Renal tumor segmentation, visualization, and segmentation confidence using ensembles of neural networks in patients undergoing surgical resection.

OBJECTIVES: To develop an automatic segmentation model for solid renal tumors on contrast-enhanced CTs and to visualize segmentation with associated confidence to promote clinical applicability. MATERIALS AND METHODS: The training dataset included solid renal tumor patients from two tertiary centers undergoing surgical resection and receiving CT in the corticomedullary or nephrogenic contrast media (CM) phase. Manual tumor segmentation was performed on all axial CT slices serving as reference standard for automatic segmentations. Independent testing was performed on the publicly available KiTS 2019 dataset. Ensembles of neural networks (ENN, DeepLabV3) were used for automatic renal tumor segmentation, and their performance was quantified with DICE score. ENN average foreground entropy measured segmentation confidence (binary: successful segmentation with DICE score > 0.8 versus inadequate segmentation ≤ 0.8). RESULTS: N = 639/n = 210 patients were included in the training and independent test dataset. Datasets were comparable regarding age and sex (p > 0.05), while renal tumors in the training dataset were larger and more frequently benign (p < 0.01). In the internal test dataset, the ENN model yielded a median DICE score = 0.84 (IQR: 0.62-0.97, corticomedullary) and 0.86 (IQR: 0.77-0.96, nephrogenic CM phase), and the segmentation confidence an AUC = 0.89 (sensitivity = 0.86; specificity = 0.77). In the independent test dataset, the ENN model achieved a median DICE score = 0.84 (IQR: 0.71-0.97, corticomedullary CM phase); and segmentation confidence an accuracy = 0.84 (sensitivity = 0.86 and specificity = 0.81). ENN segmentations were visualized with color-coded voxelwise tumor probabilities and thresholds superimposed on clinical CT images. CONCLUSIONS: ENN-based renal tumor segmentation robustly performs in external test data and might aid in renal tumor classification and treatment planning. CLINICAL RELEVANCE STATEMENT: Ensembles of neural networks (ENN) models could automatically segment renal tumors on routine CTs, enabling and standardizing downstream image analyses and treatment planning. Providing confidence measures and segmentation overlays on images can lower the threshold for clinical ENN implementation. KEY POINTS: Ensembles of neural networks (ENN) segmentation is visualized by color-coded voxelwise tumor probabilities and thresholds. ENN provided a high segmentation accuracy in internal testing and in an independent external test dataset. ENN models provide measures of segmentation confidence which can robustly discriminate between successful and inadequate segmentations.

Plasma Lipidomic Profiling Using Mass Spectrometry for Multiple Sclerosis Diagnosis and Disease Activity Stratification (LipidMS).

This investigation explores the potential of plasma lipidomic signatures for aiding in the diagnosis of Multiple Sclerosis (MS) and evaluating the clinical course and disease activity of diseased patients. Plasma samples from 60 patients with MS (PwMS) were clinically stratified to either a relapsing-remitting (RRMS) or a chronic progressive MS course and 60 age-matched controls were analyzed using state-of-the-art direct infusion quantitative shotgun lipidomics. To account for potential confounders, data were filtered for age and BMI correlations. The statistical analysis employed supervised and unsupervised multivariate data analysis techniques, including a principal component analysis (PCA), a partial least squares discriminant analysis (oPLS-DA) and a random forest (RF). To determine whether the significant absolute differences in the lipid subspecies have a relevant effect on the overall composition of the respective lipid classes, we introduce a class composition visualization (CCV). We identified 670 lipids across 16 classes. PwMS showed a significant increase in diacylglycerols (DAG), with DAG 16:0;0_18:1;0 being proven to be the lipid with the highest predictive ability for MS as determined by RF. The alterations in the phosphatidylethanolamines (PE) were mainly linked to RRMS while the alterations in the ether-bound PEs (PE O-) were found in chronic progressive MS. The amount of CE species was reduced in the CPMS cohort whereas TAG species were reduced in the RRMS patients, both lipid classes being relevant in lipid storage. Combining the above mentioned data analyses, distinct lipidomic signatures were isolated and shown to be correlated with clinical phenotypes. Our study suggests that specific plasma lipid profiles are not merely associated with the diagnosis of MS but instead point toward distinct clinical features in the individual patient paving the way for personalized therapy and an enhanced understanding of MS pathology.

