Identification of Immune-Related lncRNA Signature to Predict Prognosis and Immunotherapeutic Efficiency in Bladder Cancer

Purpose

Identify immune-related lncRNA (IRL) signature related to the prognosis and immunotherapeutic efficiency for bladder cancer (BLCA) patients.

Methods

A total of 397 samples, which contained RNA-seq and clinical information from The Cancer Genome Atlas (TCGA) database, were used for the following study. Then the Lasso penalized Cox proportional hazards regression model was used to construct prognostic signature. According to the optimal cut-off value determined by time-dependent ROC curve, low and high-risk groups were set up. One immunotherapy microarray dataset as validation set was used to verify the ability of predicting immunotherapy efficacy. Furthermore, more evaluation between two risk groups related clinical factors were conducted. Finally, external validation of IRL-signature was conducted in Zhengzhou cohort.

Result

Four IRLs (HCP5, IPO5P1, LINC00942, and LINC01356) with significant prognostic value (P<0.05) were distinguished. This signature can accurately predict the overall survival of BLCA patients and was verified in the immunotherapy validation set. IRL-signatures can be used as independent prognostic risk factor in various clinical subgroups. According to the results of GSVA and MCP algorithm, we found that IRL-signature risk score is strikingly negative correlated with tumor microenvironment (TME) CD8+T cells and Cytotoxic lymphocytes infiltration, indicating that the better prognosis and immunotherapy might be caused partly by these. Then, the results from the TIDE analysis revealed that IRL could efficiently predict the response of immunotherapy in BLCA. External validation had similar results with TCGA-BLCA cohort.

Conclusions

The novel IRL-signature has a significant prognostic value for BLCA patients might facilitate predicting the efficacy of immunotherapy.

Bcl9 Depletion Modulates Endothelial Cell in Tumor Immune Microenvironment in Colorectal Cancer Tumor

Tumor endothelial cells are an important part of the tumor microenvironment, and angiogenesis inhibitory therapy has shown potential in tumor treatment. However, which subtypes of tumor endothelial cells are distributed in tumors, what are the differences between tumor endothelial cells and normal endothelial cells, and what is the mechanism of angiogenesis inhibitory therapy at the histological level, are all need to be resolved urgently. Using single-cell mRNA sequencing, we analyzed 12 CT26 colon cancer samples from mice, and found that knockdown of the downstream factor BCL9 in the Wnt signaling pathway or inhibitor-mediated functional inhibition can modulate tumor endothelial cells at a relatively primitive stage, inhibiting their differentiation into further extracellular matrix construction and angiogenesis functions. Furthermore, we propose a BCL9-endo-Score based on the differential expression of cells related to different states of BCL9 functions. Using published data sets with normal endothelial cells, we found that this score can characterize endothelial cells at different stages of differentiation. Finally, in the The Cancer Genome Atlas (TCGA) pan-cancer database, we found that BCL9-endo-Score can well predict the prognosis of diseases including colon cancer, kidney cancer and breast cancer, and identified the markers of these tumor subtypes, provide a basis for the prognosis prediction of patients with such types of tumor. Our data also contributed knowledge for tumor precision treatment with angiogenesis inhibitory therapy by targeting the Wnt signaling pathway.

Expression of PD1/PDL1 in gastric cancer at different microsatellite status and its correlation with infiltrating immune cells in the tumor microenvironment

Objective: The microsatellite status and tumor immune microenvironment have a remarkable influence on tumor immunotherapy. This study was performed to investigate programmed cell death protein 1/programmed death ligand 1 (PD1/PDL1) expression and their correlations with CD8+ T cell/CD68+ macrophage (CD68+ M) densities in gastric cancer (GC) at different microsatellite statuses.

Methods: The expression of MLH1, PMS2, MSH2, and MSH6 was detected via immunohistochemistry (IHC) to determine the microsatellite status in 215 GC samples obtained from surgical resections. Furthermore, the expression of PD1, PDL1, CD8, and CD68 was detected in the samples via IHC, and the differences and correlations in GC at different microsatellite statuses were then analyzed. PDL1 expression in tumor cells was labeled as PDL1[T], while expression of PD1 and PDL1 in tumor-infiltrating immune cells was labeled as PD1 and PDL1, respectively. Kaplan-Meier analysis was used to evaluate the significance of PD1/PDL1 expression in determining overall survival. Multivariate Cox regression analysis was performed using SPSS software. P-values were determined using the log-rank test.

Results: Our results indicated that PD1, PDL1[T], and PDL1 positivity rates were 59%, 35%, and 57% in 46 microsatellite unstable (MSI) GCs and 45%, 22%, and 40% in 169 microsatellite stable (MSS) GCs, respectively. Compared with MSS GC, PD1, PDL1[T], and PDL1 expression was higher in MSI GC (P = 0.109, 0.090, and 0.044, respectively). Additionally, CD8+ T cell and CD68+ M densities were higher in MSI GC than in MSS GC (P = 0.537 and <0.001, respectively). Additionally, CD8+ T cell/CD68+ M densities were evaluated according to tumor center and invasion front. We found that PD1 expression was significantly correlated with CD8+ T cell density at the invasion front of the MSI GC (P = 0.031), whereas PDL1 expression was significantly correlated to high CD68+ M density in the tumor center and invasion front of MSS GC (P = 0.001 and 0.014, respectively). Survival analysis showed that patients with PD1-positive and PDL1[T]/PDL1-negative GC had better prognosis (P = 0.012, 0.005, and 0.022, respectively). Multivariate Cox survival analysis showed that PDL1[T] was an independent prognostic factor for GC.

Conclusion: The results suggested that PD1/PDL1 expression and immune response varied at different microsatellite statuses in GC. PD1/PDL1 expression was correlated with CD8+ T cell/CD68+ M densities in GC at different microsatellite statuses, especially at the invasion front. The patients exhibiting high PD1/PDL1 expression or high CD8+ T cell/CD68+ M densities MSI GC might be potential beneficiaries of PD1/PDL1 immunotherapy.

Clinical impact of the tumor immune microenvironment in completely resected stage IIIA(N2) non-small cell lung cancer based on an immunoscore approach

Background:

Completely resected stage IIIA(N2) non-small cell lung cancer (NSCLC) comprises a heterogeneous population according to discrepancies in survival prognosis. Accumulating evidence suggests that tumor-infiltrating lymphocytes (TILs) are clinically significant, despite a lack of consensus regarding the immunoscore (IS) in NSCLC. Here, we determined the prognostic value of the immune microenvironment as an IS in a uniform cohort of patients with completely resected stage IIIA(N2) NSCLC.

Methods:

Consecutive patients with pathologically confirmed stage IIIA(N2) NSCLC and who underwent complete resection (2005–2012) were retrospectively reviewed. Tissue microarrays (TMAs) were constructed from surgical paraffin-embedded primary lung tumor specimen. For each case, two representative regions from the tumor center (CT) and two from the invasive margin (IM) containing the highest density of lymphocytes were selected. Densities of CD3+, CD45RO+, and CD8+ lymphocytes were assessed using immunohistochemistry (IHC) by specialized pathologists according to predefined scoring scales. Patients were classified according to IS definition based on TIL type, density, and distribution, and relationships between IS and prognosis were evaluated.

Results:

Patients (N = 288) with complete IHC-based TMA spots were included. Univariate analyses showed that CD3+ T cell density was associated with neither overall survival (OS) nor distant metastasis-free survival (DMFS), whereas CD45RO+ T cell density in the IM was a significant prognostic factor for DMFS (p = 0.02) and was predictive of OS (p = 0.05). Combined CD45RO+ and CD8+ cell infiltration in tumor regions (CT and IM) significantly improved IS prognostic impact. Multivariate analyses revealed IS as an independent prognostic predictor for both DMFS (p = 0.001) and OS (p = 0.002).

Conclusion:

The proposed IS might provide valuable prognostic information, including prediction of DMFS and OS in stage IIIA(N2) NSCLC patients. Larger patient cohorts are needed to validate this IS classification, which might assist with accurate risk stratification and treatment decisions.

Prognostic Value of PLXND1 and TGF-β1 Coexpression and Its Correlation With Immune Infiltrates in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the most common primary liver malignancy with no curative treatments. Plexin D1 (PLXND1) is a cellular receptor whose functions have been explored in several human cancers; however, the critical roles of PLXND1 in HCC have rarely been probed. Therefore, the present study attempted to elucidate the expression pattern, prognostic significance, and potential roles of PLXND1 in HCC. We found that PLXND1 expression in HCC tissues was significantly higher compared with normal liver tissue from Gene Expression Profiling Interactive Analysis (GEPIA) and Integrative Molecular Database of Hepatocellular Carcinoma (HCCDB) databases. This result was further validated by immunohistochemistry staining (IHC) using tissue microarrays, which contained 216 HCC cases collected from our hospital. Additionally, PLXND1 expression showed a significant correlation with several clinical characteristics, including tumor grade and tumor hemorrhage (TH). Moreover, TISIDB and GEPIA databases were used to investigate the roles of PLXND1 in tumor-immune system interactions in HCC. As an immunoinhibitor, transforming growth factor-beta (TGF-β1) displayed the greatest correlations with PLXND1 in HCC. Finally, Kaplan-Meier curves and Cox analysis were conducted to further examine the potential clinical value of PLXND1 in HCC. We described a subclassification of HCC based on PLXND1 and TGF-β1 expression, which could be used to predict clinical outcomes and patient prognosis. Taken together, the results of this study indicate that PLXND1 might be a promising prognostic biomarker and potential therapeutic target in HCC.

Immunological Role and Prognostic Value of APBB1IP in Pan-Cancer Analysis

Objective: APBB1IP is a Rap1-binding protein that mainly acts as a regulator of leukocyte recruitment and pathogen clearance through complement-mediated phagocytosis. However, the role of APBB1IP in tumor immunity remains unclear. This study was carried out to evaluate the prognostic landscape of APBB1IP in pan-cancer analysis and investigate the relationship between APBB1IP expression and immune infiltration.

