IKZF1 Enhances Immune Infiltrate Recruitment in Solid Tumors and Susceptibility to Immunotherapy

Mechanisms of Resistance and Therapeutic Perspectives in Immunotherapy for Advanced Head and Neck Cancers

Immunotherapy is emerging as an effective treatment for advanced head and neck cancers and interest in this treatment modality has led to rapid expansion of this research. Pembrolizumab and nivolumab, monoclonal antibodies directed against the programmed cell death-1 (PD-1) receptor, are US Food and Drug Administration (FDA)- and European Medical Agency (EMA)-approved immunotherapies for head and neck squamous cell carcinoma (HNSCC). Resistance to immunotherapy is common, with about 60% of patients with recurrent or metastatic HNSCC not responding to immunotherapy and only 20-30% of patients without disease progression in the long term. Overcoming resistance to immunotherapy is therefore essential for augmenting the effectiveness of immunotherapy in HNSCC. This review details the innate and adaptive mechanisms by which head and neck cancers can become resistant to immunotherapeutic agents, biomarkers that can be used for immunotherapy patient selection, as well as other factors of the tumor microenvironment correlated with therapeutic response and prognosis. Numerous combinations and novel immunotherapies are currently being trialed, based on better understood immune evasion mechanisms. These potential treatments hold the promise of overcoming resistance to immunotherapy in head and neck cancers.

Mapping inherited genetic variation with opposite effects on autoimmune disease and cancer identifies candidate drug targets associated with the anti-tumor immune response

Background

Germline alleles near genes that encode certain immune checkpoints (CTLA4, CD200) are associated with autoimmune/autoinflammatory disease and cancer but in opposite directions. This motivates a systematic search for additional germline alleles which demonstrate this pattern with the aim of identifying potential cancer immunotherapeutic targets using human genetic evidence.

Methods

Pairwise fixed effect cross-disorder meta-analyses combining genome-wide association studies (GWAS) for breast, prostate, ovarian and endometrial cancers (240,540 cases/317,000 controls) and seven autoimmune/autoinflammatory diseases (112,631 cases/895,386 controls) coupled with in silico follow-up. To ensure detection of alleles with opposite effects on cancer and autoimmune/autoinflammatory disease, the signs on the beta coefficients in the autoimmune/autoinflammatory GWAS were reversed prior to meta-analyses.

Results

Meta-analyses followed by linkage disequilibrium clumping identified 312 unique, independent lead variants with Pmeta<5x10-8 associated with at least one of the cancer types at Pcancer<10-3 and one of the autoimmune/autoinflammatory diseases at Pauto<10-3. At each lead variant, the allele that conferred autoimmune/autoinflammatory disease risk was protective for cancer. Mapping each lead variant to its nearest gene as its putative functional target and focusing on genes with established immunological effects implicated 32 of the nearest genes. Tumor bulk RNA-Seq data highlighted that the tumor expression of 5/32 genes (IRF1, IKZF1, SPI1, SH2B3, LAT) were each strongly correlated (Spearman's ρ>0.5) with at least one intra-tumor T/myeloid cell infiltration marker (CD4, CD8A, CD11B, CD45) in every one of the cancer types. Tumor single-cell RNA-Seq data from all cancer types showed that the five genes were more likely to be expressed in intra-tumor immune versus malignant cells. The five lead SNPs corresponding to these genes were linked to them via expression quantitative trait locus mechanisms and at least one additional line of functional evidence. Proteins encoded by the genes were predicted to be druggable.

Conclusion

We provide population-scale germline genetic and functional genomic evidence to support further evaluation of the proteins encoded by IRF1, IKZF1, SPI1, SH2B3, and LAT as possible targets for cancer immunotherapy.

Comprehensive Analysis of Tumor Microenvironment Reveals Prognostic ceRNA Network Related to Immune Infiltration in Sarcoma

PURPOSE

Sarcoma is the second most common solid tumor type in children and adolescents. The high level of tumor heterogeneity as well as aggressive behavior of sarcomas brings serious difficulties to developing effective therapeutic strategies for clinical application. Therefore, it is of great importance to identify accurate biomarkers for early detection and prognostic prediction of sarcomas.

