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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'Universite de Montreal, CHUM) and tested on two independent cohorts of 76 patients [University Health Network (UHN)] and 135 patients (Centre hospitalier universitaire de Quebec-Universite 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.

To test the agreement between high-grade PCa at RP and TMA, and the ability of TMA to predict BCR. Validation of concordance between tissue microarray (TMA) and radical prostatectomy (RP) high-grade prostate cancer (PCa) is crucial because latter determines the treated natural history of PCa. We hypothesized that TMA Gleason score is in agreement with RP pathology and capable of accurately predicting biochemical recurrence (BCR). Data were provided from a multi-institutional Canadian sample of 1333 TMA and RP specimens with complete clinicopathological data. First, rate of agreement between TMA and high-grade Gleason at RP or biopsy and RP was tested. Second, ability of RP, TMA and biopsy to predict BCR was compared. Multivariable (MVA) Cox regression models were fitted and BCR rates were illustrated with Kaplan-Meier plots. Agreement between RP and TMA and between RP and biopsy was 72.6% (95% CI:69.7-75.5) and 60.4% (95% CI:57.2-63.6), respectively. In MVA predicting BCR, the accuracy for RP, TMA and biopsy was 0.73, 0.72 and 0.68, respectively. TMA added discriminatory ability among exclusively low-grade Gleason RP patients (p = 0.02), but did not improve BCR discrimination in exclusive high-grade PCa RP patients (p = 0.8). TMA Gleason grade accurately reflects presence of high-grade Gleason in RP specimen, accurately predicts BCR rates after RP and improves prediction of BCR in low-grade Gleason patients at RP.

Background IKKε is an oncogenic kinase that was found amplified and overexpressed in a substantial percentage of human breast cancer cell lines and primary tumors using genomic and gene expression analyses. Molecular studies have provided the rational for a key implication of IKKε in breast cancer cells proliferation and invasiveness through the phosphorylation of several substrates. Methods Here, we performed immunohistochemical detection of IKKε expression on tissue microarrays constituted of 154 characterized human breast cancer tumors. We further determined the association with multiple clinicopathological parameters and 5-years overall, disease-free and distant disease free survival. Results We observed expression of IKKε in 60.4% of the breast cancer tumors. IKKε expression status showed no association with a panel of markers used for molecular classification of the tumors, including ER/PR/HER2 status, or with the molecular subtypes. However, IKKε expression was inversely associated with lymph node metastasis status (p = 0.0032). Additionally, we identified a novel association between IKKε and EGFR expression (p = 0.0011). Conclusions The unexpected observation of an inverse association between IKKε and lymph node metastasis advocates for larger scale immunohistochemical profiling of primary breast tumors to clarify the role of IKKε in metastasis. This study suggests that breast cancer tumors expressing EGFR and IKKε may be potential targets for drugs aiming at inhibiting IKKε activity or expression.

