Molecular and genetic properties of tumors associated with local immune cytolytic activity

Dynamic phenotypic reprogramming and chemoresistance induced by lung fibroblasts in small cell lung cancer

Small cell lung cancer (SCLC) is heterogenous in phenotype and microenvironment. Dynamic phenotypic reprogramming, leading to heterogeneity, is prevalent in SCLC, while the mechanisms remain incompletely understood. Cancer-associated fibroblasts (CAFs) possess comprehensive roles in cancer progression, while their function in phenotypic reprogramming of SCLC remain elusive. Here, we obtained transcriptome data of SCLC tissues from publicly available databases, subsequently estimated abundance of CAFs. We found CAF-abundant SCLC exhibited non-neuroendocrine (Non-NE) characteristics. Supporting this, the positive correlation of expression level of α-SMA, the CAF marker, and expression level of REST, protein typically expressed in Non-NE type SCLC, was identified in SCLC tissue arrays. Moreover, we revealed that fibroblasts inhibited NE markers expression and cell proliferation of SCLC cells in the co-culture system comprising lung fibroblasts and SCLC cells, indicating a phenotypic reprogramming from NE to Non-NE. During this process, fibroblast-derived IL-6 activated the JAK2/STAT3 signaling, upregulated c-MYC expression, and subsequently activated the NOTCH pathway, driving phenotypic reprogramming. Moreover, CAF-enriched SCLC exhibited increased immune cell infiltration, elevated expression of immune activation-related signatures, and checkpoint molecules. Our data also highlighted the chemoresistance induced by fibroblasts in SCLC cells, which was effectively reversed by JAK inhibitor. In conclusion, fibroblasts induced phenotypic reprogramming of SCLC cells from NE to Non-NE, likely contributes to inflamed immune microenvironment and chemoresistance. These findings provide novel insights into the clinical implications of CAFs in SCLC.

DNA-methylome-derived epigenetic fingerprint as an immunophenotype indicator of durable clinical immunotherapeutic benefits in head and neck squamous cell carcinoma

BACKGROUND

Cancer immunotherapy provides durable response and improves survival in a subset of head and neck squamous cell carcinoma (HNSC) patients, which may due to discriminative tumor microenvironment (TME). Epigenetic regulations play critical roles in HNSC tumorigenesis, progression, and activation of functional immune cells. This study aims to identify an epigenetic signature as an immunophenotype indicator of durable clinical immunotherapeutic benefits in HNSC patients.

METHODS

Unsupervised consensus clustering approach was applied to distinguish immunophenotypes based on five immune signatures in The Cancer Genome Atlas (TCGA) HNSC cohort. Two immunophenotypes (immune 'Hot' and immune 'Cold') that had different TME features, diverse prognosis, and distinct DNA methylation patterns were recognized. Immunophenotype-related methylated signatures (IPMS) were identified by the least absolute shrinkage and selector operation algorithm. Additionally, the IPMS score by deconvolution algorithm was constructed as an immunophenotype classifier to predict clinical outcomes and immunotherapeutic response.

RESULTS

The 'Hot' HNSC immunophenotype had higher immunoactivity and better overall survival (p = 0.00055) compared to the 'Cold' tumors. The immunophenotypes had distinct DNA methylation patterns, which was closely associated with HNSC tumorigenesis and functional immune cell infiltration. 311 immunophenotype-related methylated CpG sites (IRMCs) was identified from TCGA-HNSC dataset. IPMS score model achieved a strong clinical predictive performance for classifying immunophenotypes. The area under the curve value (AUC) of the IPMS score model reached 85.9% and 89.8% in TCGA train and test datasets, respectively, and robustness was verified in five HNSC validation datasets. It was also validated as an immunophenotype classifier for predicting durable clinical benefits (DCB) in lung cancer patients who received anti-PD-1/PD-L1 immunotherapy (p = 0.017) and TCGA-SKCM patients who received distinct immunotherapy (p = 0.033).

CONCLUSIONS

This study systematically analyzed DNA methylation patterns in distinct immunophenotypes to identify IPMS with clinical prognostic potential for personalized epigenetic anticancer approaches in HNSC patients. The IPMS score model may serve as a reliable epigenome prognostic tool for clinical immunophenotyping to guide immunotherapeutic strategies in HNSC.

Targeting ALK averts ribonuclease 1-induced immunosuppression and enhances antitumor immunity in hepatocellular carcinoma

Tumor-secreted factors contribute to the development of a microenvironment that facilitates the escape of cancer cells from immunotherapy. In this study, we conduct a retrospective comparison of the proteins secreted by hepatocellular carcinoma (HCC) cells in responders and non-responders among a cohort of ten patients who received Nivolumab (anti-PD-1 antibody). Our findings indicate that non-responders have a high abundance of secreted RNase1, which is associated with a poor prognosis in various cancer types. Furthermore, mice implanted with HCC cells that overexpress RNase1 exhibit immunosuppressive tumor microenvironments and diminished response to anti-PD-1 therapy. RNase1 induces the polarization of macrophages towards a tumor growth-promoting phenotype through activation of the anaplastic lymphoma kinase (ALK) signaling pathway. Targeting the RNase1/ALK axis reprograms the macrophage polarization, with increased CD8+ T- and Th1- cell recruitment. Moreover, simultaneous targeting of the checkpoint protein PD-1 unleashes cytotoxic CD8+ T-cell responses. Treatment utilizing both an ALK inhibitor and an anti-PD-1 antibody exhibits enhanced tumor regression and facilitates long-term immunity. Our study elucidates the role of RNase1 in mediating tumor resistance to immunotherapy and reveals an RNase1-mediated immunosuppressive tumor microenvironment, highlighting the potential of targeting RNase1 as a promising strategy for cancer immunotherapy in HCC.

Identification of angiogenesis-related subtypes, the development of a prognosis model, and features of tumor microenvironment in colon cancer

Angiogenesis is associated with tumor progression, prognosis, and treatment effect. However, the angiogenesis' underlying mechanisms in the tumor microenvironment (TME) still remain unclear. Understanding the dynamic interactions between angiogenesis and TME in colon adenocarcinoma (COAD) is necessary. We downloaded the transcriptome data and corresponding clinical data of colon cancer patients from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases, respectively. We identified two distinct angiogenesis-related molecular subtypes (subtype A and subtype B) and assessed the clinical features, prognosis, and infiltrating immune cells of patients in the two subtypes. According to the prognostic differential genes, we defined two different gene clusters to further explore the correlation between angiogenesis and tumor heterogeneity. Then, we construct the prognostic risk scoring model angiogenesis-related gene (ARG-score) including seven genes (ARMCX2, latent transforming growth factor β binding protein 1, ADAM8, FABP4, CCL11, CXCL11, ITLN1) using Lasso-multivariate cox method. We analyzed the correlation between ARG-score and prognosis, clinicopathological features, TME, molecular feature, cancer stem cells (CSCs), and microsatellite instability (MSI) status. To assess the application value of ARG-score in clinical treatment, immunophenotype score was used to predict patients' immunotherapy response in colon cancer. We found the mutations of ARGs in TCGA-COAD dataset from genetic levels and discussed their expression patterns based on TCGA and GEO datasets. We observed important differences in clinicopathological features, prognosis, immune feature, molecular feature between the two molecular subgroups. Then, we established an ARG-score for predicting OS and validated its predictive capability. A high ARG-score characterized by higher transcription level of ARGs, suggested lower MSI-high (MSI-H), lower immune score, and worse clinical stage and survival outcome. Additionally, the ARG-score was remarkably related to the CSCs index and immunotherapy sensitivity. We found two new molecular subtypes and two gene clusters based on ARGs and established an ARG-score. Multilayered analysis revealed that ARGs were remarkably correlated to the heterogeneity of colon cancer patients and explained the process of tumorigenesis and progression better. The ARG-score can help us better assess patients' survival outcomes and provide guidance for individualized treatment.

The levels of immunosuppressive checkpoint protein PD-L1 and tumor-infiltrating lymphocytes were integrated to reveal the glioma tumor microenvironment

In spite of significant strides in the realm of cancer biology and therapeutic interventions, the clinical prognosis for patients afflicted with glioblastoma (GBM) remains distressingly dismal. The tumor immune microenvironment (TIME), a crucial player in the progression, treatment response, and prognostic trajectory of glioma, warrants thorough exploration. Within this intricate microcosm, the immunosuppressive checkpoint protein PD-L1 and tumor-infiltrating lymphocytes (TILs) emerge as pivotal constituents, underscoring their potential role in deciphering glioma biology and informing treatment strategies. However, prognostic models based on the association between PD-L1 expression and TIL infiltration in the tumor immune microenvironment have not been established. The aim of this study was to explore TIME genes associated with PD-L1 expression and TIL invasion and to construct a risk score for predicting the overall survival (OS) of GBM patients based on these genes. The samples were separately classified according to the PD-L1 expression level and TIL score and TIME-related genes were identified using differential expression and weighted gene co-expression network analysis. The DEGs were subjected to least absolute contraction and selection operator (LASSO) -Cox regression to construct TIME associated risk score (TIMErisk). A TIMErisk was developed based on STEAP3 and CXCL13 genes. The STLEAP3 was demonstrated to be involved in glioma progression. The results showed that the patients in the high TIMErisk group had poor OS compared with subjects in the low TIMErisk group. The biological phenotypes associated with TIMErisk were analyzed in terms of functional enrichment, tumor immune profile, and tumor mutation profile. The results on tumor immune dysfunction and exclusion dysfunction (TIDE) score and immune surface score (IPS) showed that GBM patients with different TIME risks had different responses to immunotherapy. Tumor purity analysis indicated that PD-L1 and TIL scores were positively correlated with TIMErisk score and negatively correlated with tumor purity. These results show that the TIMErisk-based prognostic model had high predictive value for the prognosis and immune characteristics of GBM patients. Immunohistochemical staining images of patients in the high and low TIMErisk groups were analyzed, showing that the degree of immune cell infiltration was higher in the high TIMErisk group relative to the low TIMErisk group. The present study provides a basis for understanding glioma tumor microenvironment and a foundation for conducting comprehensive immunogenomic analysis.