Complementary Dual Approach for In Silico Target Identification of Potential Pharmaceutical Compounds in Cystic Fibrosis.

Cystic fibrosis is a genetic disease caused by mutation of the CFTR gene, which encodes a chloride and bicarbonate transporter in epithelial cells. Due to the vast range of geno- and phenotypes, it is difficult to find causative treatments; however, small-molecule therapeutics have been clinically approved in the last decade. Still, the search for novel therapeutics is ongoing, and thousands of compounds are being tested in different assays, often leaving their mechanism of action unknown. Here, we bring together a CFTR-specific compound database (CandActCFTR) and systems biology model (CFTR Lifecycle Map) to identify the targets of the most promising compounds. We use a dual inverse screening approach, where we employ target- and ligand-based methods to suggest targets of 309 active compounds in the database amongst 90 protein targets from the systems biology model. Overall, we identified 1038 potential target-compound pairings and were able to suggest targets for all 309 active compounds in the database.

CFTR Lifecycle Map-A Systems Medicine Model of CFTR Maturation to Predict Possible Active Compound Combinations.

Different causative therapeutics for CF patients have been developed. There are still no mutation-specific therapeutics for some patients, especially those with rare CFTR mutations. For this purpose, high-throughput screens have been performed which result in various candidate compounds, with mostly unclear modes of action. In order to elucidate the mechanism of action for promising candidate substances and to be able to predict possible synergistic effects of substance combinations, we used a systems biology approach to create a model of the CFTR maturation pathway in cells in a standardized, human- and machine-readable format. It is composed of a core map, manually curated from small-scale experiments in human cells, and a coarse map including interactors identified in large-scale efforts. The manually curated core map includes 170 different molecular entities and 156 reactions from 221 publications. The coarse map encompasses 1384 unique proteins from four publications. The overlap between the two data sources amounts to 46 proteins. The CFTR Lifecycle Map can be used to support the identification of potential targets inside the cell and elucidate the mode of action for candidate substances. It thereby provides a backbone to structure available data as well as a tool to develop hypotheses regarding novel therapeutics.

Impact of pre-OP independence in patients with limited brain metastases on long-term survival.

BACKGROUND: Brain metastasis represents a major complication with a significantly shorter overall survival of many oncological diseases, in particular of lung cancer, breast cancer and malignant melanoma patients. However, despite the poor prognosis, sometimes clinical decision-making, between on the one hand not to harm the patient and on the other hand not withholding a potential therapeutic option, is very challenging. Thus the aim of this retrospective study was to compare various scores, including scores for activities of daily living (ADL) before resection of brain metastases and to analyse their impact on survival. METHODS: Our single institution retrospective patient cohort (N = 100) with a median age of 63.6 years, which had all undergone resection of one or more brain metastases, was categorized using the original patient files. The cohort includes 52 patients with lung cancer, 27 patients with breast cancer, 8 patients with colorectal carcinoma and 13 patients with kidney cancer. To categorize, we used different score systems which were capable to evaluate the patient in relation to self-sufficiency, activity and self-determination as part of ADL. The retrospective analysis includes the ECOG-Status, Karnofsky-Index, Barthel-Index, ASA-Classification and Katz-Index. Pre-processing and the analysis of the data was implemented using KNIME, where we used the R-plugin nodes to perform the final statistical tests with R. RESULTS: Our analysis reveals that most of the ADL scores we tested are able to give a reliable prediction on overall survival after brain metastasis surgery. The survival rates decrease significantly with a lower score in all tested score systems, with the exception of the ASA-Risk score. In particular, the Katz Index < 6 was identified to have a significant correlation with a lower cancer specific survival (CSS) (HR 3.33, 95%-CI [2.17-5.00]; p-Value = 9.6*10- 9), which is easy to use and has reproducible measurements. CONCLUSIONS: Pre-operative independence assessment by indices of ADL represents a predictor for overall survival after resection of brain metastases. Especially the easily, objectively and rapidly applicable Katz-Score is a very helpful tool to assess the pre-operative status, which could be additionally included in clinical decision making in daily practice.

