European Epidemiology of Pleural Mesothelioma-Real-Life Data From a Joint Analysis of the Mesoscape Database of the European Thoracic Oncology Platform and the European Society of Thoracic Surgery Mesothelioma Database.

INTRODUCTION: Pleural mesothelioma (PM) is an aggressive malignancy with increasing prevalence and poor prognosis. Real-life data are a unique approach to reflect the reality of PM epidemiology, treatment, and prognosis in Europe. METHODS: A joint analysis of the European Thoracic Oncology Platform Mesoscape and the European Society of Thoracic Surgeons (ESTS) databases was performed to better understand the characteristics and epidemiology of PM, including histologic subtype, staging, and treatment. Overall survival (OS) was assessed, adjusting for parameters of clinical interest. RESULTS: The analysis included 2766 patients (Mesoscape: 497/10 centers/ESTS: 2269/77 centers). The primary histologic subtype was epithelioid (71%), with 57% patients on stages III to IV. Within Mesoscape, the patients received either multimodality (59%) or palliative intention treatment (41%). The median follow-up was 47.2 months, on the basis of 1103 patients (Mesoscape: 491/ESTS: 612), with 823 deaths, and median OS was 17.4 months. In multivariable analysis, female sex, epithelioid subtype, and lower stage were associated with longer OS, when stratifying by cohort, age, and Eastern Cooperative Oncology Group Performance Status. Within Mesoscape, multimodality treatment including surgery was predictive of longer OS (hazard ratio = 0.56, 95% confidence interval: 0.45-0.69), adjusting for sex, histologic subtype, and Eastern Cooperative Oncology Group Performance Status. Overall, surgical candidates with a macroscopic complete resection had a significantly longer median OS compared with patients with R2 (25.2 m versus 16.4 m; log-rank p < 0.001). CONCLUSIONS: This combined European Thoracic Oncology Platform/ESTS database analysis offers one of the largest databases with detailed clinical and pathologic outcome. Our finding reflects a benefit for selected patients that undergo multimodality treatment, including macroscopic complete resection, and represents a valuable resource to inform the epidemiology and treatment options for individual patients.

Mutational Landscape and Expression of PD-L1 in Patients with Non-Small Cell Lung Cancer Harboring Genomic Alterations of the MET gene.

BACKGROUND: Mesenchymal-to-epithelial transition (MET) exon 14 skipping mutations and MET gene amplification occur in 3-5% of non-small cell lung cancer (NSCLC) patients. Tyrosine kinase inhibitors (TKIs) targeting MET alterations have shown promising results in these patients. OBJECTIVE: The aim of this study was to describe the genomic profile, PD-L1 expression and clinicopathological features of MET dysregulated NSCLC. PATIENTS AND METHODS: We identified 188 patients with advanced-stage NSCLC with data on MET expression by immunohistochemistry (IHC). IHC for PD-L1 expression was performed in 131 patient samples, and next-generation sequencing (NGS) analysis was performed in 109 patient samples. RESULTS: MET exon 14 skipping alterations were identified in 16 (14.7%) samples, MET amplifications with cut-off ≥4 copy number variations were identified in 11 (10.1%) samples, and an oncogenic MET mutation (MET p.D1228N) was identified in 1 (0.9%) sample. 12/15 tumors (80.0%) harboring MET exon 14 alterations and 7/11 (63.6%) MET-amplified tumors expressed PD-L1 in ≥1% of tumor cells. Tumors harboring MET exon 14 skipping alterations expressed PD-L1 more frequently than MET wild-type IHC-positive tumors (p = 0.045). Twenty-five percent of MET exon 14-altered cases and 33% of MET-amplified cases harbored potentially targetable oncogenic co-mutations in KRAS, BRAF, and EGFR. The most frequent co-occurring mutations in all MET-altered tumors were TP53, KRAS, BRAF, and CDK4. CONCLUSIONS: We demonstrated that MET exon 14 skipping alterations and MET amplification are not mutually exclusive to other oncogenic co-mutations, and report the association of genomic MET alterations with PD-L1 expression. Since genomic MET alterations are emerging targets requiring upfront treatment, optimal understanding of the co-mutational landscape for this patient population is needed.

Targeting ALK in Neuroendocrine Tumors of the Lung.