Unravelling the heterogeneity of oral squamous cell carcinoma by integrative analysis of single-cell and bulk transcriptome data

Oral squamous cell carcinoma (OSCC) is a prevalent malignancy of the head and neck with rising global incidence. Despite advances in treatment modalities, OSCC prognosis remains diverse due to the complex molecular and cellular heterogeneity within tumours, as well as the heterogeneity in tumour microenvironment (TME). In this study, we utilized single-cell RNA sequencing (scRNA-seq) analysis to explore distinct subpopulations of tumour cells in OSCC tissues and their interaction with components in TME. We identified four major tumour cell subpopulations (C0, C1, C2 and C3) with unique molecular characteristics and functional features. Pathway enrichment analysis revealed that C0 primarily expressed genes involved in extracellular matrix interactions and C1 showed higher proliferation levels, suggesting that the two cell subpopulations exhibited tumour aggressiveness. Conversely, C2 and C3 displayed features associated with keratinization and cornified envelope formation. Accordingly, C0 and C1 subpopulations were associated with shorter overall and disease-free survival times, while C2 and C3 were weakly correlated with longer survival. Genomic analysis showed that C1 demonstrated a positive correlation with tumour mutation burden. Furthermore, C0 exhibited resistant to cisplatin treatment, while C1 showed more sensitive to cisplatin treatment, indicating that C0 might exhibit more aggressive compared to C1. Additionally, C0 had a higher level of communication with fibroblasts and endothelial cells in TME via integrin-MAPK signalling, suggesting that the function of C0 was maintained by that pathway. In summary, this study provided critical insights into the molecular and cellular heterogeneity of OSCC, with potential implications for prognosis prediction and personalized therapeutic approaches.

Identification and validation of the association of Janus kinase 2 mutations with the response to immune checkpoint inhibitor therapy

BACKGROUND

Janus kinase 2 (JAK2) mutation plays an important role in T cell immunity. However, the effect of JAK2 mutation on immunotherapy is largely uncharacterized.

METHODS

In this study, we analyzed the effect of JAK2 mutation on the efficacy and outcomes of immune checkpoint inhibitor (ICI) therapy in the discovery cohort (n = 662) and the verification cohort (n = 1423). Furthermore, we explored the association of JAK2 mutation with the tumor immune microenvironment in a multiomics cohort.

RESULTS

In the discovery cohort (n = 662), JAK2 mutant-type patients had a better objective response rate (58.8% vs. 26.7%, P = 0.010), durable clinical benefit (64.7% vs. 38.9%, P = 0.043), progression-free survival (hazard ratio [HR] = 0.431, P = 0.015), and overall survival (HR = 0.378, P = 0.025), relative to JAK2 wild-type patients. Moreover, we further verified the prognostic significance of JAK2 mutation in an independent ICI treatment cohort with a larger sample size (n = 1423). In addition, we discovered that the JAK2 mutation was remarkably related to increased immunogenicity, such as a higher TMB, higher expression of costimulatory molecules and stimulation of antigen processing mechanisms. In addition, JAK2 mutation was positively correlated with activated anticancer immunity, such as infiltration of various immune cells and higher expression of chemokines.

CONCLUSION

Our study demonstrates that JAK2 mutation is a novel marker that can be used to effectively predict prognosis and response to ICI therapy.

Genetic Intratumor Heterogeneity Remodels the Immune Microenvironment and Induces Immune Evasion in Brain Metastasis of Lung Cancer

INTRODUCTION

Brain metastasis, with the highest incidence in patients with lung cancer, significantly worsens prognosis and poses challenges to clinical management. To date, how brain metastasis evades immune elimination remains unknown.

METHODS

Whole-exome sequencing and RNA sequencing were performed on 30 matched brain metastasis, primary lung adenocarcinoma, and normal tissues. Data from The Cancer Genome Atlas primary lung adenocarcinoma cohort, including multiplex immunofluorescence, were used to support the findings of bioinformatics analysis.

RESULTS

Our study highlights the key role of intratumor heterogeneity of genomic alterations in the metastasis process, mainly caused by homologous recombination deficiency or other somatic copy number alteration-associated mutation mechanisms, leading to increased genomic instability and genomic complexity. We further proposed a selection model of brain metastatic evolution in which intratumor heterogeneity drives immune remodeling, leading to immune escape through different mechanisms under local immune pressure.

CONCLUSIONS

Our findings provide novel insights into the metastatic process and immune escape mechanisms of brain metastasis and pave the way for precise immunotherapeutic strategies for patients with lung cancer with brain metastasis.

POLQ identifies a better response subset to immunotherapy in muscle-invasive bladder cancer with high PD-L1

BACKGROUND

Though programmed cell death-ligand 1 (PD-L1) has been used in predicting the efficacy of immune checkpoint blockade (ICB), it is insufficient as a single biomarker. As a key effector of an intrinsically mutagenic microhomology-mediated end joining (MMEJ) pathway, DNA polymerase theta (POLQ) was overexpressed in various malignancies, whose expression might have an influence on genomic stability, therefore altering the sensitivity to chemotherapy and immunotherapy.

METHODS

A total of 1304 patients with muscle-invasive bladder cancer (MIBC) from six independent cohorts were included in this study. The Zhongshan Hospital (ZSHS) cohort (n = 134), The Cancer Genome Atlas (TCGA) cohort (n = 391), and the Neo-cohort (n = 148) were included for the investigation of chemotherapeutic response. The IMvigor210 cohort (n = 234) and the UNC-108 cohort (n = 89) were used for the assessment of immunotherapeutic response. In addition, the relationship between POLQ and the immune microenvironment was assessed, and GSE32894 (n = 308) was used only for the evaluation of the immune microenvironment.

RESULTS

We identified POLQhigh PD-L1high patients could benefit more from immunotherapy and platinum-based chemotherapy. Further analysis revealed that high POLQ expression was linked to chromosome instability and higher tumor mutational burden (TMB), which might elicit the production of neoantigens. Further, high POLQ expression was associated with an active tumor immune microenvironment with abundant infiltration of immune effector cells and molecules.

CONCLUSIONS

The study demonstrated that high POLQ expression was correlated with chromosome instability and antitumor immune microenvironment in MIBC, and the combination of POLQ and PD-L1 could be used as a superior companion biomarker for predicting the efficacy of immunotherapy.

Towards targeting transposable elements for cancer therapy

Transposable elements (TEs) represent almost half of the human genome. Historically deemed 'junk DNA', recent technological advancements have stimulated a wave of research into the functional impact of TEs on gene-regulatory networks in evolution and development, as well as in diseases including cancer. The genetic and epigenetic evolution of cancer involves the exploitation of TEs, whereby TEs contribute directly to cancer-specific gene activities. This Review provides a perspective on the role of TEs in cancer as being a 'double-edged sword', both promoting cancer evolution and representing a vulnerability that could be exploited in cancer therapy. We discuss how TEs affect transcriptome regulation and other cellular processes in cancer. We highlight the potential of TEs as therapeutic targets for cancer. We also summarize technical hurdles in the characterization of TEs with genomic assays. Last, we outline open questions and exciting future research avenues.

Experimental and clinical evidence in favour of an effective immune stimulation in ER-positive, endocrine-dependent metastatic breast cancer

In ER+ breast cancer, usually seen as the low immunogenic type, the main mechanisms favouring the immune response or tumour growth and immune evasion in the tumour microenvironment (TME) have been examined. The principal implications of targeting the oestrogen-mediated pathways were also considered. Recent experimental findings point out that anti-oestrogens contribute to the reversion of the immunosuppressive TME. Moreover, some preliminary clinical data with the hormone-immunotherapy association in a metastatic setting support the notion that the reversion of immune suppression in TME is likely favoured by the G0-G1 state induced by anti-oestrogens. Following immune stimulation, the reverted immune suppression allows the boosting of the effector cells of the innate and adaptive immune response. This suggests that ER+ breast cancer is a molecular subtype where a successful active immune manipulation can be attained. If this is confirmed by a prospective multicentre trial, which is expected in light of the provided evidence, the proposed hormone immunotherapy can also be tested in the adjuvant setting. Furthermore, the different rationale suggests a synergistic activity of our proposed immunotherapy with the currently recommended regimen consisting of antioestrogens combined with cyclin kinase inhibitors. Overall, this lays the foundation for a shift in clinical practice within this most prevalent molecular subtype of breast cancer.

Integrative analysis of LAG3 immune signature and identification of a LAG3-related genes prognostic signature in kidney renal clear cell carcinoma

Immune checkpoint blockade (ICB) therapy has resulted in improved overall survival in kidney renal clear cell carcinoma (KIRC), but most treated patients fail to show durable clinical responses. Lymphocyte activation gene-3 (LAG3) is a novel inhibitory immune checkpoint, but its expression pattern, prognostic value, and immunological role in KIRC remain unknown. In this study, we utilized TCGA_KIRC RNA-sequencing data to analyze the relationship between LAG3 expression and clinical features. The single-cell sequencing data and tissue immunofluorescence are employed to investigate the subcellular localization of LAG3 in KIRC. Kaplan-Meier plotter, TIMER, and TISIDB were used to assess the association between LAG3 expression and prognosis, as well as its correlation with immune-related components. We constructed the LAG3 interaction network by using STRING, GeneMANIA, BioGRID, and HitPredict databases. We found that LAG3 is upregulated and correlates with poor prognostic phenotype in KIRC. LAG3 is predominantly expressed on exhausted CD8+ T cells and shows strong co-expression with PDCD1 in KIRC. Moreover, our findings indicated that LAG3 not only inhibits T cell activation but also potentially regulates cell adhesion in KIRC. In conclusion, our study implies that LAG3 can serve as a potential prognostic biomarker for KIRC. Furthermore, blocking both LAG3 and PDCD1 may alleviate resistance to anti-PDCD1 therapy, providing novel insights for immunotherapy decision-making in KIRC patients.

