Fetal Alcohol Disorder
An interesting example is provided by the fetal alcohol spectrum disorder, a multisystem condition that is causally linked to maternal alcohol use during pregnancy, and is characterized by physical, behavioral, and cognitive deficits, including developmental delay, growth deficiency, craniofacial dysmorphology, and modifications that affect other organs and systems at various degrees.
Previously, Dr. Zhou and colleagues revealed that ethanol exposure alters the cellular DNA methylation program during early neural tube development, and identified over 2,100 epigenetically changed genes in which the cytosines are differentially methylated in alcohol-treated embryos.
To better understand the protein expression changes that occur as a result of epigenetic and genetic changes in the fetal alcohol spectrum disorder, Dr. Zhou, in collaboration with Stephen Mason, Ph.D., an adjunct researcher who is also in the department of anatomy and cell biology at the Indiana University School of Medicine, used whole-embryo cultures to examine the alcohol-signature protein profile across all cell and tissue types in mice at the early neural developmental stage during neurulation.
“This study is a continuation of our previous studies,” explains Dr. Zhou.
The team identified 40 protein spots that were differentially expressed between alcohol-treated and control cultures. Several of these proteins, confirmed by mass spectrometry, fulfill key roles in the cell cycle and the ubiquitin-proteasome pathway.
The results indicated that epigenetic and genetic changes occurring as a result of alcohol exposure impact protein expression during neurulation. The biological functions that were perturbed were linked to tissues and organs that originate, during development, from all three embryonic layers.
“Analyses of epigenetic modifications and those that survey gene expression, protein expression, and metabolic perturbations are required to investigate the molecular and cellular changes as a whole, to eventually understand the causal mechanisms that differ between two distinct states, such as between the child with developmental delay caused by drinking during pregnancy and the healthy child,” explains Dr. Zhou.
“We are trying to understand how gene expression is regulated, how its deregulation causes disease, and ultimately how we can correct those deregulated states to treat disease,” says Bing Zhang, Ph.D. assistant professor of biomedical informatics at the Vanderbilt University School of Medicine.
Dr. Zhang’s group has explored the possibility of defining a gene expression signature that can be used to make prognostic and therapeutic decisions in patients with colorectal cancer. This malignancy, currently the third leading cause of cancer mortality worldwide, is stratified into four stages (I to IV), with a higher stage being assigned to more serious disease.
Cure, which occurs in approximately 95% of patients with stage I disease treated surgically, is difficult to accomplish in patients with stage IV disease, who also require chemotherapy.
“For stage II and III patients, which represent a large population, the question is whether we need to provide chemotherapy, because previous clinical trials suggest that it is not required for certain patients, but it is beneficial for others,” explains Dr. Zhang.
Histological features, such as tumor size, lymph node positivity, and metastatic dissemination have been used to perform such predictions in the past, but often they were not reliable.
“Our idea was to use gene expression analysis to better predict the prognosis of stage II and III colon cancer patients,” explains Dr. Zhang.
A challenging aspect is that different gene expression signatures from different studies often do not overlap with each other. “We tried to find common biological themes across previously published signatures, and by integrating them into biological networks, we generated a gene expression signature that is more biologically meaningful and, additionally, has a good prognostic value,” says Dr. Zhang.
This approach revealed that genes with mechanistically important roles in colorectal cancer may be used to develop reliable prognostic models that accurately predict recurrences and the response to adjuvant chemotherapy. Gene expression-based stratification of these two cancer stages is crucial for increasing survival and the quality of life, while minimizing the chemotherapy-associated toxic effects and the financial costs involved.