A whole-blood RNA transcript-based prognostic model in men with castration-resistant prostate cancer: a prospective study

Development of a multigenomic liquid biopsy (PROSTest) for prostate cancer in whole blood

INTRODUCTION

We describe the development of a molecular assay from publicly available tumor tissue mRNA databases using machine learning and present preliminary evidence of functionality as a diagnostic and monitoring tool for prostate cancer (PCa) in whole blood.

MATERIALS AND METHODS

We assessed 1055 PCas (public microarray data sets) to identify putative mRNA biomarkers. Specificity was confirmed against 32 different solid and hematological cancers from The Cancer Genome Atlas (n = 10,990). This defined a 27-gene panel which was validated by qPCR in 50 histologically confirmed PCa surgical specimens and matched blood. An ensemble classifier (Random Forest, Support Vector Machines, XGBoost) was trained in age-matched PCas (n = 294), and in 72 controls and 64 BPH. Classifier performance was validated in two independent sets (n = 263 PCas; n = 99 controls). We assessed the panel as a postoperative disease monitor in a radical prostatectomy cohort (RPC: n = 47).

RESULTS

A PCa-specific 27-gene panel was identified. Matched blood and tumor gene expression levels were concordant (r = 0.72, p < 0.0001). The ensemble classifier ("PROSTest") was scaled 0%-100% and the industry-standard operating point of ≥50% used to define a PCa. Using this, the PROSTest exhibited an 85% sensitivity and 95% specificity for PCa versus controls. In two independent sets, the metrics were 92%-95% sensitivity and 100% specificity. In the RPCs (n = 47), PROSTest scores decreased from 72% ± 7% to 33% ± 16% (p < 0.0001, Mann-Whitney test). PROSTest was 26% ± 8% in 37 with normal postoperative PSA levels (<0.1 ng/mL). In 10 with elevated postoperative PSA, PROSTest was 60% ± 4%.

CONCLUSION

A 27-gene whole blood signature for PCa is concordant with tissue mRNA levels. Measuring blood expression provides a minimally invasive genomic tool that may facilitate prostate cancer management.

Accurate prognosis for localized prostate cancer through coherent voting networks with multi-omic and clinical data

Localized prostate cancer is a very heterogeneous disease, from both a clinical and a biological/biochemical point of view, which makes the task of producing stratifications of patients into risk classes remarkably challenging. In particular, it is important an early detection and discrimination of the indolent forms of the disease, from the aggressive ones, requiring post-surgery closer surveillance and timely treatment decisions. This work extends a recently developed supervised machine learning (ML) technique, called coherent voting networks (CVN) by incorporating a novel model-selection technique to counter the danger of model overfitting. For the challenging problem of discriminating between indolent and aggressive types of localized prostate cancer, accurate prognostic prediction of post-surgery progression-free survival with a granularity within a year is attained, improving accuracy with respect to the current state of the art. The development of novel ML techniques tailored to the problem of combining multi-omics and clinical prognostic biomarkers is a promising new line of attack for sharpening the capability to diversify and personalize cancer patient treatments. The proposed approach allows a finer post-surgery stratification of patients within the clinical high-risk category, with a potential impact on the surveillance regime and the timing of treatment decisions, complementing existing prognostic methods.

Systematic Analysis of the Prognostic Significance and Roles of the Integrin Alpha Family in Non-Small Cell Lung Cancers

INTRODUCTION

Lung cancer is one of the most common cancer malignancies and the principal cause of cancer-associated deaths worldwide. Non-small cell lung cancers (NSCLCs) account for more than 80% of all lung cancer cases. Recent studies showed that the genes of the integrin alpha (α) (ITGA) subfamily play a fundamental role in various cancers. However, little is known about the expression and roles of distinct ITGA proteins in NSCLCs.

METHODS

Gene Expression Profiling Interactive Analysis and UALCAN (University of ALabama at Birmingham CANcer) web resources and The Cancer Genome Atlas (TCGA), ONCOMINE, cBioPortal, GeneMANIA, and Tumor Immune Estimation Resource databases were used to evaluate differential expression, correlations between the expression levels of individual genes, the prognostic value of overall survival (OS) and stage, genetic alterations, protein-protein interactions, and the immune cell infiltration of ITGAs in NSCLCs. We used R (v. 4.0.3) software to conduct gene correlation, gene enrichment, and clinical correlation of RNA sequencing data of 1016 NSCLCs from TCGA. To evaluate the expression of ITGA5/8/9/L at the expression and protein levels, qRT-PCR, immunohistochemistry (IHC), and hematoxylin and eosin (H&E) were performed, respectively.

RESULTS

Upregulated levels of ITGA11 messenger RNA and downregulated levels of ITGA1/3/5/7/8/9/L/M/X were observed in the NSCLC tissues. Lower expression of ITGA5/6/8/9/10/D/L was discovered to be expressively associated with advanced tumor stage or poor patient prognosis in patients with NSCLC. A high mutation rate (44%) of the ITGA family was observed in the NSCLCs. Gene Ontology functional enrichment analyses results revealed that the differentially expressed ITGAs could be involved in roles related to extracellular matrix (ECM) organization, collagen-containing ECM cellular components, and ECM structural constituent molecular functions. The results of the Kyoto Encyclopedia of Genes and Genomes analysis revealed that ITGAs may be involved in focal adhesion, ECM-receptor interaction, and amoebiasis; the expression of ITGAs was significantly correlated with the infiltration of diverse immune cells in NSCLCs. ITGA5/8/9/L was also highly correlated with PD-L1 expression. The validation results for marker gene expression in NSCLC tissues by qRT-PCR, IHC, and H&E staining indicated that the expression of ITGA5/8/9/L decreased compared with that in normal tissues.

CONCLUSION

As potential prognostic biomarkers in NSCLCs, ITGA5/8/9/L may fulfill important roles in regulating tumor progression and immune cell infiltration.

Biomarker Development Trial of Satraplatin in Patients with Metastatic Castration–Resistant Prostate Cancer

Background

In the phase III SPARC trial, satraplatin, an oral platinum analogue, demonstrated anticancer activity in men with metastatic castration–resistant prostate cancer (mCRPC). Repeat biopsies are uncommon in mCRPC, limiting the feasibility of tissue–based biomarkers. This phase II study sought to evaluate the feasibility and utility of blood–based biomarkers to identify platinum–sensitive mCRPC.

Methods

Patients with mCRPC who had progressed on docetaxel were enrolled at a single center from 2011 to 2013. Subjects received satraplatin 80 mg/m2 by mouth daily on days 1-5 and prednisone 5 mg PO twice daily, on a 35-day cycle. Serial peripheral blood samples were collected for biomarker assessment.

Results

Thirteen docetaxel-refractory mCRPC patients were enrolled, with a median age of 69 years (range 54-77 years) and median PSA of 71.7 ng/mL (range 0.04-3057). Four of 13 patients (31%) responded to satraplatin (defined as a PSA decline of ≥30%). Responders demonstrated improved time to disease progression (206 vs. 35 days, HR 0.26, 95% CI, 0.02-0.24, P = .003). A 6-gene peripheral blood RNA signature and serum tissue inhibitor of metalloproteinase-1 (TIMP-1) levels were assessed as biomarkers, but neither was significantly associated with response to satraplatin.

Conclusion

In this small series, one-third of mCRPC patients responded to platinum–based chemotherapy. Peripheral blood biomarker measurement is feasible in mCRPC, though the biomarkers we investigated were not associated with platinum response. Other biomarkers, such as DNA damage repair mutations, should be evaluated.

Liquid biopsy-based targeted gene screening highlights tumor cell subtypes in patients with advanced prostate cancer

Prostate cancer (PCa) clinical heterogeneity underscores tumor heterogeneity, which may be best defined by cell subtypes. To test if cell subtypes contributing to progression can be assessed noninvasively, we investigated whether 14 genes representing luminal, neuroendocrine, and stem cells are detectable in whole blood RNA of patients with advanced PCa. For each gene, reverse transcription quantitative polymerase chain reaction assays were first validated using RNA from PCa cell lines, and their traceability in blood was assessed in cell spiking experiments. These were next tested in blood RNA of 40 advanced PCa cases and 40 healthy controls. Expression in controls, which was low or negative, was used to define stringent thresholds for gene overexpression in patients to account for normal variation in white blood cells. Thirty-five of 40 patients overexpressed at least one gene. Patients with more genes overexpressed had a higher risk of death (hazard ratio 1.42, range 1.12-1.77). Progression on androgen receptor inhibitors was associated with overexpression of stem (odds ratio [OR] 7.74, range 1.68-35.61) and neuroendocrine (OR 13.10, range 1.24-142.34) genes, while luminal genes were associated with taxanes (OR 2.7, range 1.07-6.82). Analyses in PCa transcriptomic datasets revealed that this gene panel was most prominent in metastases of advanced disease, with diversity among patients. Collectively, these findings support the contribution of the prostate cell subtypes to disease progression. Cell-subtype specific genes are traceable in blood RNA of patients with advanced PCa and are associated with clinically relevant end points. This opens the door to minimally invasive liquid biopsies for better management of this deadly disease.

