AZGP1 deficiency promotes angiogenesis in prostate cancer.

BACKGROUND: Loss of AZGP1 expression is a biomarker associated with progression to castration resistance, development of metastasis, and poor disease-specific survival in prostate cancer. However, high expression of AZGP1 cells in prostate cancer has been reported to increase proliferation and invasion. The exact role of AZGP1 in prostate cancer progression remains elusive. METHOD: AZGP1 knockout and overexpressing prostate cancer cells were generated using a lentiviral system. The effects of AZGP1 under- or over-expression in prostate cancer cells were evaluated by in vitro cell proliferation, migration, and invasion assays. Heterozygous AZGP1± mice were obtained from European Mouse Mutant Archive (EMMA), and prostate tissues from homozygous knockout male mice were collected at 2, 6 and 10 months for histological analysis. In vivo xenografts generated from AZGP1 under- or over-expressing prostate cancer cells were used to determine the role of AZGP1 in prostate cancer tumor growth, and subsequent proteomics analysis was conducted to elucidate the mechanisms of AZGP1 action in prostate cancer progression. AZGP1 expression and microvessel density were measured in human prostate cancer samples on a tissue microarray of 215 independent patient samples. RESULT: Neither the knockout nor overexpression of AZGP1 exhibited significant effects on prostate cancer cell proliferation, clonal growth, migration, or invasion in vitro. The prostates of AZGP1-/- mice initially appeared to have grossly normal morphology; however, we observed fibrosis in the periglandular stroma and higher blood vessel density in the mouse prostate by 6 months. In PC3 and DU145 mouse xenografts, over-expression of AZGP1 did not affect tumor growth. Instead, these tumors displayed decreased microvessel density compared to xenografts derived from PC3 and DU145 control cells, suggesting that AZGP1 functions to inhibit angiogenesis in prostate cancer. Proteomics profiling further indicated that, compared to control xenografts, AZGP1 overexpressing PC3 xenografts are enriched with angiogenesis pathway proteins, including YWHAZ, EPHA2, SERPINE1, and PDCD6, MMP9, GPX1, HSPB1, COL18A1, RNH1, and ANXA1. In vitro functional studies show that AZGP1 inhibits human umbilical vein endothelial cell proliferation, migration, tubular formation and branching. Additionally, tumor microarray analysis shows that AZGP1 expression is negatively correlated with blood vessel density in human prostate cancer tissues. CONCLUSION: AZGP1 is a negative regulator of angiogenesis, such that loss of AZGP1 promotes angiogenesis in prostate cancer. AZGP1 likely exerts heterotypical effects on cells in the tumor microenvironment, such as stromal and endothelial cells. This study sheds light on the anti-angiogenic characteristics of AZGP1 in the prostate and provides a rationale to target AZGP1 to inhibit prostate cancer progression.

ACAA2 is a novel molecular indicator for cancers with neuroendocrine phenotype.

BACKGROUND: Neuroendocrine phenotype is commonly associated with therapy resistance and poor prognoses in small-cell neuroendocrine cancers (SCNCs), such as neuroendocrine prostate cancer (NEPC) and small-cell lung cancer (SCLC). Expression levels of current neuroendocrine markers exhibit high case-by-case variability, so multiple markers are used in combination to identify SCNCs. Here, we report that ACAA2 is elevated in SCNCs and is a potential molecular indicator for SCNCs. METHODS: ACAA2 expressions in tumour xenografts, tissue microarrays (TMAs), and patient tissues from prostate and lung cancers were analysed via immunohistochemistry. ACAA2 mRNA levels in lung and prostate cancer (PC) patients were assessed in published datasets. RESULTS: ACAA2 protein and mRNA levels were elevated in SCNCs relative to non-SCNCs. Medium/high ACAA2 intensity was observed in 78% of NEPC PDXs samples (N = 27) relative to 33% of adeno-CRPC (N = 86), 2% of localised PC (N = 50), and 0% of benign prostate specimens (N = 101). ACAA2 was also elevated in lung cancer patient tissues with neuroendocrine phenotype. 83% of lung carcinoid tissues (N = 12) and 90% of SCLC tissues (N = 10) exhibited medium/high intensity relative to 40% of lung adenocarcinoma (N = 15). CONCLUSION: ACAA2 expression is elevated in aggressive SCNCs such as NEPC and SCLC, suggesting it is a potential molecular indicator for SCNCs.

