Benjamin Balluff

Classification of HER2 Receptor Status in Breast Cancer Tissues by MALDI Imaging Mass Spectrometry

Clinical laboratory testing for HER2 status in breast cancer tissues is critically important for therapeutic decision making. Matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) is a powerful tool for investigating proteins through the direct and morphology-driven analysis of tissue sections. We hypothesized that MALDI-IMS may determine HER2 status directly from breast cancer tissues. Breast cancer tissues (n = 48) predefined for HER2 status were subjected to MALDI-IMS, and protein profiles were obtained through direct analysis of tissue sections. Protein identification was performed by tissue microextraction and fractionation followed by top-down tandem mass spectrometry. A discovery and an independent validation set were used to predict HER2 status by applying proteomic classification algorithms. We found that specific protein/peptide expression changes strongly correlated with the HER2 overexpression. Among these, we identified m/z 8404 as cysteine-rich intestinal protein 1. The proteomic signature was able to accurately define HER2-positive from HER2-negative tissues, achieving high values for sensitivity of 83%, for specificity of 92%, and an overall accuracy of 89%. Our results underscore the potential of MALDI-IMS proteomic algorithms for morphology-driven tissue diagnostics such as HER2 testing and show that MALDI-IMS can reveal biologically significant molecular details from tissues which are not limited to traditional high-abundance proteins.

TFAP2E–DKK4 and Chemoresistance in Colorectal Cancer

BACKGROUNDnChemotherapy for advanced colorectal cancer leads to improved survival; however, predictors of response to systemic treatment are not available. Genomic and epigenetic alterations of the gene encoding transcription factor AP-2 epsilon (TFAP2E) are common in human cancers. The gene encoding dickkopf homolog 4 protein (DKK4) is a potential downstream target of TFAP2E and has been implicated in chemotherapy resistance. We aimed to further evaluate the role of TFAP2E and DKK4 as predictors of the response of colorectal cancer to chemotherapy.nnnMETHODSnWe analyzed the expression, methylation, and function of TFAP2E in colorectal-cancer cell lines in vitro and in patients with colorectal cancer. We examined an initial cohort of 74 patients, followed by four cohorts of patients (total, 220) undergoing chemotherapy or chemoradiation.nnnRESULTSnTFAP2E was hypermethylated in 38 of 74 patients (51%) in the initial cohort. Hypermethylation was associated with decreased expression of TFAP2E in primary and metastatic colorectal-cancer specimens and cell lines. Colorectal-cancer cell lines overexpressing DKK4 showed increased chemoresistance to fluorouracil but not irinotecan or oxaliplatin. In the four other patient cohorts, TFAP2E hypermethylation was significantly associated with nonresponse to chemotherapy (P<0.001). Conversely, the probability of response among patients with hypomethylation was approximately six times that in the entire population (overall estimated risk ratio, 5.74; 95% confidence interval, 3.36 to 9.79). Epigenetic alterations of TFAP2E were independent of mutations in key regulatory cancer genes, microsatellite instability, and other genes that affect fluorouracil metabolism.nnnCONCLUSIONSnTFAP2E hypermethylation is associated with clinical nonresponsiveness to chemotherapy in colorectal cancer. Functional assays confirm that TFAP2E-dependent resistance is mediated through DKK4. In patients who have colorectal cancer with TFAP2E hypermethylation, targeting of DKK4 may be an option to overcome TFAP2E-mediated drug resistance. (Funded by Deutsche Forschungsgemeinschaft and others.).

Tumor Classification of Six Common Cancer Types Based on Proteomic Profiling by MALDI Imaging

In clinical diagnostics, it is of outmost importance to correctly identify the source of a metastatic tumor, especially if no apparent primary tumor is present. Tissue-based proteomics might allow correct tumor classification. As a result, we performed MALDI imaging to generate proteomic signatures for different tumors. These signatures were used to classify common cancer types. At first, a cohort comprised of tissue samples from six adenocarcinoma entities located at different organ sites (esophagus, breast, colon, liver, stomach, thyroid gland, n = 171) was classified using two algorithms for a training and test set. For the test set, Support Vector Machine and Random Forest yielded overall accuracies of 82.74 and 81.18%, respectively. Then, colon cancer liver metastasis samples (n = 19) were introduced into the classification. The liver metastasis samples could be discriminated with high accuracy from primary tumors of colon cancer and hepatocellular carcinoma. Additionally, colon cancer liver metastasis samples could be successfully classified by using colon cancer primary tumor samples for the training of the classifier. These findings demonstrate that MALDI imaging-derived proteomic classifiers can discriminate between different tumor types at different organ sites and in the same site.

