The PURE-01 study (NCT02736266) evaluated the use of pembrolizumab before radical cystectomy (RC) in muscle-invasive bladder cancer (MIBC).
To evaluate the ability of molecular signatures to predict ...the pathological complete response (CR: ypT0N0) and progression-free survival (PFS) after pembrolizumab and RC.
We analyzed the expression data from patients with T2–4aN0M0 MIBC enrolled in the PURE-01 study (N=84) and from patients of a retrospective multicenter cohort treated with cisplatin-based neoadjuvant chemotherapy (NAC; N=140).
Neoadjuvant pembrolizumab or NAC and RC.
Immune signatures and molecular subtyping (The Cancer Genome Atlas, consensus model, and genomic subtyping classifier GSC) were evaluated in relation to CR and PFS. Multivariable logistic regression analyses for CR were used, adjusting for gender and clinical T stage.
The Immune190 signature was significant for CR on multivariable logistic regression analyses (p= 0.02) in PURE-01, but not in the NAC cohort (p= 0.7). Hallmark signatures for interferon gamma (IFNγ; p= 0.004) and IFNα response (p= 0.006) were also associated with CR for PURE-01, but not for NAC (IFNγ: p= 0.9 and IFNα: p= 0.8). In PURE-01, 93% of patients with the highest Immune190 scores (>1st quartile) had 2-yr PFS versus 79% of those with lower scores; no difference was observed in NAC patients, as well as for the other hallmarks in both groups. The neuroendocrine-like subtype had the worst 2-yr PFS in all three subtyping models (33%) and the GSC claudin-low subtype had the best, with no recurrences in 2 yr. Basal subtypes (across classifications) with higher Immune190 scores showed 100% 2-yr PFS after pembrolizumab therapy (p = 0.04, compared with basal-Immune190 low). Statistical analyses are limited by the small number of events and short follow-up.
Higher RNA-based immune signature scores were significantly associated with CR and numerically improved PFS outcomes after pembrolizumab, but not after NAC. These data emphasize that RNA profiling is a potential tool for personalizing neoadjuvant therapy selection.
We used gene expression profiling to evaluate the association between immune gene expression and response to neoadjuvant immunotherapy, compared with standard chemotherapy, in patients with muscle-invasive bladder cancer (MIBC). We found a significant association between immune gene expression and response to pembrolizumab, but not chemotherapy. We conclude that gene expression profiling has the potential to guide personalized neoadjuvant therapy in MIBC.
By using gene expression profiling of transurethral bladder tumor resection samples from patients with muscle-invasive bladder cancer (MIBC), we reported a significant association between pre-existing immune gene expression and response to neoadjuvant pembrolizumab, but not to neoadjuvant chemotherapy. Different outcomes were also obtained according to the molecular subtype. Gene expression profiling has the potential to guide personalized neoadjuvant therapy in MIBC.
Prostate cancer (PCa) is the most common malignant neoplasm among men in many countries. Since most precancerous and cancerous tissues show signs of inflammation, chronic bacterial prostatitis has ...been hypothesized to be a possible etiology. However, establishing a causal relationship between microbial inflammation and PCa requires a comprehensive analysis of the prostate microbiome. The aim of this study was to characterize the microbiome in prostate tissue of PCa patients and investigate its association with tumour clinical characteristics as well as host expression profiles.
The metagenome and metatranscriptome of tumour and the adjacent benign tissues were assessed in 65 Chinese radical prostatectomy specimens. Escherichia, Propionibacterium, Acinetobacter and Pseudomonas were abundant in both metagenome and metatranscriptome, thus constituting the core of the prostate microbiome. The biodiversity of the microbiomes could not be differentiated between the matched tumour/benign specimens or between the tumour specimens of low and high Gleason Scores. The expression profile of ten Pseudomonas genes was strongly correlated with that of eight host small RNA genes; three of the RNA genes may negatively associate with metastasis. Few viruses could be identified from the prostate microbiomes.
