Elevated osteonectin/SPARC expression in primary prostate cancer predicts metastatic progression

Notch activation promotes bone metastasis via SPARC inhibition in adenoid cystic carcinoma

OBJECTIVES

We aimed to investigate bone metastasis induced by Notch signalling pathway dysregulation and to demonstrate that SPARC is a potential therapeutic target in adenoid cystic carcinoma (AdCC) with Notch dysregulation.

MATERIALS AND METHODS

This retrospective study enrolled 144 AdCC patients. RNA-sequencing and enrichment analyses were performed using 32 AdCC samples. Osteonectin/SPARC and the Notch activation indicator Notch intracellular domain (NICD) were detected using immunohistochemistry. Cell proliferation and migration assays were conducted using stably NICD over-expressing cells. The effect of SPARC on osteoclast differentiation in NICD cells was investigated using western blotting, quantitative reverse transcription PCR, tartrate-resistant acid phosphatase staining and resorption assays.

RESULTS

RNA-sequencing analysis showed that genes down-regulated in Notch-mutant AdCCs, such as SPARC, were enriched in ossification and osteoblast differentiation. Most (75/110, 68.2%) Notch1-wild-type AdCCs showed SPARC over-expression, whereas 30 out of 34 (88.2%) Notch1-mutant tumours showed low SPARC expression. SPARC over-expression was then found negatively to be correlated with NICD expression in 144 AdCCs. NICD over-expression promoted cell growth, migration and osteoclast differentiation, which could be partly reversed by exogenous SPARC.

CONCLUSIONS

Notch activation in AdCC contributes to bone metastasis through SPARC inhibition. The study results suggest that SPARC may represent a prognostic biomarker and potential therapeutic target.

Osteonectin (SPARC) prognostic value in prostate cancer

BACKGROUND

Prostate cancer (PCa) is common malignancy among men worldwide. To date only few molecular markers are available to predict its course and outcome. SPARC is considered to be promising prognostic marker of PCa due to its involvement in various cancer processes.

MATERIALS AND METHODS

study was conducted on PCa surgical primary tumor samples, obtained from 84 patients. Level of SPARC mRNA expression was estimated using RT-qPCR. To identify SPARC protein (osteonectin) in prostate tissue, immunohistochemical analysis was conducted. Bioinformatical analysis was performed on UALCAN and TNMplot resources.

RESULTS

bioinformatical analysis demonstrated that SPARC mRNA levels are decreased in PCa samples, in comparison to normal tissue. In patients with lymph node metastases its levels are 1.26 times higher; p = 4.66E-02, than in N0 category. Ex vivo study demonstrated that SPARC expression was elevated on both mRNA and protein levels in PCa patients with lymph node metastases (by 2.34 and 1.91, respectively, p < 0.05). We established higher levels of SPARC mRNA and protein in PCa patients with T3 tumors, as well as high Gleason score. Estimation of survival rates demonstrated that PCa patients with a high level of SPARC mRNA and protein have decreased overall 2-year survival.

CONCLUSIONS

SPARC protein was overexpressed on mRNA and protein levels in patients with presence of lymph node metastases and higher Gleason score of tumors. Also, both mRNA and protein upregulation were associated with worse survival rates. The current study has therefore provided further evidence that SPARC is indeed linked to the prognosis and aggressiveness of human PCa.

The Potential of Extracellular Matrix- and Integrin Adhesion Complex-Related Molecules for Prostate Cancer Biomarker Discovery

Prostate cancer is among the top five cancer types according to incidence and mortality. One of the main obstacles in prostate cancer management is the inability to foresee its course, which ranges from slow growth throughout years that requires minimum or no intervention to highly aggressive disease that spreads quickly and resists treatment. Therefore, it is not surprising that numerous studies have attempted to find biomarkers of prostate cancer occurrence, risk stratification, therapy response, and patient outcome. However, only a few prostate cancer biomarkers are used in clinics, which shows how difficult it is to find a novel biomarker. Cell adhesion to the extracellular matrix (ECM) through integrins is among the essential processes that govern its fate. Upon activation and ligation, integrins form multi-protein intracellular structures called integrin adhesion complexes (IACs). In this review article, the focus is put on the biomarker potential of the ECM- and IAC-related molecules stemming from both body fluids and prostate cancer tissue. The processes that they are involved in, such as tumor stiffening, bone turnover, and communication via exosomes, and their biomarker potential are also reviewed.

Spatial whole transcriptome profiling of primary tumor from patients with metastatic prostate cancer

Prostate cancer (PCa) is a highly heterogeneous disease in terms of its molecular makeup and clinical prognosis. The prostate tumor microenvironment (TME) is hypothesized to play an important role in driving disease aggressiveness, but precise mechanisms remain elusive. In our study, we used spatial transcriptomics to explore for the first time the spatial gene expression heterogeneity within primary prostate tumors from patients with metastatic disease. In total, we analyzed 5459 tissue spots from three PCa patients comprising castration-resistant (CRPC) and neuroendocrine (NEPC) disease stages. Within CRPC, we identified a T cell cluster whose activity might be impaired by nearby regulatory T cells, potentially mediating the aggressive disease phenotype. Moreover, we identified Hallmark signatures of epithelial-mesenchymal transition in a cancer-associated fibroblast (CAF) cluster, indicating the aggressive characteristic of the primary TME leading to metastatic dissemination. Within NEPC, we identified active immune-stroma cross-talk exemplified by significant ligand-receptor interactions between CAFs and M2 macrophages. Further, we identified a malignant cell population that was associated with the down-regulation of an immune-related gene signature. Lower expression of this signature was associated with higher levels of genomic instability in advanced PCa patients (SU2C cohort, n = 99) and poor recurrence free survival in early-stage PCa patients (TCGA cohort, n = 395), suggesting prognostic biomarker potential. Taken together, our study reveals the importance of whole transcriptome profiling at spatial resolution for biomarker discovery and for advancing our understanding of tumor biology.

ATP8B1: A prognostic prostate cancer biomarker identified via genetic analysis

BACKGROUND

Controlling the asymmetric distribution of phospholipids across biological membranes plays a pivotal role in the life cycle of cells; one of the most important contributors that maintain this lipid asymmetry are phospholipid-transporting adenosine triphosphatases (ATPases). Although sufficient information regarding their association with cancer exists, there is limited evidence linking the genetic variants of phospholipid-transporting ATPase family genes to prostate cancer in humans.

METHODS

In this study, we investigated the association of 222 haplotype-tagging single-nucleotide polymorphisms (SNPs) in eight phospholipid-transporting ATPase genes with cancer-specific survival (CSS) and overall survival (OS) of 630 patients treated with androgen-deprivation therapy (ADT) for prostate cancer.

RESULTS

After multivariate Cox regression analysis and multiple testing correction, we found that ATP8B1 rs7239484 was remarkably associated with CSS and OS after ADT. A pooled analysis of multiple independent gene-expression datasets demonstrated that ATP8B1 was under-expressed in tumor tissues and that a higher ATP8B1 expression was associated with a better patient prognosis. Moreover, we established highly invasive sublines using two human prostate cancer cell lines to mimic cancer progression traits in vitro. The expression of ATP8B1 was consistently downregulated in both highly invasive sublines.

CONCLUSION

Our study indicates that rs7239484 is a prognostic factor for patients treated with ADT and that ATP8B1 can potentially attenuate prostate cancer progression.

Quantitative proteomics identifies and validates urinary biomarkers of rhabdomyosarcoma in children

BACKGROUND

Rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma with poor prognosis in children. The 5-year survival rate for early RMS has improved, whereas it remains unsatisfactory for advanced patients. Urine can rapidly reflect changes in the body and identify low-abundance proteins. Early screening of tumor markers through urine in RMS allows for earlier treatment, which is associated with better outcomes.

METHODS

RMS patients under 18 years old, including those newly diagnosed and after surgery, were enrolled. Urine samples were collected at the time points of admission and after four cycles of chemotherapy during follow-up. Then, a two-stage workflow was established. (1) In the discovery stage, differential proteins (DPs) were initially identified in 43 RMS patients and 12 healthy controls (HCs) using a data-independent acquisition method. (2) In the verification stage, DPs were further verified as biomarkers in 54 RMS patients and 25 HCs using parallel reaction monitoring analysis. Furthermore, a receiver operating characteristic (ROC) curve was used to construct the protein panels for the diagnosis of RMS. Gene Ontology (GO) and Ingenuity Pathway Analysis (IPA) software were used to perform bioinformatics analysis.

RESULTS

A total of 251 proteins were significantly altered in the discovery stage, most of which were enriched in the head, neck and urogenital tract, consistent with the most common sites of RMS. The most overrepresented biological processes from GO analysis included immunity, inflammation, tumor invasion and neuronal damage. Pathways engaging the identified proteins revealed 33 common pathways, including WNT/β-catenin signaling and PI3K/AKT signaling. Finally, 39 proteins were confirmed as urinary biomarkers for RMS, and a diagnostic panel composed of 5 candidate proteins (EPS8L2, SPARC, HLA-DRB1, ACAN, and CILP) was constructed for the early screening of RMS (AUC: 0.79, 95%CI = 0.66 ~ 0.92).

