Genes involved in prostate cancer progression determine MRI visibility

Is MRI ready to replace biopsy during active surveillance?

Active surveillance (AS) is a conservative management option recommended for patients diagnosed with low-risk prostate cancer (PCa) and selected cases with intermediate-risk PCa. The adoption of prostate MRI in the primary diagnostic setting has sparked interest in its application during AS. This review aims to examine the role and performance of multiparametric MRI (mpMRI) across the entire AS pathway, from initial stratification to follow-up, also relative to the utilization of the Prostate Cancer Radiological Estimation of Change in Sequential Evaluation (PRECISE) criteria. Given the high negative predictive value of mpMRI in detecting clinically significant PCa (csPCa), robust evidence supports its use in patient selection and risk stratification at the time of diagnosis or confirmatory biopsy. However, conflicting results have been observed when using MRI in evaluating disease progression during follow-up. Key areas requiring clarification include addressing the clinical significance of MRI-negative csPCa, optimizing MRI quality, determining the role of biparametric MRI (bpMRI) or mpMRI protocols, and integrating artificial intelligence (AI) for improved performance. CLINICAL RELEVANCE STATEMENT: MRI plays an essential role in the selection, stratification, and follow up of patients in active surveillance (AS) for prostate cancer. However, owing to existing limitations, it cannot fully replace biopsies in the context of AS. KEY POINTS: Multiparametric MRI (mpMRI) has become a crucial tool in active surveillance (AS) for prostate cancer (PCa). Conflicting results have been observed regarding multiparametric MRI efficacy in assessing disease progression. Standardizing MRI-guided protocols will be critical in addressing current limitations in active surveillance for prostate cancer.

Comparison of Multiparametric MRI-targeted and Systematic Biopsies for Detection of Cribriform and Intraductal Carcinoma Prostate Cancer

Background Intraductal carcinoma (IDC) and invasive cribriform (Cr) subtypes of prostate cancer (PCa) are an indication of aggressiveness, but the evidence regarding whether MRI can be used to detect Cr/IDC-pattern PCa is contradictory. Purpose To compare the detection of Cr/IDC-pattern PCa at multiparametric MRI (mpMRI)-targeted biopsy versus systematic biopsy in biopsy-naive men at risk for PCa. Materials and Methods This study was a secondary analysis of a prospective randomized controlled trial that recruited participants with a clinical suspicion of PCa between April 2017 and November 2019 at five centers. Participants were randomized 1:1 to either the MRI arm or the systematic biopsy arm. Targeted biopsy was performed in participants with a Prostate Imaging Reporting and Data System score of at least 3. MRI features were recorded, and biopsy slides and prostatectomy specimens were reviewed for the presence or absence of Cr/IDC histologic patterns. Comparison of Cr/IDC patterns was performed using generalized linear mixed modeling. Results A total of 453 participants were enrolled, with 226 in the systematic biopsy arm (median age, 65 years [IQR, 59-70 years]; 196 biopsies available for assessment) and 227 in the mpMRI-targeted biopsy arm (median age, 67 years [IQR, 60-72 years]; 132 biopsies available for assessment). Identification of Cr/IDC PCa was lower in the systematic biopsy arm compared with the mpMRI arm (31 of 196 biopsies [16%] vs 33 of 132 biopsies [25%]; P = .01). No evidence of a difference in mean cancer core length (CCL) (11.3 mm ± 4.4 vs 9.7 mm ± 4.5; P = .09), apparent diffusion coefficient (685 µm2/sec ± 178 vs 746 µm2/sec ± 245; P = .52), or dynamic contrast-enhanced positivity (27 [82%] vs 37 [90%]; P = .33) for clinically significant PCa (csPCa) was observed between participants with or without Cr/IDC disease in the MRI arm. Cr/IDC-positive histologic patterns overall had a higher mean CCL compared with Cr/IDC-negative csPCa (11.1 mm ± 4.4 vs 9.2 mm ± 4.1; P = .009). Conclusion MRI-targeted biopsy showed increased detection of Cr/IDC histologic patterns compared with systematic biopsy. Clinical trial registration no. NCT02936258 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Scialpi and Martorana in this issue.

Lifetime Health and Economic Outcomes of Biparametric Magnetic Resonance Imaging as First-Line Screening for Prostate Cancer : A Decision Model Analysis

BACKGROUND

Contemporary prostate cancer (PCa) screening uses first-line prostate-specific antigen (PSA) testing, possibly followed by multiparametric magnetic resonance imaging (mpMRI) for men with elevated PSA levels. First-line biparametric MRI (bpMRI) screening has been proposed as an alternative.

OBJECTIVE

To evaluate the comparative effectiveness and cost-effectiveness of first-line bpMRI versus PSA-based screening.

DESIGN

Decision analysis using a microsimulation model.

DATA SOURCES

Surveillance, Epidemiology, and End Results database; randomized trials.

TARGET POPULATION

U.S. men aged 55 years with no prior screening or PCa diagnosis.

TIME HORIZON

Lifetime.

PERSPECTIVE

U.S. health care system.

INTERVENTION

Biennial screening to age 69 years using first-line PSA testing (test-positive threshold, 4 µg/L) with or without second-line mpMRI or first-line bpMRI (test-positive threshold, PI-RADS [Prostate Imaging Reporting and Data System] 3 to 5 or 4 to 5), followed by biopsy guided by MRI or MRI plus transrectal ultrasonography.

OUTCOME MEASURES

Screening tests, biopsies, diagnoses, overdiagnoses, treatments, PCa deaths, quality-adjusted and unadjusted life-years saved, and costs.

RESULTS OF BASE-CASE ANALYSIS

For 1000 men, first-line bpMRI versus first-line PSA testing prevented 2 to 3 PCa deaths and added 10 to 30 life-years (4 to 11 days per person) but increased the number of biopsies by 1506 to 4174 and the number of overdiagnoses by 38 to 124 depending on the biopsy imaging scheme. At conventional cost-effectiveness thresholds, first-line PSA testing with mpMRI followed by either biopsy approach for PI-RADS 4 to 5 produced the greatest net monetary benefits.

RESULTS OF SENSITIVITY ANALYSIS

First-line PSA testing remained more cost-effective even if bpMRI was free, all men with low-risk PCa underwent surveillance, or screening was quadrennial.

LIMITATION

Performance of first-line bpMRI was based on second-line mpMRI data.

CONCLUSION

Decision analysis suggests that comparative effectiveness and cost-effectiveness of PCa screening are driven by false-positive results and overdiagnoses, favoring first-line PSA testing with mpMRI over first-line bpMRI.

PRIMARY FUNDING SOURCE

National Cancer Institute.

Should systematic prostatic biopsies be discontinued?

INTRODUCTION

The use of systematic biopsies in addition to targeted biopsies is based on multiple studies showing that 15-20% of "clinically significant" cancers are missed on targeted biopsies. Concern about these 'missed' cancers drives many interventions. This includes systematic biopsies in men with negative imaging and in men having targeted biopsies, and drives a preference for total gland treatment in men who may be candidates for partial gland ablation. This article summarizes recent genomic and clinical data indicating that, despite "clinically significant" histology, MRI invisible lesions are genomically and clinically favorable. These studies have demonstrated that the genetic aberrations associated with cancer visibility are the same aberrations that drive cancer invasiveness and metastasis. Thus invisible cancers, even if undiagnosed at baseline, are in most cases indolent and pose little threat to the patient. The implications are that patients should be monitored with imaging rather than systematic biopsy, and subject to repeat targeted biopsy for evidence of MR progression. Patients prefer this strategy. It has many advantages in terms of reduced burden of care, cost, psychological benefits, and less diagnosis of insignificant cancer.

CONCLUSION

It is now appropriate to abandon systematic biopsies in most patients.

Magnetic Resonance Imaging-Targeted Versus Systematic Prostate Biopsies: 2-year Follow-up of a Prospective Randomized Trial (PRECISE)

BACKGROUND

The prospective randomized PRECISE trial demonstrated that magnetic resonance imaging (MRI) with only targeted biopsy (TBx) was noninferior to systematic transrectal ultrasound biopsy (SBx) in the detection of International Society of Urological Pathology grade group (GG) ≥2 prostate cancer (PC). An unanswered question is the outcome for patients who avoided a biopsy because of negative MRI findings.

