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Saturday, June 17, 2023

Immune tolerance

From Wikipedia, the free encyclopedia

Immune tolerance, or immunological tolerance, or immunotolerance, is a state of unresponsiveness of the immune system to substances or tissue that would otherwise have the capacity to elicit an immune response in a given organism. It is induced by prior exposure to that specific antigen and contrasts with conventional immune-mediated elimination of foreign antigens (see Immune response). Tolerance is classified into central tolerance or peripheral tolerance depending on where the state is originally induced—in the thymus and bone marrow (central) or in other tissues and lymph nodes (peripheral). The mechanisms by which these forms of tolerance are established are distinct, but the resulting effect is similar.

Immune tolerance is important for normal physiology. Central tolerance is the main way the immune system learns to discriminate self from non-self. Peripheral tolerance is key to preventing over-reactivity of the immune system to various environmental entities (allergens, gut microbes, etc.). Deficits in central or peripheral tolerance also cause autoimmune disease, resulting in syndromes such as systemic lupus erythematosus, rheumatoid arthritis, type 1 diabetes, autoimmune polyendocrine syndrome type 1 (APS-1), and immunodysregulation polyendocrinopathy enteropathy X-linked syndrome (IPEX), and potentially contribute to asthma, allergy, and inflammatory bowel disease. And immune tolerance in pregnancy is what allows a mother animal to gestate a genetically distinct offspring with an alloimmune response muted enough to prevent miscarriage.

Tolerance, however, also has its negative tradeoffs. It allows for some pathogenic microbes to successfully infect a host and avoid elimination. In addition, inducing peripheral tolerance in the local microenvironment is a common survival strategy for a number of tumors that prevents their elimination by the host immune system.

Historical background

The phenomenon of immune tolerance was first described by Ray D. Owen in 1945, who noted that dizygotic twin cattle sharing a common placenta also shared a stable mixture of each other's red blood cells (though not necessarily 50/50), and retained that mixture throughout life. Although Owen did not use the term immune tolerance, his study showed the body could be tolerant of these foreign tissues. This observation was experimentally validated by Leslie Brent, Rupert E. Billingham and Peter Medawar in 1953, who showed by injecting foreign cells into fetal or neonatal mice, they could become accepting of future grafts from the same foreign donor. However, they were not thinking of the immunological consequences of their work at the time: as Medawar explains:

"We did not set out with the idea in mind of studying the immunological consequences of the phenomenon described by Owen; on the contrary, we had been goaded by Dr. H.P. Donald into trying to devise a foolproof method of distinguishing monozygotic from dizygotic twins... ."

However, these discoveries, and the host of allograft experiments and observations of twin chimerism they inspired, were seminal for the theories of immune tolerance formulated by Sir Frank McFarlane Burnet and Frank Fenner, who were the first to propose the deletion of self-reactive lymphocytes to establish tolerance, now termed clonal deletion. Burnet and Medawar were ultimately credited for "the discovery of acquired immune tolerance" and shared the Nobel Prize in Physiology or Medicine in 1960.

Definitions and usage

In their Nobel Lecture, Medawar and Burnet define immune tolerance as "a state of indifference or non-reactivity towards a substance that would normally be expected to excite an immunological response." Other more recent definitions have remained more or less the same. The 8th edition of Janeway's Immunobiology defines tolerance as "immunologically unresponsive…to another's tissues.".

Immune tolerance encompasses the range of physiological mechanisms by which the body reduces or eliminates an immune response to particular agents. It is used to describe the phenomenon underlying discrimination of self from non-self, suppressing allergic responses, allowing chronic infection instead of rejection and elimination, and preventing attack of fetuses by the maternal immune system. Typically, a change in the host, not the antigen, is implied. Though some pathogens can evolve to become less virulent in host-pathogen coevolution, tolerance does not refer to the change in the pathogen but can be used to describe the changes in host physiology. Immune tolerance also does not usually refer to artificially induced immunosuppression by corticosteroids, lymphotoxic chemotherapy agents, sublethal irradiation, etc. Nor does it refer to other types of non-reactivity such as immunological paralysis. In the latter two cases, the host's physiology is handicapped but not fundamentally changed.

Immune tolerance is formally differentiated into central or peripheral; however, alternative terms such as "natural" or "acquired" tolerance have at times been used to refer to establishment of tolerance by physiological means or by artificial, experimental, or pharmacological means. These two methods of categorization are sometimes confused, but are not equivalent—central or peripheral tolerance may be present naturally or induced experimentally. This difference is important to keep in mind.

Central tolerance

Central tolerance refers to the tolerance established by deleting autoreactive lymphocyte clones before they develop into fully immunocompetent cells. It occurs during lymphocyte development in the thymus and bone marrow for T and B lymphocytes, respectively. In these tissues, maturing lymphocytes are exposed to self-antigens presented by medullary thymic epithelial cells and thymic dendritic cells, or bone marrow cells. Self-antigens are present due to endogenous expression, importation of antigen from peripheral sites via circulating blood, and in the case of thymic stromal cells, expression of proteins of other non-thymic tissues by the action of the transcription factor AIRE.

Those lymphocytes that have receptors that bind strongly to self-antigens are removed by induction of apoptosis of the autoreactive cells, or by induction of anergy, a state of non-activity. Weakly autoreactive B cells may also remain in a state of immunological ignorance where they simply do not respond to stimulation of their B cell receptor. Some weakly self-recognizing T cells are alternatively differentiated into natural regulatory T cells (nTreg cells), which act as sentinels in the periphery to calm down potential instances of T cell autoreactivity (see peripheral tolerance below).

The deletion threshold is much more stringent for T cells than for B cells since T cells alone can cause direct tissue damage. Furthermore, it is more advantageous for the organism to let its B cells recognize a wider variety of antigen so it can produce antibodies against a greater diversity of pathogens. Since the B cells can only be fully activated after confirmation by more self-restricted T cells that recognize the same antigen, autoreactivity is held in check.

This process of negative selection ensures that T and B cells that could initiate a potent immune response to the host's own tissues are eliminated while preserving the ability to recognize foreign antigens. It is the step in lymphocyte education that is key for preventing autoimmunity (entire process detailed here). Lymphocyte development and education is most active in fetal development but continues throughout life as immature lymphocytes are generated, slowing as the thymus degenerates and the bone marrow shrinks in adult life.

Peripheral tolerance

Peripheral tolerance develops after T and B cells mature and enter the peripheral tissues and lymph nodes. It is established by a number of partly overlapping mechanisms that mostly involve control at the level of T cells, especially CD4+ helper T cells, which orchestrate immune responses and give B cells the confirmatory signals they need in order to produce antibodies. Inappropriate reactivity toward normal self-antigen that was not eliminated in the thymus can occur, since the T cells that leave the thymus are relatively but not completely safe. Some will have receptors (TCRs) that can respond to self-antigens that:

  • are present in such high concentration outside the thymus that they can bind to "weak" receptors.
  • the T cell did not encounter in the thymus (such as, tissue-specific molecules like those in the islets of Langerhans, brain, or spinal cord not expressed by AIRE in thymic tissues).

Those self-reactive T cells that escape intrathymic negative selection in the thymus can inflict cell injury unless they are deleted or effectively muzzled in the peripheral tissue chiefly by nTreg cells (see central tolerance above).

Appropriate reactivity toward certain antigens can also be quieted by induction of tolerance after repeated exposure, or exposure in a certain context. In these cases, there is a differentiation of naïve CD4+ helper T cells into induced Treg cells (iTreg cells) in the peripheral tissue or nearby lymphoid tissue (lymph nodes, mucosal-associated lymphoid tissue, etc.). This differentiation is mediated by IL-2 produced upon T cell activation, and TGF-β from any of a variety of sources, including tolerizing dendritic cells (DCs), other antigen presenting cells, or in certain conditions surrounding tissue.

