Prognostic Impact of Tumor Cell Programmed Death Ligand 1 Expression and Immune Cell Infiltration in NSCLC

Pan-cell death-related signature reveals tumor immune microenvironment and optimizes personalized therapy alternations in lung adenocarcinoma

This study constructed a comprehensive analysis of cell death modules in eliminating aberrant cells and remodeling tumor microenvironment (TME). Consensus analysis was performed in 490 lung adenocarcinoma (LUAD) patients based on 4 types of cell death prognostic genes. Intersection method divided these LUAD samples into 5 cell death risk (CDR) clusters, and COX regression analysis were used to construct the CDR signature (CDRSig) with risk scores. Significant differences of TME phenotypes, clinical factors, genome variations, radiosensitivity and immunotherapy sensitivity were observed in different CDR clusters. Patients with higher risk scores in the CDRSig tended to be immune-excluded or immune-desert, and those with lower risk scores were more sensitive to radiotherapy and immunotherapy. The results from mouse model showed that intense expression of the high-risk gene PFKP was associated with low CD8+ T cell infiltration upon radiotherapy and anti-PD-L1 treatment. Deficient assays in vitro confirmed that PFKP downregulation enhanced cGAS/STING pathway activation and radiosensitivity in LUAD cells. In conclusion, our studies originally performed a comprehensive cell death analysis, suggesting the importance of CDR patterns in reprogramming TME and providing novel clues for LUAD personalized therapies.

Density of tumor-infiltrating NK and Treg cells is associated with 5 years progression-free and overall survival in resected lung adenocarcinoma

Surgical resection of pulmonary adenocarcinoma is considered to be curative but progression-free survival (PFS) has remained highly variable. Antitumor immune response may be important, however, the prognostic significance of tumor-infiltrating natural killer (NK) and regulatory T (Treg) lymphocytes is uncertain. Resected pulmonary adenocarcinoma tissues (n = 115) were studied by immunohistochemical detection of NKp46 and FoxP3 positivity to identify NK and Treg cells, respectively. Association of cell densities with clinicopathological features and progression-free survival (PFS) as well as overall survival (OS) were analyzed with a follow-up time of 60 months. Both types of immune cells were accumulated predominantly in tumor stroma. NK cell density showed association with female gender, non-smoking and KRAS wild-type status. According to Kaplan-Meier analysis, PFS and OS proved to be longer in patients with high NK or Treg cell densities (p = 0.0293 and p = 0.0375 for PFS, p = 0.0310 and p = 0.0448 for OS, respectively). Evaluating the prognostic effect of the combination of NK and Treg cell density values revealed that PFS and OS were significantly longer in NKhigh/Treghigh cases compared to the other groups combined (p = 0.0223 and p = 0.0325, respectively). Multivariate Cox regression analysis indicated that high NK cell density was independent predictor of longer PFS while high NK and high Treg cell densities both proved significant predictors of longer OS. The NKhigh/Treghigh combination also proved to be an independent prognostic factor for both PFS and OS. In conclusion, NK and Treg cells can be components of the innate and adaptive immune response at action against progression of pulmonary adenocarcinoma.

The germline HLA-A02B62 supertype is associated with a PD-L1-positive tumour immune microenvironment and poor prognosis in stage I lung cancer

Background

Germline HLA class I molecule supertypes are shown to correlate with response to anti-PD-1 therapy. Here, we investigate the significance of germline HLA-A and HLA-B supertypes in tumour microenvironment of non-small-cell lung cancer.

Methods

Totally 278 NSCLC patients were collected retrospectively. HLA genotyping was conducted using next-generation sequencing. The evaluation of tumour-infiltrating lymphocytes was performed by multiplex immunohistochemistry assay. Correlations among HLA supertypes, tumour infiltrating lymphocytes, and clinicopathological characteristics were assessed.

Results

HLA-A03 and HLA-B62 were the supertypes with the highest proportions, at 69.1% and 52.2%, respectively. HLA-A02 or HLA-B62, but not HLA-A03, associated with higher PD-L1+ tumour and stromal cells levels, CD68+ cells, and CD68+PD-L1+ cells. Patients with both HLA-A02 and HLA-B62 supertypes displayed significantly higher PD-L1+ cells, CD68+ cells, and CD8+ cells levels than patients with other supertypes (P = 0.0301, P = 0.0479, P = 0.0192). These cells collectively constitute a hot but immunosuppressive tumour microenvironment. Accordingly, patients with both HLA-A02 and HLA-B62 supertypes had short progression-free survival after surgery (HR = 2.27, P = 0.0373).

Conclusions

The HLA-A02B62 supertype could serve as a possible indicator of poor prognosis in early-stage lung cancer. However, it may also act as a favorable prognostic factor for immunotherapy, given its association with a PD-L1-positive tumour microenvironment.

Study on the role and pharmacology of cuproptosis in gastric cancer

Objective

Gastric cancer has a poor prognosis and high mortality. Cuproptosis, a novel programmed cell death, is rarely studied in gastric cancer. Studying the mechanism of cuproptosis in gastric cancer is conducive to the development of new drugs, improving the prognosis of patients and reducing the burden of disease.

Methods

The TCGA database was used to obtain transcriptome data from gastric cancer tissues and adjacent tissues. GSE66229 was used for external verification. Overlapping genes were obtained by crossing the genes obtained by differential analysis with those related to copper death. Eight characteristic genes were obtained by three dimensionality reduction methods: lasso, SVM, and random forest. ROC and nomogram were used to estimate the diagnostic efficacy of characteristic genes. The CIBERSORT method was used to assess immune infiltration. ConsensusClusterPlus was used for subtype classification. Discovery Studio software conducts molecular docking between drugs and target proteins.

Results

We have established the early diagnosis model of eight characteristic genes (ENTPD3, PDZD4, CNN1, GTPBP4, FPGS, UTP25, CENPW, and FAM111A) for gastric cancer. The results are validated by internal and external data, and the predictive power is good. The subtype classification and immune type analysis of gastric cancer samples were performed based on the consensus clustering method. We identified C2 as an immune subtype and C1 as a non-immune subtype. Small molecule drug targeting based on genes associated with cuproptosis predicts potential therapeutics for gastric cancer. Molecular docking revealed multiple forces between Dasatinib and CNN1.

Conclusion

The candidate drug Dasatinib may be effective in treating gastric cancer by affecting the expression of the cuproptosis signature gene.

Expression of p53 and Rb reveal subtypes of gastric neuroendocrine carcinoma with distinct prognosis

Gastric neuroendocrine carcinoma (NEC) is a rare tumor with a poor prognosis. Due to its rarity and disparity in prevalence across populations, there is limited data on gastric NEC. TP53 and RB1 genetic alterations or expression were reported for predictive value in neuroendocrine neoplasm and classification in pulmonary large cell NEC. This study investigated the genetic alteration and protein expression of TP53 and RB1 in gastric NEC. Thirty-nine patients were categorized as type A and B subtypes by p53 and Rb expression. Patients with concurrent abnormal p53 and Rb expression were defined as the type A group, and the remainder were defined as the type B group. Significant differences in TNM stages, tumor size, and lymph node metastasis were observed between the two subtypes. Type A characteristic is an independent predictor for worse overall survival (HR: 3.27; 95% CI: 1.12-9.58; p = .022). We further evaluated and compared immunotherapy-related markers, including PD-L1 expression, CD8 T cell infiltration, tumor mutation burden, and microsatellite instability in these two subtypes, whereas no significant differences were detected.

