Concomitant inhibition of PI3K/mTOR signaling pathways boosts antiproliferative effects of lanreotide in bronchopulmonary neuroendocrine tumor cells.

Introduction: Somatostatin analogues (SSAs) are commonly used in the treatment of hormone hypersecretion in neuroendocrine tumors (NETs), however the extent to which they inhibit proliferation is much discussed. Objective: We studied the antiproliferative effects of novel SSA lanreotide in bronchopulmonary NETs (BP-NETs). We focused on assessing whether pretreating cells with inhibitors for phosphatidylinositol 3-kinase (PI3K) and mammalian target for rapamycin (mTOR) could enhance the antiproliferative effects of lanreotide. Methods: BP-NET cell lines NCI-H720 and NCI-H727 were treated with PI3K inhibitor BYL719 (alpelisib), mTOR inhibitor everolimus and SSA lanreotide to determine the effect on NET differentiation markers, cell survival, proliferation and alterations in cancer-associated pathways. NT-3 cells, previously reported to express somatostatin receptors (SSTRs) natively, were used as control for SSTR expression. Results: SSTR2 was upregulated in NCI-H720 and NT-3 cells upon treatment with BYL719. Additionally, combination treatment consisting of BYL719 and everolimus plus lanreotide tested in NCI-H720 and NCI-H727 led to diminished cell proliferation in a dose-dependent manner. Production of proteins activating cell death mechanisms was also induced. Notably, a multiplexed gene expression analysis performed on NCI-H720 revealed that BYL719 plus lanreotide had a stronger effect on the downregulation of mitogens than lanreotide alone. Discussion/Conclusion: We report a widespread analysis of changes in BP-NET cell lines at the genetic/protein expression level in response to combination of lanreotide with pretreatment consisting of BYL719 and everolimus. Interestingly, SSTR expression reinduction could be exploited in therapeutic and diagnostic applications. The overall results of this study support the evaluation of combination-based therapies using lanreotide in preclinical studies to further increase its antiproliferative effect and ultimately facilitate its use in high-grade tumors.

Response prediction in patients with gastric and esophagogastric adenocarcinoma under neoadjuvant chemotherapy using targeted gene expression analysis and next-generation sequencing in pre-therapeutic biopsies.

OBJECTIVES: Perioperative chemo-(radio-) therapy is the accepted standard in European patients with locally advanced adenocarcinoma of the esophagogastric junction or stomach (AEG/AS). However, 30-85% of patients do not respond to this treatment. The aim of our study was the identification of predictive biomarkers in pre-therapeutic endoscopic tumor biopsies from patients with histopathologic response (Becker-1) versus non-response (Becker-2/3) to preoperative chemotherapy. METHODS: Formalin-fixed paraffin-embedded biopsies from 36 Caucasian patients (Becker-1 n = 11, Becker-2 n = 7, Becker-3 n = 18) with AEG/AS, taken prior to neoadjuvant chemotherapy were selected. For RNA expression analysis, we employed the NanoString nCounter System. To identify genomic alterations like single nucleotide variants (SNV), copy number variation (CNV) and fusion events, we used Illumina TST170 gene panel. For HER2 and FGFR2 protein expression, immunostaining was performed. Furthermore, we analyzed the microsatellite instability (MSI) and Epstein-Barr virus (EBV) infection status by EBER in situ hybridization. RESULTS: Heat map and principal component analyses showed no clustering by means of gene expression according to regression grade. Concerning two recently proposed predictive markers, our data showed equal distribution for MSI (Becker-1: 2; Becker-2: 1; Becker-3: 3; out of 29 tested) and EBV infection was rare (1/32). We could not reveal discriminating target genes concerning SNV, but found a higher mutational burden in non-responders versus responders and fusion (in 6/14) and CNV events (in 5/14) exclusively in Becker-3. CONCLUSIONS: Although we could not identify discriminating target genes, our data suggest that molecular alterations are in general more prevalent in patients with AEG/AS belonging to the non-responding Becker group 3.

Predictive biomarker for surgical outcome in patients with advanced primary high-grade serous ovarian cancer. Are we there yet? An analysis of the prospective biobank for ovarian cancer.

BACKGROUND: High-grade serous ovarian cancer (HGSOC) is the most common subtype of ovarian cancer and is associated with high mortality rates. Surgical outcome is one of the most important prognostic factors. There are no valid biomarkers to identify which patients may benefit from a primary debulking approach. OBJECTIVE: Our study aimed to discover and validate a predictive panel for surgical outcome of residual tumor mass after first-line debulking surgery. STUDY DESIGN: Firstly, "In silico" analysis of publicly available datasets identified 200 genes as predictors for surgical outcome. The top selected genes were then validated using the novel Nanostring method, which was applied for the first time for this particular research objective. 225 primary ovarian cancer patients with well annotated clinical data and a complete debulking rate of 60% were compiled for a clinical cohort. The 14 best rated genes were then validated through the cohort, using immunohistochemistry testing. Lastly, we used our biomarker expression data to predict the presence of miliary carcinomatosis patterns. RESULTS: The Nanostring analysis identified 37 genes differentially expressed between optimal and suboptimal debulked patients (p < 0.05). The immunohistochemistry validated the top 14 genes, reaching an AUC Ø0.650. The analysis for the prediction of miliary carcinomatosis patterns reached an AUC of Ø0.797. CONCLUSION: The tissue-based biomarkers in our analysis could not reliably predict post-operative residual tumor. Patient and non-patient-associated co-factors, surgical skills, and center experience remain the main determining factors when considering the surgical outcome at primary debulking in high-grade serous ovarian cancer patients.

