mutation burdens (TMB). Globally, the expression of most immunoreceptors correlated with patient survival, but did not differ between TMBhigh and TMBlow tumors. Melanomas were enriched in "naive T-cell", "effector memory T-cell", "exhausted T-cell", "resting Treg T-cell" and "Th1-like" signatures, irrespective of their BRAF, NF1 or RAS mutational status. Somatic mutations in IDO1 and HLA-DRA were frequent and could be involved in hindering patient response to ICI therapies. We finally analyzed transcriptome profiles of ICI-treated patients and associated their response with high levels of IFNγ, Merck18, CD274, CD8, and low levels of myeloid-derived suppressor cells (MDSCs), cancer-associated fibroblasts (CAFs) and M2 macrophages, irrespective of their TMB status. Overall, our findings highlight the importance of pre-existing T-cell immunity in ICI therapeutic outcomes in skin melanoma and suggest that TMBlow patients could also benefit from such therapies.

Changes in the Immune Cell Repertoire for the Treatment of Malignant Melanoma

Immune checkpoint inhibitors (ICIs) have been used for the treatment of various types of cancers, including malignant melanoma. Mechanistic exploration of tumor immune responses is essential to improve the therapeutic efficacy of ICIs. Since tumor immune responses are based on antigen-specific immune responses, investigators have focused on T cell receptors (TCRs) and have analyzed changes in the TCR repertoire. The proliferation of T cell clones against tumor antigens is detected in patients who respond to treatment with ICIs. The proliferation of these T cell clones is observed within tumors as well as in the peripheral blood. Clonal proliferation has been detected not only in CD8-positive T cells but also in CD4-positive T cells, resident memory T cells, and B cells. Moreover, changes in the repertoire at an early stage of treatment seem to be useful for predicting the therapeutic efficacy of ICIs. Further analyses of the repertoire of immune cells are desirable to improve and predict the therapeutic efficacy of ICIs.

Pan-Cancer Analysis of the Prognostic and Immunotherapeutic Value of MITD1

Microtubule-interacting and trafficking domain containing 1 (MITD1) is associated with abscission during cytokinesis. However, systematic investigation into its role in cancer is lacking. Therefore, we explored the pan-cancer role of MITD1 using multiple databases. Expression and clinical survival, immunological, and enrichment analyses were performed using R packages and online tools. For breast cancer, single-cell level analysis, immunochemistry, and in vitro experiments were performed to explore the mechanism of MITD1. A nomogram was established to predict the prognosis of patients with breast cancer and evaluate the immunotherapy biomarker based on two datasets. In some cancers, high MITD1 expression was associated with a more favorable prognosis. For instance, it inhibited tumor cell proliferation and migration in breast cancer. MITD1 may regulate cancer development by altering the tumor microenvironment, and MITD1 expression may predict the response to immune checkpoint blockade, platinum, and poly ADP-ribose polymerase inhibitor therapies. Our nomogram was used to determine the prognosis of patients with breast cancer. MITD1 can also predict the response to immunotherapy. Our first pan-cancer study of MITD1 has shown that it plays different roles in cancer development and therapy. In breast cancer, MITD1 inhibited cell proliferation and migration and serves as a new biomarker.

The integrated landscape of eRNA in gastric cancer reveals distinct immune subtypes with prognostic and therapeutic relevance

The comprehensive regulation effect of eRNA on tumor immune cell infiltration and the outcome remains obscure. We comprehensively identify the eRNA-mediated immune infiltration patterns of gastric cancer (GC) samples. We creatively proposed a random forest machine-learning (ML) algorithm to map eRNA to mRNA expression patterns. The eRNA score was constructed using principal component analysis algorithms and validated in an independent cohort. Three subtypes with distinct eRNA expression patterns were determined in GC. There were significant differences between the three subtypes in the overall survival rate, immune cell infiltration characteristics, and immunotherapy response indicators. The patients in the high eRNA score group have a higher overall survival rate and might benefit from immunotherapy. This work revealed that eRNA regulation might be a new prognostic index and might offer a potential biomarker in the response of immunotherapy. Evaluating the eRNA regulation manner of GC will contribute to guiding more effective immunotherapy strategies.

Next generation T cell therapies for solid cancers

Tumor-infiltrating lymphocytes show consistent clinical benefit in metastatic melanoma, but they are a poorly defined product with variable antitumor activity. In this issue, Palmer et al.¹ create for clinical testing a cell product consisting of highly functional tumor-reactive T cells by knocking out CISH, an inhibitor of T cell activation.

Integrative genomic analysis facilitates precision strategies for glioblastoma treatment

Glioblastoma (GBM) is the most common form of malignant primary brain tumor with a dismal prognosis. Currently, the standard treatments for GBM rarely achieve satisfactory results, which means that current treatments are not individualized and precise enough. In this study, a multiomics-based GBM classification was established and three subclasses (GPA, GPB, and GPC) were identified, which have different molecular features both in bulk samples and at single-cell resolution. A robust GBM poor prognostic signature (GPS) score model was then developed using machine learning method, manifesting an excellent ability to predict the survival of GBM. NVP−BEZ235, GDC−0980, dasatinib and XL765 were ultimately identified to have subclass-specific efficacy targeting patients with a high risk of poor prognosis. Furthermore, the GBM classification and GPS score model could be considered as potential biomarkers for immunotherapy response. In summary, an integrative genomic analysis was conducted to advance individual-based therapies in GBM.

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A multiomics-based classification of GBM was established

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Single-cell transcriptomic profiling of GBM subclasses was revealed using Scissor

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A robust prognostic risk model was developed for GBM by machine learning method

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Prediction of potential agents based on molecular and prognostic risk stratification

An integrated analysis of C5AR2 related to malignant properties and immune infiltration of gliomas

Background

C5AR2 is recognized as a proinflammatory molecule and activates the inflammatory response in multiple disorders. However, little has been reported on C5AR2 in glioma. This study sought to explore its expression, biological function, and association with clinical pathological indicators, prognosis, and immune infiltration levels in glioma through glioma cohorts.

Methods

A cohort of 657 patients was screened from the Chinese Glioma Genome Atlas (CGGA). χ 2 test was performed to calculate the difference of classified variables. Cox proportional hazard regression modeling was used to identify independent prognostic indicators of glioma patients. A survival plot was generated by the Kaplan-Meier method. The immune cell infiltration score of glioma patients was calculated by TIMER algorithm.

Results

We observed that high expression of C5AR2 was strongly associated with malignant clinical indicators in 657 patients with glioma, and patients with high C5AR2 expression had worse prognoses. Multivariate Cox analysis showed that C5AR2 could be a new independent prognostic indicator for glioma patients. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed that C5AR2 overexpression correlated with multiple inflammatory and immune biological processes. Additionally, high C5AR2 expression was strongly associated with higher abundance and marker gene expression of multiple tumor immune cells in low-grade glioma. Finally, a model was constructed to improve the prognostic evaluation of glioma patients.