Class IV semaphorins in disease pathogenesis

Semaphorins are a large family of secreted and/or transmembrane proteins, originally identified as proteins that function in axon guidance during neuronal development. However, semaphorins play crucial roles in other physiological and pathological processes, including immune responses, angiogenesis, maintenance of tissue homeostasis, and cancer progression. Class IV semaphorins may be present as transmembrane and soluble forms and are implicated in the pathogenesis of various diseases. This review discusses recent progress on the roles of class IV semaphorins determined by clinical and experimental pathology studies.

Quantitative proteomic profiling of hepatocellular carcinoma at different serum alpha-fetoprotein level

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Serum AFP equal to 400 ng/mL is a pivotal turning point not only in prognosis but also metabolic and invasion associated pathways.

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Adjacent noncancerous tissues are not biological normal components at protein level.

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Four druggable targets (C1QBP, HSPE1, CHDH, ITGAL) are identified as potential prognostic biomarkers in hepatocellular carcinoma.

Purpose

Hepatocellular carcinoma (HCC) is characterized by a poor long-term prognosis and high mortality rate. Serum alpha-fetoprotein (AFP) levels show great prognostic value in patients undergoing hepatectomy. This study aims to explore proteomic profiling in HCC samples based on AFP subgroups and identify potential key targets involved in HCC progression.

Methods

Twelve paired tumor and adjacent noncancerous tissue samples were collected from patients with HCC who underwent primary curative resection from January 2012 to December 2013. Clinical information was curated from four tissue microarrays to conduct survival analysis based on serum AFP levels. TMT-based quantitative proteomic analyses and bioinformatics analyses were performed to comprehensively profile molecular features. Immunohistochemistry was carried out to validate protein expression of identified targets. Kaplan-Meier survival analysis was performed to assess the overall survival and recurrence-free survival based on protein expressions.

Results

AFP (400 ng/mL) was a turning point in prognosis, metabolic- and invasion-associated pathways. The mass spectrometry analysis yielded a total of 5573 identified proteins. Annotations of 151 differentially expressed proteins in tumors and 95 proteins in paracancerous tissues (1.2-fold) showed similarities in biological processes, cellular components, molecular functions. Furthermore, differentially expressed hub proteins with five innovatively nominated druggable targets (C1QBP, HSPE1, GLUD2 for tumors and CHDH, ITGAL for paracancerous tissues), of which four (C1QBP, HSPE1, CHDH, ITGAL) targets were associated with poor overall survival (all Log-rank P < 0.05).

Conclusions

Our quantitative proteomics analyses identified four key prognostic biomarkers in HCC and provide opportunities for translational medicine and new treatment.

Characterization of Aging-Related Genes to Predict Prognosis and Evaluate the Tumor Immune Microenvironment in Malignant Melanoma

Objective. Malignant melanoma (MM) is one of the most malignant types of skin cancer and its incidence and mortality rates are increasing worldwide. Aging is well recognized as a significant risk factor for cancer. However, few studies have analyzed in depth the association between aging-related genes (AGs) and malignant melanoma prognosis with tumor immune microenvironment. Methods. Here, we downloaded 471 MM patients from The Cancer Genome Atlas (TCGA) with RNA sequence and clinicopathological data. 58 AGs from the TCGA dataset were examined using Cox regression and the LASSO assay. As a result, a gene signature for aging-related genes was created. The time-dependent ROC curve and Kaplan–Meier analysis were calculated to determine its predictive capability. Moreover, we created a nomogram for the clinicopathologic variables and the AGs gene signature to determine overall survival (OS). We also explored the association between three immune checkpoints, immune cell infiltration, and the aging-related gene signature. Results. We established an aging risk model to identify and predict the immune microenvironment in malignant melanoma. Then we developed and validated a prognosis risk model using three AGs (CSNK1E, C1QA, and SOD-2) in the GSE65904 dataset. The aging signature was positively associated with clinical and molecular characteristics and can be used as a prognostic factor for malignant melanoma. The low aging risk score was associated with a poor prognosis and indicated an immunosuppressive microenvironment. Conclusions. To summarize, we established and validated a model of aging risk based on three aging-related genes that acted as an independent prognostic predictor of overall survival. Besides, it also characterized the immune response in the malignant melanoma microenvironment and could provide a potential indicator of individualized immunotherapy in malignant melanoma.

The potential of using blood circular RNA as liquid biopsy biomarker for human diseases

Circular RNA (circRNA) is a novel class of single-stranded RNAs with a closed loop structure. The majority of circRNAs are formed by a back-splicing process in pre-mRNA splicing. Their expression is dynamically regulated and shows spatiotemporal patterns among cell types, tissues and developmental stages. CircRNAs have important biological functions in many physiological processes, and their aberrant expression is implicated in many human diseases. Due to their high stability, circRNAs are becoming promising biomarkers in many human diseases, such as cardiovascular diseases, autoimmune diseases and human cancers. In this review, we focus on the translational potential of using human blood circRNAs as liquid biopsy biomarkers for human diseases. We highlight their abundant expression, essential biological functions and significant correlations to human diseases in various components of peripheral blood, including whole blood, blood cells and extracellular vesicles. In addition, we summarize the current knowledge of blood circRNA biomarkers for disease diagnosis or prognosis.

Evaluation of an RNAseq-Based Immunogenomic Liquid Biopsy Approach in Early-Stage Prostate Cancer

The primary objective of this study is to detect biomarkers and develop models that enable the identification of clinically significant prostate cancer and to understand the biologic implications of the genes involved. Peripheral blood samples (1018 patients) were split chronologically into independent training (n = 713) and validation (n = 305) sets. Whole transcriptome RNA sequencing was performed on isolated phagocytic CD14+ and non-phagocytic CD2+ cells and their gene expression levels were used to develop predictive models that correlate to adverse pathologic features. The immune-transcriptomic model with the highest performance for predicting adverse pathology, based on a subtraction of the log-transformed expression signals of the two cell types, displayed an area under the curve (AUC) of the receiver operating characteristic of 0.70. The addition of biomarkers in combination with traditional clinical risk factors (age, serum prostate-specific antigen (PSA), PSA density, race, digital rectal examination (DRE), and family history) enhanced the AUC to 0.91 and 0.83 for the training and validation sets, respectively. The markers identified by this approach uncovered specific pathway associations relevant to (prostate) cancer biology. Increased phagocytic activity in conjunction with cancer-associated (mis-)regulation is also represented by these markers. Differential gene expression of circulating immune cells gives insight into the cellular immune response to early tumor development and immune surveillance.

Limitations of Explainability for Established Prognostic Biomarkers of Prostate Cancer

High-throughput technologies do not only provide novel means for basic biological research but also for clinical applications in hospitals. For instance, the usage of gene expression profiles as prognostic biomarkers for predicting cancer progression has found widespread interest. Aside from predicting the progression of patients, it is generally believed that such prognostic biomarkers also provide valuable information about disease mechanisms and the underlying molecular processes that are causal for a disorder. However, the latter assumption has been challenged. In this paper, we study this problem for prostate cancer. Specifically, we investigate a large number of previously published prognostic signatures of prostate cancer based on gene expression profiles and show that none of these can provide unique information about the underlying disease etiology of prostate cancer. Hence, our analysis reveals that none of the studied signatures has a sensible biological meaning. Overall, this shows that all studied prognostic signatures are merely black-box models allowing sensible predictions of prostate cancer outcome but are not capable of providing causal explanations to enhance the understanding of prostate cancer.

SEMA4D Knockdown Attenuates β-Catenin-Dependent Tumor Progression in Colorectal Cancer

Semaphorin 4D (SEMA4D), a protein originally demonstrated to regulate the immune system and axonal growth cone collapse in the developing central nervous system, is overexpressed in various human malignancies, including colorectal cancer (CRC). This investigation was undertaken to examine the effects of SEMA4D silencing on the biological properties of the CRC cell line. SW48 cells were transfected with a siRNA-targeting SEMA4D. The mRNA expression of underlying pro- and antiapoptotic proteins including Bax, Bcl-2, P53, and caspase-3, cancer stem cell (CSC) markers, epithelial-mesenchymal transition (EMT) markers, MMP-2, and MMP-9 was examined using qRT-PCR. Further, the protein expression of E-cadherin and β-catenin was confirmed by Western blot. SW48 cell migration and MMP activity were detected using scratch and zymography analysis, respectively. Finally, the apoptosis rate was assessed via the flowcytometry test. SEMA4D knock-down was associated with a considerable suppression of in vitro cell viability, EMT-related genes, CSC markers, β-catenin signaling pathway, sphere-forming, cell migration, and MMP-2 activity as well as induction of apoptosis. This study identifies the inhibitory effects of SEMA4D gene silencing on tumor progression. Thereby, this might conclude a possible alternative to cancer therapy by targeting several prominent pathways involved in cancer through SEMA4D suppression.

