Cervical Cancer Major Cause Death Gynecologic Cancer Worldwide Biology Essay

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Cervical cancer is the one of the major cause of death from gynecologic cancer worldwide. According to the American Cancer Society (2010), about 12,200 new cases of invasive cervical cancer will be diagnosed and about 4,210 women will die from this disease in the United States. Developing countries account for 85% of the nearly 500,000 yearly cases of cervical cancer worldwide with approximately 250,000 deaths. It is generally accepted that specific high-risk human papilloma virus (HPV) types are causally involved in the pathogenesis of cervical cancer (Walboomers et al., 1999). HPVs are small nonenveloped icosahedral viruses with 8-kb long double-stranded circular DNA genome, which comprises early and late genes that encode early proteins (E1-E7) and late proteins (L1 and L2). The early proteins are nonstructural proteins involved in replication and transcription of the genome (E1-E5) or in host cell transformation (E6 and E7), whereas L1 and L2 are the structural capsid proteins of the virion (Mantovani and Banks, 2001; Munger et al., 2001; zur Hausen, 2002; Wentzensen and von Knebel Doeberitz, 2007). There are over 100 genotypes of HPV and these are grouped into "high-risk" and "low-risk" types, reflecting their risk potential to induce invasive cancer. Genital HPV intection is extremely common and most often causes no symtoms. A proportion of individuals infected with low-risk HPV types (e.g. HPV-6 and -11) can cause benign or low-grade cervical cell changes, genital warts, and recurrent respiratory papillomatosis, whereas a subset of women with high-risk HPV types (e.g. HPV-16 and -18) will develop cervical cancers and other anogenital cancers (Table 1) (Yim and Park, 2006; zur Hausen, 2002). Cervical cancer progresses slowly from preinvasive cervical intraepithelial neoplasia (CIN) or adenocarcinoma in situ (CIS) to squamous cell carcinoma or adenocarcinoma, respectively (Ostör, 1993; zur Hausen, 2002). Currently, two HPV vaccines are on the market; Gardasil (Merck & Co.) and Cervarix (GlaxoSmithKline). Both vaccines protect against HPV-16 and -18 that cause 70% of cervical cancers and other genital cancers. Additionaly, Gardasil also protects against HPV-6 and -11 that cause 90% of genital warts and has been shown to prevent potential precursors to anal, vulvar, vaginal, and penile cancers. However, since these vaccines only cover some high-risk types of HPV, women should seek regular Pap test screening even after vaccination.

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Diagnosis

Diagnosing cervical cancer involves a series of medical tests and exams (Figure 1):

Pap test

Colposcopy and biopsy

Cystoscopy and proctoscopy

Imaging

1.1.Pap test The Pap test is a screening technique to detect early evidence of cervical cancer. It can also find noncancerous conditions, such as infection and inflammation. In taking the Pap test, a tool (e.g. a spatular, cotton swab, or brush) is used to gather cells from the outer opening of the cervix of the uterus and the endocervix, and then cells are examined under a microscope to look for abnormalities. HPV test may be done at the same time as the Pap test.

1.2.Colposcopy and biopsy If the Pap test results are abnormal, colposcopy will be performed to evaluate an area of abnormal tissue on the cervix, vagina, or vulva using a colposcope. Colposcope provides an enlarged view of the areas, allowing the colposcopist to visually distinguish normal from abnormal appearing tissue and take directed biopsies (punch biopsy, endocervical curettage (ECC), loop electro-surgical excision procedure (LEEP), or cone biopsy (also called conization)) for further pathological examination.

1.3.Cystoscopy and proctoscopy If advanced cancer is diagnosed, a cytoscopy or proctoscopy may be done using a lighted tube to view the inside of the bladder, bladder neck, and urethra (cystoscopy) or the anus, rectum, and lower colon (proctoscopy).

1.4.Imaging The imaging procedures show the extent of disease. These may include a chest x-ray, a computed tomography (CT) scan, a magnetic resonance imaging (MRI), an intravenous pyelogram (IVP), or a positron-emission tomography (PET) scan.