Conclusions

The C5AR2 gene is highly expressed in gliomas and is significantly associated with clinical indicators of malignant progression in glioma patients. In glioma, patients with high C5AR2 expression displayed a worse outcome. In glioma tissues, the expression level of C5AR2 highly correlated with the abundance of tumor immune cell infiltration. Additionally, GO and KEGG enrichment analysis revealed that C5AR2 expression may be involved in a variety of immune and inflammatory biological processes.

Prognostic stratification based on m5C regulators acts as a novel biomarker for immunotherapy in hepatocellular carcinoma

Background

Immunotherapy is a promising anti-cancer strategy in hepatocellular carcinoma (HCC). However, a limited number of patients can benefit from it. There are currently no reliable biomarkers available to find the potential beneficiaries. Methylcytosine (m⁵C) is crucial in HCC, but its role in forecasting clinical responses to immunotherapy has not been fully clarified.

Methods

In this study, we analyzed 371 HCC patients from The Cancer Genome Atlas (TCGA) database and investigated the expression of 18 m⁵C regulators. We selected 6 differentially expressed genes (DEGs) to construct a prognostic risk model as well as 2 m⁵C-related diagnostic models.

Results

The 1-, 3-, and 5-year area under the curve (AUC) of m⁵C scores for the overall survival (OS) was 0.781/0.762/0.711, indicating the m⁵C score system had an ideal distinction of prognostic prediction for HCC. The survival analysis showed that patients with high-risk scores present a worse prognosis than the patients with low-risk scores (p< 0.0001). We got consistent results in 6 public cohorts and validated them in Xiangya real-world cohort by quantitative real-time PCR and immunohistochemical (IHC) assays. The high-m⁵C score group was predicted to be in an immune evasion state and showed low sensitivity to immunotherapy, but high sensitivity to chemotherapy and potential targeted drugs and agents, such as sepantronium bromide (YM-155), axitinib, vinblastine and docetaxel. Meanwhile, we also constructed two diagnostic models to distinguish HCC tumors from normal liver tissues or liver cirrhosis.

Conclusion

In conclusion, our study helps to early screen HCC patients and select patients who can benefit from immunotherapy. Step forwardly, for the less likely beneficiaries, this study provides them with new potential targeted drugs and agents for choice to improve their prognosis.

Pan-cancer analysis reveals interleukin-17 family members as biomarkers in the prediction for immune checkpoint inhibitor curative effect

Background

The interleukin-17 (IL-17) family contains six homologous genes, IL-17A to IL-17F. Growing evidence indicates that dysregulated IL-17 family members act as major pathogenic factors in the early and late stages of cancer development and progression. However, the prevalence and predictive value of IL-17 for immune checkpoint inhibitor (ICI) therapeutic effectiveness in multiple tumor types remain largely unknown, and the associations between its expression levels and immunotherapy-associated signatures also need to be explored.

Methods

The pan-cancer dataset in The Cancer Genome Atlas (TCGA) was downloaded from UCSC Xena (http://xena.ucsc.edu/). The immunotherapeutic cohorts included IMvigor210, which were obtained from the Gene Expression Omnibus database and included in a previously published study. Other datasets, namely, the GEO dataset and PRECOG, GEO, and METABRIC databases, were also included. In 33 TCGA tumor types, a pan-cancer analysis was carried out including their expression map, clinical risk assessment, and immune subtype analysis, along with their association with the stemness indices, tumor microenvironment (TME) in pan-cancer, immune infiltration analysis, ICI-related immune indicators, and drug sensitivity. RT-PCR was also carried out to verify the gene expression levels among MCF-10A and MCF-7 cell lines.

Results

The expression of the IL-17 family is different between tumor and normal tissue in most cancers, and consistency has been observed between gene activity and gene expression. RT-PCR results show that the expression differences in the IL-17 family of human cell (MCF-10A and MCF-7) are consistent with the bioinformatics differential expression analysis. Moreover, the expression of the IL-17 family can be a sign of patients’ survival prognosis in some tumors and varies in different immune subtypes. Moreover, the expression of the IL-17 family presents a robust correlation with immune cell infiltration, ICI-related immune indicators, and drug sensitivity. High expression of the IL-17 family is significantly related to immune-relevant pathways, and the low expression of IL-17B means a better immunotherapeutic response in BLCA.

Conclusion

Collectively, IL-17 family members may act as biomarkers in predicting the prognosis of the tumor and the therapeutic effects of ICIs, which provides new guidance for cancer treatment.

Adoptive cell therapies in thoracic malignancies

Immunotherapy has gained great interest in thoracic malignancies in the last decade, first in non-small cell lung cancer (NSCLC), but also more recently in small-cell lung cancer (SCLC) and malignant pleural mesothelioma (MPM). However, while 15-20% of patients will greatly benefit from immune checkpoint blockers (ICBs), a vast majority will rapidly exhibit resistance. Reasons for this are multiple: non-immunogenic tumors, immunosuppressive tumor microenvironment or defects in immune cells trafficking to the tumor sites being some of the most frequent. Current progress in adoptive cell therapies could offer a way to overcome these hurdles and bring effective immune cells to the tumor site. In this review, we discuss advantages, limits and future perspectives of adoptive cell therapy (ACT) in thoracic malignancies from lymphokine-activated killer cells (LAK), cytokine-induced killer cells (CIK), natural killer cells (NK), dendritic cells (DC) vaccines and tumor-infiltrating lymphocytes (TILs) to TCR engineering and CARs. Trials are still in their early phases, and while there may still be many limitations to overcome, a combination of these different approaches with ICBs, chemotherapy and/or radiotherapy could vastly improve the way we treat thoracic cancers.

Core immune cell infiltration signatures identify molecular subtypes and promote precise checkpoint immunotherapy in cutaneous melanoma

Yutao Wang, China Medical University, ChinaThe tumor microenvironment (TME) has been shown to impact the prognosis of tumors in patients including cutaneous melanoma (CM); however, not all components of TME are important. Given the aforementioned situation, the functional immune cell contents correlated with CM patient prognosis are needed to optimize present predictive models and reflect the overall situation of TME. We developed a novel risk score named core tumor-infiltrating immune cell score (cTICscore), which showed certain advantages over existing biomarkers or TME-related signatures in predicting the prognosis of CM patients. Furthermore, we explored a new gene signature named cTILscore−related module gene score (cTMGs), based on four identified TME-associated genes (GCH1, GZMA, PSMB8, and PLAAT4) showing a close correlation with the cTICscore, which was generated by weighted gene co-expression network analysis and least absolute shrinkage and selection operator analysis to facilitate clinical application. Patients with low cTMGs had significantly better overall survival (OS, P = 0.002,< 0.001, = 0.002, and = 0.03, respectively) in the training and validating CM datasets. In addition, the area under the curve values used to predict the immune response in four CM cohorts were 0.723, 0.723, 0.754, and 0.792, respectively, and that in one gastric cohort was 0.764. Therefore, the four-gene signature, based on cTICscore, might improve prognostic information, serving as a predictive tool for CM patients receiving immunotherapy.cutaneous melanoma, tumor microenvironment, prognosis, immunotherapy, cTICscore