High Monocyte Count and Expression of S100A9 and S100A12 in Peripheral Blood Mononuclear Cells Are Associated with Poor Outcome in Patients with Metastatic Prostate Cancer

Increasing evidence indicates calcium-binding S100 protein involvement in inflammation and tumor progression. In this prospective study, we evaluated the mRNA levels of two members of this family, S100A9 and S100A12, in peripheral blood mononuclear cells (PBMCs) in a cohort of 121 prostate cancer patients using RT-PCR. Furthermore, monocyte count was determined by flow cytometry. By stratifying patients into different risk groups, according to TNM stage, Gleason score and PSA concentration at diagnosis, expression of S100A9 and S100A12 was found to be significantly higher in patients with metastases compared to patients without clinically detectable metastases. In line with this, we observed that the protein levels of S100A9 and S100A12 in plasma were higher in patients with advanced disease. Importantly, in patients with metastases at diagnosis, high monocyte count and high levels of S100A9 and S100A12 were significantly associated with short progression free survival (PFS) after androgen deprivation therapy (ADT). High monocyte count and S100A9 levels were also associated with short cancer-specific survival, with monocyte count providing independent prognostic information. These findings indicate that circulating levels of monocytes, as well as S100A9 and S100A12, could be biomarkers for metastatic prostate cancer associated with particularly poor prognosis.

Differentially Expressed Gene Patterns in Ascarid-Infected Chickens of Higher- or Lower-Performing Genotypes

Simple Summary

Nematode infections may increase mortality and welfare problems in laying hens. The two ascarid worms, Ascaridia galli and Heterakis gallinarum, are highly prevalent in laying hens kept in non-cage housing systems worldwide. The ability of a host to expel pathogens is a component of resistance to diseases. The molecular basis of differences between different host animals in their efficiency to expel worms is, however, not well understood. Therefore, we performed a detailed analysis of differentially expressed genes (DEGs) in two chicken genotypes (Lohmann Brown Plus (LB), Lohmann Dual (LD)), each with a lower or higher infection intensity level of A. galli and H. gallinarum. Our data showed significant upregulation of Guanylate Binding Protein 7 (GBP7) in LD hens. Gene ontology analysis revealed higher transcriptome activity related to “response to external stimulus” in LB hens, implying a higher stress response in this genotype. In contrast, LD hens showed higher transcriptomic expression of genes associated with a higher tolerance to infections.

Abstract

Here, we describe the first transcriptomic investigation of the peripheral blood of chickens exposed to Ascaridia galli and Heterakis gallinarum infections. We investigated differentially expressed gene (DEG) patterns in two chicken genotypes with either a higher (Lohmann Brown Plus, LB) or lower (Lohmann Dual, LD) laying performance level. The hens were experimentally coinfected with A. galli and H. gallinarum, and their worm burdens and infection parameters were determined six weeks post infection. Based on most representative infection parameters, the hens were clustered into lower- and higher-infection intensity classes. We identified a total of 78 DEGs contributing to infection-related phenotypic variation in the two genotypes. Our data showed significant upregulation of Guanylate Binding Protein 7 (GBP7) in LD hens, making it a promising candidate for tolerance to ascarid infections in chickens. Gene ontology analysis revealed higher transcriptome activity related to biological processes such as “response to external stimulus” in LB hens, implying a higher stress response in this genotype. In contrast, LD hens showed higher transcriptomic expression of genes related to ontology classes that are possibly associated with a higher tolerance to infections. These findings may help explain why lower-performing genotypes (i.e., LD) are less sensitive to infections in terms of maintaining their performance.

Whole blood GRHL2 expression as a prognostic biomarker in metastatic hormone-sensitive and castration-resistant prostate cancer

Background

As potent systemic therapies transition earlier in the prostate cancer disease course, molecular biomarkers are needed to guide optimal treatment selection for metastatic hormone-sensitive prostate cancer (mHSPC). The value of whole blood RNA to detect candidate biomarkers in mHSPC remains largely undefined.

Methods

In this cohort study, we used a previously optimised whole blood reverse transcription polymerase chain reaction assay to assess the prognostic utility [measured by seven-month undetectable prostate-specific antigen (PSA) and time to castration-resistance (TTCR)] of eight prostate cancer-associated gene transcripts in 43 mHSPC patients. Transcripts with statistically significant associations (P<0.05) were further investigated in a metastatic castration-resistant prostate cancer (mCRPC) cohort (n=119) receiving contemporary systemic therapy, exploring associations with PSA >50% response (PSA₅₀), progression-free survival (PFS) and overall survival (OS). Clinical outcomes were prospectively collected in a protected digital database. Kaplan-Meier estimates and multivariable Cox proportional-hazards models assessed associations between gene transcripts and clinical outcomes (mHSPC covariates: disease volume, docetaxel use and haemoglobin level; mCRPC covariates: prior exposure to chemotherapy or ARPIs, haemoglobin, performance status and presence of visceral disease). Follow-up was performed monthly during ARPI treatment, three-weekly during taxane chemotherapy, and three-monthly during androgen deprivation therapy (ADT) monotherapy. Serial PSA measurements were performed before each follow-up visit and repeat imaging was at the discretion of the investigator.

Results

Detection of circulating Grainyhead-like 2 (GRHL2) transcript was associated with poor outcomes in mHSPC and mCRPC patients. Detectable GRHL2 expression in mHSPC was associated with a lower rate of seven-month undetectable PSA levels (25% vs. 65%, P=0.059), and independently associated with shorter TTCR (HR 7.3, 95% CI: 1.5–36, P=0.01). In the mCRPC cohort, GRHL2 expression predicted significantly lower PSA₅₀ response rates (46% vs. 69%, P=0.01), and was independently associated with shorter PFS (HR 3.1, 95% CI: 1.8–5.2, P<0.001) and OS (HR 2.9, 95% CI: 1.6–5.1, P<0.001). Associations were most apparent in patients receiving ARPIs.

Conclusions

Detectable circulating GRHL2 was a negative prognostic biomarker in our mHSPC and mCRPC cohorts. These data support further investigation of GRHL2 as a candidate prognostic biomarker in metastatic prostate cancer, in addition to expanding efforts to better understand a putative role in therapeutic resistance to AR targeted therapies.

The Role of the Metzincin Superfamily in Prostate Cancer Progression: A Systematic-Like Review

Prostate cancer remains a leading cause of cancer-related morbidity in men. Potentially important regulators of prostate cancer progression are members of the metzincin superfamily of proteases, principally through their regulation of the extracellular matrix. It is therefore timely to review the role of the metzincin superfamily in prostate cancer and its progression to better understand their involvement in this disease. A systematic-like search strategy was conducted. Articles that investigated the roles of members of the metzincin superfamily and their key regulators in prostate cancer were included. The extracted articles were synthesized and data presented in tabular and narrative forms. Two hundred and five studies met the inclusion criteria. Of these, 138 investigated the role of the Matrix Metalloproteinase (MMP) subgroup, 34 the Membrane-Tethered Matrix Metalloproteinase (MT-MMP) subgroup, 22 the A Disintegrin and Metalloproteinase (ADAM) subgroup, 8 the A Disintegrin and Metalloproteinase with Thrombospondin Motifs (ADAMTS) subgroup and 53 the Tissue Inhibitor of Metalloproteinases (TIMP) family of regulators, noting that several studies investigated multiple family members. There was clear evidence that specific members of the metzincin superfamily are involved in prostate cancer progression, which can be either in a positive or negative manner. However, further understanding of their mechanisms of action and how they may be used as prognostic indicators or molecular targets is required.

Identification of IL10RA by Weighted Correlation Network Analysis and in vitro Validation of Its Association With Prognosis of Metastatic Melanoma

Skin cutaneous melanoma (SKCM) is the major cause of death for skin cancer patients, its high metastasis often leads to poor prognosis of patients with malignant melanoma. However, the molecular mechanisms underlying metastatic melanoma remain to be elucidated. In this study we aim to identify and validate prognostic biomarkers associated with metastatic melanoma. We first construct a co-expression network using large-scale public gene expression profiles from GEO, from which candidate genes are screened out using weighted gene co-expression network analysis (WGCNA). A total of eight modules are established via the average linkage hierarchical clustering, and 111 hub genes are identified from the clinically significant modules. Next, two other datasets from GEO and TCGA are used for further screening of biomarker genes related to prognosis of metastatic melanoma, and identified 11 key genes via survival analysis. We find that IL10RA has the highest correlation with clinically important modules among all identified biomarker genes. Further in vitro biochemical experiments, including CCK8 assays, wound-healing assays and transwell assays, have verified that IL10RA can significantly inhibit the proliferation, migration and invasion of melanoma cells. Furthermore, gene set enrichment analysis shows that PI3K-AKT signaling pathway is significantly enriched in metastatic melanoma with highly expressed IL10RA, indicating that IL10RA mediates in metastatic melanoma via PI3K-AKT pathway.