[Incidence and Predictive Factors for Bilaterality in Patients with Papillary Thyroid Carcinoma]. / Inzidenz und prädiktive Faktoren des bilateralen papillären Schilddrüsenkarzinoms.

BACKGROUND: The optimal extent of thyroidectomy for papillary thyroid cancer (PTC) ≥ 10 mm und < 10 mm is still controversial. Therefore, the purpose of this study was to investigate factors predictive for bilaterality in patients with papillary thyroid carcinoma (PTC). MATERIAL AND METHODS: We retrospectively reviewed 123 PTC patients in a single centre study who underwent either completion or total thyroidectomy and analysed the predictive value of tumour size, histological parameters, multifocality, and lymph node metastases with primary tumour size of ≥ 10 mm and < 10 mm as well as for ≥ 7 mm and < 7 mm. RESULTS: Out of 123 patients, 26 exhibited bilateral PTC. This was significantly more frequent in patients with a primary tumour size of ≥ 10 mm (77%) compared to a tumour size of < 10 mm (23%) (p = 0.004). Multifocality was found to be an independent predictive factor for bilaterality (p = 5.022e-18). Metachronous lymph node metastases showed a trend for bilateral PTCs (p = 0.0691). These findings were reproducible for the comparison between the ≥ 7 mm and < 7 mm group. CONCLUSION: The presence of bilateral PTC appears to be related to the size of the primary tumour ≥ 10 mm. Multifocality is a positive predictor for bilaterality. When multifocality, even with a primary tumour size of < 10 mm, is observed in patients with PTC, total thyroidectomy or completion thyroidectomy may be considered. If lobectomy is performed in patients with PTC, meticulous follow-up is needed to detect hidden malignancies in the contralateral lobe.

The utilization of multidisciplinary tumor boards (MDT) in clinical routine: results of a health care research study focusing on patients with metastasized colorectal cancer.

PURPOSE: Multidisciplinary tumor boards (MDT) have been advocated as standard of care in modern oncology. German guidelines for metastasized colorectal cancer (mCRC) recommend MDT discussion of colon cancer patients after completion of primary tumor therapy but stage IV colon cancer as well as rectal cancer patients prior to any therapy. In this health care research study, we evaluated application and decisional consequences of this approach in clinical routine. METHODS: All major institutions providing oncological care in southern Lower Saxony and Northern Hesse (N = 11) were invited. Patients with mCRC diagnosed between 01/2011 and 12/2013 were eligible. Data were collected using a standardized patient report form and stored in a GCP-conform EDC-system (secuTrial®). RESULTS: A university medical center, four teaching hospitals, one communal hospital, and three oncological focus practices participated in the study. In total, 470 patients with a median age of 70 years were enrolled. Guideline conform MDT discussion was performed in 63% of operated colon cancer patients, 38% of stage IV colon cancer patients and 47% of rectal cancer patients, respectively. Resection of metastases was performed in 41% of cases. Patients ≥70 years (n = 250) received significantly more often treatment following MDT discussion (86 versus 64%, p = 0.0002). Not the resection rate (48 versus 57%, p = 0.1574) but indication for preoperative chemotherapy (57 versus 33%, p = 0.0056) significantly differed when patients with single organ metastases experienced MDT discussion. CONCLUSIONS: MDT discussion is not as established as advocated by national guidelines. Treatment decisions differ especially in older patients and those with single organ metastases.

Dynamic Brain Lipid Profiles Modulate Microglial Lipid Droplet Accumulation and Inflammation Under Ischemic Conditions in Mice.