EXPERIMENTAL DESIGN

In this study, we characterized three subtypes of sarcomas based on tumor immune infiltration levels (TIIL), and constructed a prognosis-related competing endogenous RNA (ceRNA) network to investigate molecular regulations in the sarcoma tumor microenvironment (TME). We further built a subnetwork consisting of mRNAs and lncRNAs that are targets of key miRNAs and strongly correlated with each other in the ceRNA network. After validation using public data and experiments in vivo and in vitro, we deeply dug the biological role of the miRNAs and lncRNAs in a subnetwork and their impact on TME.

RESULTS

Altogether, 5 miRNAs (hsa-mir-125b-2, hsa-mir-135a-1, hsa-mir92a-2, hsa-mir-181a-2, and hsa-mir-214), 3 lncRNAs (LINC00641, LINC01146, and LINC00892), and 10 mRNAs (AGO2, CXCL10, CD86, CASP1, IKZF1, CD27, CD247, CD69, CCR2, and CSF2RB) in the subnetwork were identified as vital regulators to shape the TME. On the basis of the systematic network, we identified that trichostatin A, a pan-HDAC inhibitor, could potentially regulate the TME of sarcoma, thereby inhibiting the tumor growth.

CONCLUSIONS

Our study identifies a ceRNA network as a promising biomarker for sarcoma. This system provides a more comprehensive understanding and a novel perspective of how ceRNAs are involved in shaping sarcoma TME.

Characterization of tumor microenvironment in glioblastoma multiforme identifies ITGB2 as a key immune and stromal related regulator in glial cell types

Glioblastoma multiforme (GBM) is the most aggressive form of brain tumor characterized by inter and intra-tumor heterogeneity and complex tumor microenvironment. To uncover the molecular targets in this milieu, we systematically identified immune and stromal interactions at the glial cell type level that leverages on RNA-sequencing data of GBM patients from The Cancer Genome Atlas. The perturbed genes between the high vs low immune and stromal scored patients were subjected to weighted gene co-expression network analysis to identify the glial cell type specific networks in immune and stromal infiltrated patients. The intramodular connectivity analysis identified the highly connected genes in each module. Combining it with univariable and multivariable prognostic analysis revealed common vital gene ITGB2, between the immune and stromal infiltrated patients enriched in microglia and newly formed oligodendrocytes. We found following unique hub genes in immune infiltrated patients; COL6A3 (microglia), ITGAM (oligodendrocyte precursor cells), TNFSF9 (microglia), and in stromal infiltrated patients, SERPINE1 (microglia) and THBS1 (newly formed oligodendrocytes, oligodendrocyte precursor cells). To validate these hub genes, we used external GBM patient single cell RNA-sequencing dataset and this identified ITGB2 to be significantly enriched in microglia, newly formed oligodendrocytes, T-cells, macrophages and adipocyte cell types in both immune and stromal datasets. The tumor infiltration analysis of ITGB2 showed that it is correlated with myeloid dendritic cells, macrophages, monocytes, neutrophils, B-cells, fibroblasts and adipocytes. Overall, the systematic screening of tumor microenvironment components at glial cell types uncovered ITGB2 as a potential target in primary GBM.

Functional Profiling of Soft Tissue Sarcoma Using Mechanistic Models

Soft tissue sarcoma is an umbrella term for a group of rare cancers that are difficult to treat. In addition to surgery, neoadjuvant chemotherapy has shown the potential to downstage tumors and prevent micrometastases. However, finding effective therapeutic targets remains a research challenge. Here, a previously developed computational approach called mechanistic models of signaling pathways has been employed to unravel the impact of observed changes at the gene expression level on the ultimate functional behavior of cells. In the context of such a mechanistic model, RNA-Seq counts sourced from the Recount3 resource, from The Cancer Genome Atlas (TCGA) Sarcoma project, and non-diseased sarcomagenic tissues from the Genotype-Tissue Expression (GTEx) project were utilized to investigate signal transduction activity through signaling pathways. This approach provides a precise view of the relationship between sarcoma patient survival and the signaling landscape in tumors and their environment. Despite the distinct regulatory alterations observed in each sarcoma subtype, this study identified 13 signaling circuits, or elementary sub-pathways triggering specific cell functions, present across all subtypes, belonging to eight signaling pathways, which served as predictors for patient survival. Additionally, nine signaling circuits from five signaling pathways that highlighted the modifications tumor samples underwent in comparison to normal tissues were found. These results describe the protective role of the immune system, suggesting an anti-tumorigenic effect in the tumor microenvironment, in the process of tumor cell detachment and migration, or the dysregulation of ion homeostasis. Also, the analysis of signaling circuit intermediary proteins suggests multiple strategies for therapy.

