Tumour immune cell infiltration and survival after platinum-based chemotherapy in high-grade serous ovarian cancer subtypes: A gene expression-based computational study

Spatial tumor immune microenvironment phenotypes in ovarian cancer

Immunotherapy has largely failed in ovarian carcinoma (OC), likely due to that the vast tumor heterogeneity and variation in immune response have hampered clinical trial outcomes. Tumor-immune microenvironment (TIME) profiling may aid in stratification of OC tumors for guiding treatment selection. Here, we used Digital Spatial Profiling combined with image analysis to characterize regions of spatially distinct TIME phenotypes in OC to assess whether immune infiltration pattern can predict presence of immuno-oncology targets. Tumors with diffuse immune infiltration and increased tumor-immune spatial interactions had higher presence of IDO1, PD-L1, PD-1 and Tim-3, while focal immune niches had more CD163 macrophages and a preliminary worse outcome. Immune exclusion was associated with presence of Tregs and Fibronectin. High-grade serous OC showed an overall stronger immune response and presence of multiple targetable checkpoints. Low-grade serous OC was associated with diffuse infiltration and a high expression of STING, while endometrioid OC had higher presence of CTLA-4. Mucinous and clear cell OC were dominated by focal immune clusters and immune-excluded regions, with mucinous tumors displaying T-cell rich immune niches.

Immune cell landscapes are associated with high-grade serous ovarian cancer survival

High-grade serous ovarian cancer (HGSOC) is an aggressive disease known to develop resistance to chemotherapy. We investigated the prognostic significance of tumor cell states and potential mechanisms underlying chemotherapy resistance in HGSOC. Transcriptome deconvolution was performed to address cellular heterogeneity. Kaplan-Meier survival curves were plotted to illustrate the outcomes of patients with varying cellular abundances. The association between gene expression and chemotherapy response was tested. After adjusting for surgery status and grading, several cell states exhibited a significant correlation with patient survival. Cell states can organize into carcinoma ecotypes (CE). CE9 and CE10 were proinflammatory, characterized by higher immunoreactivity, and were associated with favorable survival outcomes. Ratios of cell states and ecotypes had better prognostic abilities than a single cell state or ecotype. A total of 1265 differentially expressed genes were identified between samples with high and low levels of C9 or CE10. These genes were partitioned into three co-expressed modules, which were associated with tumor cells and immune cells. Pogz was identified to be linked with immune cell genes and the chemotherapy response of paclitaxel. Collectively, the survival of HGSOC patients is correlated with specific cell states and ecotypes.

Diaphorobacter nitroreducens synergize with oxaliplatin to reduce tumor burden in mice with lung adenocarcinoma

Lung adenocarcinoma (LADC) is the most common lung cancer and the leading cause of cancer-related deaths globally. Accumulating evidence suggests that the gut microbiota regulates the host response to chemotherapeutic drugs and can be targeted to reduce the toxicity of current chemotherapeutic agents. However, the effect of Diaphorobacter nitroreducens synergized with oxaliplatin on the gut microbiota and their impact on LADC have never been explored. This study aimed to evaluate the anti-cancer effects of D. nitroreducens, oxaliplatin, and their combined treatment on tumor growth in tumor-bearing mice. The composition of gut microbiota and the immune infiltration of tumors were evaluated by using 16S rRNA gene high-throughput sequencing and immunofluorescence, respectively. The inhibitory effect of the combination treatment with D. nitroreducens and oxaliplatin was significantly stronger than that of oxaliplatin alone in tumor-bearing mice. Furthermore, we observed that the combination treatment significantly increased the relative abundance of Lactobacillus and Akkermansia in the gut microbiota. Meanwhile, the combination treatment significantly increased the proportions of macrophage but decreased the proportion of regulatory T cells in the LADC tumor tissues of mice. These findings underscored the relationship between D. nitroreducens and the gut microbiota-immune cell-LADC axis, highlighting potential therapeutic avenues for LADC treatment.

IMPORTANCE

Oxaliplatin is widely used as an effective chemotherapeutic agent in cancer treatment, but its side effects and response rate still need to be improved. Conventional probiotics potentially benefit cancer chemotherapy by regulating gut microbiota and tumor immune infiltration. This study was novel in reporting a more significant inhibitory effect of Diaphorobacter nitroreducens on lung adenocarcinoma (LADC) cells compared with common traditional probiotics and validating its potential as an adjuvant therapy for LADC chemotherapy in mice. This study investigated the impact of D. nitroreducens combined with oxaliplatin on the gut microbiota and immune infiltration of tumors as a potential mechanism to improve anticancer effects.

Identification of glycosyltransferase-related genes signature and integrative analyses in patients with ovarian cancer

BACKGROUND

Glycosyltransferases (GT) play a crucial role in glycosylation reactions, and aberrant expression of glycosyltransferase-related genes (GTs) leads to abnormal glycosylation, which is associated with tumor progression. However, the prognostic value of aberrant expression of GTs in ovarian cancer (OC) and the correlation between GTs and tumor microenvironment (TME) remain unknown.

METHODS

TCGA and GSE53963 databases were used to obtain data on OC patient samples. The association of GTs with OC was analyzed. Molecular subtypes were identified by consensus unsupervised clustering, followed by immune infiltration and functional enrichment analyses. Survival analysis was performed using Kaplan-Meier curves and log-rank tests. Least Absolute Shrinkage and Selection Operator (LASSO) and multifactorial cox regression were used to screen for signature genes associated with OC and used to establish prognostic models.

RESULT

OC patients were categorized into 5 GTs clusters using consensus unsupervised cluster analysis. Clusters D and E showed significant differences between survival, signaling pathways and immune infiltration. Then, a risk model was developed based on the 12 signature genes, which provides a more accurate evaluation of the prognosis of OC patients. We categorized patients into high-risk and low-risk groups based on the risk score and found that the survival of patients in the high-risk group was significantly lower than that in the low-risk group. Moreover, the risk score was significantly correlated with tumor microenvironment, immune infiltration, and chemotherapy sensitivity.

CONCLUSION

Overall, we performed a comprehensive analysis of GTs in OC patients and developed a risk model for OC. Our findings will provide a new insight to OC prognosis and treatment.

Targeting the immune microenvironment for ovarian cancer therapy

Ovarian cancer (OC) is an aggressive malignancy characterized by a complex immunosuppressive tumor microenvironment (TME). Immune checkpoint inhibitors have emerged as a breakthrough in cancer therapy by reactivating the antitumor immune response suppressed by tumor cells. However, in the case of OC, these inhibitors have failed to demonstrate significant improvements in patient outcomes, and existing biomarkers have not yet identified promising subgroups. Consequently, there remains a pressing need to understand the interplay between OC tumor cells and their surrounding microenvironment to develop effective immunotherapeutic approaches. This review aims to provide an overview of the OC TME and explore its potential as a therapeutic strategy. Tumor-infiltrating lymphocytes (TILs) are major actors in OC TME. Evidence has been accumulating regarding the spontaneous TILS response against OC antigens. Activated T-helpers secrete a wide range of inflammatory cytokines with a supportive action on cytotoxic T-cells. Simultaneously, mature B-cells are recruited and play a significant antitumor role through opsonization of target antigens and T-cell recruitment. Macrophages also form an important subset of innate immunity (M1-macrophages) while participating in the immune-stimulation context. Finally, OC has shown to engage a significant natural-killer-cells immune response, exerting direct cytotoxicity without prior sensitization. Despite this initial cytotoxicity, OC cells develop various strategies to induce an immune-tolerant state. To this end, multiple immunosuppressive molecules are secreted to impair cytotoxic cells, recruit regulatory cells, alter antigen presentation, and effectively evade immune response. Consequently, OC TME is predominantly infiltrated by immunosuppressive cells such as FOXP3+ regulatory T-cells, M2-polarized macrophages and myeloid-derived suppressor cells. Despite this strong immunosuppressive state, PD-1/PD-L1 inhibitors have failed to improve outcomes. Beyond PD-1/PD-L1, OC expresses multiple other immune checkpoints that contribute to immune evasion, and each representing potential immune targets. Novel immunotherapies are attempting to overcome the immunosuppressive state and induce specific immune responses using antibodies adoptive cell therapy or vaccines. Overall, the OC TME presents both opportunities and obstacles. Immunotherapeutic approaches continue to show promise, and next-generation inhibitors offer exciting opportunities. However, tailoring therapies to individual immune characteristics will be critical for the success of these treatments.

Identification of a Prognostic Signature for Ovarian Cancer Based on Ubiquitin-Related Genes Suggesting a Potential Role for FBXO9

BACKGROUND

Ovarian cancer (OV) is associated with high mortality and poses challenges in diagnosis and prognosis prediction. Ubiquitin-related genes (UbRGs) are involved in the initiation and progression of cancers, but have still not been utilized for diagnosis and prognosis of OV.

METHODS

K48-linked ubiquitination in ovarian tissues from our OV and control cohort was assessed using immunohistochemistry. UbRGs, including ubiquitin and ubiquitin-like regulators, were screened based on the TCGA-OV and GTEx database. Univariate Cox regression analysis identified survival-associated UbRGs. A risk model was established using the LASSO regression and multivariate Cox regression analysis. The relationship between UbRGs and immune cell infiltration, tumor mutational burden, drug sensitivity, and immune checkpoint was determined using the CIBERSORT, ESTIMATE, and Maftools algorithms, based on the Genomics of Drug Sensitivity in Cancer and TCGA-OV databases. GEPIA2.0 was used to analyze the correlation between FBXO9/UBD and DNA damage repair-related genes. Finally, FBXO9 and UBD were accessed in tissues or cells using immunohistochemistry, qPCR, and Western blot.

RESULTS

We confirmed the crucial role for ubiquitination in OV as a significant decrease of K48-linked ubiquitination was observed in primary OV lesions. We identified a prognostic signature utilizing two specific UbRGs, FBXO9 and UBD. The risk score obtained from this signature accurately predicted the overall survival of TCGA-OV training dataset and GSE32062 validation dataset. Furthermore, this risk score also showed association with immunocyte infiltration and drug sensitivity, revealing potential mechanisms for ubiquitination mediated OV risk. In addition, FBXO9, but not UBD, was found to be downregulated in OV and positively correlated with DNA damage repair pathways, suggesting FBXO9 as a potential cancer suppressor, likely via facilitating DNA damage repair.