Trop2 is a driver of metastatic prostate cancer with neuroendocrine phenotype via PARP1.

Resistance to androgen deprivation therapy, or castration-resistant prostate cancer (CRPC), is often accompanied by metastasis and is currently the ultimate cause of prostate cancer-associated deaths in men. Recently, secondary hormonal therapies have led to an increase of neuroendocrine prostate cancer (NEPC), a highly aggressive variant of CRPC. Here, we identify that high levels of cell surface receptor Trop2 are predictive of recurrence of localized prostate cancer. Moreover, Trop2 is significantly elevated in CRPC and NEPC, drives prostate cancer growth, and induces neuroendocrine phenotype. Overexpression of Trop2 induces tumor growth and metastasis while loss of Trop2 suppresses these abilities in vivo. Trop2-driven NEPC displays a significant up-regulation of PARP1, and PARP inhibitors significantly delay tumor growth and metastatic colonization and reverse neuroendocrine features in Trop2-driven NEPC. Our findings establish Trop2 as a driver and therapeutic target for metastatic prostate cancer with neuroendocrine phenotype and suggest that high Trop2 levels could identify cancers that are sensitive to Trop2-targeting therapies and PARP1 inhibition.

Protein signatures to distinguish aggressive from indolent prostate cancer.

BACKGROUND: Distinguishing men with aggressive from indolent prostate cancer is critical to decisions in the management of clinically localized prostate cancer. Molecular signatures of aggressive disease could help men overcome this major clinical challenge by reducing unnecessary treatment and allowing more appropriate treatment of aggressive disease. METHODS: We performed a mass spectrometry-based proteomic analysis of normal and malignant prostate tissues from 22 men who underwent surgery for prostate cancer. Prostate cancer samples included Grade Groups (3-5), with 8 patients experiencing recurrence and 14 without evidence of recurrence with a mean of 6.8 years of follow-up. To better understand the biological pathways underlying prostate cancer aggressiveness, we performed a systems biology analysis and gene enrichment analysis. Proteins that distinguished recurrent from nonrecurrent cancer were chosen for validation by immunohistochemical analysis on tissue microarrays containing samples from a larger cohort of patients with recurrent and nonrecurrent prostate cancer. RESULTS: In all, 24,037 unique peptides (false discovery rate < 1%) corresponding to 3,313 distinct proteins were identified with absolute abundance ranges spanning seven orders of magnitude. Of these proteins, 115 showed significantly (p < 0.01) different levels in tissues from recurrent versus nonrecurrent cancers. Analysis of all differentially expressed proteins in recurrent and nonrecurrent cases identified several protein networks, most prominently one in which approximately 24% of the proteins in the network were regulated by the YY1 transcription factor (adjusted p < 0.001). Strong immunohistochemical staining levels of three differentially expressed proteins, POSTN, CALR, and CTSD, on a tissue microarray validated their association with shorter patient survival. CONCLUSIONS: The protein signatures identified could improve understanding of the molecular drivers of aggressive prostate cancer and be used as candidate prognostic biomarkers.

Discovery of PTN as a serum-based biomarker of pro-metastatic prostate cancer.

Distinguishing clinically significant from indolent prostate cancer (PC) is a major clinical challenge. We utilised targeted protein biomarker discovery approach to identify biomarkers specific for pro-metastatic PC. Serum samples from the cancer-free group; Cambridge Prognostic Group 1 (CPG1, low risk); CPG5 (high risk) and metastatic disease were analysed using Olink Proteomics panels. Tissue validation was performed by immunohistochemistry in a radical prostatectomy cohort (n = 234). We discovered that nine proteins (pleiotrophin (PTN), MK, PVRL4, EPHA2, TFPI-2, hK11, SYND1, ANGPT2, and hK14) were elevated in metastatic PC patients when compared to other groups. PTN levels were increased in serum from men with CPG5 compared to benign and CPG1. High tissue PTN level was an independent predictor of biochemical recurrence and metastatic progression in low- and intermediate-grade disease. These findings suggest that PTN may represent a novel biomarker for the presence of poor prognosis local disease with the potential to metastasise warranting further investigation.

