Markers of clinical utility in the differential diagnosis and prognosis of prostate cancer

Digital analysis of the prostate tumor microenvironment with high-order chromogenic multiplexing

As our understanding of the tumor microenvironment grows, the pathology field is increasingly utilizing multianalyte diagnostic assays to understand important characteristics of tumor growth. In clinical settings, brightfield chromogenic assays represent the gold-standard and have developed significant trust as the first-line diagnostic method. However, conventional brightfield tests have been limited to low-order assays that are visually interrogated. We have developed a hybrid method of brightfield chromogenic multiplexing that overcomes these limitations and enables high-order multiplex assays. However, how compatible high-order brightfield multiplexed images are with advanced analytical algorithms has not been extensively evaluated. In the present study, we address this gap by developing a novel 6-marker prostate cancer assay that targets diverse aspects of the tumor microenvironment such as prostate-specific biomarkers (PSMA and p504s), immune biomarkers (CD8 and PD-L1), a prognostic biomarker (Ki-67), as well as an adjunctive diagnostic biomarker (basal cell cocktail) and apply the assay to 143 differentially graded adenocarcinoma prostate tissues. The tissues were then imaged on our spectroscopic multiplexing imaging platform and mined for proteomic and spatial features that were correlated with cancer presence and disease grade. Extracted features were used to train a UMAP model that differentiated healthy from cancerous tissue with an accuracy of 89% and identified clusters of cells based on cancer grade. For spatial analysis, cell-to-cell distances were calculated for all biomarkers and differences between healthy and adenocarcinoma tissues were studied. We report that p504s positive cells were at least 2× closer to cells expressing PD-L1, CD8, Ki-67, and basal cell in adenocarcinoma tissues relative to the healthy control tissues. These findings offer a powerful insight to understand the fingerprint of the prostate tumor microenvironment and indicate that high-order chromogenic multiplexing is compatible with digital analysis. Thus, the presented chromogenic multiplexing system combines the clinical applicability of brightfield assays with the emerging diagnostic power of high-order multiplexing in a digital pathology friendly format that is well-suited for translational studies to better understand mechanisms of tumor development and growth.

Timing of Early Salvage Therapy for Patients With Biochemical Relapse of Prostate Carcinoma

Between 25% and 33% of patients after radical prostatectomy experience a relapse of the disease. The risk of relapse increases in patients with risk factors up to 50%-80%. For a long time, adjuvant radiotherapy has been considered the standard of care. Four large prospective trials, that compared adjuvant and salvage radiotherapy in patients with biochemical relapse, showed the superiority of the adjuvant approach in biochemical and local relapse-free survival, but no consistent benefit in long-term endpoints (i.e., metastasis-free survival, overall survival, or carcinoma-specific survival) at the expense of increased urinary and bowel toxicity. Three large international studies comparing adjuvant and salvage radiotherapy paved the way toward early salvage radiotherapy. However, the optimal threshold of the PSA level (range of 0.2-0.5 ng/mL) for initiating early salvage radiotherapy remains unresolved and still poses a challenge in everyday clinical practice when balancing the need for early radiotherapy and the associated toxicity. Imprecise stratification of biochemical relaps patients according to the risk of clinical relapse drives efforts to find additional molecular biomarkers that would improve the timing of the salvage therapy.

Incorporation of the 40-Gene Expression Profile (40-GEP) Test to Improve Treatment Decisions in High-Risk Cutaneous Squamous Cell Carcinoma (cSCC) Patients: Case Series and Algorithm

Cutaneous squamous cell carcinoma (cSCC) has become a significant public health issue due to its rapidly rising incidence and an estimated 1.8 million newly diagnosed cases annually. As with other cancers, treatment decisions for patients with cSCC are based primarily on a patient's risk for poor outcomes. There has been improvement in clinicopathologic factor-based risk assessment approaches, either through informal methods or ever evolving staging approaches. However, these approaches misidentify patients who will eventually have disease progression as low-risk and conversely, over classify patients as high-risk who do not experience relapse. To improve the accuracy of risk assessment for patients with cSCC, the 40-gene expression profile (40-GEP) test has been validated to show statistically significant stratification of a high-risk cSCC patient's risk of nodal or distant metastasis, independent of currently available risk-assessment methods. The 40-GEP test allows for a more accurate classification of metastatic risk for high-risk cSCC patients, with the aim to influence appropriate allocation of clinician time and therapeutic resources to those patients who will most benefit. The objective of this article is to present a treatment algorithm in which clinicians can easily integrate the results of the 40-GEP test into their current treatment approaches to tailor patient care based on individual tumor biology. The following modalities were considered: surveillance imaging, sentinel lymph node biopsy (SLNB), adjuvant radiation therapy (ART), and clinical follow-up. The authors have contributed their own cases for discussion as to how they have seen the beneficial impact of 40-GEP test results in their own practice. Overall, clinicians can identify risk-aligned treatment pathway improvements with the use of the 40-GEP test for challenging to manage, high-risk cSCC patients.

Tissue immunostaining of candidate prognostic proteins in metastatic and non-metastatic prostate cancer

PURPOSE

Prostate cancer (PCa) lacks specific markers capable of distinguishing aggressive tumors from those with indolent behavior. Therefore, the aim of this study was to evaluate the immunostaining of candidate proteins (PTEN, AKT, TRPM8, and NKX3.1) through the immunohistochemistry technique (IHC) on patients with metastatic and non-metastatic PCa.

METHODS

Tissues from 60 patients were divided into three groups categorized according to prognostic parameters: better prognosis (n = 20), worse prognosis (n = 23), and metastatic (n = 17). Immunostaining was analyzed by a pathologist and staining classifications were considered according to signal intensity: (0) no staining, (+) weak, and (++ and +++) intermediate to strong.

