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Background: Tissue-resident memory T (TRM) cells can reside in the tumor microenvironment and are considered the primary response cells to immunotherapy. Heterogeneity in functional status and spatial distribution may contribute to the controversial role of TRM cells but we know little about it. Methods: Through multiplex immunofluorescence (mIF) (CD8, CD103, PD-1, Tim-3, GZMB, CK), the quantity and spatial location of TRM cell subsets were recognized in the tissue from 274 patients with NSCLC after radical surgery. By integrating multiple machine learning methods, we constructed a TRM-based spatial immune signature (TRM-SIS) to predict the prognosis. Furthermore, we conducted a CD103-related gene set enrichment analysis (GSEA) and verified its finding by another mIF panel (CD8, CD103, CK, CD31, Hif-1α). Results: The density of TRM cells was significantly correlated with the expression of PD-1, Tim-3 and GZMB. Four types of TRM cell subsets was defined, including TRM1 (PD-1−Tim-3−TRM), TRM2 (PD-1+Tim-3−TRM), TRM3 (PD-1−Tim-3+TRM) and TRM4 (PD-1+Tim-3+TRM). The cytotoxicity of TRM2 was the strongest while that of TRM4 was the weakest. Compare with TRM1 and TRM2, TRM3 and TRM4 had better infiltration and stronger interaction with cancer cells. The TRM-SIS was an independent prognostic factor for disease-free survival [HR = 2.43, 95%CI (1.63–3.60), P < 0.001] and showed a better performance than the TNM staging system for recurrence prediction. Furthermore, by CD103-related GSEA and mIF validation, we found a negative association between tumor angiogenesis and infiltration of TRM cells. Conclusions: These findings reveal a significant heterogeneity in the functional status and spatial distribution of TRM cells, and support it as a biomarker for the prognosis of NSCLC patients. Regulating TRM cells by targeting tumor angiogenesis may be a potential strategy to improve current immunotherapy. [ABSTRACT FROM AUTHOR]

Prostate cancer (PCa) is the second-most common cause of male cancer-related death in western industrialized countries, and the emergence of metastases is a key challenge in the treatment of PCa. Accumulating studies have shown that long noncoding RNAs (lncRNAs) play an important role in the regulation of diverse cellular and molecular processes during the development and progression of cancer. Here, we utilized a unique cohort of castration-resistant prostate cancer metastases (mCRPC) and corresponding localized tumors and RNA sequencing (RNA-seq). First, we showed that patient-to-patient variability accounted for most of the variance in lncRNA expression between the samples, suggesting that genomic alterations in the samples are the main drivers of lncRNA expression in PCa metastasis. Subsequently, we identified 27 lncRNAs with differential expression (DE-lncRNAs) between metastases and corresponding primary tumors, suggesting that they are mCRPC-specific lncRNAs. Analyses of potential regulation by transcription factors (TFs) revealed that approximately half of the DE-lncRNAs have at least one binding site for the androgen receptor in their regulatory regions. In addition, TF enrichment analysis revealed the enrichment of binding sites for PCa-associated TFs, such as FOXA1 and HOXB13, in the regulatory regions of the DE-lncRNAs. In a cohort of prostatectomy-treated prostate tumors, four of the DE-lncRNAs showed association with progression-free time and two of them (lnc-SCFD2-2 and lnc-R3HCC1L-8) were independent prognostic markers. Our study highlights several mCRPC-specific lncRNAs that might be important in the progression of the disease to the metastatic stage and may also serve as potential biomarkers for aggressive PCa. [ABSTRACT FROM AUTHOR]

Background: Prostate cancer (PCa) is a clinically heterogeneous disease. The creation of an expression‐based subtyping model based on prostate‐specific biological processes was sought. Methods: Unsupervised machine learning of gene expression profiles from prospectively collected primary prostate tumors (training, n = 32,000; evaluation, n = 68,547) was used to create a prostate subtyping classifier (PSC) based on basal versus luminal cell expression patterns and other gene signatures relevant to PCa biology. Subtype molecular pathways and clinical characteristics were explored in five other clinical cohorts. Results: Clustering derived four subtypes: luminal differentiated (LD), luminal proliferating (LP), basal immune (BI), and basal neuroendocrine (BN). LP and LD tumors both had higher androgen receptor activity. LP tumors also had a higher expression of cell proliferation genes, MYC activity, and characteristics of homologous recombination deficiency. BI tumors possessed significant interferon γactivity and immune infiltration on immunohistochemistry. BN tumors were characterized by lower androgen receptor activity expression, lower immune infiltration, and enrichment with neuroendocrine expression patterns. Patients with LD tumors had less aggressive tumor characteristics and the longest time to metastasis after surgery. Only patients with BI tumors derived benefit from radiotherapy after surgery in terms of time to metastasis (hazard ratio [HR], 0.09; 95% CI, 0.01–0.71; n = 855). In a phase 3 trial that randomized patients with metastatic PCa to androgen deprivation with or without docetaxel (n = 108), only patients with LP tumors derived survival benefit from docetaxel (HR, 0.21; 95% CI, 0.09–0.51). Conclusions: With the use of expression profiles from over 100,000 tumors, a PSC was developed that identified four subtypes with distinct biological and clinical features. Plain language summary: Prostate cancer can behave in an indolent or aggressive manner and vary in how it responds to certain treatments.To differentiate prostate cancer on the basis of biological features, we developed a novel RNA signature by using data from over 100,000 prostate tumors—the largest data set of its kind.This signature can inform patients and physicians on tumor aggressiveness and susceptibilities to treatments to help personalize cancer management. Data from over 100,000 prostate tumors and multiple cohorts were used to create and validate an expression‐based signature that can subtype prostate cancer on the basis of biological features and treatment susceptibilities. [ABSTRACT FROM AUTHOR]