Spatial immunophenotyping of the tumour microenvironment in non-small cell lung cancer

INTRODUCTION

Immune cells in the tumour microenvironment are associated with prognosis and response to therapy. We aimed to comprehensively characterise the spatial immune phenotypes in the mutational and clinicopathological background of non-small cell lung cancer (NSCLC).

METHODS

We established a multiplexed fluorescence imaging pipeline to spatially quantify 13 immune cell subsets in 359 NSCLC cases: CD4 effector cells (CD4-Eff), CD4 regulatory cells (CD4-Treg), CD8 effector cells (CD8-Eff), CD8 regulatory cells (CD8-Treg), B-cells, natural killer cells, natural killer T-cells, M1 macrophages (M1), CD163+ myeloid cells (CD163), M2 macrophages (M2), immature dendritic cells (iDCs), mature dendritic cells (mDCs) and plasmacytoid dendritic cells (pDCs).

RESULTS

CD4-Eff cells, CD8-Eff cells and M1 macrophages were the most abundant immune cells invading the tumour cell compartment and indicated a patient group with a favourable prognosis in the cluster analysis. Likewise, single densities of lymphocytic subsets (CD4-Eff, CD4-Treg, CD8-Treg, B-cells and pDCs) were independently associated with longer survival. However, when these immune cells were located close to CD8-Treg cells, the favourable impact was attenuated. In the multivariable Cox regression model, including cell densities and distances, the densities of M1 and CD163 cells and distances between cells (CD8-Treg-B-cells, CD8-Eff-cancer cells and B-cells-CD4-Treg) demonstrated positive prognostic impact, whereas short M2-M1 distances were prognostically unfavourable.

CONCLUSION

We present a unique spatial profile of the in situ immune cell landscape in NSCLC as a publicly available data set. Cell densities and cell distances contribute independently to prognostic information on clinical outcomes, suggesting that spatial information is crucial for diagnostic use.

Exploring the role of sphingolipid-related genes in clinical outcomes of breast cancer

Background

Despite tremendous advances in cancer research, breast cancer (BC) remains a major health concern and is the most common cancer affecting women worldwide. Breast cancer is a highly heterogeneous cancer with potentially aggressive and complex biology, and precision treatment for specific subtypes may improve survival in breast cancer patients. Sphingolipids are important components of lipids that play a key role in the growth and death of tumor cells and are increasingly the subject of new anti-cancer therapies. Key enzymes and intermediates of sphingolipid metabolism (SM) play an important role in regulating tumor cells and further influencing clinical prognosis.

Methods

We downloaded BC data from the TCGA database and GEO database, on which we performed in depth single-cell sequencing analysis (scRNA-seq), weighted co-expression network analysis, and transcriptome differential expression analysis. Then seven sphingolipid-related genes (SRGs) were identified using Cox regression, least absolute shrinkage, and selection operator (Lasso) regression analysis to construct a prognostic model for BC patients. Finally, the expression and function of the key gene PGK1 in the model were verified by in vitro experiments.

Results

This prognostic model allows for the classification of BC patients into high-risk and low-risk groups, with a statistically significant difference in survival time between the two groups. The model is also able to show high prediction accuracy in both internal and external validation sets. After further analysis of the immune microenvironment and immunotherapy, it was found that this risk grouping could be used as a guide for the immunotherapy of BC. The proliferation, migration, and invasive ability of MDA-MB-231 and MCF-7 cell lines were dramatically reduced after knocking down the key gene PGK1 in the model through cellular experiments.

Conclusion

This study suggests that prognostic features based on genes related to SM are associated with clinical outcomes, tumor progression, and immune alterations in BC patients. Our findings may provide insights for the development of new strategies for early intervention and prognostic prediction in BC.

The role of spatial interplay patterns between PD-L1-positive tumor cell and T cell in recurrence of locally advanced non-small cell lung cancer

PURPOSE

To explore the relationship between the spatial interaction of programmed death-ligand 1(PD-L1)-positive tumor cell and T cell with specific functions and the recurrence of non-small cell lung cancer (NSCLC) and optimize prognostic stratification.

MATERIALS AND METHODS

This study retrospectively included 104 patients with locally advanced NSCLC who underwent radical surgery. Tissue microarrays were constructed including tumor center (TC) and invasion margin (IM), and CK/CD4/CD8/PD-L1/programmed death-1 (PD-1) was labeled using multiplex immunofluorescence to decipher the counts and spatial distribution of tumor cells and T cells. The immune microenvironment and recurrence stratification were characterized using the Mann-Whitney U test and Cox proportional hazards model.

RESULT

Compared with the IM, the proportion of tumor cells (especially PD-L1⁺) was increased in the TC, while T cells (especially PD-1⁺) were decreased. An increase in TC PD-1⁺ CD8 T cells promoted relapse (HR = 2.183), while PD-L1⁺ tumor cells alone or in combination with T cells had no predictive value for relapse. In addition, in both TC and IM, CD8 were on average closer to PD-L1⁺ tumor cells than CD4, especially exhausted CD8. The effective density and percentage of PD-1⁺ CD4 T cells interacting with PD-L1⁺ tumor cells in the IM were both associated with recurrence, and the HRs increased sequentially (HRs were 2.809 and 4.063, respectively). Patients with low PD-1⁺CD4 count combined high PD-1⁺CD4 effective density showed significantly poorer RFS compared to those with high PD-1⁺CD4 count combined low PD-1⁺CD4 effective density, in both the TC and IM regions (HRs were 5.810 and 8.709, respectively).

CONCLUSION

Assessing the relative spatial proximity of PD-1/PD-L1 contributes to a deeper understanding of tumor immune escape and generates prognostic information in locally advanced NSCLC patients.

Fibroblast subsets in non-small cell lung cancer: Associations with survival, mutations, and immune features

BACKGROUND

Cancer-associated fibroblasts (CAFs) are molecularly heterogeneous mesenchymal cells that interact with malignant cells and immune cells and confer anti- and protumorigenic functions. Prior in situ profiling studies of human CAFs have largely relied on scoring single markers, thus presenting a limited view of their molecular complexity. Our objective was to study the complex spatial tumor microenvironment of non-small cell lung cancer (NSCLC) with multiple CAF biomarkers, identify novel CAF subsets, and explore their associations with patient outcome.

METHODS

Multiplex fluorescence immunohistochemistry was employed to spatially profile the CAF landscape in 2 population-based NSCLC cohorts (n = 636) using antibodies against 4 fibroblast markers: platelet-derived growth factor receptor-alpha (PDGFRA) and -beta (PDGFRB), fibroblast activation protein (FAP), and alpha-smooth muscle actin (αSMA). The CAF subsets were analyzed for their correlations with mutations, immune characteristics, and clinical variables as well as overall survival.

RESULTS

Two CAF subsets, CAF7 (PDGFRA-/PDGFRB+/FAP+/αSMA+) and CAF13 (PDGFRA+/PDGFRB+/FAP-/αSMA+), showed statistically significant but opposite associations with tumor histology, driver mutations (tumor protein p53 [TP53] and epidermal growth factor receptor [EGFR]), immune features (programmed death-ligand 1 and CD163), and prognosis. In patients with early stage tumors (pathological tumor-node-metastasis IA-IB), CAF7 and CAF13 acted as independent prognostic factors.

