Multiplex protein analysis and ensemble machine learning methods of fine needle aspirates from prostate cancer patients reveal potential diagnostic signatures associated with tumour grade.

BACKGROUND: Improved molecular diagnosis is needed in prostate cancer (PC). Fine needle aspiration (FNA) is a minimally invasive biopsy technique, less traumatic compared to core needle biopsy, and could be useful for diagnosis of PC. Molecular biomarkers (BMs) in FNA-samples can be assessed for prediction, eg of immunotherapy efficacy before treatment as well as at treatment decision time points during disease progression. METHODS: In the present pilot study, the expression levels of 151 BM proteins were analysed by proximity extension assay in FNA-samples from 16 patients, including benign prostate lesions (n = 3) and cancers (n = 13). An ensemble data analysis strategy was applied using several machine learning models. RESULTS: Twelve potentially predictive BM proteins correlating with International Society of Urological Pathology grade groups were identified, among them vimentin, tissue factor pathway inhibitor 2, and integrin beta-5. The validity of the results was supported by network analysis that showed functional associations between most of the identified putative BMs. We also showed that multiple immune checkpoint targets can be assessed (eg PD-L1, CD137, and Galectin-9), which may support the selection of immunotherapy in advanced PC. Results are promising but need further validation in a larger cohort. CONCLUSIONS: Our pilot study represents a "proof of concept" and shows that multiplex profiling of potential diagnostic and predictive BM proteins is feasible on tumour material obtained by FNA sampling of prostate cancer. Moreover, our results demonstrate that an ensemble data analysis strategy may facilitate the identification of BM signatures in pilot studies when the patient cohort is limited.

Fast, streamlined fluorescence nanoscopy resolves rearrangements of SNARE and cargo proteins in platelets co-incubated with cancer cells.

BACKGROUND: Increasing evidence suggests that platelets play a central role in cancer progression, with altered storage and selective release from platelets of specific tumor-promoting proteins as a major mechanism. Fluorescence-based super-resolution microscopy (SRM) can resolve nanoscale spatial distribution patterns of such proteins, and how they are altered in platelets upon different activations. Analysing such alterations by SRM thus represents a promising, minimally invasive strategy for platelet-based diagnosis and monitoring of cancer progression. However, broader applicability beyond specialized research labs will require objective, more automated imaging procedures. Moreover, for statistically significant analyses many SRM platelet images are needed, of several different platelet proteins. Such proteins, showing alterations in their distributions upon cancer progression additionally need to be identified. RESULTS: A fast, streamlined and objective procedure for SRM platelet image acquisition, analysis and classification was developed to overcome these limitations. By stimulated emission depletion SRM we imaged nanoscale patterns of six different platelet proteins; four different SNAREs (soluble N-ethylmaleimide factor attachment protein receptors) mediating protein secretion by membrane fusion of storage granules, and two angiogenesis regulating proteins, representing cargo proteins within these granules coupled to tumor progression. By a streamlined procedure, we recorded about 100 SRM images of platelets, for each of these six proteins, and for five different categories of platelets; incubated with cancer cells (MCF-7, MDA-MB-231, EFO-21), non-cancer cells (MCF-10A), or no cells at all. From these images, structural similarity and protein cluster parameters were determined, and probability functions of these parameters were generated for the different platelet categories. By comparing these probability functions between the categories, we could identify nanoscale alterations in the protein distributions, allowing us to classify the platelets into their correct categories, if they were co-incubated with cancer cells, non-cancer cells, or no cells at all. CONCLUSIONS: The fast, streamlined and objective acquisition and analysis procedure established in this work confirms the role of SNAREs and angiogenesis-regulating proteins in platelet-mediated cancer progression, provides additional fundamental knowledge on the interplay between tumor cells and platelets, and represent an important step towards using tumor-platelet interactions and redistribution of nanoscale protein patterns in platelets as a basis for cancer diagnostics.

High Levels of Chromosomal Copy Number Alterations and TP53 Mutations Correlate with Poor Outcome in Younger Breast Cancer Patients.

