Demystifying Proteomics in Hematology

The central dogma of molecular biology describes the flow of information in a cell, from the DNA in a gene to RNA to protein. Molecular machinery within a cell transcribes a gene or other segment of DNA into an RNA copy. If the RNA codes for a protein, the RNA is then translated into a protein with a biological function inside or outside of the cell.

Large-scale molecular techniques to study DNA, RNA, and proteins have generally evolved in the same sequence as the central dogma. First came DNA sequencing to catalog the coding and noncoding DNA sequences within a given species. The first full DNA sequence, of the phiX174 virus, was produced in 1977 by Frederick Sanger and, in 1995, researchers sequenced the first bacterial genome, that of Haemophilus influenzae.

In the 1990s, researchers began to study the full catalog of an organism’s RNA transcripts, produced from the genome, called the transcriptome.1 The transcriptome is analyzed using a tool called a microarray or with RNA-Seq, which uses high-throughput sequencing to capture a snapshot of all the RNA molecules in a cell or tissue at a given time. In an early success of RNA-Seq, in 2006, researchers at the British Columbia Cancer Agency Genome Sciences Centre captured all the RNA transcripts in a prostate cancer cell line.2

These whole genome and transcriptome catalogs have enabled the study of the proteome – the set of proteins present in a cell at a given time. The field of proteomics uses mass spectrometry to identify and even quantitate the proteins in a cell or tissue, often using genomic databases as a reference.

“There has been a big effort to use proteomics to understand and catalog the proteins in the blood and other fluids,” said Jean-Daniel Tissot, MD, professor of medicine and dean of the Faculty of Biology and Medicine at the University of Lausanne in Switzerland. “Most of the research on the proteome of blood and plasma has been to identify potential biomarkers of disease.”

Analyzing proteins found in the blood has been a long-standing interest of hematology researchers. In 1977, scientists identified 40 proteins found in plasma using a two-dimensional electrophoresis technique.3 Fast-forward to 2017, and the Human Plasma Proteome Project has identified 3,509 human plasma proteins using mass spectrometry, since its inception in 2002.4 Additional open-access databases from large-scale, proteomic projects have turned their sights on the platelet proteome and the red blood cell proteome.5,6

ASH Clinical News spoke with Dr. Tissot and other researchers about the principles of proteomic analysis and its application in the laboratory and the clinic.

Proteomics 101

Because most genes encode for protein products rather than RNA products, the collection of proteins in a cell or tissue provide the most detailed information about the biology, physiology, and pathological state of cells. The protein is the final functional product, the end goal of a cell’s genome.

The proteome is highly complex, encompassing protein structure, function, regulation, and interactions. The proteome also is functionally more complicated and heterogeneous than either the genome or transcriptome because, following translation, each protein can be chemically modified by attached carbohydrate groups and other modifications including phosphorylation, acetylation, and methylation.

“[Proteomic analysis] is a fantastic tool to characterize proteins and their post-translational modifications.”

—Jean-Daniel Tissot, MD

“Just knowing whether a protein is present usually is not the most important information,” said Steven M. Kornblau, MD, professor in the department of leukemia and stem cell transplantation at the MD Anderson Cancer Center in Houston. “It is important to understand if a protein has undergone a post-translational modification, such as phosphorylation, which typically converts the protein to its active form, for example. You can’t get that kind of information from messenger RNA profiling.”

Dr. Kornblau’s lab uses proteomic tools to characterize hematologic malignancies. For proteomics researchers, protein-level information is the ultimate goal in cancer research because the protein function regulates the phenotype of wild-type cells and cancer cells – providing information about a cell’s response to its environment and its pathogenetic state.

“If there is a mutation in the genome, it is good to know, but it is better to know if that mutation is transcribed into RNA and then, third, if the RNA is translated into an active protein,” he explained. “These ‘third protein level’ data – the proteomic data – are ultimately better positioned than genomic or transcriptome data to tell us how much of an actual effector there is in the activated state.”

The Proteomics Toolkit

Most techniques used in proteomic analyses require that protein samples are first fractionated to isolate various subcellular organelles. Then samples are separated and analyzed using mass spectrometry.