Integrating bulk-RNA sequencing and single-cell sequencing analyses to characterize adenosine-enriched tumor microenvironment landscape and develop an adenosine-related prognostic signature predicting immunotherapy in lung adenocarcinoma

The adenosine-signaling axis has been recognized as an important immunomodulatory pathway in tumor immunity. However, the biological role of the adenosine-signaling axis in the remodeling of the tumor microenvironment (TME) in lung adenocarcinoma (LUAD) remains unclear. Here, we quantified adenosine signaling (ado_sig) in LUAD samples using the GSVA method and assessed the prognostic value of adenosine in LUAD. Afterward, we explored the heterogeneity of the tumor-immune microenvironment at different adenosine levels. In addition, we analyzed the potential biological pathways engaged by adenosine. Next, we established single-cell transcriptional profiles of LUAD and analyzed cellular composition and cell-cell communication analysis under different adenosine microenvironments. Moreover, we established adenosine-related prognostic signatures (ARS) based on comprehensive bioinformatics analysis and evaluated the efficacy of ARS in predicting immunotherapy. The results demonstrated that adenosine signaling adversely impacted the survival of immune-enriched LUAD. The high-adenosine microenvironment exhibited elevated pro-tumor-immune infiltration, including M2 macrophages and displayed notably increased epithelial-mesenchymal transition (EMT) transformation. Furthermore, adenosine signaling displayed significant associations with the expression patterns and prognostic value of immunomodulators within the TME. Single-cell sequencing data revealed increased fibroblast occupancy and a prominent activation of the SPP1 signaling pathway in the high adenosine-signaling microenvironment. The ARS exhibited promising effectiveness in prognostication and predicting immunotherapy response in LUAD. In summary, overexpression of adenosine can cause a worsened prognosis in the LUAD with abundant immune infiltration. Moreover, increased adenosine levels are associated with pro-tumor-immune infiltration, active EMT transformation, pro-tumor angiogenesis, and other factors promoting cancer progression, which collectively contribute to the formation of an immunosuppressive microenvironment. Importantly, the ARS developed in this study demonstrate high efficacy in evaluating the response to immunotherapy.

Genetic insights into carbohydrate sulfotransferase 8 and its impact on the immunotherapy efficacy of cancer

Immune checkpoint blockade (ICB) is a promising therapy for solid tumors, but its effectiveness depends on biomarkers that are not precise. Here, we utilized genome-wide association study to investigate the association between genetic variants and tumor mutation burden to interpret ICB response. We identified 16 variants (p < 5 × 10-8) probed to 17 genes on 9 chromosomes. Subsequent analysis of one of the most significant loci in 19q13.11 suggested that the rs111308825 locus at the enhancer is causal, as its A allele impairs KLF2 binding, leading to lower carbohydrate sulfotransferase 8 (CHST8) expression. Breast cancer cells expressing CHST8 suppress T cell activation, and Chst8 loss attenuates tumor growth in a syngeneic mouse model. Further investigation revealed that programmed death-ligand 1 (PD-L1) and its homologs could be sulfated by CHST8, resulting in M2-like macrophage enrichment in the tumor microenvironment. Finally, we confirmed that low-CHST8 tumors have better ICB response, supporting the genetic effect and clinical value of rs111308825 for ICB efficacy prediction.

Identification of colon cancer subtypes based on multi-omics data-construction of methylation markers for immunotherapy

Background

Being the most widely used biomarker for immunotherapy, the microsatellite status has limitations in identifying all patients who benefit in clinical practice. It is essential to identify additional biomarkers to guide immunotherapy. Aberrant DNA methylation is consistently associated with changes in the anti-tumor immune response, which can promote tumor progression. This study aims to explore immunotherapy biomarkers for colon cancers from the perspective of DNA methylation.

Methods

The related data (RNA sequencing data and DNA methylation data) were obtained from The Cancer Genome Atlas (TCGA) and UCSC XENA database. Methylation-driven genes (MDGs) were identified through the Pearson correlation analysis. Unsupervised consensus clustering was conducted using these MDGs to identify distinct clusters of colon cancers. Subsequently, we evaluated the immune status and predicted the efficacy of immunotherapy by tumor immune dysfunction and exclusion (Tide) score. Finally, The Quantitative Differentially Methylated Regions (QDMR) software was used to identify the specific DNA methylation markers within particular clusters.

Results

A total of 282 MDGs were identified by integrating the DNA methylation and RNA-seq data. Consensus clustering using the K-means algorithm revealed that the optimal number of clusters was 4. It was revealed that the composition of the tumor immune microenvironment (TIME) in Cluster 1 was significantly different from others, and it exhibited a higher level of tumor mutation burdens (TMB) and stronger anti-tumor immune activity. Furthermore, we identified three specific hypermethylation genes that defined Cluster 1 (PCDH20, APCDD1, COCH). Receiver operating characteristic (ROC) curves demonstrated that these specific markers could effectively distinguish Cluster 1 from other clusters, with an AUC of 0.947 (95% CI 0.903-0.990). Finally, we selected clinical samples for immunohistochemical validation.

Conclusion

In conclusion, through the analysis of DNA methylation, consensus clustering of colon cancer could effectively identify the cluster that benefit from immunotherapy along with specific methylation biomarkers.

Immunological subtyping of salivary gland cancer identifies histological origin-specific tumor immune microenvironment

Gene expression analysis enhances proper cancer subtyping, a better understanding of the molecular characteristics of cancer, and strategies for precision medicine. However, salivary gland cancer (SGC) subtyping remains largely unexplored because of its rarity and diverse histopathological and immunological characteristics. This study aimed to determine whether the histological origin and immunological characteristics of SGC subtypes are intrinsic tumor immunity factors. We performed immune profiling of 94 RNA-seq of SGC tissues and found that the SGCs that originated from the excretory duct (ED), such as the salivary duct and mucoepidermoid carcinomas, exhibit higher immunity than those from the intercalated duct (ID), such as the adenoid cystic and myoepithelial carcinomas, based on the computationally predicted immune score (p < 0.001), immune cell enrichment in the tumor immune microenvironment (TIME) (p < 0.001), T-cell receptor diversity (p < 0.001), and expression of signal I (major histocompatibility complex, MHC, p < 0.001) and signal II (co-stimulatory, p < 0.001 and co-inhibitory, p < 0.001) genes. Further analysis revealed that tolerogenic dendritic cell-induced dysfunctional T-cell populations and T-cell exclusion in the TIME are the major immune evasive mechanisms of the ED-and ID-derived SGCs, respectively.

T proliferating cells derived autophagy signature associated with prognosis and immunotherapy resistance in a pan-cancer analysis

Despite autophagy modulating tumor immunity in the tumor microenvironment (TME), the immunotherapeutic efficacy and potential mechanism of autophagy signature was not explicit. We manually curated an autophagy gene set and defined a pan-cancer autophagy signature by comparing malignant tissues and normal tissues in The Cancer Genome Atlas (TCGA) cohort. The pan-cancer autophagy signature was derived from T proliferating cells as demonstrated in multiple single-cell RNA sequencing (scRNA-seq) datasets. The pan-cancer autophagy signature could influence the cell-cell interactions in the TME and predict the responsiveness of immune checkpoint inhibitors (ICIs) in the metastatic renal cell carcinoma, non-small cell lung cancer, bladder cancer, and melanoma cohorts. Metabolism inactivation accompanied with dysregulation of autophagy was investigated with transcriptomic and proteomic data. The immunotherapeutic predictive role and mechanism regulation of the autophagy signature was validated in an in-house cohort. Our study provides valuable insights into the mechanisms of ICI resistance.

Malignant cell receptor-ligand subtypes guide the prediction of prognosis and personalized immunotherapy of liver cancer

OBJECTIVE

Liver cancer is a prevalent disease with a dismal prognosis. The aim of the research is to identify subgroups based on malignant cell receptor ligand gene from single-cell RNA, which might lead to customized immunotherapy for patients with liver cancer.

METHODS

Based on scRNA-seq data, we identified the receptor-ligand genes associated with prognosis and classify patients into molecular subtypes by univariate Cox regression and consensus clustering. LASSO regression was performed to construct a prognostic model, which was validated in TCGA and ICGC datasets. Immune infiltration and prediction of immunotherapy response were analyzed using ssGSEA, ESTIMATE, TIDE, and TRS score calculation. Finally, qPCR and Western blot validation of key genes and protein levels in cell lines.

RESULTS

A risk model using 16-gene expression levels predicted liver cancer patients' prognosis. The RiskScore associated significantly with tumor clinical characteristics and immunity, integrated with clinicopathological features for survival prediction. Differential expression of SRXN1 was verified in hepatocellular carcinoma and normal liver cells.

CONCLUSION

Our study utilizes single-cell analysis to investigate the communication between malignant cells and other cell types, identifying molecular subtypes based on malignant cell receptor ligand genes, offering new insights for the development of personalized immunotherapy and prognostic prediction models.

Aggrephagy-related gene signature correlates with survival and tumor-associated macrophages in glioma: Insights from single-cell and bulk RNA sequencing

BACKGROUND

Aggrephagy is a lysosome-dependent process that degrades misfolded protein condensates to maintain cancer cell homeostasis. Despite its importance in cellular protein quality control, the role of aggrephagy in glioma remains poorly understood.

OBJECTIVE

To investigate the expression of aggrephagy-related genes (ARGs) in glioma and in different cell types of gliomas and to develop an ARGs-based prognostic signature to predict the prognosis, tumor microenvironment, and immunotherapy response of gliomas.