CONCLUSIONS

These findings provide novel biomarkers in urine that are easy to translate into clinical diagnosis of RMS and illustrate the value of global and targeted urine proteomics to identify and qualify candidate biomarkers for noninvasive molecular diagnosis.

Data-Independent Acquisition Mass Spectrometry of EPS-Urine Coupled to Machine Learning: A Predictive Model for Prostate Cancer

Prostate cancer (PCa) is annually the most frequently diagnosed cancer in the male population. To date, the diagnostic path for PCa detection includes the dosage of serum prostate-specific antigen (PSA) and the digital rectal exam (DRE). However, PSA-based screening has insufficient specificity and sensitivity; besides, it cannot discriminate between the aggressive and indolent types of PCa. For this reason, the improvement of new clinical approaches and the discovery of new biomarkers are necessary. In this work, expressed prostatic secretion (EPS)-urine samples from PCa patients and benign prostatic hyperplasia (BPH) patients were analyzed with the aim of detecting differentially expressed proteins between the two analyzed groups. To map the urinary proteome, EPS-urine samples were analyzed by data-independent acquisition (DIA), a high-sensitivity method particularly suitable for detecting proteins at low abundance. Overall, in our analysis, 2615 proteins were identified in 133 EPS-urine specimens obtaining the highest proteomic coverage for this type of sample; of these 2615 proteins, 1670 were consistently identified across the entire data set. The matrix containing the quantified proteins in each patient was integrated with clinical parameters such as the PSA level and gland size, and the complete matrix was analyzed by machine learning algorithms (by exploiting 90% of samples for training/testing using a 10-fold cross-validation approach, and 10% of samples for validation). The best predictive model was based on the following components: semaphorin-7A (sema7A), secreted protein acidic and rich in cysteine (SPARC), FT ratio, and prostate gland size. The classifier could predict disease conditions (BPH, PCa) correctly in 83% of samples in the validation set. Data are available via ProteomeXchange with the identifier PXD035942.

Adaptive and non-adaptive gene expression responses in prostate cancer during androgen deprivation

Androgen deprivation therapy is the cornerstone treatment of advanced prostate cancer. Eventually prostate cancer cells overcome androgen deprivation therapy, giving rise to castration resistant prostate cancer (CRPC) characterized by increased androgen receptor (AR) activity. Understanding the cellular mechanisms leading to CRPC is needed for development of novel treatments. We used long-term cell cultures to model CRPC; a testosterone-dependent cell line (VCaP-T) and cell line adapted to grow in low testosterone (VCaP-CT). These were used to uncover persistent and adaptive responses to testosterone level. RNA was sequenced to study AR-regulated genes. Expression level changed due to testosterone depletion in 418 genes in VCaP-T (AR-associated genes). To evaluate significance for CRPC growth, we compared which of them were adaptive i.e., restored expression level in VCaP-CT. Adaptive genes were enriched to steroid metabolism, immune response and lipid metabolism. The Cancer Genome Atlas Prostate Adenocarcinoma data were used to assess the association with cancer aggressiveness and progression-free survival. Expressions of 47 AR-associated or association gaining genes were statistically significant markers for progression-free survival. These included genes related to immune response, adhesion and transport. Taken together, we identified and clinically validated multiple genes being linked with progression of prostate cancer and propose several novel risk genes. Possible use as biomarkers or therapeutic targets should be studied further.

Study on the role of SLC14A1 gene in biochemical recurrence of prostate cancer

Prostate cancer (PCa) is a common malignant disease among men and biochemical recurrence (BCR) is considered to be a decisive risk factor for clinical recurrence and PCa metastasis. Clarifying the genes related to BCR and its possible pathways is vital for providing diagnosis and treatment methods to delay the progress of BCR. An analysis of data concerning PCa from previous datasets of The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) was performed. Immunohistochemical (IHC) staining were used to evaluate the expression of SLC14A1 in prostate tissues. Kaplan-Meier analysis, Pearson correlation, and single sample Gene Set Enrichment Analysis (ssGSEA) were used to identify the potential pathway and molecular mechanism of the function of SLC14A1 in BCR of PCa. The expression of SLC14A1 is significantly reduced in prostate cancer cells and tissue comparing to normal prostate epithelial cell and para-cancerous tissue. As indicated by Kaplan-Meier analysis, High expression of SLC14A1 could increase the BCR-free survival time of PCa patients. This effect might be related to the interaction with miRNAs (has-miR-508, has-mir-514a2, and has-mir-449a) and the infiltration of B cells. SLC14A1 is a novel important gene associated with BCR of PCa, and further studies of its molecular mechanism may delay the progress of BCR.

SPARC Induces E-Cadherin Repression and Enhances Cell Migration through Integrin αvβ3 and the Transcription Factor ZEB1 in Prostate Cancer Cells

Secreted protein acidic and rich in cysteine (SPARC), or osteonectin, is a matricellular protein that modulates interactions between cells and their microenvironment. SPARC is expressed during extracellular matrix remodeling and is abundant in bone marrow and high-grade prostate cancer (PCa). In PCa, SPARC induces changes associated with epithelial–mesenchymal transition (EMT), enhancing migration and invasion and increasing the expression of EMT transcriptional factor Zinc finger E-box-binding homeobox 1 (ZEB1), but not Zinc finger protein SNAI1 (Snail) or Zinc finger protein SNAI2 (Slug). It is unknown whether the SPARC-induced downregulation of E-cadherin in PCa cells depends on ZEB1. Several integrins are mediators of SPARC effects in cancer cells. Because integrin signaling can induce EMT programs, we hypothesize that SPARC induces E-cadherin repression through the activation of integrins and ZEB1. Through stable knockdown and the overexpression of SPARC in PCa cells, we demonstrate that SPARC downregulates E-cadherin and increases vimentin, ZEB1, and integrin β3 expression. Knocking down SPARC in PCa cells decreases the tyrosine-925 phosphorylation of FAK and impairs focal adhesion formation. Blocking integrin αvβ3 and silencing ZEB1 revert both the SPARC-induced downregulation of E-cadherin and cell migration enhancement. We conclude that SPARC induces E-cadherin repression and enhances PCa cell migration through the integrin αvβ3/ZEB1 signaling pathway.

Identification of a Gene Signature to Aid Treatment Decisions by Integrated Analysis of Mutated Genes Between Primary and Metastatic Prostate Cancer

Prostate cancer is one of the most common malignancies in males. Despite the recent development of advanced diagnostic platforms and treatment, patients with metastatic disease still have a poor five-year survival rate. Cancer metastasis is correlated with the characteristics of the tumor microenvironment and is significantly associated with patient prognosis. In this study, we obtained mutated genes with significant differences between primary and metastatic prostate cancer from the COSMIC database. Unsupervised consensus clustering was used based on the 1,051 genes obtained, and two PCa clusters were identified, which exhibited different prognostic outcomes and immune characteristics. Next, we generated a scoring system and evaluated the prognostic value of riskscore and its potential to aid treatment decisions in clinical practice. The riskscore could be applied to predict patients’ response to immunotherapy and sensitivity to Docetaxel. In conclusion, this study performed an integrated analysis of mutated genes between primary and metastatic prostate cancer and provides a novel assessment scheme to precisely select treatment strategies.

Targeted co-delivery biomimetic nanoparticles reverse macrophage polarization for enhanced rheumatoid arthritis therapy

Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease, which is characterized by synovial inflammation and autoimmunity. The main cause of the disease is the imbalance of the proportion of pro-inflammatory macrophages (M1-type) and anti-inflammatory macrophages (M2-type) in the synovial tissues of the joint. To restore this balance, in our study, the interleukin-10 encoding anti-inflammatory cytokines (IL-10 pDNA) and chemotherapeutic drug dexamethasone sodium phosphate (DSP) were co-loaded into human serum albumin (HSA) preparing pDNA/DSP-NPs to actively target macrophages in synovium tissue to promote M1-M2 polarization. Confocal laser scanning microscope and western blot were used to demonstrate the targeting ability of co-delivery nanoparticles. In vivo, the real-time fluorescence imaging system and HPLC were used to study the tissue distribution and pharmacokinetics of nanoparticles, and the results showed that the accumulation of nanoparticles in the inflammatory joint site was higher. Its pharmacodynamics were evaluated in collagen-induced arthritis (CIA) rat model, and it demonstrated that the pDNA/DSP-NPs significantly reduced the expression of serum inflammatory factors and alleviated joint swelling and bone erosion, suggesting the favorable therapeutic effect. The synergistic treatment effect of IL-10 pDNA and DSP in this system was achieved by reducing the secretion of pro-inflammatory factors (TNF-α, IL-1β) and increasing the expression of anti-inflammatory factors (IL-10) to promote the M1-M2 polarization of macrophages. Our strategy is promising for co-delivery of gene drugs and chemical drugs by biomimetic natural materials to promote macrophages polarization so that to achieve synergically treatment of inflammatory disease.

