High USP32 expression contributes to cancer progression and is correlated with immune infiltrates in hepatocellular carcinoma

BACKGROUND

Ubiquitin-specific protease 32 (USP32) is a highly conserved gene that promotes cancer progression. However, its role in hepatocellular carcinoma (HCC) is not well understood. The aim of this project is to explore the clinical significance and functions of USP32 in HCC.

METHODS

The expression of USP32 in HCC was evaluated using data from TCGA, GEO, TISCH, tissue microarray, and human HCC samples from our hospital. Survival analysis, PPI analysis and GSEA analysis were performed to evaluate USP32-related clinical significance, key molecules and enrichment pathways. Using the ssGSEA algorithm and TIMER, we investigated the relationships between USP32 and immune infiltrates in the TME. Univariate and multivariate Cox regression analyses were then used to identify key USP32-related immunomodulators and constructed a USP32-related immune prognostic model. Finally, CCK8, transwell and colony formation assays of HCC cells were performed and an HCC nude mouse model was established to verify the oncogenic role of USP32.

RESULTS

USP32 is overexpressed in HCC and its expression is an independent predictive factor for outcomes of HCC patients. USP32 is associated with pathways related to cell behaviors and cancer signaling, and its expression is significantly correlated with the infiltration of immune cells in the TME. We also successfully constructed a USP32-related immune prognostic model using 5 genes. Wet experiments confirmed that knockdown of USP32 could repress the proliferation, colony formation and migration of HCC cells in vitro and inhibit tumor growth in vivo.

CONCLUSION

USP32 is highly expressed in HCC and closely correlates with the TME of HCC. It is a potential target for improving the efficacy of chemotherapy and developing new strategies for targeted therapy and immunotherapy in HCC.

Characterization of metabolism-associated molecular patterns in prostate cancer

BACKGROUND

Metabolism is a hallmark of cancer and it involves in resistance to antitumor treatment. Therefore, the purposes of this study are to classify metabolism-related molecular pattern and to explore the molecular and tumor microenvironment characteristics for prognosis predicting in prostate cancer.

METHODS

The mRNA expression profiles and the corresponding clinical information for prostate cancer patients from TCGA, cBioPortal, and GEO databases. Samples were classified using unsupervised non-negative matrix factorization (NMF) clustering based on differentially expressed metabolism-related genes (MAGs). The characteristics of disease-free survival (DFS), clinicopathological characteristics, pathways, TME, immune cell infiltration, response to immunotherapy, and sensitivity to chemotherapy between subclusters were explored. A prognostic signature was constructed by LASSO cox regression analysis based on differentially expressed MAGs and followed by the development for prognostic prediction.

RESULTS

A total of 76 MAGs between prostate cancer samples and non-tumorous samples were found, then 489 patients were divided into two metabolism-related subclusters for prostate cancer. The significant differences in clinical characteristics (age, T/N stage, Gleason) and DFS between two subclusters. Cluster 1 was associated with cell cycle and metabolism-related pathways, and epithelial-mesenchymal transition (EMT), etc., involved in cluster 2. Moreover, lower ESTIMATE/immune/stromal scores, lower expression of HLAs and immune checkpoint-related genes, and lower half-maximal inhibitory concentration (IC50) values in cluster 1 compared with cluster 2. The 10 MAG signature was identified and constructed a risk model for DFS predicting. The patients with high-risk scores showed poorer DFS. The area under the curve (AUC) values for 1-, 3-, 5-year DFS were 0.744, 0.731, 0.735 in TCGA-PRAD dataset, and 0.668, 0.712, 0.809 in GSE70768 dataset, 0.763, 0.802, 0.772 in GSE70769 dataset. Besides, risk score and Gleason score were identified as independent factors for DFS predicting, and the AUC values of risk score and Gleason score were respectively 0.743 and 0.738. The nomogram showed a favorable performance in DFS predicting.

CONCLUSION

Our data identified two metabolism-related molecular subclusters for prostate cancer that were distinctly characterized in prostate cancer. Metabolism-related risk profiles were also constructed for prognostic prediction.

An immune risk score predicts survival of patients with diffuse large B-cell lymphoma

PURPOSE

Providing accurate prognostic models is necessary for diffuse large B-cell lymphoma, but there are still many uncertainties. So far, none of the models include immune cells. Therefore, an immune risk score was constructed to predict the survival of patients.