CONCLUSIONS

Multimarker-defined CAF subsets were identified through high-content spatial profiling. The robust associations of CAFs with driver mutations, immune features, and outcome suggest CAFs as essential factors in NSCLC progression and warrant further studies to explore their potential as biomarkers or therapeutic targets. This study also highlights multiplex fluorescence immunohistochemistry-based CAF profiling as a powerful tool for the discovery of clinically relevant CAF subsets.

Functional status and spatial interaction of T cell subsets driven by specific tumor microenvironment correlate with recurrence of non-small cell lung cancer

Background

The anti-tumoral or pro-tumoral roles of CD4+ and CD8+ T cells typify the complexity of T cell subsets function in cancer. In the non-small cell lung cancer (NSCLC), the density and topology of distinct T cell phenotypes at the tumor center (TC) versus the invasive margin (IM) are largely unknown. Here, we investigated T cell subsets density and distribution within TC and IM regions in NSCLC and its impact on the prognosis.

Methods

We performed multiplex immunofluorescence using a tissue microarray of samples from 99 patients with locally advanced NSCLC to elucidate the distributions of tumor cell, T cell subpopulations (CD4/conventional CD4/regulatory CD4/CD8/cytotoxic CD8/pre-dysfunctional CD8/dysfunctional CD8), microvessel density (MVD), cancer-associated fibroblasts (CAFs) and hypoxia-inducible factor-1α (HIF-1α) in TC and IM tissues. Cell-to-cell nearest neighbor distances and interactions were analyzed using the phenoptrreports R package. Cox regression was used to evaluate the associations between T cell subsets density and proximity to tumor cells and recurrence-free survival (RFS). Correlations between different cell subsets were examined by Spearman's or Kruskal-Wallis tests.

Results

In the locally advanced NSCLC, the proportion of tumor cells and CAFs in IM is lower than in the TC, while MVD, CD4+, and CD8+ T lymphocytes were increased, and tumor cells were closer to T lymphocytes and their subsets. The density and proximity of CD4+ and CD8+ T cells in the TC and IM regions were not associated with RFS, but in the IM area, increased density of dysfunctional CD8 and closer regulatory CD4 to tumor cells were independent risk factors for recurrence (HR were 3.536 and 2.884, respectively), and were positively correlated with HIF-1α+CD8 (r = 0.41, P = 0.000) and CAFs (P = 0.017), respectively.s.

Conclusions

In locally advanced NSCLC, the functional status of T cells in the IM region is closely related to recurrence. The density of dysfunctional CD8 and the proximity of regulatory CD4 to tumor cells were independent risk factors for recurrence, and are positively correlated with the hypoxia response of CD8+ T cells and CAFs. Targeting hypoxia or CAFs is expected to further sensitize therapy.

The prognostic impact of tumor-infiltrating B lymphocytes in patients with solid malignancies: A systematic review and meta-analysis

This study reviewed the prognostic effect of tumor-infiltrating B lymphocytes (TIBLs) on solid malignancies, to determine the potential role of TIBLs in predicting cancer patient's prognosis and their response to immunotherapy. A total of 45 original papers involving 11,099 individual patients were included in this meta-analysis covering 7 kinds of cancer. The pooled results suggested that high levels of TIBLs were correlated with favorable OS in lung, esophageal, gastric, colorectal, liver, and breast cancer; improved RFS in lung cancer; and improved DFS in gastrointestinal neoplasms. Additionally, TIBLs were significantly correlated with negative lymphatic invasion in gastric cancer, small tumor size in hepatocellular carcinoma, and negative distant metastasis in colorectal cancer. Additionally, TIBLs were reported as a discriminative feature of patients treated with immunotherapy with improved survival. We concluded that TIBLs play a favorable prognostic role among the common solid malignancie, providing theoretical evidence for further prognosis prediction for solid tumors.

A novel risk model construction and immune landscape analysis of gastric cancer based on cuproptosis-related long noncoding RNAs

Recent studies have identified cuproptosis, a new mechanism of regulating cell death. Accumulating evidence suggests that copper homeostasis is associated with tumorigenesis and tumor progression, however, the clinical significance of cuproptosis in gastric cancer (GC) is unclear. In this study, we obtained 26 prognostic cuproptosis-related lncRNAs (CRLs) based on 19 cuproptosis-related genes (CRGs) via Pearson correlation analysis, differential expression analysis, and univariate Cox analysis. A risk model based on 10 CRLs was established with the least absolute shrinkage and selection operator (LASSO) Cox regression analysis and multivariate Cox proportional hazards model to predict the prognosis and immune landscape of GC patients from The Cancer Genome Atlas (TCGA). The risk model has excellent accuracy and efficiency in predicting prognosis of GC patients (Area Under Curve (AUC) = 0.742, 0.803, 0.806 at 1,3,5 years, respectively, P < 0.05). In addition, we found that the risk score was negatively correlated with the infiltration of natural killer (NK) cells and helper T cells, while positively correlated with the infiltration of monocytes, macrophages, mast cells, and neutrophils. Moreover, we evaluated the difference in drug sensitivity of patients with different risk patterns. Furthermore, low-risk patients showed higher tumor mutation burden (TMB) and better immunotherapy response than high-risk patients. In the end, we confirmed the oncogenic role of AL121748.1 which exhibited the highest Hazard Ratio (HR) value among 10 CRLs in GC via cellular functional experiments. In conclusion, our risk model shows a significant role in tumor immunity and could be applied to predict the prognosis of GC patients.

Multimodal integration of radiology, pathology and genomics for prediction of response to PD-(L)1 blockade in patients with non-small cell lung cancer

Immunotherapy is used to treat almost all patients with advanced non-small cell lung cancer (NSCLC); however, identifying robust predictive biomarkers remains challenging. Here we show the predictive capacity of integrating medical imaging, histopathologic and genomic features to predict immunotherapy response using a cohort of 247 patients with advanced NSCLC with multimodal baseline data obtained during diagnostic clinical workup, including computed tomography scan images, digitized programmed death ligand-1 immunohistochemistry slides and known outcomes to immunotherapy. Using domain expert annotations, we developed a computational workflow to extract patient-level features and used a machine-learning approach to integrate multimodal features into a risk prediction model. Our multimodal model (area under the curve (AUC) = 0.80, 95% confidence interval (CI) 0.74-0.86) outperformed unimodal measures, including tumor mutational burden (AUC = 0.61, 95% CI 0.52-0.70) and programmed death ligand-1 immunohistochemistry score (AUC = 0.73, 95% CI 0.65-0.81). Our study therefore provides a quantitative rationale for using multimodal features to improve prediction of immunotherapy response in patients with NSCLC using expert-guided machine learning.

The Landscape of the Tumor-Infiltrating Immune Cell and Prognostic Nomogram in Colorectal Cancer

Tumor-infiltrating immune cells are associated with prognosis and immunotherapy targets in colorectal cancer (CRC). The recently developed CIBERSORT method allows immune cell analysis by deconvolution of high-throughput data onto gene expression. In this study, we analyzed the relative proportions of immune cells in GEO (94 samples) and TCGA (522 samples) CRC data based on the CIBERSORT method. A total of 22 types of tumor-infiltrating immune cells were evaluated. Combined with GEO and TCGA data, it was found that naive B cells, M2 macrophages, and resting mast cells were highly expressed in normal tissues, while M0 macrophages, M1 macrophages, activated mast cells, and neutrophils were highly expressed in tumors. Moreover, we constructed a prognostic model by infiltrating immune cells that showed high specificity and sensitivity in both the training (AUC of 5-year survival = 0.699) and validation (AUC of 5-year survival = 0.844) sets. This provides another basis for clinical prognosis. The results of multiple immunofluorescence detection showed that there were differences in the results of bioinformatics analysis. Neutrophils were highly expressed in normal tissues, and M2 macrophages were highly expressed in tumor tissues. Collectively, our data suggested that infiltrating immune cells in CRC may be an important determinant of prognosis and immunotherapy.

