Temporal effects on death by suicide: empirical evidence and possible molecular correlates.

Popular culture and medical lore have long postulated a connection between full moon and exacerbations of psychiatric disorders. We wanted to empirically analyze the hypothesis that suicides are increased during the period around full moons. We analyzed pre-COVID suicides from the Marion County Coroner's Office (n = 776), and show that deaths by suicide are significantly increased during the week of the full moon (p = 0.037), with older individuals (age ≥ 55) showing a stronger effect (p = 0.019). We also examined in our dataset which hour of the day (3-4 pm, p = 0.035), and which month of the year (September, p = 0.09) show the most deaths by suicide. We had blood samples on a subset of the subjects (n = 45), which enabled us to look at possible molecular mechanisms. We tested a list of top blood biomarkers for suicidality (n = 154) from previous studies of ours 7, to assess which of them are predictive. The biomarkers for suicidality that are predictive of death by suicide during full moon, peak hour of day, and peak month of year, respectively, compared to outside of those periods, appear to be enriched in circadian clock genes. For full moon it is AHCYL2, ACSM3, AK2, and RBM3. For peak hour it is GSK3B, AK2, and PRKCB. For peak month it is TBL1XR1 and PRKCI. Half of these genes are modulated in expression by lithium and by valproate in opposite direction to suicidality, and all of them are modulated by depression and alcohol in the same direction as suicidality. These data suggest that there are temporal effects on suicidality, possibly mediated by biological clocks, pointing to changes in ambient light (timing and intensity) as a therapeutically addressable target to decrease suicidality, that can be coupled with psychiatric pharmacological and addiction treatment preventive interventions.

Polyphenic risk score shows robust predictive ability for long-term future suicidality.

Suicides are preventable tragedies, if risk factors are tracked and mitigated. We had previously developed a new quantitative suicidality risk assessment instrument (Convergent Functional Information for Suicidality, CFI-S), which is in essence a simple polyphenic risk score, and deployed it in a busy urban hospital Emergency Department, in a naturalistic cohort of consecutive patients. We report a four years follow-up of that population (n = 482). Overall, the single administration of the CFI-S was significantly predictive of suicidality over the ensuing 4 years (occurrence- ROC AUC 80%, severity- Pearson correlation 0.44, imminence-Cox regression Hazard Ratio 1.33). The best predictive single phenes (phenotypic items) were feeling useless (not needed), a past history of suicidality, and social isolation. We next used machine learning approaches to enhance the predictive ability of CFI-S. We divided the population into a discovery cohort (n = 255) and testing cohort (n = 227), and developed a deep neural network algorithm that showed increased accuracy for predicting risk of future suicidality (increasing the ROC AUC from 80 to 90%), as well as a similarity network classifier for visualizing patient's risk. We propose that the widespread use of CFI-S for screening purposes, with or without machine learning enhancements, can boost suicidality prevention efforts. This study also identified as top risk factors for suicidality addressable social determinants. Supplementary Information: The online version contains supplementary material available at 10.1007/s44192-022-00016-z.

Precision medicine for suicidality: from universality to subtypes and personalization.

