Preoperative prolapse phenotype is predictive of surgical outcome with minimally invasive sacrocolpopexy.

BACKGROUND: The gold-standard treatment for advanced pelvic organ prolapse is sacrocolpopexy. However, the preoperative features of prolapse that predict optimal outcomes are unknown. OBJECTIVE: This study aimed to develop a clinical prediction model that uses preoperative scores on the Pelvic Organ Prolapse Quantification examination to predict outcomes after minimally invasive sacrocolpopexy for stages 2, 3, and 4 uterovaginal prolapse and vaginal vault prolapse. STUDY DESIGN: A 2-institution database of pre- and postoperative variables from 881 cases of minimally invasive sacrocolpopexy was analyzed. Data from patients were analyzed in the following 4 groups: stage 2 uterovaginal prolapse, stage 3 to 4 uterovaginal prolapse, stage 2 vaginal vault prolapse, and stage 3 to 4 vaginal vault prolapse. Unsupervised machine learning was used to identify clusters and investigate associations between clusters and outcome. The k-means clustering analysis was performed with preoperative Pelvic Organ Prolapse Quantification points and stratified by previous hysterectomy status. The "optimal" surgical outcome was defined as postoperative Pelvic Organ Prolapse Quantification stage <2. Demographic variables were compared by cluster with Student t and chi-square tests. Odds ratios were calculated to determine whether clusters could predict the outcome. Age at surgery, body mass index, and previous prolapse surgery were used for adjusted odds ratios. RESULTS: Five statistically distinct prolapse clusters (phenotypes C, A, A>P, P, and P>A) were found. These phenotypes reflected the predominant region of prolapse (apical, anterior, or posterior) and whether support was preserved in the nonpredominant region. Phenotype A (anterior compartment prolapse predominant, posterior support preserved) was found in all 4 groups of patients and was considered the reference in the analysis. In 111 patients with stage 2 uterovaginal prolapse, phenotypes A and A>P (greater anterior prolapse than posterior prolapse) were found, and patients with phenotype A were more likely than those with phenotype A>P to have an optimal surgical outcome. In 401 patients with stage 3 to 4 uterovaginal prolapse, phenotypes C (apical compartment predominant, prolapse in all compartments), A, and A>P were found, and patients with phenotype A>P were more likely than those with phenotype A to have ideal surgical outcome. In 72 patients with stage 2 vaginal vault prolapse, phenotypes A, A>P, and P (posterior compartment predominant, anterior support preserved) were found, and those with phenotype A>P were less likely to have an ideal outcome than patients with phenotype A. In 297 patients with stage 3 to 4 vaginal vault prolapse, phenotypes C, A, and P>A (prolapse greater in posterior than in anterior compartment) were found, but there were no significant differences in rate of ideal outcome between phenotypes. CONCLUSION: Five anatomic phenotypes based on preoperative Pelvic Organ Prolapse Quantification scores were present in patients with stages 2 and 3 to 4 uterovaginal prolapse and vaginal vault prolapse. These phenotypes are predictive of surgical outcome after minimally invasive sacrocolpopexy. Further work needs to confirm the presence and predictive nature of these phenotypes. In addition, whether the phenotypes represent a progression of prolapse or discrete prolapse presentations resulting from different anatomic and life course risk profiles is unknown. These phenotypes may be useful in surgical counseling and planning.

Computational repurposing of oncology drugs through off-target drug binding interactions from pharmacological databases.

