Periprostatic fat tissue transcriptome reveals a signature diagnostic for high-risk prostate cancer

OLFM4 modulates intestinal inflammation by promoting IL-22+ILC3 in the gut

Group 3 innate lymphoid cells (ILC3s) play key roles in intestinal inflammation. Olfactomedin 4 (OLFM4) is highly expressed in the colon and has a potential role in dextran sodium sulfate-induced colitis. However, the detailed mechanisms underlying the effects of OLFM4 on ILC3-mediated colitis remain unclear. In this study, we identify OLFM4 as a positive regulator of IL-22+ILC3. OLFM4 expression in colonic ILC3s increases substantially during intestinal inflammation in humans and mice. Compared to littermate controls, OLFM4-deficient (OLFM4-/-) mice are more susceptible to bacterial infection and display greater resistance to anti-CD40 induced innate colitis, together with impaired IL-22 production by ILC3, and ILC3s from OLFM4-/-mice are defective in pathogen resistance. Besides, mice with OLFM4 deficiency in the RORγt compartment exhibit the same trend as in OLFM4-/-mice, including colonic inflammation and IL-22 production. Mechanistically, the decrease in IL-22+ILC3 caused by OLFM4 deficiency involves the apoptosis signal-regulating kinase 1 (ASK1)- p38 MAPK signaling-dependent downregulation of RAR-related orphan receptor gamma (RORγt) protein. The OLFM4-metadherin (MTDH) complex upregulates p38/RORγt signaling, which is necessary for IL-22+ILC3 activation. The findings indicate that OLFM4 is a novel regulator of IL-22+ILC3 and essential for modulating intestinal inflammation and tissue homeostasis.

Specificities of mammary and periprostatic adipose tissues: A perspective from cancer research

In addition to the major subcutaneous and visceral adipose tissues (AT), other adipose depots are dispersed throughout the body and are found in close interaction with proximal organs such as mammary and periprostatic AT (MAT and PPAT respectively). These ATs have an effect on proximal organ function during physiological processes and diseases such as cancer. We highlighted here some of their most distinctive features in terms of tissular organization and responses to external stimuli and discussed how obesity affects them based on our current knowledge.

Systematic review and integrated analysis of prognostic gene signatures for prostate cancer patients

Prostate cancer (PC) is one of the most common cancers in men and becoming the second leading cause of cancer fatalities. At present, the lack of effective strategies for prognosis of PC patients is still a problem to be solved. Therefore, it is significant to identify potential gene signatures for PC patients' prognosis. Here, we summarized 71 different prognostic gene signatures for PC and concluded 3 strategies for signature construction after extensive investigation. In addition, 14 genes frequently appeared in 71 different gene signatures, which enriched in mitotic and cell cycle. This review provides extensive understanding and integrated analysis of current prognostic signatures of PC, which may help researchers to construct gene signatures of PC and guide future clinical treatment.

Single-cell RNA sequencing reveals tumor immune microenvironment in human hypopharygeal squamous cell carcinoma and lymphatic metastasis

Background

Human hypopharygeal squamous cell carcinoma (HSCC) is a common head and neck cancer with a poor prognosis in advanced stages. The occurrence and development of tumor is the result of mutual influence and co-evolution between tumor cells and tumor microenvironment (TME). Tumor immune microenvironment (TIME) refers to the immune microenvironment surrounding tumor cells. Studying TIME in HSCC could provide new targets and therapeutic strategies for HSCC.

Methods

We performed single-cell RNA sequencing (scRNA-seq) and analysis of hypopharyngeal carcinoma, paracancerous, and lymphoid tissues from five HSCC patients. Subdivide of B cells, T cells, macrophages cells, and monocytes and their distribution in three kinds of tissues as well as marker genes were analyzed. Different genes of IGHG1 plasma cells and SPP1+ macrophages between HSCC tissues, adjacent normal tissues and lymphatic tissues were analyzed. Additionally, we studied proliferating lymphocytes, T cells exhaustion, and T cell receptor (TCR) repertoire in three kinds of tissues.