CONCLUSIONS

We identified and validated a signature of UbRGs that accurately predicts the prognosis, offers valuable guidance for optimizing chemotherapy and targeted therapies, and suggests a potential role for FBXO9 in OV.

Association of Tumor Cell Metabolic Subtype and Immune Response With the Clinical Course of Hepatocellular Carcinoma

AIM

Tumor metabolism plays an important role in tumorigenesis and tumor progression. This study evaluated the potential association of tumor cell metabolism and immune cell tumor infiltration with the clinical course of hepatocellular carcinoma (HCC).

METHODS

Gene-wise normalization and principal component analysis were performed to evaluate the metabolic system. A tumor microenvironment score system of tumor immune cell infiltration was constructed to evaluate its association with metabolic subtypes. Finally, we analyzed the impact of metabolism and immune cell infiltration on the clinical course of HCC.

RESULTS

A total of 673 HCC patients were categorized into cholesterogenic (25.3%), glycolytic (14.6%), mixed (10.4%), and quiescent (49.8%) types based on glycolysis and cholesterol biosynthesis gene expression. The subgroups including the glycolytic genotyping expression (glycolytic and mixed types) showed a higher mortality rate. The glycolytic, cholesterogenic, and mixed types were positively correlated with M0 macrophage, resting mast cell, and naïve B-cell infiltration (P = .013, P = .019, and P = .006, respectively). In TCGA database, high CD8+ T cell and low M0 macrophage infiltration were associated with prolonged overall survival (OS, P = .0017 and P < .0001, respectively). Furthermore, in glycolytic and mixed types, patients with high M0 macrophage infiltration had a shorter OS (P = .03 and P = .013, respectively), and in quiescent type, patients with low naïve B-cell infiltration had a longer OS (P = .007).

CONCLUSIONS

Tumor metabolism plays a prognostic role and correlates with immune cell infiltration in HCC. M0 macrophage and CD8+ T cell appear to be promising prognostic biomarker for HCC. Finally, M0 macrophages may represent a useful immunotherapeutic target in patients with HCC.

Tumor-Associated Macrophages Expand Chemoresistant, Ovarian Cancer Stem-Like Cells

The persistence of ovarian cancer stem-like cells (OvCSCs) after chemotherapy resistance has been implicated in relapse. However, the ability of these relatively quiescent cells to produce the robust tumor regrowth necessary for relapse remains an enigma. Since normal stem cells exist in a niche, and tumor-associated macrophages (TAMs) are the highest abundance immune cell within ovarian tumors, we hypothesized that TAMs may influence OvCSC proliferation. To test this, we optimized OvCSC enrichment by sphere culture and in vitro polarization of monocytes to a TAM-like M2 phenotype. Using cocultures that permitted the exchange of only soluble factors, we found that M2 macrophages increased the proliferation of sphere cells. Longer-term exposure (5-7 days) to soluble TAM factors led to retention of some stem cell features by OvCSCs but loss of others, suggesting that TAMs may support an intermediate stemness phenotype in OvCSCs. Although TAM coculture decreased the percentage of OvCSCs surviving chemotherapy, it increased the overall number. We therefore sought to determine the influence of this interaction on chemotherapy efficacy in vivo and found that inhibiting macrophages improved chemotherapy response. Comparing the gene expression changes in OvCSCs cocultured with TAMs to publicly available patient data identified 34 genes upregulated in OvCSCs by exposure to soluble TAM factors whose expression correlates with outcome. Overall, these data suggest that TAMs may influence OvCSC proliferation and impact therapeutic response.

Prognostic Role of Neutrophil, Monocyte and Platelet to Lymphocyte Ratios in Advanced Ovarian Cancer According to the Time of Debulking Surgery

Despite a multimodal radical treatment, mortality of advanced epithelial ovarian cancer (AEOC) remains high. Host-related factors, such as systemic inflammatory response and its interplay with the immune system, remain underexplored. We hypothesized that the prognostic impact of this response could vary between patients undergoing primary debulking surgery (PDS) and those undergoing interval debulking surgery (IDS). Therefore, we evaluated the outcomes of two surgical groups of newly diagnosed AEOC patients according to the neutrophil, monocyte and platelet to lymphocyte ratios (NLR, MLR, PLR), taking median ratio values as cutoffs. In the PDS group (n = 61), low NLR and PLR subgroups showed significantly better overall survival (not reached (NR) vs. 72.7 months, 95% confidence interval [CI]: 40.9-95.2, p = 0.019; and NR vs. 56.1 months, 95% CI: 40.9-95.2, p = 0.004, respectively) than those with high values. Similar results were observed in progression free survival. NLR and PLR-high values resulted in negative prognostic factors, adjusting for residual disease, BRCA1/2 status and stage (HR 2.48, 95% CI: 1.03-5.99, p = 0.043, and HR 2.91, 95% CI: 1.11-7.64, p = 0.03, respectively). In the IDS group (n = 85), ratios were not significant prognostic factors. We conclude that NLR and PLR may have prognostic value in the PDS setting, but none in IDS, suggesting that time of surgery can modulate the prognostic impact of baseline complete blood count (CBC).

The Role of STATs in Ovarian Cancer: Exploring Their Potential for Therapy

Ovarian cancer (OvCa) is a deadly gynecologic malignancy that presents many clinical challenges due to late-stage diagnoses and the development of acquired resistance to standard-of-care treatment protocols. There is an increasing body of evidence suggesting that STATs may play a critical role in OvCa progression, resistance, and disease recurrence, and thus we sought to compile a comprehensive review to summarize the current state of knowledge on the topic. We have examined peer reviewed literature to delineate the role of STATs in both cancer cells and cells within the tumor microenvironment. In addition to summarizing the current knowledge of STAT biology in OvCa, we have also examined the capacity of small molecule inhibitor development to target specific STATs and progress toward clinical applications. From our research, the best studied and targeted factors are STAT3 and STAT5, which has resulted in the development of several inhibitors that are under current evaluation in clinical trials. There remain gaps in understanding the role of STAT1, STAT2, STAT4, and STAT6, due to limited reports in the current literature; as such, further studies to establish their implications in OvCa are necessitated. Moreover, due to the deficiency in our understanding of these STATs, selective inhibitors also remain elusive, and therefore present opportunities for discovery.

Upregulation of programmed death ligand-1 in tumor-associated macrophages affects chemotherapeutic response in ovarian cancer cells

To better understand the mechanism of chemoresistance in ovarian cancer cells, we aimed to investigate the influence of macrophages on the tumor cell response to carboplatin and identify the genes associated with chemoresistance. We mimicked the tumor microenvironment (TME) using a co-culture technique and compared the proliferation of ovarian cells with and without macrophages. We also examined M1 and M2 marker expression and the expression of key TME genes. Post the co-culture, we treated ovarian cancer cells with carboplatin and elucidated the function of programmed death-ligand 1 (PD-L1) in carboplatin chemoresistance. We investigated CD68 and PD-L1 expression in normal and cancerous ovarian tissues using immunohistochemistry (IHC). Finally, we analyzed the association between CD68 or PD-L1 expression and survival outcomes. Inducible nitric oxide synthase (iNOS) was downregulated, while the gene expression of M2 macrophage markers was increased in ovarian cancer cells. PD-L1, vascular endothelial growth factor (VEGF), Interleukin (IL)-6, IL-10, IL-12, signal transducer and activator of transcription 3 (STAT3), B-cell lymphoma 2 (BCL2), multidrug resistance 1 (MDR1), and colony stimulating factor 1 (CSF-1) were upregulated. Notably, PD-L1 was upregulated in both the ovarian cancer cells and macrophages. Ovarian cancer cells co-cultured with macrophages exhibited statistically significant carboplatin resistance compared to single-cultured ovarian cancer cells. PD-L1 silencing induced chemosensitivity in both types of co-cultured ovarian cancer cells. However, IHC results revealed no correlation between PD-L1 expression and patient survival or cancer stage. CD68 expression was significantly increased in cancer cells compared to normal or benign ovarian tumor cells, but it was not associated with the survival outcomes of ovarian cancer patients. Our study demonstrated that ovarian cancer cells interact with macrophages to induce the M2 phenotype. We also established that PD-L1 upregulation in both ovarian cancer cells and macrophages is a key factor for carboplatin chemoresistance.

Comprehensive analysis of LILR family genes expression and tumour-infiltrating immune cells in early-stage pancreatic ductal adenocarcinoma

Leucocyte immunoglobulin-like receptors (LILRs) are closely related to tumourigenesis, but their clinical value in early-stage pancreatic ductal adenocarcinoma (PDAC) after pancreaticoduodenectomy remains unknown. Kaplan-Meier and Cox proportional hazards regression models is used to investigate the association between LILR expression and prognosis in tumour biopsies and peripheral blood mononuclear cells. Risk score was calculated for each patient based on the prognostic model. DAVID, STRING, GeneMANIA, and GSEA were used to conduct pathway and functional analyses. The CIBERSORT algorithm is used to analyse tumour-infiltrating immune cells. Survival analysis showed that high levels of LILRA4 (p = 0.006) and LILRB4 (p = 0.04) were significantly associated with better overall survival. High levels of LILRA2 (p = 0.008) and LILRB4 (p = 0.038) were significantly associated with better relapse-free survival. JAK-STAT signalling pathway, regulation of T cell activation, regulation of the immune effector process, and tumour necrosis factor superfamily cytokine production were involved in molecular mechanisms that affected poor prognoses in the high-risk group in GSEA. CIBERSORT demonstrated that the high-risk group had significantly higher infiltrating fraction of memory-activated CD4 T cells and activated NK cells and lower fraction of resting dendritic cells and neutrophils. LILRB4 plays crucial roles in affecting the clinical outcomes of early-stage PDAC.