Background: The dual upregulation of TOP2A and EZH2 gene expression has been proposed as a biomarker for recurrence in prostate cancer patients to be treated with radical prostatectomy. A low tissue level of the metabolite citrate has additionally been connected to aggressive disease and recurrence in this patient group. However, for radiotherapy prostate cancer patients, few prognostic biomarkers have been suggested. The main aim of this study was to use an integrated tissue analysis to evaluate metabolites and expression of TOP2A and EZH2 as predictors for recurrence among radiotherapy patients. Methods: From 90 prostate cancer patients (56 received neoadjuvant hormonal treatment), 172 transrectal ultrasound‐guided (TRUS) biopsies were collected prior to radiotherapy. Metabolic profiles were acquired from fresh frozen TRUS biopsies using high resolution‐magic angle spinning MRS. Histopathology and immunohistochemistry staining for TOP2A and EZH2 were performed on TRUS biopsies containing cancer cells (n = 65) from 46 patients, where 24 of these patients (n = 31 samples) received hormonal treatment. Eleven radical prostatectomy cohorts of a total of 2059 patients were used for validation in a meta‐analysis. Results: Among radiotherapy patients with up to 11 years of follow‐up, a low level of citrate was found to predict recurrence, p = 0.001 (C‐index = 0.74). Citrate had a higher predictive ability compared with individual clinical variables, highlighting its strength as a potential biomarker for recurrence. The dual upregulation of TOP2A and EZH2 was suggested as a biomarker for recurrence, particularly for patients not receiving neoadjuvant hormonal treatment, p = 0.001 (C‐index = 0.84). While citrate was a statistically significant biomarker independent of hormonal treatment status, the current study indicated a potential of glutamine, glutamate and choline as biomarkers for recurrence among patients receiving neoadjuvant hormonal treatment, and glucose among patients not receiving neoadjuvant hormonal treatment. Conclusion: Using an integrated approach, our study shows the potential of citrate and the dual upregulation of TOP2A and EZH2 as biomarkers for recurrence among radiotherapy patients. [ABSTRACT FROM AUTHOR]

Purpose: Early biochemical recurrence (eBCR) indicated a high risk for potential recurrence and metastasis in prostate cancer. The N6-methyladenosine (m6A) methylation modification played an important role in prostate cancer progression. This study aimed to develop a m6A lncRNA signature to accurately predict eBCR in prostate cancer. Methods: Pearson correlation analysis was first conducted to explore m6A lncRNAs and univariate Cox regression analysis was further performed to identify m6A lncRNAs of prognostic roles for predicting eBCR in prostate cancer. The m6A lncRNA signature was constructed by least absolute shrinkage and selection operator analysis (LASSO) in training cohort and further validated in test cohort. Furthermore, half maximal inhibitory concentration (IC50) values were utilized to explore potential effective drugs for high-risk group in this study. Results: Five hundred and thirty-eighth m6A lncRNAs were searched out through Pearson correlation analysis and 25 out of 538 m6A lncRNAs were identified to pose prediction roles for eBCR in prostate cancers. An m6A lncRNA signature including 5 lncRNAs was successfully built in training cohort. The high-risk group derived from m6A lncRNA signature could efficiently predict eBCR occurrence in both training (p < 0.001) and test cohort (p = 0.002). ROC analysis also confirmed that lncRNA signature in this study posed more accurate prediction roles for eBCR occurrence when compared with PSA, TNM stages and Gleason scores. Drug sensitivity analysis further discovered that various drugs could be potentially utilized to treat high-risk samples in this study. Conclusions: The m6A lncRNA signature in this study could be utilized to efficiently predict eBCR occurrence, various clinical characteristic and immune microenvironment for prostate cancer. [ABSTRACT FROM AUTHOR]

A detectable and rising PSA following radical prostatectomy is indicative of recurrent prostate cancer. Salvage radiotherapy (SRT) with/without androgen deprivation therapy represents the main treatment option for these patients and has been historically associated with a biochemical control rate of ~70%. To determine the optimal timing, diagnostic workup, radiotherapy dosefractionation, treatment volume, and use of systemic therapy, several informative studies have been conducted in the last decade. This review examines the recent evidence to guide radiotherapy decision making in the SRT setting. Key topics include adjuvant vs salvage RT, utilization of molecular imaging and genomic classifiers, length of androgen deprivation therapy, inclusion of elective pelvic volume, and emerging role for hypofractionation. Recently reported trials, conducted in an era prior to the routine use of molecular imaging and genomic classifiers, have been pivotal in establishing the current standard of care for SRT in prostate cancer. However, decisions about radiation treatment and systemic therapy may be tailored based on available prognostic and predictive biomarkers. Data from contemporary clinical trials are awaited to define and establish individualized, biomarker-driven approaches for SRT. [ABSTRACT FROM AUTHOR]

Background: Current stratification systems for tumor prognostic prediction and immunotherapeutic efficacy evaluation are less satisfying in colorectal cancer (CRC). As infiltrating immune cells in tumor microenvironment (TME) played a key role in tumor progression and responses to immune checkpoint blockade (ICB) therapy, we want to construct an immune-related scoring system with detailed immune profiles to stratify CRC patients. Methods: We developed a scoring system based on immune-related signatures and validated its ability to predict prognosis and immunotherapeutic outcomes in CRC. CD45+ cells from CRC patients were sorted to investigate detailed immune profiles of the stratification system using mass cytometry. A single-cell RNA sequencing dataset was used to analyze transcriptomic profiles. Results: We constructed an immune-related signature score (IRScore) based on 54 recurrence-free survival (RFS)-related immune signatures to stratify CRC patients. We revealed that IRScore was positively correlated with RFS and favorable outcomes in ICB treatment. Moreover, we depicted a detailed immune profile in TME using mass cytometry and identified that CD103+CD39+ T cells, characterized by an exhaustive, cytotoxic and proliferative phenotype, were enriched in CRC patients with high IRScore. As a beneficial immune signature, CD103+CD39+ T cells could predict prognosis and responses to ICB therapy in CRC. Conclusions: All the analyses above revealed that IRScore could be a valuable tool for predicting prognosis and facilitating the development of new therapeutic strategies in CRC, and CD103+CD39+ T cells were one of defined immune signatures in IRScore, which might be a key factor for antitumor immunity. [ABSTRACT FROM AUTHOR]

Aneuploidy, the state of the cell in which the number of whole chromosomes or chromosome arms becomes imbalanced, has been recognized as playing a pivotal role in tumor evolution for over 100 years. In melanoma, the extent of aneuploidy, as well as the chromosomal regions that are affected differ across subtypes, indicative of distinct drivers of disease. Multiple studies have suggested a role for aneuploidy in diagnosis and prognosis of melanomas, as well as in the context of immunotherapy response. A number of key constituents of the cell cycle have been implicated in aneuploidy acquisition in melanoma, including several driver mutations. Here, we review the state of the art on aneuploidy in different melanoma subtypes, discuss the potential drivers, mechanisms underlying aneuploidy acquisition as well as its value in patient diagnosis, prognosis and response to immunotherapy treatment. [ABSTRACT FROM AUTHOR]