Prognosis in young patients with breast cancer is generally poor, yet considerable differences in clinical outcomes between individual patients exist. To understand the genetic basis of the disparate clinical courses, tumors were collected from 34 younger women, 17 with good and 17 with poor outcomes, as determined by disease-specific survival during a follow-up period of 17 years. The clinicopathologic parameters of the tumors were complemented with DNA image cytometry profiles, enumeration of copy numbers of eight breast cancer genes by multicolor fluorescence in situ hybridization, and targeted sequence analysis of 563 cancer genes. Both groups included diploid and aneuploid tumors. The degree of intratumor heterogeneity was significantly higher in aneuploid versus diploid cases, and so were gains of the oncogenes MYC and ZNF217. Significantly more copy number alterations were observed in the group with poor outcome. Almost all tumors in the group with long survival were classified as luminal A, whereas triple-negative tumors predominantly occurred in the short survival group. Mutations in PIK3CA were more common in the group with good outcome, whereas TP53 mutations were more frequent in patients with poor outcomes. This study shows that TP53 mutations and the extent of genomic imbalances are associated with poor outcome in younger breast cancer patients and thus emphasize the central role of genomic instability vis-a-vis tumor aggressiveness.

Protein levels of clusterin and glutathione synthetase in platelets allow for early detection of colorectal cancer.

Colorectal cancer (CRC) is one of the most frequent malignancies in the Western world. Early tumor detection and intervention are important determinants on CRC patient survival. During early tumor proliferation, dissemination and angiogenesis, platelets store and segregate proteins actively and selectively. Hence, the platelet proteome is a potential source of biomarkers denoting early malignancy. By comparing protein profiles of platelets between healthy volunteers (n = 12) and patients with early- (n = 7) and late-stage (n = 5) CRCs using multiplex fluorescence two-dimensional gel electrophoresis (2D-DIGE), we aimed at identifying differentially regulated proteins within platelets. By inter-group comparisons, 94 differentially expressed protein spots were detected (p < 0.05) between healthy controls and patients with early- and late-stage CRCs and revealed distinct separations between all three groups in principal component analyses. 54 proteins of interest were identified by mass spectrometry and resulted in high-ranked Ingenuity Pathway Analysis networks associated with Cellular function and maintenance, Cellular assembly and organization, Developmental disorder and Organismal injury and abnormalities (p < 0.0001 to p = 0.0495). Target proteins were validated by multiplex fluorescence-based Western blot analyses using an additional, independent cohort of platelet protein samples [healthy controls (n = 15), early-stage CRCs (n = 15), late-stage CRCs (n = 15)]. Two proteins-clusterin and glutathione synthetase (GSH-S)-featured high impact and were subsequently validated in this independent clinical cohort distinguishing healthy controls from patients with early- and late-stage CRCs. Thus, the potential of clusterin and GSH-S as platelet biomarkers for early detection of CRC could improve existing screening modalities in clinical application and should be confirmed in a prospective multicenter trial.

Aneuploidy, TP53 mutation, and amplification of MYC correlate with increased intratumor heterogeneity and poor prognosis of breast cancer patients.

The clinical course of breast cancer varies from one patient to another. Currently, the choice of therapy relies on clinical parameters and histological and molecular tumor features. Alas, these markers are informative in only a subset of patients. Therefore, additional predictors of disease outcome would be valuable for treatment stratification. Extensive studies showed that the degree of variation of the nuclear DNA content, i.e., aneuploidy, determines prognosis. Our aim was to further elucidate the molecular basis of aneuploidy. We analyzed five diploid and six aneuploid tumors with more than 20 years of follow-up. By performing FISH with a multiplexed panel of 10 probes to enumerate copy numbers in individual cells, and by sequencing 563 cancer-related genes, we analyzed how aneuploidy is linked to intratumor heterogeneity. In our cohort, none of the patients with diploid tumors died of breast cancer during follow-up in contrast to four of six patients with aneuploid tumors (mean survival 86.4 months). The FISH analysis showed markedly increased genomic instability and intratumor heterogeneity in aneuploid tumors. MYC gain was observed in only 20% of the diploid cancers, while all aneuploid cases showed a gain. The mutation burden was similar in diploid and aneuploid tumors, however, TP53 mutations were not observed in diploid tumors, but in all aneuploid tumors in our collective. We conclude that quantitative measurements of intratumor heterogeneity by multiplex FISH, detection of MYC amplification and TP53 mutation could augment prognostication in breast cancer patients.