Treg cells are not the only cells that mediate peripheral tolerance. Other regulatory immune cells include T cell subsets similar to but phenotypically distinct from Treg cells, including TR1 cells that make IL-10 but do not express Foxp3, TGF-β-secreting TH3 cells, as well as other less well-characterized cells that help establish a local tolerogenic environment. B cells also express CD22, a non-specific inhibitor receptor that dampens B cell receptor activation. A subset of B regulatory cells that makes IL-10 and TGF-β also exists. Some DCs can make Indoleamine 2,3-dioxygenase (IDO) that depletes the amino acid tryptophan needed by T cells to proliferate and thus reduce responsiveness. DCs also have the capacity to directly induce anergy in T cells that recognize antigen expressed at high levels and thus presented at steady-state by DCs. In addition, FasL expression by immune privileged tissues can result in activation-induced cell death of T cells.

nTreg vs. iTreg cells

The involvement of T cells, later classified as Treg cells, in immune tolerance was recognized in 1995 when animal models showed that CD4+ CD25+ T cells were necessary and sufficient for the prevention of autoimmunity in mice and rats. Initial observations showed removal of the thymus of a newborn mouse resulted in autoimmunity, which could be rescued by transplantation of CD4+ T cells. A more specific depletion and reconstitution experiment established the phenotype of these cells as CD4+ and CD25+. Later in 2003, experiments showed that Treg cells were characterized by the expression of the Foxp3 transcription factor, which is responsible for the suppressive phenotype of these cells.

It was assumed that, since the presence of the Treg cells originally characterized was dependent on the neonatal thymus, these cells were thymically derived. By the mid-2000s, however, evidence was accruing of conversion of naïve CD4+ T cells to Treg cells outside of the thymus. These were later defined as induced or iTreg cells to contrast them with thymus-derived nTreg cells. Both types of Treg cells quieten autoreactive T cell signaling and proliferation by cell-contact-dependent and -independent mechanisms including:

  • Contact-dependent:
  • Contact-independent
  • Secretion of TGF-β, which sensitizes cells to suppression and promotes Treg-like cell differentiation
  • Secretion of IL-10
  • Cytokine absorption leading to cytokine deprivation-mediated apoptosis

nTreg cells and iTreg cells, however, have a few important distinguishing characteristics that suggest they have different physiological roles:

  • nTreg cells develop in the thymus; iTreg cells develop outside the thymus in chronically inflamed tissue, lymph nodes, spleen, and gut-associated lymphoid tissue (GALT).
  • nTreg cells develop from Foxp3- CD25+ CD4+ cells while iTreg cells develop from Foxp3+ CD25- CD4- cells (both become Foxp3+ CD25+CD4+).
  • nTreg cells, when activated, require CD28 costimulation, while iTreg cells require CTLA-4 costimulation.
  • nTreg cells are specific, modestly, for self-antigen while iTreg cells recognize allergens, commensal bacteria, tumor antigens, alloantigens, and self-antigens in inflamed tissue.

Tolerance in physiology and medicine

Allograft tolerance

Immune recognition of non-self-antigens typically complicates transplantation and engrafting of foreign tissue from an organism of the same species (allografts), resulting in graft reaction. However, there are two general cases in which an allograft may be accepted. One is when cells or tissue are grafted to an immune-privileged site that is sequestered from immune surveillance (like in the eye or testes) or has strong molecular signals in place to prevent dangerous inflammation (like in the brain). The second is when a state of tolerance has been induced, either by previous exposure to the antigen of the donor in a manner that causes immune tolerance rather than sensitization in the recipient, or after chronic rejection. Long-term exposure to a foreign antigen from fetal development or birth may result in establishment of central tolerance, as was observed in Medawar's mouse-allograft experiments. In usual transplant cases, however, such early prior exposure is not possible. Nonetheless, a few patients can still develop allograft tolerance upon cessation of all exogenous immunosuppressive therapy, a condition referred to as operational tolerance. CD4+ Foxp3+ Treg cells, as well as CD8+ CD28- regulatory T cells that dampen cytotoxic responses to grafted organs, are thought to play a role. In addition, genes involved in NK cell and γδT cell function associated with tolerance have been implicated for liver transplant patients. The unique gene signatures of these patients implies their physiology may be predisposed toward immune tolerance.

Fetal development

The fetus has a different genetic makeup than the mother, as it also translates its father's genes, and is thus perceived as foreign by the maternal immune system. Women who have borne multiple children by the same father typically have antibodies against the father's red blood cell and major histocompatibility complex (MHC) proteins. However, the fetus usually is not rejected by the mother, making it essentially a physiologically tolerated allograft. It is thought that the placental tissues which interface with maternal tissues not only try to escape immunological recognition by downregulating identifying MHC proteins but also actively induce a marked peripheral tolerance. Placental trophoblast cells express a unique Human Leukocyte Antigen (HLA-G) that inhibits attack by maternal NK cells. These cells also express IDO, which represses maternal T cell responses by amino acid starvation. Maternal T cells specific for paternal antigens are also suppressed by tolerogenic DCs and activated iTregs or cross-reacting nTregs. Some maternal Treg cells also release soluble fibrinogen-like proteins 2 (sFGL2), which suppresses the function of DCs and macrophages involved in inflammation and antigen presentation to reactive T cells[24] These mechanisms altogether establish an immune-privileged state in the placenta that protects the fetus. A break in this peripheral tolerance results in miscarriage and fetal loss. (for more information, see Immune tolerance in pregnancy).

The microbiome

The skin and digestive tract of humans and many other organisms is colonized with an ecosystem of microorganisms that is referred to as the microbiome. Though in mammals a number of defenses exist to keep the microbiota at a safe distance, including a constant sampling and presentation of microbial antigens by local DCs, most organisms do not react against commensal microorganisms and tolerate their presence. Reactions are mounted, however, to pathogenic microbes and microbes that breach physiological barriers(epithelium barriers). Peripheral mucosal immune tolerance, in particular, mediated by iTreg cells and tolerogenic antigen-presenting cells, is thought to be responsible for this phenomenon. In particular, specialized gut CD103+ DCs that produce both TGF-β and retinoic acid efficiently promotes the differentiation of iTreg cells in the gut lymphoid tissue. Foxp3- TR1 cells that make IL-10 are also enriched in the intestinal lining. Break in this tolerance is thought to underlie the pathogenesis of inflammatory bowel diseases like Crohn's disease and ulcerative colitis.

Oral tolerance and hypersensitivity

Oral tolerance refers to a specific type of peripheral tolerance induced by antigens given by mouth and exposed to the gut mucosa and its associated lymphoid tissues. The hypo-responsiveness induced by oral exposure is systemic and can reduce hypersensitivity reactions in certain cases. Records from 1829 indicate that American Indians would reduce contact hypersensitivity from poison ivy by consuming leaves of related Rhus species; however, contemporary attempts to use oral tolerance to ameliorate autoimmune diseases like rheumatoid arthritis and other hypersensitivity reactions have been mixed. The systemic effects of oral tolerance may be explained by the extensive recirculation of immune cells primed in one mucosal tissue in another mucosal tissue, allowing extension of mucosal immunity. The same probably occurs for cells mediating mucosal immune tolerance.

Oral tolerance may depend on the same mechanisms of peripheral tolerance that limit inflammation to bacterial antigens in the microbiome since both involve the gut-associated lymphoid tissue. It may also have evolved to prevent hypersensitivity reactions to food proteins. It is of immense immunological importance, since it is a continuous natural immunologic event driven by exogenous antigen.

