Developing biomarkers for improved diagnosis and treatment outcome monitoring of bladder cancer

Tumor-targeting albumin nanoparticles as an efficacious drug delivery system and potential diagnostic tool in non-muscle-invasive bladder cancer therapy

Current intravesical chemotherapy for non-muscle invasive bladder cancer (NMIBC) has limited efficacy due to loss of the instilled agent from urine voiding and the agent's lack of specificity for the tumors. We developed a nanocarrier (txCD47-HNP, ∼100 nm) based on human serum albumin conjugated with a peptide that targets the cluster of differentiation 47 receptor overexpressed on bladder cancer (BC) cells. The IC₅₀ of gemcitabine elaidate (GEM) loaded in the txCD47-HNP was almost an order of magnitude lower than that of free GEM. In a mouse orthotopic BC model, GEM loaded in txCD47-HNP effectively reduced the tumor burden. Tumor cells in BC patients' urine can also be targeted by fluorescence-labeled txCD47-HNP resulting in >83 % of the cells exhibiting fluorescence. Thus, txCD47-HNP can potentially be a theranostic agent in NMIBC management by serving as a targeted drug delivery vehicle as well as an alternative to urine cytology.

Multi-omics reveals novel prognostic implication of SRC protein expression in bladder cancer and its correlation with immunotherapy response

PURPOSE

This study aims to identify potential prognostic biomarkers of bladder cancer (BCa) based on large-scale multi-omics data and investigate the role of SRC in improving predictive outcomes for BCa patients and those receiving immune checkpoint therapies (ICTs).

METHODS

Large-scale multi-comic data were enrolled from the Cancer Proteome Atlas, the Cancer Genome Atlas and gene expression omnibus based on machining-learning methods. Immune infiltration, survival and other statistical analyses were implemented using R software in cancers (n = 12,452). The predictive value of SRC was performed in 81 BCa patients receiving ICT from aa validation cohort (n = 81).

RESULTS

Landscape of novel candidate prognostic protein signatures of BCa patients was identified. Differential BECLIN, EGFR, PKCALPHA, ANNEXIN1, AXL and SRC expression significantly correlated with the outcomes for BCa patients from multiply cohorts (n = 906). Notably, risk score of the integrated prognosis-related proteins (IPRPs) model exhibited high diagnostic accuracy and consistent predictive ability (AUC = 0.714). Besides, we tested the clinical relevance of baseline SRC protein and mRNA expression in two independent confirmatory cohorts (n = 566) and the prognostic value in pan-cancers. Then, we found that elevated SRC expression contributed to immunosuppressive microenvironment mediated by immune checkpoint molecules of BCa and other cancers. Next, we validated SRC expression as a potential biomarker in predicting response to ICT in 81 BCa patient from FUSCC cohort, and found that expression of SRC in the baseline tumour tissues correlated with improved survival benefits, but predicts worse ICT response.

CONCLUSION

This study first performed the large-scale multi-omics analysis, distinguished the IPRPs (BECLIN, EGFR, PKCALPHA, SRC, ANNEXIN1 and AXL) and revealed novel prediction model, outperforming the currently traditional prognostic indicators for anticipating BCa progression and better clinical strategies. Additionally, this study provided insight into the importance of biomarker SRC for better prognosis, which may inversely improve predictive outcomes for patients receiving ICT and enable patient selection for future clinical treatment.

Shedding Light on Bladder Cancer Diagnosis in Urine

Blue light cystoscopy (BLC) is the most recent clinical approach in the detection and diagnosis of bladder cancer, a common type of cancer with a high rate of recurrence. Representing a significant advance over previous approaches, this photodynamic diagnostic technique uses a photosensitiser prodrug as an adjunct to white light cystoscopy to enhance the in vivo detection of malignant tissues in the bladder based on their distinctive fluorescence. Whilst it does improve detection rates, BLC remains an invasive and costly procedure. Meanwhile, a variety of noninvasive urine detection methods and related microdevices have been developed, none of which have yet entered routine clinical use due to unsatisfactory sensitivity. Following a brief description of the current approaches and their limitations, we provide here a systematic review of a newer niche research aiming to develop a noninvasive adaptation of photodynamic diagnosis. The research to date surrounding the ex situ use of photosensitiser prodrugs for urinary diagnosis of bladder cancer is also discussed.