Purpose: To develop and validate a risk score (P-score) algorithm which includes previously described three-gene signature and clinicopathological parameters to predict the risk of death from prostate cancer (PCa) in a retrospective cohort. Patients and Methods: A total of 591 PCa patients diagnosed between 2003 and 2008 in Stockholm, Sweden, with a median clinical follow-up time of 7.6 years (1– 11 years) were included in this study. Expression of a three-gene signature (IGFBP3, F3, VGLL3) was measured in formalin-fixed paraffin-embedded material from diagnostic core needle biopsies (CNB) of these patients. A point-based scoring system based on a Fine-Gray competing risk model was used to establish the P-score based on the three-gene signature combined with PSA value, Gleason score and tumor stage at diagnosis. The endpoint was PCa-specific mortality, while other causes of death were treated as a competing risk. Out of the 591 patients, 315 patients (estimation cohort) were selected to develop the P-score. The P-score was subsequently validated in an independent validation cohort of 276 patients. Results: The P-score was established ranging from the integers 0 to 15. Each one-unit increase was associated with a hazard ratio of 1.39 (95% confidence interval: 1.27– 1.51, p < 0.001). The P-score was validated and performed better in predicting PCa-specific mortality than both D'Amico (0.76 vs 0.70) and NCCN (0.76 vs 0.71) by using the concordance index for competing risk. Similar improvement patterns are shown by time-dependent area under the curve. As demonstrated by cumulative incidence function, both P-score and gene signature stratified PCa patients into significantly different risk groups. Conclusion: We developed the P-score, a risk stratification system for newly diagnosed PCa patients by integrating a three-gene signature measured in CNB tissue. The P-score could provide valuable decision support to distinguish PCa patients with favorable and unfavorable outcomes and hence improve treatment decisions. [ABSTRACT FROM AUTHOR]

Introduction and objectives: ISL1 serves as a biomarker of metastasis and neuroendocrine neoplasia in multiple tumors. However, the expression and relation of ISL1 to other biomarkers in prostate cancer have not been fully elucidated. Here, we characterize the expression of ISL1 and its partners in PCa and document its association to disease progression and post castration resistance neuroendocrine differentiation. Methods: The expression of ISL1 was interrogated in > 6000 primary samples from the Decipher GRID registry and 250 mCRPC samples to assess its prognostic value and relation to neuroendocrine differentiation. Results: ISL1 was highly correlated to MEIS genes and other genes related to cell motility. ISL1 down-regulation in PCa was associated with cancer progression, aggressive primary tumors, and metastatic outcome. We found that ISL1 is highly correlated to MEIS genes across multiple primary PCa and mCRPC cohorts. The expression of ISL1 and MEIS genes were significantly and inversely related to metastasis-free survival and lethal disease, and were downregulated in CRPC and hormone naïve metastatic tumors but showed upregulation in neuroendocrine tumors. Co-immunoprecipitation showed MEIS2 and ISL1 interacting with each supporting their role in modulating transcriptional regulation and nominating this complex for potential targeted therapy. Conclusions: ISL1 complex with MEIS2 serves a critical role in prostate tumor progression and its upregulation in mCRPC/NE provides a rationale for assessing the role of ISL1 and its associated protein in treatment resistance. [ABSTRACT FROM AUTHOR]

Background: Merkel cell carcinoma (MCC) is a rare and aggressive neuroendocrine cutaneous malignancy with poor prognosis. In Europe, approved systemic therapies are limited to the PD-L1 inhibitor avelumab. For avelumab-refractory patients, efficient and safe treatment options are lacking. Methods: At three different sites in Germany, clinical and molecular data of patients with metastatic MCC being refractory to the PD-L1 inhibitor avelumab and who were later on treated with combined IPI/NIVO were retrospectively collected and evaluated. Results: Five patients treated at three different academic sites in Germany were enrolled. Three out of five patients investigated for this report responded to combined IPI/NIVO according to RECIST 1.1. Combined immunotherapy was well tolerated without any grade II or III immune-related adverse events. Two out of three responders to IPI/NIVO received platinum-based chemotherapy in between avelumab and combined immunotherapy. Conclusion: In this small retrospective study, we observed a high response rate and durable responses to subsequent combined immunotherapy with IPI/NIVO in avelumab-refractory metastatic MCC patients. In conclusion, our data suggest a promising activity of second- or third-line PD-1- plus CTLA-4-blockade in patients with anti-PD-L1-refractory MCC. [ABSTRACT FROM AUTHOR]

Prognostic tests using expression profiles of several dozen genes help provide treatment choices for prostate cancer (PCa). However, these tests require improvement to meet the clinical need for resolving overtreatment, which continues to be a pervasive problem in PCa management. Genomic selection (GS) methodology, which utilizes whole-genome markers to predict agronomic traits, was adopted in this study for PCa prognosis. We leveraged The Cancer Genome Atlas (TCGA) database to evaluate the prediction performance of six GS methods and seven omics data combinations, which showed that the Best Linear Unbiased Prediction (BLUP) model outperformed the other methods regarding predictability and computational efficiency. Leveraging the BLUP-HAT method, an accelerated version of BLUP, we demonstrated that using expression data of a large number of disease-relevant genes and with an integration of other omics data (i.e. miRNAs) significantly increased outcome predictability when compared with panels consisting of a small number of genes. Finally, we developed a novel stepwise forward selection BLUP-HAT method to facilitate searching multiomics data for predictor variables with prognostic potential. The new method was applied to the TCGA data to derive mRNA and miRNA expression signatures for predicting relapse-free survival of PCa, which were validated in six independent cohorts. This is a transdisciplinary adoption of the highly efficient BLUP-HAT method and its derived algorithms to analyze multiomics data for PCa prognosis. The results demonstrated the efficacy and robustness of the new methodology in developing prognostic models in PCa, suggesting a potential utility in managing other types of cancer. [ABSTRACT FROM AUTHOR]

Background: RNA-seq data are increasingly used to derive prognostic signatures for cancer outcome prediction. A limitation of current predictors is their reliance on reference gene annotations, which amounts to ignoring large numbers of non-canonical RNAs produced in disease tissues. A recently introduced kind of transcriptome classifier operates entirely in a reference-free manner, relying on k-mers extracted from patient RNA-seq data.Methods: In this paper, we set out to compare conventional and reference-free signatures in risk and relapse prediction of prostate cancer. To compare the two approaches as fairly as possible, we set up a common procedure that takes as input either a k-mer count matrix or a gene expression matrix, extracts a signature and evaluates this signature in an independent dataset.Results: We find that both gene-based and k-mer based classifiers had similarly high performances for risk prediction and a markedly lower performance for relapse prediction. Interestingly, the reference-free signatures included a set of sequences mapping to novel lncRNAs or variable regions of cancer driver genes that were not part of gene-based signatures.Conclusions: Reference-free classifiers are thus a promising strategy for the identification of novel prognostic RNA biomarkers. [ABSTRACT FROM AUTHOR]

