Spatial analyses of immune cell infiltration in cancer: current methods and future directions: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer.

Modern histologic imaging platforms coupled with machine learning methods have provided new opportunities to map the spatial distribution of immune cells in the tumor microenvironment. However, there exists no standardized method for describing or analyzing spatial immune cell data, and most reported spatial analyses are rudimentary. In this review, we provide an overview of two approaches for reporting and analyzing spatial data (raster versus vector-based). We then provide a compendium of spatial immune cell metrics that have been reported in the literature, summarizing prognostic associations in the context of a variety of cancers. We conclude by discussing two well-described clinical biomarkers, the breast cancer stromal tumor infiltrating lymphocytes score and the colon cancer Immunoscore, and describe investigative opportunities to improve clinical utility of these spatial biomarkers. © 2023 The Pathological Society of Great Britain and Ireland.

Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer

The clinical significance of the tumor-immune interaction in breast cancer is now established, and tumor-infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2-negative) breast cancer and HER2-positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state-of-the-art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in-depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple-negative breast cancer. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Evaluation of a Natural Language Processing Approach to Identify Diagnostic Errors and Analysis of Safety Learning System Case Review Data: Retrospective Cohort Study.

BACKGROUND: Diagnostic errors are an underappreciated cause of preventable mortality in hospitals and pose a risk for severe patient harm and increase hospital length of stay. OBJECTIVE: This study aims to explore the potential of machine learning and natural language processing techniques in improving diagnostic safety surveillance. We conducted a rigorous evaluation of the feasibility and potential to use electronic health records clinical notes and existing case review data. METHODS: Safety Learning System case review data from 1 large health system composed of 10 hospitals in the mid-Atlantic region of the United States from February 2016 to September 2021 were analyzed. The case review outcome included opportunities for improvement including diagnostic opportunities for improvement. To supplement case review data, electronic health record clinical notes were extracted and analyzed. A simple logistic regression model along with 3 forms of logistic regression models (ie, Least Absolute Shrinkage and Selection Operator, Ridge, and Elastic Net) with regularization functions was trained on this data to compare classification performances in classifying patients who experienced diagnostic errors during hospitalization. Further, statistical tests were conducted to find significant differences between female and male patients who experienced diagnostic errors. RESULTS: In total, 126 (7.4%) patients (of 1704) had been identified by case reviewers as having experienced at least 1 diagnostic error. Patients who had experienced diagnostic error were grouped by sex: 59 (7.1%) of the 830 women and 67 (7.7%) of the 874 men. Among the patients who experienced a diagnostic error, female patients were older (median 72, IQR 66-80 vs median 67, IQR 57-76; P=.02), had higher rates of being admitted through general or internal medicine (69.5% vs 47.8%; P=.01), lower rates of cardiovascular-related admitted diagnosis (11.9% vs 28.4%; P=.02), and lower rates of being admitted through neurology department (2.3% vs 13.4%; P=.04). The Ridge model achieved the highest area under the receiver operating characteristic curve (0.885), specificity (0.797), positive predictive value (PPV; 0.24), and F1-score (0.369) in classifying patients who were at higher risk of diagnostic errors among hospitalized patients. CONCLUSIONS: Our findings demonstrate that natural language processing can be a potential solution to more effectively identifying and selecting potential diagnostic error cases for review and therefore reducing the case review burden.

Cannabidiol Inhibits the Proliferation and Invasiveness of Prostate Cancer Cells.

Prostate cancer is the fifth leading cause of cancer death in men, responsible for over 375,000 deaths in 2020. Novel therapeutic strategies are needed to improve outcomes. Cannabinoids, chemical components of the cannabis plant, are a possible solution. Preclinical evidence demonstrates that cannabinoids can modulate several cancer hallmarks of many tumor types. However, the therapeutic potential of cannabinoids in prostate cancer has not yet been fully explored. The aim of this study was to investigate the antiproliferative and anti-invasive properties of cannabidiol (CBD) in prostate cancer cells in vitro. CBD inhibited cell viability and proliferation, accompanied by reduced expression of key cell cycle proteins, specifically cyclin D3 and cyclin-dependent kinases CDK2, CDK4, and CDK1, and inhibition of AKT phosphorylation. The effects of CBD on cell viability were not blocked by cannabinoid receptor antagonists, a transient receptor potential vanilloid 1 (TRPV1) channel blocker, or an agonist of the G-protein-coupled receptor GPR55, suggesting that CBD acts independently of these targets in prostate cancer cells. Furthermore, CBD reduced the invasiveness of highly metastatic PC-3 cells and increased protein expression of E-cadherin. The ability of CBD to inhibit prostate cancer cell proliferation and invasiveness suggests that CBD may have potential as a future chemotherapeutic agent.