Background: Anaplastic lymphoma kinase (ALK) rearrangements are known oncogenic drivers in non-small cell lung cancer (NSCLC). Few case reports described the occurrence of such rearrangements in large cell neuroendocrine carcinomas (LCNECs) of the lung without information on clinical responses to ALK tyrosine kinase inhibitors (TKIs) in these cases. Currently, neuroendocrine tumors of the lungs are not screened for ALK rearrangements. Methods: To illustrate the clinical impact of molecular characterization in LCNECs, we report the disease course in three patients with ALK-rearranged metastatic LCNEC from our clinical routine, as well as their treatment response to ALK TKIs (index cases). To gain insight into the prevalence of ALK rearrangements in neuroendocrine tumors of the lung, we analyzed a retrospective cohort of 436 tumor biopsies including LCNEC (n = 61), small cell lung cancer (SCLC) (n = 206), typical (n = 91) and atypical (n = 69) carcinoids, and mixed histology (n = 9) for the presence of ALK rearrangements using a sequential diagnostic algorithm. ALK immunohistochemistry (IHC) was evaluable in 362 cases; fluorescence in situ hybridization (FISH) was evaluable in 28 out of the 35 IHC-positive cases, followed by next-generation sequencing (NGS) that was available in 12 cases. Results: Within the retrospective cohort, ALK IHC was positive in 35 out of 362 (9.7%) evaluable samples. FISH was positive in 3 out of the 28 (10.7%) evaluable cases: 2 with atypical carcinoids and 1 with LCNEC. Additionally, the 3 index cases showed positive ALK IHC, which was confirmed by NGS. Within the retrospective cohort, NGS confirmed the presence of an ALK genomic rearrangement in one FISH-positive atypical carcinoid where material was sufficient for sequencing. Two out of three patients with metastatic ALK-rearranged LCNEC received up-front treatment with the ALK TKI alectinib and showed rapid tumor response at all metastatic sites, including multiple brain metastases. Conclusions: ALK rearrangements represent rare but targetable oncogenic driver alterations in LCNEC. Contrarily to NSCLC, the detection of ALK rearrangements in neuroendocrine tumors of the lung is challenging, since ALK IHC can lead to false-positive results and therefore needs confirmation by FISH or NGS. Up-front comprehensive molecular profiling with NGS should be performed in metastatic LCNEC in order not to miss actionable genomic alterations.

Infiltrative growth pattern of prostate cancer is associated with lower uptake on PSMA PET and reduced diffusion restriction on mpMRI.

PURPOSE: Recently, a significant association was shown between novel growth patterns on histopathology of prostate cancer (PCa) and prostate-specific membrane antigen (PSMA) uptake on [68Ga]PSMA-PET. It is the aim of this study to evaluate the association between these growth patterns and ADC (mm2/1000 s) values in comparison to [68Ga]PSMA uptake on PET/MRI. METHODS: We retrospectively evaluated patients who underwent [68Ga]PSMA PET/MRI for staging or biopsy guidance, followed by radical prostatectomy at our institution between 07/2016 and 01/2020. The dominant lesion per patient was selected based on histopathology and correlated to PET/MRI in a multidisciplinary meeting, and quantified using SUVmax for PSMA uptake and ADCmean for diffusion restriction. PCa growth pattern was classified as expansive (EXP) or infiltrative (INF) according to its properties of forming a tumoral mass or infiltrating diffusely between benign glands by two independent pathologists. Furthermore, the corresponding WHO2016 ISUP tumor grade was evaluated. The t test was used to compare means, Pearson's test for categorical correlation, Cohen's kappa test for interrater agreement, and ROC curve to determine the best cutoff. RESULTS: Sixty-two patients were included (mean PSA 11.7 ± 12.5). The interrater agreement between both pathologists was almost perfect with κ = 0.81. While 25 lesions had an EXP-growth with an ADCmean of 0.777 ± 0.109, 37 showed an INF-growth with a significantly higher ADCmean of 1.079 ± 0.262 (p < 0.001). We also observed a significant difference regarding PSMA SUVmax for the EXP-growth (19.2 ± 10.9) versus the INF-growth (9.4 ± 6.2, p < 0.001). Within the lesions encompassing the EXP- or the INF-growth, no significant correlation between the ISUP groups and ADCmean could be observed (p = 0.982 and p = 0.861, respectively). CONCLUSION: PCa with INF-growth showed significantly lower SUVmax and higher ADCmean values compared to PCa with EXP-growth. Within the growth groups, ADCmean values were independent from ISUP grading.