RESULTS

AKT protein was associated (p = 0.012) and correlated (p = 0.014; Tau = - 0.288) with the prognostic groups. The immunostaining for TRPM8 (p = 0.010) and NKX3.1 (p = 0.003) proteins differed between malignant tumor and non-tumoral adjacent tissue as well as for proteins in cellular locations (nucleus and cytoplasm). TRPM8 was independently associated with the ISUP grade ≥ 4 (p = 0.024; OR = 8.373; 95% CI = 1.319-53.164). The NKX3.1 showed positive and predominantly strong immunostaining in all patients in both tumoral and non-tumoral adjacent tissues. All metastatic samples had positive immunostaining, with strong intensity for NKX3.1 (p = 0.021; Tau = - 0.302). In the non-metastatic group, this strong protein staining was not observed in any patients.

CONCLUSION

This study confirmed that NKX3.1 is highly specific for prostate tissue and indicated that NKX3.1, AKT, and TRPM8 may be candidate markers for prostate cancer prognosis.

Glutathione-S-Transferase p1 Gene Promoter Methylation in Cell-Free DNA as a Diagnostic and Prognostic Tool for Prostate Cancer: A Systematic Review and Meta-Analysis

BACKGROUND

Promoter methylation of glutathione-S-transferase p1 (GSTP1) is related to the occurrence of prostate cancer (PCa), but reports are inconsistent about the accuracy of GSTP1 promoter methylation in PCa diagnosis and prognosis. Therefore, we systematically evaluated the diagnostic and prognostic value of GSTP1 promoter methylation in PCa.

METHODS

The PubMed, EMBASE, Web of Science, and PMC databases were searched for all relevant studies from the date of inception to November 31, 2021. We compared differences in the incidence of GSTP1 promoter methylation in cfDNA between prostate cancer patients and controls. The odds ratio (OR) and hazard ratio (HR) were used as effect sizes, and the result of each effect size is expressed as a 95% confidence interval (95% CI).

RESULTS

Our meta-analysis showed that the combined sensitivity and specificity of GSTP1 promoter methylation in cfDNA for the diagnosis of prostate cancer were 0.37 (95% CI = 0.23, 0.53) and 0.97 (95% CI = 0.88, 0.99), respectively. The area under the curve (AUC) with 95% CI was 0.78 (95% CI = 0.75, 0.82). For prognostic variables, hypermethylation of GSTP1 was associated with shorter survival in PCa (HR = 2.57, 95% CI = 1.30, 5.10), with statistical significance in between-study heterogeneity (I ² = 72%, P=0.006). The results of the subgroup analysis indicated that the heterogeneity of studies may be due to differences in the observed indicators.

CONCLUSIONS

The results of the meta-analysis substantiate the high specificity of promoter methylation of GSTP1 in cfDNA for the diagnosis of prostate cancer, and it may be used to more precisely evaluate the prognosis of patients with prostate cancer. It may be helpful for the early detection of prostate cancer, but it still must be combined with traditional prostate-specific antigen (PSA) or other methylated genes to accomplish this goal.

Liver Microenvironment Response to Prostate Cancer Metastasis and Hormonal Therapy

Prostate cancer-associated deaths arise from disease progression and metastasis. Metastasis to the liver is associated with the worst clinical outcomes for prostate cancer patients, and these metastatic tumors can be particularly resistant to the currently widely used chemotherapy and hormonal therapies, such as anti-androgens which block androgen synthesis or directly target the androgen receptor. The incidence of liver metastases is reportedly increasing, with a potential correlation with use of anti-androgen therapies. A key player in prostate cancer progression and therapeutic response is the microenvironment of the tumor(s). This is a dynamic and adaptive collection of cells and proteins, which impart signals and stimuli that can alter biological processes within prostate cancer cells. Investigation in the prostate primary site has demonstrated that cells of the microenvironment are also responsive to hormones and hormonal therapies. In this review, we collate information about what happens when cancer moves to the liver: the types of prostate cancer cells that metastasize there, the response of resident mesenchymal cells of the liver, and how the interactions between the cancer cells and the microenvironment may be altered by hormonal therapy.

Big data in basic and translational cancer research

Historically, the primary focus of cancer research has been molecular and clinical studies of a few essential pathways and genes. Recent years have seen the rapid accumulation of large-scale cancer omics data catalysed by breakthroughs in high-throughput technologies. This fast data growth has given rise to an evolving concept of 'big data' in cancer, whose analysis demands large computational resources and can potentially bring novel insights into essential questions. Indeed, the combination of big data, bioinformatics and artificial intelligence has led to notable advances in our basic understanding of cancer biology and to translational advancements. Further advances will require a concerted effort among data scientists, clinicians, biologists and policymakers. Here, we review the current state of the art and future challenges for harnessing big data to advance cancer research and treatment.

Aberrant gene expression pattern in the glycolysis-cholesterol synthesis axis is linked with immune infiltration and prognosis in prostate cancer: A bioinformatics analysis

Aberrant lipid metabolism is an early event in tumorigenesis and has been found in a variety of tumor types, especially prostate cancer (PCa). Therefore, We hypothesize that PCa can be stratified into metabolic subgroups based on glycolytic and cholesterogenic related genes, and the different subgroups are closely related to the immune microenvironment. Bioinformatics analysis of genomic, transcriptomic, and clinical data from a comprehensive cohort of PCa patients was performed. Datasets included the Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) dataset, GSE70768, our previously published PCa cohort. The unsupervised cluster analysis was employed to stratify PCa samples based on the expression of metabolic-related genes. Four molecular subtypes were identified, named Glycolytic, Cholesterogenic, Mixed, and Quiescent. Each metabolic subtype has specific features. Among the 4 subtypes, the cholesterogenic subtype exhibited better median survival, whereas patients with high expression of glycolytic genes showed the shortest survival. The mitochondrial pyruvate carriers (MPC) 1 exhibited expression difference between PCa metabolic subgroups, but not for MPCs 2. Glycolytic subtypes had lower immune cell scores, while Cholesterogenic subgroups had higher immune cell scores. Our results demonstrated that metabolic classifications based on specific glycolytic and cholesterol-producing pathways provide new biological insights into previously established subtypes and may guide develop personalized therapies for unique tumor metabolism characteristics.