Melanoma Cell Reprogramming and Awakening of Antitumor Immunity as a Fingerprint of Hyper-Harmonized Hydroxylated Fullerene Water Complex (3HFWC) and Hyperpolarized Light Application In Vivo

In our recent study, we showed that in vitro treatment of melanoma cells with hyperpolarized light (HPL) as well as with the second derivative of fullerene, hyper-harmonized hydroxylated fullerene water complex (3HFWC) reduced viability of cells by decreasing their proliferative capacity and inducing senescence and reprogramming towards a normal, melanocytic phenotype. Therefore, we wanted to determine whether these effects persisted in vivo in the syngeneic mouse melanoma model with a combined treatment of HPL irradiation and 3HFWC per os. Our results demonstrated the potent antitumor effects of 3HFWC nanosubstance assisted by HPL irradiation. These effects were primarily driven by the stimulation of melanoma cell growth arrest, the establishment of a senescent phenotype, and melanocytic differentiation on the one hand, and the awakening of the antitumor immune response on the other. In addition, the combined treatment reduced the protumorigenic activity of immune cells by depleting T regulatory cells, myeloid-derived suppressors, and M2 macrophages. The support of the 3HFWC substance by HPL irradiation may be the axis of the new approach design based on tumor cell reprogramming synchronized with the mobilization of the host's protective immune response.

High expression of RNF169 is associated with poor prognosis in pancreatic adenocarcinoma by regulating tumour immune infiltration

Background: Pancreatic adenocarcinoma (PAAD) is a highly deadly and aggressive tumour with a poor prognosis. However, the prognostic value of RNF169 and its related mechanisms in PAAD have not been elucidated. In this study, we aimed to explore prognosis-related genes, especially RNF169 in PAAD and to identify novel potential prognostic predictors of PAAD. Methods: The GEPIA and UALCAN databases were used to investigate the expression and prognostic value of RNF169 in PAAD. The correlation between RNF169 expression and immune infiltration was determined by using TIMER and TISIDB. Correlation analysis with starBase was performed to identify a potential regulatory axis of lncRNA-miRNA-RNF169. Results: The data showed that the level of RNF169 mRNA expression in PAAD tissues was higher than that in normal tissues. High RNF169 expression was correlated with poor prognosis in PAAD. In addition, analysis with the TISIDB and TIMER databases revealed that RNF169 expression was positively correlated with tumour immune infiltration in PAAD. Correlation analysis suggested that the long non-coding RNA (lncRNA) AL049555.1 and the microRNA (miRNA) hsa-miR-324-5p were involved in the expression of RNF169, composing a potential regulatory axis to control the progression of PAAD. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses indicated that RNF169 plays a role in PAAD through pathways such as TNF, Hippo, JAK-STAT and Toll-like receptor signaling. Conclusion: In summary, the upregulation of RNF169 expression mediated by ncRNAs might influence immune cell infiltration in the microenvironment; thus, it can be used as a prognostic biomarker and a potential therapeutic target in PAAD.

Integration of local and systemic immunity in ovarian cancer: Implications for immunotherapy

Cancer is a disease that induces many local and systemic changes in immunity. The difficult nature of ovarian cancer stems from the lack of characteristic symptoms that contributes to a delayed diagnosis and treatment. Despite the enormous progress in immunotherapy, its efficacy remains limited. The heterogeneity of tumors, lack of diagnostic biomarkers, and complex immune landscape are the main challenges in the treatment of ovarian cancer. Integrative approaches that combine the tumor microenvironment - local immunity - together with periphery - systemic immunity - are urgently needed to improve the understanding of the disease and the efficacy of treatment. In fact, multiparametric analyses are poised to improve our understanding of ovarian tumor immunology. We outline an integrative approach including local and systemic immunity in ovarian cancer. Understanding the nature of both localized and systemic immune responses will be crucial to boosting the efficacy of immunotherapies in ovarian cancer patients.

Targeted drug delivery system for ovarian cancer microenvironment: Improving the effects of immunotherapy

Immunotherapies have shown modest benefits in the current clinical trials for ovarian cancer. The tumor microenvironment (TME) in an immunosuppressive phenotype contributes to this “failure” of immunotherapy in ovarian cancer. Many stromal cell types in the TME (e.g., tumor-associated macrophages and fibroblasts) have been identified as having plasticity in pro- and antitumor activities and are responsible for suppressing the antitumor immune response. Thus, the TME is an extremely valuable target for adjuvant interventions to improve the effects of immunotherapy. The current strategies targeting the TME include: 1) eliminating immunosuppressive cells or transforming them into immunostimulatory phenotypes and 2) inhibiting their immunosuppressive or pro-tumor production. Most of the effective agents used in the above strategies are genetic materials (e.g., cDNA, mRNA, or miRNA), proteins, or other small molecules (e.g., peptides), which are limited in their target and instability. Various formulations of drug delivery system (DDS) have been designed to realize the controlled release and targeting delivery of these agents to the tumor sites. Nanoparticles and liposomes are the most frequently exploited materials. Based on current evidence from preclinical and clinical studies, the future of the DDS is promising in cancer immunotherapy since the combination of agents with a DDS has shown increased efficacy and decreased toxicities compared with free agents. In the future, more efforts are needed to further identify the hallmarks and biomarkers in the ovarian TME, which is crucial for the development of more effective, safe, and personalized DDSs.

A novel subtype to predict prognosis and treatment response with DNA driver methylation-transcription in ovarian cancer

Aims: To identify a novel subtype with DNA driver methylation-transcriptomic multiomics and predict prognosis and therapy response in serous ovarian cancer (SOC). Methods: SOC cohorts with both mRNA and methylation were collected, and DNA driver methylation (DNAme) was identified with the MithSig method. A novel prognostic subtype was developed by integrating the information on DNAme and prognosis-regulated DNAme-associated mRNA by similarity network fusion. Results: 43 overlapped DNAme were identified in three independent cohorts. SOC patients were categorized into three distinct subtypes by integrated multiomics. There were differences in prognosis, tumor microenvironment and response to therapy among the subtypes. Conclusion: This study identified 43 DNAmes and proposes a novel subtype toward personalized chemotherapy and immunotherapy for SOC patients based on multiomics.

Integrated identification of key immune related genes and patterns of immune infiltration in calcified aortic valvular disease: A network based meta-analysis

Background: As the most prevalent valvular heart disease, calcific aortic valve disease (CAVD) has become a primary cause of aortic valve stenosis and insufficiency. We aim to illustrate the roles of immune related genes (IRGs) and immune cells infiltration in the occurrence of CAVD.

Methods: Integrative meta-analysis of expression data (INMEX) was adopted to incorporate multiple gene expression datasets of CAVD from Gene Expression Omnibus (GEO) database. By matching the differentially expressed genes (DEGs) to IRGs from “ImmPort” database, differentially expressed immune related genes (DEIRGs) were screened out. We performed enrichment analysis and found that DEIRGs in CAVD were closely related to inflammatory response and immune cells infiltration. We also constructed protein–protein interaction (PPI) network of DEIRGs and identified 5 key DEIRGs in CAVD according to the mixed character calculation results. Moreover, CIBERSORT algorithm was used to explore the profile of infiltrating immune cells in CAVD. Based on Spearman’s rank correlation method, correlation analysis between key DEIRGs and infiltrating immune cells was performed.

Results: A total of 220 DEIRGs were identified and the enrichment analysis of DEIRGs showed that they were significantly enriched in inflammatory responses. PPI network was constructed and PTPN11, GRB2, SYK, PTPN6 and SHC1 were identified as key DEIRGs. Compared with normal aortic valve tissue samples, the proportion of neutrophils, T cells CD4 memory activated and macrophages M0 was elevated in calcified aortic valves tissue samples, as well as reduced infiltration of macrophages M2 and NK cells activated. Furthermore, key DEIRGs identified in the present study, including PTPN11, GRB2, PTPN6, SYK, and SHC1, were all significantly correlated with infiltration of various immune cells.

Conclusion: This meta-analysis suggested that PTPN11, GRB2, PTPN6, SYK, and SHC1 might be key DEIRGs associated with immune cells infiltration, which play a pivotal role in pathogenesis of CAVD.

Adaptive transcriptomic and immune infiltrate responses in the tumor immune microenvironment following neoadjuvant chemotherapy in high grade serous ovarian cancer reveal novel prognostic associations and activation of pro-tumorigenic pathways

The high rate of ovarian cancer recurrence and chemoresistance necessitates further research into how chemotherapy affects the tumor immune microenvironment (TIME). While studies have shown that immune infiltrate increases following neoadjuvant (NACT) chemotherapy, there lacks a comprehensive understanding of chemotherapy-induced effects on immunotranscriptomics and cancer-related pathways and their relationship with immune infiltrate and patient responses. In this study, we performed NanoString nCounter^® PanCancer IO360 analysis of 31 high grade serous ovarian cancer (HGSOC) patients with matched pre-treatment biopsy and post-NACT tumor. We observed increases in pro-tumorigenic and immunoregulatory pathways and immune infiltrate following NACT, with striking increases in a cohort of genes centered on the transcription factors ATF3 and EGR1. Using quantitative PCR, we analyzed several of the top upregulated genes in HGSOC cell lines, noting that two of them, ATF3 and AREG, were consistently upregulated with chemotherapy exposure and significantly increased in platinum resistant cells compared to their sensitive counterparts. Furthermore, we observed that pre-NACT immune infiltrate and pathway scores were not strikingly related to platinum free interval (PFI), but post-NACT immune infiltrate, pathway scores, and gene expression were. Finally, we found that higher levels of a cohort of proliferative and DNA damage-related genes was related to shorter PFI. This study underscores the complex alterations in the ovarian TIME following chemotherapy exposure and begins to untangle how immunologic factors are involved in mediating chemotherapy response, which will allow for the future development of novel immunologic therapies to combat chemoresistance.

Identification of Tumor Microenvironment Scoring Scheme Based on Bioinformatics Analysis of Immune Cell Infiltration Pattern of Ovarian Cancer

Background

Tumor microenvironment (TME) is the crucial mediator of tumor progression, and the TME model based on immune cell infiltration to characterize ovarian cancer is considered to be a promising strategy.

Methods

Sample data of three ovarian cancer cohorts were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The scores of 22 kinds of immune cells were calculated based on CIBERSORT, and the TME clusters (TMECs) of ovarian cancer was determined by ConsensusClusterPlus. Genomic subtype was identified by non-negative matrix factorization (NMF). A TME scoring scheme was constructed using k-means algorithm and principal component analysis (PCA) to quantify the TME infiltration pattern of individuals.

