Landscape Of Tumor Immune Microenvironment Research Articles

Construction and Validation of a Reliable Disulfidptosis-Related LncRNAs Signature of the Subtype, Prognostic, and Immune Landscape in Colon Cancer.

Disulfidptosis, a novel form of regulated cell death (RCD) associated with metabolism, represents a promising intervention target in cancer therapy. While abnormal lncRNA expression is associated with colon cancer development, the prognostic potential and biological characteristics of disulfidptosis-related lncRNAs (DRLs) remain unclear. Consequently, the research aimed to discover a novel indication of DRLs with significant prognostic implications, and to investigate their possible molecular role in the advancement of colon cancer. Here, we acquired RNA-seq data, pertinent clinical data, and genomic mutations of colon adenocarcinoma (COAD) from the TCGA database, and then DRLs were determined through Pearson correlation analysis. A total of 434 COAD patients were divided in to three subgroups through clustering analysis based on DRLs. By utilizing univariate Cox regression, the least absolute shrinkage and selection operator (LASSO) algorithm, and multivariate Cox regression analysis, we ultimately created a prognostic model consisting of four DRLs (AC007728.3, AP003555.1, ATP2B1.AS1, and NSMCE1.DT), and an external database was used to validate the prognostic features of the risk model. According to the Kaplan-Meier curve analysis, patients in the low-risk group exhibited a considerably superior survival time in comparison to those in the high-risk group. Enrichment analysis revealed a significant association between metabolic processes and the genes that were differentially expressed in the high- and low-risk groups. Additionally, significant differences in the tumor immune microenvironment landscape were observed, specifically pertaining to immune cells, function, and checkpoints. High-risk patients exhibited a low likelihood of immune evasion, as indicated by the Tumor Immune Dysfunction and Exclusion (TIDE) analysis. Patients who exhibit both a high risk and high Tumor Mutational Burden (TMB) experience the least amount of time for survival, whereas those belonging to the low-risk and low-TMB category demonstrate the most favorable prognosis. In addition, the risk groups determined by the 4-DRLs signature displayed distinct drug sensitivities. Finally, we confirmed the levels of expression for four DRLs through rt-qPCR in both tissue samples from colon cancer patients and cell lines. Taken together, the first 4-DRLs-based signature we proposed may serve for a hopeful instrument for forecasting the prognosis, immune landscape, and therapeutic responses in colon cancer patients, thereby facilitating optimal clinical decision-making.

Identification and validation of pyroptosis-related gene landscape in prognosis and immunotherapy of ovarian cancer

BackgroundEmerging evidence has highlighted the biological significance of pyroptosis in tumor tumorigenesis and progression. Nonetheless, the potential roles of pyroptosis in tumor immune microenvironment and target therapy of ovarian cancer (OC) remain unknown.MethodsIn this study, with a series of bioinformatic and machine learning approaches, we comprehensively evaluated genetic alterations and transcriptome profiles of pyroptosis-associated genes (PYAGs) with TCGA-OV datasets. Consensus molecular clustering was performed to determine pyroptosis-associated clusters (PACs) and gene clusters in OC. Subsequently, component analysis algorithm (PCA) was employed to construct Pyrsig score and a highly accurate nomogram was established to evaluate its efficacy. Meanwhile, we systematically performed association analysis for these groups with prognosis, clinical features, TME cell-infiltrating characteristics, drug response and immunotherapeutic efficacy. Immunohistochemistry was conducted to verify molecular expression with clinical samples.ResultsThe somatic mutations and copy number variation (CNV) of 51 PYRGs in OC samples were clarified. Two distinct PACs (PAC1/2) and three gene clusters (A/B/C) were identified based on 1332 OC samples, PAC1 and gene cluster A were significantly associated with favorable overall survival (OS), clinicopathological features and TME cell-infiltrating characteristics. Subsequently, Pyrsig score was successfully established to demonstrate the prognostic value and immune characteristics of pyroptosis in OC, low Pyrsig score, characterized by activated immune cell infiltration, indicated prolonged OS, increased sensitivity of some chemotherapeutic drugs and enhanced efficacy of anti-PD-L1 immunotherapy, Consequently, a nomogram was successfully established to improve the clinical applicability and stability of Pyrsig score. With clinical OC samples, GSDMD and GZMB proteins were validated highly expressed in OC and associated with immune infiltration and Pyrsig score, GZMB and CD8 proteins were regarded as independent prognostic factors of OC.ConclusionThis work revealed pyroptosis played a non-negligible role in prognosis value, clinicopathological characteristics and tumor immune infiltration microenvironment in OC, which provided novel insights into identifying and characterizing landscape of tumor immune microenvironment, thereby guiding more effective prognostic evaluation and tailored immunotherapy strategies of OC.

