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Salt-inducible kinase 2 (SIK2; also known as serine/threonine-protein kinase SIK2) is overexpressed in several cancers and has been implicated in cancer progression. However, the mechanisms by which SIK2 regulates cancer cell motility, migration and metastasis in ovarian cancer have not been fully discovered. Here, we identify that SIK2 promotes ovarian cancer cell motility, migration and metastasis in vitro and in vivo. Mechanistically, SIK2 regulated cancer cell motility and migration by myosin light chain kinase, smooth muscle (MYLK)-meditated phosphorylation of myosin light chain 2 (MYL2). SIK2 directly phosphorylated MYLK at Ser343 and activated its downstream effector MYL2, promoting ovarian cancer cell motility and metastasis. In addition, we found that adipocytes induced SIK2 phosphorylation at Ser358 and MYLK phosphorylation at Ser343, enhancing ovarian cancer cell motility. Moreover, SIK2 protein expression was positively correlated with the expression of MYLK-pS343 in ovarian cancer cell lines and tissues. The coexpression of SIK2 and MYLK-pS343 was associated with reduced median overall survival in human ovarian cancer samples. Taken together, SIK2 positively regulates ovarian cancer motility, migration and metastasis, suggesting that SIK2 is a potential candidate for ovarian cancer treatment. [ABSTRACT FROM AUTHOR]

Simple Summary: When ovarian cancer is detected early, the survival rate is high. Unfortunately, existing blood tests are neither sensitive nor specific enough to screen women for ovarian cancer. The purpose of this study was to determine the levels of 92 cancer-related proteins in the blood of women with ovarian cancer compared to healthy women in order to develop a test for ovarian cancer detection. We tested the blood of more than 400 women and identified four proteins that, when combined, successfully detected over 90% of the women with ovarian cancer. We then tested more than 700 additional blood samples and found that the combination of the four proteins successfully distinguished the majority of the blood samples from women with both early and late stages of ovarian cancer compared to healthy women. These four proteins show promise in the development of a test to detect the early stages of ovarian cancer. Background: Individual serum biomarkers are neither adequately sensitive nor specific for use in screening the general population for ovarian cancer. The purpose of this study was to develop a multiprotein classifier to detect the early stages of ovarian cancer, when it is most treatable. Methods: The Olink Proseek Multiplex Oncology II panel was used to simultaneously quantify the expression levels of 92 cancer-related proteins in sera. Results: In the discovery phase, we generated a multiprotein classifier that included CA125, HE4, ITGAV, and SEZ6L, based on an analysis of sera from 116 women with early stage ovarian cancer and 336 age-matched healthy women. CA125 alone achieved a sensitivity of 87.9% at a specificity of 95%, while the multiprotein classifier resulted in an increased sensitivity of 91.4%, while holding the specificity fixed at 95%. The performance of the multiprotein classifier was validated in a second cohort comprised of 192 women with early stage ovarian cancer and 467 age-matched healthy women. The sensitivity at 95% specificity increased from 74.5% (CA125 alone) to 79.2% with the multiprotein classifier. In addition, the multiprotein classifier had a sensitivity of 95.1% at 98% specificity for late stage ovarian cancer samples and correctly classified 80.5% of the benign samples using the 98% specificity cutpoint. Conclusions: The inclusion of the proteins HE4, ITGAV, and SEZ6L improved the sensitivity and specificity of CA125 alone for the detection of early stages of ovarian cancer in serum samples. Furthermore, we identified several proteins that may be novel biomarkers of early stage ovarian cancer. [ABSTRACT FROM AUTHOR]

Effective cancer prevention requires the discovery and intervention of a factor critical to cancer development. Here we show that ovarian progesterone is a crucial endogenous factor inducing the development of primary tumors progressing to metastatic ovarian cancer in a mouse model of high-grade serous carcinoma (HGSC), the most common and deadliest ovarian cancer type. Blocking progesterone signaling by the pharmacologic inhibitor mifepristone or by genetic deletion of the progesterone receptor (PR) effectively suppressed HGSC development and its peritoneal metastases. Strikingly, mifepristone treatment profoundly improved mouse survival (~18 human years). Hence, targeting progesterone/PR signaling could offer an effective chemopreventive strategy, particularly in high-risk populations of women carrying a deleterious mutation in the BRCA gene. [ABSTRACT FROM AUTHOR]