Background The identification of patients with high-risk prostate cancer (PC) is a major challenge for clinicians, and the improvement of current prognostic parameters is an unmet clinical need. We and others have identified an association between the nuclear localization of NF-κB p65 and biochemical recurrence (BCR) in PC in small and/or single-centre cohorts of patients. Methods and findings In this study, we accessed 2 different multi-centre tissue microarrays (TMAs) representing cohorts of patients (Test-TMA and Validation-TMA series) of the Canadian Prostate Cancer Biomarker Network (CPCBN) to validate the association between p65 nuclear frequency and PC outcomes. Immunohistochemical staining of p65 was performed on the Test-TMA and Validation-TMA series, which include PC tissues from patients treated by first-line radical prostatectomy (n = 250 and n = 1,262, respectively). Two independent observers evaluated the p65 nuclear frequency in digital images of cancer tissue and benign adjacent gland tissue. Kaplan–Meier curves coupled with a log-rank test and univariate and multivariate Cox regression models were used for statistical analyses of continuous values and dichotomized data (cutoff of 3%). Multivariate analysis of the Validation-TMA cohort showed that p65 nuclear frequency in cancer cells was an independent predictor of BCR using continuous (hazard ratio [HR] 1.02 [95% CI 1.00–1.03], p = 0.004) and dichotomized data (HR 1.33 [95% CI 1.09–1.62], p = 0.005). Using a cutoff of 3%, we found that this biomarker was also associated with the development of bone metastases (HR 1.82 [95% CI 1.05–3.16], p = 0.033) and PC-specific mortality (HR 2.63 [95% CI 1.30–5.31], p = 0.004), independent of clinical parameters. BCR-free survival, bone-metastasis-free survival, and PC-specific survival were shorter for patients with higher p65 nuclear frequency (p < 0.005). As the small cores on TMAs are a limitation of the study, a backward validation of whole PC tissue section will be necessary for the implementation of p65 nuclear frequency as a PC biomarker in the clinical workflow. Conclusions We report the first study using the pan-Canadian multi-centre cohorts of CPCBN and validate the association between increased frequency of nuclear p65 frequency and a risk of disease progression., Fred Saad and colleagues reveal the prognostic association between nuclear NF-κB p65 expression and prostate cancer outcomes., Author summary Why was this study done? In Canada and the US, prostate cancer is the most commonly diagnosed cancer in men. Identifying patients with aggressive prostate cancer is crucial for the choice of treatment to increase survival. Previously, we and others showed that the localization of a biomarker, nuclear factor kappa B (NF-κB) p65, in the nucleus of prostate cancer cells allows the identification of patients with aggressive prostate cancer. More specifically, the nuclear expression of NF-κB p65 is associated with cancer recurrence. What did the researchers do and find? To further validate our findings in a larger, multi-centre cohort of patients, we took advantage of the Canadian Prostate Cancer Biomarker Network (CPCBN) tissue microarrays that include a test (n = 250) and a validation (n = 1,262) series built with radical prostatectomy specimens from prostate cancer patients. We showed that NF-κB p65 in the nucleus of prostate cancer cells was associated with all evaluated prostate cancer endpoints (biochemical recurrence, development of bone metastases, and prostate-cancer-specific death). What do these findings mean? We validated the association between NF-κB p65 nuclear frequency and more aggressive prostate cancer. Nuclear frequency of NF-κB p65 should help to better identify patients with a higher risk of disease progression, and this could impact patient management. For the implementation of this biomarker in the clinical workflow, the investigation of nuclear frequency of NF-κB p65 in whole diagnostic samples will be important.

Objective To test if Raman spectroscopy (RS) is an appropriate tool for the diagnosis and possibly grading of prostate cancer (PCa). Patients and methods Between 20 and 50 Raman spectra were acquired from 32 fresh and non-processed post-prostatectomy specimens using a macroscopic handheld RS probe. Each measured area was characterized and categorized according to histopathological criteria: tissue type (extraprostatic or prostatic); tissue malignancy (benign or malignant); cancer grade (Grade Groups [GGs] 1-5); and tissue glandular level. The data were analysed using machine-learning classification with neural network. Results The RS technique was able to distinguish prostate from extraprostatic tissue with a sensitivity of 82% and a specificity of 83% and benign from malignant tissue with a sensitivity of 87% and a specificity of 86%. In an exploratory fashion, RS differentiated benign from GG1 in 726/801 spectra (91%; sensitivity 80%, specificity 91%), from GG2 in 588/805 spectra (73%; sensitivity 76%, specificity 73%), from GG3 in 670/797 spectra (84%; sensitivity 86%, specificity 84%), from GG4 in 711/802 spectra (88%; sensitivity 77%, specificity 89%) and from GG5 in 729/818 spectra (89%; sensitivity 90%, specificity 89%). Conclusion Current diagnostic approaches of PCa using needle biopsies have suboptimal cancer detection rates and a significant risk of infection. Standard non-targeted random sampling results in false-negative biopsies in 15-30% of patients, which affects clinical management. RS, a non-destructive tissue interrogation technique providing vibrational molecular information, resolved the highly complex architecture of the prostate and detect cancer with high accuracy using a fibre optic probe to interrogate radical prostatectomy (RP) specimens from 32 patients (947 spectra). This proof-of-principle paves the way for the development of in vivo tumour targeting spectroscopy tools for informed biopsy collection to address the clinical need for accurate PCa diagnosis and possibly to improve surgical resection during RP as a complement to histopathological analysis.