Castration-Induced Downregulation of SPARC in Stromal Cells Drives Neuroendocrine Differentiation of Prostate Cancer

Fatal neuroendocrine differentiation (NED) of castration-resistant prostate cancer is a recurrent mechanism of resistance to androgen deprivation therapies (ADT) and antiandrogen receptor pathway inhibitors (ARPI) in patients. The design of effective therapies for neuroendocrine prostate cancer (NEPC) is complicated by limited knowledge of the molecular mechanisms governing NED. The paucity of acquired genomic alterations and the deregulation of epigenetic and transcription factors suggest a potential contribution from the microenvironment. In this context, whether ADT/ARPI induces stromal cells to release NED-promoting molecules and the underlying molecular networks are unestablished. Here, we utilized transgenic and transplantable mouse models and coculture experiments to unveil a novel tumor-stroma cross-talk that is able to induce NED under the pressure of androgen deprivation. Castration induced upregulation of GRP78 in tumor cells, which triggers miR29-b-mediated downregulation of the matricellular protein SPARC in the nearby stroma. SPARC downregulation enabled stromal cells to release IL6, a known inducer of NED. A drug that targets GRP78 blocked NED in castrated mice. A public, human NEPC gene expression dataset showed that Hspa5 (encoding for GRP78) positively correlates with hallmarks of NED. Finally, prostate cancer specimens from patients developing local NED after ADT showed GRP78 upregulation in tumor cells and SPARC downregulation in the stroma. These results point to GRP78 as a potential therapeutic target and to SPARC downregulation in stromal cells as a potential early biomarker of tumors undergoing NED. SIGNIFICANCE: Tumor-stroma cross-talk promotes neuroendocrine differentiation in prostate cancer in response to hormone therapy via a GRP78/SPARC/IL6 axis, providing potential therapeutic targets and biomarkers for neuroendocrine prostate cancer.

HOXB5 Overexpression Is Associated with Neuroendocrine Differentiation and Poor Prognosis in Prostate Cancer

Homeobox genes function as master regulatory transcription factors during embryogenesis. HOXB5 is known to play an important role in several cancers. However, the biological role of HOXB5 in prostate cancer (PCa) is not fully elucidated. This study aimed to analyze the expression and function of HOXB5 and involvement of HOXB5 in neuroendocrine differentiation in PCa. Immunohistochemistry showed that 56 (43.8%) of 128 cases of localized PCa were positive for HOXB5. HOXB5-positive cases were associated with poor prostate-specific antigen recurrence-free survival after prostatectomy. Among 74 cases of metastatic PCa, 43 (58.1%) were positive for HOXB5. HOXB5 expression was higher in metastatic PCa than that in localized PCa. HOXB5 knockdown suppressed cell growth and invasion, but HOXB5 overexpression increased cell growth and invasion in PCa cell lines. Furthermore, HOXB5 regulated RET expression. Gene set enrichment analysis revealed that Nelson androgen response gene set was enriched in low HOXB5 expression group. RB1 knockout increased HOXB5 expression. Of note, additional p53 knockdown further increased HOXB5 expression in RB1 knockout cells. In silico analysis showed that HOXB5 expression was increased in neuroendocrine PCa (NEPC). These results suggest that HOXB5 may be a promising prognostic marker after prostatectomy and is involved in progression to NEPC.

GLIPR1 and SPARC expression profile reveals a signature associated with prostate Cancer Brain metastasis

Despite advances in treatment of lethal prostate cancer, the incidence of prostate cancer brain metastases is increasing. In this sense, we analyzed the molecular profile, as well as the functional consequences involved in the reciprocal interactions between prostate tumor cells and human astrocytes. We observed that the DU145 cells, but not the LNCaP cells or the RWPE-1 cells, exhibited more pronounced, malignant and invasive phenotypes along their interactions with astrocytes. Moreover, global gene expression analysis revealed several genes that were differently expressed in our co-culture models with the overexpression of GLIPR1 and SPARC potentially representing a molecular signature associated with the invasion of central nervous system by prostate malignant cells. Further, these results were corroborated by immunohistochemistry and in silico analysis. Thus, we conjecture that the data here presented may increase the knowledge about the molecular mechanisms associated with the invasion of CNS by prostate malignant cells.

Five-gene signature associating with Gleason score serve as novel biomarkers for identifying early recurring events and contributing to early diagnosis for Prostate Adenocarcinoma

Background: Compared to non-recurrent type, recurrent prostate adenocarcinoma (PCa) is highly fatal, and significantly shortens the survival time of affected patients. Early and accurate laboratory diagnosis is particularly important in identifying patients at high risk of recurrence, necessary for additional systemic intervention. We aimed to develop efficient and accurate diagnostic and prognostic biomarkers for new PCa following radical therapy. Methods: We identified differentially expressed genes (DEGs) and clinicopathological data of PCa patients from Gene Expression Omnibus (GEO) datasets and The Cancer Genome Atlas (TCGA) repositories. We then uncovered the most relevant clinical traits and genes modules associated with PCa prognosis using the Weighted gene correlation network analysis (WGCNA). Univariate Cox regression analysis and multivariate Cox proportional hazards (Cox-PH) models were performed to identify candidate gene signatures related to Disease-Free Interval (DFI). Data for internal and external cohorts were utilized to test and validate the accuracy and clinical utility of the prognostic models. Results: We constructed and validated an accurate and reliable model for predicting the prognosis of PCa using 5 Gleason score-associated gene signatures (ZNF695, CENPA, TROAP, BIRC5 and KIF20A). The ROC and Kaplan-Meier analysis revealed the model was highly accurate in diagnosing and predicting the recurrence and metastases of PCa. The accuracy of the model was validated using the calibration curves based on internal TCGA cohort and external GEO cohort. Using the model, patients could be prognostically stratified in to various groups including TNM classification and Gleason score. Multivariate analysis revealed the model could independently predict the prognosis of PCa patients and its utility was superior to that of clinicopathological characteristics. In addition, we fund the expression of the 5 gene signatures strongly and positively correlated with tumor purity but negatively correlated with infiltration CD8+ T cells to the tumor microenvironment. Conclusions: A 5 gene signatures can accurately be used in the diagnosis and prediction of PCa prognosis. Thus this can guide the treatment and management prostate adenocarcinoma.

Evaluating the transcriptional fidelity of cancer models

BACKGROUND

Cancer researchers use cell lines, patient-derived xenografts, engineered mice, and tumoroids as models to investigate tumor biology and to identify therapies. The generalizability and power of a model derive from the fidelity with which it represents the tumor type under investigation; however, the extent to which this is true is often unclear. The preponderance of models and the ability to readily generate new ones has created a demand for tools that can measure the extent and ways in which cancer models resemble or diverge from native tumors.

METHODS

We developed a machine learning-based computational tool, CancerCellNet, that measures the similarity of cancer models to 22 naturally occurring tumor types and 36 subtypes, in a platform and species agnostic manner. We applied this tool to 657 cancer cell lines, 415 patient-derived xenografts, 26 distinct genetically engineered mouse models, and 131 tumoroids. We validated CancerCellNet by application to independent data, and we tested several predictions with immunofluorescence.

RESULTS

We have documented the cancer models with the greatest transcriptional fidelity to natural tumors, we have identified cancers underserved by adequate models, and we have found models with annotations that do not match their classification. By comparing models across modalities, we report that, on average, genetically engineered mice and tumoroids have higher transcriptional fidelity than patient-derived xenografts and cell lines in four out of five tumor types. However, several patient-derived xenografts and tumoroids have classification scores that are on par with native tumors, highlighting both their potential as faithful model classes and their heterogeneity.

CONCLUSIONS

CancerCellNet enables the rapid assessment of transcriptional fidelity of tumor models. We have made CancerCellNet available as a freely downloadable R package ( https://github.com/pcahan1/cancerCellNet ) and as a web application ( http://www.cahanlab.org/resources/cancerCellNet_web ) that can be applied to new cancer models that allows for direct comparison to the cancer models evaluated here.

The Landscape of Immune Cells Infiltrating in Prostate Cancer

Background

This study was to explore the infiltration pattern of immune cells in the prostate cancer (PCa) microenvironment and evaluate the possibility of specific infiltrating immune cells as potential prognostic biomarkers in PCa.

Methods

Infiltrating percentage of 22 immune cells were extracted from 27 normalized datasets by CIBERSORT algorithm. Samples with CIBERSORT p-value < 0.05 were subsequently merged and divided into normal or tumor groups. The differences of 22 immune cells between normal and tumor tissues were analyzed along with potential infiltrating correlations among 22 immune cells and Gleason grades. SNV data from TCGA was used to calculate the TMB score. A univariate and multivariate regression were used to evaluate the prognostic effects of immune cells in PCa.

Results

Ten immune cells with significant differences were identified, including seven increased and three decreased infiltrating immune cells from 190 normal prostate tissues and 537 PCa tissues. Among them, the percentage of infiltration of resting NK cells increased the most, whereas the percentage of infiltration of resting mast cells decreased the most. In normal tissues, CD8+ T cells had the strongest infiltrating correlation with monocytes, while activated NK cells and naive B cells were the highest in PCa tissues. Moreover, the infiltration of five immune cells was significantly associated with TMB score and mutations of immune gene change the infiltration of immune cells. The Area Under Curve (AUC) of the multivariate regression model for the five- and 10-year survival prediction of PCa reached 0.796 and 0.862. The validation cohort proved that the model was reproducible.