Once cervical cancer is diagnosed, the next step is to determine its stage (Table 2). A cervical cancer's stage is assigned based on:

The size of the cancer

How deeply the cancer has invaded into the tissue surrounding the cervix

If there are signs of cancer in the vagina, pelvis, or local lymph nodes

If there are signs of cancer spread to other organs

Protein biomarkers in cervical cancer

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HPV vaccines will eventually reduce the incidence of cervical cancers, therefore increasing the importance of biomarkers to identify women at high risk for developing cervical cancer. A number of proteins have shown promise as biomarkers for risk assessment, early detection, prognosis, and surrogate end point of cervical cancer. In this section, we will discuss the currently utilized protein biomarkers and the novel biomarkers that are now under investigation.

HPV E6

p16INK4A

Squamous cell carcinoma antigen (SCC)

Mini chromosome maintenance (MCM) proteins and Topoisomerase IIα (TOP2A)

Ki-67

2.1.HPV E6 The E6 protein has been identified as a cancer specific marker produced by HPV that is associated with progression of cervical lesions to cervical cancer. While high-risk HPV E6 forms a complex with p53 and E3 ligase E6AP, resulting in ubiquitin-mediated degradation of p53, low-risk HPV E6 is unable to bind or promote the degradation of p53 (Scheffner et al., 1990). As a consequence, p53 levels are extremely low in cervical cancer cells (Matlashewski et al., 1986), and p53-induced growth arrest and apoptosis in response to DNA damage are abolished (Kessis et al., 1993; Foster et al., 1994). Recently, Arbor Vita corp. (AVC) and PATH, a nonprofit global health agency, has developed a rapid screening test, AV Avantage HPV E6 Test, which targets E6 oncoproteins from HPV-16, -18, and -45 responsible for approximately 90% of cervical cancers. In clinical pilot studies, cervical swab specimens from HPV DNA positive women with negative pathology, histology confirmed CIN1, CIN3, or cervical cancers were tested using the AV Avantage HPV E6 Test in a blinded fashion. E6 oncoprotein was detected in nearly all specimens from women with cervical cancer and in approximately 70% of CIN3 specimens, but not in CIN1 or histology normal specimens, suggesting its potential as a diagnostic biomarker of cervical precancer and cancer (Schweizer et al., 2010).

2.2.p16INK4A HPV oncoprotein E7 is known to bind and inactivate retinoblastoma protein (pRb) (Munger et al., 1989), which eventually leads to upregulation of p16INK4A. p16INK4A is a tumor suppressor protein that inhibits cyclin dependant kinases (CDK)-4 or -6 binding to cyclin D which regulates G1 cell cycle checkpoints (Sano et al., 1998; Krakoxczyk et al., 2008). Overexpression of p16INK4A is linked to the oncogenic transformation caused by persistent high-risk HPV infection. A number of studies have demonstrated that p16INK4A may be a useful marker for squamous and glandular epithelial dysplasia in the uterine cervix (Klaes et al., 2001; Dray et al., 2005) Furthermore, expression of p16INK4A appears to correlate with the degree of cervical neoplasia (Agoff et al., 2003; Negri et al., 2004). It was also recently reported that p16INK4A immunostaining can be used for discriminating integrated from non-integrated HPV infections (Dray et al., 2005; Arias-Pulido et al., 2006). Currently, clinical trials are underway to assess a diagonostic and prognostic value of p16INK4A expression in atypical gladular cells and low grade squamous intraepithelial lesions of the cervix.

2.3.Squamous cell carcinoma antigen (SCC) SCC belongs to the family of serine and cysteine protease inhibitors (Suminami et al., 1991). This antigen is present in normal cervix epithelium with an increased expression in proportion to dysplastic lesion and cervical squamous cell carcinoma. Although SCC is not sufficiently sensitive (particulary in early-stage disease) or specific for cervical cancer for use in screening, pretreatment serum SCC values works as an independent prognostic factor. Approximately 60% of patients with all cervical cancers are detected with elevated levels of serum SCC at initial diagnosis (Farghaly, 1992). Elevated serum SCC levels have been detected in 24-53% of cervical squamous cell carcinomas (Duk et al., 1996). Several studies have concluded that serum SCC is useful in monitoring the course of squamous cell cervical cancer following primary therapy (Bolli et al. 1994). Persistently elevated and/or increasing serum SCC levels after and/or during treatment suggest tumor persistence or progressive disease (Brioschi et al. 1991). Patients with plateau SCC level revealed higher incidence of treatment failure after radiotherapy, indicating SCC levels provide useful information for the need of further work-up and management (Hong et al. 1998). In view of a strong correlation with the clinical course, SCC is suitable for monitoring the early detection of recurrent or progressive disease after primary treatment (currently in clinical use), and may therefore be useful in the management of patients.