Comprehensive methylome sequencing reveals prognostic epigenetic biomarkers for prostate cancer mortality

BACKGROUND

Prostate cancer is a clinically heterogeneous disease with a subset of patients rapidly progressing to lethal-metastatic prostate cancer. Current clinicopathological measures are imperfect predictors of disease progression. Epigenetic changes are amongst the earliest molecular changes in tumourigenesis. To find new prognostic biomarkers to enable earlier intervention and improved outcomes, we performed methylome sequencing of DNA from patients with localised prostate cancer and long-term clinical follow-up.

METHODS

We used whole-genome bisulphite sequencing (WGBS) to comprehensively map and compare DNA methylation of radical prostatectomy tissue between patients with lethal disease (n = 7) and non-lethal (n = 8) disease (median follow-up 19.5 years). Validation of differentially methylated regions (DMRs) was performed in an independent cohort (n = 185, median follow-up 15 years) using targeted multiplex bisulphite sequencing of candidate regions. Survival was assessed via univariable and multivariable analyses including clinicopathological measures (log-rank and Cox regression models).

RESULTS

WGBS data analysis identified cancer-specific methylation patterns including CpG island hypermethylation, and hypomethylation of repetitive elements, with increasing disease risk. We identified 1420 DMRs associated with prostate cancer-specific mortality (PCSM), which showed enrichment for gene sets downregulated in prostate cancer and de novo methylated in cancer. Through comparison with public prostate cancer datasets, we refined the DMRs to develop an 18-gene prognostic panel. Applying this panel to an independent cohort, we found significant associations between PCSM and hypermethylation at EPHB3, PARP6, TBX1, MARCH6 and a regulatory element within CACNA2D4. Strikingly in a multivariable model, inclusion of CACNA2D4 methylation was a better predictor of PCSM versus grade alone (Harrell's C-index: 0.779 vs. 0.684).

CONCLUSIONS

Our study provides detailed methylome maps of non-lethal and lethal prostate cancer and identifies novel genic regions that distinguish these patient groups. Inclusion of our DNA methylation biomarkers with existing clinicopathological measures improves prognostic models of prostate cancer mortality, and holds promise for clinical application.

Can we use Ki67 expression to predict prostate cancer aggressiveness?

INTRODUCTION

specialists have an urge for biomarkers that can discriminate indolent prostate cancer from aggressive tumors. Ki67 is a proliferation marker, and its expression is associated with the aggressiveness of several cancers.

OBJECTIVE

analyze the expression of Ki67 in prostate cancer samples correlating with the aggressiveness of the disease.

METHODS

Ki67 mRNA levels were determined utilizing data from a TCGA cohort (Tumor(n)=492 and control(n)=52). The protein expression was determined on 94 biopsies from patients by immunohistochemical assay.

RESULTS

in mRNA, the Ki67 upregulation is associated with cancer tissue (p<0.0001) and worst disease-free survival (p=0.035). The protein upregulation is associated with increase of the ISUP score (p<0.0001), cancer stage (p=0.05), biochemical recurrence (p=0.0006) and metastasis (p<0.0001). We also show a positive correlation between Ki67 expression and ISUP score (r=0.5112, p<0.0001) and disease risk stratification (r=0.3388, p=0.0009). Ki67 expression is a factor independently associated with biochemical recurrence (p=0.002) and metastasis (p<0.0001). Finally, the patients with high Ki67expression shows better survival regarding biochemical recurrence (p=0.008) and metastasis (p=0.056). Patients with high Ki67 expression are 2.62 times more likely to develop biochemical recurrence (p=0.036).

CONCLUSION

Ki67 upregulation is associated with prostate cancer aggressiveness.

Large and small cribriform architecture have similar adverse clinical outcome on prostate cancer biopsies

Aims

Invasive cribriform and intraductal carcinoma (IDC) are associated with adverse outcome in prostate cancer patients, with the large cribriform pattern having the worst outcome in radical prostatectomies. Our objective was to determine the impact of the large and small cribriform patterns in prostate cancer biopsies.

Methods and results

Pathological revision was carried out on biopsies of 1887 patients from the European Randomised Study of Screening for Prostate Cancer. The large cribriform pattern was defined as having at least twice the size of adjacent benign glands. The median follow‐up time was 13.4 years. Hazard ratios for metastasis‐free survival (MFS) and disease‐specific survival (DSS) were calculated using Cox proportional hazards regression. Any cribriform pattern was found in 280 of 1887 men: 1.1% IDC in grade group (GG) 1, 18.2% in GG2, 57.1% in GG3, 55.4% in GG4 and 59.3% in GG5; the large cribriform pattern was present in 0, 0.5, 9.8, 18.1 and 17.3%, respectively. In multivariable analyses, small and large cribriform patterns were both (P < 0.005) associated with worse MFS [small: hazard ratio (HR) = 3.04, 95% confidence interval (CI) = 1.93–4.78; large: HR = 3.17, 95% CI = 1.68–5.99] and DSS (small: HR = 4.07, 95% CI = 2.51–6.62; large: HR = 4.13, 95% CI = 2.14–7.98). Patients with the large cribriform pattern did not have worse MFS (P = 0.77) or DSS (P = 0.96) than those with the small cribriform pattern.

Conclusions

Both small and large cribriform patterns are associated with worse MFS and DSS in prostate cancer biopsies. Patients with the large cribriform pattern on biopsy have a similar adverse outcome as those with the small cribriform pattern.