NMR-derived targeted serum metabolic biomarkers appraisal of bladder cancer: A pre- and post-operative evaluation

With high morbidity and mortality, urinary bladder cancer (BC) ranks fifth among common cancers globally. The inherent limitations of urine cytology and cystoscopy, and marginal enhancements in the rate of survival promt us to develop surrogate serum based metabolic biomarkers of screening, identification, and follow-up protocols of management for BC patients. Earlier, we exhibited that abnormal expression levels of dimethylamine (DMA), malonate, lactate, glutamine, histidine, and valine in serum may be used as signature metabolites to differentiate BC from healthy controls (HC) (J. Proteome Res. 2013; 12(12):5839-50). Here we further gauge and validate these observations by comparing pre-operative to post-operative follow-up BC patients. This study was conducted on 160 sera samples involving HC (n = 52), pre-operative (n = 55) and post-operative (n = 53) BC cases. ¹H nuclear magnetic resonance (NMR) spectroscopy was used to generate serum metabolic profiles and to gauge aberrantly expressed metabolites. The targeted metabolomic approach revealed that the expression levels of these signature metabolites were progressively and significantly decreased in post-operative follow-up at the interval of 30, 60, and 90 days compared to pre-operative BC sera samples and were maintained at HC levels. Serum metabolic biomarkers appear to be an inspiring and least-invasive tactic for detection and prognosticating BC patient follow-up.

Three serum metabolite signatures for diagnosing low-grade and high-grade bladder cancer

To address the shortcomings of cystoscopy and urine cytology for detecting and grading bladder cancer (BC), ultrahigh performance liquid chromatography (UHPLC) coupled with Q-TOF mass spectrometry in conjunction with univariate and multivariate statistical analyses was employed as an alternative method for the diagnosis of BC. A series of differential serum metabolites were further identified for low-grade(LG) and high-grade(HG) BC patients, suggesting metabolic dysfunction in malignant proliferation, immune escape, differentiation, apoptosis and invasion of cancer cells in BC patients. In total, three serum metabolites including inosine, acetyl-N-formyl-5-methoxykynurenamine and PS(O-18:0/0:0) were selected by binary logistic regression analysis, and receiver operating characteristic (ROC) test based on their combined use for HG BC showed that the area under the curve (AUC) was 0.961 in the discovery set and 0.950 in the validation set when compared to LG BC. Likewise, this composite biomarker panel can also differentiate LG BC from healthy controls with the AUC of 0.993 and 0.991 in the discovery and validation set, respectively. This finding suggested that this composite serum metabolite signature was a promising and less invasive classifier for probing and grading BC, which deserved to be further investigated in larger samples.

A panel of three markers hyper- and hypomethylated in urine sediments accurately predicts bladder cancer recurrence

PURPOSE

The high risk of recurrence after transurethral resection of bladder tumor of nonmuscle invasive disease requires lifelong treatment and surveillance. Changes in DNA methylation are chemically stable, occur early during tumorigenesis, and can be quantified in bladder tumors and in cells shed into the urine. Some urine markers have been used to help detect bladder tumors; however, their use in longitudinal tumor recurrence surveillance has yet to be established.

EXPERIMENTAL DESIGN

We analyzed the DNA methylation levels of six markers in 368 urine sediment samples serially collected from 90 patients with noninvasive urothelial carcinoma (Tis, Ta, T1; grade low-high). The optimum marker combination was identified using logistic regression with 5-fold cross-validation, and validated in separate samples.

RESULTS

A panel of three markers discriminated between patients with and without recurrence with the area under the curve of 0.90 [95% confidence interval (CI), 0.86-0.92] and 0.95 (95% CI, 0.90-1.00), sensitivity and specificity of 86%/89% (95% CI, 74%-99% and 81%-97%) and 80%/97% (95% CI, 60%-96% and 91%-100%) in the testing and validation sets, respectively. The three-marker DNA methylation test reliably predicted tumor recurrence in 80% of patients superior to cytology (35%) and cystoscopy (15%) while accurately forecasting no recurrence in 74% of patients that scored negative in the test.