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2.4.Mini chromosome maintenance (MCM) proteins and Topoisomerase IIα (TOP2A) MCM proteins are essential for DNA replication in all eukaryotic cells and for restricting replication to once per cell cycle (Kearsey and Labib, 1998; Gonzalez et al, 2005). The eukaryotic MCM family consists of six essential proteins (MCM2-7), all of which are necessary for replication fork progression. These proteins, which are abundant throughout the cell cycle (Kearsey et al, 1996; Maiorano et al, 1996), are downregulated following cell cycle exit by quiescence, differentiation, or senescence (Musahl et al, 1998; Madine et al, 2000; Stoeber et al, 2001). In normal cervical epithelium, MCM protein staining is limited to the basal proliferating layer and is absent in differentiated and quiescent cells. In cervical glandualr and squamous dysplasia, however, MCM expression is dramatically increased (Williams et al., 1998; Muphy et al., 2005), suggesting its potential as a biomarker of cervical dysplasia. Studies have revealed a strong correlation between the number of nuclei positive for MCM5 at the surface of dysplastic epithelium and the severity of dysplasia (Williams et al., 1998; Freeman et al., 1999). MCM7 has also been identified as a highly informative marker of cervical cancer. Diffuse and full epithelium thickness staining for MCM7 staining was observed in high-grade cervical epithelial lesions and invasive cervical carcinoma (Freeman et al., 1999; Brake‌ et al., 2003). TOP2A is an enzyme that unknots and decatenates DNA for DNA replication, transcription, chromosome segregation, and cell cycle progression. Increased expression of TOP2A was observed in cervical dysplasia and cancer and TOP2A expression is correalted with the progression from CIN2 to CIN3 (Shroyer et al., 2006). The detection of two proliferation associated proteins, MCM2 and TOP2A, has been made commercially available (BD ProEx™ C). Studies performed using BD ProEx™ C on Pap samples have demonstrated increased sensitivity for the detection of biopsy proven high-grade disease compared with cytology alone and improved positive predictive value for the detection of high-grade disease compared with high-risk HPV DNA testing (Shroyer et al., 2006; Kelly et al., 2006). In addition, a recent study demonstrated that the use of BD ProEx™ C in women found to have abnormal cytology results upon routine screening predicted a 73% reduction in colposcopic procedures compared with the number of procedures predicted based on Pap results alone. The published reports on the use of MCM2 and TOP2A in Pap cytology samples have highlighted the use of these biomarkers both to detect dysplastic cells as well as to increase the detection of CIN2 within abnormal cases (Shroyer et al., 2006; Kelly et al., 2006).

2.5.Ki-67 The increased proliferation of cervical epithlial cells induced by HPV oncogene expression is reflected by the activation of proliferation markers. Ki-67, a proliferation marker known as a predictive factor for tumor development, is defined as a nuclear antigen expressed during all active phases of the cell cycle (G1, S, G2, M) except G0; the level of Ki-67 expression is used to determine the cell proliferation status (Ross and Hall, 2005; Yim and Park, 2006). It is well demonstrated that Ki-67 expression is increased in upper layers of cervical epithelia, being of major significance for the differentiation of non-neoplastic lesions that can mimic cancer (al-Saleh et al., 1995; Kruse et al., 2001; Yim and Park, 2006). Moreover, Ki-67 protein could be a biomarker of the proliferative activity and progressive potential of normal, dysplastic, and neoplastic cervical changes, with certain therapeutic implications (Yim and Park, 2006). Several studies have also suggested that Ki-67 can be used as an independent prognostic factor for the progression and biological behavior of cervical dysplasia, especially when HPV infection assessment is missing (Anju and Mati, 2008).