Characterization of the Immune Microenvironmental Landscape of Lung Squamous Cell Carcinoma with Immune Cell Infiltration.

Increasing evidence supports that immune cell infiltration (ICI) patterns play a key role in the tumor progression of lung squamous cell carcinoma (LUSC). However, to date, the immune infiltration picture of LUSC has not been elucidated. TCGA was used to download multiomics data from LUSC samples. At the same time, we included two datasets on lung squamous cell carcinoma, GSE17710 and GSE157010. To reveal the landscape of tumor immune microenvironment (TIME), the ESTIMATE algorithm, ssGSEA approach, and CIBERSORT analysis are used. To quantify the ICI pattern in a single tumor, consistent clustering is used to determine the LUSC subtype based on the ICI pattern, and principal component analysis (PCA) is used to obtain the ICI score. The prognostic value of the Kaplan-Meier curves is confirmed. GSEA (Gene Set Enrichment Analysis) was used to perform functional annotation. To investigate the immunotherapeutic effects of the ICI score, the immunophenotyping score (IPS) is used. Finally, analyze the mutation data with the "maftools" R package. We identified four different immune infiltration patterns with different prognosis and biological characteristics in 792 LUSC samples. The identification of ICI patterns in individual tumors developed under ICI-related characteristic genes based on the ICI score helps to analyze the biological process, clinical results, immune cell infiltration, immunotherapy effects, and genetic variation. Immune failure is indicated by a high ICI score subtype marked by immunosuppression. Patients with low ICI scores have an abundance of efficient immune cells, which corresponds to the immunological activation phenotype and may have therapeutic benefits. The immunophenotypic score was used as a surrogate indicator of immunotherapy results, and samples with low ICI scores obtained significantly higher immunophenotypic scores. Finally, the relationship between the ICI score and tumor mutation burden (TMB) was proven. This study fully clarified the indispensable role of the ICI model in the complexity and diversity of TIME. The quantitative identification of ICI patterns in a single tumor will help draw the picture of TIME and further optimize precision immunotherapy.

High tumor hexokinase-2 expression promotes a pro-tumorigenic immune microenvironment by modulating CD8+/regulatory T-cell infiltration

BackgroundRelationship between cancer cell glycolysis and the landscape of tumor immune microenvironment in human cancers was investigated.MethodsForty-one fresh lung adenocarcinoma (ADC) tissues were analyzed using flow cytometry for comprehensive immunoprofiling. Formalin-fixed tissues were immunostained for hexokinase-2 (HK2) to assess cancer cell glycolysis. For validation, formalin-fixed tissues from 375 lung ADC, 118 lung squamous cell carcinoma (SqCC), 338 colon ADC, and 78 lung cancer patients treated with anti-PD-1/PD-L1 immunotherapy were immunostained for HK2, CD8, and FOXP3.ResultsBased on immunoprofiling of lung ADC, HK2 tumor expression was associated with the composition of lymphoid cells rather than myeloid cells. High HK2 tumor expression was associated with immunosuppressive/pro-tumorigenic features, especially decreased ratio of CD8 + T-cells to Tregs (rho = −0.415, P = 0.012). This correlation was also confirmed in four different cohorts including lung ADC and SqCC, colon ADC, and the immunotherapy cohort (rho = −0.175~-0.335, all P < 0.05). A low CD8 + T-cell to Treg ratio was associated with poor progression-free survival and overall survival in lung SqCC patients, and a shorter overall survival in the immunotherapy cohort (all, P < 0.05).ConclusionAn increase in HK2 expression may contribute to shaping the immunosuppressive/pro-tumorigenic tumor microenvironment by modulating the CD8 + T-cell to Treg ratio. Targeting tumor HK2 expression might be a potential strategy for enhancing anti-tumor immunity.