The Identification of Plasma Exosomal miR-423-3p as a Potential Predictive Biomarker for Prostate Cancer Castration-Resistance Development by Plasma Exosomal miRNA Sequencing

Castration-resistant prostate cancer (CRPC) is the major cause of death from prostate cancer. Biomarkers to improve early detection and prediction of CRPC especially using non-invasive liquid biopsies could improve outcomes. Therefore, we investigated the plasma exosomal miRNAs associated with CRPC and their potential for development into non-invasive early detection biomarkers for resistance to treatment. RNA-sequencing, which generated approximately five million reads per patient, was performed to identify differentially expressed plasma exosomal miRNAs in 24 treatment-naive prostate cancer and 24 CRPC patients. RT-qPCR was used to confirm the differential expressions of six exosomal miRNAs, miR-423-3p, miR-320a, miR-99a-5p, miR-320d, miR-320b, and miR-150-5p (p = 7.3 × 10^-8, 0.0020, 0.018, 0.0028, 0.0013, and 0.0058, respectively) firstly in a validation cohort of 108 treatment-naive prostate cancer and 42 CRPC patients. The most significant differentially expressed miRNA, miR-423-3p, was shown to be associated with CRPC with area under the ROC curve (AUC) = 0.784. Combining miR-423-3p with prostate-specific antigen (PSA) enhanced the prediction of CRPC (AUC = 0.908). A separate research center validation with 30 treatment-naive and 30 CRPC patients also confirmed the differential expression of miR-423-3p (p = 0.016). Finally, plasma exosomal miR-423-3p expression in CRPC patients was compared to 36 non-CRPC patients under androgen depletion therapy, which showed significantly higher expression in CRPC than treated non-CRPC patients (p < 0.0001) with AUC = 0.879 to predict CRPC with no difference between treatment-naive and treated non-CRPC patients. Therefore, our findings demonstrate that a number of plasma exosomal miRNAs are associated with CRPC and miR-423-3p may serve as a biomarker for early detection/prediction of castration-resistance.

Molecular tracing of prostate cancer lethality

Prostate cancer is diagnosed mostly in men over the age of 50 years, and has favorable 5-year survival rates due to early cancer detection and availability of curative surgical management. However, progression to metastasis and emergence of therapeutic resistance are responsible for the majority of prostate cancer mortalities. Recent advancement in sequencing technologies and computational capabilities have improved the ability to organize and analyze large data, thus enabling the identification of novel biomarkers for survival, metastatic progression and patient prognosis. Large-scale sequencing studies have also uncovered genetic and epigenetic signatures associated with prostate cancer molecular subtypes, supporting the development of personalized targeted-therapies. However, the current state of mainstream prostate cancer management does not take full advantage of the personalized diagnostic and treatment modalities available. This review focuses on interrogating biomarkers of prostate cancer progression, including gene signatures that correspond to the acquisition of tumor lethality and those of predictive and prognostic value in progression to advanced disease, and suggest how we can use our knowledge of biomarkers and molecular subtypes to improve patient treatment and survival outcomes.

Sparse relative risk regression models

Clinical studies where patients are routinely screened for many genomic features are becoming more routine. In principle, this holds the promise of being able to find genomic signatures for a particular disease. In particular, cancer survival is thought to be closely linked to the genomic constitution of the tumor. Discovering such signatures will be useful in the diagnosis of the patient, may be used for treatment decisions and, perhaps, even the development of new treatments. However, genomic data are typically noisy and high-dimensional, not rarely outstripping the number of patients included in the study. Regularized survival models have been proposed to deal with such scenarios. These methods typically induce sparsity by means of a coincidental match of the geometry of the convex likelihood and a (near) non-convex regularizer. The disadvantages of such methods are that they are typically non-invariant to scale changes of the covariates, they struggle with highly correlated covariates, and they have a practical problem of determining the amount of regularization. In this article, we propose an extension of the differential geometric least angle regression method for sparse inference in relative risk regression models. A software implementation of our method is available on github (https://github.com/LuigiAugugliaro/dgcox).

Cancer transcriptomic profiling from rapidly enriched circulating tumor cells

Transcriptomic profiling of metastatic cancer can illuminate mechanisms of progression and lead to new therapies, but standard biopsy is invasive and reflects only a single metastatic site. In contrast, circulating tumor cell (CTC) profiling is noninvasive and repeatable, reflecting the dynamic and systemic nature of advanced disease. To date, transcriptomic profiling of CTCs has not delivered on its full potential, because white blood cells (WBCs) vastly outnumber CTCs. Current profiling strategies either lack cancer sensitivity and specificity or require specialized CTC capture protocols that are not readily scalable to large patient cohorts. Here, we describe a new strategy for rapid CTC enrichment and transcriptomic profiling using commercially available WBC depletion, microfluidic enrichment and RNA sequencing. When applied to blood samples from patients with advanced prostate cancer (PC), transcriptomes from enriched samples cluster with cancer positive controls and previously undetectable prostate-specific transcripts become readily measurable. Gene set enrichment analysis reveals multiple significantly enriched signaling pathways associated with PC, as well as novel pathways that merit further study. This accessible and scalable approach yields cancer-specific transcriptomic data and can be applied repeatedly and noninvasively in large cancer patient cohorts to discover new therapeutic targets in advanced disease.

Genitourinary Tumors: Update on Molecular Biomarkers for Diagnosis, Prognosis and Prediction of Response to Therapy

BACKGROUND

Research of biomarkers in genitourinary tumors goes along with the development of complex emerging techniques ranging from next generation sequencing platforms, applied to archival pathology specimens, cytological samples, liquid biopsies, and to patient-derived tumor models.

METHODS

This contribution is an update on molecular biomarkers for diagnosis, prognosis and prediction of response to therapy in genitourinary tumors. The following major topics are dealt with: Immunological biomarkers, including the microbiome, and their potential role and caveats in renal cell carcinoma, bladder and prostate cancers and testicular germ cell tumors; Tissue biomarkers for imaging and therapy, with emphasis on Prostate-specific membrane antigen in prostate cancer; Liquid biomarkers in prostate cancer, including circulating tumor cell isolation and characterization in renal cell carcinoma, bladder cancer with emphasis on biomarkers detectable in the urine and testicular germ cell tumors; and Biomarkers and economic sustainability.

CONCLUSION

The identification of effective biomarkers has become a major focus in cancer research, mainly due to the necessity of selecting potentially responsive patients in order to improve their outcomes, as well as to reduce the toxicity and costs related to ineffective treatments.

Circulating Tumor Cell Enumeration and Characterization in Metastatic Castration-Resistant Prostate Cancer Patients Treated with Cabazitaxel

(1) Background: Markers identifying which patients with metastatic, castration-resistant prostate cancer (mCRPC) will benefit from cabazitaxel therapy are currently lacking. Therefore, the aim of this study was to identify markers associated with outcome to cabazitaxel therapy based on counts and gene expression profiles of circulating tumor cells (CTCs). (2) Methods: From 120 mCRPC patients, CellSearch enriched CTCs were obtained at baseline and after 6 weeks of cabazitaxel therapy. Furthermore, 91 genes associated with prostate cancer were measured in mRNA of these CTCs. (3) Results: In 114 mCRPC patients with an evaluable CTC count, the CTC count was independently associated with poor progression-free survival (PFS) and overall survival (OS) in multivariable analysis with other commonly used variables associated with outcome in mCRPC (age, prostate specific antigen (PSA), alkaline phosphatase, lactate dehydrogenase (LDH), albumin, hemoglobin), together with alkaline phosphatase and hemoglobin. A five-gene expression profile was generated to predict for outcome to cabazitaxel therapy. However, even though this signature was associated with OS in univariate analysis, this was not the case in the multivariate analysis for OS nor for PFS. (4) Conclusion: The established five-gene expression profile in CTCs was not independently associated with PFS nor OS. However, along with alkaline phosphatase and hemoglobin, CTC-count is independently associated with PFS and OS in mCRPC patients who are treated with cabazitaxel.

Comprehensive analysis of prognostic immune-related genes in the tumor microenvironment of cutaneous melanoma

Cutaneous malignant melanoma (hereafter called melanoma) is one of the most aggressive cancers with increasing incidence and mortality rates worldwide. In this study, we performed a systematic investigation of the tumor microenvironmental and genetic factors associated with melanoma to identify prognostic biomarkers for melanoma. We calculated the immune and stromal scores of melanoma patients from the Cancer Genome Atlas (TCGA) using the ESTIMATE algorithm and found that they were closely associated with patients' prognosis. Then the differentially expressed genes were obtained based on the immune and stromal scores, and prognostic immune-related genes further identified. Functional analysis and the protein-protein interaction network further revealed that these genes enriched in many immune-related biological processes. In addition, the abundance of six infiltrating immune cells was analyzed using prognostic immune-related genes by TIMER algorithm. The unsupervised clustering analysis using immune-cell proportions revealed eight clusters with distinct survival patterns, suggesting that dendritic cells were most abundant in the microenvironment and CD8⁺ T cells and neutrophils were significantly related to patients' prognosis. Finally, we validated these genes in three independent cohorts from the Gene Expression Omnibus database. In conclusion, this study comprehensively analyzed the tumor microenvironment and identified prognostic immune-related biomarkers for melanoma.