Clinical trial is underway to assess a diagnostic value of p16, Ki-67, MCM2, CAIX (carbonic anhydrase IX: a intrinsic marker of hypoxia in carcinoma of the cervix) and HPV in liquid-based cytology specimens showing atypical glandular cell.

Therapeutics

Treatment of cervical cancer will depend on a number of factors, including the stage of the cancer, the size of the tumor, the patient's desire to have children, and the patient's age and overall health. Treatment choices for cervical cancer may include one or more of the following therapies:

Surgery to remove the cancer

Radiation therapy to treat the cancer itself or other organs affected by the cancer

Chemotherapy to help make the cancer more sensitive to radiation therapy and to treat cancer that has spread (metastasized)

3.1.Surgery

Small precancerous lesions

The following surgical procedures may be used for precancerous lesions or for cancerous tissue that has not spread beyond the cervix.

Cryosurgery (cryotherapy) A treatment that uses an instrument to freeze and destroy precancerous tissue, such as carcinoma in situ (CIS).

Laser surgery A surgical procedure that uses a narrow laser beam as a knife to destroy precancer cells. This is not used on invasive cancer. A benefit of laser treatment is its precision; it destroys only diseased tissue inside in the cervix.

Loop electrosurgical excision procedure (LEEP) A treatment that uses electrical current passed through a thin wire hook. This is primarily used on precancerous lesions under local anesthesia. The advantage of this procedure is that more of the tissue can be removed for evaluation.

Conization A procedure to diagnose or remove all of the cancerous tissue. This procedure can be used in a woman who has a very small cancerous area and who wishes to preserve the ability to have children.

Hysterectomy This operation removes the uterus and the cervix and is performed only on women with cervical cancer less than 3 mm in depth.

Bilateral salpingo-oophorectomy Surgery to remove both ovaries and both fallopian tubes.

Large Cervical Cancer Lesions

The following surgical procedures may be used for larger cervical cancer lesions (usually up to 4-5 cm in width), but only if the cancer is all within the cervical tissue.

Trachealectomy A procedure that removes the cervix and surrounding tissue but not the uterus. It is used for women who have a larger cancerous area but wish to preserve the ability to have children. This procedure may include removal of lymph nodes. Typically patients considered for this procedure have to have tumors less than 2 cm in size.

Radical hysterectomy Surgery to remove the uterus, cervix, part of the vagina, and a wide area of ligaments and tissues around these organs. The ovaries, fallopian tubes, or nearby lymph nodes may also be removed.

3.2.Radiation therapy

Radiation therapy is used for cancers that have spread beyond the cervix (II, III or IV) or very large lesions (larger than 4 cm) using high-energy X-rays or other types of radiation to kill cancer cells or shrink the tumor. This procedure is used instead of surgery in most cases. However, it is sometimes necessary after surgery if it is discovered that the cancer has spread outside the cervix, or to reduce the risk of recurrence after surgery.

External radiation therapy A precedure that uses a machine outside the body to send radiation toward the cervical cancer.

Internal radiation therapy A treatment that uses a small amount of radioactive material that is delivered directly to the tumor suing implants. Implants are inserted through the vagina into the cervix, where they are placed next to the tumor while the patient is under anesthesia.

3.3.Chemotherapy

Chemotherapy is a cancer treatment that uses drugs to stop the growth of cancer cells, either by killing the cells or by stopping them from dividing. The way the chemotherapy is given depends on the type and stage of the cancer being treated.

Systemic chemotherapy A procedure that uses anti-cancer drugs that are injected into a vein or given by mouth (orally). These drugs enter the bloodstream and reach all areas of the body, making this treatment potentially useful for cancers that have spread to distant organs (metastasized).

Regional chemotherapy A treatment which is placed directly into an organ or a body cavity, such as the abdomen. Almost all cervical cancer patients in good medical condition who are receiving radiation for stage IIA or higher, will be offered chemotherapy in addition to radiation therapy.