Prognosis and Dissection of Immunosuppressive Microenvironment in Breast Cancer Based on Fatty Acid Metabolism-Related Signature.

Fatty acid metabolism has been deciphered to augment tumorigenesis and disease progression in addition to therapy resistance via strengthened lipid synthesis, storage, and catabolism. Breast cancer is strongly associated with the biological function of fatty acid metabolism owing to the abundant presence of adipocytes in breast tissue. It has been unraveled that tumor cells exhibit considerable plasticity based on fatty acid metabolism, responding to extra-tumoral and a range of metabolic signals, in which tumor microenvironment plays a pivotal role. However, the prognostic significance of fatty acid metabolism in breast cancer remains to be further investigated. Alongside these insights, we retrieved 269 reliable fatty acid metabolism-related genes (FMGs) and identified the landscape of copy number variations and expression level among those genes. Additionally, 11 overall survival-related FMGs were clarified by univariate Cox hazards regression analysis in The Cancer Genome Atlas (TCGA) and the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) databases. Subsequently, a prognostic signature based on 6 overall survival (OS)-related FMGs was generated using Lasso Cox hazards regression analysis in TCGA dataset and was validated in two external cohorts. The correlation between the signature and several essential clinical parameters, including T, N, and PAM50 subtypes, was unveiled by comparing the accumulating signature value in various degrees. Furthermore, an optimal nomogram incorporating the signature, age, and American Joint Committee on Cancer (AJCC) stage was constructed, and the discrimination was verified by C-index, the calibration curve, and the decision curve analysis. The underlying implications for immune checkpoints inhibitors, the landscape of tumor immune microenvironment, and the predictive significance in therapy resistance to diverse strategies were depicted ultimately. In conclusion, our findings indicate the potential prognostic connotation of fatty acid metabolism in breast cancer, supporting novel insights into breast cancer patients’ prognosis and administrating effective immunotherapy.

N6-methyladenosine (m6A) RNA modification in tumor immunity.

Growing evidence supports that cancer progression is closely associated with the tumor microenvironment and immune evasion. Importantly, recent studies have revealed the crucial roles of epigenetic regulators in shaping the tumor microenvironment and restoring immune recognition. N6-methyladenosine (m6A) modification, the most prevalent epigenetic modification of mammalian mRNAs, has essential functions in regulating the processing and metabolism of its targeted RNAs, and therefore affects various biological processes including tumorigenesis and progression. Recent studies have demonstrated the critical functions and molecular mechanisms underlying abnormal m6A modification in the regulation of tumor immunity. In this review, we summarize recent research progress in the potential roles of m6A modification in tumor immunoregulation, with a special focus on the anti-tumor processes of immune cells and involvement in immune-associated molecules and pathways. Furthermore, we review current knowledge regarding the close correlation between m6A-related risk signatures and the tumor immune microenvironment landscape, and we discuss the prognostic value and therapeutic efficacy of m6A regulators in a variety of cancer types.

Low Density of CD3+ Tumor-Infiltrating Lymphocytes Is Predictive of a Poor Prognosis in Diffuse Large B-Cell Lymphoma Independently of MYC and BCL2 Double Expression Status: A Potential Utility of Immunoscore Based on Whole-Slide Image Analysis