Microglia are critically involved in post-stroke inflammation affecting neurological outcomes. Lipid droplet (LD) accumulation in microglia results in a dysfunctional and pro-inflammatory state in the aged brain and worsens the outcome of neuroinflammatory and neurodegenerative diseases. However, the role of LD-rich microglia (LDRM) under stroke conditions is unknown. Using in vitro and in vivo stroke models, herein accumulation patterns of microglial LD and their corresponding microglial inflammatory signaling cascades are studied. Interactions between temporal and spatial dynamics of lipid profiles and microglial phenotypes in different post-stroke brain regions are found. Hence, microglia display enhanced levels of LD accumulation and elevated perilipin 2 (PLIN2) expression patterns when exposed to hypoxia or stroke. Such LDRM exhibit high levels of TNF-α, IL-6, and IL-1ß as well as a pro-inflammatory phenotype and differentially expressed lipid metabolism-related genes. These post-ischemic alterations result in distinct lipid profiles with spatial and temporal dynamics, especially with regard to cholesteryl ester and triacylglycerol levels, further exacerbating post-ischemic inflammation. The present study sheds new light on the dynamic changes of brain lipid profiles and aggregation patterns of LD in microglia exposed to ischemia, demonstrating a mutual mechanism between microglial phenotype and function, which contributes to progression of brain injury.

Differential effects of ELX/TEZ/IVA on organ-specific CFTR function in two patients with the rare CFTR splice mutations c.273+1G>A and c.165-2A>G.

Introduction: Evidence for the efficiency of highly-effective triple-CFTR-modulatory therapy with elexacaftor/tezacaftor/ivacaftor (ETI), either demonstrated in clinical trials or by in vitro testing, is lacking for about 10% of people with cystic fibrosis (pwCF) with rare mutations. Comprehensive assessment of CFTR function can provide critical information on the impact of ETI on CFTR function gains for such rare mutations, lending argument of the prescription of ETI. The mutation c.165-2A>G is a rare acceptor splice mutation that has not yet been functionally characterized. We here describe the functional changes induced by ETI in two brothers who are compound heterozygous for the splice mutations c.273+1G>C and c.165-2A>G. Methods: We assessed the effects of ETI on CFTR function by quantitative pilocarpine iontophoresis (QPIT), nasal potential difference measurements (nPD), intestinal current measurements (ICM), ß-adrenergic sweat secretion tests (SST) and multiple breath washout (MBW) prior to and 4 months after the initiation of ETI. Results: Functional CFTR analysis prior to ETI showed no CFTR function in the respiratory and intestinal epithelia and in the sweat gland reabsorptive duct in either brother. In contrast, ß-adrenergic stimulated, CFTR-mediated sweat secretion was detectable in the CF range. Under ETI, both brothers continued to exhibit high sweat chloride concentration in QPIT, evidence of low residual CFTR function in the respiratory epithelia, but normalized ß-adrenergically stimulated production of primary sweat. Discussion: Our results are the first to demonstrate that the c.165-2A>G/c.273+1G>C mutation genotype permits mutant CFTR protein expression. We showed organ-specific differences in the expression of CFTR and consecutive responses to ETI of the c.165-2A>G/c.273+1G>C CFTR mutants that are probably accomplished by non-canonical CFTR mRNA isoforms. This showcase tells us that the individual response of rare CFTR mutations to highly-effective CFTR modulation cannot be predicted from assays in standard cell cultures, but requires the personalized multi-organ assessment by CFTR biomarkers.

Integrating Text Mining into the Curation of Disease Maps.

An adequate visualization form is required to gain an overview and ultimately understand the complex and diverse biological mechanisms of diseases. Recently, disease maps have been introduced for this purpose. A disease map is defined as a systems biological map or model that combines metabolic, signaling, and physiological pathways to create a comprehensive overview of known disease mechanisms. With the increase in publications describing biological interactions, efforts in creating and curating comprehensive disease maps is growing accordingly. Therefore, new computational approaches are needed to reduce the time that manual curation takes. Test mining algorithms can be used to analyse the natural language of scientific publications. These types of algorithms can take humanly readable text passages and convert them into a more ordered, machine-usable data structure. To support the creation of disease maps by text mining, we developed an interactive, user-friendly disease map viewer. The disease map viewer displays text mining results in a systems biology map, where the user can review them and either validate or reject identified interactions. Ultimately, the viewer brings together the time-saving advantages of text mining with the accuracy of manual data curation.

CFTR modulation with elexacaftor-tezacaftor-ivacaftor in people with cystic fibrosis assessed by the ß-adrenergic sweat rate assay.

