Immune response-associated gene analysis of 1,000 cancer patients using whole-exome sequencing and gene expression profiling-Project HOPE

Prognostic value of pretreatment lymphocyte percentage in oral cancer: A prospective cohort study

OBJECTIVE

To assess the prognostic role of pretreatment lymphocyte percentage (LY%) for patients with oral squamous cell carcinoma (OSCC).

METHODS

A large-scale prospective cohort study between July 2002 and March 2021 was conducted. Propensity score-matched (PSM) analysis and inverse probability of treatment weighting (IPTW) analysis were performed to adjust for potential confounders. Using random survival forest (RSF), the relative importance of pretreatment LY% in prognosis prediction was also assessed.

RESULTS

A total of 743 patients were enrolled and followed up (median: 2.75 years, interquartile range: 1.25-4.42 years). A high pretreatment LY% was significantly associated with better disease-specific survival of patients with OSCC (Hazard ratio [HR] = 0.60, 95% confidence interval [CI]: 0.42, 0.84). The same tendency was observed in PSM (HR = 0.57, 95% CI: 0.38, 0.85) and IPTW analysis (HR = 0.57, 95% CI: 0.40, 0.82). RSF showed that LY% ranked the fifth among importance ranking of all prognostic factors.

CONCLUSION

Pretreatment LY% showed a moderate predictive ability, suggesting it might be a valuable tool to predict prognosis for patients with OSCC.

Phototherapy Restores Deficient Type I IFN Production and Enhances Antitumor Responses in Mycosis Fungoides

Transcriptional profiling demonstrated markedly reduced type I IFN gene expression in untreated mycosis fungoides (MF) skin lesions compared with that in healthy skin. Type I IFN expression in MF correlated with antigen-presenting cell-associated IRF5 before psoralen plus UVA therapy and epithelial ULBP2 after therapy, suggesting an enhancement of epithelial type I IFN. Immunostains confirmed reduced baseline type I IFN production in MF and increased levels after psoralen plus UVA treatment in responding patients. Effective tumor clearance was associated with increased type I IFN expression, enhanced recruitment of CD8+ T cells into skin lesions, and expression of genes associated with antigen-specific T-cell activation. IFNk, a keratinocyte-derived inducer of type I IFNs, was increased by psoralen plus UVA therapy and expression correlated with upregulation of other type I IFNs. In vitro, deletion of keratinocyte IFNk decreased baseline and UVA-induced expression of type I IFN and IFN response genes. In summary, we find a baseline deficit in type I IFN production in MF that is restored by psoralen plus UVA therapy and correlates with enhanced antitumor responses. This may explain why MF generally develops in sun-protected skin and suggests that drugs that increase epithelial type I IFNs, including topical MEK and EGFR inhibitors, may be effective therapies for MF.

Identification of tumor microenvironment-associated immunological genes as potent prognostic markers in the cancer genome analysis project HOPE

Project High-tech Omics-based Patient Evaluation (HOPE), which used whole-exome sequencing and gene expression profiling, was launched in 2014. A total of ~2,000 patients were enrolled until March 2016, and the survival time was observed up to July 2019. In our previous study, a tumor microenvironment immune type classification based on the expression levels of the programmed death-ligand 1 (PD-L1) and CD8B genes was performed based on four types: A, adaptive immune resistance; B, intrinsic induction; C, immunological ignorance; and D, tolerance. Type A (PD-L1⁺ and CD8B⁺) exhibited upregulated features of T helper 1 antitumor responses. In the present study, survival time analysis at 5 years revealed that patients in type A had a better prognosis than those in other categories [5 year survival rate (%); A (80.5) vs. B (73.9), C (73.4) and D (72.6), P=0.0005]. Based on the expression data of 293 immune response-associated genes, 62 specific genes were upregulated in the type A group. Among these genes, 18 specific genes, such as activated effector T-cell markers (CD8/CD40LG/GZMB), effector memory T-cell markers (PD-1/CD27/ICOS), chemokine markers (CXCL9/CXCL10) and activated dendritic cell markers (CD80/CD274/SLAMF1), were significantly associated with a good prognosis using overall survival time analysis. Finally, multivariate Cox proportional hazard regression analyses of overall survival demonstrated that four genes (GZMB, HAVCR2, CXCL9 and CD40LG) were independent prognostic markers, and GZMB, CXCL9 and CD40LG may contribute to the survival benefit of patients in the immune type A group.