PURPOSE: Systematic repurposing of approved medicines for another indication may accelerate drug development in oncology. We present a strategy combining biomarker testing with drug repurposing to identify new treatments for patients with advanced cancer. METHODS: Tumours were sequenced with the Illumina TruSight Oncology 500 (TSO-500) platform or the FoundationOne CDx panel. Mutations were screened by two medical oncologists and pathogenic mutations were categorised referencing literature. Variants of unknown significance were classified as potentially pathogenic using plausible mechanisms and computational prediction of pathogenicity. Gain of function (GOF) mutations were evaluated through repurposing databases Probe Miner (PM), Broad Institute Drug Repurposing Hub (Broad Institute DRH) and TOPOGRAPH. GOF mutations were repurposing events if identified in PM, not indexed in TOPOGRAPH and excluding mutations with a known Food and Drug Administration (FDA)-approved biomarker. The computational repurposing approach was validated by evaluating its ability to identify FDA-approved biomarkers. The total repurposable genome was identified by evaluating all possible gene-FDA drug-approved combinations in the PM dataset. RESULTS: The computational repurposing approach was accurate at identifying FDA therapies with known biomarkers (94%). Using next-generation sequencing molecular reports (n = 94), a meaningful percentage of patients (14%) could have an off-label therapeutic identified. The frequency of theoretical drug repurposing events in The Cancer Genome Atlas pan-cancer dataset was 73% of the samples in the cohort. CONCLUSION: A computational drug repurposing approach may assist in identifying novel repurposing events in cancer patients with no access to standard therapies. Further validation is needed to confirm a precision oncology approach using drug repurposing.

DDR2-regulated arginase activity in ovarian cancer-associated fibroblasts promotes collagen production and tumor progression.

Ovarian cancer has poor survival outcomes particularly for advanced stage, metastatic disease. Metastasis is promoted by interactions of stromal cells, such as cancer-associated fibroblasts (CAFs) in the tumor microenvironment (TME), with tumor cells. CAFs play a key role in tumor progression by remodeling the TME and extracellular matrix (ECM) to result in a more permissive environment for tumor progression. It has been shown that fibroblasts, in particular myofibroblasts, utilize metabolism to support ECM remodeling. However, the intricate mechanisms by which CAFs support collagen production and tumor progression are poorly understood. In this study, we show that the fibrillar collagen receptor, Discoidin Domain Receptor 2 (DDR2), promotes collagen production in human and mouse omental CAFs through arginase activity. CAFs with high DDR2 or arginase promote tumor colonization in the omentum. In addition, DDR2-depleted CAFs had decreased ornithine levels leading to decreased collagen production and polyamine levels compared to WT control CAFs. Tumor cell invasion was decreased in the presence CAF conditioned media (CM) depleted of DDR2 or arginase-1, and this invasion defect was rescued in the presence of CM from DDR2-depleted CAFs that constitutively overexpressed arginase-1. Similarly, the addition of exogenous polyamines to CM from DDR2-depleted CAFs led to increased tumor cell invasion. We detected SNAI1 protein at the promoter region of the arginase-1 gene, and DDR2-depleted CAFs had decreased levels of SNAI1 protein at the arginase-1 promoter region. Furthermore, high stromal arginase-1 expression correlated with poor survival in ovarian cancer patients. These findings highlight how DDR2 regulates collagen production by CAFs in the tumor microenvironment by controlling the transcription of arginase-1, and CAFs are a major source of arginase activity and L-arginine metabolites in ovarian cancer models.

Stromal DDR2 Promotes Ovarian Cancer Metastasis through Regulation of Metabolism and Secretion of Extracellular Matrix Proteins.