Identification of Urine Biomarkers to Improve Eligibility for Prostate Biopsy and Detect High-Grade Prostate Cancer.

PCa screening is based on the measurements of the serum prostate specific antigen (PSA) to select men with higher risks for tumors and, thus, eligible for prostate biopsy. However, PSA testing has a low specificity, leading to unnecessary biopsies in 50-75% of cases. Therefore, more specific screening opportunities are needed to reduce the number of biopsies performed on healthy men and patients with indolent tumors. Urine samples from 45 patients with elevated PSA were collected prior to prostate biopsy, a mass spectrometry (MS) screening was performed to identify novel biomarkers and the best candidates were validated by ELISA. The urine quantification of PEDF, HPX, CD99, CANX, FCER2, HRNR, and KRT13 showed superior performance compared to PSA. Additionally, the combination of two biomarkers and patient age resulted in an AUC of 0.8196 (PSA = 0.6020) and 0.7801 (PSA = 0.5690) in detecting healthy men and high-grade PCa, respectively. In this study, we identified and validated novel urine biomarkers for the screening of PCa, showing that an upfront urine test, based on quantitative biomarkers and patient age, is a feasible method to reduce the number of unnecessary prostate biopsies and detect both healthy men and clinically significant PCa.

The Morphological Spectrum of Papillary Renal Cell Carcinoma and Prevalence of Provisional/Emerging Renal Tumor Entities with Papillary Growth.

Renal cell carcinoma (RCC) represents a heterogeneous disease, encompassing an increasing number of tumor subtypes. Post-2016, the World Health Organization (WHO) classification recognized that the spectrum of papillary renal cell carcinoma is evolving and has long surpassed the dichotomic simplistic "type 1 versus type 2" classification. The differential diagnosis of pRCC includes several new provisional/emerging entities with papillary growth. Type 2 tumors have been cleared out of several confounding entities, now regarded as independent tumors with specific clinical and molecular backgrounds. In this work we describe the prevalence and characteristics of emerging papillary tumor entities in two renal tumor cohorts (one consisting of consecutive papillary tumors from a single institute, the other consisting of consultation cases from several centers). After a review of 154 consecutive pRCC cases, 58% remained type 1 pRCC, and 34% type 2 pRCC. Papillary renal neoplasm with reversed polarity (1.3%), biphasic hyalinizing psammomatous RCC (1.3%), and biphasic squamoid/alveolar RCC (4.5%) were rare. Among 281 consultation cases, 121 (43%) tumors had a dominant papillary growth (most frequently MiT family translocation RCCs, mucinous tubular and spindle cell carcinoma and clear cell papillary RCC). Our data confirm that the spectrum of RCCs with papillary growth represents a major diagnostical challenge, frequently requiring a second expert opinion. Papillary renal neoplasm with reversed polarity, biphasic hyalinizing psammomatous RCC, and biphasic squamoid/alveolar RCC are rarely sent out for a second opinion, but correct classification and knowledge of these variants will improve our understanding of the clinical behavior of renal tumors with papillary growth.

A novel 5x multiplex immunohistochemical staining reveals PSMA as a helpful marker in prostate cancer with low p504s expression.

The ability to combine multiple immunohistochemical (IHC) markers within a single tissue section facilitates the evaluation and detection of co-expressions, while saving tissue. A newly developed 5x multiplex (MPX) IHC staining of five different IHC markers (Basal cell cocktail (34ßE12 + p63), p504s (SP116), ERG (EPR3864), Ki-67 (30-9), PSMA (EP192)) was applied on whole sections of n = 37 radical prostatectomies (RPE) including normal and cancerous tissue. Four different colors including brown, magenta, yellow and teal coded for different stainings, whereas magenta was used twice for nuclear Ki-67 and cytosolic / membranous PSMA. The staining of multiplex IHC was compared to single stains of ERG, PSMA and p504s. The proper staining of the basal cell cocktail and Ki-67 could be assessed by internal positive controls in the multiplex staining. The proportion of PSMA and p504s expression revealed a significant correlation between multiplex and single stains (p < 0.01) as well as a concordant staining pattern for ERG (n = 14 prostate cancers were identified ERG positive with both methods). Our proof of concept study demonstrates a robust staining pattern of all five different antibodies with this newly developed 5x MPX IHC. This approach facilitates the recognition of prostate cancer, in particular by adding PSMA in cases with low p504s expression.