Conclusions

This study demonstrated that different infiltrating immune cells in prostate cancer, especially higher infiltrating M1 macrophages and neutrophils in PCa tissue, are associated with patients’ prognosis, suggesting that these two immune cells might be potential targets for PCa diagnosis and prognosis of treatment.

Secreted protein acidic and rich in cysteine (SPARC) induces epithelial-mesenchymal transition, enhancing migration and invasion, and is associated with high Gleason score in prostate cancer

Secreted protein acidic and rich in cysteine (SPARC) is a matricellular protein highly expressed in bone tissue that acts as a chemoattractant factor promoting the arrival of prostate cancer (PCa) cells to the bone marrow. However, the contribution of SPARC during the early stages of tumor progression remains unclear. In this study, we show that SPARC is highly expressed in PCa tissues with a higher Gleason score. Through stable knockdown and overexpression of SPARC in PC3 and LNCaP cells, respectively, here we demonstrate that endogenous SPARC induces the epithelial-mesenchymal transition (EMT), decreasing E-cadherin and cytokeratin 18 and increasing N-cadherin and vimentin. Moreover, SPARC induces the expression of EMT regulatory transcription factors Snail family transcriptional repressor 1 (Snail), Snail family transcriptional repressor 2 (Slug), and zinc finger E-box binding homeobox 1 (Zeb1). In addition, SPARC knockdown in PC3 cells decreases migration and invasion in vitro, without modifying cell proliferation. Our results indicate that SPARC might facilitate tumor progression by modifying the cellular phenotype in cancer cells.

SPARC-p53: The double agents of cancer

Cancer is a complex disease with high incidence and mortality rates. The important role played by the tumor microenvironment in regulating oncogenesis, tumor growth, and metastasis is by now well accepted in the scientific community. SPARC is known to participate in tumor-stromal interactions and impact cancer growth in ambiguous ways, which either enhance or suppress cancer aggressiveness, in a context-dependent manner. p53 transcription factor, a well-established tumor suppressor, has been reported to promote tumor growth in certain situations, such as hypoxia, thus displaying a duality in its action. Although both proteins are being tested in clinical trials, the synergistic relation between them is yet to be explored in clinical practice. In this review, we address the controversial roles of SPARC and p53 as double agents in cancer, briefly summarizing the interaction found between these two molecules and its importance in cancer.

Proteomic Tissue-Based Classifier for Early Prediction of Prostate Cancer Progression

Although ~40% of screen-detected prostate cancers (PCa) are indolent, advanced-stage PCa is a lethal disease with 5-year survival rates around 29%. Identification of biomarkers for early detection of aggressive disease is a key challenge. Starting with 52 candidate biomarkers, selected from existing PCa genomics datasets and known PCa driver genes, we used targeted mass spectrometry to quantify proteins that significantly differed in primary tumors from PCa patients treated with radical prostatectomy (RP) across three study outcomes: (i) metastasis ≥1-year post-RP, (ii) biochemical recurrence ≥1-year post-RP, and (iii) no progression after ≥10 years post-RP. Sixteen proteins that differed significantly in an initial set of 105 samples were evaluated in the entire cohort (n = 338). A five-protein classifier which combined FOLH1, KLK3, TGFB1, SPARC, and CAMKK2 with existing clinical and pathological standard of care variables demonstrated significant improvement in predicting distant metastasis, achieving an area under the receiver-operating characteristic curve of 0.92 (0.86, 0.99, p = 0.001) and a negative predictive value of 92% in the training/testing analysis. This classifier has the potential to stratify patients based on risk of aggressive, metastatic PCa that will require early intervention compared to low risk patients who could be managed through active surveillance.

Meta-Analysis of steroid-converting enzymes and related receptors in prostate cancer suggesting novel combined therapies

Androgen receptor (AR) signaling is essential for prostate cancer (PC) progression and treatment. Experiments have demonstrated that the intratumoral androgen levels are not affected by circulating androgen levels, but rather modulated by local steroid-converting enzyme activities. The expression modulation status of human steroid-converting enzymes and nuclear receptors are of great promise to identify novel therapeutic targets. Meta-analysis was performed with 9 cohorts (1093 specimens) from Gene Expression Omnibus, 16 cohorts (933 specimens) from Oncomine and the TCGA cohort (550 specimens). We found significant up regulation of 5α-reductase type 1 and type 3 in both primary and metastatic PC, together with the down regulation of AKR1C2 in primary PC, contributing to the high intratumoral DHT levels. The expression of AR in metastatic PC was up regulated, indicating the importance of AR signaling in the progression of this cancer. The down regulations of HSD11B1 and NR3C1 in primary and metastatic PC may diminish the anti-inflammation and anti-proliferation effects of glucocorticoids signaling. Furthermore, the decrease of progesterone receptor (PGR) expression in primary and metastatic PC was also observed, relieving the suppression effect of PGR on PC proliferation. The clinical evidences of the remarkable expression modulation of steroid-converting enzymes and receptors in PC may indicate novel combined treatment against this highly incident cancer.

Molecular profiling of radical prostatectomy tissue from patients with no sign of progression identifies ERG as the strongest independent predictor of recurrence

BACKGROUND

As a major cause of morbidity and mortality among men, prostate cancer is a heterogenous disease, with a vast heterogeneity in the biology of the disease and in clinical outcome. While it often runs an indolent course, local progression or metastasis may eventually develop, even among patients considered "low risk" at diagnosis. Therefore, biomarkers that can discriminate aggressive from indolent disease at an early stage would greatly benefit patients. We hypothesized that tissue specimens from early stage prostate cancers may harbor predictive signatures for disease progression.

METHODS

We used a cohort of radical prostatectomy patients with longitudinal follow-up, who had tumors with low grade and stage that revealed no signs of future disease progression at surgery. During the follow-up period, some patients either remained indolent (non-BCR) or progressed to biochemical recurrence (BCR). Total RNA was extracted from tumor, and adjacent normal epithelium of formalin-fixed-paraffin-embedded (FFPE) specimens. Differential gene expression in tumors, and in tumor versus normal tissues between BCR and non-BCR patients were analyzed by NanoString using a customized CodeSet of 151 probes.

RESULTS

After controlling for false discovery rates, we identified a panel of eight genes (ERG, GGT1, HDAC1, KLK2, MYO6, PLA2G7, BICD1 and CACNAID) that distinguished BCR from non-BCR patients. We found a clear association of ERG expression with non-BCR, which was further corroborated by quantitative RT-PCR and immunohistochemistry assays.

CONCLUSIONS

Our results identified ERG as the strongest predictor for BCR and showed that potential prognostic prostate cancer biomarkers can be identified from FFPE tumor specimens.

Identification of hub genes in prostate cancer using robust rank aggregation and weighted gene co-expression network analysis

The pathogenic mechanisms of prostate cancer (PCa) remain to be defined. In this study, we utilized the Robust Rank Aggregation (RRA) method to integrate 10 eligible PCa microarray datasets from the GEO and identified a set of significant differentially expressed genes (DEGs) between tumor samples and normal, matched specimens. To explore potential associations between gene sets and PCa clinical features and to identify hub genes, we utilized WGCNA to construct gene co-expression networks incorporating the DEGs screened with the use of RRA. From the key module, we selected LMNB1, TK1, ZWINT, and RACGAP1 for validation. We found that these genes were up-regulated in PCa samples, and higher expression levels were associated with higher Gleason scores and tumor grades. Moreover, ROC and K-M plots indicated these genes had good diagnostic and prognostic value for PCa. On the other hand, methylation analyses suggested that the abnormal up-regulation of these four genes likely resulted from hypomethylation, while GSEA and GSVA for single hub gene revealed they all had a close association with proliferation of PCa cells. These findings provide new insight into PCa pathogenesis, and identify LMNB1, TK1, RACGAP1 and ZWINT as candidate biomarkers for diagnosis and prognosis of PCa.

Secreted Protein Acidic and Rich in Cysteine Mediated Biomimetic Delivery of Methotrexate by Albumin-Based Nanomedicines for Rheumatoid Arthritis Therapy

Rheumatoid arthritis (RA) is one of the most common chronic autoimmune diseases. Despite considerable advances in clinical treatment of RA, suboptimal response to therapy and treatment discontinuation are still unresolved challenges due to systemic toxicity. It is of crucial importance to actively target and deliver therapeutic agents to inflamed joints in order to promote in situ activity and decrease systemic toxicity. In this study, we found that SPARC (secreted protein acidic and rich in cysteine) was overexpressed in the synovial fluid and synovium of RA patients as well as mice with collagen-induced arthritis (CIA), which has been scarcely reported. Building upon the SPARC signature of RA joint microenvironment and the intrinsic high affinity of SPARC for albumin, we fabricated methotrexate-loaded human serum albumin nanomedicines (MTX@HSA NMs) and explored them as biomimetic drug delivery systems for RA therapy. Upon intravenous injection of chlorin e6-labeled MTX@HSA NMs into CIA mice, the fluorescence/magnetic resonance dual-modal imaging revealed higher accumulations and longer retention of MTX@HSA NMs in inflamed joints with respect to free MTX molecules. In vivo therapeutic evaluations suggested that the MTX@HSA NMs were able to attenuate the progression of RA with better efficacy and fewer side effects even at half  dose of administrated MTX in comparison with free MTX. By unraveling the mechanism driving the efficient accumulation of MTX@HSA NMs in RA joints and showing their ability to improve the safety and therapeutic efficacy of MTX, our work sheds light on the development of innovative anti-RA nanomedicines with a strong potential for clinical translation.