BACKGROUND: The cystic fibrosis (CF) sweat gland is defective in ß-adrenergically-stimulated sweat secretion in the coil and chloride reabsorption in the duct. Whereas chloride reabsorption is regularly assessed by quantitative pilocarpine iontophoresis (QPIT), the measurement of ß-adrenergic sweat secretion is not yet established in clinical practice. METHODS: A novel sweat bubble imaging protocol was developed that determines sweat secretion rates by automatic recording, processing and quality control of the kinetics of sweat droplet formation. RESULTS: Treatment of CF patients with the CFTR modulators elexacaftor, tezacaftor and ivacaftor reduced the sweat chloride concentration measured in QPIT in the majority of patients to values in the intermediate or normal range. In contrast, the ß-adrenergically-stimulated sweat secretion rate assayed by the automated bubble sweat test was normalized in only 3 patients, slightly increased in 12 patients and remained undetectable in 8 patients. CONCLUSIONS: ß-adrenergic sweat stimulation in the coil is apparently rather stringent in its requirements for a wild type CFTR conformation whereas chloride reabsorption in the duct tolerates residual structural and functional deficits of native or pharmacologically rescued mutant CFTR in the apical membrane.

Mapping Compound Databases to Disease Maps-A MINERVA Plugin for CandActBase.

The MINERVA platform is currently the most widely used platform for visualizing and providing access to disease maps. Disease maps are systems biological maps of molecular interactions relevant in a certain disease context, where they can be used to support drug discovery. For this purpose, we extended MINERVA's own drug and chemical search using the MINERVA plugin starter kit. We developed a plugin to provide a linkage between disease maps in MINERVA and application-specific databases of candidate therapeutics. The plugin has three main functionalities; one shows all the targets of all the compounds in the database, the second is a compound-based search to highlight targets of specific compounds, and the third can be used to find compounds that affect a certain target. As a use case, we applied the plugin to link a disease map and compound database we previously established in the context of cystic fibrosis and, herein, point out possible issues and difficulties. The plugin is publicly available on GitLab; the use-case application to cystic fibrosis, connecting disease maps and the compound database CandActCFTR, is available online.

Comprehensive Analysis of Chemical Structures That Have Been Tested as CFTR Activating Substances in a Publicly Available Database CandActCFTR.

Background: Cystic fibrosis (CF) is a genetic disease caused by mutations in CFTR, which encodes a chloride and bicarbonate transporter expressed in exocrine epithelia throughout the body. Recently, some therapeutics became available that directly target dysfunctional CFTR, yet research for more effective substances is ongoing. The database CandActCFTR aims to provide detailed and comprehensive information on candidate therapeutics for the activation of CFTR-mediated ion conductance aiding systems-biology approaches to identify substances that will synergistically activate CFTR-mediated ion conductance based on published data. Results: Until 10/2020, we derived data from 108 publications on 3,109 CFTR-relevant substances via the literature database PubMed and further 666 substances via ChEMBL; only 19 substances were shared between these sources. One hundred and forty-five molecules do not have a corresponding entry in PubChem or ChemSpider, which indicates that there currently is no single comprehensive database on chemical substances in the public domain. Apart from basic data on all compounds, we have visualized the chemical space derived from their chemical descriptors via a principal component analysis annotated for CFTR-relevant biological categories. Our online query tools enable the search for most similar compounds and provide the relevant annotations in a structured way. The integration of the KNIME software environment in the back-end facilitates a fast and user-friendly maintenance of the provided data sets and a quick extension with new functionalities, e.g., new analysis routines. CandActBase automatically integrates information from other online sources, such as synonyms from PubChem and provides links to other resources like ChEMBL or the source publications. Conclusion: CandActCFTR aims to establish a database model of candidate cystic fibrosis therapeutics for the activation of CFTR-mediated ion conductance to merge data from publicly available sources. Using CandActBase, our strategy to represent data from several internet resources in a merged and organized form can also be applied to other use cases. For substances tested as CFTR activating compounds, the search function allows users to check if a specific compound or a closely related substance was already tested in the CF field. The acquired information on tested substances will assist in the identification of the most promising candidates for future therapeutics.

Discriminating malignant and benign clinical T1 renal masses on computed tomography: A pragmatic radiomics and machine learning approach.