Current status of liquid biopsies for the detection and management of prostate cancer

In recent years, new therapeutic options have become available for prostate cancer (PC) patients, generating an urgent need for better biomarkers to guide the choice of therapy and monitor treatment response. Liquid biopsies, including circulating tumor cells (CTCs), circulating nucleic acids, and exosomes, have been developed as minimally invasive assays allowing oncologists to monitor PC patients with real-time cellular or molecular information. While CTC counts remain the most extensively validated prognostic biomarker to monitor treatment response, recent advances demonstrate that CTC morphology and androgen receptor characterization can provide additional information to guide the choice of treatment. Characterization of cell-free DNA (cfDNA) is another rapidly emerging field with novel technologies capable of monitoring the evolution of treatment relevant alterations such as those in DNA damage repair genes for poly (ADP-ribose) polymerase (PARP) inhibition. In addition, several new liquid biopsy fields are emerging, including the characterization of heterogeneity, CTC RNA sequencing, the culture and xenografting of CTCs, and the characterization of extracellular vesicles (EVs) and circulating microRNAs. This review describes the clinical utilization of liquid biopsies in the management of PC patients and emerging liquid biopsy technologies with the potential to advance personalized cancer therapy.

Epigenetic Control of Gene Expression in the Normal and Malignant Human Prostate: A Rapid Response Which Promotes Therapeutic Resistance

A successful prostate cancer must be capable of changing its phenotype in response to a variety of microenvironmental influences, such as adaptation to treatment or successful proliferation at a particular metastatic site. New cell phenotypes emerge by selection from the large, genotypically heterogeneous pool of candidate cells present within any tumor mass, including a distinct stem cell-like population. In such a multicellular model of human prostate cancer, flexible responses are primarily governed not only by de novo mutations but appear to be dominated by a combination of epigenetic controls, whose application results in treatment resistance and tumor relapse. Detailed studies of these individual cell populations have resulted in an epigenetic model for epithelial cell differentiation, which is also instructive in explaining the reported high and inevitable relapse rates of human prostate cancers to a multitude of treatment types.

Prognostic Utility of a Whole-blood Androgen Receptor-based Gene Signature in Metastatic Castration-resistant Prostate Cancer

BACKGROUND

The treatment paradigm for metastatic castration-resistant prostate cancer (mCRPC) has evolved significantly in recent years. Identifying predictive and/or prognostic biomarkers in the context of this rapidly expanding therapeutic armamentarium remains a pressing and unmet clinical need.

OBJECTIVE

To develop a prognostic whole-blood gene signature for mCRPC patients.

DESIGN, SETTING, AND PARTICIPANTS

As part of an ongoing prospective, multicentre biomarker research study (Australian Prostate Biomarker Alliance), we enrolled 115 mCRPC patients commencing chemotherapy (n = 34) or androgen receptor (AR) pathway inhibitors therapy (n = 81) and obtained pretreatment whole-blood samples in PAXgene RNA tubes. Gene expression was assessed using reverse transcription-polymerase chain reaction.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Gene transcripts correlating with overall survival (OS) at p < 0.10 in univariate Cox regression models were incorporated into a multigene signature. Kaplan-Meier survival estimates and multivariate analyses were used to assess association with clinical outcomes. Prognostic strength of the signature was estimated using a concordance probability estimate (CPE).

RESULTS AND LIMITATIONS

Based on univariate analysis for OS, the following genes were incorporated into a multigene signature: AR splice variant 7 (AR-V7), and three androgen-regulated genes: GRHL2, HOXB13, and FOXA1. The number of positive transcripts clearly stratified survival outcomes (median OS: not reached vs 24.8 mo vs 16.2 mo for 0, 1, and ≥2 transcripts, respectively; p = 0.0052). Notably, this multigene signature retained prognostic significance on multivariable analysis (hazard ratio, 2.1; 95% confidence interval, 1.1-4.0; p = 0.019). Moreover, CPE for this model was 0.78, indicating strong discriminative capacity. Limitations include short follow-up time.

CONCLUSIONS

Our data demonstrate the prognostic utility of a novel whole-blood AR-based signature in mCRPC patients commencing contemporary systemic therapies. Our pragmatic assay requires minimal processing, can be performed in most hospital laboratories, and could represent a key prognostic tool for risk stratification in mCRPC.

PATIENT SUMMARY

We found that expression of certain genes associated with the androgen receptor could help determine how long men with advanced prostate cancer survive after starting modern drug therapies.

Expression of SLC5A5 in Circulating Tumor Cells May Distinguish Follicular Thyroid Carcinomas from Adenomas: Implications for Blood-Based Preoperative Diagnosis

Preoperative diagnosis of thyroid nodules reduces unnecessary surgery. Circulating tumor cells (CTCs) may contain information of primary tumor(s). We asked whether the peripheral blood expression of genes specific for circulating tumor cells (CTCs) differentiates benign thyroid nodules from malignant nodules. Peripheral blood mononuclear cells from thyroid nodule patients (n = 20) were isolated preoperatively and the expression of seven CTC-associated genes was measured in patients with thyroid nodule(s) (n = 20). Among the tested genes, the expression of SLC5A5 and LGALS3 were validated in a larger number of patients (n = 64) and our results show that SLC5A5 expression differentiated follicular adenomas from follicular carcinomas (area under the curve (AUC) = 0.831). The expression of SLC5A5 in CTCs may preoperatively distinguish thyroid follicular adenomas from follicular carcinomas.

Association between prognosis and SEMA4D/Plexin-B1 expression in various malignancies: A meta-analysis

INTRODUCTION

SEMA4D and its high affinity receptor Plexin-B1 showed a promising prognosis prediction for carcinoma patients in recent studies, we performed a meta-analysis to evaluate the prognostic role of them in various malignancies.

METHODS

A systematic literature search was performed in PubMed, Embase, Web of Science, and CNKI from inception till July 2017. Eligible studies were identified by different reviewers. Hazard ratios (HRs)/related ratios (RRs) and their corresponding 95% confidence intervals (CIs) were extracted to investigate the relevance between malignancies prognosis and SEMA4D/Plexin-B1.

RESULTS

Around 2638 patients from 14 studies were included in this meta-analysis. High expression of SEMA4D was significantly associated with overall survival (OS) and disease-free survival/progression-free survival/recurrence-free survival (DFS/PFS/RFS) in tumors (respectively, HRos = 2.05, 95%CI: 1.68-2.50, P < .001; HRdfs/pfs/rfs = 1.59, 95%CI = 1.27-1.98, P < .001). However, the relationship between SEMA4D expression and prognosis of breast cancer patients was failed to find (HR = 0.76, 95%CI = 0.32-1.82, P = .539). Plexin-B1 level showed a significant positive correlation both with OS and DFS of Caucasian breast cancer patients (respectively, HRos = 0.56, 95%CI: 0.39-0.79, P = .001; HRdfs = 0.68, 95%CI = 0.51-0.90, P = .008) CONCLUSIONS:: SEMA4D could be a prospective biomarker for prognostic prediction of various malignancies except breast cancer. For Caucasian breast cancer patients, SEMA4D's high affinity receptor Plexin-B1 showed a significant positive correlation with survival.

Association of genetic variation of the six gene prognostic model for castration-resistant prostate cancer with survival

BACKGROUND

We previously identified a blood RNA transcript-based model consisting of six immune or inflammatory response genes (ABL2, SEMA4D, ITGAL, C1QA, TIMP1, and CDKN1A) that was prognostic for survival in cohorts of men with castration-resistant prostate cancer (CRPC). We investigated whether inherited variation in these six genes was associated with overall survival (OS) in men with CRPC.

METHODS

The test cohort comprised 600 patients diagnosed with CRPC between 1996 and 2011 at Dana-Farber Cancer Institute. Genotyping of 66 tagging single nucleotide polymorphisms (SNPs) spanning the six genes was performed on blood derived DNAs. For the top four SNPs (P < 0.05), validation was conducted in an independent cohort of 223 men diagnosed with CRPC between 2000 and 2014. Multivariable Cox regression adjusting for known prognostic factors estimated hazard ratios (HR) and 95% confidence intervals (CI) of the association of genetic variants with OS.

RESULTS

Two thirds of patients in both cohorts had metastases at CRPC diagnosis. Median OS from CRPC diagnosis was 3.6 (95%CI 3.3-4.0) years in the test cohort and 4.6 (95%CI 3.8-5.2) years in the validation cohort. Fifty-nine SNPs in Hardy-Weinberg equilibrium were analyzed. The major alleles of rs1318056 and rs1490311 in ABL2, and the minor alleles of rs2073917 and rs3764322 in ITGAL were associated with increased risk of death in the test cohort (adjusted-HRs 1.27-1.39; adjusted-p <0.05; false discovery rate <0.35). In the validation cohort, a similar association with OS was observed for rs1318056 in ABL2 (adjusted-HR 1.44; 95%CI 0.89-2.34) and rs2073917 in ITGAL (adjusted-HR 1.41; 95%CI 0.82-2.42). The associations did not reach statistical significance most likely due to the small sample size of the validation cohort (adjusted-p = 0.142 and 0.209, respectively). Additional eQTL analysis indicated that minor alleles of rs1318056 and rs1490311 in ABL2 are associated with a lower ABL2 expression in blood.

CONCLUSIONS

These findings corroborate our initial work on the RNA expression of genes involved in immunity and inflammation from blood and clinical outcome and suggest that germline polymorphisms in ABL2 and ITGAL may be associated with the risk of death in men with CRPC. Further studies are needed to validate these findings and to explore their functional mechanisms.