This is the first study of the human prostate microbiome employing an integrated metagenomics and metatranscriptomics approach. In this Chinese cohort, both metagenome and metatranscriptome analyses showed a non-sterile microenvironment in the prostate of PCa patients, but we did not find links between the microbiome and local progression of PCa. However, the correlated expression of Pseudomonas genes and human small RNA genes may provide tantalizing preliminary evidence that Pseudomonas infection may impede metastasis.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Clinicopathologic features and biochemical recurrence are sensitive, but not specific, predictors of metastatic disease and lethal prostate cancer. We hypothesize that a genomic expression signature ...detected in the primary tumor represents true biological potential of aggressive disease and provides improved prediction of early prostate cancer metastasis.
A nested case-control design was used to select 639 patients from the Mayo Clinic tumor registry who underwent radical prostatectomy between 1987 and 2001. A genomic classifier (GC) was developed by modeling differential RNA expression using 1.4 million feature high-density expression arrays of men enriched for rising PSA after prostatectomy, including 213 who experienced early clinical metastasis after biochemical recurrence. A training set was used to develop a random forest classifier of 22 markers to predict for cases--men with early clinical metastasis after rising PSA. Performance of GC was compared to prognostic factors such as Gleason score and previous gene expression signatures in a withheld validation set.
Expression profiles were generated from 545 unique patient samples, with median follow-up of 16.9 years. GC achieved an area under the receiver operating characteristic curve of 0.75 (0.67-0.83) in validation, outperforming clinical variables and gene signatures. GC was the only significant prognostic factor in multivariable analyses. Within Gleason score groups, cases with high GC scores experienced earlier death from prostate cancer and reduced overall survival. The markers in the classifier were found to be associated with a number of key biological processes in prostate cancer metastatic disease progression.
A genomic classifier was developed and validated in a large patient cohort enriched with prostate cancer metastasis patients and a rising PSA that went on to experience metastatic disease. This early metastasis prediction model based on genomic expression in the primary tumor may be useful for identification of aggressive prostate cancer.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Prostate cancers remain indolent in the majority of individuals but behave aggressively in a minority. The molecular basis for this clinical heterogeneity remains incompletely understood. Here we ...characterize a long noncoding RNA termed SChLAP1 (second chromosome locus associated with prostate-1; also called LINC00913) that is overexpressed in a subset of prostate cancers. SChLAP1 levels independently predict poor outcomes, including metastasis and prostate cancer-specific mortality. In vitro and in vivo gain-of-function and loss-of-function experiments indicate that SChLAP1 is critical for cancer cell invasiveness and metastasis. Mechanistically, SChLAP1 antagonizes the genome-wide localization and regulatory functions of the SWI/SNF chromatin-modifying complex. These results suggest that SChLAP1 contributes to the development of lethal cancer at least in part by antagonizing the tumor-suppressive functions of the SWI/SNF complex.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Purpose It is clinically challenging to integrate genomic-classifier results that report a numeric risk of recurrence into treatment recommendations for localized prostate cancer, which are founded ...in the framework of risk groups. We aimed to develop a novel clinical-genomic risk grouping system that can readily be incorporated into treatment guidelines for localized prostate cancer. Materials and Methods Two multicenter cohorts (n = 991) were used for training and validation of the clinical-genomic risk groups, and two additional cohorts (n = 5,937) were used for reclassification analyses. Competing risks analysis was used to estimate the risk of distant metastasis. Time-dependent c-indices were constructed to compare clinicopathologic risk models with the clinical-genomic risk groups. Results With a median follow-up of 8 years for patients in the training cohort, 10-year distant metastasis rates for National Comprehensive Cancer Network (NCCN) low, favorable-intermediate, unfavorable-intermediate, and high-risk were 7.3%, 9.2%, 38.0%, and 39.5%, respectively. In contrast, the three-tier clinical-genomic risk groups had 10-year distant metastasis rates of 3.5%, 29.4%, and 54.6%, for low-, intermediate-, and high-risk, respectively, which were consistent in the validation cohort (0%, 25.9%, and 55.2%, respectively). C-indices for the clinical-genomic risk grouping system (0.84; 95% CI, 0.61 to 0.93) were improved over NCCN (0.73; 95% CI, 0.60 to 0.86) and Cancer of the Prostate Risk Assessment (0.74; 95% CI, 0.65 to 0.84), and 30% of patients using NCCN low/intermediate/high would be reclassified by the new three-tier system and 67% of patients would be reclassified from NCCN six-tier (very-low- to very-high-risk) by the new six-tier system. Conclusion A commercially available genomic classifier in combination with standard clinicopathologic variables can generate a simple-to-use clinical-genomic risk grouping that more accurately identifies patients at low, intermediate, and high risk for metastasis and can be easily incorporated into current guidelines to better risk-stratify patients.
