Carlos Fernández Moro

Whole-tissue biopsy phenotyping of three-dimensional tumours reveals patterns of cancer heterogeneity

Intratumoral heterogeneity is a critical factor when diagnosing and treating patients with cancer. Marked differences in the genetic and epigenetic backgrounds of cancer cells have been revealed by advances in genome sequencing, yet little is known about the phenotypic landscape and the spatial distribution of intratumoral heterogeneity within solid tumours. Here, we show that three-dimensional light-sheet microscopy of cleared solid tumours can identify unique patterns of phenotypic heterogeneity, in the epithelial-to-mesenchymal transition and in angiogenesis, at single-cell resolution in whole formalin-fixed paraffin-embedded (FFPE) biopsy samples. We also show that cleared FFPE samples can be re-embedded in paraffin after examination for future use, and that our tumour-phenotyping pipeline can determine tumour stage and stratify patient prognosis from clinical samples with higher accuracy than current diagnostic methods, thus facilitating the design of more efficient cancer therapies.A method that identifies patterns of tumour heterogeneity in intact biopsy samples using 3D light-sheet microscopy stratifies patients by tumour stage.

Bioinformatory‐assisted analysis of next‐generation sequencing data for precision medicine in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is a tumor with an extremely poor prognosis, predominantly as a result of chemotherapy resistance and numerous somatic mutations. Consequently, PDAC is a prime candidate for the use of sequencing to identify causative mutations, facilitating subsequent administration of targeted therapy. In a feasibility study, we retrospectively assessed the therapeutic recommendations of a novel, evidence‐based software that analyzes next‐generation sequencing (NGS) data using a large panel of pharmacogenomic biomarkers for efficacy and toxicity. Tissue from 14 patients with PDAC was sequenced using NGS with a 620 gene panel. FASTQ files were fed into treatmentmap. The results were compared with chemotherapy in the patients, including all side effects. No changes in therapy were made. Known driver mutations for PDAC were confirmed (e.g. KRAS, TP53). Software analysis revealed positive biomarkers for predicted effective and ineffective treatments in all patients. At least one biomarker associated with increased toxicity could be detected in all patients. Patients had been receiving one of the currently approved chemotherapy agents. In two patients, toxicity could have been correctly predicted by the software analysis. The results suggest that NGS, in combination with an evidence‐based software, could be conducted within a 2‐week period, thus being feasible for clinical routine. Therapy recommendations were principally off‐label use. Based on the predominant KRAS mutations, other drugs were predicted to be ineffective. The pharmacogenomic biomarkers indicative of increased toxicity could be retrospectively linked to reported negative side effects in the respective patients. Finally, the occurrence of somatic and germline mutations in cancer syndrome‐associated genes is noteworthy, despite a high frequency of these particular variants in the background population. These results suggest software‐analysis of NGS data provides evidence‐based information on effective, ineffective and toxic drugs, potentially forming the basis for precision cancer medicine in PDAC.

Stroma-regulated HMGA2 is an independent prognostic marker in PDAC and AAC

Background:The HMGA2 protein has experimentally been linked to EMT and cancer stemness. Recent studies imply that tumour–stroma interactions regulate these features and thereby contribute to tumour aggressiveness.Methods:We analysed 253 cases of pancreatic ductal adenocarcinoma (PDAC) and 155 cases of ampullary adenocarcinoma (AAC) for HMGA2 expression by IHC. The data were correlated with stroma abundance and supplemented by experimental studies.Results:HMGA2 acts as an independent prognostic marker associated with a significantly shorter overall survival in both tumour types. Overall, HMGA2-positivity was more frequent in patients with PDAC than with AAC. The HMGA2 status in tumour cells significantly correlated with the abundance of PDGFRβ-defined stroma cells. In vivo co-injection of Panc-1 cancer cells with pancreatic stellate cells increased tumour growth in a manner associated with increased HMGA2 expression. Furthermore, in vitro treatment of Panc-1 with conditioned media from PDGF-BB-activated stellate cells increased their ability to form tumour spheroids.Conclusions:This study identifies HMGA2 expression in tumour cells as an independent prognostic marker in PDAC and AAC. Correlative data analysis gives novel tissue-based evidence for a heterotypic cross-talk with stroma cells as a possible mechanism for HMGA2 induction, which is further supported by experimental models.