OBJECTIVE

To explore the rate of PC diagnosis based on 2-yr MRI for PRECISE participants who had no biopsy and for patients who had a negative result or GG 1 on TBx in comparison to those with a negative result or GG 1 on SBx.

DESIGN, SETTING, AND PARTICIPANTS

The PRECISE prospective trial was conducted at five Canadian academic centers. The present analysis was for trial participants who were not diagnosed with clinically significant PC (csPC) at baseline. Of 453 randomized patients, 146 were diagnosed with GG ≥2 at baseline and were excluded. Eligible patients for this study included 83 men from the MRI arm who had negative MRI findings and no biopsy, 120 from the overall cohort who had a negative SBx or TBx, and 72 from the overall cohort who were diagnosed with GG 1 disease.

INTERVENTION

MRI at 2 yr in all men in the MRI and SBx arms and TBx for lesions with a Prostate Imaging-Reporting and Data System score of ≥3 or on the basis of clinical suspicion.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

The primary outcome was the proportion of men diagnosed with GG ≥2 cancer. Secondary outcomes included the MRI outcome and the proportion of men diagnosed with GG 1 PC.

RESULTS AND LIMITATIONS

Evaluable 2-yr MRI scans were available for 75 (56%) eligible patients in the MRI arm and 69 (49%) in the SBx arm. Of these patients, 55 (73%) in the MRI arm and 51 (67%) SBx arm had negative 2-yr MRI. Of the 76 patients in the SBx arm with 2-yr MRI, 16 (21%) had a biopsy, for which the result was negative in eight (10%), GG1 in two (2.6%), and GG ≥2 in six (7.9%) cases. Of the 75 men in the MRI arm with 2-yr MRI, eight (11%) were biopsied, for which the result was negative in four cases (5%) and GG ≥2 in the other four (5%). At 2 yr, including baseline biopsy results, 116/221 (52.5%) in the MRI arm and 113/204 (55%) in the SBx arm were free of GG ≥2 disease, treatment, death from any cause, or progression (OR 1.08; p = 0.66).

CONCLUSIONS

After 2-yr follow-up including MRI for patients in both arms of PRECISE, there was no difference in the rate of csPC diagnosis between the MRI and SBx groups, even though 38% of men in the MRI group avoided an initial biopsy.

PATIENT SUMMARY

The PRECISE trial compared systematic biopsy of the prostate to a strategy of magnetic resonance imaging (MRI) with targeted biopsy of any lesions suspicious for cancer on the scan. After 2 years of follow-up that included 2-year MRI with or without biopsy in both groups, there was no difference in the rate of diagnosis of significant cancer, even though 38% of men in the initial MRI arm avoided an initial biopsy, and 30% avoided biopsy altogether. The PRECISE trial is registered on ClinicalTrials.gov as NCT02936258.

Histomic and transcriptomic features of MRI-visible and invisible clinically significant prostate cancers are associated with prognosis

Magnetic resonance imaging (MRI) is increasingly used to triage patients for prostate biopsy. However, 9% to 24% of clinically significant (cs) prostate cancers (PCas) are not visible in MRI. We aimed to identify histomic and transcriptomic determinants of MRI visibility and their association to metastasis, and PCa-specific death (PCSD). We studied 45 radical prostatectomy-treated patients with csPCa (grade group [GG]2-3), including 30 with MRI-visible and 15 with MRI-invisible lesions, and 18 men without PCa. First, histological composition was quantified. Next, transcriptomic profiling was performed using NanoString technology. MRI visibility-associated differentially expressed genes (DEGs) and Reactome pathways were identified. MRI visibility was classified using publicly available genes in MSK-IMPACT and Decipher, Oncotype DX, and Prolaris. Finally, DEGs and clinical parameters were used to classify metastasis and PCSD in an external cohort, which included 76 patients with metastatic GG2-4 PCa, and 84 baseline-matched controls without progression. Luminal area was lower in MRI-visible than invisible lesions and low luminal area was associated with short metastasis-free and PCa-specific survival. We identified 67 DEGs, eight of which were associated with survival. Cell division, inflammation and transcriptional regulation pathways were upregulated in MRI-visible csPCas. Genes in Decipher, Oncotype DX and MSK-IMPACT performed well in classifying MRI visibility (AUC = 0.86-0.94). DEGs improved classification of metastasis (AUC = 0.69) and PCSD (AUC = 0.68) over clinical parameters. Our data reveals that MRI-visible csPCas harbor more aggressive histomic and transcriptomic features than MRI-invisible csPCas. Thus, targeted biopsy of visible lesions may be sufficient for risk stratification in patients with a positive MRI.

Clinical significance of prostate cancer identified by transperineal standard template biopsy in men with nonsuspicious multiparametric magnetic resonance imaging

OBJECTIVE

Multiparametric magnetic resonance imaging (mpMRI) of the prostate has excellent sensitivity in detecting clinically significant prostate cancer (csCaP). However, whether a negative mpMRI in patients with a clinical suspicion of CaP can omit a confirmatory biopsy remains less understood and without consensus. Transperineal (TP) standard template biopsy (SBx) provides an effective approach to CaP detection. Our aim is to provide a comprehensive understanding of the CaP characteristics detected through TP SBx that are systematically overlooked by mpMRI.

METHODS

We conducted a retrospective analysis of all men who underwent prebiopsy mpMRI and subsequent a 20-core TP SBx at our hospital from September 2019 to February 2021. Patients with suspicious mpMRI received a combined TP SBx and targeted biopsy (TBx) (suspicious group), while those without suspicious (negative) mpMRI and who proceeded to biopsy, received TP SBx only (nonsuspicious group). A negative mpMRI was defined as the absence of suspicious findings and/or the presence of low-risk areas with a PI-RADS score of ≤2. Subsequently, we compared and evaluated the clinical and biopsy characteristics between these 2 groups.

RESULTS

We identified 301 men in suspicious group and 215 men in nonsuspicious group. The overall CaP detection rate and csCaP detection rate by TP SBx were 74.1%, 38.9% for suspicious group and 43.3%, 14.9% for nonsuspicious group, respectively. csCaP NPV of mpMRI was 85.1% with a csCaP prevalence 28.9%. The greatest percentage of cancer involvement (GPC) in biopsy core from nonsuspicious group was significantly lower than those of suspicious group (40% vs. 50%, p = 0.005), In multivariate logistic analysis, only PSAD > 0.15 ng/ml/cc was identified as an independent and significant predictor of csCaP in nonsuspicious group.

CONCLUSION

Within our cohort, false-negative rates of mpMRI for csCaP are substantial, reaching 15%. Nonsuspicious cases may contain a large volume tumor since the high GPC of SBx. For cases with nonsuspicious imaging and higher PSAD, a confirmatory biopsy may be necessary due to the increased risk of missed csCaP by mpMRI.

Systematic review and integrated analysis of prognostic gene signatures for prostate cancer patients

Prostate cancer (PC) is one of the most common cancers in men and becoming the second leading cause of cancer fatalities. At present, the lack of effective strategies for prognosis of PC patients is still a problem to be solved. Therefore, it is significant to identify potential gene signatures for PC patients' prognosis. Here, we summarized 71 different prognostic gene signatures for PC and concluded 3 strategies for signature construction after extensive investigation. In addition, 14 genes frequently appeared in 71 different gene signatures, which enriched in mitotic and cell cycle. This review provides extensive understanding and integrated analysis of current prognostic signatures of PC, which may help researchers to construct gene signatures of PC and guide future clinical treatment.

Management of Patients With a Negative Multiparametric Prostate MRI Examination: AJR Expert Panel Narrative Review

Multiparametric MRI (mpMRI) of the prostate aids risk stratification of patients with elevated PSA levels. Although most clinically significant prostate cancers are detected by mpMRI, insignificant cancers are less evident. Thus, multiple international prostate cancer guidelines now endorse routine use of prostate MRI as a secondary screening test before prostate biopsy. Nonetheless, management of patients with negative mpMRI results (defined as PI-RADS category 1 or 2) remains unclear. This AJR Expert Panel Narrative Review summarizes the available literature on patients with an elevated screening PSA level and a negative prostate mpMRI result and provides guidance for these patients' management. Systematic biopsy should not be routinely performed after a negative mpMRI examination in patients at average risk but should be considered in patients at high risk. In patients who undergo PSA screening rather than systematic biopsy after negative mpMRI, clear triggers should be established for when to perform a repeat MRI examination. Patients with a negative MRI result followed by negative biopsy should follow their health care practitioners' preferred guidelines concerning subsequent PSA screening for the patient's risk level. Insufficient high-level data exist to support routine use of adjunctive serum or urine biomarkers, artificial intelligence, or PSMA PET to determine the need for prostate biopsy after a negative mpMRI examination.