Tissue-based proteomics reveals FXYD3, S100A11 and GSTM3 as novel markers for regional lymph node metastasis in colon cancer

Regional lymph node metastasis negatively affects prognosis in colon cancer patients. The molecular processes leading to regional lymph node metastasis are only partially understood and proteomic markers for metastasis are still scarce. Therefore, a tissue‐based proteomic approach was undertaken for identifying proteins associated with regional lymph node metastasis. Two complementary tissue‐based proteomic methods have been employed. MALDI imaging was used for identifying small proteins (≤25 kDa) in situ and label‐free quantitative proteomics was used for identifying larger proteins. A tissue cohort comprising primary colon tumours without metastasis (UICC II, pN0, n = 21) and with lymph node metastasis (UICC III, pN2, n = 33) was analysed. Subsequent validation of identified proteins was done by immunohistochemical staining on an independent tissue cohort consisting of primary colon tumour specimens (n = 168). MALDI imaging yielded ten discriminating m/z species, and label‐free quantitative proteomics 28 proteins. Two MALDI imaging‐derived candidate proteins (FXYD3 and S100A11) and one from the label‐free quantitative proteomics (GSTM3) were validated on the independent tissue cohort. All three markers correlated significantly with regional lymph node metastasis: FXYD3 (p = 0.0110), S100A11 (p = 0.0071), and GSTM3 (p = 0.0173). FXYD3 and S100A11 were more highly expressed in UICC II patient tumour tissues. GSTM3 was more highly expressed in UICC III patient tumour tissues. By our tissue‐based proteomic approach, we could identify a large panel of proteins which are associated with regional lymph node metastasis and which have not been described so far. Here we show that novel markers for regional lymph metastasis can be identified by MALDI imaging or label‐free quantitative proteomics and subsequently validated on an independent tissue cohort. Copyright

Classification of HER2/neu Status in Gastric Cancer Using a Breast-Cancer Derived Proteome Classifier.

HER2-testing in breast and gastric cancers is mandatory for the treatment with trastuzumab. We hypothesized that imaging mass spectrometry (IMS) of breast cancers may be useful for generating a classifier that may determine HER2-status in other cancer entities irrespective of primary tumor site. A total of 107 breast (n = 48) and gastric (n = 59) cryo tissue samples was analyzed by IMS (HER2 was present in 29 cases). The obtained proteomic profiles were used to create HER2 prediction models using different classification algorithms. A breast cancer proteome derived classifier, with HER2 present in 15 cases, correctly predicted HER2-status in gastric cancers with a sensitivity of 65% and a specificity of 92%. To create a universal classifier for HER2-status, breast and nonbreast cancer samples were combined, which increased sensitivity to 78%, and specificity was 88%. Our proof of principle study provides evidence that HER2-status can be identified on a proteomic level across different cancer types suggesting that HER2 overexpression may constitute a unique molecular event independent of the tumor site. Furthermore, these results indicate that IMS may be useful for the determination of potential drugable targets, as it offers a quicker, cheaper, and more objective analysis than the standard HER2-testing procedures immunohistochemistry and fluorescence in situ hybridization.

Comprehensive identification of proteins from MALDI imaging

Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) is a powerful tool for the visualization of proteins in tissues and has demonstrated considerable diagnostic and prognostic value. One main challenge is that the molecular identity of such potential biomarkers mostly remains unknown. We introduce a generic method that removes this issue by systematically identifying the proteins embedded in the MALDI matrix using a combination of bottom-up and top-down proteomics. The analyses of ten human tissues lead to the identification of 1400 abundant and soluble proteins constituting the set of proteins detectable by MALDI IMS including >90% of all IMS biomarkers reported in the literature. Top-down analysis of the matrix proteome identified 124 mostly N- and C-terminally fragmented proteins indicating considerable protein processing activity in tissues. All protein identification data from this study as well as the IMS literature has been deposited into MaTisse, a new publically available database, which we anticipate will become a valuable resource for the IMS community.

Clinical response to chemotherapy in oesophageal adenocarcinoma patients is linked to defects in mitochondria.