Background: Accumulating evidence has demonstrated that immune-related lncRNAs (IRLs) are commonly aberrantly expressed in breast cancer (BC). Thus, we aimed to establish an IRL-based tool to improve prognosis prediction in BC patients.Methods: We obtained IRL expression profiles in large BC cohorts (N = 911) from The Cancer Genome Atlas (TCGA) database. Then, in light of the correlation between each IRL and recurrence-free survival (RFS), we screened prognostic IRL signatures to construct a novel RFS nomogram via a Cox regression model. Subsequently, the performance of the IRL-based model was evaluated through discrimination, calibration ability, risk stratification ability and decision curve analysis (DCA).Results: A total of 52 IRLs were obtained from TCGA. Based on multivariate Cox regression analyses, four IRLs (A1BG-AS1, AC004477.3, AC004585.1 and AC004854.2) and two risk parameters (tumor subtype and TNM stage) were utilized as independent indicators to develop a novel prognostic model. In terms of predictive accuracy, the IRL-based model was distinctly superior to the TNM staging system (AUC: 0.728 VS 0.673, P = 0.010). DCA indicated that our nomogram had favorable clinical practicability. In addition, risk stratification analysis showed that the IRL-based tool efficiently divided BC patients into high- and low-risk groups (P < 0.001).Conclusions: A novel IRL-based model was constructed to predict the risk of 5-year RFS in BC. Our model can improve the predictive power of the TNM staging system and identify high-risk patients with tumor recurrence to implement more appropriate treatment strategies. [ABSTRACT FROM AUTHOR]

Gleason score (GS) is a powerful prognostic factor in prostate cancer (PCa). A GS-7 tumor typically has the primary Gleason (architectural) pattern and secondary prevalent one being graded with 3 and 4 (or 4 and 3), respectively. Due to the well-known intratumoral multifocal occurrence of different patterns, a biological sample from a GS-7 tumor used in a molecular experiment will be uncertain regarding the actually represented pattern if no special attention is given to specimen preparation. In this study, by an integrative analysis of several published gene expression datasets, one of which is the profiling of the paired GP-3 (Gleason pattern 3) and GP-4 (Gleason pattern 4) specimens of 13 GS-7 tumors, we demonstrate that such an uncertainty can be frequently observed in the published data. More specifically, our results suggest that the GS-7 specimens used to generate the frequently-cited The Cancer Genome Atlas (TCGA) data and the Gene Expression Omnibus (GEO) dataset GSE21032 which largely are individual GP-3 or GP-4 specimens rather than the "intermediate" specimens of GP-3 and GP-4. This indicates a pitfall in the existing molecular research of prostate tumors relevant to GS and in GS-related molecular biomarker identification using the previously documented data. [ABSTRACT FROM AUTHOR]

Purpose: To review available prostate cancer biomarkers and their performance in a clinical order, from prostate cancer detection, to treatment of localized and advanced disease. Methods: We used an electronic literature search of the PubMed database using the key words "prostate biomarkers," "genomic markers," and "prostate cancer screening," as well as specific biomarkers, until March 2019. Results: Prostate-specific antigen (PSA) lacks sensitivity for prostate cancer detection, and PSA derivatives have slightly improved its specificity, but have not resolved the limitations of PSA screening. Prostate cancer biomarkers have emerged as an ancillary tool to guide the clinical decision-making in different clinical scenarios. Urine-based tests can identify patients who may benefit from a prostate biopsy, and issue-based markers are helpful in guiding the decision regarding a second biopsy, stratifying patient with newly diagnosed prostate cancer to active surveillance or treatment, and identifying patients who may benefit from adjuvant treatment after surgery. Conclusions: New biomarkers have improved risk stratification in diagnosing and treating prostate cancer. Many of these markers are still considered experimental, and their efficacy and cost utility have not been determined. [ABSTRACT FROM AUTHOR]

Abstract: LRP1B intracellular domain is released and transported to the nucleus; however, pathological consequences of this nuclear transport are largely unclear. We aimed to unravel the pathobiological significance of nuclear localization of LRP1B intracellular domain in mammary gland carcinogenesis. Immunohistochemical staining using antibodies for LRP1B intracellular domain was performed to determine LRP1B expression in 92 invasive ductal breast carcinomas. LRP1B immunoreactivity was detected in the surface membrane and cytoplasm of 60 of 92 invasive ductal carcinomas and in the nucleus of 15 of 92 carcinomas. Nuclear LRP1B was significantly associated with poor patient prognosis, particularly luminal A type breast cancer, where it was significantly related to nodal metastasis. Doxycycline-dependent nuclear expression of LRP1B intracellular domain was established in cultured breast cancer cells. Enforced nuclear expression significantly increased Matrigel invasion activity in MCF-7 and T47D luminal A breast cancer cells. Moreover, enforced nuclear expression of LRP1B intracellular domain facilitated MCF-7 cells growth in mammary fat pad of nude mice, which was supplemented with estrogen. Comprehensive microarray-based analysis demonstrated that nuclear expression of LRP1B intracellular domain significantly increased long non-coding RNA nuclear paraspeckle assembly transcript 1 (NEAT1) expression, which facilitates breast cancer invasion with poor prognosis. Nuclear-localized LRP1B intracellular domain promoted breast cancer progression with poor prognosis, possibly through the NEAT1 pathway. Nuclear transport of LRP1B intracellular domain could be a therapeutic target for breast cancer patients.Key messages: Nuclear LRP1B was significantly associated with poor patient prognosis.Nuclear LRP1B increased Matrigel invasion activity of breast cancer cells.Nuclear expression of LRP1B intracellular domain increased NEAT1 expression. [ABSTRACT FROM AUTHOR]

Prostate cancer is a highly prevalent disease with ample spectrum of aggressiveness and treatment options. Low-risk disease can be safely managed by nonintervention strategies, such as active surveillance; however, accurate risk assessment is warranted. Molecular tests have been developed and validated to complement standard clinicopathological parameters and help to improve risk stratification in prostate cancer. Herein, we review selected tissue-based assays, including genomic prostate score, cell cycle progression score and genomic classifier, with particular emphasis on their role in patient risk assessment in a pretreatment setting, in view of their current or potential utilization in active surveillance. [ABSTRACT FROM AUTHOR]