CONCLUSIONS

Given their superior sensitivity and specificity in urine sediments, a combination of hyper- and hypomethylated markers may help avoid unnecessary invasive exams and reveal the importance of DNA methylation in bladder tumorigenesis.

Low- and high-grade bladder cancer determination via human serum-based metabolomics approach

To address the shortcomings of urine cytology and cystoscopy for probing and grading urinary bladder cancer (BC), we applied (1)H nuclear magnetic resonance (NMR) spectroscopy as a surrogate method for the identification of BC. This study includes 99 serum samples comprising low-grade (LG; n = 36) and high-grade (HG; n = 31) BC as well as healthy controls (HC; n = 32). (1)H NMR-derived serum data were analyzed using orthogonal partial least-squares discriminant analysis (OPLS-DA). OPLS-DA-derived model validity was confirmed using an internal and external cross-validation. Internal validation was performed using the initial samples (n = 99) data set. External validation was performed on a new batch of suspected BC patients (n = 106) through a double-blind study. Receiver operating characteristic (ROC) curve analysis was also performed. OPLS-DA-derived serum metabolomics (six biomarkers, ROC; 0.99) were able to discriminate 95% of BC cases with 96% sensitivity and 94% specificity when compared to HC. Likewise (three biomarkers, ROC; 0.99), 98% of cases of LG were able to differentiate from HG with 97% sensitivity and 99% specificity. External validation reveals comparable results to the internal validation. (1)H NMR-based serum metabolic screening appears to be a promising and less invasive approach for probing and grading BC in contrast to the highly invasive and painful cystoscopic approach for BC detection.

Genetic variations in micro-RNA biogenesis genes and clinical outcomes in non-muscle-invasive bladder cancer

Micro-RNAs (miRNAs) are small non-coding RNA molecules, which can act as either oncogenes or tumor suppressors. Dysregulated expression of miRNA genes have been implicated in the development of many different cancers. We hypothesize that genetic variations in miRNA biogenesis genes may be associated with the prognosis of bladder cancer. We genotyped 76 single nucleotide polymorphisms (SNPs) in eight miRNA biogenesis genes in 421 patients with non-muscle-invasive bladder cancer (NMIBC). We analyzed the associations of SNPs with recurrence and progression in all patients as well as stratified by treatment: transurethral resection (TUR) alone or TUR plus intravesical bacillus Calmette-Guérin (BCG) instillation. Two SNPs were significantly associated with tumor recurrence in TUR only subgroup after adjustment for multiple comparisons (Q < 0.1). The most significant SNP was rs197412 in DDX20: the variant allele conferred a decreased risk of recurrence [hazard ratio (HR) = 0.58, 95% confidence interval (95% CI) = 0.40-0.82]. This SNP was validated in a separate group of 586 NMIBC patients and the pooled HR was 0.62 (95% CI = 0.48-0.81, P < 0.001). Two linked SNPs (rs2073778 and rs720012) in DGCR8 showed significant association with tumor progression (HR = 4.00, 95% CI = 1.53-10.46, P = 0.005). A strong gene-dosage effect was observed with higher risk for tumor recurrence and progression with increasing number of unfavorable genotypes. Haplotype and survival tree analyses further characterized the association of miRNA-related SNPs with tumor recurrence and progression. Taken together, our results indicate that genetic variants in miRNA biogenesis pathway may influence bladder cancer clinical outcome in NMIBC patients.

Germline prognostic markers for urinary bladder cancer: obstacles and opportunities

Urinary bladder cancer is a heterogeneous disease with diverse genetic and environmental risk factors that can influence disease risk or clinical course for recurrence, progression, and survival. Therefore, identification of these factors is paramount for disease prevention and optimal clinical management of bladder cancer patients. Of particular interest is the need to identify molecular biomarkers that can give accurate assessment of tumor biological potential and to predict treatment response. Recent advances in molecular biology, cytogenetic, and genomic research have spurred discovery efforts for novel genetic, epigenetic, and proteomic biomarkers that are prognostic for cancer. This review focuses on some of the important germ line polymorphisms found to be correlated with clinical outcomes in bladder cancer. So far, most of the identified candidate loci were based on prior knowledge of pathogenesis and had not been validated for clinical applications. The future challenges are to analyze the wealth of information from whole-genome studies, to understand the underlying biological mechanisms of these associations, the network of gene-gene and gene-environment interactions, and to apply these markers for the identification of high-risk population for targeted, personalized therapy.