METHODS

ARGs were identified by searching the Reactome database. We developed the ARGs-based prognostic signature (ARPS) using data from the Cancer Genome Atlas (TCGA, n = 669) by Lasso-Cox regression. We validated the robustness of the signature in clinical subgroups and CGGA cohorts (n = 970). Gene set enrichment analysis (GSEA) was used to identify the pathways enriched in ARPS subgroups. The correlations between ARGs and macrophages were also investigated at single cell level.

RESULTS

A total of 44 ARGs showed heterogeneous expression among different cell types of gliomas. Five ARGs (HSF1, DYNC1H1, DYNLL2, TUBB6, TUBA1C) were identified to develop ARPS, an independent prognostic factor. GSEA showed gene sets of patients with high-ARPS were mostly enriched in cell cycle, DNA replication, and immune-related pathways. High-ARPS subgroup had higher immune cell infiltration states, particularly macrophages, Treg cells, and neutrophils. APRS had positive association with tumor mutation burden (TMB) and immunotherapy response predictors. At the single cell level, we found ARGs correlated with macrophage development and identified ARGs-mediated macrophage subtypes with distinct communication characteristics with tumor cells. VIM+ macrophages were identified as pro-inflammatory and had higher interactions with malignant cells.

CONCLUSION

We identified a novel signature based on ARGs for predicting glioma prognosis, tumor microenvironment, and immunotherapy response. We highlight the ARGs-mediated macrophages in glioma exhibit classical features.

A novel immunogenic cell death-related gene risk signature can identify biomarkers of gliomas and predict the immunotherapeutic response

Immunogenic cell death (ICD) is a type of cell death that plays a pivotal role in immunity. Recent studies have identified the critical role of ICD in glioma treatment. This study aimed to use ICD-associated differentially expressed genes (ICD-DEGs) to predict survival of glioma patients. We investigated the relationship between clinical prognosis and the date-to-clinical prognosis of 1,721 glioma patients by examining the expression, methylation, and mutation status of ICD-related genes (IRGs) in these patients. Our prediction of survival in glioma patients was based on three risk genes, and we explored the association between these genes and clinical outcomes. Additionally, IRG expression was used to stratify glioma patients. We further examined the relationship among the three subgroups in terms of immune microenvironment heterogeneity and immunotherapy response. In addition, this study also included analyses of histograms and sensitivity to antitumor drugs. The expression of these genes was externally validated by RT-qPCR, Western blot (WB), and immunohistochemistry (IHC) in glioma and normal brain tissue. Our findings reveal that most IRGs are overexpressed in glioma tumor tissues, and this high expression was confirmed through histological validation. We successfully developed predictive models for three prognostic genes associated with ICD. These models not only predict survival in glioma but also correlate with the tumor's immune microenvironment. Finally, using consensus clustering, we identified three ICD-associated subtypes. Notably, patients with the C3 subtype showed high levels of immune cell infiltration, whereas those with the C1 subtype exhibited lower levels of immune cell infiltration. We successfully developed an innovative IRG-based systematic approach for evaluating glioma patients. This stratification in experimental studies opens new avenues for prognosis and assessing immunotherapy responses in glioma patients. Our study demonstrates the effectiveness of this approach in treating glioma, potentially paving the way for more promising and effective therapeutic strategies in the future.

Gastric cancer with enhanced myogenesis is associated with less cell proliferation, enriched epithelial-to-mesenchymal transition and angiogenesis, and poor clinical outcomes

Gastric cancer (GC) remains a lethal disease, with over 26,000 new cases and more than 11,000 deaths annually in the US. Thus, a deeper understanding of GC biology is critical to improve survival. Myogenesis is the formation of muscle fibers, which is a mesodermal tissue. In cancer, epithelial-to-mesenchymal transition (EMT) is a known phenomenon that promotes metastasis and poor survival. Given that myogenesis produces mesenchymal cells, we hypothesized that GC with increased myogenesis is linked to aggressive tumor behaviors and less favorable outcomes. In this study, three GC patient cohorts: TCGA (n=375), GSE26253 (n=432), and GSE84437 (n=482), were analyzed. The "MYOGENESIS" set in the Hallmark collection which comprises 200 myogenesis-related genes was analyzed to perform gene set variation analysis to create a score to quantify the myogenesis activity. Our results showed that T category of AJCC cancer staging that reflects the tumor invasion to stomach wall consistently correlated with myogenesis activity in two GC cohorts. High myogenesis GC was associated with lower cell proliferation, evidenced by reduced proliferation scores, decreased Ki67 gene expression, and less enrichment of E2F Targets, G2M checkpoint, MYC Targets V1, and V2 gene sets. High myogenesis tumors showed increased stromal cells (fibroblasts and adipocytes) infiltration within the tumor microenvironment, as well as less silent and non-silent mutation rates and copy number alterations. Higher lymphocyte infiltration, leukocyte fraction, T-cell receptor richness, and B-cell receptor richness were associated with high myogenesis GC. However, infiltration of CD4 cells, T helper type 1 and 2 cells, Natural Killer cells, regulatory T cells, and plasma cells was lower, with increased infiltration of dendritic cells in high myogenesis GC. High myogenesis GC enriched EMT, Hedgehog, TGF-β, and KRAS gene sets. Furthermore, it was associated with enhanced angiogenesis, evidenced by enrichment of Angiogenesis, Coagulation, and Hypoxia gene sets, and increased infiltration of microvascular and lymphatic endothelial cells and pericytes. High myogenesis GC consistently correlated with worse overall survival in all three cohorts, and worse disease-specific and progression-free survival in the TCGA cohort. Hence, our findings suggest that GC with enhanced myogenesis is associated with decreased cell proliferation, increased EMT and angiogenesis, and worse prognosis.

Identification of cuproptosis-related diagnostic biomarkers in idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal lung disease with clinical and pathological heterogeneity. Recent studies have identified cuproptosis as a novel cell death mechanism. However, the role of cuproptosis-related genes in the pathogenesis of IPF is still unclear. Two IPF datasets of the Gene Expression Omnibus database were studied. Mann-Whitney U test, correlation analysis, functional enrichment analyses, single-sample gene set enrichment analysis, CIBERSORT, unsupervised clustering, weighted gene co-expression network analysis, and receiver operating characteristic curve analysis were used to conduct our research. The dysregulated cuproptosis-related genes and immune responses were identified between IPF patients and controls. Two cuproptosis-related molecular clusters were established in IPF, the high immune score group (C1) and the low immune score group (C2). Significant heterogeneity in immunity between clusters was revealed by functional analyses results. The module genes with the strongest correlation to the 2 clusters were identified by weighted gene co-expression network analysis results. Seven hub genes were found using the Cytoscape software. Ultimately, 2 validated diagnostic biomarkers of IPF, CDKN2A and NEDD4, were obtained. Subsequently, the results were validated in GSE47460. Our investigation illustrates that CDKN2A and NEDD4 may be valid biomarkers that were useful for IPF diagnosis and copper-related clustering.

Hyperglycosylation of prosaposin in tumor dendritic cells drives immune escape

Tumors develop strategies to evade immunity by suppressing antigen presentation. In this work, we show that prosaposin (pSAP) drives CD8 T cell-mediated tumor immunity and that its hyperglycosylation in tumor dendritic cells (DCs) leads to cancer immune escape. We found that lysosomal pSAP and its single-saposin cognates mediated disintegration of tumor cell-derived apoptotic bodies to facilitate presentation of membrane-associated antigen and T cell activation. In the tumor microenvironment, transforming growth factor-β (TGF-β) induced hyperglycosylation of pSAP and its subsequent secretion, which ultimately caused depletion of lysosomal saposins. pSAP hyperglycosylation was also observed in tumor-associated DCs from melanoma patients, and reconstitution with pSAP rescued activation of tumor-infiltrating T cells. Targeting DCs with recombinant pSAP triggered tumor protection and enhanced immune checkpoint therapy. Our studies demonstrate a critical function of pSAP in tumor immunity and may support its role in immunotherapy.

Characterizing ligand-receptor interactions and unveiling the pro-tumorigenic role of CCL16-CCR1 axis in the microenvironment of hepatocellular carcinoma

Background

The heterogeneity of the tumor microenvironment significantly influences the prognosis of hepatocellular carcinoma (HCC) patients, with cell communication through ligand-receptor complexes playing a central role.

Methods

We conducted single-cell transcriptomic analysis on ten HCC tissues to identify ligand-receptor genes involved in malignant HCC cell communication using CellChat. Leveraging RNA-Seq data from the TCGA Liver Cancer (TCGA-LIHC) and Liver Cancer - RIKEN, JP (LIRI-JP) cohorts, we employed Cox regression analysis to screen for prognosis-related genes. Prognostic risk models were constructed through unsupervised clustering and differential gene expression analysis. Subsequently, a co-culture system involving tumor cells and macrophages was established. A series of experiments, including Transwell assays, immunofluorescence staining, immunoprecipitation, flow cytometry, and immunohistochemistry, were conducted to elucidate the mechanism through which HCC cells recruit macrophages via the CCL16-CCR1 axis.

Results

Single-cell analysis unveiled significant interactions between malignant HCC cells and macrophages, identifying 76 related ligand-receptor genes. Patients were classified into three subtypes based on the expression patterns of eight prognosis-related ligand-receptor genes. The subtype with the worst prognosis exhibited reduced infiltration of T cell-related immune cells, downregulation of immune checkpoint genes, and increased M2-like tumor-associated macrophage scores. In vitro experiments confirmed the pivotal role of the CCL16-CCR1 axis in the recruitment and M2 polarization of tumor-associated macrophages. Clinical samples demonstrated a significant association between CCL16 protein expression levels and advanced stage, lymph node metastasis, and distant metastasis. Immunohistochemistry and immunofluorescence staining further confirmed the correlation between CCL16 and CCR1, CD68, and CD206, as well as CD68+CCR1+ macrophage infiltration.