4. New and emerging proteomics techniques in cancer research

Large-scale genomic studies, such as The Cancer Genome Atlas (TCGA) project funded by the National Human Genome Research Institute (NHGRI) and the National Cancer Institute (NCI) are identifying numerous disease susceptibility genes and gene expression profiles in order to help researchers understand the genetic changes underlying cancer, predict a patient's risk of developing a specific cancer, and guide treatment decisions. Although genomics has made great strides in highlighting the molecular basis of disease, these studies alone cannot capture the complete view of disease processes. A more comprehensive approach is needed to advance personalized cancer care. Progress in clinical cancer proteomics is essential for personalized medicine, wherein treatments will be tailored to individual needs based on patient stratification using non-invasive disease monitoring procedures to reveal the most appropriate therapeutic targets. The recent advancement in proteomics technologies shows great promise of meeting the demand for new biomarker discovery (Chatterjee and Zetter, 2005). Better biomarkers are urgently needed to improve diagnosis, detect cancers at an early and less-aggressive stage, improve treatment outcomes, identify likelihood of recurrence, and monitor response to treatment before standard clinical endpoints become apparent. A significant increase in clinically-relevant molecular biomarkers could have an enormous affect on improved patient outcomes and the financial viability of healthcare systems. However, studies that have applied proteomics technologies to clinical applications have met with some disappointment; it is time for new technologies and approaches! In the post-genomic era, deciphering protein molecular signature is clearly becoming a next major challenge to better understand biological processes involved in health and disease. We believe that the combined "- omics" technologies may hold promise for early detection of disease by proteomic patterns, diagnosis based on proteomic signatures as a complement to histopathology, individualized selection of therapeutic combinations that best target the entire disease-specific protein network, rational modulation of therapy based on changes in the diseased protein network associated with drug resistance and understanding of carcinogenesis. In this section, we will focus on emerging new proteomics strategies in cancer research.

Mass spectrometry-based proteomics

Recent technological advances have enabled mass spectrometry to evolve from simple protein identifications and mapping of single post-translational modifications to making possible quantitative, whole-proteome analysis. The great challenge we face is to establish high-resolution accurate mass spectrometry methods for quantitative bioanalysis. Stable isotope labeling with amino acids in cell culture (SILAC) is a simple, robust, yet powerful approach for in vivo incorporation of a label into proteins in mass spectrometry-based quantitative proteomics (Mann, 2006). SILAC labels proteins with either natural "light" or non-radioactive, stable isotope-containing "heavy" amino acids using the natural metabolic machinery of the cell (typically 13C615N2-lysine and 13C614N4-arginine, which produce a mass difference of 8.0142 Da and 10.00827 Da, respectively, for each tryptic peptide). Cells grown in this medium incorporate the heavy amino acids after five cell doublings and SILAC amino acids have no effect on cell morphology or growth rates. When light and heavy cell populations are mixed, those cells remain distinguishable by mass spectrometry, so protein abundances can be determined from the relative mass spectrometry signal intensities (Ong and Mann, 2006; Geiger et al., 2010). This technique has been successfully used in studying differential protein expression to identify disease biomarkers and drug targets in pancreatic (Grønborg et al., 2006) and breast cancer (Bose et al., 2006; Liang et al., 2006). Although, SILAC is very accurate and an ideal tool for quantifying proteomes, because it requires complete metabolic labeling of the entire proteome, it is thought to be only suitable for analyzing cell culture, not for human tissue or body fluid samples (Geiger et al., 2010). To overcome this limitation, Mann and his colleagues have recently developed a "super-SILAC" mixture, which combines five SILAC-labeled cell lines with human carcinoma tissue, resulting in hundreds of thousands of isotopically labeled peptides "in appropriate" amounts to serve as internal standards for mass spectrometry-based analysis (Geiger et al., 2010). Therefore, a super-SILAC approach may provide a general means for the identification of diagnostic biomarkers and prove to be an effective first step in defining disease biomarkers in a rational and targeted fashion.