Allergy and hypersensitivity reactions in general are traditionally thought of as misguided or excessive reactions by the immune system, possibly due to broken or underdeveloped mechanisms of peripheral tolerance. Usually, Treg cells, TR1, and Th3 cells at mucosal surfaces suppress type 2 CD4 helper cells, mast cells, and eosinophils, which mediate allergic response. Deficits in Treg cells or their localization to mucosa have been implicated in asthma and atopic dermatitis. Attempts have been made to reduce hypersensitivity reactions by oral tolerance and other means of repeated exposure. Repeated administration of the allergen in slowly increasing doses, subcutaneously or sublingually appears to be effective for allergic rhinitis. Repeated administration of antibiotics, which can form haptens to cause allergic reactions, can also reduce antibiotic allergies in children.

The tumor microenvironment

Immune tolerance is an important means by which growing tumors, which have mutated proteins and altered antigen expression, prevent elimination by the host immune system. It is well recognized that tumors are a complex and dynamic population of cells composed of transformed cells as well as stromal cells, blood vessels, tissue macrophages, and other immune infiltrates. These cells and their interactions all contribute to the changing tumor microenvironment, which the tumor largely manipulates to be immunotolerant so as to avoid elimination. There is an accumulation of metabolic enzymes that suppress T cell proliferation and activation, including IDO and arginase, and high expression of tolerance-inducing ligands like FasL, PD-1, CTLA-4, and B7. Pharmacologic monoclonal antibodies targeted against some of these ligands has been effective in treating cancer. Tumor-derived vesicles known as exosomes have also been implicated promoting differentiation of iTreg cells and myeloid derived suppressor cells (MDSCs), which also induce peripheral tolerance. In addition to promoting immune tolerance, other aspects of the microenvironment aid in immune evasion and induction of tumor-promoting inflammation.

Evolution

Though the exact evolutionary rationale behind the development of immunological tolerance is not completely known, it is thought to allow organisms to adapt to antigenic stimuli that will consistently be present instead of expending considerable resources fighting it off repeatedly. Tolerance in general can be thought of as an alternative defense strategy that focuses on minimizing impact of an invader on host fitness, instead of on destroying and eliminating the invader. Such efforts may have a prohibitive cost on host fitness. In plants, where the concept was originally used, tolerance is defined as a reaction norm of host fitness over a range of parasite burdens, and can be measured from the slope of the line fitting these data. Immune tolerance may constitute one aspect of this defense strategy, though other types of tissue tolerance have been described.

Schematic of the reaction norm of tolerance. Organisms of genotype 2 are considered more tolerant to the pathogen than organisms of genotype 1.

The advantages of immune tolerance, in particular, may be seen in experiments with mice infected with malaria, in which more tolerant mice have higher fitness at greater pathogen burdens. In addition, development of immune tolerance would have allowed organisms to reap the benefits of having a robust commensal microbiome, such as increased nutrient absorption and decreased colonization by pathogenic bacteria.

Though it seems that the existence of tolerance is mostly adaptive, allowing an adjustment of the immune response to a level appropriate for the given stressor, it comes with important evolutionary disadvantages. Some infectious microbes take advantage of existing mechanisms of tolerance to avoid detection and/or elimination by the host immune system. Induction of regulatory T cells, for instance, has been noted in infections with Helicobacter pylori, Listeria monocytogenes, Brugia malayi, and other worms and parasites. Another important disadvantage of the existence of tolerance may be susceptibility to cancer progression. Treg cells inhibit anti-tumor NK cells. The injection of Treg cells specific for a tumor antigen also can reverse experimentally-mediated tumor rejection based on that same antigen. The prior existence of immune tolerance mechanisms due to selection for its fitness benefits facilitates its utilization in tumor growth.

Tradeoffs between immune tolerance and resistance

Immune tolerance contrasts with resistance. Upon exposure to a foreign antigen, either the antigen is eliminated by the standard immune response (resistance), or the immune system adapts to the pathogen, promoting immune tolerance instead.

Resistance typically protects the host at the expense of the parasite, while tolerance reduces harm to the host without having any direct negative effects on the parasite. Each strategy has its unique costs and benefits for host fitness:


Costs Benefits
Elimination (resistance)
  • Pain, swelling, and disruption of tissue function by inflammation.
  • Tissue damage by inflammatory mediators (immunopathology)
  • High energy cost
  • Risk of autoimmunity, hypersensitivity, allergy
  • Reduces pathogen burden
  • Neutralizes toxins and eliminates dangerous organisms
  • Prevents parasitism
Tolerance
  • Direct damage by pathogen (toxins, digestion, etc.)
  • Energy and resources lost to pathogen
  • Reduced tissue damage from immune response
  • Less selection pressure on pathogens for resistance
  • Promotes commensalism
  • Lower energy cost

Evolution works to optimize host fitness, so whether elimination or tolerance occurs depends on which would benefit the organism most in a given scenario. If the antigen is from a rare, dangerous invader, the costs of tolerating its presence are high and it is more beneficial to the host to eliminate it. Conversely, if experience (of the organism or its ancestors) has shown that the antigen is innocuous, then it would be more beneficial to tolerate the presence of the antigen rather than pay the costs of inflammation.

Despite having mechanisms for both immune resistance and tolerance, any one organism may be overall more skewed toward a tolerant or resistant phenotype depending on individual variation in both traits due to genetic and environmental factors. In mice infected with malaria, different genetic strains of mice fall neatly along a spectrum of being more tolerant but less resistant or more resistant but less tolerant. Patients with autoimmune diseases also often have a unique gene signature and certain environmental risk factors that predispose them to disease. This may have implications for current efforts to identify why certain individuals may be disposed to or protected against autoimmunity, allergy, inflammatory bowel disease, and other such diseases.

Tumor antigen

From Wikipedia, the free encyclopedia
 
 
The spectrum of target antigens associated with tumor immunity and allo-immunity after allogeneic hematopoietic stem cell transplantation. Host-derived T and B cells can be induced to recognize tumor-associated antigens, whereas donor-derived B and T cells can recognize both tumor-associated antigens and alloantigens.

Tumor antigen is an antigenic substance produced in tumor cells, i.e., it triggers an immune response in the host. Tumor antigens are useful tumor markers in identifying tumor cells with diagnostic tests and are potential candidates for use in cancer therapy. The field of cancer immunology studies such topics.

Mechanism of tumor antigenesis

Processing of tumor antigens recognized by CD8+ T cells

Normal proteins in the body are not antigenic because of self-tolerance, a process in which self-reacting cytotoxic T lymphocytes (CTLs) and autoantibody-producing B lymphocytes are culled "centrally" in primary lymphatic tissue (BM) and "peripherally" in secondary lymphatic tissue (mostly thymus for T-cells and spleen/lymph nodes for B cells). Thus any protein that is not exposed to the immune system triggers an immune response. This may include normal proteins that are well sequestered from the immune system, proteins that are normally produced in extremely small quantities, proteins that are normally produced only in certain stages of development, or proteins whose structure is modified due to mutation.

Classification of tumor antigens

Classes of human tumor antigens recognized by T lymphocytes, with their genetic process

Initially tumor antigens were broadly classified into two categories based on their pattern of expression: Tumor-Specific Antigens (TSA), which are present only on tumor cells and not on any other cell and Tumor-Associated Antigens (TAA), which are present on some tumor cells and also some normal cells.

This classification, however, is imperfect because many antigens thought to be tumor-specific turned out to be expressed on some normal cells as well. The modern classification of tumor antigens is based on their molecular structure and source.