Downregulation of SPARC Is Associated with Epithelial-Mesenchymal Transition and Low Differentiation State of Biliary Tract Cancer Cells

BACKGROUND

Biliary tract cancers (BTCs) have a poor prognosis. BTCs are characterized by a prominent desmoplastic reaction which possibly contributes to the aggressive phenotype of this tumor. The desmoplastic reaction includes excessive production and deposition of extracellular matrix proteins such as periostin, secreted protein acidic and rich in cysteine (SPARC), thrombospondin-1, as well as accumulation of α-smooth muscle actin-positive cancer-associated fibroblasts and immune cells, secreting growth factors and cytokines including transforming growth factor (TGF)-β. In the present study, we investigated the expression of SPARC in BTC as well as its possible regulation by TGF-β.

METHODS

Expression levels of Sparc, TGF-β1 and its receptor ALK5 were evaluated by quantitative real-time PCR in 6 biliary tract cell lines as well as 1 immortalized cholangiocyte cell line (MMNK-1). RNAs from tumor samples of 7 biliary tract cancer patients were analyzed for expression of Sparc, TGF-β type II receptor (TbRII) as well as Twist and ZO-1. MMNK-1 cells were stimulated with TGF-β for 24 h, and Sparc, ZO-1 and E-Cadherin expressions were determined. The presence of SPARC protein was analyzed by immunohistochemistry in tumor specimens from 10 patients.

RESULTS

When comparing basal Sparc transcript levels in diverse BTC cell lines to MMNK-1 cells, we found that it was strongly downregulated in all cancer cell lines. The remaining expression levels were higher in highly differentiated cell lines (CCSW1, MZChA1, MZChA2 and TFK-1) than in less differentiated and undifferentiated ones (BDC, SKChA1). Expression of Sparc in BTC patient samples showed a significant positive correlation with expression of the epithelial marker ZO-1. In contrast, the mesenchymal marker Twist and the TbRII showed a trend of negative correlation with expression of Sparc in these samples. TGF-β exposure significantly downregulated Sparc expression in MMNK-1 cholangiocytes in vitro in parallel to downregulation of epithelial markers (E-Cadherin and ZO-1). Finally, SPARC immunostaining was performed in 10 patient samples, and the correlation between absence of SPARC and survival times was analyzed.

CONCLUSIONS

These data imply that a decrease in SPARC expression is correlated with dedifferentiation of BTC cells resulting in enhanced EMT being possibly mediated by TGF-β. Thereby SPARC levels might be a marker for individual prognosis of a patient, and strategies aiming at inhibition of SPARC downregulation might have potential for new future therapies.

Exploring candidate biomarkers for lung and prostate cancers using gene expression and flux variability analysis

Genome-scale metabolic models have provided valuable resources for exploring changes in metabolism under normal and cancer conditions. However, metabolism itself is strongly linked to gene expression, so integration of gene expression data into metabolic models might improve the detection of genes involved in the control of tumor progression. Herein, we considered gene expression data as extra constraints to enhance the predictive powers of metabolic models. We reconstructed genome-scale metabolic models for lung and prostate, under normal and cancer conditions to detect the major genes associated with critical subsystems during tumor development. Furthermore, we utilized gene expression data in combination with an information theory-based approach to reconstruct co-expression networks of the human lung and prostate in both cohorts. Our results revealed 19 genes as candidate biomarkers for lung and prostate cancer cells. This study also revealed that the development of a complementary approach (integration of gene expression and metabolic profiles) could lead to proposing novel biomarkers and suggesting renovated cancer treatment strategies which have not been possible to detect using either of the methods alone.

The relationship between homeobox B7 expression and the clinical characteristics of patient with prostate cancer

BACKGROUND

The prognosis of patients with prostate cancer (PCa) remains poor.

METHODS

GSE16560, GSE32448, GSE79957, GSE17951, and TCGA-PRAD were reanalyzed to evaluate the expression of homeobox B7 (HOXB7) between PCa tissues and normal prostate tissues and to characterize the correlation between the expression of HOXB7 and the clinicopathological features of patients with PCa. Gene set enrichment analysis was conducted to investigate the mechanisms.

RESULTS

HOXB7 was upregulated in PCa tissues (P = 0.0005). Both the univariate and multivariate analyses demonstrated that the expression of HOXB7 was correlated with the Gleason score and TNM staging of patients with PCa. The Gleason score and TNM staging were higher in the HOXB7 high expression group. The overall survival (hazard ratio [HR] = 0.632; 95% confidence interval [CI]: 0.4773-0.8369; P = 0.0014) and progression-free survival (HR = 0.544; 95% CI: 0.3157-0.9373; P = 0.0283) favored patients with PCa in HOXB7 low expression group over those in HOXB7 high expression group. PCa samples in HOXB7 low expression group were enriched in gene sets associated with the epithelial mesenchymal transition, apical junction, angiogenesis, ultraviolet response, and hypoxia.

CONCLUSIONS

HOXB7 might be an independent prognostic factor of patients with PCa.

Identification of key genes in prostate cancer gene expression profile by bioinformatics

The aim of this study was to identify key candidate genes in prostate cancer. The gene expression profiles of GSE32448, GSE45016, GSE46602 and GSE104749 were downloaded from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) between prostate cancer and normal samples were identified by R language. The gene ontology functional and pathway enrichment analyses of DEGs were performed by the Database for Annotation, Visualization and Integrated Discovery software followed by the construction of protein-protein interaction network. Hub gene identification was performed by the plug-in cytoHubba in Cytoscape software. The 217 DEGs were significantly enriched in biological processes including epithelial cell differentiation, response to estradiol and several pathways, mainly associated with protein digestion and absorption pathway in prostate cancer. Epithelial cell adhesion molecule, twist family basic helix-loop-helix transcription factor 1, CD38 molecule and vascular endothelial growth factor A were identified as hub genes. The expression levels of hub genes were consistent with data obtained in The Cancer Genome Atlas for prostate adenocarcinoma. These hub genes may be used as potential targets for prostate cancer diagnosis and treatment.

Large set data mining reveals overexpressed GPCRs in prostate and breast cancer: potential for active targeting with engineered anti-cancer nanomedicines

Over 800 G-protein-coupled receptors (GPCRs) are encoded by the human genome and many are overexpressed in tumors. GPCRs are triggered by ligand molecules outside the cell and activate internal signal transduction pathways driving cellular responses. The receptor signals are desensitized by receptor internalization and this mechanism can be exploited for the specific delivery of ligand-linked drug molecules directly into cells. Detailed expression analysis in cancer tissue can inform the design of GPCR-ligand decorated drug carriers for active tumor cell targeting. The active targeting process utilizes ligand receptor interactions leading to binding and in most cases internalization of the ligand-attached drug carrier resulting in effective targeting of cancer cells. In this report public microarray data from the Gene Expression Omnibus (GEO) repository was used to identify overexpressed GPCRs in prostate and breast cancer tissues. The analyzed data confirmed previously known cancer receptor associations and identified novel candidates for potential active targeting. Prioritization of the identified targeting receptors is also presented based on high expression levels and frequencies in cancer samples but low expression in healthy tissue. Finally, some selected examples were used in ligand docking studies to assess the feasibility for chemical conjugation to drug nanocarriers without interference of receptor binding and activation. The presented data demonstrate a large untapped potential to improve efficacy and safety of current and future anti-cancer compounds through active targeting of GPCRs on cancer cells.

miR-211 inhibits proliferation, invasion and migration of cervical cancer via targeting SPARC

Cervical cancer remains one of the most frequent gynecological malignancies among females around the world. Therefore, fully understanding the molecular mechanisms underlying the progression of cervical cancer may be critical for the development of effective therapeutic strategies against cervical cancer. The object was to evaluate the potential effect of miR-211 and verify its influence on the function of secreted protein acidic and rich in cysteine (SPARC) in cervical cancer. It was demonstrated that miR-211 was downregulated in cervical cancer cell lines (HeLa and C33A) and cervical cancer specimens, while SPARC expression level was higher in tumor tissues. We also revealed miR-211 upregulated expression could inhibit cells proliferation, migration and invasion in vivo. SPARC was confirmed as a direct and functional target of miR-211 and the inverse relationship between them was also observed. The results of the present study suggest that miR-211 reduced cancer growth, migration and invasion, and suppresses the SPARC expression in cervical cancer. This newly identified miR-211 may provide further insight into the progression and offers a promising target for cervical cancer therapy.

SPARC expression in gastric cancer predicts poor prognosis: Results from a clinical cohort, pooled analysis and GSEA assay

Background

The prognostic role of Secreted Protein Acidic and Rich in Cysteine (SPARC) in gastric cancer (GC) remains controversial. We investigated the clinical significance, the survival relevance, and potential function of SPARC in GC with resected samples, online gene set GSE62254, and cell line SGC7901.