Identification of diagnostic metabolic signatures in clear cell renal cell carcinoma using mass spectrometry imaging.

Clear cell renal cell carcinoma (ccRCC) is the most common and lethal subtype of kidney cancer. Intraoperative frozen section (IFS) analysis is used to confirm the diagnosis during partial nephrectomy. However, surgical margin evaluation using IFS analysis is time consuming and unreliable, leading to relatively low utilization. In our study, we demonstrated the use of desorption electrospray ionization mass spectrometry imaging (DESI-MSI) as a molecular diagnostic and prognostic tool for ccRCC. DESI-MSI was conducted on fresh-frozen 23 normal tumor paired nephrectomy specimens of ccRCC. An independent validation cohort of 17 normal tumor pairs was analyzed. DESI-MSI provides two-dimensional molecular images of tissues with mass spectra representing small metabolites, fatty acids and lipids. These tissues were subjected to histopathologic evaluation. A set of metabolites that distinguish ccRCC from normal kidney were identified by performing least absolute shrinkage and selection operator (Lasso) and log-ratio Lasso analysis. Lasso analysis with leave-one-patient-out cross-validation selected 57 peaks from over 27,000 metabolic features across 37,608 pixels obtained using DESI-MSI of ccRCC and normal tissues. Baseline Lasso of metabolites predicted the class of each tissue to be normal or cancerous tissue with an accuracy of 94 and 76%, respectively. Combining the baseline Lasso with the ratio of glucose to arachidonic acid could potentially reduce scan time and improve accuracy to identify normal (82%) and ccRCC (88%) tissue. DESI-MSI allows rapid detection of metabolites associated with normal and ccRCC with high accuracy. As this technology advances, it could be used for rapid intraoperative assessment of surgical margin status.

Diagnosis of prostate cancer by desorption electrospray ionization mass spectrometric imaging of small metabolites and lipids.

Accurate identification of prostate cancer in frozen sections at the time of surgery can be challenging, limiting the surgeon's ability to best determine resection margins during prostatectomy. We performed desorption electrospray ionization mass spectrometry imaging (DESI-MSI) on 54 banked human cancerous and normal prostate tissue specimens to investigate the spatial distribution of a wide variety of small metabolites, carbohydrates, and lipids. In contrast to several previous studies, our method included Krebs cycle intermediates (m/z <200), which we found to be highly informative in distinguishing cancer from benign tissue. Malignant prostate cells showed marked metabolic derangements compared with their benign counterparts. Using the "Least absolute shrinkage and selection operator" (Lasso), we analyzed all metabolites from the DESI-MS data and identified parsimonious sets of metabolic profiles for distinguishing between cancer and normal tissue. In an independent set of samples, we could use these models to classify prostate cancer from benign specimens with nearly 90% accuracy per patient. Based on previous work in prostate cancer showing that glucose levels are high while citrate is low, we found that measurement of the glucose/citrate ion signal ratio accurately predicted cancer when this ratio exceeds 1.0 and normal prostate when the ratio is less than 0.5. After brief tissue preparation, the glucose/citrate ratio can be recorded on a tissue sample in 1 min or less, which is in sharp contrast to the 20 min or more required by histopathological examination of frozen tissue specimens.

Bioorthogonal Labeling of Human Prostate Cancer Tissue Slice Cultures for Glycoproteomics.