Immunotherapy in soft tissue and bone sarcoma: unraveling the barriers to effectiveness

Sarcomas are uncommon malignancies of mesenchymal origin that can arise throughout the human lifespan, at any part of the body. Surgery remains the optimal treatment modality whilst response to conventional treatments, such as chemotherapy and radiation, is minimal. Immunotherapy has emerged as a novel approach to treat different cancer types but efficacy in soft tissue sarcoma and bone sarcoma is limited to distinct subtypes. Growing evidence shows that cancer-stroma cell interactions and their microenvironment play a key role in the effectiveness of immunotherapy. However, the pathophysiological and immunological properties of the sarcoma tumor microenvironment in relation to immunotherapy advances, has not been broadly reviewed. Here, we provide an up-to-date overview of the different immunotherapy modalities as potential treatments for sarcoma, identify barriers posed by the sarcoma microenvironment to immunotherapy, highlight their relevance for impeding effectiveness, and suggest mechanisms to overcome these barriers.

A m6A methyltransferase-mediated immune signature determines prognosis, immune landscape and immunotherapy efficacy in patients with lung adenocarcinoma

BACKGROUND

As the most abundant modification in mRNA, the N⁶-methyladenosine (m⁶A) RNA modification is involved in the occurrence and development of various tumors. However, the underlying functions of this alteration in the immune microenvironment of lung adenocarcinoma (LUAD) remain unknown.

METHODS

We identified m⁶A-mediated immune genes by performing a correlation analysis. Next, a m⁶A-mediated immune model was constructed using multiple machine learning algorithms, including univariate, least absolute shrinkage and selection operator, and multivariate Cox regression analyses. The potential of this model to predict the immune landscapes, drug sensitivities, and immunotherapy responses of different LUAD risk groups was studied.

RESULTS

A m⁶A-mediated immune model containing 13 m⁶A-mediated immune genes was established and found to be an independent predictor of survival time. The prognosis of low-risk patients was significantly better than that of high-risk patients. These two risk groups displayed different immune environments, genomic backgrounds, chemotherapy responses and immunotherapy response tendencies. The low- and high-risk groups strongly corresponded to the immune-hot and immune-cold phenotypes, respectively. The low-risk group was more enriched in immune-related biological processes, and the high-risk group was more enriched in proliferation-related biological processes. Furthermore, low-risk patients responded better to immunotherapy based on the results obtained from the tumor immune dysfunction and exclusion (TIDE) algorithm and subclass mapping algorithm using five external independent immunotherapy cohorts.

CONCLUSIONS

Our results suggest that the m⁶A modification participates in regulating the tumor microenvironment. The m⁶A-mediated immune model may be useful to predict the immunotherapy responses and outcomes of patients with LUAD.

Prediction of prognosis, immunogenicity and efficacy of immunotherapy based on glutamine metabolism in lung adenocarcinoma

BACKGROUND

Glutamine (Gln) metabolism has been reported to play an essential role in cancer. However, a comprehensive analysis of its role in lung adenocarcinoma is still unavailable. This study established a novel system of quantification of Gln metabolism to predict the prognosis and immunotherapy efficacy in lung cancer. Further, the Gln metabolism in tumor microenvironment (TME) was characterized and the Gln metabolism-related genes were identified for targeted therapy.

METHODS

We comprehensively evaluated the patterns of Gln metabolism in 513 patients diagnosed with lung adenocarcinoma (LUAD) based on 73 Gln metabolism-related genes. Based on differentially expressed genes (DEGs), a risk model was constructed using Cox regression and Lasso regression analysis. The prognostic efficacy of the model was validated using an individual LUAD cohort form Shandong Provincial Hospital, an integrated LUAD cohort from GEO and pan-cancer cohorts from TCGA databases. Five independent immunotherapy cohorts were used to validate the model performance in predicting immunotherapy efficacy. Next, a series of single-cell sequencing analyses were used to characterize Gln metabolism in TME. Finally, single-cell sequencing analysis, transcriptome sequencing, and a series of in vitro experiments were used to explore the role of EPHB2 in LUAD.

RESULTS

Patients with LUAD were eventually divided into low- and high-risk groups. Patients in low-risk group were characterized by low levels of Gln metabolism, survival advantage, "hot" immune phenotype and benefit from immunotherapy. Compared with other cells, tumor cells in TME exhibited the most active Gln metabolism. Among immune cells, tumor-infiltrating T cells exhibited the most active levels of Gln metabolism, especially CD8 T cell exhaustion and Treg suppression. EPHB2, a key gene in the model, was shown to promote LUAD cell proliferation, invasion and migration, and regulated the Gln metabolic pathway. Finally, we found that EPHB2 was highly expressed in macrophages, especially M2 macrophages. It may be involved in the M2 polarization of macrophages and mediate the negative regulation of M2 macrophages in NK cells.

CONCLUSION

This study revealed that the Gln metabolism-based model played a significant role in predicting prognosis and immunotherapy efficacy in lung cancer. We further characterized the Gln metabolism of TME and investigated the Gln metabolism-related gene EPHB2 to provide a theoretical framework for anti-tumor strategy targeting Gln metabolism.

Pan-Cancer HLA Gene-Mediated Tumor Immunogenicity and Immune Evasion

Human leukocyte antigen (HLA) expression contributes to the activation of antitumor immunity through interactions with T-cell receptors. Pan-cancer HLA-mediated immunogenicity and immunoediting mechanisms have not been systematically studied previously. In a retrospective analysis of 33 tumor types from the Cancer Genome Atlas (TCGA), we characterized the differential expression of HLA class I and class II genes across various oncogenic pathways and immune subtypes. While HLA I genes were upregulated in all immunogenically hot tumors, HLA II genes were upregulated in an inflammatory immune subtype associated with best prognosis and were systematically downregulated in specific oncogenic pathways. A subset of immunogenically hot tumors which upregulated HLA class I but not class II genes exploited HLA-mediated escape strategies. Furthermore, with a machine learning model, we demonstrated that HLA gene expression data can be used to predict the immune subtypes of patients receiving immune checkpoint blockade and stratify patient survival. Interestingly, tumors with the highest immune infiltration did not have the best prognosis but showed significantly higher immune exhaustion.

IMPLICATIONS

Taken together, we highlight the prognostic potential of HLA genes in immunotherapies and suggest that higher tumor immunogenicity mediated by HLA expression may sometimes lead to tumor escape under strong selective pressure.