Methods: We explored the expression pattern and prognostic value of APBB1IP in pan-cancer analysis through Kaplan-Meier Plotter and multiple databases, including TCGA, Oncomine. We then assessed the correlation between APBB1IP expression and immune cell infiltration using the TIMER database. Furthermore, we identified the proteins that interact with APBB1IP and performed epigenetic and transcriptional analyses. Multivariate Cox regression analyses were applied to construct a prognostic model, which consisted of APBB1IP and its interacting proteins, based on the lung cancer cohorts from the Gene Expression Omnibus (GEO) database.

Results: The expression of APBB1IP was correlated with the prognosis of several types of cancer. APBB1IP upregulation was found to be associated with increased immune cell infiltration, especially for CD8⁺ T cells, natural killer (NK) cells, and immune regulators. A link was found between APBB1IP and immune-related proteins including RAP1A/B, TLN1/2 and VCL in the interaction network.

Conclusion: APBB1IP can serve as a prognostic biomarker in pan-cancer analysis. APBB1IP upregulation was correlated with increased immune-cell infiltration, and the expression APBB1IP in different tumors might be related to the tumor immune microenvironment.

Roles of the Dynamic Tumor Immune Microenvironment in the Individualized Treatment of Advanced Clear Cell Renal Cell Carcinoma

Immune checkpoint inhibitors (ICIs) are currently a first-line treatment option for clear cell renal cell carcinoma (ccRCC). However, recent clinical studies have shown that a large number of patients do not respond to ICIs. Moreover, only a few patients achieve a stable and durable response even with combination therapy based on ICIs. Available studies have concluded that the response to immunotherapy and targeted therapy in patients with ccRCC is affected by the tumor immune microenvironment (TIME), which can be manipulated by targeted therapy and tumor genomic characteristics. Therefore, an in-depth understanding of the dynamic nature of the TIME is important for improving the efficacy of immunotherapy or combination therapy in patients with advanced ccRCC. Here, we explore the possible mechanisms by which the TIME affects the efficacy of immunotherapy and targeted therapy, as well as the factors that drive dynamic changes in the TIME in ccRCC, including the immunomodulatory effect of targeted therapy and genomic changes. We also describe the progress on novel therapeutic modalities for advanced ccRCC based on the TIME. Overall, this review provides valuable information on the optimization of combination therapy and development of individualized therapy for advanced ccRCC.

Th2 cell infiltrations predict neoadjuvant chemotherapy response of estrogen receptor-positive breast cancer

Background

High infiltration of Th2 is linked to breast cancer progression and metastasis through the induction of cytokine release and T-cell anergy. The estrogen receptor (ER)-positive subtype, which accounts for 70% of breast cancer, is known to respond less to neoadjuvant chemotherapy (NAC) due to its low potential for proliferation. We hypothesized that Th2 high tumors are highly proliferative, and thus more likely to respond to NAC in ER-positive breast cancer.

Methods

We obtained clinicopathological data and overall survival information on 1,069 breast cancer patients from The Cancer Genome Atlas (TCGA). Computational algorithms and CIBERSORT were used to estimate immune cell infiltration. Additionally, xCell was used for validation.

Results

Th2 high tumors did not consistently associate with an unfavorable immune cell composition and tumor immune microenvironment but were found to be significantly elevated in the cancer stage. Th2 high tumors also correlated with high Nottingham pathological grade, as well as with Ki-67 and proliferation score in ER-positive subtypes. High Th2 tumors achieved a pathological complete response (pCR) significantly higher in ER-positive breast cancer.

Conclusions

In conclusion, high levels of Th2 are associated with aggressive features of breast cancer. Th2 levels may be a biomarker in patient selection for NAC in ER-positive breast cancer.

The Impact of Immunofunctional Phenotyping on the Malfunction of the Cancer Immunity Cycle in Breast Cancer

Simple Summary

The cancer-immunity cycle (CIC) is a series of self-sustaining stepwise events to fight cancer growth by the immune system. We hypothesized that immunofunctional phenotyping that represent the malfunction of the CIC is clinically relevant in breast cancer (BC) utilizing total of 2979 BC cases; 1075 from TCGA cohort, 1904 from METABRIC cohort were analyzed. The immunofunctional phenotype was classified as follows: hot T-cell infiltrated, high immune cytolytic activity (CYT), cold T-cell infiltrated, high frequency of CD8+ T cells and low CYT, and non-inflamed, low frequency of CD8+ T cells and low CYT. We demonstrated that immunofunctional phenotyping not only indicated the degree of anti-cancer immune dysfunction, but also served as a prognostic biomarker and HTI was inversely related to estrogen response.

Abstract

The cancer-immunity cycle (CIC) is a series of self-sustaining stepwise events to fight cancer growth by the immune system. We hypothesized that immunofunctional phenotyping that represent the malfunction of the CIC is clinically relevant in breast cancer (BC). Total of 2979 BC cases; 1075 from TCGA cohort, 1904 from METABRIC cohort were analyzed. The immunofunctional phenotype was classified as follows: hot T-cell infiltrated (HTI), high immune cytolytic activity (CYT), Cold T-cell infiltrated (CTI), high frequency of CD8+ T cells and low CYT, and non-inflamed, low frequency of CD8+ T cells and low CYT. The analysis of tumor immune microenvironment in the immunofunctional phenotype revealed that not only immunostimulatory factors, but also immunosuppressive factors were significantly elevated and immunosuppressive cells were significantly decreased in HTI. Patients in HTI were significantly associated with better survival in whole cohort and patients in CTI were significantly associated with worse survival in triple negative. Furthers, HTI was inversely related to estrogen responsive signaling. We demonstrated that immunofunctional phenotype not only indicated the degree of anti-cancer immune dysfunction, but also served as a prognostic biomarker and HTI was inversely related to estrogen response.

An Immune Gene-Related Five-lncRNA Signature for to Predict Glioma Prognosis

Background

The tumor immune microenvironment is closely related to the malignant progression and treatment resistance of glioma. Long non-coding RNA (lncRNA) plays a regulatory role in this process. We investigated the pathological mechanisms within the glioma microenvironment and potential immunotherapy resistance related to lncRNAs.

Method

We downloaded datasets derived from glioma patients and analyzed them by hierarchical clustering. Next, we analyzed the immune microenvironment of glioma, related gene expression, and patient survival. Coexpressed lncRNAs were analyzed to generate a model of lncRNAs and immune-related genes. We analyzed the model using survival and Cox regression. Then, univariate, multivariate, receiver operating characteristic (ROC), and principle component analysis (PCA) methods were used to verify the accuracy of the model. Finally, GSEA was used to evaluate which functions and pathways were associated with the differential genes.

Results

Normal brain tissue maintains a low-medium immune state, and gliomas are clearly divided into three groups (low to high immunity). The stromal, immune, and estimate scores increased along with immunity, while tumor purity decreased. Further, human leukocyte antigen (HLA), programmed cell death-1 (PDL1), T cell immunoglobulin and mucin domain 3 (TIM-3), B7-H3, and cytotoxic T lymphocyte-associated antigen-4 (CTLA4) expression increases concomitantly with immune state, and the patient prognosis worsens. Five immune gene-related lncRNAs (AP001007.1, LBX-AS1, MIR155HG, MAPT-AS1, and LINC00515) were screened to construct risk models. We found that risk scores are related to patient prognosis and clinical characteristics, and are positively correlated with PDL1, TIM-3, and B7-H3 expression. These lncRNAs may regulate the tumor immune microenvironment through cytokine-cytokine receptor interactions, complement, and coagulation cascades, and may promote CD8 + T cell, regulatory T cell, M1 macrophage, and infiltrating neutrophils activity in the high-immunity group. In vitro, the abnormal expression of immune-related lncRNAs and the relationship between risk scores and immune-related indicators (PDL1, CTLA4, CD3, CD8, iNOS) were verified by q-PCR and immunohistochemistry (IHC).

Conclusion

For the first time, we constructed immune gene-related lncRNA risk models. The risk score may be a new biomarker for tumor immune subtypes and provide molecular targets for glioma immunotherapy.

Suppression of tumor immune microenvironment via microRNA-1 after epidermal growth factor receptor-tyrosine kinase inhibitor resistance acquirement in lung adenocarcinoma

Immunotherapy is considered one of the most important therapeutic strategies for patients with lung adenocarcinoma after the development of epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) resistance. However, useful predictors of immunotherapy for these patients has not been examined well, although the status of the tumor immune microenvironment (TIME), including programmed death-ligand 1 expression and lymphocyte infiltration, has been generally known to provide predictive markers for the efficacy of immunotherapy. This study aimed to clarify novel predictors of immunotherapy following EGFR-TKI resistance in lung adenocarcinoma, especially regarding micro RNA (miRNA). We evaluated the correlation between EGFR-TKI resistance and lymphocyte infiltration, before and after acquiring EGFR-TKI resistance, in 21 cases of lung adenocarcinoma, and further explored this by in vitro studies, using miRNA PCR arrays. Subsequently, we transfected miRNA-1 (miR-1), the most variable miRNA in this array, into three kinds of lung cancer cells, and examined the effects of miR-1 on EGFR-TKI sensitivity, cytokine expression and lymphocyte migration. Histopathological examination demonstrated that infiltration levels of CD8-positive T cells were significantly decreased after development of EGFR-TKI resistance. In vitro studies revealed that miR-1 significantly inhibited EGFR-TKI effect and induction of cytokines, such as C-C motif chemokine ligand 5 and C-X-C motif chemokine ligand 10, causing inhibition of monocyte migration. These results indicate that the upregulated miR-1 might suppress the TIME, following development of EGFR-TKI resistance. Therefore, miR-1 could be a clinically useful marker to predict therapeutic efficacy of immunotherapy in lung adenocarcinoma patients with EGFR-TKI resistance.

T lymphocytes in hepatocellular carcinoma immune microenvironment: insights into human immunology and immunotherapy

Hepatocellular carcinoma (HCC) is characterized by poor outcome and shows limited drug-response in clinical trials. Tumor immune microenvironment (TIME) exerts a strong selection pressure on HCC, leading to HCC evolvement and recurrence after multiple therapies. T cell-mediated immunoreaction during cancer surveillance and clearance is central in cancer immunity. Heterogenous T cell subsets play multiple roles in HCC development and progression. The re-educated T cells in TIME usually lead to deteriorated T cell response and tumor progression. Investigation into immune system dysregulation during HCC development will shed light on how to turn immune suppressive state to immune activation and induce more efficient immune response. Emerging T cell-based treatment such as cancer vaccines, CAR-T cell therapy, adoptive cell therapy, and immune checkpoint inhibitors (ICIs), have been proved to cause tumor regression in some clinical and preclinical trials. In this review, we focused on recent studies that explored T cells involved in HCC and how they affect the course of disease. We also briefly outlined current T cell-based immunotherapies in HCC.