Accordingly, they can be classified as;

  • Products of Mutated Oncogenes and Tumor Suppressor Genes
  • Products of Other Mutated Genes
    • Overexpressed or Aberrantly Expressed Cellular Proteins
    • Tumor Antigens Produced by Oncogenic Viruses
    • Oncofetal Antigens
    • Altered Cell Surface Glycolipids and Glycoproteins
    • Cell Type-Specific Differentiation Antigens

Types

Any protein produced in a tumor cell that has an abnormal structure due to mutation can act as a tumor antigen. Such abnormal proteins are produced due to mutation of the concerned gene. Mutation of protooncogenes and tumor suppressors which lead to abnormal protein production are the cause of the tumor and thus such abnormal proteins are called tumor-specific antigens. Examples of tumor-specific antigens include the abnormal products of ras and p53 genes. In contrast, mutation of other genes unrelated to the tumor formation may lead to synthesis of abnormal proteins which are called tumor-associated antigens.

Other examples include tissue differentiation antigens, mutant protein antigens, oncogenic viral antigens, cancer-testis antigens and vascular or stromal specific antigens. Tissue differentiation antigens are those that are specific to a certain type of tissue. Mutant protein antigens are likely to be much more specific to cancer cells because normal cells shouldn't contain these proteins. Normal cells will display the normal protein antigen on their MHC molecules, whereas cancer cells will display the mutant version. Some viral proteins are implicated in forming cancer (oncogenesis), and some viral antigens are also cancer antigens. Cancer-testis antigens are antigens expressed primarily in the germ cells of the testes, but also in fetal ovaries and the trophoblast. Some cancer cells aberrantly express these proteins and therefore present these antigens, allowing attack by T-cells specific to these antigens. Example antigens of this type are CTAG1B and MAGEA1.

Proteins that are normally produced in very low quantities but whose production is dramatically increased in tumor cells, trigger an immune response. An example of such a protein is the enzyme tyrosinase, which is required for melanin production. Normally tyrosinase is produced in minute quantities but its levels are very much elevated in melanoma cells.

Oncofetal antigens are another important class of tumor antigens. Examples are alphafetoprotein (AFP) and carcinoembryonic antigen (CEA). These proteins are normally produced in the early stages of embryonic development and disappear by the time the immune system is fully developed. Thus self-tolerance does not develop against these antigens.

Abnormal proteins are also produced by cells infected with oncoviruses, e.g. EBV and HPV. Cells infected by these viruses contain latent viral DNA which is transcribed and the resulting protein produces an immune response.

In addition to proteins, other substances like cell surface glycolipids and glycoproteins may also have an abnormal structure in tumor cells and could thus be targets of the immune system.

Importance of tumor antigens

Tumor antigens, because of their relative abundance in tumor cells are useful in identifying specific tumor cells. Certain tumors have certain tumor antigens in abundance.

Tumor antigen Tumor in which it is found Remarks
Alphafetoprotein (AFP) Germ cell tumors

Hepatocellular carcinoma


Carcinoembryonic antigen (CEA) Bowel cancers Occasional lung or breast cancer
CA-125 Ovarian cancer
MUC-1 Breast cancer
Epithelial tumor antigen (ETA) Breast cancer
Tyrosinase Malignant melanoma normally present in minute quantities; greatly elevated levels in melanoma
Melanoma-associated antigen (MAGE) Malignant melanoma Also normally present in the testis
abnormal products of ras, p53 Various tumors

Certain tumor antigens are thus used as tumor markers. More importantly, tumor antigens can be used in cancer therapy as tumor antigen vaccines.

Cancer biomarker

From Wikipedia, the free encyclopedia
text
Questions that can be answered by biomarkers

A cancer biomarker refers to a substance or process that is indicative of the presence of cancer in the body. A biomarker may be a molecule secreted by a tumor or a specific response of the body to the presence of cancer. Genetic, epigenetic, proteomic, glycomic, and imaging biomarkers can be used for cancer diagnosis, prognosis, and epidemiology. Ideally, such biomarkers can be assayed in non-invasively collected biofluids like blood or serum.

Cancer is a disease that affects society at a world-wide level. By testing for biomarkers, early diagnosis can be given to prevent deaths.

While numerous challenges exist in translating biomarker research into the clinical space; a number of gene and protein based biomarkers have already been used at some point in patient care; including, AFP (liver cancer), BCR-ABL (chronic myeloid leukemia), BRCA1 / BRCA2 (breast/ovarian cancer), BRAF V600E (melanoma/colorectal cancer), CA-125 (ovarian cancer), CA19.9 (pancreatic cancer), CEA (colorectal cancer), EGFR (Non-small-cell lung carcinoma), HER-2 (Breast Cancer), KIT (gastrointestinal stromal tumor), PSA (prostate specific antigen) (prostate cancer), S100 (melanoma), and many others. Mutant proteins themselves detected by selected reaction monitoring (SRM) have been reported to be the most specific biomarkers for cancers because they can only come from an existing tumor. About 40% of cancers can be cured if detected early through examinations.

Definitions of cancer biomarkers

Organizations and publications vary in their definition of biomarker. In many areas of medicine, biomarkers are limited to proteins identifiable or measurable in the blood or urine. However, the term is often used to cover any molecular, biochemical, physiological, or anatomical property that can be quantified or measured.

The National Cancer Institute (NCI), in particular, defines biomarker as a: “A biological molecule found in blood, other body fluids, or tissues that is a sign of a normal or abnormal process, or of a condition or disease. A biomarker may be used to see how well the body responds to a treatment for a disease or condition. Also called molecular marker and signature molecule."

In cancer research and medicine, biomarkers are used in three primary ways:

  1. To help diagnose conditions, as in the case of identifying early stage cancers (diagnostic)
  2. To forecast how aggressive a condition is, as in the case of determining a patient's ability to fare in the absence of treatment (prognostic)
  3. To predict how well a patient will respond to treatment (predictive)

Role of biomarkers in cancer research and medicine

Uses of biomarkers in cancer medicine

Risk assessment

Cancer biomarkers, particular those associated with genetic mutations or epigenetic alterations, often offer a quantitative way to determine when individuals are predisposed to particular types of cancers. Notable examples of potentially predictive cancer biomarkers include mutations on genes KRAS, p53, EGFR, erbB2 for colorectal, esophageal, liver, and pancreatic cancer; mutations of genes BRCA1 and BRCA2 for breast and ovarian cancer; abnormal methylation of tumor suppressor genes p16, CDKN2B, and p14ARF for brain cancer; hypermethylation of MYOD1, CDH1, and CDH13 for cervical cancer; and hypermethylation of p16, p14, and RB1, for oral cancer.

Diagnosis

Cancer biomarkers can also be useful in establishing a specific diagnosis. This is particularly the case when there is a need to determine whether tumors are of primary or metastatic origin. To make this distinction, researchers can screen the chromosomal alterations found on cells located in the primary tumor site against those found in the secondary site. If the alterations match, the secondary tumor can be identified as metastatic; whereas if the alterations differ, the secondary tumor can be identified as a distinct primary tumor. For example, people with tumors have high levels of circulating tumor DNA (ctDNA) due to tumor cells that have gone through apoptosis. This tumor marker can be detected in the blood, saliva, or urine. The possibility of identifying an effective biomarker for early cancer diagnosis has recently been questioned, in light of the high molecular heterogeneity of tumors observed by next-generation sequencing studies.