Looking for a Simplified Diagnostic Model to Identify Potentially Lethal Cases of Prostate Cancer at Initial Diagnosis: An ImGO Pilot Study

The recurrent genetic anomalies used to classify prostate cancer (PC) into distinct molecular subtypes have limited relevance for clinical practice. In consideration of WHO 2016 histological classification, which includes the introduction of Gleason Score 4 for patients with cribriform component and the definition of intraductal carcinoma as a new entity, a retrospective pilot study was conducted to investigate, by histological review, if there were any variations of Gleason Score and the incidence of intraductal carcinoma and cribriform pattern, intended as “phenotypic” markers of potentially lethal PC, among metastatic castration-sensitive PC (mCSPC) and metastatic castration-resistant PC (mCRPC) samples. Potentially predictive factors were also assessed. Among 125 cases, a variation in the Gleason Score was reported in 26% of cases. A cribriform (36%) or intraductal (2%) pattern was reported in a higher percentage. Of them, a primary Gleason pattern 4 was reported in 80% of cases. All patients with intraductal carcinoma present a BRCA2 mutation, also found in 80% of cases with a cribriform pattern. This pilot study documented some hypothesis-generating data, as the evaluation of de novo mCSPC and mCRPC as phenotypic/biologic model to be translated in clinical practice. A cribriform pattern/intraductal carcinoma might be a marker of potentially lethal PC. The high incidence of TP53 and BRCA2 mutations in de novo mCSPC may also have a therapeutic implication.

RNA-seq of nine canine prostate cancer cell lines reveals diverse therapeutic target signatures

BACKGROUND

Canine prostate adenocarcinoma (PAC) and transitional cell carcinoma (TCC) are typically characterized by metastasis and chemoresistance. Cell lines are important model systems for developing new therapeutic strategies. However, as they adapt to culturing conditions and undergo clonal selection, they can diverge from the tissue from which they were originally derived. Therefore, a comprehensive characterization of cell lines and their original tissues is paramount.

METHODS

This study compared the transcriptomes of nine canine cell lines derived from PAC, PAC metastasis and TCC to their respective original primary tumor or metastasis tissues. Special interests were laid on cell culture-related differences, epithelial to mesenchymal transition (EMT), the prostate and bladder cancer pathways, therapeutic targets in the PI3K-AKT signaling pathway and genes correlated with chemoresistance towards doxorubicin and carboplatin.

RESULTS

Independent analyses for PAC, PAC metastasis and TCC revealed 1743, 3941 and 463 genes, respectively, differentially expressed in the cell lines relative to their original tissues (DEGs). While genes associated with tumor microenvironment were mostly downregulated in the cell lines, patient-specific EMT features were conserved. Furthermore, examination of the prostate and bladder cancer pathways revealed extensive concordance between cell lines and tissues. Interestingly, all cell lines preserved downstream PI3K-AKT signaling, but each featured a unique therapeutic target signature. Additionally, resistance towards doxorubicin was associated with G2/M cell cycle transition and cell membrane biosynthesis, while carboplatin resistance correlated with histone, m- and tRNA processing.

CONCLUSION

Comparative whole-transcriptome profiling of cell lines and their original tissues identifies models with conserved therapeutic target expression. Moreover, it is useful for selecting suitable negative controls, i.e., cell lines lacking therapeutic target expression, increasing the transfer efficiency from in vitro to primary neoplasias for new therapeutic protocols. In summary, the dataset presented here constitutes a rich resource for canine prostate and bladder cancer research.

Current Methods and Caveats to Risk Factor Assessment in Cutaneous Squamous Cell Carcinoma (cSCC): A Narrative Review

Cutaneous squamous cell carcinoma (cSCC) is the second most common form of skin cancer, and the number of deaths due to cSCC is estimated to be greater than the number attributed to melanoma. While the majority of cSCC tumors are resectable with clear margins by standard excision practices, some lesions exhibit high-risk factors for which there is evidence of their association with recurrence, metastasis, and disease-specific death. The most commonly used staging systems and guidelines in the USA for cSCC are based on these clinical and pathologic high-risk factors; however, these are limited in their ability to predict adverse events, thus posing a challenge for implementing risk-directed patient management. Since the development of local recurrence and/or metastasis has a profound impact on the survival of patients with cSCC, accurate identification of patients at high risk for poor outcomes is critical, potentially allowing for early and appropriate adjuvant therapy. This review summarizes the current cSCC literature with a focus on how differing clinical assessments within each of the five selected risk factors (perineural invasion, differentiation, depth of invasion, size, and location) can influence the evaluation of patient outcomes, along with summarizing the utility of staging and guidelines, and highlighting the potential for molecular tools to improve upon cSCC risk assessment.

Histologically benign PI-RADS 4 and 5 lesions contain cancer-associated epigenetic alterations

BACKGROUND

The detection rate of clinically significant prostate cancer has improved with the use of multiparametric magnetic resonance imaging (mpMRI). Yet, even with MRI-guided biopsy 15%-35% of high-risk lesions (Prostate Imaging-Reporting and Data System [PI-RADS] 4 and 5) are histologically benign. It is unclear if these false positives are due to diagnostic/sampling errors or pathophysiological alterations. To better understand this, we tested histologically benign PI-RAD 4 and 5 lesions for common malignant epigenetic alterations.

MATERIALS AND METHODS

MRI-guided in-bore biopsy samples were collected from 45 patients with PI-RADS 4 (n = 31) or 5 (n = 14) lesions. Patients had a median clinical follow-up of 3.8 years. High-risk mpMRI patients were grouped based on their histology into biopsy positive for tumor (BPT; n = 28) or biopsy negative for tumor (BNT; n = 17). From these biopsy samples, DNA methylation of well-known tumor suppressor genes (APC, GSTP1, and RARβ2) was quantified.

RESULTS

Similar to previous work we observed high rates of promoter methylation at GSTP1 (92.7%), RARβ2 (57.3%), and APC (37.8%) in malignant BPT samples but no methylation in benign TURP chips. Interestingly, similar to the malignant samples the BNT biopsies also had increased methylation at the promoter of GSTP1 (78.8%) and RARβ2 (34.6%). However, despite these epigenetic alterations none of these BNT patients developed prostate cancer, and those who underwent repeat mpMRI (n = 8) demonstrated either radiological regression or stability.

CONCLUSIONS

Histologically benign PI-RADS 4 and 5 lesions harbor prostate cancer-associated epigenetic alterations.

Podemos usar a expressão de Ki67 para prever a agressividade do câncer de próstata?