Genetic and epigenetic features of neuroendocrine prostate cancer and their emerging applications

Prostate cancer is the second most prevalent cancer in men globally. De novo neuroendocrine prostate cancer (NEPC) is uncommon at initial diagnosis, however, (treatment-induced) t-NEPC emerges in up to 25% of prostate adenocarcinoma (PRAD) cases treated with androgen deprivation, carrying a drastically poor prognosis. The transition from PRAD to t-NEPC is underpinned by several key genetic mutations; TP53, RB1, and MYCN are the main genes implicated, bearing similarities to other neuroendocrine tumours. A broad range of epigenetic alterations, such as aberrations in DNA methylation, histone post-translational modifications, and non-coding RNAs, may drive lineage plasticity from PRAD to t-NEPC. The clinical diagnosis of NEPC is hampered by a lack of accessible biomarkers; recent advances in liquid biopsy techniques assessing circulating tumour cells and ctDNA in NEPC suggest that the advent of non-invasive means of monitoring progression to NEPC is on the horizon. Such techniques are vital for NEPC management; diagnosis of t-NEPC is crucial for implementing effective treatment, and precision medicine will be integral to providing the best outcomes for patients.

Comparison of Multiparametric Magnetic Resonance Imaging with Prostate-Specific Membrane Antigen Positron-Emission Tomography Imaging in Primary Prostate Cancer Diagnosis: A Systematic Review and Meta-Analysis

Multiparametric magnetic-resonance imaging (mpMRI) has proven utility in diagnosing primary prostate cancer. However, the diagnostic potential of prostate-specific membrane antigen positron-emission tomography (PSMA PET) has yet to be established. This study aims to systematically review the current literature comparing the diagnostic performance of mpMRI and PSMA PET imaging to diagnose primary prostate cancer. A systematic literature search was performed up to December 2021. Quality analyses were conducted using the QUADAS-2 tool. The reference standard was whole-mount prostatectomy or prostate biopsy. Statistical analysis involved the pooling of the reported diagnostic performances of each modality, and differences in per-patient and per-lesion analysis were compared using a Fisher’s exact test. Ten articles were included in the meta-analysis. At a per-patient level, the pooled values of sensitivity, specificity, and area under the curve (AUC) for mpMRI and PSMA PET/CT were 0.87 (95% CI: 0.83−0.91) vs. 0.93 (95% CI: 0.90−0.96, p < 0.01); 0.47 (95% CI: 0.23−0.71) vs. 0.54 (95% CI: 0.23−0.84, p > 0.05); and 0.84 vs. 0.91, respectively. At a per-lesion level, the pooled sensitivity, specificity, and AUC value for mpMRI and PSMA PET/CT were lower, at 0.63 (95% CI: 0.52−0.74) vs. 0.79 (95% CI: 0.62−0.92, p < 0.001); 0.88 (95% CI: 0.81−0.95) vs. 0.71 (95% CI: 0.47−0.90, p < 0.05); and 0.83 vs. 0.84, respectively. High heterogeneity was observed between studies. PSMA PET/CT may better confirm the presence of prostate cancer than mpMRI. However, both modalities appear comparable in determining the localisation of the lesions.

Prostate cancer multiparametric magnetic resonance imaging visibility is a tumor-intrinsic phenomena

Multiparametric magnetic resonance imaging (mpMRI) is an emerging standard for diagnosing and prognosing prostate cancer, but ~ 20% of clinically significant tumors are invisible to mpMRI, as defined by the Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) score of one or two. To understand the biological underpinnings of tumor visibility on mpMRI, we examined the proteomes of forty clinically significant tumors (i.e., International Society of Urological Pathology (ISUP) Grade Group 2)—twenty mpMRI-visible and twenty mpMRI-invisible, with matched histologically normal prostate. Normal prostate tissue was indistinguishable between patients with visible and invisible tumors, and invisible tumors closely resembled the normal prostate. These data indicate that mpMRI-visibility arises when tumor evolution leads to large-magnitude proteomic divergences from histologically normal prostate.

Cholesterol-Lowering Intervention Decreases mTOR Complex 2 Signaling and Enhances Antitumor Immunity

PURPOSE

There is a need for strategies to prevent prostate cancer. Cholesterol-lowering interventions are employed widely and safely to reduce risk of cardiovascular disease and has been proposed for chemoprevention. Using preclinical models and a window-of-opportunity clinical trial, we describe an adaptive antitumor immunity resulting from cholesterol lowering.

EXPERIMENTAL DESIGN

Statins do not reliably lower serum cholesterol in mice. Therefore, oral ezetimibe was administered to mice to lower serum cholesterol to clinically relevant levels and evaluated the final adaptive immune response. T-lymphocytes-specific mTORC2 knockout mice were used to evaluate mTOR signaling and antitumor immunity. Pretreatment and posttreatment prostate tumors and lymphocytes were examined from a window-of-opportunity clinical trial where men with prostate cancer were treated with 2 to 6 weeks of aggressive cholesterol-lowering intervention prior to radical prostatectomy.

RESULTS

Mice treated with oral ezetimibe exhibited enhanced antitumor immunity against syngeneic cancers in a CD8+ lymphocyte-dependent manner, produced immunity that was transferrable through lymphocytes, and had enhanced central CD8+ T-cell memory. In mice and in patients undergoing prostatectomy, lowering serum cholesterol inhibited mTORC2 signaling in lymphocytes and increased infiltration of CD8+ lymphocytes into prostate tumors. T-lymphocyte-specific mTORC2 knockout mice demonstrated enhanced CD8+ lymphocyte function and antitumor capacity. In patients, cholesterol-lowering intervention prior to prostatectomy decreased the proliferation of normal prostate and low-grade adenocarcinomas.

CONCLUSIONS

Lowering serum cholesterol decreased signaling through mTORC2 and enhanced antitumor CD8+ T-cell memory. We provide a rationale for large-scale clinical testing of cholesterol lowering strategies for prostate cancer chemoprevention.

Regulation of Neuroendocrine-like Differentiation in Prostate Cancer by Non-Coding RNAs

Neuroendocrine prostate cancer (NEPC) represents a variant of prostate cancer that occurs in response to treatment resistance or, to a much lesser extent, de novo. Unravelling the molecular mechanisms behind transdifferentiation of cancer cells to neuroendocrine-like cancer cells is essential for development of new treatment opportunities. This review focuses on summarizing the role of small molecules, predominantly microRNAs, in this phenomenon. A published literature search was performed to identify microRNAs, which are reported and experimentally validated to modulate neuroendocrine markers and/or regulators and to affect the complex neuroendocrine phenotype. Next, available patients’ expression datasets were surveyed to identify deregulated microRNAs, and their effect on NEPC and prostate cancer progression is summarized. Finally, possibilities of miRNA detection and quantification in body fluids of prostate cancer patients and their possible use as liquid biopsy in prostate cancer monitoring are discussed. All the addressed clinical and experimental contexts point to an association of NEPC with upregulation of miR-375 and downregulation of miR-34a and miR-19b-3p. Together, this review provides an overview of different roles of non-coding RNAs in the emergence of neuroendocrine prostate cancer.

The Multifaceted Role of Aldehyde Dehydrogenases in Prostate Cancer Stem Cells

Cancer stem cells (CSCs) are the only tumor cells possessing self-renewal and differentiation properties, making them an engine of tumor progression and a source of tumor regrowth after treatment. Conventional therapies eliminate most non-CSCs, while CSCs often remain radiation and drug resistant, leading to tumor relapse and metastases. Thus, targeting CSCs might be a powerful tool to overcome tumor resistance and increase the efficiency of current cancer treatment strategies. The identification and isolation of the CSC population based on its high aldehyde dehydrogenase activity (ALDH) is widely accepted for prostate cancer (PCa) and many other solid tumors. In PCa, several ALDH genes contribute to the ALDH activity, which can be measured in the enzymatic assay by converting 4, 4-difluoro-4-bora-3a, 4a-diaza-s-indacene (BODIPY) aminoacetaldehyde (BAAA) into the fluorescent product BODIPY-aminoacetate (BAA). Although each ALDH isoform plays an individual role in PCa biology, their mutual functional interplay also contributes to PCa progression. Thus, ALDH proteins are markers and functional regulators of CSC properties, representing an attractive target for cancer treatment. In this review, we discuss the current state of research regarding the role of individual ALDH isoforms in PCa development and progression, their possible therapeutic targeting, and provide an outlook for the future advances in this field.