The aim of this study was to discriminate malignant and benign clinical T1 renal masses on routinely acquired computed tomography (CT) images using radiomics and machine learning techniques.Adult patients undergoing surgical resection and histopathological analysis of clinical T1 renal masses were included. Preoperative CT studies in venous phase from multiple referring centers were included, without restriction to specific CT scanners, slice thickness, or degrees of artifacts. Renal masses were segmented and 120 standardized radiomic features extracted. Machine learning algorithms were used to predict malignancy of renal masses using radiomics features and cross-validation. Diagnostic accuracy of machine learning models and assessment by independent blinded radiologists were compared based on the gold standard of histopathologic diagnosis.A total of 94 patients met inclusion criteria (benign renal masses: n = 18; malignant: n = 76). CT studies from 18 different scanners were assessed with median slice thickness of 2.5 mm and artifacts in 15 cases (15.9%).Area under the receiver-operating-characteristics curve (AUC) of random forest (random forest [RF], AUC = 0.83) was significantly higher compared to the radiologists (AUC = 0.68, P = .047). Sensitivity was significantly higher for RF versus radiologists (0.88 vs 0.80, P = .045), whereas specificity was numerically higher for RF (0.67 vs 0.50, P = .083).Although limited by an overall small sample size and few benign renal tumors, a radiomic features and machine learning approach suggests a high diagnostic accuracy for discrimination of malignant and benign clinical T1 renal masses on venous phase CT. The presented algorithm robustly outperforms human readers in a real-life scenario with nonstandardized imaging studies from various referring centers.

KRAS mutation status concordance between the primary tumor and the corresponding metastasis in patients with rectal cancer.

INTRODUCTION: Oncogenic mutation within the KRAS gene represents a negative predictor for treatment response to anti-epidermal growth factor receptor (EGFR) in patients with colorectal cancer. Recently, we have shown no relevant heterogeneity for KRAS mutation status within and between pre- and posttherapeutic samples from the primary tumor in patients with locally advanced rectal cancer. The aim of this study was to evaluate the intertumoral heterogeneity of KRAS mutation status between the primary tumor and the corresponding metastasis or local recurrence in the similar cohort and to evaluate the ideal representative tissue for KRAS mutation testing. MATERIALS AND METHODS: KRAS mutation status was analyzed from 47 patients with locally advanced rectal cancer, which were enrolled in the CAO/ARO/AIO-94 or CAO/ARO/AIO-04 trial. Mutations in KRAS codons 12, 13, and 61 were analyzed by using the KRAS RGQ PCR Kit (therascreen® KRAS test). Six patients needed to be excluded due to incomplete follow up data. 11 patients showed a relapse of the disease during the follow up presented by distant metastases or local recurrence. DNA from representative areas of metastatic tissue was obtained from formalin-fixed paraffin-embedded specimens. RESULTS: The mean patient age was 64.13 ± 10.64 years. In total, 19 patients showed a KRAS mutation (46.34%) in the primary tumor. Of the eleven patients with a metastatic disease or local recurrence, five patients showed a KRAS mutation whereas six patients had a KRAS wildtype status. Metastatic localizations included the liver (n = 2), lung (n = 4), local recurrence (n = 1), liver + lung (n = 3), lung + local recurrence (n = 1). For these eleven patients with paired data available for the primary tumor and metastatic tissue, a significant KRAS mutation status concordance was detected in 81.18% (9/11) of the patients (p = 0.03271). Only two patients showed intertumoral heterogeneity, which harbored in one patient a KRAS G12C mutation status in the primary tumor, but a G12V KRAS mutation status in the corresponding lung lesion, and in the other patient a G12A mutation in the primary lesion and a WT in the lung metastasis. CONCLUSIONS: We show a significant concordance of the KRAS mutation status between tumor samples obtained from the primary tumor and the corresponding metastasis and/ or local recurrence in patients with rectal cancer indicating no relevant intertumoral heterogeneity. Our data suggest that sampling either the primary (pre- or posttherapeutical tumor tissue) or metastatic lesion may be valid for the initial evaluation of KRAS mutation status predicting the response to anti-EGFR treatment and guiding clinical decisions.

