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STAT

An MUSC blog
Keyword: biomarker

MUSC Health Rheumatologist Dr. Jim Oates

 

Summary: Medical University of South Carolina (MUSC) investigators report preclinical research showing that prognostic models for lupus nephritis that include novel biomarkers have significantly improved predictive power over models using only traditional markers, in the August 2016 issue of Arthritis & Rheumatology. Data reveal that chemokines, cytokines, and markers of cellular damage were most predictive of patients' therapeutic response. This is a critical first step to developing clinically meaningful, decision-support tools in lupus nephritis.

 

 

Caption: MUSC Health rheumatologist Jim C. Oates, M.D.

Results of preclinical studies by investigators at the Medical University of South Carolina (MUSC) reported in the August 2016 issue of Arthritis & Rheumatology demonstrate for the first time that including novel biomarkers in lupus nephritis (LN) prognostic models significantly increases their power to predict therapeutic efficacy. Identifying biomarker models with sufficient predictive power is a critical step toward developing clinical decision-making tools that can rapidly identify patients who require a change in therapy and potentially reduce onset of renal fibrosis during induction therapy.

Approximately half of all patients with systemic lupus erythematosus (SLE) develop LN, an immune complex-mediated glomerulonephritis. Lupus nephritis, in turn, leads to renal failure in up to 50% of patients within five years. American College of Rheumatology guidelines recommend changing LN treatment after six months of induction therapy if response to therapy is not achieved. However, 'response to therapy' is not clearly defined and renal damage can occur during the six-month induction period.

Currently, clinicians monitor response to treatment via blood pressure measurements, serum complement levels, anti-double-stranded DNA (anti-dsDNA) antibody levels, urinary sediment, urinary protein-to-creatinine ratios, and surrogates of renal function. Unfortunately, predicting disease progression is difficult using these traditional biomarkers due to their low sensitivity and high LN heterogeneity at presentation. Even when machine learning models are employed, traditional biomarkers are only 69% accurate in predicting a LN diagnosis among SLE patients. There is a need for individualized, decision-support tools that can better define 'therapeutic response' at the start of therapy and allow clinicians to tailor induction therapy to disease severity to prevent renal damage and unnecessary drug toxicity.

"We saw our colleagues' frustration in trying to come up with predictive models,” said Jim C. Oates, M.D., Associate Director of the MUSC Clinical and Translational Research Center, Associate Professor of Rheumatology, and senior author on the article. “The traditional markers we use in clinic today have quite limited predictive capacity. All lupus patients have varying degrees of kidney damage and levels of involvement of the different kidney structures. So, we wanted to account for this heterogeneity and the stages of disease progression. We wanted to include markers for pathways of inflammation as well as for damage."

The research team hypothesized that a targeted panel of urinary biomarkers reflecting initial resident and inflammatory cell activation (cytokines), signals for homing to the kidney (chemokines), activation of inflammatory cells (growth factors), and damage to resident cells, combined with artificial intelligence/machine learning modeling, might provide an early LN decision-support tool that could predict outcomes better than standard biomarkers alone. The team also chose to assess urine biomarkers rather than serum/plasma markers to increase the tool's sensitivity and specificity to signals of renal (rather than systemic) processes.

Urine samples from 140 patients with biopsy-proven LN who had not yet started induction therapy were analyzed for a panel of novel biomarkers using pre-mixed, commercially available kits. Univariate, receiver operating characteristic (ROC) curves were generated for each biomarker and compared to ROC area under the curve (AUC) values from machine learning models developed using random forest algorithms. Outcome models using novel biomarkers plus traditional clinical markers demonstrated greater AUC and significance compared to models developed with traditional markers alone ([AUC 0.79; P<0.001] vs. [AUC 0.61; P=0.05], respectively). The combined models also demonstrated greater power to correctly predict LN therapy outcomes (responder versus non-responder) than models using only traditional markers (76% vs. 27%, respectively [p<0.002]).

The team identified chemokines, cytokines, and markers of cellular damage as most predictive of LN therapy response. Race, anti-double-stranded DNA antibodies, and induction medication did not significantly contribute to the model.