Should I stay or should I go? Spatio-temporal control of cellular anchorage by hematopoietic factors orchestrates tumor metastatic cascade

The term "metastatic cascade" defines a process whereby few tumor cells complete a sequence of steps to leave the primary tumor to reach one or more sites elsewhere in the body, usually through the bloodstream to develop one or several metastases. Due to the nature and plasticity of cancer, unfortunately no specific and functional anti-metastatic drugs are available. In this Commentary, we are highlighting how four essential factors are able to induce adhesion-to-suspension transition (herein referred to as AST) in human cancer cells and how this process may play a key role in tumor metastasis. We further underlined the potential role of hematopoietic transcriptional regulators in reprogramming anchorage dependency of cells, supporting the possible targeting of AST factors as promising therapeutic strategy to overcome metastasis in solid tumor cells.

A Meta-Analysis Study to Infer Voltage-Gated K+ Channels Prognostic Value in Different Cancer Types

Potassium channels are often highly expressed in cancer cells with respect to healthy ones, as they provide proliferative advantages through modulating membrane potential, calcium homeostasis, and various signaling pathways. Among potassium channels, Shaker type voltage-gated Kv channels are emerging as promising pharmacological targets in oncology. Here, we queried publicly available cancer patient databases to highlight if a correlation exists between Kv channel expression and survival rate in five different cancer types. By multiple gene comparison analysis, we found a predominant expression of KCNA2, KCNA3, and KCNA5 with respect to the other KCNA genes in skin cutaneous melanoma (SKCM), uterine corpus endometrial carcinoma (UCEC), stomach adenocarcinoma (STAD), lung adenocarcinoma (LUAD), and lung squamous cell carcinoma (LUSC). This analysis highlighted a prognostic role of KCNA3 and KCNA5 in SKCM, LUAD, LUSC, and STAD, respectively. Interestingly, KCNA3 was associated with a positive prognosis in SKCM and LUAD but not in LUSC. Results obtained by the analysis of KCNA3-related differentially expressed genes (DEGs); tumor immune cell infiltration highlighted differences that may account for such differential prognosis. A meta-analysis study was conducted to investigate the role of KCNA channels in cancer using cancer patients’ datasets. Our study underlines a promising correlation between Kv channel expression in tumor cells, in infiltrating immune cells, and survival rate.

Programmed Cell Death-Ligand 1 in Head and Neck Squamous Cell Carcinoma: Molecular Insights, Preclinical and Clinical Data, and Therapies

Aberrant expression of the programmed cell death protein ligand 1 (PD-L1) constitutes one of the main immune evasion mechanisms of cancer cells. The approval of drugs against the PD-1-PD-L1 axis has given new impetus to the chemo-therapy of many malignancies. We performed a literature review from 1992 to August 2022, summarizing evidence regarding molecular structures, physiological and pathological roles, mechanisms of PD-L1 overexpression, and immunotherapy evasion. Furthermore, we summarized the studies concerning head and neck squamous cell carcinomas (HNSCC) immunotherapy and the prospects for improving the associated outcomes, such as identifying treatment response biomarkers, new pharmacological combinations, and new molecules. PD-L1 overexpression can occur via four mechanisms: genetic modifications; inflammatory signaling; oncogenic pathways; microRNA or protein-level regulation. Four molecular mechanisms of resistance to immunotherapy have been identified: tumor cell adaptation; changes in T-cell function or proliferation; alterations of the tumor microenvironment; alternative immunological checkpoints. Immunotherapy was indeed shown to be superior to traditional chemotherapy in locally advanced/recurrent/metastatic HNSCC treatments.