Analytical Validation of a Novel 6-Gene Signature for Prediction of Distant Recurrence in Estrogen Receptor-Positive, HER2-Negative, Early-Stage Breast Cancer.

BACKGROUND: OncoMasTR is a recently developed multigene prognostic test for early-stage breast cancer. The test has been developed in a kit-based format for decentralized deployment in molecular pathology laboratories. The analytical performance characteristics of the OncoMasTR test are described in this study. METHODS: Expression levels of 6 genes were measured by 1-step reverse transcription-quantitative PCR on RNA samples prepared from formalin-fixed, paraffin-embedded (FFPE) breast tumor specimens. Assay precision, reproducibility, input range, and interference were determined using FFPE-derived RNA samples representative of low and high prognostic risk scores. A pooled RNA sample derived from 6 FFPE breast tumor specimens was used to establish the linear range, limit of detection, and amplification efficiency of the individual gene expression assays. RESULTS: The overall precision of the OncoMasTR test was high with an SD of 0.16, which represents less than 2% of the 10-unit risk score range. Test results were reproducible across 4 testing sites, with correlation coefficients of 0.94 to 0.96 for the continuous risk score and concordance of 86% to 96% in low-/high-risk sample classification. Consistent risk scores were obtained across a > 100-fold RNA input range. Individual gene expression assays were linear up to quantification cycle values of 36.0 to 36.9, with amplification efficiencies of 80% to 102%. Test results were not influenced by agents used during RNA isolation, by low levels of copurified genomic DNA, or by moderate levels of copurified adjacent nontumor tissue. CONCLUSION: The OncoMasTR prognostic test displays robust analytical performance that is suitable for deployment by local pathology laboratories for decentralized use.

Pre-clinical and clinical studies on the role of RBM3 in muscle-invasive bladder cancer: longitudinal expression, transcriptome-level effects and modulation of chemosensitivity.

BACKGROUND: The response to neoadjuvant cisplatin-based chemotherapy (NAC) in muscle-invasive bladder cancer (MIBC) is impaired in up to 50% of patients due to chemoresistance, with no predictive biomarkers in clinical use. The proto-oncogene RNA-binding motif protein 3 (RBM3) has emerged as a putative modulator of chemotherapy response in several solid tumours but has a hitherto unrecognized role in MIBC. METHODS: RBM3 protein expression level in tumour cells was assessed via immunohistochemistry in paired transurethral resection of the bladder (TURB) specimens, cystectomy specimens and lymph node metastases from a consecutive cohort of 145 patients, 65 of whom were treated with NAC. Kaplan-Meier and Cox regression analyses were applied to estimate the impact of RBM3 expression on time to recurrence (TTR), cancer-specific survival (CSS), and overall survival (OS) in strata according to NAC treatment. The effect of siRNA-mediated silencing of RBM3 on chemosensitivity was examined in RT4 and T24 human bladder carcinoma cells in vitro. Cellular functions of RBM3 were assessed using RNA-sequencing and gene ontology analysis, followed by investigation of cell cycle distribution using flow cytometry. RESULTS: RBM3 protein expression was significantly higher in TURB compared to cystectomy specimens but showed consistency between primary tumours and lymph node metastases. Patients with high-tumour specific RBM3 expression treated with NAC had a significantly reduced risk of recurrence and a prolonged CSS and OS compared to NAC-untreated patients. In high-grade T24 carcinoma cells, which expressed higher RBM3 mRNA levels compared to RT4 cells, RBM3 silencing conferred a decreased sensitivity to cisplatin and gemcitabine. Transcriptomic analysis revealed potential involvement of RBM3 in facilitating cell cycle progression, in particular G1/S-phase transition, and initiation of DNA replication. Furthermore, siRBM3-transfected T24 cells displayed an accumulation of cells residing in the G1-phase as well as altered levels of recognised regulators of G1-phase progression, including Cyclin D1/CDK4 and CDK2. CONCLUSIONS: The presented data highlight the potential value of RBM3 as a predictive biomarker of chemotherapy response in MIBC, which could, if prospectively validated, improve treatment stratification of patients with this aggressive disease.