Immunohistochemical Typing of Adenocarcinomas of the Pancreatobiliary System Improves Diagnosis and Prognostic Stratification

BACKGROUND & AIMS Adenocarcinomas of the pancreatobiliary system are currently classified by their primary anatomical location. In particular, the pathological diagnosis of intrahepatic cholangiocarcinoma is still considered as a diagnosis of exclusion of metastatic adenocarcinoma. Periampullary cancers have been previously classified according to the histological type of differentiation (pancreatobiliary, intestinal), but overlapping morphological features hinder their differential diagnosis. We performed an integrative immunohistochemical analysis of pancreato-biliary tumors to improve their diagnosis and prediction of outcome. METHODS This was a retrospective observational cohort study on patients with adenocarcinoma of the pancreatobiliary system who underwent diagnostic core needle biopsy or surgical resection at a tertiary referral center. 409 tumor samples were analyzed with up to 27 conventional antibodies used in diagnostic pathology. Immunohistochemical scoring system was the percentage of stained tumor cells. Bioinformatic analysis, internal validation, and survival analysis were performed. RESULTS Hierarchical clustering and differential expression analysis identified three immunohistochemical tumor types (extrahepatic pancreatobiliary, intestinal, and intrahepatic cholangiocarcinoma) and the discriminant markers between them. Among patients who underwent surgical resection of their primary tumor with curative intent, the intestinal type showed an adjusted hazard ratio of 0.19 for overall survival (95% confidence interval 0.05-0.72; p value = 0.014) compared to the extrahepatic pancreatobiliary type. CONCLUSIONS Integrative immunohistochemical classification of adenocarcinomas of the pancreatobiliary system results in a characteristic immunohistochemical profile for intrahepatic cholangiocarcinoma and intestinal type adenocarcinoma, which helps in distinguishing them from metastatic and pancreatobiliary type adenocarcinoma, respectively. A diagnostic immunohistochemical panel and additional extended panels of discriminant markers are proposed as guidance for their pathological diagnosis.

Cerulein-induced pancreatic fibrosis is modulated by Smad7, the major negative regulator of transforming growth factor-β signaling.

Chronic pancreatitis is the most common disease of the exocrine pancreas, characterized by progressive inflammation, acinar atrophy and fibrosis. Transforming growth factor-β signaling (TGFβ) is the most potent fibrogenic cytokine known, and its increased expression is a common denominator for fibrosis in chronic pancreatitis. Smad7 is induced by the TGFβ superfamily members as an intracellular inhibitory feedback antagonizing TGFβ signaling. To investigate the functional role of Smad7 in vivo, we induced chronic pancreatitis by repeated administration of cerulein in mice that are deficient in exon-I of Smad7. The response to chronic pancreatitis induction was significantly more severe in Smad7 mutant mice as indicated by a stronger accumulation of extracellular matrix, increased levels of inflammatory cells and an elevated number of mesenchymal cells/myofibroblasts in Smad7 mutant pancreata. Taken together, we conclude that lack of a functional Smad7 gene results in more severe damage in chronic pancreatitis. Therefore, Smad7 could be envisaged as a promising target in antifibrotic therapy of the pancreas.

Publisher Correction: Whole-tissue biopsy phenotyping of three-dimensional tumours reveals patterns of cancer heterogeneity

In this Article originally published, owing to a technical error, author affiliations were incorrectly assigned in the HTML version; the PDF was correct. These errors have now been corrected.

Growth patterns of colorectal cancer liver metastases and their impact on prognosis: a systematic review

Background Colorectal cancer liver metastases (CRLM) grow in distinct histological patterns that have been associated with outcome after surgical resection. We conducted a systematic review to evaluate the frequency of different CRLM growth patterns and their impact on prognosis. Methods We searched Embase and MEDLINE databases from inception to 1 December 2017 to identify studies that reported CRLM growth pattern histopathology, their frequencies, and/or data related to outcome. Results We included a total of 23 studies (2432 patients with CRLM) published between 1991 and 2017. There were variations in the terminology used to describe the growth patterns as well as in their histopathological definitions. A ‘desmoplastic’ pattern was most frequently considered, followed by ‘pushing’ and ‘replacement’ patterns. Data supported the presence of both intralesional and interlesional heterogeneity. There were no differences in growth pattern distribution stratified by chemotherapy. While heterogeneity of histopathology assessment precluded formal meta-analysis, the majority of articles found favourable outcomes for desmoplastic and unfavourable outcomes for replacement CRLM, independently of when the study was conducted. Conclusions The results suggest that CRLM growth patterns may have prognostic potential and that they may be considered for standardised routine histopathological reporting. Further understanding of the different growth patterns may provide important insights into the biological mechanisms that underlie metastatic growth in the liver.