Novel IKZF3 transcriptomic signature correlates with positive outcomes of skin cutaneous melanoma: A pan-cancer analysis

To investigate the potential relationship between Ikaros family genes and skin cutaneous melanoma (SKCM), we undertook a pan-cancer analysis of the transcriptional signature and clinical data of melanoma through multiple databases. First, 10,327 transcriptomic samples from different cancers were included to determine the overall characteristics and clinical prognoses associated with Ikaros gene expression across cancer types. Second, differentially expressed genes analysis, prognostic evaluation, and gene set enrichment analysis were employed to investigate the role of Ikaros (IKZF) genes in SKCM. Third, we evaluated the relationship between Ikaros family genes and SKCM immune infiltrates and verified the findings using the GEO single-cell sequencing dataset. The results show that Ikaros genes were widely expressed among different cancer types with independently similar patterns as follows: 1. IKZF1 and IKZF3, and 2. IKZF2 and IKZF4–5. IKZF2 and IKZF5 were downregulated in the primary tumor, and IKZF1–3 expression decreased significantly as the T-stage or metastasis increased in SKCM. Moreover, high IKZF1–3 expression was associated with better overall survival, disease-specific survival, and progression-free interval. IKZF3 is an independent prognostic factor of SKCM. Among Ikaros genes, the expression of IKZF1 and IKZF3 positively correlated with the infiltration level of CD4⁺ T cells and CD8⁺ T cells, B cells, and Tregs in SKCM and negatively correlated with the infiltration level of M0 and M1 macrophages. Moreover, single-cell sequencing data analysis revealed that IKZF1 and IKZF3 were mainly expressed by immune cells. Correlation analysis shows the immune factors and drug responses associated with IKZF3 expression. In conclusion, the present study is the first, to our knowledge, to identify a pan-cancer genomic signature of the Ikaros gene family among different cancers. Expression of these family members, particularly high levels of IKZF3, indicate positive immunological status and beneficial clinical outcomes of SKCM. IKZF3 may therefore serve as potential targets for immunotherapy of melanoma.

Ph-like gene alterations and complex chromosomal abnormalities are frequent in patients with acute lymphoblastic leukemia experiencing relapse after allogeneic hematopoietic cell transplantation

The new aspect of our work is to reveal that Ph-like alterations are common among patients with Ph-ALL experiencing relapse after hematopoietic cell transplantation (HCT), despite acquisition of MRD-negative complete responses prior to transplant. This is also the central finding of our work. Therefore, the anticipated benefits of HCT appear diminished among this patient subset; such patients may be better served with efforts to further increase MRD depth prior to HCT, or alternative therapies.

Primary cicatricial alopecias are characterized by dysregulation of shared gene expression pathways

The primary forms of cicatricial (scarring) alopecia (PCA) are a group of inflammatory, irreversible hair loss disorders characterized by immune cell infiltrates targeting hair follicles (HFs). Lichen planopilaris (LPP), frontal fibrosing alopecia (FFA), and centrifugal cicatricial alopecia (CCCA) are among the main subtypes of PCAs. The pathogenesis of the different types of PCAs are poorly understood, and current treatment regimens yield inconsistent and unsatisfactory results. We performed high-throughput RNA-sequencing on scalp biopsies of a large cohort PCA patients to develop gene expression-based signatures, trained into machine-learning-based predictive models and pathways associated with dysregulated gene expression. We performed morphological and cytokine analysis to define the immune cell populations found in PCA subtypes. We identified a common PCA gene signature that was shared between LPP, FFA, and CCCA, which revealed a significant over-representation of mast cell (MC) genes, as well as downregulation of cholesterogenic pathways and upregulation of fibrosis and immune signaling genes. Immunohistological analyses revealed an increased presence of MCs in PCAs lesions. Our gene expression analyses revealed common pathways associated with PCAs, with a strong association with MCs. The indistinguishable differences in gene expression profiles and immune cell signatures between LPP, FFA, and CCCA suggest that similar treatment regimens may be effective in treating these irreversible forms of hair loss.

Identification of Master Regulators Driving Disease Progression, Relapse, and Drug Resistance in Lung Adenocarcinoma

Backgrounds: Lung cancer is the leading cause of cancer related death worldwide. Current treatment strategies primarily involve surgery, chemotherapy, radiotherapy, targeted therapy, and immunotherapy, determined by TNM stages, histologic types, and genetic profiles. Plenty of studies have been trying to identify robust prognostic gene expression signatures. Even for high performance signatures, they usually have few shared genes. This is not totally unexpected, since a prognostic signature is associated with patient survival and may contain no upstream regulators. Identification of master regulators driving disease progression is a vital step to understand underlying molecular mechanisms and develop new treatments.