The Prognostic Value of Tyrosine Kinase SRC Expression in Locally Advanced Rectal Cancer.

The cellular sarcoma gene (SRC) is a proto-oncogene encoding for a tyrosine kinase. SRC expression was determined in locally advanced rectal adenocarcinoma tissue from pretreatment biopsies and resection specimens. The expression level was correlated with clinicopathological parameters to evaluate the predictive and prognostic capacity. For this monocentric analysis 186 patients with locally advanced rectal cancer (median: 63.7 years; 130 men (69.9%), 56 women (30.1%)) were included. Patients with a carcinoma of the upper third of the rectum were treated with primary tumor resection (n=27; 14.5%). All other patients received a preoperative chemoradiotherapy (CRT) with 50.4 Gy and concomitant 5-fluorouracil (5-FU) or 5-FU+oxaliplatin followed by postoperative chemotherapy with 5-FU or 5-FU+oxaliplatin. SRC expression was determined with immunohistochemical staining from pretreatment biopsies (n=152) and residual tumor tissue from the resection specimens (n=163). The results were correlated with clinicopathological parameters and long-term follow-up. The expression of SRC was determined in pretherapeutic biopsies (mean H-Score: 229) and resection specimens (mean H-Score: 254). High SRC expression in pretherapeutic tumor samples significantly correlated with a negative postoperative nodal status (p=0.005). Furthermore an increased protein expression in residual tumor tissue was associated with fewer distant metastases (p=0.04). The overexpression of SRC in pretreatment tumor biopsies showed also a trend for a longer cancer-specific survival (CSS; p=0.05) and fewer local relapses (p=0.06) during long-term follow-up. High SRC expression in rectal cancer seems to be associated with a better long-term outcome. This finding could help in the future to stratify patients for a recurrence risk adapted postoperative treatment.

Neoadjuvant Therapy in Rectal Cancer - Biobanking of Preoperative Tumor Biopsies.

Translational research relies on high-quality biospecimens. In patients with rectal cancer treated preoperatively with radiochemotherapy tissue based analyses are challenging. To assess quality challenges we analyzed tissue samples taken over the last years in a multicenter setting. We retrospectively evaluated overall 197 patients of the CAO/ARO/AIO-94- and 04-trial with locally advanced rectal cancer that were biopsied preoperatively at the University Medical Center Goettingen as well as in 10 cooperating hospitals in Germany. The cellular content of tumor, mucosa, stroma, necrosis and the amount of isolated DNA and RNA as well as the RNA integrity number (RIN) as quality parameters were evaluated. A high RNA yield (p = 2.75e-07) and the content of tumor (p = 0.004) is significantly associated to high RIN-values, whereas a high content of mucosa (p = 0.07) shows a trend and a high amount of necrosis (p = 0.01) is significantly associated with RNA of poor quality. Correlating biopsies from Goettingen and the cooperating centers showed comparable tumor content results. By taking small sized biopsies we could assess a clear correlation between a good RNA quality and a high amount of RNA and tumor cells. These results also indicate that specimens collected at different centers are of comparable quality.

mRNA profiling reveals determinants of trastuzumab efficiency in HER2-positive breast cancer.

Intrinsic and acquired resistance to the monoclonal antibody drug trastuzumab is a major problem in the treatment of HER2-positive breast cancer. A deeper understanding of the underlying mechanisms could help to develop new agents. Our intention was to detect genes and single nucleotide polymorphisms (SNPs) affecting trastuzumab efficiency in cell culture. Three HER2-positive breast cancer cell lines with different resistance phenotypes were analyzed. We chose BT474 as model of trastuzumab sensitivity, HCC1954 as model of intrinsic resistance, and BTR50, derived from BT474, as model of acquired resistance. Based on RNA-Seq data, we performed differential expression analyses on these cell lines with and without trastuzumab treatment. Differentially expressed genes between the resistant cell lines and BT474 are expected to contribute to resistance. Differentially expressed genes between untreated and trastuzumab treated BT474 are expected to contribute to drug efficacy. To exclude false positives from the candidate gene set, we removed genes that were also differentially expressed between untreated and trastuzumab treated BTR50. We further searched for SNPs in the untreated cell lines which could contribute to trastuzumab resistance. The analysis resulted in 54 differentially expressed candidate genes that might be connected to trastuzumab efficiency. 90% of 40 selected candidates were validated by RT-qPCR. ALPP, CALCOCO1, CAV1, CYP1A2 and IGFBP3 were significantly higher expressed in the trastuzumab treated than in the untreated BT474 cell line. GDF15, IL8, LCN2, PTGS2 and 20 other genes were significantly higher expressed in HCC1954 than in BT474, while NCAM2, COLEC12, AFF3, TFF3, NRCAM, GREB1 and TFF1 were significantly lower expressed. Additionally, we inferred SNPs in HCC1954 for CAV1, PTGS2, IL8 and IGFBP3. The latter also had a variation in BTR50. 20% of the validated subset have already been mentioned in literature. For half of them we called and analyzed SNPs. These results contribute to a better understanding of trastuzumab action and resistance mechanisms.