"We were somewhat surprised by some of the analytes that were important in the model,” said Oates. "One traditional marker, protein-to-creatinine ratio, was the third most important, and a standard kidney function measure was the ninth. I was also surprised to see interluekin-8 so high. This is in keeping with recent publications highlighting the importance of neutrophils in the pathogenesis of lupus, however."

Including multiple mechanisms of disease pathogenesis and cellular damage likely provides a more effective diagnostic approach by better reflecting the multi-stage, heterogeneous nature of LN. This is the first study to combine a broad biomarker panel with machine learning techniques to optimize disease outcome models. "This could apply to any model where there is kidney inflammation leading to damage,” said Oates. "It's proof of concept for other kidney diseases that you can take a discovery model and incorporate machine learning to develop and validate predictive models."

The team is now testing other biomarkers and applying the model in a larger patient population to ensure external validity and improve power. They are also exploring other inputs.

"Our next approach is to harness existing data in the medical record to enhance predictions,” said Oates. “This is much more immediately translatable in the clinic than getting through a long FDA validation process and the industry pipeline. Using medical record data is cheaper, and there are patient and system factors in the medical record that you can't measure with an assay, such as economic and societal disparities, which affect outcomes. This approach could also be used to enhance biomarker predictive models”

Summary: Medical University of South Carolina (MUSC) investigators report preclinical research showing that Krüppel-like factor 12 (KLF12) promotes colorectal cancer (CRC) cell growth by activating early growth response protein 1 (EGR1), in the July 2016 issue of PLOS One. Data also reveal that levels of KLF12 and EGR1 correlate synergistically with a poor CRC prognosis. Results indicate that KLF12 plays an important role in CRC progression and provides a potential novel prognostic marker and therapeutic target.

Results of preclinical studies by MUSC investigators reported in the July 2016 issue of PLOS One (doi:10.1371/journal.pone.0159899) demonstrate for the first time that the transcription factor Krüppel-like factor 12 (KLF12) promotes poor colorectal cancer (CRC) cell growth, in part, by activating EGR1. Furthermore, data demonstrate that KLF12 and early growth response protein 1 (EGR1) levels synergistically correlate with  CRC prognoses.

CRC is the third most common and third deadliest cancer in the US. Like most cancers, CRC development is spurred by a series of genetic mutations and epigenetic changes that alter gene expression. In turn, this altered gene expression initiates tumors and supports their progression. Thus, transcription factors that regulate gene expression and signaling pathways during carcinogenesis have long been studied as potential therapeutic targets.

Dr. Raymond DuBois, Dean of the MUSC College of Medicine, Professor of Biochemistry and Molecular Biology, and senior author on the article is focused on understanding the role of inflammation in cancer. "We've been studying the connections between inflammation and cancer in my lab for some time now and have determined that some inflammatory mediators stimulate the progression of cancer,” DuBois said. “We found that KLF12 was increased dramatically in the presence of inflammation in certain cancers, so we were trying to determine the specific molecular mechanisms responsible for these effects."

Other researchers who were studying kidney development previously identified transcription factor KLF12 as a transcriptional repressor of the AP-2? gene. It was then discovered that AP-2? expression is also reduced in advanced CRC tumor tissue compared to matched normal tissue and that loss of AP-2? promoted CRC invasion. This connection illuminated a potential link between KLF12 and CRC. In vitro studies show that KLF12 promotes gastric cancer (GC) cell proliferation and invasion, and that KLF12 levels are elevated in about 40% of poorly differentiated GCs and correlate with tumor size. Furthermore, recent genome-wide analyses find high KLF12 levels in approximately 40% of esophageal adenocarcinomas and in 45% of salivary tumors. Until now, however, the role of KLF12 in CRC remained unclear.

The MUSC research team designed a series of in vitro and in vivo experiments to clarify the role of KLF12 in CRC. The first set of studies examined KLF12 expression in seven human CRC cell lines. They found not only that KLF12 was expressed in six of the seven cell lines, but also that its overexpression led to increased cell numbers and KLF12 knockdown led to reduced cell numbers. In addition, they also found that overexpression of KLF12 led to the formation of larger cecal tumors while KLF12 knockdown led to formation of smaller cecal tumors, compared to controls. Thus, this set of experiments indicates that KLF12 promotes CRC growth by enhancing cancer cell proliferation and/or survival.

