AI-guided histopathology predicts brain metastasis in lung cancer patients.

Brain metastases can occur in nearly half of patients with early and locally advanced (stage I-III) non-small cell lung cancer (NSCLC). There are no reliable histopathologic or molecular means to identify those who are likely to develop brain metastases. We sought to determine if deep learning (DL) could be applied to routine H&E-stained primary tumor tissue sections from stage I-III NSCLC patients to predict the development of brain metastasis. Diagnostic slides from 158 patients with stage I-III NSCLC followed for at least 5 years for the development of brain metastases (Met+, 65 patients) versus no progression (Met-, 93 patients) were subjected to whole-slide imaging. Three separate iterations were performed by first selecting 118 cases (45 Met+, 73 Met-) to train and validate the DL algorithm, while 40 separate cases (20 Met+, 20 Met-) were used as the test set. The DL algorithm results were compared to a blinded review by four expert pathologists. The DL-based algorithm was able to distinguish the eventual development of brain metastases with an accuracy of 87% (p < 0.0001) compared with an average of 57.3% by the four pathologists and appears to be particularly useful in predicting brain metastases in stage I patients. The DL algorithm appears to focus on a complex set of histologic features. DL-based algorithms using routine H&E-stained slides may identify patients who are likely to develop brain metastases from those who will remain disease free over extended (>5 year) follow-up and may thus be spared systemic therapy. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Do Black NonHispanic Men Produce Less Prostate Specific Antigen in Benign Prostate Tissue or Cancer Compared to White NonHispanic Men with Gleason Score 6 (Grade Group 1) Prostate Cancer?

PURPOSE: We evaluated prostate specific antigen production by benign prostate tissue and Gleason score 3+3=6 (Grade Group 1) prostate cancer in black and white nonHispanic men. MATERIALS AND METHODS: We used Gleason score 3+3=6 (Grade Group 1) cases to assess prostate specific antigen production by benign prostate tissue in cases with low volume cancer that did not influence prostate specific antigen and in those with high volume cancer in which gland weight did not influence prostate specific antigen. We then created age, prostate specific antigen and prostate weight adjusted cohorts to demonstrate tumor volume per 1 ng/ml prostate specific antigen and 1 µg prostate specific antigen mass. Prostate specific antigen density and prostate specific antigen mass density were used to adjust for prostate weight. RESULTS: Comparison of 58 black and 301 white men with low volume cancer demonstrated equal prostate specific antigen production by benign prostate tissue. Comparison of 30 black and 75 white men with high volume cancer indicated that prostate specific antigen was being driven by cancer volume, with lower prostate specific antigen production in black men. In the cohort of 54 black and 134 white men matched by age, prostate specific antigen and prostate weight, tumor volume per 1 ng/ml prostate specific antigen or 1 µg prostate specific antigen mass adjusted for prostate weight was 25% and 26% higher in black men, respectively. CONCLUSIONS: Benign prostate tissue produces equal amounts of prostate specific antigen in black and white men. Gleason score 3+3=6 (Grade Group 1) prostate cancer produces less prostate specific antigen in black men. These data should be considered for lowering prostate specific antigen and its derivatives in determining biopsy thresholds and for adjusting values for active surveillance criteria in black men.

Use of Artificial Intelligence and Machine Learning Algorithms with Gene Expression Profiling to Predict Recurrent Nonmuscle Invasive Urothelial Carcinoma of the Bladder.