Summary Background Improved clinical predictors for disease progression are needed for localised prostate cancer, since only a subset of patients develop recurrent or refractory disease after ...first-line treatment. Therefore, we undertook an unbiased analysis to identify RNA biomarkers associated with metastatic progression after prostatectomy. Methods Prostate cancer samples from patients treated with radical prostatectomy at three academic institutions were analysed for gene expression by a high-density Affymetrix GeneChip platform, encompassing more than 1 million genomic loci. In a discovery cohort, all protein-coding genes and known long non-coding RNAs were ranked by fold change in expression between tumours that subsequently metastasised versus those that did not. The top ranked gene was then validated for its prognostic value for metastatic progression in three additional independent cohorts. 95% of the gene expression assays were done in a Clinical Laboratory Improvements Amendments certified laboratory facility. All genes were assessed for their ability to predict metastatic progression by receiver-operating-curve area-under-the-curve analyses. Multivariate analyses were done for the primary endpoint of metastatic progression, with variables including Gleason score, preoperative prostate-specific antigen concentration, seminal vesicle invasion, surgical margin status, extracapsular extension, lymph node invasion, and expression of the highest ranked gene. Findings 1008 patients were included in the study: 545 in the discovery cohort and 463 in the validation cohorts. The long non-coding RNA SChLAP1 was identified as the highest-ranked overexpressed gene in cancers with metastatic progression. Validation in three independent cohorts confirmed the prognostic value of SChLAP1 for metastatic progression. On multivariate modelling, SChLAP1 expression (high vs low) independently predicted metastasis within 10 years (odds ratio OR 2·45, 95% CI 1·70–3·53; p<0·0001). The only other variable that independently predicted metastasis within 10 years was Gleason score (8–10 vs 5–7; OR 2·14, 95% CI 1·77–2·58; p<0·0001). Interpretation We identified and validated high SChLAP1 expression as significantly prognostic for metastatic disease progression of prostate cancer. Our findings suggest that further development of SChLAP1 as a potential biomarker, for treatment intensification in aggressive prostate cancer, warrants future study. Funding Prostate Cancer Foundation, National Institutes of Health, Department of Defense, Early Detection Research Network, Doris Duke Charitable Foundation, and Howard Hughes Medical Institute.
Systemic metabolic alterations associated with increased consumption of saturated fat and obesity are linked with increased risk of prostate cancer progression and mortality, but the molecular ...underpinnings of this association are poorly understood. Here, we demonstrate in a murine prostate cancer model, that high-fat diet (HFD) enhances the MYC transcriptional program through metabolic alterations that favour histone H4K20 hypomethylation at the promoter regions of MYC regulated genes, leading to increased cellular proliferation and tumour burden. Saturated fat intake (SFI) is also associated with an enhanced MYC transcriptional signature in prostate cancer patients. The SFI-induced MYC signature independently predicts prostate cancer progression and death. Finally, switching from a high-fat to a low-fat diet, attenuates the MYC transcriptional program in mice. Our findings suggest that in primary prostate cancer, dietary SFI contributes to tumour progression by mimicking MYC over expression, setting the stage for therapeutic approaches involving changes to the diet.
Neuroendocrine prostate cancer (NEPC) may be rising in prevalence as patients with advanced prostate cancer potentially develop resistance to contemporary anti-androgen treatment through a ...neuroendocrine phenotype. While prior studies comparing NEPC and prostatic adenocarcinoma have identified important candidates for targeted therapy, most have relied on few NEPC patients due to disease rarity, resulting in thousands of differentially expressed genes collectively and offering an opportunity for meta-analysis. Moreover, past studies have focused on prototypical NEPC samples with classic immunohistochemistry profiles, whereas there is increasing recognition of atypical phenotypes. In the primary setting, small cell prostatic carcinoma (SCPC) is frequently admixed with adenocarcinomas that may be clonally related, and a minority of SCPCs express markers typical of prostatic adenocarcinoma while rare cases do not express neuroendocrine markers. We derived a meta-signature of prototypical high-grade NEPC, then applied it to develop a classifier of primary SCPC incorporating disease heterogeneity.