Purpose: To validate a previously characterized 10-gene signature in prostate cancer with implication to distinguish aggressive and indolent disease within low and intermediate patients’ risk groups.Methods: A case-control study design used to select 545 patients from the Mayo clinic tumor registry who underwent radical prostatectomy. A training set from this cohort (n = 359) was used to build a 10-gene model, based on high-dimensional discriminant analysis (HDDA10) to predict several endpoints of clinical patients’ outcome. An independent set (n = 219) from the same institution was used as validation set.Results: HDDA10 showed significant performance for predicting metastasis (Mets) (AUC 0.68, p = 6.4E - 6) and biochemical recurrence (BCR) (AUC = 0.65, p = 0.003) in the validation set outperforming Gleason grade grouping (GG) for BCR (AUC 0.57, p = 0.03) and with comparable performance for Mets endpoint (GG AUC 0.66, p = 8.1E - 5). HDDA10 prognostic significance was superior to any clinical-pathological parameter within GG2 + 3 (GS7) patients achieving an AUC of 0.74 (p = 0.0037) for BCR compared to Gleason pattern 4 (AUC 0.64) (p = 0.015) and AUC for Mets of 0.68 versus AUC of 0.65 for Gleason pattern 4 (p = 0.01). HDDA10 remained significant for both BCR and Mets in multivariate analysis, suggesting that it can be used to increase accuracy in stratifying patients eligible for active surveillance.Conclusion: HDDA10 is of added value to GG and other clinical-pathological parameters in predicting BCR and Mets endpoint, especially in the low to intermediate patients’ risk groups. HDDA10 prognostic value should be further validated prospectively in stratifying patients specifically in low to intermediate GS (GG1-2), such as active surveillance programs. [ABSTRACT FROM AUTHOR]

Background/Aims: Cervical cancer, which is one of the most aggressive cancers affecting females, has high rates of recurrence and mortality. Small nucleolar RNA host gene 12 (SNHG12) is known to promote the progression of several cancers; however, its exact effects and molecular mechanisms in cervical cancer remain unknown. Methods: Real-time quantitative PCR was used to determine the expression level of SNHG12 in cervical cancer tissues and cell lines. Loss-of-function assays were performed to examine the effect of SNHG12 on the proliferation, apoptosis, migration and invasion of cervical cancer cells in vitro and tumor growth in vivo. Luciferase experiments were employed to explore the interactions between SNHG12 and miR-424-5p. Results: SNHG12 was found to be abnormally elevated in human cervical cancer tissues compared with paired adjacent normal tissues. Moreover, high SNHG12 expression in tumor tissues was significantly correlated with vascular involvement, lymph node metastasis, advanced FIGO stage and poor prognosis. Furthermore, the knockdown of SNHG12 was found to inhibit proliferation, migration and invasion of cervical cancer cells in vitro, and silencing SNHG12 was shown to suppress tumor growth in a nude mouse model. Mechanistic studies showed that SNHG12 functioned as an endogenous sponge for miR-424-5p, thereby downregulating the expression of miR-424-5p in cervical cancer. Furthermore, the inhibition of miR-424-5p in SNHG12-depleted cells partially reversed the effects on cervical cancer cell apoptosis, adhesion and invasion. Conclusion: In summary, our findings suggest that the tumor-promoting role of SNHG12 is to function as a molecular sponge, which negatively regulates miR-424-5p. These findings may provide a potent therapeutic target for cervical cancer. [ABSTRACT FROM AUTHOR]

Background/Aims: Secreted protein acidic and rich in cysteines-like 1 (SPARCL1) is abnormally expressed in gastrointestinal (GI) malignancies. However, the correlation between SPARCL1 expression and the prognosis of patients remains unknown. Therefore, we performed a metaanalysis to investigate the potential value of SPARCL1 as a prognostic predictive marker for GI malignancies. Methods: The PubMed, Embase, EBSCO, CNKI, and Wanfang databases were systematically searched for studies examining SPARCL1 and clinicopathological features, including the prognoses of patients. Hazard ratios (HRs) and odds ratios (ORs) from individual studies were calculated and pooled using a random-effects or fix-effects model. Heterogeneity and publication bias analyses were performed. Results: Data from 8 studies, including a total of 2,356 patients, were summarized. The expression of SPARCL1 suggested a better prognosis (HR=0.57, 95% CI: 0.445-0.698, P=0.000) and was associated with clinicopathological features of GI malignancies, including distant metastasis (OR=0.44, 95% CI: 0.23-0.85, P=0.014), lymph node metastasis (OR=0.56, 95% CI: 0.39-0.81, P=0.002) and tumor differentiation (OR=2.21, 95% CI: 1.82-2.69, P=0.000). Subgroup analyses based on cancer type revealed that the expression of SPARCL1 had no effect on lymph node metastasis in colorectal cancer, and it did not influence tumor differentiation in gastric cancer. Egger's test showed no evidence of publication bias (all P>0.05). Conclusion: SPARCL1 could be a novel prognostic predictive factor for GI malignancies. The expression of SPARCL1 could influence the clinicopathological features of GI malignancies. Further large-scale studies are essential to confirm SPARCL1's prognostic predictive value, and more fundamental experimental studies are needed to illustrate the mechanisms. [ABSTRACT FROM AUTHOR]

Previous studies have shown that the human SPARC‑like 1 (SPARCL1) is crucial for human cancer migration and invasion. In the present study, the expression, biological function and possible molecular regulatory mechanisms of SPARCL1 were investigated in human renal cell carcinoma (RCC). The protein expression of SPARCL1 in cells was evaluated using western blot analysis and immunohistochemical staining in the tissue microarray. The effects of SPARCL1 on the biological behaviors of RCC cells were assessed using in vitro assays. The present study also provisionally investigated the role of SPARCL1 on the mitogen‑activated protein kinase (MAPK) signaling pathway. The results revealed that the expression of SPARCL1 was decreased in the RCC cell lines examined and in the tissue microarray. The overexpression of SPARCL1 significantly inhibited cell migration and invasion, and this may have been due to the inactivation of p38/c‑Jun N‑terminal kinase (JNK)/extracellular signal‑regulated kinase (ERK) MAPKs. The results showed that high expression levels of SPARCL1 offered potential as a useful prognostic factor in RCC. Taken together, the present study demonstrated that the expression of SPARCL1 was downregulated in RCC cells and tissues, however, the overexpression of SPARCL1 inhibited RCC cell migration and invasion. SPARCL1 also reduced the expression of phosphorylated p38/JNK/ERK MAPKs. These data suggested that increasing the protein expression level of SPARCL1 may be novel strategy for treating RCC. [ABSTRACT FROM AUTHOR]