Proteins can be separated using affinity separation methods, by two-dimensional gel electrophoresis, or one- or two-dimensional chromatographic separation. Two-dimensional gel electrophoresis is frequently used to separate complex mixes of proteins by two protein properties, isoelectric point and molecular weight, to study both qualitative and quantitative protein changes among different samples. One-dimensional liquid chromatography, when used with electrospray mass spectrometry analysis, generates high-quality data about the types of proteins in a sample, but this tool cannot be used to quantitate proteins.

The next step after protein separation is protein content analysis, including identifying even small amounts of proteins, using mass spectrometry. Mass spectrometry is used in hematology biomedical research because the tool does not require a large sample to run the analysis and can be used to analyze proteins, peptides, and their post-translational modifications.

“We can identify minor modifications between two proteins or two peptides, including oxidation of amino acids and phosphorylation,” explained Dr. Tissot. “This is a fantastic tool to characterize proteins and their post-translational modifications.”

Another protein analytical tool is reverse phase protein array (RPPA), a sensitive and high-throughput technology to quantitate hundreds of proteins and phosphoproteins in biological or clinical samples. In this type of analysis, protein lysates from as many as 1,000 samples are printed onto a slide and probed with the same antibody.

The technique allows for reproducibility and sensitivity but does not allow for the assessment of an entire proteome. “This is a great technique for discovering targets and biomarkers,” said Dr. Kornblau, “but it is too time-consuming to have potential in the clinic.”

Characterizing Diseases

Proteomics is helping researchers better understand hematologic malignancies and other blood disorders, such as genetic coagulation disorders and amyloidosis.

“It is important to use proteomics for hematologic diseases where there is accumulation of proteins, as is the case with amyloidosis,” said Dr. Tissot. “It is possible to take a patient’s tissue sample and do direct proteomic analysis to characterize the accumulation of these proteins. Now, we also can isolate single cells for proteomic analyses, identifying different malignant cell populations or different types of cells that are found during differentiation and maturation of white blood cells.”

In 2005, scientists at the National Cancer Center Research Institute in Japan conducted a large-scale proteomic analysis of cell lines derived from human lymphoid cancers, including Hodgkin lymphoma and Burkitt’s lymphoma, to identify unique protein patterns among these B- and T-cell malignancies.7 They found that Hodgkin lymphoma has a unique protein expression profile that differentiated it from wild-type B and T cells and other blood cancers; ultimately, they hope to use these patterns as novel diagnostic markers for the disease.

Similarly, in 2009, Dr. Kornblau and his colleagues used RPPA to classify acute myeloid leukemia (AML). They assayed leukemia-enriched cells from 256 patients with newly diagnosed AML, identifying a total of 51 proteins that contribute to apoptosis, cell cycle regulation, and other functions often mutated in cancers. These proteins provided prognostic information that was distinct from the cytogenetics of AML cells and correlated with remissions, relapse, and patient survival.8 His team also discovered that they could obtain the same protein levels whether the samples were derived from a blood draw or bone marrow.

More recently, in 2019, they were able to probe their AML samples using antibodies that targeted many more proteins – more than 250 of them.9

In another project, Dr. Kornblau, along with pediatric oncologist Terzah Marie Horton, MD, PhD, from Baylor College of Medicine and Texas Children’s Hospital, led a team that analyzed the proteomic landscape of pediatric AML to identify potential new drug targets. The researchers found distinct protein signatures that, when combined with the cytogenetics of a patient’s AML, could add to the prognosis information for patients.10

They also assayed cells for the presence of a select group of proteins in pediatric patients with AML and identified select patients that could benefit from treatment with the proteasome inhibitor bortezomib in combination with a standard chemotherapy regimen.11

“We found protein signatures from patients that correlated with a benefit from the addition of bortezomib, as well as those groups that appeared to have no benefit from the addition of bortezomib,” Dr. Horton noted.

Drs. Horton and Kornblau said that, after additional proteomic analyses, they plan to conduct a study in pediatric AML in which patients will be screened for these protein signatures and given bortezomib if their signature predicts a response. “This research is a ‘poster child’ example of where proteomics is allowing us to identify a subgroup of patients that are likely to benefit from a drug,” added Dr. Kornblau.