Prototypical NEPC samples from 15 patients across 6 frozen tissue microarray datasets were assessed for genes with consistent outlier expression relative to adenocarcinomas. Resulting genes were used to determine subgroups of primary SCPCs (N=16) and high-grade adenocarcinomas (N=16) profiled by exon arrays using formalin-fixed paraffin-embedded (FFPE) material from our institutional archives. A subgroup classifier was developed using differential expression for feature selection, and applied to radical prostatectomy cohorts.
Sixty nine and 375 genes demonstrated consistent outlier expression in at least 80% and 60% of NEPC patients, with close resemblance in expression between NEPC and small cell lung cancer. Clustering by these genes generated 3 subgroups among primary samples from our institution. Nearest centroid classification based on the predominant phenotype from each subgroup (9 prototypical SCPCs, 9 prototypical adenocarcinomas, and 4 atypical SCPCs) achieved a 4.5% error rate by leave-one-out cross-validation. The classifier identified SCPC-like expression in 40% (2/5) of mixed adenocarcinomas and 0.3-0.6% of adenocarcinomas from prospective (4/2293) and retrospective (2/355) radical prostatectomy cohorts, where both SCPC-like retrospective cases subsequently developed metastases.
Meta-analysis generates a robust signature of prototypical high-grade NEPC, and may facilitate development of a primary SCPC classifier based on FFPE material with potential prognostic implications.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Increased expression of the transcription/translation regulatory protein Y-box binding protein-1 (YB-1) is associated with cancer aggressiveness, particularly in breast carcinoma. Here we establish ...that YB-1 levels are elevated in invasive breast cancer cells and correlate with reduced expression of E-cadherin and poor patient survival. Enforced expression of YB-1 in noninvasive breast epithelial cells induced an epithelial-mesenchymal transition (EMT) accompanied by enhanced metastatic potential and reduced proliferation rates. YB-1 directly activates cap-independent translation of messenger RNAs encoding Snail1 and other transcription factors implicated in downregulation of epithelial and growth-related genes and activation of mesenchymal genes. Hence, translational regulation by YB-1 is a restriction point enabling coordinated expression of a network of EMT-inducing transcription factors, likely acting together to promote metastatic spread.
After cisplatin-based neoadjuvant chemotherapy (NAC), 60% of patients with muscle-invasive bladder cancer (MIBC) still have residual invasive disease at radical cystectomy. The NAC-induced biological ...alterations in these cisplatin-resistant tumors remain largely unstudied.
Radical cystectomy samples were available for gene expression analysis from 133 patients with residual invasive disease after cisplatin-based NAC, of whom 116 had matched pre-NAC samples. Unsupervised consensus clustering (CC) was performed and the consensus clusters were investigated for their biological and clinical characteristics. Hematoxylin & Eosin and IHC on tissue microarrays were used to confirm tissue sampling and gene expression analysis.
Established molecular subtyping models proved to be inconsistent in their classification of the post-NAC samples. Unsupervised CC revealed four distinct consensus clusters. The CC1-Basal and CC2-Luminal subtypes expressed genes consistent with a basal and a luminal phenotype, respectively, and were similar to the corresponding established pretreatment molecular subtypes. The CC3-Immune subtype had the highest immune activity, including T-cell infiltration and checkpoint molecule expression, but lacked both basal and luminal markers. The CC4-Scar-like subtype expressed genes associated with wound healing/scarring, although the proportion of tumor cell content in this subtype did not differ from the other subtypes. Patients with CC4-Scar-like tumors had the most favorable prognosis.
This study expands our knowledge on MIBC not responding to cisplatin by suggesting molecular subtypes to understand the biology of these tumors. Although these molecular subtypes imply consequences for adjuvant treatments, this ultimately needs to be tested in clinical trials.
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