Suicide remains a clear, present and increasing public health problem, despite being a potentially preventable tragedy. Its incidence is particularly high in people with overt or un(der)diagnosed psychiatric disorders. Objective and precise identification of individuals at risk, ways of monitoring response to treatments and novel preventive therapeutics need to be discovered, employed and widely deployed. We sought to investigate whether blood gene expression biomarkers for suicide (that is, a 'liquid biopsy' approach) can be identified that are more universal in nature, working across psychiatric diagnoses and genders, using larger cohorts than in previous studies. Such markers may reflect and/or be a proxy for the core biology of suicide. We were successful in this endeavor, using a comprehensive stepwise approach, leading to a wealth of findings. Steps 1, 2 and 3 were discovery, prioritization and validation for tracking suicidality, resulting in a Top Dozen list of candidate biomarkers comprising the top biomarkers from each step, as well as a larger list of 148 candidate biomarkers that survived Bonferroni correction in the validation step. Step 4 was testing the Top Dozen list and Bonferroni biomarker list for predictive ability for suicidal ideation (SI) and for future hospitalizations for suicidality in independent cohorts, leading to the identification of completely novel predictive biomarkers (such as CLN5 and AK2), as well as reinforcement of ours and others previous findings in the field (such as SLC4A4 and SKA2). Additionally, we examined whether subtypes of suicidality can be identified based on mental state at the time of high SI and identified four potential subtypes: high anxiety, low mood, combined and non-affective (psychotic). Such subtypes may delineate groups of individuals that are more homogenous in terms of suicidality biology and behavior. We also studied a more personalized approach, by psychiatric diagnosis and gender, with a focus on bipolar males, the highest risk group. Such a personalized approach may be more sensitive to gender differences and to the impact of psychiatric co-morbidities and medications. We compared testing the universal biomarkers in everybody versus testing by subtypes versus personalized by gender and diagnosis, and show that the subtype and personalized approaches permit enhanced precision of predictions for different universal biomarkers. In particular, LHFP appears to be a strong predictor for suicidality in males with depression. We also directly examined whether biomarkers discovered using male bipolars only are better predictors in a male bipolar independent cohort than universal biomarkers and show evidence for a possible advantage of personalization. We identified completely novel biomarkers (such as SPTBN1 and C7orf73), and reinforced previously known biomarkers (such as PTEN and SAT1). For diagnostic ability testing purposes, we also examined as predictors phenotypic measures as apps (for suicide risk (CFI-S, Convergent Functional Information for Suicidality) and for anxiety and mood (SASS, Simplified Affective State Scale)) by themselves, as well as in combination with the top biomarkers (the combination being our a priori primary endpoint), to provide context and enhance precision of predictions. We obtained area under the curves of 90% for SI and 77% for future hospitalizations in independent cohorts. Step 5 was to look for mechanistic understanding, starting with examining evidence for the Top Dozen and Bonferroni biomarkers for involvement in other psychiatric and non-psychiatric disorders, as a mechanism for biological predisposition and vulnerability. The biomarkers we identified also provide a window towards understanding the biology of suicide, implicating biological pathways related to neurogenesis, programmed cell death and insulin signaling from the universal biomarkers, as well as mTOR signaling from the male bipolar biomarkers. In particular, HTR2A increase coupled with ARRB1 and GSK3B decreases in expression in suicidality may provide a synergistic mechanistical corrective target, as do SLC4A4 increase coupled with AHCYL1 and AHCYL2 decrease. Step 6 was to move beyond diagnostics and mechanistical risk assessment, towards providing a foundation for personalized therapeutics. Items scored positive in the CFI-S and subtypes identified by SASS in different individuals provide targets for personalized (psycho)therapy. Some individual biomarkers are targets of existing drugs used to treat mood disorders and suicidality (lithium, clozapine and omega-3 fatty acids), providing a means toward pharmacogenomics stratification of patients and monitoring of response to treatment. Such biomarkers merit evaluation in clinical trials. Bioinformatics drug repurposing analyses with the gene expression biosignatures of the Top Dozen and Bonferroni-validated universal biomarkers identified novel potential therapeutics for suicidality, such as ebselen (a lithium mimetic), piracetam (a nootropic), chlorogenic acid (a polyphenol) and metformin (an antidiabetic and possible longevity promoting drug). Finally, based on the totality of our data and of the evidence in the field to date, a convergent functional evidence score prioritizing biomarkers that have all around evidence (track suicidality, predict it, are reflective of biological predisposition and are potential drug targets) brought to the fore APOE and IL6 from among the universal biomarkers, suggesting an inflammatory/accelerated aging component that may be a targetable common denominator.

Towards understanding and predicting suicidality in women: biomarkers and clinical risk assessment.