Indeed, mass spectrometry has become an indispensable tool for proteomic studies (Roepstorff 1997; Lahm and Langen, 2000; Godovac-Zimmermann and Brown, 2001). Especially, desorption and ionization techniques such as matrix-assisted laser desorption ionization-mass spectrometry (MALDI-MS) (Karas and Hillenkamp, 1998; Covey et al., 2001) and electrospray ionization-mass spectrometry (ESI-MS) (Fenn et al., 1989) have revolutionized the analysis of proteins. These improvements offer levels of mass accuracy and sensitivity, never before achieved for the detection and identification of proteins. MALDI-MS is a powerful method that allows the simultaneous detection and identification of many molecules directly from biological sections (Zaima et al., 2010). A newly developed technique, MALDI-imaging mass spectrometry (MALDI-IMS) allows the visualization of proteins, peptides, lipids, and small molecules directly on thin sections cut from fresh frozen or fixed paraffin embedded (FFPE) tissues (Schwamborn and Caprioli, 2010). The major breakthrough is the possibility to study spatial localization of molecules without long and tedious steps of separation and extraction. First, matrix is uniformly applied to the tissue section, and then proteins are desorbed from discrete spots or pixels upon irradiation of the sample in an ordered array or raster of the surface. Thus, each pixel is keyed to a full mass spectrum consisting of signals from protonated species of molecules desorbed from that tissue region. A plot of the intensity of any one signal produces a map of the relative amount of that compound over the entire imaged surface. Proteomic profiling using MALDI-IMS has been applied to multiple diseased tissues, including human non-small-cell lung tumors (Yanagisawa et al., 2003), gliomas (Stoeckli et al., 2001;Schwartz et al., 2005), prostate (Schwamborn et al., 2007), breast (Xu et al., 2002; Cornett et al., 2006), and ovarian cancer (Lemaire et al., 2007). In addition, MALDI-IMS has been successfully used to identify subsets of markers useful for cancer diagnosis, as well as for improving proteomic classification of tumor samples. For example, an increased expression of thymosin β.4 (Tβ.4) was observed in the proliferating area of the tumor glioblastoma (Stoeckli et al., 2001) and in the stroma region of human breast carcinoma tissue (Seeley and Caprioli, 2008). IMS was also applied to study the therapeutic response of tumors treated with erbB receptor inhibitors OSI-774 and Herceptin (Burnum et al., 2008). Molecular signatures provided by MALDI-IMS represent a unique data set with which to classify and correlate clinically relevant information and outcome in cancer treatment. Interestingly, it has shown that molecular signatures from glioma or non-small-cell lung cancer can be used to distinguish tumor grade and were found to be correlated with patient survival (Yanagisawa et al. 2003; Schwartz et al. 2005). Recent study showed that the proteomic signature was able to accurately define HER2-positive from HER2-negative tissues, suggesting the potential of MALDI-IMS proteomic algorithms for morphology-driven tissue diagnostics (Rauser et al., 2010). Therefore, MADLI-IMS could improve the understanding of cancer onset and progression and the possible application to FFPE tissues, a still unexplored resource for biomarker research.