RESUMO Introdução: especialistas precisam biomarcadores que podem discriminar o câncer de próstata indolente de tumores agressivos. Ki67 é um marcador de proliferação, e sua expressão está associada à agressividade de vários tumores. Objetivo: analisar a expressão do Ki67 em amostras de câncer de próstata correlacionando com a agressividade da doença. Métodos: os níveis de mRNA de Ki67 foram determinados utilizando dados de uma coorte de TCGA (Tumor(n)=492 e controle(n)=52). A expressão da proteína foi determinada em 94 biópsias de pacientes por ensaio imuno-histoquímica. Resultados: no mRNA, a superexpressão Ki67 está associada ao tecido canceroso (p<0,0001) e à pior sobrevida livre de doença (p=0,035). A superexpressão proteica está associada ao aumento do escore ISUP (p<0,0001), estágio de câncer (p=0,05), recorrência bioquímica (p=0,0006) e metástase (p<0,0001). Também mostramos uma correlação positiva entre a expressão Ki67 e o escore ISUP (r=0,5112, p<0,0001) e a estratificação de risco de doença (r=0,3388, p=0,0009). A expressão Ki67 é um fator independentemente associado à recorrência bioquímica (p=0,002) e metástase (p<0,0001). Finalmente, os pacientes com alta expressão de Ki67 expression mostram melhor sobrevivência em relação à recorrência bioquímica (p=0,008) e metástase (p=0,056). Os pacientes com alta expressão de Ki67 são 2,62 vezes mais propensos a desenvolver recorrência bioquímica (p=0,036). Conclusão: a superexpressão Ki67 está associada à agressividade do câncer de próstata.

Application of computer-generated images to train pattern recognition used in semiquantitative immunohistochemistry scoring

This study aimed to clarify whether the pattern recognition involved in scoring proliferation fractions can be trained by abstract computerized images of virtual tissues. Twenty computer-generated images with randomly distributed blue or red dots were scored by 12 probands (all co-workers or collaborators of the Institute of Pathology, University of Bonn). Afterward, the probands underwent a training phase during which they received an immediate feedback on the actual rate of positivity after each image. Finally, the initial testing series was rescored. In a second round with 15 different probands, 20 Ki-67 immunohistochemistry images of tonsil tissue were scored, followed by the same training phase with computer-generated images, before the immunohistochemistry slides were scored again. Paired t-tests were used to compare the differences in mean rates pre- and post-training. Concerning computerized images, untrained probands scored the percentages of positive dots with a mean deviation from the true rates of 8.2%. Following training, the same testing series was scored significantly better with a mean deviation of 4.9% (mean improvement 3.3%, p < 0.001). Scoring real immunohistochemistry slides, the training with computerized images also improved correct estimations, albeit to a lesser degree (mean improvement 1%, p = 0.03). Abstract computerized images of virtual tissues may be a useful tool to train and improve the accuracy of pattern recognition involved in semiquantitative scoring of immunohistochemistry slides. As a side results, this study highlights the value of computer-generated images to verify the performance of image-analysis software.

An RNA-Seq-Based Framework for Characterizing Canine Prostate Cancer and Prioritizing Clinically Relevant Biomarker Candidate Genes

Prostate cancer (PCa) in dogs is a highly malignant disease akin to its human counterpart. In contrast to the situation in humans, multi-gene approaches facilitating risk stratification of canine PCa are barely established. The aims of this study were the characterization of the transcriptional landscape of canine PCa and the identification of diagnostic, prognostic and/or therapeutic biomarkers through a multi-step screening approach. RNA-Sequencing of ten malignant tissues and fine-needle aspirations (FNA), and 14 nonmalignant tissues and FNAs was performed to find differentially expressed genes (DEGs) and deregulated pathways. The 4098 observed DEGs were involved in 49 pathways. These 49 pathways could be grouped into five superpathways summarizing the hallmarks of canine PCa: (i) inflammatory response and cytokines; (ii) regulation of the immune system and cell death; (iii) cell surface and PI3K signaling; (iv) cell cycle; and (v) phagosome and autophagy. Among the highly deregulated, moderately to strongly expressed DEGs that were members of one or more superpathways, 169 DEGs were listed in relevant databases and/or the literature and included members of the PCa pathway, oncogenes, prostate-specific genes, and druggable genes. These genes are novel and promising candidate diagnostic, prognostic and/or therapeutic canine PCa biomarkers.

Molecular Characterization of Prostate Cancers in the Precision Medicine Era

Prostate cancer (PCa) therapy has been recently revolutionized by the approval of new therapeutic agents in the metastatic setting. However, the optimal therapeutic strategy in such patients should be individualized in the light of prognostic and predictive molecular factors, which have been recently studied: androgen receptor (AR) alterations, PTEN-PI3K-AKT pathway deregulation, homologous recombination deficiency (HRD), mismatch repair deficiency (MMRd), and tumor microenvironment (TME) modifications. In this review, we highlighted the clinical impact of prognostic and predictive molecular factors in PCa patients' outcomes, identifying biologically distinct subtypes. We further analyzed the relevant methods to detect these factors, both on tissue, i.e., immunohistochemistry (IHC) and molecular tests, and blood, i.e., analysis of circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA). Moreover, we discussed the main pros and cons of such techniques, depicting their present and future roles in PCa management, throughout the precision medicine era.

Adjuvant therapy for high-risk cutaneous squamous cell carcinoma: 10-year review

Standard of care for high-risk cutaneous squamous cell carcinoma (cSCC) is surgical excision of the primary lesion with clear margins when possible, and additional resection of positive margins when feasible. Even with negative margins, certain high-risk factors warrant consideration of adjuvant therapy. However, which patients might benefit from adjuvant therapy is unclear, and supporting evidence is conflicting and limited to mostly small retrospective cohorts. Here, we review literature from the last decade regarding adjuvant radiation therapy and systemic therapy in high-risk cSCC, including recent and current trials and the role of immune checkpoint inhibitors. We demonstrate evidence gaps in adjuvant therapy for high-risk cSCC and the need for prognostic tools, such as gene expression profiling, to guide patient selection. More large-cohort clinical studies are needed for collecting high-quality, evidence-based data for determining which patients with high-risk cSCC may benefit from adjuvant therapy and which therapy is most appropriate for patient management.