Background Prostate cancer (PC), initially diagnosed on biopsies by pathologists, is the most frequent cancer in North American men. However, better tools are needed for pathologists to diagnose intraductal carcinoma of the prostate (IDC), an aggressive histopathological variant of PC for which therapeutic options are now available. Indeed, no technique or biomarker is clinically available to support the diagnosis of IDC. Raman spectroscopy (RS) provides a global molecular characterisation of the tissue by analysing how photons interact with the molecules present in the tissue. Indeed, we and other groups previously used RS to detect cancer from multiple organ types, machine learning classification models being employed to process the complex Raman data. Methods We used Raman micro-spectroscopy (RµS) to detect IDC on tissues from 483 first-line radical prostatectomies from three Canadian institutions. Following a rapid, standardized and low-cost protocol, we acquired an average of 7 Raman spectra per patient and generated classification models using machine learning technology. Importantly, models were trained with data from one institution before independent testing on the data from the other two institutions. Results The three institutions included 272, 76 and 135 patients. Median age at diagnosis ranged from 61-62 years-old, with median pre-operative PSA ranging from 6.6-7.4 µg/L. Most patient had ≤3 + 4 Gleason score (60-80% of the specimens) and pT3-stage incidence was 31-55%. IDC was identified in 6-18% of the patients of each cohort. Overall, we acquired an average of 7 Raman spectra per patient. In the training cohort (N = 272), RµS identified IDC with a sensitivity of 95%, a specificity of 94% and an accuracy of 94%. Results from the testing cohort were in a similar range, with sensitivities of 88 and 92%, specificities of 83 and 91% and accuracies of 85 and 91%. Conclusions As clinically available biomarkers of IDC have reported sensitivities/specificities of ∼80%, we here identified IDC with accuracies ≥85%. Since our classification model was trained on a cohort and independently tested on the other two, these are likely to be close to real life experience making clinical implementation a realistic outcome. Legal entity responsible for the study The authors. Funding Centre de Recherche du Centre Hospitalier de l’Universite de Montreal (CRCHUM, continuum program) IVADO, Institut de valorisation des donnees. Disclosure All authors have declared no conflicts of interest.

Resistance to apoptosis induced by anti-cancer drugs is a major obstacle for the treatment of aggressive forms of breast cancer. Galectin-7 was recently shown to be specifically expressed in basal-like and HER-2 positive but not in luminal subtypes of human breast cancer. Galectin-7 also increases the metastatic behavior of breast cancer cells since overexpression of this protein in poorly metastatic breast cancer cells increases their ability to metastasize to the bone and to the lung. This pro-tumoral activity of galectin-7 in breast cancer is surprising since galectin-7 had been previously associated with activation of p53 and breast cancer cells often harbor a transcriptionally inactive form of p53. We have recently reconcile this apparent contradiction by showing that elevated levels of galectin-7 in breast cancer cells occurs via a gain-of-function mechanism of mutant p53. In p53-null breast cancer cells, we have shown that C/EBPβ-2 (also known as LAP2), the most transcriptionally active of the C/EBPβ isoforms, is responsible for the upregulation of galectin-7. How galectin-7 contributes to the progression of breast cancer remains unclear. Up to now, regulation of apoptosis by intracellular galectins has been largely attributed to their ability to translocate to mitochondria, possibly following their interaction with bcl-2. Here, we report that a mutant of galectin-7 that is unable to translocate to mitochondria induces resistance of human breast cancer cells to apoptosis induced by etoposide or by hypoxia-mimicking conditions. Surprisingly, this mutant and the wild-type form of galectin-7 bind equally well to bcl-2 in vitro and in vivo. Interestingly, both forms decreases the translocation of p53 to the nucleus and reduce the expression of p21 following treatment with doxorubicin. We also found that galectin-7 was released by breast cancer cells and that recombinant galectin-7 increased apoptosis of monocytes, T CD4+ and T CD8+ cells. This suggests that galectin-7 contributes to the establishment of an immunosuppressive tumor microenvironment by killing helper and effector T cells. Taken together, these results challenges the current paradigm that mitochondrial galectins are important for resistance to apoptosis and call for a greater focus on the role of galectin-7 in breast cancer. They also indicate that targeting both cytosolic and extracellular galectin-7 could improve the efficacy of anti-cancer drugs for the treatment of aggressive forms of breast cancer. Citation Format: Yves St-Pierre, Andrée-Anne Grosset, Marilyne Labrie, Donald Gagné, Maria-Claudia Vladoiu, Louis Gaboury, Nicolas Doucet. Galectin-7 increases resistance of breast cancer cells to drug-induced apoptosis and promotes tumor escape by killing T cells [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P1-07-16.