Phylogenetic analysis of multiple FISH markers in oral tongue squamous cell carcinoma suggests that a diverse distribution of copy number changes is associated with poor prognosis.

Oral tongue squamous cell carcinoma (OTSCC) is associated with poor prognosis. To improve prognostication, we analyzed four gene probes (TERC, CCND1, EGFR and TP53) and the centromere probe CEP4 as a marker of chromosomal instability, using fluorescence in situ hybridization (FISH) in single cells from the tumors of sixty-five OTSCC patients (Stage I, n = 15; Stage II, n = 30; Stage III, n = 7; Stage IV, n = 13). Unsupervised hierarchical clustering of the FISH data distinguished three clusters related to smoking status. Copy number increases of all five markers were found to be correlated to non-smoking habits, while smokers in this cohort had low-level copy number gains. Using the phylogenetic modeling software FISHtrees, we constructed models of tumor progression for each patient based on the four gene probes. Then, we derived test statistics on the models that are significant predictors of disease-free and overall survival, independent of tumor stage and smoking status in multivariate analysis. The patients whose tumors were modeled as progressing by a more diverse distribution of copy number changes across the four genes have poorer prognosis. This is consistent with the view that multiple genetic pathways need to become deregulated in order for cancer to progress.

Genetic Instability and Disease Prognostication.

Genetic instability is a striking feature of human cancers, with an impact on the genesis, progression and prognosis. The clinical importance of genomic instability and aneuploidy is underscored by its association with poor patient outcome in multiple cancer types, including breast and colon cancer. Interestingly, there is growing evidence that prognostic gene expression signatures simply reflect the degree of genomic instability. Additionally, also the proteome is affected by aneuploidy and has therefore become a powerful tool to screen for new targets for therapy, diagnosis and prognostication. In this context, the chapter presents the impact of genomic instability on disease prognostication occurring in human cancers.

A standardized method for quantifying proliferation by Ki-67 and cyclin A immunohistochemistry in breast cancer.

Immunohistochemical analysis of proliferation markers such as Ki-67 and cyclin A is widely used in clinical evaluation as a prognostic factor in breast cancer. The proliferation status of tumors is guiding the decision of whether or not a patient should be treated with chemotherapy because low-proliferative tumors are less sensitive by such treatment. However, the lack of optimal cutoff points and selection of tumor areas hamper its use in clinical practice. This study was performed to compare the Ki-67 and cyclin A expression counted in hot-spot vs average counting based on 5 to 14 random tumor areas in 613 breast carcinomas. We correlated the findings with 10-year follow-up in order to standardize the evaluation of proliferation markers in clinical practice. A significant correlation was found between the percentage of positive cells estimated by Ki-67 and cyclin A both by hot-spot and by average counting. Both methods showed that high expression of Ki-67 and cyclin A is associated with more adverse tumor stage. The cutoff value for Ki-67 for distant metastases was set to 22% and to 15%, using hot-spot and average counting, respectively. For cyclin A, the values were set to 14% and 8% using the respective methods. Survival curves revealed that patients with a high hot-spot proliferation index had a significantly greater risk of shorter tumor-free survival. Our findings suggest that the determination of proliferation markers in breast cancer should be standardized to hot-spot counting and that specific cutoff values for proliferation could be useful as prognostic markers in clinical practice. Moreover, we suggest that expression levels of cyclin A could be used as a complementary marker to estimate the proliferation status in tumors, especially those with "borderline" expression levels of Ki-67, in order to more accurately estimate the proliferations status of the tumors.

Anticoagulant medication at time of needle biopsy for breast cancer in relation to risk of lymph node metastasis.