Methods: In this study, we have utilized a robust workflow to identify potential master regulators that drive poor prognosis in patients with lung adenocarcinoma. This workflow takes gene expression signatures that are associated with poor survival of early-stage lung adenocarcinoma, EGFR-TKI resistance, and responses to immune checkpoint inhibitors, respectively, and identifies recurrent master regulators from seven public gene expression datasets by a regulatory network-based approach.

Results: We have found that majority of the master regulators driving poor prognosis in early stage LUAD are cell-cycle related according to Gene Ontology annotation. However, they were demonstrated experimentally to promote a spectrum of processes such as tumor cell proliferation, invasion, metastasis, and drug resistance. Master regulators predicted from EGFR-TKI resistance signature and the EMT pathway signature are largely shared, which suggests that EMT pathway functions as a hub and interact with other pathways such as hypoxia, angiogenesis, TNF-α signaling, inflammation, TNF-β signaling, Wnt, and Notch signaling pathways. Master regulators that repress immunotherapy are enriched with MYC targets, E2F targets, oxidative phosphorylation, and mTOR signaling.

Conclusion: Our study uncovered possible mechanisms underlying recurrence, resistance to targeted therapy, and immunotherapy. The predicted master regulators may serve as potential therapeutic targets in patients with lung adenocarcinoma.

Ikaros Proteins in Tumor: Current Perspectives and New Developments

Ikaros is a zinc finger transcription factor (TF) of the Krüppel family member, which significantly regulates normal lymphopoiesis and tumorigenesis. Ikaros can directly initiate or suppress tumor suppressors or oncogenes, consequently regulating the survival and proliferation of cancer cells. Over recent decades, a series of studies have been devoted to exploring and clarifying the relationship between Ikaros and associated tumors. Therapeutic strategies targeting Ikaros have shown promising therapeutic effects in both pre-clinical and clinical trials. Nevertheless, the increasingly prominent problem of drug resistance targeted to Ikaros and its analog is gradually appearing in our field of vision. This article reviews the role of Ikaros in tumorigenesis, the mechanism of drug resistance, the progress of targeting Ikaros in both pre-clinical and clinical trials, and the potential use of associated therapy in cancer therapy.

Identification of a ceRNA Network in Lung Adenocarcinoma Based on Integration Analysis of Tumor-Associated Macrophage Signature Genes

As research into tumor-immune interactions progresses, immunotherapy is becoming the most promising treatment against cancers. The tumor microenvironment (TME) plays the key role influencing the efficacy of anti-tumor immunotherapy, in which tumor-associated macrophages (TAMs) are the most important component. Although evidences have emerged revealing that competing endogenous RNAs (ceRNAs) were involved in infiltration, differentiation and function of immune cells by regulating interactions among different varieties of RNAs, limited comprehensive investigation focused on the regulatory mechanism between ceRNA networks and TAMs. In this study, we aimed to utilize bioinformatic approaches to explore how TAMs potentially influence the prognosis and immunotherapy of lung adenocarcinoma (LUAD) patients. Firstly, according to TAM signature genes, we constructed a TAM prognostic risk model by the least absolute shrinkage and selection operator (LASSO) cox regression in LUAD patients. Then, differential gene expression was analyzed between high- and low-risk patients. Weighted gene correlation network analysis (WGCNA) was utilized to identify relevant gene modules correlated with clinical characteristics and prognostic risk score. Moreover, ceRNA networks were built up based on predicting regulatory pairs in differentially expressed genes. Ultimately, by synthesizing information of protein-protein interactions (PPI) analysis and survival analysis, we have successfully identified a core regulatory axis: LINC00324/miR-9-5p (miR-33b-5p)/GAB3 (IKZF1) which may play a pivotal role in regulating TAM risk and prognosis in LUAD patients. The present study contributes to a better understanding of TAMs associated immunosuppression in the TME and provides novel targets and regulatory pathway for anti-tumor immunotherapy.

Revealing new therapeutic opportunities through drug target prediction: a class imbalance-tolerant machine learning approach

MOTIVATION

In silico drug target prediction provides valuable information for drug repurposing, understanding of side effects as well as expansion of the druggable genome. In particular, discovery of actionable drug targets is critical to developing targeted therapies for diseases.