A Novel Risk Model Identified Based on Pyroptosis-Related lncRNA Predicts Overall Survival and Associates With the Immune Landscape of GC Patients

Gastric cancer (GC) is one of the most common malignant gastrointestinal tumors worldwide. Pyroptosis was widely reported to exert a crucial function in tumor development. In addition, pyroptosis was also proved to be associated with the immune landscape. However, whether pyroptosis-related lncRNAs are associated with the prognosis and the immune landscape of GC remains unclear. In the present study, we first constructed a novel risk model by using pyroptosis-related lncRNAs. We identified 11 pyroptosis-related lncRNAs for the establishment of the risk model. The risk model could be used to predict the survival outcome and immune landscape of GC patients. The results of survival analysis and AUC value of a time-related ROC curve proved that our risk model has an elevated efficiency and accuracy in predicting the survival outcome of patients. We also found that the risk model was also associated with the immune landscape, drug sensitivity, and tumor mutation burden of GC patients. In conclusion, our risk model plays a crucial role in the tumor immune microenvironment and could be used to predict survival outcomes of GC patients.

Multi-omics analysis of an immune-based prognostic predictor in non-small cell lung cancer

BACKGROUND

Inhibitors targeting immune checkpoints, such as PD-1/PD-L1 and CTLA-4, have prolonged survival in small groups of non-small cell lung cancer (NSCLC) patients, but biomarkers predictive of the response to the immune checkpoint inhibitors (ICIs) remain rare.

METHODS

The nonnegative matrix factorization (NMF) was performed for TCGA-NSCLC tumor samples based on the LM22 immune signature to construct subgroups. Characterization of NMF subgroups involved the single sample gene set variation analysis (ssGSVA), and mutation/copy number alteration and methylation analyses. Construction of RNA interaction network was based on the identification of differentially expressed RNAs (DERs). The prognostic predictor was constructed by a LASSO-Cox regression model. Four GEO datasets were used for the validation analysis.

RESULTS

Four immune based NMF subgroups among NSCLC patients were identified. Genetic and epigenetic analyses between subgroups revealed an important role of somatic copy number alterations in determining the immune checkpoint expression on specific immune cells. Seven hub genes were recognized in the regulatory network closely related to the immune phenotype, and a three-gene prognosis predictor was constructed.

CONCLUSIONS

Our study established an immune-based prognosis predictor, which might have the potential to select subgroups benefiting from the ICI treatment, for NSCLC patients using publicly available databases.

Spatially resolved analysis of the T cell immune contexture in lung cancer-associated brain metastases

Despite unique genetic alterations within brain metastases (BrMs) and an immunologically distinct surrounding microenvironment, the composition and functional properties of tumor-infiltrating lymphocytes within BrM remain largely unexplored. In particular, the expression of coinhibitory receptors, such as programmed cell death 1 (PD-1), T cell immunoglobulin mucin receptor 3 (TIM-3), and lymphocyte activation gene 3 (LAG-3), within BrMs is unknown. Using multiplexed quantitative immunofluorescence (QIF), this study evaluates the localized expression of PD-L1, level and functional profile of major T cell subsets, and coinhibitory receptors within lung cancer-associated BrMs and primary lung tumors. Clinicopathologically annotated samples from 95 patients with lung cancer between 2002 and 2015 were represented in a tissue microarray format. Spatially resolved and multiplexed QIF was used to evaluate PD-L1 protein, phenotype markers for major T cell subsets (CD3, CD4, CD8, and FOXP3), cell-localized activation and proliferation markers (granzyme B and Ki67), and coinhibitory receptors (PD-1, LAG-3, and TIM-3). The signal for each marker was measured in marker-selected tissue compartments, and associations between marker levels, tumor location, and major clinicopathological variables were studied. In total, 41 primary lung tumors and 65 BrMs were analyzed, including paired samples from 11 patients. Levels of tumor PD-L1 expression were comparable between BrMs and primary lung tumors. BrMs had significantly lower levels of all T cell subsets relative to primary lung tumors, and T cells in BrMs displayed lower levels of granzyme B than primary lesions. PD-1, TIM-3, and LAG-3 levels in CD3⁺ T-cells were also significantly lower in BrMs. Marker expression in patients with paired samples from BrMs and primary lung tumors showed comparable results. High CD3⁺ T-cells, as well as high levels of TIM-3 and LAG-3 in CD3⁺ T-cells, were associated with longer overall survival in BrMs but not primary lung tumors. Lung cancer-associated BrMs display lower T cell infiltration, markers of cytolytic function, and immune regulatory signals than primary lung tumors. Despite these differences, high TIM-3 and high LAG-3 expressions in CD3⁺ T-cells were associated with longer survival. These features are accompanied by comparable levels of PD-L1 protein expression compared with primary lung tumors. These results highlight unique aspects of the tumor immune microenvironment within the brain and provide further support for intracranially focused therapies.

PD-L1 Dependent Immunogenic Landscape in Hot Lung Adenocarcinomas Identified by Transcriptome Analysis

Simple Summary

Lung cancer, with non-small-cell lung cancer as its most common form, is the leading cause of cancer-related mortality and shows a poor prognosis. Despite recent advantages in the field of immunotherapy, there is still a great need for an improved understanding of PD-1/PD-L1 checkpoint blockade-responsive biology. Since immune cell infiltration is regarded as an important parameter in this field, we aimed to identify the immunogenic landscape in primary lung adenocarcinoma on the transcriptomic level in context with tumoral PD-L1 expression (positive vs. negative) and extent of immune infiltration (“hot” vs. “cold” phenotype). Our results reveal that genes that are related to the tumor microenvironment are differentially expressed based on tumoral PD-L1 expression indicating novel aspects of PD-L1 regulation, with potential biological relevance, as well as relevance for immunotherapy response stratification.

Abstract

Background: Lung cancer is the most frequent cause of cancer-related deaths worldwide. The clinical development of immune checkpoint blockade has dramatically changed the treatment paradigm for patients with lung cancer. Yet, an improved understanding of PD-1/PD-L1 checkpoint blockade-responsive biology is warranted. Methods: We aimed to identify the landscape of immune cell infiltration in primary lung adenocarcinoma (LUAD) in the context of tumoral PD-L1 expression and the extent of immune infiltration (“hot” vs. “cold” phenotype). The study comprises LUAD cases (n = 138) with “hot” (≥150 lymphocytes/HPF) and “cold” (<150 lymphocytes/HPF) tumor immune phenotype and positive (>50%) and negative (<1%) tumor PD-L1 expression, respectively. Tumor samples were immunohistochemically analyzed for expression of PD-L1, CD4, and CD8, and further investigated by transcriptome analysis. Results: Gene set enrichment analysis defined complement, IL-JAK-STAT signaling, KRAS signaling, inflammatory response, TNF-alpha signaling, interferon-gamma response, interferon-alpha response, and allograft rejection as significantly upregulated pathways in the PD-L1-positive hot subgroup. Additionally, we demonstrated that STAT1 is upregulated in the PD-L1-positive hot subgroup and KIT in the PD-L1-negative hot subgroup. Conclusion: The presented study illustrates novel aspects of PD-L1 regulation, with potential biological relevance, as well as relevance for immunotherapy response stratification.