Therapeutic Strategies to Enhance Tumor Antigenicity: Making the Tumor Detectable by the Immune System

Cancer immunotherapy has revolutionized the oncology field, but many patients still do not respond to current immunotherapy approaches. One of the main challenges in broadening the range of responses to this type of treatment is the limited source of tumor neoantigens. T cells constitute a main line of defense against cancer, and the decisive step to trigger their activation is mediated by antigen recognition. Antigens allow the immune system to differentiate between self and foreign, which constitutes a critical step in recognition of cancer cells and the consequent development or control of the malignancy. One of the keystones to achieving a successful antitumor response is the presence of potent tumor antigens, known as neoantigens. However, tumors develop strategies to evade the immune system and resist current immunotherapies, and many tumors present a low tumor mutation burden limiting the presence of tumor antigenicity. Therefore, new approaches must be taken into consideration to overcome these shortcomings. The possibility of making tumors more antigenic represents a promising front to further improve the success of immunotherapy in cancer. Throughout this review, we explored different state-of-the-art tools to induce the presentation of new tumor antigens by intervening at protein, mRNA or genomic levels in malignant cells.

Establishment of a Necroptosis-Related Prognostic Signature to Reveal Immune Infiltration and Predict Drug Sensitivity in Hepatocellular Carcinoma

Background: Hepatocellular carcinoma (HCC) is a common type of primary liver cancer and has a poor prognosis. In recent times, necroptosis has been reported to be involved in the progression of multiple cancers. However, the role of necroptosis in HCC prognosis remains elusive.

Methods: The RNA-seq data and clinical information of HCC patients were downloaded from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. Differentially expressed genes (DEGs) and prognosis-related genes were explored, and the nonnegative matrix factorization (NMF) clustering algorithm was applied to divide HCC patients into different subtypes. Based on the prognosis-related DEGs, univariate Cox and LASSO Cox regression analyses were used to construct a necroptosis-related prognostic model. The relationship between the prognostic model and immune cell infiltration, tumor mutational burden (TMB), and drug response were explored.

Results: In this study, 13 prognosis-related DEGs were confirmed from 18 DEGs and 24 prognostic-related genes. Based on the prognosis-related DEGs, patients in the TCGA cohort were clustered into three subtypes by the NMF algorithm, and patients in C3 had better survival. A necroptosis-related prognostic model was established according to LASSO analysis, and HCC patients in TCGA and ICGC were divided into high- and low-risk groups. Kaplan–Meier (K–M) survival analysis revealed that patients in the high-risk group had a shorter survival time compared to those in the low-risk group. Using univariate and multivariate Cox analyses, the prognostic model was identified as an independent prognostic factor and had better survival predictive ability in HCC patients compared with other clinical biomarkers. Furthermore, the results revealed that the high-risk patients had higher stromal, immune, and ESTIMATE scores; higher TP53 mutation rate; higher TMB; and lower tumor purities compared to those in the low-risk group. In addition, there were significant differences in predicting the drug response between the high- and low-risk groups. The protein and mRNA levels of these prognostic genes were upregulated in HCC tissues compared to normal liver tissues.

Conclusion: We established a necroptosis-related prognostic signature that may provide guidance for individualized drug therapy in HCC patients; however, further experimentation is needed to validate our results.

Neoantigens in precision cancer immunotherapy: from identification to clinical applications

Immunotherapies targeting cancer neoantigens are safe, effective, and precise. Neoantigens can be identified mainly by genomic techniques such as next-generation sequencing and high-throughput single-cell sequencing; proteomic techniques such as mass spectrometry; and bioinformatics tools based on high-throughput sequencing data, mass spectrometry data, and biological databases. Neoantigen-related therapies are widely used in clinical practice and include neoantigen vaccines, neoantigen-specific CD8+ and CD4+ T cells, and neoantigen-pulsed dendritic cells. In addition, neoantigens can be used as biomarkers to assess immunotherapy response, resistance, and prognosis. Therapies based on neoantigens are an important and promising branch of cancer immunotherapy. Unremitting efforts are needed to unravel the comprehensive role of neoantigens in anti-tumor immunity and to extend their clinical application. This review aimed to summarize the progress in neoantigen research and to discuss its opportunities and challenges in precision cancer immunotherapy.

Construction and Validation of an Epigenetic Regulator Signature as A Novel Biomarker For Prognosis, Immunotherapy, And Chemotherapy In Hepatocellular Carcinoma

Background

Epigenetic modification regulates various aspects of cancer biology, from tumor growth and invasion to immune microenvironment modulation. Whether epigenetic regulators (EGRs) can decide tumor malignant degree and risk of immune evasion in liver hepatocellular carcinoma (LIHC) remains unclear.

Method

An EGR signature called “EGRscore” was constructed based on bulk RNA-seq data of EGR in hepatocellular carcinoma (HCC). The correlation between EGRscore and overall survival (OS) was validated in HCC cohorts and other tumor cohorts. Mutation profiles, copy number alterations (CNAs), enriched pathways, and response to immunotherapy and chemotherapy were compared between EGRscore-high and EGRscore-low patients.

Results

We found that EGRscore was associated with OS in HCC as well as several tumors including glioma, uveal melanoma (UVM), and kidney tumors. A mechanism study demonstrated that the distinct mutation profile of TP53 was present in EGRscore-high and EGRscore-low patients. Meanwhile, EGRscore-low patients were characterized with immune cells that promote killing tumors. Furthermore, EGRscore was associated with genes regulating drug resistance in HCC. Finally, we indicated that EGRscore-low patients had higher response rates to immunotherapy and targeted therapy.

Conclusions

EGRscore could be used to distinguish OS, tumor progression, mutation pattern, and immune microenvironment. The present study contributes to improving hepatocellular carcinoma patient prognosis and predicting response to immunotherapy.

Genomic Analysis Uncovers the Prognostic and Immunogenetic Feature of Pyroptosis in Gastric Carcinoma: Indication for Immunotherapy

Crosstalk between pyroptosis and tumor immune microenvironment (TIME) in cancer has yet to be elucidated. Herein, we aimed to explore the role of pyroptosis and its association with TIME in gastric cancer. Unsupervised clustering was performed to identify the pyroptosis-related clusters. Pyroptosis risk score was constructed using LASSO Cox regression. Clinicopathological and genetic data of pyroptosis clusters and pyroptosis risk scores were explored. Reproducibility of pyroptosis risk score in predicting response to immunotherapy and screening potential antitumor drugs was also investigated. Three pyroptosis clusters with distinct prognosis, immune cell fractions and signatures, were constructed. A low-pyroptosis risk score was characterized by increased activated T-cell subtype and M1 macrophage, decreased M2 macrophage, higher MSI status, and TMB. Meanwhile, low-score significantly correlated with PD-L1 expression, antigen presentation markers, and IFN-γ signature. The 5-year AUCs of PRS were 0.67, 0.62, 0.65, 0.67, and 0.67 in the TCGA, three external public and one real-world validation (SYSUCC) cohorts. Multivariable analyses further validated the prognostic performance of the pyroptosis risk scoring system, with HRs of 2.43, 1.83, 1.78, 2.35, and 2.67 (all p &lt; 0.05) in the five cohorts. GSEA indicated significant enrichment of DNA damage repair pathways in the low-score group. Finally, the pyroptosis risk scoring system was demonstrated to be useful in predicting response to immunotherapy, and in screening potential antitumor drugs. Our study highlights the crucial role of interaction between pyroptosis and TIME in gastric cancer. The pyroptosis risk scoring system can be used independently to predict the survival of individuals and their response to immunotherapy.