Results

High immunostaining of SPARC significantly correlated with tumor differentiation (P = 0.004), and independently predicted shorter overall survival (OS) (HR = 1.446, P = 0.022), based on the current IHC evaluation. The accuracy of the results was further validated with 1000 times bootstrapping and the time-dependent receiver-operating characteristics (ROC) curves. The meta-analysis (pooled HR = 1.60, 95% CI: 1.01−2.53) confirmed SPARC as the predictor for reduced OS in GC. Moreover, the association between enhanced SPARC expression and Adriamycin (Adr) sensitivity was revealed by GSEA, and then confirmed by comparative cellular experiments, such as the protein level analysis of SGC7901and SGC7901/Adr cell line.

Materials and Methods

Immunohistochemistry (IHC) method was used to detect SPARC expression in 137 GC cases. Meta-analysis was performed based on 5 studies published in English on PubMed up to March 2016. GSEA was performed using online data set GSE62254 and GC-related functional gene sets derived from molecular signatures database (MSigDB). Western Blot was carried out to compare protein-level differences between gastric carcinoma SGC7901 cell line and Adr resistant SGC7901/Adr cell line. MTT assay was done to confirm the induction of SPARC on Adr sensitivity

Conclusions

Increased SPARC expression in GC led to a worse clinical outcome of patients and might induce Adr sensitivity of GC cells.

Biomarkers identified for prostate cancer patients through genome-scale screening

Prostate cancer is a threat to men and usually occurs in aged males. Though prostate specific antigen level and Gleason score are utilized for evaluation of the prostate cancer in clinic, the biomarkers for this malignancy have not been widely recognized. Furthermore, the outcome varies across individuals receiving comparable treatment regimens and the underlying mechanism is still unclear. We supposed that genetic feature may be responsible for, at least in part, this process and conducted a two-cohort study to compare the genetic difference in tumorous and normal tissues of prostate cancer patients. The Gene Expression Omnibus dataset were used and a total of 41 genes were found significantly differently expressed in tumor tissues as compared with normal prostate tissues. Four genes (SPOCK3, SPON1, PTN and TGFB3) were selected for further evaluation after Gene Ontology analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis and clinical association analysis. MIR1908 was also found decreased expression level in prostate cancer whose target genes were found expressing in both prostate tumor and normal tissues. These results indicated that these potential biomarkers deserve attention in prostate cancer patients and the underlying mechanism should be further investigated.

A transcriptomic insight into the impacts of mast cells in lung, breast, and colon cancers

To date, the exact impact of mast cells in tumor microenvironment is still controversial because of inconsistency in observations regarding the relationship between mast cell infiltrates and cancer development and prognosis. The discrepancies in previous studies have motivated us to examine the roles of mast cells in cancer pathology from different perspectives. Here, we investigated the impact of mast cells on transcriptomic profiles in the tissue microenvironment. Mice carrying the W-sh mutation in c-kit (Kit^W-sh ) are deficient in mast cell production and were used to assess the influence of mast cells on gene expression. By examining the transcriptomic profile among wild-type mice, Kit^W-sh mice, and Kit^W-sh mice with mast cell engraftment, we identified a list of "mast cell-dependent genes," which are enriched for cancer-related pathways. Utilizing whole-genome gene expression data from both mouse models and human cancer patients, we demonstrated that the expression profile of the mast cell-dependent genes differs between tumor and normal tissues from lung, breast, and colon, respectively. Mast cell infiltration is potentially increased in tumors compared with normal tissues, suggesting that mast cells might participate in tumor development. Accordingly, a prognostic molecular signature was developed based on the mast cell-dependent genes, which predicted recurrence-free survival for human patients with lung, breast, and colon cancers, respectively. Our study provides a novel transcriptomic insight into the impact of mast cells in the tumor microenvironment, though further experimental investigation is needed to validate the exact role of individual mast cell-dependent genes in different cancers.

Trends in Gene Expression Profiling for Prostate Cancer Risk Assessment: A Systematic Review

Objectives

The aim of the study is to review biotechnology advances in gene expression profiling on prostate cancer (PCa), focusing on experimental platform development and gene discovery, in relation to different study designs and outcomes in order to understand how they can be exploited to improve PCa diagnosis and clinical management.

Methods

We conducted a systematic literature review on gene expression profiling studies through PubMed/MEDLINE and Web of Science between 2000 and 2016. Tissue biopsy and clinical gene profiling studies with different outcomes (e.g., recurrence, survival) were included.

Results

Over 3,000 papers were screened and 137 full-text articles were selected. In terms of technology used, microarray is still the most popular technique, increasing from 50 to 70% between 2010 and 2015, but there has been a rise in the number of studies using RNA sequencing (13% in 2015). Sample sizes have increased, as well as the number of genes that can be screened all at once, but we have also observed more focused targeting in more recent studies. Qualitative analysis on the specific genes found associated with PCa risk or clinical outcomes revealed a large variety of gene candidates, with a few consistent cross-studies.

Conclusions

The last 15 years of research in gene expression in PCa have brought a large volume of data and information that has been decoded only in part, but advancements in high-throughput sequencing technology are increasing the amount of data that can be generated. The variety of findings warrants the execution of both validation studies and meta-analyses. Genetic biomarkers have tremendous potential for early diagnosis of PCa and, if coupled with other diagnostics (e.g., imaging), can effectively be used to concretize less-invasive, personalized prediction of PCa risk and progression.

The relationship between SPARC expression in primary tumor and metastatic lymph node of resected pancreatic cancer patients and patients' survival

BACKGROUND

Previous researches in pancreatic cancer demonstrated a negative correlation between secreted protein acidic and rich in cysteine (SPARC) expression in primary tumor and survival, but not for SPARC expression in lymph node. In the present study, we aimed to evaluate the SPARC expression in various types of tissues and its impact on patients' prognosis.

METHODS

The expression of SPARC was examined by immunohistochemistry in resected pancreatic cancer specimens. Kaplan-Meier analyses and Cox proportional hazards regression were applied to assess the mortality risk.

RESULTS

A total of 222 tissue samples from 73 patients were collected to evaluate the SPARC expression, which included 73 paired primary tumor and adjacent normal tissues, 38 paired metastatic and normal lymph nodes. The proportion of positive SPARC expression in metastatic lymph node was high (32/38), whereas in normal lymph node it was negative (0/38). Positive SPARC expression in primary tumor cells was associated with a significantly decreased overall survival (P=0.007) and disease-free survival (P=0.003), whereas in other types of tissues it did not show a predictive role for prognosis. Univariate and multivariate analyses both confirmed this significance.

CONCLUSION

SPARC can serve a dual function role as both predictor for prognosis and potentially biomarker for lymph node metastasis in resected pancreatic cancer patients.

Genetic deletion of osteopontin in TRAMP mice skews prostate carcinogenesis from adenocarcinoma to aggressive human-like neuroendocrine cancers

Osteopontin (OPN) is a secreted glycoprotein, that belongs to the non-structural extracellular matrix (ECM), and its over expression in human prostate cancer has been associated with disease progression, androgen independence and metastatic ability. Nevertheless, the pathophysiology of OPN in prostate tumorigenesis has never been studied. We crossed TRansgenic Adenocarcinoma of the Mouse Prostate (TRAMP) mice with OPN deficient (OPN-/-) mice and followed tumor onset and progression in these double mutants. Ultrasound examination detected the early onset of a rapidly growing, homogeneous and spherical tumor in about 60% of OPN-/- TRAMP mice. Such neoplasms seldom occurred in parental TRAMP mice otherwise prone to adenocarcinomas and were characterized for being androgen receptor negative, highly proliferative and endowed with neuroendocrine (NE) features. Gene expression profiling showed up-regulation of genes involved in tumor progression, cell cycle and neuronal differentiation in OPN-deficient versus wild type TRAMP tumors. Down-regulated genes included key genes of TGFa pathway, including SMAD3 and Filamin, which were confirmed at the protein level. Furthermore, NE genes and particularly those characterizing early prostatic lesions of OPN-deficient mice were found to correlate with those of human prostate NE tumours. These data underscore a novel role of OPN in the early stages of prostate cancer growth, protecting against the development of aggressive NE tumors.

Structure and Function of a Prostate Cancer Dissemination-Permissive Extracellular Matrix

Purpose: The poor prognosis of metastatic prostate cancer continues to present a major challenge in prostate cancer treatment. The tumor extracellular matrix (ECM) plays an important role in facilitating metastasis. Here, we investigated the structure and function of an ECM that facilitates prostate cancer metastasis by comparing orthotopic tumors that frequently metastasize to poorly metastatic subcutaneous tumors.Experimental Design: Both tumors were derived from a human prostate cancer PC3 cell line engineered to fluoresce under hypoxia. Second harmonic generation (SHG) microscopy was used to characterize collagen 1 (Col1) fiber patterns in the xenografts as well as in human samples. MRI was used to determine albumin-Gd-diethylenetriaminepenta-acetate (alb-GdDTPA) transport through the ECM using a saturation recovery MR method combined with fast T₁ SNAPSHOT-FLASH imaging. Cancer-associated fibroblasts (CAF) were also quantified in these tumors.Results: Significant structural and functional differences were identified in the prometastatic orthotopic tumor ECM compared to the less metastatic subcutaneous tumor ECM. The significantly higher number of CAFs in orthotopic tumors may explain the higher Col1 fiber volumes in these tumors. In vivo, alb-GdDTPA pooling was significantly elevated in metastatic orthotopic tumors, consistent with the increased Col1 fibers.Conclusions: Developing noninvasive MRI indices of macromolecular transport, together with characterization of Col1 fiber patterns and CAFs can assist in stratifying prostate cancers for aggressive treatments or active surveillance. These results highlight the role of CAFs in supporting or creating aggressive cancers, and the importance of depleting CAFs to prevent metastatic dissemination in prostate cancer. Clin Cancer Res; 23(9); 2245-54. ©2016 AACR.