Results

Transcriptome profiles of 132,869 single cells were obtained and grouped into seven cell clusters, including epithelial cells, lymphocytes, mononuclear phagocytics system (MPs), fibroblasts, endothelial cells (ECs), plasmacytoid dendritic cells (pDCs), and mast cells. Tumor metastasis occurred in three lymphoid tissues. Four distinct populations were identified from lymphocytes, including B cells, plasma cells, T cells and proliferating lymphocytes. We found IGHA1 and IGHG1 specific plasma cells significantly overexpressed in HSCC tissues compared with normal hypopharygeal tissues and lymphatic tissues. Five distinct populations from MPs were identified, including macrophages, monocytes, mature dendritic cells (DCs), Type 1 conventional dendritic cells (cDC1) and Type 2 conventional dendritic cells (cDC2). SPP1+ macrophages were significantly overexpressed in HSCC tissues and lymphatic tissues compared with normal hypopharygeal tissues, which are thought to be M2-type macrophages. Exhaustion of CD8+ Teff cells occurred in HSCC tissues. At last, we verified that IgA and IgG1 protein expression levels were significantly up-regulated in HSCC tissues compared to adjacent normal tissues.

Conclusion

Overall, this study revealed TIME in HSCC and lymphatic metastasis, and provided potential therapeutic targets for HSCC.

Obesity and endocrine-related cancer: The important role of IGF-1

Obesity is increasingly becoming a global epidemic of concern and is considered a risk factor for several endocrine-related cancers. Moreover, obesity is associated with cancer development and poor prognosis. As a metabolic abnormality, obesity leads to a series of changes in insulin, IGF-1, sex hormones, IGFBPs, and adipokines. Among these factors, IGF-1 plays an important role in obesity-related endocrine cancers. This review describes the role of obesity in endocrine-related cancers, such as prostate cancer, breast cancer and pancreatic cancer, focusing on the mechanism of IGF-1 and the crosstalk with estrogen and adipokines. In addition, this review briefly introduces the current status of IGF-1R inhibitors in clinical practice and shows the prospect of IGF-1R inhibitors in combination with other anticancer drugs.

Thromboinflammatory Processes at the Nexus of Metabolic Dysfunction and Prostate Cancer: The Emerging Role of Periprostatic Adipose Tissue

Simple Summary

As overweight and obesity increase among the population worldwide, a parallel increase in the number of individuals diagnosed with prostate cancer was observed. There appears to be a relationship between both diseases where the increase in the mass of fat tissue can lead to inflammation. Such a state of inflammation could produce many factors that increase the aggressiveness of prostate cancer, especially if this inflammation occurred in the fat stores adjacent to the prostate. Another important observation that links obesity, fat tissue inflammation, and prostate cancer is the increased production of blood clotting factors. In this article, we attempt to explain the role of these latter factors in the effect of increased body weight on the progression of prostate cancer and propose new ways of treatment that act by affecting how these clotting factors work.

Abstract

The increased global prevalence of metabolic disorders including obesity, insulin resistance, metabolic syndrome and diabetes is mirrored by an increased incidence of prostate cancer (PCa). Ample evidence suggests that these metabolic disorders, being characterized by adipose tissue (AT) expansion and inflammation, not only present as risk factors for the development of PCa, but also drive its increased aggressiveness, enhanced progression, and metastasis. Despite the emerging molecular mechanisms linking AT dysfunction to the various hallmarks of PCa, thromboinflammatory processes implicated in the crosstalk between these diseases have not been thoroughly investigated. This is of particular importance as both diseases present states of hypercoagulability. Accumulating evidence implicates tissue factor, thrombin, and active factor X as well as other players of the coagulation cascade in the pathophysiological processes driving cancer development and progression. In this regard, it becomes pivotal to elucidate the thromboinflammatory processes occurring in the periprostatic adipose tissue (PPAT), a fundamental microenvironmental niche of the prostate. Here, we highlight key findings linking thromboinflammation and the pleiotropic effects of coagulation factors and their inhibitors in metabolic diseases, PCa, and their crosstalk. We also propose several novel therapeutic targets and therapeutic interventions possibly modulating the interaction between these pathological states.

Multimetric feature selection for analyzing multicategory outcomes of colorectal cancer: random forest and multinomial logistic regression models

