Long term evaluation of optimized Gleason grading in a large cohort of men with prostate cancer in Canada.

OBJECTIVES: To evaluate the International Society of Urological Pathology (ISUP) 5-tier grade grouping (GG) system of prostate cancers as well as previously proposed optimizations. PATIENTS AND METHODS: The PROCURE biobank is a prospective cohort study of patients with localized prostate cancer who underwent radical prostatectomy in Quebec province between 2005 and 2013. Surgical specimens were graded by experienced genitourinary pathologists using 2019 ISUP criteria. Follow-up was conducted until November 2021. The current 5-tier and a proposed 6-tier GG system were evaluated, the latter having two changes: 1) Gleason 3 + 4 and 4 + 3 tumors with minor/tertiary Gleason 5 patterns were upgraded to GG 3 and 4, respectively; and 2) patients in GG5 were separated based on primary Gleason pattern (4 or 5). Cox proportional hazards models and Harrell's concordance (C) indices were used for statistical analyses. RESULTS: 2003 patients were included (median follow-up: 8.7 years). The current 5-tier GG system predicted time to recurrence (hazard ratio [HR] 2.12, 95% confidence interval [95%CI] 1.99-2.25, C 0.717), androgen-deprivation therapy (HR 2.58, 95%CI 2.38-2.80, C 0.790), metastasis (HR 2.48, 95%CI 2.17-2.83, C 0.806), castration-resistant prostate cancer (HR 2.67, 95%CI 2.28-3.13, C 0.829), and cancer-specific mortality (HR 2.80, 95%CI 2.27-3.44, C 0.835). Goodness-of-fit further improved with the proposed 6-tier GG system, with Harrell's C of 0.733, 0.807, 0.827, 0.853, and 0.853, respectively. CONCLUSIONS: The 5-tier GG system predicted short- and long-term outcomes for patients with localized prostate cancer, and the proposed 6-tier GG system further improved its accuracy.

A phase IIb randomized placebo-controlled trial testing the effect of MAG-EPA long-chain omega-3 fatty acid dietary supplement on prostate cancer proliferation.

BACKGROUND: High prostate eicosapentaenoic fatty acid (EPA) levels were associated with a significant reduction of upgrading to grade group (GG) ≥ 2 prostate cancer in men under active surveillance. We aimed to evaluate the effect of MAG-EPA long-chain omega-3 fatty acid dietary supplement on prostate cancer proliferation. METHODS: A phase II double-blind randomized placebo-controlled trial was conducted in 130 men diagnosed with GG ≥ 2 prostate cancer and undergoing radical prostatectomy between 2015-2017 (Clinicaltrials.gov: NCT02333435). Participants were randomized to receive 3 g daily of either MAG-EPA (n = 65) or placebo (n = 65) for 7 weeks (range 4-10) prior to radical prostatectomy. The primary outcome was the cancer proliferation index quantified by automated image analysis of tumor nuclear Ki-67 expression using standardized prostatectomy tissue microarrays. Additional planned outcomes at surgery are reported including plasma levels of 27 inflammatory cytokines and fatty acid profiles in circulating red blood cells membranes and prostate tissue. RESULTS: Cancer proliferation index measured by Ki-67 expression was not statistically different between the intervention (3.10%) and placebo (2.85%) groups (p = 0.64). In the per protocol analyses, the adjusted estimated effect of MAG-EPA was greater but remained non-significant. Secondary outcome was the changes in plasma levels of 27 cytokines, of which only IL-7 was higher in MAG-EPA group compared to placebo (p = 0.026). Men randomized to MAG-EPA prior to surgery had four-fold higher EPA levels in prostate tissue compared to those on placebo. CONCLUSIONS: This MAG-EPA intervention did not affect the primary outcome of prostate cancer proliferation according to nuclear Ki-67 expression. More studies are needed to decipher the effects of long-chain omega-3 fatty acid dietary supplementation in men with prostate cancer.