Chemical proteomics

Chemical proteomics is an effective approach to focused proteomics, having the potential to find specific interactors in moderate-scale comprehensive analysis. A central component of this field is the design of specific protein-modifying reagents that can be used for functional studies of distinct enzyme families within a complex proteome. These chemical probes are designed to covalently modify a target enzyme in such a way that it can be subsequently identified and/or purified (Cravatt and Sorensen, 2000). Such probes have been termed activity-based probes (ABPs) to reflect their need for an active enzyme to facilitate covalent modification. Other chemical probes have been designed that target non-catalytic residues on proteins and enzymes. Regardless of their mechanism of action, chemical probes are finding increasing use in the field of proteomics and have great potential to aid in the process of target identification, target validation, and drug discovery. Activity-based protein profiling (ABPP) is a powerful resource for functional proteomics. ABPP uses active site-directed, small molecule-based covalent probes to directly assess the functional state of large numbers of enzymes in native biological systems. Activity-based probes consist of at least two key elements: a reactive group for binding and covalently labelling the active sites of many members of a given enzyme class and a reporter tag for the detection, enrichment, and identification of probe-labelled enzymes in proteomes (Nomura et al., 2010). Activity-based probes can be adapted for in situ or in vivo labelling by substituting the reporter tag with a handle, such as an alkyne or azide for use with the Huisgen 1,3-dipolar cycloaddition (Click chemistry) (Speers et al., 2003; Speers & Cravatt, 2004). ABPP probes have been successfully developed for many enzyme classes, including histone deacetylases (Salisbury et al., 1997; Salisbury et al ., 2008), proteases (Saghatelian et al., 2004; Sieberet al., 2006), kinases (Yee et al., 2005; Patricelli et al., 2007; Cohen et al., 2007), phosphatases (Kumar et al., 2004), glycosidases (Hekmat et al., 2005), and various oxidoreductases (Table 3) (Adam et al., 2001; Weerapana et al., 2008). Mechanistic studies have confirmed that these probes can distinguish active enzyme from their zymogen or inhibitor-bound forms (Barglow and Cravatt, 2007). Moreover, because ABPP probes label the active sites of their target enzymes, these reagents can be used as competitive profiling tools for inhibitor discovery in native proteomes, providing concomitant readouts of potency and selectivity. Integration of ABPP with other profiling methods, such as metabolomics, can be used to not only identify endogenous substrates and products of enzymes, but also metabolites that are upstream or downstream of these immediate substrates and products, allowing the integration of individual enzymatic reactions into the larger metabolic networks of cancer cells.

Antibody-based proteomics

Cell signaling is a continous biochemical processes and one prominet biochemical role is played by phosphorylation, a posttranslational modification. Therefore, in-depth analysis of deregulated cellular circuitry in cancer requires specialized technoloiges to detect dynamice changes. The recently developed antibody-based proteomics provides a logical strategy for the systematic generation and use of specific antibodies to explore the proteomes, and thus enable pathway comprehensive analysis (Brennan et al., 2010). Innovative high-throughput proteomic approches such as Reverse phase protein array (RPPA) have been developed to examine pathway activation using phosphospecific antibodies in large panels of patient samples (Spurrier et al., 2008). RPPA is a protein array designed as a micro or nano-scaled dot-blot platform dot-blot that allows measurement of protein expression levels in a large number of biological samples simultaneously in a quantitative manner when high-quality antibodies are available. Technically, whole-cell fraction lysates are immobilized on individual spots on a microarray and then incubated with a single specific antibody to detect expression of the target protein across many samples. Detection is performed using either a primary or a secondary labeled antibody by chemiluminescent, fluorescent, or colorimetric assays. The array is then imaged and the obtained data is quantified. Multiplexing is achieved by probing multiple arrays spotted with the same lysate with different antibodies simultaneously and can be implemented as a quantitative calibrated assay (Sheehan et al., 2005). Based on the concept that RPPAs require only miniscule sample volume for multiplex protein detection, tissue lysates from various organs have also been analyzed for biomarker discovery and clinical diagnostics using this method (Paweletz et al., 2001; Wulfkuhle et al., 2003; Rudelius et al., 2006). Another advantage of RPPA is monitoring protein dynamics as a function of time in response to different input types and doses across many samples. Such high-dimensional data acquisition can contribute to the identification of accurate molecular drug targets, as well as the examination of protein network theoretical models (Ramalingam et al., 2007; Nishizuka et al., 2008).