SPARC-like protein 1 (SPARCL1), a member of the family of secreted proteins which is acidic and rich in cysteine, is a potential tumor suppressor gene in most types of tumor. A systemic review and bioinformatics analysis was carried out to determine the associations between SPARCL1 and tumor progression and clinical factors. Downregulation of SPARCL1, thought to be regulated by epigenetic modifications including DNA methylation, serves important functions in tumor progression and development, with its regulatory functions on cell viability, migration, invasion, cell adhesion and drug resistance. Downregulation of SPARCL1 was markedly associated with a poor overall survival rate of patients with one of =7 solid tumors and predicted increased mortality in patients with one of ≥4 distinct tumor types. The present review indicated that SPARCL1 may be a therapeutic target for cancer treatment and a biomarker to determine prognosis. [ABSTRACT FROM AUTHOR]

Background: Large epidemiological studies indicate that an increased body mass index (BMI) is associated with increased prostate cancer (PCa) mortality. Data indicate that there is no association between elevated metabolic pathway proteins and PCa mortality. There are no published studies evaluating the relation between BMI and metabolic pathways with respect to PCa outcomes with a genomics approach.Methods: The Decipher Genomic Resource Information Database was queried for patients who had undergone prostatectomy and had BMI information available. These patients came from Thomas Jefferson University (TJU) and Johns Hopkins Medical Institution (JHMI); the latter provided 2 cohorts (I and II). A high-BMI group (≥30 kg/m2 ) and a low-BMI group (<25 kg/m2 ) were identified, and genomic data were interrogated for differentially expressed genes with an interquartile range filter and a Wilcoxon test. P values were adjusted for multiple testing with the Benjamini-Hochberg false-discovery rate method.Results: A total of 477 patients with a median follow-up of 108 months had BMI information available. Two genes were found to interact with BMI in both the JHMI I cohort and the TJU cohort, but there was no statistical significance after adjustments for multiple comparisons. Aberrant metabolic gene expression was significantly correlated with distant metastases (P < .05). No relation was found between BMI and metastases or overall survival (both P values > .05).Conclusions: In a genomic analysis of prostatectomy specimens, metabolic gene expression, but not BMI, was associated with PCa metastases. Cancer 2017;123:2240-2247. © 2017 American Cancer Society. [ABSTRACT FROM AUTHOR]

Background: Distinct characteristic features categorize Merkel cell carcinoma (MCC) into two subgroups according to the Merkel cell polyomavirus infection. Many mutational studies on MCC have been carried out in recent years without identifying a prominent driver mutation. However, there is paucity reporting the expression of cancer genes at the RNA level in MCC tumors. In this study, we studied the RNA expression profiles of 26 MCC tumors, with a goal to identify prospective molecular targets that could improve the treatment strategies of MCC.Methods: RNA expression of 50 cancer-related genes in 26 MCC tumors was analyzed by targeted amplicon based next-generation sequencing using the Ion Torrent technology and the expression compared with that of normal, non-cancerous skin samples. Sequencing data were processed using Torrent Suite™ Software. Expression profiles of MCV-negative and MCV-positive tumors were compared. Fluorescence in situ hybridization was performed to study ALK rearrangements and immunohistochemistry to study ALK expression in tumor tissue.Results: ALK, CDKN2A, EZH2 and ERBB4 were overexpressed, and EGFR, ERBB2, PDGFRA and FGFR1 were underexpressed in MCC tumors compared to normal skin. In the MCV-negative tumors, MET, NOTCH1, FGFR3, and SMO were overexpressed and JAK3 and NPM1 were under-expressed compared to the MCV-positive tumors.Conclusions: High expression of ALK, CDKN2A and EZH2 was recorded in MCC tumors. No ALK fusion was seen by FISH analysis. Overexpression of EZH2 suggests its potential as a drug target in MCC. [ABSTRACT FROM AUTHOR]

Altered expression of the p16 tumor suppressor is frequently found in prostate cancer, but its role for tumor development and patient prognosis is disputed. In order to clarify the prognostic role of p16 and to draw conclusions on interactions with key molecular features of prostate cancer, we studied p16 expression in a tissue microarray (TMA) with more than 12,400 prostate cancers and attached clinical, pathological, and molecular data such as ERG status and deletions of 3p13, 5q21, 6q15, and PTEN. p16 immunostaining was absent in non-neoplastic prostate cells but was found in 37 % of 9627 interpretable prostate cancers. Finding p16 expression in 58 % of ERG positive but in only 22 % of ERG negative cancers ( p < 0.0001), highlights the known androgen-dependence of both genes. Significant associations between p16 upregulation and tumor phenotype or patient prognosis were strictly limited to the subset of ERG negative cancers. For example, p16 positivity increased from 15 % in Gleason ≤3 + 3 to 38 % in Gleason ≥4 + 4 cancers ( p < 0.0001) and was associated with early PSA recurrence ( p < 0.0001). p16 upregulation was strongly linked to deletions of PTEN ( p < 0.0001), highlighting the interaction of both genes in growth control. In conclusion, p16 upregulation is a strong prognostic factor in ERG negative cancers. The strict limitation of its prognostic impact to a molecularly defined subgroup challenges the concept of molecular prognosis testing without considering molecular subtypes. [ABSTRACT FROM AUTHOR]