Anticoagulant treatment might enhance the natural defense against tumor cell dissemination caused by diagnostic needle biopsy by counteracting thrombocyte coating of such cells. To clarify whether women using anticoagulant treatment at the time of biopsy have a lower occurrence of lymph node metastasis, we conducted a nationwide Swedish cohort study of 26,528 female incident breast cancer patients in 2006-2011. Point risk ratio (RR) of risk of lymph node metastasis among users of anticoagulant treatment adjusted for age, T-stage, socioeconomic factors, and concomitant medication was RR = 0.94, (95% CI: 0.87-1.03), and lower in younger women (RR = 0.80, 95% CI 0.50-1.29). Although nonsignificant, these associations may underestimate a true negative association since women using anticoagulant treatment are likely to have more concomitant diseases, lead an unhealthier lifestyle, and have lower participation in mammography screening. These findings provide some support for the hypothesis that anticoagulant medications might counteract breast cancer spread caused by needle biopsy.

Minimally invasive biopsy-based diagnostics in support of precision cancer medicine.

Precision cancer medicine (PCM) to support the treatment of solid tumors requires minimally invasive diagnostics. Here, we describe the development of fine-needle aspiration biopsy-based (FNA) molecular cytology which will be increasingly important in diagnostics and adaptive treatment. We provide support for FNA-based molecular cytology having a significant potential to replace core needle biopsy (CNB) as a patient-friendly potent technique for tumor sampling for various tumor types. This is not only because CNB is a more traumatic procedure and may be associated with more complications compared to FNA-based sampling, but also due to the recently developed molecular methods used with FNA. Recent studies show that image-guided FNA in combination with ultrasensitive molecular methods also offers opportunities for characterization of the tumor microenvironment which can aid therapeutic decisions. Here we provide arguments for an increased implementation of molecular FNA-based sampling as a patient-friendly diagnostic method, which may, due to its repeatability, facilitate regular sampling that is needed during different treatment lines, to provide tumor information, supporting treatment decisions, shortening lead times in healthcare, and benefit healthcare economics.

The impact of cysteine-rich intestinal protein 1 (CRIP1) in human breast cancer.

BACKGROUND: CRIP1 (cysteine-rich intestinal protein 1) has been found in several tumor types, its prognostic impact and its role in cellular processes, particularly in breast cancer, are still unclear. METHODS: To elucidate the prognostic impact of CRIP1, we analyzed tissues from 113 primary invasive ductal breast carcinomas using immunohistochemistry. For the functional characterization of CRIP1, its endogenous expression was transiently downregulated in T47D and BT474 breast cancer cells and the effects analyzed by immunoblotting, WST-1 proliferation assay and invasion assay. RESULTS: We found a significant correlation between CRIP1 and HER2 (human epidermal growth factor receptor 2) expression levels (p = 0.016) in tumor tissues. In Kaplan Meier analyses, CRIP1 expression was significantly associated with the distant metastases-free survival of patients, revealing a better prognosis for high CRIP1 expression (p = 0.039). Moreover, in multivariate survival analyses, the expression of CRIP1 was an independent negative prognostic factor, along with the positive prognosticators nodal status and tumor size (p = 0.029). CRIP1 knockdown in the T47D and BT474 breast cancer cell lines led to the increased phosphorylation of MAPK and Akt, to the reduced phosphorylation of cdc2, and to a significantly elevated cell proliferation in vitro (p < 0.001). These results indicate that reduced CRIP1 levels may increase cell proliferation and activate cell growth. In addition, CRIP1 knockdown increased cell invasion in vitro. CONCLUSIONS: Because the lack of CRIP1 expression in breast cancer tissue is significantly associated with a worse prognosis for patients and low endogenous CRIP1 levels in vitro increased the malignant potential of breast cancer cells, we hypothesize that CRIP1 may act as a tumor suppressor in proliferation and invasion processes. Therefore, CRIP1 may be an independent prognostic marker with significant predictive power for use in breast cancer therapy.

Prognostic significance of cell cycle- and invasion-related molecular markers and genomic instability in primary carcinoma of the vagina.