Prognosis and treatment predictions

Another use of biomarkers in cancer medicine is for disease prognosis, which take place after an individual has been diagnosed with cancer. Here biomarkers can be useful in determining the aggressiveness of an identified cancer as well as its likelihood of responding to a given treatment. In part, this is because tumors exhibiting particular biomarkers may be responsive to treatments tied to that biomarker's expression or presence. Examples of such prognostic biomarkers include elevated levels of metallopeptidase inhibitor 1 (TIMP1), a marker associated with more aggressive forms of multiple myeloma, elevated estrogen receptor (ER) and/or progesterone receptor (PR) expression, markers associated with better overall survival in patients with breast cancer; HER2/neu gene amplification, a marker indicating a breast cancer will likely respond to trastuzumab treatment; a mutation in exon 11 of the proto-oncogene c-KIT, a marker indicating a gastrointestinal stromal tumor (GIST) will likely respond to imatinib treatment; and mutations in the tyrosine kinase domain of EGFR1, a marker indicating a patient's non-small-cell lung carcinoma (NSCLC) will likely respond to gefitinib or erlotinib treatment.

Pharmacodynamics and pharmacokinetics

Cancer biomarkers can also be used to determine the most effective treatment regime for a particular person's cancer. Because of differences in each person's genetic makeup, some people metabolize or change the chemical structure of drugs differently. In some cases, decreased metabolism of certain drugs can create dangerous conditions in which high levels of the drug accumulate in the body. As such, drug dosing decisions in particular cancer treatments can benefit from screening for such biomarkers. An example is the gene encoding the enzyme thiopurine methyl-transferase (TPMPT). Individuals with mutations in the TPMT gene are unable to metabolize large amounts of the leukemia drug, mercaptopurine, which potentially causes a fatal drop in white blood count for such patients. Patients with TPMT mutations are thus recommended to be given a lower dose of mercaptopurine for safety considerations.

Monitoring treatment response

Cancer biomarkers have also shown utility in monitoring how well a treatment is working over time. Much research is going into this particular area, since successful biomarkers have the potential of providing significant cost reduction in patient care, as the current image-based tests such as CT and MRI for monitoring tumor status are highly costly.

One notable biomarker garnering significant attention is the protein biomarker S100-beta in monitoring the response of malignant melanoma. In such melanomas, melanocytes, the cells that make pigment in our skin, produce the protein S100-beta in high concentrations dependent on the number of cancer cells. Response to treatment is thus associated with reduced levels of S100-beta in the blood of such individuals.

Similarly, additional laboratory research has shown that tumor cells undergoing apoptosis can release cellular components such as cytochrome c, nucleosomes, cleaved cytokeratin-18, and E-cadherin. Studies have found that these macromolecules and others can be found in circulation during cancer therapy, providing a potential source of clinical metrics for monitoring treatment.

Recurrence

Cancer biomarkers can also offer value in predicting or monitoring cancer recurrence. The Oncotype DX® breast cancer assay is one such test used to predict the likelihood of breast cancer recurrence. This test is intended for women with early-stage (Stage I or II), node-negative, estrogen receptor-positive (ER+) invasive breast cancer who will be treated with hormone therapy. Oncotype DX looks at a panel of 21 genes in cells taken during tumor biopsy. The results of the test are given in the form of a recurrence score that indicates likelihood of recurrence at 10 years.

Uses of biomarkers in cancer research

Developing drug targets

In addition to their use in cancer medicine, biomarkers are often used throughout the cancer drug discovery process. For instance, in the 1960s, researchers discovered the majority of patients with chronic myelogenous leukemia possessed a particular genetic abnormality on chromosomes 9 and 22 dubbed the Philadelphia chromosome. When these two chromosomes combine they create a cancer-causing gene known as BCR-ABL. In such patients, this gene acts as the principle initial point in all of the physiological manifestations of the leukemia. For many years, the BCR-ABL was simply used as a biomarker to stratify a certain subtype of leukemia. However, drug developers were eventually able to develop imatinib, a powerful drug that effectively inhibited this protein and significantly decreased production of cells containing the Philadelphia chromosome.

Surrogate endpoints

Another promising area of biomarker application is in the area of surrogate endpoints. In this application, biomarkers act as stand-ins for the effects of a drug on cancer progression and survival. Ideally, the use of validated biomarkers would prevent patients from having to undergo tumor biopsies and lengthy clinical trials to determine if a new drug worked. In the current standard of care, the metric for determining a drug's effectiveness is to check if it has decreased cancer progression in humans and ultimately whether it prolongs survival. However, successful biomarker surrogates could save substantial time, effort, and money if failing drugs could be eliminated from the development pipeline before being brought to clinical trials.

Some ideal characteristics of surrogate endpoint biomarkers include:

  • Biomarker should be involved in process that causes the cancer
  • Changes in biomarker should correlate with changes in the disease
  • Levels of biomarkers should be high enough that they can be measured easily and reliably
  • Levels or presence of biomarker should readily distinguish between normal, cancerous, and precancerous tissue
  • Effective treatment of the cancer should change the level of the biomarker
  • Level of the biomarker should not change spontaneously or in response to other factors not related to the successful treatment of the cancer

Two areas in particular that are receiving attention as surrogate markers include circulating tumor cells (CTCs) and circulating miRNAs. Both these markers are associated with the number of tumor cells present in the blood, and as such, are hoped to provide a surrogate for tumor progression and metastasis. However, significant barriers to their adoption include the difficulty of enriching, identifying, and measuring CTC and miRNA levels in blood. New technologies and research are likely necessary for their translation into clinical care.

Types of cancer biomarkers

Molecular cancer biomarkers

Tumor type Biomarker
Breast ER/PR (estrogen receptor/progesteron receptor)
HER-2/neu
Colorectal EGFR
KRAS
UGT1A1
Gastric HER-2/neu 
GIST c-KIT
Leukemia/lymphoma CD20
CD30
FIP1L1-PDGFRalpha
PDGFR
Philadelphia chromosome (BCR/ABL
PML/RAR-alpha
TPMT
UGT1A1
Lung EML4/ALK
EGFR
KRAS 
Melanoma BRAF
Pancreas Elevated levels of leucine, isoleucine and valine
Ovaries CA-125

Other examples of biomarkers:

Cancer biomarkers without specificity

Not all cancer biomarkers have to be specific to types of cancer. Some biomarkers found in the circulatory system can be used to determine an abnormal growth of cells present in the body. All these types of biomarkers can be identified through diagnostic blood tests, which is one of the main reasons to get regularly health tested. By getting regularly tested, many health issues such as cancer can be discovered at an early stage, preventing many deaths.

The neutrophil-to-lymphocyte ratio has been shown to be a non-specific determinant for many cancers. This ratio focuses on the activity of two components of the immune system that are involved in inflammatory response which is shown to be higher in presence of malignant tumors. Additionally, basic fibroblast growth factor (bFGF) is a protein that is involved in the proliferation of cells. Unfortunately, it has been shown that in the presence of tumors it is highly active which has led to the conclusion that it may help malignant cells reproduce at faster rates. Research has shown that anti-bFGF antibodies can be used to help treat tumors from many origins. Moreover, insulin-like growth factor (IGF-R) is involved in cell proliferation and growth. It has is possible that it is involved in inhibiting apoptosis, programmed cell death due to some defect. Due to this, the levels of IGF-R can be increased when cancer such as breast, prostate, lung, and colorectum is present.

Biomarker Description Biosensor used
NLR (neutrophil-to-lymphocyte ratio) Elevates with inflammation caused by cancer No
Basic Fibroblast Growth Factor (bFGF) This level increases when a tumor is present, helps with the fast reproduction of tumor cells Electrochemical
Insulin-like Growth Factor (IGF-R) High activity in cancer cells, help reproduction Electrochemical Impedance Spectroscopy Sensor

Friday, June 16, 2023

Oncogenomics

From Wikipedia, the free encyclopedia
https://en.wikipedia.org/wiki/Oncogenomics

Oncogenomics is a sub-field of genomics that characterizes cancer-associated genes. It focuses on genomic, epigenomic and transcript alterations in cancer.

