Targeting the glutamine metabolism to suppress cell proliferation in mesenchymal docetaxel-resistant prostate cancer.

Docetaxel (DX) serves as a palliative treatment option for metastatic prostate cancer (PCa). Despite initial remission, acquired DX resistance is inevitable. The mechanisms behind DX resistance have not yet been deciphered, but a mesenchymal phenotype is associated with DX resistance. Mesenchymal phenotypes have been linked to metabolic rewiring, obtaining most ATP production by oxidative phosphorylation (OXPHOS) powered substantially by glutamine (Gln). Likewise, Gln is known to play an essential role in modulating bioenergetic, redox homeostasis and autophagy. Herein, investigations of Gln deprivation on DX-sensitive and -resistant (DR) PCa cells revealed that the DR cell sub-lines were susceptible to Gln deprivation. Mechanistically, Gln deprivation reduced OXPHOS and ATP levels, causing a disturbance in cell cycle progression. Genetic and chemical inhibition of the Gln-metabolism key protein GLS1 could validate the Gln deprivation results, thereby representing a valid therapeutic target. Moreover, immunohistological investigation of GLS1 revealed a high-expressing GLS1 subgroup post-docetaxel failure, exhibiting low overall survival. This subgroup presents an intriguing opportunity for targeted therapy focusing on glutamine metabolism. Thus, these findings highlight a possible clinical rationale for the chemical inhibition of GLS1 as a therapeutic strategy to target mesenchymal DR PCa cells, thereby delaying accelerated tumour progression.

Enhancing mass spectrometry imaging accessibility using convolutional autoencoders for deriving hypoxia-associated peptides from tumors.

Mass spectrometry imaging (MSI) allows to study cancer's intratumoral heterogeneity through spatially-resolved peptides, metabolites and lipids. Yet, in biomedical research MSI is rarely used for biomarker discovery. Besides its high dimensionality and multicollinearity, mass spectrometry (MS) technologies typically output mass-to-charge ratio values but not the biochemical compounds of interest. Our framework makes particularly low-abundant signals in MSI more accessible. We utilized convolutional autoencoders to aggregate features associated with tumor hypoxia, a parameter with significant spatial heterogeneity, in cancer xenograft models. We highlight that MSI captures these low-abundant signals and that autoencoders can preserve them in their latent space. The relevance of individual hyperparameters is demonstrated through ablation experiments, and the contribution from original features to latent features is unraveled. Complementing MSI with tandem MS from the same tumor model, multiple hypoxia-associated peptide candidates were derived. Compared to random forests alone, our autoencoder approach yielded more biologically relevant insights for biomarker discovery.

Advancing rare cancer research by MALDI mass spectrometry imaging: Applications, challenges, and future perspectives in sarcoma.

MALDI mass spectrometry imaging (MALDI imaging) uniquely advances cancer research, by measuring spatial distribution of endogenous and exogenous molecules directly from tissue sections. These molecular maps provide valuable insights into basic and translational cancer research, including tumor biology, tumor microenvironment, biomarker identification, drug treatment, and patient stratification. Despite its advantages, MALDI imaging is underutilized in studying rare cancers. Sarcomas, a group of malignant mesenchymal tumors, pose unique challenges in medical research due to their complex heterogeneity and low incidence, resulting in understudied subtypes with suboptimal management and outcomes. In this review, we explore the applicability of MALDI imaging in sarcoma research, showcasing its value in understanding this highly heterogeneous and challenging rare cancer. We summarize all MALDI imaging studies in sarcoma to date, highlight their impact on key research fields, including molecular signatures, cancer heterogeneity, and drug studies. We address specific challenges encountered when employing MALDI imaging for sarcomas, and propose solutions, such as using formalin-fixed paraffin-embedded tissues, and multiplexed experiments, and considerations for multi-site studies and digital data sharing practices. Through this review, we aim to spark collaboration between MALDI imaging researchers and clinical colleagues, to deploy the unique capabilities of MALDI imaging in the context of sarcoma.

A reliable transcriptomic risk-score applicable to formalin-fixed paraffin-embedded biopsies improves outcome prediction in localized prostate cancer.