Hematoxylin and eosin (H&E) staining is a well-established technique in histopathology. However, immunohistochemistry (IHC) interpretation is done exclusively with hematoxylin counterstaining. Our goal was to investigate the potential of H&E as counterstaining (H&E-IHC) to allow for visualization of a marker while confirming the diagnosis on the same slide. The quality of immunostaining and the fast-technical performance were the main criteria to select the final protocol. We stained multiple diagnostic tissues with class I IHC tests with different subcellular localization markers (anti-CK7, CK20, synaptophysin, CD20, HMB45, and Ki-67) and with double-staining on prostate tissues with anti-high molecular weight keratins/p63 (DAB detection) and p504s (alkaline phosphatase detection). To validate the efficacy of the counterstaining, we stained tissue microarrays from the Canadian Immunohistochemistry Quality Control (cIQc) with class II IHC tests (ER, PR, HER2, and p53 markers). Interobserver and intraobserver concordance was assessed by κ statistics. Excellent agreement of H&E-IHC interpretation was observed in comparison with standard IHC from our laboratory (κ, 0.87 to 1.00), and with the cIQc reference values (κ, 0.81 to 1.00). Interobserver and intraobserver agreement was excellent (κ, 0.89 to 1.00 and 0.87 to 1.00, respectively). We therefore show for the first time the potential of using H&E counterstaining for IHC interpretation. We recommend the H&E-IHC protocol to enhance diagnostic precision for the clinical workflow and research studies.

Background To investigate the effect of intraductal carcinoma of the prostate (IDC-P) in radical prostatectomy (RP) specimens in the context of the site of recurrence, time to recurrence, and cancer-specific survival in two academic cohorts of locally, regionally, or distantly recurrent prostate cancer. Methods Our cohort included men enrolled into two academic tissue repositories from 1993 to 2011, who were treated with first-line RP who later experienced local recurrence, regional recurrence, or distant metastasis (together termed clinical recurrence, CR). RP material was reviewed to identify IDC-P and to update grading to current standards. The primary endpoint was the initial location of CR. Secondary endpoints included time to CR and cancer-specific survival. Pearson's chi-square, Welch's t-test, Mann-Whitney U test and Fisher's exact test were performed for univariate analyses. Multinomial logistic regression was used for multivariate analyses. Cancer-specific survival was analyzed with the generalized Wilcoxon test and Cox regression. Results Eighty-five patients with CR were included in the analysis. IDC-P was present in 78.5% of patients from Center 1 and 70.0% from Center 2 (P = 0.547). IDC-P was independently associated with distant metastasis at initial CR (multivariate odds ratio = 6.27, P = 0.015). IDC-P status did not affect time to recurrence; median survival without recurrence was at 53 months for IDC-P(+) and at 50 months for IDC-P(-) (P = 0.441). Distant metastases at the initial CR event had a 36% reduction of cancer-specific survival compared to local recurrences (P = 0.007). Additionally, prostatic-bed radiotherapy (adjuvant or salvage for biochemical recurrence before distant metastasis) was associated with a 25% reduction in cancer-specific mortality compared to no radiotherapy (P = 0.023). Similar reduction in cancer-specific mortality was observed in the subgroup of patients with distant metastasis and IDC-P when treated with radiotherapy (29%, P = 0.050). Conclusions In our cohort, presence of IDC-P was an independent factor for distant metastasis at initial CR, but did not have a significant impact on time to CR. Furthermore, metastatic patients showed statistically reduced cancer-specific mortality when treated with radiotherapy. This reduction in cancer-specific mortality was also identified in patients with IDC-P. Future large scale validation studies should take into account the presence of IDC-P and confirm its impact on disease progression.