METHODS

CIBERSORTx was chosen to estimate the proportion of 22 human immune cell subsets from public datasets and generate an immune risk score to predict patients' survival in a training cohort using the least absolute shrinkage and selection operator (LASSO) Cox regression model.

RESULTS

The prognostic model had high predictive ability in the training and validation cohorts. Subjects in the training cohort with high scores had a worse prognosis compared with subjects with low scores. The same result was also found in the three validation cohorts. Multivariable analysis suggested that the immune risk score was an independent prognostic factor. The merged score, including the immune risk score and the international prognostic index (IPI) risk category, had better predictive accuracy.

CONCLUSIONS

Our immune risk score promises to be a complement to current prognostic models.

A novel inflammatory response-related signature predicts the prognosis of cutaneous melanoma and the effect of antitumor drugs

Cutaneous melanoma (CM) is a skin cancer that is highly metastatic and aggressive, with a dismal prognosis. This is the first study to use inflammatory response-related genes to build a model and evaluate their predictive significance in CM. This study used public databases to download CM patients' mRNA expression profiles and clinical data to create multigene prognostic markers in the UCSC cohort. We compared overall survival (OS) between high- and low-risk groups using the Kaplan-Meier curve and determined independent predictors using Cox analysis. We also used enrichment analysis to assess immune cell infiltration fraction and immune pathway-related activity using KEGG enrichment analysis. Furthermore, we detected prognostic genes' mRNA and protein expression in CM and normal skin tissues using qRT-PCR and immunohistochemistry. Finally, we developed a 5-gene predictive model that showed that patients in the high-risk group had a considerably shorter OS than those in the low-risk group. The analysis of the receiver operating characteristic (ROC) curve proved the model's predictive ability. We also conducted a drug sensitivity analysis and discovered that the expression levels of prognostic genes were substantially linked with cancer cell sensitivity to antitumor medicines. The findings show that the model we developed, which consists of five inflammatory response-related genes, can be used to forecast the prognosis and immunological state of CM, giving personalized and precision medicine a new goal and direction.

Local radiotherapy and E7 RNA-LPX vaccination show enhanced therapeutic efficacy in preclinical models of HPV16+ cancer

Human papilloma virus (HPV) infection is a causative agent for several cancers types (genital, anal and head and neck region). The HPV E6 and E7 proteins are oncogenic drivers and thus are ideal candidates for therapeutic vaccination. We recently reported that a novel ribonucleic acid lipoplex (RNA-LPX)-based HPV16 vaccine, E7 RNA-LPX, mediates regression of mouse HPV16⁺ tumors and establishes protective T cell memory. An HPV16 E6/E7 RNA-LPX vaccine is currently being investigated in two phase I and II clinical trials in various HPV-driven cancer types; however, it remains a high unmet medical need for treatments for patients with radiosensitive HPV16⁺ tumors. Therefore, we set out to investigate the therapeutic efficacy of E7 RNA-LPX vaccine combined with standard-of-care local radiotherapy (LRT). We demonstrate that E7 RNA-LPX synergizes with LRT in HPV16⁺ mouse tumors, with potent therapeutic effects exceeding those of either monotherapy. Mode of action studies revealed that the E7 RNA-LPX vaccine induced high numbers of intratumoral-E7-specific CD8⁺ T cells, rendering cold tumors immunologically hot, whereas LRT primarily acted as a cytotoxic therapy, reducing tumor mass and intratumor hypoxia by predisposing tumor cells to antigen-specific T cell-mediated killing. Overall, LRT enhanced the effector function of E7 RNA-LPX-primed T cell responses. The therapeutic synergy was dependent on total radiation dose, rather than radiation dose-fractionation. Together, these results show that LRT synergizes with E7 RNA-LPX and enhances its anti-tumor activity against HPV16⁺ cancer models. This work paves into a new translational therapy for HPV16⁺ cancer patients.