Results

Four TME subtypes of ovarian cancer samples were defined: TMEC1, TMEC2, TMEC3, and TMEC4. There were also significant differences in overall survival (OS) among the four TMEC, and the OS of TMEC3 was the longest. The difference analysis of TMEC3 and the other three TMECs respectively identified the DEGs and took the intersection, and 585 DEGs were obtained. Two genomic subtypes were identified by NMF based on the expression of 585 genes, which were called GeneC1 and GeneC2. The TME scoring scheme constructed by k-means and PCA algorithm was used to calculate the TME score of ovarian cancer in TCGA. High-TME score was significantly correlated with shorter survival time, older age, lower immunoactivated molecules, and immune checkpoint gene expression.

Conclusions

This study highlighted the complexity and diversity of TME infiltration patterns in ovarian cancer and constructed a set of TME scoring scheme to reveal TME infiltration patterns and provided new insights into the landscape of TME.

Genomic and epigenomic BRCA alterations predict adaptive resistance and response to platinum-based therapy in patients with triple-negative breast and ovarian carcinomas

Triple-negative breast cancer (TNBC) and ovarian carcinomas (OvCas) with BRCA1 promoter methylation ( BRCA1 meth) respond more poorly to alkylating agents compared to those bearing mutations in BRCA1 and BRCA2 ( BRCA mut). This is a conundrum given the biologically equivalent homologous recombination deficiency (HRD) induced by these genetic and epigenetic BRCA perturbations. We dissected this problem through detailed genomic analyses of TNBC and OvCa cohorts and experimentation with patient-derived xenografts and genetically engineered cell lines. We found that despite identical downstream genomic mutational signatures associated with BRCA1 meth and BRCA mut states, BRCA1 meth uniformly associates with poor outcomes. Exposure of BRCA1 meth TNBCs to platinum chemotherapy, either as clinical treatment of a patient or as experimental in vivo exposure of preclinical patient derived xenografts, resulted in allelic loss of BRCA1 methylation and increased BRCA1 expression and platinum resistance. These data suggest that, unlike BRCA mut cancers, where BRCA loss is a genetically “fixed” deficiency state, BRCA1 meth cancers are highly adaptive to genotoxin exposure and, through reversal of promoter methylation, recover BRCA1 expression and become resistant to therapy. We further found a specific augmented immune transcriptional signal associated with enhanced response to platinum chemotherapy but only in patients with BRCA-proficient cancers. We showed how integrating both this cancer immune signature and the presence of BRCA mutations results in more accurate predictions of patient response when compared to either HRD status or BRCA status alone. This underscores the importance of defining BRCA heterogeneity in optimizing the predictive precision of assigning response probabilities in TNBC and OvCa.

Interrogation of T Cell-Enriched Tumors Reveals Prognostic and Immunotherapeutic Implications of Polyamine Metabolism

Metabolic features of the tumor microenvironment (TME) antagonize anti-tumor immunity. We hypothesized that T cell infiltrated tumors with a known antigen should exhibit superior clinical outcomes, though some fare worse given unfavorable metabolic features leveraging T cell-infiltrated (Thi), human papillomavirus-related (HPV+) head and neck squamous cell carcinomas (HNSC) to test this hypothesis. Expression of 2,520 metabolic genes were analyzed among Thi HPV+ HNSCs stratified by high-risk molecular subtype. RNAseq data from The Cancer Genome Atlas (TCGA; 10 cancer types), single cell RNAseq data, and an immunotherapy-treated melanoma cohort were used to test the association between metabolic gene expression and clinical outcomes and contribution of tumor versus stromal cells to metabolic gene expression. Polyamine (PA) metabolism genes were overexpressed in high-risk, Thi HPV+ HNSCs. Genes involved in PA biosynthesis and transport were associated with T cell infiltration, recurrent or persistent cancer, overall survival status, primary site, molecular subtype, and MYC genomic alterations. PA biogenesis gene sets were associated with tumor intrinsic features while myeloid cells in HPV+ HNSCs were enriched in PA catabolism, regulatory, transport, putrescine, and spermidine gene set expression. PA gene set expression also correlated with IFNγ or cytotoxic T cell ssGSEA scores across TCGA tumor types. PA transport ssGSEA scores were associated with poor survival whereas putrescine ssGSEA scores portended better survival for several tumor types. Thi melanomas enriched in PA synthesis or combined gene set expression exhibited worse anti-PD-1 responses. These data address hurdles to anti-tumor immunity warranting further investigation of divergent polyamine metabolism in the TME.

Comprehensive Analysis of mTORC1 Signaling Pathway–Related Genes in the Prognosis of HNSCC and the Response to Chemotherapy and Immunotherapy

Objective: The mammalian target of the rapamycin complex 1 (mTORC1) signaling pathway has emerged as a crucial player in the oncogenesis and development of head and neck squamous cell carcinoma (HNSCC), however, to date, no relevant gene signature has been identified. Therefore, we aimed to construct a novel gene signature based on the mTORC1 pathway for predicting the outcomes of patients with HNSCC and their response to treatment.

Methods: The gene expression and clinical data were retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The key prognostic genes associated with the mTORC1 pathway were screened by univariate Cox regression analyses. A prognostic signature was then established based on significant factors identified in the multivariate Cox regression analysis. The performance of the multigene signature was evaluated by the Kaplan–Meier (K–M) survival analysis and receiver operating characteristic (ROC) analysis. Based on the median risk score, patients were categorized into high- and low-risk groups. Subsequently, a hybrid prognostic nomogram was constructed and estimated by a calibration plot and decision curve analysis. Furthermore, immune cell infiltration and therapeutic responses were compared between the two risk groups. Finally, we measured the expression levels of seven genes by quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC).

Results: The mTORC1 pathway–based signature was constructed using the seven identified genes (SEC11A, CYB5B, HPRT1, SLC2A3, SC5D, CORO1A, and PIK3R3). Patients in the high-risk group exhibited a lower overall survival (OS) rate than those in the low-risk group in both datasets. Through the univariate and multivariate Cox regression analyses, this gene signature was confirmed to be an independent prognostic risk factor for HNSCC. The constructed nomogram based on age, American Joint Committee on Cancer (AJCC) stage, and the risk score exhibited satisfactory performance in predicting the OS. In addition, immune cell infiltration and chemotherapeutic and immunotherapeutic responses differed significantly between the two risk groups. The expression levels of SEC11A and CYB5B were higher in HNSCC tissues than in normal tissues.

Conclusion: Our study established and verified an mTORC1 signaling pathway–related gene signature that could be used as a novel prognostic factor for HNSCC.

NIBAN1, Exploring its Roles in Cell Survival Under Stress Context

Cell survival must quickly activate specific mechanisms that enable to detect changes in the cellular microenvironment. The impact of these cell alteration has direct consequences on cellular homeostasis. Cellular stress, as well as its regulation and implication, has been studied in different pathologies. In this sense, the alteration in NIBAN1 expression seems to act in response to different cellular disturbances. Over the years, the knowledge of NIBAN1 functions has improved, demonstrating its important cell roles, favoring the cell survival under stress context. In response to the disturbances, NIBAN1 seems to be involved in the decision-making process between cell survival and death. The increase in NIBAN1 expression has been related to cellular mechanisms that seek to minimize the damage caused to cellular homeostasis. In this review, the main biological insights attributed to the NIBAN1 gene in different cellular contexts and its role as a mediator of cellular stress are discussed.

The STING pathway: Therapeutic vulnerabilities in ovarian cancer

Ovarian cancer is the leading cause of mortality due to gynecologic malignancy. The majority of women diagnosed with the most common subtype, high-grade serous ovarian carcinoma (HGSC), develop resistance to conventional therapies despite initial response to treatment. HGSC tumors displaying DNA damage repair (DDR) gene deficiency and high chromosomal instability mainly associate with higher cytotoxic immune cell infiltration and expression of genes associated with these immune pathways. Despite the high level of immune infiltration observed, the majority of patients with HGSC have not benefited from immunomodulatory treatments as the mechanistic basis of this infiltration is unclear. This lack of response can be primarily attributed to heterogeneity at the levels of both cancer cell genetic alterations and the tumour immune microenvironment. Strategies to enhance anti-tumour immunity have been investigated in ovarian cancer, of which interferon activating therapies present as an attractive option. Of the several type I interferon (IFN-1) stimulating therapies, exogenously activating the cyclic GMP-AMP synthase-stimulator of interferon genes (cGAS-STING) pathway is emerging as a promising avenue. Herein, we highlight our current understanding of how constitutive and induced cGAS-STING pathway activation influences the ovarian tumour microenvironment. We further elaborate on the links between the genomic alterations prevalent in ovarian tumours and how the resultant immune phenotypes can make them more susceptible to exogenous STING pathway activation and potentiate immune-mediated killing of cancer cells. The therapeutic potential of cGAS-STING pathway activation in ovarian cancer and factors implicating treatment outcomes are discussed, providing a rationale for future combinatorial treatment approaches on the backbone of chemotherapy.

Effect of Particle Carriers for Intraperitoneal Drug Delivery on the Course of Ovarian Cancer and Its Immune Microenvironment in a Mouse Model

Novel treatment strategies are needed to provide a better prognosis for ovarian cancer. For this purpose, the current study was designed to evaluate the effects of different types of particle drug carriers on tumor response and on the tumor immune microenvironment (TME) after intraperitoneal (IP) administration in a murine tumor model. Mice with ID8-fLuc ovarian cancer were injected IP with pegylated liposomes, hydroxyapatite, polystyrene, poly(lactic-co-glycolic acid) (PLGA) and calcium carbonate (CaCO₃) microparticles to evaluate the effect of the candidate carriers without drugs. Our results show that several types of microparticle drug carriers caused hyperproliferation of the tumor when injected IP, as reflected in a reduced survival or an accelerated onset of ascites. Alterations of the product formulation of CaCO₃ microparticles could result in less hyperproliferation. The hyperproliferation caused by CaCO₃ and PLGA was largely driven by a strong innate immune suppression. A combination with chemotherapy was not able to sufficiently counteract the tumor progression caused by the drug carriers. This research points towards the importance of evaluating a drug carrier before using it in a therapeutic setting, since drug carriers themselves can detrimentally influence tumor progression and immune status of the TME. However, it remains to be determined whether the hyperproliferation in this model will be of relevance in other cancer models or in humans.

Analysis of potential genetic biomarkers using machine learning methods and immune infiltration regulatory mechanisms underlying atrial fibrillation

Objective

We aimed to screen out biomarkers for atrial fibrillation (AF) based on machine learning methods and evaluate the degree of immune infiltration in AF patients in detail.