Prostate cancer is the most frequent diagnosed cancers among men. When prostate cancer occurs, the cancer does not result in only one or few localized malignant tumor, but is generally spread within the whole prostate. In order to counteract the very high level of heterogeneities exhibited by prostate tissues, we developed a method for high-resolution co-registration of Raman spectroscopy with prostate cancer diagnosis. Raman spectra were acquired on fresh ex vivo prostate within 2 hours after radical prostatectomy using a multi-wavelength hand-held contact probe. After the measurements, the prostate was reintegrated to the usual pathological workflow: formalin fixated and paraffin embedded (FFPE), and prepared for microscope histopathological analyses. The precise reconstruction of the prostate slice with hematoxylin and eosin (H and E) tissue allows the spatial correlation of the measured area (0.2 mm2) with the correspondent histopathological information, for point-by-point diagnosis determination. The tissue was classified into groups (normal/cancer) and subgroups according to the percentage of benign glands, stroma or cancer. Different machine learning algorithms were tested to classify the spectra with increasing levels of categorization. Preliminary results showed that Raman spectroscopy is capable of detecting prostate cancer with an accuracy >90%. In addition, high percentages of stroma (vs. glands) have been correlated with spectral signature of collagen, which is the main constituent of extracellular matrix.

Background: There is an urgent need for pathologists to better define patients with high-risk prostate cancer. One of the promising tools is Raman micro-spectroscopy, also known as Raman microscopy, a nondestructive and label-free imaging technique based on light scattered after reflection. Our group has recently developed a rapid standardized protocol for the preparation of formalin-fixed, paraffin-embedded (FFPE) diagnostic tissues suitable for Raman microscopy. The objective of this study was to evaluate the potential of Raman microscopy to assess the prognosis of prostate cancer patients with FFPE tissues from radical prostatectomy. Methods: Patients treated by first-line radical prostatectomy between 1994 and 2004 at Centre hospitalier de l’Université de Montréal (CHUM) were included in this study. FFPE prostate cancer tissues from surgery were used for the construction of tissue microarrays (TMAs). To enable Raman microscopy, TMA sections of 4 µm were placed on low-cost aluminum slides. The rapid dewaxing protocol of the hospital was used (8 minutes), followed by 20 minutes of vacuum drying. All Raman spectra were acquired with the Renishaw inVia confocal Raman microscope equipped with a 785-nm line focus laser. After removing background contributions (e.g., autofluorescence) for each spectrum with Wire 4.4 software, a custom toolbox in MATLAB was used to predict biochemical recurrence. Chemometric methods and calculated ratios were used for the analysis of Raman microscopy images. Results: A total of 320 Raman spectra from 80 patients were analyzed from prostate cancer TMAs, representing 25 patients with biochemical recurrence within 18 months after radical prostatectomy and 55 without. Using a Support Vector Machine (SVM) technique and correlation feature selection for classification, our results with Raman microscopy identified biochemical recurrence with an accuracy of 83.7%, a sensitivity of 84.0% and a specificity of 83.6%. Raman peak assignment of features was used to investigate the molecular differences between these two patient groups. We found that the molecular constituents of RNA and phosphorylated proteins were more important in prostate cancer with biochemical recurrence. In contrast, Raman peaks of the phospholipid head of cell membranes, DNA, and collagen were more intense in prostate cancer without biochemical recurrence. For the visualization of these different molecular constituents of prostate cancer, we developed two methods of Raman microscopy imaging. The first method involved analysis of chemometric data (i.e., extraction of chemical information) to identify the whole tissue (phenylalanine), nuclei (DNA), and red blood cells (hemoglobin), followed by background removal. The images of our chemometric analysis created a virtual staining of hematoxylin and eosin (H&E). The second method involved testing several ratios of Raman peaks associated with proteins, lipids, DNA and RNA. Calculated ratios distinguished specific structures of the prostate tissue, such as the cancerous and normal glands, by different colors. Conclusions: This is the first study demonstrating the potential of Raman microscopy for the prediction of biochemical recurrence within 18 months following radical prostatectomy for prostate cancer. Raman microscopy imaging of tissues is a promising method for the recognition of specific structures, which could help pathologists in the accuracy of diagnosis. The accessibility of this technology to clinicians could be useful for patient follow-up and treatment strategies. Citation Format: Andrée-Anne Grosset, Catherine St-Pierre, Karl St-Arnaud, Kelly Aubertin, Michael Jermyn, Frédéric Leblond, Dominique Trudel. Raman microscopy to assess biochemical recurrence risk after radical prostatectomy [abstract]. In: Proceedings of the AACR Special Conference: Prostate Cancer: Advances in Basic, Translational, and Clinical Research; 2017 Dec 2-5; Orlando, Florida. Philadelphia (PA): AACR; Cancer Res 2018;78(16 Suppl):Abstract nr A014.

