Highlights of the Journal Cell for Oct, 2017 (III)

(Continued)

 

 

9. Draw a four-dimensional map of the self-folding of the human genome

 

Suhas S.P. Rao, Su-Chen Huang, Brian Glenn St Hilaire et al. Cohesin Loss Eliminates All Loop Domains. Cell, 5 October 2017, 171(2):305–320, doi:10.1016/j.cell.2017.09.026

 

Cohesin Loss Eliminates All Loop Domains
Cohesin Loss Eliminates All Loop Domains

In a new study, researchers from institutions such as Baylor College of Medicine, Rice University, Stanford University and Broad Institute, constructed the high-resolution four-dimensional map of the human genome fold for the first time. Thus it can be tracked when the genome folding. This finding may bring new ways of studying genetic diseases. Relevant findings are published in the Cell issue October 5, 2017, entitled “Cohesin Loss Eliminates All Loop Domains.” The essay is written by Dr. Erez Lieberman Aiden, Director of the Center for Genome Structure at Baylor College of Medicine. The first author of the paper is a medical student at Stanford University, Aiden Laboratory member Suhas Rao.

 

To track this folding process, these researchers destroyed Cohesion first, which is a circular protein complex located around almost all known circular DNA. In 2015, they have proposed that Cohesion produces DNA ring structure in the nucleus through an extrusion process.

 

Rao said, “We found that when we destroyed the Cohesion proteins, tens of thousands of DNA ring structures disappeared, and then when we introduced the Cohesion protein, all of these DNA ring structures reappeared. This process is done in minutes, which exactly accords with what the extrusion model predicted. And it suggests that the velocity of Cohesion moving along DNA is the fastest in all known human protein.”

 

But not all things happen as the researchers expected. In some cases, the role of the DNA loop structure is exactly opposite of what the researchers expected.

 

“When we observed that the tens of thousands of DNA loops in the genome became weaker, we noticed an interesting pattern, some weird DNA ring structures got stronger,” said Aiden. “Then, When we introduced Cohesion protein, most of the DNA ring structures reappeared, but these unusual DNA ring structures did the opposite thing again – they disappeared.”

 

By looking closely at how these maps changed over time, these researchers realized that extrusion was not the only mechanism that connected DNA elements together which apart from each other. The second mechanism, called compartmentalization, didn’t involve Cohesion proteins.

 

Rao explained, “The second mechanism we observed was quite different from extrusion, which extruded the two DNA elements on the same chromosome together at a time. The second mechanism could connect a large group of elements to each other, even they are on different chromosomes. And it seems as fast as the first mechanism.”

 

 

10. Identification of driver genes for diffuse large B cell lymphoma

 

Anupama Reddy, Jenny Zhang, Nicholas S. Davis et al. Genetic and Functional Drivers of Diffuse Large B Cell Lymphoma. Cell, 5 October 2017, 171(2):481–494, doi:10.1016/j.cell.2017.09.027

 

Genetic and Functional Drivers of Diffuse Large B Cell Lymphoma
Genetic and Functional Drivers of Diffuse Large B Cell Lymphoma

In a new study, researchers from research institutes such as Duke University Cancer Institute are trying to better understand the gene foundation of a most common form of cancer – diffuse large B cell lymphoma, and how these genes may play a role in the patient’s response to treatment.

 

The researchers analyzed tumor samples from 1001 patients who had been diagnosed with diffuse large B-cell lymphoma in the past 10 years. These patients have been treated in 12 research institutes worldwide.

 

Using whole exome sequencing, these researchers identified 150 driver genes for the disease, most of which were newly identified. They then conduct tests to see if there is an association between these genes and how well the patients respond to standard therapies. They used CRISPR to knock out each of the 20,000 genes in lymphoma cells in order to identify those genes that are crucial for lymphoma cell growth. By assessing genetic outcomes, CRISPR results and clinical outcomes, they found that several crucial genetic associations may help guide therapy.

 

 

11. A comprehensive molecular characterization of muscle-invasive bladder cancer ameliorates therapies

 

Gordon Robertson, Jaegil Kim, Hikmat Al-Ahmadie et al. Comprehensive Molecular Characterization of Muscle-Invasive Bladder Cancer. Cell, Published online: October 5, 2017, doi:10.1016/j.cell.2017.09.007

 

Comprehensive Molecular Characterization of Muscle-Invasive Bladder Cancer
Comprehensive Molecular Characterization of Muscle-Invasive Bladder Cancer

In a new study, a team of researchers from Baylor College of Medicine, Brigham and Women’s Hospital in the United States, MD Anderson Cancer Center at the University of Texas, British Columbia Cancer Research Center and Broad Institute, made a comprehensive analysis of molecular characterization for 412 invasive bladder cancer samples, which led them identified five different bladder cancer subtypes, each with a different sensitivity to a particular therapy. These results may lead to the development of personalized therapies in the future. These research institutes are part of the Cancer Genome Atlas Research Network (TCGA Research Network).

 

In 2014, these researchers published the results of a study of 131 bladder cancer samples in the Nature journal: a study of a comprehensive “multi-omic” profile of the molecular changes that occur with this cancer for the first time. This is a major advance in personalized chemotherapy and is a feature of the TCGA Research Network project (Nature, 20 March 2014, doi: 10.1038 / nature12965). This new study expands on the 2014 study, involving a larger research community, integrating more genomic data types, and refining molecular subtypes of bladder cancer.