BACKGROUND: Clinical manifestation of prostate cancer (PCa) is highly variable. Aggressive tumors require radical treatment while clinically non-significant ones may be suitable for active surveillance. We previously developed the prognostic ProstaTrend RNA signature based on transcriptome-wide microarray and RNA-sequencing (RNA-Seq) analyses, primarily of prostatectomy specimens. An RNA-Seq study of formalin-fixed paraffin-embedded (FFPE) tumor biopsies has now allowed us to use this test as a basis for the development of a novel test that is applicable to FFPE biopsies as a tool for early routine PCa diagnostics. METHODS: All patients of the FFPE biopsy cohort were treated by radical prostatectomy and median follow-up for biochemical recurrence (BCR) was 9 years. Based on the transcriptome data of 176 FFPE biopsies, we filtered ProstaTrend for genes susceptible to FFPE-associated degradation via regression analysis. ProstaTrend was additionally restricted to genes with concordant prognostic effects in the RNA-Seq TCGA prostate adenocarcinoma (PRAD) cohort to ensure robust and broad applicability. The prognostic relevance of the refined Transcriptomic Risk Score (TRS) was analyzed by Kaplan-Meier curves and Cox-regression models in our FFPE-biopsy cohort and 9 other public datasets from PCa patients with BCR as primary endpoint. In addition, we developed a prostate single-cell atlas of 41 PCa patients from 5 publicly available studies to analyze gene expression of ProstaTrend genes in different cell compartments. RESULTS: Validation of the TRS using the original ProstaTrend signature in the cohort of FFPE biopsies revealed a relevant impact of FFPE-associated degradation on gene expression and consequently no significant association with prognosis (Cox-regression, p-value > 0.05) in FFPE tissue. However, the TRS based on the new version of the ProstaTrend-ffpe signature, which included 204 genes (of originally 1396 genes), was significantly associated with BCR in the FFPE biopsy cohort (Cox-regression p-value < 0.001) and retained prognostic relevance when adjusted for Gleason Grade Groups. We confirmed a significant association with BCR in 9 independent cohorts including 1109 patients. Comparison of the prognostic performance of the TRS with 17 other prognostically relevant PCa panels revealed that ProstaTrend-ffpe was among the best-ranked panels. We generated a PCa cell atlas to associate ProstaTrend genes with cell lineages or cell types. Tumor-specific luminal cells have a significantly higher TRS than normal luminal cells in all analyzed datasets. In addition, TRS of epithelial and luminal cells was correlated with increased Gleason score in 3 studies. CONCLUSIONS: We developed a prognostic gene-expression signature for PCa that can be applied to FFPE biopsies and may be suitable to support clinical decision-making.

Characterization and evaluation of gene fusions as a measure of genetic instability and disease prognosis in prostate cancer.

BACKGROUND: Prostate cancer (PCa) is one of the most prevalent cancers worldwide. The clinical manifestations and molecular characteristics of PCa are highly variable. Aggressive types require radical treatment, whereas indolent ones may be suitable for active surveillance or organ-preserving focal therapies. Patient stratification by clinical or pathological risk categories still lacks sufficient precision. Incorporating molecular biomarkers, such as transcriptome-wide expression signatures, improves patient stratification but so far excludes chromosomal rearrangements. In this study, we investigated gene fusions in PCa, characterized potential novel candidates, and explored their role as prognostic markers for PCa progression. METHODS: We analyzed 630 patients in four cohorts with varying traits regarding sequencing protocols, sample conservation, and PCa risk group. The datasets included transcriptome-wide expression and matched clinical follow-up data to detect and characterize gene fusions in PCa. With the fusion calling software Arriba, we computationally predicted gene fusions. Following detection, we annotated the gene fusions using published databases for gene fusions in cancer. To relate the occurrence of gene fusions to Gleason Grading Groups and disease prognosis, we performed survival analyses using the Kaplan-Meier estimator, log-rank test, and Cox regression. RESULTS: Our analyses identified two potential novel gene fusions, MBTTPS2,L0XNC01::SMS and AMACR::AMACR. These fusions were detected in all four studied cohorts, providing compelling evidence for the validity of these fusions and their relevance in PCa. We also found that the number of gene fusions detected in a patient sample was significantly associated with the time to biochemical recurrence in two of the four cohorts (log-rank test, p-value < 0.05 for both cohorts). This was also confirmed after adjusting the prognostic model for Gleason Grading Groups (Cox regression, p-values < 0.05). CONCLUSIONS: Our gene fusion characterization workflow revealed two potential novel fusions specific for PCa. We found evidence that the number of gene fusions was associated with the prognosis of PCa. However, as the quantitative correlations were only moderately strong, further validation and assessment of clinical value is required before potential application.