Data-Driven Metabolic Pathway Compositions Enhance Cancer Survival Prediction

Altered cellular metabolism is an important characteristic and driver of cancer. Surprisingly, however, we find here that aggregating individual gene expression using canonical metabolic pathways fails to enhance the classification of noncancerous vs. cancerous tissues and the prediction of cancer patient survival. This supports the notion that metabolic alterations in cancer rewire cellular metabolism through unconventional pathways. Here we present MCF (Metabolic classifier and feature generator), which incorporates gene expression measurements into a human metabolic network to infer new cancer-mediated pathway compositions that enhance cancer vs. adjacent noncancerous tissue classification across five different cancer types. MCF outperforms standard classifiers based on individual gene expression and on canonical human curated metabolic pathways. It successfully builds robust classifiers integrating different datasets of the same cancer type. Reassuringly, the MCF pathways identified lead to metabolites known to be associated with the pertaining specific cancer types. Aggregating gene expression through MCF pathways leads to markedly better predictions of breast cancer patients’ survival in an independent cohort than using the canonical human metabolic pathways (C-index = 0.69 vs. 0.52, respectively). Notably, the survival predictive power of individual MCF pathways strongly correlates with their power in predicting cancer vs. noncancerous samples. The more predictive composite pathways identified via MCF are hence more likely to capture key metabolic alterations occurring in cancer than the canonical pathways characterizing healthy human metabolism.

Cancer proliferating cells adapt their metabolism to support the conversion of available nutrients into biomass, which often involves an increased rate of specific metabolic pathways, such as glycolysis. Surprisingly, however, we observe that aggregating individual gene expression using canonical human metabolic pathways frequently fails to enhance the classification of noncancerous vs. cancerous tissues and in the task of predicting cancer patient survival. This supports the notion that metabolic alterations in cancer rewire cellular metabolism through unconventional pathways. Here we introduce a novel algorithm (MCF) that aims to identify these cancer-mediated ‘composite’ metabolic pathways by identifying those that best differentiate between cancerous vs. non-cancerous tissues gene expression. Remarkably, MCF successfully builds robust classifiers integrating different datasets of the same cancer type. We further show that the data-driven pathways identified by MCF, in contrast to the canonical literature-based pathways, successfully generate clinically relevant features that are predictive of breast cancer patients’ survival in an independent dataset. Our findings thus suggest that cancer metabolism may be rewired via non-standard composite pathways.

Secreted Protein Acidic and Rich in Cysteine (SPARC) Mediates Metastatic Dormancy of Prostate Cancer in Bone

Prostate cancer is known to frequently recur in bone; however, how dormant cells switch its phenotype leading to recurrent tumor remains poorly understood. We have isolated two syngeneic cell lines (indolent and aggressive) through in vivo selection by implanting PC3mm stem-like cells into tibial bones. We found that indolent cells retained the dormant phenotype, whereas aggressive cells grew rapidly in bone in vivo, and the growth rates of both cells in culture were similar, suggesting a role of the tumor microenvironment in the regulation of dormancy and recurrence. Indolent cells were found to secrete a high level of secreted protein acidic and rich in cysteine (SPARC), which significantly stimulated the expression of BMP7 in bone marrow stromal cells. The secreted BMP7 then kept cancer cells in a dormant state by inducing senescence, reducing "stemness," and activating dormancy-associated p38 MAPK signaling and p21 expression in cancer cells. Importantly, we found that SPARC was epigenetically silenced in aggressive cells by promoter methylation, but 5-azacytidine treatment reactivated the expression. Furthermore, high SPARC promoter methylation negatively correlated with disease-free survival of prostate cancer patients. We also found that the COX2 inhibitor NS398 down-regulated DNMTs and increased expression of SPARC, which led to tumor growth suppression in bone in vivo These findings suggest that SPARC plays a key role in maintaining the dormancy of prostate cancer cells in the bone microenvironment.

Co-Targeting Prostate Cancer Epithelium and Bone Stroma by Human Osteonectin-Promoter-Mediated Suicide Gene Therapy Effectively Inhibits Androgen-Independent Prostate Cancer Growth

Stromal-epithelial interaction has been shown to promote local tumor growth and distant metastasis. We sought to create a promising gene therapy approach that co-targets cancer and its supporting stromal cells for combating castration-resistant prostate tumors. Herein, we demonstrated that human osteonectin is overexpressed in the prostate cancer epithelium and tumor stroma in comparison with their normal counterpart. We designed a novel human osteonectin promoter (hON-522E) containing positive transcriptional regulatory elements identified in both the promoter and exon 1 region of the human osteonectin gene. In vitro reporter assays revealed that the hON-522E promoter is highly active in androgen receptor negative and metastatic prostate cancer and bone stromal cells compared to androgen receptor-positive prostate cancer cells. Moreover, in vivo prostate-tumor–promoting activity of the hON-522E promoter was confirmed by intravenous administration of an adenoviral vector containing the hON-522E promoter-driven luciferase gene (Ad-522E-Luc) into mice bearing orthotopic human prostate tumor xenografts. In addition, an adenoviral vector with the hON-522E-promoter–driven herpes simplex virus thymidine kinase gene (Ad-522E-TK) was highly effective against the growth of androgen-independent human prostate cancer PC3M and bone stromal cell line in vitro and in pre-established PC3M tumors in vivo upon addition of the prodrug ganciclovir. Because of the heterogeneity of human prostate tumors, hON-522E promoter-mediated gene therapy has the potential for the treatment of hormone refractory and bone metastatic prostate cancers.

Matricellular proteins as regulators of cancer metastasis to bone

Metastasis is the major cause of death in cancer patients, and a frequent site of metastasis for many cancers is the bone marrow. Therefore, understanding the mechanisms underlying the metastatic process is necessary for future prevention and treatment. The tumor microenvironment is now known to play a role in the metastatic cascade, both at the primary tumor and in metastatic sites, and includes both cellular and non-cellular components. The extracellular matrix (ECM) provides structural support and signaling cues to cells. One particular group of molecules associated with the ECM, known as matricellular proteins, modulate multiple aspects of tumor biology, including growth, migration, invasion, angiogenesis and metastasis. These proteins are also important for normal function in the bone by regulating bone formation and bone resorption. Recent studies have described a link between some of these proteins and metastasis of various tumors to the bone. The aim of this review is to summarize what is currently known about matricellular protein influence on bone metastasis. Particular attention to the contribution of both tumor cells and non-malignant cells in the bone has been given.

Prognostic Value of SPARC in Patients with Pancreatic Cancer: A Systematic Review and Meta-Analysis

OBJECTIVE

There is a heated debate on whether the prognostic value of SPARC is favorable or unfavorable. Thus, we carried out a meta-analysis evaluating the relationship between SPARC expression and the prognosis of patients with pancreatic cancer.

METHODS

We searched PubMed, EMBASE and Web of Science for relevant articles. The pooled hazard ratios (HRs) and corresponding 95%CI of overall survival (OS) were calculated to evaluate the prognostic value of SPARC expression in patients with pancreatic cancer. We also performed subgroup analyses.

RESULTS

With 1623 patients pooled from 10 available studies, the incorporative HR showed an unfavorable prognosis of patients with pancreatic cancer in the multivariate analysis (HR = 1.55, 95%CI: 1.11-2.17, P = 0.01), but not in univariate analysis (HR = 1.41, 95%CI: 0.47-4.21, P = 0.54) and estimate (HR = 1.24, 95%CI: 0.72-2.13, P = 0.44). And this adverse impact could also be found in the subgroup analyses in multivariate analysis, especially in the stroma (HR = 1.53, 95%CI: 1.05-2.24, P = 0.03). However, the combined HR had the highly significant heterogeneity. No obvious publication bias was found.

CONCLUSIONS

SPARC might be an unfavorable indicator in patients with pancreatic cancer, especially in the stroma. More and further researches should be conducted to reveal the prognostic value of SPARC.

Ability of PITX2 methylation to predict survival in patients with prostate cancer

Background

The aim of this study was to explore whether candidate gene methylation can effectively predict death from prostate cancer.

Methods

After reviewing the literature to identify likely candidate genes, we assembled a case-control cohort (in a 1:2 ratio) to explore the distribution of PITX2, WNT5a, SPARC, EPB41L3, and TPM4 methylation levels. The case group comprised 45 patients with a Gleason score ≤7 who had died as a result of prostate cancer, and the control group comprised 90 current prostate cancer patients or those who died of other causes. The methylation possibility of each of the candidate genes were maximized. Univariate conditional logistic was applied for data analysis and to evaluate prediction efficiency of gene methylation on prostate cancer.