Radical Perfluoroalkylation of Arenes via Carbanion Intermediates.

The use of sodium dithionite with perfluoroalkyl iodides under basic conditions facilitates the direct perfluoroalkylation of arenes with pendant benzylic electron-withdrawing groups. This occurs via attack of the arene on the electrophilic perfluoroalkyl radical, through the donation of electron density from a benzylic anion. The substrate scope was expanded beyond benzylic nitriles with cyclic substrates bearing electron-withdrawing groups at the benzylic position-enforcing donation of electron density to the aromatic ring and enabling attack on the perfluoroalkyl radical.

Feature fusion of Raman chemical imaging and digital histopathology using machine learning for prostate cancer detection.

The diagnosis of prostate cancer is challenging due to the heterogeneity of its presentations, leading to the over diagnosis and treatment of non-clinically important disease. Accurate diagnosis can directly benefit a patient's quality of life and prognosis. Towards addressing this issue, we present a learning model for the automatic identification of prostate cancer. While many prostate cancer studies have adopted Raman spectroscopy approaches, none have utilised the combination of Raman Chemical Imaging (RCI) and other imaging modalities. This study uses multimodal images formed from stained Digital Histopathology (DP) and unstained RCI. The approach was developed and tested on a set of 178 clinical samples from 32 patients, containing a range of non-cancerous, Gleason grade 3 (G3) and grade 4 (G4) tissue microarray samples. For each histological sample, there is a pathologist labelled DP-RCI image pair. The hypothesis tested was whether multimodal image models can outperform single modality baseline models in terms of diagnostic accuracy. Binary non-cancer/cancer models and the more challenging G3/G4 differentiation were investigated. Regarding G3/G4 classification, the multimodal approach achieved a sensitivity of 73.8% and specificity of 88.1% while the baseline DP model showed a sensitivity and specificity of 54.1% and 84.7% respectively. The multimodal approach demonstrated a statistically significant 12.7% AUC advantage over the baseline with a value of 85.8% compared to 73.1%, also outperforming models based solely on RCI and mean and median Raman spectra. Feature fusion of DP and RCI does not improve the more trivial task of tumour identification but does deliver an observed advantage in G3/G4 discrimination. Building on these promising findings, future work could include the acquisition of larger datasets for enhanced model generalization.

Epigenetics of malignant melanoma.

Patients with malignant melanoma generally have a good prognosis if the disease presents prior to metastasis. Due to progress with targeted and immunotherapies, the median survival of metastatic melanoma patients is now over 2 years. The disease is characterised by one of the highest somatic mutation rates observed amongst cancer types, with a specific mutational signature based on UV radiation damage evident. Highly prevalent mutations, such as the BRAFV600E, in the MAPK cascade indicate truncal involvement of this pathway in the earliest stage of melanoma. The molecular sub-classification of melanoma based on genetic alterations is now well established. This has paved the way for researchers in epigenetics to investigate specific pathways of known importance, and the involvement of the diverse range of epigenetic mechanisms. Herein, we review the literature to highlight that epigenetic alterations are integrally involved in this malignancy. We focus on the most current evidence around the epigenetic mechanisms: DNA methylation and demethylation including 5-hydroxy-methylcytosine; histone post-translational modifications including variant histones; chromatin remodelling complexes and in particular the polycomb-repressive complex PRC2 and its histone methyltransferase subunit EZH2; and non-coding RNAs. Each mechanism is described generally, studies involving melanoma are assessed and clinical relevance is highlighted where possible.

The Emerging Role of Non-traditional Ubiquitination in Oncogenic Pathways.

The addition of ubiquitin to a target protein has long been implicated in the process of degradation and is the primary mediator of protein turnover in the cell. Recently, however, many non-proteolytic functions of ubiquitination have emerged as key regulators of cellular homeostasis. In this review, we will describe the various non-traditional functions of ubiquitination, with particular focus on how they can be used as signaling entities in cancer formation and progression. Elaboration of this topic can lead to a better understanding of oncogenic mechanisms, as well as the discovery of novel druggable proteins within the ubiquitin pathway.