Sialylated glycans are found at elevated levels in many types of cancer and have been implicated in disease progression. However, the specific glycoproteins that contribute to the cancer cell-surface sialylation are not well characterized, specifically in bona fide human disease tissue. Metabolic and bioorthogonal labeling methods have previously enabled the enrichment and identification of sialoglycoproteins from cultured cells and model organisms. Herein, we report the first application of this glycoproteomic platform to human tissues cultured ex vivo. Both normal and cancerous prostate tissues were sliced and cultured in the presence of the azide-functionalized sialic acid biosynthetic precursor Ac4 ManNAz. The compound was metabolized to the azidosialic acid and incorporated into cell surface and secreted sialoglycoproteins. Chemical biotinylation followed by enrichment and mass spectrometry led to the identification of glycoproteins that were found at elevated levels or uniquely in cancerous prostate tissue. This work therefore extends the use of bioorthogonal labeling strategies to problems of clinical relevance.

Biologic differences between peripheral and transition zone prostate cancer.

BACKGROUND: Prostate cancer arises in the transition zone (TZ) in approximately 20-25% of cases. Modern biopsy and surveillance protocols, and advances in prostate cancer imaging, have renewed interest in TZ prostate cancers. We compared TZ and PZ prostate cancer to determine if cancer location is independently associated with better outcomes. METHODS: We evaluated an expanded cohort of 1354 men who underwent radical prostatectomy between 1983 and 2003 with updated long-term clinical follow-up. Regression models were used to compare the volume of high-grade (Gleason 4 or 5) cancer and total cancer volume by location. Uni- and multi-variable logistic regression models tested the associations between cancer location and adverse pathologic features. Multivariable proportional hazard models were fit to examine cancer recurrence. RESULTS: Patients with TZ cancer presented with higher pre-operative serum PSA values (11.07 vs. 7.86 ng/ml) and larger total cancer volume (7.1 vs. 3.8 cc). Patients with TZ cancer had decreased odds of seminal vesicle invasion (OR 0.08, 95% CI 0.03, 0.21), extra-capsular extension (OR 0.56, 95% CI 0.35, 0.92), and lymphovascular invasion (OR 0.48, 95% CI 0.27, 0.87) in multivariable models. TZ cancers were independently associated with decreased hazard of tumor recurrence (HR 0.62, 95% CI 0.43, 0.90). CONCLUSIONS: TZ cancer prostate is associated with favorable pathologic features and better recurrence-free survival despite being diagnosed with larger cancers and higher PSA values. Tumor location should be taken into account when stratifying patient risk before and after prostatectomy, particularly with the evolving role of imaging in prostate cancer management.

Optimization and comprehensive characterization of a faithful tissue culture model of the benign and malignant human prostate.

Few preclinical models accurately depict normal human prostate tissue or primary prostate cancer (PCa). In vitro systems typically lack complex cellular interactions among structured prostatic epithelia and a stromal microenvironment, and genetic and molecular fidelity are concerns in both in vitro and in vivo models. 'Tissue slice cultures' (TSCs) provide realistic preclinical models of diverse tissues and organs, but have not been fully developed or widely utilized for prostate studies. Problems encountered include degeneration of differentiated secretory cells, basal cell hyperplasia, and poor survival of PCa. Here, we optimized, characterized, and applied a TSC model of primary human PCa and benign prostate tissue that overcomes many deficiencies of current in vitro models. Tissue cores from fresh prostatectomy specimens were precision-cut at 300 µm and incubated in a rotary culture apparatus. The ability of varied culture conditions to faithfully maintain benign and cancer cell and tissue structure and function over time was evaluated by immunohistological and biochemical assays. After optimization of the culture system, molecular and cellular responses to androgen ablation and to piperlongumine (PL), purported to specifically reduce androgen signaling in PCa, were investigated. Optimized culture conditions successfully maintained the structural and functional fidelity of both benign and PCa TSCs for 5 days. TSCs exhibited androgen dependence, appropriately undergoing ductal degeneration, reduced proliferation, and decreased prostate-specific antigen expression upon androgen ablation. Further, TSCs revealed cancer-specific reduction of androgen receptor and increased apoptosis upon treatment with PL, validating data from cell lines. We demonstrate a TSC model that authentically recapitulates the structural, cellular, and genetic characteristics of the benign and malignant human prostate, androgen dependence of the native tissue, and cancer-specific response to a potentially new therapeutic for PCa. The work described herein provides a basis for advancing the experimental utility of the TSC model.