Prostate Cancer Radiogenomics-From Imaging to Molecular Characterization

Radiomics and genomics represent two of the most promising fields of cancer research, designed to improve the risk stratification and disease management of patients with prostate cancer (PCa). Radiomics involves a conversion of imaging derivate quantitative features using manual or automated algorithms, enhancing existing data through mathematical analysis. This could increase the clinical value in PCa management. To extract features from imaging methods such as magnetic resonance imaging (MRI), the empiric nature of the analysis using machine learning and artificial intelligence could help make the best clinical decisions. Genomics information can be explained or decoded by radiomics. The development of methodologies can create more-efficient predictive models and can better characterize the molecular features of PCa. Additionally, the identification of new imaging biomarkers can overcome the known heterogeneity of PCa, by non-invasive radiological assessment of the whole specific organ. In the future, the validation of recent findings, in large, randomized cohorts of PCa patients, can establish the role of radiogenomics. Briefly, we aimed to review the current literature of highly quantitative and qualitative results from well-designed studies for the diagnoses, treatment, and follow-up of prostate cancer, based on radiomics, genomics and radiogenomics research.

Patient- and tumor-level risk factors for MRI-invisible prostate cancer

BACKGROUND

Multiparametric MRI is highly sensitive for detection of clinically significant prostate cancer, but has a 10-20% false negative rate. It is unknown if there are clinical factors that predict MRI invisibility. We sought to identify predictors of MRI-invisible (MRI(-)) disease.

METHODS

Men undergoing MRI/US-fusion targeted + systematic biopsy by two surgeons at our institution from 2015 to 2018 were reviewed. Patient demographics, clinical data, MRI metrics, and biopsy pathology results were obtained by chart review. An MRI(-) tumor was defined as a positive systematic biopsy in a zone without an MRI lesion. Factors associated with presence of MRI(-) tumors were identified using stepwise multivariable logistic regression.

RESULTS

Of 194 men included in the analysis, 79 (41%) and 25 (13%) men had GG1+ and GG2+ MRI(-) tumors, respectively. On multivariable analysis, only Black race was associated with presence of GG1+ MRI(-) tumors (OR 2.2, 95% CI 1.02-4.96). Black race (OR 3.5, 95% CI 1.24-9.87) and higher PSA density (OR 2.0, 95% CI 1.34-3.20) were associated with presence of GG2+ MRI(-) tumors. In non-Black and Black men, detection of MRI(-) tumors on systematic biopsy upgraded patients from no disease to GG2+ disease 1% and 11% of the time, respectively, and from GG1 to GG2+ disease 42% and 60% of the time, respectively.

CONCLUSIONS

Black race and PSA density were associated with presence of MRI(-) prostate cancer. Further study on racial differences is warranted based on these results. Surgeons should consider pre-biopsy risk factors before deciding to omit systematic prostate biopsy regardless of mpMRI results.

Prospective trial of regional (hockey-stick) prostate cryoablation: oncologic and quality of life outcomes

PURPOSE

To report long-term follow-up of the efficacy of subtotal prostate ablation using a "hockey-stick" template, including oncologic control and quality of life (QoL) impact.

METHODS

We performed a prospective controlled trial to evaluate the efficacy of subtotal prostate ablation in selected men with baseline and confirmatory biopsy showing grade group (GG) 1-2 prostate cancer. "Hockey-stick" cryoablation that included the ipsilateral hemi-gland and contralateral anterior prostate was performed. Prostate biopsies and QOL queries were performed at 6, 18 and 36 months following regional ablation, and follow-up was updated to include subsequent clinic visits.

RESULTS

Between August 2009 and January 2012, 72 men were screened for eligibility and 47 opted to undergo confirmatory biopsy. Of these, 23 were deemed eligible and treated with regional cryoablation. Median age was 64 years. Median follow-up was 74 months. A single patient had < 1 mm of in-field viable tumor with therapy effect on 36-month biopsy. At time of last follow-up, a total of 12/23 (52%) patients did not have evidence of disease, all patients had preserved urinary control with no patients requiring pads for urinary incontinence. Sexual decline was significant at 3 and 6 months (P < 0.01 for both), though improvement was seen at subsequent time points.

CONCLUSION

Subtotal (hockey-stick template) cryoablation of the prostate provides oncologic control to targeted tissue in a generally low-risk group with minimal impact on sexual and urinary function. Further studies are needed to evaluate this ablation template in the MRI-targeted era and higher risk populations.

Clinical outcomes associated with prostate cancer conspicuity on biparametric and multiparametric MRI: a protocol for a systematic review and meta-analysis of biochemical recurrence following radical prostatectomy

INTRODUCTION

There is an increasing body of evidence to suggest that visibility of prostate cancer on magnetic resonance (MRI) may be related to likelihood of adverse pathological outcomes. Biochemical recurrence (BCR) after radical prostatectomy remains a significant clinical challenge and a means of predicting likelihood of this prior to surgery could inform treatment choice. It appears that MRI could be a potential candidate strategy for BCR prediction, and as such, there is a need to review extant literature on the prognostic capability of MRI. Here, we describe a protocol for a systematic review and meta-analysis of the utility of biparametric MRI (bpMRI) and multiparametric MRI (mpMRI) in predicting BCR following radical prostatectomy for prostate cancer treatment.

METHODS AND ANALYSIS

PubMed, MEDLINE, Embase and Cochrane databases will be searched and screening will be guided by the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. In order to meet the inclusion criteria, papers must be English-language articles involving patients who have had bpMRI or mpMRI for suspected prostate cancer and have undergone radical prostatectomy as definitive therapy. Patients must have had prostate-specific antigen monitoring before and after surgery. All relevant papers published from July 1977 to October 2020 will be eligible for inclusion. The Newcastle-Ottawa score will be used to determine the quality and bias of the studies. This protocol is written in-line with the PRISMA protocol 2015 checklist.

ETHICS AND DISSEMINATION

There are no relevant ethical concerns. Dissemination of this protocol will be via peer-reviewed journals as well as national and international conferences.

PROSPERO REGISTRATION NUMBER

CRD42020206074.

The diagnostic accuracy of multiparametric MRI for detection and localization of prostate cancer depends on the affected region

Objectives

To determine the diagnostic accuracy of 3T multiparametric magnetic resonance imaging (mpMRI) for detecting and locating prostate cancer (PCa) on Dickinson's 27‐sector map, using histopathology specimens from radical prostatectomy (RP) as the reference standard.

Patients and methods

The authors studied a continuous series of 140 patients who underwent RP over three consecutive years. Prior to RP, all patients had mpMRI for detection and localization of PCa and further assessment by biopsy. To minimize the potential of disease progression, 25 patients were excluded because the interval between mpMRI and RP exceeded 6 months, which left 115 patients eligible for analysis. The mpMRI findings were reported using the Prostate Imaging‐Reporting and Data System (PI‐RADS) v2, considering PI‐RADS ≥ 3 to indicate PCa. The histopathology findings from RP specimens were graded using the Gleason scoring system, considering Gleason ≥ 6 to indicate PCa. The location of the tumors was mapped on Dickinson's 27‐sector map for both mpMRI and histopathology and compared by rigid sector‐by‐sector matching.

Results

The cohort of 115 patients eligible for analysis was aged 66.5 ± 6.0 years at RP. Of the 3105 sectors analyzed, there were 412 true positives (13%), 28 false positives (1%), 68 false negatives (2%), and 2597 true negatives (84%). Across the 27 sectors of the prostate, mpMRI sensitivity ranged from 50% to 100% and specificity from 96% to 100%, while PPV ranged from 50% to 100%, and NPV from 91% to 100%. For the anterior prostate, mpMRI had a sensitivity of 80% (CI, 71%‐86%), specificity of 99% (CI, 99%‐100%), PPV of 91% (CI, 83%‐95%), and NPV of 99% (CI, 98%‐99%). For the posterior prostate, mpMRI had a sensitivity of 88% (CI, 84%‐91%), specificity of 98% (CI, 97%‐99%), PPV of 94% (CI, 92%‐96%), and NPV of 96% (CI, 94%‐97%). Overall, mpMRI had a sensitivity of 86%, specificity of 99%, PPV of 94%, and NPV of 97%.