FOXD1 expression in head and neck squamous carcinoma: a study based on TCGA, GEO and meta-analysis

Forkhead box D1 (FOXD1) is a new member of FOX transcription factor family. FOXD1 has demonstrated multi-level roles during normal development and several diseases' pathogenesis. However, litter is known about the role of FOXD1 in the progression of head and neck squamous cancer (HNSC). In the present study, we analyzed FOXD1 expression pattern using TCGA dataset, GEO datasets, HNSC cell lines and HNSC tissues. Then, we analyzed the correlation between FOXD1 expression and clinical characteristics, and evaluated the prognostic value of FOXD1 in HNSC. Moreover, we assessed the relationship between FOXD1 expression and tumor environment (TME) and immune cell infiltration using ESTIMATE and CIBERSORT algorithms. Finally, we predicted the FOXD1-related biological processes and signal pathways. FOXD1 was up-regulated in HNSC tissues in TCGA datasets, validated by GEO datasets, HNSC cell lines and HNSC tissues. FOXD1 expression was significantly associated with tumor site and HPV infection. Univariate and multivariate Cox regression analyses showed that FOXD1 expression was an independent prognostic factor. Moreover, we found that the proportions of naïve B cells, plasma cells, and resting dendritic cells were negatively correlated with FOXD1 expression, otherwise, the proportion of activated mast cells was positively correlated with FOXD1 expression using CIBERSORT algorithm. GSEA analyses revealed that FOXD1 was mainly involved in cancer-related signaling pathway and metabolism-related pathways. FOXD1 was a potential oncogene, and might represent an indicator for predicting overall survival of HNSC patients. Moreover, many cancer-related pathways and metabolism-related processes may be regulated by FOXD1.

The tumor environment immune phenotype of LUSC by genome-wide analysis

PURPOSE

To compare the landscape of tumor microenvironment (TME) of lung squamous carcinoma (LUSC) in different immune pattern and explore potential factors on immune therapy and prognosis.

METHOD AND MATERIALS

We have obtained the LUSC data from TCGA, GEO, and our department and classified them into 2 TME clusters by random forest model based on the infiltration pattern of 24 immune cell populations. We systemically compared the genomic significance, clinical characteristics, and immune infiltration pattern in 2 TME clusters.

RESULTS

Samples were divided into 2 TME clusters based on the relative abundance of 24 immune cells, and a random forest classifier model was constructed. TME cluster B was a higher immune infiltration group with lower mutation load, richer co-infiltrate immune cells, upregulated immune-related cytokines, immune checkpoint molecules, and higher active immune cells. TME cluster was also an independent predictor in prognosis (B vs. A, p < 0.05) in patients from TCGA, GEO, and our department.

CONCLUSIONS

Our study has described the microenvironment landscape of LUSC in different immune infiltration patterns and systemically analyzed genomic and clinical characteristics with distinct immunophenotypes, thus partly revealed the interaction between tumors and the immune microenvironment, which may guide a more precise and personalized immune therapeutic strategy for LUSC patients.

Lipoproteins and the Tumor Microenvironment

The tumor microenvironment (TME) plays a key role in enhancing the growth of malignant tumors and thus contributing to "aggressive phenotypes," supporting sustained tumor growth and metastasis. The precise interplay between the numerous components of the TME that contribute to the emergence of these aggressive phenotypes is yet to be elucidated and currently under intense investigation. The purpose of this article is to identify specific role(s) for lipoproteins as part of these processes that facilitate (or oppose) malignant growth as they interact with specific components of the TME during tumor development and treatment. Because of the scarcity of literature reports regarding the interaction of lipoproteins with the components of the tumor microenvironment, we were compelled to explore topics that were only tangentially related to this topic, to ensure that we have not missed any important concepts.

Quantitative Tracking Tumor Suppression Efficiency of Human Umbilical Cord-Derived Mesenchymal Stem Cells by Bioluminescence Imaging in Mice Hepatoma Model

Background and Objectives

Tracking of the tumor progression by MSCs-based therapy is being increasingly important in evaluating relative therapy effectively. Herein, Bioluminescence imaging (BLI) technology was used to dynamically and quantitatively track the hepatocellular carcinoma suppressive effects by human umbilical cord mesenchymal stem cells (UC-MSCs).

Methods and Results

The stem cells present typical phenotypic characteristics and differentiation ability by morphology and flow cytometry analysis of marker expression. Then, the growth inhibition effect of conditioned medium and UC-MSC on H7402 cells was studied. It is found both the conditioned medium and UC-MSC can effectively decrease the proliferation of H7402 cells compared with the control group. Meanwhile, the relative migration of UC-MSC to H7402 is also increased through the transwell migration assay. In addition, a mice hepatoma tumor model was built by H7402 cells which can express a pLenti-6.3/DEST-CMV-luciferase 2-mKate2 gene. The effect of stem cells on growth inhibition of tumor in a mice transplantation model was dynamically monitored by bioluminescence imaging within 5 weeks. It has shown the bioluminescence signal intensity of the tumor model was significantly higher than that of the UC-MSC co-acting tumor model, indicating that the inhibition of UC-MSC on liver cancer resulted in low expression of bioluminescent signals.