Prognostic models for predicting overall survival in metastatic castration-resistant prostate cancer: a systematic review

PURPOSE

Prognostic models are developed to estimate the probability of the occurrence of future outcomes incorporating multiple variables. We aimed to identify and summarize existing multivariable prognostic models developed for predicting overall survival in patients with metastatic castration-resistant prostate cancer (mCRPC).

METHODS

The protocol was prospectively registered (CRD42017064448). We systematically searched Medline and reference lists up to May 2018 and included experimental and observational studies, which developed and/or internally validated prognostic models for mCRPC patients and were further externally validated or updated. The outcome of interest was overall survival. Two authors independently performed literature screening and quality assessment.

RESULTS

We included 12 studies that developed models including 8750 patients aged 42-95 years. Models included 4-11 predictor variables, mostly hemoglobin, baseline PSA, alkaline phosphatase, performance status, and lactate dehydrogenase. Very few incorporated Gleason score. Two models included predictors related to docetaxel and mitoxantrone treatments. Model performance after internal validation showed similar discrimination power ranging from 0.62 to 0.73. Overall survival models were mainly constructed as nomograms or risk groups/score. Two models obtained an overall judgment of low risk of bias.

CONCLUSIONS

Most models were not suitable for clinical use due to methodological shortcomings and lack of external validation. Further external validation and/or model updating is required to increase prognostic accuracy and clinical applicability prior to their incorporation in clinical practice as a useful tool in patient management.

Recent Advances in Liquid Biopsy in Patients With Castration Resistant Prostate Cancer

Management of localized and advanced prostate cancer benefits from several therapeutic options with a surprising improvement in terms of clinical outcome. The selection of patients more likely to benefit from a specific approach still remains a key issue as well as the early identification of patients with aggressive disease which could benefit from a more aggressive treatment strategy. The lack of reliable bio-marker in castration resistant setting able to monitor response to treatment and early inform about tumor progression is an emerging issue. Accordingly, circulating DNA and circulating tumor cells appears a promising and attractive approach despite to date practical applications of these techniques are few and not validated. The aim of this review of the literature is to explore current knowledge on liquid biopsy in prostate cancer focusing on possible future applications.

A whole-blood RNA transcript-based gene signature is associated with the development of CTLA-4 blockade-related diarrhea in patients with advanced melanoma treated with the checkpoint inhibitor tremelimumab

BACKGROUND

Anti-CTLA-4 immune checkpoint blockade is associated with immune-related adverse events (irAEs). Grade 3-4 diarrhea/colitis is the most frequent irAE requiring treatment discontinuation. Predicting high-risk diarrhea/colitis patients may facilitate early intervention, limit irAE severity, and extend treatment duration. No biomarkers currently predict for anti-CTLA-4 immunotherapy related severe diarrhea.

METHODS

Whole-blood was collected pre-treatment and 30 days post-treatment initiation from patients with stage III or IV unresectable melanoma who received 15 mg/kg tremelimumab at 90 day intervals in two clinical trials. The discovery dataset was a phase II study that enrolled 150 patients between December 2005 and November 2006. The validation dataset was a phase III study that enrolled 210 patients between March 2006 and July 2007. RT-PCR was performed for 169 genes associated with inflammation, immunity, CTLA-4 pathway and melanoma. Gene expression was correlated with grade 0-1 versus grade 2-4 diarrhea/colitis development.

RESULTS

Pre-treatment blood obtained from the discovery dataset (N = 150) revealed no gene predictive of diarrhea/colitis development (p < 0.05). A 16-gene signature (CARD12, CCL3, CCR3, CXCL1, F5, FAM210B, GADD45A, IL18bp, IL2RA, IL5, IL8, MMP9, PTGS2, SOCS3, TLR9 and UBE2C) was identified from 30 days post-tremelimumab initiation blood that discriminated patients developing grade 0-1 from grade 2-4 diarrhea/colitis. The 16-gene signature demonstrated an AUC of 0.814 (95% CI 0.743 to 0.873, p < 0.0001), sensitivity 42.9%, specificity 99.2%, positive predictive value (PPV) 90.0%, and negative predictive value (NPV) 91.4%. In the validation dataset (N = 210), the 16-gene signature discriminated patients developing grade 0-1 from grade 2-4 diarrhea/colitis with an AUC 0.785 (95% CI 0.723 to 0.838, p < 0.0001), sensitivity 57.1%, specificity 84.4%, PPV 57.1% and NPV 84.4%.

CONCLUSION

This study identifies a whole-blood mRNA signature predictive of a clinically relevant irAE in patients treated with immune checkpoint blockade. We hypothesize that immune system modulation induced by immune checkpoint blockade results in peripheral blood gene expression changes that are detectable prior to clinical onset of severe diarrhea. Assessment of peripheral blood gene expression changes in patients receiving anti-PD-1/PD-L1 immunotherapy, or combination anti-CTLA4 and anti-PD-1/PD-L1 immunotherapy, is warranted to provide early on-treatment mechanistic insights and identify clinically relevant predictive biomarkers.

TRIAL REGISTRATION

Clinicaltrials.gov , NCT00257205 , registered 22 November 2005.

Peripheral monocyte count: an independent diagnostic and prognostic biomarker for prostate cancer - a large Chinese cohort study

Increasing evidence indicates that inflammation may play important roles in tumorigenesis and progression, and an elevated peripheral monocyte count predicts a poor prognosis in various types of malignancies. Here, we evaluate the roles of peripheral monocyte count in the diagnosis and prognosis for prostate cancer in Chinese patients. A total of 1107 consecutive patients who had undergone prostate biopsy and 290 prostate cancer patients receiving androgen deprivation therapy as first-line therapy were retrospectively analyzed. The parameters were measured at the time of diagnosis. Univariate and multivariate logistic regression analyses were performed to identify the independent predictors of a positive biopsy. Patients were categorized in two groups using a cutoff point of 0.425 × 10⁹ l⁻¹ as calculated by the receiver-operating curve analysis for prognosis. Univariate and multivariate Cox regression analyses were performed to determine the associations of monocyte count with progression-free survival, cancer-specific survival, and overall survival. Multivariate logistic regression analyses showed that monocyte count, age, prostate-specific antigen (PSA), free/total PSA, and prostate volume were independent predictors for prostate cancer. Multivariate Cox regression analyses identified an elevated monocyte count as an independent prognostic factor for worse cancer-specific survival (hazard ratio = 2.244, P < 0.05) and overall survival (hazard ratio = 1.995, P < 0.05), but not progression-free survival (P = 0.117). Our results indicated that an elevated monocyte count was an independent diagnostic biomarker for prostate cancer, and pretreatment peripheral monocyte count might play a significant role in the prognosis of prostate cancer patients treated with androgen deprivation therapy.

Development and Application of Liquid Biopsies in Metastatic Prostate Cancer

PURPOSE OF REVIEW

Metastatic prostate cancer is a lethal and highly heterogeneous malignancy, associated with a broad spectrum of potentially actionable molecular alterations. In the past decade, disease profiling has expanded to include not only traditional tumor tissue, but also liquid biopsies of cells and genetic material circulating in the blood. These liquid biopsies offer a minimally invasive, repeatable source of tumor material for longitudinal disease profiling but also raise new technical and biological challenges. Here we will summarize recent advances in liquid biopsy strategies and the role they have played in biomarker development and disease management.

RECENT FINDINGS

Technologies for analysis of circulating tumor cells (CTCs) continue to evolve rapidly, and the latest high content scanning platforms have underscored the phenotypic heterogeneity of CTC populations. Among liquid biopsies, CTC enumeration remains the most extensively validated prognostic marker to date, but other clinically relevant phenotypes like androgen receptor (AR) localization or presence of AR-V7 splice variant are important new predictors of therapy response. Serial genomic profiling of CTCs or circulating tumor DNA (ctDNA) is helping to define primary and acquired resistance mechanisms and helping to guide patient selection for targeted therapies such as poly(adenosine diphosphate [ADP] ribose) polymerase (PARP) inhibition. The era of liquid biopsy-based biomarkers has arrived, driven by powerful new enrichment and analysis techniques. As new blood-based markers are identified, their biological significance as disease drivers must be elucidated to advance new therapeutic strategies, and their clinical impact must be translated through assay standardization, followed by analytical and clinical validation. These efforts, already ongoing on multiple fronts, constitute the critical steps toward more effective precision management of advanced prostate cancer.