Conclusions

The accuracy of mpMRI in detecting and locating prostate tumors depends on the affected region, but its high NPV across all sectors suggests that negative findings may not need corroboration by other techniques.

Single-cell Spatial Proteomic Revelations on the Multiparametric MRI Heterogeneity of Clinically Significant Prostate Cancer

PURPOSE

Multiparametric MRI (mpMRI) has become an indispensable radiographic tool in diagnosing prostate cancer. However, mpMRI fails to visualize approximately 15% of clinically significant prostate cancer (csPCa). The molecular, cellular, and spatial underpinnings of such radiographic heterogeneity in csPCa are unclear.

EXPERIMENTAL DESIGN

We examined tumor tissues from clinically matched patients with mpMRI-invisible and mpMRI-visible csPCa who underwent radical prostatectomy. Multiplex immunofluorescence single-cell spatial imaging and gene expression profiling were performed. Artificial intelligence-based analytic algorithms were developed to examine the tumor ecosystem and integrate with corresponding transcriptomics.

RESULTS

More complex and compact epithelial tumor architectures were found in mpMRI-visible than in mpMRI-invisible prostate cancer tumors. In contrast, similar stromal patterns were detected between mpMRI-invisible prostate cancer and normal prostate tissues. Furthermore, quantification of immune cell composition and tumor-immune interactions demonstrated a lack of immune cell infiltration in the malignant but not in the adjacent nonmalignant tissue compartments, irrespective of mpMRI visibility. No significant difference in immune profiles was detected between mpMRI-visible and mpMRI-invisible prostate cancer within our patient cohort, whereas expression profiling identified a 24-gene stromal signature enriched in mpMRI-invisible prostate cancer. Prostate cancer with strong stromal signature exhibited a favorable survival outcome within The Cancer Genome Atlas prostate cancer cohort. Notably, five recurrences in the 8 mpMRI-visible patients with csPCa and no recurrence in the 8 clinically matched patients with mpMRI-invisible csPCa occurred during the 5-year follow-up post-prostatectomy.

CONCLUSIONS

Our study identified distinct molecular, cellular, and structural characteristics associated with mpMRI-visible csPCa, whereas mpMRI-invisible tumors were similar to normal prostate tissue, likely contributing to mpMRI invisibility.

Novel Gene Signatures Predictive of Patient Recurrence-Free Survival and Castration Resistance in Prostate Cancer

Simple Summary

Molecular signatures predictive of recurrence-free survival (RFS) and castration resistance are critical for treatment decision-making in prostate cancer (PCa), but the robustness of current signatures is limited. This study aims to identify castration-resistant PCa (CRPC)-associated genes and develop robust RFS and CRPC signatures. Among 287 genes differentially expressed between localized CRPC and hormone-sensitive PCa (HSPC) samples, 6 genes constituted a signature (CRPC-derived prognosis signature, CRPCPS) that predicted RFS. Moreover, a 3-gene panel derived from the 6 CRPCPS genes was capable of distinguishing CRPC from HSPC. The CRPCPS predicted RFS in 5/9 cohorts in the multivariate analysis and maintained prognostic in patients stratified by tumor stage, Gleason score, and lymph node metastasis status. It also predicted overall survival and metastasis-free survival. Notably, the signature was validated in another six independent cohorts. These findings suggest that these two signatures could be robust tools for predicting RFS and CRPC in clinical practice.

Abstract

Molecular signatures predictive of recurrence-free survival (RFS) and castration resistance are critical for treatment decision-making in prostate cancer (PCa), but the robustness of current signatures is limited. Here, we applied the Robust Rank Aggregation (RRA) method to PCa transcriptome profiles and identified 287 genes differentially expressed between localized castration-resistant PCa (CRPC) and hormone-sensitive PCa (HSPC). Least absolute shrinkage and selection operator (LASSO) and stepwise Cox regression analyses of the 287 genes developed a 6-gene signature predictive of RFS in PCa. This signature included NPEPL1, VWF, LMO7, ALDH2, NUAK1, and TPT1, and was named CRPC-derived prognosis signature (CRPCPS). Interestingly, three of these 6 genes constituted another signature capable of distinguishing CRPC from HSPC. The CRPCPS predicted RFS in 5/9 cohorts in the multivariate analysis and remained valid in patients stratified by tumor stage, Gleason score, and lymph node status. The signature also predicted overall survival and metastasis-free survival. The signature’s robustness was demonstrated by the C-index (0.55–0.74) and the calibration plot in all nine cohorts and the 3-, 5-, and 8-year area under the receiver operating characteristic curve (0.67–0.77) in three cohorts. The nomogram analyses demonstrated CRPCPS’ clinical applicability. The CRPCPS thus appears useful for RFS prediction in PCa.

Magnetic Resonance Imaging Based Radiomic Models of Prostate Cancer: A Narrative Review

Simple Summary

The increasing interest in implementing artificial intelligence in radiomic models has occurred alongside advancement in the tools used for computer-aided diagnosis. Such tools typically apply both statistical and machine learning methodologies to assess the various modalities used in medical image analysis. Specific to prostate cancer, the radiomics pipeline has multiple facets that are amenable to improvement. This review discusses the steps of a magnetic resonance imaging based radiomics pipeline. Present successes, existing opportunities for refinement, and the most pertinent pending steps leading to clinical validation are highlighted.

Abstract

The management of prostate cancer (PCa) is dependent on biomarkers of biological aggression. This includes an invasive biopsy to facilitate a histopathological assessment of the tumor’s grade. This review explores the technical processes of applying magnetic resonance imaging based radiomic models to the evaluation of PCa. By exploring how a deep radiomics approach further optimizes the prediction of a PCa’s grade group, it will be clear how this integration of artificial intelligence mitigates existing major technological challenges faced by a traditional radiomic model: image acquisition, small data sets, image processing, labeling/segmentation, informative features, predicting molecular features and incorporating predictive models. Other potential impacts of artificial intelligence on the personalized treatment of PCa will also be discussed. The role of deep radiomics analysis-a deep texture analysis, which extracts features from convolutional neural networks layers, will be highlighted. Existing clinical work and upcoming clinical trials will be reviewed, directing investigators to pertinent future directions in the field. For future progress to result in clinical translation, the field will likely require multi-institutional collaboration in producing prospectively populated and expertly labeled imaging libraries.

Histopathological features of prostate cancer conspicuity on multiparametric MRI: protocol for a systematic review and meta-analysis

INTRODUCTION

Multiparametric MRI (mpMRI) has improved risk stratification for men with suspected prostate cancer. Indeed, mpMRI-visible tumours tend to be larger and of higher pathological grade than mpMRI-invisible tumours; however, concern remains around significant cancer that is undetected by mpMRI. There has been considerable recent interest to investigate whether tumour conspicuity on mpMRI is associated with additional histopathological features (including cellular density, microvessel density and unusual prostate cancer subtypes), which may have important clinical implications in both diagnosis and prognosis. Furthermore, analysis of these features may help reveal the radiobiology that underpins the actual mechanisms of mpMRI visibility (and invisibility) of prostate tumours. Here, we describe a protocol for a systematic review of the histopathological basis of prostate cancer conspicuity on mpMRI.

METHODS AND ANALYSIS

A systematic search of the MEDLINE, PubMed, Embase and Cochrane databases will be conducted. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines will be used to guide screening, thematic reporting and conclusions drawn from all eligible studies. Included papers will be full-text, English-language articles, comparing the histopathological characteristics of mpMRI-visible lesions and mpMRI-invisible tumours. All studies published between January 1950 and January 2020 will be eligible for inclusion. Studies using confirmatory immunohistochemistry for the identification of immune subsets or structural components will be included. Study bias and quality will be assessed using a modified Newcastle-Ottawa scale. To ensure methodological rigour, this protocol is written in accordance with the PRISMA Protocol 2015 checklist. If appropriate, a meta-analysis will be conducted comparing histopathological feature frequency between mpMRI-visible and mpMRI-invisible disease.

ETHICS AND DISSEMINATION

No ethical approval will be required as this is an academic review of published literature. Findings will be disseminated through publications in peer-reviewed journals and presentations at national and international conferences.

PROSPERO REGISTRATION NUMBER

CRD42020176049.