OBJECTIVE: This study aimed to analyze the prognostic value of DNA content and biological markers for cell cycle regulation and invasion in primary carcinoma of the vagina (PCV). MATERIAL AND METHODS: Seventy-two consecutive patients with PCV, categorized as short-term (≤ 2 years) and long-term (≥ 8 years) survivors, were evaluated for DNA content by image cytometry, and for expression of p53, p21, cyclin A, Ki67, E-cadherin, and laminin-5γ2 chain by immunohistochemistry. The relationship between these biological markers and histopathological and clinical parameters was assessed. RESULTS: All PCV showed aneuploid DNA content. Most of the PCV patients showed no overexpression of p53 and high expression of p21, cyclin A, and Ki67. Loss or underexpression of E-cadherin was found in 94% (68/72) of PCV patients, and all patients showed immunopositivity for the laminin-5γ2 chain. Tumors with a vaginal longitudinal location in the lower third or in the entire vagina more often had overexpression of p53, high expression of Ki67 (P = 0.044), and underexpression of E-cadherin (P = 0.038), than tumors confined only to the upper third. Overexpression of p53 was significantly associated with short-term survival in the univariate analysis, but not in the multivariate analysis adjusted for age at diagnosis and tumor size. CONCLUSIONS: The expression level of some markers was related to tumor location, which might be indicative of different genesis. Overexpression of p53 was associated with short-term survival, but the only independent predictors of survival were age at diagnosis and tumor size.

Protein profiling of genomic instability in endometrial cancer.

DNA aneuploidy has been identified as a prognostic factor in the majority of epithelial malignancies. We aimed at identifying ploidy-associated protein expression in endometrial cancer of different prognostic subgroups. Comparison of gel electrophoresis-based protein expression patterns between normal endometrium (n = 5), diploid (n = 7), and aneuploid (n = 7) endometrial carcinoma detected 121 ploidy-associated protein forms, 42 differentially expressed between normal endometrium and diploid endometrioid carcinomas, 37 between diploid and aneuploid endometrioid carcinomas, and 41 between diploid endometrioid and aneuploid uterine papillary serous cancer. Proteins were identified by mass spectrometry and evaluated by Ingenuity Pathway Analysis. Targets were confirmed by liquid chromatography/mass spectrometry. Mass spectrometry identified 41 distinct polypeptides and pathway analysis resulted in high-ranked networks with vimentin and Nf-κB as central nodes. These results identify ploidy-associated protein expression differences that overrule histopathology-associated expression differences and emphasize particular protein networks in genomic stability of endometrial cancer.

Protein expression changes in ovarian cancer during the transition from benign to malignant.

Epithelial ovarian carcinoma has in general a poor prognosis since the vast majority of tumors are genomically unstable and clinically highly aggressive. This results in rapid progression of malignancy potential while still asymptomatic and thus in late diagnosis. It is therefore of critical importance to develop methods to diagnose epithelial ovarian carcinoma at its earliest developmental stage, that is, to differentiate between benign tissue and its early malignant transformed counterparts. Here we present a shotgun quantitative proteomic screen of benign and malignant epithelial ovarian tumors using iTRAQ technology with LC-MALDI-TOF/TOF and LC-ESI-QTOF MS/MS. Pathway analysis of the shotgun data pointed to the PI3K/Akt signaling pathway as a significant discriminatory pathway. Selected candidate proteins from the shotgun screen were further confirmed in 51 individual tissue samples of normal, benign, borderline or malignant origin using LC-MRM analysis. The MRM profile demonstrated significant differences between the four groups separating the normal tissue samples from all tumor groups as well as perfectly separating the benign and malignant tumors with a ROC-area of 1. This work demonstrates the utility of using a shotgun approach to filter out a signature of a few proteins only that discriminates between the different sample groups.

HDAC2 and TXNL1 distinguish aneuploid from diploid colorectal cancers.