Infiltration of NK and plasma cells is associated with a distinct immune subset in non-small cell lung cancer

Immune cells of the tumor microenvironment are central but erratic targets for immunotherapy. The aim of this study was to characterize novel patterns of immune cell infiltration in non-small cell lung cancer (NSCLC) in relation to its molecular and clinicopathologic characteristics. Lymphocytes (CD3+, CD4+, CD8+, CD20+, FOXP3+, CD45RO+), macrophages (CD163+), plasma cells (CD138+), NK cells (NKp46+), PD1+, and PD-L1+ were annotated on a tissue microarray including 357 NSCLC cases. Somatic mutations were analyzed by targeted sequencing for 82 genes and a tumor mutational load score was estimated. Transcriptomic immune patterns were established in 197 patients based on RNA sequencing data. The immune cell infiltration was variable and showed only poor association with specific mutations. The previously defined immune phenotypic patterns, desert, inflamed, and immune excluded, comprised 30, 13, and 57% of cases, respectively. Notably, mRNA immune activation and high estimated tumor mutational load were unique only for the inflamed pattern. However, in the unsupervised cluster analysis, including all immune cell markers, these conceptual patterns were only weakly reproduced. Instead, four immune classes were identified: (1) high immune cell infiltration, (2) high immune cell infiltration with abundance of CD20+ B cells, (3) low immune cell infiltration, and (4) a phenotype with an imprint of plasma cells and NK cells. This latter class was linked to better survival despite exhibiting low expression of immune response-related genes (e.g. CXCL9, GZMB, INFG, CTLA4). This compartment-specific immune cell analysis in the context of the molecular and clinical background of NSCLC reveals two previously unrecognized immune classes. A refined immune classification, including traits of the humoral and innate immune response, is important to define the immunogenic potency of NSCLC in the era of immunotherapy. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

High expression of PIMREG predicts poor survival outcomes and is correlated with immune infiltrates in lung adenocarcinoma

Background

PIMREG is upregulated in multiple cancer types. However, the potential role of PIMREG in lung adenocarcinoma (LUAD) remains unclear. The present study aimed to explore its clinical significance in LUAD.

Methods

Using the Cancer Genome Atlas (TCGA) databases, we obtained 513 samples of LUAD and 59 normal samples from the Cancer Genome Atlas (TCGA) databases to analyze the relationship between PIMREG and LUAD. We used t and Chi-square tests to evaluate the level of expression of PIMREG and its clinical implication in LUAD. The prognostic value of PIMREG in LUAD was identified through the Kaplan–Meier method, Cox regression analysis, and nomogram. Gene set enrichment analysis (GSEA) and single-sample gene set enrichment analysis (ssGSEA) were performed to screen biological pathways and analyze the correlation of the immune infiltrating level with the expression of PIMREG in LUAD.

Results

PIMREG was highly expressed in patients with LUAD. Specifically, the level of PIMREG gradually increased from pathological stage I to IV. Further, we validated the higher expression of PIMREG expressed in LUAD cell lines. Moreover, PIMREG had a high diagnostic value, with an -AUC of 0.955. Kaplan–Meier survival and Cox regression analyses revealed that the high expression of PIMREG was independently associated with poor clinical outcomes. In our prognostic nomogram, the expression of PIMREG implied a significant prognostic value. Gene set enrichment analysis (GSEA) identified that the high expression PIMREG phenotype was involved in the mitotic cell cycle, mRNA splicing, DNA repair, Rho GTPase signaling, TP53 transcriptional regulation, and translation pathways. Next, we also explored the correlation of PIMREG and tumor-immune interactions and found a negative correlation between PIMREG and the immune infiltrating level of T cells, macrophages, B cells, dendritic cells (DCs) , and CD8⁺ T cells in LUAD.

Conclusions

High levels of PIMREG correlated with poor prognosis and immune infiltrates in LUAD.

Single-cell transcriptomics reveals heterogeneous progression and EGFR activation in pancreatic adenosquamous carcinoma

Pancreatic adenosquamous carcinoma (PASC) — a rare pathological pancreatic cancer (PC) type — has a poor prognosis due to high malignancy. To examine the heterogeneity of PASC, we performed single-cell RNA sequencing (scRNA-seq) profiling with sample tissues from a healthy donor pancreas, an intraductal papillary mucinous neoplasm, and a patient with PASC. Of 9,887 individual cells, ten cell subpopulations were identified, including myeloid, immune, ductal, fibroblast, acinar, stellate, endothelial, and cancer cells. Cancer cells were divided into five clusters. Notably, cluster 1 exhibited stem-like phenotypes expressing UBE2C, ASPM, and TOP2A. We found that S100A2 is a potential biomarker for cancer cells. LGALS1, NPM1, RACK1, and PERP were upregulated from ductal to cancer cells. Furthermore, the copy number variations in ductal and cancer cells were greater than in the reference cells. The expression of EREG, FCGR2A, CCL4L2, and CTSC increased in myeloid cells from the normal pancreas to PASC. The gene sets expressed by cancer-associated fibroblasts were enriched in the immunosuppressive pathways. We demonstrate that EGFR-associated ligand-receptor pairs are activated in ductal-stromal cell communications. Hence, this study revealed the heterogeneous variations of ductal and stromal cells, defined cancer-associated signaling pathways, and deciphered intercellular interactions following PASC progression.

Association between PD-L1 expression and initial brain metastasis in patients with non-small cell lung cancer and its clinical implications

Background

Brain metastases frequently occur in patients with non‐small cell lung cancer (NSCLC) resulting in a poor prognosis. Here, we investigated the association between PD‐L1 expression and brain metastasis in patients with NSCLC and its clinical significance.

Methods

A total of 270 patients diagnosed with metastatic NSCLC who underwent PD‐L1 testing on their tumor tissue between January 2017 and March 2019 were retrospectively reviewed. The VENTANA PD‐L1 (SP263) assay was used, and positive PD‐L1 expression was defined as staining in ≥1% of tumor cells.

Results

Positive PD‐L1 expression was observed in 181 (67.0%) patients, and 74 (27.4%) patients had brain metastasis at diagnosis. Synchronous brain metastases were more frequently observed in PD‐L1‐positive compared with PD‐L1‐negative patients (31.5% vs. 19.1%, p = 0.045). Multiple logistic regression analysis identified positive PD‐L1 expression (odds ratio [OR]: 2.24, p = 0.012) as an independent factor associated with synchronous brain metastasis, along with the histological subtype of nonsquamous cell carcinoma (OR: 2.84, p = 0.003). However, the incidence of central nervous system (CNS) progression was not associated with PD‐L1 positivity, with a two‐year cumulative CNS progression rate of 26.3% and 28.4% in PD‐L1‐positive and PD‐L1‐negative patients, respectively (log rank p = 0.944). Furthermore, positive PD‐L1 expression did not affect CNS progression or overall survival in patients with synchronous brain metastasis (long rank p = 0.513 and 0.592, respectively).