Background: Long noncoding RNAs (LncRNAs) have been demonstrated as playing important roles in diverse biological processes including tumorigenesis. However, the clinical significance and biological function of LncRNA nuclear-enriched abundant transcript 1 (NEAT1) in gastric cancer are still unknown. The aim of this study was to identify the role of LncRNA NEAT1 in gastric cancer. Methods: The expression of LncRNA NEAT1 was detected in gastric cancer samples and cell lines by real-time PCR. The clinical and prognostic significance of LncRNA NEAT1 in gastric cancer patients was analyzed. Furthermore, the biological function of LncRNA NEAT1 on tumor cell growth and mobility were explored through MTT, colony formation, transwell migration, and invasion assays in vitro. The potential mechanism of LncRNA NEAT1 was identified by Western blot. Results: LncRNA NEAT1 was overexpressed in gastric cancer tissues and cell lines and corrected with clinical stage, histological type, lymph node metastasis, and distant metastasis. Furthermore, patients with high levels of LncRNA NEAT1 had poorer survival than those with lower levels of LncRNA NEAT1. Univariate and multivariate Cox regression analyses showed that LncRNA NEAT1 overexpression was a poor independent prognostic factor for gastric cancer patients. Moreover, knocking down LncRNA NEAT1 expression significantly suppressed the gastric cancer cell migration and invasion in vitro and regulated EMT-associated proteins expression. Conclusion: LncRNA NEAT1 plays an important role on gastric cancer tumorigenesis and progression and may act as a potential biomarker for therapeutic strategy and prognostic prediction. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the performance of the Decipher test in predicting lymph node invasion (LNI) on radical prostatectomy (RP) specimens. Methods: We identified 1,987 consecutive patients with RP who received the Decipher test between February and August 2015 (contemporary cohort). In the contemporary cohort, only the Decipher score from RP specimens was available for analysis. In addition, we identified a consecutive cohort of patients treated with RP between 2006 and 2012 at the University of California, San Diego, with LNI upon pathologic examination (retrospective cohort). The retrospective cohort yielded seven, 22, and 18 tissue specimens from prostate biopsy, RP, and lymph nodes (LNs) for individual patients, respectively. Univariable and multivariable logistic regression analyses were used to evaluate the performance of Decipher in the contemporary cohort with LNI as the endpoint. In the retrospective cohort, concordance of risk groups was assessed using validated cut-points for low (,0.45), intermediate (0.45-0.60), and high (.0.60) Decipher scores. Results: In the contemporary cohort, 51 (2.6%) patients had LNI. Decipher had an odds ratio of 1.73 (95% confidence interval, 1.46-2.05) and 1.42 (95% confidence interval, 1.19-1.7) per 10% increase in score on univariable and multivariable (adjusting for pathologic Gleason score, extraprostatic extension, and seminal vesicle invasion), respectively. No significant difference in the clinical and pathologic characteristics between the LN positive patients of contemporary and retrospective cohorts was observed (all P.0.05). Accordingly, among LN-positive patients in the contemporary cohort and retrospective cohort, 80% and 77% had Decipher high risk scores (P=1). In the retrospective cohort, prostate biopsy cores with the highest Gleason grade and percentage of tumor involvement had 86% Decipher risk concordance with both RP and LN specimens. Conclusion: Decipher scores were highly concordant between pre- and post-surgical specimens. Further, Decipher scores from RP tissue were predictive of LNI at RP. If validated in a larger cohort of prostate biopsy specimens for prediction of adverse pathology at RP, Decipher may be useful for improved pre-operative staging. [ABSTRACT FROM AUTHOR]

Localized prostate cancer (PCa) is a clinically heterogeneous disease, which presents with variability in patient outcomes within the same risk stratification (low, intermediate or high) and even within the same Gleason scores. Genomic tools have been developed with the purpose of stratifying patients affected by this disease to help physicians personalize therapies and follow-up schemes. This review focuses on these tissue-based tools. At present, four genomic tools are commercially available: Decipher™, Oncotype DX®, Prolaris® and ProMark®. Decipher™ is a tool based on 22 genes and evaluates the risk of adverse outcomes (metastasis) after radical prostatectomy (RP). Oncotype DX® is based on 17 genes and focuses on the ability to predict outcomes (adverse pathology) in very low-low and low-intermediate PCa patients, while Prolaris® is built on a panel of 46 genes and is validated to evaluate outcomes for patients at low risk as well as patients who are affected by high risk PCa and post-RP. Finally, ProMark® is based on a multiplexed proteomics assay and predicts PCa aggressiveness in patients found with similar features to Oncotype DX®. These biomarkers can be helpful for post-biopsy decision-making in low risk patients and post-radical prostatectomy in selected risk groups. Further studies are needed to investigate the clinical benefit of these new technologies, the financial ramifications and how they should be utilized in clinics. [ABSTRACT FROM AUTHOR]

Objectives To evaluate the impact of a genomic classifier ( GC) test for predicting metastasis risk after radical prostatectomy ( RP) on urologists' decision-making about adjuvant treatment of patients with high-risk prostate cancer. Subjects and Methods Patient case history was extracted from the medical records of each of the 145 patients with pT3 disease or positive surgical margins ( PSMs) after RP treated by six high-volume urologists, from five community practices. GC results were available for 122 (84%) of these patients. US board-certified urologists ( n = 107) were invited to provide adjuvant treatment recommendations for 10 cases randomly drawn from the pool of patient case histories. For each case, the study participants were asked to make an adjuvant therapy recommendation without (clinical variables only) and with knowledge of the GC test results. Recommendations were made without knowledge of other participants' responses and the presentation of case histories was randomised to minimise recall bias. Results A total of 110 patient case histories were available for review by the study participants. The median patient age was 62 years, 71% of patients had pT3 disease and 63% had PSMs. The median (range) 5-year predicted probability of metastasis by the GC test for the cohort was 3.9 (1-33)% and the GC test classified 72% of patients as having low risk for metastasis. A total of 51 urologists consented to the study and provided 530 adjuvant treatment recommendations without, and 530 with knowledge of the GC test results. Study participants performed a mean of 130 RPs/year and 55% were from community-based practices. Without GC test result knowledge, observation was recommended for 57% ( n = 303), adjuvant radiation therapy ( ART) for 36% ( n = 193) and other treatments for 7% ( n = 34) of patients. Overall, 31% (95% CI: 27-35%) of treatment recommendations changed with knowledge of the GC test results. Of the ART recommendations without GC test result knowledge, 40% ( n = 77) changed to observation (95% CI: 33-47%) with this knowledge. Of patients recommended for observation, 13% ( n = 38 [95% CI: 9-17%]) were changed to ART with knowledge of the GC test result. Patients with low risk disease according to the GC test were recommended for observation 81% of the time ( n = 276), while of those with high risk, 65% were recommended for treatment ( n = 118; P < 0.001). Treatment intensity was strongly correlated with the GC-predicted probability of metastasis ( P < 0.001) and the GC test was the dominant risk factor driving decisions in multivariable analysis (odds ratio 8.6, 95% CI: 5.3-14.3%; P < 0.001). Conclusions Knowledge of GC test results had a direct effect on treatment strategies after surgery. Recommendations for observation increased by 20% for patients assessed by the GC test to be at low risk of metastasis, whereas recommendations for treatment increased by 16% for patients at high risk of metastasis. These results suggest that the implementation of genomic testing in clinical practice may lead to significant changes in adjuvant therapy decision-making for high-risk prostate cancer. [ABSTRACT FROM AUTHOR]

Primary prostate cancer is the most common malignancy in men but has highly variable outcomes, highlighting the need for biomarkers to determine which patients can be managed conservatively. Few large prostate oncogenome resources currently exist that combine the molecular and clinical outcome data necessary to discover prognostic biomarkers. Previously, we found an association between relapse and the pattern of DNA copy number alteration (CNA) in 168 primary tumors, raising the possibility of CNA as a prognostic biomarker. Here we examine this question by profiling an additional 104 primary prostate cancers and updating the initial 168 patient cohort with long-term clinical outcome. We find that CNA burden across the genome, defined as the percentage of the tumor genome affected by CNA, was associated with biochemical recurrence and metastasis after surgery in these two cohorts, independent of the prostate specific antigen biomarker or Gleason grade, a major existing histopathological prognostic variable in prostate cancer. Moreover, CNA burden was associated with biochemical recurrence in intermediate risk Gleason 7 prostate cancers, independent of prostate specific antigen or nomogram score. We further demonstrate that CNA burden can be measured in diagnostic needle biopsies using low input whole genome sequencing, setting the stage for studies of prognostic impact in conservatively treated cohorts. [ABSTRACT FROM AUTHOR]