Methods

Two datasets (GSE41177 and GSE79768) related to AF were downloaded from Gene expression omnibus (GEO) database and merged for further analysis. Differentially expressed genes (DEGs) were screened out using “limma” package in R software. Candidate biomarkers for AF were identified using machine learning methods of the LASSO regression algorithm and SVM-RFE algorithm. Receiver operating characteristic (ROC) curve was employed to assess the diagnostic effectiveness of biomarkers, which was further validated in another independent validation dataset of GSE14975. Moreover, we used CIBERSORT to study the proportion of infiltrating immune cells in each sample, and the Spearman method was used to explore the correlation between biomarkers and immune cells.

Results

129 DEGs were identified, and CYBB, CXCR2, and S100A4 were identified as key biomarkers of AF using LASSO regression and SVM-RFE algorithm. Both in the training dataset and the validation dataset, CYBB, CXCR2, and S100A4 showed favorable diagnostic effectiveness. Immune infiltration analysis indicated that, compared with sinus rhythm (SR), the atrial samples of patients with AF contained a higher T cells gamma delta, neutrophils and mast cells resting, whereas T cells follicular helper were relatively lower. Correlation analysis demonstrated that CYBB, CXCR2, and S100A4 were significantly correlated with the infiltrating immune cells.

Conclusions

In conclusion, this study suggested that CYBB, CXCR2, and S100A4 are key biomarkers of AF correlated with infiltrating immune cells, and infiltrating immune cells play pivotal roles in AF.

Identification of the Immune Signatures for Ovarian Cancer Based on the Tumor Immune Microenvironment Genes

Ovarian cancer (OV) is a deadly gynecological cancer. The tumor immune microenvironment (TIME) plays a pivotal role in OV development. However, the TIME of OV is not fully known. Therefore, we aimed to provide a comprehensive network of the TIME in OV. Gene expression data and clinical information from OV patients were obtained from the Cancer Genome Atlas Program (TCGA) database. Non-negative Matrix Factorization, NMFConsensus, and nearest template prediction algorithms were used to perform molecular clustering. The biological functions of differentially expressed genes (DEGs) were identified using Metascape, gene set enrichment analysis (GSEA), gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The copy number variations (CNVs), single nucleotide polymorphisms (SNPs) and tumor mutation burden were analyzed using Gistic 2.0, R package maftools, and TCGA mutations, respectively. Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data and CIBERSORT were utilized to elucidate the TIME. Moreover, external data from the International Cancer Genome Consortium (ICGC) and ArrayExpress databases were used to validate the signature. All 361 samples from the TCGA OV dataset were classified into Immune Class and non-Immune Class with immune signatures. By comparing the two classes, we identified 740 DEGs that accumulated in immune-related, cancer-related, inflammation-related biological functions and pathways. There were significant differences in the CNVs between the Immune and non-Immune Classes. The Immune Class was further divided into immune-activated and immune-suppressed subtypes. There was no significant difference in the top 20 genes in somatic SNPs among the three groups. In addition, the immune-activated subtype had significantly increased proportions of CD4 memory resting T cells, T cells, M1 macrophages, and M2 macrophages than the other two groups. The qRT-PCR results indicated that the mRNA expression levels of RYR2, FAT3, MDN1 and RYR1 were significantly down-regulated in OV compared with normal tissues. Moreover, the signatures of the TIME were validated using ICGC cohort and the ArrayExpress cohort. Our study clustered the OV patients into an immune-activated subtype, immune-suppressed subtype, and non-Immune Class and provided potential clues for further research on the molecular mechanisms and immunotherapy strategies of OV.

Molecular Mechanism of Gleditsiae Spina for the Treatment of High-Grade Serous Ovarian Cancer Based on Network Pharmacology and Pharmacological Experiments

Background

Gleditsiae Spina, widely used in traditional Chinese medicine, has a good curative effect on malignant tumors such as ovarian cancer, but the mechanism is not clear. So, we aimed to analyze the pharmacological mechanism of Gleditsiae Spina in the treatment of high-grade serous ovarian cancer (HGSC) based on network pharmacology and biological experiments.

Methods

The main active ingredients of Gleditsiae Spina were identified by high performance liquid chromatography (HPLC) and mass spectrometry (MS), and the active ingredients were performed by ADME screening. The component targets of Gleditsiae Spina were screened using the PharmMapper platform, and differentially expressed genes in normal and HGSC tissues were identified through the GEO database. Thereafter, the network of “active ingredient-targets” was constructed by cytoscape 3.7.2 software. The protein-protein interaction network was established by the BioGenet database to mine the potential protein function. Biological processes and pathways were analyzed through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis. The binding ability of the core components of the Gleditsiae Spina and the core target of HGSC was verified by molecular docking and molecular dynamics simulation, and the therapeutic effect of Gleditsiae Spina was proved in vitro through cytotoxicity experiments. The effect of Gleditsiae Spina on the core pathway is obtained by western blotting.

Results

Gleditsiae Spina had cytotoxicity on HGSC based on network pharmacology and biological experiments. Luteolin, genistein, D-(+)-tryptophan, ursolic acid, and berberine are the identified core active ingredients of Gleditsiae Spina for regulating HGSC, with HPSE, PI3KCA, AKT1, and CTNNB1as the ideal targets. The prediction results were verified by molecular docking, molecular dynamic simulation, cell viability, and western blot analysis.

Conclusion

Gleditsiae Spina mainly downregulates the expression of heparanase and β-catenin to affect the composition of tumor cytoplasmic matrix and can regulate the PI3K-AKT pathway, integrating multiple targets and multiple pathways to play a therapeutic role. It also provides a theoretical basis for the prevention of ovarian cancer and its treatment using traditional Chinese medicine in the future.

A Novel Signature of Lipid Metabolism-Related Gene Predicts Prognosis and Response to Immunotherapy in Lung Adenocarcinoma

Background: Lipid metabolism disorder, a new hallmark of cancer initiation, has been involved in lung adenocarcinoma (LUAD). However, few biomarkers about lipid metabolism-related genes (LMRGs) have been developed for prognosis prediction and clinical treatment of LUAD patients.

Methods: In this study, we constructed and validated an effective prognostic prediction model for LUAD patients depending on LMRGs. Subsequently, we investigated the prediction model from immune microenvironment, genomic changes, and immunotherapy.

Results: Then, eleven LMRGs were identified and applied to LUAD subtyping. In comparison with the high-risk group, the low-risk group exhibited a remarkably favorable prognosis, along with a higher immune score and lower tumor purity. Moreover, the low-risk group presented higher levels of immune checkpoint molecules, lower tumor immune dysfunction and exclusion (TIDE) score and tumor mutation burden (TMB), and higher likelihood of benefiting from immunotherapy. Furthermore, the genomic changes of six LMRGs (CD79A, HACD1, CYP17A1, SLCO1B3, ANGPTL4, and LDHA) were responsible for the difference in susceptibility to LUAD by greatly influencing B-cell activation.

Conclusion: Generally speaking, the LMRG model is a reliable independent biomarker for predicting adverse outcomes in LUAD patients and has the potential to facilitate risk-stratified immunotherapy.

Genomic Instability Is Defined by Specific Tumor Microenvironment in Ovarian Cancer: A Subgroup Analysis of AGO OVAR 12 Trial

Background: Following disappointing results with PD-1/PD-L1 inhibitors in ovarian cancer, it is essential to explore other immune targets. The aim of this study is to describe the tumor immune microenvironment (TME) according to genomic instability in high grade serous ovarian carcinoma (HGSOC) patients receiving primary debulking surgery followed by carboplatin-paclitaxel chemotherapy +/− nintedanib. Methods: 103 HGSOC patients’ tumor samples from phase III AGO-OVAR-12 were analyzed. A comprehensive analysis of the TME was performed by immunohistochemistry on tissue microarray. Comparative genomic hybridization was carried out to evaluate genomic instability signatures through homologous recombination deficiency (HRD) score, genomic index, and somatic copy number alterations. The relationship between genomic instability and TME was explored. Results: Patients with high intratumoral CD3+ T lymphocytes had longer progression-free survival (32 vs. 19.6 months, p = 0.009) and overall survival (OS) (median not reached). High HLA-E expression on tumor cells was associated with a longer OS (median OS not reached vs. 52.9 months, p = 0.002). HRD profile was associated with high HLA-E expression on tumor cells and an improved OS. In the multivariate analysis, residual tumor, intratumoral CD3, and HLA-E on tumor cells were more predictive than other parameters. Conclusions: Our results suggest HLA-E/CD94-NKG2A/2C is a potential immune target particularly in the HRD positive ovarian carcinoma subgroup.

Development and validation of a novel 3-gene prognostic model for pancreatic adenocarcinoma based on ferroptosis-related genes

Background

Molecular markers play an important role in predicting clinical outcomes in pancreatic adenocarcinoma (PAAD) patients. Analysis of the ferroptosis-related genes may provide novel potential targets for the prognosis and treatment of PAAD.

Methods

RNA-sequence and clinical data of PAAD was downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) public databases. The PAAD samples were clustered by a non-negative matrix factorization (NMF) algorithm. The differentially expressed genes (DEGs) between different subtypes were used by “limma_3.42.2” package. The R software package clusterProfiler was used for functional enrichment analysis. Then, a multivariate Cox proportional and LASSO regression were used to develop a ferroptosis-related gene signature for pancreatic adenocarcinoma. A nomogram and corrected curves were constructed. Finally, the expression and function of these signature genes were explored by qRT-PCR, immunohistochemistry (IHC) and proliferation, migration and invasion assays.

Results

The 173 samples were divided into 3 categories (C1, C2, and C3) and a 3-gene signature model (ALOX5, ALOX12, and CISD1) was constructed. The prognostic model showed good independent prognostic ability in PAAD. In the GSE62452 external validation set, the molecular model also showed good risk prediction. KM-curve analysis showed that there were significant differences between the high and low-risk groups, samples with a high-risk score had a worse prognosis. The predictive efficiency of the 3-gene signature-based nomogram was significantly better than that of traditional clinical features. For comparison with other models, that our model, with a reasonable number of genes, yields a more effective result. The results obtained with qPCR and IHC assays showed that ALOX5 was highly expressed, whether ALOX12 and CISD1 were expressed at low levels in tissue samples. Finally, function assays results suggested that ALOX5 may be an oncogene and ALOX12 and CISD1 may be tumor suppressor genes.