Results

The results indicated that a raised level of PITX2 methylation increased the likelihood of death due to prostate cancer by 10% (odds ratio 1.56, 95% confidence interval 1.17–2.08; P=0.005). Methylation of SPARC was found to be able to distinguish between benign prostate hyperplasia and prostate cancer.

Conclusion

Methylation of PITX2 is an effective biomarker to predict death from prostate cancer, particularly in patients with a low Gleason score.

Coordinate regulation of microenvironmental stimuli and role of methylation in bone metastasis from breast carcinoma

The pathogenesis of bone metastasis is unclear, and much focus in metastatic biology and therapy relays on epigenetic alterations. Since DNA-methyltransferase blockade with 5-aza-2'-deoxycytidine (dAza) counteracts tumour growth, here we utilized dAza to clarify whether molecular events undergoing epigenetic control were critical for bone metastatization. In particular, we investigated the patterns of secreted-protein acidic and rich in cysteine (SPARC) and of Endothelin 1, affected by DNA methyltransferases in tumours, with the hypothesis that in bone metastasis a coordinate function of SPARC and Endothelin 1, if any occurs, was orchestrated by DNA methylation. To this purpose, we prepared a xenograft model with the clone 1833, derived from human-MDA-MB231 cells, and dAza administration slowed-down metastasis outgrowth. This seemed consequent to the reductions of SPARC and Endothelin 1 at invasive front and in the bone marrow, mostly due to loss of Twist. In the metastasis bulk Snail, partly reduced by dAza, might sustain Endothelin 1-SPARC cooperativity. Both SPARC and Endothelin 1 underwent post-translational control by miRNAs, a molecular mechanism that might explain the in vivo data. Ectopic miR29a reduced SPARC expression also under long-term dAza exposure, while Endothelin 1 down-regulation occurred in the presence of endogenous-miR98 expression. Notably, dAza effects differed depending on in vivo and in vitro conditions. In 1833 cells exposed to 30-days dAza, SPARC-protein level was practically unaffected, while Endothelin 1 induction depended on the 3'-UTR functionality. The blockade of methyltransferases leading to SPARC reduction in vivo, might represent a promising strategy to hamper early steps of the metastatic process affecting the osteogenic niche.

Signaling pathways activation profiles make better markers of cancer than expression of individual genes

Identification of reliable and accurate molecular markers remains one of the major challenges of contemporary biomedicine. We developed a new bioinformatic technique termed OncoFinder that for the first time enables to quantatively measure activation of intracellular signaling pathways basing on transcriptomic data. Signaling pathways regulate all major cellular events in health and disease. Here, we showed that the Pathway Activation Strength (PAS) value itself may serve as the biomarker for cancer, and compared it with the "traditional" molecular markers based on the expression of individual genes. We applied OncoFinder to profile gene expression datasets for the nine human cancer types including bladder cancer, basal cell carcinoma, glioblastoma, hepatocellular carcinoma, lung adenocarcinoma, oral tongue squamous cell carcinoma, primary melanoma, prostate cancer and renal cancer, totally 292 cancer and 128 normal tissue samples taken from the Gene expression omnibus (GEO) repository. We profiled activation of 82 signaling pathways that involve ~2700 gene products. For 9/9 of the cancer types tested, the PAS values showed better area-under-the-curve (AUC) scores compared to the individual genes enclosing each of the pathways. These results evidence that the PAS values can be used as a new type of cancer biomarkers, superior to the traditional gene expression biomarkers.

SPARC mediates metastatic cooperation between CSC and non-CSC prostate cancer cell subpopulations

Background

Tumor cell subpopulations can either compete with each other for nutrients and physical space within the tumor niche, or co-operate for enhanced survival, or replicative or metastatic capacities. Recently, we have described co-operative interactions between two clonal subpopulations derived from the PC-3 prostate cancer cell line, in which the invasiveness of a cancer stem cell (CSC)-enriched subpopulation (PC-3M, or M) is enhanced by a non-CSC subpopulation (PC-3S, or S), resulting in their accelerated metastatic dissemination.

Methods

M and S secretomes were compared by SILAC (Stable Isotope Labeling by Aminoacids in Cell Culture). Invasive potential in vitro of M cells was analyzed by Transwell-Matrigel assays. M cells were co-injected with S cells in the dorsal prostate of immunodeficient mice and monitored by bioluminescence for tumor growth and metastatic dissemination. SPARC levels were determined by immunohistochemistry and real-time RT-PCR in tumors and by ELISA in plasma from patients with metastatic or non-metastatic prostate cancer.

Results

Comparative secretome analysis yielded 213 proteins differentially secreted between M and S cells. Of these, the protein most abundantly secreted in S relative to M cells was SPARC. Immunodepletion of SPARC inhibited the enhanced invasiveness of M induced by S conditioned medium. Knock down of SPARC in S cells abrogated the capacity of its conditioned medium to enhance the in vitro invasiveness of M cells and compromised their potential to boost the metastatic behavior of M cells in vivo. In most primary human prostate cancer samples, SPARC was expressed in the epithelial tumoral compartment of metastatic cases.

Conclusions

The matricellular protein SPARC, secreted by a prostate cancer clonal tumor cell subpopulation displaying non-CSC properties, is a critical mediator of paracrine effects exerted on a distinct tumor cell subpopulation enriched in CSC. This paracrine interaction results in an enhanced metastatic behavior of the CSC-enriched tumor subpopulation. SPARC is expressed in the neoplastic cells of primary prostate cancer samples from metastatic cases, and could thus constitute a tumor progression biomarker and a therapeutic target in advanced prostate cancer.

Electronic supplementary material

The online version of this article (doi:10.1186/1476-4598-13-237) contains supplementary material, which is available to authorized users.

Re-sensitization of 5-FU resistance by SPARC through negative regulation of glucose metabolism in hepatocellular carcinoma

Secreted protein, acidic and rich in cysteine (SPARC), a calcium-binding matricellular glycoprotein, is implicated in the progression of many cancers. Currently, there is growing evidence for important functions of SPARC in a variety of cancers and its role in cancer depends on tumor types. In this study, we reported SPARC negatively regulated glucose metabolism in hepatocellular carcinoma (HCC). Overexpression of SPARC inhibited glucose uptake and lactate product through downregulation of key enzymes of glucose metabolism. On the other hand, knock down of SPARC reversed the phenotypes. Meanwhile, exogenous expression of SPARC in HepG2 cells resulted in tolerance to low glucose and was correlated with AMPK pathway. Interestingly, the 5-fluorouracil (5-FU)-resistant HepG2 cells showed increased glucose metabolism and downregulated SPARC levels. Finally, we reported the overexpression of SPARC re-sensitize 5-FU-resistant cells to 5-FU through inhibition of glycolysis both in vitro and in vivo. Our study proposed a novel function of SPARC in the regulation of glucose metabolism in hepatocellular carcinoma and will facilitate the development of therapeutic strategies for the treatments of liver tumor patients.

Role of SPARC in bone remodeling and cancer-related bone metastasis

There is a growing socioeconomic recognition that clinical bone diseases such as bone infections, bone tumors and osteoporotic bone loss mainly associated with ageing, are major issues in today's society. SPARC (secreted protein, acidic and rich in cysteine), a matricellular glycoprotein, may be a promising therapeutic target for preventing or treating bone-related diseases. In fact, SPARC is associated with tissue remodeling, repair, development, cell turnover, bone mineralization and may also participate in growth and progression of tumors, namely cancer-related bone metastasis. Yet, the function of SPARC in such biological processes is poorly understood and controversial. The main objective of this work is to review the current knowledge related to the activity of SPARC in bone remodeling, tumorigenesis, and bone metastasis. Progress in understanding SPARC biology may provide novel strategies for bone regeneration and the development of anti-angiogenic, anti-proliferative, or counter-adhesive treatments specifically against bone metastasis.

SPARC/osteonectin is involved in metastatic process to the lung during melanoma progression

The existence of a "metastasis gene signature" that predisposes primary breast cancer cells to metastasize to the lungs has been recently highlighted by gene expression profiling studies. The combination of genes responsible for this process includes genes encoding several metalloproteinases as well as the gene encoding SPARC (secreted protein acidic and rich in cysteine)/osteonectin. SPARC is involved in normal tissue remodeling as it regulates the deposition of extracellular matrix, but also plays a role in neoplastic transformation. Aberrant SPARC expression has been detected both in stromal cells associated with cancer and in cancer cells. The main aim of this study was to investigate whether or not SPARC might be involved in directing metastasis of other types of cancer to the lung. We constructed a tissue microarray containing lung metastases from a variety of primary tumors in different organs and used immunohistochemistry to assess SPARC expression. We found SPARC overexpressed mainly in lung metastases from melanoma. We then assessed the expression of SPARC mRNA and protein in metastatic melanoma from different anatomic sites and in their corresponding primary tumors, and found that it is overexpressed in lung metastases. Our data strongly support the hypothesis that SPARC is involved in directing melanoma metastases specifically to the lung, which underpins its potential as prognostic marker and novel target for specific therapy.