It is thought that our diet can impact our risk of cancer and affect outcomes in patients with cancer. Omega-3 fatty acids, mostly found in fatty fish, might be beneficial by protecting against prostate cancer and its adverse outcomes. We conducted a clinical trial to test the effects of an omega-3 dietary supplement (MAG-EPA) in men with prostate cancer. We randomly allocated 130 men to receive either MAG-EPA or a placebo for 7 weeks before their prostate cancer surgery. We measured a marker of how much tumor cells were proliferating (or growing in number) at the point of surgery, which might indicate how aggressive their disease was. However, the supplement did not affect tumor cell proliferation. The supplement was therefore not beneficial in this group of patients and further studies  are needed to test and confirm the effects of MAG-EPA on prostate cancer cells.

Detection of SARS-CoV-2 in saliva by a low-cost LSPR-based sensor.

The SARS-CoV-2 pandemic started more than 3 years ago, but the containment of the spread is still a challenge. Screening is imperative for informed decision making by government authorities to contain the spread of the virus locally. The access to screening tests is disproportional, due to the lack of access to reagents, equipment, finances or because of supply chain disruptions. Low and middle-income countries have especially suffered with the lack of these resources. Here, we propose a low cost and easily constructed biosensor device based on localized surface plasmon resonance, or LSPR, for the screening of SARS-CoV-2. The biosensor device, dubbed "sensor" for simplicity, was constructed in two modalities: (1) viral detection in saliva and (2) antibody against COVID in saliva. Saliva collected from 18 patients were tested in triplicates. Both sensors successfully classified all COVID positive patients (among hospitalized and non-hospitalized). From the COVID negative patients 7/8 patients were correctly classified. For both sensors, sensitivity was determined as 100% (95% CI 79.5-100) and specificity as 87.5% (95% CI 80.5-100). The reagents and equipment used for the construction and deployment of this sensor are ubiquitous and low-cost. This sensor technology can then add to the potential solution for challenges related to screening tests in underserved communities.

Spectral focusing-based stimulated Raman scattering microscopy using compact glass blocks for adjustable dispersion.

Spectral focusing is a well-established technique for increasing spectral resolution in coherent Raman scattering microscopy. However, current methods for tuning optical chirp in setups using spectral focusing, such as glass rods, gratings, and prisms, are very cumbersome, time-consuming to use, and difficult to align, all of which limit more widespread use of the spectral focusing technique. Here, we report a stimulated Raman scattering (SRS) configuration which can rapidly tune optical chirp by utilizing compact adjustable-dispersion TIH53 glass blocks. By varying the height of the blocks, the number of bounces in the blocks and therefore path length of the pulses through the glass can be quickly modulated, allowing for a convenient method of adjusting chirp with almost no necessary realignment. To demonstrate the flexibility of this configuration, we characterize our system's signal-to-noise ratio and spectral resolution at different chirp values and perform imaging in both the carbon-hydrogen stretching region (MCF-7 cells) and fingerprint region (prostate cores). Our findings show that adjustable-dispersion glass blocks allow the user to effortlessly modify their optical system to suit their imaging requirements. These blocks can be used to significantly simplify and miniaturize experimental configurations utilizing spectral focusing.

Leukocytic Infiltration of Intraductal Carcinoma of the Prostate: An Exploratory Study.

Intraductal carcinoma of the prostate (IDC-P) is an aggressive histological subtype of prostate cancer (PCa) detected in approximately 20% of radical prostatectomy (RP) specimens. As IDC-P has been associated with PCa-related death and poor responses to standard treatment, the purpose of this study was to explore the immune infiltrate of IDC-P. Hematoxylin- and eosin-stained slides from 96 patients with locally advanced PCa who underwent RP were reviewed to identify IDC-P. Immunohistochemical staining of CD3, CD8, CD45RO, FoxP3, CD68, CD163, CD209 and CD83 was performed. For each slide, the number of positive cells per mm2 in the benign tissues, tumor margins, cancer and IDC-P was calculated. Consequently, IDC-P was found in a total of 33 patients (34%). Overall, the immune infiltrate was similar in the IDC-P-positive and the IDC-P-negative patients. However, FoxP3+ regulatory T cells (p < 0.001), CD68+ and CD163+ macrophages (p < 0.001 for both) and CD209+ and CD83+ dendritic cells (p = 0.002 and p = 0.013, respectively) were less abundant in the IDC-P tissues compared to the adjacent PCa. Moreover, the patients were classified as having immunologically "cold" or "hot" IDC-P, according to the immune-cell densities averaged in the total IDC-P or in the immune hotspots. The CD68/CD163/CD209-immune hotspots predicted metastatic dissemination (p = 0.014) and PCa-related death (p = 0.009) in a Kaplan-Meier survival analysis. Further studies on larger cohorts are necessary to evaluate the clinical utility of assessing the immune infiltrate of IDC-P with regards to patient prognosis and the use of immunotherapy for lethal PCa.