Cancer is a genetic disease caused by accumulation of DNA mutations and epigenetic alterations leading to unrestrained cell proliferation and neoplasm formation. The goal of oncogenomics is to identify new oncogenes or tumor suppressor genes that may provide new insights into cancer diagnosis, predicting clinical outcome of cancers and new targets for cancer therapies. The success of targeted cancer therapies such as Gleevec, Herceptin and Avastin raised the hope for oncogenomics to elucidate new targets for cancer treatment.

Overall goals of oncogenomics

Besides understanding the underlying genetic mechanisms that initiate or drive cancer progression, oncogenomics targets personalized cancer treatment. Cancer develops due to DNA mutations and epigenetic alterations that accumulate randomly. Identifying and targeting the mutations in an individual patient may lead to increased treatment efficacy.

The completion of the Human Genome Project facilitated the field of oncogenomics and increased the abilities of researchers to find oncogenes. Sequencing technologies and global methylation profiling techniques have been applied to the study of oncogenomics.

History

The genomics era began in the 1990s, with the generation of DNA sequences of many organisms. In the 21st century, the completion of the Human Genome Project enabled the study of functional genomics and examining tumor genomes. Cancer is a main focus.

The epigenomics era largely began more recently, about 2000. One major source of epigenetic change is altered methylation of CpG islands at the promoter region of genes (see DNA methylation in cancer). A number of recently devised methods can assess the DNA methylation status in cancers versus normal tissues. Some methods assess methylation of CpGs located in different classes of loci, including CpG islands, shores, and shelves as well as promoters, gene bodies, and intergenic regions. Cancer is also a major focus of epigenetic studies.

Access to whole cancer genome sequencing is important to cancer (or cancer genome) research because:

  • Mutations are the immediate cause of cancer and define the tumor phenotype.
  • Access to cancerous and normal tissue samples from the same patient and the fact that most cancer mutations represent somatic events, allow the identification of cancer-specific mutations.
  • Cancer mutations are cumulative and sometimes are related to disease stage. Metastasis and drug resistance are distinguishable.

Access to methylation profiling is important to cancer research because:

  • Epi-drivers, along with Mut-drivers, can act as immediate causes of cancers
  • Cancer epimutations are cumulative and sometimes related to disease stage

Whole genome sequencing

The first cancer genome was sequenced in 2008. This study sequenced a typical acute myeloid leukaemia (AML) genome and its normal counterpart genome obtained from the same patient. The comparison revealed ten mutated genes. Two were already thought to contribute to tumor progression: an internal tandem duplication of the FLT3 receptor tyrosine kinase gene, which activates kinase signaling and is associated with a poor prognosis and a four base insertion in exon 12 of the NPM1 gene (NPMc). These mutations are found in 25-30% of AML tumors and are thought to contribute to disease progression rather than to cause it directly.

The remaining 8 were new mutations and all were single base changes: Four were in families that are strongly associated with cancer pathogenesis (PTPRT, CDH24, PCLKC and SLC15A1). The other four had no previous association with cancer pathogenesis. They did have potential functions in metabolic pathways that suggested mechanisms by which they could act to promote cancer (KNDC1, GPR124, EB12, GRINC1B)

These genes are involved in pathways known to contribute to cancer pathogenesis, but before this study most would not have been candidates for targeted gene therapy. This analysis validated the approach of whole cancer genome sequencing in identifying somatic mutations and the importance of parallel sequencing of normal and tumor cell genomes.

In 2011, the genome of an exceptional bladder cancer patient whose tumor had been eliminated by the drug everolimus was sequenced, revealing mutations in two genes, TSC1 and NF2. The mutations disregulated mTOR, the protein inhibited by everolimus, allowing it to reproduce without limit. As a result, in 2015, the Exceptional Responders Initiative was created at the National Cancer Institute. The initiative allows such exceptional patients (who have responded positively for at least six months to a cancer drug that usually fails) to have their genomes sequenced to identify the relevant mutations. Once identified, other patients could be screened for those mutations and then be given the drug. In 2016 To that end, a nationwide cancer drug trial began in 2015, involving up to twenty-four hundred centers. Patients with appropriate mutations are matched with one of more than forty drugs.

In 2014 the Center for Molecular Oncology rolled out the MSK-IMPACT test, a screening tool that looks for mutations in 341 cancer-associated genes. By 2015 more than five thousand patients had been screened. Patients with appropriate mutations are eligible to enroll in clinical trials that provide targeted therapy.

Technologies

Current technologies being used in Oncogenomics.

Genomics technologies include:

Genome sequencing

  • DNA sequencing: Pyrosequencing-based sequencers offer a relatively low-cost method to generate sequence data.
  • Array Comparative Genome Hybridization: This technique measures the DNA copy number differences between normal and cancer genomes. It uses the fluorescence intensity from fluorescent-labeled samples, which are hybridized to known probes on a microarray.
  • Representational oligonucleotide microarray analysis: Detects copy number variation using amplified restriction-digested genomic fragments that are hybridized to human oligonucleotides, achieving a resolution between 30 and 35 kbit/s.
  • Digital Karyotyping: Detects copy number variation using genomics tags obtained via restriction enzyme digests. These tags are then linked to into ditags, concatenated, cloned, sequenced and mapped back to the reference genome to evaluate tag density.
  • Bacterial Artificial Chromosome (BAC)-end sequencing (end-sequence profiling): Identifies chromosomal breakpoints by generating a BAC library from a cancer genome and sequencing their ends. The BAC clones that contain chromosome aberrations have end sequences that do not map to a similar region of the reference genome, thus identifying a chromosomal breakpoint.

Transcriptomes

  • Microarrays: Assess transcript abundance. Useful in classification, prognosis, raise the possibility of differential treatment approaches and aid identification of mutations in the proteins' coding regions. The relative abundance of alternative transcripts has become an important feature of cancer research. Particular alternative transcript forms correlate with specific cancer types.
  • RNA-Seq

Bioinformatics and functional analysis of oncogenes

Bioinformatics technologies allow the statistical analysis of genomic data. The functional characteristics of oncogenes has yet to be established. Potential functions include their transformational capabilities relating to tumour formation and specific roles at each stage of cancer development.

After the detection of somatic cancer mutations across a cohort of cancer samples, bioinformatic computational analyses can be carried out to identify likely functional and likely driver mutations. There are three main approaches routinely used for this identification: mapping mutations, assessing the effect of mutation of the function of a protein or a regulatory element and finding signs of positive selection across a cohort of tumors. The approaches are not necessarily sequential however, there are important relationships of precedence between elements from the different approaches. Different tools are used at each step.

Operomics

Operomics aims to integrate genomics, transcriptomics and proteomics to understand the molecular mechanisms that underlie the cancer development.

Comparative oncogenomics

Comparative oncogenomics uses cross-species comparisons to identify oncogenes. This research involves studying cancer genomes, transcriptomes and proteomes in model organisms such as mice, identifying potential oncogenes and referring back to human cancer samples to see whether homologues of these oncogenes are important in causing human cancers. Genetic alterations in mouse models are similar to those found in human cancers. These models are generated by methods including retroviral insertion mutagenesis or graft transplantation of cancerous cells.

Source of cancer driver mutations, cancer mutagenesis

Mutations provide the raw material for natural selection in evolution and can be caused by errors of DNA replication, the action of exogenous mutagens or endogenous DNA damage. The machinery of replication and genome maintenance can be damaged by mutations, or altered by physiological conditions and differential levels of expression in cancer.