PURPOSE: Due to the high recurrence risk of nonmuscle invasive urothelial carcinoma it is crucial to distinguish patients at high risk from those with indolent disease. In this study we used a machine learning algorithm to identify the genes in patients with nonmuscle invasive urothelial carcinoma at initial presentation that were most predictive of recurrence. We used the genes in a molecular signature to predict recurrence risk within 5 years after transurethral resection of bladder tumor. MATERIALS AND METHODS: Whole genome profiling was performed on 112 frozen nonmuscle invasive urothelial carcinoma specimens obtained at first presentation on Human WG-6 BeadChips (Illumina®). A genetic programming algorithm was applied to evolve classifier mathematical models for outcome prediction. Cross-validation based resampling and gene use frequencies were used to identify the most prognostic genes, which were combined into rules used in a voting algorithm to predict the sample target class. Key genes were validated by quantitative polymerase chain reaction. RESULTS: The classifier set included 21 genes that predicted recurrence. Quantitative polymerase chain reaction was done for these genes in a subset of 100 patients. A 5-gene combined rule incorporating a voting algorithm yielded 77% sensitivity and 85% specificity to predict recurrence in the training set, and 69% and 62%, respectively, in the test set. A singular 3-gene rule was constructed that predicted recurrence with 80% sensitivity and 90% specificity in the training set, and 71% and 67%, respectively, in the test set. CONCLUSIONS: Using primary nonmuscle invasive urothelial carcinoma from initial occurrences genetic programming identified transcripts in reproducible fashion, which were predictive of recurrence. These findings could potentially impact nonmuscle invasive urothelial carcinoma management.

Highly scalable, uniform, and sensitive biosensors based on top-down indium oxide nanoribbons and electronic enzyme-linked immunosorbent assay.

Nanostructure field-effect transistor (FET) biosensors have shown great promise for ultra sensitive biomolecular detection. Top-down assembly of these sensors increases scalability and device uniformity but faces fabrication challenges in achieving the small dimensions needed for sensitivity. We report top-down fabricated indium oxide (In2O3) nanoribbon FET biosensors using highly scalable radio frequency (RF) sputtering to create uniform channel thicknesses ranging from 50 to 10 nm. We combine this scalable sensing platform with amplification from electronic enzyme-linked immunosorbent assay (ELISA) to achieve high sensitivity to target analytes such as streptavidin and human immunodeficiency virus type 1 (HIV-1) p24 proteins. Our approach circumvents Debye screening in ionic solutions and detects p24 protein at 20 fg/mL (about 250 viruses/mL or about 3 orders of magnitude lower than commercial ELISA) with a 35% conduction change in human serum. The In2O3 nanoribbon biosensors have 100% device yield and use a simple 2 mask photolithography process. The electrical properties of 50 In2O3 nanoribbon FETs showed good uniformity in on-state current, on/off current ratio, mobility, and threshold voltage. In addition, the sensors show excellent pH sensitivity over a broad range (pH 4 to 9) as well as over the physiological-related pH range (pH 6.8 to 8.2). With the demonstrated sensitivity, scalability, and uniformity, the In2O3 nanoribbon sensor platform makes great progress toward clinical testing, such as for early diagnosis of acquired immunodeficiency syndrome (AIDS).

Circulating tumor cell telomerase activity as a prognostic marker for overall survival in SWOG 0421: a phase III metastatic castration resistant prostate cancer trial.

Circulating tumor cells (CTC) are promising biomarkers in metastatic castration resistant prostate cancer (mCRPC), and telomerase activity (TA) is a recognized cancer marker. Therefore, we hypothesized that CTC TA may be prognostic of overall survival (OS) in mCRPC. To test this, we used a novel Parylene-C slot microfilter to measure live CTC TA in S0421, a phase III SWOG-led therapeutic trial. Blood samples underwent CTC capture and TA measurement by microfilter, as well as parallel enumeration by CellSearch (Janssen/J&J). Cox regression was used to assess baseline (pre-treatment) TA versus OS, and recursive partitioning was used to explore potential prognostic subgroups and to generate Kaplan-Meier (KM) OS curves. Samples were obtained from 263 patients and generated 215 TA measures. In patients with baseline CTC count ≥5 (47% of patients), higher CTC TA was associated with hazard ratio 1.14 (p = 0.001) for OS after adjusting for other clinical covariates including CTC counts and serum PSA at study entry. Recursive partitioning identified new candidate risk groups with KM OS curve separation based on CTC counts and TA. Notably, in men with an intermediate range baseline CTC count (6-54 CTCs/7.5 ml), low versus high CTC TA was associated with median survival of 19 versus 12 months, respectively (p = 0.009). Baseline telomerase activity from CTCs live-captured on a new slot microfilter is the first CTC-derived candidate biomarker prognostic of OS in a large patient subgroup in a prospective clinical trial. CTC telomerase activity thus merits further study and validation as a step towards molecular CTC-based precision cancer management.