Conclusions

Initial brain metastases are common in NSCLC patients with positive PD‐L1 expression. Further studies are necessary to understand the relationship between early brain metastasis and cancer immunity.

Safety, Antitumor Activity, and T-cell Responses in a Dose-Ranging Phase I Trial of the Oncolytic Peptide LTX-315 in Patients with Solid Tumors

PURPOSE

LTX-315 is a first-in-class, 9-mer membranolytic peptide that has shown potent immunomodulatory properties in preclinical models. We conducted a phase I dose-escalating study of intratumoral LTX-315 administration in patients with advanced solid tumors.

PATIENTS AND METHODS

Thirty-nine patients were enrolled, receiving LTX-315 injections into accessible tumors. The primary objective was to assess the safety and tolerability of this approach, with antitumor and immunomodulatory activity as secondary objectives. Tumor biopsies were collected at baseline and posttreatment for analysis of immunologic parameters.

RESULTS

The most common treatment-related grade 1-2 adverse events were vascular disorders including transient hypotension (18 patients, 46%), flushing (11 patients, 28%), and injection site reactions in 38% of patients. The most common grade 3 LTX-315-related toxicities were hypersensitivity or anaphylaxis (4 patients, 10%). Analysis of immune endpoints in serial biopsies indicated that LTX-315 induces necrosis and CD8⁺ T-cell infiltration into the tumor microenvironment. Sequencing of the T-cell receptor repertoire in peripheral blood identified significant expansion of T-cell clones after treatment, of which 49% were present in available tumor biopsies after treatment, suggesting that they were tumor associated. Substantial volume reduction (≥30%) of injected tumors occurred in 29% of the patients, and 86% (12/14 biopsies) had an increase in intralesional CD8⁺ T cells posttreatment. No partial responses by immune-related response criteria were seen, but evidence of abscopal effect was demonstrated following treatment with LTX-315.

CONCLUSIONS

LTX-315 has an acceptable safety profile, is clinically active, induces changes in the tumor microenvironment and contributes to immune-mediated anticancer activity.

New developments in locally advanced nonsmall cell lung cancer

Locally advanced nonsmall cell lung cancer, due to its varying prognosis, is grouped according to TNM stage IIIA, IIIB and IIIC. Developments over the last 3 years have been focused on the integration of immunotherapy into the combination treatment of a locally definitive therapy (surgery or radiotherapy) and chemotherapy. For concurrent chemoradiotherapy, consolidation therapy with durvalumab was established. Adjuvant targeted therapy has again gained increasing interest. In order to adapt treatment to the specific stage subgroup and its prognosis, fluorodeoxyglucose positron emission tomography/computed tomography and pathological evaluation of the mediastinum are important. Tumours should be investigated for immunological features and driver mutations. Regarding toxicity, evaluation of pulmonary and cardiac function, as well as symptoms and quality of life, is of increasing importance. To improve the management and prognosis of this heterogeneous entity, clinical trials and registries should take these factors into account.

Clinicopathological significance of the expression of PD-L1 in non-small cell lung cancer

INTRODUCTION

PD1/PD-L1 pathway targeting therapies are nowadays an established treatment option for patients with NSCLC. We assessed whether PD-L1 expression in NSCLC tumor cells was associated with specific clinical features or overall survival using four different clones.

METHODS AND RESULTS

A retrospective study included formalin-fixed paraffin embedded (FFPE) surgical tumors from 482 patients. PD-L1 status was assessed with immunohistochemistry in tumor cells on tissue microarrays using clones 28-8, 22C3, SP263 and SP142. Associations with OS were assessed by Kaplan-Meier and multivariate Cox's regression analysis. Patients' median age: 68 years (39-86); histology: adenocarcinoma (AdCa) 61%, squamous-cell carcinoma (SqCC) 33%, and large cell carcinoma (LCC) 6%; p-stage: IA (46%), IB (30%), IIA (10%), IIB (11,4%), IIIA (1,2%), IIIB - IV (0,4%). PD-L1 positivity (≥1%) in NSCLC for clones 28-8, 22C3, SP263, SP142 was 41.5%, 34.2%, 42.7%, 10.4%, respectively (Pearson Chi-square p < 0.0001). PD-L1 expression was correlated with histology, tumor size and grading. Statistically significant association between PD-L1 expression and OS in NSCLC and Non-AdCa was observed with clone SP142 (log-rank p = 0.045 and p = 0.05, respectively). Statistically significant association between PD-L1 expression and OS in LCC was observed with clones 22C3 (log-rank p = 0.009) and SP263 (log-rank p = 0.050).

CONCLUSIONS

Overexpression of the PD-L1 clone SP142 was associated with poor overall survival in NSCLC and Non-AdCa. Clones 22C3 and SP263 were associated with poor prognosis in LCC. PD-L1 status might serve as a prognostic marker in NSCLC.

Prognostic value of PD-L1 expression in patients with unresectable stage III non-small cell lung cancer treated with chemoradiotherapy

Background

Expression of PD-L1 is the most investigated predictor of benefit from immune checkpoint blockade in advanced NSCLC but little is known about the association of PD-L1 expression and clinicopathological parameters of patients with unresectable stage III NSCLC.

Methods

National registry data was searched for medical records of consecutive inoperable stage III NSCLC patients treated with ChT and RT from January 2012 to December 2017. Totally 249 patients were identified that met inclusion criteria and of those 117 patients had sufficient tissue for PD-L1 immunohistochemical staining.

Results

Eighty patients (68.4%) expressed PD-L1 of ≥ 1% and 29.9% of more than 50%. Median PFS was 15.9 months in PD-L1 negative patients and 16.1 months in patients with PD-L1 expression ≥ 1% (p = 0.696). Median OS in PD-L1 negative patients was 29.9 months compared to 28.5 months in patients with PD-L1 expression ≥ % (p = 0.888). There was no difference in median OS in patients with high PD-L1 expression (≥ 50%) with 29.8 months compared to 29.9 months in those with low (1–49%) or no PD-L1 expression (p = 0.694). We found that patients who received a total dose of 60 Gy or more had significantly better median OS (32 months vs. 17.5 months, p < 0.001) as well as patients with PS 0 (33.2 vs. 20.3 months, p = 0.005).

Conclusions

In our patients PD-L1 expression had no prognostic value regarding PFS and OS. Patients with good performance status and those who received a total radiation dose of more than 60 Gy had significantly better mOS.

Favorable Immune Microenvironment in Patients with EGFR and MAPK Co-Mutations

PURPOSE

Although EGFR-mutated patients generally do not benefit from checkpoint inhibitors (ICIs), some patients in the KEYNOTE-001 study consistently benefited from this treatment. This study investigated immune microenvironment characteristics to identify the subgroup of patients that may benefit from ICIs.

MATERIALS AND METHODS

Using data from The Cancer Genome Atlas Program (TCGA) and Cancer Proteome Atlas, TMB and protein level of PD-L1 were explored in the patients with EGFR mutations and wild-type patients. Different patterns of EGFR mutations (according to EGFR co-mutation with different downstream pathway genesets) were used to group EGFR mutation population. Estimated infiltration analyses were used to explore changes in the immune microenvironment.

