Dentin Bond Strength of Dental Adhesives Functionalized with Polyhedral Oligomeric Silsesquioxanes.

This study analyzed the dentin shear bond strength (SBS) of an etch-and-rinse (ER) or a self-etch (SE) adhesive incorporated with multifunctional polyhedral oligomeric silsesquioxanes (MA-POSS-8). An ER adhesive (Solobond Plus, VOCO GmbH, Cuxhaven, Germany) and a universal adhesive applied in SE mode (Scotchbond Universal, 3M, St. Paul, MN, USA) were infiltrated with MA-POSS-8 (Hybrid Plastics Inc., Hattiesburg, MS, USA) at 5 wt.% or 10 wt.%. Pure adhesives served as controls. Bovine dentin specimens were conditioned with one of the adhesives prior to the application of a nano-hybrid composite (Venus Diamond A3, Kulzer, Hanau, Germany). SBS and failure modes were determined after water storage for 24 h, 6 months, 12 months, or 24 months (each subgroup n = 20). Statistical analysis was performed using ANOVAs, Weibull statistics, and χ2 tests (p < 0.05). SBSs for the control groups after 24 h were 17.4 ± 4.9 MPa for the ER adhesive and 19.1 ± 5.2 MPa for the universal adhesive. After 24 months, the SBS of the ER adhesive was significantly higher for 5 wt.% MA-POSS-8 (17.9 ± 5.1 MPa) than for the control group (14.6 ± 3.6 MPa) and 10 wt.% MA-POSS-8 (12.8 ± 4.1 MPa), and more cohesive failures were observed. The SBS of the universal adhesive increased during aging, irrespective of the MA-POSS-8 concentration. 5 wt.% MA-POSS-8 improves the SBS of the ER adhesive and does not impair the SBS of the SE adhesive.

Processing-bias correction with DEBIAS-M improves cross-study generalization of microbiome-based prediction models.

Every step in common microbiome profiling protocols has variable efficiency for each microbe. For example, different DNA extraction kits may have different efficiency for Gram-positive and -negative bacteria. These variable efficiencies, combined with technical variation, create strong processing biases, which impede the identification of signals that are reproducible across studies and the development of generalizable and biologically interpretable prediction models. "Batch-correction" methods have been used to alleviate these issues computationally with some success. However, many make strong parametric assumptions which do not necessarily apply to microbiome data or processing biases, or require the use of an outcome variable, which risks overfitting. Lastly and importantly, existing transformations used to correct microbiome data are largely non-interpretable, and could, for example, introduce values to features that were initially mostly zeros. Altogether, processing bias currently compromises our ability to glean robust and generalizable biological insights from microbiome data. Here, we present DEBIAS-M (Domain adaptation with phenotype Estimation and Batch Integration Across Studies of the Microbiome), an interpretable framework for inference and correction of processing bias, which facilitates domain adaptation in microbiome studies. DEBIAS-M learns bias-correction factors for each microbe in each batch that simultaneously minimize batch effects and maximize cross-study associations with phenotypes. Using benchmarks of HIV and colorectal cancer classification from gut microbiome data, and cervical neoplasia prediction from cervical microbiome data, we demonstrate that DEBIAS-M outperforms batch-correction methods commonly used in the field. Notably, we show that the inferred bias-correction factors are stable, interpretable, and strongly associated with specific experimental protocols. Overall, we show that DEBIAS-M allows for better modeling of microbiome data and identification of interpretable signals that are reproducible across studies.

The CD58-CD2 axis is co-regulated with PD-L1 via CMTM6 and shapes anti-tumor immunity.

The cell-autonomous balance of immune-inhibitory and -stimulatory signals is a critical process in cancer immune evasion. Using patient-derived co-cultures, humanized mouse models, and single-cell RNA-sequencing of patient melanomas biopsied before and on immune checkpoint blockade, we find that intact cancer cell-intrinsic expression of CD58 and ligation to CD2 is required for anti-tumor immunity and is predictive of treatment response. Defects in this axis promote immune evasion through diminished T cell activation, impaired intratumoral T cell infiltration and proliferation, and concurrently increased PD-L1 protein stabilization. Through CRISPR-Cas9 and proteomics screens, we identify and validate CMTM6 as critical for CD58 stability and upregulation of PD-L1 upon CD58 loss. Competition between CD58 and PD-L1 for CMTM6 binding determines their rate of endosomal recycling over lysosomal degradation. Overall, we describe an underappreciated yet critical axis of cancer immunity and provide a molecular basis for how cancer cells balance immune inhibitory and stimulatory cues.