Preclinical trial of a new dual mTOR inhibitor, MLN0128, using renal cell carcinoma tumorgrafts.

mTOR is a rational target in renal cell carcinoma (RCC) because of its role in disease progression. However, the effects of temsirolimus, the only first-generation mTOR inhibitor approved by the FDA for first-line treatment of metastatic RCC, on tumor reduction and progression-free survival are minimal. Second-generation mTOR inhibitors have not been evaluated on RCC. We compared the effects of temsirolimus and MLN0128, a potent second-generation mTOR inhibitor, on RCC growth and metastasis using a realistic patient-derived tissue slice graft (TSG) model. TSGs were derived from three fresh primary RCC specimens by subrenal implantation of precision-cut tissue slices into immunodeficient mice that were randomized and treated with MLN0128, temsirolimus, or placebo. MLN0128 consistently suppressed primary RCC growth, monitored by magnetic resonance imaging (MRI), in three TSG cohorts for up to 2 months. Temsirolimus, in contrast, only transiently inhibited the growth of TSGs in one of two cohorts before resistance developed. In addition, MLN0128 reduced liver metastases, determined by human-specific quantitative polymerase chain reaction, in two TSG cohorts, whereas temsirolimus failed to have any significant impact. Moreover, MLN0128 decreased levels of key components of the two mTOR subpathways including TORC1 targets 4EBP1, p-S6K1, HIF1α and MTA1 and the TORC2 target c-Myc, consistent with dual inhibition. Our results demonstrated that MLN0128 is superior to temsirolimus in inhibiting primary RCC growth as well as metastases, lending strong support for further clinical development of dual mTOR inhibitors for RCC treatment.

A tissue graft model of DNA damage response in the normal and malignant human prostate.

PURPOSE: DNA damage responses are relevant to prostate cancer initiation, progression and treatment. Few models of the normal and malignant human prostate that maintain stromal-epithelial interactions in vivo exist in which to study DNA damage responses. We evaluated the feasibility of maintaining tissue slice grafts at subcutaneous vs subrenal capsular sites in RAG2(-/-)γC(-/-) mice to study the DNA damage responses of normal and malignant glands. MATERIALS AND METHODS: We compared the take rate and histology of tissue slice grafts from fresh, precision cut surgical specimens that were maintained for 1 to 4 weeks in subcutaneous vs subrenal capsular sites. Induction of γH2AX, p53, ATM and apoptosis was evaluated as a measure of the DNA damage response after irradiation. RESULTS: The take rate of subcutaneous tissue slice grafts was higher than typically reported but lower than at the subrenal capsular site. Subcutaneous tissue slice grafts frequently showed basal cell hyperplasia, squamous metaplasia and cystic atrophy, and cancer did not survive. In contrast, normal and malignant histology was well maintained in subrenal capsular tissue slice grafts. Regardless of implantation site the induction of γH2AX and ATM occurred in tissue slice graft epithelium 1 hour after irradiation and decreased to basal level by 24 hours, indicating DNA damage recognition and repair. As observed previously in prostatic ex vivo models, p53 was not activated. Notably, tumor but not normal cells responded to irradiation by undergoing apoptosis. CONCLUSIONS: To our knowledge this is the first study of DNA damage responses in a patient derived prostate tissue graft model. The subrenal capsular site of RAG2(-/-)γC(-/-) mice optimally maintains normal and malignant histology and function, permitting novel studies of DNA damage responses in a physiological context.

Critical evaluation of artificial intelligence as a digital twin of pathologists for prostate cancer pathology.