Development and Validation of an ADME-Related Gene Signature for Survival, Treatment Outcome and Immune Cell Infiltration in Head and Neck Squamous Cell Carcinoma

ADME genes are a set of genes which are involved in drug absorption, distribution, metabolism, and excretion (ADME). However, prognostic value and function of ADME genes in head and neck squamous cell carcinoma (HNSCC) remain largely unclear. In this study, we established an ADME-related prognostic model through the least absolute shrinkage and selection operator (LASSO) analysis in the Cancer Genome Atla (TCGA) training cohort and its robustness was validated by TCGA internal validation cohort and a Gene Expression Omnibus (GEO) external cohort. The 14-gene signature stratified patients into high- or low-risk groups. Patients with high-risk scores exhibited significantly poorer overall survival (OS) and disease-free survival (DFS) than those with low-risk scores. Receiver operating characteristic (ROC) curve analysis was used to confirm the signature’s predictive efficacy for OS and DFS. Furthermore, gene ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analyses showed that immune-related functions and pathways were enriched, such as lymphocyte activation, leukocyte cell-cell adhesion and T-helper cell differentiation. The Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) and other analyses revealed that immune cell (especially B cell and T cell) infiltration levels were significantly higher in the low-risk group. Moreover, patients with low-risk scores were significantly associated with immunotherapy and chemotherapy treatment benefit. In conclusion, we constructed a novel ADME-related prognostic and therapeutic biomarker associated with immune cell infiltration of HNSCC patients.

The role of neoantigens in tumor immunotherapy

Tumor neoantigens are aberrant polypeptides produced by tumor cells as a result of genomic mutations. They are also tumor-specific antigens (TSA). Neoantigens are more immunogenic than tumor-related antigens and do not induce autoimmunity. Based on the rapid development of bioinformatics and the continuous update of sequencing technology, cancer immunotherapy with tumor neoantigens has made promising breakthroughs and progress. In this review, the generation, prediction, and identification of novel antigens, as well as the individualized treatments of neoantigens, were first introduced. Secondly, the mechanism of Chimeric Antigen Receptor T-Cell Immunotherapy (CAR-T) therapy and immune checkpoint blockade therapy in the treatment of tumors were outlined, and the three treatment methods were compared. Thirdly, the application of neoantigens in CAR-T therapy and PD-1/PD-L1 blockade therapy was briefly described. The benefits of the neoantigen vaccines over common vaccines were summarized as well. Finally, the prospect of neoantigen therapy was presented.

A T cell resilience model associated with response to immunotherapy in multiple tumor types

Despite breakthroughs in cancer immunotherapy, most tumor-reactive T cells cannot persist in solid tumors due to an immunosuppressive environment. We developed Tres (tumor-resilient T cell), a computational model utilizing single-cell transcriptomic data to identify signatures of T cells that are resilient to immunosuppressive signals, such as transforming growth factor-β1, tumor necrosis factor-related apoptosis-inducing ligand and prostaglandin E2. Tres reliably predicts clinical responses to immunotherapy in melanoma, lung cancer, triple-negative breast cancer and B cell malignancies using bulk T cell transcriptomic data from pre-treatment tumors from patients who received immune-checkpoint inhibitors (n = 38), infusion products for chimeric antigen receptor T cell therapies (n = 34) and pre-manufacture samples for chimeric antigen receptor T cell or tumor-infiltrating lymphocyte therapies (n = 84). Further, Tres identified FIBP, whose functions are largely unknown, as the top negative marker of tumor-resilient T cells across many solid tumor types. FIBP knockouts in murine and human donor CD8+ T cells significantly enhanced T cell-mediated cancer killing in in vitro co-cultures. Further, Fibp knockout in murine T cells potentiated the in vivo efficacy of adoptive cell transfer in the B16 tumor model. Fibp knockout T cells exhibit reduced cholesterol metabolism, which inhibits effector T cell function. These results demonstrate the utility of Tres in identifying biomarkers of T cell effectiveness and potential therapeutic targets for immunotherapies in solid tumors.

Pan-Cancer Methylated Dysregulation of Long Non-coding RNAs Reveals Epigenetic Biomarkers

Different cancer types not only have common characteristics but also have their own characteristics respectively. The mechanism of these specific and common characteristics is still unclear. Pan-cancer analysis can help understand the similarities and differences among cancer types by systematically describing different patterns in cancers and identifying cancer-specific and cancer-common molecular biomarkers. While long non-coding RNAs (lncRNAs) are key cancer modulators, there is still a lack of pan-cancer analysis for lncRNA methylation dysregulation. In this study, we integrated lncRNA methylation, lncRNA expression and mRNA expression data to illuminate specific and common lncRNA methylation patterns in 23 cancer types. Then, we screened aberrantly methylated lncRNAs that negatively regulated lncRNA expression and mapped them to the ceRNA relationship for further validation. 29 lncRNAs were identified as diagnostic biomarkers for their corresponding cancer types, with lncRNA AC027601 was identified as a new KIRC-associated biomarker, and lncRNA ACTA2-AS1 was regarded as a carcinogenic factor of KIRP. Two lncRNAs HOXA-AS2 and AC007228 were identified as pan-cancer biomarkers. In general, the cancer-specific and cancer-common lncRNA biomarkers identified in this study may aid in cancer diagnosis and treatment.

Comprehensive assessment of cellular senescence in the tumor microenvironment

Cellular senescence (CS), a state of permanent growth arrest, is intertwined with tumorigenesis. Due to the absence of specific markers, characterizing senescence levels and senescence-related phenotypes across cancer types remain unexplored. Here, we defined computational metrics of senescence levels as CS scores to delineate CS landscape across 33 cancer types and 29 normal tissues and explored CS-associated phenotypes by integrating multiplatform data from ~20 000 patients and ~212 000 single-cell profiles. CS scores showed cancer type-specific associations with genomic and immune characteristics and significantly predicted immunotherapy responses and patient prognosis in multiple cancers. Single-cell CS quantification revealed intra-tumor heterogeneity and activated immune microenvironment in senescent prostate cancer. Using machine learning algorithms, we identified three CS genes as potential prognostic predictors in prostate cancer and verified them by immunohistochemical assays in 72 patients. Our study provides a comprehensive framework for evaluating senescence levels and clinical relevance, gaining insights into CS roles in cancer- and senescence-related biomarker discovery.