Conspicuity of prostate cancer on multiparametric magnetic resonance imaging: A cross-disciplinary translational hypothesis

Pre-biopsy multiparametric magnetic resonance imaging (mpMRI) has transformed the risk stratification and diagnostic approach for suspected prostate cancer. The majority of clinically significant prostate cancers are visible on pre-biopsy mpMRI, however, there are a subset of significant tumors that are not detected by mpMRI. The radiobiological mechanisms underpinning mpMRI-visibility and invisibility of these cancers remain uncertain. Emerging evidence suggests that mpMRI-visible tumors are enriched with molecular features associated with increased disease aggressivity and poor clinical prognosis, which is supported by short-term endpoints, such as biochemical recurrence following surgery. Furthermore, at the histopathological level, mpMRI-visible tumors appear to exhibit increased architectural and vascular density compared to mpMRI-invisible disease. It seems probable that the genomic, pathological, radiological, and clinical features of mpMRI-visible and mpMRI-invisible prostate cancers are interrelated. Here, we propose a novel cross-disciplinary theory that links genomic and molecular evidence with cellular and histopathological appearances, elucidating both the mpMRI visibility and clinical status of significant prostate cancer.

Genetic Landscape of Prostate Cancer Conspicuity on Multiparametric Magnetic Resonance Imaging: A Systematic Review and Bioinformatic Analysis

Context

Multiparametric magnetic resonance imaging (mpMRI) detects most, but not all, clinically significant prostate cancer. The genetic basis of prostate cancer visibility and invisibility on mpMRI remains uncertain.

Objective

To systematically review the literature on differential gene expression between mpMRI-visible and mpMRI-invisible prostate cancer, and to use bioinformatic analysis to identify enriched processes or cellular components in genes validated in more than one study.

Evidence acquisition

We performed a systematic literature search of the Medline, EMBASE, PubMed, and Cochrane databases up to January 2020 in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement. The primary endpoint was differential genetic features between mpMRI-visible and mpMRI-invisible tumours. Secondary endpoints were explanatory links between gene function and mpMRI conspicuity, and the prognostic value of differential gene enrichment.

Evidence synthesis

We retrieved 445 articles, of which 32 met the criteria for inclusion. Thematic synthesis from the included studies showed that mpMRI-visible cancer tended towards enrichment of molecular features associated with increased disease aggressivity, including phosphatase and tensin homologue (PTEN) loss and higher genomic classifier scores, such as Oncotype and Decipher. Three of the included studies had accompanying publicly available data suitable for further bioinformatic analysis. An over-representation analysis of these datasets revealed increased expression of genes associated with extracellular matrix components in mpMRI-visible tumours.

Conclusions

Prostate cancer that is visible on mpMRI is generally enriched with molecular features of tumour development and aggressivity, including activation of proliferative signalling, DNA damage, and inflammatory processes. Additionally, there appears to be concordant cellular components and biological processes associated with mpMRI conspicuity, as highlighted by bioinformatic analysis of large genetic datasets.

Patient summary

Prostate cancer that is detected by magnetic resonance imaging (MRI) tends to have genetic features that are associated with more aggressive disease. This suggests that MRI can be used to assess the likelihood of aggressive prostate cancer, based on tumour visibility.

Prostate cancer and the role of biomarkers

PURPOSE

To review available prostate cancer biomarkers and their performance in a clinical order, from prostate cancer detection, to treatment of localized and advanced disease.

METHODS

We used an electronic literature search of the PubMed database using the key words "prostate biomarkers," "genomic markers," and "prostate cancer screening," as well as specific biomarkers, until March 2019.

RESULTS

Prostate-specific antigen (PSA) lacks sensitivity for prostate cancer detection, and PSA derivatives have slightly improved its specificity, but have not resolved the limitations of PSA screening. Prostate cancer biomarkers have emerged as an ancillary tool to guide the clinical decision-making in different clinical scenarios. Urine-based tests can identify patients who may benefit from a prostate biopsy, and issue-based markers are helpful in guiding the decision regarding a second biopsy, stratifying patient with newly diagnosed prostate cancer to active surveillance or treatment, and identifying patients who may benefit from adjuvant treatment after surgery.

CONCLUSIONS

New biomarkers have improved risk stratification in diagnosing and treating prostate cancer. Many of these markers are still considered experimental, and their efficacy and cost utility have not been determined.

Associations of PTEN and ERG with Magnetic Resonance Imaging Visibility and Assessment of Non-organ-confined Pathology and Biochemical Recurrence After Radical Prostatectomy

BACKGROUND

Diagnosing clinically significant prostate cancer (PCa) is challenging, but may be facilitated by biomarkers and multiparametric magnetic resonance imaging (MRI).

OBJECTIVE

To determine the association between biomarkers phosphatase and tensin homolog (PTEN) and ETS-related gene (ERG) with visible and invisible PCa lesions in MRI, and to predict biochemical recurrence (BCR) and non-organ-confined (non-OC) PCa by integrating clinical, MRI, and biomarker-related data.

DESIGN, SETTING, AND PARTICIPANTS

A retrospective analysis of a population-based cohort of men with PCa, who underwent preoperative MRI followed by radical prostatectomy (RP) during 2014-2015 in Helsinki University Hospital (n = 346), was conducted. A tissue microarray corresponding to the MRI-visible and MRI-invisible lesions in RP specimens was constructed and stained for PTEN and ERG.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Associations of PTEN and ERG with MRI-visible and MRI-invisible lesions were examined (Pearson's χ² test), and predictions of non-OC disease together with clinical and MRI parameters were determined (area under the receiver operating characteristic curve and logistic regression analyses). BCR prediction was analyzed by Kaplan-Meier and Cox proportional hazard analyses.

RESULTS AND LIMITATIONS

Patients with MRI-invisible lesions (n = 35) had less PTEN loss and ERG-positive expression compared with patients (n = 90) with MRI-visible lesions (17.2% vs 43.3% [p = 0.006]; 8.6% vs 20.0% [p = 0.125]). Patients with invisible lesions had better, but not statistically significantly improved, BCR-free survival probability in Kaplan-Meier analyses (p = 0.055). Rates of BCR (5.7% vs 21.1%; p = 0.039), extraprostatic extension (11.4% vs 44.6%; p < 0.001), seminal vesicle invasion (0% vs 21.1%; p = 0.003), and lymph node metastasis (0% vs 12.2%; p = 0.033) differed between the groups in favor of patients with MRI-invisible lesions. Biomarkers had no independent role in predicting non-OC disease or BCR. The short follow-up period was a limitation.

CONCLUSIONS

PTEN loss, BCR, and non-OC RP findings were more often encountered with MRI-visible lesions.

PATIENT SUMMARY

Magnetic resonance imaging (MRI) of the prostate misses some cancer lesions. MRI-invisible lesions seem to be less aggressive than MRI-visible lesions.

An Automated Segmentation Pipeline for Intratumoural Regions in Animal Xenografts Using Machine Learning and Saturation Transfer MRI

Saturation transfer MRI can be useful in the characterization of different tumour types. It is sensitive to tumour metabolism, microstructure, and microenvironment. This study aimed to use saturation transfer to differentiate between intratumoural regions, demarcate tumour boundaries, and reduce data acquisition times by identifying the imaging scheme with the most impact on segmentation accuracy. Saturation transfer-weighted images were acquired over a wide range of saturation amplitudes and frequency offsets along with T₁ and T₂ maps for 34 tumour xenografts in mice. Independent component analysis and Gaussian mixture modelling were used to segment the images and identify intratumoural regions. Comparison between the segmented regions and histopathology indicated five distinct clusters: three corresponding to intratumoural regions (active tumour, necrosis/apoptosis, and blood/edema) and two extratumoural (muscle and a mix of muscle and connective tissue). The fraction of tumour voxels segmented as necrosis/apoptosis quantitatively matched those calculated from TUNEL histopathological assays. An optimal protocol was identified providing reasonable qualitative agreement between MRI and histopathology and consisting of T₁ and T₂ maps and 22 magnetization transfer (MT)-weighted images. A three-image subset was identified that resulted in a greater than 90% match in positive and negative predictive value of tumour voxels compared to those found using the entire 24-image dataset. The proposed algorithm can potentially be used to develop a robust intratumoural segmentation method.