Prostate cancer pathology plays a crucial role in clinical management but is time-consuming. Artificial intelligence (AI) shows promise in detecting prostate cancer and grading patterns. We tested an AI-based digital twin of a pathologist, vPatho, on 2603 histological images of prostate tissue stained with hematoxylin and eosin. We analyzed various factors influencing tumor grade discordance between the vPatho system and six human pathologists. Our results demonstrated that vPatho achieved comparable performance in prostate cancer detection and tumor volume estimation, as reported in the literature. The concordance levels between vPatho and human pathologists were examined. Notably, moderate to substantial agreement was observed in identifying complementary histological features such as ductal, cribriform, nerve, blood vessel, and lymphocyte infiltration. However, concordance in tumor grading decreased when applied to prostatectomy specimens (κ = 0.44) compared to biopsy cores (κ = 0.70). Adjusting the decision threshold for the secondary Gleason pattern from 5 to 10% improved the concordance level between pathologists and vPatho for tumor grading on prostatectomy specimens (κ from 0.44 to 0.64). Potential causes of grade discordance included the vertical extent of tumors toward the prostate boundary and the proportions of slides with prostate cancer. Gleason pattern 4 was particularly associated with this population. Notably, the grade according to vPatho was not specific to any of the six pathologists involved in routine clinical grading. In conclusion, our study highlights the potential utility of AI in developing a digital twin for a pathologist. This approach can help uncover limitations in AI adoption and the practical application of the current grading system for prostate cancer pathology.

UCHL1 is a potential molecular indicator and therapeutic target for neuroendocrine carcinomas.

Neuroendocrine carcinomas, such as neuroendocrine prostate cancer and small-cell lung cancer, commonly have a poor prognosis and limited therapeutic options. We report that ubiquitin carboxy-terminal hydrolase L1 (UCHL1), a deubiquitinating enzyme, is elevated in tissues and plasma from patients with neuroendocrine carcinomas. Loss of UCHL1 decreases tumor growth and inhibits metastasis of these malignancies. UCHL1 maintains neuroendocrine differentiation and promotes cancer progression by regulating nucleoporin, POM121, and p53. UCHL1 binds, deubiquitinates, and stabilizes POM121 to regulate POM121-associated nuclear transport of E2F1 and c-MYC. Treatment with the UCHL1 inhibitor LDN-57444 slows tumor growth and metastasis across neuroendocrine carcinomas. The combination of UCHL1 inhibitors with cisplatin, the standard of care used for neuroendocrine carcinomas, significantly delays tumor growth in pre-clinical settings. Our study reveals mechanisms of UCHL1 function in regulating the progression of neuroendocrine carcinomas and identifies UCHL1 as a therapeutic target and potential molecular indicator for diagnosing and monitoring treatment responses in these malignancies.

Patient-derived tissue slice grafts accurately depict response of high-risk primary prostate cancer to androgen deprivation therapy.

BACKGROUND: Effective eradication of high-risk primary prostate cancer (HRPCa) could significantly decrease mortality from prostate cancer. However, the discovery of curative therapies for HRPCa is hampered by the lack of authentic preclinical models. METHODS: We improved upon tumorgraft models that have been shown to predict drug response in other cancer types by implanting thin, precision-cut slices of HRPCa under the renal capsule of immunodeficient mice. Tissue slice grafts (TSGs) from 6 cases of HRPCa were established in mice. Following androgen deprivation by castration, TSGs were recovered and the presence and phenotype of cancer cells were evaluated. RESULTS: High-grade cancer in TSGs generated from HRPCa displayed characteristic Gleason patterns and biomarker expression. Response to androgen deprivation therapy (ADT) was as in humans, with some cases exhibiting complete pathologic regression and others showing resistance to castration. As in humans, ADT decreased cell proliferation and prostate-specific antigen expression in TSGs. Adverse pathological features of parent HRPCa were associated with lack of regression of cancer in corresponding TSGs after ADT. Castration-resistant cancer cells remaining in TSGs showed upregulated expression of androgen receptor target genes, as occurs in castration-resistant prostate cancer (CRPC) in humans. Finally, a rare subset of castration-resistant cancer cells in TSGs underwent epithelial-mesenchymal transition, a process also observed in CRPC in humans. CONCLUSIONS: Our study demonstrates the feasibility of generating TSGs from multiple patients and of generating a relatively large number of TSGs from the same HRPCa specimen with similar cell composition and histology among control and experimental samples in an in vivo setting. The authentic response of TSGs to ADT, which has been extensively characterized in humans, suggests that TSGs can serve as a surrogate model for clinical trials to achieve rapid and less expensive screening of therapeutics for HRPCa and primary CRPC.