Early detection of ovarian cancer remains an important unmet medical need. Effective screening could reduce mortality by 10%-30%. Used individually, neither serum CA125 nor transvaginal sonography (TVS) is sufficiently sensitive or specific. Two-stage strategies have proven more effective, where a significant rise above a woman's baseline CA125 prompts TVS and an abnormal sonogram prompts surgery. Two major screening trials have documented that this strategy has adequate specificity, but sensitivity for early-stage (I-II) disease must improve to have a greater impact on mortality. To improve the first stage, different panels of protein biomarkers have detected cases missed by CA125. Autoantibodies against TP53 have detected 20% of early-stage ovarian cancers 8 months before elevation of CA125 and 22 months before clinical diagnosis. Panels of autoantibodies and antigen-autoantibody complexes are being evaluated with the goal of detecting >90% of early-stage ovarian cancers, alone or in combination with CA125, while maintaining 98% specificity in control subjects. Other biomarkers, including micro-RNAs, ctDNA, methylated DNA, and combinations of ctDNA alterations, are being tested to provide an optimal first-stage test. New technologies are also being developed with greater sensitivity than TVS to image small volumes of tumor. [ABSTRACT FROM AUTHOR]

HRAS, NRAS, and KRAS4A/KRAS4B comprise the RAS family of small GTPases that regulate signaling pathways controlling cell proliferation, differentiation, and survival. RAS pathway abnormalities cause developmental disorders and cancers. We found that KRAS4B colocalizes on the cell membrane with other RAS isoforms and a subset of prenylated small GTPase family members using a live-cell quantitative split luciferase complementation assay. RAS protein coclustering is mainly mediated by membrane association-facilitated interactions (MAFIs). Using the RAS–RBD (CRAF RAS binding domain) interaction as a model system, we showed that MAFI alone is not sufficient to induce RBD-mediated RAS inhibition. Surprisingly, we discovered that high-affinity membrane-targeted RAS binding proteins inhibit RAS activity and deplete RAS proteins through an autophagosome–lysosome-mediated degradation pathway. Our results provide a mechanism for regulating RAS activity and protein levels, a more detailed understanding of which should lead to therapeutic strategies for inhibiting and depleting oncogenic RAS proteins. [ABSTRACT FROM AUTHOR]

Background: The objective of this study was to determine patient characteristics associated with potentially inappropriate medication (PIM) use and its impact on outcomes for patients with breast or colorectal cancer receiving adjuvant chemotherapy.Methods: The Surveillance, Epidemiology, and End Results database, linked to Medicare claims, was used. The cohort included patients who were 66 years old or older and were diagnosed with stage II or III breast or colorectal cancer between July 1, 2007, and December 31, 2009. The Drugs to Avoid in the Elderly (DAE) list and the Beers criteria were used to identify PIM use. Univariate/multivariate logistic regression determined the association of baseline PIMs with covariates. Event-free survival (EFS) was defined as the time from chemotherapy initiation to the first emergency room (ER) visit, hospitalization, death, or a composite until 3 months after chemotherapy. Cox proportional hazards modeling determined the association of PIMs with EFS.Results: The analysis included 1595 patients with breast cancer and 1528 patients with colorectal cancer. The baseline PIM frequencies were 22.2% (according to the DAE list) and 27.6% (according to the Beers criteria) in the breast cohort and 15.5% (according to the DAE list) and 24.8% (according to the Beers criteria) in the colorectal cohort. Among patients with breast cancer, 37.5% had at least 1 adverse outcome; associations included the use of ≥5 medications, an advanced stage, higher comorbidity, and prior ER visits/hospitalizations. Baseline PIM use according to the DAE list was associated with an increased risk of death in patients with breast cancer. Among patients with colorectal cancer, 45% had at least 1 adverse outcome, and associations included the use of ≥5 medications, older age, female sex, and higher comorbidity. A time-to-event analysis revealed no association between baseline PIM use and most outcomes.Conclusions: These findings require further prospective confirmation, but they support a correlation between polypharmacy and adverse outcomes for cancer patients and call into question the association with PIMs. Cancer 2018;124:3000-7. © 2018 American Cancer Society. [ABSTRACT FROM AUTHOR]