Women are under-represented in research on suicidality to date. Although women have a lower rate of suicide completion than men, due in part to the less-violent methods used, they have a higher rate of suicide attempts. Our group has previously identified genomic (blood gene expression biomarkers) and clinical information (apps) predictors for suicidality in men. We now describe pilot studies in women. We used a powerful within-participant discovery approach to identify genes that change in expression between no suicidal ideation (no SI) and high suicidal ideation (high SI) states (n=12 participants out of a cohort of 51 women psychiatric participants followed longitudinally, with diagnoses of bipolar disorder, depression, schizoaffective disorder and schizophrenia). We then used a Convergent Functional Genomics (CFG) approach to prioritize the candidate biomarkers identified in the discovery step by using all the prior evidence in the field. Next, we validated for suicidal behavior the top-ranked biomarkers for SI, in a demographically matched cohort of women suicide completers from the coroner's office (n=6), by assessing which markers were stepwise changed from no SI to high SI to suicide completers. We then tested the 50 biomarkers that survived Bonferroni correction in the validation step, as well as top increased and decreased biomarkers from the discovery and prioritization steps, in a completely independent test cohort of women psychiatric disorder participants for prediction of SI (n=33) and in a future follow-up cohort of psychiatric disorder participants for prediction of psychiatric hospitalizations due to suicidality (n=24). Additionally, we examined how two clinical instruments in the form of apps, Convergent Functional Information for Suicidality (CFI-S) and Simplified Affective State Scale (SASS), previously tested in men, perform in women. The top CFI-S item distinguishing high SI from no SI states was the chronic stress of social isolation. We then showed how the clinical information apps combined with the 50 validated biomarkers into a broad predictor (UP-Suicide), our apriori primary end point, predicts suicidality in women. UP-Suicide had a receiver-operating characteristic (ROC) area under the curve (AUC) of 82% for predicting SI and an AUC of 78% for predicting future hospitalizations for suicidality. Some of the individual components of the UP-Suicide showed even better results. SASS had an AUC of 81% for predicting SI, CFI-S had an AUC of 84% and the combination of the two apps had an AUC of 87%. The top biomarker from our sequential discovery, prioritization and validation steps, BCL2, predicted future hospitalizations due to suicidality with an AUC of 89%, and the panel of 50 validated biomarkers (BioM-50) predicted future hospitalizations due to suicidality with an AUC of 94%. The best overall single blood biomarker for predictions was PIK3C3 with an AUC of 65% for SI and an AUC of 90% for future hospitalizations. Finally, we sought to understand the biology of the biomarkers. BCL2 and GSK3B, the top CFG scoring validated biomarkers, as well as PIK3C3, have anti-apoptotic and neurotrophic effects, are decreased in expression in suicidality and are known targets of the anti-suicidal mood stabilizer drug lithium, which increases their expression and/or activity. Circadian clock genes were overrepresented among the top markers. Notably, PER1, increased in expression in suicidality, had an AUC of 84% for predicting future hospitalizations, and CSNK1A1, decreased in expression, had an AUC of 96% for predicting future hospitalizations. Circadian clock abnormalities are related to mood disorder, and sleep abnormalities have been implicated in suicide. Docosahexaenoic acid signaling was one of the top biological pathways overrepresented in validated biomarkers, which is of interest given the potential therapeutic and prophylactic benefits of omega-3 fatty acids. Some of the top biomarkers from the current work in women showed co-directionality of change in expression with our previous work in men, whereas others had changes in opposite directions, underlying the issue of biological context and differences in suicidality between the two genders. With this study, we begin to shed much needed light in the area of female suicidality, identify useful objective predictors and help understand gender commonalities and differences. During the conduct of the study, one participant committed suicide. In retrospect, when the analyses were completed, her UP-Suicide risk prediction score was at the 100 percentile of all participants tested.

Small-molecule inhibitors targeting the DNA-binding domain of STAT3 suppress tumor growth, metastasis and STAT3 target gene expression in vivo.

Signal transducer and activator of transcription 3 (STAT3) is constitutively activated in malignant tumors and has important roles in multiple aspects of cancer aggressiveness. Thus targeting STAT3 promises to be an attractive strategy for treatment of advanced metastatic tumors. Although many STAT3 inhibitors targeting the SH2 domain have been reported, few have moved into clinical trials. Targeting the DNA-binding domain (DBD) of STAT3, however, has been avoided due to its 'undruggable' nature and potentially limited selectivity. In a previous study, we reported an improved in silico approach targeting the DBD of STAT3 that resulted in a small-molecule STAT3 inhibitor (inS3-54). Further studies, however, showed that inS3-54 has off-target effect although it is selective to STAT3 over STAT1. In this study, we describe an extensive structure and activity-guided hit optimization and mechanistic characterization effort, which led to identification of an improved lead compound (inS3-54A18) with increased specificity and pharmacological properties. InS3-54A18 not only binds directly to the DBD and inhibits the DNA-binding activity of STAT3 both in vitro and in situ but also effectively inhibits the constitutive and interleukin-6-stimulated expression of STAT3 downstream target genes. InS3-54A18 is completely soluble in an oral formulation and effectively inhibits lung xenograft tumor growth and metastasis with little adverse effect on animals. Thus inS3-54A18 may serve as a potential candidate for further development as anticancer therapeutics targeting the DBD of human STAT3 and DBD of transcription factors may not be 'undruggable' as previously thought.

Understanding and predicting suicidality using a combined genomic and clinical risk assessment approach.