Centromere protein F and Forkhead box M1 correlation with prognosis of non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is the most common histological type of lung cancer. Altered expression of centromere protein F (CENPF), a transient kinetochore protein, has been found in a variety of human cancers. However, its clinical significance in NSCLC remains unknown. In the present study the results of quantitative PCR and western blot analyses demonstrated that CENPF and Forkhead box M1 (FOXM1) were significantly higher in NSCLC tissues than in the non-cancerous controls at both transcriptional and translational levels. Immunohistochemical staining results showed 58.7% (44/75) and 64.0% (48/75) of NSCLC tissues displayed high expression of CENPF and FOXM1, respectively. CENPF protein expression showed a positive correlation with tumor size (P=0.0179), vital status (P=0.0008) and FOXM1 expression (P=0.0013) in NSCLC. Poor overall survival was correlated with high levels of CENPF and FOXM1 in NSCLC patients as evaluated by Kaplan-Meier and log rank test. Multivariate analyses showed that CENPF expression was an independent prognostic factor for NSCLC. In conclusion, our study provides evidence of the prognostic function of CENPF in NSCLC.

Genetic landscape of prostate cancer conspicuity on multiparametric MRI: a protocol for a systematic review and bioinformatic analysis

INTRODUCTION

The introduction of multiparametric MRI (mpMRI) has enabled enhanced risk stratification for men at risk of prostate cancer, through accurate prebiopsy identification of clinically significant disease. However, approximately 10%-20% of significant prostate cancer may be missed on mpMRI. It appears that the genomic basis of lesion visibility or invisibility on mpMRI may have key implications for prognosis and treatment. Here, we describe a protocol for the first systematic review and novel bioinformatic analysis of the genomic basis of prostate cancer conspicuity on mpMRI.

METHODS AND ANALYSIS

A systematic search of MEDLINE, PubMed, EMBASE and Cochrane databases will be conducted. Screening, data extraction, statistical analysis and reporting will be performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Included papers will be full text articles, written between January 1980 and December 2019, comparing molecular characteristics of mpMRI-visible lesions and mpMRI-invisible lesions at the DNA, DNA-methylation, RNA or protein level. Study bias and quality will be assessed using a modified Newcastle-Ottawa score. Additionally, we will conduct a novel bioinformatic analysis of supplementary material and publicly available data, to combine transcriptomic data and reveal common pathways highlighted across studies. To ensure methodological rigour, this protocol is written in accordance with the PRISMA Protocol 2015 checklist.

ETHICS AND DISSEMINATION

Ethical approval will not be required, as this is an academic review of published literature. Findings will be disseminated through publications in peer-reviewed journals, and presentations at national and international conferences.

PROSPERO REGISTRATION NUMBER

CRD42019147423.

CEST MRI detectable liposomal hydrogels for multiparametric monitoring in the brain at 3T

Adjuvant treatment using local drug delivery is applied in treating glioblastoma multiforme (GBM) after tumor resection. However, there are no non-invasive imaging techniques available for tracking the compositional changes of hydrogel-based drug treatment.

Methods: We developed Chemical Exchange Saturation Transfer Magnetic Resonance Imaging (CEST MRI) detectable and injectable liposomal hydrogel to monitor these events in vivo at 3T clinical field. Mechanical attributes of these hydrogels and their in vitro and in vivo CEST imaging properties were systematically studied.

Results: The MRI detectable hydrogels were capable of generating multiparametric readouts for monitoring specific components of the hydrogel matrix simultaneously and independently. Herein, we report, for the first time, CEST contrast at -3.4 ppm provides an estimated number of liposomes and CEST contrast at 5 ppm provides an estimated amount of encapsulated drug. CEST contrast decreased by 1.57% at 5 ppm, while the contrast at -3.4 ppm remained constant over 3 d in vivo, demonstrating different release kinetics of these components from the hydrogel matrix. Furthermore, histology analysis confirmed that the CEST contrast at -3.4 ppm was associated with liposome concentrations.

Conclusion: This multiparametric CEST imaging of individual compositional changes in liposomal hydrogels, formulated with clinical-grade materials at 3T and described in this study, has the potential to facilitate the refinement of adjuvant treatment for GBM.

In Vivo 3D MRI Measurement of Tumour Volume in an Orthotopic Mouse Model of Prostate Cancer

Prostate cancer (CaP) is the most commonly diagnosed cancer in males in western countries. Orthotopic implantation is considered as an ideal xenograft model for CaP study, and noninvasive measurement of tumor volume changes is important for monitoring responses to anticancer therapies. In this study, the T2-weighted fast spin echo sequence magnetic resonance imaging (MRI) was performed on a CaP orthotopic non-obese diabetic/severe combined immunodeficiency (NOD/SCID) mouse model weekly for 6 weeks post PC-3 CaP cell inoculation, and the fat signal was suppressed using a chemical shift-selective pulse. Subsequently, the MRI data were imported into the image processing software Avizo Standard and stacked into three-dimensional (3D) volumes. Our results demonstrate that MRI, combined with 3D reconstruction, is a feasible and sensitive method to assess tumor growth in a PC-3 orthotopic CaP mouse model and this established monitoring approach is promising for longitudinal observation of CaP xenograft development after anticancer therapy in vivo. Further investigation is needed to validate this protocol in a larger cohort of mice to generate enough statistical power.

Significant random signatures reveals new biomarker for breast cancer

BACKGROUND

In 2012, Venet et al. proposed that at least in the case of breast cancer, most published signatures are not significantly more associated with outcome than randomly generated signatures. They suggested that nominal p-value is not a good estimator to show the significance of a signature. Therefore, one can reasonably postulate that some information might be present in such significant random signatures.

METHODS

In this research, first we show that, using an empirical p-value, these published signatures are more significant than their nominal p-values. In other words, the proposed empirical p-value can be considered as a complimentary criterion for nominal p-value to distinguish random signatures from significant ones. Secondly, we develop a novel computational method to extract information that are embedded within significant random signatures. In our method, a score is assigned to each gene based on the number of times it appears in significant random signatures. Then, these scores are diffused through a protein-protein interaction network and a permutation procedure is used to determine the genes with significant scores. The genes with significant scores are considered as the set of significant genes.

RESULTS

First, we applied our method on the breast cancer dataset NKI to achieve a set of significant genes in breast cancer considering significant random signatures. Secondly, prognostic performance of the computed set of significant genes is evaluated using DMFS and RFS datasets. We have observed that the top ranked genes from this set can successfully separate patients with poor prognosis from those with good prognosis. Finally, we investigated the expression pattern of TAT, the first gene reported in our set, in malignant breast cancer vs. adjacent normal tissue and mammospheres.

CONCLUSION

Applying the method, we found a set of significant genes in breast cancer, including TAT, a gene that has never been reported as an important gene in breast cancer. Our results show that the expression of TAT is repressed in tumors suggesting that this gene could act as a tumor suppressor in breast cancer and could be used as a new biomarker.

The Oncogene Metadherin Interacts with the Known Splicing Proteins YTHDC1, Sam68 and T-STAR and Plays a Novel Role in Alternative mRNA Splicing

Oncogenic metadherin is a key contributor to tumourigenesis with metadherin expression and cytoplasmic localisation previously linked to poor survival. A number of reports have shown metadherin localises specifically to nuclear speckles known to be rich in RNA-binding proteins including the splicing proteins YTHDC1, Sam68 and T-STAR, that have been shown to select alternative splice sites in mRNA of tumour-associated proteins including BRCA, MDM2 and VEGF. Here we investigate the interaction and relationship between metadherin and the splice factors YTHDC1, T-STAR and Sam68. Using a yeast two-hybrid assay and immunoprecipitation we show that metadherin interacts with YTHDC1, Sam68 and T-STAR and demonstrate that T-STAR is significantly overexpressed in prostate cancer tissue compared to benign prostate tissue. We also demonstrate that metadherin influences splice site selection in a dose-dependent manner in CD44v5-luc minigene reporter assays. Finally, we demonstrate that prostate cancer patients with higher metadherin expression have greater expression of the CD44v5 exon. CD44v5 expression could be used to discriminate patients with poor outcomes following radical prostatectomy. In this work we show for the first time that metadherin interacts with, and modulates, the function of key components of splicing associated with cancer development and progression.

Biologic Significance of Magnetic Resonance Imaging Invisibility in Localized Prostate Cancer

PURPOSE

Multiparametric magnetic resonance imaging (mpMRI) is used widely for prostate cancer (PCa) evaluation. Approximately 35% of aggressive tumors, however, are not visible on mpMRI. We sought to identify the molecular alterations associated with mpMRI-invisible tumors and determine whether mpMRI visibility is associated with PCa prognosis.