The Comprehensive "Omics" Approach from Metabolomics to Advanced Omics for Development of Immune Checkpoint Inhibitors: Potential Strategies for Next Generation of Cancer Immunotherapy

In the past decade, immunotherapies have been emerging as an effective way to treat cancer. Among several categories of immunotherapies, immune checkpoint inhibitors (ICIs) are the most well-known and widely used options for cancer treatment. Although several studies continue, this treatment option has yet to be developed into a precise application in the clinical setting. Recently, omics as a high-throughput technique for understanding the genome, transcriptome, proteome, and metabolome has revolutionized medical research and led to integrative interpretation to advance our understanding of biological systems. Advanced omics techniques, such as multi-omics, single-cell omics, and typical omics approaches, have been adopted to investigate various cancer immunotherapies. In this review, we highlight metabolomic studies regarding the development of ICIs involved in the discovery of targets or mechanisms of action and assessment of clinical outcomes, including drug response and resistance and propose biomarkers. Furthermore, we also discuss the genomics, proteomics, and advanced omics studies providing insights and comprehensive or novel approaches for ICI development. The overview of ICI studies suggests potential strategies for the development of other cancer immunotherapies using omics techniques in future studies.

A Quest for New Cancer Diagnosis, Prognosis and Prediction Biomarkers and Their Use in Biosensors Development

Traditional techniques for cancer diagnosis, such as nuclear magnetic resonance, ultrasound and tissue analysis, require sophisticated devices and highly trained personnel, which are characterized by elevated operation costs. The use of biomarkers has emerged as an alternative for cancer diagnosis, prognosis and prediction because their measurement in tissues or fluids, such as blood, urine or saliva, is characterized by shorter processing times. However, the biomarkers used currently, and the techniques used for their measurement, including ELISA, western-blot, polymerase chain reaction (PCR) or immunohistochemistry, possess low sensitivity and specificity. Therefore, the search for new proteomic, genomic or immunological biomarkers and the development of new noninvasive, easier and cheaper techniques that meet the sensitivity and specificity criteria for the diagnosis, prognosis and prediction of this disease has become a relevant topic. The purpose of this review is to provide an overview about the search for new cancer biomarkers, including the strategies that must be followed to identify them, as well as presenting the latest advances in the development of biosensors that possess a high potential for cancer diagnosis, prognosis and prediction, mainly focusing on their relevance in lung, prostate and breast cancers.

Autoinducer-2 of gut microbiota, a potential novel marker for human colorectal cancer, is associated with the activation of TNFSF9 signaling in macrophages

Objectives: The interaction between the quorum sensing (QS) molecules of gut microbiota and the immunity of colorectal cancer (CRC) has not been investigated before. Methods: We measured the concentration of autoinducer-2 (AI-2) in samples of stool, colorectal tissue, saliva and serum of CRC patients, and compared this to AI-2 levels in colorectal adenoma (AD) and normal colon mucosa (NC). To explore the activated signaling pathways involved, we utilized AI-2 extracted from Fusobacterium nucleatum to stimulate macrophages and validated these in vitro findings in human CRC tissues. Results: The AI-2 concentration in both colorectal tissue and stool of CRC patients was significantly higher when compared to that in AD and NC (all P values < .01). The AI-2 concentration along with the progression of CRC in both tissues and stools was significantly increased (P= .045，P= .0003, respectively). After AI-2 stimulation, TNFSF9 was the most significantly increased protein in macrophage cells (P < .01). TNFSF9 expression was significantly higher in CRC tissues when compared to NCs (P< .0001), which was mainly derived from macrophages in the tumor microenvironment. Moreover, AI-2 level was positively associated with CD3 + T cell numbers (P= .0462), and negatively associated with CD4/CD8 ratio (P= .0113) within CRC tissues. Conclusions: We demonstrated for the first time that AI-2 may serve as a novel marker for screening CRC in the clinic. AI-2 was associated with tumor immunity in CRCs through tumor-associated macrophages and CD4/CD8 ratio in a TNFSF9-dependent manner.