Colorectal cancer (CRC) is one of the most common cancers worldwide, and a leading cause of cancer deaths. Better classifying multicategory outcomes of CRC with clinical and omic data may help adjust treatment regimens based on individual's risk. Here, we selected the features that were useful for classifying four-category survival outcome of CRC using the clinical and transcriptomic data, or clinical, transcriptomic, microsatellite instability and selected oncogenic-driver data (all data) of TCGA. We also optimized multimetric feature selection to develop the best multinomial logistic regression (MLR) and random forest (RF) models that had the highest accuracy, precision, recall and F1 score, respectively. We identified 2073 differentially expressed genes of the TCGA RNASeq dataset. MLR overall outperformed RF in the multimetric feature selection. In both RF and MLR models, precision, recall and F1 score increased as the feature number increased and peaked at the feature number of 600-1000, while the models' accuracy remained stable. The best model was the MLR one with 825 features based on sum of squared coefficients using all data, and attained the best accuracy of 0.855, F1 of 0.738 and precision of 0.832, which were higher than those using clinical and transcriptomic data. The top-ranked features in the MLR model of the best performance using clinical and transcriptomic data were different from those using all data. However, pathologic staging, HBS1L, TSPYL4, and TP53TG3B were the overlapping top-20 ranked features in the best models using clinical and transcriptomic, or all data. Thus, we developed a multimetric feature-selection based MLR model that outperformed RF models in classifying four-category outcome of CRC patients. Interestingly, adding microsatellite instability and oncogenic-driver data to clinical and transcriptomic data improved models' performances. Precision and recall of tuned algorithms may change significantly as the feature number changes, but accuracy appears not sensitive to these changes.

Periprostatic Adipose Tissue Microenvironment: Metabolic and Hormonal Pathways During Prostate Cancer Progression

The periprostatic adipose tissue (PPAT) is a site of invasion of prostate cancer (PCa) and is part of the microenvironment. It was shown that PPAT secretes factors and fatty acids (FAs) that alter the microenvironment of the PCa. The PPAT secretome of patients with PCa-T3 stage (PPAT-T3) has a metabolic profile enriched in several pathways related to energy production, indicating a greater energy requirement by the tumor, when compared to that of patients in the PCa-T2 stage (PPAT-T2). PPAT-T3 also shows enrichment in pathways related to hormone response, polyamine synthesis, and control of protein synthesis, through amino acid, RNA, and nucleotide metabolism. PPAT-T2 and PPAT-BPH secretomes have less complex metabolic profile, both related with energy balance, while PPAT-BPH has hormone response through insulin pathway. Undoubtedly, a deeper characterization of the human PPAT will lead to a better understanding of the disease and possibly allow new stratification factors and the design of a specific therapy that targets crucial components of the tumor microenvironment as another way to treat or control the disease.

Identification of hub genes in colorectal cancer based on weighted gene co-expression network analysis and clinical data from The Cancer Genome Atlas

Colorectal cancer (CRC) is one of the most common tumors worldwide and is associated with high mortality. Here we performed bioinformatics analysis, which we validated using immunohistochemistry in order to search for hub genes that might serve as biomarkers or therapeutic targets in CRC. Based on data from The Cancer Genome Atlas (TCGA), we identified 4832 genes differentially expressed between CRC and normal samples (1562 up-regulated and 3270 down-regulated in CRC). Gene ontology (GO) analysis showed that up-regulated genes were enriched mainly in organelle fission, cell cycle regulation, and DNA replication; down-regulated genes were enriched primarily in the regulation of ion transmembrane transport and ion homeostasis. Weighted gene co-expression network analysis (WGCNA) identified eight gene modules that were associated with clinical characteristics of CRC patients, including brown and blue modules that were associated with cancer onset. Analysis of the latter two hub modules revealed the following six hub genes: adhesion G protein-coupled receptor B3 (BAI3, also known as ADGRB3), cyclin F (CCNF), cytoskeleton-associated protein 2 like (CKAP2L), diaphanous-related formin 3 (DIAPH3), oxysterol binding protein-like 3 (OSBPL3), and RERG-like protein (RERGL). Expression levels of these hub genes were associated with prognosis, based on Kaplan–Meier survival analysis of data from the Gene Expression Profiling Interactive Analysis database. Immunohistochemistry of CRC tumor tissues confirmed that OSBPL3 is up-regulated in CRC. Our findings suggest that CCNF, DIAPH3, OSBPL3, and RERGL may be useful as therapeutic targets against CRC. BAI3 and CKAP2L may be novel biomarkers of the disease.

Transcriptome sequencing and multi-plex imaging of prostate cancer microenvironment reveals a dominant role for monocytic cells in progression

BACKGROUND

Prostate cancer is caused by genomic aberrations in normal epithelial cells, however clinical translation of findings from analyses of cancer cells alone has been very limited. A deeper understanding of the tumour microenvironment is needed to identify the key drivers of disease progression and reveal novel therapeutic opportunities.

RESULTS

In this study, the experimental enrichment of selected cell-types, the development of a Bayesian inference model for continuous differential transcript abundance, and multiplex immunohistochemistry permitted us to define the transcriptional landscape of the prostate cancer microenvironment along the disease progression axis. An important role of monocytes and macrophages in prostate cancer progression and disease recurrence was uncovered, supported by both transcriptional landscape findings and by differential tissue composition analyses. These findings were corroborated and validated by spatial analyses at the single-cell level using multiplex immunohistochemistry.