Role of serum response factor expression in prostate cancer biochemical recurrence.

BACKGROUND: Up to a third of prostate cancer patients fail curative treatment strategies such as surgery and radiation therapy in the form of biochemical recurrence (BCR) which can be predictive of poor outcome. Recent clinical trials have shown that men experiencing BCR might benefit from earlier intervention post-radical prostatectomy (RP). Therefore, there is an urgent need to identify earlier prognostic biomarkers which will guide clinicians in making accurate diagnosis and timely decisions on the next appropriate treatment. The objective of this study was to evaluate Serum Response Factor (SRF) protein expression following RP and to investigate its association with BCR. MATERIALS AND METHODS: SRF nuclear expression was evaluated by immunohistochemistry (IHC) in TMAs across three international radical prostatectomy cohorts for a total of 615 patients. Log-rank test and Kaplan-Meier analyses were used for BCR comparisons. Stepwise backwards elimination proportional hazard regression analysis was used to explore the significance of SRF in predicting BCR in the context of other clinical pathological variables. Area under the curve (AUC) values were generated by simulating repeated random sub-samples. RESULTS: Analysis of the immunohistochemical staining of benign versus cancer cores showed higher expression of nuclear SRF protein expression in cancer cores compared with benign for all the three TMAs analysed (P < 0.001, n = 615). Kaplan-Meier curves of the three TMAs combined showed that patients with higher SRF nuclear expression had a shorter time to BCR compared with patients with lower SRF expression (P < 0.001, n = 215). Together with pathological T stage T3, SRF was identified as a predictor of BCR using stepwise backwards elimination proportional hazard regression analysis (P = 0.0521). Moreover ROC curves and AUC values showed that SRF was better than T stage in predicting BCR at year 3 and 5 following radical prostatectomy, the combination of SRF and T stage had a higher AUC value than the two taken separately. CONCLUSIONS: SRF assessment by IHC following RP could be useful in guiding clinicians to better identify patients for appropriate follow-up and timely treatment.

Development of acquired resistance to lapatinib may sensitise HER2-positive breast cancer cells to apoptosis induction by obatoclax and TRAIL.

BACKGROUND: Lapatinib has clinical efficacy in the treatment of trastuzumab-refractory HER2-positive breast cancer. However, a significant proportion of patients develop progressive disease due to acquired resistance to the drug. Induction of apoptotic cell death is a key mechanism of action of lapatinib in HER2-positive breast cancer cells. METHODS: We examined alterations in regulation of the intrinsic and extrinsic apoptosis pathways in cell line models of acquired lapatinib resistance both in vitro and in patient samples from the NCT01485926 clinical trial, and investigated potential strategies to exploit alterations in apoptosis signalling to overcome lapatinib resistance in HER2-positive breast cancer. RESULTS: In this study, we examined two cell lines models of acquired lapatinib resistance (SKBR3-L and HCC1954-L) and showed that lapatinib does not induce apoptosis in these cells. We identified alterations in members of the BCL-2 family of proteins, in particular MCL-1 and BAX, which may play a role in resistance to lapatinib. We tested the therapeutic inhibitor obatoclax, which targets MCL-1. Both SKBR3-L and HCC1954-L cells showed greater sensitivity to obatoclax-induced apoptosis than parental cells. Interestingly, we also found that the development of acquired resistance to lapatinib resulted in acquired sensitivity to TRAIL in SKBR3-L cells. Sensitivity to TRAIL in the SKBR3-L cells was associated with reduced phosphorylation of AKT, increased expression of FOXO3a and decreased expression of c-FLIP. In SKBR3-L cells, TRAIL treatment caused activation of caspase 8, caspase 9 and caspase 3/7. In a second resistant model, HCC1954-L cells, p-AKT levels were not decreased and these cells did not show enhanced sensitivity to TRAIL. Furthermore, combining obatoclax with TRAIL improved response in SKBR3-L cells but not in HCC1954-L cells. CONCLUSIONS: Our findings highlight the possibility of targeting altered apoptotic signalling to overcome acquired lapatinib resistance, and identify potential novel treatment strategies, with potential biomarkers, for HER2-positive breast cancer that is resistant to HER2 targeted therapies.

Impact of somatic PI3K pathway and ERBB family mutations on pathological complete response (pCR) in HER2-positive breast cancer patients who received neoadjuvant HER2-targeted therapies.