Conclusions

Our study identified molecular subtypes, a prognostic model, and immune microenvironment features based on ligand-receptor interactions in malignant HCC cell communication. Moreover, we revealed the pro-tumorigenic role of HCC cells in recruiting M2-like tumor-associated macrophages through the CCL16-CCR1 axis.

Predicting patient outcomes after treatment with immune checkpoint blockade: A review of biomarkers derived from diverse data modalities

Immune checkpoint blockade (ICB) therapy targeting cytotoxic T-lymphocyte-associated protein 4, programmed death 1, and programmed death ligand 1 has shown durable remission and clinical success across different cancer types. However, patient outcomes vary among disease indications. Studies have identified prognostic biomarkers associated with immunotherapy response and patient outcomes derived from diverse data types, including next-generation bulk and single-cell DNA, RNA, T cell and B cell receptor sequencing data, liquid biopsies, and clinical imaging. Owing to inter- and intra-tumor heterogeneity and the immune system's complexity, these biomarkers have diverse efficacy in clinical trials of ICB. Here, we review the genetic and genomic signatures and image features of ICB studies for pan-cancer applications and specific indications. We discuss the advantages and disadvantages of computational approaches for predicting immunotherapy effectiveness and patient outcomes. We also elucidate the challenges of immunotherapy prognostication and the discovery of novel immunotherapy targets.

Integrated multi-omics profiling to dissect the spatiotemporal evolution of metastatic hepatocellular carcinoma

Comprehensive molecular analyses of metastatic hepatocellular carcinoma (HCC) are lacking. Here, we generate multi-omic profiling of 257 primary and 176 metastatic regions from 182 HCC patients. Primary tumors rich in hypoxia signatures facilitated polyclonal dissemination. Genomic divergence between primary and metastatic HCC is high, and early dissemination is prevalent. The remarkable neoantigen intratumor heterogeneity observed in metastases is associated with decreased T cell reactivity, resulting from disruptions to neoantigen presentation. We identify somatic copy number alterations as highly selected events driving metastasis. Subclones without Wnt mutations show a stronger selective advantage for metastasis than those with Wnt mutations and are characterized by a microenvironment rich in activated fibroblasts favoring a pro-metastatic phenotype. Finally, metastases without Wnt mutations exhibit higher enrichment of immunosuppressive B cells that mediate terminal exhaustion of CD8+ T cells via HLA-E:CD94-NKG2A checkpoint axis. Collectively, our results provide a multi-dimensional dissection of the complex evolutionary process of metastasis.

Comprehensive molecular analysis identifies RET alterations association with response of ICIs in multi-immunotherapy cohorts

BACKGROUND

The RET gene, which is frequently mutated across many types of cancer, has been proven to be critically involved in tumorigenesis and tumour development; however, its prediction of the therapeutic efficacy of immune checkpoint inhibitor (ICI) therapy remains to be elucidated. The present research aims to investigate the association between RET mutations and the efficiency of ICI therapy.

METHOD

We analysed the role of RET mutations in predicting the prognosis of patients receiving ICIs therapy in the discovery cohort and validated it in the validation cohort. Then, multi-omics data from TCGA pan-cancer cohort was employed to propose the association between RET mutations and tumour inflamed anti-tumour immune response and tumour antigenicity.

RESULTS

Our study revealed that among 606 cases and across five types of cancer, RET mutation was associated with better clinical outcomes for ICIs therapy, including elevated response rate, longer progression-free survival PFS, and longer overall survival OS. Multivariate analysis showed that RET mutation could independently predict the prognosis of patients treated with ICIs, after adjusting cancer types. The predictive value of RET status for the OS of patients treated with ICIs immunotherapy was further validated in the validation cohort (n = 1,409). Subgroup analysis suggested that only the monotherapy group showed significant differences in OS(P < 0.05) and PFS(P < 0.05) between RET-wildtype tumours and RET-mutant tumours. Multi-omics data analysis revealed potential anti-tumour immunity mechanisms of RET mutations, suggesting that RET-mutant tumours have enhanced immunogenicity, higher expression of immune checkpoints and chemokines, and higher immune cell infiltration than those observed in RET-wildtype tumours; thus, potentially indicating a more favourable response to immunotherapy.

CONCLUSIONS

RET mutation may be a predictive biomarker of enhanced response to ICIs therapy. Extensive investigation of the underlying molecular mechanisms and prospective studies are needed in the future.

Proteogenomic characterization of small cell lung cancer identifies biological insights and subtype-specific therapeutic strategies

We performed comprehensive proteogenomic characterization of small cell lung cancer (SCLC) using paired tumors and adjacent lung tissues from 112 treatment-naive patients who underwent surgical resection. Integrated multi-omics analysis illustrated cancer biology downstream of genetic aberrations and highlighted oncogenic roles of FAT1 mutation, RB1 deletion, and chromosome 5q loss. Two prognostic biomarkers, HMGB3 and CASP10, were identified. Overexpression of HMGB3 promoted SCLC cell migration via transcriptional regulation of cell junction-related genes. Immune landscape characterization revealed an association between ZFHX3 mutation and high immune infiltration and underscored a potential immunosuppressive role of elevated DNA damage response activity via inhibition of the cGAS-STING pathway. Multi-omics clustering identified four subtypes with subtype-specific therapeutic vulnerabilities. Cell line and patient-derived xenograft-based drug tests validated the specific therapeutic responses predicted by multi-omics subtyping. This study provides a valuable resource as well as insights to better understand SCLC biology and improve clinical practice.

Identification of a Notch transcriptomic signature for breast cancer

BACKGROUND

Dysregulated Notch signalling contributes to breast cancer development and progression, but validated tools to measure the level of Notch signalling in breast cancer subtypes and in response to systemic therapy are largely lacking. A transcriptomic signature of Notch signalling would be warranted, for example to monitor the effects of future Notch-targeting therapies and to learn whether altered Notch signalling is an off-target effect of current breast cancer therapies. In this report, we have established such a classifier.

METHODS

To generate the signature, we first identified Notch-regulated genes from six basal-like breast cancer cell lines subjected to elevated or reduced Notch signalling by culturing on immobilized Notch ligand Jagged1 or blockade of Notch by γ-secretase inhibitors, respectively. From this cadre of Notch-regulated genes, we developed candidate transcriptomic signatures that were trained on a breast cancer patient dataset (the TCGA-BRCA cohort) and a broader breast cancer cell line cohort and sought to validate in independent datasets.

RESULTS

An optimal 20-gene transcriptomic signature was selected. We validated the signature on two independent patient datasets (METABRIC and Oslo2), and it showed an improved coherence score and tumour specificity compared with previously published signatures. Furthermore, the signature score was particularly high for basal-like breast cancer, indicating an enhanced level of Notch signalling in this subtype. The signature score was increased after neoadjuvant treatment in the PROMIX and BEAUTY patient cohorts, and a lower signature score generally correlated with better clinical outcome.

CONCLUSIONS

The 20-gene transcriptional signature will be a valuable tool to evaluate the response of future Notch-targeting therapies for breast cancer, to learn about potential effects on Notch signalling from conventional breast cancer therapies and to better stratify patients for therapy considerations.

Guanosine diphosphate-mannose suppresses homologous recombination repair and potentiates antitumor immunity in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer with poor prognosis. TNBCs with high homologous recombination deficiency (HRD) scores benefit from DNA-damaging agents, including platinum drugs and poly(ADP-ribose) polymerase (PARP) inhibitors, whereas those with low HRD scores still lack therapeutic options. Therefore, we sought to exploit metabolic alterations to induce HRD and sensitize DNA-damaging agents in TNBCs with low HRD scores. We systematically analyzed TNBC metabolomics and identified a metabolite, guanosine diphosphate (GDP)-mannose (GDP-M), that impeded homologous recombination repair (HRR). Mechanistically, the low expression of the upstream enzyme GDP-mannose-pyrophosphorylase-A (GMPPA) led to the endogenous up-regulation of GDP-M in TNBC. The accumulation of GDP-M in tumor cells further reduced the interaction between breast cancer susceptibility gene 2 (BRCA2) and ubiquitin-specific peptidase 21 (USP21), which promoted the ubiquitin-mediated degradation of BRCA2 to inhibit HRR. Therapeutically, we illustrated that the supplementation of GDP-M sensitized DNA-damaging agents to impair tumor growth in both in vitro (cancer cell line and patient-derived organoid) and in vivo (xenograft in immunodeficient mouse) models. Moreover, the combination of GDP-M with DNA-damaging agents activated STING-dependent antitumor immunity in immunocompetent syngeneic mouse models. Therefore, GDP-M supplementation combined with PARP inhibition augmented the efficacy of anti-PD-1 antibodies. Together, these findings suggest that GDP-M is a crucial HRD-related metabolite and propose a promising therapeutic strategy for TNBCs with low HRD scores using the combination of GDP-M, PARP inhibitors, and anti-PD-1 immunotherapy.

Combined OLA1 and CLEC3B Gene Is a Prognostic Signature for Hepatocellular Carcinoma and Impact Tumor Progression

Hepatocellular carcinoma (HCC), partly because of its complexity and high heterogeneity, has a poor prognosis and an extremely high mortality rate. In this study, mRNA sequencing expression profiles and relevant clinical data of HCC patients were gathered from different public databases. Kaplan-Meier survival curves as well as ROC curves validated that OLA1|CLEC3B was an independent predictor with better predictive capability of HCC prognosis compared to OLA1 and CLEC3B separately. Further, the cell transfection experiment verified that knockdown of OLA1 inhibited cell proliferation, facilitated apoptosis, and improved sensitivity of HCC cells to gemcitabine. In this study, the prognostic model of HCC composed of OLA1/CLEC3B genes was constructed and verified, and the prediction ability was favorable. A higher level of OLA1 along with a lower level of CEC3B is a sign of poor prognosis in HCC. We revealed a novel gene pair OLA1|CLEC3B overexpressed in HCC patients, which may serve as a promising independent predictor of HCC survival and an approach for innovative diagnostic and therapeutic strategies.