Alteration of tumor-associated macrophage subtypes mediated by KRT6A in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is severely affecting the health and lives of patients. Clarifying the composition and regulatory factors of tumor immune microenvironment (TIME) is helpful for the treatment of PDAC. We analyzed the unique TIMEs and gene expression patterns between PDAC and adjacent normal tissue (ANT) using Gene Expression Omnibus (GEO) to find new immunotherapy targets. The Cancer Genome Atlas (TCGA) datasets were used to elucidate the possible mechanism of which tumor-associated macrophages (TAMs) changed in PDAC. We found that the composition of TAMs subtypes, including M0, M1, and M2, was different between PDAC and ANT, which was validated in recently published single-cell RNA-seq data. Many immune cells interacted with each other to affect the TIME. There were many DEGs enriched in some pathways that could potentially change the immune cell composition. KRT6A was found to be a DEG between PDAC and ANT that overlapped with DEGs between the M0-high group and the M0-low group in TCGA datasets, and it might alter and regulate TAMs via a collection of genes including COL5A2, COL1A2, MIR3606, SPARC, and COL6A3. TAMs, which could be a target of immunotherapy, might be influenced by genes through KRT6A and indicate an undesirable prognosis in PDAC.

Emerging Role of Immunotherapy for Colorectal Cancer with Liver Metastasis

Colorectal cancer (CRC) is the third most common malignant tumor in the world and the second leading cause of cancer-related deaths, with the liver as the most common site of distant metastasis. The prognosis of CRC with liver metastasis is poor, and most patients cannot undergo surgery. In addition, conventional antitumor approaches such as chemotherapy, radiotherapy, targeted therapy, and surgery result in unsatisfactory outcomes. In recent years, immunotherapy has shown good prospects in the treatment of assorted tumors by enhancing the host's antitumor immune function, and it may become a new effective treatment for liver metastasis of CRC. However, challenges remain in applying immunotherapy to CRC with liver metastasis. This review examines how the microenvironment and immunosuppressive landscape of the liver favor tumor progression. It also highlights the latest research advances in immunotherapy for colorectal liver metastasis and identifies immunotherapy as a treatment regimen with a promising future in clinical applications.

Tumor Derived SIGLEC Family Genes May Play Roles in Tumor Genesis, Progression, and Immune Microenvironment Regulation

Background

SIGLEC family genes can also be expressed on tumor cells in different cancer types, and though it has been found that SIGLEC genes expressed by immune cells can be exploited by tumors to escape immune surveillance, functions of tumor derived SIGLEC expression in tumor microenvironment (TME) were barely investigated, which could play roles in cancer patients' survival.

Methods

Using bioinformatic analysis, mutation status of SIGLEC family genes was explored through the cBioPortal database, and expression of them in different tumors was explored through the UALCAN database. The GEPIA database was used to compare SIGLEC family genes' mRNA between cancers and to generate a highly correlated gene list in tumors. A KM-plotter database was used to find the association between SIGLEC genes and survival of patients. The associations between SIGLEC family genes' expression, immune infiltration, and immune regulators' expression in TME were generated and examined by the TIMER 2.0 database; the differential fold changes of SIGLEC family genes in specific oncogenic mutation groups of different cancer types were also yielded by TIMER 2.0. The networks of SIGLEC family genes and highly correlated genes were constructed by the STRING database, and gene ontology and pathway annotation of SIGLEC family highly correlated genes were performed through the DAVID database.

Results

SIGLEC family genes were highly mutated and amplified in melanoma, endometrial carcinoma, non-small cell lung cancer, bladder urothelial carcinoma, and esophagogastric adenocarcinoma, while deep deletion of SIGLEC family genes was common in diffuse glioma. Alteration of SIGLEC family genes demonstrated different levels in specific tumors, and oncogenic mutation in different cancer types could influence SIGLEC family genes' expression. Most SIGLEC family genes were related to patients' overall survival and progression free survival. Also, tumor derived SIGLEC family genes were related to tumor immune cell infiltration and may regulate TME by influencing chemokine axis.

Conclusion

Our computational analysis showed SIGLEC family genes expressed by tumor cells were associated with tumor behaviors, and they may also influence TME through chemokine axis, playing vital roles in patients' survival. Further experiments targeting tumor derived SIGLEC family genes are needed to confirm their influences on tumor growth, metastasis, and immune environment regulation.

Prognostic value of intratumoral lymphocyte-to-monocyte ratio and M0 macrophage enrichment in tumor immune microenvironment of melanoma

Skin cutaneous melanoma is characterized by significant heterogeneity in its molecular, genomic and immunologic features. Whole transcriptome RNA sequencing data from The Cancer Genome Atlas of skin cutaneous melanoma (n = 328) was utilized. CIBERSORT was used to identify immune cell type composition, on which unsupervised hierarchical clustering was performed. Analysis of overall survival was performed using Kaplan–Meier estimates and multivariate Cox regression analyses. Membership in the lymphocyte:monocyte^low, monocyte^high and M0^high cluster was an independently poor prognostic factor for survival (HR: 3.03; 95% CI: 1.12–8.20; p = 0.029) and correlated with decreased predicted response to immune checkpoint blockade. In conclusion, an M0-macrophage-enriched, lymphocyte-to-monocyte-ratio-low phenotype in the primary melanoma tumor site independently characterizes an aggressive phenotype that may differentially respond to treatment.

Analysis of Spatial Organization of Suppressive Myeloid Cells and Effector T Cells in Colorectal Cancer-A Potential Tool for Discovering Prognostic Biomarkers in Clinical Research

The development and progression of solid tumors such as colorectal cancer (CRC) are known to be affected by the immune system and cell types such as T cells, natural killer (NK) cells, and natural killer T (NKT) cells are emerging as interesting targets for immunotherapy and clinical biomarker research. In addition, CD3⁺ and CD8⁺ T cell distribution in tumors has shown positive prognostic value in stage I–III CRC. Recent developments in digital computational pathology support not only classical cell density based tumor characterization, but also a more comprehensive analysis of the spatial cell organization in the tumor immune microenvironment (TiME). Leveraging that methodology in the current study, we tried to address the question of how the distribution of myeloid derived suppressor cells in TiME of primary CRC affects the function and location of cytotoxic T cells. We applied multicolored immunohistochemistry to identify monocytic (CD11b⁺CD14⁺) and granulocytic (CD11b⁺CD15⁺) myeloid cell populations together with proliferating and non-proliferating cytotoxic T cells (CD8⁺Ki67^+/–). Through automated object detection and image registration using HALO software (IndicaLabs), we applied dedicated spatial statistics to measure the extent of overlap between the areas occupied by myeloid and T cells. With this approach, we observed distinct spatial organizational patterns of immune cells in tumors obtained from 74 treatment-naive CRC patients. Detailed analysis of inter-cell distances and myeloid-T cell spatial overlap combined with integrated gene expression data allowed to stratify patients irrespective of their mismatch repair (MMR) status or consensus molecular subgroups (CMS) classification. In addition, generation of cell distance-derived gene signatures and their mapping to the TCGA data set revealed associations between spatial immune cell distribution in TiME and certain subsets of CD8⁺ and CD4⁺ T cells. The presented study sheds a new light on myeloid and T cell interactions in TiME in CRC patients. Our results show that CRC tumors present distinct distribution patterns of not only T effector cells but also tumor resident myeloid cells, thus stressing the necessity of more comprehensive characterization of TiME in order to better predict cancer prognosis. This research emphasizes the importance of a multimodal approach by combining computational pathology with its detailed spatial statistics and gene expression profiling. Finally, our study presents a novel approach to cancer patients’ characterization that can potentially be used to develop new immunotherapy strategies, not based on classical biomarkers related to CRC biology.

The Expression Pattern and Clinical Significance of the Immune Checkpoint Regulator VISTA in Human Breast Cancer

Background

Immunotherapies targeting CTLA-4 and PD-1 have elicited promising responses in a variety of cancers. However, the relatively low response rates warrant the identification of additional immunosuppressive pathways. V domain immunoglobulin suppressor of T cell activation (VISTA) plays a critical role in antitumor immunity and is a valuable target in cancer immunotherapy.

Methods

Here, we used single-cell RNA-seq to analyze the gene expression levels of 14897 cells from a breast cancer sample and its paired 7,320 normal cells. Then, we validated the protein expression of immune checkpoint molecules (VISTA, PD-1, PD-L1, TIGIT, TIM3, and LAG3) in 324 human breast cancer samples by immunohistochemistry and quantitative immunofluorescence (QIF) approaches.

Results

Single cell RNA-seq results show a higher level of immune checkpoint VISTA expression in breast cancer tissue compared to adjacent normal tissue. We also found that VISTA expressed highest in breast cancer tissue than other immune-checkpoints. Immunohistochemical results showed that VISTA was detected with a membranous/cytoplasmic staining pattern in intratumoral immune cells and breast cancer cells. Additionally, VISTA was positively correlated with pathological grade, lymph node status and the levels of PD-1 according to the chi-square test or Fisher’s test. Furthermore, VISTA expression was higher in CD68+ tumor-associated macrophages (TAMs) than in CD4+ T cells, CD8+ cytotoxic T cells or CD20+ B cells.

Conclusions

These findings therefore support the immunoregulatory role of VISTA in breast cancer and indicate that targeting VISTA may benefit breast cancer immunotherapy.