Conclusions

The microenvironment of UC-MSCs can effectively inhibit the growth of liver cancer cells, and this therapeutic effect can be dynamically and quantitatively monitored in vivo by BLI. This is of great significance for the imaging research and application of stem cells in anticancer therapy.

CCL22 Signaling in the Tumor Environment

T cell-mediated elimination of malignant cells is one cornerstone of endogenous and therapeutically induced antitumor immunity. Tumors exploit numerous regulatory mechanisms to suppress T cell immunity. Regulatory T cells (T regs) play a crucial role in this process due to their ability to inhibit antitumoral immune responses and they are known to accumulate in various cancer entities. The chemokine CCL22, predominately produced by dendritic cells (DCs), regulates T reg migration via binding to its receptor CCR4. CCL22 controls T cell immunity, both by recruiting T regs to the tumor tissue and by promoting the formation of DC-T reg contacts in the lymph node. Here, we review the current knowledge on the role of CCL22 in cancer immunity. After revising the principal mechanisms of CCL22-induced immune suppression, we address the factors leading to CCL22 expression and ways of targeting this chemokine therapeutically. Therapeutic interventions to the CCL22-CCR4 axis may represent a promising strategy in cancer immunotherapy.

Tumor Macroenvironment: An Update

Modes of tumor cell interaction include autocrine stimulation, secretion of paracrine growth factors and inhibitors, as well as interaction with the tumor macroenvironment. This evolving concept in tumor pathobiology describes the interaction of a malignant tumor with its host as an extension and addition to its local interaction with tumor cells and surrounding nontransformed cells, the tumor microenvironment. Angiogenesis, which is considered part of the tumor microenvironment, also allows reciprocal interactions between cancer cells and other organs and systems. Well-known examples of tumor endocrine signaling are the paraneoplastic syndromes. In addition, cachexia, a severe complication of tumor growth, results from the systemic reprogramming of the host metabolism as a result of tumor growth and progression. Moreover, recent reports indicate that cancer cells may secrete factors that might play a role in forming premetastatic niches at distant sites. In addition, cancer cells seem to be able to secrete factors influencing and resetting endogenous circadian organizers. The importance of understanding the whole complex interaction of a malignant tumor and its host - the tumor macroenvironment - is of great importance for the better management and treatment of cancer patients.

Malignant peritoneal effusion acting as a tumor environment in ovarian cancer progression: Impact and significance

Until recently, ovarian cancer research has mainly focused on the tumor cells themselves ignoring for the most part the surrounding tumor environment which includes malignant peritoneal effusions. However, one of the major conceptual advances in oncology over the last few years has been the appreciation that cancer progression cannot be explained by aberrations in cancer cells themselves and is strongly influenced by the surrounding tumor environment. The mechanisms of ovarian cancer progression differ from that of other solid tumors because ovarian cancer cells primarily disseminate within the peritoneal cavity. Malignant peritoneal effusion accumulates in the peritoneal cavity during ovarian cancer progression. These exudative fluids act as a unique tumor environment providing a framework that orchestrates cellular and molecular changes contributing to aggressiveness and disease progression. The composition of ascites, which includes cellular and acellular components, constantly adapts during the course of the disease in response to various cellular cues originating from both tumor and stromal cells. The tumor environment that represents peritoneal effusions closely constitute an ecosystem, with specific cell types and signaling molecules increasing and decreasing during the course of the disease progression creating a single complex network. Although recent advances aiming to understand the ovarian tumor environment have focused one at a time on components, the net impact of the whole environment cannot be understood simply from its parts or outside is environmental context.

Precision immunotherapy; dynamics in the cellular profile of pleural effusions in malignant mesothelioma patients

OBJECTIVES

Clinical studies have proven the potential of immunotherapy in malignancies. To increase efficacy, a prerequisite is that treatment is tailored, so precision immune-oncology is the logical next step. In order to tailor treatment, characterization of the patient's tumor environment is key. Pleural effusion (PE) often accompanies malignant pleural mesothelioma (MPM) and is an important part of the MPM environment. Furthermore, the composition of PE is used as surrogate for the tumor. In this study, we provide an insight in the dynamics of the MPM environment through characterization of PE composition over time and show that the immunological characteristics of PE do not necessarily mirror those of the tumor.