Single-cell N6-methyladenosine regulator patterns guide intercellular communication of tumor microenvironment that contribute to colorectal cancer progression and immunotherapy

BACKGROUND

N6-methyladenosine (m⁶A) RNA methylation plays a critical role in key genetic events for various cancers; yet, how m⁶A functions within the tumor microenvironment (TME) remains to be elucidated.

METHODS

A total of 65,362 single cells from single-cell RNA-seq data derived from 33 CRC tumor samples were analyzed by nonnegative matrix factorization (NMF) for 23 m⁶A RNA methylation regulators. CRC and Immunotherapy cohorts from public repository were used to determine the prognosis and immune response of TME clusters.

RESULTS

The fibroblasts, macrophages, T and B cells were respectively grouped into 4 to 5 subclusters and then classified according to various biological processes and different marker genes. Furthermore, it revealed that the m⁶A RNA methylation regulators might be significantly related to the clinical and biological features of CRC, as well as the pseudotime trajectories of main TME cell types. Bulk-seq analysis suggested that these m⁶A-mediated TME cell subclusters had significant prognostic value for CRC patients and distinguished immune response for patients who underwent ICB therapy, especially for the CAFs and macrophages. Notably, CellChat analysis revealed that RNA m⁶A methylation-associated cell subtypes of TME cells manifested diverse and extensive interaction with tumor epithelial cells. Further analysis showed that ligand-receptor pairs, including MIF -  (CD74 + CXCR4), MIF -  (CD74 + CD44), MDK-NCL and LGALS9 - CD45, etc. mediated the communication between m⁶A associated subtypes of TME cells and tumor epithelial cells.

CONCLUSIONS

Taken together, our study firstly revealed the m⁶A methylation mediated intercellular communication of the tumor microenvironment in the regulation of tumor growth and antitumor immunomodulatory processes.

Genomic Correlates of Outcome in Tumor-Infiltrating Lymphocyte Therapy for Metastatic Melanoma

PURPOSE

Adoptive cell therapy (ACT) of tumor-infiltrating lymphocytes (TIL) historically yields a 40%-50% response rate in metastatic melanoma. However, the determinants of outcome are largely unknown.

EXPERIMENTAL DESIGN

We investigated tumor-based genomic correlates of overall survival (OS), progression-free survival (PFS), and response to therapy by interrogating tumor samples initially collected to generate TIL infusion products.

RESULTS

Whole-exome sequencing (WES) data from 64 samples indicated a positive correlation between neoantigen load and OS, but not PFS or response to therapy. RNA sequencing analysis of 34 samples showed that expression of PDE1C, RTKN2, and NGFR was enriched in responders who had improved PFS and OS. In contrast, the expression of ELFN1 was enriched in patients with unfavorable response, poor PFS and OS, whereas enhanced methylation of ELFN1 was observed in patients with favorable outcomes. Expression of ELFN1, NGFR, and PDE1C was mainly found in cancer-associated fibroblasts and endothelial cells in tumor tissues across different cancer types in publicly available single-cell RNA sequencing datasets, suggesting a role for elements of the tumor microenvironment in defining the outcome of TIL therapy.

CONCLUSIONS

Our findings suggest that transcriptional features of melanomas correlate with outcomes after TIL therapy and may provide candidates to guide patient selection.

Tumor-infiltrating lymphocytes for adoptive cell therapy: recent advances, challenges, and future directions

INTRODUCTION

Adoptive cell therapy (ACT) with tumor-infiltrating lymphocytes (TILs) is a highly personalized type of cancer immunotherapy. TIL-based ACT exploits naturally occurring TILs, derived from the patients' tumor. This treatment has shown consistent clinical responses in melanoma, and recent results point toward a potential use in multiple cancer diagnoses. However, several limitations have restricted the clinical development and adaptation of TIL-based ACT.

AREAS COVERED

In this review, we present the principles of TIL-based ACT and discuss the most significant limitations for therapeutic efficacy and its widespread application. The topics of therapeutic resistance (both innate and acquired), treatment-related toxicity, and the novel research topic of metabolic barriers in the tumor microenvironment (TME) are covered.

EXPERT OPINION

There are many ongoing areas of research focusing on improving clinical efficacy and optimizing TIL-based ACT. Many strategies have shown great potential, particularly strategies advancing TIL efficacy (such as increasing and harnessing ex vivo the sub-population of tumor-reactive TILs) and manufacturing processes. Novel approaches can help overcome current limitations and potentially result in TIL-based ACT entering the mainstream of cancer therapy across tumor types.

CD8+ T cells and fatty acids orchestrate tumor ferroptosis and immunity via ACSL4

Tumor cell intrinsic ferroptosis-initiating mechanisms are unknown. Here, we discover that T cell-derived interferon (IFN)γ in combination with arachidonic acid (AA) induces immunogenic tumor ferroptosis, serving as a mode of action for CD8+ T cell (CTL)-mediated tumor killing. Mechanistically, IFNγ stimulates ACSL4 and alters tumor cell lipid pattern, thereby increasing incorporations of AA into C16 and C18 acyl chain-containing phospholipids. Palmitoleic acid and oleic acid, two common C16 and C18 fatty acids in blood, promote ACSL4-dependent tumor ferroptosis induced by IFNγ plus AA. Moreover, tumor ACSL4 deficiency accelerates tumor progression. Low-dose AA enhances tumor ferroptosis and elevates spontaneous and immune checkpoint blockade (ICB)-induced anti-tumor immunity. Clinically, tumor ACSL4 correlates with T cell signatures and improved survival in ICB-treated cancer patients. Thus, IFNγ signaling paired with selective fatty acids is a natural tumor ferroptosis-promoting mechanism and a mode of action of CTLs. Targeting the ACSL4 pathway is a potential anti-cancer approach.

The Current State of Treatment and Future Directions in Cutaneous Malignant Melanoma

Malignant melanoma is the leading cause of death among cutaneous malignancies. While its incidence is increasing, the most recent cancer statistics show a small but clear decrease in mortality rate. This trend reflects the introduction of novel and more effective therapeutic regimens, including the two cornerstones of melanoma therapy: immunotherapies and targeted therapies. Immunotherapies exploit the highly immunogenic nature of melanoma by modulating and priming the patient's own immune system to attack the tumor. Treatments combining immunotherapies with targeted therapies, which disable the carcinogenic products of mutated cancer cells, have further increased treatment efficacy and durability. Toxicity and resistance, however, remain critical challenges to the field. The present review summarizes past treatments and novel therapeutic interventions and discusses current clinical trials and future directions.