Molecular imaging of chemokine-like receptor 1 (CMKLR1) in experimental acute lung injury.

The lack of techniques for noninvasive imaging of inflammation has challenged precision medicine management of acute respiratory distress syndrome (ARDS). Here, we determined the potential of positron emission tomography (PET) of chemokine-like receptor-1 (CMKLR1) to monitor lung inflammation in a murine model of lipopolysaccharide-induced injury. Lung uptake of a CMKLR1-targeting radiotracer, [64Cu]NODAGA-CG34, was significantly increased in lipopolysaccharide-induced injury, correlated with the expression of multiple inflammatory markers, and reduced by dexamethasone treatment. Monocyte-derived macrophages, followed by interstitial macrophages and monocytes were the major CMKLR1-expressing leukocytes contributing to the increased tracer uptake throughout the first week of lipopolysaccharide-induced injury. The clinical relevance of CMKLR1 as a biomarker of lung inflammation in ARDS was confirmed using single-nuclei RNA-sequencing datasets which showed significant increases in CMKLR1 expression among transcriptionally distinct subsets of lung monocytes and macrophages in COVID-19 patients vs. controls. CMKLR1-targeted PET is a promising strategy to monitor the dynamics of lung inflammation and response to anti-inflammatory treatment in ARDS.

Multimodal single-cell and whole-genome sequencing of small, frozen clinical specimens.

Single-cell genomics enables dissection of tumor heterogeneity and molecular underpinnings of drug response at an unprecedented resolution1-11. However, broad clinical application of these methods remains challenging, due to several practical and preanalytical challenges that are incompatible with typical clinical care workflows, namely the need for relatively large, fresh tissue inputs. In the present study, we show that multimodal, single-nucleus (sn)RNA/T cell receptor (TCR) sequencing, spatial transcriptomics and whole-genome sequencing (WGS) are feasible from small, frozen tissues that approximate routinely collected clinical specimens (for example, core needle biopsies). Compared with data from sample-matched fresh tissue, we find a similar quality in the biological outputs of snRNA/TCR-seq data, while reducing artifactual signals and compositional biases introduced by fresh tissue processing. Profiling sequentially collected melanoma samples from a patient treated in the KEYNOTE-001 trial12, we resolved cellular, genomic, spatial and clonotype dynamics that represent molecular patterns of heterogeneous intralesional evolution during anti-programmed cell death protein 1 therapy. To demonstrate applicability to banked biospecimens of rare diseases13, we generated a single-cell atlas of uveal melanoma liver metastasis with matched WGS data. These results show that single-cell genomics from archival, clinical specimens is feasible and provides a framework for translating these methods more broadly to the clinical arena.

B-cells Drive Response to PD-1 Blockade in Glioblastoma Upon Neutralization of TGFß-mediated Immunosuppression.

Immunotherapy has revolutionized cancer treatment but has yet to be translated into brain tumors. Studies in other solid tumors suggest a central role of B-cell immunity in driving immune-checkpoint-blockade efficacy. Using single-cell and single-nuclei transcriptomics of human glioblastoma and melanoma brain metastasis, we found that tumor-associated B-cells have high expression of checkpoint molecules, known to block B-cell-receptor downstream effector function such as plasmablast differentiation and antigen-presentation. We also identified TGFß-1/TGFß receptor-2 interaction as a crucial modulator of B-cell suppression. Treatment of glioblastoma patients with pembrolizumab induced expression of B-cell checkpoint molecules and TGFß-receptor-2. Abrogation of TGFß using different conditional knockouts expanded germinal-center-like intratumoral B-cells, enhancing immune-checkpoint-blockade efficacy. Finally, blocking αVß8 integrin (which controls the release of active TGFß) and PD-1 significantly increased B-cell-dependent animal survival and immunological memory. Our study highlights the importance of intratumoral B-cell immunity and a remodeled approach to boost the effects of immunotherapy against brain tumors.

A single-nucleus and spatial transcriptomic atlas of the COVID-19 liver reveals topological, functional, and regenerative organ disruption in patients.