The next set of experiments focused on clarifying which KLF12 target genes may be involved in regulating CRC growth. Using microarray assays, the researchers found that KLF12 overexpression altered multiple genes including EGR1. It has been previously reported that KLF12 regulates expression of some target genes by binding to the CACCC motif.  They found that the EGR1 promoter contains two possible KLF12 DNA-binding motifs located at -1488bp (motif 1) and -808bp (motif 2) relative to the transcription start site. Using ChIP assay, the MUSC researcher team found that KLF12 does, indeed, bind strongly to the EGR1 promoter motif 2 but not to motif 1. In vitro experiments demonstrated that, at both the mRNA and protein levels, CRC cells with undetectable levels of KLF12 expressed the lowest levels of EGR1 compared to cells expressing high levels of KLF12. In vivo studies using mice implanted with CRC tumor cells that overexpressed KLF12 showed that EGR1 expression was up-regulated compared to mice implanted with control cells. Furthermore, staining of human CRC tissue specimens produced the same pattern. Taken together, these results indicate that KLF12 directly activates EGR1 in CRC.

The third set of experiments looked at whether EGR1 mediated the effects of KLF12 on tumor cell growth. Results showed that EGR1 knockdown reduced KLF12-induced tumor cell growth, whereas EGR1 overexpression promoted CRC cell growth in vitro as well as tumor growth in the mouse model. The results of this set of studies, thus, indicate that KLF12 enhances CRC cell growth by activating EGR1.

The final set of experiments evaluated whether KLF12 and EGR1 levels correlate with CRC patients' prognoses. Using gene expression data from publicly available microarray databases (Moffitt [n = 177]; Vanderbilt Medical Center [n = 55]), CRC patients were stratified by level of KLF12 and/or EGR1 expression. These data showed that patients with high levels of either KLF12 or EGR1 had worse outcomes compared to those with low levels of these genes, and that those with high levels of both KLF12 and EGR1 had the lowest survival rates.

This is the first study to clarify the role of KLF12 in CRC tumor growth and progression, which appears to occur, at least in part, through EGR1 activation. The finding that synergistic contributions of KLF12 and EGR1 produce the worst outcomes among CRC patients illuminates their potential in developing novel therapies. More studies are needed to further clarify the role of KLF12 in CRC progression and its potential as a novel prognostic marker and therapeutic target. 

External carotidIn an article published ahead of print on November 24, 2015 in the journal Diabetes (available at http://dx.doi.org/10.2337/db15-0930), researchers from the Medical University of South Carolina (MUSC), the American University of Beirut (AUB), and Case Western Reserve University report that a molecule called pre-kallikrein (PK) could be a target for the vascular complications associated with type 1 diabetes. PK has been formerly suggested as a marker for diabetic vascular disease of the kidneys, but the new work supports the idea that increased plasma PK levels are an independent risk factor for whole-body diabetic vascular disease, similar to the risks of high triglycerides or high blood pressure in heart disease. Ayad A. Jaffa, Ph.D., who holds a dual appointment at MUSC and AUB, led the study. Other MUSC investigators included Miran A Jaffa, Ph.D., Deirdre Luttrell, Ph.D., Richard L. Klein, Ph.D., Maria Lopes-Virella, M.D., Ph.D., and Louis M Luttrell, M.D., Ph.D.  

PK is a member of the kallikrein-kinin system, a group of molecules that frequent the walls of blood vessels. In healthy vessels, circulating PK reaches the vessel surface and activates a sequence of molecular signals that travel inward to the inner vessel layers, called the intima-media, causing momentary changes in dilation and tension. The types of blood vessel malfunction seen in patients with diabetes causes the cells of the intima-media to spread to the surface, allowing PK to contact them directly. This contact closes the circuit of an alternative pathway of chronic inflammation. Scientists who study the kallikrein-kinin system suspect that this chronic inflammation is responsible for the blood vessel thickening observed in diabetic kidney disease, retinopathy, and atherosclerosis.