A m6Avalue predictive of prostate cancer stemness, tumor immune landscape and immunotherapy response

The molecular mechanisms underpinning prostate cancer (PCa) progression are incompletely understood, and precise stratification of aggressive primary PCa (pri-PCa) from indolent ones poses a major clinical challenge. Here, we comprehensively dissect, genomically and transcriptomically, the m⁶A (N ⁶-methyladenosine) pathway as a whole in PCa. Expression, but not the genomic alteration, repertoire of the full set of 24 m⁶A regulators at the population level successfully stratifies pri-PCa into three m⁶A clusters with distinct molecular and clinical features. These three m⁶A modification patterns closely correlate with androgen receptor signaling, stemness, proliferation and tumor immunogenicity of cancer cells, and stroma activity and immune landscape of tumor microenvironment (TME). We observe a discrepancy between a potentially higher neoantigen production and a deficiency in antigen presentation processes in aggressive PCa, offering insights into the failure of immunotherapy. Identification of PCa-specific m⁶A phenotype-associated genes provides a basis for construction of m⁶Avalue to measure m⁶A methylation patterns in individual patients. Tumors with lower m⁶Avalue are relatively indolent with abundant immune cell infiltration and stroma activity. Interestingly, m⁶Avalue separates PCa TME into fibrotic and nonfibrotic phenotypes (instead of previously reported immune-proficient or -desert phenotypes in other cancer types). Significantly, m⁶Avalue can be used to predict drug response and clinical immunotherapy efficacy in both castration-resistant PCa and other cancer types. Therefore, our study establishes m⁶A methylation modification pattern as a determinant in PCa progression via impacting cancer cell aggressiveness and TME remodeling.

A FBXO7/EYA2-SCFFBXW7 axis promotes AXL-mediated maintenance of mesenchymal and immune evasion phenotypes of cancer cells

A mesenchymal tumor phenotype associates with immunotherapy resistance, although the mechanism is unclear. Here, we identified FBXO7 as a maintenance regulator of mesenchymal and immune evasion phenotypes of cancer cells. FBXO7 bound and stabilized SIX1 co-transcriptional regulator EYA2, stimulating mesenchymal gene expression and suppressing IFNα/β, chemokines CXCL9/10, and antigen presentation machinery, driven by AXL extracellular ligand GAS6. Ubiquitin ligase SCFFBXW7 antagonized this pathway by promoting EYA2 degradation. Targeting EYA2 Tyr phosphatase activity decreased mesenchymal phenotypes and enhanced cancer cell immunogenicity, resulting in attenuated tumor growth and metastasis, increased infiltration of cytotoxic T and NK cells, and enhanced anti-PD-1 therapy response in mouse tumor models. FBXO7 expression correlated with mesenchymal and immune-suppressive signatures in patients with cancer. An FBXO7-immune gene signature predicted immunotherapy responses. Collectively, the FBXO7/EYA2-SCFFBXW7 axis maintains mesenchymal and immune evasion phenotypes of cancer cells, providing rationale to evaluate FBXO7/EYA2 inhibitors in combination with immune-based therapies to enhance onco-immunotherapy responses.

Pan-Cancer Analyses Identify the CTC1-STN1-TEN1 Complex as a Protective Factor and Predictive Biomarker for Immune Checkpoint Blockade in Cancer

The CTC1-STN1-TEN1 (CST) complex plays a crucial role in telomere replication and genome stability. However, the detailed mechanisms of CST regulation in cancer remain largely unknown. Here, we perform a comprehensive analysis of CST across 33 cancer types using multi-omic data from The Cancer Genome Atlas. In the genomic landscape, we identify CTC1/STN1 deletion and mutation and TEN1 amplification as the dominant alteration events. Expressions of CTC1 and STN1 are decreased in tumors compared to those in adjacent normal tissues. Clustering analysis based on CST expression reveals three cancer clusters displaying differences in survival, telomerase activity, cell proliferation, and genome stability. Interestingly, we find that CTC1 and STN1, but not TEN1, are co-expressed and associated with better survival. CTC1-STN1 is positively correlated with CD8 T cells and B cells and predicts a better response to immune checkpoint blockade in external datasets of cancer immunotherapy. Pathway analysis shows that MYC targets are negatively correlated with CTC1-STN1. We experimentally validated that knockout of CTC1 increased the mRNA level of c-MYC. Furthermore, CTC1 and STN1 are repressed by miRNAs and lncRNAs. Finally, by mining the connective map database, we discover a number of potential drugs that may target CST. In sum, this study illustrates CTC1-STN1 as a protective factor and provides broad molecular signatures for further functional and therapeutic studies of CST in cancer.

Bacillus Calmette–Guérin Treatment Changes the Tumor Microenvironment of Non-Muscle-Invasive Bladder Cancer

Background

Bacillus Calmette–Guérin (BCG) is currently the most effective intravesical therapy for non-muscle-invasive bladder cancer (NMIBC) as it can prevent disease recurrence and progression and lower mortality. However, the response rates to BCG vary widely and are dependent on a multitude of factors.

Methods

We performed a systematic discovery by analyzing the whole exome sequence, expression profile, and immune repertoire sequence of treatment-naive and 5-year time-serial relapsed tumors from 24 NMIBC patients.

Results

BCG therapy showed bidirectional effects on tumor evolution and immune checkpoint landscape, along with a significant reduction of the percentage of neoantigen burden. In addition, a remarkable proportion of subclonal mutations were unique to the matched pre- or post-treatment tumors, suggesting the presence of BCG-induced and/or spatial heterogeneity. In the relapsed tumors, we identified and validated a shift in the mutational signatures in which mutations associated with aristolochic acid (AA) exposure were enriched, implying AA may be associated with tumor recurrence. Enhanced expressions of immune checkpoint regulation genes were found in the relapsed tumors, suggesting that the combination of immune checkpoint with BCG treatment may be an effective strategy to treat NMIBC. TCR sequencing revealed treatment-associated changes in the T-cell repertoire in the primary and relapsed tumors.

Conclusion

Our results provide insight into the genomic and immune dynamics of tumor evolution with BCG treatment, suggest new mechanisms of BCG resistance, and inform the development of clinically relevant biomarkers and trials of potential immune checkpoint inhibitor combination therapies.

Transcriptomic signatures of tumors undergoing T cell attack

BACKGROUND

Studying tumor cell-T cell interactions in the tumor microenvironment (TME) can elucidate tumor immune escape mechanisms and help predict responses to cancer immunotherapy.

METHODS

We selected 14 pairs of highly tumor-reactive tumor-infiltrating lymphocytes (TILs) and autologous short-term cultured cell lines, covering four distinct tumor types, and co-cultured TILs and tumors at sub-lethal ratios in vitro to mimic the interactions occurring in the TME. We extracted gene signatures associated with a tumor-directed T cell attack based on transcriptomic data of tumor cells.