BACKGROUND: The Cancer Genome Atlas analysis revealed that somatic EGFR, receptor tyrosine-protein kinase erbB-2 (ERBB2), Erb-B2 receptor tyrosine kinase 3 (ERBB3) and Erb-B2 receptor tyrosine kinase 4 (ERBB4) gene mutations (ERBB family mutations) occur alone or co-occur with somatic mutations in the gene encoding the phosphatidylinositol 3-kinase (PI3K) catalytic subunit (PIK3CA) in 19% of human epidermal growth factor receptor 2 (HER2)-positive breast cancers. Because ERBB family mutations can activate the PI3K/AKT pathway and likely have similar canonical signalling effects to PI3K pathway mutations, we investigated their combined impact on response to neoadjuvant HER2-targeted therapies. METHODS: Baseline tumour biopsies were available from 74 patients with HER2-positive breast cancer who were enrolled in the phase II TCHL neoadjuvant study (ICORG 10-05) assessing TCH (docetaxel, carboplatin, trastuzumab) (n = 38) versus TCL (docetaxel, carboplatin, lapatinib) (n = 10) versus TCHL (docetaxel, carboplatin, trastuzumab, lapatinib) (n = 40), each for six cycles. Activating mutations in PIK3CA and ERBB family genes were identified using mass spectrometry-based genotyping. Phosphatase and tensin homolog (PTEN) expression was assessed by immunohistochemistry. RESULTS: PIK3CA and/or ERBB family mutations were detected in 23 (31.1%) tumour samples tested, whereas PTEN expression was low in 31.1% of cases tested. Mutation frequency was similar in each treatment arm (31.3% in TCH arm, 30% in TCL arm and 31.3% in TCHL arm) and was not influenced by oestrogen receptor (ER) status (27.6% in ER-negative patients, 33.3% in ER-positive patients) or progesterone receptor (PR) status (32.6% in PR-negative patients, 29% in PR-positive patients). There was no significant difference in pathological complete response (pCR) rates between 47 patients with wild-type (WT) tumours and 22 patients whose tumours carried mutations (in either PIK3CA or ERBB family genes) (42.5% vs. 54.5%; p = 0.439). Similarly, there was no significant difference in pCR rates between patients with PIK3CA/ERBB family mutated/PTEN-low (i.e., PI3K-activated) tumours and patients without PI3K activation (50% vs. 44%; p = 0.769). However, in the TCHL (but not the TCH) group, the pCR rate was higher for 9 patients with PIK3CA/ERBB family mutated tumours than for 20 patients with PIK3CA/ERBB family WT tumours (77.8% vs. 35%; p = 0.05). CONCLUSIONS: Our results indicate that patients who receive neoadjuvant TCHL and have PIK3CA/ERBB family mutated tumours may be more likely to have a pCR than patients with WT tumours. TRIAL REGISTRATION: ClinicalTrials.gov, NCT01485926 . Registered on 2 December 2011.

Comprehensive DNA methylation study identifies novel progression-related and prognostic markers for cutaneous melanoma.

BACKGROUND: Cutaneous melanoma is the deadliest skin cancer, with an increasing incidence and mortality rate. Currently, staging of patients with primary melanoma is performed using histological biomarkers such as tumor thickness and ulceration. As disruption of the epigenomic landscape is recognized as a widespread feature inherent in tumor development and progression, we aimed to identify novel biomarkers providing additional clinical information over current factors using unbiased genome-wide DNA methylation analyses. METHODS: We performed a comprehensive DNA methylation analysis during all progression stages of melanoma using Infinium HumanMethylation450 BeadChips on a discovery cohort of benign nevi (n = 14) and malignant melanoma from both primary (n = 33) and metastatic (n = 28) sites, integrating the DNA methylome with gene expression data. We validated the discovered biomarkers in three independent validation cohorts by pyrosequencing and immunohistochemistry. RESULTS: We identified and validated biomarkers for, and pathways involved in, melanoma development (e.g., HOXA9 DNA methylation) and tumor progression (e.g., TBC1D16 DNA methylation). In addition, we determined a prognostic signature with potential clinical applicability and validated PON3 DNA methylation and OVOL1 protein expression as biomarkers with prognostic information independent of tumor thickness and ulceration. CONCLUSIONS: Our data underscores the importance of epigenomic regulation in triggering metastatic dissemination through the inactivation of central cancer-related pathways. Inactivation of cell-adhesion and differentiation unleashes dissemination, and subsequent activation of inflammatory and immune system programs impairs anti-tumoral defense pathways. Moreover, we identify several markers of tumor development and progression previously unrelated to melanoma, and determined a prognostic signature with potential clinical utility.