For the first time, molecular information deduced from Raman spectroscopy measurements was spatially correlated with histopathologic analysis to detect and characterize prostate cancer (PCa) using Raman spectroscopy (RS). Ex vivo post-prostatectomy specimen were interrogated using a handheld RS probe. Up to 50 areas (of 500µm in diameter each) per prostate slice were correlated spatially with hematoxylin, phloxine, and saffron (HPS) stained images for detailed histopathologic characteristics, including percentage of benign glands and cancer grade group (International Society of Urological Pathology, ISUP): (1) each measured area was identified with a spot of Indian ink; (2) a photograph was taken at the end of the measurements to build a mask including the prostate slice contour and circles corresponding to the measured areas; (3) the whole prostate slice was reconstructed from the HPS scans guided by anatomic landmarks to insure spatial correspondence with the fresh prostate slice photograph. The Raman spectra were analyzed in terms of univariate statistics of specific Raman peaks corresponding to biomolecules such as DNA/RNA, amino acids, or lipids. In addition, the spectra were submitted to multivariate statistical classification using machine learning algorithms (artificial neural network). In order to test the validity of ex vivo conditions regarding intraoperative (i.e., in vivo) applications, we measured and compared different rat organs (including brain, prostate, ovarian, spleen, kidney, and liver) in in vivo and ex vivo conditions. Previous studies about the use of RS for PCa detection were done exclusively on cell lines or snap-frozen human tissue by considering the overall patient diagnosis. PCa tissues are highly heterogeneous morphologically: cancer glands are intermingled with benign glands and tumors are often multiclonal. Therefore, local histopathologic criteria must be considered. We designed a method that allows us to correlate spatially each Raman spectrum with precise diagnostic criteria and we were able to distinguish extraprostatic from prostatic tissue with an accuracy of 82% (sensibility of 82%, specificity of 83%), malignant from benign prostatic tissue with an accuracy over 86% (sensibility of 87%, specificity of 86%), and different cancer grade groups, for instance, with an accuracy of 84% for distinguishing ISUP grade group 1 from 5. When comparing in vivo with ex vivo rat tissues, preliminary results showed that the difference between average spectra is of the same magnitude than the variability within the same tissue type (same organ from different rats), therefore meaning that ex vivo RS data could be used to train classifier for in vivo diagnosis. Thanks to our robust methodology spatially correlating the optical measurements with local histopathologic characteristics, our work on ex vivo human prostates has proved that we have the capability to characterize the heterogeneity of prostate tissue in the context of PCa. In addition, we established that the use of ex vivo specimen to mimic intraoperative condition is valid. These are promising results, especially in the context of optical guided biopsy procedure to help collect targeted tissue to decrease the false-negative rate nowadays associated with the procedure (~30%). Citation Format: Kelly Aubertin, Mirela Birlea, Michael Pinto, Karl St-Arnaud, Vincent Quoc Trinh, Andrée-Anne Grosset, Frédéric Leblond, Dominique Trudel. Towards the use of Raman spectroscopy to guide prostate biopsy procedure [abstract]. In: Proceedings of the AACR Special Conference: Prostate Cancer: Advances in Basic, Translational, and Clinical Research; 2017 Dec 2-5; Orlando, Florida. Philadelphia (PA): AACR; Cancer Res 2018;78(16 Suppl):Abstract nr B063.