Worldwide, one person dies every 40 seconds by suicide, a potentially preventable tragedy. A limiting step in our ability to intervene is the lack of objective, reliable predictors. We have previously provided proof of principle for the use of blood gene expression biomarkers to predict future hospitalizations due to suicidality, in male bipolar disorder participants. We now generalize the discovery, prioritization, validation, and testing of such markers across major psychiatric disorders (bipolar disorder, major depressive disorder, schizoaffective disorder, and schizophrenia) in male participants, to understand commonalities and differences. We used a powerful within-participant discovery approach to identify genes that change in expression between no suicidal ideation and high suicidal ideation states (n=37 participants out of a cohort of 217 psychiatric participants followed longitudinally). We then used a convergent functional genomics (CFG) approach with existing prior evidence in the field to prioritize the candidate biomarkers identified in the discovery step. Next, we validated the top biomarkers from the prioritization step for relevance to suicidal behavior, in a demographically matched cohort of suicide completers from the coroner's office (n=26). The biomarkers for suicidal ideation only are enriched for genes involved in neuronal connectivity and schizophrenia, the biomarkers also validated for suicidal behavior are enriched for genes involved in neuronal activity and mood. The 76 biomarkers that survived Bonferroni correction after validation for suicidal behavior map to biological pathways involved in immune and inflammatory response, mTOR signaling and growth factor regulation. mTOR signaling is necessary for the effects of the rapid-acting antidepressant agent ketamine, providing a novel biological rationale for its possible use in treating acute suicidality. Similarly, MAOB, a target of antidepressant inhibitors, was one of the increased biomarkers for suicidality. We also identified other potential therapeutic targets or biomarkers for drugs known to mitigate suicidality, such as omega-3 fatty acids, lithium and clozapine. Overall, 14% of the top candidate biomarkers also had evidence for involvement in psychological stress response, and 19% for involvement in programmed cell death/cellular suicide (apoptosis). It may be that in the face of adversity (stress), death mechanisms are turned on at a cellular (apoptosis) and organismal level. Finally, we tested the top increased and decreased biomarkers from the discovery for suicidal ideation (CADM1, CLIP4, DTNA, KIF2C), prioritization with CFG for prior evidence (SAT1, SKA2, SLC4A4), and validation for behavior in suicide completers (IL6, MBP, JUN, KLHDC3) steps in a completely independent test cohort of psychiatric participants for prediction of suicidal ideation (n=108), and in a future follow-up cohort of psychiatric participants (n=157) for prediction of psychiatric hospitalizations due to suicidality. The best individual biomarker across psychiatric diagnoses for predicting suicidal ideation was SLC4A4, with a receiver operating characteristic (ROC) area under the curve (AUC) of 72%. For bipolar disorder in particular, SLC4A4 predicted suicidal ideation with an AUC of 93%, and future hospitalizations with an AUC of 70%. SLC4A4 is involved in brain extracellular space pH regulation. Brain pH has been implicated in the pathophysiology of acute panic attacks. We also describe two new clinical information apps, one for affective state (simplified affective state scale, SASS) and one for suicide risk factors (Convergent Functional Information for Suicide, CFI-S), and how well they predict suicidal ideation across psychiatric diagnoses (AUC of 85% for SASS, AUC of 89% for CFI-S). We hypothesized a priori, based on our previous work, that the integration of the top biomarkers and the clinical information into a universal predictive measure (UP-Suicide) would show broad-spectrum predictive ability across psychiatric diagnoses. Indeed, the UP-Suicide was able to predict suicidal ideation across psychiatric diagnoses with an AUC of 92%. For bipolar disorder, it predicted suicidal ideation with an AUC of 98%, and future hospitalizations with an AUC of 94%. Of note, both types of tests we developed (blood biomarkers and clinical information apps) do not require asking the individual assessed if they have thoughts of suicide, as individuals who are truly suicidal often do not share that information with clinicians. We propose that the widespread use of such risk prediction tests as part of routine or targeted healthcare assessments will lead to early disease interception followed by preventive lifestyle modifications and proactive treatment.

Discovery and validation of blood biomarkers for suicidality.