Identification of the prognostic immune subtype in copy-number high endometrial cancer

OBJECTIVE

The TCGA molecular subtype of endometrial cancer (EC) is widely applied, among which the copy-number high (CNH) subtype has the poorest prognosis. However, the heterogeneity of this subtype remains elusive. In this study, we aimed to identify heterogeneous immune subtypes in CNH EC and explore their prognostic significance.

METHODS

We collected 60 CNH EC cases in the TCGA database and performed unsupervised cluster analysis based on the enrichment scores of immune-related gene signatures to identify immune subtypes. We described their immune characteristics and prognoses and conducted differential gene analysis and lasso regression to identify a prognostic biomarker, GZMM. For experimental validation, we performed immunohistochemical staining of GZMM in 39 p53-positive EC surgical samples.

RESULTS

We defined two immune subtypes, immune-hot (IH) and immune-cold (IC), which differed in immune cell infiltration, cytokine and chemokine expression and prognosis. The IH subtype has significantly stronger immune activation than the IC subtype, showing a significant infiltration of immune effector cells and high expression of relevant chemokines, with better prognosis. Moreover, the immunohistochemical staining of GZMM in a cohort of 39 p53-positive EC surgical samples confirmed GZMM as a unique prognostic biomarker, with high expression in both tumor cells and lymphocytes predicting a better prognosis.

CONCLUSION

Our study revealed heterogeneous immune subtypes in CNH EC and identified GZMM as a prognostic biomarker. The stratified classification strategy combining molecular and immune subtypes provides valuable insights for future clinical practice.

Construction of RNA Methylation Modification-immune-related lncRNA Molecular Subtypes and Prognostic Scoring System in Lung Adenocarcinoma

BACKGROUND

RNA methylation modification is not only intimately interrelated with cancer development and progression but also actively influences immune cell infiltration in the tumor microenvironment (TME). RNA methylation modification genes influence the therapeutic progression of lung adenocarcinoma (LUAD), and mining RNA methylation modification prognosis-related markers in LUAD is crucial for its precise prognosis.

METHODS

RNA-Seq data and Gene sets were collected from online databases or published literature. Genomic variation analysis was conducted by the Maftools package. RNA methylation-immune-related lncRNAs were obtained by Pearson correlation analysis. Then, Consistent clustering analysis was performed to obtain RNA methylation modification- immune molecular subtypes (RMM-I Molecular subtypes) in LUAD based on selected lncRNAs. COX and random survival forest analysis were carried out to construct the RMM-I Score. The receiver operating characteristic (ROC) curve and Kaplan Meier survival analysis were used to assess survival differences. Tumor immune microenvironment was assessed through related gene signatures and CIBERSORT algorithm. In addition, drug sensitivity analysis was executed by the pRRophetic package.

RESULTS

Four RNA methylation modified-immune molecular subtypes (RMM-I1, RMM- I2, RMM-I3, RMM-I4) were presented in LUAD. Patients in RMM-I4 exhibited excellent survival advantages and immune activity. HAVCR2, CD274, and CTLA-4 expression were activated in RMM-I4, which might be heat tumors and a potential beneficial group for immunotherapy. OGFRP1, LINC01116, DLGAP1-AS2, CRNDE, LINC01137, MIR210HG, and CYP1B1-AS1 comprised the RMM-I Score. The RMM-I Score exhibited excellent accuracy in the prognostic assessment of LUAD, as patients with a low RMM- I Score exhibited remarkable survival advantage. Patients with a low RMM-I score might be more sensitive to treatment with Docetaxel, Vinorelbine, Paclitaxel, Cisplatin, and immunotherapy.

CONCLUSION

The RMM-I molecular subtype constituted the novel molecular characteristic subtype of LUAD, which complemented the existing pathological typing. More refined and accurate molecular subtypes provide help to reveal the mechanism of LUAD development. In addition, the RMM-I score offers a reliable tool for accurate prognosis of LUAD.

A recurrence-predictive model based on eight genes and tumor mutational burden/microsatellite instability status in Stage II/III colorectal cancer

BACKGROUND

Although adjuvant chemotherapy (ACT) is widely used to treat patients with Stage II/III colorectal cancer (CRC), administering ACT to specific patients remains a challenge. The decision to ACT requires an accurate assessment of recurrence risk and absolute treatment benefit. However, the traditional TNM staging system does not accurately assess a patient's individual risk of recurrence.

METHODS

To identify recurrence risk-related genetic factors for Stage II/III CRC patients after radical surgery, we conducted an analysis of whole-exome sequencing of 47 patients with Stage II/III CRC who underwent radical surgery at five institutions. Patients were grouped into non-recurrence group (NR, n = 24, recurrence-free survival [RFS] > 5 years) and recurrence group (R, n = 23, RFS <2 years). The TCGA-COAD/READ cohort was employed as the validation dataset.

RESULTS

A recurrence-predictive model (G8plus score) based on eight gene (CUL9, PCDHA12, HECTD3, DCX, SMARCA2, FAM193A, AATK, and SORCS2) mutations and tumor mutation burden/microsatellite instability (TMB/MSI) status was constructed, with 97.87% accuracy in our data and 100% negative predictive value in the TCGA-COAD/READ cohort. For the TCGA-COAD/READ cohort, the G8plus-high group had better RFS (HR = 0.22, p = 0.024); the G8plus-high tumors had significantly more infiltrated immune cell types, higher tertiary lymphoid structure signature scores, and higher immunological signature scores. The G8plus score was also a predict biomarker for immunotherapeutic in advanced CRC in the PUCH cohort.

CONCLUSIONS

In conclusion, the G8plus score is a powerful biomarker for predicting the risk of recurrence in patients with stage II/III CRC. It can be used to stratify patients who benefit from ACT and immunotherapy.

Loss of Human Leukocyte Antigen and Immune Escape in Head and Neck Cancer

OBJECTIVES/HYPOTHESIS

Cancer cells evade recognition by the immune system to survive. Head and neck squamous cell carcinoma (HNSCC) is characterized by high levels of immune infiltration and mutation-associated neoantigens; therefore, immune evasion is likely to be an important mechanism in HNSCC tumorigenesis and progression. A commonly employed mechanism of immune evasion is downregulation of human leukocyte antigen (HLA) or loss of heterozygosity (LOH) in tumor cells. The objective of this study was to integrate multi-dimensional genomic and transcriptomic data from HNSCC tumors to better understand the clinical and immunologic implications of HLA LOH.

STUDY TYPE/DESIGN

Cross-sectional integrated clinical and genomic analysis.

METHODS

Whole-exome sequencing and RNA-sequencing data from 522 tumors profiled in The Cancer Genome Atlas HNSCC cohort were analyzed and integrated with secondary analyses including immune cell deconvolution data. Associations were analyzed with categorical hypothesis testing and multivariable logistic and Cox regression.

RESULTS

HLA LOH was a prevalent event that was identified in 53% of HNSCC tumors; in many cases, more than one class I HLA gene was targeted for LOH. HLA LOH was more common in advanced-stage tumors. Tumors with somatic HLA LOH had tumor microenvironments defined by decreased lymphocyte and T cell infiltration.

CONCLUSIONS

HLA LOH is one of the most prevalent genetic alterations in HNSCC, and is associated with a cold immune microenvironment, suggesting that HLA LOH is a means of immune evasion. It may have value as a predictive biomarker or potential as a cancer cell-specific therapeutic target.

LEVEL OF EVIDENCE

3 Laryngoscope, 134:160-165, 2024.

Update on Biomarkers in Renal Cell Carcinoma

Immune checkpoint inhibitors have significantly transformed the treatment paradigm for metastatic renal cell carcinoma (RCC), offering prolonged overall survival and achieving remarkable deep and durable responses. However, given the multiple ICI-containing, standard-of-care regimens approved for RCC, identifying biomarkers that predict therapeutic response and resistance is of critical importance. Although tumor-intrinsic features such as pathological characteristics, genomic alterations, and transcriptional signatures have been extensively investigated, they have yet to provide definitive, robust predictive biomarkers. Current research is exploring host factors through in-depth characterization of the immune system. Additionally, innovative technological approaches are being developed to overcome challenges presented by existing techniques, such as tumor heterogeneity. Promising avenues in biomarker discovery include the study of the microbiome, radiomics, and spatial transcriptomics.

A comprehensive study of oxidative stress-related effects on the prognosis and drug therapy of cervical cancer

BACKGROUND

Cervical cancer (CC) is a serious global disease with poor prognoses and a significant recurrence rate in patients with advanced disease. Oxidative stress (OS) greatly influences many types of human cancers, making it crucial to understand the functional mechanisms of OS-related genes in CC.

METHODS

The transcriptome and clinical data of three normal samples and 306 patients with CC were obtained from The Cancer Genome Atlas dataset. The GSE44001 dataset was acquired from the Gene Expression Omnibus database. OS-related subtypes in the cohort with CC were identified using unsupervised hierarchical clustering, univariate Cox analysis, gene set enrichment analysis (GSEA), and least absolute shrinkage and selection operator regression analysis. Additionally, molecular pathways that differ across subtypes were determined and OS-related genes linked to the prognosis of patients of CC were determined. Finally, a clinical prognostic gene signature was developed and validated. The relative infiltration level of immune cell subpopulations in different risk groups and subtypes was evaluated using the cell-type identification by estimating relative subsets of RNA transcripts (CIBERPORT) algorithm and single-sample GSEA (ssGSEA) techniques.