In situ Raman spectroscopy and machine learning unveil biomolecular alterations in invasive breast cancer.

Significance: As many as 60% of patients with early stage breast cancer undergo breast-conserving surgery. Of those, 20% to 35% need a second surgery because of incomplete resection of the lesions. A technology allowing in situ detection of cancer could reduce re-excision procedure rates and improve patient survival. Aim: Raman spectroscopy was used to measure the spectral fingerprint of normal breast and cancer tissue ex-vivo. The aim was to build a machine learning model and to identify the biomolecular bands that allow one to detect invasive breast cancer. Approach: The system was used to interrogate specimens from 20 patients undergoing lumpectomy, mastectomy, or breast reduction surgery. This resulted in 238 ex-vivo measurements spatially registered with standard histology classifying tissue as cancer, normal, or fat. A technique based on support vector machines led to the development of predictive models, and their performance was quantified using a receiver-operating-characteristic analysis. Results: Raman spectroscopy combined with machine learning detected normal breast from ductal or lobular invasive cancer with a sensitivity of 93% and a specificity of 95%. This was achieved using a model based on only two spectral bands, including the peaks associated with C-C stretching of proteins around 940 cm - 1 and the symmetric ring breathing at 1004 cm - 1 associated with phenylalanine. Conclusions: Detection of cancer on the margins of surgically resected breast specimen is feasible with Raman spectroscopy.

T cell-loaded injectable chitosan scaffold shows short-term efficacy in localised cancer immunotherapy in mice.

Adoptive cell therapy (ACT) shows success against treatment-resistant cancers, but is limited by the large number of intravenously delivered T cells required and toxicity related to systemic administration. In this work, we hypothesized that localized T cell delivery in an in situ gelling chitosan hydrogel will allow similar treatment efficacy despite delivering fewer cells than systemic intravenous delivery. A rapidly gelling chitosan gel with good mechanical properties was used for this study. Gel biocompatibility and biodegradability were tested over 8 weeks in mice. No adverse effects were observed. The gel elicited a local granulomatous reaction (foreign body reaction), degrading by about 75% volume at 8 weeks. The survival, escape and bioactivity against the tumour cells of encapsulated murine lymphocytes (OT-I) and human Jurkat cells were confirmed in vitro by live/dead assay and flow cytometry. Efficacy was studied using a mouse tumour model where the injected OT-I can specifically recognize and attack ovalbumin (OVA) protein-expressing tumours. The OT-I cell delivery scaffold was compared to untreated controls, OT-I in saline and intravenous systemic treatment with 3-fold more OT-I, observing tumour growth and localization by intravital microscopy and histology. Gel-encapsulated OT-I limited tumour growth significantly up to 11 days after treatment compared to that of untreated mice and mice with longer PBS-suspended OT-I treatment (9 days), but slightly less than that of mice with IV-delivered OT-I treatment (14 days). No significant difference was observed when directly comparing the gel and IV treatments. Although further optimization of the treatment is required, this work shows the feasibility and potential of the chitosan gel for localised OT-I delivery in cancer immunotherapy.

Open-sourced Raman spectroscopy data processing package implementing a baseline removal algorithm validated from multiple datasets acquired in human tissue and biofluids.