Conclusions

We present a novel prognostic molecular model for PAAD based on ferroptosis-related genes, which serves as a potentially effective tool for prognostic differentiation in pancreatic cancer patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02431-8.

The Role of the Extracellular Matrix and Tumor-Infiltrating Immune Cells in the Prognostication of High-Grade Serous Ovarian Cancer

Ovarian cancer is the eighth global leading cause of cancer-related death among women. The most common form is the high-grade serous ovarian carcinoma (HGSOC). No further improvements in the 5-year overall survival have been seen over the last 40 years since the adoption of platinum- and taxane-based chemotherapy. Hence, a better understanding of the mechanisms governing this aggressive phenotype would help identify better therapeutic strategies. Recent research linked onset, progression, and response to treatment with dysregulated components of the tumor microenvironment (TME) in many types of cancer. In this study, using bioinformatic approaches, we identified a 19-gene TME-related HGSOC prognostic genetic panel (19 prognostic genes (PLXNB2, HMCN2, NDNF, NTN1, TGFBI, CHAD, CLEC5A, PLXNA1, CST9, LOXL4, MMP17, PI3, PRSS1, SERPINA10, TLL1, CBLN2, IL26, NRG4, and WNT9A) by assessing the RNA sequencing data of 342 tumors available in the TCGA database. Using machine learning, we found that specific patterns of infiltrating immune cells characterized each risk group. Furthermore, we demonstrated the predictive potential of our risk score across different platforms and its improved prognostic performance compared with other gene panels.

M2-Polarization-related CNTNAP1 gene might be a novel immunotherapeutic target and biomarker for clear cell renal cell carcinoma

Clear cell renal carcinoma (ccRCC) is one of the most common malignancies, characterized by high mortality rate in urology. Unfortunately, reliable biomarkers for ccRCC diagnosis and prognosis remain lacking. Contactin Associated Protein 1 (CNTNAP1) has yet to be thoroughly investigated in cancer, especially its relationship with immune infiltration or clinical outcomes of ccRCC. Here, we explored the Cancer Genome Atlas Kidney Clear Cell Carcinoma database (TCGA-KIRC) for prognostic significance, differential expression, and probable mechanism of CNTNAP1. The aberrant CNTNAP1 expression was also validated by international Cancer Genome Consortium (ICGC) and ccRCC clinic samples. We used Database for Annotation, Visualization, and Integrated Discovery (DAVID) to performed the GO & KEGG enrichment. TIMER database was further utilized to assess its correlation with immune infiltration in ccRCC. The the CellMiner database was used to analyse the relationship between CNTNAP1 expression and drug sensitivity. Results showed CNTNAP1 was upregulated in TCGA-KIRC, ICGC and clinic samples. And CNTNAP1 expression was positively related to infiltration levels of cancer-associated fibroblast, regulatory T cells, and Myeloid-derived suppressor cells, while negatively related to eosinophils. Furthermore, we observed CNTNAP1 was appreciably positively associated with alternatively activated macrophage (M2) in ccRCC. Finally, high CNTNAP1 expression was negatively correlated with Nilotinib, Crizotinib, Eribulin mesylate, and Vinorelbine. Collectively, these results strongly suggest that CNTNAP1 might act as an immunotherapeutic target and a promising novel biomarker for ccRCC.

Clinicopathological significance and underlying molecular mechanism of downregulation of basonuclin 1 expression in ovarian carcinoma

In this study, we aim to identify the clinical significance of basonuclin 1 (BNC1) expression in ovarian carcinoma (OV) and to explore its latent mechanisms. Via integrating in-house tissue microarrays, gene chips, and RNA-sequencing data, we explored the expression and clinical value of BNC1 in OV. Immunohistochemical staining was utilized to confirm the protein expression status of BNC1. A combined SMD of -2.339 (95% CI: -3.649 to -1.028, P < 0.001) identified that BNC1 was downregulated based on 1346 samples, and the sROC (AUC = 0.93) showed a favorable discriminatory ability of BNC1 in OV patients. We used univariate and multivariate Cox regulation to evaluate the prognostic role of BNC1 for OV patients, and a combined hazard ratio of 0.717 (95% CI: 0.445-0.989, P < 0.001) revealed that BNC1 was a protective factor for OV. Furthermore, the fraction of infiltrating naive B cells, memory B cells, and other immune cells showed statistical differences between the high- and low-BNC1 expression groups through cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm. Enrichment analysis showed that BNC1 may have a relationship with immune-related items in OV. By predicting the potential regulatory transcription factors (TFs) of BNC1, friend leukemia virus integration 1 (FLI1) may be a potential upstream TF of BNC1. Corporately, a decreasing trend of BNC1 may serve as a tumor suppressor and prognostic biomarker in OV patients. Moreover, BNC1 may take part in immune-related pathways and influence the fraction of tumor-infiltrating immune cells.

Significance of TEAD Family in Diagnosis, Prognosis and Immune Response for Ovarian Serous Carcinoma

Purpose

To explore the molecular profiles of transcriptional enhanced associate domain (TEAD) family in ovarian serous carcinoma (OSC).

Methods

In this study, we use bioinformatics methods including GEPIA, GE-mini, Oncomine 3.0, Kaplan–Meier plotter, cBioPortal, WebGestalt, TIMER2.0 and DiseaseMeth2.0, and in vitro experimental RT-PCR to assess the expression profiles and prognostic significance of TEAD family in OSC.

Results

According to the bioinformatics analysis, TEAD family was abnormally expressed in OSC. In terms of prognosis, Kaplan–Meier plotter indicated that OSC patients with high level of TEAD4 showed poor overall survival (OS), progression-free survival (PFS) and post progression survival (PPS). TEAD family also had significantly diagnostic values for OSC patients. Tumor Immune Estimation Resource (TIMER) algorithm indicated that TEAD family was significantly associated with different types of infiltrating immune cells, including B cells, macrophages, dendritic cells, neutrophils, CD8+ T cells and CD4+ T cells. Gene set enrichment analysis of TEAD family-associated coexpression genes was further explored. In in vitro experiments, the RT-PCR results showed the upregulated TEAD2/4 in OSC tissues and cells (A2780 and TOV112D). Moreover, decreased expression of TEAD2 could induce the ferroptosis through increasing the ROS accumulation.

Conclusion

Thus, TEAD family correlated with the diagnosis, prognosis and immune infiltration in OSC. These results could provide comprehensive understanding of TEAD family in the diagnosis and prognosis of OSC patients.

Prognostic value of preoperative soluble interleukin 2 receptor α as a novel immune biomarker in epithelial ovarian cancer

PURPOSE

Epithelial ovarian cancer (EOC) is regarded as the deadliest gynecological cancer, and the demand for novel noninvasive prognostic biomarkers remains significant. This study aimed to investigate the prognostic value of preoperative blood biomarkers in EOC patients.

METHODS

In total, 73 patients who had undergone ovarian mass resection were enrolled. Serum concentration of biomarkers, including soluble interleukin 2 receptor α (sIL-2R), was measured 1-2 weeks before surgery. Independent prognostic factors for progression-free survival (PFS) were investigated with multivariate Cox regression analysis. A prognostic model was subsequently developed and evaluated by discrimination, calibration and clinical net benefit. Furthermore, transcriptome data of 376 EOC cases from The Cancer Genome Atlas (TCGA) were analyzed with ESTIMATE, CIBERSORT and Maftools algorithm to evaluate the correlation of IL2RA expression with tumor immune microenvironment and immunotherapeutic response.

RESULTS

High sIL-2R concentration was found to be the only significant prognostic blood biomarker for PFS by multivariate Cox regression analysis in our center. A prognostic nomogram was developed with satisfactory discrimination, calibration and clinical net benefit. In addition, higher IL2RA expression was significantly associated with higher immune scores, activated CD4⁺ T cells, M2 macrophages and resting dendritic cells in TCGA data. Furthermore, IL2RA expression was closely related to TMB scores.

CONCLUSIONS

sIL-2R is a potential prognostic immune biomarker for EOC patients, and a comprehensive prognostic model comprising sIL-2R with satisfactory discrimination and clinical appliance was developed. Therefore, we recommend routine sIL-2R testing in EOC patients.

Omental Macrophagic "Crown-like Structures" Are Associated with Poor Prognosis in Advanced-Stage Serous Ovarian Cancer

The tumor microenvironment is a well-recognized framework in which immune cells present in the tumor microenvironment promote or inhibit cancer formation and development. A crown-like structure (CLS) has been reported as a dying or dead adipocyte surrounded by a 'crown' of macrophages within adipose tissue, which is a histologic hallmark of the inflammatory process in this tissue. CLSs have also been found to be related to formation, progression and prognosis of some types of cancer. However, the presence of CLSs in the omentum of advanced-stage high-grade serous ovarian carcinoma (HGSOC) has not been thoroughly investigated. By using CD68, a pan-macrophage marker, and CD163, an M2-like polarization macrophage marker, immunohistochemistry (IHC) was performed to identify tumor-associated macrophages (TAMs) and CLSs. This retrospective study analyzed 116 patients with advanced-stage HGSOC who received complete treatment and had available clinical data from July 2008 through December 2016 at National Cheng Kung University Hospital (NCKUH) (Tainan, Taiwan). Based on multivariate Cox regression analysis, patients with omental CD68⁺ CLSs had poor OS (median survival: 24 vs. 38 months, p = 0.001, hazard ratio (HR): 2.26, 95% confidence interval (CI): 1.41-3.61); patients with omental CD163⁺ CLSs also had poor OS (median survival: 22 vs. 36 months, HR: 2.14, 95%CI: 1.33-3.44, p = 0.002). Additionally, patients with omental CD68⁺ or CD163⁺ CLSs showed poor PFS (median survival: 11 vs. 15 months, HR: 2.28, 95%CI: 1.43-3.64, p = 0.001; median survival: 11 vs. 15 months, HR: 2.17, 95%CI: 1.35-3.47, respectively, p = 0.001). Conversely, the density of CD68⁺ or CD163⁺ TAMs in ovarian tumors was not associated with patient prognosis in advanced-stage HGSOC in our cohort. In conclusion, we, for the first time, demonstrate that the presence of omental CLSs is associated with poor prognosis in advanced-stage HGSOC.