What's behind 68Ga-PSMA-11 uptake in primary prostate cancer PET? Investigation of histopathological parameters and immunohistochemical PSMA expression patterns.

PURPOSE: Prostate-specific membrane antigen (PSMA-) PET has become a promising tool in staging and restaging of prostate carcinoma (PCa). However, specific primary tumour features might impact accuracy of PSMA-PET for PCa detection. We investigated histopathological parameters and immunohistochemical PSMA expression patterns on radical prostatectomy (RPE) specimens and correlated them to the corresponding 68Ga-PSMA-11-PET examinations. METHODS: RPE specimens of 62 patients with preoperative 68Ga-PSMA-11-PET between 2016 and 2018 were analysed. WHO/ISUP grade groups, growth pattern (expansive vs. infiltrative), tumour area and diameter as well as immunohistochemical PSMA heterogeneity, intensity and negative tumour area (PSMA%neg) were correlated with spatially corresponding SUVmax on 68Ga-PSMA-11-PET in a multidisciplinary analysis. RESULTS: All tumours showed medium to strong membranous (2-3 +) and weak to strong cytoplasmic (1-3 +) PSMA expression. Heterogeneously expressed PSMA was found in 38 cases (61%). Twenty-five cases (40%) showed at least 5% and up to 80% PSMA%neg. PSMA%neg, infiltrative growth pattern, smaller tumour area and diameter and WHO/ISUP grade group 2 significantly correlated with lower SUVmax values. A ROC curve analysis revealed 20% PSMA%neg as an optimal cutoff with the highest sensitivity and specificity (89% and 86%, AUC 0.923) for a negative PSMA-PET scan. A multiple logistic regression model revealed tumoural PSMA%neg (p < 0.01, OR = 9.629) and growth pattern (p = 0.0497, OR = 306.537) as significant predictors for a negative PSMA-PET scan. CONCLUSIONS: We describe PSMA%neg, infiltrative growth pattern, smaller tumour size and WHO/ISUP grade group 2 as parameters associated with a lower 68Ga-PSMA-11 uptake in prostate cancer. These findings can serve as fundament for future biopsy-based biomarker development to enable an individualized, tumour-adapted imaging approach.

Convergent network effects along the axis of gene expression during prostate cancer progression.

BACKGROUND: Tumor-specific genomic aberrations are routinely determined by high-throughput genomic measurements. It remains unclear how complex genome alterations affect molecular networks through changing protein levels and consequently biochemical states of tumor tissues. RESULTS: Here, we investigate the propagation of genomic effects along the axis of gene expression during prostate cancer progression. We quantify genomic, transcriptomic, and proteomic alterations based on 105 prostate samples, consisting of benign prostatic hyperplasia regions and malignant tumors, from 39 prostate cancer patients. Our analysis reveals the convergent effects of distinct copy number alterations impacting on common downstream proteins, which are important for establishing the tumor phenotype. We devise a network-based approach that integrates perturbations across different molecular layers, which identifies a sub-network consisting of nine genes whose joint activity positively correlates with increasingly aggressive tumor phenotypes and is predictive of recurrence-free survival. Further, our data reveal a wide spectrum of intra-patient network effects, ranging from similar to very distinct alterations on different molecular layers. CONCLUSIONS: This study uncovers molecular networks with considerable convergent alterations across tumor sites and patients. It also exposes a diversity of network effects: we could not identify a single sub-network that is perturbed in all high-grade tumor regions.

Immunohistochemical PSMA expression patterns of primary prostate cancer tissue are associated with the detection rate of biochemical recurrence with 68Ga-PSMA-11-PET.