Abstract 3165: An evidence-based software tool for personalized cancer medicine to recommend therapeutic options and avoid toxicity

Background. For many tumors, therapeutic options are sparse beyond the guidelines, especially for pancreatic cancer. At the same time, more and more biomarkers are known, informing about or supporting treatment decisions. Finally, tumor DNA analysis with next generation sequencing (NGS) is quickly becoming a routine test, at least for tumors. However, to analyse the vast amount of data and provide concrete, evidence-based treatment recommendations has been a challenge. Methods. Applying NGS in a quality controlled set-up together with the newly developed evidence-based software tool EngineusGUIDETM (CE-marked). Results. During the time from Oct 2013 until Oct 2015, 87 patients were analysed with EngineusGUIDE. In 7 cases, more than one tumor was investigated. NGS was performed (WXS = 48; panel/paired = 16, panel = 23). Sequencing could be performed in all but one patient (Whole Exome; bone metastasis). Sequencing quality was insufficient for analysis in 3 cases (paired panel), sequencing revealed insufficient tumor content in the sample for one patient (Whole Exome) leaving 82 patients. The indication was: Pancreatic Neoplasms = 21 cases; Colorectal Neoplasms = 12; Breast Neoplasms = 5; CUP = 6; NSCLC = 3; 2 cases each for Bronchial Neoplasms, Adenoid Cystic Carcinoma, Common Bile Duct Neoplasms, Glioblastoma, Multiple Myeloma, Prostatic Neoplasms and 1 case each for Adenocarcinoma, Duodenal Neoplasms, Endometrial Neoplasms, Hemangiosarcoma, Hypopharyngeal Neoplasms, Leukemia (Lymphocytic, Chronic, B-Cell), Liposarcoma, Liver Neoplasms, Lung Neoplasms, B-Cell Lymphoma, Mantle-Cell Lymphoma, Meningioma, Oropharyngeal Neoplasms, Ovarian Neoplasms, Paranasal Sinus Neoplasms, Parathyroid Neoplasms, Sarcoma, Sigmoid Neoplasms, Squamous Cell Neoplasms, Stomach Neoplasms, Thyroid Neoplasms, Urinary Bladder Neoplasms, Uveal melanoma. In 67/82 patients, druggable targets (response biomarkers) could be identified (range 0-8; median 2). In 45/82 patients (range 0-5; median 1) biomarkers indicated lack of efficacy (e.g. KRAS mutation in CRC). In 65/82 patients, biomarkers indicated increased toxicity (range 0-7; median 2), in 19/82 patients FDA-approved biomarkers for toxicity were detected (28 biomarkers). Of the positive biomarkers, 40 biomarkers in 26 patients indicated drugs approved in the indication, 75 biomarkers in 45 patients indicated approved drugs, and 58 biomarkers in 39 patients indicated experimental drugs (pre-clinical and phase I - III). Six patients have already received drugs recommended by EngineusGUIDE. In 11 patients, toxicity markers may explain observed toxicity during previous treatment. We are currently collecting the outcome parameters of EngineusGUIDE recommendations. Citation Format: Matthias Lohr, Katrin Stecker, Caroline Huelsewig, Sandra Morandell, Isin Ertongur, Sarah Luke-Glaser, Anna Laib, Linnea Malgerud, Carlos Fernandez Moro, Masoud Karimi, Johan Permert, Rainer Heuchel, Johan Lindberg, Valtteri Wirta, Alexander Picker, Marco Del Chiaro, Stephan L. Haas, Caroline S. Verbek, Lars Engstrand, Jens Siveke, David Jackson, Henrik Gronberg, Dirk Jager, Stephan Brock. An evidence-based software tool for personalized cancer medicine to recommend therapeutic options and avoid toxicity. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3165.