Orthotopic Glioblastoma Models for Evaluation of the Clinical Target Volume Concept.

In times of high-precision radiotherapy, the accurate and precise definition of the primary tumor localization and its microscopic spread is of enormous importance. In glioblastoma, the microscopic tumor extension is uncertain and, therefore, population-based margins for Clinical Target Volume (CTV) definition are clinically used, which could either be too small-leading to increased risk of loco-regional recurrences-or too large, thus, enhancing the probability of normal tissue toxicity. Therefore, the aim of this project is to investigate an individualized definition of the CTV in preclinical glioblastoma models based on specific biological tumor characteristics. The microscopic tumor extensions of two different orthotopic brain tumor models (U87MG_mCherry; G7_mCherry) were evaluated before and during fractionated radiotherapy and correlated with corresponding histological data. Representative tumor slices were analyzed using Matrix-Assisted Laser Desorption/Ionization (MALDI) and stained for putative stem-like cell markers as well as invasion markers. The edges of the tumor are clearly shown by the MALDI segmentation via unsupervised clustering of mass spectra and are consistent with the histologically defined border in H&E staining in both models. MALDI component analysis identified specific peaks as potential markers for normal brain tissue (e.g., 1339 m/z), whereas other peaks demarcated the tumors very well (e.g., 1562 m/z for U87MG_mCherry) irrespective of treatment. MMP14 staining revealed only a few positive cells, mainly in the tumor border, which could reflect the invasive front in both models. The results of this study indicate that MALDI information correlates with microscopic tumor spread in glioblastoma models. Therefore, an individualized CTV definition based on biological tumor characteristics seems possible, whereby the visualization of tumor volume and protein heterogeneity can be potentially used to define radiotherapy-sensitive and resistant areas.

Influence of Systemic Therapy on the Expression and Activity of Selected STAT Proteins in Prostate Cancer Tissue.

Signal Transducer and Activator of Transcription (STAT) proteins have been identified as drivers of prostate cancer (PCa) progression and development of aggressive castration-resistant phenotypes. In particular, STAT3, 5, and 6 have been linked to resistance to androgen receptor inhibition and metastasis in in vitro and in vivo models. This descriptive study aimed to validate these preclinical data in tissue obtained from patients with PCa before and while under androgen-deprivation therapy. Therefore, STAT3, 5, and 6 expressions and activity were assessed by immunohistochemistry. The data revealed that STAT3 and 5 changed in PCa. However, there was no relationship between expression and survival. Moreover, due to the heterogeneous nature of PCa, the preclinical results could not be transferred congruently to the patient's material. A pilot study with a longitudinal patient cohort could also show this heterogeneous influence of systemic therapy on STAT3, 5, and 6 expressions and activity. Even if the main mechanisms were validated, these data demonstrate the urge for better patient-near preclinical models. Therefore, these data reflect the need for investigations of STAT proteins in a longitudinal patient cohort to identify factors responsible for the diverse influence of system therapy on STAT expression.

Deficiency in X-linked inhibitor of apoptosis protein promotes susceptibility to microbial triggers of intestinal inflammation.

Inflammatory bowel disease (IBD) is characterized by inappropriate immune responses to the microbiota in genetically susceptible hosts, but little is known about the pathways that link individual genetic alterations to microbiota-dependent inflammation. Here, we demonstrated that the loss of X-linked inhibitor of apoptosis protein (XIAP), a gene associated with Mendelian IBD, rendered Paneth cells sensitive to microbiota-, tumor necrosis factor (TNF)­, receptor-interacting protein kinase 1 (RIPK1)­, and RIPK3-dependent cell death. This was associated with deficiency in Paneth cell­derived antimicrobial peptides and alterations in the stratification and composition of the microbiota. Loss of XIAP was not sufficient to elicit intestinal inflammation but provided susceptibility to pathobionts able to promote granulomatous ileitis, which could be prevented by administration of a Paneth cell­derived antimicrobial peptide. These data reveal a pathway critical for host-microbial cross-talk, which is required for intestinal homeostasis and the prevention of inflammation and which is amenable to therapeutic targeting.