Suicides are a leading cause of death in psychiatric patients, and in society at large. Developing more quantitative and objective ways (biomarkers) for predicting and tracking suicidal states would have immediate practical applications and positive societal implications. We undertook such an endeavor. First, building on our previous blood biomarker work in mood disorders and psychosis, we decided to identify blood gene expression biomarkers for suicidality, looking at differential expression of genes in the blood of subjects with a major mood disorder (bipolar disorder), a high-risk population prone to suicidality. We compared no suicidal ideation (SI) states and high SI states using a powerful intrasubject design, as well as an intersubject case-case design, to generate a list of differentially expressed genes. Second, we used a comprehensive Convergent Functional Genomics (CFG) approach to identify and prioritize from the list of differentially expressed gene biomarkers of relevance to suicidality. CFG integrates multiple independent lines of evidence-genetic and functional genomic data-as a Bayesian strategy for identifying and prioritizing findings, reducing the false-positives and false-negatives inherent in each individual approach. Third, we examined whether expression levels of the blood biomarkers identified by us in the live bipolar subject cohort are actually altered in the blood in an age-matched cohort of suicide completers collected from the coroner's office, and report that 13 out of the 41 top CFG scoring biomarkers (32%) show step-wise significant change from no SI to high SI states, and then to the suicide completers group. Six out of them (15%) remained significant after strict Bonferroni correction for multiple comparisons. Fourth, we show that the blood levels of SAT1 (spermidine/spermine N1-acetyltransferase 1), the top biomarker identified by us, at the time of testing for this study, differentiated future as well as past hospitalizations with suicidality, in a live cohort of bipolar disorder subjects, and exhibited a similar but weaker pattern in a live cohort of psychosis (schizophrenia/schizoaffective disorder) subjects. Three other (phosphatase and tensin homolog (PTEN), myristoylated alanine-rich protein kinase C substrate (MARCKS), and mitogen-activated protein kinase kinase kinase 3 (MAP3K3)) of the six biomarkers that survived Bonferroni correction showed similar but weaker effects. Taken together, the prospective and retrospective hospitalization data suggests SAT1, PTEN, MARCKS and MAP3K3 might be not only state biomarkers but trait biomarkers as well. Fifth, we show how a multi-dimensional approach using SAT1 blood expression levels and two simple visual-analog scales for anxiety and mood enhances predictions of future hospitalizations for suicidality in the bipolar cohort (receiver-operating characteristic curve with area under the curve of 0.813). Of note, this simple approach does not directly ask about SI, which some individuals may deny or choose not to share with clinicians. Lastly, we conducted bioinformatic analyses to identify biological pathways, mechanisms and medication targets. Overall, suicidality may be underlined, at least in part, by biological mechanisms related to stress, inflammation and apoptosis.

The protein tyrosine phosphatase, Shp2, positively contributes to FLT3-ITD-induced hematopoietic progenitor hyperproliferation and malignant disease in vivo.

Internal tandem duplications (ITDs) in the fms-like tyrosine kinase receptor (FLT3-ITDs) confer a poor prognosis in acute myeloid leukemia (AML). We hypothesized that increased recruitment of the protein tyrosine phosphatase, Shp2, to FLT3-ITDs contributes to FLT3 ligand (FL)-independent hyperproliferation and STAT5 activation. Co-immunoprecipitation demonstrated constitutive association of Shp2 with the FLT3-ITD, N51-FLT3, as well as with STAT5. Knockdown of Shp2 in Baf3/N51-FLT3 cells significantly reduced proliferation while having little effect on WT-FLT3-expressing cells. Consistently, mutation of N51-FLT3 tyrosine 599 to phenylalanine or genetic disruption of Shp2 in N51-FLT3-expressing bone marrow low-density mononuclear cells reduced proliferation and STAT5 activation. In transplants, genetic disruption of Shp2 in vivo yielded increased latency to and reduced severity of FLT3-ITD-induced malignancy. Mechanistically, Shp2 co-localizes with nuclear phospho-STAT5, is present at functional interferon-γ activation sites (GAS) within the BCL2L1 promoter, and positively activates the human BCL2L1 promoter, suggesting that Shp2 works with STAT5 to promote pro-leukemogenic gene expression. Further, using a small molecule Shp2 inhibitor, the proliferation of N51-FLT3-expressing bone marrow progenitors and primary AML samples was reduced in a dose-dependent manner. These findings demonstrate that Shp2 positively contributes to FLT3-ITD-induced leukemia and suggest that Shp2 inhibition may provide a novel therapeutic approach to AML.

Inhibition of glycinamide ribonucleotide formyltransferase results in selective inhibition of macrophage cytokine secretion in vitro and in vivo efficacy in rat adjuvant arthritis.

OBJECTIVE: To determine the effects of a glycinamide ribonucleotide formyltransferase (GARFT) inhibitor on macrophage inflammatory processes and in vivo in rat adjuvant arthritis. METHODS: GARFT inhibitors, LY309886 (6S-2',5'-thienyl-5, 10-dideazatetrahydrofolic acid) and LY329201 (R)-N-[[5-[2-(2-amino-1,4,5,6,7,8-hexahydro-4-oxopyrido[2,3-d]pyrimidin-6-yl)ethyl]-2-thienyl]carbonyl]-L-glutamatic acid disodium salt, were investigated in vitro and ex vivo on primary murine peritoneal macrophages and in the RAW macrophage cell line for both purine depletion and inhibition of LPS induced monokine secretion. In vivo efficacy following GARFT inhibition was evaluated in modified rat adjuvant arthritis. RESULTS: LY309886 inhibited purine biosynthesis in the RAW cell line with an EC50 of 90 nM, an effect readily reversible with exogenous hypoxanthine. LY309886 and LY329201 also inhibited LPS induced TNF alpha and MIP1 alpha in these cells and in primary macrophages. A similar effect could be demonstrated ex vivo with mice dosed for two days with 3 mg/kg of LY329201. LY329201 as well as methotrexate demonstrated a dose dependent reduction in both paw and spleen weight and improved joint histology following 2 weeks of dosing in a rat adjuvant arthritis study. CONCLUSION: These results suggest that GARFT inhibitors should be tested in the treatment of rheumatoid arthritis by considering their mechanism of action, here successfully tested on activated macrophages.