De novo post-diagnosis statin use, breast cancer-specific and overall mortality in women with stage I-III breast cancer.

BACKGROUND: Prior evidence suggests a role for statins in the management of cancer. However, the benefit of statin use in the adjuvant setting remains uncertain. This study investigates associations between statin use initiated after a breast cancer diagnosis and mortality. METHODS: Women with stage I-III breast cancer were identified from the National Cancer Registry of Ireland (N=4243). Post-diagnostic statin initiators were identified from pharmacy claims data (N=837). Multivariate models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for associations between de novo statin use and mortality. RESULTS: The median duration of statin use was 6.7 years. No association was found between post-diagnostic statin use and breast cancer-specific (HR 0.88, 95% CI 0.66, 1.17) or all-cause mortality (HR 1.00, 95% CI 0.82, 1.21). CONCLUSIONS: The results from our study suggest that initiating statin use after a diagnosis of stage I-III breast cancer is not associated with a reduction in breast cancer-specific mortality.

Functionalization of emissive conjugated polymer nanoparticles by coprecipitation: consequences for particle photophysics and colloidal properties.

The functionalization of polyfluorene (PFO) nanoparticles by coprecipitation of the conjugated polymer with an amphiphilic comb polymer, consisting of a hydrophobic polystyrene backbone with hydrophilic, carboxylic acid-terminated polyethylene oxide side-chains (PS-PEG-COOH), is investigated. The comb polymer affects the properties of the formed hybrid nanoparticles. Non-functionalized particles are typically larger (28 nm) than functionalized ones (20 nm); peak molar extinction coefficients are found to differ in a similar trend. Zeta potentials are negative, consistent with negative surface charge on PFO particles due to chemical defect formation, with additional charge on functionalized particles due to the pendant carboxylic acid groups. Emission quantum yields of functionalized particles are typically larger, consistent with lower efficiency of energy transfer to quenchers in smaller particles and weaker PFO interchain interactions due to chain dilution. The trend in per-particle fluorescence brightness values, as confirmed by single particle fluorescence imaging, reflects the nanoparticle extinction coefficients. Photostability studies on aqueous dispersions of hybrid particles indicate mild photobrightening under continuous illumination while PFO particles exhibit slow exponential emission decay. Functionalized particles are also resistant to aggregation during exposure to adenocarcinoma cells. Generally, the hybrid particles exhibit more favorable time-, pH- and medium-dependent stabilities, likely due to steric and electrostatic stabilization by PEG-carboxylic acid functionalities. Overall, the functionalized particles exhibit attractive properties: Reasonably small size, tight size distribution, high absorption cross section, radiative rate and emission quantum yield, excellent brightness and photostability, and good colloidal stability.

Epidemiologic design and analysis for proteomic studies: a primer on -omic technologies.

Proteome analysis is increasingly being used in investigations elucidating the molecular basis of disease, identifying diagnostic and prognostic markers, and ultimately improving patient care. We appraised the current status of proteomic investigations using human samples, including the state of the art in proteomic technologies, from sample preparation to data evaluation approaches, as well as key epidemiologic, statistical, and translational issues. We systematically reviewed the most highly cited clinical proteomic studies published between January 2009 and March 2014 that included a minimum of 100 samples, as well as strategies that have been successfully implemented to enhance the translational relevance of proteomic investigations. Limited comparability between studies and lack of specification of biomarker context of use are frequently observed. Nevertheless, there are initial examples of successful biomarker discovery in cross-sectional studies followed by validation in high-risk longitudinal cohorts. Translational potential is currently hindered, as limitations in proteomic investigations are not accounted for. Interdisciplinary communication between proteomics experts, basic researchers, epidemiologists, and clinicians, an orchestrated assimilation of required resources, and a more systematic translational outlook for accumulation of evidence may augment the public health impact of proteomic investigations.

Relationship between serum response factor and androgen receptor in prostate cancer.