Circulating tumor cells: from bench to bedside.

Circulating tumor cells (CTCs) represent a surrogate biomarker of hematogenous metastases. In recent years, their detection has gained increasing interest. There is ample evidence regarding the ability to detect CTCs and their prognostic relevance, but their demonstrated predictive value in therapeutic response monitoring is clinically even more meaningful. Many clinical trials in the early and metastatic cancer setting now include CTCs as a monitoring parameter, and numerous translational studies attempting their molecular characterization are under way. There has been great progress in defining the clinical importance of CTCs, and it now seems likely that we may expect wider implementation of CTCs as a diagnostic oncology tool to monitor therapeutic response in real time. Novel technologies may further facilitate molecular characterization of CTCs and development of novel therapeutic targets, possibly leading to more powerful treatment strategies for cancer patients. As the detection and evaluation of CTCs are becoming an increasingly important diagnostic and prognostic tool, the goal of this review is to communicate the knowledge obtained through analysis of primary tumors and CTCs to oncologists and medical specialists in managing patients with cancer.

Update for the practicing pathologist: The International Consultation On Urologic Disease-European association of urology consultation on bladder cancer.

The International Consultations on Urological Diseases are international consensus meetings, supported by the World Health Organization and the Union Internationale Contre le Cancer, which have occurred since 1981. Each consultation has the goal of convening experts to review data and provide evidence-based recommendations to improve practice. In 2012, the selected subject was bladder cancer, a disease which remains a major public health problem with little improvement in many years. The proceedings of the 2nd International Consultation on Bladder Cancer, which included a 'Pathology of Bladder Cancer Work Group,' have recently been published; herein, we provide a summary of developments and consensus relevant to the practicing pathologist. Although the published proceedings have tackled a comprehensive set of issues regarding the pathology of bladder cancer, this update summarizes the recommendations regarding selected issues for the practicing pathologist. These include guidelines for classification and grading of urothelial neoplasia, with particular emphasis on the approach to inverted lesions, the handling of incipient papillary lesions frequently seen during surveillance of bladder cancer patients, descriptions of newer variants, and terminology for urine cytology reporting.

Significance of lymphovascular invasion in organ-confined, node-negative urothelial cancer of the bladder: data from the prospective p53-MVAC trial.

OBJECTIVES: To investigate the association between lymphovascular invasion (LVI) and clinical outcome in organ-confined, node-negative urothelial cancer of the bladder (UCB) in a post hoc analysis of a prospective clinical trial. To explore the effect of adjuvant chemotherapy with methotrexate, vinblastine, doxorubicin, and cisplatin (MVAC) on outcome in the subset of patients whose tumours exhibited LVI. PATIENTS AND METHODS: Surgical and tumour factors were extracted from the operative and pathology reports of 499 patients who had undergone radical cystectomy (RC) for pT1-T2 N0 UCB in the p53-MVAC trial (Southwest Oncology Group 4B951/NCT00005047). The presence or absence of LVI was determined by pathological examination of transurethral resection or RC specimens. Variables were examined in univariate and multivariate Cox proportional hazards models for associations with time to recurrence (TTR) and overall survival (OS). RESULTS: Among 499 patients with a median follow-up of 4.9 years, a subset of 102 (20%) had LVI-positive tumours. Of these, 34 patients had pT1 and 68 had pT2 disease. LVI was significantly associated with TTR with a hazard ratio (HR) of 1.78 [95% confidence interval (CI) 1.15-2.77; number of events (EV) 95; P = 0.01) and with OS with a HR of 2.02 (95% CI 1.31-3.11; EV 98; P = 0.001) after adjustment for pathological stage. Among 27 patients with LVI-positive tumours who were randomised to receive adjuvant chemotherapy, receiving MVAC was not significantly associated with TTR (HR 0.70, 95% CI 0.16-3.17; EV 7; P = 0.65) or with OS (HR 0.45, 95% CI 0.11-1.83; EV 9; P = 0.26). CONCLUSIONS: Our post hoc analysis of the p53-MVAC trial revealed an association between LVI and shorter TTR and OS in patients with pT1-T2N0 disease. The analysis did not show a statistically significant benefit of adjuvant MVAC chemotherapy in patients with LVI, although a possible benefit was not excluded.