Expression of multidrug resistance-associated protein 2 (MRP2) in normal human tissues and carcinomas using tissue microarrays.

AIMS: Using tissue microarrays, this study analysed the expression of the multidrug resistance protein, MRP2, by immunohistochemistry with two different MRP2 antibodies. This is the first study to address the expression of MRP2 in various common human neoplasms. METHODS AND RESULTS: Immunohistochemistry was performed on zinc formalin-fixed tissue to evaluate normal tissues and carcinomas using two antibodies against MRP2 (EAG5, a polyclonal antibody, and M2-lll-6, a monoclonal antibody). Immunostaining was localized in neoplastic cells mainly on the cell membrane with M2-lll-6 and cell membrane and cytoplasm with EAG5. In normal tissues MRP2 was expressed in liver, gastrointestinal tract, and kidney tubular epithelial cells with both antibodies. MRP2 was seen in nine of 22 renal cell carcinomas, eight of 13 gastric carcinomas, 25 of 49 breast carcinomas, 14 of 32 lung carcinomas, 39 of 50 colon carcinomas, and 16 of 17 ovarian carcinomas. There was < 10% variability between the two antibodies. MRP2 expression was highest in moderate to poorly differentiated tumours from colon, lung, gastric, and ovarian carcinomas and in grade 2 and 3 breast and renal carcinomas. CONCLUSION: The expression of MRP2 in many solid human tumours indicates that inherent drug resistance may play an important role as a biomarker for predictive chemotherapy treatment.

AKT-1, -2, and -3 are expressed in both normal and tumor tissues of the lung, breast, prostate, and colon.

PURPOSE: The AKT/PKB kinase controls many of the intracellular processes that are dysregulated in human cancer, including the suppression of apoptosis and anoikis and the induction of cell cycle progression. Three isoforms of AKT have been identified: AKT-1, -2, and -3. Selective up-regulation of AKT-3 RNA expression has been reported in hormone-independent breast and prostate cancer cell lines suggesting that AKT-3 expression may be increased with breast or prostate tumor progression. To determine whether AKT-3 RNA expression is selectively up-regulated in human cancers and whether the patterns of AKT RNA expression may change with tumor development, we examined AKT isoform expression by RT-PCR in human cancer cell lines, primary human cancers, and normal human tissues. EXPERIMENTAL DESIGN: AKT-1, -2, and -3 RNA expression was examined by RT-PCR. Because up-regulated AKT-3 expression has been implicated in human breast and prostate cancer progression, we also examined AKT-3 expression levels by semiquantitative RT-PCR using matched normal/tumor first-strand cDNA pairs from colon, breast, prostate, and lung cancers. RESULTS: Our data reveal that the overwhelming majority of both normal and tumor tissues express all three of the AKT isoforms. Moreover, semiquantitative RT-PCR of matched normal/tumor pairs confirmed similar AKT-3 RNA expression levels in both normal and tumor tissue. CONCLUSIONS: Our data show that both normal and tumor tissues express all three of the AKT isoforms and indicate that tumorigenesis does not involve a dramatic shift in the RNA expression patterns of the three AKT isoforms.

Decreased p38 MAPK activity in end-stage failing human myocardium: p38 MAPK alpha is the predominant isoform expressed in human heart.