Glyoxalase 1 Expression as a Novel Diagnostic Marker of High-Grade Prostatic Intraepithelial Neoplasia in Prostate Cancer

Glyoxalase 1 (GLO1) is an enzyme involved in the detoxification of methylglyoxal (MG), a reactive oncometabolite formed in the context of energy metabolism as a result of high glycolytic flux. Prior clinical evidence has documented GLO1 upregulation in various tumor types including prostate cancer (PCa). However, GLO1 expression has not been explored in the context of PCa progression with a focus on high-grade prostatic intraepithelial neoplasia (HGPIN), a frequent precursor to invasive cancer. Here, we have evaluated GLO1 expression by immunohistochemistry in archival tumor samples from 187 PCa patients (stage 2 and 3). Immunohistochemical analysis revealed GLO1 upregulation during tumor progression, observable in HGPIN and PCa versus normal prostatic tissue. GLO1 upregulation was identified as a novel hallmark of HGPIN lesions, displaying the highest staining intensity in all clinical patient specimens. GLO1 expression correlated with intermediate-high risk Gleason grade but not with patient age, biochemical recurrence, or pathological stage. Our data identify upregulated GLO1 expression as a molecular hallmark of HGPIN lesions detectable by immunohistochemical analysis. Since current pathological assessment of HGPIN status solely depends on morphological features, GLO1 may serve as a novel diagnostic marker that identifies this precancerous lesion.

Immunohistochemistry for Prostate Biopsy-Impact on Histological Prostate Cancer Diagnoses and Clinical Decision Making

BACKGROUND

To test the value of immunohistochemistry (IHC) staining in prostate biopsies for changes in biopsy results and its impact on treatment decision-making.

METHODS

Between January 2017-June 2020, all patients undergoing prostate biopsies were identified and evaluated regarding additional IHC staining for diagnostic purpose. Final pathologic results after radical prostatectomy (RP) were analyzed regarding the effect of IHC at biopsy.

RESULTS

Of 606 biopsies, 350 (58.7%) received additional IHC staining. Of those, prostate cancer (PCa) was found in 208 patients (59.4%); while in 142 patients (40.6%), PCa could be ruled out through IHC. IHC patients harbored significantly more often Gleason 6 in biopsy (p < 0.01) and less suspicious baseline characteristics than patients without IHC. Of 185 patients with positive IHC and PCa detection, IHC led to a change in biopsy results in 81 (43.8%) patients. Of these patients with changes in biopsy results due to IHC, 42 (51.9%) underwent RP with 59.5% harboring ≥pT3 and/or Gleason 7-10.

CONCLUSIONS

Patients with IHC stains had less suspicious characteristics than patients without IHC. Moreover, in patients with positive IHC and PCa detection, a change in biopsy results was observed in >40%. Patients with changes in biopsy results partly underwent RP, in which 60% harbored significant PCa.

The 2019 Genitourinary Pathology Society (GUPS) White Paper on Contemporary Grading of Prostate Cancer

CONTEXT.—

Controversies and uncertainty persist in prostate cancer grading.

OBJECTIVE.—

To update grading recommendations.

DATA SOURCES.—

Critical review of the literature along with pathology and clinician surveys.

CONCLUSIONS.—

Percent Gleason pattern 4 (%GP4) is as follows: (1) report %GP4 in needle biopsy with Grade Groups (GrGp) 2 and 3, and in needle biopsy on other parts (jars) of lower grade in cases with at least 1 part showing Gleason score (GS) 4 + 4 = 8; and (2) report %GP4: less than 5% or less than 10% and 10% increments thereafter. Tertiary grade patterns are as follows: (1) replace "tertiary grade pattern" in radical prostatectomy (RP) with "minor tertiary pattern 5 (TP5)," and only use in RP with GrGp 2 or 3 with less than 5% Gleason pattern 5; and (2) minor TP5 is noted along with the GS, with the GrGp based on the GS. Global score and magnetic resonance imaging (MRI)-targeted biopsies are as follows: (1) when multiple undesignated cores are taken from a single MRI-targeted lesion, an overall grade for that lesion is given as if all the involved cores were one long core; and (2) if providing a global score, when different scores are found in the standard and the MRI-targeted biopsy, give a single global score (factoring both the systematic standard and the MRI-targeted positive cores). Grade Groups are as follows: (1) Grade Groups (GrGp) is the terminology adopted by major world organizations; and (2) retain GS 3 + 5 = 8 in GrGp 4. Cribriform carcinoma is as follows: (1) report the presence or absence of cribriform glands in biopsy and RP with Gleason pattern 4 carcinoma. Intraductal carcinoma (IDC-P) is as follows: (1) report IDC-P in biopsy and RP; (2) use criteria based on dense cribriform glands (>50% of the gland is composed of epithelium relative to luminal spaces) and/or solid nests and/or marked pleomorphism/necrosis; (3) it is not necessary to perform basal cell immunostains on biopsy and RP to identify IDC-P if the results would not change the overall (highest) GS/GrGp part per case; (4) do not include IDC-P in determining the final GS/GrGp on biopsy and/or RP; and (5) "atypical intraductal proliferation (AIP)" is preferred for an intraductal proliferation of prostatic secretory cells which shows a greater degree of architectural complexity and/or cytological atypia than typical high-grade prostatic intraepithelial neoplasia, yet falling short of the strict diagnostic threshold for IDC-P. Molecular testing is as follows: (1) Ki67 is not ready for routine clinical use; (2) additional studies of active surveillance cohorts are needed to establish the utility of PTEN in this setting; and (3) dedicated studies of RNA-based assays in active surveillance populations are needed to substantiate the utility of these expensive tests in this setting. Artificial intelligence and novel grading schema are as follows: (1) incorporating reactive stromal grade, percent GP4, minor tertiary GP5, and cribriform/intraductal carcinoma are not ready for adoption in current practice.