As pointed out by Gao et al., the stability and integrity of the human genome are maintained by the DNA-damage response (DDR) system. Un-repaired DNA damage is a major cause of mutations that drive carcinogenesis. If DNA repair is deficient, DNA damage tends to accumulate. Such excess DNA damage can increase mutational errors during DNA replication due to error-prone translesion synthesis. Excess DNA damage can also increase epigenetic alterations due to errors during DNA repair. Such mutations and epigenetic alterations can give rise to cancer. DDR genes are often repressed in human cancer by epigenetic mechanisms. Such repression may involve DNA methylation of promoter regions or repression of DDR genes by a microRNA. Epigenetic repression of DDR genes occurs more frequently than gene mutation in many types of cancer (see Cancer epigenetics). Thus, epigenetic repression often plays a more important role than mutation in reducing expression of DDR genes. This reduced expression of DDR genes is likely an important driver of carcinogenesis.

Nucleotide sequence context influences mutation probability and analysis of mutational (mutable) DNA motifs can be essential for understanding the mechanisms of mutagenesis in cancer. Such motifs represent the fingerprints of interactions between DNA and mutagens, between DNA and repair/replication/modification enzymes. Examples of motifs are the AID motif WRCY/RGYW (W = A or T, R = purine and Y = pyrimidine) with C to T/G/A mutations, and error-prone DNA pol η attributed AID-related mutations (A to G/C/G) in WA/TW motifs.

Another (agnostic) way to analyze the observed mutational spectra and DNA sequence context of mutations in tumors involves pooling all mutations of different types and contexts from cancer samples into a discrete distribution. If multiple cancer samples are available, their context-dependent mutations can be represented in the form of a nonnegative matrix. This matrix can be further decomposed into components (mutational signatures) which ideally should describe individual mutagenic factors. Several computational methods have been proposed for solving this decomposition problem. The first implementation of Non-negative Matrix Factorization (NMF) method is available in Sanger Institute Mutational Signature Framework in the form of a MATLAB package. On the other hand, if mutations from a single tumor sample are only available, the DeconstructSigs R package and MutaGene server may provide the identification of contributions of different mutational signatures for a single tumor sample. In addition, MutaGene server provides mutagen or cancer-specific mutational background models and signatures that can be applied to calculate expected DNA and protein site mutability to decouple relative contributions of mutagenesis and selection in carcinogenesis.

Synthetic lethality

Synthetic lethality arises when a combination of deficiencies in the expression of two or more genes leads to cell death, whereas a deficiency in only one of these genes does not. The deficiencies can arise through mutations, epigenetic alterations or inhibitors of one of the genes.

The therapeutic potential of synthetic lethality as an efficacious anti-cancer strategy is continually improving. Recently, the applicability of synthetic lethality to targeted cancer therapy has heightened due to the recent work of scientists including Ronald A. DePinho and colleagues, in what is termed 'collateral lethality'. Muller et al. found that passenger genes, with chromosomal proximity to tumor suppressor genes, are collaterally deleted in some cancers. Thus, the identification of collaterally deleted redundant genes carrying out an essential cellular function may be the untapped reservoir for then pursuing a synthetic lethality approach. Collateral lethality therefore holds great potential in identification of novel and selective therapeutic targets in oncology. In 2012, Muller et al. identified that homozygous deletion of redundant-essential glycolytic ENO1 gene in human glioblastoma (GBM) is the consequence of proximity to 1p36 tumor suppressor locus deletions and may hold potential for a synthetic lethality approach to GBM inhibition. ENO1 is one of three homologous genes (ENO2, ENO3) that encodes the mammalian alpha-enolase enzyme. ENO2, which encodes enolase 2, is mostly expressed in neural tissues, leading to the postulation that in ENO1-deleted GBM, ENO2 may be the ideal target as the redundant homologue of ENO1. Muller found that both genetic and pharmacological ENO2 inhibition in GBM cells with homozygous ENO1 deletion elicits a synthetic lethality outcome by selective killing of GBM cells. In 2016, Muller and colleagues discovered antibiotic SF2312 as a highly potent nanomolar-range enolase inhibitor which preferentially inhibits glioma cell proliferation and glycolytic flux in ENO1-deleted cells. SF2312 was shown to be more efficacious than pan-enolase inhibitor PhAH and have more specificity for ENO2 inhibition over ENO1. Subsequent work by the same team showed that the same approach could be applied to pancreatic cancer, whereby homozygously deleted SMAD4 results in the collateral deletion of mitochondrial malic enzyme 2 (ME2), an oxidative decarboxylase essential for redox homeostasis. Dey et al. show that ME2 genomic deletion in pancreatic ductal adenocarcinoma cells results in high endogenous reactive oxygen species, consistent with KRAS-driven pancreatic cancer, and essentially primes ME2-null cells for synthetic lethality by depletion of redundant NAD(P)+-dependent isoform ME3. The effects of ME3 depletion were found to be mediated by inhibition of de novo nucleotide synthesis resulting from AMPK activation and mitochondrial ROS-mediated apoptosis. Meanwhile, Oike et al. demonstrated the generalizability of the concept by targeting redundant essential-genes in process other than metabolism, namely the SMARCA4 and SMARCA2 subunits in the chromatin-remodeling SWI/SNF complex.

Some oncogenes are essential for survival of all cells (not only cancer cells). Thus, drugs that knock out these oncogenes (and thereby kill cancer cells) may also damage normal cells, inducing significant illness. However, other genes may be essential to cancer cells but not to healthy cells.

Treatments based on the principle of synthetic lethality have prolonged the survival of cancer patients, and show promise for future advances in reversal of carcinogenesis. A major type of synthetic lethality operates on the DNA repair defect that often initiates a cancer, and is still present in the tumor cells. Some examples are given here.

BRCA1 or BRCA2 expression is deficient in a majority of high-grade breast and ovarian cancers, usually due to epigenetic methylation of its promoter or epigenetic repression by an over-expressed microRNA (see articles BRCA1 and BRCA2). BRCA1 and BRCA2 are important components of the major pathway for homologous recombinational repair of double-strand breaks. If one or the other is deficient, it increases the risk of cancer, especially breast or ovarian cancer. A back-up DNA repair pathway, for some of the damages usually repaired by BRCA1 and BRCA2, depends on PARP1. Thus, many ovarian cancers respond to an FDA-approved treatment with a PARP inhibitor, causing synthetic lethality to cancer cells deficient in BRCA1 or BRCA2. This treatment is also being evaluated for breast cancer and numerous other cancers in Phase III clinical trials in 2016.

There are two pathways for homologous recombinational repair of double-strand breaks. The major pathway depends on BRCA1, PALB2 and BRCA2 while an alternative pathway depends on RAD52. Pre-clinical studies, involving epigenetically reduced or mutated BRCA-deficient cells (in culture or injected into mice), show that inhibition of RAD52 is synthetically lethal with BRCA-deficiency.

Mutations in genes employed in DNA mismatch repair (MMR) cause a high mutation rate. In tumors, such frequent subsequent mutations often generate “non-self” immunogenic antigens. A human Phase II clinical trial, with 41 patients, evaluated one synthetic lethal approach for tumors with or without MMR defects. The product of gene PD-1 ordinarily represses cytotoxic immune responses. Inhibition of this gene allows a greater immune response. When cancer patients with a defect in MMR in their tumors were exposed to an inhibitor of PD-1, 67% - 78% of patients experienced immune-related progression-free survival. In contrast, for patients without defective MMR, addition of PD-1 inhibitor generated only 11% of patients with immune-related progression-free survival. Thus inhibition of PD-1 is primarily synthetically lethal with MMR defects.