Equine Penile Squamous Cell Carcinomas as a Model for Human Disease: A Preliminary Investigation on Tumor Immune Microenvironment

Penile squamous cell carcinomas (SCCs) are common tumors in older horses, with poor prognosis mostly due to local invasion and recurrence. These tumors are thought to be mainly caused by Equus caballus papillomavirus type 2 (EcPV-2). The aim of this study is to characterize the tumor immune environment (TIME) in equine penile tumors. Equine penile epithelial tumors (17 epSCCs; 2 carcinomas in situ, CIS; 1 papilloma, P) were retrospectively selected; immune infiltrate was assessed by histology and immunohistochemistry; RT-qPCR tested the expression of selected chemokines and EcPV-2 DNA and RNA. The results confirmed EcPV-2-L1 DNA in 18/20 (90%) samples. L1 expression was instead retrieved in 13/20 cases (65%). The samples showed an increased infiltration of CD3⁺lymphocytes, macrophages (MAC387; IBA1), plasma cells (MUM1), and FoxP3⁺lymphocytes in the intra/peritumoral stroma when compared to extratumoral tissues (p < 0.05). Only MAC387⁺neutrophils were increased in EcPV-2^high viral load samples (p < 0.05). IL12/p35 was differentially expressed in EcPV^high and EcPV^low groups (p = 0.007). A significant decrease of IFNG and IL2 expression was highlighted in TGFB1-positive samples (p < 0.05). IBA1 and CD20 were intratumorally increased in cases where IL-10 was expressed (p < 0.005). EpSCCs may represent a good spontaneous model for the human counterpart. Further prospective studies are needed in order to confirm these preliminary results.

Immune Microenvironment Related Competitive Endogenous RNA Network as Powerful Predictors for Melanoma Prognosis Based on WGCNA Analysis

Cutaneous melanoma is the most life-threatening skin malignant tumor due to its increasing metastasis and mortality rate. The abnormal competitive endogenous RNA network promotes the development of tumors and becomes biomarkers for the prognosis of various tumors. At the same time, the tumor immune microenvironment (TIME) is of great significance for tumor outcome and prognosis. From the perspective of TIME and ceRNA network, this study aims to explain the prognostic factors of cutaneous melanoma systematically and find novel and powerful biomarkers for target therapies. We obtained the transcriptome data of cutaneous melanoma from The Cancer Genome Atlas (TCGA) database, 3 survival-related mRNAs co-expression modules and 2 survival-related lncRNAs co-expression modules were identified through weighted gene co-expression network analysis (WCGNA), and 144 prognostic miRNAs were screened out by univariate Cox proportional hazard regression. Cox regression model and Kaplan-Meier survival analysis were employed to identify 4 hub prognostic mRNAs, and the prognostic ceRNA network consisting of 7 lncRNAs, 1 miRNA and 4 mRNAs was established. After analyzing the composition and proportion of total immune cells in cutaneous melanoma microenvironment through CIBERSORT algorithm, it is found through correlation analysis that lncRNA-TUG1 in the ceRNA network was closely related to the TIME. In this study, we first established cutaneous melanoma’s TIME-related ceRNA network by WGCNA. Cutaneous melanoma prognostic markers have been identified from multiple levels, which has important guiding significance for clinical diagnosis, treatment, and further scientific research on cutaneous melanoma.

Ceramide Pathway Regulators Predict Clinical Prognostic Risk and Affect the Tumor Immune Microenvironment in Lung Adenocarcinoma

Purpose

The ceramide pathway is strongly associated with the regulation of tumor proliferation, differentiation, senescence, and apoptosis. This study aimed to explore the gene signatures, prognostic value, and immune-related effects of ceramide-regulated genes in lung adenocarcinoma (LUAD).

Methods

Public datasets of LUAD from The Cancer Genome Atlas and Gene Expression Omnibus were selected. Consensus clustering was adopted to classify LUAD patients, and a least absolute shrinkage and selection operator (LASSO) regression model was employed to develop a prognostic risk signature. CIBERSORT algorithm was used to estimate the association between the risk signature and the tumor immune microenvironment.

Results

Most of the 22 ceramide-regulated genes were differentially expressed between LUAD and normal samples. LUAD patients were classified into two subgroups (cluster 1 and 2) and cluster 2 was associated with a poor prognosis. Furthermore, a prognostic risk signature was developed based on the three ceramide-regulated genes, Cytochrome C (CYCS), V-rel reticuloendotheliosis viral oncogene homolog A (RELA) and Fas-associated via death domain (FADD). LUAD patients with low- and high-risk scores differed concerning the subtypes of tumor-infiltrating immune cells. A moderate to weak correlation was observed between the risk score and tumor-infiltrating immune cells.

Conclusions

Ceramide-regulated genes could predict clinical prognostic risk and affect the tumor immune microenvironment in LUAD.

Tumor Immune Microenvironments (TIMEs): Responsive Nanoplatforms for Antitumor Immunotherapy

Interest in cancer immunotherapy has rapidly risen since it offers many advantages over traditional approaches, such as high efficiency and prevention of metastasis. Efforts have primarily focused on two major strategies for regulating the body's antitumor immune response mechanisms: “enhanced immunotherapy” that aims to amplify the immune activation, and “normalized immunotherapy” that corrects the defective immune mechanism in the tumor immune microenvironments (TIMEs), which returns to the normal immune trajectory. However, due to the complexity and heterogeneity of the TIMEs, and lack of visualization research on the immunotherapy process, cancer immunotherapy has not been widely used in clinical setting. Recently, through the design and modification of nanomaterials, intelligent TIME-responsive nanoplatforms were developed from which encouraging results in many aspects of immunotherapy have been achieved. In this mini review, the status of designed nanomaterials for nanoplatform-based immune regulation of TIMEs has been emphasized, particularly with respect to the aforementioned approaches. It is envisaged that future prospects will focus on a combination of multiple immunotherapies for more efficient cancer inhibition and elimination.

TRIM28 is a distinct prognostic biomarker that worsens the tumor immune microenvironment in lung adenocarcinoma

The tumor immune microenvironment (TIME) is an important determinant of cancer prognosis and treatment efficacy. To identify immune-related prognostic biomarkers of lung adenocarcinoma, we used the ESTIMATE algorithm to calculate the immune and stromal scores of 517 lung adenocarcinoma patients from The Cancer Genome Atlas (TCGA). We detected 985 differentially expressed genes (DEGs) between patients with high and low immune and stromal scores, and we analyzed their functions and protein-protein interactions. TRIM28 was upregulated in lung adenocarcinoma patients with low immune and stromal scores, and was associated with a poor prognosis. The TISIDB and TIMER databases indicated that TRIM28 expression correlated negatively with immune infiltration. We then explored genes that were co-expressed with TRIM28 in TCGA, and investigated DEGs based on TRIM28 expression in GSE43580 and GSE7670. The 429 common DEGs from these analyses were functionally analyzed. We also performed a Gene Set Enrichment Analysis using TCGA data, and predicted substrates of TRIM28 using UbiBrowser. The results indicated that TRIM28 may negatively regulate the TIME by increasing the SUMOylation of IRF5 and IRF8. Correlation analyses and validations in two lung adenocarcinoma cell lines (PC9 and H1299) confirmed these findings. Thus, TRIM28 may worsen the TIME and prognosis of lung adenocarcinoma.

Abundance of Regulatory T Cell (Treg) as a Predictive Biomarker for Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer

Simple Summary

Regulatory CD4⁺ T cell (Treg) is one of the suppressive immune cells, but data on its clinical relevance in large human breast cancer cohort is limited. Abundance of Tregs in 5177 breast cancer patient samples from five independent cohorts was analyzed by the xCell algorithm using tumor transcriptomics. Treg abundance was lower in metastatic tumors when compared to matched primary tumors. Treg was associated with a high mutation rate of TP53 genes and copy number mutations as well as with increased tumor infiltration of M2 macrophages and decreased infiltration of T helper type 1 cells. Interestingly, low Treg abundance was significantly associated with pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) in TNBC, but not in ER-positive/Her2-negative subtype. Abundance of Treg was also associated with high expression of multiple immune checkpoint molecules. In conclusion, Treg abundance may have a potential as a predictive biomarker of pCR after NAC in TNBC.

Abstract

Regulatory CD4⁺ T cell (Treg), a subset of tumor-infiltrating lymphocytes (TILs), are known to suppress anticancer immunity but its clinical relevance in human breast cancer remains unclear. In this study, we estimated the relative abundance of Tregs in breast cancer of multiple patient cohorts by using the xCell algorithm on bulk tumor gene expression data. In total, 5177 breast cancer patients from five independent cohorts (TCGA-BRCA, GSE96058, GSE25066, GSE20194, and GSE110590) were analyzed. Treg abundance was not associated with cancer aggressiveness, patient survival, or immune activity markers, but it was lower in metastatic tumors when compared to matched primary tumors. Treg was associated with a high mutation rate of TP53 genes and copy number mutations as well as with increased tumor infiltration of M2 macrophages and decreased infiltration of T helper type 1 (Th1) cells. Pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) was significantly associated with low Treg abundance in triple negative breast cancer (TNBC) but not in ER-positive/Her2-negative subtype. High Treg abundance was significantly associated with high tumor expression of multiple immune checkpoint inhibitor genes. In conclusion, Treg abundance may have potential as a predictive biomarker of pCR after NAC in TNBC.

Cis- and Trans-Acting Expression Quantitative Trait Loci of Long Non-Coding RNA in 2,549 Cancers With Potential Clinical and Therapeutic Implications

Many cancer risk loci act as expression quantitative trait loci (eQTLs) of transcripts including non-coding RNA. Long non-coding RNAs (lncRNAs) are implicated in various human cancers. However, the pathological and clinical impacts of the genetic determinants of lncRNAs in cancers remain largely unknown. In this study, we performed eQTL mapping of lncRNA expression (elncRNA) in 11 TCGA cancer types and characterized the biological processes of elncRNAs in the setting of genomic location, cancer treatment responses, and immune microenvironment. As a result, 10.86% of the cis-eQTLs and 1.67% of the trans-eQTLs of lncRNA were related to known genome-wide association studies (GWAS) cancer risk loci. The elncRNAs are significantly enriched for those which are previously annotated as predictive of drug sensitivities in cancer cell lines. We further revealed the downstream transcriptomic effectors of eQTL-elncRNA pairs. Our data specifically suggested that the genes affected by eQTL-elncRNA associations are enriched in the immune system processes and eQTL-elncRNA associations influence the constitution of tumor infiltrating lymphocytes. In ovarian cancer, the "rs34631313-AC092580.4" pair was associated with increased fraction of CD8+ T cells and M1 Macrophage; whereas in KIRC, the "rs9546285-LINC00426" pair was associated with increased fraction of CD8+ T cells and a decreased fraction of M2 macrophages. Our findings provide a systematic view of the transcriptomic impacts of the eQTL landscape of lncRNA in human cancers and suggest its strong potential relevance to cancer immunity and treatment.