Discovery of potential bladder cancer biomarkers by comparative urine proteomics and analysis

OBJECTIVE

We searched for bladder tumor markers by analyzing urine samples from patients with bladder cancer and from normal controls.

METHODS

Proteins in urine samples of patients with bladder cancer and with normal controls were systematically examined by 2-dimensional electrophoresis combined with matrix-assisted laser desorption ionization time-of-flight mass spectrometry. The expression of the protein apolipoprotein A-I (apoA-I) was confirmed by Western blot analysis and further evaluated.

RESULTS

We successfully obtained the 2-dimensional electrophoresis gel maps of urinary proteins in patients with bladder cancer and in normal controls. Thirty differentially expressed protein spots were successfully matched by matrix-assisted laser desorption ionization time-of-flight mass spectrometry. Combined with the SWISS-PROT database, only 14 proteins (beta-2-microglobulin, fatty acid-binding protein adipocyte, gelsolin, isoform 1 of gelsolin, myoglobin, isoform 2 of fibrinogen alpha chain, apoA-I, prostaglandin D(2) synthase 21 kDa [brain], protein AMBP, transthyretin, keratin type II cytoskeletal 1, type II cytoskeletal 8, putative uncharacterized protein ALB, putative uncharacterized protein MASP2 [fragment]) were identified, including 2 putative proteins. Furthermore, apoA-I was confirmed by Western blot analysis, and the high level of apoA-I was found in urine samples from patients with bladder tumors compared with normal controls.

CONCLUSIONS

Analysis of urinary proteome may be a feasible, noninvasive, and efficient strategy for searching for potential bladder tumor biomarkers. A significant relationship of expressed apoA-I was established between bladder cancer and normal controls. We concluded that 14 differential spots included the apoA-I and would be potential urinary biomarkers for the diagnosis and surveillance of bladder cancer.

Epigenetic alterations in bladder cancer and their potential clinical implications

Urothelial carcinoma (UC), the most common type of bladder cancer, is one of the most expensive malignancies to treat due to its high rate of recurrence. The characterization of the genetic alterations associated with UC has revealed the presence of two mutually exclusive molecular pathways along which distinct genetic abnormalities contribute to the formation of invasive and noninvasive tumors. Here, we focus on the epigenetic alterations found in UC, including the presence of an epigenetic field defect throughout bladders with tumors. A distinct hypomethylation pattern was found in noninvasive tumors, whereas widespread hypermethylation was found in invasive tumors, indicating the two pathways given rise to two tumor types also differ epigenetically. Since certain epigenetic alterations precede histopathological changes, they can serve as excellent markers for the development of diagnostic, prognostic, and surveillance tools. In addition, their dynamic nature and reversibility with pharmacological interventions open new and exciting avenues for therapies. The epigenetic abnormalities associated with UC would make it an excellent target for epigenetic therapy, which is currently approved for the treatment of a few hematological malignancies. Future research is needed to address efficacy and potential toxicity issues before it can be implemented as a therapeutic strategy for solid tumors.

Biomarkers for prognosis and treatment selection in advanced bladder cancer patients

PURPOSE OF REVIEW

Patients with locally 'advanced' or muscle invasive bladder cancer have higher mortality rates than patients with nonmuscle invasive ('superficial') bladder cancer. Biomarkers can stratify clinical outcomes and thus promise to more accurately prognosticate and thus help assign patients to the appropriate treatments. The aim of this review is to summarize biomarker developments in the past year and to discuss their implications in prognosis and treatment selection in locally advanced bladder cancer.