Prostate-specific membrane antigen (PSMA) targeted PET has a high detection rate for biochemical recurrence (BCR) of prostate cancer (PCa). Nevertheless, even at high prostate-specific antigen (PSA) levels (> 3 ng/ml), a relevant number of PSMA-PET scans are negative, mainly due to PSMA-negative PCa. Our objective was to investigate whether PSMA-expression patterns of the primary tumour on immunohistochemistry (IHC) are associated with PSMA-PET detection rate of recurrent PCa. Methods: Retrospective institutional review board approved single-centre analysis of patients who had undergone 68Ga-PSMA-11-PET for BCR after radical prostatectomy (RPE) between 04/2016 and 07/2019, with tumour specimens available for PSMA-IHC. Clinical information (age, PSA-level, ongoing androgen deprivation therapy (ADT), Gleason score) and PSMA-IHC of the primary tumour were collected and their relationship to results from PSMA-PET (positive/negative) was investigated using a multiple logistic regression analysis. Results: 120 PSMA-PET scans in 74 patients were available for this analysis. Overall detection rate was 62% (74/120 scans), with a mean PSA value at scan time of 0.99 ng/ml (IQR 0.32-4.27). Of the clinical factors, only PSA-level and ADT were associated with PSMA-PET positivity. The percentage of PSMA-negative tumour area on IHC (PSMA%neg) had a significant association to PSMA-PET negativity (OR = 2.88, p < 0.001), while membranous PSMA-expression showed no association (p = 0.73). The positive predictive value of PSMA%neg ≥ 50% for a negative PSMA-PET was 85% (13/11) and for a PSMA%neg of 80% or more, 100% (9/9). Conclusions: PSMA-negative tumour area on IHC exhibited the strongest association with negative PSMA-PET scans, beside PSA-level and ADT. Even at very high PSA levels, PSMA-PET scans were negative in most of the patients with PSMA%neg ≥ 50%.

Diagnostic Accuracy of Multiparametric MRI versus 68Ga-PSMA-11 PET/MRI for Extracapsular Extension and Seminal Vesicle Invasion in Patients with Prostate Cancer.

Background Recent studies have reported the additive value of combined gallium 68 (68Ga)-labeled Glu-urea-Lys (Ahx)-HBED-CC ligand targeting the prostate-specific membrane antigen (PSMA) (hereafter called 68Ga-PSMA-11) PET/MRI for the detection and localization of primary prostate cancer compared with multiparametric MRI. Purpose To compare the diagnostic accuracy and interrater agreement of multiparametric MRI and 68Ga-PSMA-11 PET/MRI for the detection of extracapsular extension (ECE) and seminal vesicle infiltration (SVI) in patients with prostate cancer. Materials and Methods Retrospective analysis of 40 consecutive men who underwent multiparametric MRI and 68Ga-PSMA-11 PET/MRI within 6 months for suspected prostate cancer followed by radical prostatectomy between April 2016 and July 2018. Four readers blinded to clinical and histopathologic findings rated the probability of ECE and SVI at multiparametric MRI and PET/MRI by using a five-point Likert-type scale. The prostatectomy specimen served as the reference standard. Accuracy was assessed with a multireader multicase analysis and by calculating reader-average areas under the receiver operating characteristics curve (AUCs), sensitivity, and specificity for ordinal and dichotomized data in a region-specific and patient-specific approach. Interrater agreement was assessed with the Fleiss multirater κ. Results For multiparametric MRI versus PET/MRI in ECE detection, respectively, AUC, sensitivity, and specificity in the region-specific analysis were 0.67 and 0.75 (P = .07), 28% (21 of 76) and 47% (36 of 76) (P = .09), and 94% (529 of 564) and 90% (509 of 564) (P = .007). For the patient-specific analysis, AUC, sensitivity, and specificity were 0.66 and 0.73 (P = .19), 46% (22 of 48) and 69% (33 of 48) (P = .04), and 75% (84 of 112) and 67% (75 of 112) (P = .19), respectively. For multiparametric MRI versus PET/MRI in SVI detection, respectively, AUC, sensitivity, and specificity of the region-specific analysis were 0.66 and 0.74 (P = .21), 35% (seven of 20) and 50% (10 of 20) (P = .25), and 98% (295 of 300) and 94% (282 of 300) (P < .001). For the patient-specific analysis, AUC, sensitivity, and specificity were 0.65 and 0.79 (P = .25), 35% (seven of 20) and 55% (11 of 20) (P = .20), and 98% (137 of 140) and 94% (131 of 140) (P = .07), respectively. Interrater reliability for multiparametric MRI versus PET/MRI did not differ for ECE (κ, 0.46 vs 0.40; P = .24) and SVI (κ, 0.23 vs 0.33; P = .39). Conclusion Our results suggest that gallium 68 (68Ga)-labeled Glu-urea-Lys (Ahx)-HBED-CC ligand targeting the prostate-specific membrane antigen (PSMA) (68Ga-PSMA-11) PET/MRI and multiparametric MRI perform similarly for local staging of prostate cancer in patients with intermediate-to-high-risk prostate cancer. The increased sensitivity of 68Ga-PSMA-11 PET/MRI for the detection of extracapsular disease comes at the cost of a slightly reduced specificity. © RSNA, 2019.