Ovarian cancer is the leading cause of gynecologic cancer-related deaths. The propensity for metastasis within the peritoneal cavity is a driving factor for the poor outcomes associated with this disease, but there is currently no effective therapy targeting metastasis. In this study, we investigate the contribution of stromal cells to ovarian cancer metastasis and identify normal stromal cell expression of the collagen receptor, discoidin domain receptor 2 (DDR2), that acts to facilitate ovarian cancer metastasis. In vivo, global genetic inactivation of Ddr2 impairs the ability of Ddr2-expressing syngeneic ovarian cancer cells to spread throughout the peritoneal cavity. Specifically, DDR2 expression in mesothelial cells lining the peritoneal cavity facilitates tumor cell attachment and clearance. Subsequently, omentum fibroblast expression of DDR2 promotes tumor cell invasion. Mechanistically, we find DDR2-expressing fibroblasts are more energetically active, such that DDR2 regulates glycolysis through AKT/SNAI1 leading to suppressed fructose-1,6-bisphosphatase and increased hexokinase activity, a key glycolytic enzyme. Upon inhibition of DDR2, we find decreased protein synthesis and secretion. Consequently, when DDR2 is inhibited, there is reduction in secreted extracellular matrix proteins important for metastasis. Specifically, we find that fibroblast DDR2 inhibition leads to decreased secretion of the collagen crosslinker, LOXL2. Adding back LOXL2 to DDR2 deficient fibroblasts rescues the ability of tumor cells to invade. Overall, our results suggest that stromal cell expression of DDR2 is an important mediator of ovarian cancer metastasis. IMPLICATIONS: DDR2 is highly expressed by stromal cells in ovarian cancer that can mediate metastasis and is a potential therapeutic target in ovarian cancer.

Integrative analysis reveals marker genes for intestinal mucosa barrier repairing in clinical patients.

This study aims to identify biomarkers of intestinal repair and provide potential therapeutic clues for improving functional recovery and prognostic performance after intestinal inflammation or injury. Here, we conducted a large-scale screening of multiple transcriptomic and scRNA-seq datasets of patients with inflammatory bowel disease (IBD), and identified 10 marker genes that potentially contribute to intestinal barrier repairing: AQP8, SULT1A1, HSD17B2, PADI2, SLC26A2, SELENBP1, FAM162A, TNNC2, ACADS, and TST. Analysis of a published scRNA-seq dataset revealed that expression of these healing markers were specific to absorptive cell types in intestinal epithelium. Furthermore, we conducted a clinical study where 11 patients underwent ileum resection demonstrating that upregulation of post-operative AQP8 and SULT1A1 expression were associated with improved recovery of bowel functions after surgery-induced intestinal injury, making them confident biomarkers of intestinal healing as well as potential prognostic markers and therapeutic targets for patients with impaired intestinal barrier functions.

RAD51 Foci as a Biomarker Predictive of Platinum Chemotherapy Response in Ovarian Cancer.

PURPOSE: To determine the ability of RAD51 foci to predict platinum chemotherapy response in high-grade serous ovarian cancer (HGSOC) patient-derived samples. EXPERIMENTAL DESIGN: RAD51 and γH2AX nuclear foci were evaluated by immunofluorescence in HGSOC patient-derived cell lines (n = 5), organoids (n = 11), and formalin-fixed, paraffin-embedded tumor samples (discovery n = 31, validation n = 148). Samples were defined as RAD51-High if >10% of geminin-positive cells had ≥5 RAD51 foci. Associations between RAD51 scores, platinum chemotherapy response, and survival were evaluated. RESULTS: RAD51 scores correlated with in vitro response to platinum chemotherapy in established and primary ovarian cancer cell lines (Pearson r = 0.96, P = 0.01). Organoids from platinum-nonresponsive tumors had significantly higher RAD51 scores than those from platinum-responsive tumors (P < 0.001). In a discovery cohort, RAD51-Low tumors were more likely to have a pathologic complete response (RR, 5.28; P < 0.001) and to be platinum-sensitive (RR, ∞; P = 0.05). The RAD51 score was predictive of chemotherapy response score [AUC, 0.90; 95% confidence interval (CI), 0.78-1.0; P < 0.001). A novel automatic quantification system accurately reflected the manual assay (92%). In a validation cohort, RAD51-Low tumors were more likely to be platinum-sensitive (RR, ∞; P < 0.001) than RAD51-High tumors. Moreover, RAD51-Low status predicted platinum sensitivity with 100% positive predictive value and was associated with better progression-free (HR, 0.53; 95% CI, 0.33-0.85; P < 0.001) and overall survival (HR, 0.43; 95% CI, 0.25-0.75; P = 0.003) than RAD51-High status. CONCLUSIONS: RAD51 foci are a robust marker of platinum chemotherapy response and survival in ovarian cancer. The utility of RAD51 foci as a predictive biomarker for HGSOC should be tested in clinical trials.