Prostate cancer (CaP) is the most commonly diagnosed malignancy in males in the Western world with one in six males diagnosed in their lifetime. Current clinical prognostication groupings use pathologic Gleason score, pre-treatment prostatic-specific antigen and Union for International Cancer Control-TNM staging to place patients with localized CaP into low-, intermediate- and high-risk categories. These categories represent an increasing risk of biochemical failure and CaP-specific mortality rates, they also reflect the need for increasing treatment intensity and justification for increased side effects. In this article, we point out that 30-50% of patients will still fail image-guided radiotherapy or surgery despite the judicious use of clinical risk categories owing to interpatient heterogeneity in treatment response. To improve treatment individualization, better predictors of prognosis and radiotherapy treatment response are needed to triage patients to bespoke and intensified CaP treatment protocols. These should include the use of pre-treatment genomic tests based on DNA or RNA indices and/or assays that reflect cancer metabolism, such as hypoxia assays, to define patient-specific CaP progression and aggression. More importantly, it is argued that these novel prognostic assays could be even more useful if combined together to drive forward precision cancer medicine for localized CaP. [ABSTRACT FROM AUTHOR]

In prostate biopsies and in prostatectomy specimens, the Gleason score remains the strongest prognosticator of prostate cancer progression, in addition to serum PSA level and DRE findings, in spite of numerous potential biomarkers discovered during the last few decades. Inter- and intratumoural heterogeneity may have limited the employment of tissue biomarkers on prostate biopsies. Nevertheless, the monoclonality of morphologically heterogeneous (Gleason score 7) tumour foci would suggest that genetic biomarkers, arising early in prostate carcinogenesis, may overcome issues related to intratumoural heterogeneity. In spite of the above limitations, a few biomarkers including the proliferation marker Ki-67 and genetic markers such as c-MYC and PTEN have consistently shown their independent prognostic impact both for biochemical recurrence and for clinical outcome parameters such as metastatic disease or prostate-specific mortality. The routine application of biomarkers requiring immunostaining (e.g. Ki-67) has particularly been hindered by the lack of standardized protocols for processing and scoring, while the application of fluorescence in situ hybridization (FISH) technology is considered more labour intensive but better standardized. Future steps to enhance the uptake of prostate tissue biomarkers should be focused on prospective studies, particularly on prostate biopsy specimens, using protocols that are highly standardized for the processing and scoring of the biomarkers. A few recently developed RNA-based test signatures may provide an alternative to FISH or immunohistochemistry-based tests. [ABSTRACT FROM AUTHOR]

Background: Leukemia stem cell (LSC)-enriched genes have been shown to be highly prognostic in acute myeloid leukemia (AML). However, the prognostic value of tumor suppressor genes (TSGs) that are repressed early in LSC remains largely unknown.Methods: We compared the public available expression/methylation profiling data of LSCs with that of hematopoietic stem cells (HSCs), in order to identify potential tumor suppressor genes in LSC. The prognostic relevance of PCDH17 was analyzed on a cohort of 173 AML patients from The Cancer Genome Atlas (TCGA), and further validated in three independent cohorts (n = 339).Results: We identified protocadherin17 (PCDH17) and demonstrated that it was significantly down-regulated and hypermethylated in LSCs compared with HSCs. Our analyses of primary AML patient samples also confirmed these deregulations. Clinically, low PCDH17 expression was associated with female sex (P = 0.01), higher WBC (P < 0.0001), higher percentages of blasts in bone marrow (BM) and peripheral blood (PB) (P = 0.04 and < 0.001, respectively), presence of FLT3-internal tandem duplications (P = 0.002), mutated NPM1 (P = 0.02), and wild-type TP53 (P = 0.005). Moreover, low PCDH17 expression predicted worse overall survival (OS) in four independent cohorts as well as in the molecularly defined subgroups of AML patients. In multivariable analyses, low PCDH17 expression retained independent prognostic value for OS. Biologically, PCDH17 expression-associated gene signatures were characterized by deregulations of EMT- and Wnt pathway-related genes.Conclusions: PCDH17 gene was silenced by DNA methylation in AML. Low PCDH17 expression is associated with distinct clinical and biological features and improves risk stratification in patients with AML. [ABSTRACT FROM AUTHOR]

Background: Malignant growth and metastasis of gastrointestinal stromal tumors (GIST) occur in some patients even during the course of treatment, but their mechanisms remains poorly understand at the molecular level so far.Methods: Profiles of protein expression in gastric GIST tissues were explored using protein microarray analysis, down-regulation of SPARCL1 (secreted protein acidic and rich in cysteine-like protein 1) was validated by RT-qPCR, western blot and immunohistochemistry. The effect of specific shRNA-induced SPARCL1 downregulation on the biological traits of GIST 882 cell was investigated. We then employed a mouse xenograft model to investigate whether the low-expression of SPARCL1 impact the metastasis ability of GIST cells in vivo.Results: SPARCL1 was significantly downregulated in the gastric GIST with high-grade malignance as compared with low-grade malignance, its expression was closely correlated with tumor size, mitotic index, distant metastasis at the time of initial diagnosis and tumor progression of GIST (P < 0.05). Moreover, results of the Cox analysis showed that expression of SPARCL1 is an independent prognostic predictors for gastric GIST (P = 0.008; HR 0.157, 95% CI 0.040~ 0.612). Downregulation of SPARCL1 promoted cell migration and invasion, but did not affect proliferation, cell cycle and apoptosis of GIST 882 cells. In mouse xenograft model, GIST cells with the decreased expression of SPARCL1 presented an enhanced ability of liver metastasis (P < 0.05).Conclusions: Taken together, our present study demonstrated that SPARCL1 have a certain degree of malignancy-suppressing potential through inhibiting the metastasis of gastric GIST. [ABSTRACT FROM AUTHOR]

Prostate cancer is a common malignancy in men, but its management is fraught with controversy owing to its variable biologic and clinical behavior. Despite evidence that PSA screening reduces prostate cancer specific metastasis and death, it has not gained acceptance by various health authorities. Nevertheless, recent advances in biomarker development potentially address many of the shortcomings of routine PSA testing alone, including improved specificity for the detection of clinically significant cancer, optimized risk stratification to aid clinical management decisions, and discovery of genetic variants that may guide optimized therapy of advanced disease. [ABSTRACT FROM PUBLISHER]