RESULTS

The present study established two distinct OS subtypes (OS clusters A and B). Analysis using ssGSEA and CIBERSPORT revealed that OS cluster B exhibited a significant level of immune infiltration. A clinical prognostic gene signature was established using OS-related characteristic genes identified by examining the differentially expressed genes across both subtypes. Furthermore, patients with CC were grouped into high- and low-risk groups, with the low-risk group showing higher survival rates. Additionally, these individuals exhibited significant advantages in terms of survival and immunotherapy. Receiver operating characteristic curve analysis demonstrated the higher predictive value of the clinical prognostic gene signature. The outcomes of the validation group depicted congruence with those recorded in the training group.

CONCLUSIONS

A new model was constructed based on eight OS-related characteristic genes to aid the prediction of the survival rates of individuals with CC. The present study contributes to the existing literature on the mechanisms of OS genes in CC and offers a fresh perspective for future advancements in immunotherapy for such individuals.

Ezurpimtrostat, A Palmitoyl-Protein Thioesterase-1 Inhibitor, Combined with PD-1 Inhibition Provides CD8+ Lymphocyte Repopulation in Hepatocellular Carcinoma

BACKGROUND

Palmitoyl-protein thioesterase-1 (PPT1) is a clinical stage druggable target for inhibiting autophagy in cancer.

OBJECTIVE

We aimed to determine the cellular and molecular activity of targeting PPT1 using ezurpimtrostat, in combination with an anti-PD-1 antibody.

METHODS

In this study we used a transgenic immunocompetent mouse model of hepatocellular carcinoma.

RESULTS

Herein, we revealed that inhibition of PPT1 using ezurpimtrostat decreased the liver tumor burden in a mouse model of hepatocellular carcinoma by inducing the penetration of lymphocytes into tumors when combined with anti-programmed death-1 (PD-1). Inhibition of PPT1 potentiates the effects of anti-PD-1 immunotherapy by increasing the expression of major histocompatibility complex (MHC)-I at the surface of liver cancer cells and modulates immunity through recolonization and activation of cytotoxic CD8+ lymphocytes.

CONCLUSIONS

Ezurpimtrostat turns cold tumors into hot tumors and, thus, could improve T cell-mediated immunotherapies in liver cancer.

Construction and validation of molecular subtype and signature of immune cell-related telomeric genes and prediction of prognosis and immunotherapy efficacy in ovarian cancer patients

BACKGROUND

Ovarian cancer (OVC) has emerged as a fatal gynecological malignancy as a result of a lack of reliable methods for early detection, limited biomarkers and few treatment options. Immune cell-related telomeric genes (ICRTGs) show promise as potential biomarkers.

METHODS

ICRTGs were discovered using weighted gene co-expression network analysis (WGCNA). ICRTGs were screened for significant prognosis using one-way Cox regression analysis. Subsequently, molecular subtypes of prognosis-relevant ICRTGs were constructed and validated for OVC, and the immune microenvironment's landscape across subtypes was compared. OVC prognostic models were built and validated using prognosis-relevant ICRTGs. Additionally, chemotherapy susceptibility drugs for OVC patients in the low- and high-risk groups of ICRTGs were screened using genomics of drug susceptibility to cancer (GDSC). Finally, the immunotherapy response in the low- and high-risk groups was detected using the data from GSE78220. We conducted an immune index correlation analysis of ICRTGs with significant prognoses. The MAP3K4 gene, for which the prognostic correlation coefficient is the highest, was validated using tissue microarrays for a prognostic-immune index correlation.

RESULTS

WGCNA analysis constructed a gene set of ICRTGs and screened 22 genes with prognostic significance. Unsupervised clustering analysis revealed the best molecular typing for two subtypes. The Gene Set Variation Analysis algorithm was used to calculate telomere scores and validate the molecular subtyping. A prognostic model was constructed using 17 ICRTGs. In the The Cancer Genome Atlas-OVC training set and the Gene Expression Omnibus validation set (GSE30161), the risk score model's predicted risk groups and the actual prognosis were shown to be significantly correlated. GDSC screened Axitinib, Bexarotene, Embelin and the GSE78220 datasets and demonstrated that ICRTGs effectively distinguished the group that responds to immunotherapy from the non-responsive group. Additionally, tissue microarray validation results revealed that MAP3K4 significantly predicted patient prognosis. Furthermore, MAP3K4 exhibited a positive association with PD-L1 and a negative relationship with the M1 macrophage markers CD86 and INOS.

CONCLUSIONS

ICRTGs may be reliable biomarkers for the molecular typing of patients with OVC, enabling the prediction of prognosis and immunotherapy efficacy.

The microRNA target site profile is a novel biomarker in the immunotherapy response

MicroRNAs (miRNAs) bind on the 3' untranslated region (3'UTR) of messenger RNAs (mRNAs) and regulate mRNA expression in physiological and pathological conditions, including cancer. Thus, studies have identified miRNAs as potential biomarkers by correlating the miRNA expression with the expression of important mRNAs and/or clinical outcomes in cancers. However, tumors undergo pervasive 3'UTR shortening/lengthening events through alternative polyadenylation (APA), which varies the number of miRNA target sites in mRNA, raising the number of miRNA target sites (numTS) as another important regulatory axis of the miRNA binding effects. In this study, we developed the first statistical method, BIOMATA-APA, to identify predictive miRNAs based on numTS features. Running BIOMATA-APA on The Cancer Genome Atlas (TCGA) and independent cohort data both with immunotherapy and no immunotherapy, we demonstrated for the first time that the numTS feature 1) distinguishes different cancer types, 2) predicts tumor proliferation and immune infiltration status, 3) explains more variation in the proportion of tumor-infiltrating immune cells, 4) predicts response to immune checkpoint blockade (ICB) therapy, and 5) adds prognostic power beyond clinical and miRNA expression. To the best of our knowledge, this is the first pan-cancer study to systematically demonstrate numTS as a novel type of biomarker representing the miRNA binding effects underlying tumorigenesis and pave the way to incorporate miRNA target sites for miRNA biomarker identification. Another advantage of examining the miRNA binding effect using numTS is that it requires only RNA-Seq data, not miRNAs, thus resulting in high power in the miRNA biomarker identification.

Comprehensive genomic profiling of breast cancers characterizes germline-somatic mutation interactions mediating therapeutic vulnerabilities

Germline-somatic mutation interactions are universal and associated with tumorigenesis, but their role in breast cancer, especially in non-Caucasians, remains poorly characterized. We performed large-scale prospective targeted sequencing of matched tumor-blood samples from 4079 Chinese females, coupled with detailed clinical annotation, to map interactions between germline and somatic alterations. We discovered 368 pathogenic germline variants and identified 5 breast cancer DNA repair-associated genes (BCDGs; BRCA1/BRCA2/CHEK2/PALB2/TP53). BCDG mutation carriers, especially those with two-hit inactivation, demonstrated younger onset, higher tumor mutation burden, and greater clinical benefits from platinum drugs, PARP inhibitors, and immune checkpoint inhibitors. Furthermore, we leveraged a multiomics cohort to reveal that clinical benefits derived from two-hit events are associated with increased genome instability and an immune-activated tumor microenvironment. We also established an ethnicity-specific tool to predict BCDG mutation and two-hit status for genetic evaluation and therapeutic decisions. Overall, this study leveraged the large sequencing cohort of Chinese breast cancers, optimizing genomics-guided selection of DNA damaging-targeted therapy and immunotherapy within a broader population.

Molecular landscapes of oral cancers of unknown etiology

The incidence of the mobile tongue cancer in young patients has been rising. This oral cancer (OC) type has no identified risk factors (NIRF), no established molecular markers and is not yet recognized as a distinct clinical entity. To understand this emerging malignancy, we innovatively analyzed the public head and neck cancer multi-omics data. We identified mutational signatures that successfully stratified 307 OC and 109 laryngeal cancer cases according to their clinico-pathological characteristics. The NIRF OCs exhibited significantly increased activities of endogenous clock-like and APOBEC-associated mutagenesis, alongside specific cancer driver gene mutations, distinct methylome patterns and prominent antimicrobial transcriptomic responses. Furthermore, we show that mutational signature SBS16 in OCs reflects the combined effects of alcohol drinking and tobacco smoking. Our study characterizes the unique disease histories and molecular programs of the NIRF OCs revealing that this emerging cancer subtype is likely driven by increased endogenous mutagenesis correlated with responses to microbial insults.

Single-cell dissection reveals the role of aggrephagy patterns in tumor microenvironment components aiding predicting prognosis and immunotherapy on lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is one of the leading malignant cancers. Aggrephagy plays a critical role in key genetic events for various cancers; yet, how aggrephagy functions within the tumor microenvironment (TME) in LUAD remains to be elucidated.

METHODS

In this study, by sequential non-negative matrix factorization (NMF) algorithm, pseudotime analysis, cell-cell interaction analysis, and SCENIC analysis, we have shown that aggrephagy genes demonstrated various patterns among different cell types in LUAD TME. LUAD and Immunotherapy cohorts from public repository were used to determine the prognosis and immune response of aggrephagy TME subtypes. The aggrephagy-deprived prognostic score (ADPS) was quantified based on machine learning algorithms.

RESULTS

The cancer-associated fibroblasts (CAFs), tumor-associated macrophages (TAMs), and CD8+ T cells have various aggrephagy patterns, which enhance the intensity of intercellular communication and transcription factor activation. Furthermore, based on the signatures of the newly defined aggrephagy cell subtypes and expression profiles of large cohorts in LUAD patients, we determine that DYNC1I2+CAF-C1, DYNLL1+CAF-C2, PARK7+CAF-C3, VIM+Mac-C1, PARK7+Mac-C2, VIM+CD8+T_cells-C1, UBA52+CD8+T_cells-C2, TUBA4A+CD8+T_ cells-C3, and TUBA1A+CD8+T_cells-C4 are crucial prognostic factors for LUAD patients. The developed ADPS could predict survival outcomes and immunotherapeutic response across ten cohorts (n = 1838), and patients with low ADPS owned a better prognosis, lower genomic alterations, and are more sensitive to immunotherapy. Meanwhile, based on PRISM, CTRP, and CMAP databases, PLK inhibitor BI-2536, may be a potential agent for patients with high ADPS.