Jaffa’s team wanted to know if these suspicions were relevant to patients. Specifically, are levels of PK in the blood associated with the blood vessel thickening commonly seen in people with type 1 diabetes?

They started by examining patient samples housed at MUSC and collected as part of a multi-center observational study, called the Epidemiology of Diabetes Interventions and Complications, designed to track the complications and progression of vascular disease in hundreds of people with diabetes. They focused on levels of PK in blood samples paired with ultrasounds taken to measure the thickness of the intima-media of their carotid arteries.

Relevance was found: patients with higher levels of PK in their blood do have thicker layers of intima-media in the vasculature of their carotids.

It isn’t clear if high levels of PK cause arteries to thicken or if thicker arteries release more PK. In other words, Jaffa’s group can’t say yet if PK causes vascular disease or not. Their work, though, is an important first step to developing a treatment for the vascular complications that seem unavoidable for patients with type 1 diabetes. Their next steps involve developing drug candidates to target PK in preclinical experiments. “These preclinical studies not only will give us insights into the involvement of plasma PK in vascular disease,” says Jaffa, “but will also contribute to development of novel treatment strategies for diabetic vascular disease.”

Image Caption: Arteries of the neck - right side. The external carotid artery arises from the common carotid artery - labeled Common caroti on the figure. From Gray's Anatomy 1918. Public Domain Available at http://www.bartleby.com/107/Images/large/image520.gif

heart made out of rope to represent fibrotic heartIn patients with heart failure with a preserved ejection fraction (HFpEF), the prescribed treatments for managing comorbid hypertension do not seem to improve mortality as they do in other heart failure patients. Now MUSC researchers want to know why. In patients with HFpEF, who account for about half of all heart failure cases, the ventricles gradually thicken and stiffen, preventing normal relaxation from beat to beat. The underlying myocardial changes responsible for HFpEF development have proven elusive, providing a major challenge for cardiologists who seek to treat HFpEF patients. Using a translational approach, MUSC researchers and their colleagues are the first to address this challenge directly.

 MUSC Health cardiologists Michael R. Zile, M.D., and John S. Ikonomidis, M.D., Ph.D., along with their MUSC colleagues Catalin Baicu, Ph.D. and Amy Bradshaw, Ph.D., suspect that changes in certain fibrous proteins contribute to left ventricle relaxation deficits in HFpEF patients. Emerging data from a study led by Zile and published in the April 7, 2015 issue of Circulation1 examined changes in collagen and titin, two major fibrous proteins that constitute the physical scaffold necessary for normal relaxation in the heart. Using small myocardial muscle strips extracted from the hearts of 70 cardiac bypass surgery patients, Zile’s group discovered that a measure of ventricular muscle tension during relaxation, called passive stiffness, was pathologically increased in those patients with HFpEF. Just as suspected, this increase was dependent on changes in both collagen and titin. Importantly, these changes were only detected in patients with both hypertension and HFpEF. Moreover, biomarkers in patient plasma reflecting changes in collagen correlated with the presence and severity of HFpEF.

This work, undertaken at MUSC in collaboration with other centers, is the first to use tissue from HFpEF patients to pinpoint specific changes in titin and collagen as important underlying drivers of HFpEF development. How can this new information be used to help patients? Zile states that MUSC scientists are already collaborating with major pharmaceutical partners to develop new biomarker tools for HFpEF detection. “Proteins and peptides that indicate changes in collagen in the heart can be easily measured in small amounts of blood,” says Zile. “These biomarkers can be used to help make early diagnosis and predict prognostic outcomes in HFpEF patients. The arrival for these novel applications is just over the horizon.”

 Reference

 1Zile MR, et al. Myocardial stiffness in patients with heart failure and a preserved ejection fraction: contributions of collagen and titin. Circulation. 2015 Apr 7;131(14):1247-59.

 

In patients with HFpEF, thicker and stiffer ventricles impair normal relaxation and filling.

 

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