Shotgun lipidomics-based characterization of the landscape of lipid metabolism in colorectal cancer.

Solid tumors are characterized by global metabolic alterations which contribute to their growth and progression. Altered gene expression profiles and plasma lipid composition suggested a role for metabolic reprogramming in colorectal cancer (CRC) development. However, a conclusive picture of CRC-associated lipidome alterations in the tumor tissue has not emerged. Here, we determined molar abundances of 342 species from 20 lipid classes in matched biopsies of CRC and adjacent normal mucosa. We demonstrate that in contrast to previous reports, CRC shows a largely preserved lipidome composition that resembles that of normal colonic mucosa. Important exceptions include increased levels of lyso-phosphatidylinositols in CRC and reduced abundance of ether phospholipids in advanced stages of CRC. As such, our observations challenge the concept of widespread alterations in lipid metabolism in CRC and rather suggest changes in the cellular lipid profile that are limited to selected lipids involved in signaling and the scavenging of reactive oxygen species.

Automated detection of the HER2 gene amplification status in Fluorescence in situ hybridization images for the diagnostics of cancer tissues.

The human epidermal growth factor receptor 2 (HER2) gene amplification status is a crucial marker for evaluating clinical therapies of breast or gastric cancer. We propose a deep learning-based pipeline for the detection, localization and classification of interphase nuclei depending on their HER2 gene amplification state in Fluorescence in situ hybridization (FISH) images. Our pipeline combines two RetinaNet-based object localization networks which are trained (1) to detect and classify interphase nuclei into distinct classes normal, low-grade and high-grade and (2) to detect and classify FISH signals into distinct classes HER2 or centromere of chromosome 17 (CEN17). By independently classifying each nucleus twice, the two-step pipeline provides both robustness and interpretability for the automated detection of the HER2 amplification status. The accuracy of our deep learning-based pipeline is on par with that of three pathologists and a set of 57 validation images containing several hundreds of nuclei are accurately classified. The automatic pipeline is a first step towards assisting pathologists in evaluating the HER2 status of tumors using FISH images, for analyzing FISH images in retrospective studies, and for optimizing the documentation of each tumor sample by automatically annotating and reporting of the HER2 gene amplification specificities.

Neuropilin-2 Regulates Endosome Maturation and EGFR Trafficking to Support Cancer Cell Pathobiology.

Neuropilin-2 (NRP2) is a non-tyrosine kinase receptor frequently overexpressed in various malignancies, where it has been implicated in promoting many protumorigenic behaviors, such as imparting therapeutic resistance to metastatic cancer cells. Here, we report a novel function of NRP2 as a regulator of endocytosis, which is enhanced in cancer cells and is often associated with increased metastatic potential and drug resistance. We found that NRP2 depletion in human prostate and pancreatic cancer cells resulted in the accumulation of EEA1/Rab5-positive early endosomes concomitant with a decrease in Rab7-positive late endosomes, suggesting a delay in early-to-late endosome maturation. NRP2 depletion also impaired the endocytic transport of cell surface EGFR, arresting functionally active EGFR in endocytic vesicles that consequently led to aberrant ERK activation and cell death. Mechanistic investigations revealed that WD-repeat- and FYVE-domain-containing protein 1 (WDFY1) functioned downstream of NRP2 to promote endosome maturation, thereby influencing the endosomal trafficking of EGFR and the formation of autolysosomes responsible for the degradation of internalized cargo. Overall, our results indicate that the NRP2/WDFY1 axis is required for maintaining endocytic activity in cancer cells, which supports their oncogenic activities and confers drug resistance. Therefore, therapeutically targeting endocytosis may represent an attractive strategy to selectively target cancer cells in multiple malignancies.