Role of tumor gene mutations in treatment response to immune checkpoint blockades

Early studies shed light on the immune suppression of immune checkpoint molecules in the cancer microenvironment, with later studies applying immune checkpoint blockade (ICB) in treatment of various malignancies. Despite the encouraging efficacy of ICBs in a substantial subset of cancer patients, the treatment response varies. Gene mutations of both tumor cells and immune cells in the tumor microenvironment have recently been identified as potential predictors of the ICB response. Recent developments in gene expression profiling of tumors have allowed identification of a panel of mutated genes that may affect tumor cell response to ICB treatment. In this review, we discuss the association of the ICB response with gene expression and mutation profiles in tumor cells, which it is hoped will help to optimize the clinical application of ICBs in cancer patients.

Classification of tumor microenvironment immune types based on immune response-associated gene expression

In 2014, the Shizuoka Cancer Center launched project High‑tech Omics‑based Patient Evaluation (HOPE), which features whole exome sequencing (WES) and gene expression profiling (GEP) of fresh surgical specimens from cancer patients. With the development of clinical trials of programmed death‑1 (PD‑1)/PD‑ligand 1 (PD‑L1) blockade, PD‑L1 expression and a high tumor mutation burden become possible biomarkers that could be used to predict immune responses. In this study, based on WES and GEP data from 1,734 tumors from the HOPE project, we established a tumor microenvironment (TME) immune‑type classification consisting of 4 types to evaluate the immunological status of cancer patients and analyze immunological pathways specific for immune types. Project HOPE was conducted in accordance with the Ethical Guidelines for Human Genome and Genetic Analysis Research with the approval of the Institutional Review Board. Based on the expression level of the PD‑L1 and CD8B genes, the immunological status was divided into 4 types as follows: A, PD‑L1+CD8B+; B, PD‑L1+CD8B‑; C, PD‑L1‑CD8B‑; and D, PD‑L1‑CD8B+. Type A, with PD‑L1+ and CD8B+, exhibited an upregulation of cytotoxic T lymphocyte (CTL) killing‑associated genes, T‑cell activation genes, antigen‑presentation and dendritic cell (DC) maturation genes, and T‑cell‑attracting chemokine genes, which promoted Th1 antitumor responses. By contrast, type C, with PD‑L1‑ and CD8B‑, exhibited a low expression of T‑cell‑activating genes and an upregulation of cancer driver gene signaling, which suggested an immune‑suppressive status. With regard to hypermutator tumors, PD‑L1+ hypermutator cases exhibited a specific upregulation of the IL6 gene compared with the PD‑L1‑ cases. On the whole, our data indicate that the classification of the TME immune types may prove to be a useful tool for evaluating the immunological status and predicting antitumor responses and prognosis.

Integrated analysis of gene expression and copy number identified potential cancer driver genes with amplification-dependent overexpression in 1,454 solid tumors

Identification of driver genes contributes to the understanding of cancer etiology and is imperative for the development of individualized therapies. Gene amplification is a major event in oncogenesis. Driver genes with tumor-specific amplification-dependent overexpression can be therapeutic targets. In this study, we aimed to identify amplification-dependent driver genes in 1,454 solid tumors, across more than 15 cancer types, by integrative analysis of gene expression and copy number. Amplification-dependent overexpression of 64 known driver oncogenes were found in 587 tumors (40%); genes frequently observed were MYC (25%) and MET (18%) in colorectal cancer; SKP2 (21%) in lung squamous cell carcinoma; HIST1H3B (19%) and MYCN (13%) in liver cancer; KIT (57%) in gastrointestinal stromal tumors; and FOXL2 (12%) in squamous cell carcinoma across tissues. Genomic aberrations in 138 known cancer driver genes and 491 established fusion genes were found in 1,127 tumors (78%). Further analyses of 820 cancer-related genes revealed 16 as potential driver genes, with amplification-dependent overexpression restricted to the remaining 22% of samples (327 tumors) initially undetermined genetic drivers. Among them, AXL, which encodes a receptor tyrosine kinase, was recurrently overexpressed and amplified in sarcomas. Our studies of amplification-dependent overexpression identified potential drug targets in individual tumors.