RESULTS

Here, we develop a robust method for drug target prediction by leveraging a class imbalance-tolerant machine learning framework with a novel training scheme. We incorporate novel features, including drug-gene phenotype similarity and gene expression profile similarity that capture information orthogonal to other features. We show that our classifier achieves robust performance and is able to predict gene targets for new drugs as well as drugs that potentially target unexplored genes. By providing newly predicted drug-target associations, we uncover novel opportunities of drug repurposing that may benefit cancer treatment through action on either known drug targets or currently undrugged genes.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Transcriptional Regulation of Cancer Immune Checkpoints: Emerging Strategies for Immunotherapy

The study of immune evasion has gained a well-deserved eminence in cancer research by successfully developing a new class of therapeutics, immune checkpoint inhibitors, such as pembrolizumab and nivolumab, anti-PD-1 antibodies. By aiming at the immune checkpoint blockade (ICB), these new therapeutics have advanced cancer treatment with notable increases in overall survival and tumor remission. However, recent reports reveal that 40-60% of patients fail to benefit from ICB therapy due to acquired resistance or tumor relapse. This resistance may stem from increased expression of co-inhibitory immune checkpoints or alterations in the tumor microenvironment that promotes immune suppression. Because these mechanisms are poorly elucidated, the transcription factors that regulate immune checkpoints, known as "master regulators", have garnered interest. These include AP-1, IRF-1, MYC, and STAT3, which are known to regulate PD/PD-L1 and CTLA-4. Identifying these and other potential master regulators as putative therapeutic targets or biomarkers can be facilitated by mining cancer literature, public datasets, and cancer genomics resources. In this review, we describe recent advances in master regulator identification and characterization of the mechanisms underlying immune checkpoints regulation, and discuss how these master regulators of immune checkpoint molecular expression can be targeted as a form of auxiliary therapeutic strategy to complement traditional immunotherapy.

Identification of Tumor Microenvironment-Related Prognostic Biomarkers in Luminal Breast Cancer

Background: The tumor microenvironment (TME) has been reported to have significant value in the diagnosis and prognosis of cancers. This study aimed to identify key biomarkers in the TME of luminal breast cancer (BC).

Methods: We obtained immune scores (ISs) and stromal scores (SSs) for The Cancer Genome Atlas (TCGA) luminal BC cohort from the online ESTIMATE (Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data) portal. The relationships between ISs and SSs and the overall survival of luminal BC patients were assessed by the Kaplan-Meier method. The differentially expressed messenger RNAs (DEmRNAs) related to the ISs and SSs were subjected to functional enrichment analysis. Additionally, a competing endogenous RNA (ceRNA) network was constructed with differentially expressed microRNAs (DEmiRNAs) and long noncoding RNAs (DElncRNAs). Furthermore, a protein–protein interaction (PPI) network was established to analyze the DEmRNAs in the ceRNA network. Then, survival analysis of biomarkers involved in the ceRNA network was carried out to explore their prognostic value. Finally, these biomarkers were validated using the luminal BC dataset from the Gene Expression Omnibus (GEO) database.

Results: The results showed that ISs were significantly associated with longer survival times of luminal BC patients. Functional enrichment analysis showed that the DEmRNAs were mainly associated with immune response, antigen binding, and the extracellular region. In the PPI network, the top 10 DEmRNAs were identified as hub genes that affected the TME of luminal BC. Finally, two DEmiRNAs, two DElncRNAs, and 17 DEmRNAs of the ceRNA network associated with the TME were shown to have prognostic value. Subsequently, the expression of 15 prognostic biomarkers was validated in one additional dataset (GSE81002). In particular, one lncRNA (GVINP1) and five mRNAs (CCDC69, DOCK2, IKZF1, JCHAIN, and NCKAP1L) were novel biomarkers.

Conclusions: Our studies demonstrated that ISs were associated with the survival of luminal BC patients, and a set of novel biomarkers that might play a prognostic role in the TME of luminal BC was identified.

MMP25 Regulates Immune Infiltration Level and Survival Outcome in Head and Neck Cancer Patients

Background: MMP25 is a critical gene of matrix metalloproteinases (MMPs). However, the molecular mechanism of MMP25 in head and neck cancer pathogenesis remains unclear.

Methods: MMP25 expression was analyzed using The Cancer Genome Atlas (TCGA) database, and its influence on clinical prognosis was performed using Kaplan–Meier and Cox regression analyses. The correlation between MMP25 and immune infiltration was investigated by CIBERSORT, TIMER, and ESTIMATE. In addition, the relationship between MMP25 expression and molecular mechanisms was analyzed by gene set enrichment analysis (GSEA), gene ontology (GO), and weighted gene co-expression network analysis (WGCNA).