BACKGROUND: Serum response factor (SRF) is an important transcription factor in castrate-resistant prostate cancer (CRPC). Since CRPC is associated with androgen receptor (AR) hypersensitivity, we investigated the relationship between SRF and AR. MATERIALS AND METHODS: Transcriptional activity was assessed by luciferase assay. Cell proliferation was measured by MTT and flow cytometry. Protein expression in patients was assessed by immunohistochemistry. RESULTS: To investigate AR involvement in SRF response to androgen, AR expression was down-regulated using siRNA. This resulted in the abrogation of SRF induction post-DHT. Moreover, DHT stimulation failed to induce SRF transcriptional activity in AR-negative PC346 DCC cells, which was only restored following AR over-expression. Next, SRF expression was down-regulated by siRNA, resulting in AR increased transcriptional activity in castrate-resistant LNCaP Abl cells but not in the parental LNCaP. This negative feedback loop in the resistant cells was confirmed by immunohistochemistry which showed a negative correlation between AR and SRF expression in CRPC bone metastases and a positive correlation in androgen-naïve prostatectomies. Cell proliferation was next assessed following SRF inhibition, demonstrating that SRF inhibition is more effective than AR inhibition in castrate-resistant cells. CONCLUSION: Our data support SRF as a promising therapeutic target in combination with current treatments.

Tumour islet Foxp3+ T-cell infiltration predicts poor outcome in nonsmall cell lung cancer.

The impact of host immunity on outcome in nonsmall cell lung cancer (NSCLC) is controversial. We examined the relationship between lymphoid infiltration patterns in NSCLC and prognosis.Tumour- and stroma-infiltrating CD3(+), CD8(+) and forkhead box P3 (Foxp3)(+) T-lymphocytes were identified using immunohistochemistry and a novel image analysis algorithm to assess total, cytotoxic and regulatory T-lymphocyte counts, respectively, in 196 NSCLC cases. The median cell count was selected as a cut-point to define patient subgroups and the ratio of the corresponding tumour islet:stroma (TI/S) counts was determined.There was a positive association between overall survival and increased CD8(+) TI/S ratio (hazard ratio (HR) for death 0.44, p<0.001) but an inverse relationship between Foxp3(+) TI/S ratio and overall survival (HR 4.86, p<0.001). Patients with high CD8(+) islet (HR 0.48, p<0.001) and Foxp3(+) stromal (HR 0.23, p<0.001) counts had better survival, whereas high CD3(+) and CD8(+) stromal counts and high Foxp3(+) islet infiltration conferred a worse survival (HR 1.55, 2.19 and 3.14, respectively). By multivariate analysis, a high CD8(+) TI/S ratio conferred an improved survival (HR 0.48, p=0.002) but a high Foxp3(+) TI/S ratio was associated with worse survival (HR 3.91, p<0.001).Microlocalisation of infiltrating T-lymphocytes is a powerful predictor of outcome in resected NSCLC.

The Role of Exosomes in Breast Cancer.

BACKGROUND: Although it has been long realized that eukaryotic cells release complex vesicular structures into their environment, only in recent years has it been established that these entities are not merely junk or debris, but that they are tailor-made specialized minimaps of their cell of origin and of both physiological and pathological relevance. These exosomes and microvesicles (ectosomes), collectively termed extracellular vesicles (EVs), are often defined and subgrouped first and foremost according to size and proposed origin (exosomes approximately 30-120 nm, endosomal origin; microvesicles 120-1000 nm, from the cell membrane). There is growing interest in elucidating the relevance and roles of EVs in cancer. CONTENT: Much of the pioneering work on EVs in cancer has focused on breast cancer, possibly because breast cancer is a leading cause of cancer-related deaths worldwide. This review provides an in-depth summary of such studies, supporting key roles for exosomes and other EVs in breast cancer cell invasion and metastasis, stem cell stimulation, apoptosis, immune system modulation, and anti-cancer drug resistance. Exosomes as diagnostic, prognostic, and/or predictive biomarkers and their potential use in the development of therapeutics are discussed. SUMMARY: Although not fully elucidated, the involvement of exosomes in breast cancer development, progression, and resistance is becoming increasingly apparent from preclinical and clinical studies, with mounting interest in the potential exploitation of these vesicles for breast cancer biomarkers, as drug delivery systems, and in the development of future novel breast cancer therapies.