Short duration exposure to cellular stresses have been shown to activate p38 mitogen-activated protein kinase (MAPK) in cultured rat ventricular cardiomyocytes and isolated perfused hearts; however, effects of chronic stress on p38 MAPK are not well understood. This study determined whether alterations in the p38 MAPK pathway occurred prior to end-stage human heart failure. The p38 MAPK alpha isoform was detectable in human cardiac tissue. However, carefully controlled analysis of protein and message in this study demonstrated an absence of the p38 MAPK beta -isoform. Low levels of message for the non-SB203580 sensitive p38 MAPK gamma and delta isoforms were also detected in both normal and failing human myocardium. Ischemic and idiopathic end-stage failing human hearts were compared to non-failing hearts for both p38 alpha MAPK protein level and total p38 MAPK activity. Western blotting techniques demonstrated no significant changes in total p38 alpha MAPK content. However, approximately 75% decreases in active/phosphorylated p38 MAPK (P<0.005) were observed in both ischemic and idiopathic failing hearts compared to non-failing hearts. In-gel kinase assays confirmed that activated p38 MAPK, detected by Western blotting, phosphorylated its potential downstream targets. When compared to non-failing hearts, approximately 46% decreases in p38 MAPK phosphorylation of mitogen-activated protein kinase-activated protein kinase-2 (MAPKAPK-2) were observed in ischemic and idiopathic failing hearts (P=0.03 and P=0.04 respectively). Active p38 MAPK was localized to sarcomeric structures in the cytosol of myocytes by confocal immunofluorescence microscopy. The correlation between decreased MAPKAPK-2 phosphorylation and loss of active p38 MAPK in failing human myocytes suggests that decreases in the activation of p38 MAPK alpha, the predominant cardiac isoform, occur prior to end-stage heart failure.

Human truncated Smad 6 (Smad 6s) inhibits the BMP pathway in Xenopus laevis.

A previously identified truncated form of the human Smad 6 gene containing a unique 12 amino acid motif at its N-terminus was studied. We have named this truncated form of the gene Smad 6s, for 'short-form', to distinguish it from the full-length form (Smad 6fl). Reverse transcription-polymerase chain reaction and immunohistochemistry revealed that Smad 6s has a unique pattern of expression in human coronary tissue and is upregulated in diseased heart tissue. We used the expression of human Smad 6s in Xenopus laevis as a model system to assess Smad 6s function. Injection of Smad 6fl RNA (4-cell embryos, 2 x ventral) produced tadpoles with partial secondary axes. In contrast, Smad 6s RNA injected in a similar manner produced tadpoles with a severe 'head-only' phenotype with no morphological appearance of a secondary axis. Mutant Smad 6s RNA lacking the unique 12 amino acids at the N-terminus of the Smad 6s isoform produced no embryonic phenotype, suggesting that this region is important in conferring biological activity. Ectodermal explant assays show that Smad 6s has activity consistent with being a BMP antagonist and can synergize with and enhance the activities of the activin and fibroblast growth factor pathways, all of which are novel findings in this study.

Protein kinase C-alpha and -epsilon modulate connexin-43 phosphorylation in human heart.

We have previously demonstrated that protein kinase C (PKC)- alpha expression is significantly elevated in failing human left ventricle, with immunostaining showing increased PKC- alpha localization at the intercalated disks of cardiomyocytes. In the present study we sought to determine, in the failing heart, if PKC- alpha interacted with connexin-43 (Cx-43) both spatially and functionally, and to compare the association of PKC- alpha/Cx-43 with that of PKC- epsilon, a PKC isozyme that does not significantly increase in failing hearts. The possibility of a PKC- alpha or PKC- epsilon/Cx-43 association in non-failing hearts was also investigated. Co-immunoprecipitation of PKC- alpha or PKC- epsilon and Cx-43 in non-failing and failing left ventricle was achieved using antibodies to PKC- alpha or Cx-43. Confocal microscopy confirmed that PKC- alpha distribution within the cardiomyocyte included co-localization with connexin-43 in both failing and non-failing myocardium. In a similar manner, confocal imaging of PKC- epsilon showed cardiomyocyte distribution in both cytosol and membrane, and colocalization of PKC- epsilon with Cx-43. Recombinant PKC- alpha or - epsilon increased PKC activity significantly above endogenous levels in the co-immunoprecipitated Cx-43 complexes (P<0.05). However, phosphorylation of purified human Cx-43 (isolated from failing human left ventricle) by recombinant PKC- alpha or PKC- epsilon resulted in only PKC- epsilon mediated Cx-43 phosphorylation. Thus, in the human heart PKC- alpha, PKC- epsilon, and Cx-43 appear to form a closely associated complex. Whereas only PKC- epsilon directly phosphorylates Cx-43, both PKC isoforms result in increased phosphorylation within the Cx-43 co-immunoprecipitated complex.

Increased AKT activity contributes to prostate cancer progression by dramatically accelerating prostate tumor growth and diminishing p27Kip1 expression.