CONCLUSIONS

Taken together, our novel and systematic single-cell analysis has revealed the unique role of aggrephagy in remodeling the TME of LUAD. As a newly demonstrated biomarker, the ADPS facilitates the clinical management and individualized treatment of LUAD.

Dissecting cellular states of infiltrating microenvironment cells in melanoma by integrating single-cell and bulk transcriptome analysis

BACKGROUND

Cellular states of different immune cells can affect the activity of the whole immune microenvironment.

METHODS

Here, leveraging reference profiles of microenvironment cell states that were constructed based on single-cell RNA-seq data of melanoma, we dissected the composition of microenvironment cell states across 463 skin cutaneous melanoma (SKCM) bulk samples through CIBERSORT-based deconvolution of gene expression profiles and revealed high heterogeneity of their distribution. Correspondence analysis on the estimated cellular fractions of melanoma bulk samples was performed to identify immune phenotypes. Based on the publicly available clinical survival and therapy data, we analyzed the relationship between immune phenotypes and clinical outcomes of melanoma.

RESULTS

By analysis of the relationships among those cell states, we further identified three distinct tumor microenvironment immune phenotypes: "immune hot/active", "immune cold-suppressive" and "immune cold-exhausted". They were characterized by markedly different patterns of cell states: most notably the CD8 T Cytotoxic state, CD8 T Mixed state, B non-regulatory state and cancer-associated fibroblasts (CAFs), depicting distinct types of antitumor immune response (or immune activity). These phenotypes had prognostic significance for progression-free survival and implications in response to immune therapy in an independent cohort of anti-PD1 treated melanoma patients.

CONCLUSIONS

The proposed strategy of leveraging single-cell data to dissect the composition of microenvironment cell states in individual bulk tumors can also extend to other cancer types, and our results highlight the importance of microenvironment cell states for the understanding of tumor immunity.

Molecular cartography uncovers evolutionary and microenvironmental dynamics in sporadic colorectal tumors

Colorectal cancer exhibits dynamic cellular and genetic heterogeneity during progression from precursor lesions toward malignancy. Analysis of spatial multi-omic data from 31 human colorectal specimens enabled phylogeographic mapping of tumor evolution that revealed individualized progression trajectories and accompanying microenvironmental and clonal alterations. Phylogeographic mapping ordered genetic events, classified tumors by their evolutionary dynamics, and placed clonal regions along global pseudotemporal progression trajectories encompassing the chromosomal instability (CIN+) and hypermutated (HM) pathways. Integrated single-cell and spatial transcriptomic data revealed recurring epithelial programs and infiltrating immune states along progression pseudotime. We discovered an immune exclusion signature (IEX), consisting of extracellular matrix regulators DDR1, TGFBI, PAK4, and DPEP1, that charts with CIN+ tumor progression, is associated with reduced cytotoxic cell infiltration, and shows prognostic value in independent cohorts. This spatial multi-omic atlas provides insights into colorectal tumor-microenvironment co-evolution, serving as a resource for stratification and targeted treatments.

Dysregulated Repeat Element Viral-like Immune Response in Hepatocellular Carcinoma

Purpose

Dysregulation of viral-like repeat RNAs are a common feature across many malignancies that are linked with immunological response, but the characterization of these in hepatocellular carcinoma (HCC) is understudied. In this study, we performed RNA in situ hybridization (RNA-ISH) of different repeat RNAs, immunohistochemistry (IHC) for immune cell subpopulations, and spatial transcriptomics to understand the relationship of HCC repeat expression, immune response, and clinical outcomes.

Experimental Design

RNA-ISH for LINE1, HERV-K, HERV-H, and HSATII repeats and IHC for T-cell, Treg, B-cell, macrophage, and immune checkpoint markers were performed on 43 resected HCC specimens. Spatial transcriptomics on tumor and vessel regions of interest was performed on 28 specimens from the same cohort.

Results

High HERV-K and high LINE1 expression were both associated with worse overall survival. There was a positive correlation between LINE1 expression and FOXP3 T-regulatory cells (r = 0.51 p < 0.001) as well as expression of the TIM3 immune checkpoint (r = 0.34, p = 0.03). Spatial transcriptomic profiling of HERV-K high and LINE-1 high tumors identified elevated expression of multiple genes previously associated with epithelial mesenchymal transition, cellular proliferation, and worse overall prognosis in HCC including SSX1, MAGEC2, and SPINK1.

Conclusion

Repeat RNAs may serve as useful prognostic biomarkers in HCC and may also serve as novel therapeutic targets. Additional study is needed to understand the mechanisms by which repeat RNAs impact HCC tumorigenesis.

Targeting MHC-I molecules for cancer: function, mechanism, and therapeutic prospects

The molecules of Major histocompatibility class I (MHC-I) load peptides and present them on the cell surface, which provided the immune system with the signal to detect and eliminate the infected or cancerous cells. In the context of cancer, owing to the crucial immune-regulatory roles played by MHC-I molecules, the abnormal modulation of MHC-I expression and function could be hijacked by tumor cells to escape the immune surveillance and attack, thereby promoting tumoral progression and impairing the efficacy of cancer immunotherapy. Here we reviewed and discussed the recent studies and discoveries related to the MHC-I molecules and their multidirectional functions in the development of cancer, mainly focusing on the interactions between MHC-I and the multiple participators in the tumor microenvironment and highlighting the significance of targeting MHC-I for optimizing the efficacy of cancer immunotherapy and a deeper understanding of the dynamic nature and functioning mechanism of MHC-I in cancer.

Recent advances in immune checkpoint inhibitors in the treatment of urothelial carcinoma: A review

Treatment options for urothelial carcinoma were limited until the emergence of immune checkpoint inhibitors, and even now, the prognosis of metastatic disease is poor compared with the other two major genitourinary cancers, renal cell carcinoma and prostate cancer. Despite the increasing use of immune checkpoint inhibitors in the sequential treatment of urothelial carcinoma, conflicting results from similar randomized clinical trials call into question the efficacy of this treatment. In addition, physicians must be aware of the clinical characteristics of immune checkpoint inhibitors, including immune-related adverse events, pseudo- and hyperprogression. This review summarizes the conflicting results of recent clinical trials and provides insights into the role of immune checkpoint inhibitors in the treatment of urothelial carcinoma.

Nivolumab plus ipilimumab in advanced salivary gland cancer: a phase 2 trial

Salivary gland cancers (SGCs) are rare, aggressive cancers without effective treatments when metastasized. We conducted a phase 2 trial evaluating nivolumab (nivo, anti-PD-1) and ipilimumab (ipi, anti-CTLA-4) in 64 patients with metastatic SGC enrolled in two histology-based cohorts (32 patients each): adenoid cystic carcinoma (ACC; cohort 1) and other SGCs (cohort 2). The primary efficacy endpoint (≥4 objective responses) was met in cohort 2 (5/32, 16%) but not in cohort 1 (2/32, 6%). Treatment safety/tolerability and progression-free survival (PFS) were secondary endpoints. Treatment-related adverse events grade ≥3 occurred in 24 of 64 (38%) patients across both cohorts, and median PFS was 4.4 months (95% confidence interval (CI): 2.4, 8.3) and 2.2 months (95% CI: 1.8, 5.3) for cohorts 1 and 2, respectively. We present whole-exome, RNA and T cell receptor (TCR) sequencing data from pre-treatment and on-treatment tumors and immune cell flow cytometry and TCR sequencing from peripheral blood at serial timepoints. Responding tumors universally demonstrated clonal expansion of pre-existing T cells and mutational contraction. Responding ACCs harbored neoantigens, including fusion-derived neoepitopes, that induced T cell responses ex vivo. This study shows that nivo+ipi has limited efficacy in ACC, albeit with infrequent, exceptional responses, and that it could be promising for non-ACC SGCs, particularly salivary duct carcinomas. ClinicalTrials.gov identifier: NCT03172624 .

Identifying biomarkers associated with immunotherapy response in melanoma by multi-omics analysis

Despite immune checkpoint inhibitors (ICIs) have shown the greatest success in melanoma treatment, only a subset of melanoma patients responds well to ICIs. Thus, identifying predictive biomarkers for immunotherapy response is crucial. In this study, we took complementary advantages of immunotherapy data and The Cancer Genome Atlas (TCGA) multi-omics data to explore the predictive biomarkers for the response to immunotherapy in melanoma. We first predicted responsive and non-responsive melanomas in the TCGA skin cutaneous melanoma (SKCM) cohort based on both somatic mutation and transcriptome datasets which involved immunotherapy data for melanoma. This method identified 170 responsive and 56 non-responsive melanomas in TCGA-SKCM. Based on the TCGA-SKCM data, we performed a comprehensive comparison of multi-omics molecular features between responsive and non-responsive melanomas. We identified the molecular features significantly associated with immunotherapy response in melanoma at the genome, transcriptome, epigenome, and proteome levels, respectively. Our analysis confirmed certain immunotherapy response-associated biomarkers, such as tumor mutation burden (TMB), copy number alteration (CNA), intratumor heterogeneity (ITH), PD-L1 expression, and tumor immunity. Moreover, we identified some novel molecular features associated with immunotherapy response: (1) the activation of mast cells and dendritic cells correlating negatively with immunotherapy response; (2) the enrichment of many oncogenic pathways correlating positively with immunotherapy response, such as JAK-STAT, RAS, MAPK, HIF-1, PI3K-Akt, and VEGF pathways; and (3) a number of microRNAs and proteins whose expression correlates with immunotherapy response. In addition, the mTOR signaling pathway has a negative association with immunotherapy response. The novel biomarkers have potential predictive values in immunotherapy response and warrant further investigation.