Establishment of the Prognostic Index Reflecting Tumor Immune Microenvironment of Lung Adenocarcinoma Based on Metabolism-Related Genes

Background: The incidence of lung adenocarcinoma (LUAD) increased substantially in recent years. A systematic investigation of the metabolic genomics pattern is critical to improve the treatment and prognosis of LUAD. This study aimed to analyze the relationship between tumor microenvironment (TME) and metabolism-related genes of LUAD.

Methods: The data was extracted from TCGA and GEO datasets. The metabolism-related gene expression profile and the corresponding clinical data of LUAD patients were then integrated. The survival-related genes were screened out using univariate COX regression and lasso regression analysis. The latent properties and molecular mechanisms of these LUAD-specific metabolism-related genes were investigated by computational biology.

Results: A novel prognostic model was established based on 8 metabolism-related genes, including TYMS, ALDH2, PKM, GNPNAT1, LDHA, ENTPD2, NT5E, and MAOB. The immune infiltration of LUAD was also analyzed using CIBERSORT algorithms and TIMER database. In addition, the high- and low-risk groups exhibited distinct layout modes in the principal component analysis.

Conclusions: In summary, our studies identified clinically significant metabolism-related genes, which were potential signature for LUAD diagnosis, monitoring, and prognosis.

Decoding cancer's camouflage: epithelial-mesenchymal plasticity in resistance to immune checkpoint blockade

Epithelial-mesenchymal plasticity (EMP) of cancer cells contributes to cancer cell heterogeneity, and it is well established that EMP is a critical determinant of acquired resistance to cancer treatment modalities including radiation therapy, chemotherapy, and targeted therapies. Here, we aimed to explore how EMP contributes to cancer cell camouflage, allowing an ever-changing population of cancer cells to pass under the radar of our immune system and consequently compromise the effect of immune checkpoint blockade therapies. The ultimate clinical benefit of any combination regimen is evidenced by the sum of the drug-induced alterations observed in the variety of cellular populations composing the tumor immune microenvironment. The finely-tuned molecular crosstalk between cancer and immune cells remains to be fully elucidated, particularly for the spectrum of malignant cells along the epithelial to mesenchymal axis. High-dimensional single cell analyses of specimens collected in ongoing clinical studies is becoming a key contributor to our understanding of these interactions. This review will explore to what extent targeting EMP in combination with immune checkpoint inhibition represents a promising therapeutic avenue within the overarching strategy to reactivate a halting cancer-immunity cycle and establish a robust host immune response against cancer cells. Therapeutic strategies currently in clinical development will be discussed.

Prognostic significance of spatial immune profiles in human solid cancers

Immune-based tumor characteristics in the context of tumor heterogeneity are associated with suppression as well as promotion of cancer progression in various tumor types. As immunity typically functions based on intercellular contacts and short-distance cytokine communications, the location and spatial relationships of the tumor immune microenvironment can provide a framework to understand the biology and potential predictive biomarkers related to disease outcomes. Immune spatial analysis is a newly emerging form of cancer research based on recent methodological advances in in situ single-cell analysis, where cell-cell interaction and the tissue architecture can be analyzed in relation to phenotyping the tumor immune heterogeneity. Spatial characteristics of tumors can be stratified into the tissue architecture level and the single-cell level. At the tissue architecture level, the prognostic significance of the density of immune cell lineages, particularly T cells, is leveraged by understanding longitudinal changes in cell distribution in the tissue architecture such as intra-tumoral and peri-tumoral regions, and invasive margins. At the single-cell level, the proximity of the tumor to the immune cells correlates with disease aggressiveness and therapeutic resistance, providing evidence to understand biological interactions and characteristics of the tumor immune microenvironment. In this review, we summarize recent findings regarding spatial information of the tumor immune microenvironment and review advances and challenges in spatial single-cell analysis toward developing tissue-based biomarkers rooted in the immune spatial landscape.

ATOH8 overexpression inhibits the tumor progression and monocyte chemotaxis in hepatocellular carcinoma

OBJECTIVE

ATOH8 is reported to be associated with the progression of many tumors; however, there are remaining controversies. The aim of this study is to explore the role of ATOH8 in hepatocellular carcinoma (HCC) and its effect on monocyte chemotaxis.

METHODS

Bioinformatics analysis was performed based on the LIHC data in GEPIA and LinkedOmic. Fresh human liver cancer and adjacent nontumor tissue specimens were collected at the Shanghai Public Health Clinical Center. qRT-PCR was performed to determine the transcript level, and western blot analysis and ELISA were used to detect protein expression. CCK8, colony formation, wound-healing, Transwell migration and invasion assays were performed to examine cell proliferation, migration and invasion. An HCC xenograft mouse model was used to determine oncogenicity in vivo. Cell apoptosis and related markers were detected by flow cytometry. Additionally, chemotaxis was assessed by the Transwell migration assay.

RESULTS

ATOH8 expression is downregulated in HCC tissue and hepatoma cell lines. High expression of ATOH8 predicts a favorable prognosis. Overexpression of ATOH8 in liver cancer cells inhibits proliferation, migration and invasion in vitro, and tumor progression in nude mice. Knockdown of ATOH8 promotes proliferation of Huh7 and EMT-related proteins. Overexpression of ATOH8 increases chemosensitivity to 5-FU, which is probably caused by inhibiting the phosphorylation of AKT (Ser473). Furthermore, overexpression of ATOH8 in Huh7 reduced MCP1 to inhibit chemotactic THP-1, and promoted antitumor inflammatory cytokine (TNF-α and IFN-γ) secretion in monocytes.

CONCLUSION

In addition to the intrinsic oncosuppressive function of ATOH8 in the liver, ATOH8 may modulate the microenvironment to create an immune activation state. This may partly be attributed to ATOH8 inhibition of the monocyte recruitment via suppressing MCP1 expression so as to promote antitumor inflammatory cytokine secretion in monocytes.

Complement C7 (C7), a Potential Tumor Suppressor, Is an Immune-Related Prognostic Biomarker in Prostate Cancer (PC)

Objectives: Prostate cancer (PC) is the second most frequent tumor in men, which has a high recurrence rate and poor prognosis. Therefore, this study aimed to identify novel prognostic biomarkers and therapeutic targets for immunotherapy and small molecule drugs for PC treatment.

Materials and Methods: The Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) algorithm was applied to calculate immune scores and stromal scores of TCGA-PRAD data. Differentially expressed genes (DEGs) were identified using R package “limma.” GO, KEGG, and DO analyses were performed to analyze DEGs. Overall survival and disease-free survival analyses were conducted for hub gene identification. To validate the hub gene at the mRNA and protein expression levels, genetic alterations were measured, and CCLE and Cox regression analyses were performed. Connectivity map (CMap) analysis and GSEA were performed for drug exploration and function analysis, respectively.

Results: Immune scores ranged from −1795.98 to 2339.39, and stomal scores ranged from −1877.60 to 1659.96. In total, 45 tumor microenvironment (TME)-related DEGs were identified, of which Complement C7 (C7) was selected and validated as a hub gene. CMap analysis identified six small molecule drugs as potential agents for PC treatment. Further analysis demonstrated that C7 expression was significantly correlated with clinical T, pathological N, and immune infiltration level.

Conclusions: In conclusion, of the 45 TME-related DEGs, C7 was shown to correlate with PC prognosis in patients, indicating it as a novel prognostic biomarker and immunotherapy target in PC. Additionally, six small molecule drugs showed strong therapeutic potential for PC treatment.

Comprehensive Study of Tumor Immune Microenvironment and Relevant Genes in Hepatocellular Carcinoma Identifies Potential Prognostic Significance

Background: The tumor immune microenvironment (TIME) is an external immune system that regulates tumorigenesis. However, cellular interactions involving the TIME in hepatocellular carcinoma (HCC) are poorly characterized.

Methods: In this study, we used multidimensional bioinformatic methods to comprehensively analyze cellular TIME characteristics in 735 HCC patients. Additionally, we explored associations involving TIME molecular subtypes and gene types and clinicopathological features to construct a prognostic signature.

Results: Based on their characteristics, we classified TIME and gene signatures into three phenotypes (TIME T1–3) and two gene clusters (Gene G1–2), respectively. Further analysis revealed that Gene G1 was associated with immune activation and surveillance and included CD8⁺ T cells, natural killer cell activation, and activated CD4⁺ memory T cells. In contrast, Gene G2 was characterized by increased M0 macrophage and regulatory T cell levels. After calculation of principal component algorithms, a TIME score (TS) model, including 78 differentially expressed genes, was constructed based on TIME phenotypes and gene clusters. Furthermore, we observed that the Gene G2 cluster was characterized by high TS, and Gene G1 was characterized by low TS, which correlated with poor and favorable prognosis of HCC, respectively. Correlation analysis showed that TS had a positive association with several clinicopathologic signatures [such as grade, stage, tumor (T), and node (N)] and known somatic gene mutations (such as TP53 and CTNNB1). The prognostic value of the TS model was verified using external data sets.

Conclusion: We constructed a TS model based on differentially expressed genes and involving immune phenotypes and demonstrated that the TS model is an effective prognostic biomarker and predictor for HCC patients.