Purpose: Although the murine orthologue of glycoprotein nonmetastatic B (GPNMB), Osteoactivin, promotes breast cancer metastasis in an in vivo mouse model, its importance in human breast cancer is unknown. We have examined the significance of GPNMB expression as a prognostic indicator of recurrence and assessed its potential as a novel therapeutic target in breast cancer. Experimental Design: The clinical significance of GPNMB expression in breast cancer was addressed by analyzing GPNMB levels in several published gene expression data sets and two independent tissue microarrays derived from human breast tumors. GPNMB-expressing human breast cancer cell lines were further used to validate a toxin-conjugated anti-GPNMB antibody as a novel therapeutic agent. Results: GPNMB expression correlates with shorter recurrence times and reduced overall survival of breast cancer patients. Epithelial-specific GPNMB staining is an independent prognostic indicator for breast cancer recurrence. GPNMB is highly expressed in basal and triple-negative breast cancers and is associated with increased risk of recurrence within this subtype. GPNMB expression confers a more migratory and invasive phenotype on breast cancer cells and sensitizes them to killing by CDX-011 (glembatumumab vedotin), a GPNMB-targeted antibody-drug conjugate. Conclusions: GPNMB expression is associated with the basal/triple-negative subtype and is a prognostic marker of poor outcome in patients with breast cancer. CDX-011 (glembatumumab vedotin) is a promising new targeted therapy for patients with metastatic triple-negative breast cancers, a patient population that currently lacks targeted-therapy options. Clin Cancer Res; 16(7); 2147–56. ©2010 AACR.

80 Background: The CPCBN has assembled a TMA-based resource comprising the specimens of 1512 prostate cancer patients treated by radical prostatectomy. This richly annotated and multi-institutional resource is available to researchers who wish to access a large cohort to validate prognostic biomarkers (http://www.tfri.ca/en/research/translational-research/cpcbn.aspx). Over the last decade, our laboratory demonstrated with an independent cohort (Gannon PO, et al. Eur J Cancer. 2013 Jul;49(10):2441-8, Labouba I, et al. PLoS One. 2015 Jul 17;10(7):e0131024), the reproducible association of nuclear factor-kappa B (NF-kB) p65 with patient’s risk of biochemical recurrence. Here, we evaluated the CPCBN TMA-series for p65 expression. Methods: Two independent observers scored the frequency of p65 nuclear localisation on digital images obtained after automated immunohistochemistry analysis of p65. Over the available minimum 3 cores of tumour tissue per patient, an average percentage of positive nucleus frequency was used. Statistical analyses were performed using SPSS software. Results: High nuclear frequency of NF-kB p65 (cut-off at 3%) was associated with an increased risk for patients to experience a biochemical relapse (p < 0.001; Exp(B) = 1.599; 95%CI = 1.321-1.937), develop bone metastasis (p = 0.007; Exp(B) = 2.126; 95%CI = 1.234-3.663)and die from their disease (p = 0.001; Exp(B) = 3.117; 95%CI = 1.55-6.266). In multivariate analyses, p65 also remained independent from clinical parameters (PSA, Gleason score and pTNM): biochemical relapse (p = 0.005; Exp(B) = 1.331; 95%CI = 1.092-1.623), bone metastasis (p = 0.033; Exp(B) = 1.82; 95%CI = 1.04- 3.158), mortality (p = 0.007; Exp(B) = 2.626; 95%CI = 1.298-5.312) Conclusions: Using a large cohort of Canadian men, our study reiterates the previous study linking NF-kB p65 with prostate cancer progression and highlights the suitability of CPCBN TMAs for biomarker validation. Our results also reveal the role of p65 as a predictor of bone metastasis development and prostate cancer-specific mortality.

Prostate cancer (PCa) is the most frequently diagnosed cancer among men. PCa diagnosis is currently based on analyses of the morphological organization of tissue. The process from tissue collection to diagnosis is time consuming and can be too long for intraoperative diagnosis. Raman spectroscopy (RS) is a label-free and non-destructive laser-based technique that provides real-time molecular information about tissue. Histologically, cancer patterns are intermingled with entrapped benign glands. Because of the very high level of heterogeneity exhibited by prostate tissues, it is highly important to identify precisely the tissue type measured by RS. To this aim, we developed a method for high-resolution co-registration of RS with PCa diagnosis.Raman spectra are acquired on fresh ex vivo prostates within 2 hours after radical prostatectomy using a multi-wavelength hand-held contact Raman probe. The prostate is then reintegrated to the usual clinical pathological workflow for formalin fixation and paraffin embedding (FFPE) and preparation for optic microscope histopathological analyses. The precise reconstruction of the prostate slice with hematoxylin & eosin (H&E) tissue allows the spatial correlation of the measured areas (0.2 mm2) with the correspondent histopathological information, for point-by-point diagnosis. The tissue is then classified into groups (benign/malignant) and subgroups according to the percentage of benign glands, stroma or cancer grades.Different machine learning algorithms were tested to classify the spectra with different levels of categorization. Preliminary results showed that RS is capable of detecting PCa with an accuray of 89%. Within the benign tissue group, high stroma/glands rations have been correlated with the spectral signature of collagen, which is the main constituent of stroma. Within the cancer tissue group, high grade patterns were find to be different from low grade patterns, demonstrating that RS is able to distinguish aggressive from less aggressive cancers.