Enzyme-linked immunosorbent assay (ELISA) is a gold standard for measuring protein concentration in human body fluids and have been used for decades in research and development, disease diagnosis and other critical fields in sciences. Although ELISA is reliable and accurate, the classic approaches allow for only single antigen detection and often require relatively large sample volume compared with newer methods. Multiplex assays have been developed from classical ELISA assays to quantify multiple antigens in a single sample (Brennan et al., 2010). They are available in several different formats based on the utilization of flow cytometry, chemiluminescence, or electrochemiluminescence technology (Lenget al., 2008). Flow cytometric multiplex arrays, also known as bead-based multiplex assays, represent probably the most commonly used format at the present time. The cytometric bead array (CBA) system from BD Biosciences and the Luminex multi-analyte profiling (xMAP) technology from Luminex both employ proprietary bead sets which are distinguishable under flow cytometry. Each bead set is coated with a specific capture antibody, and fluorescence or streptavidin-labeled detection antibodies bind to the specific capture antibody complex on the bead set, which can be detected by flow cytometry. Multiplex ELISA from Quansys Biosciences coats multiple specific capture antibodies at multiple spots (one antibody at one spot) in the same well on a 96-well microplate. Chemiluminescence technology, which is more sensitive than chromogenic detection in traditional ELISA, is then employed to detect multiple cytokines at the corresponding spots on the plate. Multiplex kits from Meso Scale Discovery employ electrochemiluminescence technology with multiple specific capture antibodies coated at corresponding spots on an electric wired microplate. The detection antibody is conjugated to a proprietary tag which is excited with emission beams in the electric field. The proprietary co-reactant in the "read buffer" then further amplifies the signal. Multiplex arrays have several advantages, including their high-throughput nature, requirement for less smaple volume, efficiency in terms of time and cost, the ability to evalulate one antigen in the context of multiple others, and the ability to reliably detect different proteins across a broad dynamic range of concentrations. Preclinical studies examing the effect of the PI3K inhibitor LY294002 on human xenografts demonstrated the effectiveness of using multiplexed assays to measure pharmacodynamic responses to accurately monitor the provision of therapy (Gowan et al., 2007).

Cancer biomarker studies using the combination of tissue microarray and automated quantitative assessment of immunofluorescence (TMA-AQUA) have been successfully performed for various types of human carcinoma (Yang et al., 2011). TMAs are a high-throughput platform for the simultaneous investigation of the protein expression in multiple tissue specimens, principally using immunohistochemistry (IHC) (Kononen et al., 1998). Over the past decade, TMAs have become an estabilished and crucial component of the cancer biomarker discovery and validation pipeline (Brennan et al., 2007; Camp et al., 2008; Brennan et al., 2010). With the advent of TMAs and high-throughput pathology, new demands have been placed on the quality, reproducibility, and accuracy of IHC assays. Identifying and scoring cancer markers plays a key role in oncology, helping to characterize the tumor and predict the clinical course of the disease. The current method for scoring IHC slides is labor-intensive and has inherent issues of quantitation (Choudhury et al., 2010). Automated IHC scoring systems offer the opportunity to further advance a well-established and clinically useful assay to accurately quantify both staining intensity and the subcellular localization of protein expression in a reproducible fashion. Additionally, automated anaytical approaches provide quantitative data that can be subjected to more robust statistical analysis than the qualitative or semi-quantitative data that are prodiced form manual analysis. Various automated image analysis solutions are currently available, some of which have received US FDA clearance for cancer-specific biomarker applications. Several groups have demonstrated that automated algorithms can be used to accurately quantify IHC stainin in cell lines (Strömberg et al., 2007) and have also linked automated analysis of IHC to clinical outcome in a selection of different tumor types (Pagès et al., 2005; Brennan et al., 2009; Brennan et al., 2010). The HistoRx AUQA plaform, a well-established automated fluorescence-based immunohistochemistry image analysis, identifies tumor cells using cytokeratin expression, and so creates an interest region, allowing the definition of subcellular compartments and the accurate quantification of protein expression in FFPE tissue samples (Camp et al., 2002). The output of the analysis, called the AQUA score, can be correlated with other parameters such as disease detection, progression, response to therapy, or expression of proteins in alternate pathways. This technology will help to advance personalized medicine by identifying and validating new drug targets. Several studies have demonstrated that AQUA can measure protein expression on histological specimens from various tumor types with good accuracy and reproducibility, and this can then be linked to clinical outcome (McCabe et al., 2005; Dolled-Filhart et al., 2006; Giltnane et al., 2007; Gould Rothberg et al., 2009). The AQUA system allows for high-throughput hig-resolution analysis of TMA, therefore, TMA-AQUA can serve a unique role as both a discovery tool and as a validation tool for nucleic-acid expression profiling-based target discoveries with results equivalent to ELISA quantitation.