Variability in surgical quality in a phase III clinical trial of radical cystectomy in patients with organ-confined, node-negative urothelial carcinoma of the bladder.

BACKGROUND AND OBJECTIVES: Previous studies have shown that variability in surgical technique can affect the outcomes of cooperative group trials. We analyzed measures of surgical quality and clinical outcomes in patients enrolled in the p53-MVAC trial. METHODS: We performed a post-hoc analysis of patients with pT1-T2N0M0 urothelial carcinoma of the bladder following radical cystectomy (RC) and bilateral pelvic and iliac lymphadenectomy (LND). Measures of surgical quality were examined for associations with time to recurrence (TTR) and overall survival (OS). RESULTS: We reviewed operative and/or pathology reports for 440 patients from 35 sites. We found that only 31% of patients met all suggested trial eligibility criteria of having ≥15 lymph nodes identified in the pathologic specimen (LN#) and having undergone both extended and presacral LND. There was no association between extent of LND, LN#, or presacral LND and TTR or OS after adjustment for confounders and multiple testing. CONCLUSIONS: We demonstrated that there was substantial variability in surgical technique within a cooperative group trial. Despite explicit entry criteria, many patients did not undergo per-protocol LNDs. While outcomes were not apparently affected, it is nonetheless evident that careful attention to study design and quality monitoring will be critical to successful future trials.

Is Fragmentation of Prostate Core Biopsies Inevitable? A Quality Improvement Initiative.

CONTEXT.­: Core biopsies are standard of care for diagnosis and surveillance of prostate cancer. Fragmentation makes numeric assessment of cancer challenging and increases risk of inaccurate staging with direct implications on management. OBJECTIVE.­: To determine factors responsible for fragmentation at our institution. DESIGN.­: Prostate core biopsies performed at 2 hospital sites during 1 week were prospectively identified. Biopsies were received in multipart formalin jars, either mounted on a nonadherent dressing pad (Telfa, Medtronic Inc) or freely suspended, and grossed by experienced pathologists' assistants. Fragmentation was defined as the difference between number of cores sent by the clinician and number of cores counted by the pathologist on microscopy. RESULTS.­: Forty-six cases (15 benign; 31 malignant) with 535 specimen jars were identified of which 309 of 535 (57.8%) had >1 biopsy core per jar; 230 of 535 (43%) were received mounted on Telfa and 185 of 535 (34.6%) had histologic evidence of adenocarcinoma. Overall fragmentation rate was 157 of 535 (29.3%). Lowest fragmentation rate was seen when 1 core was submitted per jar regardless of mounting method (31 of 226; 14% for single versus 126 of 309; 41% for >1 per jar; P < .001). For 1 Telfa-mounted core, rate of fragmentation was 5 of 18 (27.8%) versus 26 of 203 (12.8%) when unmounted (P = .24). Significant increase in fragmentation of Telfa-mounted cores was seen when there were 3 per jar (32 of 70; 46% mounted fragmented versus 9 of 47; 19% unmounted fragmented specimens; P = .01). CONCLUSIONS.­: Submission of >1 biopsy core per jar and use of Telfa for mounting are associated with increased fragmentation. We recommend limiting submission to 1 core per jar and avoid mounting on Telfa pads.

Impact of Stain Variation and Color Normalization for Prognostic Predictions in Pathology.