Anti-Oligomannose Antibodies as Potential Serum Biomarkers of Aggressive Prostate Cancer.

[Table: see text] This study bridges a carbohydrate microarray discovery and a large-scale serological validation of anti-oligomannose antibodies as novel serum biomarkers of aggressive prostate cancer (PCa). Experimentally, a Man9-cluster-specific enzyme-linked immunosorbent assay was established to enable sensitive detection of anti-Man9 antibodies in human sera. A large-cohort of men with PCa or benign prostatic hyperplasia (BPH) whose sera were banked at Stanford University was characterized using this assay. Subjects included patients with 100% Gleason grade 3 cancer (n = 84), with Gleason grades 4 and/or 5 cancer (n = 204), and BPH controls (n = 135). Radical prostatectomy Gleason grades and biochemical (PSA) recurrence served as key parameters for serum biomarker evaluation. It was found that IgGMan9 and IgMMan9 were widely present in the sera of men with BPH, as well as those with cancer. However, these antibody reactivities were significantly increased in the subjects with the largest volumes of high grade cancer. Detection of serum IgGMan9 and IgMMan9 significantly predicted the clinical outcome of PCa post-radical prostatectomy. Given these results, we suggest that IgGMan9 and IgMMan9 are novel serum biomarkers for monitoring aggressive progression of PCa. The potential of oligomannosyl antigens as targets for PCa subtyping and targeted immunotherapy is yet to be explored.

Distinguishing Renal Cell Carcinoma From Normal Kidney Tissue Using Mass Spectrometry Imaging Combined With Machine Learning.

PURPOSE: Accurately distinguishing renal cell carcinoma (RCC) from normal kidney tissue is critical for identifying positive surgical margins (PSMs) during partial and radical nephrectomy, which remains the primary intervention for localized RCC. Techniques that detect PSM with higher accuracy and faster turnaround time than intraoperative frozen section (IFS) analysis can help decrease reoperation rates, relieve patient anxiety and costs, and potentially improve patient outcomes. MATERIALS AND METHODS: Here, we extended our combined desorption electrospray ionization mass spectrometry imaging (DESI-MSI) and machine learning methodology to identify metabolite and lipid species from tissue surfaces that can distinguish normal tissues from clear cell RCC (ccRCC), papillary RCC (pRCC), and chromophobe RCC (chRCC) tissues. RESULTS: From 24 normal and 40 renal cancer (23 ccRCC, 13 pRCC, and 4 chRCC) tissues, we developed a multinomial lasso classifier that selects 281 total analytes from over 27,000 detected molecular species that distinguishes all histological subtypes of RCC from normal kidney tissues with 84.5% accuracy. On the basis of independent test data reflecting distinct patient populations, the classifier achieves 85.4% and 91.2% accuracy on a Stanford test set (20 normal and 28 RCC) and a Baylor-UT Austin test set (16 normal and 41 RCC), respectively. The majority of the model's selected features show consistent trends across data sets affirming its stable performance, where the suppression of arachidonic acid metabolism is identified as a shared molecular feature of ccRCC and pRCC. CONCLUSION: Together, these results indicate that signatures derived from DESI-MSI combined with machine learning may be used to rapidly determine surgical margin status with accuracies that meet or exceed those reported for IFS.

Transcript levels of androgen receptor variant AR-V1 or AR-V7 do not predict recurrence in patients with prostate cancer at indeterminate risk for progression.