The molecular underpinnings of organ dysfunction in acute COVID-19 and its potential long-term sequelae are under intense investigation. To shed light on these in the context of liver function, we performed single-nucleus RNA-seq and spatial transcriptomic profiling of livers from 17 COVID-19 decedents. We identified hepatocytes positive for SARS-CoV-2 RNA with an expression phenotype resembling infected lung epithelial cells. Integrated analysis and comparisons with healthy controls revealed extensive changes in the cellular composition and expression states in COVID-19 liver, reflecting hepatocellular injury, ductular reaction, pathologic vascular expansion, and fibrogenesis. We also observed Kupffer cell proliferation and erythrocyte progenitors for the first time in a human liver single-cell atlas, resembling similar responses in liver injury in mice and in sepsis, respectively. Despite the absence of a clinical acute liver injury phenotype, endothelial cell composition was dramatically impacted in COVID-19, concomitantly with extensive alterations and profibrogenic activation of reactive cholangiocytes and mesenchymal cells. Our atlas provides novel insights into liver physiology and pathology in COVID-19 and forms a foundational resource for its investigation and understanding.

Contribution of Trp63CreERT2-labeled cells to alveolar regeneration is independent of tuft cells.

Viral infection often causes severe damage to the lungs, leading to the appearance of ectopic basal cells (EBCs) and tuft cells in the lung parenchyma. Thus far, the roles of these ectopic epithelial cells in alveolar regeneration remain controversial. Here, we confirm that the ectopic tuft cells are originated from EBCs in mouse models and COVID-19 lungs. The differentiation of tuft cells from EBCs is promoted by Wnt inhibition while suppressed by Notch inhibition. Although progenitor functions have been suggested in other organs, pulmonary tuft cells don't proliferate or give rise to other cell lineages. Consistent with previous reports, Trp63CreERT2 and KRT5-CreERT2-labeled ectopic EBCs do not exhibit alveolar regeneration potential. Intriguingly, when tamoxifen was administrated post-viral infection, Trp63CreERT2 but not KRT5-CreERT2 labels islands of alveolar epithelial cells that are negative for EBC biomarkers. Furthermore, germline deletion of Trpm5 significantly increases the contribution of Trp63CreERT2-labeled cells to the alveolar epithelium. Although Trpm5 is known to regulate tuft cell development, complete ablation of tuft cell production fails to improve alveolar regeneration in Pou2f3-/- mice, implying that Trpm5 promotes alveolar epithelial regeneration through a mechanism independent of tuft cells.

Dissecting the treatment-naive ecosystem of human melanoma brain metastasis.

Melanoma brain metastasis (MBM) frequently occurs in patients with advanced melanoma; yet, our understanding of the underlying salient biology is rudimentary. Here, we performed single-cell/nucleus RNA-seq in 22 treatment-naive MBMs and 10 extracranial melanoma metastases (ECMs) and matched spatial single-cell transcriptomics and T cell receptor (TCR)-seq. Cancer cells from MBM were more chromosomally unstable, adopted a neuronal-like cell state, and enriched for spatially variably expressed metabolic pathways. Key observations were validated in independent patient cohorts, patient-derived MBM/ECM xenograft models, RNA/ATAC-seq, proteomics, and multiplexed imaging. Integrated spatial analyses revealed distinct geography of putative cancer immune evasion and evidence for more abundant intra-tumoral B to plasma cell differentiation in lymphoid aggregates in MBM. MBM harbored larger fractions of monocyte-derived macrophages and dysfunctional TOX+CD8+ T cells with distinct expression of immune checkpoints. This work provides comprehensive insights into MBM biology and serves as a foundational resource for further discovery and therapeutic exploration.

Risk factors for repeated general anesthesia for dental treatment of adult patients with intellectual and/or physical disabilities.

AIM: Repeated dental treatment of patients with intellectual and/or physical disabilities under general anesthesia (GA) often becomes necessary. This study aimed to identify potential risk factors predictive of repeated dental treatment under general anesthesia. MATERIALS AND METHODS: Data of adult patients with intellectual and/or physical disabilities receiving dental treatment under GA within a time period of 7 years were analyzed (n = 203, mean age: 41.0 ± 14.9 years). All patients received comprehensive dental treatment (professional tooth cleaning, periodontal therapy, composite restorations, and/or extractions); patients receiving extractions only for emergency dental care were not included as a second intervention for restorative treatment often followed. Demographic, anamnestic, oral health, and treatment factors were obtained from dental records. Duration of intervals without dental treatment under GA was assessed using Kaplan-Meier statistics. Potential predictive factors were tested using univariate and multivariate cox regression analyses. RESULTS: Thirty-five patients (17.2%) received a second and five patients (2.5%) a third dental treatment under GA during that period. In the univariate analysis, patients' age, living situation, and nutrition were associated with repeated GA. In the multivariate Cox regression analysis, only nutrition remained significant. Risk for repeated treatment increased if patients were tube-fed (HR: 7.54, p = 0.001) or received pureed/liquid food (HR: 4.32, p = 0.007) compared to nutrition without limitation. CONCLUSION: In adult patients with intellectual and/or physical disabilities, nutrition affects the risk for repeated dental treatment under GA. CLINICAL RELEVANCE: Identification of risk factors making repeated dental treatment under GA of patients with intellectual and/or physical disabilities more likely is essential to adjust preventive measures.