Results: MMP25 expression level correlated with prognosis and immune infiltrating levels, especially activated CD4⁺ memory T cells, in head and neck cancer. Moreover, MMP25 expression potentially mediated genes, such as IRF8, IKZF1, and DOCK2, and tumor-associated pathways, including p53 signaling, PI3K/AKT/mTOR signaling, and JAK/STAT signaling pathway.

Conclusions: These findings suggested that MMP25 plays a critical role in the prognosis and immune infiltration level of head and neck cancer. In addition, MMP25 expression significantly correlated with the regulation of various oncogenes and tumor-related pathways.

Mutational Landscape of Esophageal Squamous Cell Carcinoma in an Indian Cohort

Esophageal squamous cell carcinoma (ESCC) is the most common histological subtype of esophageal cancer in India. Cigarette smoking and chewing tobacco are known risk factors associated with ESCC. However, genomic alterations associated with ESCC in India are not well-characterized. In this study, we carried out exome sequencing to characterize the mutational landscape of ESCC tumors from subjects with a varied history of tobacco usage. Whole exome sequence analysis of ESCC from an Indian cohort revealed several genes that were mutated or had copy number changes. ESCC from tobacco chewers had a higher frequency of C:G > A:T transversions and 2-fold enrichment for mutation signature 4 compared to smokers and non-users of tobacco. Genes, such as TP53, CSMD3, SYNE1, PIK3CA, and NOTCH1 were found to be frequently mutated in Indian cohort. Mutually exclusive mutation patterns were observed in PIK3CA-NOTCH1, DNAH5-ZFHX4, MUC16-FAT1, and ZFHX4-NOTCH1 gene pairs. Recurrent amplifications were observed in 3q22-3q29, 11q13.3-q13.4, 7q22.1-q31.1, and 8q24 regions. Approximately 53% of tumors had genomic alterations in PIK3CA making this pathway a promising candidate for targeted therapy. In conclusion, we observe enrichment of mutation signature 4 in ESCC tumors from patients with a history of tobacco chewing. This is likely due to direct exposure of esophagus to tobacco carcinogens when it is chewed and swallowed. Genomic alterations were frequently observed in PIK3CA-AKT pathway members independent of the history of tobacco usage. PIK3CA pathway can be potentially targeted in ESCC which currently has no effective targeted therapeutic options.

Current Understanding of the Mechanisms Underlying Immune Evasion From PD-1/PD-L1 Immune Checkpoint Blockade in Head and Neck Cancer

Starting in 2014, large phase III clinical trials began to disclose the study results of using programmed death (PD)-1 immune checkpoint inhibitors (ICIs) (pembrolizumab, nivolumab) and PD-ligand (L)1 (atezolizumab, durvalumab, avelumab) ICIs immunotherapy in patients with advanced head and neck squamous cell carcinoma (HNSCC). In the recurrent and metastatic (R/M), cisplatin-refractory setting, nivolumab achieved a 2.2-fold increase of the median 1-year overall survival as compared with investigators' choice of salvage chemotherapy (36.0 vs. 16.6%). A paradigm shift to the winning regimen, pembrolizumab combined with platinum and infusional fluorouracil, has outperformed the past gold standard of cetuximab-based platinum and fluorouracil combination in terms of overall survival (median, 13.6 vs. 10.1 mo) when administered as the first-line treatment for R/M HNSCC. Nevertheless, many patients still did not respond to the PD-1/PD-L1 checkpoint inhibitor treatment, indicating innate, adapted, or quickly acquired resistance to the immunotherapy. The mechanisms of resistance to ICIs targeting the PD-1/PD-L1 signaling pathway in the context of HNSCC are the focus of this review. The past 5 years have seen improved understanding of the mechanisms underlying checkpoint inhibition resistance in tumor cells, such as: tumor cell adaption with malfunction of the antigen-presenting machinery via class I human leukocyte antigen (HLA), reintroduction of cyclin D-cyclin-dependent kinase (CDK) 4 complex to cell cycles, enrichment of CD44+ cancer stem-like cells, or development of inactivating mutation in IKZF1 gene; impairment of T-cell functions and proliferation through mutations in the interferon-γ-regulating genes, suppression of the stimulator of interferon genes (STING) pathway, or resulted from constitutional nutritional iron deficiency state; metabolic reprogramming by cancer cells with changes in metabolites such as GTP cyclohydrolase 1, tetrahydrobiopterin, kynurenine, indoleamine 2,3-dioxygenase, and arginase 1; defective dendritic cells, CD-69 sufficient state; and the upregulation or activation of the alternative immune checkpoints, including lymphocyte activation gene-3 (LAG3), T-cell immunoglobulin and ITIM domain (TIGIT)/CD155 pathway, T-cell immunoglobulin mucin-3 (TIM-3), and V domain-containing Ig suppressor of T-cell activation (VISTA). Several potential biomarkers or biosignatures, which could predict the response or resistance to the PD-1/PD-L1 checkpoint immunotherapy, are also discussed.