UHRF1/UBE2L6/UBR4-mediated ubiquitination regulates EZH2 abundance and thereby melanocytic differentiation phenotypes in melanoma.

Cellular heterogeneity in cancer is linked to disease progression and therapy response, although mechanisms regulating distinct cellular states within tumors are not well understood. We identified melanin pigment content as a major source of cellular heterogeneity in melanoma and compared RNAseq data from high-pigmented (HPCs) and low-pigmented melanoma cells (LPCs), suggesting EZH2 as a master regulator of these states. EZH2 protein was found to be upregulated in LPCs and inversely correlated with melanin deposition in pigmented patient melanomas. Surprisingly, conventional EZH2 methyltransferase inhibitors, GSK126 and EPZ6438, had no effect on LPC survival, clonogenicity and pigmentation, despite fully inhibiting methyltransferase activity. In contrast, EZH2 silencing by siRNA or degradation by DZNep or MS1943 inhibited growth of LPCs and induced HPCs. As the proteasomal inhibitor MG132 induced EZH2 protein in HPCs, we evaluated ubiquitin pathway proteins in HPC vs LPCs. Biochemical assays and animal studies demonstrated that in LPCs, the E2-conjugating enzyme UBE2L6 depletes EZH2 protein in cooperation with UBR4, an E3 ligase, via ubiquitination at EZH2's K381 residue, and is downregulated in LPCs by UHRF1-mediated CpG methylation. Targeting UHRF1/UBE2L6/UBR4-mediated regulation of EZH2 offers potential for modulating the activity of this oncoprotein in contexts in which conventional EZH2 methyltransferase inhibitors are ineffective.

Cystathionine gamma-lyase (Cth) induces efferocytosis in macrophages via ERK1/2 to modulate intestinal barrier repair.

BACKGROUND: The inflammatory response induced by intestinal ischaemia‒reperfusion injury (I/R) is closely associated with infectious complications and mortality in critically ill patients, and the timely and effective clearance of apoptotic cells is an important part of reducing the inflammatory response. Studies have shown that the efferocytosis by phagocytes plays an important role. Recently, studies using small intestine organoid models showed that macrophage efferocytosis could promote the repair capacity of the intestinal epithelium. However, no studies have reported efferocytosis in the repair of I/R in animal models. RESULTS: We used an in vivo efferocytosis assay and discovered that macrophage efferocytosis played an indispensable role in repairing and maintaining intestinal barrier function after I/R. In addition, the specific molecular mechanism that induced macrophage efferocytosis was Cth-ERK1/2 dependent. We found that Cth drove macrophage efferocytosis in vivo and in vitro. Overexpression/silencing Cth promoted/inhibited the ERK1/2 pathway, respectively, which in turn affected efferocytosis and mediated intestinal barrier recovery. In addition, we found that the levels of Cth and macrophage efferocytosis were positively correlated with the recovery of intestinal function in clinical patients. CONCLUSION: Cth can activate the ERK1/2 signalling pathway, induce macrophage efferocytosis, and thus promote intestinal barrier repair. Video Abstract.

GAS6/AXL Inhibition Enhances Ovarian Cancer Sensitivity to Chemotherapy and PARP Inhibition through Increased DNA Damage and Enhanced Replication Stress.