Background: Anti-tumor immunity plays a key role in tumor development and progression and the landscape of tumor immune microenvironment could affect the clinical outcome of patients. The concept of immunoscore based on immune cell infiltration has been actively applied to solid tumors including colon cancer and malignant melanoma and successfully predicted prognosis of patients. However, a potential utility of immunoscore in predicting prognosis of patients with diffuse large B-cell lymphoma (DLBCL) remains unclear. For easy application of immunoscore to daily practice, we investigated the prognostic value of tumor-infiltrating CD3+ T-cell density which is routinely stained for diagnosing malignant lymphomas, and then explored the feasibility of immunoscore application in DLBCL.Method: One-hundred-four patients with DLBCL treated with R-CHOP therapy, whose tumors were prospectively immunoprofiled for routine clinical diagnosis, were enrolled in this study. Immunohistochemistry was performed on representative whole formalin-fixed paraffin-embedded tissue sections using CD3, CD20, MYC, BCL2, BCL6, CD10 and MUM1. Cell-of-origin was determined using the Hans' algorithm and MYC/BCL2 double expressor (DE) was defined as the co-expression of MYC (in ≥ 40% of tumor cells) and BCL2 (in ≥ 70% of tumor cells). Whole-slide scanning was performed, whole tumor regions were annotated, and images were analyzed with Aperio ImageScope v.12.4.3 software (Leica Biosystems, Nussloch, Germany). The CD3+ density was quantified in three different methods: the total numbers of CD3+ cells/area (mm 2), CD3+ cells/total cells and CD3+ cells/CD20+ cells. Correlation between the CD3 density and clinicopathologic parameters and prognostic impact of the CD3 density were analyzed. To validate the findings, publicly available mRNA and clinical datasets of two DLBCL cohorts were downloaded and analyzed (Schmitz et al. 2018 and Sha et al. 2019). To dichotomizing low versus high CD3 density cases, the optimal cut-off values for overall survival were determined by ROC curve analysis using MedCalc Software v 19.4 (MedCalc Software, Ostend, Belgium). Remaining all statistical analyses were performed using SPSS version 25.0 (SPSS).Result: All three methods assessing CD3+ cell density showed high concordance (CD3+ cells/area vs CD3+ cells/total cells, k=0.540 p=0.000; CD3+ cells/total cells vs CD3+ cells/CD20+ cells, k=0.394 p=0.000; CD3+ cells/CD20+ cells vs CD3+ cells/area, k=0.739 p=0.000). Patients with low CD3 density had elevated serum LDH (all, p<0.05) and tended to show poor clinical parameters including high Ann Arbor stage (III-IV), high international prognostic index (IPI, 3-5) and DE status. Patients with low CD3 density by all three methods had worse overall survival (OS) and progression free survival (PFS) (all, p<0.05). In univariate analysis, the following clinical variables were predictive of worse OS: Ann Arbor stage IV, Eastern Cooperative Oncology Group performance status (ECOG PS) ≥2, elevated serum LDH, IPI ≥3, DE and low CD3 density by all three methods. In multivariate analysis, low CD3 density by all methods predicted poor OS independent of the DE status, ECOG PS, LDH or Ann Arbor stage (all, p<0.05). Taken together, these findings suggested that evaluating CD3 density by any methods worked well as prognostic indicators and further might work well as immunoscoring methods in DLBCL. Potential utility of CD3+ cell density as an immunoscore observed in our cohort was validated using publicly available dataset generated by Schmitz et al. and Sha et al. In both validation cohorts, patients with low CD3E mRNA expression had elevated serum LDH (p<0.05) and in Sha et al. cohort, low CD3E mRNA expression was correlated with high ECOG PS, high IPI and DE status (p<0.05). Moreover, in both of Schmitz et al. and Sha et al. cohorts, patients with low CD3E mRNA expression tended to have worse PFS (p=0.067 and 0.002, respectively) and OS (both, p<0.05). In multivariate analysis, low CD3E mRNA predicted poor OS, independent of the IPI and DE status, in both validation cohorts.Conclusion: Low CD3 density was a poor prognostic factor in DLBCL independent of other poor prognostic parameters such as IPI score and DE status. Therefore, evaluating CD3 density might be suitable for immunoscoring DLBCL cases to predict prognosis. DisclosuresKim: Boryung: Consultancy, Membership on an entity's Board of Directors or advisory committees; BeyondBIO: Consultancy, Membership on an entity's Board of Directors or advisory committees; Hanmi: Consultancy, Membership on an entity's Board of Directors or advisory committees; AstraZeneca/MedImmune: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bayer: Consultancy, Membership on an entity's Board of Directors or advisory committees; AstraZeneca-KHIDI: Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; Sanofi: Consultancy, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees; GI CELL: Consultancy, Membership on an entity's Board of Directors or advisory committees; Roche/Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees.