Purpose: While the murine orthologue of GPNMB (Glycoprotein non-metastatic B, DC-HIL, HGFIN), Osteoactivin, has been shown to promote breast cancer metastasis in an in vivo mouse model, its importance in human breast cancer is unknown. We have examined the significance of GPNMB expression as a prognostic indicator of recurrence and assessed its potential as a novel therapeutic target in breast cancer. Experimental Design: The clinical significance of GPNMB expression in breast cancer was addressed by analyzing GPNMB mRNA levels in several published gene expression datasets and by determining GPNMB protein expression in two independent tissue microarrays derived from human breast tumors. Human breast cancer cell lines endogenously or exogenously expressing GPNMB were further used to validate a toxin-conjugated anti-GPNMB antibody as a novel therapeutic agent. Results: GPNMB expression correlates with shorter times to recurrence and reduced overall survival of breast cancer patients. Epithelial-specific staining of GPNMB serves as an independent prognostic indicator for breast cancer recurrence. GPNMB is highly expressed in basal and triple-negative (TN) breast cancers and is associated with increased risk of recurrence within this subtype. GPNMB expression confers a more migratory and invasive phenotype on breast cancer cells. Treatment of mice harbouring endogenous GPNMB-expressing human breast cancer xenografts with CDX-011 (glembatumumab vedotin, CR011-vcMMAE), a GPNMB-targeted antibody-drug conjugate, induces and sustains tumor regression in vivo. Conclusions: GPNMB expression is associated with the basal/TN subtype and is a prognostic marker of poor outcome in patients with breast cancer. CDX-011 (glembatumumab vedotin) is a promising new targeted therapy for patients with metastatic TN breast cancers, a patient population that currently lacks targeted-therapy options. Citation Information: Clin Cancer Res 2010;16(7 Suppl):A8

Background Resistance to apoptosis induced by anti-cancer drugs is a major obstacle for the treatment of aggressive forms of breast cancer. Galectin-7 (gal-7) was recently shown to be specifically expressed in basal-like but not in luminal subtypes of human breast cancer. Methods We generated a mutant form of gal-7 (R74S). Arginine 74 is the structural equivalent of arginine 186 found in human galectin-3. Mutation R186S was previously shown to abolish the biological function of galectin-3. Results Mutation of arginine 74 induced only limited and local changes to the gal-7 fold. Recombinant forms of R74S and wtgal-7 were also equally effective at forming dimers in solution. Analysis of the thermodynamic parameters by isothermal titration calorimetry (ITC) indicated, however, that binding of lactose to gal-7 was inhibited by the R74S mutation. Using confocal microscopy and electron microscopy, we confirmed the expression of gal-7 in the cytosolic and nuclear compartments of breast cancer cells and the ability of gal-7 to translocate to mitochondria. The mutation at position 74, however, greatly reduced the expression of gal-7 in the nuclear and mitochondrial compartments. Interestingly, cells expressing mutated gal-7 were equally if not even more resistant to drug-induced apoptosis when compared to cells expressing wtgal-7. We also found that both wtgal-7 and R74S inhibited dox-induced PARP-1 cleavage and p53 protein expression. The inhibition of p53 correlated with a decrease in p21 protein expression and CDKN1A mRNA. Furthermore, analysis of nuclear and cytoplasmic fractions showed that both wild type and R74S mutant gal-7 inhibited p53 nuclear translocation, possibly by increasing degradation of cytosolic p53. Conclusions These findings pose a challenge to the paradigm that has guided the design of galectin-specific inhibitors for the treatment of cancer. This study suggests that targeting CRD-independent cytosolic gal-7 in breast cancer cells may be a valuable strategy for the treatment of this disease. Our study will thus complement efforts towards improving selectivity of targeted anticancer agents. Electronic supplementary material The online version of this article (doi:10.1186/1471-2407-14-801) contains supplementary material, which is available to authorized users.