Over 80% of women with high-grade serous ovarian cancer (HGSOC) develop tumor resistance to chemotherapy and die of their disease. There are currently no FDA-approved agents to improve sensitivity to first-line platinum- and taxane-based chemotherapy or to PARP inhibitors. Here, we tested the hypothesis that expression of growth arrest-specific 6 (GAS6), the ligand of receptor tyrosine kinase AXL, is associated with chemotherapy response and that sequestration of GAS6 with AVB-S6-500 (AVB-500) could improve tumor response to chemotherapy and PARP inhibitors. We found that GAS6 levels in patient tumor and serum samples collected before chemotherapy correlated with ovarian cancer chemoresponse and patient survival. Compared with chemotherapy alone, AVB-500 plus carboplatin and/or paclitaxel led to decreased ovarian cancer-cell survival in vitro and tumor burden in vivo. Cells treated with AVB-500 plus carboplatin had more DNA damage, slower DNA replication fork progression, and fewer RAD51 foci than cells treated with carboplatin alone, indicating AVB-500 impaired homologous recombination (HR). Finally, treatment with the PARP inhibitor olaparib plus AVB-500 led to decreased ovarian cancer-cell survival in vitro and less tumor burden in vivo. Importantly, this effect was seen in HR-proficient and HR-deficient ovarian cancer cells. Collectively, our findings suggest that GAS6 levels could be used to predict response to carboplatin and AVB-500 could be used to treat platinum-resistant, HR-proficient HGSOC. IMPLICATIONS: GAS6/AXL is a novel target to sensitize ovarian cancers to carboplatin and olaparib. Additionally, GAS6 levels can be associated with response to carboplatin treatment.

Therapeutic Inhibition of the Receptor Tyrosine Kinase AXL Improves Sensitivity to Platinum and Taxane in Ovarian Cancer.

Ovarian cancer, one of the deadliest malignancies in female cancer patients, is characterized by recurrence and poor response to cytotoxic chemotherapies. Fewer than 30% of patients with resistant disease will respond to additional chemotherapy treatments. This study aims to determine whether and how inhibition of the receptor tyrosine kinase AXL can restore sensitivity to first-line platinum and taxane therapy in ovarian cancer. AXL staining was quantified in a patient tissue microarray and correlated with chemoresponse of patients. We used small hairpin RNAs to knock down AXL expression and the small-molecule inhibitor BGB324 to inhibit AXL and assessed sensitivity of cell lines and primary patient-derived cells to chemotherapy. We quantified platinum accumulation by inductivity-coupled plasma phase mass spectrometry. Finally, we treated chemoresistant patient-derived xenografts with chemotherapy, BGB324, or chemotherapy plus BGB324 and monitored tumor burden. AXL expression was higher in chemoresistant patient tumors and cell lines than in chemosensitive tumors and cell lines. AXL staining significantly predicted chemoresponse. Knockdown and inhibition of AXL dose-dependently improved response to paclitaxel and carboplatin in both cell lines and primary cells. AXL inhibition increased platinum accumulation by 2-fold (*, P < 0.05). In vivo studies indicated that AXL inhibition enhanced the ability of chemotherapy to prevent tumor growth (****, P < 0.0001). AXL contributes to platinum and taxane resistance in ovarian cancer, and inhibition of AXL improves chemoresponse and accumulation of chemotherapy drugs. This study supports continued investigation into AXL as a clinical target.

TWIST1 induces expression of discoidin domain receptor 2 to promote ovarian cancer metastasis.

The mesenchymal gene program has been shown to promote the metastatic progression of ovarian cancer; however, specific proteins induced by this program that lead to these metastatic behaviors have not been identified. Using patient derived tumor cells and established human ovarian tumor cell lines, we find that the Epithelial-to-Mesenchymal Transition inducing factor TWIST1 drives expression of discoidin domain receptor 2 (DDR2), a receptor tyrosine kinase (RTK) that recognizes fibrillar collagen as ligand. The expression and action of DDR2 was critical for mesothelial cell clearance, invasion and migration in ovarian tumor cells. It does so, in part, by upregulating expression and activity of matrix remodeling enzymes that lead to increased cleavage of fibronectin and spreading of tumor cells. Additionally, DDR2 stabilizes SNAIL1, allowing for sustained mesenchymal phenotype. In patient derived ovarian cancer specimens, DDR2 expression correlated with enhanced invasiveness. DDR2 expression was associated with advanced stage ovarian tumors and metastases. In vivo studies demonstrated that the presence of DDR2 is critical for ovarian cancer metastasis. These findings indicate that the collagen receptor DDR2 is critical for multiple steps of ovarian cancer progression to metastasis, and thus, identifies DDR2 as a potential new target for the treatment of metastatic ovarian cancer.