CONCLUSIONS

This study advances our knowledge concerning the role of monocyte-derived recruitment in primary prostate cancer, and supports their key role in disease progression, patient survival and prostate microenvironment immune modulation.

Identification of genes that correlate clear cell renal cell carcinoma and obesity and exhibit potential prognostic value

Background

Renal cell carcinoma (RCC) is a common urologic malignancy. Although the relationship between clear cell RCC (ccRCC) and obesity has been well-established by several large-scale retrospective studies, the molecular mechanisms and genetic characteristics behind this correlation remains unclear. In the current study, several bioinformatics tools were used to identify the key genes in ccRCC related to obesity.

Methods

Microarray data comparing ccRCC with normal renal tissues in patients with and without obesity were downloaded from the GEO database for screening of differentially expressed genes (DEGs). The DEGs were verified with expression level and survival analysis using several online bioinformatics tools.

Results

In the current study, the differential expression of five genes correlated with both ccRCC and obesity; IGHA1 and IGKC as oncogenes, and MAOA, MUC20 and TRPM3 as tumor suppressor genes. These genes were verified by comparing the relationship between the expression levels and survival outcomes from open-source data in The Cancer Genome Atlas (TCGA) dataset.

Conclusions

In conclusion, the five genes differentially expressed in ccRCC and obesity are related to disease progression and prognosis, and therefore could provide prognostic value for patients with ccRCC.

Identification of a Transcriptomic Prognostic Signature by Machine Learning Using a Combination of Small Cohorts of Prostate Cancer

Determining which treatment to provide to men with prostate cancer (PCa) is a major challenge for clinicians. Currently, the clinical risk-stratification for PCa is based on clinico-pathological variables such as Gleason grade, stage and prostate specific antigen (PSA) levels. But transcriptomic data have the potential to enable the development of more precise approaches to predict evolution of the disease. However, high quality RNA sequencing (RNA-seq) datasets along with clinical data with long follow-up allowing discovery of biochemical recurrence (BCR) biomarkers are small and rare. In this study, we propose a machine learning approach that is robust to batch effect and enables the discovery of highly predictive signatures despite using small datasets. Gene expression data were extracted from three RNA-Seq datasets cumulating a total of 171 PCa patients. Data were re-analyzed using a unique pipeline to ensure uniformity. Using a machine learning approach, a total of 14 classifiers were tested with various parameters to identify the best model and gene signature to predict BCR. Using a random forest model, we have identified a signature composed of only three genes (JUN, HES4, PPDPF) predicting BCR with better accuracy [74.2%, balanced error rate (BER) = 27%] than the clinico-pathological variables (69.2%, BER = 32%) currently in use to predict PCa evolution. This score is in the range of the studies that predicted BCR in single-cohort with a higher number of patients. We showed that it is possible to merge and analyze different small and heterogeneous datasets altogether to obtain a better signature than if they were analyzed individually, thus reducing the need for very large cohorts. This study demonstrates the feasibility to regroup different small datasets in one larger to identify a predictive genomic signature that would benefit PCa patients.

Prognostic Value of CT-Attenuation and 18F-Fluorodeoxyglucose Uptake of Periprostatic Adipose Tissue in Patients with Prostate Cancer

This study aimed to assess the prognostic value of computed tomography (CT)-attenuation and ¹⁸F-fluorodeoxyglucose (FDG) uptake of periprostatic adipose tissue (PPAT) for predicting disease progression-free survival (DPFS) in patients with prostate cancer. Seventy-seven patients with prostate cancer who underwent staging FDG positron emission tomography (PET)/CT were retrospectively reviewed. CT-attenuation (HU) and FDG uptake (SUV) of PPAT were measured from the PET/CT images. The relationships between these PPAT parameters and clinical factors were assessed, and a Cox proportional hazard regression test was performed to evaluate the prognostic significance of PPAT HU and SUV. PPAT HU and SUV showed significant positive correlations with tumor stage and serum prostate-specific antigen level (PSA) (p < 0.05). Patients with high PPAT HU and SUV had significantly worse DPFS than those with low PPAT HU and SUV (p < 0.05). In multivariate analysis, PPAT SUV was a significant predictor of DPFS after adjusting for tumor stage, serum PSA, and tumor SUV (p = 0.003; hazard ratio, 1.50; 95% confidence interval, 1.15–1.96). CT-attenuation and FDG uptake of PPAT showed significant association with disease progression in patients with prostate cancer. These imaging findings may be evidence of the role of PPAT in prostate cancer progression.