CD8 T Cell Score as a Prognostic Biomarker for Triple Negative Breast Cancer

CD8 T cell is an essential component of tumor-infiltrating lymphocytes (TIL) and tumor immune microenvironment (TIME). Using the xCell CD8 T cell score of whole tumor gene expression data, we estimated these cells in total of 3837 breast cancer patients from TCGA, METABRIC and various GEO cohorts. The CD8 score correlated strongly with expression of CD8 genes. The score was highest for triple-negative breast cancer (TNBC), and a high score was associated with high tumor immune cytolytic activity and better survival in TNBC but not other breast cancer subtypes. In TNBC, tumors with a high CD8 score had enriched expression of interferon (IFN)-α and IFN-γ response and allograft rejection gene sets, and greater infiltration of anti-cancerous immune cells. The score strongly correlated with CD4 memory T cells in TNBC, and tumors with both a high CD8 score and high CD4 memory T cell abundance had significantly better survival. Finally, a high CD8 score was significantly associated with high expression of multiple immune checkpoint molecules. In conclusion, a high CD8 T cell score is associated with better survival in TNBC, particularly when tumor CD4 memory T cells were elevated. Our findings also suggest a possible use of the score as a predictive biomarker for response to immune checkpoint therapy.

Identification and validation of the prognostic value of immune-related genes in non-small cell lung cancer

Immune-related genes play a significant role in predicting the overall survival and monitoring the status of the cancer immune microenvironment. The aim of this research study was to identify differentially expressed immune-related genes (DEIRGs) and establish a Cox prediction model for the evaluation of prognosis in patients with non-small cell lung cancer (NSCLC). Transcription expression data, immune gene data, and tumor transcription factor data from The Cancer Genome Atlas (TCGA), the Immunology Database and Analysis Portal, and the Cistrome Cancer database were analyzed to detect differentially expressed genes (DEGs), DEIRGs, and differentially expressed transcription factors (DETFs). Multivariate Cox regression analysis was used to obtain potential DEIRGs as independent prognostic factors. Oncomine, The Human Protein Atlas (HPA), TIMER databases were performed to validate the mRNA and protein expression level of DEIRGs. TIMER database was performed to explore the immunocytes infiltration of DEIRGs. In total, 7448 DEGs, 536 DEIRGs, 87 DETFs were identified from 1,037 NSCLC tissues and 108 normal tissues in TCGA database. Fifteen-DEIRG signatures (THBS1, S100P, S100A16, DLL4, CD70, DKK1, IL33, NRTN, PDGFB, STC2, VGF, GCGR, HTR3A, LGR4, SHC3) could be perceived as independent prognostic factors for predicting the overall survival of patients with NSCLC (P = 4.89e--09). Immune cell correlation analysis showed that neutrophils and b cells were positively and negatively correlated with the riskscore of the prediction model, respectively. Our study identified a Cox prediction model based on DEIRGs to predict the overall survival of patients with NSCLC. The immunocyte infiltration analysis provided a novel horizon for monitoring the status of the NSCLC immune microenvironment.

Carbonic Anhydrase 4 serves as a Clinicopathological Biomarker for Outcomes and Immune Infiltration in Renal Cell Carcinoma, Lower Grade Glioma, Lung Adenocarcinoma and Uveal Melanoma

Background: Carbonic anhydrase 4 (CA4) maintains homeostasis of carbon dioxide and bicarbonate. It is suggested to be a potential prognostic biomarker, while the correlations between CA4 and different cancers are indistinct.

Methods: Differential mRNA expression of CA4 among different cancers and corresponding normal tissues was compared based on datasets on the Cancer Genome Atlas (TCGA) platforms. Then, survival analysis was performed using Tumor-immune system interactionsplatform and TCGA cohort on the basis of distinct comparison expression of CA4 in five kinds of tumors. In addition, molecular penal analysis and functional annotations of CA4-related genes was elaborated. The correlation between CA4 mRNA expression and tumor immune microenvironment were analyzed in detail.

Results: Compared with adjacent normal tissues, CA4 mRNA expressions were found significantly lower in various tumors. Moreover, decreased expression of CA4 was significantly related to worse overall survival (OS) and progression-free survival (PFS) in kidney renal clear cell carcinoma (KIRC), brain lower grade glioma (LGG), lung adenocarcinoma (LUAD) and uveal melanoma (UVM), and worse OS of prostate adenocarcinoma (PRAD) (p<0.05). Cox regression analyses indicated that CA4 was a significant prognostic biomarker in KIRC, LGG, LUAD and UVM. Moreover, CA4 showed markedly relationship with tumor immune environment and diverse immune infiltration signatures in KIRC, LGG, LUAD and UVM.

Conclusions: Our study revealed that CA4 was a potential biomarker for aggressive progression and poor prognosis in KIRC, LGG, LUAD, PRAD and UVM, correlated with immune infiltration in various tumor environments. These results suggested that CA4 possibly served as a promising prognostic and immune infiltration biomarker in many cancers.

A bilateral tumor model identifies transcriptional programs associated with patient response to immune checkpoint blockade

Immune checkpoint blockade (ICB) has revolutionized treatment of many cancer types, but the majority of treated patients still do not respond to ICB. There is an urgent need to identify predictive biomarkers of response prior to or shortly after therapy initiation, as well as the underlying mechanisms. Here we utilize a model of bilateral tumor implantations followed by resection and immunotherapy-response assessment to study the tumor microenvironment shortly following treatment, identifying biomarkers for response or resistance at early time points. Our biomarker gene signatures derived from CD8⁺ T cells significantly segregate patients by survival and associate with patient response to ICB. Our findings provide a general approach for studying mechanisms of resistance to ICB and discovering predictive biomarkers of response.

Immune checkpoint blockade (ICB) is efficacious in many diverse cancer types, but not all patients respond. It is important to understand the mechanisms driving resistance to these treatments and to identify predictive biomarkers of response to provide best treatment options for all patients. Here we introduce a resection and response-assessment approach for studying the tumor microenvironment before or shortly after treatment initiation to identify predictive biomarkers differentiating responders from nonresponders. Our approach builds on a bilateral tumor implantation technique in a murine metastatic breast cancer model (E0771) coupled with anti-PD-1 therapy. Using our model, we show that tumors from mice responding to ICB therapy had significantly higher CD8⁺ T cells and fewer Gr1⁺CD11b⁺ myeloid-derived suppressor cells (MDSCs) at early time points following therapy initiation. RNA sequencing on the intratumoral CD8⁺ T cells identified the presence of T cell exhaustion pathways in nonresponding tumors and T cell activation in responding tumors. Strikingly, we showed that our derived response and resistance signatures significantly segregate patients by survival and associate with patient response to ICB. Furthermore, we identified decreased expression of CXCR3 in nonresponding mice and showed that tumors grown in Cxcr3^−/− mice had an elevated resistance rate to anti-PD-1 treatment. Our findings suggest that the resection and response tumor model can be used to identify response and resistance biomarkers to ICB therapy and guide the use of combination therapy to further boost the antitumor efficacy of ICB.

Development and validation of a prognostic and immunotherapeutically relevant model in hepatocellular carcinoma

Background

The tumor immune microenvironment is pivotal in predicting clinical outcomes and therapeutic efficacy in cancer patients. This study aims to develop an immune prediction model (IPM) to effectively predict prognosis and immunotherapeutic response in patients with hepatocellular carcinoma (HCC).

Methods

An IPM was constructed and validated based on immune-related genes. The influence of IPM on the HCC immune microenvironment, as well as the possible mechanism, was comprehensively analyzed. The value of the model in predicting the response of HCC patients to immunotherapy was also evaluated.

Results

A novel IPM based on eight genes was developed and validated to predict the prognosis of HCC patients. These genes are matrix metalloproteinase 12 (MMP12), heme oxygenase 1 (HMOX1), C-X-C motif chemokine receptor 6 (CXCR6), hepatoma-derived growth factor (HDGF), placental growth factor (PGF), tyrosine kinase 2 (TYK2), retinoid X receptor beta (RXRB), and cyclin-dependent kinase 4 (CDK4). High-risk patients showed significantly poorer survival than low-risk patients. A nomogram was also established based on the IPM and tumor, node, metastasis (TNM) classification, which showed some net clinical benefit. Gene set enrichment analysis (GSEA) revealed several significantly enriched oncological signatures and immunologic signatures. Furthermore, high-risk patients were characterized by severe clinicopathological characteristics and immune cell infiltration. Finally, we found the that the IPM showed a significant positive correlation with programmed cell death 1 (PDCD1), cluster of differentiation 274 (CD274), and cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) expression, suggesting a potentially enhanced effects of immunotherapy antibodies in HCC patients with a high risk score.

Conclusions

A novel IPM that could predict clinical prognosis and immunotherapeutic response in HCC patients was developed. Our findings not only provide new insights into the identification of HCC patients with poor survival, but also deepen our understanding of the immune microenvironment, as well as the mechanism of immunotherapy, in HCC.

Maternal obesity increases offspring's mammary cancer recurrence and impairs tumor immune response

Over 50% of women at a childbearing age in the United States are overweight or obese, and this can adversely affect their offspring. We studied if maternal obesity-inducing high fat diet (HFD) not only increases offspring's mammary cancer risk but also impairs response to antiestrogen tamoxifen. Female rat offspring of HFD and control diet-fed dams, in which estrogen receptor-positive (ER+) mammary tumors were induced with the carcinogen 7,12-dimethylbenz[a]anthracene (DMBA), exhibited similar initial responses to antiestrogen tamoxifen. However, after tamoxifen therapy was completed, almost all (91%) tumors recurred in HFD offspring, compared with only 29% in control offspring. The increase in local mammary tumor recurrence in HFD offspring was linked to an increase in the markers of immunosuppression (Il17f, Tgfβ1, VEGFR2) in the tumor microenvironment (TME). Protein and mRNA levels of the major histocompatibility complex II (MHC-II), but not MHC-I, were reduced in the recurring DMBA tumors of HFD offspring. Further, infiltration of CD8+ effector T cells and granzyme B+ (GZMB+) cells were lower in their recurring tumors. To determine if maternal HFD can pre-program similar changes in the TME of allografted E0771 mammary tumors in offspring of syngeneic mice, flow cytometry analysis was performed. E0771 mammary tumor growth was significantly accelerated in the HFD offspring, and a reduction in the numbers of GZMB and non-significant reduction of interferon γ (IFNγ) secreting CD8+ T cells in the TME was seen. Thus, consumption of a HFD during pregnancy increases susceptibility of the female rat and mouse offspring to tumor immune suppression and mammary tumor growth and recurrence.