A molecular single-cell lung atlas of lethal COVID-19.

Respiratory failure is the leading cause of death in patients with severe SARS-CoV-2 infection1,2, but the host response at the lung tissue level is poorly understood. Here we performed single-nucleus RNA sequencing of about 116,000 nuclei from the lungs of nineteen individuals who died of COVID-19 and underwent rapid autopsy and seven control individuals. Integrated analyses identified substantial alterations in cellular composition, transcriptional cell states, and cell-to-cell interactions, thereby providing insight into the biology of lethal COVID-19. The lungs from individuals with COVID-19 were highly inflamed, with dense infiltration of aberrantly activated monocyte-derived macrophages and alveolar macrophages, but had impaired T cell responses. Monocyte/macrophage-derived interleukin-1ß and epithelial cell-derived interleukin-6 were unique features of SARS-CoV-2 infection compared to other viral and bacterial causes of pneumonia. Alveolar type 2 cells adopted an inflammation-associated transient progenitor cell state and failed to undergo full transition into alveolar type 1 cells, resulting in impaired lung regeneration. Furthermore, we identified expansion of recently described CTHRC1+ pathological fibroblasts3 contributing to rapidly ensuing pulmonary fibrosis in COVID-19. Inference of protein activity and ligand-receptor interactions identified putative drug targets to disrupt deleterious circuits. This atlas enables the dissection of lethal COVID-19, may inform our understanding of long-term complications of COVID-19 survivors, and provides an important resource for therapeutic development.

COVID-19 tissue atlases reveal SARS-CoV-2 pathology and cellular targets.

COVID-19, which is caused by SARS-CoV-2, can result in acute respiratory distress syndrome and multiple organ failure1-4, but little is known about its pathophysiology. Here we generated single-cell atlases of 24 lung, 16 kidney, 16 liver and 19 heart autopsy tissue samples and spatial atlases of 14 lung samples from donors who died of COVID-19. Integrated computational analysis uncovered substantial remodelling in the lung epithelial, immune and stromal compartments, with evidence of multiple paths of failed tissue regeneration, including defective alveolar type 2 differentiation and expansion of fibroblasts and putative TP63+ intrapulmonary basal-like progenitor cells. Viral RNAs were enriched in mononuclear phagocytic and endothelial lung cells, which induced specific host programs. Spatial analysis in lung distinguished inflammatory host responses in lung regions with and without viral RNA. Analysis of the other tissue atlases showed transcriptional alterations in multiple cell types in heart tissue from donors with COVID-19, and mapped cell types and genes implicated with disease severity based on COVID-19 genome-wide association studies. Our foundational dataset elucidates the biological effect of severe SARS-CoV-2 infection across the body, a key step towards new treatments.

Integrative genomics approach identifies molecular features associated with early-stage ovarian carcinoma histotypes.

Ovarian cancer comprises multiple subtypes (clear-cell (CCC), endometrioid (EC), high-grade serous (HGSC), low-grade serous (LGSC), and mucinous carcinomas (MC)) with differing molecular and clinical behavior. However, robust histotype-specific biomarkers for clinical use have yet to be identified. Here, we utilized a multi-omics approach to identify novel histotype-specific genetic markers associated with ovarian carcinoma histotypes (CCC, EC, HGSC, and MC) using DNA methylation, DNA copy number alteration and RNA sequencing data for 96 primary invasive early-stage (stage I and II) ovarian carcinomas. More specifically, the DNA methylation analysis revealed hypermethylation for CCC in comparison with the other histotypes. Moreover, copy number imbalances and novel chromothripsis-like rearrangements (n = 64) were identified in ovarian carcinoma, with the highest number of chromothripsis-like patterns in HGSC. For the 1000 most variable transcripts, underexpression was most prominent for all histotypes in comparison with normal ovarian samples. Overall, the integrative approach identified 46 putative oncogenes (overexpressed, hypomethylated and DNA gain) and three putative tumor suppressor genes (underexpressed, hypermethylated and DNA loss) when comparing the different histotypes. In conclusion, the current study provides novel insights into molecular features associated with early-stage ovarian carcinoma that may improve patient stratification and subclassification of the histotypes.