RESULTS

This study analyzed somatic mutation data from 1287 patients from five cohorts (TCGA, Broad, The Tumour Sequencing Project, Memorial Sloan Kettering Cancer Center, Catalogue Of Somatic Mutations In Cancer database). The probability of EGFR mutation was approximately 14.30% (184/1287) and the co-mutation rate was 11.41% (21/184) in patients with EGFR mutations. Glycosaminoglycan-related pathways were significantly upregulated in the EGFR mutant group. EGFR-mutated patients had lower TMB and PD-L1 protein levels than those in wild-type patients. Increase immature DCs infiltration and decreased NK CD56dim, T gamma delta, cytotoxic, and Th2 cell infiltration were the main immune changes in EGFR-mutated patients. Patients with EGFR-MAPK co-mutations had higher levels of TMB and PD-L1 protein expression. Meanwhile, the co-mutated patients had a similar immune microenvironment as that in wild-type patients.

CONCLUSION

In this study, we defined a subgroup of patients with EGFR-MAPK co-mutations. These co-mutated patients may benefit from ICI treatment.

An immune landscape based prognostic signature predicts the immune status and immunotherapeutic responses of patients with colorectal cancer

AIMS

Colorectal cancer (CRC) is one of the most common cancers with poor prognosis worldwide. The advent of immunotherapy has greatly improved survival in refractory patients of CRC. In this study, we aimed to identify reliable immune classification and biomarkers that predict immunotherapeutic responses in CRC patients.

MATERIALS AND METHODS

Based on transcriptome profiles of two publicly available CRC datasets, we performed single-sample gene set enrichment analysis (ssGSEA) to calculate the relative abundance of 29 immune-related items of each sample. Unsupervised clustering was used to classify CRC patients. Furthermore, an immune prognostic signature was constructed using the least absolute shrinkage and selection operator (LASSO) Cox regression analysis.

KEY FINDINGS

The CRC patients were clustered into high, medium, low immune infiltration subtypes based on the immune landscape. There was significant heterogeneity among the three subtypes. The high immune infiltration group showed higher expression of programmed cell death-ligand 1 and better prognosis than the median and low immune infiltration groups. Furthermore, we constructed a 7-immune-related prognostic gene signature and found that the signature had high predictive value and was superior to other clinicopathological parameters. Finally, the correlation analysis of the signature with immune cell infiltration and immune checkpoint molecules suggested that the signature had the potential to assess the immunotherapeutic responses of CRC patients.

SIGNIFICANCE

The immune landscape and prognostic signature of CRC contribute to a deeper understanding of the tumor microenvironment and guide accurate immunotherapy.

Systematic Characterization of the Expression and Prognostic Values of Formin-Like Gene Family in Gastric Cancer

Formin-like genes (FMNLs) are members of formins family and have been implicated to the development and progression of multiple cancers. This research aims to analyze the expression profiles, prognostic values, and immune infiltrating associations of FMNLs in gastric cancer (GC) using multiple online bioinformatics website, including Oncomine, UALCAN, Kaplan-Meier Plotter, TIMER, GeneMANIA, DAVID, and LinkedOmics databases. The mRNA levels of FMNL1/2/3 were higher in GC tissues than normal. Meanwhile, FMNLs expressions tend to be upregulated in advanced and poorly differentiated GC. Prognostic value analysis suggested that high transcription levels of FMNL1/3 were associated with poor overall survival in GC patients. Correlation analysis between FMNLs expressions and immune infiltrating GC revealed that the expressions of FMNLs were significantly associated with immune infiltrating. Protein-protein interaction network and enrichment analysis of FMNLs in GC showed that FMNLs coexpressed genes mainly participated in organizing actin cytoskeleton through affecting small G proteins activity. Moreover, Gene Set Enrichment Analysis (GSEA) analysis uncovered FMNLs and their coexpressed genes was tightly associated with immune-related cellular functions. These findings demonstrate that FMNLs might play significant immunomodulatory roles in tumor immunity and could be novel therapeutic targets and potential prognostic biomarkers in GC.

Tumor infiltrating T cells influence prognosis in stage I-III non-small cell lung cancer

Background

T cell infiltration in non-small cell lung cancer (NSCLC) is essential for the immunological response to malignant tissue, especially in the era of immune-checkpoint inhibition. To investigate the prognostic impact of CD4⁺ T helper cells (T_h), CD8⁺ cytotoxic (T_c) and FOXP3⁺ regulatory T (T_reg) cells in NSCLC, we performed this analysis.

Methods

By counterstaining of CD4, CD8 and FOXP3 we used immunohistochemistry on tissue microarrays (TMA) to evaluate peritumoral T_h cells, T_reg cells and T_c cells in n=294 NSCLC patients with pTNM stage I–III disease.

Results

Strong CD4⁺ infiltration was associated with higher tumor stages and lymphonodal spread. However, strong CD4⁺ infiltration yielded improved overall survival (OS) (P=0.014) in adenocarcinoma (ADC) and large cell carcinoma (LCC) but not in squamous cell carcinoma (SCC). A CD4/CD8 ratio <1 was associated with high grade NSCLC tumors (P=0.020). High CD8⁺ T cell infiltration was an independent prognostic factor for OS (P=0.040) and progression-free survival (PFS) (P=0.012) in the entire study collective. The OS benefit of high CD8⁺ infiltration was especially prominent in PD-L1 negative NSCLC (P=0.001) but not in PD-L1 positive tissue (P=0.335). Moreover, positive FOXP3⁺ expression in tumor infiltrating lymphocytes was associated with increased OS (P=0.007) and PFS (P=0.014) in SCC but not in ADC and LCC (all P>0.05). Here, prognostic effects were prominent in PD-L1 positive SCC (P=0.023) but not in PD-L1 negative SCC (P=0.236).

Conclusions

High proportion of CD8⁺ T_c cells correlated with improved prognostic outcome in stage I–III NSCLC. T_h cells and T_reg cells have implications on outcome with respect to tumor histology and biology.

CLEC3B as a potential diagnostic and prognostic biomarker in lung cancer and association with the immune microenvironment

Background

Lung cancer is the leading cause of cancer-related mortality globally. Discovering effective biomarkers for early diagnosis and prognosis is important to reduce the mortality rate and ensure efficient therapy for lung cancer patients. C-type lectin domain family 3 member B (CLEC3B) has been reported in various cancers, but its correlation with lung cancer remains elusive.

Methods

The GEO, TCGA and Oncomine databases were analyzed to examine the expression of CLEC3B in lung cancer. The CLEC3B mRNA levels in 15 patient tissue samples were detected by real-time PCR and the CLEC3B protein levels in 34 patient tissue samples were detected by immunohistochemistry. A Chi-square test was performed to analyze the correlation of CLEC3B expression and clinicopathological factors. The diagnostic value of CLEC3B was revealed by receiver operating characteristic (ROC) curves. Univariate and multivariate Cox proportional hazards regression models and Kaplan–Meier plots were used to evaluate the prognostic value of CLEC3B in lung cancer. The TIMER database was used to evaluate the correlation of CLEC3B and immune infiltration. Gene set enrichment analysis revealed tumor‐associated biological processes related to CLEC3B.