RECENT FINDINGS

Prognostic biomarkers for bladder cancer are identified at the DNA, RNA and/or protein levels. Some are new markers, whereas others are established markers with new roles in bladder cancer. Markers can report on the risk of disease recurrence or metastasis, or treatment responsiveness and thus are useful in determining 'who to treat' and 'what to treat with'.

SUMMARY

The list of biomarkers for prognosis and treatment selection for advanced bladder cancer is growing. For most, their clinical relevance is unclear due to their lack of validation in external datasets. MicroRNAs and new techniques including next-generation sequencing offer additional opportunities for biomarker discovery, validation, and clinical applications.

Assessment of high-throughput high-resolution MALDI-TOF-MS of urinary peptides for the detection of muscle-invasive bladder cancer

PURPOSE

There is a need for better biomarkers to both detect bladder cancer and distinguish muscle-invasive (stage T2+) from non-invasive (stage Ta/T1) disease. We assess whether MALDI-TOF-MS of the urine peptidome can achieve this.

EXPERIMENTAL DESIGN

We analysed urine from 751 patients with bladder cancer and 127 patients without bladder cancer. Endogenous peptide profiling was performed using a Bruker Ultraflextreme MALDI-TOF-MS.

RESULTS

Significant differences were seen between the spectra of urine from patients with and without T2+ disease. Albumin, total protein and haematuria were also elevated in T2+ patients. Haematuria was detected in 39% of patients with Ta/T1 disease and in 77% of patients with T2+ disease. Class prediction models based on MALDI data produced areas under receiver-operator characteristic curves of up to 0.76 but did not significantly outperform a model based on total protein alone. Many peptides significantly associated with invasive disease are fragments of abundant blood proteins and are also associated with haematuria.

CONCLUSIONS AND CLINICAL RELEVANCE

Microscopic haematuria is strongly associated with invasive disease; even traces of blood/plasma strongly influence the urinary peptidome. This needs to be taken into consideration when using 'omic' methods to search for urinary biomarkers as blood proteins may give false-positive results.

Cancer biomarker discovery: Opportunities and pitfalls in analytical methods

Many diseases result in specific and characteristic changes in the chemical and biochemical profiles of biological fluids and tissues prior to development of clinical symptoms. These changes are often useful diagnostic and prognostic biomarkers. Identifying biomarkers that can be used for the early detection of cancer will result in more efficient treatments, reduction in suffering, and lower mortality rates. An ideal screening test should be non-invasive with high sensitivity and specificity. Proteomic and metabolomic analyses of biological samples can reveal changes in abundance levels of metabolites and proteins that when validated and confirmed through clinical trials can function as clinical tests for early detection, diagnosis, monitoring disease progression, and predicting therapeutic response. While the past decade has seen great advancements in proteomics and metabolomics research producing potential biomarkers for cancer, most of the identified biomarkers have failed to replace existing clinical tests. To become a clinically approved test, a potential biomarker should be confirmed and validated using hundreds of specimens and should be reproducible, specific, and sensitive. A search of the scientific and medical literature indicates that many studies report the discovery of potential biomarkers without proper validation and/or they do not meet the above criteria. In this manuscript, we will discuss the successes and the pitfalls of biomarker research and comment on study and experimental design, which in most cases is lacking, resulting in suboptimal biomarkers.

Bioinformatic-driven search for metabolic biomarkers in disease

The search and validation of novel disease biomarkers requires the complementary power of professional study planning and execution, modern profiling technologies and related bioinformatics tools for data analysis and interpretation. Biomarkers have considerable impact on the care of patients and are urgently needed for advancing diagnostics, prognostics and treatment of disease. This survey article highlights emerging bioinformatics methods for biomarker discovery in clinical metabolomics, focusing on the problem of data preprocessing and consolidation, the data-driven search, verification, prioritization and biological interpretation of putative metabolic candidate biomarkers in disease. In particular, data mining tools suitable for the application to omic data gathered from most frequently-used type of experimental designs, such as case-control or longitudinal biomarker cohort studies, are reviewed and case examples of selected discovery steps are delineated in more detail. This review demonstrates that clinical bioinformatics has evolved into an essential element of biomarker discovery, translating new innovations and successes in profiling technologies and bioinformatics to clinical application.