CX-5461 Treatment Leads to Cytosolic DNA-Mediated STING Activation in Ovarian Cancer

Epithelial ovarian cancer (EOC) is the deadliest of the gynecologic malignancies, with an overall survival rate of <30%. Recent research has suggested that targeting RNA polymerase I (POL I) with small-molecule inhibitors may be a viable therapeutic approach to combating EOC, even when chemoresistance is present. CX-5461 is one of the most promising POL I inhibitors currently being investigated, and previous reports have shown that CX-5461 treatment induces DNA damage response (DDR) through ATM/ATR kinase. Investigation into downstream effects of CX-5461 led us to uncovering a previously unreported phenotype. Treatment with CX-5461 induces a rapid accumulation of cytosolic DNA. This accumulation leads to transcriptional upregulation of 'STimulator of Interferon Genes' (STING) in the same time frame, phosphorylation of IRF3, and activation of type I interferon response both in vitro and in vivo. This activation is mediated and dependent on cyclic GMP-AMP synthase (cGAS). Here, we show THAT CX-5461 leads to an accumulation of cytosolic dsDNA and thereby activates the cGAS-STING-TBK1-IRF3 innate immune pathway, which induces type I IFN. CX-5461 treatment-mediated immune activation may be a powerful mechanism of action to exploit, leading to novel drug combinations with a chance of increasing immunotherapy efficacy, possibly with some cancer specificity limiting deleterious toxicities.

Estrogens and the Schrödinger's Cat in the Ovarian Tumor Microenvironment

Simple Summary

Ovarian cancer is a complex pathology for which we require effective screening and therapeutical strategies. Apart from the cancer cell portion, there exist plastic immune and non-immune cell populations, jointly constituting the context-adaptive tumor microenvironment, which is pivotal in tumorigenesis. Estrogens might be synthesized in the ovarian tumor tissue and actively contribute to the shaping of an immunosuppressive microenvironment. Current immune therapies have limited effectiveness as a multitude of factors influence the outcome. A thorough understanding of the ovarian cancer biology is crucial in the efforts to reestablish homeostasis.

Abstract

Ovarian cancer is a heterogeneous disease affecting the aging ovary, in concert with a complex network of cells and signals, together representing the ovarian tumor microenvironment. As in the “Schrödinger’s cat” thought experiment, the context-dependent constituents of the—by the time of diagnosis—well-established tumor microenvironment may display a tumor-protective and -destructive role. Systemic and locally synthesized estrogens contribute to the formation of a pro-tumoral microenvironment that enables the sustained tumor growth, invasion and metastasis. Here we focus on the estrogen biosynthetic and metabolic pathways in ovarian cancer and elaborate their actions on phenotypically plastic, estrogen-responsive, aging immune cells of the tumor microenvironment, altogether highlighting the multicomponent-connectedness and complexity of cancer, and contributing to a broader understanding of the ovarian cancer biology.

Solute carrier family 16 member 5 downregulation and its methylation might serve as a prognostic indicator of prostate cancer

Prostate cancer (PCa), characterized by high invasion, metastasis, and recurrence, is the most prevalent malignant tumor in men worldwide. A clear understanding of the underlying molecular mechanisms and their role during PCa tumorigenesis can help develop prognostic and targeted therapies. We analyzed datasets from public databases, including the Cancer Genome Atlas (TCGA) and Oncomine and Gene Expression Profiling Interactive Analysis for differential expression of solute carrier family 16 member 5 (SLC16A5). We further investigated its relationship with clinical stage, pathological grade, and prognosis of PCa. The promoter methylation level of SLC16A5 in PCa was also investigated by UALCAN. We also utilized datasets from UCSC Xena to explore the prognostic role of SLC16A5 methylation levels and CpG site. Correlations between SLC16A5 and immune infiltration were discovered through TIMER. We observed significantly lower levels of SLC16A5 mRNA in PCa relative to normal tissues across six datasets from Oncomine database (p < .001) and 498 cases from TCGA database (p < .0001). SLC16A5 is strongly negatively regulated by its DNA methylation, with a Spearman of -0.81 and Pearson of -0.80 (p < .001). The aberrant SLC16A5 expression resulted in a significant relationship with clinical stage, pathological grade, and lower SLC16A5 mRNA expression, and its hypermethylation was related to a poorer PCa prognosis. SLC16A5 acted as an important factor for PCa diagnosis, with an AUC of 0.9038 (95% CI: 0.8597-0.9479; p < .0001). Besides, the aberrant SLC16A5 expression revealed close correlations with multiple immune cells. Overall, these results indicate that decreased SLC16A5 expression might be a potential biomarker for determining prognosis and immune infiltration in PCa. The positive SLC16A5 modulation might be a promising therapeutic target for PCa.

SLFN11 captures cancer-immunity interactions associated with platinum sensitivity in high-grade serous ovarian cancer

Large independent analyses on cancer cell lines followed by functional studies have identified Schlafen 11 (SLFN11), a putative helicase, as the strongest predictor of sensitivity to DNA-damaging agents (DDAs), including platinum. However, its role as a prognostic biomarker is undefined, partially due to the lack of validated methods to score SLFN11 in human tissues. Here, we implemented a pipeline to quantify SLFN11 in human cancer samples. By analyzing a cohort of high-grade serous ovarian carcinoma (HGSOC) specimens before platinum-based chemotherapy treatment, we show, for the first time to our knowledge, that SLFN11 density in both the neoplastic and microenvironmental components was independently associated with favorable outcome. We observed SLFN11 expression in both infiltrating innate and adaptive immune cells, and analyses in a second, independent, cohort revealed that SLFN11 was associated with immune activation in HGSOC. We found that platinum treatments activated immune-related pathways in ovarian cancer cells in an SLFN11-dependent manner, representative of tumor-immune transactivation. Moreover, SLFN11 expression was induced in activated, isolated immune cell subpopulations, hinting that SLFN11 in the immune compartment may be an indicator of immune transactivation. In summary, we propose SLFN11 is a dual biomarker capturing simultaneously interconnected immunological and cancer cell–intrinsic functional dispositions associated with sensitivity to DDA treatment.

Identification of Tumor Antigens and Immune Landscape in Glioblastoma for mRNA Vaccine Development

Background: Clinical benefits from standard therapies against glioblastoma (GBM) are limited in part due to the intrinsic radio- and chemo-resistance. As an essential part of tumor immunotherapy for adjunct, therapeutic tumor vaccines have been effective against multiple solid cancers, while their efficacy against GBM remains undefined. Therefore, this study aims to find the possible tumor antigens of GBM and identify the suitable population for cancer vaccination through immunophenotyping. Method: The genomic and responding clinical data of 169 GBM samples and five normal brain samples were obtained from The Cancer Genome Atlas (TCGA). The mRNA_seq data of 940 normal brain tissue were downloaded from Genotype-Tissue Expression (GTEx). Potential GBM mRNA antigens were screened out by differential expression, copy number variant (CNV), and mutation analysis. K-M survival and Cox analysis were carried out to investigate the prognostic association of potential tumor antigens. Tumor Immune Estimation Resource (TIMER) was used to explore the association between the antigens and tumor immune infiltrating cells (TIICs). Immunophenotyping of 169 samples was performed through consensus clustering based on the abundance of 22 kinds of immune cells. The characteristics of the tumor immune microenvironment (TIME) in each cluster were explored through single-sample gene set enrichment analysis based on 29 kinds of immune-related hallmarks and pathways. Weighted gene co-expression network analysis (WGCNA) was performed to cluster the genes related to immune subtypes. Finally, pathway enrichment analyses were performed to annotate the potential function of modules screened through WGCNA. Results: Two potential tumor antigens selected were significantly positively associated with the antigen-presenting immune cells (APCs) in GBM. Furthermore, the expression of antigens was verified at the protein level by Immunohistochemistry. Two robust immune subtypes, immune subtype 1 (IS1) and immune subtype 2 (IS2), representing immune status "immune inhibition" and "immune inflamed", respectively, had distinct clinical outcomes in GBM. Conclusion: ARPC1B and HK3 were potential mRNA antigens for developing GBM mRNA vaccination, and the patients in IS2 were considered the most suitable population for vaccination in GBM.

A pan-cancer analysis of the expression of gasdermin genes in tumors and their relationship with the immune microenvironment

BACKGROUND

Gasdermins (GSDMs) are a class of proteins related to pyrolysis and in humans, consist of GSDMA, GSDMB, GSDMC, GSDMD, DFNA5, and DFNB59. The inflammatory factors and cell contents released during pyrolysis can recruit immune cells and change the microenvironment. However, to date, there is a paucity of studies examining the relationship between GSDMs and the immune microenvironment in tumors. Therefore, this current report analyzed the expression of GSDM genes in tumors and their relationship with the immune microenvironment.

METHODS

Apply GSCALite and GEPIA2 online analysis tools to analyze the gene expression levels and the Single nucleotide variant (SNV), copy number variation (CNV), and methylation characteristics of GSDM genes respectively. Use R software or TISIDB online analysis tool to carry out the correlation analysis required in the article. Furthermore, Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted to examine the role of these GSDM genes in various cancers.

RESULTS

The results demonstrated that CNV can cause an increase in GSDM gene expression, and methylation can inhibit GSDM gene expression. The elevated expression of GSDMA, GSDMB, GSDMC, GSDMD, and DFNA5 in some or most tumors was often accompanied by elevated immune scores, increased immune cell infiltration, and high expression of major histocompatibility complex (MHC) molecules, chemokines and their receptors, and immune checkpoint-related genes. However, DFNB59 was often negatively correlated with these indicators in tumors. GSDMD was the most highly expressed GSDM protein in various normal tissues and tumors, and showed the strongest correlation with immune microenvironment-related genes. Moreover, the methylation of GSDMD was accompanied by low immune cell infiltration, low expression of MHC molecule-related genes, low expression of chemokines and receptor-related genes, and low expression of immune checkpoint-related genes.

CONCLUSIONS

Therefore, the expression of GSDM-related genes is associated with the tumor immune microenvironment. The GSDM genes, especially GSDMD, may be used as therapeutic targets to predict or change the tumor microenvironment and as biomarkers to predict the therapeutic efficacy of immune checkpoint inhibitors.