MATERIALS AND METHODS

From 5 MPM patients, PE and tumor biopsies were acquired at the same time point. From one of these patients multiple PEs were obtained. PEs were acquired performing thoracocenteses and total cell amounts were determined. Immunohistochemistry was performed to quantify immune cell composition (T cells, macrophages) and tumor cells in PE derived cytospins and tumor biopsies.

RESULTS

The PE amount and (immune) cellular composition varied considerably over time between multiple (n=10) thoracocenteses. These dynamics could in part be attributed to the treatment regimen consisting of standard chemotherapy and dendritic cell (DC)-based immunotherapy. In addition, the presence of T cells and macrophages in PE did not necessarily mirror the infiltration of these immune cells within tumor biopsies in 4 out of 5 patients.

CONCLUSIONS

In this proof-of-concept study with limited sample size, we demonstrate that the composition of PE is dynamic and influenced by treatment. Furthermore, the immune cell composition of PE does not automatically reflect the properties of tumor tissue. This has major consequences when applying precision immunotherapy based on PE findings in patients. Furthermore, it implies a regulated trafficking of immune regulating cells within the tumor environment.

NDRG2 Expression Decreases Tumor-Induced Osteoclast Differentiation by Down-regulating ICAM1 in Breast Cancer Cells

Bone matrix is properly maintained by osteoclasts and osteoblasts. In the tumor microenvironment, osteoclasts are increasingly differentiated by the various ligands and cytokines secreted from the metastasized cancer cells at the bone metastasis niche. The activated osteoclasts generate osteolytic lesions. For this reason, studies focusing on the differentiation of osteoclasts are important to reduce bone destruction by tumor metastasis. The N-myc downstream-regulated gene 2 (NDRG2) has been known to contribute to the suppression of tumor growth and metastasis, but the precise role of NDRG2 in osteoclast differentiation induced by cancer cells has not been elucidated. In this study, we demonstrate that NDRG2 expression in breast cancer cells has an inhibitory effect on osteoclast differentiation. RAW 264.7 cells, which are monocytic preosteoclast cells, treated with the conditioned media (CM) of murine breast cancer cells (4T1) expressing NDRG2 are less differentiated into the multinucleated osteoclast-like cells than those treated with the CM of 4T1-WT or 4T1-mock cells. Interestingly, 4T1 cells stably expressing NDRG2 showed a decreased mRNA and protein level of intercellular adhesion molecule 1 (ICAM1), which is known to enhance osteoclast maturation. Osteoclast differentiation was also reduced by ICAM1 knockdown in 4T1 cells. In addition, blocking the interaction between soluble ICAM1 and ICAM1 receptors significantly decreased osteoclastogenesis of RAW 264.7 cells in the tumor environment. Collectively, these results suggest that the reduction of ICAM1 expression by NDRG2 in breast cancer cells decreases osteoclast differentiation, and demonstrate that excessive bone resorption could be inhibited via ICAM1 down-regulation by NDRG2 expression.

The site of tumor development determines immunogenicity via temporal mobilization of antigen-laden dendritic cells in draining lymph nodes

The elimination of solid tumors largely depends on effective T-cell priming by dendritic cells (DCs). For decades, studies focusing on antitumoral immune responses have been performed with tumors transplanted subcutaneously (s.c.). These studies however do not take into account the heterogeneous tissue distribution and functionality of the different DC subsets. Given the crucial role of DCs in inducing protective immune response, we postulated that the anatomic location of tumor development may greatly impact tumor immunogenicity. We therefore implanted tumor cells either in the DC-rich dermis environment or in the s.c. tissue that mainly contains macrophages and monocytes. We showed that intradermal (i.d.), but not s.c. tumors are rapidly rejected in a T-cell-dependent manner and induce protective T-cell responses. The rejection of i.d. tumors correlates with rapid recruitment of dermal DCs presenting the tumor antigen to both CD4 and CD8 T cells in the draining lymph nodes (dLNs). The same DC subsets were mobilized upon s.c. tumor transplantation but with delayed kinetics. Altogether, our results show that the anatomical site of tumor development influences tumor immunogenicity, notably by controlling the kinetics of DC mobilization in the draining LNs.