Optimization of cell viability assays to improve replicability and reproducibility of cancer drug sensitivity screens.

Cancer drug development has been riddled with high attrition rates, in part, due to poor reproducibility of preclinical models for drug discovery. Poor experimental design and lack of scientific transparency may cause experimental biases that in turn affect data quality, robustness and reproducibility. Here, we pinpoint sources of experimental variability in conventional 2D cell-based cancer drug screens to determine the effect of confounders on cell viability for MCF7 and HCC38 breast cancer cell lines treated with platinum agents (cisplatin and carboplatin) and a proteasome inhibitor (bortezomib). Variance component analysis demonstrated that variations in cell viability were primarily associated with the choice of pharmaceutical drug and cell line, and less likely to be due to the type of growth medium or assay incubation time. Furthermore, careful consideration should be given to different methods of storing diluted pharmaceutical drugs and use of DMSO controls due to the potential risk of evaporation and the subsequent effect on dose-response curves. Optimization of experimental parameters not only improved data quality substantially but also resulted in reproducible results for bortezomib- and cisplatin-treated HCC38, MCF7, MCF-10A, and MDA-MB-436 cells. Taken together, these findings indicate that replicability (the same analyst re-performs the same experiment multiple times) and reproducibility (different analysts perform the same experiment using different experimental conditions) for cell-based drug screens can be improved by identifying potential confounders and subsequent optimization of experimental parameters for each cell line.

A 17-marker panel for global genomic instability in breast cancer.

Genomic instability is a hallmark of cancer that plays a pivotal role in breast cancer development and evolution. A number of existing prognostic gene expression signatures for breast cancer are based on proliferation-related genes. Here, we identified a 17-marker panel associated with genome stability. A total of 136 primary breast carcinomas were stratified by genome stability. Matched gene expression profiles showed an innate segregation based on genome stability. We identified a 17-marker panel stratifying the training and validation cohorts into high- and low-risk patients. The 17 genes associated with genomic instability strongly impacted clinical outcome in breast cancer. Pathway analyses determined chromosome organisation, cell cycle regulation, and RNA processing as the underlying biological processes, thereby offering options for drug development and treatment tailoring. Our work supports the applicability of the 17-marker panel to improve clinical outcome prediction for breast cancer patients based on a signature accounting for genomic instability.

Immunohistochemical validation of COL3A1, GPR158 and PITHD1 as prognostic biomarkers in early-stage ovarian carcinomas.

BACKGROUND: Ovarian cancer is the main cause of gynecological cancer-associated death. However, 5-year survival rates differ dramatically between the five main ovarian carcinoma histotypes. Therefore, we need to have a better understanding of the mechanisms that promote histotype-specific ovarian carcinogenesis and identify novel prognostic biomarkers. METHODS: Here, we evaluated the prognostic role of 29 genes for early-stage (I and II) ovarian carcinomas (n = 206) using immunohistochemistry (IHC). RESULTS: We provide evidence of aberrant protein expression patterns for Collagen type III alpha 1 chain (COL3A1), G protein-coupled receptor 158 (GPR158) and PITH domain containing 1 (PITHD1). Kaplan-Meier survival analysis revealed that COL3A1 expression was associated with shorter overall survival in the four major histotypes of epithelial ovarian carcinoma patients (P value = 0.026, HR = 2.99 (95% CI 1.089-8.19)). Furthermore, GPR158 and PITHD1 were shown to be histotype-specific prognostic biomarkers, with elevated GPR158 expression patterns in mucinous ovarian carcinoma patients with unfavorable overall survival (P value = 0.00043, HR = 6.13 (95% CI 1.98-18.98)), and an association with lower PITHD1 protein expression and unfavorable overall and disease-specific survival in clear-cell ovarian carcinoma patients (P value = 0.012, HR = 0.22 (95% CI 0.058-0.80); P value = 0.003, HR = 0.17 (95% CI 0.043-0.64)). CONCLUSIONS: The novel biomarkers identified here may improve prognostication at the time of diagnosis and may assist in the development of future individualized therapeutic strategies for ovarian carcinoma patients.