Benefit of combination chemotherapy and radiation stratified by grade of stage IIIC endometrial cancer.

OBJECTIVE: The optimal strategy for adjuvant therapy in stage IIIC endometrial cancer has not been determined. Our aim was to evaluate survival benefit of different treatments and to investigate if benefit varied by histologic grade. METHODS: We identified 199 patients with stage IIIC endometrial cancer from 2000 to 2012 through the Siteman Cancer Center registry. All patients underwent surgical staging followed by no adjuvant therapy (NAT), radiation (RT), chemotherapy (CT) or chemoradiation (CRT). The association between adjuvant treatment and overall survival was explored using Kaplan-Meier plots and multivariable Cox regression analysis. Multivariable analysis was stratified by low- or high-grade to explore the interaction between grade and treatment. RESULTS: Most patients received CRT (50.3%) followed by CT (23.1%), RT (16.1%) and NAT (10.5%). Survival after CRT was superior to NAT (p<0.001), RT (p=0.010) and CT (p<0.001). After adjusting for covariates, treatment with RT, CT and CRT led to a 57% (p=0.024), 62% (p=0.003) and 83% (p<0.001) reduction in risk of death compared to NAT, respectively. With CRT as the reference, the adjusted hazard of death was higher with NAT (5.94, p<0.001), RT (2.56, p=0.009) and CT (2.24, p=0.004). Stratifying by grade, RT and CRT led to a 67% (p=0.039) and 85% (p<0.001) reduction in death, compared to NAT in low-grade patients. CT and CRT led to a 72% (p=0.003) and 83% (p<0.001) reduction in death, compared to NAT in high-grade patients. CONCLUSIONS: Our findings suggest that CRT should be the preferred adjuvant treatment strategy for patients with stage IIIC endometrial cancer.

RNA-Puzzles Round II: assessment of RNA structure prediction programs applied to three large RNA structures.

This paper is a report of a second round of RNA-Puzzles, a collective and blind experiment in three-dimensional (3D) RNA structure prediction. Three puzzles, Puzzles 5, 6, and 10, represented sequences of three large RNA structures with limited or no homology with previously solved RNA molecules. A lariat-capping ribozyme, as well as riboswitches complexed to adenosylcobalamin and tRNA, were predicted by seven groups using RNAComposer, ModeRNA/SimRNA, Vfold, Rosetta, DMD, MC-Fold, 3dRNA, and AMBER refinement. Some groups derived models using data from state-of-the-art chemical-mapping methods (SHAPE, DMS, CMCT, and mutate-and-map). The comparisons between the predictions and the three subsequently released crystallographic structures, solved at diffraction resolutions of 2.5-3.2 Å, were carried out automatically using various sets of quality indicators. The comparisons clearly demonstrate the state of present-day de novo prediction abilities as well as the limitations of these state-of-the-art methods. All of the best prediction models have similar topologies to the native structures, which suggests that computational methods for RNA structure prediction can already provide useful structural information for biological problems. However, the prediction accuracy for non-Watson-Crick interactions, key to proper folding of RNAs, is low and some predicted models had high Clash Scores. These two difficulties point to some of the continuing bottlenecks in RNA structure prediction. All submitted models are available for download at http://ahsoka.u-strasbg.fr/rnapuzzles/.