PURPOSE: AR-V7, a ligand independent splice variant of androgen receptor, may support the growth of castration resistant prostate cancer and have prognostic value. Another variant, AR-V1, interferes with AR-V7 activity. We investigated whether AR-V7 or V1 expression would predict biochemical recurrence in men at indeterminate (about 50%) risk for progression following radical prostatectomy. MATERIALS AND METHODS: AR-V7 and V1 transcripts in a mixed grade cohort of 53 men in whom cancer contained 30% to 70% Gleason grade 4/5 and in a grade 3 only cohort of 52 were measured using a branched chain DNA assay. Spearman rank correlations of the transcripts, and histomorphological and clinical variables were determined. AR-V7 and V1 levels were assessed as determinants of recurrence in the mixed grade cohort by logistic regression and survival analysis. The impact of TMPRSS2-ERG gene fusion on prognosis was also evaluated. RESULTS: Neither AR-V7 nor V1 levels in grade 3 or 4/5 cancer in the mixed grade cohort were associated with recurrence or time to recurrence. However, AR-V7 and V1 inversely correlated with serum prostate specific antigen and positively correlated with age. The AR-V1 level in grade 3 cancer in the grade 3 only cohort was higher than in grade 3 or grade 4/5 components of mixed grade cancer. TMPRSS2-ERG fusion was not associated with AR-V7, AR-V1 or recurrence but it was associated with the percent of grade 4/5 cancer. CONCLUSIONS: The AR-V1 or V7 transcript level does not predict recurrence in patients with high grade prostate cancer at indeterminate risk for progression. Grade 3 cancer in mixed grade tumors may differ from 100% grade 3 cancer, at least in AR-V1 expression.

Multiparametric Magnetic Resonance Imaging and Metabolic Characterization of Patient-Derived Xenograft Models of Clear Cell Renal Cell Carcinoma.

Patient-derived xenografts (PDX) are high-fidelity cancer models typically credentialled by genomics, transcriptomics and proteomics. Characterization of metabolic reprogramming, a hallmark of cancer, is less frequent. Dysregulated metabolism is a key feature of clear cell renal cell carcinoma (ccRCC) and authentic preclinical models are needed to evaluate novel imaging and therapeutic approaches targeting metabolism. We characterized 5 PDX from high-grade or metastatic ccRCC by multiparametric magnetic resonance imaging (MRI) and steady state metabolic profiling and flux analysis. Similar to MRI of clinical ccRCC, T2-weighted images of orthotopic tumors of most PDX were homogeneous. The increased hyperintense (cystic) areas observed in one PDX mimicked the cystic phenotype typical of some RCC. The negligible hypointense (necrotic) areas of PDX grown under the highly vascularized renal capsule are beneficial for preclinical studies. Mean apparent diffusion coefficient (ADC) values were equivalent to those of ccRCC in human patients. Hyperpolarized (HP) [1-13C]pyruvate MRI of PDX showed high glycolytic activity typical of high-grade primary and metastatic ccRCC with considerable intra- and inter-tumoral variability, as has been observed in clinical HP MRI of ccRCC. Comparison of steady state metabolite concentrations and metabolic flux in [U-13C]glucose-labeled tumors highlighted the distinctive phenotypes of two PDX with elevated levels of numerous metabolites and increased fractional enrichment of lactate and/or glutamate, capturing the metabolic heterogeneity of glycolysis and the TCA cycle in clinical ccRCC. Culturing PDX cells and reimplanting to generate xenografts (XEN), or passaging PDX in vivo, altered some imaging and metabolic characteristics while transcription remained like that of the original PDX. These findings show that PDX are realistic models of ccRCC for imaging and metabolic studies but that the plasticity of metabolism must be considered when manipulating PDX for preclinical studies.

SU086, an inhibitor of HSP90, impairs glycolysis and represents a treatment strategy for advanced prostate cancer.

Among men, prostate cancer is the second leading cause of cancer-associated mortality, with advanced disease remaining a major clinical challenge. We describe a small molecule, SU086, as a therapeutic strategy for advanced prostate cancer. We demonstrate that SU086 inhibits the growth of prostate cancer cells in vitro, cell-line and patient-derived xenografts in vivo, and ex vivo prostate cancer patient specimens. Furthermore, SU086 in combination with standard of care second-generation anti-androgen therapies displays increased impairment of prostate cancer cell and tumor growth in vitro and in vivo. Cellular thermal shift assay reveals that SU086 binds to heat shock protein 90 (HSP90) and leads to a decrease in HSP90 levels. Proteomic profiling demonstrates that SU086 binds to and decreases HSP90. Metabolomic profiling reveals that SU086 leads to perturbation of glycolysis. Our study identifies SU086 as a treatment for advanced prostate cancer as a single agent or when combined with second-generation anti-androgens.