Establishment of a 3D Co-culture With MDA-MB-231 Breast Cancer Cell Line and Patient-Derived Immune Cells for Application in the Development of Immunotherapies

3D cell culture including different cell types, such as immune cells, is a representative platform that mimics the tumor microenvironment. Here we disclose an easy-to-handle 3D co-culture protocol using a scaffold-free technique with the breast cancer cell line MDA-MB-231 and breast cancer patient-derived immune cells from peripheral blood. The method presented is simple, less time-consuming and less expensive when compared to other 3D techniques. Additionally, this is an optimized protocol for the establishment of a 3D system for this cell line, which is normally seen as challenging to spontaneously form spheroids. The addition of patient-derived immune cells to the cancer cells' spheroid allows the study of the crosstalk between both cell types, as well as the assessment of individual therapeutic approaches to intensify the antitumor immune response. In fact, with this model, we observed that patients' immune cells exhibit a wide range of antitumor responses and we further demonstrated that it is possible to manipulate the less effective ones with a canonical stimulus, as a proof-of-concept, in order to improve their ability to lower the viability of tumor cells. Therefore, this platform could be applied for a personalized immune-based drug screening, with results after a maximum of 10 days of culture, in order to develop more tailored breast cancer treatments and ameliorate patients' survival rate.

Intratumoral Adipocyte-High Breast Cancer Enrich for Metastatic and Inflammation-Related Pathways but Associated with Less Cancer Cell Proliferation

Cancer-associated adipocytes are known to cause inflammation, leading to cancer progression and metastasis. The clinicopathological and transcriptomic data from 2256 patients with breast cancer were obtained based on three cohorts: The Cancer Genome Atlas (TCGA), GSE25066, and a study by Yau et al. For the current study, we defined the adipocyte, which is calculated by utilizing a computational algorithm, xCell, as “intratumoral adipocyte”. These intratumoral adipocytes appropriately reflected mature adipocytes in a bulk tumor. The amount of intratumoral adipocytes demonstrated no relationship with survival. Intratumoral adipocyte-high tumors significantly enriched for metastasis and inflammation-related gene sets and are associated with a favorable tumor immune microenvironment, especially in the ER+/HER2- subtype. On the other hand, intratumoral adipocyte-low tumors significantly enriched for cell cycle and cell proliferation-related gene sets. Correspondingly, intratumoral adipocyte-low tumors are associated with advanced pathological grades and inversely correlated with MKI67 expression. In conclusion, a high amount of intratumoral adipocytes in breast cancer was associated with inflammation, metastatic pathways, cancer stemness, and favorable tumor immune microenvironment. However, a low amount of adipocytes was associated with a highly proliferative tumor in ER-positive breast cancer. This cancer biology may explain the reason why patient survival did not differ by the amount of adipocytes.

Development and validation of an immune-related prognostic signature in lung adenocarcinoma

BACKGROUND

Lung adenocarcinomas (LUAD) is the most common histological subtype of lung cancers. Tumor immune microenvironment (TIME) is involved in tumorigeneses, progressions, and metastases. This study is aimed to develop a robust immune-related signature of LUAD.

METHODS

A total of 1774 LUAD cases sourced from public databases were included in this study. Immune scores were calculated through ESTIMATE algorithm and weighted gene co-expression network analysis (WGCNA) was applied to identify immune-related genes. Stability selections and Lasso COX regressions were implemented to construct prognostic signatures. Validations and comparisons with other immune-related signatures were conducted in independent Gene Expression Omnibus (GEO) cohorts. Abundant infiltrated immune cells and pathway enrichment analyses were carried out, respectively, through ImmuCellAI and gene set enrichment analysis (GSEA).

RESULTS

In Cancer Genome Atlas (TCGA) LUAD cohorts, immune scores of higher levels were significantly associated with better prognoses (P < .05). Yellow (n = 270) and Blue (n = 764) colored genes were selected as immune-related genes, and after univariate Cox regression analysis (P < .005), a total of 133 genes were screened out for subsequent model constructions. A four-gene signature (ARNTL2, ECT2, PPIA, and TUBA4A) named IPSLUAD was developed through stability selection and Lasso COX regression. It was suggested by multivariate and subgroup analyses that IPSLUAD was an independent prognostic factor. It was suggested by Kaplan-Meier survival analysis that eight out of nine patients in high-risk groups had significantly worse prognoses in validation data sets (P < .05). IPSLUAD outperformed other signatures in two independent cohorts.

CONCLUSIONS

A robust immune-related prognostic signature with great performances in multiple LUAD cohorts was developed in this study.

Immune Landscape of the Tumor Microenvironment Identifies Prognostic Gene Signature CD4/CD68/CSF1R in Osteosarcoma

Background: Osteosarcoma (OSA), the most common primary bone malignancy in children and adolescents, is prone to metastases and unfavorable prognosis. Owing to its strong genomic heterogeneity, traditional chemotherapy, or targeted immunotherapy has not effectively improved the related overall survival for decades. Since the landscape of the OSA tumor immune microenvironment is scarcely known, despite it playing a crucial role in predicting clinical outcomes and therapeutic efficacies, we aimed to elucidate its molecular characteristics.

Methods: The immune signature of 101 OSA samples was explored using transcriptome profiling and clinical characteristics retrieved from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) program. Correlations between the prognostic immune markers and their clinical chemotherapy responses were assessed and verified based on 45 OSA primary tumors.

Findings: We identified the heterogeneity underlying tumor immune signature in OSA, and found CD4+ T cells and macrophage markers CD4/IFNGR2/CD68 to be feasible prognostic factors, exerting significantly positive correlation with each other. Specifically, CSF1R, which plays an essential role in the regulation of proliferation and differentiation of macrophages, was found to be a specific signature associated with CD4/CD68, with improved OSA clinical outcomes.

Interpretation: The immune landscape based on CD4/CD68/CSF1R gene signatures showed considerable promise for prognostic and therapeutic stratification in OSA patients. A specific immune signature for OSA, abundantly consisting of Th1-polarized CD4+ T cells and CSF1R-related CD68+ macrophages, may improve the predictive efficacy of chemotherapy and improve prognosis in patients with OSA.

The Potential of Five Immune-Related Prognostic Genes to Predict Survival and Response to Immune Checkpoint Inhibitors for Soft Tissue Sarcomas Based on Multi-Omic Study

Low response rates to immunotherapy have been reported in soft tissue sarcoma (STS). There are few predictive biomarkers of response, and the tumor immune microenvironment associated with progression and prognosis remains unclear in STS. Gene expression data from the Cancer Genome Atlas were used to identify the immune-related prognostic genes (IRPGs) and construct the immune gene-related prognostic model (IGRPM). The tumor immune microenvironment was characterized to reveal differences between patients with different prognoses. Furthermore, somatic mutation data and DNA methylation data were analyzed to understand the underlying mechanism leading to different prognoses. The IGRPM was constructed using five IRPGs (IFIH1, CTSG, STC2, SECTM1, and BIRC5). Two groups (high- and low-risk patients) were identified based on the risk score. Low-risk patients with higher overall survival time had higher immune scores, more immune cell infiltration (e.g., CD8 T cell and activated natural killer cells), higher expression of immune-stimulating molecules, higher stimulating cytokines and corresponding receptors, higher innate immunity molecules, and stronger antigen-presenting capacity. However, inhibition of immunity was observed in low-risk patients owing to the higher expression of immune checkpoint molecules and inhibiting cytokines. High-risk patients had high tumor mutation burden, which did not significantly influence survival. Gene set enrichment analysis further revealed that pathways of cell cycle and cancers were activated in high-risk patients. DNA methylation analysis indicated that relative high methylation was associated with better overall survival. Finally, the age, mitotic counts, and risk scores were independent prognostic factors for STS. Five IRPGs performed well in risk stratification of patients and are candidate biomarkers for predicting response to immunotherapy. Differences observed through the multi-omic study of patients with different prognoses may reveal the underlying mechanism of the development and progression of STS, and thereby improve treatment.

Multi-omics Data Analyses Construct TME and Identify the Immune-Related Prognosis Signatures in Human LUAD

Lung cancer has been the focus of attention for many researchers in recent years for the leading contribution to cancer-related death worldwide, in which lung adenocarcinoma (LUAD) is the most common histological type. However, the potential mechanism behind LUAD initiation and progression remains unclear. Aiming to dissect the tumor microenvironment of LUAD and to discover more informative prognosis signatures, we investigated the immune-related differences in three types of genetic or epigenetic characteristics (expression status, somatic mutation, and DNA methylation) and considered the potential roles that these alterations have in the immune response and both the immune-related metabolic and neural systems by analyzing the multi-omics data from The Cancer Genome Atlas (TCGA) portal. Additionally, a four-step strategy based on lasso regression and Cox regression was used to construct the prognostic prediction model. For the prognostic predictions on the independent test set, the performance of the trained models (average concordance index [C-index] = 0.839) is satisfied, with average 1-year, 3-year, and 5-year areas under the curve (AUCs) equal to 0.796, 0.786, and 0.777. Finally, the overall model was constructed based on all samples, which comprised 27 variables and achieved a high degree of accuracy on the 1-year (AUC = 0.861), 3-year (AUC = 0.850), and 5-year (AUC = 0.916) survival predictions.

Fever-Inducible Lipid Nanocomposite for Boosting Cancer Therapy through Synergistic Engineering of a Tumor Microenvironment

A fever-mimic response capable of recruiting reprogrammed macrophages holds great potential in the engineering of the tumor microenvironment (TME). Low-temperature photothermal therapy (LT-PTT) can maintain tumors at a fever-like temperature (<45 °C) temporarily; however, it still faces several challenges in efficient regulation of TME because of reciprocal cross-talk between the bypass pathways. Here, we report a synergistic engineering of TME through an enhanced activation of a fever-mimic response based on both LT-PTT and tumor vascular normalization. Such engineering is achieved by a fever-inducible lipid nanocomposite (GNR-T/CM-L), which produces mild heat (∼43 °C) and sequentially releases multicomponents to cooperatively upregulate interferon-gamma under NIR irradiation, forming a bidirectionally closed loop for downstream M1 tumor-associated macrophage polarization and promoting the inhibition of the tumor growth. In proof-of-concept studies, GNR-T/CM-L demonstrated efficient tumor ablation in breast tumor xenograft-bearing mice and significantly prolonged their survival period. It paves an avenue to precisely reprogram TME for efficient cancer therapy through synergistic pathways of creating fever-like responses in the tumor.