ARID1A, a chromatin modifier, is required for non-homologous end joining, a major pathway that repairs double-strand breaks in DNA, and also has transcription regulatory roles. ARID1A mutations are one of the 12 most common carcinogenic mutations. Mutation or epigenetically decreased expression of ARID1A has been found in 17 types of cancer. Pre-clinical studies in cells and in mice show that synthetic lethality for ARID1A deficiency occurs by either inhibition of the methyltransferase activity of EZH2, or with addition of the kinase inhibitor dasatinib.

Another approach is to individually knock out each gene in a genome and observe the effect on normal and cancerous cells. If the knockout of an otherwise nonessential gene has little or no effect on healthy cells, but is lethal to cancerous cells containing a mutated oncogene, then the system-wide suppression of the suppressed gene can destroy cancerous cells while leaving healthy ones relatively undamaged. The technique was used to identify PARP-1 inhibitors to treat BRCA1/BRCA2-associated cancers. In this case, the combined presence of PARP-1 inhibition and of the cancer-associated mutations in BRCA genes is lethal only to the cancerous cells.

Databases for cancer research

The Cancer Genome Project is an initiative to map out all somatic mutations in cancer. The project systematically sequences the exons and flanking splice junctions of the genomes of primary tumors and cancerous cell lines. COSMIC software displays the data generated from these experiments. As of February 2008, the CGP had identified 4,746 genes and 2,985 mutations in 1,848 tumours.

The Cancer Genome Anatomy Project includes information of research on cancer genomes, transcriptomes and proteomes.

Progenetix is an oncogenomic reference database, presenting cytogenetic and molecular-cytogenetic tumor data.

Oncomine has compiled data from cancer transcriptome profiles.

The integrative oncogenomics database IntOGen and the Gitools datasets integrate multidimensional human oncogenomic data classified by tumor type. The first version of IntOGen focused on the role of deregulated gene expression and CNV in cancer. A later version emphasized mutational cancer driver genes across 28 tumor types. All releases of IntOGen data are made available at the IntOGen database.

The International Cancer Genome Consortium is the biggest project to collect human cancer genome data. The data is accessible through the ICGC website. The BioExpress® Oncology Suite contains gene expression data from primary, metastatic and benign tumor samples and normal samples, including matched adjacent controls. The suite includes hematological malignancy samples for many well-known cancers.

Specific databases for model animals include the Retrovirus Tagged Cancer Gene Database (RTCGD) that compiled research on retroviral and transposon insertional mutagenesis in mouse tumors.

Gene families

Mutational analysis of entire gene families revealed that genes of the same family have similar functions, as predicted by similar coding sequences and protein domains. Two such classes are the kinase family, involved in adding phosphate groups to proteins and the phosphatase family, involved with removing phosphate groups from proteins. These families were first examined because of their apparent role in transducing cellular signals of cell growth or death. In particular, more than 50% of colorectal cancers carry a mutation in a kinase or phosphatase gene. Phosphatidylinositold 3-kinases (PIK3CA) gene encodes for lipid kinases that commonly contain mutations in colorectal, breast, gastric, lung and various other cancers. Drug therapies can inhibit PIK3CA. Another example is the BRAF gene, one of the first to be implicated in melanomas. BRAF encodes a serine/threonine kinase that is involved in the RAS-RAF-MAPK growth signaling pathway. Mutations in BRAF cause constitutive phosphorylation and activity in 59% of melanomas. Before BRAF, the genetic mechanism of melanoma development was unknown and therefore prognosis for patients was poor.

Mitochondrial DNA

Mitochondrial DNA (mtDNA) mutations are linked the formation of tumors. Four types of mtDNA mutations have been identified:

Point mutations

Point mutations have been observed in the coding and non-coding region of the mtDNA contained in cancer cells. In individuals with bladder, head/neck and lung cancers, the point mutations within the coding region show signs of resembling each other. This suggests that when a healthy cell transforms into a tumor cell (a neoplastic transformation) the mitochondria seem to become homogenous. Abundant point mutations located within the non-coding region, D-loop, of the cancerous mitochondria suggest that mutations within this region might be an important characteristic in some cancers.

Deletions

This type of mutation is sporadically detected due to its small size ( < 1kb). The appearance of certain specific mtDNA mutations (264-bp deletion and 66-bp deletion in the complex 1 subunit gene ND1) in multiple types of cancer provide some evidence that small mtDNA deletions might appear at the beginning of tumorigenesis. It also suggests that the amount of mitochondria containing these deletions increases as the tumor progresses. An exception is a relatively large deletion that appears in many cancers (known as the "common deletion"), but more mtDNA large scale deletions have been found in normal cells compared to tumor cells. This may be due to a seemingly adaptive process of tumor cells to eliminate any mitochondria that contain these large scale deletions (the "common deletion" is > 4kb).

Insertions

Two small mtDNA insertions of ~260 and ~520 bp can be present in breast cancer, gastric cancer, hepatocellular carcinoma (HCC) and colon cancer and in normal cells. No correlation between these insertions and cancer are established.

Copy number mutations

The characterization of mtDNA via real-time polymerase chain reaction assays shows the presence of quantitative alteration of mtDNA copy number in many cancers. Increase in copy number is expected to occur because of oxidative stress. On the other hand, decrease is thought to be caused by somatic point mutations in the replication origin site of the H-strand and/or the D310 homopolymeric c-stretch in the D-loop region, mutations in the p53 (tumor suppressor gene) mediated pathway and/or inefficient enzyme activity due to POLG mutations. Any increase/decrease in copy number then remains constant within tumor cells. The fact that the amount of mtDNA is constant in tumor cells suggests that the amount of mtDNA is controlled by a much more complicated system in tumor cells, rather than simply altered as a consequence of abnormal cell proliferation. The role of mtDNA content in human cancers apparently varies for particular tumor types or sites.

Mutations in mitochondrial DNA in various cancers
Cancer Type Location of Point mutations Nucleotide Position of Deletions Increase of mtDNA copy # Decrease of mtDNA copy #
D-Loop mRNAs tRNAs rRNAs
Bladder X X
X 15,642-15,662

Breast X X X X 8470-13,447 and 8482-13459
X
Head and neck X X X X 8470-13,447 and 8482-13459 X
Oral X X

8470-13,447 and 8482-13459

Hepatocellular carcinoma (HCC) X X X X 306-556 and 3894-3960
X
Esophageal X X
X 8470-13,447 and 8482-13459 X
Gastric  X X X
298-348
X
Prostate X

X 8470-13,447 and 8482-13459 X

57.7% (500/867) contained somatic point putations and of the 1172 mutations surveyed 37.8% (443/1127) were located in the D-loop control region, 13.1% (154/1172) were located in the tRNA or rRNA genes and 49.1% (575/1127) were found in the mRNA genes needed for producing complexes required for mitochondrial respiration.

Diagnostic applications

Some anticancer drugs target mtDNA and have shown positive results in killing tumor cells. Research has used mitochondrial mutations as biomarkers for cancer cell therapy. It is easier to target mutation within mitochondrial DNA versus nuclear DNA because the mitochondrial genome is much smaller and easier to screen for specific mutations. MtDNA content alterations found in blood samples might be able to serve as a screening marker for predicting future cancer susceptibility as well as tracking malignant tumor progression. Along with these potential helpful characteristics of mtDNA, it is not under the control of the cell cycle and is important for maintaining ATP generation and mitochondrial homeostasis. These characteristics make targeting mtDNA a practical therapeutic strategy.

Cancer biomarkers

Several biomarkers can be useful in cancer staging, prognosis and treatment. They can range from single-nucleotide polymorphisms (SNPs), chromosomal aberrations, changes in DNA copy number, microsatellite instability, promoter region methylation, or even high or low protein levels.

Space travel in science fiction

From Wikipedia, the free encyclopedia https://en.wikipedia.org/wiki/Space_travel_in_science_fiction Rock...