The PTEN tumor suppressor gene is frequently inactivated in human prostate cancers, particularly in more advanced cancers, suggesting that the AKT/protein kinase B (PKB) kinase, which is negatively regulated by PTEN, may be involved in human prostate cancer progression. We now show that AKT activation and activity are markedly increased in androgen-independent, prostate-specific antigen-positive prostate cancer cells (LNAI cells) established from xenograft tumors of the androgen-dependent LNCaP cell line. These LNAI cells show increased expression of integrin-linked kinase, which is putatively responsible for AKT activation/Ser-473 phosphorylation, as well as for increased phosphorylation of the AKT target protein, BAD. Furthermore, expression of the p27(Kip1) cell cycle regulator was diminished in LNAI cells, consistent with the notion that AKT directly inhibits AFX/Forkhead-mediated transcription of p27(Kip1). To assess directly the impact of increased AKT activity on prostate cancer progression, an activated hAKT1 mutant was overexpressed in LNCaP cells, resulting in a 6-fold increase in xenograft tumor growth. Like LNAI cells, these transfectants showed dramatically reduced p27(Kip1) expression. Together, these data implicate increased AKT activity in prostate tumor progression and androgen independence and suggest that diminished p27(Kip1) expression, which has been repeatedly associated with prostate cancer progression, may be a consequence of increased AKT activity.

Immunohistochemical localization of selected early response genes expressed in trabecular bone of young rats given hPTH 1-34.

Intermittent administration of parathyroid hormone (PTH) increases trabecular bone mass in vivo by stimulating bone formation. To further characterize the cellular and molecular mediators of the anabolic response to PTH, we examined the effect of intermittent synthetic hPTH 1-34 on the expression and localization of selected early response genes, c-fos, c-jun, c-myc, and IL-6 protein, in bone tissue by immunohistochemistry. Young male Sprague-Dawley rats, 70-100 g, were injected s.c. with 8 microg/100 g PTH or vehicle control, once daily for 5 days. Femurs were harvested 1 and 24 hours after the fifth injection, then fixed, decalcified, processed for wax embedding, and sections were immunostained. Early response genes, c-fos, c-jun and IL-6, were strongly expressed in osteoblasts, osteocytes, and megakaryocytes in bones 1 hour after PTH, when compared with vehicle-treated controls or sections from rats, 24 hours after PTH injection. Osteoblasts, osteocytes, and megakaryocytes were also positive for c-myc but the differences in stain intensity between control and treated groups were marginal. Also, scattered islands of hematopoietic cells in the marrow stained intensely for IL-6 by 1 hour after PTH, but the stain intensity decreased to control level 24 hours after the last PTH injection. Scattered islands of hematopoietic cells in the bone marrow stained more strongly for c-fos than either c-jun or c-myc, but neither localization nor stain intensity were regulated by PTH at the time points examined. We conclude that during the immediate early phase of the anabolic response, PTH regulates c-fos, c-jun, and IL-6 expression in osteoblasts, osteocytes, megakaryocytes, and selected bone marrow hematopoietic cells in bone.

Hyperplasia in multiple smooth muscle tissues in transgenic mice expressing a temperature-sensitive SV40 T-antigen under the control of smooth muscle alpha-actin regulatory sequences.

Control of smooth muscle cell (SMC) proliferation is of fundamental importance in the development and pathology of the vasculature. To derive vascular SMC with conditional inactivation of negative cell cycle regulatory proteins in the context of smooth muscle protein expression, a 3.4 kb fragment of the mouse SMC alpha-actin promoter was used to target a temperature-sensitive mutant SV40 T antigen (tsA58) to smooth muscle in transgenic mice. Mice with this genotype display a heritable phenotype of abnormal SMC proliferation in the central tail artery, vasa deferentia, seminal vesicles, prostate, and uterus, with the latter resembling uterine leiomyomatosis and prostatic hypertrophy. Neither the aorta nor other viscera manifested abnormal proliferation. Cultures from aorta, vas deferens, seminal vesicle, and kidney tissue were characterized with regard to protein expression, stability, and matrix remodelling capacity. The alpha-actin content/cell was up to 3-4-fold higher, as well as more stable than in primary SMC cultures, suggesting successful selection for propagation of cells expressing this differentiation marker. All cells displayed enhanced growth at the permissive temperature. As an initial functional assessment, the cells were compared to non-transformed mouse aortic SMC with respect to the ability to remodel collagen gel matrices, and demonstrated conservation of this physiologic function. This in vivo analysis of the SMC alpha-actin promoter supports a broader range of smooth muscle-directed expression activity than previously recognized, and establishes the feasibility of its use to direct transgene expression to vascular as well as genito-urinary smooth muscle. The targeted expression of the tsA58 T antigen has yielded transgenic animals with several manifestations of smooth muscle hyperplasia; these animals have in turn permitted the derivation of several murine SMC lines with phenotypic stability and conditionally-modulated proliferation. These cells will allow expansion of derivative transfected smooth muscle cell lines under permissive conditions, as well as oncogene inactivation at the restrictive temperature when desired for functional studies.