MA03.07 Interferon-Gamma Mediated Immune Evasion: A Potential Mechanism of Resistance to Immunotherapy in Non-Small Cell Lung Cancer

Immunotherapy has unprecedentedly improved survival rates in patients with non-small cell lung cancer. Some patients with high tumor mutation burder, PD-1 and PD-L1 shows limited benefit from immunotherapy. Immune evasion described by immune contexture in tumor microenvironment could be potential mechanism of resistance to immunotherapy in non-small cell lung cancer. Data in our study were accessed from the Gene Expression Omnibus (GSE30219, GSE50081, GPL570) , The Cancer Genome Atlas (TCGA) and Immlnc database. Unsupervised hierarchical clustering was conducted to establish novel classification for NSCLC based on immune-related lncRNAs. Kaplan-Meier survival plots were utilized for survival analysis and overall survival (OS) estimation. Single sample gene set enrichment analysis and gene set variation analysis were performed to explore the landscape of tumor immune microenvironment. Gene instability and potential therapeutic effects were analyzed among three cohorts. The Tumor Immune Dysfunction and Exclusion (TIDE) algorithm mapping was applied to predict the therapeutic response to ICIs. Comparison of single nucleotide variation (SNV) and tumor mutational burden (TMB) among three identified clusters were performed through Kruskal-Wallis test. We found that cluster A had the best prognosis by Kaplan-Meier analysis, followed by cluster B and cluster C significantly (p=0.0048). With a favorable prognosis, cluster A was marked by distinct infiltration of activated B cell, activated dendritic cell, activated CD8 T cell, central memory CD4 T cell, presented as immune-inflammed phenotype. However, in cluster B, the infiltration density of plasma cells, M1 and M2 macrophages, CD8 T cells, gamma delta T cells, myeloid-derived suppressor cells and memory CD4 T cells infiltration was significantly high as well, corresponding to immune-evaded phenotype. Cluster C had the lowest existence of immune infiltrating lymphocytes, correlated with immune-desert phenotype. Tumor mutation burden in cluster B was highest (p < 0.001), while lowest in the cluster A. We subsequently investigated the expression of crucial immune checkpoints among three clusters, such as PD-1, CTLA-4, CD28, and TNFRSF14, that higher expression of immune checkpoint molecules was observed highest in cluster A, followed with cluster B (p < 0.001).With respect to predicted response to immunotherapy, cluster B had the higher tumor immune dysfunction and exclusion score and lower predicted responders than cluster A (p<0.001). Cluster B had high mutation of KEAP1, LRRC7, PAPPA2, ABCA13, APOB, MUC17, NRXN1, DNAH9, SORCS1 and ZNF804A. The hub genes analyzed by Cytoscape software and String database in cluster B were STAT1, PARP9, TRIM21, OAS3. To explore potential mechanisms, activation of interferon−gamma and MHC class I signaling pathways could be detected in cluster B by Gene Ontology functional annotation analysis. In conclusion, we established a novel prognostic classification for NSCLC corresponding with classic immune inflammation, immune evasion and immune desert phenotypes, which describe tumor features in terms of immune contexture, genomic characteristics, and immune checkpoints, targeting the tumor immune microenvironment comprehensively rather than immune checkpoint and TMB alone. Our result suggested interferon-gamma mediated immune evasion could be a potential mechanism of therapeutic resistance to immunotherapy in non-small cell lung cancer.

Tumor Immune Microenvironment Landscape in Glioma Identifies a Prognostic and Immunotherapeutic Signature.

The tumor immune microenvironment (TIME) has been recognized to be associated with sensitivity to immunotherapy and patient prognosis. Recent research demonstrates that assessing the TIME patterns on large-scale samples will expand insights into TIME and will provide guidance to formulate immunotherapy strategies for tumors. However, until now, thorough research has not yet been reported on the immune infiltration landscape of glioma. Herein, the CIBERSORT algorithm was used to unveil the TIME landscape of 1,975 glioma observations. Three TIME subtypes were established, and the TIMEscore was calculated by least absolute shrinkage and selection operator (LASSO)–Cox analysis. The high TIMEscore was distinguished by an elevated tumor mutation burden (TMB) and activation of immune-related biological process, such as IL6-JAK-STAT3 signaling and interferon gamma (IFN-γ) response, which may demonstrate that the patients with high TIMEscore were more sensitive to immunotherapy. Multivariate analysis revealed that the TIMEscore could strongly and independently predict the prognosis of gliomas [Chinese Glioma Genome Atlas (CGGA) cohort: hazard ratio (HR): 2.134, p < 0.001; Gravendeel cohort: HR: 1.872, p < 0.001; Kamoun cohort: HR: 1.705, p < 0.001; The Cancer Genome Atlas (TCGA) cohort: HR: 2.033, p < 0.001; the combined cohort: HR: 1.626, p < 0.001], and survival advantage was evident among those who received chemotherapy. Finally, we validated the performance of the signature in human tissues from Wuhan University (WHU) dataset (HR: 15.090, p = 0.008). Our research suggested that the TIMEscore could be applied as an effective predictor for adjuvant therapy and prognosis assessment.