Significance: Standardized data processing approaches are required in the field of bio-Raman spectroscopy to ensure information associated with spectral data acquired by different research groups, and with different systems, can be compared on an equal footing. Aim: An open-sourced data processing software package was developed, implementing algorithms associated with all steps required to isolate the inelastic scattering component from signals acquired using Raman spectroscopy devices. The package includes a novel morphological baseline removal technique (BubbleFill) that provides increased adaptability to complex baseline shapes compared to current gold standard techniques. Also incorporated in the package is a versatile tool simulating spectroscopic data with varying levels of Raman signal-to-background ratios, baselines with different morphologies, and varying levels of stochastic noise. Results: Application of the BubbleFill technique to simulated data demonstrated superior baseline removal performance compared to standard algorithms, including iModPoly and MorphBR. The data processing workflow of the open-sourced package was validated in four independent in-human datasets, demonstrating it leads to inter-systems data compatibility. Conclusions: A new open-sourced spectroscopic data pre-processing package was validated on simulated and real-world in-human data and is now available to researchers and clinicians for the development of new clinical applications using Raman spectroscopy.

UGT2B28 accelerates prostate cancer progression through stabilization of the endocytic adaptor protein HIP1 regulating AR and EGFR pathways.

The androgen inactivating UGT2B28 pathway emerges as a predictor of progression in prostate cancer (PCa). However, the clinical significance of UGT2B28 tumoral expression and its contribution to PCa progression remain unclear. Using the Canadian Prostate Cancer Biomarker Network biobank (CPCBN; n = 1512), we analyzed UGT2B28 tumor expression in relation to clinical outcomes in men with localized PCa. UGT2B28 was overexpressed in tumors compared to paired normal adjacent prostatic tissue and was associated with inferior outcomes. Functional analyses indicated that UGT2B28 promoted cell proliferation, and its expression was regulated by the androgen receptor (AR)/ARv7. Mechanistically, UGT2B28 was shown to be a protein partner of the endocytic adaptor protein huntingtin-interacting protein 1 (HIP1), increasing its stability and priming AR/epidermal growth factor receptor (EGFR) pathways, leading to ERK1/2 activation triggering cell proliferation and epithelial-to-mesenchymal transition (EMT). HIP1 knockdown in UGT2B28 positive cells, and dual pharmacological targeting of AR and EGFR pathways, abolished cell proliferative advantages conferred by UGT2B28. In conclusion, UGT2B28 is a prognosticator of progression in localized PCa, regulates both AR and EGFR oncogenic signaling pathways via HIP1, and therefore can be therapeutically targeted by using combination of existing AR/EGFR inhibitors.

Image-guided Raman spectroscopy navigation system to improve transperineal prostate cancer detection. Part 1: Raman spectroscopy fiber-optics system and in situ tissue characterization.

SIGNIFICANCE: The diagnosis of prostate cancer (PCa) and focal treatment by brachytherapy are limited by the lack of precise intraoperative information to target tumors during biopsy collection and radiation seed placement. Image-guidance techniques could improve the safety and diagnostic yield of biopsy collection as well as increase the efficacy of radiotherapy. AIM: To estimate the accuracy of PCa detection using in situ Raman spectroscopy (RS) in a pilot in-human clinical study and assess biochemical differences between in vivo and ex vivo measurements. APPROACH: A new miniature RS fiber-optics system equipped with an electromagnetic (EM) tracker was guided by trans-rectal ultrasound-guided imaging, fused with preoperative magnetic resonance imaging to acquire 49 spectra in situ (in vivo) from 18 PCa patients. In addition, 179 spectra were acquired ex vivo in fresh prostate samples from 14 patients who underwent radical prostatectomy. Two machine-learning models were trained to discriminate cancer from normal prostate tissue from both in situ and ex vivo datasets. RESULTS: A support vector machine (SVM) model was trained on the in situ dataset and its performance was evaluated using leave-one-patient-out cross validation from 28 normal prostate measurements and 21 in-tumor measurements. The model performed at 86% sensitivity and 72% specificity. Similarly, an SVM model was trained with the ex vivo dataset from 152 normal prostate measurements and 27 tumor measurements showing reduced cancer detection performance mostly attributable to spatial registration inaccuracies between probe measurements and histology assessment. A qualitative comparison between in situ and ex vivo measurements demonstrated a one-to-one correspondence and similar ratios between the main Raman bands (e.g., amide I-II bands, phenylalanine). CONCLUSIONS: PCa detection can be achieved using RS and machine learning models for image-guidance applications using in situ measurements during prostate biopsy procedures.