All these disease characterizations have yet not made it into general medical practice, according to Drs. Tissot and Kornblau. So far, identifying a single or a few protein biomarkers of disease has not proven to be a reliable way to make an early diagnosis of a hematologic malignancy, Dr. Tissot noted.

He sees the greatest translational potential for bringing proteomic data into the clinic in developing novel immunotherapies. “It is important to identify novel target peptides that are produced by cancer cells that we can then use for immunotherapy such as chimeric antigen receptor T-cell therapy and vaccination,” he said.

The University of Lausanne, where Dr. Tissot conducts research, is now working on a large-scale analysis of peptides that are uniquely produced by tumor cells and that can be recognized by T cells to develop new immunotherapy targets. “This is a huge effort and proteomic approaches are essential because we need to identify – accurately – the actual peptides and proteins that are being made by the cancer cells,” he noted.

Limitations and Complementation

One drawback of proteomic analysis is the time it takes to go from a sample to a full analytical result, which is typically on the order of several weeks for a large-scale proteome data set. Single cell sorting followed by mass spectrometry is quicker, by about one day.

Proper protein sample preparation is crucial, according to Dr. Tissot, as proteins are far less stable than DNA or even RNA. Samples need to be processed quickly to avoid delays between blood collection and isolating plasma or cell types that may allow time for artifacts to be introduced.

Another limitation is that, so far, it is difficult to accurately quantitate protein levels in a sample using available mass spectrometry techniques.

For Dr. Tissot, combining proteomic approaches with other modalities, including analysis of the genome and the RNA in cancer cells, is critical “to have a global view of what happens in cancer cells and the differences in their metabolism.”

“This is basic research that is crucial to understand how these cells function and respond to their environment,” he added.

“Proteomics is not yet daily lab work for hematologists,” said Dr. Tissot. “These are not yet widespread approaches, although they are coming for blood cancer, immunotherapy, and protein-based diseases such as amyloidosis. It’s important that we develop these protein tools.” —By Anna Azvolinsky

References

  1. Lowe R, Shirley N, Bleackley M, et al. Transcriptomics technologies. PLoS Comput Biol. 2017;13:e1005457.
  2. Bainbridge MN, Warren RL, Hirst M, et al. Analysis of the prostate cancer cell line LNCaP transcriptome using a sequencing-by-synthesis approach. BMC Genomics. 2006;7:246.
  3. Anderson L, Anderson NG. High-resolution two-dimensional electrophoresis of human plasma proteins. Proc Natl Acad Sci. 1977;74:5421-5.
  4. Schwenk JM, Omenn GS, Sun Z, et al. The human plasma proteome draft of 2017: building on the Human Plasma PeptideAtlas from mass spectrometry and complementary assays. J Proteome Res. 2017;16: 4299-310.
  5. Burkhart JM, Vaudel M, Gambaryan S, et al. The first comprehensive and quantitative analysis of human platelet protein composition allows the comparative analysis of structural and functional pathways. Blood; 2012;120:e73-e82.
  6. Bryk AH, Wiśniewski JR. Quantitative analysis of human red blood cell proteome. J Proteome Res. 2017;16:2752-61.
  7. Fujii K, Kondo T, Yokoo H, et al. Protein expression pattern distinguishes different lymphoid neoplasms. Proteomics. 2005;5:4274-86.
  8. Kornblau SM, Tibes R, Qui YH, et al. Functional proteomic profiling of AML predicts response and survival. Blood. 2009;113:154-64.
  9. Hu CW, Qiu Y, Ligeralde A, et al. A quantitative analysis of heterogeneities and hallmarks in acute myelogenous leukaemia. Nat Biomed Eng. 2019 April 15. [Epub ahead of print]
  10. Hoff FW, Qiu Y, Hu W, et al. Proteomic landscape of de novo pediatric acute myeloid leukemia. Blood. 2018;132(Suppl 1):294.
  11. Hoff FW, Qiu Y, Hu W, et al. Proteomic profiling of the unfolded protein response identifies patients benefiting from bortezomib in pediatric acute myeloid leukemia. Abstract #451. Presented at the 2018 AACR Annual Meeting, April 14, 2018; Philadelphia, PA.

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