Landscape of Prognostic m6A RNA Methylation Regulators in Hepatocellular Carcinoma to Aid Immunotherapy.

Background: Hepatocellular carcinoma (HCC) is the sixth most common malignancy with a high mortality worldwide. N6-methyladenosine (m6A) may participate extensively in tumor progression.Methods: To reveal the landscape of tumor immune microenvironment (TIME), ESTIMATE analysis, ssGSEA algorithm, and the CIBERSORT method were used. Taking advantage of consensus clustering, two different HCC categories were screened. We analyzed the correlation of clustering results with TIME and immunotherapy. Then, we yielded a risk signature by systematical bioinformatics analyses. Immunophenoscore (IPS) was implemented to estimate the immunotherapeutic significance of risk signature.Results: The m6A-based clusters were significantly correlated with overall survival (OS), immune score, immunological signature, immune infiltrating, and ICB-associated genes. Risk signature possessed robust prognostic validity and significantly correlated with TIME context. IPS was employed as a surrogate of immunotherapeutic outcome, and patients with low-risk scores showed significantly higher immunophenoscores.Conclusion: Collectively, m6A-based clustering subtype and signature was a robust prognostic indicator and correlated with TIME and immunotherapy, providing novel insight into antitumor management and prognostic prediction in HCC.

Clinical Significance and Inflammatory Landscape of aNovel Recurrence-Associated Immune Signature in Stage II/III Colorectal Cancer.

BackgroundA considerable number of patients with stage II/III colorectal cancer (CRC) will relapse within 5 years after surgery, which is a leading cause of death in early-stage CRC. The current TNM stage system is limited due to the heterogeneous clinical outcomes displayed in patients of same stage. Therefore, searching for a novel tool to identify patients at high recurrence-risk for improving post-operative individual management is an urgent need.MethodsUsing four independent public cohorts and qRT-PCR data from 66 tissues, we developed and validated a recurrence-associated immune signature (RAIS) based on global immune genes. The clinical and molecular features, tumor immune microenvironment landscape, and immune checkpoints profiles of RAIS were also investigated.ResultsIn five independent cohorts, this novel scoring system was proven to be an independent recurrent factor and displayed excellent discrimination and calibration in predicting the recurrence-risk at 1~5 years. Further analysis revealed that the high-risk group displayed high mutation rate of TP53, while the low-risk group had more abundance of activated CD4+/CD8+ T cells and high expression of PD-1/PD-L1.ConclusionsThe RAIS model is highly predictive of recurrence in patients with stage II/III CRC, which might serve as a powerful tool to further optimize decision-making in adjuvant chemotherapy and immunotherapy, as well as tailor surveillance protocol for individual patients.

Hyperion Image Analysis Depicts a Preliminary Landscape of Tumor Immune Microenvironment in OSCC with Lymph Node Metastasis.

Background Oral squamous cell carcinoma (OSCC) constitutes the most common types of oral cancer. Because its prognosis varies significantly, identification of a tumor immune microenvironment could be a critical tool for treatment planning and predicting a more accurate prognosis. This study is aimed at utilizing the Hyperion imaging system to depict a preliminary landscape of the tumor immune microenvironment in OSCC with lymph node metastasis. Methods We collected neoplasm samples from OSCC patients. Their formalin-fixed, paraffin-embedded (FFPE) tissue sections were obtained and stained utilizing a panel of 26 clinically relevant metal-conjugated antibodies. Detection and analysis were performed for these stained cells with the Hyperion imaging system. Results Four patients met our inclusion criteria. We depicted a preliminary landscape of their tumor immune microenvironment and identified 25 distinct immune cell subsets from these OSCC patients based on phenotypic similarity. All these patients had decreased expression of CD8+ T cells in tumor specimens. Variety in cell subsets was seen, and more immune activated cells were found in patient A and patient B than those in patient C and patient D. Such differences in tumor immune microenvironments can contribute to forecasting of individual prognoses. Conclusion The Hyperion imaging system helped to delineate a preliminary and multidimensional landscape of the tumor immune microenvironment in OSCC with lymph node metastasis and provided insights into the influence of the immune microenvironment in determination of prognoses. These results reveal possible contributory factors behind different prognoses of OSCC patients with lymph node metastasis and provide reference for individual treatment planning.