In recent years, deep neural networks (DNNs) have demonstrated remarkable performance in pathology applications, potentially even outperforming expert pathologists due to their ability to learn subtle features from large datasets. One complication in preparing digital pathology datasets for DNN tasks is variation in tinctorial qualities. A common way to address this is to perform stain normalization on the images. In this study, we show that a well-trained DNN model trained on one batch of histological slides failed to generalize to another batch prepared at a different time from the same tissue blocks, even when stain normalization methods were applied. This study used sample data from a previously reported DNN that was able to identify patients with early stage non-small cell lung cancer (NSCLC) whose tumors did and did not metastasize, with high accuracy, based on training and then testing of digital images from H&E stained primary tumor tissue sections processed at the same time. In this study we obtained a new series of histologic slides from the adjacent recuts of same tissue blocks processed in the same lab but at a different time. We found that the DNN trained on the either batch of slides/images was unable to generalize and failed to predict progression in the other batch of slides/images (AUCcross-batch = 0.52 - 0.53 compared to AUCsame-batch = 0.74 - 0.81). The failure to generalize did not improve even when the tinctorial difference correction were made through either traditional color-tuning or stain normalization with the help of a Cycle Generative Adversarial Network (CycleGAN) process. This highlights the need to develop an entirely new way to process and collect consistent microscopy images from histologic slides that can be used to both train and allow for the general application of predictive DNN algorithms.

Length-scale study in deep learning prediction for non-small cell lung cancer brain metastasis.

Deep learning-assisted digital pathology has demonstrated the potential to profoundly impact clinical practice, even surpassing human pathologists in performance. However, as deep neural network (DNN) architectures grow in size and complexity, their explainability decreases, posing challenges in interpreting pathology features for broader clinical insights into physiological diseases. To better assess the interpretability of digital microscopic images and guide future microscopic system design, we developed a novel method to study the predictive feature length-scale that underpins a DNN's predictive power. We applied this method to analyze a DNN's capability in predicting brain metastasis from early-stage non-small-cell lung cancer biopsy slides. This study quantifies DNN's attention for brain metastasis prediction, targeting features at both the cellular scale and tissue scale in H&E-stained histological whole slide images. At the cellular scale, the predictive power of DNNs progressively increases with higher resolution and significantly decreases when the resolvable feature length exceeds 5 microns. Additionally, DNN uses more macro-scale features associated with tissue architecture and is optimized when assessing visual fields greater than 41 microns. Our study computes the length-scale requirements for optimal DNN learning on digital whole-slide microscopic images, holding the promise to guide future optical microscope designs in pathology applications and facilitating downstream deep learning analysis.

Combination of molecular alterations and smoking intensity predicts bladder cancer outcome: a report from the Los Angeles Cancer Surveillance Program.

BACKGROUND: Traditional single-marker and multimarker molecular profiling approaches in bladder cancer do not account for major risk factors and their influence on clinical outcome. This study examined the prognostic value of molecular alterations across all disease stages after accounting for clinicopathological factors and smoking, the most common risk factor for bladder cancer in the developed world, in a population-based cohort. METHODS: Primary bladder tumors from 212 cancer registry patients (median follow-up, 13.2 years) were immunohistochemically profiled for Bax, caspase-3, apoptotic protease-activating factor 1 (Apaf-1), Bcl-2, p53, p21, cyclooxygenase-2, vascular endothelial growth factor, and E-cadherin alterations. "Smoking intensity" quantified the impact of duration and daily frequency of smoking. RESULTS: Age, pathological stage, surgical modality, and adjuvant therapy administration were significantly associated with survival. Increasing smoking intensity was independently associated with worse outcome (P < .001). Apaf-1, E-cadherin, and p53 were prognostic for outcome (P = .005, .014, and .032, respectively); E-cadherin remained prognostic following multivariable analysis (P = .040). Combined alterations in all 9 biomarkers were prognostic by univariable (P < .001) and multivariable (P = .006) analysis. A multivariable model that included all 9 biomarkers and smoking intensity had greater accuracy in predicting prognosis than models composed of standard clinicopathological covariates without or with smoking intensity (P < .001 and P = .018, respectively). CONCLUSIONS: Apaf-1, E-cadherin, and p53 alterations individually predicted survival in bladder cancer patients. Increasing number of biomarker alterations was significantly associated with worsening survival, although markers comprising the panel were not necessarily prognostic individually. Predictive value of the 9-biomarker panel with smoking intensity was significantly higher than that of routine clinicopathological parameters alone.

Genetic and epigenetic analysis of putative breast cancer stem cell models.