Background: Autophagy is a bulk catabolic process that modulates tumorigenesis, therapeutic resistance, and dormancy. The tumor suppressor ARHI (DIRAS3) is a potent inducer of autophagy and its expression results in necroptotic cell death in vitro and tumor dormancy in vivo. ARHI is down-regulated or lost in over 60 % of primary ovarian tumors yet is dramatically up-regulated in metastatic disease. The metabolic changes that occur during ARHI induction and their role in modulating death and dormancy are unknown. Methods: We employed Nuclear Magnetic Resonance (NMR)-based metabolomic strategies to characterize changes in key metabolic pathways in both cell culture and xenograft models of ARHI expression and autophagy. These pathways were further interrogated by cell-based immunofluorescence imaging, tracer uptake studies, targeted metabolic inhibition, and in vivo PET/CT imaging. Results: Induction of ARHI in cell culture models resulted in an autophagy-dependent increase in lactate production along with increased glucose uptake and enhanced sensitivity to glycolytic inhibitors. Increased uptake of glutamine was also dependent on autophagy and dramatically sensitized cultured ARHI-expressing ovarian cancer cell lines to glutaminase inhibition. Induction of ARHI resulted in a reduction in mitochondrial respiration, decreased mitochondrial membrane potential, and decreased Tom20 staining suggesting an ARHI-dependent loss of mitochondrial function. ARHI induction in mouse xenograft models resulted in an increase in free amino acids, a transient increase in [18F]-FDG uptake, and significantly altered choline metabolism. Conclusions: ARHI expression has previously been shown to trigger autophagy-associated necroptosis in cell culture. In this study, we have demonstrated that ARHI expression results in decreased cellular ATP/ADP, increased oxidative stress, and decreased mitochondrial function. While this bioenergetic shock is consistent with programmed necrosis, our data indicates that the accompanying up-regulation of glycolysis and glutaminolysis is autophagy-dependent and serves to support cell viability rather than facilitate necroptotic cell death. While the mechanistic basis for metabolic up-regulation following ARHI induction is unknown, our preliminary data suggest that decreased mitochondrial function and increased metabolic demand may play a role. These alterations in fundamental metabolic pathways during autophagy-associated necroptosis may provide the basis for new therapeutic strategies for the treatment of dormant ovarian tumors. [ABSTRACT FROM AUTHOR]

Objectives: Longitudinalmultimarker combinations have the potential to improve sensitivity while maintaining the high specificity required for the early detection of ovarian cancer. The use of multiplemarkers to improve sensitivity over cancer antigen 125 (CA125) in longitudinal algorithms for early ovarian cancer detection requires the selection of markers with optimal discriminatory power and low longitudinal variance relative to disease-initiated changes. Our objectivewas to identify amultimarker panel suitable for ovarian cancer, where each individual marker has its own baseline, permitting longitudinal algorithm development. Materials and Methods: In this retrospective study, we measured CA125, human epididymis protein 4 (HE4), matrix metalloproteinase-7 (MMP-7), CA72-4, CA19-9, CA15-3, carcinoembryonic antigen, and soluble vascular cell adhesion molecule (sVCAM) concentrations using immunoassays in pretreatment sera from 142 stage I ovarian cancer cases and 5 annual samples each from 217 healthy controls. After random division into training and validation sets, all possible biomarker combinations were explored exhaustively using linear classifiers to identify the panel with the greatest sensitivity for stage I disease at a high specificity of 98%. To evaluate longitudinal performance of the individual markers, the within-person over time and the between-person coefficient of variation (CV) were estimated. Hierarchical modeling across women of log-concentrations enabled the borrowing of information across subjects to moderate variance estimates given the small number of observations per subject. Results: The 4-marker panel comprising CA125, HE4, MMP-7, and CA72-4 performed with the highest sensitivity (83.2%) at 98% specificity. The within-person CVs were lower for CA125, HE4, MMP-7, and CA72-4 (15%, 25%, 25%, and 21%, respectively) compared with their corresponding between-person CV (49%, 20%, 35%, and 84%, respectively) indicating baselines in healthy volunteers. After simple log-transformations, the withinvolunteer variation across volunteers was modeled with a normal distribution permitting parsimonious hierarchical modeling. Conclusions: The multiplex panel chosen is suitable for the early detection of ovarian cancer and the individual markers have their own baseline permitting longitudinal algorithm development. [ABSTRACT FROM AUTHOR]