DNA aneuploidy has been identified as a prognostic factor for epithelial malignancies. Further understanding of the translation of DNA aneuploidy into protein expression will help to define novel biomarkers to improve therapies and prognosis. DNA ploidy was assessed by image cytometry. Comparison of gel-electrophoresis-based protein expression patterns of three diploid and four aneuploid colorectal cancer cell lines detected 64 ploidy-associated proteins. Proteins were identified by mass spectrometry and subjected to Ingenuity Pathway Analysis resulting in two overlapping high-ranked networks maintaining Cellular Assembly and Organization, Cell Cycle, and Cellular Growth and Proliferation. CAPZA1, TXNL1, and HDAC2 were significantly validated by Western blotting in cell lines and the latter two showed expression differences also in clinical samples using a tissue microarray of normal mucosa (n=19), diploid (n=31), and aneuploid (n=47) carcinomas. The results suggest that distinct protein expression patterns, affecting TXNL1 and HDAC2, distinguish aneuploid with poor prognosis from diploid colorectal cancers.

Chromosomal instability determines taxane response.

Microtubule-stabilizing (MTS) agents, such as taxanes, are important chemotherapeutics with a poorly understood mechanism of action. We identified a set of genes repressed in multiple cell lines in response to MTS agents and observed that these genes are overexpressed in tumors exhibiting chromosomal instability (CIN). Silencing 22/50 of these genes, many of which are involved in DNA repair, caused cancer cell death, suggesting that these genes are involved in the survival of aneuploid cells. Overexpression of these "CIN-survival" genes is associated with poor outcome in estrogen receptor-positive breast cancer and occurs frequently in basal-like and Her2-positive cases. In diploid cells, but not in chromosomally unstable cells, paclitaxel causes repression of CIN-survival genes, followed by cell death. In the OV01 ovarian cancer clinical trial, a high level of CIN was associated with taxane resistance but carboplatin sensitivity, indicating that CIN may determine MTS response in vivo. Thus, pretherapeutic assessment of CIN may optimize treatment stratification and clinical trial design using these agents.

Genomic instability influences the transcriptome and proteome in endometrial cancer subtypes.

BACKGROUND: In addition to clinical characteristics, DNA aneuploidy has been identified as a prognostic factor in epithelial malignancies in general and in endometrial cancers in particular. We mapped ploidy-associated chromosomal aberrations and identified corresponding gene and protein expression changes in endometrial cancers of different prognostic subgroups. METHODS: DNA image cytometry classified 25 endometrioid cancers to be either diploid (n = 16) or aneuploid (n = 9), and all uterine papillary serous cancers (UPSC) to be aneuploid (n = 8). All samples were subjected to comparative genomic hybridization and gene expression profiling. Identified genes were subjected to Ingenuity pathway analysis (IPA) and were correlated to protein expression changes. RESULTS: Comparative genomic hybridization revealed ploidy-associated specific, recurrent genomic imbalances. Gene expression analysis identified 54 genes between diploid and aneuploid endometrioid carcinomas, 39 genes between aneuploid endometrioid cancer and UPSC, and 76 genes between diploid endometrioid and aneuploid UPSC to be differentially expressed. Protein profiling identified AKR7A2 and ANXA2 to show translational alterations consistent with the transcriptional changes. The majority of differentially expressed genes and proteins belonged to identical molecular functions, foremost Cancer, Cell Death, and Cellular Assembly and Organization. CONCLUSIONS: We conclude that the grade of genomic instability rather than the histopathological subtype correlates with specific gene and protein expression changes. The identified genes and proteins might be useful as molecular targets for improved diagnostic and therapeutic intervention and merit prospective validation.

Genomic instability and oncogene amplifications in colorectal adenomas predict recurrence and synchronous carcinoma.