BACKGROUND: Cancer stem cell model hypothesizes existence of a small proportion of tumor cells capable of sustaining tumor formation, self-renewal and differentiation. In breast cancer, these cells were found to be associated with CD44⁺CD24-low and ALDH⁺ phenotype. Our study was performed to evaluate the suitability of current approaches for breast cancer stem cell analyses to evaluate heterogeneity of breast cancer cells through their extensive genetic and epigenetic characterization. METHODS: Breast cancer cell lines MCF7 and SUM159 were cultured in adherent conditions and as mammospheres. Flow cytometry sorting for CD44, CD24 and ALDH was performed. Sorted and unsorted populations, mammospheres and adherent cell cultures were subjected to DNA profiling by array CGH and methylation profiling by Epitect Methyl qPCR array. Methylation status of selected genes was further evaluated by pyrosequencing. Functional impact of methylation was evaluated by mRNA analysis for selected genes. RESULTS: Array CGH did not reveal any genomic differences. In contrast, putative breast cancer stem cells showed altered methylation levels of several genes compared to parental tumor cells. CONCLUSIONS: Our results underpin the hypothesis that epigenetic mechanisms seem to play a major role in the regulation of CSCs. However, it is also clear that more efficient methods for CSC enrichment are needed. This work underscores requirement of additional approaches to reveal heterogeneity within breast cancer.

Automatic detection of circulating tumor cells and cancer associated fibroblasts using deep learning.

Circulating tumor cells (CTCs) and cancer-associated fibroblasts (CAFs) from whole blood are emerging as important biomarkers that potentially aid in cancer diagnosis and prognosis. The microfilter technology provides an efficient capture platform for them but is confounded by two challenges. First, uneven microfilter surfaces makes it hard for commercial scanners to obtain images with all cells in-focus. Second, current analysis is labor-intensive with long turnaround time and user-to-user variability. Here we addressed the first challenge through developing a customized imaging system and data pre-processing algorithms. Utilizing cultured cancer and CAF cells captured by microfilters, we showed that images from our custom system are 99.3% in-focus compared to 89.9% from a top-of-the-line commercial scanner. Then we developed a deep-learning-based method to automatically identify tumor cells serving to mimic CTC (mCTC) and CAFs. Our deep learning method achieved precision and recall of 94% (± 0.2%) and 96% (± 0.2%) for mCTC detection, and 93% (± 1.7%) and 84% (± 3.1%) for CAF detection, significantly better than a conventional computer vision method, whose numbers are 92% (± 0.2%) and 78% (± 0.3%) for mCTC and 58% (± 3.9%) and 56% (± 3.5%) for CAF. Our custom imaging system combined with deep learning cell identification method represents an important advance on CTC and CAF analysis.

Extrinsic and intrinsic preanalytical variables affecting liquid biopsy in cancer.

Liquid biopsy, through isolation and analysis of disease-specific analytes, has evolved as a promising tool for safe and minimally invasive diagnosis and monitoring of tumors. It also has tremendous utility as a companion diagnostic allowing detection of biomarkers in a range of cancers (lung, breast, colon, ovarian, brain). However, clinical implementation and validation remains a challenge. Among other stages of development, preanalytical variables are critical in influencing the downstream cellular and molecular analysis of different analytes. Although considerable progress has been made to address these challenges, a comprehensive assessment of the impact on diagnostic parameters and consensus on standardized and optimized protocols is still lacking. Here, we summarize and critically evaluate key variables in the preanalytical stage, including study population selection, choice of biofluid, sample handling and collection, processing, and storage. There is an unmet need to develop and implement comprehensive preanalytical guidelines on the optimal practices and methodologies.

The Liquid Biopsy Consortium: Challenges and opportunities for early cancer detection and monitoring.