Blood Transcript Profiling for the Detection of Neuroendocrine Tumors: Results of a Large Independent Validation Study

Background: Available neuroendocrine biomarkers are considered to have insufficient accuracy to discriminate patients with gastro-entero-pancreatic neuroendocrine tumors (GEP-NETs) from healthy controls. Recent studies have demonstrated a potential role for circulating neuroendocrine specific transcripts analysis-the NETest-as a more accurate biomarker for NETs compared to available biomarkers. This study was initiated to independently validate the discriminative value of the NETest as well as the association between tumor characteristics and NETest score. Methods: Whole blood samples from 140 consecutive GEP-NET patients and 113 healthy volunteers were collected. Laboratory investigators were blinded to the origin of the samples. NETest results and chromogranin A (CgA) levels were compared with clinical information including radiological imaging to evaluate the association with tumor characteristics. Results: The median NETest score in NET patients was 33 vs. 13% in controls (p < 0.0001). The NETest did not correlate with age, gender, tumor location, grade, load, or stage. Using the cut-off of 14% NETest sensitivity and specificity were 93 and 56%, respectively, with an AUC of 0.87. The optimal cut-off for the NETest in our population was 20%, with sensitivity 89% and specificity 72%. The upper limit of normal for CgA was established as 100 μg/l. Sensitivity and specificity of CgA were 56 and 83% with an AUC of 0.76. CgA correlated with age (rs = 0.388, p < 0.001) and tumor load (rs = 0.458, p < 0.001). Conclusions: The low specificity of the NETest precludes its use as a screening test for GEP-NETs. The superior sensitivity of the NETest over CgA (93 vs. 56%; p < 0.001), irrespective of the stage of the disease, emphasize its potential as a marker of disease presence in follow up as well as an indicator for residual disease after surgery.

Liquid Biopsy in Prostate Cancer: Circulating Tumor Cells and Beyond

Prostate cancer is a common malignancy impacting countless men without curative options in the advanced state. Numerous therapies have been introduced in recent years improving survival and symptom control, yet optimal methods for predicting or monitoring response have not been developed. In the era of precision medicine, characterization of individual cancers is necessary to inform treatment decisions. Liquid biopsies, through evaluation of various blood-based analytes, provide a method of patient evaluation with potential applications in virtually all disease states. In this review, we will describe current approaches with a particular focus on demonstrated clinical utility in the evaluation and management of prostate cancer.

The Role of Semaphorin 4D in Bone Remodeling and Cancer Metastasis

Semaphorin 4D (Sema4D; CD100) is a transmembrane homodimer 150-kDa glycoprotein member of the Semaphorin family. Semaphorins were first identified as chemorepellants that guide neural axon growth. Sema4D also possesses immune regulatory activity. Recent data suggest other Sema4D functions: inactivation of platelets, stimulation of angiogenesis, and regulation of bone formation. Sema4D is a coupling factor expressed on osteoclasts that inhibits osteoblast differentiation. Blocking Sema4D may, therefore, be anabolic for bone. Sema4D and its receptor Plexin-B1 are commonly dysregulated in cancers, suggesting roles in cancer progression, invasion, tumor angiogenesis, and skeletal metastasis. This review focuses on Sema4D in bone and cancer biology and the molecular pathways involved, particularly Sema4D-Plexin-B1 signaling crosstalk between cancer cells and the bone marrow microenvironment-pertinent areas since a humanized Sema4D-neutralizing antibody is now in early phase clinical trials in cancers and neurological disorders.

Whole Blood mRNA Expression-Based Prognosis of Metastatic Renal Cell Carcinoma

The Memorial Sloan Kettering Cancer Center (MSKCC) prognostic score is based on clinical parameters. We analyzed whole blood mRNA expression in metastatic clear cell renal cell carcinoma (mCCRCC) patients and compared it to the MSKCC score for predicting overall survival. In a discovery set of 19 patients with mRCC, we performed whole transcriptome RNA sequencing and selected eighteen candidate genes for further evaluation based on associations with overall survival and statistical significance. In an independent validation of set of 47 patients with mCCRCC, transcript expression of the 18 candidate genes were quantified using a customized NanoString probeset. Cox regression multivariate analysis confirmed that two of the candidate genes were significantly associated with overall survival. Higher expression of BAG1 [hazard ratio (HR) of 0.14, p < 0.0001, 95% confidence interval (CI) 0.04–0.36] and NOP56 (HR 0.13, p < 0.0001, 95% CI 0.05–0.34) were associated with better prognosis. A prognostic model incorporating expression of BAG1 and NOP56 into the MSKCC score improved prognostication significantly over a model using the MSKCC prognostic score only (p < 0.0001). Prognostic value of using whole blood mRNA gene profiling in mCCRCC is feasible and should be prospectively confirmed in larger studies.

The evolution of chemotherapy for the treatment of prostate cancer

Chemotherapy has been explored as a treatment option for metastatic prostate cancer since the early 1980s. Docetaxel, a taxane chemotherapeutic, was approved for the treatment of men with metastatic castration-resistant prostate cancer in 2004, and is now standard of care for late stage disease. Recent clinical studies demonstrated that patients with metastatic castration-sensitive disease, and possibly those with high-risk localized prostate cancer also benefit from docetaxel administration, expanding the role of chemotherapy in the prostate cancer treatment landscape. Another taxane, cabazitaxel, is approved for post-docetaxel metastatic castration-resistant prostate cancer. Taxanes and other chemotherapeutics, such as carboplatin, are now being tested in combination regimens. This review presents an outline of recent and ongoing clinical studies assessing docetaxel and its derivative cabazitaxel at different stages of the disease, and in various combinations with other agents. We summarize current knowledge on biomarkers predictive of response to chemotherapy, which may in future be used to guide individualized treatment decisions.

Probing the prostate tumour microenvironment I: impact of glucose deprivation on a cell model of prostate cancer progression

In the developed world, prostate cancer is the most common cancer diagnosis in men. Although prostate cancer initially presents as a non life-threatening disease, 90% of patients will develop castration resistant prostate cancer (CRPC), which preludes distant metastasis and is largely accountable for prostate cancer associated deaths. This is because as yet, there are no viable molecular therapeutic targets for effective treatment of CRPC. It is now widely accepted that cancer cells can alter their metabolic profile during the course of tumourgenesis and metastasis such that they are able to survive in oxygen and nutrient-poor environments. This work was aimed towards gaining greater mechanistic understanding of how such 'stresses' in the tumour microenvironment impact on both androgen sensitive (LNCaP) and androgen independent (LNCaP-abl and LNCaP-abl-Hof) prostate cancer cell lines. Here we have applied technically robust and reproducible label-free liquid chromatography mass spectrometry analysis for comprehensive proteomic profiling of prostate cancer cell lines under nutrient deficient (low glucose) conditions. This led to the identification of approximately 4,000 proteins - one of the largest protein datasets for prostate cancer cell lines established to date. The biological and clinical significance of proteins showing a significant change in expression as result of low glucose conditions was established. Novel, intuitive workflows were subsequently implemented to ensure the verification of selected proteins of interest in a robust, reproducible and high throughput manner. Overall, these data suggest that this strategy supports identification of protein biomarkers of prostate cancer progression and potential therapeutic targets for CRPC.

Probing the prostate tumour microenvironment II: Impact of hypoxia on a cell model of prostate cancer progression

Approximately one in six men are diagnosed with Prostate Cancer every year in the Western world. Although it can be well managed and non-life threatening in the early stages, over time many patients cease to respond to treatment and develop castrate resistant prostate cancer (CRPC). CRPC represents a clinically challenging and lethal form of prostate cancer. Progression of CRPC is, in part, driven by the ability of cancer cells to alter their metabolic profile during the course of tumourgenesis and metastasis so that they can survive in oxygen and nutrient-poor environments and even withstand treatment. This work was carried out as a continuation of a study aimed towards gaining greater mechanistic understanding of how conditions within the tumour microenvironment impact on both androgen sensitive (LNCaP) and androgen independent (LNCaP-abl and LNCaP-abl-Hof) prostate cancer cell lines. Here we have applied technically robust and reproducible label-free liquid chromatography mass spectrometry analysis for comprehensive proteomic profiling of prostate cancer cell lines under hypoxic conditions. This led to the identification of over 4,000 proteins - one of the largest protein datasets for prostate cancer cell lines established to date. The biological and clinical significance of proteins showing a significant change in expression as result of hypoxic conditions was established. Novel, intuitive workflows were subsequently implemented to enable robust, reproducible and high throughput verification of selected proteins of interest. Overall, these data suggest that this strategy supports identification of protein biomarkers of prostate cancer progression and potential therapeutic targets for CRPC.

Strategies to avoid treatment-induced lineage crisis in advanced prostate cancer

The increasing potency of therapies that target the androgen receptor (AR) signalling axis has correlated with a rise in the proportion of patients with prostate cancer harbouring an adaptive phenotype, termed treatment-induced lineage crisis. This phenotype is characterized by features that include soft-tissue metastasis and/or resistance to standard anticancer therapies. Potent anticancer treatments might force cancer cells to evolve and develop alternative cell lineages that are resistant to primary therapies, a mechanism similar to the generation of multidrug- resistant microorganisms after continued antibiotic use. Herein, we assess the hypothesis that treatment-adapted phenotypes harbour reduced AR expression and/or activity, and acquire compensatory strategies for cell survival. We highlight the striking similarities between castration-resistant prostate cancer and triple-negative breast cancer, another poorly differentiated endocrine malignancy. Alternative treatment paradigms are needed to avoid therapy-induced resistance. Herein, we present a new clinical trial strategy designed to evaluate the potential of rapid drug cycling as an approach to delay the onset of resistance and treatment-induced lineage crisis in patients with metastatic castration-resistant prostate cancer.

Stromal Gene Expression is Predictive for Metastatic Primary Prostate Cancer

BACKGROUND

Clinical grading systems using clinical features alongside nomograms lack precision in guiding treatment decisions in prostate cancer (PCa). There is a critical need for identification of biomarkers that can more accurately stratify patients with primary PCa.