Comparative analysis of mRNA and protein degradation in prostate tissues indicates high stability of proteins.

Deterioration of biomolecules in clinical tissues is an inevitable pre-analytical process, which affects molecular measurements and thus potentially confounds conclusions from cohort analyses. Here, we investigate the degradation of mRNA and protein in 68 pairs of adjacent prostate tissue samples using RNA-Seq and SWATH mass spectrometry, respectively. To objectively quantify the extent of protein degradation, we develop a numerical score, the Proteome Integrity Number (PIN), that faithfully measures the degree of protein degradation. Our results indicate that protein degradation only affects 5.9% of the samples tested and shows negligible correlation with mRNA degradation in the adjacent samples. These findings are confirmed by independent analyses on additional clinical sample cohorts and across different mass spectrometric methods. Overall, the data show that the majority of samples tested are not compromised by protein degradation, and establish the PIN score as a generic and accurate indicator of sample quality for proteomic analyses.

Author Correction: Automated Gleason grading of prostate cancer tissue microarrays via deep learning.

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Expression and Mutation Patterns of PBRM1, BAP1 and SETD2 Mirror Specific Evolutionary Subtypes in Clear Cell Renal Cell Carcinoma.

Bi-allelic inactivation of the VHL gene on chromosome 3p is the characteristic feature in most clear cell renal cell carcinomas (ccRCC). Frequent gene alterations were also identified in SETD2, BAP1 and PBRM1, all of which are situated on chromosome 3p and encode histone/chromatin regulators. The relationship between gene mutation, loss of protein expression and the correlations with clinicopathological parameters is important for the understanding of renal cancer progression. We analyzed PBRM1 and BAP1 protein expression as well as the tri-methylation state of H3K36 as a surrogate marker for SETD2 activity in more than 700 RCC samples. In ccRCC loss of nuclear PBRM1 (68%), BAP1 (40%) and H3K36me3 (47%) expression was significantly correlated with each other, advanced tumor stage, poor tumor differentiation (P < .0001 each), and necrosis (P < .005) Targeted next generation sequencing of 83 ccRCC samples demonstrated a significant association of genetic mutations in PBRM1, BAP1, and SETD2 with absence of PBRM1, BAP1, and HEK36me3 protein expression (P < .05, each). By assigning the protein expression patterns to evolutionary subtypes, we revealed similar clinical phenotypes as suggested by TRACERx Renal. Given their important contribution to tumor suppression, we conclude that combined functional inactivation of PBRM1, BAP1, SETD2 and pVHL is critical for ccRCC progression.

Automated Gleason grading of prostate cancer tissue microarrays via deep learning.

The Gleason grading system remains the most powerful prognostic predictor for patients with prostate cancer since the 1960s. Its application requires highly-trained pathologists, is tedious and yet suffers from limited inter-pathologist reproducibility, especially for the intermediate Gleason score 7. Automated annotation procedures constitute a viable solution to remedy these limitations. In this study, we present a deep learning approach for automated Gleason grading of prostate cancer tissue microarrays with Hematoxylin and Eosin (H&E) staining. Our system was trained using detailed Gleason annotations on a discovery cohort of 641 patients and was then evaluated on an independent test cohort of 245 patients annotated by two pathologists. On the test cohort, the inter-annotator agreements between the model and each pathologist, quantified via Cohen's quadratic kappa statistic, were 0.75 and 0.71 respectively, comparable with the inter-pathologist agreement (kappa = 0.71). Furthermore, the model's Gleason score assignments achieved pathology expert-level stratification of patients into prognostically distinct groups, on the basis of disease-specific survival data available for the test cohort. Overall, our study shows promising results regarding the applicability of deep learning-based solutions towards more objective and reproducible prostate cancer grading, especially for cases with heterogeneous Gleason patterns.