P72.02 Cellular Landscape of Tumor Immune Microenvironment and Genetic Signatures Identify Prognostic of LUAD

Tumour microenvironment (TME) has been recognized to support the initiation and progression of lung adenocarcinoma (LUAD). The innate and adaptive immune cells in the lung TME harbour both tumour-promoting and tumour-suppressing activities, which may also predict clinical outcome. Therefore we carried out a systematic analysis of cellular interactions in tumor immune microenvironment. And identify cell-intrinsic and cell-extrinsic pathways cell types and activation states that may serve as biomarkers of overall survival (OS). Public gene-expression data and relevant clinical annotation were obtained from Gene-Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) database. Three TME infiltration patterns were comprehensively analyzed in 442 LUAD patients using CIBERSORT algorithm and the LM22 gene signature. Based on the TME patterns, we build a model to calculate TMEscore based on gene set variation analysis via ssGSEA algorithm. Functional enrichment analysis were performed by GO and KEGG. Four datasets with available outcome data and clinical information in GEO and TCGA-LUAD were enrolled in our study. GSE72094 was used as the training cohort, while GSE11969, GSE26939, GSE31210 and TCGA-LUAD was used as validation cohorts. TME cell network established based on GSE72094 depicted a comprehensive landscape of tumor-immune cell interactions, cell lineages, and their correlation with OS (Fig. 1A, 1B). Three subgroups with distinct TME signature gene sets were obtained/identified based on unsupervised hierarchical clustering in 442 LUAD cases. OS in TME gene subgroup B was significantly longer than which in TME gene subgroup A and subgroup C. TME gene group B was associated immune activation (Fig. 1C). TMEscore was further constructed using principal component analysis algorithms. Lower TMEscore is significantly associated with better prognosis. Functional annotation analysis showed TMEscore had a positive correlation with cell cycle, DNA replication, homologous recombination, mismatch repair, nucleotide excision repair and DNA damage repair (Fig. 1D). The enriched pathways in subtype with lowest/low TMEscore involved bile_acid_metabolism, fatty_acid_metabolism and myogenesis. While high TMEscore subtype was characterized by significant enrichment of interferon_alpha_response, myc_targets and unfolded_protein_response pathway (Fig. 1E). TMEscore model was then validated on 525 patients from GEO datasets and 585 patients from TCGA-LUAD project and proved to be a valuable method for prognostic stratification of LUAD except for TNM stage (Fig. 1F). Variability in the composition of the tumor immune microenvironment contributes to heterogeneity in OS. Deeper validation is in need to define the positive association between lower TMEscore and longer OS.

Identification and validation of a novel redox-related lncRNA prognostic signature in lung adenocarcinoma

ABSTRACT Lung adenocarcinoma (LUAD) is one of the main causes of cancer deaths globally. Redox is emerging as a crucial contributor to the pathophysiology of LUAD, which can be regulated by long non-coding RNAs (lncRNAs). The aim of our research is to identify a novel redox-related lncRNA prognostic signature (redox-LPS) for better prediction of LUAD prognosis. 535 LUAD samples from The Cancer Genome Atlas (TCGA) database and 226 LUAD samples from the Gene Expression Omnibus (GEO) database were included in our study. 67 redox genes and 313 redox-related lncRNAs were identified. After performing LASSO-Cox regression analysis, a redox-LPS consisting of four lncRNAs (i.e., CRNDE, CASC15, LINC01137, and CYP1B1-AS1) was developed and validated. Our redox-LPS was superior to another three established models in predicting survival probability of LUAD patients. Univariate and multivariate Cox regression analysis revealed that risk score and stage were independent prognostic indicators. A nomogram plot including risk score and stage was constructed to predict survival probability of LUAD patients; this was further verified by calibration curves. Functional enrichment analysis and gene set enrichment analysis, were performed to determine the differences in cellular processes and signaling pathways between the high – and low-risk subgroups. A variety of algorithms (such as single-sample gene set enrichment analysis and CIBERSOFT) were conducted to uncover the landscape of tumor immune microenvironment in the high- and low-risk subgroups. In conclusion, a novel independent redox-LPS was constructed and validated for LUAD patients, which might provide new insights for clinical decision-making and precision medicine.