Combined analysis and validation for DNA methylation and gene expression profiles associated with prostate cancer

BACKGROUND

Prostate cancer (PCa) is a malignancy cause of cancer deaths and frequently diagnosed in male. This study aimed to identify tumor suppressor genes, hub genes and their pathways by combined bioinformatics analysis.

METHODS

A combined analysis method was used for two types of microarray datasets (DNA methylation and gene expression profiles) from the Gene Expression Omnibus (GEO). Differentially methylated genes (DMGs) were identified by the R package minfi and differentially expressed genes (DEGs) were screened out via the R package limma. A total of 4451 DMGs and 1509 DEGs, identified with nine overlaps between DMGs, DEGs and tumor suppressor genes, were screened for candidate tumor suppressor genes. All these nine candidate tumor suppressor genes were validated by TCGA (The Cancer Genome Atlas) database and Oncomine database. And then, the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed by DAVID (Database for Annotation, Visualization and Integrated Discovery) database. Protein-protein interaction (PPI) network was constructed by STRING and visualized in Cytoscape. At last, Kaplan-Meier analysis was performed to validate these genes.

RESULTS

The candidate tumor suppressor genes were IKZF1, PPM1A, FBP1, SMCHD1, ALPL, CASP5, PYHIN1, DAPK1 and CASP8. By validation in TCGA database, PPM1A, DAPK1, FBP1, PYHIN1, ALPL and SMCHD1 were significant. The hub genes were FGFR1, FGF13 and CCND1. These hub genes were identified from the PPI network, and sub-networks revealed by these genes were involved in significant pathways.

CONCLUSION

In summary, the study indicated that the combined analysis for identifying target genes with PCa by bioinformatics tools promote our understanding of the molecular mechanisms and underlying the development of PCa. And the hub genes might serve as molecular targets and diagnostic biomarkers for precise diagnosis and treatment of PCa.

Analysis on GENIE reveals novel recurrent variants that affect molecular diagnosis of sizable number of cancer patients

Background

Significant numbers of variants detected in cancer patients are often left labeled only as variants of unknown significance (VUS). In order to expand precision medicine to a wider population, we need to extend our knowledge of pathogenicity and drug response in the context of VUS’s.

Methods

In this study, we analyzed variants from AACR Project GENIE Consortium APG (Cancer Discov 7:818-831, 2017) and compared them to the COSMIC database Forbes et al. (Nucleic Acids Res 43:D805-811, 2015) to identify recurrent variants that would merit further study. We filtered out known hotspot variants, inactivating variants in tumor suppressors, and likely benign variants by comparing with COSMIC and ExAC Lee et al. (Science 337:967-971, 2012).

Results

We have identified 45,933 novel variants with unknown significance unique to GENIE. In our analysis, we found on average six variants per patient where two could be considered as pathogenic or likely pathogenic and the majority are VUS’s. More importantly, we have discovered 730 recurrent variants that appear more than 3 times in GENIE but less than 3 in COSMIC. If we combine the recurrences of GENIE and COSMIC for all variants, 2586 are newly identified as occurring more than 3 times than when using COSMIC alone.

Conclusions

Although it would be inappropriate to blindly accept these recurrent variants as pathogenic, they may warrant higher priority than other observed VUS’s. These newly identified recurrent variants might affect the molecular profiles of approximately 1 in 6 patients. Further analysis and characterization of these variants in both research and clinical contexts will improve patient treatments and the development of new therapeutics.

Electronic supplementary material

The online version of this article (10.1186/s12885-019-5313-1) contains supplementary material, which is available to authorized users.