Protein kinase C targeting of luminal (T-47D), luminal/HER2-positive (BT474), and triple negative (HCC1806) breast cancer cells in-vitro with AEB071 (Sotrastaurin) is efficient but mediated by subtype specific molecular effects.

PURPOSE: Protein kinase C (PKC) plays a pivotal role in malignant cell proliferation, apoptosis, invasiveness and migration. However, its exploitation as therapeutic target in breast cancer has been merely explored. Here were evaluated the AEB071 (Sotrastaurin™) treatment efficiency of breast cancer cell lines derived from estrogen receptor positive (T-47D), estrogen/HER2 receptor positive (BT474), and triple negative (HCC1806) breast cancer cells under 2D (monolayer) and 3D (multicellular tumor spheroids) culture conditions. Additionally, spheroid cocultures of BC and N1 fibroblasts were analyzed. METHODS: We quantitatively assessed the proliferation capacity of breast cancer cells and fibroblasts as a function of AEB071 treatment using flow cytometry. The activities of PKC isoforms, substrates, and key molecules of the PKC signaling known to be involved in the regulation of tumor cell proliferation and cellular survival were additionally evaluated. Moreover, a multigene expression analysis (PanCancer Pathways assay) using the nanoString™ technology was applied. RESULTS: All breast cancer cell lines subjected to this study were sensitive to AEB071 treatment, whereby cell proliferation in 2D culture was considerably (BT474) or moderately (HCC1806) retarded in G0/G1 or in G2/M phase (T-47D) of the cell cycle. Regardless of the breast cancer subtype the efficiency of AEB071 treatment was significantly lower in the presence of N1 fibroblast cells. Subtype specific driver molecules, namely IL19, c-myb, and NGFR were mostly affected by the AEB071 treatment. CONCLUSION: A combined targeting of PKC and a subtype specific driver molecule might complement specified breast cancer treatment.

Classification of Molecular Subtypes of High-Grade Serous Ovarian Cancer by MALDI-Imaging.

Despite the correlation of clinical outcome and molecular subtypes of high-grade serous ovarian cancer (HGSOC), contemporary gene expression signatures have not been implemented in clinical practice to stratify patients for targeted therapy. Hence, we aimed to examine the potential of unsupervised matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-IMS) to stratify patients who might benefit from targeted therapeutic strategies. Molecular subtyping of paraffin-embedded tissue samples from 279 HGSOC patients was performed by NanoString analysis (ground truth labeling). Next, we applied MALDI-IMS paired with machine-learning algorithms to identify distinct mass profiles on the same paraffin-embedded tissue sections and distinguish HGSOC subtypes by proteomic signature. Finally, we devised a novel approach to annotate spectra of stromal origin. We elucidated a MALDI-derived proteomic signature (135 peptides) able to classify HGSOC subtypes. Random forest classifiers achieved an area under the curve (AUC) of 0.983. Furthermore, we demonstrated that the exclusion of stroma-associated spectra provides tangible improvements to classification quality (AUC = 0.988). Moreover, novel MALDI-based stroma annotation achieved near-perfect classifications (AUC = 0.999). Here, we present a concept integrating MALDI-IMS with machine-learning algorithms to classify patients according to distinct molecular subtypes of HGSOC. This has great potential to assign patients for personalized treatment.

Immunoprofiling in Neuroendocrine Neoplasms Unveil Immunosuppressive Microenvironment.

Checkpoint inhibitors have shown promising results in a variety of tumors; however, in neuroendocrine tumors (NET) and neuroendocrine carcinomas (NEC), low response rates were reported. We aimed herein to investigate the tumor immune microenvironment in NET/NEC to determine whether checkpoint pathways like programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) might play a role in immune escape and whether other escape mechanisms might need to be targeted to enable a functional antitumor response. Forty-eight NET and thirty NEC samples were analyzed by immunohistochemistry (IHC) and mRNA immunoprofiling including digital spatial profiling. Through IHC, both NET/NEC showed stromal, but less intratumoral CD3+ T cell infiltration, although this was significantly higher in NEC compared to NET. Expression of PD1, PD-L1, and T cell immunoglobulin and mucin domain-containing protein 3 (TIM3) on immune cells was low or nearly absent. mRNA immunoprofiling revealed low expression of IFNγ inducible genes in NET and NEC without any spatial heterogeneity. However, we observed an increased mRNA expression of chemokines, which attract myeloid cells in NET and NEC, and a high abundance of genes related to immunosuppressive myeloid cells and genes with immunosuppressive functions like CD47 and CD74. In conclusion, NET and NEC lack signs of an activation of the adaptive immune system, but rather show abundance of several immunosuppressive genes that represent potential targets for immunomodulation.