Transcriptional characterization of microenvironment and their prediction role for the prognosis of hepatocellular carcinoma after surgery.

e15650 Background: Hepatocellular carcinoma (HCC) is one of the most common prevalent fatal cancers worldwide with poor prognosis due to high incidence of recurrence. For patients with HCC, surgical treatment is a potentially cutative therapy. However, the puzzle in the therapy was the rapid recurrence after surgery. The purpose of this study was to integrate the impact of different immune context present in HCC microenvironment on patients’ prognosis, provide the molecular prediction clue of HCC recurrence. Methods: RNA targeted sequencing was performed on 12 primary tumor specimens from HCC patients. Transcripts of 395 immune related genes expressed in FFPE tumor samples were analyzed. The lima package was used to analyze the different expressed genes (DEGs) between patients with different prognosis. The gene set variance analysis (GSVA) analysis was performed to explore gene sets enrichment related to the recurrence post-resection. Results: 15 DEGs were detected in tissue samples between the two groups (group A: patients who relapsed within one year after surgery; group B: patients who hadn't relapsed beyond two years after surgery). The Antigen processing pathway enrichment may associate with the favorable prognosis (p &lt; 0.05). HLA-A gene expression in group A was lower than that in group B; The gene expression of IL23A, TP63, ALOX15B, BUB1, CXCR2, CCL20, CLEC4C, PTK7, MPO, IL1B, MMP9, GAGE2C, GAGE2A, GAGE2E, DMBT1, FOXM1 in group A was higher than that in group B. Additionally, the combination of 3 genes (TP63, IL23A and BUB1) can distinguish the patients recurrent within 1 year or beyond 2 years post-resection. The joint diagnostic equation is logit (Y = 1) = 0.073 +0.740 *(TP63) + 0.589 * (IL23A)+0.959(BUB1), (Optimal threshold: 0.667, specificity: 1, sensitivity: 0.833). Conclusions: Our results suggest that RNA-seq of immune related genes from FFPE sample can effectively profile the specific landscape of tumor immune microenvironment and predict the survival of HCC. 3 genes’ expression (TP63, IL23A and BUB1) might correlate with recurrence in HCC patients after surgery.

Transcriptional characterization of immune microenvironment and their prediction role for the prognosis of local advanced lung adenocarcinoma.

e20625 Background: The resection of early stage NSCLC offers patients the best hope of a cure. However, the recurrence rate post-resection remains high. As the mechanisms involved in the process is still not clear due to the unavailability of accurate targets, our study was aimed to integrate the impact of different immune context present in lung adenocarcinoma (LUAD) microenvironment on patients’ prognosis. Methods: RNA targeted sequencing was performed on 24 primary tumor specimens from the resected local advanced LUADs . Transcripts of 395 immune related genes expressed in FFPE tumor samples were analyzed. The limma package was used to analyze the different expressed genes (DEGs) between patients with different prognosis. The gene set variance analysis (GSVA) analysis was performed to explore gene sets enrichment related to the prognosis (PFS, progression free survival) post-resection. Results: 23 DEGs were detected in primary tumor between the better (PFS &gt; 18months, n = 12 ) and worse (PFS≤18months, n = 12 ) prognosis group. The combined prediction model containing MPO, IL-6, CXCR2, FCGR3B, ADGRE5 could identify the favorable prognosis of patients. GSVA and Log Rank test of survival data demonstrated that the antigen processing and lymphocyte activation pathway enrichment may associate with better prognosis (p = 0.01), whereas higher Neutrophils cell infiltration in primary tumor demonstrated a shorter PFS (p = 0.008). Conclusions: In LUAD, the immune related genes such as MPO, IL-6, CXCR2, FCGR3B, ADGRE5, can effectively profile the landscape of tumor immune microenvironment and predict the survival in early stage of lung adenocarcinoma. Accordingly immune pathways were correlated with prognosis of these patients. Our findings suggest that immune-related RNA expression pattern in locally advanced LUAD may provide a potential predictive marker for early recurrence after surgical resection.