A curated collection of tissue microarray images and clinical outcome data of prostate cancer patients.

Microscopy image data of human cancers provide detailed phenotypes of spatially and morphologically intact tissues at single-cell resolution, thus complementing large-scale molecular analyses, e.g., next generation sequencing or proteomic profiling. Here we describe a high-resolution tissue microarray (TMA) image dataset from a cohort of 71 prostate tissue samples, which was hybridized with bright-field dual colour chromogenic and silver in situ hybridization probes for the tumour suppressor gene PTEN. These tissue samples were digitized and supplemented with expert annotations, clinical information, statistical models of PTEN genetic status, and computer source codes. For validation, we constructed an additional TMA dataset for 424 prostate tissues, hybridized with FISH probes for PTEN, and performed survival analysis on a subset of 339 radical prostatectomy specimens with overall, disease-specific and recurrence-free survival (maximum 167 months). For application, we further produced 6,036 image patches derived from two whole slides. Our curated collection of prostate cancer data sets provides reuse potential for both biomedical and computational studies.

Image-based computational quantification and visualization of genetic alterations and tumour heterogeneity.

Recent large-scale genome analyses of human tissue samples have uncovered a high degree of genetic alterations and tumour heterogeneity in most tumour entities, independent of morphological phenotypes and histopathological characteristics. Assessment of genetic copy-number variation (CNV) and tumour heterogeneity by fluorescence in situ hybridization (ISH) provides additional tissue morphology at single-cell resolution, but it is labour intensive with limited throughput and high inter-observer variability. We present an integrative method combining bright-field dual-colour chromogenic and silver ISH assays with an image-based computational workflow (ISHProfiler), for accurate detection of molecular signals, high-throughput evaluation of CNV, expressive visualization of multi-level heterogeneity (cellular, inter- and intra-tumour heterogeneity), and objective quantification of heterogeneous genetic deletions (PTEN) and amplifications (19q12, HER2) in diverse human tumours (prostate, endometrial, ovarian and gastric), using various tissue sizes and different scanners, with unprecedented throughput and reproducibility.

Oxygen supply maps for hypoxic microenvironment visualization in prostate cancer.

BACKGROUND: Intratumoral hypoxia plays an important role with regard to tumor biology and susceptibility to radio- and chemotherapy. For further investigation of hypoxia-related changes, areas of certain hypoxia must be reliably detected within cancer tissues. Pimonidazole, a 2-nitroimindazole, accumulates in hypoxic tissue and can be easily visualized using immunohistochemistry. MATERIALS AND METHODS: To improve detection of highly hypoxic versus normoxic areas in prostate cancer, immunoreactivity of pimonidazole and a combination of known hypoxia-related proteins was used to create computational oxygen supply maps of prostate cancer. Pimonidazole was intravenously administered before radical prostatectomy in n = 15 patients, using the da Vinci robot-assisted surgical system. Prostatectomy specimens were immediately transferred into buffered formaldehyde, fixed overnight, and completely embedded in paraffin. Pimonidazole accumulation and hypoxia-related protein expression were visualized by immunohistochemistry. Oxygen supply maps were created using the normalized information from pimonidazole and hypoxia-related proteins. RESULTS: Based on pimonidazole staining and other hypoxia.related proteins (osteopontin, hypoxia-inducible factor 1-alpha, and glucose transporter member 1) oxygen supply maps in prostate cancer were created. Overall, oxygen supply maps consisting of information from all hypoxia-related proteins showed high correlation and mutual information to the golden standard of pimonidazole. Here, we describe an improved computer-based ex vivo model for an accurate detection of oxygen supply in human prostate cancer tissue. CONCLUSIONS: This platform can be used for precise colocalization of novel candidate hypoxia-related proteins in a representative number of prostate cancer cases, and improve issues of single marker correlations. Furthermore, this study provides a source for further in situ tests and biochemical investigations.