Report From the International Society of Urological Pathology (ISUP) Consultation Conference on Molecular Pathology of Urogenital Cancers. I. Molecular Biomarkers in Prostate Cancer

The combined clinical and molecular heterogeneity of prostate cancer necessitates the use of prognostic, predictive, and diagnostic biomarkers to assist the clinician with treatment selection. The pathologist plays a critical role in guiding molecular biomarker testing in prostate cancer and requires a thorough knowledge of the current testing options. In the setting of clinically localized prostate cancer, prognostic biomarkers such as Ki-67 labeling, PTEN loss or mRNA-based genomic signatures can be useful to help determine whether definitive therapy is required. In the setting of advanced disease, predictive biomarkers, such as the presence of DNA repair deficiency mediated by BRCA2 loss or mismatch repair gene defects, may suggest the utility of poly-ADP ribosylase inhibition or immune checkpoint blockade. Finally, androgen receptor-related biomarkers or diagnostic biomarkers indicating the presence of small cell neuroendocrine prostate cancer may help guide the use of androgen receptor signaling inhibitors and chemotherapy. In this review, we examine the current evidence for several prognostic, predictive and diagnostic tissue-based molecular biomarkers in prostate cancer management. For each assay, we summarize a recent survey of the International Society of Urology Pathology (ISUP) members on current testing practices and include recommendations for testing that emerged from the ISUP Working Group on Molecular Pathology of Prostate Cancer and the 2019 Consultation Conference on Molecular Pathology of Urogenital Cancers.

Advances in Prognostic Methylation Biomarkers for Prostate Cancer

There is a major clinical need for accurate biomarkers for prostate cancer prognosis, to better inform treatment strategies and disease monitoring. Current clinically recognised prognostic factors, including prostate-specific antigen (PSA) levels, lack sensitivity and specificity in distinguishing aggressive from indolent disease, particularly in patients with localised intermediate grade prostate cancer. There has therefore been a major focus on identifying molecular biomarkers that can add prognostic value to existing markers, including investigation of DNA methylation, which has a known role in tumorigenesis. In this review, we will provide a comprehensive overview of the current state of DNA methylation biomarker studies in prostate cancer prognosis, and highlight the advances that have been made in this field. We cover the numerous studies into well-established candidate genes, and explore the technological transition that has enabled hypothesis-free genome-wide studies and the subsequent discovery of novel prognostic genes.

Potential biomarkers and risk assessment models to enhance the tumor-node-metastasis (TNM) staging classification of urologic cancers

INTRODUCTION

The anatomic-based TNM classification is considered the benchmark in cancer staging and has been regularly updated since its inception. In the current era of precision medicine, the added intention for future TNM modifications is to heighten its impact in the more 'personalized' level of cancer care. In urologic cancers, this goal may be achieved by incorporating 'non-anatomic' factors into TNM, such as biomarkers (e.g. gene alterations, molecular subtypes, genomic classifiers) and risk assessment models (e.g. nomogram, look-up table), while maintaining the anatomic extent as the foundation of staging. These different prognosticators can be combined and integrated, may serve as substratifiers for T, N, or M categories, and perhaps, incorporated as elements in TNM stage groupings to enhance their prognostic capability in urologic cancers.

AREAS COVERED

This review highlights candidate biomarkers and risk assessment models that can be explored to potentially improve TNM prognostication of bladder, prostate, kidney, and testicular cancers.

EXPERT OPINION

Recent advances in molecular analysis have increased the understanding of the genomic, transcriptomic, and epigenetic features for biomarker use in prognostication of urologic cancers, which together with the available risk assessment models, may complement and overcome the limitations of the traditional TNM staging.

Prostate cancer growth patterns beyond the Gleason score: entering a new era of comprehensive tumour grading

The Gleason grading system is one of the most important factors in clinical decision‐making for prostate cancer patients, and is entirely based on the classification of tumour growth patterns. In recent years it has become clear that some individual growth patterns themselves have independent prognostic value, and could be used for better personalised risk stratification. In this review we summarise recent literature on the clinicopathological value and molecular characteristics of individual prostate cancer growth patterns, and show how these, most particularly cribriform architecture, could alter treatment decisions for prostate cancer patients.

Integrating gene expression profiling into NCCN high-risk cutaneous squamous cell carcinoma management recommendations: impact on patient management

Objective: To integrate gene expression profiling into the management of high-risk cutaneous squamous cell carcinoma (cSCC) within the National Comprehensive Cancer Network (NCCN) guidelines to improve risk-aligned management recommendations.Methods: A cohort of 300 NCCN-defined high-risk cSCC patients, along with the American Joint Committee on Cancer (AJCC) T stage, Brigham and Women's Hospital (BWH) T stage, and known patient outcomes were analyzed. Risk classifications using a validated 40-gene expression profile (40-GEP) test and T stage were applied to NCCN patient management guidelines. Risk-directed patient management recommendations within the NCCN guidelines framework were aligned based on risk for metastasis.Results: Of the 300 NCCN high-risk cSCC patients, 159 (53.0%) were 40-GEP Class 1 and AJCC T1-T2, and 173 (57.7%) were Class 1 and BWH T1-2a, indicating low risk for metastasis and, thereby, suggesting low management intensity. The 40-GEP integration suggested high intensity management for only 24 (8.0%) patients (all Class 2B), and moderate intensity management for the remainder of the cohort.Conclusions: The 40-GEP test can be integrated within existing NCCN guideline recommendations for managing cSCC patients to help refine risk-directed management decisions. Integration of the 40-GEP test would allow >50% of this NCCN-defined high-risk cohort to be managed with the lowest intensity recommendations within the broad NCCN guidelines. High intensity management was deemed risk-appropriate for a small subpopulation (8.0%). This study demonstrates that the 40-GEP test, in combination with T stage, has clinical utility to impact patient management decisions in NCCN high-risk cSCC for improving risk-aligned management within the NCCN guidelines framework.