Progesterone, as well as 17ß-estradiol, is important for regulating AHR battery homoeostasis in the rat uterus.

Several studies indicate that the aryl hydrocarbon receptor (AHR), which plays an important role in mediating the toxicity of many industrial chemicals, plays an important role in the physiology of female reproductive tract organs. This makes it likely that the AHR and additional components of the AHR signalling pathway are under the control of female sex steroids. In a previous study, we could already demonstrate the regulation of many members of the AHR battery by 17ß-estradiol (E2) in the uterus of rats. In this study, we addressed the potential role of progesterone (P4) in this context. In a comparative approach using ovariectomized rats which were treated for 3 days with either vehicle control, E2, progesterone (P4) or the combination of both hormones in addition to sham-operated animals, we could demonstrate that in addition to E2, P4 is also an important factor in regulating AHR signalling in the rat uterus. P4 has effects similar to E2 on uterine Ahr, Arnt and Arnt2 mRNA levels, resulting in a downregulation of these genes, while the E2-mediated downregulation of key AHR response genes Cyp1a1, Gsta2 and Ugt1 is completely antagonized by P4. As with E2, P4 leads to an increase in uterine AHR levels, especially in the endometrial epithelium despite the decrease in corresponding mRNA levels. This indicates a complex gene-specific regulatory network involving E2, P4 and possibly AHR itself to maintain all components of the AHR signalling cascade at the required levels during all stages of the oestrous cycle and pregnancy.

Autophagy: detection, regulation and its role in cancer and therapy response.

PURPOSE: Macroautophagy is a catabolic pathway that degrades cellular components through the lysosomal machinery. Cytoplasmic components are sequestered in double-membrane autophagosomes. They fuse with lysosomes where their cargo is delivered for degradation and recycling. Autophagy acts as a survival mechanism under stress by producing energy and as an intracellular quality management system by clearing damaged organelles like mitochondria and proteins. In this review, the regulation and the role of autophagy in cancer and therapy response are discussed. Furthermore, we will summarize methods for detecting autophagy in vitro and in vivo. CONCLUSION: During the early and late stages of cancer development, the role of autophagy differs. In the very early stages of carcinogenesis, autophagy has an important function by reducing cancer initiating genetic instability and aberrant protein aggregates as well as promoting anti-cancer immune response. In established malignant tumors autophagy confers resistance against metabolic stress caused by nutrient deprivation and the rapid proliferation of carcinoma cells. This function of autophagy is also important for radiation and chemotherapy resistance in cancer. Our laboratory has found that Neuropilin-2-induced autophagy is a potent mediator of therapy resistance in different cancer types. Autophagy not only promotes the survival of tumor cells, but also leads to autophagic cell death. During dysfunctional apoptosis this form of cell death mainly sensitizes cancer cells for therapy such as ionizing radiation. Therefore, the functions of autophagy during cancer progression and therapy are two-sided and further research is needed to understand these in more detail.

Autophagy control by the VEGF-C/NRP-2 axis in cancer and its implication for treatment resistance.

A major contributor to cancer mortality is recurrence and subsequent metastatic transformation following therapeutic intervention. Therefore, in order to develop new treatment modalities and improve the efficacy of current ones, it is important to understand the molecular mechanisms that promote resistance to therapy in cancer cells. One pathway contributing to therapy resistance is autophagy, a self-digestive process that can eliminate unnecessary or damaged organelles to protect cancer cells from death. We have found that the VEGF-C/NRP-2 axis is involved in the activation of autophagy, which helps cancer cell survival following treatment. Inhibition of mTOR complex 1 activity by this axis is the underlying mechanism for the activation of autophagy. Furthermore, we identified two VEGF-C/NRP-2-regulated genes, LAMP-2 and WDFY-1, that have previously been suggested to participate in autophagy and vesicular trafficking. Upregulation of WDFY-1 following VEGF-C or NRP-2 depletion contributes to cytotoxic drug-mediated cell death. Together, these data suggest a link between the VEGF-C/NRP-2 axis and cancer cell survival despite the presence of chemotherapy-induced stress. Effective targeting of this pathway may lead to the development of new cancer therapies.