Gas6/Axl Signaling Pathway in the Tumor Immune Microenvironment

Receptor tyrosine kinases have been shown to dysregulate a number of pathways associated with tumor development, progression, and metastasis. Axl is a receptor tyrosine kinase expressed in many cancer types and has been associated with therapy resistance and poor clinical prognosis and outcomes. In addition, Axl and its ligand growth arrest specific 6 (Gas6) protein are expressed by a number of host cells. The Gas6/Axl signaling pathway has been implicated in the promotion of tumor cell proliferation, survival, migration, invasion, angiogenesis, and immune evasion. As a result, Axl is an attractive, novel therapeutic target to impair multiple stages of tumor progression from both neoplastic and host cell axes. This review focuses on the role of the Gas6/Axl signaling pathway in promoting the immunosuppressive tumor microenvironment, as immune evasion is considered one of the hallmarks of cancer. The review discusses the structure and activation of the Gas6/Axl signaling pathway, GAS6 and AXL expression patterns in the tumor microenvironment, mechanisms of Axl-mediated tumor immune response, and the role of Gas6/Axl signaling in immune cell recruitment.

Comprehensive analysis of multiple parameters associated with tumor immune microenvironment in ARID1A mutant cancers

Aim: To verify the relationship between ARID1A and tumor immune microenvironment thus immune checkpoint inhibitors (ICIs) response. Material & methods: Several public databases were used to characterize the association between ARID1A gene alteration and tumor immunity. Results: The gene mutation frequency was 8.2% in all cancer types. The ARID1A-mutated cancers have higher scores of mutation count, tumor mutational burden, neoantigen load (p < 0.001) and T cell repertoire, B cell repertoire diversity (p < 0.05). The gene mutation has tight association with multiple-activated immune cells. Survival analysis suggested that patients with ARID1A mutant cancers benefit more from ICIs treatment (p = 0.013). Conclusion: The ARID1A gene mutation was correlated with higher tumor immunogenicity and activated antitumor immune microenvironment, resulting in superior cohort that respond well to ICIs.

Immunophenotypes Based on the Tumor Immune Microenvironment Allow for Unsupervised Penile Cancer Patient Stratification

The tumor immune microenvironment (TIME) plays an important role in penile squamous cell carcinoma (peSCC) pathogenesis. Here, the immunophenotype of the TIME in peSCC was determined by integrating the expression patterns of immune checkpoints (programmed cell death-1 (PD-1)/programmed cell death ligand-1 (PD-L1), cytotoxic T lymphocyte antigen 4 (CTLA-4), and Siglec-15) and the components of tumor-infiltrating lymphocytes, including CD8⁺ or Granzyme B⁺ T cells, FOXP3⁺ regulatory T cells, and CD68⁺ or CD206⁺ macrophages, in 178 patients. A high density of Granzyme B, FOXP3, CD68, CD206, PD-1, and CTLA-4 was associated with better disease-specific survival (DSS). The patients with diffuse PD-L1 tumor cell expression had worse prognoses than those with marginal or negative PD-L1 expression. Four immunophenotypes were identified by unsupervised clustering analysis, based on certain immune markers, which were associated with DSS and lymph node metastasis (LNM) in peSCC. There was no significant relationship between the immunophenotypes and high-risk human papillomavirus (hrHPV) infection. However, the hrHPV–positive peSCC exhibited a higher density of stromal Granzyme B and intratumoral PD-1 than the hrHPV–negative tumors (p = 0.049 and 0.002, respectively). In conclusion, the immunophenotypes of peSCC were of great value in predicting LNM and prognosis, and may provide support for clinical stratification management and immunotherapy intervention.

Identification and Validation of the Immune Subtypes of Lung Adenocarcinoma: Implications for Immunotherapy

Lung adenocarcinoma (LUAD) is a devastating disease with poor patient survival. Cancer immunotherapy has revolutionized the treatment of LUAD, but only a limited number of patients effectively respond to this treatment. Thus, the work to elucidate the LUAD immune heterogeneity could be crucial in developing new immunotherapeutic strategies with better efficacy. Non-negative matrix factorization-based deconvolution was performed to identify robust clusters of 489 LUAD patients in The Cancer Genome Atlas (TCGA) and verify their reproducibility and stability in an independent LUAD cohort of 439 patients from the Gene Expression Omnibus (GEO). We used the graph learning-based dimensionality reduction to visualize the distribution of individual patients. In this study, four reproducible immune subtypes, Clusters 1-4 (C1-C4) associated with distinct gene module signatures, clinicopathological features, molecular and cellular characteristics were identified and validated. The immune-cold subtype, C3, was associated with the Dead event, the most advanced T stage, N stage, TNM stage and the worst prognosis for LUAD patients. Moreover, C3 exhibited the lowest infiltrating levels of B cells, T cell receptor (TCR) repertoire diversity and the highest level of neoantigen and mutation rate among C1-C4. On the other hand, the immune-hot subtype (C4) exhibited the highest infiltration of six types of infiltrating immune cells as well as the greatest leukocyte fraction, TCR and B cell receptor (BCR) repertoire diversity. C1 and C2 subtypes showed diverse clinicopathological and immunological features. Finally, our investigations discovered a complex immune landscape with a scattered immune subtype profile. This work may help inform immunotherapeutic decision-making and design advanced immunotherapy strategies for the treatment of lung cancer.

Tumor-Infiltrating Neutrophils Predict Poor Survival of Non-Functional Pancreatic Neuroendocrine Tumor

OBJECTIVE

This study retrospectively characterized the immune infiltrating profile in nonfunctional pancreatic neuroendocrine tumors (NF-PanNETs).

METHODS

Tumor tissues from the 109-patient Fudan cohort and a 73-patient external validation set were evaluated by immunohistochemistry for 9 immune cell types: tumor-infiltrating neutrophils (TINs), tumor-associated macrophages (TAMs), CD11c+ dendritic cells, anti-NCR1+ natural killer (NK) cells, CD4+ and CD8+ T cells, CD45RO+ memory T cells, FOXP3+ regulatory T cells (Tregs), and CD20+ B cells.

RESULTS

TINs were primarily distributed in the intratumoral area, dendritic cells and NK cells were scattered evenly in intratumoral and stromal areas, and Tregs were rarely detected. The remaining 5 cell types were primarily present in peritumoral stroma. Total TINs (P < .001) and TAMs (P = .002) increased as NF-PanNET grade rose. Kaplan-Meier analyses showed that high intratumoral TINs, total TAMs, and stromal CD4+ T-cell infiltration correlated with shorter recurrence-free survival (RFS, P = .010, P = .027, and P = .035, respectively) and overall survival (OS, P = .017, P = .029, and P = .045, respectively). Additionally, high intratumoral CD8+ T cell infiltration correlated with prolonged RFS (P = .039). Multivariate Cox regression demonstrated that intratumoral TINs, World Health Organization (WHO) classification, and eighth edition of the American Joint Committee on Cancer tumor-node-metastasis staging system (AJCC8th TNM) were independent factors for RFS (P = .043, P = .023, and P = .029, respectively), whereas intratumoral TINs and WHO classification were independent factors for OS (P = .010 and P = .007, respectively). Furthermore, the combination of TINs, WHO classification, and AJCC8th TNM remarkably improved prognostic accuracy for RFS. These results have been verified in the external validation set.

CONCLUSION

Intratumoral TINs are an independent and unfavorable predictor of postoperative NF-PanNETs. A combination of TINs, WHO classification, and AJCC8th TNM could improve prognostic accuracy for RFS.

[Interleukin-12 over-expression in malignant melanoma B16 cells reduces programmed death-1 expression on T cells in mice with immune reconstitution]

OBJECTIVE

To investigate whether interleukin-12 (IL-12) over-expression in malignant melanoma B16 cells affects the expression level of programmed death-1 (PD-1) on T cells in mice during immune microenvironment reconstruction.

METHODS

B16 cells were transfected with an IL-12 expression lentiviral vector, and IL-12 over-expression in the cells was verified qPCR and ELISA. Plate cloning assay was used to compare the cell proliferation activity between B16 cells and B16/IL-12 cells. The expression of IL-12 protein in B16/IL-12 cells-derived tumor tissue were detected by ELISA. C57BL/6 mice were inoculated with B16 cells or B16/IL-12 cells, and 14 days later the proportion of T cells with high expression of PD-1 in the tumor-draining lymph nodes was detected by flow cytometry. Mouse models of immune reconstitution established by 650 cGy X-ray radiation were inoculated with B16 (B16+RT group) or B16/IL-12 (B16/IL-12+RT group) cells, with the mice without X-ray radiation prior to B16 cell inoculation as controls. Tumor growth in the mice was recorded at different time points, and on day 14, flow cytometry was performed to detect the proportion of T cells with high PD-1 expression in the tumor-draining lymph nodes and in the tumor tissue.

RESULTS

B16 cells infected with the IL-12-overexpressing lentiviral vector showed significantly increased mRNA and protein levels of IL-12 (P &lt; 0.001) without obvious changes in cell viability (P&gt;0.05). B16/IL-12 cells expressed higher levels of IL-12 than B16 cells in vivo (P &lt; 0.01). In the tumor-bearing mouse models, the proportion of CD4 ⁺ PD-1⁺ T cells was significantly lower in B16/IL-12 group than in B16 group (P &lt; 0.01). In the mice with X-ray radiation-induced immune reconstitution, PD-1 expressions on CD4⁺ T cells (P &lt; 0.05) and CD8+ T cells (P &lt; 0.01) were significantly higher in B16+ RT group than in the control mice and in B16/IL-12+RT group (P &lt; 0.01 or 0.001); the tumors grew more slowly in B16/IL-12+RT group than in B16 + RT group (P &lt; 0.001).

CONCLUSIONS

During immune microenvironment reconstruction, overexpression IL-12 in the tumor microenvironment can reduce the percentage of PD-1 ⁺ T cells and suppress the growth of malignant melanoma in mice.