Individual colorectal adenomas have different propensities to progress to invasive disease. In this study, we explored whether these differences could be explained by gene copy number alterations. We evaluated 18 adenomas of patients without synchronous or subsequent carcinoma (6.5 years follow-up), 23 adenomas of carcinoma patients, and 6 related carcinomas. All samples were measured for their DNA ploidy status. Centromere probes for chromosomes 17 and 18, as well as gene-specific probes for SMAD7, EGFR, NCOA3, TP53, MYC, and RAB20 were assessed by multicolor fluorescence in situ hybridization. An increased genomic instability index of CEP17, SMAD7, and EGFR, as well as TP53 deletions and MYC amplifications defined adenomas of patients with synchronous carcinoma (P<0.05). Diploid NCOA3 signal counts were associated with longer adenoma recurrence-free surveillance (P=0.042). In addition, NCOA3, MYC, EGFR, and RAB20 amplifications, as well as TP53 deletions correlated with increased DNA stem line values and/or aneuploidy in adenomas (P<0.05). Furthermore, aberrations of NCOA3, MYC, and RAB20 were associated with histopathologically defined high-risk adenomas (P<0.05). RAB20 amplifications were also correlated with high-grade dysplastic adenomas (P=0.002). We conclude that genomic instability in colorectal adenomas is reflected by EGFR, MYC, NCOA3, and RAB20 amplifications that do correlate with histomorphological features and are indicative for adenoma recurrence and the presence of synchronous carcinomas.

PITX2 DNA-Methylation: Predictive versus Prognostic Value for Anthracycline-Based Chemotherapy in Triple-Negative Breast Cancer Patients.

BACKGROUND: PITX2 DNA methylation has been shown to predict outcomes in high-risk breast cancer patients after anthracycline-based chemotherapy. To determine its prognostic versus predictive value, the impact of PITX2 DNA methylation on outcomes was studied in an untreated cohort vs. an anthracycline-treated triple-negative breast cancer (TNBC) cohort. MATERIAL AND METHODS: The percent DNA methylation ratio (PMR) of paired-like homeodomain transcription factor 2 (PITX2) was determined by a validated methylation-specific real-time PCR test. Patient samples of routinely collected archived formalin-fixed paraffin-embedded (FFPE) tissue and clinical data from 144 TNBC patients of 2 independent cohorts (i.e., 66 untreated patients and 78 patients treated with anthracycline-based chemotherapy) were analyzed. RESULTS: The risk of 5- and 10-year overall survival (OS) increased continuously with rising PITX2 DNA methylation in the anthracycline-treated population, but it increased only slightly during 10-year follow-up time in the untreated patient population. PITX2 DNA methylation with a PMR cutoff of 2 did not show significance for poor vs. good outcomes (OS) in the untreated patient cohort (HR = 1.55; p = 0.259). In contrast, the PITX2 PMR cutoff of 2 identified patients with poor (PMR >2) vs. good (PMR ≤2) outcomes (OS) with statistical significance in the anthracycline-treated cohort (HR = 3.96; p = 0.011). The results in the subgroup of patients who did receive anthracyclines only (no taxanes) confirmed this finding (HR = 5.71; p = 0.014). CONCLUSION: In this hypothesis-generating study PITX2 DNA methylation demonstrated predominantly predictive value in anthracycline treatment in TNBC patients. The risk of poor outcome (OS) correlates with increasing PITX2 DNA methylation.

SATB1, genomic instability and Gleason grading constitute a novel risk score for prostate cancer.

Current prostate cancer risk classifications rely on clinicopathological parameters resulting in uncertainties for prognostication. To improve individual risk stratification, we examined the predictive value of selected proteins with respect to tumor heterogeneity and genomic instability. We assessed the degree of genomic instability in 50 radical prostatectomy specimens by DNA-Image-Cytometry and evaluated protein expression in related 199 tissue-microarray (TMA) cores. Immunohistochemical data of SATB1, SPIN1, TPM4, VIME and TBB5 were correlated with the degree of genomic instability, established clinical risk factors and overall survival. Genomic instability was associated with a GS ≥ 7 (p = 0.001) and worse overall survival (p = 0.008). A positive SATB1 expression was associated with a GS ≤ 6 (p = 0.040), genomic stability (p = 0.027), and was a predictor for increased overall survival (p = 0.023). High expression of SPIN1 was also associated with longer overall survival (p = 0.048) and lower preoperative PSA-values (p = 0.047). The combination of SATB1 expression, genomic instability, and GS lead to a novel Prostate Cancer Prediction Score (PCP-Score) which outperforms the current D'Amico et al. stratification for predicting overall survival. Low SATB1 expression, genomic instability and GS ≥ 7 were identified as markers for poor prognosis. Their combination overcomes current clinical risk stratification regimes.