Image-guided Raman spectroscopy navigation system to improve transperineal prostate cancer detection. Part 2: in-vivo tumor-targeting using a classification model combining spectral and MRI-radiomics features.

SIGNIFICANCE: The diagnosis and treatment of prostate cancer (PCa) are limited by a lack of intraoperative information to accurately target tumors with needles for biopsy and brachytherapy. An innovative image-guidance technique using optical devices could improve the diagnostic yield of biopsy and efficacy of radiotherapy. AIM: To evaluate the performance of multimodal PCa detection using biomolecular features from in-situ Raman spectroscopy (RS) combined with image-based (radiomics) features from multiparametric magnetic resonance images (mpMRI). APPROACH: In a prospective pilot clinical study, 18 patients were recruited and underwent high-dose-rate brachytherapy. Multimodality image fusion (preoperative mpMRI with intraoperative transrectal ultrasound) combined with electromagnetic tracking was used to navigate an RS needle in the prostate prior to brachytherapy. This resulting dataset consisted of Raman spectra and co-located radiomics features from mpMRI. Feature selection was performed with the constraint that no more than 10 features were retained overall from a combination of inelastic scattering spectra and radiomics. These features were used to train support vector machine classifiers for PCa detection based on leave-one-patient-out cross-validation. RESULTS: RS along with biopsy samples were acquired from 47 sites along the insertion trajectory of the fiber-optics needle: 26 were confirmed as benign or grade group = 1, and 21 as grade group >1, according to histopathological reports. The combination of the fingerprint region of the RS and radiomics showed an accuracy of 83% (sensitivity = 81 % and a specificity = 85 % ), outperforming by more than 9% models trained with either spectroscopic or mpMRI data alone. An optimal number of features was identified between 6 and 8 features, which have good potential for discriminating grade group ≥1 / grade group <1 (accuracy = 87 % ) or grade group >1 / grade group ≤1 (accuracy = 91 % ). CONCLUSIONS: In-situ Raman spectroscopy combined with mpMRI radiomics features can lead to highly accurate PCa detection for improved in-vivo targeting of biopsy sample collection and radiotherapy seed placement.

High Levels of MFG-E8 Confer a Good Prognosis in Prostate and Renal Cancer Patients.

Milk fat globule-epidermal growth factor-8 (MFG-E8) is a glycoprotein secreted by different cell types, including apoptotic cells and activated macrophages. MFG-E8 is highly expressed in a variety of cancers and is classically associated with tumor growth and poor patient prognosis through reprogramming of macrophages into the pro-tumoral/pro-angiogenic M2 phenotype. To date, correlations between levels of MFG-E8 and patient survival in prostate and renal cancers remain unclear. Here, we quantified MFG-E8 and CD68/CD206 expression by immunofluorescence staining in tissue microarrays constructed from renal (n = 190) and prostate (n = 274) cancer patient specimens. Percentages of MFG-E8-positive surface area were assessed in each patient core and Kaplan-Meier analyses were performed accordingly. We found that MFG-E8 was expressed more abundantly in malignant regions of prostate tissue and papillary renal cell carcinoma but was also increased in the normal adjacent regions in clear cell renal carcinoma. In addition, M2 tumor-associated macrophage staining was increased in the normal adjacent tissues compared to the malignant areas in renal cancer patients. Overall, high tissue expression of MFG-E8 was associated with less disease progression and better survival in prostate and renal cancer patients. Our observations provide new insights into tumoral MFG-E8 content and macrophage reprogramming in cancer.