Autophagy inhibition in 3T3-L1 adipocytes breaks the crosstalk with tumor cells by suppression of adipokine production

Several studies have revealed the functional importance of autophagy in both adipogenesis and carcinogenesis. Here, we investigated autophagy as a link between tumorigenesis and adipogenesis using 3T3-L1 cells, which have been shown to closely mimic the in vivo differentiation process. The relative levels of LC3-II/I showed that autophagy was the highest after 4–6 days of initiation of differentiation and it diminished thereafter. Furthermore, chloroquine (CQ), a late autophagy inhibitor, effectively inhibited adipogenic differentiation of 3T3-L1 cells, suggesting that autophagy may have a positive impact on adipogenic differentiation. Notably, real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR) analysis showed that CQ completely blocked the mRNA expression of three adipokines (adiponectin, leptin, and peroxisome proliferator-activated receptor-γ (PPARγ)), which increased proportionally to adipocyte differentiation. Using adipokine antibody arrays, we also found that among 38 adipokines examined, 6 adipokines were significantly differentially regulated in mature adipocytes compared to those in preadipocytes. A comparative analysis of adipokine production revealed that CQ-treated adipocytes displayed a profile similar to that of preadipocytes. Subsequently, CQ treatment significantly inhibited the migration capacity of v-Ha-ras-transformed cells in both 3T3-L1 adipocyte-conditioned medium and co-culture with 3T3-L1 using a transwell plate. Taken together, our results suggest that autophagy inhibition blocks the production of mediators relevant to the adipogenic process and may significantly contribute to reducing obesity-related cancer risk.

Pre-treatment ratio of periprostatic to subcutaneous fat thickness on MRI is an independent survival predictor in hormone-naïve men with advanced prostate cancer

BACKGROUND

Epidemiological studies have shown an association between obesity and prostate cancer (PCa) aggressiveness. However, little is known about periprostatic fat (PPF) and its relationship with overall fat deposition in PCa. PPF is thought to contribute to PCa growth and migration via secreted factors and induction of chronic inflammation. We investigated if pre-treatment PPF thickness correlates with overall survival (OS).

METHODS

We reviewed 85 hormone-naïve men with advanced PCa who had received androgen deprivation therapy (ADT). PPF thickness was measured by magnetic resonance imaging (MRI) and compared with subcutaneous fat (SCF) thickness as an internal control. Visceral fat (VF) area measured by computed tomography served as an additional control. We evaluated the relationship between laboratory data, pathology results, and obesity parameters and OS.

RESULTS

Median follow-up was 50.6 months. Thirty-six patients died during follow-up. Univariate analysis revealed that nadir PSA titer, Gleason score, N stage, M stage, extent of disease by bone scan grade, hemoglobin, lactate dehydrogenase, alkaline phosphatase, and PPF/SCF ratio were associated with OS. Multivariate analysis revealed that nadir PSA titer, N stage, and PPF/SCF ratio were independent prognostic factors for survival. The 5-year OS in the patients with higher PPF/SCF ratio (≥ 1) and lower PPF/SCF ratio (< 1) was 49.5% and 66.5%, respectively (P = 0.039).

CONCLUSIONS

Pre-treatment ratio of PPF-to-SCF thickness on MRI is an independent predictor of survival in hormone-naïve men with advanced PCa. This could be useful for predicting which patients are more likely to develop castration-resistant PCa.

Androgen deprivation therapy promotes an obesity-like microenvironment in periprostatic fat

Prostate cancer is a leading cause of morbidity and cancer-related death worldwide. Androgen deprivation therapy (ADT) is the cornerstone of management for advanced disease. The use of these therapies is associated with multiple side effects, including metabolic syndrome and truncal obesity. At the same time, obesity has been associated with both prostate cancer development and disease progression, linked to its effects on chronic inflammation at a tissue level. The connection between ADT, obesity, inflammation and prostate cancer progression is well established in clinical settings; however, an understanding of the changes in adipose tissue at the molecular level induced by castration therapies is missing. Here, we investigated the transcriptional changes in periprostatic fat tissue induced by profound ADT in a group of patients with high-risk tumours compared to a matching untreated cohort. We find that the deprivation of androgen is associated with a pro-inflammatory and obesity-like adipose tissue microenvironment. This study suggests that the beneficial effect of therapies based on androgen deprivation may be partially counteracted by metabolic and inflammatory side effects in the adipose tissue surrounding the prostate.