HER-2 and HER-3 expression in liver metastases of patients with colorectal cancer.

OBJECTIVE: In this study, we evaluate the frequency of HER-2 and HER-3 expression in liver metastases from patients with colorectal cancer (CRLM). We analyzed the potential of HER-2 and HER-3 as therapeutic targets and evaluated their prognostic value. PATIENTS AND METHODS: Overall 208 patients with CRLM were enrolled. HER-2 and HER-3 expression were determined in metastatic tissue of diagnostic punch biopsies (n = 29) or resection specimens (n = 179). The results of immunohistochemistry (IHC) scoring and In-situ-hybridization (ISH)-amplification were correlated with clinical parameters and for the 179 resected patients with cancer-specific (CSS) and overall survival (OS). The mean follow-up time was 56.7 months. RESULTS: Positivity of HER-2 status (IHC score 2+/ISH+ and IHC 3+) was found in 8.2% of CRLM. High expression of HER-3 (IHC score 2+ and IHC 3+) was detected in 75.0% of liver metastases. CSS after liver surgery was determined and was independent from the HER-2 status (p = 0.963); however HER-3 was prognostic with a favorable course for patients showing an overexpression of HER-3 (p = 0.037). CONCLUSIONS: HER-2 overexpression occurs in only 8% of patients with CRLM but with 75% of cases HER-3 is frequently overexpressed in CRLM. Therefore, HER-2 and particularly HER-3 could serve as novel targets to be addressed within multimodal treatment approaches.

Frequency of HER-2 positivity in rectal cancer and prognosis.

In patients with advanced rectal cancer (cUICC II and III) multimodality therapy resulted in better long-term local tumor control. Ongoing clinical trials are focusing on therapy intensification to improve disease-free (DFS) and cancer-specific survival (CSS), the integration of biomarkers for prediction of individual recurrence risk, and the identification of new targets. In this context, we investigated HER-2, a member of the epidermal growth factor receptor family, whose expression pattern and role was unclear in rectal cancer. A total of 264 patients (192 male, 72 female; median age 64 y) received standardized multidisciplinary treatment according to protocols of phase II/III trials of the German Rectal Cancer Study Group. HER-2 status was determined in pretherapeutic biopsies and resection specimens using immunohistochemistry scoring and detection of silver in situ hybridization amplification. Tumors with an immunohistochemistry score of 3 or silver in situ hybridization ratios of ≥2.0 were classified HER-2 positive; these results were correlated with clinicopathologic parameters [eg, resection (R) status, nodal status ((y)pN)], DFS, and CSS. Positive HER-2 status was found in 12.4% of biopsies and in 26.7% of resected specimens. With a median follow-up of 46.5 months, patients with HER-2 positivity showed in trend a better DFS (P=0.1) and a benefit in CSS (P=0.03). The 5-year survival rate was 96.0% (HER-2 positive) versus 80.0% (HER-2 negative). In univariate and multivariate analyses, HER-2 was an independent predictor for CSS (0.02) along with the (y)pN status (P<0.00001) and R status (P=0.011). HER-2 amplification is detectable in a relevant proportion (26.7%) of rectal cancer patients. For the development of innovative new therapies, HER-2 may represent a promising target and should be further assessed within prospective clinical trials.