High Keratin-7 Expression in Benign Peri-Tumoral Prostatic Glands Is Predictive of Bone Metastasis Onset and Prostate Cancer-Specific Mortality.

BACKGROUND: New predictive biomarkers are needed to accurately predict metastasis-free survival (MFS) and cancer-specific survival (CSS) in localized prostate cancer (PC). Keratin-7 (KRT7) overexpression has been associated with poor prognosis in several cancers and is described as a novel prostate progenitor marker in the mouse prostate. METHODS: KRT7 expression was evaluated in prostatic cell lines and in human tissue by immunohistochemistry (IHC, on advanced PC, n = 91) and immunofluorescence (IF, on localized PC, n = 285). The KRT7 mean fluorescence intensity (MFI) was quantified in different compartments by digital analysis and correlated to clinical endpoints in the localized PC cohort. RESULTS: KRT7 is expressed in prostatic cell lines and found in the basal and supra-basal compartment from healthy prostatic glands and benign peri-tumoral glands from localized PC. The KRT7 staining is lost in luminal cells from localized tumors and found as an aberrant sporadic staining (2.2%) in advanced PC. In the localized PC cohort, high KRT7 MFI above the 80th percentile in the basal compartment was significantly and independently correlated with MFS and CSS, and with hypertrophic basal cell phenotype. CONCLUSION: High KRT7 expression in benign glands is an independent biomarker of MFS and CSS, and its expression is lost in tumoral cells. These results require further validation on larger cohorts.

Intraductal Carcinoma of the Prostate as a Cause of Prostate Cancer Metastasis: A Molecular Portrait.

Intraductal carcinoma of the prostate (IDC-P) is one of the most aggressive types of prostate cancer (PCa). IDC-P is identified in approximately 20% of PCa patients and is associated with recurrence, metastasis, and PCa-specific death. The main feature of this histological variant is the colonization of benign glands by PCa cells. Although IDC-P is a well-recognized independent parameter for metastasis, mechanisms by which IDC-P cells can spread and colonize other tissues are not fully known. In this review, we discuss the molecular portraits of IDC-P determined by immunohistochemistry and genomic approaches and highlight the areas in which more research is needed.

The Movember Global Action Plan 1 (GAP1): Unique Prostate Cancer Tissue Microarray Resource.

BACKGROUND: The need to better understand the molecular underpinnings of the heterogeneous outcomes of patients with prostate cancer is a pressing global problem and a key research priority for Movember. To address this, the Movember Global Action Plan 1 Unique tissue microarray (GAP1-UTMA) project constructed a set of unique and richly annotated tissue microarrays (TMA) from prostate cancer samples obtained from multiple institutions across several global locations. METHODS: Three separate TMA sets were built that differ by purpose and disease state. RESULTS: The intended use of TMA1 (Primary Matched LN) is to validate biomarkers that help determine which clinically localized prostate cancers with associated lymph node metastasis have a high risk of progression to lethal castration-resistant metastatic disease, and to compare molecular properties of high-risk index lesions within the prostate to regional lymph node metastases resected at the time of prostatectomy. TMA2 (Pre vs. Post ADT) was designed to address questions regarding risk of castration-resistant prostate cancer (CRPC) and response to suppression of the androgen receptor/androgen axis, and characterization of the castration-resistant phenotype. TMA3 (CRPC Met Heterogeneity)'s intended use is to assess the heterogeneity of molecular markers across different anatomic sites in lethal prostate cancer metastases. CONCLUSIONS: The GAP1-UTMA project has succeeded in combining a large set of tissue specimens from 501 patients with prostate cancer with rich clinical annotation. IMPACT: This resource is now available to the prostate cancer community as a tool for biomarker validation to address important unanswered clinical questions around disease progression and response to treatment.

Saliva-based detection of COVID-19 infection in a real-world setting using reagent-free Raman spectroscopy and machine learning.