RESULTS

An autologous T cell attack induced pronounced transcriptomic changes in the attacked tumor cells, partially independent of IFN-γ signaling. Transcriptomic changes were mostly independent of the tumor histological type and allowed identifying common gene expression changes, including a shared gene set of 55 transcripts influenced by T cell recognition (Tumors undergoing T cell attack, or TuTack, focused gene set). TuTack scores, calculated from tumor biopsies, predicted the clinical outcome after anti-PD-1/anti-PD-L1 therapy in multiple tumor histologies. Notably, the TuTack scores did not correlate to the tumor mutational burden, indicating that these two biomarkers measure distinct biological phenomena.

CONCLUSIONS

The TuTack scores measure the effects on tumor cells of an anti-tumor immune response and represent a comprehensive method to identify immunologically responsive tumors. Our findings suggest that TuTack may allow patient selection in immunotherapy clinical trials and warrant its application in multimodal biomarker strategies.

Valid-NEO: A Multi-Omics Platform for Neoantigen Detection and Quantification from Limited Clinical Samples

The presentation of neoantigens on the cell membrane is the foundation for most cancer immunotherapies. Due to their extremely low abundance, analyzing neoantigens in clinical samples is technically difficult, hindering the development of neoantigen-based therapeutics for more general use in the treatment of diverse cancers worldwide. Here, we describe an integrated system, "Valid-NEO", which reveals patient-specific cancer neoantigen therapeutic targets from minute amounts of clinical samples through direct observation, without computer-based prediction, in a sensitive, rapid, and reproducible manner. The overall four-hour procedure involves mass spectrometry analysis of neoantigens purified from tumor samples through recovery of HLA molecules with HLA antibodies. Valid-NEO could be applicable to the identification and quantification of presented neoantigens in cancer patients, particularly when only limited amounts of sample are available.

Mechanisms of MHC-I Downregulation and Role in Immunotherapy Response

Immunotherapy has become a key therapeutic strategy in the treatment of many cancers. As a result, research efforts have been aimed at understanding mechanisms of resistance to immunotherapy and how anti-tumor immune response can be therapeutically enhanced. It has been shown that tumor cell recognition by the immune system plays a key role in effective response to T cell targeting therapies in patients. One mechanism by which tumor cells can avoid immunosurveillance is through the downregulation of Major Histocompatibility Complex I (MHC-I). Downregulation of MHC-I has been described as a mechanism of intrinsic and acquired resistance to immunotherapy in patients with cancer. Depending on the mechanism, the downregulation of MHC-I can sometimes be therapeutically restored to aid in anti-tumor immunity. In this article, we will review current research in MHC-I downregulation and its impact on immunotherapy response in patients, as well as possible strategies for therapeutic upregulation of MHC-I.

Immunological Classification of Tumor Types and Advances in Precision Combination Immunotherapy

Immunity is an important physiological function acquired throughout evolution as a defense system against the invasion of pathogenic microorganisms. The immune system also eliminates senescent cells and maintains homeostasis, monitoring cell mutations and preventing tumor development via the action of the immune cells and molecules. Immunotherapy often relies on the interaction of immune cells with the tumor microenvironment (TME). Based on the distribution of the number of lymphocytes (CD3 and CD8) in the center and edge of the tumor and the expression level of B7-H1/PD-L1, tumors are divided into hot tumors, cold tumors, and intermediate tumors (including immune-suppressed and isolated). This review focuses on the advances in precision combination immunotherapy, which has been widely explored in recent years, and its application in different tumor types.

Guanylate-Binding Protein 1 as a Potential Predictor of Immunotherapy: A Pan-Cancer Analysis

Background: Mainstream application of cancer immunotherapy is hampered by the low response rate of most cancer patients. A novel immunotherapeutic target or a biomarker predicting response to immunotherapy needs to be developed. Guanylate-binding protein 1 (GBP1) is an interferon (IFN)-inducible guanosine triphosphatases (GTPases) involving inflammation and infection. However, the immunological effects of GBP1 in pan-cancer patients are still obscure.

Methods: Using large-scale public data, we delineated the landscape of GBP1 across 33 cancer types. The correlation between GBP1 expression or mutation and immune cell infiltration was estimated by ESTIMATE, TIMER, xCell, and quanTIseq algorithms. GBP1-related genes and proteins were subjected to function enrichment analysis. Clustering analysis explored the relationship between GBP1 expression and anti-tumor immune phenotypes. We assessed the patient’s response to immunotherapy using the tumor immune dysfunction and exclusion (TIDE) score and immunophenoscore (IPS). Furthermore, we validated the predictive power of GBP1 expression in four independent immunotherapy cohorts.

Results: GBP1 was differentially expressed in tumors and normal tissues in multiple cancer types. Distinct correlations existed between GBP1 expression and prognosis in cancer patients. GBP1 expression and mutation were positively associated with immune cell infiltration. Function enrichment analysis showed that GBP1-related genes were enriched in immune-related pathways. Positive correlations were also observed between GBP1 expression and the expression of immune checkpoints, as well as tumor mutation burden (TMB). Pan-cancer patients with higher GBP1 expression were more inclined to display “hot” anti-tumor immune phenotypes and had lower TIDE scores and higher immunophenoscore, suggesting that these patients had better responses to immunotherapy. Patients with higher GBP1 expression exhibited improved overall survival and clinical benefits in immunotherapy cohorts, including the Gide et al. cohort [area under the curve (AUC): 0.813], the IMvigor210 cohort (AUC: 0.607), the Lauss et al. cohort (AUC: 0.740), and the Kim et al. cohort (AUC: 0.793).

Conclusion: This study provides comprehensive insights into the role of GBP1 in a pan-cancer manner. We identify GBP1 expression as a predictive biomarker for immunotherapy, potentially enabling more precise and personalized immunotherapeutic strategies in the future.

Molecular Characterization and Clinical Relevance of ALDH2 in Human Cancers

Background: Aldehyde dehydrogenase 2 (ALDH2) is well-known to be a key enzyme in alcohol metabolism. However, a comprehensive understanding of ALDH2 across human cancers is lacking.

Methods: A systematic and comprehensive analysis of the molecular alterations and clinical relevance for ALDH2 in more than 10,000 samples from 33 cancer types was performed. qRT-PCR was performed on 60 cancer and 60 paired nontumor tissues.

Results: It was observed that ALDH2 was generally downregulated in most cancers, which was mainly driven by DNA hypermethylation rather than mutations or copy number variations. Besides, ALDH2 was closely related to the inhibition and activation of tumor pathways and a variety of potential targeted agents had been discovered in our research. Last but not least, ALDH2 had the best prediction efficacy in assessing immunotherapeutic response compared with PD-L1, PD-1, CTLA4, CD8, and tumor mutation burden (TMB) in cutaneous melanoma. According to the analysis of large-scale public data and 60 pairs of clinical cancer samples, we found the downregulation of ALDH2 expression tends to suggest the malignant phenotypes and adverse prognosis, which might enhance the precise diagnosis and timely intervention of cancer patients.

Conclusion: This study advanced the understanding of ALDH2 across cancers, and provided important insight into chemotherapy, immunotherapy and prognosis of patients with cancer.