Discovery and Validation of Novel Biomarkers for Detection of Epithelial Ovarian Cancer.

Detection of epithelial ovarian cancer (EOC) poses a critical medical challenge. However, novel biomarkers for diagnosis remain to be discovered. Therefore, innovative approaches are of the utmost importance for patient outcome. Here, we present a concept for blood-based biomarker discovery, investigating both epithelial and specifically stromal compartments, which have been neglected in search for novel candidates. We queried gene expression profiles of EOC including microdissected epithelium and adjacent stroma from benign and malignant tumours. Genes significantly differentially expressed within either the epithelial or the stromal compartments were retrieved. The expression of genes whose products are secreted yet absent in the blood of healthy donors were validated in tissue and blood from patients with pelvic mass by NanoString analysis. Results were confirmed by the comprehensive gene expression database, CSIOVDB (Ovarian cancer database of Cancer Science Institute Singapore). The top 25% of candidate genes were explored for their biomarker potential, and twelve were able to discriminate between benign and malignant tumours on transcript levels (p < 0.05). Among them T-cell differentiation protein myelin and lymphocyte (MAL), aurora kinase A (AURKA), stroma-derived candidates versican (VCAN), and syndecan-3 (SDC), which performed significantly better than the recently reported biomarker fibroblast growth factor 18 (FGF18) to discern malignant from benign conditions. Furthermore, elevated MAL and AURKA expression levels correlated significantly with a poor prognosis. We identified promising novel candidates and found the stroma of EOC to be a suitable compartment for biomarker discovery.

High-accuracy determination of internal circadian time from a single blood sample.

BACKGROUND: The circadian clock is a fundamental and pervasive biological program that coordinates 24-hour rhythms in physiology, metabolism, and behavior, and it is essential to health. Whereas therapy adapted to time of day is increasingly reported to be highly successful, it needs to be personalized, since internal circadian time is different for each individual. In addition, internal time is not a stable trait, but is influenced by many factors, including genetic predisposition, age, sex, environmental light levels, and season. An easy and convenient diagnostic tool is currently missing. METHODS: To establish a validated test, we followed a 3-stage biomarker development strategy: (a) using circadian transcriptomics of blood monocytes from 12 individuals in a constant routine protocol combined with machine learning approaches, we identified biomarkers for internal time; and these biomarkers (b) were migrated to a clinically relevant gene expression profiling platform (NanoString) and (c) were externally validated using an independent study with 28 early or late chronotypes. RESULTS: We developed a highly accurate and simple assay (BodyTime) to estimate the internal circadian time in humans from a single blood sample. Our assay needs only a small set of blood-based transcript biomarkers and is as accurate as the current gold standard method, dim-light melatonin onset, at smaller monetary, time, and sample-number cost. CONCLUSION: The BodyTime assay provides a new diagnostic tool for personalization of health care according to the patient's circadian clock. FUNDING: This study was supported by the Bundesministerium für Bildung und Forschung, Germany (FKZ: 13N13160 and 13N13162) and Intellux GmbH, Germany.

Proteasome inhibitor bortezomib enhances the effect of standard chemotherapy in small cell lung cancer.

Small cell lung cancer (SCLC) is an aggressive cancer showing a very poor prognosis because of metastasis formation at an early stage and acquisition of chemoresistance. One key driver of chemoresistance is the transcription factor Forkhead box protein M1 (FOXM1) that regulates cell cycle proliferation, maintenance of genomic stability, DNA damage response, and cell differentiation in numerous tumor entities. In this study we investigated the role of FOXM1 in SCLC progression and analyzed the effect of FOXM1 inhibition using two proteasome inhibitors, bortezomib and siomycin A. FOXM1 was strongly expressed in patient-derived SCLC samples (n=123) and its nuclear localization was associated with the proliferation marker Ki-67. Both proteasome inhibitors successfully inhibited FOXM1 expression leading to a significantly reduced proliferation and a decreased mitotic rate along with cell cycle arrest and apoptosis induction. These effects were further enhanced by addition of bortezomib to standard chemotherapy. Treatment of mice bearing chemoresistant SCLC xenografts with bortezomib reduced the mean bioluminescence signal of tumors by 54%. Similarly, treatment with cisplatin as a standard chemotherapy reduced the mean bioluminescence signal of tumors by 58%. However, in combination with standard chemotherapy bortezomib further reduced the mean bioluminescence signal by 93% (p=0.0258). In conclusion, we demonstrate the effect of bortezomib in inhibiting FOXM1 expression and thus in sensitizing resistant SCLC cells to standard chemotherapy. Thus, addition of bortezomib to standard chemotherapy might potently improve SCLC therapy, particularly in an extensive cancer stage.