SIGNIFICANCE: The primary method of COVID-19 detection is reverse transcription polymerase chain reaction (RT-PCR) testing. PCR test sensitivity may decrease as more variants of concern arise and reagents may become less specific to the virus. AIM: We aimed to develop a reagent-free way to detect COVID-19 in a real-world setting with minimal constraints on sample acquisition. The machine learning (ML) models involved could be frequently updated to include spectral information about variants without needing to develop new reagents. APPROACH: We present a workflow for collecting, preparing, and imaging dried saliva supernatant droplets using a non-invasive, label-free technique-Raman spectroscopy-to detect changes in the molecular profile of saliva associated with COVID-19 infection. RESULTS: We used an innovative multiple instance learning-based ML approach and droplet segmentation to analyze droplets. Amongst all confounding factors, we discriminated between COVID-positive and COVID-negative individuals yielding receiver operating coefficient curves with an area under curve (AUC) of 0.8 in both males (79% sensitivity and 75% specificity) and females (84% sensitivity and 64% specificity). Taking the sex of the saliva donor into account increased the AUC by 5%. CONCLUSION: These findings may pave the way for new rapid Raman spectroscopic screening tools for COVID-19 and other infectious diseases.

Multispectral label-free Raman spectroscopy can detect ovarian and endometrial cancer with high accuracy.

Up to 70% of ovarian cancer patients are diagnosed with advanced-stage disease and the degree of cytoreduction is an important survival prognostic factor. The aim of this study was to evaluate if Raman spectroscopy could detect cancer from different organs within the abdominopelvic region, including the ovaries. A Raman spectroscopy probe was used to interrogate specimens from a cohort of nine patients undergoing cytoreductive surgery, including four ovarian cancer patients and three patients with endometrial cancer. A feature-selection algorithm was developed to determine which spectral bands contributed to cancer detection and a machine-learning model was trained. The model could detect cancer using only eight spectral bands. The receiver-operating-characteristic curve had an area-under-the-curve of 0.96, corresponding to an accuracy, a sensitivity and a specificity of 90%, 93% and 88%, respectively. These results provide evidence multispectral Raman spectroscopy could be developed to detect ovarian cancer intraoperatively.

The Triple-Tracer strategy against Metastatic PrOstate cancer (3TMPO) study protocol.

OBJECTIVE: To determine the prevalence of intra-patient inter-metastatic heterogeneity based on positron emission tomography (PET)/computed tomography (CT) in patients with metastatic castration-resistant prostate cancer (mCRPC) and to determine the prevalence of neuroendocrine disease in these patients and their eligibility for radioligand therapies (RLTs). PATIENTS AND METHODS: This multicentre observational prospective clinical study will include 100 patients with mCRPC from five Canadian academic centres. Patients with radiological or biochemical progression and harbouring at least three metastases by conventional imaging will be accrued. Intra-patient inter-metastatic heterogeneity will be determined with triple-tracer imaging using fluorine-18 fluorodeoxyglucose (18 F-FDG), gallium-68-(68 Ga)-prostate-specific membrane antigen (PSMA)-617 and 68 Ga-DOTATATE, which are a glucose analogue, a PSMA receptor ligand and a somatostatin receptor ligand, respectively. The 68 Ga-PSMA-617 and 18 F-FDG PET/CT scans will be performed first. If at least one PSMA-negative/FDG-positive lesion is observed, an additional PET/CT scan with 68 Ga-DOTATATE will be performed. The tracer uptake of individual lesions will be assessed for each PET tracer and patients with lesions presenting discordant uptake profiles will be considered as having inter-metastatic heterogeneous disease and may be offered a biopsy. EXPECTED RESULTS: The proposed triple-tracer approach will allow whole-body mCRPC characterisation, investigating the inter-metastatic heterogeneity in order to better understand the phenotypic plasticity of prostate cancer, including the neuroendocrine transdifferentiation that occurs during mCRPC progression. Based on 68 Ga-PSMA-617 or 68 Ga-DOTATATE PET positivity, the potential eligibility of patients for PSMA and DOTATATE-based RLT will be assessed. Non-invasive whole-body determination of mCRPC heterogeneity and transdifferentiation is highly innovative and might establish the basis for new therapeutic strategies. Comparison of molecular imaging findings with biopsies will also link metastasis biology to radiomic features. CONCLUSION: This study will add novel, biologically relevant dimensions to molecular imaging: the non-invasive detection of inter-metastatic heterogeneity and transdifferentiation to neuroendocrine prostate cancer by using a multi-tracer PET/CT strategy to further personalise the care of patients with mCRPC.