The emerging field of liquid biopsy stands at the forefront of novel diagnostic strategies for cancer and other diseases. Liquid biopsy allows minimally invasive molecular characterization of cancers for diagnosis, patient stratification to therapy, and longitudinal monitoring. Liquid biopsy strategies include detection and monitoring of circulating tumor cells, cell-free DNA, and extracellular vesicles. In this review, we address the current understanding and the role of existing liquid-biopsy-based modalities in cancer diagnostics and monitoring. We specifically focus on the technical and clinical challenges associated with liquid biopsy and biomarker development being addressed by the Liquid Biopsy Consortium, established through the National Cancer Institute. The Liquid Biopsy Consortium has developed new methods/assays and validated existing methods/technologies to capture and characterize tumor-derived circulating cargo, as well as addressed existing challenges and provided recommendations for advancing biomarker assays.

Risk stratification of organ confined bladder cancer after radical cystectomy using cell cycle related biomarkers.

PURPOSE: We tested whether assessing the expression of cell cycle related proteins (p53, pRB, p21 and p27) could predict clinical outcomes after radical cystectomy in patients with organ confined urothelial carcinoma of the bladder. MATERIALS AND METHODS: Our study included a development cohort of 272 patients and an external testing cohort of 52 patients with chemotherapy naïve pT1-2N0M0 urothelial carcinoma of the bladder treated with radical cystectomy. Immunohistochemical staining of p53, p27, p21 and pRB was performed on the development cohort of 272 patients and the external testing cohort of 52 patients. RESULTS: Overall 260 (80.2%) patients had altered expression of at least 1 molecular marker and 105 (32.4%), 95 (29.3%), 44 (13.6%) and 16 (4.9%) had 1 to 4 altered molecular markers, respectively. Addition of the number of altered molecular markers increased the predictive accuracy of the base model for disease recurrence and cancer specific mortality by 15.6% and 14.8%, respectively (p <0.001). The base model included age, gender, pT1 vs pT2 stage, grade, number of lymph nodes removed, lymphovascular invasion and concomitant carcinoma in situ. The combination of molecular markers yielded a predictive accuracy superior to that of any single molecular marker. We developed nomograms for the prediction of recurrence-free and cancer specific survival. CONCLUSIONS: Assessment of the number of altered cell cycle regulatory proteins in the cystectomy specimen improves the prediction of urothelial carcinoma of the bladder recurrence and survival in patients with organ confined disease. A combination of multiple markers is needed to capture the complex biological behavior of urothelial carcinoma of the bladder.

Pathological possibilities and pitfalls in detecting aggressive bladder cancer.

PURPOSE OF REVIEW: The prognosis of patients with high-risk bladder cancer is generally poor. In addition to advanced stage and high-grade tumors, several histopathological subtypes of invasive bladder cancer have been identified as being more aggressive than conventional forms. However, modalities for early detection of such aggressive neoplasms are limited. This review examines the pathological features of aggressive bladder cancer and critically reviews the performance of selected methodologies that are commonly used to detect such lesions. RECENT FINDINGS: Strategies including bladder tumor antigen assay, NMP22, ImmunoCyt, and UroVysion hold promise for the early detection of aggressive urothelial carcinomas of the bladder. However, such approaches are currently limited by their sensitivity and potential for false-positive results, and are unlikely to substitute cystoscopy. SUMMARY: Molecular-based detection techniques represent potentially attractive strategies for noninvasive detection of aggressive bladder cancer using urine as the specimen source. Identification of new markers and development of novel platforms may improve detection in the future.

3D microfilter device for viable circulating tumor cell (CTC) enrichment from blood.

Detection of circulating tumor cells has emerged as a promising minimally invasive diagnostic and prognostic tool for patients with metastatic cancers. We report a novel three dimensional microfilter device that can enrich viable circulating tumor cells from blood. This device consists of two layers of parylene membrane with pores and gap precisely defined with photolithography. The positions of the pores are shifted between the top and bottom membranes. The bottom membrane supports captured cells and minimize the stress concentration on cell membrane and sustain cell viability during filtration. Viable cell capture on device was investigated with scanning electron microscopy, confocal microscopy, and immunofluorescent staining using model systems of cultured tumor cells spiked in blood or saline. The paper presents and validates this new 3D microfiltration concept for circulation tumor cell enrichment application. The device provides a highly valuable tool for assessing and characterizing viable enriched circulating tumor cells in both research and clinical settings.