OBJECTIVE

To identify a robust prognostic signature to better distinguish indolent from aggressive prostate cancer (PCa).

DESIGN, SETTING, AND PARTICIPANTS

To develop the signature, whole-genome and whole-transcriptome sequencing was conducted on five PCa patient-derived xenograft (PDX) models collected from independent foci of a single primary tumor and exhibiting variable metastatic phenotypes. Multiple independent clinical cohorts including an intermediate-risk cohort were used to validate the biomarkers.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

The outcome measurement defining aggressive PCa was metastasis following radical prostatectomy. A generalized linear model with lasso regularization was used to build a 93-gene stroma-derived metastasis signature (SDMS). The SDMS association with metastasis was assessed using a Wilcoxon rank-sum test. Performance was evaluated using the area under the curve (AUC) for the receiver operating characteristic, and Kaplan-Meier curves. Univariable and multivariable regression models were used to compare the SDMS alongside clinicopathological variables and reported signatures. AUC was assessed to determine if SDMS is additive or synergistic to previously reported signatures.

RESULTS AND LIMITATIONS

A close association between stromal gene expression and metastatic phenotype was observed. Accordingly, the SDMS was modeled and validated in multiple independent clinical cohorts. Patients with higher SDMS scores were found to have worse prognosis. Furthermore, SDMS was an independent prognostic factor, can stratify risk in intermediate-risk PCa, and can improve the performance of other previously reported signatures.

CONCLUSIONS

Profiling of stromal gene expression led to development of an SDMS that was validated as independently prognostic for the metastatic potential of prostate tumors.

PATIENT SUMMARY

Our stroma-derived metastasis signature can predict the metastatic potential of early stage disease and will strengthen decisions regarding selection of active surveillance versus surgery and/or radiation therapy for prostate cancer patients. Furthermore, profiling of stroma cells should be more consistent than profiling of diverse cellular populations of heterogeneous tumors.

Navigating the evolving therapeutic landscape in advanced prostate cancer

Prostate cancer is the most common cause of cancer in men, with 137.9 new cases per 100,000 men per year. The overall 5-year survival rate for prostate cancer is very high. Up to 20% of men who undergo state-of-the art treatment for prostate cancer will develop castration-resistant prostate cancer (CRPC) within 5 years, with median survival for those with metastatic CRPC ranging from approximately 15 to 36 months in recent studies. With the advent of several new drugs in the past 5 years to treat CRPC, the challenge facing clinicians is how to best sequence or combine therapies or both to optimize outcomes. A better understanding of the disease process and the role of the androgen receptor as a target for both therapy and resistance have led to the consideration of biomarkers as an approach to aid in selecting the appropriate agent for a given patient as patients respond to or tolerate different drugs differently. Research to identify new prognostic biomarkers, which are associated with outcome measures, as well as predictive biomarkers, which predict response or resistance to therapy is ongoing. The treatment of advanced prostate cancer and the research related to biomarkers are discussed.

Whole blood mRNA in prostate cancer reveals a four-gene androgen regulated panel

Due to increased sensitivity, the expression of circulating nucleotides is rapidly gaining popularity in cancer diagnosis. Whole blood mRNA has been used in studies on a number of cancers, most notably two separate studies that used whole blood mRNA to define non-overlapping signatures of prostate cancer that has become castration independent. Prostate cancer is known to rely on androgens for initial growth, and there is increasing evidence on the importance of the androgen axis in advanced disease. Using whole blood mRNA samples from patients with prostate cancer, we have identified the four-gene panel of FAM129A, MME, KRT7 and SOD2 in circulating mRNA that are differentially expressed in a discovery cohort of metastatic samples. Validation of these genes at the mRNA and protein level was undertaken in additional cohorts defined by risk of relapse following surgery and hormone status. All the four genes were downregulated at the mRNA level in the circulation and in primary tissue, but this was not always reflected in tissue protein expression. MME demonstrated significant differences in the hormone cohorts, whereas FAM129A is downregulated at the mRNA level but is raised at the protein level in tumours. Using published ChIP-seq data, we have demonstrated that this may be due to AR binding at the FAM129A and MME loci in multiple cell lines. These data suggest that whole blood mRNA of androgen-regulated genes has the potential to be used for diagnosis and monitoring of prostate cancer.

Germline genetic variation in JAK2 as a prognostic marker in castration-resistant prostate cancer

OBJECTIVES

To evaluate the prognostic significance of germline variation in candidate genes in patients with castration-resistant prostate cancer (CRPC).

METHODS

Germline DNA was extracted from peripheral blood mononuclear cells of patients with CRPC enrolled in a clinically annotated registry. Fourteen candidate genes implicated in either initiation or progression of prostate cancer were tagged using single nucleotide polymorphisms (SNPs) from HapMap with a minor allele frequency of >5%. The primary endpoint was overall survival (OS), defined as time from development of CRPC to death. Principal component analysis was used for gene levels tests of significance. For SNP-level results the per allele hazard ratios (HRs) and 95% confidence intervals (CIs) under the additive allele model were estimated using Cox regression, adjusted for age at CRPC and Gleason score (GS).

RESULTS

A total of 240 patients with CRPC were genotyped (14 genes; 84 SNPs). The median (range) age of the cohort was 69 (43-93) years. The GS distribution was 55% with GS ≥8, 32% with GS = 7 and 13% with GS <7 or unknown. The median (interquartile range) time from castration resistance to death for the cohort was 2.67 (1.6-4.07) years (144 deaths). At the gene level, a single gene, JAK2 was associated with OS (P < 0.01), and 11 of 18 JAK2 SNPs were individually associated with OS after adjustment for age and GS. A multivariate model consisting of age, GS, rs2149556 (HR 0.67; 95% CI 0.38-1.18) and rs4372063 (HR 2.17; 95% CI 1.25-3.76) was constructed to predict survival in patients with CRPC (concordance of 0.69, P < 3.2 × 10^-9 ).

CONCLUSIONS

Germline variation in the JAK2 gene was associated with survival in patients with CRPC and warrants further validation as a potential prognostic biomarker.

Persistent Neutrophil to Lymphocyte Ratio >3 during Treatment with Enzalutamide and Clinical Outcome in Patients with Castration-Resistant Prostate Cancer

The baseline value of neutrophil to lymphocyte ratio (NLR) has been found to be prognostic in patients with metastatic castration resistant prostate cancer (CRPC). We evaluated the impact of baseline NLR and its change in patients receiving enzalutamide. We included consecutive metastatic CRPC patients treated with enzalutamide after docetaxel and studies the change of NLR (>3 vs ≤3) after week 4 and 12 weeks. Progression-free survival (PFS), overall survival (OS) and their 95% Confidence Intervals (95% CI) were estimated by the Kaplan-Meier method and compared with the log-rank test. The impact of NLR on PFS and OS was evaluated by Cox regression analyses and on prostate-specific antigen response rates (PSA RR; PSA decline >50%) were evaluated by binary logistic regression. Data collected on 193 patients from 9 centers were evaluated. Median age was 73.1 years (range, 42.8–90.7). The median baseline NLR was 3.2. The median PFS was 3.2 months (95% CI = 2.7–4.2) in patients with baseline NLR >3 and 7.4 months (95% CI = 5.5–9.7) in those with NLR ≤3, p < 0.0001. The median OS was 10.4 months (95% CI = 6.5–14.9) in patients with baseline NLR >3 and 16.9 months (95% CI = 11.2–20.9) in those with baseline NLR ≤3, p < 0.0001. In multivariate analysis, changes in NLR at 4 weeks were significant predictors of both PFS [hazard ratio (HR) 1.24, 95% confidence interval (95% CI) 1.07–1.42, p = 0.003, and OS (HR 1.29, 95% CI 1.10–1.51, p = 0.001. A persistent NLR >3 during treatment with enzalutamide seems to have both prognostic and predictive value in CRPC patients.

A comprehensive review of genomic landscape, biomarkers and treatment sequencing in castration-resistant prostate cancer

Hormone-naïve prostate cancer and its castration-resistant state (CRPC) are clinically and genetically heterogeneous diseases. From initiation of prostate carcinogenesis to its evolution towards therapeutic resistance, various combinations of genetic and epigenetic events occur. Schematically, progression to CRPC could be divided in two distinct pathways, either dependent or independent of the androgen receptor activity. Nevertheless, because the better knowledge of the genetic landscape of CRPC is under way, limited clinical applications are available at the moment, underlying the usefulness of prognostic and predictive biomarkers in daily practice. Despite the promising prognostic value of circulating tumor cells, no biomarker has been currently validated as a surrogate for overall survival in CRPC patients. Inversely, considerable interest has been generated with the recent finding of the splice variant AR-V7 that allows to predict resistance to abiraterone acetate and enzalutamide. However, other predictive biomarkers would be necessary to accurately guide personalized sequencing of CRPC treatment, which now includes numerous possibilities based on the six validated drugs, without accounting for those currently under investigation in the ongoing randomized controlled trials. As a consequence, only rational sequencing, which consists in choosing an agent that is not expected to have cross-resistance with previous therapy, can be currently advised.