Results

CLEC3B is significantly downregulated in lung cancer patients compared with nontumor controls according to database analysis and patient tissue sample detection (p < 0.001). Specifically, CLEC3B is significantly downregulated in stage IA lung cancer patients (p < 0.001) and has a high diagnostic accuracy (area under the receiver operating characteristic curve > 0.9). Moreover, low expression of CLEC3B is related to poor progression-free survival (HR = 0.60, 95% CI 0.49–0.74, p = 8.3e−07) and overall survival (HR = 0.66, 95% CI 0.58–0.75, p = 2.1e−10), indicating it as a risk factor for lung cancer. Multivariate analysis value showed that low expression of CLEC3B may be an independent risk factor for disease‐free survival in lung cancer patients (HR = 0.655, 95% CI 0.430–0.996, Cox p = 0.048). In addition, we also investigated the potential role of CLEC3B in tumor-immune interactions and found that CLEC3B might be associated with the immune infiltration and immune activation of lung cancer, especially in squamous cell carcinoma.

Conclusions

Our findings indicate that CLEC3B expression is downregulated in lung cancer and reveal the diagnostic and prognostic potential of CLEC3B in lung cancer and its potential as an immune-related therapeutic target in lung cancer.

Immune and Stroma Related Genes in Breast Cancer: A Comprehensive Analysis of Tumor Microenvironment Based on the Cancer Genome Atlas (TCGA) Database

Background: Tumor microenvironment is essential for breast cancer progression and metastasis. Our study sets out to examine the genes affecting stromal and immune infiltration in breast cancer progression and prognosis.

Materials and Methods: This work provides an approach for quantifying stromal and immune scores by using ESTIMATE algorithm based on gene expression matrix of breast cancer patients in TCGA database. We found differentially expressed genes (DEGs) through limma R package. Functional enrichments were accessed through Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Besides, we constructed a protein-protein network, identified several hub genes in Cytoscape, and discovered functionally similar genes in GeneMANIA. Hub genes were validated with prognostic data by Kaplan-Meier analysis both in The Cancer Genome Atlas (TCGA) database and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) database and a meta-analysis of hub genes prognosis data was utilized in multiple databases. Furthermore, their relationship with infiltrating immune cells was evaluated by Tumor IMmune Estimation Resource (TIMER) web tool. Cox regression was utilized for overall survival (OS) and recurrence-free survival (RFS) in TCGA database and OS in METABRIC database in order to evaluate the impact of stromal and immune scores on patients prognosis.

Results: One thousand and eighty-five breast cancer patients were investigated and 480 differentiated expressed genes (DEGs) were found based on the analysis of mRNA expression profiles. Functional analysis of DEGs revealed their potential functions in immune response and extracellular interaction. Protein-protein interaction network gave evidence of 10 hub genes. Some of the hub genes could be used as predictive markers for patients prognosis. In this study, we found that tumor purity and specific immune cells infiltration varied in response to hub genes expression. The multivariate cox regression highlighted the fact that immune score played a detrimental role in overall survival (HR = 0.45, 95% CI: 0.27–0.74, p = 0.002) and recurrence-free survival (HR = 0.41, 95% CI: 0.22–0.77, p = 0.006) in TCGA database. These result was confirmed in METABRIC database that immune score was a protector of OS (HR = 0.88, 95% CI: 0.77–0.99, p = 0.039).

Conclusions: Our findings promote a better understanding of the potential genes behind the regulation of tumor microenvironment and cells infiltration. Immune score should be considered as a prognostic factor for patients' survival.

Immune Checkpoint Markers in Neuroendocrine Carcinoma of the Digestive System

Digestive system neuroendocrine carcinomas (NECs) are rare neoplasms originating from neuroendocrine cells with a poor prognosis and limited effective treatments. Programmed cell death protein 1/ligand 1 (PD-1/PD-L1) blockade has been used in the management of more than 10 solid tumors and has achieved promising clinical outcomes. PD-L1 expression, immune cell infiltration, tumor mutational burden (TMB), and microsatellite instability (MSI) are all verified biomarkers that can predict the response to anti-PD-1/PD-L1 therapy. Here, we investigated PD-L1 expression and immune cell infiltration density by immunohistochemical (IHC) staining of tumor samples from 33 patients with digestive system NECs. Tumor and paratumor normal samples from 31 of these patients underwent whole-exome sequencing to evaluate TMB and the MSI-high (MSI-H) status. In total, 29.0% of digestive system NECs had positive PD-L1 expression according to the tumor proportion score (TPS). Infiltration of CD3⁺, CD8⁺, and CD68⁺ cells was observed in 69.7, 27.3, and 54.5% of patients, respectively. The TMB value for patients sequenced ranged from 0.57 to 11.75 mutations/Mb, with a median of 5.68 mutations/Mb. mSINGS, MSIsensor, and MSIseq were used to analyze the MSI status according to the sequencing data, and in our evaluation, no MSI-H status was detected. Our data might indicate a limited potential of anti-PD-1/PD-L1 monotherapy in digestive system NECs, although clinical trials are warranted.

An immune relevant signature for predicting prognoses and immunotherapeutic responses in patients with muscle-invasive bladder cancer (MIBC)

Immune checkpoint inhibitors (ICIs) are novel treatments that significantly improve the survival time of MIBC patients, but immunotherapeutic responses are different among MIBC patients. Therefore, it is urgent to find predictive biomarkers that can accurately identify MIBC patients who are sensitive to ICIs. In this study, we computed the relative abundances of 24 immune cells based on the expression profiles of MIBC patients using single‐sample gene set enrichment analysis (ssGSEA). Unsupervised clustering analysis of the 24 immune cells was performed to classify MIBC patients into different immune‐infiltrating groups. Genome (gene mutation and copy number variation), transcriptome (mRNA, lncRNA, and miRNA), and functional enrichment were found to be heterogeneous among different immune‐infiltrating groups. We identified 282 differentially expressed genes (DEGs) associated with immune infiltration by comparing the expression profiles of patients with different immune infiltration profiles, and 20 core prognostic DEGs were identified by univariate Cox regression analysis. An immune‐relevant gene signature (TIM signature) consisting of nine key prognostic DEGs (CCDC80, CD3D, CIITA, FN1, GBP4, GNLY, SPINK1, UBD, and VIM) was constructed using least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Receiver operating characteristic (ROC) curves and subgroup analysis confirmed that the TIM signature was an ideal biomarker for predicting the prognosis of MIBC patients. Its value in predicting immunotherapeutic responses was also validated in The Cancer Genome Atlas (TCGA) cohort (AUC = 0.69, 95% CI = 0.63‐0.74) and the IMvigor210 cohort (AUC = 0.64, 95% = 0.55‐0.74). The TIM signature demonstrates a powerful ability to distinguish MIBC patients with different prognoses and immunotherapeutic responses, but more prospective studies are needed to assess its reliability in the future.

WITHDRAWN: Characterization of Patterns of Immune Cell Infiltration in NSCLC

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Targeting Immune-Mediated Dormancy: A Promising Treatment of Cancer

Immune-mediated dormancy is when the immune system keeps proliferating tumor cells unchanged, mostly via cytotoxic activity of immune cells. Cancer dormancy, especially immune-mediated dormancy, may be the explanation for tumor refractory and may be responsible for resistance to conventional chemo- and radiotherapies. Here, we will describe different scenarios as to how the immune cells and cytokines involved in cancer progression are connected with the initiation of dormancy and cancer treatment. Two distinct treatment methods, such as maintaining metastatic tumor cells dormant and awakening them, are also discussed. A better understanding of immune-mediated dormancy will help to design novel and effective immunotherapies and will likely increase the efficiency of tumor treatment inhibiting metastasis.