High-grade serous tubo-ovarian cancer refined with single-cell RNA sequencing: specific cell subtypes influence survival and determine molecular subtype classification

BACKGROUND

High-grade serous tubo-ovarian cancer (HGSTOC) is characterised by extensive inter- and intratumour heterogeneity, resulting in persistent therapeutic resistance and poor disease outcome. Molecular subtype classification based on bulk RNA sequencing facilitates a more accurate characterisation of this heterogeneity, but the lack of strong prognostic or predictive correlations with these subtypes currently hinders their clinical implementation. Stromal admixture profoundly affects the prognostic impact of the molecular subtypes, but the contribution of stromal cells to each subtype has poorly been characterised. Increasing the transcriptomic resolution of the molecular subtypes based on single-cell RNA sequencing (scRNA-seq) may provide insights in the prognostic and predictive relevance of these subtypes.

METHODS

We performed scRNA-seq of 18,403 cells unbiasedly collected from 7 treatment-naive HGSTOC tumours. For each phenotypic cluster of tumour or stromal cells, we identified specific transcriptomic markers. We explored which phenotypic clusters correlated with overall survival based on expression of these transcriptomic markers in microarray data of 1467 tumours. By evaluating molecular subtype signatures in single cells, we assessed to what extent a phenotypic cluster of tumour or stromal cells contributes to each molecular subtype.

RESULTS

We identified 11 cancer and 32 stromal cell phenotypes in HGSTOC tumours. Of these, the relative frequency of myofibroblasts, TGF-β-driven cancer-associated fibroblasts, mesothelial cells and lymphatic endothelial cells predicted poor outcome, while plasma cells correlated with more favourable outcome. Moreover, we identified a clear cell-like transcriptomic signature in cancer cells, which correlated with worse overall survival in HGSTOC patients. Stromal cell phenotypes differed substantially between molecular subtypes. For instance, the mesenchymal, immunoreactive and differentiated signatures were characterised by specific fibroblast, immune cell and myofibroblast/mesothelial cell phenotypes, respectively. Cell phenotypes correlating with poor outcome were enriched in molecular subtypes associated with poor outcome.

CONCLUSIONS

We used scRNA-seq to identify stromal cell phenotypes predicting overall survival in HGSTOC patients. These stromal features explain the association of the molecular subtypes with outcome but also the latter's weakness of clinical implementation. Stratifying patients based on marker genes specific for these phenotypes represents a promising approach to predict prognosis or response to therapy.

Extracellular Vesicle Transmission of Chemoresistance to Ovarian Cancer Cells Is Associated with Hypoxia-Induced Expression of Glycolytic Pathway Proteins, and Prediction of Epithelial Ovarian Cancer Disease Recurrence

Simple Summary

Ovarian cancer is one of the most lethal cancers affecting women worldwide. Its high mortality rate is often attributed to the non-specific nature of early symptoms of the disease. Developing a better understanding of the disease progression and identifying clinically useful biomarkers that aid in clinical management are requisite to reducing the mortality rate of ovarian cancer. Reduced oxygen tension (i.e., hypoxia) is not only a characteristic of solid tumors but may also enhance the metastatic capacity of tumors by inducing the release of tumor growth promoting factors. Recently, it has been proposed that small tumor-derived extracellular vesicles (sEVs) facilitate cancer progression. In this study, we established that sEVs produced under low oxygen tension induce a metabolic switch in ovarian cancer cells associated with changes in glycolytic pathway proteins that promote resistance to carboplatin. Significantly, we identified a suite of sEV-associated glycolysis pathway proteins that are present in patients with ovarian cancer that can predict disease recurrence with over 90% accuracy.

Abstract

Hypoxia is a key regulator of cancer progression and chemoresistance. Ambiguity remains about how cancer cells adapt to hypoxic microenvironments and transfer oncogenic factors to surrounding cells. In this study, we determined the effects of hypoxia on the bioactivity of sEVs in a panel of ovarian cancer (OvCar) cell lines. The data obtained demonstrate a varying degree of platinum resistance induced in OvCar cells when exposed to low oxygen tension (1% oxygen). Using quantitative mass spectrometry (Sequential Window Acquisition of All Theoretical Fragment Ion Mass Spectra, SWATH) and targeted multiple reaction monitoring (MRM), we identified a suite of proteins associated with glycolysis that change under hypoxic conditions in cells and sEVs. Interestingly, we identified a differential response to hypoxia in the OvCar cell lines and their secreted sEVs, highlighting the cells’ heterogeneity. Proteins are involved in metabolic reprogramming such as glycolysis, including putative hexokinase (HK), UDP-glucuronosyltransferase 1–6 (UD16), and 6-phosphogluconolactonase (6 PGL), and their presence correlates with the induction of platinum resistance. Furthermore, when normoxic cells were exposed to sEVs from hypoxic cells, platinum-resistance increased significantly (p < 0.05). Altered chemoresistance was associated with changes in glycolysis and fatty acid synthesis. Finally, sEVs isolated from a clinical cohort (n = 31) were also found to be enriched in glycolysis-pathway proteins, especially in patients with recurrent disease. These data support the hypothesis that hypoxia induces changes in sEVs composition and bioactivity that confers carboplatin resistance on target cells. Furthermore, we propose that the expression of sEV-associated glycolysis-pathway proteins is predictive of ovarian cancer recurrence and is of clinical utility in disease management.

Active Ratio Test (ART) as a Novel Diagnostic for Ovarian Cancer

Background: Despite substantial effort, there remains a lack of biomarker-based, clinically relevant testing for the accurate, non-invasive diagnostic or prognostic profiling of epithelial ovarian cancers (EOC). Our previous work demonstrated that whilst the inflammatory marker C-X-C motif chemokine ligand 10 (CXCL10) has prognostic relevance in ovarian cancer, its use is complicated by the presence of multiple, N-terminally modified variants, mediated by several enzymes including Dipeptidyl Peptidase 4 (DPP4). Methods: In this study, we provide the first evidence for the “Active Ratio Test” (ART) as a novel method to measure biologically relevant CXCL10 proteoforms in clinical samples. Results: In a cohort of 275 patients, ART accurately differentiated patients with malignant EOCs from those with benign gynaecological conditions (AUC 0.8617) and significantly out-performed CA125 alone. Moreover, ART combined with the measurement of CA125 and DPP4 significantly increased prognostic performance (AUC 0.9511; sensitivity 90.0%; specificity 91.7%; Cohen’s d > 1) for EOC detection. Conclusion: Our data demonstrate that ART provides a useful method to accurately discriminate between patients with benign versus malignant EOC, and highlights their relevance to ovarian cancer diagnosis. This marker combination may also be applicable in broader screening applications, to identify or discriminate benign from malignant disease in asymptomatic women.

KCNN4 is a potential prognostic marker and critical factor affecting the immune status of the tumor microenvironment in kidney renal clear cell carcinoma

Background

The tumor microenvironment (TME) has emerged as a crucial factor in cancer development and progression. Recent findings have indicated that tumor-infiltrating immune cells (TICs) in the TME may predict cancer prognosis and response to treatment. Herein, we sought to identify critical modulators of the kidney renal clear cell carcinoma (KIRC) TME.

Methods

KIRC datasets from The Cancer Genome Atlas (TCGA) were analyzed using the ESTIMATE algorithm to determine the ImmuneScore and StromalScore. By profiling the differentially expressed genes (DEGs) in the ImmuneScore and StromalScore, we finally identified the immune- and stromal-related DEGs of the cases, through which we then performed intersection analysis to determine the immune-related genes (IRGs). Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis were used to identify critical IRGs and construct a prognostic model. The CIBERSORT algorithm was used to calculate the relative content of 22 immune cell types. Finally, the datasets from the Gene Expression Omnibus (GEO) database were analyzed to validate results from the above analyses. Experimental validation was used on KIRC tissues by quantitative polymerase chain reaction (qPCR) and western blot.

Results

We found that the ImmuneScore was negatively correlated with patients’ prognosis. Intersection analysis of the ImmuneScore and StromalScore identified 118 IRGs that were enriched in immune-related functions. Following IRGs screening by Cox and LASSO regression analyses, six genes were identified and used to construct a KIRC prognostic model. Intersection analysis of these six genes and protein-protein interaction (PPI) were performed and obtained the most critical gene: Potassium Calcium-Activated Channel Subfamily N Member 4 (KCNN4). Further analysis showed that KCNN4 expression was higher in tumor samples relative to normal controls, and was negatively correlated with prognosis. CIBERSORT analysis revealed significant correlation between KCNN4 expression and multiple types of TICs, demonstrating that KCNN4 may affect KIRC prognosis by influencing the TME immune status. Ultimately, the GEO datasets and validation experiments confirmed that KCNN4 was highly expressed in tumor tissues compared to the corresponding normal tissues.

Conclusions

Our study demonstrated that KCNN4 might be a potential prognostic marker in KIRC, offering a novel therapeutic avenue.

Immune System-Related Changes in Preclinical GL261 Glioblastoma under TMZ Treatment: Explaining MRSI-Based Nosological Imaging Findings with RT-PCR Analyses

Glioblastomas (GB) are brain tumours with poor prognosis even after aggressive therapy. Previous work suggests that magnetic resonance spectroscopic imaging (MRSI) could act as a biomarker of efficient immune system attack onto GB, presenting oscillatory changes. Glioma-associated microglia/macrophages (GAMs) constitute the most abundant non-tumour cell type within the GB and can be polarised into anti-tumour (M1) or pro-tumour (M2) phenotypes. One of the mechanisms to mediate immunosuppression in brain tumours is the interaction between programmed cell death-1 ligand 1 (PD-L1) and programmed cell death-1 receptor (PD-1). We evaluated the subpopulations of GAMs in responding and control GB tumours to correlate PD-L1 expression to GAM polarisation in order to explain/validate MRSI-detected findings. Mice were evaluated by MRI/MRSI to assess the extent of response to treatment and with qPCR for GAMs M1 and M2 polarisation analyses. M1/M2 ratios and PD-L1 expression were higher in treated compared to control tumours. Furthermore, PD-L1 expression was positively correlated with the M1/M2 ratio. The oscillatory change in the GAMs prevailing population could be one of the key causes for the differential MRSI-detected pattern, allowing this to act as immune system activity biomarker in future work.