 

Dr. John N. Weinstein, co-author of the paper’s and director of the Department of Bioinformatics and Computational Biology at the MD Anderson Cancer Center at the University of Texas, said: “In this study, we increased the number of bladder cancer samples studied by three-fold from 2014 of the 141 species to 412 in 2017, which led to the identification of another 32 frequently mutated genes and the addition of less common mutations that appear to be involved in this cancer. These altered genes identified provide a variety of opportunities for the development of new therapeutic interventions. Bladder cancer is one of the cancers which have the highest mutation rate. It appears that APOBEC characteristic mutations associated with this higher mutation load, which involved in up to 70% of bladder cancer. Tumors with the highest number of mutations and higher APOBEC levels are associated with survival rates. ”

 

In addition, the integration of multiple molecular parameters (such as mutations, gene amplification, RNA and protein profiling) revealed that bladder cancer can be subdivided into four subtypes. But in 2014, the researchers identified five subtypes type. They suggest that each subtype may associate with a unique response to treatment, and this needs to be validated in future clinical trials.

 

 

12. Breakthrough! Scientists have developed new ways to effectively find cancer drugs

 

Liron Bar-Peled, Esther K. Kemper, Radu M. Suciu, et al. Chemical Proteomics Identifies Druggable Vulnerabilities in a Genetically Defined Cancer.  Cell (2017) doi:10.1016/j.cell.2017.08.051

 

Chemical Proteomics Identifies Druggable Vulnerabilities in a Genetically Defined Cancer
Chemical Proteomics Identifies Druggable Vulnerabilities in a Genetically Defined Cancer

Researchers from the Scripps Research Institute have developed a new strategy which is expected to help discover new anticancer therapies. Researchers use this new strategy to find small molecule inhibitors of proteins that are important for the growth of non-small cell lung cancer (NSCLCs), which accounts for 85% of all lung cancers and are not sensitive to drug therapy.

 

In this study, researchers used proteomic strategies to identify potential targets for NSCLCs. NSCLCs could be supported by over-activation transcription factor NRF2. NRF2 can act as a powerful antioxidant switch, and some cancer cells use this reaction protects itself from the damaging effects of oxidative byproducts, which often have unusual metabolic activity as well as uncontrolled properties.

 

Subsequently, researchers used proteomics platform to identify cysteine molecules in NRF2-driven NSCLCs cells. By inhibiting the expression of NRF2 in cells, the researchers were able to observe how cysteine activity changed. Most of the NRF2-related reactivity changes stem from the changes induced by protein production when NRF2 is deleted, but the 20% reactivity change appears to depend on the oxidative modification of the protein, which is a result of the accumulation of reactive oxygen species in the cell.

 

Bar-Peled, a researcher, said that under normal circumstances we would think that transcription factors such as NRF2 can regulate the enzymes’ function by changing their concentration level, but in many cases, NRF2 seems to alter the environment in which enzymes are present to let the enzymes work better. Next Step, researchers plan to use a pair of highly selective cysteine-binding probes in NSCLC cells to identify potential cysteines that can be used as drugs’ target which may meet two criteria: First, its reactivity will change with the change of NRF2 activity. Second, the host protein can only be expressed in NSCLC cells driven by over-activation NRF2.

 

Interestingly, there is a protein called NR0B1 that satisfies both of the above two criteria and normally functions in lung cancer cell nuclei as part of a protein complex that regulates gene expression. By small molecule compound library screening, the researchers found that two compounds could attach to the NR0B1 protein reactive cysteine, triggering the destruction of the protein complex. Later, the researchers used these compounds as probes to study the function of NR0B1 and found that the protein can promote the expression activity of NRF2 gene. In addition, the researchers also used these compounds to prove that targeting NR0B1 protein has a certain therapeutic effect.

 

 

13. Breakthrough! A group of neurons that perceived light intensity in the retina was found

 

Elliott Scott, Michael Tri Hoang Do. A Population Representation of Absolute Light Intensity in the Mammalian Retina. Cell, Published online: September 28, 2017, doi:10.1016/j.cell.2017.09.005

 

A Population Representation of Absolute Light Intensity in the Mammalian Retina
A Population Representation of Absolute Light Intensity in the Mammalian Retina

In a new study, researchers from Boston Children’s Hospital in the United States described an unexpected way in which we were able to detect the overall level of light in the environment. They found that the neurons in the retina work in a division of labor cooperation that allows specific neurons to be conditioned respond to different light intensity ranges.

 

Unlike rod and cone cells in the retina, which are primarily used to detect shape and motion, other light-sensitive neurons specifically designed to detect “non-image” vision are used to set up our biological clock, regulate sleep and control hormone levels. These neurons, called M1 ganglion cell photoreceptors, play a role even in those who are blind.

 

Milner and Do found that although these M1 cells appear visually indistinguishable from one another, they are regulated to respond to different levels of light, and when these levels of light change, they signal to the brain in turn. Therefore, the brain derives information on light intensity based on the identity of these active cells, not just signal size.

 

Interestingly, the rotation system of these M1 cells uses a mechanism that is often considered abnormal or pathological – depolarization block. Depolarization blocking is usually observed in certain diseases such as epilepsy.

 

As light levels rise, a protein called Melanopsin in M1 cells captures more and more photons. This causes the cell membrane voltage to become more positive, which is “depolarization.” As the cell membrane voltage becomes more positive, these M1 cells produce more electrical spikes (also known as action potentials), that are sent to the brain.