Radiation-induced genomic instability in breast carcinomas of the Swedish hemangioma cohort.

Radiation-induced genomic instability (GI) is hypothesized to persist after exposure and ultimately promote carcinogenesis. Based on the absorbed dose to the breast, an increased risk of developing breast cancer was shown in the Swedish hemangioma cohort that was treated with radium-226 for skin hemangioma as infants. Here, we screened 31 primary breast carcinomas for genetic alterations using the OncoScan CNV Plus Assay to assess GI and chromothripsis-like patterns associated with the absorbed dose to the breast. Higher absorbed doses were associated with increased numbers of copy number alterations in the tumor genome and thus a more unstable genome. Hence, the observed dose-dependent GI in the tumor genome is a measurable manifestation of the long-term effects of irradiation. We developed a highly predictive Cox regression model for overall survival based on the interaction between absorbed dose and GI. The Swedish hemangioma cohort is a valuable cohort to investigate the biological relationship between absorbed dose and GI in irradiated humans. This work gives a biological basis for improved risk assessment to minimize carcinogenesis as a secondary disease after radiation therapy.

Questionnaire Survey on the Management of Erosive Tooth Wear.

PURPOSE: This questionnaire survey aimed to analyse management strategies for erosive tooth wear and to identify factors influencing dentists' decision-making. MATERIALS AND METHODS: A questionnaire presenting clinical cases with erosive tooth wear on anterior and posterior teeth (BEWE scores 1 to 3) was sent electronically to German dentists (n = 13.683). Statistical analysis was performed by Wilcoxon signed-rank tests, Kruskal-Wallis-tests and Fisher's exact tests (p <0.05). RESULTS: Only 455 dentists (3.3%, mean age: 52.3 ± 9.6) participated. Suggested therapeutic measures were statistically significantly different between BEWE 1, 2 and 3 (p <0.001) and between anterior and posterior teeth with BEWE scores 1 or 2 (p ≤0.025). Initial erosive lesions (BEWE 1) were mainly treated by information about the main causes and/or preventive measures (posterior teeth: 75.6%, anterior teeth: 64.4%), only 20.0% and 31.3% considered restorative treatment for posterior and anterior teeth, respectively. For teeth presenting score 2, a very high proportion of dentists considered restorative treatment (posterior teeth: 60.6%) additionally to prevention, especially when anterior teeth (91.0%) were affected. In case of severe erosive lesions (BEWE 3), the vast majority of dentists considered restorative treatment (posterior teeth: 98.3%, anterior teeth: 99.8%). The decision-making was mainly dependent on the lesion depth, size of affected surfaces and the presence of pain. Fluoride agents and agents containing tin chloride or tin fluoride were most frequently recommended as preventive measures. If distinct defects (BEWE 2) were treated restoratively, mainly composite restorations were performed (posterior teeth: 72.0%, anterior teeth: 90.5%). Severe defects (BEWE 3) were mostly restored with ceramic restorations (posterior teeth: 66.1%, anterior teeth: 66.6%). CONCLUSION: Stepwise management of erosive tooth wear was observed. Dentists' decision-making was related to severity and localisation of erosive tooth wear and to various patient-related factors (e.g. depth of lesion and size of affected surface per tooth).

Transcriptomic and genomic profiling of early-stage ovarian carcinomas associated with histotype and overall survival.

Ovarian cancer is the most lethal gynecological malignancy in the western world. Despite recent efforts to characterize ovarian cancer using molecular profiling, few targeted treatment options are currently available. Here, we examined genetic variants, fusion transcripts, SNP genotyping, and gene expression patterns for early-stage (I and II) ovarian carcinomas (n=96) in relation to clinicopathological characteristics and clinical outcome, thereby identifying novel genetic features of ovarian carcinomas. Furthermore, mutation frequencies of specific genetic variants and/or their gene expression patterns were associated with histotype and overall survival, e.g. SLC28A2 (mucinous ovarian carcinoma histotype), ARCN1 (low expression in 0-2 year survival group), and tumor suppressor MTUS1 (mutation status and overall survival). The long non-coding RNA MALAT1 was identified as a highly promiscuous fusion transcript in ovarian carcinoma. Moreover, gene expression deregulation for 23 genes was associated with tumor aggressiveness. Taken together, the novel biomarkers identified here may improve ovarian carcinoma subclassification and patient stratification according to histotype and overall survival.