Validation of a 40-gene expression profile test to predict metastatic risk in localized high-risk cutaneous squamous cell carcinoma

BACKGROUND

Current staging systems for cutaneous squamous cell carcinoma (cSCC) have limited positive predictive value for identifying patients who will experience metastasis.

OBJECTIVE

To develop and validate a gene expression profile (GEP) test for predicting risk for metastasis in localized, high-risk cSCC with the goal of improving risk-directed patient management.

METHODS

Archival formalin-fixed paraffin-embedded primary cSCC tissue and clinicopathologic data (n = 586) were collected from 23 independent centers in a prospectively designed study. A GEP signature was developed using a discovery cohort (n = 202) and validated in a separate, nonoverlapping, independent cohort (n = 324).

RESULTS

A prognostic 40-GEP test was developed and validated, stratifying patients with high-risk cSCC into classes based on metastasis risk: class 1 (low risk), class 2A (high risk), and class 2B (highest risk). For the validation cohort, 3-year metastasis-free survival rates were 91.4%, 80.6%, and 44.0%, respectively. A positive predictive value of 60% was achieved for the highest-risk group (class 2B), an improvement over staging systems, and negative predictive value, sensitivity, and specificity were comparable to staging systems.

LIMITATIONS

Potential understaging of cases could affect metastasis rate accuracy.

CONCLUSION

The 40-GEP test is an independent predictor of metastatic risk that can complement current staging systems for patients with high-risk cSCC.

A new era: artificial intelligence and machine learning in prostate cancer

Artificial intelligence (AI) - the ability of a machine to perform cognitive tasks to achieve a particular goal based on provided data - is revolutionizing and reshaping our health-care systems. The current availability of ever-increasing computational power, highly developed pattern recognition algorithms and advanced image processing software working at very high speeds has led to the emergence of computer-based systems that are trained to perform complex tasks in bioinformatics, medical imaging and medical robotics. Accessibility to 'big data' enables the 'cognitive' computer to scan billions of bits of unstructured information, extract the relevant information and recognize complex patterns with increasing confidence. Computer-based decision-support systems based on machine learning (ML) have the potential to revolutionize medicine by performing complex tasks that are currently assigned to specialists to improve diagnostic accuracy, increase efficiency of throughputs, improve clinical workflow, decrease human resource costs and improve treatment choices. These characteristics could be especially helpful in the management of prostate cancer, with growing applications in diagnostic imaging, surgical interventions, skills training and assessment, digital pathology and genomics. Medicine must adapt to this changing world, and urologists, oncologists, radiologists and pathologists, as high-volume users of imaging and pathology, need to understand this burgeoning science and acknowledge that the development of highly accurate AI-based decision-support applications of ML will require collaboration between data scientists, computer researchers and engineers.

Where is the limit of prostate cancer biomarker research? Systematic investigation of potential prognostic and diagnostic biomarkers

BACKGROUND

The identification of appropriate biomarkers is essential to support important clinical decisions in patients with prostate cancer. The aim of our study was a systematic bioinformatical analysis of the mRNA expression of all genes available for the prostate adenocarcinoma cohort of The Cancer Genome Atlas (TCGA), regarding their potential prognostic and diagnostic role.

METHODS

The study cohort comprises 499 patients (TCGA prostate cancer cohort). mRNA expression data were available for approx. 20,000 genes. The bioinformatical statistical pipeline addressed gene expression differences in tumor vs. benign prostate tissue (including gene set enrichment analysis, GSEA) in samples from tumors with different aggressivenesses (Gleason score), as well as prognostic values in multistep survival analyses.

RESULTS

Among all genes analyzed, 1754 were significantly downregulated and 1553 genes were significantly upregulated in tumor tissue. In GSEA, 16 of 30 top enriched biological processes were alterations of epigenetic regulation at different levels. Significant correlation with Gleason Score was evident for 8724 genes (range of Pearson r-values 0.09-0.43; all p < 0.05). In univariate Cox regression analyses, mRNA expression of 3571 genes showed statistically significant association with biochemical recurrence-free survival with a range of hazard ratios 0.3-3.8 (p-value 7.4e- 07 to 0.05). Among these, 571 genes were independently associated with biochemical recurrence in multivariate analysis. Access to the full database including results is provided as supplement.

CONCLUSIONS

In our systematic analysis we found a big number of genes of potential diagnostic and prognostic value, many of which have not been studied in prostate cancer to date. Due to the comprehensive nature of this analysis and free access to the results, this study represents a reference database for prostate cancer researchers which can be used as a powerful tool for validation purposes and planning of new studies.

Multi-region proteome analysis quantifies spatial heterogeneity of prostate tissue biomarkers

Application of pressure cycling technology and Sequential Windowed Acquisition of all THeoretical mass spectrometry allows quantifying the degree of intra-tumor heterogeneity of protein expression in prostate tumors. The data show that protein intra-tumor heterogeneity, if not characterized, may distort protein biomarker suitability in tumor tissues.

It remains unclear to what extent tumor heterogeneity impacts on protein biomarker discovery. Here, we quantified proteome intra-tissue heterogeneity (ITH) based on a multi-region analysis of prostate tissues using pressure cycling technology and Sequential Windowed Acquisition of all THeoretical fragment ion mass spectrometry. We quantified 6,873 proteins and analyzed the ITH of 3,700 proteins. The level of ITH varied depending on proteins and tissue types. Benign tissues exhibited more complex ITH patterns than malignant tissues. Spatial variability of 10 prostate biomarkers was validated by immunohistochemistry in an independent cohort (n = 83) using tissue microarrays. Prostate-specific antigen was preferentially variable in benign prostatic hyperplasia, whereas growth/differentiation factor 15 substantially varied in prostate adenocarcinomas. Furthermore, we found that DNA repair pathways exhibited a high degree of variability in tumorous tissues, which may contribute to the genetic heterogeneity of tumors. This study conceptually adds a new perspective to protein biomarker discovery: it suggests that recent technological progress should be exploited to quantify and account for spatial proteome variation to complement biomarker identification and utilization.