METHODS

Discovery and validation cohorts included patients who underwent mpMRI before radical prostatectomy and were found to harbor both mpMRI-visible (Prostate Imaging and Reporting Data System 3 to 5) and -invisible (Prostate Imaging and Reporting Data System 1 or 2) foci on surgical pathology. Next-generation sequencing was performed to determine differential gene expression between mpMRI-visible and -invisible foci. A genetic signature for tumor mpMRI visibility was derived in the discovery cohort and assessed in an independent validation cohort. Its association with long-term oncologic outcomes was evaluated in a separate testing cohort.

RESULTS

The discovery cohort included 10 patients with 26 distinct PCa foci on surgical pathology, of which 12 (46%) were visible and 14 (54%) were invisible on preoperative mpMRI. Next-generation sequencing detected prioritized genetic mutations in 14 (54%) tumor foci (n = 8 mpMRI visible, n = 6 mpMRI invisible). A nine-gene signature (composed largely of cell organization/structure genes) associated with mpMRI visibility was derived (area under the curve = 0.89), and the signature predicted MRI visibility with 75% sensitivity and 100% specificity (area under the curve = 0.88) in the validation cohort. In the testing cohort (n = 375, median follow-up 8 years) there was no significant difference in biochemical recurrence, distant metastasis, or cancer-specific mortality in patients with predicted mpMRI-visible versus -invisible tumors (all P > .05).

CONCLUSION

Compared with mpMRI-invisible disease, mpMRI-visible tumors are associated with underexpression of cellular organization genes. mpMRI visibility does not seem to be predictive of long-term cancer outcomes, highlighting the need for biopsy strategies that detect mpMRI-invisible tumors.

Downregulation of CENPF Remodels Prostate Cancer Cells and Alters Cellular Metabolism

Metabolic alterations in prostate cancer (PC) are associated with progression and aggressiveness. However, the underlying mechanisms behind PC metabolic functions are unknown. The authors' group recently reported on the important role of centromere protein F (CENPF), a protein associated with the centromere-kinetochore complex and chromosomal segregation during mitosis, in PC MRI visibility. This study focuses on discerning the role of CENPF in metabolic perturbation in human PC3 cells. A series of bioinformatics analyses shows that CENPF is one gene that is strongly associated with aggressive PC and that its expression is positively correlated with metastasis. By identifying and reconstructing the CENPF network, additional associations with lipid regulation are found. Further untargeted metabolomics analysis using gas chromatography-time-of-flight-mass spectrometry reveals that silencing of CENPF alters the global metabolic profiles of PC cells and inhibits cell proliferation, which suggests that CENPF may be a critical regulator of PC metabolism. These findings provide useful scientific insights that can be applied in future studies investigating potential targets for PC treatment.

Correlation between MRI phenotypes and a genomic classifier of prostate cancer: preliminary findings

OBJECTIVES

We sought to evaluate the correlation between MRI phenotypes of prostate cancer as defined by PI-RADS v2 and the Decipher Genomic Classifier (used to estimate the risk of early metastases).

METHODS

This single-center, retrospective study included 72 nonconsecutive men with prostate cancer who underwent MRI before radical prostatectomy performed between April 2014 and August 2017 and whose MRI registered lesions were microdissected from radical prostatectomy specimens and then profiled using Decipher (89 lesions; 23 MRI invisible [PI-RADS v2 scores ≤ 2] and 66 MRI visible [PI-RADS v2 scores ≥ 3]). Linear regression analysis was used to assess clinicopathologic and MRI predictors of Decipher results; correlation coefficients (r) were used to quantify these associations. AUC was used to determine whether PI-RADS v2 could accurately distinguish between low-risk (Decipher score < 0.45) and intermediate-/high-risk (Decipher score ≥ 0.45) lesions.

RESULTS

MRI-visible lesions had higher Decipher scores than MRI-invisible lesions (mean difference 0.22; 95% CI 0.13, 0.32; p < 0.0001); most MRI-invisible lesions (82.6%) were low risk. PI-RADS v2 had moderate correlation with Decipher (r = 0.54) and had higher accuracy (AUC 0.863) than prostate cancer grade groups (AUC 0.780) in peripheral zone lesions (95% CI for difference 0.01, 0.15; p = 0.018).

CONCLUSIONS

MRI phenotypes of prostate cancer are positively correlated with Decipher risk groups. Although PI-RADS v2 can accurately distinguish between lesions classified by Decipher as low or intermediate/high risk, some lesions classified as intermediate/high risk by Decipher are invisible on MRI.

KEY POINTS

• MRI phenotypes of prostate cancer as defined by PI-RADS v2 positively correlated with a genomic classifier that estimates the risk of early metastases. • Most but not all MRI-invisible lesions had a low risk for early metastases according to the genomic classifier. • MRI could be used in conjunction with genomic assays to identify lesions that may carry biological potential for early metastases.

Centromere protein F (CENPF), a microtubule binding protein, modulates cancer metabolism by regulating pyruvate kinase M2 phosphorylation signaling

Prostate cancer (PC) is the most commonly diagnosed cancer in men and is the second leading cause of male cancer-related death in North America. Metabolic adaptations in malignant PC cells play a key role in fueling the growth and progression of the disease. Unfortunately, little is known regarding these changes in cellular metabolism. Here, we demonstrate that centromere protein F (CENPF), a protein associated with the centromere-kinetochore complex and chromosomal segregation during mitosis, is mechanically linked to altered metabolism and progression in PC. Using the CRISPR-Cas9 system, we silenced the gene for CENPF in human PC3 cells. These cells were found to have reduced levels of epithelial-mesenchymal transition markers and inhibited cell proliferation, migration, and invasion. Silencing of CENPF also simultaneously improved sensitivity to anoikis-induced apoptosis. Mass spectrometry analysis of tyrosine phosphorylated proteins from CENPF knockout (CENPFKO) and control cells revealed that CENPF silencing increased inactive forms of pyruvate kinase M2, a rate limiting enzyme needed for an irreversible reaction in glycolysis. Furthermore, CENPFKO cells had reduced global bio-energetic capacity, acetyl-CoA production, histone acetylation, and lipid metabolism, suggesting that CENPF is a critical regulator of cancer metabolism, potentially through its effects on mitochondrial functioning. Additional quantitative immunohistochemistry and imaging analyzes on a series of PC tumor microarrays demonstrated that CENPF expression is significantly increased in higher-risk PC patients. Based on these findings, we suggest the CENPF may be an important regulator of PC metabolism through its role in the mitochondria.

Knockdown of anti-silencing function 1B histone chaperone induces cell apoptosis via repressing PI3K/Akt pathway in prostate cancer

Prostate cancer (PCa) is one of the most common malignancies among males worldwide. Anti-silencing function 1B histone chaperone (ASF1B) has been reported to be involved in PCa. The present study aimed to investigate the role and molecular mechanism of ASF1B in PCa. Data of genes were obtained from The Cancer Genome Atlas data- base. The core gene was identified using the DAVID website. Cell viability and colony formation were detected using a cell counting kit-8 assay and crystal violet staining, respectively. Cell cycle distribution and apoptosis were assessed using flow cytometry analysis. The corresponding factors were analyzed by reverse transcription-quantitative polymerase chain reaction and western blotting. It was demonstrated that ASF1B was highly expressed in the PCa tissues and cells compared with the non-PCa tissues and cells, respectively. While siRNA-ASF1B significantly reduced the viability and colony formation, it promoted apoptosis, G1 phase cell cycle arrest of LNCap as well as C4-2 cells. siRNA-ASF1B was revealed to significantly reduce the level of B-cell lymphoma-2 and cyclin D1, and enhance the expression levels of p53, caspase-3 and Bcl-2 associated X protein. Furthermore, the phosphorylation levels of phosphatidylinositol 3 kinase (PI3K) and protein kinase B (Akt) were significantly decreased in the siRNA-ASF1B group compared with the mock group. In summary, the present study demonstrated that silencing of ASF1B suppressed the proliferation, and promoted apoptosis and cell cycle arrest of PCa cells. Inhibition of the PI3K/Akt signaling pathway was pertinent to the role of si-ASF1B. This phenomenon suggests that the downregulation of ASF1B may aid in inhibiting the progression of PCa.