Identification of Morphologic Criteria Associated with Biochemical Recurrence in Intraductal Carcinoma of the Prostate.

Intraductal carcinoma of the prostate (IDC-P) is an aggressive subtype of prostate cancer strongly associated with an increased risk of biochemical recurrence (BCR). However, approximately 40% of men with IDC-P remain BCR-free five years after radical prostatectomy. In this retrospective multicenter study, we aimed to identify histologic criteria associated with BCR for IDC-P lesions. A total of 108 first-line radical prostatectomy specimens were reviewed. In our test cohort (n = 39), presence of larger duct size (>573 µm in diameter), cells with irregular nuclear contours (CINC) (≥5 CINC in two distinct high-power fields), high mitotic score (>1.81 mitoses/mm2), blood vessels, and comedonecrosis were associated with early BCR (<18 months) (p < 0.05). In our validation cohort (n = 69), the presence of CINC or blood vessels was independently associated with an increased risk of BCR (hazard ratio [HR] 2.32, 95% confidence interval [CI] 1.09-4.96, p = 0.029). When combining the criteria, the presence of any CINC, blood vessels, high mitotic score, or comedonecrosis showed a stronger association with BCR (HR 2.74, 95% CI 1.21-6.19, p = 0.015). Our results suggest that IDC-P can be classified as low versus high-risk of BCR. The defined morphologic criteria can be easily assessed and should be integrated for clinical application following validation in larger cohorts.

Dimensional reduction based on peak fitting of Raman micro spectroscopy data improves detection of prostate cancer in tissue specimens.

SIGNIFICANCE: Prostate cancer is the most common cancer among men. An accurate diagnosis of its severity at detection plays a major role in improving their survival. Recently, machine learning models using biomarkers identified from Raman micro-spectroscopy discriminated intraductal carcinoma of the prostate (IDC-P) from cancer tissue with a ≥85 % detection accuracy and differentiated high-grade prostatic intraepithelial neoplasia (HGPIN) from IDC-P with a ≥97.8 % accuracy. AIM: To improve the classification performance of machine learning models identifying different types of prostate cancer tissue using a new dimensional reduction technique. APPROACH: A radial basis function (RBF) kernel support vector machine (SVM) model was trained on Raman spectra of prostate tissue from a 272-patient cohort (Centre hospitalier de l'Université de Montréal, CHUM) and tested on two independent cohorts of 76 patients [University Health Network (UHN)] and 135 patients (Centre hospitalier universitaire de Québec-Université Laval, CHUQc-UL). Two types of engineered features were used. Individual intensity features, i.e., Raman signal intensity measured at particular wavelengths and novel Raman spectra fitted peak features consisting of peak heights and widths. RESULTS: Combining engineered features improved classification performance for the three aforementioned classification tasks. The improvements for IDC-P/cancer classification for the UHN and CHUQc-UL testing sets in accuracy, sensitivity, specificity, and area under the curve (AUC) are (numbers in parenthesis are associated with the CHUQc-UL testing set): +4 % (+8 % ), +7 % (+9 % ), +2 % (6%), +9 (+9) with respect to the current best models. Discrimination between HGPIN and IDC-P was also improved in both testing cohorts: +2.2 % (+1.7 % ), +4.5 % (+3.6 % ), +0 % (+0 % ), +2.3 (+0). While no global improvements were obtained for the normal versus cancer classification task [+0 % (-2 % ), +0 % (-3 % ), +2 % (-2 % ), +4 (+3)], the AUC was improved in both testing sets. CONCLUSIONS: Combining individual intensity features and novel Raman fitted peak features, improved the classification performance on two independent and multicenter testing sets in comparison to using only individual intensity features.