Chemotherapeutic drugs kill cancer cells, but it is unclear why this happens in responding patients but not in non‐responders. Proteomic profiles of patients with oesophageal adenocarcinoma may be helpful in predicting response and selecting more effective treatment strategies. In this study, pretherapeutic oesophageal adenocarcinoma biopsies were analysed for proteomic changes associated with response to chemotherapy by MALDI imaging mass spectrometry. Resulting candidate proteins were identified by liquid chromatography–tandem mass spectrometry (LC–MS/MS) and investigated for functional relevance in vitro. Clinical impact was validated in pretherapeutic biopsies from an independent patient cohort. Studies on the incidence of these defects in other solid tumours were included. We discovered that clinical response to cisplatin correlated with pre‐existing defects in the mitochondrial respiratory chain complexes of cancer cells, caused by loss of specific cytochrome c oxidase (COX) subunits. Knockdown of a COX protein altered chemosensitivity in vitro, increasing the propensity of cancer cells to undergo cell death following cisplatin treatment. In an independent validation, patients with reduced COX protein expression prior to treatment exhibited favourable clinical outcomes to chemotherapy, whereas tumours with unchanged COX expression were chemoresistant. In conclusion, previously undiscovered pre‐existing defects in mitochondrial respiratory complexes cause cancer cells to become chemosensitive: mitochondrial defects lower the cells threshold for undergoing cell death in response to cisplatin. By contrast, cancer cells with intact mitochondrial respiratory complexes are chemoresistant and have a high threshold for cisplatin‐induced cell death. This connection between mitochondrial respiration and chemosensitivity is relevant to anticancer therapeutics that target the mitochondrial electron transport chain. Copyright

High-mass-resolution MALDI mass spectrometry imaging of metabolites from formalin-fixed paraffin-embedded tissue

Formalin-fixed and paraffin-embedded (FFPE) tissue specimens are the gold standard for histological examination, and they provide valuable molecular information in tissue-based research. Metabolite assessment from archived tissue samples has not been extensively conducted because of a lack of appropriate protocols and concerns about changes in metabolite content or chemical state due to tissue processing. We present a protocol for the in situ analysis of metabolite content from FFPE samples using a high-mass-resolution matrix-assisted laser desorption/ionization fourier-transform ion cyclotron resonance mass spectrometry imaging (MALDI-FT-ICR-MSI) platform. The method involves FFPE tissue sections that undergo deparaffinization and matrix coating by 9-aminoacridine before MALDI-MSI. Using this platform, we previously detected ∼1,500 m/z species in the mass range m/z 50–1,000 in FFPE samples; the overlap compared with fresh frozen samples is 72% of m/z species, indicating that metabolites are largely conserved in FFPE tissue samples. This protocol can be reproducibly performed on FFPE tissues, including small samples such as tissue microarrays and biopsies. The procedure can be completed in a day, depending on the size of the sample measured and raster size used. Advantages of this approach include easy sample handling, reproducibility, high throughput and the ability to demonstrate molecular spatial distributions in situ. The data acquired with this protocol can be used in research and clinical practice.

Multicenter Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI MSI) Identifies Proteomic Differences in Breast-Cancer-Associated Stroma

MALDI mass spectrometry imaging (MSI) has rapidly established itself as a powerful biomarker discovery tool. To date, no formal investigation has assessed the center-to-center comparability of MALDI MSI experiments, an essential step for it to develop into a new diagnostic method. To test such capabilities, we have performed a multicenter study focused on biomarkers of stromal activation in breast cancer. MALDI MSI experiments were performed in two centers using independent tissue banks, infrastructure, methods, and practitioners. One of the data sets was used for discovery and the other for validation. Areas of intra- and extratumoral stroma were selected, and their protein signals were compared. Four protein signals were found to be significantly associated with tumor-associated stroma in the discovery data set measured in Munich. Three of these peaks were also detected in the independent validation data set measured in Leiden, all of which were also significantly associated with intratumoral stroma. Hierarchical clustering displayed 100% accuracy in the Munich MSI data set and 80.9% accuracy in the Leiden MSI data set. The association of one of the identified mass signals (PA28) with stromal activation was confirmed with immunohistochemistry performed on 20 breast tumors. Independent and international MALDI MSI investigations could identify validated biomarkers of stromal activation.

High-resolution MALDI-FT-ICR MS imaging for the analysis of metabolites from formalin-fixed, paraffin-embedded clinical tissue samples.

We present the first analytical approach to demonstrate the in situ imaging of metabolites from formalin‐fixed, paraffin‐embedded (FFPE) human tissue samples. Using high‐resolution matrix‐assisted laser desorption/ionization Fourier‐transform ion cyclotron resonance mass spectrometry imaging (MALDI‐FT‐ICR MSI), we conducted a proof‐of‐principle experiment comparing metabolite measurements from FFPE and fresh frozen tissue sections, and found an overlap of 72% amongst 1700 m/z species. In particular, we observed conservation of biomedically relevant information at the metabolite level in FFPE tissues. In biomedical applications, we analysed tissues from 350 different cancer patients and were able to discriminate between normal and tumour tissues, and different tumours from the same organ, and found an independent prognostic factor for patient survival. This study demonstrates the ability to measure metabolites in FFPE tissues using MALDI‐FT‐ICR MSI, which can then be assigned to histology and clinical parameters. Our approach is a major technical, histochemical, and clinicopathological advance that highlights the potential for investigating diseases in archived FFPE tissues. Copyright